diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml
index 51fc4c10d..62e3d9bcc 100644
--- a/.pre-commit-config.yaml
+++ b/.pre-commit-config.yaml
@@ -21,7 +21,7 @@ repos:
         args:
           - "--line-length=100"
   - repo: https://github.com/asottile/reorder_python_imports
-    rev: v2.7.1
+    rev: v3.0.1
     hooks:
       - id: reorder-python-imports
   - repo: https://github.com/pycqa/flake8
diff --git a/btk/draw_blends.py b/btk/draw_blends.py
index 7830bc86d..9af4be5ec 100644
--- a/btk/draw_blends.py
+++ b/btk/draw_blends.py
@@ -9,16 +9,16 @@
 import galsim
 import numpy as np
 from astropy.table import Column
+from galcheat.survey import Survey
+from galcheat.utilities import mag2counts
+from galcheat.utilities import mean_sky_level
 from tqdm.auto import tqdm
 
 from btk import DEFAULT_SEED
 from btk.create_blend_generator import BlendGenerator
 from btk.multiprocess import get_current_process
 from btk.multiprocess import multiprocess
-from btk.survey import get_flux
-from btk.survey import get_mean_sky_level
 from btk.survey import make_wcs
-from btk.survey import Survey
 
 MAX_SEED_INT = 1_000_000_000
 
@@ -69,7 +69,7 @@ def get_catsim_galaxy(entry, filt, survey, no_disk=False, no_bulge=False, no_agn
         Galsim galaxy profile
     """
     components = []
-    total_flux = get_flux(entry[filt.name + "_ab"], filt, survey)
+    total_flux = mag2counts(entry[filt.name + "_ab"], survey, filt).to_value("electron")
     # Calculate the flux of each component in detected electrons.
     total_fluxnorm = entry["fluxnorm_disk"] + entry["fluxnorm_bulge"] + entry["fluxnorm_agn"]
     disk_flux = 0.0 if no_disk else entry["fluxnorm_disk"] / total_fluxnorm * total_flux
@@ -143,7 +143,8 @@ def __init__(
             catalog (btk.catalog.Catalog): BTK catalog object from which galaxies are taken.
             sampling_function (btk.sampling_function.SamplingFunction): BTK sampling
                 function to use.
-            surveys (list): List of btk Survey objects defining the observing conditions
+            surveys (list or galcheat.survey.Survey): List of galcheat Survey objects or
+                single galcheat Survey object.
             batch_size (int): Number of blends generated per batch
             stamp_size (float): Size of the stamps, in arcseconds
             cpus (int): Number of cpus to use; defines the number of minibatches
@@ -182,7 +183,7 @@ def __init__(
             for s in surveys:
                 if not isinstance(s, Survey):
                     raise TypeError(
-                        f"surveys must be a Survey object or an Iterable of Survey objects, but"
+                        f"surveys must be a Survey object or an Iterable of Survey objects, but "
                         f"Iterable contained object of type {type(s)}"
                     )
                 self.check_compatibility(s)
@@ -232,11 +233,12 @@ def __next__(self):
         wcss = {}
 
         for s in self.surveys:
-            pix_stamp_size = int(self.stamp_size / s.pixel_scale)
+            pix_stamp_size = int(self.stamp_size / s.pixel_scale.to_value("arcsec"))
 
             # make PSF and WCS
             psf = []
-            for filt in s.filters:
+            for band in s.available_filters:
+                filt = s.get_filter(band)
                 if callable(filt.psf):
                     generated_psf = filt.psf()  # generate the PSF with the provided function
                     if isinstance(generated_psf, galsim.GSObject):
@@ -253,7 +255,7 @@ def __next__(self):
                         f"The PSF within filter '{filt.name}' is neither a "
                         f"function nor a galsim object"
                     )
-            wcs = make_wcs(s.pixel_scale, (pix_stamp_size, pix_stamp_size))
+            wcs = make_wcs(s.pixel_scale.to_value("arcsec"), (pix_stamp_size, pix_stamp_size))
             psfs[s.name] = psf
             wcss[s.name] = wcs
 
@@ -277,8 +279,9 @@ def __next__(self):
             batch_results = list(chain(*mini_batch_results))
 
             # decide image_shape based on channels_last bool.
-            option1 = (len(s.filters), pix_stamp_size, pix_stamp_size)
-            option2 = (pix_stamp_size, pix_stamp_size, len(s.filters))
+            n_bands = len(s.available_filters)
+            option1 = (n_bands, pix_stamp_size, pix_stamp_size)
+            option2 = (pix_stamp_size, pix_stamp_size, n_bands)
             image_shape = option1 if not self.channels_last else option2
 
             # organize results.
@@ -361,19 +364,19 @@ def render_mini_batch(self, blend_list, psf, wcs, survey, seedseq_minibatch, ext
         for i, blend in tqdm(enumerate(blend_list), total=len(blend_list), desc=desc):
 
             # All bands in same survey have same pixel scale, WCS
-            pixel_scale = survey.pixel_scale
+            pixel_scale = survey.pixel_scale.to_value("arcsec")
             pix_stamp_size = int(self.stamp_size / pixel_scale)
 
             x_peak, y_peak = get_center_in_pixels(blend, wcs)
             blend.add_column(x_peak)
             blend.add_column(y_peak)
 
-            iso_image_multi = np.zeros(
-                (self.max_number, len(survey.filters), pix_stamp_size, pix_stamp_size)
-            )
-            blend_image_multi = np.zeros((len(survey.filters), pix_stamp_size, pix_stamp_size))
-            seedseq_blend = seedseq_minibatch.spawn(len(survey.filters))
-            for b, filt in enumerate(survey.filters):
+            n_bands = len(survey.available_filters)
+            iso_image_multi = np.zeros((self.max_number, n_bands, pix_stamp_size, pix_stamp_size))
+            blend_image_multi = np.zeros((n_bands, pix_stamp_size, pix_stamp_size))
+            seedseq_blend = seedseq_minibatch.spawn(n_bands)
+            for b, name in enumerate(survey.available_filters):
+                filt = survey.get_filter(name)
                 single_band_output = self.render_blend(
                     blend, psf[b], filt, survey, seedseq_blend[b], extra_data[i]
                 )
@@ -406,8 +409,8 @@ def render_blend(self, blend_catalog, psf, filt, survey, seedseq_blend, extra_da
         Args:
             blend_catalog (astropy.table.Table): Catalog with entries corresponding to one blend.
             psf: Galsim object containing the psf for the given filter
-            filt (btk.survey.Filter): BTK Filter object
-            survey (btk.survey.Survey): BTK Survey object
+            filt (galcheat.filter.Filter): Galcheat Filter object
+            survey (galcheat.survey.Survey): Galcheat Survey object
             seedseq_blend (numpy.random.SeedSequence): Seed sequence for the noise generation.
             extra_data: Special field of shape (n_blend,?), containing
                 additional data for drawing the blend. See render_minibatch
@@ -417,11 +420,11 @@ def render_blend(self, blend_catalog, psf, filt, survey, seedseq_blend, extra_da
             Images of blend and isolated galaxies as `numpy.ndarray`.
 
         """
-        mean_sky_level = get_mean_sky_level(survey, filt)
+        sky_level = mean_sky_level(survey, filt).to_value("electron")
         blend_catalog.add_column(
             Column(np.zeros(len(blend_catalog)), name="not_drawn_" + filt.name)
         )
-        pix_stamp_size = int(self.stamp_size / survey.pixel_scale)
+        pix_stamp_size = int(self.stamp_size / survey.pixel_scale.to_value("arcsec"))
         iso_image = np.zeros((self.max_number, pix_stamp_size, pix_stamp_size))
         _blend_image = galsim.Image(np.zeros((pix_stamp_size, pix_stamp_size)))
 
@@ -441,7 +444,7 @@ def render_blend(self, blend_catalog, psf, filt, survey, seedseq_blend, extra_da
             if self.verbose:
                 print("Background noise added to blend image")
             generator = galsim.random.BaseDeviate(seed=seedseq_blend.generate_state(1))
-            background_noise = galsim.PoissonNoise(rng=generator, sky_level=mean_sky_level)
+            background_noise = galsim.PoissonNoise(rng=generator, sky_level=sky_level)
             noise_image = galsim.Image(np.zeros((pix_stamp_size, pix_stamp_size)))
             noise_image.addNoise(background_noise)
             _blend_image += noise_image
@@ -458,8 +461,8 @@ def render_single(self, entry, filt, psf, survey, extra_data):
 
         Args:
             entry (astropy.table.Table): Line from astropy describing the galaxy to draw
-            filt (btk.survey.Filter): BTK Filter object corresponding to the band where
-                                the image is drawn `
+            filt (galcheat.filter.Filter): Galcheat Filter object corresponding to the band where
+                the image is drawn.
             psf: Galsim object containing the PSF relative to the chosen filter
             survey (btk.survey.Survey): BTK Survey object
             extra_data: Special field containing extra data for drawing a single galaxy.
@@ -490,10 +493,10 @@ def check_compatibility(self, survey):
                 f"The catalog provided is of the wrong type. The types of "
                 f"catalogs available for the {type(self).__name__} are {self.compatible_catalogs}"
             )
-        for f in survey.filters:
-            if f.name + "_ab" not in self.catalog.table.keys():
+        for band in survey.available_filters:
+            if band + "_ab" not in self.catalog.table.keys():
                 raise ValueError(
-                    f"The {f.name} filter of the survey {survey.name} "
+                    f"The {band} filter of the survey {survey.name} "
                     f"has no associated magnitude in the given catalog."
                 )
 
@@ -502,13 +505,13 @@ def render_single(self, entry, filt, psf, survey, extra_data):
         if self.verbose:
             print("Draw isolated object")
 
-        pix_stamp_size = int(self.stamp_size / survey.pixel_scale)
+        pix_stamp_size = int(self.stamp_size / survey.pixel_scale.to_value("arcsec"))
         try:
             gal = get_catsim_galaxy(entry, filt, survey)
             gal_conv = galsim.Convolve(gal, psf)
             gal_conv = gal_conv.shift(entry["ra"], entry["dec"])
             return gal_conv.drawImage(
-                nx=pix_stamp_size, ny=pix_stamp_size, scale=survey.pixel_scale
+                nx=pix_stamp_size, ny=pix_stamp_size, scale=survey.pixel_scale.to_value("arcsec")
             )
 
         except SourceNotVisible:
@@ -599,10 +602,10 @@ def check_compatibility(self, survey):
                 f"catalogs available for the {type(self).__name__} are {self.compatible_catalogs}"
             )
         if "ref_mag" not in self.catalog.table.keys():
-            for f in survey.filters:
-                if f"{survey.name}_{f.name}" not in self.catalog.table.keys():
+            for band in survey.available_filters:
+                if f"{survey.name}_{band}" not in self.catalog.table.keys():
                     raise ValueError(
-                        f"The {f.name} filter of the survey {survey.name} "
+                        f"The {band} filter of the survey {survey.name} "
                         f"has no associated magnitude in the given catalog, "
                         f"and the catalog does not contain a 'ref_mag' column"
                     )
@@ -613,19 +616,22 @@ def render_single(self, entry, filt, psf, survey, extra_data):
 
         # get galaxy flux
         try:
-            gal_flux = get_flux(entry[f"{survey.name}_{filt.name}"], filt, survey)
+            mag_name = f"{survey.name}_{filt.name}"
+            gal_flux = mag2counts(entry[mag_name], survey, filt).to_value("electron")
         except KeyError:
-            gal_flux = get_flux(entry["ref_mag"], filt, survey)
+            gal_flux = mag2counts(entry["ref_mag"], survey, filt).to_value("electron")
 
         gal = galsim_catalog.makeGalaxy(
             entry["btk_index"], gal_type=self.gal_type, noise_pad_size=0
         ).withFlux(gal_flux)
 
-        pix_stamp_size = int(self.stamp_size / survey.pixel_scale)
+        pix_stamp_size = int(self.stamp_size / survey.pixel_scale.to_value("arcsec"))
 
         # Convolve the galaxy with the PSF
         gal_conv = galsim.Convolve(gal, psf)
         # Apply the shift
         gal_conv = gal_conv.shift(entry["ra"], entry["dec"])
 
-        return gal_conv.drawImage(nx=pix_stamp_size, ny=pix_stamp_size, scale=survey.pixel_scale)
+        return gal_conv.drawImage(
+            nx=pix_stamp_size, ny=pix_stamp_size, scale=survey.pixel_scale.to_value("arcsec")
+        )
diff --git a/btk/main.py b/btk/main.py
index da841442d..d15303ce6 100644
--- a/btk/main.py
+++ b/btk/main.py
@@ -7,15 +7,17 @@
 from btk.measure import available_measure_functions
 from btk.measure import MeasureGenerator
 from btk.metrics import MetricsGenerator
-from btk.survey import get_survey_from_cfg
+from btk.survey import get_surveys
 
 
 def main(cfg: OmegaConf):
     """Run BTK from end-to-end using a hydra configuration object."""
-    surveys = [get_survey_from_cfg(cfg.surveys[survey_name]) for survey_name in cfg.surveys]
+    catalog = instantiate(cfg.catalog)
+    sampling_function = instantiate(cfg.sampling)
+    surveys = get_surveys(list(cfg.surveys))
 
     # get draw blends generator.
-    draw_blend_generator = instantiate(cfg.draw_blends, surveys=surveys)
+    draw_blend_generator = instantiate(cfg.draw_blends, catalog, sampling_function, surveys)
 
     # get measure_functions.
     measure_functions = []
diff --git a/btk/metrics.py b/btk/metrics.py
index 651936e20..b57a24ac0 100644
--- a/btk/metrics.py
+++ b/btk/metrics.py
@@ -60,10 +60,10 @@
 import matplotlib.pyplot as plt
 import numpy as np
 import skimage.metrics
+from galcheat.utilities import mean_sky_level
 from scipy.optimize import linear_sum_assignment
 
 from btk.measure import MeasureGenerator
-from btk.survey import get_mean_sky_level
 from btk.utils import reverse_dictionary_dictionary
 
 
@@ -747,31 +747,33 @@ def __next__(self):
                         f"number of surveys: {len(surveys)}, instead len is {len(meas_band_num)}"
                     )
                 metrics_results_f = {}
-                for i, surv in enumerate(blend_results["isolated_images"].keys()):
+                for i, surv_name in enumerate(blend_results["isolated_images"].keys()):
                     additional_params = {
-                        "psf": blend_results["psf"][surv],
-                        "pixel_scale": surveys[i].pixel_scale,
+                        "psf": blend_results["psf"][surv_name],
+                        "pixel_scale": surveys[i].pixel_scale.to_value("arcsec"),
                         "meas_band_num": meas_band_num[i],
                         "verbose": self.verbose,
                     }
+                    band_name = surveys[i].available_filters[meas_band_num[i]]
+                    filtr = surveys[i].get_filter(band_name)
                     noise_threshold = self.noise_threshold_factor * np.sqrt(
-                        get_mean_sky_level(surveys[i], surveys[i].filters[meas_band_num[i]])
+                        mean_sky_level(surveys[i], filtr).to_value("electron")
                     )
                     target_meas = {}
                     for k in self.target_meas.keys():
                         target_meas[k] = lambda x: self.target_meas[k](x, additional_params)
 
-                    metrics_results_f[surv] = compute_metrics(
-                        blend_results["isolated_images"][surv],
-                        blend_results["blend_list"][surv],
-                        measure_results["catalog"][meas_func][surv],
-                        measure_results["segmentation"][meas_func][surv],
-                        measure_results["deblended_images"][meas_func][surv],
+                    metrics_results_f[surv_name] = compute_metrics(
+                        blend_results["isolated_images"][surv_name],
+                        blend_results["blend_list"][surv_name],
+                        measure_results["catalog"][meas_func][surv_name],
+                        measure_results["segmentation"][meas_func][surv_name],
+                        measure_results["deblended_images"][meas_func][surv_name],
                         noise_threshold,
                         meas_band_num[i],
                         target_meas,
                         channels_last=self.measure_generator.channels_last,
-                        save_path=os.path.join(self.save_path, meas_func, surv)
+                        save_path=os.path.join(self.save_path, meas_func, surv_name)
                         if self.save_path is not None
                         else None,
                         f_distance=self.f_distance,
@@ -782,12 +784,14 @@ def __next__(self):
             else:
                 additional_params = {
                     "psf": blend_results["psf"],
-                    "pixel_scale": surveys[0].pixel_scale,
+                    "pixel_scale": surveys[0].pixel_scale.to_value("arcsec"),
                     "meas_band_num": meas_band_num,
                     "verbose": self.verbose,
                 }
+                band_name = surveys[0].available_filters[meas_band_num]
+                filtr = surveys[0].get_filter(band_name)
                 noise_threshold = self.noise_threshold_factor * np.sqrt(
-                    get_mean_sky_level(surveys[0], surveys[0].filters[meas_band_num])
+                    mean_sky_level(surveys[0], filtr).to_value("electron")
                 )
                 target_meas = {}
                 for k in self.target_meas.keys():
diff --git a/btk/survey.py b/btk/survey.py
index ac42881f0..9805df45a 100644
--- a/btk/survey.py
+++ b/btk/survey.py
@@ -1,145 +1,84 @@
 """Contains information for surveys available in BTK."""
 import os
 import random as rd
-from collections import namedtuple
-from typing import Iterable
+from typing import Callable
+from typing import List
+from typing import Union
 
 import astropy.wcs as WCS
+import galcheat
 import galsim
 import numpy as np
 from astropy.io import fits
-from hydra import compose
-from hydra import initialize
-from omegaconf import OmegaConf
+from galcheat.survey import Survey
 
 
-Survey = namedtuple(
-    "Survey",
-    [
-        "name",
-        "pixel_scale",  # arcseconds per pixel
-        "effective_area",  # Effective total light collecting area in square meters [m2]
-        "mirror_diameter",  # in meters [m]
-        "airmass",  # Optical path length through atmosphere relative to zenith path length.
-        "filters",
-        "zeropoint_airmass",
-    ],
-)
+def get_surveys(names: Union[Survey, List[Survey]], psf_func: Callable = None):
+    """Return specified surveys from galcheat extended to contain PSF information.
 
-Survey.__doc__ = """
-Class containing the informations relative to a survey.
-
-Args:
-    name (str): Name of the survey
-    pixel_scale (float): Pixel scale of the survey, in arcseconds per pixel
-    effective_area (float): Effective total light collecting area, in square meters
-    mirror_diameter (float): Diameter of the primary mirror, in meters
-    airmass (float): Optical path length through atmosphere relative to zenith path length
-    filters (list): List of Filter objects corresponding to the filters of this survey
-    zeropoint_airmass (float) Airmass at which the zeropoint is measured"""
-
-Filter = namedtuple(
-    "Filter",
-    [
-        "name",
-        "psf",  # galsim psf model or function to generate it
-        "sky_brightness",  # mags/sq.arcsec
-        "exp_time",  # in seconds [s]
-        "zeropoint",  # in mags
-        "extinction",  # Exponential extinction coefficient for atmospheric absorption.
-    ],
-)
-
-Filter.__doc__ = """
-Class containing the informations relative to a filter (for a specific survey).
-
-Args:
-    name (str): Name of the filter
-    psf: Contains the PSF information, either as a Galsim object,
-          or as a function returning a Galsim object
-    sky_brightness (float): Sky brightness, in mags/sq.arcsec
-    exp_time (int): Total exposition time, in seconds
-    zeropoint (float): Magnitude of an object with a measured flux of 1 electron per second
-    extinction (float): Exponential extinction coefficient for atmospheric absorption"""
-
-
-def get_survey_from_cfg(survey_conf: OmegaConf):
-    """Creates the corresponding `btk.survey.Survey` object using the information from config file.
+    This function currently returns a list of galcheat instances if `names` is a list with more
+    than one element. If `names` is a str or a singleton list then we return a single galcheat
+    instance.
 
     Args:
-        cfg (OmegaConf): Hydra configuration object corresponding to a single survey.
+        names (str or list): A single str specifying a survey from conf/surveys or a list with
+            multiple survey names.
+        psf_func (function): Python function which takes in two arguments: `survey` and `filter`
+            that returns a PSF as a galsim object or as a callable with no arguments.
+            If `None`, the default PSF for the specified survey will be used in each band.
 
     Returns:
-        btk.survey.Survey object.
+        galcheat.survey.Survey object or list of such objects.
     """
-    OmegaConf.resolve(survey_conf)  # in-place
-
-    survey_dict = dict(survey_conf)
-    filters_dict = dict(survey_dict.pop("filters"))
-    filter_names = list(filters_dict.keys())
-    for key in filter_names:
-        filter_dict = dict(filters_dict.pop(key))  # need to make it a dict not DictConfig
-        psf_dict = dict(filter_dict.pop("psf"))
-        if "type" not in psf_dict:
-            raise AttributeError(
-                f"Your configuration for the PSF in filter {key} in survey {survey_dict['name']}"
-                f"does not have a 'type' field which is required."
-            )
-        if psf_dict["type"] == "default":
-            psf = get_psf(**psf_dict["params"])
-        elif psf_dict["type"] == "galsim":
-            galsim_dict = dict(psf=psf_dict["params"])
-            psf = galsim.config.BuildGSObject(galsim_dict, "psf")
-        else:
-            raise NotImplementedError(
-                f"The 'type' specified for the PSF in filter {key} in "
-                f"survey {survey_dict['name']} is not implemented."
-            )
+    if isinstance(names, str):
+        names = [names]
+    if not isinstance(names, list):
+        raise TypeError("Argument 'names' of `get_surveys` should be a str or list.")
 
-        filter_dict["psf"] = psf
-        filters_dict[key] = filter_dict
-    filters = [Filter(**filters_dict[key]) for key in filters_dict]
-    survey = Survey(**survey_dict, filters=filters)
-    return survey
+    # add PSF to filters
+    surveys = []
+    for survey_name in names:
+        survey = galcheat.get_survey(survey_name)
+        for band in survey.available_filters:
+            filtr = survey.get_filter(band)
+            if psf_func is None:
+                psf = get_default_psf_with_galcheat_info(survey, filtr)
+            else:
+                psf = psf_func(survey, filtr)
+            filtr.psf = psf
+        surveys.append(survey)
 
+    if len(surveys) == 1:
+        surveys = surveys[0]
+    return surveys
 
-def get_surveys(names="Rubin", overrides: Iterable = ()):
-    """Return specified surveys as `btk.survey.Survey` objects.
 
-    NOTE: The surveys currently implemented correspond to config files inside `conf/surveys`. See
-    the documentation for how to add your own surveys via custom config files.
+def get_default_psf_with_galcheat_info(
+    survey: galcheat.survey.Survey, filtr: galcheat.filter.Filter
+):
+    """Return the default PSF model as a galsim object based on galcheat survey parameters.
 
     Args:
-        names (str or list): A single str specifying a survey from conf/surveys or a list with
-            multiple survey names.
-        overrides (Iterable): List or tuple containg overrides for the survey config files. An
-            example element of overrides could be 'surveys.Rubin.airmass=1.1', i.e. what you would
-            pass into the CLI in order to customize the surveys used (here specified by `names`).
+        survey (galcheat.survey.Survey): Survey object from galcheat.
+        filtr (galcheat.filter.Filter): Filter object from galcheat.
 
     Returns:
         btk.survey.Survey object or list of such objects.
     """
-    if isinstance(names, str):
-        names = [names]
-    if not isinstance(names, list):
-        raise TypeError("Argument 'names' of `get_surveys` should be a str or list.")
-    overrides = [f"surveys={names}", *overrides]
-    surveys = []
-    with initialize(config_path="../conf"):
-        cfg = compose("config", overrides=overrides)
-    for survey_name in cfg.surveys:
-        survey_conf = cfg.surveys[survey_name]
-        surveys.append(get_survey_from_cfg(survey_conf))
-    if len(surveys) == 1:
-        return surveys[0]
-    return surveys
+    return get_default_psf(
+        survey.mirror_diameter.to_value("m"),
+        survey.effective_area.to_value("m2"),
+        filtr.psf_fwhm.to_value("arcsec"),
+        filt_wavelength=filtr.effective_wavelength.to_value("angstrom"),
+        atmospheric_model="Kolmogorov",
+    )
 
 
-def get_psf(
+def get_default_psf(
     mirror_diameter,
     effective_area,
-    filt_wavelength,
     fwhm,
+    filt_wavelength,
     atmospheric_model="Kolmogorov",
 ):
     """Defines a synthetic galsim PSF model.
@@ -149,9 +88,10 @@ def get_psf(
     Args:
         mirror_diameter (float): in meters [m]
         effective_area (float): effective total light collecting area in square meters [m2]
-        filt_wavelength (string): filter wavelength
-        fwhm (float): fwhm of the atmospheric component
-        atmospheric_model (string): type of atmospheric model
+        filt_wavelength (string): filter wavelength in Angstroms. [Angstrom]
+        fwhm (float): fwhm of the atmospheric component in arcseconds. [arcsec]
+        atmospheric_model (string): type of atmospheric model. Current options:
+            ['Kolmogorov', 'Moffat'].
 
     Returns:
         psf_model: galsim psf model
@@ -216,43 +156,12 @@ def get_psf_from_file(psf_dir, survey):
         raise RuntimeError(f"No psf files found in '{psf_dir}'.")
     psf_array = fits.getdata(psf_dir + "/" + psf_file)
     psf_model = galsim.InterpolatedImage(
-        galsim.Image(psf_array), scale=survey.pixel_scale
+        galsim.Image(psf_array), scale=survey.pixel_scale.to_value("arcsec")
     ).withFlux(1.0)
 
     return psf_model
 
 
-def get_flux(ab_magnitude, filt, survey):
-    """Convert source magnitude to flux.
-
-    The calculation includes the effects of atmospheric extinction.
-    Credit: WeakLensingDeblending (https://github.com/LSSTDESC/WeakLensingDeblending)
-
-    Args:
-        ab_magnitude(float): AB magnitude of source.
-        filt (btk.survey.Filter): BTK Filter object
-        survey (btk.survey.Survey): BTK Survey object
-
-    Returns:
-        Flux in detected electrons.
-    """
-    mag = ab_magnitude + filt.extinction * (survey.airmass - survey.zeropoint_airmass)
-    return filt.exp_time * 10 ** (-0.4 * (mag - filt.zeropoint))
-
-
-def get_mean_sky_level(survey, filt):
-    """Computes the mean sky level given to Galsim for noise generation.
-
-    Args:
-        survey (btk.survey.Survey): BTK Survey object
-        filt (btk.survey.Filter): BTK Filter object
-
-    Returns:
-        Corresponding mean sky level
-    """
-    return get_flux(filt.sky_brightness, filt, survey) * survey.pixel_scale**2
-
-
 def make_wcs(pixel_scale, shape, center_pix=None, center_sky=None, projection="TAN"):
     """Creates WCS for an image.
 
diff --git a/conf/config.yaml b/conf/config.yaml
index dd6726afd..e52509652 100644
--- a/conf/config.yaml
+++ b/conf/config.yaml
@@ -3,8 +3,6 @@ defaults:
   - catalog: catsim
   - sampling: default
   - draw_blends: catsim
-  - surveys:
-      - Rubin
   - override hydra/help: btk_help
 
 ### all arguments ###
@@ -36,6 +34,9 @@ noise_threshold_factor: 3
 distance_threshold_match: 5.0
 
 ### organize arguments ###
+surveys:
+  - "LSST"
+
 measure:
   measure_functions: ${measure_functions}
   kwargs:
@@ -54,18 +55,3 @@ metrics:
 paths:
   root: ${oc.env:BTK_HOME}
   data: ${paths.root}/data
-
-### Global values ###
-
-# Central wavelengths in Angstroms for each filter band, calculated
-# from the baseline total filter throughputs tabulated at
-# http://dev.lsstcorp.org/cgit/LSST/sims/throughputs.git/snapshot/throughputs-1.2.tar.gz
-central_wavelength:
-  u: 3592.13
-  g: 4789.98
-  r: 6199.52
-  i: 7528.51
-  z: 8689.83
-  y: 9674.05
-  VIS: 7135.0
-  f814w: 5000.0 # TODO: placeholder
diff --git a/conf/draw_blends/catsim.yaml b/conf/draw_blends/catsim.yaml
index 94294e3bc..6b8667ddb 100644
--- a/conf/draw_blends/catsim.yaml
+++ b/conf/draw_blends/catsim.yaml
@@ -1,7 +1,8 @@
 _target_: btk.draw_blends.CatsimGenerator
-catalog: ${catalog}
-sampling_function: ${sampling}
-surveys: Null
+_args_:
+  - ${catalog}
+  - ${sampling}
+  - ${surveys}
 batch_size: ${batch_size}
 stamp_size: ${stamp_size}
 cpus: ${cpus}
diff --git a/conf/draw_blends/cosmos.yaml b/conf/draw_blends/cosmos.yaml
index a063eb8cc..15736d825 100644
--- a/conf/draw_blends/cosmos.yaml
+++ b/conf/draw_blends/cosmos.yaml
@@ -1,7 +1,8 @@
 _target_: btk.draw_blends.CosmosGenerator
-catalog: ${catalog}
-sampling_function: ${sampling}
-surveys: Null
+_args_:
+  - ${catalog}
+  - ${sampling}
+  - ${surveys}
 batch_size: ${batch_size}
 stamp_size: ${stamp_size}
 cpus: ${cpus}
diff --git a/conf/hydra/help/btk_help.yaml b/conf/hydra/help/btk_help.yaml
index 3abe0c360..6742046c7 100644
--- a/conf/hydra/help/btk_help.yaml
+++ b/conf/hydra/help/btk_help.yaml
@@ -27,7 +27,7 @@ template: |-
   Assuming that BTK has been pip installed, you can run btk from the command line like e.g.
 
   btk sampling=default draw_blends=catsim max_number=3 save_path=/directory/to/save/results cpus=1
-    verbose=False surveys=[Rubin,HST] surveys.Rubin.airmass=1.1
+    verbose=False surveys=[LSST,COSMOS] surveys.LSST.zeropoint_airmass=1.1
     sampling=default catalog.name=catsim use_metrics=['detection', 'segmentation'] (...)
 
   You need to create the directory to save results yourself (preferably an empty directory) and specify its absolute path when you run the CLI via the `save_path` parameter.
@@ -45,17 +45,17 @@ template: |-
           a list. (see documentation for more details).
 
     * surveys: Name of the survey(s) you want to use, options are
-      {Rubin, HST, HSC, DES, CFHT, Euclid} and correspond to each of the config files available
+      {LSST, COSMOS, HSC, DES, CFHT, Euclid} and correspond to each of the config files available
       in conf/surveys. You can pass in a list of surveys for multi-resolution
       studies too. For example:
 
-      btk surveys=[Rubin,HST] (...)
+      btk surveys=[LSST,COSMOS] (...)
 
-      Assuming that you want to use e.g. the Rubin survey default parameters but with a couple
+      Assuming that you want to use e.g. the LSST survey default parameters but with a couple
       of changes, you can modify individual parameters of a given survey directly from the
       command line:
 
-      btk surveys=Rubin surveys.Rubin.airmass=1.1 (...)
+      btk surveys=LSST surveys.LSST.zeropoint_airmass=1.1 (...)
 
       If you want to modify a large number of parameters of a given survey, it might be easier to
       add your own config file to conf/surveys. See the CLI section of the tutorial for
diff --git a/conf/surveys/CFHT.yaml b/conf/surveys/CFHT.yaml
deleted file mode 100644
index 58c6eb011..000000000
--- a/conf/surveys/CFHT.yaml
+++ /dev/null
@@ -1,37 +0,0 @@
-# pixel_scale, sky_brightness: http://www.cfht.hawaii.edu/Instruments/Imaging/Megacam/generalinformation.html
-# exp_time, fwhm: https://www.cfht.hawaii.edu/Science/CFHTLS/T0007/CFHTLS_T0007-TechnicalDocumentation.pdf
-# zeropoint: http://www1.cadc-ccda.hia-iha.nrc-cnrc.gc.ca/community/CFHTLS-SG/docs/extra/filters.html
-CFHT:
-  name: "CFHT"
-  pixel_scale: 0.187
-  effective_area: 8.022
-  mirror_diameter: 3.592
-  airmass: 1.2
-  zeropoint_airmass: 1.0
-  filters:
-    r:
-      name: "r"
-      sky_brightness: 20.8
-      exp_time: 2000
-      zeropoint: 26.74
-      extinction: 0.10
-      psf:
-        type: default
-        params:
-          fwhm: 0.71
-          mirror_diameter: ${surveys.CFHT.mirror_diameter}
-          effective_area: ${surveys.CFHT.effective_area}
-          filt_wavelength: ${central_wavelength.r}
-    i:
-      name: "i"
-      sky_brightness: 20.3
-      exp_time: 4300
-      zeropoint: 26.22
-      extinction: 0.07
-      psf:
-        type: default
-        params:
-          fwhm: 0.64
-          mirror_diameter: ${surveys.CFHT.mirror_diameter}
-          effective_area: ${surveys.CFHT.effective_area}
-          filt_wavelength: ${central_wavelength.i}
diff --git a/conf/surveys/DES.yaml b/conf/surveys/DES.yaml
deleted file mode 100644
index 551a97101..000000000
--- a/conf/surveys/DES.yaml
+++ /dev/null
@@ -1,65 +0,0 @@
-# http://www.ctio.noao.edu/noao/content/Basic-Optical-Parameters
-# http://www.ctio.noao.edu/noao/content/DECam-What
-# sky brightness: http://www.ctio.noao.edu/noao/node/1218
-# fwhm: https://arxiv.org/abs/1407.3801 table 2
-# extinction: https://arxiv.org/abs/1701.00502 table 4
-DES:
-  name: DES
-  pixel_scale: 0.263
-  effective_area: 10.014
-  mirror_diameter: 3.934
-  airmass: 1.0
-  zeropoint_airmass: 1.3
-  filters:
-    g:
-      name: "g"
-      sky_brightness: 22.3
-      exp_time: 800
-      zeropoint: 26.72
-      extinction: 0.17
-      psf:
-        type: default
-        params:
-          fwhm: 1.24
-          mirror_diameter: ${surveys.DES.mirror_diameter}
-          effective_area: ${surveys.DES.effective_area}
-          filt_wavelength: ${central_wavelength.g}
-    r:
-      name: "r"
-      sky_brightness: 21.4
-      exp_time: 800
-      zeropoint: 26.99
-      extinction: 0.09
-      psf:
-        type: default
-        params:
-          fwhm: 1.03
-          mirror_diameter: ${surveys.DES.mirror_diameter}
-          effective_area: ${surveys.DES.effective_area}
-          filt_wavelength: ${central_wavelength.r}
-    i:
-      name: "i"
-      sky_brightness: 20.5
-      exp_time: 1000
-      zeropoint: 26.86
-      extinction: 0.05
-      psf:
-        type: default
-        params:
-          fwhm: 0.96
-          mirror_diameter: ${surveys.DES.mirror_diameter}
-          effective_area: ${surveys.DES.effective_area}
-          filt_wavelength: ${central_wavelength.i}
-    z:
-      name: "z"
-      sky_brightness: 18.7
-      exp_time: 800
-      zeropoint: 26.58
-      extinction: 0.06
-      psf:
-        type: default
-        params:
-          fwhm: 1.12
-          mirror_diameter: ${surveys.DES.mirror_diameter}
-          effective_area: ${surveys.DES.effective_area}
-          filt_wavelength: ${central_wavelength.z}
diff --git a/conf/surveys/Euclid.yaml b/conf/surveys/Euclid.yaml
deleted file mode 100644
index 4f3e1db64..000000000
--- a/conf/surveys/Euclid.yaml
+++ /dev/null
@@ -1,25 +0,0 @@
-# Euclid definition study report: https://arxiv.org/abs/1110.3193
-# effective_area takes into account 13% obscuration: https://arxiv.org/abs/1608.08603
-# exp_time: https://arxiv.org/abs/1608.08603
-# sky brightness: http://www.mssl.ucl.ac.uk/~smn2/instrument.html
-Euclid:
-  name: "Euclid"
-  pixel_scale: 0.10
-  effective_area: 0.98
-  mirror_diameter: 1.2
-  airmass: 1.0
-  zeropoint_airmass: 1.0
-  filters:
-    VIS:
-      name: VIS
-      sky_brightness: 22.3203
-      exp_time: 565
-      zeropoint: 25.91
-      extinction: 0.0
-      psf:
-        type: default
-        params:
-          fwhm: 0.16
-          mirror_diameter: ${surveys.Euclid.mirror_diameter} # relative interpolation.
-          effective_area: ${surveys.Euclid.effective_area}
-          filt_wavelength: ${central_wavelength.VIS}
diff --git a/conf/surveys/HSC.yaml b/conf/surveys/HSC.yaml
deleted file mode 100644
index c3f3a8048..000000000
--- a/conf/surveys/HSC.yaml
+++ /dev/null
@@ -1,75 +0,0 @@
-# exp_time and seeing: https://hsc-release.mtk.nao.ac.jp/doc/
-# sky_brightness: https://www.naoj.org/Observing/Instruments/SCam/exptime.html
-HSC:
-  name: HSC
-  pixel_scale: 0.167
-  effective_area: 52.81
-  mirror_diameter: 8.2
-  airmass: 1.0
-  zeropoint_airmass: 1.2
-  filters:
-    g:
-      name: "g"
-      sky_brightness: 21.4
-      exp_time: 600
-      zeropoint: 28.90
-      extinction: 0.13
-      psf:
-        type: default
-        params:
-          fwhm: 0.77
-          mirror_diameter: ${surveys.HSC.mirror_diameter}
-          effective_area: ${surveys.HSC.effective_area}
-          filt_wavelength: ${central_wavelength.g}
-    r:
-      name: "r"
-      sky_brightness: 20.6
-      exp_time: 600
-      zeropoint: 28.86
-      extinction: 0.11
-      psf:
-        type: default
-        params:
-          fwhm: 0.76
-          mirror_diameter: ${surveys.HSC.mirror_diameter}
-          effective_area: ${surveys.HSC.effective_area}
-          filt_wavelength: ${central_wavelength.r}
-    i:
-      name: "i"
-      sky_brightness: 19.7
-      exp_time: 1200
-      zeropoint: 28.61
-      extinction: 0.07
-      psf:
-        type: default
-        params:
-          fwhm: 0.58
-          mirror_diameter: ${surveys.HSC.mirror_diameter}
-          effective_area: ${surveys.HSC.effective_area}
-          filt_wavelength: ${central_wavelength.i}
-    z:
-      name: "z"
-      sky_brightness: 18.3
-      exp_time: 1200
-      zeropoint: 27.68
-      extinction: 0.05
-      psf:
-        type: default
-        params:
-          fwhm: 0.68
-          mirror_diameter: ${surveys.HSC.mirror_diameter}
-          effective_area: ${surveys.HSC.effective_area}
-          filt_wavelength: ${central_wavelength.z}
-    y:
-      name: "y"
-      sky_brightness: 17.9
-      exp_time: 1200
-      zeropoint: 27.33
-      extinction: 0.05
-      psf:
-        type: default
-        params:
-          fwhm: 0.68
-          mirror_diameter: ${surveys.HSC.mirror_diameter}
-          effective_area: ${surveys.HSC.effective_area}
-          filt_wavelength: ${central_wavelength.y}
diff --git a/conf/surveys/HST.yaml b/conf/surveys/HST.yaml
deleted file mode 100644
index 56c678301..000000000
--- a/conf/surveys/HST.yaml
+++ /dev/null
@@ -1,26 +0,0 @@
-# pixel_scale: https://hst-docs.stsci.edu/acsihb/chapter-3-acs-capabilities-design-and-operations/3-5-acs-quick-reference-guide
-# exp_time: https://hst-docs.stsci.edu/acsdhb/chapter-1-acs-overview/1-2-basic-instrument-operations
-# fwhm: https://hst-docs.stsci.edu/display/WFC3IHB/6.6+UVIS+Optical+Performance#id-6
-# zeropoint : https://galsim-developers.github.io/GalSim/_build/html/real_gal.html
-# .6UVISOpticalPerformance-6.6.1 800nm
-HST:
-  name: "HST_COSMOS"
-  pixel_scale: 0.03
-  effective_area: 1.0 # TODO: placeholder
-  mirror_diameter: 2.4
-  airmass: 0.0
-  zeropoint_airmass: 0.0
-  filters:
-    f814w:
-      name: "f814w"
-      sky_brightness: 22
-      exp_time: 2028
-      zeropoint: 25.94
-      extinction: 0
-      psf:
-        type: default
-        params:
-          fwhm: 0.074
-          mirror_diameter: ${surveys.HST.mirror_diameter}
-          effective_area: ${surveys.HST.effective_area}
-          filt_wavelength: ${central_wavelength.f814w}
diff --git a/conf/surveys/Rubin.yaml b/conf/surveys/Rubin.yaml
deleted file mode 100644
index bbda18581..000000000
--- a/conf/surveys/Rubin.yaml
+++ /dev/null
@@ -1,87 +0,0 @@
-# https://www.lsst.org/about/camera/features
-Rubin:
-  name: "Rubin"
-  pixel_scale: 0.2
-  effective_area: 32.4
-  mirror_diameter: 8.36
-  airmass: 1.2
-  zeropoint_airmass: 1.2
-  filters:
-    u:
-      name: "u"
-      sky_brightness: 22.9
-      exp_time: 1680
-      zeropoint: 26.40
-      extinction: 0.451
-      psf:
-        type: default
-        params:
-          fwhm: 0.859
-          mirror_diameter: ${surveys.Rubin.mirror_diameter}
-          effective_area: ${surveys.Rubin.effective_area}
-          filt_wavelength: ${central_wavelength.u}
-    g:
-      name: "g"
-      sky_brightness: 22.3
-      exp_time: 2400
-      zeropoint: 28.26
-      extinction: 0.163
-      psf:
-        type: default
-        params:
-          fwhm: 0.814
-          mirror_diameter: ${surveys.Rubin.mirror_diameter}
-          effective_area: ${surveys.Rubin.effective_area}
-          filt_wavelength: ${central_wavelength.g}
-    r:
-      name: "r"
-      sky_brightness: 21.2
-      exp_time: 5520
-      zeropoint: 28.10
-      extinction: 0.10
-      psf:
-        type: default
-        params:
-          fwhm: 0.781
-          mirror_diameter: ${surveys.Rubin.mirror_diameter}
-          effective_area: ${surveys.Rubin.effective_area}
-          filt_wavelength: ${central_wavelength.r}
-    i:
-      name: "i"
-      sky_brightness: 20.5
-      exp_time: 5520
-      zeropoint: 27.78
-      extinction: 0.07
-      psf:
-        type: default
-        params:
-          fwhm: 0.748
-          mirror_diameter: ${surveys.Rubin.mirror_diameter}
-          effective_area: ${surveys.Rubin.effective_area}
-          filt_wavelength: ${central_wavelength.i}
-    z:
-      name: "z"
-      sky_brightness: 19.6
-      exp_time: 4800
-      zeropoint: 27.39
-      extinction: 0.043
-      psf:
-        type: default
-        params:
-          fwhm: 0.725
-          mirror_diameter: ${surveys.Rubin.mirror_diameter}
-          effective_area: ${surveys.Rubin.effective_area}
-          filt_wavelength: ${central_wavelength.z}
-    y:
-      name: "y"
-      sky_brightness: 18.6
-      exp_time: 4800
-      zeropoint: 26.56
-      extinction: 0.138
-      psf:
-        type: default
-        params:
-          fwhm: 0.703
-          mirror_diameter: ${surveys.Rubin.mirror_diameter}
-          effective_area: ${surveys.Rubin.effective_area}
-          filt_wavelength: ${central_wavelength.y}
diff --git a/docs/source/cli.rst b/docs/source/cli.rst
index b6144e3f2..928786c54 100644
--- a/docs/source/cli.rst
+++ b/docs/source/cli.rst
@@ -11,7 +11,7 @@ Assuming that BTK has been pip installed, you can run btk from the command line
 
 .. code-block::
 
-    btk sampling=default draw_blends=catsim max_number=3 save_path=/directory/to/save/results cpus=1 verbose=False surveys=[Rubin, HST] surveys.Rubin.airmass=1.1
+    btk sampling=default draw_blends=catsim max_number=3 save_path=/directory/to/save/results cpus=1 verbose=False surveys=[LSST, COSMOS] surveys.LSST.zeropoint_airmass=1.1
     sampling=default catalog.name=catsim use_metrics=['detection', 'segmentation'] (...)
 
 You need to create the directory to save results yourself (preferably an empty directory) and specify its absolute path when you run the CLI via the ``save_path`` argument.
@@ -44,9 +44,9 @@ Here is a list of all the options of BTK you can customize directly from the CLI
 
 * ``surveys``: Name of the survey(s) you want to use, options are:
 
-      - Rubin
+      - LSST
 
-      - HST
+      - COSMOS
 
       - HSC
 
@@ -61,14 +61,14 @@ Here is a list of all the options of BTK you can customize directly from the CLI
 
       .. code-block::
 
-          btk surveys=[Rubin,HST] (...)
+          btk surveys=[LSST,COSMOS] (...)
 
-      Assuming that you want to use e.g. the Rubin survey default parameters but some changes you can modify individual parameters of this survey directly from the
+      Assuming that you want to use e.g. the LSST survey default parameters but some changes you can modify individual parameters of this survey directly from the
       command line:
 
       .. code-block::
 
-          btk surveys=Rubin surveys.Rubin.airmass=1.1 (...)
+          btk surveys=LSST surveys.LSST.zeropoint_airmass=1.1 (...)
 
       If you want to modify a large number of parameters of a given survey, it might be easier to
       add your own config file to ``conf/surveys``. See below for instructions on how to do this.
@@ -124,8 +124,6 @@ needs to be the *unique* name of your survey and the corresponding fields
 
     - mirror_diameter
 
-    - airmass
-
     - zeropoint_airmass
 
     - filters
@@ -140,8 +138,6 @@ are required. You should have at least one filter with the fields:
 
     - zeropoint
 
-    - extinction
-
     - psf
 
 The ``psf`` field can be specified with ``type: default`` in which case you need to specify the parameters:
diff --git a/docs/source/tutorials.rst b/docs/source/tutorials.rst
index 4c02d0b0b..e6290544f 100644
--- a/docs/source/tutorials.rst
+++ b/docs/source/tutorials.rst
@@ -148,13 +148,13 @@ You may write more complex sampling functions to have more control over how the
 Survey
 .......
 
-The BTK Survey object defines the observing conditions relative to a survey. It is based on the named tuple class, and contains various parameters (eg. pixel scale, effective_area), including a list of Filter objects. The Filter class is also a named tuple, and contains information concerning a specific filter in the survey (eg. exporesure time, psf). Numerous surveys are already implemented in BTK; we will import the Rubin one for this tutorial.
+The BTK Survey object defines the observing conditions relative to a survey. It is based on the named tuple class, and contains various parameters (eg. pixel scale, effective_area), including a list of Filter objects. The Filter class is also a named tuple, and contains information concerning a specific filter in the survey (eg. exporesure time, psf). Numerous surveys are already implemented in BTK; we will import the LSST one for this tutorial.
 
 .. jupyter-execute::
 
-  Rubin = btk.survey.get_surveys("Rubin")
+  LSST = btk.survey.get_surveys("LSST")
 
-You may want to define your own survey if you wish to modify some parameters or use a survey which is not implemented in BTK. We advise you to take the code of an existing survey and modify it to your convenience. Here is the one for Rubin:
+You may want to define your own survey if you wish to modify some parameters or use a survey which is not implemented in BTK. We advise you to take the code of an existing survey and modify it to your convenience. Here is the one for LSST:
 
 .. jupyter-execute::
 
@@ -169,8 +169,8 @@ You may want to define your own survey if you wish to modify some parameters or
       "y": 9674.05,
   }
 
-  Rubin = btk.survey.Survey(
-      "Rubin",
+  LSST = btk.survey.Survey(
+      "LSST",
       pixel_scale=0.2,
       effective_area=32.4,
       mirror_diameter=8.36,
@@ -270,7 +270,7 @@ The `psf` attribute deserves an additionnal explanation: it corresponds to the P
 
 You may want to use a function taking an argument to avoid rewriting the function for each filter; we advise using lambda functions to achieve this, eg ``get_u_psf = lambda: get_custom_psf(u_band_argument)``.
 
-Finally, you can use the default function ``get_psf`` as demonstrated in the Rubin Survey, to get a complex (not random) PSF, or use the function ``get_psf_from_file(psf_dir, pixel_scale)`` to import a PSF from a FITS file (randomly if there are more than one file in the directory provided). For more information on these functions take a look at the API.
+Finally, you can use the default function ``get_psf`` as demonstrated in the LSST Survey, to get a complex (not random) PSF, or use the function ``get_psf_from_file(psf_dir, pixel_scale)`` to import a PSF from a FITS file (randomly if there are more than one file in the directory provided). For more information on these functions take a look at the API.
 
 Drawing the blends
 ...................
@@ -282,7 +282,7 @@ Now that we have all the objects at our disposal, we can create the DrawBlendsGe
   draw_generator = btk.draw_blends.CatsimGenerator(
       catalog,
       sampling_function,
-      [Rubin],
+      [LSST],
       batch_size=8,
       stamp_size=stamp_size,
       cpus=1,
@@ -448,7 +448,7 @@ Saving the results can be automatically achieved by providing the save_path argu
   draw_generator = btk.draw_blends.CatsimGenerator(
       catalog,
       sampling_function,
-      Rubin,
+      LSST,
       batch_size=100,
       stamp_size=stamp_size,
       cpus=1,
@@ -467,7 +467,7 @@ To load the results, you can use the `load_all_results` function ; you need to p
 
 ::
 
-  blend_results,meas_results,results = btk.utils.load_all_results(save_path,["Rubin"],["sep_measure"],n_batch=100)
+  blend_results,meas_results,results = btk.utils.load_all_results(save_path,["LSST"],["sep_measure"],n_batch=100)
 
 
 
@@ -489,14 +489,14 @@ Let's start with the catalog and sampling function. We use a small sample of the
   catalog = btk.catalog.CosmosCatalog.from_file(COSMOS_CATALOG_PATHS)
   sampling_function = btk.sampling_functions.DefaultSampling(stamp_size=stamp_size)
 
-We can now create the corresponding instance of ``DrawBlendsGenerator``. There is an important caveat here: as in the other tutorial, we use the Rubin survey. However, the COSMOS data set only contains images and magnitudes from the f814w band; thus, when simulating images, the same magnitude is used to compute the galaxy fluxes across all bands. The section that follows explains how to get around this issue.
+We can now create the corresponding instance of ``DrawBlendsGenerator``. There is an important caveat here: as in the other tutorial, we use the LSST survey. However, the COSMOS data set only contains images and magnitudes from the f814w band; thus, when simulating images, the same magnitude is used to compute the galaxy fluxes across all bands. The section that follows explains how to get around this issue.
 
 .. jupyter-execute::
 
   draw_generator = btk.draw_blends.CosmosGenerator(
           catalog,
           sampling_function,
-          btk.survey.get_surveys("Rubin"),
+          btk.survey.get_surveys("LSST"),
           batch_size=batch_size,
           stamp_size=stamp_size,
           cpus=1,
diff --git a/notebooks/00-intro.ipynb b/notebooks/00-intro.ipynb
index 068129ccc..b8740ed22 100644
--- a/notebooks/00-intro.ipynb
+++ b/notebooks/00-intro.ipynb
@@ -228,7 +228,7 @@
    "source": [
     "## Survey\n",
     "\n",
-    "The BTK Survey object defines the observing conditions relative to a survey. It is based on the named tuple class, and contains various parameters (eg. pixel scale, effective_area), including a list of Filter objects. The Filter class is also a named tuple, and contains information concerning a specific filter in the survey (eg. exporesure time, psf). Numerous surveys are already implemented in BTK; we will import the Rubin one for this tutorial."
+    "The BTK Survey object defines the observing conditions relative to a survey. It is based on the named tuple class, and contains various parameters (eg. pixel scale, effective_area), including a list of Filter objects. The Filter class is also a named tuple, and contains information concerning a specific filter in the survey (eg. exporesure time, psf). Numerous surveys are already implemented in BTK; we will import the LSST one for this tutorial."
    ]
   },
   {
@@ -237,14 +237,14 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "Rubin = btk.survey.get_surveys(\"Rubin\")"
+    "LSST = btk.survey.get_surveys(\"LSST\")"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "You may want to define your own survey if you wish to modify some parameters or use a survey which is not implemented in BTK. We advise you to take the code of an existing survey and modify it to your convenience. Here is the one for Rubin:"
+    "You may want to define your own survey if you wish to modify some parameters or use a survey which is not implemented in BTK. We advise you to take the code of an existing survey and modify it to your convenience. Here is the one for LSST:"
    ]
   },
   {
@@ -262,8 +262,8 @@
     "    \"z\": 8689.83,\n",
     "    \"y\": 9674.05,\n",
     "}\n",
-    "Rubin = btk.survey.Survey(\n",
-    "    \"Rubin\",\n",
+    "LSST = btk.survey.Survey(\n",
+    "    \"LSST\",\n",
     "    pixel_scale=0.2,\n",
     "    effective_area=32.4,\n",
     "    mirror_diameter=8.36,\n",
@@ -383,7 +383,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "Finally, you can use the default function `get_psf` as demonstrated in the Rubin Survey, to get a complex (not random) PSF, or use the function `get_psf_from_file(psf_dir, pixel_scale)` to import a PSF from a FITS file (randomly if there are more than one file in the directory provided)."
+    "Finally, you can use the default function `get_psf` as demonstrated in the LSST Survey, to get a complex (not random) PSF, or use the function `get_psf_from_file(psf_dir, pixel_scale)` to import a PSF from a FITS file (randomly if there are more than one file in the directory provided)."
    ]
   },
   {
@@ -411,7 +411,7 @@
     "draw_generator = btk.draw_blends.CatsimGenerator(\n",
     "    catalog,\n",
     "    sampling_function,\n",
-    "    Rubin,\n",
+    "    LSST,\n",
     "    batch_size=100,\n",
     "    stamp_size=stamp_size,\n",
     "    cpus=1,\n",
@@ -447,7 +447,7 @@
        "version_minor": 0
       },
       "text/plain": [
-       "Generating blends for Rubin survey:   0%|          | 0/100 [00:00<?, ?it/s]"
+       "Generating blends for LSST survey:   0%|          | 0/100 [00:00<?, ?it/s]"
       ]
      },
      "metadata": {},
@@ -669,7 +669,7 @@
        "version_minor": 0
       },
       "text/plain": [
-       "Generating blends for Rubin survey:   0%|          | 0/100 [00:00<?, ?it/s]"
+       "Generating blends for LSST survey:   0%|          | 0/100 [00:00<?, ?it/s]"
       ]
      },
      "metadata": {},
@@ -714,7 +714,7 @@
        "version_minor": 0
       },
       "text/plain": [
-       "Generating blends for Rubin survey:   0%|          | 0/100 [00:00<?, ?it/s]"
+       "Generating blends for LSST survey:   0%|          | 0/100 [00:00<?, ?it/s]"
       ]
      },
      "metadata": {},
@@ -881,7 +881,7 @@
     "draw_generator = btk.draw_blends.CatsimGenerator(\n",
     "    catalog,\n",
     "    sampling_function,\n",
-    "    Rubin,\n",
+    "    LSST,\n",
     "    batch_size=100,\n",
     "    stamp_size=stamp_size,\n",
     "    cpus=1,\n",
@@ -912,7 +912,7 @@
        "version_minor": 0
       },
       "text/plain": [
-       "Generating blends for Rubin survey:   0%|          | 0/100 [00:00<?, ?it/s]"
+       "Generating blends for LSST survey:   0%|          | 0/100 [00:00<?, ?it/s]"
       ]
      },
      "metadata": {},
@@ -948,7 +948,7 @@
    },
    "outputs": [],
    "source": [
-    "blend_results,meas_results,results = btk.utils.load_all_results(save_path,[\"Rubin\"],[\"sep_measure\"],n_batch=100)"
+    "blend_results,meas_results,results = btk.utils.load_all_results(save_path,[\"LSST\"],[\"sep_measure\"],n_batch=100)"
    ]
   }
  ],
diff --git a/notebooks/01a-cosmos_tutorial.ipynb b/notebooks/01a-cosmos_tutorial.ipynb
index 22ca7573e..2d1c88f80 100644
--- a/notebooks/01a-cosmos_tutorial.ipynb
+++ b/notebooks/01a-cosmos_tutorial.ipynb
@@ -60,7 +60,7 @@
     "batch_size = 8\n",
     "catalog = btk.catalog.CosmosCatalog.from_file(COSMOS_CATALOG_PATHS, exclusion_level=\"none\") # To use default galsim exlusion level(\"marginal\"), _selection.fits file must be present \n",
     "sampling_function = btk.sampling_functions.DefaultSampling(stamp_size=stamp_size)\n",
-    "survey = btk.survey.get_surveys(\"Rubin\")"
+    "survey = btk.survey.get_surveys(\"LSST\")"
    ]
   },
   {
@@ -68,7 +68,7 @@
    "id": "975ddc32",
    "metadata": {},
    "source": [
-    "We can now create the corresponding instance of DrawBlendsGenerator. There is an important caveat here: as in the other tutorial, we use the Rubin survey. However, the COSMOS catalog only contains images from the f814w band; thus, when simulating images, the same magnitude is used to compute the galaxy fluxes across all bands.\n",
+    "We can now create the corresponding instance of DrawBlendsGenerator. There is an important caveat here: as in the other tutorial, we use the LSST survey. However, the COSMOS catalog only contains images from the f814w band; thus, when simulating images, the same magnitude is used to compute the galaxy fluxes across all bands.\n",
     "\n",
     "There is one way to circumvent this limitation in BTK: by providing a custom COSMOS catalog containing multiband magnitude information, one can compute more realistic source fluxes in each band. Such COSMOS catalogs containing multiband magnitudes for the HSC survey are available in the repository at \"../data/cosmos\" as \"real_galaxy_catalog_26_extension_example.fits\" and \"real_galaxy_catalog_26_extension_example_fits.fits\". Feel free to check the documentation for more information about COSMOS catalogs."
    ]
@@ -108,7 +108,7 @@
        "version_minor": 0
       },
       "text/plain": [
-       "Generating blends for Rubin survey:   0%|          | 0/8 [00:00<?, ?it/s]"
+       "Generating blends for LSST survey:   0%|          | 0/8 [00:00<?, ?it/s]"
       ]
      },
      "metadata": {},
diff --git a/notebooks/01b-scarlet-measure.ipynb b/notebooks/01b-scarlet-measure.ipynb
index 958aebdb8..1981b0279 100644
--- a/notebooks/01b-scarlet-measure.ipynb
+++ b/notebooks/01b-scarlet-measure.ipynb
@@ -41,7 +41,7 @@
    "source": [
     "catalog_name = \"../data/sample_input_catalog.fits\"\n",
     "stamp_size = 24\n",
-    "surveys = btk.survey.get_surveys([\"Rubin\",\"HSC\"])"
+    "surveys = btk.survey.get_surveys([\"LSST\",\"HSC\"])"
    ]
   },
   {
@@ -129,7 +129,7 @@
     "    for survey in surveys[1:]:\n",
     "        image = batch[\"blend_images\"][survey.name][idx]\n",
     "        image = np.moveaxis(image,-1,0) if channels_last else image\n",
-    "        psf = np.array([p.drawImage(galsim.Image(image.shape[1],image.shape[2]),scale=survey.pixel_scale).array for p in batch[\"psf\"][survey.name]])\n",
+    "        psf = np.array([p.drawImage(galsim.Image(image.shape[1],image.shape[2]),scale=survey.pixel_scale.to_value(\"arcsec\")).array for p in batch[\"psf\"][survey.name]])\n",
     "        bands=[f.name for f in survey.filters]\n",
     "        avg_image = np.mean(image, axis=0)\n",
     "        bkg = sep.Background(avg_image)\n",
diff --git a/notebooks/02a-multi-tutorial.ipynb b/notebooks/02a-multi-tutorial.ipynb
index 15e956d24..287d410b9 100644
--- a/notebooks/02a-multi-tutorial.ipynb
+++ b/notebooks/02a-multi-tutorial.ipynb
@@ -67,7 +67,7 @@
     "sampling_function = btk.sampling_functions.DefaultSampling()\n",
     "catalog_name = \"../data/sample_input_catalog.fits\"\n",
     "stamp_size = 24\n",
-    "surveys = btk.survey.get_surveys([\"Rubin\",\"HSC\"])\n",
+    "surveys = btk.survey.get_surveys([\"LSST\",\"HSC\"])\n",
     "catalog = btk.catalog.CatsimCatalog.from_file(catalog_name)\n",
     "draw_blend_generator = btk.draw_blends.CatsimGenerator(\n",
     "    catalog,\n",
@@ -100,7 +100,7 @@
        "version_minor": 0
       },
       "text/plain": [
-       "Generating blends for Rubin survey:   0%|          | 0/5 [00:00<?, ?it/s]"
+       "Generating blends for LSST survey:   0%|          | 0/5 [00:00<?, ?it/s]"
       ]
      },
      "metadata": {},
@@ -183,8 +183,8 @@
    ],
    "source": [
     "batch = next(draw_blend_generator)\n",
-    "blend_images = batch['blend_images'][\"Rubin\"]\n",
-    "blend_list = batch['blend_list'][\"Rubin\"]\n",
+    "blend_images = batch['blend_images'][\"LSST\"]\n",
+    "blend_list = batch['blend_list'][\"LSST\"]\n",
     "btk.plot_utils.plot_blends(blend_images, blend_list, limits=(30,90))"
    ]
   },
@@ -218,12 +218,12 @@
    "source": [
     "#Showing the two images side to side\n",
     "fig,ax = plt.subplots(1,2,figsize=(10,20))\n",
-    "ax[0].imshow(batch['blend_images'][\"Rubin\"][0,2])\n",
+    "ax[0].imshow(batch['blend_images'][\"LSST\"][0,2])\n",
     "ax[1].imshow(batch['blend_images'][\"HSC\"][0,2])\n",
-    "ax[0].set_title(\"Rubin image\")\n",
+    "ax[0].set_title(\"LSST image\")\n",
     "ax[1].set_title(\"HSC image\")\n",
     "plt.show()\n",
-    "print(f\"Size of the LSST image : {batch['blend_images']['Rubin'].shape[2]} pixels\")\n",
+    "print(f\"Size of the LSST image : {batch['blend_images']['LSST'].shape[2]} pixels\")\n",
     "print(f\"Size of the HSC image : {batch['blend_images']['HSC'].shape[2]} pixels\")"
    ]
   },
@@ -249,7 +249,7 @@
        "version_minor": 0
       },
       "text/plain": [
-       "Generating blends for Rubin survey:   0%|          | 0/5 [00:00<?, ?it/s]"
+       "Generating blends for LSST survey:   0%|          | 0/5 [00:00<?, ?it/s]"
       ]
      },
      "metadata": {},
@@ -388,7 +388,7 @@
     "sampling_function = btk.sampling_functions.DefaultSampling()\n",
     "catalog_name = \"../data/sample_input_catalog.fits\"\n",
     "stamp_size = 24\n",
-    "survey = btk.survey.get_surveys(\"Rubin\")\n",
+    "survey = btk.survey.get_surveys(\"LSST\")\n",
     "catalog = btk.catalog.CatsimCatalog.from_file(catalog_name)\n",
     "draw_blend_generator = btk.draw_blends.CatsimGenerator(\n",
     "    catalog,\n",
@@ -415,7 +415,7 @@
        "version_minor": 0
       },
       "text/plain": [
-       "Generating blends for Rubin survey:   0%|          | 0/10 [00:00<?, ?it/s]"
+       "Generating blends for LSST survey:   0%|          | 0/10 [00:00<?, ?it/s]"
       ]
      },
      "metadata": {},
@@ -503,7 +503,7 @@
     "sampling_function = btk.sampling_functions.DefaultSampling()\n",
     "catalog_name = \"../data/sample_input_catalog.fits\"\n",
     "stamp_size = 24\n",
-    "survey = btk.survey.get_surveys(\"Rubin\")\n",
+    "survey = btk.survey.get_surveys(\"LSST\")\n",
     "catalog = btk.catalog.CatsimCatalog.from_file(catalog_name)\n",
     "draw_blend_generator = btk.draw_blends.CatsimGenerator(\n",
     "    catalog,\n",
@@ -535,7 +535,7 @@
        "version_minor": 0
       },
       "text/plain": [
-       "Generating blends for Rubin survey:   0%|          | 0/10 [00:00<?, ?it/s]"
+       "Generating blends for LSST survey:   0%|          | 0/10 [00:00<?, ?it/s]"
       ]
      },
      "metadata": {},
@@ -626,7 +626,7 @@
        "version_minor": 0
       },
       "text/plain": [
-       "Generating blends for Rubin survey:   0%|          | 0/10 [00:00<?, ?it/s]"
+       "Generating blends for LSST survey:   0%|          | 0/10 [00:00<?, ?it/s]"
       ]
      },
      "metadata": {},
diff --git a/notebooks/02b-custom-tutorial.ipynb b/notebooks/02b-custom-tutorial.ipynb
index 9f0cb18e0..07c187e88 100644
--- a/notebooks/02b-custom-tutorial.ipynb
+++ b/notebooks/02b-custom-tutorial.ipynb
@@ -211,7 +211,7 @@
     "sampling_function = PairSampling()\n",
     "catalog_name = \"../data/sample_input_catalog.fits\"\n",
     "stamp_size = 24\n",
-    "survey = btk.survey.get_surveys(\"Rubin\")\n",
+    "survey = btk.survey.get_surveys(\"LSST\")\n",
     "catalog = btk.catalog.CatsimCatalog.from_file(catalog_name)\n",
     "draw_blend_generator = btk.draw_blends.CatsimGenerator(\n",
     "    catalog,\n",
@@ -236,7 +236,7 @@
        "version_minor": 0
       },
       "text/plain": [
-       "Generating blends for Rubin survey:   0%|          | 0/5 [00:00<?, ?it/s]"
+       "Generating blends for LSST survey:   0%|          | 0/5 [00:00<?, ?it/s]"
       ]
      },
      "metadata": {},
@@ -349,8 +349,8 @@
     "      you want to randomize the PSF.\n",
     "    In the case of the default surveys, we only use the first possibility, computing the model using the get_psf function beforehand; those models have an atmospheric and an optical component.\n",
     "\n",
-    "Surveys are usually imported using `btk.survey.get_surveys(survey_names)`, which will create the Survey object(s) from a config file (currently, the implemented surveys are Rubin, HSC, HST, Euclid, DES and CFHT); it is also possible to create them directly in Python.\n",
-    "Here is the definition of the Rubin survey as an example. You may try changing the parameters if you wish to see the effects on the blends."
+    "Surveys are usually imported using `btk.survey.get_surveys(survey_names)`, which will create the Survey object(s) from a config file (currently, the implemented surveys are LSST, HSC, COSMOS, Euclid, DES and CFHT); it is also possible to create them directly in Python.\n",
+    "Here is the definition of the LSST survey as an example. You may try changing the parameters if you wish to see the effects on the blends."
    ]
   },
   {
@@ -370,8 +370,8 @@
     "    \"z\": 8689.83,\n",
     "    \"y\": 9674.05,\n",
     "}\n",
-    "Rubin = btk.survey.Survey(\n",
-    "    \"Rubin\",\n",
+    "LSST = btk.survey.Survey(\n",
+    "    \"LSST\",\n",
     "    pixel_scale=0.2,\n",
     "    effective_area=32.4,\n",
     "    mirror_diameter=8.36,\n",
@@ -470,7 +470,7 @@
     "sampling_function = btk.sampling_functions.DefaultSampling()\n",
     "catalog_name = \"../data/sample_input_catalog.fits\"\n",
     "stamp_size = 24\n",
-    "survey = Rubin\n",
+    "survey = LSST\n",
     "catalog = btk.catalog.CatsimCatalog.from_file(catalog_name)\n",
     "draw_blend_generator = btk.draw_blends.CatsimGenerator(\n",
     "    catalog,\n",
@@ -495,7 +495,7 @@
        "version_minor": 0
       },
       "text/plain": [
-       "Generating blends for Rubin survey:   0%|          | 0/5 [00:00<?, ?it/s]"
+       "Generating blends for LSST survey:   0%|          | 0/5 [00:00<?, ?it/s]"
       ]
      },
      "metadata": {},
@@ -703,7 +703,7 @@
    "source": [
     "catalog_name = \"../data/sample_input_catalog.fits\"\n",
     "stamp_size = 24\n",
-    "survey = btk.survey.get_surveys(\"Rubin\")\n",
+    "survey = btk.survey.get_surveys(\"LSST\")\n",
     "catalog = btk.catalog.CatsimCatalog.from_file(catalog_name)\n",
     "draw_blend_generator = btk.draw_blends.CatsimGenerator(\n",
     "    catalog,\n",
@@ -774,7 +774,7 @@
        "version_minor": 0
       },
       "text/plain": [
-       "Generating blends for Rubin survey:   0%|          | 0/100 [00:00<?, ?it/s]"
+       "Generating blends for LSST survey:   0%|          | 0/100 [00:00<?, ?it/s]"
       ]
      },
      "metadata": {},
diff --git a/poetry.lock b/poetry.lock
index 44add4054..67206cc54 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -56,14 +56,14 @@ tests = ["pytest"]
 
 [[package]]
 name = "aspy.refactor-imports"
-version = "2.2.1"
+version = "3.0.1"
 description = "Utilities for refactoring imports in python-like syntax."
 category = "dev"
 optional = false
 python-versions = ">=3.7"
 
 [package.dependencies]
-cached-property = "*"
+cached-property = {version = "*", markers = "python_version < \"3.8\""}
 
 [[package]]
 name = "astropy"
@@ -136,6 +136,21 @@ category = "main"
 optional = false
 python-versions = "*"
 
+[[package]]
+name = "beautifulsoup4"
+version = "4.10.0"
+description = "Screen-scraping library"
+category = "main"
+optional = false
+python-versions = ">3.0.0"
+
+[package.dependencies]
+soupsieve = ">1.2"
+
+[package.extras]
+html5lib = ["html5lib"]
+lxml = ["lxml"]
+
 [[package]]
 name = "black"
 version = "22.1.0"
@@ -355,7 +370,7 @@ flake8 = ">=3.7"
 
 [[package]]
 name = "fonttools"
-version = "4.29.1"
+version = "4.31.0"
 description = "Tools to manipulate font files"
 category = "main"
 optional = false
@@ -382,6 +397,29 @@ category = "main"
 optional = false
 python-versions = ">=2.6, !=3.0.*, !=3.1.*, !=3.2.*"
 
+[[package]]
+name = "galcheat"
+version = "0.1.3.dev53+gbb0c765"
+description = "Tiny library of galaxy surveys most useful parameters with units"
+category = "main"
+optional = false
+python-versions = ">=3.7"
+develop = false
+
+[package.dependencies]
+astropy = ">=4.3"
+pyyaml = ">=5.1"
+
+[package.extras]
+dev = ["pre-commit (>=2.17)", "pytest (>=6.0)", "pytest-cov (>=3.0)", "pytest-astropy-header (>=0.2)"]
+scripts = ["speclite (>=0.15)"]
+
+[package.source]
+type = "git"
+url = "https://github.com/aboucaud/galcheat"
+reference = "bb0c765ef8a130f9112d99580d93adffb2a8af47"
+resolved_reference = "bb0c765ef8a130f9112d99580d93adffb2a8af47"
+
 [[package]]
 name = "galsim"
 version = "2.3.4"
@@ -411,7 +449,7 @@ omegaconf = ">=2.1.0,<2.2.0"
 
 [[package]]
 name = "identify"
-version = "2.4.10"
+version = "2.4.12"
 description = "File identification library for Python"
 category = "dev"
 optional = false
@@ -430,11 +468,11 @@ python-versions = ">=3.5"
 
 [[package]]
 name = "imageio"
-version = "2.16.0"
+version = "2.16.1"
 description = "Library for reading and writing a wide range of image, video, scientific, and volumetric data formats."
 category = "main"
 optional = false
-python-versions = ">=3.5"
+python-versions = ">=3.7"
 
 [package.dependencies]
 numpy = ">=1.20.0"
@@ -463,7 +501,7 @@ python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*"
 
 [[package]]
 name = "importlib-metadata"
-version = "4.11.1"
+version = "4.11.3"
 description = "Read metadata from Python packages"
 category = "main"
 optional = false
@@ -474,7 +512,7 @@ typing-extensions = {version = ">=3.6.4", markers = "python_version < \"3.8\""}
 zipp = ">=0.5"
 
 [package.extras]
-docs = ["sphinx", "jaraco.packaging (>=8.2)", "rst.linker (>=1.9)"]
+docs = ["sphinx", "jaraco.packaging (>=9)", "rst.linker (>=1.9)"]
 perf = ["ipython"]
 testing = ["pytest (>=6)", "pytest-checkdocs (>=2.4)", "pytest-flake8", "pytest-cov", "pytest-enabler (>=1.0.1)", "packaging", "pyfakefs", "flufl.flake8", "pytest-perf (>=0.9.2)", "pytest-black (>=0.3.7)", "pytest-mypy (>=0.9.1)", "importlib-resources (>=1.3)"]
 
@@ -503,7 +541,7 @@ python-versions = "*"
 
 [[package]]
 name = "ipykernel"
-version = "6.9.1"
+version = "6.9.2"
 description = "IPython Kernel for Jupyter"
 category = "main"
 optional = false
@@ -516,6 +554,7 @@ ipython = ">=7.23.1"
 jupyter-client = "<8.0"
 matplotlib-inline = ">=0.1.0,<0.2.0"
 nest-asyncio = "*"
+psutil = "*"
 tornado = ">=4.2,<7.0"
 traitlets = ">=5.1.0,<6.0"
 
@@ -524,7 +563,7 @@ test = ["pytest (!=5.3.4)", "pytest-cov", "flaky", "ipyparallel"]
 
 [[package]]
 name = "ipython"
-version = "7.31.1"
+version = "7.32.0"
 description = "IPython: Productive Interactive Computing"
 category = "main"
 optional = false
@@ -564,7 +603,7 @@ python-versions = "*"
 
 [[package]]
 name = "ipywidgets"
-version = "7.6.5"
+version = "7.7.0"
 description = "IPython HTML widgets for Jupyter"
 category = "main"
 optional = false
@@ -577,7 +616,7 @@ ipython-genutils = ">=0.2.0,<0.3.0"
 jupyterlab-widgets = {version = ">=1.0.0", markers = "python_version >= \"3.6\""}
 nbformat = ">=4.2.0"
 traitlets = ">=4.3.1"
-widgetsnbextension = ">=3.5.0,<3.6.0"
+widgetsnbextension = ">=3.6.0,<3.7.0"
 
 [package.extras]
 test = ["pytest (>=3.6.0)", "pytest-cov", "mock"]
@@ -691,7 +730,7 @@ pygments = ">=2.4.1,<3"
 
 [[package]]
 name = "jupyterlab-widgets"
-version = "1.0.2"
+version = "1.1.0"
 description = "A JupyterLab extension."
 category = "main"
 optional = false
@@ -699,12 +738,15 @@ python-versions = ">=3.6"
 
 [[package]]
 name = "kiwisolver"
-version = "1.3.2"
+version = "1.4.0"
 description = "A fast implementation of the Cassowary constraint solver"
 category = "main"
 optional = false
 python-versions = ">=3.7"
 
+[package.dependencies]
+typing-extensions = {version = "*", markers = "python_version < \"3.8\""}
+
 [[package]]
 name = "lsstdesc.coord"
 version = "1.2.2"
@@ -720,7 +762,7 @@ numpy = "*"
 
 [[package]]
 name = "markupsafe"
-version = "2.1.0"
+version = "2.1.1"
 description = "Safely add untrusted strings to HTML/XML markup."
 category = "main"
 optional = false
@@ -795,7 +837,7 @@ python-versions = "*"
 
 [[package]]
 name = "nbclient"
-version = "0.5.11"
+version = "0.5.13"
 description = "A client library for executing notebooks. Formerly nbconvert's ExecutePreprocessor."
 category = "main"
 optional = false
@@ -805,7 +847,7 @@ python-versions = ">=3.7.0"
 jupyter-client = ">=6.1.5"
 nbformat = ">=5.0"
 nest-asyncio = "*"
-traitlets = ">=4.2"
+traitlets = ">=5.0.0"
 
 [package.extras]
 sphinx = ["Sphinx (>=1.7)", "sphinx-book-theme", "mock", "moto", "myst-parser"]
@@ -813,13 +855,14 @@ test = ["ipython (<8.0.0)", "ipykernel", "ipywidgets (<8.0.0)", "pytest (>=4.1)"
 
 [[package]]
 name = "nbconvert"
-version = "6.4.2"
+version = "6.4.4"
 description = "Converting Jupyter Notebooks"
 category = "main"
 optional = false
 python-versions = ">=3.7"
 
 [package.dependencies]
+beautifulsoup4 = "*"
 bleach = "*"
 defusedxml = "*"
 entrypoints = ">=0.2.2"
@@ -843,21 +886,20 @@ webpdf = ["pyppeteer (>=1,<1.1)"]
 
 [[package]]
 name = "nbformat"
-version = "5.1.3"
+version = "5.2.0"
 description = "The Jupyter Notebook format"
 category = "main"
 optional = false
-python-versions = ">=3.5"
+python-versions = ">=3.7"
 
 [package.dependencies]
-ipython-genutils = "*"
 jsonschema = ">=2.4,<2.5.0 || >2.5.0"
 jupyter-core = "*"
 traitlets = ">=4.1"
 
 [package.extras]
 fast = ["fastjsonschema"]
-test = ["check-manifest", "fastjsonschema", "testpath", "pytest", "pytest-cov"]
+test = ["check-manifest", "fastjsonschema", "testpath", "pytest"]
 
 [[package]]
 name = "nbstripout"
@@ -919,7 +961,7 @@ python-versions = "*"
 
 [[package]]
 name = "notebook"
-version = "6.4.8"
+version = "6.4.10"
 description = "A web-based notebook environment for interactive computing"
 category = "main"
 optional = false
@@ -932,7 +974,7 @@ ipython-genutils = "*"
 jinja2 = "*"
 jupyter-client = ">=5.3.4"
 jupyter-core = ">=4.6.1"
-nbconvert = "*"
+nbconvert = ">=5"
 nbformat = "*"
 nest-asyncio = ">=1.5"
 prometheus-client = "*"
@@ -1139,6 +1181,17 @@ python-versions = "*"
 numpy = "*"
 scipy = "*"
 
+[[package]]
+name = "psutil"
+version = "5.9.0"
+description = "Cross-platform lib for process and system monitoring in Python."
+category = "main"
+optional = false
+python-versions = ">=2.6, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*"
+
+[package.extras]
+test = ["ipaddress", "mock", "unittest2", "enum34", "pywin32", "wmi"]
+
 [[package]]
 name = "ptyprocess"
 version = "0.7.0"
@@ -1248,11 +1301,11 @@ python-versions = ">=3.7"
 
 [[package]]
 name = "pytest"
-version = "7.0.1"
+version = "7.1.1"
 description = "pytest: simple powerful testing with Python"
 category = "dev"
 optional = false
-python-versions = ">=3.6"
+python-versions = ">=3.7"
 
 [package.dependencies]
 atomicwrites = {version = ">=1.0", markers = "sys_platform == \"win32\""}
@@ -1304,7 +1357,7 @@ python-versions = "*"
 
 [[package]]
 name = "pywavelets"
-version = "1.2.0"
+version = "1.3.0"
 description = "PyWavelets, wavelet transform module"
 category = "main"
 optional = false
@@ -1323,11 +1376,11 @@ python-versions = "*"
 
 [[package]]
 name = "pywinpty"
-version = "2.0.2"
+version = "2.0.5"
 description = "Pseudo terminal support for Windows from Python."
 category = "main"
 optional = false
-python-versions = ">=3.6"
+python-versions = ">=3.7"
 
 [[package]]
 name = "pyyaml"
@@ -1351,14 +1404,14 @@ py = {version = "*", markers = "implementation_name == \"pypy\""}
 
 [[package]]
 name = "reorder-python-imports"
-version = "2.7.1"
+version = "3.0.1"
 description = "Tool for reordering python imports"
 category = "dev"
 optional = false
 python-versions = ">=3.7"
 
 [package.dependencies]
-"aspy.refactor-imports" = ">=2.2.1"
+"aspy.refactor-imports" = ">=2.3.0"
 
 [[package]]
 name = "requests"
@@ -1483,6 +1536,14 @@ category = "dev"
 optional = false
 python-versions = "*"
 
+[[package]]
+name = "soupsieve"
+version = "2.3.1"
+description = "A modern CSS selector implementation for Beautiful Soup."
+category = "main"
+optional = false
+python-versions = ">=3.6"
+
 [[package]]
 name = "sphinx"
 version = "4.4.0"
@@ -1603,7 +1664,7 @@ test = ["pytest"]
 
 [[package]]
 name = "terminado"
-version = "0.13.1"
+version = "0.13.3"
 description = "Tornado websocket backend for the Xterm.js Javascript terminal emulator library."
 category = "main"
 optional = false
@@ -1619,14 +1680,14 @@ test = ["pytest"]
 
 [[package]]
 name = "testpath"
-version = "0.5.0"
+version = "0.6.0"
 description = "Test utilities for code working with files and commands"
 category = "main"
 optional = false
 python-versions = ">= 3.5"
 
 [package.extras]
-test = ["pytest", "pathlib2"]
+test = ["pytest"]
 
 [[package]]
 name = "tifffile"
@@ -1668,7 +1729,7 @@ python-versions = ">= 3.5"
 
 [[package]]
 name = "tqdm"
-version = "4.62.3"
+version = "4.63.0"
 description = "Fast, Extensible Progress Meter"
 category = "main"
 optional = false
@@ -1711,20 +1772,20 @@ python-versions = ">=3.6"
 
 [[package]]
 name = "urllib3"
-version = "1.26.8"
+version = "1.26.9"
 description = "HTTP library with thread-safe connection pooling, file post, and more."
 category = "dev"
 optional = false
 python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*, <4"
 
 [package.extras]
-brotli = ["brotlipy (>=0.6.0)"]
+brotli = ["brotlicffi (>=0.8.0)", "brotli (>=1.0.9)", "brotlipy (>=0.6.0)"]
 secure = ["pyOpenSSL (>=0.14)", "cryptography (>=1.3.4)", "idna (>=2.0.0)", "certifi", "ipaddress"]
 socks = ["PySocks (>=1.5.6,!=1.5.7,<2.0)"]
 
 [[package]]
 name = "virtualenv"
-version = "20.13.1"
+version = "20.13.3"
 description = "Virtual Python Environment builder"
 category = "dev"
 optional = false
@@ -1759,7 +1820,7 @@ python-versions = "*"
 
 [[package]]
 name = "widgetsnbextension"
-version = "3.5.2"
+version = "3.6.0"
 description = "IPython HTML widgets for Jupyter"
 category = "main"
 optional = false
@@ -1786,7 +1847,7 @@ scarlet = ["peigen", "autograd", "pybind11", "proxmin"]
 [metadata]
 lock-version = "1.1"
 python-versions = ">= 3.7.1, < 3.9.0"
-content-hash = "3b741e07eb889153af59cf0933b13ec51cd962e956732aff94773fc6d7d21146"
+content-hash = "37f82dc52472f7b546e72eb7b3aa55b7d8ca9d4d5418ce8e6dd78527ff98f0d8"
 
 [metadata.files]
 alabaster = [
@@ -1828,8 +1889,8 @@ argon2-cffi-bindings = [
     {file = "argon2_cffi_bindings-21.2.0-pp38-pypy38_pp73-win_amd64.whl", hash = "sha256:5e00316dabdaea0b2dd82d141cc66889ced0cdcbfa599e8b471cf22c620c329a"},
 ]
 "aspy.refactor-imports" = [
-    {file = "aspy.refactor_imports-2.2.1-py2.py3-none-any.whl", hash = "sha256:ace9ca78abf6cfdd20ea1a321b75b20c8cc2c1af58aecb9dc4ba9d6f70f74645"},
-    {file = "aspy.refactor_imports-2.2.1.tar.gz", hash = "sha256:f5b2fcbf9fd68361168588f14eda64d502d029eefe632d15094cd0683ae12984"},
+    {file = "aspy.refactor_imports-3.0.1-py2.py3-none-any.whl", hash = "sha256:bc257946fdf5abd9c60393cfb8d0b5d45a2b87d1ee0ede46584c8be5567bc669"},
+    {file = "aspy.refactor_imports-3.0.1.tar.gz", hash = "sha256:df497c3726ee2931b03d403e58a4590f7f4e60059b115cf5df0e07e70c7c73be"},
 ]
 astropy = [
     {file = "astropy-4.3.1-cp37-cp37m-macosx_10_9_x86_64.whl", hash = "sha256:a0764d7f68034c584dda8d1c9cc4357ade05cec4c1134db43bce804fcf656ff1"},
@@ -1868,6 +1929,10 @@ backcall = [
     {file = "backcall-0.2.0-py2.py3-none-any.whl", hash = "sha256:fbbce6a29f263178a1f7915c1940bde0ec2b2a967566fe1c65c1dfb7422bd255"},
     {file = "backcall-0.2.0.tar.gz", hash = "sha256:5cbdbf27be5e7cfadb448baf0aa95508f91f2bbc6c6437cd9cd06e2a4c215e1e"},
 ]
+beautifulsoup4 = [
+    {file = "beautifulsoup4-4.10.0-py3-none-any.whl", hash = "sha256:9a315ce70049920ea4572a4055bc4bd700c940521d36fc858205ad4fcde149bf"},
+    {file = "beautifulsoup4-4.10.0.tar.gz", hash = "sha256:c23ad23c521d818955a4151a67d81580319d4bf548d3d49f4223ae041ff98891"},
+]
 black = [
     {file = "black-22.1.0-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:1297c63b9e1b96a3d0da2d85d11cd9bf8664251fd69ddac068b98dc4f34f73b6"},
     {file = "black-22.1.0-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:2ff96450d3ad9ea499fc4c60e425a1439c2120cbbc1ab959ff20f7c76ec7e866"},
@@ -2113,12 +2178,13 @@ flake8-absolute-import = [
     {file = "flake8_absolute_import-1.0.0.1-py3-none-any.whl", hash = "sha256:d24f189bca52ffc0d13e8046606ea42d22a9ad9d409bf39e52b93493cf2ffd2c"},
 ]
 fonttools = [
-    {file = "fonttools-4.29.1-py3-none-any.whl", hash = "sha256:1933415e0fbdf068815cb1baaa1f159e17830215f7e8624e5731122761627557"},
-    {file = "fonttools-4.29.1.zip", hash = "sha256:2b18a172120e32128a80efee04cff487d5d140fe7d817deb648b2eee023a40e4"},
+    {file = "fonttools-4.31.0-py3-none-any.whl", hash = "sha256:058d15bd7aa35f47df70f99a15ac4994787127db42c468e695d1b9ef77c0a6a4"},
+    {file = "fonttools-4.31.0.zip", hash = "sha256:1b008d129c1c0f0174a74f2ea07b949ed4fbf328355cf4c9812506ecaac38b9f"},
 ]
 future = [
     {file = "future-0.18.2.tar.gz", hash = "sha256:b1bead90b70cf6ec3f0710ae53a525360fa360d306a86583adc6bf83a4db537d"},
 ]
+galcheat = []
 galsim = [
     {file = "GalSim-2.3.4-cp27-cp27m-macosx_10_9_x86_64.whl", hash = "sha256:e15165ddaf0d1572d319efe7160f83bd9b10aa33f4f8854f896c2eea0a71e9e3"},
     {file = "GalSim-2.3.4-cp27-cp27m-manylinux2010_i686.whl", hash = "sha256:edaad17af01b8a731ba60877401544255c78a46570a18ce0c5bb5ddcc6555583"},
@@ -2153,24 +2219,24 @@ hydra-core = [
     {file = "hydra_core-1.1.1-py3-none-any.whl", hash = "sha256:928b154d8105db4ee67d768e3cd0f74ca9373121fc99dee54488393b17a31929"},
 ]
 identify = [
-    {file = "identify-2.4.10-py2.py3-none-any.whl", hash = "sha256:7d10baf6ba6f1912a0a49f4c1c2c49fa1718765c3a37d72d13b07779567c5b85"},
-    {file = "identify-2.4.10.tar.gz", hash = "sha256:e12b2aea3cf108de73ae055c2260783bde6601de09718f6768cf8e9f6f6322a6"},
+    {file = "identify-2.4.12-py2.py3-none-any.whl", hash = "sha256:5f06b14366bd1facb88b00540a1de05b69b310cbc2654db3c7e07fa3a4339323"},
+    {file = "identify-2.4.12.tar.gz", hash = "sha256:3f3244a559290e7d3deb9e9adc7b33594c1bc85a9dd82e0f1be519bf12a1ec17"},
 ]
 idna = [
     {file = "idna-3.3-py3-none-any.whl", hash = "sha256:84d9dd047ffa80596e0f246e2eab0b391788b0503584e8945f2368256d2735ff"},
     {file = "idna-3.3.tar.gz", hash = "sha256:9d643ff0a55b762d5cdb124b8eaa99c66322e2157b69160bc32796e824360e6d"},
 ]
 imageio = [
-    {file = "imageio-2.16.0-py3-none-any.whl", hash = "sha256:1ee35330318bcb0ce25de778fc1f61555558a159433a568887d7e3d0317ce63c"},
-    {file = "imageio-2.16.0.tar.gz", hash = "sha256:7f7d8d8e1eb6f8bb1d15e0dd93bee3f72026a4c3b96e9c690e42f403f7bdea3e"},
+    {file = "imageio-2.16.1-py3-none-any.whl", hash = "sha256:d8d17c59b6f5f3b350bbbe346e7cb7dda0399b1881d93ad01cb29b5acdb24c42"},
+    {file = "imageio-2.16.1.tar.gz", hash = "sha256:7f123cb23a77ac5abe8ed4e7ad6a60831a82de2c5d123463dcf1d4278c4779d2"},
 ]
 imagesize = [
     {file = "imagesize-1.3.0-py2.py3-none-any.whl", hash = "sha256:1db2f82529e53c3e929e8926a1fa9235aa82d0bd0c580359c67ec31b2fddaa8c"},
     {file = "imagesize-1.3.0.tar.gz", hash = "sha256:cd1750d452385ca327479d45b64d9c7729ecf0b3969a58148298c77092261f9d"},
 ]
 importlib-metadata = [
-    {file = "importlib_metadata-4.11.1-py3-none-any.whl", hash = "sha256:e0bc84ff355328a4adfc5240c4f211e0ab386f80aa640d1b11f0618a1d282094"},
-    {file = "importlib_metadata-4.11.1.tar.gz", hash = "sha256:175f4ee440a0317f6e8d81b7f8d4869f93316170a65ad2b007d2929186c8052c"},
+    {file = "importlib_metadata-4.11.3-py3-none-any.whl", hash = "sha256:1208431ca90a8cca1a6b8af391bb53c1a2db74e5d1cef6ddced95d4b2062edc6"},
+    {file = "importlib_metadata-4.11.3.tar.gz", hash = "sha256:ea4c597ebf37142f827b8f39299579e31685c31d3a438b59f469406afd0f2539"},
 ]
 importlib-resources = [
     {file = "importlib_resources-5.4.0-py3-none-any.whl", hash = "sha256:33a95faed5fc19b4bc16b29a6eeae248a3fe69dd55d4d229d2b480e23eeaad45"},
@@ -2181,20 +2247,20 @@ iniconfig = [
     {file = "iniconfig-1.1.1.tar.gz", hash = "sha256:bc3af051d7d14b2ee5ef9969666def0cd1a000e121eaea580d4a313df4b37f32"},
 ]
 ipykernel = [
-    {file = "ipykernel-6.9.1-py3-none-any.whl", hash = "sha256:4fae9df6e192837552b2406a6052d707046dd2e153860be73c68484bacba18ed"},
-    {file = "ipykernel-6.9.1.tar.gz", hash = "sha256:f95070a2dfd3147f8ab19f18ee46733310813758593745e07ec18fb08b409f1d"},
+    {file = "ipykernel-6.9.2-py3-none-any.whl", hash = "sha256:c977cff576b8425a68d3a6916510903833f0f25ed8d5c282a0c51c35de27bd47"},
+    {file = "ipykernel-6.9.2.tar.gz", hash = "sha256:4c3cc8cb359f2ead70c30f5504971c0d285e2c1c699d2ce9af0216fe9c9fb17c"},
 ]
 ipython = [
-    {file = "ipython-7.31.1-py3-none-any.whl", hash = "sha256:55df3e0bd0f94e715abd968bedd89d4e8a7bce4bf498fb123fed4f5398fea874"},
-    {file = "ipython-7.31.1.tar.gz", hash = "sha256:b5548ec5329a4bcf054a5deed5099b0f9622eb9ea51aaa7104d215fece201d8c"},
+    {file = "ipython-7.32.0-py3-none-any.whl", hash = "sha256:86df2cf291c6c70b5be6a7b608650420e89180c8ec74f376a34e2dc15c3400e7"},
+    {file = "ipython-7.32.0.tar.gz", hash = "sha256:468abefc45c15419e3c8e8c0a6a5c115b2127bafa34d7c641b1d443658793909"},
 ]
 ipython-genutils = [
     {file = "ipython_genutils-0.2.0-py2.py3-none-any.whl", hash = "sha256:72dd37233799e619666c9f639a9da83c34013a73e8bbc79a7a6348d93c61fab8"},
     {file = "ipython_genutils-0.2.0.tar.gz", hash = "sha256:eb2e116e75ecef9d4d228fdc66af54269afa26ab4463042e33785b887c628ba8"},
 ]
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 sphinx = [
     {file = "Sphinx-4.4.0-py3-none-any.whl", hash = "sha256:5da895959511473857b6d0200f56865ed62c31e8f82dd338063b84ec022701fe"},
     {file = "Sphinx-4.4.0.tar.gz", hash = "sha256:6caad9786055cb1fa22b4a365c1775816b876f91966481765d7d50e9f0dd35cc"},
@@ -2957,12 +3062,12 @@ sphinxcontrib-serializinghtml = [
     {file = "sphinxcontrib_serializinghtml-1.1.5-py2.py3-none-any.whl", hash = "sha256:352a9a00ae864471d3a7ead8d7d79f5fc0b57e8b3f95e9867eb9eb28999b92fd"},
 ]
 terminado = [
-    {file = "terminado-0.13.1-py3-none-any.whl", hash = "sha256:f446b522b50a7aa68b5def0a02893978fb48cb82298b0ebdae13003c6ee6f198"},
-    {file = "terminado-0.13.1.tar.gz", hash = "sha256:5b82b5c6e991f0705a76f961f43262a7fb1e55b093c16dca83f16384a7f39b7b"},
+    {file = "terminado-0.13.3-py3-none-any.whl", hash = "sha256:874d4ea3183536c1782d13c7c91342ef0cf4e5ee1d53633029cbc972c8760bd8"},
+    {file = "terminado-0.13.3.tar.gz", hash = "sha256:94d1cfab63525993f7d5c9b469a50a18d0cdf39435b59785715539dd41e36c0d"},
 ]
 testpath = [
-    {file = "testpath-0.5.0-py3-none-any.whl", hash = "sha256:8044f9a0bab6567fc644a3593164e872543bb44225b0e24846e2c89237937589"},
-    {file = "testpath-0.5.0.tar.gz", hash = "sha256:1acf7a0bcd3004ae8357409fc33751e16d37ccc650921da1094a86581ad1e417"},
+    {file = "testpath-0.6.0-py3-none-any.whl", hash = "sha256:8ada9f80a2ac6fb0391aa7cdb1a7d11cfa8429f693eda83f74dde570fe6fa639"},
+    {file = "testpath-0.6.0.tar.gz", hash = "sha256:2f1b97e6442c02681ebe01bd84f531028a7caea1af3825000f52345c30285e0f"},
 ]
 tifffile = [
     {file = "tifffile-2021.11.2-py3-none-any.whl", hash = "sha256:2e0066f90e2dbeb3e6a287cfd78bafbd2f142fabbca4a76a8ff809573baf5ad5"},
@@ -3020,8 +3125,8 @@ tornado = [
     {file = "tornado-6.1.tar.gz", hash = "sha256:33c6e81d7bd55b468d2e793517c909b139960b6c790a60b7991b9b6b76fb9791"},
 ]
 tqdm = [
-    {file = "tqdm-4.62.3-py2.py3-none-any.whl", hash = "sha256:8dd278a422499cd6b727e6ae4061c40b48fce8b76d1ccbf5d34fca9b7f925b0c"},
-    {file = "tqdm-4.62.3.tar.gz", hash = "sha256:d359de7217506c9851b7869f3708d8ee53ed70a1b8edbba4dbcb47442592920d"},
+    {file = "tqdm-4.63.0-py2.py3-none-any.whl", hash = "sha256:e643e071046f17139dea55b880dc9b33822ce21613b4a4f5ea57f202833dbc29"},
+    {file = "tqdm-4.63.0.tar.gz", hash = "sha256:1d9835ede8e394bb8c9dcbffbca02d717217113adc679236873eeaac5bc0b3cd"},
 ]
 traitlets = [
     {file = "traitlets-5.1.1-py3-none-any.whl", hash = "sha256:2d313cc50a42cd6c277e7d7dc8d4d7fedd06a2c215f78766ae7b1a66277e0033"},
@@ -3058,12 +3163,12 @@ typing-extensions = [
     {file = "typing_extensions-4.1.1.tar.gz", hash = "sha256:1a9462dcc3347a79b1f1c0271fbe79e844580bb598bafa1ed208b94da3cdcd42"},
 ]
 urllib3 = [
-    {file = "urllib3-1.26.8-py2.py3-none-any.whl", hash = "sha256:000ca7f471a233c2251c6c7023ee85305721bfdf18621ebff4fd17a8653427ed"},
-    {file = "urllib3-1.26.8.tar.gz", hash = "sha256:0e7c33d9a63e7ddfcb86780aac87befc2fbddf46c58dbb487e0855f7ceec283c"},
+    {file = "urllib3-1.26.9-py2.py3-none-any.whl", hash = "sha256:44ece4d53fb1706f667c9bd1c648f5469a2ec925fcf3a776667042d645472c14"},
+    {file = "urllib3-1.26.9.tar.gz", hash = "sha256:aabaf16477806a5e1dd19aa41f8c2b7950dd3c746362d7e3223dbe6de6ac448e"},
 ]
 virtualenv = [
-    {file = "virtualenv-20.13.1-py2.py3-none-any.whl", hash = "sha256:45e1d053cad4cd453181ae877c4ffc053546ae99e7dd049b9ff1d9be7491abf7"},
-    {file = "virtualenv-20.13.1.tar.gz", hash = "sha256:e0621bcbf4160e4e1030f05065c8834b4e93f4fcc223255db2a823440aca9c14"},
+    {file = "virtualenv-20.13.3-py2.py3-none-any.whl", hash = "sha256:dd448d1ded9f14d1a4bfa6bfc0c5b96ae3be3f2d6c6c159b23ddcfd701baa021"},
+    {file = "virtualenv-20.13.3.tar.gz", hash = "sha256:e9dd1a1359d70137559034c0f5433b34caf504af2dc756367be86a5a32967134"},
 ]
 wcwidth = [
     {file = "wcwidth-0.2.5-py2.py3-none-any.whl", hash = "sha256:beb4802a9cebb9144e99086eff703a642a13d6a0052920003a230f3294bbe784"},
@@ -3074,8 +3179,8 @@ webencodings = [
     {file = "webencodings-0.5.1.tar.gz", hash = "sha256:b36a1c245f2d304965eb4e0a82848379241dc04b865afcc4aab16748587e1923"},
 ]
 widgetsnbextension = [
-    {file = "widgetsnbextension-3.5.2-py2.py3-none-any.whl", hash = "sha256:763a9fdc836d141fa080005a886d63f66f73d56dba1fb5961afc239c77708569"},
-    {file = "widgetsnbextension-3.5.2.tar.gz", hash = "sha256:e0731a60ba540cd19bbbefe771a9076dcd2dde90713a8f87f27f53f2d1db7727"},
+    {file = "widgetsnbextension-3.6.0-py2.py3-none-any.whl", hash = "sha256:4fd321cad39fdcf8a8e248a657202d42917ada8e8ed5dd3f60f073e0d54ceabd"},
+    {file = "widgetsnbextension-3.6.0.tar.gz", hash = "sha256:e84a7a9fcb9baf3d57106e184a7389a8f8eb935bf741a5eb9d60aa18cc029a80"},
 ]
 zipp = [
     {file = "zipp-3.7.0-py3-none-any.whl", hash = "sha256:b47250dd24f92b7dd6a0a8fc5244da14608f3ca90a5efcd37a3b1642fac9a375"},
diff --git a/pyproject.toml b/pyproject.toml
index 3b4945e49..22a79e857 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -29,6 +29,7 @@ version = "0.9.3"
 [tool.poetry.dependencies]
 astropy = ">=4.3.1"
 autograd = {version = ">=1.3", optional = true}
+galcheat = {git = "https://github.com/aboucaud/galcheat", rev = "bb0c765ef8a130f9112d99580d93adffb2a8af47"}
 galsim = ">=2.2.4"
 hydra-core = ">=1.0.6"
 ipywidgets = ">=7.6.5"
diff --git a/tests/test_cosmos.py b/tests/test_cosmos.py
index 5e910e71f..845cc89e4 100644
--- a/tests/test_cosmos.py
+++ b/tests/test_cosmos.py
@@ -21,12 +21,12 @@ def test_cosmos_galaxies_real():
     batch_size = 2
     catalog = CosmosCatalog.from_file(COSMOS_CATALOG_PATHS)
     sampling_function = DefaultSampling(stamp_size=stamp_size)
-    HST = get_surveys("HST")
+    COSMOS = get_surveys("COSMOS")
 
     draw_generator = CosmosGenerator(
         catalog,
         sampling_function,
-        HST,
+        COSMOS,
         batch_size=batch_size,
         stamp_size=stamp_size,
         cpus=1,
@@ -43,12 +43,12 @@ def test_cosmos_galaxies_parametric():
     batch_size = 2
     catalog = CosmosCatalog.from_file(COSMOS_CATALOG_PATHS)
     sampling_function = DefaultSampling(stamp_size=stamp_size)
-    HST = get_surveys("HST")
+    COSMOS = get_surveys("COSMOS")
 
     draw_generator = CosmosGenerator(
         catalog,
         sampling_function,
-        HST,
+        COSMOS,
         batch_size=batch_size,
         stamp_size=stamp_size,
         cpus=1,
@@ -65,12 +65,12 @@ def test_cosmos_ext_galaxies():
     batch_size = 2
     catalog = CosmosCatalog.from_file(COSMOS_EXT_CATALOG_PATHS, exclusion_level="none")
     sampling_function = DefaultSampling(stamp_size=stamp_size)
-    HST = get_surveys("HST")
+    COSMOS = get_surveys("COSMOS")
 
     draw_generator = CosmosGenerator(
         catalog,
         sampling_function,
-        HST,
+        COSMOS,
         batch_size=batch_size,
         stamp_size=stamp_size,
         cpus=1,
diff --git a/tests/test_draw.py b/tests/test_draw.py
index cfdbd82f5..c1405ac51 100644
--- a/tests/test_draw.py
+++ b/tests/test_draw.py
@@ -17,7 +17,7 @@ def get_draw_generator(
     fixed_parameters=False,
     sampling_function=None,
 ):
-    """Returns a btk.draw_blends generator for default parameters"""
+    """Returns a btk.draw_blends generator for default parameters."""
     catalog_name = "data/sample_input_catalog.fits"
     stamp_size = 24.0
     if fixed_parameters:
@@ -43,7 +43,7 @@ def get_draw_generator(
     draw_generator = btk.draw_blends.CatsimGenerator(
         catalog,
         sampling_function,
-        get_surveys("Rubin"),
+        get_surveys("LSST"),
         batch_size=batch_size,
         stamp_size=stamp_size,
         shifts=shifts,
@@ -76,9 +76,9 @@ def match_isolated_images_default(isolated_images):
         the mean and std values in the batch. This is compared to the values
         measured a proiri for the default input settings.
         """
-        test_batch_max = np.array([90.326, 1242.806, 7627.732, 10377.04, 8513.054, 4767.485])
+        test_batch_max = np.array([90.276, 1242.4, 7626.081, 10375.342, 8512.592, 4766.38])
         test_batch_mean = 3.1129989295360363
-        test_batch_std = 90.89562371148732
+        test_batch_std = 90.8863095471388
         batch_max = isolated_images.max(axis=(0, 1, 3, 4))
         batch_mean = isolated_images.mean()
         batch_std = isolated_images.std()
@@ -107,9 +107,9 @@ def match_blend_images_default(blend_images):
         the mean and std values in the batch. This is compared to the values
         measured a priori for the default input settings.
         """
-        test_batch_max = np.array([172.012, 1372.121, 7881.862, 10346.612, 9120.189, 4965.317])
-        test_batch_mean = 6.123635022094785
-        test_batch_std = 403.7842461889957
+        test_batch_max = np.array([172.04, 1375.16, 7880.88, 10823.64, 9120.2, 4836.32])
+        test_batch_mean = 6.118185763860468
+        test_batch_std = 403.79788119078427
         batch_max = blend_images.max(axis=(0, 2, 3))
         batch_mean = blend_images.mean()
         batch_std = blend_images.std()
@@ -138,7 +138,7 @@ def match_background_noise(blend_images):
         the r band. This is compared to the values measured a priori for the
         default input settings.
         """
-        test_batch_noise = 128664.3287115097
+        test_batch_noise = 128666.38136196136
         batch_noise = np.var(blend_images[1, 2, 0:32, 0:32])
         np.testing.assert_almost_equal(
             batch_noise,
@@ -147,6 +147,13 @@ def match_background_noise(blend_images):
             err_msg="Did not get desired mean pixel values of blend images",
         )
 
+    def test_basic_sampling(self):
+        sampling_function = btk.sampling_functions.BasicSampling()
+        draw_generator = get_draw_generator(
+            fixed_parameters=True, sampling_function=sampling_function
+        )
+        next(draw_generator)
+
     @patch("btk.plot_utils.plt.show")
     def test_default(self, mock_show):
         default_draw_generator = get_draw_generator(fixed_parameters=True)
@@ -162,13 +169,6 @@ def test_default(self, mock_show):
             len(draw_output["blend_list"][3]) < 3
         ), "Default max_number should \
             generate 2 or 1 galaxies per blend."
-        self.match_blend_images_default(draw_output["blend_images"])
-        self.match_isolated_images_default(draw_output["isolated_images"])
         self.match_background_noise(draw_output["blend_images"])
-
-    def test_basic_sampling(self):
-        sampling_function = btk.sampling_functions.BasicSampling()
-        draw_generator = get_draw_generator(
-            fixed_parameters=True, sampling_function=sampling_function
-        )
-        draw_output = next(draw_generator)  # noqa: F841
+        self.match_isolated_images_default(draw_output["isolated_images"])
+        self.match_blend_images_default(draw_output["blend_images"])
diff --git a/tests/test_error_cases.py b/tests/test_error_cases.py
index ae43b7f9f..e7a7a2b10 100644
--- a/tests/test_error_cases.py
+++ b/tests/test_error_cases.py
@@ -1,5 +1,6 @@
 import pytest
 from conftest import data_dir
+from galcheat.filter import Filter
 
 from btk.catalog import CatsimCatalog
 from btk.catalog import CosmosCatalog
@@ -9,8 +10,8 @@
 from btk.draw_blends import SourceNotVisible
 from btk.sampling_functions import DefaultSampling
 from btk.sampling_functions import SamplingFunction
-from btk.survey import Filter
-from btk.survey import get_psf
+from btk.survey import get_default_psf
+from btk.survey import get_default_psf_with_galcheat_info
 from btk.survey import get_psf_from_file
 from btk.survey import get_surveys
 
@@ -50,7 +51,7 @@ def compatible_catalogs(self):
         draw_generator = CatsimGenerator(
             catalog,
             sampling_function,
-            get_surveys("Rubin"),
+            get_surveys("LSST"),
             stamp_size=stamp_size,
             batch_size=batch_size,
             cpus=cpus,
@@ -81,7 +82,7 @@ def compatible_catalogs(self):
         draw_generator = CatsimGenerator(
             catalog,
             sampling_function,
-            get_surveys("Rubin"),
+            get_surveys("LSST"),
             stamp_size=stamp_size,
             batch_size=batch_size,
             cpus=cpus,
@@ -117,7 +118,7 @@ def compatible_catalogs(self):
         draw_generator = CatsimGenerator(
             catalog,
             sampling_function,
-            get_surveys("Rubin"),
+            get_surveys("LSST"),
             stamp_size=stamp_size,
             batch_size=batch_size,
             cpus=cpus,
@@ -129,24 +130,21 @@ def compatible_catalogs(self):
 
 
 def test_source_not_visible():
-    filt = Filter(
-        name="u",
-        psf=get_psf(
-            mirror_diameter=8.36,
-            effective_area=32.4,
-            filt_wavelength=3592.13,
-            fwhm=0.859,
-        ),
-        sky_brightness=22.9,
-        exp_time=1680,
-        zeropoint=9.16,
-        extinction=0.451,
+    survey = get_surveys("LSST")
+    filt = Filter.from_dict(
+        dict(
+            name="u",
+            psf_fwhm=0.859,
+            zeropoint=9.16,
+            sky_brightness=22.9,
+            exposure_time=1680,
+            effective_wavelength=3592.13,
+        )
     )
+    filt.psf = get_default_psf_with_galcheat_info(survey, filt)
     catalog = CatsimCatalog.from_file(CATALOG_PATH)
     with pytest.raises(SourceNotVisible):
-        gal = get_catsim_galaxy(  # noqa: F841
-            catalog.table[0], filt, get_surveys("Rubin"), True, True, True
-        )
+        get_catsim_galaxy(catalog.table[0], filt, survey, True, True, True)
 
 
 def test_survey_not_list():
@@ -167,18 +165,18 @@ def test_survey_not_list():
             cpus=cpus,
             add_noise=add_noise,
         )
-        draw_output = next(draw_generator)  # noqa: F841
+        next(draw_generator)
 
 
 def test_psf():
-    get_psf(
+    get_default_psf(
         mirror_diameter=8.36,
         effective_area=32.4,
         filt_wavelength=7528.51,
         fwhm=0.748,
         atmospheric_model="Moffat",
     )
-    get_psf(
+    get_default_psf(
         mirror_diameter=8.36,
         effective_area=32.4,
         filt_wavelength=7528.51,
@@ -186,7 +184,7 @@ def test_psf():
         atmospheric_model=None,
     )
     with pytest.raises(NotImplementedError) as excinfo:
-        get_psf(
+        get_default_psf(
             mirror_diameter=8.36,
             effective_area=32.4,
             filt_wavelength=7528.51,
@@ -197,12 +195,12 @@ def test_psf():
     assert "atmospheric model request" in str(excinfo.value)
 
     with pytest.raises(RuntimeError) as excinfo:
-        get_psf(mirror_diameter=1, effective_area=4, filt_wavelength=7528.51, fwhm=0.748)
+        get_default_psf(mirror_diameter=1, effective_area=4, filt_wavelength=7528.51, fwhm=0.748)
 
     assert "Incompatible effective-area and mirror-diameter values." in str(excinfo.value)
 
     with pytest.raises(RuntimeError) as excinfo:
-        get_psf(
+        get_default_psf(
             mirror_diameter=0,
             effective_area=0,
             filt_wavelength=7528.51,
@@ -214,10 +212,10 @@ def test_psf():
         excinfo.value
     )
 
-    get_psf(mirror_diameter=0, effective_area=0, filt_wavelength=7528.51, fwhm=0.748)
+    get_default_psf(mirror_diameter=0, effective_area=0, filt_wavelength=7528.51, fwhm=0.748)
 
-    get_psf_from_file("tests/example_psf", get_surveys("Rubin"))
-    get_psf_from_file("tests/multi_psf", get_surveys("Rubin"))
+    get_psf_from_file("tests/example_psf", get_surveys("LSST"))
+    get_psf_from_file("tests/multi_psf", get_surveys("LSST"))
     # The case where the folder is empty cannot be tested as you cannot add an empty folder to git
 
 
@@ -234,7 +232,7 @@ def test_incompatible_catalogs():
         draw_generator = CosmosGenerator(  # noqa: F841
             catalog,
             sampling_function,
-            get_surveys("Rubin"),
+            get_surveys("LSST"),
             stamp_size=stamp_size,
             batch_size=batch_size,
             cpus=cpus,
@@ -242,10 +240,10 @@ def test_incompatible_catalogs():
         )
     with pytest.raises(ValueError):
         # Missing filter
-        draw_generator = CatsimGenerator(  # noqa: F841
+        CatsimGenerator(
             catalog,
             sampling_function,
-            get_surveys("HST"),
+            get_surveys("COSMOS"),
             stamp_size=stamp_size,
             batch_size=batch_size,
             cpus=cpus,
@@ -254,10 +252,10 @@ def test_incompatible_catalogs():
 
     catalog = CosmosCatalog.from_file(COSMOS_CATALOG_PATHS, exclusion_level="none")
     with pytest.raises(ValueError):
-        draw_generator = CatsimGenerator(  # noqa: F841
+        CatsimGenerator(
             catalog,
             sampling_function,
-            get_surveys("Rubin"),
+            get_surveys("LSST"),
             stamp_size=stamp_size,
             batch_size=batch_size,
             cpus=cpus,
diff --git a/tests/test_group_sampling.py b/tests/test_group_sampling.py
index a5ae2d2f6..9676c5203 100644
--- a/tests/test_group_sampling.py
+++ b/tests/test_group_sampling.py
@@ -10,13 +10,13 @@
 
 
 def get_group_sampling_draw_generator(batch_size=3):
-    """Returns draw generator with group sampling function"""
+    """Returns draw generator with group sampling function."""
     wld_catalog_name = data_dir / "sample_group_catalog.fits"
     catalog_name = data_dir / "sample_group_input_catalog.fits"
 
     max_number = 10
     stamp_size = 24
-    survey = get_surveys("Rubin")
+    survey = get_surveys("LSST")
     pixel_scale = 0.2
     shift = [0.8, -0.7]
     catalog = CatsimCatalog.from_file(catalog_name)
@@ -30,7 +30,7 @@ def get_group_sampling_draw_generator(batch_size=3):
 
 
 def test_group_sampling():
-    """Test blends drawn with group sampling function"""
+    """Test blends drawn with group sampling function."""
     draw_blend_generator = get_group_sampling_draw_generator()
     output = next(draw_blend_generator)
     blend_images = output["blend_images"]
diff --git a/tests/test_main.py b/tests/test_main.py
index 62d9987c2..37c3581c7 100644
--- a/tests/test_main.py
+++ b/tests/test_main.py
@@ -19,9 +19,9 @@ def test_main():
     main(cfg)
 
     # test survey CLI
-    cfg = get_cfg(overrides={"surveys": "Rubin"})
+    cfg = get_cfg(overrides={"surveys": ["LSST"]})
     main(cfg)
-    cfg = get_cfg(overrides={"surveys": ["Rubin", "DES"], "meas_band_num": [0, 0]})
+    cfg = get_cfg(overrides={"surveys": ["LSST", "DES"], "meas_band_num": [0, 0]})
     main(cfg)
 
 
diff --git a/tests/test_measure.py b/tests/test_measure.py
index 35ae48dc7..2b08a5a35 100644
--- a/tests/test_measure.py
+++ b/tests/test_measure.py
@@ -16,7 +16,7 @@ def get_meas_results(meas_function, cpus=1, measure_kwargs=None):
 
     catalog_name = data_dir / "sample_input_catalog.fits"
     stamp_size = 24
-    survey = get_surveys("Rubin")
+    survey = get_surveys("LSST")
     shifts = [[-0.3, 1.2]]
     indexes = [[1]]
     catalog = CatsimCatalog.from_file(catalog_name)
diff --git a/tests/test_metrics.py b/tests/test_metrics.py
index 7343abbc7..60f03b38c 100644
--- a/tests/test_metrics.py
+++ b/tests/test_metrics.py
@@ -27,7 +27,7 @@ def get_metrics_generator(
     """Returns draw generator with group sampling function"""
     catalog_name = "data/sample_input_catalog.fits"
     stamp_size = 24
-    survey = get_surveys("Rubin")
+    survey = get_surveys("LSST")
     shifts = [
         [[-0.3, 1.2], [-1.6, -1.7]],
         [[-1.1, -2.1], [1.4, 1.8]],
@@ -105,7 +105,7 @@ def test_measure_kwargs(mock_show):
     )
     _, _, results = next(metrics_generator)
     average_precision = auc(results, "sep_measure", 2, plot=True)
-    assert average_precision == 0.4375
+    assert average_precision == 0.5
 
 
 def test_detection_eff_matrix():
diff --git a/tests/test_mr.py b/tests/test_mr.py
index a34c1ee24..fbd214c62 100644
--- a/tests/test_mr.py
+++ b/tests/test_mr.py
@@ -21,7 +21,7 @@ def test_multiresolution(mock_show):
     batch_size = 8
     cpus = 1
     add_noise = "all"
-    surveys = get_surveys(["Rubin", "HSC"])
+    surveys = get_surveys(["LSST", "HSC"])
 
     catalog = CatsimCatalog.from_file(catalog_name)
     sampling_function = DefaultSampling(stamp_size=stamp_size)
@@ -41,22 +41,22 @@ def test_multiresolution(mock_show):
     )
     blend_results, measure_results, metrics_results = next(metrics_generator)
 
-    assert "Rubin" in blend_results["blend_list"].keys(), "Both surveys get well defined outputs"
+    assert "LSST" in blend_results["blend_list"].keys(), "Both surveys get well defined outputs"
     assert "HSC" in blend_results["blend_list"].keys(), "Both surveys get well defined outputs"
-    assert blend_results["blend_images"]["Rubin"][0].shape[-1] == int(
+    assert blend_results["blend_images"]["LSST"][0].shape[-1] == int(
         24.0 / 0.2
-    ), "Rubin survey should have a pixel scale of 0.2"
+    ), "LSST survey should have a pixel scale of 0.2"
     assert blend_results["blend_images"]["HSC"][0].shape[-1] == int(
-        24.0 / 0.167
+        24.0 / 0.168
     ), "HSC survey should have a pixel scale of 0.167"
     assert (
-        "Rubin" in measure_results["catalog"]["sep_measure"].keys()
+        "LSST" in measure_results["catalog"]["sep_measure"].keys()
     ), "Both surveys get well defined outputs"
     assert (
         "HSC" in measure_results["catalog"]["sep_measure"].keys()
     ), "Both surveys get well defined outputs"
     assert (
-        "Rubin" in metrics_results["galaxy_summary"]["sep_measure"].keys()
+        "LSST" in metrics_results["galaxy_summary"]["sep_measure"].keys()
     ), "Both surveys get well defined outputs"
     assert (
         "HSC" in metrics_results["galaxy_summary"]["sep_measure"].keys()
diff --git a/tests/test_save.py b/tests/test_save.py
index 513ce0b7c..cfc342ae3 100644
--- a/tests/test_save.py
+++ b/tests/test_save.py
@@ -23,7 +23,7 @@ def test_save():
     draw_blend_generator = CatsimGenerator(
         catalog,
         sampling_function,
-        get_surveys("Rubin"),
+        get_surveys("LSST"),
         batch_size=batch_size,
         stamp_size=stamp_size,
         save_path=output_dir,
@@ -36,10 +36,10 @@ def test_save():
     )
     blend_results, measure_results, metrics_results = next(metrics_generator)
     blend_results2, measure_results2, metrics_results2 = load_all_results(
-        output_dir, ["Rubin"], ["sep_measure"], batch_size
+        output_dir, ["LSST"], ["sep_measure"], batch_size
     )
     np.testing.assert_array_equal(
-        blend_results["blend_images"], blend_results2["blend_images"]["Rubin"]
+        blend_results["blend_images"], blend_results2["blend_images"]["LSST"]
     )
     np.testing.assert_array_equal(
         measure_results["segmentation"]["sep_measure"][0],