Docs update

README.rst

@@ -70,7 +70,7 @@ The easiest way to install Tangelo in your local environment. We recommend upgra
 
 .. code-block::
 
-   python -m pip install -–upgrade pip.
+   python -m pip install --upgrade pip.
    pip install tangelo-gc
 
 
@@ -184,7 +184,7 @@ find and run all tests (assuming you are in the ``tangelo`` subfolder that conta
 Contributions
 -------------
 
-Thank you very much for considering contributing to this project; we’d love to have you on board !
+Thank you very much for considering contributing to this project; we'd love to have you on board !
 You do not need to be a seasoned software developer or expert in your field to make contributions to this project: it will take various kinds of people and backgrounds to tackle the challenges that await us.
 
 However we need some guidelines and processes to ensure that we build something of quality for the community. We describe them in the `contributions <./CONTRIBUTIONS.rst>`_ file.

docs/source/conf.py

@@ -18,11 +18,11 @@
 # -- Project information -----------------------------------------------------
 
 project = 'tangelo'
-copyright = '2022 Good Chemistry Company'
+copyright = '2023 Good Chemistry Company'
 author = 'Valentin senicourt, Alexandre Fleury, Ryan Day, James Brown'
 
 # The full version, including alpha/beta/rc tags
-release = '0.3.1'
+release = '0.3.4'
 
 
 # -- General configuration ---------------------------------------------------

examples/overview_endtoend.ipynb

@@ -257,7 +257,7 @@
    "source": [
     "### Problem decomposition to reduce resource requirements <a class=\"anchor\" id=\"51\"></a>\n",
     "\n",
-    "Problem decomposition is an approach that can be investigated in order to reduce resource requirements, attempting to find the solution to the initial problem by solving a collection of smaller subproblems. This packages offers several problem decomposition techniques, such as DMET, which is the one we explore here (see [DMET](dmet.ipynb) and [ONIOM](problem_decomposition_oniom.ipynb) notebooks for more details).\n",
+    "Problem decomposition is an approach that can be investigated in order to reduce resource requirements, attempting to find the solution to the initial problem by solving a collection of smaller subproblems. This packages offers several problem decomposition techniques, such as DMET, which is the one we explore here (see [DMET](dmet.ipynb) and [ONIOM](oniom.ipynb) notebooks for more details).\n",
     "\n",
     "We decompose more and more aggressively to show the impact on resource requirements, going down to fragments of size one atom. Since all fragments play a identical role in our case, for symmetry reasons, we only focus on one of them and treat the others with CCSD to simplify output and calculations. \n",
     "\n",

tangelo/algorithms/variational/adapt_vqe_solver.py

@@ -135,7 +135,7 @@ def build(self):
         algorithm.
         """
 
-        # Building molecule data with a pyscf molecule.
+        # Building molecule data.
         if self.molecule:
 
             self.n_spinorbitals = self.molecule.n_active_sos

tangelo/toolboxes/circuits/qsp.py

@@ -46,7 +46,7 @@ def ham_sim_phases(tau: float, eps: float = 1.e-2, n_attempts: int = 10, method:
     try:
         import pyqsp
     except ModuleNotFoundError:
-        raise ModuleNotFoundError("pyqsp package is required to calculate QSP time-evolution phases using 'lauren' or 'tf' method.")
+        raise ModuleNotFoundError("pyqsp package is required to calculate QSP time-evolution phases using 'laurent' or 'tf' method.")
 
     from pyqsp import angle_sequence
     from pyqsp.angle_sequence import AngleFindingError

tangelo/toolboxes/qubit_mappings/hcb.py

@@ -65,7 +65,7 @@ def boson_to_qubit_mapping(bos_op):
     annihilation operators.
 
     In short, every creation operator b^{\dagger} (resp. annihilation b) are
-    mapped to X+iY strings (resp. X-iY), where X and Y are referring to the
+    mapped to X-iY strings (resp. X+iY), where X and Y are referring to the
     Pauli matrices.
 
     Args: