Update pennylane requirement from ~=0.35.1 to ~=0.36.0

[dependabot]

Updates the requirements on pennylane to permit the latest version.

Release notes

Sourced from pennylane's releases.

Release 0.36.0

• This version of PennyLane lays the foundation for estimating the total error in a quantum circuit from the combination of individual gate errors. [(#5154)](PennyLaneAI/pennylane#5154) [(#5464)](PennyLaneAI/pennylane#5464) [(#5465)](PennyLaneAI/pennylane#5465) [(#5278)](PennyLaneAI/pennylane#5278) [(#5384)](PennyLaneAI/pennylane#5384)

Two new user-facing classes enable calculating and propagating gate errors in PennyLane:

• qml.resource.SpectralNormError: the spectral norm error is defined as the distance, in spectral norm, between the true unitary we intend to apply and the approximate unitary that is actually applied.

• qml.resource.ErrorOperation: a base class that inherits from qml.operation.Operation and represents quantum operations which carry some form of algorithmic error.

  SpectralNormError can be used for back-of-the-envelope type calculations like obtaining the spectral norm error between two unitaries via get_error:

  import pennylane as qml 
  from pennylane.resource import ErrorOperation, SpectralNormError
  intended_op = qml.RY(0.40, 0)
  actual_op = qml.RY(0.41, 0) # angle of rotation is slightly off

  >>> SpectralNormError.get_error(intended_op, actual_op) 
  0.004999994791668309 

  SpectralNormError is also a key tool to specify errors in larger quantum circuits:

• For operations representing a major building block of an algorithm, we can create a custom operation that inherits from ErrorOperation. This child class must override the error method and should return a SpectralNormError instance:

  class MyErrorOperation(ErrorOperation):
  def init(self, error_val, wires):
  self.error_val = error_val
  super().init(wires=wires)
  def error(self):
  return SpectralNormError(self.error_val)

  In this toy example, MyErrorOperation introduces an arbitrary SpectralNormError when called in a QNode. It does not require a decomposition or matrix representation when used with null.qubit (suggested for use with resource and error estimation since circuit executions are not required to calculate resources or errors).

  dev = qml.device("null.qubit")
  @​qml.qnode(dev)
  def circuit():

... (truncated)

Commits

• 6d80d25 Update upload.yml to use codecov token (#5662)
• 195b230 Update minimum compiler version (#5645)
• 4879a61 Fix error raised when taking dot of a single Tensor (#5651)
• 2522e58 [Bugfix] Hamiltonian is rendered in top level docs (#5640)
• 0aa8a68 Release notes v0.36 — Error estimation suggestion (#5641)
• f964d44 lightning qubit uses parameter shift if metric tensor applied (#5624)
• 76edb60 Minor fixes for 0.36 release (#5633)
• 5a66aaa Fix links in news/new_opmath.rst (#5636)
• 287cb54 Updates to v0.36 release notes - part 2 (#5573)
• 88e87f3 Docs reflection (#5605)
• Additional commits viewable in compare view

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[codecov]

Codecov Report

All modified and coverable lines are covered by tests ✅

Project coverage is 98.22%. Comparing base (3a11517) to head (98b4984).

Additional details and impacted files

@@           Coverage Diff           @@
##             main    #2349   +/-   ##
=======================================
  Coverage   98.22%   98.22%           
=======================================
  Files          87       87           
  Lines        4056     4056           
=======================================
  Hits         3984     3984           
  Misses         72       72           

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