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Rewrites the fidelity function for clarity #226

Merged
merged 7 commits into from
Feb 13, 2021
Merged

Rewrites the fidelity function for clarity #226

merged 7 commits into from
Feb 13, 2021

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nquesada
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The fidelity function in quantum/gaussian_checks.py is rewritten to add clarity and also a reference and test are added.
This should clarify the (non-) bug posited in #223

@nquesada nquesada requested a review from antalszava February 12, 2021 15:29
@nquesada nquesada mentioned this pull request Feb 12, 2021
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@nquesada nquesada requested review from thisac and removed request for antalszava February 12, 2021 20:00
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codecov bot commented Feb 12, 2021

Codecov Report

Merging #226 (bf6d6c4) into master (49de978) will not change coverage.
The diff coverage is 100.00%.

@@            Coverage Diff            @@
##            master      #226   +/-   ##
=========================================
  Coverage   100.00%   100.00%           
=========================================
  Files           20        20           
  Lines         1191      1188    -3     
=========================================
- Hits          1191      1188    -3     
Impacted Files Coverage Δ
thewalrus/quantum/gaussian_checks.py 100.00% <100.00%> (ø)

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Nice addition @nquesada. Was easy and clear to follow. Just a few minor comments on variable names and code, that you might want to address.

sigma2 = cov2 / hbar
deltar = (mu1 - mu2) / np.sqrt(hbar)

Omega = sympmat(n0 // 2) # The symplectic matrix
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I would recommend using lowercase for these variables, since capitalization would be used for classes, and thus get highlighted differently. Any reason for changing to capitalized versions?

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I knew this would come up! So I am just trying to follow the paper and LaTeX naming, i.e., Omega is meant to be $\Omega$. The Walrus has no classes.

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But if you feel strongly about this I am happy to change it.

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Sorry about this. It's a case of programming vs. academic conventions. I would say it's still better to keep lowercase, and follow Python syntax rules here. Either having it as omega or even big_omega (but I think the former is probably better).

thewalrus/quantum/gaussian_checks.py Outdated Show resolved Hide resolved
thewalrus/quantum/gaussian_checks.py Outdated Show resolved Hide resolved
Comment on lines 150 to 151
f = np.sqrt(np.linalg.det(Sigma_inv) * np.linalg.det(det_arg)) * np.exp(
-0.5 * deltar @ Sigma_inv @ deltar
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No transpose on the first deltar? It seems like the paper writes it np.exp(-0.5 * deltar.T @ Sigma_inv @ deltar), but maybe that's the same in this case. 🤔

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It makes no difference, although it could be added. If you do a @ b and a and b are 1D arrays the numpy is smart enough to know that what you want is mathematically speaking a^T \cdot b

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Fair enough. That's what I suspected, just wanted to clarify. Thanks!

Comment on lines +110 to +111
The actual implementation used here corresponds to the *square* of Eq. 96 of
`'Gaussian states and operations - a quick reference', Brask <https://arxiv.org/abs/2102.05748>`_.
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💯

nquesada and others added 3 commits February 12, 2021 15:54
Co-authored-by: Theodor <theodor@xanadu.ai>
Co-authored-by: Theodor <theodor@xanadu.ai>
@nquesada nquesada merged commit 706e38d into master Feb 13, 2021
@nquesada nquesada deleted the fidelity branch February 13, 2021 01:39
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2 participants