Add noisy channel: thermal relaxation

[alejomonbar]

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Context:
Adding a new noisy channel which gives the thermal relaxation channel as part of the #971 issue. I got the information from the supplementary of Quantum classifier with tailored quantum kernel. I still need to figure out how to get the second case when T2 > T1.
Description of the Change:

Benefits:

Possible Drawbacks:

Related GitHub Issues:

[codecov]

Codecov Report

Merging #1766 (22ef764) into master (085833d) will increase coverage by 0.00%.
The diff coverage is 100.00%.

@@           Coverage Diff           @@
##           master    #1766   +/-   ##
=======================================
  Coverage   98.98%   98.98%           
=======================================
  Files         218      218           
  Lines       16375    16428   +53     
=======================================
+ Hits        16208    16261   +53     
  Misses        167      167           

Impacted Files	Coverage Δ
pennylane/devices/default_mixed.py	100.00% <ø> (ø)
pennylane/ops/channel.py	100.00% <100.00%> (ø)

---

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[josh146]

Thanks @alejomonbar for this nice contribution! 🙂 Let us know if you have any questions, or when this PR is ready for review, and someone from the team will be on hand to help.

[alejomonbar]

Thanks @alejomonbar for this nice contribution! 🙂 Let us know if you have any questions, or when this PR is ready for review, and someone from the team will be on hand to help.

Thank you @josh146. Indeed, I have some questions. For the case of T2 > T1, the usual approach is to map the Choi matrix into a Kraus operator. I'm wondering if I should create that mapping function as it is made for example in Qiskit and if that's the case, where!

[rmoyard]

Thanks @alejomonbar for this nice contribution! 🙂 Let us know if you have any questions, or when this PR is ready for review, and someone from the team will be on hand to help.

Thank you @josh146. Indeed, I have some questions. For the case of T2 > T1, the usual approach is to map the Choi matrix into a Kraus operator. I'm wondering if I should create that mapping function as it is made for example in Qiskit and if that's the case, where!

Thank you for opening this PR, I'll check the different documents and come back to you asap for the case T2 > T1!

[rmoyard]

@alejomonbar I checked the different documents about thermal relaxation. As PennyLane has no Choi representation of quantum channel, we indeed need to construct the kraus matrices from the Choi matrix given in the paper. Therefore for the case where dephasing is more prevalent than relaxation (T2>T1), you will need indeed need this transformation. For the moment you can create this function directly in channel.py and work there. I will check if a better location is needed.

Thank you again for your contribution and feel free to ask any question. Let me know when the PR will be ready for review!

[alejomonbar]

@alejomonbar I checked the different documents about thermal relaxation. As PennyLane has no Choi representation of quantum channel, we indeed need to construct the kraus matrices from the Choi matrix given in the paper. Therefore for the case where dephasing is more prevalent than relaxation (T2>T1), you will need indeed need this transformation. For the moment you can create this function directly in channel.py and work there. I will check if a better location is needed.

Thank you again for your contribution and feel free to ask any question. Let me know when the PR will be ready for review!

Thank you, I will look at that and come back when I implement it!

[alejomonbar]

@antalszava I improve the code and now it gives results for both cases, T2 <= T1 and T2 > T1, the second case needs the Choi-matrix eigenvalues and eigenvectors, I put the parametric representation of those values. Let me know if you have any comments. Also, I added a test for the new ThermalRelaxation error.

[rmoyard]

@antalszava I improve the code and now it gives results for both cases, T2 <= T1 and T2 > T1, the second case needs the Choi-matrix eigenvalues and eigenvectors, I put the parametric representation of those values. Let me know if you have any comments. Also, I added a test for the new ThermalRelaxation error.

@alejomonbar Thank you, I'll give a look to the PR today and will give some advice!

[rmoyard]

Thank you for the contribution, before I can give a full review you have different points to work on:

1. Codefactor: in the folder channel.py minor things like trailinng white spaces and too many statements should be solved easily.
2. You can pip install black and run black -l 100 your_file.py on all the changed files.
3. For docstrings and documentation, there probably some small errors of formatting.
4. Some tests are failing, like test_kraus_matrices_sum_identitydid you check it locally? Maybe there is small mistake in the Kraus operators or you need to adapt the test for the case. Same for the new tests are failing as well, do they pass locally for you?

[alejomonbar]

Thank you for the contribution, before I can give a full review you have different points to work on:

1. Codefactor: in the folder channel.py minor things like trailinng white spaces and too many statements should be solved easily.
2. You can pip install black and run black -l 100 your_file.py on all the changed files.
3. For docstrings and documentation, there probably some small errors of formatting.
4. Some tests are failing, like test_kraus_matrices_sum_identitydid you check it locally? Maybe there is small mistake in the Kraus operators or you need to adapt the test for the case. Same for the new tests are failing as well, do they pass locally for you?

Thank you @rmoyard , I tried it but I have a problem when trying to run the test I got the following message, ModuleNotFoundError:No module named 'autoray' and I installed it using pip install autoray, and looks like it is installed, but still, I got the same message.

[rmoyard]

Thank you for the contribution, before I can give a full review you have different points to work on:

1. Codefactor: in the folder channel.py minor things like trailinng white spaces and too many statements should be solved easily.
2. You can pip install black and run black -l 100 your_file.py on all the changed files.
3. For docstrings and documentation, there probably some small errors of formatting.
4. Some tests are failing, like test_kraus_matrices_sum_identitydid you check it locally? Maybe there is small mistake in the Kraus operators or you need to adapt the test for the case. Same for the new tests are failing as well, do they pass locally for you?

Thank you @rmoyard , I tried it but I have a problem when trying to run the test I got the following message, ModuleNotFoundError:No module named 'autoray' and I installed it using pip install autoray, and looks like it is installed, but still, I got the same message.

Does it appear in the environment if you write pip list?

[alejomonbar]

Thank you for the contribution, before I can give a full review you have different points to work on:

1. Codefactor: in the folder channel.py minor things like trailinng white spaces and too many statements should be solved easily.
2. You can pip install black and run black -l 100 your_file.py on all the changed files.
3. For docstrings and documentation, there probably some small errors of formatting.
4. Some tests are failing, like test_kraus_matrices_sum_identitydid you check it locally? Maybe there is small mistake in the Kraus operators or you need to adapt the test for the case. Same for the new tests are failing as well, do they pass locally for you?

Thank you @rmoyard , I tried it but I have a problem when trying to run the test I got the following message, ModuleNotFoundError:No module named 'autoray' and I installed it using pip install autoray, and looks like it is installed, but still, I got the same message.

Does it appear in the environment if you write pip list?

Yes, it does with version autoray 0.2.5

[rmoyard]

@alejomonbar Could you give me your system information? import pennylane as qml; qml.about()

[alejomonbar]

@alejomonbar Could you give me your system information? import pennylane as qml; qml.about()

No, I cannot import pennylane as qml, I got the same message ModuleNotFoundError: No module named 'autoray'

[alejomonbar]

@alejomonbar In the pennylane/devices/default_mixed.py file you can find a list of operations/channels and you have to add ThermalRelaxationError channel there!

@rmoyard Thank you. Now, all the tests pass, let me know if you have any questions about what I did

[rmoyard]

@alejomonbar You have to do multiple things to pass all the CI checks:

1. Codefactor: trailing whitespaces issues
2. Codefactor: unecessary else after return
3. Codecov: you need to add tests for line 557/559/561, basically just test that the error messages are raised.
4. Two issues with docstrings: /github/workspace/pennylane/ops/channel.py:docstring of pennylane.ops.channel.ThermalRelaxationError:48: WARNING: Unexpected indentation. /github/workspace/pennylane/ops/channel.py:docstring of pennylane.ops.channel.ThermalRelaxationError:60: WARNING: Definition list ends without a blank line;

[alejomonbar]

@alejomonbar You have to do multiple things to pass all the CI checks:

1. Codefactor: trailing whitespaces issues
2. Codefactor: unecessary else after return
3. Codecov: you need to add tests for line 557/559/561, basically just test that the error messages are raised.
4. Two issues with docstrings: /github/workspace/pennylane/ops/channel.py:docstring of pennylane.ops.channel.ThermalRelaxationError:48: WARNING: Unexpected indentation. /github/workspace/pennylane/ops/channel.py:docstring of pennylane.ops.channel.ThermalRelaxationError:60: WARNING: Definition list ends without a blank line;

@rmoyard I have problems with make docs, maybe that's why I cannot pass this test. When I try to run it, I get the following message AttributeError: 'Sphinx' object has no attribute 'add_stylesheet'. In any case, I tried to follow your comments.

[rmoyard]

@alejomonbar If you solve the two doc issues mentioned in my previous comment (line 48 unexpected indentation and line 60 blank line), the doc tests should pass.

[rmoyard]

@alejomonbar Thank you for the work, I'll give a full review asap!

[rmoyard]

Thanks @alejomonbar, it looks good overall. I've left some comments, let me know if you have some questions.

[rmoyard]

It looks good to me, last comments for Code factor errors and also a dosctring. After that it should be all good 💯