SX gate implementation for lightning.qubit

[tomlqc]

Important Note

⚠️ This issue is part of an internal assignment and not meant for external contributors

Context

PennyLane has support for many quantum gates natively at the Python level, but often we may require faster implementations. lightning.qubit is a fully C++ backed simulator library that can be called from PennyLane, with optimal implementations of many highly-used gates. Implementing more optimized gates in the C++ backend would boost the performance of this simulator.

Requirements

The SX gate has to be implemented in the lightning.qubit C++ backend. For more information about the SX gate, please refer to PennyLane doc.

• Add a method for the SX gate to the lightning_qubit/gates/cpu_kernels/GateImplementationsLM.hpp file. Update the source file accordingly.

• Add a GateOpToMemberFuncPtr struct in lightning_qubit/gates/OpToMemberFuncPtr.hpp similar to the struct added for Hadamard.

• Add C++ tests for the SX gate to Test_GateImplementations_Nonparam.cpp. You can follow the same style used for other gates in this test file.

• Explain how the SX C++ kernel can be updated to execute concurrently using C++ threads or OpenMP (you may look at the other gates implementation). What can you say about the performance factor here?

• Update the list of supported gates in pennylane_lightning/lightning_qubit/lightning_qubit.py.

• Add Python tests in tests/test_gates.py to check the correctness of this gate against PennyLane qml.SX. (you may reuse existing tests, but add some if coverage requires it)

• Create a pull-request in the PennyLane Lightning repository and ensure to complete all the necessary steps outlined for creating the PR before marking it ready for review.

Feel free to ask any questions or raise any concerns regarding the issue. We'll be happy to discuss with you!