Pyqrack

For CPU-based and OpenCL-based back ends, a minor improvement has been made in the algorithm of MAll(), such that single-shot simulation might see a small average-case performance benefit.

Also, Qrack's intention was always that internal "epsilon" for n bit precision was 2^-(n+1); these values were accidentally set much lower. (The change has been tested with the "normalization" features of Qrack, which are basically all this change should affect, and it works.)

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QTensorNetwork` has been changed from asynchronous (for gate dispatch without output) to synchronous (with threading for `QCircuit`, but with usual `QInterface` threading). This should fix segmentation faults with no major performance drawbacks.

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The thread safety of `QCircuit` asynchronous dispatch (as in `QTensorNetwork`) has been debugged. Also, `GetUnitaryFidelity()` has been patched through `QTensorNetwork` from an underlying `QUnit` simulator instance.

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Next week, the development team will be presenting at IEEE Quantum Week 2023! This patch just brings `QTensorNetwork` more "neurotically" into line with Qrack code standards, as there will be no opportunity to publish another release until after the conference. (The release content is minor, but it does more closely follow our standards.)

(See you at IEEE Quantum Week 2023! Qrack is submission "254" in the "QSYS" track, presented on Thursday morning!)

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A new layer called `QTensorNetwork` has been added at "top" of the "optimal stack." This layer represents quantum state as a vector of sub-circuits and vector of measurement layers. The circuits are optimized "just-in-time" as the state evolves. When "physically observable" output values are requested by the user, they are calculated with recourse to the original default "layer stack" of simulators. Depending on circuit width, observable outputs might be calculated on the "past light cone" of single qubits.

`QTensorNetwork` does not implement `Compose()`, `Decompose()`, `Dispose()`, or the `QAlu` and `QParity` interfaces. (Some ALU operations are still available, through "decompositions" in `QInterface`. "Schmidt decomposition" API is not necessary internally for optimization in this case, since `QUnit` resides "below" `QTensorNetwork` in the suggested simulation layer stack.)

A follow-up release will implement NVIDIA's `cuTensorNet` API in CUDA builds of `QTensorNetwork`.

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**Full Changelog**: https://github.com/unitaryfund/pyqrack/compare/v1.20.10...v1.21.0

The changes in this release bring Qrack into line with its code standards. `constexpr`, a feature of C++11 and forward, is used to declare unitary 2x2 matrices known at compile time. Headers have also been reviewed, to fix any bugs and reduce redundant `include` statements.

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