Tensorflow-quantum

No functional changes. Fix for internal build systems.

New Features / Improvements

`tfq.math` now contains high performance fixed bond dimension MPS simulation to sample, compute expectation values and compute expectation values via sampling from 1D non periodic circuits.
`tfq.math.mps_1d_expectation`
`tfq.math.mps_1d_sample`
`tfq.math.mps_1d_sampled_expectation`
These are fully parallelized and based on new qsim MPS functionality found here: https://github.com/quantumlib/qsim/blob/d063d427d1f55d580416259233ce9c64037c00a0/lib/mps_simulator.h#L1

Instances of `cirq.LineQubit` are now supported when serializing circuits and paulisum objects.

`tfq.optimizers` now contains an implementation of SPSA optimization: https://www.jhuapl.edu/spsa/
`tfq.optimizers.spsa_minimize`.
Other

Minor CPU performance boosts from qsim upgrades.
TFQ now relies on TensorFlow version 2.7.0.
New tutorials that can be found on website.

Full commit list:
* Bump working version to 0.6.0 by MichaelBroughton in https://github.com/tensorflow/quantum/pull/570
* Remove -q flag from pip install in notebooks. by MichaelBroughton in https://github.com/tensorflow/quantum/pull/575
* Quantum reinforcement learning tutorial by sjerbi in https://github.com/tensorflow/quantum/pull/541
* Removed fixed grpcio version. by MichaelBroughton in https://github.com/tensorflow/quantum/pull/584
* Cleaned up latex and docs rendering. by MichaelBroughton in https://github.com/tensorflow/quantum/pull/585
* Added new noise tutorial. by MichaelBroughton in https://github.com/tensorflow/quantum/pull/582
* Upgraded sympy to v1.8. by MichaelBroughton in https://github.com/tensorflow/quantum/pull/591
* Updated tensorflow.org/quantum landing cards. by MichaelBroughton in https://github.com/tensorflow/quantum/pull/593
* Pulled out Cirq proto dependency. by MichaelBroughton in https://github.com/tensorflow/quantum/pull/590
* Ensure gradient of tf.math.fidelity remains float32 when autographed. by MichaelBroughton in https://github.com/tensorflow/quantum/pull/596
* Fix internal build error by jaeyoo in https://github.com/tensorflow/quantum/pull/600
* Upgrade to TF2.5.1 by jaeyoo in https://github.com/tensorflow/quantum/pull/612
* Upgrade CI to 18.04 to follow TF 2.5.0 by MichaelBroughton in https://github.com/tensorflow/quantum/pull/613
* Update concepts.md by MichaelBroughton in https://github.com/tensorflow/quantum/pull/626
* Update design.md by MichaelBroughton in https://github.com/tensorflow/quantum/pull/627
* importlib.reload(pkg_resources) for tensorflow.org by MarkDaoust in https://github.com/tensorflow/quantum/pull/631
* Fix QRL tutorial by sjerbi in https://github.com/tensorflow/quantum/pull/634
* Add cirq.LineQubit support to op_deserializer.py. by MichaelBroughton in https://github.com/tensorflow/quantum/pull/633
* Add support for cirq.LineQubit to op_serializer.py by MichaelBroughton in https://github.com/tensorflow/quantum/pull/632
* Increment requirement to Cirq to 0.13.1 by tonybruguier in https://github.com/tensorflow/quantum/pull/621
* Add support for LineQubit to serializer.py by MichaelBroughton in https://github.com/tensorflow/quantum/pull/637
* Fix auditwheel script by jaeyoo in https://github.com/tensorflow/quantum/pull/639
* Finish support for LineQubit everywhere. by MichaelBroughton in https://github.com/tensorflow/quantum/pull/641
* Implement serialization logic for ProjectorSums. by tonybruguier in https://github.com/tensorflow/quantum/pull/623
* Run format_all script by tonybruguier in https://github.com/tensorflow/quantum/pull/644
* change import to cirq_google from cirq.google by tonybruguier in https://github.com/tensorflow/quantum/pull/643
* Upgrade to TF 2.7.0. by MichaelBroughton in https://github.com/tensorflow/quantum/pull/650
* Add `tfq.math.mps_1d_expectation` for 1D MPS by jaeyoo in https://github.com/tensorflow/quantum/pull/610
* update qsim to latest version. by MichaelBroughton in https://github.com/tensorflow/quantum/pull/651
* Add mps 1d Sample / SampledExpectation ops by jaeyoo in https://github.com/tensorflow/quantum/pull/654
* Add SPSA optimizer by lockwo in https://github.com/tensorflow/quantum/pull/653
* Update MPS docs by MichaelBroughton in https://github.com/tensorflow/quantum/pull/657
* Loosen cirq requirements in anticipation of release. by MichaelBroughton in https://github.com/tensorflow/quantum/pull/659
* constrain xticks in two plt figures by tbcdebug in https://github.com/tensorflow/quantum/pull/658

New Contributors
* sjerbi made their first contribution in https://github.com/tensorflow/quantum/pull/541
* tbcdebug made their first contribution in https://github.com/tensorflow/quantum/pull/658

**Full Changelog**: https://github.com/tensorflow/quantum/compare/v0.5.0...v0.6.0

Remove explicit and potentially problematic `grpcio==1.30.0` dependency, along with some docs cleanup.

TensorFlow Quantum 0.5.0 includes new features, bug fixes and minimal API changes.

**New Features/Improvements:**
Added support for Cirq gates that have arbitrary control via the `gate.controlled_by` function. (Gradient support as well)
Added `tfq.math.inner_product` gradient. This op will now provide a gradient via `tf.GradientTape`.
Added `tfq.math.fidelity` op and gradient. This op will now provide a gradient via `tf.GradientTape`.
Added support in `tfq.convert_to_tensor` for circuits containing any Cirq noise channel from [common_channels](https://github.com/quantumlib/Cirq/blob/master/cirq-core/cirq/ops/common_channels.py) .
Added `tfq.noise.expectation` op and support with existing Differentiators for noisy analytic expectation calculation. Noisy simulations done via monte-carlo/trajectory sampling.
Added `tfq.noise.samples` op to draw bitstring samples from noisy circuits.
Added `tfq.noise.sampled_expectation` op and support with existing Differentiators for sample based expectation calculation.
Introduced `get_gradient_circuits` interface method for differentiators for users wanting to define a custom Differentiator.
Updated `tfq.layers.Expectation`, `tfq.layers.Samples`, `tfq.layers.SampledExpectation` with `__init__` parameter `backend=noisy`, `backend='noiseless'` to support noisy circuits.
Added `tfq.layers.NoisyPQC` and `tfq.layers.NoisyControlledPQC` which are noisy equivalents of `tfq.layers.PQC` and `tfq.layers.ControlledPQC`.
New datasets available via `tfq.datasets`.
Improved stability and performance in distributed training with `MultiWorkerMirroredStrategy` and `ParameterServer`.

**Bug fixes**
Fixed an issue where backward passes done on expectation ops with empty input tensors would cause `SEGFAULT`.
Fixed inconsistent output shapes between some ops, when input was the empty tensor.
Fixed randomness sources used for sampling to use thread safe `philox_random` approaches from TF instead of `std::mt19937` from the standard library.
Removed parallel calls to custom Cirq simulators when using `backend != None` inside of any `tfq.layers`. This is to ensure compatibility with high performance remote simulators as well as when running on real devices.

**Breaking changes**
We now depend on `cirq==0.11.0` and `tensorflow==2.4.1`.

A big thanks to all of our contributors for this release:
zaqqwerty , jaeyoo , lamberta , MarkDaoust , MichaelBroughton , therooler , sjerbi, balopat , lockwo, gatorwatt .

TensorFlow Quantum Release 0.4.0 includes several new features, bug fixes and some breaking changes.

**New Features/Improvement**:
Added `tfq.datasets.tfi_chain` downloadable dataset.
Added `tfq.datasets.xxz_chain` downloadable dataset.
Performance improvement across all ops with improved parallelization in circuit parsing.
Improved `np.float32` and `np.float64` reliability when serializing circuits.
Updated circuit simulation parallelization scheme. When circuits are less than 25 qubits each unique circuit gets 1 thread. Otherwise all threads are used for each individual circuit.
Reduced memory overhead of `tfq.get_sampling_op()`.
Moved to depending on oss qsim (https://github.com/quantumlib/qsim).
Removed last of stray Eigen3 dependencies.
Added `tfq.enable_low_latency_op_mode` to block graph level parallelism (useful when hitting real devices or in memory/compute limited scenarios).
Added adjoint differentiation, capable of analytic differentiation with thousands of symbols and better runtime complexity than methods like SGDifferentiator and ParameterShift.
Added Rotosolve optimizer for use as a black box optimizer with quantum circuits.
Added `tfq.math` ops with the first op featured being `inner_product`.

**Bug Fixes**:
Fixed certain invalid inputs in all underlying ops causing SIGSEGV instead of raising tf.invalidargumenterrors.

**Breaking changes**:
Removed SGDifferentiator (Performance improvements and large rewrite needed).
TensorFlow dependency is now required to be 2.3.1.
Cirq dependency is now required to be Cirq 0.9.1.
Pinned Sympy dependency to 1.5, until now we allowed flexibility with whatever the Cirq requirements were.
Windows builds will not be provided for this release (We do have hopes to add them back in later versions).

A big thanks to all of our contributors for this version:

zaqqwerty , SachinCompton , therooler , jaeyoo , vinitX , yuanoook , tiancheng2000 , MarkDaoust , lamberta , MichaelBroughton , kristenrq .

**NO FUNCTIONAL CHANGES.**
Added installer support for internal builds.