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tensorflow_quantum/release.md

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# Release 0.7.0
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# Major Features and Improvements
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- Significant performance improvements by introducing cuQuantum support for circuit execution on GPU:
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- TensorFlow Quantum Keras layers can now be executed on GPU by setting `use_cuquantum=True` at layer instantiation. Examples:
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- `tfq.layers.Expectation(use_cuquantum=True)`
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- `tfq.layers.SampledExpectation(use_cuquantum=True)` (note that cuQuantum runtime is unsupported for any noisy circuit operations
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- `tfq.layers.State(use_cuquantum=True)`
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- `tfq.layers.Sample(use_cuquantum=True)`
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- `tfq.layers.SimulateSample(use_cuquantum=True)`
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- Build, compilation, and packaging:
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- The TensorFlow dependency has been upgraded from 2.7.0 to 2.11.0:
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- TensorFlow Quantum is now compiled with `_GLIBCXX_USE_CXX11_ABI=1`. Downstream projects that encounter `std::__cxx11` or `[abi:cxx11]` linker errors will need to adopt this compiler option. See [the GNU C++ Library docs on Dual ABI](https://gcc.gnu.org/onlinedocs/libstdc++/manual/using_dual_abi.html).
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- TensorFlow Quantum is now compiled with `-std=c++17`, see [install.md](/docs/install.md) for build instructions.
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# Thanks to our Contributors
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This release contains contributions from many people at Google, Nvidia, as well as:

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