pyqrack

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Pure Python bindings for the pure C++11 Qrack quantum computer simulator library

(PyQrack is just pure Qrack.)

This is the purely CPU-based variant of PyQrack (with module name pyqrack-cpu). This alternate build of PyQrack is provided so that systems that won't use OpenCL or CUDA anyway (such as because they lack any GPUs or other accelerators like the Intel HD) do not need to install the OpenCL library in order to use PyQrack. In this form, both the PyQrack module and the underlying C++ Qrack library are entirely external dependency-free.

If you're looking for Mac ARM support, use the package pyqrack, not pyqrack-cpu. Mac officially "deprecated" OpenCL years ago. Hence, accelerator support is not included in ARM-based Mac wheels, and OpenCL installation is not required on these systems, but, if you have a CUDA accelerator on ARM-based Mac, you could try the package pyqrack-cuda instead.

Performance can benefit greatly from following the Qrack repository "Quick Start" and "Power user considerations."

Import and instantiate QrackSimulator instances. This simulator can perform arbitrary single qubit and controlled-single-qubit gates, as well as other specific gates like SWAP.

Any 2x2 bit operator matrix is represented by a list of 4 complex floating point numbers, in row-major order.

Single and array "b" parameters represent Pauli operator bases. They are specified according to the enumeration of the Pauli class.

MC[x] and MAC[x] methods are controlled single bit gates, with as many control qubits as you specify via Python list c argument. MCX is multiply-controlled Pauli X, and MACX is "anti-"controlled Pauli X, i.e. "anti-control" activates the gate if all control bits are specifically off, as opposed to on.

To load the required unitaryfund/qrack libraries from a different location, set the PYQRACK_SHARED_LIB_PATH environment variable.

PyQrack has experimental support for PyZX Circuit definitions as an intermediate representation for QrackSimulator. To try this, load a Circuit in PyZX, (use that module to optimize your circuit, as you like,) and create a QrackSimulator() instance using the pyzxCircuit named argument of the constructor, like so:

sim = QrackSimulator(pyzxCircuit=c)

where c is a PyZX circuit object. The circuit will automatically be simulated in the constructed QrackSimulator instance. This also allows loading from QASM and other intermediate representations supported by PyZX.

See https://pyqrack.readthedocs.io/en/latest/ for an API reference.

For custom Qrack build floating-point precision, where options are half, float, double, and quad, set an environment variable via export QRACK_FPPOW=[n] (or as appropriate to your shell) where [n] is the logarithm base 2 of the number of bits in the systemic floating point type (4, 5, 6, or 7, with 5 or float as default, i.e. 2**5=32 for 32-bit float). Your Qrack installation floating-point build option must match this specific value, which might require a custom Qrack build.

Please feel welcome to open an issue, if you'd like help. 😃

Special thanks go to Zeeshan Ahmed, for bug fixes and design suggestions, Ashish Panigrahi, for documentation and design suggestions, WingCode, for documentation, Or Golan, for CI build pipeline tooling, and to the broader community of Qrack contributors, for years of happy Qracking! You rock!

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  • Released:
Newer release available (2.17.2)

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Credits

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Author: Daniel Strano

License

MIT

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dev

Tags

pyqrack qrack simulator quantum gpu

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Empirical results are worse

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Reason this release was yanked:

Potential segfault in mid-circuit measurement

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Reason this release was yanked:

1.32.17 is correct! The erata Qrack commit bc1d5d8 was unnecessary.

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