| Name | mqt.qecc JSON |
| Version |
1.5.0
JSON |
| download |
| home_page | |
| Summary | QECC - An MQT Tool for Quantum Error Correcting Codes |
| upload_time | 2023-10-06 09:02:19 |
| maintainer | |
| docs_url | None |
| author | |
| requires_python | >=3.8 |
| license | MIT License Copyright (c) 2023 Chair for Design Automation, Technical University of Munich Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. |
| keywords |
mqt
quantum-computing
error-correction
maxsat
qldpc
|
| VCS |
 |
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
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No Travis.
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No coveralls.
|
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# MQT QECC: A tool for Quantum Error Correcting Codes written in C++
A tool for quantum error correcting codes and numerical simulations developed as part of the [_Munich Quantum Toolkit_](https://mqt.readthedocs.io) (_MQT_) by the [Chair for Design Automation](https://www.cda.cit.tum.de/) at the [Technical University of Munich](https://www.tum.de/).
It builds upon [MQT Core](https://github.com/cda-tum/mqt-core), which forms the backbone of the MQT.
The tool can be used to:
- Decode quantum LDPC codes and conduct respective numerical simulations.
- At the moment the general QLDPC
decoder [[2]](https://ieeexplore.ieee.org/abstract/document/9682738)
and a heuristic (which improves the runtime of the algorithm) [[1]](https://arxiv.org/abs/2209.01180) are
implemented.
Currently, open-source software by Joschka Roffe et
al.: [[3]](https://github.com/quantumgizmos/bias_tailored_qldpc) is used to construct codes (toric, lifted product
and
hypergraph product).
- Decode (triangular) color codes and conduct respective numerical simulations.
- The decoder is based on an analogy to the classical LightsOut puzzle and formulated as a MaxSAT problem. The SMT solver
Z3 is used to determine minimal solutions of the MaxSAT problem, resulting in minimum-weight decoding estimates.
- Apply error correction to quantum circuits.
- The framework allows to apply different QECC schemes to quantum circuits and either exports the resulting
circuits or simulates them using Qiskit [[4]](https://qiskit.org/). Currently, six different ECCs are supported
with varying extent of functionality.
<p align="center">
<a href="https://mqt.readthedocs.io/projects/qecc">
<img width=30% src="https://img.shields.io/badge/documentation-blue?style=for-the-badge&logo=read%20the%20docs" alt="Documentation" />
</a>
</p>
If you have any questions, feel free to contact us via [quantum.cda@xcit.tum.de](mailto:quantum.cda@xcit.tum.de) or by
creating an issue on [GitHub](https://github.com/cda-tum/mqt-qecc/issues).
## Getting Started
QECC is available via [PyPI](https://pypi.org/project/mqt.qecc/) for Linux and macOS and supports Python 3.8 to 3.12.
```console
(venv) $ pip install mqt.qecc
```
The following code gives an example on the usage:
### Example for decoding quantum LDPC codes
```python3
from mqt.qecc import *
import numpy as np
H = [[1, 0, 0, 1, 0, 1, 1], [0, 1, 0, 1, 1, 0, 1], [0, 0, 1, 0, 1, 1, 1]]
code = Code(H, H)
decoder = UFHeuristic()
decoder.set_code(code)
x_err = sample_iid_pauli_err(code.N, 0.05)
decoder.decode(code.get_x_syndrome(x_err))
result = decoder.result
print(result)
residual_err = np.array(x_err) ^ np.array(result.estimate)
print(code.is_x_stabilizer(residual_err))
```
### Example for decoding color codes
Simply running the following code will perform a numerical analysis of the MaxSAT color code decoder for an instance of
the distance-21 triangular color code with a bit-flip error rate of 0.01 and 1000 simulations.
```python3
from mqt.qecc.cc_decoder import decoder
d = 21 # distance of the triangular code to simulate
p = 0.01 # (bit-flip) error rate
nr_sims = 1000 # number of simulations to run
decoder.run(distance=d, error_rate=p, nr_sims=nr_sims)
```
The dataset used in the paper evaluation on decoding quantum color codes is available on Zenodo:
[](https://doi.org/10.5281/zenodo.7760135)
### Example for applying error correction to a circuit
```python3
from mqt import qecc
file = "path/to/qasm/file.qasm" # Path to the OpenQASM file the quantum circuit shall be loaded from
ecc = "Q7Steane" # Error correction code that shall be applied to the quantum circuit
ecc_frequency = 100 # After how many times a qubit is used, error correction is applied
result = qecc.apply_ecc(file, ecc, ecc_frequency)
# print the resulting circuit as OpenQASM string
print(result["circ"])
```
A wrapper script for applying error correction to quantum circuits (provided as OpenQASM) and performing a
noise-aware quantum circuit simulation (using Qiskit) is provided. The script can be used like this:
```bash
$ (venv) ecc_qiskit_wrapper -ecc Q7Steane -fq 100 -m D -p 0.0001 -n 2000 -fs aer_simulator_stabilizer -s 0 -f ent_simple1000_n2.qasm
_____Trying to simulate with D (prob=0.0001, shots=2000, n_qubits=17, error correction=Q7Steane) Error______
State |00> probability 0.515
State |01> probability 0.0055
State |10> probability 0.0025
State |11> probability 0.477
```
**Detailed documentation on all available methods, options, and input formats is available
at [ReadTheDocs](https://mqt.readthedocs.io/projects/qecc).**
## System Requirements and Building
The implementation is compatible with any C++17 compiler and a minimum CMake version of 3.19.
Please refer to the [documentation](https://mqt.readthedocs.io/projects/qecc) on how to build the project.
Building (and running) is continuously tested under Linux and macOS using the
[latest available system versions for GitHub Actions](https://github.com/actions/virtual-environments).
Windows support is currently experimental.
## Reference
If you use our tool for your research, we will be thankful if you refer to it by citing the appropriate publication:
- [](https://arxiv.org/abs/2303.14237)
L. Berent, L. Burgholzer, P.J. Derks, J. Eisert, and R. Wille, "Decoding quantum color codes with MaxSAT".
- [](https://arxiv.org/pdf/2301.05731)
T. Grurl, C. Pichler, J. Fuss and R. Wille, "Automatic Implementation and Evaluation of Error-Correcting Codes for
Quantum Computing: An Open-Source Framework for Quantum Error-Correction," in International Conference on VLSI
Design and International Conference on Embedded Systems (VLSID), 2023
- [](https://arxiv.org/abs/2209.01180)
L. Berent, L. Burgholzer, and R.
Wille, "[Software Tools for Decoding Quantum Low-Density Parity Check Codes](https://arxiv.org/abs/2209.01180),"
in Asia and South Pacific Design Automation Conference (ASP-DAC), 2023
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"author_email": "Lucas Berent <lucas.berent@tum.de>, Lukas Burgholzer <lukas.burgholzer@tum.de>, Peter-Jan H.S. Derks <peter-janderks@hotmail.com>",
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"description": "[](https://opensource.org/licenses/MIT)\n[](https://github.com/cda-tum/mqt-qecc/actions/workflows/ci.yml)\n[](https://github.com/cda-tum/mqt-qecc/actions/workflows/python-ci.yml)\n[](https://github.com/cda-tum/mqt-qecc/actions/workflows/deploy.yml)\n[](https://codecov.io/gh/cda-tum/mqt-qecc)\n\n<p align=\"center\">\n <picture>\n <source media=\"(prefers-color-scheme: dark)\" srcset=\"https://raw.githubusercontent.com/cda-tum/mqt-qecc/main/docs/source/_static/mqt_light.png\" width=\"60%\">\n <img src=\"https://raw.githubusercontent.com/cda-tum/mqt-qecc/main/docs/source/_static/mqt_dark.png\" width=\"60%\">\n </picture>\n </p>\n\n# MQT QECC: A tool for Quantum Error Correcting Codes written in C++\n\nA tool for quantum error correcting codes and numerical simulations developed as part of the [_Munich Quantum Toolkit_](https://mqt.readthedocs.io) (_MQT_) by the [Chair for Design Automation](https://www.cda.cit.tum.de/) at the [Technical University of Munich](https://www.tum.de/).\nIt builds upon [MQT Core](https://github.com/cda-tum/mqt-core), which forms the backbone of the MQT.\n\nThe tool can be used to:\n\n- Decode quantum LDPC codes and conduct respective numerical simulations.\n - At the moment the general QLDPC\n decoder [[2]](https://ieeexplore.ieee.org/abstract/document/9682738)\n and a heuristic (which improves the runtime of the algorithm) [[1]](https://arxiv.org/abs/2209.01180) are\n implemented.\n Currently, open-source software by Joschka Roffe et\n al.: [[3]](https://github.com/quantumgizmos/bias_tailored_qldpc) is used to construct codes (toric, lifted product\n and\n hypergraph product).\n- Decode (triangular) color codes and conduct respective numerical simulations.\n - The decoder is based on an analogy to the classical LightsOut puzzle and formulated as a MaxSAT problem. The SMT solver\n Z3 is used to determine minimal solutions of the MaxSAT problem, resulting in minimum-weight decoding estimates.\n- Apply error correction to quantum circuits.\n - The framework allows to apply different QECC schemes to quantum circuits and either exports the resulting\n circuits or simulates them using Qiskit [[4]](https://qiskit.org/). Currently, six different ECCs are supported\n with varying extent of functionality.\n\n<p align=\"center\">\n <a href=\"https://mqt.readthedocs.io/projects/qecc\">\n <img width=30% src=\"https://img.shields.io/badge/documentation-blue?style=for-the-badge&logo=read%20the%20docs\" alt=\"Documentation\" />\n </a>\n</p>\n\nIf you have any questions, feel free to contact us via [quantum.cda@xcit.tum.de](mailto:quantum.cda@xcit.tum.de) or by\ncreating an issue on [GitHub](https://github.com/cda-tum/mqt-qecc/issues).\n\n## Getting Started\n\nQECC is available via [PyPI](https://pypi.org/project/mqt.qecc/) for Linux and macOS and supports Python 3.8 to 3.12.\n\n```console\n(venv) $ pip install mqt.qecc\n```\n\nThe following code gives an example on the usage:\n\n### Example for decoding quantum LDPC codes\n\n```python3\nfrom mqt.qecc import *\nimport numpy as np\n\nH = [[1, 0, 0, 1, 0, 1, 1], [0, 1, 0, 1, 1, 0, 1], [0, 0, 1, 0, 1, 1, 1]]\ncode = Code(H, H)\ndecoder = UFHeuristic()\ndecoder.set_code(code)\nx_err = sample_iid_pauli_err(code.N, 0.05)\ndecoder.decode(code.get_x_syndrome(x_err))\nresult = decoder.result\nprint(result)\nresidual_err = np.array(x_err) ^ np.array(result.estimate)\nprint(code.is_x_stabilizer(residual_err))\n```\n\n### Example for decoding color codes\n\nSimply running the following code will perform a numerical analysis of the MaxSAT color code decoder for an instance of\nthe distance-21 triangular color code with a bit-flip error rate of 0.01 and 1000 simulations.\n\n```python3\nfrom mqt.qecc.cc_decoder import decoder\n\nd = 21 # distance of the triangular code to simulate\np = 0.01 # (bit-flip) error rate\nnr_sims = 1000 # number of simulations to run\ndecoder.run(distance=d, error_rate=p, nr_sims=nr_sims)\n```\n\nThe dataset used in the paper evaluation on decoding quantum color codes is available on Zenodo:\n[](https://doi.org/10.5281/zenodo.7760135)\n\n### Example for applying error correction to a circuit\n\n```python3\nfrom mqt import qecc\n\nfile = \"path/to/qasm/file.qasm\" # Path to the OpenQASM file the quantum circuit shall be loaded from\necc = \"Q7Steane\" # Error correction code that shall be applied to the quantum circuit\necc_frequency = 100 # After how many times a qubit is used, error correction is applied\n\nresult = qecc.apply_ecc(file, ecc, ecc_frequency)\n\n# print the resulting circuit as OpenQASM string\nprint(result[\"circ\"])\n```\n\nA wrapper script for applying error correction to quantum circuits (provided as OpenQASM) and performing a\nnoise-aware quantum circuit simulation (using Qiskit) is provided. The script can be used like this:\n\n```bash\n$ (venv) ecc_qiskit_wrapper -ecc Q7Steane -fq 100 -m D -p 0.0001 -n 2000 -fs aer_simulator_stabilizer -s 0 -f ent_simple1000_n2.qasm\n_____Trying to simulate with D (prob=0.0001, shots=2000, n_qubits=17, error correction=Q7Steane) Error______\nState |00> probability 0.515\nState |01> probability 0.0055\nState |10> probability 0.0025\nState |11> probability 0.477\n```\n\n**Detailed documentation on all available methods, options, and input formats is available\nat [ReadTheDocs](https://mqt.readthedocs.io/projects/qecc).**\n\n## System Requirements and Building\n\nThe implementation is compatible with any C++17 compiler and a minimum CMake version of 3.19.\nPlease refer to the [documentation](https://mqt.readthedocs.io/projects/qecc) on how to build the project.\n\nBuilding (and running) is continuously tested under Linux and macOS using the\n[latest available system versions for GitHub Actions](https://github.com/actions/virtual-environments).\nWindows support is currently experimental.\n\n## Reference\n\nIf you use our tool for your research, we will be thankful if you refer to it by citing the appropriate publication:\n\n- [](https://arxiv.org/abs/2303.14237)\n L. Berent, L. Burgholzer, P.J. Derks, J. Eisert, and R. Wille, \"Decoding quantum color codes with MaxSAT\".\n\n- [](https://arxiv.org/pdf/2301.05731)\n T. Grurl, C. Pichler, J. Fuss and R. Wille, \"Automatic Implementation and Evaluation of Error-Correcting Codes for\n Quantum Computing: An Open-Source Framework for Quantum Error-Correction,\" in International Conference on VLSI\n Design and International Conference on Embedded Systems (VLSID), 2023\n\n- [](https://arxiv.org/abs/2209.01180)\n L. Berent, L. Burgholzer, and R.\n Wille, \"[Software Tools for Decoding Quantum Low-Density Parity Check Codes](https://arxiv.org/abs/2209.01180),\"\n in Asia and South Pacific Design Automation Conference (ASP-DAC), 2023\n",
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