qcompute-qep 1.0.0

A Quantum Error Processing toolkit developed by the Institute for Quantum Computing at Baidu Research.

Copyright (c) 2022 Institute for Quantum Computing, Baidu Inc. All Rights Reserved.

About QEP

QEP is a Quantum Error Processing toolkit developed by the Institute for Quantum Computing at Baidu Research. It aims to deal with quantum errors inherent in quantum devices using software solutions. Currently, it offers three powerful quantum error processing functions: randomized benchmarking, quantum error characterization, and quantum error mitigation:

• Randomized benchmarking is used for assessing the capabilities and extendibilities of quantum computing hardware platforms, through estimating the average error rates that are measured with long sequences of random quantum circuits. It provides standard randomized benchmarking, interleaved randomized benchmarking, cross-entropy benchmarking, and unitarity randomized benchmarking.

• Quantum error characterization is used for reconstructing the comprehensive information in quantum computing hardware platforms, through many partial and limited experimental results. It provides quantum state tomography, quantum process tomography, quantum detector tomography, quantum gateset tomography, and spectral quantum tomography.

• Quantum error mitigation is used for improving the accuracy of quantum computational results, through post-processing the experiment data obtained by varying noisy experiments, extending the computational reach of a noisy superconducting quantum processor. It provides zero-noise extrapolation technique to mitigate quantum gate noise, and a collection of methods such as inverse, least-square, iterative Bayesian unfolding, Neumann series to mitigate quantum measurement noise.

QEP is based on QCompute, a Python-based open-source quantum computing platform SDK also developed by Institute for Quantum Computing. It provides a full-stack programming experience for senior users via hybrid quantum programming language features and high-performance simulators. You can install QCompute via pypi. When you install QEP, the dependency QCompute will be automatically installed. Please refer to QCompute's official Open Source page for more details.

Installation

Install QEP

The package QEP is compatible with 64-bit Python 3.8 and 3.9, on Linux, MacOS (10.14 or later) and Windows. We highly recommend the users to install QEP via pip. Open the Terminal and run

pip install qcompute-qep

This will install the QEP binaries as well as the QEP package. For those using an older version of QEP, keep up to date by installing with the --upgrade flag for additional features and bug fixes.

Run Examples

After installation, you can try the following simple program to check whether QEP has been successfully installed.

from QCompute import *
import qcompute_qep.tomography as tomography
import qcompute_qep.utils.circuit as circuit

# Set the token. You must set your VIP token in order to access the hardware
Define.hubToken = "Token"

# Step 1. Initialize a quantum program for preparing the Bell state
qp = QEnv()  # qp is short for "quantum program", instance of QProgram
qp.Q.createList(2)
H(qp.Q[0])
CX(qp.Q[0], qp.Q[1])

# Step 2. Set the quantum computer (instance of QComputer).
# For debugging, change qc to BackendName.LocalBaiduSim2
qc = BackendName.LocalBaiduSim2
# For test on real quantum hardware, change qc to BackendName.CloudBaiduQPUQian
# qc = BackendName.CloudBaiduQPUQian

# Step 3. Perform Quantum State Tomography, check how well the Bell state is prepared.
st = tomography.StateTomography()
# Call the tomography procedure and obtain the noisy quantum state
st.fit(qp, qc, method='inverse', shots=8192)

print('Fidelity between the ideal and noisy Bell states is: F = {:.5f}'.format(st.fidelity))

More examples can be found in QEP Tutorials and the source file of QEP hosted in GitHub. You can get started from there.

Tutorials

QEP provides detailed and comprehensive tutorials for randomized benchmarking, quantum error characterization, and quantum error mitigation, from theoretical analysis to practical application. We recommend the interested researchers or deverlopers to download the Jupyter Notebooks and try it. The tutorials are listed as follows:

• Randomized Benchmarking

  • Standard Randomized Benchmarking
  • Interleaved Randomized Benchmarking
  • Cross-Entropy Benchmarking
  • Unitarity Randomized Benchmarking

• Quantum Error Characterization

  • Quantum State Tomography
  • Quantum Process Tomography
  • Quantum Detector Tomography
  • Quantum Gateset Tomography
  • Spectral Quantum Tomography

• Quantum Error Mitigation

  • Zero-Noise Extrapolation
  • Measurement Error Mitigation
  • Applications of Measurement Error Mitigation

API Documentation

For those who are looking for explanation on the python classes and functions in QEP, please refer to our API documentation.

Feedbacks

Users are encouraged to contact us via email [e-mail] with general questions, unfixed bugs, and potential improvements. We hope to make QEP better together with the community!

Research based on QEP

We encourage researchers and developers to use QEP to explore quantum error processing. If your work uses QEP, please feel free to send us a notice via [e-mail] and cite us with the following BibTeX:

@misc{QEP,
      title = {{Quantum Error Processing in Baidu Quantum Platform}},
      year = {2022},
      url = {https://quantum-hub.baidu.com/qep/}
}

Copyright and License

QEP uses Apache-2.0 license.