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Quantum Leaf (量易伏) is a Cloud-Native quantum computing platform developed by the Institute for Quantum Computing, Baidu. It is used for programming, simulating and executing quantum computers, aiming at providing the quantum programming environment for Quantum infrastructure as a Service (QaaS).
QCompute is a Python-based open-source SDK. It provides a full-stack programming experience for advanced users via the features of hybrid quantum programming language and a high-performance simulator. Users can use the already-built objects and modules of quantum programming environment, pass parameters to build and execute the quantum circuits on the local simulator or the cloud simulator/hardware.
QCompute provides services for creating and analyzing quantum circuits, and calling quantum backend. The architecture of Quantum Leaf including QCompute is shown in the figure below.
In particular, cloud service requires login at Quantum-hub. The token, credit points, large-scale results and more information can be found from the website.
pip install qcompute
pip install -e .
Then, config the python interpreter to execute examples.
Please get Python environment and Pip tool prepared. Be careful about different path separators on operating systems. At present, Python 3.8-3.10 versions are compatible.
python -m Test.PostInstall.PostInstall_test
Input your token which could be found on https://quantum-hub.baidu.com/ to do cloud test, or press Enter to do local test only.
Use the sample code and tutorials in the Example folder to learn how to use QCompute SDK.
QCompute SDK contains quantum toolkits, simulators, examples and docs. If concerned with quantum toolkits, e.g., the QCompute subfolder, you are highly suggested using 'local setup' process to ensure that any development could be reflected in the executing process.
Most researchers who only work on the quantum applications (examples) are suggested to use one-step live setup. In this case, the local modification of QCompute would NOT be reflected in the executing process. However, the modification on the subfolder, Example, would be still valid.
Coding requirements:
Be familiar with quantum circuit model. Any pull should be tested first and then submitted. Be careful about the order of qubits.
Please comply with development specifications of relevant programming languages.
If any questions, advices, suggestions, please contact us via Email: quantum@baidu.com ;
Or, you can use feedback table in Quantum-hub to provide any feedbacks;
Or, you are also welcomed to join our discussion QQ group: QQ Group Number:1147781135.
Institute for Quantum Computing, Baidu.
The new backend "local_cuquantum" is constructed under cuQuantum SDK (https://developer.nvidia.com/cuquantum-sdk) and is supported by NVIDIA.
The changelog of this project can be found in CHANGELOG.md.
This project is licensed under the Apache License 2.0 - see the LICENSE file for details.
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