Open Source Quantum Computing Software - Page 2
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A python package that allows scientists to easily create configurable and reusable experiments. Intended for use with the LabRAD framework. Developed by the Haeffner group studying quantum simulation at UC Berkeley. Wiki at lrexp.wikispaces.com
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NBO Analyzer
Analyze output of NBO computations
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OPEN GENERAL SCIENTIFIC INTERFACES homepage : http://www.opengsi.org
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OpenQASM
Quantum assembly language for extended quantum circuits
OpenQASM is an imperative programming language designed for near-term quantum computing algorithms and applications. Quantum programs are described using the measurement-based quantum circuit model with support for classical feed-forward flow control based on measurement outcomes. OpenQASM presents a parameterized set of physical logic gates and concurrent real-time classical computations. Its main goal is to serve as an intermediate representation for higher-level compilers to communicate with quantum hardware. Allowances have been made for human usability. In particular, the language admits different representations of the same program as it is transformed from a high-level description to a pulse representation. -
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Paddle Quantum
Paddle Quantum
Paddle Quantum (量桨) is the world's first cloud-integrated quantum machine learning platform based on Baidu PaddlePaddle. It supports the building and training of quantum neural networks, making PaddlePaddle the first deep-learning framework in China. Paddle Quantum is feature-rich and easy to use. It provides comprehensive API documentation and tutorials help users get started right away. Paddle Quantum aims at establishing a bridge between artificial intelligence (AI) and quantum computing (QC). It has been utilized for developing several quantum machine learning applications. With the PaddlePaddle deep learning platform empowering QC, Paddle Quantum provides strong support for the scientific research community and developers in the field to easily develop QML applications. Moreover, it provides a learning platform for quantum computing enthusiasts. -
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PetoronHash-System
PHASH | post-quantum XOF hashing algorithm | C++20
PHASH is a self-contained, dependency-free, post-quantum XOF hashing algorithm implemented in modern C++20. This release delivers the first fully stable production implementation of the PetoronHash-System — a 1600-bit sponge-based hash function with domain separation, extendable output, and deterministic behavior. Key Features No external dependencies — pure C++20 implementation. Extendable Output (XOF) — supports arbitrary output length (256–8192+ bits). Post-quantum oriented design — ARX-based sponge resistant to Grover-type attacks. Context and salt separation — unique hashing domains for each use-case. Optimized performance — ~120–130 MB/s Comprehensive verification — verify_all.sh performs KAT tests, determinism checks, and performance validation. Verification Script: chmod +x verify_all.sh ./verify_all.sh https://github.com/01alekseev/PetoronHash-System Ivan Alekseev | petoron.org -
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PetoronHash2
PH2 Permutation-based cryptographic post-quantum hash library with duplex construction (C++20)
PetoronHash2 (PH2) is a standalone ARX-based sponge construction that combines: A 4096-bit internal permutation core A sponge/duplex architecture with explicit capacity separation An extendable-output function (XOF) Memory-hard (HARD) and burn (BURN) modes A structured tagged absorb scheme A parameterized architecture suitable for hashing, KDF, and stress-oriented derivation PH2 is designed as a wide-state cryptographic primitive with explicit domain separation and configurable output length. https://github.com/01alekseev/PetoronHash2 Petoron | Ivan Alekseev | MIT license -
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ProjectQ
An open source software framework for quantum computing
ProjectQ is an open-source effort for quantum computing. It features a compilation framework capable of targeting various types of hardware, a high-performance quantum computer simulator with emulation capabilities, and various compiler plug-ins. -
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PyQuil
A Python library for quantum programming using Quil
PyQuil is a Python library for quantum programming using Quil, the quantum instruction language developed at Rigetti Computing. PyQuil serves three main functions. PyQuil has a ton of other features, which you can learn more about in the docs. However, you can also keep reading below to get started with running your first quantum program. Without installing anything, you can quickly get started with quantum programming by exploring our interactive Jupyter Notebook tutorials and examples. To run them in a preconfigured execution environment on Binder, click the "launch binder" badge at the top of the README or the link here! To learn more about the tutorials and how you can add your own, visit the rigetti/forest-tutorials repository. If you'd rather set everything up locally, or are interested in contributing to pyQuil, continue to the next section for instructions on installing pyQuil and the Forest SDK. -
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Q-CTRL Open Controls
Q-CTRL Open Controls
Q-CTRL Open Controls is an open-source Python package that makes it easy to create and deploy established error-robust quantum control protocols from the open literature. The aim of the package is to be the most comprehensive library of published and tested quantum control techniques developed by the community, with easy-to-use export functions allowing users to deploy these controls on. -
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QPanda 2
QPanda 2 is an open source quantum computing framework
QPanda2 is an open source quantum computing framework developed by Origin Quantum, which can be used to build, run and optimize quantum algorithms. QPanda2 is the basic library of a series of software developed by Origin Quantum, which provides core components for QRunes, Qurator and quantum computing services. -
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Qbsolv
A decomposing solver
Qbsolv,a decomposing solver, finds a minimum value of a large quadratic unconstrained binary optimization (QUBO) problem by splitting it into pieces solved either via a D-Wave system or a classical tabu solver. (Note that qbsolv by default uses its internal classical solver. Access to a D-Wave system must be arranged separately.) -
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QuCAT
Quantum Circuit Analyzer Tool
QuCAT stands for Quantum Circuit Analyzer Tool. This open source python library provides standard analysis tools for superconducting electronic circuits, built around Josephson junctions. QuCAT features an intuitive graphical or programmatical interface to create circuits, the ability to compute their Hamiltonian, and a set of complimentary functionalities such as calculating dissipation rates or visualizing current flows in the circuit. QuCAT currently supports quantization in the basis of normal modes. -
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QuCoSi is a C++ library for simulating a quantum computer. The used qubits and gates are plain vectors and matrices that can be inspected and modified easily. Its emphasis lies on readability and ease of use.
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Quantum Information Toolkit is a comprehensive, easy-to-use interactive numerical toolkit for quantum information and computing, available for both MATLAB and Python.
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Quantum++
Modern C++ quantum computing library
Quantum++ is a modern C++ general-purpose quantum computing library, composed solely of template header files. Quantum++ is written in standard C++17 and has very low external dependencies, using only the Eigen 3 linear algebra header-only template library and, if available, the OpenMP multiprocessing library. Quantum++ is not restricted to qubit systems or specific quantum information processing tasks, being capable of simulating arbitrary quantum processes. The main design factors taken in consideration were ease of use, high portability, and high performance. The library's simulation capabilities are only restricted by the amount of available physical memory. On a typical machine (Intel i5 8Gb RAM) Quantum++ can successfully simulate the evolution of 25 qubits in a pure state or of 12 qubits in a mixed state reasonably fast. -
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Qulacs
Variational Quantum Circuit Simulator for Quantum Computation Research
Variational Quantum Circuit Simulator for Quantum Computation Research. Qulacs is a Python/C++ library for fast simulation of large, noisy, or parametric quantum circuits. Qulacs is developed at QunaSys, Osaka University, NTT, and Fujitsu. -
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Relevant Data Storage System (RDSS)
Relevant Data Storage System (RDSS)
"Relevant Data Storage System" (RDSS) eliminates the need of having the PC "end user" store their data by using a “forced remembrance” of the navigation address and or pathway of a folder hierarchy along with the assigned or designated file name for later data acquisition. The new innovative method I have created makes possible that any end user regardless of their native language can retrieve all relevant data no matter the language, be Chinese, English, Hindu, Italian, Russian, Hawaiian, even Klingon if wanted, etcetera. This means, the creator saves their data (in English as an example), but a Japanese "end user" can retrieve the SAME data without needing to know English at all. Of course, this process isn't meant to convert the English into the Japanese language. This method is meant only to insure anyone using any language known, can recover the SAME data without ever needing to know the original creator. -
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:awsum: You lost the game.
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ScaffCC
Compilation and optimization framework for the Scaffold language
ScaffCC is a compiler and scheduler for the Scaffold programing language. It is written using the LLVM open-source infrastructure. It is for the purpose of writing and analyzing code for quantum computing applications. ScaffCC enables researchers to compile quantum applications written in Scaffold to a low-level quantum assembly format (QASM), apply error correction, and generate time and area metrics. It is written to be scalable up to problem sizes in which quantum algorithms outperform classical ones, and as such provide valuable insight into the overheads involved and possible optimizations for a realistic implementation on a future device technology. -
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Simuquant
A quantum circuit simulator written in Scala
Simuquant is made to construct and simulate universal quantum circuits. It's GUI enables intuitive access and direct graphical feedback, making it useful in a classroom situation and the like. Simulation processing is done in parallel, utilizing parallel collections introduced in scala 2.9. This application has been created as part a bachelor-thesis at the Hamburg University of Applied Sciences. The thesis is available at: http://opus.haw-hamburg.de/volltexte/2012/1843/pdf/ba_dahl.pdf Future plans: - Operator grouping (enables repeated blocks) - Editable library -
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Superstaq
Quantum software platform that is optimized across the quantum stack
This repository is the home of the Superstaq development team's open-source work. Our quantum software platform is optimized across the quantum stack and enables users to write quantum programs in Cirq or Qiskit and target a variety of quantum computers and simulators.
