Best Quantum Computing Software for Linux of 2024

Open source platform for machine learning. TensorFlow is a machine learning platform that is open-source and available to all. It offers a flexible, comprehensive ecosystem of tools, libraries, and community resources that allows researchers to push the boundaries of machine learning. Developers can easily create and deploy ML-powered applications using its tools. Easy ML model training and development using high-level APIs such as Keras. This allows for quick model iteration and debugging. No matter what language you choose, you can easily train and deploy models in cloud, browser, on-prem, or on-device. It is a simple and flexible architecture that allows you to quickly take new ideas from concept to code to state-of the-art models and publication. TensorFlow makes it easy to build, deploy, and test.

Quantum computing is a promising way to develop new molecules and materials quickly and at a low cost. InQuanto is a cutting-edge quantum computational chemistry platform that represents a crucial step towards this goal. Quantum chemistry is used to accurately predict and describe the fundamental properties of matter. It is therefore a powerful tool for the design and development new molecules and materials. However, industrially relevant molecules and materials are complex and difficult to accurately simulate. The current capabilities force a trade either to use highly accurate methods for the smallest systems or to use approximating technologies. InQuanto’s modular workflow allows both computational chemists, and quantum algorithm developers, to easily mix and combine the latest quantum algorithms and advanced subroutines with error mitigation techniques.

> is a software architecture and tool suite for quantum computing. It includes a programming langage, optimization and scheduling algorithm, and quantum simulations. > can be used to translate a quantum algorithm written in the form of a high-level program into the low-level machine instructions for a quantum device. > is being developed by the quantum architectures and computation Group (QuArC) at Microsoft Research. >. > allows the simulation of Hamiltonians, quantum circuits, quantum stabilizer circuits, and quantum noise models, and supports client, service, and cloud operation.

In addition to the design of quantum computers, the development of useful algorithms for quantum computing is a major focus. In the absence a large quantum computer, a software simulation of quantum computers is needed to simulate the execution and study of quantum algorithms. The QX simulator is able to simulate a realistic noisy execution by using different error models, such as depolarizing noise. The user can select the error model, and then define a physical probability of error to simulate a target quantum computer. This error rate can also be defined by the gate fidelity of the target platform and the qubit decoherence.

The Quantum Exact Simulation Toolkit is a high performance simulator of quantum circuits. It also simulates state-vectors, density matrices and density vectors. QuEST uses multithreading and GPU acceleration to run lightning-fast on laptops, desktops, and networked supercomputers. QuEST is a stand-alone program that requires no installation and is easy to compile. QuEST does not require any setup. It can be downloaded, compiled, and run within seconds. QuEST is free of external dependencies, and it compiles natively under Windows, Linux, and MacOS. You can get QuEST to run on almost any device, whether it's a laptop, desktop, supercomputer, microcontroller or cloud.

Bayesforge™ is a Linux image that curates all the best open source software available for data scientists who need advanced analytical tools as well as quantum computing and computational math practitioners who want to work with QC frameworks. The image combines open source software such as D-Wave and Rigetti, IBM Quantum Experience, Google's new quantum computer language Cirq and other advanced QC Frameworks. Qubiter, our quantum compiler and fog modeling framework can be cross-compiled to all major architectures. The Jupyter WebUI makes all software accessible. Its modular architecture allows users to code in Python R and Octave.