Best Free Quantum Computing Software 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.

Covalent's serverless HPC architecture makes it easy to scale jobs from your laptop to the HPC/Cloud. Covalent is a Pythonic workflow tool that computational scientists, AI/ML program engineers, and anyone who needs to perform experiments on limited or costly computing resources such as HPC clusters and GPU arrays, cloud services, and quantum computers. Covalent allows researchers to run computation tasks on advanced hardware platforms, such as a serverless HPC cluster or quantum computer, using just one line of code. Covalent's latest release includes three major enhancements and two new feature sets. Covalent's modular design allows users to create custom pre-and post-hooks for electrons. This allows them to facilitate a variety of use cases, including setting up remote environments (using DepsPip), and running custom functions.

Data scientists need innovative and efficient turn-key solutions. For quantum engineers, powerful circuit building blocks. Turn-key implementations of algorithms for data scientists, financial analysts, engineers. Explore problems in binary optimization and machine learning on simulators and real hardware. You don't need to have any prior experience in quantum computing. To load classical data into quantum states, use NISQ data loader devices. Circuit building blocks are available for linear algebra with distance estimation or matrix multiplication circuits. You can create your own algorithms using our circuit building blocks. You can get a significant performance boost with D-Wave hardware. Also, the latest gate-based improvements will help you. Quantum data loaders and algorithms offer guaranteed speed-ups in clustering, classification, regression.