Quriust

Simulate quantum circuits, state-vectors, and density matrices with high performance. Utilizes multithreading, GPUs, and distribution. Stand-alone, requires no installation.

Solve time-dependent open quantum systems efficiently in parallel. Supports general systems like Jaynes-Cummings and spin-boson models, plus quantum information features.

Accelerate quantum circuit simulation using a fast, lightweight, modular library written in Assembly. Supports x86 and ARM64 architectures for high-performance computation.

Quantum Computing library leveraging graph building to build efficient quantum circuit simulations.

Achieve high-performance quantum circuit simulation on distributed systems. Optimized for multi-core and multi-node architectures using MPI for scalable state vector representation.

Simulate Quil programs efficiently with a high-performance, featureful virtual machine. Model quantum computer characteristics and deploy as a binary or server.

Provides pure, safe, and standard Rust bindings for the high-performance Qrack quantum simulator. Leverage Qrack's OpenCL acceleration within Rust applications.

Access a fast C++11/OpenCL quantum simulator from Python. Supports OpenCL acceleration, zero-copy mode, and integration with PyZX for circuit optimization.

Framework for full-stack quantum computing development, via high performance and fundamentally optimized simulation. The intent of "Qrack" is to provide maximum performance for the simulation of an ideal, virtually error-free quantum computer, across the broadest possible set of hardware and operating systems.