Intel Quantum Simulator

Cirq is a Python software library for writing, manipulating, and optimizing quantum circuits, and then running them on quantum computers and quantum simulators. Cirq provides useful abstractions for dealing with today’s noisy intermediate-scale quantum computers, where details of the hardware are vital to achieving state-of-the-art results. Cirq comes with built-in simulators, both for wave functions and for density matrices. These can handle noisy quantum channels using monte carlo or full density matrix simulations. In addition, Cirq works with a state-of-the-art wavefunction simulator: qsim. These simulators can be used to mock quantum hardware with the quantum virtual machine. Cirq is used to run experiments on Google's quantum processors. Learn more about the latest experiments and access the code to se how to run them yourself.

Unique and efficient turn-key algorithms for data scientists. Powerful circuit building blocks for quantum engineers. Turn-key algorithm implementations for data scientists, financial analysts, and engineers. Explore problems in binary optimization, machine learning, linear algebra, and monte carlo sampling on simulators and real quantum hardware. No prior experience with quantum computing is required. Use NISQ data loader circuits to load classical data into quantum states to use with your algorithms. Use circuit building blocks for linear algebra with distance estimation and matrix multiplication circuits. Use our circuit building blocks to create your own algorithms. Get a significant performance boost for D-Wave hardware and use the latest improvements for gate-based approaches. Try out quantum data loaders and algorithms with guaranteed speed-ups on clustering, classification, and regression.