Search results
Results from the WOW.Com Content Network
Quantum chemistry computer programs are used in computational chemistry to implement the methods of quantum chemistry. Most include the Hartree–Fock (HF) and some post-Hartree–Fock methods. They may also include density functional theory (DFT), molecular mechanics or semi-empirical quantum chemistry methods .
QuTiP, short for the Quantum Toolbox in Python, is an open-source computational physics software library for simulating quantum systems, particularly open quantum systems. [1] [2] QuTiP allows simulation of Hamiltonians with arbitrary time-dependence, allowing simulation of situations of interest in quantum optics, ion trapping, superconducting circuits and quantum nanomechanical resonators.
Qiskit (Quantum Information Software Kit) is an open-source software development kit (SDK) for working with quantum Computers at the level of circuits, pulses, and algorithms. It provides tools for creating and manipulating quantum programs and running them on prototype quantum devices on IBM Quantum Platform or on simulators on a local computer.
qBraid Lab by qBraid [10] is a cloud-based platform for quantum computing. It provides software tools for researchers and developers in quantum, as well as access to quantum hardware. qBraid provides cloud based access to IBM and Amazon Braket devices including IBM, Xanadu, OQC, QuEra, Amazon Braket simulators, Rigetti, and IonQ as of August 2023.
Free open source: ms-2.de: OpenMM: No No Yes Yes Yes Yes No Yes Yes High Performance MD, highly flexible, Python scriptable Free open source MIT: OpenMM: Orac: No No Yes Yes No Yes No Yes No Molecular dynamics simulation program to explore free energy surfaces in biomolecular systems at the atomic level Free open source: Orac download page ...
Quantum programming is the process of designing or assembling sequences of instructions, called quantum circuits, using gates, switches, and operators to manipulate a quantum system for a desired outcome or results of a given experiment.
Cirq was developed by the Google AI Quantum Team, and the public alpha was announced at the International Workshop on Quantum Software and Quantum Machine Learning on July 18, 2018. [2] A demo by QC Ware showed an implementation of QAOA solving an example of the maximum cut problem being solved on a Cirq simulator.
Unlike the approach taken by other quantum-enhanced machine learning algorithms, HQMMs can be viewed as models inspired by quantum mechanics that can be run on classical computers as well. [90] Where classical HMMs use probability vectors to represent hidden 'belief' states, HQMMs use the quantum analogue: density matrices .