Search Results for "backend"

Mitiq is a Python toolkit for implementing error mitigation techniques on quantum computers. Current quantum computers are noisy due to interactions with the environment, imperfect gate applications, state preparation and measurement errors, etc. Error mitigation seeks to reduce these effects at the software level by compiling quantum programs in clever ways.

...Yao supports both forward-mode (faithful gradient) and reverse-mode automatic differentiation with its builtin engine optimized specifically for quantum circuits. Top performance for quantum circuit simulations. Its CUDA backend and batched quantum register support can make typical quantum circuits even faster. Yao is designed to be extensible. Its hierarchical architecture allows you to extend the framework to support and share your new algorithm and hardware.

Tequila is an abstraction framework for (variational) quantum algorithms. It operates on abstract data structures allowing the formulation, combination, automatic differentiation and optimization of generalized objectives. Tequila can execute the underlying quantum expectation values on state-of-the-art simulators as well as on real quantum devices.

Variational Quantum Circuit Simulator for Quantum Computation Research. Qulacs is a Python/C++ library for fast simulation of large, noisy, or parametric quantum circuits. Qulacs is developed at QunaSys, Osaka University, NTT, and Fujitsu.

The Blueqat project has been renamed the Qaqarot Project because of the branding strategy of blueqat inc.