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The Quantum Tensor network Emulator Applications

The Quantum

Tensor-network
Emulator
Applications

The Quantum

Tensor-network
Emulator
Applications
about

About

The Quantum TEA combines a suite of applications using tensor network methods to simulate quantum systems and solve machine learning tasks.

 

Applications

Quantum TEA

The Quantum Tensor network Emulator Applications combines a suite of applications using tensor network methods to simulate quantum systems and solve machine learning tasks.

Quantum Green TEA

It solves the static and time-dependent Schrödinger equation and Lindblad equation, e.g., one can simulate ground states, finite temperature states, and time evolutions.

Quantum Matcha TEA

It is a quantum computer emulator powered by matrix product states. It is designed to simulate quantum circuits with a large number of qubits and defined with the Qiskit API or directly from your Python API without worrying about backends.

Quantum TEA

The Quantum Tensor network Emulator Applications combine a suite of applications using tensor network methods to simulate quantum systems and solve machine learning tasks.

Quantum Green TEA

Quantum green TEA solves the static and time-dependent Schrödinger equation and Lindblad equation, e.g., one can simulate ground states, finite temperature states, and time evolutions.

Quantum Matcha TEA

Quantum matcha TEA simulates quantum circuits via matrix product states. The backends for the simulation are tunable between CPUs and GPUs as well as between python and fortran and are scalable up to MPI towards running on HPC clusters.

Quantum Red TEA

Quantum red TEA contains the tensor libraries on which Quantum green TEA, Quantum matcha TEA, and Quantum chai TEA rely on for their tensor operations. Here, we provide the interfaces to BLAS/LAPACK and CUDA for the higher-level applications.

Quantum Chai TEA

Quantum chai TEA contains the machine learning applications using tensor networks.

Quantum TEA leaves

Auxiliary libraries, python-fortran interfaces, and python solutions for common tensor network geometries are combined in this part of the quantum TEA library.

Quantum Chai TEA

It contains the machine learning applications using tensor networks.

Quantum Red TEA

It contains the tensor libraries on which Quantum green TEA, Quantum matcha TEA, and Quantum chai TEA rely on for their tensor operations. Here, we provide the interfaces to BLAS/LAPACK and CUDA for the higher-level applications.

Quantum TEA leaves

Auxiliary libraries, Python-FORTRAN interfaces, and Python solutions for common tensor network geometries are combined in this part of the quantum TEA library.

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