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Introduction

HQS Quantum Solver gives you the ability to reduce the size of your quantum problem by letting you select the relevant subspaces. It will then provide you the relevant Hamiltonians and Operators. This documentation is geared towards spin systems, but the Quantum Solver can also address fermionic and bosonic problems.

Schematic overwiew of HQS Quantum Solver

Providing a consistent and extensible interface, it offers routines for the construction of Hamiltonians and operators in either full configurational space or subspaces characterized by conserved quantities such as the spin or the particle number.

Applications

HQS Quantum Solver is a powerful tool for researchers and enthusiasts in the field of spin physics, quantum computing, and beyond. It can be used for a wide range of applications, including but not limited to:

  • Evaluating dynamic correlation functions for spin problems.

  • Calculate expectation values, static correlation functions, and eigenenergies.

  • Simulating coherent and incoherent time-evolution of spin.

  • For advanced users: studying interacting lattice models.

Getting started

HQS Quantum Solver is a tool that can be used in conjunction with other HQStage modules by HQS Quantum Simulations GmbH. To install this module run

hqstage install hqs-quantum-solver

To use HQS Quantum Solver, you furthermore need to install the Intel Math Kernel Library (MKL), which can be done in three different ways.

  1. You can use HQStage to install the MKL into the currently active virtual environment.

    hqstage install mkl

  2. You can manually provide a version of the MKL by making sure that the file libmkl_rt.so is found by the dynamic linker. That means, that a system-wide installation should be found automatically.

  3. You can install the MKL via pip.

    pip install mkl

For a collection of examples to start using HQS Quantum Solver please refer to the Quick Start chapter.

Features

  • Enables exploitation of symmetries like spin conservation, particle number, or the fermion parity.

  • Flexible choice of combinations of subspaces, allows the choice of excitation subspaces adapted to your problem.

  • Calculation of static and dynamical correlations functions in frequency domain including the correction vector approach and the expansion in Chebyshev polynomials.

  • Krylov-based master equation solver, which is faster than QuTip in many regimes.

  • Extensibility: HQS Quantum Solver allows users to integrate their own backends, tools, and algorithms.

  • Interoperable: Integrates well with the scientific Python ecosystem, especially with NumPy and SciPy.

The API documentation can be found here.