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qlbm -- A Quantum Lattice Boltzmann Software Framework

Călin A. Georgescu, Merel A. Schalkers, Matthias Möller

TL;DR

qlbm delivers an end-to-end Python framework for developing, simulating, and analyzing Quantum Lattice Boltzmann Methods (QBMs). It introduces a modular quantum component architecture (primitives, operators, algorithms) and system-level separation (Lattice, Infrastructure, SimulationConfig) to enable rapid prototyping across multiple QBMs such as QTM and STQBM. The paper presents novel performance enhancements, including ancilla reuse, adaptable registers, classical preprocessing, statevector snapshots, sampling, and reinitialization, demonstrated on 2D and 3D simulations with CPU and GPU backends and cross-vendor compilers. By providing extensive testing, documentation, visualization, and a replication package, qlbm aims to accelerate QBM research, enhance reproducibility, and foster collaboration in quantum CFD.

Abstract

We present qlbm, a Python software package designed to facilitate the development, simulation, and analysis of Quantum Lattice Boltzmann Methods (QBMs). qlbm is a modular framework that introduces a quantum component abstraction hierarchy tailored to the implementation of novel QBMs. The framework interfaces with state-of-the-art quantum software infrastructure to enable efficient simulation and validation pipelines, and leverages novel execution and pre-processing techniques that significantly reduce the computational resources required to develop quantum circuits. We demonstrate the versatility of the software by showcasing multiple QBMs in 2D and 3D with complex boundary conditions, integrated within automated benchmarking utilities. Accompanying the source code are extensive test suites, thorough online documentation resources, analysis tools, visualization methods, and demos that aim to increase the accessibility of QBMs while encouraging reproducibility and collaboration. The source code of qlbm is publicly available under a permissive MPL 2.0 license at https://github.com/QCFD-Lab/qlbm.

qlbm -- A Quantum Lattice Boltzmann Software Framework

TL;DR

qlbm delivers an end-to-end Python framework for developing, simulating, and analyzing Quantum Lattice Boltzmann Methods (QBMs). It introduces a modular quantum component architecture (primitives, operators, algorithms) and system-level separation (Lattice, Infrastructure, SimulationConfig) to enable rapid prototyping across multiple QBMs such as QTM and STQBM. The paper presents novel performance enhancements, including ancilla reuse, adaptable registers, classical preprocessing, statevector snapshots, sampling, and reinitialization, demonstrated on 2D and 3D simulations with CPU and GPU backends and cross-vendor compilers. By providing extensive testing, documentation, visualization, and a replication package, qlbm aims to accelerate QBM research, enhance reproducibility, and foster collaboration in quantum CFD.

Abstract

We present qlbm, a Python software package designed to facilitate the development, simulation, and analysis of Quantum Lattice Boltzmann Methods (QBMs). qlbm is a modular framework that introduces a quantum component abstraction hierarchy tailored to the implementation of novel QBMs. The framework interfaces with state-of-the-art quantum software infrastructure to enable efficient simulation and validation pipelines, and leverages novel execution and pre-processing techniques that significantly reduce the computational resources required to develop quantum circuits. We demonstrate the versatility of the software by showcasing multiple QBMs in 2D and 3D with complex boundary conditions, integrated within automated benchmarking utilities. Accompanying the source code are extensive test suites, thorough online documentation resources, analysis tools, visualization methods, and demos that aim to increase the accessibility of QBMs while encouraging reproducibility and collaboration. The source code of qlbm is publicly available under a permissive MPL 2.0 license at https://github.com/QCFD-Lab/qlbm.

Paper Structure

This paper contains 33 sections, 5 equations, 19 figures.

Table of Contents

  1. Introduction
  2. Software and QBM Research
  3. Lattice Boltzmann Methods
  4. qlbm Overview
  5. Internal Architecture
  6. Quantum Component Architecture
  7. System Architecture
  8. Performance Enhancements
  9. Algorithmic Improvements
  10. Ancilla qubit reuse.
  11. Adaptable register setup.
  12. Classical logic computation.
  13. Computational Improvements
  14. Statevector snapshots.
  15. Statevector sampling.
  16. ...and 18 more sections

Figures (19)

  • Figure 1: Overview of end-to-end qlbm workflow.
  • Figure 2: Representation of internal quantum circuit abstraction hierarchy.
  • Figure 3: Comparison of qlbm primitive quantum circuits.
  • Figure 4: Sample qlbm operator code.
  • Figure 5: Class diagram representation of the qlbm quantum component architecture.
  • ...and 14 more figures