A quantum machine learning surrogate based on parameterized circuits with data re-uploading approximates the full BGK collision dynamics in LBM across all admissible relaxation parameters and is validated on Taylor-Green vortex and double shear layer benchmarks.
Budinski, Quantum algorithm for the advection–diffusion equation simulated with the lattice boltzmann method, Quantum Information Processing 20 (2) (2021)
3 Pith papers cite this work. Polarity classification is still indexing.
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Demonstration of quantum circuit implementation for 2D obstacle flow via Carleman-linearized LBM solved with QSVT, achieving logarithmic qubit and gate scaling with lattice points.
A quantum algorithm for evolving Schwarzschild spacetime in the WEBB NR formalism is implemented in Qiskit and tested on simulators and IBM quantum computers.
citing papers explorer
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A Quantum-Classical Surrogate Model for the Collision Operator of the Lattice Boltzmann Method
A quantum machine learning surrogate based on parameterized circuits with data re-uploading approximates the full BGK collision dynamics in LBM across all admissible relaxation parameters and is validated on Taylor-Green vortex and double shear layer benchmarks.
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A Demonstration of Quantum Circuit Implementation for Obstacle Flow Using Carleman-Linearized Lattice Boltzmann Method
Demonstration of quantum circuit implementation for 2D obstacle flow via Carleman-linearized LBM solved with QSVT, achieving logarithmic qubit and gate scaling with lattice points.