Quantum computing presents a possible paradigm shift in computing, given its advantages in memory and speed. However, there is a growing need to demonstrate its utility in solving practical problems that are nonlinear, such as in fluid dynamics, which is the subject of this work. To facilitate this objective, it is essential to have a dedicated toolkit that enables the development, testing, and simulation of new quantum algorithms and flow problems, taken together. To this end, we present here a high performance, quantum computational simulation package called Quantum Flow Simulator (QFlowS), designed for computational fluid dynamics simulations. QFlowS is a versatile tool that can create and simulate quantum circuits using an in-built library of fundamental quantum gates and operations. We outline here all its functionalities with illustrations. Algorithms to solve flow problems can be built using the expanding list of the core functionalities of QFlowS with its hybrid quantum–classical type workflow. This is demonstrated here by solving an example, one-dimensional, diffusion flow problem. These simulations serve as a check on the algorithm's correctness as well as an ideal test-bed for making them more efficient and better suited for near-term quantum computers for addressing flow problems.
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October 2024
Research Article|
October 03 2024
QFlowS: Quantum simulator for fluid flows
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Sachin S. Bharadwaj
Sachin S. Bharadwaj
a)
(Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Software, Visualization, Writing – original draft, Writing – review & editing)
Department of Mechanical and Aerospace Engineering, New York University
, New York, New York 11201, USA
a)Author to whom correspondence should be addressed: [email protected]
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a)Author to whom correspondence should be addressed: [email protected]
Physics of Fluids 36, 107112 (2024)
Article history
Received:
June 28 2024
Accepted:
September 13 2024
Citation
Sachin S. Bharadwaj; QFlowS: Quantum simulator for fluid flows. Physics of Fluids 1 October 2024; 36 (10): 107112. https://doi.org/10.1063/5.0226074
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