Bulletin of the American Physical Society
APS March Meeting 2023
Volume 68, Number 3
Las Vegas, Nevada (March 5-10)
Virtual (March 20-22); Time Zone: Pacific Time
Session A70: Machine Learning and Quantum Simulation
8:00 AM–11:00 AM,
Monday, March 6, 2023
Room: Room 409
Sponsoring
Unit:
DQI
Chair: Daoheng Niu, University of Texas at Austin
Abstract: A70.00008 : Quantum Boundary Integral Algorithm for linear and nonlinear PDEs in Quantum Computation of Fluid Dynamics
9:24 AM–9:36 AM
Presenter:
Sachin Satish Bharadwaj
(New York University (NYU))
Authors:
Sachin Satish Bharadwaj
(New York University (NYU))
Balu Nadiga
(LANL)
Stephan Eidenbenz
(Los Alamos National Laboratory)
K. R Sreenivasan
(Department, Courant Institute of Mathema)
In this setting, and with a view to permit end-to-end solutions, we have developed a high performance quantum simulator called QuON; QuON is specifically designed for simulating fluid flows using QC. Using QuOn, the time-dependent Poiseuille and Couette flows are solved as initial examples to demonstrate, for the first time, a high precision, fully gate level implementation of a QLSA method for a CFD simulation. Next, we propose a Quantum Boundary Integral Algorithm (QBIA) formulation that seeks to solve nonlinear partial differential equations by combining the Homotopy Analysis Method (HAM) with QLSA. We expect that our integral formulation is better suited for QC than the usual methods that focus on discretizing the strong differential form of the governing dynamics, both in terms of accuracy and efficiency. We discuss some preliminary efforts to solve a 1D Burgers flow using this approach. Along with this we also aim at evaluating the minimum requirements as well as the potential and obstacles for transitioning from computational fluid dynamics (CFD) to Quantum Computation of Fluid Dynamics (QCFD).
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