5 citations · 8 across the 12 of their papers we have counts for
6 papers · 1 filter
Quantum Data Loading for Carleman Linearized Systems: Application to the Lattice-Boltzmann Equation
Reuben Demirdjian, Thomas Hogancamp, Abeynaya Gnanasekaran +2
Nonlinear ordinary and partial differential equations are ubiquitous in science and engineering, yet finding their solutions is often computationally intractable for classical hard…
Quantum Lattice Boltzmann Solutions for Transport under 3D Spatially Varying Advection on Trapped Ion Hardware
Sayonee Ray, Jezer Jojo, Jason Iaconis +5
The Quantum Lattice Boltzmann Method (QLBM) has emerged as one of the most promising quantum computing approaches for the numerical simulation of problems in computational fluid dy…
Efficient Quantum Access Model for Sparse Structured Matrices using Linear Combination of Things
Abeynaya Gnanasekaran, Amit Surana
We present a novel framework for Linear Combination of Unitaries (LCU)-style decomposition tailored to structured sparse matrices, which frequently arise in the numerical solution…
Variational Quantum Framework for Nonlinear PDE Constrained Optimization Using Carleman Linearization
Abeynaya Gnanasekaran, Amit Surana, Hongyu Zhu
We present a novel variational quantum framework for nonlinear partial differential equation (PDE) constrained optimization problems. The proposed work extends the recently introdu…
Variational Quantum Framework for Partial Differential Equation Constrained Optimization
Amit Surana, Abeynaya Gnanasekaran
We present a novel variational quantum framework for linear partial differential equation (PDE) constrained optimization problems. Such problems arise in many scientific and engine…
Efficient Variational Quantum Linear Solver for Structured Sparse Matrices
Abeynaya Gnanasekaran, Amit Surana
We develop a novel approach for efficiently applying variational quantum linear solver (VQLS) in context of structured sparse matrices. Such matrices frequently arise during numeri…