7 papers
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…
Statistical Quantum Phase Estimation: Extensions and Practical Considerations
Amit Surana, Brandon Allen
We present several refinements and extensions of the statistical quantum phase estimation (SQPE) framework to address some of its key practical limitations, improving its applicabi…
Solving Constrained Optimization Problems Using Hybrid Qubit-Qumode Quantum Devices
Rishab Dutta, Brandon Allen, Chuzhi Xu +8
Variational Quantum Algorithms (VQAs) provide a promising framework for tackling complex optimization problems on near-term quantum hardware. Here, we demonstrate that hybrid qubit…
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…