Quantum-centric supercomputing for materials science: A perspective on challenges and future directions
Computational models are an essential tool for the design, characterization, and discovery
of novel materials. Computationally hard tasks in materials science stretch the limits of …
of novel materials. Computationally hard tasks in materials science stretch the limits of …
Towards provably efficient quantum algorithms for large-scale machine-learning models
Large machine learning models are revolutionary technologies of artificial intelligence
whose bottlenecks include huge computational expenses, power, and time used both in the …
whose bottlenecks include huge computational expenses, power, and time used both in the …
Improved quantum algorithms for linear and nonlinear differential equations
H Krovi - Quantum, 2023 - quantum-journal.org
We present substantially generalized and improved quantum algorithms over prior work for
inhomogeneous linear and nonlinear ordinary differential equations (ODE). Specifically, we …
inhomogeneous linear and nonlinear ordinary differential equations (ODE). Specifically, we …
Exponential quantum speedup in simulating coupled classical oscillators
We present a quantum algorithm for simulating the classical dynamics of 2 n coupled
oscillators (eg, 2 n masses coupled by springs). Our approach leverages a map** …
oscillators (eg, 2 n masses coupled by springs). Our approach leverages a map** …
Quantum simulation of partial differential equations: Applications and detailed analysis
We study a recently introduced simple method [S. **, N. Liu, and Y. Yu, Quantum simulation
of partial differential equations via Schrödingerisation, ar** quantum algorithms to efficiently simulate dynamics beyond …
of partial differential equations via Schrödingerisation, ar** quantum algorithms to efficiently simulate dynamics beyond …