193 citations · 288 across the 15 of their papers we have counts for
5 papers · 1 filter
Effective-Hamiltonian Quantum Solvers for Differential Equations: Alternative Constructions and Function Encodings
Annie E. Paine
Differential equations can be encoded as ground-state problems by constructing a positive-semidefinite effective Hamiltonian whose minimum-energy state represents the solution. We…
OpenQARP: a modular framework for quantum application research
Stefano Scali, Vicente P. Soloviev, Antonio Márquez Romero +7
We introduce OpenQARP, the Open Quantum Application Research Package: an open-source Python framework for quantum application research, built on a compiled C++ core. In OpenQARP, a…
Benchmarking a machine-learning differential equations solver on a neutral-atom logical processor
Pauline Mathiot, Elio Garnaoui, Axel-Ugo Leriche +37
We report on a performance comparison between physical and logical computations on a prototypical machine-learning application: solving differential equations using quantum kernel…
A unified quantum computing quantum Monte Carlo framework through structured state preparation
Giuseppe Buonaiuto, Antonio Marquez Romero, Brian Coyle +4
We extend Quantum Computing Quantum Monte Carlo (QCQMC) beyond ground-state energy estimation by systematically constructing the quantum circuits used for state preparation. Replac…
Weak forms offer strong regularisations: how to make physics-informed (quantum) machine learning more robust
Annie E. Paine, Smit Chaudhary, Antonio A. Gentile
Physics-informed (PI) methodologies have surged to become a pillar route to solve Differential Equations (DEs), sustained by the growth of machine learning methods in scientific co…