6 papers
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…
Quantum Randomized Subspace Iteration
Stefano Scali, Brian Coyle, Giuseppe Buonaiuto +1
Resolving degenerate quantum eigenspaces - including topologically ordered ground states and frustrated magnets - requires preparing high-fidelity states that span every direction…
Purified phase estimation samples spectra efficiently
Stefano Scali, Josh Kirsopp, Antonio Márquez Romero +1
Quantum phase estimation (QPE) is a cornerstone algorithm for extracting Hamiltonian eigenvalues, but its standard, eigenstate-centric form relies on carefully prepared coherent in…
Polaritonic Machine Learning for Graph-based Data Analysis
Yuan Wang, Stefano Scali, Oleksandr Kyriienko
Photonic and polaritonic systems offer a fast and efficient platform for accelerating machine learning (ML) through physics-based computing. To gain a computational advantage, howe…
Quantum community detection via deterministic elimination
Chukwudubem Umeano, Stefano Scali, Oleksandr Kyriienko
We propose a quantum algorithm for calculating the structural properties of complex networks and graphs. The corresponding protocol -- deteQt -- is designed to perform large-scale…
Addressing the Readout Problem in Quantum Differential Equation Algorithms with Quantum Scientific Machine Learning
Chelsea A. Williams, Stefano Scali, Antonio A. Gentile +2
Quantum differential equation solvers aim to prepare solutions as -qubit quantum states over a fine grid of points, surpassing the linear scaling of classical solvers.…