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quant-ph2025
Assessing Quantum Advantage for Gaussian Process Regression
Dominic Lowe, M. S. Kim, Roberto Bondesan
Gaussian Process Regression is a well-known machine learning technique for which several quantum algorithms have been proposed. We show here that in a wide range of scenarios these…
quant-ph2025
Efficient Learning of Long-Range and Equivariant Quantum Systems
Å tÄpán Å mÃd, Roberto Bondesan
In this work, we consider a fundamental task in quantum many-body physics - finding and learning ground states of quantum Hamiltonians and their properties. Recent works have studi…
quant-ph2024
Accurate Learning of Equivariant Quantum Systems from a Single Ground State
Å tÄpán Å mÃd, Roberto Bondesan
Predicting properties across system parameters is an important task in quantum physics, with applications ranging from molecular dynamics to variational quantum algorithms. Recentl…