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Quasiprobabilistic state-overlap estimator for NISQ devices
Leonardo Guerini, Roeland Wiersema, Juan Felipe Carrasquilla +1
As quantum technologies mature, the development of tools for benchmarking their ability to prepare and manipulate complex quantum states becomes increasingly necessary. A key conce…
Measurement-induced entanglement phase transitions in variational quantum circuits
Roeland Wiersema, Cunlu Zhou, Juan Felipe Carrasquilla +1
Variational quantum algorithms (VQAs), which classically optimize a parametrized quantum circuit to solve a computational task, promise to advance our understanding of quantum many…
Optimal control of quantum thermal machines using machine learning
Ilia Khait, Juan Carrasquilla, Dvira Segal
Identifying optimal thermodynamical processes has been the essence of thermodynamics since its inception. Here, we show that differentiable programming (DP), a machine learning (ML…
Neural Error Mitigation of Near-Term Quantum Simulations
Elizabeth R. Bennewitz, Florian Hopfmueller, Bohdan Kulchytskyy +2
Near-term quantum computers provide a promising platform for finding ground states of quantum systems, which is an essential task in physics, chemistry, and materials science. Near…
Neural networks in quantum many-body physics: a hands-on tutorial
Juan Carrasquilla, Giacomo Torlai
Over the past years, machine learning has emerged as a powerful computational tool to tackle complex problems over a broad range of scientific disciplines. In particular, artificia…