Year: 2026
Type: article
Abstract: When learning descriptions of many-body quantum systems, assuming locality of interactions can dramatically reduce the required number of observations and computational time compared to unstructured approaches. In this work, we uncover an infinite-dimensional instance of this phenomenon, initiating the study of Hamiltonian learning for positive-temperature bosonic Gaussian states. We present sample- and computationally efficient protocols for inferring the parameters and graph structure of underlying quadratic Hamiltonians, provided that temperature, squeezing, displacement, and the interaction graph’s maximal degree are bounded. Notably, our protocol relies solely on heterodyne measurements, which are often experimentally feasible, and achieves a sample complexity that scales only logarithmically with the number of modes. Furthermore, our techniques allow for the learning of positive-temperature Gaussian states in trace distance with quadratic scaling in precision and polynomial scaling in the number of modes.
Source: Nature Communications
Institutions: Universitat Autònoma de Barcelona, Télécom Paris, University of Copenhagen, Institut national de recherche en sciences et technologies du numérique, Institut Polytechnique de Paris, Laboratoire Traitement et Communication de l’Information, Centre Inria de Saclay, QURIOSITY: Communication et Traitement Quantiques de l'Information, Lyon 1 Université, École Normale Supérieure de Lyon, Centre National de la Recherche Scientifique, Laboratoire de l'Informatique du Parallélisme, QINFO: Traitement optimal de l'information avec des dispositifs quantiques
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $6,990
Awards: G1175115578, G1190173965, G120905174, Efficient Conversion of Quantum Information Resources, G1272927172, Quantum trajectories, G2064873908, G210041235, G2262748287, G2452073530, G2462415295, G2601397997, Initiative Nationale Hybride HPC Quantique – R&D et Support des communautés, G2988934680, G3005324705, G300979063, G34346518, G3480869486, G3546882995, G357246561, G3606912791, G3681454997, G3693981238, G4042783231, G4105022999, G425668148, G4526231891, G5080475149, G5195188938, G5296751580, G531036588, G5922099756, G6701137214, G69051668, G6934589879, G7084143925, G7352392636
OpenAlex ID: W4404390522