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quant-ph2026

Diffusion-warm sampling of the XY model enables fast thermalization at scale

Sehmimul Hoque, Roger Melko, Pooya Ronagh

We introduce a novel technique for scalable sampling of spin-system states with continuous symmetries using diffusion models. By applying our approach to the XY model, a fundamenta…

quant-ph2026

Distributions of Noisy Expectation Values over Sets of Measurement Operators

Matthew Duschenes, Roger G. Melko, Juan Carrasquilla +1

Expectation values of measurement operators, interpreted as measurement probabilities, arise frequently throughout quantum algorithms. When quantum states are randomly distributed,…

quant-ph2026

Taming multiparty entanglement at measurement-induced phase transitions

Liuke Lyu, James Allen, Yi Hong Teoh +2

Measurement-induced phase transitions (MIPT) give rise to novel dynamical states of quantum matter realized by balancing unitary evolution and measurements. We present large-scale…

quant-ph2025

Artificial Intelligence for Quantum Computing

Yuri Alexeev, Marwa H. Farag, Taylor L. Patti +25

Artificial intelligence (AI) advancements over the past few years have had an unprecedented and revolutionary impact across everyday application areas. Its significance also extend…

quant-ph2025

Beyond-classical computation in quantum simulation

Andrew D. King, Alberto Nocera, Marek M. Rams +60

Quantum computers hold the promise of solving certain problems that lie beyond the reach of conventional computers. However, establishing this capability, especially for impactful…

quant-ph2025

Autoregressive Typical Thermal States

Tarun Advaith Kumar, Leon Balents, Timothy H. Hsieh +1

A variety of generative neural networks recently adopted from machine learning have provided promising strategies for studying quantum matter. In particular, the success of autoreg…