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Autonomous phase discovery
Shiyu Zhou, Yuxuan Zhang, Sebastian Wetzel +2
Understanding quantum phases of matter has long relied on physicists' intuition and mathematical tools such as symmetry and topology. Remarkably successful as these approaches have…
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…
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,…
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…
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…
Probing Defects with Quantum Simulator Snapshots
Abhijat Sarma, Nayan Myerson-Jain, Yue Liu +4
Snapshots, i.e. projective measurements of local degrees of freedom, are the most standard data taken in experiments on quantum simulators. Snapshots are usually used to probe loca…