1.5k citations · 11.2k across the 149 of their papers we have counts for
153 papers
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…
Do Quantum Models Scale Like LLMs?
David S. Berman, Ying-Jer Kao, Roger G. Melko +1
In this work, we study the neural scaling laws of RydbergGPT, an autoregressive transformer model trained on qubit projective measurement data gathered from interacting Rydberg ato…
Quantum phases in endofullerene zigzag chains
Tobias Serwatka, Muhammad Shaeer Moeed, Roger G. Melko +1
We employ large-scale density matrix renormalization group calculations to study the quantum phases of dipolar molecules confined in bent (zigzag) endofullerene chains, as a functi…
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,…
Unlearnable phases of matter
Tarun Advaith Kumar, Yijian Zou, Amir-Reza Negari +2
We identify fundamental limitations in machine learning by demonstrating that non-trivial mixed-state phases of matter are computationally hard to learn. Focusing on unsupervised l…