Machine Learning and Quantum Many-Body Physics

Workshop

When

  • All Day

  • All Day

Where

162 Fifth Avenue, 9th Floor Classroom

160 Fifth Avenue

New York, NY 10010

This workshop brings together a small number of researchers from quantum physics; condensed matter physics; machine learning; and computer science to discuss applications of machine learning tools and methods to challenging problems in many-body physics, and how ideas from quantum many-body could be applied to machine learning.

Agenda

Thursday, April 26

8:00 – 9:00 AM

Breakfast

9:00 – 9:10 AM Giuseppe Carleo, Miles Stoudenmire Welcome and Introduction
Morning Session
9:15 – 9:40 AM Roger Melko (University of Waterloo) Research at Perimeter’s Quantum Intelligence Lab
9:40 – 10:05 AM Lei Wang (Chinese Academy of Science) Neural Network Renormalization Group
10:05 – 10:30 AM Ivan Glasser (Max Planck Institute of Quantum Optics) Duality between neural networks and tensor networks with
applications to chiral topological states and supervised learning
10:30 – 11:00 AM Break
11:00 – 11:30 AM Discussion
11:30 – 11:55 AM Dries Sels (Boston University) Reinforcement learning quantum optimal control
11:55 – 12:20 PM Dong Ling Deng (University of Maryland) Measuring Quantum Entanglement Entropy through Restricted
Boltzmann Machine
12:20- 12:45 PM Titus Neupert (University of Zurich) Neural networks for quantum many-body calculations: Including
Symmetries and reaching excited states
12:45 – 2:45 PM Lunch and Discussion
Afternoon Session
2:45 – 3:10 PM Masatoshi Imada (University of Tokyo) Boltzmann machine for quantum ground states and hidden-structure
analyses of experimental data
3:10 – 3:35 PM Giacomo Torlai (University of Waterloo) Neural-network quantum state tomography
3:35 – 4:00 PM Markus Heyl (Max Planck Inst. for the Physics of Complex Systems) Quantum dynamics with classical networks and machine learning
4:00- 4:45 PM Break and Discussion
4:45 – 5:30 PM Hot Topics- Jan Budich Lode Pollet, Steven Clark, Andrea Rocchetto
5:30 – 6:30 PM Posters

Friday, April 27

8:00 – 9:00 AM

Breakfast

Morning Session
9:00 – 9:25 AM Simon Trebst (University of Cologne) Quantum phase recognition
9:25 – 9:50 AM Eun-Ah Kim (Cornell University) Learning Quantum Emergence with AI
9:50 – 10:15 AM Kyle Cranmer (New York University) Quantum Inference
10:15 – 11:15 AM Break and Discussion
11:15 – 11:40 PM Yoav Levine (The Hebrew University of Jerusalem) Bridging Many-Body Physics and Deep Learning via Tensor Networks
11:40 – 12:05 PM Evert van Nieuwenberg (California Institute of Technology) Learning a phase diagram from dynamics
12:05 – 12:30 PM Juan Carrasquilla (Vector Institute) Toward learning quantum states with generative models
12:30 – 3:00 PM Lunch, Discussion and Departure

More Events

Speakers

Pilar Cossio, Jutta Rogal

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November 16–18, 2026

Speakers

Angel Rubio, Timothy Berkelbach, Jutta Rogal, Ankit Mahajan, Diptarka Hait, + 2 more

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