Collection Number C19025
Description

Machine learning techniques are rapidly being adopted into the field of quantum many-body physics including condensed matter theory experiment and quantum information science.  The steady increase in data being produced by highly-controlled quantum experiments brings the potential of machine learning algorithms to the forefront of scientific advancement.  Particularly exciting is the prospect of using machine learning for the discovery and design of quantum materials devices and computers.  In order to make progress the field must address a number of fundamental questions related to the challenges of studying many-body quantum mechanics using classical computing algorithms and hardware. The goal of this conference is to bring together experts in computational physics machine learning and quantum information to make headway on a number of related topics including: Data-drive quantum state reconstruction Machine learning strategies for quantum error correction Neural-network based wavefunctions Near-term prospects for data from quantum devices Machine learning for quantum algorithm discovery Registration for this event is now closed

Collection Type Conference/School
Source PIRSA
Title Speaker(s) Date Series/Collection Type Institution Repository Info
Goodbye and Closing Remarks Roger Melko 2019‑07‑12 Machine Learning for Quantum Design Conference Perimeter Institute PIRSA View details
Differentiable Programming Tensor Networks and Quantum Circuits Lei Wang 2019‑07‑12 Machine Learning for Quantum Design Conference Perimeter Institute PIRSA View details
RL-driven Quantum Computation Pooya Ronagh 2019‑07‑12 Machine Learning for Quantum Design Conference Perimeter Institute PIRSA View details
Glassy and Correlated Phases of Optimal Quantum Control Marin Bukov 2019‑07‑12 Machine Learning for Quantum Design Conference Perimeter Institute PIRSA View details
Neural Belief-Propagation Decoders for Quantum Error-Correcting Codes Yehua Liu 2019‑07‑11 Machine Learning for Quantum Design Conference Perimeter Institute PIRSA View details
Operational quantum tomography Olivia Di Matteo 2019‑07‑11 Machine Learning for Quantum Design Conference Perimeter Institute PIRSA View details
Machine learning phase discovery in quantum gas microscope images Ehsan Khatami 2019‑07‑11 Machine Learning for Quantum Design Conference Perimeter Institute PIRSA View details
Machine Learning Physics: From Quantum Mechanics to Holographic Geometry Yi-Zhuang You 2019‑07‑11 Machine Learning for Quantum Design Conference Perimeter Institute PIRSA View details
Attention is all you get Paul Ginsparg 2019‑07‑11 Machine Learning for Quantum Design Conference Perimeter Institute PIRSA View details
Deep learning and density functional theory Isaac Tamblyn 2019‑07‑11 Machine Learning for Quantum Design Conference Perimeter Institute PIRSA View details
Machine learning ground-state energies and many-body wave function Sebastiano Pilati 2019‑07‑10 Machine Learning for Quantum Design Conference Perimeter Institute PIRSA View details
Quantum machine learning and the prospect of near-term applications on noisy devices Kristan Temme 2019‑07‑10 Machine Learning for Quantum Design Conference Perimeter Institute PIRSA View details