Rostock 2019 – scientific programme
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SYQM: Symposium Novel Perspectives in Quantum Metrology
SYQM 1: Symposium: Novel Perspectives in Quantum Technologies
SYQM 1.3: Invited Talk
Friday, March 15, 2019, 11:30–12:00, U Audimax
Learning Hamiltonians using quantum and classical resources — Nathan Wiebe1 and •Chris Granade2 — 1Microsoft Research, Redmond USA — 2Microsoft Quantum Architectures and Computation Group
Modeling quantum dynamics can be a challenging task. In recent years, a new approach has come forward that used Bayesian inference to learn an approximate model for a hitherto unknown system. In this talk I will discuss recent advances in this field including our recent work that utilizes this approach to perform NV center magnetometry at room temperature and directly learn Hamiltonian models for poorly characterized NV center Hamiltonians. Finally, I will show how quantum computers can be used to exponentially improve these processes and show how ideas from machine learning can be introduced to allow computers to dream up new models and test them against existing ones and by doing so demonstrate artificial intelligences can already not only help learn Hamiltonians, but autonomously conduct science.