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SYQM: Symposium Novel Perspectives in Quantum Metrology

SYQM 1: Symposium: Novel Perspectives in Quantum Technologies

SYQM 1.3: Hauptvortrag

Freitag, 15. März 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.