RQC Seminar

281st RQC Seminar

• Speaker

  Prof. Dr. Felix Motzoi
  ( Forschungszentrum Jülich )

• Date

  13:10-14:10, (1:10 p.m.-2:10 p.m.) Monday, June 15, 2026

• Venue

  Hybrid( Zoom,
  345-347 Seminar Room, 3F, Main Research Building, Wako Campus / 和光地区 研究本館3階 セミナー室 (345-347) (C01))

• Title

  Learning how to calibrate quantum processors

• Inquiries

  norilab_rqc_assist[at]ml.riken.jp

Abstract
In this talk, I will discuss progress towards streamlining the optimization of quantum dynamics affecting other layers of the computing stack. Given operations that must be repeated in time, typically parameterized by variables up and down the stack, we aim to automatically learn the performance landscape, particularly near the optima peaks. These learning tasks thus encompass both prescribing behaviour of operations as a function of the (control, state, parameter) search spaces, as well as inverting the optimization problem as a function of stack parameters [1]. These inter-layer functional dependencies can be captured using automatically differentiable computer algebra [2], and more generally using supervised and unsupervised (reinforcement [3]) learning methods.

[1] PRXQ 3, 040311 (2022); [2] PRQ 3, 030313 (2022); [3] NPJQI 6, 6 (2020), Quantum 8, 1343 (2024), arXiv:2509.03974 (2025).