Login

2023 CAP Congress / Congrès de l'ACP 2023

18–23 Jun 2023
University of New Brunswick
America/Halifax timezone
Welcome to the 2023 CAP Congress Program website! / Bienvenue au siteweb du programme du Congrès de l'ACP 2023!

Support

Session

(DCMMP) T4-7 Quantum Materials Symposium | Symposium sur les matériaux quantiques (DPMCM)

T4-7
20 Jun 2023, 15:15
University of New Brunswick

University of New Brunswick

Conveners

(DCMMP) T4-7 Quantum Materials Symposium | Symposium sur les matériaux quantiques (DPMCM)

  • Tami Pereg-Barnea
  • Tamar Pereg-Barnea

Presentation materials

There are no materials yet.

  1. 3574. (I) Enhanced quantum state reconstruction with artificial neural networks
    Stef Czischek (University of Ottawa)
    20/06/2023, 15:15
    Symposia Day (DCMMP - DPMCM) - Quantum Materials | Matériaux quantiques
    Invited Speaker / Conférencier(ère) invité(e)

    Over the last years, artificial neural networks have been explored as powerful and systematically tuneable ansatz to represent quantum wave functions. Such numerical models can tomographically reconstruct quantum states and operator expectation values from a finite amount of measurements. At the same time, artificial neural networks can find the ground state wave function of a given...

    Go to contribution page
  2. 3632. (I) Neural quantum state tomography, improvements and applications
    Pooya Ronagh
    20/06/2023, 15:45
    Symposia Day (DCMMP - DPMCM) - Quantum Materials | Matériaux quantiques
    Invited Speaker / Conférencier(ère) invité(e)

    Viewing neural quantum state tomography (NQST) as a flexible method for capturing classical snapshots of experimentally prepared quantum states opens doors to many applications of it in quantum simulation. In this talk we first review "Neural Error Mitigation" (Nat Mach Intell 4, 2022) for improving predictions of various observables obtained via quantum simulation of quantum states of...

    Go to contribution page
  3. 3936. (I) The Quantum Many-Body Problem in the Age of Machine Learning
    Prof. Adrian Feiguin (Northeastern University)
    20/06/2023, 16:15
    Symposia Day (DCMMP - DPMCM) - Quantum Materials | Matériaux quantiques
    Invited Speaker / Conférencier(ère) invité(e)

    In the past couple of years, machine learning has permeated many areas of physics and found numerous applications in condensed matter and chemistry. In particular, we have witnessed remarkable progress toward developing computational methods using neural networks as variational estimators. Variational representations of quantum states abound and have successfully been used to guess...

    Go to contribution page
Building timetable...