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Algorithms23

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Elm Lecture Theatre (The Nucleus building, Edinburgh)

Elm Lecture Theatre

The Nucleus building, Edinburgh

Thomas Bayes Rd, Edinburgh EH9 3FG
Description

The Algorithms23 workshop on recent progress in algorithms for lattice field theory brings together experts for four days of discussions to assess the latest developments in the field and future directions. The workshop will be held at the University of Edinburgh from 24th to 27th of April 2023.

The workshop takes place in the Nucleus building which is located within the University of Edinburgh's King's Buildings campus.

The topics will cover the latest developments in

  • Master Field simulations
  • Multilevel algorithms
  • Machine Learning
  • Quantum Computing
  • Implementation on current and future hardware (exascale projects)
  • Energy efficiency
  • Mathematical foundations

Registration Deadline: March 17, 2023

Warning about Scams: If you received emails from travellerpoint(dot)org, please be careful. The email asks about arrival and departure dates to Edinburgh and offers a hotel booking form where they ask for credit card details. Please, ignore the emails and do not reply nor click on any link given by them.

Confirmed speakers:

Gert Aarts (Swansea University)
Ryan Abbott (MIT)
Simone Bacchio (The Cyprus Institute)
David Barrett (DeepMind)
Peter Boyle (BNL)
Kate Clark (Nvidia)
Patrick Fritzsch (Trinity College Dublin)
Andreas Frommer (University of Wuppertal)
Tim Harris (ETH Zürich)
Christoph Lehner (University of Regensburg)
Martin Lüscher (CERN)
Antonin Portelli (The University of Edinburgh)
Sofia Vallecorsa (CERN)
Urs Wenger (University of Bern)
Tilo Wettig (University of Regensburg)
Xinhao Yu (The University of Edinburgh)

Local Organising Committee:

Constantia Alexandrou
Luigi Del Debbio
Ines Foidl
Fabian Joswig
Mike Peardon

The Algorithms23 workshop is supported by:

Participants
  • Alessandro Cotellucci
  • Alessandro Lupo
  • Andreas Frommer
  • Anthony Kennedy
  • Antonin Portelli
  • Brian Pendleton
  • Christoph Lehner
  • Constantia Alexandrou
  • David Barrett
  • Fabian Joswig
  • Felix Erben
  • Gert Aarts
  • Gurtej Kanwar
  • Isabel Campos
  • Juan Andres Urrea Niño
  • Julian Urban
  • Justus Kuhlmann
  • Kate Clark
  • Luigi Del Debbio
  • Magdalena Glinka
  • Marco Cè
  • Marta Orwat
  • Martin Lüscher
  • Matteo Di Carlo
  • Max Hansen
  • Michael Marshall
  • Michael Peardon
  • Mostafa Khalil
  • Nelson Lachini
  • Nils Hermansson-Truedsson
  • Nuha Chreim
  • Patrick Fritzsch
  • Peter Boyle
  • Raoul Hodgson
  • Roger Horsley
  • Ruben Kara
  • Ryan Abbott
  • Ryan Hill
  • Sara Rosso
  • Simon Bürger
  • Simone Bacchio
  • Sofia Vallecorsa
  • Srijit Paul
  • Tilo Wettig
  • Tim Harris
  • Timo Eichhorn
  • Travis Whyte
  • Urs Wenger
  • Vera Guelpers
  • Xinhao Yu
  • Monday, 24 April
    • 09:30 → 10:00
      Coffee break 30m Elm Lecture Theatre

      Elm Lecture Theatre

      The Nucleus building, Edinburgh

      Thomas Bayes Rd, Edinburgh EH9 3FG
    • 10:00 → 11:00
      Multilevel strategies for full-QCD simulations 1h Elm Lecture Theatre

      Elm Lecture Theatre

      The Nucleus building, Edinburgh

      Thomas Bayes Rd, Edinburgh EH9 3FG
      Speaker: Martin Lüscher
      higgs23.pdf
    • 11:00 → 12:00
      Variance reduction in the leading hadronic contribution to $g_\mu-2$ from a two-level QCD simulation 1h Elm Lecture Theatre

      Elm Lecture Theatre

      The Nucleus building, Edinburgh

      Thomas Bayes Rd, Edinburgh EH9 3FG

      I will review the signal-to-noise ratio problem for the electromagnetic current correlator, which hampers the accurate determination of the leading-order hadronic vacuum polarization contribution to the muon anomaly from first principles, among other physically-interesting matrix elements. Thanks to the recent factorization of the fermionic determinant, multi-level integration can be performed in QCD which offers exponential improvement in the precision in many correlation functions at long distances. In the work with Dalla Brida, Giusti and Pepe, we investigated the variance reduction in the current correlator in a two-level QCD simulation with light quarks corresponding to a pion mass of about 270 MeV and in a large volume of 3fm. The best estimate is obtained by using translation averaging for the correlator, and some time will be devoted discussing its implementation in our simulation.

      Speaker: Tim Harris (University of Edinburgh)
    • 12:00 → 12:30
      Transfer matrices and temporal factorization of the Wilson fermion determinant 30m Elm Lecture Theatre

      Elm Lecture Theatre

      The Nucleus building, Edinburgh

      Thomas Bayes Rd, Edinburgh EH9 3FG
      Speaker: Urs Wenger
    • 12:30 → 14:30
      Lunch break 2h Elm Lecture Theatre

      Elm Lecture Theatre

      The Nucleus building, Edinburgh

      Thomas Bayes Rd, Edinburgh EH9 3FG
    • 14:30 → 16:00
      Discussion on Masterfield simulations & Multilevel algorithms 1h 30m Elm Lecture Theatre

      Elm Lecture Theatre

      The Nucleus building, Edinburgh

      Thomas Bayes Rd, Edinburgh EH9 3FG
      Speaker: Patrick Fritzsch
    • 16:00 → 16:30
      Coffee break 30m Elm Lecture Theatre

      Elm Lecture Theatre

      The Nucleus building, Edinburgh

      Thomas Bayes Rd, Edinburgh EH9 3FG
  • Tuesday, 25 April
    • 09:30 → 10:00
      Coffee break 30m Elm Lecture Theatre

      Elm Lecture Theatre

      The Nucleus building, Edinburgh

      Thomas Bayes Rd, Edinburgh EH9 3FG
    • 10:00 → 11:00
      QCD software and algorithms for the exascale 1h Elm Lecture Theatre

      Elm Lecture Theatre

      The Nucleus building, Edinburgh

      Thomas Bayes Rd, Edinburgh EH9 3FG

      I will give an overview of the development directions of Grid on current and future US exascale computers. I will also give an overview of the USQCD SciDAC-5 algorithm project to develop multiscale algorithms to exploit these.

      Speaker: Peter Boyle
    • 11:00 → 12:00
      Learning Trivializing Gradient Flows 1h Elm Lecture Theatre

      Elm Lecture Theatre

      The Nucleus building, Edinburgh

      Thomas Bayes Rd, Edinburgh EH9 3FG

      In our recent work, [arXiv:2212.08469], we have presented a new approach for trivializing flows that starts from the perturbative construction of trivializing maps by Lüscher and improves on it by learning. The resulting continuous normalizing flow model can be implemented using common tools of lattice field theory and requires several orders of magnitude fewer parameters than state-of-the-art deep learning approaches. Specifically, our model can achieve competitive performance with as few as 14 parameters while existing deep-learning models have around 1 million parameters for SU(3).

      Speaker: Simone Bacchio
      Bacchio.pdf
    • 12:00 → 12:30
      Optimisation of lattice simulations energy efficiency 30m Elm Lecture Theatre

      Elm Lecture Theatre

      The Nucleus building, Edinburgh

      Thomas Bayes Rd, Edinburgh EH9 3FG
      Speaker: Prof. Antonin Portelli (The University of Edinburgh)
    • 12:30 → 14:30
      Lunch break 2h Elm Lecture Theatre

      Elm Lecture Theatre

      The Nucleus building, Edinburgh

      Thomas Bayes Rd, Edinburgh EH9 3FG
    • 14:30 → 16:00
      Discussion on exascale computing 1h 30m Elm Lecture Theatre

      Elm Lecture Theatre

      The Nucleus building, Edinburgh

      Thomas Bayes Rd, Edinburgh EH9 3FG
      Speaker: Kate Clark
    • 16:00 → 16:30
      Coffee break 30m Elm Lecture Theatre

      Elm Lecture Theatre

      The Nucleus building, Edinburgh

      Thomas Bayes Rd, Edinburgh EH9 3FG
    • 18:30 → 20:30
      Workshop dinner 2h Amber Restaurant

      Amber Restaurant

      The Scotch Whisky Experience 354 Castlehill Edinburgh EH1 2NE
  • Wednesday, 26 April
    • 09:30 → 10:00
      Coffee break 30m Elm Lecture Theatre

      Elm Lecture Theatre

      The Nucleus building, Edinburgh

      Thomas Bayes Rd, Edinburgh EH9 3FG
    • 10:00 → 11:00
      Quantum Machine Learning in High Energy Physics 1h Elm Lecture Theatre

      Elm Lecture Theatre

      The Nucleus building, Edinburgh

      Thomas Bayes Rd, Edinburgh EH9 3FG

      Theoretical and algorithmic advances, availability of data, and computing power have opened the door to exceptional perspectives for application of classical Machine Learning in the most diverse fields of science, business and society at large, and notably in High Energy Physics (HEP). In particular, Machine Learning is among the most promising techniques to analyse and understand the data the next generation HEP detectors will produce.
      Machine Learning is also a promising task for near-term quantum devices that can leverage compressed high dimensional representations and use the stochastic nature of quantum measurements as random source. Several architectures are being investigated. Quantum implementations of Boltzmann Machines, classifiers or Auto-Encoders, among the most popular ones, are being proposed for different applications. Born machines are purely quantum models that can generate probability distributions in a unique way, inaccessible to classical computers. One-class Support Vector Machines have proven to be very powerful tools in anomaly detection problems.

      This talk will give an overview of the current state of the art in terms of Machine Learning on quantum computers with focus on their application to HEP.

      Speaker: Sofia Vallecorsa
      QML_algorithms23_Sofia.pdf
    • 11:00 → 12:00
      The Physics of Deep Learning 1h Elm Lecture Theatre

      Elm Lecture Theatre

      The Nucleus building, Edinburgh

      Thomas Bayes Rd, Edinburgh EH9 3FG

      Throughout the last decade, deep learning has provided us with state-of-the-art results across a wide variety of disciplines, from image recognition and game-play through to protein folding and physics. The connection to physics is particularly interesting since deep learning can be used for physics, and visa-versa, we can use ideas from physics to improve our understanding of deep learning. In this talk, we will derive equations of motion for deep learning using backward error analysis, we will use dynamical systems theory to analyse these equations and we will review recent applications of deep learning in physics and beyond.

      Speaker: David Barrett
    • 12:00 → 14:00
      Lunch break 2h Elm Lecture Theatre

      Elm Lecture Theatre

      The Nucleus building, Edinburgh

      Thomas Bayes Rd, Edinburgh EH9 3FG
    • 14:00 → 15:00
      Normalizing Flows for Lattice QCD 1h Elm Lecture Theatre

      Elm Lecture Theatre

      The Nucleus building, Edinburgh

      Thomas Bayes Rd, Edinburgh EH9 3FG

      Normalizing flows have recently emerged as a new approach to sampling in lattice field theories. In this talk I will give an overview of how normalizing flows have been developed for this application, and discuss the current status as well as future directions for these tools.

      Speaker: Ryan Abbott
      Abbott_Algorithms23.pdf
    • 15:00 → 16:30
      Discussion on machine learning in lattice field theories 1h 30m Elm Lecture Theatre

      Elm Lecture Theatre

      The Nucleus building, Edinburgh

      Thomas Bayes Rd, Edinburgh EH9 3FG
      Speaker: Gert Aarts
      aarts.pdf
    • 16:30 → 17:00
      Coffee break 30m Elm Lecture Theatre

      Elm Lecture Theatre

      The Nucleus building, Edinburgh

      Thomas Bayes Rd, Edinburgh EH9 3FG
  • Thursday, 27 April
    • 09:30 → 10:00
      Coffee break 30m Elm Lecture Theatre

      Elm Lecture Theatre

      The Nucleus building, Edinburgh

      Thomas Bayes Rd, Edinburgh EH9 3FG
    • 10:00 → 11:00
      Improving coarsest level solves in multigrid for lattice QCD 1h Elm Lecture Theatre

      Elm Lecture Theatre

      The Nucleus building, Edinburgh

      Thomas Bayes Rd, Edinburgh EH9 3FG

      Aggregation-based, adaptive algebraic multigrid has established itself as the most efficient linear solver for QCD lattice discretizations such as the (clover improved) Wilson discretization or the twisted mass discretizationn. As we are now able to simulate at the physical point, the resulting systems are severely ill-conditioned, and the multigrid approach shifts this ill-conditioning to the coarsest level in the multigrid hierarchy. This is why now often the by far largest amount of time is spent in the coarse level solves, where standard multigrid implementations for lattice QCD rely just on (restarted) GMRES as a solver.
      In this talk we present three ways of accelerating the coarsest level solves, namely (1) polynomial preconditioning, (2) deflation and (3) using an (incomplete) LU-factorization. We will explain the heuristics underlying all three improvements and present numerical results on large lattices. It turns out that the twisted mass calculations profit the most of these improvements and that a technique called agglomeration is particularly beneficial in case (3). Agglomeration means that we reduce the number of cores used on the coarsest level to reduce communication.

      Speaker: Andreas Frommer
      frommer.pdf
    • 11:00 → 11:30
      Gauge-equivariant multigrid neural networks I 30m Elm Lecture Theatre

      Elm Lecture Theatre

      The Nucleus building, Edinburgh

      Thomas Bayes Rd, Edinburgh EH9 3FG
      Speaker: Tilo Wettig
    • 11:30 → 12:00
      Gauge-equivariant multigrid neural networks II 30m Elm Lecture Theatre

      Elm Lecture Theatre

      The Nucleus building, Edinburgh

      Thomas Bayes Rd, Edinburgh EH9 3FG
      Speaker: Christoph Lehner
    • 12:00 → 12:30
      On the geometric convergence of HMC on Riemannian manifolds 30m Elm Lecture Theatre

      Elm Lecture Theatre

      The Nucleus building, Edinburgh

      Thomas Bayes Rd, Edinburgh EH9 3FG

      In this presentation we apply Harris' ergodic theorem on Markov chains to prove the geometric convergence of Hamiltonian Monte Carlo: first on compact Riemannian manifolds, and secondly on a large class of non-compact Riemannian manifolds by introducing an extra Metropolis step in the radial direction. We shall use $\phi^4$ theory as an explicit example of the latter case.

      Speaker: Xinhao Yu
    • 12:30 → 14:00
      Lunch break 1h 30m Elm Lecture Theatre

      Elm Lecture Theatre

      The Nucleus building, Edinburgh

      Thomas Bayes Rd, Edinburgh EH9 3FG
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