DiRAC-3 Operations 2023-26 - Leicester Additional Grant
Lead Research Organisation:
University of Leicester
Department Name: Physics and Astronomy
Abstract
The DiRAC High Performance Computing (HPC) facility provides cutting-edge computing services for the STFC theory communities in particle physics, astrophysics, cosmology and nuclear physics. Our complementary programmes of HPC skills training and innovation activities provide further support to the STFC theory research programme, as well as delivering significant benefits to wider society and the economy.
Physicists across the astrophysics, cosmology, nuclear and particle physics communities are focussed
on understanding how the Universe works at a very fundamental level. The distance scales
with which they work vary by more than 40 orders of magnitude from the smallest distances probed
by experiments at the Large Hadron Collider, deep within the atomic
nucleus, to the largest scale galaxy clusters observed in the Universe. The science challenges,
however, are linked through questions such as: How did the Universe begin and how is it evolving?
and What are the fundamental constituents and fabric of the Universe and how do they interact?
Progress requires a combination of new astronomical observations, new experimental data and new theoretical insights. Today, theoretical understanding comes increasingly from large-scale
computations that allow us to confront, in detail, the implications of our theoretical models with data from observations or experiments, or to interrogate the data to extract information that has
impact on our theories. Increasingly, theoretical calculations use artificial intelligence and machine learning algorithms to enhance their physical realism, improve their computational efficiency, or both.
These computations require the performance of the fastest computers available and push the boundaries of technology in this sector. They also provide an excellent
environment for training students in state-of-the-art techniques for code optimisation, data mining and visualisation; all valuable skills for their future careers.
The DiRAC HPC facility has been operating since 2009, providing computing resources for theoretical research
in all areas of particle physics, astrophysics, cosmology and nuclear physics supported by STFC. It is a highly productive
facility, supporting the STFC theory community in publishing over 270 papers annually in international, peer-reviewed journals.
In 2020, DiRAC received a £20m capital investment from the UKRI World Class Laboratories fund, allowing the deployment of DiRAC-3 Phase 1, the first major uplift in our
computational resources since DiRAC-2 in 2012 and providing a vital boost to the STFC theory programme for 2022/23.
The main purpose of the funding requested in this proposal is to support the continued operation of the DiRAC HPC facility for the period 2023-2026, including staff and power costs. These resources will enable DiRAC to continue sustainably as an internationally competitive computing facility for the STFC theory community, to train the next generation of leading computational scientists and to play a lead role in the UKRI Digital Research Infrastructure over the next decade.
Physicists across the astrophysics, cosmology, nuclear and particle physics communities are focussed
on understanding how the Universe works at a very fundamental level. The distance scales
with which they work vary by more than 40 orders of magnitude from the smallest distances probed
by experiments at the Large Hadron Collider, deep within the atomic
nucleus, to the largest scale galaxy clusters observed in the Universe. The science challenges,
however, are linked through questions such as: How did the Universe begin and how is it evolving?
and What are the fundamental constituents and fabric of the Universe and how do they interact?
Progress requires a combination of new astronomical observations, new experimental data and new theoretical insights. Today, theoretical understanding comes increasingly from large-scale
computations that allow us to confront, in detail, the implications of our theoretical models with data from observations or experiments, or to interrogate the data to extract information that has
impact on our theories. Increasingly, theoretical calculations use artificial intelligence and machine learning algorithms to enhance their physical realism, improve their computational efficiency, or both.
These computations require the performance of the fastest computers available and push the boundaries of technology in this sector. They also provide an excellent
environment for training students in state-of-the-art techniques for code optimisation, data mining and visualisation; all valuable skills for their future careers.
The DiRAC HPC facility has been operating since 2009, providing computing resources for theoretical research
in all areas of particle physics, astrophysics, cosmology and nuclear physics supported by STFC. It is a highly productive
facility, supporting the STFC theory community in publishing over 270 papers annually in international, peer-reviewed journals.
In 2020, DiRAC received a £20m capital investment from the UKRI World Class Laboratories fund, allowing the deployment of DiRAC-3 Phase 1, the first major uplift in our
computational resources since DiRAC-2 in 2012 and providing a vital boost to the STFC theory programme for 2022/23.
The main purpose of the funding requested in this proposal is to support the continued operation of the DiRAC HPC facility for the period 2023-2026, including staff and power costs. These resources will enable DiRAC to continue sustainably as an internationally competitive computing facility for the STFC theory community, to train the next generation of leading computational scientists and to play a lead role in the UKRI Digital Research Infrastructure over the next decade.
Organisations
People |
ORCID iD |
Mark Wilkinson (Principal Investigator) |
Publications
Huško F
(2023)
The buildup of galaxies and their spheroids: The contributions of mergers, disc instabilities, and star formation
in Monthly Notices of the Royal Astronomical Society
Icaza-Lizaola M
(2023)
A sparse regression approach for populating dark matter haloes and subhaloes with galaxies
in Monthly Notices of the Royal Astronomical Society
Jahns-Schindler J
(2023)
How limiting is optical follow-up for fast radio burst applications? Forecasts for radio and optical surveys
in Monthly Notices of the Royal Astronomical Society
Jennings F
(2023)
Shattering and growth of cold clouds in galaxy clusters: the role of radiative cooling, magnetic fields, and thermal conduction
in Monthly Notices of the Royal Astronomical Society
Jennings F
(2023)
Halo scaling relations and hydrostatic mass bias in the simba simulation from realistic mock X-ray catalogues
in Monthly Notices of the Royal Astronomical Society
Ježo T
(2023)
Resonance-aware NLOPS matching for off-shell $$ t\overline{t} $$ + tW production with semileptonic decays
in Journal of High Energy Physics
Joswig F
(2023)
Exploring distillation at the SU(3) flavour symmetric point
Kannan R
(2023)
The MillenniumTNG project: the galaxy population at z = 8
in Monthly Notices of the Royal Astronomical Society
Katz H
(2023)
The SPHINX Public Data Release: Forward Modelling High-Redshift JWST Observations with Cosmological Radiation Hydrodynamics Simulations
in The Open Journal of Astrophysics
Kugel R
(2023)
FLAMINGO: calibrating large cosmological hydrodynamical simulations with machine learning.
in Monthly notices of the Royal Astronomical Society