Peter Nugent
I build and use large-scale computational models — of exploding stars, of epidemics, of supply chains — and the data pipelines that feed them. Most of my work lives at the seam between a scientific question and the high-performance computing needed to answer it.
I am Project Scientist and Deputy Director of the La Silla Schmidt Southern Survey (LS4), and a member of DES, DESI and LSST-DESC. Previously I was Department Head for Computational Science at LBNL, PI of the Palomar Transient Factory Type Ia Supernova Project, and a co-founder of the Computational Cosmology Center. I have been an Oppenheimer Science and Energy Leadership Fellow and shared the 2015 Breakthrough Prize in Fundamental Physics and the 2007 Gruber Cosmology Prize.
Research Interests
I am always looking for better and faster ways to solve an interesting problem, and most of what I do sits where a scientific question meets the computing it takes to answer it: GPU porting and performance at scale, hybrid-parallel deep learning on large 3-D data, surrogate models that stand in for expensive simulations, real-time pipelines that turn telescope pixels into alerts, and the workflow plumbing that makes ensembles of 100,000 runs tractable. The domains change — supernovae, the intergalactic medium, epidemics, supply chains — but the approach is the same. These are the things I am working on now.
Agent-based modeling & epidemiology
ExaEpi is an agent-based epidemiological code built on the AMReX framework, able to simulate the United States agent-by-agent on GPU-accelerated exascale machines. It is the simulation engine of EMERGE, a DOE/ASCR multi-lab project on robust, generalizable epidemiology — including large ensemble campaigns on Aurora and Perlmutter, coupling to CMIP6 climate and weather projections, surrogate and reduced-order modeling, and venue-by-venue validation against LANL's EpiCast.
Critical minerals & supply-chain modeling
pyExaMINE (Python ExaScale Minerals & Infrastructure Network Evaluation) is an agent-based model of worldwide critical-mineral supply chains at facility resolution — individual mines, processors and recyclers for lithium, nickel, cobalt, manganese and platinum, with shipments routed through the real maritime chokepoints (Hormuz, Suez, Malacca, Panama, the Cape) and price dynamics driven by embargoes, chokepoint crises and material substitution.
AI for science — the Genesis Mission
Two projects selected in the DOE Genesis Mission RFA:
AHPI, the Agentic HPC Pipeline Initiative, will build AI workflows that enable U.S. manufacturers to run powerful DOE research codes on commercial cloud platforms.
HERALD, High-throughput ECI Review and Agentic Legacy Document processing, will build an AI platform to vet decades of secure government research, unlocking it for the commercial industry to accelerate nuclear innovation.
Time-domain surveys: PTF, ZTF and LS4
I was PI of the Type Ia supernova project within the Palomar Transient Factory (2008–2014), which built the real-time subtraction and machine-learning pipeline at NERSC that found SN 2011fe within hours of explosion. That work carried into the Zwicky Transient Facility — transient discovery at scale, plus searches for microlensing black holes and for the tidal-disruption and AGN variability signatures of massive black-hole mergers — and now into LS4, the La Silla Schmidt Southern Survey, where I am Project Scientist and Deputy Director.
Supernova physics
The discovery and observation of supernovae of all types, with the goal of understanding the physics of their explosions, their progenitor systems, and their nucleosynthesis products. Spectrum synthesis is the main tool: 1-D non-LTE with PHOENIX, and 3-D LTE Monte Carlo with SEDONA. Recent threads include sub-Chandrasekhar and super-Chandrasekhar Type Ia models, circumstellar interaction, and the interior structure of dying stars.
Supernova cosmology
Measuring the cosmological parameters using supernovae as distance probes — not only Type Ia but also Type II-P, via the spectral-fitting expanding atmosphere method. The K-correction and extinction-correction machinery underpinning much of this is what the spectral templates on this site are for.
Strongly lensed supernovae
When a supernova sits behind a massive galaxy, gravity splits its light into several images that arrive days to weeks apart. Because Type Ia supernovae are standardizable candles, a lensed one gives you the lens magnification for free and a time delay that measures H0 independently of the distance ladder. With Daniel Goldstein I worked out how to find them — a SN Ia that looks far too bright for its apparent elliptical host is almost certainly lensed — and how to recover precise time delays despite the chromatic microlensing of the individual images. With Ariel Goobar we forecast the rates and properties LSST-class surveys should expect, and I was part of the discovery and follow-up of iPTF16geu, the first resolved multiply-imaged SN Ia, and of its ZTF successor SN Zwicky.
Nyx & the Lyman-α forest
Nyx is an adaptive-mesh, massively parallel N-body + hydrodynamics code for cosmology, built on the AMReX framework. It started in 2010 as a conversation with Ann Almgren about adapting the Castro astrophysics code to follow dark matter particles interacting with hydrogen gas in an expanding universe; an LDRD seeded it, SciDAC and then the Exascale Computing Project carried it, and with Zarija Lukić leading the physics it became a workhorse for simulating the Lyman-α forest — the absorption imprinted on quasar light by intergalactic gas — at the volumes and resolutions DESI needs. It is open source, runs on CPUs and GPUs alike, and its filaments are painted on the side of Perlmutter.
I am a former member of the Nearby Supernova Factory and the Supernova Cosmology Project.
Contact
Lawrence Berkeley National Laboratory
MS 59-4029
1 Cyclotron Road
Berkeley, CA 94720
Elsewhere
E-mail: [email protected]
Phone: +1 (510) 486-6942
Fax: +1 (510) 486-5812
GitHub: github.com/nugent68