Steven Stroberg
University of Notre Dame, IN·Physics·Early-career
The Standard Model of particle physics explains most of what we observe. Yet it cannot account for gravity, dark matter, or why there is more matter than antimatter.
- Fields
Physics
- Topics
nuclear theory
ab initio nuclear structure
in-medium similarity renormalization group
- Grants
- 1 known grant, through Jul 2029
What they work on
- Develop a computationally tractable way to include three-particle interactions in the in-medium similarity renormalization group (IMSRG), a method for solving the quantum many-body problem of atomic nuclei.
- Build a framework that estimates the size of the effects the IMSRG approximation leaves out, giving nuclear structure calculations theoretical error bars.
- Bring ab initio nuclear calculations to the precision needed to interpret table-top experiments searching for deviations from Standard Model predictions.
More about the research
One way to find new physics is to make extremely precise measurements, often on table-top experiments, and look for tiny departures from Standard Model predictions. Many of these tests involve atomic nuclei. Spotting a deviation therefore requires very precise calculations of how protons and neutrons behave together inside a nucleus, along with honest error bars on those calculations.
Why it matters
Precise nuclear calculations with reliable error bars are needed to interpret precision experiments searching for physics beyond the Standard Model, such as clues about dark matter or the matter-antimatter imbalance. This work could let table-top experiments test such ideas, complementing searches at particle colliders.
Known grants
From NIH and NSF research grants. Labs often have other funding we can't see.
Closest labs
Jonathan Engel
University of North Carolina at Chapel Hill, NC·Physics
Compute nuclear matrix elements for neutrinoless double-beta decay in experimentally used isotopes, using three ab initio nuclear-structure methods that build nuclei from their protons and neutrons.
Jesse Thaler
Massachusetts Institute of Technology, MA·Physics
Develop "ab initio AI" methods that build first principles of fundamental physics into machine learning, to make intractable theoretical physics calculations, such as precision structure-of-matter predictions, feasible.
Andrea Shindler
University of California-Berkeley, CA·Physics
Calculate the electric dipole moments of protons and neutrons induced by theories beyond the Standard Model, to probe the source of the universe's matter-antimatter asymmetry.
The school
University of Notre Dame: 19 labs on PI Pages, $346M a year on research, 277 research doctorates a year.
Reach out
A start for your email. Fill in the brackets.