Christian Drischler

Christian Drischler

Assistant Professor of Physics and FRIB-TA Bridge Faculty

Research

I’m a theoretical physicist working at the intersection of nuclear physics and nuclear astrophysics. My research aims to understand strongly interacting matter across 18 orders of magnitude, ranging from atomic nuclei studied in laboratory experiments to neutron stars observed through multimessenger astronomy.

My research program is built on three interconnected thrusts:

  1. Nuclear matter and neutron stars: I derive microscopic constraints on the nuclear equation of state (EOS) and investigate their implications for the structure and evolution of neutron stars.
  2. Chiral effective field theory and many-body methods: I develop advanced methods for solving the many-body Schrödinger equation using nuclear microscopic interactions derived from chiral effective field theory (EFT).
  3. Bayesian uncertainty quantification and AI/ML methods: I develop Bayesian statistical methods, fast, accurate emulators, and other AI/ML techniques to quantify theoretical uncertainties and enable robust comparisons between nuclear theory, laboratory experiments, and multimessenger observations.

Open questions

Although QCD describes nuclear matter across all relevant density scales, no microscopic framework is currently available to predict the EOS and composition of the high-density matter in the cores of heavy neutron stars.

While a lot has recently been learned about dense matter through neutron star observation, heavy-ion collisions, and theory predictions, many key questions remain unanswered; for example:

My research, funded by both DOE and NSF, aims to advance our microscopic understanding of the nuclear EOS, the structure and evolution of neutron stars, and the nucleosynthesis of heavy elements in the universe.

To this end, I leverage chiral EFT, a low-energy effective theory of QCD, advanced many-body methods, and state-of-the-art computational tools to solve the nuclear many-body problem with quantified uncertainties. My work on automated diagram evaluation for many-body perturbation theory and on rigorous EFT truncation-error quantification has shaped how the field now reports EOS uncertainties.

Nuclear theory has made tremendous progress in developing chiral EFT into a powerful framework for deriving nuclear forces consistent with the symmetries of low-energy QCD. I have contributed to this progress with several new ideas in chiral EFT, many-body methods, and Bayesian machine learning (ML), applying them to the study of neutron star physics.

My Monte Carlo framework for diagrammatic nuclear matter calculations overcame previously required approximations and limitations using automated diagram evaluation, thereby enabling more accurate EOS predictions with controlled uncertainties. With my BUQEYE collaborators, I set the standard for rigorously quantifying theoretical uncertainties in EOS predictions due to truncating the EFT expansion at a finite order.

These EFT truncation errors grow rapidly with baryon density, and rigorously quantifying them is critical for modeling neutron stars; previous EOS predictions only provided rough uncertainty estimates. My EOS calculations with quantified uncertainties have produced statistically robust predictions for neutron star structure that can be confronted with the wealth of experimental and observational EOS constraints anticipated in the multimessenger era, advancing our understanding of dense matter.

Future directions

In the next few years, I aim to take full advantage of multimessenger astronomy, novel experimental campaigns, and advances in nuclear theory to constrain the nuclear EOS at zero and finite temperatures with unprecedented precision. This will shed light on additional open questions in nuclear astrophysics, such as:

The high computational cost of nuclear many-body calculations will be mitigated by developing fast and accurate emulators using model-reduction methods.

Nuclear systems are notoriously complex, and their theoretical modeling often includes superfluous information for describing the quantities of interest. Emulators are fast surrogate models that systematically reduce a system’s complexity while accurately approximating high-fidelity models — a game-changer for applying Bayesian statistical methods to nuclear physics, where each high-fidelity calculation can otherwise be prohibitively expensive to repeat thousands of times.

My research program is tightly coupled to the Facility for Rare Isotope Beams (FRIB) at Michigan State University (MSU) and multimessenger observations, both of which will produce a wealth of data in the next decade. I aim to provide rigorous interpretations of this data to obtain a fundamental understanding of dense matter with quantified uncertainties.

Interested in EOS physics and fast and accurate emulators for nuclear physics?
If so, please feel free to reach out to me. I’m always happy to discuss this research with students, postdocs, and anyone interested.

Further reading

In the meantime, let me draw your attention to the following pedagogical review articles for further reading:

I recently gave the recorded Science Café titled The Strong Force Awakens: A Neutron Star Story, which covered many of the mentioned subjects in a generally accessible way.

Collaborations

This research is naturally collaborative, and I’m grateful to my colleagues in the following collaborations for making this joint endeavor productive, engaging, and exciting: