102 citations
- Argonne National LaboratoryUS5 papers
- Northwestern UniversityUS5 papers
- Michigan State UniversityUS2 papers
- Bates CollegeUS1 paper
- Commissariat à l'Énergie Atomique et aux Énergies AlternativesFR1 paper
- ETH ZurichCH1 paper
- Fermi National Accelerator LaboratoryUS1 paper
- Istituto Nazionale di Fisica Nucleare, Trento Institute for Fundamental Physics And ApplicationsIT1 paper
- Laboratoire d’Innovation pour les Technologies des Énergies Nouvelles et les nanomatériauxFR1 paper
- Miami UniversityUS1 paper
- Ohio UniversityUS1 paper
- The Ohio State UniversityUS1 paper
9 papers
Uncertainty Quantification in Breakup Reactions
Özge Sürer, Filomena M. Nunes, Matthew Plumlee +1
Breakup reactions are one of the favored probes to study loosely bound nuclei, particularly those in the limit of stability forming a halo. In order to interpret such breakup exper…
Assessing the accuracy of compound formation energies with quantum Monte Carlo
Eric B. Isaacs, Hyeondeok Shin, Abdulgani Annaberdiyev +4
Accurately predicting the formation energy of a compound, which describes its thermodynamic stability, is a key challenge in materials physics. Here, we employ many-body quantum Mo…
Trapping Interlayer Excitons in van der Waals Heterostructures by Potential Arrays
Darien J. Morrow, Xuedan Ma
Transition metal dichalcogenide heterostructures can host interlayer excitons (IXs), which consist of electrons and holes spatially separated in different layers. IXs possess perma…
Leggett Modes Accompanying Crystallographic Phase Transitions
Quintin N. Meier, Daniel Hickox-Young, Geneva Laurita +3
Higgs and Goldstone modes, well known in high energy physics, have been realized in a number of condensed matter physics contexts, including superconductivity and magnetism. The Go…
Get on the BAND Wagon: A Bayesian Framework for Quantifying Model Uncertainties in Nuclear Dynamics
D. R. Phillips, R. J. Furnstahl, U. Heinz +8
We describe the Bayesian Analysis of Nuclear Dynamics (BAND) framework, a cyberinfrastructure that we are developing which will unify the treatment of nuclear models, experimental…
Machine learning-based inversion of nuclear responses
Krishnan Raghavan, Prasanna Balaprakash, Alessandro Lovato +2
A microscopic description of the interaction of atomic nuclei with external electroweak probes is required for elucidating aspects of short-range nuclear dynamics and for the corre…