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DOE OSTI2020

Machine Learning for Neutron Resonance Evaluations [Slides]

The performance of nuclear reactors and other nuclear systems depends on a precise understanding of the neutron interaction cross sections for materials used in these systems. These cross sections exhibit a resonance structure whose shape is determined in part by the angular momentum quantum numbers of the resonances. The correct assignment of the quantum numbers of neutron resonances is therefore of paramount importance. In this presentation, we describe the application of machine learning to automate the quantum number assignments. Scikit-learn classifiers were trained on simulated resonance data whose statistical properties were chosen to mimic real data. We explored the use of several physics (and random matrix theory)-motivated features for training the classifiers, including the nearest neighbor spacing distribution, cumulative level distribution, and channel width distributions. Initial results demonstrated that we can determine resonance spin groups somewhat reliably. We are now investigating the application of our approach to 52 Cr resonance data.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Quantum Sensing and its Potential for Nuclear Safeguards

Quantum sensing has the potential to provide ultrasensitive measurements of physical phenomenon. Unlike quantum computing, quantum sensing is available now, though in general at research laboratories. A notable commercially-available quantum sensing device is the ubiquitous Superconducting Quantum Interference Device (SQUID), which can measure faint magnetic fields such as found in the human brain. Quantum sensing is used for direct measurement of environmental phenomenon, such as electromagnetic fields and accelerations, which then are used for certain applications. For example, quantum sensing of accelerations is useful for Position, Navigation, and Timing (PNT) applications. It is not clear, however, how quantum sensing can be useful for nuclear safeguards. This report provides first a background in quantum sensing, followed by a survey of potential safeguards utilizations of quantum sensing. Several potential safeguards applications are identified and explored.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2026

Hybrid Oscillator-Qubit Quantum Processors: Instruction Set Architectures, Abstract Machine Models, and Applications

This tutorial offers a pedagogical guide to hybrid quantum processors that integrate discrete-variable (DV) qubits and continuous-variable (CV) oscillators. Aimed at computer scientists, engineers, and physicists, it provides an overview of the experimental, algorithmic, and architectural aspects of this novel and rapidly developing hardware model. Experimental realizations of this model include superconducting, trapped-ion, and neutral-atom platforms. By combining DV and CV components, hybrid oscillator-qubit processors enable a powerful new paradigm that offers complementary strengths for quantum control, error correction, computation, and simulation. Working toward the goal of a full-stack system connecting applications to CV-DV hardware, we define and formulate abstract machine models and instruction set architectures. These essential abstractions enable codesign of hardware and software, and resource estimation for exploring the potential of current and future hardware for computational and simulation tasks. Using these abstractions, we present both new and existing examples that illustrate the benefits of hybrid CV-DV processors relative to traditional DV-only hardware in computation as well as quantum simulation of physical models. Examples include algorithms for transferring states between DV and CV systems, performing the quantum Fourier transform, and simulation of lattice gauge theories. Relative to qubit-only hardware, the bosonic degrees of freedom natively available in hybrid architectures can substantially reduce the circuit complexity of simulations for physical models containing bosons. A key technique is the extension of quantum signal processing ideas to CV-DV systems. This work is intended to serve as a timely and comprehensive guide to this relatively unexplored yet promising approach to quantum computation and to provide a road map to guide future development.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Discovering nuclear models from symbolic machine learning

Numerous phenomenological nuclear models have been proposed to describe specific observables within different regions of the nuclear chart. However, developing a unified model that describes the complex behavior of all nuclei remains an open challenge. Here, we explore whether symbolic Machine Learning (ML) can rediscover traditional nuclear physics models or identify alternatives with improved simplicity, fidelity, and predictive power. To address this challenge, we developed a Multi-objective Iterated Symbolic Regression approach that handles symbolic regressions over multiple target observables, accounts for experimental uncertainties and is robust against high-dimensional problems. As a proof of principle, we applied this method to describe the nuclear binding energies and charge radii of light and medium mass nuclei. Our approach identified simple analytical relationships based on the number of protons and neutrons, providing interpretable models with precision comparable to state-of-the-art nuclear models. Additionally, we integrated this ML-discovered model with an existing complementary model to estimate the limits of nuclear stability. These results highlight the potential of symbolic ML to develop accurate nuclear models and guide our description of complex many-body problems.

Nuclear structure↗
DOE OSTI2015

Uncertainty quantification for nuclear density functional theory and information content of new measurements

Statistical tools of uncertainty quantification can be used to assess the information content of measured observables with respect to present-day theoretical models, to estimate model errors and thereby improve predictive capability, to extrapolate beyond the regions reached by experiment, and to provide meaningful input to applications and planned measurements. To showcase new opportunities offered by such tools, we make a rigorous analysis of theoretical statistical uncertainties in nuclear density functional theory using Bayesian inference methods. By considering the recent mass measurements from the Canadian Penning Trap at Argonne National Laboratory, we demonstrate how the Bayesian analysis and a direct least-squares optimization, combined with high-performance computing, can be used to assess the information content of the new data with respect to a model based on the Skyrme energy density functional approach. Employing the posterior probability distribution computed with a Gaussian process emulator, we apply the Bayesian framework to propagate theoretical statistical uncertainties in predictions of nuclear masses, two-neutron dripline, and fission barriers. Overall, we find that the new mass measurements do not impose a constraint that is strong enough to lead to significant changes in the model parameters. In addition, the example discussed in this study sets the stage for quantifying and maximizing the impact of new measurements with respect to current modeling and guiding future experimental efforts, thus enhancing the experiment-theory cycle in the scientific method.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Projection algorithm for state preparation on quantum computers

We present an efficient method to prepare states of a many-body system on quantum hardware, first isolating individual quantum numbers and then using time evolution to isolate the energy. Our method in its simplest form requires only one additional auxiliary qubit. The total time evolved for an accurate solution is proportional to the ratio of the spectrum range of the trial state to the gap to the lowest excited state, a substantial improvement over other projection algorithms, and the accuracy increases exponentially with the time evolved. Isolating the quantum numbers is efficient because of the known eigenvalues and increases the gap thus shortening the propagation time required. The success rate of the algorithm, or the probability of producing the desired state, is a simple function of measurement times and phases and is dominated by the square overlap of the original state to the desired state. We present examples from the nuclear shell model and the Heisenberg model. In conclusion, we compare this algorithm to previous algorithms for short evolution times and discuss potential further improvements.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2011

Scientific Discovery with the Blue Gene/L

This project succeeded in developing key software optimization tools to bring fundamental QCD calculations of nucleon structure from the Terascale era through the Petascale era and prepare for the Exascale era. It also enabled fundamental QCD physics calculations and demonstrated the power of placing small versions of frontier emerging architectures at MIT to attract outstanding students to computational science. MIT also hosted a workshop September 19 2008 to brainstorm ways to promote computational science at top tier research universities and attract gifted students into the field, some of whom would provide the next generation of talent at our defense laboratories.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Perturbative Quantum Monte Carlo Method for Nuclear Physics

While first order perturbation theory is routinely used in quantum Monte Carlo (QMC) calculations, higher-order terms present significant numerical challenges. We present a new approach for computing perturbative corrections in projection QMC calculations. Here we demonstrate the method by computing nuclear ground state energies up to second order for a realistic chiral interaction. We calculate the binding energies of several light nuclei up to 16 O by expanding the Hamiltonian around the Wigner SU(4) limit and find good agreement with data. In contrast to the natural ordering of the perturbative series, we find remarkably large second-order energy corrections. This occurs because the perturbing interactions break the symmetries of the unperturbed Hamiltonian. Our method is free from the sign problem and can be applied to QMC calculations for many-body systems in nuclear physics, condensed matter physics, ultracold atoms, and quantum chemistry.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2012

From nucleons to nuclei to fusion reactions

Nuclei are prototypes of many-body open quantum systems. Complex aggregates of protons and neutrons that interact through forces arising from quantum chromo-dynamics, nuclei exhibit both bound and unbound states, which can be strongly coupled. In this respect, one of the major challenges for computational nuclear physics, is to provide a unified description of structural and reaction properties of nuclei that is based on the fundamental underlying physics: the constituent nucleons and the realistic interactions among them. This requires a combination of innovative theoretical approaches and high-performance computing. In this contribution, we present one of such promising techniques, the ab initio no-core shell model/resonating-group method, and discuss applications to light nuclei scattering and fusion reactions that power stars and Earth-base fusion facilities.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2017

Computing Properties of Hadrons, Nuclei and Nuclear Matter from Quantum Chromodynamics

This project was part of a coordinated software development effort which the nuclear physics lattice QCD community pursues in order to ensure that lattice calculations can make optimal use of present, and forthcoming leadership-class and dedicated hardware, including those of the national laboratories, and prepares for the exploitation of future computational resources in the exascale era. The UW team improved and extended software libraries used in lattice QCD calculations related to multi-nucleon systems, enhanced production running codes related to load balancing multi-nucleon production on large-scale computing platforms, and developed SQLite (addressable database) interfaces to efficiently archive and analyze multi-nucleon data and developed a Mathematica interface for the SQLite databases.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2015

Hadron polarizability data analysis: GoAT

The A2 Collaboration at the Institute for Nuclear Physics in Mainz, Germany, is working towards determining the polarizabilities of hadrons from nonperturbative quantum chromodynamics through Compton scattering experiments at low energies. The asymmetry observables are directly related to the scalar and spin polarizabilities of the hadrons. Online analysis software, which will give real-time feedback on asymmetries, efficiencies, energies, and angle distributions, has been developed. The new software is a big improvement over the existing online code and will greatly develop the quality of the acquired data.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Quantum error mitigation for Fourier moment computation

Hamiltonian moments in Fourier space—expectation values of the unitary evolution operator under a Hamiltonian at different times—provide a convenient framework to understand quantum systems. They offer insights into the energy distribution, higher-order dynamics, response functions, correlation information, and physical properties. This paper focuses on the computation of Fourier moments within the context of a nuclear effective field theory on superconducting quantum hardware. The study integrates echo verification and noise renormalization into Hadamard tests using control reversal gates. These techniques, combined with purification and error suppression methods, effectively address quantum hardware decoherence. The analysis, conducted using noise models, reveals a significant reduction in noise strength by two orders of magnitude. Moreover, quantum circuits involving up to 266 gates over five qubits demonstrate high accuracy under these methodologies when run on IBM superconducting quantum devices. Published by the American Physical Society 2025

Kiss, Oriel (ORCID:0000000174613342)↗
DOE OSTI2019

Quantum annealing for systems of polynomial equations

Abstract Numerous scientific and engineering applications require numerically solving systems of equations. Classically solving a general set of polynomial equations requires iterative solvers, while linear equations may be solved either by direct matrix inversion or iteratively with judicious preconditioning. However, the convergence of iterative algorithms is highly variable and depends, in part, on the condition number. We present a direct method for solving general systems of polynomial equations based on quantum annealing, and we validate this method using a system of second-order polynomial equations solved on a commercially available quantum annealer. We then demonstrate applications for linear regression, and discuss in more detail the scaling behavior for general systems of linear equations with respect to problem size, condition number, and search precision. Finally, we define an iterative annealing process and demonstrate its efficacy in solving a linear system to a tolerance of 10 −8 .

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2016

Design of virtual SCADA simulation system for pressurized water reactor

The Virtual SCADA system is a software-based Human-Machine Interface that can visualize the process of a plant. This paper described the results of the virtual SCADA system design that aims to recognize the principle of the Nuclear Power Plant type Pressurized Water Reactor. This simulation uses technical data of the Nuclear Power Plant Unit Olkiluoto 3 in Finland. This device was developed using Wonderware Intouch, which is equipped with manual books for each component, animation links, alarm systems, real time and historical trending, and security system. The results showed that in general this device can demonstrate clearly the principles of energy flow and energy conversion processes in Pressurized Water Reactors. This virtual SCADA simulation system can be used as instructional media to recognize the principle of Pressurized Water Reactor.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Quantum computing for energy correlators

In recent years, energy correlators have emerged as powerful observables for probing the fragmentation dynamics of high-energy collisions. We introduce the first numerical strategy for calculating energy correlators using the Hamiltonian lattice approach, providing access to the intriguing nonperturbative dynamics of these observables. Furthermore, motivated by rapid advances in quantum computing hardware and algorithms, we propose a quantum algorithm for calculating energy correlators in quantum field theories. This algorithm includes ground state preparation, the application of source, sink, energy flux and real-time evolution operators, and the Hadamard test. We validate our approach by applying it to the SU(2) pure gauge theory in 2 + 1 dimensions on 3 × 3 and 5 × 5 honeycomb lattices with 𝑗 max = $\frac{1}{2}$ at various couplings, utilizing both classical methods and the quantum algorithm, the latter tested using the IBM emulator for specific configurations. The results are consistent with the expected behavior of the strong coupling regime and motivate a more comprehensive study to probe the confinement dynamics across the weak and strong coupling regimes.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2017

Nuclear Computational Low Energy Initiative (NUCLEI)

This is the Final Report for Ohio State University for the NUCLEI SciDAC­3 project. In addition to the local OSU summary given here, we have attached a global NUCLEI summary and a list of papers and talks by the full collaboration, with OSU contributions marked in red. The NUCLEI project, as defined by the scope of work, developed, implemented and ran codes for large­scale computations of many topics in low­energy nuclear physics. Physics studied included the properties of nuclei and nuclear decays, nuclear structure and reactions, and the properties of nuclear matter. The computational techniques used included Quantum Monte Carlo, Configuration Interaction, Coupled Cluster, In­Medium SRG, and Density Functional methods. The research program emphasized areas of high interest to current and possible future DOE nuclear physics facilities, including ATLAS and FRIB (nuclear structure and reactions, and nuclear astrophysics), TJNAF (neutron distributions in nuclei, few body systems, and electroweak processes), NIF (thermonuclear reactions), MAJORANA and FNPB (neutrinoless double­beta decay and physics beyond the Standard Model), and LANSCE (fission studies). Research at Ohio State University played an integral role in NUCLEI by providing input microscopic interactions and operators needed for ab initio structure and reaction calculations including uncertainty quantification, independent ab initio calculations using the in­medium similarity renormalization group (IM­SRG), and developing microscopic constraints for the next­generation energy density functionals (EDF). Much of the theoretical work at OSU was closely coordinated with the theory team at Michigan State University. Although the OSU group did not usually directly develop codes for the highest performance computing components of NUCLEI, we provided needed inputs for much of the effort. In particular, our work contributes to the “Validated Nuclear Interactions” task as well as to both of the “Structure and Reactions” tasks.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2017

Multistate Landau-Zener models with all levels crossing at one point

Within this paper, we discuss common properties and reasons for integrability in the class of multistate Landau-Zener models with all diabatic levels crossing at one point. Exploring the Stokes phenomenon, we show that each previously solved model has a dual one, whose scattering matrix can be also obtained analytically. For applications, we demonstrate how our results can be used to study conversion of molecular into atomic Bose condensates during passage through the Feshbach resonance, and provide purely algebraic solutions of the bowtie and special cases of the driven Tavis-Cummings model.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗