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Essay: Quantum Sensing with Atomic, Molecular, and Optical Platforms for Fundamental Physics

Atomic, molecular, and optical (AMO) physics has been at the forefront of the development of quantum science while laying the foundation for modern technology. With the growing capabilities of quantum control of many atoms for engineered many-body states and quantum entanglement, a key question emerges: what critical impact will the second quantum revolution with ubiquitous applications of entanglement bring to bear on fundamental physics? In this Essay, we argue that a compelling long-term vision for fundamental physics and novel applications is to harness the rapid development of quantum information science to define and advance the frontiers of measurement physics, with strong potential for fundamental discoveries. As quantum technologies, such as fault-tolerant quantum computing and entangled quantum sensor networks, become much more advanced than today’s realization, we wonder what doors of basic science can these tools unlock. We anticipate that some of the most intriguing and challenging problems, such as quantum aspects of gravity, fundamental symmetries, or new physics beyond the minimal standard model, will be tackled at the emerging quantum measurement frontier. . Published by the American Physical Society 2024

Physics↗

Monotonic Gaussian Process for Physics-Constrained Machine Learning With Materials Science Applications

Physics-constrained machine learning is emerging as an important topic in the field of machine learning for physics. One of the most significant advantages of incorporating physics constraints into machine learning methods is that the resulting model requires significantly less data to train. By incorporating physical rules into the machine learning formulation itself, the predictions are expected to be physically plausible. Gaussian process (GP) is perhaps one of the most common methods in machine learning for small datasets. In this paper, we investigate the possibility of constraining a GP formulation with monotonicity on three different material datasets, where one experimental and two computational datasets are used. The monotonic GP is compared against the regular GP, where a significant reduction in the posterior variance is observed. The monotonic GP is strictly monotonic in the interpolation regime, but in the extrapolation regime, the monotonic effect starts fading away as one goes beyond the training dataset. Imposing monotonicity on the GP comes at a small accuracy cost, compared to the regular GP. The monotonic GP is perhaps most useful in applications where data are scarce and noisy, and monotonicity is supported by strong physical evidence.

36 MATERIALS SCIENCE↗

Deep Underground Neutrino Experiment (DUNE), Far Detector Technical Design Report, Volume II: DUNE Physics

The preponderance of matter over antimatter in the early universe, the dynamics of the supernovae that produced the heavy elements necessary for life, and whether protons eventually decay -- these mysteries at the forefront of particle physics and astrophysics are key to understanding the early evolution of our universe, its current state, and its eventual fate. DUNE is an international world-class experiment dedicated to addressing these questions as it searches for leptonic charge-parity symmetry violation, stands ready to capture supernova neutrino bursts, and seeks to observe nucleon decay as a signature of a grand unified theory underlying the standard model. The DUNE far detector technical design report (TDR) describes the DUNE physics program and the technical designs of the single- and dual-phase DUNE liquid argon TPC far detector modules. Volume II of this TDR, DUNE Physics, describes the array of identified scientific opportunities and key goals. Crucially, we also report our best current understanding of the capability of DUNE to realize these goals, along with the detailed arguments and investigations on which this understanding is based. This TDR volume documents the scientific basis underlying the conception and design of the LBNF/DUNE experimental configurations. As a result, the description of DUNE's experimental capabilities constitutes the bulk of the document. Key linkages between requirements for successful execution of the physics program and primary specifications of the experimental configurations are drawn and summarized. This document also serves a wider purpose as a statement on the scientific potential of DUNE as a central component within a global program of frontier theoretical and experimental particle physics research. Thus, the presentation also aims to serve as a resource for the particle physics community at large.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

New Physics from the Neutrino Portal: Early Universe Implications and Detection Prospects

Despite their ubiquity, the nature of Dark Matter (DM) and neutrinos remains mysterious. Both are examples of particles which are neutral, stable, and require physics beyond the Standard Model (SM) of particle physics. It is therefore natural to investigate theories which relate them. If DM has more than gravitational interactions, it must not couple very sizably to the Standard Mode (SM) in order to have escaped detection so far. The nature of this coupling (or “portal”) is of paramount importance in determining the optimal experimental search strategies. This proposal aims to focus on the implications of “Hidden Sector” models of new physics where the dominant interaction is from the neutrino-mixing portal. Such scenarios give rise to new neutrino self-interactions and DM-neutrino interactions with a variety of consequences. By undertaking the thorough study of neutrino portal (NP) theories of DM this proposal seeks to achieve the following specific objectives: (1) Expand and deepen the theoretical foundations of self-interacting neutrinos in the early universe with application to sterile neutrino DM, (2) establish theoretical and phenomenological bases for DM-modified neutrino oscillations, (3) establish sensitivity projections for neutrino self-interactions from future IceCube data. The proposed research will intellectually contribute to the physics literature by thoroughly characterizing the consequences of “hidden sector” models incorporating DM and neutrinos. Theoretical consistency and a complete description of their impact on the early universe will constitute one component of this work. As a result of the additional structure in the neutrino sector the detectability of various aspects of neutrino physics will be impacted. This includes modifications to oscillation experiments, ultra-high-energy neutrino telescopes (e.g. IceCube, KM3NET), and Cosmic Microwave Background data. The success of this research proposal will depend on the successful integration of these complementary probes of new physics in the proper context of theoretically motivated scenarios determined from their impact on the early universe.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

SU(n) and Quantum SU(n) Symmetries in Physical Systems [Slides]

Presence of SU(n) or other Lie group symmetry in a physical system is its powerful, usually underutilized property. In many cases it allows for finding analytical solutions to nonlinear differential equations describing this system. Power of the method is presented on diversified examples from mathematical physics: Lie-group symmetries in finding solutions of generalized, multidimensional theory of gravity; analytical Dirac–equation solutions for description of conducting polymers; stability of qubit states in quantum computers; spatial defects in condensed matter; reconstruction of 3D object from its 2D tomographic image; significant improvement of numerical solutions stability for Euler equations. The next question after obtaining such Lie group symmetric solution is: does a generalized solution with appropriate quantum group symmetry exists for the given physical system, and if yes what is the physical meaning of the deformation parameter q introduced by such solution. In many cases it can be identified. Any SU(n) solution is by its nature singular, assuming a perfect symmetry of the physical system discussed. Such solution gives a powerful insight to theoretical physics, yet the assumption may be too demanding for experimental applications. Deformation parameter q from a quantum group symmetry allows for a continuum of solutions, more applicable to experiments.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Computational Physics Overview [Slides]

Computational physics is an important part of the overall investment in National Security Science at LANL. Computational physics is the study and implementation of numerical analysis to solve problems in physics for which a quantitative theory already exists. Historically, computational physics was the first application of modern computers in science. There are three key elements to computational physics: mathematical models of physical phenomena and conservation equations, computer codes that implement these models, and computer platforms that execute the code instructions and manipulate the data.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

The Path to Global Discovery: U.S. Leadership and Partnership in Particle Physics

In February 2022, HEPAP, the High Energy Physics Advisory Panel to DOE (Department of Energy) and NSF (National Science Foundation), was charged with forming a subpanel to conduct an international benchmarking study to evaluate U.S. leadership in particle physics in a global context (Appendix D). HEPAP formed an International Benchmarking Subpanel and gathered qualitative and quantitative data from the international particle physics community to 1) determine how the U.S. particle physics program can maintain critical international cooperation in an increasingly competitive environment for both talent and resources, 2) identify key areas where the U.S. has or could aspire to leadership roles, and 3) determine how programs and facilities can be structured to attract and retain talented people. This report also serves as input to P5 (Particle Physics Project Prioritization Panel), a subpanel of HEPAP that defines the strategic scientific direction for the U.S. particle physics program.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Challenges of Future Accelerators for Particle Physics Research

For over half a century, high-energy particle accelerators have been a major enabling technology for particle and nuclear physics research as well as sources of X-rays for photon science research in material science, chemistry and biology. Particle accelerators for energy and intensity Frontier research in particle and nuclear physics continuously push the accelerator community to invent ways to increase the energy and improve the performance of accelerators, reduce their cost, and make them more power efficient. The accelerator community has demonstrated imagination and creativity in developing a plethora of future accelerator ideas and proposals. The technical maturity of the proposed facilities ranges from shovel-ready to those that are still largely conceptual. At this time, over 100 contributed papers have been submitted to the Accelerator Frontier of the US particle physics decadal community planning exercise known as Snowmass’2021. These papers cover a broad spectrum of topics: beam physics and accelerator education, accelerators for neutrinos, colliders for Electroweak/Higgs studies and multi-TeV energies, accelerators for Physics Beyond Colliders and rare processes, advanced accelerator concepts, and accelerator technology for Radio Frequency cavities (RF), magnets, targets and sources. This paper provides an overview of the present state of accelerators for particle physics and gives a brief description of some of the major facilities that have been proposed, their perceived advantages and some of the remaining challenges.

43 PARTICLE ACCELERATORS↗

Modeling Data Flows with Network Calculus in Cyber-Physical Systems: Enabling Feature Analysis for Anomaly Detection Applications

The electric grid is becoming increasingly cyber-physical with the addition of smart technologies, new communication interfaces, and automated grid-support functions. Because of this, it is no longer sufficient to only study the physical system dynamics, but the cyber system must also be monitored as well to examine cyber-physical interactions and effects on the overall system. To address this gap for both operational and security needs, cyber-physical situational awareness is needed to monitor the system to detect any faults or malicious activity. Techniques and models to understand the physical system (the power system operation) exist, but methods to study the cyber system are needed, which can assist in understanding how the network traffic and changes to network conditions affect applications such as data analysis, intrusion detection systems (IDS), and anomaly detection. In this paper, we examine and develop models of data flows in communication networks of cyber-physical systems (CPSs) and explore how network calculus can be utilized to develop those models for CPSs, with a focus on anomaly and intrusion detection. This provides a foundation for methods to examine how changes to behavior in the CPS can be modeled and for investigating cyber effects in CPSs in anomaly detection applications.

97 MATHEMATICS AND COMPUTING↗

Physical examination during space flight

OBJECTIVE: To develop techniques for conducting a physical examination in microgravity and to describe and document the physiologic changes noted with use of a modified basic physical examination. DESIGN: On the basis of data gathered from physical examinations on KC-135 flights, three physical variables were assessed serially in astronauts during two shuttle missions (of 8- and 10-day duration, respectively). Preflight, in-flight, and postflight examinations were conducted by trained physician-astronauts or flight surgeons, who used this modified examination. MATERIAL AND METHODS: Five male and two female crewmembers participated in the "hands-on" physical examination of all physiologic systems except the genitourinary system. Level of edema, intensity of bowel sounds, and peripheral reflexes were assessed and graded. RESULTS: This investigation identified unique elements of a physical examination performed during space flight that will assist in the development of standard methods for conducting examinations of astronauts in weightlessness. In addition, demonstrable changes induced by microgravity were noted in most physiologic systems examined. CONCLUSION: The data support the hypothesis that the microgravity examination differs from that conducted on earth or in a 1g environment. In addition, alterations in the physiologic response can be detected with use of hands-on technique. These data are invaluable in the development of optimal medical care for humans in space.

STS Shuttle Project↗

NASA Physics of Failure (PoF) for Reliability

An item’s reliability or longevity is dependent not only on its design but also on how it is used, manufactured, tested, and the stresses it has or will experience. Stresses include operational and environmental exposures to thermal, voltage, current, age/exposure, mechanical, and radiation mechanisms. Therefore, in reliability analysis, it is important to consider the contributions of all of these factors when predicting the failure rates of components. Historically, there has been a reliance on handbook data (e.g., MIL-HDBK-217), but experience has shown that these values and distributions are not representative of actual performance (1,2). Therefore, to make more credible reliability and risk assessments for its missions, NASA must transition to estimating likelihoods of failure based on an item’s reliability/longevity factors (or the physical susceptibilities and strengths impacting the design’s performance) has or will experience, whenever possible. To facilitate this transition a “Handbook on Methodology for Physics of Failure Based Reliability Assessments” has been developed by NASA to assist in applying physics experiences or experiment physics for empirical analysis and conceptualized physics exposures or theoretical physics for deterministic analysis, to develop and aggregate realistic likelihoods of failure leading to more credible forecasts of item performance and longevity. In addition, since it is NASA’s intention that this document continues to evolve based on community lessons learned and the introduction of new assessment methodologies, NASA is encouraging and appreciates the contributions of current and future authors to maintain and enhance this handbook and its supporting case studies.

Physics of Failure↗

Methodology and Application of Physical Security Effectiveness Based on Dynamic Force-on-Force Modeling

This report describes the research and development being performed at INL towards a dynamic modeling and simulation framework to enable physical security optimization at commercial nuclear power plants. The framework is based on the dynamic modeling tool EMRALD and is demonstrated for applications that can result in physical security optimization. Two main applications are presented: 1. Integrating FLEX portable equipment performance with FOF models of a plant’s physical security posture, and 2. Location optimization of bullet resistant enclosure. The generic framework for modeling FLEX portable equipment is described in detail, followed by a case study modeling an adversarial attack aimed at causing a radiological release by sabotaging the plant’s power supply and its ultimate heat sink capabilities at a hypothetical PWR. Two distinct FLEX deployment strategies, series and parallel, are modeled with distinct timelines. The results of the adversarial attack modeled in a commercial FOF tool, AVERT, are integrated with the FLEX deployment model in EMRALD. Monte Carlo simulation is used to model the distribution of the timeline in FLEX deployment strategies. Thermal-hydraulic analysis of FLEX performance is performed in RELAP5 and integrated with the EMRALD simulations to provide more realistic timelines in the models. The results demonstrate that, even in the extreme case of a successful adversarial attack, deployment of FLEX equipment can result in a significantly high likelihood of preventing radiological release. The modeling and simulation framework of integrating FLEX equipment with FOF models enables the NPPs to credit FLEX portable equipment in the plant security posture, resulting in an efficient and optimized physical security. The objective of location optimization of BRE is to determine the best location in the plant for a new BRE being planned by the plant to enhance their physical security effectiveness. The plant physical security FOF model is integrated with EMRALD that performs Monte Carlo simulation to run different attack scenarios and a discrete set of potential BRE locations. Sensitivity analysis is used to determine the most effective location for the BRE. The optimization approach can be extended to wide applications such as location optimization of remotely operated weapons and other strategic fixed assets.

97 MATHEMATICS AND COMPUTING↗

High Energy Physics Opportunities Using Reactor Antineutrinos

Nuclear reactors are uniquely powerful, abundant, and flavor-pure sources of antineutrinos that continue to play a vital role in the US neutrino physics program. The US reactor antineutrino physics community is a diverse interest group encompassing many detection technologies and many particle physics topics, including Standard Model and short-baseline oscillations, BSM physics searches, and reactor flux and spectrum modeling. The community's aims offer strong complimentary with numerous aspects of the wider US neutrino program and have direct relevance to most of the topical sub-groups composing the Snowmass 2021 Neutrino Frontier. Reactor neutrino experiments also have a direct societal impact and have become a strong workforce and technology development pipeline for DOE National Laboratories and universities. This white paper, prepared as a submission to the Snowmass 2021 community organizing exercise, will survey the state of the reactor antineutrino physics field and summarize the ways in which current and future reactor antineutrino experiments can play a critical role in advancing the field of particle physics in the next decade.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Rapid Inverse Parameter Inference Using Physics-Informed Neural Network

As Li-ion batteries become more essential in today's economy, tools need to be developed to accurately and rapidly diagnose a battery's internal state-of-health. Using a Li-ion battery's (high-rate) voltage response, it is proposed to determine a battery's internal state through Bayesian calibration. However, Bayesian calibration is notoriously slow and requires thousands of model runs. To accelerate parameter inference using Bayesian calibration, a surrogate model is developed to replace the underlying physics-based Li-ion model. Developing a surrogate model for rapid Bayesian calibration analysis is discussed for both the single particle model (SPM) and the pseudo two-dimensional (P2D) model. Surrogate models are constructed using physics-informed neural networks (PINNs) that encode the influence of internal properties on observed voltage responses. In practice, a neural network can be trained by: 1) using simulation results of the physics-based model (i.e., a data-loss approach); 2) using the residuals of the governing equations themselves (i.e., a physics-loss approach); or 3) using a combination of simulation results and governing equation residuals. In the present work, PINNs are developed using a variety of training losses and neural network architectures. In this analysis, it is shown that a PINN surrogate model can be reliably trained with only physics-informed loss. However, using a coupled data-informed and physics-loss approach produced the most accurate PINNs.

Bayesian calibration↗

Emerging Jets Search, Triton Server Deployment, and Track Quality Development: Machine Learning Applications in High Energy Physics

Machine learning is becoming prevalent in high energy physics, with numerous applications in physics analyses and event reconstruction showing great improvements compared to traditional computing methods. This thesis studies three projects which each propose new avenues for machine learning applications within the high energy physics CMS experiment located at CERN. In the first project, a search for a dark matter signal called “emerging jets” is performed, using graph neural networks to greatly increase sensitivity to the signal’s signature within the data. The result of this dark matter search sets the most stringent exclusion limits to date on theoretical emerging jet models. Motivated by inefficiencies encountered when processing the emerging jet graph neural network at Fermi National Accelerator Laboratory’s computing centers, the second project re-optimizes the computing centers for machine learning inference. This re-optimization uses NVIDIA Triton Inference Servers to process users’ analysis code heterogeneously, therefore achieving high processing throughput and decreasing user time-to-insight. The last project focuses on an upgrade to the CMS experiment’s real-time event selection system which improves physics object reconstruction under harsh processing conditions. A boosted decision tree is used to quickly and efficiently quantify a reconstructed particle’s “track quality” in order to remove particle tracks reconstructed erroneously. In summary, this thesis will not only present examples of how high energy physics can greatly benefit by leveraging machine learning techniques for physics analysis and reconstruction, but will also provide guidance on how the field can prepare for the inevitable increase in machine learning applications.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

MSR Proliferation Resistance and Physical Protection White Paper

This document represents the status of Proliferation Resistance and Physical Protection (PR&PP) characteristics for the Molten Salt Reactor designs selected by the Generation IV International Forum (GIF) Molten Salt Reactor (MSR) provisional System Steering Committee (pSSC) as representatives of three broad classes of MSRs. The three classes of MSRs are: (1) Liquid-fueled with integrated salt processing, (2) Liquid-fueled without integrated salt processing, (3) Solid-fueled with salt coolant. The intent is to generate preliminary information about the PR&PP merits of the MSR Reactor Technology and to provide insights for optimizing their PR&PP performance for the benefit of MSR system designers. It updates the MSR analysis published in the 2011 report “Proliferation Resistance and Physical Protection of the Six Generation IV Nuclear Energy Systems”, prepared Jointly by the Proliferation Resistance and Physical Protection Working Group (PRPPWG) and the System Steering Committees of the Generation IV International Forum, taking into account the evolution of both the systems and the GIF R&D activities since its publication. The document, prepared jointly by the GIF PRPPWG and the GIF MSR pSSC, follows the high-level paradigm of the GIF Proliferation Resistance and Physical Protection Evaluation Methodology to investigate the Proliferation Resistance and Physical Protection features of the GIF MSR representative designs. For PR, the document analyses and discusses the proliferation resistance aspects in terms of robustness against State-based threats associated with diversion of materials, misuse of facilities, breakout scenarios, and production in clandestine facilities. Similarly, for physical protection, the document discusses the robustness against theft of material and sabotage by non-State actors.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Extended harmonic mapping connects the equations in classical, statistical, fluid, quantum physics and general relativity

Abstract One potential pathway to find an ultimate rule governing our universe is to hunt for a connection among the fundamental equations in physics. Recently, Ren et al. reported that the harmonic maps with potential introduced by Duan, named extended harmonic mapping (EHM), connect the equations of general relativity, chaos and quantum mechanics via a universal geodesic equation. The equation, expressed as Euler–Lagrange equations on the Riemannian manifold, was obtained from the principle of least action. Here, we further demonstrate that more than ten fundamental equations, including that of classical mechanics, fluid physics, statistical physics, astrophysics, quantum physics and general relativity, can be connected by the same universal geodesic equation. The connection sketches a family tree of the physics equations, and their intrinsic connections reflect an alternative ultimate rule of our universe, i.e. , the principle of least action on a Finsler manifold.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Preface to special topic: The High Repetition Rate Frontier in High-Energy-Density Physics

High-repetition-rate (HRR) experiments can collect large datasets with high temporal, spatial, and/or parametric resolution or large numbers of repeat measurements for statistics. HRR experiments also enable new experimental designs, including active feedback control loops and novel diagnostics, that can improve the reproducibility as well as the quantity of measurements. Together, these attributes make HRR experiments ideal for performing high-quality repeatable science. Until recently, these techniques have not been applied to high-energy-density–physics (HEDP) experiments, which are typically restricted to repetition rates of a few per day. However, recent advancements in lasers, pulsed-power drivers, target fabrication, and diagnostics are starting to change this fact, opening an exciting new frontier of HRR HEDP experiments. A mini-conference on this subject at the 2021 meeting of the American Physical Society Division of Plasma Physics brought together members of this growing community. As a result, the “High Repetition Rate Frontier in High-Energy-Density Physics” special topic in Physics of Plasmas highlights current progress in this exciting area.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗