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DOE OSTI2022

Dynamics of non-Gaussian fluctuations in model A

Motivated by the experimental search for the QCD critical point, we perform simulations of a stochastic field theory with purely relaxational dynamics (model A). We verify the expected dynamic scaling of correlation functions. Using a finite size scaling analysis, we obtain the dynamic critical exponent z = 2.026(56). We investigate time dependent correlation functions of higher moments M n (t) of the order parameter M(t) for n = 1, 2, 3, 4. We obtain dynamic scaling with the same critical exponent z for all n, but the relaxation constant depends on n. We also study the relaxation of M n (t) after a quench, where the simulation is initialized in the high temperature phase, and the dynamics is studied at the critical temperature T c . Finally, we find that the evolution does not follow simple scaling with the dynamic exponent z, and that it involves an early time rise followed by late stage relaxation.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2025

Multiplicity and net-electric charge fluctuations in central Ar+Sc interactions at 13 A , 19 A , 30 A , 40 A , 75 A , and 150 A GeV/c beam momenta measured by NA61/SHINE at the CERN SPS

This paper presents results on multiplicity fluctuations of positively and negatively charged hadrons as well as net-electric charge fluctuations measured in central Ar+Sc interactions at beam momenta 13 A , 19 A , 30 A , 40 A , 75 A , and 150 A GeV/c. The fluctuation analysis is one of the tools to search for the predicted critical point of strongly interacting matter. Results are corrected for the experimental biases and quantified using cumulant ratios. In most instances, multiplicity and net-charge distributions appear narrower than the corresponding Poisson or Skellam distributions. Cumulant ratios are compared with the EPOS1.99 model predictions, which provide a qualitative description that aligns with observations for positively and negatively charged particles. The obtained results are also compared to earlier NA61/SHINE results from inelastic p+p interactions in the same analysis acceptance.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2022

MCS solutions for the TVA Watts Bar Unit 1 multi-physics depletion benchmark

The high-fidelity solution for exercises 1-3 of the recently developed TVA Watts Bar Unit 1 multi-physics and multi-cycle depletion benchmark using MCS was coupled with two different thermal-hydraulics (TH) codes: TH1D and COBRA-TF (CTF), and their solutions were compared. The solutions from MCS/CTF and MCS/TH1D for typical Pressurized Water Reactor (PWR) problems are quite close. And to evaluate MCS solutions for the benchmark, their results were also compared against measured data as well as publicly available high-fidelity solutions. The MCS criticality solutions at Hot Zero Power (HZP) deviate within 50 pcm against the reference solutions. While for the critical boron concentration (CBC) search calculations, the difference on the MCS calculated CBC is about 7 ppm, and the root-mean-squared (RMS) errors for the assembly power distribution and outlet coolant temperature are less than 0.5% and 1 Celsius degree respectively. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2021

FAIR Interfaces for Geospatial Scientific Data Searches

Several factors must be considered in designing a highly accurate, reliable, scalable, and user-friendly geospatial data search interfaces. This paper examines four critical questions that ought to be considered during design phase: (1) Is the search interface or API that provides the search capability useable by both humans and machines? (2) Are the results consistent and reliable? (3) Is the output response format free to use, community-defined, and non-propriety? (4) Does the API clearly state the usage clauses? This paper discusses how certain data repositories at the US Department of Energy's Oak Ridge National Laboratory apply FAIR data principles to enable geospatial searches and address the above-mentioned questions.

Devarakonda, Ranjeet↗

DOE OSTI2024

Chapter 8: Searching for Life Beyond Earth

The search for life beyond Earth necessitates a rigorous and comprehensive examination of biosignatures, the types of observable imprints that life produces. These imprints and our ability to detect them with advanced instrumentation hold the key to our understanding of the presence and abundance of life in the universe. Biosignatures are the chemical or physical features associated with past or present life and may include the distribution of elements and molecules, alone or in combination, as well as changes in structural components or physical processes that would be distinct from an abiotic background. The scientific and technical strategies used to search for life on other planets include those that can be conducted in situ to planetary bodies and those that could be observed remotely. Here this chapter discusses numerous strategies that can be employed to look for biosignatures directly on other planetary bodies using robotic exploration including those that have been deployed to other planetary bodies, are currently being developed for flight, or will become a critical technology on future missions. Search strategies for remote observations using current and planned ground-based and space-based telescopes are also described. Evidence from spectral absorption, emission, or transmission features can be used to search for remote biosignatures and technosignatures. Improving our understanding of biosignatures, their production, transformation, and preservation on Earth can enhance our search efforts to detect life on other planets.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

Dynamical Aspects of the Quark Gluon Plasma

Shortly after the Big Bang the entire universe was filled with a nearly perfect fluid known as the Quark Gluon Plasma. Relativistic heavy ion collisions can now reproduce this fluid in the laboratory where the Quark Gluon Plasma exhibits a rapid but smooth cross-over phase transition into hadrons at vanishing net-baryon densities. Recent experiments plan to explore finite baryon densities where a critical point is expected. If found, this would mark the first discovery of a critical point in a relativistic system described by a fundamental theory of nature, which would have far-reaching consequences for high-energy nuclear physics and nuclear astrophysics (such as in neutron star mergers). Characteristic temperatures of equilibrium (e.g. the inflection point of the entropy density) and transport coefficients (e.g. minimum of the shear viscosity over entropy density) vary widely at a cross-over phase transition but converge at a critical point, and extracting the behavior of these characteristic temperatures is a major focal point of this research. Specifically, the interplay between strange and light hadrons is exploited to study the flavor hierarchy in the cross-over region. To investigate this, a viscous relativistic hydrodynamics framework with two conserved charges is being developed into a new open-source code along with initial conditions that contain baryon number and strangeness. Flow observables sensitive to the equation of state and transport coefficients are calculated across beam energies. New techniques are being developed to study this flavor hierarchy from first principles and to extract the characteristic temperatures from experimental data. Through this new dynamical framework, this project provides essential guidance to the Beam Energy Scan II runs at Relativistic Heavy-Ion Collider and the future Facility for Antiproton and Ion Research facility in the search for the Quantum Chromodynamic critical point and subsequent investigation of the baryon-rich Quark Gluon Plasma.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2025

Harnessing the Quantum Zeno Effect in superconducting qubits for particle detection

Superconducting qubits, originally developed for quantum computing, are emerging as a potentially powerful tool for detecting low-energy particle interactions, such as dark matter and neutrinos. These devices can register energy deposits as small as a few meV, dramatically lowering the detection threshold compared to conventional sensors. However, their deployment in rare-event searches is hampered by a critical and unresolved background: Two-Level Systems (TLSes). TLSes are material defects that can scramble qubit frequencies and coherence times in a way that resembles particle energy deposits. Such false signals can critically limit the sensitivity and extend experimental runtimes for qubit-based sensors by years. This talk introduces a novel method to eliminate TLSes as a background source in superconducting qubit-based detectors. By harnessing the Quantum Zeno Effect (QZE), a well-established quantum phenomenon where frequent observation inhibits system evolution, I will discuss the possibility of “freezing” these TLS defects in place. This effectively suppresses their interference, stabilizes qubit behavior, and opens the door to using TLSes themselves as auxiliary sensors. I have already identified target TLSes and observed early signs of QZE-like dynamics in Fermilab-fabricated devices. The method builds on my existing collaborations at Fermilab’s Quantum Information Testbed (QUIET), with access to low muon flux cryogenic facilities 100 meters underground, control electronics, and expert mentors across multiple institutions. By removing a key bottleneck to superconducting sensor deployment, this research targets advancing the development of a general-purpose technique to enhance sensitivity, reduce false positives, and accelerate discovery in searches for dark matter, neutrinos, and other rare phenomena.

Seidel, Olivia [Texas U., Arlington]↗

DOE OSTI2023

Postdisaster Routing of Movable Energy Resources for Enhanced Distribution System Resilience: A Deep Reinforcement Learning-Based Approach

The deployment of movable energy resources (MERs) can be an effective strategy to restore critical loads to enhance power system resilience when no other energy sources are available after the occurrence of an extreme event. Since the optimal locations of MERs following an extreme event are dependent on system operating states (e.g., the loads at each node, on/off status of system branches, and so on), existing analytical and population-based approaches must repeat the entire analysis and calculation when the system operating states change. On the contrary, if deep reinforcement learning (DRL)-based algorithms are sufficiently trained with a wide range of scenarios, they can quickly find optimal or near-optimal locations irrespective of changes in system states. A deep Q-learning-based approach is proposed for optimal MER deployment to enhance power system resilience. MERs can be also utilized to complement other types of resources, if available. The proposed approach operates in two stages after the occurrence of extreme events. In the first stage, the distribution network is represented as a graph, and the network is then reconfigured using tie switches by using Kruskal’s spanning forest search algorithm (KSFSA). To maximize critical load recovery, the optimal or near-optimal locations of MERs are chosen in the second stage. Further, case studies on a 33-node distribution system and a modified IEEE 123-node system demonstrate the effectiveness of the proposed approach for postdisaster routing of MERs.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2020

Dijet Acoplanarity in CUJET3 as a Probe of the Nonperturbative Color Structure of QCD Perfect Fluids

Using the CUJET3=DGLV+VISHNU jet-medium interaction framework, we show that dijet azimuthal acoplanarity in high energy A + A collisions is sensitive to possible non-perturbative enhancement of the jet transport coefficient, $\hat{q}$(T,E), in the QCD crossover temperature T ~ 150–300 MeV range. With jet-medium couplings constrained by global RHIC& LHC χ 2 fits to nuclear modification data on R AA (p T > 20) GeV, we compare predictions of the medium induced dijet transverse momentum squared, $Q_s^2~\langle \hat{q}L\rangle~ΔΦ^2E^2$, in two models of the temperature, T, and jet energy E dependence of the jet medium transport coefficient, $\hat{q}$(T,E)). In one model, wQGP, the chromo degrees of freedom (dof) are approximated by a perturbative dielectric gas of quark and gluons dof. In the second model, sQGMP, we consider a nonperturbative partially confined semi-Quark-Gluon-Monopole-Plasma with emergent color magnetic dof constrained by lattice QCD data. Unlike the slow variation of the scaled jet transport coefficient, $\hat{q}_{wQGP}/T^3$, the sQGMP model $\hat{q}_{sQGMP}/T^3$ features a sharp maximum in the QCD confinement crossover T range. We show that the dijet path averaged medium induced azimuthal acoplanarity, Δφ 2 , in sQGMP is robustly ~ 2 times larger than in perturbative wQGP. even though the radiative energy loss in both models is very similar as needed to fit the same R AA data. Future A+A dijet acoplanarity measurements constrained together with single jet R AA and ν n measurements therefore appears to be a promising strategy to search for possible signatures of critical opalescence like phenomena in the QCD confinement temperature range.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2022

Measurement of Neutral-Current $\pi^0$ Cross Section in MicroBooNE using Wire-Cell Reconstruction

This note presents the extraction of flux-averaged total and differential neutral-current $π^0$ cross section measurements, based on the Wiener-SVD unfolding method, using the MicroBooNE Liquid Argon Time Projection Chamber (LArTPC) and the Wire-Cell reconstruction paradigm. This measurement is critical for single-photon searches as neutral-current pion production represents one of the largest sources of background. We report the results for an exposure corresponding to 5.327 × 10 19 protons-on-target (POT).

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2024

Designing multicomponent hydrides with potential high T c superconductivity

While hydrogen-rich materials have been demonstrated to exhibit high T c superconductivity at high pressures, there is an ongoing search for ternary, quaternary, and more chemically complex hydrides that achieve such high critical temperatures at much lower pressures. First-principles searches are impeded by the computational complexity of solving the Eliashberg equations for large, complex crystal structures. Here, we adopt a simplified approach using electronic indicators previously established to be correlated with superconductivity in hydrides. This is used to study complex hydride structures, which are predicted to exhibit promisingly high critical temperatures for superconductivity. In particular, we propose three classes of hydrides inspired by the Fm$\overline{3}$ m RH 3 structures that exhibit strong hydrogen network connectivity, as defined through the electron localization function. The first class [RH 11 X 3 Y] is based on a Pm$\overline{3}$m structure showing moderately high T c , where the T c estimate from electronic properties is compared with direct Eliashberg calculations and found to be surprisingly accurate. The second class of structures [(RH 11 ) 2 X 6 YZ] improves on this with promisingly high density of states with dominant hydrogen character at the Fermi energy, typically enhancing T c . The third class [(R 1 H 11 )(R 2 H 11 )X 6 YZ] improves the strong hydrogen network connectivity by introducing anisotropy in the hydrogen network through a specific doping pattern. These design principles and associated model structures provide flexibility to optimize both T c and the structural stability of complex hydrides.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2023

Effects of rare-earth magnetism on the superconducting upper critical field in infinite-layer nickelates

The search for superconductivity in infinite-layer nickelates was motivated by analogy to the cuprates, and this perspective has framed much of the initial consideration of this material. However, a growing number of studies have highlighted the involvement of rare-earth orbitals; in that context, the consequences of varying the rare-earth element in the superconducting nickelates have been much debated. Here, we show notable differences in the magnitude and anisotropy of the superconducting upper critical field across the La-, Pr-, and Nd-nickelates. These distinctions originate from the 4f electron characteristics of the rare-earth ions in the lattice: They are absent for La 3+ , nonmagnetic for the Pr 3+ singlet ground state, and magnetic for the Nd 3+ Kramer’s doublet. The unique polar and azimuthal angle-dependent magnetoresistance found in the Nd-nickelates can be understood to arise from the magnetic contribution of the Nd 3+ 4f moments. Such robust and tunable superconductivity suggests potential in future high-field applications.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2023

Saddle point search with dynamic active volume

Sampling potential energy surface (PES) is critical for many problems in materials science, chemistry, physics, and biology and requires highly efficient saddle point searches (SPS). In the study, we introduce the concept of dynamic active volume (DAV) in addition to the active volume in self-evolving atomistic kinetic Monte Carlo (SEAKMC). The DAV method has further reduced the dimensionality of the PES at the elevation stage of a SPS. At the subsequent converging stage, the dynamic boundary in DAV is lifted to allow the system to converge to the right location of a saddle point. Coupled with the dimer method, the DAV method not only significantly reduces the time cost for a given search attempt, but also dramatically increases the probability of finding relevant saddle points for PES sampling. Further, a Python software package within the framework SEAKMC (SEAKMC_py) with the DAV method has been developed.

36 MATERIALS SCIENCE↗

DOE OSTI2024

A framework to enhance disaster debris estimation with AI and aerial photogrammetry

This study addresses the critical need to enhance disaster preparedness and response, focusing on hurricane impact assessment and debris estimation. Accurate assessments in this context are critical for post-event search-and-rescue (SAR) operations and resource distribution. Recent computing advancements are revealing the potential of unmanned aerial vehicles (UAVs) and artificial intelligence (AI) technologies in collecting data and assisting with post-hurricane reconnaissance. However, the use of AI and UAV photogrammetry for accurate disaster impact analysis remains underexplored. To this end, this study proposes a damage and debris analysis framework harnessing reality capture through aerial imagery and photogrammetry. Within this framework, a region-based neural network is leveraged to detect debris locations in aerial imagery with favorable performance. In a testbed within the Beaumont-Port Arthur region, in Southeast Texas, this study performs 3D reality captures of the built environment. Since the accuracy of the 3D reality capture is of importance in research areas associated with time-sensitive disaster response, we further investigate the optimal 2D aerial imagery overlap ratio required to generate a sufficiently accurate 3D model for disaster impact analysis and debris volume estimation. Results indicate that, in the case of aerial imagery for infrastructure systems, a minimum of 60 % overlap is recommended for damage assessment and debris analysis. In contrast, for flat green areas, a minimum of 50 % overlap is adequate. Overall, for disaster response applications, our study reveals that an overlap ratio between 60 % and 70 % is optimal for achieving a balance between time efficiency and data quality in aerial data collection. Furthermore, these quantitative recommendations are crucial for enabling efficient disaster response efforts. Additionally, our study outcomes will improve disaster impact analysis and facilitating timely and effective response strategies.

Artificial intelligence↗

DOE OSTI2020

Mapping the phases of quantum chromodynamics with beam energy scan

We review the present status of the search for a phase transition and critical point as well as anomalous transport phenomena in Quantum Chromodynamics (QCD), with an emphasis on the Beam Energy Scan program at the Relativistic Heavy Ion Collider at Brookhaven National Laboratory. We present the conceptual framework and discuss the observables deemed most sensitive to a phase transition, QCD critical point, and anomalous transport, focusing on fluctuation and correlation measurements. Selected experimental results for these observables together with those characterizing the global properties of the systems created in heavy ion collisions are presented. We then discuss what can be already learned from the currently available data about the QCD critical point and anomalous transport as well as what additional measurements and theoretical developments are needed in order to discover these phenomena.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2020

High precision magnetic field measurement and mapping of the LEReC 180 degree bending magnet using very low field NMR with hall combined probe (140 - 350 gauss)

The Relativistic Heavy Ion Collider (RHIC) at BNL are using the Low Energy RHIC Electron Cooling (LEReC) to conduct experiments that search for the quantum chromodynamic (QCD) critical point. The first ever electron cooling based on the RF acceleration of electron beams was experimentally demonstrated on April 5, 2019 at LEReC at BNL. The first critical step in obtaining successful 3D non-magnetized cooling of the Au ion bunches in the RHIC cooling section was matching the electron beam energy with a relative error less than 5*10 -4 to the ion beam energy. Part of the LEReC beamline is a dipole magnet that bends the electron beam 180 degree. One of the most outstanding measurement challenges is that the dipole field is so low (≈200 G). Most of the existing NMR probes can only measure fields >400 G. Lower signal-to-noise ratio at low fields is requires the use of larger sample volumes. Working with CAYLAR, a NMR probe has been redesigned and optimized for these low field measurements with high resolution. We report the methods, challenges, and results for extensive magnetic field mappings of the 180 dipole magnet. A combination of NMR and Hall sensors has been successfully implemented to measure uniform field regimes inside the magnet center area and non-uniform field regimes at the magnet ends. Detailed measurement and mapping have been performed at five radii and five heights along the beam trajectory. Meanwhile a finite element magnetic modeling simulation of the magnet using Opera software has been performed. The calculated and measured data are compared, and the calculated data is good reference for measured data over long length mapping from magnet edge to center. The measured magnetic measurement data is directly useful for beam instrumentation, diagnostics and operation.

Magnetic Field Measurement↗

DOE OSTI2022

Comparison of temperature and doping dependence of elastoresistivity near a putative nematic quantum critical point

Abstract Strong electronic nematic fluctuations have been discovered near optimal doping for several families of Fe-based superconductors, motivating the search for a possible link between these fluctuations, nematic quantum criticality, and high temperature superconductivity. Here we probe a key prediction of quantum criticality, namely power-law dependence of the associated nematic susceptibility as a function of composition and temperature approaching the compositionally tuned putative quantum critical point. To probe the ‘bare’ quantum critical point requires suppression of the superconducting state, which we achieve by using large magnetic fields, up to 45 T, while performing elastoresistivity measurements to follow the nematic susceptibility. We performed these measurements for the prototypical electron-doped pnictide, Ba(Fe 1− x Co x ) 2 As 2 , over a dense comb of dopings. We find that close to the putative quantum critical point, the elastoresistivity appears to obey power-law behavior as a function of composition over almost a decade of variation in composition. Paradoxically, however, we also find that the temperature dependence for compositions close to the critical value cannot be described by a single power law.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2020

Accurate Identification of Deamidation and Citrullination from Global Shotgun Proteomics Data Using a Dual-Search Delta Score Strategy

While proteins with deamidated/citrullinated amino acids play critical roles in the pathogenesis of many human diseases, identifying these modifications in complex biological samples has been an ongoing challenge. Herein we present a method to accurately identify these modifications from shotgun proteomics data from a deep proteome profiling study of human pancreatic islets obtained by laser capture microdissection. All MS/MS spectra were searched against database by MSGF+ twice with or without a +0.9840 Da mass shift on amino acids asparagine, glutamine, and arginine (NQR) as a dynamic modification. Consequently, for each spectrum the resulting two peptide-to-spectrum matches (PSM) with their respective MSGF+ scores were used for Delta Score calculation. It was observed that all PSMs with positive Delta Score values were clustered with mass errors around 0 ppm, while PSMs with negative Delta Score values were distributed nearly equally within the defined mass error range (20 ppm) for database searching. To estimate false discovery rate (FDR), a “pseudo-decoy” approach was applied whether datasets were searched against a database with a “real modification” mass shift (+0.9840 Da) and a “mock modification” mass shift (+1.0227 Da). FDR was controlled to ~2% with a Delta Score filter greater than zero. Manual inspection of spectra showed that PSMs with positive Delta Score value contained deamidated/citrullinated fragments in their MS/MS spectra. Finally, the results demonstrated that in-situ deamidated/citrullinated peptides can be accurately identified from shotgun tissue proteomics data by the Dual-search Delta Score Strategy.

59 BASIC BIOLOGICAL SCIENCES↗