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DOE OSTI2025

Data-driven high-dimensional statistical inference with generative models

Crucial to many measurements at the LHC is the use of correlated multi-dimensional information to distinguish rare processes from large backgrounds, which is complicated by the poor modeling of many of the crucial backgrounds in Monte Carlo simulations. In this work, we introduce HI-SIGMA, a method to perform unbinned high-dimensional statistical inference with data-driven background distributions. In contradistinction to many applications of Simulation Based Inference in High Energy Physics, HI-SIGMA relies on generative ML models, rather than classifiers, to learn the signal and background distributions in the high-dimensional space. These ML models allow for interpretable inference while also incorporating model errors and other sources of systematic uncertainties. We showcase this methodology on a simplified version of a di-Higgs measurement in the bbγγ final state, where the di-photon resonance allows for background interpolation from sidebands into the signal region. We demonstrate that HI-SIGMA provides improved sensitivity as compared to standard classifier-based methods, and that systematic uncertainties can be straightforwardly incorporated by extending methods which have been used for histogram based analyses.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2020

Beam impedance and heating analysis of the diagnostic stripline

In this work the heat transfer analysis has been performed for the stripline kicker, design of which is used at many accelerator facilities as a part of the transverse bunch-by-bunch feed-back system, including NSLS-II. The experimental data of the electrode temperature have been collected from a special diagnostic stripline designed with six infrared view ports. The temperature analysis is based on the power loss calculations and the loss factor computed by the 3-D electromagnetic simulation code GdfidL. To estimate the power loss, we analyze the real part of the longitudinal impedance and the loss factor for two different regimes. We use the ANSYS finite element code to correlate the temperature with the power loss. Lambertson and Shafer formalisms of the longitudinal and transverse beam impedances are discussed for the simplified stripline geometries. The required characteristic impedances and the geometric factors are determined analytically for the simplified geometries and compared with the results for the designed stripline geometry using the 2-D POISSON code by solving the Laplace’s equation in two dimensions. Lambertson’s equations are compared with numerical results. We introduce the frequency range, within which we can apply the analytical approach.

43 PARTICLE ACCELERATORS↗

DOE OSTI2021

Universal dwell time optimization for deterministic optics fabrication

Computer-Controlled Optical Surfacing (CCOS) has been greatly developed and widely used for precision optical fabrication in the past three decades. It relies on robust dwell time solutions to determine how long the polishing tools must dwell at certain points over the surfaces to achieve the expected forms. However, as dwell time calculations are modeled as ill-posed deconvolution, it is always non-trivial to reach a reliable solution that 1) is non-negative, since CCOS systems are not capable of adding materials, 2) minimizes the residual in the clear aperture 3) minimizes the total dwell time to guarantee the stability and efficiency of CCOS processes, 4) can be flexibly adapted to different tool paths, 5) the parameter tuning of the algorithm is simple, and 6) the computational cost is reasonable. In this study, we propose a novel Universal Dwell time Optimization (UDO) model that universally satisfies these criteria. First, the matrix-based discretization of the convolutional polishing model is employed so that dwell time can be flexibly calculated for arbitrary dwell points. Second, UDO simplifies the inverse deconvolution as a forward scalar optimization for the first time, which drastically increases the solution stability and the computational efficiency. Finally, the dwell time solution is improved by a robust iterative refinement and a total dwell time reduction scheme. The superiority and general applicability of the proposed algorithm are verified on the simulations of different CCOS processes. A real application of UDO in improving a synchrotron X-ray mirror using Ion Beam Figuring (IBF) is then demonstrated. The simulation indicates that the estimated residual in the 92.3 mm × 15.7 mm CA can be reduced from 6.32 nm Root Mean Square (RMS) to 0.20 nm RMS in 3.37 min. After one IBF process, the measured residual in the CA converges to 0.19 nm RMS, which coincides with the simulation.

36 MATERIALS SCIENCE↗

DOE OSTI2020

The organic redox transistor for neuromorphic computing

Inspired by the in-memory computing architectures of biological systems, neuromorphic computing using crossbar arrays of artificial synapses based on non-volatile memory (NVM) devices with variable conductances has emerged as a new paradigm to enable massively parallel and ultra-low power computing hardware for data centric applications. Although inference has been demonstrated successfully using crossbars based on a variety of NMV technologies, efficient learning and scaling to large arrays (>10 6 elements) remains a challenge due to the synaptic elements' non-ideal electrical characteristics which degrades ANN accuracy. A further challenge is that in the conductive state memristors draw large currents >μA resulting in significant voltage drops in the interconnect wires and increased probability of failure in scaled arrays. We suggest the organic polymer redox transistor (RT) is an alternate approach that could solve many of these challenges, enabling both inference and parallel outer product updates, as recently demonstrated by Fuller et al. An RT consists of redox-active channel and gate electrodes in contact with a liquid or solid electrolyte. lon insertion through the electrolyte controls the channel electronic conductivity, while electron transfer through an external circuit maintains overall charge neutrality. Unlike a rechargeable battery, in the RT the voltage built-up across the electrolyte is kept to a minimum (typically <100 mV) by using the same material for the gate and channel. Elimination of the voltage offset simplifies integration of the RT into programmable arrays by enabling the use of various selectors. RTs based on inorganic and organic materials have been recently demonstrated with conductance tuning occurring at potentials of just a few mV and hundreds to thousands of linearly and symmetrically programmable conductance states, enabling near ideal accuracy in neural network simulations. Introduced in the 1980's, redox transistors with metallic gate electrodes and organic channel materials, also known as organic electrochemical transistors (OECTs), have been explored for a variety of applications such as chem- and bio-sensing, neural interfaces, and low cost printed circuits. A typical channel material for OECTs is the conducting polymer poly(3,4-ethylenedioxythiophene) doped with poly(styrene sulfonate) (PEDOT:PSS). PEDOT is a p-type semiconducting polymer with mobile positively charged polarons that hop chain-to-chain.

Talin, Albert Alec↗

DOE OSTI2022

Disentangling jet modification in jet simulations and in Z+jet data

The selection of jets in heavy-ion collisions based on their p T after jet quenching is known to bias towards jets that lost little energy in the quark-gluon plasma. In this work, we study and quantify the impact of this selection bias on jet substructure observables so as to isolate effects caused by the modification of the substructure of jets by quenching. We do so at first in a simplified Monte Carlo study in which it is possible to identify the same jet before and after quenching. We show explicitly that jets selected based on their quenched (i.e. observable) p T have substantially smaller fractional energy loss than those selected based on the p T that they would have had in the absence of any quenching. This selection bias has a large impact on jet structure and substructure observables. As an example, we consider the angular separation ΔR of the hardest splitting in each jet, and find that the ΔR distribution of the (biased) sample of jets selected based upon their quenched p T is almost unmodified by quenching. In contrast, quenching causes dramatic modifications to the ΔR distribution of a sample of jets selected based upon their unquenched p T , with a significant enhancement at larger ΔR coming from the soft particles originating from the wake of the jet in the quark-gluon plasma. The jets which contribute to this enhancement are those which have lost the most energy and which were, therefore, left out of the sample selected after quenching. In a more realistic study, we then show that the same qualitative effects can all be observed in Z+jet events. Selecting jets in such events based on either the jet p T or the Z-boson p T provides an experimentally accessible way to quantify the effects of selection biases in jet observables and separate them from the modification of jet substructure caused by quenching. Selecting Z+jet events based upon the jet p T yields a ΔR distribution that appears almost unmodified whereas selecting Z+jet events based upon the Z-boson p T reveals a significant modification to the ΔR-distribution caused by quenching, once again arising from the wakes of those jets that lose more energy.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2022

Coupling of nTRACER to COBRA-TF for full core high-fidelity analysis of VVERs

The evolution of computing clusters allows the use of high-resolution multi-physics solvers for reactor analysis. Despite the continuous expansion of VVER technology, only one other high-fidelity sub-pin multi-physics core solver is currently developed for safety analysis. To that end the Laboratory of Reactor Physics and Thermal-Hydraulics (LRT) of Paul Scherrer Institut is developing such a tool with the coupling of the neutronic code nTRACER and the sub-channel code COBRA-TF. This work follows the initial steps of the coupling and focuses to the extension of the core solver to full core VVER geometries. The X2 VVER-1000 benchmark is modeled with the novel core solver. The results are compared to the ones of a standalone nTRACER calculation where the feedbacks are provided by a simplified 1D thermal-hydraulic solver. Despite relatively good agreement in power distribution, the limitations of the simplified solver become apparent especially when comparing global temperature profiles. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2023

Sensitivity of Arctic Surface Temperature to Including a Comprehensive Ocean Interior Reflectance to the Ocean Surface Albedo Within the Fully Coupled CESM2

Abstract Almost all current climate models simplify the ocean surface albedo (OSA) by assuming the reflected solar energy without the ocean interior contribution. In this study, an improved ocean surface albedo scheme is incorporated into the Community Earth System Model version 2 (CESM2) to assess the sensitivity of Arctic surface temperature to including ocean interior reflectance to the OSA. Fully coupled CESM2 simulations with and without ocean interior reflectance are subsequently performed, we focus on the analysis of Arctic surface temperature responses. Incorporating ocean interior reflectance increases absorbed solar radiation and warms the ocean, enhancing seasonal heat storage and release across the Arctic Ocean, and increasing sea ice reduction and positive climate feedbacks that elevates Arctic surface temperature. Seasonal variations in air‐surface temperature differences induce changes in turbulent heat flux patterns, concurrently modifying dynamic advection and moisture processes that affect boundary layer humidity and low clouds, especially in winter. Based on partitioning physical processes in the thermodynamic energy equation, surface air warming is induced primarily through positive heating anomalies of vertical advection, latent heat release, and longwave radiative forcing. Through an examination of the surface energy budget, skin temperature warming is driven predominantly by increased downward longwave radiation, positive surface albedo feedback in summer, and increased conductive heat transport from the ocean particularly in winter. Significant effects of ocean interior reflectance on the Arctic Ocean, including sea surface warming and sea ice reduction, justify the importance of ocean interior reflectance in climate models for better understanding of ongoing Arctic climate changes.

Meteorology & Atmospheric Sciences↗

DOE OSTI2020

Rapid thermal emittance and quantum efficiency mapping of a cesium telluride cathode in an rf photoinjector using multiple laser beamlets

Thermal emittance and quantum efficiency (QE) are key figures of merit of photocathodes, and their uniformity is critical to high-performance photoinjectors. Several QE mapping technologies have been successfully developed; however, there is still a dearth of information on thermal emittance maps. This is because of the extremely time-consuming procedure to gather measurements by scanning a small beam across the cathode with fine steps. To simplify the mapping procedure and to reduce the time required to take measurements, we propose a new method that requires only a single scan of the solenoid current to simultaneously obtain thermal emittance and QE distribution by using a pattern beam with multiple beamlets. In this paper, its feasibility has been confirmed by both beam dynamics simulation and theoretical analysis. The method has been successfully demonstrated in a proof-of-principle experiment using an L-band radio-frequency photoinjector with a cesium telluride cathode. In the experiment, seven beamlets were generated from a microlens array system and their corresponding thermal emittance and QE varied from 0.93 to 1.14 mu m/nun and from 4.6% to 8.7%, respectively. We also discuss the limitations and future improvements of the method in this paper.

43 PARTICLE ACCELERATORS↗

DOE OSTI2023

Characterizing the expected behavior of non-Poissonian template fitting

We have performed a systematic study of the statistical behavior of non-Poissonian template fitting (NPTF), a method designed to analyze and characterize unresolved point sources in general counts datasets. Here, in this paper, we focus on the properties and characteristics of the Fermi-LAT gamma-ray data set. In particular, we have simulated and analyzed gamma-ray sky maps under varying conditions of exposure, angular resolution, pixel size, energy window, event selection, and source brightness. We describe how these conditions affect the sensitivity of NPTF to the presence of point sources, for inner-galaxy studies of point sources within the Galactic Center excess, and for the simplified case of isotropic emission. We do not find opportunities for major gains in sensitivity from varying these choices, within the range available with current Fermi-LAT data. We provide an analytic estimate of the NPTF sensitivity to point sources for the case of isotropic emission and perfect angular resolution, and find good agreement with our numerical results for that case.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2025

Q-Cluster: Quantum Error Mitigation Through Noise-Aware Unsupervised Learning

Quantum error mitigation (QEM) is critical in reducing the impact of noise in the pre-fault-tolerant era, and is expected to complement error correction in fault-tolerant quantum computing (FTQC). In this work, we propose a novel QEM approach, Q-Cluster, that uses unsupervised learning (clustering) to reshape the measured bit-string distribution. Our approach starts with a simplified bit-flip noise model. It first performs clustering on noisy measurement results, i.e., bit-strings, based on the Hamming distance. The centroid of each cluster is calculated using a qubit-wise majority vote. Next, the noisy distribution is adjusted with the clustering outcomes and the bitflip error rates using Bayesian inference. Our simulation results show that Q-Cluster can mitigate high noise rates (up to 40% per qubit) with the simple bit-flip noise model. However, real quantum computers do not fit such a simple noise model. To address the problem, we (a) apply Pauli twirling to tailor the complex noise channels to Pauli errors, and (b) employ a machine learning model, ExtraTrees regressor, to estimate an effective bit-flip error rate using a feature vector consisting of machine calibration data (gate & measurement error rates), circuit features (number of qubits, numbers of different types of gates, etc.) and the shape of the noisy distribution (entropy). Our experimental results show that our proposed Q-Cluster scheme improves the fidelity by a factor of 1.46x, on average, compared to the unmitigated output distribution, for a set of low-entropy benchmarks on five different IBM quantum machines. Our approach outperforms the state-of-art QEM approaches RZNE [28], M3 [24], Hammer [35], and QBEEP [33] by 1.26x,1.29x,1.47x, and 2.65 x, respectively.

42 ENGINEERING↗

DOE OSTI2021

Modeling Microstructural Effects on Heterogeneous Temperature Fields within Polycrystalline Explosives

The paper addresses the role of crystal anisotropy on the evolution of heterogeneous temperature fields in plastic-bonded explosives (PBXs) under conditions of weak shock. The modeling approach is based on simplified idealizations of PBX microstructure including RDX grains and estane binder regions subjected to velocity boundary conditions representative of impact conditions in situ. The constitutive description of the microstructure constituents includes a dislocation-based, anisotropic, single crystal plasticity model for the explosive grains and a linear viscoelastic model to represent the estane binder. Large suites of simulations were used to systematically study the correlation in heating of the grains with local wave dynamics, crystal orientation, and the microstructural neighborhood. These correlations were identified through the selection of characteristics of crystal anisotropy including oriented wave speeds and Taylor factor. A key observation is that the wave dispersion within a certain distance from the impact interface plays a dominant role in the temperature field. Beyond this distance, individual crystal orientations play a more dominant role, but cannot entirely account for the observed heterogeneity without consideration of the local microstructure neighborhood.

42 ENGINEERING↗

DOE OSTI2020

Resolution matters when modeling climate change in headwaters of the Colorado River

The continued growth of Southwestern cities depends on reliable water export from Rocky Mountain headwaters, which provide ~85% of Colorado River Basin (CRB) streamflow. Despite being more sensitive to warming temperatures, alpine systems are simplified in the regional-scale models currently in use to plan for future water supply. We used an integrated hydrologic model that couples groundwater and surface water with snow and vegetation processes to examine the effect of topographic simplifications as a result of grid coarsening in a representative CRB headwater basin. High-resolution (100 m) simulations predicted headwater streamflow losses of 16% by 2050 while coarse-resolution (1 km) simulations predict only 12%, suggesting that regional-scale models (coarser than 1 km) likely overestimate future Colorado River Basin water supplies.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Advancing the Frontiers of Deep Learning for Low-Dose 3D Cone-Beam CT Reconstruction

X-ray computed tomography (CT) is an important noninvasive medical imaging modality for studying the structural details of internal organs. Image reconstruction in CT is an inverse problem of recovering an object's internal structure from the absorption profile of X-ray beams (sinogram) measured using a detector. The classical variational approach for CT reconstruction minimizes an energy functional using an appropriate iterative algorithm. Motivated by the success of deep learning (DL), researchers have begun to leverage training data and enhanced computing capabilities in recent years to produce high-fidelity reconstructed images. Nonetheless, much of the academic research in DL algorithms for CT has focused primarily on the two-dimensional setting (with simplified forward operators and noise model) for proofs-of-concept, and a comprehensive benchmarking of various classical and data-driven CT reconstruction approaches has not beenundertaken. The key objective of our CT reconstruction grand challenge was to promote methodological advancements for both classical and DL-based approaches for clinical CT with a reasonably accurately simulated 3D CT forward operator and noise model. We have utilized the publicly available LIDC-IDRI dataset and simulated sinograms and FDK images corresponding to two dose levels (clinical- and low-dose, constituting two tracks of the challenge) starting from the normal-dose images as the ground truth. In this paper, we summarize the motivation, context, and results of our challenge, and highlight the future research directions in DL for clinical CT.

X-ray tomography↗

DOE OSTI2024

Numerical Improvements in Magnetohydrodynamic, Pulsed Power Simulations of Near-Target Plasmas

Magnetohydrodynamic (MHD) simulations of pulsed power experiments frequently result in unphysical runaway heating when extended to low values of mass density. Traditionally, this has been addressed by the use of conductivity floors below which the plasma is given an arbitrarily low conductivity value. Here, a low-density treatment is presented that allows for low-density material to carry current while maintaining a stable temperature. This treatment is implemented in the Ares multiphysics code. Numerical modifications to the conventional vacuum treatment include an energy-conserving density floor, a modified averaging procedure to determine the thermal conductivity at the edge of adjacent zones, and a modified averaging procedure for determining the thermal conductivity in mixed zones that contain material from differing regions. Additionally, anomalous resistivity and Bohm diffusion models are implemented as simplified models for microphysics-induced enhancement of collisional transport. Importantly, the advantage of these various improvements are illustrated in a simple 1-D pulsed power target where the combined changes result in stable temperatures within the lower density regions.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2021

Plasma heating and current sheet structure in anti-parallel magnetic reconnection

A theoretical model and an analytic theory of current sheet structure are presented for understanding anti-parallel driven magnetic reconnection in 2-1/2 dimension in collisionless plasmas. The theoretical model provides formulation to compute the current sheet y-profiles by specifying the profiles of electron and ion flow velocities V ex (x,y) and V ix (x,y). The current sheet solutions depend on the plasma density n in , merging magnetic field B 0 , ion velocity v i , and electron velocity ve in the upstream and the S evz =V ez /V dz parameter where V ez is the electron velocity accelerated by the reconnection electric field E z in the electron orbit meandering region, V dz ≃cE y /B x is the $\overrightarrow{E}$ × $\overrightarrow{B}$ drift velocity as electrons enter the orbit meandering region, B x is the merging magnetic field, and E y is the electrostatic electric field. With simplifying assumptions on the y-profiles of V ex and V ix , we have also developed an analytic theory of the current sheet structure. Analytic expressions for the anomalous resistivity, the electrostatic potential drop, and the maximum E y amplitude E max are obtained. The analytic results agree reasonably well with both the particle-in-cell simulation results and the numerical solutions of the theoretical model. The ions energy gain due to the potential drop is $∝B^2_0/n_{in}$. The electron energy gain is $∝(B^2_0 /8πn_{in})S_{evz}$. The $B^2_0/n_{in}$ scaling of the average ion and electron energy gains are consistent with laboratory experiments and space plasma observations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2022

Evaluating power grid model hydropower feasibility with a river operations model

Production cost models (PCMs) simulate dispatch of generators across a large power grid and are used widely by planners to study the reliability of electricity supply. As energy systems transition away from the thermoelectric technologies that have traditionally balanced electricity supply and demand, hydropower and its representation in PCMs is of increasing importance. A limitation of PCMs applied to continental power grids with diverse generation portfolios is that hydropower generation is simulated without full consideration of complex river dynamics, leading to possible misrepresentation of grid flexibility and performance. In addition, data used in PCMs may reflect outdated operating policies. In this paper we propose a hydropower generation feasibility test for PCMs. The approach uses a detailed hydropower model to determine whether the hourly hydropower schedule from a PCM with simplified monthly parameterization can be attained after accounting for realistic river dynamics and operating policies, such as spill requirements and general water movement and balance through a cascade reservoir system. We perform this hydropower generation test for the ‘Big 10’ hydropower system on the Columbia River (part of the Western Interconnect of the United States), revealing 9% overestimation of available hydropower generation in a PCM solution in an average hydrologic year. Our evaluation provides insight on the cost and opportunities for better representing hydropower in PCMs.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Chemical timescale effects on detonation convergence

Numerical simulations of detonation-containing flows have emerged as crucial tools for designing next- generation power and propulsion devices. As these tools mature, it is important for the combustion community to properly understand and isolate grid resolution effects when simulating detonations. To this end, the objective of this work is to provide a comprehensive analysis of the numerical convergence of unsteady detonation simulations, with focus on isolating the impacts of chemical timescale modifications on convergence characteristics in the context of operator splitting. With the aid of an AMReX-based adaptive mesh refinement flow solver-which enables resolutions up to ($\mathcal{O}$ (1000) cells-per-induction length-the convergence analysis is conducted using two kinetics configurations: (1) the simplified three-step Arrhenius-based model mechanism of Short and Quirk (1997), where chemical timescales in the detonation are modified by adjusting activation energies in the initiation and branching reactions, and (2) a detailed hydrogen- air mechanism, where the chemical timescales are adjusted by varying the ambient pressure. The convergence of unsteady self-sustained detonations in one-dimensional channels is then analyzed with reference to steady-state theoretical baseline solutions using these mechanisms. The goal of the analysis is to provide a detailed comparison of the effects of grid resolution on both macroscopic (peak pressures and wave speeds) and microscopic (wave structure) quantities of interest, drawing connections between the deviations from steady-state baselines and minimum chemical timescales. In particular, chemical timescale reductions were found to have minimal impact on the convergence of macroscopic properties. Furthermore, analyses of microscopic convergence trends, particularly in the reaction front location, revealed a key insight: maintaining the induction time while eliminating prohibitive chemical timescales through mechanism simplifications and combustion modeling can significantly enhance detonation convergence properties. Ultimately, this work uncovers resolution-dependent unsteady detonation convergence regimes and highlights the important role played by not only the chemical timescales, but also the ratio between the chemical timescale and induction time on the numerical convergence of the detonation wave structure.

Adaptive mesh refinement↗

DOE OSTI2023

IM3 GO WEST Parameter Search Dataset

GO WEST is an open-source power grid modeling framework for U.S. Western Interconnection, which allows users to tailor the model depending on their research study and science questions. It is developed to address weather and water dynamics, and associated vulnerabilities in this bulk power system. It covers 28 balancing authorities (BA) and 12 states in U.S. Western Interconnection. GO WEST allows users to select different number of nodes and come up with a simplified network by utilizing 10,000 nodal topology of U.S. Western Interconnection created by Texas A&M University. Users can try and select different number of nodes, mathematical formulations (linear programming vs. mixed-integer linear programming), transmission line limit scaling factors, and hurdle rate scaling factors. GO WEST offers a unit commitment and economic dispatch (UC/ED) module to simulate grid operations on an hourly scale. In this sense, users can calibrate and validate their model versions by comparing model outputs to historical datasets. Therefore, GO WEST can help researchers to strike a balance between model fidelity (i.e. accuracy) and computational complexity (i.e. runtime). This dataset includes model inputs and outputs from 600 model versions for each 2019, 2020, and 2021. The folder naming convention is as follows: Exp{Number of Nodes}_{Mathematical Formulation}_{Transmission Line Limit Scaling Factor in MW}_{Hurdle Rate Scaling Factor in %}_{Year}. Linear programming is designated with "simple" label whereas mixed-integer linear programming is designated with "coal" label. For example, "Exp100_simple_1000_50_2019" folder contains inputs and outputs from 2019 model version with 100 nodes, linear programming, +1000 MW transmission line limit scaling factor, and +50% hurdle rate scaling factor. GO WEST GitHub repository hosts all raw datasets, processing scripts, and model scripts. Please refer to the README file for a detailed description of the included files.

Economics↗