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DOE OSTI2026

Computationally efficient Bayesian estimation of graphical networks for omics data

Graphical networks are useful, widely-used modeling approaches to represent complex biological processes with biological measurements generated by platforms such as mass spectrometry. Bayesian analyses of graphical networks for omics data have several advantages over their frequentist counterparts, such as the inclusion of prior knowledge in the estimation of models. However, Bayesian approaches to date have only been feasible for data with a couple hundred biomolecules due to prohibitive computational time, but omics data often contains tens of thousands of biomolecules. Here, we present and illustrate a more computationally efficient approach named BPlane (Bayesian PseudoLikelihood-based Algorithm for Network Estimation) to extend Bayesian modeling capabilities for larger-sized datasets, such as most untargeted proteomics data. Via simulation, we demonstrate that BPlane produces substantial computational savings over a current state-of-the-art Bayesian algorithm while maintaining competitive edge detection accuracy. On a SARS-CoV2 proteomics data with 7000 proteins, the competing algorithm takes three times as long to complete the first iteration as BPlane takes to converge after over 100 iterations.

EM algorithm↗

DOE OSTI2020

Energy Storage in Long-Term System Models: A Review of Considerations, Best Practices, and Research Needs

Technological change and policy support have heightened expectations for the role of energy storage in power systems, creating a need to enhance representations of energy storage in long-term models to inform decision-making. Energy storage technologies have complex and diverse cost, value, and performance characteristics that make them challenging to model, but there is limited guidance about best practices and research gaps for energy storage analysis. This paper reviews the literature and draws upon our collective experience to provide recommendations to analysts on approaches for representing energy storage in long-term electric sector models, navigating tradeoffs in model development, and identifying research gaps for existing tools and data. The review focuses on national-scale models with technological, temporal, and regional detail given their prevalence in planning and policy, though many insights are transferable to other modeling contexts. It also offers guidance to consumers of model outputs on proper use and interpretation based on model strengths and limitations. In particular, this review demonstrates the importance of capturing how the values of energy storage and other resources change as the system composition changes (e.g. with different levels of storage, renewables deployment, and emissions outcomes). These considerations require model detail like high spatiotemporal resolutions and endogenous investments that global integrated assessment models and price-taker frameworks do not typically resolve. Research gaps include linking tools of different resolutions, developing reduced-form representations of value streams, incorporating hybrid energy storage and renewable systems, and representing longer-duration energy storage technologies.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

DOE OSTI2025

Differential cross-section measurements of Higgs boson production in the H → τ + τ - decay channel in pp collisions at $\sqrt{s}$ = 13 TeV with the ATLAS detector

Differential measurements of Higgs boson production in the τ-lepton-pair decay channel are presented in the gluon fusion, vector-boson fusion (VBF), VH and $t\overline{t}H$ associated production modes, with particular focus on the VBF production mode. The data used to perform the measurements correspond to 140 fb -1 of proton-proton collisions collected by the ATLAS experiment at the LHC. Two methods are used to perform the measurements: the Simplified Template Cross-Section (STXS) approach and an Unfolded Fiducial Differential measurement considering only the VBF phase space. For the STXS measurement, events are categorized by their production mode and kinematic properties such as the Higgs boson’s transverse momentum (${p}_{\textrm{T}}^{\textrm{H}}$ ), the number of jets produced in association with the Higgs boson, or the invariant mass of the two leading jets (mjj). For the VBF production mode, the ratio of the measured cross-section to the Standard Model prediction for m jj > 1.5 TeV and ${p}_{\textrm{T}}^{\textrm{H}}$ > 200 GeV (${p}_{\textrm{T}}^{\textrm{H}}$ < 200 GeV) is ${1.29}_{-0.34}^{+0.39}$ (${0.12}_{-0.33}^{+0.34}$ ). This is the first VBF measurement for the higher-${p}_{\textrm{T}}^{\textrm{H}}$ criteria, and the most precise for the lower-${p}_{\textrm{T}}^{\textrm{H}}$ criteria. The fiducial cross-section measurements, which only consider the kinematic properties of the event, are performed as functions of variables characterizing the VBF topology, such as the signed ΔΦ jj between the two leading jets. The measurements have a precision of 30%–50% and agree well with the Standard Model predictions. These results are interpreted in the SMEFT framework, and place the strongest constraints to date on the CP-odd Wilson coefficient ${c}_{H\overset{\sim }{W}}$ .

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2020

PASSAT: particle accelerator helioScopes for Slim Axion-like-particle deTection

We propose a novel method to search for axion-like particles (ALPs) at particle accelerator experiments. ALPs produced at the target via the Primakoff effect subsequently enter a region with a magnetic field, where they are converted to photons that are then detected. Dubbed Particle Accelerator helioScopes for Slim Axion-like-particle deTection (PASSAT), our proposal uses the principle of the axion helioscope but replaces ALPs produced in the Sun with those produced in a target material. Since we rely on ALP-photon conversions , our proposal probes light (slim) ALPs that are otherwise inaccessible to laboratory-based experiments which rely on ALP decay, and complements astrophysical probes that are more model-dependent. As a first application, we reinterpret existing data from the NOMAD experiment in light of PASSAT, and constrain the parameter space for ALPs lighter than $$\sim 100~\mathrm{eV}$$ ~ 100 eV and ALP-photon coupling larger than $$\sim 10^{-4}~\mathrm{GeV}^{-1}$$ ~ 10 - 4 GeV - 1 . As benchmarks of feasible low-cost experiments improving over the NOMAD limits, we study the possibility of re-using the magnets of the CAST and the proposed BabyIAXO experiments and placing them at the proposed BDF facility at CERN, together with some new detectors. We find that these realizations of PASSAT allow for a direct probe of the parameter space for ALPs lighter than $$\sim 100~\mathrm{eV}$$ ~ 100 eV and ALP-photon coupling larger than $$\sim 4\times 10^{-6}~\mathrm{GeV}^{-1}$$ ~ 4 × 10 - 6 GeV - 1 , which are regions that have not been probed yet by experiments with laboratory-produced ALPs. In contrast to other proposals aiming at detecting single or two-photon only events in hadronic beam dump environments, that rely heavily on Monte Carlo simulations, the background in our proposal can be directly measured in-situ , its suppression optimized, and the irreducible background statistically subtracted. Sensitivity evaluations with other beams will be the subject of a future paper. The measurements suggested in this paper represent an additional physics case for the BDF at CERN beyond those already proposed.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2026

Collapse of magnetized white dwarfs as site of heavy-element formation and kilonova signal

We present the first end-to-end calculation connecting the accretion-induced collapse (AIC) of a magnetized, rapidly rotating white dwarf to observable kilonova signatures, combining two-dimensional (2D) general-relativistic neutrino-magnetohydrodynamic simulations, followed by radiation hydrodynamics with in-situ nuclear network and 2D Monte Carlo radiative transfer with spatially resolved heating rates. Unlike all previous unmagnetized AIC models – which predicted proton-rich, $^{56}$Ni-dominated ejecta – strong magnetic fields eject ${\approx }\, 0.2\, \mathrm{ M}_\odot$ of neutron-rich material ($\langle Y_e \rangle \sim 0.24$) on dynamical time-scales, before neutrino irradiation can raise the electron fraction, enabling strong r-process nucleosynthesis up to and beyond the third peak. The resulting kilonova is lanthanide-rich ($X_{\rm lan} \approx 8~{{\ \rm per\ cent}}$) and dominated by near-infrared emission. We compute synthetic light curves in the Large Synoptic Survey Telescope and J ames Webb Space Telescope bands and find striking agreement, without parameter tuning, between the observations of AT 2023vfi/GRB 230307A and our broadband light curves for polar viewing angles. These results establish magnetized AIC as a viable channel for heavy r-process element production and a compelling progenitor candidate for long-duration gamma-ray bursts with kilonova signatures.

MHD↗

DOE OSTI2021

Modelling the stellar halo with RR-Lyrae stars

ABSTRACT A seven-parameter distribution function (DF) is fitted to $20\, 000$ RR-Lyrae stars for which only astrometric data are available. The observational data are predicted by the DF in conjunction with the gravitational potential of a self-consistent model Galaxy defined by DFs for the dark halo, the bulge, and a four-component disc. Tests of the technique developed to deal with missing line-of-sight velocities show that adding such velocities tightens constraints on the DF only slightly. The recovered model of the RR-Lyrae population confirms that the population is flattened and has a strongly radially biased velocity distribution. At large radii, its density profile tends to ρ ∼ r−4.5 but no power law provides a good fit inside the solar sphere. The model is shown to provide an excellent fit to the data for stars brighter than r = 16.5 but at certain longitudes it predicts too few faint stars at Galactocentric radii $\sim 20\, \mathrm{kpc}$, possibly signalling that the halo is not axisymmetric. The DF is used to predict the velocity distribution of BHB stars for which space velocities are available. The z components are predicted successfully but too much anisotropy in the vRvϕ plane is expected.

Li, Chengdong↗

DOE OSTI2021

Quality Data Essential for Modeling Water Cycles Effectively

The experimental and observational data is the backbone of effective modeling of all aspects of water cycles. As the computer technology used for these data gathering efforts has improved dramatically in the recent decades, the environmental conditions these instruments are subjected to remain pretty much the same. These measuring instruments are exposed to the sun light, wind, rain, snow and ice; and they are immersed in dirt, water and mud. All of these are damaging to the electronics components used for data gathering, storage, and transmission, which creates many different kinds of data quality issues that affect the quality and reliability of modeling and prediction efforts.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

The three-dimensional structure of black hole accretion flows within the plunging region

ABSTRACT We analyse, using new analytical models and numerical general relativistic magnetohydrodynamic simulations, the three-dimensional properties of accretion flows inside the plunging region of black hole spacetimes (i.e. at radii smaller than the innermost stable circular orbit). These simulations are of thick discs, with aspect ratios of order unity $h/r \sim 1$, and with a magnetic field geometry given by the standard low-magnetization ‘SANE’ configuration. This work represents the first step in a wider analysis of this highly relativistic region. We show that analytical expressions derived in the ‘thin disc’ limit describe the numerical results remarkably well, despite the large aspect ratio of the flow. We further demonstrate that accretion within this region is typically mediated via spiral arms, and that the geometric properties of these spiral structures can be understood with a simple analytical model. These results highlight how accretion within the plunging region is fundamentally two-dimensional in character, which may have a number of observational implications. We derive a modified theoretical description of the pressure within the plunging region which accounts for turbulent heating and may be of use to black hole image modelling.

Astronomy & Astrophysics↗

DOE OSTI2024

A Deep Multimodal Representation Learning Framework for Accurate Molecular Properties Prediction

Drug discovery is a complex and challenging process, requiring the optimization of candidate compounds to identify those with the potential to become safe and effective drugs. Predicting molecular properties is an indispensable step in the drug discovery pipeline. Traditionally, this process is costly and time-intensive, involving multiple rounds of experiments and clinical trials, rendering it impractical for every candidate compound. Deep learning techniques have emerged as a promising approach to drug discovery to reduce the cost and time required to identify novel drugs. However, prevalent research in deep learning models focused on predicting molecular properties has primarily fixated on single-modal models, which utilize a single modality of data, neglecting the potential benefits of combining different data modalities. To overcome this limitation, we introduce MRL-Mol: a deep \textbf{M}ultimodal \textbf{R}epresentation \textbf{L}earning framework for accurate \textbf{Mol}ecular properties prediction. MRL-Mol harnesses three data modalities: sequence, graph, and image, augmenting the depth of comprehension. Leveraging a large-scale unlabeled dataset~($\sim$1M unique molecules), we pretrain MRL-Mol to extract inter- and intra-modal information. Our study demonstrates the superior performance of MRL-Mol in predicting molecular properties across six benchmark datasets, including both classification and regression tasks. Notably, MRL-Mol outperforms other state-of-the-art molecular properties prediction models. These findings suggest that by combining information from multiple data modalities, MRL-Mol can comprehend molecules better than single-modal deep learning models and identify molecular properties with better accuracy.

Yang, Yuxin↗

DOE OSTI2021

Studying Corrosion Using Miniaturized Particle Attached Working Electrodes and the Nafion Membrane

We developed a new approach to attach particles onto a conductive layer as a working electrode (WE) in a microfluidic electrochemical cell with three electrodes. Nafion, an efficient proton transfer molecule, is used to form a thin protection layer to secure particle electrodes. Spin coating is used to develop a thin and even layer of Nafion membrane. The effects of Nafion (5 wt% 20 wt%) and spinning rates were evaluated using multiple sets of replicates. The electrochemical performance of various devices was demonstrated. Additionally, the electrochemical performance of the devices is used to select and optimize fabrication conditions. The results show that a higher spinning rate and a lower Nafion concentration (5 wt%) induce a better performance, using cerium oxide (CeO2) particles as a testing model. The WE surfaces were characterized using atomic force microscopy (AFM), scanning electron microscopy-focused ion beam (SEM-FIB), time-of-flight secondary ion mass spectrometry (ToF-SIMS), and X-ray photoelectron spectroscopy (XPS). The comparison between the pristine and corroded WE surfaces shows that Nafion is redistributed after potential is applied. Our results verify that Nafion membrane offers a reliable means to secure particles onto electrodes. Furthermore, the electrochemical performance is reliable and reproducible. Thus, this approach provides a new way to study more complex and challenging particles, such as uranium oxide, in the future.

42 ENGINEERING↗

DOE OSTI2024

An FPGA-based hardware accelerator supporting sensitive sequence homology filtering with profile hidden Markov models

Abstract Background Sequence alignment lies at the heart of genome sequence annotation. While the BLAST suite of alignment tools has long held an important role in alignment-based sequence database search, greater sensitivity is achieved through the use of profile hidden Markov models (pHMMs). Here, we describe an FPGA hardware accelerator, called HAVAC, that targets a key bottleneck step (SSV) in the analysis pipeline of the popular pHMM alignment tool, HMMER. Results The HAVAC kernel calculates the SSV matrix at 1739 GCUPS on a $$\sim$$ ∼ $3000 Xilinx Alveo U50 FPGA accelerator card, $$\sim$$ ∼ 227× faster than the optimized SSV implementation in nhmmer . Accounting for PCI-e data transfer data processing, HAVAC is 65× faster than nhmmer’s SSV with one thread and 35× faster than nhmmer with four threads, and uses $$\sim$$ ∼ 31% the energy of a traditional high end Intel CPU. Conclusions HAVAC demonstrates the potential offered by FPGA hardware accelerators to produce dramatic speed gains in sequence annotation and related bioinformatics applications. Because these computations are performed on a co-processor, the host CPU remains free to simultaneously compute other aspects of the analysis pipeline.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2020

An updated estimate of the Mu2e experiment sensitivity

The Mu2e experiment at Fermilab will search for the conversion of a negative muon into an electron inside the field of a nucleus. This process does not conserve charged-lepton flavour and is heavily suppressed in the Standard Model (SM), with a branching ratio < 10-50. Any evidence of it would be an undeniable evidence of new physics beyond the SM. The project sets out to achieve a single event sensitivity of $\sim 3 × 10^{-17}$ on the ratio between the probability for a conversion of a negative muon into an electron and the one for a muon capture by the nucleus. Such a sensitivity would represent a 4 orders of magnitude improvement on the previous upper limit for the process, making possible to test predictions of different extensions of the SM. Mu2e uses three superconducting solenoids to produce and measure the muon conversions. In the first solenoid, the Production Solenoid, pions and kaons are produced, together with other secondary products, by 8 GeV kinetic energy proton interactions in a tungsten target. A gradient magnetic field is specifically designed to direct low momentum particles into the Transport Solenoid, an S-shaped magnet that filters out particles with unwanted charge and momentum. Muons, produced by pion and kaon decays, finally reach the aluminum Stopping Target in the Detector Solenoid, where they eventually stop and convert. The result of the conversion process is a monochromatic electron of ~105 MeV/c momentum. The Detector Solenoid also hosts the two main detectors: a straw tube tracker and two CsI calorimeter disks, both providing measurement of event kinematics. A germanium detector and a LaBr crystal are located downstream of the Detector Solenoid to measure the X and gamma rays produced by the muon captures in the Stopping Target. A veto system of scintillators covering the Detector Solenoid and half of the Transport Solenoid is used to identify and reject cosmic rays interactions. With respect to the initial project, the Mu2e running plan has evolved to a staged configuration with 2 years at reduced intensity before the 2025 accelerator shutdown for the neutrino beam upgrade and 2 or 3 years at full intensity after that. This, together with geometry changes and a better knowledge of detector performances obtained by the first slice tests, has required a full revision of the signal over background selection that is the subject of this thesis. In order to achieve a new estimate of Mu2e sensitivity, the simulation of the data corresponding to the first 2 years of data acquisition has been performed. This includes both conversion electrons (CE) and the main sources of background: cosmics, decay-in orbits (DIO), radiative pion captures (RPC) and antiprotons. The characteristics of the signal and of the main backgrounds have been studied to define the best selection variables for CE. A special effort has been devoted to the evaluation of the antiproton background. The lack of experimental data for antiproton production cross section makes the systematic uncertainty on this background significant. A new parameterization of the cross section has been developed to fit the existing data and to provide a more reliable estimate of the systematic uncertainty by comparing the results of the old and the new model. A special effort has been devoted to the optimization of the antiprotons Monte Carlo generator. This study has also revealed that the dominant component within this background is represented by antiprotons produced in the opposite direction with respect to the Transport Solenoid entrance and then redirected to it by back-scattering processes in the Production Target. This ultimately highlights the sensitivity of the background estimate to the G4 handling of antiproton interactions in the 1 to 3 GeV/c momentum range. Finally, the final experimental sensitivity has been studied. The momentum and time selection have been optimized to obtain the 5-sigma discovery reach or, in case of no signal, the upper limit on conversion probability. The results confirm that, in the firs t two years of data taking, Mu2e will be able to improve the current experimental sensitivity for muon-to-electron conversion in an atomic field by more than 3 order of magnitudes.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2021

Enhancing the sensitivity of the LUX-ZEPLIN (LZ) dark matter experiment to low energy signals

Two-phase xenon detectors, such as that at the core of the forthcoming LZ dark matter experiment, use photomultiplier tubes to sense the primary (S1) and secondary (S2) scintillation signals resulting from particle interactions in their liquid xenon target. This paper describes a simulation study exploring two techniques to lower the energy threshold of LZ to gain sensitivity to low-mass dark matter and astrophysical neutrinos, which will be applicable to other liquid xenon detectors. The energy threshold is determined by the number of detected S1 photons; typically, these must be recorded in three or more photomultiplier channels to avoid dark count coincidences that mimic real signals. To lower this threshold: a) we take advantage of the double photoelectron emission effect, whereby a single vacuum ultraviolet photon has a $\sim20\%$ probability of ejecting two photoelectrons from a photomultiplier tube photocathode; and b) we drop the requirement of an S1 signal altogether, and use only the ionization signal, which can be detected more efficiently. For both techniques we develop signal and background models for the nominal exposure, and explore accompanying systematic effects, including the dependence on the free electron lifetime in the liquid xenon. When incorporating double photoelectron signals, we predict a factor of $\sim 4$ sensitivity improvement to the dark matter-nucleon scattering cross-section at $2.5$ GeV/c$^2$, and a factor of $\sim1.6$ increase in the solar $^8$B neutrino detection rate. Dropping the S1 requirement may allow sensitivity gains of two orders of magnitude in both cases. Finally, we apply these techniques to even lower masses by taking into account the atomic Migdal effect; this could lower the dark matter particle mass threshold to $80$ MeV/c$^2$.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2021

Enhancing the sensitivity of the LUX-ZEPLIN (LZ) dark matter experiment to low energy signals

Akerib, DS↗

DOE OSTI2021

Wigner SU(4) symmetry, clustering, and the spectrum of $$^{12}$$C

Abstract We present lattice calculations of the low-lying spectrum of $$^{12}$$ 12 C using a simple nucleon–nucleon interaction that is independent of spin and isospin and therefore invariant under Wigner’s SU(4) symmetry. We find strong signals for all excited states up to $$\sim 15$$ ∼ 15 MeV above the ground state, and explore the structure of each state using a large variety of $$\alpha $$ α cluster and harmonic oscillator trial states, projected onto given irreducible representations of the cubic group. We are able to verify earlier findings for the $$\alpha $$ α clustering in the Hoyle state and the second $$2^+$$ 2 + state of $$^{12}$$ 12 C. The success of these calculations to describe the full low-lying energy spectrum using spin-independent interactions suggest that either the spin-orbit interactions are somewhat weak in the $$^{12}$$ 12 C system, or the effects of $$\alpha $$ α clustering are diminishing their influence. This is in agreement with previous findings from ab initio shell model calculations.

Shen, Shihang (ORCID:0000000280516466)↗

DOE OSTI2020

Model-independent discovery prospects for primordial black holes at LIGO

ABSTRACT Primordial black holes may encode the conditions of the early Universe, and may even constitute a significant fraction of cosmological dark matter. Their existence has yet to be established. However, black holes with masses below ${\sim}{1}{\, \mathrm{M}_\odot }$ cannot form as an endpoint of stellar evolution, so the detection of even one such object would be a smoking gun for new physics, and would constitute evidence that at least a fraction of the dark matter consists of primordial black holes. Gravitational wave detectors are capable of making a definitive discovery of this kind by detecting mergers of light black holes. But since the merger rate depends strongly on the shape of the black hole mass function, it is difficult to determine the potential for discovery or constraint as a function of the overall abundance of black holes. Here, we directly maximize and minimize the merger rate to connect observational results to the actual abundance of observable objects. We show that LIGO can discover mergers of light primordial black holes within the next decade even if such black holes constitute only a very small fraction of dark matter. A single merger event involving such an object would (i) provide conclusive evidence of new physics, (ii) establish the nature of some fraction of dark matter, and (iii) probe cosmological history at scales far beyond those observable today.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2025

Exploring additive manufacturing of wind tunnel models for a hypersonic wind tunnel

Presentation for supersonic tunnel association international.

Bhakta, Rajkumar Bipin [Sandia National Laboratori↗

DOE OSTI2020

The completed SDSS-IV extended baryon oscillation spectroscopic survey: pairwise-inverse probability and angular correction for fibre collisions in clustering measurements

ABSTRACT The completed extended Baryon Oscillation Spectroscopic Survey (eBOSS) catalogues contain redshifts of 344 080 quasars at 0.8 < z < 2.2, 174 816 luminous red galaxies between 0.6 < z < 1.0, and 173 736 emission-line galaxies over 0.6 < z < 1.1 in order to constrain the expansion history of the Universe and the growth rate of structure through clustering measurements. Mechanical limitations of the fibre-fed spectrograph on the Sloan telescope prevent two fibres being placed closer than 62 arcsec in a single pass of the instrument. These ‘fibre collisions’ strongly correlate with the intrinsic clustering of targets and can bias measurements of the two-point correlation function resulting in a systematic error on the inferred values of the cosmological parameters. We combine the new techniques of pairwise-inverse probability and the angular upweighting (PIP+ANG) to correct the clustering measurements for the effect of fibre collisions. Using mock catalogues, we show that our corrections provide unbiased measurements, within data precision, of both the projected $\rm {\mathit{ w}_p}\left(\mathit{ r}_p\right)$ and the redshift-space multipole ξ(ℓ = 0, 2, 4)(s) correlation functions down to $0.1\, h^{-1}{\rm Mpc}$, regardless of the tracer type. We apply the corrections to the eBOSS DR16 catalogues. We find that, on scales $s\gtrsim 20\, h^{-1}{\rm Mpc}$ for ξℓ, as used to make baryon acoustic oscillation and large-scale redshift-space distortion measurements, approximate methods such as nearest-neighbour upweighting are sufficiently accurate given the statistical errors of the data. Using the PIP method, for the first time for a spectroscopic program of the Sloan Digital Sky Survey, we are able to successfully access the one-halo term in the clustering measurements down to $\sim 0.1\, h^{-1}{\rm Mpc}$ scales. Our results will therefore allow studies that use the small-scale clustering to strengthen the constraints on both cosmological parameters and the halo occupation distribution models.

79 ASTRONOMY AND ASTROPHYSICS↗