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At least 289 records · Page 16

Core formation in high-z massive haloes: heating by post-compaction satellites and response to AGN outflows

ABSTRACT Observed rotation curves in star-forming galaxies indicate a puzzling dearth of dark matter in extended flat cores within haloes of mass ≥1012M⊙ at z ∼ 2. This is not reproduced by current cosmological simulations, and supernova-driven outflows are not effective in such massive haloes. We address a hybrid scenario where post-compaction merging satellites heat up the dark-matter cusps by dynamical friction, allowing active galactic nucleus (AGN)-driven outflows to generate cores. Using analytic and semi-analytic models (SatGen), we estimate the dynamical friction heating as a function of satellite compactness for a cosmological sequence of mergers. Cosmological simulations (VELA) demonstrate that satellites of initial virial masses >1011.3M⊙, which undergo wet compactions, become sufficiently compact for significant heating. Constituting a major fraction of the accretion on to haloes ≥1012M⊙, these satellites heat up the cusps in half a virial time at z ∼ 2. Using a model for outflow-driven core formation (CuspCore), we demonstrate that the heated dark-matter cusps develop extended cores in response to removal of half the gas mass, while the more compact stellar systems remain intact. The mergers keep the dark matter hot, while the gas supply, fresh and recycled, is sufficient for the AGN outflows. AGNs indeed become effective in haloes ≥1012M⊙, where the black hole growth is no longer suppressed by supernovae and its compaction-driven rapid growth is maintained by a hot circumgalactic medium. For simulations to reproduce the dynamical friction effects, they should resolve the compaction of the massive satellites and avoid artificial tidal disruption. AGN feedback could be boosted by clumpy black hole accretion and clumpy response to AGN.

Dekel, Avishai↗

GW190814: Gravitational Waves from the Coalescence of a 23 Solar Mass Black Hole with a 2.6 Solar Mass Compact Object

We report the observation of a compact binary coalescence involving a 22.2-24.3 M ⊙ black hole and a compact object with a mass of 2.50-2.67 M ⊙ (all measurements quoted at the 90% credible level). The gravitational-wave signal, GW190814, was observed during LIGO's and Virgo's third observing run on 2019 August 14 at 21:10:39 UTC and has a signal-to-noise ratio of 25 in the three-detector network. The source was localized to 18.5 deg 2 at a distance of 241 +41-41 Mpc; no electromagnetic counterpart has been confirmed to date. The source has the most unequal mass ratio yet measured with gravitational waves , 0.112+0.0090.008, , and its secondary component is either the lightest black hole or the heaviest neutron star ever discovered in a double compact-object system. The dimensionless spin of the primary black hole is tightly constrained to ≤0.07. Tests of general relativity reveal no measurable deviations from the theory, and its prediction of higher-multipole emission is confirmed at high confidence. We estimate a merger rate density of 1-23 Gpc -3 yr -1 for the new class of binary coalescence sources that GW190814 represents. Astrophysical models predict that binaries with mass ratios similar to this event can form through several channels, but are unlikely to have formed in globular clusters. However, the combination of mass ratio, component masses, and the inferred merger rate for this event challenges all current models of the formation and mass distribution of compact-object binaries.

79 ASTRONOMY AND ASTROPHYSICS↗

Development and application of sorption mass transfer models for fission product transport in TRISO fuel systems using BISON

Fission product mass transfer within and between TRISO particle and compact layers is an important phenomenon. It directly impacts fission product release predictions, which are used as source terms for safety and licensing calculations. Modeling fission product transport within layers and across bonded interfaces is relatively straightforward under the assumptions of isotropic Fickian diffusion, concentration continuity, and flux continuity. Modeling fission product transport across gaps and debonded layers is more difficult. Gaps are known to form between the buffer and inner PyC (IPyC), and debonding may occur between the IPyC and silicon carbide (SiC). A new mass transfer model was developed to provide a more accurate and robust fission product release calculation by accounting for interlayer sorptivity. One importance of the new model is to account for temperature and material changes across the gap based on sorption isotherm. This work presents the development of the sorption behavioral model and a fission product trapping model, and analyses the subsequent fission product diffusion behavior, specifically cesium, through TRISO particles and compact materials using the BISON fuel performance code.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Data Quality Monitoring for the Hadron Calorimeters Using Transfer Learning for Anomaly Detection

The proliferation of sensors brings an immense volume of spatio-temporal (ST) data in many domains, including monitoring, diagnostics, and prognostics applications. Data curation is a time-consuming process for a large volume of data, making it challenging and expensive to deploy data analytics platforms in new environments. Transfer learning (TL) mechanisms promise to mitigate data sparsity and model complexity by utilizing pre-trained models for a new task. Despite the triumph of TL in fields like computer vision and natural language processing, efforts on complex ST models for anomaly detection (AD) applications are limited. In this study, we present the potential of TL within the context of high-dimensional ST AD with a hybrid autoencoder architecture, incorporating convolutional, graph, and recurrent neural networks. Motivated by the need for improved model accuracy and robustness, particularly in scenarios with limited training data on systems with thousands of sensors, this research investigates the transferability of models trained on different sections of the Hadron Calorimeter of the Compact Muon Solenoid experiment at CERN. The key contributions of the study include exploring TL’s potential and limitations within the context of encoder and decoder networks, revealing insights into model initialization and training configurations that enhance performance while substantially reducing trainable parameters and mitigating data contamination effects.

47 OTHER INSTRUMENTATION↗

A microchannel shell-and-tube absorber for ammonia-water absorption

A shell-and-tube absorber with microscale geometric features that yields significant volumetric heat duties is investigated. A vertically-oriented baffled shell-and-tube heat exchanger with a tightly packed tube bundle is designed to serve as the absorber for a 10.5 kW nominal cooling capacity absorption chiller. The heat and mass transfer in this absorber is investigated experimentally at operating conditions spanning a wide range of working fluid and coupling fluid flow rates and ambient temperatures. An experimental facility is fabricated to closely simulate the operating conditions in an absorption refrigeration system. Absorption heat duties in the range of 5-15 kW are measured. In addition to operating the absorber in the baseline co-current flow configuration with premixed inlet, fluid ports are provided to enable operation in counter-current flow, where the dilute solution enters from the top and vapor enters from the bottom. The performance of these two flow configurations is compared. A preliminary heat and mass transfer model is developed to quantify the local temperatures, concentrations, and mass flow rates of the solution and vapor streams along the length of the absorber. The model predictions for total heat duty agree with the experimental results within 10% for almost all the data points, with an AAD of ~3.4%. Finally, the results of this study, along with the modeling framework, can guide further development of highly compact and efficient absorbers absorption systems.

42 ENGINEERING↗

NeRVI: Compressive neural representation of visualization images for communicating volume visualization results

We present NeRVI, a new deep-learning approach that compresses a large collection of visualization images generated from time-varying data for communicating volume visualization results. Based on an image-based implicit neural representation, our approach represents tens of thousands of high-resolution rendering images parametrized by different parameters via a hybrid model of multilayer perceptrons and convolutional neural networks. Here, our model predicts images and corresponding masks, and the masks are utilized for loss computation and network training to capture fine structural details and small components. In conjunction with model quantization and weight encoding, NeRVI yields highly compact compressive neural representations while preserving the image fidelity well. We demonstrate the effectiveness of NeRVI with isosurface rendering and direct volume rendering images generated from multiple data sets and compare NeRVI with other state-of-the-art deep learning-based (InSituNet, SIREN, NeRF, and NeRV) methods. Quantitative and qualitative results show that NeRVI provides an alternative solution that augments domain scientists' ability to manage, represent, and communicate scientific visualization output.

97 MATHEMATICS AND COMPUTING↗

Equivalence between Fermion-to-Qubit Mappings in two Spatial Dimensions

We argue that all locality-preserving mappings between fermionic observables and Pauli matrices on a two-dimensional lattice can be generated from the exact bosonization in Chen et al., whose gauge constraints project onto the subspace of the toric code with emergent fermions. Starting from the exact bosonization and applying Clifford finite-depth generalized local unitary transformation, we can achieve all possible fermion-to-qubit mappings (up to the re-pairing of Majorana fermions). In particular, we discover a new supercompact encoding using 1.25 qubits per fermion on the square lattice. We prove the existence of finite-depth quantum circuits to obtain fermion-to-qubit mappings with qubit-fermion ratios r = 1 + 1/2k for positive integers k, utilizing the trivialness of quantum cellular automata in two spatial dimensions. Also, we provide direct constructions of fermion-to-qubit mappings with ratios arbitrarily close to 1. When the ratio reaches 1, the fermion-to-qubit mapping reduces to the one-dimensional Jordan-Wigner transformation along a certain path in the two-dimensional lattice. Finally, we explicitly demonstrate that the Bravyi-Kitaev superfast simulation, the Verstraete-Cirac auxiliary method, Kitaev’s exactly solved model, the Majorana loop stabilizer codes, and the compact fermion-to-qubit mapping can all be obtained from the exact bosonization.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Engine Combustion System Optimization Using Computational Fluid Dynamics and Machine Learning: A Methodological Approach

Gasoline compression ignition (GCI) engines are considered an attractive alternative to traditional spark-ignition and diesel engines. Here, a Machine Learning-Grid Gradient Ascent (ML-GGA) approach was developed to optimize the performance of internal combustion engines. ML offers a pathway to transform complex physical processes that occur in a combustion engine into compact informational processes. The developed ML-GGA model was compared with a recently developed Machine Learning-Genetic Algorithm (ML-GA). Detailed investigations of optimization solver parameters and variable limit extension were performed in the present ML-GGA model to improve the accuracy and robustness of the optimization process. Detailed descriptions of the different procedures, optimization tools, and criteria that must be followed for a successful output are provided here. The developed ML-GGA approach was used to optimize the operating conditions (case 1) and the piston bowl design (case 2) of a heavy-duty diesel engine running on a gasoline fuel with a research octane number (RON) of 80. The ML-GGA approach yielded >2% improvements in the merit function, compared with the optimum obtained from a thorough computational fluid dynamics (CFD) guided system optimization. The predictions from the ML-GGA approach were validated with engine CFD simulations. This study demonstrates the potential of ML-GGA to significantly reduce the time needed for optimization problems, without loss in accuracy compared with traditional approaches.

33 ADVANCED PROPULSION SYSTEMS↗

CRADA Final Report: CRADA Number NFE-22-09330 with General Fusion

General Fusion is developing a magnetized target fusion (MTF) approach that involves compressing an initial magnetically confined plasma inside a cavity formed in liquid metal. This approach builds from concepts initially developed under the Linus program at the U.S. Naval Research Laboratory and combines it with advances from compact toroid experiment (CTX) and sustained spheromak plasma experiment (SSPX) in compact toroid plasmas and coaxial Marshall gun systems. Modeling the tokamak during compression is central to designing a successful MTF device. The plasma is formed by coaxial helicity injection in the General Fusion device. Immediately after formation, the plasma has a diverted tokamak configuration with a single null. As the wall moves inwards, the plasma is repelled from the conducting surface and driven inwards by currents induced by its magnetic field in the liquid metal wall. As the liquid metal closes (or bridges) the opening of the coaxial plasma injector, the magnetic field topology alters to remove the null. Due to this, the plasma moves from a diverted to a wall-limited configuration. The liquid metal liner continues to close in and change shape, reducing in radius by a factor of ten at the peak of plasma compression. A model of the MTF plasma must be able to handle this continually varying geometry, and to be predictive, it must faithfully include the real imperfections arising in the process. In this project, we pursued a Monte Carlo approach to closures for MHD by computing kinetic electron trajectories in an MHD plasma background from simulations of GF devices. This requires enhancing the capabilities of the KORC-T code for running large ensembles of kinetic trajectories by porting it to GPU architectures and enabling workflows for large ensembles on OLCF machines. With these capabilities, it is possible to produce a large library of kinetic calculations of electron orbits evolving in plasma configurations spanning the magnetic configurations and plasma density profiles, including non-axisymmetry, arising in the General Fusion’s existing PI3 spherical tokamak device. Using ensembles will capture particles passing a single point in space in a given magnetic configuration, and the entire dataset will cover a range of global magnetic field geometries. By sampling around many starting points, this dataset will capture the spatial dependence of the plasma parameters. From this large dataset, it is possible to produce a reduced model for the kinetic effects not captured in MHD.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

PopSyCLE: A New Population Synthesis Code for Compact Object Microlensing Events

We present a new Milky Way microlensing simulation code, dubbed PopSyCLE (Population Synthesis for Compact object Lensing Events). PopSyCLE is the first resolved microlensing simulation to include a compact object distribution derived from numerical supernovae explosion models and both astrometric and photometric microlensing effects. We demonstrate the capabilities of PopSyCLE by investigating the optimal way to find black holes (BHs) with microlensing. Candidate BHs have typically been selected from wide-field photometric microlensing surveys, such as OGLE, by selecting events with long Einstein crossing times (tE > 120 days). These events can be selected at closest approach and monitored astrometrically in order to constrain the mass of each lens; PopSyCLE predicts a BH detection rate of ~40% for such a program. We find that the detection rate can be enhanced to ~ 85% by selecting events with both tE > 120 days and a microlensing parallax of πE < 0.08. Unfortunately, such a selection criterion cannot be applied during the event as πE requires both pre- and post-peak photometry. However, historical microlensing events from photometric surveys can be revisited using this new selection criteria in order to statistically constrain the abundance of BHs in the Milky Way. The future WFIRST microlensing survey provides both precise photometry and astrometry and will yield individual masses of O(100 - 1000) black holes, which is at least an order of magnitude more than is possible with individual candidate follow-up with current facilities. The resulting sample of BH masses from WFIRST will begin to constrain the shape of the black hole present-day mass function, BH multiplicity, and BH kick velocity distributions

79 ASTRONOMY AND ASTROPHYSICS↗

The Stellar decomposition: A compact representation for simplicial complexes and beyond

Here, we introduce the Stellar decomposition, a model for efficient topological data structures over a broad range of simplicial and cell complexes. A Stellar decomposition of a complex is a collection of regions indexing the complex’s vertices and cells such that each region has sufficient information to locally reconstruct the star of its vertices, i.e., the cells incident in the region’s vertices. Stellar decompositions are general in that they can compactly represent and efficiently traverse arbitrary complexes with a manifold or non-manifold domain. They are scalable to complexes in high dimension and of large size, and they enable users to easily construct tailored application-dependent data structures using a fraction of the memory required by a corresponding global topological data structure on the complex. As a concrete realization of this model for spatially embedded complexes, we introduce the Stellar tree, which combines a nested spatial tree with a simple tuning parameter to control the number of vertices in a region. Stellar trees exploit the complex’s spatial locality by reordering vertex and cell indices according to the spatial decomposition and by compressing sequential ranges of indices. Stellar trees are competitive with state-of-the-art topological data structures for manifold simplicial complexes and offer significant improvements for cell complexes and non-manifold simplicial complexes. We conclude with a high-level description of several mesh processing and analysis applications that utilize Stellar trees to process large datasets.

97 MATHEMATICS AND COMPUTING↗

Origin of spin–orbit misalignments: the microblazar V4641 Sgr

ABSTRACT Of the known microquasars, V4641 Sgr boasts the most severe lower limit (>52°) on the misalignment angle between the relativistic jet axis and the binary orbital angular momentum. Assuming the jet and black hole spin axes coincide, we attempt to explain the origin of this extreme spin–orbit misalignment with a natal kick model, whereby an aligned binary system becomes misaligned by a supernova kick imparted to the newborn black hole. The model inputs are the kick velocity distribution, which we measure customized to V4641 Sgr, and the immediate pre/post-supernova binary system parameters. Using a grid of binary stellar evolution models, we determine post-supernova configurations that evolve to become consistent with V4641 Sgr today and obtain the corresponding pre-supernova configurations by using standard prescriptions for common envelope evolution. Using each of these potential progenitor system parameter sets as inputs, we find that a natal kick struggles to explain the origin of the V4641 Sgr spin–orbit misalignment. Consequently, we conclude that evolutionary pathways involving a standard common envelope phase followed by a supernova kick are highly unlikely for V4641 Sgr. An alternative interpretation is that the jet axis does not reliably trace the black hole spin axis. Our results raise concerns about compact object merger statistics gleaned from binary population synthesis models, which rely on unverified prescriptions for common envelope evolution and natal kicks. We also challenge the spin–orbit alignment assumption routinely invoked to measure black hole spin magnitudes.

79 ASTRONOMY AND ASTROPHYSICS↗

The invisible black widow PSR J1720−0534: implications for the electron density towards the North Polar Spur

Radio emission from pulsars can be used to map out their distances through dispersion measure (DM), which quantifies the amount of radio pulse dispersion. However, this method relies on accurately modelling the free electron density in the line of sight. Here, we present a detailed study of the multiwavelength emission from PSR J1720−0534, a black widow compact binary millisecond pulsar discovered in 2021, which the latest electron density model of the Galaxy places at only 191 pc. We obtained and analysed deep multiwavelength observations in the γ-ray ( Fermi -Large Area Telescope, 2008–2022), optical (Las Cumbres Observatory, 2.7 h), near-infrared (Nordic Optical Telescope, 3.5 h), and X-ray ( Swift -X-Ray Telescope, 10 ks) bands. We found no significant detection of γ-ray, optical, near-infrared, or X-ray counterparts around the radio-timing position of PSR J1720−0534, which we thus nickname ‘the invisible black widow’. Employing the most constraining near-infrared limit ( J > 23.4 mag), we established a lower limit on the source distance, d > 1.1 kpc, assuming conservative properties for the black widow companion star. This distance lower limit differs drastically (by a factor of more than 5) from the Yao et al. DM distance estimate. We attribute this difference to the inclusion in the Yao et al. model of a large and dense component towards the North Polar Spur. Considering our results and recent parallax distances to other pulsars in this direction, we argue that such a local and large component in the electron density model of the Galaxy is unnecessary.

79 ASTRONOMY AND ASTROPHYSICS↗

High Voltage Multiplier: A New, Compact Design using SiC High Frequency MOSFETs

In this report, power supply models for particle accelerators are examined and electrical equivalent model for a high-voltage multiplier power supply is developed. The ultimate goal is to provide the blue prints for the realization of real world models to power both the electrical and magnetic dipoles that make up the key components of the typical particle accelerator assembly.

43 PARTICLE ACCELERATORS↗

Global Kinetic Modeling of the Intrabinary Shock in Spider Pulsars

Abstract Spider pulsars are compact binary systems composed of a millisecond pulsar and a low-mass companion. The relativistic magnetically dominated pulsar wind impacts onto the companion, ablating it and slowly consuming its atmosphere. The interaction forms an intrabinary shock, a proposed site of particle acceleration. We perform global fully kinetic particle-in-cell simulations of the intrabinary shock, assuming that the pulsar wind consists of plane-parallel stripes of alternating polarity and that the shock wraps around the companion. We find that particles are efficiently accelerated via shock-driven reconnection. We extract first-principles synchrotron spectra and light curves, which are in good agreement with X-ray observations: (1) the synchrotron spectrum is nearly flat, F ν ∝ const; (2) when the pulsar spin axis is nearly aligned with the orbital angular momentum, the light curve displays two peaks, just before and after the pulsar eclipse (pulsar superior conjunction), separated in phase by ∼0.8 rad; (3) the peak flux exceeds the one at the inferior conjunction by a factor of 10.

79 ASTRONOMY AND ASTROPHYSICS↗

A statistical and simulation-informed model for estimating permeability from pore size distribution in saturated geomaterials

Accurate permeability estimation is essential across subsurface engineering applications but remains challenging due to the complex pore structures of natural geomaterials. Traditional empirical methods and simplified theoretical models often inadequately capture the role of pore size distribution and connectivity. Here, this study develops a statistical and simulation-informed permeability model that collapses pore-scale complexity into a compact scaling of the form k = αϕμ d 2 , where ϕ is porosity, μ d is mean pore size, and α is a weakly varying coefficient. By combining pore network simulations with statistical analysis of unimodal and bimodal pore size distributions, we identify three key findings: (i) permeability is much more sensitive to mean pore size than to porosity; (ii) across extensive datasets, the ratio σ d /μ d (standard deviation to mean) clusters around a characteristic value ∼0.4, allowing the effects of the full pore size distribution to be represented by μ d and a narrowly varying α ≈ 0.05; and (iii) for bimodal systems, there exists a critical fraction of small pores ∼0.78 above which flow becomes small-pore dominated, enabling the definition of an effective flow-controlling pore population and facilitating simplified permeability estimation for such systems. The resulting model, which requires only porosity and a representative mean pore size as inputs, is validated against comprehensive experimental datasets (>1700 samples) spanning diverse soils and rocks and achieves good predictive accuracy. Overall, this work provides a physically grounded yet practically simple permeability estimator suitable for subsurface engineering, environmental protection, and resource management applications.

Permeability↗

Toward fully coherent soft x-ray free-electron laser via echo-enabled harmonic generation in fourth generation synchrotron light sources

Having previously reported on bunching via echo-enabled harmonic generation (EEHG) as an effective way to improve the longitudinal coherence in the NSLS-II storage ring [X. Yang et al., Sci. Rep. 12, 9437 (2022)], we demonstrate that this EEHG scheme can be easily adopted to any fourth generation diffraction-limited synchrotron light source with significant benefits. The advantage of the scheme is that it requires no change of the lattice and is fully compatible with other beamlines. Since the EEHG performance is mainly determined by the momentum compaction, beam emittances, and beta functions of a SR lattice, we have identified these crucial parameters and successfully built a generalized model, which can predict the performance of nearly any SLS. Regarding the fourth generation SLSs, momentum compactions are often significantly smaller; thus, to cover the x rays with a photon energy of up to 1 keV, we utilize a specific design, including a 250 nm seed-laser wavelength. Our model predicts that for most of the current and future fourth generation SLSs, the EEHG scheme can produce significant prebunching up to harmonic 200 and, thus, generate a few MW scale peak power at 1.25 nm wavelength.

47 OTHER INSTRUMENTATION↗

Uncertainty Quantification of Calculated Temperatures for the AGR 5/6/7 Experiment

This report documents the quantification of uncertainty of the calculated temperature data for the Advanced Gas Reactor (AGR) 5/6/7 fuel irradiation experiment conducted in the Advanced Test Reactor at Idaho National Laboratory in support of the Advanced Reactor Technologies? research and development program. Recognizing uncertainties inherent in physics and thermal simulations of the AGR 5/6/7 capsules, the results of the numerical simulations are used in combination with statistical analysis methods to improve qualification of measured data. The calculated fuel temperatures for AGR tests are also used for validation of the fission product transport and fuel performance simulation models. These crucial roles of the calculated fuel temperatures in ensuring achievement of the AGR experimental program objectives require accurate determination of the model temperature uncertainties. This report covers temperature uncertainty results for each of the five AGR 5/6/7 capsules. To quantify the uncertainty of calculated temperatures determined using the ABAQUS finite element heat transfer code, this study identifies and analyzes model parameters of potential importance to the calculated temperatures of fuel compacts and thermocouples. The selection of input parameters for uncertainty quantification is based on the ranking of their influences upon temperature predictions. Thus, selected input parameters include those with high sensitivity and those with the largest uncertainty. Propagation of model parameter uncertainty and sensitivity is then used to quantify the overall uncertainty of calculated temperatures. Measurement uncertainty, analysis of modeling assumptions, and expert judgment are used as the basis to quantify the uncertainty range for selected input parameters. The input uncertainties are dynamic, accounting for the effect of unplanned events and changes in thermal properties of capsule components over extended exposure to high temperatures and fast neutron irradiation. The sensitivity analysis performed in this work went beyond the traditional local sensitivity. Using experimental design, analysis of pairwise interactions of model parameters was performed to establish sufficiency of the time dependent first order (linear) expansion terms in constructing the temperature response surface. To achieve completeness, uncertainty propagation made use of pairwise noise correlations of model parameters. Furthermore, using an interpolation scheme over the input parameter domain, the analysis obtains time dependent sensitivity over the test campaign duration. This allows computation of uncertainty for the calculated fuel temperatures and the calculated graphite temperatures at thermocouple locations during the entire irradiation period.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗