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At least 1,495 records · Page 83

FULL PARTICLE ELECTROMAGNETIC SIMULATIONS OF ENTROPY GENERATION ACROSS A COLLISIONLESS SHOCK

Experimental data from Cluster have shown that entropy density can be generated across Earth's bow shock. These new observations are a starting point for a more sophisticated analysis that includes computer modeling of a collisionless shock using observed shock parameters as input. In this Letter, we present the first comparison between observations and particle-in-cell simulations of such entropy generation across a collisionless shock. The ion heating at the shock is dominated by the phase mixing of reflected and directly transmitted ions, which are separated from the incident ions. The electron heating is a nearly thermal process due to the conservation of their angular momentum. For both species, we calculate the entropy density across the shock, and obtain good consistency between observations and simulations on entropy generation across the shock. We also find that the entropy generation rate is reduced as the shock Mach number decreases.

79 ASTRONOMY AND ASTROPHYSICS↗

Photon detection probability prediction using one-dimensional generative neural network

Abstract Photon detection is important for liquid argon detectors for direct dark matter searches or neutrino property measurements. Precise simulation of photon transport is widely used to understand the probability of photon detection in liquid argon detectors. Traditional photon transport simulation, which tracks every photon using the Geant4 simulation toolkit, is a major computational challenge for kilo-tonne-scale liquid argon detectors and GeV-level energy depositions. In this work, we propose a one-dimensional generative model which efficiently generates features using an O u t e r P r o d u c t -layer. This model bypasses photon transport simulation and predicts the number of photons detected by particular photon detectors at the same level of detail as the Geant4 simulation. The application to simulating photon detection systems in kilo-tonne-scale liquid argon detectors demonstrates this novel generative model is able to reproduce Geant4 simulation with good accuracy and 20 to 50 times faster. This generative model can be used to quickly predict photon detection probability in huge liquid argon detectors like ProtoDUNE or DUNE.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Syntgen: a system to generate temporal networks with user-specified topology

Abstract In the last few years, the study of temporal networks has progressed markedly. The evolution of clusters of nodes (or communities) is one of the major focus of these studies. However, the time dimension increases complexity, introducing new constructs and requiring novel and enhanced algorithms. In spite of recent improvements, the relative scarcity of timestamped representations of empiric networks, with known ground truth, hinders algorithm validation. A few approaches have been proposed to generate synthetic temporal networks that conform to static topological specifications while in general adopting an ad hoc approach to temporal evolution. We believe there is still a need for a principled synthetic network generator that conforms to problem domain topological specifications from a static as well as temporal perspective. Here, we present such a system. The unique attributes of our system include accepting arbitrary node degree and cluster size distributions and temporal evolution under user control, while supporting tunable joint distribution and temporal correlation of node degrees. Theoretical contributions include the analysis of conditions for graphic sequences of inter- and intracluster node degrees and cluster sizes and the development of a heuristic to search for the cluster membership of nodes that minimizes the shared information distance between clusterings. Our work shows that this system is capable of generating networks under user controlled topology with up to thousands of nodes and hundreds of clusters with strong topology adherence. Much larger networks are possible with relaxed requirements. The generated networks support algorithm validation as well as problem domain analysis.

Pereira, Luis Ramada↗

Near-field non-radial motion generation from underground chemical explosions in jointed granite

Here, this paper describes analysis of non-radial ground motion generated by chemical explosions in a jointed rock formation during the Source Physics Experiment (SPE). Such motion makes it difficult to discriminate between various subsurface events such as explosions, implosions (i.e. mine collapse) and earthquakes. We apply 3-D numerical simulations to understand experimental data collected during the SPEs. The joints are modelled explicitly as compliant thin inclusions embedded into the rock mass. Mechanical properties of the rock and the joints as well as the joint spacing and orientation are inferred from experimental test data, and geophysical and geological characterization of the SPE site which is dominantly Climax Stock granitic outcrop. The role of various factors characterizing the joints such as joint spacing, frictional properties, orientation and persistence in generation of non-radial motion is addressed. The joints in granite at the SPE site are oriented in nearly orthogonal directions with two vertical sets dipping at 70–80 degrees with the same strike angle, one vertical set almost orthogonal to the first two and one shallow angle joint set dipping 15 degrees. In this study we establish the relationship between the joint orientation and azimuthal variations in the polarity of the observed shear motion. The majority of the shear motion is generated due to the effects of non-elastic sliding on the joints near the source, where the wave can create significant shear stress to overcome the cohesive forces at the joints. Near the surface the joints are less confined and are subject to sliding when the pressure waves are reflected. In the far field, where the cohesive forces on the joints cannot be overcome, additional shear motion can be generated due to elastic anisotropy of the rock mass given by preferred spatial orientations of compliant joints.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

Anomaly detection in Hyper Suprime-Cam galaxy images with generative adversarial networks

ABSTRACT The problem of anomaly detection in astronomical surveys is becoming increasingly important as data sets grow in size. We present the results of an unsupervised anomaly detection method using a Wasserstein generative adversarial network (WGAN) on nearly one million optical galaxy images in the Hyper Suprime-Cam (HSC) survey. The WGAN learns to generate realistic HSC-like galaxies that follow the distribution of the data set; anomalous images are defined based on a poor reconstruction by the generator and outlying features learned by the discriminator. We find that the discriminator is more attuned to potentially interesting anomalies compared to the generator, and compared to a simpler autoencoder-based anomaly detection approach, so we use the discriminator-selected images to construct a high-anomaly sample of ∼13 000 objects. We propose a new approach to further characterize these anomalous images: we use a convolutional autoencoder to reduce the dimensionality of the residual differences between the real and WGAN-reconstructed images and perform UMAP clustering on these. We report detected anomalies of interest including galaxy mergers, tidal features, and extreme star-forming galaxies. A follow-up spectroscopic analysis of one of these anomalies is detailed in the Appendix; we find that it is an unusual system most likely to be a metal-poor dwarf galaxy with an extremely blue, higher-metallicity H ii region. We have released a catalogue with the WGAN anomaly scores; the code and catalogue are available at https://github.com/kstoreyf/anomalies-GAN-HSC; and our interactive visualization tool for exploring the clustered data is at https://weirdgalaxi.es.

79 ASTRONOMY AND ASTROPHYSICS↗

Second-generation dust in planetary systems: the case of HD 163296

Observations indicate that large, dust-laden protoplanetary discs are common. Some features, like gaps, rings, and spirals, suggest they may host young planets, which can excite the orbits of nearby leftover planetesimals. Energetic collisions among these bodies can lead to the production of second-generation dust. Grains produced by collisions may have a dynamical behaviour different from that of first-generation, primordial dust out of which planetesimals and planets formed. Here, we aim to study these differences for the HD 163296 system and determine whether dynamical signatures in the mixture of the two dust populations can help separate their contributions. We use three-dimensional (3D) hydrodynamic models to describe the gaseous disc with three, Saturn- to Jupiter-mass, embedded planets. Dust grains, of sizes $1\, \mu \mathrm{m}$–$1\, \mathrm{mm}$, are treated as Lagrangian particles with resolved thermodynamics and mass-loss. Initial disc and planet configurations are derived from observation-based work, which indicates low gas viscosity. The 3D approach also allows us to detect the formation of vortices induced by Rossby waves, where dust becomes concentrated and may contribute to planetesimal formation. We find that the main differences in the dynamical behaviour of first- and second-generation dust occur in the vertical distribution. The two populations have similar distributions around the disc mid-plane, although second-generation dust shows longer residence times close to the radial locations of the planets’ gas gaps. Sedimentation rates of $\mu$m-sized grains are comparable to or lower than the production rates by planetesimals’ collisions, making this population potentially observable. These outcomes can be extended to similar systems harbouring giant planets.

79 ASTRONOMY AND ASTROPHYSICS↗

Realistic galaxy image simulation via score-based generative models

ABSTRACT We show that a denoising diffusion probabilistic model (DDPM), a class of score-based generative model, can be used to produce realistic mock images that mimic observations of galaxies. Our method is tested with Dark Energy Spectroscopic Instrument (DESI) grz imaging of galaxies from the Photometry and Rotation curve OBservations from Extragalactic Surveys (PROBES) sample and galaxies selected from the Sloan Digital Sky Survey. Subjectively, the generated galaxies are highly realistic when compared with samples from the real data set. We quantify the similarity by borrowing from the deep generative learning literature, using the ‘Fréchet inception distance’ to test for subjective and morphological similarity. We also introduce the ‘synthetic galaxy distance’ metric to compare the emergent physical properties (such as total magnitude, colour, and half-light radius) of a ground truth parent and synthesized child data set. We argue that the DDPM approach produces sharper and more realistic images than other generative methods such as adversarial networks (with the downside of more costly inference), and could be used to produce large samples of synthetic observations tailored to a specific imaging survey. We demonstrate two potential uses of the DDPM: (1) accurate inpainting of occluded data, such as satellite trails, and (2) domain transfer, where new input images can be processed to mimic the properties of the DDPM training set. Here we ‘DESI-fy’ cartoon images as a proof of concept for domain transfer. Finally, we suggest potential applications for score-based approaches that could motivate further research on this topic within the astronomical community.

79 ASTRONOMY AND ASTROPHYSICS↗

Magnetorotational dynamo can generate large-scale vertical magnetic fields in 3D GRMHD simulations of accreting black holes

ABSTRACT Jetted astrophysical phenomena with black hole engines, including binary mergers, jetted tidal disruption events, and X-ray binaries, require a large-scale vertical magnetic field for efficient jet formation. However, a dynamo mechanism that could generate these crucial large-scale magnetic fields has not been identified and characterized. We have employed three-dimensional global general relativistic magnetohydrodynamical simulations of accretion discs to quantify, for the first time, a dynamo mechanism that generates large-scale magnetic fields. This dynamo mechanism primarily arises from the non-linear evolution of the magnetorotational instability (MRI). In this mechanism, large non-axisymmetric MRI-amplified shearing wave modes, mediated by the axisymmetric azimuthal magnetic field, generate and sustain the large-scale vertical magnetic field through their non-linear interactions. We identify the advection of magnetic loops as a crucial feature, transporting the large-scale vertical magnetic field from the outer regions to the inner regions of the accretion disc. This leads to a larger characteristic size of the, now advected, magnetic field when compared to the local disc height. We characterize the complete dynamo mechanism with two time-scales: one for the local magnetic field generation, $t_{\rm gen}$, and one for the large-scale scale advection, $t_{\rm adv}$. Whereas the dynamo we describe is non-linear, we explore the potential of linear mean field models to replicate its core features. Our findings indicate that traditional $\alpha$-dynamo models, often computed in stratified shearing box simulations, are inadequate and that the effective large-scale dynamics is better described by the shear current effects or stochastic $\alpha$-dynamos.

Astronomy & Astrophysics↗

A Single Xyloglucan Xylosyltransferase Is Sufficient for Generation of the XXXG Xylosylation Pattern of Xyloglucan

ABSTRACT Xyloglucan is the most abundant hemicellulose in the primary cell walls of dicots. Dicot xyloglucan is the XXXG type consisting of repeating units of three consecutive xylosylated Glc residues followed by one unsubstituted Glc. Its xylosylation is catalyzed by xyloglucan 6-xylosyltransferases (XXTs) and there exist five XXTs (AtXXT1-5) in Arabidopsis. While AtXXT1 and AtXXT2 have been shown to add the first two Xyl residues in the XXXG repeat, which XXTs are responsible for the addition of the third Xyl residue remains elusive although AtXXT5 was a proposed candidate. In this report, we generated recombinant proteins of all five Arabidopsis XXTs and one rice XXT (OsXXT1) in the mammalian HEK293 cells and investigated their ability to sequentially xylosylate Glc residues to generate the XXXG xylosylation pattern. We found that like AtXXT1/2, AtXXT4 and OsXXT1 could efficiently xylosylate the cellohexaose (G6) acceptor to produce mono- and di-xylosylated G6, whereas AtXXT5 was only barely capable of adding one Xyl onto G6. When AtXXT1-catalyzed products were used as acceptors, AtXXT1/2/4 and OsXXT1, but not AtXXT5, were able to xylosylate additional Glc residues to generate tri- and tetra-xylosylated G6. Further characterization of the tri- and tetra-xylosylated G6 revealed that they had the sequence of GXXXGG and GXXXXG with three and four consecutive xylosylated Glc residues, respectively. In addition, we have found that although tri-xylosylation occurred on G6, cello-oligomers with a degree of polymerization of 3 to 5 could only be mono- and di-xylosylated. Together, these results indicate that each of AtXXT1/2/4 and OsXXT1 is capable of sequentially adding Xyl onto three contiguous Glc residues to generate the XXXG xylosylation pattern and these findings provide new insight into the biochemical mechanism underlying xyloglucan biosynthesis.

Cell Biology↗

Efficient many-jet event generation with flow matching

We apply for the first time, to the best of our knowledge, the flow matching method to the problem of phase-space sampling for event generation in high-energy collider physics. By training the model to remap the random numbers used to generate the momenta and helicities of the scattering matrix elements as implemented in the portable partonic event generator pepper, we find substantial efficiency improvements in the studied processes. We focus our study on the highest final-state multiplicities in Drell-Yan and top-antitop pair production used in simulated samples for the Large Hadron Collider, which computationally are the most relevant ones. We find that the unweighting efficiencies improve by factors of 184 and 25, respectively, when compared to the standard approach of using a vegas-based optimization. We also compare continuous normalizing flows trained with flow matching against the previously studied normalizing flows based on coupling layers and find that the former leads to better results, faster training and a better scaling behavior across the studied multiplicity range, while the latter evaluate faster. When combining the advantages of both methods using the regflow approach, we find parton-level unweighted event generation walltime gains of about a factor of 10 at the highest final-state multiplicities.

Bothmann, E. [CERN; Gottingen U.] (ORCID:000000016↗

Phase-matching analysis in high-order harmonic generation with nonzero orbital angular momentum Laguerre-Gaussian beams

Through high-order harmonic generation driven by intense ultrashort vortex infrared or midinfrared lasers, a nonzero orbital angular momentum can be imprinted onto extreme ultraviolet (XUV) or soft-x-ray (SXR) light pulses. Here we simulate the generation of vortex XUV harmonics in the gas medium as well as their propagation in vacuum till reaching the far field. In this work, we find that the intensity and phase of generated high harmonics are very sensitive to the position of gas jet with respect to the laser focus. The topological charge of the $\textit{q}$th harmonic is found to be $\textit{q}$ times that of the driving Laguerre-Gaussian beam. Each harmonic in the far field appears as a single ring in the transverse plane with an invariant diameter which is scalable with the fundamental topological charge only when the gas jet is placed after the laser focus. The underlying phase-matching mechanism is analyzed by examining the spatial map of the coherence length and by calculating the evolution of harmonic emission in the medium. We anticipate this work to stimulate interest in generating intense vortex XUV or SXR attosecond pulses for probing dynamics of molecules where special molecular features are difficult to be detected with linear or circular XUV or SXR pulses.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Probing multirescattering dynamics and electron quantum paths for below- and near-threshold harmonic generation of H 2 in an intense laser field

Most previous studies of high-order-harmonic generation have focused on the regime beyond the ionization threshold; the dynamical origin of below- and near-threshold harmonics, particularly for the molecular systems, is less understood and largely unexplored. Here, we report a self-interaction free time-dependent density-functional-theory study along with an extended semiclassical study for the nonperturbative probing of the dynamical origin of below- and near-threshold harmonic generation of the H 2 molecule in an intense near-infrared laser field. Our approach allows an accurate study of the electron trajectories as a function of energy, time, and position for below-, near-, and above-threshold harmonics for electrons departing initially from each of the individual hydrogen cores of the H 2 molecule. We discover that short trajectories are multiphoton dominated and can have multiple returns for below-threshold harmonics, and excited-state resonances can have significant effects on the generation of neighboring below-threshold harmonics. Furthermore, we find that the electron dynamics for below-threshold long, short, and resonant trajectories differ greatly depending upon which hydrogen core (left or right) the electron was released from initially. An intuitive and appealing picture of near- and below-threshold harmonic generation discovered in our study can give guidance to future experiments in this forefront area of ultrafast atomic, molecular, and optical physics.

74 ATOMIC AND MOLECULAR PHYSICS↗

Antibunching dynamics of plasmonically mediated entanglement generation

Dissipative entanglement generation protocols embrace open quantum system dynamics to generate long-lived entangled states. In this letter, we report that zero-delay anti-bunching in the $g^{(2)}(\tau)$ correlation function is a signature of dissipative entanglement between actively driven quantum emitters coupled to a plasmonic resirvoir. The anti-bunching effect is a universal signature for entangled bi-partite states generated by relaxation to sub-radiant subspaces. We discuss how the anti-bunching can be validated on experimentally feasible timescales by a Hanburry Brown and Twiss interferometer and analyze the entanglement generation robustness with respect to variations in local detunings, system couplings, and driving fields.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Low-energy cross-section measurement of the B 10 ( α , n ) N 13 reaction and its impact on neutron production in first-generation stars

Nucleosynthesis in the first generation of massive stars offers a unique setting to explore the creation of the first heavier nuclei in an environment free of impurities from earlier stellar generations. In later generations of massive stars, hydrogen burning occurs predominantly through the CNO cycles, but without the carbon, nitrogen, and oxygen to catalyze the reaction sequence, first stars would have to rely on the inefficient pp chains for their energy production. Observations of second and third generation stars show pronounced abundances of carbon and oxygen isotopes, which suggests a rapid conversion of the primordial abundances to heavier elements. While the triple-alpha-process primarily facilitates this conversion, there are alternative reaction sequences, such as 2 H(α,γ) 6 Li(α,γ) 10 B(α,n) 13 N, that may play a significant role. To study such alternate reaction pathways for production of carbon and heavier nuclei, a number of new measurements are needed. In this work, new measurements are reported for the 10 B(α,n) 13 N reaction, extending the cross section down to 575 keV incident α-particle energy. The measurements were made using a state-of-the-art deuterated liquid scintillator and a spectrum unfolding technique. An R-matrix analysis was performed in order to facilitate a comparison of the underlying nuclear structure with the reaction measurements. An unexpected upturn is observed in the low-energy S factor that indicates the presence of a new low-energy resonance. Finally, a revised reaction rate is determined that takes into account the present data as well as other previous measurements from the literature that were previously neglected.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Measuring the properties of f - mode oscillations of a protoneutron star by third-generation gravitational-wave detectors

Core-collapse supernovae are among the astrophysical sources of gravitational waves that could be detected by third-generation gravitational-wave detectors. Here, we analyze the gravitational-wave strain signals from two- and three-dimensional simulations of core-collapse supernovae generated using the code FORNAX. A subset of the two-dimensional simulations has non-zero core rotation at the core bounce. A dominant source of time changing quadrupole moment is the l = 2 fundamental mode (f- mode) oscillation of the proto-neutron star. From the time-frequency spectrogram of the gravitational-wave strain we see that, starting ~ 400 ms after the core bounce, most of the power lies within a narrow track that represents the frequency evolution of the f-mode oscillations. The f-mode frequencies obtained from linear perturbation analysis of the angle averaged profile of the protoneutron star corroborate what we observe in the spectrograms of the gravitational wave signal. We explore the measurability of the f-mode frequency evolution of protoneutron star for a supernova signal observed in the third-generation gravitational-wave detectors. Measurement of the frequency evolution can reveal information about the masses, radii, and densities of the proto-neutron stars. We find that if the third generation detectors observe a supernova within 10 kpc, we can measure these frequencies to within ~90% accuracy. Here, we can also measure the energy emitted in the fundamental f-mode using the spectrogram data of the strain signal. We find that the energy in the f-mode can be measured to within 20% error for signals observed by Cosmic Explorer using simulations with successful explosion, assuming source distances within 10 kpc.

79 ASTRONOMY AND ASTROPHYSICS↗

Improving generative model-based unfolding with Schrödinger bridges

Machine learning-based unfolding has enabled unbinned and high-dimensional differential cross section measurements. Two main approaches have emerged in this research area; one based on discriminative models and one based on generative models. The main advantage of discriminative models is that they learn a small correction to a starting simulation while generative models scale better to regions of phase space with little data. We propose to use Schrödinger bridges and diffusion models to create , an unfolding approach that combines the strengths of both discriminative and generative models. The key feature of is that its generative model maps one set of events into another without having to go through a known probability density as is the case for normalizing flows and standard diffusion models. We show that achieves excellent performance compared to state of the art methods on a synthetic Z + jets dataset. Published by the American Physical Society 2024

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Entangling Quantum Generative Adversarial Networks

Generative adversarial networks (GANs) are one of the most widely adopted machine learning methods for data generation. In this work, we propose a new type of architecture for quantum generative adversarial networks (an entangling quantum GAN, EQ-GAN) that overcomes limitations of previously proposed quantum GANs. Leveraging the entangling power of quantum circuits, the EQ-GAN converges to the Nash equilibrium by performing entangling operations between both the generator output and true quantum data. In the first multiqubit experimental demonstration of a fully quantum GAN with a provably optimal Nash equilibrium, we use the EQ-GAN on a Google Sycamore superconducting quantum processor to mitigate uncharacterized errors, and we numerically confirm successful error mitigation with simulations up to 18 qubits. Finally, we present an application of the EQ-GAN to prepare an approximate quantum random access memory and for the training of quantum neural networks via variational datasets.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

SynthNotes: A Generator Framework for High-volume, High-fidelity Synthetic Mental Health Notes

One of the key, emerging challenges that connects the "Big Data" and the AI domain is the availability of sufficient volumes of training data for AI/Machine Learning tasks. SynthNotes is a framework for generating standards-compliant, realistic mental health progress report notes at the very large, population-level scale, and in a strict privacy-preserving manner. Our framework, inspired by the needs to explore, evaluate, and train computational methods for the emerging mental health crisis in the US, is useful for benchmarking, optimization, and training of biomedical natural language processing, information extraction, and machine learning systems intended to operate at "Big Data" scale (billions of notes). The free text notes generated by SynthNotes are based on the literature and public statistical models allowing for realistic, natural language representation of a patient, and his or her mental health characteristics. Additionally, SynthNotes can partially simulate stylistic, grammatical, and expressive characteristics of a licensed mental health professional. SynthNotes is modular and flexible, allowing for representation of variety of conditions, incorporation of alternative foundational models, and parametrization of the variability of the structure, content, and size of the synthetically generated corpus. In this paper, we report on the initial use and performance characteristics of our SynthNotes framework and on the ongoing work for inclusion of content planning and deep learning-based generative methods trained on real data.

Begoli, Edmon↗