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At least 1,387 records · Page 77
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Collaborative Research: Explosive reconnection in relativistic magnetically-dominated plasmas

Magnetic fields can be the dominant component of astrophysical plasmas, so that the magnetic energy density might exceed even the rest-mass energy density of matter. In this extreme (and largely unexplored) regime the magnetic field controls the overall plasma evolution, dissipation, and acceleration of non-thermal particles. This plasma regime, applicable to a variety of astrophysical sources --- magnetars, pulsars and pulsar wind nebulae (PWNe), jets of Active Galactic Nuclei (AGNs) and Gamma-Ray Bursters (GRBs) --- is dramatically different from laboratory plasmas, the magnetospheres of planets, and the interplanetary plasma. Relativistic astrophysical sources then provide an unique opportunity to study the fundamental plasma physics of magnetically-dominated plasmas; a novel and quickly evolving field of theoretical research which, by investigating energy conversion and particle energization processes in plasmas, is of vital importance to the Fusion Energy Sciences DoE program.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Gamma-Ray Transient Network Science Analysis Group Report

The Interplanetary Network (IPN) is a detection, localization and alert system that utilizes the arrival time of transient signals in gamma-ray detectors on spacecraft separated by planetary baselines to geometrically locate the origin of these transients. Due to the changing astrophysical landscape and the new emphasis on time domain and multi messenger astrophysics (TDAMM) from the Pathways to Discovery in Astronomy and Astrophysics for the 2020s , this Gamma-ray Transient Network Science Analysis Group was tasked to understand the role of the IPN and high-energy monitors in this new era. The charge includes describing the science made possible with these facilities, tracing the corresponding requirements and capabilities, and highlighting where improved operations of existing instruments and the IPN would enhance TDAMM science. While this study considers the full multiwavelength and multimessenger context, the findings are specific to space-based high-energy monitors. These facilities are important both for full characterization of these transients as well as facilitating follow-up observations through discovery and localization. The full document reports the history of this field in Section 1, followed by our detailed analyses and findings in some 68 pages, providing a holistic overview of the role of the IPN and high-energy monitors in the coming decades.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Cosmic Algorithms: Unveiling Mysteries of the Universe with Artificial Intelligence

In the boundless expanse of the cosmos lies a tapestry of mysteries waiting to be unraveled. In this talk, we delve into the realm of "Cosmic Algorithms," where the marriage of cutting-edge artificial intelligence (AI) and astrophysical inquiry paves the way for unprecedented discoveries. One of the foremost challenges we face in contemporary astrophysics is the staggering size and complexity of astronomical datasets. I will discuss how AI provides a transformative solution to these challenges, enabling us to efficiently sift through vast amounts of data to extract meaningful insights. Moreover, I will explore the fascinating realm of gravitationally lensed galaxies and merging galaxies, showcasing how AI algorithms play a pivotal role in identifying, characterizing, and understanding these phenomena. Today we stand at the threshold of unprecedented discovery, inspired by the boundless potential of Cosmic Algorithms to illuminate the darkest corners of space. The remarkable synergy between AI and astrophysics will continue to push the boundaries of human knowledge and open new roads to discovery.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Achieving Higher Order Accuracy in Space in Hydrodynamic Simulations of Self-Gravitating Gas

Modern astrophysical simulation codes employ a variety of numerical algorithms capable of achieving higher-order accuracy in both space and time. Albeit they succeed in achieving an effective higher spatial resolution and in suppressing the numerical damping of waves, to our knowledge, all current astrophysical simulations invoking self-gravity are limited to second-order accuracy in space. If we can devise an algorithm to evaluate self-gravity with a higher-order spatial accuracy, we can better the evaluation of the gravitational acceleration and gravitational energy release which dictate the evolution of many astrophysical systems. Herein, we present a numerical algorithm for self-gravitating hydrodynamics capable of achieving fourth order accuracy for a given density distribution on a Cartesian uniform grid. First, we derive the cell-averaged gravitational potential at fourth-order accuracy from the cell-averaged density by solving the Poisson equation. Next, we obtain the cell average of the product of the density and gravitational acceleration, which differs from the cell-averaged density multiplied by the cell-averaged gravitational acceleration. We then show the verification of the algorithm by applying it to critical test problems: (1) maintaining equilibria of self-gravitating slabs, even upon advection, (2) evolving a polytropic sphere with a massive power-law envelope, and (3) conservation of specific entropy during the propagation of a sound wave.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Particle Dark Matter Across Scales (Final Technical Report)

The research supported by this DOE grant investigated the nature of dark matter, particularly its particle properties and astrophysical manifestations, over the period of 2018 to 2024. The proposal focused on leveraging astrophysical probes, cosmological models, and high-resolution simulations to further our understanding of dark matter, its possible interactions, and the theoretical models that could explain its properties. This research directly contributes to the DOE's mission of exploring the fundamental constituents of the universe, advancing particle physics, and using cosmological and astrophysical observations to detect dark matter.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Multimessenger Gamma-Ray and Neutrino Coincidence Alerts Using HAWC and IceCube Subthreshold Data

The High Altitude Water Cerenkov (HAWC) and IceCube observatories, through the Astrophysical Multimessenger Observatory Network (AMON) framework, have developed a multimessenger joint search for extragalactic astrophysical sources. This analysis looks for sources that emit both cosmic neutrinos and gamma rays that are produced in photohadronic or hadronic interactions. The AMON system is running continuously, receiving subthreshold data (i.e., data that are not suited on their own to do astrophysical searches) from HAWC and IceCube, and combining them in real time. Here we present the analysis algorithm, as well as results from archival data collected between 2015 June and 2018 August, with a total live time of 3.0 yr. During this period we found two coincident events that have a false-alarm rate (FAR) of <1 coincidence yr -1 , consistent with the background expectations. The real-time implementation of the analysis in the AMON system began on 2019 November 20 and issues alerts to the community through the Gamma-ray Coordinates Network with an FAR threshold of <4 coincidences yr -1 .

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

A Cross-correlation Study between IceCube Neutrino Events and the FERMI Unresolved Gamma-Ray Sky

With the coincident detections of electromagnetic radiation together with gravitational waves (GW170817) or neutrinos (TXS 0506+056), the new era of multimessenger astrophysics has begun. Of particular interest are the searches for correlation between the high-energy astrophysical neutrinos detected by the IceCube Observatory and gamma-ray photons detected by the Fermi Large Area Telescope (LAT). So far, only sources detected by the LAT have been considered in correlation with IceCube neutrinos, neglecting any emission from sources too faint to be resolved individually. Here we present the first cross-correlation analysis considering the unresolved gamma-ray background (UGRB) and IceCube events. We perform a thorough sensitivity study, and, given the lack of identified correlation, we place upper limits on the fraction of the observed neutrinos that would be produced in proton–proton or proton–$γ$ interactions from the population of sources contributing to the UGRB emission and dominating its spatial anisotropy (aka blazars). Our analysis suggests that, under the assumption that there is no intrinsic cutoff and/or hardening of the spectrum above Fermi-LAT energies, and that all gamma rays from the unresolved blazars dominating the UGRB fluctuation field are produced by neutral pions from $p–p$ ($p–γ$) interactions, up to 60% (30%) of such a population may contribute to the total neutrino events observed by IceCube. This translates into an O (1%) maximum contribution to the astrophysical high-energy neutrino flux observed by IceCube at 100 TeV.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Debiasing with Diffusion: Probabilistic Reconstruction of Dark Matter Fields from Galaxies with CAMELS

Abstract Galaxies are biased tracers of the underlying cosmic web, which is dominated by dark matter (DM) components that cannot be directly observed. Galaxy formation simulations can be used to study the relationship between DM density fields and galaxy distributions. However, this relationship can be sensitive to assumptions in cosmology and astrophysical processes embedded in galaxy formation models, which remain uncertain in many aspects. In this work, we develop a diffusion generative model to reconstruct DM fields from galaxies. The diffusion model is trained on the CAMELS simulation suite that contains thousands of state-of-the-art galaxy formation simulations with varying cosmological parameters and subgrid astrophysics. We demonstrate that the diffusion model can predict the unbiased posterior distribution of the underlying DM fields from the given stellar density fields while being able to marginalize over uncertainties in cosmological and astrophysical models. Interestingly, the model generalizes to simulation volumes ≈500 times larger than those it was trained on and across different galaxy formation models. The code for reproducing these results can be found athttps://github.com/victoriaono/variational-diffusion-cdm✎.

Astronomy & Astrophysics↗
DOE OSTI2025

Inference of Multichannel r -process Element Enrichment in the Milky Way Using Binary Neutron Star Merger Observations

Observations of GW170817 strongly suggest that binary neutron star (BNS) mergers produce rapid neutron-capture nucleosynthesis ( r -process) elements. However, it remains an open question whether these mergers can account for all the r -process element enrichment in the Milky Way’s history. Here, we constrain the contributions of the BNS channel using astrophysical neutron star observations. The rate and mass distributions are constrained by LIGO/Virgo/Kagra through the latest catalog GWTC-3, the neutron star equation of state by gravitational-wave, radio, and X-ray observations, and the delay time distribution by short gamma-ray burst (GRB) host galaxy associations. We present a Bayesian framework to consistently combine these observations with abundance information to quantify the contribution and uncertainties of single and multiple astrophysical enrichment sources, and obtain a distribution of per-event BNS r -process element yields consistent with geophysical and astrophysical abundance constraints. We then adopt a Galactic chemical evolution model assuming an instantaneous and fixed amount of Fe enrichment from core-collapse supernovae, and show that BNS-only enrichment scenarios remain inconsistent with the observed r-process abundance trend of disk stars in the Galaxy even with the uncertainties in BNS merger observations. Using stellar abundance observations instead of the short GRB constraints, we can infer a shorter BNS delay time distribution with power-law index α ≤ −2.0 and minimum delay time ${t}_{{\rm{\min }}}\leqslant 40$ Myr at 90% confidence, consistent with detailed Galactic chemical evolution models. Such delay times are in tension with those predicted by standard BNS formation models. Alternatively, we confirm that a two-channel scenario, in which the second channel tracks the star formation history without significant delay, can account for both Galactic stellar and short GRB observations. We estimate that 45%–90% of the r -process abundance in the Milky Way today would have been produced by this star formation-tracking channel, rather than BNS mergers with significant delay times.

gravitational wave astronomy↗
DOE OSTI2025

Surrogate Modeling of Landau Damping with Deep Operator Networks

Kinetic simulations excel at capturing microscale plasma physics phenomena with high accuracy, but their computational demands make them impractical for modeling large-scale space and astrophysical systems. In this context, we build a surrogate model, using Deep Operator Networks (DeepONets), based upon the Vlasov–Poisson simulation data to model the dynamical evolution of plasmas, focusing on the Landau damping process—a fundamental kinetic phenomenon in space and astrophysical plasmas. The trained DeepONets are able to capture the evolution of electric field energy in both linear and nonlinear regimes under various conditions. Extensive validation highlights DeepONets’ robust performance in reproducing complex plasma behaviors with high accuracy, paving the way for large-scale modeling of space and astrophysical plasmas.

plasma astrophysics↗
NASA NTRS2016

Status and Path Forward for the Large Ultraviolet Optical Infrared Surveyor (LUVOIR) Mission Concept Study

In preparation of the 2020 Astrophysics Decadal Survey, National Aeronautics and Space Administration (NASA) has commenced a process for the astronomical community to study several large mission concepts leveraging the lessons learned from past Decadal Surveys. This will enable the Decadal Survey committee to make more informed recommendations to NASA on its astrophysics science and mission priorities with respect to cost and risk. Four astrophysics large mission concepts were identified. Each of them had a Science and Technology Definition Teem(STDT) chartered to produce scientifically compelling, feasible, and executable design reference mission (DRM)concepts to present to the 2020 Decadal Survey. In addition, The Aerospace Corporation will perform an independent cost and technical evaluation (CATE) of each of these mission concept studies in advance of the 2020 Decadal Survey by interacting with the STDTs to provide detailed technical details on certain areas for which deep dives are appropriate. This paper presents the status and path forward for one of the four large mission concepts, namely, the Large UltraViolet, Optical, InfraRed surveyor (LUVOIR).

Study Office: science analyses↗
NASA NTRSDate not supplied

Transforming Science Prioritization Processes Using Artificial Intelligence

Artificial Intelligence (AI) and Machine Learning (ML) have potential to augment significantly the current labor-intensive processes of science prioritization, specifically by the National Academies’ Decadal Survey on behalf of NASA and NSF. Here we summarize what we believe to be the first exploratory demonstration-of-concept results from an application of AI/ML to Survey science prioritization. Specifically, we applied Latent Dirichlet Allocation (LDA) and Natural Language Processing (NLP) to reveal trends in published astrophysics research that may indicate science priorities and which could be applied to strategic planning. For the purpose of the work that we summarize here, AI/ML is able to analyze – that is, to “understand,” in a manner of speaking – a vast amount of text to reveal complex relationships among research topics, including the growth or decline of science community activities in those topics over time. We trained ourselves and AI/ML algorithms by using ~400,000 abstracts in the period 1998 to 2010 to “forecast” the Academies’ Astro2010 recommendations and compare with the solicited white papers. Comparing our results with actual Astro2010 recommendations allowed us to identify candidate metrics that better predicted the actual results of the Survey. We found, for example, that Compound Annual Growth Rate (CAGR) of papers published in a topic area is a good proxy measure for importance of this topic area of research. With this training complete, we identified candidate astrophysics astrophysics science priorities for the 2021+ period using the research during 2007 - 2019 . We conclude that appropriate application of AI can potentially significantly reduce the current workload of the Decadal Survey processes and reveal otherwise unrecognized characteristics in the body of astronomical research. We emphasize throughout the exploratory nature of our work, encouraging colleagues to pursue promising results further. Our most critical governing assumption was that increased (or decreased) research activity can be used to identify scientific or technology topic areas worthy of increased (or decreased) future emphasis. We discuss advantages, limitations, and recognize the “black box” nature of our technique. We note ethics issues associated, for example, with using AI/ML to reveal “hidden” meanings and biases in published work. Furthermore, inevitable improvements in AI may soon enable widespread and welcome identification of and advocacy for science and technology priorities by disparate and diverse groups and organizations. Consequently, we continue to urge a near-term, in-depth evaluation of appropriate applications of AI, including implications and consequences, as well as support for multiple follow-on assessments, of which ours is only a beginning.

Artificial Intelligence↗
DOE OSTI2025

The R -Process Alliance: Exploring the cosmic scatter among ten r -process sites with stellar abundances

Context. The astrophysical origin of the rapid neutron-capture process (r-process), responsible for producing roughly half of the elements heavier than iron, remains uncertain. Detailed chemical signatures from the oldest, most metal-poor stars, which act as fossil records of the earliest nucleosynthesis events, can be used to identify the dominant r-process sites. Aims. We present a homogeneous chemical abundance analysis of ten r-process element-enhanced stars. These old and metal-poor stars are strongly enriched in r-process elements with minimal contamination from other nucleosynthetic sources. By focusing on this chemically pure sample, we aim to investigate intrinsic variations in the r-process abundance patterns and explore their implications for the nature and potential diversity of r-process sites. Methods. We performed a detailed chemical abundance analysis of high-resolution, high-signal-to-noise spectra. For each star, we inspected over 1400 individual absorption lines using a combination of equivalent width measurements and spectral synthesis. The analysis was conducted under the assumption of 1D local thermodynamic equilibrium and employing the MOOG radiative transfer code. Results. We derived abundances for 54 chemical species, including 29 neutron-capture (n-capture) elements, covering the full mass range of the r-process abundance pattern. A kinematic analysis reveals that stars likely originated from ten kinematically distinct systems. Based on this assumption, we used the sample to probe the maximum variation expected from ten independent r-process nucleosynthesis events and computed the intrinsic dispersion of each element relative to Zr and Eu for the light and heavy r-process elements, respectively. This exercise resulted in a remarkably low cosmic scatter across the ten r-process sites enriching these stars; for the rare earth and third peak elements, for example, we find σ [La/Eu] = 0.08 and σ [Os/Eu] = 0.11 dex, while the scatter between light and heavy elements, σ [Zr/Eu] , is slightly higher at 0.18 dex. Conclusions. The elemental abundance patterns across the ten independent r-process sites show remarkably small cosmic dispersions. This minimal dispersion suggests a high degree of uniformity in r-process yields across diverse astrophysical environments.

Astronomy and AstroPhysics↗
DOE OSTI2026

Total absorption spectroscopy of two isomers in 70 Cu influencing nucleosynthesis signatures

Isomers have long been known to be important for astrophysical nucleosynthesis processes, yet they are often neglected in network calculations due to computational limitations or lack of data. "Astromers" are astrophysically metastable nuclear states that can greatly impact nucleosynthesis pathways. In this work we show that astromers further impact the time-dependent electromagnetic signal during heavy element nucleosynthesis. In an experiment performed at the National Superconducting Cyclotron Laboratory, three 𝛽-decaying states of 70 Cu (6 − ground state, and two isomeric states: 3 − and 1 + ) were produced. 𝛽-feeding values were extracted from experimental spectra and compared to shell-model and QRPA+PVC calculations. Here, average 𝛾-ray energies from the 𝛽-decay events were incorporated into simulations of heavy element nucleosynthesis and were found to exhibit different energy release profiles over time, which may impact, in aggregate, time-dependent observable signals.

59 ≤ A ≤ 89↗
DOE OSTI2020

Hard Synchrotron Spectra from Magnetically Dominated Plasma Turbulence

Synchrotron emission from astrophysical nonthermal sources usually assumes that the emitting particles are isotropic. By means of large-scale two- and three-dimensional particle-in-cell simulations, we demonstrate that the dissipation of magnetically dominated (${\sigma }_{0}\gg 1$) turbulence in pair plasmas leads to strongly anisotropic particle distributions. At Lorentz factors $\sim {\sigma }_{0}{\gamma }_{\mathrm{th}0}$ (here, ${\gamma }_{\mathrm{th}0}$ is the initial Lorentz factor), the particle velocity is preferentially aligned with the local magnetic field; instead, the highest energy particles are preferentially oriented in the plane perpendicular to the field. This energy-dependent anisotropy leads to a synchrotron spectral flux $\nu {F}_{\nu }\propto {\nu }^{s}$ that is much harder than for isotropic particles. Remarkably, for ${\sigma }_{0}\gg 1$ we find that the angle-integrated spectral slope in the slow cooling regime is $s\sim 0.5-0.7$ for a wide range of turbulence fluctuations, $0.25\lesssim \delta {B}_{\mathrm{rms}0}^{2}/{B}_{0}^{2}\lesssim 4$, despite significant variations in the power-law energy spectrum of nonthermal particles. This is because weaker turbulence levels imprint a stronger degree of anisotropy, thereby counteracting the effect of the steeper particle spectrum. The synchrotron spectral slope may be even harder, $s\gtrsim 0.7$, if the observer is in the plane perpendicular to the mean magnetic field. Our results are independent of domain size and dimensionality. Further, our findings may help explain the origin of hard synchrotron spectra of astrophysical nonthermal sources, most notably the radio spectrum of pulsar wind nebulae.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

High-energy and ultra-high-energy neutrinos: A Snowmass white paper

Astrophysical neutrinos are excellent probes of astroparticle physics and high-energy physics. With energies far beyond solar, supernovae, atmospheric, and accelerator neutrinos, high-energy and ultra-high-energy neutrinos probe fundamental physics from the TeV scale to the EeV scale and beyond. They are sensitive to physics both within and beyond the Standard Model through their production mechanisms and in their propagation over cosmological distances. They carry unique information about their extreme non-thermal sources by giving insight into regions that are opaque to electromagnetic radiation. Here in this white paper describes the opportunities astrophysical neutrino observations offer for astrophysics and high-energy physics, today and in coming years.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Plasma image classification using cosine similarity constrained convolutional neural network

Plasma jets are widely investigated both in the laboratory and in nature. Astrophysical objects such as black holes, active galactic nuclei and young stellar objects commonly emit plasma jets in various forms. With the availability of data from plasma jet experiments resembling astrophysical plasma jets, classification of such data would potentially aid in not only investigating the underlying physics of the experiments but also the study of astrophysical jets. In this work we use deep learning to process all of the laboratory plasma images from the Caltech Spheromak Experiment spanning two decades. We found that cosine similarity can aid in feature selection, classify images through comparison of feature vector direction and be used as a loss function for the training of AlexNet for plasma image classification. We also develop a simple vector direction comparison algorithm for binary and multi-class classification. Using our algorithm we demonstrate 93 % accurate binary classification to distinguish unstable columns from stable columns and 92 % accurate five-way classification of a small, labelled data set which includes three classes corresponding to varying levels of kink instability.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Detection of a particle shower at the Glashow resonance with IceCube

The Glashow resonance describes the resonant formation of a W - boson during the interaction of a high-energy electron antineutrino with an electron, peaking at an antineutrino energy of 6.3 petaelectronvolts (PeV) in the rest frame of the electron. Whereas this energy scale is out of reach for currently operating and future planned particle accelerators, natural astrophysical phenomena are expected to produce antineutrinos with energies beyond the PeV scale. Here we report the detection by the IceCube neutrino observatory of a cascade of high-energy particles (a particle shower) consistent with being created at the Glashow resonance. A shower with an energy of 6.05 ± 0.72 PeV (determined from Cherenkov radiation in the Antarctic Ice Sheet) was measured. Features consistent with the production of secondary muons in the particle shower indicate the hadronic decay of a resonant W - boson, confirm that the source is astrophysical and provide improved directional localization. The evidence of the Glashow resonance suggests the presence of electron antineutrinos in the astrophysical flux, while also providing further validation of the standard model of particle physics. Its unique signature indicates a method of distinguishing neutrinos from antineutrinos, thus providing a way to identify astronomical accelerators that produce neutrinos via hadronuclear or photohadronic interactions, with or without strong magnetic fields. As such, knowledge of both the flavour (that is, electron, muon or tau neutrinos) and charge (neutrino or antineutrino) will facilitate the advancement of neutrino astronomy.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗