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At least 37 records · Page 2

Collapsar R-process Yields Can Reproduce [Eu/Fe] Abundance Scatter in Metal-poor Stars

It is unclear if neutron star mergers can explain the observed r-process abundances of metal-poor stars. Collapsars, defined here as rotating massive stars whose collapse results in a rapidly accreting disk around a black hole that can launch jets, are a promising alternative. We find that we can produce a self-consistent model in which a population of collapsars with stochastic europium yields synthesizes all of the r-process material in metal-poor ([Fe/H] < - 2.5) stars. Our model reproduces the observed scatter and evolution of scatter of [Eu/Fe] abundances. We find that if collapsars are the dominant r-process site for metal-poor stars, r-process synthesis may be linked to supernovae that produce long γ-ray bursts. Our results also allow for the possibility that core-collapse supernovae beyond those that launch γ-ray bursts also produce r-process material (e.g., potentially a subset of Type Ic-BL supernovae). Furthermore, we identify collapsar jet properties (isotropic energy, engine luminosity, or engine time) that may trace r-process yield and verify that the amount of r-process yield produced per collapsar in our model ( ~ 0.07M⊙) is consistent with other independent estimates. In the future, achieving 0.05 dex precision on distribution scatter or a reliable selection function would further constrain our probe of r-process production. Our model would also hold for another prompt r-process site with a power-law yield, and work is needed to determine if, for example, fast-merging neutron stars can also explain abundance scatter.

Astronomy & Astrophysics↗

Electrochemical storage

The source of the problem within the individual single cell which is related to the stochastic properties of cell populations and to the actual electrochemistry and chemistry taking place is described. The complications which arise in multicell batteries to show how different electrochemistries might alleviate or accentuate these problems is described. The concept of the electrochemical system is introduced to show how certain shortcomings of the single cell/battery string concept can be circumvented. Some of these electrochemical systems permit performance characteristics that are impossible by using conventional battery design philosophies. Projections for energy density and performance characteristics of the concepts are addressed.

Thaller, L. H.↗

Particle Acceleration in Active Galactic Nuclei

The high efficiency of energy generation inferred from radio observations of quasars and X-ray observations of Seyfert active galactic nuclei (AGNs) is apparently achieved only by the gravitational conversion of the rest mass energy of accreting matter onto supermassive black holes. Evidence for the acceleration of particles to high energies by a central engine is also inferred from observations of apparent superluminal motion in flat spectrum, core-dominated radio sources. This phenomenon is widely attributed to the ejection of relativistic bulk plasma from the nuclei of active galaxies, and accounts for the existence of large scale radio jets and lobes at large distances from the central regions of radio galaxies. Reports of radio jets and superluminal motion from galactic black hole candidate X-ray sources indicate that similar processes are operating in these sources. Observations of luminous, rapidly variable high-energy radiation from active galactic nuclei (AGNs) with the Compton Gamma Ray Observatory show directly that particles are accelerated to high energies in a compact environment. The mechanisms which transform the gravitational potential energy of the infalling matter into nonthermal particle energy in galactic black hole candidates and AGNs are not conclusively identified, although several have been proposed. These include direct acceleration by static electric fields (resulting from, for example, magnetic reconnection), shock acceleration, and energy extraction from the rotational energy of Kerr black holes. The dominant acceleration mechanism(s) operating in the black hole environment can only be determined, of course, by a comparison of model predictions with observations. The purpose of the work proposed for this grant was to investigate stochastic particle acceleration through resonant interactions with plasma waves that populate the magnetosphere surrounding an accreting black hole. Stochastic acceleration has been successfully applied to the problem of ion and electron energization in solar flares, and is capable of accounting for a wide range of both neutral and charged particle emissions. It is also a component in diffusive shock acceleration, since pitch-angle scattering (which is necessary for multiple shock crossings) is accompanied by diffusion in momentum space, which in turn yields a net systematic energy gain; however, stochastic energization will dominate the first-order shock process only in certain parameter regimes. Although stochastic acceleration has been applied to particle energization in the lobes of radio galaxies, its application to the central regions of AGNs has only recently been considered, but not in detail. We proposed to systematically investigate the plasma processes responsible for stochastic particle acceleration in black hole magnetospheres along with the energy-loss processes which impede particle energization. To this end we calculated acceleration rates and escape time scales for protons and electrons resonating with Alfven waves, and for electrons resonating with whistlers. Assuming either a Kolmogorov or Kraichnan wave spectrum, accretion at the Eddington limit, magnetic field strengths near equipartition, and turbulence energy densities approx. 10% of the total magnetic field energy density, we find that Alfven waves accelerate protons to Lorentz factors approx, equals 10(exp 4) - 10(exp 6) before they escape from the system. Acceleration of electrons by fast mode and whistler waves can produce a nonthermal population of relativistic electrons whose maximum energy is determined by a competition with radiation losses.

Miller, James A.↗

Patchy nuclear chain reactions

Stochastic fluctuations of the neutron population within a nuclear reactor are typically prevented by operating the core at a sufficient power, since a deterministic (i.e., exactly predictable) behavior of the neutron population is required by automatic safety systems to detect unwanted power excursions. In order to characterize the reactor operating conditions at which the fluctuations vanish, an experiment was designed and took place in 2017 at the Rensselaer Polytechnic Institute Reactor Critical Facility. This experiment however revealed persisting fluctuations and striking patchy spatial patterns in neutron spatial distributions. Here we report these experimental findings, interpret them by a stochastic modeling based on branching random walks, and extend them using a “numerical twin” of the reactor core. Consequences on nuclear safety will be discussed.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Patchy snapshots of nuclear chain reactions

Stochastic fluctuations of the neutron population within a nuclear reactor are typically prevented by operating the core at a sufficiently high power. This regime, where the evolution of the neutron density is essentially deterministic, is key for automatic protection and safety systems to safely detect unwanted power excursions during an accident, and to rapidly initiate a reactor trip procedure in case it is needed. Recent works, supported by numerical simulations, have however reported that, for large reactors, the branching nature of the fission reactions might induce strongly non-Poissonian patterns in the neutron spatial distribution, and that stochastic fluctuations might still persist at reactor powers close to operating conditions (startup phase). An international program conducted by LANL, IRSN and CEA was therefore setup to experimentally detect and characterize such fluctuations and correlations. An experiment took place in 2017 at the Reactor Critical Facility (RCF) of the Rensselaer Polytechnic Institute (USA). In this paper we will report the main findings of this experimental program, supported by stochastic models and by the development of a dedicated high-fidelity Monte Carlo simulation code. We will in particular describe and explain the strong patchiness in neutron power distributions measured at the RCF, as well as a peculiar ‘blinking’ behavior of the core, and discuss the consequences of these findings on nuclear safety.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Differentiable Predictions for Large Scale Structure with SHAMNet

In simulation-based models of the galaxy-halo connection, theoretical predictions for galaxy clustering and lensing are typically made based on Monte Carlo realizations of a mock universe. In this paper, we use Subhalo Abundance Matching (SHAM) as a toy model to introduce an alternative to stochastic predictions based on mock population, demonstrating how to make simulation-based predictions for clustering and lensing that are both exact and differentiable with respect to the parameters of the model. Conventional implementations of SHAM are based on iterative algorithms such as Richardson-Lucy deconvolution; here we use the JAX library for automatic differentiation to train SHAMNet, a neural network that accurately approximates the stellar-to-halo mass relation (SMHM) defined by abundance matching. In our approach to making differentiable predictions of large-scale structure, we map parameterized PDFs onto each simulated halo, and calculate gradients of summary statistics of the galaxy distribution by using autodiff to propagate the gradients of the SMHM through the statistical estimators used to measure one- and two-point functions. Our techniques are quite general, and we conclude with an overview of how they can be applied in tandem with more complex, higher-dimensional models, creating the capability to make differentiable predictions for the multi-wavelength universe of galaxies.

79 ASTRONOMY AND ASTROPHYSICS↗

Particle Acceleration in Active Galactic Nuclei

The investigation of stochastic particle acceleration through resonant interactions with plasma waves that populate the magnetosphere surrounding an accreting black hole is presented. Stochastic acceleration has been successfully applied to the problem of ion and electron energization in solar flares, and is capable of accounting for a wide range of both neutral and charged particle emissions. It is also a component in diffusive shock acceleration, since pitch-angle scattering (which is necessary for multiple shock crossings) is accompanied by diffusion in momentum space, which in turn yields a net systematic energy gain; however, stochastic energization will dominate the first-order shock process only in certain parameter regimes. Although stochastic acceleration has been applied to particle energization in the lobes of radio galaxies, its application to the central regions of AGNs (active galactic nuclei) has only recently been considered, but not in detail. We proposed to systematically investigate the plasma processes responsible for stochastic particle acceleration in black hole magnetospheres along with the energy-loss processes which impede particle energization. To this end, we calculated acceleration rates and escape time scales for protons and electrons resonating with Alfven waves, and for electrons resonating with whistlers. We also considered the "hot" topic of gamma-ray line emission from the Orion complex. We proposed that the observed gamma-ray lines are produced by energetic ions that are stochastically accelerated by cascading Alfven waves in the accretion plasma near a black hole. Related research papers that were published in journals are listed.

Miller, James A.↗

Critical Slowing Down in Time-to-Extinction: An Example of Critical Phenomena in Ecology

We study a model for two competing species that explicitly accounts for effects due to discreteness, stochasticity and spatial extension of populations. The two species are equally preferred by the environment and do better when surrounded by others of the same species. We observe that the final outcome depends on the initial densities (uniformly distributed in space) of the two species. The observed phase transition is a continuous one and key macroscopic quantities like the correlation length of clusters and the time-to-extinction diverge at a critical point. Away from the critical point, the dynamics can be described by a mean-field approximation. Close to the critical point, however, there is a crossover to power-law behavior because of the gross mismatch between the largest and smallest scales in the system. We have developed a theory based on surface effects, which is in good agreement with the observed behavior. The course-grained reaction-diffusion system obtained from the mean-field dynamics agrees well with the particle system.

Gandhi, Amar↗

Improving Project Management with Simulation and Completion Distribution Functions

Despite the critical importance of project completion timeliness, management practices in place today remain inadequate for addressing the persistent problem of project completion tardiness. A major culprit in late projects is uncertainty, which most, if not all, projects are inherently subject to. This uncertainty resides in the estimates for activity durations, the occurrence of unplanned and unforeseen events, and the availability of critical resources. In response to this problem, this research developed a comprehensive simulation based methodology for conducting quantitative project completion time risk analysis. It is called the Project Assessment by Simulation Technique (PAST). This new tool enables project stakeholders to visualize uncertainty or risk, i.e. the likelihood of their project completing late and the magnitude of the lateness, by providing them with a completion time distribution function of their projects. Discrete event simulation is used within PAST to determine the completion distribution function for the project of interest. The simulation is populated with both deterministic and stochastic elements. The deterministic inputs include planned project activities, precedence requirements, and resource requirements. The stochastic inputs include activity duration growth distributions, probabilities for events that can impact the project, and other dynamic constraints that may be placed upon project activities and milestones. These stochastic inputs are based upon past data from similar projects. The time for an entity to complete the simulation network, subject to both the deterministic and stochastic factors, represents the time to complete the project. Repeating the simulation hundreds or thousands of times allows one to create the project completion distribution function. The Project Assessment by Simulation Technique was demonstrated to be effective for the on-going NASA project to assemble the International Space Station. Approximately $500 million per month is being spent on this project, which is scheduled to complete by 2010. NASA project stakeholders participated in determining and managing completion distribution functions produced from PAST. The first result was that project stakeholders improved project completion risk awareness. Secondly, using PAST, mitigation options were analyzed to improve project completion performance and reduce total project cost.

Cates, Grant R.↗

Stochastic histories of refractory interstellar dust

Histories of refractory interstellar dust particles (IDPs) are calculated. The profile of a particle population is assembled from a large number of stochastic, or Monte Carlo, histories of single particles; the probabilities for each of the events that may befall a given particle are specified, and the particle's history is unfolded by a sequence of random numbers. The assumptions that are made and the techniques of the calculation are described together with the results obtained. Several technical demonstrations are presented.

Liffman, Kurt↗

The eROSITA Final Equatorial-Depth Survey (eFEDS)

The eROSITA Final Equatorial Depth Survey (eFEDS), completed in survey mode during the calibration and performance verification phase of the eROSITA instrument on Spectrum Roentgen Gamma, delivers data at and beyond the final depth of the 4-yr eROSITA all-sky survey (eRASS:8), f 0.5–2 keV = 1.1 × 10 –14 erg s –1 cm –2 , over 140 deg 2 . It provides the first view of normal galaxy X-ray emission from X-ray binaries (XRBs) and the hot interstellar medium at the full depth of eRASS:8. We used the Heraklion Extragalactic Catalogue (HECATE) of galaxies to correlate with eFEDS X-ray sources and identify X-ray detected normal galaxies. This flux-limited X-ray survey is relatively free from selection effects and enables the study of integrated normal galaxy X-ray emission and its relation to galaxy parameters such as the stellar mass, star formation rate (SFR), and metallicity. We cross-correlated 32 646 eFEDS X-ray sources to 1181 HECATE normal galaxies and obtained 94 matches. We classified galaxies as star-forming, early-type, composite, and active galactic nuclei (AGN) using Sloan Digital Sky Survey (SDSS) and Six-degree Field (6dF) optical spectroscopy. The eFEDS field harbours 37 normal galaxies: 36 late-type (star-forming) galaxies and one early-type galaxy. There are 1.9 times as many normal galaxies as predicted by scaling relations via simulations, with an overabundance of late-type galaxies and a dearth of early-type galaxies. When compared with empirical relations, eFEDS dwarf galaxies with a high specific SFR have elevated L X /SFR at a fixed specific SFR and metallicity, indicating an increase in XRB emission due to low metallicity. We expect that eRASS:8 will detect 12 500 normal galaxies, the majority of which will be star-forming, with the caveat that there are unclassified sources in eFEDS and galaxy catalogue incompleteness issues that could increase the actual number of detected galaxies over these current estimates. eFEDS observations detected a rare population of galaxies – the metal-poor dwarf starbursts – that do not follow known scaling relations. eRASS is expected to discover significant numbers of these high-redshift analogues, which are important for studying the heating of the intergalactic medium at high redshift. Further investigation of the hot gas emission from normal galaxies and stochastic effects in the dwarf galaxy population are required to constrain their X-ray output.

79 ASTRONOMY AND ASTROPHYSICS↗

A Process-based Model with Temperature, Water, and Lab-derived Data Improves Predictions of Daily Culex pipiens/restuans Mosquito Density

While the number of human cases of mosquito-borne diseases has increased in North America in the last decade, accurate modeling of mosquito population density has remained a challenge. Longitudinal mosquito trap data over the many years needed for model calibration, and validation is relatively rare. In particular, capturing the relative changes in mosquito abundance across seasons is necessary for predicting the risk of disease spread as it varies from year to year. We developed a discrete, semi-stochastic, mechanistic process-based mosquito population model that captures life-cycle egg, larva, pupa, adult stages, and diapause for Culex pipiens (Diptera, Culicidae) and Culex restuans (Diptera, Culicidae) mosquito populations. This model combines known models for development and survival into a fully connected age-structured model that can reproduce mosquito population dynamics. Mosquito development through these stages is a function of time, temperature, daylight hours, and aquatic habitat availability. The time-dependent parameters are informed by both laboratory studies and mosquito trap data from the Greater Toronto Area. The model incorporates city-wide water-body gauge and precipitation data as a proxy for aquatic habitat. This approach accounts for the nonlinear interaction of temperature and aquatic habitat variability on the mosquito life stages. We demonstrate that the full model predicts the yearly variations in mosquito populations better than a statistical model using the same data sources. This improvement in modeling mosquito abundance can help guide interventions for reducing mosquito abundance in mitigating mosquito-borne diseases like West Nile virus.

59 BASIC BIOLOGICAL SCIENCES↗

The Stochastic Gause Predator-Prey model: Noise-induced extinctions and invariance

We consider the Gause predator-prey with general bounded or sub‑linear functional responses, – which includes those of Holling types Ⅰ–Ⅳ. – and multiplicative Gaussian noise. In contrast to previous studies, the prey in our model follows logistic dynamics while the predator's population is solely regulated by consumption of the prey. To ensure well-posedeness, we derive explicit Lyapunov‐type criteria ensuring global positivity and moment boundedness of solutions. We find conditions for noise‑induced extinctions, proving that stochasticity can drive either population to collapse even when the deterministic analogue predicts stable coexistence. In the case when the predator becomes extinct, we establish a limiting distribution for the predator's population. Last, for functional responses of Holling type Ⅰ, we provide sufficient conditions on the intensity of the noise for the existence and uniqueness of a stationary distribution.

Gause model↗

Interplanetary ions during an energetic storm particle event - The distribution function from solar wind thermal energies to 1.6 MeV

An ion velocity distribution function of the postshock phase of an energetic storm particle (ESP) event is obtained from data from the ISEE 2 and ISEE 3 experiments. The distribution function is roughly isotropic in the solar wind frame from solar wind thermal energies to 1.6 MeV. The ESP event studied (8/27/78) is superposed upon a more energetic particle event which was predominantly field-aligned and which was probably of solar origin. The observations suggest that the ESP population is accelerated directly out of the solar wind thermal population or its quiescent suprathermal tail by a stochastic process associated with shock wave disturbance. The acceleration mechanism is sufficiently efficient so that approximately 1% of the solar wind population is accelerated to suprathermal energies. These suprathermal particles have an energy density of approximately 290 eV cubic centimeters.

Gosling, J. T.↗

Resource distribution under spatiotemporal uncertainty of disease spread: Stochastic versus robust approaches

We consider the problem of optimizing locations of distribution centers (DCs) and plans for distributing resources such as test kits and vaccines, under spatiotemporal uncertainties of disease spread and demand for the resources. We aim to balance the operational cost (including costs of deploying facilities, shipping, and storage) and quality of service (reflected by demand coverage), while ensuring equity and fairness of resource distribution across multiple populations. We compare a sample-based stochastic programming (SP) approach with a distributionally robust optimization (DRO) approach using a moment-based ambiguity set. Numerical studies are conducted on instances of distributing COVID-19 vaccines in the United States and test kits, to compare SP and DRO models with a deterministic formulation using estimated demand and with the current resource distribution plans implemented in the US. We demonstrate the results over distinct phases of the pandemic to estimate the cost and speed of resource distribution depending on scale and coverage, and show the “demand-driven” properties of the SP and DRO solutions. Furthermore, our results further indicate that if the worst-case unmet demand is prioritized, then the DRO approach is preferred despite of its higher overall cost. Nevertheless, the SP approach can provide an intermediate plan under budgetary restrictions without significant compromises in demand coverage.

97 MATHEMATICS AND COMPUTING↗

Inferring Stochastic Rates from Heterogeneous Snapshots of Particle Positions

Many imaging techniques for biological systems—like fixation of cells coupled with fluorescence microscopy—provide sharp spatial resolution in reporting locations of individuals at a single moment in time but also destroy the dynamics they intend to capture. In this study, these snapshot observations contain no information about individual trajectories, but still encode information about movement and demographic dynamics, especially when combined with a well-motivated biophysical model. The relationship between spatially evolving populations and single-moment representations of their collective locations is well-established with partial differential equations (PDEs) and their inverse problems. However, experimental data is commonly a set of locations whose number is insufficient to approximate a continuous-in-space PDE solution. Here, motivated by popular subcellular imaging data of gene expression, we embrace the stochastic nature of the data and investigate the mathematical foundations of parametrically inferring demographic rates from snapshots of particles undergoing birth, diffusion, and death in a nuclear or cellular domain. Toward inference, we rigorously derive a connection between individual particle paths and their presentation as a Poisson spatial process. Using this framework, we investigate the properties of the resulting inverse problem and study factors that affect quality of inference. One pervasive feature of this experimental regime is the presence of cell-to-cell heterogeneity. Rather than being a hindrance, we show that cell-to-cell geometric heterogeneity can increase the quality of inference on dynamics for certain parameter regimes. Altogether, the results serve as a basis for more detailed investigations of subcellular spatial patterns of RNA molecules and other stochastically evolving populations that can only be observed for single instants in their time evolution.

59 BASIC BIOLOGICAL SCIENCES↗

Genetic monitoring of steelhead in the Klickitat River to estimate productivity, straying, and migration timing

Abstract Objective Salmonids with a complex life history variation present challenges for conservation management, but genetic approaches alongside fisheries monitoring can address questions regarding the viability of the natural populations. Methods We genotyped adult (n = 3108) and juvenile (n = 2624) samples of steelhead Oncorhynchus mykiss that were collected in the Klickitat River, Washington, USA at traps in the lower drainage to examine tributary level productivity, straying from outside sources, and variation in adult migration timing. Result Genetic assignment of steelhead from this system indicated that the majority were produced within or near tributaries of the middle Klickitat River (juvenile mean = 72.8%; adult mean = 87.3%). Analyses with parentage-based tagging identified that most hatchery-origin adults were assigned to the Skamania Hatchery (80.8%), as expected, since this has been the release stock for decades within the Klickitat River drainage. Hatchery-origin adults were also identified from programs operating outside the Klickitat River, which were primarily strays from Snake River hatcheries. Most natural-origin steelhead were assigned to the Klickitat River, but there were also natural-origin fish identified as strays from other regions of the Columbia River (22.3% of natural returns). We also examined genes known to be associated with migration timing in adult steelhead observed at the trap and observed a strong relationship between migration date and alleles for early and late migration, but individual outliers were detected across seasons. Conclusion Our results indicate that genetic variation of steelhead in the Klickitat River has been influenced by hatchery programs as well as natural-origin straying from other subbasins, but genetic diversity remains high throughout the subbasin, and both early and late migration alleles are maintained. The genetic diversity present in Klickitat River steelhead may enable this Endangered Species Act listed (threatened) species to better adapt to stochastic environmental conditions compared to less diverse populations.

Collins, Erin E. (ORCID:0000000260978479)↗

Runaway electron seed formation at reactor-relevant temperature

Systematic variation of the pre-disruption core electron temperature (T e ) from 1 to 12 keV using an internal transport barrier scenario reveals a dramatic increase in the production of ‘seed’ runaway electrons (REs), ultimately accessing near-complete conversion of the pre-disruption current into sub-MeV RE current. Injected Ar pellets are observed to ablate more intensely and promptly as T e rises. At high T e , the observed ablation exceeds predictions from published thermal ablation models. Simultaneously, the thermal quench (TQ) is observed to significantly shorten with increasing T e —a surprising result. While the reason for the shorter TQ is not yet understood, candidate mechanisms include: insufficiently accurate thermal ablation models, enhanced ablation driven by the seed RE population, or significant parallel heat transport along stochastic fields. Kinetic modeling that self-consistently treats the plasma cooling via radiation, the induced electric field, and the formation of the seed RE is performed. Including the combined effect of the inherent dependence of hot-tail RE seeding on T e together with the shortened TQ, modeling recovers the progression towards near-complete conversion of the pre-disruption current to RE current as T e rises. Measurement of the HXR spectrum during the early current quench (CQ) reveals a trend of decreasing energy with pre-disruption T e . At the very highest T e (≈ 12 keV), ≈ 100% conversion of the thermal current to runaway current is found. The energy of this peculiar RE beam is inferred to be sub-MeV as it emits vanishingly few MeV hard x-rays (HXRs). These measurements demonstrate novel TQ dynamics as Te is varied and illustrate the limitations of treating the RE seed formation problem without considering the inter-related dependencies of the pellet ablation, radiative energy loss, and resultant variations of the TQ duration. Finally, if the observed shortening of the TQ with increasing T e extends to fusion-grade plasmas, than their propensity to form large quantities of RE seeds at high T e may be far worse than previously thought. Positively, the high T e scenario in DIII-D produces REs so prodigiously that it can serve as a meaningful new platform for demonstrating RE avoidance techniques.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗