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At least 811 records · Page 45

Watch and learn—a generalized approach for transferrable learning in deep neural networks via physical principles

Transfer learning refers to the use of knowledge gained while solving a machine learning task and applying it to the solution of a closely related problem. Such an approach has enabled scientific breakthroughs in computer vision and natural language processing where the weights learned in state-of-the-art models can be used to initialize models for other tasks which dramatically improve their performance and save computational time. Here we demonstrate an unsupervised learning approach augmented with basic physical principles that achieves fully transferrable learning for problems in statistical physics across different physical regimes. By coupling a sequence model based on a recurrent neural network to an extensive deep neural network, we are able to learn the equilibrium probability distributions and inter-particle interaction models of classical statistical mechanical systems. Our approach, distribution-consistent learning, DCL, is a general strategy that works for a variety of canonical statistical mechanical models (Ising and Potts) as well as disordered interaction potentials. Using data collected from a single set of observation conditions, DCL successfully extrapolates across all temperatures, thermodynamic phases, and can be applied to different length-scales. This constitutes a fully transferrable physics-based learning in a generalizable approach.

97 MATHEMATICS AND COMPUTING↗

Soft x ray properties of the Geminga pulsar

The ROSAT soft x ray spectrum and pulse profile of the Geminga pulsar are analyzed and interpreted in terms of thermal emission from the surface of the neutron star. The x ray spectrum appears to consist of two blackbody components with T(sub 1) = (5.2 +/- 1.0) x 10 (exp 5) K and T(sub 2) approximately 3 x 10(exp 6) K, respectively. The inferred ratio of surface areas, A(sub 2)/A(sub 1), is approximately 3 x 10(exp -5). Both components are highly modulated at the pulsar rotation period, but the harder x ray pulse is narrower, and leads the main (soft) x ray pulse by about 105 deg of phase. The soft x ray component is interpreted as photospheric cooling of much of the neutron star's surface area, while the small, hot region could be part of the much smaller polar cap heated by energetic particles flowing inward from the magnetospheric accelerator which is responsible for the production of Geminga's gamma rays. Geminga's gamma ray emission is consistent with outer-magnetosphere accelerator models for highly inclined dipoles. These predict the beaming of energetic gamma rays close enough to the star to give copious e(+/-) production in the stellar magnetic field and a large circumstellar pair density from pair inflow toward the surface. These pairs may quench radio emission, and also reflect most of the hard polar cap x rays back to the stellar surface by cyclotron resonance scattering. They are then reemitted from that much larger area at the lower temperature T(sub 1). The single-peaked nature of the x ray pulse and its energy-dependent phase suggest an off-center dipole geometry for the surface magnetic field. Under the assumption that the soft x ray emission comes from the full surface of a neutron star of radius R = 10 km, a distance estimate of (150-400) pc is derived. This range is consistent with the fit interstellar column density of (1.5 +/- 0.5) x 10(exp 20) cm(exp -2). Distances less than 150 pc are probably ruled out both by the lower limit on the column density, and also by the requirement that the Rayleigh-Jeans extrapolation of the soft x ray spectrum not exceed the observed blue flux of the faint optical counterpart. This distance estimate implies that Geminga's efficiency for converting spindown power into gamma-rays is near unity, and that there may be significant beaming of the gamma rays as well. These results tend to bolster the prospect that most of the unidentified high-energy gamma ray sources in the Galactic plane are pulsars, some of which may be radio quiet.

Halpern, J. P.↗

Experimentally Produced Spinel Rims on Ca-Al-Rich Inclusion Bulk Compositions

Most Ca-Al-rich inclusions (CAls) from Allende are surrounded by a series of mineralogically distinct rim layers. Proposed modes of formation for these layers include flash heating, evaporation, and condensation. The innermost of these rim layers is generally spinel (SP), in some cases intergrown with perovskite (PV), and commonly containing varying amounts of secondary iron increasing towards the edge of the CAI. The SP or SP+PV rim is not always contiguous with the other rim layers, indicating that it is probably the result of a separate event. We have produced continuous SP rims on synthetic analogs representing Type A/B1, average Type B, and Type B2 bulk compositions by reheating a solid glass experimental charge to subliquidus crystallization temperatures. This experimental result is consistent with the formation of chondrules; and CAIs by more than one sequence of heating and cooling. Previous work indicated that prior crystallization events produced observable effects in the texture and chemistry of the final run product. Information on the nature of the heating/cooling cycles experienced by CAls and chondrules is important in modeling the environment of their formation. Additional information is contained in the original extended abstract.

Paque, Julie M.↗

The Characteristics and Consequences of the Break-up of the Fengyun-1C Spacecraft

The intentional break-up of the Fengyun-1C spacecraft on 11 January 2007 via hypervelocity collision with a ballistic object created the most severe artificial debris cloud in Earth orbit since the beginning of space exploration. More than 900 debris on the order of 10 cm or greater in size have been identified by the U.S. Space Surveillance Network (SSN). The majority of these debris reside in long-lived orbits. The NASA Orbital Debris Program Office has conducted a thorough examination of the nature of the Fengyun-1C debris cloud, using SSN data for larger debris and special Haystack radar observations for smaller debris. These data have been compared with the NASA standard satellite break-up model for collisions, and the results are presented in this paper. The orbital longevity of the debris have also been evaluated for both small and large debris. The consequent long-term spatial density effects on the low Earth orbit (LEO) regime are then described. Finally, collision probabilities between the Fengyun-1C debris cloud and the resident space object population of 1 January 2007 have been calculated. The potential effect on the growth of the near-Earth satellite population is presented.

Johnson, Nicholas L.↗

Update on Automated Classification of Interplanetary Dust Particles

Every year, the Earth accretes about 40,000 tons of extraterrestrial material less than 1 mm in size on its surface. These dust particles originate from active comets, from impacts between asteroids and may also be coming from interstellar space for the very small particles. Since 1981, NASA Jonhson Space Center (JSC) has been systematically collecting the dust from Earth's strastosphere by airborne collectors and gathered them into "Cosmic Dust Catalogs". In those catalogs, a preliminary analysis of the dust particles based on SEM images, some geological characteristics and X-ray energy-dispersive spectrometry (EDS) composition is compiled. Based on those properties, the IDPs are classified into four main groups: C (Cosmic), TCN (Natural Terrestrial Contaminant), TCA (Artificial Terrestrial Contaminant) and AOS (Aluminium Oxide Sphere). Nevertheless, 20% of those particles remain ambiguously classified. Lasue et al. presented a methodology to help automatically classify the particles published in the catalog 15 based on their EDS spectra and nonlinear multivariate projections (as shown in Fig. 1). This work allowed to relabel 155 particles out of the 467 particles in catalog 15 and reclassify some contaminants as potential cosmic dusts. Further analyses of three such particles indicated their probable cosmic origin. The current work aims to bring complementary information to the automatic classification of IDPs to improve identification criteria.

Maroger, I.↗

Inferring the shape of data: a probabilistic framework for analysing experiments in the natural sciences

A critical step in data analysis for many different types of experiments is the identification of features with theoretically defined shapes in N -dimensional datasets; examples of this process include finding peaks in multi-dimensional molecular spectra or emitters in fluorescence microscopy images. Identifying such features involves determining if the overall shape of the data is consistent with an expected shape; however, it is generally unclear how to quantitatively make this determination. In practice, many analysis methods employ subjective, heuristic approaches, which complicates the validation of any ensuing results—especially as the amount and dimensionality of the data increase. Here, we present a probabilistic solution to this problem by using Bayes’ rule to calculate the probability that the data have any one of several potential shapes. This probabilistic approach may be used to objectively compare how well different theories describe a dataset, identify changes between datasets and detect features within data using a corollary method called Bayesian Inference-based Template Search; several proof-of-principle examples are provided. Altogether, this mathematical framework serves as an automated ‘engine’ capable of computationally executing analysis decisions currently made by visual inspection across the sciences.

Science & Technology - Other Topics↗

LeptonInjector and LeptonWeighter: A neutrino event generator and weighter for neutrino observatories

In this work, we present a high-energy neutrino event generator, called LeptonInjector, alongside an event weighter, called LeptonWeighter. Both are designed for large-volume Cherenkov neutrino telescopes such as IceCube. The neutrino event generator allows for quick and flexible simulation of neutrino events within and around the detector volume, and implements the leading Standard Model neutrino interaction processes relevant for neutrino observatories: neutrino-nucleon deep-inelastic scattering and neutrino-electron annihilation. In this paper, we discuss the event generation algorithm, the weighting algorithm, and the main functions of the publicly available code, with examples. Program summary: Program Titles: LeptonInjector and LeptonWeighter CPC Library link to program files: https://doi.org/10.17632/662gkpjfd9.1 Developer's repository links: https://github.com/icecube/LeptonInjector and https://github.com/icecube/LeptonWeighter Licensing provisions: GNU Lesser General Public License, version 3. Programming Language: C++11 External Routines: • Boost • HDF5 • nuflux (https://github.com/icecube/nuflux) • nuSQuIDS (https://github.com/arguelles/nuSQuIDS) • Photospline (https://github.com/icecube/photospline) • SuiteSparse (https://github.com/DrTimothyAldenDavis/SuiteSparse) Nature of problem: LeptonInjector: Generate neutrino interaction events of all possible topologies and energies throughout and around a detector volume. LeptonWeighter: Reweight Monte Carlo events, generated by a set of LeptonInjector Generators, to any desired physical neutrino flux or cross section. Solution method: LeptonInjector: Projected ranges of generated leptons and the extent of the detector, in terms of column depth, are used to inject events in and around the detector volume. Event kinematics follow distributions provided in cross section files. LeptonWeighter: Event generation probabilities are calculated for each Generator, which are then combined into a generation weight and used to calculate an overall event weight.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Biophotonic rogue waves in red blood cell suspensions

Rogue waves are ubiquitous in nature, appearing in a variety of physical systems ranging from acoustics, microwave cavities, optical fibers, and resonators to plasmas, superfluids, and Bose–Einstein condensates. Unlike nonlinear solitary waves, rogue waves are extreme events that can occur even without nonlinearity by, for example, spontaneous synchronization of waves with different spatial frequencies in a linear system. Here, we report the observation of rogue-wave-like events in human red blood cell (RBC) suspensions under weak light illumination, characterized by an abnormal L-shaped probability distribution. Such biophotonic extreme events arise mostly due to the constructive interference of Mie-scattered waves from the suspended RBCs, whose biconcave shape and mutable orientation give rise to a time-dependent random phase modulation to an incident laser beam. We numerically simulate the beam propagation through the colloidal suspensions with added disorder in both spatial and temporal domains to mimic random scattering due to Brownian motion. In addition, at high power levels, nonlinear beam self-focusing is also observed, leading to a dual-exponential probability distribution associated with the formation of multiple soliton-like spots. Such rogue wave events should also exist in environments with cells of other species such as swimming bacteria, and understanding of their underlying physics may lead to unexpected biophotonic applications.

59 BASIC BIOLOGICAL SCIENCES↗

Approximate maximum likelihood decoding of block codes

Approximate maximum likelihood decoding algorithms, based upon selecting a small set of candidate code words with the aid of the estimated probability of error of each received symbol, can give performance close to optimum with a reasonable amount of computation. By combining the best features of various algorithms and taking care to perform each step as efficiently as possible, a decoding scheme was developed which can decode codes which have better performance than those presently in use and yet not require an unreasonable amount of computation. The discussion of the details and tradeoffs of presently known efficient optimum and near optimum decoding algorithms leads, naturally, to the one which embodies the best features of all of them.

Greenberger, H. J.↗

KAO and AAT observations of the Galactic Center filaments

We have used the Kuiper Airborne Observatory (KAO) and the Anglo-Australian Telescope (AAT) to investigate the nature of the filamentary radio emission from the Galactic center region. KAO observations of the FIR line and continuum emission from the radio peak G0.095+0.012 and the E2 thermal radio filament northeast of the Galactic center can be produced by numerous nearby stars with T(sub eff) approx. 35,000 K; these can account for both the FIR luminosity and the excitation of the gas. Much of the FIR continuum and most of the strong (Si II) (34.8 micron) line emission are probably produced in the ionized gas of the filament. The FIR (O III) 52 and 88 micron lines imply an electron density of a few hundred; when compared with the radio emission measure, this implies the filament is roughly tubular or somewhat flattened in the plane of the sky. The (O III) and (S III) lines show higher excitation associated with the filament, and suggest that exciting stars may be located within the filaments and/or southeast of the E2 filament. AAT observations in the near infrared (NIR) in fact reveal a nearby cluster of hot stars southeast of the E2 filament. Additional hot stars, not identifiable from their NIR spectra, are likely to be present. These stars and those in the cluster can plausibly produce the observed radio and FIR emission in the region. The morphology of the filament is not explained by existing information however.

Erickson, Edwin F.↗

Probabilistic Assessment of Radiation Risk for Astronauts in Space Missions

Accurate predictions of the health risks to astronauts from space radiation exposure are necessary for enabling future lunar and Mars missions. Space radiation consists of solar particle events (SPEs), comprised largely of medium energy protons, (less than 100 MeV); and galactic cosmic rays (GCR), which include protons and heavy ions of higher energies. While the expected frequency of SPEs is strongly influenced by the solar activity cycle, SPE occurrences themselves are random in nature. A solar modulation model has been developed for the temporal characterization of the GCR environment, which is represented by the deceleration potential, phi. The risk of radiation exposure from SPEs during extra-vehicular activities (EVAs) or in lightly shielded vehicles is a major concern for radiation protection, including determining the shielding and operational requirements for astronauts and hardware. To support the probabilistic risk assessment for EVAs, which would be up to 15% of crew time on lunar missions, we estimated the probability of SPE occurrence as a function of time within a solar cycle using a nonhomogeneous Poisson model to fit the historical database of measurements of protons with energy > 30 MeV, (phi)30. The resultant organ doses and dose equivalents, as well as effective whole body doses for acute and cancer risk estimations are analyzed for a conceptual habitat module and a lunar rover during defined space mission periods. This probabilistic approach to radiation risk assessment from SPE and GCR is in support of mission design and operational planning to manage radiation risks for space exploration.

Kim, Myung-Hee↗

Emerging signals of declining forest resilience under climate change

Forest ecosystems depend on their capacity to withstand and recover from natural and anthropogenic perturbations (that is, their resilience). Experimental evidence of sudden increases in tree mortality is raising concerns about variation in forest resilience, yet little is known about how it is evolving in response to climate change. Here we integrate satellite-based vegetation indices with machine learning to show how forest resilience, quantified in terms of critical slowing down indicators, has changed during the period 2000–2020. We show that tropical, arid and temperate forests are experiencing a significant decline in resilience, probably related to increased water limitations and climate variability. By contrast, boreal forests show divergent local patterns with an average increasing trend in resilience, probably benefiting from warming and CO 2 fertilization, which may outweigh the adverse effects of climate change. These patterns emerge consistently in both managed and intact forests, corroborating the existence of common large-scale climate drivers. Reductions in resilience are statistically linked to abrupt declines in forest primary productivity, occurring in response to slow drifting towards a critical resilience threshold. Approximately 23% of intact undisturbed forests, corresponding to 3.32 Pg C of gross primary productivity, have already reached a critical threshold and are experiencing a further degradation in resilience. Together, these signals reveal a widespread decline in the capacity of forests to withstand perturbation that should be accounted for in the design of land-based mitigation and adaptation plans

54 ENVIRONMENTAL SCIENCES↗

Magnetospheric electron density measurements from upper hybrid resonance noise observed by IMP-6

A band of natural radio noise between the local electron plasma frequency and the upper hybrid resonance frequency is observed by the IMP-6 satellite. The band exists over a large range of geocentric radial distances extending from inside the plasmapause boundary to greater than 10 earth radii in the outer magnetosphere. The center frequency of the noise band decreases with increasing radial distance, and changes abruptly at the plasmapause boundary. The broadband electric field strength of this noise is very small, seldom exceeding 10 microvolts/meter, and probably could not be detected without using long electric antennas of IMP-6. It is believed that this noise is produced by incoherent Cerenkov emission from super-thermal electrons. In some cases a second very narrow noise band was observed at a frequency slightly above the second harmonic of the electron gyrofrequency.

Shaw, R. R.↗

Shielding materials for highly penetrating space radiations

Interplanetary travel involves the transfer from an Earth orbit to a solar orbit. Once outside the Earth's magnetosphere, the major sources of particulate radiation are solar cosmic rays (SCR's) and galactic cosmic rays (GCR's). Intense fluxes of SCR's come from solar flares and consist primarily of protons with energies up to 1 GeV. The GCR consists of a low flux of nuclei with energies up to 10(exp 10) GeV. About 70 percent of the GCR are protons, but a small amount (0.6 percent) are nuclei with atomic numbers greater than 10. High energy charged particles (HZE) interact with matter by transferring energy to atomic electrons in a Coulomb process and by reacting with an atomic nucleus. Energy transferred in the first process increases with the square of the atomic number, so particles with high atomic numbers would be expected to lose large amounts of energy by this process. Nuclear reactions produced by (HZE) particles produce high-energy secondary particles which in turn lose energy to the material. The HZE nuclei are a major concern for radiation protection of humans during interplanetary missions because of the very high specific ionization of both primary and secondary particles. Computer codes have been developed to calculate the deposition of energy by very energetic charged particles in various materials. Calculations show that there is a significant buildup of secondary particles from nuclear fragmentation and Coulomb dissociation processes. A large portion of these particles are neutrons. Since neutrons carry no charge, they only lose energy by collision or reaction with a nucleus. Neutrons with high energies transfer large amounts of energy by inelastic collisions with nuclei. However, as the neutron energy decreases, elastic collisions become much more effective for energy loss. The lighter the nucleus, the greater the fraction of the neutron's kinetic energy that can be lost in an elastic collision. Thus, hydrogen-containing materials such as polymers are most effective in reducing the energy of neutrons. Once neutrons are reduced to very low energies, the probability for undergoing a reaction with a nucleus (the cross section) becomes very high. The product of such a reaction is often radioactive and can involve the release of a significant amount of energy. Thus, it is important to provide protection from low energy neutrons during a long duration space flight. Among the light elements, lithium and boron each have an isotope with a large thermal neutron capture cross section, Li-6 and B-10. However, B-10 is more abundant in the naturally-occurring element than Li-6, has a thermal neutron capture cross section four times that of Li-6, and produces the stable products, He-4 and Li-7 in the interaction while Li-6 produces radioactive tritium (H-3). Thus, boron is the best light-weight material for thermal neutron absorption in spacecraft. The work on this project was focused in two areas: computer design where existing computer codes were used, and in some cases modified, to calculate the propagation and interactions of high energy charged particles through various media, and materials development where boron was incorporated into high performance materials.

Kiefer, Richard L.↗

Toward a Physical Characterization of Raindrop Collision Outcome Regimes

A comprehensive raindrop collision outcome regime diagram that delineates the physical conditions associated with the outcome regimes (i.e., bounce, coalescence, and different breakup types) of binary raindrop collisions is proposed. The proposed diagram builds on a theoretical regime diagram defined in the phase space of collision Weber numbers We and the drop diameter ratio p by including critical angle of impact considerations. In this study, the theoretical regime diagram is first evaluated against a comprehensive dataset for drop collision experiments representative of raindrop collisions in nature. Subsequently, the theoretical regime diagram is modified to explicitly describe the dominant regimes of raindrop interactions in (We, p) by delineating the physical conditions necessary for the occurrence of distinct types of collision-induced breakup (neck/filament, sheet, disk, and crown breakups) based on critical angle of impact consideration. Crown breakup is a subtype of disk breakup for lower collision kinetic energy that presents distinctive morphology. Finally, the experimental results are analyzed in the context of the comprehensive collision regime diagram, and conditional probabilities that can be used in the parameterization of breakup kernels in stochastic models of raindrop dynamics are provided.

Testik, F. Y.↗

KMT-2021-BLG-0912Lb: A Microlensing Super Earth Around A K-Type Star

Aims . The light curve of the microlensing event KMT-2021-BLG-0912 exhibits a very short anomaly relative to a single-lens single-source form. We investigate the light curve for the purpose of identifying the origin of the anomaly. Methods . We model the light curve under various interpretations. From this, we find four solutions, in which three solutions are found under the assumption that the lens is composed of two masses (2L1S models), and the other solution is found under the assumption that the source is comprised of binary stars (1L2S model). The 1L2S model is ruled out based on the contradiction that the faint source companion is bigger than its primary, and one of the 2L1S solutions is excluded from the combination of the poorer fit, blending constraint, and lower overall probability, leaving two surviving solutions with the planet/host mass ratios of q ∼ 2.8 × 10 −5 and ∼1.1 × 10 −5 . A subtle central deviation supports the possibility of a tertiary lens component, either a binary companion to the host with a very large or small separation, or a second planet lying near the Einstein ring, but it is difficult to claim a secure detection due to the marginal improvement of the fit, lack of consistency among different data sets, and difficulty in uniquely specifying the nature of the tertiary component. Results . With the observables of the event, it is estimated that the masses of the planet and host are ∼(6.9 M ⊕ , 0.75 M ⊙ ) according to one solution and ∼(2.8 M ⊕ , 0.80 M ⊙ ) according to the other, indicating that the planet is a super Earth around a K-type star, regardless of the solution. The fact that 16 (including the one reported in this work) out of 19 microlensing planets with M ≲ 10 M ⊕ were detected during the last 6 yr nicely demonstrates the importance of high-cadence global surveys in detecting very low-mass planets.

gravitational lensing↗

Exponential Escape Rate of Filamentary Incubation in Mott Spiking Neurons

Mott materials such as vanadium oxides, when subject to a strong applied voltage, present an inhomogeneous insulator-to-metal transition with formation of metallic filaments within the insulating bulk. This property is enabling the development of compact and power-efficient neuromorphic devices known as Mott neurons. However, the nature of the transition has not been fully understood yet, as it may be attributed to different effects, including Joule self-heating and hot-carrier injection. Moreover, the experimental determination of the threshold voltage needed to induce the transition has proven to be challenging, as the transition becomes increasingly unpredictable when the threshold is approached. The physical understanding of these issues would not only deepen our understanding of Mott insulators, but would also be an important step toward the realization of neuromorphic devices based on such materials. In this work we use numerical simulations based on the Mott resistor network model to study the nature of the filament incubation and formation process. Here, we show that both electronic and thermal effects, in the form of current density focusing and Joule self-heating, respectively, contribute to the filamentary incubation and growth. Remarkably, we find that the percolation of the metallic filaments near the threshold is intrinsically stochastic, qualitatively similar to the familiar Arrhenius activated behavior and to the stochastic firing of biological neurons. More precisely, we characterize the filament percolation as a Poisson point process, which has the same probability distribution as mathematical models of neuronal firing with an exponential escape rate. Finally, we support the numerical simulation results by performing experiments in VO 2 that are in agreement with the exponential escape rate behavior. Thus, we establish a functionality of Mott insulators that opens a path toward implementing neuromorphic hardware with quantum materials.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

An Introduction to Word Embeddings and Language Models

Language models have advanced at a phenomenal pace over the past decade. This document provides a short introduction to terminology, word embeddings (aka low-dimensional representations), and popular large-scale language models (LMs). Word embeddings are used to represent words as numerical vectors and are context-independent, meaning a word can only have a single representation (e.g., club can only be club sandwich, not golf club ). Language models can determine the probability of a given sequence of words occurring in a sentence and can provide context to distinguish between words and phrases that sound similar. LMs are context-dependent (e.g., club can be club sandwich or golf club ) and largely fall in two main classes – autoregressive and autoencoding models. Autoregressive models are pretrained on the classic language modeling task: guess the next token having read all the previous ones. Those models can be fine-tuned and achieve great results on many tasks, the most natural application is text generation. A typical example of such models is GPT, but others include GPT-2, GPT-3, CTLR, TRANSFORMER-XL, REFORMER, XLNET. Autoencoding models are pretrained by corrupting the input tokens in some way and trying to reconstruct the original sentence. They can be fine-tuned and achieve great results on many tasks such as text generation, but their most natural application is sentence classification or token classification. A typical example of such models is BERT, but others include ROBERTA, ALBERT, XML, XML-ROBERTA, FLAUBERT AND LONGFORMER.

97 MATHEMATICS AND COMPUTING↗