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A standard problem in gamma-ray astronomy data analysis is the decomposition of a set of observed counts, described by Poisson statistics, according to a given multi-component linear model, with underlying physical count rates or fluxes which are to be estimated from the data.
A general theory for retrieving the fraction of ground flashes in N lightning observed by a satellite-based lightning imager is provided. An "exponential model" is applied as a physically reasonable constraint to describe the measured optical parameter distributions, and population statistics (i.e., mean, variance) are invoked to add additional constraints to the retrieval process. The retrieval itself is expressed in terms of a Bayesian inference, and the Maximum A Posteriori (MAP) solution is obtained. The approach is tested by performing simulated retrievals, and retrieval error statistics are provided. The ability to retrieve ground flash fraction has important benefits to the atmospheric chemistry community. For example, using the method to partition the existing satellite global lightning climatology into separate ground and cloud flash climatologies will improve estimates of lightning nitrogen oxides (NOx) production; this in turn will improve both regional air quality and global chemistry/climate model predictions.
A Bayesian inversion method is introduced for retrieving the fraction of ground flashes in a set of N lightning observed by a satellite lightning imager (such as the Geostationary Lightning Mapper, GLM). An exponential model is applied as a physically reasonable constraint to describe the measured lightning optical parameter distributions. Population statistics (i.e., the mean and variance) are invoked to add additional constraints to the retrieval process. The Maximum A Posteriori (MAP) solution is employed. The approach is tested by performing simulated retrievals, and retrieval error statistics are provided. The approach is feasible for N greater than 2000, and retrieval errors decrease as N is increased.
Improved estimates of near-surface air temperature and air humidity are critical to the development of more accurate turbulent surface heat fluxes over the ocean. Recent progress in retrieving these parameters has been made through the application of artificial neural networks (ANN) and the use of multi-sensor passive microwave observations. Details are provided on the development of an improved retrieval algorithm that applies the nonlinear statistical ANN methodology to a set of observations from the Advanced Microwave Scanning Radiometer (AMSR-E) and the Advanced Microwave Sounding Unit (AMSU-A) that are currently available from the NASA AQUA satellite platform. Statistical inversion techniques require an adequate training dataset to properly capture embedded physical relationships. The development of multiple training datasets containing only in-situ observations, only synthetic observations produced using the Community Radiative Transfer Model (CRTM), or a mixture of each is discussed. An intercomparison of results using each training dataset is provided to highlight the relative advantages and disadvantages of each methodology. Particular emphasis will be placed on the development of retrievals in cloudy versus clear-sky conditions. Near-surface air temperature and humidity retrievals using the multi-sensor ANN algorithms are compared to previous linear and non-linear retrieval schemes.
The satellite-borne PAMELA experiment has been continuously collecting data since 2006.This apparatus is designed to study charged particles in the cosmic radiation. The combination of a permanent magnet, a silicon strip tracker and a silicon-tungsten imaging calorimeter, and the redundancy of instrumentation allow very precise studies on the physics of cosmic rays in a wide energy range and with high statistics. This makes PAMELA a very suitable instrument for Solar Energetic Particle (SEP) observations. Not only does its pan the energy range between the ground-based neutron monitor data and the observations of SEPs from space,but PAMELA also carries out the first direct measurements of the composition for the highest energy SEP events, including those causing Ground Level Enhancements (GLEs).In particular, PAMELA has registered many SEP events during solar cycle 24,offering unique opportunities to address the question of high-energy SEP origin. A preliminary analysis on proton spectra behaviour during this event is presented in this work.
Contemporary approaches to aerospace vehicle system monitoring rely heavily on thresholds that represent a compromise between providing warning early enough to avert a mishap while simultaneously minimizing false alarms. While this reliance on thresholds has been in place for decades and has permeated both cockpits and control rooms, we often find it insufficient when retrospectively analyzing data from an accident. To modernize and enhance flight test safety, we introduce new methods of monitoring for anomalous patterns of interaction rather than for thresholds exceedance. For systems with a well characterized baseline we show how the Inductive Monitoring System (IMS), utilized by NASA in the aftermath of the Columbia accident, might be implemented in real-time to provide earlier warning than currently employed techniques. For systems without such a baseline, we introduce new developments in statistical methods relating to critical slowing down, first applied in medicine and physics, which show promise for adaptation to flight test. Finally, the familiar resource constrained environment leads to a reliance on increased instrumentation that is challenging the limits of the current one-sensor, one-indicator threshold paradigm. Existing methods thus fail to accurately reflect the true complexity of a vehicle rich with interdependent interacting systems. We highlight these concepts in a brief summary of the 2001 Air Transat Flight 236 deadstick landing in the Azores. We then suggest control room and cockpit modifications to better display the information gleaned using these novel monitoring methods.
Contemporary approaches to aerospace vehicle system monitoring rely heavily on thresholds that represent a compromise between providing warning early enough to avert a mishap while simultaneously minimizing false alarms. While this reliance on thresholds has been in place for decades and has permeated both cockpits and control rooms, we often find it insufficient when retrospectively analyzing data from an accident. To modernize and enhance flight test safety, we introduce new methods of monitoring for anomalous patterns of interaction rather than for thresholds exceedance. For systems with a well characterized baseline we show how the Inductive Monitoring System (IMS), utilized by NASA in the aftermath of the Columbia accident, might be implemented in real-time to provide earlier warning than currently employed techniques. For systems without such a baseline, we introduce new developments in statistical methods relating to critical slowing down, first applied in medicine and physics, which show promise for adaptation to flight test. Finally, the familiar resource constrained environment leads to a reliance on increased instrumentation that is challenging the limits of the current "one-sensor, one-indicator" threshold paradigm. Existing methods thus fail to accurately reflect the true complexity of a vehicle rich with interdependent interacting systems. We highlight these concepts in a brief summary of the 2001 Air Transat Flight 236 deadstick landing in the Azores. We then suggest control room and cockpit modifications to better display the information gleaned using these novel monitoring methods.
Southern Africa produces almost a third of the Earth’s biomass burning (BB) aerosol particles, yet the fate of these particles and their influence on regional and global climate is poorly understood. ORACLES (ObseRvations of Aerosols above CLouds and their intEractionS) is a 5-year NASA EVS-2 (Earth Venture Suborbital-2) investigation with three intensive observation periods designed to study key atmospheric processes that determine the climate impacts of these aerosols. During the Southern Hemisphere winter and spring (June–October), aerosol particles reaching 3–5 km in altitude are transported westward over the southeast Atlantic, where they interact with one of the largest subtropical stratocumulus (Sc) cloud decks in the world. The representation of these interactions in climate models remains highly uncertain in part due to a scarcity of observational constraints on aerosol and cloud properties, as well as due to the parameterized treatment of physical processes. Three ORACLES deployments by the NASA P-3 aircraft in September 2016, August 2017, and October 2018 (totaling ~ 350 science flight hours), augmented by the deployment of the NASA ER-2 aircraft for remote sensing in September 2016 (totaling ~ 100 science flight hours), were intended to help fill this observational gap. ORACLES focuses on three fundamental science themes centered on the climate effects of African BB aerosols: (a) direct aerosol radiative effects, (b) effects of aerosol absorption on atmospheric circulation and clouds, and (c) aerosol–cloud microphysical interactions. This paper summarizes the ORACLES science objectives, describes the project implementation, provides an overview of the flights and measurements in each deployment, and highlights the integrative modeling efforts from cloud to global scales to address science objectives. Significant new findings on the vertical structure of BB aerosol physical and chemical properties, chemical aging, cloud condensation nuclei, rain and precipitation statistics, and aerosol indirect effects are emphasized, but their detailed descriptions are the subject of separate publications. The main purpose of this paper is to familiarize the broader scientific community with the ORACLES project and the dataset it produced.
Solar Energetic Particle (SEP) events are interesting from a scientific perspective as they are the product of a broad set of physical processes from the corona out through the extent of the heliosphere, and provide insight into processes of particle acceleration and transport that are widely applicable in astrophysics. From the operations perspective, SEP events pose a radiation hazard for aviation, electronics in space, and human space exploration, in particular for missions outside of the Earth’s protective magnetosphere including to the Moon and Mars (Whitman et al 2022). For these reasons, SEP modelers have developed a rich and diverse set of models with a wide variety of aims. Some models probe the basic physics at the heart of particle acceleration and transport. Others produce fast statistical forecasts or employ disruptive new techniques like Machine Learning with the goal to assist end users in making operational decisions. To enable a consistent and quantitative understanding of SEP model performance, a generalized, automated validation infrastructure, called SPHINX, is being developed at NASA SRAG in close collaboration with NASA CCMC, NASA M2M, NOAA SWPC, and BIRA-IASB. This infrastructure has been built up through a multi-year community challenge. Starting in 2018 at the SHINE workshop, an effort was launched through SHINE, ISWAT, and ESWW to encourage quantitative, comprehensive, and consistent validation of SEP models. This effort has defined a set of challenge SEP events with the aim of generating quantitative comparisons between forecasts and observations and a set of challenge “non-events” to assess false alarms. In 2023, these challenge lists have been extended to statistically significant numbers with a prescribed set of rules for producing forecasts and supported through the dedicated SEPVAL working meetings. The participation of the research community has allowed the infrastructure to validate all the types of outputs being produced by SEP models. In parallel, the SPHINX code is being applied to real time forecasts submitted to the SEP Scoreboards, ensuring that the validation infrastructure can interpret forecasts produced in an operational scenario and provide metrics meaningful for operations. Upon completion, SPHINX and its interactive user interface, SPHINX-Web, will be made available for public use.
Algorithmic art selected as a winner of the contest Pixel by Pixel: The Art of CHANCE, to be published in the April 2024 issue of CHANCE, the magazine of the American Statistical Association.
We compute the complex, long-distance two-photon-exchange amplitude which contributes to the rare 𝐾 L → 𝜇 + 𝜇 − decay from lattice QCD. We use a 24 3 × 64 physical-pion-mass gauge field ensemble at an inverse lattice spacing of 1.023 GeV and a QED ∞ -based formalism. Our implementation strategies for all five non-SU(3)-flavor-suppressed diagram topologies are given in detail. We achieve a 25% statistical precision on the dispersive part of this long-distance amplitude. This calculation is carried out with 2+1 quark flavors and therefore requires the addition of counterterms to compensate for the absence of the Glashow-Iliopoulos-Maiani mechanism. These counterterms are not included in the current calculation and will be the subject of a second paper. Although a direct comparison to experiment cannot yet be made because of those omitted counterterms, the present exploratory calculation allows one to identify principal sources of statistical uncertainty in this calculation. The precision of our results is limited by the reconstruction of the physical contribution of the 𝜂 intermediate state, for which various strategies are tested and compared.
An analysis is put forth that relates explosive properties including microstructure, temperature, and chemistry to explosive ignition and sensitivity. Unlike approaches that focus only on elucidating mesoscopic mechanisms important to ignition, the present analysis seeks a methodology directly applicable to continuum explosive burn models. Because the Scaled Uniform Reactive Front (SURF) burn model has a microstructural basis, it is chosen as the starting point of the present analysis. To build upon the SURF framework, a literal translation is performed of the high-level conceptual notions for which SURF is based, to concrete ignition–combustion parameters, a statistical description of the microstructure, and other thermo-chemical data acquired by non-shock experiments. The analysis requires a void volume fraction distribution acquired from ultra-small angle neutron scattering (USANS). The shock response of PBX 9502 is used to illustrate the theory. While the analysis requires calibration to a shock experiment (the pop plot, for example), the results are a self-consistent set of realistic physical quantities that contribute to the shock initiation process including, initial temperature, chemical kinetics, a statistical description of the microstructure, and the hot spot size, spacing, and temperature. The utility of having a mesoscale based theory is that once the critical hot spot temperature, as a function of shock pressure, is known for a given explosive and initial porosity distribution, the entire set of meso- and macro-scale results, including the pop plot can be calculated for any other porosity. Thus, one can understand changes in sensitivity at different densities (void size distributions), relying only on the assumption that the hot spot temperature curve would not differ significantly if the morphology of the hots spots were similar. Another important utility of the present analysis is to address the question of the role of initial temperature on the observed shock sensitivity of PBX 9502 and other explosives.
Dark matter is one of the remaining great mysteries of modern physics. Cosmological and astrophysical evidence hints strongly at a new particle, or set of particles, unknown to the Standard Model, comprising some 80% of all of the matter in the universe. SuperCDMS is one of the world-leading direct-detection experiments attempting to directly measure interactions between dark and regular matter. SuperCDMS uses solid state crystalline detectors in a nearly-zero background environment to attempt to measure the particle properties of dark matter. The detectors themselves, however, are quite complex; and a very detailed understanding of the microscopic physics is helpful in analyzing the very rare events that occur within them. Furthermore, better understanding and modeling of the detectors can aid in the design and optimization of future iterations of the experiment. The SuperCDMS detectors are well-understood in ideal cases. However, an accurate understanding of the detector response to outlier events or under non-ideal conditions is important for a low-statistics experiment. This work describes the design and implementation of a low temperature condensed matter physics simulation library built on top of the popular Geant4 particle tracking framework. The library, named \Geant4 Condensed Matter Physics" or G4CMP, introduces several solid state concepts to the Geant4 framework such as crystal lattices, phonon quasiparticles, non-scalar elective masses, and implements several physics processes relevant to cryogenic temperature crystals. In addition to the physics library, which is intended for general use, this work also describes a full Monte Carlo simulation package for the SuperCDMS iZIP detectors which utilizes G4CMP at its core and also fully simulates the detector readout sensors. The document will begin with the canonical motivations for the cold dark matter hypothesis, followed by a description of the SuperCDMS experiment. It will then describe the microscopic physics inside of the SuperCDMS detectors, as well as details on their implementation in G4CMP. The full detector simulation with corresponding sensor readout will follow, along with plans for future work; including both scientific studies and improvements, as well as computational improvements and added efficiencies.
In this study, we use the inchworm quantum Monte Carlo method to investigate the full counting statistics of particle and energy currents in a strongly correlated quantum dot. Our method is used to extract the heat fluctuations and entropy production of a quantum thermoelectric device, as well as cumulants of the particle and energy currents. The energy-particle current cross correlations reveal information on the preparation of the system and the interplay of thermal and electric currents. Finally, we demonstrate the signature of a crossover from Coulomb blockade to Kondo physics in the energy current fluctuations, and show how the conventional master equation approach to full counting statistics systematically fails to capture this crossover.
To address the statistics of binary stars in the 8 Myr old Upper Scorpius (USco) star formation region, we conducted a speckle interferometric survey of 614 association members more massive than 0.4 M{sub ⊙} (spectral types earlier than M3V) based on the list of Luhman et al. (2018). We resolved 187 pairs, 55 of which are new discoveries. Also using the published data and the Gaia DR2, a catalog of 250 physical binaries was produced. We carefully estimated detection limits for each target and studied binary statistics in the separation range from 0.″06 to 20″ (9–2800 au), as well as clustering at larger separations. The frequency of companions with mass ratios q > 0.3 in this separation range is 0.33 ± 0.04 and 0.35 ± 0.04 for early M- and solar-type stars, respectively, larger by 1.62 ± 0.22 and 1.39 ± 0.18 times compared to field stars of similar masses. The excess is produced mostly by pairs closer than 100 au. At separations from 100 to 10{sup 4} au, the separation distribution and companion fraction resemble those of solar-type stars in the field. However, unlike in the field, we see a relative deficit of equal-mass binaries at separations of ∼500 au, compared to smaller and larger separations. The distribution of q depends on the separation, with a preference of larger q and a larger fraction of twins with q > 0.95 at smaller separations. The binary population of USco differs from binaries in the field in several ways and suggests that binary statistics is not universal.
Halide perovskites form the foundation of an emerging class of materials for broad application in renewable and sustainable applications, including photocatalysis and solar energy harvesting. These materials exhibit beneficial photophysical properties, including bandgaps suitable for solar energy harvesting and efficient charge screening that underlies efficient charge carrier separation and resistance to defects. For organic–inorganic hybrid perovskites, these benefits are thought to arise, in part, from dipolar molecular cations that can reorient in response to charged particles and defects. In this work, we provide a similar perspective for inorganic metal halide perovskites, which do not contain molecular species with permanent dipoles. We discuss how lone pair electrons lead to dipolar ions that exhibit dynamics in analogy with traditional molecular plastic crystals and hybrid perovskites. We argue that further understanding these electronic plastic crystal motions with first principles simulations and synchrotron scattering can help create a basic understanding of photophysical properties of metal halide perovskites and inform the design of advanced functional materials.
Historically, extreme waves have been the most destructive force in the Gulf of Mexico, destroying and damaging thousands of offshore structures. The American Petroleum Institute has revised its design criteria for offshore platforms several times over the decades, as new data continues to become available, showing that data for our present climate is insufficient. This problem is exacerbated in a changing climate. By using synthetic physics-based tropical cyclones to force a third-generation wave model, we can generate adequate statistics for present and future climates. These simulations have been completed using Joule Supercomputer.
We investigate the number of physical companion galaxies for a sample of relatively isolated elliptical galaxies. The NASA/IPAC Extragalactic Database (NED) has been usedto reinvestigate the incidence of satellite galaxies for a sample of 34 elliptical galaxies, firstinvestigated by Bothun & Sullivan (1977) using a visual inspection of Palomar Sky Survey prints out to a projected search radius of 75 kpc. We have repeated their original investigation usingdata cataloged data in NED. Nine of these ellipticals appear to be members of galaxy clusters:the remaining sample of 25 galaxies reveals an average of +1.0 f 0.5 apparent companions per galaxy within a projected search radius of 75 kpc, in excess of two equal-area comparisonregions displaced by 150-300 kpc. This is nearly an order of magnitude larger than the +0.12+/- 0.42 companions/galaxy found by Bothun & Sullivan for the identical sample. Making use of published radial velocities, mostly available since the completion of the Bothun-Sullivan study,identifies the physical companions and gives a somewhat lower estimate of +0.4 companions per elliptical. This is still a factor of 3x larger than the original statistical study, but giventhe incomplete and heterogeneous nature of the survey redshifts in NED, it still yields a firmlower limit on the number (and identity) of physical companions. An expansion of the searchradius out to 300 kpc, again restricted to sampling only those objects with known redshifts in NED, gives another lower limit of 4.3 physical companions per galaxy. (Excluding fiveelliptical galaxies in the Fornax cluster this average drops to 3.5 companions per elliptical.)These physical companions are individually identified and listed, and the ensemble-averagedradial density distribution of these associated galaxies is presented. For the ensemble, the radial density distribution is found to have a fall-off consistent with p c( R^-0.5 out to approximately150 kpc. For non-Fornax cluster companions the fall-off continues out to the 300-kpc limit of thesurvey. The velocity dispersion of these companions is found to be constant with projected radial distance from the central elliptical, holding at a value of approximately +/- 300-350 km/sec overall.