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At least 523 records · Page 29

Maximum Likelihood Estimation of the Broken Power Law Spectral Parameters with Detector Design Applications

The method of Maximum Likelihood (ML) is used to estimate the spectral parameters of an assumed broken power law energy spectrum from simulated detector responses. This methodology, which requires the complete specificity of all cosmic-ray detector design parameters, is shown to provide approximately unbiased, minimum variance, and normally distributed spectra information for events detected by an instrument having a wide range of commonly used detector response functions. The ML procedure, coupled with the simulated performance of a proposed space-based detector and its planned life cycle, has proved to be of significant value in the design phase of a new science instrument. The procedure helped make important trade studies in design parameters as a function of the science objectives, which is particularly important for space-based detectors where physical parameters, such as dimension and weight, impose rigorous practical limits to the design envelope. This ML methodology is then generalized to estimate broken power law spectral parameters from real cosmic-ray data sets.

Howell, Leonard W.↗

Singly and doubly oxidized carbenes and their applications in catalysis

Over the last three decades, the highly tunable properties of N-heterocyclic carbenes (NHCs) and other stable singlet carbenes have led to a variety of applications. This perspective shows a novel facet of carbenes—i.e., their reductive properties—that allows them to function as catalysts in single-electron transfer (SET) reactions. The isolation and even the spectroscopic characterization of a singly oxidized carbene have yet to be done, but these species readily abstract hydrogen atoms while giving back the carbene conjugate acid, which behaves as the resting state of catalytic cycles. In sharp contrast, a doubly oxidized carbene has been isolated, and there is a strong likelihood that many other carbene dications will be isolated. Their first Lewis acidity is very high, suggesting possible applications in Lewis acid catalysis.

dication↗

Characterizing a supernova’s standing accretion shock instability with neutrinos and gravitational waves

Here, we perform a novel multi-messenger analysis for the identification and parameter estimation of the Standing Accretion Shock Instability (SASI) in a core collapse supernova with neutrino and gravitational wave (GW) signals. In the neutrino channel, this method performs a likelihood ratio test for the presence of SASI in the frequency domain. For gravitational wave signals we process an event with a modified constrained likelihood method. Using simulated supernova signals, the properties of the Hyper-Kamiokande neutrino detector, and O3 LIGO Interferometric data, we produce the two-dimensional probability density distribution (PDF) of the SASI activity indicator and calculate the probability of detection P D as well as the false identification probability P FI . We discuss the probability to establish the presence of the SASI as a function of the source distance in each observational channel, as well as jointly. Compared to a single-messenger approach, the joint analysis results in P D (at P FI = 0.1) of SASI activities that is larger by up to ≈ 40% for a distance to the supernova of 5 kpc. We also discuss how accurately the frequency and duration of the SASI activity can be estimated in each channel separately. Our methodology is suitable for implementation in a realistic data analysis and a multi-messenger setting.

79 ASTRONOMY AND ASTROPHYSICS↗

Control/display trade-off study for single-pilot instrument flight rule operations

The objectives were to determine minimum autopilot functions and displays required to keep pilot workload at an acceptable level; to determine what constitutes an acceptable level of workload; to identify critical tasks; and to suggest specific experiments required to refine conclusions. It was determined that workload relief is derived from basic stability augmentation; that complex autopilots can lead to serious blunders; and that displays need to enhance positional awareness and minimize the likelihood of false hypothesis.

Hoh, R.↗

Results and Analysis from Space Suit Joint Torque Testing

A space suit s mobility is critical to an astronaut s ability to perform work efficiently. As mobility increases, the astronaut can perform tasks for longer durations with less fatigue. The term mobility, with respect to space suits, is defined in terms of two key components: joint range of motion and joint torque. Individually these measures describe the path which in which a joint travels and the force required to move it through that path. Previous space suits mobility requirements were defined as the collective result of these two measures and verified by the completion of discrete functional tasks. While a valid way to impose mobility requirements, such a method does necessitate a solid understanding of the operational scenarios in which the final suit will be performing. Because the Constellation space suit system requirements are being finalized with a relatively immature concept of operations, the Space Suit Element team elected to define mobility in terms of its constituent parts to increase the likelihood that the future pressure garment will be mobile enough to enable a broad scope of undefined exploration activities. The range of motion requirements were defined by measuring the ranges of motion test subjects achieved while performing a series of joint maximizing tasks in a variety of flight and prototype space suits. The definition of joint torque requirements has proved more elusive. NASA evaluated several different approaches to the problem before deciding to generate requirements based on unmanned joint torque evaluations of six different space suit configurations being articulated through 16 separate joint movements. This paper discusses the experiment design, data analysis and results, and the process used to determine the final values for the Constellation pressure garment joint torque requirements.

Matty, Jennifer E.↗

Interactions of Mean Climate Change and Climate Variability on Food Security Extremes

Recognizing that climate change will affect agricultural systems both through mean changes and through shifts in climate variability and associated extreme events, we present preliminary analyses of climate impacts from a network of 1137 crop modeling sites contributed to the AgMIP Coordinated Climate-Crop Modeling Project (C3MP). At each site sensitivity tests were run according to a common protocol, which enables the fitting of crop model emulators across a range of carbon dioxide, temperature, and water (CTW) changes. C3MP can elucidate several aspects of these changes and quantify crop responses across a wide diversity of farming systems. Here we test the hypothesis that climate change and variability interact in three main ways. First, mean climate changes can affect yields across an entire time period. Second, extreme events (when they do occur) may be more sensitive to climate changes than a year with normal climate. Third, mean climate changes can alter the likelihood of climate extremes, leading to more frequent seasons with anomalies outside of the expected conditions for which management was designed. In this way, shifts in climate variability can result in an increase or reduction of mean yield, as extreme climate events tend to have lower yield than years with normal climate.C3MP maize simulations across 126 farms reveal a clear indication and quantification (as response functions) of mean climate impacts on mean yield and clearly show that mean climate changes will directly affect the variability of yield. Yield reductions from increased climate variability are not as clear as crop models tend to be less sensitive to dangers on the cool and wet extremes of climate variability, likely underestimating losses from water-logging, floods, and frosts.

Variability↗

The DESI-Lensing Mock Challenge: large-scale cosmological analysis of 3x2-pt statistics

The current generation of large galaxy surveys will test the cosmological model by combining multiple types of observational probes. Realising the statistical promise of these new datasets requires rigorous attention to all aspects of analysis including cosmological measurements, modelling, covariance and parameter likelihood. In this paper we present the results of an end-to-end simulation study designed to test the analysis pipeline for the combination of the Dark Energy Spectroscopic Instrument (DESI) Year 1 galaxy redshift dataset and separate weak gravitational lensing information from the Kilo-Degree Survey, Dark Energy Survey and Hyper-Suprime-Cam Survey. Our analysis employs the 3x2-pt correlation functions including cosmic shear and galaxy-galaxy lensing, together with the projected correlation function of the spectroscopic DESI lenses. We build realistic simulations of these datasets including galaxy halo occupation distributions, photometric redshift errors, weights, multiplicative shear calibration biases and magnification. We calculate the analytical covariance of these correlation functions including the Gaussian, noise and super-sample contributions, and show that our covariance determination agrees with estimates based on the ensemble of simulations. We use a Bayesian inference platform to demonstrate that we can recover the fiducial cosmological parameters of the simulation within the statistical error margin of the experiment, investigating the sensitivity to scale cuts. This study is the first in a sequence of papers in which we present and validate the large-scale 3x2-pt cosmological analysis of DESI-Y1.

79 ASTRONOMY AND ASTROPHYSICS↗

Disaggregating Customer-Level Behind-the-Meter PV Generation Using Smart Meter Data and Solar Exemplars

Customer-level rooftop photovoltaic (PV) has been widely integrated into distribution systems. In most cases, PVs are installed behind-the-meter (BTM), and only the net demand is recorded. Therefore, the native demand and PV generation are unknown to utilities. Separating native demand and solar generation from net demand is critical for improving grid-edge observability. In this paper, a novel approach is proposed for disaggregating customer-level BTM PV generation using low-resolution but widely available hourly smart meter data. The proposed approach exploits the strong correlation between monthly nocturnal and diurnal native demands and the high similarity among PV generation profiles. First, a joint probability density function (PDF) of monthly nocturnal and diurnal native demands is constructed for customers without PVs, using Gaussian mixture modeling (GMM). Deviation from the constructed PDF is utilized to probabilistically assess the monthly solar generation of customers with PVs. Then, to identify hourly BTM solar generation for these customers, their estimated monthly solar generation is decomposed into an hourly timescale; to do this, we have proposed a maximum likelihood estimation (MLE)-based technique that utilizes hourly typical solar exemplars. Leveraging the strong monthly native demand correlation and high PV generation similarity enhances our approach's robustness against the volatility of customers’ hourly load and enables highly-accurate disaggregation. Furthermore, the proposed approach has been verified using real native demand and PV generation data.

14 SOLAR ENERGY↗

Estimation of parameters in linear structural relationships Sensitivity to the choice of the ratio of error variances

Maximum likelihood estimation of parameters in linear structural relationships under normality assumptions requires knowledge of one or more of the model parameters if no replication is available. The most common assumption added to the model definition is that the ratio of the error variances of the response and predictor variates is known. This paper investigates the use of asymptotic formulae for variances and mean squared errors as a function of sample size and the assumed value for the error variance ratio.

Lakshminarayanan, M. Y.↗

The Containment Assurance Risk Framework of the Mars Sample Return Program

The Mars Sample Return campaign aims at bringing rock and atmospheric samples from Mars to Earth through a series of robotic missions. These missions would collect the samples being cached and deposited on Martian soil by the Perseverance rover, place them in a container, and launch them into Martian orbit for subsequent capture by an orbiter that would bring them back. Given there exists a non-zero probability that the samples contain biological material, precautions are being taken to design systems that would break the chain of contact between Mars and Earth. These include techniques such as sterilization of Martian particles, redundant containment vessels, and a robust reentry capsule capable of accurate landings without a parachute. Requirements exist that the probability of containment not assured of Martian-contaminated material into Earth’s biosphere be less than one in a million. To demonstrate compliance with this strict requirement, a statistical framework was developed to assess the likelihood of containment loss during each sample return phase and make a statement about the total combined mission probability of containment not assured. The work presented here describes this framework, which considers failure modes or fault conditions that can initiate failure sequences ultimately leading to containment not assured. Reliability estimates are generated from databases, design heritage, component specifications, or expert opinion in the form of probability density functions or point estimates and provided as inputs to the mathematical models that simulate the different failure sequences. The probabilistic outputs are then combined following the logic of several fault trees to compute the ultimate probability of containment not assured. Given the multidisciplinary nature of the problem and the different types of mathematical models used, the statistical tools needed for analysis are required to be computationally efficient. While standard Monte Carlo approaches are used for fast models, a multi-fidelity approach to rare event probabilities is proposed for expensive models. In this paradigm, inexpensive low-fidelity models are developed for computational acceleration purposes while the expensive high-fidelity model is kept in the loop to retain accuracy in the results. This work presents an example of end-to-end application of this framework highlighting the computational benefits of a multi-fidelity approach.

Giuseppe Cataldo↗

AutoClass: A Bayesian Approach to Classification

We describe a Bayesian approach to the untutored discovery of classes in a set of cases, sometimes called finite mixture separation or clustering. The main difference between clustering and our approach is that we search for the "best" set of class descriptions rather than grouping the cases themselves. We describe our classes in terms of a probability distribution or density function, and the locally maximal posterior probability valued function parameters. We rate our classifications with an approximate joint probability of the data and functional form, marginalizing over the parameters. Approximation is necessitated by the computational complexity of the joint probability. Thus, we marginalize w.r.t. local maxima in the parameter space. We discuss the rationale behind our approach to classification. We give the mathematical development for the basic mixture model and describe the approximations needed for computational tractability. We instantiate the basic model with the discrete Dirichlet distribution and multivariant Gaussian density likelihoods. Then we show some results for both constructed and actual data.

Stutz, John↗

Estimating Cosmological Constraints from Galaxy Cluster Abundance using Simulation-Based Inference

Inferring the values and uncertainties of cosmological parameters in a cosmology model is of paramount importance for modern cosmic observations. In this paper, we use the simulation-based inference (SBI) approach to estimate cosmological constraints from a simplified galaxy cluster observation analysis. Using data generated from the Quijote simulation suite and analytical models, we train a machine learning algorithm to learn the probability function between cosmological parameters and the possible galaxy cluster observables. The posterior distribution of the cosmological parameters at a given observation is then obtained by sampling the predictions from the trained algorithm. Our results show that the SBI method can successfully recover the truth values of the cosmological parameters within the 2σ limit for this simplified galaxy cluster analysis, and acquires similar posterior constraints obtained with a likelihood-based Markov Chain Monte Carlo method, the current state-of the-art method used in similar cosmological studies.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Data Format Classification for Autonomous Software Defined Radios

We present maximum-likelihood (ML) coherent and noncoherent classifiers for discriminating between NRZ and Manchester coded (biphase-L) data formats for binary phase-shift-keying (BPSK) modulation. Such classification of the data format is an essential element of so-called autonomous software defined radio (SDR) receivers (similar to so-called cognitive SDR receivers in the military application) where it is desired that the receiver perform each of its functions by extracting the appropriate knowledge from the received signal and, if possible, with as little information of the other signal parameters as possible. Small and large SNR approximations to the ML classifiers are also proposed that lead to simpler implementation with comparable performance in their respective SNR regions. Numerical performance results obtained by a combination of computer simulation and, wherever possible, theoretical analyses, are presented and comparisons are made among the various configurations based on the probability of misclassification as a performance criterion. Extensions to other modulations such as QPSK are readily accomplished using the same methods described in the paper.

classification↗

Dark Energy Survey Year 3 Results: Cosmological constraints from second- and third-order shear statistics

Here, we present a cosmological analysis of the third-order aperture mass statistic using Dark Energy Survey Year 3 (DES Y3) data. We perform a complete tomographic measurement of the three-point correlation function of the Y3 weak lensing shape catalog with the four fiducial source redshift bins. Building upon our companion methodology paper, we apply a pipeline that combines the two-point function ξ ± with the mass aperture skewness statistic ⟨ M ap 3 ⟩ , which is an efficient compression of the full shear three-point function. We use a suite of simulated shear maps to obtain a joint covariance matrix. By jointly analyzing ξ ± and ⟨ M ap 3 ⟩ measured from DES Y3 data with a Λ CDM model, we find S 8 = 0.780 ± 0.015 and Ω m = 0.26 6 - 0.040 + 0.039 , yielding 111% of figure-of-merit improvement in the Ω m - S 8 plane relative to ξ ± alone, consistent with expectations from simulated likelihood analyses. With a w CDM model, we find S 8 = 0.74 9 - 0.026 + 0.027 and w 0 = - 1.39 ± 0.31 , which gives an improvement of 22% on the joint S 8 - w 0 constraint. Our results are consistent with w 0 = - 1 . Our new constraints are compared to CMB data from the Planck satellite, and we find that with the inclusion of ⟨ M ap 3 ⟩ the existing tension between the datasets is at the level of 2.3 σ . We show that the third-order statistic enables us to self-calibrate the mean photometric redshift uncertainty parameter of the highest redshift bin with little degradation in the figure of merit. Our results demonstrate the constraining power of higher-order lensing statistics and establish ⟨ M ap 3 ⟩ as a practical observable for joint analyses in current and future surveys.

Gomes, R. C. H. [University of Pennsylvania] (ORCI↗

Asynchronous Message Service Reference Implementation

This software provides a library of middleware functions with a simple application programming interface, enabling implementation of distributed applications in conformance with the CCSDS AMS (Consultative Committee for Space Data Systems Asynchronous Message Service) specification. The AMS service, and its protocols, implement an architectural concept under which the modules of mission systems may be designed as if they were to operate in isolation, each one producing and consuming mission information without explicit awareness of which other modules are currently operating. Communication relationships among such modules are self-configuring; this tends to minimize complexity in the development and operations of modular data systems. A system built on this model is a society of generally autonomous, inter-operating modules that may fluctuate freely over time in response to changing mission objectives, modules functional upgrades, and recovery from individual module failure. The purpose of AMS, then, is to reduce mission cost and risk by providing standard, reusable infrastructure for the exchange of information among data system modules in a manner that is simple to use, highly automated, flexible, robust, scalable, and efficient. The implementation is designed to spawn multiple threads of AMS functionality under the control of an AMS application program. These threads enable all members of an AMS-based, distributed application to discover one another in real time, subscribe to messages on specific topics, and to publish messages on specific topics. The query/reply (client/server) communication model is also supported. Message exchange is optionally subject to encryption (to support confidentiality) and authorization. Fault tolerance measures in the discovery protocol minimize the likelihood of overall application failure due to any single operational error anywhere in the system. The multi-threaded design simplifies processing while enabling application nodes to operate at high speeds; linked lists protected by mutex semaphores and condition variables are used for efficient, inter-thread communication. Applications may use a variety of transport protocols underlying AMS itself, including TCP (Transmission Control Protocol), UDP (User Datagram Protocol), and message queues.

Burleigh, Scott C.↗

Modeling the Redshift Evolution of the Normal Galaxy X-Ray Luminosity Function

Emission from X-ray binaries (XRBs) is a major component of the total X-ray luminosity of normal galaxies, so X-ray studies of high-redshift galaxies allow us to probe the formation and evolution of XRBs on very long timescales (approximately 10 Gyr). In this paper, we present results from large-scale population synthesis models of binary populations in galaxies from z = 0 to approximately 20. We use as input into our modeling the Millennium II Cosmological Simulation and the updated semi-analytic galaxy catalog by Guo et al. to self-consistently account for the star formation history (SFH) and metallicity evolution of each galaxy. We run a grid of 192 models, varying all the parameters known from previous studies to affect the evolution of XRBs. We use our models and observationally derived prescriptions for hot gas emission to create theoretical galaxy X-ray luminosity functions (XLFs) for several redshift bins. Models with low common envelope efficiencies, a 50% twins mass ratio distribution, a steeper initial mass function exponent, and high stellar wind mass-loss rates best match observational results from Tzanavaris & Georgantopoulos, though they significantly underproduce bright early-type and very bright (L(sub x) greater than 10(exp 41)) late-type galaxies. These discrepancies are likely caused by uncertainties in hot gas emission and SFHs, active galactic nucleus contamination, and a lack of dynamically formed low-mass XRBs. In our highest likelihood models, we find that hot gas emission dominates the emission for most bright galaxies. We also find that the evolution of the normal galaxy X-ray luminosity density out to z = 4 is driven largely by XRBs in galaxies with X-ray luminosities between 10(exp 40) and 10(exp 41) erg s(exp −1).

Tremmel, M.↗

The Role of Cation Coordination in the Electrical and Optical Properties of Amorphous Transparent Conducting Oxides

Amorphous oxide semiconductor materials have demonstrated numerous advantages without compromise of electrical properties as compared to their crystalline counterparts, yet understanding of the fundamental principles allowing this has remained elusive. To study the origins of enhanced optoelectronic properties, we apply high-throughput, combinatorial sputtering, structural and spectral mapping, and computationally intensive ab initio molecular dynamics simulations with density functional theory to a ternary, post-transition metal oxide system, namely, zinc tin oxide. The deposited thin films exhibit a high figure of merit, achieving carrier densities in the range of 1019 to 1020 cm–3 and carrier mobilities up to 35 cm2/Vs. These results highlight the role of local distortions and cation coordination in determining the microscopic origins of carrier generation and transport. In particular, we identify the strong likelihood of Sn undercoordination in both Zn-poor and Zn-rich phases leading to the high carrier concentrations observed. This not only diverges from the still widespread historical indictment of oxygen vacancies controlling carrier population in crystalline oxides but also provides a comprehensive framework to describe the unique structure–property relationships using specific structural and electronic descriptors in disordered phase materials.

CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSICS,M↗

The time since land-use transition drives changes in fire activity in the Amazon-Cerrado region

Abstract Deforestation and climate change are expected to alter fire regimes along the Cerrado-Amazon transition, one of the world’s most active agricultural frontiers. Here we tested the hypothesis that the time since land-use transition (age of frontier) and agricultural intensification also drive changes in the region’s fire regimes by reducing fire probability in both drought and non-drought years. We modeled fire probability as a function of the time since land-use transitions based on MapBiomas Project datasets from 1986 to 2020. We find that, while burned area declined as pasturelands aged and croplands advanced, deforestation abruptly increased fire activity before (Amazon: 4 years; Cerrado: 3 years) and after (Amazon: 8 years; Cerrado: 7 years) land clearing for pasture, especially in the Amazon. Additionally, the combination of ignition risk, drought, and air-dryness increased the likelihood of large extents of burned areas associated with deforestation. Incorporating frontier age as a proxy for governance in fire modeling is crucial, given the ecological implications of changing fire regimes despite declining rates of fire probability. Most importantly, protecting against deforestation and preserving native vegetation are vital.

Environmental Sciences & Ecology↗