Continuous-Domain Real-Time Distributed ADMM Algorithm for Aggregator Scheduling and Voltage Stability in Distribution Network
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Laika BOSS (Binary Object Scanning System), often written as "Laikaboss", is an object scanner and intrusion detection system that strives to be scalable, flexible, and verbose. Its goal is to take arbitrary file input and extract all relevant subfiles and metadata for use in helping analysts determine the function and maliciousness of a file at a glance. This is an extension to the original code developed by Lockheed Martin.
The traditional Fermi function (long-distance radiative contribution) ansatz for nuclear beta decay describes enhanced perturbative effects in the limit of large nuclear charge $Z$ and/or small electron velocity $\beta$. We define and compute the quantum field theory object that replaces this ansatz for neutron beta decay, where neither of these limits hold.
We present a catalog of 1.4 million photometrically selected quasar candidates in the southern hemisphere over the ~5000 deg 2 Dark Energy Survey (DES) wide survey area. We combine optical photometry from the DES second data release (DR2) with available near-infrared (NIR) and the all-sky unWISE mid-infrared photometry in the selection. We build models of quasars, galaxies, and stars with multivariate skew-t distributions in the multidimensional space of relative fluxes as functions of redshift (or color for stars) and magnitude. Our selection algorithm assigns probabilities for quasars, galaxies, and stars and simultaneously calculates photometric redshifts (photo-z) for quasar and galaxy candidates. Benchmarking on spectroscopically confirmed objects, we successfully classify (with photometry) 94.7% of quasars, 99.3% of galaxies, and 96.3% of stars when all IR bands (NIR YJHK and WISE W1W2) are available. The classification and photo-z regression success rates decrease when fewer bands are available. Our quasar (galaxy) photo-z quality, defined as the fraction of objects with the difference between the photo-z z p and the spectroscopic redshift z s , |Δz| ≡ |z s - z p |/(1 + z s ) ≤ 0.1, is 92.2% (98.1%) when all IR bands are available, decreasing to 72.2% (90.0%) using optical DES data only. Our photometric quasar catalog achieves an estimated completeness of 89% and purity of 79% at r < 21.5 (0.68 million quasar candidates), with reduced completeness and purity at 21.5 < r ≲ 24. Among the 1.4 million quasar candidates, 87,857 have existing spectra, and 84,978 (96.7%) of them are spectroscopically confirmed quasars. Finally, we provide quasar, galaxy, and star probabilities for all (0.69 billion) photometric sources in the DES DR2 coadded photometric catalog.
We report the first results of a high-redshift (z ≳ 5) quasar survey using the Dark Energy Spectroscopic Instrument (DESI). As a DESI secondary target program, this survey is designed to carry out a systematic search and investigation of quasars at 4.8 < z < 6.8. The target selection is based on the DESI Legacy Imaging Surveys (the Legacy Surveys) DR9 photometry, combined with the Pan-STARRS1 data and J-band photometry from public surveys. A first quasar sample has been constructed from the DESI Survey Validation 3 (SV3) and first-year observations until 2022 May. This sample includes more than 400 new quasars at redshift 4.7 ≤ z < 6.6, down to 21.5 magnitude (AB) in the z band, discovered from 35% of the entire target sample. Remarkably, there are 220 new quasars identified at z ≥ 5, more than one-third of existing quasars previously published at this redshift. The observations so far result in an average success rate of 23% at z > 4.7. The current spectral data set has already allowed analysis of interesting individual objects (e.g., quasars with damped Lyα absorbers and broad absorption line features), and statistical analysis will follow the survey's completion. A set of science projects will be carried out leveraging this program, including quasar luminosity function, quasar clustering, intergalactic medium, quasar spectral properties, intervening absorbers, and properties of early supermassive black holes. Additionally, a sample of 38 new quasars at z ~ 3.8–5.7 discovered from a pilot survey in the DESI SV1 is also published in this paper.
Advances in performance and analysis capabilities have accelerated the development of object tracking algorithms for atmospheric research. This has resulted in a growing number of studies using Lagrangian tracking techniques to analyze the evolution of atmospheric phenomena and the underlying processes. However, the increasing complexity and variety of tracking algorithms present a steep learning curve for new users and make it difficult for existing users to compare algorithm performance. We introduce CoCoMET (Community Cloud Model Evaluation Toolkit), an open-source toolkit that addresses these issues. CoCoMET simplifies the process of running multiple tracking algorithms simultaneously and analyzing objects in both model and observational datasets by specifying parameters in a single configuration file. It standardizes input data from different sources into a consistent format and unifies the tracking output across algorithms. CoCoMET enhances the functionality of existing tracking methods by calculating additional properties such as cell growth and dissipation rates, perimeter, surface area, convexity, and irregularity. In addition, CoCoMET includes a novel method for identifying mergers and splits in 2D and 3D tracks and supports the integration of Eulerian/stationary datasets external to the tracking data for process studies. Its potential utility is demonstrated through examples of model intercomparison, model evaluation against observations, and comparisons between tracking algorithms. Designed for open-source environments, CoCoMET will continue to expand with future releases, incorporating more input data types and tracking algorithms.
The second generation of stars in the globular clusters (GCs) of the Milky Way (MW) exhibit unusually high N, Na, or Al, compared to typical Galactic halo stars at similar metallicities. The halo field stars enhanced with such elements are believed to have originated in disrupted GCs or escaped from existing GCs. We identify such stars in the metallicity range –3.0 < [Fe/H] < 0.0 from a sample of ~ 36,800 giant stars observed in the Sloan Digital Sky Survey and Large Sky Area Multi-Object Fiber Spectroscopic Telescope survey, and present their dynamical properties. The N-rich population (NRP) and N-normal population (NNP) among our giant sample do not exhibit similarities in either in their metallicity distribution function (MDF) or dynamical properties. We find that, even though the MDF of the NRP looks similar to that of the MW’s GCs in the range of [Fe/H] < –1.0, our analysis of the dynamical properties does not indicate similarities between them in the same metallicity range, implying that the escaped members from existing GCs may account for a small fraction of our N-rich stars, or the orbits of the present GCs have been altered by the dynamical friction of the MW. We also find a significant increase in the fraction of N-rich stars in the halo field in the very metal-poor (VMP; [Fe/H] < –2.0) regime, comprising up to ~ 20% of the fraction of the N-rich stars below [Fe/H] = –2.5, hinting that partially or fully destroyed VMP GCs may have in some degree contributed to the Galactic halo. A more detailed dynamical analysis of the NRP reveals that our sample of N-rich stars do not share a single common origin. Although a substantial fraction of the N-rich stars seem to originate from the GCs formed in situ, more than 60% of them are not associated with those of typical Galactic populations, but probably have extragalactic origins associated with Gaia Sausage/Enceladus, Sequoia, and Sagittarius dwarf galaxies, as well as with presently unrecognized progenitors.
Volumetric 3D printing motivated by computed axial lithography enables rapid printing of homogeneous parts but requires a high dimensionality gradient-descent optimization to calculate image sets. Here we introduce a new, simpler approach to image-computation that algebraically optimizes a model of the printed object, significantly improving print accuracy of complex parts under imperfect material and optical precision by improving optical dose contrast between the target and surrounding regions. Quality metrics for volumetric printing are defined and shown to be significantly improved by the new algorithm. The approach is extended beyond binary printing to grayscale control of conversion to enable functionally graded materials. The flexibility of the technique is digitally demonstrated with realistic projector point spread functions, printing around occluding structures, printing with restricted angular range, and incorporation of materials chemistry such as inhibition. Finally, simulations show that the method facilitates new printing modalities such as printing into flat, rather than cylindrical packages to extend the applications of volumetric printing.
Plastic deformation of samples compressed to Mbar pressures at high strain rates at the National Ignition Facility (NIF) forms the basis of ongoing material strength experiments in conditions relevant to meteor impacts, geophysics, armor development, and inertial confinement fusion. Hard x-ray radiography is the primary means of measuring the evolution of these samples, typically employing a slit-collimated high-Z microdot driven by the NIF laser to generate >40 keV x rays [E. Gumbrell et al., Rev. Sci. Instrum. 89, 10G118 (2018) and C. M. Huntington et al., Rev. Sci. Instrum. 89, 10G121 (2018)]. Alternatively, a dysprosium “micro-flag” target driven by the Advanced Radiographic Capability laser (~2 kJ, 10 ps) can deliver significantly higher spatiotemporal resolution [M. P. Hill et al., Rev. Sci. Instrum. 92, 033535 (2021)], especially in high-opacity samples. Here, initial experiments revealed problematic brightness and spectral gradients from this source, but by radiographing a set of diamond-turned, 105 µm-thick Pb test objects and supported by simulations using the 3D Monte Carlo code GEANT4, these geometry-dependent gradients across the field of view are quantified and mitigation strategies are assessed. In addition to significantly enhancing the modulation transfer function compared to the existing system, image stacking from multiple layers of image plate is shown to almost double the signal to noise ratio that will reduce uncertainties in future dynamic strength experiments.
Abstract Compositionally graded alloys, a subclass of functionally graded materials (FGMs), utilize localized variations in composition with a single metal part to achieve higher performance than traditional single material parts. In previous work [Kirk, T., Galvan, E., Malak, R., and Arroyave, R., 2018, “Computational Design of Gradient Paths in Additively Manufactured Functionally Graded Materials,” J. Mech. Des., 140, p. 111410. 10.1115/1.4040816], the authors presented a computational design methodology that avoids common issues which limit a gradient alloy’s feasibility, such as deleterious phases, and optimizes for performance objectives. However, the previous methodology only samples the interior of a composition space, meaning designed gradients must include all elements in the space throughout the gradient. Because even small amounts of additional alloying elements can introduce new deleterious phases, this characteristic often neglects potentially simpler solutions to otherwise unsolvable problems and, consequently, discourages the addition of new elements to the state space. The present work improves upon the previous methodology by introducing a sampling method that includes subspaces with fewer elements in the design search. The new method samples within an artificially expanded form of the state space and projects samples outside the true region to the nearest true subspace. This method is evaluated first by observing the sample distribution in each subspace of a 3D, 4D, and 5D state space. Next, a parametric study in a synthetic 3D problem compares the performance of the new sampling scheme to the previous methodology. Lastly, the updated methodology is applied to design a gradient from stainless steel to equiatomic NiTi that has practical uses such as embedded shape memory actuation and for which the previous methodology fails to find a feasible path.
The electron injection system for the Electron-Ion Collider (EIC) at BNL is designed to provide a beam of polarized electrons, which is crucial for studying the structure of protons and atomic nuclei. The Beam Accumulator Ring (BAR) is a part of the injection chain between the 750 MeV linear accelerator and the Rapid Cycling Synchrotron (RCS), which accelerates the beam up to full energy (5–18 GeV). The functional role of the BAR is to accumulate the charge injected from the linear accelerator in order to achieve the high intensity of the polarized electron beam required by the specifications for injection into the RCS. This objective will be realized through the sequential injection of bunches with a charge of 1.1 nC at a repetition rate of 30 Hz. Once the charge of a single bunch reaches 28 nC, the beam will be extracted from the BAR and injected into the RCS. The beam instrumentation needs to provide reliable measurements with the required accuracy over the dynamic range from 0.1 nC (one tenth of a typical injected bunch charge) to 32 nC – the maximum expected accumulated current. There are 10 Beam Position Monitors (BPMs) in the ring, 1 extra button-electrode assembly for the RF system, and 8 BPMs in the beam transport lines. The BPM locations are shown in Fig. 1, marked by blue rectangles. The ring BPMs will be capable of both average orbit and turn-by-turn measurement modes. Accurate measurement of the beam position with a large horizontal offset requires polynomial correction of the BPM nonlinearity.
The major goal of this project was the synthesis and study of receptors for key ions of interest to the DOE mission, namely cesium, lithium, sulfate, hydroxide, carbon dioxide/bicarbonate, and early actinides. The work, fundamental in nature, had as its objective achieving an increased understanding of how changes in receptor design could be used to optimize binding energies, ion specificity, complex structure, extraction efficiency, and substrate release. Within this broad paradigm, particular emphasis was placed on systems that could be used to sense the cesium cation in mixed aqueous media and act as extractants for the lithium cation and, separately, the carbon dioxide/bicarbonate and hydroxide anions in the form of ion pairs likely to be encountered under conditions of putative use in the field. The development of new nitrogen-rich ligands that act as receptors for early, high-valent actinide cations was also a major point of emphasis. The first in-plane actinide complexes were synthesized using a hexa-aza porphyrin analogue. The complexes exhibited an increase in the ligand–metal bonding covalency on passing from thorium(IV) to uranium(IV) to neptunium(IV) and illustrates how the use of appropriate porphyrinoid-like ligands could be used to modulate the covalency interactions between an f-element metal center and a ligand.
A Gamma-Ray and Neutron Spectrometer (GRNS) instrument has been developed as part of the science payload for NASA’s Discovery Program Psyche mission to the M-class asteroid (16) Psyche. The GRNS instrument is designed to measure the elemental composition of Psyche with the goal to understand the origin of this mysterious, potentially metal-rich planetary body. The GRNS will measure the near-surface abundances for the elements Ni, Fe, Si, K, S, Al, and Ca, as well as the spatial distribution of Psyche’s metal-to-silicate fraction (or metal fraction). These measurements address three of the five Psyche mission science objectives: determine if Psyche is a core; determine whether small metal bodies incorporate light elements into the metal phase; and determine whether Psyche was formed under reducing conditions. The Gamma-Ray Spectrometer (GRS) uses a cryocooled, high-purity Ge (HPGe) sensor to detect cosmic-ray generated gamma rays in the 60 to 9000-keV energy range. The HPGe sensor is surrounded by a borated plastic anticoincidence shield that provides three functions: active background rejection from charged particle interactions in the HPGe sensor; fast neutron measurements; and direct measurements of the incident galactic cosmic ray flux. The Neutron Spectrometer (NS) uses three 3 He gas proportional sensors, each with different material wraps to measure thermal (<0.4 eV), low-energy epithermal (0.4 eV to 1 keV), and high-energy epithermal (up to 100 keV) neutrons. This paper provides an overview of the Psyche GRNS, including: its science and measurement objectives; the design of the instrument hardware, software, and operation; pre-launch performance measurements and its initial performance in space; and an overview of its data products and expected operation for different Psyche mission phases.
The faint-end slope of the quasar luminosity function at z ~ 6 and its implication on the role of quasars in reionizing the intergalactic medium at early times has been an outstanding problem for some time. The identification of faint high-redshift quasars with luminosities of <10 44.5 erg s –1 is challenging. They are rare (few per square degree), and the separation of these unresolved quasars from late-type stars and compact star-forming galaxies is difficult from ground-based observations alone. In addition, source confusion becomes significant at >25 mag, with ~30% of sources having their flux contaminated by foreground objects when the seeing resolution is ~0''.7. We mitigate these issues by performing a pixel-level joint processing of ground and space-based data from Subaru/Hyper-SuprimeCam (HSC) and Hubble Space Telescope (HST) Advanced Camera for Surveys (ACS). We create a deconfused catalog over the 1.64 deg 2 of the COSMOS field, after accounting for spatial varying point-spread functions and astrometric differences between the two data sets. We identify twelve low-luminosity (M UV ~ –21 mag) z > 6 quasar candidates through (i) their red color measured between ACS/F814W and HSC/i band and (ii) their compactness in the space-based data. Nondetections of our candidates in Hubble DASH data argues against contamination from late-type stars. Our constraints on the faint end of the quasar luminosity function at z ~ 6.4 suggest a negligibly small contribution to reionization compared to the star-forming galaxy population. The confirmation of our candidates and the evolution of number density with redshift could provide better insights into how supermassive galaxies grew in the first billion years of cosmic time.
A search for pair production of third-generation scalar leptoquarks decaying into a top quark and a τ-lepton is presented. The search is based on a dataset of pp collisions at $\sqrt{s}$ = 13 TeV recorded with the ATLAS detector during Run 2 of the Large Hadron Collider, corresponding to an integrated luminosity of 139 fb -1 . Events are selected if they have one light lepton (electron or muon) and at least one hadronically decaying τ -lepton, or at least two light leptons. In addition, two or more jets, at least one of which must be identified as containing b-hadrons, are required. Six final states, defined by the multiplicity and flavour of lepton candidates, are considered in the analysis. Each of them is split into multiple event categories to simultaneously search for the signal and constrain several leading backgrounds. The signal-rich event categories require at least one hadronically decaying τ-lepton candidate and exploit the presence of energetic final-state objects, which is characteristic of signal events. No significant excess above the Standard Model expectation is observed in any of the considered event categories, and 95% CL upper limits are set on the production cross section as a function of the leptoquark mass, for different assumptions about the branching fractions into tτ and bν. Scalar leptoquarks decaying exclusively into tτ are excluded up to masses of 1.43 TeV while, for a branching fraction of 50% into tτ, the lower mass limit is 1.22 TeV.
Scientific advancement is universally based on the dynamic interplay between theoretical insights, modeling, and experimental discoveries. However, this feedback loop is often slow, including delayed community interactions and the gradual integration of experimental data into theoretical frameworks. This challenge is particularly exacerbated in domains dealing with high-dimensional object spaces, such as molecules and complex microstructures. Hence, the integration of theory within automated and autonomous experimental setups, or theory in the loop-automated experiment, is emerging as a crucial objective for accelerating scientific research. The critical aspect is to use not only theory but also on-the-fly theory updates during the experiment. Furthermore, we introduce a method for integrating theory into the loop through Bayesian conavigation of theoretical model space and experimentation. Our approach leverages the concurrent development of surrogate models for both simulation and experimental domains at the rates determined by latencies and costs of experiments and computation, alongside the adjustment of control parameters within theoretical models to minimize epistemic uncertainty over the experimental object spaces. This methodology facilitates the creation of digital twins of material structures, encompassing both the surrogate model of behavior that includes the correlative part and the theoretical model itself. While being demonstrated here within the context of functional responses in ferroelectric materials, our approach holds promise for broader applications, such as the exploration of optical properties in nanoclusters, microstructure-dependent properties in complex materials, and properties of molecular systems.
The van der Waals (vdW) interaction plays a prominent role between neutral objects at separations where short ranged chemical forces are negligible. This type of dispersive coupling is determined by the interplay between geometry and response properties of the materials making up the objects. Here, we investigate the vdW interaction between 1D, 2D, and 3D standard and Dirac materials within the Random Phase Approximation, which takes into account collective excitations originating from the electronic Coulomb potential. A comprehensive understanding of characteristic functionalities and scaling laws are obtained for systems with parabolic energy dispersion (standard materials) and crossing linear bands (Dirac materials). By comparing the quantum mechanical and thermal limits the onset of thermal fluctuations in the vdW interaction is discussed showing that thermal effects are significantly pronounced at smaller scales in reduced dimensions.
Fiber-reinforced polymer composites (FRPCs) are valid alternatives to metals, especially in the aerospace industry, for their superior strength-to-weight ratio. FRPCs are generally manufactured by stacking layers of fibers and infusing them with epoxy-based adhesives to result in laminates. Such layer-by-layer structure often ensues a poor interlaminar property of the composites. Additionally, FRPCs can sustain complex damage modes because of their inherent anisotropic characteristics. For example, delamination can occur due to low-velocity impact at a subsurface level, which can result in premature catastrophic failures if undetected. Thus, structural monitoring is crucial to identify such damage. Point-based sensors (e.g., strain gauges, accelerometers, among many) can be embedded in the FRPCs for structural monitoring. However, their electrical power demand often embroils their usage. Therefore, the main objective of this research is to design and implement multifunctional composites that can simultaneously perform passive sensing and energy harvesting while exhibiting better mechanical performance. Previous research efforts have demonstrated that a continuous feed-through deposition of functional materials on fiber surfaces simultaneously enhanced the mechanical and sensing properties of the FRPCs. This study explores a similar approach to encode passive sensing and energy harvesting properties in the FRPCs by integrating ferroelectric microparticles on the fiber surfaces. Upon ensuring their superior interlaminar shear strength, sensing and energy harvesting properties were characterized through experimental studies. The outcome is a multifunctional composite fabricated by coating the fibers with functional microparticles through a high throughput, scalable, and low-cost approach that enables passive sensing, energy harvesting, and improved mechanical performance.