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At least 1,063 records · Page 59

The dark energy survey 5-yr photometrically identified type Ia supernovae

ABSTRACT As part of the cosmology analysis using Type Ia Supernovae (SN Ia) in the Dark Energy Survey (DES), we present photometrically identified SN Ia samples using multiband light curves and host galaxy redshifts. For this analysis, we use the photometric classification framework SuperNNovatrained on realistic DES-like simulations. For reliable classification, we process the DES SN programme (DES-SN) data and introduce improvements to the classifier architecture, obtaining classification accuracies of more than 98 per cent on simulations. This is the first SN classification to make use of ensemble methods, resulting in more robust samples. Using photometry, host galaxy redshifts, and a classification probability requirement, we identify 1863 SNe Ia from which we select 1484 cosmology-grade SNe Ia spanning the redshift range of 0.07 < z < 1.14. We find good agreement between the light-curve properties of the photometrically selected sample and simulations. Additionally, we create similar SN Ia samples using two types of Bayesian Neural Network classifiers that provide uncertainties on the classification probabilities. We test the feasibility of using these uncertainties as indicators for out-of-distribution candidates and model confidence. Finally, we discuss the implications of photometric samples and classification methods for future surveys such as Vera C. Rubin Observatory Legacy Survey of Space and Time.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

SDSS-IV MaNGA: a catalogue of spectroscopically detected strong galaxy–galaxy lens candidates

ABSTRACT We spectroscopically detected candidate emission-lines of 8 likely, 17 probable, and 69 possible strong galaxy–galaxy gravitational lens candidates found within the spectra of $\approx 10\, 000$ galaxy targets contained within the completed Mapping of Nearby Galaxies at Apache Point Observatory survey. This search is based upon the methodology of the Spectroscopic Identification of Lensing Objects project, which extends the spectroscopic detection methods of the BOSS Emission-Line Lensing Survey and the Sloan Lens ACS Survey. We scanned the co-added residuals that we constructed from stacks of foreground subtracted row-stacked-spectra so a sigma-clipping method can be used to reject cosmic rays and other forms of transients that impact only a small fraction of the combined exposures. We also constructed narrow-band images from the signal to noise of the co-added residuals to observe signs of lensed source images. We also use several methods to compute the probable strong lensing regime for each candidate lens to determine which candidate background galaxies may reside sufficiently near the galaxy centre for strong lensing to occur. We present the spectroscopic redshifts within a value-added catalogue (VAC) for data release 17 (DR17) of SDSS-IV. We also present the lens candidates, spectroscopic data, and narrow-band images within a VAC for DR17. High resolution follow-up imaging of these lens candidates are expected to yield a sample of confirmed grade-A lenses with sufficient angular size to probe possible discrepancies between the mass derived from a best-fitting lens model, and the dynamical mass derived from the observed stellar velocities.

79 ASTRONOMY AND ASTROPHYSICS↗

The Calar Alto Legacy Integral Field Area survey: extended and remastered data release

ABSTRACT This paper describes the extended data release (eDR) of the Calar Alto Legacy Integral Field Area (CALIFA) survey. It comprises science-grade quality data for 895 galaxies obtained with the Potsdam Multi Aperture Spectograph/PPak instrument at the 3.5-m telescope at the Calar Alto Observatory along the last 12 yr, using the V500 setup [3700–7500 Å, 6 Å/full-width at half-maximum (FWHM)] and the CALIFA observing strategy. It includes galaxies of any morphological type, star formation stage, a wide range of stellar masses (∼107–1012 M⊙), at an average redshift of ∼0.015 (90 per cent within 0.005 < z < 0.05). Primarily selected based on the projected size and apparent magnitude, we demonstrate that it can be volume corrected resulting in a statistically limited but representative sample of the population of galaxies in the nearby Universe. All the data were homogeneous re-reduced, introducing a set of modifications to the previous reduction. The most relevant is the development and implementation of a new cube-reconstruction algorithm that provides with an (almost) seeing-limited spatial resolution (FWHMPSF ∼ 1.0 arcsec). To illustrate the usability and quality of the data, we extracted two aperture spectra for each galaxy (central 1.5 arcsec and fully integrated), and analyse them using pyFIT3D. We obtain a set of observational and physical properties of both the stellar populations and the ionized gas, that have been compared for the two apertures, exploring their distributions as a function of the stellar masses and morphologies of the galaxies, comparing with recent results in the literature.

Sánchez, S. F. (ORCID:0000000164449307)↗

Survey of Gravitationally lensed objects in HSC Imaging (SuGOHI). VIII. New galaxy-scale lenses from the HSC SSP

Abstract We conduct a search for galaxy-scale strong gravitational lens systems in Data Release 4 of the Hyper Suprime-Cam Subaru Strategic Program (HSC SSP), consisting of data taken up to the S21A semester. We select 103191 luminous red galaxies from the Baryon Oscillation Spectroscopic Survey (BOSS) sample that have deep multiband imaging from the HSC SSP and use the YattaLens algorithm to identify lens candidates with blue arc-like features automatically. The candidates are visually inspected and graded based on their likelihood of being a lens. We find eight definite lenses, 28 probable lenses, and 138 possible lenses. The new lens candidates generally have lens redshifts in the range 0.3 ≲ zL ≲ 0.9, a key intermediate redshift range to study the evolution of galaxy structure. Follow-up spectroscopy will confirm these new lenses and measure source redshifts to enable detailed lens modeling.

Astronomy & Astrophysics↗

Global estimates of the fitness advantage of SARS-CoV-2 variant Omicron

Abstract New variants of SARS-CoV-2 show remarkable heterogeneity in their relative fitness over both time and space. In this paper we extend the tools available for estimating the selection strength for new SARS-CoV-2 variants to a hierarchical, mixed-effects, renewal equation model. This formulation allows us to estimate selection effects at the global level while incorporating both measured and unmeasured heterogeneity among countries. Applying this model to the spread of Omicron in forty countries, we find evidence for very strong but very heterogeneous selection effects. To test whether this heterogeneity is explained by differences in the immune landscape, we considered several measures of vaccination rates and recent population-level infection as covariates, finding moderately strong, statistically significant effects. We also found a significant positive correlation between the selection advantage of Delta and Omicron at the country level, suggesting that other region-specific explanatory variables of fitness differences do exist. Our method is implemented in the Stan programming language, can be run on standard consumer-grade computing resources, and will be straightforward to apply to future variants.

59 BASIC BIOLOGICAL SCIENCES↗

Demonstration of a Novel Radiochemical Mix Diagnostic for Fusion Implosions at the National Ignition Facility

Mixing of the ablator material into the fuel of an inertial confinement fusion implosion reduces compression and enhances radiative losses, preventing ignition. Here, we describe a novel use of charged-particle radiochemistry to measure the ablator mix in contact with the fusion hot spot. The capsule uses a graded Be-Cr layer to increase the confinement of the hot spot. 52 Mn and 51 Cr isotopes are collected from the implosion and counted, and the ratio is related to the amount of Cr mixed into the hot spot. Thus, a new diagnostic to determine the degradation due to mix on fusion implosions has been developed.

MacLaren, S. A. [Lawrence Livermore National Labor↗

Energy Conversion from Heat to Electricity by Highly Reversible Phase-Transforming Ferroelectrics

The search for performant multiferroic materials has attracted general research interest in energy science as they have been increasingly exploited as the conversion media among thermal, electric, magnetic, and mechanical energies by using their temperature-dependent ferroic properties. Here we report a material development strategy that guides us to discover a reversible phase-transforming ferroelectric material exhibiting enduring energy harvesting from small temperature differences. The material satisfies the crystallographic compatibility condition between polar and nonpolar phases, which shows only 2.5°C thermal hysteresis and a high figure of merit. It stably generates 15μA of electricity in consecutive thermodynamic cycles in the absence of any bias fields. We demonstrate our device to consistently generate 6μA/cm 2 current density near 100°C over 540 complete phase transformation cycles without any electric and functional degradation. The energy-conversion device can light up an LED directly without attaching an external power source. Furthermore, this promising material candidate brings the low-grade waste-heat harvesting closer to a practical realization, e.g., small temperature fluctuations around the water boiling point can be considered as a clean energy source.

30 DIRECT ENERGY CONVERSION↗

SENSEI: Characterization of Single-Electron Events Using a Skipper Charge-Coupled Device

We use a science-grade skipper charge-coupled device (skipper CCD) operating in a low-radiation background environment to develop a semi-empirical model that characterizes the origin of single-electron events in CCDs. We identify, separate, and quantify three independent contributions to the single-electron events, which were previously bundled together and classified as "dark counts": dark current, amplifier light, and spurious charge. We measure a dark current, which depends on exposure, of (5.89±0.77)×10 -4 e - /pix/day, and an unprecedentedly low spurious charge contribution of (1.52±0.07)×10 -4 e - /pix, which is exposure independent. In addition, we provide a technique to study events produced by light emitted from the amplifier, which allows the detector's operation to be optimized to minimize this effect to a level below the dark-current contribution. Our accurate characterization of the single-electron events allows one to greatly extend the sensitivity of experiments searching for dark matter or coherent neutrino scattering. Moreover, an accurate understanding of the origin of single-electron events is critical to further progress in ongoing research and development efforts of skipper and conventional CCDs.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Precision Measurement of the Microwave Dielectric Loss of Sapphire in the Quantum Regime with Parts-per-Billion Sensitivity

Dielectric loss is known to limit state-of-the-art superconducting qubit lifetimes. Recent experiments imply upper bounds on bulk dielectric loss tangents on the order of 100 parts per billion but because these inferences are drawn from fully fabricated devices with many loss channels, these experiments do not definitely implicate or exonerate the dielectric. To resolve this ambiguity, we devise a measurement method capable of separating and resolving bulk dielectric loss with a sensitivity at the level of 5 ×10 –9 . The method, which we call the dielectric dipper, involves the in situ insertion of a dielectric sample into a high-quality microwave cavity mode. Smoothly varying the participation of the sample in the cavity mode enables a differential measurement of the dielectric loss tangent of the sample. The dielectric dipper can probe the low-power behavior of dielectrics at cryogenic temperatures and does so without the need for any lithographic process, enabling controlled comparisons of substrate materials and processing techniques. We demonstrate the method with measurements of sapphire grown by edge-defined film-fed growth (EFG) in comparison to high-grade sapphire grown by the heat-exchanger method (HEMEX). For EFG sapphire, we infer a bulk loss tangent of 63⁢(8) ×10 –9 and a substrate-air interface loss tangent of 15⁢(3) ×10 –4 (assuming a sample surface thickness of 3 nm). For a typical transmon, this bulk loss tangent would limit device quality factors to Q ≲20 ×10 6 , suggesting that bulk loss is likely the dominant loss mechanism in the longest-lived transmons on sapphire. We also demonstrate this method on HEMEX sapphire and bound its bulk loss tangent to be less than 19⁢(6) ×10 –9 . As this bound is about 3 times smaller than the bulk loss tangent of EFG sapphire, the use of HEMEX sapphire as a substrate would lift the bulk dielectric coherence limit of a typical transmon qubit to several milliseconds.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

String membrane nets from higher-form gauging: An alternate route to 𝑝-string condensation

We present a new perspective on the $p$-string condensation procedure for constructing 3+1D fracton phases by implementing this process via the gauging of higher-form symmetries. Specifically, we show that gauging a 1-form symmetry in 3+1D that is generated by Abelian anyons in isotropic stacks of 2+1D topological orders naturally results in a 3+1D $p$-string condensed phase, providing a controlled non-perturbative construction that realizes fracton orders. This approach clarifies the symmetry principles underlying $p$-string condensation and generalizes the familiar connection between anyon condensation and one-form gauging in two spatial dimensions. We demonstrate this correspondence explicitly in both field theories and lattice models: in field theory, we derive the foliated field theory description of the $\mathbb{Z}_N$ X-Cube model by gauging a higher-form symmetry in stacks of 2+1D $\mathbb{Z}_N$ gauge theories; on the lattice, we show how gauging a diagonal 1-form symmetry in isotropic stacks of $G$-graded string-net models leads to string-membrane-nets hosting restricted mobility excitations. This perspective naturally generalizes to spatial dimensions $d \geq 2$ and provides a step towards building an algebraic theory of $p$-string condensation.

Anyons↗

IRIXS Spectrograph: an ultra high-resolution spectrometer for tender RIXS

The IRIXS Spectrograph represents a new design of an ultra-high-resolution resonant inelastic X-ray scattering (RIXS) spectrometer that operates at the Ru L 3 -edge (2840 eV). First proposed in the field of hard X-rays by Shvyd'ko [(2015), Phys. Rev. A, 91, 053817], the X-ray spectrograph uses a combination of laterally graded multilayer mirrors and collimating/dispersing Ge(111) crystals optics in a novel spectral imaging approach to overcome the energy resolution limitation of a traditional Rowland-type spectrometer [Gretarsson et al. (2020), J. Synchrotron Rad. 27, 538–544]. In combination with a dispersionless nested four-bounce high-resolution monochromator design that utilizes Si(111) and Al 2 O 3 (110) crystals, an overall energy resolution better than 35 meV full width at half-maximum has been achieved at the Ru L 3 -edge, in excellent agreement with ray-tracing simulations.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

A Novel Protection Scheme for Unbalanced Faults in Inverter Dominated Networks: A Computationally Efficient Algorithm for Entry-Level Relays

Microgrids are now a common practice in distribution systems to increase resilience and reliability. However, microgrid protection remains a critical challenge, considering its requirement to operate in both grid connected and islanded, and the variability in fault characteristics under each mode of operation. This paper presents unbalanced power (S unb ) based fault detection algorithm, which considers local voltage and current unbalances to determine faults in the system. S unb is a computationally efficient fault detection algorithm that is suitable for implementation in the programmable logic of entry level protective relays. In addition, the difference in current and voltage unbalance (D n ) is used to determine the fault type. The proposed method demonstrates high sensitivity and selectivity for line-to-ground (LG), line-to-line (LL), and double line-to-ground (LLG) faults, representing the most common faults in distribution systems. It also allows relay coordination with upstream and downstream protection devices in both island and grid connected operation, while preserving grading margins. The same pickup and time multiplier settings of a particular relay for both modes of operation eliminates the need for adaptive settings, which rely on communication networks. Validation was performed with a hardware-in-the-loop (HIL) setup using Typhoon HIL real time simulator interfaced with three entry-level, SEL 751 relays. Results confirmed the algorithm’s ability to discriminate fault conditions, and determine the fault type under both operating modes, maintain fast detection times, and ensure proper protection coordination.

fault classification↗

Microgrid to Microgrid Synchronization with Grid-Forming Inverters: Challenges and Solution

Research on network microgrids has primarily focused on control and optimization. However, application aspects such as microgrid-to-microgrid synchronization have not been fully addressed in existing literature. This paper first addresses the challenges of networking microgrids with grid-forming inverter in droop control. Then, it proposes a pre-synchronization algorithm to improves the synchronization speed and transient stability. To improve the speed, the phase difference between adjacent microgrids is minimized. Transients such as inrush current and oscillations are effectively mitigated by increasing the virtual impedance during interconnection. The proposed strategy allows smooth transitions when reconfiguration of the microgrids is needed. The applicability of this strategy to today’s microgrid systems is demonstrated through a validation in a 480V three-phase network microgrid testbed with commercial-grade inverters, protective devices, and switchgear.

Ferrari Maglia, Max↗

A Robust Communication-Free Protection Scheme for Islanded Microgrids with Relay Logic and Hardware-in-the-Loop Validation

This paper presents the Imbalance Square Factor (ISF) detection algorithm, an effective, computationally lightweight method for detecting faults in inverter-based microgrids. ISF provides a high magnitude at the time of the fault, which allows for fast detection and coordination between primary and backup relays. The imbalance squared factor, calculated using local voltage and currents, is used for fault detection and coordination among three relays. ISF is validated in hardware-in-the-loop (HIL) implementation inside commercial-grade relay logic (SEL-751). The HIL validation shows that ISF can coordinate primary, secondary, and tertiary relays in the 13-bus system in islanded operation.

Ferrari Maglia, Max [ORNL]↗

Neural Learning Based Blind Source Separation for Detection of Material Defects in Pulsed Thermography Images

In this paper, we introduce a neural learning-based approach to blind source separation for detection of material flaws in pulsed thermography (PT) images. This approach can be used to detect internal defects (pores) in metallic Additively Manufactured (AM) materials. Such defects occur in high-strength alloys produced with direct laser sintering AM method for nuclear energy applications. Pulsed thermal imaging system utilizes a high intensity flash lamp to rapidly heat surface of sample, a high sensitivity infrared camera to capture data of surface temperature variations. The data cube obtained with PT (stack of surface temperature images at different times) can be analyzed with image processing algorithms to detect material defects. Compared with conventional nondestructive evaluation (NDE) methods, such as digital radiography and ultrasonic testing, the PT pulsed infrared thermal detection technique has advantages of one-sided non-contact measurements, fast processing of large sample areas captured in one image. Detection of small material defects requires finding features in thermal images, which have signal contrast levels approaching sensitivity limit of IR camera. In this study, an optimized Neural Learning based Blind Source Separation (NLBSS) algorithm, including Principal Component Analysis (PCA), and Independent Component Analysis (ICA) is demonstrated to automatically extract principal temporal and spatial features of thermography frames to enhance flaw detection. By using the NLBSS algorithm, material internal defects can be automatically detected. Furthermore, this processing approach compensates for experimental thermal imaging artifacts, such as noise and uneven heating. By merging artificial intelligence with the photothermic, the NDE system detects internal calibrated defects of various sizes and depths in AM nuclear-grade metallic alloys.

Zhang, Xin↗

Digital Filter Design for Point-on-Wave Sensors: Highlighting Frequency Response Limitations and Enhancing Grid Simulation Accuracy

Data is proving to be the backbone of today's and, more importantly, tomorrow's grid. As the system changes and introduces fast-acting devices like power electronics, overall observability tends to decrease from the utility point-of-view. This can be mitigated by adding more high-fidelity sensors onto the grid, although this incurs a cost. These sensors are never ideal, and each have unique frequency responses that may influence the data produced. This may, in turn, impact the protection and control of the power grid. This paper presents a methodology of representing these point-on-wave sensors digitally by estimating digital-filter representations of them, thereby introducing means of improving the sensor models used in electromagnetic-transient (EMT) simulations. This may help with identifying potential high-frequency, sensor-induced distortions, and system resonance compensation. Three commercial-grade medium-voltage point-on-wave sensors are utilized in a lab environment to obtain experimental frequency responses with a frequency sweep, and it is shown that both Infinite Impulse Response (IIR) and Finite Impulse Response (FIR) filter representations may approximate these responses with varying degrees of accuracy, though each has their own strengths and weaknesses. It is found that, in general, FIR estimation better approximates these sensors than IIR estimation does.

Wilson, Aaron [ORNL] (ORCID:0000000327331697)↗

Characterizing Minimum Admissible Separation Distances in Heavy Duty Vehicle Platoons

Heavy duty (HD) vehicles platooning under highway operating conditions, have been projected to provide significant fuel economy (FE) gains based on aerodynamic drag reduction of the platooning vehicles. Realizing these benefits under real-world operating conditions have several challenges. This paper (the second as part of series) quantifies the minimum admissible separation distance between platooning vehicles in HD commercial vehicle (CV) applications. This distance must be set up such that no collision occurs with leading vehicles under all deceleration conditions. In this paper key interactions to characterize this distance are demonstrated. These include, road surface conditions, grade, inter-vehicle communication delays, air-brake lag time, vehicle speed, weight, and aerodynamic drag. It is seen that characterizing the vehicle and road dynamics will be critical in establishing required deceleration or stopping distances for each vehicle in a platoon. The results of the study also necessitate vehicle control systems that can dynamically adjust not only the separation distances but also the braking reference points based on road conditions. The narrative provides application decision personnel with a well-defined set of admissible separation distance impact factors to consider as part of their architecture selection process.

Sujan, Vivek↗

An FPGA-Based Neuromorphic Processor with All-to-All Connectivity

Neuromorphic computing is a promising paradigm for future energy-efficient computing. At present, however, it is in its nascent stages—most hardware implementations are research-grade, commercial products are not available, and the software tools are not production-ready. The lack of hardware and software tools makes neuromorphic computing inaccessible to researchers around the globe. To this extent, we intend to build a low-cost, open-source, FPGA-based digital neuromorphic processor that can be used by researchers worldwide. In this paper, we present a preliminary implementation of the processor on a Xilinx Artix-7 FPGA using SystemVerilog. Our implementation supports the integrate-and-fire neuron with two parameters each for neurons and synapses. It also features all-to-all connectivity among neurons on the hardware. We test our implementation on four cases: bars and stripes datasets, shortest path algorithm, logic gates, and 8-3 encoder. We also perform a scalability study to understand the resource utilization of the FPGA as the number of all-to-all connected neurons increases. With our implementation, the Artix- 7 supports 65 neurons with all-to-all connectivity. Moreover, all the test cases mentioned above achieve 100% accuracy.

Maheshwari, Disha↗