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At least 631 records · Page 35

Redshift-dependent RSD bias from intrinsic alignment with DESI Year 1 spectra

ABSTRACT We estimate the redshift-dependent, anisotropic clustering signal in the Dark Energy Spectroscopic Instrument (DESI) Year 1 Survey created by tidal alignments of Luminous Red Galaxies (LRGs) and a selection-induced galaxy orientation bias. To this end, we measured the correlation between LRG shapes and the tidal field with DESI’s Year 1 redshifts, as traced by LRGs and Emission-Line Galaxies. We also estimate the galaxy orientation bias of LRGs caused by DESI’s aperture-based selection, and find it to increase by a factor of seven between redshifts 0.4−1.1 due to redder, fainter galaxies falling closer to DESI’s imaging selection cuts. These effects combine to dampen measurements of the quadrupole of the correlation function (ξ2) caused by structure growth on scales of 10–80 h−1 Mpc by about 0.15 per cent for low redshifts (0.4 < z < 0.6) and 0.8 per cent for high (0.8 < z < 1.1), a significant fraction of DESI’s error budget. We provide estimates of the ξ2 signal created by intrinsic alignments that can be used to correct this effect, which is necessary to meet DESI’s forecasted precision on measuring the growth rate of structure. While imaging quality varies across DESI’s footprint, we find no significant difference in this effect between imaging regions in the Legacy Imaging Survey.

79 ASTRONOMY AND ASTROPHYSICS↗

Broadband coplanar-waveguide-based impedance-transformed Josephson parametric amplifier

Quantum-limited Josephson parametric amplifiers play a pivotal role in advancing the field of circuit quantum electrodynamics by enabling the fast and high-fidelity measurement of weak microwave signals. Therefore, it is necessary to develop robust parametric amplifiers with low noise, broad bandwidth, and reduced design complexity for microwave detection. However, current broadband parametric amplifiers either have degraded noise performance or rely on complex designs. Here, we present a device based on the broadband impedance-transformed Josephson parametric amplifier that integrates a hornlike coplanar waveguide transmission line, which significantly decreases the design and fabrication complexity while keeping comparable performance. The device shows an instantaneous bandwidth of 700 (200) MHz for 15 (20) dB gain with an average input saturation power of − 110 dBm and near quantum-limited added noise. The operating frequency can be tuned over 1.4 GHz using an external flux bias. We further demonstrate the negligible backaction from our device on a transmon qubit. The amplification performance and simplicity of our device promise its wide adaptation in quantum metrology, quantum communication, and quantum information processing. Published by the American Physical Society 2024

Qing, Bingcheng (ORCID:0000000345227017)↗

Visualizing Fault Induced Traveling Waves In Medium Voltage Systems

Traveling waves are induced in power systems during most transient events in the grid. These waves travel close to the speed of light in overhead lines and 50% to 60% the speed of light in underground cables. Even though traveling wave-based protection schemes for transmission systems are available commercially, traveling waves in medium voltage distribution networks are still in research space. Compared to transmission system, medium voltage distribution systems contain more reflections and refractions. Thus, visualization is challenging and is critical in locating faults in distribution network. To address this visualization challenge, this paper presents an open-source tool to visualize the traveling waves using Bewley lattice approach. The developed visualization tool will be useful for the protection engineers to detect and triangulate fault locations in the medium voltage systems and isolate the faults.

Bewley Lattice↗

Developing a New Polyolefin Precursor for Low-Cost, High-Strength Carbon Fiber

Current high-strength carbon fibers (CFs) are mostly derived from PAN polymer precursor, which are very expensive with limited usage in the high-end products. On the other hand, it has also stimulated research interest to develop new low-cost precursors and manufacturing process. Despite numerous studies, researchers have yet to develop a new polymeric precursor that is less expensive, melt-spinnable, and offers a high C-yield. In this three-year R&D project, we proposed three consecutive research phases, including (i) the development of new polyolefin-based precursors that can be thermally transformed to C material in one heating step under inert atmosphere and achieved a C-yield >80%, which is more than 60% higher than that of current PAN precursor, (ii) With the suitable new polyolefin-based precursor, we can focus on CF manufacturing process, including fiber spinning, stabilization, and carbonization, to form high quality carbon fibers with the desirable polymorphous morphology, and (iii) the investigation of thermal conversion process under tension for converting polyolefin-based precursor fibers to high tensile strength carbon fibers with specific graphite crystallite size, orientation of basal line, order-disorder ratio, fiber diameter, and reduced structural defect (voids). composites.

08 HYDROGEN↗

Improving Predictive Capability in REHEDS Simulations with Fast, Accurate, and Consistent Non-Equilibrium Material Properties

Predictive design of REHEDS experiments with radiation-hydrodynamic simulations requires knowledge of material properties (e.g. equations of state (EOS), transport coefficients, and radiation physics). Interpreting experimental results requires accurate models of diagnostic observables (e.g. detailed emission, absorption, and scattering spectra). In conditions of Local Thermodynamic Equilibrium (LTE), these material properties and observables can be pre-computed with relatively high accuracy and subsequently tabulated on simple temperature-density grids for fast look-up by simulations. When radiation and electron temperatures fall out of equilibrium, however, non-LTE effects can profoundly change material properties and diagnostic signatures. Accurately and efficiently incorporating these non-LTE effects has been a longstanding challenge for simulations. At present, most simulations include non-LTE effects by invoking highly simplified inline models. These inline non-LTE models are both much slower than table look-up and significantly less accurate than the detailed models used to populate LTE tables and diagnose experimental data through post-processing or inversion. Because inline non-LTE models are slow, designers avoid them whenever possible, which leads to known inaccuracies from using tabular LTE. Because inline models are simple, they are inconsistent with tabular data from detailed models, leading to ill-known inaccuracies, and they cannot generate detailed synthetic diagnostics suitable for direct comparisons with experimental data. This project addresses the challenge of generating and utilizing efficient, accurate, and consistent non-equilibrium material data along three complementary but relatively independent research lines. First, we have developed a relatively fast and accurate non-LTE average-atom model based on density functional theory (DFT) that provides a complete set of EOS, transport, and radiative data, and have rigorously tested it against more sophisticated first-principles multi-atom DFT models, including time-dependent DFT. Next, we have developed a tabular scheme and interpolation methods that compactly capture non-LTE effects for use in simulations and have implemented these tables in the GORGON magneto-hydrodynamic (MHD) code. Finally, we have developed post-processing tools that use detailed tabulated non-LTE data to directly predict experimental observables from simulation output.

36 MATERIALS SCIENCE↗

Porewater Geochemical Assessment of Seismic Indications for Gas Hydrate Presence and Absence: Mahia Slope, East of New Zealand’s North Island

We compare sediment vertical methane flux off the Mahia Peninsula, on the Hikurangi Margin, east of New Zealand’s North Island, with a combination of geochemical, multichannel seismic and sub-bottom profiler data. Stable carbon isotope data provided an overview of methane contributions to shallow sediment carbon pools. Methane varied considerably in concentration and vertical flux across stations in close proximities. At two Mahia transects, methane profiles correlated well with integrated seismic and TOPAS data for predicting vertical methane migration rates from deep to shallow sediment. However, at our “control site”, where no seismic blanking or indications of vertical gas migration were observed, geochemical data were similar to the two Mahia transect lines. This apparent mismatch between seismic and geochemistry data suggests a potential to underestimate gas hydrate volumes based on standard seismic data interpretations. To accurately assess global gas hydrate deposits, multiple approaches for initial assessment, e.g., seismic data interpretation, heatflow profiling and controlled-source electromagnetics, should be compared to geochemical sediment and porewater profiles. A more thorough data matrix will provide better accuracy in gas hydrate volume for modeling climate change and potential available energy content.

03 NATURAL GAS↗

Energy Evolution from the Chromosphere to the Heliosphere in the 2021 October 28 Solar Eruption

We perform a detailed study of the energetics for a well-observed solar eruption and flare that occurred on 2021 October 28. This event included a GOES class X1.0 flare, a global extreme-UV (EUV) wave, and a coronal mass ejection (CME) that reached speeds of >2000 km s −1 . The event was observed from a variety of spacecraft in NASA’s Heliophysics System Observatory, including multiple missions near Earth, STEREO-A off the Sun-Earth line, and Solar Orbiter, near the Sun-Earth line at about 0.8 au. Using remote sensing, in situ observations, and in some cases scaling laws based on previous observations, we characterize the following quantities: free magnetic energy, energy in nonthermal electrons, energy in nonthermal ions, bolometric energy, energy deposited in the chromosphere, thermal energy radiated in the flare loops, energy dissipated by the EUV wave, CME kinetic and gravitational potential energy, CME energy flux in the heliosphere, and the energy partition in the CME shock. We find that the total energy released during the event is consistent with estimates of the pre-event stored magnetic energy, and the CME kinetic + potential energy dominates the energy partition.

solar coronal mass ejection shocks↗

Visualizing Fault Induced Traveling Waves in Medium Voltage Systems: Preprint

Traveling waves are induced in power systems during most transient events in the grid. These waves travel close to the speed of light in overhead lines and 50% to 60% the speed of light in underground cables. Even though traveling wave-based protection schemes for transmission systems are available commercially, traveling waves in medium voltage distribution networks are still in research space. Compared to transmission system, medium voltage distribution systems contain more reflections and refractions. Thus, visualization is challenging and is critical in locating faults in distribution network. To address this visualization challenge, this paper presents an open-source tool to visualize the traveling waves using Bewley lattice approach. The developed visualization tool will be useful for the protection and safety engineers to detect and triangulate fault locations in the medium voltage systems and isolate the faults.

Bewley Lattice↗

A Fast Algebraic Multigrid Solver and Accurate Discretization for Highly Anisotropic Heat Flux I: Open Field Lines

We present a novel solver technique for the anisotropic heat flux equation, aimed at the high level of anisotropy seen in magnetic confinement fusion plasmas. Such problems pose two major challenges: (i) discretization accuracy and (ii) efficient implicit linear solvers. We simultaneously address each of these challenges by constructing a new finite element discretization with excellent accuracy properties, tailored to a novel solver approach based on algebraic multigrid (AMG) methods designed for advective operators. We pose the problem in a mixed formulation, introducing the directional temperature gradient as an auxiliary variable. The temperature and auxiliary fields are discretized in a scalar discontinuous Galerkin space with upwinding principles used for discretizations of advection. We demonstrate the proposed discretization’s superior accuracy over other discretizations of anisotropic heat flux, achieving error 1000x smaller for anisotropy ratio of 10 9 , for closed field lines. The block matrix system is reordered and solved in an approach where the two advection operators are inverted using AMG solvers based on approximate ideal restriction, which is particularly efficient for upwind discontinuous Galerkin discretizations of advection. To ensure that the advection operators are nonsingular, in this paper we restrict ourselves to considering open (acyclic) magnetic field lines for the linear solvers. We demonstrate fast convergence of the proposed iterative solver in highly anisotropic regimes where other diffusion-based AMG methods fail.

97 MATHEMATICS AND COMPUTING↗

DeepDiagnostics: A Software Package for Streamlined Posterior Evaluation

Automated prediction techniques like simulation-based inference (SBI) are important tasks for science experiments that produce large amounts of complex, raw data. However, their development remains in its early stages because the uncertainties of these techniques lack sufficient trustworthiness and interpretability. Packages for SBI provide a growing set of diagnostics; however, the software requirements are substantial, as they are tied to the inference technology itself, and the APIs lack adaptability. We introduce the DeepDiagnostics package for diagnosing posteriors from analytic likelihood-based methods and SBI methods, such as neural posterior estimation. DeepDiagnostics produces a comprehensive set of high-quality visualizations and metrics in a highly accessible, easy-to-use, and flexible package. We address all of these goals by providing a command-line inference tool and a Python API that is controlled through a configuration file. The package includes common diagnostics, such as parity plots, corner (covariance) plots, simulation-based calibration (SBC) diagnostics (including posterior coverage and rank histograms), Lemos et al. s PQMass and TARP, Masserano et al. s WALDO, Linhart et al. s LC2ST, as well as credible region diagnostics developed by our group.

Voetberg, Maggie [Fermilab]↗

Spectroscopic observations of progenitor activity 100 days before a Type Ibn supernova

Obtaining spectroscopic observations of the progenitors of core-collapse supernovae is often unfeasible, due to an inherent lack of knowledge as to what stars experience supernovae and when they will explode. In this Letter we present photometric and spectroscopic observations of the progenitor activity of SN 2023fyq before the He-rich progenitor explodes as a Type Ibn supernova. The progenitor of SN 2023fyq shows an exponential rise in flux prior to core collapse. Complex He I emission line features are observed in the progenitor spectra, with a P Cygni-like profile, as well as an evolving broad base with velocities of the order of 10 000 km s −1 . The luminosity and evolution of SN 2023fyq is consistent with a Type Ibn, reaching a peak r -band magnitude of −18.8 mag, although there is some uncertainty regarding the distance to the host, NGC 4388, which is located in the Virgo cluster. We present additional evidence of asymmetric He-rich material being present both prior to and after the explosion of SN 2023fyq, which suggests that this material survived the ejecta interaction. Broad [O I ], C I , and the Ca II triplet lines are observed at late phases, confirming that SN 2023fyq was a genuine supernova, rather than a non-terminal interacting transient. SN 2023fyq provides insight into the final moments of a massive star’s life, demonstrating that the progenitor is likely highly unstable before core collapse.

Brennan, S. J. (ORCID:0000000313256235)↗

A Sample of Massive Black Holes in Dwarf Galaxies Detected via [Fe x] Coronal Line Emission: Active Galactic Nuclei and/or Tidal Disruption Events

The massive black hole (BH) population in dwarf galaxies ( M BH ≲ 10 5 M ⊙ ) can provide strong constraints on the origin of BH seeds. However, traditional optical searches for active galactic nuclei (AGNs) only reliably detect high-accretion, relatively high-mass BHs in dwarf galaxies with low amounts of star formation, leaving a large portion of the overall BH population in dwarf galaxies relatively unexplored. Here, we present a sample of 81 dwarf galaxies ( M $\star$ ≤ 3 × 10 9 M ⊙ ) with detectable [Fe x]λ6374 coronal line emission indicative of accretion onto massive BHs, only two of which were previously identified as optical AGNs. Here, we analyze optical spectroscopy from the Sloan Digital Sky Survey and find [Fe x]λ6374 luminosities in the range L [Fe x] ≈ 10 36 –10 39 erg s –1 , with a median value of 1.6 × 10 38 erg s –1 . The [Fe x]λ6374 luminosities are generally much too high to be produced by stellar sources, including luminous Type IIn supernovae (SNe). Moreover, based on known SNe rates, we expect at most eight Type IIn SNe in our sample. That said, the [Fe x]λ6374 luminosities are consistent with accretion onto massive BHs from AGNs or tidal disruption events (TDEs). We find additional indicators of BH accretion in some cases using other emission line diagnostics, optical variability, and X-ray and radio emission (or some combination of these). However, many of the galaxies in our sample only have evidence for a massive BH based on their [Fe x]λ6374 luminosities. This work highlights the power of coronal line emission to find BHs in dwarf galaxies missed by other selection techniques and to probe the BH population in bluer, lower-mass dwarf galaxies.

79 ASTRONOMY AND ASTROPHYSICS↗

Dry electrodes with a printed cellulose–graphene ink for low-profile strain sensors in electromyography

Dihydrolevoglucosenone, commonly known as Cyrene, is a renewable and fully biodegradable cellulose-waste derived, environmentally friendly solvent, presenting a non-toxic alternative to N-methyl-2-pyrrolidone (NMP). Currently, solution-based processing of graphene and other similar van der Waals solids favor toxic solvents such as NMP, limiting their use for biosensing. However, with the use of Cyrene, bio-compatible printable devices are possible, and studies have already demonstrated its use in temperature and other biosensing methods through screen-printing. Screen-printing unfortunately often requires masks that constrain the minimum acquirable feature size to be above hundreds of centimeters and wastes material, adding to process complexity and cost. Conversely, inkjet-printing is an attractive alternative for the maskless patterning of hierarchically assembled structures, with micron length scales attainable. Graphene's high conductivity positions it ideally for long-wear sensors such as dry electrodes or respiration monitors. Here, we demonstrate the potential of Cyrene-based graphene inks through few-layer inkjet printing on flexible substrates for the first time, to produce non-toxic conductors toward a strain-mediated mechanism for biosensing, used to detect bodily motion for wearable electronics. The challenges overcome in this study include engineering ink chemistry and printing parameters such that Cyrene's relatively high viscosity compared to typical inkjet solvents, still allows for droplet ejection in a conventional material printer, yielding well-resolved clean line-edges in contrast to other solvents that exhibit diffuse line-edges possibly from stray droplets and ink-splashing. Temperature-dependent transport measurements on the inkjet-printed Cyrene-based graphene films showed the conductivity to be largely temperature-invariant but at lower temperatures below 100 K, conductivity decreased, likely as a result of increased inter-membrane separation arising from thermal contraction. Additionally, temperature-dependent Raman spectroscopy showed the red-shift in the G-band, 2D-band and D-band peaks, as temperature increased. As a result, by validating flexion motion detection of the proximal interphalangeal joint demonstrated in this study, our work is the first of its kind to successfully additively manufacture inkjet-printed Cyrene-based graphene strain sensors on flexible substrates for bio-sensing and wearables.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Detecting Low-level Radiation Sources Using Border Monitoring Gamma Sensors

We consider a problem of detecting a low-level radiation source using a network of Gamma spectral sensors placed on the periphery of a monitored region. We propose a computationally light-weight, correlation-based method which is primarily intended for systems with limited computing capacity. Sensor measurements are combined at the fusion by first generating decisions at each time step and then taking their majority vote within a time widow. At each time step, decisions are generated using two strategies: (i) SUM method based on a threshold decision on a correlation statistic derived from measurements from all sensors, and (ii) OR method based on logical-OR of threshold decisions based on correlations statistics of individual sensor measurements. We derive analytical performance bounds for false alarm rates of SUM and OR methods, and show that their performance is enhanced by the temporal smoothing of majority vote within a time window. Using measurements from a test campaign, we generate a border monitoring scenario with twelve 2"x2" NaI Gamma sensors deployed on the periphery of 42m x 42m outdoor region. A Cs-137 source is moved in a straight-line across this region, starting several meters outside and finally moving away from it. We illustrate the performance of both correlation-based detection methods, and compare their performances with each other and with a particle filter method. Overall, under small false-alarm conditions, the OR fusion is found to produce better detection performance.

Sen, Satyabrata↗

AGGREGATE: dAta-driven modelinG preservinG contRollable dEr for outaGe mAnagemenT and rEsiliency (Report for Task 10: Controllability and Observability Analysis (Deliverable D7))

It is common to have less than full observability for distribution systems, as the number of available measurements are not sufficient. Considering increasing penetration of distributed energy resources (DERs), it is imperative to understand and control distribution systems better. Developed for the transmission system, the original numerical observability analysis methods were based on the canonical DC Power Flow (DC-PF) model. However, the DC-PF model is ill-suited for the distribution system in which line resistance to reactance (R/X) ratios can be near unity. In this report, we apply the non-iterative Observability Test (OT) and Observable Island Identification Procedure (OIIP) in to the gain matrix from the distribution system state estimator. Because sensors are few in distribution systems, pseudo-measurements based on historical load profiles and zero-injection virtual measurements are often employed to ensure observability. However, both the observability and the accuracy of the state estimates are uncertain when historical data is limited/unavailable.

42 ENGINEERING↗

SALSAA: a statistical approach to line shapes from an average atom

Ion-Stark line broadening is a key density diagnostic for hot dense plasmas relevant to inertial fusion and astrophysics. It is caused by interactions of a radiating ion with nearby perturbing ions, whose electric microfields lead to changes in bound-bound transition energies. Ion-Stark broadening becomes increasingly difficult to compute for complex, many-electron ions with myriad transitions. In this paper, we propose a simplified approach to ion-Stark broadening based on self-consistent ion distributions and electronic structure from an average-atom model. We find that this approach reproduces the line shape predictions of one traditional method for high-n K-shell emission lines in aluminum ions with accuracy sufficient for density diagnostics in thermal plasmas with equal ion and electron temperatures. We expect that this approach can be extended to provide a reasonable picture of ion-Stark broadening in many-electron ions, enabling rapid calculations of line profiles in complex spectra.

average-atom↗

sOPTICS: a modified density-based algorithm for identifying galaxy groups/clusters and brightest cluster galaxies

A direct approach to studying the galaxy–halo connection is to analyse groups and clusters of galaxies that trace the underlying dark matter haloes, emphasizing the importance of identifying galaxy clusters and their associated brightest cluster galaxies (BCGs). In this work, we test and propose a robust density-based clustering algorithm that outperforms the traditional Friends-of-Friends (FoF) algorithm in the currently available galaxy group/cluster catalogues. Our new approach is a modified version of the Ordering Points To Identify the Clustering Structure (OPTICS) algorithm, which accounts for line-of-sight positional uncertainties due to redshift space distortions by incorporating a scaling factor, and is thereby referred to as sOPTICS. When tested on both a galaxy group catalogue based on semi-analytic galaxy formation simulations and observational data, our algorithm demonstrated robustness to outliers and relative insensitivity to hyperparameter choices. In total, we compared the results of eight clustering algorithms. The proposed density-based clustering method, sOPTICS, outperforms FoF in accurately identifying giant galaxy clusters and their associated BCGs in various environments with higher purity and recovery rate, also successfully recovering 115 BCGs out of 118 reliable BCGs from a large galaxy sample. Furthermore, when applied to an independent observational catalogue without extensive re-tuning, sOPTICS maintains high recovery efficiency, confirming its flexibility and effectiveness for large-scale astronomical surveys.

79 ASTRONOMY AND ASTROPHYSICS↗

BASS. XXIX. The Near-infrared View of the Broad-line Region (BLR): The Effects of Obscuration in BLR Characterization

Virial black hole (BH) mass (M BH ) determination directly involves knowing the broad-line region (BLR) clouds' velocity distribution, their distance from the central supermassive BH (R BLR ), and the virial factor (f). Understanding whether biases arise in M BH estimation with increasing obscuration is possible only by studying a large (N > 100) statistical sample of obscuration-unbiased (hard) X-ray-selected active galactic nuclei (AGNs) in the rest-frame near-infrared (0.8–2.5 μm) since it penetrates deeper into the BLR than the optical. We present a detailed analysis of 65 local Burst Alert Telescope (BAT) selected Seyfert galaxies observed with Magellan/FIRE. Adding these to the near-infrared BAT AGN spectroscopic survey database, we study a total of 314 unique near-infrared spectra. While the FWHMs of Hα and near-infrared broad lines (He i, Paβ, Paα) remain unbiased to either BLR extinction or X-ray obscuration, the Hα broad-line luminosity is suppressed when N H ≳ 10 21 cm –2 , systematically underestimating M BH by 0.23–0.46 dex. Near-infrared line luminosities should be preferred to Hα until N H < 10 22 cm –2 , while at higher obscuration a less-biased R BLR proxy should be adopted. We estimate f for Seyfert 1 and 2 using two obscuration-unbiased M BH measurements, i.e., the stellar velocity dispersion and a BH mass prescription based on near-infrared and X-ray, and find that the virial factors do not depend on the redshift or obscuration, but some broad lines show a mild anticorrelation with M BH . Furthermore, our results show the critical impact obscuration can have on BLR characterization and the importance of the near-infrared and X-rays for a less-biased view of the BLR.

79 ASTRONOMY AND ASTROPHYSICS↗