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At least 523 records · Page 29

Validation of the DESI DR2 measurements of baryon acoustic oscillations from galaxies and quasars

The Dark Energy Spectroscopic Instrument (DESI) Data Release 2 (DR2) galaxy and quasar clustering data represents a significant expansion of data from Data Release 1 (DR1), providing improved statistical precision in baryon acoustic oscillation (BAO) constraints across multiple tracers, including bright galaxies, luminous red galaxies, emission line galaxies, and quasars. In this paper, we validate the BAO analysis of DR2. We present the results of robustness tests on the blinded DR2 data and, after unblinding, consistency checks on the unblinded DR2 data. All results are compared with those obtained from a suite of mock catalogs that replicate the selection and clustering properties of the DR2 sample. We confirm the consistency of DR2 BAO measurements with DR1 while achieving a reduction in statistical uncertainties due to the increased survey volume and completeness. The combined BAO precision, including both statistical and systematic errors, improves from ∼0.52% in DR1 to 0.30% in DR2—a factor of 1.7 gain. We assess the impact of analysis choices, including different data vectors (correlation function vs power spectrum), modeling approaches and systematics treatments, and an assumption of the Gaussian likelihood, finding that our BAO constraints are stable across these variations and assumptions with a few minor refinements to the baseline setup of the DR1 BAO analysis. We summarize a series of pre-unblinding tests that confirmed the readiness of our analysis pipeline, the final systematic errors, and the DR2 BAO analysis baseline. The successful completion of these tests led to the unblinding of the DR2 BAO measurements, ultimately leading to the DESI DR2 cosmological analysis, with their implications for the expansion history of the Universe and the nature of dark energy presented in the DESI key paper (companion paper).

79 ASTRONOMY AND ASTROPHYSICS↗

Draft genome sequences of strains CBS6241 and CBS6242 of the basidiomycetous yeast Filobasidium floriforme

The Tremellomycetes are a species-rich group within the basidiomycete fungi; however, most analyses of this group to date have focused on pathogenic Cryptococcus species within the order Tremellales. Recent genome-assisted studies of other Tremellomycetes have identified interesting features with respect to biotechnological applications as well as the evolution of genes involved in mating and sexual development. Here, we report genome sequences of two strains of Filobasidium floriforme, a species from the order Filobasidiales, which branches basally to the Tremellales, Trichosporonales, and Holtermanniales. The assembled genomes of strains CBS6241 and CBS6242 are 27.4 Mb and 26.4 Mb in size, respectively, with 8314 and 7695 predicted protein-coding genes. Overall sequence identity at nucleic acid level between the strains is 97%. Among the predicted genes are pheromone precursor and pheromone receptor genes as well as two genes encoding homedomain (HD) transcription factors, which are predicted to be part of the mating type (MAT) locus. Sequence analysis indicates that CBS6241 and CBS6242 carry different alleles for both the pheromone/receptor genes as well as the HD transcription factors. Orthology inference identified 1482 orthogroups exclusively found in F. floriforme, some of which were involved in carbohydrate transport and metabolism. Subsequent CAZyme repertoire characterization identified 267 and 247 enzymes for CBS6241 and CBS6242, respectively, the second highest number of CAZymes among the analyzed Tremellomycete species. In addition, F. floriforme contains five CAZymes absent in other species and several plant-cell-wall degrading CAZymes with the highest copy number in Tremellomycota, indicating the biotechnological potential of this species.

59 BASIC BIOLOGICAL SCIENCES↗

Effects of spatial variability in vegetation phenology, climate, landcover, biodiversity, topography, and soil property on soil respiration across a coastal ecosystem

Coastal terrestrial-aquatic interfaces (TAIs) are crucial contributors to global biogeochemical cycles and carbon exchange. A systematic evaluation of the interaction between coastal catchment properties and carbon dioxide (CO2) emission by soil respiration is significant for assessing carbon dynamics and predicting the future trajectory of atmospheric CO2 concentrations in coastal TAIs. The soil CO2 efflux in these transition zones is however poorly understood due to the high spatiotemporal dynamics of TAIs, as various sub-ecosystems in this region are compressed and expanded by complex influences of tides, changes in river levels, climate, and land use. We focus on the Chesapeake Bay region to (i) investigate the spatial heterogeneity of the coastal ecosystem and identify spatial zones with similar environmental characteristics based on the spatial data layers, including vegetation index (kNDVI), climate, landcover, diversity, topography, soil property, and relative tidal elevation; (ii) understand the primary driving factors affecting soil respiration within sub-ecosystems of the coastal ecosystem. Specifically, we employed hierarchical clustering analysis to identify spatial regions with distinct environmental characteristics, followed by the determination of main driving factors using Random Forest regression and SHapley Additive exPlanations. Maximum and minimum temperature are the main drivers common to all sub-ecosystems, while each region also has additional unique major drivers that differentiate them from one another. Precipitation exerts an influence on vegetated lands, while soil pH value holds importance specifically in forested lands. In croplands characterized by high clay content and low sand content, the significant role is attributed to bulk density. Wetlands demonstrate the importance of both elevation and sand content, with clay content being more relevant in non-inundated wetlands than in inundated wetlands. The topographic wetness index significantly contributes to the mixed vegetation areas, including shrub, grass, pasture, and forest. Additionally, our research reveals that dense vegetation land covers and urban/developed areas exhibit distinct soil property drivers. Overall, there is no one-size-fits-all approach to modeling carbon fluxes in coastal TAIs, and our study highlights the importance of further research and monitoring practices to improve our understanding of carbon dynamics and promote the sustainable management of coastal TAIs.

54 ENVIRONMENTAL SCIENCES↗

Phenol-soluble modulins PSMα3 and PSMβ2 form nanotubes that are cross-α amyloids

The formation of cross-α amyloids has been shown by crystallographic analysis of the highly cytolytic peptide PSMα3, a secreted virulence factor associated with the human pathogen Staphylococcus aureus . However, the relationship of the crystallographic cross-α structure to self-assembled filaments of PSMα3 and its relevance to other phenol-soluble modulin (PSM) peptides remained an open question. We report the cryo–electron microscopy structural analysis of three nanotubes derived from self-assembly of PSMα3 and PSMβ2 peptides in aqueous solution. In each case, the nanotubes are derived from self-association of cross-α amyloid protofilaments. The self-assembly behavior of S. aureus PSMα3 and PSMβ2 peptides provides strong evidence for the importance of the cross-α fold in self-assembled peptide and protein structures in general and for PSMs in particular.

59 BASIC BIOLOGICAL SCIENCES↗

A compendium and meta-analysis of flatband potentials for TiO2, ZnO, and SnO2 semiconductors in aqueous media

Semiconductor/electrolyte interfaces are of great interest to numerous scientific fields including renewable energy, (photo)electrochemistry, and energy storage. The semiconductor flatband potential is a key parameter in locating the conduction band minimum or valence band maximum of the semiconductor material in electrolyte. Despite its importance for quantifying the energetic location of the semiconductor bands, literature reports for the same material demonstrate significant variability in the flatband potential. In this compendium and meta-analysis, reported flatband potentials of the common semiconductor materials TiO2, SnO2, and ZnO in aqueous electrolyte were compiled and assessed to quantify the spread in literature flatband potentials as well as determine the factors that lead to the significant spread. For TiO2, SnO2, and ZnO, literature flatband potentials referenced to the reversible hydrogen electrode span a range of nearly 2 V each. Flatband potential tabulations were separated by variables such as the solution pH, the crystalline polymorph, the crystal facet, the morphology, and the dimensions or combinations of these variables to assess the factors that contribute to the observed spread. Important and surprising findings from these categorizations are summarized: (1) Even for the narrowest categorizations, the spread in flatband potential is still large. (2) Flatband potentials of TiO2 and SnO2 follow the expected Nernstian dependence with solution pH. ZnO materials deviate from this Nernstian dependence. (3) In the aggregate, there is no statistically significant difference in the reported flatband potentials of anatase and rutile TiO2. Single crystal tabulations were the only distributions to have statistically significant differences in the flatband potential between anatase and rutile TiO2. (4) Anatase TiO2 materials with a nanotube morphology appear to have a +400 mV difference in mean flatband potential compared to all other morphologies, but we argue that this is likely due to widespread misuse of the Mott–Schottky analysis. Other interesting findings are revealed within the spread of literature flatband potentials, and possible explanations are provided to generate discussion. We also briefly review and discuss common techniques that were used to determine the flatband potential and the pitfalls/criticisms of these techniques. Last, we discuss some ways in which future research on the determination of the flatband potential can be performed to improve the reliability of reported values and the quality of the work. In total, the results from this meta-analysis suggest multiple factors can affect the measured flatband potential and that an abundance of caution should be applied when attempting to quantify the flatband potential of complex or nanostructured systems.

Patel, Milan Y. (ORCID:0000000291948141)↗

Factorization and resummation of QED radiative corrections for neutron beta decay

Details of the two-loop analysis of long-distance QED radiative corrections to neutron beta decay are presented. Explicit expressions are given for hard, jet, and soft functions appearing in the factorization formula that describes the limit of small electron mass and large electron energy. Numerical enhancements from the infrared region are resummed using renormalization group methods. Power corrections, cancellation of singularities in the small-mass expansion, renormalization scheme dependence, and bound-state effects are also discussed. These results provide the most precise determination of long-distance radiative corrections to neutron beta decay and impact the determination of |𝑉 𝑢⁢𝑑 | from the measured neutron lifetime and thus set a target for uncertainty reductions in the experimental and short-distance inputs.

Beta decay↗

Failure analysis of field-failed bypass diodes

Defective bypass diodes are often found as the largest factor leading to power loss in solar modules. Here, we report on failure mechanisms by investigating shunted bypass diodes from a rooftop installation, using a combination of multiple characterizations including current–voltage analysis, thermal-runaway testing, X-ray computed tomography, lock-in thermography, focused ion-beam cross-section imaging, chemical decapsulation, optical microscopy, and scanning electron microscopy with energy-dispersive X-ray spectroscopy. Differing from static discharge typically associated with lightning strikes on modules, we found diode failure by the mechanism of thermal damage under continuous, long-term overstress in forward bias. Our conclusion is based on evidence of energy dissipated—the small to medium extent of melt-through on the Schottky diode face. The diode failure shows distortions or roughening of the Schottky diode metal-semiconductor interface with the die attach, and some failures are accompanied by die-attach solder melting. We propose that nonuniform irradiance on the modules caused diode shunting due to extended periods of heat dissipation in the modules, because modules in this string were placed in two different orientations. In contrast, a second parallel module string of the same module type on the same rooftop with a unique plane of array did not show any diode failures. The thermal damage failure of melt-through was caused by the long-term current generated by overstressing of diodes that may have had crystalline and impurity defects.

14 SOLAR ENERGY↗

Advancing Li-plating detection: Motivating a multi-signal correlation approach

Facilitating fast charging in lithium-ion batteries (LiBs) is often linked to Li-plating, which harms performance, longevity, and safety. Early detection of Li-plating is essential for rapid technological development and for preventing performance deterioration and ensuring safety during operation. Fast and real-time detection, using commonly collected measurements like voltage (V), current (I), temperature (T), and pressure (P), is highly desirable. Existing standalone methods relying on electrochemical and mechanical signatures, using half, smaller, or specially designed cells often operated at lower temperatures, fail to account for real-world fast-charging conditions. These signatures may also have inherent unreliability in aged LiBs, a phenomenon currently not-well understood. All these uncertainties have complicated practical implementation of a robust Li-plating detection technique. This study, through multiple case studies involving real-world fast-charging conditions using automotive-grade 11.6 Ah LiBs, shows that many single signal-based diagnostic techniques may be inadequate to detect Li-plating. Among various signatures, end-of-charge rest pressure, differential pressure-sensing, and end-of-charge rest voltage were identified as particularly useful in detecting Li-plating. Furthermore, A multi-signal-based detection technique is shown to be more robust in detecting Li-plating. Using both fresh and aged cells, the results and analysis highlight how detection capabilities are influenced by various factors, including battery design, size, charging speed, operating temperature, and degradation level. Adopting such a multi-signal Li-plating detection approach may be instrumental in the rapid development of battery technology in laboratories, as well as ensuring the enhanced safety of next-generation LiBs in real-world fast-charging applications.

25 ENERGY STORAGE↗

Column separation of tetravalent cerium fission products from trivalent rare earth radio-isotopes

Rapid and efficient isolation of individual rare earth element (REE) radioisotopes from complex mixtures is necessary to support the fields of nuclear forensics, medical isotope production and nuclear physics measurements. The separations must be robust and generate sufficiently high purity samples for subsequent radiological analysis. Current methodologies utilize a laborious two step Ce(IV)-iodate precipitation followed by Ce(IV)-nitrate di-(2-ethylhexyl)phosphoric acid/n-heptane extraction. This work reports an alternative method to isolate Ce fission product isotopes equilibrated with milligrams of cold carrier, from the remaining REE’s using a Ce(IV)/LN-resin (Eichrom Technologies) based separation. Optimization of Ce(IV) loading, REE(III) elution volume and subsequent Ce(III) stripping step utilized 166m Ho tracer. Mixed fission product experiments provided a further test of this LN-resin method, with analysis of purified 141/144 Ce, 147 Nd and 91 Y. Overall, while decontamination factors were lower for the LN-resin method, (vs. the combined precipitation/extraction) the simplicity of the technique and the satisfactory fission product analysis results point to the efficacy of this method.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

A near magnetic-to-kinetic energy equipartition flare from the relativistic jet in AO 0235 + 164 during 2013–2019

ABSTRACT We present the multiwavelength flaring activity of the blazar AO 0235 + 164 during its recent active period from 2013 to 2019. From a discrete correlation function analysis, we find a significant ($\gt 95~{{\ \rm per\ cent}}$) correlation between radio and gamma-ray light curves with flares at longer wavelengths following flares at shorter wavelengths. We identify a new jet component in 43 GHz Very Long Baseline Array data that was ejected from the radio core on MJD $57246^{+26}_{-30}$ (2015 August 12), during the peak of the 2015 radio flare. From the analysis of the jet component, we derived a Doppler factor of δvar = 28.5 ± 8.4, a bulk Lorentz factor of $\Gamma =16.8^{+3.6}_{-3.1}$, and an intrinsic viewing angle of $\theta _{\rm v}=1.42^{+1.07}_{-0.52}\textrm {~degrees}$. Investigation of the quasi-simultaneous radio data revealed a partially absorbed spectrum with the turnover frequency varying in the range of 10−70 GHz and the peak flux density varying in the range of 0.7−4 Jy. We find the synchrotron self-absorption magnetic field strength to be $B_{\rm SSA}=15.3^{+12.6}_{-14.0}\textrm {~mG}$ at the peak of the 2015 radio flare, which is comparable to the equipartition magnetic field strength of $B_{\rm EQ}=43.6^{+10.6}_{-10.4}\textrm {~mG}$ calculated for the same epoch. Additional analysis of the radio emission region in the relativistic jet of AO 0235 + 164 suggests that it did not significantly deviate from equipartition during its recent flaring activity.

Astronomy & Astrophysics↗

New physics versus quenching factors in Coherent Neutrino Scattering

Recent results on the Coherent Elastic Neutrino-Nucleus Scattering (CEνNS) on germanium present significant discrepancies among experiments. We perform a combined analysis of the Dresden-II, CONUS+ and COHERENT data, quantifying the impact of quenching factor uncertainties on their CEνNS cross section measurement. No choice of quenching factor can bring these three data sets into mutual agreement, whereas the combination of COHERENT with either Dresden-II or CONUS+ agrees well albeit for very different quenching factors. We further study the quenching factor dependence on the sensitivity of these experiments to a large neutrino magnetic moment, finding that the constraints can vary by up to an order of magnitude. Our work highlights the importance of reducing this uncertainty on quenching factors in order to probe new physics from neutrinos at the low-energy frontier.

neutrino interactions↗

On the detectability of the moving lens signal in CMB experiments

Abstract Upcoming cosmic microwave background (CMB) experiments are expected to detect new signals probing interaction of CMB photons with intervening large-scale structure. Among these the moving-lens effect, the CMB temperature anisotropy induced by cosmological structures moving transverse to our line of sight, is anticipated to be measured to high significance in the near future. In this paper, we investigate two possible strategies for the detection of this signal: pairwise transverse-velocity estimation and oriented stacking. We expand on previous studies by including in the analysis realistic simulations of competing signals and foregrounds. We confirm that the moving lens effect can be detected at ≥ 10σlevel by a combination of CMB-S4 and LSST surveys. We show that the limiting factors in the detection depend on the strategy: for the stacking analysis, correlated extragalactic foregrounds, namely the cosmic infrared background and thermal Sunyaev Zel'dovich effect, play the most important role. The addition of foregrounds make the signal-to-noise ratio be most influenced by large and nearby objects. As for the pairwise detection, halo lensing and pair number counts are the main issues. In light of our findings, we elaborate on possible strategies to improve the analysis approach for the moving lens detection with upcoming experiments. We also deliver to the community all the simulations and tools we developed for this study.

Astronomy & Astrophysics↗

Solar PV and BESS Plant-Level Voltage Control and Interactions: Experiments and Analysis

In real world operation, low-frequency oscillations associated with plant-level voltage control of inverter-based resources (IBRs) have been a concern of grid operators. Here, this research aims to demonstrate and analyze the effect of plant-level voltage control on system stability and potential interactions among IBRs. The experiment results of a 13.2-kV system interconnected with two IBRs—a 1-MW battery energy storage system (BESS) and a 430-kW solar photovoltaic (PV) plant—are presented. Both 0.5-Hz and 3-Hz oscillations become visible at certain conditions. The phenomenon is further explained by use of a feedback system consisting of the plant-level droop control and the effect of reactive power or var injection on voltage. The main components of the block diagram are obtained via frequency scan measurements. The analysis offers an understanding of the main contributors and other influencing factors of the 3-Hz and 0.5-Hz modes. It also reveals the role of the volt-var droop gain, the low-pass filter time constant, and the system impedance in stability.

14 SOLAR ENERGY↗

Randomized Projection for Rank-Revealing Matrix Factorizations and Low-Rank Approximations

Rank-revealing matrix decompositions provide an essential tool in spectral analysis of matrices, including the Singular Value Decomposition (SVD) and related low-rank approximation techniques. QR with Column Pivoting (QRCP) is usually suitable for these purposes, but it can be much slower than the unpivoted QR algorithm. For large matrices, the difference in performance is due to increased communication between the processor and slow memory, which QRCP needs in order to choose pivots during decomposition. Our main algorithm, Randomized QR with Column Pivoting (RQRCP), uses randomized projection to make pivot decisions from a much smaller sample matrix, which we can construct to reside in a faster level of memory than the original matrix. This technique may be understood as trading vastly reduced communication for a controlled increase in uncertainty during the decision process. Furthermore, for rank-revealing purposes, the selection mechanism in RQRCP produces results that are the same quality as the standard algorithm, but with performance near that of unpivoted QR (often an order of magnitude faster for large matrices). Additionally, we also propose two formulas that facilitate further performance improvements. The first efficiently updates sample matrices to avoid computing new randomized projections. The second avoids large trailing updates during the decomposition in truncated low-rank approximations. Our truncated version of RQRCP also provides a key initial step in our truncated SVD approximation, TUXV. These advances open up a new performance domain for large matrix factorizations that will support efficient problem-solving techniques for challenging applications in science, engineering, and data analysis.

97 MATHEMATICS AND COMPUTING↗

Thermal loading analysis of the ring injection dump for the Spallation Neutron Source facility

The ring injection dump (RID) is the largest beam dump in the Spallation Neutron Source facility at Oak Ridge National Laboratory and accepts a fraction of the beam from the ring that is not captured in the ring during injection. Thermo-fluid modeling of the RID components was performed during the initial design by using the software ANSYS CFX to characterize the power rating for the RID. From the calculations, the power rating was lowered from 200 kW to 150 kW, at 1.3 GeV beam energy due to concerns regarding the heating of the concrete structure. The Proton Power Upgrade project scope included reevaluating the power limit to the RID in anticipation that increasing it would provide more operational flexibility. The focus was on the shielding because it was the limiting factor, and data collected from thermocouples installed on the structure were used to benchmark the analysis. A three-stage process was adopted in the latest study. First, the already existing steady-state calculations were validated and extended with the latest Monte Carlo N-Particle source term calculations. Second, transient calculations were conducted to capture the dynamic state of the system in response to the energy dumped to the RID during the following operational period of the beam from 2005–2019 (14 years), and sensitivity analyses of crucial parameters were performed to benchmark the model with reasonable accuracy. Finally, an idealized transient cycle analysis was conducted with realistic duty factors to predict the temperature distribution at higher beam powers. Overall, the results confirmed the accuracy of the original steady state model but allowed the development of a new validated transient model with higher accuracy for future analyses.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Data Assimilation using Non-invasive Monte Carlo Sensitivity Analysis of Reactor Kinetics Parameters

Accurately predicting the criticality of an experiment before interacting with the experimental components is very important for criticality safety. Radiation transport software can be utilized to calculate the effective neutron multiplication factor of a nuclear system. Because of the integral nature of the effective neutron multiplication factor, the value calculated contains various sources of nuclear-data induced uncertainty. The sensitivity analysis and data assimilation technique presented in this paper exhibit one possible method of identifying and reducing the effective neutron multiplication factor nuclear-data induced uncertainty. The results presented in this work show that it is possible to use relative sensitivity coefficients of the prompt neutron decay constant and the effective delayed neutron fraction to 239 Pu nuclear data to reduce nuclear-data induced uncertainties in the effective neutron multiplication factor. This work has been utilized by members of the Los Alamos National Laboratory project EUCLID (Experiments Underpinned by Computational Learning for Improvements in Nuclear Data) for optimally designing a new experiment, which will be used to reduce compensating errors in 239 Pu nuclear data.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Oscillation Risks of Grid-Following and Grid-Forming Inverter-Based Resources in Series-Compensated Networks

Here, this paper investigates the dynamic behavior of a grid-connected inverter-based resource (IBR) when connected radially to a series compensated line. Potential interactions between the series compensation and the IBR have been identified for both types: grid-following (GFL) or grid-forming (GFM). The study begins with electromagnetic transient (EMT) simulations to demonstrate stability issues. Subsequently, nonlinear analytical models are formulated in the dq frame, validated against the EMT simulation, and leveraged to assess eigenvalues and participation factors. Influencing factors of the dominant oscillation modes have been identified. The analysis results show that series compensation may make a mode associated with the synchronization unit unstable. Furthermore, customized feedback systems are built for the synchronizing loop. Series compensation can increase the sensitivity of the voltage phase angle towards the synchronizing angle, and introduce phase lag in the real power response towards the synchronizing angle. These factors may cause interactions with the phase-locked loop in GFL-IBR systems and with power-based synchronization in GFM-IBR systems, potentially leading to instability.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Extensive analysis of reconstruction algorithms for DESI 2024 baryon acoustic oscillations

Reconstruction of the baryon acoustic oscillation (BAO) signal has been a standard procedure in BAO analyses over the past decade and has helped to improve the BAO parameter precision by a factor of ∼2 on average. The Dark Energy Spectroscopic Instrument (DESI) BAO analysis for the first year (DR1) data uses the “standard” reconstruction framework, in which the displacement field is estimated from the observed density field by solving the linearized continuity equation in redshift space, and galaxy and random positions are shifted in order to partially remove non-linearities. There are several approaches to solving for the displacement field in real survey data, including the multigrid (MG), iterative Fast Fourier Transform (iFFT), and iterative Fast Fourier Transform particle (iFFTP) algorithms. In this work, we analyze these algorithms and compare them with various metrics including two-point statistics and the displacement itself using realistic DESI mocks. We focus on three representative DESI samples, the emission line galaxies (ELG), quasars (QSO), and the bright galaxy sample (BGS), which cover the extreme redshifts and number densities, and potential wide-angle effects. We conclude that the MG and iFFT algorithms agree within 0.4% in post-reconstruction power spectrum on BAO scales with the RecSym convention, which does not remove large-scale redshift space distortions (RSDs), in all three tracers. The RecSym convention appears to be less sensitive to displacement errors than the RecIso convention, which attempts to remove large-scale RSDs. However, iFFTP deviates from the first two; thus, we recommend against using iFFTP without further development. In addition, we provide the optimal settings for reconstruction for five years of DESI observation. The analyses presented in this work pave the way for DESI DR1 analysis as well as future BAO analyses.

79 ASTRONOMY AND ASTROPHYSICS↗