An ultra-dynamic anion-cluster-based organic framework
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37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
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Spatially Accelerated Winding Numbers for Curved Geometry
The generalized winding number (GWN) is a scalar field that supports robust containment queries on curved geometry, including non-watertight, overlapping, and nested boundary representations. While queries can be easily parallelized over samples, direct evaluation on parametric curves and surfaces remains costly for large and complex models. Fast, state-of-the-art GWN approaches leverage a spatial index to approximate the GWN, typically coupled with a Taylor expansion which approximates the GWN contribution for far clusters of geometric primitives. However, such methods operate only on discrete inputs such as triangle meshes and point clouds, and would introduce containment errors near boundaries if applied to curved input. We extend support for fast GWN evaluation over arbitrary collections of NURBS curves in 2D and trimmed NURBS patches in 3D via a Bounding Volume Hierarchy that stores efficiently precomputed moment data in the hierarchy nodes. When querying the hierarchy, approximations for far clusters are used alongside direct evaluation for nearby NURBS primitives, achieving sub-linear complexity while preserving the geometric features in the vicinity of the query point. Central to our performance improvements is an adaptive subdivision strategy for NURBS primitives during a preprocessing phase, creating better spatial partitions while retaining the same accuracy for containment decisions as a direct evaluation. We demonstrate the performance and accuracy of our approach across a large collection of 2D and 3D datasets.
Computer science↗
Phylogenomics and Comparative Genomics Highlight Specific Genetic Features in Ganoderma Species
The Ganoderma species in Polyporales are ecologically and economically relevant wood decayers used in traditional medicine, but their genomic traits are still poorly documented. In the present study, we carried out a phylogenomic and comparative genomic analyses to better understand the genetic blueprint of this fungal lineage. We investigated seven Ganoderma genomes, including three new genomes, G. australe, G. leucocontextum, and G. lingzhi. The size of the newly sequenced genomes ranged from 60.34 to 84.27 Mb and they encoded 15,007 to 20,460 genes. A total of 58 species, including 40 white-rot fungi, 11 brown-rot fungi, four ectomycorrhizal fungi, one endophyte fungus, and two pathogens in Basidiomycota, were used for phylogenomic analyses based on 143 single-copy genes. It confirmed that Ganoderma species belong to the core polyporoid clade. Comparing to the other selected species, the genomes of the Ganoderma species encoded a larger set of genes involved in terpene metabolism and coding for secreted proteins (CAZymes, lipases, proteases and SSPs). Of note, G. australe has the largest genome size with no obvious genome wide duplication, but showed transposable elements (TEs) expansion and the largest set of terpene gene clusters, suggesting a high ability to produce terpenoids for medicinal treatment. G. australe also encoded the largest set of proteins containing domains for cytochrome P450s, heterokaryon incompatibility and major facilitator families. Besides, the size of G. australe secretome is the largest, including CAZymes (AA9, GH18, A01A), proteases G01, and lipases GGGX, which may enhance the catabolism of cell wall carbohydrates, proteins, and fats during hosts colonization. The current genomic resource will be used to develop further biotechnology and medicinal applications, together with ecological studies of the Ganoderma species.
59 BASIC BIOLOGICAL SCIENCES↗
Coupled-Cluster Theory Employing Approximate Integrals: An Approach to Avoid the Input/Output and Storage Bottlenecks
By representing orbital products in an expansion basis, certain classes of two-electron integrals are approximated for use in CCSD(T) calculations (singles and doubles coupled-cluster plus a perturbational estimate of the effects of connected triple excitations). This leads to a very large reduction in disk storage and input/output requirements, with usually only a modest increase in computational effort. The new procedure will allow very large CCSD(T) calculations to be undertaken, limited only by available processor time. Using the molecular basis as the expansion basis, explicit numerical comparisons of equilibrium geometries, harmonic frequencies, and energy differences indicate that the error due to the use of approximate integrals is less than the error associated with truncation of the molecular basis set.
Rendell, Alistair P.↗
Ultra high resolution molecular beam cars spectroscopy with application to planetary atmospheric molecules
The measurement of high resolution pulsed and continuous wave (CW) coherent anti-Stokes Raman spectroscopy (CARS) measurements in pulsed and steady state supersonic expansions were demonstrated. Pulsed molecular beam sources were characterized, and saturation of a Raman transition and, for the first time, the Raman spectrum of a complex molecular cluster were observed. The observation of CW CARS spectra in a molecular expansion and the effects of transit time broadening is described. Supersonic expansion is established as a viable technique for high resolution Raman spectroscopy of cold molecules with resolutions of 100 MH2.
Byer, R. L.↗
Scalable generalized screening for high-order terms in the many-body expansion: Algorithm, open-source implementation, and demonstration
The many-body expansion lies at the heart of numerous fragment-based methods that are intended to sidestep the nonlinear scaling of ab initio quantum chemistry, making electronic structure calculations feasible in large systems. In principle, inclusion of higher-order n-body terms ought to improve the accuracy in a controllable way, but unfavorable combinatorics often defeats this in practice and applications with n ≥ 4 are rare. Here, we outline an algorithm to overcome this combinatorial bottleneck, based on a bottom-up approach to energy-based screening. This is implemented within a new open-source software application (“Fragme∩t”), which is integrated with a lightweight semi-empirical method that is used to cull subsystems, attenuating the combinatorial growth of higher-order terms in the graph that is used to manage the calculations. This facilitates applications of unprecedented size, and we report four-body calculations in (H2O)64 clusters that afford relative energies within 0.1 kcal/mol/monomer of the supersystem result using less than 10% of the unique subsystems. We also report n-body calculations in (H2O)20 clusters up to n = 8, at which point the expansion terminates naturally due to screening. These are the largest n-body calculations reported to date using ab initio electronic structure theory, and they confirm that high-order n-body terms are mostly artifacts of basis-set superposition error.
Chemistry↗
Numerical experiments on the clustering of galaxies
Consistent and robust growth rates for disturbances which lead to galaxy clustering are obtainable with a precision of 1-2 percent, in numerical experiments that encompass such conditions as expansion, nonexpansion, and parameter variations. The experiments have given attention to the dominant physical processes of gravitational clustering in an expanding universe of conventional matter, and are based on n-body integrations for 100,000 particles responding self-consistently to forces of self-gravitation with periodic boundary conditions. Observed structures of the scale of galaxy clusters and superclusters are most easily described in terms of matter swept away from growing empty regions. The result of this process has a cellular appearance which resembles clustering of the scale of large voids and superclusters.
Miller, R. H.↗
The completed SDSS-IV extended baryon oscillation spectroscopic survey: pairwise-inverse probability and angular correction for fibre collisions in clustering measurements
ABSTRACT The completed extended Baryon Oscillation Spectroscopic Survey (eBOSS) catalogues contain redshifts of 344 080 quasars at 0.8 < z < 2.2, 174 816 luminous red galaxies between 0.6 < z < 1.0, and 173 736 emission-line galaxies over 0.6 < z < 1.1 in order to constrain the expansion history of the Universe and the growth rate of structure through clustering measurements. Mechanical limitations of the fibre-fed spectrograph on the Sloan telescope prevent two fibres being placed closer than 62 arcsec in a single pass of the instrument. These ‘fibre collisions’ strongly correlate with the intrinsic clustering of targets and can bias measurements of the two-point correlation function resulting in a systematic error on the inferred values of the cosmological parameters. We combine the new techniques of pairwise-inverse probability and the angular upweighting (PIP+ANG) to correct the clustering measurements for the effect of fibre collisions. Using mock catalogues, we show that our corrections provide unbiased measurements, within data precision, of both the projected $\rm {\mathit{ w}_p}\left(\mathit{ r}_p\right)$ and the redshift-space multipole ξ(ℓ = 0, 2, 4)(s) correlation functions down to $0.1\, h^{-1}{\rm Mpc}$, regardless of the tracer type. We apply the corrections to the eBOSS DR16 catalogues. We find that, on scales $s\gtrsim 20\, h^{-1}{\rm Mpc}$ for ξℓ, as used to make baryon acoustic oscillation and large-scale redshift-space distortion measurements, approximate methods such as nearest-neighbour upweighting are sufficiently accurate given the statistical errors of the data. Using the PIP method, for the first time for a spectroscopic program of the Sloan Digital Sky Survey, we are able to successfully access the one-halo term in the clustering measurements down to $\sim 0.1\, h^{-1}{\rm Mpc}$ scales. Our results will therefore allow studies that use the small-scale clustering to strengthen the constraints on both cosmological parameters and the halo occupation distribution models.
79 ASTRONOMY AND ASTROPHYSICS↗
Galaxy bias in the era of LSST: perturbative bias expansions
Upcoming imaging surveys will allow for high signal-to-noise measurements of galaxy clustering at small scales. In this work, we present the results of the Rubin Observatory Legacy Survey of Space and Time (LSST) bias challenge, the goal of which is to compare the performance of different nonlinear galaxy bias models in the context of LSST Year 10 (Y10) data. Specifically, we compare two perturbative approaches, Lagrangian perturbation theory (LPT) and Eulerian perturbation theory (EPT) to two variants of Hybrid Effective Field Theory (HEFT), with our fiducial implementation of these models including terms up to second order in the bias expansion as well as nonlocal bias and deviations from Poissonian stochasticity. Here, we consider a variety of different simulated galaxy samples and test the performance of the bias models in a tomographic joint analysis of LSST-Y10-like galaxy clustering, galaxy-galaxy-lensing and cosmic shear. We find both HEFT methods as well as LPT and EPT combined with non-perturbative predictions for the matter power spectrum to yield unbiased constraints on cosmological parameters up to at least a maximal scale of k max = 0.4 Mpc -1 for all samples considered, even in the presence of assembly bias. While we find that we can reduce the complexity of the bias model for HEFT without compromising fit accuracy, this is not generally the case for the perturbative models. We find significant detections of non-Poissonian stochasticity in all cases considered, and our analysis shows evidence that small-scale galaxy clustering predominantly improves constraints on galaxy bias rather than cosmological parameters. These results therefore suggest that the systematic uncertainties associated with current nonlinear bias models are likely to be subdominant compared to other sources of error for tomographic analyses of upcoming photometric surveys, which bodes well for future galaxy clustering analyses using these high signal-to-noise data.
79 ASTRONOMY AND ASTROPHYSICS↗
Observed impacts of large wind farms on grassland carbon cycling
Deployment of wind energy is an essential renewable energy source that mitigates climate change and reduces air pollution. Over the last several decades, wind energy development has increased worldwide, expanding from ~20 to ~900 GW (gigawatt) during 2001-2022. Nonetheless, researchers have identified unintended consequences of wind energy on microclimate via turbine-altered surface-atmosphere exchanges of energy, momentum, mass, and trace gases. Based on multi-source observations and models, researchers also have drawn some conclusions that wind farms could warm the land surface, especially at night, at regional and continental scales. Consequently, altered microclimates at wind farms may affect vegetation productivity and carbon sequestration, two critically important ecosystem services related to carbon dynamics; however, such potential impacts and driving mechanisms remain poorly understood. Wind energy deployment is increasing globally to meet carbon neutrality goals, with upscaling of onshore wind power capacity projected to grow from 542 GW in 2018 to 1787 and 5044 GW by 2030 and 2050, respectively. Furthermore, increased demand for wind energy deployment may lead to much larger wind farms in open, expansive landscapes. In turn, a large array of geographically clustered wind turbines could collectively modify local microclimate and amplify turbine-atmosphere interactions, which, if large enough, may produce detectable impacts on ecosystem dynamics. Thus, identifying and quantifying the potential impacts of wind farms on carbon-related ecosystem services may facilitate sustainable wind energy development globally.
17 WIND ENERGY↗
Final-state interactions and spin structure in E 1 breakup of Li 11 in halo effective field theory
In this work, we calculate the E1 breakup of the 2n halo nucleus 11 Li in halo effective field theory (Halo EFT) at leading order. In Halo EFT, 11 Li is treated as a three-body system of a 9 Li core and two neutrons. We present a detailed investigation of final-state interactions (FSIs) in the neutron-neutron (nn) and neutron-core (nc) channels. We employ Møller operators to formulate an expansion scheme that satisfies the non-energy-weighted cluster sum rule and successively includes higher-order terms in the multiple-scattering series for the FSI. Computing the E1 strength up to third order in this scheme, we observe apparent convergence and good agreement with experiment. The neutron-neutron FSI is by far the most important contribution and largely determines the maximum value of the E1 distribution. However, inclusion of nc FSI does shift the peak position to slightly lower energies. Moreover, we investigate the sensitivity of the E1 response to the spin structure of the neutron- 9 Li interaction. We contrast results for an interaction that is the same in the spin-1 and spin-2 channels with one that is only operative in the spin-2 channel, and find that good agreement with experimental data is only obtained if the interaction is present in both spin channels. The latter case is shown to be equivalent to a calculation in which the spin of 9 Li is neglected.
73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
Converting dark matter to dark radiation does not solve cosmological tensions
Tensions between cosmological parameters (in particular the local expansion rate H 0 and the amplitude of matter clustering S8) inferred from low-redshift data and data from the cosmic microwave background (CMB) and large-scale structure (LSS) experiments have inspired many extensions to the standard cosmological model, LCDM. Models which simultaneously lessen both tensions are of particular interest. We consider one scenario with the potential for such a resolution, in which some fraction of the dark matter has converted into dark radiation since the release of the CMB. Such a scenario encompasses and generalizes the more standard "decaying dark matter" model, allowing additional flexibility in the rate and time at which the dark matter converts into dark radiation. In this paper, we constrain this scenario with a focus on exploring whether it can solve (or reduce) these tensions. We find that such a model is effectively ruled out by CMB data, in particular by the reduced peak-smearing due to CMB lensing on the power spectrum and the excess integrated Sachs--Wolfe (ISW) signal caused by the additional dark energy density required to preserve flatness after dark matter conversion into dark radiation. Thus, such a model does not have the power to reduce these tensions without further modifications. This conclusion extends and generalizes related conclusions derived for the standard decaying dark matter model.
79 ASTRONOMY AND ASTROPHYSICS↗
Cosmological preference for a negative neutrino mass
The most precise determination of the sum of neutrino masses from cosmological data, derived from analysis of the cosmic microwave background (CMB) and baryon acoustic acoustic oscillations (BAO) from the Dark Energy Spectroscopic Instrument (DESI), favors a value below the minimum inferred from neutrino flavor oscillation experiments. We explore which data is most responsible of this puzzling aspect of the current constraints on neutrino mass and whether it is related to other anomalies in cosmology. We demonstrate conclusively that the preference for negative neutrino masses is a consequence of larger than expected lensing of the CMB in both the two- and four-point lensing statistics. Furthermore, we show that this preference is robust to changes in likelihoods of the BAO and CMB optical depth analyses given the available data. We then show that this excess clustering is not easily explained by changes to the expansion history and is likely distinct from the preference for for dynamical dark energy in DESI BAO data. Finally, we discuss how future data may impact these results, including an analysis of Planck CMB with mock DESI 5-year data. Here, we conclude that the negative neutrino mass preference is likely to persist even as more cosmological data is collected in the near future.
72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
Evaluation of Seismic Artificial Intelligence with Uncertainty
Artificial intelligence has transformed the seismic community with deep learning models (DLMs) that are trained to complete specific tasks within workflows. However, there is still a lack of robust evaluation frameworks for evaluating and comparing DLMs. Here, we address this gap by designing an evaluation framework that jointly incorporates two crucial aspects: performance uncertainty and learning efficiency. To target these aspects, we meticulously construct the training, validation, and test splits using a clustering method tailored to seismic data and enact an expansive training design to segregate performance uncertainty arising from stochastic training processes and random data sampling. The framework’s ability to guard against misleading declarations of model superiority is demonstrated through the evaluation of PhaseNet (Zhu and Beroza, 2018), a popular seismic phase picking DLM, under three training approaches. Our framework helps practitioners choose the best model for their problem and set performance expectations by explicitly analyzing model performance with uncertainty at varying budgets of training data.
58 GEOSCIENCES↗
Signatures of clustering accessible with a Time Projection Chamber: TexAT
Many experimental observables in clustering require high-sensitivity, almost background-free measurements. The use of Time Projection Chambers (TPCs) over the past 15 years have demonstrated their capability as a step change in the accessibility of many of these observables, as well as the possibility to study clustering via new techniques. A summary of the difficulties and pitfalls of determining the type of clustering from observables is briefly discussed, with a focus on α-condensation and the possibility of an additional (Efimov) 0 + state in 12 C, below the Hoyle state. The expansion of the technique used to tackle this challenge to study 3α + p clustering in 13 N is also discussed, highlighting the exciting opportunities TPCs provide to study clustering inaccessible by conventional means. Finally, an overview of the recent and upcoming advances in TPC technology is given as well as listing additional future challenges that are needed to be overcome, in the context of discussing the next-generation upgrade to the existing TexAT TPC, known as TeBAT (TExas Birmingham Active Target).
Bishop, Jack↗
VAST: the Void Analysis Software Toolkit
Voids are expansive regions in the universe containing significantly fewer galaxies than surrounding galaxy clusters and filaments. They are a fundamental feature of the cosmic web and provide important information about galaxy physics and cosmology. For example, correlations between voids and luminous tracers of large-scale structure improve constraints on the expansion of the universe as compared to using tracers alone, and numerous studies have shown that the void environment influences the evolution of galaxies. However, what constitutes a void is vague and formulating a concrete definition to use in a void-finding algorithm is not trivial. As a result, several different algorithms exist to identify these cosmic underdensities. Our Void Analysis Software Toolkit, or VAST, provides Python 3 implementations of two such algorithms: VoidFinder and V 2 . This consolidation of two popular void-finding algorithms allows the user to, for example, easily compare the results of their analysis using different void definitions.
97 MATHEMATICS AND COMPUTING↗
Cosmic Growth Rate as Probe of Dark Matter and Gravity. Final Report
Some 95% of the energy content of the universe lies outside the standard model of particle physics, with approximately 70% arising from physics that accelerates cosmic expansion in opposition to normal gravity and about 25% dark matter that clusters under gravity but does not interact directly with light. This project made significant advances in developing methods to extract information on the former – dark energy or modified gravity – and latter – dark matter through their effects on the expansion history of the universe and the cosmic growth of large scale structures under the influence of gravity and dark energy. These results directly benefit experimental/observational cosmic surveys of large scale structure imaging hundreds of millions of galaxies and mapping spectroscopically the 3D positions of tens of millions.
72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
The onset of gravothermal oscillations in globular cluster evolution
We have carried out an extensive set of Fokker-Planck simulations of the evolution of globular clusters on very long timescales, up to 600 times the initial core collapse time t(sub cc). We consider an idealized equal mass star cluster, with a wide range of values for the total number of stars, 7000 less than N less than 2 x 10(exp 6). Our models include the heating effect of compact binaries formed in three-body encounters, which halts the initial core collapse and drives a core reexpansion. Postcollapse gravothermal oscillations of the cluster core are found to occur for all N approximately greater than or equal to 8000. For 8000 approximately less than or equal to N approximately less than or equal to 11,000, the oscillation has a simple, regular waveform with a single, well-defined period. For N approximately equals 12,000, the oscillations become nonlinear in a process resembling a period doubling. For N approximately greater than or equal to 14,000, the waveform of the oscillations becomes increasingly more irregular with increasing N, resembling chaotic behavior for N approximately greater than or equal to 15,000. During the oscillations, the core radius and core mass vary dramatically: by more than a factor of 10 for N greater than 15,000, by more than a factor of 100 for N greater than 5 x 10(exp 4), and by more than a factor of 1000 for N greater than 5 x 10(exp 5). However, even during the times of maximum expansion, the core contains only a small fraction of the cluster mass. For most N values, the maximum core mass at any time after core collapse is less than 1% of the cluster mass. The exceptions lie in the range 5 x 10(exp 4) approximately less than or equal to N approximately equal to or less than 2 x 10(exp 5), where the maximum post-collapse core mass reaches approximately 2% of the cluster mass. We discuss the observational implications of these predictions.
Breeden, Joseph L.↗