Soft X-ray Spectroscopy Simulations with Multiconfigurational Wave Function Theory: Spectrum Completeness, Sub-eV Accuracy, and Quantitative Reproduction of Line Shapes
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37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
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Results for “Shape function”
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Functional Traits Resolve Mechanisms Governing the Assembly and Distribution of Nitrogen-Cycling Microbial Communities in the Global Ocean
Microorganisms drive much of the marine nitrogen (N) cycle, which jointly controls the primary production in the global ocean. However, our understanding of the microbial communities driving the global ocean N cycle remains fragmented. Focusing on “who is doing what, where, and how?”, this study draws a clear picture describing the global biogeography of marine N-cycling microbial communities by utilizing the Tara Oceans shotgun metagenomes. The marine N-cycling communities are highly variable taxonomically but relatively even at the functional trait level, showing clear functional redundancy properties. The functional traits and taxonomic groups are shaped by the same set of geo-environmental factors, among which, depth is the major factor impacting marine N-cycling communities, differentiating mesopelagic from epipelagic communities. Latitudinal diversity gradients and distance-decay relationships are observed for taxonomic groups, but rarely or weakly for functional traits. The composition of functional traits is strongly deterministic as revealed by null model analysis, while a higher degree of stochasticity is observed for taxonomic composition. Integrating multiple lines of evidence, in addition to drawing a biogeographic picture of marine N-cycling communities, this study also demonstrated an essential microbial ecological theory—determinism governs the assembly of microbial communities performing essential biogeochemical processes; the environment selects functional traits rather than taxonomic groups; functional redundancy underlies stochastic taxonomic community assembly.
59 BASIC BIOLOGICAL SCIENCES↗
Energy-Energy Correlators for Precision QCD
In this contribution to the Proceedings of the US Community Study on the Future of Particle Physics (Snowmass 2021) we review recent progress in the evaluation and application of the Energy-Energy Correlator (EEC) event shape observable in $e^+e^⁻$ annihilation, hadronic collisions, and deep inelastic scattering. The importance of EEC as a precision probe of the perturbative and non perturbative aspects of QCD dynamics is emphasized. It can be used to extract the strong coupling constant and to constrain TMD distribution functions. Closely related energy-correlation shape variables have also been used to tag boosted objects produced in high energy collisions. The opportunities to study EEC at the future Electron-Ion Collider are also highlighted.
72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
Antiprotons and Elementary Particles over a Solar Cycle: Results from the Alpha Magnetic Spectrometer
We present results over an 11-year Solar cycle of cosmic antiprotons based on 1.1 × 10 6 events in the rigidity range from 1.00 to 41.9 GV. The $\bar{𝑝}$ fluxes exhibit distinct properties. The magnitude of the $\bar{𝑝}$ flux temporal variation is significantly smaller than those of 𝑝, 𝑒 − , and 𝑒 + . A hysteresis between the $\bar{𝑝}$ fluxes and the 𝑝 fluxes is observed, whereas the $\bar{𝑝}$ and 𝑒 − fluxes show a linear correlation. With a model-independent analysis, we found a universal relation between the shape of the rigidity spectrum and the magnitude of flux temporal variation over an 11-year Solar cycle for both positively and negatively charged particles. The simultaneous results on $\bar{𝑝}$ and 𝑝, 𝑒 − , and 𝑒 + provide unique information for understanding particle transport in the Solar System as a function of mass, charge, and spectral shape.
cosmic ray composition & spectra↗
Stellar angular momentum distribution linked to galaxy morphology
ABSTRACT We study the spatially resolved stellar specific angular momentum j* in a high-quality sample of 24 Calar Alto Legacy Integral Field Area galaxies covering a broad range of visual morphology, accounting for stellar velocity and velocity dispersion. The shape of the spaxelwise probability density function of normalized s = j*/j*mean, PDF(s), deviates significantly from the near-universal initial distribution expected of baryons in a dark matter halo and can be explained by the expected baryonic effects in galaxy formation that remove and redistribute angular momentum. Further we find that the observed shape of the PDF(s) correlates significantly with photometric morphology, where late-type galaxies have a PDF(s) that is similar to a normal distribution, whereas early types have a strongly skewed PDF(s) resulting from an excess of low-angular momentum material. Galaxies that are known to host pseudo-bulges (bulge Sérsic index nb < 2.2) tend to have less skewed bulge PDF(s), with skewness (b1rb) ≲ 0.8. The PDF(s) encodes both kinematic and photometric information and appears to be a robust tracer of morphology. Its use is motivated by the desire to move away from traditional component-based classifications which are subject to observer bias, to classification on a galaxy’s fundamental (stellar mass and angular momentum) properties. In future, PDF(s) may also be useful as a kinematic decomposition tool.
Sweet, Sarah M.↗
Imaging how thermal capillary waves and anisotropic interfacial stiffness shape nanoparticle supracrystals
Abstract Development of the surface morphology and shape of crystalline nanostructures governs the functionality of various materials, ranging from phonon transport to biocompatibility. However, the kinetic pathways, following which such development occurs, have been largely unexplored due to the lack of real-space imaging at single particle resolution. Here, we use colloidal nanoparticles assembling into supracrystals as a model system, and pinpoint the key role of surface fluctuation in shaping supracrystals. Utilizing liquid-phase transmission electron microscopy, we map the spatiotemporal surface profiles of supracrystals, which follow a capillary wave theory. Based on this theory, we measure otherwise elusive interfacial properties such as interfacial stiffness and mobility, the former of which demonstrates a remarkable dependence on the exposed facet of the supracrystal. The facet of lower surface energy is favored, consistent with the Wulff construction rule. Our imaging–analysis framework can be applicable to other phenomena, such as electrodeposition, nucleation, and membrane deformation.
77 NANOSCIENCE AND NANOTECHNOLOGY↗
Shape-Selective Mesoscale Nanoarchitectures: Preparation and Photocatalytic Performance
We create ordered arrays of shape-selective gold-titania composite nanomaterials at the mesoscale (100 µm to 5 mm) by a combination of both bottom-up and top-down approaches for exquisite control of the size, shape, and arrangement of nanomaterials. Lithographic techniques along with wet chemical synthetic methods were combined to create these composite nanomaterials. The photocatalytic activity of these TiO 2, TiO 2 -Au and SiO 2 -TiO 2 -Au nano-composite mesoscale materials was monitored by the photodegradation of a model analyte, methyl orange, under UV and visible (Vis) illumination. Bare TiO 2 - and SiO 2 -TiO 2 -coated pillar arrays showed significant activity toward methyl orange in UV light with degradation rates on the order of 10 −4 –10 −3 min −1 . The photocatalytic activity of these arrays was also found to depend on the nanoparticle shape, in which particles with more edges and corners were found to be more reactive than spherical particles (i.e., the photocatalytic activity decreased as follows: diamonds > squares > triangles > spheres). SiO 2 -TiO 2 -Au nano-composite pillar arrays were tested in both UV and Vis light and showed increased activity in Vis light but decreased activity in UV light as compared to the bare semiconductor arrays. Additionally, the Au nanorod-functionalized nanoarrays exhibit a strong shape-dependence in their photocatalytic activity toward methyl orange degradation in Vis light.
36 MATERIALS SCIENCE↗
Landscape of nuclear deformation softness with spherical quasiparticle random-phase approximation
We investigate the stability and softness of nuclei against quadrupole, octupole, and hexadecapole deformation. By applying the spherical Skyrme-force Hartree-Fock Bardeen-Cooper-Schrieffer quasiparticle random phase approximation, we diagnose ground-state deformation when imaginary solutions are obtained, i.e., the spherical ground state collapses. We also calculate the multipole polarizability in spherical nuclei with no collapse, as a measure of softness. This numerically light and theoretically sound method is found able to capture deformation patterns across the nuclide chart. As a result, the connection between the intrinsic shape of nuclei and the dynamics of their low-lying collective states is established and the role of shell structure is discussed.
73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
Experimental platforms for investigating feature-driven jets for HED mix model validation
High-energy-density (HED) systems, such as inertial confinement fusion (ICF), are susceptible to hydrodynamic instabilities that can significantly affect both experimental results and modeling predictions. Isolated features, such as fill tubes or divots in the capsule, can cause material to jet as a result of the compressive shock exciting the Richtmyer–Meshkov instability, and serve as one of the primary degradation mechanisms in ICF yield. Simulations of feature-driven jets and how they mix require extensive experimental validation, particularly for understanding to what degree the initial size and shape of a feature influence jet dynamics, and how much instability feeds through downstream layers. A better understanding of feature-driven jetting can improve our mix modeling capabilities and increase hydrodynamic simulation accuracy. This manuscript describes a series of experimental platforms fielded by Los Alamos National Laboratory as a part of the Mshock Omega 60 and ModCons Omega EP campaigns to explore feature-driven jetting. These platforms are designed to benchmark jet evolution and growth as a function of initial feature size and shape, investigate jet-layer interactions leading to instability feedthrough, and will be used to characterize jet-jet interactions resulting from clusters of features. In conclusion, preliminary results for both platforms are shown. The ModCons experiments are on-going, and a discussion of future work directions is included.
70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
The impact of anisotropic redshift distributions on angular clustering
A leading way to constrain physical theories from cosmological observations is to test their predictions for the angular clustering statistics of matter tracers, a technique that is set to become ever more central with the next generation of large imaging surveys. Interpretation of this clustering requires knowledge of the projection kernel, or the redshift distribution of the sources, and the typical assumption is an isotropic redshift distribution for the objects. However, variations in the kernel are expected across the survey footprint due to photometric variations and residual observational systematic effects. Here, we develop the formalism for anisotropic projection and present several limiting cases that elucidate the key aspects. We quantify the impact of anisotropies in the redshift distribution on a general class of angular two-point statistics. In particular, we identify a mode-coupling effect that can add power to auto-correlations, including galaxy clustering and cosmic shear, and remove it from certain cross-correlations. If the projection anisotropy is primarily at large scales, the mode-coupling depends upon its variance as a function of redshift; furthermore, it is often of similar shape to the signal. In contrast, the cross-correlation of a field whose selection function is anisotropic with another one featuring no such variations — such as CMB lensing — is immune to these effects. We discuss explicitly several special cases of the general formalism including galaxy clustering, galaxy-galaxy lensing, cosmic shear and cross-correlations with CMB lensing, and publicly release a code to compute the biases.
79 ASTRONOMY AND ASTROPHYSICS↗
The Completed SDSS-IV extended Baryon Oscillation Spectroscopic Survey: exploring the halo occupation distribution model for emission line galaxies
We study the modelling of the halo occupation distribution (HOD) for the eBOSS DR16 emission line galaxies (ELGs). Motivated by previous theoretical and observational studies, we consider different physical effects that can change how ELGs populate haloes. We explore the shape of the average HOD, the fraction of satellite galaxies, their probability distribution function (PDF), and their density and velocity profiles. Our baseline HOD shape was fitted to a semi-analytical model of galaxy formation and evolution, with a decaying occupation of central ELGs at high halo masses. We consider Poisson and sub/super-Poissonian PDFs for satellite assignment. We model both Navarro–Frenk–White and particle profiles for satellite positions, also allowing for decreased concentrations. We model velocities with the virial theorem and particle velocity distributions. Additionally, we introduce a velocity bias and a net infall velocity. We study how these choices impact the clustering statistics while keeping the number density and bias fixed to that from eBOSS ELGs. The projected correlation function, w p , captures most of the effects from the PDF and satellites profile. The quadrupole, ξ 2 , captures most of the effects coming from the velocity profile. We find that the impact of the mean HOD shape is subdominant relative to the rest of choices. Here, we fit the clustering of the eBOSS DR16 ELG data under different combinations of the above assumptions. The catalogues presented here have been analysed in companion papers, showing that eBOSS RSD+BAO measurements are insensitive to the details of galaxy physics considered here. These catalogues are made publicly available.
79 ASTRONOMY AND ASTROPHYSICS↗
Damped Ly α absorbers and atomic hydrogen in galaxies: the view of the GAEA model
ABSTRACT Using the GAEA semi-analytic model, we analyse the connection between Damped Ly α systems (DLAs) and H i in galaxies. Our state-of-the-art semi-analytic model is tuned to reproduce the local galaxy H i mass function, and that also reproduces other important galaxy properties, including the galaxy mass–gas metallicity relation. To produce catalogues of simulated DLAs we throw 105 random lines of sight in a composite simulated volume: dark matter haloes with log$(\frac{M_{200}}{ {\rm M}_{\odot }}) \ge 11.5$ are extracted from the Millennium Simulation, while for $9.2 \le \log (\frac{M_{200}}{ \mathrm{M}_{\odot }})\lt 11.5$ we use the Millennium II, and for $8 \le \log (\frac{M_{200}}{\mathrm{M}_{\odot }}) \lt 9.2$ a halo occupation distribution model. At 2 < z < 3, where observational data are more accurate, our fiducial model predicts the correct shape of the column density distribution function, but its normalization falls short of the observations, with the discrepancy increasing at higher redshift. The agreement with observations is significantly improved increasing both the H i masses and the disc radii of model galaxies by a factor of 2, as implemented ‘a posteriori’ in our 2M−2R model. In the redshift range of interest, haloes with $M_{200} \ge {10}^{11} \, \mathrm{M}_{\odot }$ give the major contribution to ΩDLA, and the typical DLA host halo mass is $\sim \!{10}^{11} \, \mathrm{M}_{\odot }$. The simulated DLA metallicity distribution is in relatively good agreement with observations, but our model predicts an excess of DLAs at low metallicities. Our results suggest possible improvements for the adopted modelling of the filtering mass and metal ejection in low-mass haloes.
Di Gioia, Serafina↗
Explainable Machine Learning for Functional Data
Black-box machine learning models are recognized as useful tools for prediction applications, but the algorithmic complexity of some models causes interpretation challenges. Explainability methods have been proposed to provide insight into these models, but there is little research focused on supervised modeling with functional data inputs. We argue that, especially in applications of high consequence, it is important to explicitly model the functional dependence in a black-box analysis to not obscure or misrepresent patterns in explanations. As such, we propose the V ariable importance E xplainable E lastic S hape A nalysis (VEESA) pipeline for training supervised machine learning models with functional inputs. The pipeline is an analysis process that includes the data preprocessing, modeling, and post-hoc explanations. The preprocessing is done using elastic functional principal components analysis, which accounts for vertical and horizontal variability in functional data and, ultimately, allows for explanations in the original data space that identify the important functional variability without bias due to correlated variables. Here, we demonstrate the pipeline on two high-consequence applications: explosives classification for national security and inkjet printer identification in forensic science. The applications exhibit the VEESA pipeline’s ability to provide an understanding of the characteristics of the functional data useful for prediction. Code for implementing the pipeline is available in the veesa R package (and supplemental python code).
Elastic Shape Analysis↗
Model study of the energy dependence of the correlation between anisotropic flow and the mean transverse momentum in Au + Au collisions
A hybrid model that employs the hadron-string transport model UrQMD and the (3+1)-dimensional relativistic viscous hydrodynamic code vHLLE, is used to investigate the beam energy dependence of the correlation coefficient ρ(v$^{2}_{2}$,[p T ]) between the average transverse momentum [p T ] of hadrons emitted in an event and the square of the anisotropic flow coefficient v$^{2}_{2}$. For Au+Au collisions, the model predicts characteristic patterns for the energy and event-shape dependence of the variances for [p T ] and v$^{2}_{n}$ [Var([p T ] and Var(v$^{2}_{2}$)], and the covariance of v$^{2}_{n}$ and [p T ][cov(v$^{2}_{2}$,[p T ])], consistent with the attenuation effects of the specific shear viscosity η/s. Here in contrast, ρ(v$^{2}_{2}$,[p T ]) is predicted to be insensitive to the beam energy but sensitive to the initial-state geometry of the collisions. These observations suggest that a precise set of measurements for Var([p T ]), Var(v$^{2}_{2}$), cov(v$^{2}_{2}$,[p T ]) and ρ(v$^{2}_{2}$,[p T ]) as a function of beam energy and event shape, could serve to constrain better the eccentricities and their fluctuations over the entire span of beam energies, and consequently aid precision extraction of the temperature and baryon chemical-potential dependence of η/s from the wealth of Au+Au data obtained in the RHIC beam energy scan.
73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
Sensitivity of cellular automata grain structure predictions for high solidification rates
Understanding as-solidified grain structure development during constrained (G 0) alloy solidification conditions is a necessary component of understanding the larger process-microstructure relationships during additive manufacturing (AM) processing. This study applies a cellular automata (CA) model, for static solidification velocities and thermal gradients on the order of those expected in AM melt pools, to investigate grain shape development across ranges of input parameters governing temperature field evolution, nucleation, and growth. Variation in nucleated grain shape from columnar to equiaxed as a function of thermal gradient and nucleation density is modeled with CA and verified against the established transition model of Hunt and Gaumann. Furthermore, while thermal conditions and nucleation density are shown to have the largest roles on microstructure development, the sensitivity of grain structure was very unevenly distributed across parameter space. In particular, it was found that microstructure is very sensitive to mean nucleation undercooling and the interfacial response function in process space regimes near grain structure transitions, but entirely controlled by a combination of thermal gradient, solidification velocity, and nucleation density away from such transitions. The understanding of grain shape sensitivity obtained through CA modeling, particularly at large thermal gradient and nucleation density, will be necessary for accurate microstructure prediction during the extreme processing conditions and large input parameter uncertainty common to AM.
36 MATERIALS SCIENCE↗
Epigenetic effects associated with salmonid supplementation and domestication
Abstract Several studies have demonstrated lower fitness of salmonids born and reared in a hatchery setting compared to those born in nature, yet broad-scale genome-wide genetic differences between hatchery-origin and natural-origin fish have remained largely undetected. Recent research efforts have focused on using epigenetic tools to explore the role of heritable changes outside of genetic variation in response to hatchery rearing. We synthesized the results from salmonid studies that have directly compared methylation differences between hatchery-origin and natural-origin fish. Overall, the majority of studies found substantial differences in methylation patterns and overlap in functional genomic regions between hatchery-origin and natural-origin fish which have been replicated in parallel across geographical locations. Epigenetic differences were consistently found in the sperm of hatchery-origin versus natural-origin fish along with evidence for maternal effects, providing a potential source of multigenerational transmission. While there were clear epigenetic differences in gametic lines between hatchery-origin and natural-origin fish, only a limited number explored the potential mechanisms explaining these differences. We outline opportunities for epigenetics to inform salmonid breeding and rearing practices and to mitigate for fitness differences between hatchery-origin and natural-origin fish. We then provide possible explanations and avenues of future epigenetics research in salmonid supplementation programs, including: 1) further exploration of the factors in early development shaping epigenetic differences, 2) understanding the functional genomic changes that are occurring in response to epigenetic changes, 3) elucidating the relationship between epigenetics, phenotypic variation, and fitness, and 4) determining heritability of epigenetic marks along with persistence of marks across generations.
Koch, Ilana J. (ORCID:0000000335943108)↗
The Sejong Open Cluster Survey (SOS). VII. A Photometric Study of the Young Open Cluster IC 1590
Young open clusters are ideal laboratories to understand the star formation process. We present deep UBVI and Hα photometry for the young open cluster IC 1590 in the center of the H ii region NGC 281. Early-type members are selected from UBV photometric diagrams, and low-mass pre-main-sequence (PMS) members are identified by using Hα photometry. In addition, the published X-ray source list and Gaia astrometric data are also used to isolate probable members. A total of 408 stars are selected as members. The mean reddening obtained from early-type members is ⟨E(B – V)⟩ = 0.40 ± 0.06 (s.d.). We confirm the abnormal extinction law for the intracluster medium. The distance modulus to the cluster determined from the zero-age main-sequence fitting method is 12.3 ± 0.2 mag (d = 2.88 ± 0.28 kpc), which is consistent with the distance d=2.70{sub -0.20}{sup +0.24} kpc from the recent Gaia parallaxes. We also estimate the ages and masses of individual members by means of stellar evolutionary models. The mode of the age of PMS stars is about 0.8 Myr. The initial mass function of IC 1590 is derived. It appears to be a steeper shape (Γ = -1.49 ± 0.14) than that of the Salpeter/Kroupa initial mass function for the high-mass regime (m > 1 M {sub ⊙}). The signature of mass segregation is detected from the difference in the slopes of the initial mass functions for the inner ([[Formula]]) and outer regions of this cluster. We finally discuss the star formation history in NGC 281.
47 OTHER INSTRUMENTATION↗
The three major axes of terrestrial ecosystem function
The leaf economics spectrum and the global spectrum of plant forms and functions revealed fundamental axes of variation in plant traits, which represent different ecological strategies that are shaped by the evolutionary development of plant species. Ecosystem functions depend on environmental conditions and the traits of species that comprise the ecological communities. However, the axes of variation of ecosystem functions are largely unknown, which limits our understanding of how ecosystems respond as a whole to anthropogenic drivers, climate and environmental variability. Here we derive a set of ecosystem functions from a dataset of surface gas exchange measurements across major terrestrial biomes. We find that most of the variability within ecosystem functions (71.8%) is captured by three key axes. The first axis reflects maximum ecosystem productivity and is mostly explained by vegetation structure. The second axis reflects ecosystem water-use strategies and is jointly explained by variation in vegetation height and climate. The third axis, which represents ecosystem carbon-use efficiency, features a gradient related to aridity, and is explained primarily by variation in vegetation structure. We show that two state-of-the-art land surface models reproduce the first and most important axis of ecosystem functions. However, the models tend to simulate more strongly correlated functions than those observed, which limits their ability to accurately predict the full range of responses to environmental changes in carbon, water and energy cycling in terrestrial ecosystems.
54 ENVIRONMENTAL SCIENCES↗