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At least 55 records · Page 3

QuantImPy: Minkowski functionals and functions with Python

The Minkowski functionals and functions are a family of morphological measures and can be used to describe both the morphology (shape) and topology (connectedness) of a system. This paper presents the QuantImPy Python package which can compute both the Minkowski functionals and functions. In addition, this package can efficiently perform basic morphological operations and compute their distance maps. QuantImPy is easy to install, well documented, integrated with existing Python packages, and open source.

97 MATHEMATICS AND COMPUTING↗

METABOLIC: high-throughput profiling of microbial genomes for functional traits, metabolism, biogeochemistry, and community-scale functional networks

Background Advances in microbiome science are being driven in large part due to our ability to study and infer microbial ecology from genomes reconstructed from mixed microbial communities using metagenomics and single-cell genomics. Such omics-based techniques allow us to read genomic blueprints of microorganisms, decipher their functional capacities and activities, and reconstruct their roles in biogeochemical processes. Currently available tools for analyses of genomic data can annotate and depict metabolic functions to some extent; however, no standardized approaches are currently available for the comprehensive characterization of metabolic predictions, metabolite exchanges, microbial interactions, and microbial contributions to biogeochemical cycling. Results We present METABOLIC (METabolic And BiogeOchemistry anaLyses In miCrobes), a scalable software to advance microbial ecology and biogeochemistry studies using genomes at the resolution of individual organisms and/or microbial communities. The genome-scale workflow includes annotation of microbial genomes, motif validation of biochemically validated conserved protein residues, metabolic pathway analyses, and calculation of contributions to individual biogeochemical transformations and cycles. The community-scale workflow supplements genome-scale analyses with determination of genome abundance in the microbiome, potential microbial metabolic handoffs and metabolite exchange, reconstruction of functional networks, and determination of microbial contributions to biogeochemical cycles. METABOLIC can take input genomes from isolates, metagenome-assembled genomes, or single-cell genomes. Results are presented in the form of tables for metabolism and a variety of visualizations including biogeochemical cycling potential, representation of sequential metabolic transformations, community-scale microbial functional networks using a newly defined metric “MW-score” (metabolic weight score), and metabolic Sankey diagrams. METABOLIC takes ~ 3 h with 40 CPU threads to process ~ 100 genomes and corresponding metagenomic reads within which the most compute-demanding part of hmmsearch takes ~ 45 min, while it takes ~ 5 h to complete hmmsearch for ~ 3600 genomes. Tests of accuracy, robustness, and consistency suggest METABOLIC provides better performance compared to other software and online servers. To highlight the utility and versatility of METABOLIC, we demonstrate its capabilities on diverse metagenomic datasets from the marine subsurface, terrestrial subsurface, meadow soil, deep sea, freshwater lakes, wastewater, and the human gut. Conclusion METABOLIC enables the consistent and reproducible study of microbial community ecology and biogeochemistry using a foundation of genome-informed microbial metabolism, and will advance the integration of uncultivated organisms into metabolic and biogeochemical models. METABOLIC is written in Perl and R and is freely available under GPLv3 at https://github.com/AnantharamanLab/METABOLIC.

59 BASIC BIOLOGICAL SCIENCES↗

Response Functions of Correlated Systems within Green's Function Theory

Why use Green's functions as the fundamental variable? Wave-function (Psi) methods are king for high-fidelity and Density-functional (Rho) methods are very efficient (Kohn-Sham). Goldilocks principle: Green's function (G) methods straddle the Rho and Psi methods, intermediate in both accuracy and efficiency. Also, when interest lies in excitations & 2-particle properties: G-methods are natural - intrinsic to the theory.

DMFT↗

Modeling Pb(II) Adsorption on Mineral Surfaces: Bridging Density Functional Theory and Experiment with Thermodynamic Insights

Despite decades of work on aqueous lead (Pb) adsorption on a-Fe2O3 (hematite) and a-Al2O3 (alumina), gaps between measurements and modeling obscure molecular-level understanding. Achieving well-matched geometries between theory and experimental for mineral-water interfaces is a hurdle, as surface functional group type and distribution must be accounted for in determining mechanisms. Additionally, computational methods that can describe the substrate are often not appropriate to capture aqueous effects. Progress requires focusing on well-studied and relevant systems, such as key facets (001),(012), and (110) of hematite and alumina, and ubiquitous contaminants such as aqueous Pb. In the past, bulk-parametrized bond-valence principles were used to rationalize Pb(II) adsorption trends. These approaches can break down at surfaces, where flexible bonding environments and adsorption-induced surface relaxations play a critical role. Here, we adapt and apply a density functional theory (DFT) and thermodynamics framework, integrating DFT-calculated energies with experimental data and electrochemical principles, to predict Pb(II) adsorption. Our model results capture trends across the full set of surfaces and predict that inner-sphere Pb(II) sorption on (001) alumina varies from unfavorable to weakly favorable across a range of pH conditions. This aligns with experiment insights that Pb(II) interacts at that surface through outer-sphere interactions. Extending to Fe(II) adsorption, we demonstrate a coverage-dependent site preference, potentially explaining disorder in overlayers grown by the oxidative adsorption of Fe(II) on hematite (001).

lead contamination↗

Lattice-QCD Computable Quark Correlation Functions at Three-Loop Order and Extraction of Splitting Functions

We present the first complete next-to-next-to-next-to-leading-order calculation of the matching coefficients that link unpolarized flavor nonsinglet parton distribution functions with lattice QCD computable correlation functions. By using this high-order result, we notice a reduction in theoretical uncertainties compared to relying solely on previously known lower-order matching coefficients. Furthermore, based on this result we have extracted the three-loop unpolarized flavor nonsinglet splitting function, which is in agreement with the state-of-the-art result. Because of the simplicity of our method, it has the potential to advance the calculation of splitting functions to the desired four-loop order.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Optimized Auxiliary Functions for Robust Mitigation of Finite-Size Errors in Periodic Hybrid Density Functional Theory

When calculating properties of periodic systems at the thermodynamic limit (TDL), the dominant source of finite size error (FSE) arises from the long-range Coulomb interaction, and can manifest as a slowly converging quadrature error when approximating an integral in the reciprocal space by a finite sum. The singularity subtraction (SS) method offers a systematic approach for reducing this quadrature error and thus the FSE. Here, in this work, we first investigate the performance of the SS method in the simplest setting, aiming at reducing the FSE in exact exchange calculations by subtracting the Coulomb contribution with a single, adjustable Gaussian auxiliary function. We demonstrate that a simple fitting method can robustly estimate the optimal Gaussian width and leads to rapid convergence toward the TDL. Furthermore, we suggest new forms of the auxiliary function, whose optimal parameters could also be determined through least-squares fitting. For a range of semiconductors and insulators, the proposed auxiliary functions achieve robust, millihartree-level accuracy in hybrid density functional theory calculations, including cases with sparse k-meshes and large basis sets.

Quiton, Stephen Jon [University of California, Ber↗

Synthesis and Surface Attachment of Molecular Re(I) Hydride Species with Silatrane Functionalized Bipyridyl Ligands

Three molecular Re hydrides of the form ( R bpy)Re(CO) 3 H with 2,2′-bipyridine (bpy) ligands containing silatrane functional groups for surface attachment on metal oxide surfaces were synthesized. IR spectroscopy and cyclic voltammetry (CV) demonstrated that the complexes containing the silatrane functional groups have electronic properties similar to those of a control compound, which did not contain functional groups for attachment. Additionally, in a similar fashion to the control compound, the silatrane containing Re hydrides are electrocatalysts for the reduction of CO 2 to CO in solution. The silatrane containing complexes were immobilized on a thin layer of TiO 2 on Si, and the resulting composites were characterized using X-ray photoelectron and IR spectroscopy as well as cyclic voltammetry in the dark and under illumination. Control experiments indicated that the hydride complexes are not stable on the surface and degrade to species which contain a bpy ligand, three CO ligands, and an unknown ligand in the sixth site. Similarly, when one of the silatrane containing Re hydride complexes was immobilized on Si nanoparticles with a thin layer of SiO 2 or silica nanoparticles, the hydride ligand was lost. Density functional theory calculations were used to corroborate the observed behavior of hydride species on a surface. Altogether, this work demonstrates the difficulties associated with attaching well-defined molecular hydride complexes to metal oxide surfaces.

Anions↗

Functionalized Graphene via a One-Pot Reaction Enabling Exact Pore Sizes, Modifiable Pore Functionalization, and Precision Doping

Functionalizing graphene with exact pore size, specific functional groups, and precision doping poses many significant challenges. Current methods lack precision and produce random pore sizes, sites of attachment, and amounts of dopant, leading to compromised structural integrity and affecting graphene’s applications. In this work, we report a strategy for the synthesis of functionalized graphitic materials with modifiable nanometer-sized pores via a Pictet–Spengler polymerization reaction. This one-pot, four-step synthesis uses concepts based on covalent organic frameworks (COFs) synthesis to produce crystalline two-dimensional materials that were confirmed by PXRD, TEM measurements, and DFT studies. These new materials are structurally analogous to doped graphene and graphene oxide (GO) but, unlike GO, maintain their semiconductive properties when fully functionalized.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Linear Response Function Reveals the Most Effective Remote Forcing in Causing September Arctic Sea Ice Melting in CESM

We apply the linear response function method to investigate the most excitable mode of the September Arctic sea ice and its corresponding remote oceanic forcing in climate models. The method is useful in identifying the fundamental, dynamical and causal relationship between the remote forcing and sea ice response. We find that the most excitable mode of the September Arctic sea ice preferentially takes place over the Pacic side of the Arctic and its remote forcing corresponds to a dipole pattern of precipitation anomaly in the tropics with an increase of precipitation over the western and central tropical and subtropical Pacic ocean while a decrease over the Maritime Continent. The tropical precipitation anomaly likely drives a Rossby wave train propagating toward higher latitudes and leads to a ridge anomaly over the Pacic side of the Arctic, resulting in poleward atmospheric heat transport, enhanced downward longwave radiation and thus melting of the sea ice. In addition, a good agreement is found with the leading tropical Arctic teleconnection mode detected in a pre-industrial control simulation, which supports the usefulness and robustness of the linear response function method and the importance of tropical forcing in shaping the sea ice variability.

Wu, Yutian↗

Zero-cost corrections to influence functional coefficients from bath response functions

Recent work has shown that it is possible to circumvent the calculation of the spectral density and directly generate the coefficients of the discretized influence functionals using data from classical trajectory simulations. However, the accuracy of this procedure depends on the validity of the high temperature approximation. In this work, an alternative derivation based on the Kubo formalism is provided. This enables the calculation of additional correction terms that increases the range of applicability of the procedure to lower temperatures. Because it is based on the Kubo-transformed correlation function, this approach allows the direct use of correlation functions obtained from methods such as ring-polymer molecular dynamics and centroid molecular dynamics in determining the influence functional coefficients for subsequent system-solvent simulations. The accuracy of the original procedure and the corrected procedure is investigated across a range of parameters. It is interesting that the correction term comes at zero additional cost. Furthermore, it is possible to improve upon the correction using zero-cost physical intuition and heuristics making the method even more accurate.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A linear surrogate for optimising functions of an orthogonal matrix with applications in wave function theory

The technique of surrogate optimisation is to use a simpler function to approximate a complex function that is time-consuming to evaluate. Here we show that the maximum of a special type of surrogate function f(U)=Tr(AU),UϵO(n) is at A T (AA T ) 1/2 , and that there is one and only one local maximum both in SO(n) and O(n)–SO(n). This function f(U) has been found to be useful in various aspects of electronic structure theory, including proving the Carlson-Keller theorem, and localising orbitals. As one other example, we apply it here to optimise the ground state of molecules using the Generalised Valence Bond wavefunction.

74 ATOMIC AND MOLECULAR PHYSICS↗

Polarized Structure Function {sigma}LT from {pi}0 p Electroproduction Data in the Resonance Region at 0.4 GeV2 < Q2 < 1.0 GeV2

The first results on the sigma(LT') structure function in exclusive pi(0)p electroproduction at invariant masses of the final state of 1.5 GeV < W < 1.8 GeV and in the range of photon virtualities 0.4 GeV2 < Q(2) < 1.0 GeV2 were obtained from data on beam spin asymmetries and differential cross sections measured with the CLAS detector at Jefferson Lab. The Legendre moments determined from the sigma(LT') structure function have demonstrated sensitivity to the contributions from the nucleon resonances in the second and third resonance regions. These new data on the beam spin asymmetries in pi(0)p electroproduction extend the opportunities for the extraction of the nucleon resonance electro-excitation amplitudes in the mass range above 1.6 GeV.

Isupov, E. L.↗

Performance of wave function and Green's function methods for non-equilibrium many-body dynamics

Theoretical descriptions of the non-equilibrium dynamics of quantum many-body systems essentially employ either (i) explicit treatments, relying on the truncation of the expansion of the many-body wave function, (ii) compressed representations of the many-body wave function, or (iii) evolution of an effective (downfolded) representation through Green's functions. In this work, we select representative cases of each of the methods and address how these complementary approaches capture the dynamics driven by intense field perturbations to non-equilibrium states. Under strong driving, the systems are characterized by strong entanglement of the single-particle density matrix and natural populations approaching those of a strongly interacting equilibrium system. We generate a representative set of results that are numerically exact and form a basis for a critical comparison of the distinct families of methods. We demonstrate that the compressed formulation based on similarity-transformed Hamiltonians (coupled-cluster approach) is practically exact in weak fields and, hence, weakly or moderately correlated systems. Coupled cluster, however, struggles for strong driving fields, under which the system exhibits strongly correlated behavior, as measured by the von Neumann entropy of the single-particle density matrix. The dynamics predicted by Green's functions in the (widely popular) G W approximation are less accurate, but improve significantly upon the mean-field results in the strongly driven regime. Published by the American Physical Society 2025

Reeves, Cian C. (ORCID:0009000642581845)↗

Development of combined function dipole-quadrupole PMQs magnets for NSLS-II upgrade

This paper focuses on the R&D performed for the development of permanent magnets-based dipoles-quadrupoles combined function magnets (PMQs) for the future NSLSII upgrade “complex bend” lattice (CB). This new lattice uses PMQs that provide both bending (dipole) and strong focusing (quadrupole) magnetic field on the electron beam. The permanent magnet (PM) technology is suitable for the high magnetic field strengths (0.5 T, 130 T/m) required for such combine function magnets. PM technology leads to a compact magnet design that is essential in realizing the complex bend lattice concept, as well as a passive magnet solution which does not require electrical power supply reducing power consumption by ~ 80% (from 1.7 MW to 0.3 MW for NSLS-II). Two PMQs magnets designs are under consideration: A hybrid design that use both PM and soft iron poles, and Halbach type that is a pure PM design. Both PMQs designs present challenges in achieving the specified magnetic field quality due to their higher sensitivity to errors (mechanical tolerances and PM properties). This paper presents cost-effective designs and prototypes results for hybrid and Halbach PMQs, addressing various technical challenges while meeting the field requirements of the complex bend lattice for the NSLS-II upgrade.

N'gotta, Patrick [Brookhaven]↗

Studies in astronomical time series analysis. III - Fourier transforms, autocorrelation functions, and cross-correlation functions of unevenly spaced data

This paper develops techniques to evaluate the discrete Fourier transform (DFT), the autocorrelation function (ACF), and the cross-correlation function (CCF) of time series which are not evenly sampled. The series may consist of quantized point data (e.g., yes/no processes such as photon arrival). The DFT, which can be inverted to recover the original data and the sampling, is used to compute correlation functions by means of a procedure which is effectively, but not explicitly, an interpolation. The CCF can be computed for two time series not even sampled at the same set of times. Techniques for removing the distortion of the correlation functions caused by the sampling, determining the value of a constant component to the data, and treating unequally weighted data are also discussed. FORTRAN code for the Fourier transform algorithm and numerical examples of the techniques are given.

Scargle, Jeffrey D.↗

Function Based Risk Assessment: Mapping Function to Likelihood

The concept of function offers a high potential for thinking and reasoning about designs as well as providing a common thread for relating together other design information. This paper focuses specifically on the relation between function and risk by presenting a mathematical mapping from product function to risk likelihood. This risk information is composed of design parameters, failure modes, and likelihood values. A spacecraft orientation subsystem, subsystem used to guide science instruments, and a Bell 206 rotorcraft are used to test the mapping which continues research on these products relating function to failure. Finally, a case study is presented in which the risk element likelihood is calculated for a fuel cell which is in the conceptual design phase at NASA JPL.

Tumer, Irem Y.↗

Transfer Function Identification Using Orthogonal Fourier Transform Modeling Functions

A method for transfer function identification, including both model structure determination and parameter estimation, was developed and demonstrated. The approach uses orthogonal modeling functions generated from frequency domain data obtained by Fourier transformation of time series data. The method was applied to simulation data to identify continuous-time transfer function models and unsteady aerodynamic models. Model fit error, estimated model parameters, and the associated uncertainties were used to show the effectiveness of the method for identifying accurate transfer function models from noisy data.

Morelli, Eugene A.↗

Structural- and Functional-Informed Machine Learning for Protein Function Prediction

In this project we aimed to extend methods for protein function prediction to include structural prediction data, and benchmark methods against existing tools. We proposed to apply the method to large metagenome datasets, and develop approaches to examine activity-based protein profiling results for protein function-structure patterns. Nitrogen cycle protein families were previously identified and are used here to provide a proof-of-principle for use of structure prediction in protein function classification.

59 BASIC BIOLOGICAL SCIENCES↗