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At least 73 records · Page 4

Reduced basis approximations of parameterized dynamical partial differential equations via neural networks

Projection-based reduced order models are effective at approximating parameter-dependent differential equations that are parametrically separable. When parametric separability is not satisfied, which occurs in both linear and nonlinear problems, projection-based methods fail to adequately reduce the computational complexity. Devising alternative reduced order models is crucial for obtaining efficient and accurate approximations to expensive high-fidelity models. In this work, we develop a timestepping procedure for dynamical parameter-dependent problems, in which a neural-network is trained to propagate the coefficients of a reduced basis expansion. This results in an online stage with a computational cost independent of the size of the underlying problem. Here, we demonstrate our method on several parabolic partial differential equations, including a problem that is not parametrically separable.

97 MATHEMATICS AND COMPUTING↗

Measurements of inclusive and differential cross sections for top quark production in association with a Z boson in proton-proton collisions at $\sqrt{s} $ = 13 TeV

Measurements are presented of inclusive and differential cross sections for Z boson associated production of top quark pairs ($ \textrm{t}\overline{\textrm{t}}\textrm{Z} $) and single top quarks (tZq or tWZ). The data were recorded in proton-proton collisions at a center-of-mass energy of 13 TeV, corresponding to an integrated luminosity of 138 fb$^{−1}$. Events with three or more leptons, electrons or muons, are selected and a multiclass deep neural network is used to separate three event categories, the $ \textrm{t}\overline{\textrm{t}}\textrm{Z} $ and tWZ processes, the tZq process, and the backgrounds. A profile likelihood approach is used to unfold the differential cross sections, to account for systematic uncertainties, and to determine the correlations between the two signal categories in one global fit. The inclusive cross sections for a dilepton invariant mass between 70 and 110 GeV are measured to be 1.14 ± 0.07 pb for the sum of $ \textrm{t}\overline{\textrm{t}}\textrm{Z} $ and tWZ, and 0.81 ± 0.10 pb for tZq, in good agreement with theoretical predictions.[graphic not available: see fulltext]

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Differential cross-section measurements of Higgs boson production in the H → τ + τ - decay channel in pp collisions at $\sqrt{s}$ = 13 TeV with the ATLAS detector

Differential measurements of Higgs boson production in the τ-lepton-pair decay channel are presented in the gluon fusion, vector-boson fusion (VBF), VH and $t\overline{t}H$ associated production modes, with particular focus on the VBF production mode. The data used to perform the measurements correspond to 140 fb -1 of proton-proton collisions collected by the ATLAS experiment at the LHC. Two methods are used to perform the measurements: the Simplified Template Cross-Section (STXS) approach and an Unfolded Fiducial Differential measurement considering only the VBF phase space. For the STXS measurement, events are categorized by their production mode and kinematic properties such as the Higgs boson’s transverse momentum (${p}_{\textrm{T}}^{\textrm{H}}$ ), the number of jets produced in association with the Higgs boson, or the invariant mass of the two leading jets (mjj). For the VBF production mode, the ratio of the measured cross-section to the Standard Model prediction for m jj > 1.5 TeV and ${p}_{\textrm{T}}^{\textrm{H}}$ > 200 GeV (${p}_{\textrm{T}}^{\textrm{H}}$ < 200 GeV) is ${1.29}_{-0.34}^{+0.39}$ (${0.12}_{-0.33}^{+0.34}$ ). This is the first VBF measurement for the higher-${p}_{\textrm{T}}^{\textrm{H}}$ criteria, and the most precise for the lower-${p}_{\textrm{T}}^{\textrm{H}}$ criteria. The fiducial cross-section measurements, which only consider the kinematic properties of the event, are performed as functions of variables characterizing the VBF topology, such as the signed ΔΦ jj between the two leading jets. The measurements have a precision of 30%–50% and agree well with the Standard Model predictions. These results are interpreted in the SMEFT framework, and place the strongest constraints to date on the CP-odd Wilson coefficient ${c}_{H\overset{\sim }{W}}$ .

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Measurement of differential t-channel single top (anti)quark production cross-sections at 13 TeV with the ATLAS detector

The production of single top quarks and top antiquarks via the t-channel exchange of a virtual W boson is measured in proton-proton collisions at a centre-of-mass energy of 13 TeV at the Large Hadron Collider. The full Run 2 data sample recorded with the ATLAS detector in the years 2015–2018 is used, corresponding to an integrated luminosity of 140 fb−1. The absolute and normalised production cross-sections are measured differentially as a function of the transverse momentum and absolute rapidity of the top quark and top antiquark. In addition, the ratio of top quark to top antiquark production cross-sections is measured. The measured distributions are compared with next-to-leading-order quantum chromodynamics predictions obtained with different combinations of matrix-element generators, parton-shower programs and proton parton distribution functions, as well as to next-to-next-to-leading-order calculations. Overall, good agreement is observed between the measurements and the theoretical predictions. For most measured distributions, the sensitivity to differences between the predictions is limited by the systematic uncertainties in the measurement. The measured differential distributions are also interpreted in an effective field theory approach to constrain the Wilson-Coefficient CQq3,1$$ {C}_{Qq}^{3,1} $$ associated with a four-quark operator. The interpretation accounts for the effect of the selection efficiency, which is altered significantly by non-zero contributions from CQq3,1$$ {C}_{Qq}^{3,1} $$.

Aad, G↗

Differential cross-sections for events with missing transverse momentum and jets measured with the ATLAS detector in 13 TeV proton-proton collisions

Measurements of inclusive, differential cross-sections for the production of events with missing transverse momentum in association with jets in proton-proton collisions at √s = 13 TeV are presented. The measurements are made with the ATLAS detector using an integrated luminosity of 140 fb –1 and include measurements of dijet distributions in a region in which vector-boson fusion processes are enhanced. They are unfolded to correct for detector resolution and efficiency within the fiducial acceptance, and are designed to allow robust comparisons with a wide range of theoretical predictions. A measurement of differential cross sections for the Z → νν process is made. The measurements are generally well-described by Standard Model predictions except for the dijet invariant mass distribution. Auxiliary measurements of the hadronic system recoiling against isolated leptons, and photons, are also made in the same phase space. Ratios between the measured distributions are then derived, to take advantage of cancellations in modelling effects and some of the major systematic uncertainties. These measurements are sensitive to new phenomena, and provide a mechanism to easily set constraints on phenomenological models. To illustrate the robustness of the approach, these ratios are compared with two common Dark Matter models, where the constraints derived from the measurement are comparable to those set by dedicated detector-level searches.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Interpretations of the ATLAS measurements of Higgs boson production and decay rates and differential cross-sections in pp collisions at $\sqrt{s}$ = 13 TeV

Measurements of the Higgs boson production times decay rates and differential cross-sections have recently been performed by the ATLAS experiment in several decay channels using up to 139 fb -1 of proton-proton collision data at $\sqrt{s}$ = 13 TeV recorded at the Large Hadron Collider. This paper presents multiple interpretations of these Higgs boson measurements. Measurements of production-mode cross-sections, simplified template cross-sections and fiducial differential cross-sections in different decay channels are reparameterised in terms of the impact of Standard Model effective field theory operators, and constraints are reported on the corresponding Wilson coefficients. Production and decay rate measurements are interpreted in UV-complete extensions of the Standard Model, namely the two-Higgs-doublet model (2HDM) near the alignment limit and the Minimal Supersymmetric Standard Model (MSSM) for various MSSM benchmark scenarios. The constraints on the 2HDM parameters (cos(β - α), tanβ) and the MSSM parameters (m A , tanβ) are complementary to those obtained from direct searches for additional Higgs bosons.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Differentiable lagrangian shock hydrodynamics with application to stable shock acceleration of density interfaces

We develop a gradient based optimization approach for the equations of compressible, Lagrangian hydrodynamics and demonstrate how it can be employed to automatically uncover strategies to control hydrodynamic instabilities arising from shock acceleration of density interfaces. Strategies for controlling the Richtmyer-Meshkov instability (RMI) are of great benefit for inertial confinement fusion (ICF) where shock interactions with many small imperfections in the density interface lead to instabilities which rapidly grow over time. These instabilities lead to mixing which, in the case of laser driven ICF, quenches the runaway fusion process ruining the potential for positive energy return. Here, we demonstrate that control of these instabilities can be achieved by optimization of initial conditions with ( > 100) parameters. Optimizing over a large parameter space like this is not possible with gradient-free optimization strategies. This requires computation of the gradient of the outputs of a numerical solution to the equations of Lagrangian hydrodynamics with respect to the inputs. We show that the efficient computation of these gradients is made possible via a judicious application of (i) adjoint methods, the exact formal representation of sensitivities involving partial differential equations, and (ii) automatic differentiation (AD), the algorithmic calculation of derivatives of functions. Careful regularization of multiple operators including artificial viscosity and timestep control is required. We perform design optimization of > 100 parameter energy field driving the Richtmyer Meshkov instability showing significant suppression while simultaneously enhancing the acceleration of the interface relative to a nominal baseline case.

Hydrophysics↗

Differential Ligation Alters Electronic State and Coupling Signals of Iron-Sulfur Clusters in Flavin-Based Electron Bifurcation

Flavin-based electron bifurcation (FBEB) is employed by microorganisms for controlling pools of redox equivalents by reversibly splitting electron pairs into high- and low-energy levels from an initial midpoint potential. Our ability to harness this phenomenon is crucial for biocatalytic design which is limited by our understanding of energy coupling in the bifurcation system. In Pyrococcus furiosus, FBEB is carried out by the NADH-dependent ferredoxin:NADP+-oxidoreductase (NfnSL), coupling the uphill reduction of ferredoxin in NfnL to the downhill reduction of NAD+ in NfnS from oxidation of NADPH. Flanking the bifurcating flavin are two site-differentiated iron-sulfur clusters; the nearest is a glutamate-ligated [4Fe-4S] cluster in NfnL. Recent biochemical experiments substituting the native glutamate with cysteine led to loss of coupling between the uphill and downhill pathways, in contrast to the tight thermodynamic coupling in the native system. To understand how this decoupling is biochemically manifested by the cysteine-substituted [4Fe-4S] in NfnL, we employed electron paramagnetic resonance (EPR) spectroscopy to identify changes in electronic architecture and square wave voltammetry (SWV) to probe thermodynamic shifts produced by the substitution. We observed notable g-value shifts in the EPR for the cysteine-substituted iron-sulfur cluster in addition to significant downward shifts in the redox potential, as well as the disappearance of several low-field signals observed in the native NfnSL complex. These results suggest the site-differentiated glutamate residue facilitates higher spin states in the [4Fesingle bond4S] cluster to bridge energetic gaps in electron transfer to the bifurcating flavin in the native complex, preventing unwanted short-circuiting seen in the cysteine-substituted complex.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Understanding latent timescales in neural ordinary differential equation models of advection-dominated dynamical systems

The neural ordinary differential equation (ODE) framework has shown considerable promise in recent years in developing highly accelerated surrogate models for complex physical systems characterized by partial differential equations (PDEs). For PDE-based systems, state-of-the-art neural ODE strategies leverage a two-step procedure to achieve this acceleration: a nonlinear dimensionality reduction step provided by an autoencoder, and a time integration step provided by a neural-network based model for the resultant latent space dynamics (the neural ODE). This work explores the applicability of such autoencoder-based neural ODE strategies for PDEs in which advection terms play a critical role. More specifically, alongside predictive demonstrations, physical insight into the sources of model acceleration (i.e., how the neural ODE achieves its acceleration) is the scope of the current study. Such investigations are performed by quantifying the effects of both autoencoder and neural ODE components on latent system time-scales using eigenvalue analysis of dynamical system Jacobians. To this end, the sensitivity of various critical training parameters – de-coupled versus end-to-end training, latent space dimensionality, and the role of training trajectory length, for example – to both model accuracy and the discovered latent system timescales is quantified. Furthermore, this work specifically uncovers the key role played by the training trajectory length (the number of rollout steps in the loss function during training) on the latent system timescales: larger trajectory lengths correlate with an increase in limiting neural ODE time-scales, and optimal neural ODEs are found to recover the largest time-scales of the full-order (ground-truth) system. Demonstrations are performed across fundamentally different unsteady fluid dynamics configurations influenced by advection: (1) the Kuramoto–Sivashinsky equations (2) Hydrogen-Air channel detonations (the compressible reacting Navier–Stokes equations with detailed chemistry), and (3) 2D Atmospheric flow.

Advection-dominated dynamical systems↗

First measurement of polarized spin-density matrix elements and differential cross sections dσ/dt in ω photoproduction off the proton for 2.7 < Eγ < 5.2 GeV using CLAS at Jefferson Lab

We report on the differential cross sections dσ/dt, the unpolarized spin-density matrix elements ρ 00 0 , ρ 1 − 1 0 , Re ρ 10 0 , and the first extraction of the polarized elements Im ρ 10 3 , Im ρ 1 − 1 3 for the reaction γp → pω using the CLAS spectrometer at Jefferson Laboratory. The ω mesons were detected in their dominant charged decay mode, ω → π + π − π 0 , and all t-dependent results are presented in a fine binning for incident photon energies between 2.73 and 5.16 GeV (corresponding to the center-of-mass energy range W ∈ [ 2.45, 3.25 ] GeV). All matrix elements are first measurements for − t > 0.6 GeV2. Moreover, differential cross sections dσ/d(cos Θ c . m . ω ) and the corresponding angle-dependent unpolarized spin-density matrix elements in the Adair frame are presented for the incident photon energy range 1.56–3.80 GeV (corresponding to W ∈ [ 1.95, 2.83 ] GeV). These new ω photoproduction data are consistent with earlier CLAS results but extend the energy range well beyond the nucleon resonance region into the Regge regime. The comparison with Regge-theory-based model predictions shows that the new data impose more stringent constraints on our understanding of ω photoproduction.

Hu, T.↗

Structure and dynamics of magneto-inertial, differentially rotating laboratory plasmas

We present a detailed characterization of the structure and evolution of differentially rotating plasmas driven on the MAGPIE pulsed-power generator (1.4 MA peak current, 240 ns rise time). The experiments were designed to simulate physics relevant to accretion discs and jets on laboratory scales. A cylindrical aluminium wire array Z pinch enclosed by return posts with an overall azimuthal off-set angle was driven to produce ablation plasma flows that propagate inwards in a slightly off-radial trajectory, injecting mass, angular momentum and confining ram pressure to a rotating plasma column on the axis. However, the plasma is free to expand axially, forming a collimated, differentially rotating axial jet that propagates at ${\approx }100\,{\rm km}\,{\rm s}^{-1}$ . The density profile of the jet corresponds to a dense shell surrounding a low-density core, which is consistent with the centrifugal barrier effect being sustained along the jet's propagation. We show analytically that, as the rotating plasma accretes mass, conservation of mass and momentum implies plasma radial growth scaling as $r \propto t^{1/3}$ . As the characteristic moment of inertia increases, the rotation velocity is predicted to decrease and settle on a characteristic value ${\approx }20\,{\rm km}\,{\rm s}^{-1}$ . We find that both predictions are in agreement with Thomson scattering and optical self-emission imaging measurements.

Valenzuela-Villaseca, V. (ORCID:0000000167721441)↗

Inferring Plant Acclimation and Improving Model Generalizability With Differentiable Physics‐Informed Machine Learning of Photosynthesis

Net photosynthesis (A N ) is a key component of the global carbon cycle influencing climate feedback over decadal scales. Although plant acclimation to environmental changes can modify A N , traditional vegetation models in Earth system models (ESMs) often rely on plant functional type (PFT)-specific parameterizations or simplified acclimation assumptions limiting generalizability across time, space, and PFTs. In this study, we developed a differentiable photosynthesis model to learn the environmental dependencies of V c,max25 (maximum carboxylation rate at 25°C, representing photosynthetic capacity), as this genre of hybrid physics-informed machine learning can seamlessly train neural networks and process-based equations together. Compared to PFT-specific parameterization of V c,max25 , learning the environment dependencies of key photosynthetic parameters improved model spatiotemporal generalizability. Applying environmental acclimation to V c,max25 led to substantial variations in global mean A N indicating the need to address acclimation in ESMs. The model effectively captured multivariate observations (V c,max25 , A N , and stomatal conductance (g s )) simultaneously with multivariate constraints, improving generalization across space and PFTs. It also learned sensible acclimation relationships of V c,max25 to different environmental conditions. The model explained more than 54%, 57%, and 62% of the variance of A N , g s , and V c,max25 , respectively, presenting a first global-scale spatial test benchmark of A N and g s . These results highlight the potential for differentiable modeling to enhance process-based modules in ESMs and effectively leverage information from large, multivariate data sets.

54 ENVIRONMENTAL SCIENCES↗

Ecological trade-offs drive phenotypic and genetic differentiation of Arabidopsis thaliana in Europe

Plant diversity is shaped by trade-offs between traits related to competitive ability, propagule dispersal, and stress resistance. However, we still lack a clear understanding of how these trade-offs influence species distribution and population dynamics. In Arabidopsis thaliana , recent genetic analyses revealed a group of cosmopolitan genotypes that successfully recolonized Europe from its center after the last glaciation, excluding older (relict) lineages from the distribution except for their north and south margins. Here, we tested the hypothesis that cosmopolitans expanded due to higher colonization ability, while relicts persisted at the margins due to higher tolerance to competition and/or stress. We compared the phenotypic and genetic differentiation between 71 European genotypes originating from the center, and the south and north margins. We showed that a trade-off between plant fecundity and seed mass shapes the differentiation of A. thaliana in Europe, suggesting that the success of the cosmopolitan groups could be explained by their high dispersal ability. However, at both north and south margins, we found evidence of selection for alleles conferring low dispersal but highly competitive and stress-resistance abilities. This study sheds light on the role of ecological trade-offs as evolutionary drivers of the distribution and dynamics of plant populations.

59 BASIC BIOLOGICAL SCIENCES↗

Cu site differentiation in tetracopper(I) sulfide clusters enables biomimetic N 2 O reduction

Copper clusters feature prominently in both metalloenzymes and synthetic nanoclusters that mediate catalytic redox transformations of gaseous small molecules. Such reactions are critical to biological energy conversion and are expected to be crucial parts of renewable energy economies. However, the precise roles of individual metal atoms within clusters are difficult to elucidate, particularly for cluster systems that are dynamic under operating conditions. Here, we present a metal site-specific analysis of synthetic Cu 4 (μ 4 -S) clusters that mimic the Cu Z active site of the nitrous oxide reductase enzyme. Leveraging the ability to obtain structural snapshots of both inactive and active forms of the synthetic model system, we analyzed both states using resonant X-ray diffraction anomalous fine structure (DAFS), a technique that enables X-ray absorption profiles of individual metal sites within a cluster to be extracted independently. Using DAFS, we found that a change in cluster geometry between the inactive and active states is correlated to Cu site differentiation that is presumably required for efficient activation of N 2 O gas. More precisely, we hypothesize that the Cu δ+ ∙∙∙Cu δ- pairs produced upon site differentiation are poised for N 2 O activation, as supported by computational modeling. These results provide an unprecedented level of detail on the roles of individual metal sites within the synthetic cluster system and how those roles interplay with cluster geometry to impact the reactivity function. We expect this fundamental knowledge to inform understanding of metal clusters in settings ranging from (bio)molecular to nanocluster to extended solid systems involved in energy conversion.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Interface-modulated kinetic differentials in electron and hole transfer rates as a key design principle for redox photocatalysis by Sb2VO5/QD heterostructures

The efficient conversion of solar energy to chemical energy represents a critical bottleneck to the energy transition. Photocatalytic splitting of water to generate solar fuels is a promising solution. Semiconductor quantum dots (QDs) are prime candidates for light-harvesting components of photocatalytic heterostructures, given their size-dependent photophysical properties and band-edge energies. A promising series of heterostructured photocatalysts interface QDs with transition-metal oxides which embed midgap electronic states derived from the stereochemically active electron lone pairs of p-block cations. Here, we examine the thermodynamic driving forces and dynamics of charge separation in Sb2VO5/CdSe QD heterostructures, wherein a high density of Sb 5s2-derived midgap states are prospective acceptors for photogenerated holes. Hard-x-ray valence band photoemission spectroscopy measurements of Sb2VO5/CdSe QD heterostructures were used to deduce thermodynamic driving forces for charge separation. Interfacial charge transfer dynamics in the heterostructures were examined as a function of the mode of interfacial connectivity, contrasting heterostructures with direct interfaces assembled by successive ion layer adsorption and reaction (SILAR) and interfaces comprising molecular bridges assembled by linker-assisted assembly (LAA). Transient absorption spectroscopy measurements indicate ultrafast (<2 ps) electron and hole transfer in SILAR-derived heterostructures, whereas LAA-derived heterostructures show orders of magnitude differentials in the kinetics of hole (<100 ps) and electron (∼1 ns) transfer. The interface-modulated kinetic differentials in electron and hole transfer rates underpin the more effective charge separation, reduced charge recombination, and greater photocatalytic efficiency observed for the LAA-derived Sb2VO5/CdSe QD heterostructures.

Chemistry↗

Performant automatic differentiation of local coupled cluster theories: Response properties and ab initio molecular dynamics

In this work, we introduce a differentiable implementation of the local natural orbital coupled cluster (LNO-CC) method within the automatic differentiation framework of the PySCFAD package. The implementation is comprehensively tuned for enhanced performance, which enables the calculation of first-order static response properties on medium-sized molecular systems using coupled cluster theory with single, double, and perturbative triple excitations [CCSD(T)]. We evaluate the accuracy of our method by benchmarking it against the canonical CCSD(T) reference for nuclear gradients, dipole moments, and geometry optimizations. In addition, we demonstrate the possibility of property calculations for chemically interesting systems through the computation of bond orders and Mössbauer spectroscopy parameters for a [NiFe]-hydrogenase active site model, along with the simulation of infrared spectra via ab initio LNO-CC molecular dynamics for a protonated water hexamer.

Chemistry↗

A generalized effective potential for differentially rotating plasmas

Global stability of differentially rotating plasma is investigated using a generalized effective potential. We first, for a current-free system, obtain a general form of an effective potential in terms of the free energies of global curvature and gradients of rotation for non-axisymmetric disturbances. We then examine the stability of differentially rotating disks for several rotation profiles and present the associated effective potential for the onset of these instabilities in the MHD regime. In particular, results for global axisymmetric magnetorotational instability as well as local and global non-axisymmetric modes are presented. The latter constitute two distinct non-axisymmetric modes, a high frequency local MRI and a global low-frequency non-axisymmetric mode (the magneto-curvature mode, introduced in Ebrahimi and Pharr [Astrophys. J. 936, 145 (2022)]), confined either between two Alfvénic resonances or an Alfvénic resonance and a boundary.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Crystal generation using the fully differentiable pipeline and latent space optimization

We present a materials generation framework that couples a symmetry-conditioned variational autoencoder with a differentiable SO(3) power spectrum objective to steer candidates toward a specified local environment under the crystallographic constraints. In particular, we implement a fully differentiable pipeline that performs batch-wise optimization on both direct and latent crystallographic representations. Using the GPU acceleration, the implementation achieves about fivefold speed compared to our previous CPU workflow, while yielding comparable outcomes. In addition, we introduce the optimization strategy that alternatively performs optimization on the direct and latent crystal representations. This dual-level relaxation approach can effectively escape local minima defined by different objective gradients, thus increasing the success rate of generating complex structures satisfying the target local environments. This framework can be extended to systems consisting of multi-components and multi-environments, providing a scalable route to generate material structures with the target local environment.

conditional VAE↗