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At least 109 records · Page 6

Priors on red galaxy stochasticity from hybrid effective field theory

ABSTRACT We investigate the stochastic properties of typical red galaxy samples in a controlled numerical environment. We use halo occupation distribution (HOD) modelling to create mock realizations of three separate bright red galaxy samples consistent with data sets used for clustering and lensing analyses in modern galaxy surveys. Second-order Hybrid Effective Field Theory (HEFT) is used as a field-level forward model to describe the full statistical distribution of these tracer samples, and their stochastic power spectra are directly measured and compared to the Poisson shot-noise prediction. While all of the galaxy samples we consider are hosted within haloes with sub-Poisson stochasticity, we observe that the galaxy samples themselves possess stochasticities that range from sub-Poisson to super-Poisson, in agreement with predictions from the halo model. As an application of our methodology, we place priors on the expected degree of non-Poisson stochasticity in cosmological analyses using such samples. We expect these priors will be useful in reducing the complexity of the full parameter space for future analyses using second-order Lagrangian bias models. More generally, the techniques outlined here present the first application of HEFT methods to characterize models of the galaxy–halo connection at the field level, revealing new connections between once-disparate modelling frameworks.

79 ASTRONOMY AND ASTROPHYSICS↗

Electric Vehicle Managed Charging: Forward-Looking Estimates of Bulk Power System Value

When and where electric vehicle charging occurs has significant implications for power systems supporting widespread electric vehicle deployment with high shares of wind and solar generation. Numerous studies have estimated the value of scheduling or otherwise managing electric vehicle charging in such power systems. This study improves on those earlier works by leveraging detailed simulation models for electric vehicle adoption, electric vehicle use, electric vehicle charging, and bulk power system operations; and linking them with methods for describing charging flexibility at both the individual vehicle and aggregate levels. This study closely analyzes electric vehicle managed charging (EVMC) performance along the dimensions of flexibility type (within-charging session or within-week scheduling), dispatch mechanism (direct load control or one of several price-based mechanisms), and participation rate, under the assumptions of ubiquitous chargers and all trips completed on time. The study is located in a passenger light-duty vehicle adoption scenario with 100% electric vehicle sales by 2035, and in an envisioned 2038 New England power system for which within-region generation is 84% clean.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

On the Reliability of Parameter Inferences in a Multiscale Model for Transport in Stream Corridors

Nonreacting tracer tests capture information about physical processes in transient storage zones including the hyporheic zone (HZ). However, reliably extracting this information from breakthrough curves (BTCs) and distinguishing the effects of in-channel dispersion and transient storage are well-known challenges. Using BTCs from a nonreacting tracer test monitored at multiple locations, we explore ways for reliable parameter estimations. The identifiability of parameters is greatly influenced by the choice of forward and inverse modeling frameworks in addition to the quality of the data. Our forward model is a recently proposed multiscale model that uses subgrid transport models written in the Lagrangian form to represent transport along a diverse set of HZ pathways with a shape-free distribution of travel times. Joint distributions of HZ and channel parameters are estimated using the Markov Chain Monte Carlo technique. Numerical experiments show ambiguity between channel dispersion and HZ transport when the reach length is too short to allow significant solute-HZ interaction, the observation period is too brief to observe the tailing behavior, or the solute source is spread in time. In contrast, we obtained reliable parameter estimates by simultaneously fitting BTCs observed at different locations in the test reach using a single set of HZ parameters and section-specific channel areas and dispersion coefficients. Furthermore, this study demonstrates the estimation of travel time distributions, HZ exchange rates, and channel parameters in a new multiscale approach and offers guidance for extracting reliable parameter estimates from multiple BTCs.

54 ENVIRONMENTAL SCIENCES↗

Causal explicit algorithm for heat conduction in a plasma

Hyperbolic heat conduction extends standard Spitzer-Harm heat conduction by including a term proportional to the time derivative of the heat flux. The new term arises from a kinetic derivation of the heat flux that includes higher order corrections. Here we present a causal explicit numerical algorithm for solving the nonlinear hyperbolic heat conduction equation in an unmagnetized plasma. The maximum stable timestep for the causal explicit algorithm scales linearly with the cell size, owing to the hyperbolic nature of the problem. This is in contrast to the quadratic scaling of the maximum stable timestep with the cell size for the parabolic forward time centered space algorithm. The favorable scaling of the timestep with the cell size enables a practical explicit implementation of heat conduction in high-performance massively parallel plasma codes. In particular, we have implemented the causal explicit algorithm in the laser plasma interaction code pF3D. We verify the CE algorithm and analyze its convergence rate by simulating a harmonic mode, which has an analytic solution within the context of the HHC model. We also compare simulations using the CE algorithm to those using the forward time centered space algorithm on a pair of test problems: evolution in time of a Gaussian temperature perturbation in a uniform plasma and heat transport in the presence of inverse bremsstrahlung heating by a Gaussian laser speckle.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Spanning the Gap From Bulk to Bin: A Novel Spectral Microphysics Method

Microphysics methods for climate models and numerical weather prediction typically track one, two, or three moments of a droplet size distribution for various categories of liquid, ice, and aerosol. Such methods rely on conversion parameters between these categories, which introduces uncertainty into predictions. While higher-fidelity options such as bin and Lagrangian schemes exist, they require too many degrees of freedom for climate modeling applications and introduce numerical challenges. Here we introduce a flexible spectral microphysics method based on collocation of basis functions. This method generalizes to a linear bulk scheme when using few basis functions and to a smoothed bin scheme with more degrees of freedom. Tested in an idealized box setting, the method improves spectral accuracy for droplet collision-coalescence and may eliminate the need for precipitation autoconversion rates required by bulk methods; furthermore, it generalizes well to multimodal distributions with less complexity than a bin method. The potential to extend this collocation representation to multiple hydrometeor classes suggests a path forward to unify liquid, ice, and aerosol microphysics in a single, flexible, computational framework for climate modeling.

54 ENVIRONMENTAL SCIENCES↗

Modeling phonon-mediated quasiparticle poisoning in superconducting qubit arrays

Correlated errors caused by ionizing radiation impacting superconducting qubit chips are problematic for quantum error correction. Such impacts generate quasiparticle (QP) excitations in the qubit electrodes, which temporarily reduce qubit coherence significantly. The many energetic phonons produced by a particle impact travel efficiently throughout the device substrate and generate quasiparticles with high probability, thus causing errors on a large fraction of the qubits in an array simultaneously. Here, we describe a comprehensive strategy for the numerical simulation of the phonon and quasiparticle dynamics in the aftermath of an impact. We compare the simulations with experimental measurements of phonon-mediated QP poisoning and demonstrate that our modeling captures the spatial and temporal footprint of the QP poisoning for various configurations of phonon downconversion structures. We thus present a path forward for the operation of superconducting quantum processors in the presence of ionizing radiation.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Selenium interaction with iron minerals: Quantitative comparison of sorption and coprecipitation impacts on mobility

Given the significance of selenium (Se) as a micronutrient, the radioactive nature of some of its isotopes, and its affinity to iron (Fe) minerals, extensive research has been conducted on the sorption mechanisms between Se and these minerals. Here, in this study, we employ sorption data sourced from the L-SCIE database and coprecipitation data from available literature to achieve the following objectives: i) establish coherence between adsorption and coprecipitation processes, ii) quantitatively evaluate the importance of these processes in nuclear waste repository science, and iii) propose a forward-looking approach for integrating coprecipitation into reactive transport models. Our findings indicate that a correlation between Se adsorption and coprecipitation can be established using the λ formalism. The comparable log(λ Se(IV) /λ Se(VI) ) ratios derived from adsorption and coprecipitation experiments suggest that these processes can be quantitatively compared and evaluated using our numerical approach. Across all iron oxide phases examined, coprecipitation leads to significantly greater immobilization of Se compared to adsorption. Specifically, for hydrous ferric oxide, hematite, and goethite, coprecipitation is predicted to result in 100–1000 times more Se immobilization compared to adsorption, irrespective of the Se oxidation state (Se(IV) or Se(VI)); notably stronger immobilization potential via coprecipitation was observed for magnetite. The modeling approach and quantitative analysis presented herein clearly highlight the importance of including coprecipitation processes when simulating Se (and other elements) transport, particularly under conditions where mineral compositions are transient or evolving with time. Neglecting coprecipitation in models is likely to lead to significant overestimates of migration.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

Relevance of anisotropy in the Kondo effect: Lessons from the symplectic case

A Kondo model with symplectic symmetry was recently put forward as the effective low-energy theory of a superconducting-island device coupled to multiple leads. This model, which possesses non-Fermi liquid physics and effective anyons, was argued to belong to the class of topological Kondo effects. Here, we clarify the extent of stability of its exotic fixed point using perturbative and numerical renormalization group in conjunction with bosonization and conformal field theory. In contrast to previous claims, we show that asymmetry in the coupling to the leads destabilizes the non-Fermi liquid. Other destabilizing perturbations include asymmetry in the superconducting pairing or internal energy of the individual quantum dots in the island. Nevertheless, these perturbations all generate the same relevant operators. Thus, only a small number of couplings need to be tuned individually, and these can be selected according to experimental convenience. Our results highlight a common misconception that anisotropy in single-channel Kondo couplings is always irrelevant. As demonstrated, relevant terms will emerge whenever the group generators do not span the full space of impurity operators. This calls for a more detailed inspection of models that exhibit this property, such as large-spin impurities and SO⁡( M ) Kondo models.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Unsupervised Learning Based Interaction Force Model for Nonspherical Particles in Incompressible Flows

This project provides a neural network-based interaction force model for gas-solid flows from low to intermediate Reynolds numbers and concentration, which can be linked to MFiX-DEM. We have constructed a database of the interaction force between the irregular-shaped particles using a spherical harmonic method and the fluid phase based on the particle-resolved direct numerical simulation (PR-DNS) with immersed boundary-based gas kinetic scheme. Unsupervised learning method, i.e., variational auto-encoder (VAE) has been applied to extract the primitive shape factors determining the drag force, lifting forces, and torque. The interaction force model has been trained and validated with a simple but effective multi-layer feed-forward neural network: multi-layer perceptron (MLP), which will be concatenated after the encoder of the previously trained VAE for geometry feature extraction for single, irregular particles. We have trained transpose convolutional neural networks with the PR-DNS data to predict the velocity and pressure gradient of the single particle systems and utilized them to calculate drag force of multi-particle systems. This model can provide high computational efficiency because it does not require collecting multiparticle system data from PR-DNS.

99 GENERAL AND MISCELLANEOUS↗

Enhancing photoionization rate calculations in low-temperature plasmas using spectral methods

Photoionization plays a central role in the development of streamer discharges and other non-equilibrium plasma phenomena. It creates seed electrons, which are essential for positive streamer propagation, allowing the ionization front to move forward. Because of this, accurate modeling of photoionization is very important for predicting streamer behavior and plasma evolution. The photoionization process in air (N 2 – O 2 mixture) is often described by the Zheleznyak model (1982). This model is usually solved through Helmholtz-type equations that approximate the Zheleznyak photoionization model (Zheleznyak et al. 1982) as Partial Differential Equations (PDEs). Conventional numerical methods, such as the Finite Difference Method (FDM) or Finite Volume Method (FVM), are widely used to solve these equations. Although they are prevalent, the computational cost of these methods due to their need for matrix operations and iterative solver is demanding. To address this challenge, this work develops a spectral solver based on the Fast Fourier Transform (FFT) combined with Discrete Cosine Transform (DCT) and Discrete Sine Transform (DST) to calculate the photoionization rate efficiently in an axisymmetric cylindrical domain. This method naturally satisfies the boundary conditions used in the model and converts the PDE into algebraic ones in spectral space. Thus, avoids the need for iterative matrix solvers. When compared with FDM results, it is demonstrated that the new solver not only maintains accuracy, but also reduces the computational cost, showing a performance increase of approximately 100 compared to FDM over a wide range of problem sizes. The method is parallelized using Message Passing Interface (MPI) and has been integrated into a fluid plasma model for streamer simulation. Here, this FFT-based approach provides a fast and reliable alternative for calculating photoionization in fluid models, helping large-scale plasma simulations run faster and efficiently, and allows higher-resolution simulation without extra computational cost.

Axisymmetric system↗

Complexity growth in integrable and chaotic models

We use the SYK family of models with N Majorana fermions to study the complexity of time evolution, formulated as the shortest geodesic length on the unitary group manifold between the identity and the time evolution operator, in free, integrable, and chaotic systems. Initially, the shortest geodesic follows the time evolution trajectory, and hence complexity grows linearly in time. We study how this linear growth is eventually truncated by the appearance and accumulation of conjugate points, which signal the presence of shorter geodesics intersecting the time evolution trajectory. By explicitly locating such “shortcuts” through analytical and numerical methods, we demonstrate that: (a) in the free theory, time evolution encounters conjugate points at a polynomial time; consequently complexity growth truncates at O($\sqrt{N}$), and we find an explicit operator which “fast-forwards” the free N-fermion time evolution with this complexity, (b) in a class of interacting integrable theories, the complexity is upper bounded by O(poly(N)), and (c) in chaotic theories, we argue that conjugate points do not occur until exponential times O(e N ), after which it becomes possible to find infinitesimally nearby geodesics which approximate the time evolution operator. Finally, we explore the notion of eigenstate complexity in free, integrable, and chaotic models.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Development and preliminary results of 270 GHz microwave forward scattering diagnostic system on the experimental advanced superconducting tokamak (EAST)

To measure localized (intermediate, high) poloidal wavenumber electron density fluctuations, a tangential millimeter-wave collective scattering system has been designed and successfully developed on the experimental advanced superconducting tokamak (EAST). This innovative system employs a 270 GHz mm-wave probe beam, emitted from the mid-plane of Port K and directed towards Port P after passing through a combination of two in-vessel mirrors. Here these two ports are located on the EAST device’s midplane and are 110° apart. The downward scattered signals pass through two in-vessel mirrors, and exit through the P window. The received multi-channel separated scattering signals are arranged along the poloidal direction. This optical arrangement makes the monitored turbulent wave number is poloidal dominant and up to 40 cm −1 . The tangential microwave scattering scheme enables this diagnostic to monitor local density fluctuations, with typically a radial spatial resolution △ R = 5 cm, and a wavenumber resolution of △ k = 0.4 cm −1 . The scattering system underwent comprehensive laboratory testing in 2023, with installation finalized in 2024. The system features steerable launch and receiver optics, allowing remote control to position the scattering volume from normalized radius ρ –0 to the pedestal region on a shot-by-shot basis. Effective experimental data, characterized by distinct off-center spectral peaks, have been successfully obtained in neutral beam-heated plasmas on EAST. The beam tracing forward modeling has been employed for experimental data interpretation. The advanced millimeter-wave scattering system provides fluctuation measurement capability from ion temperature gradient to electron temperature gradient scale on low field side. Preliminary experimental density fluctuation data have been successfully obtained in neutral beam-heated plasmas on EAST. The localized measurement will be used for kinetic turbulence transport numerical simulation validation.

high-k collective scattering↗

Recent evolution of risk analyses in atomic bomb survivor studies: new methods and applications

Abstract Several decades ago a dramatic leap forward occurred in the development and application of statistical methods for modeling radiation risk at the Radiation Effects Research Foundation (RERF). Poisson regression analysis for grouped person-year cohort data and the linear excess relative risk model were introduced, and subsequently a devoted software system, Epicure® (https://www.hirosoft.com), was developed by researchers at RERF and at the U.S. National Cancer Institute. Numerous advancements in understanding radiation effects on humans were made possible with these methods, which are still the state-of-the-art for risk assessment at RERF and have remained part of the standard toolbox for radiation—and other environmental—epidemiological studies worldwide. Nevertheless, as our understanding of radiation risk has increased, so have the breadth and depth of questions that require answers based on emerging data that are not amenable to these conventional methods. This overview briefly recounts the conventional methods and then describes our recent diversification into the use or development of new statistical approaches to meet the challenges of burgeoning biological data and emerging mechanistic information. We briefly discuss the development and application of new methods, current and planned, that are part of the RERF Statistics Department’s role in supporting institution-wide research, especially in our collaborations involving the Life Span Study, Adult Health Study, and First-generation Offspring Clinical Study. Some approaches to modeling and assessing radiation risk with newer methods mentioned herein have already been published, while some are still in development or are only beginning at the proposal stage.

Oncology↗

Two-level overlapping additive Schwarz preconditioner for training scientific machine learning applications

In this work we introduce a novel two-level overlapping additive Schwarz preconditioner for accelerating the training of scientific machine learning applications. The design of the proposed preconditioner is motivated by the nonlinear two-level overlapping additive Schwarz preconditioner. The neural network parameters are decomposed into groups (subdomains) with overlapping regions. In addition, the network’s feed-forward structure is indirectly imposed through a novel subdomain-wise synchronization strategy and a coarse-level training step. Through a series of numerical experiments, which consider physicsinformed neural networks and operator learning approaches, we demonstrate that the proposed two-level preconditioner significantly speeds up the convergence of the standard (LBFGS) optimizer while also yielding more accurate machine learning models. Moreover, the devised preconditioner is designed to take advantage of model-parallel computations, which can further reduce the training time.

97 MATHEMATICS AND COMPUTING↗

Time-Lapse Gravity Monitoring of CO2 Migration Based on Numerical Modeling of a Faulted Storage Complex

In this study, the performance of both surface and borehole time-lapse gravity monitoring to detect CO2 leakage from a carbon storage site is evaluated. Several hypothetical scenarios of CO2 migration in a leaky fault, and thief zones at different depths at the Kimberlina site (California, USA) constitute the basis of the approach. The CO2 displacement is simulated using the TOUGH2 simulator applied to a detailed geological model of the site. The gravity responses to these CO2 plumes are simulated using forward modeling with sensors at ground surface and in vertical boreholes. Results of inversion on one scenario are also presented. The surface-based gravity responses obtained for the different leakage scenarios demonstrate that leakage can be detected at the surface in all the scenarios but the time to detection is highly variable (10 to 40 years) and dependent on the detection threshold considered. Borehole measurements of the vertical component of gravity provide excellent constrains in depth when they are located in proximity of the density anomaly associated with the presence of CO2, thus discriminating multiple leaks in different thief zones. Joint inversion of surface and borehole data can bring valuable information of the occurrence of leakages and their importance by providing a reasonable estimate of mass of displaced fluids. This study demonstrates the importance of combining multiphase flow simulations with gravity modeling in order to define if and when gravity monitoring would be applicable at a given storage site.

Time-lapse gravity monitoring, leak detection, CCS↗

Field-level reconstruction from foreground-contaminated 21-cm maps

Current and upcoming 21-cm experiments will soon be able to map 21-cm spatial fluctuations in three dimensions for a wide range of redshifts. However, bright foreground contamination and the nature of radio interferometry create significant challenges, making it difficult to access rich cosmological information from the Fourier modes that lie within the “foreground wedge”. Here, in this work, we introduce two approaches aiming to reconstruct the full 21-cm density field, including the missing modes in the wedge: (a) a field-level inference under an effective field theory (EFT) framework; (b) a diffusion-based deep generative model trained on simulations. Under the EFT framework, we implement a fully differentiable forward model that maps the initial conditions of matter fluctuations to the observed, foreground-filtered 21-cm maps. This enables a gradient-based sampler to simultaneously sample the initial conditions and bias parameters, allowing a physically motivated mode reconstruction. Alternatively, we apply a variational diffusion model to perform 21-cm density reconstruction at the map level. Our model is trained on semi-numerical simulations over a wide range of astrophysical parameters. Our results from both approaches should provide improved cosmological constraints from the field level and also enable cross-correlation between experiments that have little or no overlapping modes.

cosmological perturbation theory↗

Dynamically reconfigurable topological routing in nonlinear photonic systems

The propagation path of topologically protected states is bound to the interface between regions with different topology, and as such, the functionality of linear photonic devices leveraging these states is fixed during fabrication. Here, we propose a mechanism for dynamic control over a driven dissipative system’s local topology, yielding reconfigurable topological interfaces and thus tunable paths for protected routing. We illustrate our approach in non-resonantly pumped polariton lattices, where the nonlinear interaction between the polaritons and the exciton reservoir due to non-resonant pumping can yield picosecond-scale changes in the propagation paths of the chiral edge states. To analytically confirm the numerically observed topological dynamics, we generalize the spectral localizer framework to non-linear non-Hermitian Chern materials and apply this framework to a continuous model of the polariton system based on a driven-dissipative Gross-Pitaevskii equation. In doing so, we show that the local changes in the polariton lattice’s topology are captured by a local Chern marker. Looking forward, we anticipate such reconfigurable topological routing will enable the realization of novel classes of topological photonic devices.

Wong, Stephan [Sandia National Laboratories (SNL-N↗

Scrambling Dynamics with Imperfections in a Solvable Model

We study how probes of quantum scrambling dynamics respond to two kinds of imperfections -- unequal forward and backward evolutions and decoherence -- in a solvable Brownian circuit model. We calculate a ``renormalized'' out-of-time-order correlator (ROTOC) in the model with $N$ qubits, and we show that the circuit-averaged ROTOC is controlled by an effective probability distribution in operator weight space which obeys a system of $N$ non-linear equations of motion. These equations can be easily solved numerically for large system sizes which are beyond the reach of exact methods. Moreover, for an operator initially concentrated on weight one $w_0=1$, we provide an exact solution to the equations in the thermodynamic limit of many qubits that is valid for all times, all non-vanishing perturbation strengths $p\gtrsim 1/\sqrt{N}$, and all decoherence strengths. We also show that a generic initial condition $w_0 >1$ leads to a metastable state that eventually collapses to the $w_0=1$ case after a lifetime $\sim \log(N/w_0)$. Our results highlight situations where it is still possible to extract the unperturbed chaos exponent even in the presence of imperfections, and we comment on the applications of our results to existing experiments with nuclear spins and to future scrambling experiments.

FOS: Physical sciences↗