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At least 271 records · Page 15

FolpsD: combining EFT and phenomenological approaches for joint power spectrum and bispectrum analyses

We present a theoretical model for the power spectrum and bispectrum of galaxy clustering that exploits the complementarity between small-scale power spectrum information and large-scale bispectrum measurements. We extend the FOLPS code by combining its one-loop EFT galaxy power spectrum with a tree-level galaxy bispectrum projected onto the tripolar spherical harmonics (Sugiyama) basis. To access additional small-scale information, we also consider a line-of-sight damping factor in both statistics, mirroring approaches commonly used in studies of redshift-space distortions. We test the model using DESI DR2 galaxy mocks. Even without damping, the joint analysis of the EFT power spectrum and bispectrum significantly improves constraints and reduces parameter degeneracies relative to power spectrum analyses alone. For LRG-like samples, including the damping further extends the range beyond $k\sim 0.3 \,h \text{Mpc}^{-1}$ in the power spectrum and $k \sim 0.24 \,h \text{Mpc}^{-1}$ in the bispectrum without introducing statistically significant parameter biases. This leads to up to $\sim 30\%$ tighter constraints on $A_s$ and $ω_{cdm}$. For low signal-to-noise tracers such as QSOs, however, the damping parameters are weakly constrained and can absorb noise fluctuations, leading to shifts in inferred parameters. Similar limitations may arise in models where cosmological information is encoded in power-spectrum shape features degenerate with the damping, such as scenarios with massive neutrinos. In contrast, for $w_0w_a$CDM we obtain $15\%$ and $21\%$ tighter constraints on $w_0$ and $w_a$, respectively, yielding a deviation from constant dark energy at slightly more than the $1σ$ level using full-shape information alone. The code is publicly available at https://github.com/cosmodesi/FolpsD

Bansal, P. [Michigan U., MCTP; Michigan U.] (ORCID↗

Enhancements in Cloud Condensation Nuclei Activity From Turbulent Fluctuations in Supersaturation

Abstract The effect of aerosols on the properties of clouds is a large source of uncertainty in predictions of weather and climate. These aerosol‐cloud interactions depend critically on the ability of aerosol particles to form cloud droplets. A challenge in modeling aerosol‐cloud interactions is the representation of interactions between turbulence and cloud microphysics. Turbulent mixing leads to small‐scale fluctuations in water vapor and temperature that are unresolved in large‐scale atmospheric models. To quantify the impact of turbulent fluctuations on cloud condensation nuclei (CCN) activation, we used a high‐resolution Large Eddy Simulation of a convective cloud chamber to drive particle‐based cloud microphysics simulations. We show small‐scale fluctuations strongly impact CCN activity. Once activated, the relatively long timescales of evaporation compared to fluctuations causes droplets to persist in subsaturated regions, which further increases droplet concentrations.

54 ENVIRONMENTAL SCIENCES↗

HED Hydrodynamics in the Common Modeling Framework

Within the Common Modeling Framework (CMF), the HED Hydrodynamics Project has implemented a common methodology, or "Authority", for modeling high energy density (HED) experiments by extending development of the Eulerian Applications Project code Authority, "EAPA," to include relevant physics models, customization tools and templates, and in situ and post-processing capabilities. Additionally, several models for small-scale HED experiments were successfully added to the CMF and simulations reproduce the results of preexisting, benchmarked input decks. We expect use of the CMF to improve our effectiveness in developing predictive capabilities for experiments ranging from small-scale planar single-interface, single-shock to multi-interface, multi-shock configurations and up through multi-shell inertial confinement fusion (ICF) implosions. Additionally, this will strengthen our ability to design future targeted experiments. Using the CMF infrastructure and Authorities for HED modeling has three key impacts. First, it enables a version-controlled, pedigreed and archived base model for each experiment with tools that allow easy setup, execution and analysis of simulations to assess and/or expose sensitivities to various parameters. Second, having a common base set of inputs and physics definitions helps identify systematic differences between models in the codes and experimental data to support code validation, and build confidence in our predictive capabilities. Finally, designed to work in concert with multiple programs and projects including PEM, IC, OES, V&V and DSW, the CMF supports improved collaboration and integration through shared model definitions, data, simulations and results, enhancing the workflow required to underwrite the knowledge base and capabilities ultimately required for stockpile stewardship

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

HERO WEC V1: Design and Experimental Data Collection Efforts

The Hydraulic and Electric Reverse Osmosis Wave Energy Converter (HERO WEC) is a research platform aimed at developing a modular, small-scale wave-powered desalination system for remote and disaster-response applications. Funded by the Department of Energy (DOE)'s Water Power Technologies Office (WPTO), the project aims to advance wave-powered desalination by developing and testing a small-scale, modular wave energy converter (WEC). The insights gained from this project will help guide the design and development of larger-scale wave energy devices as well as the integration of marine energy and reverse osmosis (RO) desalination. The HERO WEC was initially developed to derisk the Waves to Water prize, enabling the staff to practice WEC deployment and recovery, while optimizing installation protocols ologies, aiming to advance the broader fields of marine energy and water treatment.

13 HYDRO ENERGY↗

Generation of lognormal synthetic Lyman-α forest spectra for P 1 D analysis

The one-dimensional flux power spectrum (P 1 D ) of the Lyman-α forest probes small-scale structure in the intergalactic medium (IGM) and is therefore sensitive to a variety of cosmological and astrophysical parameters. These include the amplitude and shape of the matter power spectrum, the thermal history of the IGM, the sum of neutrino masses, and potential small-scale fluctuations due to the nature of dark matter. However, P 1 D is also highly sensitive to observational and instrumental systematics, making accurate synthetic spectra essential for validating analyses and quantifying these effects, especially in high-volume surveys like the Dark Energy Spectroscopic Instrument (DESI). We present an efficient lognormal mock framework for generating one-dimensional Lyman-α forest spectra tailored for P 1 D analysis. Our method captures the redshift evolution of the mean transmitted flux and the scale-dependent shape and amplitude of the one-dimensional flux power spectrum by tuning Gaussian field correlations and transformation parameters. Across the DESI Early Data Release (EDR) redshift range (2.0 ≤ z ≤ 3.8), and a wide range of scales (10 -4 s km -1 ≤ k ≤ 1.0 s km -1 ), our mocks recover the mean flux evolution with redshift to sub-percent accuracy, and the P 1 D at the percent level. Additionally, we discuss potential extensions of this framework, such as the incorporation of astrophysical contaminants, continuum uncertainties, and instrumental effects. Such improvements would expand its utility in ongoing and upcoming surveys and enable a broader range of validation efforts and systematics studies for P 1 D inference and precision cosmology.

Lyman alpha forest↗

Maximum entropy distributions of dark matter in ΛCDM cosmology

Context. Small-scale challenges to ΛCDM cosmology require a deeper understanding of dark matter physics. Aims. This paper aims to develop the maximum entropy distributions for dark matter particle velocity (denoted by X ), speed (denoted by Z ), and energy (denoted by E ) that are especially relevant on small scales where system approaches full virialization. Methods. For systems involving long-range interactions, a spectrum of halos of different sizes is required to form to maximize system entropy. While the velocity in halos can be Gaussian, the velocity distribution throughout the entire system, involving all halos of different sizes, is non-Gaussian. With the virial theorem for mechanical equilibrium, we applied the maximum entropy principle to the statistical equilibrium of entire system, such that the maximum entropy distribution of velocity (the X distribution) could be analytically derived. The halo mass function was not required in this formulation, but it did indeed result from the maximum entropy. Results. The predicted X distribution involves a shape parameter α and a velocity scale, v 0 . The shape parameter α reflects the nature of force ( α → 0 for long-range force or α → ∞ for short-range force). Therefore, the distribution approaches Laplacian with α → 0 and Gaussian with α → ∞. For an intermediate value of α , the distribution naturally exhibits a Gaussian core for v ≪ v 0 and exponential wings for v ≫ v 0 , as confirmed by N -body simulations. From this distribution, the mean particle energy of all dark matter particles with a given speed, v , follows a parabolic scaling for low speeds (∝ v 2 for v ≪ v 0 in halo core region, i.e., “Newtonian”) and a linear scaling for high speeds (∝ v for v ≫ v 0 in halo outskirt, i.e., exhibiting “non-Newtonian” behavior due to long-range gravity). We compared our results against N -body simulations and found a good agreement.

79 ASTRONOMY AND ASTROPHYSICS↗

Signatures of Light Massive Relics on non-linear structure formation

ABSTRACT Cosmologies with Light Massive Relics (LiMRs) as a subdominant component of the dark sector are well-motivated from a particle physics perspective, and can also have implications for the σ8 tension between early and late time probes of clustering. The effects of LiMRs on the cosmic microwave background (CMB) and structure formation on large (linear) scales have been investigated extensively. In this paper, we initiate a systematic study of the effects of LiMRs on smaller, non-linear scales using cosmological N-body simulations; focusing on quantities relevant for photometric galaxy surveys. For most of our study, we use a particular model of non-thermal LiMRs but the methods developed generalizing to a large class of LiMR models – we explicitly demonstrate this by considering the Dodelson–Widrow velocity distribution. We find that, in general, the effects of LiMR on small scales are distinct from those of a ΛCDM universe, even when the value of σ8 is matched between the models. We show that weak lensing measurements around massive clusters, between ∼0.1 h−1Mpc and ∼10 h−1Mpc, should have sufficient signal-to-noise in future surveys to distinguish between ΛCDM and LiMR models that are tuned to fit both CMB data and linear scale clustering data at late times. Furthermore, we find that different LiMR cosmologies indistinguishable by conventional linear probes can be distinguished by non-linear probes if their velocity distributions are sufficiently different. LiMR models can, therefore, be best tested by jointly analyzing the CMB and late-time structure formation on both large and small scales.

79 ASTRONOMY AND ASTROPHYSICS↗

Modeling ablator grain structure impacts in ICF implosions

High-density carbon is a leading ablator material for inertial confinement fusion (ICF). This and some other ablator materials have grain structure which is believed to introduce very small-scale (~nm) density inhomogeneity. In principle, such inhomogeneity can affect key ICF metrics like fuel compression and yield, by, for example, acting as a seed for instabilities and inducing mix between ablator and fuel. However, assessments of such effects are uncertain due to the difficulty of modeling this small-scale structure in ICF simulations, typically requiring reduced-resolution modeling that scales these features. We present a grain model and show both the impact of de-resolving grains and the complex mixing dynamics such structures can induce. We find that different methods for de-resolving grains can yield both different total deposition of kinetic energy perturbations and different fuel–ablator mixing. We then show a simple-to-implement approach for approximately conserving the deposition of perturbed kinetic energy and demonstrate that, for the present grain model and test cases, this approach yields a reasonably matched time history of mix width between less and more resolved grain models. The simulations here also demonstrate the complex interaction history between grain-induced mixing and instability around the fuel–ablator interface, showing, for example, that the grain-induced perturbations typically trigger instability of conduction-driven density gradients in the DT fuel, enhancing mix penetration early in the acceleration of the shell. Furthermore simulating both microscale and nanoscale grains, we find initial evidence for larger mixing in the microscale case of the present model, despite smaller deposited kinetic energy perturbation.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Mode transitions and spoke structures in E × B Penning discharge

Two-dimensional particle-in-cell simulations in the (radial-azimuthal) plane perpendicular to the axial direction of a cylindrical $E$ x $B$ Penning discharge are presented. The low-pressure discharge is self-consistently supported by plasma ionization from the electron beam injected axially, along the direction of the external magnetic field. It is shown that with the increasing strength of the external magnetic field, the discharge undergoes a sequence of transitions between several azimuthal modes. Azimuthal m > 1 spiral arm structures are excited at low magnetic field values as plasma confinement improves and the radial density profile becomes peaked. With a larger field, spiral arms with m > 1 are replaced by the m = 1 spoke mode, most clearly seen in plasma density. A transition from spiral arms to the spoke regime occurs when the plasma potential in the center changes from weakly positive (or zero) to negative. Further increase in the magnetic field results in a well-developed m = 1 spoke mode with additional small-scale higher-frequency m > 1 structures inside and around the spoke. It is shown that while ionization and collisions affect some characteristics of the observed fluctuations, the basic features of the spoke and m > 1 spiral structure remained similar without ionization. The role of energy conservation in small-scale high-frequency modes and spoke dynamics is discussed. It is demonstrated that in regimes with the m = 1 spoke mode, additional m = 4 harmonics of the ion and electron fluxes to the wall appear due to the square boundary. The frequency of the m = 1 mode is weakly affected by the geometry of the boundary.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Azimuthal structures and turbulent transport in Penning discharge

Azimuthal structures in cylindrical Penning discharge are studied with a 2D3V radial–azimuthal PIC/MCC model with the axial magnetic field. The discharge is self-consistently supported by ionization due to the axial injection of electrons. It is shown that the steady-state discharge can be supported in two different regimes with different types of observed azimuthal structures. The transition between the regimes is controlled by the mechanism of the energy input to the discharge. In the first regime (low energy of the injected electrons), with the pronounced m = 1 spoke activity, the power input is dominated by the energy absorption due to the radial current and self-consistent electric field. In the other regime (higher energy of the injected electrons), with prevalent small-scale m > 1 spiral structures, and the lower values of the anomalous transport, the total energy deposited to the discharge is lower and is mostly due to the direct input of the kinetic energy from the axial electron beam. Here we show that the large (m = 1) spoke and small-scale structures occur as a result of Simon–Hoh and lower hybrid instabilities driven by the electric field, density gradient, and collisions.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Mitigating baryonic effects with a theoretical error covariance

ABSTRACT One of the primary sources of uncertainties in modelling the cosmic-shear power spectrum on small scales is the effect of baryonic physics. Accurate cosmology for stage-IV surveys requires knowledge of the matter power spectrum deep in the non-linear regime at the per cent level. Therefore, it is important to develop reliable mitigation techniques to take into account baryonic uncertainties if information from small scales is to be considered in the cosmological analysis. In this work, we develop a new mitigation method for dealing with baryonic physics for the case of the shear angular power spectrum. The method is based on an augmented covariance matrix that incorporates baryonic uncertainties informed by hydrodynamical simulations. We use the results from 13 hydrodynamical simulations and the residual errors arising from a fit to a ΛCDM model using the extended halo model code HMCode to account for baryonic physics. These residual errors are used to model a so-called theoretical error covariance matrix that is added to the original covariance matrix. In order to assess the performance of the method, we use the 2D tomographic shear from four hydrodynamical simulations that have different extremes of baryonic parameters as mock data and run a likelihood analysis comparing the residual bias on Ωm and σ8 of our method and the HMCode for an LSST-like survey. We use different modelling of the theoretical error covariance matrix to test the robustness of the method. We show that it is possible to reduce the bias in the determination of the tested cosmological parameters at the price of a modest decrease in the precision.

79 ASTRONOMY AND ASTROPHYSICS↗

Impacts of Mesoscale Cloud Organization on Aerosol-Induced Cloud Water Adjustment and Cloud Brightness

The role of mesoscale cellular convection (MCC) in regulating aerosol-induced cloud brightness remains unaddressed. Using 7 years of satellite-based observations of cloud water adjustment to aerosol-induced perturbations for closed MCCs across different sizes (8, 16, 32, and 64 km) over the North Atlantic Ocean, we show that MCC cell-size plays a nontrivial role in regulating aerosol-induced cloud brightness via cloud water adjustment. In cells that are primarily non-precipitating, the adjustment in small-scale MCCs can be 10 times more negative than in large-scale MCCs, consistent with stronger evaporation via cloud top entrainment. Consequently, the response of cloud brightness is significantly stronger for large-scale MCCs. We also find notable intra-cell co-variability between cloud liquid water path (LWP) and drop concentration (N d ) within MCCs that varies with cell size. Erroneously considering such co-variability as a LWP response to N d can lead to a significant positive bias, especially for small scale MCCs.

54 ENVIRONMENTAL SCIENCES↗

Exxon Mobil-NETL Testing of DAC Materials

This joint initiative is aimed at extending our understanding of real DAC testing conditions at the NETL DAC testbed facility. Of particular focus will be: • Small Scale testing of powdered and formulated materials (supplied by ExxonMobil) to evaluate various performance metrics under DAC process cycles • Pilot scale testing of formulated materials at larger scales ExxonMobil will work with NETL to shake down equipment, validate testing methods, and define best practices for data analysis. Three tasks are proposed: 1. Validation of multi-cycle test data on powdered and formulated materials to benchmark various performance metrics of these materials. 2. Steam regeneration of powdered samples at small scale to define baseline performance under commercially relevant conditions. 3. Pilot scale testing of larger formulated materials to test commercially relevant samples under actual process cycles.

36 MATERIALS SCIENCE↗

Decentralized and mobile biomass torrefaction to upgrade the biomass supply chain

As part of the Cyclotron Road program, Takachar seeks to investigate the scaling laws and behaviors of a small-scale biomass torrefaction reactor design and its technoeconomic feasibility in various potential applications. Traditionally, biomass is logistically expensive and complicated to utilize in various energy and chemical industries, because it is often loose, wet, bulky, and present in small pockets in dispersed regions. Biomass torrefaction is an approach whereby raw biomass is subject to moderate heat, releasing low-energy molecules. The resultant torrefied biomass becomes energy and volume dense, which reduces the relative transportation cost, and in many cases can even support a local value chain that would otherwise not be possible. However, conventional biomass torrefaction systems are often large-scale, centralized in design, rending them difficult to deploy in many biomass applications in rural/decentralized regions. By building upon prior research at Massachusetts Institute of Technology (MIT), the concept of small-scale, low-cost, and portable biomass torrefaction units was explored further. This investigation has led to the advancement and scale-up of the MIT technology which can be deployed to a much wider spectrum of the biomass market than the conventional technologies.

09 BIOMASS FUELS↗

Upscaling Reactive Transport and Clogging in Shale Microcracks by Deep Learning

Fracture networks in shales exhibit multiscale features. A rock system may contain a few main fractures and thousands of microcracks, whose length and aperture are orders of magnitude smaller than the former. It is computationally prohibitive to resolve all the fractures explicitly for such multiscale fracture networks. One traditional approach is to model the small-scale features (e.g., microcracks in shales) as an effective medium. Although this fracture-matrix conceptualization significantly reduces the problem complexity, there are classes of physical processes that cannot be accurately upscaled by effective medium approximations, e.g., microcrack clogging during mineral reactions. Here, we employ deep learning in place of effective medium theory to upscale physical processes in small-scale features. Specifically, we consider reactive transport in a fracture-microcrack network where microcracks can be clogged by precipitation. A deep learning multiscale algorithm is developed, in which the microcracks are upscaled as a wall boundary condition of the main fractures. The wall boundary condition is constructed by recurrent neural networks, which take concentration histories as input and predict the solute transport from main fractures to microcracks. The deep learning multiscale algorithm is firstly employed in specific scenarios, then a general model is developed which can work under various conditions. The new approach is validated against fully resolved simulations and an analytical solution, providing a reliable and efficient solution for problems that cannot be upscaled by effective medium models.

58 GEOSCIENCES↗

Forced Crowding of Colloids by Thermophoresis and Convection in a Custom Liquid Clusius–Dickel Microdevice

Here, we report a study demonstrating that simultaneous induction of a steady-state convection current and temperature gradient in a confined geometry can be an effective way to force crowding of dissolved particulates. To investigate this thermogravitationally driven concentration of particles in-situ, we developed a micro-device capable of sustaining controlled transverse temperature gradients within a 5 cm long, 0.1 mm inner diameter capillary that allowed visualization of particle movement with standard optical microscopy. Experiments were conducted on two material systems representative of nano-scale small molecules and micro-scale particles. With the small molecules (aromatic dyes, 530-790 g/mol, 1-1.5 nm) thermophoretic and gravitational effects in the micro-device resulted in an asymmetrical 2x concentration change along the capillary height over 3 days. In contrast, the concentration change under similar conditions for 40-micron diameter latex colloids is 50-fold in 30 minutes. This dramatic difference in separation times is consistent with simulations and models of thermophoresis where the thermophoretic effect scales with particle size. Induced crowding of particulates leads to formation of accumulation and depletion zones in at the bottom and top of the capillary respectively. Both the concentration of dye molecules over time in the depletion zone and spatial distribution of colloids over the entire capillary length were found to be good fits to simple first-order exponential decay functions. Furthermore, these results suggest potential applications of thermogravitational separation in developing new functional materials via thermophoretic and convective effects.

36 MATERIALS SCIENCE↗

The mechanical properties of Kel-F 800 (FK-800) as a function of crystallinity

Kel-F 800 is a copolymer of chlorotrifluoroethylene PTFE (75 wt. %) and vinylidene fluoride PVDF (25 wt. %). It has previously been used as a PBX binder for insensitive explosives such as PBX 9502 and LX-17. 3M started production of Kel-F 800 in 1957 and small-scale batches continued to be made until 2002 when production ceased due to environmental concerns regarding one of the emulsifiers used during production. Around 2000 the Kel-F 800 name was changed to FK-800 to avoid trademark concerns because rights to produce another polymer with a similar tradename (Kel-F 81) had been sold to another manufacturer. The Kel designation came from the original manufacturer of PCTFE (Kel-F 81), the Kellog company. To avoid confusion this document will only refer to Kel-F 800. In 2006, production of small-scale batches of Kel-F 800 was started again by 3M in response to customer enquiries. This new material, the first blended batch is referred to as LOT 1, was produced with a different emulsifier than used previously. Because Kel-F 800 is made in a small batch reactor, considerable variation in crystallinity can be expected from lot to lot and year to year. In many ways, this is not significant since the material is dissolved in a solvent (often MEK, ethylmethyl ketone or ethyl acetate) for PBX production purposes. This destroys the as received crystallinity and the resulting crystallinity in the processed material is a function of polymer molecular weight and thermal history. Producing large billets of Kel-F 800 from solvent extraction is not practical and so a compression molding technique has been used above the melting temperature. This method also removes residual crystallinity from the supplied granules. The molecular weight of a polymer can be estimated by several techniques, the most common being gel permittivity chromatography (GPC), size exclusion chromatography (SEC) and shear rheometry measurements of polymer/solvent solutions. Changes in molecular weight will affect the crystallization rate and the maximum crystallinity reached for a specific thermal history. Both references agree that the new LOT 1 material molecular weight falls within the deviation found from averaging previous historical lots of Kel-F 800.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Sensitivity of an integrated experiment to uncertainty in the high explosive equations of state

Traditionally, hydrodynamics simulations are performed with a single equation-of-state (EOS) to describe each material. These EOSs typically have a physics-informed functional form with adjustable parameters that are calibrated in order to replicate small-scale data. However, because the calibration data have uncertainty and there are typically inherent degeneracies in fitting the EOS, there are actually multiple EOSs that might be consistent with calibration data. In this work, we perform uncertainty quantification (UQ) for the reactant and product equations of state for the high explosive PBX 9501 to yield an ensemble of EOSs that match the uncertain small-scale calibration data. We then simulate an experiment of an explosively formed penetrator repeatedly with different EOSs to both validate the UQ analysis and determine the effects of EOS uncertainty on the prediction of quantities of interest in the experiment. In general, we find good agreement between the simulation predictions and the experimental measurements, and we identify an EOS variable that contributes most directly to the spread in the predictions as the EOSs are varied.

36 MATERIALS SCIENCE↗