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At least 919 records · Page 51

Icehouse Effect: A Polar Autumn and Winter Cooling Trend

The icehouse effect is a hypothesized polar climate trend toward cooling (or lack of warming) in response to greenhouse warming of adjacent lower latitudes. When greenhouse warmed air from lower latitudes moves over ice and snow, it generates a stronger, more stable, cappino, inversion than in a parallel case without greenhouse warming. Because the degree of decoupling between vertically adjacent air masses is directly dependent on the strength of the inversion, the capping inversion acts somewhat analogously to the walls and roof of the icehouse of generations past. What is inside the icehouse, namely the cold polar atmospheric boundary layer (ABL) air, is preserved by the "insulation" or decoupling, provided by the warm air aloft. Observations over the Arctic Ocean have shown an unexpected lack of any detectable surface warming trend over the past 40 years. This finding strongly contradicts climate model predictions that polar regions should show the strongest effect of greenhouse warming. It also stands in contrast to the consensus reached by the Intergovernmental Panel on Climate Change (IPCC), that human caused greenhouse warming is now detectable globally. One might ask: Are these Arctic observations wrong? Or, if right, is there a plausible physical explanation for them? The published observations mentioned above used about 50,000 soundings over the Arctic Ocean. Here I present a novel analysis of ALL available Arctic rawinsonde data north of 65N--a total of more than 1.1 million soundings. The analysis confirms the previously published result: There is indeed a slight climate-cooling trend in the vast majority of the data. Importantly, there are also select conditions (very strong and very weak stability of the ABL) which show a consistent, strong Arctic warming trend. It is the juxtaposition of these warming and cooling trends which defines a unique "icehouse signature" for which an explanation can be sought.

Wetzel, Peter J.↗

Near-wall model for compressible turbulent boundary layers based on an inverse velocity transformation

In this work, a near-wall model, which couples the inverse of a recently developed compressible velocity transformation (Griffin et al., Proc. Natl Acad. Sci., vol. 118, 2021, p. 34) and an algebraic temperature–velocity relation, is developed for high-speed turbulent boundary layers. As input, the model requires the mean flow state at one wall-normal height in the inner layer of the boundary layer and at the boundary-layer edge. As output, the model can predict mean temperature and velocity profiles across the entire inner layer, as well as the wall shear stress and heat flux. The model is tested in an a priori sense using a wide database of direct numerical simulation high-Mach-number turbulent channel flows, pipe flows and boundary layers (48 cases, with edge Mach numbers in the range 0.77–11, and semi-local friction Reynolds numbers in the range 170–5700). The present model is significantly more accurate than the classical ordinary differential equation (ODE) model for all cases tested. The model is deployed as a wall model for large-eddy simulations in channel flows with bulk Mach numbers in the range 0.7–4 and friction Reynolds numbers in the range 320–1800. When compared to the classical framework, in the a posteriori sense, the present method greatly improves the predicted heat flux, wall stress, and temperature and velocity profiles, especially in cases with strong heat transfer. In addition, the present model solves one ODE instead of two, and has a computational cost and implementation complexity similar to that of the commonly used ODE model.

42 ENGINEERING↗

Inversion of coherent surface scattering images via deep learning network

Coherent surface scattering imaging is a powerful tool for imaging a surface/interface of a thin nanostructure deposited on an opaque substrate. A mathematical conversion of an object image from a scattering pattern is essential for coherent surface scattering imaging to visualize structures of specimens. It has been achieved by using phase retrieval algorithms requiring oversampling in scattering patterns and employing alternating projection approaches. It is a computationally challenging and time-consuming process. In this paper, we demonstrate CSSI-NN, which is a deep learning neural network model to predict images of objects from scattering intensities in coherent surface scattering imaging. This model allowing for the instant outcome from scattering patterns would be tremendously beneficial not only for effective experiments but also for data analysis of phase retrieval.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Sign Problem in Tensor-Network Contraction

We investigate how the computational difficulty of contracting tensor networks depends on the sign structure of the tensor entries. Using results from computational complexity, we observe that the approximate contraction of tensor networks with only positive entries has lower computational complexity as compared to tensor networks with general real or complex entries. This raises the question of how this transition in computational complexity manifests itself in the hardness of different tensor-network-contraction schemes. We pursue this question by studying random tensor networks with varying bias toward positive entries. First, we consider contraction via Monte Carlo sampling and find that the transition from hard to easy occurs when the tensor entries become predominantly positive; this can be understood as a tensor-network manifestation of the well-known negative-sign problem in quantum Monte Carlo. Second, we analyze the commonly used contraction based on boundary tensor networks. The performance of this scheme is governed by the number of correlations in contiguous parts of the tensor network (which by analogy can be thought of as entanglement). Remarkably, we find that the transition from hard to easy—i.e., from a volume-law to a boundary-law scaling of entanglement—already occurs for a slight bias of the tensor entries toward a positive mean, scaling inversely with the bond dimension D , and thus the problem becomes easy the earlier the larger D occurs. This is in contrast both to expectations and to the behavior found in Monte Carlo contraction, where the hardness at fixed bias increases with the bond dimension. To provide insight into this early breakdown of computational hardness and the accompanying entanglement transition, we construct an effective classical statistical-mechanical model that predicts a transition at a bias of the tensor entries of 1 / D , confirming our observations. We conclude by investigating the computational difficulty of computing expectation values of tensor-network wave functions (projected entangled-pair states, PEPSs) and find that in this setting, the complexity of entanglement-based contraction always remains low. We explain this by providing a local transformation that maps PEPS expectation values to a positive-valued tensor network. This not only provides insight into the origin of the observed boundary-law entanglement scaling but also suggests new approaches toward PEPS contraction based on positive decompositions. Published by the American Physical Society 2025

Chen, Jielun (ORCID:0000000178411545)↗

The dynamic liquid squeeze film.

Experiments were conducted during which plane circular surfaces bounding a liquid squeeze film were subjected to impulsive loads. Pressure measurements within the liquid film and the boundary motion were recorded. These experimental results were compared with theoretical analyses which predict the bonding strength of dynamic squeeze films. The data show that the fluid inertia contributes significantly to the value of the bonding strength. It was also found that, for high loading rates, the liquid squeeze film can resist tensile loads. When in tension, liquid cavitation was observed. A photographic study was conducted which indicated that the inception of cavitation is directly related to the squeeze film liquid viscosity and inversely related to the film thickness.

Riepe, R.↗

An airborne sensor for the avoidance of clear air turbulence

This paper describes an airborne microwave radiometer that may be able to provide altitude guidance away from layers containing clear air turbulence, CAT. The sensor may also be able to predict upper limits for the severity of upcoming CAT. The 55 GHz radiometer is passive, not radar, and it measures the temperature of oxygen molecules in the viewing direction (averaged along a several-kilometer path). A small computer directs the viewing direction through elevation angle scans, and converts observed quantities to an 'altitude temperature profile'. The principle for CAT avoidance is that CAT is found statistically more often within inversion layers and at the tropopause, both of which are easily located from sensor-generated altitude temperature profiles.

Gary, B. L.↗

Characterizing terrestrial ecosystems and productivity from remote sensing data

Predictive relationships were studied between the leaf area index (LAI) of temperate coniferous forests and the canopy of reflective properties as sensed by satellites. Also, the relationship was examined between this sensible variable, LAI, and functional properties such as net primary productivity (NPP) and nitrogen mineralization. Leaf surface area is a locus of many important material and energy exchanges. If LAI can be reasonably estimated from remote sensing measurements, then it could be used with models to predict evapotranspiration, radiation interception, precipitation interception, and other ecosystem processes over large areas. Nineteen mature closed canopy forest stands were measured for leaf area index distributed along a temperature moisture gradient across Oregon. The LAI varies from 15.4 to 0.6. Infrared radiation is strongly scattered by leaves so that it penetrates deeply and its reflectance is proportional to LAI. Red radiation is strongly absorbed by chlorophyll and its reflectance is inversely related to LAI, becoming asymptotic at LAI values of about 3. The ratio of infrared to red radiation compensates for irradiance variations across this transect.

Peterson, David L.↗

The Solar Wind

Parker's model of a spherically expanding corona, the "solar wind," is compared with D. E. Blackwell's observations of the 1954 minimum equatorial corona. A significant discrepancy is found between the predicted and the observed electron densities at distances from the sun greater than 20 solar radii. Blackwell's data are found to be consistent with a model in which the corona expands mostly within a disk less than 25 solar radii thick, lying within the sun's equatorial plane. The thickness of the disk as a function of distance from the sun is qualitatively explained in terms of magnetic pressure. The solar wind is found to have a considerable effect on the lunar atmosphere. First, the calculated density of the lunar atmosphere is greatly reduced by collisions with protons in the solar wind. If the flux of particles in this wind has the conventional values ranging between 10(exp 10) to 10(exp 11) per sq cm-sec, the calculations yield a lunar pressure of 10(exp -13) atmosphere of argon, in agreement with the value predicted by Elsmore and Whitfield on the basis of observations on the occultation of radio stars. Second, following a suggestion by Gold, it was found that the collisions of solar-wind protons with the lunar surface produce an atmosphere of cold neutral hydrogen with a density of 10(exp 5) per cu cm at the lunar surface. The density falls off at greater distances in accordance with the inverse-square law. Estimates indicate that the interaction of solar particles with the neutral hydrogen will produce an extended lunar ionosphere with a density of the order of 400 protons/cu cm in the vicinity of the moon.

Herring, J. R.↗

Line Coupling and Line Mixing Effects on Calculated Widths of Symmetric-Top Molecules With the k-Degeneracy: A Theoretical Study of N 2 -, O 2 -, and Air-Broadened Lines of CH 3 I

Calculations of the N 2 -, O 2 - and air-broadened widths, together with their temperature dependence exponents have been made for transitions of CH 3 I in the v 5 and v 6 bands. The calculations are based on a semi-classical line shape formalism developed by the current authors through modifying and refining the Robert-Bonamy formalism. In recent years, we have applied this formalism for linear molecules, symmetric-top molecules with inversion symmetry, and asymmetric-top molecules. For symmetric-top molecules with the k degeneracy such as CH 3 I, the formalism has a new feature. In this case, one should consider each of the CH 3 I transitions labeled by k i or ƒ ≠ 0 as a doublet. Then, one needs to consider the effects of the line mixing process between these two components. Comparisons of our theoretical predictions with some data available demonstrate a very reasonable agreement. Finally we propose new experiments at higher perturber pressures that would enable one to check the theoretically calculated relaxation matrices and to extend the analysis to the interdoublet mixing effects.

Line coupling↗

Line coupling and line mixing effects on calculated widths of symmetric-top molecules with the k-degeneracy: A theoretical study of N 2 -, O 2 -, and air-broadened lines of CH 3 I

Calculations of the N 2 -, O 2 -, and air-broadened widths, together with their temperature dependence exponents have been made for transitions of CH 3 I in the ν 5 and ν 6 bands. The calculations are based on a semi-classical line shape formalism developed by the current authors through modifying and refining the Robert-Bonamy formalism. In recent years, we have applied this formalism for linear molecules, symmetric-top molecules with inversion symmetry, and asymmetric-top molecules. For symmetric-top molecules with the k degeneracy such as CH 3 I, the formalism has a new feature. In this case, one should consider each of the CH 3 I transitions labeled by k i or f ≠ 0 as a doublet. Then, one needs to consider the effects of the line mixing process between these two components. Furthermore, comparisons of our theoretical predictions with some data available demonstrate a very reasonable agreement. Finally, we propose new experiments at higher perturber pressures that would enable one to check the theoretically calculated relaxation matrices and to extend the analysis to the inter-doublet mixing effects.

74 ATOMIC AND MOLECULAR PHYSICS↗

Large Ensemble Particle Filter for Spatial Climate Reconstructions Using a Linear Inverse Model

Proxy records that document the last 2000 years of climate provide evidence for the wide range of the natural climate variability from inter-annual to secular timescales not captured by the short window of recent direct observations. Assessing climate models ability to reproduce such natural variations is crucial to understand climate sensitivity and impacts of future climate change. Paleoclimate data assimilation (PDA) offers a powerful way to extend the short instrumental period by optimally combining the physics described by General Circulation Climate Models (GCMs) with information from available proxy records while taking into account their uncertainties. Here we present a new PDA approach based on a sequential importance resampling (SIR) Particle filter (PF) that uses Linear Inverse Modeling (LIM) as an emulator of several CMIP-class GCMs. We examine in a perfect-model framework the skill of the various LIMs to forecast the dynamics of the surface temperatures and provide spatial field reconstructions over the last millennium in a SIR PF. Our results show that the LIMs allow for skillful ensemble forecasts at 1-year lead-time based on GCMs dynamical knowledge with best prediction in the tropics and the North Atlantic. The PDA further provides a set of physically consistent spatial fields allowing robust uncertainty quantification related to climate models biases and proxy spatial sampling. Our results indicate that the LIM yields dynamical memory improving climate variability reconstructions and support the use of the LIM as a GCM-emulator in real reconstruction to propagate large ensembles of particles at low cost in SIR PF.

54 ENVIRONMENTAL SCIENCES↗

Role of self-generated magnetic fields in the inertial fusion ignition threshold

Magnetic fields spontaneously grow at unstable interfaces around hot-spot asymmetries during inertial confinement fusion implosions. Although difficult to measure, theoretical considerations and numerical simulations predict field strengths exceeding 5 kT in current National Ignition Facility experiments. Magnetic confinement of electrons then reduces the rate of hot-spot heat loss by >5%. We demonstrate this via magnetic post-processing of two-dimensional xRAGE hydrodynamic simulation data at bang time. We then derive a model for the self-magnetization, finding that it varies with the square of the hot-spot temperature and inversely with the areal density. The self-magnetized Lawson analysis then gives a slightly reduced ignition threshold. Time-dependent hot-spot energy balance models corroborate this finding, with the magnetic field quadrupling the fusion yield for near-threshold parameters. The inclusion of magnetized multi-dimensional fluid instabilities could further alter the ignition threshold and will be the subject of future work.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Evaluation of the Fitch Wind-Farm Wake Parameterization with Large-Eddy Simulations of Wakes Using the Weather Research and Forecasting Model

Abstract Wind-farm parameterizations in weather models can be used to predict both the power output and farm effects on the flow; however, their correctness has not been thoroughly assessed. We evaluate the wind-farm parameterization of the Weather Research and Forecasting Model with large-eddy simulations (LES) of the wake performed with the same model. We study the impact on the velocity and turbulence kinetic energy (TKE) of inflow velocity, roughness, resolution, number of turbines (one or two), and inversion height and strength. We compare the mesoscale with the LES by spatially averaging the LES within areas correspondent to the mesoscale horizontal spacing: one covering the turbine area and two downwind. We find an excellent agreement of the velocity within the turbine area between the two types of simulations. However, within the same area, we find the largest TKE discrepancies because in mesoscale simulations, the turbine-added TKE has to be highest at the turbine position to be advected downwind. Within the downwind areas, differences between velocities increase as the wake recovers faster in the LES, whereas for the TKE both types of simulations show similar levels. From the various configurations, the impact of inversion height and strength is small for these heights and inversion levels. The highest impact for the one-turbine simulations appears under the low-speed case due to the higher thrust, whereas the impact of resolution is low for the large-eddy simulations but high for the mesoscale simulations. Our findings demonstrate that higher-fidelity simulations are needed to validate wind-farm parameterizations.

17 WIND ENERGY↗

On extracting brightness temperature maps from scanning radiometer data

The extraction of brightness temperature maps from scanning radiometer data is described as a typical linear inverse problem. Spatial quantization and parameter estimation is described and is suggested as an advantageous approach to a solution. Since this approach takes into explicit account the multivariate nature of the problem, it permits an accurate determination of the most detailed resolution extractable from the data as well as explicitly defining the possible compromises between accuracy and resolution. To illustrate the usefulness of the method described for algorithm design and accuracy prediction, it was applied to the problem of providing brightness temperature maps during the NOSS flight segment. The most detained possible resolution was determined and a curve which displays the possible compromises between accuracy and resolution was provided.

Argentiero, P.↗

INVESTIGATING THE FEASIBILITY AND STABILITY FOR MODELING ACOUSTIC WAVE SCATTERING USING A TIME-DOMAIN BOUNDARY INTEGRAL EQUATION WITH IMPEDANCE BOUNDARY CONDITION

Reducing aircraft noise is a major objective in the field of computational aeroacoustics. When designing next generation quiet and environmentally friendly aircraft, it is important to be able to accurately and efficiently predict the acoustic scattering by an aircraft body from a given noise source. Acoustic liners are an effective tool for aircraft noise reduction and are characterized by a frequency-dependent impedance. Converted into the time-domain using Fourier transforms, an impedance boundary condition can be used to simulate the acoustic wave scattering by geometric bodies treated with acoustic liners. This work considers using either an impedance or an admittance (inverse of impedance) boundary condition to allow for acoustic scattering problems to be modeled with geometries consisting of both un-lined and lined surfaces. Three acoustic liner models are discussed: the Extended Helmholtz Resonator Model, the Three-Parameter Impedance Model, and the Broadband Impedance Model. In both the Helmholtz and Three-Parameter models, liner impedance is specified at a given frequency, whereas the Broadband model allows for the investigation of multiple frequencies simultaneously. The impedance and admittance boundary conditions for acoustic liners are derived for each model and coupled with a time-domain boundary integral equation. The scattering solution is obtained iteratively using a boundary element method with constant spatial and third-order temporal basis functions. Time-domain boundary integral equations are unfortunately prone to numerical instabilities due to resonant frequencies resulting from non-trivial solutions in the interior domain. When reformulated with the Burton-Miller method, the instabilities are eliminated. Using a Burton-Miller reformulation, the stability of the boundary element method assuming a liner boundary condition is assessed using eigenvalue analysis. The stability of each liner model is discussed, and it is shown that the Three-Parameter and Broadband models are sufficient for modeling an acoustic liner on the surface of scattering bodies. The Helmholtz model demonstrates strict limitations for stability, whereas the Three-Parameter and Broadband models are stable for most cases. Also included in this work is an assessment of the spatial accuracy of the time-domain boundary element method with respect to the surface element basis functions, as well as a performance study of the numerical algorithm.

computational mathematics↗

A DECADE of dwarfs: first detection of weak lensing around spectroscopically confirmed low-mass galaxies

We present the first detection of weak gravitational lensing around spectroscopically confirmed dwarf galaxies, using the large overlap between DESI DR1 spectroscopic data and DECADE/DES weak lensing catalogs. A clean dwarf galaxy sample with well-defined redshift and stellar mass cuts enables excess surface mass density measurements in two stellar mass bins ($\log \rm{M}_*=[8.2, 9.2]~M_\odot$ and $\log \rm{M}_*=[9.2, 10.2]~M_\odot$), with signal-to-noise ratios of $5.6$ and $12.4$ respectively. This signal-to-noise drops to $4.5$ and $9.2$ respectively for measurements without applying individual inverse probability (IIP) weights, which mitigates fiber incompleteness from DESI's targeting. The measurements are robust against variations in stellar mass estimates, photometric shredding, and lensing calibration systematics. Using a simulation-based modeling framework with stellar mass function priors, we constrain the stellar mass-halo mass relation and find a satellite fraction of $\simeq 0.3$, which is higher than previous photometric studies but $1.5σ$ lower than $Λ$CDM predictions. We find that IIP weights have a significant impact on lensing measurements and can change the inferred $f_{\rm{sat}}$ by a factor of two, highlighting the need for accurate fiber incompleteness corrections for dwarf galaxy samples. Our results open a new observational window into the galaxy-halo connection at low masses, showing that future massively multiplexed spectroscopic observations and weak lensing data will enable stringent tests of galaxy formation models and $Λ$CDM predictions.

To, Chun-Hao [Chicago U., Astron. Astrophys. Ctr.;↗

Dislocation model for aseismic crustal deformation at Hollister, California

A model of crustal deformation during the interseismic phase is developed and applied (using the improved Bayesian inversion algorithm described by Jackson and Matsu'ura, 1985) to trilateration data for the USGS Hollister (CA) network. In the model, rigid blocks in motion relative to each other experience friction only in a brittle upper zone, while their ductile lower zones slide freely; the Hollister model comprises five blocks and nine rectangular fault patches. The data and results are presented in tables, graphs, and maps and characterized in detail. The model predicts steady block motion on time scales between 10 yr and 1 Myr, with net motion across the San Andreas/Calaveras fault system 38 + or - 3 mm/yr and brittle/ductile transition depths ranging from 0.4 to 11 km. Two San Andreas segments with higher probabilities of moderate-to-large earthquakes are identified.

Matsuura, Mitsuhiro↗

Inverse design of cellular structures with the targeted nonlinear mechanical response

Advanced additive manufacturing capabilities have enabled a transformational ability to create sophisticated cellular structures using diverse materials. By altering the topology of the unit cell, the mechanical behavior, such as the stress-strain response during compression, can be modulated. Nevertheless, identifying a printable topology within an enormous design space that would precisely deliver the targeted nonlinear material response is challenging. We propose a data-driven generative framework based on a conditional variational autoencoder (cVAE) architecture that can inverse design the cellular structure based on the intended nonlinear stress-strain response. Trained on a dataset of structure-property pairs, the cVAE learns a compact and expressive latent space that enables efficient mapping from targets to feasible geometries. Two inference modes are explored: (1) decoder-only generation, which enables the exploration of diverse designs conditioned solely on the desired mechanical response, and (2) encoder-decoder generation, which further allows for the incorporation of desired topologies, ensuring the generated structure conforms to both mechanical properties and to desired-topology constraints. The results demonstrate that the model can generate structurally plausible and mechanically accurate designs, with the predicted stress-strain curves closely matching the targets. Even under joint conditioning, the model effectively balances geometric fidelity and functional performance.

36 MATERIALS SCIENCE↗