A Step-Function Abstract Domain for Granular Floating-Point Error Analysis
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Dario, Anthony↗
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Determination of the N$_f$=12 step scaling function using Möbius domain wall fermions
We calculate the renormalized step scaling function for twelve fundamental flavors nonperturbatively by determining the gradient flow coupling on gauge field configurations generated with dynamical stout-smeared M\"obius domain wall fermions and Symanzik gauge action. Using Zeuthen, Symanzik, and Wilson flow we measure the energy density with three different operators. Our updated analysis is based on up to five volume pairs ranging from L 4 =8 4 up to 32 4 . Predictions for the infinite volume extrapolated step scaling function based on different flows and operators are mutually consistent. Our new results confirm the previously observed significant discrepancy with staggered fermion simulations in a wide range of the renormalized coupling.
72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
BICEP/Keck XXI: Constraints on early-Universe parity violation from multipole-dependent birefringence
We present the first constraints on multipole-dependent cosmic birefringence using CMB polarization data from the BK18 dataset, which combines observations from BICEP2, Array, and BICEP3 at frequencies of 95, 150, and 220 GHz. Photon coupling to an axionlike field leads to the rotation of CMB polarization, inducing nonzero cross-correlations. We show that a multipole-dependent rotation imprints a distinct signature in the polarization spectra that can be constrained. Specifically, we consider an early dark energy (EDE) scenario in which a pseudoscalar field couples to photons through a Chern-Simons interaction, generating a polarization rotation with multipole dependence. We introduce a phenomenological as a step function, obtaining constraints on the step function size consistent with zero, with uncertainties less than (68% CL). In addition, using multi-frequency , , and cross spectra, along with robust BICEP/ foreground treatment and likelihood framework, we derive constraints on the axion-photon coupling amplitude for several choices of EDE parameters. For the baseline best-fit value from the 2018 analysis, we obtain (68% CL), consistent with previous limits.
Ade, P A R↗
Accuracy of environmental tracers and consequences for determining the Type Ia supernova magnitude step
Type Ia Supernovae (SNe Ia) are standardizable candles that allow us to measure the recent expansion rate of the Universe. Due to uncertainties in progenitor physics, potential astrophysical dependencies may bias cosmological measurements if not properly accounted for. The dependency of the intrinsic luminosity of SNe Ia with their host-galaxy environment is often used to standardize SNe Ia luminosity and is commonly parameterized as a step function. This functional form implicitly assumes two-populations of SNe Ia. In the literature, multiple environmental indicators have been considered, finding different, sometimes incompatible, step function amplitudes. We compare these indicators in the context of a two-populations model, based on their ability to distinguish the two populations. We show that local Hα-based specific star formation rate (lsSFR) and global stellar mass are better tracers than, for instance, host galaxy morphology. We show that tracer accuracy can explain the discrepancy between the observed SNe Ia step amplitudes found in the literature. Using lsSFR or global mass to identify the two populations can explain all other observations, though lsSFR is favoured. As lsSFR is strongly connected to age, our results favour a prompt and delayed population model. In any case, there exists two populations that differ in standardized magnitude by at least 0.121 ± 0.010 mag.
79 ASTRONOMY AND ASTROPHYSICS↗
Calculation of the Thermodynamic Voltage Limit of CdSeTe Solar Cells
The first step to understand the origin of losses in any photovoltaic solar cell is to determine the fundamental thermodynamic efficiency and voltage limits of such a device. In this contribution, we detail techniques to calculate the voltage limit in the case of cadmium selenium telluride (CdSeTe) solar cells, and how approaches based on bandgap alone—i.e., the Shockley-Queisser approach with step-function absorptance—can overestimate the thermodynamic open-circuit voltage limit Voc,ideal . This is particularly true for arsenic-doped samples, which tend to exhibit below-bandgap absorptance.
absorptance↗
Soil enzymes as indicators of soil function: A step toward greater realism in microbial ecological modeling
Soil carbon (C) and nitrogen (N) cycles and their complex responses to environmental changes have received increasing attention. However, large uncertainties in model predictions remain, partially due to the lack of explicit representation and parameterization of microbial processes. One great challenge is to effectively integrate rich microbial functional traits into ecosystem modeling for better predictions. Here, using soil enzymes as indicators of soil function, we developed a competitive dynamic enzyme allocation scheme and detailed enzyme-mediated soil inorganic N processes in the Microbial-ENzyme Decomposition (MEND) model. We conducted a rigorous calibration and validation of MEND with diverse soil C-N fluxes, microbial C:N ratios, and functional gene abundances from a 12-year CO 2 × N grassland experiment (BioCON) in Minnesota, USA. In addition to accurately simulating soil CO 2 fluxes and multiple N variables, the model correctly predicted microbial C:N ratios and their negative response to enriched N supply. Model validation further showed that, compared to the changes in simulated enzyme concentrations and decomposition rates, the changes in simulated activities of eight C-N-associated enzymes were better explained by the measured gene abundances in responses to elevated atmospheric CO 2 concentration. In conclusion, our results demonstrated that using enzymes as indicators of soil function and validating model predictions with functional gene abundances in ecosystem modeling can provide a basis for testing hypotheses about microbially mediated biogeochemical processes in response to environmental changes. Further development and applications of the modeling framework presented here will enable microbial ecologists to address ecosystem-level questions beyond empirical observations, toward more predictive understanding, an ultimate goal of microbial ecology.
59 BASIC BIOLOGICAL SCIENCES↗
Approximating Photo- z PDFs for Large Surveys
Modern galaxy surveys produce redshift probability density functions (PDFs) in addition to traditional photometric redshift (photo-z) point estimates. However, the storage of photo-z PDFs may present a challenge with increasingly large catalogs, as we face a trade-off between the accuracy of subsequent science measurements and the limitation of finite storage resources. This work presents qp, a Python package for manipulating parameterizations of one-dimensional PDFs, as suitable for photo-z PDF compression. We use qp to investigate the performance of three simple PDF storage formats (quantiles, samples, and step functions) as a function of the number of stored parameters on two realistic mock data sets, representative of upcoming surveys with different data qualities. We propose some best practices for choosing a photo-z PDF approximation scheme and demonstrate the approach on a science case using performance metrics on both ensembles of individual photo-z PDFs and an estimator of the overall redshift distribution function. We show that both the properties of the set of PDFs we wish to approximate and the fidelity metric(s) chosen affect the optimal parameterization. Additionally, we find that quantiles and samples outperform step functions, and we encourage further consideration of these formats for PDF approximation.
79 ASTRONOMY AND ASTROPHYSICS↗
Computational studies on scattering of radio frequency waves by density filaments in fusion plasmas
In modern magnetic fusion devices, such as tokamaks and stellarators, radio frequency (RF) waves are commonly used for plasma heating and current profile control, as well as for certain diagnostics. The frequencies of the RF waves range from ion cyclotron frequency to the electron cyclotron frequency. The RF waves are launched from structures, like waveguides and current straps, placed near the wall in a very low density, tenuous plasma region of a fusion device. The RF electromagnetic fields have to propagate through this scrape-off layer before coupling power to the core of the plasma. The scrape-off layer is characterized by turbulent plasmas fluctuations and by blobs and filaments. The variations in the edge density due to these fluctuations and filaments can affect the propagation characteristics of the RF waves—changes in density leading to regions with differing plasma permittivity. Analytical full-wave theories have shown that scattering by blobs and filaments can alter the RF power flow into the core of the plasma in a variety of ways, such as through reflection, refraction, diffraction, and shadowing [see, for example, Ram and Hizanidis, Phys. Plasmas 23, 022504 (2016), and references therein]. There are changes in the wave vectors and the distribution of power–scattering leading to coupling of the incident RF wave to other plasma waves, side-scattering, surface waves, and fragmentation of the Poynting flux in the direction towards the core. However, these theoretical models are somewhat idealized. In particular, it is assumed that there is step-function discontinuity in the density between the plasma inside the filament and the background plasma. In this paper, results from numerical simulations of RF scattering by filaments using a commercial full-wave code are described. The filaments are taken to be cylindrical with the axis of the cylinder aligned along the direction of the ambient magnetic field. The plasma inside and outside the filament is assumed to be cold. There are three primary objectives of these studies. The first objective is to validate the numerical simulations by comparing with the analytical results for the same plasma description—a step-function discontinuity in density. A detailed comparison of the Poynting flux shows that numerical simulations lead to the same results as those from the theoretical model. The second objective is to extend the simulations to take into account a smooth transition in density from the background plasma to the interior of the filament. The ensuing comparison shows that the deviations from the results of the theoretical model are quite small. The third objective is to consider the scattering process for situations well beyond a reasonable theoretical analysis. This includes scattering off multiple filaments with different densities and sizes. In conclusion, simulations for these complex arrangements of filaments show that, in spite of the obvious limitations, the essential physics of RF scattering is captured by the analytical theory for a single filament
70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
Pareto Optimal Spectrally Selective Emitters for Thermophotovoltaics via Weak Absorber Critical Coupling
Tailoring the emission spectra of a thermophotovoltaic (TPV) emitter away from that of a blackbody has the potential to minimize transmission and thermalization loss in a photovoltaic receiver. Selective TPV emitters can lead to solar energy conversion with efficiency greater than the Shockley-Queisser limit and can facilitate the generation of useful energy from waste heat. A new design is introduced to radically tune thermal emission that leverages the interplay between two resonant phenomena in simple planar nanostructures-absorption in weakly absorbing nanofilms and reflection in multilayer dielectric stacks. A virtual screening approach is employed to identify promising structures for a selective thermal emitter from a search space of millions, several of which approach the ideal values of a step-function selective thermal emitter. One of these structures is experimentally fabricated and evaluated, which includes a weakly absorbing alloy with tailored optical properties fabricated by atomic layer deposition (ALD). The versatility of the design and fabrication approach result in an emitter with excellent spectral density (0.8 W cm(-2) sr(-1)) and spectral efficiency (46.8%) at 1373 K. Future experimental challenges to a more accurate realization of the optimal structures calculated are also considered.
atomic layer deposition↗
Gradient flow step-scaling function for SU(3) with twelve flavors
Not Available
72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
Gradient flow step-scaling function for SU(3) with ten fundamental flavors
Not Available
72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
Gradient flow step-scaling function for SU(3) with N f = 6 or 4 fundamental flavors
Not Available
72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
Gradient flow step-scaling function for SU(3) with N f = 8 fundamental flavors
Not Available
72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
Effects of exposure estimation errors on estimated exposure-response relations for PM2.5
Highlights: • Recent literature has identified associations between concentrations of fine particulate matter (PM2.5) in ambient air and adverse health effects at estimated exposure concentrations below current air ambient quality standards. • The models and analyses used do not usually quantify uncertainty about exposure estimates. • Realistic errors in exposure estimates can be estimated from available air quality monitoring stations by predicting concentrations at each station from concentrations at neighboring stations. • Exposure estimation errors are large enough to obscure low-dose nonlinearities or thresholds in the true concentration-response (C-R) function, artificially making them appear to be linear at low doses. • Better estimates of C-R functions will require modeling exposure distributions and estimation errors, rather than just estimating average exposure concentrations. Associations between fine particulate matter (PM2.5) exposure concentrations and a wide variety of undesirable outcomes, from autism and auto theft to elderly mortality, suicide, and violent crime, have been widely reported. Influential articles have argued that reducing National Ambient Air Quality Standards for PM2.5 is desirable to reduce these outcomes. Yet, other studies have found that reducing black smoke and other particulate matter by as much as 70% and dozens of micrograms per cubic meter has not detectably affected all-cause mortality rates even after decades, despite strong, statistically significant positive exposure concentration-response (C-R) associations between them. This paper examines whether this disconnect between association and causation might be explained in part by ignored estimation errors in estimated exposure concentrations. We use EPA air quality monitor data from the Los Angeles area of California to examine the shapes of estimated C-R functions for PM2.5 when the true C-R functions are assumed to be step functions with well-defined response thresholds. The estimated C-R functions mistakenly show risk as smoothly increasing with concentrations even well below the response thresholds, thus incorrectly predicting substantial risk reductions from reductions in concentrations that do not affect health risks. We conclude that ignored estimation errors obscure the shapes of true C-R functions, including possible thresholds, possibly leading to unrealistic predictions of the changes in risk caused by changing exposures. Instead of estimating improvements in public health per unit reduction (e.g., per 10 µg/m{sup 3} decrease) in average PM2.5 concentrations, it may be essential to consider how interventions change the distributions of exposure concentrations.
54 ENVIRONMENTAL SCIENCES↗
Coupling dinitrogen and hydrocarbons through aryl migration
A persistent challenge in chemistry is to activate abundant molecules such as hydrocarbons and atmospheric N 2 , because these compounds are often inert. In particular, forming C–N bonds from N 2 typically requires a reactive organic precursor, which limits the ability to design catalytic cycles. In this article, we report an diketiminate-supported iron system that is able to sequentially activate benzene and N 2 , forming aniline derivatives. The key to this new coupling reaction is the partial silylation of a reduced iron-N 2 complex, which is followed by migratory insertion of a benzene-derived phenyl group to the nitrogen. Further reduction releases the nitrogen products, and the iron product can re-enter the resulting cyclic pathway. Using a mixture of sodium powder, crown ether, and trimethylsilyl bromide, an easily prepared diketiminate iron bromide complex can mediate the one-pot conversion of several petroleum-derived liquid compounds into the corresponding silylated aniline derivatives using N 2 as the nitrogen source. Numerous compounds along the cyclic pathway have been isolated and crystallographically characterized; their reactivity outlines the mechanism including the hydrocarbon activation step and the N 2 functionalization step. This new strategy incorporates nitrogen atoms from N 2 directly into abundant hydrocarbons.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Verilator Testbench Environment (VTE) v0.1
VTE is a library that allows fast and simple generation of C++ testers for modules written in Chisel and build an efficient interface to existing C++ based simulators. It contains Scala-based interface and C++ testbench class. Scala interface interacts with Firtl Interpreter and generates a basic set of C++ testbench files. These files contain the list of the Device Under Test (DUT) input-output ports as well as their parameters. C++ testbench provides functionalities similar to the Chisel PeekPokeTester, such as poke, expect, step functions. As a backend it uses Verilator.
Fatollahi-Fard, Farzad↗
Towards a unified nonlocal, peridynamics framework for the coarse-graining of molecular dynamics data with fractures
Molecular dynamics (MD) has served as a powerful tool for designing materials with reduced reliance on laboratory testing. However, the use of MD directly to treat the deformation and failure of materials at the mesoscale is still largely beyond reach. In this work, we propose a learning framework to extract a peridynamics model as a mesoscale continuum surrogate from MD simulated material fracture data sets. Firstly, we develop a novel coarse-graining method, to automatically handle the material fracture and its corresponding discontinuities in the MD displacement data sets. Inspired by the weighted essentially non-oscillatory (WENO) scheme, the key idea lies at an adaptive procedure to automatically choose the locally smoothest stencil, then reconstruct the coarse-grained material displacement field as the piecewise smooth solutions containing discontinuities. Then, based on the coarse-grained MD data, a two-phase optimization-based learning approach is proposed to infer the optimal peridynamics model with damage criterion. In the first phase, we identify the optimal nonlocal kernel function from the data sets without material damage to capture the material stiffness properties. Then, in the second phase, the material damage criterion is learnt as a smoothed step function from the data with fractures. As a result, a peridynamics surrogate is obtained. As a continuum model, our peridynamics surrogate model can be employed in further prediction tasks with different grid resolutions from training, and hence allows for substantial reductions in computational cost compared with MD. We illustrate the efficacy of the proposed approach with several numerical tests for the dynamic crack propagation problem in a single-layer graphene. Our tests show that the proposed data-driven model is robust and generalizable, in the sense that it is capable of modeling the initialization and growth of fractures under discretization and loading settings that are different from the ones used during training.
97 MATHEMATICS AND COMPUTING↗
LightMAT - Pediction of Aluminum/Steel Joint Failure
Develop a predictive model of dissimilar metallic spot joints and their behavior during fracture; specifically, whether the joint fractures via interfacial fracture or button pull-out as a function of alloy, sheet thickness, faying interface microstructure, and thermal-mechanical treatment of the weld nugget and heat affected zone. Having the ability to model whether a given joint structure would fracture inter-facially or via button pullout will reduce development time and provide savings to vehicle design programs. This would provide a significant step function improvement in reducing the time-to-market for this multi-material, weight-saving technology.
36 MATERIALS SCIENCE↗