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A sparsity-promoting resolvent analysis for the identification of spatiotemporally-localized amplification mechanisms
No full textThis work introduces a variant of resolvent analysis that identifies forcing and response modes that are sparse in both space and time. This is achieved through the use of a sparse principal component analysis (PCA) algorithm, which formulates the associated optimization problem as a nonlinear eigenproblem that can be solved with an inverse power method. We apply this method to parallel shear flows, both in the case where we assume Fourier modes in time (as in standard resolvent analysis) and obtain spatial localization, and where we allow for temporally-sparse modes through the use of a linearized Navier-Stokes operator discretized in both space and time. Appropriate choice of desired mode sparsity allows for the identification of structures corresponding to high amplification that are localized in both space and time. We report on the similarities and differences between these structures and those from standard methods of analysis. After validating this space-time resolvent analysis on statistically-stationary channel flow, we next implement the methodology on a time-periodic Stokes boundary layer, demonstrating the applicability of the approach to non-statistically-stationary systems
A novel insight into deterioration of heavily sulfur-loaded cathode in Li-S battery
No full textActive-substance (S₈ and Li₂S) deposition layer formed on polar interfaces is more reactive than that formed on apolar interfaces. However, when deposition layer reaches a certain thickness, by-path active-substance deposition takes place because of polysulfide disproportionation, which aggravates active-substance segregation to decrease the reactivity. This leads to a significant capacity decay and failure to accomplish polysulfide delithiation after certain cycles, which is understood as the results of decreased active-substance utilization and formed local micro-short-circuits, respectively. The finding of correlation between active-substance segregation and cathode deterioration inspires the design of polytetrafluoroethylene-based self-supported cathode to suppress active-substance segregation through avoiding increase of interphase contact resistance during cycling. With S-loading of 4.0 mg cm⁻², the as-prepared cathode demonstrates excellent cycleability, retaining a capacity of 300 mAh g⁻¹ at a rate of 2C after 1000 cycles. When increasing S-loading up to 36.5 mg cm⁻², the as-obtained cathode delivers an ultra-high areal capacity of 24.6 mAh cm⁻² after 100 cycles at 0.1 C. However, increasing S-loading aggravates Li₂S segregation which then narrows down Li⁺ transportation, leading to formation and growth of Li-shunts which in turn stimulates active-substance segregation. Such an inductive interaction between Li-shunt growth and active-substance segregation results in the fast formation of local micro-short-circuits, causing the constant supply of Li from Li shunts to cathode, and eventually accelerating cathode deterioration
OUTformation: Distributed Data-Gathering with Feedback under Unknown Environment and Communication Delay Constraints
No full textTowards the informed design of large-scale distributed data-gathering architectures under real-world assumptions such as nonzero communication delays and unknown environment dynamics, this paper considers the effects of allowing feedback communication from the central processor to external sensors. Using simple but representative state-estimation examples, we investigate fundamental tradeoffs between the mean-squared error (MSE) of the central processor's estimate of the environment state, and the total power expenditure per sensor under more conventional architectures without feedback (INformation) versus those with broadcast feedback (OUTformation). The primary advantage of enabling feedback is that each sensor's understanding of the central processor's estimate improves, which enables each sensor to determine when and what parts of its current observations to transmit. We use theory to demonstrate conditions in which OUTformation maintains the same MSE as INformation with less power expended on average, and conditions in which OUTformation obtains less MSE than INformation at additional power cost. These performance tradeoffs are also considered under settings where environments undergo less variation, and sensors implement random backoff times to prevent transmission collisions. Our results are supported via numerical studies, which show that the properties derived in theory still hold even when some of the simplifying assumptions are removed
Robust Trajectory Prediction against Adversarial Attacks
No full textTrajectory prediction using deep neural networks (DNNs) is an essential component of autonomous driving (AD) systems. However, these methods are vulnerable to adversarial attacks, leading to serious consequences such as collisions. In this work, we identify two key ingredients to defend trajectory prediction models against adversarial attacks including (1) designing effective adversarial training methods and (2) adding domain-specific data augmentation to mitigate the performance degradation on clean data. We demonstrate that our method is able to improve the performance by 46% on adversarial data and at the cost of only 3% performance degradation on clean data, compared to the model trained with clean data. Additionally, compared to existing robust methods, our method can improve performance by 21% on adversarial examples and 9% on clean data. Our robust model is evaluated with a planner to study its downstream impacts. We demonstrate that our model can significantly reduce the severe accident rates (e.g., collisions and off-road driving)
FourCastNet: Accelerating Global High-Resolution Weather Forecasting using Adaptive Fourier Neural Operators
No full textExtreme weather amplified by climate change is causing increasingly devastating impacts across the globe. The current use of physics-based numerical weather prediction (NWP) limits accuracy due to high computational cost and strict time-to-solution limits. We report that a data-driven deep learning Earth system emulator, FourCastNet, can predict global weather and generate medium-range forecasts five orders-of-magnitude faster than NWP while approaching state-of-the-art accuracy. FourCast-Net is optimized and scales efficiently on three supercomputing systems: Selene, Perlmutter, and JUWELS Booster up to 3,808 NVIDIA A100 GPUs, attaining 140.8 petaFLOPS in mixed precision (11.9%of peak at that scale). The time-to-solution for training FourCastNet measured on JUWELS Booster on 3,072GPUs is 67.4minutes, resulting in an 80,000times faster time-to-solution relative to state-of-the-art NWP, in inference. FourCastNet produces accurate instantaneous weather predictions for a week in advance, enables enormous ensembles that better capture weather extremes, and supports higher global forecast resolutions
Quasinormal-mode filters: A new approach to analyze the gravitational-wave ringdown of binary black-hole mergers
No full textWe propose two frequency-domain filters to analyze ringdown signals of binary black hole mergers. The first rational filter is constructed based on a set of (arbitrary) quasinormal modes (QNMs) of the remnant black holes, whereas the second full filter comes from the transmissivity of the remnant black holes. The two filters can remove corresponding QNMs from original time-domain ringdowns, while changing early inspiral signals in a trivial way—merely a time and phase shift. After filtering out dominant QNMs we can visualize the existence of various subdominant effects. For example, by applying our filters to a GW150914-like numerical relativity (NR) waveform, we find second-order effects in the (l = 4, m = 4), (l = 5, m = 4), and (l = 5, m = 5) harmonics; the spherical-spheroidal mixing mode in the (l = 2, m = 2) harmonic; and a mixing mode in the (l = 2, m = 1) harmonic due to a gravitational recoil. In another NR simulation where two component spins are antialigned with the orbital angular momentum we also find retrograde modes. The filters are sensitive to the remnant properties (i.e., mass and spin) and thus have a potential application to future data analyses and parameter estimations. We also investigate the stability of the full filter. Its connection to the instability of QNM spectra is discussed
Galaxy Zoo: Clump Scout – Design and first application of a two-dimensional aggregation tool for citizen science
No full textGalaxy Zoo: Clump Scout is a web-based citizen science project designed to identify and spatially locate giant star forming clumps in galaxies that were imaged by the Sloan Digital Sky Survey Legacy Survey. We present a statistically driven software framework that is designed to aggregate two-dimensional annotations of clump locations provided by multiple independent Galaxy Zoo: Clump Scout volunteers and generate a consensus label that identifies the locations of probable clumps within each galaxy. The statistical model our framework is based on allows us to assign false-positive probabilities to each of the clumps we identify, to estimate the skill levels of each of the volunteers who contribute to Galaxy Zoo: Clump Scout and also to quantitatively assess the reliability of the consensus labels that are derived for each subject. We apply our framework to a data set containing 3561 454 two-dimensional points, which constitute 1739 259 annotations of 85 286 distinct subjects provided by 20 999 volunteers. Using this data set, we identify 128 100 potential clumps distributed among 44 126 galaxies. This data set can be used to study the prevalence and demographics of giant star forming clumps in low-redshift galaxies. The code for our aggregation software framework is publicly available at: https://github.com/ou-astrophysics/BoxAggregato
Improving White Dwarfs as Chronometers with Gaia Parallaxes and Spectroscopic Metallicities
No full textWhite dwarfs (WDs) offer unrealized potential in solving two problems in astrophysics: stellar age accuracy and precision. WD cooling ages can be inferred from surface temperatures and radii, which can be constrained with precision by high-quality photometry and parallaxes. Accurate and precise Gaia parallaxes along with photometric surveys provide information to derive cooling and total ages for vast numbers of WDs. Here we analyze 1372 WDs found in wide binaries with main-sequence (MS) companions and report on the cooling and total age precision attainable in these WD+MS systems. The total age of a WD can be further constrained if its original metallicity is known because the MS lifetime depends on metallicity at fixed mass, yet metallicity is unavailable via spectroscopy of the WD. We show that incorporating spectroscopic metallicity constraints from 38 wide binary MS companions substantially decreases internal uncertainties in WD total ages compared to a uniform constraint. Averaged over the 38 stars in our sample, the total (internal) age uncertainty improves from 21.04% to 16.77% when incorporating the spectroscopic constraint. Higher mass WDs yield better total age precision; for eight WDs with zero-age MS masses ≥2.0 M_⊙, the mean uncertainty in total ages improves from 8.61% to 4.54% when incorporating spectroscopic metallicities. We find that it is often possible to achieve 5% total age precision for WDs with progenitor masses above 2.0 M_⊙ if parallaxes with ≤1% precision and Pan-STARRS g, r, and i photometry with ≤0.01 mag precision are available
A Panchromatic Study of Massive Stars in the Extremely Metal-poor Local Group Dwarf Galaxy Leo A
No full textWe characterize massive stars (M > 8 M_⊙) in the nearby (D ∼ 0.8 Mpc) extremely metal-poor (Z ∼ 5% Z_⊙) galaxy Leo A using Hubble Space Telescope ultraviolet (UV), optical, and near-infrared (NIR) imaging along with Keck/Low-Resolution Imaging Spectrograph and MMT/Binospec optical spectroscopy for 18 main-sequence OB stars. We find that: (a) 12 of our 18 stars show emission lines, despite not being associated with an H ii region, suggestive of stellar activity (e.g., mass loss, accretion, binary star interaction), which is consistent with previous predictions of enhanced activity at low metallicity; (b) six are Be stars, which are the first to be spectroscopically studied at such low metallicity—these Be stars have unusual panchromatic SEDs; (c) for stars well fit by the TLUSTY nonlocal thermodynamic equilibrium models, the photometric and spectroscopic values of log (T_(eff)) and log (g) agree to within ∼0.01 dex and ∼0.18 dex, respectively, indicating that near-UV/optical/NIR imaging can be used to reliably characterize massive (M ∼ 8–30 M_⊙) main-sequence star properties relative to optical spectroscopy; (d) the properties of the most-massive stars in H II regions are consistent with constraints from previous nebular emission line studies; and (e) 13 stars with M > 8M_⊙ are > 40 pc from a known star cluster or H II region. Our sample comprises ∼50% of all known massive stars at Z ≲ 10% Z_⊙ with derived stellar parameters, high-quality optical spectra, and panchromatic photometry
Biosignature Preservation Aided by Organic-Cation Interactions in Proterozoic Tidal Environments
No full textThe preservation of organic biosignatures during the Proterozoic Eon required specific taphonomic windows that could entomb organic matter to preserve amorphous kerogen and even microbial body fossils before they could be extensively degraded. Some of the best examples of such preservation are found in early diagenetic chert that formed in peritidal environments. This chert contains discrete domains of amorphous kerogen and sometimes kerogenous microbial mat structures and microbial body fossils. Our understanding of how these exquisite microfossils were preserved and the balance between organic degradation and mineral formation has remained incomplete. Here, we present new insights into organic preservation in Proterozoic peritidal environments facilitated through interactions among organic matter, cations, and silica. Organic matter from Proterozoic peritidal environments is not preserved by micro- or cryptocrystalline quartz alone. Rather, preservation includes cation-rich nanoscopic phases containing magnesium, calcium, silica, and aluminum that pre-date chert emplacement and may provide nucleation sites for silica deposition and enable further chert development. Using scanning electron microscopy and elemental mapping with energy dispersive X-ray spectroscopy, we identify cation enrichment in Proterozoic organic matter and cation-rich nanoscopic phases that pre-date chert. We pair these analyses with precipitation experiments to investigate the role of cations in the precipitation of silica from seawater. Our findings suggest that organic preservation in peritidal environments required rapid formation of nanoscopic mineral phases through the interactions of organic matter with seawater. These organic-cation interactions likely laid the initial foundation for the preservation and entombment of biosignatures, paving the way for the development of the fossiliferous chert that now contains these biosignatures and preserves a record of Proterozoic life