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P- and S-wave velocity estimation by ensemble Kalman inversion of dispersion data for strong motion stations in California
No full textThis study uses an ensemble Kalman method for near-surface seismic site characterization of 154 network earthquake monitoring stations in California to improve the resolution of S-wave velocity (V_S) and P-wave velocity (V_P) profiles—up to the resolution depth—coupled with better quantification of uncertainties compared to previous site characterization studies at this network. These stations were part of the Yong et al. site characterization project, with selected stations based on future recordings of ground motions that are expected to exceed 10 per cent peak ground acceleration in 50 yr. To estimate V_S and V_P from experimental dispersion data, Yong et al. investigated these stations using linearized (local search and iteration) routines, and Yong et al. later studied a subset of these stations using nonlinear (global search and optimization) routines. In both studies, the selection of model parameters—that is, discretization of the V_S and V_P profiles with only five fixed thickness layers—was mainly based on trial and error. In contrast, this paper uses an approximate Bayesian method to assimilate experimental dispersion data and sequentially update an ensemble of particle estimates that span the V_S and V_P parameter spaces. Doing so, we systematically determine the most probable profiles conditioned on the experimental dispersion data, the introduced noise levels, and a priori knowledge in the form of physical constraints. We consider two configurations to discretize the soil depth from the surface to half of the maximum discernible wavelength obtained from the experimental dispersion data, namely refined and coarse models, and two initial models for each configuration to study solution multiplicity. Our results suggest that using the refined model for the top surface layers improves the resolution of near-surface site characteristics and the model’s success rate in capturing dispersion data at high frequencies. All models result in similar VS but distinct VP profiles, with increasing uncertainty at deeper layers, suggesting that the fundamental mode of Rayleigh wave dispersion data is not adequate to constrain the P-wave velocity profile and the S-wave velocity close to the resolution depth
Transient and Equilibrium Responses of the Atlantic Overturning Circulation to Warming in Coupled Climate Models: The Role of Temperature and Salinity
No full textThe long-term response of the Atlantic meridional overturning circulation (AMOC) to climate change remains poorly understood, in part due to the computational expense associated with running atmosphere–ocean general circulation models (GCMs) to equilibrium. Here, we use a collection of millennial-length GCM simulations to examine the transient and equilibrium responses of the AMOC to an abrupt quadrupling of atmospheric carbon dioxide. We find that GCMs consistently simulate an AMOC weakening during the first century but exhibit diverse behaviors over longer time scales, showing different recovery levels. To explain the AMOC behavior, we use a thermal-wind expression, which links the overturning circulation to the meridional density difference between deep-water formation regions and the Atlantic basin. Using this expression, we attribute the evolution of the AMOC on different time scales to changes in temperature and salinity in distinct regions. The initial AMOC shoaling and weakening occurs on centennial time scales and is attributed to a warming of the deep-water formation region. A partial recovery of the AMOC occurs over the next few centuries, and is linked to a simultaneous warming of the Atlantic basin and a positive high-latitude salinity anomaly. The latter reduces the subsurface stratification and reinvigorates deep-water formation. GCMs that exhibit a prolonged AMOC weakening tend to have smaller high-latitude salinity anomalies and increased Arctic sea ice loss. After multiple millennia, the AMOC in some GCMs is stronger than the initial state due to warming of the low-latitude Atlantic. These results highlight the importance of considering high-latitude freshwater changes when examining the past and future evolution of the AMOC evolution on long time scales
Catalytic Enantioselective α-Alkylation of Amides by Unactivated Alkyl Electrophiles
No full textCarbonyl groups that bear an α stereocenter are commonly found in bioactive compounds, and intense effort has therefore been dedicated to the pursuit of stereoselective methods for constructing this motif. While the chiral auxiliary-enabled coupling of enolates with alkyl electrophiles represented groundbreaking progress in addressing this challenge, the next advance in the evolution of this enolate–alkylation approach would be to use a chiral catalyst to control stereochemistry. Herein we describe the achievement of this objective, demonstrating that a nickel catalyst can accomplish enantioselective intermolecular alkylations of racemic Reformatsky reagents with unactivated electrophiles; the resulting α-alkylated carbonyl compounds can be converted in one additional step into a diverse array of ubiquitous families of chiral molecules. Applying a broad spectrum of mechanistic tools, we have gained insight into key intermediates (including the alkylnickel(II) resting state) and elementary steps of the catalytic cycle
All-sky, all-frequency directional search for persistent gravitational waves from Advanced LIGO’s and Advanced Virgo’s first three observing runs
No full textWe present the first results from an all-sky all-frequency (ASAF) search for an anisotropic stochastic gravitational-wave background using the data from the first three observing runs of the Advanced LIGO and Advanced Virgo detectors. Upper limit maps on broadband anisotropies of a persistent stochastic background were published for all observing runs of the LIGO-Virgo detectors. However, a broadband analysis is likely to miss narrowband signals as the signal-to-noise ratio of a narrowband signal can be significantly reduced when combined with detector output from other frequencies. Data folding and the computationally efficient analysis pipeline, PyStoch, enable us to perform the radiometer map-making at every frequency bin. We perform the search at 3072 HEALPix equal area pixels uniformly tiling the sky and in every frequency bin of width
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in the range 20–1726 Hz, except for bins that are likely to contain instrumental artefacts and hence are notched. We do not find any statistically significant evidence for the existence of narrowband gravitational-wave signals in the analyzed frequency bins. Therefore, we place 95% confidence upper limits on the gravitational-wave strain for each pixel-frequency pair, the limits are in the range (0.030 − 9.6) × 10⁻²⁴. In addition, we outline a method to identify candidate pixel-frequency pairs that could be followed up by a more sensitive (and potentially computationally expensive) search, e.g., a matched-filtering-based analysis, to look for fainter nearly monochromatic coherent signals. The ASAF analysis is inherently independent of models describing any spectral or spatial distribution of power. We demonstrate that the ASAF results can be appropriately combined over frequencies and sky directions to successfully recover the broadband directional and isotropic results
Training physics‐based machine‐learning parameterizations with gradient‐free ensemble Kalman methods
No full textMost machine learning applications in Earth system modeling currently rely on gradient-based supervised learning. This imposes stringent constraints on the nature of the data used for training (typically, residual time tendencies are needed), and it complicates learning about the interactions between machine-learned parameterizations and other components of an Earth system model. Approaching learning about process-based parameterizations as an inverse problem resolves many of these issues, since it allows parameterizations to be trained with partial observations or statistics that directly relate to quantities of interest in long-term climate projections. Here we demonstrate the effectiveness of Kalman inversion methods in treating learning about parameterizations as an inverse problem. We consider two different algorithms: unscented and ensemble Kalman inversion. Both methods involve highly parallelizable forward model evaluations, converge exponentially fast, and do not require gradient computations. In addition, unscented Kalman inversion provides a measure of parameter uncertainty. We illustrate how training parameterizations can be posed as a regularized inverse problem and solved by ensemble Kalman methods through the calibration of an eddy-diffusivity mass-flux scheme for subgrid-scale turbulence and convection, using data generated by large-eddy simulations. We find the algorithms amenable to batching strategies, robust to noise and model failures, and efficient in the calibration of hybrid parameterizations that can include empirical closures and neural networks
How to Deploy a 10-km Interferometric Radio Telescope on the Moon with Just Four Tethered Robots
No full textThe Far-side Array for Radio Science Investigations of the Dark ages and Exoplanets (FARSIDE) is a proposed mission concept to the lunar far side that seeks to deploy and operate an array of 128 dual-polarization, dipole antennas over a region of 100 square kilometers. The resulting interferometric radio telescope would provide unprecedented radio images of distant star systems, allowing for the investigation of faint ra-dio signatures of coronal mass ejections and energetic particle events and could also lead to the detection of magnetospheres around exoplanets within their parent star's habitable zone. Simultaneously, FARSIDE would also measure the ‘Dark Ages' of the early Universe at a global 21-cm signal across a range of red shifts (z ~50-100). Each discrete antenna node in the array is connected to a central hub (located at the lander) via a communication and power tether. Nodes are driven by cold-operable electronics that continuously monitor (for 5 or more years) an extremely wide-band of frequencies (200 kHz to 40 MHz), which surpass the capabilities of Earth-based telescopes by two orders of magnitude. Achieving this ground-breaking capability requires a robust deployment strategy on the lunar surface, which is feasible with existing, high-TRL technologies (demonstrated or under active development) and is capable of delivery to the surface on next-generation commercial landers, such as Blue Origin's Blue Moon Lander. This paper presents an antenna packaging, placement, and surface deployment trade study that leverages recent advances in tethered mobile robots under development at NASA's Jet Propulsion Laboratory, which are used to deploy a flat, antenna-embedded, tape tether with optical communication and power transmission capabilities. We investigate the feasibility of deploying 4 separate 12-km tethers, each with 64 remotely powered electronics nodes, using just four rovers that trace out a large spiral pattern that is over 10-km in diameter, where each arm in the spiral is precisely laid out and aligned with respect to a global heading (NSEW) to provide dual polarization across the entire array. Further, we provide a detailed design for an instrument/antenna-embedded tether, detail its accommodation within and deployment from a two-wheeled rover, and show how the entire system can be packaged and deployed from a commercial lunar lander system
Reconstruction of the NuSTAR PSF Using Single-laser Metrology
No full textThis paper describes a method by which the metrology system of the Nuclear Spectroscopic Telescope Array (NuSTAR) X-ray space observatory, which uses two lasers to characterize the relative motion of the optics and focal plane benches, can be approximated if one laser fails. The optics and focal plane benches are separated by a ten-meter-long rigid mast that undergoes small amounts of thermal flexing depending on how the spacecraft is illuminated by the Sun. Compensation for this motion is required in order to produce an in-focus image. We analyze the trends of mast motion by observation parameters, using archival NuSTAR data between 2012 and 2021, in order to discover whether parameters such as the solar aspect angle (SAA) can be used to predict the mast motion in future observations. We find that, by using the SAA, observation date, and orbital phase, we can simulate the motion measured by one of the lasers by translating the track produced by the other laser and applying modifications to the mast aspect solution calculated during the NuSTAR data reduction pipeline. With this simulated mast solution, we are able to reconstruct a minimally distorted point spread function for all but two narrow ranges of SAA. We plan to implement the generation of simulated mast files alongside the usual NuSTAR data reduction pipeline for contingency purposes should a laser on the spacecraft fail in the future. This work also has implications for reducing the risk of implementing laser metrology systems on future missions that use deployable masts to achieve the long focal lengths required in high-energy astronomy
Optical Network Sensing: Opportunities and Challenges
No full textThe scientific community is exploring complementary applications for optical fiber networks. We review recent developments in seismic sensing and discuss the challenge of telemetry pipelines to enable novel fundamental science and wider societal benefits
BASS. XXIII. A New Mid-infrared Diagnostic for Absorption in Active Galactic Nuclei
No full textIn this study, we use the Swift/BAT AGN sample, which has received extensive multiwavelength follow-up analysis as a result of the BAT AGN Spectroscopic Survey, to develop a diagnostic for nuclear obscuration by examining the relationship between the line-of-sight column densities (N_H), the 2–10 keV to 12 μm luminosity ratio, and WISE mid-infrared colors. We demonstrate that heavily obscured AGNs tend to exhibit both preferentially “redder” mid-infrared colors and lower values of L_(X,Obs.)/L_(12 μm) than less obscured AGNs, and we derive expressions relating N_H to the L_(X,Obs.)/L_(12 μm) and L_(22 μm)/L_(4.6 μm) luminosity ratios, as well as develop diagnostic criteria using these ratios. Our diagnostic regions yield samples that are ≳ 80% complete and ≳ 60% pure for AGNs with log(N_H/cm⁻²) ≥ 24, as well as ≳ 85% pure for AGNs with log(N_H/cm⁻²) ≳ 23.5. We find that these diagnostics cannot be used to differentiate between optically star-forming galaxies and active galaxies. Further, mid-IR contributions from host galaxies that dominate the observed 12 μm emission can lead to larger apparent X-ray deficits and redder mid-IR colors than the AGNs would intrinsically exhibit, though this effect helps to better separate less and more obscured AGNs. Finally, we test our diagnostics on two catalogs of AGNs and infrared galaxies, including the XMM-Newton XXL-N field, and we identify several known Compton-thick AGNs, as well as a handful of candidate heavily obscured AGNs based upon our proposed obscuration diagnostics
AIROPA II: modeling instrumental aberrations for off-axis point spread functions in adaptive optics
No full textImages obtained with single-conjugate adaptive optics (AO) show spatial variation of the point spread function (PSF) due to both atmospheric anisoplanatism and instrumental aberrations. The poor knowledge of the PSF across the field of view strongly impacts the ability to take full advantage of AO capabilities. The AIROPA project aims to model these PSF variations for the NIRC2 imager at the Keck Observatory. Here, we present the characterization of the instrumental phase aberrations over the entire NIRC2 field of view and we present a metric for quantifying the quality of the calibration, the fraction of variance unexplained (FVU). We used phase diversity measurements obtained on an artificial light source to characterize the variation of the aberrations across the field of view and their evolution with time. We find that there is a daily variation of the wavefront error (RMS of the residuals is 94 nm) common to the whole detector, but the differential aberrations across the field of view are very stable (RMS of the residuals between different epochs is 59 nm). This means that instrumental calibrations need to be monitored often only at the center of the detector, and the much more time-consuming variations across the field of view can be characterized less frequently (most likely when hardware upgrades happen). Furthermore, we tested AIROPA’s instrumental model through real data of the fiber images on the detector. We find that modeling the PSF variations across the field of view improves the FVU metric by 60% and reduces the detection of fake sources by 70%