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Photometric Confirmation and Characterization of the Ennomos Collisional Family in the Jupiter Trojans
No full textCollisional families offer a unique window into the interior composition of asteroid populations. Previous dynamical studies of the Jupiter Trojans have uncovered a handful of potential collisional families, two of which have been subsequently confirmed through spectral characterization. In this paper, we present new multiband photometric observations of the proposed Ennomos family and derive precise g − i colors of 75 candidate family members. While the majority of the targets have visible colors that are indistinguishable from background objects, we identify 13 objects with closely grouped dynamical properties that have significantly bluer colors. We determine that the true Ennomos collisional family is tightly confined to a’_p > 5.29 au and 0.45 < sin i_p < 0.47, and the majority of its confirmed members have near-solar spectral slopes, including some of the bluest objects hitherto discovered in the Trojan population. The property of distinctly neutral colors that is shared by both the Ennomos family and the previously characterized Eurybates family indicates that the spectral properties of freshly exposed surfaces in the Jupiter region are markedly different than the surfaces of uncollided Trojans. This implies that the processes of ice sublimation and space weathering at 5.2 au yield a distinct regolith chemistry from the primordial environment within which the Trojans were initially accreted. It also suggests that the Trojans were emplaced in their present-day location from elsewhere sometime after the initial population formed, which is a key prediction of recent dynamical instability models of solar system evolution
Investigation of signal characteristics and charge sharing in AC-LGADs with laser and test beam measurements
No full textAC-LGADs, also referred to as resistive silicon detectors, are a recent development of low-gain avalanche detectors (LGADs), based on a sensor design where the multiplication layer and n⁺ contact are continuous, and only the metal layer is patterned. In AC-LGADs, the signal is capacitively coupled from the continuous, resistive n⁺ layer over a dielectric to the metal electrodes. Therefore, the spatial resolution is not only influenced by the electrode pitch, but also the relative size of the metal electrodes. Signal propagation between the metallized areas and charge sharing between electrodes plays a larger role in these detectors than in conventional silicon sensors read out in DC mode. AC-LGADs from two manufacturers were studied in beam tests and with infrared laser scans. The impact of n⁺ layer resistivity and metal electrode pitch on the charge sharing and achievable position resolution is shown. For strips with 100 µm pitch, a resolution of ¡ 5 µm can be reached. The charge sharing between neighboring strips is investigated in more detail, indicating the induction of signal charge and subsequent re-sharing over the n⁺ layer. Furthermore, an approach to identify signal sharing over large distances is presented
Posttraumatic stress disorder symptom trajectories in a 16-month COVID-19 pandemic period
No full textCOVID-19 pandemic presents an unheralded opportunity to better understand trajectories of posttraumatic stress disorder (PTSD) symptoms across a prolonged period of social disruption and stress. We tracked PTSD symptoms among trauma-exposed individuals in the United States and sought to identify population-based variability in PTSD symptom trajectories and understand what, if any, early pandemic experiences predicted membership in one trajectory versus others. As part of a longitudinal study of U.S. residents during the pandemic, participants who reported at least one potentially traumatic experience in their lifetime (N = 1,206) at Wave 1 (April 2020) were included in the current study. PTSD symptoms were assessed using the PCL-5 at four time points extending to July 2021. Latent growth mixture modeling was used to identify heterogeneous symptom trajectories. Trajectory membership was regressed on experiences from the early stage of the pandemic as measured using the Epidemic-Pandemic Impacts Inventory in a model that controlled for variables with documented associations to PTSD trajectories, including age, sex, income, and trauma history. Four trajectories were identified, categorized as resilient (73.0%), recurring (13.3%), recovering (8.3%), and chronic (5.5%). Emotional and physical health problems and positive changes associated with the early phase of the pandemic were each significant predictors of trajectory membership over and above all other variables in the model. Predictors primarily differentiated the resilient trajectory from each of the other three trajectories. Distinct PTSD symptom trajectories during the COVID-19 pandemic suggest a need for targeted efforts to help individuals at most risk for ongoing distress
ᴛʀɪɴɪᴛʏ I: self-consistently modelling the dark matter halo-galaxy-supermassive black hole connection from z = 0-10
No full textWe present ᴛʀɪɴɪᴛʏ, a flexible empirical model that self-consistently infers the statistical connection between dark matter haloes, galaxies, and supermassive black holes (SMBHs). ᴛʀɪɴɪᴛʏ is constrained by galaxy observables from 0 < z < 10 [galaxies’ stellar mass functions, specific and cosmic star formation rates (SFRs), quenched fractions, and UV luminosity functions] and SMBH observables from 0 < z < 6.5 (quasar luminosity functions, quasar probability distribution functions, active black hole mass functions, local SMBH mass–bulge mass relations, and the observed SMBH mass distributions of high-redshift bright quasars). The model includes full treatment of observational systematics [e.g. active galactic nucleus (AGN) obscuration and errors in stellar masses]. From these data, ᴛʀɪɴɪᴛʏ infers the average SMBH mass, SMBH accretion rate, merger rate, and Eddington ratio distribution as functions of halo mass, galaxy stellar mass, and redshift. Key findings include: (1) the normalization and the slope of the SMBH mass–bulge mass relation increases mildly from z = 0 to z = 10; (2) The best-fitting AGN radiative+kinetic efficiency is ∼0.05–0.06, but can be in the range ∼0.035–0.07 with alternative input assumptions; (3) AGNs show downsizing, i.e. the Eddington ratios of more massive SMBHs start to decrease earlier than those of lower mass objects; (4) The average ratio between average SMBH accretion rate and SFR is ∼10⁻³ for low-mass galaxies, which are primarily star-forming. This ratio increases to ∼10⁻¹ for the most massive haloes below z ∼ 1, where star formation is quenched but SMBHs continue to accrete
Solid Earth–atmosphere interaction forces during the 15 January 2022 Tonga eruption
No full textRapid venting of volcanic material during the 15 January 2022 Tonga eruption generated impulsive downward reaction forces on the Earth of ~2.0 × 10¹³ N that radiated seismic waves observed throughout the planet, with ~25 s source bursts persisting for ~4.5 hours. The force time history is determined by analysis of teleseismic P waves and Rayleigh waves with periods approximately <50 s, providing insight into the overall volcanic eruption process. The atmospheric acoustic-gravity Lamb wave expanding from the eruption produced broadband ground motions when transiting land, along with driven and conventional tsunami waves. Atmospheric standing acoustic waves near the source produced oscillatory peak forces as large as 4 × 10¹² N, exciting resonant solid Earth Rayleigh wave motions at frequencies of 3.7 and 4.6 mHz
High-dimensional isotomics, part 1: A mathematical framework for isotomics
No full textMolecules can exist in a variety of isotopic forms, called isotopologues, with varying numbers of isotopic substitutions at symmetrically nonequivalent atomic positions. The concentrations of these isotopologues in a sample, referred to here as the sample's isotome, encodes information about that sample's physical and chemical history. While much of this information remains inaccessible due to experimental challenges, recent advances have enabled the measurement of many new constraints on a sample's isotome. These constraints, which may be obtained from several different technologies, currently consist of ratios of subsets of the isotome and in almost all cases fail to directly observe most isotopologues. Thus, it is challenging to relate the set of all measured constraints to the abundances of all possible isotopologues. We here develop a mathematical framework for understanding how various measurements of a sample's isotome relate to one another. We first show a method for tracking isotopologues through complicated experimental designs, to rigorously and precisely state what subsets of the isotome are being measured. We then propose the generalization of the so-called ‘clumped’ isotope ratios to a new ratio type, the “U” value, which gives the concentration of any set of isotopologues relative to the unsubstituted isotopologue; this is a more appropriate way to report many isotopologue measurements. The U value can be used to compare and combine clumped, molecular-average, and site-specific measures of isotopic content; we demonstrate that for molecules with near-stochastic distributions of isotopes (and thus for many cases of interest), the molecular-average or site-specific U values are approximately equal to the corresponding molecular-average or site-specific isotope ratio. The U values therefore provide a convenient framework for comparing and manipulating many different types of observations. To demonstrate our work in practice, we apply it to a MS/MS experiment in which a subset of isotopologues with a given cardinal mass is selected, subjected to collisional fragmentation, and then observed in an Orbitrap mass spectrometer. This design, which is now practical, offers many constraints on a sample's isotome that are conceptually difficult to relate to concentrations of individual isotopologues. We analyze a simulated MS/MS experiment offering over 100 constraints on a methionine isotome (we plan to present our experimental results from this experiment in a companion publication). Our framework enables us to report conventional data products, such as overall molecular δ^(13C)_(PDB) values, as well as measurements of various singly and multiply-substituted (including triply-substituted) isotopologues, demonstrating the efficacy and generalizability of our mathematical methods
Model-Free and Prior-Free Data-Driven Inference in Mechanics
No full textWe present a model-free data-driven inference method that enables inferences on system outcomes to be derived directly from empirical data without the need for intervening modeling of any type, be it modeling of a material law or modeling of a prior distribution of material states. We specifically consider physical systems with states characterized by points in a phase space determined by the governing field equations. We assume that the system is characterized by two likelihood measures: one μ_D measuring the likelihood of observing a material state in phase space; and another μ_E measuring the likelihood of states satisfying the field equations, possibly under random actuation. We introduce a notion of intersection between measures which can be interpreted to quantify the likelihood of system outcomes. We provide conditions under which the intersection can be characterized as the athermal limit μ_∞ of entropic regularizations μ_B, or thermalizations, of the product measure μ = μ_D x μ_E as β → +∞. We also supply conditions under which μ_∞ can be obtained as the athermal limit of carefully thermalized (μ_[h,β_(h)]) sequences of empirical data sets (μ_h) approximating weakly an unknown likelihood function μ. In particular, we find that the cooling sequence β_h → +∞ must be slow enough, corresponding to annealing, in order for the proper limit μ_∞ to be delivered. Finally, we derive explicit analytic expressions for expectations E[⨍] of outcomes ⨍ that are explicit in the data, thus demonstrating the feasibility of the model-free data-driven paradigm as regards making convergent inferences directly from the data without recourse to intermediate modeling steps
Location-aware ingestible microdevices for wireless monitoring of gastrointestinal dynamics
No full textLocalization and tracking of ingestible microdevices in the gastrointestinal (GI) tract is valuable for the diagnosis and treatment of GI disorders. Such systems require a large field-of-view of tracking, high spatiotemporal resolution, wirelessly operated microdevices and a non-obstructive field generator that is safe to use in practical settings. However, the capabilities of current systems remain limited. Here, we report three dimensional (3D) localization and tracking of wireless ingestible microdevices in the GI tract of large animals in real time and with millimetre-scale resolution. This is achieved by generating 3D magnetic field gradients in the GI field-of-view using high-efficiency planar electromagnetic coils that encode each spatial point with a distinct magnetic field magnitude. The field magnitude is measured and transmitted by the miniaturized, low-power and wireless microdevices to decode their location as they travel through the GI tract. This system could be useful for quantitative assessment of the GI transit-time, precision targeting of therapeutic interventions and minimally invasive procedures
Model-free Data-Driven inference in computational mechanics
No full textWe extend the model-free Data-Driven computing paradigm to solids and structures that are stochastic due to intrinsic randomness in the material behavior. The behavior of such materials is characterized by a likelihood measure instead of a constitutive relation. We specifically assume that the material likelihood measure is known only through an empirical point-data set in material or phase space. The state of the solid or structure is additionally subject to compatibility and equilibrium constraints. The problem is then to infer the likelihood of a given structural outcome of interest. In this work, we present a Data-Driven method of inference that determines likelihoods of outcomes from the empirical material data and that requires no material or prior modeling. In particular, the computation of expectations is reduced to explicit sums over local material data sets and to quadratures over admissible states, i.e., states satisfying compatibility and equilibrium. The complexity of the material data-set sums is linear in the number of data points and in the number of members in the structure. Efficient population annealing procedures and fast search algorithms for accelerating the calculations are presented. The scope, cost and convergence properties of the method are assessed with the aid selected applications and benchmark tests
Late-time post-merger modeling of a compact binary: effects of relativity, r-process heating, and treatment of transport
No full textDetectable electromagnetic counterparts to gravitational waves from compact binary mergers can be produced by outflows from the black hole-accretion disk remnant during the first 10 s after the merger. Two-dimensional axisymmetric simulations with effective viscosity remain an efficient and informative way to model this late-time post-merger evolution. In addition to the inherent approximations of axisymmetry and modeling turbulent angular momentum transport by a viscosity, previous simulations often make other simplifications related to the treatment of the equation of state and turbulent transport effects. In this paper, we test the effect of these modeling choices. By evolving with the same viscosity the exact post-merger initial configuration previously evolved in Newtonian viscous hydrodynamics, we find that the Newtonian treatment provides a good estimate of the disk ejecta mass but underestimates the outflow velocity. We find that the inclusion of heavy nuclei causes a notable increase in ejecta mass. An approximate inclusion of r-process effects has a comparatively smaller effect, except for its designed effect on the composition. Diffusion of composition and entropy, modeling turbulent transport effects, has the overall effect of reducing ejecta mass and giving it a speed with lower average and more tightly-peaked distribution. Also, we find significant acceleration of outflow even at distances beyond 10 000 km, so that thermal wind velocities only asymptote beyond this radius and at higher values than often reported