Deep Ensemble Analysis for Imaging X-ray Polarimetry

We present a method for enhancing the sensitivity of X-ray telescopic observations with imaging polarimeters, with a focus on the gas pixel detectors (GPDs) to be flown on the Imaging X-ray Polarimetry Explorer (IXPE). Our analysis determines photoelectron directions, X-ray absorption points and X-ray energies for 1-9 keV event tracks, with estimates for both the statistical and model (reconstruction) uncertainties. We use a weighted maximum likelihood combination of predictions from a deep ensemble of ResNet convolutional neural networks, trained on Monte Carlo event simulations. We define a figure of merit to compare the polarization bias-variance trade-off in track reconstruction algorithms. For power-law source spectra, our method improves on the current planned IXPE analysis (and previous deep learning approaches), providing ~45% increase in effective exposure times. For individual energies, our method produces 20-30% absolute improvements in modulation factor for simulated 100% polarized events, while keeping residual systematic modulation within 1 sigma of the finite sample minimum. Absorption point location and photon energy estimates are also significantly improved. We have validated our method with sample data from real GPD detectors.Comment: 18 pages, 9 figures. Accepted to Nuclear Instruments and Methods in Physics Research Section A, Sep 202

Analyzing the footprints of near-surface aqueous turbulence: An image processing-based approach

In this contribution, a detailed investigation of surface thermal patterns on the water surface is presented, with wind speeds ranging from 1 to 7 m s  − 1 and various surface conditions. Distinct structures can be observed on the surface—small-scale short-lived structures termed fish scales and larger-scale cold streaks that are consistent with the footprints of Langmuir circulations. The structure of the surface heat pattern depends strongly on wind-induced stress. Consistent behavior regarding the spacing of cold streaks can be observed in a range of laboratory facilities when expressed as a function of water-sided friction velocity, u * . This behavior systematically decreased until a point of saturation at u *  = 0.7 cm/s. We present a new image processing-based approach to the analysis of the spacing of cold streaks based on a machine learning approach to classify the thermal footprints of near-surface turbulence. Comparison is made with studies of Langmuir circulation and the following key points are found. Results suggest a saturation in the tangential stress, anticipating that similar behavior will be observed in the open ocean. A relation to Langmuir numbers shows that thermal footprints in infrared images are consistent with Langmuir circulations and depend strongly on wind wave conditions

Testing High-energy Emission Models for Blazars with X-Ray Polarimetry

Both leptonic and hadronic emission processes may contribute to blazar jet emission; which dominates in blazars' high-energy emission component remains an open question. Some intermediate synchrotron peaked blazars transition from their low- to high-energy emission components in the X-ray band making them excellent laboratories to probe both components simultaneously, and good targets for the newly launched Imaging X-ray Polarimetry Explorer (IXPE). We characterize the spectral energy distributions for three such blazars, CGRaBS J0211+1051, TXS 0506+056, and S5 0716+714, predicting their X-ray polarization behavior by fitting a multizone polarized leptonic jet model. We find that a significant detection of electron synchrotron dominated polarization is possible with a 300 ks observation for S5 0716+714 and CGRaBS J0211+1051 in their flaring states, while even 500 ks observations are unlikely to measure synchrotron self-Compton (SSC) polarization. Importantly, nonleptonic emission processes like proton synchrotron are marginally detectable for our brightest intermediate synchrotron peaked blazar (ISP), S5 0716+714, during a flaring state. Improved IXPE data reduction methods or next-generation telescopes like eXTP are needed to confidently measure SSC polarization.</p

Evolutionary bursts in Euphorbia (Euphorbiaceae) are linked with photosynthetic pathway

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/109954/1/evo12534.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/109954/2/evo12534-sup-0001-SuppMAT.pd

Ants Sow the Seeds of Global Diversification in Flowering Plants

Background: The extraordinary diversification of angiosperm plants in the Cretaceous and Tertiary periods has produced an estimated 250,000–300,000 living angiosperm species and has fundamentally altered terrestrial ecosystems. Interactions with animals as pollinators or seed dispersers have long been suspected as drivers of angiosperm diversification, yet empirical examples remain sparse or inconclusive. Seed dispersal by ants (myrmecochory) may drive diversification as it can reduce extinction by providing selective advantages to plants and can increase speciation by enhancing geographical isolation by extremely limited dispersal distances. Methodology/Principal Findings: Using the most comprehensive sister-group comparison to date, we tested the hypothesis that myrmecochory leads to higher diversification rates in angiosperm plants. As predicted, diversification rates were substantially higher in ant-dispersed plants than in their non-myrmecochorous relatives. Data from 101 angiosperm lineages in 241 genera from all continents except Antarctica revealed that ant-dispersed lineages contained on average more than twice as many species as did their non-myrmecochorous sister groups. Contrasts in species diversity between sister groups demonstrated that diversification rates did not depend on seed dispersal mode in the sister group and were higher in myrmecochorous lineages in most biogeographic regions. Conclusions/Significance: Myrmecochory, which has evolved independently at least 100 times in angiosperms and is estimated to be present in at least 77 families and 11 000 species, is a key evolutionary innovation and a globally important driver of plant diversity. Myrmecochory provides the best example to date for a consistent effect of any mutualism on largescale diversification