90 research outputs found
Feature Extraction and Classification from Planetary Science Datasets enabled by Machine Learning
In this paper we present two examples of recent investigations that we have
undertaken, applying Machine Learning (ML) neural networks (NN) to image
datasets from outer planet missions to achieve feature recognition. Our first
investigation was to recognize ice blocks (also known as rafts, plates,
polygons) in the chaos regions of fractured ice on Europa. We used a transfer
learning approach, adding and training new layers to an industry-standard Mask
R-CNN (Region-based Convolutional Neural Network) to recognize labeled blocks
in a training dataset. Subsequently, the updated model was tested against a new
dataset, achieving 68% precision. In a different application, we applied the
Mask R-CNN to recognize clouds on Titan, again through updated training
followed by testing against new data, with a precision of 95% over 369 images.
We evaluate the relative successes of our techniques and suggest how training
and recognition could be further improved. The new approaches we have used for
planetary datasets can further be applied to similar recognition tasks on other
planets, including Earth. For imagery of outer planets in particular, the
technique holds the possibility of greatly reducing the volume of returned
data, via onboard identification of the most interesting image subsets, or by
returning only differential data (images where changes have occurred) greatly
enhancing the information content of the final data stream
Search for the Migdal effect in liquid xenon with keV-level nuclear recoils
The Migdal effect predicts that a nuclear recoil interaction can be
accompanied by atomic ionization, allowing many dark matter direct detection
experiments to gain sensitivity to sub-GeV masses. We report the first direct
search for the Migdal effect for M- and L-shell electrons in liquid xenon using
7.01.6 keV nuclear recoils produced by tagged neutron scatters. Despite an
observed background rate lower than that of expected signals in the region of
interest, we do not observe a signal consistent with predictions. We discuss
possible explanations, including inaccurate predictions for either the Migdal
rate or the signal response in liquid xenon. We comment on the implications for
direct dark-matter searches and future Migdal characterization efforts.Comment: 8 pages, 4 figure
Quasi-elastic polarization-transfer measurements on the deuteron in anti-parallel kinematics
We present measurements of the polarization-transfer components in the
H reaction, covering a previously unexplored kinematic
region with large positive (anti-parallel) missing momentum, , up
to 220 MeV, and . These measurements, performed
at the Mainz Microtron (MAMI), were motivated by theoretical calculations which
predict small final-state interaction (FSI) effects in these kinematics, making
them favorable for searching for medium modifications of bound nucleons in
nuclei. We find in this kinematic region that the measured
polarization-transfer components and and their ratio agree with the
theoretical calculations, which use free-proton form factors. Using this, we
establish upper limits on possible medium effects that modify the bound
proton's form factor ratio at the level of a few percent. We also
compare the measured polarization-transfer components and their ratio for H
to those of a free (moving) proton. We find that the universal behavior of
H, He and C in the double ratio
is maintained in the positive
missing-momentum region
Low-latency gravitational wave alert products and their performance in anticipation of the fourth LIGO-Virgo-KAGRA observing run
Multi-messenger searches for binary neutron star (BNS) and neutron star-black
hole (NSBH) mergers are currently one of the most exciting areas of astronomy.
The search for joint electromagnetic and neutrino counterparts to gravitational
wave (GW)s has resumed with Advanced LIGO (aLIGO)'s, Advanced Virgo (AdVirgo)'s
and KAGRA's fourth observing run (O4). To support this effort, public
semi-automated data products are sent in near real-time and include
localization and source properties to guide complementary observations.
Subsequent refinements, as and when available, are also relayed as updates. In
preparation for O4, we have conducted a study using a simulated population of
compact binaries and a Mock Data Challenge (MDC) in the form of a real-time
replay to optimize and profile the software infrastructure and scientific
deliverables. End-to-end performance was tested, including data ingestion,
running online search pipelines, performing annotations, and issuing alerts to
the astrophysics community. In this paper, we present an overview of the
low-latency infrastructure as well as an overview of the performance of the
data products to be released during O4 based on a MDC. We report on expected
median latencies for the preliminary alert of full bandwidth searches (29.5 s)
and for the creation of early warning triggers (-3.1 s), and show consistency
and accuracy of released data products using the MDC. This paper provides a
performance overview for LVK low-latency alert structure and data products
using the MDC in anticipation of O4
Network Structure Implied by Initial Axon Outgrowth in Rodent Cortex: Empirical Measurement and Models
The developmental mechanisms by which the network organization of the adult cortex is established are incompletely understood. Here we report on empirical data on the development of connections in hamster isocortex and use these data to parameterize a network model of early cortical connectivity. Using anterograde tracers at a series of postnatal ages, we investigate the growth of connections in the early cortical sheet and systematically map initial axon extension from sites in anterior (motor), middle (somatosensory) and posterior (visual) cortex. As a general rule, developing axons extend from all sites to cover relatively large portions of the cortical field that include multiple cortical areas. From all sites, outgrowth is anisotropic, covering a greater distance along the medial/lateral axis than along the anterior/posterior axis. These observations are summarized as 2-dimensional probability distributions of axon terminal sites over the cortical sheet. Our network model consists of nodes, representing parcels of cortex, embedded in 2-dimensional space. Network nodes are connected via directed edges, representing axons, drawn according to the empirically derived anisotropic probability distribution. The networks generated are described by a number of graph theoretic measurements including graph efficiency, node betweenness centrality and average shortest path length. To determine if connectional anisotropy helps reduce the total volume occupied by axons, we define and measure a simple metric for the extra volume required by axons crossing. We investigate the impact of different levels of anisotropy on network structure and volume. The empirically observed level of anisotropy suggests a good trade-off between volume reduction and maintenance of both network efficiency and robustness. Future work will test the model's predictions for connectivity in larger cortices to gain insight into how the regulation of axonal outgrowth may have evolved to achieve efficient and economical connectivity in larger brains
A planet within the debris disk around the pre-main-sequence star AU Microscopii
AU Microscopii (AU Mic) is the second closest pre main sequence star, at a
distance of 9.79 parsecs and with an age of 22 million years. AU Mic possesses
a relatively rare and spatially resolved3 edge-on debris disk extending from
about 35 to 210 astronomical units from the star, and with clumps exhibiting
non-Keplerian motion. Detection of newly formed planets around such a star is
challenged by the presence of spots, plage, flares and other manifestations of
magnetic activity on the star. Here we report observations of a planet
transiting AU Mic. The transiting planet, AU Mic b, has an orbital period of
8.46 days, an orbital distance of 0.07 astronomical units, a radius of 0.4
Jupiter radii, and a mass of less than 0.18 Jupiter masses at 3 sigma
confidence. Our observations of a planet co-existing with a debris disk offer
the opportunity to test the predictions of current models of planet formation
and evolution.Comment: Nature, published June 24th [author spelling name fix
Measuring the predictability of life outcomes with a scientific mass collaboration.
How predictable are life trajectories? We investigated this question with a scientific mass collaboration using the common task method; 160 teams built predictive models for six life outcomes using data from the Fragile Families and Child Wellbeing Study, a high-quality birth cohort study. Despite using a rich dataset and applying machine-learning methods optimized for prediction, the best predictions were not very accurate and were only slightly better than those from a simple benchmark model. Within each outcome, prediction error was strongly associated with the family being predicted and weakly associated with the technique used to generate the prediction. Overall, these results suggest practical limits to the predictability of life outcomes in some settings and illustrate the value of mass collaborations in the social sciences
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