Self-Updating Models with Error Remediation

Many environments currently employ machine learning models for data processing and analytics that were built using a limited number of training data points. Once deployed, the models are exposed to significant amounts of previously-unseen data, not all of which is representative of the original, limited training data. However, updating these deployed models can be difficult due to logistical, bandwidth, time, hardware, and/or data sensitivity constraints. We propose a framework, Self-Updating Models with Error Remediation (SUMER), in which a deployed model updates itself as new data becomes available. SUMER uses techniques from semi-supervised learning and noise remediation to iteratively retrain a deployed model using intelligently-chosen predictions from the model as the labels for new training iterations. A key component of SUMER is the notion of error remediation as self-labeled data can be susceptible to the propagation of errors. We investigate the use of SUMER across various data sets and iterations. We find that self-updating models (SUMs) generally perform better than models that do not attempt to self-update when presented with additional previously-unseen data. This performance gap is accentuated in cases where there is only limited amounts of initial training data. We also find that the performance of SUMER is generally better than the performance of SUMs, demonstrating a benefit in applying error remediation. Consequently, SUMER can autonomously enhance the operational capabilities of existing data processing systems by intelligently updating models in dynamic environments.Comment: 17 pages, 13 figures, published in the proceedings of the Artificial Intelligence and Machine Learning for Multi-Domain Operations Applications II conference in the SPIE Defense + Commercial Sensing, 2020 symposiu

Polarimetric Properties of Event Horizon Telescope Targets from ALMA

We present the results from a full polarization study carried out with the Atacama Large Millimeter/submillimeter Array (ALMA) during the first Very Long Baseline Interferometry (VLBI) campaign, which was conducted in 2017 April in the λ3 mm and λ1.3 mm bands, in concert with the Global mm-VLBI Array (GMVA) and the Event Horizon Telescope (EHT), respectively. We determine the polarization and Faraday properties of all VLBI targets, including Sgr A*, M87, and a dozen radio-loud active galactic nuclei (AGNs), in the two bands at several epochs in a time window of 10 days. We detect high linear polarization fractions (2%–15%) and large rotation measures (RM > 103.3–105.5 rad m−2), confirming the trends of previous AGN studies at millimeter wavelengths. We find that blazars are more strongly polarized than other AGNs in the sample, while exhibiting (on average) order-of-magnitude lower RM values, consistent with the AGN viewing angle unification scheme. For Sgr A* we report a mean RM of (−4.2 ± 0.3) × 105 rad m−2 at 1.3 mm, consistent with measurements over the past decade and, for the first time, an RM of (–2.1 ± 0.1) × 105 rad m−2 at 3 mm, suggesting that about half of the Faraday rotation at 1.3 mm may occur between the 3 mm photosphere and the 1.3 mm source. We also report the first unambiguous measurement of RM toward the M87 nucleus at millimeter wavelengths, which undergoes significant changes in magnitude and sign reversals on a one year timescale, spanning the range from −1.2 to 0.3 × 105 rad m−2 at 3 mm and −4.1 to 1.5 × 105 rad m−2 at 1.3 mm. Given this time variability, we argue that, unlike the case of Sgr A*, the RM in M87 does not provide an accurate estimate of the mass accretion rate onto the black hole. We put forward a two-component model, comprised of a variable compact region and a static extended region, that can simultaneously explain the polarimetric properties observed by both the EHT (on horizon scales) and ALMA (which observes the combined emission from both components). These measurements provide critical constraints for the calibration, analysis, and interpretation of simultaneously obtained VLBI data with the EHT and GMVA

Search for intermediate mass black hole binaries in the first observing run of Advanced LIGO

International audienceDuring their first observational run, the two Advanced LIGO detectors attained an unprecedented sensitivity, resulting in the first direct detections of gravitational-wave signals produced by stellar-mass binary black hole systems. This paper reports on an all-sky search for gravitational waves (GWs) from merging intermediate mass black hole binaries (IMBHBs). The combined results from two independent search techniques were used in this study: the first employs a matched-filter algorithm that uses a bank of filters covering the GW signal parameter space, while the second is a generic search for GW transients (bursts). No GWs from IMBHBs were detected; therefore, we constrain the rate of several classes of IMBHB mergers. The most stringent limit is obtained for black holes of individual mass 100  M⊙, with spins aligned with the binary orbital angular momentum. For such systems, the merger rate is constrained to be less than 0.93  Gpc−3 yr−1 in comoving units at the 90% confidence level, an improvement of nearly 2 orders of magnitude over previous upper limits

First low-frequency Einstein@Home all-sky search for continuous gravitational waves in Advanced LIGO data

International audienceWe report results of a deep all-sky search for periodic gravitational waves from isolated neutron stars in data from the first Advanced LIGO observing run. This search investigates the low frequency range of Advanced LIGO data, between 20 and 100 Hz, much of which was not explored in initial LIGO. The search was made possible by the computing power provided by the volunteers of the Einstein@Home project. We find no significant signal candidate and set the most stringent upper limits to date on the amplitude of gravitational wave signals from the target population, corresponding to a sensitivity depth of 48.7  [1/Hz]. At the frequency of best strain sensitivity, near 100 Hz, we set 90% confidence upper limits of 1.8×10-25. At the low end of our frequency range, 20 Hz, we achieve upper limits of 3.9×10-24. At 55 Hz we can exclude sources with ellipticities greater than 10-5 within 100 pc of Earth with fiducial value of the principal moment of inertia of 1038  kg m2

Search for intermediate-mass black hole binaries in the third observing run of Advanced LIGO and Advanced Virgo

International audienceIntermediate-mass black holes (IMBHs) span the approximate mass range 100−105 M⊙, between black holes (BHs) that formed by stellar collapse and the supermassive BHs at the centers of galaxies. Mergers of IMBH binaries are the most energetic gravitational-wave sources accessible by the terrestrial detector network. Searches of the first two observing runs of Advanced LIGO and Advanced Virgo did not yield any significant IMBH binary signals. In the third observing run (O3), the increased network sensitivity enabled the detection of GW190521, a signal consistent with a binary merger of mass ∼150 M⊙ providing direct evidence of IMBH formation. Here, we report on a dedicated search of O3 data for further IMBH binary mergers, combining both modeled (matched filter) and model-independent search methods. We find some marginal candidates, but none are sufficiently significant to indicate detection of further IMBH mergers. We quantify the sensitivity of the individual search methods and of the combined search using a suite of IMBH binary signals obtained via numerical relativity, including the effects of spins misaligned with the binary orbital axis, and present the resulting upper limits on astrophysical merger rates. Our most stringent limit is for equal mass and aligned spin BH binary of total mass 200 M⊙ and effective aligned spin 0.8 at 0.056 Gpc−3 yr−1 (90% confidence), a factor of 3.5 more constraining than previous LIGO-Virgo limits. We also update the estimated rate of mergers similar to GW190521 to 0.08 Gpc−3 yr−1.Key words: gravitational waves / stars: black holes / black hole physicsCorresponding author: W. Del Pozzo, e-mail: [email protected]† Deceased, August 2020

Open data from the first and second observing runs of Advanced LIGO and Advanced Virgo

Advanced LIGO and Advanced Virgo are monitoring the sky and collecting gravitational-wave strain data with sufficient sensitivity to detect signals routinely. In this paper we describe the data recorded by these instruments during their first and second observing runs. The main data products are gravitational-wave strain time series sampled at 16384 Hz. The datasets that include this strain measurement can be freely accessed through the Gravitational Wave Open Science Center at http://gw-openscience.org, together with data-quality information essential for the analysis of LIGO and Virgo data, documentation, tutorials, and supporting software