Machine-learning nonstationary noise out of gravitational-wave detectors

Signal extraction out of background noise is a common challenge in high-precision physics experiments, where the measurement output is often a continuous data stream. To improve the signal-to-noise ratio of the detection, witness sensors are often used to independently measure background noises and subtract them from the main signal. If the noise coupling is linear and stationary, optimal techniques already exist and are routinely implemented in many experiments. However, when the noise coupling is nonstationary, linear techniques often fail or are suboptimal. Inspired by the properties of the background noise in gravitational wave detectors, this work develops a novel algorithm to efficiently characterize and remove nonstationary noise couplings, provided there exist witnesses of the noise source and of the modulation. In this work, the algorithm is described in its most general formulation, and its efficiency is demonstrated with examples from the data of the Advanced LIGO gravitational-wave observatory, where we could obtain an improvement of the detector gravitational-wave reach without introducing any bias on the source parameter estimation

Experiential Learning Framework for Smaller Computer Science Programs

Experiential learning (EL) permeates the Computer Science discipline. This work seeks to codify EL practices for computer science pedagogy into ve key pillars. These pillars have been successfully applied at a small to mid-sized college within the heavily competitive Boston area. This paper further describes how a computer science department may eectively implement the pillars in their own curriculum

A Distribution of Large Particles in the Coma of Comet 103P/Hartley 2

The coma of comet 103P/Hartley 2 has a significant population of large particles observed as point sources in images taken by the Deep Impact spacecraft. We measure their spatial and flux distributions, and attempt to constrain their composition. The flux distribution of these particles implies a very steep size distribution with power-law slopes ranging from -6.6 to -4.7. The radii of the particles extend up to 20 cm, and perhaps up to 2 m, but their exact sizes depend on their unknown light scattering properties. We consider two cases: bright icy material, and dark dusty material. The icy case better describes the particles if water sublimation from the particles causes a significant rocket force, which we propose as the best method to account for the observed spatial distribution. Solar radiation is a plausible alternative, but only if the particles are very low density aggregates. If we treat the particles as mini-nuclei, we estimate they account for <16-80% of the comet's total water production rate (within 20.6 km). Dark dusty particles, however, are not favored based on mass arguments. The water production rate from bright icy particles is constrained with an upper limit of 0.1 to 0.5% of the total water production rate of the comet. If indeed icy with a high albedo, these particles do not appear to account for the comet's large water production rate. production rate. Erratum: We have corrected the radii and masses of the large particles of comet 103P/Hartley 2 and present revised conclusions in the attached erratum.Comment: Original article: 46 pages, 17 figures, 5 tables, published in Icarus. Erratum: 5 pages, 1 table, accepted for publication in Icaru

Optical properties of cometary particles collected by the COSIMA mass spectrometer on-board <i>Rosetta</i> during the rendezvous phase around comet 67P/Churyumov–Gerasimenko

40 000 collected cometary particles have been identified on the 21 targets exposed by the COSIMA experiment on-board Rosetta to the environment of comet 67P/Churyumov–Gerasimenko from 2014 August to 2016 September. The images of the targets where obtained by the COSIMA microscope (Cosiscope, 13.95 μm pixel−1) with near grazing incidence, which is optimal for the primary objective (detection of collected particles) but very challenging for photometry. However, more than 300 of the collected particles are larger than 100 μm which makes it possible to derive constraints on the optical properties from the distribution of light levels within the particles. Two types of particles collected by COSIMA (compact particles and cluster particles) have been identified in Langevin et al. The best estimate reflectance factors of compact particles range from 10 per cent to 23 per cent. For cluster particles (>90 per cent of large collected particles), the comparison of the signal profiles with illumination from two opposite directions shows that there is scattering within the particles, with a mean free path in the 20–25 μm range, which requires high porosity. The best estimate reflectance factors of cluster particles range from 3 per cent to 22 per cent. This range of reflectance factors overlaps with that obtained from observations of the cometary nucleus at macroscopic scales by OSIRIS and it is consistent with that measured for interplanetary dust particles collected in the stratosphere of the Earth

Experiential Learning in the Technology Disciplines February 2020

Learning-by-doing has long been a tradition in the technology disciplines. It is the hands-on work, combined with student reflection, feedback and assessment, that reinforces theory into practice. Over the past 40 years, experiential learning (EL) in higher education has grown beyond in-class assignments to include internships, cooperative education, team-based learning, project-based learning, community engagement, service learning, international and study-away experiences, capstone projects and research opportunities. This paper provides an overview of experiential education theory and practice in the undergraduate technology disciplines, and presents examples of how experiential learning practices have evolved over time at a medium-sized institution in the Northeast USA. In addition, this paper offers instructors theoretical strategies to improve the hands-on work that is likely already present in their courses

Low Frequency Tilt Seismology with a Precision Ground Rotation Sensor

We describe measurements of the rotational component of teleseismic surface waves using an inertial high-precision ground-rotation-sensor installed at the LIGO Hanford Observatory (LHO). The sensor has a noise floor of 0.4 nrad$/ \sqrt{\rm Hz}$ at 50 mHz and a translational coupling of less than 1 $\mu$rad/m enabling translation-free measurement of small rotations. We present observations of the rotational motion from Rayleigh waves of six teleseismic events from varied locations and with magnitudes ranging from M6.7 to M7.9. These events were used to estimate phase dispersion curves which shows agreement with a similar analysis done with an array of three STS-2 seismometers also located at LHO

Blip glitches in Advanced LIGO data

Blip glitches are short noise transients present in data from ground-based gravitational-wave observatories. These glitches resemble the gravitational-wave signature of massive binary black hole mergers. Hence, the sensitivity of transient gravitational-wave searches to such high-mass systems and other potential short duration sources is degraded by the presence of blip glitches. The origin and rate of occurrence of this type of glitch have been largely unknown. In this paper we explore the population of blip glitches in Advanced LIGO during its first and second observing runs. On average, we find that Advanced LIGO data contains approximately two blip glitches per hour of data. We identify four subsets of blip glitches correlated with detector auxiliary or environmental sensor channels, however the physical causes of the majority of blips remain unclear