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

Improving LIGO calibration accuracy by tracking and compensating for slow temporal variations

Calibration of the second-generation LIGO interferometric gravitational-wave detectors employs a method that uses injected periodic modulations to track and compensate for slow temporal variations in the differential length response of the instruments. These detectors utilize feedback control loops to maintain resonance conditions by suppressing differential arm length variations. We describe how the sensing and actuation functions of these servo loops are parameterized and how the slow variations in these parameters are quantified using the injected modulations. We report the results of applying this method to the LIGO detectors and show that it significantly reduces systematic errors in their calibrated outputs.Comment: 13 pages, 8 figures. This is an author-created, un-copyedited version of an article published in Classical and Quantum Gravity. IOP Publishing Ltd is not responsible for any errors or omissions in this version of the manuscript or any version derived from i

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

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

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

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

Reconstructing the calibrated strain signal in the Advanced LIGO detectors

Advanced LIGO's raw detector output needs to be calibrated to compute dimensionless strain h(t). Calibrated strain data is produced in the time domain using both a low-latency, online procedure and a high-latency, offline procedure. The low-latency h(t) data stream is produced in two stages, the first of which is performed on the same computers that operate the detector's feedback control system. This stage, referred to as the front-end calibration, uses infinite impulse response (IIR) filtering and performs all operations at a 16384 Hz digital sampling rate. Due to several limitations, this procedure currently introduces certain systematic errors in the calibrated strain data, motivating the second stage of the low-latency procedure, known as the low-latency gstlal calibration pipeline. The gstlal calibration pipeline uses finite impulse response (FIR) filtering to apply corrections to the output of the front-end calibration. It applies time-dependent correction factors to the sensing and actuation components of the calibrated strain to reduce systematic errors. The gstlal calibration pipeline is also used in high latency to recalibrate the data, which is necessary due mainly to online dropouts in the calibrated data and identified improvements to the calibration models or filters.Comment: 20 pages including appendices and bibliography. 11 Figures. 3 Table

Prediction for new magnetoelectric fluorides

We use symmetry considerations in order to predict new magnetoelectric fluorides. In addition to these magnetoelectric properties, we discuss among these fluorides the ones susceptible to present multiferroic properties. We emphasize that several materials present ferromagnetic properties. This ferromagnetism should enhance the interplay between magnetic and dielectric properties in these materials.Comment: 12 pages, 4 figures, To appear in Journal of Physics: Condensed Matte

The Stardust – a successful encounter with the remarkable comet Wild 2

On January 2, 2004 the Stardust spacecraft completed a close flyby of comet Wild2 (P81). Flying at a relative speed of 6.1 km/s within 237km of the 5 km nucleus, the spacecraft took 72 close-in images, measured the flux of impacting particles and did TOF mass spectrometry

Impact ionization mass spectra of anorthite cosmic dust analogue particles

Anorthite, the Ca-rich end-member of plagioclase feldspar, is a dominant mineral component of the Lunar highlands. Plagioclase feldspar is also found in comets, meteorites and stony asteroids. It is therefore expected to contribute to the population of interplanetary (and circumplanetary) dust grains within the solar system. After coating micron- and submicron-sized grains of Anorthite with a conductive layer of Platinum, the mineral was successfully accelerated to hypervelocity speeds in the Max Planck Institut für Kernphysik’s Van de Graaff accelerator. We present impact ionization mass spectra generated following the impacts of anorthite grains with a prototype mass spectrometer (the Large Area Mass Analyser, LAMA) designed for use in space, and discuss the behavior of the spectra with increasing impact energy. Correlation analysis is used to identify the compositions and sources of cations present in the spectra, enabling the identification of several molecular cations (e.g., CaAlO2, CaSiO2, Ca2AlO3/CaAlSi2O2) which identify anorthite as the progenitor bulk grain material