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Register a new userImplications of dedicated seismometer measurements on Newtonian-noise cancellation for Advanced LIGO
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Newtonian gravitational noise from seismic fields will become a limiting noise source at low frequency for second-generation, gravitational-wave detectors. It is planned to use seismic sensors surrounding the detectors test masses to coherently subtract Newtonian noise using Wiener filters derived from the correlations between the sensors and detector data. In this work, we use data from a seismometer array deployed at the corner station of the LIGO Hanford detector combined with a tiltmeter for a detailed characterization of the seismic field and to predict achievable Newtonian-noise subtraction levels. As was shown previously, cancellation of the tiltmeter signal using seismometer data serves as the best available proxy of Newtonian-noise cancellation. According to our results, a relatively small number of seismometers is likely sufficient to perform the noise cancellation due to an almost ideal two-point spatial correlation of seismic surface displacement at the corner station, or alternatively, a tiltmeter deployed under each of the two test masses of the corner station at Hanford will be able to efficiently cancel Newtonian noise. Furthermore, we show that the ground tilt to differential arm-length coupling observed during LIGOs second science run is consistent with gravitational coupling.
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This paper presents an adaptable, parallelizable method for subtracting linearly coupled noise from Advanced LIGO data. We explain the features developed to ensure that the process is robust enough to handle the variability present in Advanced LIGO data. In this work, we target subtraction of noise due to beam jitter, detector calibration lines, and mains power lines. We demonstrate noise subtraction over the entirety of the second observing run, resulting in increases in sensitivity comparable to those reported in previous targeted efforts. Over the course of the second observing run, we see a 30% increase in Advanced LIGO sensitivity to gravitational waves from a broad range of compact binary systems. We expect the use of this method to result in a higher rate of detected gravitational-wave signals in Advanced LIGO data.
The Advanced LIGO detectors have recently completed their second observation run successfully. The run lasted for approximately 10 months and lead to multiple new discoveries. The sensitivity to gravitational waves was partially limited by correlated noise. Here, we utilize auxiliary sensors that witness these correlated noise sources, and use them for noise subtraction in the time domain data. This noise and line removal is particularly significant for the LIGO Hanford Observatory, where the improvement in sensitivity is greater than 20%. Consequently, we were also able to improve the astrophysical estimation for the location, masses, spins and orbital parameters of the gravitational wave progenitors.
The raw outputs of the detectors within the Advanced Laser Interferometer Gravitational-Wave Observatory need to be calibrated in order to produce the estimate of the dimensionless strain used for astrophysical analyses. The two detectors have been upgraded since the second observing run and finished the year-long third observing run. Understanding, accounting, and/or compensating for the complex-valued response of each part of the upgraded detectors improves the overall accuracy of the estimated detector response to gravitational waves. We describe improved understanding and methods used to quantify the response of each detector, with a dedicated effort to define all places where systematic error plays a role. We use the detectors as they stand in the first half (six months) of the third observing run to demonstrate how each identified systematic error impacts the estimated strain and constrain the statistical uncertainty therein. For this time period, we estimate the upper limit on systematic error and associated uncertainty to be $< 7%$ in magnitude and $< 4$ deg in phase ($68%$ confidence interval) in the most sensitive frequency band 20-2000 Hz. The systematic error alone is estimated at levels of $< 2%$ in magnitude and $< 2$ deg in phase.
The sensitivity of the Advanced LIGO detectors to gravitational waves can be affected by environmental disturbances external to the detectors themselves. Since the transition from the former initial LIGO phase, many improvements have been made to the equipment and techniques used to investigate these environmental effects. These methods have aided in tracking down and mitigating noise sources throughout the first three observing runs of the advanced detector era, keeping the ambient contribution of environmental noise below the background noise levels of the detectors. In this paper we describe the methods used and how they have led to the mitigation of noise sources, the role that environmental monitoring has played in the validation of gravitational wave events, and plans for future observing runs.
Advanced LIGOs 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 detectors 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.
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