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User: As a text script expert, please help me to write a short text script with the topic " Coherence DeepClean: Toward autonomous denoising of gravitational-wave detector data Christina Reissel†1,2,5, Siddharth Soni†1,2, Muhammed Saleem3,4,5, Michael Coughlin3,5, Philip Harris1,5, Erik Katsavounidis1,2,5 1Department of Physics, MIT, Cambridge, MA 02139 2MIT LIGO Laboratory, Cambridge, MA 02139 3School of Physics and Astronomy, University of Minnesota, Minneapolis, MN 55455 4Center for Gravitational Physics, University of Texas at Austin, Austin, TX 78712 5NSF Institute on Accelerated AI Algorithms for Data-Driven Discovery (A3D3), MIT, Cambridge, MA 02139 and University of Minnesota, Minneapolis, MN 55455 E-mail: <PRESIDIO_ANONYMIZED_EMAIL_ADDRESS> December 2024 Abstract.Technical and environmental noise in ground-based laser interferometers designed for gravitational-wave observations like Advanced LIGO, Advanced Virgo and KAGRA, can manifest as narrow (< 1Hz) or broadband (10′s or even 100′s of Hz) spectral lines and features in the instruments’ strain amplitude spectral density.Other than fundamental noise, instrument sensitivity is adversely impacted by short-duration noise transients and long-duration noise couplings originating from the environment or the interferometry [9].This article presents our work on reducing a variety of long-duration noise in gravitational-wave data, focusing on the Advanced LIGO detectors, one in Livingston, Louisiana, and another one in Hanford, Washington State, with a fully automated pipeline.Noise in ground-based gravitational-wave detectors Long-duration noise in ground-based gravitational-wave detectors is characterized by a complex, composite spectrum consisting of both broadband noise and spectral (narrow) lines.While known contributions to the noise budget at frequencies above 1kHz are dominated by quantum noise originating from fluctuations in the phase quadrature of the vacuum field (shot-noise), dominant contributions at lower frequencies are from control noise [7].Itcanbeinterpretedasthefrequencydomainanalogofthecross-correlation Toward autonomous denoising of gravitational-wave detector data 4 Figure 1: Coherence between h(t) and a LIGO Livingston detector corner station magnetometer.Toward autonomous denoising of gravitational-wave detector data 5 Figure 2: Plot showing the highest coherence at each frequency bin.In this section we discuss a new tool called CohMon that we developed for measuring the coherence between the strain data and hundreds of “safe” auxiliary channels once every hour of the observing time for both detectors [34].The primary motivation behind Python based CohMon is witness channel identification so that this information can be fed to noise cleaning tool DeepClean for immediate noise subtraction.Toward autonomous denoising of gravitational-wave detector data 6 0.6 0.5 0.4 0.3 0.2 0.1 0 5 10 15 20 25 30 35 40 Frequency[Hz] ecnerehoC Nov-7 Nov-9 20 Nov-11 15 10 5 0 Nov7 Nov9 Nov11 Dates ruohrepetarhctilG Figure 3: Left: Coherence between the length sensing and control radio frequency reflected light port (LSC REFL RF) photodiode and h(t) is seen increasing during November 7-11 2024 measurements.Statistically significant variation in coherence as a function of time may also be Toward autonomous denoising of gravitational-wave detector data 7 3.0 2.5 2.0 1.5 1.0 0.5 70 75 80 85 90 95 100 Frequency[Hz] zH√/niartsytisneDlartcepSedutilpmA ×10−23 Noisy 0.8 Quiet 0.6 0.4 0.2 0.0 0 1024 2048 3072 4096 5120 6144 7168 Time[Secs]from1415984418 ecnerehoC Figure 4: Left: The peak at 83.3 Hz in the strain amplitude spectral density appears after the residual gas analysis work at the LIGO Livingston mid-station.At the same time the identification and ranking based on coherence values of possible noise witness channels using CohMon provides the basis for noise subtraction in software.Toward autonomous denoising of gravitational-wave detector data 8 Figure 5: Schematic overview of the Coherence DeepClean (CDC) pipeline.Before this work, DeepClean has been demonstrated to clean broadband noise due to beam jitter noise in O2 as well as narrow line noise related to the 60Hz power line [20, 24].Coherence Monitoring: we monitor the coherence between the strain channel and all auxiliary channels considered “safe”, in total approximately 900 channels per detector, using 1024s of data and a Fast Fourier Transform window of 10s.Witness Channel Selection: from the coherence monitor output and for a given Toward autonomous denoising of gravitational-wave detector data 9 frequency interval, we extract the list of witness channels that are highest correlated to the strain.Depending on the noise removal problem, we find the number of selected witness channels to vary between zero and 35, with zero indicating that no suitable witness channel monitoring the noise is found and subsequent denoising is not possible.Results Applying the CDC pipeline to data taken by the LIGO Hanford detector starting September 10, 2023 (GPS time 1378403243), we identify six frequency bands with suitable amounts of witnessed noise: 10-13Hz, 28.5-31.5Hz, 104-109Hz, 110-130Hz, 150-155Hz and 177-183Hz.In figure 7, we show the ASD for particular frequency bands, demonstrating that by applying the CDC pipeline, we can subtract noise with varying characteristics from broadband noise to the removal of single spectral lines or the combination of both.While, in general, we observe significantly less monitored low-frequency noise Toward autonomous denoising of gravitational-wave detector data 11 4 ×10−23 3 ×10−23 2 ×10−23 28.5 29 29.5 30 30.5 31 Frequency[Hz] ]2/1zH/niarts[DSA 8 ×10−24 7 ×10−24 6 ×10−24 5 ×10−24 4 ×10−24 110 112.5 115 117.5 120 122.5 125 127.5 130 Frequency[Hz] ]2/1zH/niarts[DSA 10−23 5 ×10−24 177 178 179 180 181 182 183 Frequency[Hz] ]2/1zH/niarts[DSA Figure 7: Amplitude spectral density (ASD) before (black) and after (red) denoising for dedicated frequency bands using data taken with the LIGO Hanford detector.Given the outputs obtained with the coherence monitor, we select suitable witness channels for denoising Toward autonomous denoising of gravitational-wave detector data 12 12 10 8 6 4 2 0 152 154 156 158 160 BNSRange[Mpc] tnuoC Original(Median: 155.2Mpc) Cleaned(Median: 157.3Mpc) Figure 8: Binary Neutron Star (BNS) Range calculated on 60s long data segments taken with the LIGO Hanford detector on September 10, 2023 (GPS time 1378403243), before and after applying the CDC pipeline.The pipeline, which we refer to as Coherence DeepClean, or CDC, allows us to subtract disparate noise contributions from spectral lines, broadband and composite noise for the first time.While the REFERENCES 13 CDC pipeline improves our understanding of the interferometers and may also help to mimicnoisecouplingsinhardware, itisafirstimportantsteptorwardsfullyautonomous denoising of gravitational-wave detector data in software, adapting to changing noise conditions with minimal human intervention and minimal turn-around times.37 055002 (Preprint 1908.11170) [10] Soni S et al. (LIGO) 2024 Preprint 2409.02831 [11] Davis D et al. (LIGO) 2021 Class.Coherence DeepClean: Toward autonomous denoising of gravitational-wave detector data Christina Reissel†1,2,5, Siddharth Soni†1,2, Muhammed Saleem3,4,5, Michael Coughlin3,5, Philip Harris1,5, Erik Katsavounidis1,2,5 1Department of Physics, MIT, Cambridge, MA 02139 2MIT LIGO Laboratory, Cambridge, MA 02139 3School of Physics and Astronomy, University of Minnesota, Minneapolis, MN 55455 4Center for Gravitational Physics, University of Texas at Austin, Austin, TX 78712 5NSF Institute on Accelerated AI Algorithms for Data-Driven Discovery (A3D3), MIT, Cambridge, MA 02139 and University of Minnesota, Minneapolis, MN 55455 E-mail: <PRESIDIO_ANONYMIZED_EMAIL_ADDRESS> December 2024 Abstract.Technical and environmental noise in ground-based laser interferometers designed for gravitational-wave observations like Advanced LIGO, Advanced Virgo and KAGRA, can manifest as narrow (< 1Hz) or broadband (10′s or even 100′s of Hz) spectral lines and features in the instruments’ strain amplitude spectral density.Other than fundamental noise, instrument sensitivity is adversely impacted by short-duration noise transients and long-duration noise couplings originating from the environment or the interferometry [9].This includes astrophysical searches [12, 13], parameter estimation [14, 15], monitoring squeezing [16], classifying transient noise [17– 19], removing noise couplings [20–22] and multiple other areas [23].Our pipeline combines measurements of the actual instrumental and environmental noise conditions with machine learning denoising algorithms that ultimately improve the instruments’ sensitivity to astrophysical sources.Noise in ground-based gravitational-wave detectors Long-duration noise in ground-based gravitational-wave detectors is characterized by a complex, composite spectrum consisting of both broadband noise and spectral (narrow) lines.Seismometers, microphones, accelerometers, radio receivers, magnetometers, and interferometer state controls are widely used in gravitational-wave detectors to monitor detector behavior and environmental conditions.Narrow spectral artifacts also known as lines adversely impact the gravitational-wave search sensitivity and the LIGO Detector Characterization group employs multiple tools such as Fscan [31], STAMP-PEM [32] and StochMon [33] to study and monitor these lines.Toward autonomous denoising of gravitational-wave detector data 6 0.6 0.5 0.4 0.3 0.2 0.1 0 5 10 15 20 25 30 35 40 Frequency[Hz] ecnerehoC Nov-7 Nov-9 20 Nov-11 15 10 5 0 Nov7 Nov9 Nov11 Dates ruohrepetarhctilG Figure 3: Left: Coherence between the length sensing and control radio frequency reflected light port (LSC REFL RF) photodiode and h(t) is seen increasing during November 7-11 2024 measurements.Radio frequency reflected light ports in the length sensing and control subsystem (LSC REFL RF) are good witnesses of this slow scattering transients.Statistically significant variation in coherence as a function of time may also be Toward autonomous denoising of gravitational-wave detector data 7 3.0 2.5 2.0 1.5 1.0 0.5 70 75 80 85 90 95 100 Frequency[Hz] zH√/niartsytisneDlartcepSedutilpmA ×10−23 Noisy 0.8 Quiet 0.6 0.4 0.2 0.0 0 1024 2048 3072 4096 5120 6144 7168 Time[Secs]from1415984418 ecnerehoC Figure 4: Left: The peak at 83.3 Hz in the strain amplitude spectral density appears after the residual gas analysis work at the LIGO Livingston mid-station.For example, the residual gas analysis (RGA) started driving the mid-station baffle resonance at LIGO Livingston around 5:30 pm UTC on November 18 2024 [38].Our end-to-end, combined pipeline aims to identify and remove a wide variety of noises in different frequency ranges; we refer to this pipeline as Coherence DeepClean (CDC).Witness Channel Selection: from the coherence monitor output and for a given Toward autonomous denoising of gravitational-wave detector data 9 frequency interval, we extract the list of witness channels that are highest correlated to the strain.The hyperparameters of our neural network architecture are derived following hyperparameter tuning, and various analysis parameters (e.g., time-stride, frequency band, coherence threshold, number of channels) have been empirically established.Depending on the exact cleaning problem, the data-taking period, and the number of selected witness channels, selecting suitable witness channels, training, and inference as described above takes between several to up to 15 minutes utilizing a single NVIDIA TITAN X Pascal GPU on the IGWN computing grid.Results Applying the CDC pipeline to data taken by the LIGO Hanford detector starting September 10, 2023 (GPS time 1378403243), we identify six frequency bands with suitable amounts of witnessed noise: 10-13Hz, 28.5-31.5Hz, 104-109Hz, 110-130Hz, 150-155Hz and 177-183Hz.In figure 7, we show the ASD for particular frequency bands, demonstrating that by applying the CDC pipeline, we can subtract noise with varying characteristics from broadband noise to the removal of single spectral lines or the combination of both.While, in general, we observe significantly less monitored low-frequency noise Toward autonomous denoising of gravitational-wave detector data 11 4 ×10−23 3 ×10−23 2 ×10−23 28.5 29 29.5 30 30.5 31 Frequency[Hz] ]2/1zH/niarts[DSA 8 ×10−24 7 ×10−24 6 ×10−24 5 ×10−24 4 ×10−24 110 112.5 115 117.5 120 122.5 125 127.5 130 Frequency[Hz] ]2/1zH/niarts[DSA 10−23 5 ×10−24 177 178 179 180 181 182 183 Frequency[Hz] ]2/1zH/niarts[DSA Figure 7: Amplitude spectral density (ASD) before (black) and after (red) denoising for dedicated frequency bands using data taken with the LIGO Hanford detector.The plots show the variety of noise that can be removed with the pipeline, including broadband noise (top left), spectral lines (top right), and a combination of both (bottom).The performance of the CDC pipeline in removingthisshorter-durationstationarynoiseusingdatatakenbytheLIGOLivingston interferometer on November 18, 2024 (GPS time 1415997186) and July 20, 2023 (GPS time 1373846418) is shown in figure 9 (left) and figure 9 (right), respectively.Summary and outlook We developed an automated coherence monitor to analyze ground-based gravitational- wave detector environmental and instrumental noise couplings.Given the outputs obtained with the coherence monitor, we select suitable witness channels for denoising Toward autonomous denoising of gravitational-wave detector data 12 12 10 8 6 4 2 0 152 154 156 158 160 BNSRange[Mpc] tnuoC Original(Median: 155.2Mpc) Cleaned(Median: 157.3Mpc) Figure 8: Binary Neutron Star (BNS) Range calculated on 60s long data segments taken with the LIGO Hanford detector on September 10, 2023 (GPS time 1378403243), before and after applying the CDC pipeline.10−23 5 ×10−24 82 82.5 83 83.5 84 84.5 Frequency[Hz] ]2/1zH/niarts[DSA 9 ×10−24 8 ×10−24 7 ×10−24 6 ×10−24 5 ×10−24 4 ×10−24 118 118.5 119 119.5 120 120.5 121 121.5 Frequency[Hz] ]2/1zH/niarts[DSA Figure 9: Amplitude spectral density (ASD) before (black) and after denoising (blue) for dedicated frequency bands.5281/zenodo.10966714 [32] Meyers P M 2018 Cross-correlation searches for persistent gravitational waves with Advanced LIGO and noise studies for current and future ground-based gravitational- wave detectors Ph.D. thesis Minnesota U.".You have three tasks, which are:\n    1.to summarize the text I provided into a Summary .Please answer within 150-300 characters.\n    2.to summarize the text I provided, using up to seven Highlight.\n    3.to summarize the text I provided, using up to seven Key Insights. Each insight should include a brief in-depth analysis. Key Insight should not include timestamps.\n    Your output should use the following template strictly, provide the results for the three tasks:\n    ## Summary\n    ## Highlights\n    - Highlights\n    ## Key Insights\n    - Key Insights .\n  Importantly your output must use language "English"
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