BEGIN:VCALENDAR VERSION:2.0 PRODID:researchseminars.org CALSCALE:GREGORIAN X-WR-CALNAME:researchseminars.org BEGIN:VEVENT SUMMARY:Leïla Haegel (University of Paris) DTSTART:20211115T160000Z DTEND:20211115T165000Z DTSTAMP:20260404T060945Z UID:CMO-21w5066/1 DESCRIPTION:Title: Probes of new physics during gravitational waves propagation - Leila Haegel\nby Leïla Haegel (University of Paris) as part of CMO-De tection and Analysis of Gravitational Waves in the era of Multi-Messenger Astronomy\n\n\nAbstract\nThe direct detection of gravitational waves opene d an unprecedented channel to probe fundamental physics. Proposed extensio ns of our current theories predict a dispersion of the gravitational waves during their propagation\, distorting the signals observed by ground-base d interferometers compared to their predictions from general relativity. In this talk\, I present several analysis probing different alternative th eories of gravitation. Using the multimessenger events consisting of gravi tational waves and their electromagnetic counterpart\, extra dimensions an d scalar-tensor theories are constrained from the comparison of the lumino sity distance inferred independently from both signals. Relying only on gr avitational wave signals\, a large class of proposed theories (e.g. massiv e gravity) predict a frequency-dependent dispersion of the gravitational w aves breaking local CPT and/or Lorentz symmetry. Constraints on the corres ponding effective field theories coefficients are obtained from the analys is of 31 events from the second LIGO-Virgo detections catalog.\n LOCATION:https://stable.researchseminars.org/talk/CMO-21w5066/1/ END:VEVENT BEGIN:VEVENT SUMMARY:Michael Coughlin (University of Minnesota) DTSTART:20211115T165000Z DTEND:20211115T174000Z DTSTAMP:20260404T060945Z UID:CMO-21w5066/2 DESCRIPTION:Title: Inference as a service for gravitational-wave astronomy\nby Michael Coughlin (University of Minnesota) as part of CMO-Detection and A nalysis of Gravitational Waves in the era of Multi-Messenger Astronomy\n\n \nAbstract\nWe present a novel paradigm for the deployment of computing in frastructure for the low-latency analyses of gravitational wave (GW) data. Here\, we specifically discuss two deep-learning algorithms\, 'DeepClean' and 'BBHNet'\, which are used for GW data denoising and compact binary so urce identification respectively. Using “replayed” streams of the GW d ata of LIGO Hanford and Livingston from their third observing run\, we dem onstrate the subtraction of stationary and non-stationary noise sources fo llowed by identification of candidates for the astrophysical transient det ections at low latency. Depending on the computing platform used\, we show that it is possible to achieve these at latencies of ~ a few hundreds of milliseconds to a few seconds. Real-time delivery of gravitational-wave al erts is important for enabling rapid multi-messenger follow-up\, especiall y to capture short-lived electromagnetic counterparts. Additionally\, our implementation offers seamless incorporation of hardware accelerators and enables the use of as-a-service computing\, which would be capable of meet ing the future needs of gravitational-wave data analysis.\n LOCATION:https://stable.researchseminars.org/talk/CMO-21w5066/2/ END:VEVENT BEGIN:VEVENT SUMMARY:Massimiliano Razzano (University of Pisa) DTSTART:20211115T181000Z DTEND:20211115T190000Z DTSTAMP:20260404T060945Z UID:CMO-21w5066/3 DESCRIPTION:Title: Deep learning methods to investigate noise features in gravitat ional wave detectors\nby Massimiliano Razzano (University of Pisa) as part of CMO-Detection and Analysis of Gravitational Waves in the era of Mu lti-Messenger Astronomy\n\n\nAbstract\nGravitational waves have opened a n ew window on the Universe and paved the way to multimessenger astronomy. A dvanced LIGO and Advanced Virgo interferometers are probing an increasingl y larger volume of space\, discovering more and more signals produced by t he coalescence of compact binary systems. Characterizing these detectors a nd their noise is crucial to optimize the sensitivity. In particular\, gli tches are transient noise events impacting the data quality\, and their de tection and classification is very important to improve the performance of the interferometers. Deep learning techniques are a promising approach to recognize and classify glitches and to study noise in general. We will pr esent how machine learning can help in investigating the time-frequency ev olution of glitches and thus contribute to the low-latency characterizatio n of gravitational wave detectors.\n LOCATION:https://stable.researchseminars.org/talk/CMO-21w5066/3/ END:VEVENT BEGIN:VEVENT SUMMARY:Adam Coogan (Université de Montréal and Mila) DTSTART:20211115T190000Z DTEND:20211115T195000Z DTSTAMP:20260404T060945Z UID:CMO-21w5066/4 DESCRIPTION:Title: Observing and characterizing the dark matter environments of bl ack hole binaries with gravitational waves\nby Adam Coogan (Universit é de Montréal and Mila) as part of CMO-Detection and Analysis of Gravita tional Waves in the era of Multi-Messenger Astronomy\n\n\nAbstract\nGravit ational wave measurements provide a new opportunity to determine whether d ark matter is truly a cold\, collisionless particle. Intermediate mass-rat io inspirals (IMRIs) embedded in dark matter halos are particularly promis ing targets. These IMRIs can compress their dark halos to extreme densitie s as they form\, leading to distinctive gravitational wave signals. In thi s talk I will show that future interferometers could observe and character ize these "dark dress" systems over large swaths of their parameter space. After explaining their waveform modeling\, I will map out which dark dres ses could be detected\, distinguished from astrophysical IMRIs and accurat ely measured.\n LOCATION:https://stable.researchseminars.org/talk/CMO-21w5066/4/ END:VEVENT BEGIN:VEVENT SUMMARY:Sydney Otten (Radboud University & University of Amsterdam) DTSTART:20211115T220000Z DTEND:20211115T224500Z DTSTAMP:20260404T060945Z UID:CMO-21w5066/5 DESCRIPTION:Title: (Conference Room San Felipe and Zoom)\nby Sydney Otten (Rad boud University & University of Amsterdam) as part of CMO-Detection and An alysis of Gravitational Waves in the era of Multi-Messenger Astronomy\n\nA bstract: TBA\n LOCATION:https://stable.researchseminars.org/talk/CMO-21w5066/5/ END:VEVENT BEGIN:VEVENT SUMMARY:Ryan Quitzow-James (Missouri University of Science and Technology) DTSTART:20211115T224500Z DTEND:20211115T233000Z DTSTAMP:20260404T060945Z UID:CMO-21w5066/6 DESCRIPTION:Title: Estimating glitch contaminated gravitational-wave signals using artificial neural networks with NNETFIX\nby Ryan Quitzow-James (Misso uri University of Science and Technology) as part of CMO-Detection and Ana lysis of Gravitational Waves in the era of Multi-Messenger Astronomy\n\n\n Abstract\nInstrumental and environmental transient noise bursts in gravita tional-wave detectors\, or glitches\, may impair astrophysical observation s by adversely affecting the sky localization and the parameter estimation of gravitational-wave signals. Denoising of detector data is especially r elevant during low-latency operations because electromagnetic follow-up of candidate detections requires accurate\, rapid sky localization and infer ence of astrophysical sources. NNETFIX is a machine learning-based algorit hm designed to remove glitches detected in coincidence with transient grav itational-wave signals. NNETFIX uses artificial neural networks to estimat e the portion of the data lost due to the presence of the glitch\, which a llows the recalculation of the sky localization of the astrophysical signa l. The sky localization of the denoised signal may be significantly more a ccurate than the sky localization obtained from the original data or by ex cising the portion of the data impacted by the glitch. We test NNETFIX in simulated scenarios of binary black hole coalescence signals and discuss t he potential for its use in future low-latency LIGO-Virgo-KAGRA searches.\ n LOCATION:https://stable.researchseminars.org/talk/CMO-21w5066/6/ END:VEVENT BEGIN:VEVENT SUMMARY:Gianfranco Bertone (University of Amsterdam) DTSTART:20211116T160000Z DTEND:20211116T165000Z DTSTAMP:20260404T060945Z UID:CMO-21w5066/7 DESCRIPTION:Title: Dark matter\, black holes\, and gravitational waves\nby Gia nfranco Bertone (University of Amsterdam) as part of CMO-Detection and Ana lysis of Gravitational Waves in the era of Multi-Messenger Astronomy\n\n\n Abstract\nThe interplay between dark matter and black holes remains largel y unexplored. Dark matter can in principle be *made of* black holes\, as l ong as these are primordial\, i.e. they are formed in the very early unive rse. Dark matter can also accumulate *around* black holes\, be them astrop hysical or primordial\, and modify the rich phenomenology exhibited by th ese objects. After a brief overview of the status of dark matter searches\ , I will discuss the prospects for detecting primordial black holes\, or robustly ruling them out as dark matter candidates. I will then discuss t he prospects for characterizing and identifying dark matter using gravitat ional waves\, covering a wide range of dark matter candidate types and sig nals.\n LOCATION:https://stable.researchseminars.org/talk/CMO-21w5066/7/ END:VEVENT BEGIN:VEVENT SUMMARY:Gabriele Vajente (California Institute of Technology) DTSTART:20211116T165000Z DTEND:20211116T174000Z DTSTAMP:20260404T060945Z UID:CMO-21w5066/8 DESCRIPTION:Title: Machine Learning and Gravitational Wave Detectors\nby Gabri ele Vajente (California Institute of Technology) as part of CMO-Detection and Analysis of Gravitational Waves in the era of Multi-Messenger Astronom y\n\n\nAbstract\nThe use of machine learning techniques in the analysis of the data produced by gravitational wave detectors is a very active field of research\, with many promising results. In this talk however\, I will d iscuss how machine learning could also be applied to the instrument scienc e side of gravitational wave detectors\, to improve the sensitivity with n oise subtraction or to improve the detector robustness with advanced contr ol systems. This is a less mature field of research\, and results are only recently starting to appear.\n LOCATION:https://stable.researchseminars.org/talk/CMO-21w5066/8/ END:VEVENT BEGIN:VEVENT SUMMARY:Pablo Cerdá-Durán (niversidad de Valencia) DTSTART:20211116T181000Z DTEND:20211116T190000Z DTSTAMP:20260404T060945Z UID:CMO-21w5066/9 DESCRIPTION:Title: (Conference Room San Felipe and Zoom)\nby Pablo Cerdá-Dur án (niversidad de Valencia) as part of CMO-Detection and Analysis of Grav itational Waves in the era of Multi-Messenger Astronomy\n\nAbstract: TBA\n LOCATION:https://stable.researchseminars.org/talk/CMO-21w5066/9/ END:VEVENT BEGIN:VEVENT SUMMARY:Pablo Laguna (University of Texas at Austin) DTSTART:20211116T190000Z DTEND:20211116T195000Z DTSTAMP:20260404T060945Z UID:CMO-21w5066/10 DESCRIPTION:Title: Black Hole - Neutron Star Binary Mergers: The Imprint of Tidal Debris\nby Pablo Laguna (University of Texas at Austin) as part of CM O-Detection and Analysis of Gravitational Waves in the era of Multi-Messen ger Astronomy\n\n\nAbstract\nDistinguishing black hole – neutron star bi naries from binary black holes mergers for high mass ratios could be chall enging because the neutron star coalesces with the black hole without expe riencing significant disruption. To investigate the transition of the beha vior of a mixed binary merger into one like a black hole binary\, we prese nt results from a series of merger simulations for different mass ratios. We show how the degree of disruption of the neutron star impacts the inspi ral and merger dynamics\, the properties of the final black hole\, the acc retion disk formed from the circularization of the tidal debris\, the grav itational waves\, and the strain spectrum and mismatches. The simulations use initial data constructed with a method that generalizes the Bowen-York initial data for black hole punctures to the case of neutron stars.\n LOCATION:https://stable.researchseminars.org/talk/CMO-21w5066/10/ END:VEVENT BEGIN:VEVENT SUMMARY:Vasileios Skliris (Cardiff University)) DTSTART:20211116T220000Z DTEND:20211116T224500Z DTSTAMP:20260404T060945Z UID:CMO-21w5066/11 DESCRIPTION:Title: Real-Time Detection of Unmodeled Gravitational-Wave Transients Using Convolutional Neural Networks\nby Vasileios Skliris (Cardiff Un iversity)) as part of CMO-Detection and Analysis of Gravitational Waves in the era of Multi-Messenger Astronomy\n\n\nAbstract\nConvolutional Neural Networks (CNNs) have demonstrated potential for the real-time analysis of data from gravitational-wave detector networks for the specific case of si gnals from coalescing compact-object binaries such as black-hole binaries. Unfortunately\, training these CNNs requires a precise model of the targe t signal\; they are therefore not applicable to a wide class of potential gravitational-wave sources\, such as core-collapse supernovae and long gam ma-ray bursts\, where unknown physics or computational limitations prevent the development of comprehensive signal models. We demonstrate for the fi rst time a CNN with the ability to detect generic signals -- those without a precise model -- with sensitivity across a wide parameter space. Our CN N has a novel structure that uses not only the network strain data but als o the Pearson cross-correlation between detectors to distinguish correlate d gravitational-wave signals from uncorrelated noise transients. We demons trate the efficacy of our CNN using data from the second LIGO-Virgo observ ing run. We show that it has sensitivity approaching that of the "gold-sta ndard'' unmodeled transient searches currently used by LIGO-Virgo\, at ext remely low (order of 1 second) latency and using only a fraction of the co mputing power required by existing searches\, allowing our models the poss ibility of true real-time detection of gravitational-wave transients assoc iated with gamma-ray bursts\, core-collapse supernovae\, and other relativ istic astrophysical phenomena.\n LOCATION:https://stable.researchseminars.org/talk/CMO-21w5066/11/ END:VEVENT BEGIN:VEVENT SUMMARY:Jade Powell (Swinburne University of Technology) DTSTART:20211116T224500Z DTEND:20211116T233000Z DTSTAMP:20260404T060945Z UID:CMO-21w5066/12 DESCRIPTION:Title: The final core-collapse of pulsational pair instability supern ovae\nby Jade Powell (Swinburne University of Technology) as part of C MO-Detection and Analysis of Gravitational Waves in the era of Multi-Messe nger Astronomy\n\n\nAbstract\nIn this talk I will present 3D core-collapse supernova simulations of massive pop III progenitor stars at the transiti on to the pulsational pair instability regime. We simulate two progenitor models with initial masses of 85 and 100 solar masses with multiple equati ons of state. The 85 solar mass progenitor experiences a pair instability pulse coincident with core collapse\, whereas the 100 solar mass progenito r has already gone through a sequence of four pulses 1\,500 years before c ollapse in which it ejected its hydrogen and helium envelope. The 85 solar mass models experience shock revival and then delayed collapse to a black hole due to ongoing accretion. We show the models have strong gravitation al wave emission in the frequency band of current gravitational wave detec tors. We demonstrate how our understanding of the gravitational wave emiss ion can aid in the detection of core-collapse supernovae and understanding the parameters of the astrophysical source.\n LOCATION:https://stable.researchseminars.org/talk/CMO-21w5066/12/ END:VEVENT BEGIN:VEVENT SUMMARY:Bernhard Mueller (Monash University) DTSTART:20211117T160000Z DTEND:20211117T165000Z DTSTAMP:20260404T060945Z UID:CMO-21w5066/13 DESCRIPTION:Title: Magnetic Fields in Core-Collapse Supernovae and their Progenit ors\nby Bernhard Mueller (Monash University) as part of CMO-Detection and Analysis of Gravitational Waves in the era of Multi-Messenger Astronom y\n\n\nAbstract\nMulti-dimensional simulations of core-collapse supernovae are essential for providing waveforms that can assist the detection and i nterpretation of gravitational waves from a prospective nearby explosion. An emerging theme in core-collapse supernova modelling is the wider import ance of magnetic fields. While magnetorotational explosions have long been investigated as a scenario for rare hypernova explosions\, recent simulat ions suggest that magnetic fields may play an important role in normal exp losions as well. To better understand the role of magnetic fields both in normal and hyperenergetic explosions\, it is also imperative to revisit th e interplay of convection\, magnetic fields and rotation during the pre-su pernova evolution of massive stars. I will discuss progress on 3D magnetoh ydrodynamic simulations of supernovae and their progenitors\, possible imp lications for hypernovae and magnetar formation\, and point to open issues in the current models\n LOCATION:https://stable.researchseminars.org/talk/CMO-21w5066/13/ END:VEVENT BEGIN:VEVENT SUMMARY:Elena Cuoco (European Gravitational Observatory) DTSTART:20211117T165000Z DTEND:20211117T174000Z DTSTAMP:20260404T060945Z UID:CMO-21w5066/14 DESCRIPTION:Title: Multimodal Analysis of Gravitational Wave Signals and Gamma-Ra y Bursts from Binary Neutron Star Mergers\nby Elena Cuoco (European Gr avitational Observatory) as part of CMO-Detection and Analysis of Gravitat ional Waves in the era of Multi-Messenger Astronomy\n\n\nAbstract\nA major boost in the understanding of the universe was given by the revelation of the first coalescence event of two neutron stars (GW170817) and the obse rvation of the same event across the entire electromagnetic spectrum. With third-generation gravitational wave detectors and the new astronomical f acilities\, we expect many multi-messenger events of the same type. We an ticipate the need to analyse the data provided to us by such events not on ly to fulfill the requirements of real-time analysis\, but also in order t o decipher the event in its entirety through the information emitted in th e different messengers using machine learning. What we propose is the appl ication of a multimodal machine learning approach to characterize these ev ents.\n LOCATION:https://stable.researchseminars.org/talk/CMO-21w5066/14/ END:VEVENT BEGIN:VEVENT SUMMARY:Jess McIver (University of British Columbia) DTSTART:20211117T181000Z DTEND:20211117T190000Z DTSTAMP:20260404T060945Z UID:CMO-21w5066/15 DESCRIPTION:Title: New methods for gravitational-wave data analysis\nby Jess McIver (University of British Columbia) as part of CMO-Detection and Analy sis of Gravitational Waves in the era of Multi-Messenger Astronomy\n\n\nAb stract\nThe global network of ground-based gravitational wave (GW) detecto rs is expected to expand and increase in sensitivity by the middle of this decade. Effective characterization and calibration of near-future detecto rs will allow us to explore new physics and astrophysics\, including the o rigin of detected GW sources and probes of cosmology. I will give an overv iew of recent efforts at UBC to develop new approaches to characterize the performance of current and near-future detectors\, including novel metric s for detector performance and characterization\, new methods for distingu ishing between true GW signals and detector noise\, and improved technique s for GW signal reconstruction.\n LOCATION:https://stable.researchseminars.org/talk/CMO-21w5066/15/ END:VEVENT BEGIN:VEVENT SUMMARY:Deirdre Shoemaker (University of Texas at Austin) DTSTART:20211117T190000Z DTEND:20211117T195000Z DTSTAMP:20260404T060945Z UID:CMO-21w5066/16 DESCRIPTION:Title: Brave new world of numerical relativity\nby Deirdre Shoema ker (University of Texas at Austin) as part of CMO-Detection and Analysis of Gravitational Waves in the era of Multi-Messenger Astronomy\n\n\nAbstra ct\nAfter decades of preparation\, the era of gravitational wave astronomy has begun. The gravitational wave detectors\, LIGO and Virgo\, have publi shed a catalog of 50 events of coalescing compact objects including black holes and neutron stars. I will present the role that numerical relativity played in the unveiling of the gravitational wave sky and anticipate how it might improve our understanding of gravity as the detectors improve..\n LOCATION:https://stable.researchseminars.org/talk/CMO-21w5066/16/ END:VEVENT BEGIN:VEVENT SUMMARY:Ik Siong Heng (University of Glasgow) DTSTART:20211118T160000Z DTEND:20211118T165000Z DTSTAMP:20260404T060945Z UID:CMO-21w5066/17 DESCRIPTION:Title: Astrophysics with joint analysis of multi-messenger observatio ns\nby Ik Siong Heng (University of Glasgow) as part of CMO-Detection and Analysis of Gravitational Waves in the era of Multi-Messenger Astronom y\n\n\nAbstract\nMulti-messenger observations of compact binary coalescenc es will enrich our understanding of the astrophysics behind such sources\, especially binary neutron star mergers. The joint analysis of gravitation al wave data in conjunction with electromagnetic observations is a crucial ingredient for multi-messenger astrophysics. This talk will present an ov erview of multi-messenger astrophysics research at the University of Glasg ow\, including the analysis of kilonova light curves for joint observation s and a hierarchical Bayesian analysis\, with a machine learning augmented sampler (Nessai)\, for combining gravitational wave and gamma-ray observa tions to identify plausible models for gamma-ray burst jet structures.\n LOCATION:https://stable.researchseminars.org/talk/CMO-21w5066/17/ END:VEVENT BEGIN:VEVENT SUMMARY:Deep Chatterjee (U. Illinois Urbana-Champaign) DTSTART:20211118T165000Z DTEND:20211118T174000Z DTSTAMP:20260404T060945Z UID:CMO-21w5066/18 DESCRIPTION:Title: Application of machine learning in low-latency counterpart inf erence from gravitational waves\nby Deep Chatterjee (U. Illinois Urban a-Champaign) as part of CMO-Detection and Analysis of Gravitational Waves in the era of Multi-Messenger Astronomy\n\n\nAbstract\nThe panchromatic ob servations of the electromagnetic (EM) counterpart of the binary neutron s tar (BNS) merger\, GW170817\, marked the dawn of multi-messenger EMGW astr onomy. But it remains the only success story\, even after the LIGO/Virgo t hird observing run\, which reported 56 GW discoveries publicly. This shows that while we may have reached an era of routine GW astronomy\, the same for EMGW astronomy still awaits us. The first step is to develop low-laten cy data-products that aid the follow-up of interesting GW candidates. The low-latency nature of the problem\, taking into account physically motivat ed models plus un-modeled or poorly understood sources of search biases ma kes the use of data-driven approaches and machine learning particularly su ited for this problem. I will talk about such efforts using machine learni ng approaches both from the GW and EM standpoint for near real-time infere nce of EMGW counterparts.\n LOCATION:https://stable.researchseminars.org/talk/CMO-21w5066/18/ END:VEVENT BEGIN:VEVENT SUMMARY:Greg Ashton (Royal Holloway\, University of London) DTSTART:20211118T180000Z DTEND:20211118T190000Z DTSTAMP:20260404T060945Z UID:CMO-21w5066/19 DESCRIPTION:Title: (Conference Room San Felipe and Zoom)\nby Greg Ashton (Roy al Holloway\, University of London) as part of CMO-Detection and Analysis of Gravitational Waves in the era of Multi-Messenger Astronomy\n\nAbstract : TBA\n LOCATION:https://stable.researchseminars.org/talk/CMO-21w5066/19/ END:VEVENT BEGIN:VEVENT SUMMARY:Javier M. Antelis (Embry-Riddle Aeronautical University) DTSTART:20211118T190000Z DTEND:20211118T195000Z DTSTAMP:20260404T060945Z UID:CMO-21w5066/20 DESCRIPTION:Title: Reduction of noise events in searches of gravitational wave bu rsts from core-collapse supernovae with machine learning\nby Javier M. Antelis (Embry-Riddle Aeronautical University) as part of CMO-Detection a nd Analysis of Gravitational Waves in the era of Multi-Messenger Astronomy \n\n\nAbstract\nThe search of gravitational waves (GW) from core-collapse supernovae (CCSNe) relies on detection algorithms such as coherent WaveBur st (cWB). False alarm rates and statistical significance might be affected by blip and glitch noises embedded in the strain data\, which survive rej ection tests. It is of interest then to detect and discard surviving noise events. This work presents the use of supervised machine learning (ML) me thods\, in specific\, Linear Discriminant Analysis and Support Vector Mach ines\, to recognize between noise and signal events using a set of reconst ruction parameters from cWB. We tested this ML follow-up method using stra in data from the O3a run of advanced LIGO\, and CCSNe GW signals extracted from 3D simulations. The ML model is learned using a dataset of noise and signal events extracted from a given on-source window\, and then it is us ed to identify and discard noise events in cWB analyses in different on-so urce windows. Noise and signal reduction levels were assessed in single de tector networks (L1 and H1) and two detector networks (L1H1). The results showed an effective enhancement of the statistical significance of cWB-bas ed searches of GWs from CCSNe.\n LOCATION:https://stable.researchseminars.org/talk/CMO-21w5066/20/ END:VEVENT BEGIN:VEVENT SUMMARY:Christopher Messenger (Glasgow University) DTSTART:20211118T220000Z DTEND:20211118T224500Z DTSTAMP:20260404T060945Z UID:CMO-21w5066/21 DESCRIPTION:Title: (Conference Room San Felipe and Zoom)\nby Christopher Mess enger (Glasgow University) as part of CMO-Detection and Analysis of Gravit ational Waves in the era of Multi-Messenger Astronomy\n\nAbstract: TBA\n LOCATION:https://stable.researchseminars.org/talk/CMO-21w5066/21/ END:VEVENT BEGIN:VEVENT SUMMARY:Kendall Ackley (University of Warwick) DTSTART:20211118T224500Z DTEND:20211118T233000Z DTSTAMP:20260404T060945Z UID:CMO-21w5066/22 DESCRIPTION:Title: (Conference Room San Felipe and Zoom)\nby Kendall Ackley ( University of Warwick) as part of CMO-Detection and Analysis of Gravitatio nal Waves in the era of Multi-Messenger Astronomy\n\nAbstract: TBA\n LOCATION:https://stable.researchseminars.org/talk/CMO-21w5066/22/ END:VEVENT END:VCALENDAR