Searching for gravitational-wave transients with Advanced detectors Ik Siong Heng on behalf of the LIGO Scientific Collaboration and Virgo NRmGW workshop, Valencia, December 2016 G1602350

Generic transient (burst) analysis Searches for gravitational-wave bursts do not require knowledge about the phase evolution (waveform) of the expected signal Burst searches aim to cover a broad parameter space which can overlap with well-modelled signals (eg. binary black holes) potential for discovering new sources of gravitational waves Steps of a typical generic burst search: weight data by the noise at each frequency (whitening) make time-frequency representation of the data identify correlated excess power in multiple detectors estimate false alarm rate of observations Some burst searches target GWs expected from particular sources or are informed by non-GW observations of astrophysical phenomena NRmGW workshop, Valencia, December 2016 2 G1602350

Burst science All-sky search for ‘unmodelled’ transients search for transients with long (~10-500s) and short durations short transient searches run in low-latency (GW150914) Search for intermediate-mass binary black holes Search for GWs from cosmic strings kinks and cusps Transient search associated with GRBs high-energy neutrinos neutron star transients (eg. SGR flares) nearby optical supernovae Fast Radio Bursts Search counterpart EM transients (follow-ups) NRmGW workshop, Valencia, December 2016 3 G1602350

Online all-sky burst searches coherent WaveBurst (cWB) Multi-resolution time-frequency map of data is obtained through wavelet decomposition Triggers are analyzed coherently to estimate signal waveform, polarization, source location, using a constrained likelihood method (maximised over sky position) Omicron+LIB (oLIB) Data is decomposed using sine-gaussian templates to form time-frequency map; triggers within 100 ms with same central frequency and quality factor are clustered Coincident triggers analyzed using Bayesian parameter estimation and model selection algorithm (with single sine Gaussian template) cWB+BayesWave Bayesian model selection using a liner combination of sine Gaussian templates (optimized using a reversible jump Markov chain Monte Carlo). Posterior distributions for estimation parameters and waveform reconstruction NRmGW workshop, Valencia, December 2016 4

Online all-sky burst searches Gravitational wave data cWB Omicron cWB and oLIB generate skymaps within minutes-hours of event detection NRmGW workshop, Valencia, December 2016 BayesWave LIB LIB GraceDB (event parameters/skymaps/annotations) data quality 5 G1602350

O1 all-sky search Search for generic gravitational wave transients using all data from O1 No non-BBH signals were observed Able to detect gravitational wave energy of just over 10-9M☉c2 at 10 kpc around 100 Hz ~1045 ergs @ 10 kpc or ~1051 ergs @ 10 Mpc NRmGW workshop, Valencia, December 2016 6 https://arxiv.org/abs/1611.02972 G1602350

O1 long-duration burst searches Search O1 data for transients lasting between 10 and 500 seconds in duration, from 24 to 2048 Hz Possible sources hydrodynamic instabilities during supernovae accretion disk instabilities (ADI) in black holes formed from collapsars (long GRBs) magnetars deformation following GRB Use three search algorithms STAMP-AS, which was previously used on S5/S6 data S5/S6 results: Phys. Rev. D 93, 042005 (2016) cWB and X-SphRad also used for O1 data Estimate search sensitivity improvement over S5/S6 to be about factor of 3 NRmGW workshop, Valencia, December 2016 7 G1602350

NRmGW workshop, Valencia, December 2016

NRmGW workshop, Valencia, December 2016

NRmGW workshop, Valencia, December 2016

Triggered searches High-energy neutrinos Gamma-ray bursts correlates cWB trigger times and sky location with IceCube and Antares events Gamma-ray bursts Search for modelled signals (short & ambiguous GRBs) and unmodelled search (all GRBs) Also search for short and long GWs associated with magnetar flares Fast Radio Bursts search previously performed on FRBs detected by Green Bank Telescope and Parkes between 2007 and 2013 (arXiv:1605.01707) Supernovae (see talk by M. Szczepanczyk) search for GWs from nearby supernovae performed on SN2007gr and SN2011dh (arXiv:1605.01785) also have searches triggered by SNEWS alerts ANTARES+IceCube+LIGO+Virgo PRD 2016 (arXiv:1602.05411) NRmGW workshop, Valencia, December 2016 11 G1602350

NRmGW workshop, Valencia, December 2016

NRmGW workshop, Valencia, December 2016

NRmGW workshop, Valencia, December 2016

Waveform reconstruction NRmGW workshop, Valencia, December 2016 The detected signal is fitted by a set of sine-gaussian waveforms BayesWave uses a stochastic sampler (RJMCMC) to find likely waveforms that fit the data, leaving only gaussian noise as residual cWB reconstructs the waveform by adding up the power of all detected time-frequency pixels 15 Phys. Rev. D 93, 122004 (2016) arxiv.org:1602.03843

Waveform reconstruction NRmGW workshop, Valencia, December 2016 Numerical relativity – waveform obtained from numerical relativity simulations of binary black hole coalescence using estimated signal parameters Reconstructed (wavelet) – 90% credible region for waveforms reconstructed by combination of wavelet templates Reconstructed (template) – 90% credible region for best fitting templates assuming binary black hole coalescence 16 G1602350 LIGO-Virgo Collaboration, PRL 116, 061102 (2016)

Estimating astrophysical properties Generic properties of the observed signal can be mapped to physical attributes of the observed system, assuming specific models (eg. GW150914) NRmGW workshop, Valencia, December 2016 17 Phys. Rev. D 93, 122004 (2016) arxiv.org:1602.03843 G1602350

NRmGW workshop, Valencia, December 2016

NRmGW workshop, Valencia, December 2016

NRmGW workshop, Valencia, December 2016

NRmGW workshop, Valencia, December 2016

NRmGW workshop, Valencia, December 2016

NRmGW workshop, Valencia, December 2016

Points for discussion Are there broad signal features we should be targeting? for searches? for astrophysical interpretation? If a detection is made now, how should we use the current sets of simulations (waveform catalogues) to interpret our observation? eg. use approximants to NR matter waveforms How can we better integrate information from NR matter simulations into Burst analyses in the mid to longer term future? in terms of designing/updating Burst analyses in terms of generating new waveforms/catalogues Attention: CCSN simulation and data analysis workshop with the LVC on 17th and 18th March in Pasadena NRmGW workshop, Valencia, December 2016

Back up slides NRmGW workshop, Valencia, December 2016 25

HEN trigger times NRmGW workshop, Valencia, December 2016 26