MNFT : Robust detection of slow nonstationarity in LIGO Science data Soma Mukherjee Max Planck Institut fuer Gravitationsphysik Germany. LSC Meeting, Livingston,

Slides:

Advertisements

Similar presentations

A walk through some statistic details of LSC results.

Advertisements

Median Based Line Tracker Soumya D. Mohanty Max Planck Insitut für Gravitationsphysik LIGO-G Z.

LIGO-G Z LSC March 2004 KYF1 Veto efficiency study of triple coincidence playground WaveBurst events using WaveMon and glitchMon S2 veto triggers.

LIGO Reduced Data Sets E7 standard reduced data set RDS generation for future runs decimation examples LIGO-G Z Isabel Leonor (w/ Robert Schofield)

R. Stone for the LSC Center for Gravitational Wave Astronomy Department of Physics and Astronomy University of Texas at Brownsville. GWDAW, Boston, MA,

Noise Floor Non-stationarity Monitor Roberto Grosso*, Soma Mukherjee + + University of Texas at Brownsville * University of Nuernburg, Germany Detector.

LIGO-G Z External Triggers Circulation only within LIGO I authorship list Status of the Triggered Burst Search (highlights from LIGO DCC# T Z,

Searching for pulsars using the Hough transform Badri Krishnan AEI, Golm (for the pulsar group) LSC meeting, Hanford November 2003 LIGO-G Z.

LIGO-G Z Coherent Coincident Analysis of LIGO Burst Candidates Laura Cadonati Massachusetts Institute of Technology LIGO Scientific Collaboration.

Detector Characterization in GEO 600 by Alicia M. Sintes-Olives on behalf of the GEO-DC team Universitat de les Illes Balears

Soma Mukherjee, GWDAW7, Kyoto, Japan, 19/12/02, LIGO-G Z1 Robust Detection of Noise Floor Drifts in Interferometric Data Soma Mukherjee Max Planck.

The “probability event horizon” and probing the astrophysical GW background School of Physics University of Western Australia Research is funded by the.

LIGO-G Z Detector characterization for LIGO burst searches Shourov K. Chatterji for the LIGO Scientific Collaboration 10 th Gravitational Wave.

21 Feb 2002Soumya D. Mohanty, AEI1 DCR Plan of presentation Soumya Mohanty: Overview, aims & work done R. Balasubramanian: Details of Hardware, Database.

Soma Mukherjee GWDAW8, Milwaukee, Dec '03 Interferometric Data Modeling: Issues in realistic data generation. Soma Mukherjee CGWA University of Texas.

New data analysis for AURIGA Lucio Baggio Italy, INFN and University of Trento AURIGA.

Data Characterization in Gravitational Waves Soma Mukherjee Max Planck Institut fuer Gravitationsphysik Golm, Germany. Talk at University of Texas, Brownsville.

June 1, 2001GEO DC Workshop Detector Characterization Robot (Progress Since January 2001) Design (Already exists) Algorithmic and Statistical studies (In.

The Role of Data Quality in S5 Burst Analyses Lindy Blackburn 1 for the LIGO Scientific Collaboration 1 Massachusetts Institute of Technology, Cambridge,

LIGO-G Z Peter Shawhan, for the LIGO Scientific Collaboration APS Meeting April 25, 2006 Search for Gravitational Wave Bursts in Data from the.

LIGO-G Z The AURIGA-LIGO Joint Burst Search L. Cadonati, G. Prodi, L. Baggio, S. Heng, W. Johnson, A. Mion, S. Poggi, A. Ortolan, F. Salemi, P.

Applications of change point detection in Gravitational Wave Data Analysis Soumya D. Mohanty AEI.

Analysis of nonstationarity in LIGO S5 data using the NoiseFloorMon output A proposal for a seismic Data Quality flag. R. Stone for the LSC The Center.

Comparison of Line Removal Techniques Bernard F. Whiting University of Florida (LSC 7, Hanford, Aug. 2000)

Multidimensional classification of burst triggers from the fifth science run of LIGO Soma Mukherjee CGWA, UTB GWDAW11, Potsdam, 12/18/06 LIGO-G

Abstract: We completed the tuning of the analysis procedures of the AURIGA-LIGO joint burst search and we are in the process of verifying our results.

S.Klimenko, August 2005, LSC, G Z Constraint likelihood analysis with a network of GW detectors S.Klimenko University of Florida, in collaboration.

18/01/01GEO data analysis meeting, Golm Issues in GW bursts Detection Soumya D. Mohanty AEI Outline of the talk Transient Tests (Transient=Burst) Establishing.

Veto Selection for Gravitational Wave Event Searches Erik Katsavounidis 1 and Peter Shawhan 2 1 Massachusetts Institute of Technology, Cambridge, MA 02139,

GWDAW-8 December 18, 2003LIGO Scientific Collaboration, UW - Milwaukee 1LIGO-G Z Broad-band CW searches (for isolated pulsars) in LIGO and GEO.

Dec 16, 2005GWDAW-10, Brownsville Population Study of Gamma Ray Bursts S. D. Mohanty The University of Texas at Brownsville.

G030XXX-00-Z Excess power trigger generator Patrick Brady and Saikat Ray-Majumder University of Wisconsin-Milwaukee LIGO Scientific Collaboration.

Multidimensional classification of burst triggers from LIGO S5 run Soma Mukherjee for the LSC Center for Gravitational Wave Astronomy University of Texas.

A Waveform Consistency Test for Binary Inspirals using LIGO data LSC Inspiral Analysis Working Group LIGO-G Z LSC Meeting Andres C. Rodriguez.

21 Feb 2002Soumya D. Mohanty, AEI1 Detector/Data Characterization Robot Towards Data Mining Soumya D. Mohanty Max Planck Institut für Gravitationsphysik.

Searching for Gravitational Waves from Binary Inspirals with LIGO Duncan Brown University of Wisconsin-Milwaukee for the LIGO Scientific Collaboration.

LIGO-G Z Status of MNFTmon Soma Mukherjee +, Roberto Grosso* + University of Texas at Brownsville * University of Nuernberg, Germany LSC Detector.

1 Status of Search for Compact Binary Coalescences During LIGO’s Fifth Science Run Drew Keppel 1 for the LIGO Scientific Collaboration 1 California Institute.

GEO++ Online Detector Characterization System. LIGO-G Z GEO++ working group GEO++ working group Cardiff University: Birmingham University Cardiff.

LIGO-G Z The Q Pipeline search for gravitational-wave bursts with LIGO Shourov K. Chatterji for the LIGO Scientific Collaboration APS Meeting.

T.Akutsu, M.Ando, N.Kanda, D.Tatsumi, S.Telada, S.Miyoki, M.Ohashi and TAMA collaboration GWDAW10 UTB Texas 2005 Dec. 13.

S.Klimenko, G Z, December 2006, GWDAW11 Coherent detection and reconstruction of burst events in S5 data S.Klimenko, University of Florida for.

LIGO-G Z Confidence Test for Waveform Consistency of LIGO Burst Candidate Events Laura Cadonati LIGO Laboratory Massachusetts Institute of Technology.

Data Analysis Algorithm for GRB triggered Burst Search Soumya D. Mohanty Center for Gravitational Wave Astronomy University of Texas at Brownsville On.

Multidimensional classification analysis of kleine Welle triggers in LIGO S5 run Soma Mukherjee for the LSC University of Texas at Brownsville GWDAW12,

LIGO- G Z AJW, Caltech, LIGO Project1 A Coherence Function Statistic to Identify Coincident Bursts Surjeet Rajendran, Caltech SURF Alan Weinstein,

LSC meeting – Mar05 Livingston, LA A. Di Credico Syracuse University Glitch investigations with kleineWelle Reporting on work done by several people: L.

Validation of realistically simulated non-stationary data. Soma Mukherjee Centre for Gravitational Wave Astronomy University of Texas at Brownsville. GWDAW9,

Soma Mukherjee GWDAW8, Milwaukee, December'03 Interferometric Data Modeling: Issues in realistic data generation. Soma Mukherjee CGWA Dept. of Physics.

Soma Mukherjee LSC, Hanford, Aug.19 '04 Generation of realistic data segments: production and application. Soma Mukherjee Centre for Gravitational Wave.

Igor Yakushin, December 2004, GWDAW-9 LIGO-G Z Status of the untriggered burst search in S3 LIGO data Igor Yakushin (LIGO Livingston Observatory)

2 June 2003Soumya D. Mohanty et al, LIGO-G D1 LASER INTERFEROMETER GRAVITATIONAL WAVE OBSERVATORY - LIGO – CALIFORNIA INSTITUTE OF TECHNOLOGY.

LIGO- G Z Update on standalone power burst- detection code Patrick Brady University of Wisconsin-Milwaukee.

SEARCH FOR INSPIRALING BINARIES S. V. Dhurandhar IUCAA Pune, India.

LIGO-G Z The Q Pipeline search for gravitational-wave bursts with LIGO Shourov K. Chatterji for the LIGO Scientific Collaboration APS Meeting.

LIGO-G05????-00-Z Detector characterization for LIGO burst searches Shourov K. Chatterji For the LIGO Scientific Collaboration 10 th Gravitational Wave.

Searching for pulsars using the Hough transform

Advanced Virgo Detector Monitoring and Data Quality

The Q Pipeline search for gravitational-wave bursts with LIGO

Soma Mukherjee Centre for Gravitational Wave Astronomy

LIGO Scientific Collaboration meeting

Soma Mukherjee for LIGO Science Collaboration

Broad-band CW searches in LIGO and GEO S2 and S3 data

Broad-band CW searches in LIGO and GEO S2 and S3 data

LIGO Scientific Collaboration, UW - Milwaukee

Broad-band CW searches in LIGO and GEO S2 and S3 data

Excess power trigger generator

Searching for GRB-GWB coincidence during LIGO science runs

Coherent Coincident Analysis of LIGO Burst Candidates

Presentation transcript:

MNFT : Robust detection of slow nonstationarity in LIGO Science data Soma Mukherjee Max Planck Institut fuer Gravitationsphysik Germany. LSC Meeting, Livingston, LA, March 17-20, 2003 LIGO-G Z

Soma Mukherjee, 20/3/03 Why :  Interferometric data has three components : Lines, transients, noise floor.  Study of a change in any one of these without elimination of the other two will cause interference.  Lines dominate.  Presence of transients change the central tendency.  “SLOW” nonstationarity of noise floor interesting in the analysis of several astrophysical searches, e.g. Externally triggered search.  To be able to simulate the non-stationarity to test the efficiencies of various algorithms.

Method : Soma Mukherjee, 20/3/03 Method :  MNFT : 1.Bandpass and resample given timeseries x(k). 2.Construct FIR filter than whitens the noise floor. Resulting timeseries : w(k) 3.Remove lines using notch filter. Cleaned timeseries : c(k) 4.Track variation in second moment of c(k) using Running Median*. 5.Obtain significance levels of the sampling distribution via Monte Carlo simulations. * Mohanty S.D., 2002, CQG

Soma Mukherjee, GWDAW7, Kyoto, Japan, 19/12/02 4 Sequence : Soma Mukherjee 20/3/03 Sequence : Low pass and resample Estimate spectral noise floor using Running Median Design FIR Whitening filter. Whiten data. Clean lines. Highpass. Compute Running Median of the squared timeseries. Thresholds set by Simulation.

Data : Soma Mukherjee, 20/3/03 Data : Locked segments from :  LIGO S1 : L1 and H2  LIGO S2 : L1 and H1

Soma Mukherjee, 20/3/03

Soma Mukherjee 20/3/03

With transients added

Soma Mukherjee 20/3/03

Computation of : G(m)=V(Z t+m – Z t )/V(Z t+1 – Z t ) Z t : t th sample of a timeseries. m: Lag.

Soma Mukherjee 20/3/03

Comments : Soma Mukherjee 20/3/03 Comments :  LIGO Tech doc : LIGO-T Z.  Threshold setting by single simulation.  Discussions underway for incorporation in the externally triggered burst search analysis.  Automation.  Use MBLT for line removal.  C++ codes underway.  DMT monitor ? ( may be )

Soma Mukherjee 20/3/03 Questions wrt Astrophysical Search  Threshold and tolerance. … being worked up on.