LIGO-G000193-00-M

LIGO IScience Run

Barry Barish

PAC Meeting - LHODecember 13, 2000

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The LIGO I Science RunData & Computing Group Operations Plan

9th Meeting of the LIGO PACLIGO Livingston Observatory

Livingston, Louisiana13 December 2000

Albert Lazzarini

LIGO Laboratory Caltech

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LIGO Plansschedule

1996 Construction Underway (mostly civil)

1997 Facility Construction (vacuum system)

1998 Interferometer Construction (complete facilities)

1999 Construction Complete (interferometers in vacuum)

2000 Detector Installation (commissioning subsystems)

2001 Commission Interferometers (first coincidences)

2002 Sensitivity studies (initiate LIGO I Science Run)

2003+ LIGO I data run (one year integrated data at h ~ 10-21)

2005+ Begin ‘advanced’ LIGO installation

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Revised Schedule

As proposed to the NSF – May 2000

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Significant Events

Hanford 2km

interferometer

Single arm test complete installation complete interferometer locked

6/00 8/00 12/00

Livingston 4km

interferometer

Input Optics completed interferometer installed interferometer locked

7/00 10/00 2/01

Coincidence Engineering Run (Hanford 2km & Livingston 4km)

Initiate Complete

7/01 7/02

Hanford 4km

interferometer

All in-vacuum components installed interferometer installed interferometer locked

10/00 6/01 8/01

LIGO I Science Run (3 interferometers)

Initiate Complete (obtain 1 yr @ h ~ 10-21 )

7/02 1/05

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•operating as a Michelson with Fabry-Perot arms

•reduced input laser power (about 100 mW)

•without recycling •noise level is a factor of 104-105 above the final specification

•sources of excess noise are under investigation

Strain SensitivityNov 2000

2-km Hanford Interferometer

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LIGO Isteps to science run

commissioning interferometer » robust locking» three interferometers» sensitivity» duty cycle

interleave engineering runs» implement and test acquisition and analysis tools» characterization and diagnostics studies» reduced data sets» merging data streams» upper limits

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LIGO/LSC Data Analysis Model

Now: » Initial engineering runs starting to set the stage for how

science, research is done

» Data being archived at Caltech in HPSS

» Access from archive according to LIGO Laboratory MOUs

» “Stress testing” of software and hardware systems - both LDAS and GDS/DAQS/CDS

» Initial data analyses focus on – sorting out commissioning issues, – understanding environment, – Calibrations, data conditioning, pre-processing

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LIGO/LSC Data Analysis Model

Near-term (2Q2001): » LIGO science will focus on using engineering runs to extract

meaningful first upper limits» Organized around 4 upper limits papers using ~1 week of data

in 2Q2001» Opportunity to set current best upper limits on these classes of

sources» Provides a basis to "exercise" the LSC data analysis groups» Provides a basis for future organization of the LIGO I Science

Run search teams– groups will expand as interest grows in LIGO science.

Problems:» LDAS readiness to support the engineering run goal» Strategy is to limit scope primarily to LDAS supported goals

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Astrophysical Signaturesdata analysis

Compact binary inspiral: “chirps”» NS-NS waveforms are well described» BH-BH need better waveforms » search technique: matched templates

Supernovae / GRBs: “bursts” » burst search algorithms – eg. excess power; time-frequency patterns» burst signals in coincidence with signals in electromagnetic radiation » prompt alarm (~ one hour) with neutrino detectors

Pulsars in our galaxy: “periodic”» search for observed neutron stars (frequency, doppler shift)» all sky search (computing challenge)» r-modes

Cosmological Signals “stochastic background”

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LIGO/LSC Data Analysis Model

LIGO I Science Run (2Q2002):» Key astrophysical searches follow the LSC Data Analysis

White Paper plan:

» Organized around teams, as in near-term upper limit studies– Open to all who are willing to work

» LIGO Lab LDAS resources to be used for searches will be shared among the teams

» LSC member institutional resources used by individual researchers

» Longer term: establish 5 LIGO/LSC Tier 2 centers (“University Research Centers” or URCs) to provide additional computational, data distribution resources across collaboration

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Inspiral Sources

LSC Upper Limit

Group

Inspiral Sources Co-chair Patrick Brady, Gabriela Gonzalez

-------------------------------------------------------------------

Bruce Allen ballen@gravity.phys.uwm.edu

Sukanta Bose bose@aei-potsdam.mpg.de

Douglas Boyd Douglas.Boyd@astro.cf.ac.uk

Patrick Brady patrick@gravity.phys.uwm.edu

Duncan Brown duncan@gravity.phys.uwm.edu

Jordan Camp camp_j@ligo.caltech.edu

Nelson Christensen nchriste@carleton.edu

Jolien Creighton jolien@gravity.phys.uwm.edu

S.V. Dhurander sdh@iucaa.ernet.in

Gabriela Gonzalez gig1@psu.edu

Andri Gretarsson andri@suhep.phy.syr.edu

Gregg Harry gharry@phy.syr.edu*

Syd Meshkov meshkov_s@ligo.caltech.edu

Tom Prince prince@srl.caltech.edu

David Reitze reitze@phys.ufl.edu

B.S. Sathyaprakash B.Sathyaprakash@astro.cf.ac.uk

Peter Shawhan shawhan_p@ligo.caltech.edu

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Interferometersastrophysical sources

Compact binary mergers

Sensitivity to coalescing binaries

Binary inspiral ‘chirp’ signal

2002

2007

future

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Interferometer Data40 m

Real interferometer data is UGLY!!!(Gliches - known and unknown)

LOCKING

RINGING

NORMAL

ROCKING

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The Problem

How much does real data degrade complicate the data analysis and degrade the sensitivity ??

Test with real data by setting an upper limit on galactic neutron star inspiral rate using 40 m data

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“Clean up” data stream

Effect of removing sinusoidal artifacts using multi-taper methods

Non stationary noise Non gaussian tails

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Inspiral ‘Chirp’ Signal

Template Waveforms

“matched filtering”687 filters

44.8 hrs of data39.9 hrs arms locked25.0 hrs good data

sensitivity to our galaxyh ~ 3.5 10-19 mHz-1/2

expected rate ~10-6/yr

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Detection Efficiency

• Simulated inspiral events provide end to end test of analysis and simulation code for reconstruction efficiency

• Errors in distance measurements from presence of noise are consistent with SNR fluctuations

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Setting a limit

Upper limit on event rate can be determined from SNR of ‘loudest’ event

Limit on rate:R < 0.5/hour with 90% CL = 0.33 = detection efficiency

An ideal detector would set a limit:R < 0.16/hour

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Two Sites - Three Interferometers»Single Interferometer non-gaussian level~50/hr

»Hanford (Doubles) correlated rate (x1000) ~1/day

»Hanford + Livingston uncorrelated (x5000)<0.1/yr

Coincidencesbetween

LLO & LHO

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Burst Souces LSC Upper Limit Group

Burst Sources Co-chair Sam Finn, Peter Saulson

-----------------------------------------------------------

Warren Anderson wganderson@utb1.utb.edu

Barry Barish barish@ligo.caltech.edu

Biplab Bhawal bbhawal@ligo.caltech.edu

Jim Brau jimbrau@faraday.uoregon.edu

Eric Black black_e@ligo.caltech.edu

Kent Blackburn blackburn_k@ligo.caltech.edu

Ed Daw daw@lsuligo.phys.lsu.edu

Ronald Drever rdrever@caltech.edu

Sam Finn finn@phys.psu.edu

Ray Frey rayfrey@cosmic.uoregon.edu

Ken Ganezer ganezer@DHVX20.CSUDH.EDU

Joe Giaime giaime@lsuligo.phys.lsu.edu

Gabriela Gonzalez gig1@psu.edu

Andri Gretarsson andri@suhep.phy.syr.edu

Bill Hamilton hamilton@dave.phys.lsu.edu

Warren Johnson johnson@dave.phys.lsu.edu

Masahiro Ito

S. Klimenko klimenko@phys.ufl.edu

Al Lazzarini lazz@ligo.caltech.edu

Szabi Marka marka_s@ligo.caltech.edu

Genakh Mitselmakher mitselmakher@phys.ufl.edu

Soumya Mohanty mohanty@aei-potsdam.mpg.de

Benoit Mours mours_b@ligo.caltech.edu

Soma Mukherjee soma@aei-potsdam.mpg.de

Fred Raab fjr@ligo.caltech.edu

Ravha Rahkola

Peter Saulson saulson@ligo-la.caltech.edu

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pulsar proper motions

Velocities - young SNR(pulsars?) > 500 km/sec

Supernovaeasymmetric collapse?

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LIGO Iscience run

Strategy» initiate science run when good coincidence data can be reliably taken and

straightforward sensitivity improvements have been implemented (~ 7/02)» Then, interleave periods of science running with periods of sensitivity

improvements

Goals» obtain 1 year of integrated data at h ~ 10-21

» searches in coincidence with astronomical observations (eg. supernovae, gamma ray bursts)

» searches for known sources (eg. neutron stars)» stand alone searches for compact binary coalescence, periodic sources,

burst sources, stochastic background and unknown sources at h ~ 10-21 sensitivities

Exploit science at h ~ 10-21 before initiating ‘advanced’ LIGO upgrades

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LIGO/LSC Data Analysis Model

Throughout Engineering & Science Runs, the Laboratory’s Data & Computing Group fulfills the following roles:

» LIGO science, data analysis: scientific staff are actively engaged in the astrophysics searches

» Simulation & Modeling: detector support, data analysis» Continuous management and movement of large volumes of

data» Maintaining pipeline analyses running, archive running» Software maintenance/improvements/enhancements» LSC support, visitors» LIGO Laboratory-wide IT support

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LDAS Staffing Plan

Personnel FTE LIGOScience

Run;AlgorithmPerf. Mon

LIGOScienceRun; HWPerf. Mon

LIGOScience

Run; DataArchival

LIGOScience

Run; DataAnalysis &Research

Operations: DB

Mgmnt

Operations:Sys. Admin

SW Dev& Maint.

Graduate Student 2.0 2

Post DoctoralResearcher

3.0 0.45 0.33 0.25 1.97

Sci. 3.8 1.38 0.2 0.45 1.24 0.53

Sw. Eng 3.8 1.42 2.38

Contract SW Eng. 1.0 1

DB Admin 1.0 0.5 0.5

HPSS Admin 1.0 0.5 0.5

LDAS-SysAdmin 1.0 1

CIT Totals -> 16.6 3.25 0.53 1.7 5.21 0.5 1.5 3.91

LHO Sci* 1.0 0.2 0.2 0.2 0.2 0.2

LLO Sci* 1.0 0.2 0.2 0.2 0.2 0.2

LIGO Lab Totals -> 18.6 3.65 0.93 2.1 5.61 0.5 1.9 3.91

Personnel Students 2

Classifications Post Docs 0.45 0.33 0.25 1.97

Scientists 1.38 0.2 0.45 1.24 0.53

SW Eng. 1.42 3.38

SysAdmin 1 0.5 1.5

* NOTE: LHO and LLO personnel are in the budgetary proposals from the respective observatories

Data & Computing Group Principal LDAS activities during operations

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Data & Computing Group Principal Modeling & Simulation

activities during operations

Modeling & Simulation Staffing Plan

Personnel FTE Code environ.Development:Architecture

Code environ.Development:

EM Fields,Optics

Code environ.Development:

Mechanicalsystems

Code environ.Development:GUI Develop.

DetectorPerformance

Modeling

DataAnalysis

Simulation

Graduate Student 2.0 1 1

Post DoctoralResearcher

1.0 0.5 0.5

Sci. 2.0 0.5 0.5 0.25 0.5 0.25

Sw. Eng 1.0 0.75 0.25

Contract SW Eng. 1.0 1

CIT Totals -> 7.0 1.25 0.5 0.75 1.25 2 1.25

Personnel Students 1 1

Classifications Post Docs 0.5 0.5

Scientists 0.5 0.5 0.25 0.5 0.25

SW Eng. 0.75 0.25 1

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Data & Computing Group Principal General Computingactivities during operations

General Computing Staffing Plan

Personnel FTE Server & DataSystems

DesktopWorkstations

LAN & WANAdministration

TelecommunicationsAdministration

Web & DBAdministration

Student Asst. 0.40 0.4

www, DB Admin 0.50 0.5

Sci. 0.10 0.1

Sr. Sys. Admin 1.00 0.2 0.15 0.3 0.35

Asst. Sys. Admin 1.00 0.3 0.6 0.1

Contract Sys.Admin.

1.00 0.25 0.75

CIT Totals -> 4.00 0.75 1.9 0.5 0.35 0.5

MIT Sys. Admin* 1.00 0.3 0.6 0.1

LHO Sys. Admin.* 1.25 0.3 0.6 0.1 0.13 0.12

LLO Sys. Admin.* 1.25 0.3 0.6 0.1 0.13 0.12

LIGO Lab Totals -> 7.50 1.35 3.1 0.7 0.48 0.62

Personnel Students 0.4

Classifications DB Admin. 0.5

Sci. 0.1

SysAdmin 0.75 1.5 0.4 0.35

* NOTE: MIT, LHO, and LLO personnel are in the budgetary proposals from the respective sites

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LDAS OperationsStatistics derived from actual experience

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* MIT, LHO, and LLOhave local General

Computing staff

* LHO, and LLOhave local LDAS staff

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Data and Computing Budget Breakdown

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Hardware Class

ProcurementExpense

Maintenance @ 30%/yr

HPSS $1428.0K $428.4K

Servers $272.0K $81.6K

Switches $163.0K $48.9K $/yr $/qtrFY2001Q4-FY2004Q1

Maintenance

FY2001Q4-FY2004Q1

Maintenance

HW RAID, Small Robots

$735.0K $220.5K $779.4K $194.9K $194.9K $107.1K

Maintenance @ 15%/yr

FY2001Q4-FY2004Q1 Equipment

FY2001Q4-FY2004Q1 Equipment

Workststions, small switches, disks

$1387.0K $208.1K $208.1K $52.0K $52.0K $139.8K

Totals-> $3985.0K $987.5K $987.5K $246.9K $246.9K $246.9K

From Procurement Plan C90755-A

LDAS Operations BudgetHardware Support

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Requested Increment - Operations

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Conclusionsscience run

Short term -- » implement LDAS

– 4 sites; computing; archiving

» engineering runs– data handling and access, reduced data sets

– diagnostics; characterize instrument and data

– algorithms; statistics

Longer Term» LIGO Lab support for Science Run

Support Required» LDAS procurement and implementation» incremental resources requested

– manpower

– maintenance and networking

– support of LSC