Calibration Tasks and Milestones (Towards O3)

Goals

• Make the whole chain of h(t) reconstruction running with Pcal
  • 3 types of h(t) provide (online, low latency, offline)
  • online h(t) generation using Pcal(DGS)
  • low latency and offline will be similar code
• Accuracy at the initial LIGO O1 level (10%,10deg.)
  • LIGO also have many try and error
  • free sweging is used for calibration method comparison
  • final goal is 1%, 1deg.
• By the starting of phase-2 engineering run (well in advance of joining O3)

Task (Responsible and sub-responsible person(s))

• Cross out if the tasks are completed

Listing-up (S.Haino and responsible people)

• List-up tasks and responsible person

• List-up milestones and deadline
• Submit the list of task and milestone to the KAGRA scheduler

Pcal (Y.Inoue, C.Kozakai, Cory, Bin-Hua)

• Install Pcal at X and Y-end and coordinate[status: on going | expected finish: Sep. 1, 2018]

• the long-term Pcal characterization [status: to do | expected finish: Sep. 1, 2018]

• Prepare for the necessary EPICS channels to the online system for the calibration

• List-up the systematic error budget table for O3 [status: on going | expected finish: until O3]

• Achieve 1% displacement error [status: to do | expected finish: Apr. 1, 2019]

• Absolute power calibration[status: to do | expected finish: Jan. 1, 2019]

• Note: Maintenance at Kamioka site.
  • BH should stay Kamioka and periodic work
  • Telephoto camera
    • Installation is almost done
    • Maintenance of TCam is done by T.Yokozawa
    • IR filter issue(spare camera), additional spare camera.
    • Image analysis by Tomigami.

Front-end (T.Yamamoto, +1person from off-site)

• Make the models for the online h(t) reconstruction [status: ongoing | expected finish: Jan. 1, 2019]

• Provide the necessary DAQ channels for the low-latency calibration[status: ongoing | expected finish: Jan. 1, 2019]

  • The necessary channels had already existed in Phase-1 operation (What we should are only small fix.).
• ...

Low-latency and offline (D.Tuyenbayev, S.Tsuchida, S.Haino)

• Ask to LIGO CAL team for the detailed information of gstlal-calibration (DT) [status: ongoing | expected finish: none]

• Make gstlal-calibration running on a machine at KAGRA (DT, SH) [status: ongoing | expected finish: Jul 15]

  • Find names and versions of all prerequisite libraries
  • Install prerequisites and gstlal-cal package on a machine at AS
  • Test gstlal-cal pipeline on an AS machine
  • Install prerequisites and gstlal-cal package on a machine at KAGRA
  • Test the pipeline on a KAGRA machine

• Use gstlal-calibration for the initial offline h(t) reconstruction from bKAGRA phase-1 data (ST, DT) [status: to do | expected finish: Aug 15]

  • Note: depends on the installation of gstlal-cal on a machine at AS
  • Produce dummy output equivalent to online cal output
  • Compare gstlal and online outputs of bKAGRA phase-1 data

• Use gstlal-calibration for the better offline h(t) reconstruction from bKAGRA phase-1 data (ST, DT) [status: to do | expected finish: Oct 1]

  • Note: depends on the completion of using gstlal-calibration for the initial offline h(t) reconstruction from bKAGRA phase-1 data
  • Generate simple FIR filters to compensate AA/AI effects at high frequencies
  • Compare better gstlal (this task), gstlal dummy (previous task) and online outputs of bKAGRA phase-1 data

• Generate status vector (DT, ST, SH) [status: to do | expected finish: Sep 15]

  • Decide status vector bits
  • Modify (adapt) the function that generates the status vector
  • Produce the status vector data

• Generation of FIR filters for KAGRA DARM model (ST, DT) [status: to do | expected finish: end of bKAGRA phase-2]

  • Note: Depends on the readiness of the DARM model

• Feed KAGRA online channels into gstlal-calibration and generate low-latency h(t) (ST, DT, SH) [status: to do | expected finish: end of bKAGRA phase-2]

  • Note: Depends on the readiness of DMT
  • Run run the pipeline in low-latency during bKAGRA phase-2

DARM model (T.Yamamoto, D.Tuyenbayev, T.Yokozawa)

• Make a subway map of the KAGRA DARM model [status: to do | expected finish: Sep. 1, 2018]

• Optimize the calibration lines [status: to do | expected finish: May 1, 2019]

  • DARM sensitivity is required in order to optimize.

• Coordinate the Open Loop Gain (OLG) Transfer function measurements [status: to do | expected finish: Apr. 1, 2019]

  • DARM lock is required because this task contains try and error of the swept sine injection.

• Estimate and trace the slow time variation of the calibration parameters [status: to do | expected finish: Jun. 1, 2019]

• Electronics transfer function. [status: to do | expected finish: Oct. 1, 2018]

  • The subway map help us to decide the necessary component.

Pcal verification (Y.Inoue,...)

• Coordinate h(t) calibration with the Free-swinging Michelson method [status: to do | expected finish: May. 1, 2019]

• Compare h(t)s calibrated between Free-swinging Michelson and Pcal[status: to do | expected finish: May. 1, 2019]

• Compare h(t)s calculated between diff,common,...[status: to do | expected finish: May. 1, 2019]

Hardware injection (T.Yokozawa, Cory )

• Make the online model for the hardware injection with actuators[status: fist version finished | expected finish: end of August]

• Make the online model for the hardware injection with Pcal[status: fist version finished | expected finish: end of August]

• Coordinate the hardware injection tests[status: to do | expected finish: end of bKAGRA phase-2]

• Analyze the hardware injected data and verify the DARM subway map[status: to do | expected finish: end of bKAGRA phase-2]

Systematic errors assignment (T.Sawada, Y.Inoue, S.Haino, T.Yokozawa)

• Goal: Estimate the systematic errors due to calibration
• Details:

  • Estimate the value of calibration uncertainties(maximum and minimum of errors with +-1sigma uncertainties) for magnitude[%] and phase[deg.] (TS) [status: to do | expected finish: end of Jul]

  • Estimate the total calibration error and uncertainty envelope with respect to the frequency (TS) [status: to do | expected finish: end of Jul]

  • Then Provide them to the data analysis group and simulation group
• Make a simulation.
• Provide the calibration envelopes for the data analysis group
• (If possible) Incorporate DARM model and parameter uncertainties in the data analysis
  • A.Miyamoto will show the first results of the effect of calibration uncertainties to the POP III data analysis