CW signals: plans for S2CW signals: plans for S2

June 16-17 the group held a f2f meeting to discuss plans for analyses of S2 data (and beyond).

Slides from the various presentations can be found at www.lsc-group.phys.uwm.edu/pulgroup/

The content of this presentation is mostly cut-and-paste from these.

Coherent search methods

•Time domain Bayesian analyses:

• extend to all known isolated pulsars emitting above ~ 50 Hz (Glasgow).

• special search for Crab (Glasgow)

• Metropolis-Hastings Markov Chain Monte Carlo method for parameter estimation and small parameter space searches (Carleton)

• Frequency domain analyses:

• extend to inspect a larger parameter space (non-targeted search) (AEI+UWM)

• extend to search for signals from a pulsar in a binary system, will be applied to Sco X-1 (Birmingham)

Non-coherent search methodsNon-coherent search methods

• Unbiased searches (Michigan)

• Hough search (AEI)

• Stack-slide (Hanford)

TDS: Known pulsarsTDS: Known pulsars

(R. Dupuis, G. Woan, GLASGOW)

Perform similar statistical analysis as S1 for all known isolated radio pulsars with f

GW > 50 Hz.

Total of 34 pulsars

Computational cost minimal. Processing time on Medusa should be around 15 min

per pulsar. Another 15 minutes on a workstation to calculate posterior probability.Automatic characterization of noise in small freq.

band

• Would like to perform a coherent analysis using all IFOs for every pulsar.

• Preliminary results should be available by August LSC.

Isolated pulsars with fGW

> 50 Hz# PULSAR FREQUENCY (HZ)

1 B0021-72C 173.7082189660532 B0021-72D 186.6516698568383 B0021-72F 381.158663656554 B0021-72G 247.501525096525 B0021-72L 230.087746291506 B0021-72M 271.987228788937 B0021-72N 327.444318617558 J0024-7204V 207.909 J0030+0451 205.5306992749310 B0531+21 30.2254370 11 J0537-6910 62.05509612 J0711-6830 182.11723766639013 J1024-0719 193.7156866910314 B1516+02A 180.0636246972715 J1629-6902 166.6499060407416 B1639+36A 96.36223456417 J1709+23 215.9418 J1721-2457 285.989348011919 J1730-2304 123.11028917979720 J1744-1134 245.426123707305921 J1748-2446C 118.538253056322 B1820-30A 183.8234354177723 B1821-24 327.4056651498924 J1910-5959B 119.648732845725 J1910-5959C 189.4898710701926 J1910-5959D 110.677191984027 J1910-5959E 218.733857589328 B1937+21 641.928261106808229 J2124-3358 202.79389723498830 B2127+11D 208.21168801031 B2127+11E 214.98740790632 B2127+11F 248.32118076033 B2127+11H 148.29327256534 J2322+2057 207.968166802197

Black dots show expected upper limit using H2 S2 data.Red dots show limits on ellipticity based on spindown.

Crab pulsarCrab pulsar

(M. Pitkin, R. Dupuis, G. Woan, GLASGOW)

Frequency residuals will cause large deviations in phase if not taken into account.

Young pulsar with large spindown and timing noise

Timing noise not irrelevant:

RMS frequency deviations (Hz)

RMS phase deviations (rad)

Time interval(months)

2 1.3 1.9E-64 157.1 9.7E-56 2115.7 8.4E-48 12286 3.6E-310 46229.3 1.0E-212 134652.8 2.5E-2

More on the Crab

Removing the timing noise Use Jodrell Bank monthly crab ephemeris to recalculate

spin down params every month.

Calculate phase residuals between radio observations and fixed spin down parameters. Then add another heterodyning phase to data processing to remove timing noise.

Open IssuesCould add another parameter = - IEM / IGW (I. Jones

paper)

No glitches during S2 but in the event of a glitch we would need to add an extra parameter for jump in GW phase 60 Hz, filters

Preliminary results should be available by August LSC

MCMC's (N. Christensen) Definitely useful to nail down signal parameter values around candidates Might be useful for small parameter space searches, e.g. the Middleditch optical pulsar in SNR1987A. On-going work to efficiently search over additional parameters (frequency, fdot, wobble angle) in low signal-to-noise conditions.

Automation of TDS (G. Santostasi) Plan to automate the data processing done in the time domain

search making it an on-line analysis (perhaps LDAS?)

Just starting to look at this.

Time Domain SearchesTime Domain Searches

FDS: parameter space searchesFDS: parameter space searches

(M.A. Papa, X. Siemens – AEI , UWM)

Have modified the software used for the targeted S1 search to search for arbitrary ranges of f0 (with arbitrary resolution), areas in the sky and spin-down parameter values (now only 1st order)

The limiting factor is computational time need to decide how to spend the computing cycles that we have

We have decided to pursue two types of searches: short observation time (low sensitivity), no spin-down paramaters, wide band (300-400 Hz), all sky search longer observation time (higher sensitivity), 1 spin-down param, small area search (galactic plane/first spiral arm), low frequencies (~ 70 Hz), small bands

Note: different choices could be made in order to produce the best ULs.

FDS: Sco X1FDS: Sco X1

(C. Messenger, A. Vecchio – Birmingham)

Sco X-1:• Frequency: not known a priori – search on a wide band (~ 100 Hz)• Doppler effects:

• Source position: known (no search over sky position)• Orbit: circular (e < 3x10-4), therefore 3 search parameters (projected semi-

major axis, orbital period, initial phase on the orbit)• For T < 1 month period is not a search parameters• Search over only 2 parameters (flat parameter space)

• Spin-down/up: number of spin-down parameters depend on the integration time, but for T < 10 days signal monochromatic

• Physical scenarios:• Accretion induced temperature asymmetry (Bildsten, 1998;

Ushomirsky, Cutler, Bildsten, 2000)• R-modes (Andersson et al, 1999; Wagoner, 2002)

Sco X-1 and LIGO/GEO sensitivity

PSR J1939+2134

Sco X-1 (Rejean’s plot)

Upper-limit on Sco X-1Upper-limit on Sco X-1

PULG F2F Meeting, UWM, 16PULG F2F Meeting, UWM, 16thth - 17 - 17thth March, 2003 March, 2003

June 16, 2003 face-to-face pulsar meeting - UWM

Unbiased, All-sky CW Search -- Michigan Group

12

Unbiased All-Sky Search (Michigan)[ D. Chin, V. Dergachev, K. Riles ]

Analysis Strategy: (Quick review)• Measure power in selected bins of averaged periodograms• Bins defined by source parameters (f, RA, ) • Estimate noise level & statistics from neighboring bins• Set “raw” upper limit on quasi-sinusoidal signal on top of

empirically determined noise• Scale upper limit by antenna pattern correction, Doppler

modulation correction, orientation correction• Refine corrected upper limits further with results from

explicit signal simulation

Preliminary Data Pipeline Diagram for Unbiased All-Sky CW Search

Overview:

Creation of Power Statistic

Raw Data

Simulated Data

Loop over frequency and sky:

Determine search range and control sample range

Determine upper limit on detected power

Apply efficiency corrections (Doppler, AM, orientation

Determine limit on h0 and store

Determine efficiency corrections

S2 Numbers:

59 days = 1416 hours = 84,960 minutes = 5.1 × 106 seconds Single FFT: 0.2 μHz bins

Power sum for 1-minute FFT’s: 0-2000 Hz x 60 bins/Hz x 4 Bytes/bin = 480 kB (17mHz bins)

Power sum for 30-minute FFT’s: 0-2000 Hz x 1800 bins/Hz x 4 Bytes/bin = 14.4 MB (0.56 mHz bins)

What will be ready by August LSC meeting?

Expect bare-bones baseline limits over samples of clean frequency ranges with semi-analytical efficiency corrections

Primary goal in next two months

Refinements under consideration but not in baseline:

Non-uniform weighting of SFT’s

Explicit consideration of spin-down parameters

Shifting frequency search range vs SFT

What is unlikely to be ready by August:

Graceful handling of problematic frequency ranges

Efficiency corrections based on full MC simulations

Hough TransformHough Transform

(B. Krishnan, A. Sintes, (map) – AEI)

• start with SFTs with baseline of ~ 30 minutes (or more if stationarity of data allows it).

• for every SFT () select frequency bins i such |SFT|i2/<|SFT|2> exceeds some threshold time-frequency plane of zeros and ones.

• Hough transform: track patterns of “ones” consistent with what one would expect from a signal.

Something should be added regarding status

Stack slideStack slide

(M . Landry, G. Mendell – Hanford)

• new proposal presented in May at a meeting devoted to new data analysis proposals

• based on P.R. Brady, T. Creighton Phys.Rev. D61 (2000) 082001

• it is a hierarchical search: the coherent stage could be performed by either resampling and FFT-ing or by the F statistic. The incoherent search consists in summing appropriately (by choosing the appropriate search frequency values) the outcome of the first stage.

• as a first step, the idea is to implement a stack-slide that starts from SFTs. Similar to Hough, but without peak selection.