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Refining the time delay in JVAS B0218+357

Refining the time delay in JVAS B0218+357. Andy Biggs UK ATC. 0218 in a nutshell. Time delay: Variable Polarised Resolvable with VLA Modelling Single galaxy lens Known redshifts Extended emission. 0218+357 time delay history. Monitored 4 times with the VLA Oct - Jan 1992/93

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Refining the time delay in JVAS B0218+357

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  1. Refining the time delay inJVAS B0218+357 Andy Biggs UK ATC

  2. 0218 in a nutshell • Time delay: • Variable • Polarised • Resolvable with VLA • Modelling • Single galaxy lens • Known redshifts • Extended emission

  3. 0218+357 time delay history • Monitored 4 times with the VLA • Oct - Jan 1992/93 • Corbett et al. (1996) [ = 12 ± 3 days] • Mar - May 1994 • Chris Sykes’ thesis? • Oct - Jan 1996/97 • Biggs et al. (1999) [ = 10.5 ± 0.4 days] • Cohen et al. (2000) [ = 10.1 ± 1.5 days]

  4. Total flux density (1996-1997) ratio (A/B) = 3.73

  5. Polarisation p.a. (1996-1997)  p.a. (AB) = 15.4°

  6. Motivation for re-visiting data • Calibration techniques have improved • gain/elevation correction • Time delay can be found from all data simultaneously • long time baseline • light curves can be combinations of different ‘measures’ • 1993 total flux + 1994 position angle + 1996 polarised flux • many light curves formed in this way • Investigate possible time-variable Faraday rotation • Recent VLA proposals rejected

  7. Monitoring strategy • 3C147/3C48 (not 1996/97) • get approximate flux density of variable 3C84 • 3C84 • set flux scale of each epoch • assume non-variable (!) • calibrate polarisation leakage assuming non-polarised • 3C119 • calibrate polarisation position angle

  8. Preliminary results Corbett data (1992/1993) Polarised flux density Polarisation position angle

  9. Problems with 1994 data Unstable gains Bizarre polarisation behaviour Elongated beam (BnA configuration)

  10. To do • Reduce all data in uniform fashion • Resolve polarisation issue • Decide on model-fitting strategy • Measure time delays for all combinations of data • Derive errors using Monte Carlo simulations

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