Intraday variability of Sgr A* at radio wavelengths: A Day in the Life of Sgr A* Doug Roberts Northwestern University Adler Planetarium & Astronomy Museum

Collaborators Farhad Yusef-Zadeh – Northwestern University Geoff Bowers – University of California Berkeley Craig Heinke – Northwestern University

Motivation: Campaign Started as part of multi-wavelength campaign in March Follow-up observations of Sgr A* and nearby X- ray/radio transient were done throughout

Motivation: Previous determinations of radio variability Long term radio variability –106 day variability 15 & 22 GHz (Zhao et al. 2001) –2.5 yr observations at 15, 22 & 43 GHz suggest bimodal flux densities and spectral indices (Herrnstein et al. 2004) Hourly variability at high frequencies: –1.5 hour (x 2 flux) flare at 100 & 140 GHz (Miyazaki et al. 2004) –2.5 hour variability at 100 GHz (Mauerhan et al. 2005)

Radio observations used various telescopes (5-83 GHz) ATCA (17, 19 GHz) VLA (5, 22, 43 GHz) BIMA (83 GHz)

Observations designed to observe intraday variability All observations were done with frequent pointings between Sgr A* and a nearby (3º) calibrator (cycled between 90 seconds on source and 30 seconds on calibrator). Less frequent observations of a strong calibrator further away (10º). Pointing scans every hour. Tipping scan to determine the atmospheric opacity at the beginning of the run.

Lots of data! 32 Datasets Each about 5 hr in length 20 GB of raw data

Data analysis Phase calibration on calibrators applied before ordinary calibration. Phase self-cal on Sgr A*. Flux of Sgr A* determined by fitting point source model in visibility plane, using only long spacing that filter out diffuse emission from Sgr A West.

First look Radio variability of 5- 10% at various timescales. High time resolution samples show few percent variation every sample (2 minutes). Significant day-to-day variability. Example light curve – 1 day Example light curve – 1 week

Calibration issues Is variation real or artifact of observation or problems with calibration?

Calibration issues Is variation real or artifact of observation or problems with calibration? –Variation within an observation is pretty reliable. –Day-to-day variation is harder to verify.

Analysis of light curve Lomb-Scargle analysis of each light curve separately. Monte Carlo simulation of red noise – P(f) ~ f -1 – using the statistics of the relevant observation – following technique of Mauerhan et al.

Hourly variability: VLA (43 GHz)

Hourly variability: ATCA (17.6, GHz)

Hourly variability: BIMA (83 GHz)

Hourly variability: radio statistics

Interpretation of variability distribution Lower limit to time scale for variability of 2.5 hr. Similar to peak in OVRO 83 GHz power spectrum. If the time scale for this variability is related to dynamics of emitting gas, this suggests a dynamical radius of 10 R s.

Radio flare simultaneously detected at 22 & 43 GHz

43 GHz emission leads 22 GHz by about 20 minutes. Spectral index is steeper at higher frequencies and during flares, consistent with Herrnstein et al. (2004). Consistent with expansion of self- absorbed synchrotron source.

Scintillation vs. intrinsic changes Similar shape of light curve and delay between 22 & 43 GHz. Scintillation effects cannot explain this delay.

Summary Typical variability within one day is 5-10%. Variability on various timescales from 2 hr to 5 hr (to 10 hr for long ATCA tracks). Lower limit to dynamic length scale is around 10 R s. Delay in 22 GHz and 43 GHz observations of flare. Model of variability suggests high optical depth from expanding synchrotron source.