1. REDUCTION OF GALFACTS DATA AND VARIABLE RADIO SOURCES Scott Barenfeld with Tapasi Ghosh and Chris Salter

2. VARIABLE RADIO SOURCES First discovered in 1965 Radio galaxies and quasars that vary in brightness and sometimes polarization Time scales from months and years to hours and days

3. VARIABLE RADIO SOURCES Cause of variability is unclear Based on the timescale of the variability, the size of the active region can be constrained Much smaller than the angular resolution of even VLBI

4. VARIABLE RADIO SOURCES-THEORIES Extrinsic causes: Interstellar scintillation Gravitational microlensing Both probably contribute to some cases of variability Won’t work for most cases though

5. VARIABLE RADIO SOURCES-THEORIES Intrinsic causes: Brightness temperatures of up to 10^21 K, so non-thermal emission Probably syncotron Adiabatic expansion Shocks in jets More work needed Two Methods to Study Variable Sources

6. GALFACTS Survey of the Arecibo sky ALFA 1225-1525 MHz Study of Milky Way and extragalactic sources

7. DATA ANALYSIS Average By Channel Pick Out Good Channels Average By Time Original Data Pick Out Sources

8. DATA ANALYSIS Original DataRemove NaNs Convolution Average by Channel Find and Remove RFI Average Good Channels by Time Filter Convolution Again Pick Out Individual Sources Fit Gaussians to Sources Generate Source List Repeat for Each Day’s Data

9. ORIGINAL DATA # RA DEC AST I Q U V 31.00725852 32.78314564 7472.84 41.117783 0.301337 -1.375706 -1.126522 31.00809381 32.78314601 7473.05 41.173588 0.231408 -1.335442 -1.265603 31.00892909 32.78314638 7473.25 41.160358 0.237417 -1.247413 -1.216029 31.00976438 32.78314675 7473.45 41.159851 0.254429 -1.443475 -1.250774 31.01059967 32.78314712 7473.65 41.194580 0.249643 -1.441542 -1.235810 31.01143495 32.78314749 7473.85 41.101738 0.275147 -1.326443 -1.270772 31.01227024 32.78314786 7474.05 41.122730 0.290011 -1.371698 -1.205746 31.01310553 32.78314823 7474.25 41.114750 0.284960 -1.252110 -1.164530 31.01394081 32.78314859 7474.45 41.126972 0.274343 -1.416226 -1.382210 31.01477610 32.78314896 7474.65 41.196613 0.261553 -1.401918 -1.186886 31.01561138 32.78314933 7474.85 41.132881 0.270624 -1.375244 -1.249733 31.01644667 32.78314970 7475.05 41.140030 0.299704 -1.307124 -1.188367 31.01728196 32.78315007 7475.25 41.143154 0.280979 -1.370005 -1.201098 31.01811724 32.78315044 7475.45 41.194427 0.279727 -1.422677 -1.149286 31.01895253 32.78315081 7475.65 41.182938 0.271683 -1.370870 -1.185971 31.01978782 32.78315118 7475.85 41.137146 0.269577 -1.388050 -1.163989 31.02062310 32.78315155 7476.05 41.176136 0.274557 -1.311299 -1.188414 31.02145839 32.78315192 7476.25 41.154861 0.280283 -1.289776 -1.157237 31.02229368 32.78315229 7476.45 41.224983 0.218572 -1.254922 -1.158064 31.02312896 32.78315266 7476.66 41.199093 0.268448 -1.330183 -1.215898 31.02396425 32.78315303 7476.86 41.164238 0.248226 -1.427136 -1.265751 31.02478764 32.78315339 7477.06 41.146324 0.225548 -1.332560 -1.138965 31.02561104 32.78315376 7477.26 41.192913 0.228657 -1.368893 -1.161209 31.02643443 32.78315412 7477.46 41.164112 0.249461 -1.329204 -1.107040 31.02725783 32.78315449 7477.66 41.156616 0.262676 -1.337611 -1.315423 31.02808122 32.78315485 7477.86 41.162651 0.251219 -1.269606 -1.259569 31.02891649 32.78316350 7478.06 41.172379 0.239708 -1.350749 -1.105756

10. ORIGINAL DATA Test data first- known source 2048 Files RA, DEC, Time, I, Q, U, V

11. REMOVE NaNs NaNs create problems when averaging Program runs fastest if they are removed first Each channel’s file is searched Channel numbers with no NaNs are listed These channels are then averaged

12. AVERAGE BY CHANNEL Once the NaNs are removed, data can be averaged The I, Q, U, and V values are averaged for each channel The results are outputted to a new file, and plotted

13. AVERAGE BY CHANNEL

14. HOW TO FIND RFI? Next Step was to find channels with RFI Anything above a certain value is RFI?

15. HOW TO FIND RFI? Need to flatten spectrum while maintaining spikes Convolution Answer:

16. CONVOLUTION

17. One Up, Two Down

18. Now, anything above or below a certain value can be removed RMS of several intervals ± 6 sigma Channels with no RFI are written in a separate file FIND AND REMOVE RFI

19. AVERAGE BY TIME Go through original data and average I, Q, U, and V by time Use only channels with no RFI or NaNs Can anyone guess where the source is?

20. FILTER Pick out sources like we picked out spikes- convolution Noise created a problem Noise had to be removed first Convolution with sin(x)/x

21. FILTER BeforeAfter

22. CONVOLUTION AGAIN Still problems 1 up, 2 down didn’t work Tried several different functions Settled on 1 up, 4 down

23. Calculated theoretical sigma.017 K Only used the I data from this point on ±8 Sigma PICK OUT INDIVIDUAL SOURCES

24. FIT GAUSSIANS TO SOURCES Find what points to use 8 points taken on either side to form Gaussian 5 points taken on either side 28 points away for a baseline

25. FIT GAUSSIANS TO SOURCES Program created by GMRT scientists using Numerical Recipes Needed estimates of position, height, width of Gaussian, and slope and y-intercept of baseline Used width from slope of line fitted earlier Calculated the other parameters for each source Final fitted parameters are then returned

26. GENERATE SOURCE LIST Sources are sorted into two lists The scan direction, position, time, fit parameters, and chi squared are listed for each source JD Beam Source Direction RA DEC Time A W Chisq 54704 beam0 Source 4 Down 31.44833374 33.04096985 7578.803711 0.642669 1.262841 0.000213 54704 beam0 Source 5 Down 31.70193291 33.02297592 7639.703613 5.308535 1.31514 0.002747 54704 beam0 Source 6 Up 31.8161869 32.97714615 7667.099121 0.406619 2.01089 0.00019 54704 beam0 Source 7 Down 31.93537903 33.12375641 7695.759277 0.684071 1.468946 0.000137

27. REPEAT FOR EACH DAYS DATA All this was done for just one day and one beam of ALFA Next step to run the program on multiple days Run two levels up, with a list of file names JD and beam number are included in the final source list Sources sorted by RA

28. FUTURE WORK Still a lot of work to do The extended sources need to be fitted with multiple Gaussians Program needs to be run on the full data set Fluxes need to be calculated for each source Variability of sources needs to be analyzed All this needs to be done for Q, U, and V, as well as I

29. LIGHTNING

30. BREAKING NEWS…

31. QUESTIONS?

32. REFERENCES Altschluer 1990 Wagner and Witzel 1995 http://www.ucalgary.ca/ras/GALFACTS http://en.wikipedia.org/wiki/Convolution