Fermi Source Analyses and Identifying VERITAS Candidates

Transcription

1 Fermi Source Analyses and Identifying VERITAS Candidates University of California, Berkeley

2 2 Overview Introduction VERITAS Fermi Analysis Likelihood Doppler Factor Estimation Motivations Blazars Open Questions Sources 3FGL J FGL J B

3 3 Overview Introduction VERITAS Fermi Analysis Likelihood Doppler Factor Estimation Motivations Blazars Open Questions Sources 3FGL J FGL J B

4 4 VERITAS Very Energetic Radiation Imaging Telescope Array System Atmospheric Cherenkov Radiation Telescopes Maximum sensitivity from 85 GeV 10 TeV Three level trigger system (pixel, pattern, array)

5 5 Fermi Telescope Fermi Large Area Telescope Uses pair conversion instruments Detection range from 20 MeV GeV First trigger is detection in three planes, followed by an anticoincidence systems

6 6 Overview Introduction VERITAS Fermi Analysis Likelihood Doppler Factor Estimation Motivations Blazars Open Questions Sources 3FGL J FGL J B

7 7 Blazars Thermal processes alone cannot create γ-rays Disk-dominated AGNs Jet-dominated AGNs SEDs show two distinct peaks

8 8 Cosmology, Structure Formation, Space-Time, and Dark Matter Extragalactic Background Light constrains galactic formation history TeV γ-rays annihilate and pair produce on EBL absorption feature in blazar spectra TeV photon annihilation should result in GeV emission in blazar spectra. Not actually observed Intergalactic Magnetic Fields Blazar Heating Burst variability could constrain energy-dependent speed of light c 2 p 2 = E ξe + ηe2 E QG E QG 2 + Δt = ξ E E QG L c γ-ray energies well suited for dark matter particle candidate searches Finding possible sources for ultra high energy cosmic rays

9 9 Overview Introduction VERITAS Fermi Analysis Likelihood Doppler Factor Estimation Motivations Blazars Open Questions Sources 3FGL J FGL J B

10 10 Fermi Likelihood Analysis Likelihood (L): probability of observing detected counts in a bin L = e N exp i m i N exp = total number of counts model predicts m i = expected number of counts in i-th bin Test Statistic (TS): 2ln L null L ; σ 2 Spectral Model Used: dn de = N 0( E E 0 ) γ Prefactor = N 0 Index = γ Scale = E 0

11 11 Doppler Factor Estimations Variability time scales can be calculated using light curve data during flares F t = F C + F 0 2 (t t 0) t var F c = average source flux F 0 = flux of flare at t 0 t var = variability time scale δ σ Td L 2 5hc z 2α F 1keV t var E γ GeV α 1 4+2α σ T = Thomson cross section d L = luminosity distance α = X-ray spectral index E γ = highest energy photon F 1keV = X-ray flux in μjy

12 12 Overview Introduction VERITAS Fermi Analysis Likelihood Doppler Factor Estimation Motivations Blazars Open Questions Sources 3FGL J FGL J B

13 13 Population Studies Compared integrated fluxes to Crab Nebula Flux N0 ( E ) γ de E 0 F = Eth N 0 = Flux Density E 0 = Pivot Energy E th = 80 GeV γ = Spectral Index

14 14 3FGL J TS Map > 5% Crab Nebula Flux RA: 12h 50m s DEC: Energy range: 5 GeV 100 GeV Time range: Sep 2008 Sep 2010 Source region radius: 10 0 ROI radius: 5 0

15 15 3FGL J TS Map > 5% Crab Nebula Flux RA: 12h 50m s DEC: Energy range: 5 GeV 100 GeV Time range: Sep 2008 Sep 2010 Source region radius: 10 0 ROI radius: 5 0

16 16 5BZB J Counts Map BL Lac object in catalog BZCAT5 RA: 12h 46m s DEC: Redshift (z): 0.386

17 17 3FGL J TS Map > 2% Crab Nebula Flux RA: 22h 09m s DEC: Energy range: 5 GeV 300 GeV Time range: Sep 2008 Sep 2010 Source region radius: 10 0 ROI radius: 5 0

18 18 3FGL J Light Curve Time Range: Sep 2008 Sep 2012 Energy Range: 5 GeV 300 GeV Fixed Spectral Index: 1.13 ± energy bins Monthly bins

19 19 3FGL J Associations? Swift-XRT survey of Fermi unassociated sources find: 1RXS J away NVSS J away

20 20 B TS Map RA: 12h 17m s DEC: Energy range: 100 MeV 100 GeV Time range: Jan 2015 Jul 2015 Source region radius: 20 0 ROI radius: 10 0

21 21 B Light Curves Time Range: Jan 2015 Jul 2015 Energy Range: 100 MeV 100 GeV Fixed Spectral Index: 1.90 ± energy bins

22 22 B Light Curves Time Range: One week Energy Range: 100 MeV 100 GeV Non-Fixed Spectral Index 8 energy bins

23 23 Doppler Factor Estimations Variability time scales can be calculated using light curve data during flares F t = F C + F 0 2 (t t 0) t var F c = average source flux F 0 = flux of flare at t 0 t var = variability time scale δ σ Td L 2 5hc z 2α F 1keV t var E γ GeV α 1 4+2α σ T = Thomson cross section d L = luminosity distance α = X-ray spectral index E γ = highest energy photon F 1keV = X-ray flux in μjy

24 24 Doppler Factor Estimations Analysis by Floriana Zefi of B conducted Fermi-Lat and VERITAS detected flare in February 2014 Variability time scale derived form Fermi light curve t var = 4.5h Minimum Doppler factor δ = 5.7

25 25 Conclusion Gamma-ray sources require some form of nonthermal emission for detection Blazars are common candidate 3FGL J not convincingly detected, but analysis reveals corresponding source in ROI from different catalog 3FGL J convincingly detected. Light curve needs improvement B has significant detection. Doppler factor estimations help reveal jet properties

26 26 Acknowledgements I would like to thank Reshmi Mukherjee, Brian Humensky, and Marcos Santander for their guidance Congratulations to my fellow REU students for all of their accomplishments Thanks Mike Shaevitz, John Parsons, and Amy Garwood Brought to you by the National Science Foundation

27 27 QUESTIONS?