Gamma-ray blazars Stefan Larsson Dalarna University and KTH for - - PowerPoint PPT Presentation

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Gamma-ray blazars Stefan Larsson Dalarna University and KTH for - - PowerPoint PPT Presentation

Oct 08, 2023 861 likes •1.06k views

Gamma-ray blazars Stefan Larsson Dalarna University and KTH for the Fermi-LAT collaboration Blazars Blazars are AGN with a relativistic jet pointing towards our line of sight Doppler boosting: Bright and rapidly variable Boston University

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Gamma-ray blazars

Stefan Larsson Dalarna University and KTH for the Fermi-LAT collaboration

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Lund 2020 Stefan Larsson

Blazars

Blazars are AGN with a relativistic jet pointing towards our line of sight Doppler boosting: Bright and rapidly variable

Boston University 
 Blazar Research Group http://www.bu.edu/blazars/bllac_files/agn_nature_cam3_360sqpix.mov

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Lund 2020 Stefan Larsson

Fermi-LAT Sky map (9 years)

> 5000 point sources

Energy range 100 MeV - 300 GeV

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Lund 2020 Stefan Larsson

Blazar variability

✦ Periodicities? ✦ Gravitational lensing ✦ 3C279: ~5 minute time scale variability ✦ rms - flux relation? ✦ Radio - gamma-ray correlation

Variability and MW Correla*ons: A few examples

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Lund 2020 Stefan Larsson

Fermi-LAT light curves

Lott et al (2012)

monthly (2FGL) adaptive (σ=25%)

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Lund 2020 Stefan Larsson

Blazar periodicities?

PG1553+113: A quasi-periodic flux modulation? (Ackermann et al 2015 ApJL 813 L41) P ~2 years?

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Lund 2020 Stefan Larsson

Blazar periodicities?

54000 55000 56000 57000 58000 59000 MJD 5.0×10-9 1.0×10-8 1.5×10-8 2.0×10-8 2.5×10-8 3.0×10-8 Flux (E > 1 GeV) [ cm-2 s-1 ]

Preliminary PG1553+113: A quasi-periodic flux modulation: Yes Cutini et al (in preparation) BH binary?

  • Accr. disc QPO?
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Lund 2020 Stefan Larsson

B0218+357: A gravitationally lensed blazar

Lag = 10.5 ± 0.4 d data 
 (Biggs et al 1999)

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(Cheung et al 2014 ApJL 782 L14)

B0218+357: A gravitationally lensed blazar

Lag = 10.5 ± 0.4 d 
 (Biggs et al 1999) Biggs & Browne (2018) reanalysis => Lag = 11.3 ± 0.2 d => H0 = 72.9 ± 2.6 km s−1 Mpc−1

Autocorrelation analysis of Fermi- LAT data

50 100 150 200 250 F

γ (10 −6 photons cm −2s −1)

1 2 3 4 5

Flaring Interval

1−day bins

Fermi ToO pointing

pre 1st 2nd 3rd post

2012 Jun 22 − 2013 Mar 14

T (MJD − 56100 days)

Lag = 11.46 ± 0.16 d

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Lund 2020 Stefan Larsson

3C 279: Rapid variability

In bright states a few sources have shown variability on time scales of 10 minutes or less.(Ackermann et al 2016))

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3C 279 Power Density Spectrum

Also the Power Density Spectrum differ between the two epochs
 (Ackermann et al 2016)

µ

a b

  • -
  • D

Second 3.5 year epoch 2015 outburst (~2 weeks) First 3.5 year epoch

3C 279 Overlapping PDS is consistent with constant RMS/Flux

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3C 279 RMS-Flux (> 100 MeV) for the first (+) and second (diamonds) 3.5 years of Fermi-LAT observations (flux binned)

P r e l i m i n a r y

Non/slowly variable component?

The RMS-Flux relation at gamma-ray energies

(ph cm-2 s-1) (ph cm-2 s-1)

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RMS - Flux relation in X-rays

Fig.2. Left Panel rms-flux relationship for Cyg X-1 [22]

Uttley & McHardy,2001,MNRAS,323,L26

6 8 10 12 14 0.5 1 1.5 2 2.5 RMS FLUX 1 1.5 2 2.5 3 0.2 0.4 0.6 0.8 RMS FLUX

Fig.5. Left Panel rms-flux relationship for 3C273 derived from the X-ray lightcurve shown in Fig.4.

3C 273 3C 279

McHardy (2008)

A linear relation is well established for X-ray binaries. Consistent with accretion disc models Suggested also in X-rays for 3C 273 and 3C 279. But origin of the X-ray emission is unclear.

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The RMS - Flux relation and jet models

Marscher (2014)

In addition to power spectra, the RMS-Flux relation should also be used as a test of models

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statistical Discrete Cross-Correlation Function analysis

The method in brief:

DCCF

2e-07 4e-07 6e-07 8e-07 flux (E>100 MeV) [ph cm

  • 2 s
  • 1]

Fermi-LAT

J1159+2914

54800 55000 55200 55400 55600 55800 MJD 1 2 3 4 flux density [Jy]

0.8 mm 2 mm 3 mm 7 mm 9 mm 13 mm 20 mm 28 mm 36 mm 60 mm 110 mm

relative timing of flares

  • 600
  • 1.0
  • 0.5

0.0 0.5 1.0 1.5

J1159+2914

  • 600
  • 400
  • 200

200 400 600 LAG (Days)

  • 1.0
  • 0.5

0.0 0.5 1.0 1.5 DCCF

Radio - Gamma-ray correlation

Fuhrmann et al (2014)

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statistical Discrete Cross-Correlation Function analysis

The method in brief:

DCCF

2e-07 4e-07 6e-07 8e-07 flux (E>100 MeV) [ph cm

  • 2 s
  • 1]

Fermi-LAT

J1159+2914

54800 55000 55200 55400 55600 55800 MJD 1 2 3 4 flux density [Jy]

0.8 mm 2 mm 3 mm 7 mm 9 mm 13 mm 20 mm 28 mm 36 mm 60 mm 110 mm

relative timing of flares

  • 600
  • 1.0
  • 0.5

0.0 0.5 1.0 1.5

J1159+2914

  • 600
  • 400
  • 200

200 400 600 LAG (Days)

  • 1.0
  • 0.5

0.0 0.5 1.0 1.5 DCCF

Stacking (54 sources)

Stacked DCCF

  • 600
  • 400
  • 200

200 400 600

  • 0.2
  • 0.1

0.0 0.1 0.2 0.3 0.4 DCCF

Highly significant average correlation for the sample

Radio - Gamma-ray correlation

Fuhrmann et al (2014)

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Radio - Gamma-ray correlation

  • 400
  • 200

200 400 LAG (Days)

  • 0.5

0.0 0.5 1.0 1.5 2.0 DCCF

50 100 150 200 250 300 350 frequency [GHz] 20 40 60 80 100 time lag [days] τ = Α + Βν

−1

0.5 1 1.5 2 2.5 log (frequency) 0.3 0.6 0.9 1.2 1.5 1.8 2.1 log (time lag)

0.8 mm 11 cm

Fuhrmann et al (2014) Radio time lag as a function of radio frequency

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In summary: The regular sampling and essentially continuous coverage of Fermi-LAT light curves over more than a decade allow us to conduct detailed statistical studies of variability and multi wavelength relations for blazars. Analysis of blazar light curves provides information on the structure and dynamics of AGN jets.

Summary