Identification of Fermi-LAT Gamma-ray Sources Roberto P . Mignani - - PowerPoint PPT Presentation

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Jun 04, 2023 284 likes •510 views

Identification of Fermi-LAT Gamma-ray Sources Roberto P . Mignani INAF-Istituto di Astro fi sica Spaziale, Milan (Italy) Janusz Gil Institute of Astronomy, Zielona Gora (Poland) Fermi-LAT Collaboration

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Identification

Fermi-LAT Gamma-ray Sources

Roberto P . Mignani

INAF-Istituto di Astrofisica Spaziale, Milan (Italy) Janusz Gil Institute of Astronomy, Zielona Gora (Poland) Fermi-LAT Collaboration

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γ e- e+

CsI Calorimeter Si Tracker segmented scintillator tiles

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SAS-2

COS-B CGRO Fermi

3 sources 25 sources 271 sources 1783 sources (in 2 yr)

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3rd Fermi LAT Gamma-ray Source Catalogue (3FGL)

Produced out of the first 4 years of operation (Acero+ 2015). 3033 sources above 4σ
Associated: X-matches with master catalogues.

Catalogues may be non homogeneous, outdated,

incomplete. Chance coincidence probability.
Identified: Correlated radio/optical/X-ray variability

(AGNs, Novae), orbital modulation (XRBs), pulsation (PSRs), extension (SNR,PWN). Multi-λ observations not always simultaneous!

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X-ray map of the

γ-ray error box Optical map of the X-ray sources Optical identification

X-ray counterpart

classification γ-ray source identification

Spectral Index Curvature Index Variability Index

PSR AGN PSR PSR AGN AGN

Classification with decision-tree, linear regression, neural network techniques based on γ-ray source characteristics Templates from identified or associated γ-ray sources. Pulsar/AGN templates Variability most efficient discriminator Some sources do not fit either template. New, unexpected γ-ray source classes discovered (e.g. novae). Multi-λ follow-ups needed to validate classification methods, solve doubtful cases, find new templates Multi-wavelength phenomenology to be added to the classification criteria riability most efficient di Var me sources do no Som t d N

the

iscriminator ither template. ent di

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AGN

PSR PSR !

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– ⇒ – ⇒

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HOW TO CLASSIFY THE X-RAY SOURCE ?

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Optical/X-ray follow up program of a sample of unassociated 3FGL sources with the

VLT and XMM-Newton (Mignani, Nonino+ 2016)

Dozen γ-ray sources selected from X-ray coverage and γ-ray error box size (<16’)
XMM-Newton ~30 ks FF exposures +

Sequence of 4xBVI VLT/VIMOS

bservations (2400s/filter/tile)
Two γ-ray sources have X-ray

counterparts associated with optical sources with periodic (~hrs) flux modulations.

Tentative identification as binary MSPs. Periodicity confirmed by Romani&Shaw 2011;

Romani+2012. γ-ray pulsations detected later (Pletsch+ 2013; Ray+)

Again, γ-ray source identification easier thanks to the optical period
Identification more difficult for those γ-ray sources without optical timing signature
MW identification approach is consolidated but hands-on doable in a few cases only
We need an automatic γ-ray source identification approach+algorithm.
Is it at all realistic with present data and technology?

1FGL J1311.7-3429 1FGL J2339.7-0531

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