A statistical approach to recognizing source classes for unassociated sources in the first Fermi-LAT catalog
read more
Citations
The second fermi large area telescope catalog of gamma-ray pulsars
Fermi Large Area Telescope Fourth Source Catalog Data Release 2
The first fermi lat supernova remnant catalog
The cosmic evolution of Fermi BL Lacertae objects
Gamma-ray binaries and related systems
References
Applied Logistic Regression
Classification and Regression Trees.
The Large Area Telescope on the Fermi Gamma-ray Space Telescope Mission
The Likelihood Analysis of EGRET Data
Related Papers (5)
Fermi Large Area Telescope Second Source Catalog
Fermi large area telescope first source catalog
The Large Area Telescope on the Fermi Gamma-ray Space Telescope Mission
The second catalog of active galactic nuclei detected by the Fermi Large Area Telescope
The wide-field infrared survey explorer (wise): mission description and initial on-orbit performance
Frequently Asked Questions (12)
Q2. Why are the hardness ratios preferred for this analysis?
Since the hardness ratios provide more information about spectral shape than the spectral index, they are preferred for this analysis.
Q3. What is the spectral index of a power-law fit?
because pulsar spectra are not well described by power laws, the spectral index of a power-law fit is not a good discriminator between pulsar and AGN classes.
Q4. What is the predictor distribution for the 24 sources that were not used during the training procedure?
The predictor distribution for the 24 sources that were not used during the training procedure can be used to estimate the further contamination from these sources to the AGN and pulsar candidate distributions.
Q5. How many pulsars were found using blind frequency searches?
Of the 56 pulsars listed in 1FGL, 24 were discovered using blind frequency searches (Abdo et al. 2009d) for γ -ray pulsations from the bright unassociated sources.
Q6. How many sources are correctly classified as AGN candidates?
For AGNs, the authors find that 126 sources are correctly classified as AGN candidates by the CT analysis (efficiency: 71%), 11 were classified as pulsar candidates (false negative: 6%), while the remaining 40 sources were considered still unclassified (23%).
Q7. What was the first step forward for the detection and identification of high-energy ray?
A major step forward for detection and identification of highenergy γ -ray sources came when the Gamma-ray Large Area Space Telescope was launched on 2008 June 11.
Q8. Why do the pulsars have a correlation between the curvature index and?
the broken power-law spectral forms of bright blazars (e.g., Ackermann et al. 2010) also have the effect of inducing a correlation between curvature index and flux for LAT blazars.
Q9. How many of the newly classified AGN candidates will belong to the other classes?
the authors expect that up to 2% of the newly classified AGN candidates and up to 4% of the newly classified pulsar candidates will indeed belong to one of the “other” classes (galaxies, globular clusters, supernova remnants, etc.).
Q10. What is the probability of association with a particular class of sources?
LR evaluates the probability of association with a particular class of sources as a function of the independent variables (e.g., spectral shape or variability).
Q11. What is the probability that an unassociated source is an AGN?
Since the LR analysis used AGNs as primary source type, the output parameter (A) listed in Table 4 describes the probability that an unassociated source is an AGN.
Q12. How many of the 77 correlated positions were genuine?
they used only the ROSAT Bright Source Catalog as a reference and found, on statistical grounds, that 60 of the 77 correlated positions should be genuine associations.