Fermi-LAT 16-year Source List

Abstract

The current Fermi-LAT source catalog (4FGL-DR4: 7194 sources over 14 years) was built incrementally from the 8-year catalog. In a survey mission like Fermi, data accumulate on each source over time, so after 16 years (reached in August 2024) and twice the data for the original 4FGL sources we have more precise localization (by 24% on average). It is thus time to generate a new original catalog, which implies, beyond adding the sources newly detectable after two more years, changing the existing source names (derived from their coordinates) and reviewing the associations. We present an early 16-year list (FL16Y) of 7220 sources, which relocalizes all sources and improves a few aspects of the catalog analysis, but still uses the same model of interstellar diffuse emission as 4FGL-DR4.

Figures (6)

• Figure 1: Prior sigma $\sigma_P$ for band fluxes compared to the errors in the SED calculation without priors, on DR4 sources. Left: Distributions of the ratio between $\sigma_P$ and SED error in all bands. The average ratio increases from band 1 to band 4 (best constraints), and decreases again in higher-energy bands. It is less than one (so the prior has a strong impact) in many sources in bands 1 and 2 only. The numbers in parentheses are the widths (standard deviation) of the distributions (in log$_{10}$, like the abscissa). Right: Correlation between that ratio and the spectral index in band 1 only, separately for each spectral type used in the model. For LogParabola and PLEC4, 2$-$PL_Index is replaced by the average index in $\nu F_\nu$ between band 1 and the pivot frequency $\nu_0$, i.e. $1+\ln(F_\nu(\nu_1)/F_\nu(\nu_0))/\ln(\nu_1/\nu_0)$, where $\nu_1$ is the logarithmic mid-point of the band. That quantity (intermediate between 2$-$PL_Index itself - appropriate at $\nu_0$ - and the local spectral slope at $\nu_1$) resulted in the narrowest correlation. The ratio decreases from soft to hard sources in the first band, because hard sources are constrained by higher energies.
• Figure 2: SED of 4FGL J1105.4$-$6108 (PSR J1105$-$6107) in the official DR4 catalog (left) and after applying priors (right). The effect of the priors is obvious in the first two bands. For that confused source in the Galactic plane, the very uncertain SED points in DR4 have been pulled much closer to the model prediction (dashed curve) and the errors have been reduced. The effect in the other bands (above 300 MeV) is small. The automatic Y range reacted to the differing upper limits so it is not the same in both plots.
• Figure 3: Effect of the priors on the errors in band 1 (50 to 100 MeV). It is illustrated on the upper errors (second entry in Unc_Flux_Band, toward larger fluxes), because the lower errors are truncated when the best fit is close to 0. Left: Direct correlation between the errors with priors (abscissa) and the original errors (ordinate). The dashed line is the one-to-one correlation. Essentially all points are above the line, indicating that the errors are reduced. The maximal reduction is approximately a factor ten. Right: Correlation of the relative errors (with respect to the best fit). The plot looks very different because the best fit changes as well. The effect, as expected, is largest for faint sources ($dF/F > 1$), and becomes smaller for strong ones. The very strong sources ($dF/F < 0.1$) tend to be all above the one-to-one correlation, corresponding to smaller errors with priors. This behavior is not a direct consequence of the priors, since the adopted prior sigma is always at least as large as the flux. Rather, it arises indirectly from constraining nearby faint sources from deviating excessively from their global models, as intended.
• Figure 4: Localization improvement between 4FGL and FL16Y. Left: Error radius distribution in FL16Y (solid) compared to 4FGL-DR4 (dashed), restricted to sources at low TS and high latitude (comparable). The means are $4.6\arcmin$ and $5.3\arcmin$, respectively. Right: Distribution of the ratio of error radii for the same sources in DR4 and FL16Y. The mean is 1.24.
• Figure 5: Spectral fit improvement between 4FGL DR4 and FL16Y for LS I +61 303 at TS $\simeq$ 71,000 as a single source. Left: Spectral fit with a single LogParabola in DR4. Center: Spectral fit of the main (soft) component with PLEC4 in FL16Y. Right: Spectral fit of the secondary (hard) component with a power law in FL16Y. The global TS in FL16Y increased by 42 between the two models.