# 1FLAT.fits

This dataset is associated with the paper:

📄 **[1FLAT: a Firmamento-based catalog of AGN in Fermi-LAT high-Galactic-latitude γ-ray sources](https://arxiv.org/abs/2510.06962)**

## Description

**1FLAT.fits** is the first Firmamento–LAT AGN table derived from an independent reassessment of **5,062** high-Galactic-latitude (|b| ≥ 10°) γ-ray sources in **Fermi-LAT 4FGL-DR4**, using the [Firmamento](https://firmamento.nyuad.nyu.edu/home) multi-frequency discovery platform with human-in-the-loop validation. The catalog provides updated/confirmed associations and new candidates, plus homogeneous estimates of the **synchrotron-peak frequency** and **peak flux** for blazars.

### Key outcomes (from the paper)
- Agreement with 4FGL/4LAC in **4,493 cases (88.8%)**.  
- **421** new blazar associations for previously unassociated 4FGL sources.  
- **64** alternative blazar associations where 1FLAT prefers a different counterpart.  
- **49** cases where the 4FGL/4LAC association is not confirmed by 1FLAT.  
- **854** sources remain without a plausible counterpart (confirmed “no-counterpart” cases).

These results significantly reduce the fraction of unidentified extragalactic LAT sources at high latitude and furnish uniform blazar SED peak metrics for population studies. 

## File and Format

- **File:** `1FLAT.fits`  
- **Type:** FITS binary table (HDU 1)  
- **Rows:** one per 4FGL high-latitude source
- **Access:** Readable with common astronomy tools (e.g., `astropy.io.fits`). Column names are sanitized (letters/digits/underscores). 

## Main Fields (selected)

**1FLAT layer**
- `1FLAT_name` — Firmamento identifier (e.g., `1FLAT JHHMMSS.s±DDMMSS`); for unassociated sources this mirrors the 4FGL source.  
- `RAJ2000`, `DEJ2000` — J2000 coordinates (association or, for unassociated, 4FGL position).  
- `CLASS` — Blazar SED class: `LSP`, `IBL`, `HSP`, or `galaxy` / `uncertain`. Thresholds:  
  - `log10(ν_peak/Hz) < 13.5` (LSP), `13.5 ≤ log10(ν_peak/Hz) < 15` (IBL), ` log10(ν_peak/Hz) ≥ 15` (HSP).  
- `nu_syn`, `nuFnu_syn` — Synchrotron-peak frequency (log10 Hz, observer frame) and peak νFν (log10 erg cm⁻² s⁻¹), estimated with **W-Peak**; BLAST estimates are used for validation.  
- `TAG` — Classification tag summarizing agreement/novelty (e.g., `BLAZAR confirmed`, `BLAZAR new`, `BLAZAR different`, `NOC confirmed`, `UNCERTAIN`, etc.). :contentReference[oaicite:4]{index=4}

**4FGL-DR4 provenance**
- `4FGL_Source_Name`, `4FGL_ASSOC1/CLASS1`, `4FGL_ASSOC2/CLASS2`  
- `4FGL_Signif_Avg`, `4FGL_PL_Index`, `4FGL_Energy_Flux100`, `4FGL_Frac_Variability`, `ASSOC_PROB_BAY`, `ASSOC_PROB_LR`.
- 
**4LAC-DR3 provenance**
- `4LAC_ASSOC1`, `4LAC_CLASS`, `4LAC_nu_syn`, `4LAC_nuFnu_syn`. 

> See the paper’s Appendix D/Table 6–7 for a full column dictionary and allowed values. 

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## Quick Start (Python)

```python
from astropy.io import fits
import numpy as np
import pandas as pd

hdul = fits.open("1FLAT.fits")
data = hdul[1].data
# Convert to DataFrame (handle FITS endian)
df = pd.DataFrame(np.array(data).byteswap().newbyteorder())

# Example: list newly discovered blazars with their peak metrics
new_blazars = df[df["TAG"] == "BLAZAR new"][
    ["1FLAT_name", "RAJ2000", "DEJ2000", "CLASS", "nu_syn", "nuFnu_syn"]
].sort_values("1FLAT_name")
print(new_blazars.head())