KMTNet 南天广域巡天第三卷：第一数据释放
KMTNet Synoptic Survey of Southern Sky III: The First Data Release
AI总结：
KMTNet 南天广域巡天首次发布数据释放，提供4000平方度的科学级数据，包含深度图像和两个源目录，支持多种天体物理研究。
摘要：
我们呈现了KMTNet南天广域巡天（KS4）的第一公众数据释放（DR1）。该深广域成像调查利用三台1.6米望远镜，在B、V、R和I波段覆盖南天-85° < 经度 < -28.8°区域。尽管主要设计用于提供引力波对应物识别的参考成像，DR1为约4000平方度提供了科学级数据，支持广泛天体物理研究。该释放包含深度叠加图像，达到中位5σ深度22.0-23.5 AB magnitude。它附带两个源目录，包含超过2亿个源，SNR>5：一个I波段选择的强制光度目录，优化一致的颜色，和一个合并波段目录，提供增强的完整性。验证显示数据质量稳健，以Gaia DR3为基准，平均天体测量偏移为RA +0.054 ± 0.129 arcsec，Dec -0.015 ± 0.120 arcsec。光度统一性在97.5-99.8%的区域内保持在±0.03 mag以内。KS4的关键优势是其统一且连续的空间覆盖。它比其他统一调查更暗，同时填补现有深数据集中的不规则空缺。所有数据产品通过CDS和NOIRLab的Astro Data Lab公开发布。
英文摘要：
We present the first public data release (DR1) of the KMTNet Synoptic Survey of Southern Sky (KS4). This deep, wide-field imaging survey covers a southern footprint of -85$^{\circ}$ < Decl. < -28.8$^{\circ}$ in the $B$, $V$, $R$, and $I$ bands using a network of three 1.6-m telescopes. Although primarily designed to secure reference imaging for gravitational wave counterpart identification, DR1 delivers science-ready data for $\sim$4,000 deg$^{2}$ to enable a broad range of astrophysical research. The release includes deep co-added images reaching median 5$σ$ depths of 22.0-23.5 AB mag. It is accompanied by two source catalogs containing over 200 million sources with SNR $>5$: an $I$-band-selected forced-photometry catalog optimized for consistent colors, and a band-merged catalog offering enhanced completeness. Validation demonstrates robust data quality, characterized by mean astrometric offsets of $+0.054 \pm 0.129$ arcsec in RA and $-0.015 \pm 0.120$ arcsec in Dec relative to Gaia DR3. {\refbf Photometric uniformity for point sources is maintained within $\pm 0.03$ mag relative to Gaia XP for 97.5--99.8\% of the footprint across all four bands.} A key advantage of KS4 is its uniform and contiguous spatial coverage. It extends to fainter magnitudes than other uniform surveys while filling irregular gaps in existing deep datasets. All data products are publicly available via the CDS and NOIRLab's Astro Data Lab.
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