Blade Runner -What kind objects are there in the JVO ALMA Archive?-

TL;DR

This paper introduces 'Blade Runner,' a Java tool that cross-identifies sources in the JVO ALMA Archive with external databases like SIMBAD to enhance data search capabilities based on astronomical object names.

Contribution

The paper presents a new software tool that improves source identification in the ALMA archive by integrating external astronomical databases, enabling more flexible data searches.

Findings

Successful development of the 'Blade Runner' application

Preliminary source identification results in the archive

Enhanced search capabilities for astronomical objects

Abstract

The JVO ALMA Archive provides users one of the easiest ways to access the ALMA archival data. The users can have a quick look at a 3 or 4-dimensional data cube without downloading multiple huge tarballs from a science portal of ALMA Regional Centers (ARCs). Since we just synchronize all datasets with those of ARCs, the metadata are identical to the upstream, including ``target name'' for each dataset. The name is not necessarily a common one like NGC numbers, but sometimes one of sequential numbers assigned in an observation proposal. Compilation of these artificial names into astronomical ones could provide users more flexible and powerful search interfaces; for instance, with the knowledge of the redshift for each source, the users can easily find the datasets which observed their interested emission/absorption lines at not the observer frame but the rest frame, fitting well with theoretical studies. To implement this functionality, cross-identification of all the sources in our archive with those in some other astronomical databases such as NED and SIMBAD is required. We developed a tiny Java application named ``Blade Runner'' for this purpose. The program works as a crawler for both the JVO ALMA Archive and SIMBAD, storing all information onto a SQLite-based database file; this portable design enables us to communicate results to each other even under different computing environments. In this paper, we introduce its software design and our recent work on the application, and report a preliminary result on the source identification in our archive.