fallingstar-data.com

What It Is

ATLAS Forced Photometry is the forced-photometry server for the ATLAS sky survey project, providing public access to the full historical ATLAS photometry archive. After registration, users can submit forced-photometry requests for any sky coordinates, upload lists of positions, or request data for moving objects by MPC name. It is not a general-purpose development platform, but a data tool for time-domain astronomy. Typical use cases include historical light-curve analysis of variable stars, transients, asteroids, and comets.

Core Capabilities and API

The service provides a REST API. Its documentation uses Python examples to demonstrate the full workflow: exchange a username and password for a token, submit RA/Dec, MJD, and other parameters to the queue with an Authorization request header, poll the task URL, download the text output from the result_url once the task is complete, and parse it with pandas if needed. The API is built around an asynchronous queue, making it suitable for batch scripting and automated processing. The documentation also notes that overly frequent requests may trigger 429 rate limits, and that result URLs may expire.

Data and Ecosystem

ATLAS consists of multiple 0.5m telescopes and performs high-cadence all-sky surveys using cyan and orange filters, with magnitudes reported in the AB system. The project is closely connected with the ATLAS homepage, the Minor Planet Center, the IAU Transient Name Server, GitHub Issues, and the academic citation ecosystem. The FAQ provides fairly specialized explanations of topics such as negative flux in difference images, step changes caused by template replacement, MPC packed designations for Solar System objects, and bad-pixel filtering criteria. Overall, the documentation quality is strong for its target research users.

Pricing, Open Source, and Support

The main documentation states that it provides full public access and is available after registration. No paid plans, payment methods, or commercial pricing were found. The project describes itself as an open-source volunteer project; issues can be submitted via GitHub, and urgent or security-related matters can be sent to the maintainers by email. However, this also means support is closer to that of an academic open-source project, with no visible SLA, enterprise support, or stability guarantees.

Pros, Cons, and Who It’s For

Its main strengths are scarce, long-baseline data and complete API examples, making it well suited to automated research workflows. The drawbacks are that users need a background in astronomical photometry, and crowded fields, bad weather, template changes, and similar factors can affect interpretation. Users must handle their own data cleaning. It is best suited to astronomy researchers, PhD students, survey-data analysts, and research teams that need light curves in bulk. The source text does not provide information on access from China; network connectivity, registration emails, and download speeds need to be tested in practice. If access is limited, alternatives such as ZTF, Pan-STARRS, Gaia, ASAS-SN, or MAST may be worth considering.