Paper detail

Young Stellar Object Variability (YSOVAR): Long Timescale Variations in the Mid-Infrared

The YSOVAR (Young Stellar Object VARiability) Spitzer Space Telescope observing program obtained the first extensive mid-infrared (3.6 & 4.5 um) time-series photometry of the Orion Nebula Cluster plus smaller footprints in eleven other star-forming cores (AFGL490, NGC1333, MonR2, GGD 12-15, NGC2264, L1688, Serpens Main, Serpens South, IRAS 20050+2720, IC1396A, and Ceph C). There are ~29,000 unique objects with light curves in either or both IRAC channels in the YSOVAR data set. We present the data collection and reduction for the Spitzer and ancillary data, and define the "standard sample" on which we calculate statistics, consisting of fast cadence data, with epochs about twice per day for ~40d. We also define a "standard sample of members", consisting of all the IR-selected members and X-ray selected members. We characterize the standard sample in terms of other properties, such as spectral energy distribution shape. We use three mechanisms to identify variables in the fast cadence data--the Stetson index, a chi^2 fit to a flat light curve, and significant periodicity. We also identified variables on the longest timescales possible of ~6 years, by comparing measurements taken early in the Spitzer mission with the mean from our YSOVAR campaign. The fraction of members in each cluster that are variable on these longest timescales is a function of the ratio of Class I/total members in each cluster, such that clusters with a higher fraction of Class I objects also have a higher fraction of long-term variables. For objects with a YSOVAR-determined period and a [3.6]-[8] color, we find that a star with a longer period is more likely than those with shorter periods to have an IR excess. We do not find any evidence for variability that causes [3.6]-[4.5] excesses to appear or vanish within our data; out of members and field objects combined, at most 0.02% may have transient IR excesses.

preprint2014arXivOpen access
0citations
0reviews
0saves
Nocode
Nodataset
0institutions

Next steps

Decide what to do with this paper

Use like or dislike for the fast social read. The more specific scholarly feedback stays available below when needed.

Log in to curate

Reading frame

Keep the important context close to the paper

Keep the important signals around this paper in one place: votes, save state, collection context, reviews and the metadata you need before deciding what to do next.

Add specific reaction

Move through the context

Research map

Open full explorer

Move through nearby people, institutions, topics and adjacent work without leaving the paper page.

Building this graph slice

BZPEER is loading the nearby papers, people, topics and institutions for this page.

Structured reviews

0 review(s)

ContributeLeave structured feedbackUse the review template when you have a concrete strength, concern or method question.Open review form

No structured reviews yet. High-signal critique starts here.

Work discussion

0 comment(s)

DiscussAdd a high-signal commentKeep quick notes, caveats and replication pointers separate from formal reviews.Open comment form

No discussion yet. The first strong comment sets the tone.