Evryscope Science: Exploring the Potential of All-Sky Gigapixel-Scale Telescopes
Bibliographic record
Abstract
Low-cost mass-produced sensors and optics have recently made it feasible to build telescope arrays which observe the entire accessible sky simultaneously. In this article, we discuss the scientific motivation for these telescopes, including exoplanets, stellar variability, and extragalactic transients. To provide a concrete example we detail the goals and expectations for the Evryscope, an under-construction 780 MPix telescope which covers 8660 sq. deg. in each 2-minute exposure; each night, 18,400 sq. deg. will be continuously observed for an average of ≈6 hr. Despite its small 61 mm aperture, the system's large field of view provides an étendue which is ∼10% of LSST. The Evryscope, which places 27 separate individual telescopes into a common mount which tracks the entire accessible sky with only one moving part, will return 1%-precision, many-year-length, high-cadence light curves for every accessible star brighter than ∼16th magnitude. The camera readout times are short enough to provide near-continuous observing, with a 97% survey time efficiency. The array telescope will be capable of detecting transiting exoplanets around every solar-type star brighter than mV = 12, providing at least few-millimagnitude photometric precision in long-term light curves. It will be capable of searching for transiting giant planets around the brightest and most nearby stars, where the planets are much easier to characterize; it will also search for small planets nearby M-dwarfs, for planetary occultations of white dwarfs, and will perform comprehensive nearby microlensing and eclipse-timing searches for exoplanets inaccessible to other planet-finding methods. The Evryscope will also provide comprehensive monitoring of outbursting young stars, white dwarf activity, and stellar activity of all types, along with finding a large sample of very-long-period M-dwarf eclipsing binaries. When relatively rare transients events occur, such as gamma-ray bursts (GRBs), nearby supernovae, or even gravitational wave detections from the Advanced LIGO/Virgo network, the array will return minute-by-minute light curves without needing pointing toward the event as it occurs. By coadding images, the system will reach V ∼ 19 in 1-hr integrations, enabling the monitoring of faint objects. Finally, by recording all data, the Evryscope will be able to provide pre-event imaging at 2-minute cadence for bright transients and variable objects, enabling the first high-cadence searches for optical variability before, during and after all-sky events.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".