A Rapidly Declining Transient Discovered with the Subaru/Hyper Suprime-Cam
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
We perform a high-cadence transient survey with the Subaru Hyper Suprime-Cam (HSC), which we call the Subaru HSC survey Optimized for Optical Transients (SHOOT). We conduct HSC imaging observations with time intervals of about one hour on two successive nights, and spectroscopic and photometric follow-up observations. A rapidly declining blue transient SHOOT14di at z = 0.4229 is found in observations on two successive nights using an image-subtraction technique. The rate of brightness change is +1.28(-0.20)(+0.40) mag day(-1) (+1.83(-0.39)(+0.57) day(-1)) in the observer (rest) frame and the rest-frame color between 3400 and 4400 angstrom is M-3400 (angstrom)-M-4400 (angstrom) = -0.4. The nature of the object is investigated by comparing its peak luminosity, decline rate, and color with those of transients and variables previously observed, and with those of theoretical models. None of the transients or variables share the same properties as SHOOT14di. Comparisons with theoretical models demonstrate that, while the emission from the cooling envelope of a SN IIb shows a slower decline rate than SHOOT14di, and the explosion of a red supergiant star with a dense circumstellar wind shows a redder color than SHOOT14di, the shock breakout at the stellar surface of the explosion of a 25M(circle dot) red supergiant star with a small explosion energy of <= 0.4 x 10(51) erg reproduces the multicolor light curve of SHOOT14di. This discovery shows that a high-cadence, multicolor optical transient survey at intervals of about one hour, and continuous and immediate follow-up observations, is important for studies of normal core-collapse supernovae at high redshifts.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 it