GrailQuest: hunting for atoms of space and time hidden in the wrinkle of Space-Time
Bibliographic record
Abstract
Abstract GrailQuest(Gamma Ray Astronomy International Laboratory for QUantum Exploration of Space-Time) is a mission concept based on a constellation (hundreds/thousands) of nano/micro/small-satellites in low (or near) Earth orbits. Each satellite hosts a non-collimated array of scintillator crystals coupled with Silicon Drift Detectors with broad energy band coverage (keV-MeV range) and excellent temporal resolution (≤ 100 nanoseconds) each with effective area $\sim 100 \text {cm}^{2}$ ∼100cm2 . This simple and robust design allows for mass-production of the satellites of the fleet. This revolutionary approach implies a huge reduction of costs, flexibility in the segmented launching strategy, and an incremental long-term plan to increase the number of detectors and their performance; this will result in a living observatory for next-generation, space-based astronomical facilities.GrailQuestis conceived as an all-sky monitor for fast localisation of high signal-to-noise ratio transients in the X-/gamma-ray band, e.g. the elusive electromagnetic counterparts of gravitational wave events. Robust temporal triangulation techniques will allow unprecedented localisation capabilities, in the keV-MeV band, of a few arcseconds or below, depending on the temporal structure of the transient event. The ambitious ultimate goal of this mission is to perform the first experiment, in quantum gravity, to directly probe space-time structure down to the minuscule Planck scale, by constraining or measuring a first-order dispersion relation for lightin vacuo. This is obtained by detecting delays between photons of different energies in the prompt emission of Gamma-Ray Bursts.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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 source (direct Gemma or distilled Codex), 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".