Bibliographic record
Abstract
In the near future, gravitational wave (GW) detections are expected to become common, opening a new window on the Universe. Using the two 4 km Laser Interferometer Gravitational wave Observatory (LIGO) detectors and the 3 km Virgo detector we can triangulate a passing GW to a region of the sky with an area of tens of square degrees. These regions can then be observed using electromagnetic (EM) observatories. Pairing GW and EM observations can verify the astrophysical origin of a GW detection, and provide a more complete picture of the processes taking place. \n \nThis thesis describes the first triggered search for EM counterparts to GW candidates from the 2009-2010 LIGO/Virgo observing run. To improve the search strategy of this observing run, we created a catalogue of galaxies within 100 Mpc, known as the Gravitational Wave Galaxy Catalogue (GWGC), which was used to select locations in the GW skymaps to be imaged by EM partner observatories. Analysis of optical images taken as part of this run, from the Liverpool Telescope (LT) and ROTSE observatory network, find no associated counterparts. We also simulate the optical transients expected from GW sources across the LIGO/Virgo horizon of 50 Mpc, and find that the LT would be able to detect most optical counterparts across the majority of the horizon distance, while ROTSE can only detect counterparts over a fraction of the same distance. \n \nFinally, we present the design specifications of GOTO, a wide field-of-view observatory to image the skymaps expected to be produced by the next generation of GW detectors. This telescope will be able to cover ∼70 square degrees to a limiting magnitude of ∼21, the sky area and limiting magnitude required to offer a reasonable chance of detecting an EM counterpart. While NS-NS merger models are uncertain, a tentative first detection of a kilonova-like counterpart to GRB130603B leaves us optimistic that the advanced detector era will provide the first GW detections and EM counterparts.
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.
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 | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".