Chitah: STRONG-GRAVITATIONAL-LENS HUNTER IN IMAGING SURVEYS

Why is this work in the frame?

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Full frame distilled prediction

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.

Candidate categories

none

Consensus categories

none

Domain

Candidate signal: noneConsensus signal: none

Study design

Candidate signal: ObservationalConsensus signal: Observational

Genre

Candidate signal: EmpiricalConsensus signal: Empirical

Teacher disagreement score

0.012

Threshold uncertainty score

0.523

Validation status

machine_predicted_unvalidated · codex-gemma-dda1882f352a

Codex and Gemma teacher scores by category

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.

Teacher spread

0.225 · how far apart the two teachers sit on this one work

Validation status

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

Abstract

Strong gravitationally lensed quasars provide powerful means to study galaxy evolution and cosmology. Current and upcoming imaging surveys will contain thousands of new lensed quasars, augmenting the existing sample by at least two orders of magnitude. To find such lens systems, we built a robot, CHITAH, that hunts for lensed quasars by modeling the configuration of the multiple quasar images. Specifically, given an image of an object that might be a lensed quasar, CHITAH first disentangles the light from the supposed lens galaxy and the light from the multiple quasar images based on color information. A simple rule is designed to categorize the given object as a potential four-image (quad) or two-image (double) lensed quasar system. The configuration of the identified quasar images is subsequently modeled to classify whether the object is a lensed quasar system. We test the performance of CHITAH using simulated lens systems based on the Canada-France-Hawaii Telescope Legacy Survey. For bright quads with large image separations (with Einstein radius $r_{\rm ein}>1.1"$) simulated using Gaussian point-spread functions, a high true-positive rate (TPR) of $\sim$90% and a low false-positive rate of $\sim$$3\%$ show that this is a promising approach to search for new lens systems. We obtain high TPR for lens systems with $r_{\rm ein}\gtrsim0.5"$, so the performance of CHITAH is set by the seeing. We further feed a known gravitational lens system, COSMOS 5921$+$0638, to CHITAH, and demonstrate that CHITAH is able to classify this real gravitational lens system successfully. Our newly built CHITAH is omnivorous and can hunt in any ground-based imaging surveys.

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.

The record

Venue

The Astrophysical Journal

Topic

Galaxies: Formation, Evolution, Phenomena

Field

Physics and Astronomy

Canadian institutions

not available

Funders

not available

Keywords

QuasarGravitational lensLens (geology)Einstein radiusGalaxyTelescopeLarge Synoptic Survey Telescope

Has abstract in OpenAlex

yes

API

/api/v1/works/W2137507016