The Scintillating Bubble Chamber (SBC) Experiment for Dark Matter and Reactor CEvNS
Bibliographic record
Abstract
The Scintillating Bubble Chamber (SBC) experiment is a novel low-background technique aimed at detecting low-mass (0.7-7 GeV/c2) WIMP interactions and coherent scattering of reactor neutrinos (CEvNS). The detector consists of a quartz-jar filled with liquid Argon (LAr), which is spiked with O(100 ppm) of liquid Xenon (LXe) acting as a wavelength shifter. The target fluid is de-pressurized into a super-heated state by a mechanically controlled piston. Particles interacting with the LAr+100 ppm LXe can generate heat (bubbles) and scintillation light, depending on the energy intensity and density. The detector is further equipped with cameras to take pictures of the bubbles, Silicon-Photo-Multipliers to measure the scintillation light, and piezo-acoustic sensors to listen to the bubble’s formation. By combining these observables, the SBC detector is aiming to reach a threshold for nuclear recoils of 100 eV and a projected WIMP-sensitivity of 3.0x10$^{-43}$ cm$^{2}$, for a WIMP mass of 0.7 GeV/c$^{2}$. In this paper, we will present the overall design of the SBC experiment and provide an update on the ongoing construction at the Fermilab site. Finally, we will discuss the collaboration’s plans for the SNOLAB installation/operation and the reactor CEvNS search. In this paper, we will present the overall design of the SBC experiment and provide an update on the ongoing construction at the Fermilab site. Finally, we will discuss the collaboration’s plans for the SNOLAB installation/operation and the reactor CEvNS search.
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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 | 0.005 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".