Engineering topics

Dalager, Olivia [Fermilab]

Publications and source records attributed to Dalager, Olivia [Fermilab].

2 records

DOE OSTI2026

X-ARAPUCA Photon Detectors in SBND

The Short-Baseline Near Detector (SBND) is a liquid argon time projection chamber (LArTPC) for detecting neutrinos from Fermilab's Booster Neutrino Beam. Located 110 m downstream of the beam target, SBND collects both ionization electrons and scintillation photons from particle interactions within the detector volume. The photon detection system (PDS) consists of both PMTs and X-ARAPUCAs, a novel technology featuring large area cost-effective coverage with single photo-electron resolution at cryogenic temperatures. SBND utilizes two types of X-ARAPUCAs: one sensitive to vacuum ultra-violet (VUV) scintillation light produced and one sensitive to visible light for the light reflected off TPB-coated reflective foils. SBND is the only experiment currently testing the X-ARAPUCA technology in a neutrino beam over a period of several years, and will provide critical information for deployment in future detectors like DUNE. This poster will cover the calibration and early performance of X-ARAPUCAs in SBND.

Dalager, Olivia [Fermilab]↗

DOE OSTI2025

Towards Online Machine Learning in DUNE Data Acquisition

Processing the large volumes of data produced by liquid argon time projection chamber (LArTPC) experiments presents a significant challenge, especially those at the scale of DUNE. This is a particular challenge when aiming to trigger on low-energy neutrinos from core-collapse supernovae, which are typically buried in a high-rate radiological background. To enable real-time event selection suitable for such rare signals, we are developing machine learning based data filtering methods. In order to demonstrate the feasibility of this approach, we implemented such pipeline using the ICEBERG detector at Fermilab as a small-scale LArTPC, with a focus on identifying Michel electrons as a proxy for low-energy neutrino interactions. This poster will present the current status of integrating these machine learning models into the data acquisition (DAQ) system of this detector.

Dalager, Olivia [Fermilab]↗