arXiv subjects

L. Millins

Publications and source records attributed to L. Millins.

7 recordsLinked to original sources

arXiv2026

Response of a nitrogen-filled spherical proportional counter to mono-energetic neutrons

Neutron spectroscopy is an invaluable tool for a wide range of scientific and industrial applications, however, current approaches suffer from limitations that restrict their field of applicability. A safe and inexpensive alternative approach to neutron detection and spectroscopy is the use of a nitrogen-filled spherical proportional counter that exploits the $^{14}\rm{N(n,p)}^{14}\rm{C}$ and $^{14}\rm{N(n},\alpha)^{11}\rm{B}$ reactions. The neutron spectroscopy capabilities of the detector are demonstrated using beams of mono-energetic neutrons. A nitrogen-filled spherical proportional counter, operating at a pressure of $1$ bar, is exposed to neutrons with energies from $0.75$ MeV to $2.75$ MeV at the Tandem accelerator of the National Centre for Scientific Research ``Demokritos'' in Athens. A linear energy response is observed, within the statistical precision of the measurements.

hep-ex↗

arXiv2026

Optical effects in Gaseous Electron Multipliers (GEMs)

Optical time projection chambers (OTPCs) are well suited for applications that require the highest spatial resolution for particle track reconstruction. The MIGDAL experiment uses a glass GEM-based OTPC and observes a systematic excess in both the intensity and width of particle tracks in its optical readout, when compared with charge readout simulations. One hypothesis is that scintillation light produced inside a GEM hole during the avalanche propagates through the GEM substrate and exits neighboring holes. We present lab measurements testing this hypothesized optical broadening effect in three types of GEM substrates: glass, ceramic, and FR4. Our observations quantify this optical broadening and demonstrate it to be strongest in glass GEMs. Additionally, we use Geant4 simulations to both reproduce our observations and quantify optical broadening effects in realistic charge avalanches. Applying our glass GEM effects to simulated particle tracks yields increases of track intensity and widths by up to around 26% and 31%, respectively. This may explain the larger than expected intensity and track widths observed in the MIGDAL OTPC and is expected to be an observed effect in all GEM-based OTPCs.

physics.ins-det↗

arXiv2025

Overlap-aware segmentation for topological reconstruction of obscured objects

The separation of overlapping objects presents a significant challenge in scientific imaging. While deep learning segmentation-regression algorithms can predict pixel-wise intensities, they typically treat all regions equally rather than prioritizing overlap regions where attribution is most ambiguous. Recent advances in instance segmentation show that weighting regions of pixel overlap in training can improve segmentation boundary predictions in regions of overlap, but this idea has not yet been extended to segmentation regression. We address this with Overlap-Aware Segmentation of ImageS (OASIS): a new segmentation-regression framework with a weighted loss function designed to prioritize regions of object-overlap during training, enabling extraction of pixel intensities and topological features from heavily obscured objects. We demonstrate OASIS in the context of the MIGDAL experiment, which aims to directly image the Migdal effect--a rare process where electron emission is induced by nuclear scattering--in a low-pressure optical time projection chamber. This setting poses an extreme test case, as the target for reconstruction is a faint electron recoil track which is often heavily-buried within the order(s)-of-magnitude brighter nuclear recoil track. Compared to unweighted segmentation regression, we demonstrate OASIS's novel overlap region-targeted loss function weight to be the single most important training weight for improving intensity and topological reconstructions of the low-energy electron tracks that tend to be most dominated by pixel overlap. Averaging over eight training campaigns, we further show the addition of overlap-targeted weights to improve median intensity reconstruction errors from -41.1% to -13.3% for these low-energy electrons. These performance gains demonstrate OASIS as a generalizable methodology for recovering obscured signals in overlap-dominated regions.

hep-ex↗

arXiv2024

The ionization yield in a methane-filled spherical proportional counter

Spherical proportional counters (SPCs) are gaseous particle detectors sensitive to single ionization electrons in their target media, with large detector volumes and low background rates. The $\mbox{NEWS-G}$ collaboration employs this technology to search for low-mass dark matter, having previously performed searches with detectors at the Laboratoire Souterrain de Modane (LSM), including a recent campaign with a 135 cm diameter SPC filled with methane. While in situ calibrations of the detector response were carried out at the LSM, measurements of the mean ionization yield and fluctuations of methane gas in SPCs were performed using a 30 cm diameter detector. The results of multiple measurements taken at different operating voltages are presented. A UV laser system was used to measure the mean gas gain of the SPC, along with $\mathrm{^{37}Ar}$ and aluminum-fluorescence calibration sources. These measurements will inform the energy response model of future operating detectors.

physics.ins-det↗

arXiv2024

Search for Light Dark Matter with NEWS-G at the Laboratoire Souterrain de Modane Using a Methane Target

The NEWS-G direct detection experiment uses spherical proportional counters to search for light dark matter candidates. New results from a 10 day physics run with a $135\,\mathrm{cm}$ in diameter spherical proportional counter at the Laboratoire Souterrain de Modane are reported. The target consists of $114\,\mathrm{g}$ of methane, providing sensitivity to dark matter spin-dependent coupling to protons. New constraints are presented in the mass range $0.17$ to $1.2\,\mathrm{GeV/c^2}$, with a 90% confidence level cross-section upper limit of $30.9\,\mathrm{pb}$ for a mass of $0.76\,\mathrm{GeV/c^2}$.

hep-ex↗

arXiv2024

Transforming a rare event search into a not-so-rare event search in real-time with deep learning-based object detection

Deep learning-based object detection algorithms enable the simultaneous classification and localization of any number of objects in image data. Many of these algorithms are capable of operating in real-time on high resolution images, attributing to their widespread usage across many fields. We present an end-to-end object detection pipeline designed for real-time rare event searches for the Migdal effect, using high-resolution image data from a state-of-the-art scientific CMOS camera in the MIGDAL experiment. The Migdal effect in nuclear scattering, crucial for sub-GeV dark matter searches, has yet to be experimentally confirmed, making its detection a primary goal of the MIGDAL experiment. Our pipeline employs the YOLOv8 object detection algorithm and is trained on real data to enhance the detection efficiency of nuclear and electronic recoils, particularly those exhibiting overlapping tracks that are indicative of the Migdal effect. When deployed online on the MIGDAL readout PC, we demonstrate our pipeline to process and perform the rare event search on 2D image data faster than the peak 120 frame per second acquisition rate of the CMOS camera. Applying these same steps offline, we demonstrate that we can reduce a sample of 20 million camera frames to around 1000 frames while maintaining nearly all signal that YOLOv8 is able to detect, thereby transforming a rare search into a much more manageable search. Our studies highlight the potential of pipelines similar to ours significantly improving the detection capabilities of experiments requiring rapid and precise object identification in high-throughput data environments.

hep-ex↗

arXiv2023

First operation of an ACHINOS-equipped Spherical Proportional Counter with individual anode read-out

The multi-anode sensor ACHINOS revolutionised the capabilities of the spherical proportional counter by enabling large-size, high-pressure, operation and TPC-like reconstruction capabilities through individual anode read-out. First measurements with an individually read out ACHINOS are performed, which enables improved calibration and response homogenisation. Experimental results demonstrating the improvement in energy resolution brought by the individual anode calibration are presented. These are complemented by detailed simulation studies on the effect of sensor design and manufacturing imperfections, and how they may be corrected both in hardware and analysis.

physics.ins-det↗