arXiv subjects

Dale Julson

Publications and source records attributed to Dale Julson.

5 recordsLinked to original sources

arXiv2026

A Heavy Ion Monitor on a Chip Based on a Non-Volatile Memory Architecture -- Part II: Device Characterization & Modeling

Building on the demonstrated sensitivity of the Heavy Ion Monitor on a Chip (HIMoC) presented in Part I of this work, we performed additional irradiation exposures using 24.8 MeV/u beams of $^{14}$N, $^{22}$Ne, and $^{40}$Ar at the Texas A&M University Cyclotron Institute. A novel simulation workflow was developed that couples the particle-transport toolkit Geant4 with the open-source TCAD simulator DEVSIM to model the heavy-ion-induced signal in HIMoC devices. The model represents energy deposition by primary heavy ions and secondary electrons as Gaussian charge-loss profiles that produce measurable threshold-voltage shifts in the device. Good agreement between simulated and experimental $\Delta V_{\mathrm{th}}$ distributions was obtained. HIMoC was also shown to generate a signal that scales approximately linearly with a dose-like quantity proportional to ion fluence, LET, and active detector area. These results support HIMoC as a passive heavy-ion dosimeter and provide a framework for modeling the effects of radiation-induced charge loss in charge-trapping non-volatile memory devices.

physics.ins-det↗

arXiv2026

Continual Learning via Ensemble-Based Depth-Wise Masked Autoencoders for Data Quality Monitoring in High-Energy Physics

Machine learning (ML) techniques have been demonstrated to improve the accuracy and efficiency of anomaly detection (AD) when compared to conventional methods. This has led to the adoption of ML for data quality monitoring (DQM) use cases in order to monitor the operation of certain systems to ensure that they are free of undesirable or potentially deleterious anomalies. For applications in the field of High-Energy physics (HEP), where detectors must operate in long-running, harsh environments, ML models used in DQM that have been trained on static datasets are bound to experience degraded performance due to distributional shifts that naturally occur in the incoming data streams, unless directly mitigated via the inclusion of continual ML techniques. This work introduces DepthViT, a lightweight masked autoencoder architecture that employs unique depth-wise embeddings and depth-wise attention, to perform computationally efficient AD tasks. A continual learning framework is developed in which DepthViT models trained on the most recent data streams are ensembled with older models to create a robust overall system which is more resilient to shifts in incoming data streams. When evaluated on occupancy maps from the Compact Muon Solenoid (CMS) hadron calorimeter across multiple data-taking campaigns, the proposed method maintains precision above 98.8\% and a stable ratio of correct anomaly predictions to number of anomalies both under small and large distributional shifts. Beyond HEP, the same ensembling-based continual adaptation strategy can be directly applied to industrial monitoring environments where data also naturally evolve over time. This work therefore presents a path toward adaptive anomaly detection systems capable of sustained operation in dynamic data environments.

hep-ex↗

arXiv2024

A Heavy Ion Monitor on a Chip Based on a Non-Volatile Memory Architecture

The performance of a particle detector derived from nitride read-only memory (NROM) technology is evaluated, with immediate applications in space-based heavy ion radiation monitoring and detection. Irradiation exposures are performed using 40 MeV/u $^{78}$Kr and 10 MeV/u $^4$He particle beams at the Texas A&M University Cyclotron Institute. The results show a strong sensitivity to high-Z heavy ions, and medium sensitivity to low-Z heavy ions.

physics.ins-det↗

arXiv2022

Probing an MeV-Scale Scalar Boson in Association with a TeV-Scale Top-Quark Partner at the LHC

Searches for new low-mass matter and mediator particles have actively been pursued at fixed target experiments and at $e^+e^-$ colliders. It is challenging at the CERN LHC, but they have been searched for in Higgs boson decays and in $B$ meson decays by the ATLAS and CMS Collaborations, as well as in a low transverse momentum phenomena from forward scattering processes (e.g., FASER). We propose a search for a new scalar particle in association with a heavy vector-like quark. We consider the scenario in which the top quark ($t$) couples to a light scalar $\phi^\prime$ and a heavy vector-like top quark $T$. We examine single and pair production of $T$ in $pp$ collisions, resulting in a final state with a top quark that decays purely hadronically, a $T$ which decays semileptonically ($T$ $\rightarrow$ $W$ + $b$ $\rightarrow$ $\ell$ $\nu$ $b$), and a $\phi^\prime$ that is very boosted and decays to a pair of collimated photons which can be identified as a merged photon system. The proposed search is expected to achieve a discovery reach with signal significance greater than 5$\sigma$ (3$\sigma$) for $m(T)$ as large as 1.8 (2) TeV and $m(\phi^\prime)$ as small as 1 MeV, assuming an integrated luminosity of 3000 fb$^{-1}$. This search can expand the reach of $T$, and demonstrates that the LHC can probe low-mass, MeV-scale particles.

hep-ph↗

arXiv2018

Connecting Particle Physics and Cosmology: Measuring the Dark Matter Relic Density in Compressed Supersymmetry at the LHC

The identity of Dark Matter (DM) is one of the most captivating topics in particle physics today. The R-parity conserving Minimal Supersymmetric Standard Model (MSSM), which naturally provides a DM candidate in the form of the lightest neutralino ($\tildeχ_{1}^{0}$), is used as a benchmark scenario to show that a measurement of $Ω_{\tildeχ_{1}^{0}}h^{2}$ can be achieved from measurements at the CERN Large Hadron Collider. Focus is placed on compressed mass spectra regions, where the mass difference between the $\tildeχ_{1}^{0}$ and the $\tildeτ_{1}$ is small and where the $\tildeτ_{1}$-$\tildeχ_{1}^{0}$ coannihilation (CA) mechanism of the early Universe plays an important role. The technique for measuring $Ω_{\tildeχ_{1}^{0}}h^{2}$ relies on two proposed searches for compressed Supersymmetry (SUSY): 1) production via Vector Boson Fusion (VBF) processes; and 2) production with associated energetic jets from initial state radiation (ISR). These approaches allow for the determination of the relic abundance at the LHC for any model where CA is an important DM reduction mechanism in the early Universe. Thus, it is possible to confirm that the DM we observe today were $\tildeχ_{1}^{0}$'s created in the early Universe. We show that from measurements in the VBF and ISR SUSY searches at the LHC, the dark matter relic density can be measured with an uncertainty of 25\% with 3000 fb$^{-1}$ of 13 TeV proton-proton data.

hep-ph↗