Engineering topics

Pawloski, Gregory [Minnesota U.]

Publications and source records attributed to Pawloski, Gregory [Minnesota U.].

2 records

DOE OSTI2026

Transforming the $v$ World: A New Multivariate Transformer Energy Estimator for NOvA

The NOvA Transformer Energy Estimator (Transformer_EE) is a universal machine learning tool currently used to infer the incoming beam neutrino energy and the outgoing lepton energy in both near andfar detectors. It uses a unique, highly flexible framework for simultaneous multivariate prediction that supports many possible loss functions. A spectral reweighting and flattening scheme lessens training bias. A feature noising subroutine enables adversarial-like training, mitigating sensitivities to certain systematic effects at marginal resolution loss at inference time. The state of the Transformer_EE will be reviewed, and its robustness with respect to several NOvA Near and Far Detector systematics highlighted.

Tong, Leon [Minnesota U.] (ORCID:0000000231625965)↗

DOE OSTI2026

Charged Pion Production Explorations Using the NOvA Near Detector

The~300T NOvA Near Detector (ND) utilizes segmented liquid scintillator to reconstruct interacting neutrinos arriving from the NuMI Beamline at Fermilab. Given NuMI’s intensity and the ND’s relatively short baseline, NOvA has recorded some of the world’s highest statistics for neutrino interactions around ~2GeV, in great similarity to the forthcoming DUNE experiment. This energy regime is replete with resonant interactions, which will form the plurality of final states in DUNE. NOvA seeks to empower the community with measurements of processes for both semi-exclusive and semi-inclusive charged pion production across muon kinematics and pion angle via single-and multidifferential neutrino scattering cross sections. This poster will review current progress across several related analyses, and look forward to future results.

Roy, Palash K. [Wichita State U.] (ORCID:000000022↗