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This paper describes the simulation studies done for the standard NOvA target and the proposed new minimal NOvA target design, in forward and reverse horn current for studying the neutrino and antineutrino event yield and the background…
We consider the problem of detecting abrupt changes in the distribution of a multi-dimensional time series, with limited computing power and memory. In this paper, we propose a new, simple method for model-free online change-point detection…
We present the most recent 3-flavor neutrino oscillation results from the NOvA long-baseline experiment, using a joint fit of $\nu_\mu \to \nu_\mu$, $\bar{\nu}_{\mu} \to \bar{\nu}_{\mu}$, $\nu_\mu \to \nu_{e}$, and $\bar{\nu}_{\mu}\to…
Object detection, one of the three main tasks of computer vision, has been used in various applications. The main process is to use deep neural networks to extract the features of an image and then use the features to identify the class and…
Supernova neutrino detection in neutrino and dark matter experiments is usually implemented as a real-time trigger system based on counting neutrino interactions within a moving time window. The sensitivity reach of such experiments can be…
MINERvA presents a new analysis of neutrino induced quasielastic-like interactions in a hydrocarbon tracking target. We report a double-differential cross section using the muon transverse and longitudinal momentum. In addition,…
Recent works in autonomous driving have widely adopted the bird's-eye-view (BEV) semantic map as an intermediate representation of the world. Online prediction of these BEV maps involves non-trivial operations such as multi-camera data…
The core for tackling the fine-grained visual categorization (FGVC) is to learn subtle yet discriminative features. Most previous works achieve this by explicitly selecting the discriminative parts or integrating the attention mechanism via…
The next generation of very-short-baseline reactor experiments will require compact detectors operating at surface level and close to a nuclear reactor. This paper presents a new detector concept based on a composite solid scintillator…
Different CT segmentation datasets are typically obtained from different scanners under different capture settings and often provide segmentation labels for a limited and often disjoint set of organs. Using these heterogeneous data…
The MINOS experiment, operating in the NuMI beam since 2005, has provided the most precise measurement of the atmospheric mass splitting $|\Delta m^2_{32}|$, and the recent combination of the $\nu_\mu$, $\nu_e$, and atmospheric neutrino…
This paper presents Correlated Nystrom Views (XNV), a fast semi-supervised algorithm for regression and classification. The algorithm draws on two main ideas. First, it generates two views consisting of computationally inexpensive random…
The overall design of the Integrated Spectral Analysis Workbench (ISAW), being developed at Argonne, provides for an extensible, highly interactive, collaborating set of viewers for neutron scattering data. Large arbitrary collections of…
The challenges in neutrino-nucleus cross section modeling and its impact on neutrino oscillation experiments are widely recognized. However, a comprehensive and theoretically robust estimation of cross section uncertainties has been…
We study the impact of one light sterile neutrino on the prospective data expected to come from the two presently running long-baseline experiments T2K and NOvA when they will accumulate their full planned exposure. Introducing for the…
Optimizing vision models purely for classification accuracy can impose an alignment tax, degrading human-like scanpaths and limiting interpretability. We introduce EVA, a neuroscience-inspired hard-attention mechanistic testbed that makes…
The Neutrinos at the Main Injector (NuMI) beamline at Fermilab generates an intense muon neutrino beam for the NOvA (NuMI Off-axis $\nu_e$ Appearance) long-baseline neutrino experiment. Over the years, the NuMI beamline has been pivotal in…
Seismic phase association is the task of grouping phase arrival picks across a seismic network into subsets with common origins. Building on recent successes in this area with machine learning tools, we introduce a neural mixture model…
Intra-frame inconsistency has been proved to be effective for the generalization of face forgery detection. However, learning to focus on these inconsistency requires extra pixel-level forged location annotations. Acquiring such annotations…
Next generation neutrino oscillation experiments are expected to measure the remaining oscillation parameters with very good precision. They will have unprecedented capabilities to search for new physics that modify oscillations. DUNE, with…