Pith. sign in

REVIEW 1 cited by

DUNE: science and status

Not yet reviewed by Pith; the record is open.

This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.

SPECIMEN: schema-true, not a live event

T0 review · schema-true

One-sentence machine reading of the paper's core claim.

pith:XXXXXXXX · record.json · timestamp

arxiv 2502.08493 v1 pith:HLHN2PH6 submitted 2025-02-12 hep-ex physics.ins-det

classification hep-exphysics.ins-det
keywords duneneutrinobeamdetectorundergroundwillbeenexperiment
verification ladder T0 review T1 audit T2 compute T3 formal
0 comments
read the original abstract

The Deep Underground Neutrino Experiment (DUNE) is a next-generation long-baseline neutrino oscillation experiment. Its primary goal is the determination of the neutrino mass hierarchy and the CP-violating phase. The DUNE physics program also includes the detection of astrophysical neutrinos and the search for beyond the Standard Model phenomena, such as nucleon decays. DUNE will consist of a near detector complex placed at Fermilab, several hundred meters downstream of the neutrino production point, and 17-kton Liquid Argon Time Projection Chamber (LArTPC) far detector modules to be built in the Sanford Underground Research Facility (SURF), approximately 1.5 km underground and 1300 km away. The detectors will be exposed to a wide-band neutrino beam generated by a 1.2 MW proton beam, with a planned upgrade to 2.4 MW. Two prototypes of the FD technology, the ProtoDUNE 700 ton LArTPCs, have been operated at CERN for over 2 years, and have been recently optimized to take new data in 2024-2025. Additionally, the 2x2 Demonstrator, a prototype of the LAr component of the near detector, has recently started operations in the NuMI beam at Fermilab. This talk will present the science programme, as well as recent progress, of DUNE and its different prototyping efforts.

Discussion (0). Sign in to comment.

Forward citations

Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. CelloAI: Leveraging Large Language Models for HPC Software Development in High Energy Physics

    cs.SE 2025-08 conditional novelty 6.0 of 10

    A locally hosted RAG-based coding assistant improves kernel retrieval and porting coverage for HEP codebases, though no tested LLM correctly ports the hardest kernels.

Pith tools