eScholarship
metadata only
CC BY
Simultaneous energy and mass calibration of large-radius jets with the ATLAS detector using a deep neural network
The energy and mass measurements of jets are crucial tasks for the Large Hadron Collider experiments. This paper presents a new calibration method to simultaneously calibrate these quantities for large-radius jets measured with the ATLAS detector using a deep neural network (DNN). To address the spe
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Simultaneous Unbinned Differential Cross-Section Measurement of Twenty-Four Z+jets Kinematic Observables with the ATLAS Detector#255882
- Search for microscopic black holes and string balls in final states with leptons and jets with the ATLAS detector at s = 8 TeV#970677
- Jet reconstruction and performance using particle flow with the ATLAS Detector#614625
- Jet reconstruction and performance using particle flow with the ATLAS Detector#289656
- Measurement of production with a veto on additional central jet activity in pp collisions at TeV using the ATLAS detector#1097396
Record · ID 1341303
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive