activity
20222025
most citedFirst search for dark photon dark matter with a MADMAX prototype

15 citations · 28 across the 6 of their papers we have counts for

collaborators
Showing 2024Show all

6 papers · 1 filter

hep-ex2024★ 15 cited

First search for dark photon dark matter with a MADMAX prototype

J. Egge, D. Leppla-Weber, S. Knirck +43

We report the first result from a dark photon dark matter search in the mass range from to with a dielectric haloscope prototype for MADMAX (Magn…

physics.ins-det2024★ 1 cited

Measurement of the fractional radiation length of a pixel module for the CMS Phase-2 upgrade via the multiple scattering of positrons

The Tracker Group of the CMS Collaboration

High-luminosity particle collider experiments such as the ones planned at the High-Luminosity Large Hadron Collider require ever-greater vertexing precision of the tracking detecto…

physics.ins-det2024★ 5 cited

First mechanical realization of a tunable dielectric haloscope for the MADMAX axion search experiment

The MADMAX Collaboration, B. Ary Dos Santos Garcia, D. Bergermann +36

MADMAX, a future experiment to search for axion dark matter, is based on a novel detection concept called the dielectric haloscope. It consists of a booster composed of several die…

physics.ins-det2024

Shower Separation in Five Dimensions for Highly Granular Calorimeters using Machine Learning

S. Lai, J. Utehs, A. Wilhahn +48

To achieve state-of-the-art jet energy resolution for Particle Flow, sophisticated energy clustering algorithms must be developed that can fully exploit available information to se…

physics.ins-det2024

Beam Test Performance Studies of CMS Phase-2 Outer Tracker Module Prototypes

The Tracker Group of the CMS Collaboration

A new tracking detector will be installed as part of the Phase-2 upgrade of the CMS detector for the high-luminosity LHC era. This tracking detector includes the Inner Tracker, equ…

physics.ins-det2024

Software Compensation for Highly Granular Calorimeters using Machine Learning

S. Lai, J. Utehs, A. Wilhahn +61

A neural network for software compensation was developed for the highly granular CALICE Analogue Hadronic Calorimeter (AHCAL). The neural network uses spatial and temporal event in…