arXiv subjects

V. Büscher

Publications and source records attributed to V. Büscher.

6 recordsLinked to original sources

arXiv2026

An investigation of fast simulation techniques for pion showers using kernel density estimators with the CALICE AHCAL Technological Prototype

In this article, the development and investigation of fast hadron shower simulation methods is presented. A test beam dataset has been recorded in 2018 at CERN with the AHCAL Technological Prototype of the CALICE Collaboration, where the calorimeter prototype was exposed to electron, muon, and negatively charged pion beams of various initial energies. The pion shower dataset, covering energies between 10 GeV and 200 GeV, has been used to develop a data-driven fast simulation algorithm of the AHCAL response to pion showers. The resulting shower model demonstrates excellent agreement with measured shower observables. In addition, a method for simulating pion showers at arbitrary energies is introduced, based upon interpolation between simulated showers at neighbouring beam energies.

physics.ins-det↗

arXiv2022

HIKE, High Intensity Kaon Experiments at the CERN SPS

A timely and long-term programme of kaon decay measurements at a new level of precision is presented, leveraging the capabilities of the CERN Super Proton Synchrotron (SPS). The proposed programme is firmly anchored on the experience built up studying kaon decays at the SPS over the past four decades, and includes rare processes, CP violation, dark sectors, symmetry tests and other tests of the Standard Model. The experimental programme is based on a staged approach involving experiments with charged and neutral kaon beams, as well as operation in beam-dump mode. The various phases will rely on a common infrastructure and set of detectors.

hep-ex↗

arXiv2021

Sensitivity of the SHiP experiment to dark photons decaying to a pair of charged particles

Dark photons are hypothetical massive vector particles that could mix with ordinary photons. The simplest theoretical model is fully characterised by only two parameters: the mass of the dark photon m$_{γ^{\mathrm{D}}}$ and its mixing parameter with the photon, $\varepsilon$. The sensitivity of the SHiP detector is reviewed for dark photons in the mass range between 0.002 and 10 GeV. Different production mechanisms are simulated, with the dark photons decaying to pairs of visible fermions, including both leptons and quarks. Exclusion contours are presented and compared with those of past experiments. The SHiP detector is expected to have a unique sensitivity for m$_{γ^{\mathrm{D}}}$ ranging between 0.8 and 3.3$^{+0.2}_{-0.5}$ GeV, and $\varepsilon^2$ ranging between $10^{-11}$ and $10^{-17}$.

hep-ex↗

arXiv2020

SND@LHC

We propose to build and operate a detector that, for the first time, will measure the process $pp\toνX$ at the LHC and search for feebly interacting particles (FIPs) in an unexplored domain. The TI18 tunnel has been identified as a suitable site to perform these measurements due to very low machine-induced background. The detector will be off-axis with respect to the ATLAS interaction point (IP1) and, given the pseudo-rapidity range accessible, the corresponding neutrinos will mostly come from charm decays: the proposed experiment will thus make the first test of the heavy flavour production in a pseudo-rapidity range that is not accessible by the current LHC detectors. In order to efficiently reconstruct neutrino interactions and identify their flavour, the detector will combine in the target region nuclear emulsion technology with scintillating fibre tracking layers and it will adopt a muon identification system based on scintillating bars that will also play the role of a hadronic calorimeter. The time of flight measurement will be achieved thanks to a dedicated timing detector. The detector will be a small-scale prototype of the scattering and neutrino detector (SND) of the SHiP experiment: the operation of this detector will provide an important test of the neutrino reconstruction in a high occupancy environment.

physics.ins-det↗

arXiv2019

Implementation of high-performance, sub-microsecond deep neural networks on FPGAs for trigger applications

Artificial neural networks are already widely used for physics analysis, but there are only few applications within low-level hardware triggers, and typically only with small networks. Modern high-end FPGAs offer Tera-scale arithmetic performance, and thereby provide a significant amount of operations per data set even for MHz-range data rates. We present a bottom-up approach of implementing typical neural network layers, in which we took both the special constraints that come from high-performance trigger systems, such as the ATLAS hardware trigger at the LHC, as well as an efficient implementation into account. By specifically designing each layer type to match our requirements, we could develop a framework that reaches 90 to 100% processing efficiency for large layers, requires only few extra resources for data flow and controlling, and offers latencies in the range of only tens to hundreds of nanoseconds for entire (deep) networks. Additionally, a toolkit was built around these optimized layer implementations, which facilitates the creation of the FPGA implementation of a trained NN model.

physics.ins-det↗

arXiv2017

The active muon shield in the SHiP experiment

The SHiP experiment is designed to search for very weakly interacting particles beyond the Standard Model which are produced in a 400 GeV/c proton beam dump at the CERN SPS. An essential task for the experiment is to keep the Standard Model background level to less than 0.1 event after $2\times 10^{20}$ protons on target. In the beam dump, around $10^{11}$ muons will be produced per second. The muon rate in the spectrometer has to be reduced by at least four orders of magnitude to avoid muon-induced combinatorial background. A novel active muon shield is used to magnetically deflect the muons out of the acceptance of the spectrometer. This paper describes the basic principle of such a shield, its optimization and its performance.

physics.ins-det↗