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A. Crupano

Publications and source records attributed to A. Crupano.

3 recordsLinked to original sources

The Analytical Method algorithm for trigger primitives generation at the LHC Drift Tubes detector

The Compact Muon Solenoid (CMS) experiment prepares its Phase-2 upgrade for the high-luminosity era of the LHC operation (HL-LHC). Due to the increase of occupancy, trigger latency and rates, the full electronics of the CMS Drift Tube (DT) chambers will need to be replaced. In the new design, the time bin for the digitisation of the chamber signals will be of around 1~ns, and the totality of the signals will be forwarded asynchronously to the service cavern at full resolution. The new backend system will be in charge of building the trigger primitives of each chamber. These trigger primitives contain the information at chamber level about the muon candidates position, direction, and collision time, and are used as input in the L1 CMS trigger. The added functionalities will improve the robustness of the system against ageing. An algorithm based on analytical solutions for reconstructing the DT trigger primitives, called Analytical Method, has been implemented both as a software C++ emulator and in firmware. Its performance has been estimated using the software emulator with simulated and real data samples, and through hardware implementation tests. Measured efficiencies are 96 to 98\% for all qualities and time and spatial resolutions are close to the ultimate performance of the DT chambers. A prototype chain of the HL-LHC electronics using the Analytical Method for trigger primitive generation has been installed during Long Shutdown 2 of the LHC and operated in CMS cosmic data taking campaigns in 2020 and 2021. Results from this validation step, the so-called Slice Test, are presented.

hep-ex

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$_{\gamma^{\mathrm{D}}}$ 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$_{\gamma^{\mathrm{D}}}$ ranging between 0.8 and 3.3$^{+0.2}_{-0.5}$ GeV, and $\varepsilon^2$ ranging between $10^{-11}$ and $10^{-17}$.

hep-ex

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