Particle detector | EPFL Graph Search

In experimental and applied particle physics, nuclear physics, and nuclear engineering, a particle detector, also known as a radiation detector, is a device used to detect, track, and/or identify ionizing particles, such as those produced by nuclear decay, cosmic radiation, or reactions in a particle accelerator. Detectors can measure the particle energy and other attributes such as momentum, spin, charge, particle type, in addition to merely registering the presence of the particle. Examples and types Many of the detectors invented and used so far are ionization detectors (of which gaseous ionization detectors and semiconductor detectors are most typical) and scintillation detectors; but other, completely different principles have also been applied, like Čerenkov light and transition radiation. Historical examples *Bubble chamber *Wilson cloud chamber (diffusion chamber) *Photographic plate ;Detectors for radiation protection The following types of particle detector

A search for heavy long-lived staus in the LHCb detector at √s = 7 and 8 TeV

Thi Viet Nga La

The Large Hadron Collider (LHC) has been producing pp collisions at 7 and 8 TeV since 2010 and promises a new era of discoveries in particle physics. One of its experiments, the Large Hadron Collider beauty (LHCb) experiment, was constructed to study CP violation in the B meson system. In addition to B physics, new Physics beyond the Standard Model can also be searched for at this single-arm forward spectrometer. With the different sub-detectors and the high resolution of the tracking system, the LHCb detector has the ability to search for heavy, long-lived and charged particles, which are predicted by extensions of the Standard Model. One of these extensions, the minimal Gauge Mediated Supersymmetry Breaking (mGMSB), proposes such a particle, named stau (τ~) - the SUSY bosonic counterpart of the heavy lepton tau (τ). The theory proposes that the staus may be pair-produced in pp collisions or in the decays of heavier particles, and have only electromagnetic interactions with the atoms of the medium like the muons. Therefore, we expect that at the energy of the LHC these particles can be produced if they do exist and that we have a chance to discover them at LHCb, as well as at the other experiments of the LHC. This thesis is dedicated to the search for stau pairs produced in pp collisions at the centre-of-mass energies √s = 7 and 8 TeV in the LHCb detector. For this purpose, we generated the stau pairs with seven different particle masses ranging from 124 to 309 GeV/c2 and simulated their path through the LHCb detector, as well as their muon background from the decays Z0, γ∗ → μ+μ−. Based on the results from the simulation, a set of cuts are then defined to select the stau pairs. Some muon pairs at high energies will also pass the selection cuts. Thus, to separate the stau pairs from the muon pairs, the Neural Network technique has been used. A first Neural Network has been used to distinguish the stau tracks from the muon tracks using their signals left in the sub-detectors: the VELO silicon detector, the electromagnetic calorimeter, the hadron calorimeter and the RICH detectors. Then, two methods to select the stau pairs have been developed: the first one is based on the product of the two responses from the first Neural Network (NN1) for the two tracks, the second one employs a second Neural Network to separate the stau pairs from the muon pairs by using the above product of the two NN1 responses and the invariant mass of pair. Finally, a favourable region for the staus finding has been defined and the expected numbers of stau and muon pairs in this region have been evaluated. The training of the Neural Network has been achieved with the Monte Carlo variables, then the trained Neural Network has been used to classify the data. The data used in our work were collected by the LHCb experiment in 2011 and 2012 and correspond to integrated luminosities of 1 fb−1 at √s = 7 TeV and of 2 fb−1 at √s = 8 TeV. No significant excess of signal has been observed. Upper limits at 95% CL on the cross section for stau pair production in pp collisions at √s = 7 and 8 TeV have been computed by using the profile likelihood method, which is derived from the well known Feldman and Cousins method.

EPFL2013

First steps towards interlocking modular microfluidic cooling substrates (i-MμCS) for future silicon tracking detectors in High Energy Physics (HEP)

Massimo Angeletti, Philippe Renaud

In future High Energy Physics detectors, the coverage of large surfaces with silicon pixel chip sensors poses a challenge for the sensors positioning, for their cooling, assembly, and interconnection. The use of a cooling substrate on which the sensors are glued is typically limited by the bulky and complicated hydraulic interconnection between adjacent substrates. In this research, a new type of cooling substrate is presented. Its design is based on microchannels, where additive manufacturing of plastic and ceramic materials has been considered an alternative to the current silicon etching process. A solution to the mechanical and hydraulic interconnection problem is achieved through a modular interlocking concept. Design optimisation was followed having identified three relevant parameters, plug-and-ply, interchangeability and sealing performance, which qualify the substrates interconnection and guaranty their correct positioning. This paper poses the bases to a new substrate category where modularity, re-workability and easy connectivity are the strong points. This concept could find applications also outside High Energy Physics experiments such as hardware cloud computing and medical detectors.

2022

The analog readout of the LHCb vertex detector and study of the measurement of the Bs oscillation frequency

Jérémie Borel

The LHCb detector is one of the four experimental setups built to detect high-energy proton collisions to be produced by the Large Hadron Collider (LHC). Located at CERN (Geneva, Switzerland), the LHC machine and the LHCb experiment are expected to start in 2008, and will then operate for several years. Being the largest collider of its kind, the LHC will open the way to new investigations, in the very-high energies, but also in terms of statistics for the study of rare-phenomena and flavor physics. In this framework LHCb is dedicated to precise measurements of CP-violating and rare decays of beauty hadrons, in order to test (or over-constrain) the Standard Model of particle physics. From the hardware point of view, the construction of such detectors represents several challenges; one of them is the routing at a very high frequency of many signals in a harsh radiation environment. We designed to this purpose a hardware setup and a software filter which together reduce the cross-talk present in the readout of the LHCb vertex detector to a level of (1 ± 2)%, leading to an improved signal quality in the acquisition chain. From the physics point of view, many of the CP-violation measurements performed at LHCb using Bs decays, for example using Bs → Ds∓ K± decays, will require as input the Bs–Bs oscillation frequency Δms. Thus the measurement of Bs–Bs oscillations, which are best observed using the flavor-specific Bs → Ds- π+ decays, will play an important role. We have developed a complete selection of Bs → Ds- π+ and Bs → Ds∓ K± events, based on Monte Carlo simulations. Assuming 2 fb-1 of data, we expect a Bs → Ds- π+ signal yield, after the first level of trigger, of 155 k events over a background between 0.6 k and 7.8 k events at 90% confidence level. Moreover, we assess with fast Monte Carlo studies the corresponding statistical sensitivity on the Bs oscillation frequency, σ(Δms) = 0.008 ps-1, on the wrong tag fraction, σ(ω) = 0.003, as well as on other parameters related to the Bs-meson system. We also addressed an important aspect of the systematics associated with the Δms measurement, and developed a method to calibrate and assess the length scale. This calibration is performed through the reconstruction of secondary interactions occurring in the material of the vertex detector. We show that the statistical relative precision of this approach quickly matches 6 × 10-5, obtained from the survey measurements of the detector.

EPFL2008