Silicon-based detectors and electronics

Silicon plays a fundamental role in present-time electronics systems we daily interact with but also in any modern scientific apparatus, from the data management and parsing (see 1.2) down to the very hearth of the experiment, where elementary particles are detected, and their trajectories in space “photographed” by giant, ultrafast cameras called detectors. Such detectors are mostly composed of pixel sensors very similar to those found in smartphones, cameras, and other electronic equipment.
The detectors, technologies and systems developed to meet the HEP and space-borne experiments impact many other scientific fields, and the applied ones as well, see 6.2 for more details on the applied side of detectors R&D.
Compact and bulkier versions of these such detectors can be also employed in nuclear physics and astrophysics, and to produce sensors and decade-lasting batteries for space and medicine.
Contacts : Piero Giubilato, Serena Mattiazzo, Daniele Mengoni
Website:GRIT

  Detectors for precise timing measurement

In modern physics experiments, the precise measurement of particle passage times allows a reduction in the number of spurious signals and a precise reconstruction of the collision products. In particular, detectors dedicated to timing measurements with a time resolution of about 35 ps (CMS experiment) and sensors with intrinsically excellent time resolution (TIMESPOT project and IGNITE project) are being developed.
Contacts: Mia Tosi, Roberto Rossin, Gabriele Simi, Serena Mattiazzo
Website:TIMESPOT, CMS

  Photon detectors with germanium

High-resolution gamma-ray spectroscopy is one of the most powerful and sensitive tools for investigating the structure of atomic nuclei and reactions relevant to nuclear astrophysics. Significant advancements in this field have been achieved by the possibility of determining the position and energy deposition of individual photon interaction points within a germanium crystal and reconstructing the photon scattering sequence through advanced data analysis algorithms. Arrays of germanium detectors employing these techniques, known as Pulse Shape Analysis and γ-ray tracking, will achieve the necessary performance to operate effectively at future radioactive ion beam facilities
Contacts: Silvia M. Lenzi, Daniele Mengoni, Francesco Recchia

  Measurement of particle energy

For many physics experiments a fundamental ingredient is the measurement of the energy of the particles. This, combined with the measurement of the momentum, allows us to obtain the mass of the particle. The relevant detector is called a "calorimeter". As part of the LHCb collaboration, a new calorimeter is being developed that can resist the damage produced by the LHC's radiation and at the same time precisely measure the arrival times of photons.
Contacts: Donatella Lucchesi, Davide Zuliani
Website:  LHCb

  Particle identification techniques

The identification of the particles produced in accelerator collisions is of fundamental importance for understanding the nature of the underlying physical processes. For the LHCb experiment, new detectors (with the relevant electronics) are being developed based on the simultaneous measurement of the direction of the Cherenkov radiation and its arrival time which will allow the identification of charged particles of different types even in the high trace density conditions expected after the LHC upgrade.
Contacts: Gabriele Simi, Federica Borgato
Website:RICH @LHCb

  Gas detectors for charged particles and photons

  Trigger and data acquisition techniques

The LHC's proton beams collide every 25 ns; the CMS experiment detects every product of such collisions at the same incredible rate; the enormous data traffic necessarily passes through a rigorous selection. CMS currently discards more than 99.99%, which severely limits the sensitivity of the experiment to possible New Physics. The L1 Scouting project aims to process and analyze data before any filtering, reducing the distortion with which collisions are analyzed to almost zero. This requires the development of dedicated electronic boards, network protocols, online processing systems based on machine learning.
Contacts: Jacopo Pazzini, Andrea Triossi, Marco Zanetti
Website:BoostLab

  Detector optimization techniques

The use of deep learning techniques, and more generally of differentiable programming, is being considered to build differentiable models also of the intrinsically stochastic parts of the information extraction chain from a detector and a physical process of interest, through the reconstruction of the electronic signals and the creation of summary statistics, produces statistical inference on the parameters of interest.

Differentiable programming
By minimizing a loss function, which includes modeling of the radiation-matter interaction, of the geometry of the apparatus, of the pattern recognition of the signals, and of the data analysis, and of the cost of the apparatus, a full and complete optimization of the entire experimental apparatus and measurement procedure.
Contacts: Michele Doro, Mia Tosi
Website:  MODE

Quantum Machine Learning
Machine Learning techniques have proven to be extremely effective in the field of high-energy physics across a broad spectrum of applications, from classification problems to simulation. The new Quantum Machine Learning techniques, which exploit the properties of quantum computation, are currently still not widespread. The growing availability of quantum computers opens the door to developments of new algorithms for improving data analyzes and detectors.
Contacts: Donatella Lucchesi, Davide Zuliani