Fabrizio Aloschi

Long-range muons produced in proton–proton collisions at the ATLAS interaction point constitute the primary background for neutrino interaction searches at the SND@LHC experiment. This work presents a comprehensive characterization of the muon flux throughout LHC Run-3, benchmarking Monte Carlo simulations against experimental measurements. Measured and simulated muon rates agree within 10–15% across all Run-3 configurations. Following the substantial background increase in 2024 as a result of a beam optics change, the reversion to nominal optics in 2025 did not restore the 2022–2023 levels due to the unprecedented adoption of horizontal crossing in ATLAS. As indicated by simulation results, horizontal crossing enhanced the contribution of high-angle muons originating from diffractive proton losses in the LHC Dispersion Suppressor region. Their identification enabled the design of mitigation strategies that were experimentally validated. The simulation framework was also applied to the future high-luminosity LHC configuration, resulting in a considerable muon rate rise, driven by both the planned luminosity increase and the enlarged magnet aperture. Nevertheless, the upgrade from emulsion films to silicon vertex detectors will preserve the efficiency of the experiment even in such a high-rate environment.

This paper presents the design, construction, and simulation-based validation of the ColdBox, a combined neutron shielding and insulating enclosure for the Scattering and Neutrino Detector at the LHC (SND@LHC). The emulsion films in the detector's target region require protection from the intense neutron radiation background and a stable environment of 15 ± 1 °C and 50–55 % relative humidity for long-term stability. The ColdBox meets these requirements through a dual-layer structure: an external 5 cm plexiglass wall to moderate fast neutrons, and an internal 4 cm layer of borated polyethylene (with 35 % boron content) to capture thermal neutrons. The mechanical design, based on a robust aluminum frame, accommodates the constraints of the TI18 tunnel. FLUKA simulations were used to optimize the shielding configuration, showing a significant reduction in the neutron flux, with a simulated ratio of shielded to unshielded thermal neutron fluence of 2.3 × 10 ^-3 . This result is consistent with initial measurements from BatMon detectors. The design also provides a sealed volume for a cooling system to maintain the required temperature and humidity, ensuring the necessary conditions for the emulsion films' integrity.

The use of periodic materials for wave control and signal processing has been a focus of intensive research over the past two decades and continues to garner significant attention. Common signal processing mechanisms like switches and rectifiers often depend on magnetic fields and/or logic gates for their activation. We propose a metamaterial that enables the control of mechanical waves—surface acoustic waves—through an ON–OFF mechanism that switches the propagation of the waves through a tunable platform of elastic beams. In the OFF configuration, the beams remain in their undeformed state and resonate at a specific frequency range, creating a bandgap that stops wave propagation. Conversely, in the ON configuration, the beams undergo buckling, redistributing the vibration energy across multiple modes and eliminating the bandgap, thus allowing wave propagation. Analytical and numerical findings demonstrate the significant potential of this mechanism for controlling wave propagation in nonlinear periodic materials. This switching mechanism relies purely on mechanical processes, thereby eliminating the need for external fields.

We provide geographic information system (GIS) data and a multimodal dataset from a systematic infrastructure vulnerability assessment in the urban road networks of Turin and Naples, Italy. The seismic typologies of the relevant structural objects (SOs), including bridges, buildings, and roads, were evaluated using digital elevation models (DEMs) and satellite data. The presented GIS data are essential for visualizing and spatially interconnecting SOs; this enables network modeling as a complex system within the Spatial Data Infrastructure (SDI) portfolio of interest. The dataset also includes landslide characteristics from Geoportale Piemonte and the GeoNetwork catalog. Potential applications include resilience analysis, seismic risk assessment, emergency response planning, and post-disaster recovery estimations. Moreover, the dataset helps investigate the interplay between structural vulnerability and geohazards like landslides, heavy rainfall, and earthquakes. Notably, it is particularly relevant for research on urban networks as complex systems, where SDIs assess transportation efficiency and functionality in both pre- and post-event scenarios.