CyberSec Research

Muon imaging, especially muon scattering tomography (MST), has recently garnered significant attention. MST measures the magnitude of muon scattering angles inside an object, which depends not only on the material properties but also on the muon momentum. Due to the difficulty of simultaneous measurement of momentum, it was neglected and taken as a constant in multiple MST reconstruction algorithms. Recently, an experimental measurement scheme has emerged that is feasible in engineering, but it requires many layers of detectors to approach the true momentum. From this, we proposed both an algorithm to incorporating momentum into MST, and a scheme to determine the thresholds of Cherenkov detectors. This novel scheme, termed the "equi-percentage scheme", sets momentum thresholds for Cherenkov detector layers based on cosmic muon momentum distribution. Results showed our approach delivers noticeable enhancement in reconstructed image quality even with only two detector layers, reaching near-saturation performance with four layers. This study proves that momentum measurement significantly enhances short-duration MST, and that substantial improvement can be achieved with relatively coarse momentum measurement using 2-4 layers of Cherenkov detectors.

The Spin Physics Detector (SPD) experiment at the NICA collider in JINR aims to investigate the spin structure of nucleons and spin-related phenomena. The combination of the number of background processes, the event rate and conditions for event selection makes the use of a classical trigger system impractical, requiring a triggerless data acquisition (DAQ) system. The DAQ system is designed to ensure precise time synchronization, efficient data collection, and high-throughput processing. Its architecture combines commercially available FPGA-based modules and high-speed optical interfaces with custom-developed components based on widely accessible technologies. This approach provides scalability from 180,000 at the initial stage of the experiment to more than 600,000 detector channels in the final configuration and supports data rates up to 20 GB/s or more. The modular system design ensures adaptability for future upgrades while maintaining high efficiency and reliability. Such an approach makes the DAQ system suitable for other high-rate nuclear physics experiments.

Next-generation cryogenic transmission electron microscopes (TEM) aim to achieve high-resolution imaging at ultracold sample temperatures (< 90 K) and over extended hold times. Lower temperatures enable atomic-scale characterization with improved beam and dose resilience for organic specimens and access to emergent electronic phases in quantum materials. Side-entry liquid helium cooling stages presently lack the mechanical and thermal stability required to support sub-Angstrom information transfer in modern TEM. Here we demonstrate sub-Angstrom atomic imaging TEM with a side-entry stage at specimen temperatures down to ~20K and with low stage drift and stable hold times.

We use a cavity optomechanical accelerometer to perform a resonant search for ultralight dark matter at acoustic frequencies near 39 kHz (a particle mass of $0.16$ neV/$c^2$). The accelerometer is based on a Si$_3$N$_4$ membrane, cryogenically cooled to 4 K, with photothermal heating employed to scan the resonance frequency by $10^2$ detector linewidths. Leveraging shot-noise-limited displacement readout and radiation pressure feedback cooling, we realize an acceleration resolution of $\sim 10\;\text{n}g_0/\sqrt{\text{Hz}}$ over a bandwidth of $30$ Hz near the fundamental test mass resonance. We find no evidence of a dark matter signal and infer an upper bound on the coupling to normal matter that is several orders of magnitude above the stringent bounds set by equivalence principle experiments. We outline a path toward novel dark matter constraints in future experiments by exploiting arrays of mass-loaded optomechanical sensors at lower temperature probed with distributed squeezed light.

We demonstrate a grazing-incidence x-ray platform that simultaneously records time-resolved grazing-incidence small-angle x-ray scattering (GISAXS) and grazing-incidence x-ray diffraction (GID) from a femtosecond laser-irradiated gold film above the melting threshold, with picosecond resolution at an x-ray free-electron laser (XFEL). By tuning the x-ray incidence angle, the probe depth is set to tens of nanometers, enabling depth-selective sensitivity to near-surface dynamics. GISAXS resolves ultrafast changes in surface nanomorphology (correlation length, roughness), while GID quantifies subsurface lattice compression, grain orientation, melting, and recrystallization. The approach overcomes photon-flux limitations of synchrotron grazing-incidence geometries and provides stringent, time-resolved benchmarks for complex theoretical models of ultrafast laser-matter interaction and warm dense matter. Looking ahead, the same depth-selective methodology is well suited to inertial confinement fusion (ICF): it can visualize buried-interface perturbations and interfacial thermal resistance on micron to sub-micron scales that affect instability seeding and burn propagation.

This paper proposes a new detector concept that uses the decoupling of superconducting Cooper pairs to detect particles, which has a theoretical energy threshold at the sub-meV level. However, quasiparticles decoupled from Cooper pairs in superconductors is difficult to detect using conventional photoelectric devices, since the binding energy of Cooper pairs is at the sub-meV scale. A key challenge is reading out quasiparticle signals at cryogenic temperatures. Therefore, we firstly investigate the performance of silicon photomultipliers (SiPMs) at a cryogenic temperature of 10~mK, and observed that the dark count rate drops by seven orders of magnitude compared to room temperature, while the gain decreases by only a factor of 4.44. In this paper, we present a comprehensive characterization of the SiPM's performance at 10~mK, including breakdown voltage, second breakdown and operating voltage range, single-photoelectron gain and resolution, dark count rate, output waveform characteristics, and the probability of correlated signals. Based on these findings, we propose a conceptual framework for a sub-meV particle detector that uses electron multiplication in a PN junction for signal readout.

Silicon carbide (SiC) has been widely adopted in the semiconductor industry, particularly in power electronics, because of its high temperature stability, high breakdown field, and fast switching speeds. Its wide band gap makes it an interesting candidate for radiation-hard particle detectors in high-energy physics and medical applications. Furthermore, the high electron and hole drift velocities in 4H-SiC enable devices suitable for ultra-fast particle detection and timing applications. However, currently, the front-end readout electronics used for 4H-SiC detectors constitute a bottleneck in investigations of the charge carrier drift. To address these limitations, a high-frequency readout board with an intrinsic bandwidth of 10 GHz was developed. With this readout, the transient current signals of a 4H-SiC diode with a diameter of 141 $\mathrm{\mu m}$ and a thickness of 50 $\mathrm{\mu m}$ upon UV-laser, alpha particle, and high-energy proton beam excitation were recorded. In all three cases, the electron and hole drift can clearly be separated, which enables the extraction of the charge carrier drift velocities as a function of the electric field. These velocities, for the first time directly measured, provide a valuable comparison to Monte-Carlo simulated literature values and constitute an essential input for TCAD simulations. Finally, a complete simulation environment combining TCAD, the Allpix$^2$ framework, and SPICE simulations is presented, in good agreement with the measured data.

Industry is transitioning from manually monitored components and processes to data-driven solutions. At the heart of this transformation is predictive maintenance, which relies on simultaneous, real-time monitoring of key operational parameters such as temperature and vibration to anticipate and prevent equipment failures. In this work, we present a modular approach to fibre-optic sensing, where different types of optical fibres and other wires are combined to compact, hybrid cable assemblies, customized for each application. These fibre-optic assemblies can be embedded or integrated in various settings, enabling multi-parameter sensing and the measurement of new parameters.

Calorimeters operating in high-radiation environments are susceptible to damage, leading to increased noise that can significantly degrade energy resolution. A common way to mitigate noise is to apply a higher energy threshold on the cells, typically set a few standard deviations above the noise level. However, this method risks discarding cells with genuine energy deposits, worsening the energy resolution. In this paper we explore various machine learning (ML) algorithms that can replace a rigid threshold on the reconstructed cell energy and we demonstrate the improvement in calorimetric energy reconstruction and energy resolution that these ML methods can achieve in such challenging conditions.

Robust matching of side scan sonar imagery remains a fundamental challenge in seafloor mapping due to view dependent backscatter, shadows, and geometric distortion. This paper proposes a novel matching framework that combines physical decoupling and geometric consistency to enhance correspondence accuracy and consistency across viewpoints. A self supervised multi branch network, derived from the Lambertian reflection model, decomposes raw sonar images into seabed reflectivity, terrain elevation, and acoustic path loss. The reflectivity map, serving as a stable matching domain, is used in conjunction with a training-free matching pipeline combining SuperPoint and MINIMA LightGlue. Geometry aware outlier rejection leverages both terrain elevation and its physically derived shadow map to further remove mismatches in acoustically occluded and topographically inconsistent regions, thereby improving registration accuracy. Quantitative and visual evaluations against traditional, CNN, and Transformer based state of the art methods demonstrate that our method achieves lower matching error, higher geometric consistency, and greater robustness to viewpoint variations. The proposed approach provides a data efficient, physically interpretable solution for high precision side scan sonar image matching in complex seafloor environments.

The cooling storage ring external-target experiment is a large-scale nuclear physics experiment, which aims to study the physics of heavy-ion collisions at low temperatures and high baryon densities. A beam monitor (BM) is placed in the beam line to monitor the beam status and to improve the reconstruction resolution of the primary vertices. The radiation dose and particle fluence stemming from the beam interactions with gases and detector materials affect the performance of the sensors and electronics of BM. This paper uses FLUKA Monte Carlo code to simulate the radiation environment of BM detector. Radiation quantities including the total ionizing dose, 1 MeV neutron equivalent fluence, high-energy hadron flux, thermal neutron flux, and nuclear fragment flux are presented. Results of alternative simulation setups, including adding shielding layers inside the BM, are also investigated.

A gaseous beam monitor utilizing gas electron multiplier (GEM) and pixel sensors is being developed for the Cooling Storage Ring (CSR) External-target Experiment (CEE) at Heavy Ion Research Facility in Lanzhou (HIRFL). The beam monitor is mainly used to track each beam particle, providing an accurate reconstruction of the primary vertex of the collision. Two generations of the pixel sensors (named Topmetal-CEE) were produced, with the second generation's performance improving over the first one. The design and performance of the prototype are described in the paper. Characterization of the prototype with heavy-ion beams and laser beams are presented, showing a spatial resolution better than 50 $\mum$ and a time resolution better than 15 ns.

Cryosurgery employs a safe and relatively simple technique of exposure and is an advantageous and highly rated method. For its effective application, it is necessary to control both the volume of the expanding freezing zone and volumetric thermal field dynamics. The aim of this study was to perform a thermal imaging study of freezing and thawing in a model system (gel phantom) to predict the dynamics of the freezing zone during cryodestruction of biological tissues in vivo. Here, the thermal imager is an effective tool for demonstrating the surface temperature distribution. We have studied how the observed infrared image relates to the distribution and change of the thermal field in depth. For this purpose, we created test measuring equipment for simultaneous analysis of the dynamics of thermal fields on the surface, video recording of freezing and thawing on the surface as well as in the depth of the gel phantom, measuring the temperature at any given point in the depth and modeling in the zone of low-temperature exposure of vessels with different blood flow parameters. It was revealed that with a modeled vessel in the low-temperature exposure zone, the surface thermal fields deformed and they gained the shape of butterfly wings. Our experimental study in a gel phantom is supported by numerical calculations, demonstrating how the freezing zone and thermal isotherms on the surface and in depth evolve under real conditions, thereby providing a basis for assessing the cryoeffect time and intensity in practice. Key words: cryoapplication; freezing; thawing; temperature field dynamics; infrared thermography; gel phantom; testing measuring equipment; vessel simulation.

The FAMU experiment, supported and funded by the Italian Institute of Nuclear Physics (INFN) and by the Science and Technology Facilities Council (STFC), aims to perform the first measurement of the ground-state hyperfine splitting (1S-hfs) of muonic hydrogen ($\mu H$). This quantity is highly sensitive to the proton's Zemach radius $R_Z$. An experimental determination of $R_Z$ provides significant constraints on the parametrization of the proton form factors as well as on theoretical models describing the proton's electromagnetic structure. Following years of technological and methodological development, the FAMU experiment began operations in 2023 at Port 1 of the RIKEN-RAL muon beam line at the ISIS Neutron and Muon Source facility (Didcot, UK). In this paper, we first describe the unique detection technique employed by FAMU to determine the 1S-hfs of muonic hydrogen, followed by a detailed presentation of the final experimental layout. Finally, we report the first outcome from the 2023 commissioning run and from the initial physics runs performed in 2023 and 2024.

This work investigates amplitude-dependent nonlinear corrections to the dissipative conductivity in superconductors, using the Keldysh-Usadel theory of nonequilibrium superconductivity, which captures the nonequilibrium dynamics of both quasiparticles and the pair potential. Our rigorous formulation naturally incorporates both the direct nonlinear action of the photon field and indirect contributions mediated by nonequilibrium variations in the pair potential, namely the Eliashberg effect and the Higgs mode. The third-harmonic current, often regarded as a hallmark of the Higgs mode, arises from both the direct photon action and the Higgs mode. Our numerical results are in excellent agreement with previous studies. In contrast, the first-harmonic current, and consequently the dissipative conductivity, receives contributions from all three mechanisms: the direct photon action, the Higgs mode, and the Eliashberg effect. It is shown that that the nonlinear correction to dissipative conductivity can serve as a fingerprint of the Higgs mode, appearing as a resonance peak at a frequency near the superconducting gap \( \Delta \). In addition, our results provide microscopic insight into amplitude-dependent dissipation at frequencies well below \( \Delta \), which is particularly relevant for applied superconducting devices. In particular, the long-standing issue concerning the frequency dependence of the amplitude-dependent quality factor is explained as originating from the direct nonlinear action of the photon field, rather than from contributions by the Higgs mode and the Eliashberg effect. Our practical and explicit expression for the nonlinear conductivity formula makes our results accessible to a broad range of researchers.

Objective. Proton beams enable localized dose delivery. Accurate range estimation is essential, but planning still relies on X-ray CT, which introduces uncertainty in stopping power and range. Proton CT measures water equivalent thickness directly but suffers resolution loss from multiple Coulomb scattering. We develop a data driven method that reconstructs water equivalent path length (WEPL) maps from energy resolved proton radiographs, bypassing intermediate reconstructions. Approach. We present a machine learning pipeline for WEPL from high dimensional radiographs. Data were generated with the TOPAS Monte Carlo toolkit, modeling a clinical nozzle and a patient CT. Proton energies spanned 70-230 MeV across 72 projection angles. Principal component analysis reduced input dimensionality while preserving signal. A conditional GAN with gradient penalty was trained for WEPL prediction using a composite loss (adversarial, MSE, SSIM, perceptual) to balance sharpness, accuracy, and stability. Main results. The model reached a mean relative WEPL deviation of 2.5 percent, an SSIM of 0.97, and a proton radiography gamma index passing rate of 97.1 percent (2 percent delta WEPL, 3 mm distance-to-agreement) on a simulated head phantom. Results indicate high spatial fidelity and strong structural agreement. Significance. WEPL can be mapped directly from proton radiographs with deep learning while avoiding intermediate steps. The method mitigates limits of analytic techniques and may improve treatment planning. Future work will tune the number of PCA components, include detector response, explore low dose settings, and extend multi angle data toward full proton CT reconstruction; it is compatible with clinical workflows.

Chromatic calorimetry (CCAL) analyses particle detection by utilizing scintillators with distinct emission wavelengths to measure the longitudinal energy deposition of particle showers in high-energy physics, improving particle identification (PID) and energy resolution. By stacking scintillators in order of decreasing emission wavelength, CCAL enables layer-specific energy measurements, analyzed via amplitude fractions ($f_i = A_i / \sum_j A_j$) and center of gravity ($\langle z_{\text{cog}} \rangle = \sum_i z_i E_i / \sum_i E_i$). This thesis presents results from two CERN Super Proton Synchrotron (SPS) experiments conducted in 2023 and 2024, complemented by GEANT4 simulations of a quantum dot (QD)-based CCAL design, to validate its potential for future colliders such as the Future Circular Collider (FCC).

This study establishes an innovative room-temperature synthesis approach for tellurium-diol (Te-diol) compounds, which are crucial components in tellurium-loaded liquid scintillator (Te-LS). The synthesis involves the direct reaction of telluric acid with diols (e.g., 1,2-hexanediol) in methanol under ambient conditions (20$\pm$5{\deg}C) , with the key features of lower energy consumption, enhanced safety, and improved scalability. Mechanistic studies reveal that methanol serves not merely as a solvent but also as a catalyst, playing a critical role in the room-temperature synthesis. The organic amine N,N-dimethyldodecylamine demonstrates dual functionality as both catalyst and stabilizer. The Te-diol compounds enable fabrication of high-performance Te-LS exhibiting exceptional optical transparency ($\Delta Abs$(430nm) $\leq$ 0.0003 per 1% Te loading), achieving long-term spectral stability exceeding or approaching one year for both 1% and 3% Te formulations, and demonstrating a light yield comparable to that achieved by the azeotropic distillation method. The developed protocol offers a green, efficient alternative for large-scale Te-LS production, particularly valuable for next-generation neutrinoless double-beta decay experiments.