Data-driven methods enable online assessment of error states in magnetic-array-type current sensors, and long-term measurement stability can be enhanced through further self-error correction. However, when the magnetic-array-type current sensors are applied to multi-conductor systems such as multi-core cables, the time-varying correlations among conductor currents may degrade the performance of multi-latent-variable data-driven models for error evaluation. To address this issue, this paper proposes a robust self-error correcting method for magnetic-array-type current sensors even under significant variations in phase current correlations (e.g., large fluctuations in three-phase current imbalance). By incorporating phase current decoupling and principal component analysis (PCA), the correlation analysis of multi-latent variables (i.e., multi-conductor currents) is transformed into a single-latent-variable (corresponding to single phase current) modeling problem. Experimental results demonstrate that the proposed method effectively detects error drifts of magnetic field sensors as low as $2\times10^{-3}$ in relative error and $2\times10^{-3}$ rad in phase error. Accurate evaluation and correction of each magnetic field sensor's error drifts substantially eliminates the overall error drift in the magnetic-array-type current sensor, validating the feasibility and effectiveness of the proposed self-error correcting method.

A unique feature of gas xenon electroluminescent time projection chambers (GXeEL TPCs) in $0\nu\beta\beta$ searches is their ability to reconstruct event topology, in particular to distinguish "single-electron" from "double-electron" tracks, the latter being the signature of a $0\nu\beta\beta$ decay near the decay endpoint $Q_{\beta\beta}$. Together with excellent energy resolution and the t$_0$ provided by primary scintillation, this topological information is key to suppressing backgrounds. Preserving EL, however, requires operating in pure xenon (with helium as the only benign additive), and in pure xenon the diffusion of drifting electrons is large. As a result, the fidelity of reconstructed tracks is limited both by diffusion and by the intrinsic blurring of EL amplification. We propose augmenting the detector with the ability to image not only the electron track but also the corresponding mirror ion track. Introducing trace amounts of NH$_3$ ($\sim$100 ppb) converts Xe$^+$ ions into NH$_4^+$ while leaving EL unaffected. For events in the region-of-interest, an ion sensor positioned near the cathode at the projected barycenter captures the NH$_4^+$ ions. Electrons drift rapidly to the anode, producing the standard EL image, whereas the NH$_4^+$ ions drift slowly toward the cathode. Their slow drift provides time to determine the event energy and barycenter. Laser interrogation of the sensor's molecular layer then reveals an ion-track image with sub-millimeter diffusion and no EL-induced smearing. The combined electron-ion imaging substantially strengthens topological discrimination, improving background rejection by about an order of magnitude and significantly extending the discovery potential of GXeEL TPCs for very long $0\nu\beta\beta$ lifetimes.

Pulse shape discrimination (PSD) is a critical component in background rejection for neutrinoless double-beta decay and dark matter searches using Broad Energy Germanium (BEGe) detectors. To date, advanced discrimination has relied on Deep Learning approaches employing e.g. Denoising Autoencoders (DAE) and Convolutional Neural Networks (CNN). While effective, these models require tens of thousands of parameters and heavy pre-processing. In this work, we present, to the best of our knowledge, the first application of Quantum Machine Learning (QML) to real, experimental pulse waveforms from a germanium detector. We propose a quantum-classical hybrid approach using Variational Quantum Circuits (VQC) with amplitude encoding. By mapping the 1024-sample waveforms directly into a 10-qubit Hilbert space, we demonstrate that a VQC with only 302 trainable parameters achieves a receiver operating characteristic (ROC) area under the curve (AUC) of 0.98 and a global accuracy of 97.1%. This result demonstrates that even in the current Noisy Intermediate-Scale Quantum (NISQ) era, quantum models can match the performance of state-of-the-art classical baselines while reducing model complexity by over two orders of magnitude. Furthermore, we envision a scenario where future quantum sensors transmit quantum states directly to such processing units, exploiting the exponentially large Hilbert space in a natively quantum pipeline.

The ALICE collaboration is preparing an upgrade of the three innermost layers of the current Inner Tracking System (ITS) during the next LHC long shutdown (LS3). The new ITS detector will use wafer-scale (up to \SI{27}{cm} in length) Monolithic Active Pixel Sensors with a \SI{65}{nm} CMOS Image Sensor process, thinned to \SI{50}{\micro m} and bent around the beam pipe. The planned upgrade will allow the use of only two sensors per tracker layer, kept in place by just two mechanical supports at the edges and two thin carbon fibre supports at the sensor border. The substitution of water cooling with air cooling will lead to an expected reduction of the material budget per-layer from $\sim$0.36\% $X_0$ of the current detector to 0.09\% $X_0$. The R\&D process also led to the development of a new sensor variant with an additional low dose n-type implant to the previous detector. This improves charge collection speed, confirms a spatial resolution of about \SI{5}{\micro m}, a detection efficiency greater than 99\% and an excellent radiation tolerance. Large area prototypes proved the possibility to have an active area greater than 90\%, and a fake hit rate lower than \SI{e-6}{hits/pixel/event} without loosing detection efficiency. This proceeding will show the above innovations, with particular attention to a small area analogue test structure featuring a front-end which can be monitored via an on-chip Operational Amplifier buffer that preserves the steep signal edge (few hundreds of ps) in order to study the sensor timing performance. The characterization proved a time resolution of \SI{63}{ps} on average and \SI{50}{ps} for signal passing right under the electrode with a detection efficiency above 99\%.

We present an advanced model for describing the readout power dependence of the resonance characteristics of a microwave SQUID multiplexer. Our model proves valid for SQUID screening parameters up to \beta_\mathrm{L}<1, hence covering the full range of practically relevant design parameters. We demonstrate that our model significantly improves agreement with experimental data compared to the existing models, thereby enabling optimization beyond the previously accessible parameter space. Moreover, our model supports non-sinusoidal current-phase relations of the rf-SQUID's Josephson junction, allowing, for the first time, for the modeling of devices based on Josephson tunnel junctions with inhomogeneous tunnel barriers. We show that the effects of such inhomogeneities are qualitatively similar to, yet distinct from, those of the screening parameter, making their inclusion essential for accurate characterization. Incorporating these effects yields great improved agreement with measurements, even at readout power conditions well beyond typical operating parameters.

This work presents radiation-tolerant implementations for the SALSA front-end readout ASIC through redundancy methods applied to two median-finding algorithms designed for coherent noise suppression. Bit-wise Median Finder (BWMF) and Combinatorial Sum Median Finder (CSMF) were implemented in TSMC \SI{65}{\nano\meter} and evaluated in terms of area, power, and latency. Three redundancy techniques were applied in this work to compare their impact: simple TMR, full TMR, and temporal TMR (TTMR). The simple and full TMR approach was applied in both algorithms to establish comparisons and TTMR was applied to CSMF as an improvement. The results indicate that the BWMF achieves efficient performance in terms of area and power under the simple TMR scheme, but exhibits significantly higher power consumption when using the more robust full TMR approach. The TTMR technique, in turn, offers reliable fault tolerance while maintaining a feasible balance between area and power.

The RELICS (REactor neutrino LIquid xenon Coherent elastic Scattering) experiment aims to detect coherent elastic neutrino-nucleus scattering from reactor antineutrinos using a dual-phase xenon time projection chamber. To validate the detector concept and ensure technical reliability for the full-scale experiment, a dedicated prototype was designed, constructed, and operated. This work presents an overview of the design, construction, and operational performance of the prototype, with emphasis on its major subsystems, including the TPC, cryogenic and xenon purification systems, slow control, and data acquisition. During operation, the detector demonstrated the capability to achieve a sub-keV energy threshold required for the RELICS physics program, as reflected by a measured single electron gain of 34.30~$\pm$~0.01~(stat.)~PE/e$^-$ and the successful detection of 0.27~keV L-shell decay events from $^{37}$Ar. In addition, essential data analysis techniques and simulation frameworks were developed and validated, establishing the methodological foundation for future RELICS operations. The successful construction and operation of this prototype confirm the feasibility of the core technologies and provide a crucial experimental basis for the final RELICS detector.

Photon-number resolved detection with superconducting nanowire single-photon detectors (SNSPDs) attracts increasing interest, but lacks a systematic framework for interpreting and benchmarking this capability. In this work, we combine principal component analysis (PCA) with a new readout technique to explore the photon-number resolving capabilities of SNSPDs and find that the information of the photon number is contained in a single principal component which approximates the time derivative of the average response trace. We introduce a new confidence metric based on the Bhattacharyya coefficient to quantify the photon-number-resolving capabilities of a detector system and show that this metric can be used to compare different systems. Our analysis and interpretation of the principal components imply that photon-number resolution in SNSPDs can be achieved with moderate hardware requirements in terms of both sample rate (5 GSample/sec) and analog bandwidth (3 GHz) and could be implemented in an FPGA, giving a highly scalable solution for real-time photon counting.

Measurements in the highly Lorentz-boosted regime provoke increased interest in probing the Higgs boson properties and in searching for particles beyond the standard model at the LHC. In the CMS Collaboration, various boosted-object tagging algorithms, designed to identify hadronic jets originating from a massive particle decaying to $\mathrm{b\overline{b}}$ or $\mathrm{c\overline{c}}$, have been developed and deployed across a range of physics analyses. This paper highlights their performance on simulated events, and summarizes novel calibration techniques using proton-proton collision data collected at $\sqrt{s}$ = 13 TeV during the 2016$-$2018 LHC data-taking period. Three dedicated methods are used for the calibration in multijet events, leveraging either machine learning techniques, the presence of muons within energetic boosted jets, or the reconstruction of hadronically decaying high-energy Z bosons. The calibration results, obtained through a combination of these approaches, are presented and discussed.

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).

The growing demand for sustainable cryogenic operations at Fermilab has underscored the need to improve helium management, particularly at the Industrial Building 3A (IB3A) test facility. IB3A characterizes and tests superconductors, cables, and coils for projects such as the HL-LHC AUP and Mu2e, yet currently relies on 500 L Dewars whose boil-off is vented to atmosphere, wasting a critical, non-renewable resource and increasing the cost of testing. A project is therefore under way to link IB3A to an existing purification and liquefaction station in a neighboring building through a dedicated pipeline. Captured helium will be transferred, purified, reliquefied, and returned for reuse, cutting losses and operating costs. This paper details the first two project phases: "Design and Engineering" and "Procurement and Installation." The design phase finalizes pipeline specifications, establishes flow-control requirements, and resolves integration challenges with existing cryogenic infrastructure. The procurement and installation phase covers material sourcing, pipeline construction, and deployment of control and monitoring systems to assure reliable, efficient operation. Key technical hurdles-route optimization, pressure drop mitigation, and interface compatibility-are discussed alongside implemented solutions. Implementing the pipeline and upgrading IB3A will dramatically reduce helium consumption and therefore testing cost, strengthening Fermilab's capacity to support frontier science far into the future.

Muon colliders offer a compelling opportunity to explore the TeV scale and conduct precision tests of the Standard Model, all within a relatively compact geographical footprint. This paper introduces a new detector concept, MAIA (Muon Accelerator Instrumented Apparatus), optimized for $\sqrt{s}=10$ TeV $\mu\mu$ collisions. The detector features an all-silicon tracker immersed in a 5T solenoid field. High-granularity silicon-tungsten and iron-scintillator calorimeters surrounding the solenoid capture high-energy electronic and hadronic showers, respectively, and support particle-flow reconstruction. The outermost subsystem comprises an air-gap muon spectrometer, which enables standalone track reconstruction for high-momentum muons. The performance of the MAIA detector is evaluated in terms of differential particle reconstruction efficiencies and resolutions. Beam-induced background (BIB) simulations generated in FLUKA are overlaid with single particle gun samples to assess detector reconstruction capabilities under realistic experimental conditions. Even with BIB, reconstruction efficiencies exceed 95% for energetic tracks, photons, and neutrons in the central region of the detector. This paper outlines promising avenues of future work, including forward region optimization and opportunities for enhanced flavor/boosted object tagging, and addresses the technological assumptions needed to achieve the desired detector performance.

We report on a free-space-coupled superconducting nanowire single-photon detector array developed for NASA's Deep Space Optical Communications project (DSOC). The array serves as the downlink detector for DSOC's primary ground receiver terminal located at Palomar Observatory's 200-inch Hale Telescope. The 64-pixel WSi array comprises four quadrants of 16 co-wound pixels covering a 320 micron diameter active area and embedded in an optical stack. The detector system also includes cryogenic optics for filtering and focusing the downlink signal and electronics for biasing the array and amplifying the output pulses. The detector system exhibits a peak system detection efficiency of 76% at 1550 nm, a background-limited false count rate as low as 3.7 kcps across the array, timing jitter less than 120 ps FWHM, and a maximum count rate of ~ 1 Gcps.

The demand for novel detector mediums such as Water-based Liquid Scintillator (WbLS) has increased over the last few decades due to their capability for both low energy particle interactions and higher light yield. Recently, the usage of machine learning (ML) methods in high-energy physics has also been increasing. The ML and AI methods are used in many physics projects in the field since they provide effective and sensitive results. In this study, we aimed to develop a comprehensive analysis of water Cherenkov detectors and perform physics analyses to efficiently separate Cherenkov and scintillation photons with ML algorithms using the data from the WbLS detector environment. The main goal of this study was to produce more precise solutions to physics problems, such as signal classification, by applying ML techniques to the simulation and experimental data. Here, we trained more than 20 ML models, and our results revealed that three machine learning models, XGBoost, Light GBM, and Random Forest models, and their ensemble model gave us more than 95\% accuracy for separating Cherenkov and scintillation photons with balanced and unbalanced datasets. This is a significant increase in efficiency as compared with the results of the classical method by applying simple time cuts.

In this paper, we have designed a low-cost scanning tunneling microscope (STM) priced at 300 USD or 2000 CNY. This microscope is suitable for educational purposes and low-demand research imaging at the nanometer level. This microscope's motion components and scanner are controlled using piezoelectric materials, avoiding the thermal drift associated with traditional motor control. Our tip approach algorithm, which considers the capacitance and friction characteristics during piezoelectric slider movement, has reduced the time required for sample loading to establish tunneling current to approximately 1 minute. The dimensions of the microscope body are 45x45x31.5mm(WxLxH), and the control voltage does not exceed 15V, ensuring the safety of operators with limited experience. In the performance verification, we performed a scanning tunneling scan on a Highly Oriented Pyrolytic Graphite(HOPG) sample with bias voltages of 50mV and 60mV, resulting in clear observations of the atomic features of HOPG in the STM pattern.

We present PyRPL, an open source software package that allows the implementation of automatic digital feedback controllers for quantum optics experiments on commercially available, affordable FPGA boards. Our software implements the digital generation of various types of error signals, from an analog input through the application of loop filters of high complexity and real-time gain adjustment for multiple analog output signals, including different algorithms for resonance search, lock acquisition sequences and in-loop gain optimization. Furthermore, all necessary diagnostic instruments such as an oscilloscope, a network analyzer and a spectrum analyzer are integrated into our software. Apart from providing a quickly scalable, automatic feedback controller, the lock performance that can be achieved by using PyRPL with imperfect equipment such as piezoelectric transducers and noisy amplifiers is better than the one achievable with standard analog controllers due to the higher complexity of implementable filters and possibilities of nonlinear operations in the FPGA. This drastically reduces the cost of added complexity when introducing additional feedback loops to an experiment. The open-source character also distinguishes PyRPL from commercial solutions, as it allows users to customize functionalities at various levels, ranging from the easy integration of PyRPL-based feedback controllers into existing setups to the modification of the FPGA functionality. A community of developers provides fast and efficient implementation and testing of software modifications.

The Nuclotron-base Ion Collider fAcility (NICA) is under construction at the Joint Institute for Nuclear Research (JINR), with commissioning of the facility expected in late 2022. The Multi-Purpose Detector (MPD) has been designed to operate at NICA and its components are currently in production. The detector is expected to be ready for data taking with the first beams from NICA. This document provides an overview of the landscape of the investigation of the QCD phase diagram in the region of maximum baryonic density, where NICA and MPD will be able to provide significant and unique input. It also provides a detailed description of the MPD set-up, including its various subsystems as well as its support and computing infrastructures. Selected performance studies for particular physics measurements at MPD are presented and discussed in the context of existing data and theoretical expectations.

Accessible machine learning algorithms, software, and diagnostic tools for energy-efficient devices and systems are extremely valuable across a broad range of application domains. In scientific domains, real-time near-sensor processing can drastically improve experimental design and accelerate scientific discoveries. To support domain scientists, we have developed hls4ml, an open-source software-hardware codesign workflow to interpret and translate machine learning algorithms for implementation with both FPGA and ASIC technologies. We expand on previous hls4ml work by extending capabilities and techniques towards low-power implementations and increased usability: new Python APIs, quantization-aware pruning, end-to-end FPGA workflows, long pipeline kernels for low power, and new device backends include an ASIC workflow. Taken together, these and continued efforts in hls4ml will arm a new generation of domain scientists with accessible, efficient, and powerful tools for machine-learning-accelerated discovery.

Thanks to intrinsically short electronic relaxation on the ps time scale, III-V semiconductor unipolar devices are ideal candidates for ultrahigh-speed operation at mid-infrared frequencies. In this work, antenna-coupled, GaAs-based multi quantum-well photodetectors operating in the 10-11um range are demonstrated, with a responsivity of 0.3A/W and a 3dB-cutoff bandwidth of 100GHz at room-temperature. The frequency response is measured up to 220GHz: beyond 100GHz we find a roll-off dominated by the 2.5 ps-long recombination time of the photo-excited electrons. The potential of the detectors is illustrated by setting up an experiment where the time dependent emission frequency of a quantum cascade laser operated in pulsed mode is measured electronically and in real-time, over a frequency range >60GHz. By exploiting broadband electronics, and thanks to its high signal-to-noise ratio, this technique allows the acquisition, in a single-shot, of frequency-calibrated, mid-infrared molecular spectra spanning up to 100GHz and beyond, which is particularly attractive for fast, active remote sensing applications in fields such as environmental or combustion monitoring.

Positron Emission Tomography (PET) is a Nuclear Medicine technique that creates images that allow the study of metabolic activity and organ function using radiopharmaceuticals. Continuous improvement of scintillation detectors for radiation in PET as well as improvement in electronic detectors (e.g., SiPMs) and signal processing, makes the field of PET a fast and changing environment. If industry desires to build new systems implementing these technological improvements, it is of its interest to develop modelling strategies that can provide information on how to build them, reducing time and material costs. Bearing this in mind three different PET configurations, were simulated in Geant4, to determine which one presented the best performance according to quality parameters such as spatial resolution (SR), coincident time resolution (CTR) and acceptance value (A). This was done with three different (in size) pairs of LYSO crystals + SiPM detectors. It was found that the 2 Modules system presented worst results than the two Ring detector configurations. Between the Ring configurations the first was marginally better than the second.