Jet reconstruction remains a critical task in the analysis of data from HEP colliders. We describe in this paper a new, highly performant, Julia package for jet reconstruction, JetReconstruction.jl, which integrates into the growing ecosystem of Julia packages for HEP. With this package users can run sequential reconstruction algorithms for jets. In particular, for LHC events, the Anti-${k}_\text{T}$, Cambridge/Aachen and Inclusive-${k}_\text{T}$ algorithms can be used. For FCCee studies the use of alternative algorithms such as the Generalised ${k}_\text{T}$ for $e^+e^-$ and Durham are also supported. The performance of the core algorithms is better than Fastjet's C++ implementation, for typical LHC and FCCee events, thanks to the Julia compiler's exploitation of single-instruction-multiple-data (SIMD), as well as ergonomic compact data layouts. The full reconstruction history is made available, allowing inclusive and exclusive jets to be retrieved. The package also provides the means to visualise the reconstruction. Substructure algorithms have been added that allow advanced analysis techniques to be employed. The package can read event data from EDM4hep files and reconstruct jets from these directly, opening the door to FCCee and other future collider studies in Julia.

With increasing demands by future and current upgrades of particle physics experiments on rate capabilities and time resolution, the requirements on test beams are also increasing. The current infrastructure at the DESY II test beam facility includes particle tracking telescopes with long integration times, no additional timing but excellent spatial resolution. This results in readouts with multiple particles per trigger, causing ambiguities in tracking and assigning particles to triggers. Also, it is likely not to trigger on particles that pass through a small device under test, leading to inefficient data taking. These issues can be solved by adding TelePix2 as a timing and flexible region of interest trigger layer. TelePix2 is a full scale HV-CMOS chip based on the successful small scale prototype TelePix. The DAQ system and the sensors performance featuring efficiencies above 99 % and a time resolution of 3.844(2) ns are presented. The integration into EUDAQ2 and the AIDA-TLU to seamlessly work in the test beam environment as well as into the analysis chain is described. First successful use cases are highlighted to conclude that TelePix2 is a well-suited timing and trigger layer for test beams

Julia is a mature general-purpose programming language, with a large ecosystem of libraries and more than 12000 third-party packages, which specifically targets scientific computing. As a language, Julia is as dynamic, interactive, and accessible as Python with NumPy, but achieves run-time performance on par with C/C++. In this paper, we describe the state of adoption of Julia in HEP, where momentum has been gathering over a number of years. HEP-oriented Julia packages can already, via UnROOT.jl, read HEP's major file formats, including TTree and RNTuple. Interfaces to some of HEP's major software packages, such as through Geant4.jl, are available too. Jet reconstruction algorithms in Julia show excellent performance. A number of full HEP analyses have been performed in Julia. We show how, as the support for HEP has matured, developments have benefited from Julia's core design choices, which makes reuse from and integration with other packages easy. In particular, libraries developed outside HEP for plotting, statistics, fitting, and scientific machine learning are extremely useful. We believe that the powerful combination of flexibility and speed, the wide selection of scientific programming tools, and support for all modern programming paradigms and tools, make Julia the ideal choice for a future language in HEP.

We propose a dark matter direct-detection strategy using charged particle decays at accelerator-based experiments. If ultralight $(m_\phi \ll \text{eV})$ dark matter has a misalignment abundance, its local field oscillates in time at a frequency set by its mass. If it also couples to flavor-changing neutral currents, rare exotic decays such as $\mu \to e \phi$ and $\tau\to e(\mu)\phi$ inherit this modulation. Focusing on such charged lepton flavor-violating decays, we show that sufficient event samples can enable detection of ultralight dark matter candidates at Mu3e, Belle-II, and FCC-ee.

We perform an updated global analysis of the known and unknown parameters of the standard $3\nu$ framework as of 2025. The known oscillation parameters include three mixing angles $(\theta_{12},\,\theta_{23},\,\theta_{13})$ and two squared mass gaps, chosen as $\delta m^2=m^2_2-m^2_1>0$ and $\Delta m^2=m^2_3-{\textstyle\frac{1}{2}}(m^2_1+m^2_2)$, where $\alpha=\mathrm{sign}(\Delta m^2)$ distinguishes normal ordering (NO, $\alpha=+1$) from inverted ordering (IO, $\alpha=-1$). With respect to our previous 2021 update, the combination of oscillation data leads to appreciably reduced uncertainties for $\theta_{23}$, $\theta_{13}$ and $|\Delta m^2|$. In particular, $|\Delta m^2|$ is the first $3\nu$ parameter to enter the domain of subpercent precision (0.8\% at $1\sigma$). We underline some issues about systematics, that might affect this error estimate. Concerning oscillation unknowns, we find a relatively weak preference for NO versus IO (at $2.2\sigma$), for CP violation versus conservation in NO (1.3$\sigma$) and for the first $\theta_{23}$ octant versus the second in NO ($1.1\sigma$). We discuss the status and qualitative prospects of the mass ordering hint in the plane $(\delta m^2,\,\Delta m^2_{ee})$, where $\Delta m^2_{ee}=|\Delta m^2|+{\textstyle\frac{1}{2}}\alpha(\cos^2\theta_{12}-\sin^2\theta_{12})\delta m^2$, to be measured by the JUNO experiment with subpercent precision. We also discuss upper bounds on nonoscillation observables. We report $m_\beta<0.50$~eV and $m_{\beta\beta}<0.086$~eV ($2\sigma$). Concerning the sum of neutrino masses $\Sigma$, we discuss representative combinations of data, with or without augmenting the $\Lambda$CDM model with extra parameters accounting for possible systematics or new physics. The resulting $2\sigma$ upper limits are roughly spread around the bound $\Sigma < 0.2$~eV within a factor of three. [Abridged]

The Pierre Auger Observatory, the world's largest cosmic ray detector, plays a pivotal role in exploring the frontiers of physics beyond the standard model of particle physics. By the observation of ultra-high energy cosmic rays, Auger provides critical insights into two major scenarios: super heavy dark matter and Lorentz invariance violation. Super heavy dark matter, hypothesized to originate in the early universe, offers a compelling explanation for the dark matter problem and is constrained by Auger through searches for photons and neutrinos resulting from its decay. Lorentz invariance violations, motivated by quantum gravity theories implying deviations from fundamental symmetries, are probed by Auger through alterations of the particle dispersion relation and the energy thresholds of their interactions with astrophysical photons backgrounds.

Low Gain Avalanche Diodes, also known as LGADs, are widely considered for fast-timing applications in high energy physics, nuclear physics, space science, medical imaging, and precision measurements of rare processes. Such devices are silicon-based and feature an intrinsic gain due to a $p{^+}$-doped layer that allows the production of a controlled avalanche of carriers, with multiplication on the order of 10-100. This technology can provide time resolution on the order of 20-30 ps, and variants of this technology can provide precision tracking too. The characterization of LGAD performance has so far primarily been focused on the interaction of minimum ionizing particles for high energy and nuclear physics applications. This article expands the study of LGAD performance to highly-ionizing particles, such as 28-MeV protons, which are relevant for several future scientific applications, e.g. in biology and medical physics, among others. These studies were performed with a beam of 28-MeV protons from a tandem Van de Graaff accelerator at Brookhaven National Laboratory and beta particles from a $^{90}{\rm Sr}$ source; these were used to characterize the response and the gain of an LGAD as a function of bias voltage and collected charge. The experimental results are also compared to TCAD simulations.

Most of the fundamental, emergent, and phenomenological parameters of particle and nuclear physics are determined through parametric template fits. Simulations are used to populate histograms which are then matched to data. This approach is inherently lossy, since histograms are binned and low-dimensional. Deep learning has enabled unbinned and high-dimensional parameter estimation through neural likelihiood(-ratio) estimation. We compare two approaches for neural simulation-based inference (NSBI): one based on discriminative learning (classification) and one based on generative modeling. These two approaches are directly evaluated on the same datasets, with a similar level of hyperparameter optimization in both cases. In addition to a Gaussian dataset, we study NSBI using a Higgs boson dataset from the FAIR Universe Challenge. We find that both the direct likelihood and likelihood ratio estimation are able to effectively extract parameters with reasonable uncertainties. For the numerical examples and within the set of hyperparameters studied, we found that the likelihood ratio method is more accurate and/or precise. Both methods have a significant spread from the network training and would require ensembling or other mitigation strategies in practice.

This paper presents the measurement of charged-hadron and identified-hadron ($K^\mathrm{0}_\mathrm{S}$, $\Lambda$, $\Xi^\mathrm{-}$) yields in photo-nuclear collisions using 1.7 $\mathrm{nb^{-1}}$ of $\sqrt{s_\mathrm{NN}} = 5.02$ TeV Pb+Pb data collected in 2018 with the ATLAS detector at the Large Hadron Collider. Candidate photo-nuclear events are selected using a combination of tracking and calorimeter information, including the zero-degree calorimeter. The yields as a function of transverse momentum and rapidity are measured in these photo-nuclear collisions as a function of charged-particle multiplicity. These photo-nuclear results are compared with 0.1 $\mathrm{nb^{-1}}$ of $\sqrt{s_\mathrm{NN}} = 5.02$ TeV $p$+Pb data collected in 2016 by ATLAS using similar charged-particle multiplicity selections. These photo-nuclear measurements shed light on potential quark-gluon plasma formation in photo-nuclear collisions via observables sensitive to radial flow, enhanced baryon-to-meson ratios, and strangeness enhancement. The results are also compared with the Monte Carlo DPMJET-III generator and hydrodynamic calculations to test whether such photo-nuclear collisions may produce small droplets of quark-gluon plasma that flow collectively.

By combining the effective Lagrangian and Bethe-Salpeter framework, we studied the mass spectra, wave functions, and strong decay widths of the two pentaquark states $P_\psi^N(4440)^+$ and $P_\psi^N(4457)^+$ reported by LHCb in 2019. We calculate the one-boson-exchange interaction kernel of $\bar D^*\Sigma_c$ in the isospin-$\frac12$ configuration. Then we present the Bethe-Salpeter equation(BSE) and wave functions for the bound states of a vector meson and a $\frac12$ baryon with $J^P={\frac12}^-$ and ${\frac32}^-$. By solving the BSE we obtain 2 bound states for both ${\frac12}^-$ and ${\frac32}^-$ spin-parity configuration, and the mass results favor the $(\frac32)^-$ and $(\frac12)^-$ configuration for the $P_\psi^N(4440)$ and $P_\psi^N(4457)$. Combining the effective Lagrangians and the obtained BS wave functions, we further calculate the strong decay channels $\bar D^{(*)0}\Lambda_c^+$, $J/\psi(\eta_c) p$, and $\bar D\Sigma_c^{(*)}$ for the two $P_\psi^N$ states. In the favored $\frac32^-$ and $\frac12^-$ configuration, the obtained total widths are 34.8 MeV and $2.2$ MeV for $P_\psi^N(4440)$ and $P_\psi^N(4457)$, respectively, which are substantially consistent with the LHCb data. The obtained decay widths suggest that $\bar D^{*0}\Lambda_c^+$ and $\bar D\Sigma_c$ are the dominant decay channels to detect $P_\psi^N(4440)$ and $P_\psi^N(4457)$. Taking into account both the mass spectra and decay widths, our results favor the interpretation of $P_\psi^N(4440)$ and $P_\psi^N(4457)$ as the isospin-$\frac12$ $[\bar D^*\Sigma_c]$ molecular states with $J^P$ configuration $(\frac{3}{2})^-$ and $(\frac12)^-$ respectively.

The DarkSide-20k dark matter experiment, currently under construction at LNGS, features a dual-phase time projection chamber (TPC) with a ~50 t argon target from an underground well. At this scale, it is crucial to optimise the argon flow pattern for efficient target purification and for fast distribution of internal gaseous calibration sources with lifetimes of the order of hours. To this end, we have performed computational fluid dynamics simulations and heat transfer calculations. The residence time distribution shows that the detector is well-mixed on time-scales of the turnover time (~40 d). Notably, simulations show that despite a two-order-of-magnitude difference between the turnover time and the half-life of $^{83\text{m}}$Kr of 1.83 h, source atoms have the highest probability to reach the centre of the TPC 13 min after their injection, allowing for a homogeneous distribution before undergoing radioactive decay. We further analyse the thermal aspects of dual-phase operation and define the requirements for the formation of a stable gas pocket on top of the liquid. We find a best-estimate value for the heat transfer rate at the liquid-gas interface of 62 W with an upper limit of 144 W and a minimum gas pocket inlet temperature of 89 K to avoid condensation on the acrylic anode. This study also informs the placement of liquid inlets and outlets in the TPC. The presented techniques are widely applicable to other large-scale, noble-liquid detectors.