We investigate primordial black hole (PBH) production via the collapse of supercritical domain walls in a quadratic f(R)-gravity model with tensor extensions. The effective field theory for an extra space’s scalar curvature provides a foundation for the formation of these dense walls. In our work, domain walls are found to be supercritical. Their properties were extensively studied in the literature, where it was demonstrated that they create wormholes and escape into baby universes through them. Closure of the wormhole leads to black hole creation, providing a mechanism for the production of primordial black holes in our model. We calculate the mass spectrum of such black holes and mass distribution within clusters of them. When accretion is accounted for, the black holes produced under this mechanism present viable dark matter candidates.

The interpretation of high-precision Galactic cosmic-ray data from AMS-02, CALET, DAMPE, etc., is fundamentally limited by nuclear cross-sections uncertainties. This proceeding highlights the results presented at the XSCRC2024 workshop, which aims at bringing together the cosmic-ray, nuclear, and particle physics communities, with the goal of improving cross-section measurements across various domains, from nuclei production for constraining cosmic-ray transport parameters, to antiproton and anti-deuteron production for dark matter searches. This workshop lead to a comprehensive roadmap for new cross-section measurements in the next decade, as well as other outcomes.

Identified-hadron production (p, π±, K±) in π++Be at plab=60GeV/c (s≃10.6GeV) is investigated using Pythia 8.315 (Monash tune) with the Angantyr extension. Differential multiplicities d2n/(dpdθ) are confronted with NA61/SHINE measurements across standard θ bins. Within the fluctuating-radii Double-Strikman (DS) scheme, two unsuppressed opacity mappings are compared to quantify systematics. In addition, a minimal extension is introduced: a flat, post-classification, channel-wise acceptance applied after ND/SD/DD/EL tagging. It acts on primary and secondary πN pairs, keeps hadronization fixed (Lund string), and leaves the internal event generation of each admitted subcollision unchanged. Opacity-mapping variations alone induce only percent-level differences and do not resolve the soft/forward tensions. By contrast, the flat acceptance—interpretable as a reduced effective ND weight—improves agreement across species and angles. It hardens the forward π+ spectra and lowers large-θ yields, produces milder charge-asymmetric changes for π− consistent with the weaker leading feed, suppresses proton yields at all angles (with a residual ∼30% forward high-p deficit), and improves K±, with a stronger effect for K+ than K−. These results show that a geometry-blind reweighting of the subcollision mixture suffices to capture the main NA61/SHINE trends for π++Be at SPS energies without modifying hadronization. The approach provides a controlled baseline for subsequent, channel-balanced refinements and broader π+A tuning.

This paper presents the procedures employed for experimental functional and performance characterization of a 2 × 2 pixel prototype detection system tailored specifically for the X and Gamma-ray Imaging Spectrometer (XGIS) instrument onboard the THESEUS mission. The XGIS system comprises of two coded masked wide field cameras integrated with monolithic SDDs (Silicon Drift Detectors) and CsI:Tl (Thallium doped-Cesium Iodide) scintillators, contributing to its broad X and γ-ray detection range. Given the space instrumentation complexity, thorough requirement qualification and testing procedures are essential. This work focuses on working principle, the testing setup utilized, and observed performance for the small scale four-pixel XGIS prototype. Furthermore, the alignment of light output performance of the four-pixel SDD and scintillator prototype detection system with the XGIS instrument requirements is emphasized.

Our Sun is the closest X-ray astrophysical source to Earth. As such, it makes for a strong case study to better understand astrophysical processes. Solar flares are particularly interesting as they are linked to coronal mass ejections as well as magnetic field reconnection sites in the solar atmosphere. Flares can therefore provide insightful information on the physical processes at play on their production sites but also on the emission and acceleration of energetic charged particles towards our planet, making it an excellent forecasting tool for space weather. While solar flares are critical to understanding magnetic reconnection and particle acceleration, their hard X-ray polarization—key to distinguishing between competing theoretical models—remains poorly constrained by existing observations. To address this, we present the CUbesat Solar Polarimeter (CUSP), a mission under development to perform solar flare polarimetry in the 25–100 keV energy range. CUSP consists of a 6U-XL platform hosting a dual-phase Compton polarimeter. The polarimeter is made of a central assembly of four 4 × 4 arrays of plastic scintillators, each coupled to multi-anode photomultiplier tubes, surrounded by four strips of eight elongated GAGG scintillator bars coupled to avalanche photodiodes. Both types of sensors from Hamamatsu are, respectively, read out by the MAROC-3A and SKIROC-2A ASICs from Weeroc. In this manuscript, we present the preliminary spectral performances of single plastic and GAGG channels measured in a laboratory using development boards of the ASICs foreseen for the flight model.

This paper discusses issues encountered during the early development of the instrument on the Imaging X-ray Polarimetry Explorer (IXPE), a NASA–ASI Small Explorer mission launched on 9 December 2021. IXPE has observed about 100 sources, yielding meaningful polarimetry for most of them. An on-board calibration system mitigated most non-ideal detector behaviors during operations. Data from the on-board polarized and unpolarized X-ray sources are routinely ingested by the flight pipeline to correct the instrument response in a manner transparent to users. Based on its scientific return and payload health, the IXPE mission has been extended through 2028. The lessons learned are informing the design of next-generation X-ray polarimetry missions, as discussed elsewhere in these conferences.

The hadron calorimeter is a central component of the CMS detector, vital for measuring hadron energies and reconstructing missing transverse momentum. This paper reviews its performance before and after the Phase 1 upgrade (completed in 2019), which upgraded both back-end and front-end electronics, including photodetectors and charge-integrating ADC with precise-timing TDC, as well as its depth segmentation in the barrel and endcaps. This paper describes energy reconstruction algorithms that suppress out-of-time signals, along with high-precision timing alignment and multi-step energy calibration procedures to mitigate radiation damage and improve energy resolution Performance evaluations using proton–proton collision data demonstrate that the upgraded detector and reconstruction techniques achieve good resolution and robust operation under high-luminosity conditions.

The blast-wave model with Boltzmann–Gibbs statistics is used to examine the transverse momentum spectra of K∗0 mesons generated at the Relativistic High-Energy Collider (RHIC) Beam Energies with mid-rapidity (|y|<1) in symmetric Au−Au collisions. There is a clear correlation between the extracted kinetic freeze-out temperature (T0) and transverse flow velocity (βT) in various collision centralities and center-of-mass energies (sNN). Since a larger initial energy density delays freeze-out and a shorter system lifetime limits cooling, T0 is directly proportional to both sNN and peripheral collisions. On the other hand, βT drops in peripheral symmetric collisions due to weaker collective expansion, while it rises with sNN because of larger pressure gradients. The concurrence between the thermal and collective energy components in the expanding fireball is reflected in the obvious anti-correlation between T0 and βT. These findings support hydrodynamic predictions and offer important new information about QGP’s freeze-out behavior.

The study of the antimatter component in cosmic rays is essential for the understanding of their acceleration and propagation mechanisms, and is one of the most powerful tools for the indirect search of dark matter. Current methods rely on magnetic spectrometers for charge-sign discrimination, but these are not suitable for extending measurements to the TeV region within a short timeframe of a few decades. Since most of present and upcoming high-energy space experiments use large calorimeters, it is crucial to develop an alternative charge-sign discrimination technique that can be integrated with them. The Electron/Positron Space Instrument (EPSI) project, a two-year R&D initiative launched in 2023 with EU recovery funds, aims to address this challenge. The basic idea is to exploit the synchrotron radiation emitted by charged particles moving through Earth’s magnetic field. The simultaneous detection of an electron/positron with an electromagnetic calorimeter and synchrotron photons with an X-ray detector is enough to discriminate between the two particles at the event level. The main challenge is to develop an X-ray detector with a very large active area, high X-ray detection efficiency, and a low-energy detection threshold, compliant with space applications. In this paper, we give an overview of the EPSI project, with a focus on the general idea of the detection principle, the concept of the space instrument, and the design of the X-ray detector.

Next-generation space observatories for high-energy gamma-ray astrophysics will increase scientific return using onboard machine learning (ML). This is now possible thanks to today’s low-power, radiation-tolerant processors and artificial intelligence accelerators. This paper provides an overview of current and future ML applications in gamma-ray space missions focused on high-energy transient phenomena. We discuss onboard ML use cases that will be implemented in the future, including real-time event detection and classification (e.g., gamma-ray bursts), and autonomous decision-making, such as rapid repointing to transient events or optimising instrument configuration based on the scientific target or environmental conditions.