Papers

Although photomultiplier tubes (PMTs) are sufficiently sensitive for applications based on counting single photons, the thermionic emission of electrons from the photocathode is one of the dominant background sources. In this study, we modeled the dark count rate of a given PMT as a function of the temperature and external electric field based on the Richardson-Dushman equation and incorporated the Schottky effect. To validate the model, measurements were performed using an eight-centimeter Hamamatsu R14374 PMT equipped with a bialkali photocathode. The dark count rate was measured over a range of temperatures from 10 to 40 degree Celsius. An external electric field was applied to the outside surface of the optical window with the photocathode by varying the potential difference between the photocathode and the surrounding medium from 0 to 1100 V. The result confirmed that the influence of the external potential difference remained relatively small within a difference of 200 V, with the increase in the dark count rate remaining below 50 % across all measured temperatures. This behavior was incorporated into the proposed model by including an error function to predict the dark count rate under operating conditions with varying temperatures and external electric fields.

The first sentence of this abstract–and the introduction to these proceedings–was authored by a human, but the bulk of this document was generated by an agentic AI system. In this talk, I take stock of machine learning (ML) for the LHC physics program over the twelve months from May 2025 to May 2026. The corpus is the HEPML Living Review, split at May 2025 into 1,756 earlier papers and 569 later ones. An AI pipeline surveyed the 569 abstracts, ranked them by citations, recency, theme, and collaboration involvement, and read 103 papers in full (95 from after the split, plus 8 earlier baseline papers), producing a structured note for each. The notes were then synthesized into six claims about the state of the field, checked by independent reviewer agents, and re-verified against the source papers. The headline claim is that (1) ML for high-energy physics (HEPML) stopped being a research area that builds tools and became infrastructure that the LHC physics program depends on: ATLAS and CMS now publish physics results that depend on neural networks, and the archived ALEPH data have re-entered production. The other five claims are: (2) simulation-based inference and foundation models are two revolutions starting to merge; (3) AI agents are the genuinely new front, with 47 papers in twelve months and no adopted measurement yet; (4) "do we trust it?" is the fastest-growing agenda, with one recent paper in five about uncertainty, calibration, or interpretability; (5) what is slowing down is informative, since equivariance was absorbed into a tool and model-specific phenomenology ceded ground to model-agnostic searches; and (6) theory ML crossed a capability threshold in multiple research areas. I close with what is settled, what is incoming, and what is open, and briefly discuss the concerns raised by this way of working with AI.

We initiate the study of quantum state tomography—the experimental reconstruction of the complete spin density matrix—of massless and massive quark-antiquark pairs produced at the future Electron-Ion Collider (EIC). We show that all components of the spin density matrix can be accessed through azimuthal angular correlations between hadron and dihadron pairs generated by the Collins and dihadron fragmentation functions. This enables the experimental investigation of a variety of quantum information properties at the EIC, such as entanglement and Bell-nonlocality. We predict that the recently discovered maximal entanglement in the heavy-quark sector is signaled by a strong modification of the usual Collins angular dependence $\cos(\phi+\phi')$

We present a systematic study of the ground states of pentaquark systems using the neural network variational Monte Carlo method within the constituent quark potential model. We investigate all manifestly exotic pentaquark systems with negative parity, which cannot mix with the conventional baryons through the creation and annihilation of light or strange quark pair. We exhaust 387 color, spin, and isospin configurations and identify 21 pentaquark bound state candidates with binding energies ranging from $2$ to $15$ MeV. A striking observation is that all of the bound states are shallowly bound molecular states, and a deeply bound pentaquark state does not exist. The $QQqq\bar{Q}$, $ssqq\bar{Q}$, $Qsqq\bar{Q}$ and $Qqqq\bar{Q}$ bound states are composed of a heavy vector meson and a baryon, while the $QQqq\bar{s}$ and $Qqqq\bar{s}$ bound states are composed of a $K$ meson and a heavy baryon. As a cross-validation, the ground-state energies of the unbound systems converge to the baryon–meson thresholds from above, which are consistent with the S-wave scattering states and provide a reliable baseline for the bound-state criterion. Especially, we reproduce the lowest scattering states $\eta_c N$ and $\eta_c \Lambda$ in the $qqqc\bar{c}$ and $qqsc\bar{c}$ channels respectively, where the hidden-charm pentaquark resonances were observed experimentally. We also find that all fully heavy pentaquark states are unbound. Our results provide valuable guidance for future pentaquark searches at LHCb, Belle II, and other experiments.

Charged lepton flavor violation (CLFV) is forbidden in the Standard Model (SM) due to massless neutrinos and absence of right-handed neutrinos. The discovery of neutrino oscillations established that the neutrinos are massive and the lepton flavor is not an exact symmetry of nature. A minimal extension of the SM that incorporates right-handed neutrinos gives rise to CLFV through loop-level diagrams involving neutrinos. However, such processes are extremely rare, for instance, the branching fraction of $\mu \to e\gamma$ is expected to be at the level of $10^{-54}$, far beyond the sensitivity of current collider experiments. In contrast, several new physics models predict CLFV decay rates within the sensitivity of current experiments, such as the Belle and Belle II experiments, which have collected the world's largest asymmetric $e^+e^-$ collision data near the $\Upsilon(4S)$ resonance. The large data sample has utilized to explore the possibility of CLFV decays of $\tau$ leptons, $B$ mesons, and bottomonium states. The report reviews some latest results on these CLFV decays at Belle and Belle II.

We propose a training recipe that treats charged-particle trajectory parameter regression on high-energy physics detector data as a sequence-modeling task. Kalman filters and linearized least-squares fits have been the classical standard approach for this task: they are optimal estimators for sparsely sampled linear-Gaussian data and are commonly used for trajectory parameter regression (fitting). The classical fitting techniques implemented for this domain reach a final precision of one part in $10^5$ through detailed modeling of detector geometry, material, detection effects and precise numerical integration of the equations of motion through the detector's inhomogeneous magnetic field. With this study, we demonstrate that using a bidirectional gated linear recurrent encoder, one is able to reproduce the full precision of classical track fitting techniques. Using a custom kernel, we also achieve significantly higher throughput during GPU inference, compared to classical fitting software running on similarly priced multi-core CPU servers representing typically employed hardware. Such a speedup would lead to considerable cost savings for the pattern recognition at the Large Hadron Collider. To our knowledge, this is the first end-to-end learned track fit to reach the full precision and, at the same time, offer the opportunity to reduce the computing costs.

We interpret the $248~\mathrm{keV_{nr}}$ nuclear-recoil candidate reported by LZ through elastic dark matter scattering mediated by a light Majoron. The Majoron provides a natural origin for the required pseudoscalar interaction: it is the pseudo Nambu-Goldstone boson associated with spontaneous lepton number breaking, directly connecting the recoil signal to neutrino mass generation. After a model independent analysis of this idea, we present a concrete realization in a scotogenic ultraviolet completion in which the lightest singlet Majorana fermion is dark matter and acquires both its mass and Majoron coupling from the symmetry breaking dynamics. A vector like up type quark and a type-I Dirac seesaw in quark sector communicate the Majoron interaction to the up quark. At low energies, the resulting portal generates the nonrelativistic operator $\mathcal O_6$, whose momentum dependence reproduces the high-recoil event without overpopulating the lower energy bins. Its spin structure removes the dominant heavy element solar capture channels, while capture on hydrogen is suppressed by poor kinematic matching and small momentum transfer. This construction simultaneously reproduces the LZ recoil spectrum and the observed thermal relic abundance while strongly suppressing solar capture.

The FCC's projected average electricity consumption is 1.3 TWh per year. If supplied entirely by nuclear power, this would represent about 10% of the annual output of a large third-generation nuclear reactor, together with a corresponding share of its radioactive waste. By 2050, however, renewable sources could provide up to 80% of this electricity on a substantially decarbonised European grid, supported by long-term power-purchase agreements and flexible operation. This could reduce the residual nuclear requirement, and its associated waste, by up to a factor of five. This essay asks whether hydrogen could help bridge the remaining periods of low wind and solar generation. It examines production from renewable electricity, transport as hydrogen or ammonia, storage and conversion back into electricity, together with their efficiency losses and carbon footprints. It then considers the still uncertain prospect of naturally occurring hydrogen. None of these routes offers a ready-made solution. But the decades before the FCC begins operation leave time to develop one–and CERN could help accelerate that development by becoming a credible long-term customer.

We report on the design, simulation, and initial testing of Low Gain Avalanche Diode (LGAD) sensors fabricated in 65 nm CMOS technology on 12 inch wafers. These sensors were developed as part of a project to demonstrate full wafer to wafer hybrid bonding of sensors and 28 nm Readout Integrated Circuits (ROICs). The sensor submission and test included standard (reach-through) LGADs, AC coupled LGADs, and Deep Junction LGADs as well as various test structures.

High-throughput data movement is a defining requirement of the WLCG computing model, yet end-to-end performance is often constrained less by the network backbone than by host-level configuration. We present the results of a WLCG mini-capability challenge focused on host optimization at ATLAS and CMS sites (FNAL, UCSD, UNL, BNL, AGLT2, MWT2, and Vanderbilt), using EL8/9 hosts with 25\,Gbps or higher NICs. NET2 participated in a subsequent trans-Atlantic test. The methodology combines ESnet Fasterdata guidance with the OSG-hosted fasterdata-tuning.sh framework, applying TCP, queue, offload, and ring-buffer tuning with save and restore support for safe baseline comparisons. Results show that tuning benefit depends critically on the local bottleneck. Where DTNs and storage were both capable (UNL), FTS throughput rose from 60 to 90\,Gbps. Where storage was the binding constraint (UCSD), iperf3 throughput improved from 20 to 90\,Gbps while FTS was unchanged. Where the NIC was the binding constraint (Vanderbilt, 25\,G NIC), the tuning profile actively reduced throughput, motivating a review of per-site applicability. The challenge also surfaced and resolved a dCache proxying misconfiguration at AGLT2, demonstrating that mini-challenges serve a diagnostic function beyond raw performance measurement.

Reconstruction and simulation at a collider experiment are long chains of specialised algorithms, each tuned to a single step. We explore how one model can serve many of those steps at once, while still producing the intermediate objects (tracks, calorimeter cells, clusters, particles and jets) that make the chain interpretable. To do so, we represent every object in a jet in a single shared token vocabulary and train one model to map any subset of these modalities to any other. A task is then only a choice of which modalities to provide and which to request: particle flow, detector simulation and charged energy subtraction are all directions through the same set of weights. We train over all modality combinations, with a decoder emitting tokens either autoregressively or in parallel. With tokenisation, both architectures train stably with little tuning. In evaluations, both models produce realistic reconstruction and simulation objects, with the autoregressive model particularly faithful to output from Geant4. The autoregressive model also outperforms a state-of-the-art particle flow algorithm on many typical jet reconstruction metrics.

We show that the $\rho\to\pi\pi$ helicity convention used in the time-dependent Dalitz-plot measurements of $B^0\to(\rho\pi)^0$ decays does not match the convention assumed in the subsequent isospin analysis. Once corrected, the tension between the direct determination of the unitarity-triangle angle $\alpha$ from these decays and its indirect determination from global fits decreases from $2.9\sigma$ to $2.1\sigma$. Combined with the $B\to\pi\pi$ and $B\to\rho\rho$ modes, the direct determination becomes $\alpha = (87.0^{+11.8}_{-4.7})^\circ$, compared with the original world average $(84.1^{+3.7}_{-3.0})^\circ$.

Hypothesis-awkward is a collection of Hypothesis strategies for Awkward Array. Awkward Array can represent a wide variety of nested, variable-length, mixed-type data. Many tools that process Awkward Arrays are widely used and actively developed. The unit test cases of many of these tools list predefined input samples. In practice, such samples can cover only a small portion of the vast combinatorial space of Awkward Array instances. Hypothesis, a Python property-based testing library, generates test data that can make test cases fail and automatically explores edge cases. The main strategy of Hypothesis-awkward generates nearly all possible Awkward Arrays, with options to control the layout, data types, missing values, masks, and other array attributes. Property-based tests written with these strategies have begun to run in the continuous integration of Awkward Array; to date, they cover a small part of Awkward Array and have found 37 bugs in it, as well as one in Hypothesis itself. These strategies make the tests of Awkward Array and of the tools that use it more reliable.

Top-quark pair production at the LHC provides a bipartite spin system whose correlations are imprinted in the angular distributions of the decay products and can be studied with quantum-information tools. We investigate whether this spin structure can be used to probe invisible new physics in $pp\to t\bar t+X$, where $X$ is a spin-0 or spin-1 mediator motivated by top-philic simplified dark-matter models. Focusing on the dileptonic channel at the High-Luminosity LHC, we compare the sensitivity of the inclusive event yield, the visible invariant-mass distribution, an event-level estimator of the entanglement marker $D$, and the fiducial spin correlation $\mathcal{D}$ measured as a function of the visible invariant mass. We find that observables retaining spin information improve the expected exclusion sensitivity with respect to rate and kinematic information alone, with $\mathcal{D}(M_{t\bar t}^{\rm vis})$ providing the strongest reach for both mediator spins. The same observables also enhance the discrimination between scalar and pseudoscalar couplings of the spin-zero mediator, with $\mathcal{D}(M_{t\bar t}^{\rm vis})$ again providing the strongest sensitivity, particularly at larger mediator masses. These results show that quantum-information-motivated observables of the $t\bar t$ system can be efficient tools to probe both the presence of invisible new physics and the structure of its couplings to top quarks.

We present a detailed feasibility study of exotic muon decay searches using the muon beam at the High Intensity heavy-ion Accelerator Facility (HIAF). For the decay channel mu to eX0, where X0 denotes a new boson featuring LFV couplings, the produced electron carries very low energy when the mass of X0 approaches the muon mass, making detection challenging. Nevertheless, the high-energy beam at HIAF can boost these electrons up to a measurable energy range. The detector system proposed here comprises front-end scintillators for particle identification (PID) and a main detector consisting of an RPC stack to track decay products and a scintillator for energy measurement. Leveraging the kinematic properties of low momenta and small emission angles of signal electrons, we employ optimized momentum and angular acceptance cuts on the RPC detector to efficiently suppress background events. With this strategy, we obtain an upper limit of 1e-5 on the branching ratio of the exotic muon decay at 95% confidence level, achieving state-of-the-art sensitivity.

The GlueX experiment at Jefferson Lab is well suited for exclusive studies of strangeness production, combining a linearly polarized photon beam at $8.0 < E_\gamma < 8.8$ GeV with a large-acceptance detector that reconstructs weakly decaying hyperons. We outline a research program built on three aspects: (i) spectroscopy of strange mesons, where many excited $K^*$ states remain unestablished and crypto-exotic strange hybrids must be identified from combined spectrum and decay information, anchored by the $K^*(892)$ as a standard candle; (ii) spin dynamics, where the first precise measurements of the complete spin-density matrix elements in the photoproduced $K^*(892)\Lambda$ system beyond the Schilling formalism constrain the $t$-channel strange production mechanism; and (iii) hadronization, probed through the newly published $p\bar{p}$, $\Lambda\bar{\Lambda}$, and $p\bar{\Lambda}$ photoproduction cross sections and emerging $\Lambda\bar{\Lambda}$ spin-correlation measurements. We place these efforts in the context of the broader GlueX strangeness program and give an outlook toward the high-statistics GlueX-II era.

Detector simulation and event reconstruction will be computationally expensive for future $e^+e^-$ collider programs and are currently critical bottlenecks for accurate feasibility studies. To address this challenge, we build a Parnassus model for the CLD detector concept. Parnassus is a framework for automatically tuning a surrogate model, in our case, a conditional flow matching neural network, to emulate a full detector simulation and reconstruction. We train on $e^+e^-\to Z\to q\bar q$ events at $\sqrt{s}=91.2$ GeV processed through a Geant4 simulation of the CLD detector concept and the Pandora particle-flow reconstruction and reproduce single-particle kinematics, particle-IDs, and impact-parameter distributions. We also examine jet- and event-level features, inclusively and split by flavor, and find excellent fidelity, significantly better than the parameterized program Delphes. Furthermore, we train a transformer-based flavor tagger on the reconstructed particle-flow constituents and show that the surrogate preserves the $b/c/s/q$ discrimination of the full CLD reconstruction. The Parnassus CLD model achieves a generation cost of about 1.2 ms (40 ms) per event on a single GPU (CPU), over three (two) orders of magnitude faster than full simulation and reconstruction. Our model is publicly available for feasibility and design studies.

FireworksWeb is a web-based event display utilizing a C++ ROOT-Eve backend with SAPUI5 frontend for interactive 3D visualization of particle physics events directly in the browser. Building upon ROOT-Eve and RenderCore, it eliminates local software installation while maintaining professional-grade event display capabilities. FireworksWeb is currently deployed for live event monitoring in the CMS control room, demonstrating its reliability for real-time data visualization in production environments. The CMS experiment has made a large amount of collision datasets publicly available through the CERN Open Data portal, which are the valuable resources for education, outreach, and research. We have extended FireworksWeb to enable visualization of these open datasets, making particle physics data accessible to diverse audiences without requiring local software installation. Our prototype implementation includes standalone cameras, event filters, configurable collection settings, and projection controls with fish-eye distortion for cylindrical geometries. The web architecture communicating via CGI enables dataset queries and filtered event selection based on physics criteria. We demonstrate the prototype with CMS Open Data events, discuss the technical architecture, and outline applications for education, public outreach, and exploratory physics analysis.

Neutrinos can pass through substantial matter, potentially enabling direct links where electromagnetic paths are obstructed, but their weak interactions make reception difficult. We present two separate calculations. First, a repeated OOK/CRC simulation calibrated to the published NuMI-MINERvA selected-event mean correctly accepts 65.7% of simulated packets with a 40-bit payload and an eight-bit CRC after five repetitions, with about 587 s mean latency under assumed external synchronization. Varying the input mean across its approximate Poisson counting interval gives 60-72% correct acceptance; this is a sensitivity range, not a joint confidence interval. Second, a distinct idealized far-field model gives 24.4 MW peak neutrino-carried on-slot power for a 10 kt receiver at 5,000 km, conditional on 3 GeV neutrinos, 1 mrad divergence, 50% selection efficiency, unit flavor survival, zero background and one-second slots. Neither result establishes a practical long-baseline source or measured CRC performance.

Detailed Geant4 simulation of calorimeter showers is the largest single computing cost of collider experiments, and the High-Luminosity LHC will need about ten times more simulated events than are currently produced. We summarise recent progress in generative point cloud fast simulation for highly granular calorimeters. CaloClouds3 generates photon (electromagnetic) showers, is geometry-independent, and runs on average about 120x faster than Geant4 on a single CPU. CaloHadronic uses transformer attention to extend the point cloud diffusion approach to pion (hadronic) showers spanning the electromagnetic and hadronic calorimeters. AllShowers unifies twelve particle types in a single model with far fewer parameters than the specialised baselines while matching or exceeding their fidelity. We close with cross-geometry transfer learning, which needs two to three orders of magnitude fewer training showers while preserving the generative performance.

The LUX-ZEPLIN (LZ) experiment has reported an event consistent with a $248$ keV nuclear recoil. Explaining the absence of lower-energy recoil events typically calls for some form of upscattering that kinematically forbids such events. In this work, we present a framework in which the LZ observation has a neutrino origin, with atmospheric neutrinos providing the dominant flux in the required energy range. A scenario in which atmospheric neutrinos upscatter to a heavier neutral state would also produce a large number of neutral-current events in neutrino experiments. In particular, scattering on lighter nuclear targets results in much larger nuclear recoil energies compared to xenon, yet no such excess has been observed. We show that this constraint from neutrino experiments can be evaded if atmospheric neutrinos within a narrow energy window first produce a nearly monoenergetic state $N_1$, followed by the upscattering of $N_1$ to its heavier partner $N_2$ in LZ. In such a scenario, scattering on xenon becomes kinematically allowed for $N_2$ masses around $250$ MeV, while scattering on oxygen, carbon, and other targets used in large-scale neutrino experiments remains kinematically forbidden. We show that this two-step process, $\nu \to N_1 \to N_2$, can be realized through a parametric resonance induced by a dark matter background that efficiently produces $N_1$, followed by $N_1 \to N_2$ upscattering mediated by a vector boson in a model with gauged $U(1)_B$. The latter interaction can be sufficiently stronger than the weak interaction, which is necessary to lift the neutrino floor and yield $\mathscr{O}(1)$ event at LZ.

High-dimensional, unbinned neural simulation-based inference often relies on neural ratio estimation, which uses expressive supervised models to estimate density ratios, but a learned ratio by itself provides neither an explicit normalized density nor a generative model. Flow-based surrogate models instead enable tractable density evaluation and efficient sampling, but residual density-estimation errors can limit precision for complex implicit distributions. We propose hybrid neural density estimation, which uses a flow to define a parameter-independent reference distribution, and classifiers to estimate target-to-reference density ratios. Multiplying a learned ratio by the reference density gives an evaluable target density surrogate. The ratio also provides importance weights for integration and resampling. We show how this representation defines an exact Asimov dataset, whose maximum likelihood fit returns the generating parameters. We also show how the tractable reference supplies renewable samples for pseudo-experiments and how it enables methods to reduce the Monte Carlo variance of expected test statistic calculations. We demonstrate the construction in a toy statistical model motivated by high-energy physics measurements, but for which the exact densities are known analytically.

Could a collider become the symbol of everything that must be abandoned to save the climate? In the summer of 2026, this question ran through discussions within the Particles and Fields Division of the French Physical Society. An unacceptable carbon footprint, two EPR nuclear reactors, five hundred deaths, billions to be reallocated and, to top it all, unclear scientific objectives: the objections to CERN's Future Circular Collider (FCC) appeared to form an overwhelming indictment. This essay examines each charge in turn. Grounded in a clear and compelling scientific vision, it confronts emotionally charged imagery with orders of magnitude, distinguishes a project's footprint from its full balance sheet, considers the costs of postponing or abandoning it, and explores ways of reducing its impacts-including the still uncertain prospect of natural hydrogen. The climate alone does not decide the future of the FCC; it requires us to judge the available choices by their real consequences. Developed for the public debate organised by France's National Commission for Public Debate (CNDP) and for the Swiss consultation, this essay is intended for the broadest possible readership, well beyond particle physics and the scientific community. It frames the FCC debate as a choice about the kind of society we want to build: should we organise society around renunciation and ever-shrinking horizons, or transform how we produce and choose a future worth wanting?

Exclusive photoproduction is an important probe of nuclear parton distributions at low Bjorken-$x$. The Good-Walker paradigm relates coherent photoproduction to the average nuclear configuration, giving access to the transverse distribution of gluons in a target, while incoherent photoproduction is sensitive to fluctuations such as gluonic hotspots. Efficiently separating coherent and incoherent interactions is a key challenge for experiments at the future Electron-Ion Collider (EIC). In this article, we study nuclear de-excitation via photon emission, and see how the finite photon detection efficiency leads to misidentification of incoherent emission. We compare the detection efficiency for incoherent $J/\psi$ production using the BeAGLE event generator for Ag-107, Au-197, and Pb-208 targets, for two different forward photon energy thresholds: 50 MeV and 200 MeV. The shell structures of the three species exhibit different incoherent tagging efficiencies due to differences in the lifetimes and energy levels of their excited states. Some of the low-lying states live long enough so that they decay outside the EIC detectors. Especially for the lower photon energy threshold, lead allows a higher tagging efficiency than gold, due to its lack of low-lying and/or long-lived excited states.

Track reconstruction in drift chambers is essential for momentum measurement and particle identification at electron-positron colliders. While Transformer architectures have transformed many sequence-processing domains, their application to tracking in high energy physics is still being explored. We present a model that combines a BERT encoder with a Transformer decoder to perform hit-to-track association through autoregressive sorting. The model is evaluated on the DCTracks open dataset that provides realistic drift chamber simulations with varying particle types, momenta, track multiplicities, and noise conditions. Across single-track, two-track, and multi-track samples, the model achieves high hit and track efficiencies while keeping the rates of clones and fakes very low. It also works well in the reconstruction of displaced vertices. These results show BERT-based sequence-to-sequence models as a promising approach for track reconstruction in low-background, precision-oriented experiments.

Flavour physics and CP violation play a key role for the testing of the Standard Model and search for New Physics at the high-precision frontier. After a compact discussion of the current status of (quark)-flavour physics, I will illustrate theoretical prospects for benchmark processes in the sector of decays of B mesons, ranging from precision determinations of the CP-violating phases of neutral B-meson mixing over non-leptonic decays governed by penguin topologies and channels arising only from tree diagrams to rare loop-induced decays into final states with leptons. Exciting opportunities for theorists and experimentalists arise in the era of the HL-LHC and Belle II and beyond at the FCC-ee.

We propose a novel method to measure the strength and isospin dependence of short-range correlations (SRCs) in nuclei with their collisions at relativistic energies. Since nucleons in the high-momentum tail (HMT) induced by SRCs have large transverse velocities, we find that measuring the yield ratio of free spectator neutrons at large to small transverse distances detected by Zero-Degree Calorimeter (ZDC) array may probe the fraction of nucleons in the HMT. In addition, measuring the yield ratio of ZDC neutrons in central $^{96}$Zr+$^{96}$Zr to $^{96}$Ru+$^{96}$Ru collisions at large transverse distances may probe the isospin dependence of the HMT and SRCs. Compared to traditional scattering experiments, our study illustrates that relativistic heavy-ion collisions may serve as an alternative way of measuring SRCs in colliding nuclei with less final-state interactions.

Observations of collective signatures within jets of particles have been recently reported by measurements at the Large Hadron Collider at CERN laboratory, providing insights on the minimum conditions required for forming a Quark Gluon Plasma state. A quantitative comparison with data measurements on intrajet azimuthal anisotropies and predictions from PYTHIA event generator soft QCD model parameter tunes: Monash, CP5, and QCD-scheme CR is presented. Energetic jets with transverse momentum over 550 GeV from proton-proton collisions at 13 TeV are reconstructed. Results from predictions using the standard E-scheme (ES) and jet axis choice are compared with those from the Winner-Take-All (WTA) frame. Significant differences are present between predictions from WTA and ES frames at the lowest and highest intrajet charged particles multiplicities ($N_{\mathrm{ch}}$), with the QCD-scheme CR tune showing the smallest variation between frames. Predictions for $v_2$ at the highest $N_{\mathrm{ch}}$ are consistent with the data measurements at a 2.3$\sigma$ uncertainty level. These results set new guidance towards the search for intrajet collective effects and understanding of nonperturbative QCD dynamics originated from a single parton.

The Starterkit Lessons online and Starterkit Workshops held in Geneva each year have been the main method of onboarding newcomers to the LHCb experiment since its founding in 2015. The new software corresponding to Upgrade 1 of the LHCb and Run 3 of datataking at the LHC has necessitated a new version of this Starterkit to be written. This new version has made several improvements over the old one, with increased maintainability through testing of examples in CI pipelines, and has also allowed for translations of the Starterkit Lessons. In late 2025 the Run 3 Starterkit lessons were translated into Mandarin Chinese, to allow for a sibling Starterkit event to take place in China, with a dedicated liaison role set up to ensure synchronization between the two translations. To measure the success of the Chinese Starterkit Lessons, analytics have been added revealing that roughly 22% of all visits to the Starterkit website will access at least one Chinese-language page.

The Multi-Purpose Detector (MPD) experiment at NICA is designed to investigate strongly interacting matter at high net-baryon density through a broad program of heavy-ion measurements. Dielectrons constitute one of the key probes in this program, with contributions emitted throughout the entire space-time evolution of the collision. Their experimental measurement is, however, challenged by a large combinatorial background arising primarily from incompletely reconstructed photon conversions and Dalitz decays of light neutral mesons. In this work, we study the performance and capabilities of the MPD experiment for dielectron measurements using simulated minimum-bias $^{209}$Bi+$^{209}$Bi collisions at $\sqrt{s_{NN}}$ = 9.2 GeV. Electron identification is performed using the combined information from the TPC, the TOF detector and the ECal. A multilayer-perceptron classifier is used to optimize electron identification, leading to a substantial increase in electron detection efficiency relative to sequential one-dimensional selections while preserving an electron-sample purity close to unity over a broad momentum range. To address the dominant sources of combinatorial background, a pair-analysis strategy is developed that exploits partially reconstructed electron tracks. The method combines the pair opening angle, the TPC dE/dx signal, and an approximate reconstruction of the pair invariant mass to tag tracks from photon conversions and $\pi^0$ Dalitz decays at the pair level. In the mass interval 0.2 $< m_{ee}<0.7 $ GeV/$c^2$, the method improves the signal-to-background ratio by a factor of about 3.5 with the current track reconstruction algorithm. The study demonstrates the strong potential of the MPD experiment for dielectron measurements at NICA energies and highlights the importance of further improvements in low-$p_{\rm T}$ track reconstruction.