CERN has embarked on a new programme of Particle Accelerator Efficiency improvements that is inspired by lessons learned from the last years of operation and by the latest technology advancements. The field of equipment automation is being addressed through a mix of concrete developments and pilot projects. This paper presents the work on preparing a new paradigm of accelerator equipment automation and reporting, anomaly detection and advanced analysis for predictive maintenance. An example of such automation is presented using the case of the SPS injection kicker (MKP) and the automatic classification of vacuum spike events to provide additional context to experts and stand-by personnel during interventions on the installation. This contribution also outlines how Kicker magnet faults caused by high voltage electrical discharge events can be distinguished from standard vacuum spike events, thus allowing a rapid automatic recovery without expert interventions.

Optics tuning and correction in the Interaction Point (IP) region of the FCC-ee is critical for achieving the target luminosity. By utilizing dedicated IP tuning knobs, lattice errors at multiple IP's are corrected to restore the design optics, enabling dynamic aperture studies on the fully corrected lattice. These studies, conducted using the pyAT optics code, assess the impact of corrections and the effectiveness of various tuning knobs in mitigating beam size growth at the IP's while maintaining beam stability. Benchmarking of pyAT results with the Xsuite framework ensures the reliability and robustness of the analysis. This approach provides valuable insights into the precision of IP optics tuning and its role in optimizing the collider's operational performance.

As previously described*, high-intensity beams of ultra-bright light sources present new machine protection concerns by creating high-energy-density (HED) conditions in beam-intercepting components. Simulating these HED conditions required us to develop a method for coupling three codes for particle dynamics (elegant), particle-matter interaction (MARS/FLUKA), and hydrodynamics (FLASH). This paper discusses the recent advancements made toward this effort including the use of phase and temperature dependent thermal properties such as thermal conductivity and specific heat, transition from MARS to FLUKA, and improved liquid phase dynamics. For benchmarking purposes we compare simulation results with experimental data collected during the final run of the Advanced Photon Source (APS) ring as well as observations of collimator surface damage following the first user run of the upgraded machine. This methodology is also used to make predictions of collimator damage in future APS-Upgrade (APS-U) runs and to examine locations where synchrotron radiation may lead to HED conditions.

Bayesian optimization is an effective method for designing complex systems with costly, non-analytic black box objective functions. It enables efficient exploration of the parameter space, making it well-suited for challenging problems in accelerator design which involve computationally intensive simulations such as FLUKA. This study presents a framework to apply Bayesian optimization techniques to design the magnetic horn of Neutrinos from Stored Muons (nuSTORM) experiment for increased pion capture. The optimization process spans a wide range of operational energies, from 1 to 7 GeV, to address the physics reach of nuSTORM. Batch sampling is enabled through specialized acquisition functions, allowing simulations to run in parallel across a computational cluster and significantly reducing the time needed to identify optimal target and horn configurations for the muon source. By leveraging the surrogate models generated through Bayesian optimization, horn configurations at different energies are systematically compared. This facilitates sensitivity studies to determine a minimal set of horn designs that efficiently cover the nuSTORM kinematic range.

The National Synchrotron Radiation Research Cen-ter (NSRRC) operates the Taiwan Light Source (TLS) and Taiwan Photon Source (TPS) accelerators and approximately 40 end stations, about 10 of which are dedicated to biological research. Biologists from around the world utilize these facilities to investigate the structures and functions of biomolecules and cells, advancing the life sciences. Given the potential risks associated with biological experiments, particularly those involving biohazards, ongoing risk management is essential to ensure biosafety, as protocol failures often caused by human error or inadequate technique can increase the likelihood of exposure. This paper outlines the biosafety management framework at NSRRC, which supports users in sample classification, document submission, and risk identification to facili-tate a safe and efficient experimental review process.

Nonlinear effects in particle accelerators have historically been treated as harmful influences that necessitate various mitigation schemes. Therefore, the simulation tools available are largely focused on identifying and correcting resonances. However, recent advances proved that nonlinear beam dynamics enables new techniques for manipulating particle beams and can characterise diffusion and chaos in particle accelerators. The simulation tools currently available for these purposes are difficult to integrate across different frameworks. This paper presents Xnlbd, a new Python package extending the Xsuite simulation framework, which aims to provide a unified set of tools for analysing nonlinear beam dynamics phenomena. It allows the visualisation of highly nonlinear phase spaces, the efficient finding of both stable and unstable fixed points and separatrices, the calculation of resonance driving terms and normal forms, and the computation of dynamic indicators for the detection of chaotic motion.

As part of its ongoing and future contributions to high-Q/high-G activities in major international projects such as PIP-II, ILC Technology Network, and the European Strategy for Particle Physics, INFN-LASA is upgrading its experimental facility for vertical cold tests of superconducting cavities. This upgrade will enable cavity performance characterization in a low residual magnetic field environment and with dedicated diagnostics for understanding possible performance limitation. In parallel, state-of-the-art surface treatments aimed at achieving high-Q and high-G performance are being developed and applied to single and multicell cavities at different frequencies. This paper presents the current status of the facility, its key features, an overview of cavities currently in production, and the experimental results obtained to date.

The implementation of a new product data management (PDM) and product lifecycle management (PLM) system at CERN has significantly improved lifecycles and workflows for 3D integration studies, thanks to the advanced features and tools of the platform. This new PDM/PLM system has provided an opportunity to reassess and optimize user methodologies, focusing on better organization of 3D CAD data, improved collaboration with mechanical and services design offices, and more effective validation processes. Additionally, enhanced traceability throughout workflows is expected to boost overall process quality. This paper examines the challenges encountered during the transition as well as the benefits of the new PDM/PLM, highlighting its contribution to increased efficiency and quality.

With the advancement of science and technology, people are more dependent on the Internet and digital technology. We continue to improve our network system to increase speed and security of information transmission at NSRRC. We had established various levels of Information Security System (ISMS) documents and conducted many tasks and obtained the certification of ISO-27001.

The MADOCA control system was developed for the present SPring-8 in 1997. Nowadays we faced problems of outdated technologies of the MADOCA. In 2025, SPring-8 upgrade project "SPring-8-II" will be started. Toward to the SPring-8-II, we decided to renovate the MADOCA control system. The new control system inherits former MADOCA's concepts, which are characterized by SVOC-style messaging, database-oriented framework, and distributed control design using network system. In contrast with the inherited concepts, we renew the base technologies. Upgrades of messaging platform, data acquisition, and databases are already reported.\*,** We continue to develop other components. For edge computing, we use both MicroTCA.4 and generic PC server instead of outdated VME system. By combining EtherCAT with these edge computers, we support various I/O interfaces with simple wiring. We also provide REST API as database reading method to support external system linkage. Prior to the SPring-8-II project, the new control system is introduced into NanoTerasu. In this paper, we report the latest developments and prospective of the new control system.

These days designing an accelerator consist of prototyping and testing adequate commissioning software. Digital twins serve as natural test benches for validating and monitoring the required physics software stack. These twins must align with the current design state of the accelerator from the project's inception to the machine's commissioning. The authors have developed a modern digital twin framework based on software design patterns. Its architecture emphasizes clean design principles with minimal coupling between components. Its setup requires only lattice and device configuration data. Thanks to its design, it seamlessly integrates into prototyping environments or control system infrastructures. In this paper, we briefly describe the design patterns underlying this architecture, highlight the flexibility and advantages of the infrastructure, and outline the steps needed to implement it for a machine currently lacking a digital twin.

This work investigates the potential of using synthetic images generated from CAD models to train an object detector for identifying components of a particle accelerator. The study focuses on magnets within the new ALS Accumulator Ring at Lawrence Berkeley National Laboratory. Generating large volumes of real-world training data is often challenging in such complex systems. To address this, CAD files were converted into 3D models and used to produce diverse synthetic datasets. These datasets were augmented with a smaller set of real-world images to train a YOLOv8-based model. This approach aims to evaluate whether synthetic images can effectively support the development of object detectors in environments where real data collection is limited. The study lays the groundwork for future development of real-time recognition tools to assist accelerator operations.

Function Generator Controllers (FGCs) are key devices used in CERN’s converter control systems to regulate and monitor the power converters that supply current to the magnets in the accelerator complex. To ensure the reliability and enhance the quality assurance of the software that controls these devices, the FGC Test Manager has been developed. It encompasses the Python library pyfgc_test_framework, which provides an interface for test scripts to seamlessly communicate with the FGC devices; and a web tool providing an interface to run test scripts on schedule and on demand, assign tests to resources, review test results, and directly access test logs. The web tool uses Vue 3 for the frontend and FastAPI with a PostgreSQL database for the backend. Test execution is handled by the GitLab Pipeline API, which executes pipelines directly in the repository containing the tests. This paper presents the design and functionality of the FGC Test Manager and the improvements it brings to the quality assurance of CERN's converter control systems.