Related papers: Hyperloop -- The ALICE analysis train system for R…
Data science applications increasingly rely on heterogeneous data sources and analytics. This has led to growing interest in polystore systems, especially analytical polystores. In this work, we focus on a class of emerging multi-data model…
The online event reconstruction for the ALICE experiment at CERN requires processing capabilities to process central Pb-Pb collisions at a rate of more than 200 Hz, corresponding to an input data rate of about 25 GB/s. The reconstruction of…
The upgrade of the Inner Tracking System (ITS) of ALICE (A Large Ion Collider Experiment) will extend measurements of heavy-flavour hadrons and low-mass dileptons to a lower transverse momentum than currently achieved and increase the…
The application of agentic AI systems in autonomous decision-making is growing in the areas of healthcare, smart cities, digital forensics, and supply chain management. Even though these systems are flexible and offer real-time reasoning,…
AliEn (ALICE Environment) is a GRID-like system for large scale job submission and distributed data management developed and used in the context of ALICE, the CERN LHC heavy-ion experiment. With the aim of exploiting upcoming Grid resources…
Coupled AI-Simulation workflows are becoming the major workloads for HPC facilities, and their increasing complexity necessitates new tools for performance analysis and prototyping of new in-situ workflows. We present SimAI-Bench, a tool…
We introduce TRACE, a cross-domain engineering framework for trustworthy agentic AI in operationally critical domains. TRACE combines a four-layer reference architecture with an explicit classical-ML vs. LLM-validator split (L2a/L2b), a…
A general overview of the results obtained by the ALICE experiment from the analysis of the $\PbPb$ data sample collected at the end of 2010 during the first heavy-ion run at the LHC is presented.
The ATLAS experiment at the Large Hadron Collider has a broad physics programme ranging from precision measurements to direct searches for new particles and new interactions, requiring ever larger and ever more accurate datasets of…
The LHC with its unprecedented energy offers unique opportunities for groundbreaking measurements in p+p, p+A and A+A collisions even beyond the baseline experimental designs. ALICE is setting up a program of detector upgrades, which could…
Recent measurements in small collision systems at the LHC show striking similarities between high multiplicity pp, p-Pb collisions and Pb-Pb collisions. In particular, study of hadronic resonances provide valuable information about the…
The upgraded Inner Tracking System (ITS2) of the ALICE experiment at the CERN Large Hadron Collider is based on Monolithic Active Pixel Sensors (MAPS). With a sensitive area of about 10 $m^2$ and 12.5 billion pixels, ITS2 represents the…
The LHCb Stripping project is a pivotal component of the experiment's data processing framework, designed to refine vast volumes of collision data into manageable samples for offline analysis. It ensures the re-analysis of Runs 1 and 2…
High Energy Physics (HEP) distributed computing infrastructures require automatic tools to monitor, analyze and react to potential security incidents. These tools should collect and inspect data such as resource consumption, logs and…
Endowing robots with the ability to rearrange various large and heavy objects, such as furniture, can substantially alleviate human workload. However, this task is extremely challenging due to the need to interact with diverse objects and…
The third version of the open-domain dialogue system Alquist developed within the Alexa Prize 2020 competition is designed to conduct coherent and engaging conversations on popular topics. The main novel contribution is the introduction of…
Recent advances in reinforcement learning (RL) have predominantly leveraged neural network policies for decision-making, yet these models often lack interpretability, posing challenges for stakeholder comprehension and trust. Concept…
The very high growth of Intelligent Transportation Systems (ITS) has generated an urgent requirement for secure, effective, and context-aware data sharing mechanisms, especially over heterogeneous and geographically dispersed settings. This…
The LHCb collaboration continues to heavily utilize the Run 1 and Run 2 legacy datasets well into Run 3. As the operational focus shifts from the legacy data to the live Run 3 samples, it is vital that a sustainable and efficient system is…
Large language models (LLMs) deployed on edge servers are increasingly used in latency-sensitive applications such as personalized assistants, recommendation, and content moderation. However, the non-stationary nature of user data…