Related papers: RootInteractive tool for multidimensional statisti…
This study explores integrating reinforcement learning (RL) with idealised climate models to address key parameterisation challenges in climate science. Current climate models rely on complex mathematical parameterisations to represent…
In ultra-relativistic heavy-ion collisions at $\sqrt{s_{NN}}$ = 5.5 TeV at the ALICE experiment at the LHC, interactions between the high-$p_{T}$ partons and the hot, dense medium produced in the collisions, are expected to lead to jet…
Remote sensing image change detection is one of the fundamental tasks in remote sensing intelligent interpretation. Its core objective is to identify changes within change regions of interest (CRoI). Current multimodal large models encode…
Real-world machine learning applications may require functions that are fast-to-evaluate and interpretable. In particular, guaranteed monotonicity of the learned function can be critical to user trust. We propose meeting these goals for…
We present RooAgent as a natural-language interface for Root-based high energy physics data analysis. The package provides physics analysis functions as tools that an LLM agent invokes in response to plain-language prompts. Two operating…
Holistic analysis of many real-world problems are based on data collected from multiple sources contributing to some aspect of that problem. The word fusion has also been used in the literature for such problems involving disparate data…
The increasing data rates in modern high-energy physics experiments such as ALICE at the LHC and the upcoming ePIC experiment at the Electron-Ion Collider (EIC) present significant challenges in real-time event selection and data storage.…
The ROOT based Offline and Online Analysis (ROAn) framework was developed to perform data analysis on data from Depleted P-channel Field Effect Transistor (DePFET) detectors, a type of active pixel sensors developed at the MPI…
In reinforcement learning (RL), agents often operate in partially observed and uncertain environments. Model-based RL suggests that this is best achieved by learning and exploiting a probabilistic model of the world. 'Active inference' is…
The ALICE experiment is a dedicated heavy ion physics detector at the LHC with unique capabilities for studying identified particle production. In this proceeding preliminary results for RAA for pi and K+p (sum), are reported, based on…
Accurate net load forecasting is vital for energy planning, aiding decisions on trade and load distribution. However, assessing the performance of forecasting models across diverse input variables, like temperature and humidity, remains…
ALICE is the dedicated heavy ion experiment at the LHC at CERN and records lead-lead collisions at a rate of up to 50 kHz in LHC Run 3. To cope with such collision and data rates, ALICE uses a new GEM TPC with continuous readout and a…
The ALICE Collaboration proposes a completely new apparatus, ALICE 3, for the LHC Runs 5 and 6. The detector consists of a large pixel-based tracking system covering eight units of pseudorapidity, complemented by multiple systems for…
We present MiroThinker v1.0, an open-source research agent designed to advance tool-augmented reasoning and information-seeking capabilities. Unlike previous agents that only scale up model size or context length, MiroThinker explores…
The Large Hadron Collider at CERN currently provides p$+$p collisions at center of mass energies of $\sqrt{s} = 7$~TeV, which allow to study high $\pT$ particle production and jet properties in a new energy regime. For a clear…
This thesis investigates the application of state-of-the-art advances in generative neural networks for fast simulation of the Zero Degree Calorimeter (ZDC) neutron detector in the ALICE experiment at CERN. Traditional simulation methods…
The ALICE apparatus at CERN has undergone significant upgrade during the LHC's Long Shutdown 2 to increase the experiment's rate capability and measurement precision for Run 3 and Run 4. One of the key detectors newly introduced to the…
ALICE is the dedicated heavy-ion experiment at the CERN Large Hadron Collider (LHC). Its main tracking and particle-identification detector is a large volume Time Projection Chamber (TPC). The TPC has been designed to perform well in the…
After close to 20 years of preparation, the dedicated heavy ion experiment ALICE took first data at the CERN LHC accelerator with proton collisions at the end of 2009 and with lead nuclei at the end of 2010. After a short introduction into…
The ALICE experiment at the CERN Large Hadron Collider (LHC) is a multi-purpose particle detector, mainly focused on the study of quark-gluon plasma (QGP) in heavy-ion collisions. In the forward rapidity region, 2.5 $<$ y $<$ 4, ALICE is…