Related papers: A framework and implementation for data-driven tri…
With the steady increase in the precision of flavour physics measurements collected during LHC Run 2, the LHCb experiment requires simulated data samples of larger and larger sizes to study the detector response in detail. The simulation of…
Event-based state estimation can achieve estimation quality comparable to traditional time-triggered methods, but with a significantly lower number of samples. In networked estimation problems, this reduction in sampling instants does,…
Most of the computing resources pledged to the LHCb experiment at CERN are necessary to the production of simulated samples used to predict resolution functions on the reconstructed quantities and the reconstruction and selection…
Data-driven modeling is an approach in energy systems modeling that has been gaining popularity. In data-driven modeling, machine learning methods such as linear regression, neural networks or decision-tree based methods are being applied.…
Trigger and data acquisition (TDAQ) systems for modern HEP experiments are composed of thousands of hardware and software components depending on each other in a very complex manner. Typically, such systems are operated by non-expert shift…
Hydraulic systems are widely utilized in industrial applications due to their high force generation, precise control, and ability to function in harsh environments. Hydraulic cylinders, as actuators in these systems, apply force and…
The main b-physics trigger algorithm used by the LHCb experiment is the so-called topological trigger. The topological trigger selects vertices which are a) detached from the primary proton-proton collision and b) compatible with coming…
Particle identification in large high-energy physics experiments typically relies on classifiers obtained by combining many experimental observables. Predicting the probability density function (pdf) of such classifiers in the multivariate…
In recent years fully-parametric fast simulation methods based on generative models have been proposed for a variety of high-energy physics detectors. By their nature, the quality of data-driven models degrades in the regions of the phase…
The data-taking conditions expected in Run 3 of the LHCb experiment at CERN are unprecedented and challenging for the software and computing systems. Despite that, the LHCb collaboration pioneers the use of a software-only trigger system to…
Self-triggered control, a well-documented technique for reducing the communication overhead while ensuring desired system performance, is gaining increasing popularity. However, existing methods for self-triggered control require explicit…
In this paper, we introduce a data-driven framework for synthesis of provably-correct controllers for general nonlinear switched systems under complex specifications. The focus is on systems with unknown disturbances whose effects on the…
Understanding the set of elementary steps and kinetics in each reaction is extremely valuable to make informed decisions about creating the next generation of catalytic materials. With physical and mechanistic complexity of industrial…
The operating conditions defining the current data taking campaign at the Large Hadron Collider, known as Run 3, present unparalleled challenges for the real-time data acquisition workflow of the LHCb experiment at CERN. To address the…
The LHCb experiment at the Large Hadron Collider (LHC) is performing high precision measurements in the flavour sector. An excellent performance of the particle identification (PID) detectors as well as the development of new data taking…
This paper presents a new tool to perform various steps in jet tagger development in an efficient and comprehensive way. A common data structure is used for training, as well as for performance evaluation in data. The introduction of this…
Our predictions for particle physics processes are realized in a chain of complex simulators. They allow us to generate high-fidelity simulated data, but they are not well-suited for inference on the theory parameters with observed data. We…
Nonlinear dynamical behaviours in engineering applications can be approximated by linear-parameter varying (LPV) representations, but obtaining precise model knowledge to develop a control algorithm is difficult in practice. In this paper,…
With the current increase in the data produced by the Large Hadron Collider (LHC) at CERN, it becomes important to process this data in a corresponding manner. To begin with, to efficiently select events that contain relevant information…
This letter explores intelligent scheduling of sensor-to-controller communication in networked control systems, particularly when data transmission incurs a cost. While the optimal controller in a standard linear quadratic Gaussian (LQG)…