相关论文: A hybrid deep learning approach to vertexing

LHCb is the dedicated heavy flavour experiment at the Large Hadron Collider at CERN. The partially assembled silicon vertex locator (VELO) of the LHCb experiment has been tested in a beam test. The data from this beam test have been used to…

This paper aims at one-shot learning of deep neural nets, where a highly parallel setting is considered to address the algorithm calibration problem - selecting the best neural architecture and learning hyper-parameter values depending on…

The High-Luminosity upgrade of the LHC will see the accelerator reach an instantaneous luminosity of $7\times 10^{34} cm^{-2}s^{-1}$ with an average pileup of $200$ proton-proton collisions. These conditions will pose an unprecedented…

Vertex hunting (VH) is the task of estimating a simplex from noisy data points and has many applications in areas such as network and text analysis. We introduce a new variant, semi-supervised vertex hunting (SSVH), in which partial…

Run-2 of the Large Hadron Collider (LHC) will provide new challenges to track and vertex reconstruction with higher energies, denser jets and higher rates. Therefore the ATLAS experiment has constructed the first 4-layer Pixel Detector in…

The LHCb experiment will operate at a luminosity of $2\times10^{33}$ cm$^{-2}$s$^{-1}$ during LHC Run 3. At this rate the present readout and hardware Level-0 trigger become a limitation, especially for fully hadronic final states. In order…

A new downstream tracking system, known as the Mighty Tracker, is planned to be installed at LHCb during LS4 of the LHC. This will allow an increase in instantaneous luminosity from $2\cdot10^{33}~\mathrm{cm}^{-2}\mathrm{s}^{-1}$ to…

Advanced detector R&D for both new and ongoing experiments in HEP requires performing computationally intensive and detailed simulations as part of the detector-design optimisation process. We propose a versatile approach to this task that…

We introduce Patch Refinement a two-stage model for accurate 3D object detection and localization from point cloud data. Patch Refinement is composed of two independently trained Voxelnet-based networks, a Region Proposal Network (RPN) and…

Despite recent breakthroughs in deep learning methods for image lighting enhancement, they are inferior when applied to portraits because 3D facial information is ignored in their models. To address this, we present a novel deep learning…

Charged-particle reconstruction is a fundamental part of the event reconstruction in modern multi-purpose high-energy physics detectors. This paper describes the algorithms used to reconstruct charged particles and primary vertices with the…

The high-luminosity phase of LHC operations (HL-LHC), will feature a large increase in simultaneous proton-proton interactions per bunch crossing up to 200, compared with a typical leveling target of 64 in Run 3. Such an increase will…

The application of deep learning techniques using convolutional neural networks to the classification of particle collisions in High Energy Physics is explored. An intuitive approach to transform physical variables, like momenta of…

This paper presents a novel hybrid representation learning framework for streaming data, where an image frame in a video is modeled by an ensemble of two distinct deep neural networks; one is a low-bit quantized network and the other is a…

In the next decade, the demands for computing in large scientific experiments are expected to grow tremendously. During the same time period, CPU performance increases will be limited. At the CERN Large Hadron Collider (LHC), these two…

This work uses visual knowledge discovery in parallel coordinates to advance methods of interpretable machine learning. The graphic data representation in parallel coordinates made the concepts of hypercubes and hyperblocks (HBs) simple to…

The LHCb experiment will operate for about five years at a luminosity of 2x10^32 cm^-2 s^-1 and plans are to accumulate a data sample of ~10 fb^-1. Here we present the physics programme and detector design for a future high luminosity phase…

The LHCb detector has been designed to study CP violation and other rare phenomena in B-meson decays up to a luminosity of $\sim 5.10^{32}\rm cm^{-2}s^{-1}$. This paper will describe what is limiting LHCb to exploit the much higher…

LHCb is a general purpose forward detector located at the Large Hadron Collider (LHC) at CERN. Although initially optimized for the study of hadrons containing beauty quarks, the better than expected performance of the detector hardware and…

High energy physics (HEP) experiments at the LHC generate data at a rate of $\mathcal{O}(10)$ Terabits per second. This data rate is expected to exponentially increase as experiments will be upgraded in the future to achieve higher…