Physics of Particles and Nuclei最新文献

Baikal-GVD is a neutrino telescope with an effective volume of approximately 0.7 km located in Lake Baikal. To facilitate observations within the framework of neutrino astronomy, two critical event processing challenges should be addressed: (1) the isolation of the neutrino-induced events from background events caused by extensive air showers, (2) the reconstruction of muon neutrino-induced event parameters, such as the energy of the corresponding muon. This report presents a neural network-based approach, to address these challenges. For the first problem, we show that convolutional neural networks can preserve 64% of neutrino-induced events while achieving the background suppression factor of 10(^{6}). This model could be instrumental in creating catalogs of neutrino-induced events. For the second problem, we develop a neural network model that reconstructs both the energy and its associated uncertainty for a given event. On Monte Carlo simulated data we achieve an error factor of 3 for a wide range of energies (from 10 GeV and above) and a factor of 2 for high energies (from 10 TeV and above). The networks were trained and evaluated using Monte Carlo simulated data.

This article describes a method for alignment of layers in multilayer 2D-coordinate detectors of charged particles with coordinates of particle tracks. We obtain alignment parameters of the layers by minimization of square of difference between reconstructed tracks and measured particle positions. Minimization process produces trigonometric equations which are solved by the Newton method each.

A method allowing to increase a computational efficiency of evaluation of non-local characteristics of a pair of qubits is described. The method is based on the construction of coordinates on a generic section of 2-qubit’s entanglement space ({{mathcal{E}}_{{2 times 2}}}) represented as the direct product of an ordered 3-dimensional simplex and the double coset ({text{SU(2)}} times {text{SU(2)}}{kern 1pt} backslash {kern 1pt} {text{SU(4)}}{kern 1pt} /{kern 1pt} {{{text{T}}}^{{text{3}}}}{kern 1pt} .) Within this framework, the subset (mathcal{S}{{mathcal{E}}_{{2 times 2}}} subset {{mathcal{E}}_{{2 times 2}}}) corresponding to the rank-4 separable 2-qubit states is described as a semialgebraic variety given by a system of 3rd and 4th order polynomial inequalities in eigenvalues of the density matrix, whereas the polynomials coefficients are trigonometric functions defined over a direct product of two regular octahedra.

The FITTER_WEB application was developed to solve the problems of fitting experimental data with multiparameter theoretical functions which model the objects under study. The user is given full control over the fitting process, as well as the ability to use the built-in ROOT mechanisms of parallelism. The contribution describes the structure of the web application, the software tools used for its development, and the specifics of deployment to the JINR cloud infrastructure. The results of the parallel FITTER_WEB analysis of the small-angle scattering data on a samples of polydispersed populations of phospholipid-based unilamellar vesicles are presented. The possibilities of optimizing the web application operation by the allocation of computing resources in the JINR cloud, as well as multi-user calculations, are discussed.

Many engineering applications involve problems with flows in porous media. The problem becomes even more complicated if in the region under consideration there is a system consisting of a free flow of a pure liquid and solid inclusions considered as a fully saturated porous body. This paper proposes a model for calculating flows in the “free flow–porous medium” system based on the generalized quasi-gasdynamic (QGD) system of equations involving Darcy–Forchheimer terms. By analogy with the papers of other authors, where averaging of the Navier–Stokes equations over an elementary volume is used, the system of QGD equations is averaged over a small representative volume of a computational domain in our model. The model is unified for both subdomains of the system—a free flow and a porous medium. This makes possible to perform calculations throughout the entire computational domain using a homogeneous numerical algorithm. Test calculations of flows in a plane channel with a porous plug and in a lid-driven cavity partially filled with a porous medium are presented. In both cases, a good enough agreement with similar calculations by other authors was obtained.

The presented work describes an algorithm for the reconstruction of the simplest hypernuclei ((_{Lambda }^{3})H and (_{Lambda }^{4})H) in the BM@N experiment. We propose a method for separation of double charged nuclei from single charged particles for helium extraction in the formation of daughter pairs from hypernuclei decays. Mass spectra are shown, and their characteristics, such as signal, signal-to-noise ratio and significance of the reconstructed signal are evaluated.

The ATLAS EventIndex is a catalog of all recorded and simulated ATLAS events, one of four main experiments at the LHC accelerator at CERN. The Event Picking Service is one of the components of the ATLAS Event Index. It is used when a user wants to collect interesting events from a huge amount of ATLAS data and reprocess them. The process of retrieving an event can be split into separate tasks. The set of tasks may differ for different event types. Some tasks use external services, which can take a long time to receive results. An error may occur as a result of completing the task. Some of these errors can be corrected automatically by the service, but some require administrator intervention. Failed tasks must be restarted from the specified step after the problem is manually corrected by the administrator. This is critical if the error occurs after a long-running task has been completed. All of the above leads to the fact that the Event Picking Service must be flexible and be able to be customized for a specific situation. This paper is dedicated to describing how elasticity is achieved in the Event Picking Service and how it improves during operation.

Using field-theoretic renormalization group analysis, we study the Kardar–Parisi–Zhang equation of random surface growth with a spatially quenched random noise taking into account turbulent environment described by the Navier–Stokes equation. The latter is taken in the form that allows to model both macroscopic shaking of the fluid and fully turbulent flow. After establishing multiplicative renormalizability of the constructed action functional with additional non-linearity, we perform one-loop calculations (to the leading order in (varepsilon = 4 - d) and (y) where (d) is the space dimension) and find three sets of renormalization group equations’ fixed points: Gaussian fixed point (regime of ordinary diffusion), a curve of fixed points (macroscopic shaking) with infrared attractive segment, and a surface of fixed points for a special case (varepsilon = y) that also involved infrared attractive area. We also investigate marginal values of the coupling constants to look for “hidden” fixed points.

The paper introduces a data and communication security approach in decentralized, cloud-based, self-organizing unmanned aerial vehicles (UAV) swarms. UAV swarms exhibit emergent behavior, where local interactions lead to globally coordinated actions. Peers within the swarm autonomously establish communication links, adapt to changes in hazardous and hostile environments, and collaboratively perform distributed tasks without relying on a fixed infrastructure or external control. Each UAV in the swarm is governed by aerodynamics and physical constraints like lift, drag, and weight which together determine their maneuverability and real-time stability. In our construction, the underlying logical and technological framework consists of three main models, each developed by the authors: the information full exchange during the swarm quasi-random walk; the rotor-router model interpreting the peers’ discrete-time walk, and fault-tolerant gossip/broadcast schemes supporting the swarm resilience to internal failures and external cyber-attacks. The proposed cloud network topology encompasses connectivity options and ensures the swarm’s expected behavior. To ensure swarm security, we suggest embedding a blockchain-equipped robust identity verification scheme to ensure peers’ tamper-proof, transparent, and decentralized authentication, while accounting for the inherent limitations posed by their resource-constrained nature.

A finite element method scheme for solving the boundary value problem of collective nuclear models is presented. Its efficiency is demonstrated on calculations of rotational-vibrational spectra and electrical quadrupole transitions (B(E2)) for the isotopes ¹⁵⁴Gd and ²³⁸U with tabularly specified coefficients of the boundary value problem, including one-well and double-well potential energy surfaces, respectively, calculated from the relativistic mean-field model.