A5079498366- Particle Accelerators and Free-Electron Lasers
- Particle accelerators and beam dynamics
- Superconducting Materials and Applications
- Particle physics theoretical and experimental studies
- Computational Physics and Python Applications
- Neural Networks and Applications
- Electromagnetic Simulation and Numerical Methods
- Quantum Chromodynamics and Particle Interactions
- Magnetic confinement fusion research
- Model Reduction and Neural Networks
- Scientific Computing and Data Management
- Iterative Learning Control Systems
- Numerical methods for differential equations
- Matrix Theory and Algorithms
- Distributed and Parallel Computing Systems
- Atomic and Subatomic Physics Research
- Advanced Data Processing Techniques
- Chaos control and synchronization
- Characterization and Applications of Magnetic Nanoparticles
- Electronic and Structural Properties of Oxides
- Gyrotron and Vacuum Electronics Research
- Magnetic and transport properties of perovskites and related materials
- Engineering Applied Research
- Dark Matter and Cosmic Phenomena
- Quantum, superfluid, helium dynamics
Deutsches Elektronen-Synchrotron DESY
2020
St Petersburg University
2013-2016
Austrian Academy of Sciences
2007
A new experiment is described to detect a permanent electric dipole moment of the proton with sensitivity $10^{-29}e\cdot$cm by using polarized "magic" momentum $0.7$~GeV/c protons in an all-electric storage ring. Systematic errors relevant are discussed and techniques address them presented. The measurement sensitive physics beyond Standard Model at scale 3000~TeV.
This paper presents a novel approach for constructing neural networks which model charged particle beam dynamics. In our approach, the Taylor maps arising in representation of dynamics are mapped onto weights polynomial network. The resulting network approximates dynamical system with perfect accuracy prior to training and provides possibility tune on additional experimental data. We propose symplectic regularization such that always restricts trained Hamiltonian systems significantly...
Spin-nematic and spin-smectic phases have been reported in magnetic materials, which break rotational symmetry while preserving translational along certain directions. However, until now the analogy to liquid crystals remained incomplete because no analog of cholesteric order was known. Here we show that bilayer perovskite Sr$_3$Fe$_2$O$_7$, previously believed adopt a simple single-$\mathbf{q}$ spin-helical order, hosts two distinct types multi-$\mathbf{q}$ spin textures first...
To search for proton Electric Dipole Moments (EDM) using storage ring with purely electrostatic elements, the concept of frozen spin method has been proposed [1]. This is based on two facts: in equation precession, magnetic field dependence entirely eliminated, and at “magic” energy, precession frequency coincides particle momentum. In case deuteron we have to use electrical simultaneously as will be explained later, keeping direction along momentum pure ring. this article, suggest...
MODE (Matrix integration of Ordinary Differential Equations) is a software package that provides nonlinear matrix maps building for spin-orbit beam dynamics simulation. In this article we briefly describe the developed integrated development environment features and present computational comparison with other simulation tools. mathematical model based on Newton-Lorentz T-BMT equations are expanded to Taylor series up necessary order nonlinearity. The numerical algorithm presentation Lie...
The connection of Taylor maps and polynomial neural networks (PNN) to solve ordinary differential equations (ODEs) numerically is considered. Having the system ODEs, it possible calculate weights PNN that simulates dynamics these equations. It shown proposed architecture can provide better accuracy with less computational time in comparison traditional numerical solvers. Moreover, network derived from ODEs be used for simulation different initial conditions, but without training procedure....
Simulation of beam dynamics is an important step needed to aid the design and configuration particle accelerators. A number methods software packages have been developed address modeling in accelerator physics. However, results simulations often need be validated by simultaneous usage several for solving similar problem comparing results. In addition, different can used together, each a single forming workflow processing steps together. this paper we describe Virtual Accelerator environment...
Nonlinear matrix integration as a mapping approach for ordinary differential equations solving provides powerful technique particle dynamics simulation. The numerical implementation of this method by MODE software package. In program one can build map particles spin-orbit motion in arbitrary electromagnetic fields.
We discuss the electromagnetic corrections to πN scattering lengths generated by minimal e. m. coupling from a knowledge of low energy expansion elastic amplitude as well nucleon and Δ pole terms, all taken for purely strong interactions. In heavy baryon limit there is no free parameter, since masses axial form factors are known. The different terms have clear physical intuitive origin. particular, large isospin breaking contribution isoscalar term appears in charged-pion lengths. attempt...
This paper discusses an approach for incorporating prior physical knowledge into the neural network to improve data efficiency and generalization of predictive models. If dynamics a system approximately follows given differential equation, Taylor mapping method can be used initialize weights polynomial network. allows fine-tuning model from one training sample real dynamics. The describes practical results on experiments with both simple pendulum largest worldwide X-ray source. It is...