A new idea is developed that the fluid–fluid phase transition in warm dense hydrogen is related to the partial ionization of molecular hydrogen H2 with formation of molecular ions H2+ and H3+ . Conventional ab initio quantum modeling is applied. Proton pair correlation functions (PCF) obtained are used for the nonconventional diagnostics of the phase transition and elucidation of its nature for temperatures 700-1500 K. Short- and longrange changes of PCF’s are studied. H2 molecules ionization and molecular ions H2+ and H3+ appearance is revealed. The validity of the soft sphere model is tested for the long-range order.

The article shows that large artificial neural networks can be used for mutual ordering of a set of multi-dimensional patterns of the same nature (handwritten text, voice, smells, taste). Each neural network must be pre-trained to recognize one of the patterns. As a measure of ordering one can use the entropy of patterns "Strangers" that are input to a neural network trained to recognize only examples of the pattern "familiar". The neural network after training reduces the entropy of the examples of the pattern "Familiar" and increases the entropy of examples of pattern "Stranger." It is shown that the entropy measure of the ordering always has two global minima. The first minimum corresponds to the pattern "Familiar", the second to the inversion of the pattern "Familiar". It is also shown that the Hamming distance between the patterns belonging to two different groups (groups of the two global minima) is always as large as possible.

In this work we discuss complex dynamics arising in a model describing behavior of an encapsulated bubble contrast agent oscillating close to an elastic wall. We demonstrate presence of three coexisting attractors in the system. We propose an efficient numerical procedure based on the continuation method that can be used to locate the area of coexistence of these attractors in the parameters space. We provide area of coexistence of three attractors obtained by means of the proposed procedure.

When combined with error-correction codes reception techniques based on nonparametric hypothesis testing and order statistics provide strong immunity to different types of interference including multiuser interference. That makes communication systems using such reception techniques most appealing candidates for various applications such as Machine-to-Machine (M2M) communications and Internet Of Things (IOT). Unfortunately analytical treatment of communication systems with nonparametric reception remains a cumbersome task. Therefore simulation remains the main tool for the development of such systems. For multiuser systems supporting hundreds of active users and operating in fading channels (e.g. IOT) time spending grows drastically hampering the design process. Thus the development of simplified multiuser channel models is of great interest. In this paper two simplified mathematical models of multiuser interference for the case of a single user nonparametric reception are proposed. The effectiveness of the proposed models is compared by means of modulation. Special attention is paid to the problem of software implementation of the models proposed.

The CRAYFIS experiment proposes to use privately owned mobile phones as a ground detector array for Ultra High Energy Cosmic Rays. Upon interacting with Earth’s atmosphere, these events produce extensive particle showers which can be detected by cameras on mobile phones. A typical shower contains minimally-ionizing particles such as muons. As these particles interact with CMOS image sensors, they may leave tracks of faintly-activated pixels that are sometimes hard to distinguish from random detector noise. Triggers that rely on the presence of very bright pixels within an image frame are not efficient in this case. We present a trigger algorithm based on Convolutional Neural Networks which selects images containing such tracks and are evaluated in a lazy manner: the response of each successive layer is computed only if activation of the current layer satisfies a continuation criterion. Usage of neural networks increases the sensitivity considerably comparable with image thresholding, while the lazy evaluation allows for execution of the trigger under the limited computational power of mobile phones.

In this volume we have collected papers based on the presentations given at the International Conference on Computer Simulations in Physics and beyond (CSP2015), held in Moscow, September 6-10, 2015. We hope that this volume will be helpful and scientifically interesting for readers.

The Conference was organized for the first time with the common efforts of the Moscow Institute for Electronics and Mathematics (MIEM) of the National Research University Higher School of Economics, the Landau Institute for Theoretical Physics, and the Science Center in Chernogolovka. The name of the Conference emphasizes the multidisciplinary nature of computational physics. Its methods are applied to the broad range of current research in science and society. The choice of venue was motivated by the multidisciplinary character of the MIEM. It is a former independent university, which has recently become the part of the National Research University Higher School of Economics.

Current mechanisms of radiation-induced chromosomal aberration (CA) formation suggest misrepair of chromosomal lesions being in spatial proximity. In this case CAs have to depend on pattern of chromosomal contacts and on chromosome spatial organization in a cell nucleus. We were interested in whether variation of nucleus 3D organization results in difference of radiation induced CA formation frequency. Experimental data available do not provide information sufficient for definite conclusions. To have more deep insight in this issue we developed the biophysical modeling technique taking into account different levels of chromosome/nuclear organization and radiation damage of DNA and chromosomes. Computer experiments on gamma irradiation were carried out for two types of cells with different 3D organization of nuclei, preferentially peripheral and internal. CA frequencies were found to depend on spatial positioning of chromosomes within a nucleus which determines a pattern of interchromosomal contacts. For individual chromosomes this effect can be more pronounced than for genome averaged. Since significant part of aberrations, for example dicentrics, results in cell death, the proposed technique is capable of evaluating radiosensitivity of cells, both normal and cancer, with the incorporation of 3D genome information. This predictive technology allows to reduce uncertainties of prognosis of biological effects of radiation compared to phenomenological methods and may have variety of biomedical applications, in particular, in cancer radiation therapy.

High-energy physics experiments rely on reconstruction of the trajectories of particles produced at the interaction point. This is a challenging task, especially in the high track multiplicity environment generated by p-p collisions at the LHC energies. A typical event includes hundreds of signal examples (interesting decays) and a significant amount of noise (uninteresting examples). This work describes a modification of the Artificial Retina algorithm for fast track finding: numerical optimization methods were adopted for fast local track search. This approach allows for considerable reduction of the total computational time per event. Test results on simplified simulated model of LHCb VELO (VErtex LOcator) detector are presented. Also this approach is well-suited for implementation of paralleled computations as GPGPU which look very attractive in the context of upcoming detector upgrades.

High-energy physics experiments rely on reconstruction of the trajectories of particles produced at the interaction point. This is a challenging task, especially in the high track multiplicity environment generated by p-p collisions at the LHC energies. A typical event includes hundreds of signal examples (interesting decays) and a significant amount of noise (uninteresting examples). This work describes a modification of the Artificial Retina algorithm for fast track finding: numerical optimization methods were adopted for fast local track search. This approach allows for considerable reduction of the total computational time per event. Test results on simplified simulated model of LHCb VELO (VErtex LOcator) detector are presented. Also this approach is well-suited for implementation of paralleled computations as GPGPU which look very attractive in the context of upcoming detector upgrades.

We consider N-component synchronization models defined in terms of stochastic particle systems with special interaction. For general (nonsymmetric) Markov models we discuss phenomenon of the long time stochastic synchronization. We study behavior of the system in different limit situations related to appropriate changes of variables and scalings. For N = 2 limit distributions are found explicitly.

We investigate combinatorial properties of a higher invariant of magnetic lines. Assume that a 3-component link L is modeled by a magnetic eld B, which is represented by 3 closed magnetic lines. Main Theorem relates the integral invariant M(B) and a combinatorial invariant ~M (L), dened from the Conway polynomial. As a corollary of Main Theorem, asymptotic properties for combinatorial links are proposed. The combinatorial invariant ~M satises these asymptotic properties.

L´evy stochastic processes and related fine analytic properties of probability distributions such as infinite divisibility play an important role in construction of stochastic models of various distributed networks (e.g., local clock synchronization), of some physical systems (e.g., anomalous diffusions, quantum probability models), of finance etc. Nevertheless, little is known about limit probability laws resulted from the long time behavior of such stochastic systems. In this paper we will focus on the impact of interaction graph topologies on limit laws of multicomponent synchronization models.

We review recent advances in the analysis of the Wang–Landau algorithm, which is designed for the direct Monte Carlo estimation of the density of states (DOS). In the case of a discrete energy spectrum, we present an approach based on introducing the transition matrix in the energy space (TMES). The TMES fully describes a random walk in the energy space biased with the Wang–Landau probability. Properties of the TMES can explain some features of the Wang–Landau algorithm, for example, the flatness of the histogram. We show that the Wang–Landau probability with the true DOS generates a Markov process in the energy space and the inverse spectral gap of the TMES can estimate the mixing time of this Markov process. We argue that an efficient implementation of theWang–Landau algorithm consists of two simulation stages: the original Wang–Landau procedure for the first stage and a 1/t modification for the second stage. The mixing time determines the characteristic time for convergence to the true DOS in the second simulation stage. The parameter of the convergence of the estimated DOS to the true DOS is the difference of the largest TMES eigenvalue from unity. The characteristic time of the first stage is the tunneling time, i.e., the time needed for the system to visit all energy levels.

In this paper we construct a smooth arc without bifurcation points joining source- sink diffeomorphisms on the two-dimensional sphere.

We consider a family of nonlinear diffusion equations with nonlinear sources. Weassume that all nonlinearities are polynomials with respect to a dependent variable. Thetraveling wave reduction of this family of equations is an equation of the Lienard–type. Applyingrecently obtained criteria for integrability of Lienard–type equations we find some new integrablefamilies of traveling wave reductions of nonlinear diffusion equations as well as their generalanalytical solutions.

We study a model of a spatial evolutionary game, based on the Prisoner’s dilemma for two regular arrangements of players, on a square lattice and on a triangular lattice. We analyze steady state distributions of players which evolve from irregular, random initial configurations. We find significant differences between the square and triangular lattice, and we characterize the geometric structures which emerge on the triangular lattice.

We present preliminary results of the investigation of the properties of the Markov random walk in the energy space generated by the Wang-Landau probability. We build transition matrix in the energy space (TMES) using the exact density of states for one-dimensional and two-dimensional Ising models. The spectral gap of TMES is inversely proportional to the mixing time of the Markov chain. We estimate numerically the dependence of the mixing time on the lattice size, and extract the mixing exponent.

The SHiP experiment is designed to search for very weakly interacting particles beyond the Standard Model which are produced in a 400 GeV/c proton beam dump at the CERN SPS. The critical challenge for this experiment is to keep the Standard Model background level negligible. In the beam dump, around 10^11 muons will be produced per second. The muon rate in the spectrometer has to be reduced by at least four orders of magnitude to avoid muoninduced backgrounds. It is demonstrated that new improved active muon shield may be used to magnetically deflect the muons out of the acceptance of the spectrometer.

In this work, we experimentally studied optical delay lines on silicon nitride platform for telecomm wavelength (1550 nm). We modeled the group delay time and fabricated spiral optical delay lines with different waveguide widths and radii as well as measured their transmission. For the half etched rib waveguides we achieved the losses in the range of 3 dB/cm

We discuss a class of optimization problems related to stochastic models of wireless sensor networks (WSNs). We consider a sensor network that consists of a single server node and m groups of identical client nodes. The goal is to minimize the cost functional which accumulates synchronization errors and energy consumption over a given time interval. The control function u(*t*) = (*u*1(*t*),...,um(*t*)) corresponds to the power of the server node transmitting synchronization signals to the groups of clients. We find the structure of extremal trajectories. We show that optimal solutions for such models can contain singular arcs.

In the process of astronomical observations collected vast amounts of data. BSA (Big Scanning Antenna) LPI used in the study of impulse phenomena, daily logs 87.5 GB of data (32 TB per year). These data have important implications for both short-and long-term monitoring of various classes of radio sources (including radio transients of different nature), monitoring the Earth's ionosphere, the interplanetary and the interstellar plasma, the search and monitoring of different classes of radio sources. In the framework of the studies discovered 83096 individual pulse events (in the interval of the study highlighted July 2012 - October 2013), which may correspond to pulsars, twinkling springs, and a rapid radio transients. Detected impulse events are supposed to be used to filter subsequent observations. The study suggests approach, using the creation of the multilayered artificial neural network, which processes the input raw data and after processing, by the hidden layer, the output layer produces a class of impulsive phenomena.