Motivated by recent developments in atomic frequency standards employing the eﬀect of coherent population trapping (CPT), we propose a theoretical framework for the frequency modulation spectroscopy of the CPT resonances. Under realistic assumptions we provide simple yet non-trivial analytical formulae for the major spectroscopic signals such as the CPT resonance line and the in-phase/quadrature responses. We discuss the inﬂuence of the light shift and, in particular, derive a simple expression for the displacement of the resonance as a function of modulation index. The performance of the model is checked against numerical simulations, the agreement is good to perfect. The obtained results can be used in more general models accounting for light absorption in the thick optical medium.
We report on the development and fabrication of a 9-channel coarse wavelength- division multiplexing for telecommunication wavelengths (1550 nm) using anti-reflection contra-directional couplers, based on silicon nitride (Si3N4) rib waveguide. The transmitted and reflected spectrum in each channel of the demultiplexer were measured. The average full width at half maximum of the transmitted (reflected) spectra is about 3 nm. 1
Demographic and population structure inference is one of the most important problems in genomics. Population parameters such as effective population sizes, population split times and migration rates are of high interest both themselves and for many applications, e.g. for genome-wide association studies. Hidden Markov Model (HMM) based methods, such as PSMC, MSMC, coalHMM etc., proved to be powerful and useful for estimation of these parameters in many population genetics studies. At the same time, machine and deep learning have began to be used in natural science widely. In particular, deep learning based approaches have already substituted hidden Markov models in many areas, such as speech recognition or user input prediction. We develop a deep learning (DL) approach for local coalescent time estimation from one whole diploid genome. Our DL models are trained on simulated datasets. Importantly, demographic and population parameters can be inferred based on the distribution of coalescent times. We expect that our approach will be useful under complex population scenarios, which cannot be studied with existing HMM based methods. Our work is also a crucial step in developing a deep learning framework which would allow to create population genomics methods for different genomic data representations.
Daily operation of a large-scale experiment is a resource consuming task, particularly from perspectives of routine data quality monitoring. Typically, data comes from different sub-detectors and the global quality of data depends on the combinatorial performance of each of them. In this paper, the problem of identifying channels in which anomalies occurred is considered. We introduce a generic deep learning model and prove that, under reasonable assumptions, the model learns to identify ’channels’ which are affected by an anomaly. Such model could be used for data quality manager cross-check and assistance and identifying good channels in anomalous data samples. The main novelty of the method is that the model does not require ground truth labels for each channel, only global flag is used. This effectively distinguishes the model from classical classification methods. Being applied to CMS data collected in the year 2010, this approach proves its ability to decompose anomaly by separate channels.
It is often suggested that inter-particle distance in stable dusty plasma structures decreases with cooling as a square root of neutral gas temperature. Deviations from this dependence (up to the increase at cryogenic temperatures) found in the experimental results for the pressures range 0.1–8.0 mbar and for the currents range 0.1–1.0 mA are given. Inter-particle distance dependences on the charge of particles, parameter of the trap and the screening length in surrounding plasma are obtained for different conditions from molecular dynamics simulations. They are well approximated by power functions in the mentioned range of parameters. It is found that under certain assumptions thermophoretical force is responsible for inter-particle distance increase at cryogenic temperatures
The very first step towards a challenging goal of creation of monolithic generic neuro-symbolic systems is application of sub-symbolic ideas to particular symbolic algorithms like aggregation of fuzzy linguistic assessments during Linguistic Decision Making. A novel theoretical idea is to express this aggregation as structural manipulations and translate them in a neuroalgorithm. Tensor Product Representation (TPR) methodology provides a generic framework of designing neural networks that do not require training and produce an exact result equivalent to the result of symbolic algorithms. This paper demonstrates design of TPR-based arithmetic as a basic building block for expressing linguistic assessments aggregation on a sub-symbolic level and a neural architecture for the basic arithmetic operation.
The paper presents a possibility of estimating a human cardiac pacemaker using combined application of nonlinear integral transformation and fuzzy logic, which allows carrying out the analysis in the real-time mode. The system of fuzzy logical conclusion is proposed, membership functions and rules of fuzzy products are defined. It was shown that the ratio of the value of a truth degree of the winning rule condition to the value of a truth degree of any other rule condition is at least 3.
The primary purpose of this paper is to provide an overview of existing education solutions for IoT and develop proposals for their improvement. The study draws analysis of current conditions of the educational IoT sphere, a comparative analysis of educational products used for teaching of undergraduate students. With that the article describes the architecture of our own software and hardware platform for learning IOT. Moreover, this paper reviews methods and technical instruments employed to design software and hardware appliances.
This article describes a technical solution of the system generator of configuration files of development boards “Marsohod 2”, “Marsohod 2bis”, “Marsohod 3”, “Marsohod 3bis” for Quartus Prime software. The solution includes a web interface for the system generator, generation of configuration files, introduction of additional modules into the generated project, such as a frequency divider, Uart8 (RS-232), a module for preventing of contact bounce, and several types of simplest MIPS processor cores. This technical solution improves the convenience and speed of FPGA development, as well as reduces its entry threshold which can be significant for starting developers.
In this paper, we fabricate and experimentally study focusing grating couplers for lithium niobate on an insulator photonic platform. The transmittance of a waveguide equipped with in- and out-couplers with respect to the grating period is measured with and without silicon dioxide cladding applied. Our results show the influence of silicon dioxide cladding on the efficiency and the central wavelength of grating couplers and can be used to improve grating coupling efficiency. Our study is supported by numerical simulations.
We report on development of superconducting single-photon detectors (SSPD) with high intrinsic quantum efficiency in the wavelength range 1.31 – 3.3 μm. By optimization of the NbN film thickness and its compound, we managed to improve detection efficiency of the detectors in the range up to 3.3 μm. Optimized devices showed intrinsic quantum efficiencies as high as 10% at mid-IR range.
At the present, the actual task is using 3D printers for the manufacture of certain objects with a given level of price / quality ratio. In many cases, it is economically feasible to use a low cost 3D printer. Therefore, it is necessary to have models that predict and classify the printing quality of such printers. The work has involved the development and assembly of a low cost 3D printer. For this purpose, the creation of geometric models of the component parts and the printer itself was carried out, and engineering calculations and optimization of the received designs were performed. It has been developed a printer control system. An experiment was conducted to produce cubes with different printing parameters on such printer. Based on regression analysis, linear and logistic regressions were constructed. Linear regression will allow to assess the quality level of the result depending on the printing parameters, and the logistic regression will allow to classify and predict the probability of manufacturing objects with a given quality level. The influence of each of the print parameters on the quality and result of the classification was analyzed.
This work includes a review of MIPS architecture processor cores and a review of network topology consisting of routers. It was demonstrated by realization of 2 multiprocessor systems developed on the basis of mesh topology using modified schoolMIPS soft-processor cores, in which architecture additional blocks and instructions were added, and routers with XY routing. As a result, the obtained NoC performance is up to 1.87 Gbit/s (4 processor cores), and up to 1.54 Gbit/s (10 processor cores). The extended processor core schoolMIPS consumes 452 ALMs and 1692 bits of memory; NoC of 4 processor cores takes 2223 ALMs and 9136 bits of memory; NoC of 10 processor cores – 5696 ALMs and 22840 bits of memory. The obtained results suggest that there is a possibility of NoC development with the number of nodes up to 200 nodes on Stratix IV GX EP4SGX230 (DE4).
We performed a numerical study of a surrounding medium influence on coupling efficiency between a microdisk resonator supporting optical whispering gallery modes and a straight optical waveguide. Quality factors of the modes and relative optical power coupled to the waveguide were calculated using COMSOL Multiphysics environment. It was shown that the most efficient coupling takes place when propagation constants of the modes of the microdisk and the waveguide match. The coupling can be significantly strengthened by increasing the index of the surrounding medium.
We performed a numerical study of optical whispering gallery modes in microdisk resonators modified via their embedding in a homogeneous dielectric surrounding or covering with a thin dielectric layer. Mode spectra and electromagnetic field distributions were calculated through the solution of the Helmholtz equation using COMSOL Multiphysics environment. It is shown that the modification results in the decimation of the resonator modes.
Recombination in liquid in diffusion regime is considered using molecular dynamics. A method to take into account change in interaction potential due to recombination act is suggested. Different processes that affect recombination rate are considered. It is found that ion cluster pair formation is important in addition to diffusion motion of ions. Results of the computation suggest that no other factors affect recombination at least within accuracy of 10%. It is shown with help of variation of recombination threshold radius and ion radius.
This article describes expediency of using a graphics processing unit (GPU) in big data processing in the context of digital images processing. It provides a short description of a parallel computing technology and its usage in different areas, definition of the image noise and a brief overview of some noise removal algorithms. It also describes some basic requirements that should be met by certain noise removal algorithm in the projection to computer tomography. It provides comparison of the performance with and without using GPU as well as with different percentage of using CPU and GPU.
This paper presents a system providing recommendations for optimizing the LHCb data storage. The LHCb data storage system is a hybrid system. All datasets are kept as archives on magnetic tapes. The most popular datasets are kept on disks. The recommendation system takes the dataset usage history and metadata (size, type, configuration etc.) to generate a recommendation report. In this article present how we use machine learning algorithms to predict future data popularity. Using these predictions it is possible to estimate which datasets should be removed from disk. We use regression algorithms and time series analysis to find the optimal number of replicas for datasets that are kept on disk. Based on the data popularity and the number of replicas optimization, the recommendation system minimizes a loss function to find the optimal data distribution. The loss function represents all requirements for data distribution in the data storage system. We demonstrate how the recommendation system helps to save disk space and to reduce waiting times for jobs using this data.
We describe all formal symmetric solutions of dispersionless 2D Toda hierarchy. This classication we use for solving of two classical problems: 1) The calculation of conformal mapping of an arbitrary simply connected domain to the standard disk; 2) Calculation of 2-Hurwitz numbers of genus 0.
We propose new deterministic and stochastic models for synchronization of clocks in nodes of distributed networks. An external accurate time server is used to ensure convergence of the node clocks to the exact time. These systems have much in common with mathematical models of opinion formation in multiagent systems. There is a direct analogy between the time server/node clocks pair in asynchronous networks and the leader/follower pair in the context of social network models.
The description of the properties of the plasma–dust system can be improved by using elements of thermodynamics. Divergence of the dusty particles trajectories allows us to estimate Krylov–Kolmogorov–Sinai entropy for a system of dust particles in plasma. In this way, we can verify if the behavior of the K-entropy of the dusty plasma subsystem in the partial equilibrium is close to the physical entropy. A picture of the divergence of trajectories for the dusty plasma model is obtained. The memory time of the model is estimated. The dependence of K-entropy on the number of dust particles and on the average kinetic energy of the dust particles are presented. The similarity of the behavior of the K-entropy parameter in the plasma–dust system and in the classical molecular-dynamic gas model is shown. The possibility of using this parameter for the description of dusty plasma is discussed.