Spectral representation and QCD sum rules for nucleon at finite temperature

We examine the problem of constructing spectral representations for two point correlation functions, needed to write down the QCD sum rules in the medium. We suggest constructing them from the Feynman diagrams for the correlation functions. As an example we use this procedure to write the QCD sum rules for the nucleon current at finite temperature

Isovector soft dipole mode in 6Be

By using the 1H(6Li,6Be)n charge-exchange reaction, continuum states in 6Be were populated up to E_t=16 MeV, E_t being the 6Be energy above its three-body decay threshold. In kinematically complete measurements performed by detecting alpha+p+p coincidences, an E_t spectrum of high statistics was obtained, containing approximately ~5x10^6 events. The spectrum provides detailed correlation information about the well-known 0^+ ground state of 6Be at E_t=1.37 MeV and its 2^+ state at E_t=3.05 MeV. Moreover, a broad structure extending from 4 to 16 MeV was observed. It contains negative parity states populated by Delta L=1 angular momentum transfer without other significant contributions. This structure can be interpreted as a novel phenomenon, i.e. the isovector soft dipole mode associated with the 6Li ground state. The population of this mode in the charge-exchange reaction is a dominant phenomenon for this reaction, being responsible for about 60% of the cross section obtained in the measured energy range.Comment: 8 pages, 7 figure

Computation of the winding number diffusion rate due to the cosmological sphaleron

A detailed quantitative analysis of the transition process mediated by a sphaleron type non-Abelian gauge field configuration in a static Einstein universe is carried out. By examining spectra of the fluctuation operators and applying the zeta function regularization scheme, a closed analytical expression for the transition rate at the one-loop level is derived. This is a unique example of an exact solution for a sphaleron model in $3+1$ spacetime dimensions.Comment: Some style corrections suggested by the referee are introduced (mainly in Sec.II), one reference added. To appear in Phys.Rev.D 29 pages, LaTeX, 3 Postscript figures, uses epsf.st

Estimation of Imageability Ratings of English Words Using Neural Networks

The article considers the problem of imageability ratings estimation of English words using artificial neural networks. To train and test the models, we use data of several freely available psycholinguistic databases. We compared two approaches based on different vector representations of words. The first approach uses pre-trained fastText vectors. The second one utilizes explicit word vectors built on the basis of co-occurrence statistics with the most frequent words extracted from the Google Books Ngram corpus. We employed the MRC Psycholinguistic Database to obtain the value of Spearman's correlation coefficient between imageability ratings and their estimations. The highest resulting value equaled 0.882. This significantly improves the results obtained in previous works. The approach proposed in this paper can be used to create large dictionaries with imageability ratings, which is important for many practical problems

Calculation of a confidence interval of semantic distance estimates obtained using a large diachronic corpus

Several methods for detection changes in words semantics and appearance of new word meanings have been suggested. These methods use different techniques of estimating semantic distance between words. They are based both on neural network vector models and on simpler vector representations that use frequencies of n-grams including the studied words. This paper proposes a method for calculation the confidence interval of the semantic distance estimations obtained based on the frequency data of n-grams extracted from the large diachronic corpus. This task is complicated because the question about the law of distribution of frequency fluctuations of words and n-grams, despite a number of studies, remains open. The confidence intervals are calculated by statistic modeling using random permutations of n-gram frequencies. To test the proposed method, estimation of semantic distance between two Russian synonyms is used as an example

Neural Network Recognition of Russian Noun and Adjective Cases in the Google Books Ngram Corpus

The article proposes a solution to the problem of automatic recognition of Russian noun and adjective cases in the Google Books Ngram corpus. The recognition was performed by using information on word co-occurrence statistics extracted from the corpus. Explicit Word Vectors composed of frequencies of ordinary and syntactic bigrams that include a given word were fed to the input of the recognizer. Comparative testing of several types of vector representation and preliminary data normalization were carried out. The trained model was a multi-layer perceptron with a softmax output layer. To train and test the model, we selected 50000 adjectives and 50000 nouns that were most frequently used in the Google Books Ngram Russian subcorpus between 1920 and 2009. Parts of speech and cases were determined using the OpenCorpora electronic morphological dictionary. The recognition accuracy of the cases obtained using the trained neural network model was 96.45% for the nouns and 99.63% for the adjectives

Recognition of Named Entities in the Russian Subcorpus Google Books Ngram

© 2020, Springer Nature Switzerland AG. This paper describes how to build a recognizer to identify named entities that occur in the Google Books Ngram corpus. In the previous studies, the text was usually input to the recognizer to solve the task of named entities recognition. In this paper, the decision is made based on the analysis of the word co-occurrence statistics. The recognizer is a neural network. A vector of frequencies of bigrams or syntactic bigrams including the studied word is fed at the input. The task is to recognize named entities denoted by one word. However, the proposed method can be further applied to recognize two- or multi-word named entities. The recognition error probability obtained on the test sample of 10 thousand words, which are free from homonymy, was 2.71% (F1-score is 0.963). Solving the problem of word classification in Google Books Ngram will allow one to create large dictionaries of named entities that will improve recognition quality of named entities in texts by existing algorithms

Substantiation of the Fault-Block Structure for Effective Additional Exploration and Development of the West-Kommunarsky Field

While the seismic exploration and methodological geological interpretation of geological data for drilling various wells and other types of research are improved for a significant part of the fields being developed in the Samara Region, the reliability of the structure of geological and recoverable oil and gas reserves increases. The complication of the structure and multiple recalculations of reserves at a number of fields are due to the introduction into the development of undiscovered to the required conditions of complex geological fields and licensed areas. The example of the West-Kommunarsky field shows how its geological structure becomes more complex as its study becomes more extensive. Thus, the oil reservoir in the Lower Paschian sediments, according to the created integrated model, has horizontal positions, but with different levels of water-oil contact in adjacent blocks separated by downthrows. The justification of disjunctive dislocations, which have been planned but not tracked due to their uncertainty in seismic data and determination of their main characteristics, was performed by stratigraphic correlation of well sections using the rules of projective geometry and confirmed by other traditional methodical methods. With each new tectonic movement along the strike-slip, a near-faul fracture of rocks is formed parallel to it, as a reflection of geodynamic stresses and energy-intensive processes in the downthrows and strike-slips of rocks along the fault plane. Near-fault regular changes in the fracturing of rocks and the dependence of well productivity on their location relative to the disjunctive make it possible to predict the latitudinal reservoirs zonation in near-fault area: fractured, porous-fractured, fractured-porous and porous types. Such a dialectical process of movement towards a real model of the field ensures the reliability of revised reserves and updated technological documents for the development of fields

Numerical simulations of energy transfer in two collisionless interpenetrating plasmas

Ion stream instabilities are essential for collisionless shock formation as seen in astrophysics. Weakly relativistic shocks are considered as candidates for sources of high energy cosmic rays. Laboratory experiments may provide a better understanding of this phenomenon. High intensity short pulse laser systems are opening possibilities for efficient ion acceleration to high energies. Their collision with a secondary target could be used for collisionless shock formation. In this paper, using particle-in-cell simulations we are studying interaction of a sub-relativistic, laser created proton beam with a secondary gas target. We show that the ion bunch initiates strong electron heating accompanied by the Weibel-like filamentation and ion energy losses. The energy repartition between ions, electrons and magnetic fields are investigated. This yields insight on the processes occurring in the interstellar medium (ISM) and gamma-ray burst afterglows