Using frequency analysis and Grover's algorithm to implement known ciphertext attack on symmetric ciphers

In this paper we construct quantum circuit implementing known ciphertext attack on symmetric cipher. We assume that plaintext is in natural language and have known letter distribution. Our method allows to find key using one query to (quantum) decryption oracle and has O(√{pipe}K{pipe}) time complexity, where K-set of possible keys. © 2013 Pleiades Publishing, Ltd

From graphs to keyed quantum hash functions

© 2016, Pleiades Publishing, Ltd.We present two new constructions of quantum hash functions: the first based on expander graphs and the second based on extractor functions and estimate the amount of randomness that is needed to construct them. We also propose a keyed quantum hash function based on extractor function that can be used in quantum message authentication codes and assess its security in a limited attacker model

Physics discovery in nanoplasmonic systems via autonomous experiments in Scanning Transmission Electron Microscopy

Physics-driven discovery in an autonomous experiment has emerged as a dream application of machine learning in physical sciences. Here we develop and experimentally implement a deep kernel learning workflow combining the correlative prediction of the target functional response and its uncertainty from the structure, and physics-based selection of acquisition function, which autonomously guides the navigation of the image space. Compared to classical Bayesian optimization methods, this approach allows to capture the complex spatial features present in the images of realistic materials, and dynamically learn structure-property relationships. In combination with the flexible scalarizer function that allows to ascribe the degree of physical interest to predicted spectra, this enables physical discovery in automated experiment. Here, this approach is illustrated for nanoplasmonic studies of nanoparticles and experimentally implemented in a truly autonomous fashion for bulk- and edge plasmon discovery in MnPS3, a lesser-known beam-sensitive layered 2D material. This approach is universal, can be directly used as-is with any specimen, and is expected to be applicable to any probe-based microscopic techniques including other STEM modalities, Scanning Probe Microscopies, chemical, and optical imaging

New automata definition of language for game development

© 2016 Taylor & Francis Group, London.In this paper, we describe a novel Domain-Specific Language (DSL), which is useful for describing AI in games. This DSL is based on a firm theoretical ground of finite automata theory. We provide full specification of the language and discuss the optimized implementation. We use this DSL in the development of an educational game “Bolgar XIV”

Minimizing collisions for quantum hashing

© Medwell Journals, 2017.Hashing is a widely used technique in computer science. The recently proposed quantum hashing has also proved its usefulness in a number of applications. The key property of both classical and quantum hashing is the ability to withstand collisions however, the notion of collision itself is different in the classical and quantum setting. In this study we analyze the set of numeric parameters that determine the probability of quantum collisions for the quantum hashing. Although, there is a general method of obtaining good hashing parameters, it makes sense for comparatively large inputs. That is why we construct different methods to complement the general one. We present two explicit optimization algorithms for computation of quantum hashing parameters: one is based on the genetic approach and the other uses the annealing simulation. The solution to the considered optimization problem can be used for the variety of quantum hash functions and also provides a solution to the general problem of constructing sets of pairwise distinguishable states in low-dimensional spaces

Nitrided Ferroalloy Production By Metallurgical SHS Process: Scientific Foundations and Technology

The main objective of this paper is to present results of the research in the development of a specialized self-propagating high-temperature synthesis (SHS) technology for ferroalloy composites, as applied to steelmaking. The problem of creating such a production cycle has been solved by developing a new approach to the practical implementation of self-propagating high-temperature synthesis, as applied to metallurgy. The metallurgical variation of SHS is based on the use of different metallurgic alloys (including waste in the form of dust from ferroalloy production) as basic raw materials in the new process. Here, the process of synthesis by combustion is realized through exothermic exchange reactions. The process produces a composite, based on inorganic compositions with a bond of iron and/or alloy based on iron. It has been shown that in terms of the aggregate state of initial reagents, metallurgical SHS processes are either gasless or gas-absorbing. Combustion regimes significantly differ when realized in practice. To organize the metallurgical SHS process in weakly exothermic systems, different variations of the thermal trimming principle are used. In the present study, self-propagating high-temperature synthesis of ferrovanadium nitride, ferrochromium nitride and ferrosilicon nitride; which is widely used in steel alloying, was investigated. Keywords: self-propagating high-temperature synthesis (SHS); composite ferroalloys; nitrides; borides; filtration combustion; ferrovanadium nitride ferrochromium nitride and ferrosilicon nitrid

Dynamic Geometry Environments as a Tool for Computer Modeling in the System of Modern Mathematics Education

Abstract. This paper discusses a number of issues and problems associated with the use of computer models in the study of geometry in university, as well as school mathematics in order to improve its efficiency. We show that one of the efficient ways to solve a number of problems in nowadays mathematics education is to use dynamic geometry environment GeoGebra. We also provide some examples of computer models created with GeoGebra. Keywords: dynamic geometry environment; GeoGebra, computer mathematics; innovations; learning process; interactive computer models; Internet; mathematics education. Введение. Системы динамической геометрии (СДГ), или интерактивные геометрические системы (ИГС), представляют собой программные среды, позволяющие создавать и манипулировать геометрическими построениями, прежде всего на плоскости (в плоской Евклидовой геометрии) СДГ предназначены прежде всего для решения задач школьного курса геометрии: в них можно создавать всевозможные конструкции из точек, векторов, отрезков, прямых; строить графики элементарных функций, которые также возможно динамически изменять варьированием некоторого параметра (или нескольких параметров), входящего(их) в уравнение; строить перпендикулярные и параллельные заданной прямой линии, серединные перпендикуляры, биссектрисы углов, касательные; определять длины отрезков, площади многоугольников и замкнутых кривых и т.д. Кроме того, в некоторых СДГ координаты точек могут быть введены вручную на панели объектов, а уравнения кривых и касательных к ним в строке ввода при помощи соответствующих команд. СДГ также позволяют работать и с более сложными для понимания студента разделами геометрии: проективной [2] и дифференциальной. Особую ценность представляют присущие некоторым СДГ возможности визуализации различного рода теорем, а также поэтапного воспроизведения решения задач и иных демонстраций. Все это делает такие системы весьма привлекательными для школьного и даже вузовского образования. Следует также отметить, что СДГ признаны во всем мире наиболее эффективным средством обучения математике с применением информационно-компьютерных технологий