18,301 research outputs found

    Geometric structure and information change in phase transitions

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    We propose a toy model for a cyclic order-disorder transition and introduce a new geometric methodology to understand stochastic processes involved in transitions. Specifically, our model consists of a pair of Forward and Backward Processes (FP and BP) for the emergence and disappearance of a structure in a stochastic environment. We calculate time-dependent PDFs and the information length L, which is the total number of different states that a system undergoes during the transition. Time-dependent PDFs during transient relaxation exhibit strikingly different behaviour in FP and BP. In particular, FP driven by instability undergoes the broadening of the PDF with large increase in fluctuations before the transition to the ordered state accompanied by narrowing the PDF width. During this stage, we identify an interesting geodesic solution accompanied by the self-regulation between the growth and nonlinear damping where the time scale Ļ„ of information change is constant in time, independent of the strength of the stochastic noise. In comparison, BP is mainly driven by the macroscopic motion due to the movement of the PDF peak. The total information length L between initial and final states is much larger in BP than in FP, increasing linearly with the deviation Ī³ of a control parameter from the critical state in BP while increasing logarithmically with Ī³ in FP. L scales as | ln D| and Dā€¾Ā½ in FP and BP, respectively, where D measures the strength of the stochastic forcing. These differing scalings with Ī³ and D suggest a great utility of L in capturing different underlying processes, specifically, diffusion vs advection in phase transition by geometry. We discuss physical origins of these scalings and comment on implications of our results for bistable systems undergoing repeated order-disorder transitions (e.g. fitness)

    PCV12 THE ECONOMIC BURDEN OF ATRIAL FIBRILLATION AND FLUTTER IN KOREA

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    Rotational symmetry and degeneracy: a cotangent-perturbed rigid rotator of unperturbed level multiplicity

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    We predict level degeneracy of the rotational type in diatomic molecules described by means of a cotangent-hindered rigid rotator. The problem is shown to be exactly solvable in terms of non-classical Romanovski polynomials. The energies of such a system are linear combinations of t(t+1) and 1/[t(t+1)+1/4] terms with the non-negative integer principal quantum number t=n+|/bar{m}| being the sum of the degree n of the polynomials and the absolute value, |/bar{m}|, of the square root of the separation constant between the polar and azimuthal motions. The latter obeys, with respect to t, the same branching rule, |/bar{m}|=0,1,..., t, as does the magnetic quantum number with respect to the angular momentum, l, and, in this fashion, the t quantum number presents itself indistinguishable from l. In effect, the spectrum of the hindered rotator has the same (2t+1)-fold level multiplicity as the unperturbed one. For small t values, the wave functions and excitation energies of the perturbed rotator differ from the ordinary spherical harmonics, and the l(l+1) law, respectively, while approaching them asymptotically with increasing t. In this fashion the breaking of the rotational symmetry at the level of the representation functions is opaqued by the level degeneracy. The model provides a tool for the description of rotational bands with anomalously large gaps between the ground state and its first excitation.Comment: 10 pages, 6 figures; Molecular Physics 201

    Linkless octree using multi-level perfect hashing

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    The standard C/C++ implementation of a spatial partitioning data structure, such as octree and quadtree, is often inefficient in terms of storage requirements particularly when the memory overhead for maintaining parent-to-child pointers is significant with respect to the amount of actual data in each tree node. In this work, we present a novel data structure that implements uniform spatial partitioning without storing explicit parent-to-child pointer links. Our linkless tree encodes the storage locations of subdivided nodes using perfect hashing while retaining important properties of uniform spatial partitioning trees, such as coarse-to-fine hierarchical representation, efficient storage usage, and efficient random accessibility. We demonstrate the performance of our linkless trees using image compression and path planning examples.postprin

    An International Comparison Study Exploring the Influential Variables Affecting Studentsā€™ Reading Literacy and Life Satisfaction

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    The Program for International Student Assessment (PISA) aims to provide comparative data on 15-year-oldsā€™ academic performance and well-being. The purpose of the current study is to explore and compare the variables that predict the reading literacy and life satisfaction of U.S. and South Korean students. The random forest algorithm, which is a machine learning approach, was applied to PISA 2018 data (4,677 U.S. students and 6,650 South Korean students) to explore and select the key variables among 305 variables that predict reading literacy and life satisfaction. In each random forest analysis, one for the U.S. and another for South Korea, 23 variables were derived as key variables in studentsā€™ reading literacy. In addition, 23 variables in the U.S. and 26 variables in South Korea were derived as important variables for studentsā€™ life satisfaction. The multilevel analysis revealed that various student-, teacher- or school-related key variables derived from the random forest were statistically related to either U.S. and/or South Korean studentsā€™ reading literacy and/or life satisfaction. The current study proposes to use a machine learning approach to examine international large-scale data for an international comparison. The implications of the current study and suggestions for future research are discussed
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