March 2013 arXiv papers — page 49

Alice Zhuo-Yu Chan, Luis Alberto Garcia German, Stephan Ramon Garcia, Amy L. Shoemaker

The matrix equation $XA + AX^T = 0$ was recently introduced by De Terán and Dopico to study the dimension of congruence orbits. They reduced the study of this equation to a number of special cases, several of which have not been explicitly solved. In this note we obtain an explicit, closed-form solution in the difficult Type 0-I interaction case.

David T. Limmer, David Chandler

This paper extends our earlier studies of free energy functions of density and crystalline order parameters for models of supercooled water, which allows us to examine the possibility of two distinct metastable liquid phases [J. Chem. Phys. 135, 134503 (2011) and arXiv:1107.0337v2]. Low-temperature reversible free energy surfaces of several different atomist

Anh D. Phan, Lilia M. Woods, The-Long Phan

The van der Waals interactions between two parallel graphitic nanowiggles (GNWs) are calculated using the coupled dipole method (CDM). The CDM is an efficient and accurate approach to determine such interactions explicitly by taking into account the discrete atomic structure. Our findings show that the van der Waals forces vary from attraction to repulsion a

Valerio Scarani

This text is an introduction to an operational outlook on Bell inequalities, which has been very fruitful in the past few years. It has lead to the recognition that Bell tests have their own place in applied quantum technologies, because they quantify non-classicality in a device-independent way, that is, without any need to describe the degrees of freedom u

Jeffrey C. Regier, Philip B. Stark

Consider approximating a "black box" function $f$ by an emulator $\hat{f}$ based on $n$ noiseless observations of $f$. Let $w$ be a point in the domain of $f$. How big might the error $|\hat{f}(w) - f(w)|$ be? If $f$ could be arbitrarily rough, this error could be arbitrarily large: we need some constraint on $f$ besides the data. Suppose $f$ is Lips

R. U. Gobithaasan, M. A Jamaludin

In CAGD/CAD research and education, users are involved with development of mathematical algorithms and followed by the analysis of the resultant algorithm. This process involves geometric display which can only be carried out with high end graphics display. There are many approaches practiced and one of the so-called easiest approaches is by using C/C++ prog

S. Eckel, P. Hamilton, E. Kirilov, H. W. Smith

We present results of the first experiment to probe for the electric dipole moment (EDM) of the electron using an $Ω$-doublet state in a polar molecule. If the molecule is both massive and has a large molecular-fixed frame dipole moment, then the $Ω$-doublet states have the potential to greatly increase the sensitivity of experiments searching for the EDM wh

Elias Gonzalez, Laszlo B. Kish, Robert Balog, Prasad Enjeti

We introduce a protocol with a reconfigurable filter system to create non-overlapping single loops in the smart power grid for the realization of the Kirchhoff-Law-Johnson-(like)-Noise secure key distribution system. The protocol is valid for one-dimensional radial networks (chain-like power line) which are typical of the electricity distribution network bet

Juan Carlos Hidalgo, Adam J. Christopherson, Karim A. Malik

We calculate the relativistic constraint equation which relates the curvature perturbation to the matter density contrast at second order in cosmological perturbation theory. This relativistic "second order Poisson equation" is presented in a gauge where the hydrodynamical inhomogeneities coincide with their Newtonian counterparts exactly for a perfe

Kai Kratzer, Axel Arnold, Rosalind J. Allen

Forward flux sampling (FFS) provides a convenient and efficient way to simulate rare events in equilibrium or non-equilibrium systems. FFS ratchets the system from an initial state to a final state via a series of interfaces in phase space. The efficiency of FFS depends sensitively on the positions of the interfaces. We present two alternative methods for pl

Bojana Femić

We study versions of the categories of Yetter-Drinfel'd modules over a Hopf algebra $H$ in a braided monoidal category $\C$. Contrarywise to Bespalov's approach, all our structures live in $\C$. This forces $H$ to be transparent or equivalently to lie in Müger's center $\Z_2(\C)$ of $\C$. We prove that versions of the categories of Yetter-Drinfel

Keitaro Takahashi, Masaki Mori, Kiyotomo Ichiki, Susumu Inoue

Lower bounds are derived on the amplitude B of intergalactic magnetic fields (IGMFs) in the region between Galaxy and the blazar Mrk 421, from constraints on the delayed GeV pair-echo flux that are emitted by secondary e^-e^+ produced in γγinteractions between primary TeV gamma-rays and the cosmic infrared background. The distribution of galaxies mapped by t

J. Sirker, N. P. Konstantinidis, F. Andraschko, N. Sedlmayr

We derive a necessary and sufficient condition for the thermalization of a local observable in a closed quantum system which offers an alternative explanation, independent of the eigenstate thermalization hypothesis, for the thermalization process. We also show that this approach is useful to investigate thermalization based on a finite-size scaling of numer

Zhong-Bo Kang, Xiaohui Liu, Sonny Mantry, Jian-Wei Qiu

We study single jet production in electron-nucleus collisions e^- + N_A -> J + X, using the 1-jettiness (τ_1) global event shape. It inclusively quantifies the pattern of radiation in the final state, gives enhanced sensitivity to soft radiation at wide angles from the nuclear beam and final-state jet, and facilitates the resummation of large Sudakov logarit

Duccio Pappadopulo, Andrea Thamm, Riccardo Torre

We construct and study the 5D realization of a composite Higgs model with minimal tuning. The Higgs is a (pseudo-)Goldstone boson from the spontaneous breaking of a global SO(5) symmetry to an SO(4) subgroup. The peculiarity of our construction lies in the specific choice of the SO(5) representations of the 5D fermions from which the Standard Model fields ar

Nevin Lianwen Zhang, David L. Poole

This paper presents a new approach for computing posterior probabilities in Bayesian nets, which sidesteps the triangulation problem. The current state of art is the clique tree propagation approach. When the underlying graph of a Bayesian net is triangulated, this approach arranges its cliques into a tree and computes posterior probabilities by appropriatel

Hong Xu

Valuation-based system (VBS) provides a general framework for representing knowledge and drawing inferences under uncertainty. Recent studies have shown that the semantics of VBS can represent and solve Bayesian decision problems (Shenoy, 1991a). The purpose of this paper is to propose a decision calculus for Dempster-Shafer (D-S) theory in the framework of

Yang Xiang, David L. Poole, Michael P. Beddoes

Current Bayesian net representations do not consider structure in the domain and include all variables in a homogeneous network. At any time, a human reasoner in a large domain may direct his attention to only one of a number of natural subdomains, i.e., there is ?localization' of queries and evidence. In such a case, propagating evidence through a homog

Michael S. K. M. Wong, L. S. Wang, Y. Y. Yao

In this paper, a unified framework for representing uncertain information based on the notion of an interval structure is proposed. It is shown that the lower and upper approximations of the rough-set model, the lower and upper bounds of incidence calculus, and the belief and plausibility functions all obey the axioms of an interval structure. An interval st

Carl G. Wagner

Jeffrey's rule has been generalized by Wagner to the case in which new evidence bounds the possible revisions of a prior probability below by a Dempsterian lower probability. Classical probability kinematics arises within this generalization as the special case in which the evidentiary focal elements of the bounding lower probability are pairwise disjoin

Tom S. Verma, Judea Pearl

In a previous paper [Pearl and Verma, 1991] we presented an algorithm for extracting causal influences from independence information, where a causal influence was defined as the existence of a directed arc in all minimal causal models consistent with the data. In this paper we address the question of deciding whether there exists a causal model that explains

Helmut Thone, Ulrich Guntzer, Werner Kiessling

The DUCK-calculus presented here is a recent approach to cope with probabilistic uncertainty in a sound and efficient way. Uncertain rules with bounds for probabilities and explicit conditional independences can be maintained incrementally. The basic inference mechanism relies on local bounds propagation, implementable by deductive databases with a bottom-up

Chin-Wang Tao, Wiley E. Thompson

This paper discusses a target tracking problem in which no dynamic mathematical model is explicitly assumed. A nonlinear filter based on the fuzzy If-then rules is developed. A comparison with a Kalman filter is made, and empirical results show that the performance of the fuzzy filter is better. Intensive simulations suggest that theoretical justification of

Luis Enrique Sucar, Duncan F. Gillies

Bayesian networks have been used extensively in diagnostic tasks such as medicine, where they represent the dependency relations between a set of symptoms and a set of diseases. A criticism of this type of knowledge representation is that it is restricted to this kind of task, and that it cannot cope with the knowledge required in other artificial intelligen

Paul Snow

The general use of subjective probabilities to model belief has been justified using many axiomatic schemes. For example, ?consistent betting behavior' arguments are well-known. To those not already convinced of the unique fitness and generality of probability models, such justifications are often unconvincing. The present paper explores another rational

Philippe Smets

Within the transferable belief model, positive basic belief masses can be allocated to the empty set, leading to unnormalized belief functions. The nature of these unnormalized beliefs is analyzed.

Prakash P. Shenoy

This paper introduces the notions of independence and conditional independence in valuation-based systems (VBS). VBS is an axiomatic framework capable of representing many different uncertainty calculi. We define independence and conditional independence in terms of factorization of the joint valuation. The definitions of independence and conditional indepen

Ross D. Shachter, Mark Alan Peot

The analysis of decision making under uncertainty is closely related to the analysis of probabilistic inference. Indeed, much of the research into efficient methods for probabilistic inference in expert systems has been motivated by the fundamental normative arguments of decision theory. In this paper we show how the developments underlying those efficient m

Thomas Schiex

Many AI synthesis problems such as planning or scheduling may be modelized as constraint satisfaction problems (CSP). A CSP is typically defined as the problem of finding any consistent labeling for a fixed set of variables satisfying all given constraints between these variables. However, for many real tasks such as job-shop scheduling, time-table schedulin

Peter J. Regan, Samuel Holtzman

This paper describes the architecture of R&D Analyst, a commercial intelligent decision system for evaluating corporate research and development projects and portfolios. In analyzing projects, R&D Analyst interactively guides a user in constructing an influence diagram model for an individual research project. The system's interactive approach can be cle

Yuping Qiu, Louis Anthony Cox,, Lawrence Davis

An expert classification system having statistical information about the prior probabilities of the different classes should be able to use this knowledge to reduce the amount of additional information that it must collect, e.g., through questions, in order to make a correct classification. This paper examines how best to use such prior information and addit

Luigi Portinale

Although the notion of diagnostic problem has been extensively investigated in the context of static systems, in most practical applications the behavior of the modeled system is significantly variable during time. The goal of the paper is to propose a novel approach to the modeling of uncertainty about temporal evolutions of time-varying systems and a chara

Thomas S. Paterson, Michael R. Fehling

This paper describes some results of research on associate systems: knowledge-based systems that flexibly and adaptively support their human users in carrying out complex, time-dependent problem-solving tasks under uncertainty. Based on principles derived from decision theory and decision analysis, a problem-solving approach is presented which can overcome m

Gerhard Paaß

Probabilistic reasoning systems combine different probabilistic rules and probabilistic facts to arrive at the desired probability values of consequences. In this paper we describe the MESA-algorithm (Maximum Entropy by Simulated Annealing) that derives a joint distribution of variables or propositions. It takes into account the reliability of probability va

Kristian G. Olesen, Steffen L. Lauritzen, Finn Verner Jensen

The paper describes aHUGIN, a tool for creating adaptive systems. aHUGIN is an extension of the HUGIN shell, and is based on the methods reported by Spiegelhalter and Lauritzen (1990a). The adaptive systems resulting from aHUGIN are able to adjust the C011ditional probabilities in the model. A short analysis of the adaptation task is given and the features o

Raymond T. Ng, V. S. Subrahmanian

We address the problem of supporting empirical probabilities in monadic logic databases. Though the semantics of multivalued logic programs has been studied extensively, the treatment of probabilities as results of statistical findings has not been studied in logic programming/deductive databases. We develop a model-theoretic characterization of logic databa

Ann Nicholson, J. M. Brady

The trajectory of a robot is monitored in a restricted dynamic environment using light beam sensor data. We have a Dynamic Belief Network (DBN), based on a discrete model of the domain, which provides discrete monitoring analogous to conventional quantitative filter techniques. Sensor observations are added to the basic DBN in the form of specific evidence.

Serafin Moral

In Moral, Campos (1991) and Cano, Moral, Verdegay-Lopez (1991) a new method of conditioning convex sets of probabilities has been proposed. The result of it is a convex set of non-necessarily normalized probability distributions. The normalizing factor of each probability distribution is interpreted as the possibility assigned to it by the conditioning infor

Izhar Matzkevich, Bruce Abramson

Bayes nets are relatively recent innovations. As a result, most of their theoretical development has focused on the simplest class of single-author models. The introduction of more sophisticated multiple-author settings raises a variety of interesting questions. One such question involves the nature of compromise and consensus. Posterior compromises let each

Weiru Liu, John G. Hughes, Michael F. McTear

The Dempster-Shafer theory of evidence has been used intensively to deal with uncertainty in knowledge-based systems. However the representation of uncertain relationships between evidence and hypothesis groups (heuristic knowledge) is still a major research problem. This paper presents an approach to representing such heuristic knowledge by evidential mappi

Dekang Lin

Bayesian networks are directed acyclic graphs representing independence relationships among a set of random variables. A random variable can be regarded as a set of exhaustive and mutually exclusive propositions. We argue that there are several drawbacks resulting from the propositional nature and acyclic structure of Bayesian networks. To remedy these short

Tze-Yun Leong

Automated decision making is often complicated by the complexity of the knowledge involved. Much of this complexity arises from the context sensitive variations of the underlying phenomena. We propose a framework for representing descriptive, context-sensitive knowledge. Our approach attempts to integrate categorical and uncertain knowledge in a network form

Kathryn Blackmond Laskey

The ideal Bayesian agent reasons from a global probability model, but real agents are restricted to simplified models which they know to be adequate only in restricted circumstances. Very little formal theory has been developed to help fallibly rational agents manage the process of constructing and revising small world models. The goal of this paper is to pr

Kathryn Blackmond Laskey

This paper presents a Bayesian framework for assessing the adequacy of a model without the necessity of explicitly enumerating a specific alternate model. A test statistic is developed for tracking the performance of the model across repeated problem instances. Asymptotic methods are used to derive an approximate distribution for the test statistic. When the

Henry E. Kyburg, Michael Pittarelli

We discuss problems for convex Bayesian decision making and uncertainty representation. These include the inability to accommodate various natural and useful constraints and the possibility of an analog of the classical Dutch Book being made against an agent behaving in accordance with convex Bayesian prescriptions. A more general set-based Bayesianism may b

Henry E. Kyburg

A number of writers(Joseph Halpern and Fahiem Bacchus among them) have offered semantics for formal languages in which inferences concerning probabilities can be made. Our concern is different. This paper provides a formalization of nonmonotonic inferences in which the conclusion is supported only to a certain degree. Such inferences are clearly 'invalid

George J. Klir, Behzad Parviz

A new entropy-like measure as well as a new measure of total uncertainty pertaining to the Dempster-Shafer theory are introduced. It is argued that these measures are better justified than any of the previously proposed candidates.

Frank Klawonn, Philippe Smets

The fundamental updating process in the transferable belief model is related to the concept of specialization and can be described by a specialization matrix. The degree of belief in the truth of a proposition is a degree of justified support. The Principle of Minimal Commitment implies that one should never give more support to the truth of a proposition th

Uffe Kjærulff

A computational scheme for reasoning about dynamic systems using (causal) probabilistic networks is presented. The scheme is based on the framework of Lauritzen and Spiegelhalter (1988), and may be viewed as a generalization of the inference methods of classical time-series analysis in the sense that it allows description of non-linear, multivariate dynamic

Moises Goldszmidt, Judea Pearl

We recently described a formalism for reasoning with if-then rules that re expressed with different levels of firmness [18]. The formalism interprets these rules as extreme conditional probability statements, specifying orders of magnitude of disbelief, which impose constraints over possible rankings of worlds. It was shown that, once we compute a priority f

Robert P. Goldman, John S. Breese

To date, most probabilistic reasoning systems have relied on a fixed belief network constructed at design time. The network is used by an application program as a representation of (in)dependencies in the domain. Probabilistic inference algorithms operate over the network to answer queries. Recognizing the inflexibility of fixed models has led researchers to

Angelo Gilio, Fulvio Spezzaferri

In the probabilistic approach to uncertainty management the input knowledge is usually represented by means of some probability distributions. In this paper we assume that the input knowledge is given by two discrete conditional probability distributions, represented by two stochastic matrices P and Q. The consistency of the knowledge base is analyzed. Coher

Dan Geiger

This article offers a modification of Chow and Liu's learning algorithm in the context of handwritten digit recognition. The modified algorithm directs the user to group digits into several classes consisting of digits that are hard to distinguish and then constructing an optimal conditional tree representation for each class of digits instead of for eac

Francesco Fulvio Monai, Thomas Chehire

Data fusion allows the elaboration and the evaluation of a situation synthesized from low level informations provided by different kinds of sensors. The fusion of the collected data will result in fewer and higher level informations more easily assessed by a human operator and that will assist him effectively in his decision process. In this paper we present

Didier Dubois, Henri Prade, Lluis Godo, Ramon Lopez de Mantaras

This paper investigates the possibility of performing automated reasoning in probabilistic logic when probabilities are expressed by means of linguistic quantifiers. Each linguistic term is expressed as a prescribed interval of proportions. Then instead of propagating numbers, qualitative terms are propagated in accordance with the numerical interpretation o

Adnan Darwiche

This paper introduces the notion of objection-based causal networks which resemble probabilistic causal networks except that they are quantified using objections. An objection is a logical sentence and denotes a condition under which a, causal dependency does not exist. Objection-based causal networks enjoy almost all the properties that make probabilistic c

Bruce D'Ambrosio, Tony Fountain, Zhaoyu Li

We report on an experimental investigation into opportunities for parallelism in beliefnet inference. Specifically, we report on a study performed of the available parallelism, on hypercube style machines, of a set of randomly generated belief nets, using factoring (SPI) style inference algorithms. Our results indicate that substantial speedup is available,

Norman C. Dalkey

The product expansion of conditional probabilities for belief nets is not maximum entropy. This appears to deny a desirable kind of assurance for the model. However, a kind of guarantee that is almost as strong as maximum entropy can be derived. Surprisingly, a variant model also exhibits the guarantee, and for many cases obtains a higher performance score t

Paul Dagum, Eric J. Horvitz

We describe how we selectively reformulate portions of a belief network that pose difficulties for solution with a stochastic-simulation algorithm. With employ the selective conditioning approach to target specific nodes in a belief network for decomposition, based on the contribution the nodes make to the tractability of stochastic simulation. We review pre

Paul Dagum, Adam Galper, Eric J. Horvitz

We have developed a probabilistic forecasting methodology through a synthesis of belief network models and classical time-series analysis. We present the dynamic network model (DNM) and describe methods for constructing, refining, and performing inference with this representation of temporal probabilistic knowledge. The DNM representation extends static beli

Philippe Chatalic, Christine Froidevaux

Experts do not always feel very, comfortable when they have to give precise numerical estimations of certainty degrees. In this paper we present a qualitative approach which allows for attaching partially ordered symbolic grades to logical formulas. Uncertain information is expressed by means of parameterized modal operators. We propose a semantics for this

Brian Y. Chan, Ross D. Shachter

Influence diagram is a graphical representation of belief networks with uncertainty. This article studies the structural properties of a probabilistic model in an influence diagram. In particular, structural controllability theorems and structural observability theorems are developed and algorithms are formulated. Controllability and observability are fundam

Craig Boutilier

Possibilistic logic has been proposed as a numerical formalism for reasoning with uncertainty. There has been interest in developing qualitative accounts of possibility, as well as an explanation of the relationship between possibility and modal logics. We present two modal logics that can be used to represent and reason with qualitative statements of possib

Remco R. Bouckaert

An algorithm for generating the structure of a directed acyclic graph from data using the notion of causal input lists is presented. The algorithm manipulates the ordering of the variables with operations which very much resemble arc reversal. Operations are only applied if the DAG after the operation represents at least the independencies represented by the

Zhi An, David A. Bell, John G. Hughes

In this paper we describe a novel method for evidential reasoning [1]. It involves modelling the process of evidential reasoning in three steps, namely, evidence structure construction, evidence accumulation, and decision making. The proposed method, called RES, is novel in that evidence strength is associated with an evidential support relationship (an argu

Xianfu Chen, Honggang Zhang, Tao Chen, Mika Lasanen

One of the efficient solutions of improving coverage and increasing capacity in cellular networks is the deployment of femtocells. As the cellular networks are becoming more complex, energy consumption of whole network infrastructure is becoming important in terms of both operational costs and environmental impacts. This paper investigates energy efficiency

Fotis K. Diakonos, Alexandros K. Karlis, Peter Schmelcher

Cross-correlations are usually considered to emerge through interaction between particles. Here we present a mechanism capable to generate power-law cross-correlations between non-interacting particles exposed to an external potential. This phenomenon can occur as an ensemble property when the external potential induces intermittent dynamics, providing lamin

Joshua Rosen, Neoklis Polyzotis, Vinayak Borkar, Yingyi Bu

Large datasets ("Big Data") are becoming ubiquitous because the potential value in deriving insights from data, across a wide range of business and scientific applications, is increasingly recognized. In particular, machine learning - one of the foundational disciplines for data analysis, summarization and inference - on Big Data has become routine a

Sergiu I. Vacaru

The aims of this work are 1) to sketch a proof that there are such parameterizations of the local frame and canonical connection structures when the gravitational field equations in f(R,T)-modified gravity, MG, can be integrated in generic off-diagonal forms with metrics depending on all spacetime coordinates and 2) to provide some examples of exact solution

Konstantin Belov

While the fluorescence and the ground counter techniques for the detection of ultra-high energy cosmic rays (UHECR) were being developed for decades, the interest in the radio detection diminished after the initial experiments in the 1960s. As a result, the fluorescence and the surface array techniques are more mature today, providing more reliable measureme

Ryen C. Lapham, Beverly J. Smith, Curtis Struck

We construct UV/optical/IR spectral energy distributions for 29 star forming regions in the interacting galaxy Arp 107, using GALEX UV, Sloan Digitized Sky Survey optical, and Spitzer infrared images. In an earlier study utilizing only the Spitzer data, we found a sequence in the mid-infrared colors of star-forming knots along the strong tidal arm in this sy

Andrei K. Lerner

We consider the one-dimensional John-Nirenberg inequality: $$ |\{x\in I_0:|f(x)-f_{I_0}|>\a\}|\le C_1|I_0|\exp\Big(-\frac{C_2}{\|f\|_{*}}\a\Big). $$ A. Korenovskii found that the sharp $C_2$ here is $C_2=2/e$. It is shown in this paper that if $C_2=2/e$, then the best possible $C_1$ is $C_1= \frac{1}{2}e^{4/e}$.

Hans Christianson, Jason Metcalfe

We consider a family of spherically symmetric, asymptotically Euclidean manifolds with two trapped sets, one which is unstable and one which is semi-stable. The phase space structure is that of an inflection transmission set. We prove a sharp local smoothing estimate for the linear Schrödinger equation with a loss which depends on how flat the manifold is ne

Wade DeGottardi, Manisha Thakurathi, Smitha Vishveshwara, Diptiman Sen

We present a comprehensive study of two of the most experimentally relevant extensions of Kitaev's spinless model of a 1D p-wave superconductor: those involving (i) longer range hopping and superconductivity and (ii) inhomogeneous potentials. We commence with a pedagogical review of the spinless model and, as a means of characterizing topological phases

Florian Beutler

This thesis presents the analysis of the clustering of galaxies in the 6dF Galaxy Survey (6dFGS). At large separation scales the baryon acoustic oscillation (BAO) signal is detected which allows to make an absolute distance measurement at $z_{\rm eff} = 0.106$. Such a measurement can be used to constrain the Hubble constant, $H_0 = 67.0\pm3.2\;$km s$^{-1}\;$

C. Lindsey, A. -C. Donea, J. C. Martinez Oliveros, H. S. Hudson

The physics of transient seismic emission in flares remains largely mysterious. Its discoverers proposed that these "sunquakes" are the signature of a shock driven by "thick-target heating" of the flaring chromosphere. H-α observations show evidence for such a shock. However, simulations of shocks driven by impulsive chromospheric heating sho

Panayotis G. Kevrekidis, Dmitry E. Pelinovsky, Dmitry Y. Tyugin

In the present work we examine both the linear and nonlinear properties of two related PT-symmetric systems of the discrete nonlinear Schrodinger (dNLS) type. First, we examine the parameter range for which the finite PT-dNLS chains have real eigenvalues and PT-symmetric linear eigenstates. We develop a systematic way of analyzing the nonlinear stationary st

Y. X. Zhao, Z. D. Wang

The subtle relation of the marginality of Dirac model and the emergence of the Hopf term through a Yukawa-type interaction is revealed in this work. We show that the improvement of the marginality of Dirac mode through an infinitesimal non-relativistic term, which is irrelevant for renormalization group, is necessary to emerge the Hopf term. It is found that

Rodrigo Bezerra de Matos, Jose Fabio B. Montenegro

We prove that if $M$ is a complete hypersurface in $\mathbb{R}^{n+1}$ which is graph of a real radial function, then the spectrum of the Laplace operator on M is the interval $[0,\infty)$.

S. Bilir, T. Ak, S. Ak, T. Yontan

We present an M_V absolute magnitude calibration including the B-V colour and [Fe/H] metallicity for the red clump stars in the globular and open clusters with a wide range of metallicities: M_V = 0.627(0.104)(B-V)o+0.046(0.043)[Fe/H]+0.262(0.111). The calibration equation is valid in the ranges 0.42<(B-V)o<1.20 mag, -1.55<[Fe/H]<+0.40 dex and 0.43<M_V<1.03

Umberto D&#39;Alesio

The distribution of transversely polarized quarks inside a transversely polarized nucleon, known as transversity, encodes a basic piece of information on the nucleon structure, sharing the same status with the more familiar unpolarized and helicity distributions. I will review its properties and discuss different ways to access it, with highlights and limita

Solomon Endlich, Alberto Nicolis

We study the dynamics of a nearly incompressible fluid via (classical) effective field theory. In the kinematical regime corresponding to near incompressibility (small fluid velocities and accelerations), compressional modes are, by definition, difficult to excite, and can be dealt with perturbatively. We systematically outline the corresponding perturbative

Michael Okun, Pierre Yger, Kenneth D. Harris

A response to a comment of Fiser et al.

Thomas H. Reiprich, Kaustuv Basu, Stefano Ettori, Holger Israel

Until recently, only about 10% of the total intracluster gas volume had been studied with high accuracy, leaving a vast region essentially unexplored. This is now changing and a wide area of hot gas physics and chemistry awaits discovery in galaxy cluster outskirts. Also, robust large-scale total mass profiles and maps are within reach. First observational a

Matthias Bartelmann, Marceau Limousin, Massimo Meneghetti, Robert Schmidt

The core structure of galaxy clusters is fundamentally important. Even though self-gravitating systems have no stable equilibrium state due to their negative heat capacity, numerical simulations find density profiles which are universal in the sense that they are fairly flat within a scale radius and gradually steepen farther outward, asymptotically approach

J. F. Nossa, M. Fhokrul Islam, C. M. Canali, M. R. Pederson

Using first-principles methods we study theoretically the properties of an individual $\{Fe_4\}$ single-molecule magnet (SMM) attached to metallic leads in a single-electron transistor geometry. We show that the conductive leads do not affect the spin ordering and magnetic anisotropy of the neutral SMM. On the other hand, the leads have a strong effect on th

Quinn M. Konopacky, Travis S. Barman, Bruce A. Macintosh, Christian Marois

Determining the atmospheric structure and chemical composition of an exoplanet remains a formidable goal. Fortunately, advancements in the study of exoplanets and their atmospheres have come in the form of direct imaging - spatially resolving the planet from its parent star - which enables high-resolution spectroscopy of self-luminous planets in Jovian-like

Sergei Manzhos

Effects of nuclear dynamics on the energetics of polythiophene relevant for the performance of organic solar cells are studied for the first time. Nuclear motions change the expectation values of frontier orbital energies and the band gap by about 0.1 eV vs. values at the equilibrium geometry, which is expected to have a significant effect on light absorptio

Amaury Lambert, Chunhua Ma

We consider a dynamic metapopulation involving one large population of size N surrounded by colonies of size \varepsilon_NN, usually called peripheral isolates in ecology, where N\to\infty and \varepsilon_N\to 0 in such a way that \varepsilon_NN\to\infty. The main population periodically sends propagules to found new colonies (emigration), and each colony ev

D0 Collaboration

We present a search for the standard model (SM) Higgs boson produced in association with a Z boson in 9.7 fb-1 of ppbar collisions collected with the D0 detector at the Fermilab Tevatron Collider at sqrt{s} = 1.96 TeV. Selected events contain one reconstructed Z -> e+e- or Z -> mu+mu- candidate and at least two jets, including at least one jet likely to cont

Henk Hoekstra, Matthias Bartelmann, Haakon Dahle, Holger Israel

Despite consistent progress in numerical simulations, the observable properties of galaxy clusters are difficult to predict ab initio. It is therefore important to compare both theoretical and observational results to a direct measure of the cluster mass. This can be done by measuring the gravitational lensing effects caused by the bending of light by the cl

Adam D. Hincks, Amir Hajian, Graeme E. Addison

We cross-correlate the 100 um Improved Reprocessing of the IRAS Survey (IRIS) map and galaxy clusters at 0.1 < z < 0.3 in the maxBCG catalogue taken from the Sloan Digital Sky Survey, measuring an angular cross-power spectrum over multipole moments 150 < l < 3000 at a total significance of over 40 sigma. The cross-spectrum, which arises from the spatial corr

Andrey Beresnyak

Stochasticity of magnetic field lines is important for particle transport properties. Magnetic field lines separate faster than diffusively in turbulent plasma, which is called superdiffusion. We discovered that this superdiffusion is pronouncedly asymmetric, so that the separation of field lines along the magnetic field direction is different from the separ

Kirill Sokolovsky, Stanislav Korotkiy, Alexandr Lebedev

Currently, it may take days for a bright nova outburst to be detected. With the few exceptions, little is known about novae behaviour prior to maximum light. A theoretically-predicted population of ultra-fast novae with t2<1d is evading observational discovery because it is not possible to routinely organize fast follow-up observations of nova candidates. Wi

F. Massaro, R. D&#39;Abrusco, A. Paggi, N. Masetti

One of the main scientific objectives of the recent Fermi mission is investigating the origin of the unidentified gamma-ray sources (UGSs). Despite the large improvements of Fermi in the gamma-ray source localization with respect to the past gamma-ray missions, about 1/3 of the gamma-ray objects detected do not have yet an assigned counterpart a low energies

J. N. Swaminathan, P. Kumar, M. Vinoth

The SSPA has wide application in Communication system, but its high output power varies due to its non linear gain. Pre-distortion method plays major role in power amplifier linearization. Polynomial is one of the methods used. The error estimation in Polynomial method is carried out by LMS Filter. Our main work is to analysis the error estimation performanc

J. Blåbäck, A. Borghese, S. S. Haque

In this paper we search for accelerating power-law solutions and ekpyrotic solutions within minimal and maximal four dimensional supergravity theories. We focus on the STU model for N=1 and on the new CSO(p,q,r) theories, which were recently obtained exploiting electromagnetic duality, for N=8. In the minimal case we find some new ekpyrotic solutions, while

Vladimir Maz&#39;ya, Robert McOwen

For a second-order elliptic equation of nondivergence form in the plane, we investigate conditions on the coefficients which imply that all strong solutions have first-order derivatives that are Lipschitz continuous or differentiable at a given point. We assume the coefficients have modulus of continuity satisfying the square-Dini condition, and obtain addit

Li Xiao, Xiang-Gen Xia, Wenjie Wang

It is well-known that the traditional Chinese remainder theorem (CRT) is not robust in the sense that a small error in a remainder may cause a large error in the reconstruction solution. A robust CRT was recently proposed for a special case when the greatest common divisor (gcd) of all the moduli is more than 1 and the remaining integers factorized by the gc

S. A. Sato, K. Yabana, Y. Shinohara, T. Otobe

We calculate the dielectric response of crystalline silicon following irradiation by a high-intensity laser pulse, modeling the dynamics by time-dependent density functional theory (TDDFT). The pump-probe measurements are numerically simulated by solving the time-dependent Kohn-Sham equation with the pump and probe fields included as external fields. As expe