August 2014 arXiv papers — page 54

Grégoire Charlot

This article deals with 2d almost Riemannian structures, which are generalized Riemannian structures on manifolds of dimension 2. Such sub-Riemannian structures can be locally defined by a pair of vector fields (X,Y), playing the role of orthonormal frame, that may become colinear on some subset. We denote D = span(X,Y). After a short introduction, I first g

François Delbot, Christian Laforest, Stephane Rovedakis

In many wireless networks, there is no fixed physical backbone nor centralized network management. The nodes of such a network have to self-organize in order to maintain a virtual backbone used to route messages. Moreover, any node of the network can be a priori at the origin of a malicious attack. Thus, in one hand the backbone must be fault-tolerant and in

Sergey Bobkov, Nathael Gozlan, Cyril Roberto, Paul-Marie Samson

The de cit in the logarithmic Sobolev inequality for the Gaussian measure is considered and estimated by means of transport and information-theoretic distances.

Ivan Dotu, Juan Antonio Garcia-Martin, Betty L. Slinger, Vinodh Mechery

Nanotechnology and synthetic biology currently constitute one of the most innovative, interdisciplinary fields of research, poised to radically transform society in the 21st century. This paper concerns the synthetic design of ribonucleic acid molecules, using our recent algorithm, RNAiFold, which can determine all RNA sequences whose minimum free energy sec

Maria Isabel Cortez, Fabien Durand, Samuel Petite

We give conditions on the subgroups of the circle to be realized as the subgroups of eigenvalues of minimal Cantor systems belonging to a determined strong orbit equivalence class. Actually, the additive group of continuous eigenvalues E(X,T) of the minimal Cantor system (X,T) is a subgroup of the intersection I(X,T) of all the images of the dimension group

Armand Lachand

Let $F(X_1,X_2)\in\mathbb{Z}[X_1,X_2] $ be an irreducible binary form of degree $3$ and $h$ an arithmetic function. We give some estimates for the average order $\sum_{\substack{|n_1|\leq x,|n_2|\leq x}}h(F(n_1,n_2))$ when $h$ satisfy certain conditions. As an application, we provide some asymptotic formula for the number of $y$-friable values of $F(n_1,n_2)

Aleksandra Drozd, Bohdan Grzadkowski, John F. Gunion, Yun Jiang

We extend the two-Higgs doublet models of Type I and Type II by adding a real gauge-singlet scalar S dark matter candidate (2HDMS models). We impose theoretical constraints deriving from perturbativity, stability, unitarity and correct electroweak symmetry breaking and require that the lightest CP-even Higgs, h, fit the LHC data for the $\sim 125.5$ GeV stat

Mercel Vubangsi, Martin Tchoffo, Lukong Cornelius Fai

We show that for a given setting of the Von Roos ambiguity parameters, it is not required that the Morrow and Brownstein condition be satisfied to achieve physically acceptable transport properties at abrupt heterojunctions. We have derived two such settings and corresponding envelope function matching conditions.

Martin Monperrus

At ICSE'2013, there was the first session ever dedicated to automatic program repair. In this session, Kim et al. presented PAR, a novel template-based approach for fixing Java bugs. We strongly disagree with key points of this paper. Our critical review has two goals. First, we aim at explaining why we disagree with Kim and colleagues and why the reason

Joe Alexandersen, Niels Aage, Casper Schousboe Andreasen, Ole Sigmund

This paper demonstrates the application of the density-based topology optimisation approach for the design of heat sinks and micropumps based on natural convection effects. The problems are modelled under the assumptions of steady-state laminar flow using the incompressible Navier-Stokes equations coupled to the convection-diffusion equation through the Bous

Bergfinnur Durhuus, Thordur Jonsson

We prove that the number of combinatorially distinct causal 3-dimensional triangulations homeomorphic to the 3-dimensional sphere is bounded by an exponential function of the number of tetrahedra. It is also proven that the number of combinatorially distinct causal 4-dimensional triangulations homeomorphic to the 4-sphere is bounded by an exponential functio

T. Morel, N. Castro, L. Fossati, S. Hubrig

The B fields in OB stars (BOB) survey is an ESO large programme collecting spectropolarimetric observations for a large number of early-type stars in order to study the occurrence rate, properties, and ultimately the origin of magnetic fields in massive stars. As of July 2014, a total of 98 objects were observed over 20 nights with FORS2 and HARPSpol. Our pr

Xingang Chen, Razieh Emami, Hassan Firouzjahi, Yi Wang

We examine the impact of different anisotropic relics on inflation, in particular the predictions on the density perturbations. These relics can be the source of the large scale anomalies in the cosmic microwave background. There are two different types of background relics, one from the matter sector and the other purely from the metric. Although the angula

Salomon Ofman

To account for the first proof of existence of an irrational magnitude, historians of science as well as commentators of Aristotle refer to the texts on the incommensurability of the diagonal in Prior Analytics, since they are the most ancient on the subject. The usual proofs suggested by the historians of science derive from a proposition found at the end o

Luc Trouche, Paul Drijvers

The integration of digital tools in mathematics education is considered both promising and problematic. To deal with this issue, notions of webbing and instrumental orchestration are developed. However, the two seemed to be disconnected, and having different cultural and theoretical roots. In this article, we investigate the distinct and joint journeys of th

Haizhong Li, Changwei Xiong

We study the stability of capillary hypersurfaces in a unit Euclidean ball. It is proved that if the mass center of the generalized body enclosed by the immersed capillary hypersurface and the wetted part of the sphere is located at the origin, then the hypersurface is unstable. An immediate result is that all known examples except the totally geodesic ones

T. Reichenbach, A. J. Hudspeth

Most sounds of interest consist of complex, time-dependent admixtures of tones of diverse frequencies and variable amplitudes. To detect and process these signals, the ear employs a highly nonlinear, adaptive, real-time spectral analyzer: the cochlea. Sound excites vibration of the eardrum and the three miniscule bones of the middle ear, the last of which ac

Yang-Hui He, John McKay

With a jocund air, we present an observation on the first 24 coefficients of the modular invariant and of the modular discriminant. The observation is purely for the sake of entertainment and could be of some diversion to a mathematical audience.

Tomasz Gogacz, Jerzy Marcinkowski

Bounded Derivation Depth property (BDD) and Finite Controllability (FC) are two properties of sets of datalog rules and tuple generating dependencies (known as Datalog +/- programs), which recently attracted some attention. We conjecture that the first of these properties implies the second, and support this conjecture by some evidence proving, among other r

Lars Flöer, Benjamin Winkel, Jürgen Kerp

Context. Source extraction for large-scale HI surveys currently involves large amounts of manual labor. For data volumes expected from future HI surveys with upcoming facilities, this approach is not feasible any longer. Aims. We describe the implementation of a fully automated source finding, parametrization, and classification pipeline for the Effelsberg-B

Arsany Guirguis, Raymond Guirguis, Moustafa Youssef

Network coding has proved its efficiency in increasing the network performance for traditional ad-hoc networks. In this paper, we investigate using network coding for enhancing the throughput of multi-hop cognitive radio networks. We formulate the network coding throughput maximization problem as a graph theory problem, where different constraints and primar

Roger Casals, Francisco Presas

In this article we address the existence of positive loops of contactomorphisms in overtwisted contact 3-folds. We present a construction of such positive loops in the contact fibered connected sum of certain contact 3-folds along transverse knots. In particular, we obtain positive loops of contactomorphisms in overtwisted contact structures.

Per Hyldgaard, Kristian Berland, Elsebeth Schröder

The nonlocal correlation energy in the van der Waals density functional (vdW-DF) method [Phys. Rev. Lett. 92, 246401 (2004); Phys. Rev. B 76, 125112 (2007); Phys. Rev. B 89, 035412 (2014)] can be interpreted in terms of a coupling of zero-point energies of characteristic modes of semilocal exchange-correlation (xc) holes. These xc holes reflect the internal

S. Bhagat, S. Gan Chaudhuri, K. Mukhopadhyaya

The traditional distributed model of autonomous, homogeneous, mobile point robots usually assumes that the robots do not create any visual obstruction for the other robots, i.e., the robots are see through. In this paper, we consider a slightly more realistic model, by incorporating the notion of obstructed visibility (i.e., robots are not see through) for o

S. M. Wang, Q. Q. Cheng, Y. X. Gong, P. Xu

It has been proved that surface plasmon polariton (SPP) can well conserve and transmit the quantum nature of entangled photons. Therefore, further utilization and manipulation of such quantum nature of SPP in a plasmonic chip will be the next task for scientists in this field. In quantum logic circuits, the controlled-NOT (CNOT) gate is the key building bloc

Aristide Tossou, Christos Dimitrakakis

We consider the problem of learning by demonstration from agents acting in unknown stochastic Markov environments or games. Our aim is to estimate agent preferences in order to construct improved policies for the same task that the agents are trying to solve. To do so, we extend previous probabilistic approaches for inverse reinforcement learning in known MD

Vikas Sindhwani, Ha Quang Minh, Aurelie Lozano

We propose a general matrix-valued multiple kernel learning framework for high-dimensional nonlinear multivariate regression problems. This framework allows a broad class of mixed norm regularizers, including those that induce sparsity, to be imposed on a dictionary of vector-valued Reproducing Kernel Hilbert Spaces. We develop a highly scalable and eigendec

Stephane Ross, Paul Mineiro, John Langford

We introduce online learning algorithms which are independent of feature scales, proving regret bounds dependent on the ratio of scales existent in the data rather than the absolute scale. This has several useful effects: there is no need to pre-normalize data, the test-time and test-space complexity are reduced, and the algorithms are more robust.

Krikamol Muandet, Bernhard Schoelkopf

We propose one-class support measure machines (OCSMMs) for group anomaly detection which aims at recognizing anomalous aggregate behaviors of data points. The OCSMMs generalize well-known one-class support vector machines (OCSVMs) to a space of probability measures. By formulating the problem as quantile estimation on distributions, we can establish an inter

Joris Mooij, Dominik Janzing, Bernhard Schoelkopf

We show how, and under which conditions, the equilibrium states of a first-order Ordinary Differential Equation (ODE) system can be described with a deterministic Structural Causal Model (SCM). Our exposition sheds more light on the concept of causality as expressed within the framework of Structural Causal Models, especially for cyclic models.

Rishabh Iyer, Jeff A. Bilmes

We extend the recently introduced theory of Lovasz-Bregman (LB) divergences (Iyer & Bilmes 2012) in several ways. We show that they represent a distortion between a "score" and an "ordering", thus providing a new view of rank aggregation and order based clustering with interesting connections to web ranking. We show how the LB divergences hav

Tomoharu Iwata, David Duvenaud, Zoubin Ghahramani

A mixture of Gaussians fit to a single curved or heavy-tailed cluster will report that the data contains many clusters. To produce more appropriate clusterings, we introduce a model which warps a latent mixture of Gaussians to produce nonparametric cluster shapes. The possibly low-dimensional latent mixture model allows us to summarize the properties of the

Jie Chen, Nannan Cao, Kian Hsiang Low, Ruofei Ouyang

Gaussian processes (GP) are Bayesian non-parametric models that are widely used for probabilistic regression. Unfortunately, it cannot scale well with large data nor perform real-time predictions due to its cubic time cost in the data size. This paper presents two parallel GP regression methods that exploit low-rank covariance matrix approximations for distr

Somphong Jitman

A vector-circulant matrix is a natural generalization of the classical circulant matrix and has applications in constructing additive codes. This article formulates the concept of a vector-circulant matrix over finite fields and gives an algebraic characterization for this kind of matrix. Finally, a construction of additive codes with vector-circulant based

Krishnendu Chatterjee, Martin Chmelik

We consider partially observable Markov decision processes (POMDPs) with limit-average payoff, where a reward value in the interval [0,1] is associated to every transition, and the payoff of an infinite path is the long-run average of the rewards. We consider two types of path constraints: (i) quantitative constraint defines the set of paths where the payoff

Giorgos Borboudakis, Ioannis Tsamardinos

A significant theoretical advantage of search-and-score methods for learning Bayesian Networks is that they can accept informative prior beliefs for each possible network, thus complementing the data. In this paper, a method is presented for assigning priors based on beliefs on the presence or absence of certain paths in the true network. Such beliefs corres

Sheeraz Ahmad, Angela Yu

Sensory inference under conditions of uncertainty is a major problem in both machine learning and computational neuroscience. An important but poorly understood aspect of sensory processing is the role of active sensing. Here, we present a Bayes-optimal inference and control framework for active sensing, C-DAC (Context-Dependent Active Controller). Unlike pr

Amy Zhang, Nadia Fawaz, Stratis Ioannidis, Andrea Montanari

It is often the case that, within an online recommender system, multiple users share a common account. Can such shared accounts be identified solely on the basis of the userprovided ratings? Once a shared account is identified, can the different users sharing it be identified as well? Whenever such user identification is feasible, it opens the way to possibl

David Wipf

In many applications that require matrix solutions of minimal rank, the underlying cost function is non-convex leading to an intractable, NP-hard optimization problem. Consequently, the convex nuclear norm is frequently used as a surrogate penalty term for matrix rank. The problem is that in many practical scenarios there is no longer any guarantee that we c

Erik J. Schlicht, Ritchie Lee, David H. Wolpert, Mykel J. Kochenderfer

Multi-fidelity methods combine inexpensive low-fidelity simulations with costly but highfidelity simulations to produce an accurate model of a system of interest at minimal cost. They have proven useful in modeling physical systems and have been applied to engineering problems such as wing-design optimization. During human-in-the-loop experimentation, it has

Mathias Niepert

We present a novel approach to detecting and utilizing symmetries in probabilistic graphical models with two main contributions. First, we present a scalable approach to computing generating sets of permutation groups representing the symmetries of graphical models. Second, we introduce orbital Markov chains, a novel family of Markov chains leveraging model

Rishabh Iyer, Jeff A. Bilmes

We extend the work of Narasimhan and Bilmes [30] for minimizing set functions representable as a dierence between submodular functions. Similar to [30], our new algorithms are guaranteed to monotonically reduce the objective function at every step. We empirically and theoretically show that the per-iteration cost of our algorithms is much less than [30], and

Maria Lugaro, Alexander Heger, Dean Osrin, Stephane Goriely

Among the short-lived radioactive nuclei inferred to be present in the early solar system via meteoritic analyses, there are several heavier than iron whose stellar origin has been poorly understood. In particular, the abundances inferred for 182Hf (half-life = 8.9 million years) and 129I (half-life = 15.7 million years) are in disagreement with each other i

Nicholas Hay, Stuart Russell, David Tolpin, Solomon Eyal Shimony

Sequential decision problems are often approximately solvable by simulating possible future action sequences. Metalevel decision procedures have been developed for selecting which action sequences to simulate, based on estimating the expected improvement in decision quality that would result from any particular simulation; an example is the recent work on us

Yutian Chen, Max Welling

In recent years a number of methods have been developed for automatically learning the (sparse) connectivity structure of Markov Random Fields. These methods are mostly based on L1-regularized optimization which has a number of disadvantages such as the inability to assess model uncertainty and expensive crossvalidation to find the optimal regularization par

Jie Chen, Kian Hsiang Low, Colin Keng-Yan Tan, Ali Oran

The problem of modeling and predicting spatiotemporal traffic phenomena over an urban road network is important to many traffic applications such as detecting and forecasting congestion hotspots. This paper presents a decentralized data fusion and active sensing (D2FAS) algorithm for mobile sensors to actively explore the road network to gather and assimilat

Konstantin Voevodski, Maria-Florina Balcan, Heiko Roglin, Shang-Hua Teng

Given a point set S and an unknown metric d on S, we study the problem of efficiently partitioning S into k clusters while querying few distances between the points. In our model we assume that we have access to one versus all queries that given a point s 2 S return the distances between s and all other points. We show that given a natural assumption about t

Ameet Talwalkar, Afshin Rostamizadeh

The Nystrom method is an efficient technique used to speed up large-scale learning applications by generating low-rank approximations. Crucial to the performance of this technique is the assumption that a matrix can be well approximated by working exclusively with a subset of its columns. In this work we relate this assumption to the concept of matrix cohere

Ricardo Silva, Robert B. Gramacy

In a variety of disciplines such as social sciences, psychology, medicine and economics, the recorded data are considered to be noisy measurements of latent variables connected by some causal structure. This corresponds to a family of graphical models known as the structural equation model with latent variables. While linear non-Gaussian variants have been w

Yucheng Low, Joseph E. Gonzalez, Aapo Kyrola, Danny Bickson

Designing and implementing efficient, provably correct parallel machine learning (ML) algorithms is challenging. Existing high-level parallel abstractions like MapReduce are insufficiently expressive while low-level tools like MPI and Pthreads leave ML experts repeatedly solving the same design challenges. By targeting common patterns in ML, we developed Gra

Alexey Chernov, Vladimir Vovk

In the framework of prediction with expert advice, we consider a recently introduced kind of regret bounds: the bounds that depend on the effective instead of nominal number of experts. In contrast to the Normal- Hedge bound, which mainly depends on the effective number of experts but also weakly depends on the nominal one, we obtain a bound that does not co

Ryan Prescott Adams, George E. Dahl, Iain Murray

Probabilistic matrix factorization (PMF) is a powerful method for modeling data associ- ated with pairwise relationships, Finding use in collaborative Filtering, computational bi- ology, and document analysis, among other areas. In many domains, there are additional covariates that can assist in prediction. For example, when modeling movie ratings, we might

Shohei Shimizu, Aapo Hyvarinen, Yoshinobu Kawahara

Structural equation models and Bayesian networks have been widely used to analyze causal relations between continuous variables. In such frameworks, linear acyclic models are typically used to model the datagenerating process of variables. Recently, it was shown that use of non-Gaussianity identifies a causal ordering of variables in a linear acyclic model w

Issei Sato, Kenichi Kurihara, Shu Tanaka, Hiroshi Nakagawa

This paper presents studies on a deterministic annealing algorithm based on quantum annealing for variational Bayes (QAVB) inference, which can be seen as an extension of the simulated annealing for variational Bayes (SAVB) inference. QAVB is as easy as SAVB to implement. Experiments revealed QAVB finds a better local optimum than SAVB in terms of the variat

Kenichi Kurihara, Shu Tanaka, Seiji Miyashita

This paper studies quantum annealing (QA) for clustering, which can be seen as an extension of simulated annealing (SA). We derive a QA algorithm for clustering and propose an annealing schedule, which is crucial in practice. Experiments show the proposed QA algorithm finds better clustering assignments than SA. Furthermore, QA is as easy as SA to implement.

Vicenc Gomez, Hilbert Kappen, Michael Chertkov

We introduce novel results for approximate inference on planar graphical models using the loop calculus framework. The loop calculus (Chertkov and Chernyak, 2006b) allows to express the exact partition function Z of a graphical model as a finite sum of terms that can be evaluated once the belief propagation (BP) solution is known. In general, full summation

Michael A. Finegold, Mathias Drton

Graphical Gaussian models have proven to be useful tools for exploring network structures based on multivariate data. Applications to studies of gene expression have generated substantial interest in these models, and resulting recent progress includes the development of fitting methodology involving penalization of the likelihood function. In this paper we

Hal Daume

We learn multiple hypotheses for related tasks under a latent hierarchical relationship between tasks. We exploit the intuition that for domain adaptation, we wish to share classifier structure, but for multitask learning, we wish to share covariance structure. Our hierarchical model is seen to subsume several previously proposed multitask learning models an

Alina Beygelzimer, John Langford, Yuri Lifshits, Gregory Sorkin

We consider the problem of estimating the conditional probability of a label in time O(log n), where n is the number of possible labels. We analyze a natural reduction of this problem to a set of binary regression problems organized in a tree structure, proving a regret bound that scales with the depth of the tree. Motivated by this analysis, we propose the

Mathias Niepert, Dirk Van Gucht, Marc Gyssens

A lattice-theoretic framework is introduced that permits the study of the conditional independence (CI) implication problem relative to the class of discrete probability measures. Semi-lattices are associated with CI statements and a finite, sound and complete inference system relative to semi-lattice inclusions is presented. This system is shown to be (1) s

Gert de Cooman, Filip Hermans, Erik Quaeghebeur

When the initial and transition probabilities of a finite Markov chain in discrete time are not well known, we should perform a sensitivity analysis. This is done by considering as basic uncertainty models the so-called credal sets that these probabilities are known or believed to belong to, and by allowing the probabilities to vary over such sets. This lead

Pierre-Arnuad Coquelin, Remi Munos

Bandit based methods for tree search have recently gained popularity when applied to huge trees, e.g. in the game of go [6]. Their efficient exploration of the tree enables to re- turn rapidly a good value, and improve preci- sion if more time is provided. The UCT algo- rithm [8], a tree search method based on Up- per Confidence Bounds (UCB) [2], is believed

Eldar Karabaev, Olga Skvortsova

We present a heuristic search algorithm for solving first-order MDPs (FOMDPs). Our approach combines first-order state abstraction that avoids evaluating states individually, and heuristic search that avoids evaluating all states. Firstly, we apply state abstraction directly on the FOMDP avoiding propositionalization. Such kind of abstraction is referred to

Fujun Du, Edwin A. Bergin

Water vapor has been detected in protoplanetary disks. In this work we model the distribution of water vapor in protoplanetary disks with a thermo-chemical code. For a set of parameterized disk models, we calculate the distribution of dust temperature and radiation field of the disk with a Monte Carlo method, and then solve the gas temperature distribution a

Cosma Shalizi, Kristina Lisa Klinkner

We present a new method for nonlinear prediction of discrete random sequences under minimal structural assumptions. We give a mathematical construction for optimal predictors of such processes, in the form of hidden Markov models. We then describe an algorithm, CSSR (Causal-State Splitting Reconstruction), which approximates the ideal predictor from data. We

Ramoni Adeogun

In this paper, we investigated the capacity and bit error rate (BER) performance of Multiple Input Multiple Output (MIMO) satellite systems with single and multiple dual polarized satellites in geostationary orbit and a mobile ground receiving station with multiple antennas. We evaluated the effects of both system parameters such as number of satellites, num

Vignon Oussa

Let $n$ be a natural number larger than two. Let $D_{2n}=\langle r,s : r^{n}=s^{2}=e, srs=r^{n-1} \rangle$ be the Dihedral group, and $κ$ an $n$-dimensional unitary representation of $D_{2n}$ acting in $\mathbb{C}^n$ as follows. $(κ(r)v)(j)=v((j-1)\mod n)$ and $(κ(s)v)(j)=v((n-j)\mod n)$ for $v\in\mathbb{C}^n.$ For any representation which is unitarily equiv

Paul E. Grabowski

Warm dense matter systems created in the laboratory are highly dynamical. In such cases electron dynamics is often needed to accurately simulate the evolution and properties of the system. Large systems force one to make simple approximations enabling computationally feasibility. Wave packet molecular dynamics (WPMD) provides a simple framework for simulatin

K. A. Kopotun, D. Leviatan, I. A. Shevchuk

We introduce new moduli of smoothness for functions $f\in L_p[-1,1]\cap C^{r-1}(-1,1)$, $1\le p\le\infty$, $r\ge1$, that have an $(r-1)$st locally absolutely continuous derivative in $(-1,1)$, and such that $φ^rf^{(r)}$ is in $L_p[-1,1]$, where $φ(x)=(1-x^2)^{1/2}$. These moduli are equivalent to certain weighted DT moduli, but our definition is more transpa

Abdessamad Elboushaki, Rachida Hannane, P. Nagabhushan, Mohammed Javed

Recovering the original printed texts from a document with added handwritten annotations in the marginal area is one of the challenging problems, especially when the original document is not available. Therefore, this paper aims at salvaging automatically the original document from the annotated document by detecting and removing any handwritten annotations

Paul E. Grabowski, Kieron Burke

Two electrons at the threshold of ionization represent a severe test case for electronic structure theory. A pseudospectral method yields a very accurate density of the two-electron ion with nuclear charge close to the critical value. Highly accurate energy components and potentials of Kohn-Sham density functional theory are given, as well as a useful parame

W. Jing, P. E. Souganidis, H. V. Tran

We study the averaging of fronts moving with positive oscillatory normal velocity, which is periodic in space and stationary ergodic in time. The problem can be reformulated as the homogenization of coercive level set Hamilton-Jacobi equations with spatio-temporal oscillations. To overcome the difficulties due to the oscillations in time and the sublinear gr

T. Schoof, S. Groth, M. Bonitz

In low-temperature high-density plasmas quantum effects of the electrons are becoming increasingly important. This requires the development of new theoretical and computational tools. Quantum Monte Carlo methods are among the most successful approaches to first-principle simulations of many-body quantum systems. In this chapter we present a recently develope

Edwin Wang, Naif Zaman, Shauna Mcgee, Jean-Sébastien Milanese

We discuss a cancer hallmark network framework for modelling genome-sequencing data to predict cancer clonal evolution and associated clinical phenotypes. Strategies of using this framework in conjunction with genome sequencing data in an attempt to predict personalized drug targets, drug resistance, and metastasis for a cancer patient, as well as cancer ris

Peter J. Forrester, Colin J. Thompson

The Golden-Thompson inequality, ${\rm Tr} \, (e^{A + B}) \le {\rm Tr} \, (e^A e^B)$ for $A,B$ Hermitian matrices, appeared in independent works by Golden and Thompson published in 1965. Both of these were motivated by considerations in statistical mechanics. In recent years the Golden-Thompson inequality has found applications to random matrix theory. In thi

Mercedes Lopez-Morales, Amaury H. M. J. Triaud, Florian Rodler, Xavier Dumusque

We present Rossiter-McLaughlin observations of the transiting super-Earth 55 Cnc e collected during six transit events between January 2012 and November 2013 with HARPS and HARPS-N. We detect no radial-velocity signal above 35 cm/s (3-sigma) and confine the stellar v sin i to 0.2 +/- 0.5 km/s. The star appears to be a very slow rotator, producing a very low

X. F. Lu, N. Z. Wang, H. Wu, Y. P. Wu

FeSe-derived superconductors show some unique behaviors relative to iron-pnictide superconductors, which are very helpful to understand the mechanism of superconductivity in high-Tc iron-based superconductors. The low-energy electronic structure of the heavily electron-doped AxFe2Se2 (A=K, Rb, Cs) demonstrates that interband scattering or Fermi surface nesti

Yizhen Zhang, Zihan Tan, Bhaskar Krishnamachari

We provide an analysis of the expected meeting time of two independent random walks on a regular graph. For 1-D circle and 2-D torus graphs, we show that the expected meeting time can be expressed as the sum of the inverse of non-zero eigenvalues of a suitably defined Laplacian matrix. We also conjecture based on empirical evidence that this result holds mor

Geoffrey Exoo, Dan Ismailescu

The lower bound for the chromatic number of $\mathbb{R}^n$ is improved for $n = 6, 7, 10, 11, 12, 13 \mbox{ and } 14$.

Hongqiang Song, Jie Zhang, Yao Chen, Xin Cheng

Coronal mass ejections (CMEs) are the most spectacular eruptive phenomena in the solar atmosphere. It is generally accepted that CMEs are results of eruptions of magnetic flux ropes (MFRs). However, a heated debate is on whether MFRs pre-exist before the eruptions or they are formed during the eruptions. Several coronal signatures, \textit{e.g.}, filaments,

Bjørn Kjos-Hanssen, Jan Reimann

An important theorem of geometric measure theory (first proved by Besicovitch and Davies for Euclidean space) says that every analytic set of non-zero $s$-dimensional Hausdorff measure $\mathcal H^s$ contains a closed subset of non-zero (and indeed finite) $\mathcal H^s$-measure. We investigate the question how hard it is to find such a set, in terms of the

Michaël Bensimhoun

The theorem proved in this note, although elementary, is related to a certain misconception. If $K$ is a field, $f\in K[X]$ is separable and irreducible over $K$, and $g$ is a polynomial dividing $f$, whose coefficients lie in some finite Galois extension of $K$, it may seem natural to assert that the product of the conjugates of $g$ over $K[X]$ is $f$. But

Rich Meier, Eduardo Cotilla-Sanchez, Alan Fern

In recent years there have been many improvements in the reliability of critical infrastructure systems. Despite these improvements, the power systems industry has seen relatively small advances in this regard. For instance, power quality deficiencies, a high number of localized contingencies, and large cascading outages are still too widespread. Though prog

Abel Klein, C. S. Sidney Tsang

We prove a quantitative unique continuation principle for Schrödinger operators $H=-Δ+V$ on $\mathrm{L}^2(Ω)$, where $Ω$ is an open subset of $\mathbb{R}^d$ and $V$ is a singular potential: $V \in \mathrm{L}^\infty(Ω) + \mathrm{L}^p(Ω)$. As an application, we derive a unique continuation principle for spectral projections of Schrödinger operators with singul

Luca Puricelli, Massimiliano Galluzzi, Carsten Schulte, Alessandro Podestà

Atomic Force Microscopy (AFM) has a great potential as a tool to characterize mechanical and morphological properties of living cells; these properties have been shown to correlate with cells' fate and patho-physiological state in view of the development of novel early-diagnostic strategies. Although several reports have described experimental and techni

D. Marian, E. Colomés, X. Oriols

Two-particle scattering probabilities in tunneling scenarios with exchange interaction are analyzed with quasi-particle wave packets. Two initial one-particle wave packets (with opposite central momentums) are spatially localized at each side of a barrier. After impinging upon a tunneling barrier, each wave packet splits into transmitted and reflected compon

Soma Maity

We study stability and local minimizing properties of $L^p$- norms of Riemannian curvature tensor denoted by $\mathcal{R}_p$ by variational methods. We compute the Hessian of $\mathcal{R}_p$ at compact rank 1 symmetric spaces and prove that they are stable for $\mathcal{R}_p$ for certain values of p > 2. A similar result also holds for compact quotients of r

Hong Xing, Liang Liu, Rui Zhang

Simultaneous wireless information and power transfer (SWIPT) has recently drawn significant interests for its dual use of radio signals to provide wireless data and energy access at the same time. However, a challenging secrecy communication issue arises as the messages sent to the information receivers (IRs) may be eavesdropped by the energy receivers (ERs)

Ross J. Kang, Guillem Perarnau

We prove that every graph with maximum degree $Δ$ admits a partition of its edges into $O(\sqrtΔ)$ parts (as $Δ\to\infty$) none of which contains $C_4$ as a subgraph. This bound is sharp up to a constant factor. Our proof uses an iterated random colouring procedure.

André Platzer

Differential game logic (dGL) is a logic for specifying and verifying properties of hybrid games, i.e. games that combine discrete, continuous, and adversarial dynamics. Unlike hybrid systems, hybrid games allow choices in the system dynamics to be resolved adversarially by different players with different objectives. The logic dGL can be used to study the e

Charles W. Thiel, Neil Sinclair, Wolfgang Tittel, Rufus L. Cone

We investigate the relevant spectroscopic properties of the 795 nm $^3$H$_6$$\leftrightarrow$$^3$H$_4$ transition in 1% Tm$^{3+}$:Y$_3$Ga$_5$O$_{12}$ at temperatures as low as 1.2 K for optical quantum memories based on persistent spectral tailoring of narrow absorption features. Our measurements reveal that this transition has uniform coherence properties o

Lifang Xia, E. V. Gorbar, V. A. Miransky, I. A. Shovkovy

The interaction induced chiral asymmetry is calculated in cold QED plasma beyond the weak-field approximation. By making use of the recently developed Landau-level representation for the fermion self-energy, the chiral shift and the parity-even chiral chemical potential function are obtained with the help of numerical methods. The results are used to quantif

MAGIC Collaboration, J. Aleksić, S. Ansoldi, L. A. Antonelli

PG 1553+113 is a very-high-energy (VHE, $E>100\,\mathrm{GeV}$) $γ$-ray emitter classified as a BL Lac object. Its redshift is constrained by intergalactic absorption lines in the range $0.4<z<0.58$. The MAGIC telescopes have monitored the source&#39;s activity since 2005. In early 2012, PG 1553+113 was found in a high-state, and later, in April of the same y

Endre Csóka, Gabor Lippner, Oleg Pikhurko

The classical theorem of Vizing states that every graph of maximum degree $d$ admits an edge-coloring with at most $d+1$ colors. Furthermore, as it was earlier shown by Kőnig, $d$ colors suffice if the graph is bipartite. We investigate the existence of measurable edge-colorings for graphings. A graphing is an analytic generalization of a bounded-degree grap

Abram H. Clark, Alec J. Petersen, Lou Kondic, R. P. Behringer

We experimentally study nonlinear force propagation into granular material during impact from an intruder, and we explain our observations in terms of the nonlinear grain-scale force relation. Using high-speed video and photoelastic particles, we determine the speed and spatial structure of the force response just after impact. We show that these quantities

G. B. Lesovik, I. A. Sadovskyy

We consider the scattering matrix approach to quantum electron transport in meso- and nano-conductors. This approach is an alternative to the more conventional kinetic equation and Green&#39;s function approaches, and often is more efficient for coherent conductors (especially for proving general relations) and typically more transparent. We provide a descri

Gang Chen, Hae-Young Kee, Yong Baek Kim

Motivated by recent experiments on the quantum-spin-liquid candidate material LiZn2Mo3O8, we study a single-band extended Hubbard model on an anisotropic Kagome lattice with the 1/6 electron filling. Due to the partial filling of the lattice, the inter-site repulsive interaction is necessary to generate Mott insulators, where electrons are localized in clust

C. Robertson

The concept of fusing rules for defects in a^(1)_r affine Toda field theories is introduced in the classical and quantum contexts. This idea is employed in finding a new transmission matrix for the a^(1)_3 theory which obeys the triangle relations and the crossing-unitarity relations.

Aaron C. Vincent, Enrique Fernandez Martinez, Pilar Hernandez, Massimiliano Lattanzi

We employ state-of-the art cosmological observables including supernova surveys and BAO information to provide constraints on the mass and mixing angle of a non-resonantly produced sterile neutrino species, showing that cosmology can effectively rule out sterile neutrinos which decay between BBN and the present day. The decoupling of an additional heavy neut

Jérôme Gleyzes, David Langlois, Federico Piazza, Filippo Vernizzi

We have recently proposed a new class of gravitational scalar-tensor theories free from Ostrogradski instabilities, in arXiv:1404.6495. As they generalize Horndeski theories, or &#34;generalized&#34; galileons, we call them G$^3$. These theories possess a simple formulation when the time hypersurfaces are chosen to coincide with the uniform scalar field hype