February 2017 arXiv papers — page 2

José Garre-Rubio, Sofyan Iblisdir, David Pérez-García

Topological ordered phases are related to changes in the properties of their quasi-particle excitations (anyons). We study these relations in the framework of projected entanglement pair states (\textsf{PEPS}) and show how condensing and confining anyons reduces a local gauge symmetry to a global on-site symmetry. We also study the action of this global symm

G. E. Pavlou, N. E. Palaiodimopoulos, P. A. Kalozoumis, A. Sourpis

We are considering the time-dependent transport through a discrete system, consiting of a quantum dot T-coupled to an infinite tight-binding chain. The periodic driving that is induced on the coupling between the dot and the chain, leads to the emergence of a characteristic multiple Fano resonant profile in the transmission spectrum. We focus on investigatin

Chinmay Khandekar, Alejandro W. Rodriguez

We present an approach for achieving large Kerr $χ^{(3)}$--mediated thermal energy transfer at the nanoscale that exploits a general coupled-mode description of triply resonant, four-wave mixing processes. We analyze the efficiency of thermal upconversion and energy transfer from mid- to near-infrared wavelengths in planar geometries involving two slabs supp

Jinn-Ouk Gong, Gonzalo A. Palma, Spyros Sypsas

If time-dependent disruptions from slow-roll occur during inflation, the correlation functions of the primordial curvature perturbation should have scale-dependent features, a case which is marginally supported from the cosmic microwave background (CMB) data. We offer a new approach to analyze the appearance of such features in the primordial bispectrum that

Xing Zhang, Tan Liu, Wen Zhao

Screened modified gravity (SMG) is a kind of scalar-tensor theory with screening mechanisms, which can suppress the fifth force in dense regions and allow theories to evade the solar system and laboratory tests. In this paper, we investigate how the screening mechanisms in SMG affect the gravitational radiation damping effects, calculate in detail the rate o

S. V. Gusev

It is unknown so far, whether the lattice of all varieties of monoids satisfies some non-trivial identity. The objective of this note is to give the negative answer to this question. Namely, we prove that any finite lattice is a homomorphic image of some sublattice of the lattice of overcommutative varieties of monoids (i.e., varieties that contain the varie

Bülent Karasözen, Murat Uzunca, Tuğba Küçükseyhan

In this paper, we compare three model order reduction methods: the proper orthogonal decomposition (POD), discrete empirical interpolation method (DEIM) and dynamic mode decomposition (DMD) for the optimal control of the convective FitzHugh-Nagumo (FHN) equations. The convective FHN equations consists of the semi-linear activator and the linear inhibitor equ

Peter Gracar, Alexandre Stauffer

Consider the graph induced by $\mathbb{Z}^d$, equipped with uniformly elliptic random conductances. At time $0$, place a Poisson point process of particles on $\mathbb{Z}^d$ and let them perform independent simple random walks. Tessellate the graph into cubes indexed by $i\in\mathbb{Z}^d$ and tessellate time into intervals indexed by $τ$. Given a local event

A. E. Sitnitsky

We construct a double-well potential for which the Schrödinger equation can be exactly solved via reducing to the confluent Heun's one. Thus the wave function is expressed via the confluent Heun's function. The latter is tabulated in {\sl {Maple}} so that the obtained solution is easily treated. The potential is infinite at the boundaries of the fina

Daniel Grigat, Fabio Caccioli

We reverse engineer dynamics of financial contagion to find the scenario of smallest exogenous shock that, should it occur, would lead to a given final systemic loss. This reverse stress test can be used to identify the potential triggers of systemic events, and it removes the arbitrariness in the selection of shock scenarios in stress testing. We consider i

Manuel Aprile, Yuri Faenza, Samuel Fiorini, Tony Huynh

The extension complexity $\mathsf{xc}(P)$ of a polytope $P$ is the minimum number of facets of a polytope that affinely projects to $P$. Let $G$ be a bipartite graph with $n$ vertices, $m$ edges, and no isolated vertices. Let $\mathsf{STAB}(G)$ be the convex hull of the stable sets of $G$. It is easy to see that $n \leqslant \mathsf{xc} (\mathsf{STAB}(G)) \l

Joseph Doolittle, Eran Nevo, Guillermo Pineda-Villavicencio, Julien Ugon

Blind and Mani, and later Kalai, showed that the face lattice of a simple polytope is determined by its graph, namely its $1$-skeleton. Call a vertex of a $d$-polytope \emph{nonsimple} if the number of edges incident to it is more than $d$. We show that (1) the face lattice of any $d$-polytope with at most two nonsimple vertices is determined by its $1$-skel

Roxana Rădulescu, Peter Vrancx, Ann Nowé

Congestion problems are omnipresent in today's complex networks and represent a challenge in many research domains. In the context of Multi-agent Reinforcement Learning (MARL), approaches like difference rewards and resource abstraction have shown promising results in tackling such problems. Resource abstraction was shown to be an ideal candidate for sol

Simon Becker, Marjan Mirahmadi, Burkhard Schmidt, Konrad Schatz

We have subjected the planar pendulum eigenproblem to a symmetry analysis with the goal of explaining the relationship between its conditional quasi-exact solvability (C-QES) and the topology of its eigenenergy surfaces, established in our earlier work [Frontiers in Physical Chemistry and Chemical Physics 2, 1-16, (2014)]. The present analysis revealed that

Joanna Mikolajewska, Michael M. Shara

If accreting white dwarfs (WD) in binary systems are to produce type Ia supernovae (SNIa), they must grow to nearly the Chandrasekhar mass and ignite carbon burning. Proving conclusively that a WD has grown substantially since its birth is a challenging task. Slow accretion of hydrogen inevitably leads to the erosion, rather than the growth of WDs. Rapid hyd

Pascal Chossat, Alexander Lohse, Olga Podvigina

We study pseudo-simple heteroclinic cycles for a $Γ$-equivariant system in $R^4$ with finite $Γ\subset O(4)$, and their nearby dynamics. In particular, in a first step towards a full classification - analogous to that which exists already for the class of simple cycles - we identify all finite subgroups of $O(4)$ admitting pseudo-simple cycles. To this end w

Jan Rybizki, Andreas Just, Hans-Walter Rix

Elemental abundances of stars are the result of the complex enrichment history of their galaxy. Interpretation of observed abundances requires flexible modeling tools to explore and quantify the information about Galactic chemical evolution (GCE) stored in such data. Here we present Chempy, a newly developed code for GCE modeling, representing a parametrized

Karlis Freivalds, Renars Liepins

Algorithm learning is a core problem in artificial intelligence with significant implications on automation level that can be achieved by machines. Recently deep learning methods are emerging for synthesizing an algorithm from its input-output examples, the most successful being the Neural GPU, capable of learning multiplication. We present several improveme

Ouraman Hajizadeh, Axel Maas

The inner structure of neutron stars is still an open question. To make progress and understand the qualitative impact of gauge interactions on the neutron star structure we study neutron stars in a modified version of QCD. In this modification the gauge group of QCD is replaced by the exceptional Lie group G$_2$, which has neutrons and is accessible at fini

Sourav Bhattacharya, Sumanta Chakraborty, T. Padmanabhan

Earlier it was shown that the entropy of an ideal gas, contained in a box and moving in a gravitational field, develops an area dependence when it approaches the horizon of a static, spherically symmetric spacetime. Here we extend the above result in two directions; viz., to (a) the stationary axisymmteric spacetimes and (b) time dependent cosmological space

Weihua Hu, Takeru Miyato, Seiya Tokui, Eiichi Matsumoto

Learning discrete representations of data is a central machine learning task because of the compactness of the representations and ease of interpretation. The task includes clustering and hash learning as special cases. Deep neural networks are promising to be used because they can model the non-linearity of data and scale to large datasets. However, their m

Michael Schwarz, Samuel Weiser, Daniel Gruss, Clémentine Maurice

In modern computer systems, user processes are isolated from each other by the operating system and the hardware. Additionally, in a cloud scenario it is crucial that the hypervisor isolates tenants from other tenants that are co-located on the same physical machine. However, the hypervisor does not protect tenants against the cloud provider and thus the sup

Linta Joseph, Anil Shaji

Open quantum dynamics in a tripartite scenario including a system, its environment and a passive reference is shown to resolve several open questions regarding not completely positive (NCP) dynamical maps as valid descriptions of open quantum evolution. The steering states of the system and the environment with respect to the reference, reduced down to a den

Patrizio Angelini, Michael A. Bekos, Franz J. Brandenburg, Giordano Da Lozzo

A graph is $k$-planar $(k \geq 1)$ if it can be drawn in the plane such that no edge is crossed more than $k$ times. A graph is $k$-quasi planar $(k \geq 2)$ if it can be drawn in the plane with no $k$ pairwise crossing edges. The families of $k$-planar and $k$-quasi planar graphs have been widely studied in the literature, and several bounds have been prove

Tongliang Liu, Gábor Lugosi, Gergely Neu, Dacheng Tao

We introduce a notion of algorithmic stability of learning algorithms---that we term \emph{argument stability}---that captures stability of the hypothesis output by the learning algorithm in the normed space of functions from which hypotheses are selected. The main result of the paper bounds the generalization error of any learning algorithm in terms of its

Karim Ghorbani

We investigate the vacuum stability and perturbativity of a pseudoscalar portal dark matter model with a Dirac dark matter (DM) candidate, through the renormalization group equation analysis at one-loop order. The model has a particular feature which can evade the direct detection upper bounds measured by XENON100 and even that from planned experiment XENON1

Khazret S. Nirov, Alexander V. Razumov

We discuss highest $\ell$-weight representations of quantum loop algebras and the corresponding functional relations between integrability objects. In particular, we compare the prefundamental and $q$-oscillator representations of the positive Borel subalgebras of the quantum group $\mathrm{U}_q(\mathcal L(\mathfrak{sl}_{l+1}))$ for arbitrary values of $l$.

Steven D. King, Frank W. Nijhoff

A modern notion of integrability is that of multidimensional consistency (MDC), which classically implies the coexistence of (commuting) dynamical flows in several independent variables for one and the same dependent variable. This property holds for both continuous dynamical systems as well as for discrete ones defined in discrete space-time. Possibly the s

Kevin Scaman, Francis Bach, Sébastien Bubeck, Yin Tat Lee

In this paper, we determine the optimal convergence rates for strongly convex and smooth distributed optimization in two settings: centralized and decentralized communications over a network. For centralized (i.e. master/slave) algorithms, we show that distributing Nesterov's accelerated gradient descent is optimal and achieves a precision $\varepsilon >

Shao-Bo Lin, Jinshan Zeng, Xiangyu Chang

This paper aims at refined error analysis for binary classification using support vector machine (SVM) with Gaussian kernel and convex loss. Our first result shows that for some loss functions such as the truncated quadratic loss and quadratic loss, SVM with Gaussian kernel can reach the almost optimal learning rate, provided the regression function is smoot

Hongdiao Wen

Dermoscopy image detection stays a tough task due to the weak distinguishable property of the object.Although the deep convolution neural network signifigantly boosted the performance on prevelance computer vision tasks in recent years,there remains a room to explore more robust and precise models to the problem of low contrast image segmentation.Towards the

Yan Cui, Huiping Zhu, Lei Wang, Bo Li

Materials that change their magnetic properties in response to the external stimuli have long been of interest for their potential applicability in magnetic storage device, spintronics and smart magnetic materials. Organic materials are suitable candidates for such materials due to their chemical diversity, flexibility and designablity. However, most methods

Wolfgang Steimle

In this note we show that a semisimplicial set with the weak Kan condition admits a simplicial structure, provided any object allows an idempotent self-equivalence. Moreover, any two choices of simplicial structures give rise to equivalent quasi-categories. The method is purely combinatorial and extends to semisimplicial objects in other categories; in parti

Juan Rojas, Shuangqi Luo, Dingqiao Zhu, Yunlong Du

Robotic failure is all too common in unstructured robot tasks. Despite well-designed controllers, robots often fail due to unexpected events. How do robots measure unexpected events? Many do not. Most robots are driven by the sense-plan act paradigm, however more recently robots are undergoing a sense-plan-act-verify paradigm. In this work, we present a prin

Mahito Sugiyama, Karsten Borgwardt

The search for higher-order feature interactions that are statistically significantly associated with a class variable is of high relevance in fields such as Genetics or Healthcare, but the combinatorial explosion of the candidate space makes this problem extremely challenging in terms of computational efficiency and proper correction for multiple testing. W

Will Clemens, Nick Evans

The Nambu Jona-Lasinio model of chiral symmetry breaking predicts a second order chiral phase transition. If the fermions in addition have non-abelian gauge interactions then the transition is expected to become a crossover as the NJL term enhances the IR chiral symmetry breaking of the gauge theory. We study this behaviour in the holographic Dynamic AdS/QCD

Long Chen, Junyu Dong, ShengKe Wang, Kin-Man Lam

Fine-grained recognition is a challenging task due to the small intra-category variances. Most of top-performing fine-grained recognition methods leverage parts of objects for better performance. Therefore, part annotations which are extremely computationally expensive are required. In this paper, we propose a novel cascaded deep CNN detection framework for

Weifeng Ge, Yizhou Yu

Deep neural networks require a large amount of labeled training data during supervised learning. However, collecting and labeling so much data might be infeasible in many cases. In this paper, we introduce a source-target selective joint fine-tuning scheme for improving the performance of deep learning tasks with insufficient training data. In this scheme, a

A. I. Shushin

Kinetics of singlet fission in organic semiconductors, in which the excited singlet state (S_1) spontaneously splits into a pair of triplet (T) excitons, is known to be strongly influenced by back geminate annihilation of TT-pairs. We show that this influence can be properly described only by taking into account the diffusive exciton migration. The migration

Vitaly A. Kuzkin, Anton M. Krivtsov

An approach for analytical description of thermal processes in harmonic lattices is presented. We cover longitudinal and transverse vibrations of chains and out-of-plane vibrations of two-dimensional lattices with interactions of an arbitrary number of neighbors. Motion of each particle is governed by a single scalar equation and therefore the notion "sc

J. Kluson

We find Carroll non-BPS Dp-brane action by performing Carroll limit of a canonical form of unstable Dp-brane action. We analyze different Carroll limits and discuss solutions of the equations of motion of Carroll non-BPS Dp-brane at the tachyon vacuum.

Jiří Rosický

A. Avilés and C. Brech proved a intriguing result about the existence and uniqueness of certain injective Boolean algebras or Banach spaces. Their result refines the standard existence and uniqueness of saturated models. They express a wish to obtain a unified approach in the context of category theory. We provide this in the framework of weak factorization

M. Chmara, J. Maksymiuk

In this paper we study some properties of anisotropic Orlicz and anisotropic Orlicz-Sobolev spaces of vector valued functions for a special class of G-functions. We introduce a variational setting for a class of Lagrangian Systems. We give conditions which ensure that the principal part of variational functional is finitely defined and continuously different

Pablo F. Damasceno, Sharon C. Glotzer, Michael Engel

Quasicrystals are frequently encountered in condensed matter. They are important candidates for equilibrium phases from the atomic scale to the nanoscale. Here, we investigate the computational self-assembly of four quasicrystals in a single model system of identical particles interacting with a tunable isotropic pair potential. We reproduce a known icosahed

Pengyu Wang, Yuan Gan, Panpan Shui, Fenggen Yu

We desgin a novel fully convolutional network architecture for shapes, denoted by Shape Fully Convolutional Networks (SFCN). 3D shapes are represented as graph structures in the SFCN architecture, based on novel graph convolution and pooling operations, which are similar to convolution and pooling operations used on images. Meanwhile, to build our SFCN archi

Wei Hu, Xiu-Hua Luo, Bao-Lin Xiong, Guodong Zhou

We generalize the monomorphism category from quiver (with monomial relations) to arbitrary finite dimensional algebras by a homological definition. Given two finite dimension algebras $A$ and $B$, we use the special monomorphism category Mon(B, A-Gproj) to describe some Gorenstein projective bimodules over the tensor product of $A$ and $B$. If one of the two

P. Ko, Yuji Omura, Yoshihiro Shigekami, Chaehyun Yu

We study an extended Standard Model with a gauged U(1)$^{\prime}$ flavor symmetry, motivated not only by the fermion mass hierarchy but also by the excesses in $B \to K^{(*)} l l$ reported by the LHCb collaborations. The U(1)$^{\prime}$ charges are assigned to quarks and leptons in a flavor-dependent manner, and flavored Higgs doublets are also introduced in

Yinan Li, Youming Qiao

A matrix space of size $m\times n$ is a linear subspace of the linear space of $m\times n$ matrices over a field $\mathbb{F}$. The rank of a matrix space is defined as the maximal rank over matrices in this space. A matrix space $\mathcal{A}$ is called rank-critical, if any matrix space which properly contains it has rank strictly greater than that of $\math

Danny Nguyen, Igor Pak

We prove that integer programming with three quantifier alternations is $NP$-complete, even for a fixed number of variables. This complements earlier results by Lenstra and Kannan, which together say that integer programming with at most two quantifier alternations can be done in polynomial time for a fixed number of variables. As a byproduct of the proof, w

Danny Nguyen, Igor Pak

We give complexity analysis of the class of short generating functions (GF). Assuming $\#P \not\subseteq FP/poly$, we show that this class is not closed under taking many intersections, unions or projections of GFs, in the sense that these operations can increase the bitlength of coefficients of GFs by a super-polynomial factor. We also prove that truncated

Shuntaro Sumita, Takuya Nomoto, Youichi Yanase

Discoveries of marked similarities to high-$T_{\text{c}}$ cuprate superconductors point to the realization of superconductivity in the doped $J_{\text{eff}} = 1 / 2$ Mott insulator Sr$_2$IrO$_4$. Contrary to the mother compound of cuprate superconductors, several stacking patterns of in-plane canted antiferromagnetic moments have been reported, which are dis

Robert Griffin, Tyson Cobb, Travis Craig, Mark Daniel

Exoskeletons are a promising technology that enables individuals with mobility limitations to walk again. As the 2016 Cybathlon illustrated, however, the community has a considerable way to go before exoskeletons have the necessary capabilities to be incorporated into daily life. While most exoskeletons power only hip and knee flexion, Team Institute for Hum

Ali Gholami Rudi

In the General Position Subset Selection (GPSS) problem, the goal is to find the largest possible subset of a set of points such that no three of its members are collinear. If $s_{\mathrm{GPSS}}$ is the size of the optimal solution, $\sqrt{s_{\mathrm{GPSS}}}$ is the current best guarantee for the size of the solution obtained using a polynomial time algorith

Asli Celikyilmaz, Li Deng, Lihong Li, Chong Wang

We introduce a new paradigm of learning for reasoning, understanding, and prediction, as well as the scaffolding network to implement this paradigm. The scaffolding network embodies an incremental learning approach that is formulated as a teacher-student network architecture to teach machines how to understand text and do reasoning. The key to our computatio

Pichao Wang, Wanqing Li, Zhimin Gao, Yuyao Zhang

Scene flow describes the motion of 3D objects in real world and potentially could be the basis of a good feature for 3D action recognition. However, its use for action recognition, especially in the context of convolutional neural networks (ConvNets), has not been previously studied. In this paper, we propose the extraction and use of scene flow for action r

Alexandre Y. Aravkin, James V. Burke, Dmitriy Drusvyatskiy, Michael P. Friedlander

We revisit the foundations of gauge duality and demonstrate that it can be explained using a modern approach to duality based on a perturbation framework. We therefore put gauge duality and Fenchel-Rockafellar duality on equal footing, including explaining gauge dual variables as sensitivity measures, and showing how to recover primal solutions from those of

Ozsel Kilinc, Ismail Uysal

In this paper, we discuss a different type of semi-supervised setting: a coarse level of labeling is available for all observations but the model has to learn a fine level of latent annotation for each one of them. Problems in this setting are likely to be encountered in many domains such as text categorization, protein function prediction, image classificat

Siheon Ryee, Myung Joon Han

A systematic first-principles study has been performed to understand the magnetism of thin film SrRuO$_3$ which lots of research efforts have been devoted to but no clear consensus has been reached about its ground state properties. The relative t$_{2g}$ level difference, lattice distortion as well as the layer thickness play together in determining the spin

Peng Lei, Fuxin Li, Sinisa Todorovic

Using deep learning, this paper addresses the problem of joint object boundary detection and boundary motion estimation in videos, which we named boundary flow estimation. Boundary flow is an important mid-level visual cue as boundaries characterize objects spatial extents, and the flow indicates objects motions and interactions. Yet, most prior work on moti

Sang-Ho Kim, Seung-il Nam, Daisuke Jido, Hyun-Chul Kim

We investigate the photoproduction of $Λ(1405)\equivΛ^*$ hyperon resonance, i.e., $γp\to K^+Λ^*$, employing the effective Lagrangian approach with the $t$-channel Regge trajectories at tree level. We extensively explore the effects from the nucleon resonances in the vicinity of the threshold $\sqrt{s}_\mathrm{th}\approx1900$ MeV, i.e., $N(2000)$, $N(2030)$,

Andrei M. Beloborodov

The persistent radio counterpart of FRB 121102 is estimated to have $N\sim 10^{52}$ particles, energy $E_N\sim 10^{48}$ erg, and size $R\sim 10^{17}$ cm. The source can be a nebula inflated and heated by an intermittent outflow from a magnetar --- a neutron star powered by its magnetic (rather than rotational) energy. The object is young and frequently liber

Maicol A. Ochoa, Andrés Villaveces

We study model-theoretical structures for prototypical physical systems. First, a summary of the model theory of sheaves, adapted to the metric case, is presented. In particular, we provide conditions for a generalization of the generic model theorem to metric sheaves. The essentials of the model theory of metric sheaves appeared in the form of Conference Pr

Wenguan Wang, Jianbing Shen, Fatih Porikli

Conventional video segmentation approaches rely heavily on appearance models. Such methods often use appearance descriptors that have limited discriminative power under complex scenarios. To improve the segmentation performance, this paper presents a pyramid histogram based confidence map that incorporates structure information into appearance statistics. It

John Malik, Neil Reed, Chun-Li Wang, Hautieng Wu

A novel single-lead f-wave extraction algorithm based on the modern diffusion geometry data analysis framework is proposed. The algorithm is essentially an averaged beat subtraction algorithm, where the ventricular activity template is estimated by combining a newly designed metric, the "diffusion distance," and the non-local Euclidean median based o

Wenguan Wang, Jianbing Shen, Jianwen Xie, Fatih Porikli

We introduce a novel semi-supervised video segmentation approach based on an efficient video representation, called as "super-trajectory". Each super-trajectory corresponds to a group of compact trajectories that exhibit consistent motion patterns, similar appearance and close spatiotemporal relationships. We generate trajectories using a probabilist

Preeti Bhandari, Vikas Malik, Syed Rashid Ahmad

The lattice model of Coulomb Glass in two dimensions with box-type random field distribution is studied at zero temperature for system size upto $96^{2}$. To obtain the minimum energy state we annealed the system using Monte Carlo simulation followed by further minimization using cluster-flipping. The values of the critical exponents are determined using the

Leonid Chekhov, Paul Norbury

We prove a Givental type decomposition for partition functions that arise out of topological recursion applied to spectral curves. Copies of the Konstevich-Witten KdV tau function arise out of regular spectral curves and copies of the Brezin-Gross-Witten KdV tau function arise out of irregular spectral curves. We present the example of this decomposition for

Isaac J. Sledge, Jose C. Principe

Conventional reinforcement learning methods for Markov decision processes rely on weakly-guided, stochastic searches to drive the learning process. It can therefore be difficult to predict what agent behaviors might emerge. In this paper, we consider an information-theoretic cost function for performing constrained stochastic searches that promote the format

Yiyang Wang, Risheng Liu, Xiaoliang Song, Zhixun Su

In recent years, numerous vision and learning tasks have been (re)formulated as nonconvex and nonsmooth programmings(NNPs). Although some algorithms have been proposed for particular problems, designing fast and flexible optimization schemes with theoretical guarantee is a challenging task for general NNPs. It has been investigated that performing inexact in

H. M. Antia, J. S. Yadav, P. C. Agrawal, Jai Verdhan Chauhan

We present the calibration and background model for the Large Area X-ray Proportional Counter (LAXPC) detectors on-board AstroSat. LAXPC instrument has three nominally identical detectors to achieve large collecting area. These detectors are independent of each other and in the event analysis mode, they record the arrival time and energy of each photon that

Xinyu Li, Yanyi Zhang, Jianyu Zhang, Yueyang Chen

Process modeling and understanding are fundamental for advanced human-computer interfaces and automation systems. Most recent research has focused on activity recognition, but little has been done on sensor-based detection of process progress. We introduce a real-time, sensor-based system for modeling, recognizing and estimating the progress of a work proces

Charlotte Sleight, Massimo Taronna

We develop a systematic framework to compute the conformal partial wave expansions (CPWEs) of tree-level four-point Witten diagrams with totally symmetric external fields of arbitrary mass and integer spin in AdS$_{d+1}$. Employing this framework, we determine the CPWE of a generic exchange Witten diagram with spinning exchanged field. As an intermediate ste

H. Ahmed, U. Bekbaev, I. Rakhimov

A complete classification of two-dimensional algebras over algebraically closed fields is provided

Chiaki Hikage, Rachel Mandelbaum, Alexie Leauthaud, Eduardo Rozo

Galaxy cluster centring is a key issue for precision cosmology studies using galaxy surveys. Mis-identification of central galaxies causes systematics in various studies such as cluster lensing, satellite kinematics, and galaxy clustering. The red-sequence Matched-filter Probabilistic Percolation (redMaPPer) estimates the probability that each member galaxy

Shintaro Nakamura, Ryotaro Kase, Shinji Tsujikawa

The beyond-generalized Proca theories are the extension of second-order massive vector-tensor theories (dubbed generalized Proca theories) with two transverse vector modes and one longitudinal scalar besides two tensor polarizations. Even with this extension, the propagating degrees of freedom remain unchanged on the isotropic cosmological background without

Finale Doshi-Velez, Been Kim

As machine learning systems become ubiquitous, there has been a surge of interest in interpretable machine learning: systems that provide explanation for their outputs. These explanations are often used to qualitatively assess other criteria such as safety or non-discrimination. However, despite the interest in interpretability, there is very little consensu

Yuncong Chen, Lauren McElvain, Alex Tolpygo, Daniel Ferrante

While modern imaging technologies such as fMRI have opened exciting new possibilities for studying the brain in vivo, histological sections remain the best way to study the anatomy of the brain at the level of single neurons. The histological atlas changed little since 1909 and localizing brain regions is a still a labor intensive process performed only by e

H. -W. Hammer, C. Ji, D. R. Phillips

Nuclear halos emerge as new degrees of freedom near the neutron and proton driplines. They consist of a core and one or a few nucleons which spend most of their time in the classically-forbidden region outside the range of the interaction. Individual nucleons inside the core are thus unresolved in the halo configuration, and the low-energy effective interact

Siyu Zhu, Tianwei Shen, Lei Zhou, Runze Zhang

In this paper, we tackle the accurate and consistent Structure from Motion (SfM) problem, in particular camera registration, far exceeding the memory of a single computer in parallel. Different from the previous methods which drastically simplify the parameters of SfM and sacrifice the accuracy of the final reconstruction, we try to preserve the connectiviti

Y. Koohsarian, K. Javidan, A. Shirzad

We find the Casimir energy, at finite temperature, for acoustic phonons in a Graphene sheet suspended over a rectangular trench, and the corresponding Casimir forces are interpreted as correction terms to the built-in tensions of the Graphene. We show that these corrections generally break the tensional isotropy of the membrane, and can increase or decrease

Kevin Chen, Rachael Hong, Jerry Qu, David Wang

Let $p$ be a prime. In this short note we study some families of super congruences involving the following alternating sums \begin{equation*} \sum_{\substack{j_1+j_2+\cdots+j_n=2 p^r p\nmid j_1 j_2 \cdots j_n}} \frac{(-1)^{j_1+\cdots+j_b}}{j_1\cdots j_n} \pmod{p^r}, \end{equation*} which extend similar statements proved by Shen and Cai who treated the cases

Sheng Li, Jongsoo Park, Ping Tak Peter Tang

Sparse methods and the use of Winograd convolutions are two orthogonal approaches, each of which significantly accelerates convolution computations in modern CNNs. Sparse Winograd merges these two and thus has the potential to offer a combined performance benefit. Nevertheless, training convolution layers so that the resulting Winograd kernels are sparse has

M. Barbero-Liñán, H. Cendra, E. García-Toraño Andrés, D. Martín de Diego

We provide a generalization of the notion of Dirac system by using Morse families to intrinsically embrace the dynamics associated with different physical systems such as constrained variational calculus, optimal control, Lagrangian mechanics, etc., from both the Lagrangian and the Hamiltonian viewpoint. Besides, we introduce a geometric construction of Port

Yuhe Zhang, J. K. Jain, J. P. Eisenstein

In a bilayer system consisting of a composite-fermion Fermi sea in each layer, the tunnel current is exponentially suppressed at zero bias, followed by a strong peak at a finite bias voltage $V_{\rm max}$. This behavior, which is qualitatively different from that observed for the electron Fermi sea, provides fundamental insight into the strongly correlated n

Michael T. Lacey

We consider the averages of a function $ f$ on $ \mathbb R ^{n}$ over spheres of radius $ 0< r< \infty $ given by $ A_{r} f (x) = \int_{\mathbb S ^{n-1}} f (x-r y) \; d σ(y)$, where $ σ$ is the normalized rotation invariant measure on $ \mathbb S ^{n-1}$. We prove a sharp range of sparse bounds for two maximal functions, the first the lacunary spherical maxi

Andrew Banman, Lori Ziegelmeier

The Gapminder project set out to use statistics to dispel simplistic notions about global development. In the same spirit, we use persistent homology, a technique from computational algebraic topology, to explore the relationship between country development and geography. For each country, four indicators, gross domestic product per capita; average life expe

Jie Yen Fan, Kais Hamza, Peter Jagers, Fima C. Klebaner

We consider a family of general branching processes with reproduction parameters depending on the age of the individual as well as the population age structure and a parameter $K$, which may represent the carrying capacity. These processes are Markovian in the age structure. In a previous paper the Law of Large Numbers as $K\to\infty$ was derived. Here we pr

David Balduzzi, Marcus Frean, Lennox Leary, JP Lewis

A long-standing obstacle to progress in deep learning is the problem of vanishing and exploding gradients. Although, the problem has largely been overcome via carefully constructed initializations and batch normalization, architectures incorporating skip-connections such as highway and resnets perform much better than standard feedforward architectures despi

R. Li, J. Lassen, Z. P. Zhong, F. D. Jia

Multi-step laser resonance ionization spectroscopy of lutetium (Lu) has been performed at TRIUMF&#39;s off-line laser ion source test stand. The even-parity Rydberg series $6s^2nd$ $^2D_{3/2}$, $6s^2nd$ $^2D_{5/2}$ and $6s^2ns$ $^2S_{1/2}$ were observed converging to the 6s$^2$ ionization potential. The experimental results has been compared to previous work

Richard Schmidt, Michael Knap, Dmitri A. Ivanov, Jhih-Shih You

In this work we discuss the dynamical response of heavy quantum impurities immersed in a Fermi gas at zero and at finite temperature. Studying both the frequency and the time domain allows one to identify interaction regimes that are characterized by distinct many-body dynamics. From this theoretical study a picture emerges in which impurity dynamics is univ

Lenz Belzner, Thomas Gabor

Motivated by runtime verification of QoS requirements in self-adaptive and self-organizing systems that are able to reconfigure their structure and behavior in response to runtime data, we propose a QoS-aware variant of Thompson sampling for multi-armed bandits. It is applicable in settings where QoS satisfaction of an arm has to be ensured with high confide

Henrietta Forssen, Riyaz S. Patel, Natalie Fitzpatrick, Aroon Hingorani

Metabolomic data can potentially enable accurate, non-invasive and low-cost prediction of coronary artery disease. Regression-based analytical approaches however might fail to fully account for interactions between metabolites, rely on a priori selected input features and thus might suffer from poorer accuracy. Supervised machine learning methods can potenti

Ahmedou Yahya Ould Mohameden, Mohamed Vall Ould Moustapha

In this article, we give the explicit solutions to the Laplace equations associated to the Dirac operator, Euler operator and the harmonic oscillator in R.

Saad Omar, Dan Jiao

Linear complexity iterative and log-linear complexity direct solvers are developed for the volume integral equation (VIE) based general large-scale electrodynamic analysis. The dense VIE system matrix is first represented by a new cluster-based multilevel low-rank representation. In this representation, all the admissible blocks associated with a single clus

Aswin Sekhar, David Asher, Stephanie Werner, Jeremie Vaubaillon

Both General Relativistic (GR) precession and the Lidov-Kozai mechanism, separately, are known to play an important role in the orbital evolution of solar system bodies. Previous works have studied these two mechanisms independently in great detail. However, both these phenomena occurring at the same time in real solar system bodies have rarely been explored

Mehdi Babaei, Ahmed Abu-Siada

Frequency Response Analysis (FRA) is generally used to detect any changes in the active part of the test object. Several studies have analyzed the effect of different mechanical changes including deformations and oil insulation decays on frequency response of transformers as a test object, however noresearch has ever studied the effect of gas degradation on

Alessandro Loriga, Parvin Moyassari, Daniele Bernardini, Gregorio Landi

We demonstrate the capabilities of nonlinear Volterra models to simulate the behavior of an audio system and compare them to linear filters. In this paper a nonlinear model of an audio system based on Volterra series is presented and Normalized Least Mean Square algorithm is used to determine the Volterra series to third order. Training data for the models w

Claudio Mazzola, Peter Evans

The principle of common cause asserts that positive correlations between causally unrelated events ought to be explained through the action of some shared causal factors. Reichenbachian common cause systems are probabilistic structures aimed at accounting for cases where correlations of the aforesaid sort cannot be explained through the action of a single co

Md Arafat Hossain, John Canning, Zhikang Yu, Sandra Ast

A smartphone fluorimeter capable of time-based fluorescence intensity measurements at various temperatures is reported. Excitation is provided by an integrated UV LED (370 nm) and detection obtained using the in-built CMOS camera. A Peltier is integrated to allow measurements of the intensity over T = 10 to 40 C with a maximum temperature resolution of DELTA

Hermano Velten, Jose Beltrán Jiménez, Federico Piazza

A large class of modified theories of gravity used as models for dark energy predict a propagation speed for gravitational waves which can differ from the speed of light. This difference of propagations speeds for photons and gravitons has an impact in the emission of gravitational waves by binary systems. Thus, we revisit the usual quadrupolar emission of b