title:
Thermalization, Isotropization and Elliptic Flow from Nonequilibrium
  Initial Conditions with a Saturation Scale

abstract:
  In this article we report on our results about the computation of the
elliptic flow of the quark-gluon-plasma produced in relativistic heavy ion
collisions, simulating the expansion of the fireball by solving the
relativistic Boltzmann equation for the parton distribution function tuned at a
fixed shear viscosity to entropy density ratio $\eta/s$. Our main goal is to
put emphasis on the role of a saturation scale in the initial gluon spectrum,
which makes the initial distribution far from a thermalized one. We find that
the presence of the saturation scale reduces the efficiency in building-up the
elliptic flow, even if the thermalization process is quite fast $\tau_{therm}
\approx 0.8 \,\rm fm/c$ and the pressure isotropization even faster
$\tau_{isotr} \approx 0.3 \,\rm fm/c$. The impact of the non-equilibrium
implied by the saturation scale manifests for non-central collisions and can
modify the estimate of the viscosity respect to the assumption of full
thermalization in $p_T$-space. We find that the estimate of $\eta/s$ is
modified from $\eta/s \approx 2/4\pi$ to $\eta/s \approx 1/4\pi$ at RHIC and
from $\eta/s \approx 3/4\pi$ to $\eta/s \approx 2/4\pi$ at LHC. We complete our
investigation by a study of the thermalization and isotropization times of the
fireball for different initial conditions and values of $\eta/s$ showing how
the latter affects both isotropization and thermalization. Lastly, we have seen
that the range of values explored by the phase-space distribution function $f$
is such that at $p_T<0.5\, \rm GeV$ the inner part of the fireball stays with
occupation number significantly larger than unity despite the fast longitudinal
expansion, which might suggest the possibility of the formation of a transient
Bose-Einstein Condensate.


title: Driving forces in researchers mobility

abstract:
  Starting from the dataset of the publication corpus of the APS during the
period 1955-2009, we reconstruct the individual researchers trajectories,
namely the list of the consecutive affiliations for each scholar. Crossing this
information with different geographic datasets we embed these trajectories in a
spatial framework. Using methods from network theory and complex systems
analysis we characterise these patterns in terms of topological network
properties and we analyse the dependence of an academic path across different
dimensions: the distance between two subsequent positions, the relative
importance of the institutions (in terms of number of publications) and some
socio-cultural traits. We show that distance is not always a good predictor for
the next affiliation while other factors like "the previous steps" of the
career of the researchers (in particular the first position) or the linguistic
and historical similarity between two countries can have an important impact.
Finally we show that the dataset exhibit a memory effect, hence the fate of a
career strongly depends from the first two affiliations.


title:
Stopping Criteria in Contrastive Divergence: Alternatives to the
  Reconstruction Error

abstract:
  Restricted Boltzmann Machines (RBMs) are general unsupervised learning
devices to ascertain generative models of data distributions. RBMs are often
trained using the Contrastive Divergence learning algorithm (CD), an
approximation to the gradient of the data log-likelihood. A simple
reconstruction error is often used to decide whether the approximation provided
by the CD algorithm is good enough, though several authors (Schulz et al.,
2010; Fischer & Igel, 2010) have raised doubts concerning the feasibility of
this procedure. However, not many alternatives to the reconstruction error have
been used in the literature. In this manuscript we investigate simple
alternatives to the reconstruction error in order to detect as soon as possible
the decrease in the log-likelihood during learning.


title:
Light curves of symbiotic stars in massive photomeric surveys II: S and
  D'-type systems

abstract:
  We present results of period analysis of ASAS, MACHO and OGLE light curves of
79 symbiotic stars classified as S and D'-type. The light curves of 58 objects
show variations with the orbital period. In case of 34 objects, orbital periods
are estimated for the first time, what increases the number of symbiotic stars
with known orbital periods by about 64 %. The light curves of 46 objects show,
in addition to the long-term or/and orbital variations, short-term variations
with time scales of 50-200 days most likely due to stellar pulsations of the
cool giant component. We also report eclipse-like minima and outbursts present
in many of the light curves.


title: Extending Construction X for Quantum Error-Correcting Codes

abstract:
  In this paper we extend the work of Lisonek and Singh on construction X for
quantum error-correcting codes to finite fields of order $p^2^ where p is
prime. The results obtained are applied to the dual of Hermitian repeated root
cyclic codes to generate new quantum error-correcting codes.


title: On summation of non-harmonic Fourier series

abstract:
  Let a sequence $\Lambda\subset\mathbb{C}$ be such that the corresponding
system of exponential functions $\mathcal{E}(\Lambda):=\{e^{i\lambda
t}\}_{\lambda\in\Lambda}$ is complete and minimal in $L^2(-\pi,\pi)$ and thus
each function $f\in L^2(-\pi,\pi)$ corresponds to a non-harmonic Fourier series
in $\mathcal{E}(\Lambda)$. We prove that if the generating function $G$ of
$\Lambda$ satisfies Muckenhoupt $(A_2)$ condition on $\mathbb{R}$, then this
series admits a linear summation method. Recent results show that $(A_2)$
condition cannot be omitted.


title: Existence of the Stark-Wannier quantum resonances

abstract:
  In this paper we prove the existence of the Stark-Wannier quantum resonances
for one-dimensional Schrodinger operators with smooth periodic potential and
small external homogeneous electric field. Such a result extends the existence
result previously obtained in the case of periodic potentials with a finite
number of open gaps.


title:
Planck and WMAP constraints on generalised Hubble flow inflationary
  trajectories

abstract:
  We use the Hamilton--Jacobi formalism to constrain the space of possible
single field, inflationary Hubble flow trajectories when compared to the WMAP
and Planck satellites Cosmic Microwave Background (CMB) results. This method
yields posteriors on the space of Hubble Slow Roll (HSR) parameters that
uniquely determine the history of the Hubble parameter during the inflating
epoch. The trajectories are used to numerically determine the observable
primordial power spectrum and bispectra that can then be compared to
observations. Our analysis is used to infer the most likely shape of the
inflaton potential $V(\phi)$ and also yields a prediction for, $f_{\rm NL}$,
the dimensionless amplitude of the non-Gaussian bispectrum.


title: Atlas of three body mean motion resonances in the Solar System

abstract:
  We present a numerical method to estimate the strengths of arbitrary three
body mean motion resonances between two planets in circular coplanar orbits and
a massless particle in an arbitrary orbit. This method allows us to obtain an
atlas of the three body resonances in the Solar System showing where are
located and how strong are thousands of resonances involving all the planets
from 0 to 1000 au. This atlas confirms the dynamical relevance of the three
body resonances involving Jupiter and Saturn in the asteroid belt but also
shows the existence of a family of relatively strong three body resonances
involving Uranus and Neptune in the far Trans-Neptunian region and relatively
strong resonances involving terrestrial and jovian planets in the inner
planetary system. We calculate the density of relevant resonances along the
Solar System resulting that the main asteroid belt is located in a region of
the planetary system with the lowest density of three body resonances. The
method also allows the location of the equilibrium points showing the existence
of asymmetric librations (sigma different from 0 or 180 degrees). We obtain the
functional dependence of the resonance's strength with the order of the
resonance and the eccentricity and inclination of the particle's orbit. We
identify some objects evolving in or very close to three body resonances with
Earth-Jupiter, Saturn-Neptune and Uranus-Neptune apart from Jupiter-Saturn, in
particular the NEA 2009 SJ18 is evolving in the resonance 1-1E-1J and the
centaur 10199 Chariklo is evolving under the influence of the resonance
5-2S-2N.


title:
A fractional Brownian field indexed by $L^2$ and a varying Hurst
  parameter

abstract:
  Using structures of Abstract Wiener Spaces, we define a fractional Brownian
field indexed by a product space $(0,1/2] \times L^2(T,m)$, $(T,m)$ a separable
measure space, where the first coordinate corresponds to the Hurst parameter of
fractional Brownian motion. This field encompasses a large class of existing
fractional Brownian processes, such as L\'evy fractional Brownian motions and
multiparameter fractional Brownian motions, and provides a setup for new ones.
We prove that it has satisfactory incremental variance in both coordinates and
derive certain continuity and H\"older regularity properties in relation with
metric entropy. Also, a sharp estimate of the small ball probabilities is
provided, generalizing a result on L\'evy fractional Brownian motion. Then, we
apply these general results to multiparameter and set-indexed processes,
proving the existence of processes with prescribed local H\"older regularity on
general indexing collections.


title:
Resolving Structure in Human Brain Organization: Identifying Mesoscale
  Organization in Weighted Network Representations

abstract:
  Human brain anatomy and function display a combination of modular and
hierarchical organization, suggesting the importance of both cohesive
structures and variable resolutions in the facilitation of healthy cognitive
processes. However, tools to simultaneously probe these features of brain
architecture require further development. We propose and apply a set of methods
to extract cohesive structures in network representations of brain connectivity
using multi-resolution techniques. We employ a combination of soft
thresholding, windowed thresholding, and resolution in community detection,
that enable us to identify and isolate structures associated with different
weights. One such mesoscale structure is bipartivity, which quantifies the
extent to which the brain is divided into two partitions with high connectivity
between partitions and low connectivity within partitions. A second,
complementary mesoscale structure is modularity, which quantifies the extent to
which the brain is divided into multiple communities with strong connectivity
within each community and weak connectivity between communities. Our methods
lead to multi-resolution curves of these network diagnostics over a range of
spatial, geometric, and structural scales. For statistical comparison, we
contrast our results with those obtained for several benchmark null models. Our
work demonstrates that multi-resolution diagnostic curves capture complex
organizational profiles in weighted graphs. We apply these methods to the
identification of resolution-specific characteristics of healthy weighted graph
architecture and altered connectivity profiles in psychiatric disease.


title: A Radio Survey of Galactic Center Clouds

abstract:
  We present a survey of molecules in a sample of Galactic center molecular
clouds using the Karl G. Jansky Very large Array, which includes M0.25+0.01,
the clouds near Sgr A, and Sgr B2. The molecules detected are primarily NH3 and
HC3N; in Sgr B2-N we also detect nonmetastable NH3, vibrationally-excited HC3N,
torsionally-excited CH3OH, and numerous isotopologues of these species. 36 GHz
Class I CH3OH masers are ubiquitous in these fields, and in several cases are
associated with new NH3 (3,3) maser candidates. We also find that NH3 and HC3N
are depleted or absent toward several of the highest dust column density peaks
identified in submillimeter observations, which are associated with water
masers and are thus likely in the early stages of star formation.


title:
Operation of an optically coherent frequency comb outside the metrology
  lab

abstract:
  We demonstrate a self-referenced fiber frequency comb that can operate
outside the well-controlled optical laboratory. The frequency comb has residual
optical linewidths of < 1 Hz, sub-radian residual optical phase noise, and
residual pulse-to-pulse timing jitter of 2.4 - 5 fs, when locked to an optical
reference. This fully phase-locked frequency comb has been successfully
operated in a moving vehicle with 0.5 g peak accelerations and on a shaker
table with a sustained 0.5 g rms integrated acceleration, while retaining its
optical coherence and 5-fs-level timing jitter. This frequency comb should
enable metrological measurements outside the laboratory with the precision and
accuracy that are the hallmarks of comb-based systems. Work of the U.S.
government, not subject to copyright


title: Beables/Observables in Classical and Quantum Gravity

abstract:
  Observables 'are observed' whereas beables just 'are'. This gives beables
more scope in the cosmological and quantum domains. Both observables and
beables are entities that form 'brackets' with 'the constraints' that are
'equal to' zero. We explain how depending on circumstances, these could be,
e.g., Poisson, Dirac, commutator, histories, Schouten-Nijenhuis, double or
Nambu brackets, first-class, gauge, linear or effective constraints, and
strong, weak or weak-effective equalities. The Dirac-Bergmann distinction in
notions of gauge leads to further notions of observables or beables, and is
tied to a number of diffeomorphism-specific subtleties. Thus we cover a wide
range of notions of observables or beables that occur in classical and quantum
gravitational theories: Dirac, Kucha\v{r}, effective, Bergmann, histories,
multisymplectic, master, Nambu and bi-. Indeed this review covers a
representatively wide range of such theories: general relativity, loop quantum
gravity, histories theory, supergravity and M-theory.


title:
Single-Field Consistency Relations of Large Scale Structure. Part III:
  Test of the Equivalence Principle

abstract:
  The recently derived consistency relations for Large Scale Structure do not
hold if the Equivalence Principle (EP) is violated. We show it explicitly in a
toy model with two fluids, one of which is coupled to a fifth force. We explore
the constraints that galaxy surveys can set on EP violation looking at the
squeezed limit of the 3-point function involving two populations of objects. We
find that one can explore EP violations of order 10^{-3} - 10^{-4} on
cosmological scales. Chameleon models are already very constrained by the
requirement of screening within the Solar System and only a very tiny region of
the parameter space can be explored with this method. We show that no violation
of the consistency relations is expected in Galileon models.


title: Quantum graph vertices with minimal number of passbands

abstract:
  We study a set of scattering matrices of quantum graphs containing minimal
number of passbands, i.e., maximal number of zero elements. The cases of even
and odd vertex degree are considered. Using a solution of inverse scattering
problem, we reconstruct boundary conditions of scale-invariant vertex
couplings. Potential-controlled universal flat filtering properties are found
for considered types of vertex couplings. Obtained boundary conditions are
approximated by simple graphs carrying only $\delta$ potentials and inner
magnetic field.


title:
Fractional porous media equations: existence and uniqueness of weak
  solutions with measure data

abstract:
  We prove existence and uniqueness of solutions to a class of porous media
equations driven by the fractional Laplacian when the initial data are positive
finite Radon measures on the Euclidean space. For given solutions without a
prescribed initial condition, the problem of existence and uniqueness of the
initial trace is also addressed. By the same methods we can also treat weighted
fractional porous media equations, with a weight that can be singular at the
origin, and must have a sufficiently slow decay at infinity (power-like). In
particular, we show that the Barenblatt-type solutions exist and are unique.
Such a result has a crucial role in [24], where the asymptotic behavior of
solutions is investigated. Our uniqueness result solves a problem left open,
even in the non-weighted case, in [42]


title: Efficient Visual Coding: From Retina To V2

abstract:
  The human visual system has a hierarchical structure consisting of layers of
processing, such as the retina, V1, V2, etc. Understanding the functional roles
of these visual processing layers would help to integrate the
psychophysiological and neurophysiological models into a consistent theory of
human vision, and would also provide insights to computer vision research. One
classical theory of the early visual pathway hypothesizes that it serves to
capture the statistical structure of the visual inputs by efficiently coding
the visual information in its outputs. Until recently, most computational
models following this theory have focused upon explaining the receptive field
properties of one or two visual layers. Recent work in deep networks has
eliminated this concern, however, there is till the retinal layer to consider.
Here we improve on a previously-described hierarchical model Recursive ICA
(RICA) [1] which starts with PCA, followed by a layer of sparse coding or ICA,
followed by a component-wise nonlinearity derived from considerations of the
variable distributions expected by ICA. This process is then repeated. In this
work, we improve on this model by using a new version of sparse PCA (sPCA),
which results in biologically-plausible receptive fields for both the sPCA and
ICA/sparse coding. When applied to natural image patches, our model learns
visual features exhibiting the receptive field properties of retinal ganglion
cells/lateral geniculate nucleus (LGN) cells, V1 simple cells, V1 complex
cells, and V2 cells. Our work provides predictions for experimental
neuroscience studies. For example, our result suggests that a previous
neurophysiological study improperly discarded some of their recorded neurons;
we predict that their discarded neurons capture the shape contour of objects.


title: Higgs branch localization in three dimensions

abstract:
  We show that the supersymmetric partition function of three-dimensional N=2
R-symmetric Chern-Simons-matter theories on the squashed S^3 and on S^2 x S^1
can be computed with the so-called Higgs branch localization method,
alternative to the more standard Coulomb branch localization. For theories that
could be completely Higgsed by Fayet-Iliopoulos terms, the path integral is
dominated by BPS vortex strings sitting at two circles in the geometry. In this
way, the partition function directly takes the form of a sum, over a finite
number of points on the classical Coulomb branch, of a vortex-string times an
antivortex-string partition functions.


title:
An Improved Outer Bound on the Storage-Repair-Bandwidth Tradeoff of
  Exact-Repair Regenerating Codes

abstract:
  In this paper we establish an improved outer bound on the
storage-repair-bandwidth tradeoff of regenerating codes under exact repair. The
result shows that in particular, it is not possible to construct exact-repair
regenerating codes that asymptotically achieve the tradeoff that holds for
functional repair. While this had been shown earlier by Tian for the special
case of $[n,k,d]=[4,3,3]$ the present result holds for general $[n,k,d]$. The
new outer bound is obtained by building on the framework established earlier by
Shah et al.


title:
Analysis of the Evolution of Hydrodynamic Instability at the Interface
  of Active and Passive Media

abstract:
  The evolution of an instability at the interface of active and passive media
is considered. An asymptotic form of a collision integral is found and the
limitations of hydrodynamic approach are determined. A growth increment of
small perturbations of the interface is found using the potential flows theory.
The obtained results were applied to estimation of the instability contribution
to the development of some known physical processes.


title:
A note on condensations of function spaces onto $\sigma$-compact and
  analytic spaces

abstract:
  Modifying a construction of W. Marciszewski we prove (in ZFC) that there
exists a subspace of the real line $\mathbb{R}$, such that the realcompact
space $C_p(X)$ of continuous real-valued functions on $X$ with the pointwise
convergence topology does not admit a continuous bijection onto a
$\sigma$-compact space. This answers a question of Arhangel'skii.


title:
Multi-digit Number Recognition from Street View Imagery using Deep
  Convolutional Neural Networks

abstract:
  Recognizing arbitrary multi-character text in unconstrained natural
photographs is a hard problem. In this paper, we address an equally hard
sub-problem in this domain viz. recognizing arbitrary multi-digit numbers from
Street View imagery. Traditional approaches to solve this problem typically
separate out the localization, segmentation, and recognition steps. In this
paper we propose a unified approach that integrates these three steps via the
use of a deep convolutional neural network that operates directly on the image
pixels. We employ the DistBelief implementation of deep neural networks in
order to train large, distributed neural networks on high quality images. We
find that the performance of this approach increases with the depth of the
convolutional network, with the best performance occurring in the deepest
architecture we trained, with eleven hidden layers. We evaluate this approach
on the publicly available SVHN dataset and achieve over $96\%$ accuracy in
recognizing complete street numbers. We show that on a per-digit recognition
task, we improve upon the state-of-the-art, achieving $97.84\%$ accuracy. We
also evaluate this approach on an even more challenging dataset generated from
Street View imagery containing several tens of millions of street number
annotations and achieve over $90\%$ accuracy. To further explore the
applicability of the proposed system to broader text recognition tasks, we
apply it to synthetic distorted text from reCAPTCHA. reCAPTCHA is one of the
most secure reverse turing tests that uses distorted text to distinguish humans
from bots. We report a $99.8\%$ accuracy on the hardest category of reCAPTCHA.
Our evaluations on both tasks indicate that at specific operating thresholds,
the performance of the proposed system is comparable to, and in some cases
exceeds, that of human operators.


title:
Deformation Patterns and Surface Morphology in a Minimal Model of
  Amorphous Plasticity

abstract:
  We investigate a minimal model of the plastic deformation of amorphous
materials. The material elements are assumed to exhibit ideally plastic
behavior (J2 plasticity). Structural disorder is considered in terms of random
variations of the local yield stresses. Using a finite element implementation
of this simple model, we simulate the plane-strain deformation of long thin
rods loaded in tension. The resulting strain patterns are statistically
characterized in terms of their spatial correlation functions. Studies of the
corresponding surface morphology reveal a non-trivial Hurst exponent of approx.
0.8, indicating the presence of long range correlations in the deformation
patterns. The simulated deformation patterns and surface morphology exhibit
persistent features which emerge already at the very onset of plastic
deformation, while subsequent evolution is characterized by growth in amplitude
without major morphology changes. The findings are compared to experimental
observations.


title: Current amplification and relaxation in Dirac systems

abstract:
  We study how electron-electron (e-e) interactions affect the current carried
by excited electrons and holes in Dirac systems such as graphene or topological
insulators. We find that the current shows distinctly different behavior for
e-e collisions involving the electron or the hole. Most surprisingly, for
positive Fermi energy, collisions of the electrons can substantially increase
the current. This remarkable amplification of the current can be of the order
of $\sim 10\%$ per scattering event. It also causes a strong suppression of the
overall current relaxation rate of a photoexcited electron-hole pair, with the
amplification of the electron current making up for a fast decay of the hole
current.


title: Nematic order in iron superconductors - who is in the driver's seat?

abstract:
  Although the existence of nematic order in iron-based superconductors is now
a well-established experimental fact, its origin remains controversial. Nematic
order breaks the discrete lattice rotational symmetry by making the $x$ and $y$
directions in the Fe plane non-equivalent. This can happen because of (i) a
tetragonal to orthorhombic structural transition, (ii) a spontaneous breaking
of an orbital symmetry, or (iii) a spontaneous development of an Ising-type
spin-nematic order - a magnetic state that breaks rotational symmetry but
preserves time-reversal symmetry. The Landau theory of phase transitions
dictates that the development of one of these orders should immediately induce
the other two, making the origin of nematicity a physics realization of a
"chicken and egg problem". The three scenarios are, however, quite different
from a microscopic perspective. While in the structural scenario lattice
vibrations (phonons) play the dominant role, in the other two scenarios
electronic correlations are responsible for the nematic order. In this review,
we argue that experimental and theoretical evidence strongly points to the
electronic rather than phononic mechanism, placing the nematic order in the
class of correlation-driven electronic instabilities, like superconductivity
and density-wave transitions. We discuss different microscopic models for
nematicity in the iron pnictides, and link nematicity to other ordered states
of the global phase diagram of these materials -- magnetism and
superconductivity. In the magnetic model nematic order pre-empts stripe-type
magnetic order, and the same interaction which favors nematicity also gives
rise to an unconventional $s^{+-}$ superconductivity. In the charge/orbital
model magnetism appears as a secondary effect of ferro-orbital order, and the
interaction which favors nematicity gives rise to a conventional $s^{++}$
superconductivity.


title: The return of AdaBoost.MH: multi-class Hamming trees

abstract:
  Within the framework of AdaBoost.MH, we propose to train vector-valued
decision trees to optimize the multi-class edge without reducing the
multi-class problem to $K$ binary one-against-all classifications. The key
element of the method is a vector-valued decision stump, factorized into an
input-independent vector of length $K$ and label-independent scalar classifier.
At inner tree nodes, the label-dependent vector is discarded and the binary
classifier can be used for partitioning the input space into two regions. The
algorithm retains the conceptual elegance, power, and computational efficiency
of binary AdaBoost. In experiments it is on par with support vector machines
and with the best existing multi-class boosting algorithm AOSOLogitBoost, and
it is significantly better than other known implementations of AdaBoost.MH.


title:
Higher index focus-focus singularities in the Jayne-Cummings-Gaudin
  model : symplectic invariants and monodromy

abstract:
  We study the symplectic geometry of the Jaynes-Cummings-Gaudin model with
$n=2m-1$ spins. We show that there are focus-focus singularities of maximal
Williamson type $(0,0,m)$. We construct the linearized normal flows in the
vicinity of such a point and show that soliton type solutions extend them
globally on the critical torus. This allows us to compute the leading term in
the Taylor expansion of the symplectic invariants and the monodromy associated
to this singularity.


title:
Nonlinear vs. bolometric radiation response and phonon thermal
  conductance in graphene-superconductor junctions

abstract:
  Graphene is a promising candidate for building fast and ultra-sensitive
bolometric detectors due to its weak electron-phonon coupling and low heat
capacity. In order to realize a practical graphene-based bolometer, several
important issues, including the nature of radiation response, coupling
efficiency to the radiation and the thermal conductance need to be carefully
studied. Addressing these issues, we present graphene-superconductor junctions
as a viable option to achieve efficient and sensitive bolometers, with the
superconductor contacts serving as hot electron barriers. For a
graphene-superconductor device with highly transparent interfaces, the
resistance readout in the presence of radio frequency radiation is dominated by
non-linear response. On the other hand, a graphene-superconductor tunnel device
shows dominantly bolometric response to radiation. For graphene devices
fabricated on $SiO_{2}$ substrates, we confirm recent theoretical predictions
of $T^{2}$ temperature dependence of phonon thermal conductance in the presence
of disorder in the graphene channel at low temperatures.


title: Integral criteria for Strong Renewal Theorems with infinite mean

abstract:
  Let $F$ be a probability measure on $\mathbb{R}$ in the domain of attraction
of a stable law with exponent $\alpha\in (0, 1)$. We establish integral
criteria on $F$ that significantly expand the probabilistic approach to Strong
Renewal Theorems (SRTs). The criterion for $\alpha \in (0,1/2]$ is much weaker
than currently available ones and in some cases provides sufficient and
necessary conditions for the SRT. The criterion for $\alpha \in (1/2, 1)$
establishes the SRT in full generality and in a unified way, barring the Limit
Local Theorems employed. As an application, for infinitely divisible $F$, an
integral criterion on its L\'evy measure is established for the SRT. As another
application, for $F$ in the domain of attraction of a stable law without
centering, an integral criterion on $F$ is established for the SRT for the
ladder height process of a random walk with step distribution $F$.


title: Graph-based representation for multiview image coding

abstract:
  In this paper, we propose a new representation for multiview image sets. Our
approach relies on graphs to describe geometry information in a compact and
controllable way. The links of the graph connect pixels in different images and
describe the proximity between pixels in the 3D space. These connections are
dependent on the geometry of the scene and provide the right amount of
information that is necessary for coding and reconstructing multiple views.
This multiview image representation is very compact and adapts the transmitted
geometry information as a function of the complexity of the prediction
performed at the decoder side. To achieve this, our GBR adapts the accuracy of
the geometry representation, in contrast with depth coding, which directly
compresses with losses the original geometry signal. We present the principles
of this graph-based representation (GBR) and we build a complete prototype
coding scheme for multiview images. Experimental results demonstrate the
potential of this new representation as compared to a depth-based approach. GBR
can achieve a gain of 2 dB in reconstructed quality over depth-based schemes
operating at similar rates.


title:
Spin-orbit coupling and weak antilocalization in thermoelectric material
  $\beta$-K$_{2}$Bi$_{8}$Se$_{13}$

abstract:
  We have studied the effect of spin-orbital coupling (SOC) on electronic
transport properties of the thermoelectric material
$\beta$-K$_{2}$Bi$_{8}$Se$_{13}$ via magnetoresistance (MR) measurements. We
found that the strong SOC in this material results in weak antilocalization
(WAL) effect, which can be well described by the three-dimensional weak
localization model. The phase coherence length extracted from theoretical
fitting exhibits a power-law temperature dependence with an exponent around
2.1, indicating that the electron phase dephasing is governed by electron -
transverse phonon interactions. Like in topological insulators, the WAL effect
in $\beta$-K$_{2}$Bi$_{8}$Se$_{13}$ can be quenched by magnetic impurities (Mn)
but is robust against non-magnetic impurities (Te). Although our
magnetotransport studies do not provide any evidences for topological surface
states, our analyses suggest that SOC plays an important role in determining
thermoelectric properties of $\beta$-K$_{2}$Bi$_{8}$Se$_{13}$.


title:
A Simple and Efficient Preconditioning Scheme for Heaviside Enriched
  XFEM

abstract:
  The eXtended Finite Element Method (XFEM) is an approach for solving problems
with non-smooth solutions. In the XFEM, the approximate solution is locally
enriched to capture discontinuities without requiring a mesh which conforms to
the geometric features. One drawback of the XFEM is that an ill-conditioned
system of equations results when the ratio of volumes on either side of the
interface in an element is small. In this paper, to avoid this
ill-conditioning, a simple and efficient scheme based on a geometric
preconditioner and constraining degrees of freedom to zero for small
intersections is proposed. This geometric preconditioner is computed from the
nodal basis functions, and therefore may be constructed prior to building the
system of equations. This feature and the low-cost of constructing the
preconditioning matrix makes it well suited for nonlinear problems with fixed
and moving interfaces.


title: Distributional transformations without orthogonality relations

abstract:
  Distributional transformations characterized by equations relating
expectations of test functions weighted by a given biasing function on the
original distribution to expectations of the test function's higher derivatives
with respect to the transformed distribution play a great role in Stein's
method and were, in great generality, first considered by Goldstein and Reinert
\cite{GolRei05b}. We prove two abstract existence and uniqueness results for
such distributional transformations, generalizing their $X-P$ bias
transformation. On the one hand, we show how one can abandon previously
necessary orthogonality relations by subtracting an explicitly known polynomial
depending on the test function from the test function itself. On the other
hand, we prove that for a given nonnegative integer $m$ it is possible to
obtain the expectation of the $m$-th derivative of the test function with
respect to the transformed distribution in the defining equation, even though
the biasing function may have $k<m$ sign changes, if these two numbers have the
same parity. We explain, how these results can be used to guarantee the
existence of two different generalizations of the zero bias transformation by
Goldstein and Reinert \cite{GolRei97}. Further applications include the
derivation of Stein type characterizations without needing to solve any Stein
equation and the presentation of a general framework of estimating the distance
of the distribution of a given real random variable $X$ to that of a random
variable $Z$, whose distribution is characterized by some $m$-th order linear
differential operator. We also explain the fact that, in general, the biased
distribution depends on the choice of the sign change points, if these are
ambiguous. This new phenomenon does not appear in the framework from
\cite{GolRei05b}.


title:
Energy Efficient Control of an Induction Machine under Load Torque Step
  Change

abstract:
  Optimal control of magnetizing current for minimizing induction motor power
losses during load torque step change was developed. Obtained strategy has
feedback form and is exactly optimal of ideal speed controller performance and
absence of saturation in motor. The impact of limited bandwidth of real speed
controller is analyzed. For case of main induction saturation the sub-optimal
optimal control is suggested. Relative accuracy of sub-optimality is studied.
Hardware implementation of optimal strategy and experimentation conducted with
induction motors under vector control.


title: Multi-View Priors for Learning Detectors from Sparse Viewpoint Data

abstract:
  While the majority of today's object class models provide only 2D bounding
boxes, far richer output hypotheses are desirable including viewpoint,
fine-grained category, and 3D geometry estimate. However, models trained to
provide richer output require larger amounts of training data, preferably well
covering the relevant aspects such as viewpoint and fine-grained categories. In
this paper, we address this issue from the perspective of transfer learning,
and design an object class model that explicitly leverages correlations between
visual features. Specifically, our model represents prior distributions over
permissible multi-view detectors in a parametric way -- the priors are learned
once from training data of a source object class, and can later be used to
facilitate the learning of a detector for a target class. As we show in our
experiments, this transfer is not only beneficial for detectors based on
basic-level category representations, but also enables the robust learning of
detectors that represent classes at finer levels of granularity, where training
data is typically even scarcer and more unbalanced. As a result, we report
largely improved performance in simultaneous 2D object localization and
viewpoint estimation on a recent dataset of challenging street scenes.


title: Properties of Answer Set Programming with Convex Generalized Atoms

abstract:
  In recent years, Answer Set Programming (ASP), logic programming under the
stable model or answer set semantics, has seen several extensions by
generalizing the notion of an atom in these programs: be it aggregate atoms,
HEX atoms, generalized quantifiers, or abstract constraints, the idea is to
have more complicated satisfaction patterns in the lattice of Herbrand
interpretations than traditional, simple atoms. In this paper we refer to any
of these constructs as generalized atoms. Several semantics with differing
characteristics have been proposed for these extensions, rendering the big
picture somewhat blurry. In this paper, we analyze the class of programs that
have convex generalized atoms (originally proposed by Liu and Truszczynski in
[10]) in rule bodies and show that for this class many of the proposed
semantics coincide. This is an interesting result, since recently it has been
shown that this class is the precise complexity boundary for the FLP semantics.
We investigate whether similar results also hold for other semantics, and
discuss the implications of our findings.


title: Compact homogeneous Riemannian manifolds with low co-index of symmetry

abstract:
  We develop a general structure theory for compact homogeneous Riemannian
manifolds in relation to the co-index of symmetry. We will then use these
results to classify irreducible, simply connected, compact homogeneous
Riemannian manifolds whose co-index of symmetry is less or equal than three. We
will also construct many examples which arise from the theory of polars and
centrioles in Riemannian symmetric spaces of compact type.


title:
On the number of response regions of deep feed forward networks with
  piece-wise linear activations

abstract:
  This paper explores the complexity of deep feedforward networks with linear
pre-synaptic couplings and rectified linear activations. This is a contribution
to the growing body of work contrasting the representational power of deep and
shallow network architectures. In particular, we offer a framework for
comparing deep and shallow models that belong to the family of piecewise linear
functions based on computational geometry. We look at a deep rectifier
multi-layer perceptron (MLP) with linear outputs units and compare it with a
single layer version of the model. In the asymptotic regime, when the number of
inputs stays constant, if the shallow model has $kn$ hidden units and $n_0$
inputs, then the number of linear regions is $O(k^{n_0}n^{n_0})$. For a $k$
layer model with $n$ hidden units on each layer it is $\Omega(\left\lfloor
{n}/{n_0}\right\rfloor^{k-1}n^{n_0})$. The number
$\left\lfloor{n}/{n_0}\right\rfloor^{k-1}$ grows faster than $k^{n_0}$ when $n$
tends to infinity or when $k$ tends to infinity and $n \geq 2n_0$.
Additionally, even when $k$ is small, if we restrict $n$ to be $2n_0$, we can
show that a deep model has considerably more linear regions that a shallow one.
We consider this as a first step towards understanding the complexity of these
models and specifically towards providing suitable mathematical tools for
future analysis.


title: Stability Boundaries for Resonant Migrating Planet Pairs

abstract:
  Convergent migration allows pairs of planet to become trapped into mean
motion resonances. Once in resonance, the planets' eccentricities grow to an
equilibrium value that depends on the ratio of migration time scale to the
eccentricity damping timescale, $K=\tau_a/\tau_e$, with higher values of
equilibrium eccentricity for lower values of $K$. For low equilibrium
eccentricities, $e_{eq}\propto K^{-1/2}$. The stability of a planet pair
depends on eccentricity so the system can become unstable before it reaches its
equilibrium eccentricity. Using a resonant overlap criterion that takes into
account the role of first and second order resonances and depends on
eccentricity, we find a function $K_{min}(\mu_p, j)$ that defines the lowest
value for $K$, as a function of the ratio of total planet mass to stellar mass
($\mu_p$) and the period ratio of the resonance defined as $P_1/P_2=j/(j+k)$,
that allows two convergently migrating planets to remain stable in resonance at
their equilibrium eccentricities. We scaled the functions $K_{min}$ for each
resonance of the same order into a single function $K_c$. The function $K_{c}$
for planet pairs in first order resonances is linear with increasing planet
mass and quadratic for pairs in second order resonances with a coefficient
depending on the relative migration rate and strongly on the planet to planet
mass ratio. The linear relation continues until the mass approaches a critical
mass defined by the 2/7 resonance overlap instability law and $K_c \to \infty$.
We compared our analytic boundary with an observed sample of resonant two
planet systems. All but one of the first order resonant planet pair systems
found by radial velocity measurements are well inside the stability region
estimated by this model. We calculated $K_c$ for Kepler systems without
well-constrained eccentricities and found only weak constraints on $K$.


title: Shape variation of micelles in polymer thin films

abstract:
  The equilibrium properties of block copolymer micelles confined in polymer
thin films are investigated using self-consistent field theory. The theory is
based on a model system consisting of AB diblock copolymers and A homopolymers.
Two different methods, based on the radius of gyration tensor and the spherical
harmonics expansion, are used to characterize the micellar shape. The results
reveal that the morphology of micelles in thin films depends on the thickness
of the thin films and the selectivity of the confining surfaces. For spherical
(cylindrical) micelles, the spherical (cylindrical) symmetry is broken by the
presence of the one-dimensional confinement, whereas the top-down symmetry is
broken by the selectivity of the confining surfaces. Morphological transitions
from spherical or cylindrical micelles to cylinders or lamella are predicted
when the film thickness approaches the micellar size.


title: Concatenated Raptor Codes in NAND Flash Memory

abstract:
  Two concatenated coding schemes based on fixed-rate Raptor codes are proposed
for error control in NAND flash memory. One is geared for off-line recovery of
uncorrectable pages and the other is designed for page error correction during
the normal read mode. Both proposed coding strategies assume hard-decision
decoding of the inner code with inner decoding failure generating erasure
symbols for the outer Raptor code. Raptor codes allow low-complexity decoding
of very long codewords while providing capacity- approaching performance for
erasure channels. For the off-line page recovery scheme, one whole NAND block
forms a Raptor codeword with each inner codeword typically made up of several
Raptor symbols. An efficient look-up-table strategy is devised for Raptor
encoding and decoding which avoids using large buffers in the controller
despite the substantial size of the Raptor code employed. The potential
performance benefit of the proposed scheme is evaluated in terms of the
probability of block recovery conditioned on the presence of uncorrectable
pages. In the suggested page-error-correction strategy, on the other hand, a
hard-decision-iterating product code is used as the inner code. The specific
product code employed in this work is based on row-column concatenation with
multiple intersecting bits allowing the use of longer component codes. In this
setting the collection of bits captured within each intersection of the
row-column codes acts as the Raptor symbol(s), and the intersections of failed
row codes and column codes are declared as erasures. The error rate analysis
indicates that the proposed concatenation provides a considerable performance
boost relative to the existing error correcting system based on long
Bose-Chaudhuri-Hocquenghem (BCH) codes.


title:
Asymptotically Efficient Estimation of Weighted Average Derivatives with
  an Interval Censored Variable

abstract:
  This paper studies the identification and estimation of weighted average
derivatives of conditional location functionals including conditional mean and
conditional quantiles in settings where either the outcome variable or a
regressor is interval-valued. Building on Manski and Tamer (2002) who study
nonparametric bounds for mean regression with interval data, we characterize
the identified set of weighted average derivatives of regression functions.
Since the weighted average derivatives do not rely on parametric specifications
for the regression functions, the identified set is well-defined without any
parametric assumptions. Under general conditions, the identified set is compact
and convex and hence admits characterization by its support function. Using
this characterization, we derive the semiparametric efficiency bound of the
support function when the outcome variable is interval-valued. We illustrate
efficient estimation by constructing an efficient estimator of the support
function for the case of mean regression with an interval censored outcome.


title: A Dundas-McCarthy theorem for bimodules over exact categories

abstract:
  From a bimodule $M$ over an exact category $C$, we define an exact category
$C\ltimes M$ with a projection down to $C$. This construction classifies
certain split square zero extensions of exact categories. We show that the
trace map induces an equivalence between the relative $K$-theory of $C\ltimes
M$ and its relative topological cyclic homology. When applied to the bimodule
$\hom(-,-\otimes_AM)$ on the category of finitely generated projective modules
over a ring $A$ one recovers the classical Dundas-McCarthy theorem for split
square zero extensions of rings.


title: Imaginary Schur-Weyl duality

abstract:
  We study imaginary representations of the Khovanov-Lauda-Rouquier algebras of
affine Lie type. Irreducible modules for such algebras arise as simple heads of
standard modules. In order to define standard modules one needs to have a
cuspidal system for a fixed convex preorder. A cuspidal system consists of
irreducible cuspidal modules---one for each real positive root for the
corresponding affine root system ${\tt X}_l^{(1)}$, as well as irreducible
imaginary modules---one for each $l$-multipartition. We study imaginary modules
by means of `imaginary Schur-Weyl duality'. We introduce an imaginary analogue
of tensor space and the imaginary Schur algebra. We construct a projective
generator for the imaginary Schur algebra, which yields a Morita equivalence
between the imaginary and the classical Schur algebra. We construct imaginary
analogues of Gelfand-Graev representations, Ringel duality and the Jacobi-Trudy
formula.


title:
Hybrid Automated Reasoning Tools: from Black-box to Clear-box
  Integration

abstract:
  Recently, researchers in answer set programming and constraint programming
spent significant efforts in the development of hybrid languages and solving
algorithms combining the strengths of these traditionally separate fields.
These efforts resulted in a new research area: constraint answer set
programming (CASP). CASP languages and systems proved to be largely successful
at providing efficient solutions to problems involving hybrid reasoning tasks,
such as scheduling problems with elements of planning. Yet, the development of
CASP systems is difficult, requiring non-trivial expertise in multiple areas.
This suggests a need for a study identifying general development principles of
hybrid systems. Once these principles and their implications are well
understood, the development of hybrid languages and systems may become a
well-established and well-understood routine process. As a step in this
direction, in this paper we conduct a case study aimed at evaluating various
integration schemas of CASP methods.


title: Observational constraints on the types of cosmic strings

abstract:
  This paper is aimed at setting observational limits to the number of cosmic
strings (Nambu-Goto, Abelian-Higgs, semilocal) and other topological defects
(textures). Radio maps of CMB anisotropy, provided by the space mission Planck
for various frequencies, were filtered and then processed by the method of
convolution with modified Haar functions (MHF) to search for cosmic string
candidates. This method was designed to search for solitary strings, without
additional assumptions about the presence of networks of such objects. The
sensitivity of the MHF method is $\delta T \approx 10 \mu K$ in a background of
$\delta T \approx 100 \mu K$. The comparison of these with previously known
results on search string network shows that strings can only be semilocal in an
amount of $1 \div 5$, with the upper restriction on individual strings tension
(linear density) of $G\mu/c^2 \le 7.36 \cdot 10^{-7}$. The texture model is
also legal. There are no strings with $G\mu/c^2 > 7.36 \cdot 10^{-7}$. However,
comparison with the data for the search of non-Gaussian signals shows that the
presence of several (up to 3) of Nambu-Goto strings is also possible. For
$G\mu/c^2 \le 4.83 \cdot 10^{-7}$ the MHF method is ineffective because of
unverifiable spurious string candidates. Thus the existence of strings with
tensions $G\mu/c^2 \le 4.83 \cdot 10^{-7}$ is not prohibited but it is beyond
the Planck data possibilities.


title: Spectroscopy for a Few Atoms Harmonically-Trapped in One Dimension

abstract:
  Spectroscopic labels for a few particles with spin that are harmonically
trapped in one-dimension with effectively zero-range interactions are provided
by quantum numbers that characterize the symmetries of the Hamiltonian:
permutations of identical particles, parity inversion, and the separability of
the center-of-mass. The exact solutions for the non-interacting and infinitely
repulsive cases are reduced with respect to these symmetries. This reduction
explains how states of single-component and multi-component fermions and bosons
transform under adiabatic evolution from non-interacting to strong hard-core
repulsion. These spectroscopic methods also clarify previous analytic and
numerical results for intermediate values of interaction strength. Several
examples, including adiabatic mapping for two-component fermionic states in the
cases $N=3-5$, are provided.

categories: quant-ph cond-mat.quant-gas math-ph math.MP


title:
Modeling correlations in spontaneous activity of visual cortex with
  centered Gaussian-binary deep Boltzmann machines

abstract:
  Spontaneous cortical activity -- the ongoing cortical activities in absence
of intentional sensory input -- is considered to play a vital role in many
aspects of both normal brain functions and mental dysfunctions. We present a
centered Gaussian-binary Deep Boltzmann Machine (GDBM) for modeling the
activity in early cortical visual areas and relate the random sampling in GDBMs
to the spontaneous cortical activity. After training the proposed model on
natural image patches, we show that the samples collected from the model's
probability distribution encompass similar activity patterns as found in the
spontaneous activity. Specifically, filters having the same orientation
preference tend to be active together during random sampling. Our work
demonstrates the centered GDBM is a meaningful model approach for basic
receptive field properties and the emergence of spontaneous activity patterns
in early cortical visual areas. Besides, we show empirically that centered
GDBMs do not suffer from the difficulties during training as GDBMs do and can
be properly trained without the layer-wise pretraining.


title:
A first-principles approach to nonlinear lattice dynamics: Anomalous
  spectra in PbTe

abstract:
  Here we introduce a new approach to compute the finite temperature lattice
dynamics from first-principles via the newly developed slave mode expansion. We
study PbTe where inelastic neutron scattering (INS) reveals strong signatures
of nonlinearity as evidenced by anomalous features which emerge in the phonon
spectra at finite temperature. Using our slave mode expansion in the classical
limit, we compute the vibrational spectra and show remarkable agreement with
temperature dependent INS measurements. Furthermore, we resolve experimental
controversy by showing that there are no appreciable local nor global
spontaneously broken symmetries at finite temperature and that the anomalous
spectral features simply arise from two anharmonic interactions. Our approach
should be broadly applicable across the periodic table.


title: Learning Generative Models with Visual Attention

abstract:
  Attention has long been proposed by psychologists as important for
effectively dealing with the enormous sensory stimulus available in the
neocortex. Inspired by the visual attention models in computational
neuroscience and the need of object-centric data for generative models, we
describe for generative learning framework using attentional mechanisms.
Attentional mechanisms can propagate signals from region of interest in a scene
to an aligned canonical representation, where generative modeling takes place.
By ignoring background clutter, generative models can concentrate their
resources on the object of interest. Our model is a proper graphical model
where the 2D Similarity transformation is a part of the top-down process. A
ConvNet is employed to provide good initializations during posterior inference
which is based on Hamiltonian Monte Carlo. Upon learning images of faces, our
model can robustly attend to face regions of novel test subjects. More
importantly, our model can learn generative models of new faces from a novel
dataset of large images where the face locations are not known.


title:
Phenomenology of dark energy: exploring the space of theories with
  future redshift surveys

abstract:
  We use the effective field theory of dark energy to explore the space of
modified gravity models which are capable of driving the present cosmic
acceleration. We identify five universal functions of cosmic time that are
enough to describe a wide range of theories containing a single scalar degree
of freedom in addition to the metric. The first function (the effective
equation of state) uniquely controls the expansion history of the universe. The
remaining four functions appear in the linear cosmological perturbation
equations, but only three of them regulate the growth history of large scale
structures. We propose a specific parameterization of such functions in terms
of characteristic coefficients that serve as coordinates in the space of
modified gravity theories and can be effectively constrained by the next
generation of cosmological experiments. We address in full generality the
problem of the soundness of the theory against ghost-like and gradient
instabilities and show how the space of non-pathological models shrinks when a
more negative equation of state parameter is considered. This analysis allows
us to locate a large class of stable theories that violate the null energy
condition (i.e. super-acceleration models) and to recover, as particular
subsets, various models considered so far. Finally, under the assumption that
the true underlying cosmological model is the $\Lambda$ Cold Dark Matter
($\Lambda$CDM) scenario, and relying on the figure of merit of EUCLID-like
observations, we demonstrate that the theoretical requirement of stability
significantly narrows the empirical likelihood, increasing the discriminatory
power of data. We also find that the vast majority of these non-pathological
theories generating the same expansion history as the $\Lambda$CDM model
predict a different, lower, growth rate of cosmic structures.


title:
Ontological metaphors for negative energy in an interdisciplinary
  context

abstract:
  Teaching about energy in interdisciplinary settings that emphasize coherence
among physics, chemistry, and biology leads to a more central role for chemical
bond energy. We argue that an interdisciplinary approach to chemical energy
leads to modeling chemical bonds in terms of negative energy. While recent work
on ontological metaphors for energy has emphasized the affordances of the
substance ontology, this ontology is problematic in the context of negative
energy. Instead, we apply a dynamic ontologies perspective to argue that
blending the substance and location ontologies for energy can be effective in
reasoning about negative energy in the context of reasoning about chemical
bonds. We present data from an introductory physics for the life sciences
(IPLS) course in which both experts and students successfully use this blended
ontology. Blending these ontologies is most successful when the substance and
location ontologies are combined such that each is strategically utilized in
reasoning about particular aspects of energetic processes.


title:
Aspartame: Solving Constraint Satisfaction Problems with Answer Set
  Programming

abstract:
  Encoding finite linear CSPs as Boolean formulas and solving them by using
modern SAT solvers has proven to be highly effective, as exemplified by the
award-winning sugar system. We here develop an alternative approach based on
ASP. This allows us to use first-order encodings providing us with a high
degree of flexibility for easy experimentation with different implementations.
The resulting system aspartame re-uses parts of sugar for parsing and
normalizing CSPs. The obtained set of facts is then combined with an ASP
encoding that can be grounded and solved by off-the-shelf ASP systems. We
establish the competitiveness of our approach by empirically contrasting
aspartame and sugar.


title: Auto-Encoding Variational Bayes

abstract:
  How can we perform efficient inference and learning in directed probabilistic
models, in the presence of continuous latent variables with intractable
posterior distributions, and large datasets? We introduce a stochastic
variational inference and learning algorithm that scales to large datasets and,
under some mild differentiability conditions, even works in the intractable
case. Our contributions is two-fold. First, we show that a reparameterization
of the variational lower bound yields a lower bound estimator that can be
straightforwardly optimized using standard stochastic gradient methods. Second,
we show that for i.i.d. datasets with continuous latent variables per
datapoint, posterior inference can be made especially efficient by fitting an
approximate inference model (also called a recognition model) to the
intractable posterior using the proposed lower bound estimator. Theoretical
advantages are reflected in experimental results.


title: Neuronal Synchrony in Complex-Valued Deep Networks

abstract:
  Deep learning has recently led to great successes in tasks such as image
recognition (e.g Krizhevsky et al., 2012). However, deep networks are still
outmatched by the power and versatility of the brain, perhaps in part due to
the richer neuronal computations available to cortical circuits. The challenge
is to identify which neuronal mechanisms are relevant, and to find suitable
abstractions to model them. Here, we show how aspects of spike timing, long
hypothesized to play a crucial role in cortical information processing, could
be incorporated into deep networks to build richer, versatile representations.
  We introduce a neural network formulation based on complex-valued neuronal
units that is not only biologically meaningful but also amenable to a variety
of deep learning frameworks. Here, units are attributed both a firing rate and
a phase, the latter indicating properties of spike timing. We show how this
formulation qualitatively captures several aspects thought to be related to
neuronal synchrony, including gating of information processing and dynamic
binding of distributed object representations. Focusing on the latter, we
demonstrate the potential of the approach in several simple experiments. Thus,
neuronal synchrony could be a flexible mechanism that fulfills multiple
functional roles in deep networks.


title: Improving Deep Neural Networks with Probabilistic Maxout Units

abstract:
  We present a probabilistic variant of the recently introduced maxout unit.
The success of deep neural networks utilizing maxout can partly be attributed
to favorable performance under dropout, when compared to rectified linear
units. It however also depends on the fact that each maxout unit performs a
pooling operation over a group of linear transformations and is thus partially
invariant to changes in its input. Starting from this observation we ask the
question: Can the desirable properties of maxout units be preserved while
improving their invariance properties ? We argue that our probabilistic maxout
(probout) units successfully achieve this balance. We quantitatively verify
this claim and report classification performance matching or exceeding the
current state of the art on three challenging image classification benchmarks
(CIFAR-10, CIFAR-100 and SVHN).


title:
Comparison three methods of clustering: k-means, spectral clustering and
  hierarchical clustering

abstract:
  Comparison of three kind of the clustering and find cost function and loss
function and calculate them. Error rate of the clustering methods and how to
calculate the error percentage always be one on the important factor for
evaluating the clustering methods, so this paper introduce one way to calculate
the error rate of clustering methods. Clustering algorithms can be divided into
several categories including partitioning clustering algorithms, hierarchical
algorithms and density based algorithms. Generally speaking we should compare
clustering algorithms by Scalability, Ability to work with different attribute,
Clusters formed by conventional, Having minimal knowledge of the computer to
recognize the input parameters, Classes for dealing with noise and extra
deposition that same error rate for clustering a new data, Thus, there is no
effect on the input data, different dimensions of high levels, K-means is one
of the simplest approach to clustering that clustering is an unsupervised
problem.


title:
Thermally activated switching rate of a nanomagnet in the presence of
  spin torque

abstract:
  The current dependence of the spin torque switching rate in a thermally
activated region of an in-plane magnetized system was studied. The logarithm of
the switching rate depended nonlinearly on current in the high-current region,
I_{c} < I < I_{c}^{*}, where I_{c} and I_{c}^{*} are critical currents
distinguishing the stability of the magnetization. We also found that the
attempt frequency had a minimum around I_{c}, and that the attempt frequency at
I_{c} was three orders of magnitude smaller than that at zero current, contrary
to the assumption in previous analyses of experiments that it remains constant.


title:
A New Frequency Control Reserve Framework based on Energy-Constrained
  Units

abstract:
  Frequency control reserves are an essential ancillary service in any electric
power system, guaranteeing that generation and demand of active power are
balanced at all times. Traditionally, conventional power plants are used for
frequency reserves. There are economical and technical benefits of instead
using energy constrained units such as storage systems and demand response, but
so far they have not been widely adopted as their energy constraints prevent
them from following traditional regulation signals, which sometimes are biased
over long time-spans. This paper proposes a frequency control framework that
splits the control signals according to the frequency spectrum. This guarantees
that all control signals are zero-mean over well-defined time-periods, which is
a crucial requirement for the usage of energy-constraint units such as
batteries. A case-study presents a possible implementation, and shows how
different technologies with widely varying characteristics can all participate
in frequency control reserve provision, while guaranteeing that their
respective energy constraints are always fulfilled.


title:
Exact solutions to the nonlinear dynamics of learning in deep linear
  neural networks

abstract:
  Despite the widespread practical success of deep learning methods, our
theoretical understanding of the dynamics of learning in deep neural networks
remains quite sparse. We attempt to bridge the gap between the theory and
practice of deep learning by systematically analyzing learning dynamics for the
restricted case of deep linear neural networks. Despite the linearity of their
input-output map, such networks have nonlinear gradient descent dynamics on
weights that change with the addition of each new hidden layer. We show that
deep linear networks exhibit nonlinear learning phenomena similar to those seen
in simulations of nonlinear networks, including long plateaus followed by rapid
transitions to lower error solutions, and faster convergence from greedy
unsupervised pretraining initial conditions than from random initial
conditions. We provide an analytical description of these phenomena by finding
new exact solutions to the nonlinear dynamics of deep learning. Our theoretical
analysis also reveals the surprising finding that as the depth of a network
approaches infinity, learning speed can nevertheless remain finite: for a
special class of initial conditions on the weights, very deep networks incur
only a finite, depth independent, delay in learning speed relative to shallow
networks. We show that, under certain conditions on the training data,
unsupervised pretraining can find this special class of initial conditions,
while scaled random Gaussian initializations cannot. We further exhibit a new
class of random orthogonal initial conditions on weights that, like
unsupervised pre-training, enjoys depth independent learning times. We further
show that these initial conditions also lead to faithful propagation of
gradients even in deep nonlinear networks, as long as they operate in a special
regime known as the edge of chaos.

categories: cs.NE cond-mat.dis-nn cs.CV cs.LG q-bio.NC stat.ML


title: HOPS 136: An Edge-On Orion Protostar Near the End of Envelope Infall

abstract:
  Edge-on protostars are valuable for understanding the disk and envelope
properties of embedded young stellar objects, since the disk, envelope, and
envelope cavities are all distinctly visible in resolved images and well
constrained in modeling. Comparing 2MASS, WISE, Spitzer, Herschel, APEX, and
IRAM photometry and limits from 1.25 to 1200 microns, Spitzer spectroscopy from
5 to 40 microns, and high-resolution Hubble imaging at 1.60 and 2.05 microns to
radiative transfer modeling, we determine envelope and disk properties for the
Class I protostar HOPS 136, an edge-on source in Orion's Lynds 1641 region. The
source has a bolometric luminosity of 0.8 L_sun, a bolometric temperature of
170 K, and a ratio of submillimeter to bolometric luminosity of 0.8%. Via
modeling, we find a total luminosity of 4.7 L_sun (larger than the observed
luminosity due to extinction by the disk), an envelope mass of 0.06 M_sun, and
a disk radius and mass of 450 AU and 0.002 M_sun. The stellar mass is highly
uncertain but is estimated to fall between 0.4 and 0.5 M_sun. To reproduce the
flux and wavelength of the near-infrared scattered-light peak in the spectral
energy distribution, we require 5.4 x 10^-5 M_sun of gas and dust in each
cavity. The disk has a large radius and a mass typical of more evolved T Tauri
stars in spite of the significant remaining envelope. HOPS 136 appears to be a
key link between the protostellar and optically revealed stages of star
formation.


title:
Shadow networks: Discovering hidden nodes with models of information
  flow

abstract:
  Complex, dynamic networks underlie many systems, and understanding these
networks is the concern of a great span of important scientific and engineering
problems. Quantitative description is crucial for this understanding yet, due
to a range of measurement problems, many real network datasets are incomplete.
Here we explore how accidentally missing or deliberately hidden nodes may be
detected in networks by the effect of their absence on predictions of the speed
with which information flows through the network. We use Symbolic Regression
(SR) to learn models relating information flow to network topology. These
models show localized, systematic, and non-random discrepancies when applied to
test networks with intentionally masked nodes, demonstrating the ability to
detect the presence of missing nodes and where in the network those nodes are
likely to reside.

categories: physics.soc-ph cond-mat.dis-nn cs.SI physics.data-an


title:
Exotic circuit elements from zero-modes in hybrid superconductor/quantum
  Hall systems

abstract:
  Heterostructures formed by quantum Hall systems and superconductors have
recently been shown to support widely coveted Majorana fermion zero-modes and
still more exotic `parafermionic' generalizations. Here we establish that
probing such zero-modes using quantum Hall edge states yields non-local
transport signatures that pave the way towards a variety of novel circuit
elements. In particular, we demonstrate quite generally that at low energies
the zero-modes convert chirally moving quasiparticles into oppositely charged
quasiholes propagating in the same direction---that is, they swap the sign of
the chiral edge currents. One may then construct new and potentially useful
circuit elements using this `perfect Andreev conversion' process, including
superconducting current and voltage mirrors as well as transistors for
fractional charge currents. Characterization of these circuit elements should
provide striking evidence of the zero-mode physics.


title: Persistent Superconductor Currents in Holographic Lattices

abstract:
  We consider a persistent superconductor current along the direction with no
translational symmetry in a holographic gravity model. Incorporating a lattice
structure into the model, we numerically construct novel solutions of hairy
charged stationary black brane with momentum/rotation along the latticed
direction. The lattice structure prevents the horizon from rotating, and the
total momentum is only carried by matter fields outside the black brane
horizon. This is consistent with the black hole rigidity theorem, and suggests
that in dual field theory with lattices, superconductor currents are made up by
"composite" fields, rather than "fractionalized" degrees of freedom. We also
show that our solutions are consistent with the superfluid hydrodynamics.


title: BPS domain walls from backreacted orientifolds

abstract:
  Compactifications with D-brane and orientifold sources lead to standard
gauged supergravity theories if the sources are smeared over the internal
directions. It is therefore of interest to find how the solutions described by
the gauged supergravity are altered by properly localising the sources. In this
paper we analyse this for BPS domain wall solutions in the seven-dimensional
gauged supergravity obtained from an O6 toroidal orientifold compactification
in massive IIA supergravity. This is one of the simplest no-scale
supergravities that can be constructed and analysed in full detail. We find and
discuss the BPS domain walls both when the O6 planes are smeared and localised.
When the O6 planes are localised the domain wall solutions live in a warped
compactification. In order to get explicit expressions we also consider the
non-compact versions of the solutions for which the O6 planes have been traded
for D6 branes. Through T-duality we obtain partially localised solutions for
compactifications to four dimensions using O3 planes with 3-form fluxes.


title:
On the sensitivity of extrasolar mass-loss rate ranges: HD 209458b a
  case study

abstract:
  We present a 3D hydrodynamic study of the effects that different stellar wind
conditions and planetary wind structures have on the calculated Ly-$\alpha$
absorptions produced during the transit of HD 209458b. Considering a range of
stellar wind speeds $\sim$[350-800] km s$^{-1}$, coronal temperature
$\sim$[3-7] $\times10^{6}$ K and two values of the polytropic index $\Gamma$
$\sim$[1.01-1.13], while keeping fixed the stellar mass loss rate, we found a
that a $\dot M_p$ range between $\sim$[3-5] $\times 10^{10}$g s$^{-1}$ give
account for the observational absorption in Ly-$\alpha$ measured for the
planetary system. Also, several models with anisotropic evaporation profiles
for the planetary escaping atmosphere were carried out, showing that both, the
escape through polar regions and through the night side yields larger
absorptions than an isotropic planetary wind.


title:
Three-Dimensional General Relativistic Radiation Magnetohydrodynamical
  Simulation of Super-Eddington Accretion, using a new code HARMRAD with M1
  Closure

abstract:
  Black hole (BH) accretion flows and jets are dynamic hot relativistic
magnetized plasma flows whose radiative opacity can significantly affect flow
structure and behavior. We describe a numerical scheme, tests, and an
astrophysically relevant application using the M1 radiation closure within a
new three-dimensional (3D) general relativistic (GR) radiation (R)
magnetohydrodynamics (MHD) massively parallel code called HARMRAD. Our 3D
GRRMHD simulation of super-Eddington accretion (about $20$ times Eddington)
onto a rapidly rotating BH (dimensionless spin $j=0.9375$) shows sustained
non-axisymmemtric disk turbulence, a persistent electromagnetic jet driven by
the Blandford-Znajek effect, and a total radiative output consistently near the
Eddington rate. The total accretion efficiency is of order $20\%$, the
large-scale electromagnetic jet efficiency is of order $10\%$, and the total
radiative efficiency that reaches large distances remains low at only order
$1\%$. However, the radiation jet and the electromagnetic jet both emerge from
a geometrically beamed polar region, with super-Eddington isotropic equivalent
luminosities. Such simulations with HARMRAD can enlighten the role of BH spin
vs.\ disks in launching jets, help determine the origin of spectral and
temporal states in x-ray binaries, help understand how tidal disruption events
(TDEs) work, provide an accurate horizon-scale flow structure for M87 and other
active galactic nuclei (AGN), and isolate whether AGN feedback is driven by
radiation or by an electromagnetic, thermal, or kinetic wind/jet. For example,
the low radiative efficiency and weak BH spin-down rate from our simulation
suggest that BH growth over cosmological times to billions of solar masses by
redshifts of $z\sim 6-8$ is achievable even with rapidly rotating BHs and ten
solar mass BH seeds.


title: Imbalanced Relativistic Force-Free Magnetohydrodynamic Turbulence

abstract:
  When magnetic energy density is much larger than that of matter, as in
pulsar/black hole magnetospheres, the medium becomes force-free and we need
relativity to describe it. As in non-relativistic magnetohydrodynamics (MHD),
Alfv\'enic MHD turbulence in the relativistic limit can be described by
interactions of counter-traveling wave packets. In this paper we numerically
study strong imbalanced MHD turbulence in such environments. Here, imbalanced
turbulence means the waves traveling in one direction (dominant waves) have
higher amplitudes than the opposite-traveling waves (sub-dominant waves). We
find that (1) spectrum of the dominant waves is steeper than that of
sub-dominant waves, (2) the anisotropy of the dominant waves is weaker than
that of sub-dominant waves, and (3) the dependence of the ratio of magnetic
energy densities of dominant and sub-dominant waves on the ratio of energy
injection rates is steeper than quadratic (i.e., \$b_+^2/b_-^2 \propto
(\epsilon_+/\epsilon_-)^n \$ with n>2). These results are consistent with those
obtained for imbalanced non-relativistic Alfv\'enic turbulence. This
corresponds well to the earlier reported similarity of the relativistic and
non-relativistic balanced magnetic turbulence.


title: Effects of multiple-scale driving on turbulence statistics

abstract:
  Turbulence is ubiquitous in astrophysical fluids such as the interstellar
medium (ISM) and the intracluster medium (ICM). In turbulence studies, it is
customary to assume that fluid is driven on a single scale. However, in
astrophysical fluids, there can be many different driving mechanisms that act
on different scales. If there are multiple energy-injection scales, the process
of energy cascade and turbulence dynamo will be different compared with the
case of single energy-injection scale. In this work, we perform
three-dimensional incompressible/compressible magnetohydrodynamic (MHD)
turbulence simulations. We drive turbulence in Fourier space in two wavenumber
ranges, 2\$\leq k \leq \sqrt{12}\$ (large-scale) and 15 \$\lesssim k \lesssim
\$ 26 (small-scale). We inject different amount of energy in each range by
changing the amplitude of forcing in the range. We present the time evolution
of the kinetic and magnetic energy densities and discuss the turbulence dynamo
in the presence of energy injections at two scales. We show how kinetic,
magnetic and density spectra are affected by the two-scale energy injections
and we discuss the observational implications. In the case \$\epsilon_L <
\epsilon_S\$, where \$\epsilon_L\$ and \$\epsilon_S\$ are energy-injection
rates at the large and small scales, respectively, our results show that even a
tiny amount of large-scale energy injection can significantly change the
properties of turbulence. On the other hand, when \$\epsilon_L \gtrsim
\epsilon_S\$, the small-scale driving does not influence the turbulence
statistics much unless \$\epsilon_L \sim \epsilon_S\$.


title: A Functional View of Strong Negation in Answer Set Programming

abstract:
  The distinction between strong negation and default negation has been useful
in answer set programming. We present an alternative account of strong
negation, which lets us view strong negation in terms of the functional stable
model semantics by Bartholomew and Lee. More specifically, we show that, under
complete interpretations, minimizing both positive and negative literals in the
traditional answer set semantics is essentially the same as ensuring the
uniqueness of Boolean function values under the functional stable model
semantics. The same account lets us view Lifschitz's two-valued logic programs
as a special case of the functional stable model semantics. In addition, we
show how non-Boolean intensional functions can be eliminated in favor of
Boolean intensional functions, and furthermore can be represented using strong
negation, which provides a way to compute the functional stable model semantics
using existing ASP solvers. We also note that similar results hold with the
functional stable model semantics by Cabalar.


title:
From fractionally charged solitons to Majorana bound states in a
  one-dimensional interacting model

abstract:
  We consider one-dimensional topological insulators hosting fractionally
charged midgap states in the presence and absence of induced superconductivity
pairing. Under the protection of a discrete symmetry, relating positive and
negative energy states, the solitonic midgap states remain pinned at zero
energy when superconducting correlations are induced by proximity effect. When
the superconducting pairing dominates the initial insulating gap, Majorana
fermion phases develop for a class of insulators. As a concrete example, we
study the Creutz model with induced s-wave superconductivity and repulsive
Hubbard-type interactions. For a finite wire, without interactions, the
solitonic modes originating from the nonsuperconducting model survive at zero
energy, revealing a fourfold-degenerate ground state. However, interactions
break the aforementioned discrete symmetry and completely remove this
degeneracy, thereby producing a unique ground state which ischaracterized by a
topological bulk invariant with respect to the product of fermion parity and
bond inversion. In contrast, the Majorana edge modes are globally robust to
interactions. Moreover, the parameter range for which a topological Majorana
phase is stabilized expands when increasing the repulsive Hubbard interaction.
The topological phase diagram of the interacting model is obtained using a
combination of mean-field theory and density matrix renormalization group
techniques.


title: One-dimensional edge state transport in a topological Kondo insulator

abstract:
  Topological insulators, with metallic boundary states protected against
time-reversal-invariant perturbations, are a promising avenue for realizing
exotic quantum states of matter including various excitations of collective
modes predicted in particle physics, such as Majorana fermions and axions.
According to theoretical predictions, a topological insulating state can emerge
from not only a weakly interacting system with strong spin-orbit coupling, but
also in insulators driven by strong electron correlations. The Kondo insulator
compound SmB6 is an ideal candidate for realizing this exotic state of matter,
with hybridization between itinerant conduction electrons and localized
$f$-electrons driving an insulating gap and metallic surface states at low
temperatures. Here we exploit the existence of surface ferromagnetism in SmB6
to investigate the topological nature of metallic surface states by studying
magnetotransport properties at very low temperatures. We find evidence of
one-dimensional surface transport with a quantized conductance value of $e^2/h$
originating from the chiral edge channels of ferromagnetic domain walls,
providing strong evidence that topologically non-trivial surface states exist
in SmB6.


title:
The photon-pion transition form factor: incompatible data or
  incompatible models?

abstract:
  The elastic and $\gamma \to \pi$ transition form factors of the pion along
with its usual static observables are calculated within a light-front field
approach to the constituent quark model. The focus of this exercise in a simple
model is on a unified description of all observables with one singly
parametrized light-front wave function to detect possible discrepancies in
experimental data, in particular the contentious large momentum-squared data on
the transition factor as reported by BaBar and Belle. We also discuss the
relation of a small to vanishing pion charge radius with an almost constant
pion distribution amplitude and compare our results with those obtained in a
holographic light-front model.


title: An Algebra of Causal Chains

abstract:
  In this work we propose a multi-valued extension of logic programs under the
stable models semantics where each true atom in a model is associated with a
set of justifications, in a similar spirit than a set of proof trees. The main
contribution of this paper is that we capture justifications into an algebra of
truth values with three internal operations: an addition '+' representing
alternative justifications for a formula, a commutative product '*'
representing joint interaction of causes and a non-commutative product '.'
acting as a concatenation or proof constructor. Using this multi-valued
semantics, we obtain a one-to-one correspondence between the syntactic proof
tree of a standard (non-causal) logic program and the interpretation of each
true atom in a model. Furthermore, thanks to this algebraic characterization we
can detect semantic properties like redundancy and relevance of the obtained
justifications. We also identify a lattice-based characterization of this
algebra, defining a direct consequences operator, proving its continuity and
that its least fix point can be computed after a finite number of iterations.
Finally, we define the concept of causal stable model by introducing an
analogous transformation to Gelfond and Lifschitz's program reduct.


title:
Jellyfish: Evidence of extreme ram-pressure stripping in massive galaxy
  clusters

abstract:
  Ram-pressure stripping by the gaseous intra-cluster medium has been proposed
as the dominant physical mechanism driving the rapid evolution of galaxies in
dense environments. Detailed studies of this process have, however, largely
been limited to relatively modest examples affecting only the outermost gas
layers of galaxies in nearby and/or low-mass galaxy clusters. We here present
results from our search for extreme cases of gas-galaxy interactions in much
more massive, X-ray selected clusters at $z>0.3$. Using Hubble Space Telescope
snapshots in the F606W and F814W passbands, we have discovered dramatic
evidence of ram-pressure stripping in which copious amounts of gas are first
shock compressed and then removed from galaxies falling into the cluster.
Vigorous starbursts triggered by this process across the galaxy-gas interface
and in the debris trail cause these galaxies to temporarily become some of the
brightest cluster members in the F606W passband, capable of outshining even the
Brightest Cluster Galaxy. Based on the spatial distribution and orientation of
systems viewed nearly edge-on in our survey, we speculate that infall at large
impact parameter gives rise to particularly long-lasting stripping events. Our
sample of six spectacular examples identified in clusters from the Massive
Cluster Survey, all featuring $M_{\rm F606W}<-$21 mag, doubles the number of
such systems presently known at $z>0.2$ and facilitates detailed quantitative
studies of the most violent galaxy evolution in clusters.


title: Liquid jet eruption from hollow relaxation

abstract:
  A cavity hollowed out on a free liquid surface is relaxing, forming an
intense liquid jet. Using a model experiment where a short air pulse sculpts an
initial large crater, we depict the different stages in the gravitational
cavity collapse and in the jet formation. Prior eversion, all cavity profiles
are found to exhibit a shape similarity. Following hollow relaxation, a
universal scaling law establishing an unexpected relation between the jet
eruption velocity, the initial cavity geometry and the liquid viscosity is
evidenced experimentally. On further analysing the jet forms we demonstrate
that the stretched liquid jet also presents shape similarity. Considering that
the jet shape is a signature of the initial flow focusing, we elaborate a
simple model capturing the key features of the erupting jet velocity scaling.


title: An electrically injected photon-pair source at room temperature

abstract:
  One of the main challenges for future quantum information technologies is
miniaturization and integration of high performance components in a single
chip. In this context, electrically driven sources of non-classical states of
light have a clear advantage over optically driven ones. Here we demonstrate
the first electrically driven semiconductor source of photon pairs working at
room temperature and telecom wavelength. The device is based on type-II
intracavity Spontaneous Parametric Down-Conversion in an AlGaAs laser diode and
generates pairs at 1.57 $\mu$m. Time-correlation measurements of the emitted
pairs give an internal generation efficiency of $7 \times 10^{-11}$
pairs/injected electron. The capability of our platform to support generation,
manipulation and detection of photons opens the way to the demonstration of
massively parallel systems for complex quantum operations.


title:
Query Answering in Object Oriented Knowledge Bases in Logic Programming:
  Description and Challenge for ASP

abstract:
  Research on developing efficient and scalable ASP solvers can substantially
benefit by the availability of data sets to experiment with. KB_Bio_101
contains knowledge from a biology textbook, has been developed as part of
Project Halo, and has recently become available for research use. KB_Bio_101 is
one of the largest KBs available in ASP and the reasoning with it is
undecidable in general. We give a description of this KB and ASP programs for a
suite of queries that have been of practical interest. We explain why these
queries pose significant practical challenges for the current ASP solvers.


title: Covariant second-order perturbations in generalized two-field inflation

abstract:
  We examine the covariant properties of generalized models of two-field
inflation, with non-canonical kinetic terms and a possibly non-trivial field
metric. We demonstrate that kinetic-term derivatives and covariant field
derivatives do commute in a proper covariant framework, which was not realized
before in the literature. We also define a set of generalized slow-roll
parameters, using a unified notation. Within this framework, we study the most
general class of models that allows for well-defined adiabatic and entropic
sound speeds, which we identify as the models with parallel momentum and field
velocity vectors. For these models we write the exact cubic action in terms of
the adiabatic and isocurvature perturbations. We thus provide the tool to
calculate the exact non-Gaussianity beyond slow-roll and at any scale for these
generalized models. We illustrate our general results by considering their
long-wavelength limit, as well as with the example of two-field DBI inflation.


title: The DIAMOND System for Argumentation: Preliminary Report

abstract:
  Abstract dialectical frameworks (ADFs) are a powerful generalisation of
Dung's abstract argumentation frameworks. In this paper we present an answer
set programming based software system, called DIAMOND (DIAlectical MOdels
eNcoDing). It translates ADFs into answer set programs whose stable models
correspond to models of the ADF with respect to several semantics (i.e.
admissible, complete, stable, grounded).


title:
An effective algebraic detection of the Nielsen--Thurston classification
  of mapping classes

abstract:
  In this article, we propose two algorithms for determining the
Nielsen-Thurston classification of a mapping class $\psi$ on a surface $S$. We
start with a finite generating set $X$ for the mapping class group and a word
$\psi$ in $\langle X \rangle$. We show that if $\psi$ represents a reducible
mapping class in $\Mod(S)$ then $\psi$ admits a canonical reduction system
whose total length is exponential in the word length of $\psi$. We use this
fact to find the canonical reduction system of $\psi$. We also prove an
effective conjugacy separability result for $\pi_1(S)$ which allows us to lift
the action of $\psi$ to a finite cover $\yt{S}$ of $S$ whose degree depends
computably on the word length of $\psi$, and to use the homology action of
$\psi$ on $H_1(\yt{S},\mathbb{C})$ to determine the Nielsen-Thurston
classification of $\psi$.


title: Improved performance of graphene transistors by strain engineering

abstract:
  By means of numerical simulation, we study in this work the effects of
uniaxial strain on transport properties of strained graphene heterojunctions
and explore the possibility to achieve good performance of graphene transistors
using these hetero-channels. It is shown that a finite conduction-gap can open
in the strain junctions due to the strain-induced deformation of graphene
bandstructure. These hetero-channels are then demonstrated to improve
significantly the operation of graphene field-effect-transistors (FETs). In
particular, ON/OFF current ratio can reach a value of over 10$^5$. In graphene
normal FETs, transconductance, though reduced compared to the case of
unstrained devices, is still high while good saturation of current can be
obtained. This results in high voltage gain and high transition frequency of a
few hundreds of GHz for a gate length of 80 nm. In graphene tunneling FETs,
subthreshold swing lower than 30 mV/dec, strong non-linear effects such as gate
controllable negative differential conductance, and current rectification are
observed.


title: A System for Interactive Query Answering with Answer Set Programming

abstract:
  Reactive answer set programming has paved the way for incorporating online
information into operative solving processes. Although this technology was
originally devised for dealing with data streams in dynamic environments, like
assisted living and cognitive robotics, it can likewise be used to incorporate
facts, rules, or queries provided by a user. As a result, we present the design
and implementation of a system for interactive query answering with reactive
answer set programming. Our system quontroller is based on the reactive solver
oclingo and implemented as a dedicated front-end. We describe its functionality
and implementation, and we illustrate its features by some selected use cases.


title:
Tunneling spectroscopy of superconducting MoN and NbTiN grown by atomic
  layer deposition

abstract:
  A tunneling spectroscopy study is presented of superconducting MoN and
Nb$_{0.8}$Ti$_{0.2}$N thin films grown by atomic layer deposition (ALD). The
films exhibited a superconducting gap of 2meV and 2.4meV respectively with a
corresponding critical temperature of 11.5K and 13.4K, among the highest
reported $T_c$ values achieved by the ALD technique. Tunnel junctions were
obtained using a mechanical contact method with a Au tip. While the native
oxides of these films provided poor tunnel barriers, high quality tunnel
junctions with low zero bias conductance (below $\sim$10%) were obtained using
an artificial tunnel barrier of Al$_2$O$_3$ on the film's surface grown
$\textit{ex situ}$ by ALD. We find a large critical current density on the
order of $4\times 10^6$A/cm$^2$ at $T=0.8T_c$ for a 60nm MoN film and
demonstrate conformal coating capabilities of ALD onto high aspect ratio
geometries. These results suggest the ALD technique offers significant promise
for thin film superconducting device applications.


title: Quantum gauge theories on noncommutative 3-d space

abstract:
  We consider a class of gauge invariant models on the noncommutative space
$\mathbb{R}^3_\lambda$, a deformation of $\mathbb{R}^3$. Focusing on massless
models with no linear $A_i$ dependence, we obtain noncommutative gauge models
for which the computation of the propagator can be done in a convenient gauge.
We find that the infrared singularity of the massless propagator disappears in
the computation of the correlation functions. We show that massless gauge
invariant models on $\mathbb{R}^3_\lambda$ have quantum instabilities of the
vacuum, signaled by the occurrence of non vanishing 1-point functions for some
but not all of the components of the gauge potential. The tadpole contribution
to the effective action cannot be interpreted as a standard $\sigma$-term. Its
global symmetry does not fit with the one of the classical action, reminiscent
to an explicit global symmetry breaking term.


title: Generating Shortest Synchronizing Sequences using Answer Set Programming

abstract:
  For a finite state automaton, a synchronizing sequence is an input sequence
that takes all the states to the same state. Checking the existence of a
synchronizing sequence and finding a synchronizing sequence, if one exists, can
be performed in polynomial time. However, the problem of finding a shortest
synchronizing sequence is known to be NP-hard. In this work, the usefulness of
Answer Set Programming to solve this optimization problem is investigated, in
comparison with brute-force algorithms and SAT-based approaches.
  Keywords: finite automata, shortest synchronizing sequence, ASP


title:
Existence and Uniqueness of Mild Solutions to Neutral SFDE driven by a
  Fractional Brownian Motion with non-Lipschitz Coefficients

abstract:
  The article presents results on existence and uniqueness of mild solutions to
a class of non linear neutral stochastic functional differential equations
(NSFDEs) driven by Fractional Brownian motion in a Hilbert space with
non-Lipschitzian coefficients. The results are obtained by using the method of
Picard approximation.