title:
Modified Newton's Law of Gravitation Due to Minimal Length in Quantum
  Gravity

abstract:
  A recent theory about the origin of the gravity suggests that the gravity is
originally an entropic force. In this work, we discuss the effects of
generalized uncertainty principle (GUP) which is proposed by some approaches to
quantum gravity such as string theory, black hole physics and doubly special
relativity theories (DSR), on the area law of the entropy. This leads to a
$\sqrt{Area}$-type correction to the area law of entropy which imply that the
number of bits $N$ is modified. Therefore, we obtain a modified Newton's law of
gravitation. Surprisingly, this modification agrees with different sign with
the prediction of Randall-Sundrum II model which contains one uncompactified
extra dimension. Furthermore, such modification may have observable
consequences at length scales much larger than the Planck scale.


title: Kidney Exchange in Dynamic Sparse Heterogenous Pools

abstract:
  Current kidney exchange pools are of moderate size and thin, as they consist
of many highly sensitized patients. Creating a thicker pool can be done by
waiting for many pairs to arrive. We analyze a simple class of matching
algorithms that search periodically for allocations. We find that if only 2-way
cycles are conducted, in order to gain a significant amount of matches over the
online scenario (matching each time a new incompatible pair joins the pool) the
waiting period should be "very long". If 3-way cycles are also allowed we find
regimes in which waiting for a short period also increases the number of
matches considerably. Finally, a significant increase of matches can be
obtained by using even one non-simultaneous chain while still matching in an
online fashion. Our theoretical findings and data-driven computational
experiments lead to policy recommendations.


title: Polynomials with no zeros on a face of the bidisk

abstract:
  We present a Hilbert space geometric approach to the problem of
characterizing the positive bivariate trigonometric polynomials that can be
represented as the square of a two variable polynomial possessing a certain
stability requirement, namely no zeros on a face of the bidisk. Two different
characterizations are given using a Hilbert space structure naturally
associated to the trigonometric polynomial; one is in terms of a certain
orthogonal decomposition the Hilbert space must possess called the "split-shift
orthogonality condition" and another is an operator theoretic or matrix
condition closely related to an earlier characterization due to the first two
authors. This approach allows several refinements of the characterization and
it also allows us to prove a sums of squares decomposition which at once
generalizes the Cole-Wermer sums of squares result for two variable stable
polynomials as well as a sums of squares result related to the Schur-Cohn
method for counting the roots of a univariate polynomial in the unit disk.


title:
Comment on "Unified Formalism of Andreev Reflection at a
  Ferromagnet/Superconductor Interface" by T.Y. Chen, et al

abstract:
  A recent paper of Chen et al. claims to have derived an allegedly previously
unavailable "unified" Andreev Reflection (AR) formalism for an arbitrary spin
polarization P that recovers earlier results as its special limits. In this
Comment we show that, contrary to this claim, there are numerous works
correctly solving the problem formulated in this paper for an arbitrary P,
while Chen et al formulas fail to correctly incorporate P \neq 0 effects and
violate basic physical principles.


title: Bilayer graphene spectral function in RPA and self-consistent GW

abstract:
  We calculate the single-particle spectral function for doped bilayer graphene
in the low energy limit, described by two parabolic bands with zero band gap
and long range Coulomb interaction. Calculations are done using thermal Green's
functions in both the random phase approximation (RPA) and the fully
self-consistent GW approximation. RPA (in line with previous studies) yields a
spectral function which apart from the Landau quasiparticle peaks shows
additional coherent features interpreted as plasmarons, i.e. composite
electron-plasmon excitations. In GW the plasmaron becomes incoherent and peaks
are replaced by much broader features. The deviation of the quasiparticle
weight and mass renormalization from their non-interacting values is small
which indicates that bilayer graphene is a weakly interacting system. The
electron energy loss function, $Im[-\epsilon^{-1}_q(\omega)]$ shows a sharp
plasmon mode in RPA which in GW approximation becomes less coherent and thus
consistent with the weaker plasmaron features in the corresponding
single-particle spectral function.


title: The electromagnetic form factor of the pion in two-flavour lattice QCD

abstract:
  We present the current status of our lattice calculation of the
electromagnetic form factor of the pion with two flavours of non-perturbatively
O(a)-improved Wilson fermions. Using twisted boundary conditions and stochastic
sources we obtain accurate results with a fine momentum resolution near
$q^2=0$. This enables the computation of the charge radius without model
dependence. The ensembles cover various lattice spacings and pion masses,
ranging down to 250 MeV. This allows to compare the data to continuum chiral
perturbation theory to NNLO including corrections of finite lattice spacing to
perform a simultaneous chiral and continuum extrapolation. An estimate for the
systematic error resulting from the extrapolation can be obtained by looking at
the spread of results obtained from other functional forms such as polynomials.


title: Anomaly Classification with the Anti-Profile Support Vector Machine

abstract:
  We introduce the anti-profile Support Vector Machine (apSVM) as a novel
algorithm to address the anomaly classification problem, an extension of
anomaly detection where the goal is to distinguish data samples from a number
of anomalous and heterogeneous classes based on their pattern of deviation from
a normal stable class. We show that under heterogeneity assumptions defined
here that the apSVM can be solved as the dual of a standard SVM with an
indirect kernel that measures similarity of anomalous samples through
similarity to the stable normal class. We characterize this indirect kernel as
the inner product in a Reproducing Kernel Hilbert Space between representers
that are projected to the subspace spanned by the representers of the normal
samples. We show by simulation and application to cancer genomics datasets that
the anti-profile SVM produces classifiers that are more accurate and stable
than the standard SVM in the anomaly classification setting.


title:
Theoretical Analysis of the Characteristic Impedance in
  Metal-Insulator-Metal Plasmonic Transmission Lines

abstract:
  We propose a closed form formulation for the impedance of the
Metal-Insulator-Metal (MIM) plasmonic transmission lines by solving the
Maxwell's equations. We provide approximations for thin and thick insulator
layers sandwiched between metallic layers. In the case of very thin dielectric
layer, the surface waves on both interfaces are strongly coupled resulting in
an almost linear dependence of the impedance of the plasmonic transmission line
on the thickness of the insulator layer. On the other hand, for very thick
insulator layer, the impedance does not vary with the insulator layer thickness
due to the weak-coupling/decoupling of the surface waves on each
metal-insulator interface. We demonstrate the effectiveness of our proposed
formulation using two test scenarios, namely, almost zero reflection in
Tee-junction and reflection from line discontinuity in the design of Bragg
reflectors, where we compare our formulation against previously published
results.


title: Learnable Pooling Regions for Image Classification

abstract:
  Biologically inspired, from the early HMAX model to Spatial Pyramid Matching,
pooling has played an important role in visual recognition pipelines. Spatial
pooling, by grouping of local codes, equips these methods with a certain degree
of robustness to translation and deformation yet preserving important spatial
information. Despite the predominance of this approach in current recognition
systems, we have seen little progress to fully adapt the pooling strategy to
the task at hand. This paper proposes a model for learning task dependent
pooling scheme -- including previously proposed hand-crafted pooling schemes as
a particular instantiation. In our work, we investigate the role of different
regularization terms showing that the smooth regularization term is crucial to
achieve strong performance using the presented architecture. Finally, we
propose an efficient and parallel method to train the model. Our experiments
show improved performance over hand-crafted pooling schemes on the CIFAR-10 and
CIFAR-100 datasets -- in particular improving the state-of-the-art to 56.29% on
the latter.


title: Galactic Escape Speeds in Mirror and Cold Dark Matter Models

abstract:
  The mirror dark matter (MDM) model of Berezhiani et al. has been shown to
reproduce observed galactic rotational curves for a variety of spiral galaxies,
and has been presented as an alternative to cold dark matter (CDM) models. We
investigate possible additional tests involving the properties of stellar
orbits, which may be used to discriminate between the two models. We
demonstrate that in MDM and CDM models fitted equally well to a galactic
rotational curve, one generally expects predictable differences in escape
speeds from the disc. The recent radial velocity (RAVE) survey of the Milky Way
has pinned down the escape speed from the solar neighbourhood to
$v_{esc}=544^{+64}_{-46}$ km s$^{-1}$, placing an additional constraint on dark
matter models. We have constructed an MDM model for the Milky Way based on its
rotational curve, and find an escape speed that is just consistent with the
observed value given the current errors, which lends credence to the viability
of the MDM model. The Gaia-ESO spectroscopic survey is expected to lead to an
even more precise estimate of the escape speed that will further constrain dark
matter models. However, the largest differences in stellar escape speeds
between both models are predicted for dark matter dominated dwarf galaxies such
as DDO 154, and kinematical studies of such galaxies could prove key in
establishing, or abolishing, the validity of the MDM model.


title: On the nature of the Tsallis-Fourier Transform

abstract:
  By recourse to tempered ultradistributions, we show here that the effect of a
q-Fourier transform (qFT) is to map {\it equivalence classes} of functions into
other classes in a one-to-one fashion. This suggests that Tsallis' q-statistics
may revolve around equivalence classes of distributions and not on individual
ones, as orthodox statistics does. We solve here the qFT's non-invertibility
issue, but discover a problem that remains open.


title: Giant gravitons: a collective coordinate approach

abstract:
  In this paper I describe a collective coordinate approach to the study of
giant graviton states and their excitations in various field theories. The
method simplifies considerably the understanding of emergent gauge symmetry of
these configurations, as well as the calculation of the spectrum of strings
stretched between the giant gravitons. There is a limit where these results
reproduce the one loop dispersion relation for giant magnons. I also show that
this method gives rise to a simple geometric interpretation of a Higgs
mechanism for the emergent gauge symmetry which parallels the holographic dual
realization of these sates: the effective Higgs condensate is the geometric
separation of D-branes in the collective coordinate geometry.


title: Bounds on free energy in QCD

abstract:
  We derive some exact bounds on the free energy $W(J)$ in QCD, where $J_\mu^b$
is a source for the gluon field $A_\mu^b$ in the minimal Landau gauge, and
$W(J)$ is the generating functional of connected gluon correlators. Among other
results, we show that for a static source $J(x) = h$ the free energy vanishes,
$W(h) = 0$, together with its first derivative, ${\partial W(h) \over \partial
h} = 0,$ for all $h$, no matter how strong. Thus the system does not respond to
a static color probe. We also present numerical evaluations of the free energy
$W(J)$ and find that the bounds are well satisfied and in fact undersaturated.


title: Escape rates for rotor walk in Z^d

abstract:
  Rotor walk is a deterministic analogue of random walk. We study its
recurrence and transience properties on Z^d for the initial configuration of
all rotors aligned. If n particles in turn perform rotor walks starting from
the origin, we show that the number that escape (i.e., never return to the
origin) is of order n in dimensions d>=3, and of order n/log(n) in dimension 2.


title:
The Interplanetary Network Supplement to the Fermi GBM Catalog of Cosmic
  Gamma-Ray Bursts

abstract:
  We present Interplanetary Network (IPN) data for the gamma-ray bursts in the
first Fermi Gamma-Ray Burst Monitor (GBM) catalog. Of the 491 bursts in that
catalog, covering 2008 July 12 to 2010 July 11, 427 were observed by at least
one other instrument in the 9-spacecraft IPN. Of the 427, the localizations of
149 could be improved by arrival time analysis (or triangulation). For any
given burst observed by the GBM and one other distant spacecraft, triangulation
gives an annulus of possible arrival directions whose half-width varies between
about 0.4' and 32 degrees, depending on the intensity, time history, and
arrival direction of the burst, as well as the distance between the spacecraft.
We find that the IPN localizations intersect the 1 sigma GBM error circles in
only 52% of the cases, if no systematic uncertainty is assumed for the latter.
If a 6 degree systematic uncertainty is assumed and added in quadrature, the
two localization samples agree about 87% of the time, as would be expected. If
we then multiply the resulting error radii by a factor of 3, the two samples
agree in slightly over 98% of the cases, providing a good estimate of the GBM 3
sigma error radius. The IPN 3 sigma error boxes have areas between about 1
square arcminute and 110 square degrees, and are, on the average, a factor of
180 smaller than the corresponding GBM localizations. We identify two bursts in
the IPN/GBM sample that did not appear in the GBM catalog. In one case, the GBM
triggered on a terrestrial gamma flash, and in the other, its origin was given
as uncertain. We also discuss the sensitivity and calibration of the IPN.


title: Penalized Regression Models for the NBA

abstract:
  In the National Basketball Association (NBA), teams must make choices about
which players to acquire, how much to pay them, and other decisions that are
fundamentally dependent on player effectiveness. Thus, there is great interest
in quantitatively understanding the impact of each player. In this paper we
develop a new penalized regression model for the NBA, use cross-validation to
select its tuning parameters, and then use it to produce ratings of player
ability. We then apply the model to the 2010-2011 NBA season to predict the
outcome of games. We compare the performance of our procedure to other known
regression techniques for this problem, and demonstrate empirically that our
model produces substantially better predictions. We evaluate the performance of
our procedure against the Las Vegas gambling lines, and show that with a
sufficiently large number of games to train on our model outperforms those
lines. Finally, we demonstrate how the technique developed in this paper can be
used to quantitively identify "overrated" players who are less impactful than
common wisdom might suggest.


title:
How good is the Electricity benchmark for evaluating concept drift
  adaptation

abstract:
  In this correspondence, we will point out a problem with testing adaptive
classifiers on autocorrelated data. In such a case random change alarms may
boost the accuracy figures. Hence, we cannot be sure if the adaptation is
working well.


title: On the Analytic Structure of Scalar Glueball Operators

abstract:
  The correlator of the square of the Yang-Mills field-strength tensor
corresponds to a scalar glueball, i.e., to a bound-state formed by gluonic
ingredients only. It has quantum numbers 0++ and its mass, as predicted by
different theoretical approaches, is expected to lie between 1 and 2 GeV. Here
we restrict our considerations to the Born level, that is, we consider the
correlator to zeroth order in the coupling. Gluonic self-interaction is taken
into account indirectly by using non-perturbative gluon propagators. The
employed closed expressions are motivated by lattice and Dyson-Schwinger
studies. The analytic continuation of the integrals themselves is complicated
by additional obstructive structures like branch cuts and poles that are
induced by the inner integral in the complex plane of the outer integration
variable. We deal with this problem by deforming the outer integration contour
accordingly. For different input gluon propagators we find a positive glueball
spectral density which is required for physical states. Poles are, however,
absent which is most likely an artifact of working at Born level.


title:
The geometric approach to quantum correlations: Computability versus
  reliability

abstract:
  We propose a modified metric based on the Hilbert-Schmidt norm and adopt it
to define a rescaled version of the geometric measure of quantum discord. Such
a measure is found not to suffer from the pathological dependence on state
purity. Although the employed metric is still noncontractive under quantum
operations, we show that the resulting indicator of quantum correlations is in
agreement with other bona fide discord measures in a number of physical
examples. We present a critical assessment of the requirements of reliability
versus computability when approaching the task of quantifying, or measuring,
general quantum correlations in a bipartite state.

categories: quant-ph cond-mat.stat-mech math-ph math.MP


title: Block Coordinate Descent for Sparse NMF

abstract:
  Nonnegative matrix factorization (NMF) has become a ubiquitous tool for data
analysis. An important variant is the sparse NMF problem which arises when we
explicitly require the learnt features to be sparse. A natural measure of
sparsity is the L$_0$ norm, however its optimization is NP-hard. Mixed norms,
such as L$_1$/L$_2$ measure, have been shown to model sparsity robustly, based
on intuitive attributes that such measures need to satisfy. This is in contrast
to computationally cheaper alternatives such as the plain L$_1$ norm. However,
present algorithms designed for optimizing the mixed norm L$_1$/L$_2$ are slow
and other formulations for sparse NMF have been proposed such as those based on
L$_1$ and L$_0$ norms. Our proposed algorithm allows us to solve the mixed norm
sparsity constraints while not sacrificing computation time. We present
experimental evidence on real-world datasets that shows our new algorithm
performs an order of magnitude faster compared to the current state-of-the-art
solvers optimizing the mixed norm and is suitable for large-scale datasets.


title:
An Efficient Sufficient Dimension Reduction Method for Identifying
  Genetic Variants of Clinical Significance

abstract:
  Fast and cheaper next generation sequencing technologies will generate
unprecedentedly massive and highly-dimensional genomic and epigenomic variation
data. In the near future, a routine part of medical record will include the
sequenced genomes. A fundamental question is how to efficiently extract genomic
and epigenomic variants of clinical utility which will provide information for
optimal wellness and interference strategies. Traditional paradigm for
identifying variants of clinical validity is to test association of the
variants. However, significantly associated genetic variants may or may not be
usefulness for diagnosis and prognosis of diseases. Alternative to association
studies for finding genetic variants of predictive utility is to systematically
search variants that contain sufficient information for phenotype prediction.
To achieve this, we introduce concepts of sufficient dimension reduction and
coordinate hypothesis which project the original high dimensional data to very
low dimensional space while preserving all information on response phenotypes.
We then formulate clinically significant genetic variant discovery problem into
sparse SDR problem and develop algorithms that can select significant genetic
variants from up to or even ten millions of predictors with the aid of dividing
SDR for whole genome into a number of subSDR problems defined for genomic
regions. The sparse SDR is in turn formulated as sparse optimal scoring
problem, but with penalty which can remove row vectors from the basis matrix.
To speed up computation, we develop the modified alternating direction method
for multipliers to solve the sparse optimal scoring problem which can easily be
implemented in parallel. To illustrate its application, the proposed method is
applied to simulation data and the NHLBI's Exome Sequencing Project dataset


title: Discrete Restricted Boltzmann Machines

abstract:
  We describe discrete restricted Boltzmann machines: probabilistic graphical
models with bipartite interactions between visible and hidden discrete
variables. Examples are binary restricted Boltzmann machines and discrete naive
Bayes models. We detail the inference functions and distributed representations
arising in these models in terms of configurations of projected products of
simplices and normal fans of products of simplices. We bound the number of
hidden variables, depending on the cardinalities of their state spaces, for
which these models can approximate any probability distribution on their
visible states to any given accuracy. In addition, we use algebraic methods and
coding theory to compute their dimension.


title:
The Neural Representation Benchmark and its Evaluation on Brain and
  Machine

abstract:
  A key requirement for the development of effective learning representations
is their evaluation and comparison to representations we know to be effective.
In natural sensory domains, the community has viewed the brain as a source of
inspiration and as an implicit benchmark for success. However, it has not been
possible to directly test representational learning algorithms directly against
the representations contained in neural systems. Here, we propose a new
benchmark for visual representations on which we have directly tested the
neural representation in multiple visual cortical areas in macaque (utilizing
data from [Majaj et al., 2012]), and on which any computer vision algorithm
that produces a feature space can be tested. The benchmark measures the
effectiveness of the neural or machine representation by computing the
classification loss on the ordered eigendecomposition of a kernel matrix
[Montavon et al., 2011]. In our analysis we find that the neural representation
in visual area IT is superior to visual area V4. In our analysis of
representational learning algorithms, we find that three-layer models approach
the representational performance of V4 and the algorithm in [Le et al., 2012]
surpasses the performance of V4. Impressively, we find that a recent supervised
algorithm [Krizhevsky et al., 2012] achieves performance comparable to that of
IT for an intermediate level of image variation difficulty, and surpasses IT at
a higher difficulty level. We believe this result represents a major milestone:
it is the first learning algorithm we have found that exceeds our current
estimate of IT representation performance. We hope that this benchmark will
assist the community in matching the representational performance of visual
cortex and will serve as an initial rallying point for further correspondence
between representations derived in brains and machines.


title:
On dynamic spectral risk measures, a limit theorem and optimal portfolio
  allocation

abstract:
  In this paper we propose the notion of continuous-time dynamic spectral
risk-measure (DSR). Adopting a Poisson random measure setting, we define this
class of dynamic coherent risk-measures in terms of certain backward stochastic
differential equations. By establishing a functional limit theorem, we show
that DSRs may be considered to be (strongly) time-consistent continuous-time
extensions of iterated spectral risk-measures, which are obtained by iterating
a given spectral risk-measure (such as Expected Shortfall) along a given
time-grid. Specifically, we demonstrate that any DSR arises in the limit of a
sequence of such iterated spectral risk-measures driven by lattice-random
walks, under suitable scaling and vanishing time- and spatial-mesh sizes. To
illustrate its use in financial optimisation problems, we analyse a dynamic
portfolio optimisation problem under a DSR.


title:
Order-v^4 Relativistic Corrections to Gluon Fragmentation into ^3S_1
  Quarkonium

abstract:
  We compute the relativistic corrections to the color-singlet contribution to
gluon fragmentation into a J/psi at relative order v^4, making use of the
nonrelativistic QCD (NRQCD) factorization approach. The corresponding full-QCD
process exhibits infrared divergences that manifest themselves as single and
double poles in epsilon in 4-2epsilon dimensions. We isolate the
infrared-divergent contributions and treat them analytically. In the matching
of full QCD to NRQCD, the pole contributions are absorbed into long-distance
NRQCD matrix elements. The renormalizations of the ultraviolet divergences of
the long-distance NRQCD matrix elements involve Born and one-loop single-pole
counterterm contributions and Born double-pole counterterm contributions. While
the order-v^4 contribution enhances the J/psi hadroproduction rate for the
color-singlet channel substantially, this contribution is not important
numerically in comparison with the color-octet contributions. We also find that
the ^3P_J color-octet channel in the gluon fragmentation function contributes
to J/psi hadroproduction significantly in comparison with the complete
contribution of next-to-leading order in alpha_s in that channel.


title: Sparse Penalty in Deep Belief Networks: Using the Mixed Norm Constraint

abstract:
  Deep Belief Networks (DBN) have been successfully applied on popular machine
learning tasks. Specifically, when applied on hand-written digit recognition,
DBNs have achieved approximate accuracy rates of 98.8%. In an effort to
optimize the data representation achieved by the DBN and maximize their
descriptive power, recent advances have focused on inducing sparse constraints
at each layer of the DBN. In this paper we present a theoretical approach for
sparse constraints in the DBN using the mixed norm for both non-overlapping and
overlapping groups. We explore how these constraints affect the classification
accuracy for digit recognition in three different datasets (MNIST, USPS, RIMES)
and provide initial estimations of their usefulness by altering different
parameters such as the group size and overlap percentage.


title: The Life and Times of the Parkes-Tidbinbilla Interferometer

abstract:
  The Parkes-Tidbinbilla took advantage of a real-time radio-link connecting
the Parkes and Tidbinbilla antennas to form the world's longest real-time
interferometer. Built on a minuscule budget, it was an extraordinarily
successful instrument, generating some 24 journal papers including 3 Nature
papers, as well as facilitating the early development of the Australia
Telescope Compact Array. Here we describe its origins, construction, successes,
and life cycle, and discuss the future use of single-baseline interferometers
in the era of SKA and its pathfinders.


title: Airport Gate Scheduling for Passengers, Aircraft, and Operation

abstract:
  Passengers' experience is becoming a key metric to evaluate the air
transportation system's performance. Efficient and robust tools to handle
airport operations are needed along with a better understanding of passengers'
interests and concerns. Among various airport operations, this paper studies
airport gate scheduling for improved passengers' experience. Three objectives
accounting for passengers, aircraft, and operation are presented. Trade-offs
between these objectives are analyzed, and a balancing objective function is
proposed. The results show that the balanced objective can improve the
efficiency of traffic flow in passenger terminals and on ramps, as well as the
robustness of gate operations.


title:
Weak stabilization of a transmission Euler-Bernoulli plate equation with
  force and moment feedback

abstract:
  In this paper we will study the asymptotic behaviour of the energy decay of a
transmission plate equation with force and moment feedback. Precisly, we shall
prove that the energy decay at least logarithmically over the time. The method
consist to use the classical second order Carleman estimate to estabish a
resolvent estimate which provide by the famous Burq's result [Bur98] the kind
of decay above mentionned.


title:
Learning Stable Group Invariant Representations with Convolutional
  Networks

abstract:
  Transformation groups, such as translations or rotations, effectively express
part of the variability observed in many recognition problems. The group
structure enables the construction of invariant signal representations with
appealing mathematical properties, where convolutions, together with pooling
operators, bring stability to additive and geometric perturbations of the
input. Whereas physical transformation groups are ubiquitous in image and audio
applications, they do not account for all the variability of complex signal
classes.
  We show that the invariance properties built by deep convolutional networks
can be cast as a form of stable group invariance. The network wiring
architecture determines the invariance group, while the trainable filter
coefficients characterize the group action. We give explanatory examples which
illustrate how the network architecture controls the resulting invariance
group. We also explore the principle by which additional convolutional layers
induce a group factorization enabling more abstract, powerful invariant
representations.


title: Ordering and criticality in an underscreened Kondo chain

abstract:
  Motivated by the nickel valence controversy in the perovskite nickelate
RNiO_3, we consider a one-dimensional underscreened Kondo chain consisting of
alternating spin-1 ("nickel") and electron ("oxygen") sites, which in addition
to the usual electron hopping and spin-spin interaction between the S=1 spin
and the electron also contains a spin mediated electron hopping term. Using the
density-matrix renormalization group (DMRG), we obtained the zero temperature
phase diagram of the model, as well as various correlation functions in each
phase. Importantly, for a certain range of parameters the model exhibits a
quasi-long-range spiral (QS) order. To understand the DMRG results, we
construct a mean-field theory based on a Schwinger fermion decomposition of the
S=1 spins, from which we argue that the QS phase corresponds to a phase in
proximity to the spin Bose metal state proposed by D. N. Sheng, O. I.
Motrunich, and M. P. A. Fisher [Phys. Rev. B 79, 205112 (2009)]. Notably, we
find no evidence for a phase with the symmetry of "nickel"-centered charge
order, which has been argued to arise due to site-selective Kondo screening of
half the S=1 spins, and suggest that order of this type occurs only due to an
additional energy gain from spontaneous lattice distortions, not present in
this model.


title:
Learning Features with Structure-Adapting Multi-view Exponential Family
  Harmoniums

abstract:
  We proposea graphical model for multi-view feature extraction that
automatically adapts its structure to achieve better representation of data
distribution. The proposed model, structure-adapting multi-view harmonium
(SA-MVH) has switch parameters that control the connection between hidden nodes
and input views, and learn the switch parameter while training. Numerical
experiments on synthetic and a real-world dataset demonstrate the useful
behavior of the SA-MVH, compared to existing multi-view feature extraction
methods.


title: Ordered-Current State of Electrons in Bilayer Graphene

abstract:
  Based on the four-band continuum model, we study the ordered-current state
(OCS) for electrons in bilayer graphene at the charge neutrality point. The
present work resolves the puzzles that (a) the energy gap increases
significantly with increasing the magnetic field $B$, (b) the energy gap can be
closed by the external electric field of either polarization, and (c) the
particle-hole spectrum is asymmetric in the presence of $B$, all these as
observed by the experiment. We also present the prediction of the hysteresis
energy gap behavior with varying $B$, which explains the existing experimental
observation on the electric conductance at weak $B$. The large energy gap of
the OCS is shown to originate from the disappearance of Landau levels of $n$ =
0 and 1 states in conduction/valence band. By comparing with the existing
models and the experiments, we conclude that the OCS is a possible ground state
of electrons in bilayer graphene.


title: Deep Predictive Coding Networks

abstract:
  The quality of data representation in deep learning methods is directly
related to the prior model imposed on the representations; however, generally
used fixed priors are not capable of adjusting to the context in the data. To
address this issue, we propose deep predictive coding networks, a hierarchical
generative model that empirically alters priors on the latent representations
in a dynamic and context-sensitive manner. This model captures the temporal
dependencies in time-varying signals and uses top-down information to modulate
the representation in lower layers. The centerpiece of our model is a novel
procedure to infer sparse states of a dynamic model which is used for feature
extraction. We also extend this feature extraction block to introduce a pooling
function that captures locally invariant representations. When applied on a
natural video data, we show that our method is able to learn high-level visual
features. We also demonstrate the role of the top-down connections by showing
the robustness of the proposed model to structured noise.


title:
Assignment of the NV0 575 nm zero-phonon line in diamond to a 2E-2A2
  transition

abstract:
  The time-averaged emission spectrum of single nitrogen-vacancy defects in
diamond gives zero-phonon lines of both the negative charge state at 637 nm
(1.945 eV) and the neutral charge state at 575 nm (2.156 eV). This occurs
through photo-conversion between the two charge states. Due to strain in the
diamond the zero-phonon lines are split and it is found that the splitting and
polarization of the two zero-phonon lines are the same. From this observation
and consideration of the electronic structure of the nitrogen-vacancy center it
is concluded that the excited state of the neutral center has A2 orbital
symmetry. The assignment of the 575 nm transition to a 2E - 2A2 transition has
not been established previously.


title: Event-driven Molecular Dynamics of Soft Particles

abstract:
  The dynamics of dissipative soft-sphere gases obeys Newton's equation of
motion which are commonly solved numerically by (force-based) Molecular
Dynamics schemes. With the assumption of instantaneous, pairwise collisions,
the simulation can be accelerated considerably using event-driven Molecular
Dynamics, where the coefficient of restitution is derived from the interaction
force between particles. Recently it was shown, however, that this approach may
fail dramatically, that is, the obtained trajectories deviate significantly
from the ones predicted by Newton's equations. In this paper, we generalize the
concept of the coefficient of restitution and derive a numerical scheme which,
in the case of dilute systems and frictionless interaction, allows us to
perform highly efficient event-driven Molecular Dynamics simulations even for
non-instantaneous collisions. We show that the particle trajectories predicted
by the new scheme agree perfectly with the corresponding (force-based)
Molecular Dynamics, except for a short transient period whose duration
corresponds to the duration of the contact. Thus, the new algorithm solves
Newton's equations of motion like force-based MD while preserving the
advantages of event-driven simulations.


title:
Non-Abelian Quasi-Gapless Modes Localized on Mass Vortices in Superfluid
  3He-B

abstract:
  Kelvin waves or Kelvons have been known for a long time as gapless
excitations propagating along superfluid vortices. These modes can be
interpreted as the Nambu-Goldstone excitations arising from the spontaneous
breaking of the translational symmetry. Recently a different type of gapless
excitation localized on strings -- the so-called non-Abelian mode -- attracted
much attention in high-energy physics. We discuss their relevance in condensed
matter physics. Although we failed to find exactly gapless non-Abelian modes,
non-Abelian rotational quasigapless excitations are argued to exist on the mass
vortices in the B phase of the superfluid 3He, due to the fact that the order
parameter in 3He-B is tensorial. While the U(1) rotational excitations are well
established in vortices with asymmetric cores, the non-Abelian rotational
excitations belonging to the same family were not considered. In the general
case they are coupled with the translational modes.


title: Metric-Free Natural Gradient for Joint-Training of Boltzmann Machines

abstract:
  This paper introduces the Metric-Free Natural Gradient (MFNG) algorithm for
training Boltzmann Machines. Similar in spirit to the Hessian-Free method of
Martens [8], our algorithm belongs to the family of truncated Newton methods
and exploits an efficient matrix-vector product to avoid explicitely storing
the natural gradient metric $L$. This metric is shown to be the expected second
derivative of the log-partition function (under the model distribution), or
equivalently, the variance of the vector of partial derivatives of the energy
function. We evaluate our method on the task of joint-training a 3-layer Deep
Boltzmann Machine and show that MFNG does indeed have faster per-epoch
convergence compared to Stochastic Maximum Likelihood with centering, though
wall-clock performance is currently not competitive.


title:
Analysis of a model arising from invasion by precursor and
  differentiated cells

abstract:
  We study the wave solutions for a degenerated reaction diffusion system
arising from the invasion of cells. We show that there exists a family of waves
for the wave speed larger than or equals a certain number, and below which
there is no monotonic wave solutions. We also investigate the monotonicity,
uniqueness and asymptotics of the waves.


title: A Rhetorical Analysis Approach to Natural Language Processing

abstract:
  The goal of this research was to find a way to extend the capabilities of
computers through the processing of language in a more human way, and present
applications which demonstrate the power of this method. This research presents
a novel approach, Rhetorical Analysis, to solving problems in Natural Language
Processing (NLP). The main benefit of Rhetorical Analysis, as opposed to
previous approaches, is that it does not require the accumulation of large sets
of training data, but can be used to solve a multitude of problems within the
field of NLP. The NLP problems investigated with Rhetorical Analysis were the
Author Identification problem - predicting the author of a piece of text based
on its rhetorical strategies, Election Prediction - predicting the winner of a
presidential candidate's re-election campaign based on rhetorical strategies
within that president's inaugural address, Natural Language Generation - having
a computer produce text containing rhetorical strategies, and Document
Summarization. The results of this research indicate that an Author
Identification system based on Rhetorical Analysis could predict the correct
author 100% of the time, that a re-election predictor based on Rhetorical
Analysis could predict the correct winner of a re-election campaign 55% of the
time, that a Natural Language Generation system based on Rhetorical Analysis
could output text with up to 87.3% similarity to Shakespeare in style, and that
a Document Summarization system based on Rhetorical Analysis could extract
highly relevant sentences. Overall, this study demonstrated that Rhetorical
Analysis could be a useful approach to solving problems in NLP.


title: Other neutrino oscillation measurements

abstract:
  Neutrino oscillation results from several experiments and sources are
discussed. Recent results from solar neutrino measurements by Super-Kamiokande
and Borexino, atmospheric neutrino measurements from Super-Kamiokande, and
accelerator neutrino measurements by MINOS and OPERA are the main topics of
this document.


title: Electronic analogy of Goos-H\"{a}nchen effect: a review

abstract:
  The analogies between optical and electronic Goos-H\"{a}nchen effects are
established based on electron wave optics in semiconductor or graphene-based
nanostructures. In this paper, we give a brief overview of the progress
achieved so far in the field of electronic Goos-H\"{a}nchen shifts, and show
the relevant optical analogies. In particular, we present several theoretical
results on the giant positive and negative Goos-H\"{a}nchen shifts in various
semiconductor or graphen-based nanostructures, their controllability, and
potential applications in electronic devices, e.g. spin (or valley) beam
splitters.


title: Drinfeld realization of quantum twisted affine algebras via braid group

abstract:
  The Drinfled realization of quantum affine algebras has been tremendously
useful since its discovery. Combining techniques of Beck and Nakajima with our
previous approach, we give a complete and conceptual proof of the Drinfeld
realization for the twisted quantum affine algebras using Lusztig's twisted
braid group action.


title: Information Theoretic Learning with Infinitely Divisible Kernels

abstract:
  In this paper, we develop a framework for information theoretic learning
based on infinitely divisible matrices. We formulate an entropy-like functional
on positive definite matrices based on Renyi's axiomatic definition of entropy
and examine some key properties of this functional that lead to the concept of
infinite divisibility. The proposed formulation avoids the plug in estimation
of density and brings along the representation power of reproducing kernel
Hilbert spaces. As an application example, we derive a supervised metric
learning algorithm using a matrix based analogue to conditional entropy
achieving results comparable with the state of the art.


title:
Negative Imaginary Systems Theory in the Robust Control of Highly
  Resonant Flexible Structures

abstract:
  This paper covers recent developments in the theory of negative imaginary
systems and their application to the control of highly resonant flexible
structures. The theory of negative imaginary systems arose out of a desire to
unify a number of classical methods for the control of lightly damped
structures with collocated force actuators and position sensors including
positive position feedback and integral force feedback. The key result is a
stability result which shows why these methods are guaranteed to yield robust
closed loop stability in the face of unmodelled spillover dynamics. Related
results to be presented connect the theory of negative imaginary systems to
positive real systems theory and a negative imaginary lemma has been
established which is analogous to the positive real lemma. The paper also
presents recent controller synthesis results based on the theory of negative
imaginary systems.


title:
Glassy dynamics and Landau-Zener phenomena in trapped quasi-one
  dimensional coupled Bose-Einstein condensates

abstract:
  The purpose of this article is to address the dynamics of an interacting
Bose-Einstein condensate confined in coupled one-dimensional Landau-Zener
arrays under the influence of disorder and harmonic confinement. In particular,
we concentrate in studying the interplay of disorder and interparticle
interaction on the transfer of atoms depending on the speed of Landau-Zener
sweeps. A dynamical phase diagram summarizing the final situation across ground
state and inverse sweeps is given in terms of the effect of disorder,
interaction and the speed of the sweeps.


title:
Sharp bounds in terms of the power of the contra-harmonic mean for
  Neuman-Sandor mean

abstract:
  In the paper, the authors obtain sharp bounds in terms of the power of the
contra-harmonic mean for Neuman-S\'andor mean.


title:
Exploring tidal effects of coalescing binary neutron stars in numerical
  relativity

abstract:
  We study gravitational waves emitted in the late inspiral stage of binary
neutron stars by analyzing the waveform obtained in numerical-relativity
simulations. For deriving the physical gravitational waveforms from the
numerical results, the resolution extrapolation plays an essential role for our
simulations. The extrapolated gravitational-wave phases are compared with those
calculated in the post-Newtonian (PN) and effective-one-body (EOB) formalisms
including corrections of tidal effects. We show that the extrapolated
gravitational-wave phases in numerical relativity agree well with those by the
PN and EOB calculations for most of the inspiral stage except for a
tidally-dominated, final inspiral stage, in which the PN and EOB results
underestimate the tidal effects. Nevertheless, the accumulated phase difference
between our extrapolated results and the results by the PN/EOB calculations is
at most 1--3 radian in the last 15 cycles.


title:
Multi-integral representations for associated Legendre and Ferrers
  functions

abstract:
  For the associated Legendre and Ferrers functions of the first and second
kind, we obtain new multi-derivative and multi-integral representation
formulas. The multi-integral representation formulas that we derive for these
functions generalize some classical multi-integration formulas. As a result of
the determination of these formulae, we compute some interesting special values
and integral representations for certain particular combinations of the degree
and order including the case where there is symmetry and antisymmetry for the
degree and order parameters. As a consequence of our analysis, we obtain some
new results for the associated Legendre function of the second kind including
parameter values for which this function is identically zero.


title:
Stochastic Pooling for Regularization of Deep Convolutional Neural
  Networks

abstract:
  We introduce a simple and effective method for regularizing large
convolutional neural networks. We replace the conventional deterministic
pooling operations with a stochastic procedure, randomly picking the activation
within each pooling region according to a multinomial distribution, given by
the activities within the pooling region. The approach is hyper-parameter free
and can be combined with other regularization approaches, such as dropout and
data augmentation. We achieve state-of-the-art performance on four image
datasets, relative to other approaches that do not utilize data augmentation.


title: Model Selection for Gaussian Mixture Models

abstract:
  This paper is concerned with an important issue in finite mixture modelling,
the selection of the number of mixing components. We propose a new penalized
likelihood method for model selection of finite multivariate Gaussian mixture
models. The proposed method is shown to be statistically consistent in
determining of the number of components. A modified EM algorithm is developed
to simultaneously select the number of components and to estimate the mixing
weights, i.e. the mixing probabilities, and unknown parameters of Gaussian
distributions. Simulations and a real data analysis are presented to illustrate
the performance of the proposed method.


title: Separation of variables in an asymmetric cyclidic coordinate system

abstract:
  A global analysis is presented of solutions for Laplace's equation on
three-dimensional Euclidean space in one of the most general orthogonal
asymmetric confocal cyclidic coordinate systems which admit solutions through
separation of variables. We refer to this coordinate system as five-cyclide
coordinates since the coordinate surfaces are given by two cyclides of genus
zero which represent the inversion at the unit sphere of each other, a cyclide
of genus one, and two disconnected cyclides of genus zero. This coordinate
system is obtained by stereographic projection of sphero-conal coordinates on
four-dimensional Euclidean space. The harmonics in this coordinate system are
given by products of solutions of second-order Fuchsian ordinary differential
equations with five elementary singularities. The Dirichlet problem for the
global harmonics in this coordinate system is solved using multiparameter
spectral theory in the regions bounded by the asymmetric confocal cyclidic
coordinate surfaces.


title:
Complexity of Representation and Inference in Compositional Models with
  Part Sharing

abstract:
  This paper describes serial and parallel compositional models of multiple
objects with part sharing. Objects are built by part-subpart compositions and
expressed in terms of a hierarchical dictionary of object parts. These parts
are represented on lattices of decreasing sizes which yield an executive
summary description. We describe inference and learning algorithms for these
models. We analyze the complexity of this model in terms of computation time
(for serial computers) and numbers of nodes (e.g., "neurons") for parallel
computers. In particular, we compute the complexity gains by part sharing and
its dependence on how the dictionary scales with the level of the hierarchy. We
explore three regimes of scaling behavior where the dictionary size (i)
increases exponentially with the level, (ii) is determined by an unsupervised
compositional learning algorithm applied to real data, (iii) decreases
exponentially with scale. This analysis shows that in some regimes the use of
shared parts enables algorithms which can perform inference in time linear in
the number of levels for an exponential number of objects. In other regimes
part sharing has little advantage for serial computers but can give linear
processing on parallel computers.


title:
Conventional superconductivity and hysteretic Campbell penetration depth
  in single crystals MgCNi$_3$

abstract:
  Single crystals of MgCNi$_3$, with areas sized up to 1 mm$^{2}$, were grown
by the self flux method using a cubic anvil high pressure technique. The first
critical field \textit{H$_{c1}$}, determined from a zero temperature
extrapolation, is around 18 mT. Using the tunnel - diode resonator technique,
the London penetration depth was measured with no applied \textit{dc} field and
the Campbell penetration depth was measured with the external \textit{dc}
fields up to 9T for two different sample orientations with respect to the
direction of applied magnetic field. The absolute value of the London
penetration depth, $\lambda(0) = 245 \pm 10$ nm was determined from the
thermodynamic Rutgers formula. The superfluid density,
$\rho_s=(\lambda(0)/\lambda(T))^2$ was found to follow the clean isotropic
\textit{s}-wave behavior predicted by the weak - coupling BCS theory in the
whole temperature range. The low - temperature behavior of the London
penetration depth fits the BCS analytic form as well and produces close to the
weak - coupling value of $\Delta (0)/k_BT_c = 1.71$. The temperature dependence
of the upper critical field, \textit{$H_{c2}$}, was found to be isotropic with
a slope at \textit{T$_c$} of -2.63 T/K and \textit{H$_{c2}$}(0) $\approx$ 12.3
T at zero temperature. The Campbell penetration depth probes the vortex lattice
response in the mixed state and is sensitive to the details of the pinning
potential. For MgCNi$_3$, an irreversible feature has been observed in the TDR
response when the sample is field-cooled and warmed versus zero-field-cooled
and warmed. This feature possesses a non-monotonic field dependence and has
commonly been referred to as the peak effect and is most likely related to a
field - dependent non - parabolic pinning potential.


title:
On deriving flux freezing in magnetohydrodynamics by direct
  differentiation

abstract:
  The magnetic flux freezing theorem or Alfv\'en's theorem, is a basic
principle of ideal magnetohydrodynamics (MHD), a commonly used approximation to
describe the aspects of astrophysical and laboratory plasmas. The theorem
states that the magnetic flux---the integral of magnetic field penetrating a
surface---is conserved in time as that surface is distorted in in time by fluid
motions. Pedagogues of MHD commonly derive flux freezing without showing how to
take the material derivative of a general flux integral and/or assuming a
vanishing field divergence from the outset. Here I avoid these shortcomings and
derive flux freezing by direct differentiation, explicitly using a Jacobian to
transform between the evolving field-penetrating surface at different times.
The approach is instructive for its generality and helps elucidate the role of
magnetic monopoles in breaking flux freezing. The paucity of appearances of
this derivation in standard MHD texts suggests that its pedagogic value is
underappreciated.


title:
Dirichlet series associated to cubic fields with given quadratic
  resolvent

abstract:
  Let k be a quadratic field. We give an explicit formula for the Dirichlet
series enumerating cubic fields whose quadratic resolvent field is isomorphic
to k.
  Our work is a sequel to previous work of Cohen and Morra, where such formulas
are proved in a more general setting, in terms of sums over characters of
certain groups related to ray class groups. In the present paper we carry the
analysis further and prove explicit formulas for these Dirichlet series over Q.
In a companion paper we do the same for quartic fields having a given cubic
resolvent.
  As an application (not present in the initial version), we compute tables of
the number of S_3-sextic fields E with |Disc(E)| < X, for X ranging up to
10^23. An accompanying PARI/GP implementation is available from the second
author's website.


title:
Emergent p-wave Kondo Coupling in Multi-Orbital Bands with Mirror
  Symmetry Breaking

abstract:
  We examine Kondo effect in the periodic Anderson model for which the
conduction band is of multi-orbital character and subject to mirror symmetry
breaking field imposed externally. Taking p-orbital-based toy model for
analysis, we find the Kondo pairing symmetry of p-wave character emerges
self-consistently over some regions of parameter space and filling factor even
though only the on-site Kondo hybridization is assumed in the microscopic
Hamiltonian. The band structure in the Kondo-hybridized phase becomes nematic,
with only two-fold symmetry, due to the p-wave Kondo coupling. The reduced
symmetry should be readily observable in spectroscopic or transport
measurements for heavy fermion system in a multilayer environment such as
successfully grown recently.


title:
Vortex lattice solutions to the Gross-Pitaevskii equation with
  spin-orbit coupling in optical lattices

abstract:
  Effective spin-orbit coupling can be created in cold atom systems using
atom-light interaction. We study the BECs in an optical lattice using the
Gross-Pitaevskii equation with spin-orbit coupling. Bloch states for the linear
equation are numerically obtained, and compared with stationary solutions to
the Gross-Pitaevskii equation with nonlinear terms. Various vortex lattice
states are found when the spin-orbit coupling is strong.


title:
Deviation from Universality in Collisions of Ultracold $^6$Li$_2$
  Molecules

abstract:
  Collisions of $^6$Li$_2$ molecules with free $^6$Li atoms reveal a striking
deviation from universal predictions based on long-range van der Waals
interactions. Li$_2$ closed-channel molecules are formed in the highest
vibrational state near a narrow Feshbach resonance, and decay via two-body
collisions with Li$_2$, Li, and Na. For Li$_2$+Li$_2$ and Li$_2$+Na, the decay
rates agree with the universal predictions of the quantum Langevin model. In
contrast, the rate for Li$_2$+Li is exceptionally small, with an upper bound
ten times smaller than the universal prediction. This can be explained by the
low density of available decay states in systems of light atoms [G.
Qu\'em\'ener, J.-M. Launay, and P. Honvault, Phys. Rev. A \textbf{75}, 050701
(2007)], for which such collisions have not been studied before.


title:
Integrable equations with Ermakov-Pinney nonlinearities and Chiellini
  damping

abstract:
  We introduce a special type of dissipative Ermakov-Pinney equations of the
form v_{\zeta \zeta}+g(v)v_{\zeta}+h(v)=0, where h(v)=h_0(v)+cv^{-3} and the
nonlinear dissipation g(v) is based on the corresponding Chiellini integrable
Abel equation. When h_0(v) is a linear function, h_0(v)=\lambda^2v, general
solutions are obtained following the Abel equation route. Based on particular
solutions, we also provide general solutions containing a factor with the phase
of the Milne type. In addition, the same kinds of general solutions are
constructed for the cases of higher-order Reid nonlinearities. The Chiellini
dissipative function is actually a dissipation-gain function because it can be
negative on some intervals. We also examine the nonlinear case
h_0(v)=\Omega_0^2(v-v^2) and show that it leads to an integrable hyperelliptic
case


title: Joint Training Deep Boltzmann Machines for Classification

abstract:
  We introduce a new method for training deep Boltzmann machines jointly. Prior
methods of training DBMs require an initial learning pass that trains the model
greedily, one layer at a time, or do not perform well on classification tasks.
In our approach, we train all layers of the DBM simultaneously, using a novel
training procedure called multi-prediction training. The resulting model can
either be interpreted as a single generative model trained to maximize a
variational approximation to the generalized pseudolikelihood, or as a family
of recurrent networks that share parameters and may be approximately averaged
together using a novel technique we call the multi-inference trick. We show
that our approach performs competitively for classification and outperforms
previous methods in terms of accuracy of approximate inference and
classification with missing inputs.


title: $k$-Schur functions and affine Schubert calculus

abstract:
  This book is an exposition of the current state of research of affine
Schubert calculus and $k$-Schur functions. This text is based on a series of
lectures given at a workshop titled "Affine Schubert Calculus" that took place
in July 2010 at the Fields Institute in Toronto, Ontario. The story of this
research is told in three parts: 1. Primer on $k$-Schur Functions 2. Stanley
symmetric functions and Peterson algebras 3. Affine Schubert calculus


title: A Nested HDP for Hierarchical Topic Models

abstract:
  We develop a nested hierarchical Dirichlet process (nHDP) for hierarchical
topic modeling. The nHDP is a generalization of the nested Chinese restaurant
process (nCRP) that allows each word to follow its own path to a topic node
according to a document-specific distribution on a shared tree. This alleviates
the rigid, single-path formulation of the nCRP, allowing a document to more
easily express thematic borrowings as a random effect. We demonstrate our
algorithm on 1.8 million documents from The New York Times.


title:
Numerical Simulation of Three-Dimensional Dendrites using Coupled Map
  Lattices

abstract:
  Three dimensional dendrites are studied with a coupled map lattice model. We
study the fractal dimensions, the f(\alpha) spectrum, the size distribution of
sidebranches, and the envelope formed by sidebranches.


title: Indoor Semantic Segmentation using depth information

abstract:
  This work addresses multi-class segmentation of indoor scenes with RGB-D
inputs. While this area of research has gained much attention recently, most
works still rely on hand-crafted features. In contrast, we apply a multiscale
convolutional network to learn features directly from the images and the depth
information. We obtain state-of-the-art on the NYU-v2 depth dataset with an
accuracy of 64.5%. We illustrate the labeling of indoor scenes in videos
sequences that could be processed in real-time using appropriate hardware such
as an FPGA.


title:
Symmetry and magnitude of spin-orbit torques in ferromagnetic
  heterostructures

abstract:
  Current-induced spin torques are of great interest to manipulate the
orientation of nanomagnets without applying external magnetic fields. They find
direct application in non-volatile data storage and logic devices, and provide
insight into fundamental processes related to the interdependence between
charge and spin transport. Recent demonstrations of magnetization switching
induced by in-plane current injection in ferromagnetic heterostructures have
drawn attention to a class of spin torques based on orbital-to-spin momentum
transfer, which is alternative to pure spin transfer torque (STT) between
noncollinear magnetic layers and amenable to more diversified device functions.
Due to the limited number of studies, however, there is still no consensus on
the symmetry, magnitude, and origin of spin-orbit torques (SOTs). Here we
report on the quantitative vector measurement of SOTs in Pt/Co/AlO trilayers
using harmonic analysis of the anomalous and planar Hall effects as a function
of the applied current and magnetization direction. We provide an all-purpose
scheme to measure the amplitude and direction of SOTs for any arbitrary
orientation of the magnetization, including corrections due to the interplay of
Hall and thermoelectric effects. Based on general space and time inversion
symmetry arguments, we show that asymmetric heterostructures allow for two
different SOTs having odd and even behavior with respect to magnetization
reversal. Our results reveal a scenario that goes beyond established models of
the Rashba and spin Hall contributions to SOTs. The even SOT is STT-like but
stronger than expected from the spin Hall effect in Pt. The odd SOT is composed
of a constant field-like term and an additional component, which is strongly
anisotropic and does not correspond to a simple Rashba field.


title: Dynamical behavior of disordered spring networks

abstract:
  We study the dynamical rheology of spring networks with a percolation model
constructed by bond dilution in a two-dimensional triangular lattice.
Hydrodynamic interactions are implemented by a Stokesian viscous coupling
between the network nodes and a uniformly deforming liquid. Our simulations
show that in a critical connectivity regime, these systems display weak power
law rheology in which the complex shear modulus scales with frequency as G^* ~
(i * omega)^Delta where Delta = 0.41, in discord with a mean field prediction
of Delta = 1/2. The weak power law rheology in the critical regime can be
understood from a simple scaling relation between the macroscopic rheology and
the nonaffine strain fluctuations, which diverge with vanishing frequency for
isostatic networks. We expand on a dynamic effective medium theory, showing
that it quantitatively describes the rheology of a diluted triangular lattice
far from isostaticity; although the EMT correctly predicts the scaling form for
the rheology of near-isostatic networks, there remains a quantitative disparity
due to the mean-field nature of the EMT. Surprisingly, by connecting this
critical scaling of the rheology with that of the strain fluctuations, we find
that the dynamical behavior of disordered spring networks is fully determined
by the critical exponents that govern the behavior of elastic network in the
absence of viscous interactions.


title:
Kernelized Locality-Sensitive Hashing for Semi-Supervised Agglomerative
  Clustering

abstract:
  Large scale agglomerative clustering is hindered by computational burdens. We
propose a novel scheme where exact inter-instance distance calculation is
replaced by the Hamming distance between Kernelized Locality-Sensitive Hashing
(KLSH) hashed values. This results in a method that drastically decreases
computation time. Additionally, we take advantage of certain labeled data
points via distance metric learning to achieve a competitive precision and
recall comparing to K-Means but in much less computation time.


title: Multipartite Entanglement and Hypergraph states of three qubits

abstract:
  Several entanglement measures are used to define equivalence classes in the
set of hypergraph states of three qubits. Our classifications reveal that (i)
under local unitary transformations, hypergraph states of three qubits are
split into six classes and only one class of them is not equivalent to any
graph state; (ii) under stochastic local operations with classical
communication, for the single copy case hypergraph states of three qubits,
partitioned into five classes which can not be converted into a W state, are
equivalent to graph states; and (iii) when bipartite entanglement in three
qubits considered, hypergraph states of three qubits are split into five
classes and only one class of them has the same entangled graph as the W state.


title: Saturating Auto-Encoders

abstract:
  We introduce a simple new regularizer for auto-encoders whose hidden-unit
activation functions contain at least one zero-gradient (saturated) region.
This regularizer explicitly encourages activations in the saturated region(s)
of the corresponding activation function. We call these Saturating
Auto-Encoders (SATAE). We show that the saturation regularizer explicitly
limits the SATAE's ability to reconstruct inputs which are not near the data
manifold. Furthermore, we show that a wide variety of features can be learned
when different activation functions are used. Finally, connections are
established with the Contractive and Sparse Auto-Encoders.


title: Cramer-Rao Lower Bound and Information Geometry

abstract:
  This article focuses on an important piece of work of the world renowned
Indian statistician, Calyampudi Radhakrishna Rao. In 1945, C. R. Rao (25 years
old then) published a pathbreaking paper, which had a profound impact on
subsequent statistical research.


title:
High-Pressure Evolution of the Specific Heat of a Strongly Underdoped
  Ba(Fe0.963Co0.037)As2 Iron-Based Superconductor

abstract:
  We report specific-heat experiments under the influence of high pressure on a
strongly underdoped Co-substituted BaFe2As2 single crystal. This allows us to
study the phase diagram of this iron pnictide superconductor with a bulk
thermodynamic method and pressure as a clean control parameter. The data show
large specific-heat anomalies at the superconducting transition temperature,
which proves the bulk nature of pressure-induced superconductivity. The
transitions in the specific heat are sharper than in resistivity, which
demonstrates the necessity of employing bulk thermodynamic methods to explore
the exact phase diagram of pressure-induced Fe-based superconductors. The Tc at
optimal pressure and the superconducting condensation energy are found to be
larger than in optimally Co-doped samples at ambient pressure, which we
attribute to a weak pair breaking effect of the Co ions.


title: Self-induced inverse spin Hall effect in permalloy at room temperature

abstract:
  Inverse spin Hall effect (ISHE) allows the conversion of pure spin current
into charge current in nonmagnetic materials (NM) due to spin-orbit interaction
(SOI). In ferromagnetic materials (FM), SOI is known to contribute to anomalous
Hall effect (AHE), anisotropic magnetoresistance (AMR), and other
spin-dependent transport phenomena. However, SOI in FM has been ignored in ISHE
studies in spintronic devices, and the possibility of "self-induced ISHE" in FM
has never been explored until now. In this paper, we demonstrate the
experimental verification of ISHE in FM. We found that the spin-pumping-induced
spin current in permalloy (Py) film generates a transverse electromotive force
(EMF) in the film itself, which results from the coupling of spin current and
SOI in Py. The control experiments ruled out spin rectification effect and
anomalous Nernst effect as the origin of the EMF.


title: D-optimal Factorial Designs under Generalized Linear Models

abstract:
  Generalized linear models (GLMs) have been used widely for modelling the mean
response both for discrete and continuous random variables with an emphasis on
categorical response. Recently Yang, Mandal and Majumdar (2013) considered full
factorial and fractional factorial locally D-optimal designs for binary
response and two-level experimental factors. In this paper, we extend their
results to a general setup with response belonging to a single-parameter
exponential family and for multi-level predictors.


title:
Expansion Formulas of Basic Hypergeometric Series via the
  (1-xy,y-x)--Inversion and Its Applications

abstract:
  With the use of the $(f,g)$-matrix inversion under specializations that
$f=1-xy,g=y-x$, we establish an $(1-xy,y-x)$-expansion formula. When
specialized to basic hypergeometric series, this $(1-xy,y-x)$-expansion formula
leads us to some expansion formulas expressing any ${}_{r}\phi_{s}$ series in
variable $x~t$ in terms of a linear combination of ${}_{r+2}\phi_{s+1}$ series
in $t$, as well as various specifications. All these results can be regarded as
common generalizations of many konwn expansion formulas in the setting of
$q$-series. As specific applications, some new transformation formulas of
$q$-series including new approach to the Askey-Wilson polynomials, the
Rogers-Fine identity, Andrews' four-parametric reciprocity theorem and
Ramanujan's ${}_1\psi_1$ summation formula, as well as a transformation for
certain well-poised Bailey pairs, are presented.


title: Big Neural Networks Waste Capacity

abstract:
  This article exposes the failure of some big neural networks to leverage
added capacity to reduce underfitting. Past research suggest diminishing
returns when increasing the size of neural networks. Our experiments on
ImageNet LSVRC-2010 show that this may be due to the fact there are highly
diminishing returns for capacity in terms of training error, leading to
underfitting. This suggests that the optimization method - first order gradient
descent - fails at this regime. Directly attacking this problem, either through
the optimization method or the choices of parametrization, may allow to improve
the generalization error on large datasets, for which a large capacity is
required.


title: Revisiting Natural Gradient for Deep Networks

abstract:
  We evaluate natural gradient, an algorithm originally proposed in Amari
(1997), for learning deep models. The contributions of this paper are as
follows. We show the connection between natural gradient and three other
recently proposed methods for training deep models: Hessian-Free (Martens,
2010), Krylov Subspace Descent (Vinyals and Povey, 2012) and TONGA (Le Roux et
al., 2008). We describe how one can use unlabeled data to improve the
generalization error obtained by natural gradient and empirically evaluate the
robustness of the algorithm to the ordering of the training set compared to
stochastic gradient descent. Finally we extend natural gradient to incorporate
second order information alongside the manifold information and provide a
benchmark of the new algorithm using a truncated Newton approach for inverting
the metric matrix instead of using a diagonal approximation of it.


title:
Introduction to the Rotating Wave Approximation (RWA) : Two Coherent
  Oscillations

abstract:
  In this note I introduce a mysterious approximation called the rotating wave
approximation (RWA) to undergraduates or non-experts who are interested in both
Mathematics and Quantum Optics. In Quantum Optics it plays a very important
role in order to obtain an analytic approximate solution of some
Schr{\"o}dinger equation, while it is curious from the mathematical point of
view. I explain it carefully with two coherent oscillations for them and expect
that they will overcome the problem in the near future.


title:
Exact solutions to the Navier-Stokes equation for an incompressible flow
  from the interpretation of the Schroedinger wave function

abstract:
  The existence of the velocity potential is a direct consequence from the
derivation of the continuity equation from the Schroedinger equation. This
implies that the Cole-Hopf transformation is applicable to the Navier-Stokes
equation for an incompressible flow and allows reducing the Navier-Stokes
equation to the Einstein-Kolmogorov equation, in which the reaction term
depends on the pressure. The solution to the resulting equation, and to the
Navier-Stokes equation as well, can then be written in terms of the Green's
function of the heat equation and is given in the form of an integral mapping.
Such a form of the solution makes bifurcation period doubling possible, i.e.
solutions to transition and turbulent flow regimes in spite of the existence of
the velocity potential.


title:
Subaru/HDS study of HE 1015-2050: Spectral evidence of R Coronae
  Borealis light decline

abstract:
  Hydrogen deficiency and a sudden optical light decline by about 6-8 mag are
two principal characteristics of R Coronae Borealis (RCB) stars. The high
latitude carbon star HE 1015-2050 was identified as a hydrogen-deficient carbon
star from low-resolution spectroscopy. Photometric data of the Catalina
Real-Time Transient Survey gathered between 2006 February and 2012 May indicate
that the object exhibits no variability. However, a high-resolution (R ~
50,000) optical spectrum of this object obtained with the 8.2m Subaru telescope
using High Dispersion Spectrograph on the 2012 January 13 offers sufficient
spectral evidences for the object being a cool HdC star of RCB type undergoing
light decline. In contrast to the Na I D broad absorption features, seen in the
low-resolution spectra on several occasions, the high-resolution spectrum
exhibits Na I D2 and D1 features in emission. A few emission lines due to Mg I,
Sc II, Ti I, Ti II, Fe II and Ba I are also observed in the spectrum of this
object for the first time. Such emission features combined with neutral and
singly ionized lines of Ca, Ti, Fe, etc., in absorption are reportedly seen in
RCBs spectra in the early stage of decline or during the recovery to maximum.
Further, the light decline of RCBs is ascribed to the formation of a cloud of
soot that obscures the visible photosphere. Presence of such circumstellar
material is evident from the polarimetric observations with an estimated V-band
percentage polarization of ~1.7% for this object.


title:
Impact of the non-Gaussian covariance of the weak lensing power spectrum
  and bispectrum on cosmological parameter estimation

abstract:
  We study how well the Gaussian approximation is valid for computing the
covariance matrices of the convergence power and bispectrum in weak
gravitational lensing analyses. We focus on its impact on the cosmological
parameter estimations by comparing the results with and without non-Gaussian
error contribution in the covariance matrix. We numerically derive the
covariance matrix as well as the cosmology dependence of the spectra from a
large set of N-body simulations performed for various cosmologies and carry out
Fisher matrix forecasts for tomographic weak lensing surveys with three source
redshifts. After showing the consistency of the power and bispectra measured
from our simulations with the state-of-the-art fitting formulas, we investigate
the covariance matrix assuming a typical ongoing survey across 1500 deg^2 with
the mean source number density of 30 arcmin^{-2} at the mean redshift z_s=1.0.
Although the shape noise contributes a significant fraction to the total error
budget and it mitigates the impact of the non-Gaussian error for this source
number density, we find that the non-Gaussian error degrades the cumulative
signal-to-noise ratio up to the maximum multipole of 2000 by a factor of about
2 (3) in the power (bi-) spectrum analysis. Its impact on the final
cosmological parameter forecast with 6 parameters can be as large as 15% in the
size of the one-dimensional statistical error. This can be a problem in future
wide and deep weak lensing surveys for precision cosmology. We also show how
much the dark energy figure of merit is affected by the non-Gaussian error
contribution and demonstrate an optimal survey design with a fixed
observational time.


title:
Effective models for nematic liquid crystals composites with
  ferromagnetic inclusions

abstract:
  Molecules of a nematic liquid crystal respond to an applied magnetic field by
reorienting themselves in the direction of the field. Since the dielectric
anisotropy of a nematic is small, it takes relatively large fields to elicit a
significant liquid crystal response. The interaction may be enhanced in
colloidal suspensions of ferromagnetic particles in a liquid crystalline
matrix---ferronematics--- as proposed by Brochard and de Gennes in 1970. The
ability of these particles to align with the field and, simultaneously, cause
reorientation of the nematic molecules, greatly increases the magnetic response
of the mixture. Essentially the particles provide an easy axis of magnetization
that interacts with the liquid crystal via surface anchoring.
  We derive an expression for the effective energy of ferronematic in the
dilute limit, that is, when the number of particles tends to infinity while
their total volume fraction tends to zero. The total energy of the mixture is
assumed to be the sum of the bulk elastic liquid crystal contribution, the
anchoring energy of the liquid crystal on the surfaces of the particles, and
the magnetic energy of interaction between the particles and the applied
magnetic field. The homogenized limiting ferronematic energy is obtained
rigorously using a variational approach. It generalizes formal expressions
previously reported in a physical literature.


title: Tree structured sparse coding on cubes

abstract: A brief description of tree structured sparse coding on the binary cube.


title: Multi-Particle Baryon Spectroscopy

abstract:
  In Nature the excited states of the hadron spectrum appear as resonances.
Consequently, there has been significant interest in studying the excited
baryon spectrum using lattice QCD. With this in mind we perform spectroscopic
calculations with five-quark interpolating fields. Stochastic estimation
techniques are used in order to calculate the loop propagators, with dilution
in spin, colour and time implemented as a means of variance reduction. We
present effective mass plots extracted from these five-quark interpolators, and
examine the contributions from fully-connected and loop-containing pieces of
the correlation function, keeping in mind their use in future corre- lation
matrix studies.


title: Deep Learning for Detecting Robotic Grasps

abstract:
  We consider the problem of detecting robotic grasps in an RGB-D view of a
scene containing objects. In this work, we apply a deep learning approach to
solve this problem, which avoids time-consuming hand-design of features. This
presents two main challenges. First, we need to evaluate a huge number of
candidate grasps. In order to make detection fast, as well as robust, we
present a two-step cascaded structure with two deep networks, where the top
detections from the first are re-evaluated by the second. The first network has
fewer features, is faster to run, and can effectively prune out unlikely
candidate grasps. The second, with more features, is slower but has to run only
on the top few detections. Second, we need to handle multimodal inputs well,
for which we present a method to apply structured regularization on the weights
based on multimodal group regularization. We demonstrate that our method
outperforms the previous state-of-the-art methods in robotic grasp detection,
and can be used to successfully execute grasps on two different robotic
platforms.


title: Super-stretched and graded countable Cohen-Macaulay type

abstract:
  We define what it means for a Cohen-Macaulay ring to to be super-stretched
and show that Cohen-Macaulay rings of graded countable Cohen-Macaulay type are
super-stretched. We use this result to show that rings of graded countable
Cohen-Macaulay type, and positive dimension, have possible h-vectors (1),
(1,n), or (1,n,1). Further, one dimensional standard graded Gorenstein rings of
graded countable type are shown to be hypersurfaces; this result is not known
in higher dimensions. In the non-Gorenstein case, rings of graded countable
Cohen-Macaulay type of dimension larger than 2 are shown to be of minimal
multiplicity.


title:
Cohomological relation between Jacobi forms and skew-holomorphic Jacobi
  forms

abstract:
  Eichler and Zagier developed a theory of Jacobi forms to understand and
extend Maass' work on the Saito-Kurokawa conjecture. Later Skoruppa introduced
skew-holomorphic Jacobi forms, which play an important role in understanding
liftings of modular forms and Jacobi forms. In this paper, we explain a
relation between holomorphic Jacobi forms and skew-holomorphic Jacobi forms in
terms of a group cohomology. More precisely, we introduce an isomorphism from
the direct sum of the space of Jacobi cusp forms on $\Gamma^J$ and the space of
skew-holomorphic Jacobi cusp forms on $\Gamma^J$ with the same half-integral
weight to the Eichler cohomology group of $\Gamma^J$ with a coefficient module
coming from polynomials.


title:
Diophantine approximation of the orbit of 1 in the dynamical system of
  bete expansions

abstract:
  We consider the distribution of the orbits of the number 1 under the
$\beta$-transformations $T_\beta$ as $\beta$ varies. Mainly, the size of the
set of $\beta>1$ for which a given point can be well approximated by the orbit
of 1 is measured by its Hausdorff dimension. That is, the dimension of the
following set $$ E\big({\ell_n}_{n\ge 1}, x_0\big)=\Big{\beta>1:
|T^n_{\beta}1-x_0|<\beta^{-\ell_n}, {for infinitely many} n\in \N\Big} $$ is
determined, where $x_0$ is a given point in $[0,1]$ and ${\ell_n}_{n\ge 1}$ is
a sequence of integers tending to infinity as $n\to \infty$. For the proof of
this result, the notion of the recurrence time of a word in symbolic space is
introduced to characterize the lengths and the distribution of cylinders (the
set of $\beta$ with a common prefix in the expansion of 1) in the parameter
space ${\beta\in \R: \beta>1}$.


title: Mechanical generation of spin current by spin-rotation coupling

abstract:
  Spin-rotation coupling, which is responsible for angular momentum conversion
between the electron spin and rotational deformations of elastic media, is
exploited for generating spin current. This method requires neither magnetic
moments nor spin-orbit interaction. The spin current generated in nonmagnets is
calculated in presence of surface acoustic waves. We solve the spin diffusion
equation, extended to include spin-rotation coupling, and find that larger spin
currents can be obtained in materials with longer spin lifetimes. Spin
accumulation induced on the surface is predicted to be detectable by
time-resolved Kerr spectroscopy.


title: FEL Polarization Control Studies on Dalian Coherent Light Source

abstract:
  The polarization switch of a free-electron laser (FEL) is of great importance
to the user scientific community. In this paper, we investigate the generation
of controllable polarization FEL from two well-known approaches for Dalian
coherent light source, i.e., crossed planar undulator and elliptical permanent
undulator. In order to perform a fair comparative study, a one-dimensional
time-dependent FEL code has been developed, in which the imperfection effects
of an elliptical permanent undulator are taken into account. Comprehensive
simulation results indicate that the residual beam energy chirp and the
intrinsic FEL gain may contribute to the degradation of the polarization
performance for the crossed planar undulator. And the elliptical permanent
undulator is not very sensitive to the undulator errors and beam imperfections.
Meanwhile, with proper configurations of the main planar undulators and
additional elliptical permanent undulator section, circular polarized FEL with
pulse energy exceeds 100 $\mu$J could be achieved at Dalian coherent light
source.


title:
Low-Complexity Scheduling Policies for Achieving Throughput and
  Asymptotic Delay Optimality in Multi-Channel Wireless Networks

abstract:
  In this paper, we study the scheduling problem for downlink transmission in a
multi-channel (e.g., OFDM-based) wireless network. We focus on a single cell,
with the aim of developing a unifying framework for designing low-complexity
scheduling policies that can provide optimal performance in terms of both
throughput and delay. We develop new easy-to-verify sufficient conditions for
rate-function delay optimality (in the many-channel many-user asymptotic
regime) and throughput optimality (in general non-asymptotic setting),
respectively. The sufficient conditions allow us to prove rate-function delay
optimality for a class of Oldest Packets First (OPF) policies and throughput
optimality for a large class of Maximum Weight in the Fluid limit (MWF)
policies, respectively. By exploiting the special features of our carefully
chosen sufficient conditions and intelligently combining policies from the
classes of OPF and MWF policies, we design hybrid policies that are both
rate-function delay-optimal and throughput-optimal with a complexity of
$O(n^{2.5} \log n)$, where $n$ is the number of channels or users. Our
sufficient condition is also used to show that a previously proposed policy
called Delay Weighted Matching (DWM) is rate-function delay-optimal. However,
DWM incurs a high complexity of $O(n^5)$. Thus, our approach yields
significantly lower complexity than the only previously designed delay and
throughput optimal scheduling policy. We also conduct numerical experiments to
validate our theoretical results.


title:
Technical Report: Beaconless Geo-Routing Under The Spotlight: Practical
  Link Models and Application Scenarios

abstract:
  Analysis and simulation of beaconless geo-routing protocols have been
traditionally conducted assuming equal communication ranges for the data and
control packets. In reality, this is not true since the communication range is
actually function of the packet length. Control packets are typically much
shorter than data packets. As a consequence, a substantial discrepancy exists
in practice between their respective communication ranges. In this paper, we
devise a practical link model for computing the effective communication range.
We further introduce two simple strategies for bridging the gap between the
control and data packet communication ranges. Our primary objective in this
paper is to construct a realistic analytical framework describing the
end-to-end performance of beaconless geo-routing protocols. Two flagship
protocols are selected in this paper for further investigation under the
developed framework. For a better perspective, the two protocols are actually
compared to a hypothetical limit case; one which offers optimal energy and
latency performance. Finally, we present four different application scenarios.
For each scenario, we highlight the geo-routing protocol which performs the
best and discuss the reasons behind it.


title: Long-lived Scattering Resonances and Bragg Structures

abstract:
  We consider a system governed by the wave equation with index of refraction
$n(x)$, taken to be variable within a bounded region $\Omega\subset \mathbb
R^d$, and constant in $\mathbb R^d \setminus \Omega$. The solution of the
time-dependent wave equation with initial data, which is localized in $\Omega$,
spreads and decays with advancing time. This rate of decay can be measured (for
$d=1,3$, and more generally, $d$ odd) in terms of the eigenvalues of the
scattering resonance problem, a non-selfadjoint eigenvalue problem governing
the time-harmonic solutions of the wave (Helmholtz) equation which are outgoing
at $\infty$. Specifically, the rate of energy escape from $\Omega$ is governed
by the complex scattering eigenfrequency, which is closest to the real axis. We
study the structural design problem: Find a refractive index profile $n_*(x)$
within an admissible class which has a scattering frequency with minimal
imaginary part. The admissible class is defined in terms of the compact support
of $n(x)-1$ and pointwise upper and lower (material) bounds on $n(x)$ for $x
\in \Omega$, i.e., $0 < n_- \leq n(x) \leq n_+ < \infty$. We formulate this
problem as a constrained optimization problem and prove that an optimal
structure, $n_*(x)$ exists. Furthermore, $n_*(x)$ is piecewise constant and
achieves the material bounds, i.e., $n_*(x) \in {n_-, n_+} $. In one dimension,
we establish a connection between $n_*(x)$ and the well-known class of Bragg
structures, where $n(x)$ is constant on intervals whose length is one-quarter
of the effective wavelength.

categories: math.OC math-ph math.AP math.MP physics.optics


title:
Statistical Analysis of Self-Organizing Networks with Biased Cell
  Association and Interference Avoidance

abstract:
  In this work, we assess the viability of heterogeneous networks composed of
legacy macrocells which are underlaid with self-organizing picocells. Aiming to
improve coverage, cell-edge throughput and overall system capacity,
self-organizing solutions, such as range expansion bias, almost blank subframe
and distributed antenna systems are considered. Herein, stochastic geometry is
used to model network deployments, while higher-order statistics through the
cumulants concept is utilized to characterize the probability distribution of
the received power and aggregate interference at the user of interest. A
compre- hensive analytical framework is introduced to evaluate the performance
of such self-organizing networks in terms of outage probability and average
channel capacity with respect to the tagged receiver. To conduct our studies,
we consider a shadowed fading channel model incorporating log-normal shadowing
and Nakagami-m fading. Results show that the analytical framework matches well
with numerical results obtained from Monte Carlo simulations. We also observed
that by simply using almost blank subframes the aggregate interference at the
tagged receiver is reduced by about 12dB. Although more elaborated interference
control techniques such as, downlink bitmap and distributed antennas systems
become needed, when the density of picocells in the underlaid tier gets high.


title:
Fourier transform methods for pathwise covariance estimation in the
  presence of jumps

abstract:
  We provide a new non-parametric Fourier procedure to estimate the trajectory
of the instantaneous covariance process (from discrete observations of a
multidimensional price process) in the presence of jumps extending the seminal
work Malliavin and Mancino~\cite{MM:02, MM:09}. Our approach relies on a
modification of (classical) jump-robust estimators of integrated realized
covariance to estimate the Fourier coefficients of the covariance trajectory.
Using Fourier-F\'ejer inversion we reconstruct the path of the instantaneous
covariance. We prove consistency and central limit theorem (CLT) and in
particular that the asymptotic estimator variance is smaller by a factor $ 2/3$
in comparison to classical local estimators.
  The procedure is robust enough to allow for an iteration and we can show
theoretically and empirically how to estimate the integrated realized
covariance of the instantaneous stochastic covariance process. We apply these
techniques to robust calibration problems for multivariate modeling in finance,
i.e., the selection of a pricing measure by using time series and derivatives'
price information simultaneously.


title:
Solution of Seventh Order Boundary Value Problems using Adomian
  Decomposition Method

abstract:
  Adomian decomposition method is used for solving the seventh order boundary
value problems. The approximate solutions of the problems are calculated in the
form of a rapid convergent series and not at grid points. Two numerical
examples have been considered to illustrate the efficiency and implementation
of the method.


title: Massive logarithmic graviton in the critical generalized massive gravity

abstract:
  We study the generalized massive gravity in three dimensional flat spacetime.
A massive logarithmic mode is propagating in the flat spacetime at the critical
point where two masses degenerate. Furthermore, we discuss the logarithmic
extension of the Galilean conformal algebra (GCA) which may arise from the
exotic and standard rank-2 logarithmic conformal field theory (LCFT) on the
boundary of AdS3 spacetime.


title:
Feature Learning in Deep Neural Networks - Studies on Speech Recognition
  Tasks

abstract:
  Recent studies have shown that deep neural networks (DNNs) perform
significantly better than shallow networks and Gaussian mixture models (GMMs)
on large vocabulary speech recognition tasks. In this paper, we argue that the
improved accuracy achieved by the DNNs is the result of their ability to
extract discriminative internal representations that are robust to the many
sources of variability in speech signals. We show that these representations
become increasingly insensitive to small perturbations in the input with
increasing network depth, which leads to better speech recognition performance
with deeper networks. We also show that DNNs cannot extrapolate to test samples
that are substantially different from the training examples. If the training
data are sufficiently representative, however, internal features learned by the
DNN are relatively stable with respect to speaker differences, bandwidth
differences, and environment distortion. This enables DNN-based recognizers to
perform as well or better than state-of-the-art systems based on GMMs or
shallow networks without the need for explicit model adaptation or feature
normalization.


title: NGC5694: another extra-galactic globular cluster

abstract:
  We discuss the chemical composition of six giant stars of the outer Halo
globular cluster NGC5694, through the analysis of UVES@FLAMES high-resolution
spectra. The cluster has an average iron content [Fe/H]=--1.83+-0.01,
solar-scaled [alpha/Fe] ratios and a very low Ba abundance
([Ba/Fe]=--0.71+-0.06). These anomalous abundance patterns are different from
those observed in other Halo globular clusters but similar to those of the
metal-poor stars in typical dwarf spheroidal galaxies. These findings suggest
an extra-galactic origin for NGC5694, likely from a dwarf spheroidal galaxy.


title:
The Kinetic Sunyaev-Zel'dovich effect as a probe of the physics of
  cosmic reionization: the effect of self-regulated reionization

abstract:
  We calculate the angular power spectrum of the Cosmic Microwave Background
(CMB) temperature fluctuations induced by the kinetic Sunyaev-Zel'dovich (kSZ)
effect from the epoch of reionization (EOR). We use detailed N-body+radiative
transfer simulations to follow inhomogeneous reionization of the intergalactic
medium (IGM). For the first time we take into account the "self-regulation" of
reionization: star formation in low-mass dwarf galaxies (10^8 M_\sun \lesssim M
\lesssim 10^9 M_\sun) or minihalos (10^5 M_\sun \lesssim M \lesssim 10^8
M_\sun) is suppressed if these halos form in the regions that were already
ionized or Lyman-Werner dissociated. Some previous work suggested that the
amplitude of the kSZ power spectrum from the EOR can be described by a
two-parameter family: the epoch of half ionization and the duration of
reionization. However, we argue that this picture applies only to simple forms
of the reionization history which are roughly symmetric about the
half-ionization epoch. In self-regulated reionization, the universe begins to
be ionized early, maintains a low level of ionization for an extended period,
and then finishes reionization as soon as high-mass atomically-cooling halos
dominate. While inclusion of self-regulation affects the amplitude of the kSZ
power spectrum only modestly (\sim 10 %), it can change the duration of
reionization by a factor of more than two. We conclude that the simple
two-parameter family does not capture the effect of a physical, yet complex,
reionization history caused by self-regulation. When added to the
post-reionization kSZ contribution, our prediction for the total kSZ power
spectrum is below the current upper bound from the South Pole Telescope.
Therefore, the current upper bound on the kSZ effect from the EOR is consistent
with our understanding of the physics of reionization.


title: Universal Gauss-Thakur sums and L-series

abstract:
  In this paper we study the behavior of the function omega of Anderson-Thakur
evaluated at the elements of the algebraic closure of the finite field with q
elements F_q. Indeed, this function has quite a remarkable relation to explicit
class field theory for the field K=F_q(T). We will see that these values,
together with the values of its divided derivatives, generate the maximal
abelian extension of K which is tamely ramified at infinity. We will also see
that omega is, in a way that we will explain in detail, an universal
Gauss-Thakur sum. We will then use these results to show the existence of
functional relations for a class of L-series introduced by the second author.
Our results will be finally applied to obtain a new class of congruences for
Bernoulli-Carlitz fractions, and an analytic conjecture is stated, implying an
interesting behavior of such fractions modulo prime ideals of A=F_q[T].