title: Managing Appointment Booking under Customer Choices

abstract:
  Motivated by the increasing use of online appointment booking platforms, we
study how to offer appointment slots to customers in order to maximize the
total number of slots booked. We develop two models, non-sequential offering
and sequential offering, to capture different types of interactions between
customers and the scheduling system. In these two models, the scheduler offers
either a single set of appointment slots for the arriving customer to choose
from, or multiple sets in sequence, respectively. For the non-sequential model,
we identify a static randomized policy which is asymptotically optimal when the
system demand and capacity increase simultaneously, and we further show that
offering all available slots at all times has a constant factor of 2
performance guarantee. For the sequential model, we derive a closed-form
optimal policy for a large class of instances and develop a simple, effective
heuristic for those instances without an explicit optimal policy. By comparing
these two models, our study generates useful operational insights for improving
the current appointment booking processes. In particular, our analysis reveals
an interesting equivalence between the sequential offering model and the
non-sequential offering model with perfect customer preference information.
This equivalence allows us to apply sequential offering in a wide range of
interactive scheduling contexts. Our extensive numerical study shows that
sequential offering can significantly improve the slot fill rate (6-8% on
average and up to 18% in our testing cases) compared to non-sequential
offering.


title:
Charged particle dynamics in the presence of non-Gaussian L\'evy
  electrostatic fluctuations

abstract:
  Full orbit dynamics of charged particles in a $3$-dimensional helical
magnetic field in the presence of $\alpha$-stable L\'evy electrostatic
fluctuations and linear friction modeling collisional Coulomb drag is studied
via Monte Carlo numerical simulations. The L\'evy fluctuations are introduced
to model the effect of non-local transport due to fractional diffusion in
velocity space resulting from intermittent electrostatic turbulence. The
probability distribution functions of energy, particle displacements, and
Larmor radii are computed and showed to exhibit a transition from exponential
decay, in the case of Gaussian fluctuations, to power law decay in the case of
L\'evy fluctuations. The absolute value of the power law decay exponents are
linearly proportional to the L\'evy index $\alpha$. The observed anomalous
non-Gaussian statistics of the particles' Larmor radii (resulting from outlier
transport events) indicate that, when electrostatic turbulent fluctuations
exhibit non-Gaussian L\'evy statistics, gyro-averaging and guiding centre
approximations might face limitations and full particle orbit effects should be
taken into account.


title:
Boosting local field enhancement by on-chip nanofocusing and
  impedance-matched plasmonic antennas

abstract:
  Strongly confined surface plasmon-polariton modes can be used for efficiently
delivering the electromagnetic energy to nano-sized volumes by reducing the
cross sections of propagating modes far beyond the diffraction limit, i.e., by
nanofocusing. This process results in significant local-field enhancement that
can advantageously be exploited in modern optical nanotechnologies, including
signal processing, biochemical sensing, imaging and spectroscopy. Here, we
propose, analyze, and experimentally demonstrate on-chip nanofocusing followed
by impedance-matched nanowire antenna excitation in the end-fire geometry at
telecom wavelengths. Numerical and experimental evidences of the efficient
excitation of dipole and quadrupole (dark) antenna modes are provided,
revealing underlying physical mechanisms and analogies with the operation of
plane-wave Fabry-P\'erot interferometers. The unique combination of efficient
nanofocusing and nanoantenna resonant excitation realized in our experiments
offers a major boost to the field intensity enhancement up to $\sim 12000$,
with the enhanced field being evenly distributed over the gap volume of
$30\times 30\times 10\ {\rm nm}^3$, and promises thereby a variety of useful
on-chip functionalities within sensing, nonlinear spectroscopy and signal
processing.


title:
Asymptotic frequentist coverage properties of Bayesian credible sets for
  sieve priors

abstract:
  We investigate the frequentist coverage properties of Bayesian credible sets
in a general, adaptive, nonparametric framework. It is well known that the
construction of adaptive and honest confidence sets is not possible in general.
To overcome this problem we introduce an extra assumption on the functional
parameters, the so called "general polished tail" condition. We then show that
under standard assumptions both the hierarchical and empirical Bayes methods
results in honest confidence sets for sieve type of priors in general settings
and we characterize their size. We apply the derived abstract results to
various examples, including the nonparametric regression model, density
estimation using exponential families of priors, density estimation using
histogram priors and nonparametric classification model, for which we show that
their size is near minimax adaptive with respect to the considered specific
semi-metrics.


title:
Evidence of Cosmic Strings by the Observation of the Alignment of Quasar
  Polarization Axes on Mpc scale

abstract:
  We find a emergent azimuthal-angle dependency of the Nielsen-Olesen vortices
in the general relativistic situation just after the symmetry breaking at
GUT-scale. Using a high-frequency perturbation method, we obtain in the first
and second order perturbation equations $\varphi$-dependent terms left over
after the phase transition of the Higgs field. Vortices with high multiplicity
decay into a lattice with entangled Abrikosov vortices. The stability of this
lattice of correlated flux $n=1$ vortices with preferred azimuthal-angle is
guaranteed by the contribution from the bulk spacetime by means of the warp
factor: the cosmic string becomes super-massive for some time during the
evolution and initiates the excitations of the vortices to high multiplicity.
The correlation will not fade away during the expansion by the warp factor. We
used this azimuthal-angle correlation for the explanation of the recently
observed alignment of polarization axes of quasars in large quasar groups. The
detailed behavior of this alignment can be explained with our model. The two
different orientations perpendicular to each other in quasars groups of less
richness could be a second order effect in our model. There is a striking
similarity between this phase transition of the gauged Higgs field and the
temporarily breaking of the axially symmetry of self-gravitating cosmic string,
by the appearance of non-diagonal energy-momentum tensor components. The
eccentricity of the ellipsoid can be seen as order parameter. Recovery to SO(2)
symmetry induces emission of gravitational and electro-magnetic radiation. More
data of high-redshift quasars will be needed in order to test the second order
effect predicted in our model.


title: Measures in Mutlifield Inflation

abstract:
  We examine the classical dynamics of multifield inflation models with
quadratic potentials. Such models are shown to have inflationary attractors in
phase space, consistent with the stretching of phase space trajectories along
the volume factor of the universe during inflation. Using the symplectic
structure associated with Hamiltonian systems we form a measure on the phase
space, as initially proposed by Gibbons, Hawking and Stewart. This is used to
calculate lower bounds on the probabilities of observational agreement (i.e.
the probability the model gives a value for the spectral index within the
region $n_{s}=0.968\pm{0.006}$) for equal mass two and three field models with
quadratic potentials, giving values of 0.982 and 0.997 respectively. We derive
the measure for a general $N$-field model and argue that as the number of
fields approaches infinity, the probability of observational agreement
approaches one.


title: Hamiltonian and Godunov Structures of the Grad Hierarchy

abstract:
  The time evolution governed by the Boltzmann kinetic equation is compatible
with mechanics and thermodynamics. The former compatibility is mathematically
expressed in the Hamiltonian and Godunov structures, the latter in the
structure of gradient dynamics guaranteeing the growth of entropy and
consequently the approach to equilibrium. We carry all three structures to the
Grad reformulation of the Boltzmann equation (to the Grad hierarchy). First, we
recognize the structures in the infinite Grad hierarchy and then in several
examples of finite hierarchies representing extended hydrodynamic equations. In
the context of Grad's hierarchies we also investigate relations between
Hamiltonian and Godunov structures.

categories: cond-mat.stat-mech math-ph math.MP physics.flu-dyn


title: Four loop renormalization of the Gross-Neveu model

abstract:
  We renormalize the SU(N) Gross-Neveu model in the modified minimal
subtraction (MSbar) scheme at four loops and determine the beta-function at
this order. The theory ceases to be multiplicatively renormalizable when
dimensionally regularized due to the generation of evanescent 4-fermi
operators. The first of these appears at three loops and we correctly take
their effect into account in deriving the renormalization group functions. We
use the results to provide estimates of critical exponents relevant to phase
transitions in graphene.

categories: hep-th cond-mat.dis-nn cond-mat.mes-hall cond-mat.str-el


title:
Matching uncertainties in the prediction of the Higgs boson transverse
  momentum in the SM and beyond

abstract:
  We present the results of our recent study (arXiv:1510.08850) of the
theoretical uncertainties that affect the predictions for the Higgs-boson
transverse-momentum in gluon fusion when fixed- and all-order results are
matched. Our investigation consists of a twofold analysis: first we present a
detailed comparison of two recently introduced prescriptions for the
determination of the matching scale (arXiv:1409.0531, arXiv:1505.00735), then
we apply the results of these methods to three widely used matching frameworks,
namely the aMC@NLO and POWHEG Monte Carlo approaches and analytic resummation.
The results of our study are applied to the production of the SM Higgs boson
and of the neutral Higgs bosons of the Two-Higgs-Doublet Model in a variety of
scenarios.


title:
Ab initio calculations to support accurate modelling of the rovibronic
  spectroscopy calculations of vanadium monoxide (VO)

abstract:
  Accurate knowledge of the rovibronic near-infrared and visible spectra of
vanadium monoxide (VO) is very important for studies of cool stellar and hot
planetary atmospheres. Here, the required ab initio dipole moment and
spin-orbit coupling curves for VO are produced. This data forms the basis of a
new VO line list considering 13 different electronic states and containing over
277 million transitions. Open shell transition, metal diatomics are challenging
species to model through ab initio quantum mechanics due to the large number of
low-lying electronic states, significant spin-orbit coupling and strong static
and dynamic electron correlation. Multi-reference configuration interaction
methodologies using orbitals from a complete active space self-consistent-field
(CASSCF) calculation are the standard technique for these systems. We use
different state-specific or minimal-state CASSCF orbitals for each electronic
state to maximise the calculation accuracy. The off-diagonal dipole moment
controls the intensity of electronic transitions. We test finite-field
off-diagonal dipole moments, but found that (1) the accuracy of the excitation
energies were not sufficient to allow accurate dipole moments to be evaluated
and (2) computer time requirements for perpendicular transitions were
prohibitive. The best off-diagonal dipole moments are calculated using
wavefunctions with different CASSCF orbitals.


title: Stability of sin-cones and cosh-cylinders

abstract:
  This work concerns stability and instability of Einstein warped products with
an Einsteinian fiber of codimension 1. We study the cases where the scalar
curvature of the warped product and of the fiber are either both positive or
both negative to complement the results in [Kr\"o16]. Up to a small gap in the
case of sin-cones, the stability properties of such warped products are now
completely determined by spectral properties of the Laplacian and the Einstein
operator of the fiber. For cosh-cylinders, we are furthermore able to prove a
convergence result for the Ricci flow starting in a small neighbourhood. As an
interesting class of examples, we determine the stability properties of
sin-cones over symmetric spaces of compact type.


title:
A new approach for modelling chromospheric evaporation in response to
  enhanced coronal heating: I The method

abstract:
  We present a new computational approach that addresses the difficulty of
obtaining the correct interaction between the solar corona and the transition
region in response to rapid heating events. In the coupled corona, transition
region and chromosphere system, an enhanced downward conductive flux results in
an upflow (chromospheric evaporation). However, obtaining the correct upflow
generally requires high spatial resolution in order to resolve the transition
region. With an unresolved transition region, artificially low coronal
densities are obtained because the downward heat flux jumps across the
unresolved region to the chromosphere, underestimating the upflows. Here, we
treat the lower transition region as a discontinuity that responds to changing
coronal conditions through the imposition of a jump condition that is derived
from an integrated form of energy conservation. To illustrate and benchmark
this approach against a fully resolved one-dimensional model, we present
field-aligned simulations of coronal loops in response to a range of impulsive
(spatially uniform) heating events. We show that our approach leads to a
significant improvement in the coronal density evolution than just when using
coarse spatial resolutions insufficient to resolve the lower transition region.
Our approach compensates for the jumping of the heat flux by imposing a
velocity correction that ensures that the energy from the heat flux goes into
driving the transition region dynamics, rather than being lost through
radiation. Hence, it is possible to obtain improved coronal densities. The
advantages of using this approach in both one-dimensional hydrodynamic and
three-dimensional magnetohydrodynamic simulations are discussed.


title:
Colloidal CuFeS2 Nanocrystals: Intermediate Fe d-Band Leads to High
  Photothermal Conversion Efficiency

abstract:
  We describe the colloidal hot-injection synthesis of phase-pure nanocrystals
(NCs) of a highly abundant mineral, chalcopyrite (CuFeS2). Absorption bands
centered at around 480 and 950 nm, spanning almost the entire visible and near
infrared regions, encompass their optical extinction characteristics. These
peaks are ascribable to electronic transitions from the valence band (VB) to
the empty intermediate band (IB), located in the fundamental gap and mainly
composed of Fe 3d orbitals. Laser-irradiation (at 808 nm) of an aqueous
suspension of CuFeS2 NCs exhibited significant heating, with a photothermal
conversion efficiency of 49%. Such efficient heating is ascribable to the
carrier relaxation within the broad IB band (owing to the indirect VB-IB gap),
as corroborated by transient absorption measurements. The intense absorption
and high photothermal transduction efficiency (PTE) of these NCs in the
so-called biological window (650-900 nm) makes them suitable for photothermal
therapy as demonstrated by tumor cell annihilation upon laser irradiation. The
otherwise harmless nature of these NCs in dark conditions was confirmed by in
vitro toxicity tests on two different cell lines. The presence of the deep Fe
levels constituting the IB is the origin of such enhanced PTE, which can be
used to design other high performing NC photothermal agents.


title:
In-Situ Monitoring of Thermal Annealing Induced Evolution in Film
  Morphology and Film-Substrate Bonding in a Monolayer MoS2 Film

abstract:
  We perform in-situ two-cycle thermal cycling and annealing studies for a
transferred CVD-grown monolayer MoS2 on a SiO2/Si substrate, using spatially
resolved micro-Raman and PL spectroscopy. After the thermal cycling and being
annealed at 305 deg C twice, the film morphology and film-substrate bonding are
significantly modified, which together with the removal of polymer residues
cause major changes in the strain and doping distribution over the film, and
thus the optical properties. Before annealing, the strain associated with
ripples in the transferred film dominates the spatial distributions of the PL
peak position and intensity over the film; after annealing, the variation in
film-substrate bonding, affecting both strain and doping, becomes the leading
factor. This work reveals that the film-substrate bonding, and thus the strain
and doping, is unstable under thermal stress, which is important for
understanding the substrate effects on the optical and transport properties of
the 2D material and their impact on device applications.


title: Hybrid Beamforming for Massive MIMO - A Survey

abstract:
  Hybrid multiple-antenna transceivers, which combine large-dimensional analog
pre/postprocessing with lower-dimensional digital processing, are the most
promising approach for reducing the hardware cost and training overhead in
massive MIMO systems. This paper provides a comprehensive survey of the various
incarnations of such structures that have been proposed in the literature. We
provide a taxonomy in terms of the required channel state information (CSI),
namely whether the processing adapts to the instantaneous or the average
(second-order) CSI; while the former provides somewhat better signal-to-noise
and interference ratio (SNIR), the latter has much lower overhead for CSI
acquisition. We furthermore distinguish hardware structures of different
complexities. Finally, we point out the special design aspects for operation at
millimeter-wave frequencies.


title: Explicit Computational Paths

abstract:
  The treatment of equality as a type in type theory gives rise to an
interesting type-theoretic structure known as `identity type'. The idea is
that, given terms $a,b$ of a type $A$, one may form the type $Id_{A}(a,b)$,
whose elements are proofs that $a$ and $b$ are equal elements of type $A$. A
term of this type, $p : Id_{A}(a,b)$, makes up for the grounds (or proof) that
establishes that $a$ is indeed equal to $b$. Based on that, a proof of equality
can be seen as a sequence of substitutions and rewrites, also known as a
`computational path'. One interesting fact is that it is possible to rewrite
computational paths using a set of reduction rules arising from an analysis of
redundancies in paths. These rules were mapped by De Oliveira in 1994 in a term
rewrite system known as $LND_{EQ}-TRS$. Here we use computational paths and
this term rewrite system to develop the main foundations of homotopy type
theory, i.e., we develop the lemmas and theorems connected to the main types of
this theory, types such as products, coproducts, identity type, transport and
many others. We also show that it is possible to directly construct path spaces
through computational paths. To show this, we construct the natural numbers and
the fundamental group of the circle, showing results connected to these
structures.


title:
Block Compressed Sensing Based Distributed Device Detection for M2M
  Communications

abstract:
  In this work, we utilize the framework of compressed sensing (CS) for
distributed device detection and resource allocation in large-scale
machine-to-machine (M2M) communication networks. The devices deployed in the
network are partitioned into clusters according to some pre-defined criteria.
Moreover, the devices in each cluster are assigned a unique signature of a
particular design that can be used to indicate their active status to the
network. The proposed scheme in this work mainly consists of two essential
steps: (i) The base station (BS) detects the active clusters and the number of
active devices in each cluster using a novel block sketching algorithm, and
then assigns a certain amount of resources accordingly. (ii) Each active device
detects its ranking among all the active devices in its cluster using an
enhanced greedy algorithm and accesses the corresponding resource for
transmission based on the ranking. By exploiting the correlation in the device
behaviors and the sparsity in the activation pattern of the M2M devices, the
device detection problem is thus tackled as a CS support recovery procedure for
a particular binary block-sparse signal $x\in\mathbb{B}^N$ -- with block
sparsity $K_B$ and in-block sparsity $K_I$ over block size $d$. Theoretical
analysis shows that the activation pattern of the M2M devices can be reliably
reconstructed within an acquisition time of $\mathcal{O}(\max\{K_B\log N,
K_BK_I\log d\})$, which achieves a better scaling and less computational
complexity of $\mathcal{O}(N(K_I^2+\log N))$ compared with standard CS
algorithms. Moreover, extensive simulations confirm the robustness of the
proposed scheme in the detection process, especially in terms of higher
detection probability and reduced access delay when compared with conventional
schemes like LTE random access (RA) procedure and classic cluster-based access
approaches.


title:
Asymptotic Analysis of Equivalences and Core-Structures in
  Kronecker-Style Graph Models

abstract:
  Growing interest in modeling large, complex networks has spurred significant
research into generative graph models. Kronecker-style models (SKG and R-MAT)
are often used due to their scalability and ability to mimic key properties of
real-world networks. Although a few papers theoretically establish these
models' behavior for specific parameters, many claims used to justify their use
are supported only empirically. In this work, we prove several results using
asymptotic analysis which illustrate that empirical studies may not fully
capture the true behavior of the models.
  Paramount to the widespread adoption of Kronecker-style models was the
introduction of a linear-time edge-sampling variant (R-MAT), which existing
literature typically treats as interchangeable with SKG. We prove that although
several R-MAT formulations are asymptotically equivalent, their behavior
diverges from that of SKG. Further, we show these results are observable even
at relatively small graph sizes. Second, we consider a case where asymptotic
analysis reveals unexpected behavior within a given model.


title:
Monadic BL-algebras: the equivalent algebraic semantics of H\'ajek's
  monadic fuzzy logic

abstract:
  In this article we introduce the variety of monadic BL-algebras as
BL-algebras endowed with two monadic operators $\forall$ and $\exists$. After a
study of the basic properties of this variety we show that this class is the
equivalent algebraic semantics of the monadic fragment of H\'ajek's basic
predicate logic. In addition, we start a systematic study of the main
subvarieties of monadic BL-algebras, some of which constitute the algebraic
semantics of well-known monadic logics: monadic G\"odel logic and monadic
{\L}ukasiewicz logic. In the last section we give a complete characterization
of totally ordered monadic BL-algebras.


title:
Existence result for a dislocation based model of single crystal
  gradient plasticity with isotropic or linear kinematic hardening

abstract:
  We consider a dislocation-based rate-independent model of single crystal
gradient plasticity with isotropic or linear kinematic hardening. The model is
weakly formulated through the so-called primal form of the flow rule as a
variational inequality for which a result of existence and uniqueness is
obtained using the functional analytical framework developed by Han-Reddy.


title: Secure Multicast Communications with Private Jammers

abstract:
  This paper investigates secrecy rate optimization for a multicasting network,
in which a transmitter broadcasts the same information to multiple legitimate
users in the presence of multiple eavesdroppers. In order to improve the
achievable secrecy rates, private jammers are employed to generate interference
to confuse the eavesdroppers. These private jammers charge the legitimate
transmitter for their jamming services based on the amount of interference
received at the eavesdroppers. Therefore, this secrecy rate maximization
problem is formulated as a Stackelberg game, in which the private jammers and
the transmitter are the leaders and the follower of the game, respectively. A
fixed interference price scenario is considered first, in which a closed-form
solution is derived for the optimal amount of interference generated by the
jammers to maximize the revenue of the legitimate transmitter. Based on this
solution, the Stackelberg equilibrium of the proposed game, at which both
legitimate transmitter and the private jammers achieve their maximum revenues,
is then derived. Simulation results are also provided to validate these
theoretical derivations.


title:
Thermally induced passage and current of particles in a highly unstable
  optical potential

abstract:
  We discuss the statistics of first-passage times of a Brownian particle
moving in a highly unstable nonlinear potential proportional to an odd power of
position. We observe temperature-induced shortening of the mean first-passage
time and its dependence on the power of nonlinearity. We propose a passage-time
fraction as both a simple and experimentally detectable witness of the
nonlinearity. It is advantageously independent of all other parameters of the
experiment and observable for a small number of trajectories. To better
characterize the stochastic passage in the unstable potential, we introduce an
analogy of the signal-to-noise ratio for the statistical distribution of the
first-passage times. Interestingly, the upper bound for the signal-to-noise
ratio is temperature independent in the unstable potential. Finally, we
describe the nonequilibrium steady state of the particle cyclically passing
through unstable odd nonlinearity. The maximum of the steady-state probability
distribution shifts against the directions of the current and this
counterintuitive effect increases with temperature. All these thermally induced
effects are very promising targets for experimental tests of highly nonlinear
stochastic dynamics of particles placed into optical potential landscapes of
shaped optical tweezers.


title: Non-inner amenability of the Thompson groups T and V

abstract:
  In this paper we prove that the Thompson groups $T$ and $V$ are not inner
amenable. In particular, their group von Neumann algebras do not have property
$\Gamma$. Moreover, we prove that if the reduced group $C^\ast$-algebra of $T$
is simple, then the Thompson group $F$ is non-amenable. Furthermore, we give a
few new equivalent characterizations of amenability of $F$.


title:
Online Learning for Offloading and Autoscaling in Renewable-Powered
  Mobile Edge Computing

abstract:
  Mobile edge computing (a.k.a. fog computing) has recently emerged to enable
\emph{in-situ} processing of delay-sensitive applications at the edge of mobile
networks. Providing grid power supply in support of mobile edge computing,
however, is costly and even infeasible (in certain rugged or under-developed
areas), thus mandating on-site renewable energy as a major or even sole power
supply in increasingly many scenarios. Nonetheless, the high intermittency and
unpredictability of renewable energy make it very challenging to deliver a high
quality of service to users in renewable-powered mobile edge computing systems.
In this paper, we address the challenge of incorporating renewables into mobile
edge computing and propose an efficient reinforcement learning-based resource
management algorithm, which learns on-the-fly the optimal policy of dynamic
workload offloading (to centralized cloud) and edge server provisioning to
minimize the long-term system cost (including both service delay and
operational cost). Our online learning algorithm uses a decomposition of the
(offline) value iteration and (online) reinforcement learning, thus achieving a
significant improvement of learning rate and run-time performance when compared
to standard reinforcement learning algorithms such as Q-learning.


title:
A new Measurement of Thermal Conductivity of Iron at high pressures and
  temperatures

abstract:
  Thermal conductivity of the most abundant element in the planetary core, Iron
(Fe) is measured up to Earth's outer core pressure $\sim 120$ GPa. The
measurements are carried out using the laser heated diamond anvil cell
facility, where the absorbed power by Fe metal foil is calculated using
thermodynamical equation. The thermal conductivity of $\gamma-Fe$ linearly
increases up to a maximum experimental pressure 40 GPa. Thermal conductivity of
$\epsilon-Fe$ measured by us shows a saturated value $\sim$ 52 ($\pm$ 5)
$Wm^{-1}K^{-1}$ in the pressure range 77 - 120 GPa. At different pressures
temperature dependence of thermal conductivity show a sharp drop during
melting, which indicates the formation of liquid layer resulting in a thermal
buffer to the heat conduction.


title:
SIOUX project: a simultaneous multiband camera for exoplanet atmospheres
  studies

abstract:
  The exoplanet revolution is well underway. The last decade has seen
order-of-magnitude increases in the number of known planets beyond the Solar
system. Detailed characterization of exoplanetary atmospheres provide the best
means for distinguishing the makeup of their outer layers, and the only hope
for understanding the interplay between initial composition chemistry,
temperature-pressure atmospheric profiles, dynamics and circulation. While
pioneering work on the observational side has produced the first important
detections of atmospheric molecules for the class of transiting exoplanets,
important limitations are still present due to the lack of sys- tematic,
repeated measurements with optimized instrumentation at both visible (VIS) and
near-infrared (NIR) wavelengths. It is thus of fundamental importance to
explore quantitatively possible avenues for improvements. In this paper we
report initial results of a feasibility study for the prototype of a versatile
multi-band imaging system for very high-precision differential photometry that
exploits the choice of specifically selected narrow-band filters and novel
ideas for the execution of simultaneous VIS and NIR measurements. Starting from
the fundamental system requirements driven by the science case at hand, we
describe a set of three opto-mechanical solutions for the instrument prototype:
1) a radial distribution of the optical flux using dichroic filters for the
wavelength separation and narrow-band filters or liquid crystal filters for the
observations; 2) a tree distribution of the optical flux (implying 2 separate
foci), with the same technique used for the beam separation and filtering; 3)
an exotic solution consisting of the study of a complete optical system (i.e. a
brand new telescope) that exploits the chromatic errors of a reflecting surface
for directing the different wavelengths at different foci.


title: Thermodynamics, entropy and waterwheels

abstract:
  In this paper the analogy between a thermal engine and a waterwheel is
developed in details, showing that the analogous of the flow of water in an
hydraulic engine is the flow of entropy in a thermal one. This analogy mat
serve to analyse in details the aspects of a thermal engine that are quite
distant from pupils' intuition. The discussion is complemented by an
illustration of the working of thermal and hydraulic engines at the microscopic
level, thus furnishing a view of what heat and work are at this level, and
introducing the statistical and information aspects of entropy. Both hydraulic
and thermal non-ideal engines are also discussed.


title: Bounding heights uniformly in families of hyperbolic varieties

abstract:
  We show that, assuming Vojta's height conjecture, the height of a rational
point on an algebraically hyperbolic variety can be bounded "uniformly" in
families. This generalizes a result of Su-Ion Ih for curves of genus at least
two to higher-dimensional varieties. As an application, we show that, assuming
Vojta's height conjecture, the height of a rational point on a curve of general
type is uniformly bounded. Finally, we prove a similar result for smooth
hyperbolic surfaces with $c_1^2 > c_2$.


title: Neutral Hydrogen and its Emission Lines in the Solar Corona

abstract:
  Since the Lalpha rocket observations of (Gabriel, Solar Phys. 21, 392, 1971),
it has been realized that the hydrogen (H) lines could be observed in the
corona and offer an interesting diagnostic for the temperature, density, and
radial velocity of the coronal plasma. Moreover, various space missions have
been proposed to measure the coronal magnetic and velocity fields through
polarimetry in H lines. A necessary condition for such measurements is to
benefit from a sufficient signal-to-noise ratio. The aim of this article is to
evaluate the emission in three representative lines of H for three different
coronal structures. The computations have been performed with a full non-local
thermodynamic equilibrium (non-LTE) code and its simplified version without
radiative transfer. Since all collisionnal and radiative quantities (including
incident ionizing and exciting radiation) are taken into account, the
ionization is treated exactly. Profiles are presented at two heights (1.05 and
1.9 solar radii, from Sun center) in the corona, and the integrated intensities
are computed at heights up to five solar radii.We compare our results with
previous computations and observations (e.g. Lalpha from UVCS) and find a rough
(model-dependent) agreement. Since the Halpha line is a possible candidate for
ground-based polarimetry, we show that in order to detect its emission in
various coronal structures, it is necessary to use a very narrow (less than 2 A
wide) bandpass filter.


title: Complex Chern-Simons and Gribov

abstract:
  We explore a contact point between two distinct approaches to the confinment
problem. We show that BLG-ABJM like theories generate gauge propagators with
just the complex pole structure prescribed by the Gribov scenario for
confinemnt. This structure, known as i-particles in Gribov-Zwanziger theories,
effectively allows the definition of composite operators with a positive
K\"{a}ll\'{e}n-Lehmann spectral representation for their two-point functions .
Then, these operators satisfy the criteria to describe glue-ball condensates.
We calculate the (first order) contribution to the two-point function of the
gauge invariant condensate in an ABJM environment, showing its interpretation
as a physical particle along K\"{a}ll\'{e}n-Lehmann. In the meantime, we argue
for the necessity of absorbing Witten's work on holomorphic complex theories in
order to settle the physical interpretation of this non-perturbative scenario.


title:
All smooth four-dimensional Schoenflies balls are geometrically simply
  connected

abstract: This paper gives a complete proof of the result announced in the title.


title:
A Spectral Symplectic Algorithm for Cylindrical Electromagnetic Plasma
  Simulations

abstract:
  Symplectic integrators for Hamiltonian systems have been quite successful for
studying few-body dynamical systems. These integrators are frequently derived
using a formalism built on symplectic maps. There have been recent efforts to
extend the symplectic approach to plasmas, which have focused primarily on
discrete Lagrangian mechanics. In this paper, we derive a a symplectic
electromagnetic macroparticle algorithm using the map formalism. The resulting
algorithm is designed to prevent numerical instabilities such as numerical
\v{C}erenkov, which result from incorrect dispersion relations for the fields,
as well as the artificial heating of plasmas, which arise from the
non-symplectic nature of conventional particle-in-cell algorithms. This is the
first self-consistent electromagnetic algorithm derived using a map-based
approach.


title:
DiNoDB: an Interactive-speed Query Engine for Ad-hoc Queries on
  Temporary Data

abstract:
  As data sets grow in size, analytics applications struggle to get instant
insight into large datasets. Modern applications involve heavy batch processing
jobs over large volumes of data and at the same time require efficient ad-hoc
interactive analytics on temporary data. Existing solutions, however, typically
focus on one of these two aspects, largely ignoring the need for synergy
between the two. Consequently, interactive queries need to re-iterate costly
passes through the entire dataset (e.g., data loading) that may provide
meaningful return on investment only when data is queried over a long period of
time. In this paper, we propose DiNoDB, an interactive-speed query engine for
ad-hoc queries on temporary data. DiNoDB avoids the expensive loading and
transformation phase that characterizes both traditional RDBMSs and current
interactive analytics solutions. It is tailored to modern workflows found in
machine learning and data exploration use cases, which often involve iterations
of cycles of batch and interactive analytics on data that is typically useful
for a narrow processing window. The key innovation of DiNoDB is to piggyback on
the batch processing phase the creation of metadata that DiNoDB exploits to
expedite the interactive queries. Our experimental analysis demonstrates that
DiNoDB achieves very good performance for a wide range of ad-hoc queries
compared to alternatives %such as Hive, Stado, SparkSQL and Impala.


title: Spectral methods for multiscale stochastic differential equations

abstract:
  This paper presents a new method for the solution of multiscale stochastic
differential equations at the diffusive time scale. In contrast to
averaging-based methods, e.g., the heterogeneous multiscale method (HMM) or the
equation-free method, which rely on Monte Carlo simulations, in this paper we
introduce a new numerical methodology that is based on a spectral method. In
particular, we use an expansion in Hermite functions to approximate the
solution of an appropriate Poisson equation, which is used in order to
calculate the coefficients of the homogenized equation. Spectral convergence is
proved under suitable assumptions. Numerical experiments corroborate the theory
and illustrate the performance of the method. A comparison with the HMM and an
application to singularly perturbed stochastic PDEs are also presented.


title:
Weather instabilities as a warning sign for a nearby climatic tipping
  point?

abstract:
  Using in a simple way the theory of non linear dynamical systems, we show
that increasing climatic instabilities may be a qualitative warning sign for
the occurrence of a nearby bifurcation, yielding a discontinuous and sudden
climate tipping towards an unknown and unpredictable state. The possibility of
an accurate prediction of the occurrence time of such a transition is also
discussed in terms of the approach of a critical point.


title: A systematic method to enforce conservativity on semi-Lagrangian schemes

abstract:
  Semi-Lagrangian schemes have proven to be very efficient to model advection
problems. However most semi-Lagrangian schemes are not conservative. Here, a
systematic method is introduced in order to enforce the conservative property
on a semi-Lagrangian advection scheme. This method is shown to generate
conservative schemes with the same linear stability range and the same order of
accuracy as the initial advection scheme from which they are derived. We used a
criterion based on the column-balance property of the schemes to assess their
conservativity property. We show that this approach can be used with large CFL
numbers and third order schemes.


title:
Schmidt number of bipartite and multipartite states under local
  projections

abstract:
  The Schmidt number is a fundamental parameter characterizing the properties
of quantum states, and the local projections are a fundamental operation in
quantum physics. We investigate the relation between the Schmidt numbers of
bipartite states and their projected states. We show that there exist bipartite
positive-partial-transpose (PPT) entangled states of any given Schmidt number.
We further construct the notion of joint Schmidt number for multipartite
states, and its relation with the Schmidt number of bipartite reduced density
operators.


title:
Solving ill-posed control problems by stabilized finite element methods:
  an alternative to Tikhonov regularization

abstract:
  Tikhonov regularization is one of the most commonly used methods of
regularization of ill-posed problems. In the setting of finite element
solutions of elliptic partial differential control problems, Tikhonov
regularization amounts to adding suitably weighted least squares terms of the
control variable, or derivatives thereof, to the Lagrangian determining the
optimality system. In this note we show that stabilization methods for
discretely ill--posed problems developed in the setting of
convection--dominated convection--diffusion problems, can be highly suitable
for stabilizing optimal control problems, and that Tikhonov regularization will
lead to less accurate discrete solutions. We consider data assimilation
problems for Poisson's equation as illustration and derive new error estimates
both for the the reconstruction of the solution from measured data and
reconstruction of the source term from measured data. These estimates include
both the effect of discretization error and error in measurements.


title: Physics Program for the STAR/CBM eTOF Upgrade

abstract:
  The STAR Collaboration and the CBM Collaboration institutions: Heidelberg,
Darmstadt, CCNU, Tsinghua, and USTC propose to install an end-cap
time-of-flight upgrade (eTOF) to the STAR detector for the RHIC beam energy
scan phase II (BES-II) program in 2019 and 2020. BES-II will cover the
collision energy range 3.0 to 19.6 GeV. This is the region of interest in the
search for a critical point and first-order phase transition, identified by the
results from BES-I and by model calculations. For the collider-mode portion of
the energy scan, 7.7 to 19.6 GeV, eTOF will extend particle identification
(PID) for pions, kaons, and protons to a rapidity of 1.2, complementing the
inner Time Projection Chamber (iTPC) upgrade to the forward tracking. The
rapidity coverage for PID would extend to only 0.8 without the eTOF upgrade.
The eTOF upgrade will enable precision studies of the key bulk property
observables, essential to the BES-II search. An internal fixed-target program
will allow the energy scan to cover 3.0 to 7.7 GeV. The eTOF upgrade will
provide essential mid-rapidity PID for the 4.5 to 7.7 GeV portion of the scan
in fixed-target mode. Otherwise there would be a large energy gap in the middle
of the BES-II program. A full description of the physics provided by the eTOF
upgrade to STAR is presented in this note.


title: Learning Tuple Probabilities

abstract:
  Learning the parameters of complex probabilistic-relational models from
labeled training data is a standard technique in machine learning, which has
been intensively studied in the subfield of Statistical Relational Learning
(SRL), but---so far---this is still an under-investigated topic in the context
of Probabilistic Databases (PDBs). In this paper, we focus on learning the
probability values of base tuples in a PDB from labeled lineage formulas. The
resulting learning problem can be viewed as the inverse problem to confidence
computations in PDBs: given a set of labeled query answers, learn the
probability values of the base tuples, such that the marginal probabilities of
the query answers again yield in the assigned probability labels. We analyze
the learning problem from a theoretical perspective, cast it into an
optimization problem, and provide an algorithm based on stochastic gradient
descent. Finally, we conclude by an experimental evaluation on three real-world
and one synthetic dataset, thus comparing our approach to various techniques
from SRL, reasoning in information extraction, and optimization.


title:
Intrinsic normalization and extrinsic denormalization of formant data of
  vowels

abstract:
  Using a known speaker-intrinsic normalization procedure, formant data are
scaled by the reciprocal of the geometric mean of the first three formant
frequencies. This reduces the influence of the talker but results in a
distorted vowel space. The proposed speaker-extrinsic procedure re-scales the
normalized values by the mean formant values of vowels. When tested on the
formant data of vowels published by Peterson and Barney, the combined approach
leads to well separated clusters by reducing the spread due to talkers. The
proposed procedure performs better than two top-ranked normalization procedures
based on the accuracy of vowel classification as the objective measure.


title: STAX. An Axion-like Particle Search with Microwave Photons

abstract:
  We discuss an improved detection scheme for a light-shining-through-wall
(LSW) experiment for axion-like particle searches. We propose to use: gyrotrons
or klystrons, which can provide extremely intense photon fluxes at frequencies
around 30 GHz; transition-edge-sensors (TES) single photon detectors in this
frequency domain, with efficiency $\approx1$; high quality factor Fabry-Perot
cavities in the microwave domain, both on the photon-axion conversion and
photon regeneration sides. We compute that present laboratory exclusion limits
on axion-like particles might be improved by at least four orders of magnitude
for axion masses $\lesssim 0.02$ meV.


title:
Near-Surface Boundary Layer Turbulence Along a Horizontally-Moving,
  Surface-Piercing Vertical Wall

abstract:
  The complex interaction between turbulence and the free surface in boundary
layer shear flow created by a vertical surface-piercing wall is considered. A
laboratory-scale device was built that utilizes a surface-piercing stainless
steel belt that travels in a loop around two vertical rollers, with one length
of the belt between the rollers acting as a horizontally-moving flat wall. The
belt is accelerated suddenly from rest until reaching constant speed in order
to create a temporally-evolving boundary layer analogous to the
spatially-evolving boundary layer that would exist along a surface-piercing
towed flat plate. Surface profiles are measured with a cinematic laser-induced
fluorescence system and sub-surface velocity fields are recorded using a
high-speed planar particle image velocimetry system. It is found that the belt
initially travels through the water without creating any significant waves,
before the free surface bursts with activity close to the belt surface. These
free surface ripples travel away from the belt before appearing to become
freely-propagating waves. From sub-surface velocity measurements, it is found
that close to the surface, transition to turbulence happens sooner than far
from the surface, leading to an overall thicker boundary layer in the vicinity
of the free surface. A secondary peak in streamwise velocity fluctuations
accompanies this transition to turbulence and this peak reaches a maximum value
a short time later before smoothing outward. Using momentum thickness as a
length scale and the streamwise velocity fluctuations at the location of this
outer peak as a velocity scale, free surface bursting and air entrainment onset
are found to depend in some way on Weber number and agreement is found with
scaling arguments for air entrainment presented by Brocchini and Pregrine (J.
Fluid Mech., 499, 225-254, 2001).


title:
Data assimilation for the heat equation using stabilized finite element
  methods

abstract:
  We consider data assimilation for the heat equation using a finite element
space semi-discretization. The approach is optimization based, but the design
of regularization operators and parameters rely on techniques from the theory
of stabilized finite elements. The space semi-discretized system is shown to
admit a unique solution. Combining sharp estimates of the numerical stability
of the discrete scheme and conditional stability estimates of the ill-posed
continuous pde-model we then derive error estimates that reflect the
approximation order of the finite element space and the stability of the
continuous model. Two different data assimilation situations with different
stability properties are considered to illustrate the framework. Full detail on
how to adapt known stability estimates for the continuous model to work with
the numerical analysis framework is given in appendix.


title: A multi-sensor multi-Bernoulli filter

abstract:
  In this paper we derive a multi-sensor multi-Bernoulli (MS-MeMBer) filter for
multi-target tracking. Measurements from multiple sensors are employed by the
proposed filter to update a set of tracks modeled as a multi-Bernoulli random
finite set. An exact implementation of the MS-MeMBer update procedure is
computationally intractable. We propose an efficient approximate implementation
by using a greedy measurement partitioning mechanism. The proposed filter
allows for Gaussian mixture or particle filter implementations. Numerical
simulations conducted for both linear-Gaussian and non-linear models highlight
the improved accuracy of the MS-MeMBer filter and its reduced computational
load with respect to the multi-sensor cardinalized probability hypothesis
density filter and the iterated-corrector cardinality-balanced multi-Bernoulli
filter especially for low probabilities of detection.


title: Preferential sampling of helicity by isotropic helicoids

abstract:
  We present a theoretical and numerical study on the motion of isotropic
helicoids in complex flows. These are particles whose motion is invariant under
rotations but not under mirror reflections of the particle. This is the
simplest, yet unexplored, extension of the much studied case of small spherical
particles. We show that heavy isotropic helicoids, due to the coupling between
translational and rotational degrees of freedom, preferentially sample
different helical regions in laminar or chaotic advecting flows. This opens the
way to control and engineer particles able to track complex flow structures
with potential applications to microfluidics and turbulence.


title: Parameterized and Approximation Complexity of Partial VC Dimension

abstract:
  We introduce the problem Partial VC Dimension that asks, given a hypergraph
$H=(X,E)$ and integers $k$ and $\ell$, whether one can select a set $C\subseteq
X$ of $k$ vertices of $H$ such that the set $\{e\cap C, e\in E\}$ of distinct
hyperedge-intersections with $C$ has size at least $\ell$. The sets $e\cap C$
define equivalence classes over $E$. Partial VC Dimension is a generalization
of VC Dimension, which corresponds to the case $\ell=2^k$, and of
Distinguishing Transversal, which corresponds to the case $\ell=|E|$ (the
latter is also known as Test Cover in the dual hypergraph). We also introduce
the associated fixed-cardinality maximization problem Max Partial VC Dimension
that aims at maximizing the number of equivalence classes induced by a solution
set of $k$ vertices. We study the algorithmic complexity of Partial VC
Dimension and Max Partial VC Dimension both on general hypergraphs and on more
restricted instances, in particular, neighborhood hypergraphs of graphs.


title:
Detection with Multimodal Dependent Data Using Low Dimensional Random
  Projections

abstract:
  Performing likelihood ratio based detection with high dimensional multimodal
data is a challenging problem since the computation of the joint probability
density functions (pdfs) in the presence of inter-modal dependence is
difficult. While some computationally expensive approaches have been proposed
for dependent multimodal data fusion (e.g., based on copula theory), a commonly
used tractable approach is to compute the joint pdf as the product of marginal
pdfs ignoring dependence. However, this method leads to poor performance when
the data is strongly dependent. In this paper, we consider the problem of
detection when dependence among multimodal data is modeled in a compressed
domain where compression is obtained using low dimensional random projections.
We employ a Gaussian approximation while modeling inter-modal dependence in the
compressed domain which is computationally more efficient. We show that, under
certain conditions, detection with multimodal dependent data in the compressed
domain with a small number of compressed measurements yields enhanced
performance compared to detection with high dimensional data via either the
product approach or other suboptimal fusion approaches proposed in the
literature.


title: Barcodes for Medical Image Retrieval Using Autoencoded Radon Transform

abstract:
  Using content-based binary codes to tag digital images has emerged as a
promising retrieval technology. Recently, Radon barcodes (RBCs) have been
introduced as a new binary descriptor for image search. RBCs are generated by
binarization of Radon projections and by assembling them into a vector, namely
the barcode. A simple local thresholding has been suggested for binarization.
In this paper, we put forward the idea of "autoencoded Radon barcodes". Using
images in a training dataset, we autoencode Radon projections to perform
binarization on outputs of hidden layers. We employed the mini-batch stochastic
gradient descent approach for the training. Each hidden layer of the
autoencoder can produce a barcode using a threshold determined based on the
range of the logistic function used. The compressing capability of autoencoders
apparently reduces the redundancies inherent in Radon projections leading to
more accurate retrieval results. The IRMA dataset with 14,410 x-ray images is
used to validate the performance of the proposed method. The experimental
results, containing comparison with RBCs, SURF and BRISK, show that autoencoded
Radon barcode (ARBC) has the capacity to capture important information and to
learn richer representations resulting in lower retrieval errors for image
retrieval measured with the accuracy of the first hit only.


title: Bleach: A Distributed Stream Data Cleaning System

abstract:
  In this paper we address the problem of rule-based stream data cleaning,
which sets stringent requirements on latency, rule dynamics and ability to cope
with the unbounded nature of data streams.
  We design a system, called Bleach, which achieves real-time violation
detection and data repair on a dirty data stream. Bleach relies on efficient,
compact and distributed data structures to maintain the necessary state to
repair data, using an incremental version of the equivalence class algorithm.
Additionally, it supports rule dynamics and uses a "cumulative" sliding window
operation to improve cleaning accuracy.
  We evaluate a prototype of Bleach using a TPC-DS derived dirty data stream
and observe its high throughput, low latency and high cleaning accuracy, even
with rule dynamics. Experimental results indicate superior performance of
Bleach compared to a baseline system built on the micro-batch streaming
paradigm.


title: Staggered domain wall fermions

abstract:
  We construct domain wall fermions with a staggered kernel and investigate
their spectral and chiral properties numerically in the Schwinger model. In
some relevant cases we see an improvement of chirality by more than an order of
magnitude as compared to usual domain wall fermions. Moreover, we present first
results for four-dimensional quantum chromodynamics, where we also observe
significant reductions of chiral symmetry violations for staggered domain wall
fermions.


title: Dense Wide-Baseline Scene Flow From Two Handheld Video Cameras

abstract:
  We propose a new technique for computing dense scene flow from two handheld
videos with wide camera baselines and different photometric properties due to
different sensors or camera settings like exposure and white balance. Our
technique innovates in two ways over existing methods: (1) it supports
independently moving cameras, and (2) it computes dense scene flow for
wide-baseline scenarios.We achieve this by combining state-of-the-art
wide-baseline correspondence finding with a variational scene flow formulation.
First, we compute dense, wide-baseline correspondences using DAISY descriptors
for matching between cameras and over time. We then detect and replace occluded
pixels in the correspondence fields using a novel edge-preserving Laplacian
correspondence completion technique. We finally refine the computed
correspondence fields in a variational scene flow formulation. We show dense
scene flow results computed from challenging datasets with independently
moving, handheld cameras of varying camera settings.


title:
Adaptive Windowing for ICI Mitigation in Doubly Selective Channels with
  Unknown Statistics

abstract:
  In doubly selective channels, receiver windowing constitutes an effective
technique for enhancing the banded structure of the frequency-domain channel
matrix, and thus improving the effectiveness of a banded equalizer for
intercarrier interference (ICI) mitigation. A common window design technique,
which performs close to optimal, is based on the criterion of maximum average
signal-to-interference-plus-noise ratio (SINR). The optimality of this
technique has been verified for stationary channels with perfectly known
statistics. However, in cases where this assumption does not hold, a near
optimal performance can be achieved at the expense of high complexity cost. To
overcome these limitations, an adaptive windowing technique is proposed that is
able to track the optimal receiver window offering low-complexity requirements.
Through simulation experiments it has been verified that the proposed technique
is able to adapt to the varying channel statistics with increased robustness to
channel modeling errors.


title:
Troisi\`eme groupe de cohomologie non ramifi\'ee des torseurs universels
  sur les surfaces rationnelles

abstract:
  Let $k$ a field of characteristic zero. Let $X$ be a smooth, projective,
geometrically rational $k$-surface. Let $\mathcal{T}$ be a universal torsor
over $X$ with a $k$-point et $\mathcal{T}^c$ a smooth compactification of
$\mathcal{T}$. There is an open question: is $\mathcal{T}^c$ $k$-birationally
equivalent to a projective space? We know that the unramified cohomology groups
of degree 1 and 2 of $\mathcal{T}$ and $\mathcal{T}^c$ are reduced to their
constant part. For the analogue of the third cohomology groups, we give a
sufficient condition using the Galois structure of the geometrical Picard group
of $X$. This enables us to show that
$H^{3}_{nr}(\mathcal{T}^{c},\mathbb{Q}/\mathbb{Z}(2))/H^3(k,\mathbb{Q}/\mathbb{Z}(2))$
vanishes if $X$ is a generalised Ch\^atelet surface and that this group is
reduced to its $2$-primary part if $X$ is a del Pezzo surface of degree at
least 2.


title: Radon-Gabor Barcodes for Medical Image Retrieval

abstract:
  In recent years, with the explosion of digital images on the Web,
content-based retrieval has emerged as a significant research area. Shapes,
textures, edges and segments may play a key role in describing the content of
an image. Radon and Gabor transforms are both powerful techniques that have
been widely studied to extract shape-texture-based information. The combined
Radon-Gabor features may be more robust against scale/rotation variations,
presence of noise, and illumination changes. The objective of this paper is to
harness the potentials of both Gabor and Radon transforms in order to introduce
expressive binary features, called barcodes, for image annotation/tagging
tasks. We propose two different techniques: Gabor-of-Radon-Image Barcodes
(GRIBCs), and Guided-Radon-of-Gabor Barcodes (GRGBCs). For validation, we
employ the IRMA x-ray dataset with 193 classes, containing 12,677 training
images and 1,733 test images. A total error score as low as 322 and 330 were
achieved for GRGBCs and GRIBCs, respectively. This corresponds to $\approx
81\%$ retrieval accuracy for the first hit.


title:
Deep Impression: Audiovisual Deep Residual Networks for Multimodal
  Apparent Personality Trait Recognition

abstract:
  Here, we develop an audiovisual deep residual network for multimodal apparent
personality trait recognition. The network is trained end-to-end for predicting
the Big Five personality traits of people from their videos. That is, the
network does not require any feature engineering or visual analysis such as
face detection, face landmark alignment or facial expression recognition.
Recently, the network won the third place in the ChaLearn First Impressions
Challenge with a test accuracy of 0.9109.


title: Triangular reductions of 2D Toda hierarchy

abstract:
  New reductions of the 2D Toda equations associated with low-triangular
difference operators are proposed. Their explicit Hamiltonian description is
obtained.


title: Cooper pairs and bipolarons

abstract:
  It is shown that Cooper pairs are a solution of the bipolaron problem for
model Fr\"{o}hlich Hamiltonian. The total energy of a pair for the initial
Fr\"{o}hlich Hamiltonian is found. Differences between the solutions for the
model and initial two-particle problems are discussed.


title:
Search for anomalous electroweak production of $WW/WZ$ in association
  with a high-mass dijet system in $pp$ collisions at $\sqrt{s}=8$ TeV with the
  ATLAS detector

abstract:
  A search is presented for anomalous quartic gauge boson couplings in
vector-boson scattering. The data for the analysis correspond to $20.2$
fb$^{-1}$ of $\sqrt{s}=8$ TeV $pp$ collisions, and were collected in 2012 by
the ATLAS experiment at the Large Hadron Collider. The search looks for the
production of $WW$ or $WZ$ boson pairs accompanied by a high-mass dijet system,
with one $W$ decaying leptonically, and a $W$ or $Z$ decaying hadronically. The
hadronically decaying $W/Z$ is reconstructed as either two small-radius jets or
one large-radius jet using jet substructure techniques. Constraints on the
anomalous quartic gauge boson coupling parameters $\alpha_4$ and $\alpha_5$ are
set by fitting the transverse mass of the diboson system, and the resulting 95%
confidence intervals are $-0.024<\alpha_4<0.030$ and $-0.028<\alpha_5<0.033$.


title: Learning Opposites Using Neural Networks

abstract:
  Many research works have successfully extended algorithms such as
evolutionary algorithms, reinforcement agents and neural networks using
"opposition-based learning" (OBL). Two types of the "opposites" have been
defined in the literature, namely \textit{type-I} and \textit{type-II}. The
former are linear in nature and applicable to the variable space, hence easy to
calculate. On the other hand, type-II opposites capture the "oppositeness" in
the output space. In fact, type-I opposites are considered a special case of
type-II opposites where inputs and outputs have a linear relationship. However,
in many real-world problems, inputs and outputs do in fact exhibit a nonlinear
relationship. Therefore, type-II opposites are expected to be better in
capturing the sense of "opposition" in terms of the input-output relation. In
the absence of any knowledge about the problem at hand, there seems to be no
intuitive way to calculate the type-II opposites. In this paper, we introduce
an approach to learn type-II opposites from the given inputs and their outputs
using the artificial neural networks (ANNs). We first perform \emph{opposition
mining} on the sample data, and then use the mined data to learn the
relationship between input $x$ and its opposite $\breve{x}$. We have validated
our algorithm using various benchmark functions to compare it against an
evolving fuzzy inference approach that has been recently introduced. The
results show the better performance of a neural approach to learn the
opposites. This will create new possibilities for integrating oppositional
schemes within existing algorithms promising a potential increase in
convergence speed and/or accuracy.


title:
Critical Rayleigh number of for error function temperature profile with
  a quasi-static assumption

abstract:
  When a semi-infinite body is heated from below by a sudden increase in
temperature (or cooled from above) an error function temperature profile grows
as the heat diffuses into the fluid. The stability of such a profile is
investigated using a large-wavelength asymptotic expansion under the
quasi-static, or frozen-time, approximation. The critical Rayleigh number for
this layer is found to be $Ra=\pi^{1/2}$ based on the length-scale $(\kappa
t)^{1/2}$ where $\kappa$ is the thermal diffusivity and $t$ the time since the
onset of heating.


title:
Counting unstable eigenvalues in Hamiltonian spectral problems via
  commuting operators

abstract:
  We present a general counting result for the unstable eigenvalues of linear
operators of the form $JL$ in which $J$ and $L$ are skew- and self-adjoint
operators, respectively. Assuming that there exists a self-adjoint operator $K$
such that the operators $JL$ and $JK$ commute, we prove that the number of
unstable eigenvalues of $JL$ is bounded by the number of nonpositive
eigenvalues of~$K$. As an application, we discuss the transverse stability of
one-dimensional periodic traveling waves in the classical KP-II
(Kadomtsev--Petviashvili) equation. We show that these one-dimensional periodic
waves are transversely spectrally stable with respect to general
two-dimensional bounded perturbations, including periodic and localized
perturbations in either the longitudinal or the transverse direction, and that
they are transversely linearly stable with respect to doubly periodic
perturbations.

categories: nlin.SI math-ph math.AP math.DS math.MP nlin.PS


title:
On regular Stein neighborhoods of a union of two maximal totally real
  subspaces in $\mathbb{C}^n$

abstract:
  We present a construction of regular Stein neighborhoods of a union of
maximally totally real subspaces $M=(A+iI)\mathbb{R}^n$ and $N=\mathbb{R}^n$ in
$\mathbb{C}^n$, provided that the entries of a real $n \times n$ matrix $A$ are
sufficiently small. Our proof is based on a local construction of a suitable
plurisubharmonic function $\rho$ near the origin, such that the sublevel sets
of $\rho$ are strongly pseudoconvex and admit strong deformation retraction to
$M\cup N$. We also give the application of this result to totally real
immersions of real $n$-manifolds in $\mathbb{C}^n$ with only finitely many
double points, and such that the union of the tangent spaces at each
intersection in some local coordinates coincides with $M\cup N$, described
above.


title:
Skew plane partitions according to the $m$th largest and $m$th smallest
  parts

abstract:
  We extend recent results by G. E. Andrews and G. Simay on the $m$th largest
and $m$th smallest parts of a partition to the more general context of skew
plane partitions. In order to do this, we introduce new objects called skew
plane overpartitions.


title: Epidemic Processes over Time-Varying Networks

abstract:
  The spread of viruses in biological networks, computer networks, and human
contact networks can have devastating effects; developing and analyzing
mathematical models of these systems can be insightful and lead to societal
benefits. Prior research has focused mainly on network models with static graph
structures, however the systems being modeled typically have dynamic graph
structures. Therefore to better understand and analyze virus spread, further
study is required. In this paper, we consider virus spread models over networks
with dynamic graph structures, and investigate the behavior of diseases in
these systems. A stability analysis of epidemic processes over time-varying
networks is performed, examining conditions for the disease free equilibrium,
in both the deterministic and stochastic cases. We present simulation results,
propose a number of corollaries based on these simulations, and discuss
quarantine control via simulation.


title:
A geometric invariant characterising initial data for the Kerr-Newman
  spacetime

abstract:
  We describe the construction of a geometric invariant characterising initial
data for the Kerr-Newman spacetime. This geometric invariant vanishes if and
only if the initial data set corresponds to exact Kerr-Newman initial data, and
so characterises this type of data. We first illustrate the characterisation of
the Kerr-Newman spacetime in terms of Killing spinors. The space spinor
formalism is then used to obtain a set of four independent conditions on an
initial Cauchy hypersurface that guarantee the existence of a Killing spinor on
the development of the initial data. Following a similar analysis in the vacuum
case, we study the properties of solutions to the approximate Killing spinor
equation and use them to construct the geometric invariant.


title:
SemanticFusion: Dense 3D Semantic Mapping with Convolutional Neural
  Networks

abstract:
  Ever more robust, accurate and detailed mapping using visual sensing has
proven to be an enabling factor for mobile robots across a wide variety of
applications. For the next level of robot intelligence and intuitive user
interaction, maps need extend beyond geometry and appearence - they need to
contain semantics. We address this challenge by combining Convolutional Neural
Networks (CNNs) and a state of the art dense Simultaneous Localisation and
Mapping (SLAM) system, ElasticFusion, which provides long-term dense
correspondence between frames of indoor RGB-D video even during loopy scanning
trajectories. These correspondences allow the CNN's semantic predictions from
multiple view points to be probabilistically fused into a map. This not only
produces a useful semantic 3D map, but we also show on the NYUv2 dataset that
fusing multiple predictions leads to an improvement even in the 2D semantic
labelling over baseline single frame predictions. We also show that for a
smaller reconstruction dataset with larger variation in prediction viewpoint,
the improvement over single frame segmentation increases. Our system is
efficient enough to allow real-time interactive use at frame-rates of
approximately 25Hz.


title:
Global Sensitivity Analysis in a Mathematical Model of the Renal
  Interstitium

abstract:
  The pressure in the renal interstitium is an important factor for normal
kidney function. Here we develop a computational model of the rat kidney and
use it to investigate the relationship between arterial blood pressure and
interstitial fluid pressure. In addition, we investigate how tissue flexibility
influences this relationship. Due to the complexity of the model, the large
number of parameters, and the inherent uncertainty of the experimental data, we
utilize Monte Carlo sampling to study the model's behavior under a wide range
of parameter values and to compute first- and total-order sensitivity indices.
Characteristically, at elevated arterial blood pressure, the model predicts
cases with increased or reduced interstitial pressure. The transition between
the two cases is controlled mostly by the compliance of the blood vessels
located before the afferent arterioles.


title:
Low Complexity Multiply Accumulate Unit for Weight-Sharing Convolutional
  Neural Networks

abstract:
  Convolutional Neural Networks (CNNs) are one of the most successful deep
machine learning technologies for processing image, voice and video data. CNNs
require large amounts of processing capacity and memory, which can exceed the
resources of low power mobile and embedded systems. Several designs for
hardware accelerators have been proposed for CNNs which typically contain large
numbers of Multiply Accumulate (MAC) units. One approach to reducing data sizes
and memory traffic in CNN accelerators is "weight sharing", where the full
range of values in a trained CNN are put in bins and the bin index is stored
instead of the original weight value. In this paper we propose a novel MAC
circuit that exploits binning in weight-sharing CNNs. Rather than computing the
MAC directly we instead count the frequency of each weight and place it in a
bin. We then compute the accumulated value in a subsequent multiply phase. This
allows hardware multipliers in the MAC circuit to be replaced with adders and
selection logic. Experiments show that for the same clock speed our approach
results in fewer gates, smaller logic, and reduced power.


title: On finite determinacy for matrices of power series

abstract:
  Let $R=K[[x_1,...,x_s]]$ be the ring of formal power series with maximal
ideal $\mathfrak{m}$ over a field $K$ of arbitrary characteristic. On the ring
$M_{m,n}$ of $m\times n$ matrices $A$ with entries in $R$ we consider several
equivalence relations given by the action on $M_{m,n}$ of a group $G$. $G$ can
be the group of automorphisms of $R$, combined with the multiplication of
invertible matrices from the left, from the right, or from both sides,
respectively. We call $A$ finitely $G$-determined if $A$ is $G$-equivalent to
any matrix $B$ with ${A-B} \in {\mathfrak{m}^k M_{m,n}}$ for some finite
integer $k$, which implies in particular that $A$ is $G$--equivalent to a
matrix with polynomial entries.
  The classical criterion for analytic or differential map germs $f:(K^s,0) \to
(K^m,0)$, $K = \mathbb{R}, \mathbb{C}$, says that $f \in M_{m,1}$ is finitely
determined (with respect to various group actions) iff the tangent space to the
orbit of $f$ has finite codimension in $M_{m,1}$. We extend this criterion to
arbitrary matrices in $M_{m,n}$ if the characteristic of K is 0 or, more
general, if the orbit map is separable. In positive characteristic however, the
problem is more subtle since the orbit map is in general not separable, as we
show by an example. This fact had been overlooked in previous papers. Our main
result is a general sufficient criterion for finite $G$-determinacy in
$M_{m,n}$ in arbitrary characteristic in terms of the tangent image of the
orbit map, which we introduce in this paper. This criterion provides a
computable bound for the $G$-determinacy of a matrix $A$ in $M_{m,n}$, which is
new even in characteristic 0.


title: Intrinsic coherence in assisted sub-state discrimination

abstract:
  We study intrinsic coherence in the tripartite process to unambiguously
discriminate two nonorthogonal states of a qubit, entangled with another one,
and assisted by an auxiliary system. The optimal success probability is found
to be benefited by initial intrinsic coherence, but no extra one is required.
The transformations among different contributions of intrinsic coherence are
necessary in this procedure, which increase with the overlap between the states
to recognize. Such state discrimination is a key step of the probabilistic
teleportation protocol. Entanglement of the quantum channel decreases the
coherence characterizing the reliance on an ancilla.


title:
Virtual Micromagnetics: A Framework for Accessible and Reproducible
  Micromagnetic Simulation

abstract:
  Computational micromagnetics requires numerical solution of partial
differential equations to resolve complex interactions in magnetic
nanomaterials. The Virtual Micromagnetics project described here provides
virtual machine simulation environments to run open-source micromagnetic
simulation packages. These environments allow easy access to simulation
packages that are often difficult to compile and install, and enable
simulations and their data to be shared and stored in a single virtual hard
disk file, which encourages reproducible research. Virtual Micromagnetics can
be extended to automate the installation of micromagnetic simulation packages
on non-virtual machines, and to support closed-source and new open-source
simulation packages, including packages from disciplines other than
micromagnetics, encouraging reuse. Virtual Micromagnetics is stored in a public
GitHub repository under a three-clause Berkeley Software Distribution (BSD)
license.


title: Hardness Results for Consensus-Halving

abstract:
  We study the consensus-halving problem of dividing an object into two
portions, such that each of $n$ agents has equal valuation for the two
portions. The $\epsilon$-approximate consensus-halving problem allows each
agent to have an $\epsilon$ discrepancy on the values of the portions. We prove
that computing $\epsilon$-approximate consensus-halving solution using $n$ cuts
is in PPA, and is PPAD-hard, where $\epsilon$ is some positive constant; the
problem remains PPAD-hard when we allow a constant number of additional cuts.
It is NP-hard to decide whether a solution with $n-1$ cuts exists for the
problem. As a corollary of our results, we obtain that the approximate
computational version of the Continuous Necklace Splitting Problem is PPAD-hard
when the number of portions $t$ is two.


title:
A unifying framework for fast randomization of ecological networks with
  fixed (node) degrees

abstract:
  The switching model is a Markov chain approach to sample graphs with fixed
degree sequence uniformly at random. The recently invented Curveball algorithm
for bipartite graphs applies several switches simultaneously (`trades'). Here,
we introduce Curveball algorithms for simple (un)directed graphs which use
single or simultaneous trades. We show experimentally that these algorithms
converge magnitudes faster than the corresponding switching models.


title:
Heavy flavor Production and Interactions in Relativistic Heavy-Ion
  Collisions in CMS Experiment

abstract:
  This paper presents the CMS measurements of quarkonia and open heavy flavor
production in \pp, \pPb, and \PbPb collisions at \sqrtsnn = 2.76 and 5.02 TeV.
A brief outlook of the near-future CMS heavy flavor physics analyses is
provided at the end.


title:
Existence of weak solutions for a general porous medium equation with
  nonlocal pressure

abstract:
  We study the general nonlinear diffusion equation $u_t=\nabla\cdot
(u^{m-1}\nabla (-\Delta)^{-s}u)$ that describes a flow through a porous medium
which is driven by a nonlocal pressure. We consider constant parameters $m>1$
and $0<s<1$, we assume that the solutions are non-negative and the problem is
posed in the whole space. In this paper we prove existence of weak solutions
for all integrable initial data $u_0 \ge 0$ and for all exponents $m>1$ by
developing a new approximation method that allows to treat the range $m\ge 3$
that could not be covered by previous works. We also extend the class of
initial data to include any non-negative measure $\mu$ with finite mass. In
passing from bounded initial data to measure data we make strong use of an
$L^1$-$L^\infty$ smoothing effect and other functional estimates. Finite speed
of propagation is established for all $m\ge 2$, and this property implies the
existence of free boundaries. The authors had already proved that finite
propagation does not hold for $m<2$.


title: The Option-Critic Architecture

abstract:
  Temporal abstraction is key to scaling up learning and planning in
reinforcement learning. While planning with temporally extended actions is well
understood, creating such abstractions autonomously from data has remained
challenging. We tackle this problem in the framework of options [Sutton, Precup
& Singh, 1999; Precup, 2000]. We derive policy gradient theorems for options
and propose a new option-critic architecture capable of learning both the
internal policies and the termination conditions of options, in tandem with the
policy over options, and without the need to provide any additional rewards or
subgoals. Experimental results in both discrete and continuous environments
showcase the flexibility and efficiency of the framework.


title: STEM: A Scheme for Two-phase Evaluation of Majority Logic

abstract:
  The switching time of a magnet in a spin current based majority gate depends
on the input vector combination, and this often restricts the speed of
majority-based circuits. To address this issue, this work proposes a novel
two-phase scheme to implement majority logic and evaluates it on an all-spin
logic (ASL) majority-based logic structures. In Phase 1, the output is
initialized to a preset value. Next in Phase 2, the inputs are evaluated to
switch the output magnet to its correct value. The time window for the output
to switch in Phase 2 is fixed. Using such a scheme, an n-input AND gate which
requires a total of (2n-1) inputs in the conventional implementation can now be
implemented with only (n+1) inputs. When applied to standard logic functions,
it is demonstrated that the proposed method of designing ASL gates are 1.6-3.4X
faster and 1.9-6.9X more energy-efficient than the conventional method, and for
a five-magnet full adder, it is shown that the proposed ASL implementation is
1.5X faster, 2.2X more energy-efficient, and provides a 16% improvement in
area.


title: Spectral geometry of the Steklov problem on orbifolds

abstract:
  We consider how the geometry and topology of a compact $n$-dimensional
Riemannian orbifold with boundary relates to its Steklov spectrum. In two
dimensions, motivated by work of A. Girouard, L. Parnovski, I. Polterovich and
D. Sher in the manifold setting, we compute the precise asymptotics of the
Steklov spectrum in terms of only boundary data. As a consequence, we prove
that the Steklov spectrum detects the presence and number of orbifold
singularities on the boundary of an orbisurface and it detects the number each
of smooth and singular boundary components. Moreover, we find that the Steklov
spectrum also determines the lengths of the boundary components modulo an
equivalence relation, and we show by examples that this result is the best
possible. We construct various examples of Steklov isospectral Riemannian
orbifolds which demonstrate that these two-dimensional results do not extend to
higher dimensions. In addition, we give two-dimensional examples which show
that the Steklov spectrum does \emph{not} detect the presence of interior
singularities nor does it determine the orbifold Euler characteristic. In fact,
a flat disk is Steklov isospectral to a cone.
  In another direction, we obtain upper bounds on the Steklov eigenvalues of a
Riemannian orbifold in terms of the isoperimetric ratio and a conformal
invariant. We generalize results of B. Colbois, A. El Soufi and A. Girouard,
and the fourth author to the orbifold setting; in the process, we gain a
sharpness result on these bounds that was not evident in the manifold setting.
In dimension two, our eigenvalue bounds are solely in terms of the orbifold
Euler characteristic and the number each of smooth and singular boundary
components.


title:
Target-driven Visual Navigation in Indoor Scenes using Deep
  Reinforcement Learning

abstract:
  Two less addressed issues of deep reinforcement learning are (1) lack of
generalization capability to new target goals, and (2) data inefficiency i.e.,
the model requires several (and often costly) episodes of trial and error to
converge, which makes it impractical to be applied to real-world scenarios. In
this paper, we address these two issues and apply our model to the task of
target-driven visual navigation. To address the first issue, we propose an
actor-critic model whose policy is a function of the goal as well as the
current state, which allows to better generalize. To address the second issue,
we propose AI2-THOR framework, which provides an environment with high-quality
3D scenes and physics engine. Our framework enables agents to take actions and
interact with objects. Hence, we can collect a huge number of training samples
efficiently.
  We show that our proposed method (1) converges faster than the
state-of-the-art deep reinforcement learning methods, (2) generalizes across
targets and across scenes, (3) generalizes to a real robot scenario with a
small amount of fine-tuning (although the model is trained in simulation), (4)
is end-to-end trainable and does not need feature engineering, feature matching
between frames or 3D reconstruction of the environment.
  The supplementary video can be accessed at the following link:
https://youtu.be/SmBxMDiOrvs.


title:
Photoproduction of a large invariant mass $\gamma \rho$ pair at small
  momentum transfer

abstract:
  The collinear factorization framework allows to describe the exclusive
photoproduction of a $\gamma\,\rho$ pair in the generalized Bjorken regime in
terms of a perturbatively calculable coefficient function and universal
generalized parton distributions. The kinematics are defined by a large
invariant mass of the $\gamma \rho$ pair and a small transverse momentum of the
final nucleon. We calculate the scattering amplitude at leading order in
$\alpha_s$ and the differential cross sections for the process where the
$\rho-$meson is either longitudinally or transversely polarized, in the
kinematics of the near future Jlab experiments. Our estimate of the cross
section demonstrates that this process is measurable at JLab 12-GeV.


title:
The $A^2$ asymmetry and propagators in lattice $SU(2)$ gluodynamics at
  $T>T_c$

abstract:
  We study numerically the chromoelectric-chromomagnetic asymmetry of the
dimension two $A^2$ gluon condensate as well as the transverse and longitudinal
gluon propagators at $T>T_c$ in the Landau-gauge $SU(2)$ lattice gauge theory
with a particular emphasis on finite-volume effects. We show that previously
found so called symmetric point at which asymmetry changes sign is an artifact
of the finite volume effects. We find that with increasing temperature the
asymmetry decreases approaching zero value from above in agreement with
perturbative result. Instead of the asymmetry we suggest the ratio of the
transverse to longitudinal propagator taken at zero momentum as an indicator of
the boundary of the postconfinement domain and find it at $T \simeq 1.7 T_c$.


title:
On asymptotic dynamics for $L^2$ critical generalized KdV equations with
  a saturated perturbation

abstract:
  In this paper, we consider the $L^2$ critical gKdV equation with a saturated
perturbation: $\partial_t u+(u_{xx}+u^5-\gamma u|u|^{q-1})_x=0$, where $q>5$
and $0<\gamma\ll1$. For any initial data $u_0\in H^1$, the corresponding
solution is always global and bounded in $H^1$. This equation has a family of
solitons, and our goal is to classify the dynamics near soliton. Together with
a suitable decay assumption, there are only three possibilities: (i) the
solution converges asymptotically to a solitary wave, whose $H^1$ norm is of
size $\gamma^{-2/(q-1)}$, as $\gamma\rightarrow0$; (ii) the solution is always
in a small neighborhood of the modulated family of solitary waves, but blows
down at $+\infty$; (iii) the solution leaves any small neighborhood of the
modulated family of the solitary waves. This extends the classification of the
rigidity dynamics near the ground state for the unperturbed $L^2$ critical gKdV
(corresponding to $\gamma=0$) by Martel, Merle and Rapha\"el. However, the
blow-down behavior (ii) is completely new, and the dynamics of the saturated
equation cannot be viewed as a perturbation of the $L^2$ critical dynamics of
the unperturbed equation. This is the first example of classification of the
dynamics near ground state for a saturated equation in this context. The cases
of $L^2$ critical NLS and $L^2$ supercritical gKdV, where similar
classification results are expected, are completely open.


title:
High Contrast Imaging in the Visible: First Experimental Results at the
  Large Binocular Telescope

abstract:
  In February 2014, the SHARK-VIS (System for High contrast And coronography
from R to K at VISual bands) Forerunner, a high contrast experimental imager
operating at visible wavelengths, was installed at LBT (Large Binocular
Telescope). Here we report on the first results obtained by recent on-sky
tests. These results show the extremely good performance of the LBT ExAO
(Extreme Adaptive Optics) system at visible wavelengths, both in terms of
spatial resolution and contrast achieved. Similarly to what was done by (Amara
et al. 2012), we used the SHARK-VIS Forerunner data to quantitatively assess
the contrast enhancement. This is done by injecting several different synthetic
faint objects in the acquired data and applying the ADI (angular differential
imaging) technique. A contrast of the order of $5 \times 10^{-5}$ is obtained
at 630 nm for angular separations from the star larger than 100 mas. These
results are discussed in light of the future development of SHARK-VIS and
compared to those obtained by other high contrast imagers operating at similar
wavelengths.


title:
Discovering and Deciphering Relationships Across Disparate Data
  Modalities

abstract:
  Understanding the relationships between different properties of data, such as
whether a connectome or genome has information about disease status, is
becoming increasingly important in modern biological datasets. While existing
approaches can test whether two properties are related, they often require
unfeasibly large sample sizes in real data scenarios, and do not provide any
insight into how or why the procedure reached its decision. Our approach,
"Multiscale Graph Correlation" (MGC), is a dependence test that juxtaposes
previously disparate data science techniques, including k-nearest neighbors,
kernel methods (such as support vector machines), and multiscale analysis (such
as wavelets). Other methods typically require double or triple the number
samples to achieve the same statistical power as MGC in a benchmark suite
including high-dimensional and nonlinear relationships - spanning polynomial
(linear, quadratic, cubic), trigonometric (sinusoidal, circular, ellipsoidal,
spiral), geometric (square, diamond, W-shape), and other functions, with
dimensionality ranging from 1 to 1000. Moreover, MGC uniquely provides a simple
and elegant characterization of the potentially complex latent geometry
underlying the relationship, providing insight while maintaining computational
efficiency. In several real data applications, including brain imaging and
cancer genetics, MGC is the only method that can both detect the presence of a
dependency and provide specific guidance for the next experiment and/or
analysis to conduct.


title:
Hierarchical Quantum Master Equation Approach to Electronic-Vibrational
  Coupling in Nonequilibrium Transport through Nanosystems

abstract:
  Within the hierarchical quantum master equation (HQME) framework, an approach
is presented, which allows a numerically exact description of nonequilibrium
charge transport in nanosystems with strong electronic-vibrational coupling.
The method is applied to a generic model of vibrationally coupled transport
considering a broad spectrum of parameters ranging from the nonadiabatic to the
adiabatic regime and including both resonant and off-resonant transport. We
show that nonequilibrium effects are important in all these regimes. In
particular in the off-resonant transport regime, the inelastic co-tunneling
signal is analyzed for a vibrational mode in full nonequilibrium, revealing a
complex interplay of different transport processes and deviations from the
commonly used $G_0/2$-thumb-rule. In addition, the HQME-approach is used to
benchmark approximate master equation and nonequilibrium Green's function
methods.


title: Lamda*-Closed sets and new separation axioms in Alexandroff spaces

abstract:
  Here we have studied the ideas of g*-closed sets, g^tou -sets and
Lamda*-closed sets and investigate some of their properties in the spaces of A.
D. Alexandroff [1]. We have also studied few separation axioms like
T-omega/4,T-3omega/8, T-omega in Alexandroff spaces and have introduced a new
separation axiom namely T-5omega/8 axiom in this space.


title:
Random Search with Memory in Patchy Media: Exploration-Exploitation
  Tradeoff

abstract:
  How to best exploit patchy resources? This long-standing question belongs to
the extensively studied class of explore/exploit problems that arise in a wide
range of situations, from animal foraging, to robotic exploration, and to human
decision processes. Despite its broad relevance, the issue of optimal
exploitation has previously only been tackled through two paradigmatic limiting
models---patch-use and random search---that do not account for the interplay
between searcher motion within patches and resource depletion. Here, we bridge
this gap by introducing a minimal patch exploitation model that incorporates
this coupling: the searcher depletes the resources along its random-walk
trajectory within a patch and travels to a new patch after it takes
$\mathcal{S}$ consecutive steps without finding resources. We compute the
distribution of the amount of resources $F_t$ consumed by time $t$ for this
non-Markovian random walker and show that exploring multiple patches is
beneficial. In one dimension, we analytically derive the optimal strategy to
maximize $F_t$. We show that this strategy is robust with respect to the
distribution of resources within patches and the criterion for leaving a given
patch. We also show that $F_t$ can be optimized in the ecologically-relevant
case of two-dimensional patchy environments.


title:
Style Imitation and Chord Invention in Polyphonic Music with Exponential
  Families

abstract:
  Modeling polyphonic music is a particularly challenging task because of the
intricate interplay between melody and harmony. A good model should satisfy
three requirements: statistical accuracy (capturing faithfully the statistics
of correlations at various ranges, horizontally and vertically), flexibility
(coping with arbitrary user constraints), and generalization capacity
(inventing new material, while staying in the style of the training corpus).
Models proposed so far fail on at least one of these requirements. We propose a
statistical model of polyphonic music, based on the maximum entropy principle.
This model is able to learn and reproduce pairwise statistics between
neighboring note events in a given corpus. The model is also able to invent new
chords and to harmonize unknown melodies. We evaluate the invention capacity of
the model by assessing the amount of cited, re-discovered, and invented chords
on a corpus of Bach chorales. We discuss how the model enables the user to
specify and enforce user-defined constraints, which makes it useful for
style-based, interactive music generation.


title:
The Emergence of Solar Supergranulation as a Natural Consequence of
  Rotationally-Constrained Interior Convection

abstract:
  We investigate how rotationally-constrained, deep convection might give rise
to supergranulation, the largest distinct spatial scale of convection observed
in the solar photosphere. While supergranulation is only weakly influenced by
rotation, larger spatial scales of convection sample the deep convection zone
and are presumably rotationally influenced. We present numerical results from a
series of nonlinear, 3-D simulations of rotating convection and examine the
velocity power distribution realized under a range of Rossby numbers. When
rotation is present, the convective power distribution possesses a pronounced
peak, at characteristic wavenumber $\ell_\mathrm{peak}$, whose value increases
as the Rossby number is decreased. This distribution of power contrasts with
that realized in non-rotating convection, where power increases monotonically
from high to low wavenumbers. We find that spatial scales smaller than
$\ell_\mathrm{peak}$ behave in analogy to non-rotating convection. Spatial
scales larger than $\ell_\mathrm{peak}$ are rotationally-constrained and
possess substantially reduced power relative to the non-rotating system. We
argue that the supergranular scale emerges due to a suppression of power on
spatial scales larger than $\ell\approx100$ owing to the presence of deep,
rotationally-constrained convection. Supergranulation thus represents the
largest non-rotationally-constrained mode of solar convection. We conclude that
the characteristic spatial scale of supergranulation bounds that of the deep
convective motions from above, making supergranulation an indirect measure of
the deep-seated dynamics at work in the solar dynamo. Using the spatial scale
of supergranulation in conjunction with our numerical results, we estimate an
upper bound of 10 m s$^{-1}$ for the Sun's bulk rms convective velocity.


title: Relatively hyperbolic groups with fixed peripherals

abstract:
  We build quasi--isometry invariants of relatively hyperbolic groups which
detect the hyperbolic parts of the group; these are variations of the stable
dimension constructions previously introduced by the authors.
  We prove that, given any finite collection of finitely generated groups
$\mathcal{H}$ each of which either has finite stable dimension or is
non-relatively hyperbolic, there exist infinitely many quasi--isometry types of
one--ended groups which are hyperbolic relative to $\mathcal{H}$.
  The groups are constructed using small cancellation theory over free
products.


title: Ultrafast Magnetic Switching of GdFeCo with Electronic Heat Currents

abstract:
  We report the magnetic response of Au/GdFeCo bilayers to optical irradiation
of the Au surface. For bilayers with Au thickness greater than 50 nm, the great
majority of energy is absorbed by the Au electrons, creating an initial
temperature differential of thousands of Kelvin between the Au and GdFeCo
layers. The resulting electronic heat currents between the Au and GdFeCo layers
last for several picoseconds with energy flux in excess of 2 TW m-2, and
provide sufficient heating to the GdFeCo electrons to induce deterministic
reversal of the magnetic moment.


title:
Finite dimensional thermo-mechanical systems and second order
  constraints

abstract:
  In this paper we study a class of physical systems that combine a finite
number of mechanical and thermodynamic observables. We call them finite
dimensional thermo-mechanical systems. We introduce these systems by means of
simple examples. The evolution equations of the involved observables are
obtained in each example by using, essentially, the Newton's law and the First
Law of Thermodynamics only. We show that such equations are similar to those
defining certain mechanical systems with higher order constraints. Moreover, we
show that all of the given examples can be described in a variational formalism
in terms of second order constrained systems.

categories: math-ph math.DG math.MP physics.class-ph