title: An elementary proof of a conjecture on graph-automorphism

abstract:
  In this article, we give an elementary combinatorial proof of a conjecture
about the determination of automorphism group of the power graph of finite
cyclic groups, proposed by Doostabadi, Erfanian and Jafarzadeh in 2013.


title: Lie applicable surfaces

abstract:
  We give a detailed account of the gauge-theoretic approach to Lie applicable
surfaces and the resulting transformation theory. In particular, we show that
this approach coincides with the classical notion of $\Omega$- and
$\Omega_{0}$-surfaces of Demoulin.


title:
Energy Saving of Base Stations Sleep Scheduling for Multi-Hop Vehicular
  Networks

abstract:
  This paper investigates the energy saving of base station (BS) deployed in a
1-D multi-hop vehicular network with sleep scheduling strategy. We consider
cooperative BS scheduling strategy where BSs can switch between sleep and
active modes to reduce the average energy consumption utilizing the information
of vehicular speeds and locations. Assuming a Poisson distribution of vehicles,
we derive an appropriate probability distribution function of distance between
two adjacent cluster heads, where a cluster is a maximal set of vehicles in
which every two adjacent vehicles can communicate directly when their Euclidean
distance is less than or equal to a threshold, known as the communication range
of vehicles. Furthermore, the expected value of the sojourn time in the sleep
mode and energy saving are obtained. The numerical results show that the sleep
scheduling strategy significantly reduces the energy consumption of the base
stations.


title: A Boyer-Moore Type Algorithm for Timed Pattern Matching

abstract:
  The timed pattern matching problem is formulated by Ulus et al. and has been
actively studied since, with its evident application in monitoring real-time
systems. The problem takes as input a timed word/signal and a timed pattern
(specified either by a timed regular expression or by a timed automaton); and
it returns the set of those intervals for which the given timed word, when
restricted to the interval, matches the given pattern. We contribute a
Boyer-Moore type optimization in timed pattern matching, relying on the classic
Boyer-Moore string matching algorithm and its extension to (untimed) pattern
matching by Watson and Watson. We assess its effect through experiments; for
some problem instances our Boyer-Moore type optimization achieves speed-up by
two times, indicating its potential in real-world monitoring tasks where data
sets tend to be massive.


title: Optimal Evacuation Flows on Dynamic Paths with General Edge Capacities

abstract:
  A Dynamic Graph Network is a graph in which each edge has an associated
travel time and a capacity (width) that limits the number of items that can
travel in parallel along that edge. Each vertex in this dynamic graph network
begins with the number of items that must be evacuated into designated sink
vertices. A $k$-sink evacuation protocol finds the location of $k$ sinks and
associated evacuation movement protocol that allows evacuating all the items to
a sink in minimum time. The associated evacuation movement must impose a
confluent flow, i.e, all items passing through a particular vertex exit that
vertex using the same edge. In this paper we address the $k$-sink evacuation
problem on a dynamic path network. We provide solutions that run in $O(n \log
n)$ time for $k=1$ and $O(k n \log^2 n)$ for $k >1$ and work for arbitrary edge
capacities.


title: Synchronization of two cavity-coupled qubits measured by entanglement

abstract:
  Some nonlinear radiations such as superfluorescence can be understood as
cooperative effects between atoms. We regard the cooperative radiation as a
manifested effect secondary to the intrinsic synchronization among the atoms
and propose a time-resolved measure of synchronization on a cavity-coupled
dual-qubit system using multipartite concurrence. Comparing the variation of
the concurrence over time with that of an asynchronicity measure, we find that
the synchronization between the qubits features a time delay characteristic to
the initiation of superfluorescent pulses. The delay coincides with the
duration for the qubits to establish cooperation and emit the collective
radiation, after which the concurrence monotonically increases to a stationary
value while the asynchronicity dives to a steady minimum. Furthermore, the
establishment of synchronization is determined by the qubit-cavity coupling
strength. Asynchronicity shows that synchronization is only possible when the
coupling enters strong regime and sustains to a high level when the coupling
becomes ultra-strong.


title: Particles as superoscillations of spacetime with a nonlocal metric?

abstract:
  Einstein field equations show how matter curve spacetime, but, does curved
spacetime creates matter? And if so, can we have geometrical foundations to
every matter in the universe? In this note, we suggest an approach to derive
non-general relativistic dynamics of particles as curvatures of spacetime under
the assumption of nonlocality. In particular, we examine the possibility that
particles are obtained by superoscillatory functions of spacetime. By
introducing a metric that has an impact on every point in spacetime, we give a
precondition for nonlocality under this ontic model. The model is deterministic
and contains a nonlocal hidden variable. This hidden variable is the mass
density of the global metric. Due to the uncertainty principle, this hidden
variable is hidden in the sense that for getting full information about it one
should concentrate energy/momentum in a small volume in spacetime that it will
create a black hole which will destroy the mass-density at that particular
area. Therefore, it remains hidden by the protection of spacetime itself and
its geometric structure.


title: Toward a Deep Neural Approach for Knowledge-Based IR

abstract:
  This paper tackles the problem of the semantic gap between a document and a
query within an ad-hoc information retrieval task. In this context, knowledge
bases (KBs) have already been acknowledged as valuable means since they allow
the representation of explicit relations between entities. However, they do not
necessarily represent implicit relations that could be hidden in a corpora.
This latter issue is tackled by recent works dealing with deep representation
learn ing of texts. With this in mind, we argue that embedding KBs within deep
neural architectures supporting documentquery matching would give rise to
fine-grained latent representations of both words and their semantic relations.
In this paper, we review the main approaches of neural-based document ranking
as well as those approaches for latent representation of entities and relations
via KBs. We then propose some avenues to incorporate KBs in deep neural
approaches for document ranking. More particularly, this paper advocates that
KBs can be used either to support enhanced latent representations of queries
and documents based on both distributional and relational semantics or to serve
as a semantic translator between their latent distributional representations.


title:
Implications of a zero-nonlinearity wavelength in optical fibers doped
  with silver nanoparticles

abstract:
  Photonic crystal fibers doped with silver nanoparticles exhibit the Kerr
nonlinearity that can be positive or negative depending on wavelength and
vanishes at a specific wavelength. We study numerically how the simultaneous
presence of a zero-nonlinearity wavelength (ZNW) and a zero-dispersion
wavelength affects evolution of soliton and supercontinuum generation inside
such fibers and find a number of unique features. The existence of negative
nonlinearity allows soliton formation even in the normaldispersion region of
the fiber, and the ZNW acts as a barrier for the Raman-induced red shift of
solitons.


title:
Disappearance of macroscopic superpositions in perfectly isolated
  systems

abstract:
  Schr\"odinger's illustration of an imaginary cat in a box, neither alive nor
dead, leads to a question of whether and how long a macroscopic quantum
superposition can exist in various situations. It is well known that a
macroscopic superposition is destroyed very quickly by environmental effects
called decoherence. On the contrary, it is often believed that a macroscopic
superposition continues to "survive" if it is ideally isolated from its
environment. In this paper, using a well-established measure of macroscopic
superpositions and the eigenstate thermalization hypothesis, we show that
macroscopic superpositions even in ideally closed systems are destroyed by
thermalization processes. We further investigate specific examples of a
disordered Heisenberg spin chain varied between the thermalization phase and
the many-body localized (MBL) phase. This leads to consistent results; initial
macroscopic superpositions disappear under thermalization while they may be
preserved in the MBL phase in which thermalization does not occur.


title: The problematic growth of dust in high redshift galaxies

abstract:
  Dust growth via accretion of gas species has been proposed as the dominant
process to increase the amount of dust in galaxies. We show here that this
hypothesis encounters severe difficulties that make it unfit to explain the
observed UV and IR properties of such systems, particularly at high redshifts.
Dust growth in the diffuse ISM phases is hampered by (a) too slow accretion
rates; (b) too high dust temperatures, and (c) the Coulomb barrier that
effectively blocks accretion. In molecular clouds these problems are largely
alleviated. Grains are cold (but not colder than the CMB temperature, (Tcmb =
20 K at redshift z=6). However, in dense environments accreted materials form
icy water mantles, perhaps with impurities. Mantles are immediately
photo-desorbed as grains return to the diffuse ISM at the end of the cloud
lifetime, thus erasing any memory of the growth. We conclude that dust
attenuating stellar light at high-$z$ must be ready-made stardust largely
produced in supernova ejecta.


title: Optimal Local and Remote Controllers with Unreliable Communication

abstract:
  We consider a decentralized optimal control problem for a linear plant
controlled by two controllers, a local controller and a remote controller. The
local controller directly observes the state of the plant and can inform the
remote controller of the plant state through a packet-drop channel. We assume
that the remote controller is able to send acknowledgments to the local
controller to signal the successful receipt of transmitted packets. The
objective of the two controllers is to cooperatively minimize a quadratic
performance cost. We provide a dynamic program for this decentralized control
problem using the common information approach. Although our problem is not a
partially nested LQG problem, we obtain explicit optimal strategies for the two
controllers. In the optimal strategies, both controllers compute a common
estimate of the plant state based on the common information. The remote
controller's action is linear in the common estimated state, and the local
controller's action is linear in both the actual state and the common estimated
state.


title:
Loose crystalline lifts and overconvergence of \'etale $(\varphi,
  \tau)$-modules

abstract:
  Let $p$ be a prime, $K$ a finite extension of $\mathbb Q_p$, and let $G_K$ be
the absolute Galois group of $K$. The category of \'etale $(\varphi,
\tau)$-modules is equivalent to the category of $p$-adic Galois representations
of $G_K$. In this paper, we show that all \'etale $(\varphi, \tau)$-modules are
overconvergent; this answers a question of Caruso. Our result is an analogy of
the classical overconvergence result of Cherbonnier and Colmez in the setting
of \'etale $(\varphi, \Gamma)$-modules. However, our method is completely
different from theirs. Indeed, we first show that all $p$-power-torsion
representations admit loose crystalline lifts; this allows us to construct
certain Kisin models in these torsion representations. We study the structure
of these Kisin models, and use them to build an overconvergence basis.


title:
Understanding doping, vacancy, lattice stability and superconductivity
  in KxFe2-ySe2

abstract:
  Metal-intercalated iron selenides are a class of superconductors that have
received much attention but are less understood in comparison with their
FeAs-based counterparts. Here, the controversial issues such as Fe vacancy, the
real phase responsible for superconductivity, and lattice stability have been
addressed based on first-principles calculations. New insights into the
distinct features in terms of carrier doping have been revealed.


title:
A Cloudiness Index for Transiting Exoplanets Based on the Sodium and
  Potassium Lines: Tentative Evidence for Hotter Atmospheres Being Less Cloudy
  at Visible Wavelengths

abstract:
  We present a dimensionless index that quantifies the degree of cloudiness of
the atmosphere of a transiting exoplanet. Our cloudiness index is based on
measuring the transit radii associated with the line center and wing of the
sodium or potassium line. In deriving this index, we revisited the algebraic
formulae for inferring the isothermal pressure scale height from transit
measurements. We demonstrate that the formulae of Lecavelier et al. and Benneke
& Seager are identical: the former is inferring the temperature while assuming
a value for the mean molecular mass and the latter is inferring the mean
molecular mass while assuming a value for the temperature. More importantly,
these formulae cannot be used to distinguish between cloudy and cloudfree
atmospheres. We derive values of our cloudiness index for a small sample of 7
hot Saturns/Jupiters taken from Sing et al. We show that WASP-17b, WASP-31b and
HAT-P-1b are nearly cloudfree at visible wavelengths. We find the tentative
trend that more irradiated atmospheres tend to have less clouds consisting of
sub-micron-sized particles. We also derive absolute sodium and/or potassium
abundances $\sim 10^2$ cm$^{-3}$ for WASP-17b, WASP-31b and HAT-P-1b (and upper
limits for the other objects). Higher-resolution measurements of both the
sodium and potassium lines, for a larger sample of exoplanetary atmospheres,
are needed to confirm or refute this trend.


title:
Learning Dynamic Classes of Events using Stacked Multilayer Perceptron
  Networks

abstract:
  People often use a web search engine to find information about events of
interest, for example, sport competitions, political elections, festivals and
entertainment news. In this paper, we study a problem of detecting
event-related queries, which is the first step before selecting a suitable
time-aware retrieval model. In general, event-related information needs can be
observed in query streams through various temporal patterns of user search
behavior, e.g., spiky peaks for popular events, and periodicities for
repetitive events. However, it is also common that users search for non-popular
events, which may not exhibit temporal variations in query streams, e.g., past
events recently occurred, historical events triggered by anniversaries or
similar events, and future events anticipated to happen. To address the
challenge of detecting dynamic classes of events, we propose a novel deep
learning model to classify a given query into a predetermined set of multiple
event types. Our proposed model, a Stacked Multilayer Perceptron (S-MLP)
network, consists of multilayer perceptron used as a basic learning unit. We
assemble stacked units to further learn complex relationships between neutrons
in successive layers. To evaluate our proposed model, we conduct experiments
using real-world queries and a set of manually created ground truth.
Preliminary results have shown that our proposed deep learning model
outperforms the state-of-the-art classification models significantly.


title: A long-lived Zeeman trapped-ion qubit

abstract:
  We demonstrate a coherence time of 2.1(1)~s for electron spin superposition
states of a single trapped $^{40}$Ca$^+$ ion. The coherence time, measured with
a spin-echo experiment, corresponds to residual rms magnetic field fluctuations
$\leq$~2.7$\times$10$^{-12}$~T. The suppression of decoherence induced by
fluctuating magnetic fields is achieved by combining a two-layer $\mu$-metal
shield, which reduces external magnetic noise by 20 to 30~dB for frequencies of
50~Hz to 100~kHz, with Sm$_2$Co$_{17}$ permanent magnets for generating a
quantizing magnetic field of 0.37~mT. Our results extend the coherence time of
the simple-to-operate spin qubit to ultralong coherence times which so far have
been observed only for magnetic insensitive transitions in atomic qubits with
hyperfine structure.


title: Packaging stiff polymers in small containers: A molecular dynamics study

abstract:
  The question of how stiff polymers are able to pack into small containers is
particularly relevant to the study of DNA packaging in viruses. A reduced
version of the problem based on coarse-grained representations of the main
components of the system -- the DNA polymer and the spherical viral capsid --
has been studied by molecular dynamics simulation. The results, involving
longer polymers than in earlier work, show that as polymers become more rigid
there is an increasing tendency to self-organize as spools that wrap from the
inside out, rather than the inverse direction seen previously. In the final
state, a substantial part of the polymer is packed into one or more coaxial
spools, concentrically layered with different orientations, a form of packaging
achievable without twisting the polymer.


title: Toward Realistic Gauge-Higgs Grand Unification

abstract:
  The $SO(11)$ gauge-Higgs grand unification in the Randall-Sundrum warped
space is presented. The 4D Higgs field is identified as the zero mode of the
fifth dimensional component of the gauge potentials, or as the fluctuation mode
of the Aharonov-Bohm phase $\theta_H$ along the fifth dimension. Fermions are
introduced in the bulk in the spinor and vector representations of $SO(11)$.
$SO(11)$ is broken to $SO(4) \times SO(6)$ by the orbifold boundary conditions,
which is broken to $SU(2)_L \times U(1)_Y \times SU(3)_C$ by a brane scalar.
Evaluating the effective potential $V_{\rm eff} (\theta_H)$, we show that the
electroweak symmetry is dynamically broken to $U(1)_{\rm EM}$. The quark-lepton
masses are generated by the Hosotani mechanism and brane interactions, with
which the observed mass spectrum is reproduced. The proton decay is forbidden
thanks to the new fermion number conservation. It is pointed out that there
appear light exotic fermions. The Higgs boson mass is determined with the
quark-lepton masses given, which, however, turns out smaller than the observed
value.


title: Open star cluster: formation, parameters, membership and importance

abstract:
  We have been represented the collective information of estimation procedures
of parameters of the open clusters and put them together for showing the
importance of clusters to understand their role in stellar evolution
phenomenon. Moreover, we have been discussed about analytic techniques to
determine the structural and dynamical properties of galactic clusters. The
members of clusters provide unique opportunity to determine their basic
parameters such as: age, metallicity, distance, reddening etc. The membership
probabilities of stars of clusters is assigned through the various approaches
and each approach provides different number of probable members of the cluster.
Here, we have been briefly discussed about various approaches to determine the
stellar membership within clusters.


title: Reduction of bridge positions along a bridge disk

abstract:
  Suppose a knot in a $3$-manifold is in $n$-bridge position. We consider a
reduction of the knot along a bridge disk $D$ and show that the result is an
$(n-1)$-bridge position if and only if there is a bridge disk $E$ such that
$(D, E)$ is a cancelling pair. We apply this to an unknot $K$, in $n$-bridge
position with respect to a bridge sphere $S$ in the $3$-sphere, to consider the
relationship between a bridge disk $D$ and a disk in the $3$-sphere that $K$
bounds. We show that if a reduction of $K$ along $D$ yields an $(n-1)$-bridge
position, then $K$ bounds a disk that contains $D$ as a subdisk and intersects
$S$ in $n$ arcs.


title: Quark-Pauli effects in three octet-baryons

abstract:
  To sustain a neutron star with about two times the solar mass, multi baryons
including hyperons are expected to produce repulsive effects in the interior of
its high baryon-density region. To examine possible quark-Pauli repulsion among
the baryons, we solve the eigenvalue problem of the quark antisymmetrizer for
three octet-baryons that are described by most compact spatial configurations.
We find that the Pauli blocking effect is weak in the $\Lambda nn$ system,
while it is strong in the $\Sigma^-nn$ system. The appearance of the $\Sigma^-$
hyperon is suppressed in the neutron star interior but no quark-Pauli repulsion
effectively works for the $\Lambda$ hyperon.


title:
Parallel Scheduling Algorithm based on Complex Coloring for Input-Queued
  Switches

abstract:
  This paper explores the application of a new algebraic method of edge
coloring, called complex coloring, to the scheduling problems of input queued
switches. The proposed distributed parallel scheduling algorithm possesses two
important features: optimality and rearrangeability. Optimality ensures that
the algorithm always returns a proper coloring with the minimum number of
required colors, and rearrangeability allows partially re-coloring the existing
connection patterns if the underlying graph only changes slightly. The running
time of the proposed scheduling algorithm is on the order of $O(\log^2 N)$ per
frame, and the amortized time complexity, the time to compute a matching per
timeslot, is only $O(\log N)$. The scheduling algorithm is highly robust in the
face of traffic fluctuations. Since the higher the variable density, the higher
the efficiency of the variable elimination process, complex coloring provides a
natural adaptive solution to non-uniform input traffic patterns. The proposed
scheduling algorithm for packet switching can achieve nearly 100% throughput.


title: Static large deviations for a reaction-diffusion model

abstract:
  We consider the superposition of a symmetric simple exclusion dynamics,
speeded-up in time, with a spin-flip dynamics in a one-dimensional interval
with periodic boundary conditions. We prove the large deviations principle for
the empirical measure under the stationary state. We deduce from this result
that the stationary state is concentrated on the stationary solutions of the
hydrodynamic equation which are stable.


title:
Prevalence and trend estimation from observational data with highly
  variable post-stratification weights

abstract:
  In observational surveys, post-stratification is used to reduce bias
resulting from differences between the survey population and the population
under investigation. However, this can lead to inflated post-stratification
weights and, therefore, appropriate methods are required to obtain less
variable estimates. Proposed methods include collapsing post-strata, trimming
post-stratification weights, generalized regression estimators (GREG) and
weight smoothing models, the latter defined by random-effects models that
induce shrinkage across post-stratum means. Here, we first describe the
weight-smoothing model for prevalence estimation from binary survey outcomes in
observational surveys. Second, we propose an extension of this method for trend
estimation. And, third, a method is provided such that the GREG can be used for
prevalence and trend estimation for observational surveys. Variance estimates
of all methods are described. A simulation study is performed to compare the
proposed methods with other established methods. The performance of the
nonparametric GREG is consistent over all simulation conditions and therefore
serves as a valuable solution for prevalence and trend estimation from
observational surveys. The method is applied to the estimation of the
prevalence and incidence trend of influenza-like illness using the 2010/2011
Great Influenza Survey in Flanders, Belgium.


title:
Kinematics and Magnetic Properties of a Light Bridge in a Decaying
  Sunspot

abstract:
  We present the results obtained by analyzing high spatial and spectral
resolution data of the solar photosphere acquired by the CRisp Imaging
SpectroPolarimeter at the Swedish Solar Telescope on 6 August 2011, relevant to
a large sunspot with a light bridge (LB) observed in NOAA AR 11263. These data
are complemented by simultaneous Hinode Spectropolarimeter (SP) observation in
the Fe I 630.15 nm and 630.25 nm lines. The continuum intensity map shows a
discontinuity of the radial distribution of the penumbral filaments in
correspondence with the LB, which shows a dark lane (about 0.3" wide and about
8.0" long) along its main axis. The available data were inverted with the
Stokes Inversion based on Response functions (SIR) code and physical parameters
maps were obtained. The line-of-sight (LOS) velocity of the plasma along the LB
derived from the Doppler effect shows motions towards and away from the
observer up to 0.6 km/s, which are lower in value than the LOS velocities
observed in the neighbouring penumbral filaments. The noteworthy result is that
we find motions toward the observer up to 0.6 km/s in the dark lane where the
LB is located between two umbral cores, while the LOS velocity motion toward
the observer is strongly reduced where the LB is located between an umbral core
at one side and penumbral filaments on the other side. Statistically, the LOS
velocities correspond to upflows/downflows andcomparing these results with
Hinode/SP data, we conclude that the surrounding magnetic field configuration
(whether more or less inclined) could have a role in maintaining the conditions
for the process of plasma piling up along the dark lane. The results obtained
from our study support and confirm outcomes of recent magnetohydro-dynamic
simulations showing upflows along the main axis of a LBs.


title: Deep Learning Markov Random Field for Semantic Segmentation

abstract:
  Semantic segmentation tasks can be well modeled by Markov Random Field (MRF).
This paper addresses semantic segmentation by incorporating high-order
relations and mixture of label contexts into MRF. Unlike previous works that
optimized MRFs using iterative algorithm, we solve MRF by proposing a
Convolutional Neural Network (CNN), namely Deep Parsing Network (DPN), which
enables deterministic end-to-end computation in a single forward pass.
Specifically, DPN extends a contemporary CNN to model unary terms and
additional layers are devised to approximate the mean field (MF) algorithm for
pairwise terms. It has several appealing properties. First, different from the
recent works that required many iterations of MF during back-propagation, DPN
is able to achieve high performance by approximating one iteration of MF.
Second, DPN represents various types of pairwise terms, making many existing
models as its special cases. Furthermore, pairwise terms in DPN provide a
unified framework to encode rich contextual information in high-dimensional
data, such as images and videos. Third, DPN makes MF easier to be parallelized
and speeded up, thus enabling efficient inference. DPN is thoroughly evaluated
on standard semantic image/video segmentation benchmarks, where a single DPN
model yields state-of-the-art segmentation accuracies on PASCAL VOC 2012,
Cityscapes dataset and CamVid dataset.


title:
A Compact Formulation for the $\ell_{2,1}$ Mixed-Norm Minimization
  Problem

abstract:
  Parameter estimation from multiple measurement vectors (MMVs) is a
fundamental problem in many signal processing applications, e.g., spectral
analysis and direction-of- arrival estimation. Recently, this problem has been
address using prior information in form of a jointly sparse signal structure. A
prominent approach for exploiting joint sparsity considers mixed-norm
minimization in which, however, the problem size grows with the number of
measurements and the desired resolution, respectively. In this work we derive
an equivalent, compact reformulation of the $\ell_{2,1}$ mixed-norm
minimization problem which provides new insights on the relation between
different existing approaches for jointly sparse signal reconstruction. The
reformulation builds upon a compact parameterization, which models the
row-norms of the sparse signal representation as parameters of interest,
resulting in a significant reduction of the MMV problem size. Given the sparse
vector of row-norms, the jointly sparse signal can be computed from the MMVs in
closed form. For the special case of uniform linear sampling, we present an
extension of the compact formulation for gridless parameter estimation by means
of semidefinite programming. Furthermore, we derive in this case from our
compact problem formulation the exact equivalence between the $\ell_{2,1}$
mixed-norm minimization and the atomic-norm minimization. Additionally, for the
case of irregular sampling or a large number of samples, we present a low
complexity, grid-based implementation based on the coordinate descent method.


title: Distributed Wireless Power Transfer with Energy Feedback

abstract:
  Energy beamforming (EB) is a key technique for achieving efficient
radio-frequency (RF) transmission enabled wireless energy transfer (WET). By
optimally designing the waveforms from multiple energy transmitters (ETs) over
the wireless channels, they can be constructively combined at the energy
receiver (ER) to achieve an EB gain that scales with the number of ETs.
However, the optimal design of EB waveforms requires accurate channel state
information (CSI) at the ETs, which is challenging to obtain practically,
especially in a distributed system with ETs at separate locations. In this
paper, we study practical and efficient channel training methods to achieve
optimal EB in a distributed WET system. We propose two protocols with and
without centralized coordination, respectively, where distributed ETs either
sequentially or in parallel adapt their transmit phases based on a
low-complexity energy feedback from the ER. The energy feedback only depends on
the received power level at the ER, where each feedback indicates one
particular transmit phase that results in the maximum harvested power over a
set of previously used phases. Simulation results show that the two proposed
training protocols converge very fast in practical WET systems even with a
large number of distributed ETs, while the protocol with sequential ET phase
adaptation is also analytically shown to converge to the optimal EB design with
perfect CSI by increasing the training time. Numerical results are also
provided to evaluate the performance of the proposed distributed EB and
training designs as compared to other benchmark schemes.


title: Adaptive Task Assignment in Online Learning Environments

abstract:
  With the increasing popularity of online learning, intelligent tutoring
systems are regaining increased attention. In this paper, we introduce adaptive
algorithms for personalized assignment of learning tasks to student so that to
improve his performance in online learning environments. As main contribution
of this paper, we propose a a novel Skill-Based Task Selector (SBTS) algorithm
which is able to approximate a student's skill level based on his performance
and consequently suggest adequate assignments. The SBTS is inspired by the
class of multi-armed bandit algorithms. However, in contrast to standard
multi-armed bandit approaches, the SBTS aims at acquiring two criteria related
to student learning, namely: which topics should the student work on, and what
level of difficulty should the task be. The SBTS centers on innovative reward
and punishment schemes in a task and skill matrix based on the student
behaviour.
  To verify the algorithm, the complex student behaviour is modelled using a
neighbour node selection approach based on empirical estimations of a students
learning curve. The algorithm is evaluated with a practical scenario from a
basic java programming course. The SBTS is able to quickly and accurately adapt
to the composite student competency --- even with a multitude of student
models.


title:
High-order evolving surface finite element method for parabolic problems
  on evolving surfaces

abstract:
  High-order spatial discretisations and full discretisations of parabolic
partial differential equations on evolving surfaces are studied. We prove
convergence of the high-order evolving surface finite element method, by
showing high-order versions of geometric approximation errors and perturbation
error estimates and by the careful error analysis of a modified Ritz map.
Furthermore, convergence of full discretisations using backward difference
formulae and implicit Runge-Kutta methods are also shown.


title:
P-Wave Contact Tensor -- Universal Properties of Axisymmetry-Broken
  P-Wave Fermi Gases

abstract:
  We investigate universal properties of a p-wave Fermi gas with a resonant
interaction in which the axisymmetry is broken spontaneously or externally.
Here, the short-range correlations can be completely characterized by the
nine-component p-wave contact tensor, which can be measured by applying a
generalized adiabatic sweep theorem. The distinctive features of the p-wave
contact tensor emerge in a normal p-wave Fermi gas in an anisotropic trap and
in a superfluid phase. An experimental scheme to measure the p-wave contact
tensor and test the adiabatic sweep theorem is also discussed.


title:
The Edge-Szeged Index and the PI Index of Benzenoid Systems in Linear
  Time

abstract:
  The edge-Szeged index of a graph $G$ is defined as $Sz_e(G) = \sum_{e=uv \in
E(G)}m_u(e)m_v(e)$, where $m_u(e)$ denotes the number of edges of $G$ whose
distance to $u$ is smaller than the distance to $v$ and $m_v(e)$ denotes the
number of edges of $G$ whose distance to $v$ is smaller than the distance to
$u$. Similarly, the PI index is defined as $PI(G) = \sum_{e=uv \in E(G)}(m_u(e)
+ m_v(e))$. In this paper it is shown how the problem of calculating the
indices of a benzenoid system can be reduced to the problem of calculating
weighted indices of three different weighted quotient trees. Furthermore, using
these results, algorithms are established that, for a given benzenoid system
$G$ with $m$ edges, compute the edge-Szeged index and the PI index of $G$ in
$O(m)$ time. Moreover, it is shown that the results can also be applied to
weighted benzenoid systems.


title: Return to the Origin as a Probe of Atomic Phase Coherence

abstract:
  We report on the observation of the coherent enhancement of the return
probability ("enhanced return to the origin" , ERO) in a periodically kicked
cold-atom gas. By submitting an atomic wave packet to a pulsed, periodically
shifted laser standing wave, we induce an oscillation of ERO in time and
explain it in terms of a periodic, reversible dephasing in the
weak-localization interference sequences responsible for ERO. Monitoring the
temporal decay of ERO, we exploit its quantum coherent nature to quantify the
decoherence rate of the atomic system.


title: Further ALMA observations and detailed modeling of the Red Rectangle

abstract:
  We present new high-quality ALMA observations of the Red Rectangle (a well
known post-AGB object) in C17O J=6-5 and H13CN J=4-3 line emission and results
from a new reduction of already published 13CO J=3-2 data. A detailed model
fitting of all the molecular line data, including previous maps and single-dish
spectra, was performed using a sophisticated code. These observations and the
corresponding modeling allowed us to deepen the analysis of the nebular
properties. We also stress the uncertainties in the model fitting.
  We confirm the presence of a rotating equatorial disk and an outflow, which
is mainly formed of gas leaving the disk. The mass of the disk is ~ 0.01 Mo,
and that of the CO-rich outflow is ~ 10 times smaller. High temperatures of ~
100 K are derived for most components. From comparison of the mass values, we
roughly estimate the lifetime of the rotating disk, which is found to be of
about 10000 yr. Taking data of a few other post-AGB composite nebulae into
account, we find that the lifetimes of disks around post-AGB stars typically
range between 5000 and more than 20000 yr. The angular momentum of the disk is
found to be high, ~ 9 Mo AU km/s, which is comparable to that of the stellar
system at present. Our observations of H13CN show a particularly wide velocity
dispersion and indicate that this molecule is only abundant in the inner
Keplerian disk, at ~ 60 AU from the stellar system. We suggest that HCN is
formed in a dense photodissociation region (PDR) due to the UV excess known to
be produced by the stellar system, following chemical mechanisms that are well
established for interstellar medium PDRs and disks orbiting young stars. We
further suggest that this UV excess could lead to the efficient formation and
excitation of PAHs and other C-bearing macromolecules, whose emission is very
intense in the optical counterpart.


title:
Non Local Spatial and Angular Matching : Enabling higher spatial
  resolution diffusion MRI datasets through adaptive denoising

abstract:
  Diffusion magnetic resonance imaging datasets suffer from low Signal-to-Noise
Ratio, especially at high b-values. Acquiring data at high b-values contains
relevant information and is now of great interest for microstructural and
connectomics studies. High noise levels bias the measurements due to the
non-Gaussian nature of the noise, which in turn can lead to a false and biased
estimation of the diffusion parameters. Additionally, the usage of in-plane
acceleration techniques during the acquisition leads to a spatially varying
noise distribution, which depends on the parallel acceleration method
implemented on the scanner. This paper proposes a novel diffusion MRI denoising
technique that can be used on all existing data, without adding to the scanning
time. We first apply a statistical framework to convert the noise to Gaussian
distributed noise, effectively removing the bias. We then introduce a spatially
and angular adaptive denoising technique, the Non Local Spatial and Angular
Matching (NLSAM) algorithm. Each volume is first decomposed in small 4D
overlapping patches to capture the structure of the diffusion data and a
dictionary of atoms is learned on those patches. A local sparse decomposition
is then found by bounding the reconstruction error with the local noise
variance. We compare against three other state-of-the-art denoising methods and
show quantitative local and connectivity results on a synthetic phantom and on
an in-vivo high resolution dataset. Overall, our method restores perceptual
information, removes the noise bias in common diffusion metrics, restores the
extracted peaks coherence and improves reproducibility of tractography. Our
work paves the way for higher spatial resolution acquisition of diffusion MRI
datasets, which could in turn reveal new anatomical details that are not
discernible at the spatial resolution currently used by the diffusion MRI
community.


title:
PAC-Bayesian Analysis for a two-step Hierarchical Multiview Learning
  Approach

abstract:
  We study a two-level multiview learning with more than two views under the
PAC-Bayesian framework. This approach, sometimes referred as late fusion,
consists in learning sequentially multiple view-specific classifiers at the
first level, and then combining these view-specific classifiers at the second
level. Our main theoretical result is a generalization bound on the risk of the
majority vote which exhibits a term of diversity in the predictions of the
view-specific classifiers. From this result it comes out that controlling the
trade-off between diversity and accuracy is a key element for multiview
learning, which complements other results in multiview learning. Finally, we
experiment our principle on multiview datasets extracted from the Reuters
RCV1/RCV2 collection.


title:
Joint User Association and Downlink Beamforming for Green Cloud-RANs
  with Limited Fronthaul

abstract:
  With the explosive growth of smart devices and mobile data traffic, limited
fronthaul capacity has become a notable bottleneck of green communication
access networks, such as cloud radio access networks(C-RANs). In this paper, we
proposed a joint user association and downlink beamforming scheme for green
C-RANs to minimize the network power consumption with the limited fronthaul
links. We first formulate the design problem as a mixed integer nonlinear
programming (MINLP), and then transformed the MINLP problem into a mixed
integer second-order cone program (MI-SOCP) which is a convex program when the
integer variables are fixed. By relaxing the integer variables to continuous
ones, an inflation algorithm, which can be finished within polynomial time, was
proposed to solved the problem. The simulation results are presented to
validate the effectiveness of our proposed algorithm compared with the the
scheme adopted by LTE-A.


title:
Holomorphic normal form of nonlinear perturbations of nilpotent vector
  fields

abstract:
  We consider germs of holomorphic vector fields at a fixed point having a
nilpotent linear part at that point, in dimension $n \geq 3$. Based on
Belitskii's work, we know that such a vector field is formally conjugate to a
(formal) normal form. We give a condition on that normal form which ensure that
the normalizing transformation is holomorphic at the fixed point. We shall show
that this sufficient condition is a nilpotent version of Bruno's condition (A).
In dimension 2, no condition is required since, according to Str{\'o}zyna-
Zoladek, each such germ is holomorphically conjugate to a Takens normal form.
Our proof is based on Newton's method and $\frak{sl}\_2(\Bbb
C)$-representations.


title:
Recovery of time-dependent coefficient on Riemanian manifold for
  hyperbolic equations

abstract:
  Given $(M,g)$, a compact connected Riemannian manifold of dimension $d \geq
2$, with boundary $\partial M$, we study the inverse boundary value problem of
determining a time-dependent potential $q$, appearing in the wave equation
$\partial_t^2u-\Delta_g u+q(t,x)u=0$ in $\bar M=(0,T)\times M$ with $T>0$.
Under suitable geometric assumptions we prove global unique determination of
$q\in L^\infty(\bar M)$ given the Cauchy data set on the whole boundary
$\partial \bar M$, or on certain subsets of $\partial \bar M$. Our problem can
be seen as an analogue of the Calder\'on problem on the Lorentzian manifold
$(\bar M, dt^2 - g)$.


title: Strong times and first hitting

abstract:
  We generalize the notion of strong stationary time and we give a
representation formula for the hitting time to a target set in the general case
of non-reversible Markov processes.


title: Molecules associated to Hardy spaces with pointwise variable anisotropy

abstract:
  In this paper we introduce molecules associated to Hardy spaces with
pointwise variable anisotropy, and prove that each molecule can be represented
as a sum of atoms.


title: Testing for simultaneous jumps in case of asynchronous observations

abstract:
  This paper proposes a novel test for simultaneous jumps in a bivariate It\^o
semimartingale when observation times are asynchronous and irregular. Inference
is built on a realized correlation coefficient for the jumps of the two
processes which is estimated using bivariate power variations of
Hayashi-Yoshida type without an additional synchronization step. An associated
central limit theorem is shown whose asymptotic distribution is assessed using
a bootstrap procedure. Simulations show that the test works remarkably well in
comparison with the much simpler case of regular observations.


title: Human Computer Interaction Using Marker Based Hand Gesture Recognition

abstract:
  Human Computer Interaction (HCI) has been redefined in this era. People want
to interact with their devices in such a way that has physical significance in
the real world, in other words, they want ergonomic input devices. In this
paper, we propose a new method of interaction with computing devices having a
consumer grade camera, that uses two colored markers (red and green) worn on
tips of the fingers to generate desired hand gestures, and for marker detection
and tracking we used template matching with kalman filter. We have implemented
all the usual system commands, i.e., cursor movement, right click, left click,
double click, going forward and backward, zoom in and out through different
hand gestures. Our system can easily recognize these gestures and give
corresponding system commands. Our system is suitable for both desktop devices
and devices where touch screen is not feasible like large screens or projected
screens.


title: The Carath\'eodory-Fej\'er interpolation problem for the polydisc

abstract:
  We give an algorithm for finding a solution to the Carath\'{e}odory-Fej\'{e}r
interpolation problem on the polydisc $\mathbb D^n,$ whenever it exists. A
necessary condition for the existence of a solution becomes apparent from this
algorithm. A generalization of the well-known theorem due to Nehari has been
obtained. A proof of the Kor\'{a}nyi--Puk\'{a}nszky theorem is given using the
spectral theorem.


title:
Galois covers of type (p,...,p), vanishing cycles formula, and the
  existence of torsor structures

abstract:
  In this article we prove a local Riemman-Hurwitz formula which compares the
dimensions of the spaces of vanishing cycles in a finite Galois cover of type
(p,p,...,p) between formal germs of p-adic curves and which generalises the
formula proven by the first author in the case of Galois covers of degree p. We
also investigate the problem of the existence of a torsor structure for a
finite Galois cover of type (p,p,...,p) between p-adic schemes.


title:
The best m-term approximation with respect to polynomials with constant
  coefficients

abstract:
  In this paper we show that that greedy bases can be defined as those where
the error term using $m$-greedy approximant is uniformly bounded by the best
$m$-term approximation with respect to polynomials with constant coefficients
in the context of the weak greedy algorithm and weights.


title: Algorithmic Composition of Melodies with Deep Recurrent Neural Networks

abstract:
  A big challenge in algorithmic composition is to devise a model that is both
easily trainable and able to reproduce the long-range temporal dependencies
typical of music. Here we investigate how artificial neural networks can be
trained on a large corpus of melodies and turned into automated music composers
able to generate new melodies coherent with the style they have been trained
on. We employ gated recurrent unit networks that have been shown to be
particularly efficient in learning complex sequential activations with
arbitrary long time lags. Our model processes rhythm and melody in parallel
while modeling the relation between these two features. Using such an approach,
we were able to generate interesting complete melodies or suggest possible
continuations of a melody fragment that is coherent with the characteristics of
the fragment itself.


title: On the effective Lagrangian of CP^(N-1) models in the large N limit

abstract:
  The effective low energy Lagrangian of $CP^{N-1}$ models in $d < 4$
dimensions can be constructed in the large $N$ limit by solving the saddle
point equations in the presence of a constant field strength. The two
dimensional case is explicitly worked out and possible applications are briefly
discussed.


title:
Robust 3D Hand Pose Estimation in Single Depth Images: from Single-View
  CNN to Multi-View CNNs

abstract:
  Articulated hand pose estimation plays an important role in human-computer
interaction. Despite the recent progress, the accuracy of existing methods is
still not satisfactory, partially due to the difficulty of embedded
high-dimensional and non-linear regression problem. Different from the existing
discriminative methods that regress for the hand pose with a single depth
image, we propose to first project the query depth image onto three orthogonal
planes and utilize these multi-view projections to regress for 2D heat-maps
which estimate the joint positions on each plane. These multi-view heat-maps
are then fused to produce final 3D hand pose estimation with learned pose
priors. Experiments show that the proposed method largely outperforms
state-of-the-art on a challenging dataset. Moreover, a cross-dataset experiment
also demonstrates the good generalization ability of the proposed method.


title: Hodge-Theoretic Mirror Symmetry for Toric Stacks

abstract:
  Using the mirror theorem [CCIT15], we give a Landau-Ginzburg mirror
description for the big equivariant quantum cohomology of toric Deligne-Mumford
stacks. More precisely, we prove that the big equivariant quantum D-module of a
toric Deligne-Mumford stack is isomorphic to the Saito structure associated to
the mirror Landau-Ginzburg potential. We give a GKZ-style presentation of the
quantum D-module, and a combinatorial description of quantum cohomology as a
quantum Stanley-Reisner ring. We establish the convergence of the mirror
isomorphism and of quantum cohomology in the big and equivariant setting.


title:
Radiation hardness test of un-doped CsI crystals and Silicon
  Photomultipliers for the Mu2e calorimeter

abstract:
  The Mu2e calorimeter is composed by 1400 un-doped CsI crystals coupled to
large area UV extended Silicon Photomultipliers arranged in two annular disks.
This calorimeter has to provide precise information on energy, timing and
position. It should also be fast enough to handle the high rate background and
it must operate and survive in a high radiation environment. Simulation studies
estimated that, in the hottest regions, each crystal will absorb a dose of 300
Gy and will be exposed to a neutron fluency of 6 x 10^{11} n/cm^2 in 3 years of
running.
  Test of un-doped CsI crystals irradiated up to 900 Gy and to a neutron
fluency up to 9 x 10^{11} n/cm^2 have been performed at CALLIOPE and FNG ENEA
facilities in Italy. We present our study on the variation of light yield (LY)
and longitudinal response uniformity (LRU) of these crystals after irradiation.
The ionization dose does not modify LRU while a 20% reduction in LY is observed
at 900 Gy. Similarly, the neutron flux causes an acceptable LY deterioration
(<15%). A neutron irradiation test on different types of SIPMs (two different
array models from Hamamatsu and one from FBK) have also been carried out by
measuring the variation of the leakage current and the charge response to an
ultraviolet led. We concluded that, in the experiment, we will need to cool
down the SIPMs to 0 C reduce the leakage current to an acceptable level.


title: Saliency Driven Object recognition in egocentric videos with deep CNN

abstract:
  The problem of object recognition in natural scenes has been recently
successfully addressed with Deep Convolutional Neuronal Networks giving a
significant break-through in recognition scores. The computational efficiency
of Deep CNNs as a function of their depth, allows for their use in real-time
applications. One of the key issues here is to reduce the number of windows
selected from images to be submitted to a Deep CNN. This is usually solved by
preliminary segmentation and selection of specific windows, having outstanding
"objectiveness" or other value of indicators of possible location of objects.
In this paper we propose a Deep CNN approach and the general framework for
recognition of objects in a real-time scenario and in an egocentric
perspective. Here the window of interest is built on the basis of visual
attention map computed over gaze fixations measured by a glass-worn
eye-tracker. The application of this set-up is an interactive user-friendly
environment for upper-limb amputees. Vision has to help the subject to control
his worn neuro-prosthesis in case of a small amount of remaining muscles when
the EMG control becomes unefficient. The recognition results on a specifically
recorded corpus of 151 videos with simple geometrical objects show the mAP of
64,6\% and the computational time at the generalization lower than a time of a
visual fixation on the object-of-interest.


title: Prehomogeneous tensor spaces

abstract:
  We refine the classification of prehomogeneous vector spaces, provided by
Sato-Kimura, in the case of tensor spaces, presenting a quick way to check
whether a given tensor space is prehomogeneous or not.


title: On the power graph of the direct product of two groups

abstract:
  The power graph $P(G)$ of a finite group $G$ is the graph with vertex set $G$
and two distinct vertices are adjacent if either of them is a power of the
other. Here we show that the power graph $P(G_1 \times G_2)$ of the direct
product of two groups $G_1$ and $G_2$ is not isomorphic to either of the
direct, cartesian and normal product of their power graphs $P(G_1)$ and
$P(G_2)$. A new product of graphs, namely generalized product, has been
introduced and we prove that the power graph $P(G_1 \times G_2)$ is isomorphic
to a generalized product of $P(G_1)$ and $P(G_2)$.


title: Log-based Evaluation of Label Splits for Process Models

abstract:
  Process mining techniques aim to extract insights in processes from event
logs. One of the challenges in process mining is identifying interesting and
meaningful event labels that contribute to a better understanding of the
process. Our application area is mining data from smart homes for elderly,
where the ultimate goal is to signal deviations from usual behavior and provide
timely recommendations in order to extend the period of independent living.
Extracting individual process models showing user behavior is an important
instrument in achieving this goal. However, the interpretation of sensor data
at an appropriate abstraction level is not straightforward. For example, a
motion sensor in a bedroom can be triggered by tossing and turning in bed or by
getting up. We try to derive the actual activity depending on the context
(time, previous events, etc.). In this paper we introduce the notion of label
refinements, which links more abstract event descriptions with their more
refined counterparts. We present a statistical evaluation method to determine
the usefulness of a label refinement for a given event log from a process
perspective. Based on data from smart homes, we show how our statistical
evaluation method for label refinements can be used in practice. Our method was
able to select two label refinements out of a set of candidate label
refinements that both had a positive effect on model precision.


title: KW-models for (multivariate) linear differential systems

abstract:
  A class of state models, called Kronecker-Weierstrass models (or, simply,
KW-models), is introduced, and the state representation problem for linear
differential systems is studied in the context of these models. It is shown, in
particular, that there is a canonical one-to-one correspondence between linear
differential systems and similarity classes of minimal proper KW-models.


title: Real-time cosmography with redshift derivatives

abstract:
  The drift in the redshift of objects passively following the cosmological
expansion has long been recognized as a key model-independent probe of
cosmology. Here, we study the cosmological relevance of measurements of time or
redshift derivatives of this drift, arguing that the combination of first and
second redshift derivatives is a powerful test of the $\Lambda$CDM cosmological
model. In particular, the latter can be obtained numerically from a set of
measurements of the drift at different redshifts. We show that, in the
low-redshift limit, a measurement of the derivative of the drift can provide a
constraint on the jerk parameter, which is $j=1$ for flat $\Lambda$CDM, while
generically $j\neq1$ for other models. We emphasize that such a measurement is
well within the reach of the ELT-HIRES and SKA Phase 2 array surveys.


title:
On the Theoretical Capacity of Evolution Strategies to Statistically
  Learn the Landscape Hessian

abstract:
  We study the theoretical capacity to statistically learn local landscape
information by Evolution Strategies (ESs). Specifically, we investigate the
covariance matrix when constructed by ESs operating with the selection operator
alone. We model continuous generation of candidate solutions about quadratic
basins of attraction, with deterministic selection of the decision vectors that
minimize the objective function values. Our goal is to rigorously show that
accumulation of winning individuals carries the potential to reveal valuable
information about the search landscape, e.g., as already practically utilized
by derandomized ES variants. We first show that the statistically-constructed
covariance matrix over such winning decision vectors shares the same
eigenvectors with the Hessian matrix about the optimum. We then provide an
analytic approximation of this covariance matrix for a non-elitist multi-child
$(1,\lambda)$-strategy, which holds for a large population size $\lambda$.
Finally, we also numerically corroborate our results.


title: Finite phylogenetic complexity and combinatorics of tables

abstract:
  We prove that the phylogenetic complexity -- an invariant introduced by
Sturmfels and Sullivant -- of any finite abelian group is finite.


title: Graphs of hyperbolic groups and a limit set intersection theorem

abstract:
  Minor changes in the exposition and small corrections on the previous
version.


title: $\Psi$-Epistemic Quantum Cosmology?

abstract:
  This paper provides a prospectus for a new way of thinking about the
wavefunction of the universe: a $\Psi$-epistemic quantum cosmology. We present
a proposal that, if successfully implemented, would resolve the cosmological
measurement problem and simultaneously allow us to think sensibly about
probability and evolution in quantum cosmology. Our analysis draws upon recent
work on the problem of time in quantum gravity, upon causally-symmetric local
hidden variable theories, and upon a dynamical origin for the cosmological
arrow of time. Our conclusion weighs the strengths and weaknesses of the
approach and points towards paths for future development.


title:
The abundance and thermal history of water ice in the disk surrounding
  HD142527 from the DIGIT Herschel Key Program

abstract:
  The presence or absence of ice in protoplanetary disks is of great importance
for the formation of planets. By enhancing the solid surface density and
increasing the sticking efficiency, ice catalyzes the rapid formation of
planetesimals and decreases the time scale for giant planet core accretion.
Aims: In this paper we analyse the composition of the outer disk around the
Herbig star HD~142527. We focus on the composition of the water ice, but also
analyse the abundances of previously proposed minerals. Methods: We present new
Herschel far infrared spectra and a re-reduction of archival data from the
Infrared Space Observatory (ISO). We model the disk using full 3D radiative
transfer to obtain the disk structure. Also, we use an optically thin analysis
of the outer disk spectrum to obtain firm constraints on the composition of the
dust component. Results: The water ice in the disk around HD~142527 contains a
large reservoir of crystalline water ice. We determine the local abundance of
water ice in the outer disk (i.e. beyond 130\,AU). The re-reduced ISO spectrum
differs significantly from that previously published, but matches the new
Herschel spectrum at their common wavelength range. In particular, we do not
detect any significant contribution from carbonates or hydrous silicates, in
contrast to earlier claims. Conclusions: The amount of water ice detected in
the outer disk requires $\sim80\,$\% of the oxygen atoms. This is comparable to
the water ice abundance in the outer solar system, in comets and in dense
interstellar clouds. The water ice is highly crystalline while the temperatures
where we detect it are too low to crystallize the water on relevant time
scales. We discuss the implications of this finding.


title:
Definition, existence, stability and uniqueness of the solution to a
  semilinear elliptic problem with a strong singularity at $ u = 0 $

abstract:
  In this paper we consider a semilinear elliptic equation with a strong
singularity at $u=0$, namely $ \displaystyle u\geq 0 \mbox{ in } \Omega$, $
\displaystyle - div \,A(x) D u = F(x,u) \mbox{ in} \; \Omega$, $u = 0 \mbox{
on} \; \partial \Omega$, with $F(x,s)$ a Carath\'eodory function such that $$
0\leq F(x,s)\leq \frac{h(x)}{\Gamma(s)}\,\,\mbox{ a.e. } x\in\Omega,\, \forall
s>0, $$ with $h$ in some $L^r(\Omega)$ and $\Gamma$ a $C^1([0,+\infty[)$
function such that $\Gamma(0)=0$ and $\Gamma'(s)>0$ for every $s>0$. We
introduce a notion of solution to this problem in the spirit of the solutions
defined by transposition. This definition allows us to prove the existence and
the stability of this solution, as well as its uniqueness when $F(x,s)$ is
nonincreasing in $s$.


title: Semi-supervised Inference: General Theory and Estimation of Means

abstract:
  We propose a general semi-supervised inference framework focused on the
estimation of the population mean. As usual in semi-supervised settings, there
exists an unlabeled sample of covariate vectors and a labeled sample consisting
of covariate vectors along with real-valued responses ("labels"). Otherwise,
the formulation is "assumption-lean" in that no major conditions are imposed on
the statistical or functional form of the data. We consider both the ideal
semi-supervised setting where infinitely many unlabeled samples are available,
as well as the ordinary semi-supervised setting in which only a finite number
of unlabeled samples is available.
  Estimators are proposed along with corresponding confidence intervals for the
population mean. Theoretical analysis on both the asymptotic distribution and
$\ell_2$-risk for the proposed procedures are given. Surprisingly, the proposed
estimators, based on a simple form of the least squares method, outperform the
ordinary sample mean. The simple, transparent form of the estimator lends
confidence to the perception that its asymptotic improvement over the ordinary
sample mean also nearly holds even for moderate size samples. The method is
further extended to a nonparametric setting, in which the oracle rate can be
achieved asymptotically. The proposed estimators are further illustrated by
simulation studies and a real data example involving estimation of the homeless
population.


title:
Stochastic models of the binding kinetics of VEGF-A to VEGFR1 and VEGFR2
  in endothelial cells

abstract:
  Vascular endothelial growth factor receptors (VEGFRs) are receptor tyrosine
kinases (RTKs) that regulate proliferation, migration, angiogenesis and
vascular permeability of endothelial cells. VEGFR1 and VEGFR2 bind vascular
endothelial growth factors (VEGFs), inducing receptor dimerisation and
activation, characterised by phosphorylation of tyrosine residues in their
cytoplasmic domain. Although experimental evidence suggests that RTK signalling
occurs both on the plasma membrane and intra-cellularly, and reveals the role
of endocytosis in RTK signal transduction, we still lack knowledge of VEGFR
phosphorylation-site use and of the spatiotemporal regulation of VEGFR
signalling. In this paper, we introduce four stochastic mathematical models to
study the binding kinetics of vascular endothelial growth factor VEGF-A to
VEGFR1 and VEGFR2, and phosphorylation. The formation of phosphorylated dimers
on the cell surface is a two-step process: diffusive transport and binding. The
first two of our models only consider VEGFR2, which allows us to introduce new
stochastic descriptors making use of a matrix-analytic approach. The two
remaining models describe the competition of VEGFR1 and VEGFR2 for ligand
availability, and are analysed making use of Gillespie simulations and the van
Kampen approximation. Under the hypothesis that bound phosphorylated receptor
dimers are the signalling units, we study the time to reach a threshold number
of such complexes. Our results indicate that the presence of VEGFR1 does not
only affect the timescale to reach a given signalling threshold, but it also
affects the maximum attainable threshold. This result is consistent with the
conjectured role of VEGFR1 as a decoy receptor, that prevents VEGF-A binding to
VEGFR2, and thus, VEGFR2 attaining suitable phosphorylation levels. We identify
an optimum range of ligand concentration for sustained dimer phosphorylation.


title:
Recursion Operators admitted by non-Abelian Burgers equations: Some
  Remarks

abstract:
  The recursion operators admitted by different operator Burgers equations, in
the framework of the study of nonlinear evolution equations, are here con-
sidered. Specifically, evolution equations wherein the unknown is an operator
acting on a Banach space are investigated. Here, the mirror non-Abelian Burgers
equation is considered: it can be written as $r_t = r_{xx} + 2r_x r$. The
structural properties of the admitted recursion operator are studied; thus, it
is proved to be a strong symmetry for the mirror non-Abelian Burgers equation
as well as to be the hereditary. These results are proved via direct
computations as well as via computer assisted manipulations; ad hoc routines
are needed to treat non-Abelian quantities and relations among them. The
obtained recursion operator generates the $mirror$ non-Abelian Burgers
hierarchy. The latter, when the unknown operator $r$ is replaced by a real
valued function reduces to the usual (commutative) Burgers hierarchy.
Accordingly, also the recursion operator reduces to the usual Burgers one.


title: Forward and backward galaxy evolution in comoving number density space

abstract:
  Galaxy comoving number density is commonly used to forge
progenitor/descendant links between observed galaxy populations at different
epochs. However, this method breaks down in the presence of galaxy mergers, or
when galaxies experience stochastic growth rates. We present a simple analytic
framework to treat the physical processes that drive the evolution and
diffusion of galaxies within comoving number density space. The evolution in
mass rank order of a galaxy population with time is influenced by the galaxy
coagulation rate and galaxy "mass rank scatter" rate. We quantify the relative
contribution of these two effects to the mass rank order evolution. We show
that galaxy coagulation is dominant at lower redshifts and stellar masses,
while scattered growth rates dominate the mass rank evolution at higher
redshifts and stellar masses. For a galaxy population at $10^{10} M_\odot$,
coagulation has been the dominant effect since $z=2.2$, but a galaxy population
at $10^{11} M_\odot$ was dominated by mass rank scatter until $z=0.6$. We show
that although the forward and backward median number density evolution tracks
are asymmetric, the backward median number density evolution can be obtained by
convolving the descendant distribution function with progenitor relative
abundances. We tabulate fits for the median number density evolution and
scatter which can be applied to improve the way galaxy populations are linked
in multi-epoch observational datasets.


title: A bocs theoretic characterization of gendo-symmetric algebras

abstract:
  Gendo-symmetric algebras were recently introduced by Fang and K\"onig. An
algebra is called gendo-symmetric in case it is isomorphic to the endomorphism
ring of a generator over a finite dimensional symmetric algebra. We show that a
finite dimensional algebra $A$ over a field $K$ is gendo-symmetric if and only
if there is a bocs-structure on $(A,D(A))$, where $D=Hom_K(-,K)$ is the natural
duality. Assuming that $A$ is gendo-symmetric, we show that the module category
of the bocs $(A,D(A))$ is isomorphic to the module category of the algebra
$eAe$, when $e$ is an idempotent such that $eA$ is the unique minimal faithful
projective-injective right $A$-module. We also prove some new results about
gendo-symmetric algebras using the theory of bocses.


title: Asymptotic spectral analysis in colliding leaky quantum layers

abstract:
  We consider the Schroedinger operator with a complex delta interaction
supported by two parallel hypersurfaces in the Euclidean space of any
dimension. We analyse spectral properties of the system in the limit when the
distance between the hypersurfaces tends to zero. We establish the
norm-resolvent convergence to a limiting operator and derive first-order
corrections for the corresponding eigenvalues.

categories: math-ph math.AP math.MP math.SP quant-ph


title: Measurements of Hadron Form Factors at BESIII

abstract:
  BEPCII is a symmetric $e^+e^-$-collider located in Beijing running at
center-of-mass energies between 2.0 and 4.6 GeV. This energy range allows the
BESIII-experiment to measure hadron form factors both from direct
$e^+e^-$-annihilation and from initial state radiation processes. In this
paper, results on $e^+e^-\rightarrow p\bar{p}$ based on data collected by
BESIII in 2011 and 2012 are presented. We also present preliminary results on
$e^+e^-\rightarrow \Lambda \bar{\Lambda}$ based on the same data samples at 4
center-of-mass energies. BESIII results obtained from $e^+e^-\rightarrow
\pi^+\pi^-$ using the initial state radiation technique at the center-of-mass
energy of 3.773 GeV are also summarized. Finally, expectations on the
measurement of baryon electromagnetic form factors from the BESIII high
luminosity energy scan in 2015 and from initial state radiation processes at
different center-of-mass energies are also reported.


title: Quantum measurement and uncertainty relations in photon polarization

abstract:
  Recent theoretical and experimental studies have given raise to new aspects
in quantum measurements and error-disturbance uncertainty relations. After a
brief review of these issues, we present an experimental test of the
error-disturbance uncertainty relations in photon polarization measurement.
Using generalized, strength-variable measurement of a single photon
polarization state, we experimentally evaluate the error and disturbance in the
measurement process and demonstrate the validity of recently proposed
uncertainty relations.


title: Dual theory of transmission line outages

abstract:
  A new graph dual formalism is presented for the analysis of line outages in
electricity networks. The dual formalism is based on a consideration of the
flows around closed cycles in the network. After some exposition of the theory
is presented, a new formula for the computation of Line Outage Distribution
Factors (LODFs) is derived, which is not only computationally faster than
existing methods, but also generalizes easily for multiple line outages and
arbitrary changes to line series reactance. In addition, the dual formalism
provides new physical insight for how the effects of line outages propagate
through the network. For example, in a planar network a single line outage can
be shown to induce monotonically decreasing flow changes, which are
mathematically equivalent to an electrostatic dipole field.


title: Validation of the Replica Trick for Simple Models

abstract:
  We discuss replica analytic continuation using several simple models in order
to prove mathematically the validity of replica analysis, which is used in a
wide range of fields related to large scale complex systems. While replica
analysis consists of two analytical techniques, the replica trick (or replica
analytic continuation) and the thermodynamical limit (and/or order parameter
expansion), we focus our study on replica analytic continuation, which is the
mathematical basis of the replica trick. We apply replica analysis to solve a
variety of analytical models, and examine the properties of replica analytic
continuation. Based on the positive results for these models we propose that
replica analytic continuation is a robust procedure in replica analysis.

categories: cond-mat.dis-nn cond-mat.stat-mech cs.IT math.IT q-fin.PM


title: Generations of solvable discrete-time dynamical systems

abstract:
  A technique is introduced which allows to generate -- starting from any
solvable discrete-time dynamical system involving N time-dependent variables --
new, generally nonlinear, generations of discrete-time dynamical systems, also
involving N time-dependent variables and being as well solvable by algebraic
operations (essentially by finding the N zeros of explicitly known polynomials
of degree N). The dynamical systems constructed using this technique may also
feature large numbers of arbitrary constants, and they need not be autonomous.
The solvable character of these models allows to identify special cases with
remarkable time evolutions: for instance, isochronous or asymptotically
isochronous discrete-time dynamical systems. The technique is illustrated by a
few examples.


title:
Multiclass feature learning for hyperspectral image classification:
  sparse and hierarchical solutions

abstract:
  In this paper, we tackle the question of discovering an effective set of
spatial filters to solve hyperspectral classification problems. Instead of
fixing a priori the filters and their parameters using expert knowledge, we let
the model find them within random draws in the (possibly infinite) space of
possible filters. We define an active set feature learner that includes in the
model only features that improve the classifier. To this end, we consider a
fast and linear classifier, multiclass logistic classification, and show that
with a good representation (the filters discovered), such a simple classifier
can reach at least state of the art performances. We apply the proposed active
set learner in four hyperspectral image classification problems, including
agricultural and urban classification at different resolutions, as well as
multimodal data. We also propose a hierarchical setting, which allows to
generate more complex banks of features that can better describe the
nonlinearities present in the data.


title:
Spin-Hall nano-oscillator with oblique magnetization and
  Dzyaloshinskii-Moriya interaction as generator of skyrmions and nonreciprocal
  spin-waves

abstract:
  Spin-Hall oscillators are promising sources of spin-wave signals for
magnonics applications, and can serve as building blocks for magnonic logic in
ultralow power computation devices. Here, we analytically and micromagnetically
study magnetization dynamics excited in a Spin-Hall oscillator with oblique
magnetization when the spin-Hall effect and interfacial Dzyaloshinskii-Moriya
interaction act simultaneously. Our key results are (i) excitation of
nonreciprocal spin-waves propagating perpendicularly to the in-plane projection
of the static magnetization, (ii) skyrmions generation by pure spin-current,
(iii) excitation of a new spin-wave mode with a spiral spatial profile
originating from a gyrotropic rotation of a dynamical skyrmion. These results
demonstrate that Spin-Hall oscillators can be used as generators of magnetic
skyrmions and different types of propagating spin-waves for magnetic data
storage and signal processing applications.


title:
Effective geometries and generalized uncertainty principle corrections
  to the Bekenstein-Hawking entropy

abstract:
  In this work we construct several black hole metrics which are consistent
with the generalized uncertainty principle logarithmic correction to the
Bekenstein-Hawking entropy formula. After preserving the event horizon at the
usual position, a singularity at the Planck scale is found. Finally, these
geometries are shown to be realized by certain model of nonlinear
electrodynamics, which resembles previously studied regular black hole
solutions.


title: A review of Gaussian Markov models for conditional independence

abstract:
  Markov models lie at the interface between statistical independence in a
probability distribution and graph separation properties. We review model
selection and estimation in directed and undirected Markov models with Gaussian
parametrization, emphasizing the main similarities and differences. These two
model classes are similar but not equivalent, although they share a common
intersection. We present the existing results from a historical perspective,
taking into account the amount of literature existing from both the artificial
intelligence and statistics research communities, where these models were
originated. We cover classical topics such as maximum likelihood estimation and
model selection via hypothesis testing, but also more modern approaches like
regularization and Bayesian methods. We also discuss how the Markov models
reviewed fit in the rich hierarchy of other, higher level Markov model classes.
Finally, we close the paper overviewing relaxations of the Gaussian assumption
and pointing out the main areas of application where these Markov models are
nowadays used.


title:
Event Abstraction for Process Mining using Supervised Learning
  Techniques

abstract:
  Process mining techniques focus on extracting insight in processes from event
logs. In many cases, events recorded in the event log are too fine-grained,
causing process discovery algorithms to discover incomprehensible process
models or process models that are not representative of the event log. We show
that when process discovery algorithms are only able to discover an
unrepresentative process model from a low-level event log, structure in the
process can in some cases still be discovered by first abstracting the event
log to a higher level of granularity. This gives rise to the challenge to
bridge the gap between an original low-level event log and a desired high-level
perspective on this log, such that a more structured or more comprehensible
process model can be discovered. We show that supervised learning can be
leveraged for the event abstraction task when annotations with high-level
interpretations of the low-level events are available for a subset of the
sequences (i.e., traces). We present a method to generate feature vector
representations of events based on XES extensions, and describe an approach to
abstract events in an event log with Condition Random Fields using these event
features. Furthermore, we propose a sequence-focused metric to evaluate
supervised event abstraction results that fits closely to the tasks of process
discovery and conformance checking. We conclude this paper by demonstrating the
usefulness of supervised event abstraction for obtaining more structured and/or
more comprehensible process models using both real life event data and
synthetic event data.


title: Real Algebraic Geometry and its Applications

abstract:
  This is a survey article on real algebra and geometry, and in particular on
its recent applications in optimization and convexity. We first introduce basic
notions and results from the classical theory. We then explain how these relate
to optimization, mostly via semidefinite programming. We introduce interesting
geometric problems arising from the classification of feasible sets for
semidefinite programming. We close with a perspective on the very active area
of non-commutative real algebra and geometry.


title:
Identifying individual facial expressions by deconstructing a neural
  network

abstract:
  This paper focuses on the problem of explaining predictions of psychological
attributes such as attractiveness, happiness, confidence and intelligence from
face photographs using deep neural networks. Since psychological attribute
datasets typically suffer from small sample sizes, we apply transfer learning
with two base models to avoid overfitting. These models were trained on an age
and gender prediction task, respectively. Using a novel explanation method we
extract heatmaps that highlight the parts of the image most responsible for the
prediction. We further observe that the explanation method provides important
insights into the nature of features of the base model, which allow one to
assess the aptitude of the base model for a given transfer learning task.
Finally, we observe that the multiclass model is more feature rich than its
binary counterpart. The experimental evaluation is performed on the 2222 images
from the 10k US faces dataset containing psychological attribute labels as well
as on a subset of KDEF images.


title:
Importance sampling strategy for non-convex randomized block-coordinate
  descent

abstract:
  As the number of samples and dimensionality of optimization problems related
to statistics an machine learning explode, block coordinate descent algorithms
have gained popularity since they reduce the original problem to several
smaller ones. Coordinates to be optimized are usually selected randomly
according to a given probability distribution. We introduce an importance
sampling strategy that helps randomized coordinate descent algorithms to focus
on blocks that are still far from convergence. The framework applies to
problems composed of the sum of two possibly non-convex terms, one being
separable and non-smooth. We have compared our algorithm to a full gradient
proximal approach as well as to a randomized block coordinate algorithm that
considers uniform sampling and cyclic block coordinate descent. Experimental
evidences show the clear benefit of using an importance sampling strategy.


title:
Picture It In Your Mind: Generating High Level Visual Representations
  From Textual Descriptions

abstract:
  In this paper we tackle the problem of image search when the query is a short
textual description of the image the user is looking for. We choose to
implement the actual search process as a similarity search in a visual feature
space, by learning to translate a textual query into a visual representation.
Searching in the visual feature space has the advantage that any update to the
translation model does not require to reprocess the, typically huge, image
collection on which the search is performed. We propose Text2Vis, a neural
network that generates a visual representation, in the visual feature space of
the fc6-fc7 layers of ImageNet, from a short descriptive text. Text2Vis
optimizes two loss functions, using a stochastic loss-selection method. A
visual-focused loss is aimed at learning the actual text-to-visual feature
mapping, while a text-focused loss is aimed at modeling the higher-level
semantic concepts expressed in language and countering the overfit on
non-relevant visual components of the visual loss. We report preliminary
results on the MS-COCO dataset.


title:
Some non-existence results for distance-$j$ ovoids in small generalized
  polygons

abstract:
  We give a computer-based proof for the non-existence of distance-$2$ ovoids
in the dual split Cayley hexagon $\mathsf{H}(4)^D$.
  Furthermore, we give upper bounds on partial distance-$2$ ovoids of
$\mathsf{H}(q)^D$ for $q \in \{2, 4\}$.


title: Non-convex regularization in remote sensing

abstract:
  In this paper, we study the effect of different regularizers and their
implications in high dimensional image classification and sparse linear
unmixing. Although kernelization or sparse methods are globally accepted
solutions for processing data in high dimensions, we present here a study on
the impact of the form of regularization used and its parametrization. We
consider regularization via traditional squared (2) and sparsity-promoting (1)
norms, as well as more unconventional nonconvex regularizers (p and Log Sum
Penalty). We compare their properties and advantages on several classification
and linear unmixing tasks and provide advices on the choice of the best
regularizer for the problem at hand. Finally, we also provide a fully
functional toolbox for the community.


title:
On a kinetic equation in weak turbulence theory for the nonlinear
  Schr\"odinger equation

abstract:
  The results from J. Stat. Phys. 159:668-712 & 163:1350-1393, on a quadratic
kinetic equation in the analysis of the long time asymptotics of weak
turbulence theory for the nonlinear Schr\"odinger equation, are summarized and
placed in context. Additionally, two conjectures on self-similar solutions are
presented, and backed with consistency analysis and numerics.


title: Drude weight fluctuations in many-body localized systems

abstract:
  We numerically investigate the distribution of Drude weights $D$ of many-body
states in disordered one-dimensional interacting electron systems across the
transition to a many-body localized phase. Drude weights are proportional to
the spectral curvatures induced by magnetic fluxes in mesoscopic rings. They
offer a method to relate the transition to the many-body localized phase to
transport properties. In the delocalized regime, we find that the Drude weight
distribution at a fixed disorder configuration agrees well with the
random-matrix-theory prediction $P(D) \propto (\gamma^2+D^2)^{-3/2}$, although
the distribution width $\gamma$ strongly fluctuates between disorder
realizations. A crossover is observed towards a distribution with different
large-$D$ asymptotics deep in the many-body localized phase, which however
differs from the commonly expected Cauchy distribution. We show that the
average distribution width $\langle \gamma\rangle $, rescaled by $L\Delta$,
$\Delta$ being the average level spacing in the middle of the spectrum and $L$
the systems size, is an efficient probe of the many-body localization
transition, as it increases/vanishes exponentially in the delocalized/localized
phase.


title:
Spectra and Electromagnetic Properties of the Neutron-Excess Nucleus
  $^{132}$In

abstract:
  Spectra of levels and transition rates are calculated for the odd--odd
particle--hole neutron excess nucleus $^{132}$In in the framework of the RPA
approach.


title: Can giant radio halos probe the merging rate of galaxy clusters?

abstract:
  Radio and X-ray observations of galaxy clusters probe a direct link between
cluster mergers and giant radio halos (RH), suggesting that these sources can
be used as probes of the cluster merging rate with cosmic time. In this paper
we carry out an explorative study that combines the observed fractions of
merging clusters (fm) and RH (fRH) with the merging rate predicted by
cosmological simulations and attempt to infer constraints on merger properties
of clusters that appear disturbed in X-rays and of clusters with RH. We use
morphological parameters to identify merging systems and analyze the currently
largest sample of clusters with radio and X-ray data (M500>6d14 Msun, and
0.2<z<0.33, from the Planck SZ cluster catalogue). We found that in this sample
fm~62-67% while fRH~44-51%. The comparison of the theoretical f_m with the
observed one allows to constrain the combination (xi_m,tau_m), where xi_m and
tau_m are the minimum merger mass ratio and the timescale of merger-induced
disturbance. Assuming tau_m~ 2-3 Gyr, as constrained by simulations, we find
that the observed f_m matches the theoretical one for xi_m~0.1-0.18. This is
consistent with optical and near-IR observations of clusters in the sample
(xi_m~0.14-0.16). The fact that RH are found only in a fraction of merging
clusters may suggest that merger events generating RH are characterized by
larger mass ratio; this seems supported by optical/near-IR observations of RH
clusters in the sample (xi_min~0.2-0.25). Alternatively, RH may be generated in
all mergers but their lifetime is shorter than \tau_m (by ~ fRH/fm). This is an
explorative study, however it suggests that follow up studies using the
forthcoming radio surveys and adequate numerical simulations have the potential
to derive quantitative constraints on the link between cluster merging rate and
RH at different cosmic epochs and for different cluster masses.


title: A Numerical Approach to Stability of Multiclass Queueing Networks

abstract:
  The Multi-class Queueing Network (McQN) arises as a natural multi-class
extension of the traditional (single-class) Jackson network. In a single-class
network subcriticality (i.e. subunitary nominal workload at every station)
entails stability, but this is no longer sufficient when jobs/customers of
different classes (i.e. with different service requirements and/or routing
scheme) visit the same server; therefore, analytical conditions for stability
of McQNs are lacking, in general. In this note we design a numerical
(simulation-based) method for determining the stability region of a McQN, in
terms of arrival rate(s). Our method exploits certain (stochastic) monotonicity
properties enjoyed by the associated Markovian queue-configuration process.
Stochastic monotonicity is a quite common feature of queueing models and can be
easily established in the single-class framework (Jackson networks); recently,
also for a wide class of McQNs, including first-come-first-serve (FCFS)
networks, monotonicity properties have been established. Here, we provide a
minimal set of conditions under which the method performs correctly.
Eventually, we illustrate the use of our numerical method by presenting a set
of numerical experiments, covering both single and multi-class networks.


title:
Proceedings Fifteenth Conference on Theoretical Aspects of Rationality
  and Knowledge

abstract:
  The 15th Conference on Theoretical Aspects of Rationality and Knowledge
(TARK) took place in Carnegie Mellon University, Pittsburgh, USA from June 4 to
6, 2015.
  The mission of the TARK conferences is to bring together researchers from a
wide variety of fields, including Artificial Intelligence, Cryptography,
Distributed Computing, Economics and Game Theory, Linguistics, Philosophy, and
Psychology, in order to further our understanding of interdisciplinary issues
involving reasoning about rationality and knowledge.
  These proceedings consist of a subset of the papers / abstracts presented at
the TARK conference.


title:
FMR studies of exchange-coupled multiferroic polycrystalline
  Pt/BiFeO$_3$/Ni$_{81}$Fe$_{19}$/Pt heterostructures

abstract:
  An experimental study of the in-plane azimuthal behaviour and frequency
dependence of the ferromagnetic resonance field and the resonance linewidth as
a function of BiFeO$_3$ thickness is carried out in a polycrystalline
exchange-biased BiFeO$_3$/Ni$_{81}$Fe$_{19}$ system. The magnetization decrease
of the Pt/BiFeO$_3$/Ni$_{81}$Fe$_{19}$/Pt heterostructures with BiFeO$_3$
thickness deduced from static measurements has been confirmed by dynamic
investigations. Ferromagnetic resonance measurements have shown lower
gyromagnetic ratio in a perpendicular geometry compared with that of a parallel
geometry. The monotonous decrease of gyromagnetic ratio in a perpendicular
geometry as a function of the BiFeO$_3$ film thickness seems to be related to
the spin-orbit interactions due to the neighbouring Pt film at its interface
with Ni$_{81}$Fe$_{19}$ film. The in-plane azimuthal shape of the total
linewidth of the uniform mode shows isotropic behaviour that increases with
BiFeO$_3$ thickness. The study of the frequency dependence of the resonance
linewidth in a broad band of 3 to 35 GHz has allowed the determination of
intrinsic and extrinsic contributions to the relaxation as function of
BiFeO$_3$ thickness in perpendicular geometries. In our system the magnetic
relaxation is dominated by the spin-pumping mechanism due to the presence of
Pt. The insertion of BiFeO$_3$ between Pt and Ni$_{81}$Fe$_{19}$ attenuates the
spin-pumping damping at one interface.


title:
Signatures of nonlocal Cooper-pair transport and of a singlet-triplet
  transition in the critical current of a double-quantum-dot Josephson junction

abstract:
  We study the critical Josephson current flowing through a double quantum dot
weakly coupled to two superconducting leads. We use analytical as well as
numerical methods to investigate this setup in the limit of small and large
bandwidth leads in all possible charging states, where we account for on-site
interactions exactly. Our results provide clear signatures of nonlocal
spin-entangled pairs, which support interpretations of recent experiments
[Deacon, R. S. et al., Nat. Commun. 6, 7446 (2015)]. In addition, we find that
the ground state with one electron on each quantum dot can undergo a tunable
singlet-triplet phase transition in the regime where the superconducting gap in
the leads is not too large, which gives rise to an additional new signature of
nonlocal Cooper pair transport.


title: Explaining Predictions of Non-Linear Classifiers in NLP

abstract:
  Layer-wise relevance propagation (LRP) is a recently proposed technique for
explaining predictions of complex non-linear classifiers in terms of input
variables. In this paper, we apply LRP for the first time to natural language
processing (NLP). More precisely, we use it to explain the predictions of a
convolutional neural network (CNN) trained on a topic categorization task. Our
analysis highlights which words are relevant for a specific prediction of the
CNN. We compare our technique to standard sensitivity analysis, both
qualitatively and quantitatively, using a "word deleting" perturbation
experiment, a PCA analysis, and various visualizations. All experiments
validate the suitability of LRP for explaining the CNN predictions, which is
also in line with results reported in recent image classification studies.


title: Force sensors with precision beyond the standard quantum limit

abstract:
  We propose force sensing protocols using linear ion chain which can operate
beyond the quantum standard limit. We show that oscillating forces that are
off-resonance with the motional trap frequency can be detected very efficiently
by using quantum probes represented by various spin-boson models. We
demonstrate that the temporal evolution of a quantum probe described by the
Dicke model can be mapped on the nonlinear Ramsey interferometry which allows
to detect far-detuned forces simply by measuring the collective spin
populations. Moreover, we show that the measurement uncertainty can reach the
Heisenberg limit by using initial spin correlated states, instead of motional
entangled states. An important advantage of the sensing technique is its
natural robustness against the thermally induced dephasing, which extends the
coherence time of the measurement protocol. Furthermore, we introduce sensing
scheme that utilize the strong spin-phonon coupling to improve the force
estimation. We show that for quantum probe represented by quantum Rabi model
the force sensitivity can overcome those using simple harmonic oscillator as a
force sensor.


title: A Note on a Sum of Lognormals

abstract:
  This note considers the applicability of Gauss-Hermite quadrature and direct
numerical quadrature for computation of moment generating function (mgf) and
the derivatives. A preprocessing using the asymptotic technique is employed
while computing the characteristic function (chf) using Gauss Hermite
quadrature while this is optional for mgf. The mgf of the low and high
amplitude regions of a single lognormal variable and the derivatives is
examined and attention is drawn to the effect of variance. The problem of
inversion of the mgf/chf of a sum of lognormals to obtain the CDF/pdf is
considered with special reference to methods related to Post Widder technique,
Gaussian quadrature and the Fourier series method. The method based on the
complex exponential integral which makes use of the derivative of the cumulant
is an alternative. Segmentation of the mgf/chf on the basis of the derivative
structure which indicates activity rate is shown to be useful.


title: The true quantum face of the "exponential" decay law

abstract:
  Results of theoretical studies of the quantum unstable systems caused that
there are rather widespread belief that a universal feature od the quantum
decay process is the presence of three time regimes of the decay process: the
early time (initial) leading to the Quantum Zeno (or Anti Zeno) Effects,
"exponential" (or "canonical") described by the decay law of the exponential
form, and late time characterized by the decay law having inverse--power law
form. Based on the fundamental principles of the quantum theory we give the
proof that there is no time interval in which the survival probability (decay
law) could be a decreasing function of time of the purely exponential form but
even at the "exponential" regime the decay curve is oscillatory modulated with
a smaller or a large amplitude of oscillations depending on parameters of the
model considered.


title:
Plasmonic Gold Helices for the visible range fabricated by oxygen plasma
  purification of electron beam induced deposits

abstract:
  Electron beam induced deposition (EBID) currently provides the only direct
writing technique for truly three-dimensional nanostructures with geometrical
features below 50 nm. Unfortunately, the depositions from metal-organic
precursors suffer from a substantial carbon content. This hinders many
applications, especially in plasmonics where the metallic nature of the
geometric surfaces is mandatory. To overcome this problem a post-deposition
treatment with oxygen plasma at room temperature was investigated for the
purification of gold containing EBID structures. Upon plasma treatment, the
structures experience a shrinkage in diameter of about 18 nm but entirely keep
their initial shape. The proposed purification step results in a core-shell
structure with the core consisting of mainly unaffected EBID material and a
gold shell of about 20 nm in thickness. These purified structures are
plasmonically active in the visible wavelength range as shown by dark field
optical microscopy on helical nanostructures. Most notably, electromagnetic
modeling of the corresponding scattering spectra verified that the thickness
and quality of the resulting gold shell ensures an optical response equal to
that of pure gold nanostructures.


title:
Non-Sequential Double Ionization by Counter Rotating Circularly
  Polarized Two-Color Laser Fields

abstract:
  We report on non-sequential double ionization of Ar by a laser pulse
consisting of two counter rotating circularly polarized fields (390 nm and 780
nm). The double ionization probability depends strongly on the relative
intensity of the two fields and shows a "knee"-like structure as function of
intensity. We conclude that double ionization is driven by a beam of nearly
monoenergetic recolliding electrons, which can be controlled in intensity and
energy by the field parameters. The electron momentum distributions show the
recolliding electron as well as a second electron which escapes from an
intermediate excited state of Ar$^+$.