title: Compact and extended objects from self-interacting phantom fields

abstract:
  In this work we investigate localized and extended objects for gravitating,
self-interacting phantom fields. The phantom fields come from two scalar fields
with a "wrong sign" (negative) kinetic energy term in the Lagrangian. This
study covers several solutions supported by these phantom fields: phantom
balls, traversable wormholes, phantom cosmic strings, and "phantom" domain
walls. These four systems are solved numerically and we try to draw out
general, interesting features in each case.


title:
Echidna Mark II: one giant leap for 'tilting spine' fibre positioning
  technology

abstract:
  The Australian Astronomical Observatory's 'tilting spine' fibre positioning
technology has been redeveloped to provide superior performance in a smaller
package. The new design offers demonstrated closed-loop positioning errors of
2.8 {\mu}m RMS in only five moves (~10 s excluding metrology overheads) and an
improved capacity for open-loop tracking during observations. Tilt-induced
throughput losses have been halved by lengthening spines while maintaining
excellent accuracy. New low-voltage multilayer piezo actuator technology has
reduced a spine's peak drive amplitude from ~150 V to <10 V, simplifying the
control electronics design, reducing the system's overall size, and improving
modularity. Every spine is now a truly independent unit with a dedicated drive
circuit and no restrictions on the timing or direction of fibre motion.


title: FPGA Online Tracking Algorithm for the PANDA Straw Tube Tracker

abstract:
  A novel FPGA based online tracking algorithm for helix track reconstruction
in a solenoidal field, developed for the PANDA spectrometer, is described.
Employing the Straw Tube Tracker detector with 4636 straw tubes, the algorithm
includes a complex track finder, and a track fitter. Implemented in VHDL, the
algorithm is tested on a Xilinx Virtex-4 FX60 FPGA chip with different types of
events, at different event rates. A processing time of 7 $\mu$s per event for
an average of 6 charged tracks is obtained. The momentum resolution is about
3\% (4\%) for $p_t$ ($p_z$) at 1 GeV/c. Comparing to the algorithm running on a
CPU chip (single core Intel Xeon E5520 at 2.26 GHz), an improvement of 3 orders
of magnitude in processing time is obtained. The algorithm can handle severe
overlapping of events which are typical for interaction rates above 10 MHz.


title: Bifurcation and Stability Analysis of Bistable Neuromodules

abstract:
  This paper presents a stability analysis of simple neuromodules displaying
fold bifurcations (leading to hysteresis), flip bifurcations (period doubling
and undoubling to and from chaos) and Neimark-Sacker bifurcations
(quasiperiodic and periodic bifurcations). For the first time, bifurcation
diagrams are plotted using a feedback mechanism. It is shown that the stability
curves and bifurcation diagrams must be dealt with simultaneously in order to
fully understand the dynamics of the systems involved. Synaptic weights, biases
and gradients of transfer functions are varied and the system is shown to be
history dependent. The work can be applied to artificial neural networks and
developing brains and gives a very important generalization of previous work in
this field.


title:
Nonrelativistic asymptotics of solitary waves in the Dirac equation with
  the Soler-type nonlinearity

abstract:
  We use the perturbation theory to build solitary wave solutions
$\phi_\omega(x)e^{-i\omega t}$ to the nonlinear Dirac equation in
$\mathbb{R}^n$, $n\ge 1$, with the Soler-type nonlinear term
$f(\bar\psi\psi)\beta\psi$, with $f(\tau)=|\tau|^k+o(|\tau|^k)$, $k>0$, which
is continuous but not necessarily differentiable. We obtain the asymptotics of
solitary waves in the nonrelativistic limit $\omega\lesssim m$; these
asymptotics are important for the linear stability analysis of solitary wave
solutions. We also show that in the case when the power of the nonlinearity is
Schr\"odinger charge-critical, one has $Q'(\omega)<0$ for $\omega\lesssim m$,
implying the absence of the degeneracy of zero eigenvalue of the linearization
at a solitary wave.


title:
Likelihood-based Parameter Estimation and Comparison of Dynamical
  Cognitive Models

abstract:
  Dynamical models of cognition play an increasingly important role in driving
theoretical and experimental research in psychology. Therefore, parameter
estimation, model analysis and comparison of dynamical models are of essential
importance. Here we propose a maximum-likelihood approach for model analysis in
a fully dynamical framework that includes time-ordered experimental data. Our
methods can be applied to dynamical models for the prediction of discrete
behavior (e.g., movement onsets), in particular, we use a dynamical model of
saccade generation in scene viewing as a case study for our approach. For this
model, the likelihood function can be computed directly by numerical
simulation, which enables more efficient parameter estimation including
Bayesian inference to obtain reliable estimates and corresponding credible
intervals. Using hierarchical models inference is even possible for individual
observers. Furthermore, our likelihood approach can be used to compare
different models. In our example, the dynamical framework is shown to
outperform non-dynamical statistical models. Additionally, the likelihood based
evaluation differentiates model variants, which produced indistinguishable
predictions on hitherto used statistics. Our results indicate that the
likelihood approach is a promising framework for dynamical cognitive models.


title: Fault-Tolerant Adaptive Parallel and Distributed Simulation

abstract:
  Discrete Event Simulation is a widely used technique that is used to model
and analyze complex systems in many fields of science and engineering. The
increasingly large size of simulation models poses a serious computational
challenge, since the time needed to run a simulation can be prohibitively
large. For this reason, Parallel and Distributes Simulation techniques have
been proposed to take advantage of multiple execution units which are found in
multicore processors, cluster of workstations or HPC systems. The current
generation of HPC systems includes hundreds of thousands of computing nodes and
a vast amount of ancillary components. Despite improvements in manufacturing
processes, failures of some components are frequent, and the situation will get
worse as larger systems are built. In this paper we describe FT-GAIA, a
software-based fault-tolerant extension of the GAIA/ART\`IS parallel simulation
middleware. FT-GAIA transparently replicates simulation entities and
distributes them on multiple execution nodes. This allows the simulation to
tolerate crash-failures of computing nodes; furthermore, FT-GAIA offers some
protection against byzantine failures since synchronization messages are
replicated as well, so that the receiving entity can identify and discard
corrupted messages. We provide an experimental evaluation of FT-GAIA on a
running prototype. Results show that a high degree of fault tolerance can be
achieved, at the cost of a moderate increase in the computational load of the
execution units.


title:
Skorohod's representation theorem and optimal strategies for markets
  with frictions

abstract:
  We prove the existence of optimal strategies for agents with cumulative
prospect theory preferences who trade in a continuous-time illiquid market,
transcending known results which pertained only to risk-averse utility
maximizers. The arguments exploit an extension of Skorohod's representation
theorem for tight sequences of probability measures. This method is applicable
in a number of similar optimization problems.


title: Unsupervised preprocessing for Tactile Data

abstract:
  Tactile information is important for gripping, stable grasp, and in-hand
manipulation, yet the complexity of tactile data prevents widespread use of
such sensors. We make use of an unsupervised learning algorithm that transforms
the complex tactile data into a compact, latent representation without the need
to record ground truth reference data. These compact representations can either
be used directly in a reinforcement learning based controller or can be used to
calibrate the tactile sensor to physical quantities with only a few datapoints.
We show the quality of our latent representation by predicting important
features and with a simple control task.


title:
Optimizing Decoy State Enabled Quantum Key Distribution Systems to
  Maximize Quantum Throughput and Detect Photon Number Splitting Attacks with
  High Confidence

abstract:
  Quantum Key Distribution (QKD) is an innovative quantum communications
protocol which exploits the laws of quantum mechanics to generate
unconditionally secure cryptographic keying material between two geographically
separated parties. The unique nature of QKD shows promise for high-security
applications such as those found in banking, government, and military
environments. However, QKD systems contain implementation non-idealities which
can negatively impact their performance and security.In particular, QKD systems
often employ the decoy state protocol to improve system throughput and mitigate
the threat of Photon Number Splitting (PNS) attacks. In this work, a detailed
analysis of the decoy state protocol is conducted which optimizes both
performance in terms of quantum throughput and security with respect to
detecting PNS attacks. The results of this study uniquely demonstrate that the
decoy state protocol can ensure PNS attacks are detected with high confidence,
while maximizing the secure key generation rate at no additional cost.
Additionally, implementation security guidance is provided for QKD system
developers and users.


title:
Multi-layer Thick Gas Electron Multiplier (M-THGEM): a new MPDG
  structure for high-gain operation at low-pressure

abstract:
  The operating principle and performances of the Multi-layer Thick Gaseous
Electron Multiplier (M-THGEM) is presented. The M-THGEM is a novel hole-type
gaseous electron multiplier produced by multi-layer printed circuit board
technology; it consists of a densely perforated assembly of multiple insulating
substrate sheets (e.g., FR-4), sandwiched between thin metallic-electrode
layers. The electron avalanche processes occur along the successive
multiplication stages within the M-THGEM holes, under the action of strong
dipole fields resulting from the application of suitable potential differences
between the electrodes. The present work focuses on investigation of two
different geometries: a two-layer M-THGEM (either as single or double-cascade
detector) and a single three-layer M-THGEM element, tested in various
low-pressure He-based gas mixtures. The intrinsically robust confinement of the
avalanche volume within the M-THGEM holes provides an efficient suppression of
the photon-induced secondary effects, resulting in a high-gain operation over a
broad pressure range, even in pure noble gas. The operational principle, main
properties (maximum achievable gain, long-term stability, energy resolution,
etc.) under different irradiation conditions, as well as capabilities and
potential applications are discussed.


title: Nearly-optimal Robust Matrix Completion

abstract:
  In this paper, we consider the problem of Robust Matrix Completion (RMC)
where the goal is to recover a low-rank matrix by observing a small number of
its entries out of which a few can be arbitrarily corrupted. We propose a
simple projected gradient descent method to estimate the low-rank matrix that
alternately performs a projected gradient descent step and cleans up a few of
the corrupted entries using hard-thresholding. Our algorithm solves RMC using
nearly optimal number of observations as well as nearly optimal number of
corruptions. Our result also implies significant improvement over the existing
time complexity bounds for the low-rank matrix completion problem. Finally, an
application of our result to the robust PCA problem (low-rank+sparse matrix
separation) leads to nearly linear time (in matrix dimensions) algorithm for
the same; existing state-of-the-art methods require quadratic time. Our
empirical results corroborate our theoretical results and show that even for
moderate sized problems, our method for robust PCA is an an order of magnitude
faster than the existing methods.


title: Determining the Hubble constant from Hubble parameter measurements

abstract:
  We use 28 Hubble parameter, $H(z)$, measurements at intermediate redshifts
$0.07 \leq z \leq 2.3$ to determine the present-day Hubble constant $H_0$ in
four cosmological models. We measure $H_0 = 68.3^{ +2.7}_{ -2.6 }, 68.4^{ +2.9
}_{ -3.3 }, 65.0^{ +6.5 }_{ -6.6 }$ and $ 67.9^{ +2.4}_{-2.4}$ km s${}^{-1}$
Mpc${}^{-1}$ (1$\sigma$ errors) in the $\Lambda$CDM (spatially flat and
non-flat), $\omega$CDM and $\phi$CDM models, respectively. These measured $H_0$
values are more consistent with the lower values determined from recent cosmic
microwave background and baryon acoustic oscillation data, as well as with that
found from a median statistics analysis of Huchra's compilation of $H_0$
measurements,but include the higher local measurements of $H_0$ within the
2$\sigma$ confidence limits.


title:
Twisted Poincare Series and Zeta functions on finite quotients of
  buildings

abstract:
  In the case where $G=$SL$_{2}(F)$ for a non-archimedean local field $F$ and
$\Gamma$ is a discrete torsion-free cocompact subgroup of $G$, there is a known
relationship between the Ihara zeta function for the quotient of the
Bruhat-Tits tree of $G$ by the action of $\Gamma$, and an alternating product
of determinants of twisted Poincar\'e series for parabolic subgroups of the
affine Weyl group of $G$. We show how this can be generalised to other split
simple algebraic groups of rank two over $F$, and formulate a conjecture about
how this might be generalised to groups of higher rank.


title:
Convergence of the Allen-Cahn Equation to multi-phase mean-curvature
  flow

abstract:
  We present a convergence result for solutions of the vector-valued Allen-Cahn
Equation. In the spirit of the work of Luckhaus and Sturzenhecker we establish
convergence towards a distributional formulation of multi-phase mean-curvature
flow using sets of finite perimeter. Like their result, ours relies on the
assumption that the time-integrated energies of the approximations converge to
those of the limit. Furthermore, we apply our proof to two variants of the
equation, incorporating external forces and a volume constraint.


title:
Strongly nonlinear models for internal waves: an application for the
  dam-break problem

abstract:
  Strongly nonlinear models of internal wave propagation for incompressible
stratified Euler fluids are investigated numerically and analytically to
determine the evolution of a class of initial conditions of interest in
laboratory experiments. This class of step-like initial data severely tests the
robustness of the models beyond their strict long-wave asymptotic validity, and
model fidelity is assessed by direct numerical simulations (DNS) of the parent
Euler system.
  It is found that the primary dynamics of near-solitary wave formation is
remarkably well predicted by the models for both wave and fluid properties, at
a fraction of the computational costs of the DNS code.


title:
Local well-posedness and global existence for the biharmonic heat
  equation with exponential nonlinearity

abstract:
  In this paper we prove local well-posedness in Orlicz spaces for the
biharmonic heat equation $\partial_{t} u+ \Delta^2 u=f(u),\;t>0,\;x\in\R^N,$
with $f(u)\sim \mbox{e}^{u^2}$ for large $u.$ Under smallness condition on the
initial data and for exponential nonlinearity $f$ such that $f(u)\sim u^m$ as
$u\to 0,$ $m$ integer and $N(m-1)/4\geq 2$, we show that the solution is
global. Moreover, we obtain a decay estimates for large time for the nonlinear
biharmonic heat equation as well as for the nonlinear heat equation. Our
results extend to the nonlinear polyharmonic heat equation.


title: Electromagnon dispersion probed by inelastic x-ray scattering

abstract:
  Inelastic x-ray scattering with meV energy resolution (IXS) is an ideal tool
to measure collective excitations in solids and liquids. In non-resonant
scattering condition, the cross section is strongly dominated by lattice
vibrations (phonons). However, it is possible to probe additional degrees of
freedom such as magnetic fluctuations that are strongly coupled to the phonons.
The IXS spectrum of the coupled system will contain not only the phonon
dispersion (majority component) but also the so far undetected magnetic
correlation function (minority component). Here we report the discovery of
strong magnon-phonon coupling in LiCrO$_2$ that enables the measurement of
magnetic correlations throughout the Brillouin-zone via IXS. We found
electromagnon excitations and electric dipole active two-magnon excitations in
the magnetically ordered phase and paraelectromagnons in the paramagnetic phase
of LiCrO$_2$. We predict that the numerous group of (frustrated) magnets with
dominant direct exchange and non-collinear magnetism shows similarly strong
coupling and surprisingly large and measurable IXS cross section for magnons
and multi-magnon processes.


title:
SRB measures for certain class of non-uniformly hyperbolic endomorphisms
  on the solid torus

abstract:
  In this paper we address the existence and ergodicity of non-hyperbolic
attracting sets for a certain class of smooth endomorphisms on the solid torus.
Such systems allow a formulation as a skew product system defined by planar
diffeomorphisms have contraction on average which forced by any expanding
circle map. These attractors are invariant graphs of upper semicontinuous maps
which support exactly one $SRB$ measure. In our approach, these skew product
systems arising from iterated function systems generated by a finitely many
weak contractive diffeomorphisms. Under some conditions including negative
fiber Lyapunov exponents, we prove the existence of unique non-hyperbolic
attracting invariant graphs for these systems which attract positive orbits of
almost all initial points. Also, we prove that these systems are Bernoulli and
therefore they are mixing. Moreover, these properties remain true under small
perturbations in the space of endomorphisms on the solid torus.


title: Quantum production of black holes at colliders

abstract:
  We investigate black hole production in pp collisions at the Large Hadron
Collider by employing the horizon quantum mechanics for models of gravity with
extra spatial dimensions. This approach can be applied to processes around the
fundamental gravitational scale and naturally yields a suppression below the
fundamental gravitational scale and for increasing number of extra dimensions.
The results of numerical simulations performed with the black hole event
generator BLACKMAX are here reported in order to illustrate the main
differences in the number of expected black hole events and mass distributions.


title: Dynamical optical flow of saliency maps for predicting visual attention

abstract:
  Saliency maps are used to understand human attention and visual fixation.
However, while very well established for static images, there is no general
agreement on how to compute a saliency map of dynamic scenes. In this paper we
propose a mathematically rigorous approach to this prob- lem, including static
saliency maps of each video frame for the calculation of the optical flow.
Taking into account static saliency maps for calculating the optical flow
allows for overcoming the aperture problem. Our ap- proach is able to explain
human fixation behavior in situations which pose challenges to standard
approaches, such as when a fixated object disappears behind an occlusion and
reappears after several frames. In addition, we quantitatively compare our
model against alternative solutions using a large eye tracking data set.
Together, our results suggest that assessing optical flow information across a
series of saliency maps gives a highly accurate and useful account of human
overt attention in dynamic scenes.


title: Statistical Models for Tornado Climatology: Long and Short-Term Views

abstract:
  This paper estimates local tornado risk from records of past events using
statistical models. First, a spatial model is fit to the tornado counts
aggregated in counties with terms that control for changes in observational
practices over time. Results provide a long-term view of risk that delineates
the main tornado corridors in the United States where the expected annual rate
exceeds two tornadoes per 10,000 square km. A few counties in the Texas
Panhandle and central Kansas have annual rates that exceed four tornadoes per
10,000 square km. Refitting the model after removing the least damaging
tornadoes from the data (EF0) produces a similar map but with the greatest
tornado risk shifted south and eastward. Second, a space-time model is fit to
the counts aggregated in raster cells with terms that control for changes in
climate factors. Results provide a short-term view of risk. The short-term view
identifies the shift of tornado activity away from the Ohio Valley under El
Ni\~no conditions and away from the Southeast under positive North Atlantic
oscillation conditions. The combined predictor effects on the local rates is
quantified by fitting the model after leaving out the year to be predicted from
the data. The models provide state-of-the-art views of tornado risk that can be
used by government agencies, the insurance industry, and the general public.


title: DropNeuron: Simplifying the Structure of Deep Neural Networks

abstract:
  Deep learning using multi-layer neural networks (NNs) architecture manifests
superb power in modern machine learning systems. The trained Deep Neural
Networks (DNNs) are typically large. The question we would like to address is
whether it is possible to simplify the NN during training process to achieve a
reasonable performance within an acceptable computational time. We presented a
novel approach of optimising a deep neural network through regularisation of
net- work architecture. We proposed regularisers which support a simple
mechanism of dropping neurons during a network training process. The method
supports the construction of a simpler deep neural networks with compatible
performance with its simplified version. As a proof of concept, we evaluate the
proposed method with examples including sparse linear regression, deep
autoencoder and convolutional neural network. The valuations demonstrate
excellent performance.
  The code for this work can be found in
http://www.github.com/panweihit/DropNeuron


title:
BFKL phenomenology: resummation of high-energy logs in semi-hard
  processes at LHC

abstract:
  A study of differential cross sections and azimuthal observables for
semi-hard processes at LHC energies, including BFKL resummation effects, is
presented. Particular attention has been paid to the behaviour of the azimuthal
correlation momenta, when a couple of forward/backward jets or identified
hadrons is produced in the final state with a large rapidity separation. Three-
and four- jet production has been also considered, the main focus lying on the
definition of new, generalized azimuthal observables, whose dependence on the
transverse momenta and the rapidities of the central jet(s) can be considered
as a distinct signal of the onset of BFKL dynamics.


title: Hidden Gauge Structure of Supersymmetric Free Differential Algebras

abstract:
  The aim of this paper is to clarify the role of the nilpotent fermionic
generator Q' introduced in Ref. [3] and appearing in the hidden supergroup
underlying the free differential algebra (FDA) of D=11 supergravity. We give a
physical explanation of its role by looking at the gauge properties of the
theory. We find that its presence is necessary, in order that the extra 1-forms
of the hidden supergroup give rise to the correct gauge transformations of the
p-forms of the FDA.
  This interpretation is actually valid for any supergravity containing
antisymmetric tensor fields, and any supersymmetric FDA can always be traded
for a hidden Lie superalgebra containing extra fermionic nilpotent generators.
As an interesting example we construct the hidden superalgebra associated with
the FDA of N=2, D=7 supergravity. In this case we are able to parametrize the
mutually non local 2- and 3-form B^(2) and B^(3) in terms of hidden 1-forms and
find that supersymmetry and gauge invariance require in general the presence of
two nilpotent fermionic generators in the hidden algebra. We propose that our
approach, where all the invariances of the FDA are expressed as Lie derivatives
of the $p$-forms in the hidden supergroup manifold, could be an appropriate
framework to discuss theories defined in enlarged versions of superspace
recently considered in the literature, such us double field theory and its
generalizations.


title:
Columnar structure formation of a dilute suspension of settling
  spherical particles in a quiescent fluid

abstract:
  The settling of heavy spherical particles in a column of quiescent fluid is
investigated. The performed experiments cover a range of Galileo numbers ($110
\leq \text{Ga} \leq 310$) for a fixed density ratio of $\Gamma = \rho_p/\rho_f
= 2.5$. In this regime the particles are known (M. Jenny, J. Du\v{s}ek and G.
Bouchet, Journal of Fluid Mechanics 508, 201 (2004).) to show a variety of
motions. It is known that the wake undergoes several transitions for increasing
$\text{Ga}$ resulting in particle motions that are successively: vertical,
oblique, oblique oscillating, and finally chaotic. Not only does this change
the trajectory of single, isolated, settling particles, but it also changes the
dynamics of a swarm of particles as collective effects become important even
for dilute suspensions, with volume fraction up to $\Phi_V =
\mathcal{O}\left(10^{-3}\right)$, which are investigated in this work.
Multi-camera recordings of settling particles are recorded and tracked over
time in 3 dimensions. A variety of analysis are performed and show a strong
clustering behavior. The distribution of the cell areas of the Vorono\"i
tessellation in the horizontal plane are compared to that of a random
distribution of particles and shows clear clustering. Moreover, a negative
correlation was found between the Vorono\"i area and the particle velocity;
clustered particles fall faster. In addition, the angle between two adjacent
particles and the vertical is calculated and compared to a homogeneous
distribution of particles, clear evidence of vertical alignment of particles is
found. The experimental findings are compared to simulations.


title:
Exact Quantization Conditions, Toric Calabi-Yau and Nonperturbative
  Topological String

abstract:
  We establish the precise relation between the Nekrasov-Shatashvili (NS)
quantization scheme and Grassi-Hatsuda-Marino conjecture for the mirror curve
of arbitrary toric Calabi-Yau threefold. For a mirror curve of genus $g$, the
NS quantization scheme leads to $g$ quantization conditions for the
corresponding integrable system. The exact NS quantization conditions enjoy a
self S-duality with respect to Planck constant $\hbar$ and can be derived from
the Lockhart-Vafa partition function of nonperturbative topological string.
Based on a recent observation on the correspondence between spectral theory and
topological string, another quantization scheme was proposed by
Grassi-Hatsuda-Marino, in which there is a single quantization condition and
the spectra are encoded in the vanishing of a quantum Riemann theta function.
We demonstrate that there actually exist at least $g$ nonequivalent quantum
Riemann theta functions and the intersections of their theta divisors coincide
with the spectra determined by the exact NS quantization conditions. This
highly nontrivial coincidence between the two quantization schemes requires
infinite constraints among the refined Gopakumar-Vafa invariants. The
equivalence for mirror curves of genus one has been verified for some local del
Pezzo surfaces. In this paper, we generalize the correspondence to higher
genus, and analyze in detail the resolved $\mathbb{C}^3/\mathbb{Z}_5$ orbifold
and several $SU(N)$ geometries. We also give a proof for some models at
$\hbar=2\pi/k$.


title:
Resistive properties and phase diagram of the organic antiferromagnetic
  metal $\kappa$-(BETS)$_2$FeCl$_4$

abstract:
  The low-temperature electronic state of the layered organic charge-transfer
salt $\kappa$-(BETS)$_2$FeCl$_4$ was probed by interlayer electrical resistance
measurements under magnetic field. Both above and below
$T_{\mathrm{N}}=0.47\,$K, the temperature of antiferromagnetic ordering of
$3d$-electron spins of Fe$^{3+}$ localized in the insulating anion layers, a
non-saturating linear $R(T)$ dependence has been observed. A weak
superconducting signal has been detected in the antiferromagnetic state, at
temperatures $\leq 0.2\,$K. Despite the very high crystal quality, only a tiny
fraction of the sample appears to be superconducting. Besides a small kink
feature in the resistivity, the impact of the antiferromagnetic ordering of
localized Fe$^{3+}$ spins on the conduction $\pi$-electron system is clearly
manifested in the Fermi surface reconstruction, as evidenced by Shubnikov-de
Haas oscillations. The "magnetic field -- temperature" phase diagrams for the
field directions parallel to each of the three principal crystal axes have been
determined. For magnetic field along the easy axis a spin-flop transition has
been found. Similarities and differences between the present material and the
sister compound $\kappa$-(BETS)$_2$FeBr$_4$ are discussed.


title:
Kardar-Parisi-Zhang equation and large deviations for random walks in
  weak random environments

abstract:
  We consider the transition probabilities for random walks in $1+1$
dimensional space-time random environments (RWRE). For critically tuned weak
disorder we prove a sharp large deviation result: after appropriate rescaling,
the transition probabilities for the RWRE evaluated in the large deviation
regime, converge to the solution to the stochastic heat equation (SHE) with
multiplicative noise (the logarithm of which is the KPZ equation). We apply
this to the exactly solvable Beta RWRE and additionally present a formal
derivation of the convergence of certain moment formulas for that model to
those for the SHE.


title: Asymmetry in the reconstructed deceleration parameter

abstract:
  We study the orientation dependence of the reconstructed deceleration
parameter as a function of redshift. We use the Union 2 and Loss datasets, by
using the well known preferred axis discussed in the literature, finding the
best fit reconstructed deceleration parameter. We found that a low redshift
transition of the reconstructed $q(z)$ is clearly absent in one direction and
amazingly sharp in the opposite one. We discuss the possibility that such a
behavior can be associated with large scale structures affecting the data.


title: Partition regularity of generalised Fermat equations

abstract:
  Let $\alpha,\beta,\gamma\in\mathbb{N}$. We prove that given an $r$-colouring
of $\mathbb{F}_p$ with $p$ prime, there are more than
$c_{r,\alpha,\beta,\gamma} p^2$ solutions to the equation
$x^\alpha+y^\beta=z^\gamma$ with all of $x,y,z$ of the same colour. Here
$c_{r,\alpha,\beta,\gamma}>0$ is some constant depending on the number of
colours and the exponents in the equation. This is already a new result for
$\alpha=\beta=1$ and $\gamma=2$, that is to say for the equation $x+y=z^2$.


title:
Planck intermediate results. L. Evidence for spatial variation of the
  polarized thermal dust spectral energy distribution and implications for CMB
  $B$-mode analysis

abstract:
  The characterization of the Galactic foregrounds has been shown to be the
main obstacle in the challenging quest to detect primordial B-modes in the
polarized microwave sky. We make use of the Planck-HFI 2015 data release at
high frequencies to place new constraints on the properties of the polarized
thermal dust emission at high Galactic latitudes. Here, we specifically study
the spatial variability of the dust polarized spectral energy distribution, and
its potential impact on the determination of the tensor-to-scalar ratio. We use
the correlation ratio of the $C_\ell^{BB}$ angular power spectra between the
217- and 353-GHz channels as a tracer of these potential variations, computed
on different high Galactic latitude regions, ranging from 80% to 20% of the
sky. The new insight from Planck data is a departure of the correlation ratio
from unity that cannot be attributed to a spurious decorrelation due to the
cosmic microwave background, instrumental noise, or instrumental systematics.
The effect is marginally detected on each region, but the statistical
combination of all the regions gives more than 99% confidence for this
variation in polarized dust properties. In addition, we show that the
decorrelation increases when there is a decrease in the mean column density of
the region of the sky being considered, and we propose a simple power-law
empirical model for this dependence, which matches what is seen in the Planck
data. We explore the effect that this measured decorrelation has on simulations
of the BICEP2-Keck Array/Planck analysis and show that the 2015 constraints
from those data still allow a decorrelation between the dust at 150 and 353GHz
of the order of the one we measure. Finally we show that either spatial
variation of the dust SED or of the dust polarization angle could produce
decorrelations between 217- and 353-GHz data similar to those we observe in the
data.


title:
Covariance estimation for vertically partitioned data in a distributed
  environment

abstract:
  The major sources of abundant data are constantly expanding with the
available data collection methodologies in various applications - medical,
insurance, scientific, bio-informatics and business. These data sets may be
distributed geographically, rich in size and as well as dimensions also. To
analyze these data sets to find out the hidden patterns, it is required to
down- load the data to a centralized site which is a challenging task in terms
of the limited bandwidth available and computationally also expensive. The
covariance matrix is one of the methods to estimate the relation between any
two dimensions. In this paper, we propose a communication efficient algorithm
to estimate the covariance matrix in a distributed manner. The global
covariance matrix is computed by merging the local covariance matrices using a
distributed approach. The results show that it is exactly same as centralized
method with good speed-up in terms of computation. The reason for speed-up is
because of the parallel construction of local covariances and distributing the
cross-covariances among the nodes so that the load is balanced. The results are
analyzed by considering Mfeat data set on the various partitions which address
the scalability also.


title:
Conjunctive Query Answering via a Fragment of Set Theory (Extended
  Version)

abstract:
  We address the problem of Conjunctive Query Answering (CQA) for the
description logic $\dlssx$ ($\shdlssx$, for short) which extends the logic
$\dlss$ with Boolean operations on concrete roles and with the product of
concepts.
  The result is obtained by formalizing $\shdlssx$-knowledge bases and
$\shdlssx$-conjunctive queries in terms of formulae of the four-level
set-theoretic fragment $\flqsr$, which admits a restricted form of
quantification on variables of the first three levels and on pair terms. We
solve the CQA problem for $\shdlssx$ through a decision procedure for the
satisfiability problem of $\flqsr$. We further define a \ke\space based
procedure for the same problem, more suitable for implementation purposes, and
analyze its computational complexity.


title: Optical designs for the Maunakea Spectroscopic Explorer Telescope

abstract:
  Optical designs are presented for the Maunakea Spectroscopic Explorer (MSE)
telescope. The adopted baseline design is a prime focus telescope with a
segmented primary of 11.25m aperture, with speed f/1.93 and 1.52deg
field-of-view, optimized for wavelengths 360-1800nm. The Wide-Field Corrector
(WFC) has five aspheric lenses, mostly of fused silica, with largest element
1.33m diameter and total glass mass 788kg. The Atmospheric Dispersion Corrector
(ADC) is of the compensating lateral type, combining a motion of the entire WFC
via the hexapod, with a restoring motion for a single lens. There is a modest
amount of vignetting (average 5% over the hexagonal field); this greatly
improves image quality, and allows the design to be effectively pupil-centric.
The polychromatic image quality is d80<0.225"/0.445" at ZD 0/60deg over more
than 95% of the hexagonal field-of-view. The ADC action allows adjustment of
the plate-scale with zenith distance, which is used to halve the image motions
caused by differential refraction. A simple design is presented for achieving
the required ADC lens shifts and tilts. A two-mirror design was also undertaken
for MSE, but was not selected. This is a 12.3m F/2.69 forward Cassegrain
design, with a 2.75m diameter M2, and three silica lenses, of largest diameter
1.33m. The field-of-view is again 1.52deg. The f/0.95 primary makes the design
remarkably compact, being under 10m long. The ADC action involves a small
motion of M2 (again via a hexapod), and shifts and tilts of a single lens. The
design is effectively pupil-centric, with modest vignetting (5.9% average). The
image quality is virtually identical to the prime focus design.


title:
Parisian Ruin of the Brownian Motion Risk Model with Constant Force of
  Interest

abstract:
  Let $B(t), t\in \mathbb{R}$ be a standard Brownian motion. Define a risk
process \label{Rudef} R_u^{\delta}(t)=e^{\delta
t}\left(u+c\int^{t}_{0}e^{-\delta s}d s-\sigma\int_{0}^{t}e^{-\delta s}d
B(s)\right), t\geq0, where $u\geq 0$ is the initial reserve, $\delta\geq0$ is
the force of interest, $c>0$ is the rate of premium and $\sigma>0$ is a
volatility factor. In this contribution we obtain an approximation of the
Parisian ruin probability
\mathcal{K}_S^{\delta}(u,T_u):=\mathbb{P}\left\{\inf_{t\in[0,S]}
\sup_{s\in[t,t+T_u]} R_u^{\delta}(s)<0\right\}, S\ge 0, as $u\rightarrow\infty$
where $T_u$ is a bounded function. Further, we show that the Parisian ruin time
of this risk process can be approximated by an exponential random variable. Our
results are new even for the classical ruin probability and ruin time which
correspond to $T_u\equiv0$ in the Parisian setting.


title: On black hole thermodynamics with a momentum relaxation

abstract:
  We investigate black hole thermodynamics involving a scalar hair which is
dual to a momentum relaxation of the dual field theory. This black hole
geometry is able to be classified by two parameters. One is a momentum
relaxation and the other is a mass density of another matter localized at the
center. Even though all parameters are continuous, there exists a specific
point where its thermodynamic interpretation is not continuously connected to
the one defined in the other parameter regime. The similar feature also appears
in a topological AdS black hole. In this work, we show why such an unusual
thermodynamic feature happens and provide a unified way to understand such an
exotic black hole thermodynamically in the entire parameter range.


title: Transfer reaction code with nonlocal interactions

abstract:
  We present a suite of codes (NLAT for nonlocal adiabatic transfer) to
calculate the transfer cross section for single-nucleon transfer reactions,
$(d,N)$ or $(N,d)$, including nonlocal nucleon-target interactions, within the
adiabatic distorted wave approximation. For this purpose, we implement an
iterative method for solving the second order nonlocal differential equation,
for both scattering and bound states. The final observables that can be
obtained with NLAT are differential angular distributions for the cross
sections of $A(d,N)B$ or $B(N,d)A$. Details on the implementation of the
T-matrix to obtain the final cross sections within the adiabatic distorted wave
approximation method are also provided. This code is suitable to be applied for
deuteron induced reactions in the range of $E_d=10-70$ MeV, and provides cross
sections with $4\%$ accuracy.


title:
Modeling a spheroidal microswimmer and cooperative swimming in thin
  films

abstract:
  We propose a hydrodynamic model for a spheroidal microswimmer with two
tangential surface velocity modes. This model is analytically solvable and
reduces to Lighthill's and Blake's spherical squirmer model in the limit of
equal major and minor semi-axes. Furthermore, we present an implementation of
such a spheroidal squirmer by means of multiparticle collision dynamics
simulations. We investigate its properties as well as the scattering of two
spheroidal squirmers in a slit geometry. Thereby we find a stable fixed point,
where two pullers swim cooperatively forming a wedge-like conformation with a
small constant angle.


title:
Time-reversal-breaking topological phases in antiferromagnetic
  Sr$_2$FeOsO$_6$ films

abstract:
  In this work, we studied time-reversal-breaking topological phases as a
result of the interplay between antiferromagnetism and inverted band structures
in thin films of antiferromagnetic double perovskite transition-metal
Sr$_2$FeOsO$_6$. By combining the first-principles calculations and analytical
models, we demonstrate that the quantum anomalous Hall phase and chiral
topological superconducting phase can be realized in this system. We find that
to achieve time-reversal-breaking topological phases in antiferromagnetic
materials, it is essential to break the combined symmetry of time reversal and
inversion, which generally exists in antiferromagnetic structures. As a result,
we can utilize an external electric gate voltage to induce the phase transition
between topological phases and trivial phases, thus providing an electrically
controllable topological platform for the future transport experiments.


title: Examining the effect of nonlocality in $(d,n)$ transfer reactions

abstract:
  Background: In the last year we have been exploring the effect of the
explicit inclusion of nonlocality in (d,p) reactions. Purpose: The goal of this
work is to extend previous studies to (d,n) reactions, which, although similar
to (d,p), have specific properties that merit inspection. Method: We apply our
methods (both the distorted wave Born approximation and the adiabatic wave
approximation) to $(d,n)$ reactions on $^{16}$O, $^{40}$Ca, $^{48}$Ca,
$^{126}$Sn, $^{132}$Sn, and $^{208}$Pb at $20$ and $50$ MeV. Results: We look
separately at the modifications introduced by nonlocality in the final bound
and scattering states, as well as the consequences reflected on the
differential angular distributions. The cross sections obtained when using
nonlocality explicitly are significantly different than those using the local
approximation, just as in (d,p). Due to the particular role of Coulomb in the
bound state, often we found the effects of nonlocality to be larger in (d,n)
than in (d,p). Conclusions: Our results confirm the importance of including
nonlocality explicitly in deuteron induced reactions.


title:
A Communication Efficient and Scalable Distributed Data Mining for the
  Astronomical Data

abstract:
  In 2020, ~60PB of archived data will be accessible to the astronomers. But to
analyze such a paramount data will be a challenging task. This is basically due
to the computational model used to download the data from complex
geographically distributed archives to a central site and then analyzing it in
the local systems. Because the data has to be downloaded to the central site,
the network BW limitation will be a hindrance for the scientific discoveries.
Also analyzing this PB-scale on local machines in a centralized manner is
challenging. In this virtual observatory is a step towards this problem,
however, it does not provide the data mining model. Adding the distributed data
mining layer to the VO can be the solution in which the knowledge can be
downloaded by the astronomers instead the raw data and thereafter astronomers
can either reconstruct the data back from the downloaded knowledge or use the
knowledge directly for further analysis.Therefore, in this paper, we present
Distributed Load Balancing Principal Component Analysis for optimally
distributing the computation among the available nodes to minimize the
transmission cost and downloading cost for the end user. The experimental
analysis is done with Fundamental Plane(FP) data, Gadotti data and complex
Mfeat data. In terms of transmission cost, our approach performs better than
Qi. et al. and Yue.et al. The analysis shows that with the complex Mfeat data
~90% downloading cost can be reduced for the end user with the negligible loss
in accuracy.


title: Recent advances on integrated quantum communications

abstract:
  In recent years, the use of integrated technologies for applications in the
field of quantum information processing and communications has made great
progress. The resulting devices feature valuable characteristics such as
scalability, reproducibility, low cost and interconnectivity, and have the
potential to revolutionize our computation and communication practices in the
future, much in the way that electronic integrated circuits have drastically
transformed our information processing capacities since the last century. Among
the multiple applications of integrated quantum technologies, this review will
focus on typical components of quantum communication systems and on overall
integrated system operation characteristics. We are interested in particular in
the use of photonic integration platforms for developing devices necessary in
quantum communications, including sources, detectors and both passive and
active optical elements. We also illustrate the challenges associated with
performing quantum communications on chip, by using the case study of quantum
key distribution - the most advanced application of quantum information
science. We conclude with promising perspectives in this field.


title: Dynamical Systems On Weighted Lattices: General Theory

abstract:
  In this work a theory is developed for unifying large classes of nonlinear
discrete-time dynamical systems obeying a superposition of a weighted maximum
or minimum type. The state vectors and input-output signals evolve on nonlinear
spaces which we call complete weighted lattices and include as special cases
the nonlinear vector spaces of minimax algebra. Their algebraic structure has a
polygonal geometry. Some of the special cases unified include max-plus,
max-product, and probabilistic dynamical systems. We study problems of
representation in state and input-output spaces using lattice monotone
operators, state and output responses using nonlinear convolutions, solving
nonlinear matrix equations using lattice adjunctions, stability and
controllability. We outline applications in state-space modeling of nonlinear
filtering; dynamic programming (Viterbi algorithm) and shortest paths (distance
maps); fuzzy Markov chains; and tracking audio-visual salient events in
multimodal information streams using generalized hidden Markov models with
control inputs.


title:
Localized spatially nonlinear matter waves in atomic-molecular
  Bose-Einstein condensates with space-modulated nonlinearity

abstract:
  The intrinsic nonlinearity is the most remarkable characteristic of the
Bose-Einstein condensates (BECs) systems. Many studies have been done on atomic
BECs with time- and space- modulated nonlinearities, while there is few work
considering the atomic-molecular BECs with space-modulated nonlinearities.
Here, we obtain two kinds of Jacobi elliptic solutions and a family of rational
solutions of the atomic-molecular BECs with trapping potential and
space-modulated nonlinearity and consider the effect of three-body interaction
on the localized matter wave solutions. The topological properties of the
localized nonlinear matter wave for no coupling are analysed: the parity of
nonlinear matter wave functions depends only on the principal quantum number
$n$, and the numbers of the density packets for each quantum state depend on
both the principal quantum number $n$ and the secondary quantum number $l$.
When the coupling is not zero,the localized nonlinear matter waves given by the
rational function, their topological properties are independent of the
principal quantum number $n$, only depend on the secondary quantum number $l$.
The Raman detuning and the chemical potential can change the number and the
shape of the density packets. The stability of the Jacobi elliptic solutions
depends on the principal quantum number $n$, while the stability of the
rational solutions depends on the chemical potential and Raman detuning.


title:
Solution of the Bartels-Kwiecinski-Praszalowicz equation via Monte Carlo
  integration

abstract:
  We present a method of solution of the Bartels-Kwiecinski-Praszalowicz (BKP)
equation based on the numerical integration of iterated integrals in transverse
momentum and rapidity space. As an application, our procedure, which makes use
of Monte Carlo integration techniques, is applied to obtain the gluon Green
function in the odderon case at leading order. The same approach can be used
for more complicated scenarios.


title: In the Light of Deep Coalescence: Revisiting Trees Within Networks

abstract:
  Phylogenetic networks model reticulate evolutionary histories. The last two
decades have seen an increased interest in establishing mathematical results
and developing computational methods for inferring and analyzing these
networks. A salient concept underlying a great majority of these developments
has been the notion that a network displays a set of trees and those trees can
be used to infer, analyze, and study the network.
  In this paper, we show that in the presence of coalescence effects, the set
of displayed trees is not sufficient to capture the network. We formally define
the set of parental trees of a network and make three contributions based on
this definition. First, we extend the notion of anomaly zone to phylogenetic
networks and report on anomaly results for different networks. Second, we
demonstrate how coalescence events could negatively affect the ability to infer
a species tree that could be augmented into the correct network. Third, we
demonstrate how a phylogenetic network can be viewed as a mixture model that
lends itself to a novel inference approach via gene tree clustering.
  Our results demonstrate the limitations of focusing on the set of trees
displayed by a network when analyzing and inferring the network. Our findings
can form the basis for achieving higher accuracy when inferring phylogenetic
networks and open up new venues for research in this area, including new
problem formulations based on the notion of a network's parental trees.


title:
A Relevant Content Filtering Based Framework For Data Stream
  Summarization

abstract:
  Social media platforms are a rich source of information these days, however,
of all the available information, only a small fraction is of users' interest.
To help users catch up with the latest topics of their interests from the large
amount of information available in social media, we present a relevant content
filtering based framework for data stream summarization. More specifically,
given the topic or event of interest, this framework can dynamically discover
and filter out relevant information from irrelevant information in the stream
of text provided by social media platforms. It then further captures the most
representative and up-to-date information to generate a sequential summary or
event story line along with the evolution of the topic or event. Our framework
does not depend on any labeled data, it instead uses the weak supervision
provided by the user, which matches the real scenarios of users searching for
information about an ongoing event. We experimented on two real events traced
by a Twitter dataset from TREC 2011. The results verified the effectiveness of
relevant content filtering and sequential summary generation of the proposed
framework. It also shows its robustness of using the most easy-to-obtain weak
supervision, i.e., trending topic or hashtag. Thus, this framework can be
easily integrated into social media platforms such as Twitter to generate
sequential summaries for the events of interest. We also make the manually
generated gold-standard sequential summaries of the two test events publicly
available for future use in the community.


title: An inverse problem from condense matter physics

abstract:
  We consider the problem of reconstructing the features of a weak anisotropic
background potential by the trajectories of vortex dipoles in a nonlinear
Gross-Pitaevskii equation. At leading order, the dynamics of vortex dipoles are
given by a Hamiltonian system. If the background potential is sufficiently
smooth and flat, the background can be reconstructed using ideas from the
boundary and the lens rigidity problems. We prove that reconstructions are
unique, derive an approximate reconstruction formula, and present numerical
examples.


title: Local law for random Gram matrices

abstract:
  We prove a local law in the bulk of the spectrum for random Gram matrices
$XX^*$, a generalization of sample covariance matrices, where $X$ is a large
matrix with independent, centered entries with arbitrary variances. The
limiting eigenvalue density that generalizes the Marchenko-Pastur law is
determined by solving a system of nonlinear equations. Our entrywise and
averaged local laws are on the optimal scale with the optimal error bounds.
They hold both in the square case (hard edge) and in the properly rectangular
case (soft edge). In the latter case we also establish a macroscopic gap away
from zero in the spectrum of $XX^*$.


title:
Constraining heavy decaying dark matter with the high energy gamma-ray
  limits

abstract:
  We consider decaying dark matter with masses $10^{7} \lesssim M \lesssim
10^{16}$ GeV, as a source of ultra-high energy (UHE) gamma rays. Using recent
limits on UHE gamma-ray flux for energies $E_\gamma > 2 \cdot 10^{14}$ eV,
provided by extensive air shower observatories, we put limits on masses and
lifetimes of the dark matter. We also discuss possible dark matter decay origin
of tentative 100 PeV photon flux detected with EAS-MSU experiment.


title: The ionization conjecture in Thomas-Fermi-Dirac-von Weizs\"acker theory

abstract:
  We prove that in Thomas-Fermi-Dirac-von Weizs\"acker theory, a nucleus of
charge $Z>0$ can bind at most $Z+C$ electrons, where $C$ is a universal
constant. This result is obtained through a comparison with Thomas-Fermi theory
which, as a by-product, gives bounds on the screened nuclear potential and the
radius of the minimizer. A key ingredient of the proof is a novel technique to
control the particles in the exterior region, which also applies to the liquid
drop model with a nuclear background potential.


title: Analyzing the Behavior of Visual Question Answering Models

abstract:
  Recently, a number of deep-learning based models have been proposed for the
task of Visual Question Answering (VQA). The performance of most models is
clustered around 60-70%. In this paper we propose systematic methods to analyze
the behavior of these models as a first step towards recognizing their
strengths and weaknesses, and identifying the most fruitful directions for
progress. We analyze two models, one each from two major classes of VQA models
-- with-attention and without-attention and show the similarities and
differences in the behavior of these models. We also analyze the winning entry
of the VQA Challenge 2016.
  Our behavior analysis reveals that despite recent progress, today's VQA
models are "myopic" (tend to fail on sufficiently novel instances), often "jump
to conclusions" (converge on a predicted answer after 'listening' to just half
the question), and are "stubborn" (do not change their answers across images).


title: Parameter Optimisation of a Virtual Synchronous Machine in a Microgrid

abstract:
  Parameters of a virtual synchronous machine in a small microgrid are
optimised. The dynamical behaviour of the system is simulated after a
perturbation, where the system needs to return to its steady state. The cost
functional evaluates the system behaviour for different parameters. This
functional is minimised by Parallel Tempering. Two perturbation scenarios are
investigated and the resulting optimal parameters agree with analytical
predictions. Dependent on the focus of the optimisation different optima are
obtained for each perturbation scenario. During the transient the system leaves
the allowed voltage and frequency bands only for a short time if the
perturbation is within a certain range.


title: Selection by Partitioning the Solution Paths

abstract:
  The performance of penalized likelihood approaches depends profoundly on the
selection of the tuning parameter; however, there is no commonly agreed-upon
criterion for choosing the tuning parameter. Moreover, penalized likelihood
estimation based on a single value of the tuning parameter suffers from several
drawbacks. This article introduces a novel approach for feature selection based
on the entire solution paths rather than the choice of a single tuning
parameter, which significantly improves the accuracy of the selection.
Moreover, the approach allows for feature selection using ridge or other
strictly convex penalties. The key idea is to classify variables as relevant or
irrelevant at each tuning parameter and then to select all of the variables
which have been classified as relevant at least once. We establish the
theoretical properties of the method, which requires significantly weaker
conditions than existing methods in the literature. We also illustrate the
advantages of the proposed approach with simulation studies and a data example.


title: Magnetic eigenmaps for community detection in directed networks

abstract:
  Communities in directed networks have often been characterized as regions
with a high density of links, or as sets of nodes with certain patterns of
connection. Our approach for community detection combines the optimization of a
quality function and a spectral clustering of a deformation of the
combinatorial Laplacian, the so-called magnetic Laplacian. The eigenfunctions
of the magnetic Laplacian, that we call magnetic eigenmaps, incorporate
structural information. Hence, using the magnetic eigenmaps, dense communities
including directed cycles can be revealed as well as "role" communities in
networks with a running flow, usually discovered thanks to mixture models.
Furthermore, in the spirit of the Markov stability method, an approach for
studying communities at different energy levels in the network is put forward,
based on a quantum mechanical system at finite temperature.


title: Low Power Wide Area Networks: An Overview

abstract:
  Low Power Wide Area (LPWA) networks are attracting a lot of attention
primarily because of their ability to offer affordable connectivity to the
low-power devices distributed over very large geographical areas. In realizing
the vision of the Internet of Things (IoT), LPWA technologies complement and
sometimes supersede the conventional cellular and short range wireless
technologies in performance for various emerging smart city and
machine-to-machine (M2M) applications. This review paper presents the design
goals and the techniques, which different LPWA technologies exploit to offer
wide-area coverage to low-power devices at the expense of low data rates. We
survey several emerging LPWA technologies and the standardization activities
carried out by different standards development organizations (e.g., IEEE, IETF,
3GPP, ETSI) as well as the industrial consortia built around individual LPWA
technologies (e.g., LORa Alliance,WEIGHTLESS-SIG, and DASH7 Alliance). We
further note that LPWA technologies adopt similar approaches, thus sharing
similar limitations and challenges. This paper expands on these research
challenges and identifies potential directions to address them. While the
proprietary LPWA technologies are already hitting the market with large
nationwide roll-outs, this paper encourages an active engagement of the
research community in solving problems that will shape the connectivity of tens
of billions of devices in the next decade.


title: Constraint Analysis of Two-Dimensional Quadratic Gravity from BF Theory

abstract:
  Quadratic gravity in two dimensions can be formulated as a Background Field
(BF) theory plus an interaction term which is polynomial in both, the gauge and
Background fields. This formulation is similar to the one given by Freidel and
Starodubtsev to obtain MacDowell-Mansouri gravity in four dimensions.
  In this article we use the Dirac's Hamiltonian formalism to analyze the
constraint structure of the two-dimensional Polynomial BF action. After we
obtain the constraints of the theory, we proceed with the
Batalin-Fradkin-Vilkovisky procedure to obtain the transition amplitude. We
also compare our results with the ones obtained from generalized dilaton
gravity.


title: Restricted developments in partizan misere game theory

abstract:
  Much progress has been made in misere game theory using the technique of
restricted misere play, where games can be considered equivalent inside a
restricted set of games without being equal in general. This paper provides a
survey of recent results in this area, including two particularly interesting
properties of restricted misere games: (1) a game can have an additive inverse
that is not its negative, and (2) a position can be reversible through an end
(a game with Left but not Right options, or vice versa). These properties are
not possible in normal play and general misere play, respectively. Related open
problems are discussed.


title: Coincidence Reidemeister trace and its generalization

abstract:
  We give a homotopy invariant construction of the Reidemeister trace for the
coincidence of two maps between closed manifolds of not necessarily the same
dimensions. It is realized as a homology class of the homotopy equalizer, which
coincides with the Hurewicz image of Koschorke's stabilized bordism invariant.
To define it, we use a kind of shriek maps appearing string topology. As an
application, we compute the coincidence Reidemeister trace for the
self-coincidence of the projections of $S^1$-bundles on $\mathbb{C}P^n$. We
also mention how to relate our construction to the string topology operation
called the loop coproduct.


title: Derived invariants for surface cut algebras II: the punctured case

abstract:
  For each algebra of global dimension 2 arising from the quiver with potential
associated to a triangulation of an unpunctured surface, Amiot-Grimeland have
defined an integer-valued function on the first singular homology group of the
surface, and have proved that two such algebras of global dimension 2 are
derived equivalent precisely when there exists an automorphism of the surface
that makes their associated functions coincide.
  In the present paper we generalize the constructions and results of
Amiot-Grimeland to the setting of arbitrarily punctured surfaces. As an
application, we show that there always is a derived equivalence between any two
algebras of global dimension 2 arising from the quivers with potential of
(valency at least 2) triangulations of arbitrarily punctured polygons.
  While in the unpunctured case the quiver with potential of any triangulation
admits cuts yielding algebras of global dimension at most 2, in the case of
punctured surfaces the QPs of some triangulations do not admit cuts, and even
when they do, the global dimension of the corresponding degree-0 algebra may
exceed 2. In this paper we give a combinatorial characterization of each of
these two situations.


title: Parallel SGD: When does averaging help?

abstract:
  Consider a number of workers running SGD independently on the same pool of
data and averaging the models every once in a while -- a common but not well
understood practice. We study model averaging as a variance-reducing mechanism
and describe two ways in which the frequency of averaging affects convergence.
For convex objectives, we show the benefit of frequent averaging depends on the
gradient variance envelope. For non-convex objectives, we illustrate that this
benefit depends on the presence of multiple globally optimal points. We
complement our findings with multicore experiments on both synthetic and real
data.


title:
Origin of reversible photo-induced phase separation in hybrid
  perovskites

abstract:
  Nonequilibrium processes occurring in functional materials can significantly
impact device efficiencies and are often difficult to characterize due to the
broad range of length and time scales involved. In particular, mixed halide
hybrid perovskites are promising for optoelectronics, yet the halides
reversibly phase separate when photo-excited, significantly altering device
performance. By combining nanoscale imaging and multiscale modeling, we
elucidate the mechanism underlying this phenomenon, demonstrating that local
strain induced by photo-generated polarons promotes halide phase separation and
leads to nucleation of light-stabilized iodide-rich clusters. This effect
relies on the unique electromechanical properties of hybrid materials,
characteristic of neither their organic nor inorganic constituents alone.
Exploiting photo-induced phase separation and other nonequilibrium phenomena in
hybrid materials, generally, could enable new opportunities for expanding the
functional applications in sensing, photoswitching, optical memory, and energy
storage.


title: Thermodynamics of a Simple Three-Dimensional DNA Hairpin Model

abstract:
  We characterize the equation of state for a simple three-dimensional DNA
hairpin model using a Metropolis Monte Carlo algorithm. This algorithm was run
at constant temperature and fixed separation between the terminal ends of the
strand. From the equation of state, we compute the compressibility, thermal
expansion coefficient, and specific heat along with adiabatic path.


title:
Transient cerebral hypoperfusion and hypertensive events during atrial
  fibrillation: a plausible mechanism for cognitive impairment

abstract:
  Atrial fibrillation (AF) is associated with an increased risk of dementia and
cognitive decline, independent of strokes. Several mechanisms have been
proposed to explain this association, but altered cerebral blood flow dynamics
during AF has been poorly investigated: in particular, it is unknown how AF
influences hemodynamic parameters of the distal cerebral circulation, at the
arteriolar and capillary level. Two coupled lumped-parameter models (systemic
and cerebrovascular circulations, respectively) were here used to simulate
sinus rhythm (SR) and AF. For each simulation 5000 cardiac cycles were analyzed
and cerebral hemodynamic parameters were calculated. With respect to SR, AF
triggered a higher variability of the cerebral hemodynamic variables which
increases proceeding towards the distal circulation, reaching the maximum
extent at the arteriolar and capillary levels. This variability led to critical
cerebral hemodynamic events of excessive pressure or reduced blood flow: 303
hypoperfusions occurred at the arteriolar level, while 387 hypertensive events
occurred at the capillary level during AF. By contrast, neither hypoperfusions
nor hypertensive events occurred during SR. Thus, the impact of AF per se on
cerebral hemodynamics candidates as a relevant mechanism into the genesis of
AF-related cognitive impairment/dementia.


title: Personalized Prognostic Models for Oncology: A Machine Learning Approach

abstract:
  We have applied a little-known data transformation to subsets of the
Surveillance, Epidemiology, and End Results (SEER) publically available data of
the National Cancer Institute (NCI) to make it suitable input to standard
machine learning classifiers. This transformation properly treats the
right-censored data in the SEER data and the resulting Random Forest and
Multi-Layer Perceptron models predict full survival curves. Treating the 6, 12,
and 60 months points of the resulting survival curves as 3 binary classifiers,
the 18 resulting classifiers have AUC values ranging from .765 to .885. Further
evidence that the models have generalized well from the training data is
provided by the extremely high levels of agreement between the random forest
and neural network models predictions on the 6, 12, and 60 month binary
classifiers.


title: Almost balanced biased graph representations of frame matroids

abstract:
  Given a 3-connected biased graph $\Omega$ with a balancing vertex, and with
frame matroid $F(\Omega)$ nongraphic and 3-connected, we determine all biased
graphs $\Omega'$ with $F(\Omega') = F(\Omega)$. As a consequence, we show that
if $M$ is a 4-connected nongraphic frame matroid represented by a biased graph
$\Omega$ having a balancing vertex, then $\Omega$ essentially uniquely
represents $M$. More precisely, all biased graphs representing $M$ are obtained
from $\Omega$ by replacing a subset of the edges incident to its unique
balancing vertex with unbalanced loops.


title:
Model $I$--$V$ curves and figures of merit of underdamped deterministic
  Josephson ratchets

abstract:
  We propose simple models for the current-voltage characteristics of typical
Josephson ratchets. We consider the case of a ratchet working against a
constant applied counter force and derive analytical expressions for the key
characteristics of such a ratchet: rectification curve, stopping force, input
and output powers and rectification efficiency. Optimization of the ratchet
performance is discussed.


title:
Automatic Neuron Detection in Calcium Imaging Data Using Convolutional
  Networks

abstract:
  Calcium imaging is an important technique for monitoring the activity of
thousands of neurons simultaneously. As calcium imaging datasets grow in size,
automated detection of individual neurons is becoming important. Here we apply
a supervised learning approach to this problem and show that convolutional
networks can achieve near-human accuracy and superhuman speed. Accuracy is
superior to the popular PCA/ICA method based on precision and recall relative
to ground truth annotation by a human expert. These results suggest that
convolutional networks are an efficient and flexible tool for the analysis of
large-scale calcium imaging data.


title: VideoMCC: a New Benchmark for Video Comprehension

abstract:
  While there is overall agreement that future technology for organizing,
browsing and searching videos hinges on the development of methods for
high-level semantic understanding of video, so far no consensus has been
reached on the best way to train and assess models for this task. Casting video
understanding as a form of action or event categorization is problematic as it
is not fully clear what the semantic classes or abstractions in this domain
should be. Language has been exploited to sidestep the problem of defining
video categories, by formulating video understanding as the task of captioning
or description. However, language is highly complex, redundant and sometimes
ambiguous. Many different captions may express the same semantic concept. To
account for this ambiguity, quantitative evaluation of video description
requires sophisticated metrics, whose performance scores are typically hard to
interpret by humans.
  This paper provides four contributions to this problem. First, we formulate
Video Multiple Choice Caption (VideoMCC) as a new well-defined task with an
easy-to-interpret performance measure. Second, we describe a general
semi-automatic procedure to create benchmarks for this task. Third, we publicly
release a large-scale video benchmark created with an implementation of this
procedure and we include a human study that assesses human performance on our
dataset. Finally, we propose and test a varied collection of approaches on this
benchmark for the purpose of gaining a better understanding of the new
challenges posed by video comprehension.


title: Multi-Stage Temporal Difference Learning for 2048-like Games

abstract:
  Szubert and Jaskowski successfully used temporal difference (TD) learning
together with n-tuple networks for playing the game 2048. However, we observed
a phenomenon that the programs based on TD learning still hardly reach large
tiles. In this paper, we propose multi-stage TD (MS-TD) learning, a kind of
hierarchical reinforcement learning method, to effectively improve the
performance for the rates of reaching large tiles, which are good metrics to
analyze the strength of 2048 programs. Our experiments showed significant
improvements over the one without using MS-TD learning. Namely, using 3-ply
expectimax search, the program with MS-TD learning reached 32768-tiles with a
rate of 18.31%, while the one with TD learning did not reach any. After further
tuned, our 2048 program reached 32768-tiles with a rate of 31.75% in 10,000
games, and one among these games even reached a 65536-tile, which is the first
ever reaching a 65536-tile to our knowledge. In addition, MS-TD learning method
can be easily applied to other 2048-like games, such as Threes. Based on MS-TD
learning, our experiments for Threes also demonstrated similar performance
improvement, where the program with MS-TD learning reached 6144-tiles with a
rate of 7.83%, while the one with TD learning only reached 0.45%.


title:
A coupled $2\times2$D Babcock-Leighton solar dynamo model. II. Reference
  dynamo solutions

abstract:
  In this paper we complete the presentation of a new hybrid $2\times2$D flux
transport dynamo (FTD) model of the solar cycle based on the Babcock-Leighton
mechanism of poloidal magnetic field regeneration via the surface decay of
bipolar magnetic regions (BMRs). This hybrid model is constructed by allowing
the surface flux transport (SFT) simulation described in Lemerle et al. 2015 to
provide the poloidal source term to an axisymmetric FTD simulation defined in a
meridional plane, which in turn generates the BMRs required by the SFT. A key
aspect of this coupling is the definition of an emergence function describing
the probability of BMR emergence as a function of the spatial distribution of
the internal axisymmetric magnetic field. We use a genetic algorithm to
calibrate this function, together with other model parameters, against observed
cycle 21 emergence data. We present a reference dynamo solution reproducing
many solar cycle characteristics, including good hemispheric coupling, phase
relationship between the surface dipole and the BMR-generating internal field,
and correlation between dipole strength at cycle maximum and peak amplitude of
the next cycle. The saturation of the cycle amplitude takes place through the
quenching of the BMR tilt as a function of the internal field. The observed
statistical scatter about the mean BMR tilt, built into the model, acts as a
source of stochasticity which dominates amplitude fluctuations. The model thus
can produce Dalton-like epochs of strongly suppressed cycle amplitude lasting a
few cycles and can even shut off entirely following an unfavorable sequence of
emergence events.


title: Flat structures on the deformations of Gepner chiral rings

abstract:
  We propose a simple method for the computation of the flat coordinates and
Saito primitive forms on Frobenius manifolds of the deformations of Jacobi
rings associated with isolated singularities. The method is based on using a
conjecture about integral representations for the flat coordinates and on the
Saito cohomology theory. This reduces the computation to a simple linear
problem. We consider the case of the deformed Gepner chiral rings. The
knowledge of the flat structures of Frobenius manifolds can be used for exact
solution of the models of the topological conformal field theories
corresponding to these chiral rings.


title: Split-sideband spectroscopy in slowly modulated optomechanics

abstract:
  Optomechanical coupling between the motion of a mechanical oscillator and a
cavity represents a new arena for experimental investigation of quantum effects
on the mesoscopic and macroscopic scale.The motional sidebands of the output of
a cavity offer ultra-sensitive probes of the dynamics. We introduce a scheme
whereby these sidebands split asymmetrically and show how they may be used as
experimental diagnostics and signatures of quantum noise limited dynamics. We
show split-sidebands with controllable asymmetry occur by simultaneously
modulating the light-mechanical coupling $g$ and $\omega_M$ - slowly and out
of-phase. Such modulations are generic but already occur in optically trapped
set-ups where the equilibrium point of the oscillator is varied cyclically. We
analyse recently observed, but overlooked, experimental split-sideband
asymmetries; although not yet in the quantum regime, the data suggests that
split sideband structures are easily accessible to future experiments.


title: Weibull Generalized Exponential Distribution

abstract:
  This paper introduces a new three-parameters model called the Weibull-G
exponential distribution (WGED) distribution which exhibits bathtub-shaped
hazard rate. Some of it's statistical properties are obtained including
quantile, moments, generating functions, reliability and order statistics. The
method of maximum likelihood is used for estimating the model parameters and
the observed Fisher's information matrix is derived. We illustrate the
usefulness of the proposed model by applications to real data.


title:
Separately Radial and Radial Toeplitz Operators on the Projective Space
  and Representation Theory

abstract:
  We consider separately radial (with corresponding group $\mathbb{T}^n$) and
radial (with corresponding group $\mathrm{U}(n))$ symbols on the projective
space $\mathbb{P}^n(\mathbb{C})$, as well as the associated Toeplitz operators
on the weighted Bergman spaces. It is known that the $C^*$-algebras generated
by each family of such Toeplitz operators are commutative. We present a new
representation theoretic proof of such commutativity. Our method is easier and
more enlightening as it shows that the commutativity of the $C^*$-algebras is a
consequence of the existence of multiplicity-free representations. Furthermore,
our method shows how to extend the current formulas for the spectra of the
corresponding Toeplitz operators to any closed group lying between
$\mathbb{T}^n$ and $\mathrm{U}(n)$.


title: Variable-Sized Uncertainty and Inverse Problems in Robust Optimization

abstract:
  In robust optimization, the general aim is to find a solution that performs
well over a set of possible parameter outcomes, the so-called uncertainty set.
In this paper, we assume that the uncertainty size is not fixed, and instead
aim at finding a set of robust solutions that covers all possible uncertainty
set outcomes. We refer to these problems as robust optimization with
variable-sized uncertainty. We discuss how to construct smallest possible sets
of min-max robust solutions and give bounds on their size.
  A special case of this perspective is to analyze for which uncertainty sets a
nominal solution ceases to be a robust solution, which amounts to an inverse
robust optimization problem. We consider this problem with a min-max regret
objective and present mixed-integer linear programming formulations that can be
applied to construct suitable uncertainty sets.
  Results on both variable-sized uncertainty and inverse problems are further
supported with experimental data.


title:
Spread, volatility, and volume relationship in financial markets and
  market making profit optimization

abstract:
  We study the relationship between price spread, volatility and trading
volume. We find that spread forms as a result of interplay between order
liquidity and order impact. When trading volume is small adding more liquidity
helps improve price accuracy and reduce spread, but after some point additional
liquidity begins to deteriorate price. The model allows to connect the bid-ask
spread and high-low bars to measurable microstructural parameters and express
their dependence on trading volume, volatility and time horizon. Using the
established relations, we address the operating spread optimization problem to
maximize market-making profit.


title:
Finite-time Partitions for Lagrangian Structure Identification in Gulf
  Stream Eddy Transport

abstract:
  We develop a methodology to identify finite-time Lagrangian structures from
data and models using an extension of the Koopman operator-theoretic methods
developed for velocity fields with simple (periodic, quasi-periodic)
time-dependence. To achieve this, the notion of the Finite Time Ergodic (FiTER)
partition is developed and rigorously justified. In combination with a
clustering-based approach, the methodology enables identification of the
temporal evolution of Lagrangian structures in a classic, benchmark,
oceanographic transport problem, namely the cross-stream flux induced by the
interaction of a meso- scale Gulf Stream Ring eddy with the main jet. We focus
on a single mixing event driven by the interaction between an energetic cold
core ring (a cyclone), the strong jet, and a number of smaller scale cyclones
and anticyclones. The new methodology enab les reconstruction of Lagrangian
structures in three dimensions and analysis of their time-evolution.


title: Network Infusion to Infer Information Sources in Networks

abstract:
  Several significant models have been developed that enable the study of
diffusion of signals across biological, social and engineered networks. Within
these established frameworks, the inverse problem of identifying the source of
the propagated signal is challenging, owing to the numerous alternative
possibilities for signal progression through the network. In real world
networks, the challenge of determining sources is compounded as the true
propagation dynamics are typically unknown, and when they have been directly
measured, they rarely conform to the assumptions of any of the well-studied
models. In this paper we introduce a method called Network Infusion (NI) that
has been designed to circumvent these issues, making source inference practical
for large, complex real world networks. The key idea is that to infer the
source node in the network, full characterization of diffusion dynamics, in
many cases, may not be necessary. This objective is achieved by creating a
diffusion kernel that well-approximates standard diffusion models, but lends
itself to inversion, by design, via likelihood maximization or error
minimization. We apply NI for both single-source and multi-source diffusion,
for both single-snapshot and multi-snapshot observations, and for both
homogeneous and heterogeneous diffusion setups. We prove the mean-field
optimality of NI for different scenarios, and demonstrate its effectiveness
over several synthetic networks. Moreover, we apply NI to a real-data
application, identifying news sources in the Digg social network, and
demonstrate the effectiveness of NI compared to existing methods. Finally, we
propose an integrative source inference framework that combines NI with a
distance centrality-based method, which leads to a robust performance in cases
where the underlying dynamics are unknown.


title: Robust Learning of Fixed-Structure Bayesian Networks

abstract:
  We investigate the problem of learning Bayesian networks in a robust model
where an $\epsilon$-fraction of the samples are adversarially corrupted. In
this work, we study the fully observable discrete case where the structure of
the network is given. Even in this basic setting, previous learning algorithms
either run in exponential time or lose dimension-dependent factors in their
error guarantees. We provide the first computationally efficient robust
learning algorithm for this problem with dimension-independent error
guarantees. Our algorithm has near-optimal sample complexity, runs in
polynomial time, and achieves error that scales nearly-linearly with the
fraction of adversarially corrupted samples. Finally, we show on both synthetic
and semi-synthetic data that our algorithm performs well in practice.


title:
Nodes Localization in 3D Wireless Sensor Networks Based on
  Multidimensional Scaling Algorithm

abstract:
  In the recent years, there has been a huge advancement in wireless sensor
computing technology. Today, wireless sensor network (WSN) has become a key
technology for different types of smart environment. Nodes localization in WSN
has arisen as a very challenging problem in the research community. Most of the
applications for WSN are not useful without a priory known nodes positions.
Adding GPS receivers to each node is an expensive solution and inapplicable for
indoor environments. In this paper, we implemented and evaluated an algorithm
based on multidimensional scaling (MDS) technique for three-dimensional (3D)
nodes localization in WSN using improved heuristic method for distance
calculation. Using extensive simulations we investigated our approach regarding
various network parameters. We compared the results from the simulations with
other approaches for 3D-WSN localization and showed that our approach
outperforms other techniques in terms of accuracy.


title:
Application of Wireless Sensor Networks for Indoor Temperature
  Regulation

abstract:
  Wireless sensor networks take a major part in our everyday lives by enhancing
systems for home automation, healthcare, temperature control, energy
consumption monitoring, and so forth. In this paper we focus on a system used
for temperature regulation for residential, educational, industrial, and
commercial premises, and so forth. We propose a framework for indoor
temperature regulation and optimization using wireless sensor networks based on
ZigBee platform. This paper considers architectural design of the system, as
well as implementation guidelines. The proposed system favors methods that
provide energy savings by reducing the amount of data transmissions through the
network. Furthermore, the framework explores techniques for localization, such
that the location of the nodes can be used by algorithms that regulate
temperature settings.


title: Non-parametric estimation of morphological lopsidedness

abstract:
  Asymmetries in the neutral hydrogen gas distribution and kinematics of
galaxies are thought to be indicators for both gas accretion and gas removal
processes. These are of fundamental importance for galaxy formation and
evolution. Upcoming large blind HI surveys will provide tens of thousands of
galaxies for a study of these asymmetries in a proper statistical way. Due to
the large number of expected sources and the limited resolution of the majority
of objects, detailed modelling is not feasible for most detections. We need
fast, automatic and sensitive methods to classify these objects in an objective
way. Existing non-parametric methods suffer from effects like the dependence on
signal to noise, resolution and inclination. Here we show how to correctly take
these effects into account and show ways to estimate the precision of the
methods. We will use existing and modelled data to give an outlook on the
performance expected for galaxies observed in the various sky surveys planned
for e.g. WSRT/APERTIF and ASKAP.


title: A taxonomy of localization techniques based on multidimensional scaling

abstract:
  Localization in Wireless Sensor Networks (WSNs) has been a challenging
problem in the last decade. The most explored approaches for this purpose are
based on multidimensional scaling (MDS) technique. The first algorithm that
introduced MDS for nodes localization in sensor networks is well known as
MDS-MAP. Since its appearance in 2003, many variations of MDS-MAP have been
proposed in the literature. This paper aims to provide a comprehensive survey
of the localization techniques that are based on MDS. We classify MDS-based
algorithms according to different taxonomy features and different evaluation
metrics.


title:
Improved MDS-based Algorithm for Nodes Localization in Wireless Sensor
  Networks

abstract:
  With the recent development of technology, wireless sensor networks (WSN) are
becoming an important part of many applications. Knowing the exact location of
each sensor in the network is very important issue. Therefore, the localization
problem is a growing field of interest. Adding GPS receivers to each sensor
node is costly solution and inapplicable on nodes with limited resources.
Additionally, it is not suitable for indoor environments. In this paper, we
propose an algorithm for nodes localization in WNS based on multidimensional
scaling (MDS) technique. Our approach improves MDS by distance matrix
refinement. Using extensive simulations we investigated in details our approach
regarding different network topologies, various network parameters and
performance issues. The results from simulations show that our improved MDS
(IMDS) algorithm outperforms well known MDS-MAP algorithm [1] in terms of
accuracy.


title: Gravitational redshift from rotating body having intense magnetic field

abstract:
  It is well known fact that gravitational field can alter the space-time
structure and gravitational redshift is its one example. Electromagnetic field
can also alter the space-time similar to gravitational field. So
electromagnetic field can give rise to an additional effect on gravitational
redshift. There are many objects in nature, like neutron stars, magnetars etc
which have high amount of rotation and magnetic field. In the present paper we
will derive the expression of gravitational redshift from rotating body having
intense magnetic field by using the action function of the electromagnetic
fields.


title:
Atmospheric neutrinos, $nu_e-nu_s$ oscillations, and a novel neutrino
  evolution equation

abstract:
  If a sterile neutrino nu_s with an eV-scale mass and a sizeable mixing to the
electron neutrino exists, as indicated by the reactor and gallium neutrino
anomalies, a strong resonance enhancement of nu_e-nu_s oscillations of
atmospheric neutrinos should occur in the TeV energy range. At these energies
neutrino flavour transitions in the 3+1 scheme depend on just one neutrino mass
squared difference and are fully described within a 3-flavour oscillation
framework. We demonstrate that the flavour transitions of atmospheric nu_e can
actually be very accurately described in a 2-flavour framework, with neutrino
flavour evolution governed by an inhomogeneous Schroedinger-like equation.
Evolution equations of this type have not been previously considered in the
theory of neutrino oscillations.


title:
On the decidability of the $\Sigma_2$ theories of the arithmetic and
  hyperarithmetic degrees as uppersemilattices

abstract:
  We establish the decidability of the $\Sigma_2$ theory of both the arithmetic
and hyperarithmetic degrees in the language of uppersemilattices i.e. the
language with $\leq, 0$ and $\sqcup$. This is achieved by using Kumabe-Slaman
forcing - along with other known results - to show that given finite
uppersemilattices $\mathcal{M}$ and $\mathcal{N}$, where $\mathcal{M}$ is a
subuppersemilattice of $\mathcal{N}$, then for both degree structures, every
embedding of $\mathcal{M}$ into the structure extends to one of $\mathcal{N}$
iff $\mathcal{N}$ is an end-extension of $\mathcal{M}$.


title:
Artificial intelligence applied to the automatic analysis of absorption
  spectra. Objective measurement of the fine structure constant

abstract:
  A new and automated method is presented for the analysis of high-resolution
absorption spectra. Three established numerical methods are unified into one
"artificial intelligence" process: a genetic algorithm (GVPFIT); non-linear
least-squares with parameter constraints (VPFIT); and Bayesian Model Averaging
(BMA).
  The method has broad application but here we apply it specifically to the
problem of measuring the fine structure constant at high redshift. For this we
need objectivity and reproducibility. GVPFIT is also motivated by the
importance of obtaining a large statistical sample of measurements of
$\Delta\alpha/\alpha$. Interactive analyses are both time consuming and complex
and automation makes obtaining a large sample feasible.
  In contrast to previous methodologies, we use BMA to derive results using a
large set of models and show that this procedure is more robust than a human
picking a single preferred model since BMA avoids the systematic uncertainties
associated with model choice.
  Numerical simulations provide stringent tests of the whole process and we
show using both real and simulated spectra that the unified automated fitting
procedure out-performs a human interactive analysis. The method should be
invaluable in the context of future instrumentation like ESPRESSO on the VLT
and indeed future ELTs.
  We apply the method to the $z_{abs} = 1.8389$ absorber towards the $z_{em} =
2.145$ quasar J110325-264515. The derived constraint of $\Delta\alpha/\alpha =
3.3 \pm 2.9 \times 10^{-6}$ is consistent with no variation and also consistent
with the tentative spatial variation reported in Webb et al (2011) and King et
al (2012).


title:
Deliberation favours social efficiency by making people disregard their
  relative shares: Evidence from US and India

abstract:
  Groups make decisions on both the production and the distribution of
resources. These decisions typically involve a tension between increasing the
total level of group resources (i.e. social efficiency) and distributing these
resources among group members (i.e. individuals' relative shares). This is the
case because the redistribution process may destroy part of the resources, thus
resulting in socially inefficient allocations. Here we apply a dual-process
approach to understand the cognitive underpinnings of this fundamental tension.
We conducted a set of experiments to examine the extent to which different
allocation decisions respond to intuition or deliberation. In a newly developed
approach, we assess intuition and deliberation at both the trait level (using
the Cognitive Reflection Test, henceforth CRT) and the state level (through the
experimental manipulation of response times). To test for robustness,
experiments were conducted in two countries: the US and India. Despite absolute
level differences across countries, in both locations we show that: (i) time
pressure and low CRT scores are associated with individuals' concerns for their
relative shares; (ii) time delay and high CRT scores are associated with
individuals' concerns for social efficiency. These findings demonstrate that
deliberation favours social efficiency by overriding individuals' intuitive
tendency to focus on relative shares.


title: Syzygies over the Polytope Semiring

abstract:
  Tropical geometry and its applications indicate a "theory of syzygies" over
polytope semirings. Taking cue from this indication, we study a notion of
syzygies over the polytope semiring. We begin our exploration with the concept
of Newton basis, an analogue of Gr\"obner basis that captures the image of an
ideal under the Newton polytope map. The image ${\rm New}(I)$ of a graded ideal
$I$ under the Newton polytope is a graded sub-semimodule of the polytope
semiring. Analogous to the Hilbert series, we define the notion of
Newton-Hilbert series that encodes the rank of each graded piece of ${\rm
New}(I)$. We prove the rationality of the Newton-Hilbert series for
sub-semimodules that satisfy a property analogous to Cohen-Macaulayness. We
define notions of regular sequence of polytopes and syzygies of polytopes. We
show an analogue of the Koszul property characterizing the syzygies of a
regular sequence of polytopes.


title: Fast Multi-Layer Laplacian Enhancement

abstract:
  A novel, fast and practical way of enhancing images is introduced in this
paper. Our approach builds on Laplacian operators of well-known edge-aware
kernels, such as bilateral and nonlocal means, and extends these filter's
capabilities to perform more effective and fast image smoothing, sharpening and
tone manipulation. We propose an approximation of the Laplacian, which does not
require normalization of the kernel weights. Multiple Laplacians of the
affinity weights endow our method with progressive detail decomposition of the
input image from fine to coarse scale. These image components are blended by a
structure mask, which avoids noise/artifact magnification or detail loss in the
output image. Contributions of the proposed method to existing image editing
tools are: (1) Low computational and memory requirements, making it appropriate
for mobile device implementations (e.g. as a finish step in a camera pipeline),
(2) A range of filtering applications from detail enhancement to denoising with
only a few control parameters, enabling the user to apply a combination of
various (and even opposite) filtering effects.


title:
Swift observations of the 2015 outburst of AG Peg -- from slow nova to
  classical symbiotic outburst

abstract:
  Symbiotic stars often contain white dwarfs with quasi-steady shell burning on
their surfaces. However, in most symbiotics, the origin of this burning is
unclear. In symbiotic slow novae, however, it is linked to a past thermonuclear
runaway. In June 2015, the symbiotic slow nova AG Peg was seen in only its
second optical outburst since 1850. This recent outburst was of much shorter
duration and lower amplitude than the earlier eruption, and it contained
multiple peaks -- like outbursts in classical symbiotic stars such as Z And. We
report Swift X-ray and UV observations of AG Peg made between June 2015 and
January 2016. The X-ray flux was markedly variable on a time scale of days,
particularly during four days near optical maximum, when the X-rays became
bright and soft. This strong X-ray variability continued for another month,
after which the X-rays hardened as the optical flux declined. The UV flux was
high throughout the outburst, consistent with quasi-steady shell burning on the
white dwarf. Given that accretion disks around white dwarfs with shell burning
do not generally produce detectable X-rays (due to Compton-cooling of the
boundary layer), the X-rays probably originated via shocks in the ejecta. As
the X-ray photo-electric absorption did not vary significantly, the X-ray
variability may directly link to the properties of the shocked material. AG
Peg's transition from a slow symbiotic nova (which drove the 1850 outburst) to
a classical symbiotic star suggests that shell burning in at least some
symbiotic stars is residual burning from prior novae.