title:
Achieving Geometric Convergence for Distributed Optimization over
  Time-Varying Graphs

abstract:
  This paper considers the problem of distributed optimization over
time-varying graphs. For the case of undirected graphs, we introduce a
distributed algorithm, referred to as DIGing, based on a combination of a
distributed inexact gradient method and a gradient tracking technique. The
DIGing algorithm uses doubly stochastic mixing matrices and employs fixed
step-sizes and, yet, drives all the agents' iterates to a global and consensual
minimizer. When the graphs are directed, in which case the implementation of
doubly stochastic mixing matrices is unrealistic, we construct an algorithm
that incorporates the push-sum protocol into the DIGing structure, thus
obtaining Push-DIGing algorithm. The Push-DIGing uses column stochastic
matrices and fixed step-sizes, but it still converges to a global and
consensual minimizer. Under the strong convexity assumption, we prove that the
algorithms converge at R-linear (geometric) rates as long as the step-sizes do
not exceed some upper bounds. We establish explicit estimates for the
convergence rates. When the graph is undirected it shows that DIGing scales
polynomially in the number of agents. We also provide some numerical
experiments to demonstrate the efficacy of the proposed algorithms and to
validate our theoretical findings.


title: Saturation scale fluctuations and multi-particle rapidity correlations

abstract:
  We study the effect of intrinsic fluctuations of the proton saturation
momentum scale on event-by-event rapidity distributions. Saturation scale
fluctuations generate an asymmetry in the single particle rapidity distribution
in each event resulting in genuine n-particle correlations having a component
linear in the rapidities of the produced particles, $y_1\cdots y_n$. We
introduce a color domain model that naturally explains the centrality
dependence of the two-particle rapidity correlations recently measured by ATLAS
while constraining the probability distribution of saturation scale
fluctuations in the proton. Predictions for n = 4, 6 and 8 particle
correlations find that the four and eight-particle cumulant change sign at an
intermediate multiplicity, a signature which could be tested experimentally.


title: Generic linear perturbations

abstract:
  In his celebrated paper "Generic projections", John Mather has shown that
almost all linear projections from a submanifold of a vector space into a
subspace are transverse with respect to a given modular submanifold. In this
paper, an improvement of Mather's result is stated. Namely, we show that almost
all linear perturbations of a smooth mapping from a submanifold of
$\mathbb{R}^m$ into $\mathbb{R}^\ell$ yield a transverse mapping with respect
to a given modular submanifold. Moreover, applications of this result are
given.


title: Two-Element Mixture of Bose and Fermi Superfluids

abstract:
  We report on the production of a stable mixture of bosonic and fermionic
superfluids composed of the elements $^{174}$Yb and $^6$Li which feature a
strong mismatch in mass and distinct electronic properties. We demonstrate
elastic coupling between the superfluids by observing the shift in dipole
oscillation frequency of the bosonic component due to the presence of the
fermions. The measured magnitude of the shift is consistent with a mean-field
model and its direction determines the previously unknown sign of the
interspecies scattering length to be positive. We also observe the exchange of
angular momentum between the superfluids from the excitation of a scissors mode
in the bosonic component through interspecies interactions. We explain this
observation using an analytical model based on superfluid hydrodynamics.


title: Gland Instance Segmentation by Deep Multichannel Side Supervision

abstract:
  In this paper, we propose a new image instance segmentation method that
segments individual glands (instances) in colon histology images. This is a
task called instance segmentation that has recently become increasingly
important. The problem is challenging since not only do the glands need to be
segmented from the complex background, they are also required to be
individually identified. Here we leverage the idea of image-to-image prediction
in recent deep learning by building a framework that automatically exploits and
fuses complex multichannel information, regional and boundary patterns, with
side supervision (deep supervision on side responses) in gland histology
images. Our proposed system, deep multichannel side supervision (DMCS),
alleviates heavy feature design due to the use of convolutional neural networks
guided by side supervision. Compared to methods reported in the 2015 MICCAI
Gland Segmentation Challenge, we observe state-of-the-art results based on a
number of evaluation metrics.


title:
Understanding spin parity of $P_c(4450)$ and $Y(4274)$ in a hadronic
  molecular state picture

abstract:
  The hidden-charmed pentaquark $P_c(4450)$ and the charmonium-like state
$Y(4274)$ are investigated as a $\bar{D}^*\Sigma_c$ and a
$D_s\bar{D}_{s0}(2317)$ molecular state, respectively. The spin parities of
these two states cannot be well understood if only S-wave $\bar{D}^*\Sigma_c$
and $D_s\bar{D}_{s0}(2317)$ interactions are considered. In this work, the
interactions are studied in a quasipotential Bethe-Salpeter equation approach
with a partial wave decomposition on spin parity $J^P$, and the contributions
of different partial waves are studied in a two-channel scattering model
including a generating channel and an observation channel. Two poles at
$4447\pm4i$ and $4392\pm46i$ MeV are produced from the $\bar{D}^*\Sigma_c$
interaction coupled with the $J/\psi p$ channel in $3/2^-$ wave and $5/2^+$
wave, respectively. The peak for the $5/2^+$ state has a comparable height as
that of the $3/2^-$ state in the $J/\psi p$ invariant mass spectrum. The
$D_s\bar{D}_{s0}(2317)$ interaction coupled with the $J/\psi\phi$ channel is
studied and a pole at $4275\pm11i$ MeV is produced in $J^{P}=1^{+}$ wave, which
corresponds to P-wave $D_s\bar{D}_{s0}(2317)$ interaction. The pole from S-wave
$D_s\bar{D}_{s0}(2317)$ interaction is far below that from P-wave interaction
even the $J/\psi\phi$ threshold, so cannot be observed in the $J/\psi\phi$
channel. The result suggests that in these cases a state carrying a spin parity
corresponding to P-wave interaction should be taken as seriously as these
carrying a spin parity corresponding to S-wave interaction in the hadronic
molecular state picture.


title: A fast algorithm for identifying Friends-of-Friends halos

abstract:
  We describe a simple and fast algorithm for identifying friends-of-friends
features and prove its correctness. The algorithm avoids unnecessary expensive
neighbor queries, uses minimal memory overhead, and rejects slowdown in high
over-density regions. We define our algorithm formally based on pair
enumeration, a problem that has been heavily studied in fast 2-point
correlation codes and our reference implementation employs a dual KD-tree
correlation function code. We construct features in a hierarchical tree
structure, and use a splay operation to reduce the average cost of identifying
the root of a feature from $O[\log L]$ to $O[1]$ ($L$ is the size of a feature)
without additional memory costs. This reduces the overall time complexity of
merging trees from $O[L\log L]$ to $O[L]$, reducing the number of operations
per splay by orders of magnitude. We next introduce a pruning operation that
skips merge operations between two fully self-connected KD-tree nodes. This
improves the robustness of the algorithm, reducing the number of merge
operations in high density peaks from $O[\delta^2]$ to $O[\delta]$. We show
that for cosmological data set the algorithm eliminates more than half of merge
operations for typically used linking lengths $b \sim 0.2$ (relative to mean
separation). Furthermore, our algorithm is extremely simple and easy to
implement on top of an existing pair enumeration code, reusing the optimization
effort that has been invested in fast correlation function codes.


title: Constraining the Mass of the Photon with Gamma-Ray Bursts

abstract:
  One of the cornerstones of modern physics is Einstein's special relativity,
with its constant speed of light and zero photon mass assumptions. Constraint
on the rest mass m_{\gamma} of photons is a fundamental way to test Einstein's
theory, as well as other essential electromagnetic and particle theories. Since
non-zero photon mass can give rise to frequency-(or energy-) dependent
dispersions, measuring the time delay of photons with different frequencies
emitted from explosive astrophysical events is an important and
model-independent method to put such a constraint. The cosmological gamma-ray
bursts (GRBs), with short time scales, high redshifts as well as broadband
prompt and afterglow emissions, provide an ideal testbed for m_{\gamma}
constraints. In this paper we calculate the upper limits of the photon mass
with GRB early time radio afterglow observations as well as multi-band radio
peaks, thus improve the results of Schaefer (1999) by nearly half an order of
magnitude.


title:
Local feature hierarchy for face recognition across pose and
  illumination

abstract:
  Even though face recognition in frontal view and normal lighting condition
works very well, the performance degenerates sharply in extreme conditions.
Recently there are many work dealing with pose and illumination problems,
respectively. However both the lighting and pose variation will always be
encountered at the same time. Accordingly we propose an end-to-end face
recognition method to deal with pose and illumination simultaneously based on
convolutional networks where the discriminative nonlinear features that are
invariant to pose and illumination are extracted. Normally the global structure
for images taken in different views is quite diverse. Therefore we propose to
use the 1*1 convolutional kernel to extract the local features. Furthermore the
parallel multi-stream multi-layer 1*1 convolution network is developed to
extract multi-hierarchy features. In the experiments we obtained the average
face recognition rate of 96.9% on multiPIE dataset,which improves the
state-of-the-art of face recognition across poses and illumination by 7.5%.
Especially for profile-wise positions, the average recognition rate of our
proposed network is 97.8%, which increases the state-of-the-art recognition
rate by 19%.


title: Spectrum-Power Trading for Energy-Efficient Small Cell

abstract:
  This paper investigates spectrum-power trading be- tween a small cell (SC)
and a macro-cell (MC), where the SC consumes power to serve the macro-cell
users (MUs) in exchange for some bandwidth from the MC. Our goal is to maximize
the system energy efficiency (EE) of the SC while guaranteeing the quality of
service (QoS) of each MU as well as small cell users (SUs). Specifically, given
the minimum data rate requirement and the bandwidth provided by the MC, the SC
jointly optimizes MU selection, bandwidth allocation, and power allocation
while guaranteeing its own minimum required system data rate. The problem is
challenging due to the binary MU selection variables and the fractional form
objective function. We first show that in order to achieve the maximum system
EE, the bandwidth of an MU is shared with at most one SU in the SC. Then, for a
given MU selection, the optimal bandwidth and power allocations are obtained by
exploiting the fractional programming. To perform MU selection, we first
introduce the concept of trading EE. Then, we reveal a sufficient and necessary
condition for serving an MU without considering the total power constraint and
the minimum data rate constraint. Based on this insight, we propose a low
computational complexity MU selection algorithm. Simulation results demonstrate
the effectiveness of the proposed algorithms.


title: Quantum Spin Liquid States

abstract:
  This article is an introductory review of the physics of quantum spin liquid
(QSL) states. Quantum magnetism is a rapidly evolving field, and recent
developments reveal that the ground states and low-energy physics of frustrated
spin systems may develop many exotic behaviors once we leave the regime of
semi-classical approaches. The purpose of this article is to introduce these
developments. The article begins by explaining how semi-classical approaches
fail once quantum mechanics become important and then describes the alternative
approaches for addressing the problem. We discuss mainly spin $1/2$ systems,
and we spend most of our time in this article on one particular set of
plausible spin liquid states in which spins are represented by fermions. These
states are spin-singlet states and may be viewed as an extension of Fermi
liquid states to Mott insulators, and they are usually classified in the
category of so-called $SU(2)$, $U(1)$ or $Z_2$ spin liquid states. We review
the basic theory regarding these states and the extensions of these states to
include the effect of spin-orbit coupling and to higher spin ($S>1/2$) systems.
Two other important approaches with strong influences on the understanding of
spin liquid states are also introduced: (i) matrix product states and projected
entangled pair states and (ii) the Kitaev honeycomb model. Experimental
progress concerning spin liquid states in realistic materials, including
anisotropic triangular lattice systems ($\kappa$-(ET)$_{2}$Cu$_{2}$(CN)$_{3}$
and EtMe$_{3}$Sb[(Pd(dmit)$_{2}$]$_{2}$), kagome lattice systems
(ZnCu$_{3}$(OH)$_{6}$Cl$_{2}$) and hyperkagome lattice systems
(Na$_{4}$Ir$_{3}$O$_{8}$), is reviewed and compared against the corresponding
theories.


title: A nucleus-dependent valence-space approach to nuclear structure

abstract:
  We present a nucleus-dependent valence-space approach for calculating ground
and excited states of nuclei, which generalizes the shell-model in-medium
similarity renormalization group to an ensemble reference with fractionally
filled orbitals. Because the ensemble is used only as a reference, and not to
represent physical states, no symmetry restoration is required. This allows us
to capture 3N forces among valence nucleons with a valence-space Hamiltonian
specifically targeted to each nucleus of interest. Predicted ground-state
energies from carbon through nickel agree with results of other large-space ab
initio methods, generally to the 1\% level. In addition, we show that this new
approach is required in order to obtain convergence for nuclei in the upper $p$
and $sd$ shells. Finally, we address the $1^+$/$3^+$ ground-state inversion
problem in $^{22}\text{Na}$ and $^{46}\text{V}$. This approach extends the
reach of ab initio nuclear structure calculations to essentially all light- and
medium-mass nuclei.


title:
The Impact of Non-Uniform Thermal Structure on the Interpretation of
  Exoplanet Emission Spectra

abstract:
  The determination of atmospheric structure and molecular abundances of
planetary atmospheres via spectroscopy involves direct comparisons between
models and data. While varying in sophistication, most model-spectra
comparisons fundamentally assume "1D" model physics. However, knowledge from
general circulation models and of solar system planets suggests that planetary
atmospheres are inherently "3D" in their structure and composition. We explore
the potential biases resulting from standard "1D" assumptions within a Bayesian
atmospheric retrieval framework. Specifically, we show how the assumption of a
single 1-dimensional thermal profile can bias our interpretation of the thermal
emission spectrum of a hot Jupiter atmosphere that is composed of two thermal
profiles. We retrieve upon spectra of unresolved model planets as observed with
a combination of $HST$ WFC3+$Spitzer$ IRAC as well as $JWST$ under varying
differences in the two thermal profiles. For WFC3+IRAC, there is a
significantly biased estimate of CH$_4$ abundance using a 1D model when the
contrast is 80%. For $JWST$, two thermal profiles are required to adequately
interpret the data and estimate the abundances when contrast is greater than
40%. We also apply this preliminary concept to the recent WFC3+IRAC phase curve
data of the hot Jupiter WASP-43b. We see similar behavior as present in our
simulated data: while the H$_2$O abundance determination is robust, CH$_4$ is
artificially well-constrained to incorrect values under the 1D assumption. Our
work demonstrates the need to evaluate model assumptions in order to extract
meaningful constraints from atmospheric spectra and motivates exploration of
optimal observational setups.


title:
Continuous excitations of the triangular-lattice quantum spin liquid
  YbMgGaO4

abstract:
  A quantum spin liquid (QSL) is an exotic state of matter in which electrons'
spins are quantum entangled over long distances, but do not show
symmetry-breaking magnetic order in the zero-temperature limit. The observation
of QSL states is a central aim of experimental physics, because they host
collective excitations that transcend our knowledge of quantum matter; however,
examples in real materials are scarce. Here, we report neutron-scattering
measurements on YbMgGaO4, a QSL candidate in which Yb3+ ions with effective
spin-1/2 occupy a triangular lattice. Our measurements reveal a continuum of
magnetic excitations - the essential experimental hallmark of a QSL - at very
low temperature (0.06 K). The origin of this peculiar excitation spectrum is a
crucial question, because isotropic nearest-neighbor interactions do not yield
a QSL ground state on the triangular lattice. Using measurements of the
magnetic excitations close to the field-polarized state, we identify
antiferromagnetic next-nearest-neighbor interactions in the presence of planar
anisotropy as key ingredients for QSL formation in YbMgGaO4.


title: Rigged configurations as tropicalizations of loop Schur functions

abstract:
  We conjecture an explicit formula for the image of a tensor product of
Kirillov-Reshetikhin crystals $\bigotimes_{i=1}^m B^{1, s_i}$ under the
Kirillov-Schilling-Shimozono bijection. Our conjectured formula is
piecewise-linear, where the shapes are given by the tropicalization of
cylindric loop Schur functions and the riggings are given by the
tropicalization of loop Schur functions. We prove that our formula changes the
riggings by the correct amount based upon the time evolution of the
corresponding box-ball system. We show that our formula is correct under the
column splitting portion of the Kirillov-Schilling-Shimozono bijection and for
$B^{1, s}$.


title:
The Prescribed Ricci Curvature Problem on Three-Dimensional Unimodular
  Lie Groups

abstract:
  Let G be a three-dimensional unimodular Lie group, and let T be a
left-invariant symmetric (0, 2)-tensor field on G. We provide the necessary and
sufficient conditions on T for the existence of a pair (g, c) consisting of a
left-invariant Riemannian metric g and a positive constant c such that Ric(g) =
cT, where Ric(g) is the Ricci curvature of g. We also discuss the uniqueness of
such pairs and show that, in almost all cases, there exists at most one
positive constant c such that Ric(g) = cT is solvable for some left-invariant
Riemannian metric g.


title: Optimal induced universal graphs for bounded-degree graphs

abstract:
  We show that for any constant $\Delta \ge 2$, there exists a graph $G$ with
$O(n^{\Delta / 2})$ vertices which contains every $n$-vertex graph with maximum
degree $\Delta$ as an induced subgraph. For odd $\Delta$ this significantly
improves the best-known earlier bound of Esperet et al. and is optimal up to a
constant factor, as it is known that any such graph must have at least
$\Omega(n^{\Delta/2})$ vertices.
  Our proof builds on the approach of Alon and Capalbo (SODA 2008) together
with several additional ingredients. The construction of $G$ is explicit and is
based on an appropriately defined composition of high-girth expander graphs.
The proof also provides an efficient deterministic procedure for finding, for
any given input graph $H$ on $n$ vertices with maximum degree at most $\Delta$,
an induced subgraph of $G$ isomorphic to $H$.


title: Compact Star Matter: EoS with New Scaling Law

abstract:
  In this paper we present a simple discussion on the properties of compact
stars using an EoS obtained in effective field theory anchored on scale and
hidden-local symmetric Lagrangian endowed with topology change and a
unequivocal prediction on the deformation of the compact star, that could be
measured in gravitational waves. The objective is not to offer a superior or
improved EoS for compact stars but to confront with a forthcoming astrophysical
observable the given model formulated in what is considered to be consistent
with the premise of QCD. The model so obtained is found to satisfactorily
describe the observation of a 2-solar mass neutron star with a minimum number
of parameters. Specifically the observable we are considering in this paper is
the tidal deformability parameter (equivalently the Love number k_2), which
affects gravitational wave forms at the late period of inspiral stage. The
forthcoming aLIGO and aVirgo observations of gravitational waves from binary
neutron star system will provide a valuable guidance for arriving at a better
understanding of highly compressed baryonic matter.


title: Sequential measurements, disturbance and property testing

abstract:
  We describe two procedures which, given access to one copy of a quantum state
and a sequence of two-outcome measurements, can distinguish between the case
that at least one of the measurements accepts the state with high probability,
and the case that all of the measurements have low probability of acceptance.
The measurements cannot simply be tried in sequence, because early measurements
may disturb the state being tested. One procedure is based on a variant of
Marriott-Watrous amplification. The other procedure is based on the use of a
test for this disturbance, which is applied with low probability. We find a
number of applications. First, quantum query complexity separations in the
property testing model for testing isomorphism of functions under group
actions. We give quantum algorithms for testing isomorphism, linear isomorphism
and affine isomorphism of boolean functions which use exponentially fewer
queries than is possible classically, and a quantum algorithm for testing graph
isomorphism which uses polynomially fewer queries than the best algorithm
known. Second, testing properties of quantum states and operations. We show
that any finite property of quantum states can be tested using a number of
copies of the state which is logarithmic in the size of the property, and give
a test for genuine multipartite entanglement of states of n qubits that uses
O(n) copies of the state. Third, correcting an error in a result of Aaronson on
de-Merlinizing quantum protocols. This result claimed that, in any one-way
quantum communication protocol where two parties are assisted by an
all-powerful but untrusted third party, the third party can be removed with
only a modest increase in the communication cost. We give a corrected proof of
a key technical lemma required for Aaronson's result.


title: Higher level Fock spaces and affine Yangian

abstract:
  We construct actions of the affine Yangian of type A on higher level Fock
spaces by extending known actions of the Yangian of finite type A due to Uglov.
This is a degenerate analog of a result by Takemura-Uglov, which constructed
actions of the quantum toroidal algebra on higher level $q$-deformed Fock
spaces.


title: Scratchpad Sharing in GPUs

abstract:
  GPGPU applications exploit on-chip scratchpad memory available in the
Graphics Processing Units (GPUs) to improve performance. The amount of thread
level parallelism present in the GPU is limited by the number of resident
threads, which in turn depends on the availability of scratchpad memory in its
streaming multiprocessor (SM). Since the scratchpad memory is allocated at
thread block granularity, part of the memory may remain unutilized. In this
paper, we propose architectural and compiler optimizations to improve the
scratchpad utilization. Our approach, Scratchpad Sharing, addresses scratchpad
under-utilization by launching additional thread blocks in each SM. These
thread blocks use unutilized scratchpad and also share scratchpad with other
resident blocks. To improve the performance of scratchpad sharing, we propose
Owner Warp First (OWF) scheduling that schedules warps from the additional
thread blocks effectively. The performance of this approach, however, is
limited by the availability of the shared part of scratchpad.
  We propose compiler optimizations to improve the availability of shared
scratchpad. We describe a scratchpad allocation scheme that helps in allocating
scratchpad variables such that shared scratchpad is accessed for short
duration. We introduce a new instruction, relssp, that when executed, releases
the shared scratchpad. Finally, we describe an analysis for optimal placement
of relssp instructions such that shared scratchpad is released as early as
possible.
  We implemented the hardware changes using the GPGPU-Sim simulator and
implemented the compiler optimizations in Ocelot framework. We evaluated the
effectiveness of our approach on 19 kernels from 3 benchmarks suites: CUDA-SDK,
GPGPU-Sim, and Rodinia. The kernels that underutilize scratchpad memory show an
average improvement of 19% and maximum improvement of 92.17% compared to the
baseline approach.


title: The SensorCloud Protocol: Securely Outsourcing Sensor Data to the Cloud

abstract:
  The increasing deployment of sensor networks, ranging from home networks to
industrial automation, leads to a similarly growing demand for storing and
processing the collected sensor data. To satisfy this demand, the most
promising approach to date is the utilization of the dynamically scalable,
on-demand resources made available via the cloud computing paradigm. However,
prevalent security and privacy concerns are a huge obstacle for the outsourcing
of sensor data to the cloud. Hence, sensor data needs to be secured properly
before it can be outsourced to the cloud. When securing the outsourcing of
sensor data to the cloud, one important challenge lies in the representation of
sensor data and the choice of security measures applied to it. In this paper,
we present the SensorCloud protocol, which enables the representation of sensor
data and actuator commands using JSON as well as the encoding of the object
security mechanisms applied to a given sensor data item. Notably, we solely
utilize mechanisms that have been or currently are in the process of being
standardized at the IETF to aid the wide applicability of our approach.


title: Weakly Supervised Learning of Heterogeneous Concepts in Videos

abstract:
  Typical textual descriptions that accompany online videos are 'weak': i.e.,
they mention the main concepts in the video but not their corresponding
spatio-temporal locations. The concepts in the description are typically
heterogeneous (e.g., objects, persons, actions). Certain location constraints
on these concepts can also be inferred from the description. The goal of this
paper is to present a generalization of the Indian Buffet Process (IBP) that
can (a) systematically incorporate heterogeneous concepts in an integrated
framework, and (b) enforce location constraints, for efficient classification
and localization of the concepts in the videos. Finally, we develop posterior
inference for the proposed formulation using mean-field variational
approximation. Comparative evaluations on the Casablanca and the A2D datasets
show that the proposed approach significantly outperforms other
state-of-the-art techniques: 24% relative improvement for pairwise concept
classification in the Casablanca dataset and 9% relative improvement for
localization in the A2D dataset as compared to the most competitive baseline.


title: Exclusive production observed at the CMS experiment

abstract:
  Exclusive W$^{+}$W$^{-}$ pair production in photon-photon collisions during
the pp runs at 7 and 8 TeV are observed and used to put constraints on the
Anomalous Quartic Gauge Couplings. During the proton lead collisions in
photon-induced vector meson production is observed via the decay of upsilon
into two muons. The slope of the squared p$_{\rm T}$ distribution is measured
to determine the size of the production region.


title:
Chemical differentiation in a prestellar core traces non-uniform
  illumination

abstract:
  Dense cloud cores present chemical differentiation due to the different
distribution of C-bearing and N-bearing molecules, the latter being less
affected by freeze-out onto dust grains. In this letter we show that two
C-bearing molecules, CH$_3$OH and $c$-C$_3$H$_2$, present a strikingly
different (complementary) morphology while showing the same kinematics toward
the prestellar core L1544. After comparing their distribution with large scale
H$_2$ column density N(H$_2$) map from the Herschel satellite, we find that
these two molecules trace different environmental conditions in the surrounding
of L1544: the $c$-C$_3$H$_2$ distribution peaks close to the southern part of
the core, where the surrounding molecular cloud has a N(H$_2$) sharp edge,
while CH$_3$OH mainly traces the northern part of the core, where N(H$_2$)
presents a shallower tail. We conclude that this is evidence of chemical
differentiation driven by different amount of illumination from the
interstellar radiation field: in the South, photochemistry maintains more C
atoms in the gas phase allowing carbon chain (such as $c$-C$_3$H$_2$)
production; in the North, C is mainly locked in CO and methanol traces the zone
where CO starts to freeze out significantly. During the process of cloud
contraction, different gas and ice compositions are thus expected to mix toward
the central regions of the core, where a potential Solar-type system will form.
An alternative view on carbon-chain chemistry in star-forming regions is also
provided.


title: SCOR: Software-defined Constrained Optimal Routing Platform for SDN

abstract:
  A Software-defined Constrained Optimal Routing (SCOR) platform is introduced
as a Northbound interface in SDN architecture. It is based on constraint
programming techniques and is implemented in MiniZinc modelling language. Using
constraint programming techniques in this Northbound interface has created an
efficient tool for implementing complex Quality of Service routing applications
in a few lines of code. The code includes only the problem statement and the
solution is found by a general solver program. A routing framework is
introduced based on SDN's architecture model which uses SCOR as its Northbound
interface and an upper layer of applications implemented in SCOR. Performance
of a few implemented routing applications are evaluated in different network
topologies, network sizes and various number of concurrent flows.


title:
Simulation study of the correlation ($X_{max}^{\mu}$, $N^{\mu}$) in view
  of obtaining information on primary mass of the UHECRs

abstract:
  In this paper we study, using Monte Carlo simulations, the possibility to
discriminate the mass of the Ultra High Energy Cosmic Rays (UHECRs) by
combining information obtained from the maximum $X_{max}^{\mu}$ of the muon
production rate longitudinal profile of Extensive Air Showers (EAS) and the
number of muons, $N^{\mu}$, which hit an array of detectors located in the
horizontal plane. We investigate the sensitivity of the 2D distribution
$X_{max}^{\mu}$ versus $N^{\mu}$ to the mass of the primary particle generating
the air shower. To this purpose we analyze a set of CORSIKA showers induced by
protons and iron nuclei at energies of $10^{19}$eV and $10^{20}$eV, at five
angles of incidence, $0^{\circ}$, $37^{\circ}$, $48^{\circ}$, $55^{\circ}$ and
$60^{\circ}$. Using the simulations we obtain the 2D Probability Functions
$Prob(X_{max}^{\mu},N^{\mu} \ | \ p)$ and $Prob(X_{max}^{\mu},N^{\mu} \ | \
Fe)$ which give the probability that a shower induced by a proton or iron
nucleus contributes to a specific point on the plane ($X_{max}^{\mu}$,
$N^{\mu}$). Then we construct the probability functions $Prob(p\ | \
X_{max}^{\mu},N^{\mu})$ and $Prob(Fe \ | \ X_{max}^{\mu},N^{\mu})$ which give
the probability that a certain point on the plane ($X_{max}^{\mu}$, $N^{\mu}$)
corresponds to a shower initiated by a proton or an iron nucleus, respectively.
Finally, a test of this procedure using a Bayesian approach, confirms an
improved accuracy of the primary mass estimation in comparison with the results
obtained using only the $X_{max}^{\mu}$ distributions.


title: Programming Internet of Things, Service, and People (IoTSP) Applications

abstract:
  Application development for Internet of Things, Service, and People (IoTSP)
is challenging because it involves dealing with the heterogeneity that exists
both in Physical and Internet worlds. Second, stakeholders involved in the
application development have to address issues pertaining to different
life-cycles ranging from design, implementation to deployment. Given these, a
critical challenge is to enable an application development for IoTSP
applications with effectively and efficiently from various stakeholders.
Several approaches to tackling this challenge have been proposed in the fields
of Wireless Sensor Networks (WSN) and Pervasive Computing, regarded as
precursors to the modern day of IoTSP. However, existing approaches only cover
limited subsets of the above mentioned challenges when applied to the IoTSP. In
view of this, we have built upon existing framework and evolved it into a
framework for developing IoTSP applications, with substantial additions and
enhancements in high-level modeling languages and their integration into the
framework, and we present a comparative evaluation results with existing
approaches. This provides the IoTSP community for further benchmarking. The
evaluation is carried out on real devices exhibiting heterogeneity. Our
experimental analysis and results demonstrate that our approach drastically
reduces development effort for IoTSP applications compared to existing
approaches.


title:
Theory for transitions between log and stationary phases: universal laws
  for lag time

abstract:
  Quantitative characterization of bacterial growth has gathered substantial
attention since Monod's pioneering study. Theoretical and experimental work has
uncovered several laws for describing the log growth phase, in which the number
of cells grows exponentially. However, microorganism growth also exhibits lag,
stationary, and death phases under starvation conditions, in which cell growth
is highly suppressed, while quantitative laws or theories for such phases are
underdeveloped. In fact, models commonly adopted for the log phase that consist
of autocatalytic chemical components, including ribosomes, can only show
exponential growth or decay in a population, and phases that halt growth are
not realized. Here, we propose a simple, coarse-grained cell model that
includes inhibitor molecule species in addition to the autocatalytic active
protein. The inhibitor forms a complex with active proteins to suppress the
catalytic process. Depending on the nutrient condition, the model exhibits the
typical transition among the lag, log, stationary, and death phases.
Furthermore, the lag time needed for growth recovery after starvation follows
the square root of the starvation time and is inverse to the maximal growth
rate, in agreement with experimental observations. Moreover, the distribution
of lag time among cells shows an exponential tail, also consistent with
experiments. Our theory further predicts strong dependence of lag time upon the
speed of substrate depletion, which should be examined experimentally. The
present model and theoretical analysis provide universal growth laws beyond the
log phase, offering insight into how cells halt growth without entering the
death phase.


title:
Quantum Coherence as a Witness of Vibronically Hot Energy Transfer in
  Bacterial Reaction Centre

abstract:
  Photosynthetic proteins have evolved over billions of years so as to undergo
optimal energy transfer to the sites of charge separation. Based on
spectroscopically detected quantum coherences, it has been suggested that this
energy transfer is partially wavelike. This conclusion critically depends on
assignment of the coherences to the evolution of excitonic superpositions. Here
we demonstrate for a bacterial reaction centre protein that long-lived coherent
spectroscopic oscillations, which bear canonical signatures of excitonic
superpositions, are essentially vibrational excited state coherences shifted to
the ground state of the chromophores . We show that appearance of these
coherences is brought about by release of electronic energy during the energy
transfer. Our results establish how energy migrates on vibrationally hot
chromophores in the reaction centre and they call for a re-examination of
claims of quantum energy transfer in photosynthesis.


title:
Quantum and Thermal Phase Transitions in a Bosonic Atom-Molecule Mixture
  in a Two-dimensional Optical Lattice

abstract:
  We study the ground state and the thermal phase diagram of a two-species
Bose-Hubbard model, with $U(1)\times \mathbb{Z}_2$ symmetry, describing atoms
and molecules on a 2D optical lattice interacting via a Feshbach resonance.
Using quantum Monte Carlo simulations and mean field theory, we show that the
conversion between the two-species, coherently coupling the atomic and
molecular states, has a crucial impact on the Mott-Superfluid transition and
stabilizes an insulating phase with a gap controlled by the conversion term --
\textit{the Feshbach insulator} -- instead of a standard Mott insulating phase.
Depending on the detuning between atoms and molecules, this model exhibits
three phases: the Feshbach insulator, a molecular condensate coexisting with
non condensed atoms and a mixed atomic-molecular condensate. Employing a
finite-size scaling method, we observe 3D XY (3D Ising) transition when $U(1)$
($ \mathbb{Z}_2$) is broken whereas the transition is first-order when both
$U(1)$ and $ \mathbb{Z}_2$ symmetries are spontaneously broken. The finite
temperature phase diagram is also discussed. The thermal disappearance of the
molecular superfluid leads to a Berezinskii-Kosterlitz-Thouless transition with
unusual universal jump in the superfluid density. The loss of the
quasi-long-range coherence of the mixed atomic and molecular superfluid is more
subtle since only atoms exhibit conventional Berezinskii-Kosterlitz-Thouless
criticality. We also observe a classical first-order transition between the
mixed superfluid and the normal Bose liquid at low temperature.


title: All entangled states can demonstrate non-classical teleportation

abstract:
  Quantum teleportation, the process by which Alice can transfer an unknown
quantum state to Bob by using pre-shared entanglement and classical
communication, is one of the cornerstones of quantum information. The standard
benchmark for certifying quantum teleportation consists in surpassing the
maximum average fidelity between the teleported and the target states that can
be achieved classically. According to this figure of merit, not all entangled
states are useful for teleportation. Here we propose a new benchmark that uses
the full information available in a teleportation experiment and prove that all
entangled states can implement a quantum channel which can not be reproduced
classically. We introduce the idea of non-classical teleportation witness to
certify if a teleportation experiment is genuinely quantum and discuss how to
quantify this phenomenon. Our work provides new techniques for studying
teleportation that can be immediately applied to certify the quality of quantum
technologies.


title:
Network Trimming: A Data-Driven Neuron Pruning Approach towards
  Efficient Deep Architectures

abstract:
  State-of-the-art neural networks are getting deeper and wider. While their
performance increases with the increasing number of layers and neurons, it is
crucial to design an efficient deep architecture in order to reduce
computational and memory costs. Designing an efficient neural network, however,
is labor intensive requiring many experiments, and fine-tunings. In this paper,
we introduce network trimming which iteratively optimizes the network by
pruning unimportant neurons based on analysis of their outputs on a large
dataset. Our algorithm is inspired by an observation that the outputs of a
significant portion of neurons in a large network are mostly zero, regardless
of what inputs the network received. These zero activation neurons are
redundant, and can be removed without affecting the overall accuracy of the
network. After pruning the zero activation neurons, we retrain the network
using the weights before pruning as initialization. We alternate the pruning
and retraining to further reduce zero activations in a network. Our experiments
on the LeNet and VGG-16 show that we can achieve high compression ratio of
parameters without losing or even achieving higher accuracy than the original
network.


title: Majorization results for zeros of orthogonal polynomials

abstract:
  We show that the zeros of consecutive orthogonal polynomials $p_n$ and
$p_{n-1}$ are linearly connected by a doubly stochastic matrix for which the
entries are explicitly computed in terms of Christoffel numbers. We give
similar results for the zeros of $p_n$ and the associated polynomial
$p_{n-1}^{(1)}$ and for the zeros of the polynomial obtained by deleting the
$k$th row and column $(1 \leq k \leq n)$ in the corresponding Jacobi matrix.


title:
Scheduling massively parallel multigrid for multilevel Monte Carlo
  methods

abstract:
  The computational complexity of naive, sampling-based uncertainty
quantification for 3D partial differential equations is extremely high.
Multilevel approaches, such as multilevel Monte Carlo (MLMC), can reduce the
complexity significantly, but to exploit them fully in a parallel environment,
sophisticated scheduling strategies are needed. Often fast algorithms that are
executed in parallel are essential to compute fine level samples in 3D, whereas
to compute individual coarse level samples only moderate numbers of processors
can be employed efficiently. We make use of multiple instances of a parallel
multigrid solver combined with advanced load balancing techniques. In
particular, we optimize the concurrent execution across the three layers of the
MLMC method: parallelization across levels, across samples, and across the
spatial grid. The overall efficiency and performance of these methods will be
analyzed. Here the scalability window of the multigrid solver is revealed as
being essential, i.e., the property that the solution can be computed with a
range of process numbers while maintaining good parallel efficiency. We
evaluate the new scheduling strategies in a series of numerical tests, and
conclude the paper demonstrating large 3D scaling experiments.


title:
A Parallel Trajectory Swapping Wang - Landau Study Of The HP Protein
  Model

abstract:
  The HP model of protein folding, where the chain exists in a free medium, is
investigated using a parallel Monte Carlo scheme based upon Wang-Landau
sampling. Expanding on the work of Wust and Landau by introducing a lesser
known replica -exchange scheme between individual Wang- Landau samplers, the
problem of dynamical trapping (spiking in the density of states) was avoided
and an enhancement in the efficiency of traversing configuration space was
obtained. Highlighting dynamical trapping as an issue for lattice polymer
simulations for increasing lengths is explicitly done here for the first time.
The 1/t scheme is also integrated within this sophisticated Monte Carlo
methodology. A trial move set was developed which includes pull, bond
re-bridging, pivot, kink-flip and a newly invented and implemented fragment
random walk move which allowed rapid exploration of high and low temperature
configurations. A native state search was conducted leading to the attainment
of the native states of the benchmark sequences of 2D50 (-21), 2D60 (-36)and
2D64 (-42), whilst attaining minimum energies close to the native state for
2D85(-52 NATIVE= -53), 2D100a (-47 NATIVE= -48) and 2D100b (-49 NATIVE=-50).
Thermodynamic observables such as the specific heat, internal energy, entropy
and free energy were computed for 2D benchmark sequences at varying
temperatures and folding and unfolding behaviour was investigated. Lattice
polymers with monomeric hydrophobic structure were also studied in the same
manner with the recording of minimum energy values and thermodynamic behaviour.
The native results for the benchmark sequences and lattice polymers were
compared with varying computational methods.


title: NxWLAN: Neighborhood eXtensible WLAN

abstract:
  The increased usage of IEEE 802.11 Wireless LAN (WLAN) in residential
environments by unexperienced users leads to dense, unplanned and chaotic
residential WLAN deployments. Often WLAN Access Points (APs) are deployed
unprofitable in terms of radio coverage and interference conditions. In many
cases the usage of the neighbor's AP would be beneficial as it would provide
better radio coverage in some parts of the residential user's apartment.
Moreover, the network performance can be dramatically improved by balancing the
network load over spatially co-located APs.
  We address this problem by presenting Neighborhood extensible WLAN (NxWLAN)
which enables the secure extension of user's home WLANs through usage of
neighboring APs in residential environments with zero configuration efforts and
without revealing WPA2 encryption keys to untrusted neighbor APs. NxWLAN makes
use of virtualization techniques utilizing neighboring AP by deploying
on-demand a Wireless Termination Point (WTP) on the neighboring AP and by
tunneling encrypted 802.11 traffic to the Virtual Access Point (VAP) residing
on the home AP. This allows the client devices to always authenticate against
the home AP using the WPA2-PSK passphrase already stored in the device without
any additional registration process.
  We implemented NxWLAN prototypically using off-the-shelf hardware and open
source software. As the OpenFlow is not suited for forwarding native 802.11
frames, we built software switch using P4 language. The performance evaluation
in a small 802.11 indoor testbed showed the feasibility of our approach. NxWLAN
is provided to the community as open source.


title: A Variational Model for Joint Motion Estimation and Image Reconstruction

abstract:
  The aim of this paper is to derive and analyze a variational model for the
joint estimation of motion and reconstruction of image sequences, which is
based on a time-continuous Eulerian motion model. The model can be set up in
terms of the continuity equation or the brightness constancy equation. The
analysis in this paper focuses on the latter for robust motion estimation on
sequences of two-dimensional images. We rigorously prove the existence of a
minimizer in a suitable function space setting. Moreover, we discuss the
numerical solution of the model based on primal-dual algorithms and investigate
several examples. Finally, the benefits of our model compared to existing
techniques, such as sequential image reconstruction and motion estimation, are
shown.


title:
Quasiparticle Excitations in the Superconducting State of FeSe Probed by
  Thermal Hall Conductivity in the Vicinity of the BCS-BEC Crossover

abstract:
  There is growing evidence that the superconducting semimetal FeSe ($T_c\sim8$
K) is in the crossover regime between weak-coupling Bardeen-Cooper-Schrieffer
(BCS) and strong-coupling Bose-Einstein-condensate (BEC) limits. We report on
longitudinal and transverse thermal conductivities, $\kappa_{xx}$ and
$\kappa_{xy}$, respectively, in magnetic fields up to 20 T. The field
dependences of $\kappa_{xx}$ and $\kappa_{xy}$ imply that a highly anisotropic
small superconducting gap forms at the electron Fermi-surface pocket whereas a
more isotropic and larger gap forms at the hole pocket. Below $\sim1.0$ K, both
$\kappa_{xx}$ and $\kappa_{xy}$ exhibit distinct anomalies (kinks) at the upper
critical field $H_{c2}$ and at a field $H^*$ slightly below $H_{c2}$. The
analysis of the thermal Hall angle ($\kappa_{xy}/\kappa_{xx}$) indicates a
change of the quasiparticle scattering rate at $H^*$. These results provide
strong support to the previous suggestion that above $H^*$ a distinct
field-induced superconducting phase emerges with an unprecedented large spin
imbalance.


title: City-Identification of Flickr Videos Using Semantic Acoustic Features

abstract:
  City-identification of videos aims to determine the likelihood of a video
belonging to a set of cities. In this paper, we present an approach using only
audio, thus we do not use any additional modality such as images, user-tags or
geo-tags. In this manner, we show to what extent the city-location of videos
correlates to their acoustic information. Success in this task suggests
improvements can be made to complement the other modalities. In particular, we
present a method to compute and use semantic acoustic features to perform
city-identification and the features show semantic evidence of the
identification. The semantic evidence is given by a taxonomy of urban sounds
and expresses the potential presence of these sounds in the city- soundtracks.
We used the MediaEval Placing Task set, which contains Flickr videos labeled by
city. In addition, we used the UrbanSound8K set containing audio clips labeled
by sound- type. Our method improved the state-of-the-art performance and
provides a novel semantic approach to this task


title: Target Directed Event Sequence Generation for Android Applications

abstract:
  Testing is a commonly used approach to ensure the quality of software, of
which model-based testing is a hot topic to test GUI programs such as Android
applications (apps). Existing approaches mainly either dynamically construct a
model that only contains the GUI information, or build a model in the view of
code that may fail to describe the changes of GUI widgets during runtime.
Besides, most of these models do not support back stack that is a particular
mechanism of Android. Therefore, this paper proposes a model LATTE that is
constructed dynamically with consideration of the view information in the
widgets as well as the back stack, to describe the transition between GUI
widgets. We also propose a label set to link the elements of the LATTE model to
program snippets. The user can define a subset of the label set as a target for
the testing requirements that need to cover some specific parts of the code. To
avoid the state explosion problem during model construction, we introduce a
definition "state similarity" to balance the model accuracy and analysis cost.
Based on this model, a target directed test generation method is presented to
generate event sequences to effectively cover the target. The experiments on
several real-world apps indicate that the generated test cases based on LATTE
can reach a high coverage, and with the model we can generate the event
sequences to cover a given target with short event sequences.


title:
Opto-Electronic Characterization of Three Dimensional Topological
  Insulators

abstract:
  We demonstrate that the terahertz/infrared radiation induced photogalvanic
effect, which is sensitive to the surface symmetry and scattering details, can
be applied to study the high frequency conductivity of the surface states in
(Bi1-xSbx)2Te3 based three dimensional (3D) topological insulators (TI). In
particular, measuring the polarization dependence of the photogalvanic current
and scanning with a micrometre sized beam spot across the sample, provides
access to (i) topographical inhomogeneity's in the electronic properties of the
surface states and (ii) the local domain orientation. An important advantage of
the proposed method is that it can be applied to study TIs at room temperature
and even in materials with a high electron density of bulk carriers.


title: Modified LLL algorithm with shifted start column

abstract:
  Multiple-input multiple-output (MIMO) systems are playing an important role
in the recent wireless communication. The complexity of the different systems
models challenge different researches to get a good complexity to performance
balance. Lattices Reduction Techniques and Lenstra-Lenstra-Lovasz (LLL)
algorithm bring more resources to investigate and can contribute to the
complexity reduction purposes. In this paper, we are looking to modify the LLL
algorithm to reduce the computation operations by exploiting the structure of
the upper triangular matrix without big performance degradation. Basically, the
first columns of the upper triangular matrix contain many zeroes, so the
algorithm will perform several operations with very limited income. We are
presenting a performance and complexity study and our proposal show that we can
gain in term of complexity while the performance results remains almost the
same.


title: Twin Primes Via Exceptional Characters

abstract:
  We give an account of the arguments that lead from the assumption of the
existence of exceptional characters to the asymptotics in related ranges for
the counting function of twin primes.


title: Non-leptonic kaon decays at large $N_c$

abstract:
  We study the scaling with the number of colours, $N_c$, of the weak
amplitudes mediating kaon mixing and decay. We evaluate the amplitudes of the
two relevant current-current operators on the lattice for $N_c=3-7$. We
conclude that the subleading $1/N_c$ corrections in $\hat{B}_K$ are small, but
those in the $K \rightarrow \pi\pi$ amplitudes are large and fully
anti-correlated in the $I=0, 2$ isospin channels. We briefly comment on the
implications for the $\Delta I=1/2$ rule.


title: Thermal spin dynamics of yttrium iron garnet

abstract:
  Yttrium Iron Garnet is the prototypical material used to study pure spin
currents. It is a complex material with 20 magnetic atoms in the unit cell.
Almost all theories and experimental analysis approximates this complicated
material to a simple ferromagnet with a single spin wave mode. We use the
method of atomistic spin dynamics to study the temperature evolution of the
full 20 mode exchange spin wave spectrum. Our results show a strong frequency
dependence of the modes in quantitative agreement with neutron scattering
experiments. We find this causes in a reduction in the net spin pumping due to
the thermal occupation of optical modes with the opposite chirality to the FMR
mode.


title: Joining measures for horocycle flows on abelian covers

abstract:
  A celebrated result of Ratner from the eighties says that two horocycle flows
on hyperbolic surfaces of finite area are either the same up to algebraic
change of coordinates, or they have no non-trivial joinings. Recently,
Mohammadi and Oh extended Ratner's theorem to horocycle flows on hyperbolic
surfaces of infinite area but finite genus. In this paper, we present the first
joining classification result of a horocycle flow on a hyperbolic surface of
infinite genus: a $\mathbb{Z}$ or $\mathbb{Z}^2$-cover of a general compact
hyperbolic surface. We also discuss several applications.


title:
Curvature of higher direct image sheaves and its application on
  negative-curvature criterion for the Weil-Petersson metric

abstract:
  We shall show that $q$-semipositivity of the vector bundle $E$ over a
K\"ahler total space $\mathcal X$ implies the Griffiths-semipositivity of the
$q$-th direct image of $\mathcal O(K_{\mathcal X/B}\otimes E)$. As an
application, we shall give a negative-curvature criterion for the generalized
Weil-Petersson metric on the base manifold.


title:
External control strategies for self-propelled particles: optimizing
  navigational efficiency in the presence of limited resources

abstract:
  We experimentally and numerically study the dependence of different
navigation strategies regarding the effectivity of an active particle to reach
a predefined target area. As the only control parameter, we vary the particle's
propulsion velocity depending on its position and orientation relative to the
target site. By introducing different figures of merit, e.g. the time to target
or the total consumed propulsion energy, we are able to quantify and compare
the efficiency of different strategies. Our results suggest, that each strategy
to navigate towards a target, has its strengths and weaknesses and none of them
outperforms the other in all regards. Accordingly, the choice of an ideal
navigation strategy will strongly depend on the specific conditions and the
figure of merit which should be optimized.


title:
OGLE-2012-BLG-0950Lb: The First Planet Mass Measurement from Only
  Microlens Parallax and Lens Flux

abstract:
  We report the discovery of a microlensing planet OGLE-2012-BLG-0950Lb with
the planet/host mass ratio of $q \sim 2 \times 10^{-4}$. A long term distortion
detected in both MOA and OGLE light curve can be explained by the microlens
parallax due to the Earth's orbital motion around the Sun. Although the finite
source effect is not detected, we obtain the lens flux by the high resolution
Keck AO observation. Combining the microlens parallax and the lens flux reveal
the nature of the lens: a planet with mass of $M_{\rm p} = 35^{+17}_{-9}
M_{\oplus}$ is orbiting around a M-dwarf with mass of $M_{\rm host} =
0.56^{+0.12}_{-0.16} M_{\odot}$ with a planet-host projected separation of
$r_{\perp} =2.7^{+0.6}_{-0.7}$ AU located at $D_{\rm L} = 3.0^{+0.8}_{-1.1}$
kpc from us. This is the first mass measurement from only microlens parallax
and the lens flux without the finite source effect. In the coming space
observation-era with $Spitzer$, $K2$, $Euclid$, and $WFIRST$, we expect many
such events for which we will not be able to measure any finite source effect.
This work demonstrates an ability of mass measurements in such events.


title:
Tailoring the topological details of the magnetic skyrmion by the spin
  configuration at the edges

abstract:
  The magnetic skyrmion structure can be formed in the chiral magnets (CMs)
with strong Dzyaloshinskii-Moriya interactions. In this work, we propose a way
of artificially tailoring the topological details of the skyrmion such as its
radial and whirling symmetric patterns by external magnetic fields besieging
the CM slab. As long as the boundary magnetic fields are strong enough to fix
the boundary ferromagnetism, the attained skyrmion profile is stable over time.
The dynamics of spins is considered by numerically solving the non-equilibrium
Landau-Lifshitz-Gilbert equation.


title:
General formalism for Fourier based Wave Front Sensing: application to
  the Pyramid wave front sensors

abstract:
  In this article, we compare a set of Wave Front Sensors (WFS) based on
Fourier filtering technique. In particular, this study explores the "class of
pyramidal WFS" defined as the 4 faces pyramid WFS, all its recent variations
(6, 8 faces, the flattened PWFS, etc.) and also some new WFSs as the flattened
cone WFS or the 3 faces pyramid WFS. In the first part, we describe such a
sensors class thanks to the optical parameters of the Fourier filtering mask
and the modulation parameters. In the second part, we use the unified formalism
to create a set of performance criteria: size of the signal on the detector,
efficiency of incoming flux, sensitivity, linear range and chromaticity. In the
third part, we show the influence of the previous optical and modulation
parameters on these performance criteria. This exhaustive study allows to know
how to optimize the sensor regarding to performance specifications. We show in
particular that the number of faces has influence on the number of pixels
required to do the wave front sensing but no influence on the sensitivity and
linearity range. To modify these criteria, we show that the modulation radius
and the apex angle are much more relevant. Moreover we observe that the time
spent on edges or faces during a modulation cycle allows to adjust the
trade-off between sensitivity and linearity range.


title:
Enhanced VIP Algorithms for Forwarding, Caching, and Congestion Control
  in Named Data Networks

abstract:
  Emerging Information-Centric Networking (ICN) architectures seek to optimally
utilize both bandwidth and storage for efficient content distribution over the
network. The Virtual Interest Packet (VIP) framework has been proposed to
enable joint design of forwarding, caching, and congestion control strategies
within the Named Data Networking (NDN) architecture. While the existing VIP
algorithms exhibit good performance, they are primarily focused on maximizing
network throughput and utility, and do not explicitly consider user delay. In
this paper, we develop a new class of enhanced algorithms for joint dynamic
forwarding, caching and congestion control within the VIP framework. These
enhanced VIP algorithms adaptively stabilize the network and maximize network
utility, while improving the delay performance by intelligently making use of
VIP information beyond one hop. Generalizing Lyapunov drift techniques, we
prove the throughput optimality and characterize the utility-delay tradeoff of
the enhanced VIP algorithms. Numerical experiments demonstrate the superior
performance of the resulting enhanced algorithms for handling Interest Packets
and Data Packets within the actual plane, in terms of low network delay and
high network utility.


title: Relative hard Lefschetz for Soergel bimodules

abstract:
  We prove the relative hard Lefschetz theorem for Soergel bimodules. It
follows that the structure constants of the Kazhdan-Lusztig basis are unimodal.
We explain why the relative hard Lefschetz theorem implies that the tensor
category associated by Lusztig to any 2-sided cell in a Coxeter group is rigid
and pivotal.


title:
Performance and Complexity Analysis of a Reduced Iterations LLL
  Algorithm

abstract:
  Multiple-input multiple-output (MIMO) systems are playing an increasing and
interesting role in the recent wireless communication. The complexity and the
performance of the systems are driving the different studies and researches.
Lattices Reduction techniques bring more resources to investigate the
complexity and performances of such systems. In this paper, we look to modify a
fixed complexity verity of the LLL algorithm to reduce the computation
operations by reducing the number of iterations without important performance
degradation. Our proposal shows that we can achieve a good performance results
while avoiding extra iteration that does not bring much performance.


title: Scalar Quadratic-Gaussian Soft Watermarking Games

abstract:
  We introduce the zero-sum game problem of soft watermarking: The hidden
information (watermark) comes from a continuum and has a perceptual value; the
receiver generates an estimate of the embedded watermark to minimize the
expected estimation error (unlike the conventional watermarking schemes where
both the hidden information and the receiver output are from a discrete finite
set). Applications include embedding a multimedia content into another. We
consider in this paper the scalar Gaussian case and use expected mean-squared
distortion. We formulate the resulting problem as a zero-sum game between the
encoder & receiver pair and the attacker. We show that for the lin- ear
encoder, the optimal attacker is Gaussian-affine, derive the optimal system
parameters in that case, and discuss the corresponding system behavior. We also
provide numerical results to gain further insight and understanding of the
system behavior at optimality.


title: A Cross-Platform Collection of Social Network Profiles

abstract:
  The proliferation of Internet-enabled devices and services has led to a
shifting balance between digital and analogue aspects of our everyday lives. In
the face of this development there is a growing demand for the study of privacy
hazards, the potential for unique user de-anonymization and information leakage
between the various social media profiles many of us maintain. To enable the
structured study of such adversarial effects, this paper presents a dedicated
dataset of cross-platform social network personas (i.e., the same person has
accounts on multiple platforms). The corpus comprises 850 users who generate
predominantly English content. Each user object contains the online footprint
of the same person in three distinct social networks: Twitter, Instagram and
Foursquare. In total, it encompasses over 2.5M tweets, 340k check-ins and 42k
Instagram posts. We describe the collection methodology, characteristics of the
dataset, and how to obtain it. Finally, we discuss a common use case,
cross-platform user identification.


title: Stable Ulrich Bundles on Fano Threefolds with Picard Number 2

abstract:
  In this paper, we consider the existence problem of rank one and two stable
Ulrich bundles on imprimitive Fano 3-folds obtained by blowing-up one of
$\mathbb{P}^{3}$, $Q$ (smooth quadric in $\mathbb{P}^{4}$), $V_{3}$ (smooth
cubic in $\mathbb{P}^{4}$) or $V_{4}$ (complete intersection of two quadrics in
$\mathbb{P}^{5}$) along a smooth irreducible curve. We prove that the only
class which admits Ulrich line bundles is the one obtained by blowing up a
genus 3, degree 6 curve in $\mathbb{P}^{3}$. Also, we prove that there exist
stable rank two Ulrich bundles with $c_{1}=3H$ on a generic member of this
deformation class.


title: Fast and simple decycling and dismantling of networks

abstract:
  Decycling and dismantling of complex networks are underlying many important
applications in network science. Recently these two closely related problems
were tackled by several heuristic algorithms, simple and considerably
sub-optimal, on the one hand, and time-consuming message-passing ones that
evaluate single-node marginal probabilities, on the other hand. In this paper
we propose a simple and extremely fast algorithm, CoreHD, which recursively
removes nodes of the highest degree from the $2$-core of the network. CoreHD
performs much better than all existing simple algorithms. When applied on
real-world networks, it achieves equally good solutions as those obtained by
the state-of-art iterative message-passing algorithms at greatly reduced
computational cost, suggesting that CoreHD should be the algorithm of choice
for many practical purposes.


title: Detection of a very low mass star in an Eclipsing Binary system

abstract:
  We report the detection of a very low mass star (VLMS) companion to the
primary star 1SWASPJ234318.41+295556.5A (J2343+29A), using radial velocity (RV)
measurements from the PARAS (PRL Advanced Radial-velocity Abu-sky Search) high
resolution echelle spectrograph. The periodicity of the single-lined eclipsing
binary (SB1) system, as determined from 20 sets of RV observations from PARAS
and 6 supporting sets of observations from SOPHIE data, is found to be 16.953 d
as against the 4.24 d period reported from SuperWasp photometry. It is likely
that inadequate phase coverage of the transit with SuperWasp photometry led to
the incorrect determination of the period for this system. We derive the
spectral properties of the primary star from the observed stellar spectra: Teff
= 5125 +/- 67 K, [Fe/H] = 0.1 +/- 0.14 and log g = 4.6 +/- 0.14, indicating a
K1V primary. Applying the Torres relation to the derived stellar parameters, we
estimate a primary mass 0.864 +/- 0.097 M_sun and a radius of 0.854 +/- 0.050
R_sun. We combine RV data with SuperWASP photometry to estimate the mass of the
secondary, M_B = 0.098 +/- 0.007 M_sun, and its radius, R_B = 0.127 +/- 0.007
R_sun, with an accuracy of around 7%. Although the observed radius is found to
be consistent with the Baraffe's theoretical models, the uncertainties on the
mass and radius of the secondary reported here are model dependent and should
be used with discretion. Here, we establish this system as a potential
benchmark for the study of VLMS objects, worthy of both photometric follow-up
and the investment of time on high-resolution spectrographs paired with
large-aperture telescopes.


title: Partition of unity interpolation using stable kernel-based techniques

abstract:
  In this paper we propose a new stable and accurate approximation technique
which is extremely effective for interpolating large scattered data sets. The
Partition of Unity (PU) method is performed considering Radial Basis Functions
(RBFs) as local approximants and using locally supported weights. In
particular, the approach consists in computing, for each PU subdomain, a stable
basis. Such technique, taking advantage of the local scheme, leads to a
significant benefit in terms of stability, especially for flat kernels.
Furthermore, an optimized searching procedure is applied to build the local
stable bases, thus rendering the method more efficient.


title: Monotone and convex restrictions of continuous functions

abstract:
  Suppose that $f$ belongs to a suitably defined complete metric space $ {{\cal
C}}^{{\alpha}}$ of H\"older $ {\alpha}$-functions defined on $[0,1]$. We are
interested in whether one can find large (in the sense of Hausdorff, or
lower/upper Minkowski dimension) sets $A {\subset} [0,1]$ such that $f|_{A}$ is
monotone, or convex/concave. Some of our results are about generic functions in
$ {{\cal C}}^{{\alpha}}$ like the following one: we prove that for the generic
$f\in C_{1}^{{\alpha}}[0,1]$, $0\leq {\alpha}<2$ for any $A {\subset} [0,1]$
such that $f|_{A}$ is convex, or concave we have ${\mathrm{dim}}_{\mathrm H}
A\leq \underline{\mathrm{dim}}_M A\leq \max \{0, {\alpha}-1 \}.$ On the other
hand, we also have some results about all functions belonging to a certain
space. For example the previous result is complemented by the following one:
for $1< {\alpha}\leq 2$ for any $f\in C^{{\alpha}}[0,1]$ there is always a set
$A {\subset}[0,1]$ such that ${\mathrm{dim}}_{\mathrm H} A= {\alpha}-1$ and
$f|_{A}$ is convex, or concave on $A$.


title:
Analytical and Simulation Performance of a Typical User in Random
  Cellular Network

abstract:
  Spatial Poisson Point Process (PPP) network, whose Base Stations (BS)s are
distributed according to a Poisson distribution, is currently used as a
accurate model to analyse the performance of a cellular network. Most current
work on evaluation of PPP network in Rayleigh fading channels are usually
assumed that the BSs have fixed transmission power levels and there is only a
Resource Block (RB) or a user in each cell. In this paper, the
Rayleigh-Lognormal fading channels are considered, and it is assumed that each
cell is allocated $N$ Resource Blocks (RB) to serve M users. Furthermore, the
serving and interfering BS of a typical user are assumed to transmit at
different power levels. The closed-form expression for the network coverage
probability for both low and high SNR is derived by using Gauss-Legendre
approximation. The analytical results indicates that the performance of the
typical user is proportional to the transmission power and density of BSs when
SNR<10 dB and {\lambda}<1, and reaches the upper bound when SNR>10 dB or
{\lambda}>1. The variance of Monte Carlo simulation is considered to verify the
stability and accuracy of simulation results.


title: Jet Measurements in Heavy-ion Collisions with CMS

abstract:
  The production of a strongly interacting medium in heavy-ion collisions is
identified through suppression of high transverse momentum jets leading to an
effect known as jet quenching. Detailed measurements of nuclear modification
factors and energy flow of the aforementioned quenched jets are performed with
the CMS detector. These new results extend previous measurements to large
angles with respect to the quenched jets and increase reach in the transverse
momentum range. High statistics pp, pPb and PbPb data taken in 2011-13 are used
in the following analysis. A new data-driven method to estimate the underlying
event contribution from the forward calorimeter energy distribution is employed
which takes into account possible event by event flow modulation. The flavor
dependence of energy loss of jets is studied by tagging heavy flavor b-jets in
these systems.


title:
Almost global existence of weak solutions for the nonlinear
  elastodynamics system for a class of strain energies

abstract:
  The aim of this paper is to prove the existence of almost global weak
solutions for the unsteady nonlinear elastodynamics system in dimension $d=2$
or $3$, for a range of strain energy density functions satisfying some given
assumptions. These assumptions are satisfied by the main strain energies
generally considered. The domain is assumed to be bounded, and mixed boundary
conditions are considered. Our approach is based on a nonlinear parabolic
regularization technique, involving the $p$-Laplace operator. First we prove
the existence of a local-in-time solution for the regularized system, by a
fixed point technique. Next, using an energy estimate, we show that if the data
are small enough, bounded by $\varepsilon >0$, then the maximal time of
existence does not depend on the parabolic regularization parameter, and the
behavior of the lifespan $T$ is $\gtrsim \log (1/\varepsilon)$, defining what
we call here {\it almost global existence}. The solution is thus obtained by
passing this parameter to zero. The key point of our proof is due to recent
nonlinear Korn's inequalities proven by Ciarlet \& Mardare in
$\mathrm{W}^{1,p}$ spaces, for $p>2$.


title: Electric octupole order in bilayer Rashba system

abstract:
  The odd-parity multipole is an emergent degree of freedom, leading to
spontaneous inversion symmetry breaking. The odd-parity multipole order may
occur by forming staggered even-parity multipoles in a unit cell. We focus on a
locally noncentrosymmetric bilayer Rashba system, and study an odd-parity
electric octupole order caused by the antiferro stacking of local electric
quadrupoles. Analyzing the forward scattering model, we show that the electric
octupole order is stabilized by a layer-dependent Rashba spin-orbit coupling.
The roles of the spin-orbit coupling are clarified on the basis of the analytic
formula of multipole susceptibility. The spin texture allowed in the D_2d point
group symmetry and its magnetic response are revealed. Furthermore, we show
that the parity-breaking quantum critical point appears in the magnetic field.
The possible realization of the electric octupole order in bilayer high-T_c
cuprate superconductors is discussed.


title: A Machine learning approach for Shape From Shading

abstract:
  The aim of Shape From Shading (SFS) problem is to reconstruct the relief of
an object from a single gray level image. In this paper we present a new method
to solve the problem of SFS using Machine learning method. Our approach belongs
to Local resolution category. The orientation of each part of the object is
represented by the perpendicular vector to the surface (Normal Vector), this
vector is defined by two angles SLANT and TILT, such as the TILT is the angle
between the normal vector and Z-axis, and the SLANT is the angle between the
the X-axis and the projection of the normal to the plane. The TILT can be
determined from the gray level, the unknown is the SLANT. To calculate the
normal of each part of the surface (pixel) a supervised Machine learning method
has been proposed. This method divided into three steps: the first step is the
preparation of the training data from 3D mathematical functions and synthetic
objects. The second step is the creation of database of examples from 3D
objects (off-line process). The third step is the application of test images
(on-line process). The idea is to find for each pixel of the test image the
most similar element in the examples database using a similarity value.


title: Size consistency in Smoothed Dissipative Particle Dynamics

abstract:
  Smoothed Dissipative Particle Dynamics (SDPD) is a mesoscopic method which
allows to select the level of resolution at which a fluid is simulated. In this
work, we study the consistency of the resulting thermodynamic properties as a
function of the size of the mesoparticles, both at equilibrium and out of
equilibrium. We also propose a reformulation of the SDPD equations in terms of
energy variables. This increases the similarities with Dissipative Particle
Dynamics with Energy conservation and opens the way for a coupling between the
two methods. Finally, we present a numerical scheme for SDPD that ensures the
conservation of the invariants of the dynamics. Numerical simulations
illustrate this approach.


title: The Ho-Zhao Problem

abstract:
  Given a poset $P$, the set, $\Gamma(P)$, of all Scott closed sets ordered by
inclusion forms a complete lattice. A subcategory $\mathbf{C}$ of
$\mathbf{Pos}_d$ (the category of posets and Scott-continuous maps) is said to
be $\Gamma$-faithful if for any posets $P$ and $Q$ in $\mathbf{C}$, $\Gamma(P)
\cong \Gamma(Q)$ implies $P \cong Q$. It is known that the category of all
continuous dcpos and the category of bounded complete dcpos are
$\Gamma$-faithful, while $\mathbf{Pos}_d$ is not. Ho & Zhao (2009) asked
whether the category $\mathbf{DCPO}$ of dcpos is $\Gamma$-faithful. In this
paper, we answer this question in the negative by exhibiting a counterexample.
To achieve this, we introduce a new subcategory of dcpos which is
$\Gamma$-faithful. This subcategory subsumes all currently known
$\Gamma$-faithful subcategories. With this new concept in mind, we construct
the desired counterexample which relies heavily on Johnstone's famous dcpo
which is not sober in its Scott topology.


title:
Probing carrier dynamics in photo-excited graphene with time-resolved
  ARPES

abstract:
  The dynamics of photo-generated electron-hole pairs in solids are dictated by
many-body interactions such as electron-electron and electron-phonon
scattering. Hence, understanding and controlling these scattering channels is
crucial for many optoelectronic applications, ranging from light harvesting to
optical amplification. Here we measure the formation and relaxation of the
photo-generated non-thermal carrier distribution in monolayer graphene with
time- and angle-resolved photoemission spectroscopy. Using sub 10fs pulses we
identify impact ionization as the primary scattering channel, which dominates
the dynamics for the first 25fs after photo-excitation. Auger recombination is
found to set in once the carriers have accumulated at the Dirac point with time
scales between 100 and 250fs, depending on the number of non-thermal carriers.
Our observations help in gauging graphene's potential as a solar cell and
TeraHertz lasing material.


title: Critical zeros of lacunary L-functions

abstract:
  Assuming the existence of a sequence of exceptional discriminants of
quadratic fields, we show that a hundred percent of zeros of the Riemann zeta
function are on the critical line in specific segments. This is a special case
of a more general statement for lacunary $L$-functions.


title: Boundary conditions for Shape from Shading

abstract:
  The Shape From Shading is one of a computer vision field. It studies the 3D
reconstruction of an object from a single grayscale image. The difficulty of
this field can be expressed in the local ambiguity (convex / concave). J.Shi
and Q.Zhu have proposed a method (Global View) to solve the local ambiguity.
This method based on the graph theory and the relationship between the singular
points. In this work we will show that the use of singular points is not
sufficient and requires further information on the object to resolve this
ambiguity.


title: Automatic Bridge Bidding Using Deep Reinforcement Learning

abstract:
  Bridge is among the zero-sum games for which artificial intelligence has not
yet outperformed expert human players. The main difficulty lies in the bidding
phase of bridge, which requires cooperative decision making under partial
information. Existing artificial intelligence systems for bridge bidding rely
on and are thus restricted by human-designed bidding systems or features. In
this work, we propose a pioneering bridge bidding system without the aid of
human domain knowledge. The system is based on a novel deep reinforcement
learning model, which extracts sophisticated features and learns to bid
automatically based on raw card data. The model includes an
upper-confidence-bound algorithm and additional techniques to achieve a balance
between exploration and exploitation. Our experiments validate the promising
performance of our proposed model. In particular, the model advances from
having no knowledge about bidding to achieving superior performance when
compared with a champion-winning computer bridge program that implements a
human-designed bidding system.


title: Free sets for a set-mapping relative to a family of sets

abstract:
  Given a family $\mathcal{F}$ of subsets of $\{1,\ldots,m\}$, we try to
compute the least natural number $n$ such that for every function
$S:[\aleph_n]^{<\omega}\longrightarrow [\aleph_n]^{<\omega}$ there exists a
bijection $u:\{1,\ldots,m\}\longrightarrow Y\subset \aleph_n$ such that
$Su(A)\cap Y \subset u(A)$ for all $A\in\mathcal{F}$.


title: Quadboost: A Scalable Concurrent Quadtree

abstract:
  Building concurrent spatial trees is more complicated than binary search
trees since a space hierarchy should be preserved during modifications. We
present a non-blocking quadtree-quadboost-that supports concurrent insert,
remove, move, and contain operations. To increase its concurrency, we propose a
decoupling approach that separates physical adjustment from logical removal
within the remove operation. In addition, we design a continuous find mechanism
to reduce its search cost. The move operation combines the searches for
different keys together and modifies different positions with atomicity. The
experimental results show that quadboost scales well on a multi-core system
with 32 hardware threads. More than that, it outperforms existing concurrent
trees in retrieving two-dimensional keys with up to 109% improvement when the
number of threads is large. The move operation proved to perform better than
the best-known algorithm, with up to 47%.


title: Two giant outbursts of V 0332+53 observed with INTEGRAL

abstract:
  In July 2015, the high-mass X-ray binary V 0332+53 underwent a giant
outburst, a decade after the previous one. This system hosts a strongly
magnetized neutron star. During the 2004--2005 outburst, an anti-correlation
between the centroid energy of its fundamental cyclotron resonance scattering
features (CRSFs) and the X-ray luminosity was observed. The long ($\approx 100$
d) and bright ($L_{\rm x} \approx 10^{38}$ erg s$^{-1}$) 2015 outburst offered
the opportunity to study during another outburst the unique properties of the
fundamental CRSF and its dependence on the X-ray luminosity. The source was
observed by the INTEGRAL satellite for $\sim 330$ ks. We exploit the spectral
resolution at high energies of the SPectrometer on INTEGRAL (SPI) and the Joint
European X-ray Monitors to characterize its spectral properties, focusing in
particular on the CRSF-luminosity dependence. We complement the data of the
2015 outburst with those collected by SPI in 2004--2005 and left unpublished so
far. We find a highly significant anti-correlation of the centroid energy of
the fundamental CRSF and the $3-100$ keV luminosity of $E_1 \propto
-0.095(8)L_{37}$ keV. This trend is observed for both outbursts. We confirm the
correlation between the width of the fundamental CRSF and the X-ray luminosity
previously found in the JEM-X and IBIS dataset of the 2004--2005 outburst. By
exploiting the RXTE/ASM and Swift/BAT monitoring data we also report on the
detection of a $\sim 34$ d modulation superimposed on the mean profiles and
roughly consistent with the orbital period of the pulsar. We discuss possible
interpretations of such variability.


title:
Asymptotic Near-Minimaxity of the Randomized Shiryaev-Roberts-Pollak
  Change-Point Detection Procedure in Continuous Time

abstract:
  For the classical continuous-time quickest change-point detection problem it
is shown that the randomized Shiryaev-Roberts-Pollak procedure is
asymptotically nearly minimax-optimal (in the sense of Pollak 1985) in the
class of randomized procedures with vanishingly small false alarm risk. The
proof is explicit in that all of the relevant performance characteristics are
found analytically and in a closed form. The rate of convergence to the
(unknown) optimum is elucidated as well. The obtained optimality result is a
one-order improvement of that previously obtained by Burnaev et al. (2009) for
the very same problem.


title:
Multilevel Picard iterations for solving smooth semilinear parabolic
  heat equations

abstract:
  We introduce a new family of numerical algorithms for approximating solutions
of general high-dimensional semilinear parabolic partial differential equations
at single space-time points. The algorithm is obtained through a delicate
combination of the Feynman-Kac and the Bismut-Elworthy-Li formulas, and an
approximate decomposition of the Picard fixed-point iteration with multilevel
accuracy. The algorithm has been tested on a variety of semilinear partial
differential equations that arise in physics and finance, with very
satisfactory results. Analytical tools needed for the analysis of such
algorithms, including a semilinear Feynman-Kac formula, a new class of
semi-norms and their recursive inequalities, are also introduced. They allow us
to prove for semilinear heat equations with gradient-independent nonlinearity
that the computational complexity of the proposed algorithm is bounded by
$O(d\,\varepsilon^{-(4+\delta)})$ for any $\delta \in (0,\infty)$ under
suitable assumptions, where $d\in \mathbb{N}$ is the dimensionality of the
problem and $\varepsilon\in(0,\infty)$ is the prescribed accuracy.


title: Implicit Negative Feedback in Clinical Information Retrieval

abstract:
  In this paper, we reflect on ways to improve the quality of bio-medical
information retrieval by drawing implicit negative feedback from negated
information in noisy natural language search queries. We begin by studying the
extent to which negations occur in clinical texts and quantify their
detrimental effect on retrieval performance. Subsequently, we present a number
of query reformulation and ranking approaches that remedy these shortcomings by
resolving natural language negations. Our experimental results are based on
data collected in the course of the TREC Clinical Decision Support Track and
show consistent improvements compared to state-of-the-art methods. Using our
novel algorithms, we are able to reduce the negative impact of negations on
early precision by up to 65%.


title: Statistics of the zeros of $L$-functions and arithmetic correlations

abstract:
  This thesis determines some of the implications of non-universal and emergent
universal statistics on arithmetic correlations and fluctuations of arithmetic
functions, in particular correlations amongst prime numbers and the variance of
the expected number of prime numbers over short intervals are generalised by
associating these concepts to $L$-functions arising from number theoretic
objects.


title:
$\mu$SR evidence for the U(1) quantum spin liquid ground state in the
  triangular antiferromagnet YbMgGaO$_4$

abstract:
  Muon spin relaxation and rotation ($\mu$SR) experiments on single crystals of
the structurally perfect triangular antiferromagnet YbMgGaO$_4$ indicate the
absence of both static long-range magnetic order and spin freezing down to
0.048 K in zero field. Below 0.4 K, the $\mu^{+}$ spin relaxation rates, which
are proportional to the dynamic correlation function of the Yb$^{3+}$
spins,exhibit temperature-independent plateaus. Same behavior is revealed by
temperature-independent local susceptibilities extracted from the Knight shifts
of the $\mu^{+}$ spin rotation frequencies under a transverse field of 20 Oe.
All these $\mu$SR results unequivocally support the formation of a gapless U(1)
quantum spin liquid ground state in the triangular antiferromagnet YbMgGaO$_4$.


title:
Rapidly rotating neutron stars with a massive scalar field - structure
  and universal relations

abstract:
  We construct rapidly rotating neutron star models in scalar-tensor theories
with a massive scalar field. The fact that the scalar field has nonzero mass
leads to very interesting results since the allowed range of values of the
coupling parameters is significantly broadened. These deviations from pure
general relativity can be very large for values of the parameters that are in
agreement with the observations. The rapid rotation can magnify the differences
several times compared to the static case. The universal relations between the
normalized moment of inertia and quadrupole moment are also investigated both
for the slowly and rapidly rotating cases. The results show that these
relations are still EOS independent up to a large extend and the deviations
from pure general relativity can be large. This places the massive
scalar-tensor theories amongst the few alternative theories of gravity that can
be tested via the universal $I$-Love-$Q$ relations.


title: From Dependence to Causation

abstract:
  Machine learning is the science of discovering statistical dependencies in
data, and the use of those dependencies to perform predictions. During the last
decade, machine learning has made spectacular progress, surpassing human
performance in complex tasks such as object recognition, car driving, and
computer gaming. However, the central role of prediction in machine learning
avoids progress towards general-purpose artificial intelligence. As one way
forward, we argue that causal inference is a fundamental component of human
intelligence, yet ignored by learning algorithms.
  Causal inference is the problem of uncovering the cause-effect relationships
between the variables of a data generating system. Causal structures provide
understanding about how these systems behave under changing, unseen
environments. In turn, knowledge about these causal dynamics allows to answer
"what if" questions, describing the potential responses of the system under
hypothetical manipulations and interventions. Thus, understanding cause and
effect is one step from machine learning towards machine reasoning and machine
intelligence. But, currently available causal inference algorithms operate in
specific regimes, and rely on assumptions that are difficult to verify in
practice.
  This thesis advances the art of causal inference in three different ways.
First, we develop a framework for the study of statistical dependence based on
copulas and random features. Second, we build on this framework to interpret
the problem of causal inference as the task of distribution classification,
yielding a family of novel causal inference algorithms. Third, we discover
causal structures in convolutional neural network features using our
algorithms. The algorithms presented in this thesis are scalable, exhibit
strong theoretical guarantees, and achieve state-of-the-art performance in a
variety of real-world benchmarks.


title: Thermodynamic transport theory of spin waves in ferromagnetic insulators

abstract:
  We use the Boltzmann transport theory in the relaxation time approximation to
describe the thermal transport of spin waves in a ferromagnet. By treating spin
waves as magnon excitations we are able to compute analytically and numerically
the coefficients of the constitutive thermo-magnetic transport equations. As a
main result, we find that the absolute thermo-magnetic power coefficient
$\epsilon_M$, relating the gradient of the potential of the magnetization
current and the gradient of the temperature, in the limit of low temperature
and low field, is a constant $\epsilon_M = -0.6419 \, k_B/\mu_B$. The theory
correctly describes the low-temperature and magnetic-field dependencies of spin
Seebeck experiments. Furthermore, the theory predicts that in the limit of very
low temperatures the spin Peltier coefficient $\Pi_M$, relating the heat and
the magnetization currents, tends to a finite value which depends on the
amplitude of the magnetic field. This indicates the possibility to exploit the
spin Peltier effect as an efficient cooling mechanism in cryogenics.


title: Bayesian estimators of the Gamma distribution

abstract:
  In this paper we introduce two Bayesian estimators for learning the
parameters of the Gamma distribution. The first algorithm uses a well known
unnormalized conjugate prior for the Gamma shape and the second one uses a
non-linear approximation to the likelihood and a prior on the shape that is
conjugate to the approximated likelihood. In both cases use the Laplace
approximation to compute the required expectations. We perform a theoretical
comparison between maximum like- lihood and the presented Bayesian algorithms
that allow us to provide non-informative parameter values for the priors hyper
parameters. We also provide a numerical comparison using synthetic data. The
introduction of these novel Bayesian estimators open the possibility of
including Gamma distributions into more complex Bayesian structures, e.g.
variational Bayesian mixture models.


title:
Baryogenesis in the two doublet and inert singlet extension of the
  Standard Model

abstract:
  We investigate an extension of the Standard Model containing two Higgs
doublets and a singlet scalar field (2HDSM). We show that the model can have a
strongly first-order phase transition and give rise to the observed baryon
asymmetry of the Universe, consistent with all experimental constraints. In
particular, the constraints from the electron and neutron electric dipole
moments are less constraining here than in pure two-Higgs-doublet model (2HDM).
The two-step, first-order transition in 2HDSM, induced by the singlet field,
may lead to strong supercooling and low nucleation temperatures in comparison
with the critical temperature, $T_n \ll T_c$, which can significantly alter the
usual phase-transition pattern in 2HD models with $T_n \approx T_c$.
Furthermore, the singlet field can be the dark matter particle. However, in
models with a strong first-order transition its abundance is typically but a
thousandth of the observed dark matter abundance.


title: Active dynamics of tissue shear flow

abstract:
  We present a hydrodynamic theory to describe shear flows in developing
epithelial tissues. We introduce hydrodynamic fields corresponding to state
properties of constituent cells as well as a contribution to overall tissue
shear flow due to rearrangements in cell network topology. We then construct a
generic linear constitutive equation for the shear rate due to topological
rearrangements and we investigate a novel rheological behaviour resulting from
memory effects in the tissue. We identify two distinct active cellular
processes: generation of active stress in the tissue, and actively driven
topological rearrangements. We find that these two active processes can produce
distinct cellular and tissue shape changes, depending on boundary conditions
applied on the tissue. Our findings have consequences for the understanding of
tissue morphogenesis during development.


title: Camera Elevation Estimation from a Single Mountain Landscape Photograph

abstract:
  This work addresses the problem of camera elevation estimation from a single
photograph in an outdoor environment. We introduce a new benchmark dataset of
one-hundred thousand images with annotated camera elevation called Alps100K. We
propose and experimentally evaluate two automatic data-driven approaches to
camera elevation estimation: one based on convolutional neural networks, the
other on local features. To compare the proposed methods to human performance,
an experiment with 100 subjects is conducted. The experimental results show
that both proposed approaches outperform humans and that the best result is
achieved by their combination.


title:
An Automatic Identification System (AIS) Database for Maritime
  Trajectory Prediction and Data Mining

abstract:
  In recent years, maritime safety and efficiency become more and more
important across the world. Automatic Identification System (AIS) tracks vessel
movement by onboard transceiver and terrestrial and/or satellite base station.
The data collected by AIS contains broadcast kinematic information and static
information. Both of them are useful for anomaly detection and route prediction
which are key techniques in intelligent maritime research area. This paper is
devoted to construct a standard AIS database for maritime trajectory learning,
prediction and data mining. A path prediction algorithm is tested on this AIS
database and the testing results show this database can be used as a
standardized training resource for different trajectory prediction algorithms
and other AIS data mining algorithms.


title: An Introductory Course to Judgment Aggregation

abstract:
  Reaching some form of consensus is often necessary for autonomous agents that
want to coordinate their actions or otherwise engage in joint activities. One
way to reach a consensus is by aggregating individual information, such as
decisions, beliefs, preferences and constraints. Judgment aggregation is a
social choice method, which generalises voting, that studies the aggregation of
individual judgments regarding the truth-value of logically related
propositions. As such, judgment aggregation is applicable for consensus
reaching problems in multi agent systems. As other social choice theory,
judgment aggregation research is abundant with impossibility results. However,
the aim of this tutorial is to give an introduction to the methods of judgment
aggregation, not the impossibility results. In particular, the tutorial will
introduce the basic frameworks that model judgment aggregation problems and
give an overview of the judgment aggregation functions so far developed as well
as their social theoretic and computational complexity properties. The focus of
the tutorial are consensus reaching problems in multi agent systems that can be
modelled as judgment aggregation problems. The desirable properties of a
judgment aggregation method applied to these problems are not necessarily the
same as properties desirable in legal or political contexts, which is
considered to be the native domain of judgment aggregation. After this tutorial
the participants are expected to be able to read and understand judgment
aggregation literature and have a grasp on the state-of-the-art and open
questions in judgment aggregation research of interest to multi agent systems.