title: Dynamical Phonon Laser in Coupled Active-Passive Microresonators

abstract:
  Effective transition between the population-inverted optical eigenmodes of
two coupled microcavities carrying mechanical oscillation realizes a phonon
analogue of optical two-level laser. By providing an approach that linearizes
the dynamical equations of weak nonlinear systems without relying on their
steady states, we study such phonon laser action as a realistic dynamical
process, which exhibits time-dependent stimulated phonon field amplification
especially when one of the cavities is added with optical gain medium. The
approach we present explicitly gives the conditions for the optimum phonon
lasing, and thermal noise is found to be capable of facilitating the phonon
laser action significantly.


title: BLISlab: A Sandbox for Optimizing GEMM

abstract:
  Matrix-matrix multiplication is a fundamental operation of great importance
to scientific computing and, increasingly, machine learning. It is a simple
enough concept to be introduced in a typical high school algebra course yet in
practice important enough that its implementation on computers continues to be
an active research topic. This note describes a set of exercises that use this
operation to illustrate how high performance can be attained on modern CPUs
with hierarchical memories (multiple caches). It does so by building on the
insights that underly the BLAS-like Library Instantiation Software (BLIS)
framework by exposing a simplified "sandbox" that mimics the implementation in
BLIS. As such, it also becomes a vehicle for the "crowd sourcing" of the
optimization of BLIS. We call this set of exercises BLISlab.


title:
Cost-effective description of strong correlation: efficient
  implementations of the perfect quadruples and perfect hextuples models

abstract:
  Novel implementations based on dense tensor storage are presented for the
singlet-reference perfect quadruples (PQ) [Parkhill, Lawler, and Head-Gordon,
J. Chem. Phys. 130, 084101 (2009)] and perfect hextuples (PH) [Parkhill and
Head-Gordon, J. Chem. Phys. 133, 024103 (2010)] models. The methods are
obtained as block decompositions of conventional coupled-cluster theory that
are exact for four electrons in four orbitals (PQ) and six electrons in six
orbitals (PH), but that can also be applied to much larger systems. PQ and PH
have storage requirements that scale as the square, and as the cube of the
number of active electrons, respectively, and exhibit quartic scaling of the
computational effort for large systems. Applications of the new implementations
are presented for full-valence calculations on linear polyenes (C n H n+2 ),
which highlight the excellent computational scaling of the present
implementations that can routinely handle active spaces of hundreds of
electrons. The accuracy of the models is studied in the {\pi} space of the
polyenes, in hydrogen chains (H 50 ), and in the {\pi} space of polyacene
molecules. In all cases, the results compare favorably to density matrix
renormalization group values. With the novel implementation of PQ, active
spaces of 140 electrons in 140 orbitals can be solved in a matter of minutes on
a single core workstation, and the relatively low polynomial scaling means that
very large systems are also accessible using parallel computing.


title:
Coupled dynamics of node and link states in complex networks: A model
  for language competition

abstract:
  Inspired by language competition processes, we present a model of coupled
evolution of node and link states. In particular, we focus on the interplay
between the use of a language and the preference or attitude of the speakers
towards it, which we model, respectively, as a property of the interactions
between speakers (a link state) and as a property of the speakers themselves (a
node state). Furthermore, we restrict our attention to the case of two socially
equivalent languages and to socially inspired network topologies based on a
mechanism of triadic closure. As opposed to most of the previous literature,
where language extinction is an inevitable outcome of the dynamics, we find a
broad range of possible asymptotic configurations, which we classify as: frozen
extinction states, frozen coexistence states, and dynamically trapped
coexistence states. Moreover, metastable coexistence states with very long
survival times and displaying a non-trivial dynamics are found to be abundant.
Interestingly, a system size scaling analysis shows, on the one hand, that the
probability of language extinction vanishes exponentially for increasing system
sizes and, on the other hand, that the time scale of survival of the
non-trivial dynamical metastable states increases linearly with the size of the
system. Thus, non-trivial dynamical coexistence is the only possible outcome
for large enough systems. Finally, we show how this coexistence is
characterized by one of the languages becoming clearly predominant while the
other one becomes increasingly confined to "ghetto-like" structures: small
groups of bilingual speakers arranged in triangles, with a strong preference
for the minority language, and using it for their intra-group interactions
while they switch to the predominant language for communications with the rest
of the population.

categories: physics.soc-ph cond-mat.stat-mech cs.SI nlin.AO


title:
Search for Tetraneutron by Pion Double Charge Exchange Reaction at
  J-PARC

abstract:
  Tetraneutron ($^4n$) has come back in the limelight, because of recent
observation of a candidate resonant state at RIBF. We propose to investigate
the pion double charge exchange (DCX) reaction, i.e. $^4\mathrm{He}({\pi}^- ,
{\pi}^+)$, as an alternative way to populate tetraneutron. An intense ${\pi}^-$
beam with the kinetic energy of ~850 MeV, much higher than that in past
experiments at LAMPF and TRIUMF, will open up a possibility to improve the
experimental sensitivity of the formation cross section, which will be much
smaller than hitherto known DCX cross sections such as $^9\mathrm{Be}({\pi}^-,
{\pi}^+)^9\mathrm{He}\ (g.s.)$.


title:
Observation of Chirality Transition of Quasiparticles at Stacking
  Solitons in Trilayer Graphene

abstract:
  Trilayer graphene (TLG) exhibits rich novel electronic properties and
extraordinary quantum Hall phenomena owning to enhanced electronic interactions
and tunable chirality of its quasiparticles. Here, we report direct observation
of chirality transition of quasiparticles at stacking solitons of TLG via
spatial-resolved Landau level spectroscopy. The one-dimensional stacking
solitons with width of the order of 10 nm separate adjacent Bernal-stacked TLG
and rhombohedral-stacked TLG. By using high field tunneling spectra of scanning
tunneling microscopy, we measured Landau quantization in both the
Bernal-stacked TLG and the rhombohedral-stacked TLG and, importantly, we
observed evolution of quasiparticles between the chiral degree l = 1&2 and l =
3 across the stacking domain wall solitons. Our experiment indicates that such
a chirality transition occurs smoothly, accompanying the transition of the
stacking orders of TLG, around the domain wall solitons. This result
demonstrates the important and hitherto neglected relationship between the
crystallographic stacking order and the chirality of quasiparticles in graphene
systems.


title:
All Fingers are not Equal: Intensity of References in Scientific
  Articles

abstract:
  Research accomplishment is usually measured by considering all citations with
equal importance, thus ignoring the wide variety of purposes an article is
being cited for. Here, we posit that measuring the intensity of a reference is
crucial not only to perceive better understanding of research endeavor, but
also to improve the quality of citation-based applications. To this end, we
collect a rich annotated dataset with references labeled by the intensity, and
propose a novel graph-based semi-supervised model, GraLap to label the
intensity of references. Experiments with AAN datasets show a significant
improvement compared to the baselines to achieve the true labels of the
references (46% better correlation). Finally, we provide four applications to
demonstrate how the knowledge of reference intensity leads to design better
real-world applications.


title:
A potential theoretic approach to Tanaka formula for asymmetric L\'evy
  processes

abstract:
  In this paper, we shall introduce the Tanaka formula from viewpoint of the
Doob-Meyer decomposition. For symmetric L\'evy processes, if the local time
exists, Salminen and Yor (2007) obtained the Tanaka formula by using the
potential theoretic techniques. On the other hand, for asymmetric stable
processes with index $\alpha \in (1,2)$, we studied the Tanaka formula by using
It\^o's stochastic calculus and the Fourier analysis. In this paper, we study
the Tanaka formula for asymmetric L\'evy processes via the potential theoretic
approach. We give several examples for important processes. Our approach also
gives the invariant excessive function with respect to the killed process in
the case of asymmetric L\'evy processes and it generalized the result in Yano
(2013).


title: Black Hole Ringing, Quasinormal Modes, and Light Rings

abstract:
  Modelling of gravitational waves from binary black hole inspiral has played
an important role in the recent observations of such signals. The late-stage
ringdown phase of the gravitational waveform is often associated with the null
particle orbit ("light ring") of the black hole spacetime. With simple models
we show that this link between the light ring and spacetime ringing is based
more on the history of specific models than on an actual constraining
relationship. We also show, in particular, that a better understanding of the
dissociation of the two may be relevant to the astrophysically interesting case
of rotating (Kerr) black holes.


title:
Gaussian complex zeros on the hole event: the emergence of a forbidden
  region

abstract:
  We consider the Gaussian Entire Function (GEF) whose Taylor coefficients are
independent complex-valued Gaussian variables, and the variance of the kth
coefficient is 1/k!. This random Taylor series is distinguished by the
invariance of its zero set with respect to the isometries of the complex plane.
  We show that the law of the zero set, conditioned on the GEF having no zeros
in a disk of radius r, and properly normalized, converges to an explicit
limiting Radon measure in the plane, as r goes to infinity. A remarkable
feature of this limiting measure is the existence of a large 'forbidden region'
between a singular part supported on the boundary of the (scaled) hole and the
equilibrium measure far from the hole.


title: A Novel Progressive Learning Technique for Multi-class Classification

abstract:
  In this paper, a progressive learning technique for multi-class
classification is proposed. This newly developed learning technique is
independent of the number of class constraints and it can learn new classes
while still retaining the knowledge of previous classes. Whenever a new class
(non-native to the knowledge learnt thus far) is encountered, the neural
network structure gets remodeled automatically by facilitating new neurons and
interconnections, and the parameters are calculated in such a way that it
retains the knowledge learnt thus far. This technique is suitable for
real-world applications where the number of classes is often unknown and online
learning from real-time data is required. The consistency and the complexity of
the progressive learning technique are analyzed. Several standard datasets are
used to evaluate the performance of the developed technique. A comparative
study shows that the developed technique is superior.


title:
A novel online multi-label classifier for high-speed streaming data
  applications

abstract:
  In this paper, a high-speed online neural network classifier based on extreme
learning machines for multi-label classification is proposed. In multi-label
classification, each of the input data sample belongs to one or more than one
of the target labels. The traditional binary and multi-class classification
where each sample belongs to only one target class forms the subset of
multi-label classification. Multi-label classification problems are far more
complex than binary and multi-class classification problems, as both the number
of target labels and each of the target labels corresponding to each of the
input samples are to be identified. The proposed work exploits the high-speed
nature of the extreme learning machines to achieve real-time multi-label
classification of streaming data. A new threshold-based online sequential
learning algorithm is proposed for high speed and streaming data classification
of multi-label problems. The proposed method is experimented with six different
datasets from different application domains such as multimedia, text, and
biology. The hamming loss, accuracy, training time and testing time of the
proposed technique is compared with nine different state-of-the-art methods.
Experimental studies shows that the proposed technique outperforms the existing
multi-label classifiers in terms of performance and speed.


title:
Review of the theoretical description of time-resolved angle-resolved
  photoemission spectroscopy in electron-phonon mediated superconductors

abstract:
  We review recent work on the theory for pump/probe photoemission spectroscopy
of electron-phonon mediated superconductors in both the normal and the
superconducting states. We describe the formal developments that allow one to
solve the Migdal-Eliashberg theory in nonequilibrium for an ultrashort laser
pumping field, and explore the solutions which illustrate the relaxation as
energy is transferred from electrons to phonons. We focus on exact results
emanating from sum rules and approximate numerical results which describe rules
of thumb for relaxation processes. In addition, in the superconducting state,
we describe how Higg's oscillations can be excited due to the nonlinear
coupling with the electric field and how pumping the system can enhance
superconductivity.


title: Statistics on bargraphs viewed as cornerless Motzkin paths

abstract:
  A bargraph is a self-avoiding lattice path with steps $U=(0,1)$, $H=(1,0)$
and $D=(0,-1)$ that starts at the origin and ends on the $x$-axis, and stays
strictly above the $x$-axis everywhere except at the endpoints. Bargraphs have
been studied as a special class of convex polyominoes, and enumerated using the
so-called wasp-waist decomposition of Bousquet-M\'elou and Rechnitzer. In this
paper we note that there is a trivial bijection between bargraphs and Motzkin
paths without peaks or valleys. This allows us to use the recursive structure
of Motzkin paths to enumerate bargraphs with respect to several statistics,
finding simpler derivations of known results and obtaining many new ones. We
also count symmetric bargraphs and alternating bargraphs. In some cases we
construct statistic-preserving bijections between different combinatorial
objects, proving some identities that we encounter along the way.


title: Quadratic Generated Normal Domains From Graphs

abstract:
  Determining whether an arbitrary subring $R$ of $k[x_1^{\pm 1},\dots,
x_n^{\pm 1}]$ is a normal domain is, in general, a nontrivial problem, even in
the special case of a monomial generated domain. In this paper, we provide a
complete characterization of the normality and normalizations of
quadratic-monomial generated domains. For a quadratic-monomial generated domain
$R$, we develop a combinatorial structure that assigns, to each quadratic
monomial of the ring, an edge in a mixed signed, directed graph $G$, i.e., a
graph with signed edges and directed edges. We classify the normality and the
normalizations of such rings in terms of a generalization of the combinatorial
odd cycle condition on $G$.


title: Attribute Truss Community Search

abstract:
  Recently, community search over graphs has attracted significant attention
and many algorithms have been developed for finding dense subgraphs from large
graphs that contain given query nodes. In applications such as analysis of
protein protein interaction (PPI) networks, citation graphs, and collaboration
networks, nodes tend to have attributes. Unfortunately, previously developed
community search algorithms ignore these attributes and result in communities
with poor cohesion w.r.t. their node attributes. In this paper, we study the
problem of attribute-driven community search, that is, given an undirected
graph $G$ where nodes are associated with attributes, and an input query $Q$
consisting of nodes $V_q$ and attributes $W_q$, find the communities containing
$V_q$, in which most community members are densely inter-connected and have
similar attributes.
  We formulate our problem of finding attributed truss communities (ATC), as
finding all connected and close k-truss subgraphs containing $V_q$, that are
locally maximal and have the largest attribute relevance score among such
subgraphs. We design a novel attribute relevance score function and establish
its desirable properties. The problem is shown to be NP-hard. However, we
develop an efficient greedy algorithmic framework, which finds a maximal
$k$-truss containing $V_q$, and then iteratively removes the nodes with the
least popular attributes and shrinks the graph so as to satisfy community
constraints. We also build an elegant index to maintain the known $k$-truss
structure and attribute information, and propose efficient query processing
algorithms. Extensive experiments on large real-world networks with
ground-truth communities shows the efficiency and effectiveness of our proposed
methods.


title: Approximate Bisimulation and Discretization of Hybrid CSP

abstract:
  Hybrid Communicating Sequential Processes (HCSP) is a powerful formal
modeling language for hybrid systems, which is an extension of CSP by
introducing differential equations for modeling continuous evolution and
interrupts for modeling interaction between continuous and discrete dynamics.
In this paper, we investigate the semantic foundation for HCSP from an
operational point of view by proposing notion of approximate bisimulation,
which provides an appropriate criterion to characterize the equivalence between
HCSP processes with continuous and discrete behaviour. We give an algorithm to
determine whether two HCSP processes are approximately bisimilar. In addition,
based on that, we propose an approach on how to discretize HCSP, i.e., given an
HCSP process A, we construct another HCSP process B which does not contain any
continuous dynamics such that A and B are approximately bisimilar with given
precisions. This provides a rigorous way to transform a verified control model
to a correct program model, which fills the gap in the design of embedded
systems.


title: Representation of convex geometries by circles on a plane

abstract:
  Convex geometries are closure systems satisfying the anti-exchange axiom.
Every finite convex geometry can be embedded into a convex geometry of finitely
many points in an n-dimensional space equipped with a convex hull operator, by
the result of K. Kashiwabara, M.Nakamura and Y.Okamoto (2005). Allowing circles
rather than points, as was suggested by G.Cz\'edli (2014), may presumably
reduce the dimension for representation. This paper introduces a property, the
Weak $2\times 3$-Carousel rule, which is satisfied by all convex geometries of
circles on a plane, and we show that it does not hold in all finite convex
geometries. This raises a number of representation problems for convex
geometries, which may allow us to better understand the properties of Euclidean
space related to its dimension.


title:
From geometry to geology: An invitation to mathematical pluralism
  through the phenomenon of independence

abstract:
  This paper explores how a pluralist view can arise in a natural way out of
the day-to-day practice of modern set theory. By contrast, the widely accepted
orthodox view is that there is an ultimate universe of sets $V$, and it is in
this universe that mathematics takes place. From this view, the purpose of set
theory is "learning the truth about $V$." It has become apparent, however, that
the phenomenon of independence - those questions left unresolved by the axioms
- holds a central place in the investigation. This paper introduces the notion
of independence, explores the primary tool ("soundness") for establishing
independence results, and shows how a plurality of models arises through the
investigation of this phenomenon. Building on a familiar example from Euclidean
geometry, a template for independence proofs is established. Applying this
template in the domain of set theory leads to a consideration of forcing, the
tool par excellence for constructing universes of sets. Fifty years of forcing
has resulted in a profusion of universes exhibiting a wide variety of
characteristics - a multiverse of set theories. Direct study of this multiverse
presents technical challenges due to its second-order nature. Nonetheless,
there are certain nice "local neighborhoods" of the multiverse that are
amenable to first-order analysis, and \emph{set-theoretic geology} studies just
such a neighborhood, the collection of grounds of a given universe $V$ of set
theory. I will explore some of the properties of this collection, touching on
major concepts, open questions, and recent developments.


title: Articulation Points in Complex Networks

abstract:
  An articulation point in a network is a node whose removal disconnects the
network. Those nodes play key roles in ensuring connectivity of many real-world
networks, from infrastructure networks to protein interaction networks and
terrorist communication networks. Despite their fundamental importance, a
general framework of studying articulation points in complex networks is
lacking. Here we develop analytical tools to study key issues pertinent to
articulation points, e.g. the expected number of them and the network
vulnerability against their removal, in an arbitrary complex network. We find
that a greedy articulation point removal process provides us a novel
perspective on the organizational principles of complex networks. Moreover,
this process is associated with two fundamentally different types of
percolation transitions with a rich phase diagram. Our results shed light on
the design of more resilient infrastructure networks and the effective
destruction of terrorist communication networks.


title: Lech's conjecture in dimension three

abstract:
  Let $(R,m)\to (S,n)$ be a flat local extension of local rings. Lech
conjectured in 1960 that there should be a general inequality $e(R)\leq e(S)$
on the Hilbert-Samuel multiplicities. This conjecture is known when the base
ring $R$ has dimension less than or equal to two, and remains open in higher
dimensions. In this paper, we prove Lech's conjecture in dimension three when
$R$ has equal characteristic. In higher dimension, our method yields
substantial partial estimate: $e(R)\leq (d!/2^d)\cdot e(S)$ where $d=\dim R\geq
4$, in equal characteristic.


title:
Image segmentation based on histogram of depth and an application in
  driver distraction detection

abstract:
  This study proposes an approach to segment human object from a depth image
based on histogram of depth values. The region of interest is first extracted
based on a predefined threshold for histogram regions. A region growing process
is then employed to separate multiple human bodies with the same depth
interval. Our contribution is the identification of an adaptive growth
threshold based on the detected histogram region. To demonstrate the
effectiveness of the proposed method, an application in driver distraction
detection was introduced. After successfully extracting the driver's position
inside the car, we came up with a simple solution to track the driver motion.
With the analysis of the difference between initial and current frame, a change
of cluster position or depth value in the interested region, which cross the
preset threshold, is considered as a distracted activity. The experiment
results demonstrated the success of the algorithm in detecting typical
distracted driving activities such as using phone for calling or texting,
adjusting internal devices and drinking in real time.


title:
Eventful Evolution of Giant Molecular Clouds in Dynamically Evolving
  Spiral Arms

abstract:
  The formation and evolution of giant molecular clouds (GMCs) in spiral
galaxies have been investigated in the traditional framework of the combined
quasi-stationary density wave and galactic shock model. However, our
understanding of the dynamics of spiral arms is changing from the traditional
spiral model to a dynamically evolving spiral model. In this study, we
investigate the structure and evolution of GMCs in a dynamically evolving
spiral arm using a three-dimensional N-body/hydrodynamic simulation of a barred
spiral galaxy at parsec-scale resolution. This simulation incorporated
self-gravity, molecular hydrogen formation, radiative cooling, heating due to
interstellar far-ultraviolet radiation, and stellar feedback by both HII
regions and Type-II supernovae. In contrast to a simple expectation based on
the traditional spiral model, the GMCs exhibited no systematic evolutionary
sequence across the spiral arm. Our simulation showed that the GMCs behaved as
highly dynamic objects with eventful lives involving collisional build-up,
collision-induced star formation, and destruction via stellar feedback. The GMC
lifetimes were predicted to be short, only a few tens of millions years. We
also found that, at least at the resolutions and with the feedback models used
in this study, most of the GMCs without HII regions were collapsing, but half
of the GMCs with HII regions were expanding owing to the HII-region feedback
from stars within them. Our results support the dynamic and feedback-regulated
GMC evolution scenario. Although the simulated GMCs were converging rather than
virial equilibrium, they followed the observed scaling relationship well. We
also analysed the effects of galactic tides and external pressure on GMC
evolution and suggested that GMCs cannot be regarded as isolated systems since
their evolution in disc galaxies is complicated because of these environmental
effects.


title:
SpECTRE: A Task-based Discontinuous Galerkin Code for Relativistic
  Astrophysics

abstract:
  We introduce a new relativistic astrophysics code, SpECTRE, that combines a
discontinuous Galerkin method with a task-based parallelism model. SpECTRE's
goal is to achieve more accurate solutions for challenging relativistic
astrophysics problems such as core-collapse supernovae and binary neutron star
mergers. The robustness of the discontinuous Galerkin method allows for the use
of high-resolution shock capturing methods in regions where (relativistic)
shocks are found, while exploiting high-order accuracy in smooth regions. A
task-based parallelism model allows efficient use of the largest supercomputers
for problems with a heterogeneous workload over disparate spatial and temporal
scales. We argue that the locality and algorithmic structure of discontinuous
Galerkin methods will exhibit good scalability within a task-based parallelism
framework. We demonstrate the code on a wide variety of challenging benchmark
problems in (non)-relativistic (magneto)-hydrodynamics. We demonstrate the
code's scalability including its strong scaling on the NCSA Blue Waters
supercomputer up to the machine's full capacity of 22,380 nodes using 671,400
threads.


title: Design and Implementation of A Network Security Management System

abstract:
  In recent years, the emerged network worms and attacks have distributive
characteristic, which can spread globally in a very short time. Security
management crossing network to co-defense network-wide attacks and improve
efficiency of security administration is urgently needed. This paper proposes a
hierarchical distributed network security management system (HD-NSMS), which
can centrally manage security across networks. First describes the system in
macrostructure and microstructure; then discusses three key problems when
building HD-NSMS: device model, alert mechanism and emergency response
mechanism; at last, describes the implementation of HD-NSMS. The paper is
valuable for implementing NSMS in that it derives from a practical network
security management system (NSMS).


title:
Suspicious-Taint-Based Access Control for Protecting OS from Network
  Attacks

abstract:
  Today, security threats to operating systems largely come from network.
Traditional discretionary access control mechanism alone can hardly defeat
them. Although traditional mandatory access control models can effectively
protect the security of OS, they have problems of being incompatible with
application software and complex in administration. In this paper, we propose a
new model, Suspicious-Taint-Based Access Control (STBAC) model, for defeating
network attacks while being compatible, simple and maintaining good system
performance. STBAC regards the processes using Non-Trustable-Communications as
the starting points of suspicious taint, traces the activities of the
suspiciously tainted processes by taint rules, and forbids the suspiciously
tainted processes to illegally access vital resources by protection rules. Even
in the cases when some privileged processes are subverted, STBAC can still
protect vital resources from being compromised by the intruder. We implemented
the model in the Linux kernel and evaluated it through experiments. The
evaluation showed that STBAC could protect vital resources effectively without
significant impact on compatibility and performance.


title: Baryon effects on void statistics in the EAGLE simulation

abstract:
  Cosmic voids are promising tools for cosmological tests due to their
sensitivity to dark energy, modified gravity and alternative cosmological
scenarios. Most previous studies in the literature of void properties use
cosmological N-body simulations of dark matter (DM) particles that ignore the
potential effect of baryonic physics. Using a spherical underdensity finder, we
analyse voids using the mass field and subhalo tracers in the EAGLE
simulations, which follow the evolution of galaxies in a $\rm{\Lambda}$ cold
dark matter Universe with state-of-the-art subgrid models for baryonic
processes in a $(100 \rm{cMpc})^3$ volume. We study the effect of baryons on
void statistics by comparing results with DM-only simulations that use the same
initial conditions as EAGLE. When identifying voids in the mass field, we find
that a DM-only simulation produces 24 per cent more voids than a hydrodynamical
one due to the action of galaxy feedback polluting void regions with hot gas,
specially for small voids with $r_{\rm{void}} \le 10\ \rm{Mpc}$. We find that
the way in which galaxy tracers are selected has a strong impact on the
inferred void properties. Voids identified using galaxies selected by their
stellar mass are larger and have cuspier density profiles than those identified
by galaxies selected by their total mass. Overall, baryons have minimal effects
on void statistics, as void properties are well captured by DM-only
simulations, but it is important to account for how galaxies populate DM haloes
to estimate the observational effect of different cosmological models on the
statistics of voids.


title: Approximate Kerr-Newman-like Metric with Quadrupole

abstract:
  The Kerr metric is known to present issues when trying to find an interior
solution. In this work we continue in our efforts to construct a more realistic
exterior metric for astrophysical objects. A new approximate metric
representing the spacetime of a charged, rotating and slightly-deformed body is
obtained by perturbing the Kerr-Newman metric to include the mass-quadrupole
and quadrupole-quadrupole orders. It has a simple form, because is
Kerr-Newman-like. Its post-linear form without charge coincides with
post-linear quadrupole-quadrupole metrics already found.


title:
Neutron tomography of magnetic Majorana fermions in a proximate quantum
  spin liquid

abstract:
  Quantum matter provides an effective vacuum out of which arise emergent
particles not corresponding to any experimentally detected elementary particle.
Topological quantum materials in particular have become a focus of intense
research in part because of the remarkable possibility to realize Majorana
fermions, with their potential for new, decoherence-free quantum computing
architectures. In this paper we undertake a study on high-quality single
crystal of $\alpha-RuCl_3$ which has been identified as a material realizing a
proximate Kitaev state, a topological quantum state with magnetic Majorana
fermions. Four-dimensional tomographic reconstruction of dynamical correlations
measured using neutrons is uniquely powerful for probing such magnetic states.
We discover unusual signals, including an unprecedented column of scattering
over a large energy interval around the Brillouin zone center which is
remarkably stable with temperature. This is straightforwardly accounted for in
terms of the Majorana excitations present in Kitaev's topological quantum spin
liquid. Other, more delicate, features in the scattering can be transparently
associated with perturbations to an ideal model. This opens a window on
emergent magnetic Majorana fermions in correlated materials.


title:
A Likelihood Ratio Detector for Identifying Within-Perimeter Computer
  Network Attacks

abstract:
  The rapid detection of attackers within firewalls of enterprise computer net-
works is of paramount importance. Anomaly detectors address this problem by
quantifying deviations from baseline statistical models of normal network
behav- ior and signaling an intrusion when the observed data deviates
significantly from the baseline model. However, many anomaly detectors do not
take into account plausible attacker behavior. As a result, anomaly detectors
are prone to a large number of false positives due to unusual but benign
activity. This paper first in- troduces a stochastic model of attacker behavior
which is motivated by real world attacker traversal. Then, we develop a
likelihood ratio detector that compares the probability of observed network
behavior under normal conditions against the case when an attacker has possibly
compromised a subset of hosts within the network. Since the likelihood ratio
detector requires integrating over the time each host be- comes compromised, we
illustrate how to use Monte Carlo methods to compute the requisite integral. We
then present Receiver Operating Characteristic (ROC) curves for various network
parameterizations that show for any rate of true posi- tives, the rate of false
positives for the likelihood ratio detector is no higher than that of a simple
anomaly detector and is often lower. We conclude by demon- strating the
superiority of the proposed likelihood ratio detector when the network
topologies and parameterizations are extracted from real-world networks.


title:
Influence of interstitial Fe to the phase diagram of
  Fe$_{1+y}$Te$_{1-x}$Se$_x$ single crystals

abstract:
  Superconductivity (SC) with the suppression of long-range antiferromagnetic
(AFM) order is observed in the parent compounds of both iron-based and cuprate
superconductors. The AFM wave vectors are bicollinear ($\pi$, 0) in the parent
compound FeTe different from the collinear AFM order ($\pi$, $\pi$) in most
iron pnictides. Study of the phase diagram of Fe$_{1+y}$Te$_{1-x}$Se$_x$ is the
most direct way to investigate the competition between bicollinear AFM and SC.
However, presence of interstitial Fe affects both magnetism and SC of
Fe$_{1+y}$Te$_{1-x}$Se$_x$, which hinders the establishment of the real phase
diagram. Here, we report the comparison of doping-temperature ($x$-$T$) phase
diagrams for Fe$_{1+y}$Te$_{1-x}$Se$_x$ (0 $\leq$ $x$ $\leq$ 0.43) single
crystals before and after removing interstitial Fe. Without interstitial Fe,
the AFM state survives only for $x$ $<$ 0.05, and bulk SC emerges from $x$ =
0.05, and does not coexist with the AFM state. The previously reported spin
glass state, and the coexistence of AFM and SC may be originated from the
effect of the interstitial Fe. The phase diagram of Fe$_{1+y}$Te$_{1-x}$Se$_x$
is found to be similar to the case of the "1111" system such as
LaFeAsO$_{1-x}$F$_x$, and is different from that of the "122" system.


title: Parasitic Photon-Pair Suppression via Photonic Stop-Band Engineering

abstract:
  We calculate that an appropriate modification of the field associated with
only one of the photons of a photon pair can suppress generation of the pair
entirely. From this general result, we develop a method for suppressing the
generation of undesired photon pairs utilizing photonic stop bands. For a
third-order nonlinear optical source of frequency-degenerate photons we
calculate the modified frequency spectrum (joint spectral intensity) and show a
significant increase in a standard metric, the coincidence to accidental ratio.
These results open a new avenue for photon-pair frequency correlation
engineering.


title: A mathematical consideration of vortex thinning in 2D turbulence

abstract:
  In two dimensional turbulence, vortex thinning process is one of the
attractive mechanism to explain inverse energy cascade in terms of vortex
dynamics. By direct numerical simulation to the two-dimensional Navier-Stokes
equations with small-scale forcing and large-scale damping, Xiao-Wan-Chen-Eyink
(2009) found an evidence that inverse energy cascade may proceed with the
vortex thinning mechanism. The aim of this paper is to analyze the
vortex-thinning mechanism mathematically (using the incompressible Euler
equations), and give a mathematical evidence that large-scale vorticity gains
energy from small-scale vorticity due to the vortex-thinning process.


title: How a user's personality influences content engagement in social media

abstract:
  Social media presents an opportunity for people to share content that they
find to be significant, funny, or notable. No single piece of content will
appeal to all users, but are there systematic variations between users that can
help us better understand information propagation? We conducted an experiment
exploring social media usage during disaster scenarios, combining
electroencephalogram (EEG), personality surveys, and prompts to share social
media, we show how personality not only drives willingness to engage with
social media but also helps to determine what type of content users find
compelling. As expected, extroverts are more likely to share content. In
contrast, one of our central results is that individuals with depressive
personalities are the most likely cohort to share informative content, like
news or alerts. Because personality and mood will generally be highly
correlated between friends via homophily, our results may be an import factor
in understanding social contagion.


title: The Complexity of (List) Edge-Coloring Reconfiguration Problem

abstract:
  Let $G$ be a graph such that each edge has its list of available colors, and
assume that each list is a subset of the common set consisting of $k$ colors.
Suppose that we are given two list edge-colorings $f_0$ and $f_r$ of $G$, and
asked whether there exists a sequence of list edge-colorings of $G$ between
$f_0$ and $f_r$ such that each list edge-coloring can be obtained from the
previous one by changing a color assignment of exactly one edge. This problem
is known to be PSPACE-complete for every integer $k \ge 6$ and planar graphs of
maximum degree three, but any complexity hardness was unknown for the non-list
variant. In this paper, we first improve the known result by proving that, for
every integer $k \ge 4$, the problem remains PSPACE-complete even if an input
graph is planar, bounded bandwidth, and of maximum degree three. We then give
the first complexity hardness result for the non-list variant: for every
integer $k \ge 5$, we prove that the non-list variant is PSPACE-complete even
if an input graph is planar, of bandwidth linear in $k$, and of maximum degree
$k$.


title:
A Decomposition Method for Global Evaluation of Shannon Entropy and
  Local Estimations of Algorithmic Complexity

abstract:
  We investigate the properties of a Block Decomposition Method (BDM), which
extends the power of a Coding Theorem Method (CTM) that approximates local
estimations of algorithmic complexity based upon Solomonoff-Levin's theory of
algorithmic probability providing a closer connection to algorithmic complexity
than previous attempts based on statistical regularities e.g. as spotted by
some popular lossless compression schemes. The strategy behind BDM is to find
small computer programs that produce the components of a larger, decomposed
object. The set of short computer programs can then be artfully arranged in
sequence so as to produce the original object and to estimate an upper bound on
the length of the shortest computer program that produces said original object.
We show that the method provides efficient estimations of algorithmic
complexity but that it performs like Shannon entropy when it loses accuracy. We
estimate errors and study the behaviour of BDM for different boundary
conditions, all of which are compared and assessed in detail. The measure may
be adapted for use with more multi-dimensional objects than strings, objects
such as arrays and tensors. To test the measure we demonstrate the power of CTM
on low algorithmic-randomness objects that are assigned maximal entropy (e.g.
$\pi$) but whose numerical approximations are closer to the theoretical low
algorithmic-randomness expectation. We also test the measure on larger objects
including dual, isomorphic and cospectral graphs for which we know that
algorithmic randomness is low. We also release implementations of the methods
in most major programming languages---Wolfram Language (Mathematica), Matlab,
R, Perl, Python, Pascal, C++, and Haskell---and a free online algorithmic
complexity calculator.


title: Jacobian elliptic Kummer surfaces and special function identities

abstract:
  We derive formulas for the construction of all inequivalent Jacobian elliptic
fibrations on the Kummer surface of two non-isogeneous elliptic curves from
extremal rational elliptic surfaces by rational base transformations and
quadratic twists. We then show that each such decomposition yields a
description of the Picard-Fuchs system satisfied by the periods of the
holomorphic two-form as either a tensor product of two Gauss' hypergeometric
differential equations, an Appell hypergeometric system, or a GKZ differential
system. As the answer must be independent of the fibration used, identities
relating differential systems are obtained. They include a new identity
relating Appell's hypergeometric system to a product of two Gauss'
hypergeometric differential equations by a cubic transformation.


title:
Analytic Evaluation of Three Different Five-Electron Atomic Integrals
  Involving Exponentially Correlated Functions of $r_{ij}$ With $r_{ij}$'s Not
  Forming A Closed Loop

abstract:
  The simple method outlined in our earlier paper [B.Padhy, Orissa Journal of
Physics, vol.19, No.1, p.1, February 2012] has been utilized here for analytic
evaluation of three different five-electron atomic integrals with integrands
involving products of s Slater-type orbitals and exponentially correlated
functions of the form $r_{ij} exp(-\lambda_{ij} r_{ij})$. Only products of
those $r_{ij}$'s which do not form a closed loop by themselves, are considered.


title: Dark matter properties implied by gamma ray interstellar emission models

abstract:
  We infer dark matter properties from gamma ray residuals extracted using
eight different interstellar emission scenarios proposed by the Fermi-LAT
Collaboration to explain the Galactic Center gamma ray excess. Adopting the
most plausible simplified ansatz, we assume that the dark matter particle is a
Majorana fermion interacting with standard fermions via a scalar mediator.
Using this theoretical hypothesis and the Fermi residuals we calculate Bayesian
evidences, including Fermi-LAT exclusion limits from 15 dwarf spheroidal
galaxies as well. Our Bayes factors single out four of the Fermi scenarios as
compatible with the simplified dark matter model. In the most preferred
scenario the dark matter (mediator) mass is in the 100-500 (1-200) GeV range
and its annihilation is dominated by top quark final state. Less preferred but
still plausible is annihilation into b\bar{b} and tau^+tau^- final states with
an order of magnitude lower dark matter mass. Our conclusion is that the
properties of dark matter extracted from gamma ray data are highly sensitive to
the modeling of the interstellar emission.


title: Wiener index, Harary index and Hamiltonicity of graphs

abstract:
  In this paper, we prove tight sufficient conditions for traceability and
Hamiltonicity of connected graphs with given minimum degree, in terms of Wiener
index and Harary index. We also prove some result on Hamiltonicity of balanced
bipartite graphs in the similar fashion. In two recent papers
\cite{LDJ2016,LDJ2017}, Liu et al. corrected some previous work on traceability
of connected graphs in terms of Wiener index and Harary index, respectively,
such as \cite{HW2013,Y2013}. We generalize these results and give short and
unified proofs. All results in this paper are best possible.


title: Optimal State Estimation with Measurements Corrupted by Laplace Noise

abstract:
  Optimal state estimation for linear discrete-time systems is considered.
Motivated by the literature on differential privacy, the measurements are
assumed to be corrupted by Laplace noise. The optimal least mean square error
estimate of the state is approximated using a randomized method. The method
relies on that the Laplace noise can be rewritten as Gaussian noise scaled by
Rayleigh random variable. The probability of the event that the distance
between the approximation and the best estimate is smaller than a constant is
determined as function of the number of parallel Kalman filters that is used in
the randomized method. This estimator is then compared with the optimal linear
estimator, the maximum a posteriori (MAP) estimate of the state, and the
particle filter.


title:
Neural Coarse-Graining: Extracting slowly-varying latent degrees of
  freedom with neural networks

abstract:
  We present a loss function for neural networks that encompasses an idea of
trivial versus non-trivial predictions, such that the network jointly
determines its own prediction goals and learns to satisfy them. This permits
the network to choose sub-sets of a problem which are most amenable to its
abilities to focus on solving, while discarding 'distracting' elements that
interfere with its learning. To do this, the network first transforms the raw
data into a higher-level categorical representation, and then trains a
predictor from that new time series to its future. To prevent a trivial
solution of mapping the signal to zero, we introduce a measure of
non-triviality via a contrast between the prediction error of the learned model
with a naive model of the overall signal statistics. The transform can learn to
discard uninformative and unpredictable components of the signal in favor of
the features which are both highly predictive and highly predictable. This
creates a coarse-grained model of the time-series dynamics, focusing on
predicting the slowly varying latent parameters which control the statistics of
the time-series, rather than predicting the fast details directly. The result
is a semi-supervised algorithm which is capable of extracting latent
parameters, segmenting sections of time-series with differing statistics, and
building a higher-level representation of the underlying dynamics from
unlabeled data.


title: Group Rotation Type Crowdsourcing

abstract:
  A common workflow to perform a continuous human task stream is to divide
workers into groups, have one group perform the newly-arrived task, and rotate
the groups. We call this type of workflow the group rotation. This paper
addresses the problem of how to manage Group Rotation Type Crowdsourcing, the
group rotation in a crowdsourcing setting. In the group-rotation type
crowdsourcing, we must change the group structure dynamically because workers
come in and leave frequently. This paper proposes an approach to explore a
design space of methods for group restructuring in the group rotation type
crowdsourcing.


title: An algebra of synchronous atomic steps

abstract:
  This research started with an algebra for reasoning about rely/guarantee
concurrency for a shared memory model. The approach taken led to a more
abstract algebra of atomic steps, in which atomic steps synchronise (rather
than interleave) when composed in parallel. The algebra of rely/guarantee
concurrency then becomes an interpretation of the more abstract algebra. Many
of the core properties needed for rely/guarantee reasoning can be shown to hold
in the abstract algebra where their proofs are simpler and hence allow a higher
degree of automation. Moreover, the realisation that the synchronisation
mechanisms of standard process algebras, such as CSP and CCS/SCCS, can be
interpreted in our abstract algebra gives evidence of its unifying power. The
algebra has been encoded in Isabelle/HOL to provide a basis for tool support.


title:
Geometrically Exact Finite Element Formulations for Curved Slender
  Beams: Kirchhoff-Love Theory vs. Simo-Reissner Theory

abstract:
  The present work focuses on geometrically exact finite elements for highly
slender beams. It aims at the proposal of novel formulations of Kirchhoff-Love
type, a detailed review of existing formulations of Kirchhoff-Love and
Simo-Reissner type as well as a careful evaluation and comparison of the
proposed and existing formulations. Two different rotation interpolation
schemes with strong or weak Kirchhoff constraint enforcement, respectively, as
well as two different choices of nodal triad parametrizations in terms of
rotation or tangent vectors are proposed. The combination of these schemes
leads to four novel finite element variants, all of them based on a
C1-continuous Hermite interpolation of the beam centerline. Essential
requirements such as representability of general 3D, large-deformation, dynamic
problems involving slender beams with arbitrary initial curvatures and
anisotropic cross-section shapes or preservation of objectivity and
path-independence will be investigated analytically and verified numerically
for the different formulations. It will be shown that the geometrically exact
Kirchhoff-Love beam elements proposed in this work are the first ones of this
type that fulfill all the considered requirements. On the contrary,
Simo-Reissner type formulations fulfilling these requirements can be found in
the literature very well. However, it will be argued that the shear-free
Kirchhoff-Love formulations can provide considerable numerical advantages when
applied to highly slender beams. Concretely, several representative numerical
test cases confirm that the proposed Kirchhoff-Love formulations exhibit a
lower discretization error level as well as a considerably improved nonlinear
solver performance in the range of high beam slenderness ratios as compared to
two representative Simo-Reissner element formulations from the literature.


title:
The long-term dynamical evolution of disc-fragmented multiple systems in
  the Solar Neighborhood

abstract:
  The origin of very low-mass hydrogen-burning stars, brown dwarfs, and
planetary-mass objects at the low-mass end of the initial mass function is not
yet fully understood. Gravitational fragmentation of circumstellar discs
provides a possible mechanism for the formation of such low-mass objects. The
kinematic and binary properties of very low-mass objects formed through disc
fragmentation at early times (< 10 Myr) were discussed in Li et al. (2015). In
this paper we extend the analysis by following the long-term evolution of
disc-fragmented systems, up to an age of 10 Gyr, covering the ages of the
stellar and substellar population in the Galactic field. We find that the
systems continue to decay, although the rates at which companions escape or
collide with each other are substantially lower than during the first 10 Myr,
and that dynamical evolution is limited beyond 1 Gyr. By t = 10 Gyr, about one
third of the host stars is single, and more than half have only one companion
left. Most of the other systems have two companions left that orbit their host
star in widely separated orbits. A small fraction of companions have formed
binaries that orbit the host star in a hierarchical triple configuration. The
majority of such double companion systems have internal orbits that are
retrograde with respect to their orbits around their host stars. Our
simulations allow a comparison between the predicted outcomes of
disc-fragmentation with the observed low-mass hydrogen-burning stars, brown
dwarfs, and planetary-mass objects in the Solar neighborhood. Imaging and
radial velocity surveys for faint binary companions among nearby stars are
necessary for verification or rejection for the formation mechanism proposed in
this paper.


title: On the non-vanishing conjecture and existence of log minimal models

abstract:
  We prove that the non-vanishing conjecture and the log minimal model
conjecture for projective log canonical pairs can be reduced to the
non-vanishing conjecture for smooth projective varieties such that the boundary
divisor is zero.


title:
Convergence rates and $W^{1,p}$ estimates in homogenization theory of
  Stokes systems in Lipschitz domains

abstract:
  Concerned with the Stokes systems with rapidly oscillating periodic
coefficients, we mainly extend the recent works in \cite{SGZWS,G} to those in
term of Lipschitz domains.
  The arguments employed here are quite different from theirs, and the basic
idea comes from \cite{QX2}, originally motivated by \cite{SZW2,SZW12,TS}. We
obtain an almost-sharp $O(\varepsilon\ln(r_0/\varepsilon))$ convergence rate in
$L^2$ space, and a sharp $O(\varepsilon)$ error estimate in
$L^{\frac{2d}{d-1}}$ space by a little stronger assumption.
  Under the dimensional condition $d=2$, we also establish the optimal
$O(\varepsilon)$ convergence rate on pressure terms in $L^2$ space. Then
utilizing the convergence rates we can derive the $W^{1,p}$ estimates uniformly
down to microscopic scale $\varepsilon$ without any smoothness assumption on
the coefficients, where $|\frac{1}{p}-\frac{1}{2}|<\frac{1}{2d}+\epsilon$ and
$\epsilon$ is a positive constant independent of $\varepsilon$. Combining the
local estimates, based upon $\text{VMO}$ coefficients, consequently leads to
the uniform $W^{1,p}$ estimates. Here the proofs do not rely on the well known
compactness methods.


title: Effective criteria for specific identifiability of tensors and forms

abstract:
  In applications where the tensor rank decomposition arises, one often relies
on its identifiability properties for interpreting the individual rank-$1$
terms appearing in the decomposition. Several criteria for identifiability have
been proposed in the literature, however few results exist on how frequently
they are satisfied. We propose to call a criterion effective if it is satisfied
on a dense, open subset of the smallest semi-algebraic set enclosing the set of
rank-$r$ tensors. We analyze the effectiveness of Kruskal's criterion when it
is combined with reshaping. It is proved that this criterion is effective for
both real and complex tensors in its entire range of applicability, which is
usually much smaller than the smallest typical rank. Our proof explains when
reshaping-based algorithms for computing tensor rank decompositions may be
expected to recover the decomposition. Specializing the analysis to symmetric
tensors or forms reveals that the reshaped Kruskal criterion may even be
effective up to the smallest typical rank for some third, fourth and sixth
order symmetric tensors of small dimension as well as for binary forms of
degree at least three. We extended this result to $4 \times 4 \times 4 \times
4$ symmetric tensors by analyzing the Hilbert function, resulting in a
criterion for symmetric identifiability that is effective up to symmetric rank
$8$, which is optimal.


title:
Abelian color cycles: a new approach to strong coupling expansion and
  dual representations for non-abelian lattice gauge theory

abstract:
  We propose a new approach to strong coupling series and dual representations
for non-abelian lattice gauge theories using the SU(2) case as an example. The
Wilson gauge action is written as a sum over "abelian color cycles" (ACC) which
correspond to loops in color space around plaquettes. The ACCs are complex
numbers which can be commuted freely such that the strong coupling series and
the dual representation can be obtained as in the abelian case. Using a
suitable representation of the SU(2) gauge variables we integrate out all
original gauge links and identify the constraints for the dual variables in the
SU(2) case. We show that the construction can be generalized to the case of
SU(2) gauge fields with staggered fermions. The result is a strong coupling
series where all gauge integrals are known in closed form and we discuss its
applicability for possible dual simulations. The abelian color cycle concept
can be generalized to other non-abelian gauge groups such as SU(3).


title:
Effect of pressure on magneto-transport properties in the
  superconducting and normal phases of the metallic double chain compound
  Pr$_{2}$Ba$_{4}$Cu$_{7}$O$_{15-\delta }$

abstract:
  To examine the electronic phase diagram of superconducting CuO double chains,
we report the effect of external pressure on the magneto-transport properties
in superconducting and non-superconducting polycrystalline samples of
Pr$_{2}$Ba$_{4}$Cu$_{7}$O$_{15-\delta }$ at low temperatures (1.8-40 K) under
various magnetic fields (up to 14 T). In the as-sintered non-superconducting
sample, the magneto-resistance (MR) follows a power law of $H^{3/2}$ at low
temperatures, which is in no agreement with the $H^{2}$ dependence of MR in the
PrBa$_{2}$Cu$_{4}$O$_{8}$ system. The negative pressure dependence of the
superconducting phase is qualitatively consistent with a theoretical prediction
on the basis of the Tomonaga-Luttinger Liquid theory. The 48-h-reduced
superconducting sample at ambient pressure exhibits no clear increase in MR for
$T > T_{c,on}=26.5$ K. In contrast, with the application of pressure to the
superconducting sample, the MR effects reappear and are also well fitted by
$H^{3/2}$. The model of slightly warped Fermi surfaces explains not only the MR
effect of the non-superconducting sample, but is also related to the reasons
for the pressure-induced MR phenomena of the superconducting sample.


title:
PPCU: Proportional Per-packet Consistent Updates for Software Defined
  Networks - A Technical Report

abstract:
  In Software Defined Networks, where the network control plane can be
programmed by updating switch rules, consistently updating switches is a
challenging problem. In a per-packet consistent update (PPC), a packet either
matches the new rules added or the old rules to be deleted, throughout the
network, but not a combination of both. PPC must be preserved during an update
to prevent packet drops and loops, provide waypoint invariance and to apply
policies consistently. No algorithm exists today that confines changes required
during an update to only the affected switches, yet preserves PPC and does not
restrict applicable scenarios. We propose a general update algorithm called
PPCU that preserves PPC, is concurrent and provides an all-or-nothing semantics
for an update, irrespective of the execution speeds of switches and links,
while confining changes to only the affected switches and affected rules. We
use data plane time stamps to identify when the switches must move from the old
rules to the new rules. For this, we use the powerful programming features
provided to the data plane by the emerging programmable switches, which also
guarantee line rate. We prove the algorithm, identify its significant
parameters and analyze the parameters with respect to other algorithms in the
literature.


title:
On a class of conserved phase field systems with a maximal monotone
  perturbation

abstract:
  We prove existence and regularity for the solutions to a Cahn-Hilliard system
describing the phenomenon of phase separation for a material contained in a
bounded and regular domain. Since the first equation of the system is perturbed
by the presence of an additional maximal monotone operator, we show our results
using suitable regularization of the nonlinearities of the problem and
performing some a priori estimates which allow us to pass to the limit thanks
to compactness and monotonicity arguments. Next, under further assumptions, we
deduce a continuous dependence estimate whence the uniqueness property is also
achieved. Then, we consider the relating sliding mode control (SMC) problem and
show that the chosen SMC law forces a suitable linear combination of the
temperature and the phase to reach a given (space dependent) value within
finite time.


title: Linear differential polynomials in zero-free meromorphic functions

abstract:
  The paper determines all meromorphic functions with finitely many zeros in
the plane having the property that a linear differential polynomial in the
function, of order at least 3 and with rational functions as coefficients, also
has finitely many zeros.


title: Grid Loss: Detecting Occluded Faces

abstract:
  Detection of partially occluded objects is a challenging computer vision
problem. Standard Convolutional Neural Network (CNN) detectors fail if parts of
the detection window are occluded, since not every sub-part of the window is
discriminative on its own. To address this issue, we propose a novel loss layer
for CNNs, named grid loss, which minimizes the error rate on sub-blocks of a
convolution layer independently rather than over the whole feature map. This
results in parts being more discriminative on their own, enabling the detector
to recover if the detection window is partially occluded. By mapping our loss
layer back to a regular fully connected layer, no additional computational cost
is incurred at runtime compared to standard CNNs. We demonstrate our method for
face detection on several public face detection benchmarks and show that our
method outperforms regular CNNs, is suitable for realtime applications and
achieves state-of-the-art performance.


title: Transparent Live Code Offloading on FPGA

abstract:
  Even though it seems that FPGAs have finally made the transition from
research labs to the consumer devices' market, programming them remains
challenging. Despite the improvements made by High-Level Synthesis (HLS), which
removed the language and paradigm barriers that prevented many computer
scientists from working with them, producing a new design typically requires at
least several hours, making data- and context-dependent adaptations virtually
impossible.
  In this paper we present a new framework that off-loads, on-the-fly and
transparently to both the user and the developer, computationally-intensive
code fragments to FPGAs. While the performance should not surpass that of
hand-crafted HDL code, or even code produced by HLS, our results come with no
additional development costs and do not require producing and deploying a new
bit-stream to the FPGA each time a change is made. Moreover, since
optimizations are made at run-time, they may fit particular datasets or usage
scenarios, something which is rarely foreseeable at design or compile time.
  Our proposal revolves around an overlay architecture that is pre-programmed
on the FPGA and dynamically reconfigured by our framework to execute code
fragments extracted from the Data Flow Graph (DFG) of computational intensive
routines. We validated our solution using standard benchmarks and proved we are
able to off-load to FPGAs without developer's intervention.


title:
Active Osmotic Exchanger for Efficient Nanofiltration Inspired by the
  Kidney

abstract:
  In this paper, we investigate the physical mechanisms underlying one of the
most efficient filtration devices: the kidney. Building on a minimal model of
the Henle loop - the central part of the kidney filtration - we investigate
theoretically the detailed out-of-equilibrium fluxes in this separation process
in order to obtain absolute theoretical bounds for its efficiency in terms of
separation ability and energy consumption. We demonstrate that this separation
process operates at a remarkably small energy cost as compared to traditional
sieving processes while working at much smaller pressures. This unique
energetic efficiency originates in the double-loop geometry of the nephron,
which operates as an active osmotic exchanger. The principles for an
artificial-kidney-inspired filtration device could be readily mimicked based on
existing soft technologies to build compact and low-energy artificial dialytic
devices. Such a "kidney on a chip" also points to new avenues for advanced
water recycling, targeting, in particular, sea-water pretreatment for
decontamination and hardness reduction.


title:
Axiomatization of if-then-else over possibly non-halting programs and
  tests

abstract:
  In order to study the axiomatization of the if-then-else construct over
possibly non-halting programs and tests, this paper introduces the notion of
$C$-sets by considering the tests from an abstract $C$-algebra. When the
$C$-algebra is an ada, the axiomatization is shown to be complete by obtaining
a subdirect representation of $C$-sets. Further, this paper considers the
equality test with the if-then-else construct and gives a complete
axiomatization through the notion of agreeable $C$-sets.


title: dr0wned - Cyber-Physical Attack with Additive Manufacturing

abstract:
  Additive manufacturing (AM), or 3D printing, is an emerging manufacturing
technology that is expected to have far-reaching socioeconomic, environmental,
and geopolitical implications. As use of this technology increases, it will
become more common to produce functional parts, including components for
safety-critical systems. AM's dependence on computerization raises the concern
that the manufactured part's quality can be compromised by sabotage. This paper
demonstrates the validity of this concern, as we present the very first full
chain of attack involving AM, beginning with a cyber attack aimed at
compromising a benign AM component, continuing with malicious modification of a
manufactured object's blueprint, leading to the sabotage of the manufactured
functional part, and resulting in the physical destruction of a cyber-physical
system that employs this part. The contributions of this paper are as follows.
We propose a systematic approach to identify opportunities for an attack
involving AM that enables an adversary to achieve his/her goals. Then we
propose a methodology to assess the level of difficulty of an attack, thus
enabling differentiation between possible attack chains. Finally, to
demonstrate the experimental proof for the entire attack chain, we sabotage the
3D printed propeller of a quadcopter UAV, causing the quadcopter to literally
fall from the sky.


title:
Near-Sun and 1 AU magnetic field of coronal mass ejections: A parametric
  study

abstract:
  Aims. The magnetic field of coronal mass ejections (CMEs) determines their
structure, evolution, and energetics, as well as their geoeffectiveness.
However, we currently lack routine diagnostics of the near-Sun CME magnetic
field, which is crucial for determining the subsequent evolution of CMEs.
Methods. We recently presented a method to infer the near-Sun magnetic field
magnitude of CMEs and then extrapolate it to 1 AU. This method uses relatively
easy to deduce observational estimates of the magnetic helicity in CME-source
regions along with geometrical CME fits enabled by coronagraph observations. We
hereby perform a parametric study of this method aiming to assess its
robustness. We use statistics of active region (AR) helicities and CME
geometrical parameters to determine a matrix of plausible near-Sun CME magnetic
field magnitudes. In addition, we extrapolate this matrix to 1 AU and determine
the anticipated range of CME magnetic fields at 1 AU representing the radial
falloff of the magnetic field in the CME out to interplanetary (IP) space by a
power law with index aB. Results. The resulting distribution of the near-Sun
(at 10 Rs ) CME magnetic fields varies in the range [0.004, 0.02] G, comparable
to, or higher than, a few existing observational inferences of the magnetic
field in the quiescent corona at the same distance. We also find that a
theoretically and observationally motivated range exists around aB = -1.6
+-0.2, thereby leading to a ballpark agreement between our estimates and
observationally inferred field magnitudes of magnetic clouds (MCs) at L1.
Conclusions. In a statistical sense, our method provides results that are
consistent with observations.


title:
Asymptotic for the perturbed heavy ball system with vanishing damping
  term

abstract:
  We investigate the long time behavior of solutions to the differential
equation $\ddot{x}(t)+\frac{c}{\left( t+1\right) ^{\alpha}}\dot{x}(t)+\nabla
\Phi\left( x(t)\right) =g(t),~t\geq0, $ where $c$ is nonnegative constant,
$\alpha\in\lbrack0,1[,$ $\Phi$ is a $C^{1}$ convex function on a Hilbert space
$\mathcal{H}$ and $g\in L^{1} (0,+\infty;\mathcal{H}).$ We obtain sufficient
conditions on the source term $g(t)$ ensuring the weak or the strong
convergence of any trajectory $x(t)$ as $t\rightarrow+\infty$ to a minimizer of
the function $\Phi$ if one exists.


title:
Spontaneous orbital-selective Mott transitions and the Jahn-Teller metal
  of A$_3$C$_{60}$

abstract:
  The alkali-doped fullerides A$_3$C$_{60}$ are half-filled three-orbital
Hubbard systems which exhibit an unconventional superconducting phase next to a
Mott insulator. While the pairing is understood to arise from an effectively
negative Hund coupling, the highly unusual Jahn-Teller metal near the Mott
transition, featuring both localized and itinerant electrons, has not been
understood. This property is consistently explained by a previously
unrecognized phenomenon: the spontaneous transition of multiorbital systems
with negative Hund coupling into an orbital-selective Mott state. This
symmetry-broken state, which has no ordinary orbital moment, is characterized
by an orbital-dependent two-body operator (the double occupancy) or an
orbital-dependent kinetic energy, and may be regarded as a diagonal-order
version of odd-frequency superconductivity. We propose that the recently
discovered Jahn-Teller metal phase of Rb$_x$Cs$_{3-x}$C$_{60}$ is an
experimental realization of this novel state of matter.


title:
The Night Sky Spectrum of Xinglong Observatory: Changes from 2004 to
  2015

abstract:
  We present spectroscopic measurements on the night sky of Xinglong
Observatory for a period of 12 years from 2004 to 2015. The spectra were
obtained on moonless clear nights using the OMR spectrograph mounted on a
2.16-m reflector with a wavelength coverage of 4000-7000A. The night sky
spectrum shows the presence of emission lines from Hg I and Na I due to local
artificial sources, along with the atmospheric emission lines, i.e., O I and OH
molecules, indicating the existence of light pollution. We have monitored the
night sky brightness during the whole night and found some decrement in the sky
brightness with time, but the change is not significant. Also, we monitored the
light pollution level in different azimuthal directions and found that the
influence of light pollution from the direction of Beijing is stronger compared
with that from the direction of Tangshan and other areas. An analysis of night
sky spectra for the entire data set suggested that the zenith sky brightness of
Xinglong Observatory has brightened by about 0.5 mag arcsec -2 in the V and B
bands from 2004 to 2015. We recommend consecutive spectroscopic measurements of
the night sky brightness at Xinglong Observatory in the future, not only for
monitoring but also for scientific reference.


title:
Central measures on multiplicative graphs, representations of Lie
  algebras and weight polytopes

abstract:
  To each finite-dimensional representation of a simple Lie algebra is
associated a multiplicative graph in the sense of Kerov and Vershik definedfrom
the decomposition of its tensor powers into irreducible components. The
conditioning of naturalrandom Littelmann paths to stay in their corresponding
Weyl chamber is thencontrolled by central measures on this type of graphs.
Using the K-theory of associated C*-algebras, Handelman established a
homeomorphism between the set of central measures on these multiplicative
graphs and the weight polytope of theunderlying representation. In the present
paper, we make explicit this homeomorphism independently of Handelman's results
by using Littelmann's path model. As a by-product we also get an explicit
parametrization of theweight polytope in terms of drifts of random Littelmann
paths. This explicit parametrization yields a complete description of harmonic
and c-harmonic functions for this Littelmann paths model.


title:
Multivariate Gaussian extended quadrature method of moments for
  turbulent disperse multiphase flow

abstract:
  The present contribution introduces a fourth-order moment formalism for
particle trajectory crossing (PTC) in the framework of multiscale modeling of
disperse multiphase flow. In our previous work, the ability to treat PTC was
examined with direct-numerical simulations (DNS) using either quadrature
reconstruction based on a sum of Dirac delta functions denoted as
Quadrature-Based Moment Methods (QBMM) in order to capture large scale
trajectory crossing, or by using low order hydrodynamics closures in the
Levermore hierarchy denoted as Kinetic-Based Moment Methods (KBMM) in order to
capture small scale trajectory crossing. Whereas KBMM leads to well-posed PDEs
and has a hard time capturing large scale trajectory crossing for particles
with enough inertia, QBMM based on a discrete reconstruction suffers from
singularity formation and requires too many moments in order to capture the
effect of PTC at both small scale and large scale both to small-scale
turbulence as well as free transport coupled to drag in an Eulerian mesoscale
framework. The challenge addressed in this work is thus twofold: first, to
propose a new generation of method at the interface between QBMM and KBMM with
less singular behavior and the associated proper mathematical properties, which
is able to capture both small scale and large scale trajectory crossing, and
second to limit the number of moments used for applicability in 2-D and 3-D
configurations without losing too much accuracy in the representation of
spatial fluxes. In order to illustrate its numerical properties, the proposed
Gaussian extended quadrature method of moments (Gaussian-EQMOM) is applied to
solve 1-D and 2-D kinetic equations representing finite-Stokes-number particles
in a known turbulent fluid flow.


title: Experimental study of shear band formation: bifurcation and localization

abstract:
  We report the experimental observation of the bifurcation at the origin of
localization of the deformation in a granular material submitted to uniaxial
compression. We present a quantitative characterization of the heterogeneity in
the strain field repartition allowing to evidence objectively the existence of
a bifurcation initiating the shear bands formation process. We show that this
bifurcation is supercritical and has no clear signature on the stress-strain
curve. At the bifurcation, a symmetry breaking occurs characterized by the
emergence of a well-defined orientation corresponding to the Mohr-Coulomb
angle. Yet, plasticity is still diffuse and the shear band extension is of the
order of the sample width. While loading proceeds, the shear band narrows until
it reaches, after the peak of the stress-strain curve, a stationary width.


title:
Data Integration Model for Air Quality: A Hierarchical Approach to the
  Global Estimation of Exposures to Ambient Air Pollution

abstract:
  Air pollution is a major risk factor for global health, with both ambient and
household air pollution contributing substantial components of the overall
global disease burden. One of the key drivers of adverse health effects is fine
particulate matter ambient pollution (PM$_{2.5}$) to which an estimated 3
million deaths can be attributed annually. The primary source of information
for estimating exposures has been measurements from ground monitoring networks
but, although coverage is increasing, there remain regions in which monitoring
is limited. Ground monitoring data therefore needs to be supplemented with
information from other sources, such as satellite retrievals of aerosol optical
depth and chemical transport models. A hierarchical modelling approach for
integrating data from multiple sources is proposed allowing spatially-varying
relationships between ground measurements and other factors that estimate air
quality. Set within a Bayesian framework, the resulting Data Integration Model
for Air Quality (DIMAQ) is used to estimate exposures, together with associated
measures of uncertainty, on a high resolution grid covering the entire world.
Bayesian analysis on this scale can be computationally challenging and here
approximate Bayesian inference is performed using Integrated Nested Laplace
Approximations. Model selection and assessment is performed by cross-validation
with the final model offering substantial increases in predictive accuracy,
particularly in regions where there is sparse ground monitoring, when compared
to current approaches: root mean square error (RMSE) reduced from 17.1 to 10.7,
and population weighted RMSE from 23.1 to 12.1 $\mu$gm$^{-3}$. Based on
summaries of the posterior distributions for each grid cell, it is estimated
that 92% of the world's population reside in areas exceeding the World Health
Organization's Air Quality Guidelines.


title:
On the Performance of Multihop-Intervehicular Communications Systems
  over n*Rayleigh Fading Channels

abstract:
  We investigate the performance of multihop-intervehicular communication
systems with regenerative and nonregenerative relaying. We consider the
so-called "n*Rayleigh distribution" as an adequate multipath fading channel
model for vehicle-to-vehicle communication scenarios. We derive a novel
approximation for the outage probability of maximum ratio combining (MRC)
diversity reception. In addition, we analyze the amount of fading and optimize
the power allocation for the investigated scenario. Numerical results show that
regenerative systems are more efficient than nonregenerative systems when the
cascading order (n) is small; however, for large n, our results demonstrate
that the performance of both relaying techniques is rather similar.


title: Rectangular superpolynomials for the figure-eight knot

abstract:
  We rewrite the recently proposed differential expansion formula for HOMFLY
polynomials of the knot $4_1$ in arbitrary rectangular representation $R=[r^s]$
as a sum over all Young sub-diagrams $\lambda$ of $R$ with extraordinary simple
coefficients $D_{\lambda^{tr}}(r)\cdot D_\lambda(s)$ in front of the
$Z$-factors. Somewhat miraculously, these coefficients are made from quantum
dimensions of symmetric representations of the groups $SL(r)$ and $SL(s)$ and
restrict summation to diagrams with no more than $s$ rows and $r$ columns. They
possess a natural $\beta$-deformation to Macdonald dimensions and produces
positive Laurent polynomials, which can be considered as plausible candidates
for the role of the rectangular superpolynomials. Both polynomiality and
positivity are non-evident properties of arising expressions, still they are
true. This extends the previous suggestions for symmetric and antisymmetric
representations (when $s=1$ or $r=1$ respectively) to arbitrary rectangular
representations. As usual for differential expansion, there are additional
gradings. In the only example, available for comparison -- that of the trefoil
knot $3_1$, to which our results for $4_1$ are straightforwardly extended, --
one of them reproduces the "fourth grading" for hyperpolynomials. Factorization
properties are nicely preserved even in the 5-graded case.


title: Orbifold points on Prym-Teichm\"{u}ller curves in genus four

abstract:
  For each discriminant $D>1$, McMullen constructed the Prym-Teichm\"uller
curves $W_D(4)$ and $W_D(6)$ in $\mathcal{M}_{3}$ and $\mathcal{M}_{4}$, which
constitute one of the few known infinite families of geometrically primitive
Teichm\"{u}ller curves. In the present paper, we determine for each $D$ the
number and type of orbifold points on $W_D(6)$. These results, together with a
previous result of the two authors in the genus $3$ case and with results of
Lanneau-Nguyen and M\"oller, complete the topological characterisation of all
Prym-Teichm\"uller curves and determine their genus.
  The study of orbifold points relies on the analysis of intersections of
$W_D(6)$ with certain families of genus $4$ curves with extra automorphisms. As
a side product of this study, we give an explicit construction of such families
and describe their Prym-Torelli images, which turn out to be isomorphic to
certain products of elliptic curves. We also give a geometric description of
the flat surfaces associated to these families and describe the asymptotics of
the genus of $W_D(6)$ for large $D$.


title: Quasi-Galois theory in symmetric-monoidal categories

abstract:
  Given a ring object $A$ in a symmetric monoidal category, we investigate what
it means for the extension $\mathbb{1}\rightarrow A$ to be (quasi-)Galois. In
particular, we define splitting ring extensions and examine how they occur.
Specializing to tensor-triangulated categories, we study how
extension-of-scalars along a quasi-Galois ring object affects the Balmer
spectrum. We define what it means for a separable ring to have constant degree,
which is a necessary and sufficient condition for the existence of a
quasi-Galois closure. Finally, we illustrate the above for separable rings
occurring in modular representation theory.


title:
T-PHOT version 2.0: improved algorithms for background subtraction,
  local convolution, kernel registration, and new options

abstract:
  We present the new release v2.0 of T-PHOT, a publicly available software
package developed to perform PSF-matched, prior-based, multiwavelength
deconfusion photometry of extragalactic fields. New features included in the
code are presented and discussed: background estimation, fitting using position
dependent kernels, flux prioring, diagnostical statistics on the residual
image, exclusion of selected sources from the model and residual images,
individual registration of fitted objects. These new options improve on the
performance of the code, allowing for more accurate results and providing
useful aids for diagnostics.


title: Two-connected spanning subgraphs with at most $\frac{10}{7}$OPT edges

abstract:
  We present a $\frac{10}{7}$-approximation algorithm for the minimum
two-vertex-connected spanning subgraph problem.


title: On the Reduction and Evaluation of Generalized Polylogarithms

abstract:
  This is a contribution to the proceedings of the 2016 "Loops and legs"
conference, based on the talk by HF. The talk was based on the paper "On the
reduction of Generalized Polylogarithms to $\text{Li}_n$ and $\text{Li}_{2,2}$
and on the reduction thereof" by the three authors, published in March 2016 in
JHEP.


title: From Community Detection to Community Deception

abstract:
  The community deception problem is about how to hide a target community C
from community detection algorithms. The need for deception emerges whenever a
group of entities (e.g., activists, police enforcements) want to cooperate
while concealing their existence as a community. In this paper we introduce and
formalize the community deception problem. To solve this problem, we describe
algorithms that carefully rewire the connections of C's members. We
experimentally show how several existing community detection algorithms can be
deceived, and quantify the level of deception by introducing a deception score.
We believe that our study is intriguing since, while showing how deception can
be realized it raises awareness for the design of novel detection algorithms
robust to deception techniques.


title: Reward Augmented Maximum Likelihood for Neural Structured Prediction

abstract:
  A key problem in structured output prediction is direct optimization of the
task reward function that matters for test evaluation. This paper presents a
simple and computationally efficient approach to incorporate task reward into a
maximum likelihood framework. By establishing a link between the log-likelihood
and expected reward objectives, we show that an optimal regularized expected
reward is achieved when the conditional distribution of the outputs given the
inputs is proportional to their exponentiated scaled rewards. Accordingly, we
present a framework to smooth the predictive probability of the outputs using
their corresponding rewards. We optimize the conditional log-probability of
augmented outputs that are sampled proportionally to their exponentiated scaled
rewards. Experiments on neural sequence to sequence models for speech
recognition and machine translation show notable improvements over a maximum
likelihood baseline by using reward augmented maximum likelihood (RAML), where
the rewards are defined as the negative edit distance between the outputs and
the ground truth labels.


title: Several Proofs of Security for a Tokenization Algorithm

abstract:
  In this paper we propose a tokenization algorithm of Reversible Hybrid type,
as defined in PCI DSS guidelines for designing a tokenization solution, based
on a block cipher with a secret key and (possibly public) additional input. We
provide some formal proofs of security for it, which imply our algorithm
satisfies the most significant security requirements described in PCI DSS
tokenization guidelines. Finally, we give an instantiation with concrete
cryptographic primitives and fixed length of the PAN, and we analyze its
efficiency and security.


title: Triple arrays from difference sets

abstract:
  This paper addresses the question whether triple arrays can be constructed
from Youden squares developed from difference sets. We prove that if the
difference set is abelian, then having $-1$ as multiplier is both a necessary
and sufficient condition for the construction to work. Using this, we are able
to give a new infinite family of triple arrays. We also give an alternative and
more direct version of the construction, leaving out the intermediate step via
Youden squares. This is used when we analyse the case of non-abelian difference
sets, for which we prove a sufficient condition for giving triple arrays. We do
a computer search for such non-abelian difference sets, but have not found any
examples satisfying the given condition.


title:
Weakly Supervised PatchNets: Describing and Aggregating Local Patches
  for Scene Recognition

abstract:
  Traditional feature encoding scheme (e.g., Fisher vector) with local
descriptors (e.g., SIFT) and recent convolutional neural networks (CNNs) are
two classes of successful methods for image recognition. In this paper, we
propose a hybrid representation, which leverages the discriminative capacity of
CNNs and the simplicity of descriptor encoding schema for image recognition,
with a focus on scene recognition. To this end, we make three main
contributions from the following aspects. First, we propose a patch-level and
end-to-end architecture to model the appearance of local patches, called {\em
PatchNet}. PatchNet is essentially a customized network trained in a weakly
supervised manner, which uses the image-level supervision to guide the
patch-level feature extraction. Second, we present a hybrid visual
representation, called {\em VSAD}, by utilizing the robust feature
representations of PatchNet to describe local patches and exploiting the
semantic probabilities of PatchNet to aggregate these local patches into a
global representation. Third, based on the proposed VSAD representation, we
propose a new state-of-the-art scene recognition approach, which achieves an
excellent performance on two standard benchmarks: MIT Indoor67 (86.2\%) and
SUN397 (73.0\%).


title:
Have precipitation extremes and annual totals been increasing in the
  world's dry regions over the last 60 years?

abstract:
  Daily rainfall extremes and annual totals have increased in large parts of
the global land area over the last decades. These observations are consistent
with theoretical considerations of a warming climate. However, until recently
these global tendencies have not been shown to consistently affect land regions
with limited moisture availability. A recent study, published by Donat et al.
(2016, Nature Climate Change, doi:10.1038/nclimate2941), now identified rapid
increases in globally aggregated dry region daily extreme rainfall and annual
rainfall totals. Here, we reassess the respective analysis and find that a)
statistical artifacts introduced by the choice of the reference period prior to
data standardization lead to an overestimation of the reported trends by up to
40%, and also that b) the definition of `dry regions of the globe' affect the
reported globally aggregated trends in extreme rainfall. Using the same
observational dataset, but accounting for the statistical artifacts and using
alternative, well-established dryness definitions, we find no significant
increases in heavy precipitation in the world's dry regions. Adequate data
pre-processing approaches and accounting for uncertainties regarding the
definition of dryness are crucial to the quantification of spatially aggregated
trends in the world's dry regions. In view of the high relevance of the
question to many potentially affected stakeholders, we call for a cautionary
consideration of specific data processing methods, including issues related to
the definition of dry areas, to guarantee robustness of communicated climate
change relevant findings.


title: Could wormholes form in dark matter galactic halos?

abstract:
  We estimate expression for velocity as a function of the radial coordinate
$r$ by using polynomial interpolation based on the experimental data of
rotational velocities at distant outer regions of galaxies. The interpolation
technique has been used to estimate fifth degree polynomial followed by cubic
spline interpolation. This rotational velocity is used to find the geometry of
galactic halo regions within the framework of Einstein's general relativity. In
this letter we have analyzed features of galactic halo regions based on two
possible choices for the dark matter density profile, viz. Navarro, Frenk \&
White (NFW) type~\citep{Navarro1996} and Universal Rotation Curve (URC)
~\citep{Castignani2012}. It is argued that spacetime of the galactic halo
possesses some of the characteristics needed to support traversable wormholes.


title: Lifting Weighted Blow-ups

abstract:
  Let f: X -> Z be a local, projective, divisorial contraction between normal
varieties of dimension n with Q-factorial singularities. Let $Y \subset X$ be a
f-ample Cartier divisor and assume that f|Y: Y -> W has a structure of a
weighted blow-up. We prove that f: X -> Z, as well, has a structure of weighted
blow-up. As an application we consider a local projective contraction f: X -> Z
from a variety X with terminal Q-factorial singularities, which contracts a
prime divisor E to an isolated Q-factorial singularity $P\in Z$, such that
$-(K_X + (n-3)L)$ is f-ample, for a f-ample Cartier divisor L on X. We prove
that (Z,P) is a hyperquotient singularity and f is a weighted blow-up.


title:
Properties of low-dimensional collective variables in the molecular
  dynamics of biopolymers

abstract:
  The description of the dynamics of a complex, high-dimensional system in
terms of a low-dimensional set of collective variables Y can be fruitful if the
low dimensional representation satisfies a Langevin equation with drift and
diffusion coefficients which depend only on Y. We present a computational
scheme to evaluate whether a given collective variable provides a faithful
low-dimensional representation of the dynamics of a high-dimensional system.
The scheme is based on the framework of finite-difference Langevin-equation,
similar to that used for molecular-dynamics simulations. This allows one to
calculate the drift and diffusion coefficients in any point of the
full-dimensional system. The width of the distribution of drift and diffusion
coefficients in an ensemble of microscopic points at the same value of Y
indicates to which extent the dynamics of Y is described by a simple Langevin
equation. Using a simple protein model we show that collective variables often
used to describe biopolymers display a non-negligible width both in the drift
and in the diffusion coefficients. We also show that the associated effective
force is compatible with the equilibrium free--energy calculated from a
microscopic sampling, but results in markedly different dynamical properties.


title: Tracking Particles with Large Displacements using Energy Minimization

abstract:
  We describe a method to track particles undergoing large displacements.
Starting with a list of particle positions sampled at different time points, we
assign particle identities by minimizing the sum across all particles of the
trace of the square of the strain tensor. This method of tracking corresponds
to minimizing the stored energy in an elastic solid or the dissipated energy in
a viscous fluid. Our energy-minimizing approach extends the advantages of
particle tracking to situations where particle imaging velocimetry and digital
imaging correlation are typically required. This approach is much more reliable
than the standard squared-displacement minimizing approach for
spatially-correlated displacements that are larger than the typical
interparticle spacing. Thus, it is suitable for particles embedded in a
material undergoing large deformations. On the other hand, squared-displacement
minimization is more effective for particles undergoing uncorrelated random
motion. In the Supplement, we include a flexible MATLAB particle tracker that
implements either approach. This implementation returns an estimation of the
strain tensor for each particle, in addition to its identification.


title: Gradient Gibbs measures and fuzzy transformations on trees

abstract:
  We study Gibbsian models of unbounded integer-valued spins on trees which
possess a symmetry under height-shift. We develop a theory relating boundary
laws to gradient Gibbs measures, which applies also in cases where the
corresponding Gibbs measures do not exist. Our results extend the classical
theory of Zachary beyond the case of normalizable boundary laws, which implies
existence of Gibbs measures, to periodic boundary laws. We provide a
construction for classes of tree-automorphism invariant gradient Gibbs measures
in terms of mixtures of pinned measures, whose marginals to infinite paths on
the tree are random walks in a q-periodic environment. Here the mixture measure
is the invariant measure of a finite state Markov chain which arises as a mod-q
fuzzy transform, and which governs the correlation decay. The construction
applies for example to SOS-models and discrete Gaussian models and delivers a
large number of gradient Gibbs measures. We also discuss relations of certain
gradient Gibbs measures to Potts and Ising models.


title:
Finite-Size Corrections to the Excitation Energy Transfer in a Massless
  Scalar Interaction Model

abstract:
  We study the excitation energy transfer (EET) for a simple model in which a
massless scalar particle is exchanged between two molecules. We show that a
finite-size effect appears in EET by the interaction energy due to overlapping
of the quantum waves in a short time interval. The effect generates finite-size
corrections to Fermi's golden rule and modifies EET probability from the
standard formula in the Forster mechanism. The correction terms come from
transition modes outside the resonance energy region and enhance EET
probability substantially.


title: Parallel Clustering of Graphs for Anonymization and Recommender Systems

abstract:
  Graph clustering is widely used in many data analysis applications. In this
paper we propose several parallel graph clustering algorithms based on Monte
Carlo simulations and expectation maximization in the context of stochastic
block models. We apply those algorithms to the specific problems of recommender
systems and social network anonymization. We compare the experimental results
to previous propositions.


title:
Transferring Object-Scene Convolutional Neural Networks for Event
  Recognition in Still Images

abstract:
  Event recognition in still images is an intriguing problem and has potential
for real applications. This paper addresses the problem of event recognition by
proposing a convolutional neural network that exploits knowledge of objects and
scenes for event classification (OS2E-CNN). Intuitively, it stands to reason
that there exists a correlation among the concepts of objects, scenes, and
events. We empirically demonstrate that the recognition of objects and scenes
substantially contributes to the recognition of events. Meanwhile, we propose
an iterative selection method to identify a subset of object and scene classes,
which help to more efficiently and effectively transfer their deep
representations to event recognition. Specifically, we develop three types of
transferring techniques: (1) initialization-based transferring, (2)
knowledge-based transferring, and (3) data-based transferring. These newly
designed transferring techniques exploit multi-task learning frameworks to
incorporate extra knowledge from other networks and additional datasets into
the training procedure of event CNNs. These multi-task learning frameworks turn
out to be effective in reducing the effect of over-fitting and improving the
generalization ability of the learned CNNs. With OS2E-CNN, we design a
multi-ratio and multi-scale cropping strategy, and propose an end-to-end event
recognition pipeline. We perform experiments on three event recognition
benchmarks: the ChaLearn Cultural Event Recognition dataset, the Web Image
Dataset for Event Recognition (WIDER), and the UIUC Sports Event dataset. The
experimental results show that our proposed algorithm successfully adapts
object and scene representations towards the event dataset and that it achieves
the current state-of-the-art performance on these challenging datasets.