title:
Green Networking in Cellular HetNets: A Unified Radio Resource
  Management Framework with Base Station ON/OFF Switching

abstract:
  In this paper, the problem of energy efficiency in cellular heterogeneous
networks (HetNets) is investigated using radio resource and power management
combined with the base station (BS) ON/OFF switching. The objective is to
minimize the total power consumption of the network while satisfying the
quality of service (QoS) requirements of each connected user. We consider the
case of co-existing macrocell BS, small cell BSs, and private femtocell access
points (FAPs). Three different network scenarios are investigated, depending on
the status of the FAPs, i.e., HetNets without FAPs, HetNets with closed FAPs,
and HetNets with semi-closed FAPs. A unified framework is proposed to
simultaneously allocate spectrum resources to users in an energy efficient
manner and switch off redundant small cell BSs. The high complexity dual
decomposition technique is employed to achieve optimal solutions for the
problem. A low complexity iterative algorithm is also proposed and its
performances are compared to those of the optimal technique. The particularly
interesting case of semi-closed FAPs, in which the FAPs accept to serve
external users, achieves the highest energy efficiency due to increased degrees
of freedom. In this paper, a cooperation scheme between FAPs and mobile
operator is also investigated. The incentives for FAPs, e.g., renewable energy
sharing and roaming prices, enabling cooperation are discussed to be considered
as a useful guideline for inter-operator agreements.


title:
Exploring CP phase in $\tau$-lepton Yukawa coupling in Higgs decays at
  the LHC

abstract:
  We study the prospect of determining the CP violating phase in $\tau$-lepton
Yukawa coupling at the Large Hadron Collider (LHC). While the current run is
already exploring the production of a pair of the third generation $\tau$
leptons from Higgs decay, these measurements are not sensitive enough to
constrain the CP violating phase. In this paper, several CP odd observables are
proposed and analyzed utilizing the dominant channels with the semi-invisible
hadronic decay of $\tau$. Several asymmetries corresponding to the T odd
momentum correlations are also studied and their sensitivities to the CP
violating phase in tau-lepton Yukawa couplings are estimated at 13 TeV LHC with
1000 ${fb}^{-1}$ of integrated luminosity. We also present a novel way to
reconstruct $\tau$ momentum at the LHC utilizing the information of impact
parameter. Finally, we obtain that the asymmetries can be as large as 35$\%$
for a case of maximal CP violation in the $\tau$ Yukawa couplings.


title:
Exactly soluble local bosonic cocycle models, statistical transmutation,
  and simplest time-reversal symmetric topological orders in 3+1D

abstract:
  We propose a generic construction of exactly soluble \emph{local bosonic
models} that realize various topological orders with gappable boundaries. In
particular, we construct an exactly soluble bosonic model that realizes a 3+1D
$Z_2$ gauge theory with emergent fermionic Kramer doublet. We show that the
emergence of such a fermion will cause the nucleation of certain topological
excitations in space-time without pin$^+$ structure. The exactly soluble model
also leads to a statistical transmutation in 3+1D. In addition, we construct
exactly soluble bosonic models that realize 2 types of time-reversal symmetry
enriched $Z_2$-topological orders in 2+1D, and 20 types of simplest
time-reversal symmetry enriched topological (SET) orders which have only one
non-trivial point-like and string-like topological excitations. Many physical
properties of those topological states are calculated using the exactly soluble
models. We find that some time-reversal SET orders have point-like excitations
that carry Kramer doublet -- a fractionalized time-reversal symmetry. We also
find that some $Z_2$ SET orders have string-like excitations that carry
anomalous (non-on-site) $Z_2$ symmetry, which can be viewed as a
fractionalization of $Z_2$ symmetry on strings. Our construction is based on
cochains and cocycles in algebraic topology, which is very versatile. In
principle, it can also realize emergent topological field theory beyond the
twisted gauge theory.


title:
On a class of inverse problems for a heat equation with involution
  perturbation

abstract:
  A class of inverse problems for a heat equation with involution perturbation
is considered using four different boundary conditions, namely, Dirichlet,
Neumann, periodic and anti-periodic boundary conditions. Proved theorems on
existence and uniqueness of solutions to these problems are presented.
Solutions are obtained in the form of series expansion using a set of
appropriate orthogonal basis for each problem. Convergence of the obtained
solutions is also discussed.


title:
Binary Central Stars of Planetary Nebulae Discovered Through Photometric
  Variability V: The Central Stars of HaTr 7 and ESO 330-9

abstract:
  We find the central stars of the planetary nebulae (PNe) HaTr 7 and ESO 330-9
to be close binary systems. Both have orbital periods of less than half a day
and contain an irradiated cool companion to the hot central star. We provide
light curves, spectra, radial velocity curves, orbital periods, and binary
modeling results for both systems. The binary modeling leads to system
parameters, or ranges of allowed parameters for each system. We find that for
the CS of HaTr 7 we need to use limb-darkening values for the cool companion
that are different than the expected values for an isolated star. We also fit
the central star spectrum to determine $\log g$ and temperature values
independent of the binary modeling. For ESO 330-9 we find that based on our
binary modeling the hot central star is most likely a post-RGB star with a mass
of around 0.4 M$_\odot$. We discuss our derived stellar and nebular parameters
in the broader context of close binary central stars and their surrounding PNe.
We also discuss the present status of known or suspected post-RGB stars in PNe.


title:
Nuclearity properties and $C^*$-envelopes of operator system inductive
  limits

abstract:
  We study the relationship between $C^*$-envelopes and inductive limit of
operator systems. Various operator system nuclearity properties of inductive
limit for a sequence of operator systems are also discussed.


title:
Geometric construction of quasiconformal mappings in the Heisenberg
  group

abstract:
  In this paper, we are interested in the construction of quasiconformal
mappings between domains of the Heisenberg group H that minimise a mean
distortion functional. We propose to construct such mappings by considering a
corresponding problem between domains of Poincar\'e half-plane $\mathbb H$. The
first map we construct is a quasiconformal map between two cylinders. We
explain the method used to find it and prove its uniqueness up to rotations.
Then, we give geometric conditions for the construction to be the only way to
find such minimizers. Eventually, as a non trivial example of the
generalisation, we manage to reconstruct the map from \cite{BFP} between two
spherical annuli.


title:
Unidirectional reflectionlessness and invisibility in the TE and TM
  modes of a PT-symmetric slab system

abstract:
  Unidirectional invisibility of a PT-symmetric optical system is of great
interest, but challenging as well since it is infeasible to fulfill it through
wide optical frequency ranges in all angular directions. Accordingly we study
reflectionless and invisible patterns in the TE and TM modes of an optical slab
system consisting of adjacent or separated pair of balanced gain and loss
layers with a gap. We provide a comprehensive study of one of the simplest
experimentally accessible examples of a unidirectionally reflectionless and
invisible PT-symmetric optical slab system. We obtain the physically optimal
conditions for the realization of these phenomena. We derive analytic
expressions, and show that only certain gain amounts restricted to take values
between certain minimum and maximum values give rise to uni/bi-directionally
invisible configurations. The size of gap decides the measure of
reflectionlessness and invisibility parameters, especially on gain value and
incident angle.


title:
On intermediate level sets of two-dimensional discrete Gaussian Free
  Field

abstract:
  We consider the discrete Gaussian Free Field (DGFF) in scaled-up
(square-lattice) versions of suitably regular continuum domains
$D\subset\mathbb C$ and describe the scaling limit, including local structure,
of the level sets at heights growing as a $\lambda$-multiple of the height of
the absolute maximum, for any $\lambda\in(0,1)$. We prove that, in the scaling
limit, the scaled spatial position of a typical point $x$ sampled from this
level set is distributed according to a Liouville Quantum Gravity (LQG) measure
in $D$ at parameter equal $\lambda$-times its critical value, the field value
at $x$ has an exponential intensity measure and the configuration near $x$
reduced by the value at $x$ has the law of a pinned DGFF reduced by a suitable
multiple of the potential kernel. In particular, the law of the total size of
the level set, properly-normalized, converges that that of the total mass of
the LQG measure. This sharpens considerably an earlier conclusion by Daviaud.


title:
Zeroth-order Asynchronous Doubly Stochastic Algorithm with Variance
  Reduction

abstract:
  Zeroth-order (derivative-free) optimization attracts a lot of attention in
machine learning, because explicit gradient calculations may be computationally
expensive or infeasible. To handle large scale problems both in volume and
dimension, recently asynchronous doubly stochastic zeroth-order algorithms were
proposed. The convergence rate of existing asynchronous doubly stochastic
zeroth order algorithms is $O(\frac{1}{\sqrt{T}})$ (also for the sequential
stochastic zeroth-order optimization algorithms). In this paper, we focus on
the finite sums of smooth but not necessarily convex functions, and propose an
asynchronous doubly stochastic zeroth-order optimization algorithm using the
accelerated technology of variance reduction (AsyDSZOVR). Rigorous theoretical
analysis show that the convergence rate can be improved from
$O(\frac{1}{\sqrt{T}})$ the best result of existing algorithms to
$O(\frac{1}{T})$. Also our theoretical results is an improvement to the ones of
the sequential stochastic zeroth-order optimization algorithms.


title:
Groups with finiteness conditions on the lower central series of
  non-normal subgroups

abstract:
  It is known that any locally graded group with finitely many derived
subgroups of non-normal subgroups is finite-by-abelian. This result is
generalized here, by proving that in a locally graded group $G$ the subgroup
$\gamma_{k}(G)$ is finite if the set $\{\gamma_{k}(H)\;|\;H\ntriangleleft G\}$
is finite. Moreover, locally graded groups with finitely many $k$th terms of
lower central series of infinite non-normal subgroups are also completely
described.


title:
Gradient flow formulation and longtime behaviour of a constrained
  Fokker-Planck equation

abstract:
  We consider a Fokker-Planck equation which is coupled to an externally given
time-dependent constraint on its first moment. This constraint introduces a
Lagrange-multiplier which renders the equation nonlocal and nonlinear.
  In this paper we exploit an interpretation of this equation as a Wasserstein
gradient flow of a free energy ${\mathcal{F}}$ on a time-constrained manifold.
First, we prove existence of solutions by passing to the limit in an explicit
Euler scheme obtained by minimizing $h
{\mathcal{F}}(\varrho)+W_2^2(\varrho^0,\varrho)$ among all $\varrho$ satisfying
the constraint for some $\varrho^0$ and time-step $h>0$.
  Second, we provide quantitative estimates for the rate of convergence to
equilibrium when the constraint converges to a constant. The proof is based on
the investigation of a suitable relative entropy with respect to minimizers of
the free energy chosen according to the constraint. The rate of convergence can
be explicitly expressed in terms of constants in suitable logarithmic Sobolev
inequalities.


title:
Extracting Implicit Social Relation for Social Recommendation Techniques
  in User Rating Prediction

abstract:
  Recommendation plays an increasingly important role in our daily lives.
Recommender systems automatically suggest items to users that might be
interesting for them. Recent studies illustrate that incorporating social trust
in Matrix Factorization methods demonstrably improves accuracy of rating
prediction. Such approaches mainly use the trust scores explicitly expressed by
users. However, it is often challenging to have users provide explicit trust
scores of each other. There exist quite a few works, which propose Trust
Metrics to compute and predict trust scores between users based on their
interactions. In this paper, first we present how social relation can be
extracted from users' ratings to items by describing Hellinger distance between
users in recommender systems. Then, we propose to incorporate the predicted
trust scores into social matrix factorization models. By analyzing social
relation extraction from three well-known real-world datasets, which both:
trust and recommendation data available, we conclude that using the implicit
social relation in social recommendation techniques has almost the same
performance compared to the actual trust scores explicitly expressed by users.
Hence, we build our method, called Hell-TrustSVD, on top of the
state-of-the-art social recommendation technique to incorporate both the
extracted implicit social relations and ratings given by users on the
prediction of items for an active user. To the best of our knowledge, this is
the first work to extend TrustSVD with extracted social trust information. The
experimental results support the idea of employing implicit trust into matrix
factorization whenever explicit trust is not available, can perform much better
than the state-of-the-art approaches in user rating prediction.


title: A hybrid model for the population dynamics of periodical cicadas

abstract:
  In addition to their unusually long life cycle, periodical cicadas, {\it
Magicicada} spp., provide an exceptional example of spatially synchronized life
stage phenology in nature. Within regions ("broods") spanning 50,000 to 500,000
km$^2$, adults emerge synchronously every 13 or 17 years. While satiation of
avian predators is believed to be a key component of the ability of these
populations to reach high densities, it is not clear why populations at a
single location remain entirely synchronized. We develop nonlinear Leslie
matrix-type models of periodical cicadas that include predation-driven Allee
effects and competition in addition to reproduction and survival. Using both
analytical and numerical techniques, we demonstrate the observed presence of a
single brood critically depends on the relationship between fecundity,
competition, and predation. We analyze the single-brood, two-brood and
all-brood equilibria in the large life-span limit using a tractable hybrid
approximation to the Leslie matrix model with continuous time competition in
between discrete reproduction events. Within the hybrid model we prove that the
single-brood equilibrium is the only stable equilibrium. This hybrid model
allows us to quantitatively predict population sizes and the range of
parameters for which the stable single-brood and unstable two-brood and
all-brood equilibria exist. The hybrid model yields a good approximation to the
numerical results for the Leslie matrix model for the biologically relevant
case of a 17-year lifespan.


title: Finite resolution effects in p-leader multifractal analysis

abstract:
  Multifractal analysis has become a standard signal processing tool,for which
a promising new formulation, the p-leader multifractal formalism, has recently
been proposed. It relies on novel multiscale quantities, the p-leaders, defined
as local l^p norms of sets of wavelet coefficients located at infinitely many
fine scales. Computing such infinite sums from actual finite-resolution data
requires truncations to the finest available scale, which results in biased
p-leaders and thus in inaccurate estimates of multifractal properties. A
systematic study of such finite-resolution effects leads to conjecture an
explicit and universal closed-form correction that permits an accurate
estimation of scaling exponents. This conjecture is formulated from the
theoretical study of a particular class of models for multifractal processes,
the wavelet-based cascades. The relevance and generality of the proposed
conjecture is assessed by numerical simulations conducted over a large variety
of multifractal processes. Finally, the relevance of the proposed corrected
estimators is demonstrated on the analysis of heart rate variability data.


title:
Three practical field normalised alternative indicator formulae for
  research evaluation

abstract:
  Although altmetrics and other web-based alternative indicators are now
commonplace in publishers' websites, they can be difficult for research
evaluators to use because of the time or expense of the data, the need to
benchmark in order to assess their values, the high proportion of zeros in some
alternative indicators, and the time taken to calculate multiple complex
indicators. These problems are addressed here by (a) a field normalisation
formula, the Mean Normalised Log-transformed Citation Score (MNLCS) that allows
simple confidence limits to be calculated and is similar to a proposal of
Lundberg, (b) field normalisation formulae for the proportion of cited articles
in a set, the Equalised Mean-based Normalised Proportion Cited (EMNPC) and the
Mean-based Normalised Proportion Cited (MNPC), to deal with mostly uncited data
sets, (c) a sampling strategy to minimise data collection costs, and (d) free
unified software to gather the raw data, implement the sampling strategy, and
calculate the indicator formulae and confidence limits. The approach is
demonstrated (but not fully tested) by comparing the Scopus citations, Mendeley
readers and Wikipedia mentions of research funded by Wellcome, NIH, and MRC in
three large fields for 2013-2016. Within the results, statistically significant
differences in both citation counts and Mendeley reader counts were found even
for sets of articles that were less than six months old. Mendeley reader counts
were more precise than Scopus citations for the most recent articles and all
three funders could be demonstrated to have an impact in Wikipedia that was
significantly above the world average.


title: Vector boson production in joint resummation

abstract:
  We study the transverse momentum ($Q_T$) distribution of an electro-weak
vector boson produced via the Drell-Yan mechanism, in the context of joint
resummation. This formalism allows for the simultaneous resummation of
logarithmic contributions that are enhanced at small $Q_T$ and at partonic
threshold. We extend joint resummation to next-to-next-to leading logarithmic
accuracy and we present resummed and matched results for three different
phenomenological setups. In particular, we study the production of a $Z$ boson
at the Tevatron and at the Large Hadron Collider (LHC), as well as the
production of a heavier $Z^\prime$ at the LHC. We compare our findings to
standard $Q_T$ resummation, as well as to fixed-order perturbation theory. We
find that joint resummation provides a moderate (but not flat) correction with
respect to $Q_T$ resummation and it leads to a reduction of the scale
dependence of the results. However, our study also shows some limitations of
this formalism. While the use of joint resummation for $Z$ production at the
Tevatron and $Z^\prime$ production at the LHC appears to be justified, our
implementation suffers from a stronger dependence on power corrections for
processes which are further away from threshold, such as $Z$ production at the
LHC, for which we cannot claim an improvement over standard $Q_T$ resummation.


title: Electronic Properties of Carbon Nanostructures

abstract:
  The carbon nanostructures are perspective materials for the future
applications. This has two reasons: first, the hexagonal atomic structure which
enables a high molecular variability by placing different kinds of the defects
and second, good electronic properties which can be modified for the purpose of
the concrete applications with the help of the defects and of the chemical
ingredients. A lot of kinds of the nanostructures was investigated. Here, the
properties of less common forms will be examined - the graphitic nanocone and
graphitic wormhole.


title: Proportional Rankings

abstract:
  In this paper we extend the principle of proportional representation to
rankings. We consider the setting where alternatives need to be ranked based on
approval preferences. In this setting, proportional representation requires
that cohesive groups of voters are represented proportionally in each initial
segment of the ranking. Proportional rankings are desirable in situations where
initial segments of different lengths may be relevant, e.g., hiring decisions
(if it is unclear how many positions are to be filled), the presentation of
competing proposals on a liquid democracy platform (if it is unclear how many
proposals participants are taking into consideration), or recommender systems
(if a ranking has to accommodate different user types). We study the
proportional representation provided by several ranking methods and prove
theoretical guarantees. Furthermore, we experimentally evaluate these methods
and present preliminary evidence as to which methods are most suitable for
producing proportional rankings.


title: Finite versus infinite: an insufficient shift

abstract:
  The shift graph is defined on the space of infinite subsets of natural
numbers by letting two sets be adjacent if one can be obtained from the other
by removing its least element. We show that this graph is not a minimum among
the graphs of the form $G_{f}$ defined on some Polish space $X$, where two
distinct points are adjacent if one can be obtained from the other by a given
Borel function $f:X\to X$. This answers the primary outstanding question from
\cite{Kechris19991}.


title:
Collaborative Multi-bitrate Video Caching and Processing in Mobile-Edge
  Computing Networks

abstract:
  Recently, Mobile-Edge Computing (MEC) has arisen as an emerging paradigm that
extends cloud-computing capabilities to the edge of the Radio Access Network
(RAN) by deploying MEC servers right at the Base Stations (BSs). In this paper,
we envision a collaborative joint caching and processing strategy for on-demand
video streaming in MEC networks. Our design aims at enhancing the widely used
Adaptive BitRate (ABR) streaming technology, where multiple bitrate versions of
a video can be delivered so as to adapt to the heterogeneity of user
capabilities and the varying of network connection bandwidth. The proposed
strategy faces two main challenges: (i) not only the videos but their
appropriate bitrate versions have to be effectively selected to store in the
caches, and (ii) the transcoding relationships among different versions need to
be taken into account to effectively utilize the processing capacity at the MEC
servers. To this end, we formulate the collaborative joint caching and
processing problem as an Integer Linear Program (ILP) that minimizes the
backhaul network cost, subject to the cache storage and processing capacity
constraints. Due to the NP-completeness of the problem and the impractical
overheads of the existing offline approaches, we propose a novel online
algorithm that makes cache placement and video scheduling decisions upon the
arrival of each new request. Extensive simulations results demonstrate the
significant performance improvement of the proposed strategy over traditional
approaches in terms of cache hit ratio increase, backhaul traffic and initial
access delay reduction.


title:
Understanding and Optimizing the Performance of Distributed Machine
  Learning Applications on Apache Spark

abstract:
  In this paper we explore the performance limits of Apache Spark for machine
learning applications. We begin by analyzing the characteristics of a
state-of-the-art distributed machine learning algorithm implemented in Spark
and compare it to an equivalent reference implementation using the high
performance computing framework MPI. We identify critical bottlenecks of the
Spark framework and carefully study their implications on the performance of
the algorithm. In order to improve Spark performance we then propose a number
of practical techniques to alleviate some of its overheads. However, optimizing
computational efficiency and framework related overheads is not the only key to
performance -- we demonstrate that in order to get the best performance out of
any implementation it is necessary to carefully tune the algorithm to the
respective trade-off between computation time and communication latency. The
optimal trade-off depends on both the properties of the distributed algorithm
as well as infrastructure and framework-related characteristics. Finally, we
apply these technical and algorithmic optimizations to three different
distributed linear machine learning algorithms that have been implemented in
Spark. We present results using five large datasets and demonstrate that by
using the proposed optimizations, we can achieve a reduction in the performance
difference between Spark and MPI from 20x to 2x.


title:
Nonreciprocal microwave signal processing with a Field-Programmable
  Josephson Amplifier

abstract:
  We report on the design and implementation of a Field Programmable Josephson
Amplifier (FPJA) - a compact and lossless superconducting circuit that can be
programmed \textit{in situ} by a set of microwave drives to perform reciprocal
and nonreciprocal frequency conversion and amplification. In this work we
demonstrate four modes of operation: frequency conversion ($-0.5~\mathrm{dB}$
transmission, $-30~\mathrm{dB}$ reflection), circulation ($-0.5~\mathrm{dB}$
transmission, $-30~\mathrm{dB}$ reflection, $30~\mathrm{dB}$ isolation),
phase-preserving amplification (gain $>20~\mathrm{dB}$, $1~\mathrm{photon}$ of
added noise) and directional phase-preserving amplification ($-10~\mathrm{dB}$
reflection, $18~\mathrm{dB}$ forward gain, $8~\mathrm{dB}$ reverse isolation,
$1~\mathrm{photon}$ of added noise). The system exhibits quantitative agreement
with theoretical prediction. Based on a gradiometric Superconducting Quantum
Interference Device (SQUID) with Nb/Al-AlO$_x$/Nb Josephson junctions, the FPJA
is first-order insensitive to flux noise and can be operated without magnetic
shielding at low temperature. Due to its flexible design and compatibility with
existing superconducting fabrication techniques, the FPJA offers a
straightforward route toward on-chip integration with superconducting quantum
circuits such as qubits or microwave optomechanical systems.


title:
Temporal correlations and structural memory effects in break junction
  measurements

abstract:
  We review data analysis techniques that can be used to study temporal
correlations among conductance traces in break junction measurements. We show
that temporal histograms are a simple but efficient tool to check the temporal
homogeneity of the conductance traces, or to follow spontaneous or triggered
temporal variations, like structural modifications in trained contacts, or the
emergence of single-molecule signatures after molecule dosing. To statistically
analyze the presence and the decay time of temporal correlations, we introduce
shifted correlation plots. Finally, we demonstrate that correlations between
opening and subsequent closing traces may indicate structural memory effects in
atomic-sized metallic and molecular junctions. Applying these methods on
measured and simulated gold metallic contacts as a test system, we show that
the surface diffusion induced flattening of the broken junctions helps to
produce statistically independent conductance traces at room temperature,
whereas at low temperature repeating tendencies are observed as long as the
contacts are not closed to sufficiently high conductance setpoints. Applying
opening-closing correlation analysis on Pt-CO-Pt single-molecule junctions, we
demonstrate pronounced contact memory effects and recovery of the molecule for
junctions breaking before atomic chains are formed. However, if chains are
pulled the random relaxation of the chain and molecule after rupture prevents
opening-closing correlations.


title: Hasse Principle Violations for Atkin-Lehner Twists of Shimura Curves

abstract:
  Let $D > 546$ be the discriminant of an indefinite rational quaternion
algebra. We show that there are infinitely many imaginary quadratic fields
$l/\mathbb Q$ such that the twist of the Shimura curve $X^D$ by the main
Atkin-Lehner involution $w_D$ and $l/\mathbb Q$ violates the Hasse Principle
over $\mathbb Q$.


title:
Solving deterministic and stochastic equilibrium problems via augmented
  Walrasian

abstract:
  We described a method to solve deterministic and stochastic Walras
equilibrium models based on associating with the given problem a bifunction
whose maxinf-points turn out to be equilibrium points. The numerical procedure
relies on an augmentation of this bifunction. Convergence of the proposed
procedure is proved by relying on the relevant lopsided convergence. In the
dynamic versions of our models, deterministic and stochastic, we are mostly
concerned with models that equip the agents with a mechanism to transfer goods
from one time period to the next, possibly simply savings, but also allows for
the transformation of goods via production


title: Palindromic widths of graph of groups

abstract:
  We prove that the palindromic width of HNN extension of a group by proper
associated subgroups is infinite. We also prove that the palindromic width of
the amalgamated free product of two groups via a proper subgroup is infinite
(except when the amalgamated subgroup has index two in each of the factors).
Combining these results it follows that the palindromic width of the
fundamental group of a graph of groups is mostly infinite.


title: Nonstandard neutrino interactions at DUNE, T2HK and T2HKK

abstract:
  We study the matter effect caused by nonstandard neutrino interactions (NSI)
in the next generation long-baseline neutrino experiments, DUNE, T2HK and
T2HKK. If multiple NSI parameters are nonzero, the potential of these
experiments to detect CP violation, determine the mass hierarchy and constrain
NSI is severely impaired by degeneracies between the NSI parameters and by the
generalized mass hierarchy degeneracy. In particular, a cancellation between
leading order terms in the appearance channels when $\epsilon_{e\tau} =
\cot\theta_{23} \epsilon_{e\mu}$, strongly affects the sensitivities to these
two NSI parameters at T2HK and T2HKK. We also study the dependence of the
sensitivities on the true CP phase $\delta$ and the true mass hierarchy, and
find that overall DUNE has the best sensitivity to the magnitude of the NSI
parameters, while T2HKK has the best sensitivity to CP violation whether or not
there are NSI. Furthermore, for T2HKK a smaller off-axis angle for the Korean
detector is better overall. We find that due to the structure of the leading
order terms in the appearance channel probabilities, the NSI sensitivities in a
given experiment are similar for both mass hierarchies, modulo the phase change
$\delta \to \delta + 180^\circ$.


title: The threshold for subgroup profiles to agree is $\Omega(\log n)$

abstract:
  For primes $p,e>2$ there are at least $p^{e-3}/e$ groups of order $p^{2e+2}$
that have equal multisets of isomorphism types of proper subgroups and proper
quotient groups, isomorphic character tables, and power maps. This obstructs
recent speculation concerning a path towards efficient isomorphism tests for
general finite groups. These groups have a special purpose polylogarithmic-time
isomorphism test.


title: N-gram Opcode Analysis for Android Malware Detection

abstract:
  Android malware has been on the rise in recent years due to the increasing
popularity of Android and the proliferation of third party application markets.
Emerging Android malware families are increasingly adopting sophisticated
detection avoidance techniques and this calls for more effective approaches for
Android malware detection. Hence, in this paper we present and evaluate an
n-gram opcode features based approach that utilizes machine learning to
identify and categorize Android malware. This approach enables automated
feature discovery without relying on prior expert or domain knowledge for
pre-determined features. Furthermore, by using a data segmentation technique
for feature selection, our analysis is able to scale up to 10-gram opcodes. Our
experiments on a dataset of 2520 samples showed an f-measure of 98% using the
n-gram opcode based approach. We also provide empirical findings that
illustrate factors that have probable impact on the overall n-gram opcodes
performance trends.


title:
Homologie Instanton Symplectique : somme connexe, chirurgie enti\`ere,
  et applications induites par cobordismes

abstract:
  Symplectic instanton homology is an invariant for closed oriented
three-manifolds, defined by Manolescu and Woodward, which conjecturally
corresponds to a symplectic version of a variant of Floer's instanton homology.
In this thesis we study the behaviour of this invariant under connected sum,
Dehn surgery, and four-dimensional cobordisms.
  We prove a K\"unneth-type formula for the connected sum : let $Y$ and $Y'$ be
two closed oriented three-manifolds, we show that the symplectic instanton
homology of their connected sum is isomorphic to the direct sum of the tensor
product of their symplectic instanton homology, and a shift of their torsion
product.
  We define twisted versions of this homology, and then prove an analog of the
Floer exact sequence, relating the invariants of a Dehn surgery triad. We use
this exact sequence to compute the rank of the groups associated to branched
double covers of quasi-alternating links, some plumbings of disc bundles over
spheres, and some integral Dehn surgeries along certain knots.
  We then define invariants for four dimensional cobordisms as maps between the
symplectic instanton homology of the two boundaries. We show that among the
three morphisms in the surgery exact sequence, two are such maps, associated to
the handle-attachment cobordisms. We also give a vanishing criteria for such
maps associated to blow-ups.


title: Graphical description of unitary transformations on hypergraph states

abstract:
  Hypergraph states form a family of multiparticle quantum states that
generalizes cluster states and graph states. We study the action and graphical
representation of nonlocal unitary transformations between hypergraph states.
This leads to a generalization of local complementation and graphical rules for
various gates, such as the CNOT gate and the Toffoli gate. As an application,
we show that already for five qubits local Pauli operations are not sufficient
to check local equivalence of hypergraph states. Furthermore, we use our rules
to construct entanglement witnesses for three-uniform hypergraph states.


title:
Spin polarizabilities and characteristics of spin-one hadrons related
  parity non-conservation in the the Duffin-Kemmer-Petiau formalism

abstract:
  In this paper the method of the relativistically-invariant effective tensor
representation of Lagrangian decomposition and the amplitudes of the two-photon
interaction with hadrons on photon energy is proposed. In the frames
Duffin-Kemmer-Petiau formalism based on this method the spin polarizabilities
of the spin 1 particles, which are characteristic for the spin 1/2 hadrons were
established. Also the authors have obtained the new spin polarizabilities which
are characteristic for spin 1 particles and are bounded with the presence of
the tensor polarizabilities of these particles. It was shown that in the
suggested covariant approach with regard to the crossing symmetry, the spatial
parity, conservation laws and gauge invariance definite spin polarizabilities
and gyrations of spin-1 particles contribute to the expansion of Compton
scattering amplitude, starting from the corresponding orders on photon energy
that is in the agreement with low-energy theorems for that process.


title:
Pion structure from twisted mass lattice QCD down to the physical pion
  mass

abstract:
  We present an investigation of pion structure based on ETMC $N_f=2$ and
$N_f=2+1+1$ twisted mass configurations at maximal twist. We compute the first
moment of the quark momentum fraction of the pion, $\langle x \rangle$ and the
electromagnetic form factor, $F_\pi(Q^2)$. For the latter, momentum is injected
using twisted boundary conditions and the calculation is carried out directly
at the physical pion mass. We find that our data are consistent with vector
meson dominance and experimental data in the region of small momentum transfer.
For $\langle x \rangle$, we find that our chirally and continuum extrapolated
result is compatible with its phenomenological value.


title:
Inspiration or Preparation? Explaining Creativity in Scientific
  Enterprise

abstract:
  Human creativity is the ultimate driving force behind scientific progress.
While the building blocks of innovations are often embodied in existing
knowledge, it is creativity that blends seemingly disparate ideas. Existing
studies have made striding advances in quantifying creativity of scientific
publications by investigating their citation relationships. Yet, little is
known hitherto about the underlying mechanisms governing scientific creative
processes, largely due to that a paper's references, at best, only partially
reflect its authors' actual information consumption. This work represents an
initial step towards fine-grained understanding of creative processes in
scientific enterprise. In specific, using two web-scale longitudinal datasets
(120.1 million papers and 53.5 billion web requests spanning 4 years), we
directly contrast authors' information consumption behaviors against their
knowledge products. We find that, of 59.0\% papers across all scientific
fields, 25.7\% of their creativity can be readily explained by information
consumed by their authors. Further, by leveraging these findings, we develop a
predictive framework that accurately identifies the most critical knowledge to
fostering target scientific innovations. We believe that our framework is of
fundamental importance to the study of scientific creativity. It promotes
strategies to stimulate and potentially automate creative processes, and
provides insights towards more effective designs of information recommendation
platforms.


title: A simple model for the location of Saturn's F ring

abstract:
  In this paper, we introduce a simplified model to understand the location of
Saturn's F ring. The model is a planar restricted five-body problem defined by
the gravitational field of Saturn, including its second zonal harmonic $J_2$,
the shepherd moons Prometheus and Pandora, and Titan. We compute accurate
long-time numerical integrations of (about 2.5 million) non-interacting
test-particles initially located in the region between the orbits of Prometheus
and Pandora, and address whether they escape or remain trapped in this region.
We obtain a wide region of initial conditions of the test particles that remain
confined. We consider a dynamical stability indicator for the test particles'
motion defined by computing the ratio of the standard deviation over the
average value of relevant dynamical quantities, in particular, for the
mean-motion and the semi-major axis. This indicator separates clearly a subset
of trapped initial conditions that appear as very localized stripes in the
initial semi-major axis and eccentricity space for the most stable orbits.
Retaining only these test particles, we obtain a narrow eccentric ring which
displays sharp edges and collective alignment. The semi-major axis of the
accumulation stripes of the stable ring-particles can be associated with
resonances, mostly involving Prometheus' outer Lindblad and co-rotation
resonances, but not exclusively. Pandora's inner Lindblad and co-rotation
resonances as well as low-order three-body resonances typically coincide with
gaps, i.e., regions of instabilities. Comparison of our results with the
nominal data for the F ring shows some correspondence.


title: ImageNet pre-trained models with batch normalization

abstract:
  Convolutional neural networks (CNN) pre-trained on ImageNet are the backbone
of most state-of-the-art approaches. In this paper, we present a new set of
pre-trained models with popular state-of-the-art architectures for the Caffe
framework. The first release includes Residual Networks (ResNets) with
generation script as well as the batch-normalization-variants of AlexNet and
VGG19. All models outperform previous models with the same architecture. The
models and training code are available at
http://www.inf-cv.uni-jena.de/Research/CNN+Models.html and
https://github.com/cvjena/cnn-models


title:
A note and a short survey on supporting lines of compact convex sets in
  the plane

abstract:
  After surveying some known properties of compact convex sets in the plane, we
give a two rigorous proofs of the general feeling that supporting lines can be
slide-turned slowly and continuously. Targeting a wide readership, our
treatment is elementary on purpose.


title:
Inferring Ice Thickness from a Glacier Dynamics Model and Multiple
  Surface Datasets

abstract:
  The future behavior of the West Antarctic Ice Sheet (WAIS) may have a major
impact on future climate. For instance, ice sheet melt may contribute
significantly to global sea level rise. Understanding the current state of WAIS
is therefore of great interest. WAIS is drained by fast-flowing glaciers which
are major contributors to ice loss. Hence, understanding the stability and
dynamics of glaciers is critical for predicting the future of the ice sheet.
Glacier dynamics are driven by the interplay between the topography,
temperature and basal conditions beneath the ice. A glacier dynamics model
describes the interactions between these processes. We develop a hierarchical
Bayesian model that integrates multiple ice sheet surface data sets with a
glacier dynamics model. Our approach allows us to (1) infer important
parameters describing the glacier dynamics, (2) learn about ice sheet
thickness, and (3) account for errors in the observations and the model.
Because we have relatively dense and accurate ice thickness data from the
Thwaites Glacier in West Antarctica, we use these data to validate the proposed
approach. The long-term goal of this work is to have a general model that may
be used to study multiple glaciers in the Antarctic.
  Keywords: ice sheet, glacier dynamics, hierarchical Bayes, Gaussian process,
Markov chain Monte Carlo, West Antarctic ice sheet.


title:
Renormalization Scheme Dependence and the Renormalization Group Beta
  Function

abstract:
  The renormalization that relates a coupling "a" associated with a distinct
renormalization group beta function in a given theory is considered.
Dimensional regularization and mass independent renormalization schemes are
used in this discussion. It is shown how the renormalization $a^*=a+x_2a^2$ is
related to a change in the mass scale $\mu$ that is induced by renormalization.
It is argued that the infrared fixed point is to be a determined in a
renormalization scheme in which the series expansion for a physical quantity
$R$ terminates.


title:
Electron efficiency measurements with the ATLAS detector using 2012 LHC
  proton-proton collision data

abstract:
  This paper describes the algorithms for the reconstruction and identification
of electrons in the central region of the ATLAS detector at the Large Hadron
Collider (LHC). These algorithms were used for all ATLAS results with electrons
in the final state that are based on the 2012 pp collision data produced by the
LHC at $\sqrt{\mathrm{s}}$ = 8 TeV. The efficiency of these algorithms,
together with the charge misidentification rate, is measured in data and
evaluated in simulated samples using electrons from $Z\rightarrow ee$,
$Z\rightarrow ee\gamma$ and $J/\psi \rightarrow ee$ decays. For these
efficiency measurements, the full recorded data set, corresponding to an
integrated luminosity of 20.3 fb$^{-1}$, is used. Based on a new reconstruction
algorithm used in 2012, the electron reconstruction efficiency is 97% for
electrons with $E_\mathrm{T}=15$ GeV and 99% at $E_\mathrm{T} = 50$ GeV.
Combining this with the efficiency of additional selection criteria to reject
electrons from background processes or misidentified hadrons, the efficiency to
reconstruct and identify electrons at the ATLAS experiment varies from 65% to
95%, depending on the transverse momentum of the electron and background
rejection.


title: Electromagnetic-radiation absorption of water

abstract:
  Why does a microwave oven work? How does biological tissue absorb
electromagnetic radiation? Astonishingly, we do not have a definite answer to
these simple questions because the microscopic processes governing the
absorption of electromagnetic waves by water are largely unclarified. This
absorption can be quantified by dielectric loss spectra, which reveal a huge
peak at a frequency of the exciting electric field of about 20 GHz and a
gradual tailing off towards higher frequencies. The microscopic interpretation
of such spectra is highly controversial and various superpositions of
relaxation and resonance processes ascribed to single-molecule or
molecule-cluster motions have been proposed for their analysis. By combining
dielectric, microwave, THz, and far-infrared spectroscopy, here we provide
nearly continuous temperature-dependent broadband spectra of water. Moreover,
we find that corresponding spectra for aqueous solutions reveal the same
features as pure water. However, in contrast to the latter, crystallization in
these solutions can be avoided by supercooling. As different spectral
contributions tend to disentangle at low temperatures, this enables to
deconvolute them when approaching the glass transition under cooling. We find
that the overall spectral development, including the 20 GHz feature (employed
for microwave heating), closely resembles the behavior known for common
supercooled liquids. Thus, water's absorption of electromagnetic waves at room
temperature is not unusual but very similar to that of glass-forming liquids at
elevated temperatures, deep in the low-viscosity liquid regime, and should be
interpreted along similar lines.


title: Support vector regression model for BigData systems

abstract:
  Nowadays Big Data are becoming more and more important. Many sectors of our
economy are now guided by data-driven decision processes. Big Data and business
intelligence applications are facilitated by the MapReduce programming model
while, at infrastructural layer, cloud computing provides flexible and cost
effective solutions for allocating on demand large clusters. In such systems,
capacity allocation, which is the ability to optimally size minimal resources
for achieve a certain level of performance, is a key challenge to enhance
performance for MapReduce jobs and minimize cloud resource costs. In order to
do so, one of the biggest challenge is to build an accurate performance model
to estimate job execution time of MapReduce systems. Previous works applied
simulation based models for modeling such systems. Although this approach can
accurately describe the behavior of Big Data clusters, it is too
computationally expensive and does not scale to large system. We try to
overcome these issues by applying machine learning techniques. More precisely
we focus on Support Vector Regression (SVR) which is intrinsically more robust
w.r.t other techniques, like, e.g., neural networks, and less sensitive to
outliers in the training set. To better investigate these benefits, we compare
SVR to linear regression.


title:
Approximate Support Recovery of Atomic Line Spectral Estimation: A Tale
  of Resolution and Precision

abstract:
  This work investigates the parameter estimation performance of
super-resolution line spectral estimation using atomic norm minimization. The
focus is on analyzing the algorithm's accuracy of inferring the frequencies and
complex magnitudes from noisy observations. When the Signal-to-Noise Ratio is
reasonably high and the true frequencies are separated by $O(\frac{1}{n})$, the
atomic norm estimator is shown to localize the correct number of frequencies,
each within a neighborhood of size $O(\sqrt{{\log n}/{n^3}} \sigma)$ of one of
the true frequencies. Here $n$ is half the number of temporal samples and
$\sigma^2$ is the Gaussian noise variance. The analysis is based on a
primal-dual witness construction procedure. The obtained error bound matches
the Cram\'er-Rao lower bound up to a logarithmic factor. The relationship
between resolution (separation of frequencies) and precision or accuracy of the
estimator is highlighted. Our analysis also reveals that the atomic norm
minimization can be viewed as a convex way to solve a $\ell_1$-norm
regularized, nonlinear and nonconvex least-squares problem to global
optimality.


title:
The 2D percolation transition at finite temperature: The phase boundary
  for in-plane ferromagnetism in $\approx$2 ML Fe/W(110) films

abstract:
  A two dimensional (2D) percolation transition in Fe/W(110) ultrathin magnetic
films occurs when islands in the second atomic layer percolate and resolve a
frustrated magnetic state to produce long-range in-plane ferromagnetic order.
Novel measurements of the magnetic susceptibility $\chi(\theta)$ as the films
are deposited at a constant temperature, allow the long-range percolation
transition to be observed as a sharp peak consistent with a critical phase
transition. The measurements are used to trace the
paramagnetic-to-ferromagnetic phase boundary between the $T=0$ percolation
magnetic transition and the thermal Curie magnetic transition of the undiluted
film. A quantitative comparison to critical scaling theory is made by fitting
the functional form of the phase boundary. The fitted parameters are then used
in theoretical expressions for $\chi(T)$ in the critical region of the
paramagnetic state to provide an excellent, independent representation of the
experimental measurements.


title:
Spin-dependent thermoelectric effects in graphene based superconductor
  junctions

abstract:
  Using the Bogoliubov de-Gennes formalism, we investigate the charge and
spin-dependent thermoelectric effects in superconductor graphene junctions.
Results demonstrate that despite normal-superconductor junctions, there is a
temperature-dependent spin thermopower both in the graphene-based
ferromagnetic-superconductor (F-S) and ferromagnetic-Rashba spin-orbit
region-superconductor (F-RSO-S) junctions. It is also shown that in the
presence of Rashba spin-orbit interaction, the charge and spin-dependent
Seebeck coefficients can reach to their maximum up to 3.5$k_B/e$ and
2.5$k_B/e$, respectively. Remarkably, these coefficients have a zero-point
critical value with respect to magnetic exchange field and chemical potential.
This effect disappears when the Rashba coupling is absent. These results
suggest that graphene-based superconductors can be used in spin-caloritronics
devices.


title: Weakly Isolated Horizons: First order actions and gauge symmetries

abstract:
  Isolated Horizons have played an important role in gravitational physics,
from characterization of the endpoint of black hole mergers to black hole
entropy. With an eye towards a canonical formulation we consider general
relativity in first order form. We focus on two issues: i) The role of the
internal gauge freedom in consistent formulations of the action principle, and
ii) the role a 3+1 decomposition has in the allowed internal gauge. We clarify
how the requirement of well posed variational principles compatible with
general weakly isolated horizons (WIHs) does lead to a partial gauge fixing in
the first order descriptions used previously in the literature. We consider the
Palatini action together with the Holst extension, with and without boundary
terms at the horizon. We show that, for the complete configuration space --with
no gauge fixing--, the Palatini action is differentiable without additional
surface terms at the WIH boundary, but the more general Holst action is not. A
surface term at the horizon --that renders the action for asymptotically flat
configurations differentiable-- makes the Holst action differentiable, but only
if one restricts configuration space and partially reduces the internal Lorentz
gauge. For the second issue, we show that upon performing a 3+1 decomposition
and imposing the time gauge, there is a further gauge reduction of the
Hamiltonian theory in terms of Ashtekar-Barbero variables to a $U(1)$-gauge
theory on the horizon. We show that even when the Holst action is
differentiable without additional surface terms or any gauge fixing for Type I
spherically symmetric (strongly) isolated horizons --and a preferred
foliation--, this result does not go through for more general isolated or
weakly isolated horizons. Our results represent the first comprehensive study
of these issues and clarify some contradictory statements found in the
literature.


title:
Embedding cosmological inflation, axion dark matter and seesaw mechanism
  in a 3-3-1 gauge model

abstract:
  The Peccei-Quinn symmetry is an automatic symmetry of the 3-3-1 gauge models
which, consequently are not plagued with the strong CP problem. Nevertheless,
the axion that emerges from spontaneous breaking of Peccei-Quinn symmetry
cannot be made invisible in the original versions of these models, unless we
extend their scalar sector by an additional neutral scalar singlet. In this
case we show that if, we also add heavy neutrinos in the singlet form, we get
to solve three interesting open questions at once: the real component of the
neutral scalar singlet driving inflation, the axion playing the role of the
dark matter of the universe and standard neutrinos gaining masses through
seesaw mechanism.


title:
Finite blocklength and moderate deviation analysis of hypothesis testing
  of correlated quantum states and application to classical-quantum channels
  with memory

abstract:
  Martingale concentration inequalities constitute a powerful mathematical tool
in the analysis of problems in a wide variety of fields ranging from
probability and statistics to information theory and machine learning. Here we
apply techniques borrowed from this field to quantum hypothesis testing, which
is the problem of discriminating quantum states belonging to two different
sequences $\{\rho_n\}_{n}$ and $\{\sigma_n\}_n$. We obtain upper bounds on the
finite blocklength type II Stein- and Hoeffding errors, which, for i.i.d.
states, are in general tighter than the corresponding bounds obtained by
Audenaert, Mosonyi and Verstraete [Journal of Mathematical Physics, 53(12),
2012]. We also derive finite blocklength bounds and moderate deviation results
for pairs of sequences of correlated states satisfying a (non-homogeneous)
factorization property. Examples of such sequences include Gibbs states of spin
chains with translation-invariant finite range interaction, as well as finitely
correlated quantum states. We apply our results to find bounds on the capacity
of a certain class of classical-quantum channels with memory, which satisfy a
so-called channel factorization property- both in the finite blocklength and
moderate deviation regimes.


title: ArtTrack: Articulated Multi-person Tracking in the Wild

abstract:
  In this paper we propose an approach for articulated tracking of multiple
people in unconstrained videos. Our starting point is a model that resembles
existing architectures for single-frame pose estimation but is substantially
faster. We achieve this in two ways: (1) by simplifying and sparsifying the
body-part relationship graph and leveraging recent methods for faster
inference, and (2) by offloading a substantial share of computation onto a
feed-forward convolutional architecture that is able to detect and associate
body joints of the same person even in clutter. We use this model to generate
proposals for body joint locations and formulate articulated tracking as
spatio-temporal grouping of such proposals. This allows to jointly solve the
association problem for all people in the scene by propagating evidence from
strong detections through time and enforcing constraints that each proposal can
be assigned to one person only. We report results on a public MPII Human Pose
benchmark and on a new MPII Video Pose dataset of image sequences with multiple
people. We demonstrate that our model achieves state-of-the-art results while
using only a fraction of time and is able to leverage temporal information to
improve state-of-the-art for crowded scenes.


title: Against free will in the contemporary natural sciences

abstract:
  The claim of the freedom of the will (understood as an individual who is
transcendent to Nature) in the name of XXth century scientific knowledge,
against the perspective of XVIIIth-XIXth century scientific materialism, is
analysed and refuted in the present paper. The hypothesis of reductionism finds
no obstacle within contemporary natural sciences. Determinism in classical
physics is irrefutable, unless classical physics is itself refuted. From
quantum mechanics, some authors argue that free will is possible because there
is an ontological indeterminism in the natural laws, and that the mind is
responsible for the wave function collapse of matter, which leads to a choice
among the different possibilities for the body. However, here I defend the
opposite thesis because indeterminism does not imply free will, and because the
considerations about an autonomous mind sending orders to the body is against
neuroscience or evolutionary theories about human beings. The quantum theory of
measurement can be interpreted without the intervention of human minds, but
other fields of science cannot contemplate the mentalist scenario. A fatalistic
or materialist view, which denies the possibility of a free will, makes much
more sense in scientific terms.


title:
Resonator with ultra-high length stability as a probe for
  Equivalence-Principle-violating physics

abstract:
  In order to investigate the long-term dimensional stability of matter, we
have operated an optical resonator fabricated from crystalline silicon at
1.5$\,$K continuously for over one year and repeatedly compared its resonance
frequency $f_{res}$ with the frequency of a GPS-monitored hydrogen maser. After
allowing for an initial settling time, over a 163-day interval we found a mean
fractional drift magnitude $|f_{res}^{-1}df_{res}/dt|<1.4\times10^{-20}$/s. The
resonator frequency is determined by the physical length and the speed of
light, and we measure it with respect to the atomic unit of time. Thus, the
bound rules out, to first order, a hypothetical differential effect of the
universe's expansion on rulers and atomic clocks. We also constrain a
hypothetical violation of the principle of Local Position Invariance for
resonator-based clocks and derive bounds for the strength of space-time
fluctuations.


title: Consecutive primes and Beatty sequences

abstract:
  Fix irrational numbers $\alpha,\hat\alpha>1$ of finite type and real numbers
$\beta,\hat\beta\ge 0$, and let $B$ and $\hat B$ be the Beatty sequences $$
B:=(\lfloor\alpha m+\beta\rfloor)_{m\ge 1}\quad\text{and}\quad\hat
B:=(\lfloor\hat\alpha m+\hat\beta\rfloor)_{m\ge 1}. $$ In this note, we study
the distribution of pairs $(p,p^\sharp)$ of consecutive primes for which $p\in
B$ and $p^\sharp\in\hat B$. Under a strong (but widely accepted) form of the
Hardy-Littlewood conjectures, we show that $$ \big|\{p\le x:p\in B\text{ and
}p^\sharp\in\hat B\}\big|=(\alpha\hat\alpha)^{-1}\pi(x)+O\big(x(\log
x)^{-3/2+\epsilon}\big), $$ where $\pi(x)$ is the prime counting function.


title:
On Extensions of supersingular representations of ${\rm
  SL}_2(\mathbb{Q}_p)$

abstract:
  In this note for $p>5$ we calculate the dimensions of ${\rm Ext}^1_{{\rm
SL}_2(\mathbb{Q}_p)}(\tau, \sigma)$ for any two irreducible supersingular
representations $\tau$ and $\sigma$ of ${\rm SL}_2(\mathbb{Q}_p)$.


title: WKB theory of large deviations in stochastic populations

abstract:
  Stochasticity can play an important role in the dynamics of biologically
relevant populations. These span a broad range of scales: from intra-cellular
populations of molecules to population of cells and then to groups of plants,
animals and people. Large deviations in stochastic population dynamics - such
as those determining population extinction, fixation or switching between
different states - are presently in a focus of attention of statistical
physicists. We review recent progress in applying different variants of
dissipative WKB approximation (after Wentzel, Kramers and Brillouin) to this
class of problems. The WKB approximation allows one to evaluate the mean time
and/or probability of population extinction, fixation and switches resulting
from either intrinsic (demographic) noise, or a combination of the demographic
noise and environmental variations, deterministic or random. We mostly cover
well-mixed populations, single and multiple, but also briefly consider
populations on heterogeneous networks and spatial populations. The spatial
setting also allows one to study large fluctuations of the speed of biological
invasions. Finally, we briefly discuss possible directions of future work.


title:
Finding the One: Identifying the Host Galaxies of Gravitational-Wave
  Sources

abstract:
  We explore the localization of compact binary coalescences with ground-based
gravitational-wave detector networks. We simulate tens of thousands of binary
events, and present the distributions of localization sky areas and
localization volumes for a range of sources and network configurations. We show
that generically there exists a tail of particularly well-localized events,
with 2D and 3D localizations of $<10\,\mbox{deg}^2$ and $<1000\,\mbox{Mpc}^3$
achievable, respectively, starting in LIGO/Virgo's third observing run.
Incorporating estimates for the galaxy density and the binary event rates, we
argue that future gravitational-wave detector networks will localize a small
number of binary systems per year to a sufficiently small volume that the
unique host galaxy might be identified. For these golden events, which are
generally the closest and loudest ones, the gravitational-wave detector
networks will point (in 3D; the length of the finger matters) directly at the
source. This will allow for studies of the properties of the host galaxies of
compact binary mergers, which may be an important component in exploring the
formation channels of these sources. In addition, since the host will provide
an independent measurement of the redshift, this will allow the use of the
event as a standard siren to measure cosmology. Furthermore, identification of
a small number of host galaxies can enable deep follow-up searches for
associated electromagnetic transients.


title:
Anomalous Dirac point transport due to extended defects in bilayer
  graphene

abstract:
  Charge transport at the Dirac point in bilayer graphene exhibits two
dramatically different transport states, insulating and metallic, that occur in
apparently otherwise indistinguishable experimental samples. We demonstrate
that the existence of these two transport states has its origin in an interplay
between evanescent modes, that dominate charge transport near the Dirac point,
and disordered configurations of extended defects in the form of partial
dislocations. In a large ensemble of bilayer systems with randomly positioned
partial dislocations, the conductivity distribution $P(\sigma)$ is found to be
strongly peaked at both the insulating and metallic limits. We argue that this
distribution form, that occurs only at the Dirac point, lies at the heart of
the observation of both metallic and insulating states in bilayer graphene.


title: Interpretation of the Neutrino-Nucleus Cross Section

abstract:
  I discuss the near-degeneracy between models of neutrino-nucleus interactions
based on diverse assumptions, and analyze a specific example illustrating how
the different reaction mechanisms taken into account, as well as the
approximations associated with their implementation, may conspire to make the
prediction of two models look similar. I argue that the relevant reaction
mechanisms may be unambiguously identified exploiting the availability of
electron-nucleus scattering data other than inclusive cross sections, providing
detailed information on the nuclear spectral function.


title:
Simple and Scalable Predictive Uncertainty Estimation using Deep
  Ensembles

abstract:
  Deep neural networks (NNs) are powerful black box predictors that have
recently achieved impressive performance on a wide spectrum of tasks.
Quantifying predictive uncertainty in NNs is a challenging and yet unsolved
problem. Bayesian NNs, which learn a distribution over weights, are currently
the state-of-the-art for estimating predictive uncertainty; however these
require significant modifications to the training procedure and are
computationally expensive compared to standard (non-Bayesian) NNs. We propose
an alternative to Bayesian NNs that is simple to implement, readily
parallelizable, requires very little hyperparameter tuning, and yields high
quality predictive uncertainty estimates. Through a series of experiments on
classification and regression benchmarks, we demonstrate that our method
produces well-calibrated uncertainty estimates which are as good or better than
approximate Bayesian NNs. To assess robustness to dataset shift, we evaluate
the predictive uncertainty on test examples from known and unknown
distributions, and show that our method is able to express higher uncertainty
on out-of-distribution examples. We demonstrate the scalability of our method
by evaluating predictive uncertainty estimates on ImageNet.


title:
Transport, Geometrical and Topological Properties of Stealthy Disordered
  Hyperuniform Two-Phase Systems

abstract:
  Disordered hyperuniform many-particle systems have attracted considerable
recent attention. One important class of such systems is the classical ground
states of "stealthy potentials." The degree of order of such ground states
depends on a tuning parameter. Previous studies have shown that these
ground-state point configurations can be counterintuitively disordered,
infinitely degenerate, and endowed with novel physical properties (e.g.,
negative thermal expansion behavior). In this paper, we focus on the disordered
regime in which there is no long-range order, and control the degree of
short-range order. We map these stealthy disordered hyperuniform point
configurations to two-phase media by circumscribing each point with a possibly
overlapping sphere of a common radius $a$: the "particle" and "void" phases are
taken to be the space interior and exterior to the spheres, respectively. We
study certain transport properties of these systems, including the effective
diffusion coefficient of point particles diffusing in the void phase as well as
static and time-dependent characteristics associated with diffusion-controlled
reactions. Besides these effective transport properties, we also investigate
several related structural properties, including pore-size functions, quantizer
error, an order metric, and percolation threshold. We show that these
transport, geometrical and topological properties of our two-phase media
derived from decorated stealthy ground states are distinctly different from
those of equilibrium hard-sphere systems and spatially uncorrelated overlapping
spheres.


title:
Modeling and Control of an Autonomous Three Wheeled Mobile Robot with
  Front Steer

abstract:
  Modeling and control strategies for a design of an autonomous three wheeled
mobile robot with front wheel steer is presented. Although, the three-wheel
vehicle design with front wheel steer is common in automotive vehicles used
often in public transport, but its advantages in navigation and localization of
autonomous vehicles is seldom utilized. We present the system model for such a
robotic vehicle. A PID controller for speed control is designed for the model
obtained and has been implemented in a digital control framework. The
trajectory control framework, which is a challenging task for such a
three-wheeled robot has also been presented in the paper. The derived system
model has been verified using experimental results obtained for the robot
vehicle design. Controller performance and robustness issues have also been
discussed briefly.


title: Domains with invertible-radical factorization

abstract:
  We study those integral domains in which every proper ideal can be written as
an invertible ideal multiplied by a nonempty product of proper radical ideals.


title:
Ab initio optical potentials and nucleon scattering on medium mass
  nuclei

abstract:
  We show the first results for the elastic scattering of neutrons off oxygen
and calcium isotopes obtained from ab initio optical potentials. The potential
is derived using self consistent Green's function theory (SCGF) with the
saturating chiral interaction NNLO$_{\textrm{sat}}$. Our calculations are
compared to available scattering data and show that it is possible to reproduce
low energy scattering observables in medium mass nuclei from first principles.


title: Authoring image decompositions with generative models

abstract:
  We show how to extend traditional intrinsic image decompositions to
incorporate further layers above albedo and shading. It is hard to obtain data
to learn a multi-layer decomposition. Instead, we can learn to decompose an
image into layers that are "like this" by authoring generative models for each
layer using proxy examples that capture the Platonic ideal (Mondrian images for
albedo; rendered 3D primitives for shading; material swatches for shading
detail). Our method then generates image layers, one from each model, that
explain the image. Our approach rests on innovation in generative models for
images. We introduce a Convolutional Variational Auto Encoder (conv-VAE), a
novel VAE architecture that can reconstruct high fidelity images. The approach
is general, and does not require that layers admit a physical interpretation.


title: Generalized RBF kernel for incomplete data

abstract:
  We construct $\bf genRBF$ kernel, which generalizes the classical Gaussian
RBF kernel to the case of incomplete data. We model the uncertainty contained
in missing attributes making use of data distribution and associate every point
with a conditional probability density function. This allows to embed
incomplete data into the function space and to define a kernel between two
missing data points based on scalar product in $L_2$. Experiments show that
introduced kernel applied to SVM classifier gives better results than other
state-of-the-art methods, especially in the case when large number of features
is missing. Moreover, it is easy to implement and can be used together with any
kernel approaches with no additional modifications.


title:
A Nonparametric Latent Factor Model For Location-Aware Video
  Recommendations

abstract:
  We are interested in learning customers' video preferences from their
historic viewing patterns and geographical location. We consider a Bayesian
latent factor modeling approach for this task. In order to tune the complexity
of the model to best represent the data, we make use of Bayesian nonparameteric
techniques. We describe an inference technique that can scale to large
real-world data sets. Finally we show results obtained by applying the model to
a large internal Netflix data set, that illustrates that the model was able to
capture interesting relationships between viewing patterns and geographical
location.


title:
Polynomial robust stability analysis for $H(\textrm{div})$-conforming
  finite elements for the Stokes equations

abstract:
  In this work we consider a discontinuous Galerkin method for the
discretization of the Stokes problem. We use $H(\textrm{div})$-conforming
finite elements as they provide major benefits such as exact mass conservation
and pressure-independent error estimates. The main aspect of this work lies in
the analysis of high order approximations. We show that the considered method
is uniformly stable with respect to the polynomial order $k$ and provides
optimal error estimates $ \| \boldsymbol{u} - \boldsymbol{u}_h \|_{1_h} + \|
\Pi^{Q_h}p-p_h \| \le c \left( h/k \right)^s \| \boldsymbol{u} \|_{s+1} $. To
derive those estimates, we prove a $k$-robust LBB condition. This proof is
based on a polynomial $H^2$-stable extension operator. This extension operator
itself is of interest for the numerical analysis of $C^0$-continuous
discontinuous Galerkin methods for $4^{th}$ order problems.


title: Can tetraneutron be a narrow resonance?

abstract:
  The search for a resonant four-neutron system has been revived thanks to the
recent experimental hints reported in Phys. Rev. Lett. \textbf{116}, 052501
(2016). The existence of such a system would deeply impact our understanding of
nuclear matter and requires a critical investigation. In this work, we study
the existence of a four-neutron resonance in the quasi-stationary formalism
using \textit{ab initio} techniques with various two-body chiral interactions.
We employ the No-Core Gamow Shell Model and the Density Matrix Renormalization
Group method, both supplemented by the use of natural orbitals and a new
identification technique for broad resonances. We demonstrate that while the
energy of the four-neutron system may be compatible with the experimental
value, its width must be larger than the reported upper limit, supporting the
interpretation of the experimental observation as a reaction process too short
to form a nucleus.


title:
Stability of the Chari-Loktev bases for local Weyl modules of
  $\mathfrak{sl}_{r+1}[t]$

abstract:
  We prove stability of the Chari-Loktev bases with respect to the inclusions
of local Weyl modules of the current algebra $\mathfrak{sl}_{r+1}[t]$. This is
conjectured in \cite{RRV2} and the $r=1$ case is proved in \cite{RRV1}. Local
Weyl modules being known to be Demazure submodules in the level one
representations of the affine Lie algebra $\widehat{\mathfrak{sl}_{r+1}}$, we
obtain, by passage to the direct limit, bases for the level one representations
themselves.


title: Asymptotically optimal control for a simplest distributed system

abstract:
  We study the problem of the minimum-time damping of a closed string under a
bounded load, applied at a single fixed point. A constructive feedback control
law is designed, which allows bringing the system to a bounded neighbourhood of
the terminal manifold. The law has the form of the dry friction at the point,
where the load is applied. The motion under the control is governed by a
nonlinear wave equation. The existence and uniqueness of solution of the Cauchy
problem for this equation are proved. The main result is the asymptotic
optimality of the suggested control law.


title:
A Linear System of Differential Equations Related to Vector-Valued Jack
  Polynomials on the Torus

abstract:
  For each irreducible module of the symmetric group $\mathcal{S}_{N}$ there is
a set of parametrized nonsymmetric Jack polynomials in $N$ variables taking
values in the module. These polynomials are simultaneous eigenfunctions of a
commutative set of operators, self-adjoint with respect to two Hermitian forms,
one called the contravariant form and the other is with respect to a
matrix-valued measure on the $N$-torus. The latter is valid for the parameter
lying in an interval about zero which depends on the module. The author in a
previous paper [SIGMA 12 (2016), 033, 27 pages, arXiv:1511.06721] proved the
existence of the measure and that its absolutely continuous part satisfies a
system of linear differential equations. In this paper the system is analyzed
in detail. The $N$-torus is divided into $(N-1)!$ connected components by the
hyperplanes $x_{i}=x_{j}$, $i<j$, which are the singularities of the system.
The main result is that the orthogonality measure has no singular part with
respect to Haar measure, and thus is given by a matrix function times Haar
measure. This function is analytic on each of the connected components.


title:
Capacity Regions of Two-Receiver Broadcast Erasure Channels with
  Feedback and Memory

abstract:
  The two-receiver broadcast packet erasure channel with feedback and memory is
studied. Memory is modeled using a finite-state Markov chain representing a
channel state. Two scenarios are considered: (i) when the transmitter has
causal knowledge of the channel state (i.e., the state is visible), and (ii)
when the channel state is unknown at the transmitter, but observations of it
are available at the transmitter through feedback (i.e., the state is hidden).
In both scenarios, matching outer and inner bounds on the rates of
communication are derived and the capacity region is determined. It is shown
that similar results carry over to channels with memory and delayed feedback
and memoryless compound channels with feedback. When the state is visible, the
capacity region has a single-letter characterization and is in terms of a
linear program. Two optimal coding schemes are devised that use feedback to
keep track of the sent/received packets via a network of queues: a
probabilistic scheme and a deterministic backpressure-like algorithm. The
former bases its decisions solely on the past channel state information and the
latter follows a max-weight queue-based policy. The performance of the
algorithms are analyzed using the frameworks of rate stability in networks of
queues, max-flow min-cut duality in networks, and finite-horizon Lyapunov drift
analysis. When the state is hidden, the capacity region does not have a
single-letter characterization and is, in this sense, uncomputable.
Approximations of the capacity region are provided and two optimal coding
algorithms are outlined. The first algorithm is a probabilistic coding scheme
that bases its decisions on the past L acknowledgments and its achievable rate
region approaches the capacity region exponentially fast in L. The second
algorithm is a backpressure-like algorithm that performs optimally in the long
run.


title: Geometry of Distribution-Constrained Optimal Stopping Problems

abstract:
  We adapt ideas and concepts developed in optimal transport (and its
martingale variant) to give a geometric description of optimal stopping times
of Brownian motion subject to the constraint that the distribution of the
stopping time is a given probability. The methods work for a large class of
cost processes. (At a minimum we need the cost process to be measurable and
adapted. Continuity assumptions can be used to guarantee existence of
solutions.) We find that for many of the cost processes one can come up with,
the solution is given by the first hitting time of a barrier in a suitable
phase space. As a by-product we recover classical solutions of the inverse
first passage time problem / Shiryaev's problem.


title: MCMC Louvain for Online Community Detection

abstract:
  We introduce a novel algorithm of community detection that maintains
dynamically a community structure of a large network that evolves with time.
The algorithm maximizes the modularity index thanks to the construction of a
randomized hierarchical clustering based on a Monte Carlo Markov Chain (MCMC)
method. Interestingly, it could be seen as a dynamization of Louvain algorithm
(see Blondel et Al, 2008) where the aggregation step is replaced by the
hierarchical instrumental probability.


title: Whiteout: Gaussian Adaptive Noise Regularization in Deep Neural Networks

abstract:
  Noise injection (NI) is an efficient technique to mitigate over-fitting in
neural networks (NNs). The Bernoulli NI procedure as implemented in dropout and
shakeout has connections with $l_1$ and $l_2$ regularization for the NN model
parameters. We propose whiteout, a family NI regularization techniques (NIRT)
through injecting adaptive Gaussian noises during the training of NNs. Whiteout
is the first NIRT than imposes a broad range of the $l_{\gamma}$ sparsity
regularization $(\gamma\in(0,2))$ without having to involving the $l_2$
regularization. Whiteout can also be extended to offer regularizations similar
to the adaptive lasso and group lasso. We establish the regularization effect
of whiteout in the framework of generalized linear models with closed-form
penalty terms and show that whiteout stabilizes the training of NNs with
decreased sensitivity to small perturbations in the input. We establish that
the noise-perturbed empirical loss function (pelf) with whiteout converges
almost surely to the ideal loss function (ilf), and the minimizer of the pelf
is consistent for the minimizer of the ilf. We derive the tail bound on the
pelf to establish the practical feasibility in its minimization. The
superiority of whiteout over the Bernoulli NIRTs, dropout and shakeout, in
learning NNs with relatively small-sized training sets and non-inferiority in
large-sized training sets is demonstrated in both simulated and real-life data
sets. This work represents the first in-depth theoretical, methodological, and
practical examination of the regularization effects of both additive and
multiplicative Gaussian NI in deep NNs.


title:
Enabling Bio-Plausible Multi-level STDP using CMOS Neurons with
  Dendrites and Bistable RRAMs

abstract:
  Large-scale integration of emerging nanoscale non-volatile memory devices,
e.g. resistive random-access memory (RRAM), can enable a new generation of
neuromorphic computers that can solve a wide range of machine learning
problems. Such hybrid CMOS-RRAM neuromorphic architectures will result in
several orders of magnitude reduction in energy consumption at a very small
form factor, and herald autonomous learning machines capable of self-adapting
to their environment. However, the progress in this area has been impeded from
the realization that the actual memory devices fall well short of their
expected behavior. In this work, we discuss the challenges associated with
these memory devices and their use in neuromorphic computing circuits, and
propose pathways to overcome these limitations by introducing 'dendritic
learning'.


title: Plane Gossip: Approximating rumor spread in planar graphs

abstract:
  We study the design of schedules for multi-commodity multicast; we are given
an undirected graph $G$ and a collection of source destination pairs, and the
goal is to schedule a minimum-length sequence of matchings that connects every
source with its respective destination. Multi-commodity multicast models a
classic information dissemination problem in networks where the primary
communication constraint is the number of connections that a node can make, not
link bandwidth.
  Multi-commodity multicast is closely related to the problem of finding a
subgraph, $H$, of optimal poise, where the poise is defined as the sum of the
maximum degree of $H$ and the maximum distance between any source-destination
pair in $H$. We first show that the minimum poise subgraph for single-commodity
multicast can be approximated to within a factor of $O(\log k)$ with respect to
the value of a natural LP relaxation in an instance with $k$ terminals. This is
the first upper bound on the integrality gap of the natural LP. Using this
poise result and shortest-path separators in planar graphs, we obtain a
$O(\log^3 k\log n/(\log\log n))$-approximation for multi-commodity multicast
for planar graphs.
  We also study the minimum-time radio gossip problem in planar graphs where a
message from each node must be transmitted to all other nodes under a model
where nodes can broadcast to all neighbors in a single step but only nodes with
a single broadcasting neighbor get a message. We give an $O(\log^2
n)$-approximation for radio gossip in planar graphs breaking previous barriers.
This is the first bound for radio gossip that does not rely on the maximum
degree of the graph.
  Finally, we show that our techniques for planar graphs extend to graphs with
excluded minors. We establish polylogarithmic-approximation algorithms for both
multi-commodity multicast and radio gossip problems in minor-free graphs.


title:
Exact solutions to the (1+1)-dimensional nonlinear Maxwell equations in
  the orthogonal curvilinear coordinates

abstract:
  Characterizing electromagnetic wave propagation in nonlinear and
inhomogeneous media is of great interest from both theoretical and practical
perspectives, even though it is extremely complicated. In fact, it is still an
unresolved issue to find the exact solutions to the nonlinear waves in the
orthogonal curvilinear coordinates. In this paper, we present an analytic
method to handle the problem of electromagnetic waves propagation in
arbitrarily nonlinear and particularly inhomogeneous media without dispersion.
Through the exact solutions of the (1+1)-dimensional nonlinear Maxwell
equations, we discuss some nonlinear phenomena, including cylindrical shock
waves, free nonlinear oscillations, and nonlinear superposition of waves.


title:
$\textit{Herschel}$/SPIRE Observations of Water Production Rates and
  Ortho-to-Para Ratios in Comets

abstract:
  This paper presents $\textit{Herschel}$/SPIRE spectroscopic observations of
several fundamental rotational ortho- and para-water transitions seen in three
Jupiter-family comets and one Oort-cloud comet. Radiative transfer models that
include excitation by collisions with neutrals and electrons, and by solar
infrared radiation were used to produce synthetic emission line profiles
originating in the cometary coma. Ortho-to-para ratios (OPRs) were determined
and used to derived water production rates for all comets. Comparisons are made
with the water production rates derived using an OPR of 3.
  The OPR of three of the comets in this study are much lower than the
statistical equilibrium value of 3, however they agree with observations of
comets 1P/Halley and C/2001 A2 (LINEAR), and the protoplanetary disc TW Hydrae.
These results provide evidence suggesting that OPR variation is caused by
post-sublimation gas-phase nuclear-spin conversion processes. The water
production rates of all comets agree with previous work and, in general,
decrease with increasing nucleocentric offset. This could be due to a
temperature profile, additional water source, or OPR variation in the comae, or
model inaccuracies.


title: ROAM: a Rich Object Appearance Model with Application to Rotoscoping

abstract:
  Rotoscoping, the detailed delineation of scene elements through a video shot,
is a painstaking task of tremendous importance in professional post-production
pipelines. While pixel-wise segmentation techniques can help for this task,
professional rotoscoping tools rely on parametric curves that offer the artists
a much better interactive control on the definition, editing and manipulation
of the segments of interest. Sticking to this prevalent rotoscoping paradigm,
we propose a novel framework to capture and track the visual aspect of an
arbitrary object in a scene, given a first closed outline of this object. This
model combines a collection of local foreground/background appearance models
spread along the outline, a global appearance model of the enclosed object and
a set of distinctive foreground landmarks. The structure of this rich
appearance model allows simple initialization, efficient iterative optimization
with exact minimization at each step, and on-line adaptation in videos. We
demonstrate qualitatively and quantitatively the merit of this framework
through comparisons with tools based on either dynamic segmentation with a
closed curve or pixel-wise binary labelling.


title:
Multi-scale Pressure-balanced Structures in Three-dimensional
  Magnetohydrodynamic Turbulence

abstract:
  Observations of solar wind turbulence indicate the existence of multi-scale
pressure-balanced structures (PBSs) in the solar wind. In this work, we conduct
a numerical simulation to investigate multi-scale PBSs and in particular their
formation in compressive MHD turbulence. By the use of a higher order Godunov
code Athena,a driven compressible turbulence with an imposed uniform guide
field is simulated. The simulation results show that both the magnetic pressure
and the thermal pressure exhibit a turbulent spectrum with a Kolmogorov-like
power law, and that in many regions of the simulation domain they are
anti-correlated. The computed wavelet cross-coherence spectrum of the magnetic
pressure and the thermal pressure, as well as their space series, indicate the
existence of multi-scale PBSs, with the small PBSs being embedded in the large
ones. These multi-scale PBSs are likely to be related with the highly
oblique-propagating slow-mode waves, as the traced multi-scale PBS is found to
be traveling in a certain direction at a speed consistent with that predicted
theoretically for a slow-mode wave propagating in the same direction.


title: Correctness and Performance for Stateful Chained Network Functions

abstract:
  Network functions virtualization (NFV) allows operators to employ NF chains
to realize custom policies, and dynamically add instances to meet demand or for
failover. NFs maintain detailed per- and cross-flow state which needs careful
management, especially during dynamic actions. Crucially, state management
must: (1) ensure NF chain-wide correctness and (2) have good performance. To
this end, we built \name, an NFV framework that leverages an external state
store coupled with state management algorithms and metadata maintenance for
correct operation even under a range of failures. Our evaluation shows that CHC
can support ~10Gbps per-NF throughput and <0.6mus increase in median per-NF
packet processing latency, and chain-wide correctness at little additional
cost.


title: Neutron Monitor Yield Function: New Improved computations

abstract:
  A ground-based neutron monitor is a standard tool to measure cosmic ray
variability near Earth, and it is crucially important to know its yield
function for primary cosmic rays. Although there are several earlier
theoretically calculated yield functions, none of them agrees with experimental
data of latitude surveys of sea-level neutron monitors, thus suggesting for an
inconsistency. A newly computed yield function of the standard sea-level 6NM64
neutron monitor is presented here separately for primary cosmic ray protons and
$\alpha-$particles, the latter representing also heavier species of cosmic
rays. The computations have been done using the GEANT-4 Planetocosmics
Monte-Carlo tool and a realistic curved atmospheric model. For the first time,
an effect of the geometrical correction of the neutron monitor effective area,
related to the finite lateral expansion of the cosmic ray induced atmospheric
cascade, is considered, that was neglected in the previous studies. This
correction slightly enhances the relative impact of higher-energy cosmic rays
(energy above 5--10 GeV/nucleon) in neutron monitor count rate. The new
computation finally resolves the long-standing problem of disagreement between
the theoretically calculated spatial variability of cosmic rays over the globe
and experimental latitude surveys. The newly calculated yield function,
corrected for this geometrical factor, appears fully consistent with the
experimental latitude surveys of neutron monitors performed during three
consecutive solar minima in 1976--77, 1986--87 and 1996--97. Thus, we provide a
new yield function of the standard sea-level neutron monitor 6NM64 that is
validated against experimental data.


title:
New concise upper bounds on quantum violation of general multipartite
  Bell inequalities

abstract:
  Last years, bounds on the maximal quantum violation of general Bell
inequalities were intensively discussed in the literature via different
mathematical tools. In the present paper, we analyze quantum violation of
general Bell inequalities via the LqHV (local quasi hidden variable) modelling
framework, correctly reproducing the probabilistic description of every quantum
correlation scenario. The LqHV mathematical framework allows us to derive for
all d and N a new upper bound (2d-1)^{N-1} on the maximal violation by an
N-qudit state of all general Bell inequalities, also, new upper bounds on the
maximal violation by an N-qudit state of general Bell inequalities for S
settings per site. These new upper bounds essentially improve all the known
precise upper bounds on quantum violation of general multipartite Bell
inequalities. For some S, d and N, the new upper bounds are attainable.


title:
Remarks on the nonvanishing of cohomology groups for perverse sheaves on
  abelian varieties

abstract:
  It is shown that for a perverse sheaf $K$ on an abelian variety $X$ the
integers $i$ for which the cohomology $H^i(X,K)$ does not vanish define an
interval in the number line (under certain conditions on the field of
definition of $K$)


title:
BrainFrame: A node-level heterogeneous accelerator platform for neuron
  simulations

abstract:
  Objective: The advent of High-Performance Computing (HPC) in recent years has
led to its increasing use in brain study through computational models. The
scale and complexity of such models are constantly increasing, leading to
challenging computational requirements. Even though modern HPC platforms can
often deal with such challenges, the vast diversity of the modeling field does
not permit for a single acceleration (or homogeneous) platform to effectively
address the complete array of modeling requirements. Approach: In this paper we
propose and build BrainFrame, a heterogeneous acceleration platform,
incorporating three distinct acceleration technologies, a Dataflow Engine, a
Xeon Phi and a GP-GPU. The PyNN framework is also integrated into the platform.
As a challenging proof of concept, we analyze the performance of BrainFrame on
different instances of a state-of-the-art neuron model, modeling the Inferior-
Olivary Nucleus using a biophysically-meaningful, extended Hodgkin-Huxley
representation. The model instances take into account not only the neuronal-
network dimensions but also different network-connectivity circumstances that
can drastically change application workload characteristics. Main results: The
synthetic approach of three HPC technologies demonstrated that BrainFrame is
better able to cope with the modeling diversity encountered. Our performance
analysis shows clearly that the model directly affect performance and all three
technologies are required to cope with all the model use cases.


title: Is a Trineutron Resonance Lower in Energy than a Tetraneutron Resonance?

abstract:
  We present quantum Monte Carlo calculations of few-neutron systems confined
in external potentials based on local chiral interactions at
next-to-next-to-leading order in chiral effective field theory. The energy and
radial densities for these systems are calculated in different external
Woods-Saxon potentials. We assume that their extrapolation to zero
external-potential depth provides a quantitative estimate of three- and
four-neutron resonances. The validity of this assumption is demonstrated by
benchmarking with an exact diagonalization in the two-body case. We find that
the extrapolated trineutron resonance, as well as the energy for shallow well
depths, is lower than the tetraneutron resonance energy. This suggests that a
three-neutron resonance exists below a four-neutron resonance in nature and is
potentially measurable. To confirm that the relative ordering of three- and
four-neutron resonances is not an artifact of the external confinement, we test
that the odd-even staggering in the helium isotopic chain is reproduced within
this approach. Finally, we discuss similarities between our results and
ultracold Fermi gases.


title: Localization in open quantum systems

abstract:
  In an isolated single-particle quantum system a spatial disorder can induce
Anderson localization. Being a result of interference, this phenomenon is
expected to be fragile in the face of dissipation. Here we show that
dissipation can drive a disordered system into a steady state with tunable
localization properties. This can be achieved with a set of identical
dissipative operators, each one acting non-trivially only on a pair of
neighboring sites. Operators are parametrized by a uniform phase, which
controls selection of Anderson modes contributing to the state. On the
microscopic level, quantum trajectories of a system in a localized steady
regime exhibit intermittent dynamics consisting of long-time sticking events
near selected modes interrupted by jumps between them.


title: Dynamic change-point detection using similarity networks

abstract:
  From a sequence of similarity networks, with edges representing certain
similarity measures between nodes, we are interested in detecting a
change-point which changes the statistical property of the networks. After the
change, a subset of anomalous nodes which compares dissimilarly with the normal
nodes. We study a simple sequential change detection procedure based on
node-wise average similarity measures, and study its theoretical property.
Simulation and real-data examples demonstrate such a simply stopping procedure
has reasonably good performance. We further discuss the faulty sensor isolation
(estimating anomalous nodes) using community detection.


title: Adiabatic Theorem for Quantum Spin Systems

abstract:
  The first proof of the quantum adiabatic theorem was given as early as 1928.
Today, this theorem is increasingly applied in a many-body context, e.g. in
quantum annealing and in studies of topological properties of matter. In this
setup, the rate of variation $\varepsilon$ of local terms is indeed small
compared to the gap, but the rate of variation of the total, extensive
Hamiltonian, is not. Therefore, applications to many-body systems are not
covered by the proofs and arguments in the literature. In this letter, we prove
a version of the adiabatic theorem for gapped ground states of quantum spin
systems, under assumptions that remain valid in the thermodynamic limit. As an
application, we give a mathematical proof of Kubo linear response formula for a
broad class of gapped interacting systems.

categories: math-ph cond-mat.stat-mech math.MP quant-ph