title:
Phase Plane Analysis of Metric-Scalar Torsion Model for Interacting Dark
  Energy

abstract:
  We study the phase space dynamics of the non-minimally coupled
Metric-Scalar-Torsion model in both Jordan and Einstein frames. We specifically
check for the existence of critical points which yield stable solutions
representing the current state of accelerated expansion of the universe fuelled
by the Dark Energy. It is found that such solutions do indeed exist, subject to
constraints on the free model parameter. In fact the evolution of the universe
at these stable critical points exactly matches the evolution given by the
cosmological solutions we found analytically in our previous work on the
subject.


title: Up-down asymmetric tokamaks

abstract:
  Bulk toroidal rotation has proven capable of stabilising both dangerous MHD
modes and turbulence. In this thesis, we explore a method to drive rotation in
large tokamaks: up-down asymmetry in the magnetic equilibrium. We seek to
maximise this rotation by finding optimal up-down asymmetric flux surface
shapes.
  First, we use the ideal MHD model to show that low order external shaping
(e.g. elongation) is best for creating up-down asymmetric flux surfaces
throughout the device. Then, we calculate realistic up-down asymmetric
equilibria for input into nonlinear gyrokinetic turbulence analysis. Analytic
gyrokinetics shows that, in the limit of fast shaping effects, a poloidal tilt
of the flux surface shaping has little effect on turbulent transport. Since
up-down symmetric surfaces do not transport momentum, this invariance to tilt
implies that devices with mirror symmetry about any line in the poloidal plane
will drive minimal rotation. Accordingly, further analytic investigation
suggests that non-mirror symmetric flux surfaces with envelopes created by the
beating of fast shaping effects may create significantly stronger momentum
transport.
  Guided by these analytic results, we carry out local nonlinear gyrokinetic
simulations of non-mirror symmetric flux surfaces created with the lowest
possible shaping effects. First, we consider tilted elliptical flux surfaces
with a Shafranov shift and find little increase in the momentum transport when
the effect of the pressure profile on the equilibrium is included. We then
simulate flux surfaces with independently-tilted elongation and triangularity.
These two-mode configurations show a $60\%$ increase over configurations with
just elongation or triangularity. A rough analytic estimate indicates that the
optimal two-mode configuration can drive rotation with an on-axis Alfven Mach
number of $1.5 \%$ in an ITER-like machine.


title:
Isolario: a Do-ut-des Approach to Improve the Appeal of BGP Route
  Collecting

abstract:
  The incompleteness of data collected from BGP route collecting projects is a
well-known issue which potentially affects every research activity carried out
on the analysis of the Internet inter-domain routing. Recent works explained
that one of the possible solutions is to increase the number of ASes feeding
these projects from the Internet periphery, in order to reveal the hidden
portion of peering connectivity of their upstream providers. The main problem
is that these projects are currently not appealing enough for the network
administrators of these ASes, which are typically not aware of their existence
or not interested enough to share their data. Our contribution is Isolario, a
project based on the do-ut-des principle which aims at persuading network
administrators to share their routing information by offering services in
return, ranging from real-time analyses of the incoming BGP session(s) to
historic analyses of routing reachability. To the best of our knowledge,
Isolario is the only route collecting project publicly available which offers a
set of services to its users to encourage their participation, aiming at
increasing the amount of BGP data publicly available for research purposes.


title: Security Schemes in Vehicular Ad hoc Networks with Cognitive Radios

abstract:
  Vehicular Ad hoc NETworks (VANETs) as the basic infrastructure can facilitate
applications and services of connected vehicles (CVs). Cognitive radio (CR)
technology is an effective supplement and enhancement for VANETs. It can reduce
the impact of deficiency of spectrum resource in VANETs. Although CR-VANETs can
utilize the unused licensed spectrum effectively, the distributed nature of
CR-VANETs may open a door for different attacks, such as spectrum sensing data
falsification attack. In this paper, we propose a joint RSU and vehicle-based
light-weighted cloud for CR-VANETs. Based on this cloud computing model, we
propose a new service named Spectrum Sensing as a Service (SSaaS), which can
perform a cooperative spectrum sensing in CR-VANETs with cloud computing
assistance to secure the spectrum sensing procedure. As a result, a reliable
service can be obtained in CR-VANETs. Simulation results show that the cloud
computing in CR-VANETs can effectively reduce latency and improve the security
of CR-VANETs.


title:
Multi-Scale Anisotropic Fourth-Order Diffusion Improves Ridge and Valley
  Localization

abstract:
  Ridge and valley enhancing filters are widely used in applications such as
vessel detection in medical image computing. When images are degraded by noise
or include vessels at different scales, such filters are an essential step for
meaningful and stable vessel localization. In this work, we propose a novel
multi-scale anisotropic fourth-order diffusion equation that allows us to
smooth along vessels, while sharpening them in the orthogonal direction. The
proposed filter uses a fourth order diffusion tensor whose eigentensors and
eigenvalues are determined from the local Hessian matrix, at a scale that is
automatically selected for each pixel. We discuss efficient implementation
using a Fast Explicit Diffusion scheme and demonstrate results on synthetic
images and vessels in fundus images. Compared to previous isotropic and
anisotropic fourth-order filters, as well as established second-order vessel
enhancing filters, our newly proposed one better restores the centerlines in
all cases.


title: Specht module cohomology and integral designs

abstract:
  We aim to construct an element satisfying Hemmer's combinatorial criterion
for $H^1(\mathfrak{S}_n, S^\lambda)$ to be non-vanishing. In the process, we
discover an unexpected and surprising link between the combinatorial theory of
integral designs and the representation theory of the symmetric groups.


title: A massive momentum-subtraction scheme

abstract:
  A new renormalization scheme is defined for fermion bilinears in QCD at non
vanishing quark masses. This new scheme, denoted RI/mSMOM, preserves the
benefits of the nonexceptional momenta introduced in the RI/SMOM scheme, and
allows a definition of renormalized composite fields away from the chiral
limit. Some properties of the scheme are investigated by performing explicit
one-loop computation in dimensional regularization.


title: The Future of X-ray Reverberation from AGN

abstract:
  XMM-Newton is capable of making a transformational advance in our
understanding of how luminous accreting black holes work, by dedicating about
10 per cent of future observing time to long observations, of order
Megaseconds, to X-ray variable Active Galactic Nuclei (AGN) research. This
would enable reverberation studies, already a commonplace feature of AGN, to
proceed to the next level and follow the behaviour of the powerful dynamic
corona. Such a dedicated legacy programme can only be carried out with
XMM-Newton.


title: Simple Mechanisms for Subadditive Buyers via Duality

abstract:
  We provide simple and approximately revenue-optimal mechanisms in the
multi-item multi-bidder settings. We unify and improve all previous results, as
well as generalize the results to broader cases. In particular, we prove that
the better of the following two simple, deterministic and Dominant Strategy
Incentive Compatible mechanisms, a sequential posted price mechanism or an
anonymous sequential posted price mechanism with entry fee, achieves a constant
fraction of the optimal revenue among all randomized, Bayesian Incentive
Compatible mechanisms, when buyers' valuations are XOS over independent items.
If the buyers' valuations are subadditive over independent items, the
approximation factor degrades to $O(\log m)$, where $m$ is the number of items.
We obtain our results by first extending the Cai-Devanur-Weinberg duality
framework to derive an effective benchmark of the optimal revenue for
subadditive bidders, and then analyzing this upper bound with new techniques.


title:
On optimal H\"older regularity of solutions to the equation $\Delta
  u+b\cdot\nabla u=0$ in two dimensions

abstract:
  We show that for an $L^2$ drift $b$ in two dimensions, if the Hardy norm of
$\text{div }b$ is small, then the weak solutions to $\Delta u+b\cdot\nabla u=0$
have the same optimal H\"older regularity as in the case of divergence-free
drift, that is, $u\in C^{\alpha}_{\text{loc}}$ for all $\alpha\in (0, 1)$.


title: On Kirkwood-Salsburg solutions at criticality

abstract:
  In this work we study the Kirkwood-Salsburg equations of equilibrium
classical continuous systems. We prove a Laurent expansion for the resolvent,
at an eigenvalue of largest modulus of the Kirkwood-Salsburg operator, which is
shown to have a pole of order 1. Then we prove that all correlation functions
have an asymptotic limit as the activity parameter tends to a smallest zero of
the partition function. As corollary, we show that any smallest zero of the
partition function is simple. The main consequence is that in case of positive
or hardcore potentials we find the spectral radius of the Kirkwood-Salsburg
operator and the convergence radius of the solutions.


title:
Complete embedded complex curves in the ball of $\mathbb{C}^2$ can have
  any topology

abstract:
  In this paper we prove that the unit ball $\mathbb{B}$ of $\mathbb{C}^2$
admits complete properly embedded complex curves of any given topological type.
Moreover, we provide examples containing any given closed discrete subset of
$\mathbb{B}$.


title:
Resilience of Energy Infrastructure and Services: Modeling, Data
  Analytics and Metrics

abstract:
  Large scale power failures induced by severe weather have become frequent and
damaging in recent years, causing millions of people to be without electricity
service for days. Although the power industry has been battling weather-induced
failures for years, it is largely unknown how resilient the energy
infrastructure and services really are to severe weather disruptions. What
fundamental issues govern the resilience? Can advanced approaches such as
modeling and data analytics help industry to go beyond empirical methods? This
paper discusses the research to date and open issues related to these
questions. The focus is on identifying fundamental challenges and advanced
approaches for quantifying resilience. In particular, a first aspect of this
problem is how to model large-scale failures, recoveries and impacts, involving
the infrastructure, service providers, customers, and weather. A second aspect
is how to identify generic vulnerability (i.e., non-resilience) in the
infrastructure and services through large-scale data analytics. And, a third is
to understand what resilience metrics are needed and how to develop them.


title: Space-Efficient Hidden Surface Removal

abstract:
  We propose a space-efficient algorithm for hidden surface removal that
combines one of the fastest previous algorithms for that problem with
techniques based on bit manipulation. Such techniques had been successfully
used in other settings, for example to reduce working space for several graph
algorithms. However, bit manipulation is not usually employed in geometric
algorithms because the standard model of computation (the real RAM) does not
support it. For this reason, we first revisit our model of computation to have
a reasonable theoretical framework. Under this framework we show how the use of
a bit representation for the union of triangles, in combination with
rank-select data structures, allows us to implicitly compute the union of $n$
triangles with roughly $O(1)$ bits per union boundary vertex. This results in
an algorithm that uses at most as much space as the previous one, and depending
on the input, can give a reduction of up to a factor $\Theta(\log n)$, while
maintaining the running time.


title: Rayleigh scattering in the transmission spectrum of HAT-P-18b

abstract:
  We have performed ground-based transmission spectroscopy of the hot Jupiter
HAT-P-18b using the ACAM instrument on the William Herschel Telescope (WHT).
Differential spectroscopy over an entire night was carried out at a resolution
of $R \approx 400$ using a nearby comparison star. We detect a bluewards slope
extending across our optical transmission spectrum which runs from 4750 to
9250\AA. The slope is consistent with Rayleigh scattering at the equilibrium
temperature of the planet (852K). We do not detect enhanced sodium absorption,
which indicates that a high-altitude haze is masking the feature and giving
rise to the Rayleigh slope. This is only the second discovery of a Rayleigh
scattering slope in a hot Jupiter atmosphere from the ground, and our study
illustrates how ground-based observations can provide transmission spectra with
precision comparable to the Hubble Space Telescope.


title: The Horn inequalities from a geometric point of view

abstract:
  We give an exposition of the Horn inequalities and their triple role
characterizing tensor product invariants, eigenvalues of sums of Hermitian
matrices, and intersections of Schubert varieties. We follow Belkale's
geometric method, but assume only basic representation theory and algebraic
geometry, aiming for self-contained, concrete proofs. In particular, we do not
assume the Littlewood-Richardson rule nor an a priori relation between
intersections of Schubert cells and tensor product invariants. Our motivation
is largely pedagogical, but the desire for concrete approaches is also
motivated by current research in computational complexity theory and effective
algorithms.

categories: math.AG math-ph math.MP math.RT math.SG quant-ph


title: Automorphy of $\mathrm{GL}_2\otimes \mathrm{GL}_n$ in the self-dual case

abstract:
  In this paper we establish a new case of Langlands functoriality. More
precisely, we prove that the tensor product of the compatible system of Galois
representations attached to a level-1 classical modular form and the compatible
system attached to an n-dimensional RACP automorphic representation of GL_n of
the adeles of Q is automorphic, for any positive integer n, under some natural
hypotheses (namely regularity and irreducibility), and a mild restriction on
the level of the n-dimensional representation.


title: In-medium rho-meson properties in a light-front approach

abstract:
  Properties of \r{ho}-meson in symmetric nuclear matter are investigated
within a light-front constituent quark model (LFCQM), using the in-medium input
calculated by the quark-meson coupling (QMC) model. The LFCQM used here was
previously applied in vacuum to calculate the \r{ho}-meson electromagnetic
properties, namely, charge G 0 , magnetic G 1 , and quadrupole G 2 form
factors, as well as the electromagnetic radius and decay constant. We predict
the in-medium modifications of the \r{ho}-meson electromagnetic form factors in
symmetric nuclear matter.


title:
Quantum phase transitions in Heisenberg $J_1-J_2$ triangular
  antiferromagnet in a magnetic field

abstract:
  We present the zero temperature phase diagram of a Heisenberg antiferromagnet
on a frustrated triangular lattice with nearest neighbor ($J_1$) and next
nearest neighbor ($J_2$) interactions, in a magnetic field. We show that the
classical model has an accidental degeneracy for all $J_2/J_1$ and all fields,
but the degeneracy is lifted by quantum fluctuations. We show that at large
$S$, for $J_2/J_1 <1/8$, quantum fluctuations select the same sequence of three
sublattice co-planar states in a field as for $J_2 =0$, and for $1/8<J_2/J_1
<1$ they select the canted stripe state for all non-zero fields. The transition
between the two states is first order in all fields, with the hysteresis width
set by quantum fluctuations. We study the model with arbitrary $S$, including
$S=1/2$, near the saturation field by exploring the fact that near saturation
the density of bosons is small for all $S$. We show that for $S >1$, the
transition remains first order, with a finite hysteresis width, but for $S=1/2$
and, possibly, $S=1$, there appears a new intermediate phase, likely without a
spontaneous long-range order.


title: Phase co-existence in bidimensional passive and active dumbbell systems

abstract:
  We demonstrate that there is macroscopic co-existence between regions with
hexatic order and regions in the liquid/gas phase over a finite interval of
packing fractions in active dumbbell systems with repulsive power-law
interactions in two dimensions. In the passive limit this interval remains
finite, similarly to what has been found in bidimensional systems of hard and
soft disks. We did not find discontinuous behaviour upon increasing activity
from the passive limit.


title: A (gravitational) toy story

abstract:
  Frequently in Physics, insights and conclusions can be drawn from simple,
idealized models. The discovery of critical behavior in the gravitational
collapse of a massless scalar field leads to the simulation of binary black
holes, from its coalescence to merging and ringdown. We refined a toy model to
explore black hole formation as these events unfold to revisit the instability
of a gravitational kink. We confirmed a conjecture related to a mass gap, for
critical behavior at the threshold of black hole formation. We find a critical
exponent twice the standard value. Surprisingly, this larger critical exponent
is also present in the multiple critical behavior for the black hole formation
from a massless scalar field in asymptotically anti-de Sitter spacetimes. What
is the meaning of this mass gap? Does it have physical relevance?


title:
Le lettere di Enrico Betti (dal 1860 al 1886) conservate presso
  l'Istituto Mazziniano di Genova

abstract:
  The content of this paper is the noted transcription of the 83 letters
written by Enrico Betti between 1860 and 1886 stored at the Istituto
Mazziniano, Museo del Risorgimento in Genova and now available at
www.luigi-cremona.it The letters are addressed to: Luigi Cremona (79), Eugenio
Beltrami (2), Pietro Blaserna (1) and one son of Gaetano Giorgini (1).
  -----
  La corrispondenza qui riprodotta, composta dalle 83 lettere scritte da Enrico
Betti tra il 1860 e il 1886, si trova a Genova (Istituto Mazziniano, Museo del
Risorgimento) e ora anche sul sito www.luigi-cremona.it Destinatari sono: Luigi
Cremona (79), Eugenio Beltrami (2), Pietro Blaserna (1) e uno dei figli di
Gaetano Giorgini (1).


title: The Sphere Packing Bound via Augustin's Method

abstract:
  A sphere packing bound (SPB) with a prefactor that is polynomial in the block
length $n$ is established for codes on a length $n$ product channel $W_{[1,n]}$
assuming that the maximum order $1/2$ Renyi capacity among the component
channels, i.e. $\max_{t\in[1,n]} C_{1/2,W_{t}}$, is $\mathit{O}(\ln n)$. The
reliability function of the discrete stationary product channels with feedback
is bounded from above by the sphere packing exponent. Both results are proved
by first establishing a non-asymptotic SPB. The latter result continues to hold
under a milder stationarity hypothesis.


title:
Robust Design of H-infinity Controller for a Launch Vehicle Autopilot
  against Disturbances

abstract:
  Atmospheric flight phase of a launch vehicle is utilized to evaluate the
performance of an H-infinity controller in the presence of disturbances.
Dynamics of the vehicle is linearly modeled using time-varying parameters. An
operating point was found to design a robust command tracker using H-infinity
control theory that guarantees a stable maneuver. At the end, the controller
was employed on the launch vehicle to assess the capability of control design
on the linearized aerospace vehicle. Experimental results illustrate the
excellent performance of the H-infinity controller and accurate tracking
implemented by the autopilot. Also the robustness of the entire system against
disturbances is demonstrated to be acceptable.


title: Electromagnetic Effects on Strongly Interacting QCD-Matter

abstract:
  In order to study the temperature dependence of the quark-hadron phase
structure and the QCD equation of state in vanishing and finite magnetic field,
the SU(3) Polyakov linear-sigma model is utilized. In mean field approximation,
the dependence of various magnetic properties such as magnetization, magnetic
susceptibility and magnetic catalysis is analyzed in finite magnetic field.
Furthermore, the influences of finite magnetic field on the temperature
dependence of some transport properties (viscosity and conductivity) from
Green-Kubo correlation are characterized.


title: Characterization of Null Geodesics on Kerr Spacetimes

abstract:
  We consider null geodesics in the exterior region of a subextremal Kerr
spacetime. We show that most well-known fundamental properties of null
geodesics can be represented on one plot. In particular, one can see
immediately that the ergoregion and trapping are separated in phase space.
Furthermore, we show that from the point of view of any timelike observer
outside of the black hole, trapping can be understood as a smooth set of
spacelike directions on the celestial sphere of the observer. Finally, we
discuss some applications of these insights.


title: Memory Lens: How Much Memory Does an Agent Use?

abstract:
  We propose a new method to study the internal memory used by reinforcement
learning policies. We estimate the amount of relevant past information by
estimating mutual information between behavior histories and the current action
of an agent. We perform this estimation in the passive setting, that is, we do
not intervene but merely observe the natural behavior of the agent. Moreover,
we provide a theoretical justification for our approach by showing that it
yields an implementation-independent lower bound on the minimal memory capacity
of any agent that implement the observed policy. We demonstrate our approach by
estimating the use of memory of DQN policies on concatenated Atari frames,
demonstrating sharply different use of memory across 49 games. The study of
memory as information that flows from the past to the current action opens
avenues to understand and improve successful reinforcement learning algorithms.


title: The intuitionistic temporal logic of dynamical systems

abstract:
  A dynamical system is a pair $(X,f)$, where $X$ is a topological space and
$f\colon X\to X$ is continuous. Kremer observed that the language of
propositional linear temporal logic can be interpreted over the class of
dynamical systems, giving rise to a natural intuitionistic temporal logic. We
introduce a variant of Kremer's logic, which we denote ${\sf ITL^c}$, and show
that it is decidable. We also show that minimality and Poincar\'e recurrence
are both expressible in the language of ${\sf ITL^c}$, thus providing a
decidable logic expressive enough to reason about non-trivial asymptotic
behavior in dynamical systems.


title: Finiteness of cohomology of local systems on rigid analytic spaces

abstract:
  We prove that the cohomology groups of an etale Q_p-local system on a smooth
proper rigid analytic space are finite-dimensional Q_p-vector spaces, provided
that the base field is either a finite extension of Q_p or an algebraically
closed nonarchimedean field containing Q_p. This result manifests as a special
case of a more general finiteness result for the higher direct images of a
relative (phi, Gamma)-module along a smooth proper morphism of rigid analytic
spaces over a mixed-characterstic nonarchimedean field.


title:
Relativistic orbits around spinning supermassive black holes. Secular
  evolution to 4.5 post-Newtonian order

abstract:
  We derive the secular evolution of the orbital elements of a stellar-mass
object orbiting a spinning massive black hole. We use the post-Newtonian
approximation in harmonic coordinates, with test-body equations of motion for
the conservative dynamics that are valid through 3PN order, including
spin-orbit, quadrupole and (spin)$^2$ effects, and with radiation-reaction
contributions linear in the mass of the body that are valid through 4.5PN
order, including the 4PN damping effects of spin-orbit coupling. The evolution
equations for the osculating orbit elements are iterated to high PN orders
using a two-timescale approach and averaging over orbital timescales. We derive
a criterion for terminating the orbit when its Carter constant drops below a
critical value, whereupon the body plunges across the event horizon at the next
closest approach. The results are valid for arbitrary eccentricities and
arbitrary inclinations. We then analyze numerically the orbits of objects
injected into high-eccentricity orbits via interactions within a surrounding
star cluster, obtaining the number of orbits and the elapsed time between
injection and plunge, and the residual orbital eccentricity at plunge as a
function of inclination. We derive an analytic approximation for the time to
plunge in terms of initial orbital variables. We show that, if the black hole
is spinning rapidly, the flux of gravitational radiation during the final orbit
before plunge may be suppressed by as much as three orders of magnitude if the
orbit is retrograde on the equatorial plane compared to its prograde
counterpart.


title: Nonlocality free wirings and the distinguishability between Bell boxes

abstract:
  Bell nonlocality can be formulated in terms of a resource theory with
local-hidden variable models as resourceless objects. Two such theories are
known, one built upon local operations assisted by shared randomness (LOSRs)
and the other one allowing, in addition, for prior-to-input classical
communication. We show that prior communication, although unable to create
nonlocality, leads to wirings not only beyond LOSRs but also not contained in a
much broader class of (nonlocality-generating) global wirings. Technically,
this is shown by proving that it can improve the statistical distinguishability
between Bell correlations optimised over all fixed measurement choices. This
has implications in nonlocality quantification, and leads us to a natural
universal definition of Bell nonlocality measures. To end up with, we also
consider the statistical strength of nonlocality proofs. We point out some
issues of its standard definition in the resource-theoretic operational
framework, and suggest simple fixes for them. Our findings reveal non-trivial
features of the geometry of the set of wirings and may have implications in the
operational distinguishability of nonlocal behaviors.


title: Unsupervised Learning for Lexicon-Based Classification

abstract:
  In lexicon-based classification, documents are assigned labels by comparing
the number of words that appear from two opposed lexicons, such as positive and
negative sentiment. Creating such words lists is often easier than labeling
instances, and they can be debugged by non-experts if classification
performance is unsatisfactory. However, there is little analysis or
justification of this classification heuristic. This paper describes a set of
assumptions that can be used to derive a probabilistic justification for
lexicon-based classification, as well as an analysis of its expected accuracy.
One key assumption behind lexicon-based classification is that all words in
each lexicon are equally predictive. This is rarely true in practice, which is
why lexicon-based approaches are usually outperformed by supervised classifiers
that learn distinct weights on each word from labeled instances. This paper
shows that it is possible to learn such weights without labeled data, by
leveraging co-occurrence statistics across the lexicons. This offers the best
of both worlds: light supervision in the form of lexicons, and data-driven
classification with higher accuracy than traditional word-counting heuristics.


title:
The SDSS-IV eBOSS: emission line galaxy catalogues at z=0.8 and study of
  systematic errors in the angular clustering

abstract:
  We present two wide-field catalogs of photometrically-selected emission line
galaxies (ELGs) at z=0.8 covering about 2800 deg^2 over the south galactic cap.
The catalogs were obtained using a Fisher discriminant technique described in a
companion paper. The two catalogs differ by the imaging used to define the
Fisher discriminant: the first catalog includes imaging from the Sloan Digital
Sky Survey and the Wide-Field Infrared Survey Explorer, the second also
includes information from the South Galactic Cap U-band Sky Survey (SCUSS).
Containing respectively 560,045 and 615,601 objects, they represent the largest
ELG catalogs available today and were designed for the ELG programme of the
extended Baryon Oscillation Spectroscopic Survey (eBOSS). We study potential
sources of systematic variation in the angular distribution of the selected
ELGs due to fluctuations of the observational parameters. We model the
influence of the observational parameters using a multivariate regression and
implement a weighting scheme that allows effective removal of all of the
systematic errors induced by the observational parameters. We show that
fluctuations in the imaging zero-points of the photometric bands have minor
impact on the angular distribution of objects in our catalogs. We compute the
angular clustering of both catalogs and show that our weighting procedure
effectively removes spurious clustering on large scales. We fit a model to the
small scale angular clustering, showing that the selections have similar biases
of 1.35/D_a(z) and 1.28/D_a(z). Both catalogs are publicly available.


title:
Why the interpretation of "Measuring propagation speed of Coulomb
  fields" stands

abstract:
  The experimental findings reported in our original paper [1]
(arXiv:1211.2913) have been criticized in ref.[2] (arXiv:1606.00710). We
believe that the arguments brought in ref. [2] are not correct and we show
evidence for this.


title:
Strong gravitational lensing --- A probe for extra dimensions and
  Kalb-Ramond field

abstract:
  Strong field gravitational lensing in the context of both higher spacetime
dimensions and in presence of Kalb-Ramond field have been studied. After
developing proper analytical tools to analyze the problem we consider
gravitational lensing in three distinct black hole spacetimes --- (a) four
dimensional black hole in presence of Kalb-Ramond field, (b) brane world black
holes with Kalb-Ramond field and finally (c) black hole solution in $f(T)$
gravity. In all the three situations we have depicted the behavior of three
observables: the asymptotic position approached by the relativistic images, the
angular separation and magnitude difference between the outermost images with
others packed inner ones, both numerically and analytically. Difference between
these scenarios have also been discussed along with possible observational
signatures.


title:
Using inspiration from synaptic plasticity rules to optimize traffic
  flow in distributed engineered networks

abstract:
  Controlling the flow and routing of data is a fundamental problem in many
distributed networks, including transportation systems, integrated circuits,
and the Internet. In the brain, synaptic plasticity rules have been discovered
that regulate network activity in response to environmental inputs, which
enable circuits to be stable yet flexible. Here, we develop a new
neuro-inspired model for network flow control that only depends on modifying
edge weights in an activity-dependent manner. We show how two fundamental
plasticity rules (long-term potentiation and long-term depression) can be cast
as a distributed gradient descent algorithm for regulating traffic flow in
engineered networks. We then characterize, both via simulation and
analytically, how different forms of edge-weight update rules affect network
routing efficiency and robustness. We find a close correspondence between
certain classes of synaptic weight update rules derived experimentally in the
brain and rules commonly used in engineering, suggesting common principles to
both.


title:
Graph states and local unitary transformations beyond local Clifford
  operations

abstract:
  Graph states are quantum states that can be described by a stabilizer
formalism and play an important role in quantum information processing. We
consider the action of local unitary operations on graph states and hypergraph
states. We focus on non-Clifford operations and find for certain
transformations a graphical description in terms of weighted hypergraphs. This
leads to the indentification of hypergraph states that are locally equivalent
to graph states. Moreover, we present a systematic way to construct pairs of
graph states which are equivalent under local unitary operations, but not
equivalent under local Clifford operations. This generates counterexamples to a
conjecture known as LU-LC conjecture. So far, the only counterexamples to this
conjecture were found by random search. Our method reproduces the smallest
known counterexample as a special case and provides a physical interpretation.


title:
Predicting 1p19q Chromosomal Deletion of Low-Grade Gliomas from MR
  Images using Deep Learning

abstract:
  Objective: Several studies have associated codeletion of chromosome arms
1p/19q in low-grade gliomas (LGG) with positive response to treatment and
longer progression free survival. Therefore, predicting 1p/19q status is
crucial for effective treatment planning of LGG. In this study, we predict the
1p/19q status from MR images using convolutional neural networks (CNN), which
could be a noninvasive alternative to surgical biopsy and histopathological
analysis. Method: Our method consists of three main steps: image registration,
tumor segmentation, and classification of 1p/19q status using CNN. We included
a total of 159 LGG with 3 image slices each who had biopsy-proven 1p/19q status
(57 nondeleted and 102 codeleted) and preoperative postcontrast-T1 (T1C) and T2
images. We divided our data into training, validation, and test sets. The
training data was balanced for equal class probability and then augmented with
iterations of random translational shift, rotation, and horizontal and vertical
flips to increase the size of the training set. We shuffled and augmented the
training data to counter overfitting in each epoch. Finally, we evaluated
several configurations of a multi-scale CNN architecture until training and
validation accuracies became consistent. Results: The results of the best
performing configuration on the unseen test set were 93.3% (sensitivity),
82.22% (specificity), and 87.7% (accuracy). Conclusion: Multi-scale CNN with
their self-learning capability provides promising results for predicting 1p/19q
status noninvasively based on T1C and T2 images. Significance: Predicting
1p/19q status noninvasively from MR images would allow selecting effective
treatment strategies for LGG patients without the need for surgical biopsy.


title: A Framework for Analyzing Resparsification Algorithms

abstract:
  A spectral sparsifier of a graph $G$ is a sparser graph $H$ that
approximately preserves the quadratic form of $G$, i.e. for all vectors $x$,
$x^T L_G x \approx x^T L_H x$, where $L_G$ and $L_H$ denote the respective
graph Laplacians. Spectral sparsifiers generalize cut sparsifiers, and have
found many applications in designing graph algorithms. In recent years, there
has been interest in computing spectral sparsifiers in semi-streaming and
dynamic settings. Natural algorithms in these settings often involve repeated
sparsification of a graph, and accumulation of errors across these steps. We
present a framework for analyzing algorithms that perform repeated
sparsifications that only incur error corresponding to a single sparsification
step, leading to better results for many resparsification-based algorithms. As
an application, we show how to maintain a spectral sparsifier in the
semi-streaming setting: We present a simple algorithm that, for a graph $G$ on
$n$ vertices and $m$ edges, computes a spectral sparsifier of $G$ with $O(n
\log n)$ edges in a single pass over $G$, using only $O(n \log n)$ space, and
$O(m \log^2 n)$ total time. This improves on previous best semi-streaming
algorithms for both spectral and cut sparsifiers by a factor of $\log{n}$ in
both space and runtime. The algorithm extends to semi-streaming row sampling
for general PSD matrices. We also use our framework to combine a spectral
sparsification algorithm by Koutis with improved spanner constructions to give
a parallel algorithm for constructing $O(n\log^2{n}\log\log{n})$ sized spectral
sparsifiers in $O(m\log^2{n}\log\log{n})$ time. This is the best known
combinatorial graph sparsification algorithm.The size of the sparsifiers is
only a factor $\log{n}\log\log{n}$ more than ones produced by numerical
routines.


title:
Self-consistent model of a solid for the description of lattice and
  magnetic properties

abstract:
  In the paper a self-consistent theoretical description of the lattice and
magnetic properties of a model system with magnetoelastic interaction is
presented. The dependence of magnetic exchange integrals on the distance
between interacting spins is assumed, which couples the magnetic and the
lattice subsystem. The framework is based on summation of the Gibbs free
energies for the lattice subsystem and magnetic subsystem. On the basis of
minimization principle for the Gibbs energy, a set of equations of state for
the system is derived. These equations of state combine the parameters
describing the elastic properties (relative volume deformation) and the
magnetic properties (magnetization changes).
  The formalism is extensively illustrated with the numerical calculations
performed for a system of ferromagnetically coupled spins $S$=1/2 localized at
the sites of simple cubic lattice. In particular, the significant influence of
the magnetic subsystem on the elastic properties is demonstrated. It manifests
itself in significant modification of such quantities as the relative volume
deformation, thermal expansion coefficient or isothermal compressibility, in
particular, in the vicinity of the magnetic phase transition. On the other
hand, the influence of lattice subsystem on the magnetic one is also evident.
It takes, for example, the form of dependence of the critical (Curie)
temperature and magnetization itself on the external pressure, which is
thoroughly investigated.


title:
The heat kernel for two Aharonov-Bohm solenoids in a uniform magnetic
  field

abstract:
  A non-relativistic quantum model is considered with a point particle carrying
a charge $e$ and moving on the plane pierced by two infinitesimally thin
Aharonov-Bohm solenoids and subjected to a perpendicular uniform magnetic field
of magnitude $B$. Relying on a technique due to Schulman and Sunada which is
applicable to Schr\"odinger operators on multiply connected configuration
manifolds a formula is derived for the corresponding heat kernel. As an
application of the heat kernel formula, an approximate asymptotic expressions
are derived for the lowest eigenvalue lying above the first Landau level and
for the corresponding eigenfunction while assuming that $|eB|R^{2}/(\hbar c)$
is large where $R$ is the distance between the two solenoids.


title: Full and Fractional Counting in Bibliometric Networks

abstract:
  In their study entitled "Constructing bibliometric networks: A comparison
between full and fractional counting," Perianes-Rodriguez, Waltman, & van Eck
(2016; henceforth abbreviated as PWvE) provide arguments for the use of
fractional counting at the network level as different from the level of
publications. Whereas fractional counting in the latter case divides the credit
among co-authors (countries, institutions, etc.), fractional counting at the
network level can normalize the relative weights of links and thereby clarify
the structures in the network. PWvE, however, propose a counting scheme for
fractional counting that is one among other possible ones. Alternative schemes
proposed by Batagelj and Cerin\v{s}ek (2013) and Park, Yoon, & Leydesdorff
(2016; henceforth abbreviated as PYL) are discussed in an appendix. However,
our approach is not correctly identified as identical to their Equation A3.
Here below, we distinguish three approaches analytically; routines for applying
these approaches to bibliometric data are also provided.


title: Hierarchically deflated conjugate residual

abstract:
  We present a progress report on a new class of multigrid solver algorithm
suitable for the solution of 5d chiral fermions such as Domain Wall fermions
and the Continued Fraction overlap. Unlike HDCG \cite{Boyle:2014rwa}, the
algorithm works directly on a nearest neighbour fine operator. The fine
operator used is Hermitian indefinite, for example $\Gamma_5 D_{dwf}$, and
convergence is achieved with an indefinite matrix solver such as outer
iteration based on conjugate residual. As a result coarse space representations
of the operator remain nearest neighbour, giving an 8 point stencil rather than
the 81 point stencil used in HDCG. It is hoped this may make it viable to
recalculate the matrix elements of the little Dirac operator in an HMC
evolution.


title:
A Metaprogramming and Autotuning Framework for Deploying Deep Learning
  Applications

abstract:
  In recent years, deep neural networks (DNNs), have yielded strong results on
a wide range of applications. Graphics Processing Units (GPUs) have been one
key enabling factor leading to the current popularity of DNNs. However, despite
increasing hardware flexibility and software programming toolchain maturity,
high efficiency GPU programming remains difficult: it suffers from high
complexity, low productivity, and low portability. GPU vendors such as NVIDIA
have spent enormous effort to write special-purpose DNN libraries. However, on
other hardware targets, especially mobile GPUs, such vendor libraries are not
generally available. Thus, the development of portable, open, high-performance,
energy-efficient GPU code for DNN operations would enable broader deployment of
DNN-based algorithms. Toward this end, this work presents a framework to enable
productive, high-efficiency GPU programming for DNN computations across
hardware platforms and programming models. In particular, the framework
provides specific support for metaprogramming, autotuning, and DNN-tailored
data types. Using our framework, we explore implementing DNN operations on
three different hardware targets: NVIDIA, AMD, and Qualcomm GPUs. On NVIDIA
GPUs, we show both portability between OpenCL and CUDA as well competitive
performance compared to the vendor library. On Qualcomm GPUs, we show that our
framework enables productive development of target-specific optimizations, and
achieves reasonable absolute performance. Finally, On AMD GPUs, we show initial
results that indicate our framework can yield reasonable performance on a new
platform with minimal effort.


title: Fault-tolerant quantum error detection

abstract:
  Quantum computers will eventually reach a size at which quantum error
correction becomes imperative. Quantum information can be protected from qubit
imperfections and flawed control operations by encoding a single logical qubit
in multiple physical qubits. This redundancy allows the extraction of error
syndromes and the subsequent detection or correction of errors without
destroying the logical state itself through direct measurement. Here we show
the encoding and syndrome measurement of a fault-tolerant logical qubit via an
error detection protocol on four physical qubits, represented by trapped atomic
ions. This demonstrates for the first time the robustness of a fault-tolerant
qubit to imperfections in the very operations used to encode it. The advantage
persists in the face of large added error rates and experimental calibration
errors.


title:
Can Self-Censorship in News Media be Detected Algorithmically? A Case
  Study in Latin America

abstract:
  Censorship in social media has been well studied and provides insight into
how governments stifle freedom of expression online. Comparatively less (or no)
attention has been paid to detecting (self) censorship in traditional media
(e.g., news) using social media as a bellweather. We present a novel
unsupervised approach that views social media as a sensor to detect censorship
in news media wherein statistically significant differences between information
published in the news media and the correlated information published in social
media are automatically identified as candidate censored events. We develop a
hypothesis testing framework to identify and evaluate censored clusters of
keywords, and a new near-linear-time algorithm (called GraphDPD) to identify
the highest scoring clusters as indicators of censorship. We outline extensive
experiments on semi-synthetic data as well as real datasets (with Twitter and
local news media) from Mexico and Venezuela, highlighting the capability to
accurately detect real-world self censorship events.


title:
Towards the understanding of jet substructures and cross sections in
  heavy ion collisions using soft collinear effective theory

abstract:
  The jet quenching phenomenon in heavy ion collisions provides a strong
evidence of the modification of parton shower in the quark-gluon plasma (QGP).
Jet substructure observables can probe various aspects of the jet formation
mechanism. They contain useful information about the QGP and allow us to study
the medium properties in great details. Here we present theoretical
calculations of jet shapes and cross sections in proton-proton and lead-lead
collisions at the LHC using soft-collinear effective theory, with Glauber gluon
interactions in the medium. We find that resumming large logarithms in the jet
substructure calculation is necessary for precise theoretical predictions. The
resummation is performed using renormalization group evolution between
characteristic jet scales. We also find that the medium induces power
corrections to jet shapes. In the end we present the comparison between our
calculations with the recent measurements at the LHC with very good agreement.
Our calculations help initiate precise jet modification studies in heavy ion
collisions.


title: Dense Captioning with Joint Inference and Visual Context

abstract:
  Dense captioning is a newly emerging computer vision topic for understanding
images with dense language descriptions. The goal is to densely detect visual
concepts (e.g., objects, object parts, and interactions between them) from
images, labeling each with a short descriptive phrase. We identify two key
challenges of dense captioning that need to be properly addressed when tackling
the problem. First, dense visual concept annotations in each image are
associated with highly overlapping target regions, making accurate localization
of each visual concept challenging. Second, the large amount of visual concepts
makes it hard to recognize each of them by appearance alone. We propose a new
model pipeline based on two novel ideas, joint inference and context fusion, to
alleviate these two challenges. We design our model architecture in a
methodical manner and thoroughly evaluate the variations in architecture. Our
final model, compact and efficient, achieves state-of-the-art accuracy on
Visual Genome for dense captioning with a relative gain of 73\% compared to the
previous best algorithm. Qualitative experiments also reveal the semantic
capabilities of our model in dense captioning.


title: Statistical Learning for OCR Text Correction

abstract:
  The accuracy of Optical Character Recognition (OCR) is crucial to the success
of subsequent applications used in text analyzing pipeline. Recent models of
OCR post-processing significantly improve the quality of OCR-generated text,
but are still prone to suggest correction candidates from limited observations
while insufficiently accounting for the characteristics of OCR errors. In this
paper, we show how to enlarge candidate suggestion space by using external
corpus and integrating OCR-specific features in a regression approach to
correct OCR-generated errors. The evaluation results show that our model can
correct 61.5% of the OCR-errors (considering the top 1 suggestion) and 71.5% of
the OCR-errors (considering the top 3 suggestions), for cases where the
theoretical correction upper-bound is 78%.


title:
Enforcing Relational Matching Dependencies with Datalog for Entity
  Resolution

abstract:
  Entity resolution (ER) is about identifying and merging records in a database
that represent the same real-world entity. Matching dependencies (MDs) have
been introduced and investigated as declarative rules that specify ER policies.
An ER process induced by MDs over a dirty instance leads to multiple clean
instances, in general. General "answer sets programs" have been proposed to
specify the MD-based cleaning task and its results. In this work, we extend MDs
to "relational MDs", which capture more application semantics, and identify
classes of relational MDs for which the general ASP can be automatically
rewritten into a stratified Datalog program, with the single clean instance as
its standard model.


title:
Inferring Fine-grained Control Flow Inside SGX Enclaves with Branch
  Shadowing

abstract:
  In this paper, we explore a new, yet critical, side-channel attack against
Intel Software Guard Extension (SGX), called a branch shadowing attack, which
can reveal fine-grained control flows (i.e., each branch) of an enclave program
running on real SGX hardware. The root cause of this attack is that Intel SGX
does not clear the branch history when switching from enclave mode to
non-enclave mode, leaving the fine-grained traces to the outside world through
a branch-prediction side channel. However, exploiting the channel is not so
straightforward in practice because 1) measuring branch
prediction/misprediction penalties based on timing is too inaccurate to
distinguish fine-grained control-flow changes and 2) it requires sophisticated
control over the enclave execution to force its execution to the interesting
code blocks. To overcome these challenges, we developed two novel exploitation
techniques: 1) Intel PT- and LBR-based history-inferring techniques and 2)
APIC-based technique to control the execution of enclave programs in a
fine-grained manner. As a result, we could demonstrate our attack by breaking
recent security constructs, including ORAM schemes, Sanctum, SGX-Shield, and
T-SGX. Not limiting our work to the attack itself, we thoroughly studied the
feasibility of hardware-based solutions (e.g., branch history clearing) and
also proposed a software-based countermeasure, called Zigzagger, to mitigate
the branch shadowing attack in practice.


title: Associative Adversarial Networks

abstract:
  We propose a higher-level associative memory for learning adversarial
networks. Generative adversarial network (GAN) framework has a discriminator
and a generator network. The generator (G) maps white noise (z) to data samples
while the discriminator (D) maps data samples to a single scalar. To do so, G
learns how to map from high-level representation space to data space, and D
learns to do the opposite. We argue that higher-level representation spaces
need not necessarily follow a uniform probability distribution. In this work,
we use Restricted Boltzmann Machines (RBMs) as a higher-level associative
memory and learn the probability distribution for the high-level features
generated by D. The associative memory samples its underlying probability
distribution and G learns how to map these samples to data space. The proposed
associative adversarial networks (AANs) are generative models in the
higher-levels of the learning, and use adversarial non-stochastic models D and
G for learning the mapping between data and higher-level representation spaces.
Experiments show the potential of the proposed networks.


title:
Aperiodicity, topological freeness and pure outerness: from group
  actions to Fell bundles

abstract:
  We generalise various non-triviality conditions for group actions to Fell
bundles over discrete groups and prove several implications between them. We
also study sufficient criteria for the reduced section C*-algebra C_r(B) of a
Fell bundle (B_g) to be strongly purely infinite. If the unit fibre A=B_e
contains an essential ideal that is separable or of Type I, then the Fell
bundle is aperiodic if and only if it is topologically free. If, in addition,
G=Z or G=Z/p for a square-free number p, then these equivalent conditions are
satisfied if and only if A detects ideals in C_r(B), if and only if A^+ \ {0}
supports C_r(B) in the Cuntz sense. For G as above and arbitrary A, C_r(B) is
simple if and only if the Fell bundle B is minimal and pointwise outer. In
general, B is aperiodic if and only if each of its non-trivial fibres has a
non-trivial Connes spectrum. If G is finite or if A contains an essential ideal
that is of Type I or simple, then aperiodicity is equivalent to pointwise pure
outerness.


title:
Signatures of internal rotation discovered in the Kepler data of five
  slowly pulsating B stars

abstract:
  Massive stars are important building blocks of the Universe, and their
stellar structure and evolution models are fundamental cornerstones of various
fields in modern astrophysics. The precision of these models is limited by our
lack of understanding of various internal mixing processes that significantly
influence the lifetime of these objects (e.g. core overshoot, chemical mixing,
or the internal differential rotation). Our goal is to calibrate models by
extending the sample of available seismic studies of slowly pulsating B (SPB)
stars, providing input for theoretical modelling efforts that will deliver
precise constraints on the parameters describing the internal mixing processes
in these objects. We used spectral synthesis and disentangling techniques to
derive fundamental parameters and to determine precise orbital parameters from
high-resolution spectra. We employed custom masks to construct light curves
from the Kepler pixel data and used standard time-series analysis tools to
construct a set of significant frequencies for each target. These sets were
first filtered from combination frequencies, and then screened for period
spacing patterns. We detect gravity mode period series of modes of the same
degree l with consecutive radial order n in four new and one revisited SPB
star. These predominantly prograde dipole series (covering ~10-40 radial
orders) are influenced by rotation and carry signatures of chemical mixing
processes. Our spectroscopic analysis, in addition to placing each object
inside the SPB instability strip and identifying KIC 4930889 as an SB2 binary,
reveals that KIC 11971405 is a fast rotator that shows very weak Be signatures.
Together with the observed photometric outbursts this illustrates that this Be
star is a fast rotating SPB star. We hypothesise that the outbursts might be
connected to its very densely compressed oscillation spectrum.


title: VM Scaling and Load Balancing via Cost Optimal MDP Solution

abstract:
  We address a cost optimization problem faced by a user who runs instances of
applications in a remote cloud configuration constructed of multiple virtual
machines (VMs). Each VM runs a single application instance which can execute
tasks specific to that application. Managing the VMs involves a sophisticated
trade-off between cloud-related demands, which are expressed by the provisional
costs of leased cloud resources, and exogenous cost demands expressed by
service revenues that are typically bound to SLAs. The internal costs may
include VM deployment/termination cost, and VM lease cost. The exogenous costs
refer to rewards accumulated due to the successfully accomplished tasks being
run by each application instance. In the case where the SLA restricts
performance to a certain load level at each VM, tasks incoming at VMs that
reached that level are rejected. Rejections cause fines deducted against the
rewards. The performance level is also quantified, namely, by means of a delay
cost, according to the average delay experienced by tasks. Typical examples for
specific applications which fall within this class of problems include handling
of scientific worklflows and network functioning virtualization (NFV). We model
this problem by cost-optimal load balancing to a queuing system with a flexible
number of queues, where a queue (VM) can be deployed, can have a task directed
to it and can be terminated. We analyze the system by Markov decision process
(MDP) and numerically solve it to find the optimal policy, which captures the
aforementioned costs and performance constraints. Within this constrained
framework, we also investigate the impact of average VM deployment time. We
show that the optimal policy possesses decision thresholds which depend on
several parameters. We validate policies found by MDP, through directing an
exogenous computational tasks flow to a set-up implemented on AWS.


title:
Influence of the fluid structure on the binding potential: comparing
  liquid drop profiles from density functional theory with results from
  mesoscopic theory

abstract:
  For a film of liquid on a solid surface, the binding potential $g(h)$ gives
the free energy as a function of the film thickness $h$ and also the closely
related structural disjoining pressure $\Pi = - \partial g / \partial h$. The
wetting behaviour of the liquid is encoded in the binding potential and the
equilibrium film thickness corresponds to the value at the minimum of $g(h)$.
Here, the method we developed in [J. Chem. Phys. 142, 074702 (2015)], and
applied with a simple discrete lattice-gas model, is used with continuum
density functional theory (DFT) to calculate the binding potential for a
Lennard-Jones fluid and other simple liquids. The DFT used is based on
fundamental measure theory and so incorporates the influence of the layered
packing of molecules at the surface and the corresponding oscillatory density
profile. The binding potential is frequently input in mesoscale models from
which liquid drop shapes and even dynamics can be calculated. Here we show that
the equilibrium droplet profiles calculated using the mesoscale theory are in
good agreement with the profiles calculated directly from the microscopic DFT.
For liquids composed of particles where the range of the attraction is much
less than the diameter of the particles, we find that at low temperatures
$g(h)$ decays in an oscillatory fashion with increasing $h$, leading to highly
structured terraced liquid droplets.


title:
Power operations for $\text{H}\underline{\mathbb{F}}_2$ and a cellular
  construction of $\text{BP}\mathbf{R}$

abstract:
  We study some power operations for ordinary $C_2$-equivariant homology with
coefficients in the constant Mackey functor $\underline{\mathbb{F}}_2$. In
addition to a few foundational results, we calculate the action of these power
operations on a $C_2$-equivariant dual Steenrod algebra. As an application, we
give a cellular construction of the $C_2$ equivariant Brown-Peterson spectrum
$\text{BP}\mathbf{R}$ and deduce its slice tower.


title:
Maximization of the Spectral Gap for Chemical Graphs by means of a
  Solution to a Mixed Integer Semidefinite Program

abstract:
  In this paper we analyze the spectral gap of a weighted graph which is the
difference between the smallest positive and largest negative eigenvalue of its
adjacency matrix. Such a graph can represent e.g. a chemical organic molecule.
Our goal is to construct a new graph by bridging two given weighted graphs over
a bipartite graph. The aim is to maximize the spectral gap with respect to a
bridging graph. To this end, we construct a mixed integer semidefinite program
for maximization of the spectral gap and compute it numerically.


title: Arithmetic patches, weak tangents, and dimension

abstract:
  We investigate the relationships between several classical notions in
arithmetic combinatorics and geometry including: the presence (or lack of)
arithmetic progressions (or patches in dimensions $\geq 2$); the structure of
tangent sets; and the Assouad dimension.
  We begin by extending a recent result of Dyatlov and Zahl by showing that a
set cannot contain arbitrarily large arithmetic progressions (patches) if it
has Assouad dimension strictly smaller than the ambient spatial dimension.
Seeking a partial converse, we go on to prove that having Assouad dimension
equal to the ambient spatial dimension is equivalent to having weak tangents
with non-empty interior and to `asymptotically' containing arbitrarily large
arithmetic patches.
  We present some applications of our results concerning sets of integers,
which include a weak solution to the Erd\"os-Tur\'an conjecture on arithmetic
progressions.


title:
Rising Novelties on Evolving Networks: Recent Behavior Dominant and
  Non-Dominant Model

abstract:
  Novelty attracts attention like popularity. Hence predicting novelty is as
important as popularity. Novelty is the side effect of competition and aging in
evolving systems. Recent behavior or recent link gain in networks plays an
important role in emergence or trend. We exploited this wisdom and came up with
two models considering different scenarios and systems. Where recent behavior
dominates over total behavior (total link gain) in the first one, and recent
behavior is as important as total behavior for future link gain in second one.
It suppose that random walker walks on a network and can jump to any node, the
probablity of jumping or making connection to other node is based on which node
is recently more active or receiving more links. In our assumption random
walker can also jump to node which is already popular but recently not popular.
We are able to predict rising novelties or popular nodes which is generally
suppressed under preferential attachment effect. To show performance of our
model we have conducted experiments on four real data sets namely, MovieLens,
Netflix, Facebook and Arxiv High Energy Physics paper citation. For testing our
model we used four information retrieval indices namely Precision, Novelty,
Area Under Receiving Operating Characteristic(AUC) and Kendal's rank
correlation coefficient. We have used four benchmark models for validating our
proposed models. Although our model doesn't perform better in all the cases
but, it has theoretical significance in working better for recent behavior
dominant systems.


title: Sampled Image Tagging and Retrieval Methods on User Generated Content

abstract:
  Traditional image tagging and retrieval algorithms have limited value as a
result of being trained with heavily curated datasets. These limitations are
most evident when arbitrary search words are used that do not intersect with
training set labels. Weak labels from user generated content (UGC) found in the
wild (e.g., Google Photos, FlickR, etc.) have an almost unlimited number of
unique words in the metadata tags. Prior work on word embeddings successfully
leveraged unstructured text with large vocabularies, and our proposed method
seeks to apply similar cost functions to open source imagery. Specifically, we
train a deep learning image tagging and retrieval system on large scale, user
generated content (UGC) using sampling methods and joint optimization of word
embeddings. By using the Yahoo! FlickR Creative Commons (YFCC100M) dataset,
such an approach builds robustness to common unstructured data issues that
include but are not limited to irrelevant tags, misspellings, multiple
languages, polysemy, and tag imbalance. As a result, the final proposed
algorithm will not only yield comparable results to state of the art in
conventional image tagging, but will enable new capability to train algorithms
on large, scale unstructured text in the YFCC100M dataset and outperform cited
work in zero-shot capability.


title:
Catch'Em All: Locating Multiple Diffusion Sources in Networks with
  Partial Observations

abstract:
  This paper studies the problem of locating multiple diffusion sources in
networks with partial observations. We propose a new source localization
algorithm, named Optimal-Jordan-Cover (OJC). The algorithm first extracts a
subgraph using a candidate selection algorithm that selects source candidates
based on the number of observed infected nodes in their neighborhoods. Then, in
the extracted subgraph, OJC finds a set of nodes that "cover" all observed
infected nodes with the minimum radius. The set of nodes is called the Jordan
cover, and is regarded as the set of diffusion sources. Considering the
heterogeneous susceptible-infected-recovered (SIR) diffusion in the Erdos-Renyi
(ER) random graph, we prove that OJC can locate all sources with probability
one asymptotically with partial observations. OJC is a polynomial-time
algorithm in terms of network size. However, the computational complexity
increases exponentially in $m,$ the number of sources. We further propose a
low-complexity heuristic based on the K-Means for approximating the Jordan
cover, named Approximate-Jordan-Cover (AJC). Simulations on random graphs and
real networks demonstrate that both AJC and OJC significantly outperform other
heuristic algorithms.


title:
High efficiency measurement of all orbital angular momentum modes in a
  light beam

abstract:
  We present an experimental demonstration of a Laguerre-Gauss (LG) spectrum
measurement technique using variable focus lenses that is able to measure the
strengths of all modes present in an unknown, incoming light beam with the
highest possible efficiency. The experiment modifies the classical projective,
phase flattening technique by including a variable sized pinhole and a two
electronic lens variable imaging system that is tuned for each mode to give the
highest possible detection efficiency irrespective of the beam waist of LG mode
chosen for the projection/decomposition. The modified experiment preserves the
orthogonality between the modes with only a 4 \% cross-talk so that
superposition states may also be detected efficiently. Our experiment results
show efficient detection of OAM vortex beams with topological charge, $l$,
values ranging from 0 to 4 with various different beam waists chosen for the
decomposition.


title: Voxel datacubes for 3D visualization in Blender

abstract:
  The growth of computational astrophysics and complexity of multidimensional
datasets evidences the need for new versatile visualization tools for both
analysis and presentation of the data. In this work we show how to use the open
source software Blender as a 3D visualization tool to study and visualize
numerical simulation results, focusing on astrophysical hydrodynamic
experiments. With a datacube as input, the software can generate a volume
rendering of the 3D data, show the evolution of a simulation in time, and do a
fly-around camera animation to highlight the points of interest. We explain the
process to import simulation outputs into Blender using the Voxel Data format,
and how to set up a visualization scene in the software interface. This method
allows scientists to perform a complementary visual analysis of their data, and
display their results in an appealing way, both for outreach and science
presentations.


title: Probing magnetic fields with Square Kilometre array and its precursors

abstract:
  Origin of magnetic fields, its structure and effects on dynamical processes
in stars to galaxies are not well understood. Lack of a direct probe has
hampered its study. The first phase of Square Kilometre Array (SKA-I), will
have more than an order of magnitude higher sensitivity than existing radio
telescopes. In this contribution, we discuss specific science cases that are of
interest to the Indian community concerned with astrophysical turbulence and
magnetic fields. The SKA-I will allow observations of a large number of
background sources with detectable polarisation and measure their Faraday
depths (FDs) through the Milky Way, other galaxies and their circum-galactic
medium. This will probe line-of-sight magnetic fields in these objects well and
provide field configurations. Detailed comparison of observational data with
models which consider various processes giving rise to field amplification and
maintenance will then be possible. Such observations will also provide the
coherence scale of the fields and measure its random component. Measuring the
random component is important to characterise turbulence in the medium.
Observations of FDs with redshift will provide important information on
magnetic field evolution as a function of redshift. The background sources
could also be used to probe magnetic fields and its coherent scale in galaxy
clusters and in bridges formed between interacting galaxies. Other than FDs,
sensitive observations of synchrotron emission from galaxies will provide
complimentary information on their magnetic field strengths in the sky plane.
The core shift measurements of AGNs can provide more precise measurements of
magnetic field very close (<pc) to the black hole and its evolution. The low
band of SKA-I will also be useful to study circularly polarized emission from
Sun and comparing various models of field configurations with observations.


title: Newforms with rational coefficients

abstract:
  We consider the set of classical newforms with rational coefficients and no
complex multiplication. We study the distribution of quadratic-twist classes of
these forms with respect to weight $k$ and minimal level $N$. We conjecture
that for each weight $k \geq 6$, there are only finitely many classes. In large
weights, we make this conjecture effective: in weights $18 \leq k \leq 24$, all
classes have $N \leq 30$, in weights $26 \leq k \leq 50$, all classes have $N
\in \{2,6\}$, and in weights $k \geq 52$, there are no classes at all. We study
some of the newforms appearing on our conjecturally complete list in more
detail, especially in the cases $N=2$, $3$, $4$, $6$, and $8$, where formulas
can be kept nearly as simple as those for the classical case $N=1$.


title:
Decomposition matrices and blocks for the symplectic blob algebra over
  the complex field

abstract:
  We find the blocks for the symplectic blob algebra for all specialisations of
the parameters over the complex numbers. We determine Gram determinants for the
cell modules. We also show that the algebra is semisimple over the complex
numbers unless at least one of the quantisation parameters, or the sum or
difference of two of the parameters is integral or $q$ is a root of unity. We
also find decomposition numbers in many of the $q$ generic cases.


title:
Kernel Cross-View Collaborative Representation based Classification for
  Person Re-Identification

abstract:
  Person re-identification aims at the maintenance of a global identity as a
person moves among non-overlapping surveillance cameras. It is a hard task due
to different illumination conditions, viewpoints and the small number of
annotated individuals from each pair of cameras (small-sample-size problem).
Collaborative Representation based Classification (CRC) has been employed
successfully to address the small-sample-size problem in computer vision.
However, the original CRC formulation is not well-suited for person
re-identification since it does not consider that probe and gallery samples are
from different cameras. Furthermore, it is a linear model, while appearance
changes caused by different camera conditions indicate a strong nonlinear
transition between cameras. To overcome such limitations, we propose the Kernel
Cross-View Collaborative Representation based Classification (Kernel X-CRC)
that represents probe and gallery images by balancing representativeness and
similarity nonlinearly. It assumes that a probe and its corresponding gallery
image are represented with similar coding vectors using individuals from the
training set. Experimental results demonstrate that our assumption is true when
using a high-dimensional feature vector and becomes more compelling when
dealing with a low-dimensional and discriminative representation computed using
a common subspace learning method. We achieve state-of-the-art for rank-1
matching rates in two person re-identification datasets (PRID450S and GRID) and
the second best results on VIPeR and CUHK01 datasets.


title: A matricial view of the Karpelevi\v{c} Theorem

abstract:
  The question of the exact region in the complex plane of the possible single
eigenvalues of all $n$-by-$n$ stochastic matrices was raised by Kolmogorov in
1937 and settled by Karpelevi\v{c} in 1951 after a partial result by Dmitriev
and Dynkin in 1946. The Karpelevi\v{c} result is unwieldy, but a simplification
was given by {\DJ}okovi\'c in 1990 and Ito in 1997. The Karpelevi\v{c} region
is determined by a set of boundary arcs each connecting consecutive roots of
unity of order less than $n$. It is shown here that each of these arcs is
realized by a single, somewhat simple, parametrized stochastic matrix. Other
observations are made about the nature of the arcs and several further
questions are raised. The doubly stochastic analog of the Karpelevi\v{c} region
remains open, but a conjecture about it is amplified.


title:
Combining micro- and macroscopic probes to untangle single-ion and
  spatial exchange anisotropies in a $S = 1$ quantum antiferromagnet

abstract:
  The magnetic ground state of the quasi-one-dimensional spin-1
antiferromagnetic chain is sensitive to the relative sizes of the single-ion
anisotropy ($D$) and the intrachain ($J$) and interchain ($J'$) exchange
interactions. The ratios $D/J$ and $J'/J$ dictate the material's placement in
one or other of three competing phases: a Haldane gapped phase, a quantum
paramagnet and an XY-ordered state, with a quantum critical point at their
junction. We have identified [Ni(HF)$_2$(pyz)$_2]$SbF$_6$, where pyz =
pyrazine, as a candidate in which this behavior can be explored in detail.
Combining neutron scattering (elastic and inelastic) in applied magnetic fields
of up to 10~tesla and magnetization measurements in fields of up to 60~tesla
with numerical modeling of experimental observables, we are able to obtain
accurate values of all of the parameters of the Hamiltonian [$D = 13.3(1)$~K,
$J = 10.4(3)$~K and $J' = 1.4(2)$~K], despite the polycrystalline nature of the
sample. Density-functional theory calculations result in similar couplings ($J
= 9.2$~K, $J' = 1.8$~K) and predict that the majority of the total spin
population of resides on the Ni(II) ion, while the remaining spin density is
delocalized over both ligand types. The general procedures outlined in this
paper permit phase boundaries and quantum-critical points to be explored in
anisotropic systems for which single crystals are as yet unavailable.


title: Measuring Sample Quality with Diffusions

abstract:
  Stein's method for measuring convergence to a continuous target distribution
relies on an operator characterizing the target and Stein factor bounds on the
solutions of an associated differential equation. While such operators and
bounds are readily available for a diversity of univariate targets, few
multivariate targets have been analyzed. We introduce a new class of
characterizing operators based on Ito diffusions and develop explicit
multivariate Stein factor bounds for any target with a fast-coupling Ito
diffusion. As example applications, we develop computable and
convergence-determining diffusion Stein discrepancies for log-concave,
heavy-tailed, and multimodal targets and use these quality measures to select
the hyperparameters of biased Markov chain Monte Carlo (MCMC) samplers, compare
random and deterministic quadrature rules, and quantify bias-variance tradeoffs
in approximate MCMC. Our results establish a near-linear relationship between
diffusion Stein discrepancies and Wasserstein distances, improving upon past
work even for strongly log-concave targets. The exposed relationship between
Stein factors and Markov process coupling may be of independent interest.


title: RhoanaNet Pipeline: Dense Automatic Neural Annotation

abstract:
  Reconstructing a synaptic wiring diagram, or connectome, from electron
microscopy (EM) images of brain tissue currently requires many hours of manual
annotation or proofreading (Kasthuri and Lichtman, 2010; Lichtman and Sanes,
2008; Seung, 2009). The desire to reconstruct ever larger and more complex
networks has pushed the collection of ever larger EM datasets. A cubic
millimeter of raw imaging data would take up 1 PB of storage and present an
annotation project that would be impractical without relying heavily on
automatic segmentation methods. The RhoanaNet image processing pipeline was
developed to automatically segment large volumes of EM data and ease the burden
of manual proofreading and annotation. Based on (Kaynig et al., 2015), we
updated every stage of the software pipeline to provide better throughput
performance and higher quality segmentation results. We used state of the art
deep learning techniques to generate improved membrane probability maps, and
Gala (Nunez-Iglesias et al., 2014) was used to agglomerate 2D segments into 3D
objects.
  We applied the RhoanaNet pipeline to four densely annotated EM datasets, two
from mouse cortex, one from cerebellum and one from mouse lateral geniculate
nucleus (LGN). All training and test data is made available for benchmark
comparisons. The best segmentation results obtained gave
$V^\text{Info}_\text{F-score}$ scores of 0.9054 and 09182 for the cortex
datasets, 0.9438 for LGN, and 0.9150 for Cerebellum.
  The RhoanaNet pipeline is open source software. All source code, training
data, test data, and annotations for all four benchmark datasets are available
at www.rhoana.org.


title:
A topological lower bound for the chromatic number of a special family
  of graphs

abstract:
  For studying topological obstructions to graph colorings, Hom-complexes were
introduced by Lov\'{a}sz. A graph $T$ is called a test graph if for every graph
$H$, the $k$-connectedness of $|Hom(T, H)|$ implies $\chi (H)\geq k + 1 +
\chi(T)$. The proof of the famous Kneser conjecture is based on the fact that
$\mathcal{K}_2$, the complete graph on $2$ vertices, is a test graph. This
result was extended to all complete graphs by Babson and Kozlov. Their proof is
based on generalized nerve lemma and discrete Morse theory.
  In this paper, we propose a new topological lower bound for the chromatic
number of a special family of graphs. As an application of this bound, we give
a new proof of the well-known fact that complete graphs and even cycles are
test graphs.


title: On the origin of C$_4$H and CH$_3$OH in protostellar envelopes

abstract:
  The formation pathways of different types of organic molecules in
protostellar envelopes and other regions of star formation are subjects of
intense current interest. We here present observations of C$_4$H and CH$_3$OH,
tracing two distinct groups of interstellar organic molecules, toward 16
protostars in the Ophiuchus and Corona Australis molecular clouds. Together
with observations in the literature, we present C$_4$H and CH$_3$OH data from
single-dish observations of 40 embedded protostars. We find no correlation
between the C$_4$H and CH$_3$OH column densities in this large sample. Based on
this lack of correlation, a difference in line profiles between C$_4$H and
CH$_3$OH, and previous interferometric observations of similar sources, we
propose that the emission from these two molecules is spatially separated, with
the CH$_3$OH tracing gas that has been transiently heated to high ($\sim$70-100
K) temperatures, and the C$_4$H tracing the cooler large-scale envelope where
CH$_4$ molecules have been liberated from ices. These results provide insight
in the differentiation between hot corino and warm carbon-chain chemistry in
embedded protostars.


title:
Externally heated protostellar cores in the Ophiuchus star-forming
  region

abstract:
  We present APEX 218 GHz observations of molecular emission in a complete
sample of embedded protostars in the Ophiuchus star-forming region. To study
the physical properties of the cores, we calculate H$_2$CO and c-C$_3$H$_2$
rotational temperatures, both of which are good tracers of the kinetic
temperature of the molecular gas. We find that the H$_2$CO temperatures range
between 16 K and 124 K, with the highest H$_2$CO temperatures toward the hot
corino source IRAS 16293-2422 (69-124 K) and the sources in the $\rho$ Oph A
cloud (23-49 K) located close to the luminous Herbig Be star S 1, which
externally irradiates the $\rho$ Oph A cores. On the other hand, the
c-C$_3$H$_2$ rotational temperature is consistently low (7-17 K) in all
sources. Our results indicate that the c-C$_3$H$_2$ emission is primarily
tracing more shielded parts of the envelope whereas the H$_2$CO emission (at
the angular scale of the APEX beam; 3600 au in Ophiuchus) mainly traces the
outer irradiated envelopes, apart from in IRAS 16293-2422, where the hot corino
emission dominates. In some sources, a secondary velocity component is also
seen, possibly tracing the molecular outflow.


title: Detecting pulsars in the Galactic centre

abstract:
  Although high-sensitivity surveys have revealed a number of highly dispersed
pulsars in the inner Galaxy, none have so far been found in the Galactic centre
(GC) region, which we define to be within a projected distance of 1~pc from
Sgr~A*. This null result is surprising given that several independent lines of
evidence predict a sizable population of neutron stars in the region. Here, we
present a detailed analysis of both the canonical and millisecond pulsar
populations in the GC and consider free-free absorption and multi-path
scattering to be the two main sources of flux density mitigation. We
demonstrate that the sensitivity limits of previous surveys are not sufficient
to detect GC pulsar population, and investigate the optimum observing frequency
for future surveys. Depending on the degree of scattering and free-free
absorption in the GC, current surveys constrain the size of the potentially
observable population (i.e.~those beaming towards us) to be up to 52 canonical
pulsars and 10000 millisecond pulsars. We find that the optimum frequency for
future surveys is in the range of 9--13~GHz. We also predict that future deeper
surveys with the Square Kilometer array will probe a significant portion of the
existing radio pulsar population in the GC.


title:
A velocity tracking approach for the Data Assimilation problem in blood
  flow simulations

abstract:
  Several advances have been made in Data Assimilation techniques applied to
blood flow modeling. Typically, idealized boundary conditions, only verified in
straight parts of the vessel, are assumed. We present a general approach, based
on a Dirichlet boundary control problem, that may potentially be used in
different parts of the arterial system. The relevance of this method appears
when computational reconstructions of the 3D domains, prone to be considered
sufficiently extended, are either not possible, or desirable, due to
computational costs. Based on taking a fully unknown velocity profile as the
control, the approach uses a discretize then optimize methodology to solve the
control problem numerically. The methodology is applied to a realistic 3D
geometry representing a brain aneurysm. The results show that this DA approach
may be preferable to a pressure control strategy, and that it can significantly
improve the accuracy associated to typical solutions obtained using idealized
velocity profiles.


title: Block decomposition of permutations and Schur-positivity

abstract:
  The block number of a permutation is the maximal number of components in its
expression as a direct sum. We show that, for $321$-avoiding permutations, the
set of left-to-right maxima has the same distribution when the block number is
assumed to be $k$ as when the last descent of the inverse is assumed to be at
position $n - k$. This result is analogous to the Foata-Sch\"utzenberger
equi-distribution theorem, and implies that the quasi-symmetric generating
function of descent set over $321$-avoiding permutations with a prescribed
number of blocks is Schur-positive.


title: Lower bounds for 2-query LCCs over large alphabet

abstract:
  A locally correctable code (LCC) is an error correcting code that allows
correction of any arbitrary coordinate of a corrupted codeword by querying only
a few coordinates. We show that any {\em zero-error} $2$-query locally
correctable code $\mathcal{C}: \{0,1\}^k \to \Sigma^n$ that can correct a
constant fraction of corrupted symbols must have $n \geq \exp(k/\log|\Sigma|)$.
We say that an LCC is zero-error if there exists a non-adaptive corrector
algorithm that succeeds with probability $1$ when the input is an uncorrupted
codeword. All known constructions of LCCs are zero-error.
  Our result is tight upto constant factors in the exponent. The only previous
lower bound on the length of 2-query LCCs over large alphabet was
$\Omega\left((k/\log|\Sigma|)^2\right)$ due to Katz and Trevisan (STOC 2000).
Our bound implies that zero-error LCCs cannot yield $2$-server private
information retrieval (PIR) schemes with sub-polynomial communication. Since
there exists a $2$-server PIR scheme with sub-polynomial communication (STOC
2015) based on a zero-error $2$-query locally decodable code (LDC), we also
obtain a separation between LDCs and LCCs over large alphabet.
  For our proof of the result, we need a new decomposition lemma for directed
graphs that may be of independent interest. Given a dense directed graph $G$,
our decomposition uses the directed version of Szemer\'edi regularity lemma due
to Alon and Shapira (STOC 2003) to partition almost all of $G$ into a constant
number of subgraphs which are either edge-expanding or empty.


title:
Multiple-View Spectral Clustering for Group-wise Functional Community
  Detection

abstract:
  Functional connectivity analysis yields powerful insights into our
understanding of the human brain. Group-wise functional community detection
aims to partition the brain into clusters, or communities, in which functional
activity is inter-regionally correlated in a common manner across a group of
subjects. In this article, we show how to use multiple-view spectral clustering
to perform group-wise functional community detection. In a series of
experiments on 291 subjects from the Human Connectome Project, we compare three
versions of multiple-view spectral clustering: MVSC (uniform weights), MVSCW
(weights based on subject-specific embedding quality), and AASC (weights
optimized along with the embedding) with the competing technique of Joint
Diagonalization of Laplacians (JDL). Results show that multiple-view spectral
clustering not only yields group-wise functional communities that are more
consistent than JDL when using randomly selected subsets of individual brains,
but it is several orders of magnitude faster than JDL.


title:
Ground-state properties of even and odd Magnesium isotopes in a
  symmetry-conserving approach

abstract:
  We present a self-consistent theory for odd nuclei with exact blocking and
particle number and angular momentum projection. The demanding treatment of the
pairing correlations in a variation-after-projection approach as well as the
explicit consideration of the triaxial deformation parameters in a projection
after variation method, together with the use of the finite-range
density-dependent Gogny force, provides an excellent tool for the description
of odd-even and even-even nuclei. We apply the theory to the Magnesium isotopic
chain and obtain an outstanding description of the ground-state properties, in
particular binding energies, odd-even mass differences, mass radii and
electromagnetic moments among others.


title: Diameter and Automorphisms of Gelfand-Tsetlin Polytopes

abstract:
  We determine the diameter of the 1-skeleton and the combinatorial
automorphism group of any Gelfand-Tsetlin polytope GT$_{\lambda}$ associated to
an integer partition $\lambda.$


title:
Universal main magnetic focus ion source: A new tool for laboratory
  research of astrophysics and Tokamak microplasma

abstract:
  A novel room-temperature ion source for the production of atomic ions in
electron beam within wide ranges of electron energy and current density is
developed. The device can operate both as conventional Electron Beam Ion
Source/Trap (EBIS/T) and novel Main Magnetic Focus Ion Source. The ion source
is suitable for generation of the low-, medium- and high-density microplasma in
steady state, which can be employed for investigation of a wide range of
physical problems in ordinary university laboratory, in particular, for
microplasma simulations relevant to astrophysics and ITER reactor. For the
electron beam characterized by the incident energy $E_e = 10$ keV, the current
density $j_e \sim 20$ kA/cm$^2$ and the number density $n_e \sim 2 \times
10^{13}$ cm$^{-3}$ were achieved experimentally. For $E_e \sim 60$ keV, the
value of electron number density $n_e \sim 10^{14}$ cm$^{-3}$ is feasible. The
efficiency of the novel ion source for laboratory astrophysics significantly
exceeds that of other existing warm and superconducting EBITs. A problem of the
K-shell electron ionization of heavy and superheavy elements is also discussed.


title: Cosmic Bell Test: Measurement Settings from Milky Way Stars

abstract:
  Bell's theorem states that some predictions of quantum mechanics cannot be
reproduced by a local-realist theory. That conflict is expressed by Bell's
inequality, which is usually derived under the assumption that there are no
statistical correlations between the choices of measurement settings and
anything else that can causally affect the measurement outcomes. In previous
experiments, this "freedom of choice" was addressed by ensuring that selection
of measurement settings via conventional "quantum random number generators" was
space-like separated from the entangled particle creation. This, however, left
open the possibility that an unknown cause affected both the setting choices
and measurement outcomes as recently as mere microseconds before each
experimental trial. Here we report on a new experimental test of Bell's
inequality that, for the first time, uses distant astronomical sources as
"cosmic setting generators." In our tests with polarization-entangled photons,
measurement settings were chosen using real-time observations of Milky Way
stars while simultaneously ensuring locality. Assuming fair sampling for all
detected photons, and that each stellar photon's color was set at emission, we
observe statistically significant $\gtrsim 7.31 \sigma$ and $\gtrsim 11.93
\sigma$ violations of Bell's inequality with estimated $p$-values of $ \lesssim
1.8 \times 10^{-13}$ and $\lesssim 4.0 \times 10^{-33}$, respectively, thereby
pushing back by $\sim$600 years the most recent time by which any local-realist
influences could have engineered the observed Bell violation.


title: Robust end-to-end deep audiovisual speech recognition

abstract:
  Speech is one of the most effective ways of communication among humans. Even
though audio is the most common way of transmitting speech, very important
information can be found in other modalities, such as vision. Vision is
particularly useful when the acoustic signal is corrupted. Multi-modal speech
recognition however has not yet found wide-spread use, mostly because the
temporal alignment and fusion of the different information sources is
challenging.
  This paper presents an end-to-end audiovisual speech recognizer (AVSR), based
on recurrent neural networks (RNN) with a connectionist temporal classification
(CTC) loss function. CTC creates sparse "peaky" output activations, and we
analyze the differences in the alignments of output targets (phonemes or
visemes) between audio-only, video-only, and audio-visual feature
representations. We present the first such experiments on the large vocabulary
IBM ViaVoice database, which outperform previously published approaches on
phone accuracy in clean and noisy conditions.


title:
Sublabel-Accurate Discretization of Nonconvex Free-Discontinuity
  Problems

abstract:
  In this work we show how sublabel-accurate multilabeling approaches can be
derived by approximating a classical label-continuous convex relaxation of
nonconvex free-discontinuity problems. This insight allows to extend these
sublabel-accurate approaches from total variation to general convex and
nonconvex regularizations. Furthermore, it leads to a systematic approach to
the discretization of continuous convex relaxations. We study the relationship
to existing discretizations and to discrete-continuous MRFs. Finally, we apply
the proposed approach to obtain a sublabel-accurate and convex solution to the
vectorial Mumford-Shah functional and show in several experiments that it leads
to more precise solutions using fewer labels.


title:
ALMA observations of 4U 1728-34 and 4U 1820-30: first detection of
  neutron star X-ray binaries at 300 GHz

abstract:
  We report on the first observations of neutron star low-mass X-ray binaries
with the Atacama Large Millimeter/submillimeter Array (ALMA) at $\sim$300 GHz.
Quasi-simultaneous observations of 4U 1728-34 and 4U 1820-30 were performed at
radio (ATCA), infrared (VLT) and X-ray (Swift) frequencies, spanning more than
eight decades in frequency coverage. Both sources are detected at high
significance with ALMA. The spectral energy distribution of 4U 1728-34 is
consistent with synchrotron emission from a jet with a break from optically
thick to optically thin emission at 1.3-11.0$\times$10$^{13}$ Hz. This is the
third time a jet spectral break has been reported for a neutron star X-ray
binary. The radio to mm spectral energy distribution of 4U 1820-30 has
significant detections at 5 and 300~GHz. This confirms the presence of radio
emission during a soft state for this neutron star and represents the first
detection of mm emission during such a state, unambiguously pointing to the
presence of a jet. We also report on three additional unrelated sources -
showing mm emission - in the ALMA fields of view of 4U 1728-34 and 4U 1820-30.


title:
Critical Points for Elliptic Equations with Prescribed Boundary
  Conditions

abstract:
  This paper concerns the existence of critical points for solutions to second
order elliptic equations of the form $\nabla\cdot \sigma(x)\nabla u=0$ posed on
a bounded domain $X$ with prescribed boundary conditions. In spatial dimension
$n=2$, it is known that the number of critical points (where $\nabla u=0$) is
related to the number of oscillations of the boundary condition independently
of the (positive) coefficient $\sigma$. We show that the situation is different
in dimension $n\geq3$. More precisely, we obtain that for any fixed (Dirichlet
or Neumann) boundary condition for $u$ on $\partial X$, there exists an open
set of smooth coefficients $\sigma(x)$ such that $\nabla u$ vanishes at least
at one point in $X$. By using estimates related to the Laplacian with mixed
boundary conditions, the result is first obtained for a piecewise constant
conductivity with infinite contrast, a problem of independent interest. A
second step shows that the topology of the vector field $\nabla u$ on a
subdomain is not modified for appropriate bounded, sufficiently high-contrast,
smooth coefficients $\sigma(x)$.
  These results find applications in the class of hybrid inverse problems,
where optimal stability estimates for parameter reconstruction are obtained in
the absence of critical points. Our results show that for any (finite number
of) prescribed boundary conditions, there are coefficients $\sigma(x)$ for
which the stability of the reconstructions will inevitably degrade.


title: The $S=1/2$ Kagome Heisenberg Antiferromagnet Revisited

abstract:
  We examine the perennial quantum spin-liquid candidate $S=1/2$ Heisenberg
antiferromagnet on the kagome lattice. Our study is based on achieving Lanczos
diagonalization of the Hamiltonian on a $48$ site cluster in sectors with
dimensions as a large as $5 \times 10^{11}$. The results reveal novel intricate
structures in the low-lying energy spectrum. These structures by no means
unambiguously support an emerging consensus of a $\mathbb{Z}_2$ spin liquid
ground state, but instead appear compatible with several scenarios, including
four-fold topological degeneracy, inversion symmetry breaking and a combination
thereof. We discuss finite-size effects, such as the apparent absence of ETH,
and note that while considerably reduced, some are still present for the
largest cluster. Finally, we observe that an XXZ model in the Ising limit
reproduces remarkably well the most striking features of finite-size spectra.


title: Krawtchouk-Griffiths Systems I: Matrix Approach

abstract:
  We call Krawtchouk-Griffiths systems, or KG-systems, systems of multivariate
polynomials orthogonal with respect to corresponding multinomial distributions.
The original Krawtchouk polynomials are orthogonal with respect to a binomial
distribution. Our approach is to work directly with matrices comprising the
values of the polynomials at points of a discrete grid based on the possible
counting values of the underlying multinomial distribution. The starting point
for the construction of a KG-system is a generating matrix satisfying the
K-condition, orthogonality with respect to the basic probability distribution
associated to an individual step of the multinomial process. The variables of
the polynomials corresponding to matrices may be interpreted as quantum
observables in the real case, or quantum variables in the complex case. The
structure of the recurrence relations for the orthogonal polynomials is
presented with multiplication operators as the matrices corresponding to the
quantum variables. An interesting feature is that the associated random walks
correspond to the Lie algebra of the representation of symmetric tensor powers
of matrices.