title:
Low-order continuous finite element spaces on hybrid non-conforming
  hexahedral-tetrahedral meshes

abstract:
  This article deals with solving partial differential equations with the
finite element method on hybrid non-conforming hexahedral-tetrahedral meshes.
By non-conforming, we mean that a quadrangular face of a hexahedron can be
connected to two triangular faces of tetrahedra. We introduce a set of
low-order continuous (C0) finite element spaces defined on these meshes. They
are built from standard tri-linear and quadratic Lagrange finite elements with
an extra set of constraints at non-conforming hexahedra-tetrahedra junctions to
recover continuity. We consider both the continuity of the geometry and the
continuity of the function basis as follows: the continuity of the geometry is
achieved by using quadratic mappings for tetrahedra connected to tri-affine
hexahedra and the continuity of interpolating functions is enforced in a
similar manner by using quadratic Lagrange basis on tetrahedra with constraints
at non-conforming junctions to match tri-linear hexahedra. The so-defined
function spaces are validated numerically on simple Poisson and linear
elasticity problems for which an analytical solution is known. We observe that
using a hybrid mesh with the proposed function spaces results in an accuracy
significantly better than when using linear tetrahedra and slightly worse than
when solely using tri-linear hexahedra. As a consequence, the proposed function
spaces may be a promising alternative for complex geometries that are out of
reach of existing full hexahedral meshing methods.


title:
Constraining the $\Lambda$CDM and Galileon models with recent
  cosmological data

abstract:
  The Galileon theory belongs to the class of modified gravity models that can
explain the late-time accelerated expansion of the Universe. In previous works,
cosmological constraints on the Galileon model were derived, both in the
uncoupled case and with a disformal coupling of the Galileon field to matter.
There, we showed that these models agree with the most recent cosmological
data. In this work, we used updated cosmological data sets to derive new
constraints on Galileon models, including the case of a constant conformal
Galileon coupling to matter. We also explored the tracker solution of the
uncoupled Galileon model. After updating our data sets, especially with the
latest \textit{Planck} data and BAO measurements, we fitted the cosmological
parameters of the $\Lambda$CDM and Galileon models. The same analysis framework
as in our previous papers was used to derive cosmological constraints, using
precise measurements of cosmological distances and of the cosmic structure
growth rate. We showed that all tested Galileon models are as compatible with
cosmological data as the $\Lambda$CDM model. This means that present
cosmological data are not accurate enough to distinguish clearly between both
theories. Among the different Galileon models, we found that a conformal
coupling is not favoured, contrary to the disformal coupling which is preferred
at the $2.3\sigma$ level over the uncoupled case. The tracker solution of the
uncoupled Galileon model is also highly disfavoured due to large tensions with
supernovae and \textit{Planck}+BAO data. However, outside of the tracker
solution, the general uncoupled Galileon model, as well as the general
disformally coupled Galileon model, remain the most promising Galileon
scenarios to confront with future cosmological data. Finally, we also discuss
constraints coming from Lunar Laser Ranging experiment and gravitational wave
speed of propagation.


title: Topological language for RNA

abstract:
  In this paper we introduce a novel, context-free grammar, {\it
RNAFeatures$^*$}, capable of generating any RNA structure including pseudoknot
structures (pk-structure). We represent pk-structures as orientable fatgraphs,
which naturally leads to a filtration by their topological genus. Within this
framework, RNA secondary structures correspond to pk-structures of genus zero.
{\it RNAFeatures$^*$} acts on formal, arc-labeled RNA secondary structures,
called $\lambda$-structures. $\lambda$-structures correspond one-to-one to
pk-structures together with some additional information. This information
consists of the specific rearrangement of the backbone, by which a pk-structure
can be made cross-free. {\it RNAFeatures$^*$} is an extension of the grammar
for secondary structures and employs an enhancement by labelings of the symbols
as well as the production rules. We discuss how to use {\it RNAFeatures$^*$} to
obtain a stochastic context-free grammar for pk-structures, using data of RNA
sequences and structures. The induced grammar facilitates fast Boltzmann
sampling and statistical analysis. As a first application, we present an $O(n
log(n))$ runtime algorithm which samples pk-structures based on ninety tRNA
sequences and structures from the Nucleic Acid Database (NDB).


title: On the dynamics of tilted black hole-torus systems

abstract:
  We present results from three-dimensional, numerical relativity simulations
of a {\it tilted} black hole-thick accretion disc system. The simulations are
analysed using tracer particles in the disc which are advected with the flow.
Such tracers, which we employ in these new simulations for the first time,
provide a powerful means to analyse in detail the complex dynamics of tilted
black hole-torus systems. We show how its use helps to gain insight in the
overall dynamics of the system, discussing the origin of the observed black
hole precession and the development of a global non-axisymmetric $m=1$ mode in
the disc. Our three-dimensional simulations show the presence of quasi-periodic
oscillations (QPOs) in the instantaneous accretion rate, with frequencies in a
range compatible with those observed in low mass X-ray binaries with either a
black hole or a neutron star component. The frequency ratio of the dominant low
frequency peak and the first overtone is $o_1/f \sim 1.9$, a frequency ratio
not attainable when modelling the QPOs as $p$-mode oscillations in axisymmetric
tori.


title:
On a Vectorized Version of a Generalized Richardson Extrapolation
  Process

abstract:
  Let $\{\xx_m\}$ be a vector sequence that satisfies $$ \xx_m\sim
\sss+\sum^\infty_{i=1}\alpha_i \gg_i(m)\quad\text{as $m\to\infty$},$$ $\sss$
being the limit or antilimit of $\{\xx_m\}$ and $\{\gg_i(m)\}^\infty_{i=1}$
being an asymptotic scale as $m\to\infty$, in the sense that
$$\lim_{m\to\infty}\frac{\|\gg_{i+1}(m)\|}{\|\gg_{i}(m)\|}=0,\quad
i=1,2,\ldots.$$ The vector sequences $\{\gg_i(m)\}^\infty_{m=0}$,
$i=1,2,\ldots,$ are known, as well as $\{\xx_m\}$. In this work, we analyze the
convergence and convergence acceleration properties of a vectorized version of
the generalized Richardson extrapolation process that is defined via the
equations $$
\sum^k_{i=1}\braket{\yy,\Delta\gg_{i}(m)}\widetilde{\alpha}_i=\braket{\yy,\Delta\xx_m},\quad
n\leq m\leq n+k-1;\quad
\sss_{n,k}=\xx_n+\sum^k_{i=1}\widetilde{\alpha}_i\gg_{i}(n),$$ $\sss_{n,k}$
being the approximation to $\sss$. Here $\yy$ is some nonzero vector,
$\braket{\cdot\,,\cdot}$ is an inner product, such that
$\braket{\alpha\aaa,\beta\bb}=\bar{\alpha}\beta\braket{\aaa,\bb}$, and
$\Delta\xx_m=\xx_{m+1}-~\xx_m$ and $\Delta\gg_i(m)=\gg_i(m+1)-\gg_i(m)$. By
imposing a minimal number of reasonable additional conditions on the
$\gg_i(m)$, we show that the error $\sss_{n,k}-\sss$ has a full asymptotic
expansion as $n\to\infty$. We also show that actual convergence acceleration
takes place and we provide a complete classification of it.


title: A global look at X-ray time lags in Seyfert Galaxies

abstract:
  X-ray reverberation, where light-travel time delays map out the compact
geometry around the inner accretion flow in supermassive black holes, has been
discovered in several of the brightest, most variable and well-known Seyfert
galaxies. In this work, we expand the study of X-ray reverberation to all
Seyfert galaxies in the XMM-Newton archive above a nominal rms variability and
exposure level (a total of 43 sources). 50 per cent of source exhibit iron K
reverberation, in that the broad iron K emission line responds to rapid
variability in the continuum. We also find that on long timescales, the hard
band emission lags behind the soft band emission in 85 per cent of sources.
This `low-frequency hard lag' is likely associated with the coronal emission,
and so this result suggests that most sources with X-ray variability show
intrinsic variability from the nuclear region. We update the known iron K lag
amplitude vs. black hole mass relation, and find evidence that the height or
extent of the coronal source (as inferred by the reverberation time delay)
increases with mass accretion rate.


title:
Interference stabilization of autoionizing states in molecular $N_2$
  studied by time- and angular-resolved photoelectron spectroscopy

abstract:
  An autoionizing resonance in molecular N$_2$ is excited by an ultrashort XUV
pulse and probed by a subsequent weak IR pulse, which ionizes the contributing
Rydberg states. Time- and angular-resolved photoelectron spectra recorded with
a velocity map imaging spectrometer reveal two electronic contributions with
different angular distributions. One of them has an exponential decay rate of
$20\pm5$ fs, while the other one is shorter than 10 fs. This observation is
interpreted as a manifestation of interference stabilization involving the two
overlapping discrete Rydberg states. A formalism of interference stabilization
for molecular ionization is developed and applied to describe the autoionizing
resonance. The results of calculations reveal, that the effect of the
interference stabilization is facilitated by rotationally-induced couplings of
electronic states with different symmetry.


title:
Oracle Based Active Set Algorithm for Scalable Elastic Net Subspace
  Clustering

abstract:
  State-of-the-art subspace clustering methods are based on expressing each
data point as a linear combination of other data points while regularizing the
matrix of coefficients with $\ell_1$, $\ell_2$ or nuclear norms. $\ell_1$
regularization is guaranteed to give a subspace-preserving affinity (i.e.,
there are no connections between points from different subspaces) under broad
theoretical conditions, but the clusters may not be connected. $\ell_2$ and
nuclear norm regularization often improve connectivity, but give a
subspace-preserving affinity only for independent subspaces. Mixed $\ell_1$,
$\ell_2$ and nuclear norm regularizations offer a balance between the
subspace-preserving and connectedness properties, but this comes at the cost of
increased computational complexity. This paper studies the geometry of the
elastic net regularizer (a mixture of the $\ell_1$ and $\ell_2$ norms) and uses
it to derive a provably correct and scalable active set method for finding the
optimal coefficients. Our geometric analysis also provides a theoretical
justification and a geometric interpretation for the balance between the
connectedness (due to $\ell_2$ regularization) and subspace-preserving (due to
$\ell_1$ regularization) properties for elastic net subspace clustering. Our
experiments show that the proposed active set method not only achieves
state-of-the-art clustering performance, but also efficiently handles
large-scale datasets.


title: On the 3x+1 conjecture

abstract:
  In this paper, we discuss the well known 3x+1 conjecture in form of the
accelerated Collatz function T defined on the positive odd integers. We present
a sequence of quotient spaces and an invertible map that are intrinsically
related to the behavior of T. This approach allows to express the 3x+1
conjecture in form of equivalent problems, which might be more accessible than
the original conjecture.


title: On Vector Linear Solvability of Multicast Networks

abstract:
  Vector linear network coding (LNC) is a generalization of the conventional
scalar LNC, such that the data unit transmitted on every edge is an
$L$-dimensional vector of data symbols over a base field GF($q$). Vector LNC
enriches the choices of coding operations at intermediate nodes, and there is a
popular conjecture on the benefit of vector LNC over scalar LNC in terms of
alphabet size of data units: there exist (single-source) multicast networks
that are vector linearly solvable of dimension $L$ over GF($q$) but not scalar
linearly solvable over any field of size $q' \leq q^L$. This paper introduces a
systematic way to construct such multicast networks, and subsequently establish
explicit instances to affirm the positive answer of this conjecture for
\emph{infinitely many} alphabet sizes $p^L$ with respect to an \emph{arbitrary}
prime $p$. On the other hand, this paper also presents explicit instances with
the special property that they do not have a vector linear solution of
dimension $L$ over GF(2) but have scalar linear solutions over GF($q'$) for
some $q' < 2^L$, where $q'$ can be odd or even. This discovery also unveils
that over a given base field, a multicast network that has a vector linear
solution of dimension $L$ does not necessarily have a vector linear solution of
dimension $L' > L$.


title: Frozen impacted drop: From fragmentation to hierarchical crack patterns

abstract:
  We investigate experimentally the quenching of a liquid pancake, obtained
through the impact of a water drop on a cold solid substrate ($0$ to
$-60^\circ$C). We show that, below a certain substrate temperature, fractures
appear on the frozen pancake and the crack patterns change from a 2D
fragmentation regime to a hierarchical fracture regime as the thermal shock is
stronger. The different regimes are discussed and the transition temperatures
are estimated through classical fracture scaling arguments. Finally, a phase
diagram presents how these regimes can be controlled by the drop impact
parameters.


title: A database of Hilbert modular forms

abstract:
  We describe the computation of tables of Hilbert modular forms of parallel
weight 2 over totally real fields.


title: Superfluid 4He dynamics beyond quasiparticle excitations

abstract:
  The dynamics of superfluid 4He at and above the Landau quasiparticle regime
is investigated by high precision inelastic neutron scattering measurements of
the dynamic structure factor. A highly structured response is observed above
the familiar phonon-maxon-roton spectrum, characterized by sharp thresholds for
phonon-phonon, maxon-roton and roton-roton coupling processes. The experimental
dynamic structure factor is compared to the calculation of the same physical
quantity by a Dynamic Many-body theory including three-phonon processes
self-consistently. The theory is found to provide a quantitative description of
the dynamics of the correlated bosons for energies up to about three times that
of the Landau quasiparticles.


title:
Re-evaluation of the $^{16}$O($n$,$\gamma$)$^{17}$O cross section at
  astrophysical energies and its role as neutron poison in the $s$ process

abstract:
  The doubly-magic nucleus $^{16}$O has a small neutron capture cross section
of just a few tens of microbarn in the astrophysical energy region. Despite of
this, $^{16}$O plays an important role as neutron poison in the astrophysical
slow neutron capture ($s$) process due to its high abundance. We present in
this paper a re-evaluation of the available experimental data for
$^{16}$O($n,\gamma$)$^{17}$O and derive a new recommendation for the
Maxwellian-averaged cross sections (MACS) between $kT$= 5$-$100 keV. Our new
recommendations are lower up to $kT$= 60 keV compared to the previously
recommended values but up to 14\% higher at $kT$= 100 keV. We explore the
impact of this different energy dependence on the weak $s$-process during core
helium- ($kT$= 26 keV) and shell carbon burning ($kT$= 90 keV) in massive stars
where $^{16}$O is the most abundant isotope.


title: Simple state preparation for contextuality tests with few observables

abstract:
  We consider any noncontextuality inequality, and the state preparation scheme
which consists in performing any von Neumann measurement on any initial state.
For an inequality which is not always satisfied, and Hilbert space dimensions
greater than a value specified by the inequality, we determine necessary and
sufficient conditions for the existence of observables with which the
inequality is violated after the preparation process. For an initial state with
no zero eigenvalues, there are always such observables, and which are
independent of this state.


title: The Stratonovich Formulation of Quantum Feedback Network Rules

abstract:
  We express the rules for forming quantum feedback networks using the
Stratonovich form of quantum stochastic calculus rather than the Ito, or SLH
form. Remarkably the feedback reduction rule implies that we obtain the Schur
complement of the matrix of Stratonovich coupling operators where we short out
the internal input/output coefficients.


title:
Outcoupling vector solitons from a Bose-Einstein condensate with
  time-dependent interatomic forces

abstract:
  We discuss the possibility of emitting vector solitons from a two-component
elongated BEC by manipulating in time the inter- or intra-species scattering
lengths with Feshbach resonance tuning. We present different situations which
do not have an analogue in the single species case. In particular, we show
vector soliton out-coupling by tuning the interspecies forces, how the
evolution in one species is controlled by tuning the dynamics of the other, and
how one can implement the so-called supersolitons. The analysis is performed by
numerical simulations of the one-dimensional Gross-Pitaevskii equation. Simple
analytic arguments are also presented in order to give a qualitative insight.


title:
Jump Markov models and transition state theory: the Quasi-Stationary
  Distribution approach

abstract:
  We are interested in the connection between a metastable continuous state
space Markov process (satisfying e.g. the Langevin or overdamped Langevin
equation) and a jump Markov process in a discrete state space. More precisely,
we use the notion of quasi-stationary distribution within a metastable state
for the continuous state space Markov process to parametrize the exit event
from the state. This approach is useful to analyze and justify methods which
use the jump Markov process underlying a metastable dynamics as a support to
efficiently sample the state-to-state dynamics (accelerated dynamics
techniques). Moreover, it is possible by this approach to quantify the error on
the exit event when the parametrization of the jump Markov model is based on
the Eyring-Kramers formula. This therefore provides a mathematical framework to
justify the use of transition state theory and the Eyring-Kramers formula to
build kinetic Monte Carlo or Markov state models.

categories: math.PR math-ph math.AP math.MP physics.chem-ph


title: Pathwise estimates for an effective dynamics

abstract:
  Starting from the overdamped Langevin dynamics in $\mathbb{R}^n$, $$ dX_t =
-\nabla V(X_t) dt + \sqrt{2 \beta^{-1}} dW_t, $$ we consider a scalar Markov
process $\xi_t$ which approximates the dynamics of the first component $X^1_t$.
In the previous work [F. Legoll, T. Lelievre, Nonlinearity 2010], the fact that
$(\xi_t)_{t \ge 0}$ is a good approximation of $(X^1_t)_{t \ge 0}$ is proven in
terms of time marginals, under assumptions quantifying the timescale separation
between the first component and the other components of $X_t$. Here, we prove
an upper bound on the trajectorial error $\mathbb{E} \left( \sup_{0 \leq t \leq
T} \left| X^1_t - \xi_t \right| \right)$, for any $T > 0$, under a similar set
of assumptions. We also show that the technique of proof can be used to obtain
quantitative averaging results.


title: Sequential motif profile of natural visibility graphs

abstract:
  The concept of sequential visibility graph motifs -subgraphs appearing with
characteristic frequencies in the visibility graphs associated to time series-
has been advanced recently along with a theoretical framework to compute
analytically the motif profiles associated to Horizontal Visibility Graphs
(HVGs). Here we develop a theory to compute the profile of sequential
visibility graph motifs in the context of Natural Visibility Graphs (VGs). This
theory gives exact results for deterministic aperiodic processes with a smooth
invariant density or stochastic processes that fulfil the Markov property and
have a continuous marginal distribution. The framework also allows for a linear
time numerical estimation in the case of empirical time series. A comparison
between the HVG and the VG case (including evaluation of their robustness for
short series polluted with measurement noise) is also presented.


title: Information Theoretically Secure Databases

abstract:
  We introduce the notion of a database system that is information
theoretically "Secure In Between Accesses"--a database system with the
properties that 1) users can efficiently access their data, and 2) while a user
is not accessing their data, the user's information is information
theoretically secure to malicious agents, provided that certain requirements on
the maintenance of the database are realized. We stress that the security
guarantee is information theoretic and everlasting: it relies neither on
unproved hardness assumptions, nor on the assumption that the adversary is
computationally or storage bounded.
  We propose a realization of such a database system and prove that a user's
stored information, in between times when it is being legitimately accessed, is
information theoretically secure both to adversaries who interact with the
database in the prescribed manner, as well as to adversaries who have installed
a virus that has access to the entire database and communicates with the
adversary.
  The central idea behind our design is the construction of a "re-randomizing
database" that periodically changes the internal representation of the
information that is being stored. To ensure security, these remappings of the
representation of the data must be made sufficiently often in comparison to the
amount of information that is being communicated from the database between
remappings and the amount of local memory in the database that a virus may
preserve during the remappings. The core of the proof of the security guarantee
is the following communication/data tradeoff for the problem of learning sparse
parities from uniformly random $n$-bit examples: any algorithm that can learn a
parity of size $k$ with probability at least $p$ and extracts at most $r$ bits
of information from each example, must see at least $p\cdot
\left(\frac{n}{r}\right)^{k/2} c_k$ examples.


title: Coherent emission of atomic soliton pairs by Feshbach-resonance tuning

abstract:
  We present two simple designs of matter-wave beam splitters in a trapped
Bose-Einstein Condensate (BEC). In our scheme, identical pairs of atomic
solitons are produced by an adequate control --- in time and/or space --- of
the scattering length. Our analysis is performed by numerical integration of
the Gross-Pitaevskii equation and supported by several analytic estimates. Our
results show that these devices can be implemented in the frame of current BEC
experiments. The system has potential applications for the construction of a
soliton interferometer.


title: Symmetry Reduced Loop Quantum Gravity: A Bird's Eye View

abstract:
  This is a brief overview of the current status of symmetry reduced models in
Loop Quantum Gravity (LQG), focussing on the very early universe. Over the last
3 years or so the subject has matured sufficiently to make direct contact with
observations of the Cosmic Microwave Background (CMB). In particular, thanks to
an unforeseen interplay between the ultraviolet features of quantum geometry
and the infrared properties of quantum fields representing cosmological
perturbations, \emph{Planck scale effects} of LQG can leave imprints on CMB
\emph{at the largest angular scales}. In addition to a summary of these
results, the article also contains a critical discussion of the symmetry
reduction procedure used in discussions of quantum cosmology (and quantum black
holes).

categories: gr-qc astro-ph.CO hep-th math-ph math.MP


title: The Langevin equation for systems with a preferred spatial direction

abstract:
  In this paper, we generalize the theory of Brownian motion and the
Onsager-Machlup theory of fluctuations for spatially symmetric systems to
equilibrium and nonequilibrium steady-state systems with a preferred spatial
direction, due to an external force. To do this, we extend the Langevin
equation to include a bias, which is introduced by the external force and
alters the Gaussian structure of the system's fluctuations. By solving this
extended equation, we demonstrate that the statistical properties of the
fluctuations in these systems can be predicted from physical observables, such
as the temperature and the hydrodynamic gradients.


title:
$\mathtt{ComEst}$: a Completeness Estimator of Source Extraction on
  Astronomical Imaging

abstract:
  The completeness of source detection is critical for analyzing the
photometric and spatial properties of the population of interest observed by
astronomical imaging. We present a software package $\mathtt{ComEst}$, which
calculates the completeness of source detection on charge-coupled device (CCD)
images of astronomical observations, especially for the optical and
near-infrared (NIR) imaging of galaxies and point sources. The completeness
estimator $\mathtt{ComEst}$ is designed for the source finder
$\mathtt{SExtractor}$ used on the CCD images saved in the Flexible Image
Transport System (FITS) format. Specifically, $\mathtt{ComEst}$ estimates the
completeness of the source detection by deriving the detection rate of
synthetic point sources and galaxies simulated on the observed CCD images. In
order to capture any observational artifacts or noise properties while deriving
the completeness, $\mathtt{ComEst}$ directly carries out the detection of
simulated sources on the observed images. Given an observed CCD image saved in
FITS format, $\mathtt{ComEst}$ derives the completeness of the source detection
from end to end as a function of source flux (or magnitude) and CCD position.
In addition, $\mathtt{ComEst}$ can also estimate the purity of the source
detection by comparing the catalog of the detected sources to the input
catalogs of the simulated sources. We run ComEst on the images from Blanco
Cosmology Survey (BCS) and compare the derived completeness as a function of
magnitude to the limiting magnitudes derived by using the Signal-to-Noise ratio
(SNR) and number count histogram of the detected sources. $\mathtt{ComEst}$ is
released as a Python package with an easy-to-use syntax and is publicly
available at https://github.com/inonchiu/ComEst


title:
A minimal model for the emergence of cooperation in randomly growing
  networks

abstract:
  Cooperation is observed widely in nature and is thought an essential
component of many evolutionary processes, yet the mechanisms by which it arises
and persists are still unclear. Among several theories, network reciprocity --
a model of inhomogeneous social interactions -- has been proposed as an
enabling mechanism to explain the emergence of cooperation. Existing
evolutionary models of this mechanism have tended to focus on highly
heterogeneous (scale-free) networks, hence typically assume preferential
attachment mechanisms, and consequently the prerequisite that individuals have
global network knowledge. Within an evolutionary game theoretic context, using
the weak prisoner's dilemma as a metaphor for cooperation, we present a minimal
model which describes network growth by chronological random addition of new
nodes, combined with regular attrition of less fit members of the population.
Specifically our model does not require that agents have access to global
information and does not assume scale-free network structure or a preferential
attachment mechanism. Further our model supports the emergence of cooperation
from initially non-cooperative populations. By reducing dependency on a number
of assumptions, this model offers broad applicability and as such may support
an explanation of the emergence of cooperation in early evolutionary
transitions, where few assumptions can be made.


title: Global network cooperation catalysed by a small prosocial migrant clique

abstract:
  Much research has been carried out to understand the emergence of cooperation
in simulated social networks of competing individuals. Such research typically
implements a population as a single connected network. Here we adopt a more
realistic premise; namely that populations consist of multiple networks, whose
members migrate from one to another. Specifically, we isolate the key elements
of the scenario where a minority of members from a cooperative network migrate
to a network populated by defectors. Using the public goods game to model
group-wise cooperation, we find that under certain circumstances, the concerted
actions of a trivial number of such migrants will catalyse widespread
behavioural change throughout an entire population. Such results support a
wider argument: that the general presence of some form of disruption
contributes to the emergence of cooperation in social networks, and
consequently that simpler models may encode a determinism that precludes the
emergence of cooperation.


title: Multiple photon Hamiltonian in linear quantum optical networks

abstract:
  We give an alternative derivation for the explicit formula of the effective
Hamiltonian describing the evolution of the quantum state of any number of
photons entering a linear optics multiport. The description is based on the
effective Hamiltonian of the optical system for a single photon and comes from
relating the evolution in the Lie group that describes the unitary evolution
matrices in the Hilbert space of the photon states to the evolution in the Lie
algebra of the Hamiltonians for one and multiple photons. We give a few
examples of how a group theory approach can shed light on some properties of
devices with two input ports.


title: Stochastic Portfolio Theory: A Machine Learning Perspective

abstract:
  In this paper we propose a novel application of Gaussian processes (GPs) to
financial asset allocation. Our approach is deeply rooted in Stochastic
Portfolio Theory (SPT), a stochastic analysis framework introduced by Robert
Fernholz that aims at flexibly analysing the performance of certain investment
strategies in stock markets relative to benchmark indices. In particular, SPT
has exhibited some investment strategies based on company sizes that, under
realistic assumptions, outperform benchmark indices with probability 1 over
certain time horizons. Galvanised by this result, we consider the inverse
problem that consists of learning (from historical data) an optimal investment
strategy based on any given set of trading characteristics, and using a
user-specified optimality criterion that may go beyond outperforming a
benchmark index. Although this inverse problem is of the utmost interest to
investment management practitioners, it can hardly be tackled using the SPT
framework. We show that our machine learning approach learns investment
strategies that considerably outperform existing SPT strategies in the US stock
market.


title: Unmixed d-uniform r-partite hypergraphs

abstract:
  In this paper, we characterize all unmixed d-uniform r-partite hypergraphs
under a certain condition. Also we give a necessary condition for unmixedness
in d-uniform hypergraphs with a perfect matching of size n. Finally we give a
sufficient condition for unmixednes in d-uniform hypergraphs with a perfect
matching.


title: Dynamical analysis of the cluster pair: A3407 + A3408

abstract:
  We carried out a dynamical study of the galaxy cluster pair A3407 \& A3408
based on a spectroscopic survey obtained with the 4 meter Blanco telescope at
the CTIO, plus 6dF data, and ROSAT All-Sky-Survey. The sample consists of 122
member galaxies brighter than $m_R=20$. Our main goal is to probe the galaxy
dynamics in this field and verify if the sample constitutes a single galaxy
system or corresponds to an ongoing merging process. Statistical tests were
applied to clusters members showing that both the composite system A3407 +
A3408 as well as each individual cluster have Gaussian velocity distribution. A
velocity gradient of $\sim 847\pm 114$ $\rm km\;s^{-1}$ was identified around
the principal axis of the projected distribution of galaxies, indicating that
the global field may be rotating. Applying the KMM algorithm to the
distribution of galaxies we found that the solution with two clusters is better
than the single unit solution at the 99\% c.l. This is consistent with the
X-ray distribution around this field, which shows no common X-ray halo
involving A3407 and A3408. We also estimated virial masses and applied a
two-body model to probe the dynamics of the pair. The more likely scenario is
that in which the pair is gravitationally bound and probably experiences a
collapse phase, with the cluster cores crossing in less than $\sim$1 $h^{-1}$
Gyr, a pre-merger scenario. The complex X-ray morphology, the gas temperature,
and some signs of galaxy evolution in A3408 suggests a post-merger scenario,
with cores having crossed each other $\sim 1.65 h^{-1}$Gyr ago, as an
alternative solution.


title:
Spin-polarized currents and noise in NS junctions with Yu-Shiba-Rusinov
  impurities

abstract:
  Conventional superconductors disordered by magnetic impurities demonstrate
physical properties drastically different from their pristine counterparts. In
our previous work [Phys. Rev. B 92, 245430 (2015)] we explored spectral and
thermodynamic properties of such systems for two extreme cases: completely
random and ferromagnetically aligned impurity magnetic moments. Here we
consider transport properties of these systems, and show that they have a
potential to be used in superconducting spintronic devices. Each magnetic
impurity contributes a Yu-Shiba-Rusinov (YSR) bound state to the spectrum,
residing at sub-gap energies. Provided the YSR states form metallic bands, we
demonstrate that the tunneling current carried by these states can be highly
spin-polarized when the impurities are ferromagnetically ordered. The spin
polarization can be switched by simply tuning the bias voltage. Moreover, even
when the impurity spins are completely uncorrelated, one can still achieve
almost 100% spin polarization of the current, if the tunnel interface is
spin-active. We compute electric current and noise, varying parameters of the
interface between tunneling and fully transparent regimes, and analyze the
relative role of single-particle and Andreev reflection processes.


title: On locally coherent hearts

abstract:
  We show that, under particular conditions, if a t-structure in the unbounded
derived category of a locally coherent Grothendieck category restricts to the
bounded derived category of its category of finitely presented objects, then
its heart is itself a locally coherent Grothendieck category. Those particular
conditions are always satisfied when the Grothendieck category is arbitrary and
one considers the t-structure associated to a torsion pair in the category of
finitely presented objects. They are also satisfied when one takes any
compactly generated t-structure in the derived category of a commutative
noetherian ring which restricts to the bounded derived category of finitely
generated modules. As a consequence, any t-structure in this latter bounded
derived category has a heart which is equivalent to the category of finitely
presented objects of some locally coherent Grothendieck category.


title: Renewal shot noise processes in the case of slowly varying tails

abstract:
  We investigate weak convergence of renewal shot noise processes in the case
of slowly varying tails of the inter-shot times. We show that these processes,
after an appropriate non-linear scaling, converge in the sense of
finite-dimensional distributions to an inverse extremal process.


title:
Information is not a Virus, and Other Consequences of Human Cognitive
  Limits

abstract:
  The many decisions people make about what to pay attention to online shape
the spread of information in online social networks. Due to the constraints of
available time and cognitive resources, the ease of discovery strongly impacts
how people allocate their attention to social media content. As a consequence,
the position of information in an individual's social feed, as well as explicit
social signals about its popularity, determine whether it will be seen, and the
likelihood that it will be shared with followers. Accounting for these
cognitive limits simplifies mechanics of information diffusion in online social
networks and explains puzzling empirical observations: (i) information
generally fails to spread in social media and (ii) highly connected people are
less likely to re-share information. Studies of information diffusion on
different social media platforms reviewed here suggest that the interplay
between human cognitive limits and network structure differentiates the spread
of information from other social contagions, such as the spread of a virus
through a population.


title: Detecting Code Clones: A review

abstract:
  Code clone detection is involved with detecting duplicated fragments of code
within a code base. Detecting these clones is useful for maintenance operations
which require editing the clones. The tools developed are expected to be robust
enough to identify clones even when they have been modified, whilst preserving
reasonable recall and precision rates. It is also expected that these tools be
easily adaptable to different programming languages. The major approaches to
this problem has involve the use of direct string matching, token comparison or
comparison using abstract syntax trees. It is difficult to compare detection
tools due to the absence of a standardized framework for measurement. More work
should be done to make the existing tools useful for other practical/industrial
purposes.


title:
Current Interactions and Holography from the 0-Form Sector of Nonlinear
  Higher-Spin Equations

abstract:
  The form of higher-spin current interactions in $AdS_4$ is derived from the
full nonlinear higher-spin equations in the sector of Weyl 0-forms. The
coupling constant in front of spin-one currents built from scalars and spinors
as well as Yukawa coupling are determined explicitly. Couplings of all other
higher-spin current interactions are determined implicitly. All couplings are
shown to be independent of the phase parameter of the nonlinear higher-spin
theory. The proper holographic dependence of the vertex on the higher-spin
phase parameter is shown to result from the boundary conditions on the bulk
fields.


title: Quantum Signature of Chaos and Thermalization in Kicked Dicke Model

abstract:
  We study the quantum dynamics of the kicked Dicke model(KDM) in terms of the
Floquet operator and analyze the connection between the chaos and
thermalization in this context. The Hamiltonian map is constructed by taking
the classical limit of the Heisenberg equation of motion suitably to study the
corresponding phase space dynamics which shows a crossover from regular to
chaotic motion by tuning the kicking strength. The fixed point analysis and
calculation of the Lyapunov exponent(LE) provides us a complete picture of the
onset of chaos in phase space dynamics. We carry out the spectral analysis of
the Floquet operator which include the calculation of quasienergy spacing
distribution, structural entropy and show the correspondence to the random
matrix theory in the chaotic regime. Finally, we analyze the thermodynamics and
statistical properties of the bosonic sector as well as the spin sector and
discuss how such periodically kicked system relaxes to a thermalized state in
accordance with the laws of statistical mechanics. We introduce the notion of
an effective temperature and show that a microcanonical picture is emerging out
in the thermodynamic limit indicating the thermalization occurring in such
system.


title: The Ramanujan Property for Simplicial Complexes

abstract:
  Let $G$ be a topological group acting on a simplicial complex $\mathcal{X}$
satisfying some mild assumptions. For example, consider a $k$-regular tree and
its automorphism group, or more generally, a regular affine Bruhat-Tits
building and its automorphism group. We define and study various types of
high-dimensional spectra of quotients of $\mathcal{X}$ by subgroups of $G$.
These spectra include the spectrum of many natural operators associated with
the quotients, e.g. the high-dimensional Laplacians.
  We prove a theorem in the spirit of the Alon-Boppana Theorem, leading to a
notion of Ramanujan quotients of $\mathcal{X}$. Ramanujan $k$-regular graphs
and Ramanuajn complexes in the sense of Lubotzky, Samuels and Vishne are
Ramanujan in dimension $0$ according to our definition (for $\mathcal{X}$, $G$
suitably chosen). We give a criterion for a quotient of $\mathcal{X}$ to be
Ramanujan which is phrased in terms of representations of $G$, and use it,
together with deep results about automorphic representations, to show that
affine buildings of inner forms of $\mathbf{GL}_n$ over local fields of
positive characteristic admit infinitely many quotients which are Ramanujan in
all dimensions. The Ramanujan (in dimension $0$) complexes constructed by
Lubotzky, Samuels and Vishne arise as a special case of our construction. Our
construction also gives rise to Ramanujan graphs which are apparently new.
  Other applications are also discussed. For example, we show that there are
non-isomorphic simiplicial complexes which are isospectral in all dimensions.


title:
Malliavin differentiability of solutions of SPDEs with L\'evy white
  noise

abstract:
  In this article, we consider a stochastic partial differential equation
(SPDE) driven by a L\'evy white noise, with Lipschitz multiplicative term
$\sigma$. We prove that under some conditions, this equation has a unique
random field solution. These conditions are verified by the stochastic heat and
wave equations. We introduce the basic elements of Malliavin calculus with
respect to the compensated Poisson random measure associated with the L\'evy
white noise. If $\sigma$ is affine, we prove that the solution is Malliavin
differentiable and its Malliavin derivative satisfies a stochastic integral
equation.


title:
The geometric discretisation of the Suslov problem: a case study of
  consistency for nonholonomic integrators

abstract:
  Geometric integrators for nonholonomic systems were introduced by Cort\'es
and Mart\'inez in [Nonholonomic integrators, Nonlinearity, 14, 2001] by
proposing a discrete Lagrange-D'Alembert principle. Their approach is based on
the definition of a discrete Lagrangian $L_d$ and a discrete constraint space
$D_d$. There is no recipe to construct these objects and the performance of the
integrator is sensitive to their choice.
  Cort\'es and Mart\'inez claim that choosing $L_d$ and $D_d$ in a consistent
manner with respect to a finite difference map is necessary to guarantee an
approximation of the continuous flow within a desired order of accuracy.
Although this statement is given without proof, similar versions of it have
appeared recently in the literature.
  We evaluate the importance of the consistency condition by comparing the
performance of two different geometric integrators for the nonholonomic Suslov
problem, only one of which corresponds to a consistent choice of $L_d$ and
$D_d$. We prove that both integrators produce approximations of the same order,
and, moreover, that the non-consistent discretisation outperforms the other in
numerical experiments and in terms of energy preservation. Our results indicate
that the consistency of a discretisation might not be the most relevant feature
to consider in the construction of nonholonomic geometric integrators.


title: Unimodular Trees versus Einstein Trees

abstract:
  The maximally helicity violating (MHV) tree level scattering amplitudes
involving three, four or five gravitons are worked out in Unimodular Gravity.
They are found to coincide with the corresponding amplitudes in General
Relativity. This a remarkable result, insofar as both the propagators and the
vertices are quite different in both theories.


title: On critical values of L-functions of potentially automorphic motives

abstract:
  In this paper we prove a version of Deligne's conjecture for potentially
automorphic motives, twisted by certain algebraic Hecke characters. The Hecke
characters are chosen in such a way that we can use automorphic methods in the
context of totally definite unitary groups.


title: The GPU-based Parallel Ant Colony System

abstract:
  The Ant Colony System (ACS) is, next to Ant Colony Optimization (ACO) and the
MAX-MIN Ant System (MMAS), one of the most efficient metaheuristic algorithms
inspired by the behavior of ants. In this article we present three novel
parallel versions of the ACS for the graphics processing units (GPUs). To the
best of our knowledge, this is the first such work on the ACS which shares many
key elements of the ACO and the MMAS, but differences in the process of
building solutions and updating the pheromone trails make obtaining an
efficient parallel version for the GPUs a difficult task. The proposed parallel
versions of the ACS differ mainly in their implementations of the pheromone
memory. The first two use the standard pheromone matrix, and the third uses a
novel selective pheromone memory. Computational experiments conducted on
several Travelling Salesman Problem (TSP) instances of sizes ranging from 198
to 2392 cities showed that the parallel ACS on Nvidia Kepler GK104 GPU (1536
CUDA cores) is able to obtain a speedup up to 24.29x vs the sequential ACS
running on a single core of Intel Xeon E5-2670 CPU. The parallel ACS with the
selective pheromone memory achieved speedups up to 16.85x, but in most cases
the obtained solutions were of significantly better quality than for the
sequential ACS.


title: Heterogeneous nucleation on a surface with heterogeneous surface energy

abstract:
  In the standard treatment of heterogeneous nucleation on a surface, the
energy of the surface is assumed to be homogeneous. Often its value is obtained
from some macroscopic measurement. We ask the question what happens if we
consider the surface energy to be heterogeneous. This is a straightforward
generalization and may realistically be important in a number of scenarios,
e.g. when the phase forming the surface is a binary alloy, solid solution, in
presence of self-organized or artifically created patterns on the surface. We
examine the effects of surface heterogeneity in a few scenarios in a model
system, 3D lattice Ising model. Utilizing umbrella sampling computer
simulations we find the nucleation barrier can be significantly lowered in
presence of surface heterogeneity, even if the average surface energy is kept
constant.


title: A Scaling Behavior of Bloch Oscillation in Weyl Semimetals

abstract:
  We predict a linear logarithmical scaling law of Bloch oscillation dynamics
in Weyl semimetals (WSMs), which can be applied to detect Weyl nodal points.
Applying the semiclassical dynamics for quasiparticles which are accelerated
bypassing a Weyl point, we show that transverse drift exhibits asymptotically a
linear log-log relation with respect to the minimal momentum measured from the
Weyl point. This linear scaling behavior is a consequence of the monopole
structure nearby the Weyl points, thus providing a direct measurement of the
topological nodal points, with the chirality and anisotropy being precisely
determined. We apply the present results to two lattice models for WSMs which
can be realized with cold atoms in experiment, and propose realistic schemes
for the experimental detection. With the analytic and numerical results we show
the feasibility of identifying topological Weyl nodal points based on the
present prediction.


title: The jet feedback mechanism (jfm) in stars, galaxies and clusters

abstract:
  I review the influence jets and the bubbles they inflate might have on their
ambient gas as they operate through a negative jet feedback mechanism (JFM). I
discuss astrophysical systems where jets are observed to influence the ambient
gas, in many cases by inflating large, hot, and low-density bubbles, and
systems where the operation of the JFM is still a theoretical suggestion. The
first group includes cooling flows in galaxies and clusters of galaxies,
star-forming galaxies, young stellar objects, and bipolar planetary nebulae.
The second group includes core collapse supernovae, the common envelope
evolution, the grazing envelope evolution, and intermediate luminosity optical
transients. The suggestion that the JFM operates in these four types of systems
is based on the assumption that jets are much more common than what is inferred
from objects where they are directly observed. Common to all eight types of
systems reviewed here is the presence of a compact object inside an extended
ambient gas. The ambient gas serves as a potential reservoir of mass to be
accreted on to the compact object. If the compact object launches jets as it
accretes mass, the jets might reduce the accretion rate as they deposit energy
to the ambient gas, or even remove the entire ambient gas, hence closing a
negative feedback cycle.


title: Parameter-free Locality Sensitive Hashing for Spherical Range Reporting

abstract:
  We present a data structure for *spherical range reporting* on a point set
$S$, i.e., reporting all points in $S$ that lie within radius $r$ of a given
query point $q$. Our solution builds upon the Locality-Sensitive Hashing (LSH)
framework of Indyk and Motwani, which represents the asymptotically best
solutions to near neighbor problems in high dimensions. While traditional LSH
data structures have several parameters whose optimal values depend on the
distance distribution from $q$ to the points of $S$, our data structure is
parameter-free, except for the space usage, which is configurable by the user.
Nevertheless, its expected query time basically matches that of an LSH data
structure whose parameters have been *optimally chosen for the data and query*
in question under the given space constraints. In particular, our data
structure provides a smooth trade-off between hard queries (typically addressed
by standard LSH) and easy queries such as those where the number of points to
report is a constant fraction of $S$, or where almost all points in $S$ are far
away from the query point. In contrast, known data structures fix LSH
parameters based on certain parameters of the input alone.
  The algorithm has expected query time bounded by $O(t (n/t)^\rho)$, where $t$
is the number of points to report and $\rho\in (0,1)$ depends on the data
distribution and the strength of the LSH family used. We further present a
parameter-free way of using multi-probing, for LSH families that support it,
and show that for many such families this approach allows us to get expected
query time close to $O(n^\rho+t)$, which is the best we can hope to achieve
using LSH. The previously best running time in high dimensions was $\Omega(t
n^\rho)$. For many data distributions where the intrinsic dimensionality of the
point set close to $q$ is low, we can give improved upper bounds on the
expected query time.


title:
Why (and How) Avoid Orthogonal Procrustes in Regularized Multivariate
  Analysis

abstract:
  Multivariate Analysis (MVA) comprises a family of well-known methods for
feature extraction that exploit correlations among input variables of the data
representation. One important property that is enjoyed by most such methods is
uncorrelation among the extracted features. Recently, regularized versions of
MVA methods have appeared in the literature, mainly with the goal to gain
interpretability of the solution. In these cases, the solutions can no longer
be obtained in a closed manner, and it is frequent to recur to the iteration of
two steps, one of them being an orthogonal Procrustes problem. This letter
shows that the Procrustes solution is not optimal from the perspective of the
overall MVA method, and proposes an alternative approach based on the solution
of an eigenvalue problem. Our method ensures the preservation of several
properties of the original methods, most notably the uncorrelation of the
extracted features, as demonstrated theoretically and through a collection of
selected experiments.


title: 3d N=2 mirror symmetry, pq-webs and monopole superpotentials

abstract:
  D3 branes stretching between webs of (p,q) 5branes provide an interesting
class of 3d N=2 theories. For generic pq-webs however the low energy field
theory is not known. We use 3d mirror symmetry and Type IIB S-duality to
construct Abelian gauge theories corresponding to D3 branes ending on both
sides of a pq-web made of many coincident NS5's intersecting one D5. These
theories contain chiral monopole operators in the superpotential and enjoy a
non trivial pattern of global symmetry enhancements. In the special case of the
pq-web with one D5 and one NS5, the 3d low energy SCFT admits three dual
formulations. This triality can be applied locally inside bigger quiver gauge
theories. We prove our statements using partial mirror symmetry `a la
Kapustin-Strassler, showing the equality of the S^3_b partition functions and
studying the quantum chiral rings.


title:
Nanoassembly of Polydisperse Photonic Crystals based on Binary and
  Ternary Polymer Opal Alloys

abstract:
  Ordered binary and ternary photonic crystals, composed of different sized
polymer-composite spheres with diameter ratios up to 120%, are generated using
bending induced oscillatory shearing (BIOS). This viscoelastic system creates
polydisperse equilibrium structures, producing mixed opaline colored films with
greatly reduced requirements for particle monodispersity, and very different
sphere size ratios, compared to other methods of nano-assembly.


title:
Building a Large Scale Dataset for Image Emotion Recognition: The Fine
  Print and The Benchmark

abstract:
  Psychological research results have confirmed that people can have different
emotional reactions to different visual stimuli. Several papers have been
published on the problem of visual emotion analysis. In particular, attempts
have been made to analyze and predict people's emotional reaction towards
images. To this end, different kinds of hand-tuned features are proposed. The
results reported on several carefully selected and labeled small image data
sets have confirmed the promise of such features. While the recent successes of
many computer vision related tasks are due to the adoption of Convolutional
Neural Networks (CNNs), visual emotion analysis has not achieved the same level
of success. This may be primarily due to the unavailability of confidently
labeled and relatively large image data sets for visual emotion analysis. In
this work, we introduce a new data set, which started from 3+ million weakly
labeled images of different emotions and ended up 30 times as large as the
current largest publicly available visual emotion data set. We hope that this
data set encourages further research on visual emotion analysis. We also
perform extensive benchmarking analyses on this large data set using the state
of the art methods including CNNs.


title: The Soergel category and the redotted Webster algebra

abstract:
  We describe a collection of graded rings which surject onto Webster rings for
sl(2) and which should be related to certain categories of singular Soergel
bimodules. In the first non-trivial case, we construct a categorical braid
group action which categorifies the Burau representation.


title: New limits on anomalous contributions to the $Wtb$ vertex

abstract:
  The latest and most precise top quark measurements at the LHC and Tevatron
are used to establish new limits on the $Wtb$ vertex. Recent results on the
measurements of the $W$-boson helicity fractions and single top quark
production cross section are combined in order to establish new limits at 95%
CL (confidence level). The allowed regions for these limits are presented, for
the first time, in three-dimensional graphics, for both real and imaginary
components of the different anomalous couplings, providing a new perspective on
the impact of the combination of different physics observables. These results
are also combined with the prospected future measurement of the single top
quark production cross section and $W$-boson helicity fractions at the LHC.


title: Graviton propagation within the context of the D-material universe

abstract:
  Motivated by the recent breakthrough of the detection of Gravitational Waves
(GW) from coalescent black holes by the aLIGO interferometers, we study the
propagation of GW in the {\sl D-material universe}, which we have recently
shown to be compatible with large-scale structure and inflationary
phenomenology. The medium of D-particles induces an effective mass for the
graviton, as a consequence of the formation of recoil-velocity field
condensates due to the underlying Born-Infeld dynamics. There is a competing
effect, due to a super-luminal refractive index, as a result of the
gravitational energy of D-particles acting as a dark matter component, with
which propagating gravitons interact. We examine conditions for the condensate
under which the latter effect is sub-leading. We argue that if quantum
fluctuations of the recoil velocity are relatively strong, which can happen in
the current era of the universe, then the condensate, and hence the induced
mass of the graviton, can be several orders of magnitude larger than the
magnitude of the cosmological constant today. Hence, we constrain the graviton
mass using aLIGO and pulsar timing observations (which give the most stringent
bounds at present). In such a sub-luminal graviton case, there is also a
gravitational Cherenkov effect for ordinary high energy cosmic matter, which is
further constrained by means of ultra-high-energy cosmic ray observations.
Assuming cosmic rays of extragalactic origin, the bounds on the quantum
condensate strength, based on the gravitational Cherenkov effect, are of the
same order as those from aLIGO measurements, in contrast to the case where a
galactic origin of the cosmic rays is assumed, in which case the corresponding
bounds are much weaker.


title: Programming complex shapes in thin nematic elastomer and glass sheets

abstract:
  Nematic elastomers and glasses are solids that display spontaneous distortion
under external stimuli. Recent advances in the synthesis of sheets with
controlled heterogeneities have enabled their actuation into non-trivial shapes
with unprecedented energy density. Thus, these have emerged as powerful
candidates for soft actuators. To further this potential, we introduce the key
metric constraint which governs shape changing actuation in these sheets. We
then highlight the richness of shapes amenable to this constraint through two
broad classes of examples which we term nonisometric origami and lifted
surfaces. Finally, we comment on the derivation of the metric constraint, which
arises from energy minimization in the interplay of stretching, bending and
heterogeneity in these sheets.


title: Note on restriction maps of Chow rings to Weyl group invariants

abstract:
  Let G be an algebraic group corresponding to a compact Lie group. We study
the restiction map from the Chow ring CH(BG) to the Wely group invariants
CH(BT)^W. For example, we note that if G is simply connect and H(G) has
torsion, then the restriction map is always not surjective.


title:
Probability of CME Impact on Exoplanets Orbiting M Dwarfs and Solar-Like
  Stars

abstract:
  Solar coronal mass ejections (CMEs) produce adverse space weather effects at
Earth. Planets in the close habitable zone of magnetically active M dwarfs may
experience more extreme space weather than at Earth, including frequent CME
impacts leading to atmospheric erosion and leaving the surface exposed to
extreme flare activity. Similar erosion may occur for hot Jupiters with close
orbits around solar-like stars. We have developed a model, Forecasting a CME's
Altered Trajectory (ForeCAT), which predicts a CME's deflection. We adapt
ForeCAT to simulate CME deflections for the mid-type M dwarf V374 Peg and hot
Jupiters with solar-type hosts. V374 Peg's strong magnetic fields can trap CMEs
at the M dwarfs's Astrospheric Current Sheet, the location of the minimum in
the background magnetic field. Solar-type CMEs behave similarly, but have much
smaller deflections and do not get trapped at the Astrospheric Current Sheet.
The probability of planetary impact decreases with increasing inclination of
the planetary orbit with respect to the Astrospheric Current Sheet - 0.5 to 5
CME impacts per day for M dwarf exoplanets, 0.05 to 0.5 CME impacts per day for
solar-type hot Jupiters. We determine the minimum planetary magnetic field
necessary to shield a planet's atmosphere from the CME impacts. M dwarf
exoplanets require values between tens and hundreds of Gauss. Hot Jupiters
around a solar-type star, however, require a more reasonable <30 G. These
values exceed the magnitude required to shield a planet from the stellar wind,
suggesting CMEs may be the key driver of atmospheric losses.


title:
Les Houches 2015: Physics at TeV colliders - new physics working group
  report

abstract:
  We present the activities of the 'New Physics' working group for the 'Physics
at TeV Colliders' workshop (Les Houches, France, 1-19 June, 2015). Our report
includes new physics studies connected with the Higgs boson and its properties,
direct search strategies, reinterpretation of the LHC results in the building
of viable models and new computational tool developments. Important signatures
for searches for natural new physics at the LHC and new assessments of the
interplay between direct dark matter searches and the LHC are also considered.


title:
HII Region Ionization of the Interstellar Medium: A Case Study of NGC
  7538

abstract:
  Using data from the Green Bank Telescope, we analyze the radio continuum
(free-free) and radio recombination line (RRL) emission of the compact HII
region NGC 7538 (Sharpless 158). We detect extended radio continuum and
hydrogen RRL emission beyond the photodissociation region (PDR) toward the
north and east, but a sharp decrease in emission toward the south and west.
This indicates that a non-uniform PDR morphology is affecting the amount of
radiation "leaking" through the PDR. The strongest carbon RRL emission is found
in the western PDR that appears to be dense. We compute a leaking fraction $f_R
= 15 \pm 5$ % of the radio continuum emission measured in the plane of the sky
which represents a lower limit when accounting for the three-dimensional
geometry of the region. We detect an average $^4\textrm{He}^+/\textrm{H}^+$
abundance ratio by number of $0.088 \pm 0.003$ inside the HII region and a
decrease in this ratio with increasing distance from the region beyond the PDR.
Using Herschel Space Observatory data, we show that small dust temperature
enhancements to the north and east of NGC 7538 coincide with extended radio
emission, but that the dust temperature enhancements are mostly contained
within a second PDR to the east. Unlike the giant HII region W43, the radiation
leaking from NGC 7538 seems to only affect the local ambient medium. This
suggests that giant HII regions may have a large effect in maintaining the
ionization of the interstellar medium.


title:
Unconstrained Still/Video-Based Face Verification with Deep
  Convolutional Neural Networks

abstract:
  Over the last five years, methods based on Deep Convolutional Neural Networks
(DCNNs) have shown impressive performance improvements for object detection and
recognition problems. This has been made possible due to the availability of
large annotated datasets, a better understanding of the non-linear mapping
between input images and class labels as well as the affordability of GPUs. In
this paper, we present the design details of a deep learning system for
unconstrained face recognition, including modules for face detection,
association, alignment and face verification. The quantitative performance
evaluation is conducted using the IARPA Janus Benchmark A (IJB-A), the JANUS
Challenge Set 2 (JANUS CS2), and the LFW dataset. The IJB-A dataset includes
real-world unconstrained faces of 500 subjects with significant pose and
illumination variations which are much harder than the Labeled Faces in the
Wild (LFW) and Youtube Face (YTF) datasets. JANUS CS2 is the extended version
of IJB-A which contains not only all the images/frames of IJB-A but also
includes the original videos for evaluating the video-based face verification
system. Some open issues regarding DCNNs for face verification problems are
then discussed.


title:
A Framework for Similarity Search with Space-Time Tradeoffs using
  Locality-Sensitive Filtering

abstract:
  We present a framework for similarity search based on Locality-Sensitive
Filtering (LSF), generalizing the Indyk-Motwani (STOC 1998) Locality-Sensitive
Hashing (LSH) framework to support space-time tradeoffs. Given a family of
filters, defined as a distribution over pairs of subsets of space with certain
locality-sensitivity properties, we can solve the approximate near neighbor
problem in $d$-dimensional space for an $n$-point data set with query time
$dn^{\rho_q+o(1)}$, update time $dn^{\rho_u+o(1)}$, and space usage $dn + n^{1
+ \rho_u + o(1)}$. The space-time tradeoff is tied to the tradeoff between
query time and update time, controlled by the exponents $\rho_q, \rho_u$ that
are determined by the filter family. Locality-sensitive filtering was
introduced by Becker et al. (SODA 2016) together with a framework yielding a
single, balanced, tradeoff between query time and space, further relying on the
assumption of an efficient oracle for the filter evaluation algorithm. We
extend the LSF framework to support space-time tradeoffs and through a
combination of existing techniques we remove the oracle assumption.
  Building on a filter family for the unit sphere by Laarhoven (arXiv 2015) we
use a kernel embedding technique by Rahimi & Recht (NIPS 2007) to show a
solution to the $(r,cr)$-near neighbor problem in $\ell_s^d$-space for $0 < s
\leq 2$ with query and update exponents
$\rho_q=\frac{c^s(1+\lambda)^2}{(c^s+\lambda)^2}$ and
$\rho_u=\frac{c^s(1-\lambda)^2}{(c^s+\lambda)^2}$ where $\lambda\in[-1,1]$ is a
tradeoff parameter. This result improves upon the space-time tradeoff of
Kapralov (PODS 2015) and is shown to be optimal in the case of a balanced
tradeoff. Finally, we show a lower bound for the space-time tradeoff on the
unit sphere that matches Laarhoven's and our own upper bound in the case of
random data.


title:
Theano: A Python framework for fast computation of mathematical
  expressions

abstract:
  Theano is a Python library that allows to define, optimize, and evaluate
mathematical expressions involving multi-dimensional arrays efficiently. Since
its introduction, it has been one of the most used CPU and GPU mathematical
compilers - especially in the machine learning community - and has shown steady
performance improvements. Theano is being actively and continuously developed
since 2008, multiple frameworks have been built on top of it and it has been
used to produce many state-of-the-art machine learning models.
  The present article is structured as follows. Section I provides an overview
of the Theano software and its community. Section II presents the principal
features of Theano and how to use them, and compares them with other similar
projects. Section III focuses on recently-introduced functionalities and
improvements. Section IV compares the performance of Theano against Torch7 and
TensorFlow on several machine learning models. Section V discusses current
limitations of Theano and potential ways of improving it.


title: Black hole radiation of massive spin-2 particles in (3+1) dimensions

abstract:
  This paper is devoted to the study of radiation of massive spin-2 boson
(graviton with a nonzero mass) through the event horizon of a generic static
and spherically symmetric black hole in (3+1) dimensions. To this end, we
consider the problem in the framework of quantum tunneling phenomenon. We
evaluate the tunneling rate of the massive gravitons by applying the
semiclassical WKB approximation to the Fierz-Pauli equation. The temperature of
the radiation is obtained with the aid of the Boltzmann expression. Our
findings are in good agreement with the existing Hawking radiation studies in
the current literature.


title: Recent results on permutations without short cycles

abstract:
  The density, denoted by $\kappa(n,r)$, of permutations having no cycles of
length less than $r+1$ in a symmetric group $\mathrm{S}_n$ is explored. New
asymptotic formulas for $\kappa(n,r)$ are obtained using the saddle-point
method when $5\leq r< n$ and $n\to\infty$.


title:
Non-degenerate locally connected models for plane continua and Julia
  sets

abstract:
  Suppose that a $X$ is an \emph{unshielded} plane continuum (i.e., $X$
coincides with the boundary of the unbounded complementary component of $X$).
Then there exists a \emph{finest monotone} map $m:X\to L$, where $L$ is a
locally connected continuum (i.e., $m^{-1}(y)$ is connected for each $y\in L$,
and any monotone map $\varphi:X\to L'$ onto a locally connected continuum is a
composition $\varphi=\varphi'\circ m$ where $\varphi':L\to L'$ is monotone).
Such finest locally connected model $L$ of $X$ is easier to understand because
$L$ is locally connected (in particular it can be described by a picture) and
represents the finest but still understandable decomposition of $X$ into
possibly complicated but pairwise disjoint \emph{fibers} (point-preimages) of
$m$. However, in some cases (i.e., in case $X$ is indecomposable) $L$ is a
singleton. In this paper we provide sufficient conditions for the existence of
a non-degenerate model depending on the existence of certain subcontinua of $X$
and apply these results to the connected Julia sets of polynomials.


title:
Round Robin: Quantitative Lateral Resolution of PHI XPS microprobes
  Quantum 2000 / Quantera SXM

abstract:
  The quantitative lateral resolution is a reliable measure for the quality of
an XPS microprobe equipped with a focused X-ray beam. It describes the long
tail contributions of the X-ray beam intensity distribution. The knowledge of
these long tail contributions is essential when judging on the origin of
signals of XPS spectra recorded on small-sized features. In this round robin
test the quantitative lateral resolution of 7 PHI XPS microprobes has been
estimated. As expected, the quantitative lateral resolution has significantly
larger values than the nominal X-ray beam diameter. The estimated values of the
quantitative lateral resolution follow a trend in time: The newer the
monochromator of an XPS microprobe so much the better the quantitative lateral
resolution.


title: Inference of High-dimensional Autoregressive Generalized Linear Models

abstract:
  Vector autoregressive models characterize a variety of time series in which
linear combinations of current and past observations can be used to accurately
predict future observations. For instance, each element of an observation
vector could correspond to a different node in a network, and the parameters of
an autoregressive model would correspond to the impact of the network structure
on the time series evolution. Often these models are used successfully in
practice to learn the structure of social, epidemiological, financial, or
biological neural networks. However, little is known about statistical
guarantees on estimates of such models in non-Gaussian settings. This paper
addresses the inference of the autoregressive parameters and associated network
structure within a generalized linear model framework that includes Poisson and
Bernoulli autoregressive processes. At the heart of this analysis is a
sparsity-regularized maximum likelihood estimator. While
sparsity-regularization is well-studied in the statistics and machine learning
communities, those analysis methods cannot be applied to autoregressive
generalized linear models because of the correlations and potential
heteroscedasticity inherent in the observations. Sample complexity bounds are
derived using a combination of martingale concentration inequalities and modern
empirical process techniques for dependent random variables. These bounds,
which are supported by several simulation studies, characterize the impact of
various network parameters on estimator performance.


title:
Photon pair generation in multimode optical fibers via intermodal
  phase-matching

abstract:
  We present a detailed study of photon-pair generation in a multimode optical
fiber via nonlinear four-wave mixing and intermodal phase-matching. We show
that in multimode optical fibers, it is possible to generate correlated photon
pairs in different fiber modes with large spectral shifts from the pump
wavelength, such that the photon pairs are immune to contamination from
spontaneous Raman scattering and residual pump photons. We also show that it is
possible to generate factorable two-photon states exhibiting minimal spectral
correlations between the photon pair components in conventional multimode
fibers using commonly available pump lasers. It is also possible to
simultaneously generate multiple factorable states from different FWM processes
in the same fiber and over a wide range of visible spectrum by varying the pump
wavelength without affecting the factorability of the states. Therefore,
photon-pair generation in multimode optical fibers exhibits considerable
potential for producing state engineered photons for quantum communications and
quantum information processing applications.


title:
Electron doping evolution of the magnetic excitations in
  NaFe$_{1-x}$Co$_x$As

abstract:
  We use time-of-flight (ToF) inelastic neutron scattering (INS) spectroscopy
to investigate the doping dependence of magnetic excitations across the phase
diagram of NaFe$_{1-x}$Co$_x$As with $x=0, 0.0175, 0.0215, 0.05,$ and $0.11$.
The effect of electron-doping by partially substituting Fe by Co is to form
resonances that couple with superconductivity, broaden and suppress low energy
($E\le 80$ meV) spin excitations compared with spin waves in undoped NaFeAs.
However, high energy ($E> 80$ meV) spin excitations are weakly Co-doping
dependent. Integration of the local spin dynamic susceptibility
$\chi^{\prime\prime}(\omega)$ of NaFe$_{1-x}$Co$_x$As reveals a total
fluctuating moment of 3.6 $\mu_B^2$/Fe and a small but systematic reduction
with electron doping. The presence of a large spin gap in the Co-overdoped
nonsuperconducting NaFe$_{0.89}$Co$_{0.11}$As suggests that Fermi surface
nesting is responsible for low-energy spin excitations. These results parallel
Ni-doping evolution of spin excitations in BaFe$_{2-x}$Ni$_x$As$_2$, confirming
the notion that low-energy spin excitations coupling with itinerant electrons
are important for superconductivity, while weakly doping dependent high-energy
spin excitations result from localized moments.


title: On the ground state energy of the inhomogeneous Bose gas

abstract:
  Within the self-consistent Hartree-Fock approximation, an explicit expression
for the ground state energy of inhomogeneous Bose gas is derived as a
functional of the inhomogeneous density of the Bose-Einstein condensate. The
results obtained are based on existence of the off-diagonal long-range order in
the single-particle density matrix for systems with a Bose-Einstein condensate.
This makes it possible to avoid the use of anomalous averages. The explicit
form of the kinetic energy, which differs from one in the Gross-Pitaevski
approach, is found. This form is valid beyond the Hartree-Fock approximation
and can be applied for arbitrary strong interparticle interaction.


title: Ask Your Neurons: A Deep Learning Approach to Visual Question Answering

abstract:
  We address a question answering task on real-world images that is set up as a
Visual Turing Test. By combining latest advances in image representation and
natural language processing, we propose Ask Your Neurons, a scalable, jointly
trained, end-to-end formulation to this problem.
  In contrast to previous efforts, we are facing a multi-modal problem where
the language output (answer) is conditioned on visual and natural language
inputs (image and question). We provide additional insights into the problem by
analyzing how much information is contained only in the language part for which
we provide a new human baseline. To study human consensus, which is related to
the ambiguities inherent in this challenging task, we propose two novel metrics
and collect additional answers which extend the original DAQUAR dataset to
DAQUAR-Consensus.
  Moreover, we also extend our analysis to VQA, a large-scale question
answering about images dataset, where we investigate some particular design
choices and show the importance of stronger visual models. At the same time, we
achieve strong performance of our model that still uses a global image
representation. Finally, based on such analysis, we refine our Ask Your Neurons
on DAQUAR, which also leads to a better performance on this challenging task.


title:
Variational Monte Carlo method for the Baeriswyl wavefunction:
  application to the one-dimensional bosonic Hubbard model

abstract:
  A variational Monte Carlo method for bosonic lattice models is introduced.
The method is based on the Baeriswyl projected wavefunction. The Baeriswyl
wavefunction consists of a kinetic energy based projection applied to the
wavefunction at infinite interaction, and is related to the shadow wavefunction
already used in the study of continuous models of bosons. The wavefunction at
infinite interaction, and the projector, are represented in coordinate space,
leading to an expression for expectation values which can be evaluated via
Monte Carlo sampling. We calculate the phase diagram and other properties of
the bosonic Hubbard model. The calculated phase diagram is in excellent
agreement with known quantum Monte Carlo results. We also analyze correlation
functions.


title:
A Theoretical Analysis of Deep Neural Networks for Texture
  Classification

abstract:
  We investigate the use of Deep Neural Networks for the classification of
image datasets where texture features are important for generating
class-conditional discriminative representations. To this end, we first derive
the size of the feature space for some standard textural features extracted
from the input dataset and then use the theory of Vapnik-Chervonenkis dimension
to show that hand-crafted feature extraction creates low-dimensional
representations which help in reducing the overall excess error rate. As a
corollary to this analysis, we derive for the first time upper bounds on the VC
dimension of Convolutional Neural Network as well as Dropout and Dropconnect
networks and the relation between excess error rate of Dropout and Dropconnect
networks. The concept of intrinsic dimension is used to validate the intuition
that texture-based datasets are inherently higher dimensional as compared to
handwritten digits or other object recognition datasets and hence more
difficult to be shattered by neural networks. We then derive the mean distance
from the centroid to the nearest and farthest sampling points in an
n-dimensional manifold and show that the Relative Contrast of the sample data
vanishes as dimensionality of the underlying vector space tends to infinity.


title: Is the Dirichlet Space a Quotient of $DA_n$?

abstract:
  We show that the Dirichlet space is not a quotient of the Drury-Arveson space
on the n-ball for any finite n. The proof is based a quantitative comparison of
the metrics induced by the Hilbert spaces


title: Lower Bounds on Time-Space Trade-Offs for Approximate Near Neighbors

abstract:
  We show tight lower bounds for the entire trade-off between space and query
time for the Approximate Near Neighbor search problem. Our lower bounds hold in
a restricted model of computation, which captures all hashing-based approaches.
In articular, our lower bound matches the upper bound recently shown in
[Laarhoven 2015] for the random instance on a Euclidean sphere (which we show
in fact extends to the entire space $\mathbb{R}^d$ using the techniques from
[Andoni, Razenshteyn 2015]).
  We also show tight, unconditional cell-probe lower bounds for one and two
probes, improving upon the best known bounds from [Panigrahy, Talwar, Wieder
2010]. In particular, this is the first space lower bound (for any static data
structure) for two probes which is not polynomially smaller than for one probe.
To show the result for two probes, we establish and exploit a connection to
locally-decodable codes.


title:
Status on bidimensional dark energy parameterizations using SNe Ia JLA
  and BAO datasets

abstract:
  Using current observations forecast type Ia supernovae (SNe Ia) Joint
Lightcurve Analysis (JLA) and baryon acoustic oscillations (BAO), in this paper
we investigate six bidimensional dark energy parameterisations in order to
explore which has more constraining power. Our results indicate that for
parameterisations that contain $z^2$-terms, the tension ($\sigma$-distance)
between these datasets seems to be reduced and their behaviour are $<$1$\sigma$
compatible with $\Lambda$CDM. Also, the results obtained by performing their
Bayesian evidence show a striking evidence in favour of the $\Lambda$CDM model,
but only one parameterisation can be distinguish by around $1\%$ from the other
models when the combination of datasets are considered.


title:
Resource Letter: RBAI-1: Research-based Assessment Instruments in
  Physics and Astronomy

abstract:
  This resource letter provides a guide to research-based assessment
instruments (RBAIs) of physics and astronomy content. These are standardized
assessments that were rigorously developed and revised using student ideas and
interviews, expert input, and statistical analyses. RBAIs have had a major
impact on physics and astronomy education reform by providing a universal and
convincing measure of student understanding that instructors can use to assess
and improve the effectiveness of their teaching. In this resource letter, we
present an overview of all content RBAIs in physics and astronomy by topic,
research validation, instructional level, format, and themes, to help faculty
find the best assessment for their course.


title:
Site-resolved measurement of the spin-correlation function in the
  Hubbard model

abstract:
  Exotic phases of matter can emerge from strong correlations in quantum
many-body systems. Quantum gas microscopy affords the opportunity to study
these correlations with unprecedented detail. Here we report site-resolved
observations of antiferromagnetic correlations in a two-dimensional,
Hubbard-regime optical lattice and demonstrate the ability to measure the
spin-correlation function over any distance. We measure the in-situ
distributions of the particle density and magnetic correlations, extract
thermodynamic quantities from comparisons to theory, and observe statistically
significant correlations over three lattice sites. The temperatures that we
reach approach the limits of available numerical simulations. The direct access
to many-body physics at the single-particle level demonstrated by our results
will further our understanding of how the interplay of motion and magnetism
gives rise to new states of matter.


title:
Integration over the quantum diagonal subgroup and associated
  Fourier-like algebras

abstract:
  By analogy with the classical construction due to Forrest, Samei and Spronk
we associate to every compact quantum group $\mathbb{G}$ a completely
contractive Banach algebra $A_\Delta(\mathbb{G})$, which can be viewed as a
deformed Fourier algebra of $\mathbb{G}$. To motivate the construction we first
analyse in detail the quantum version of the integration over the diagonal
subgroup, showing that although the quantum diagonal subgroups in fact never
exist, as noted earlier by Kasprzak and So{\l}tan, the corresponding
integration represented by a certain idempotent state on $C(\mathbb{G})$ makes
sense as long as $\mathbb{G}$ is of Kac type. Finally we analyse as an explicit
example the algebras $A_\Delta(O_N^+)$, $N\ge 2$, associated to Wang's free
orthogonal groups, and show that they are not operator weakly amenable.


title: Close encounters involving RAVE stars beyond the 47 Tucanae tidal radius

abstract:
  The most accurate 6D phase-space information from the Radial Velocity
Experiment (RAVE) was used to integrate the orbits of 105 stars around the
galactic globular cluster 47 Tucanae, to look for close encounters between them
in the past, with a minimum distance approach less than the cluster tidal
radius. The stars are currently over the distance range 3.0 kpc $<$ d $<$ 5.5
kpc. Using the uncertainties in the current position and velocity vector for
both, star and cluster, 105 pairs of star-cluster orbits were generated in a
Monte Carlo numerical scheme, integrated over 2 Gyr and considering an
axisymmetric and non-axisymmetric Milky-Way-like Galactic potential,
respectively. In this scheme, we identified 20 potential cluster members that
had close encounters with the globular cluster 47 Tucanae, all of which have a
relative velocity distribution (V$_{rel}$) less than 200 km s$^{-1}$ at the
minimum distance approach. Among these potential members, 9 had close
encounters with the cluster with velocities less than the escape velocity of 47
Tucanae, therefore a scenario of tidal stripping seems likely. These stars have
been classified with a 93\% confidence level, leading to the identification of
extratidal cluster stars. For the other 11 stars, V$_{rel}$ exceeds the escape
velocity of the cluster, therefore they were likely ejected or are unassociated
interlopers.


title: Orbit-spin coupling and the circulation of the Martian atmosphere

abstract:
  The physical origins of the observed interannual variability of weather and
climate on Mars are poorly understood. In this paper we introduce a
deterministic physical mechanism that may account for much of the variability
of the circulation of the Mars atmosphere on seasonal and longer timescales. We
derive a coupling expression linking orbital and rotational motions that
produces an acceleration field varying with position and with time on and
within a subject body. The spatially and temporally varying accelerations may
interfere constructively or destructively with large-scale flows of geophysical
fluids that are established and maintained by other means. The hypothesis
predicts cycles of intensification and relaxation of circulatory flows of
atmospheres on seasonal and longer timescales that are largely independent of
solar forcing. The predictions of the hypothesis may be tested through
numerical modeling. Examples from investigations of the atmospheric circulation
of Mars are provided to illustrate qualitative features and quantitative
aspects of the mechanism proposed. We briefly discuss the implications and
applicability of the orbit-spin coupling hypothesis for planets other than
Mars.


title:
$Extrasolar~Storms$: Pressure-dependent Changes In Light Curve Phase In
  Brown Dwarfs From Simultaneous $Hubble$ and $Spitzer$ Observations

abstract:
  We present $Spitzer$/IRAC Ch1 and Ch2 monitoring of six brown dwarfs during 8
different epochs over the course of 20 months. For four brown dwarfs, we also
obtained simulataneous $HST$/WFC3 G141 Grism spectra during two epochs and
derived light curves in five narrow-band filters. Probing different pressure
levels in the atmospheres, the multi-wavelength light curves of our six targets
all exhibit variations, and the shape of the light curves evolves over the
timescale of a rotation period, ranging from 1.4 h to 13 h. We compare the
shapes of the light curves and estimate the phase shifts between the light
curves observed at different wavelengths by comparing the phase of the primary
Fourier components. We use state-of-the-art atmosphere models to determine the
flux contribution of different pressure layers to the observed flux in each
filter. We find that the light curves that probe higher pressures are similar
and in phase, but are offset and often different from the light curves that
probe lower pressures. The phase differences between the two groups of light
curves suggest that the modulations seen at lower and higher pressures may be
introduced by different cloud layers.


title: Anatomy of the sign-problem in heavy-dense QCD

abstract:
  QCD at finite densities of heavy quarks is investigated using the
density-of-states method. The phase factor expectation value of the quark
determinant is calculated to unprecedented precision as a function of the
chemical potential. Results are validated using those from a reweighting
approach where the latter can produce a significant signal-to-noise ratio. We
confirm the particle-hole symmetry at low temperatures, find a strong sign
problem at intermediate values of the chemical potential, and an inverse Silver
Blaze feature for chemical potentials close to the onset value: here, the phase
quenched theory underestimates the density of the full theory.


title:
Tracking Illicit Drug Dealing and Abuse on Instagram using Multimodal
  Analysis

abstract:
  Illicit drug trade via social media sites, especially photo-oriented
Instagram, has become a severe problem in recent years. As a result, tracking
drug dealing and abuse on Instagram is of interest to law enforcement agencies
and public health agencies. In this paper, we propose a novel approach to
detecting drug abuse and dealing automatically by utilizing multimodal data on
social media. This approach also enables us to identify drug-related posts and
analyze the behavior patterns of drug-related user accounts. To better utilize
multimodal data on social media, multimodal analysis methods including
multitask learning and decision-level fusion are employed in our framework.
Experiment results on expertly labeled data have demonstrated the effectiveness
of our approach, as well as its scalability and reproducibility over
labor-intensive conventional approaches.


title:
Nonconvex Sparse Learning via Stochastic Optimization with Progressive
  Variance Reduction

abstract:
  We propose a stochastic variance reduced optimization algorithm for solving
sparse learning problems with cardinality constraints. Sufficient conditions
are provided, under which the proposed algorithm enjoys strong linear
convergence guarantees and optimal estimation accuracy in high dimensions. We
further extend the proposed algorithm to an asynchronous parallel variant with
a near linear speedup. Numerical experiments demonstrate the efficiency of our
algorithm in terms of both parameter estimation and computational performance.


title:
Control of spin-orbit torques through crystal symmetry in
  WTe2/ferromagnet bilayers

abstract:
  Recent discoveries regarding current-induced spin-orbit torques produced by
heavy-metal/ferromagnet and topological-insulator/ferromagnet bilayers provide
the potential for dramatically-improved efficiency in the manipulation of
magnetic devices. However, in experiments performed to date, spin-orbit torques
have an important limitation -- the component of torque that can compensate
magnetic damping is required by symmetry to lie within the device plane. This
means that spin-orbit torques can drive the most current-efficient type of
magnetic reversal (antidamping switching) only for magnetic devices with
in-plane anisotropy, not the devices with perpendicular magnetic anisotropy
that are needed for high-density applications. Here we show experimentally that
this state of affairs is not fundamental, but rather one can change the allowed
symmetries of spin-orbit torques in spin-source/ferromagnet bilayer devices by
using a spin source material with low crystalline symmetry. We use WTe2, a
transition-metal dichalcogenide whose surface crystal structure has only one
mirror plane and no two-fold rotational invariance. Consistent with these
symmetries, we generate an out-of-plane antidamping torque when current is
applied along a low-symmetry axis of WTe2/Permalloy bilayers, but not when
current is applied along a high-symmetry axis. Controlling S-O torques by
crystal symmetries in multilayer samples provides a new strategy for optimizing
future magnetic technologies.


title: The Avalanche Polynomial of a Graph

abstract:
  The (univariate) avalanche polynomial of a graph, introduced by Cori, Dartois
and Rossin in 2006, captures the distribution of the length of (principal)
avalanches in the abelian sandpile model. This polynomial has been used to show
that the avalanche distribution in the sandpile model on a multiple wheel graph
does not follow the expected power law function. In this article, we introduce
the (multivariate) avalanche polynomial that enumerates the toppling sequences
of all principal avalanches. This polynomial generalizes the univariate
avalanche polynomial and encodes more information. In particular, the avalanche
polynomial of a tree uniquely identifies the underlying tree. In this paper,
the avalanche polynomial is characterized for trees, cycles, wheels, and
complete graphs.


title: Diameter in ultra-small scale-free random graphs: Extended version

abstract:
  It is well known that many random graphs with infinite variance degrees are
ultrasmall. More precisely, for configuration models and preferential
attachment models where the proportion of vertices of degree at least $k$ is
approximately $k^{-(\tau-1)}$ with $\tau\in(2,3)$, typical distances between
pairs of vertices in a graph of size $n$ are asymptotic to $\frac{2\log\log
n}{|\log(\tau-2)|}$ and $\frac{4\log\log n}{|\log(\tau-2)|}$, respectively. In
this paper, we investigate the behavior of the diameter in such models. We show
that the diameter is of order $\log\log n$ precisely when the minimal forward
degree $d$ of vertices is at least $2$. We identify the exact constant, which
equals that of the typical distances plus $2/\log d$. Interestingly, the proof
for both models follows identical steps, even though the models are quite
different in nature.


title: Entry and return times for semi-flows

abstract:
  Haydn, Lacroix and Vaienti [Ann. Probab. 33 (2005)] proved that, for a given
ergodic map, the entry time distribution converges in the small target limit,
if and only if the corresponding return time distribution converges. The
present note explains how entry and return times can be interpreted in terms of
stationary point processes and their Palm distribution. This permits a
generalization of the results by Haydn et al. to non-ergodic maps and
continuous-time dynamical systems.


title:
$W^+W^-$ production at the LHC: fiducial cross sections and
  distributions in NNLO QCD

abstract:
  We consider QCD radiative corrections to $W^+W^-$ production at the LHC and
present the first fully differential predictions for this process at
next-to-next-to-leading order (NNLO) in perturbation theory. Our computation
consistently includes the leptonic decays of the $W$ bosons, taking into
account spin correlations, off-shell effects and non-resonant contributions.
Detailed predictions are presented for the different-flavour channel
$pp\to\mu^+e^-\nu_\mu {\bar \nu}_e+X$ at $\sqrt{s}=8$ and $13$ TeV. In
particular, we discuss fiducial cross sections and distributions in the
presence of standard selection cuts used in experimental $W^+W^-$ and $H\to
W^+W^-$ analyses at the LHC. The inclusive $W^+W^-$ cross section receives
large NNLO corrections, and, due to the presence of a jet veto, typical
fiducial cuts have a sizeable influence on the behaviour of the perturbative
expansion. The availability of differential NNLO predictions, both for
inclusive and fiducial observables, will play an important role in the rich
physics programme that is based on precision studies of $W^+W^-$ signatures at
the LHC.


title: Integral Canonical Models for Automorphic Vector Bundles of Abelian Type

abstract:
  We define and construct integral canonical models for automorphic vector
bundles over Shimura varieties of abelian type.
  More precisely, we first build on Kisin's work to construct integral
canonical models over rings of integers of number fields with finitely many
primes inverted for Shimura varieties of abelian type with hyperspecial level
at all primes we do not invert, compatible with Kisin's construction. We then
define a notion of an integral canonical model for the standard principal
bundles lying over Shimura varieties and proceed to construct them in the
abelian type case. With these in hand, one immediately also gets integral
models for automorphic vector bundles.


title: Gaussian Processes for Local Polynomial Forecasting of Time Series

abstract:
  Non-stationary time series with non-linear trends are frequently encountered
in applications. We consider here the feasibility of accurately forecasting the
signals of multiple such time series considering jointly when the number of
historic samples is inadequate for accurately forecasting the signal of each
considered in isolation. We develop a new forecasting methodology based on
Gaussian process regression that is successful in doing so in examples for
which the method of generalized least-squares is not. The new method employs a
form of deep machine learning.


title:
Measurement of $\sin^2\theta^{\rm lept}_{\rm eff}$ using $e^+e^-$ pairs
  from $\gamma^*/Z$ bosons produced in $p\bar{p}$ collisions at a
  center-of-momentum energy of 1.96 TeV

abstract:
  At the Fermilab Tevatron proton-antiproton ($p\bar{p}$) collider, Drell-Yan
lepton pairs are produced in the process $p \bar{p} \rightarrow e^+e^- + X$
through an intermediate $\gamma^*/Z$ boson. The forward-backward asymmetry in
the polar-angle distribution of the $e^-$ as a function of the $e^+e^-$-pair
mass is used to obtain $\sin^2\theta^{\rm lept}_{\rm eff}$, the effective
leptonic determination of the electroweak-mixing parameter $\sin^2\theta_W$.
The measurement sample, recorded by the Collider Detector at Fermilab (CDF),
corresponds to 9.4~fb$^{-1}$ of integrated luminosity from $p\bar{p}$
collisions at a center-of-momentum energy of 1.96 TeV, and is the full CDF Run
II data set. The value of $\sin^2\theta^{\rm lept}_{\rm eff}$ is found to be
$0.23248 \pm 0.00053$. The combination with the previous CDF measurement based
on $\mu^+\mu^-$ pairs yields $\sin^2\theta^{\rm lept}_{\rm eff} = 0.23221 \pm
0.00046$. This result, when interpreted within the specified context of the
standard model assuming $\sin^2 \theta_W = 1 - M_W^2/M_Z^2$ and that the $W$-
and $Z$-boson masses are on-shell, yields $\sin^2\theta_W = 0.22400 \pm
0.00045$, or equivalently a $W$-boson mass of $80.328 \pm 0.024 \;{\rm
GeV}/c^2$.