title:
On the frequency of star-forming galaxies in the vicinity of powerful
  AGNs: The case of SMM J04135+10277

abstract:
  (Abridged) In the last decade several massive molecular gas reservoirs were
found <100 kpc distance from active galactic nuclei (AGNs), residing in
gas-rich companion galaxies. The study of AGN-gas-rich companion systems opens
the opportunity to determine whether the stellar mass of massive local galaxies
was formed in their host after a merger event or outside of their host galaxy
in a close starbursting companion and later incorporated via mergers. We study
the quasar-companion galaxy system of SMM J04135+10277 (z=2.84) and investigate
the expected frequency of quasar-starburst galaxy pairs at high redshift using
a cosmological galaxy formation model. We use archive data and new APEX ArTeMiS
data to construct and model the spectral energy distribution of SMM J04135. We
also carry out a comprehensive analysis of the cosmological galaxy formation
model GALFORM with the aim of characterising how typical the system of SMM
J04135 is and whether quasar-star-forming galaxy pairs may constitute an
important stage in galaxy evolution. The companion galaxy of SMM J04135 is a
heavily dust-obscured starburst galaxy with a median star formation rate (SFR)
of $700\,\rm{M_{\odot}\,yr^{-1}}$, median dust mass of $5.1\times
10^9\,\rm{M_{\odot}}$ and median dust luminosity of $\textrm 9.3 \times
10^{12}\,\rm{L_{\odot}}$. Our simulations, performed at z=2.8, suggest that SMM
J04135 is not unique. In fact, at a distance of <100 kpc, 22% of our simulated
quasar sample have at least one companion galaxy of a stellar mass $>10^8\,
\rm{M_{\odot}}$, and 0.3% have at least one highly star-forming companion
($\rm{SFR}>100\,\rm{M_{\odot}\,yr^{-1}}$). Our results suggest that
quasar-gas-rich companion galaxy systems are common phenomena in the early
Universe and the high incidence of companions makes the study of such systems
crucial to understand the growth and hierarchical build-up of galaxies and
black holes.


title:
A second look at transition amplitudes in (2+1)-dimensional causal
  dynamical triangulations

abstract:
  Studying transition amplitudes in (2+1)-dimensional causal dynamical
triangulations, Cooperman and Miller discovered speculative evidence for
Lorentzian quantum geometries emerging from its Euclidean path integral. On the
basis of this evidence, Cooperman and Miller conjectured that Lorentzian de
Sitter spacetime, not Euclidean de Sitter space, dominates the ground state of
the quantum geometry of causal dynamical triangulations on large scales, a
scenario akin to that of the Hartle-Hawking no-boundary proposal in which
Lorentzian spacetimes dominate a Euclidean path integral. We argue against this
conjecture: we propose a more straightforward explanation of their findings,
and we proffer evidence for the Euclidean nature of these seemingly Lorentzian
quantum geometries. This explanation reveals another manner in which the
Euclidean path integral of causal dynamical triangulations behaves correctly in
its semiclassical limit--the implementation and interaction of multiple
constraints.


title:
The SCUBA-2 Cosmology Legacy Survey: the nature of bright submm galaxies
  from 2 deg2 of 850-um imaging

abstract:
  We present physical properties [redshifts (z), star-formation rates (SFRs)
and stellar masses (Mstar)] of bright (S850>4mJy) submm galaxies in the ~2deg2
COSMOS and UDS fields selected with SCUBA-2/JCMT. We complete the galaxy
identification process for all (~2000) S/N>3.5 850-um sources, but focus our
scientific analysis on a high-quality sub-sample of 651 S/N>4 sources with
complete multi-wavelength coverage including 1.1-mm imaging. We check the
reliability of our identifications, and the robustness of the SCUBA-2 fluxes by
revisiting the recent ALMA follow-up of 29 sources in our sample. Considering
>4mJy ALMA sources, our identification method has a completeness of ~86 per
cent with a reliability of ~92 per cent, and only ~15-20 per cent of sources
are significantly affected by multiplicity (when a secondary component
contributes >1/3 of the primary source flux). The impact of source blending on
the 850-um source counts as determined with SCUBA-2 is modest; scaling the
single-dish fluxes by ~0.9 reproduces the ALMA source counts. For our final
SCUBA-2 sample we find median z=2.40+0.10-0.04, SFR=287+-6Moyr-1, and
log(Mstar/Mo)=11.12+-0.02 (the latter for 349/651 sources with optical
identifications). These properties clearly locate bright submm galaxies on the
high-mass end of the 'main sequence' of star-forming galaxies out to z~6,
suggesting that major mergers are not a dominant driver of the high-redshift
submm-selected population. Their number densities are also consistent with the
evolving galaxy stellar mass function. Hence, the submm galaxy population is as
expected, albeit reproducing the evolution of the main sequence of star-forming
galaxies remains a challenge for theoretical models/simulations.


title: Profinite rigidity and surface bundles over the circle

abstract:
  If $M$ is a compact 3-manifold whose first betti number is 1, and $N$ is a
compact 3-manifold such that $\pi_1N$ and $\pi_1M$ have the same finite
quotients, then $M$ fibres over the circle if and only if $N$ does. We prove
that groups of the form $F_2\rtimes\mathbb{Z}$ are distinguished from one
another by their profinite completions. Thus, regardless of betti number, if
$M$ and $N$ are punctured torus bundles over the circle and $M$ is not
homeomorphic to $N$, then there is a finite group $G$ such that one of $\pi_1M$
and $\pi_1N$ maps onto $G$ and the other does not.


title:
Colours, Star formation Rates, and Environments of Star forming and
  Quiescent Galaxies at the Cosmic Noon

abstract:
  We analyse the star formation rates (SFRs), colours, and dust extinctions of
galaxies in massive (10^12.5-10^13.5 Msun) haloes at z~2 in high-resolution,
cosmological zoom-in simulations as part of the Feedback in Realistic
Environments (FIRE) project. The simulations do not model feedback from active
galactic nuclei (AGN) but reproduce well the observed relations between stellar
and halo mass and between stellar mass and SFR. About half (a third) of the
simulated massive galaxies (massive central galaxies) at z~2 have broad-band
colours classifying them as 'quiescent', and the fraction of quiescent centrals
is steeply decreasing towards higher redshift, in agreement with observations.
The progenitors of z~2 quiescent central galaxies are, on average, more
massive, have lower specific SFRs, and reside in more massive haloes than the
progenitors of similarly massive star forming centrals. The simulations further
predict a morphological mix of galaxies that includes disk-dominated,
irregular, and early-type galaxies. However, our simulations do not reproduce
the reddest of the quiescent galaxies observed at z~2. We also do not find
evidence for a colour bimodality, but are limited by our modest sample size. In
our simulations, the star formation activity of central galaxies of moderate
mass (Mstar~10^10-10^11 Msun) is affected by a combination of two distinct
physical processes. Outflows powered by stellar feedback result in a
short-lived (<100 Myr), but almost complete, suppression of star formation
activity after which many galaxies quickly recover and continue to form stars
at normal rates. In addition, galaxies residing in slowly growing haloes tend
to experience a moderate reduction of their SFRs ('cosmological starvation').
The relative importance of these processes and AGN feedback is uncertain and
will be explored in future work.


title:
A Kernel-based Lagrangian Method for Imperfectly-mixed Chemical
  Reactions

abstract:
  Current Lagrangian (particle-tracking) algorithms used to simulate
diffusion-reaction equations must employ a certain number of particles to
properly emulate the system dynamics---particularly for imperfectly-mixed
systems. The number of particles is tied to the statistics of the initial
concentration fields of the system at hand. Systems with shorter-range
correlation and/or smaller concentration variance require more particles,
potentially limiting the computational feasibility of the method. For the
well-known problem of bimolecular reaction, we show that using kernel-based,
rather than Dirac-delta, particles can significantly reduce the required number
of particles. We derive the fixed width of a Gaussian kernel for a given
reduced number of particles that analytically eliminates the error between
kernel and Dirac solutions at any specified time. We also show how to solve for
the fixed kernel size by minimizing the squared differences between solutions
over any given time interval. Numerical results show that the width of the
kernel should be kept below about 12% of the domain size, and that the analytic
equations used to derive kernel width suffer significantly from the neglect of
higher-order moments. The simulations with a kernel width given by least
squares minimization perform better than those made to match at one specific
time. A heuristic time-variable kernel size, based on the previous results,
performs on a par with the least squares fixed kernel size.


title: Equality of Opportunity in Supervised Learning

abstract:
  We propose a criterion for discrimination against a specified sensitive
attribute in supervised learning, where the goal is to predict some target
based on available features. Assuming data about the predictor, target, and
membership in the protected group are available, we show how to optimally
adjust any learned predictor so as to remove discrimination according to our
definition. Our framework also improves incentives by shifting the cost of poor
classification from disadvantaged groups to the decision maker, who can respond
by improving the classification accuracy.
  In line with other studies, our notion is oblivious: it depends only on the
joint statistics of the predictor, the target and the protected attribute, but
not on interpretation of individualfeatures. We study the inherent limits of
defining and identifying biases based on such oblivious measures, outlining
what can and cannot be inferred from different oblivious tests.
  We illustrate our notion using a case study of FICO credit scores.


title:
Indoor Space Recognition using Deep Convolutional Neural Network: A Case
  Study at MIT Campus

abstract:
  In this paper, we propose a robust and parsimonious approach using Deep
Convolutional Neural Network (DCNN) to recognize and interpret interior space.
DCNN has achieved incredible success in object and scene recognition. In this
study we design and train a DCNN to classify a pre-zoning indoor space, and
from a single phone photo to recognize the learned space features, with no need
of additional assistive technology. We collect more than 600,000 images inside
MIT campus buildings to train our DCNN model, and achieved 97.9% accuracy in
validation dataset and 81.7% accuracy in test dataset based on spatial-scale
fixed model. Furthermore, the recognition accuracy and spatial resolution can
be potentially improved through multiscale classification model. We identify
the discriminative image regions through Class Activating Mapping (CAM)
technique, to observe the model's behavior in how to recognize space and
interpret it in an abstract way. By evaluating the results with
misclassification matrix, we investigate the visual spatial feature of interior
space by looking into its visual similarity and visual distinctiveness, giving
insights into interior design and human indoor perception and wayfinding
research. The contribution of this paper is threefold. First, we propose a
robust and parsimonious approach for indoor navigation using DCNN. Second, we
demonstrate that DCNN also has a potential capability in space feature learning
and recognition, even under severe appearance changes. Third, we introduce a
DCNN based approach to look into the visual similarity and visual
distinctiveness of interior space.


title:
Automatic chemical design using a data-driven continuous representation
  of molecules

abstract:
  We report a method to convert discrete representations of molecules to and
from a multidimensional continuous representation. This model allows us to
generate new molecules for efficient exploration and optimization through
open-ended spaces of chemical compounds. A deep neural network was trained on
hundreds of thousands of existing chemical structures to construct three
coupled functions: an encoder, a decoder and a predictor. The encoder converts
the discrete representation of a molecule into a real-valued continuous vector,
and the decoder converts these continuous vectors back to discrete molecular
representations. The predictor estimates chemical properties from the latent
continuous vector representation of the molecule. Continuous representations
allow us to automatically generate novel chemical structures by performing
simple operations in the latent space, such as decoding random vectors,
perturbing known chemical structures, or interpolating between molecules.
Continuous representations also allow the use of powerful gradient-based
optimization to efficiently guide the search for optimized functional
compounds. We demonstrate our method in the domain of drug-like molecules and
also in the set of molecules with fewer that nine heavy atoms.


title: Non-parametric Morphologies of Mergers in the Illustris Simulation

abstract:
  We study non-parametric morphologies of mergers events in a cosmological
context, using the Illustris project. We produce mock g-band images comparable
to observational surveys from the publicly available Illustris simulation
idealized mock images at $z=0$. We then measure non parametric indicators:
asymmetry, Gini, $M_{20}$, clumpiness and concentration for a set of galaxies
with $M_* >10^{10}$ M$_\odot$. We correlate these automatic statistics with the
recent merger history of galaxies and with the presence of close companions.
Our main contribution is to assess in a cosmological framework, the empirically
derived non-parametric demarcation line and average time-scales used to
determine the merger rate observationally. We found that 98 per cent of
galaxies above the demarcation line have a close companion or have experienced
a recent merger event. On average, merger signatures obtained from the
$G-M_{20}$ criteria anticorrelate clearly with the elapsing time to the last
merger event. We also find that the asymmetry correlates with galaxy pair
separation and relative velocity, exhibiting the larger enhancements for those
systems with pair separations $d < 50$ h$^{-1}$ kpc and relative velocities $V
< 350$ km s$^{-1}$. We find that the $G-M_{20}$ is most sensitive to recent
mergers ($\sim0.14$ Gyr) and to ongoing mergers with stellar mass ratios
greater than 0.1. For this indicator, we compute a merger average observability
time-scale of $\sim0.2$ Gyr, in agreement with previous results and demonstrate
that the morphologically derived merger rate recovers the intrinsic total
merger rate of the simulation and the merger rate as a function of stellar
mass.


title: A Lefschetz Hyperplane Theorem for non-Archimedean Jacobians

abstract:
  We establish a Lefschetz hyperplane theorem for the Berkovich
analytifications of Jacobians of curves over an algebraically closed
non-Archimedean field. Let $J$ be the Jacobian of a curve $X$, and let $W_d
\subset J$ be the locus of effective divisor classes of degree $d$. We show
that the pair $(J^{an},W_d^{an})$ is $d$-connected, and thus in particular the
inclusion of the analytification of the theta divisor $\Theta^{an}$ into
$J^{an}$ satisfies a Lefschetz hyperplane theorem for $\mathbb{Z}$-cohomology
groups and homotopy groups. A key ingredient in our proof is a generalization,
over arbitrary characteristics and allowing arbitrary singularities on the
base, of a result of Brown and Foster for the homotopy type of analytic
projective bundles.


title: On the Structure Theorem of Clifford Algebras

abstract:
  In this paper, theory and construction of spinor representations of real
Clifford algebras $\cl_{p,q}$ in minimal left ideals are reviewed. Connection
with a general theory of semisimple rings is shown. The actual computations can
be found in, for example, [2].


title:
Charged-particle multiplicity and transverse-energy distribution using
  the Weibull-Glauber approach in heavy-ion collisions

abstract:
  The charged-particle multiplicity distribution and the transverse-energy
distribution measured in heavy-ion collisions at top RHIC and LHC energies are
described using the two-component model approach based on a convolution of the
Monte Carlo Glauber model with the Weibull model for particle production. The
model successfully describes the multiplicity and transverse-energy
distribution of minimum-bias collision data for a wide range of energies. The
Weibull-Glauber model can be used to determine the centrality classes in
heavy-ion collisions as an alternative to the conventional negative binomial
distribution (NBD)-Glauber approach.


title:
Lopsidependency in the Moser-Tardos framework: Beyond the Lopsided
  Lovasz Local Lemma

abstract:
  The Lopsided Lov\'{a}sz Local Lemma (LLLL) is a powerful probabilistic
principle which has been used in a variety of combinatorial constructions.
While originally a general statement about probability spaces, it has recently
been transformed into a variety of polynomial-time algorithms. The resampling
algorithm of Moser & Tardos (2010) is the most well-known example of this. A
variety of criteria have been shown for the LLLL; the strongest possible
criterion was shown by Shearer, and other criteria which are easier to use
computationally have been shown by Bissacot et al (2011), Pegden (2014),
Kolipaka & Szegedy (2011), and Kolipaka, Szegedy, Xu (2012).
  We show a new criterion for the Moser-Tardos algorithm to converge. This
criterion is stronger than the LLLL criterion; this is possible because it does
not apply in the same generality as the original LLLL; yet, it is strong enough
to cover many applications of the LLLL in combinatorics. We show a variety of
new bounds and algorithms. A noteworthy application is for $k$-SAT, with
bounded occurrences of variables. As shown in Gebauer, Sz\'{a}bo, and Tardos
(2011), a $k$-SAT instance in which every variable appears $L \leq
\frac{2^{k+1}}{e (k+1)}$ times, is satisfiable. Although this bound is
asymptotically tight (in $k$), we improve it to $L \leq \frac{2^{k+1} (1 -
1/k)^k}{k-1} - \frac{2}{k}$ which can be significantly stronger when $k$ is
small.
  We introduce a new parallel algorithm for the LLLL. While Moser & Tardos
described a simple parallel algorithm for the Lov\'{a}sz Local Lemma, and
described a simple sequential algorithm for a form of the Lopsided Lemma, they
were not able to combine the two. Our new algorithm applies in nearly all
settings in which the sequential algorithm works --- this includes settings
covered by our new stronger LLLL criterion.


title: Dual symmetry in a generalized Maxwell theory

abstract:
  We examine Podolsky's electrodynamics, which is noninvariant under the usual
duality transformation. We deduce a generalization of Hodge's star duality,
which leads to a dual gauge field and restores to a certain extent the dual
symmetry. The model becomes fully dual symmetric asymptotically when it reduces
to the Maxwell theory. We argue that this strict dual symmetry directly implies
the existence of the basic invariants of the electromagnetic fields.


title: Higher Dimensional Generalizations of the SYK Model

abstract:
  We discuss a 1+1 dimensional generalization of the Sachdev-Ye-Kitaev model.
The model contains $N$ Majorana fermions at each lattice site with a
nearest-neighbour hopping term. The SYK random interaction is restricted to low
momentum fermions of definite chirality within each lattice site. This gives
rise to an ordinary 1+1 field theory above some energy scale and a low energy
SYK-like behavior. We exhibit a class of low-pass filters which give rise to a
rich variety of hyperscaling behaviour in the IR. We also discuss another set
of generalizations which describes probing an SYK system with an external
fermion, together with the new scaling behavior they exhibit in the IR.


title: Large conformal metrics with prescribed scalar curvature

abstract:
  Let $(M,g)$ be an $n-$dimensional compact Riemannian manifold. Let $h$ be a
smooth function on $M$ and assume that it has a critical point $\xi\in M$ such
that $h(\xi)=0$ and which satisfies a suitable flatness assumption. We are
interested in finding conformal metrics $g_\lambda=u_\lambda^\frac4{n-2}g$,
with $u>0$, whose scalar curvature is the prescribed function
$h_\lambda=\lambda^2+h$, where $\lambda$ is a small parameter.
  In the positive case, i.e. when the scalar curvature $R_g$ is strictly
positive, we find a family of bubbling metrics $g_\lambda$, where $u_\lambda$
blows-up at the point $\xi$ and approaches zero far from $\xi$ as $\lambda$
goes to zero.
  In the general case, if in addition we assume that there exists a
non-degenerate conformal metric $g_0=u_0^\frac4{n-2}g$, with $u_0>0$, whose
scalar curvature is equal to $h$, then there exists a bounded family of
conformal metrics $g_{0,\lambda}=u_{0,\lambda}^\frac4{n-2}g$, with
$u_{0,\lambda}>0$, which satisfies $u_{0,\lambda}\to u_0$ uniformly as
$\lambda\to 0$. Here, we build a second family of bubbling metrics $g_\lambda$,
where $u_\lambda$ blows-up at the point $\xi$ and approaches $u_0$ far from
$\xi$ as $\lambda$ goes to zero. In particular, this shows that this problem
admits more than one solution.


title:
Diverse Beam Search: Decoding Diverse Solutions from Neural Sequence
  Models

abstract:
  Neural sequence models are widely used to model time-series data. Equally
ubiquitous is the usage of beam search (BS) as an approximate inference
algorithm to decode output sequences from these models. BS explores the search
space in a greedy left-right fashion retaining only the top-B candidates -
resulting in sequences that differ only slightly from each other. Producing
lists of nearly identical sequences is not only computationally wasteful but
also typically fails to capture the inherent ambiguity of complex AI tasks. To
overcome this problem, we propose Diverse Beam Search (DBS), an alternative to
BS that decodes a list of diverse outputs by optimizing for a
diversity-augmented objective. We observe that our method finds better top-1
solutions by controlling for the exploration and exploitation of the search
space - implying that DBS is a better search algorithm. Moreover, these gains
are achieved with minimal computational or memory over- head as compared to
beam search. To demonstrate the broad applicability of our method, we present
results on image captioning, machine translation and visual question generation
using both standard quantitative metrics and qualitative human studies.
Further, we study the role of diversity for image-grounded language generation
tasks as the complexity of the image changes. We observe that our method
consistently outperforms BS and previously proposed techniques for diverse
decoding from neural sequence models.


title: Quantum Cellular Automata Models for General Dirac Equation

abstract:
  The goal of this study is to provide an exact unitary quantum cellular
automata that, under discrete time steps, converges towards the Generalized
Dirac Equation (GDE) in the continuum limit. The evolutionary rules for such a
single particle walk are discussed in this paper, and it is shown that this
quantum celluar automata will maintain similar properties to the GDE.


title: Interplay of Site and Bond Electron-Phonon Coupling in One Dimension

abstract:
  The interplay of bond and charge correlations is studied in a one-dimensional
model with both Holstein and Su-Schrieffer-Heeger (SSH) couplings to quantum
phonons. The problem is solved exactly by quantum Monte Carlo simulations. If
one of the couplings dominates, the ground state is a Peierls insulator with
long-range bond or charge order. At weak coupling, the results suggest a
spin-gapped and repulsive metallic phase arising from the competing order
parameters and lattice fluctuations. Such a phase is absent from the pure SSH
model even for quantum phonons. At strong coupling, evidence for a continuous
transition between the two Peierls states is presented.


title:
The Stochastic Topic Block Model for the Clustering of Vertices in
  Networks with Textual Edges

abstract:
  Due to the significant increase of communications between individuals via
social media (Facebook, Twitter, Linkedin) or electronic formats (email, web,
e-publication) in the past two decades, network analysis has become a
unavoidable discipline. Many random graph models have been proposed to extract
information from networks based on person-to-person links only, without taking
into account information on the contents. This paper introduces the stochastic
topic block model (STBM), a probabilistic model for networks with textual
edges. We address here the problem of discovering meaningful clusters of
vertices that are coherent from both the network interactions and the text
contents. A classification variational expectation-maximization (C-VEM)
algorithm is proposed to perform inference. Simulated data sets are considered
in order to assess the proposed approach and to highlight its main features.
Finally, we demonstrate the effectiveness of our methodology on two real-word
data sets: a directed communication network and a undirected co-authorship
network.


title: The Calabi metric and desingularization of Einstein orbifolds

abstract:
  Consider an Einstein orbifold $(M_0,g_0)$ of real dimension $2n$ having a
singularity with orbifold group the cyclic group of order $n$ in ${\rm{SU}}(n)$
which is generated by an $n$th root of unity times the identity. Existence of a
Ricci-flat K\"ahler ALE metric with this group at infinity was shown by Calabi.
There is a natural "approximate" Einstein metric on the desingularization of
$M_0$ obtained by replacing a small neighborhood of the singular point of the
orbifold with a scaled and truncated Calabi metric. In this paper, we identify
the first obstruction to perturbing this approximate Einstein metric to an
actual Einstein metric. If $M_0$ is compact, we can use this to produce
examples of Einstein orbifolds which do not admit any Einstein metric in a
neighborhood of the natural approximate Einstein metric on the
desingularization. In the case that $(M_0,g_0)$ is asymptotically hyperbolic
Einstein and non-degenerate, we show that if the first obstruction vanishes,
then there does in fact exist an asymptotically hyperbolic Einstein metric on
the desingularization. We also obtain a non-existence result in the
asymptotically hyperbolic Einstein case, provided that the obstruction does not
vanish. This work extends a construction of Biquard in the case $n =2$, in
which case the Calabi metric is also known as the Eguchi-Hanson metric, but
there are some key points for which the higher-dimensional case differs.


title: Kinetics of Aggregation with Choice

abstract:
  We generalize the ordinary aggregation process to allow for choice. In
ordinary aggregation, two random clusters merge and form a larger aggregate. In
our implementation of choice, a target cluster and two candidate clusters are
randomly selected, and the target cluster merges with the larger of the two
candidate clusters. We study the long-time asymptotic behavior, and find that
as in ordinary aggregation, the size density adheres to the standard scaling
form. However, aggregation with choice exhibits a number of novel features.
First, the density of the smallest clusters exhibits anomalous scaling. Second,
both the small-size and the large-size tails of the density are overpopulated,
at the expense of the density moderate-size clusters. We also study the
complementary case where the smaller candidate clusters participates in the
aggregation process, and find abundance of moderate clusters at the expense of
small and large clusters. Additionally, we investigate aggregation processes
with choice among multiple candidate clusters, and a symmetric implementation
where the choice is between two pairs of clusters.


title: Local Euler obstructions of toric varieties

abstract:
  We use Matsui and Takeuchi's formula for toric A-discriminants to give
algorithms for computing local Euler obstructions and dual degrees of toric
surfaces and 3-folds. In particular, we consider weighted projective spaces. As
an application we give counterexamples to a conjecture by Matsui and Takeuchi.
As another application we recover the well-known fact that the only defective
normal toric surfaces are cones.


title: ResearchDoom and CocoDoom: Learning Computer Vision with Games

abstract:
  In this short note we introduce ResearchDoom, an implementation of the Doom
first-person shooter that can extract detailed metadata from the game. We also
introduce the CocoDoom dataset, a collection of pre-recorded data extracted
from Doom gaming sessions along with annotations in the MS Coco format.
ResearchDoom and CocoDoom can be used to train and evaluate a variety of
computer vision methods such as object recognition, detection and segmentation
at the level of instances and categories, tracking, ego-motion estimation,
monocular depth estimation and scene segmentation. The code and data are
available at http://www.robots.ox.ac.uk/~vgg/research/researchdoom.


title:
Model Reduction of Linear Multi-Agent Systems by Clustering and
  Associated $\mathcal{H}_2$- and $\mathcal{H}_\infty$-Error Bounds

abstract:
  In this paper, we study a model reduction technique for leader-follower
networked multi-agent systems defined on weighted, undirected graphs with
arbitrary linear multivariable agent dynamics. In the network graph of this
network, nodes represent the agents and edges represent communication links
between the agents. Only the leaders in the network receive an external input,
the followers only exchange information with their neighbors. The reduced
network is obtained by partitioning the set of nodes into disjoint sets, called
clusters, and associating with each cluster a single, new, node in a reduced
network graph. The resulting reduced network has a weighted, symmetric,
directed network graph, and inherits some of the structure of the original
network. We establish a priori upper bounds on the $\mathcal{H}_2$ and
$\mathcal{H}_\infty$ model reduction error for the special case that the graph
partition is almost equitable. These upper bounds depend on the Laplacian
eigenvalues of the original and reduced network, an auxiliary system associated
with the agent dynamics, and the number of nodes that belong to the same
clusters as the leaders in the network. Finally, we consider the problem of
obtaining a priori upper bounds if we cluster using arbitrary, possibly non
almost equitable, partitions.


title: Anomalous metapopulation dynamics on scale-free networks

abstract:
  We model transport of individuals across a heterogeneous scale-free network
where a few weakly connected nodes exhibit heavy-tailed residence times. Using
the empirical law Axiom of Cumulative Inertia and fractional analysis we show
that `anomalous cumulative inertia' overpowers highly connected nodes in
attracting network individuals. This fundamentally challenges the classical
result that individuals tend to accumulate in high-order nodes. The derived
residence time distribution has a non-trivial U-shape which we encounter
empirically across human residence and employment times.

categories: physics.soc-ph cond-mat.dis-nn cond-mat.soft cond-mat.stat-mech physics.data-an


title: Algorithmic aspects of branched coverings IV/V. Expanding maps

abstract:
  Thurston maps are branched self-coverings of the sphere whose critical points
have finite forward orbits. We give combinatorial and algebraic
characterizations of Thurston maps that are isotopic to expanding maps as
"Levy-free" maps and as maps with "contracting biset".
  We prove that every Thurston map decomposes along a unique minimal multicurve
into Levy-free and finite-order pieces, and this decomposition is
algorithmically computable. Each of these pieces admits a geometric structure.
  We apply these results to matings of post-critically finite polynomials,
extending a criterion by Mary Rees and Tan Lei: they are expanding if and only
if they do not admit a cycle of periodic rays.


title:
Symmetry-broken states in a system of interacting bosons on a two-leg
  ladder with a uniform Abelian gauge field

abstract:
  We study the quantum phases of bosons with repulsive contact interactions on
a two-leg ladder in the presence of a uniform Abelian gauge field. The model
realizes many interesting states, including Meissner phases, vortex-fluids,
vortex-lattices, charge-density-waves and the biased-ladder phase. Our work
focuses on the subset of these states that break a discrete symmetry. We use
density matrix renormalization group simulations to demonstrate the existence
of three vortex-lattice states at different vortex densities and we
characterize the phase transitions from these phases into neighboring states.
Furthermore, we provide an intuitive explanation of the chiral-current reversal
effect that is tied to some of these vortex lattices. We also study a
charge-density-wave state that exists at 1/4 particle filling at large
interaction strengths and flux values close to half a flux quantum. By changing
the system parameters, this state can transition into a completely gapped
vortex-lattice Mott-insulating state. We elucidate the stability of these
phases against nearest-neighbor interactions on the rungs of the ladder
relevant for experimental realizations with a synthetic lattice dimension. A
charge-density-wave state at 1/3 particle filling can be stabilized for flux
values close to half a flux-quantum and for very strong on-site interactions in
the presence of strong repulsion on the rungs. Finally, we analytically
describe the emergence of these phases in the low-density regime, and, in
particular, we obtain the boundaries of the biased-ladder phase, i.e., the
phase that features a density imbalance between the legs. We make contact to
recent quantum-gas experiments that realized related models and discuss
signatures of these quantum states in experimentally accessible observables.


title:
A convex framework for high-dimensional sparse Cholesky based covariance
  estimation

abstract:
  Covariance estimation for high-dimensional datasets is a fundamental problem
in modern day statistics with numerous applications. In these high dimensional
datasets, the number of variables p is typically larger than the sample size n.
A popular way of tackling this challenge is to induce sparsity in the
covariance matrix, its inverse or a relevant transformation. In particular,
methods inducing sparsity in the Cholesky pa- rameter of the inverse covariance
matrix can be useful as they are guaranteed to give a positive definite
estimate of the covariance matrix. Also, the estimated sparsity pattern
corresponds to a Directed Acyclic Graph (DAG) model for Gaussian data. In
recent years, two useful penalized likelihood methods for sparse estimation of
this Cholesky parameter (with no restrictions on the sparsity pattern) have
been developed. How- ever, these methods either consider a non-convex
optimization problem which can lead to convergence issues and singular
estimates of the covariance matrix when p > n, or achieve a convex formulation
by placing a strict constraint on the conditional variance parameters. In this
paper, we propose a new penalized likelihood method for sparse estimation of
the inverse covariance Cholesky parameter that aims to overcome some of the
shortcomings of current methods, but retains their respective strengths. We ob-
tain a jointly convex formulation for our objective function, which leads to
convergence guarantees, even when p > n. The approach always leads to a
positive definite and symmetric estimator of the covariance matrix. We
establish high-dimensional estima- tion and graph selection consistency, and
also demonstrate finite sample performance on simulated/real data.


title:
The late-type stellar density profile in the Galactic Center: A
  statistical approach

abstract:
  The late-type stellar population in the Galactic Center was first predicted
to reside in a dynamically relaxed cusp (power law slope ranging from 3/2 to
7/4). However, observations - which rely on models to correct for projection
effects - have suggested a flat distribution instead. The need for this
correction is due to the lack of information regarding the line-of-sight
distances. With a two decade long baseline in astrometric measurements, we are
now able to measure significant projected radial accelerations, six of which
are newly reported here, that directly constrain line-of-sight distances. Here
we present a statistical approach to take advantage of this information and
more accurately constrain the shape of the radial density profile of the
late-type stellar population in the Galactic Center.


title: Perverse Sheaves and Knot Contact Homology

abstract:
  In this paper, which is mostly a research announcement, we give a new
algebraic construction of knot contact homology in the sense of L. Ng [Ng05a].
For a link $L$ in $ {\mathbb R}^3 $, we define a differential graded (DG)
$k$-category $ \tilde{\mathscr A} $ with finitely many objects, whose
quasi-equivalence class is a topological invariant of $ L $. In the case when
$L$ is a knot, the endomorphism algebra of a distinguished object of $
\tilde{\mathscr A} $ coincides with the fully noncommutative knot DGA as
defined by Ekholm, Etnyre, Ng and Sullivan in [EENS13a]. The input of our
construction is a natural action of the braid group $B_n$ on the category of
perverse sheaves on a two-dimensional disk with singularities at $n$ marked
points, studied by Gelfand, MacPherson and Vilonen in [GMV96]. As an
application, we show that the category of finite-dimensional representations of
the link $k$-category $ \tilde{A} = H_0(\tilde{\mathscr A}) $ defined as the
$0$th homology of our DG category $ \tilde{\mathscr A} $ is equivalent to the
category of perverse sheaves on $ {\mathbb R}^3 $ which are singular along the
link $ L $. We also obtain several generalizations of the category $
\tilde{\mathscr A} $ by extending the Gelfand-MacPherson-Vilonen braid action.


title:
On the Largest Integer that is not a Sum of Distinct Positive $n$th
  Powers

abstract:
  It is known that for an arbitrary positive integer \(n\) the sequence
\(S(x^n)=(1^n, 2^n, \ldots)\) is complete, meaning that every sufficiently
large integer is a sum of distinct \(n\)th powers of positive integers. We
prove that every integer \(m\geq
(b-1)2^{n-1}(r+\frac{2}{3}(b-1)(2^{2n}-1)+2(b-2))^n-2a+ab\), where
\(a=n!2^{n^2}\), \(b=2^{n^3}a^{n-1}\), \(r=2^{n^2-n}a\), is a sum of distinct
\(n\)th powers of positive integers.


title: Flexible Dynamics of Two Quorum Sensing Coupled Repressilators

abstract:
  Genetic oscillators play important roles in cell life regulation. The
regulatory efficiency usually depends strongly on the emergence of stable
collective dynamic modes, which requires designing the interactions between
genetic networks. We investigate the dynamics of two identical synthetic
genetic repressilators coupled by an additional plasmid which implements quorum
sensing (QS) in each network thereby supporting global coupling. In a basic
genetic ring oscillator network in which three genes inhibit each other in
unidirectional manner, QS stimulates the transcriptional activity of chosen
genes providing for competition between inhibitory and stimulatory activities
localized in those genes. The "promoter strength", the Hill cooperativity
coefficient of transcription repression, and the coupling strength, i.e.,
parameters controlling the basic rates of genetic reactions, were chosen for
extensive bifurcation analysis. The results are presented as a map of dynamic
regimes. We found that the remarkable multistability of the anti-phase limit
cycle and stable homogeneous and inhomogeneous steady states exists over broad
ranges of control parameters. We studied the anti-phase limit cycle stability
and the evolution of irregular oscillatory regimes in the parameter areas where
the anti-phase cycle loses stability. In these regions we observed developing
complex oscillations, collective chaos, and multistability between regular
limit cycles and complex oscillations over uncommonly large intervals of
coupling strength. QS-coupling stimulates the appearance of intrachaotic
periodic windows with spatially symmetric and asymmetric partial limit cycles
which, in turn, change the type of chaos from a simple anti-phase character
into chaos composed of pieces of the trajectories having alternating polarity.
Abstract truncated...


title:
Constraining the Variability and Binary Fraction of Galactic Center
  Young Stars

abstract:
  We present constraints on the variability and binarity of young stars in the
central 10 arcseconds (~0.4 pc) of the Milky Way Galactic Center (GC) using
Keck Adaptive Optics data over a 12 year baseline. Given our experiment's
photometric uncertainties, at least 36% of our sample's known early-type stars
are variable. We identified eclipsing binary systems by searching for periodic
variability. In our sample of spectroscopically confirmed and likely early-type
stars, we detected the two previously discovered GC eclipsing binary systems.
We derived the likely binary fraction of main sequence, early-type stars at the
GC via Monte Carlo simulations of eclipsing binary systems, and find that it is
at least 32% with 90% confidence.


title:
InfraNotes: Inconspicuous Handwritten Trajectory Tracking for Lecture
  Note Recording with Infrared Sensors

abstract:
  Lecture notes are important for students to review and understand the key
points in the class. Unfortunately, the students often miss or lose part of the
lecture notes. In this paper, we design and implement an infrared sensor based
system, InfraNotes, to automatically record the notes on the board by sensing
and analyzing hand gestures of the lecturer. Compared with existing techniques,
our system does not require special accessories with lecturers such as
sensor-facilitated pens, writing surfaces or the video-taping infrastructure.
Instead, it only has an infrared-sensor module on the eraser holder of
black/white board to capture handwritten trajectories. With a lightweight
framework for handwritten trajectory processing, clear lecture notes can be
generated automatically. We evaluate the quality of lecture notes by three
standard character recognition techniques. The results indicate that InfraNotes
is a promising solution to create clear and complete lectures to promote the
education.


title:
mPDF: Framework for Watermarking PDF Files using Image Watermarking
  Algorithms

abstract:
  The advancement in digital technologies have made it possible to produce
perfect copies of digital content. In this environment, malicious users
reproduce the digital content and share it without compensation to the content
owner. Content owners are concerned about the potential loss of revenue and
reputation from piracy, especially when the content is available over the
Internet. Digital watermarking has emerged as a deterrent measure towards such
malicious activities. Several methods have been proposed for copyright
protection and fingerprinting of digital images. However, these methods are not
applicable to text documents as these documents lack rich texture information
which is abundantly available in digital images. In this paper, a framework
(mPDF) is proposed which facilitates the usage of digital image watermarking
algorithms on text documents. The proposed method divides a text document into
texture and non-texture blocks using an energy-based approach. After
classification, a watermark is embedded inside the texture blocks in a content
adaptive manner. The proposed method is integrated with five known image
watermarking methods and its performance is studied in terms of quality and
robustness. Experiments are conducted on documents in 11 different languages.
Experimental results clearly show that the proposed method facilitates the
usage of image watermarking algorithms on text documents and is robust against
attacks such as print & scan, print screen, and skew. Also, the proposed method
overcomes the drawbacks of existing text watermarking methods such as manual
inspection and language dependency.


title:
Computational Investigation of Half-Heusler Compounds for Spintronics
  Applications

abstract:
  We present first-principles density functional calculations of the electronic
structure, magnetism, and structural stability of 378 $\textit{XYZ}$
half-Heusler compounds (with $X=$ Cr, Mn, Fe, Co, Ni, Ru, Rh, $Y=$ Ti, V, Cr,
Mn, Fe, Ni, $Z=$ Al, Ga, In, Si, Ge, Sn, P, As, Sb). We find that a
"Slater-Pauling density of states" with a gap or pseudogap at three states per
atom below the gap in at least one spin channel is a common feature in
half-Heusler compounds. We find that the presence of such a gap at the Fermi
energy in one or both spin channels contributes greatly to the stability of a
half-Heusler compound. We calculate the formation energy of each compound and
systematically investigate its stability against all other phases in the Open
Quantum Materials Database (OQMD). We represent the thermodynamic phase
stability of each compound as its distance from the convex hull of stable
phases in the respective chemical space and show that the hull distance of a
compound is a good measure of the likelihood of its experimental synthesis. We
identify 26 18-electron semiconductors, 45 half-metals, and 34 near half-metals
with negative formation energy, that follow the Slater-Pauling rule of three
electrons per atom. Our calculations predict new thermodynamically stable
semiconducting phases NiScAs, RhTiP, and RuVAs, which merit further
experimental exploration. Further, two interesting zero-moment half-metals,
CrMnAs and MnCrAs, are calculated to have negative formation energy. In
addition, our calculations predict a number of new, hitherto unreported,
semiconducting (e.g., CoVGe, FeVAs), half-metallic (e.g., RhVSb), near
half-metallic (e.g., CoFeSb, CoVP) half-Heusler compounds to lie close to the
respective convex hull of stable phases, and thus may be experimentally
realized under suitable synthesis conditions, resulting in potential candidates
for various spintronics applications.


title: Instagram Post Data Analysis

abstract:
  Because of the spread of the Internet, social platforms become big data
pools. From there we can learn about the trends, culture and hot topics. This
project focuses on analyzing the data from Instagram. It shows the relationship
of Instagram filter data with location and number of likes to give users filter
suggestion on achieving more likes based on their location. It also analyzes
the popular hashtags in different locations to show visual culture differences
between different cities.


title: Densities of 3-vertex graphs

abstract:
  Let d_i(G) be the density of the 3-vertex i-edge graph in a graph G, i.e.,
the probability that three random vertices induce a subgraph with i edges. Let
S be the set of all quadruples (d_0,d_1,d_2,d_3) that are arbitrary close to
3-vertex graph densities in arbitrary large graphs. Huang, Linial, Naves, Peled
and Sudakov have recently determined the projection of the set S to the
(d_0,d_3) plane. We determine the projection of the set S to all the remaining
planes.


title:
Review: Nonstationary Spatial Modeling, with Emphasis on Process
  Convolution and Covariate-Driven Approaches

abstract:
  In many environmental applications involving spatially-referenced data,
limitations on the number and locations of observations motivate the need for
practical and efficient models for spatial interpolation, or kriging. A key
component of models for continuously-indexed spatial data is the covariance
function, which is traditionally assumed to belong to a parametric class of
stationary models. While convenient, the assumption of stationarity is rarely
realistic; as a result, there is a rich literature on alternative methodologies
which capture and model the nonstationarity present in most environmental
processes. This review document provides a rigorous and concise description of
the existing literature on nonstationary methods, paying particular attention
to process convolution (also called kernel smoothing or moving average)
approaches. A summary is also provided of more recent methods which leverage
covariate information and yield both interpretational and computational
benefits.
  Note: the article is borrowed from Chapters 1 and 2 of the author's Ph.D.
dissertation, joint with Catherine A. Calder.


title: A topological approach to the problem of emergence in complex systems

abstract:
  Emergent patterns in complex systems are related to many intriguing phenomena
in modern science and philosophy. Several conceptions such as weak, strong and
robust emergence have been proposed to emphasize different epistemological and
ontological aspects of the problem. One of the most important concerns is
whether emergence is an intrinsic property of the reality we observe, or it is
rather a consequence of epistemological limitations. To elucidate this
question, we propose a novel approximation through constructive topology, a
framework that allow us to map the space of observed objects (ontology) with
the knowledge subject conceptual apparatus (epistemology). Focusing in a
particular type of emergent processes, namely those accessible through
experiments and from which we have still no clue on the mechanistic processes
yielding its formation, we analyse how a knowledge subject would build a
conceptual explanatory framework. Working on these systems, we identify concept
disjunction as a critical logical operation needed to identify the constraints
of the system. Next, focusing on a three-bits synthetic system, we show how the
number and scope of the constraints hinder the development of such scheme.
Interestingly, we observe that our framework is unable to identify global
constraints, clearly linking the epistemological limits of the framework with
an ontological feature of the system. This allows us to propose a definition of
emergence strength which we make compatible with the scientific method through
the active intervention of the observer on the system. We think that this
definition reconciles previous attempts to classify emergent processes, at
least for the specific kind we discuss here. The paper finishes discussing the
relevance of global constraints in biological systems, understood as a downward
causal influence exerted by natural selection.


title: The asymptotic trace norm of random circulants and the graph energy

abstract:
  We compute the expected normalized trace norm (matrix/graph energy) of random
symmetric band circulant matrices and graphs in the limit of large sizes, and
obtain explicit bounds on the rate of convergence to the limit, and on the
probabilities of large deviations. We also show that random symmetric band
Toeplitz matrices have the same limit norm assuming that their band widths
remain small relative to their sizes. We compare the limit norms across a range
of related random matrix and graph ensembles.


title:
Fe3O4 thin films: controlling and manipulating an elusive quantum
  material

abstract:
  Fe3O4 (magnetite) is one of the most elusive quantum materials and at the
same time one of the most studied transition metal oxide materials for thin
film applications. The theoretically expected half-metallic behavior generates
high expectations that it can be used in spintronic devices. Yet, despite the
tremendous amount of work devoted to preparing thin films, the enigmatic first
order metal-insulator transition and the hall mark of magnetite known as the
Verwey transition, is in thin films extremely broad and occurs at substantially
lower temperatures as compared to that in high quality bulk single crystals.
Here we have succeeded in finding and making a particular class of substrates
that allows the growth of magnetite thin films with the Verwey transition as
sharp as in the bulk. Moreover, we are now able to tune the transition
temperature and, using tensile strain, increase it to substantially higher
values than in the bulk.


title: Atom Interferometry in a Warm Vapor

abstract:
  We demonstrate matterwave interference in a warm vapor of rubidium atoms.
Established approaches to light pulse atom interferometry rely on laser cooling
to concentrate a large ensemble of atoms into a velocity class resonant with
the atom optical light pulse. In our experiment, we show that clear
interference signals may be obtained without laser cooling. This effect relies
on the Doppler selectivity of the atom interferometer resonance. This
interferometer may be configured to measure accelerations, and we demonstrate
that multiple interferometers may be operated simultaneously by addressing
multiple velocity classes.


title: Flagella bending affects macroscopic properties of bacterial suspensions

abstract:
  To survive in harsh conditions, motile bacteria swim in complex environment
and respond to the surrounding flow. Here we develop a PDE model describing how
the flagella bending affects macroscopic properties of bacterial suspensions.
First, we show how the flagella bending contributes to the decrease of the
effective viscosity observed in dilute suspension. Our results do not impose
tumbling (random re-orientation) as it was done previously to explain the
viscosity reduction. Second, we demonstrate a possibility of bacterium escape
from the wall entrapment due to the self-induced buckling of flagella. Our
results shed light on the role of flexible bacterial flagella in interactions
of bacteria with shear flow and walls or obstacles.


title:
A construction of certain weak colimits and an exactness property of the
  2-category of categories

abstract:
  Given a 2-category $\mathcal{A}$, a $2$-functor $\mathcal{A} \overset {F}
{\longrightarrow} \mathcal{C}at$ and a distinguished 1-subcategory $\Sigma
\subset \mathcal{A}$ containing all the objects, a $\sigma$-cone for $F$ (with
respect to $\Sigma$) is a lax cone such that the structural $2$-cells
corresponding to the arrows of $\Sigma$ are invertible. The conical
$\sigma$-limit is the universal (up to isomorphism) $\sigma$-cone. The notion
of $\sigma$-limit generalises the well known notions of pseudo and lax limit.
We consider the fundamental notion of $\sigma$-filtered} pair $(\mathcal{A}, \,
\Sigma)$ which generalises the notion of 2-filtered 2-category. We give an
explicit construction of $\sigma$-filtered $\sigma$-colimits of categories,
construction which allows computations with these colimits. We then state and
prove a basic exactness property of the 2-category of categories, namely, that
$\sigma$-filtered $\sigma$-colimits commute with finite weighted pseudo (or bi)
limits. An important corollary of this result is that a $\sigma$-filtered
$\sigma$-colimit of exact category valued 2-functors is exact. This corollary
is essential in the 2-dimensional theory of flat and pro-representable
2-functors, that we develop elsewhere.


title: Learning What and Where to Draw

abstract:
  Generative Adversarial Networks (GANs) have recently demonstrated the
capability to synthesize compelling real-world images, such as room interiors,
album covers, manga, faces, birds, and flowers. While existing models can
synthesize images based on global constraints such as a class label or caption,
they do not provide control over pose or object location. We propose a new
model, the Generative Adversarial What-Where Network (GAWWN), that synthesizes
images given instructions describing what content to draw in which location. We
show high-quality 128 x 128 image synthesis on the Caltech-UCSD Birds dataset,
conditioned on both informal text descriptions and also object location. Our
system exposes control over both the bounding box around the bird and its
constituent parts. By modeling the conditional distributions over part
locations, our system also enables conditioning on arbitrary subsets of parts
(e.g. only the beak and tail), yielding an efficient interface for picking part
locations. We also show preliminary results on the more challenging domain of
text- and location-controllable synthesis of images of human actions on the
MPII Human Pose dataset.


title:
Approximate Nearest Neighbor Search on High Dimensional Data ---
  Experiments, Analyses, and Improvement (v1.0)

abstract:
  Approximate Nearest neighbor search (ANNS) is fundamental and essential
operation in applications from many domains, such as databases, machine
learning, multimedia, and computer vision. Although many algorithms have been
continuously proposed in the literature in the above domains each year, there
is no comprehensive evaluation and analysis of their performances.
  In this paper, we conduct a comprehensive experimental evaluation of many
state-of-the-art methods for approximate nearest neighbor search. Our study (1)
is cross-disciplinary (i.e., including 16 algorithms in different domains, and
from practitioners) and (2) has evaluated a diverse range of settings,
including 20 datasets, several evaluation metrics, and different query
workloads. The experimental results are carefully reported and analyzed to
understand the performance results. Furthermore, we propose a new method that
achieves both high query efficiency and high recall empirically on majority of
the datasets under a wide range of settings.


title: Volatility Smile as Relativistic Effect

abstract:
  We give an explicit formula for the probability distribution based on a
relativistic extension of Brownian motion. The distribution 1) is properly
normalized and 2) obeys the tower law (semigroup property), so we can construct
martingales and self-financing hedging strategies and price claims (options).
This model is a 1-constant-parameter extension of the Black-Scholes-Merton
model. The new parameter is the analog of the speed of light in Special
Relativity. However, in the financial context there is no "speed limit" and the
new parameter has the meaning of a characteristic diffusion speed at which
relativistic effects become important and lead to a much softer asymptotic
behavior, i.e., fat tails, giving rise to volatility smiles. We argue that a
nonlocal stochastic description of such (Levy) processes is inadequate and
discuss a local description from physics. The presentation is intended to be
pedagogical.


title:
Clustering of Local Group distances: publication bias or correlated
  measurements? IV. The Galactic Center

abstract:
  Aiming at deriving a statistically well-justified Galactic Center distance,
$R_0$, and reducing any occurrence of publication bias, we compiled the most
comprehensive and most complete database of Galactic Center distances available
to date, containing 273 new or revised $R_0$ estimates published since records
began in October 1918 until June 2016. We separate our $R_0$ compilation into
direct and indirect distance measurements. The latter include a large body of
estimates that rely on centroid determinations for a range of tracer
populations as well as measurements based on kinematic observations of objects
at the solar circle, combined with a mass and/or rotational model of the Milky
Way. Careful assessment of the Galactic Center distances resulting from orbital
modeling and statistical parallax measurements in the Galactic nucleus yields
our final Galactic Center distance recommendation of $R_0 = 8.3 \pm 0.2 \mbox{
(statistical)} \pm 0.4 \mbox{ (systematic)}$ kpc. The centroid-based distances
are in good agreement with this recommendation. Neither the direct measurements
nor the post-1990 centroid-based distance determinations suggest that
publication bias may be important. The kinematics-based distance estimates are
affected by significantly larger uncertainties, but they can be used to
constrain the Galaxy's rotation velocity at the solar Galactocentric distance,
$\Theta_0$. Our results imply that the International Astronomical
Union-recommended Galactic Center distance ($R_0^{\rm IAU} = 8.5$ kpc) needs a
downward adjustment, while its $\Theta_0$ recommendation ($\Theta_0 = 220$ km
s$^{-1}$) requires a substantial upward revision.


title:
Interstellar-Medium Mapping in M82 Through Light Echoes Around Supernova
  2014J

abstract:
  We present multiple-epoch measurements of the size and surface brightness of
the light echoes from supernova (SN) 2014J in the nearby starburst galaxy M82.
Hubble Space Telescope (HST) ACS/WFC images were taken ~277 and ~416 days after
B-band maximum in the filters F475W, F606W, and F775W. Observations with HST
WFC3/UVIS images at epochs ~216 and ~365 days (Crotts 2015) are included for a
more complete analysis. The images reveal the temporal evolution of at least
two major light-echo components. The first one exhibits a filled ring structure
with position-angle-dependent intensity. This radially extended, diffuse echo
indicates the presence of an inhomogeneous interstellar dust cloud ranging from
~100 pc to ~500 pc in the foreground of the SN. The second echo component
appears as an unresolved luminous quarter-circle arc centered on the SN. The
wavelength dependence of scattering measured in different dust components
suggests that the dust producing the luminous arc favors smaller grain sizes,
while that causing the diffuse light echo may have sizes similar to those of
the Milky Way dust. Smaller grains can produce an optical depth consistent with
that along the supernova-Earth line of sight measured by previous studies
around maximum light. Therefore, it is possible that the dust slab, from which
the luminous arc arises, is also responsible for most of the extinction towards
SN 2014J. The optical depths determined from the Milky Way-like dust in the
scattering matters are lower than that produced by the dust slab.


title: Anomalous Nernst Effect in Dirac Semimetal Cd3As2

abstract:
  Dirac and Weyl semimetals display a host of novel properties. In
Cd$_3$As$_2$, the Dirac nodes lead to a protection mechanism that strongly
suppresses backscattering in zero magnetic field, resulting in ultrahigh
mobility ($\sim$ 10$^7$ cm$^2$ V$^{-1}$ s$^{-1}$). In applied magnetic field,
an anomalous Nernst effect is predicted to arise from the Berry curvature
associated with the Weyl nodes. We report observation of a large anomalous
Nernst effect in Cd$_3$As$_2$. Both the anomalous Nernst signal and transport
relaxation time $\tau_{tr}$ begin to increase rapidly at $\sim$ 50 K. This
suggests a close relation between the protection mechanism and the anomalous
Nernst effect. In a field, the quantum oscillations of bulk states display a
beating effect, suggesting that the Dirac nodes split into Weyl states,
allowing the Berry curvature to be observed as an anomalous Nernst effect.


title:
A dimension reduction method with applications for coefficient inversion
  of diffusion equations

abstract:
  In this paper, we present a dimension reduction method to reduce the
dimension of parameter space and state space and efficiently solve inverse
problems. To this end, proper orthogonal decomposition (POD) and radial basis
function (RBF) are combined to represent the solution of forward model with a
form of variable separation. This POD-RBF method can be used to efficiently
evaluate the model's output. A gradient regularization method is presented to
solve the inverse problem with fast convergence. A generalized cross validation
method is suggested to select the regularization parameter and differential
step size for the gradient computation. Because the regularization method needs
many model's evaluations. This is desirable for POD-RBF method. Thus, the
POD-RBF method is integrated with the gradient regularization method to provide
an efficient approach to solve inverse problems. We focus on the coefficient
inversion of diffusion equations using the proposed approach. Based on
different types of measurement data and different basis functions for
coefficients, we present a few numerical examples for the coefficient
inversion. The numerical results show that accurate reconstruction for the
coefficient can be achieved efficiently.


title:
Problems with mean curvature-like operators and three-point boundary
  conditions

abstract:
  In this paper we study the existence of solutions for a new class of
nonlinear differential equations with three-point boundary conditions.
Existence of solutions are obtained by using the Leray-Schauder degree.


title: Continuous spectrum for a class of smooth mixing Schr\"odinger operators

abstract:
  We give the first example of a smooth volume preserving mixing dynamical
system such that the discrete Schr\"odinger operators on the line defined with
a potential generated by this system and a H\"older sampling function, have
almost surely a continuous spectrum.


title: Weaving knotted vector fields with tunable helicity

abstract:
  We present a general construction of divergence-free knotted vector fields
from complex scalar fields, whose closed field lines encode many kinds of knots
and links, including torus knots, their cables, the figure-8 knot and its
generalizations. As finite-energy physical fields they represent initial states
for fields such as the magnetic field in a plasma, or the vorticity field in a
fluid. We give a systematic procedure for calculating the vector potential,
starting from complex scalar functions with knotted zero filaments, thus
enabling an explicit computation of the helicity of these knotted fields. The
construction can be used to generate isolated knotted flux tubes, filled by
knots encoded in the lines of the vector field. Lastly we give examples of
manifestly knotted vector fields with vanishing helicity. Our results provide
building blocks for analytical models and simulations alike.

categories: math-ph hep-th math.MP physics.flu-dyn physics.plasm-ph


title: Testing noncommutativity-like model as a galactic density profile

abstract:
  Noncommutative-like model (NC-like) is an interesting alternative inspired by
string theory to understand and describe the velocity rotation curves of
galaxies without the inclusion of dark matter particles. In a natural way, a
Gaussian density profile emerges and is characterized by a parameter {\theta},
called the NC-like parameter. Hence we aim to confront the NC-like model with a
galaxy sample of the SPARC catalogue to constrain the model parameters and
compare statistically with the Einasto density profile using the Akaike and
Bayesian information criteria. According to our results, some galaxies prefer
the NC-like over the Einasto model while others do not support NC-like.


title:
Supervisory Control of Fuzzy Discrete Event Systems for Simulation
  Equivalence

abstract:
  The supervisory control theory of fuzzy discrete event systems (FDESs) for
fuzzy language equivalence has been developed. However, in a way, language
equivalence has limited expressiveness. So if the given specification can not
be expressed by language equivalence, then the control for language equivalence
does not work. In this paper, we further establish the supervisory control
theory of FDESs for fuzzy simulation equivalence whose expressiveness is
stronger than that of fuzzy language equivalence. First, we formalize the
notions of fuzzy simulation and fuzzy simulation equivalence between two FDESs.
Then we present a method for deciding whether there is a fuzzy simulation or
not. In addition, we also show several basic properties of fuzzy simulation
relations. Afterwards, we put forward the notion of fuzzy simulation-based
controllability, and particularly show that it serves as a necessary and
sufficient condition for the existence of the fuzzy supervisors of FDESs.
Moreover, we study the "range" control problem of FDESs. Some examples are
given to illustrate the main results obtained.


title:
Synchronization of Two and Three Optoeletronic Oscillators Operating in
  Chaotic Regime: Numerical Simulations and Schemes for Secure Communication

abstract:
  In this work we show a strategy for synchronization of three optoelectronic
oscillators (OEO) operating in chaotic regime. Two applications of synchronized
OEOs in secure communications are considered. In the first one the OEO is used
to produce a pseudo-random bit sequence. The second application is an optical
setup for secure transmission of sampled analog signals. Using numerical
simulations, we calculated the bit error rate taking into account parameter
mismatch noise and Gaussian noise in the input optical power. The conditions
for error rate of up to 15% during key generation are shown.


title:
The double-soft limit in cosmological correlation functions and graviton
  exchange effects

abstract:
  The graviton exchange effect on cosmological correlation functions is
examined by employing the double-soft limit technique. A new relation among
correlation functions that contain the effects due to graviton exchange
diagrams in addition to those due to scalar-exchange and
scalar-contact-interaction, is derived by using the background field method and
independently by the method of Ward identities associated with dilatation
symmetry. We compare these three terms, putting small values for the slow-roll
parameters and $(1-n_{s}) = 0.042$, where $n_{s}$ is the scalar spectral index.
It is argued that the graviton exchange effects are more dominant than the
other two and could be observed in the trispectrum in the double-soft limit.
Our observation strengthens the previous work by Seery, Sloth and Vernizzi, in
which it has been argued that the graviton exchange dominates in the
counter-collinear limit for single field slow-roll inflation.


title: Small Variance Asymptotics for Non-Parametric Online Robot Learning

abstract:
  Small variance asymptotics is emerging as a useful technique for inference in
large scale Bayesian non-parametric mixture models. This paper analyses the
online learning of robot manipulation tasks with Bayesian non-parametric
mixture models under small variance asymptotics. The analysis yields a scalable
online sequence clustering (SOSC) algorithm that is non-parametric in the
number of clusters and the subspace dimension of each cluster. SOSC groups the
new datapoint in its low dimensional subspace by online inference in a
non-parametric mixture of probabilistic principal component analyzers (MPPCA)
based on Dirichlet process, and captures the state transition and state
duration information online in a hidden semi-Markov model (HSMM) based on
hierarchical Dirichlet process. A task-parameterized formulation of our
approach autonomously adapts the model to changing environmental situations
during manipulation. We apply the algorithm in a teleoperation setting to
recognize the intention of the operator and remotely adjust the movement of the
robot using the learned model. The generative model is used to synthesize both
time-independent and time-dependent behaviours by relying on the principles of
shared and autonomous control. Experiments with the Baxter robot yield
parsimonious clusters that adapt online with new demonstrations and assist the
operator in performing remote manipulation tasks.


title: L-convexity on graph structures

abstract:
  In this paper, we study classes of discrete convex functions: submodular
functions on modular semilattices and L-convex functions on oriented modular
graphs. They were introduced by the author in complexity classification of
minimum 0-extension problems. We clarify the relationship to other discrete
convex functions, such as $k$-submodular functions, skew-bisubmodular
functions, L$^\natural$-convex functions, tree submodular functions, and
UJ-convex functions. We show that they are actually viewed as
submodular/L-convex functions in our sense. We also prove a sharp iteration
bound of the steepest descent algorithm for minimizing our L-convex functions.
The underlying structures, modular semilattices and oriented modular graphs,
have rich connections to projective and polar spaces, Euclidean building, and
metric spaces of global nonpositive curvature (CAT(0) spaces). By utilizing
these connections, we formulate an analogue of the Lov\'asz extension,
introduce well-behaved subclasses of submodular/L-convex functions, and show
that these classes can be characterized by the convexity of the Lov\'asz
extension. We demonstrate applications of our theory to combinatorial
optimization problems that include multicommodity flow, multiway cut, and
related labeling problems: these problems have been outside the scope of
discrete convex analysis so far.


title: Bi-Fuzzy Discrete Event Systems and Their Supervisory Control Theory

abstract:
  It is well known that type-1 fuzzy sets (T1 FSs) have limited capabilities to
handle some data uncertainties directly, and type-2 fuzzy sets (T2 FSs) can
cover the shortcoming of T1 FSs to a certain extent. Fuzzy discrete event
systems (FDESs) were proposed based on T1 FSs theory. Hence, FDES may not be a
satisfactory model to characterize some high-uncertainty systems. In this
paper, we propose a new model, called as bi-fuzzy discrete event systems
(BFDESs), by combining classical DESs theory and T2 FSs theory. Then, we
consider the supervisory control problem of BFDESs. The bi-fuzzy
controllability theorem and nonblocking bi-fuzzy controllability theorem are
demonstrated. Also, an algorithm for checking the bi-fuzzy controllability
condition is presented. In addition, two controllable approximations to an
uncontrollable language are investigated in detail. An illustrative example is
provided to show the applicability and the advantages of BFDESs model.


title: The Creative Process in Musical Composition: An Introspective Account

abstract:
  This chapter charts the creative process in the composition of a piece of
music titled 'Stream not gone dry' that unfolded, while I was primarily
occupied with other matters, over the course of nearly two decades. It avoids
discussion of the technical aspects of musical composition, and it can be read
by someone with no formal knowledge of music. The focus here is on what the
process of composing this particular piece of music says about how the creative
process works. My interpretation of the music-making process may be biased by
my academic view of creativity, but I believe that the influence works
primarily in the other direction, my understanding of how the creative process
works is derived from experiences creating. This intuitive understanding is
shaped over time by the process of reading scholarly papers on creativity and
working them into my own evolving theory of creativity, but the papers that I
resonate with and incorporate are those that are in line with my experience.
This chapter just makes the influence of personal experience more explicit than
in other more scholarly writings on creativity.


title:
Entanglement detection on an NMR quantum information processor using
  random local measurements

abstract:
  Random local measurements have recently been proposed to construct
entanglement witnesses and thereby detect the presence of bipartite
entanglement. We experimentally demonstrate the efficacy of one such scheme on
a two-qubit NMR quantum information processor. We show that a set of three
random local measurements suffices to detect the entanglement of a general
two-qubit state. We experimentally generate states with different amounts of
entanglement, and show that the scheme is able to clearly witness entanglement.
We perform complete quantum state tomography for each state and compute state
fidelity to validate our results. Further, we extend previous results and
perform a simulation using random local measurements to optimally detect
bipartite entanglement in a hybrid system of $2\otimes 3$ dimensionality.


title:
An Energy Stable Finite-Difference Scheme for Functionalized
  Cahn-Hilliard Equation and its Convergence Analysis

abstract:
  We present and analyze an unconditionally energy stable and convergent finite
difference scheme for the Functionalized Cahn-Hilliard equation. One key
difficulty associated with the energy stability is based on the fact that one
nonlinear energy functional term in the expansion appears as non-convex,
non-concave. To overcome this subtle difficulty, we add two auxiliary terms to
make the combined term convex, which in turns yields a convex-concave
decomposition of the physical energy. As a result, an application of the convex
splitting methodology assures both the unique solvability and the unconditional
energy stability of the proposed numerical scheme. To deal with a 4-Laplacian
solver in an $H^{-1}$ gradient flow at each time step, we apply an efficient
preconditioned steepest descent algorithm to solve the corresponding nonlinear
systems. In addition, a global in time $H_{\rm per}^2$ stability of the
numerical scheme is established at a theoretical level, which in turn ensures
the full order convergence analysis of the scheme. A few numerical results are
presented, which confirm the stability and accuracy of the proposed numerical
scheme.


title:
High Quality Stepped-Impedance Resonators Suitable for Circuit-QED
  Measurement of Superconducting Artificial Atoms

abstract:
  High quality factor coplanar resonators are critical elements in
superconducting quantum circuits. We describe the design, fabrication and
measurement of stepped impedance resonators (SIRs), which are more compact in
size than commonly used uniform impedance resonators (UIRs). With properly
chosen impedance ratio, SIRs can be 27% shorter than UIRs. As a result, the
area occupied by SIRs can be reduced. Two kinds of designs containing both SIRs
and UIRs are fabricated and measured. The power dependence of the extracted
internal quality factors (Qi) for all the resonators showed that SIRs and UIRs
have comparable performance with Qi around half-million under single-photon
level excitation. These results indicate that SIRs could be used in
superconducting quantum circuits. The reduced size of SIRs may also lead to
reduced overall circuit area and increased integration level.


title:
A Music-generating System Inspired by the Science of Complex Adaptive
  Systems

abstract:
  This paper presents NetWorks (NW), an interactive music generation system
that uses a hierarchically clustered scale free network to generate music that
ranges from orderly to chaotic. NW was inspired by the Honing Theory of
creativity, according to which human-like creativity hinges on (1) the ability
to self-organize and maintain dynamics at the 'edge of chaos' using something
akin to 'psychological entropy', and (2) the capacity to shift between analytic
and associative processing modes. At the 'edge of chaos', NW generates patterns
that exhibit emergent complexity through coherent development at low, mid, and
high levels of musical organization, and often suggests goal seeking behaviour.
The architecture consists of four 16-node modules: one each for pitch,
velocity, duration, and entry delay. The Core allows users to define how nodes
are connected, and rules that determine when and how nodes respond to their
inputs. The Mapping Layer allows users to map node output values to MIDI data
that is routed to software instruments in a digital audio workstation. By
shifting between bottom-up and top-down NW shifts between analytic and
associative processing modes.


title:
Quantum associative memory with linear and non-linear algorithms for the
  diagnosis of some tropical diseases

abstract:
  This paper presents the QAMDiagnos, a model of Quantum Associative Memory
(QAM) that can be a helpful tool for medical staff without experience or
laboratory facilities, for the diagnosis of four tropical diseases (malaria,
typhoid fever, yellow fever and dengue) which have several similar signs and
symptoms. The memory can distinguish a single infection from a polyinfection.
Our model is a combination of the improved versions of the original linear
quantum retrieving algorithm proposed by Ventura and the non-linear quantum
search algorithm of Abrams and Lloyd. From the given simulation results, it
appears that the efficiency of recognition is good when particular signs and
symptoms of a disease are inserted given that the linear algorithm is the main
algorithm. The non-linear algorithm helps confirm or correct the diagnosis or
give some advice to the medical staff for the treatment. So, our QAMDiagnos
that has a friendly graphical user interface for desktop and smart-phone is a
sensitive and a low-cost diagnostic tool that enables rapid and accurate
diagnosis of four tropical diseases.


title: Remote Creation of Quantum Coherence

abstract:
  We study remote creation of coherence (RCC) for a quantum system, A, with the
help of quantum operations on another system, B, and one-way classical
communication.We show that all the nonincoherent quantum states are useful for
RCC and all the incoherent-quantum states are not. The necessary and sufficient
conditions of RCC for the quantum operations on system B are presented for pure
states. The upper bound of average RCC is derived, giving a relation among the
entanglement (concurrence), the RCC of the given quantum state, and the RCC of
the corresponding maximally entangled state. Moreover, for two-qubit systems we
find a simple factorization law for the average remote-created coherence.


title:
Deep Convolutional Networks as Models of Generalization and Blending
  Within Visual Creativity

abstract:
  We examine two recent artificial intelligence (AI) based deep learning
algorithms for visual blending in convolutional neural networks (Mordvintsev et
al. 2015, Gatys et al. 2015). To investigate the potential value of these
algorithms as tools for computational creativity research, we explain and
schematize the essential aspects of the algorithms' operation and give visual
examples of their output. We discuss the relationship of the two algorithms to
human cognitive science theories of creativity such as conceptual blending
theory and honing theory, and characterize the algorithms with respect to
generation of novelty and aesthetic quality.


title: Amplitude analysis of the $\chi_{c1} \to \eta\pi^+\pi^-$ decays

abstract:
  Using $448.0 \times 10^6$~$\psi(3686)$ events collected with the BESIII
detector, an amplitude analysis is performed for
$\psi(3686)\to\gamma\chi_{c1}$, $\chi_{c1}\to\eta\pi^+\pi^-$ decays. The most
dominant two-body structure observed is $a_0(980)^{\pm}\pi^{\mp}$;
$a_0(980)^{\pm}\to\eta\pi^{\pm}$. The $a_0(980)$ line shape is modeled using a
dispersion relation, and a significant non-zero $a_0(980)$ coupling to the
$\eta^{\prime}\pi$ channel is measured. We observe $\chi_{c1}\to a_2(1700)\pi$
production for the first time, with a significance larger than 17$\sigma$. The
production of mesons with exotic quantum numbers, $J^{PC}=1^{-+}$, is
investigated, and upper limits for the branching fractions $\chi_{c1}\to
\pi_1(1400)^{\pm}\pi^{\mp}$, $\chi_{c1}\to \pi_1(1600)^{\pm}\pi^{\mp}$, and
$\chi_{c1}\to\pi_1(2015)^{\pm}\pi^{\mp}$, with subsequent $\pi_1(X)^{\pm} \to
\eta\pi^{\pm}$ decay, are determined.


title:
Engineering the structural and electronic phases of MoTe2 through W
  substitution

abstract:
  MoTe$_2$ is an exfoliable transition metal dichalcogenide (TMD) which
crystallizes in three symmetries, the semiconducting trigonal-prismatic
$2H-$phase, the semimetallic $1T^{\prime}$ monoclinic phase, and the
semimetallic orthorhombic $T_d$ structure. The $2H-$phase displays a band gap
of $\sim 1$ eV making it appealing for flexible and transparent
optoelectronics. The $T_d-$phase is predicted to possess unique topological
properties which might lead to topologically protected non-dissipative
transport channels. Recently, it was argued that it is possible to locally
induce phase-transformations in TMDs, through chemical doping, local heating,
or electric-field to achieve ohmic contacts or to induce useful functionalities
such as electronic phase-change memory elements. The combination of
semiconducting and topological elements based upon the same compound, might
produce a new generation of high performance, low dissipation optoelectronic
elements. Here, we show that it is possible to engineer the phases of MoTe$_2$
through W substitution by unveiling the phase-diagram of the
Mo$_{1-x}$W$_x$Te$_2$ solid solution which displays a semiconducting to
semimetallic transition as a function of $x$. We find that only $\sim 8$ \% of
W stabilizes the $T_d-$phase at room temperature. Photoemission spectroscopy,
indicates that this phase possesses a Fermi surface akin to that of WTe$_2$.


title:
Frequency Estimation of Multiple Sinusoids with Three Sub-Nyquist
  Channels

abstract:
  Frequency estimation of multiple sinusoids is significant in both theory and
application. In some application scenarios, only sub-Nyquist samples are
available to estimate the frequencies. A conventional approach is to sample the
signals at several lower rates. In this paper, we address frequency estimation
of the signals in the time domain through undersampled data. We analyze the
impact of undersampling and demonstrate that three sub-Nyquist channels are
generally enough to estimate the frequencies provided the undersampling ratios
are pairwise coprime. We deduce the condition that leads to the failure of
resolving frequency ambiguity when two coprime undersampling channels are
utilized. When three-channel sub-Nyquist samples are used jointly, the
frequencies can be determined uniquely and the correct frequencies are
estimated. Numerical experiments verify the correctness of our analysis and
conclusion.


title: 4D Crop Monitoring: Spatio-Temporal Reconstruction for Agriculture

abstract:
  Autonomous crop monitoring at high spatial and temporal resolution is a
critical problem in precision agriculture. While Structure from Motion and
Multi-View Stereo algorithms can finely reconstruct the 3D structure of a field
with low-cost image sensors, these algorithms fail to capture the dynamic
nature of continuously growing crops. In this paper we propose a 4D
reconstruction approach to crop monitoring, which employs a spatio-temporal
model of dynamic scenes that is useful for precision agriculture applications.
Additionally, we provide a robust data association algorithm to address the
problem of large appearance changes due to scenes being viewed from different
angles at different points in time, which is critical to achieving 4D
reconstruction. Finally, we collected a high quality dataset with ground truth
statistics to evaluate the performance of our method. We demonstrate that our
4D reconstruction approach provides models that are qualitatively correct with
respect to visual appearance and quantitatively accurate when measured against
the ground truth geometric properties of the monitored crops.


title: Boost K-Means

abstract:
  Due to its simplicity and versatility, k-means remains popular since it was
proposed three decades ago. The performance of k-means has been enhanced from
different perspectives over the years. Unfortunately, a good trade-off between
quality and efficiency is hardly reached. In this paper, a novel k-means
variant is presented. Different from most of k-means variants, the clustering
procedure is driven by an explicit objective function, which is feasible for
the whole l2-space. The classic egg-chicken loop in k-means has been simplified
to a pure stochastic optimization procedure. The procedure of k-means becomes
simpler and converges to a considerably better local optima. The effectiveness
of this new variant has been studied extensively in different contexts, such as
document clustering, nearest neighbor search and image clustering. Superior
performance is observed across different scenarios.


title: Honing Theory: A Complex Systems Framework for Creativity

abstract:
  This paper proposes a theory of creativity, referred to as honing theory,
which posits that creativity fuels the process by which culture evolves through
communal exchange amongst minds that are self-organizing, self-maintaining, and
self-reproducing. According to honing theory, minds, like other selforganizing
systems, modify their contents and adapt to their environments to minimize
entropy. Creativity begins with detection of high psychological entropy
material, which provokes uncertainty and is arousalinducing. The creative
process involves recursively considering this material from new contexts until
it is sufficiently restructured that arousal dissipates. Restructuring involves
neural synchrony and dynamic binding, and may be facilitated by temporarily
shifting to a more associative mode of thought. A creative work may similarly
induce restructuring in others, and thereby contribute to the cultural
evolution of more nuanced worldviews. Since lines of cultural descent
connecting creative outputs may exhibit little continuity, it is proposed that
cultural evolution occurs at the level of self-organizing minds, outputs
reflect their evolutionary state. Honing theory addresses challenges not
addressed by other theories of creativity, such as the factors that guide
restructuring, and in what sense creative works evolve. Evidence comes from
empirical studies, an agent-based computational model of cultural evolution,
and a model of concept combination.


title: An Order Statistics Approach to the Halo Model for Galaxies

abstract:
  We use the Halo Model to explore the implications of assuming that galaxy
luminosities in groups are randomly drawn from an underlying luminosity
function. We show that even the simplest of such order statistics models -- one
in which this luminosity function $p(L)$ is universal -- naturally produces a
number of features associated with previous analyses based on the `central plus
Poisson satellites' hypothesis. These include the monotonic relation of mean
central luminosity with halo mass, the Lognormal distribution around this mean,
and the tight relation between the central and satellite mass scales. In stark
contrast to observations of galaxy clustering, however, this model predicts
$\textit{no}$ luminosity dependence of large scale clustering. We then show
that an extended version of this model, based on the order statistics of a
$\textit{halo mass dependent}$ luminosity function $p(L|m)$, is in much better
agreement with the clustering data as well as satellite luminosities, but
systematically under-predicts central luminosities. This brings into focus the
idea that central galaxies constitute a distinct population that is affected by
different physical processes than are the satellites. We model this physical
difference as a statistical brightening of the central luminosities, over and
above the order statistics prediction. The magnitude gap between the brightest
and second brightest group galaxy is predicted as a by-product, and is also in
good agreement with observations. We propose that this order statistics
framework provides a useful language in which to compare the Halo Model for
galaxies with more physically motivated galaxy formation models


title:
Forward and Backward Mean-Field Stochastic Partial Differential Equation
  and Optimal Control

abstract:
  This paper is mainly concerned with the solutions to both forward and
backward mean-field stochastic partial differential equation and the
corresponding optimal control problem for mean-field stochastic partial
differential equation. We first prove the continuous dependence theorems of
forward and backward mean-field stochastic partial differential equations and
show the existence and uniqueness of solutions to them. Then we establish
necessary and sufficient optimality conditions of the control problem in the
form of Pontryagin's maximum principles. To illustrate the theoretical results,
we apply stochastic maximum principles to study an example, an
infinite-dimensional linear-quadratic control problem of mean-field type.
Further an application to a Cauchy problem for a controlled stochastic linear
PDE of mean-field type are studied.


title:
Superluminal light propagation via quantum interference in decay
  channels

abstract:
  We examine the propagation of a weak probe light through a coherently driven
$Y$-type system. Under the condition that the excited atomic levels decay via
same vacuum modes, the effects of quantum interference in decay channels are
considered. It is found that the interference in decay channels results in a
lossless anomalous dispersion between two gain peaks. We demonstrate that the
probe pulse propagation can in principle be switched from subluminal to
superluminal due to the decay-induced interference. We also show that the
system exhibits a high index of refraction with negligible absorption for the
driving fields. A dressed-state picture of the atom-light interaction is
described to explain the numerical results.


title: Perceptually-Driven Video Coding with the Daala Video Codec

abstract:
  The Daala project is a royalty-free video codec that attempts to compete with
the best patent-encumbered codecs. Part of our strategy is to replace core
tools of traditional video codecs with alternative approaches, many of them
designed to take perceptual aspects into account, rather than optimizing for
simple metrics like PSNR. This paper documents some of our experiences with
these tools, which ones worked and which did not. We evaluate which tools are
easy to integrate into a more traditional codec design, and show results in the
context of the codec being developed by the Alliance for Open Media.


title:
Enhancement of Impedance by Chromium Substitution and Correlation with
  DC Resistivity in Cobalt Ferrite

abstract:
  Chromium substituted cobalt ferrite with grain size less than the single
domain (approx. 70 nm) has been prepared by the sol-gel method. XRD analysis
reveals that the samples crystallize to cubic symmetry with spacegroup number
227. Two transition temperatures (TD (approx. 450 K) and TM (approx. 600 K)
have been observed from the impedance verses temperature measurement. TD
increases with the increase in frequency due to dipole response to the
frequency. TM is comparable with the para-ferrimagnetic transition temperature
of cobalt ferrite, which is independent of frequency. This result is well
supported by the temperature dependent DC conductivity measurement. The
modified Debye relaxation could be explained the impedance spectra of
CoFe2-xCrxO4. The grain and grain boundary effect on impedance spectroscopy has
been observed from Cole-Cole analysis. The ac conductivity follows Arrhenius
behavior at different frequencies. All the samples exhibit the negative
temperature coefficient of resistance behavior which reveals the semiconducting
behavior of the material. The Mott VRH model could explain the DC electrical
conductivity. Both ac impedance and DC resistivity are well co-related each
other to explain the electron transport properties in Cr substituted cobalt
ferrite. The electrical transport properties could be explained by the electron
hopping between different metal ions via oxygen in the material.


title: A nonparametric sequential test for online randomized experiments

abstract:
  We propose a nonparametric sequential test that aims to address two practical
problems pertinent to online randomized experiments: (i) how to do a hypothesis
test for complex metrics; (ii) how to prevent type $1$ error inflation under
continuous monitoring. The proposed test does not require knowledge of the
underlying probability distribution generating the data. We use the bootstrap
to estimate the likelihood for blocks of data followed by mixture sequential
probability ratio test. We validate this procedure on data from a major online
e-commerce website. We show that the proposed test controls type $1$ error at
any time, has good power, is robust to misspecification in the distribution
generating the data, and allows quick inference in online randomized
experiments.


title: Deformed shell model study of heavy N=Z nuclei and dark matter detection

abstract:
  Deformed shell model (DSM) based on Hartree-Fock intrinsic states is applied
to address two current problems of interest. Firstly, in the $f_{5/2}pg_{9/2}$
model space with jj44b effective interaction along with isospin projection, DSM
is used to describe the structure of the recently observed low-lying $T=0$ and
$T=1$ bands in the heavy odd-odd N=Z nucleus $^{66}$As. DSM results are close
to the data and also to the shell model results. For the $T=1$ band, DSM
predicts structural change at $8^+$ just as in the shell model. In addition,
the lowest two $T=0$ bands are found to have quasi-deuteron structure above a
$^{64}$Ge core and the $5^+$ and $9^+$ levels of the third $T=0$ band are found
to be isomeric states. Secondly, in a first application of DSM to dark matter,
detection rates for the lightest supersymmetric particle (a dark matter
candidate) are calculated with $^{73}$Ge as the detector.


title:
A Schwarz lemma for the symmetrized tridisc and description of
  interpolating functions

abstract:
  We produce a Schwarz lemma for the symmetrized tridisc \[ \mathbb G_3 =\{
(z_1+z_2+z_3,z_1z_2+z_2z_3+z_3z_1,z_1z_2z_3): \,|z_i|< 1, i=1,2,3 \}. \] We
show that an interpolating function related to the Schward lemma for $\mathbb
G_3$ is not unique and present an explicit description of all such
interpolating functions. We also study the complex geometry of $\mathbb G_3$
and present a variety of new characterizations for the open and closed
symmetrized tridisc.


title:
A Semantic Analyzer for the Comprehension of the Spontaneous Arabic
  Speech

abstract:
  This work is part of a large research project entitled "Or\'eodule" aimed at
developing tools for automatic speech recognition, translation, and synthesis
for Arabic language. Our attention has mainly been focused on an attempt to
improve the probabilistic model on which our semantic decoder is based. To
achieve this goal, we have decided to test the influence of the pertinent
context use, and of the contextual data integration of different types, on the
effectiveness of the semantic decoder. The findings are quite satisfactory.


title: Decoherence in quantum systems in a static gravitational field

abstract:
  A small quantum system is studied which is a superposition of states
localized in different positions in a static gravitational field. The time
evolution of the correlation between different positions is investigated, and
it is seen that there are two time scales for such an evolution (decoherence).
Both time scales are inversely proportional to the red shift difference between
the two points. These time scales correspond to decoherences which are linear
and quadratic, respectively, in time.