title:
A System Architecture for the Detection of Insider Attacks in Big Data
  Systems

abstract:
  In big data systems, the infrastructure is such that large amounts of data
are hosted away from the users. In such a system information security is
considered as a major challenge. From a customer perspective, one of the big
risks in adopting big data systems is in trusting the provider who designs and
owns the infrastructure from accessing user data. Yet there does not exist much
in the literature on detection of insider attacks. In this work, we propose a
new system architecture in which insider attacks can be detected by utilizing
the replication of data on various nodes in the system. The proposed system
uses a two-step attack detection algorithm and a secure communication protocol
to analyze processes executing in the system. The first step involves the
construction of control instruction sequences for each process in the system.
The second step involves the matching of these instruction sequences among the
replica nodes. Initial experiments on real-world hadoop and spark tests show
that the proposed system needs to consider only 20% of the code to analyze a
program and incurs 3.28% time overhead. The proposed security system can be
implemented and built for any big data system due to its extrinsic workflow.


title:
Spatial compression of a particle state in a parabolic potential by spin
  measurements

abstract:
  We propose a scheme for engineering compressed spatial states in a
two-dimensional parabolic potential with a spin-orbit coupling by selective
spin measurements. This sequence of measurements results in a
coordinate-dependent density matrix with probability maxima achieved at a set
of lines or at a two dimensional lattice. The resultant probability density
depends on the spin-orbit coupling and the potential parameters and allows one
to obtain a broad class of localized pure states on demand. The proposed scheme
can be realized in spin-orbit coupled Bose-Einstein condensates.


title:
Improving the Performance of Neural Networks in Regression Tasks Using
  Drawering

abstract:
  The method presented extends a given regression neural network to make its
performance improve. The modification affects the learning procedure only,
hence the extension may be easily omitted during evaluation without any change
in prediction. It means that the modified model may be evaluated as quickly as
the original one but tends to perform better.
  This improvement is possible because the modification gives better expressive
power, provides better behaved gradients and works as a regularization. The
knowledge gained by the temporarily extended neural network is contained in the
parameters shared with the original neural network.
  The only cost is an increase in learning time.


title: Scientific Biography of Stanley Mandelstam, Part I: 1955-1980

abstract:
  I review Stanley Mandelstam's many contributions to particle physics, quantum
field theory and string theory covering the years 1955 through 1980. His more
recent work will be reviewed by Nathan Berkovits. This is my contribution to
the Memorial Volume for Stanley Mandelstam (World Scientific, 2017).


title: Neutrino oscillations in dense matter

abstract:
  We propose a modification of the electroweak theory, where the fermions with
the same electroweak quantum numbers are combined in multiplets and are treated
as different quantum states of a single particle. The developed approach
enables one to calculate the probabilities of the processes taking place in the
detector at long distances from the particle source. Calculations of
higher-order processes including the computation of the contributions due to
radiative corrections can be performed in the framework of the perturbation
theory using the regular diagram technique. As a result, we obtain the analog
to the Dirac--Schwinger equation of quantum electrodynamics describing neutrino
oscillations and its spin rotation in dense matter.


title: At the Edge of Criticality: Markov Chains with Asymptotically Zero Drift

abstract:
  In Chapter 2 we introduce a classification of Markov chains with
asymptotically zero drift, which relies on relations between first and second
moments of jumps. We construct an abstract Lyapunov functions which looks
similar to functions which characterise the behaviour of diffusions with
similar drift and diffusion coefficient.
  Chapter 3 is devoted to the limiting behaviour of transient chains. Here we
prove converges to $\Gamma$ and normal distribution which generalises papers by
Lamperti, Kersting and Klebaner. We also determine the asymptotic behaviour of
the cumulative renewal function.
  In Chapter 4 we introduce a general strategy of change of measure for Markov
chains with asymptotically zero drift. This is the most important ingredient in
our approach to recurrent chains.
  Chapter 5 is devoted to the study of the limiting behaviour of recurrent
chains with the drift proportional to $1/x$. We derive asymptotics for a
stationary measure and determine the tail behaviour of recurrence times. All
these asymptotics are of power type.
  In Chapter 6 we show that if the drift is of order $x^{-\beta}$ then moments
of all orders $k\le [1/\beta]+1$ are important for the behaviour of stationary
distributions and pre-limiting tails. Here we obtain Weibull-like asymptotics.
  In Chapter 7 we apply our results to different processes, e.g. critical and
near-critical branching processes, risk processes with reserve-dependent
premium rate, random walks conditioned to stay positive and reflected random
walks.
  In Chapter 8 we consider asymptotically homogeneous in space Markov chains
for which we derive exponential tail asymptotics.


title: Competitive Caching of Contents in 5G Edge Cloud Networks

abstract:
  The surge of mobile data traffic forces network operators to cope with
capacity shortage. The deployment of small cells in 5G networks is meant to
reduce latency, backhaul traffic and increase radio access capacity. In this
context, mobile edge computing technology will be used to manage dedicated
cache space in the radio access network. Thus, mobile network operators will be
able to provision OTT content providers with new caching services to enhance
the quality of experience of their customers on the move. In turn, the cache
memory in the mobile edge network will become a shared resource. Hence, we
study a competitive caching scheme where contents are stored at given price set
by the mobile network operator. We first formulate a resource allocation
problem for a tagged content provider seeking to minimize the expected missed
cache rate. The optimal caching policy is derived accounting for popularity and
availability of contents, the spatial distribution of small cells, and the
caching strategies of competing content providers. It is showed to induce a
specific order on contents to be cached based on their popularity and
availability. Next, we study a game among content providers in the form of a
generalized Kelly mechanism with bounded strategy sets and heterogeneous
players. Existence and uniqueness of the Nash equilibrium are proved. Finally,
extensive numerical results validate and characterize the performance of the
model.


title:
Object Classification with Joint Projection and Low-rank Dictionary
  Learning

abstract:
  For an object classification system, the most critical obstacles towards
real-world applications are often caused by large intra-class variability,
arising from different lightings, occlusion and corruption, in limited sample
sets. Most methods in the literature would fail when the training samples are
heavily occluded, corrupted or have significant illumination or viewpoint
variations. Besides, most of the existing methods and especially deep
learning-based methods, need large training sets to achieve a satisfactory
recognition performance. Although using the pre-trained network on a generic
large-scale dataset and fine-tune it to the small-sized target dataset is a
widely used technique, this would not help when the content of base and target
datasets are very different. To address these issues, we propose a joint
projection and low-rank dictionary learning method using dual graph constraints
(JP-LRDL). The proposed joint learning method would enable us to learn the
features on top of which dictionaries can be better learned, from the data with
large intra-class variability. Specifically, a structured class-specific
dictionary is learned and the discrimination is further improved by imposing a
graph constraint on the coding coefficients, that maximizes the intra-class
compactness and inter-class separability. We also enforce low-rank and
structural incoherence constraints on sub-dictionaries to make them more
compact and robust to variations and outliers and reduce the redundancy among
them, respectively. To preserve the intrinsic structure of data and penalize
unfavourable relationship among training samples simultaneously, we introduce a
projection graph into the framework, which significantly enhances the
discriminative ability of the projection matrix and makes the method robust to
small-sized and high-dimensional datasets.


title:
Rgbp: An R Package for Gaussian, Poisson, and Binomial Random Effects
  Models with Frequency Coverage Evaluations

abstract:
  Rgbp is an R package that provides estimates and verifiable confidence
intervals for random effects in two-level conjugate hierarchical models for
overdispersed Gaussian, Poisson, and Binomial data. Rgbp models aggregate data
from k independent groups summarized by observed sufficient statistics for each
random effect, such as sample means, possibly with covariates. Rgbp uses
approximate Bayesian machinery with unique improper priors for the
hyper-parameters, which leads to good repeated sampling coverage properties for
random effects. A special feature of Rgbp is an option that generates synthetic
data sets to check whether the interval estimates for random effects actually
meet the nominal confidence levels. Additionally, Rgbp provides inference
statistics for the hyper-parameters, e.g., regression coefficients.


title: Laser-induced topological superconductivity in cuprate thin films

abstract:
  We propose a possible way to realize topological superconductivity with
application of laser light to superconducting cuprate thin films. Applying
Floquet theory to a model of $d$-wave superconductors with Rashba spin-orbit
coupling, we derive an effective model and discuss its topological nature.
Interplay of the Rashba spin-orbit coupling and the laser light effect induces
the synthetic magnetic fields, thus making the system gapped. Then the system
acquires the topologically non-trivial nature which is characterized by Chern
numbers. The effective magnetic fields do not create the vortices in
superconductors, and thus the proposed scheme provides a promising way to
dynamically realize a topological superconductor in cuprates. We also discuss
an experimental way to detect the signature.


title:
Deterministic and Probabilistic Conditions for Finite Completability of
  Low-Tucker-Rank Tensor

abstract:
  We investigate the fundamental conditions on the sampling pattern, i.e.,
locations of the sampled entries, for finite completability of a low-rank
tensor given some components of its Tucker rank. In order to find the
deterministic necessary and sufficient conditions, we propose an algebraic
geometric analysis on the Tucker manifold, which allows us to incorporate
multiple rank components in the proposed analysis in contrast with the
conventional geometric approaches on the Grassmannian manifold. This analysis
characterizes the algebraic independence of a set of polynomials defined based
on the sampling pattern, which is closely related to finite completion.
Probabilistic conditions are then studied and a lower bound on the sampling
probability is given, which guarantees that the proposed deterministic
conditions on the sampling patterns for finite completability hold with high
probability. Furthermore, using the proposed geometric approach for finite
completability, we propose a sufficient condition on the sampling pattern that
ensures there exists exactly one completion for the sampled tensor.


title:
Chemical Abundances of M-dwarfs from the APOGEE Survey. I. The Exoplanet
  Hosting Stars Kepler-138 and Kepler-186

abstract:
  We report the first detailed chemical abundance analysis of the
exoplanet-hosting M-dwarf stars Kepler-138 and Kepler-186 from the analysis of
high-resolution ($R$ $\sim$ 22,500) $H$-band spectra from the SDSS IV - APOGEE
survey. Chemical abundances of thirteen elements - C, O, Na, Mg, Al, Si, K, Ca,
Ti, V, Cr, Mn, and Fe - are extracted from the APOGEE spectra of these early
M-dwarfs via spectrum syntheses computed with an improved line list that takes
into account H$_{2}$O and FeH lines. This paper demonstrates that APOGEE
spectra can be analyzed to determine detailed chemical compositions of
M-dwarfs. Both exoplanet-hosting M-dwarfs display modest sub-solar
metallicities: [Fe/H]$_{Kepler-138}$ = -0.09 $\pm$ 0.09 dex and
[Fe/H]$_{Kepler-186}$ = -0.08 $\pm$ 0.10 dex. The measured metallicities
resulting from this high-resolution analysis are found to be higher by
$\sim$0.1-0.2 dex than previous estimates from lower-resolution spectra. The
C/O ratios obtained for the two planet-hosting stars are near-solar, with
values of 0.55 $\pm$ 0.10 for Kepler-138 and 0.52 $\pm$ 0.12 for Kepler-186.
Kepler-186 exhibits a marginally enhanced [Si/Fe] ratio.


title:
A characteristic 2 recurrence related to $U_{5}$, with a Hecke algebra
  application

abstract:
  In arXiv:1603.03910 [math.NT] we introduced some $C_{n}$ in $Z/2[t]$ defined
by a linear recurrence and showed that each $C_{n}$, $n\equiv 0 \bmod{4}$, is a
sum of $C_{k}$, $k<n$. Combining this with results from arXiv:1508.07523
[math.NT] we proved that the space $K$, consisting of those odd mod~2 modular
forms of level $\Gamma_{0}(3)$ that are annihilated by the operator $U_{3}+I$,
has a basis $m_{i,j}$ "adapted to $T_{7}$ and $T_{13}$" in the sense of Nicolas
and Serre. (And so the "completed shallow Hecke algebra" attached to $K$ is a
power series ring in $T_{7}$ and $T_{13}$.)
  This note derives analogous results in level $\Gamma_{0}(5)$. Now $U_{3}+I$
is replaced by $U_{5}+I$, and the operators $T_{7}$ and $T_{13}$ by $T_{3}$ and
$T_{7}$. In place of level $\Gamma_{0}(3)$ results from 1508.07523, we use
level $\Gamma_{0}(5)$ results from arXiv:1603.07085 [math.NT]. A linear
recurrence again plays the key role. Now $C_{n+6} = C_{n+5} +
(t^{6}+t^{5}+t^{2}+t)C_{n}+t^{n}(t^{2}+t)$, $C_{0}=0$, $C_{1}=C_{2}=1$,
$C_{3}=t$, $C_{4}=t^{2}$, $C_{5}=t^{4}+t^{2}+t$, and we prove that each
$C_{n}$, $n\equiv 0$ or $2\bmod{6}$ is a sum of $C_{k}$, $k<n$.


title: Distributed Gaussian Learning over Time-varying Directed Graphs

abstract:
  We present a distributed (non-Bayesian) learning algorithm for the problem of
parameter estimation with Gaussian noise. The algorithm is expressed as
explicit updates on the parameters of the Gaussian beliefs (i.e. means and
precision). We show a convergence rate of $O(1/k)$ with the constant term
depending on the number of agents and the topology of the network. Moreover, we
show almost sure convergence to the optimal solution of the estimation problem
for the general case of time-varying directed graphs.


title: Superpixels: An Evaluation of the State-of-the-Art

abstract:
  Superpixels group perceptually similar pixels to create visually meaningful
entities while heavily reducing the number of primitives for subsequent
processing steps. As of these properties, superpixel algorithms have received
much attention since their naming in 2003. By today, publicly available
superpixel algorithms have turned into standard tools in low-level vision. As
such, and due to their quick adoption in a wide range of applications,
appropriate benchmarks are crucial for algorithm selection and comparison.
Until now, the rapidly growing number of algorithms as well as varying
experimental setups hindered the development of a unifying benchmark. We
present a comprehensive evaluation of 28 state-of-the-art superpixel algorithms
utilizing a benchmark focussing on fair comparison and designed to provide new
insights relevant for applications. To this end, we explicitly discuss
parameter optimization and the importance of strictly enforcing connectivity.
Furthermore, by extending well-known metrics, we are able to summarize
algorithm performance independent of the number of generated superpixels,
thereby overcoming a major limitation of available benchmarks. Furthermore, we
discuss runtime, robustness against noise, blur and affine transformations,
implementation details as well as aspects of visual quality. Finally, we
present an overall ranking of superpixel algorithms which redefines the
state-of-the-art and enables researchers to easily select appropriate
algorithms and the corresponding implementations which themselves are made
publicly available as part of our benchmark at
davidstutz.de/projects/superpixel-benchmark/.


title: Species tree estimation using Neighbor Joining

abstract:
  Recent theoretical work has demonstrated that Neighbor Joining applied to
concatenated DNA sequences is a statistically consistent method of species tree
reconstruction. This brief note compares the accuracy of this approach to other
popular statistically consistent species tree reconstruction algorithms
including ASTRAL-II Neighbor Joining using average gene-tree internode
distances (NJst) and SVD-Quartets+PAUP*, as well as concatenation using maximum
likelihood (RaxML). We find that the faster Neighbor Joining, applied to
concatenated sequences, is among the most effective of these methods for
accurate species tree reconstruction.


title: Study of shoplifting prevention using image analysis and ERP check

abstract:
  In this paper, we propose a SaaS service which prevents shoplifting using
image analysis and ERP. In Japan, total damage of shoplifting reaches 450
billion yen and more than 1000 small shops gave up their businesses because of
shoplifting. Based on recent cloud technology and data analysis technology, we
propose a shoplifting prevention service with image analysis of security camera
and ERP data check for small shops. We evaluated stream analysis of security
camera movie using online machine learining framework Jubatus.


title: Classical Propagation in the Quantum Inverted Oscillator

abstract:
  We emphasize the fact the evolution of quantum states in the inverted
oscillator (IO) is reduced to classical equations of motion, stressing that the
corresponding tunnelling and reflexion coefficients addressed in the literature
are calculated by considering only classically trajectories. The Wigner
function formalism is employed to describe the IO classical dynamics,
subsequently leading to the introduction of the Ambiguity function lying in the
so-called Reciprocal phase space. Our findings, show that the Ambiguity
function behavior, subjected to the IO, allude a classical propagation with an
associated integral of motion, and complex conjugated doubly degenerate energy
states.


title: Zipf's law, unbounded complexity and open-ended evolution

abstract:
  A major problem for evolutionary theory is understanding the so called {\em
open-ended} nature of evolutionary change, from its definition to its origins.
Open-ended evolution (OEE) refers to the unbounded increase in complexity that
seems to characterise evolution on multiple scales. This property seems to be a
characteristic feature of biological and technological evolution and is
strongly tied to the generative potential associated with combinatorics, which
allows the system to grow and expand their available state spaces.
Interestingly, many complex systems presumably displaying OEE, from language to
proteins, share a common statistical property: the presence of Zipf's law.
Given an inventory of basic items (such as words or protein domains) required
to build more complex structures (sentences or proteins) Zipf's law tells us
that most of these elements are rare whereas a few of them are extremely
common. Using Algorithmic Information Theory, in this paper we provide a
fundamental definition for open-endedness, which can be understood as {\em
postulates}. Its statistical counterpart, based on standard Shannon Information
theory, has the structure of a variational problem which is shown to lead to
Zipf's law as the expected consequence of an evolutionary process displaying
OEE. We further explore the problem of information conservation through an OEE
process and we conclude that statistical information (standard Shannon
information) is not conserved, resulting into the paradoxical situation in
which the increase of information content has the effect of erasing itself. We
prove that this paradox is solved if we consider non-statistical forms of
information. This last result implies that standard information theory may not
be a suitable theoretical framework to explore the persistence and increase of
the information content in OEE systems.


title: Is nestedness in mutualistic networks an evolutionary spandrel?

abstract:
  Mutualistic networks have been shown to involve complex patterns of
interactions among animal and plant species. The architecture of these webs
seems to pervade some of their robust and fragile behaviour. Recent work
indicates that there is a strong correlation between the patterning of
animal-plant interactions and their phylogenetic organisation. Here we show
that such pattern and other reported regularities from mutualistic webs can be
properly explained by means of a very simple model of speciation and
divergence. This model also predicts a co-extinction dynamics under species
loss consistent with the presence of an evolutionary signal. The agreement
between observed and model networks suggests that some patterns displayed by
real mutualistic webs might actually represent evolutionary spandrels.


title:
Review of "Continuous Finite-Time Stabilization of Translational and
  Rotational Double Integrators"

abstract:
  We review Bhat et al's paper where a class of bounded, continuous
time-invariant finite time stabilizing feedback laws are derived for the double
integrator and Lyapunov theory is employed in establishing finite-time
convergence.


title: AI Researchers, Video Games Are Your Friends!

abstract:
  If you are an artificial intelligence researcher, you should look to video
games as ideal testbeds for the work you do. If you are a video game developer,
you should look to AI for the technology that makes completely new types of
games possible. This chapter lays out the case for both of these propositions.
It asks the question "what can video games do for AI", and discusses how in
particular general video game playing is the ideal testbed for artificial
general intelligence research. It then asks the question "what can AI do for
video games", and lays out a vision for what video games might look like if we
had significantly more advanced AI at our disposal. The chapter is based on my
keynote at IJCCI 2015, and is written in an attempt to be accessible to a broad
audience.


title: New simulation strategies for lattice gauge theory

abstract:
  Despite the numerous successful applications of lattice QCD in nuclear and
particle theory, fundamental algorithmic challenges remain. Among those,
relevant for numerical studies of QCD on a space-time torus, is topological
freezing--a form of critical slowing down, which becomes particularly acute for
lattice spacings less than 0.05 fm. In these proceedings, I highlight several
recently proposed simulation strategies for ameliorating the problem of
topological freezing, and discuss both their advantages and disadvantages.
Then, I turn focus toward potential strategies for addressing critical slowing
down in a more general context.


title: Tighter inapproximability for set cover

abstract:
  Set Cover is a classic NP-hard problem; as shown by Slav\'{i}k (1997) the
greedy algorithm gives an approximation ratio of $\ln n - \ln \ln n +
\Theta(1)$. A series of works by Lund \& Yannakakis (1994), Feige (1998),
Moshkovitz (2015) have shown that, under the assumption $P \neq NP$, it is
impossible to obtain a polynomial-time approximation ratio with approximation
ratio $(1 - \alpha) \ln n$, for any constant $\alpha > 0$.
  In this note, we show that under the Exponential Time Hypothesis (a stronger
complexity-theoretic assumptions than $P \neq NP$), there are no
polynomial-time algorithms achieving approximation ratio $\ln n - C \ln \ln n$,
where $C$ is some universal constant. Thus, the greedy algorithm achieves an
essentially optimal approximation ratio (up to the coefficient of $\ln \ln n$).


title: Automatic Event Detection for Signal-based Surveillance

abstract:
  Signal-based Surveillance systems such as Closed Circuits Televisions (CCTV)
have been widely installed in public places. Those systems are normally used to
find the events with security interest, and play a significant role in public
safety. Though such systems are still heavily reliant on human labour to
monitor the captured information, there have been a number of automatic
techniques proposed to analysing the data. This article provides an overview of
automatic surveillance event detection techniques . Despite it's popularity in
research, it is still too challenging a problem to be realised in a real world
deployment. The challenges come from not only the detection techniques such as
signal processing and machine learning, but also the experimental design with
factors such as data collection, evaluation protocols, and ground-truth
annotation. Finally, this article propose that multi-disciplinary research is
the path towards a solution to this problem.


title: CXOGBS J174954.5-294335: A New Deeply-Eclipsing Intermediate Polar

abstract:
  We present the results of a photometric and spectroscopic analysis of the
Galactic Bulge Survey X-ray source CXOGBS J174954.5-294335 (hereafter, referred
to as CX19). CX19 is a long period, eclipsing intermediate polar type
cataclysmic variable with broad, single-peaked Balmer and Paschen emission
lines along with HeII $\lambda4686$ and Bowen blend emission features. With
coverage of one full and two partial eclipses and archival photometry, we
determine the ephemeris for CX19 to be HJD(eclipse) = 2455691.8581(5) +
0.358704(2)$\times$N. We also recovered the white dwarf spin period of P$_{\rm
spin}$ = 503.32(3) seconds which gives a P$_{\rm spin}$/P$_{\rm orb}$ =
0.016(6), comparable to several confirmed, long period intermediate polars.
CX19 also shows a clear X-ray eclipse in the 0.3-8.0 keV range observed with
Chandra. Two optical outbursts were observed lasting between 6-8 hours (lower
limits) reaching $\sim$1.3 mags in amplitude. The outbursts, both in duration
and magnitude, the accretion disc dominated spectra and hard X-ray emission are
reminiscent of the intermediate polar V1223 Sgr sharing many of the same
characteristics. If we assume a main sequence companion, we estimate the donor
to be an early G-type star and find a minimum distance of $d \approx$ 2.1 kpc
and a 0.5-10.0 keV X-ray luminosity upper limit of 2.0 $\times$ 10$^{33}$ erg
s$^{-1}$. Such an X-ray luminosity is consistent with a white dwarf accretor in
a magnetic cataclysmic variable system. To date, CX19 is only the second
deeply-eclipsing intermediate polar with X-ray eclipses and the first which is
optically accessible.


title: Application of semifinite index theory to weak topological phases

abstract:
  Recent work by Prodan and the second author showed that weak invariants of
topological insulators can be described using Kasparov's $KK$-theory. In this
note, a complementary description using semifinite index theory is given. This
provides an alternative proof of the index formulae for weak complex
topological phases using the semifinite local index formula. Real invariants
and the bulk-boundary correspondence are also briefly considered.


title: Observed asteroid surface area in the thermal infrared

abstract:
  The rapid accumulation of thermal infrared observations and shape models of
asteroids has led to increased interest in thermophysical modeling. Most of
these infrared observations are unresolved. We consider what fraction of an
asteroid's surface area contributes the bulk of the emitted thermal flux for
two model asteroids of different shapes over a range of thermal parameters. The
resulting observed surface in the infrared is generally more fragmented than
the area observed in visible wavelengths, indicating high sensitivity to shape.
For objects with low values of the thermal parameter, small fractions of the
surface contribute the majority of thermally emitted flux. Calculating observed
areas could enable the production of spatially-resolved thermal inertia maps
from non-resolved observations of asteroids.


title: Is GW151226 a really signal of gravitational wave?

abstract:
  Recently, the LIGO Scientific Collaboration and Virgo Collaboration published
the second observation on gravitational wave GW151226 [Phys. Rev. Lett. 116,
241103 (2016)] from the binary black hole coalescence with initial masses about
14 M$_\odot$ and 8 M$_\odot$. They claimed that the peak gravitational strain
was reached at about 450 Hz, the inverse of which has been longer than the
average time a photon staying in the Fabry-Perot cavities in two arms. In this
case, the phase-difference of a photon in the two arms due to the propagation
of gravitational wave does not always increase as the photon stays in the
cavities. It might even be cancelled to zero in extreme cases. When the
propagation effect is taken into account, we find that the claimed signal
GW151226 would almost disappear.


title:
The metallicity distribution and hot Jupiter rate of the Kepler field:
  Hectochelle High-resolution spectroscopy for 776 Kepler target stars

abstract:
  The occurrence rate of hot Jupiters from the Kepler transit survey is roughly
half that of radial velocity surveys targeting solar neighborhood stars. One
hypothesis to explain this difference is that the two surveys target stars with
different stellar metallicity distributions. To test this hypothesis, we
measure the metallicity distribution of the Kepler targets using the
Hectochelle multi-fiber, high-resolution spectrograph. Limiting our
spectroscopic analysis to 610 dwarf stars in our sample with log(g)>3.5, we
measure a metallicity distribution characterized by a mean of [M/H]_{mean} =
-0.045 +/- 0.00, in agreement with previous studies of the Kepler field target
stars. In comparison, the metallicity distribution of the California Planet
Search radial velocity sample has a mean of [M/H]_{CPS, mean} = -0.005 +/-
0.006, and the samples come from different parent populations according to a
Kolmogorov-Smirnov test. We refit the exponential relation between the fraction
of stars hosting a close-in giant planet and the host star metallicity using a
sample of dwarf stars from the California Planet Search with updated
metallicities. The best-fit relation tells us that the difference in
metallicity between the two samples is insufficient to explain the discrepant
Hot Jupiter occurrence rates; the metallicity difference would need to be
$\simeq$0.2-0.3 dex for perfect agreement. We also show that (sub)giant
contamination in the Kepler sample cannot reconcile the two occurrence
calculations. We conclude that other factors, such as binary contamination and
imperfect stellar properties, must also be at play.


title: On the Marginal Value of Electricity Storage

abstract:
  We investigate the problem of characterizing the economic value of energy
storage capacity to a wind power producer (WPP) that sells its energy in a
conventional two-settlement electricity market. The WPP can offer a forward
contract to supply power in the day-ahead market, subject to financial
penalties for imbalances between the contracted power and the power that is
delivered in real-time. We consider the setting in which the WPP has access to
a co-located energy storage system, and can thus reshape its wind power
production subject to its storage capacity constraints. Modeling wind power as
a random process, we show that the problem of determining optimal forward
contract offerings--given recourse with storage--is convex. We further
establish that the maximum expected profit is concave and non-decreasing in the
energy storage capacity, which reveals that the greatest marginal benefit from
energy storage is derived from initial investment in small storage capacity. We
provide a characterization of the marginal value of small energy storage
capacity to the WPP. The formulae we derive shed light on the relationship
between the value of storage and certain statistical measures of variability in
the underlying wind power process.


title: Chained Bell Inequality Experiment with High-Efficiency Measurements

abstract:
  We report correlation measurements on two $^9$Be$^+$ ions that violate a
chained Bell inequality obeyed by any local-realistic theory. The correlations
can be modeled as derived from a mixture of a local-realistic probabilistic
distribution and a distribution that violates the inequality. A statistical
framework is formulated to quantify the local-realistic fraction allowable in
the observed distribution without the fair-sampling or
independent-and-identical-distributions assumptions. We exclude models of our
experiment whose local-realistic fraction is above 0.327 at the 95 \%
confidence level. This bound is significantly lower than 0.586, the minimum
fraction derived from a perfect Clauser-Horne-Shimony-Holt inequality
experiment. Furthermore, our data provides a device-independent certification
of the deterministically created Bell states.


title: mBART: Multidimensional Monotone BART

abstract:
  For the discovery of regression relationships between Y and a large set of p
potential predictors x 1 , . . . , x p , the flexible nonparametric nature of
BART (Bayesian Additive Regression Trees) allows for a much richer set of
possibilities than restrictive parametric approaches. However, subject matter
considerations sometimes warrant a minimal assumption of monotonicity in at
least some of the predictors. For such contexts, we introduce mBART, a
constrained version of BART that can flexibly incorporate monotonicity in any
predesignated subset of predictors using a multivariate basis of monotone
trees, while avoiding the further confines of a full parametric form. For such
monotone relationships, mBART provides (i) function estimates that are smoother
and more interpretable, (ii) better out-of-sample predictive performance, and
(iii) less post-data uncertainty. While many key aspects of the unconstrained
BART model carry over directly to mBART, the introduction of monotonicity
constraints necessitates a fundamental rethinking of how the model is
implemented. In particular, the original BART Markov Chain Monte Carlo
algorithm relied on a conditional conjugacy that is no longer available in a
monotonically constrained space. Various simulated and real examples
demonstrate the wide ranging potential of mBART.


title: Hybrid Superconductor-Quantum Point Contact Devices using InSb Nanowires

abstract:
  Proposals for studying topological superconductivity and Majorana bound
states in nanowires proximity coupled to superconductors require that transport
in the nanowire is ballistic. Previous work on hybrid nanowire-superconductor
systems has shown evidence for Majorana bound states, but these experiments
were also marked by disorder, which disrupts ballistic transport. In this
letter, we demonstrate ballistic transport in InSb nanowires interfaced
directly with superconducting Al by observing quantized conductance at
zero-magnetic field. Additionally, we demonstrate that the nanowire is
proximity coupled to the superconducting contacts by observing Andreev
reflection. These results are important steps for robustly establishing
topological superconductivity in InSb nanowires.


title: Halo bias in Lagrangian Space: Estimators and theoretical predictions

abstract:
  We present several methods to accurately estimate Lagrangian bias parameters
and substantiate them using simulations. In particular, we focus on the
quadratic terms, both the local and the non local ones, and show the first
clear evidence for the latter in the simulations. Using Fourier space
correlations, we also show for the first time, the scale dependence of the
quadratic and non-local bias coefficients. For the linear bias, we fit for the
scale dependence and demonstrate the validity of a consistency relation between
linear bias parameters. Furthermore we employ real space estimators, using both
cross-correlations and the Peak-Background Split argument. This is the first
time the latter is used to measure anisotropic bias coefficients. We find good
agreement for all the parameters among these different methods, and also good
agreement for local bias with ESP$\tau$ theory predictions. We also try to
exploit possible relations among the different bias parameters. Finally, we
show how including higher order bias reduces the magnitude and scale dependence
of stochasticity of the halo field.


title:
Ages of 70 dwarfs of three populations in the solar neighborhood:
  considering O and C abundances in stellar models

abstract:
  Oxygen and carbon are important elements in stellar populations. Their
behavior refers to the formation history of the stellar populations. C and O
abundances would also obviously influence stellar opacities and the overall
metal abundance $Z$. With observed high-quality spectroscopic properties, we
construct stellar models with C and O elements, to give more accurate ages for
70 metal-poor dwarfs, which have been determined to be high-$\alpha$ halo,
low-$\alpha$ halo and thick-disk stars. Our results show that high-$\alpha$
halo stars are relatively older than low-$\alpha$ halo stars by around 2.0 Gyr.
The thick-disk population has an age range between the two halo populations.
The age distribution profiles indicate that high-$\alpha$ halo and low-$\alpha$
halo stars match the in situ accretion simulation by Zolotov et al., and the
thick-disk stars might be formed in a relatively quiescent and long-lasting
process. We also note that stellar ages are very sensitive to O abundance,
since the ages clearly increase with increasing [O/Fe] values. Additionally, we
obtain several stars with peculiar ages, including 2 young thick-disk stars and
12 stars older than the universe age.


title:
An epiperimetric inequality for the regularity of some free boundary
  problems: the $2$-dimensional case

abstract:
  Using a direct approach, we prove a $2$-dimensional epiperimetric inequality
for the one-phase problem in the scalar and vectorial cases and for the
double-phase problem. From this we deduce, in dimension $2$, the $C^{1,\alpha}$
regularity of the free-boundary in the scalar one-phase and double-phase
problems, and of the reduced free-boundary in the vectorial case, without any
restriction on the sign of the component functions. Furthermore we show that in
the vectorial case the free boundary can end in a cusp.


title: Exponential Structure of Income Inequality: Evidence from 67 Countries

abstract:
  Economic competition between humans leads to income inequality, but, so far,
there has been little understanding of underlying quantitative mechanisms
governing such a collective behavior. We analyze datasets of household income
from 67 countries, ranging from Europe to Latin America, North America and
Asia. For all of the countries, we find a surprisingly uniform rule: Income
distribution for the great majority of populations (low and middle income
classes) follows an exponential law. To explain this empirical observation, we
propose a theoretical model within the standard framework of modern economics
and show that free competition and Rawls' fairness are the underlying
mechanisms producing the exponential pattern. The free parameters of the
exponential distribution in our model have an explicit economic interpretation
and direct relevance to policy measures intended to alleviate income
inequality.


title: Crofton Formulas and Indefinite Signature

abstract:
  We study the $O(p,q)$-invariant valuations classified by A. Bernig and the
author. Our main result is that every such valuation is given by an
$O(p,q)$-invariant Crofton formula. This is achieved by first obtaining a
handful of explicit formulas for a few sufficiently general signatures and
degrees of homogeneity, notably in the $(p-1)$ homogeneous case of $O(p,p)$,
yielding a Crofton formula for the centro-affine surface area when $p\not\equiv
3\mod 4$. We then exploit the functorial properties of Crofton formulas to pass
to the general case. We also identify the invariant formulas explicitly for all
$O(p,2)$-invariant valuations. The proof relies on the exact computation of
some integrals of independent interest. Those are related to Selberg's integral
and to the Beta function of a matrix argument, except that the
positive-definite matrices are replaced with matrices of all signatures. We
also analyze the distinguished invariant Crofton distribution supported on the
minimal orbit, and show that, somewhat surprisingly, it sometimes defines the
trivial valuation, thus producing a distribution in the kernel of the cosine
transform of particularly small support. In the heart of the paper lies the
description by Muro of the $|\det X|^s$ family of distributions on the space of
symmetric matrices, which we use to construct a family of $O(p,q)$-invariant
Crofton distributions. We conjecture there are no others, which we then prove
for $O(p,2)$ with $p$ even. The functorial properties of Crofton distributions,
which serve an important tool in our investigation, are studied by T. Wannerer
and the author in the Appendix.


title: Automated Inference of Software Library Usage Patterns

abstract:
  Modern software systems are increasingly dependent on third-party libraries.
It is widely recognized that using mature and well-tested third-party libraries
can improve developers' productivity, reduce time-to-market, and produce more
reliable software. Today's open-source repositories provide a wide range of
libraries that can be freely downloaded and used. However, as software
libraries are documented separately but intended to be used together,
developers are unlikely to fully take advantage of these reuse opportunities.
In this paper, we present a novel approach to automatically identify
third-party library usage patterns, i.e., collections of libraries that are
commonly used together by developers. Our approach employs hierarchical
clustering technique to group together software libraries based on external
client usage. To evaluate our approach, we mined a large set of over 6,000
popular libraries from Maven Central Repository and investigated their usage by
over 38,000 client systems from the Github repository. Our experiments show
that our technique is able to detect the majority (77%) of highly consistent
and cohesive library usage patterns across a considerable number of client
systems.


title:
Sequential Matching Network: A New Architecture for Multi-turn Response
  Selection in Retrieval-based Chatbots

abstract:
  We study response selection for multi-turn conversation in retrieval-based
chatbots. Existing work either concatenates utterances in context or matches a
response with a highly abstract context vector finally, which may lose
relationships among utterances or important contextual information. We propose
a sequential matching network (SMN) to address both problems. SMN first matches
a response with each utterance in the context on multiple levels of
granularity, and distills important matching information from each pair as a
vector with convolution and pooling operations. The vectors are then
accumulated in a chronological order through a recurrent neural network (RNN)
which models relationships among utterances. The final matching score is
calculated with the hidden states of the RNN. An empirical study on two public
data sets shows that SMN can significantly outperform state-of-the-art methods
for response selection in multi-turn conversation.


title: Function spaces and extension results for nonlocal Dirichlet problems

abstract:
  We study function spaces and extension results in relation with Dirichlet
problems involving integrodifferential operators. For such problems, data are
prescribed on the complement of a given domain in the Euclidean space. We
introduce a function space that serves as a trace space for nonlocal Dirichlet
problems and study related extension results.


title: Reply to comment on "Observation of subluminal twisted light in vacuum"

abstract:
  Recently, we showed experimentally that light carrying orbital angular
momentum experiences a slight subluminality under free-space propagation [1].
We thank Saari [2] for pointing out an apparent discrepancy between our
theoretical results and the well-known results for the simple case of
Laguerre-Gauss modes. In this reply, we note that the resolution of this
apparent discrepancy is the distinction between Laguerre-Gauss modes and
Hypergeometric-Gauss modes, which were used in our experiment and in our
theoretical analysis, which gives rise to different subluminal effects.


title: Parametric equations for temporal style assertions

abstract:
  Temporal logic provided an appealing approach to specifying properties of
operating systems and other "reactive" software by making referencing the state
graph implicitly. This paper shows how to get the same effect, with a finer
control over specification and a compositional notion of state, using ordinary
working mathematics, without the weight of formal logic, by using parametric
state variables.


title:
Rotor-phonon coupling in perovskite CH3NH3PbI3: the origin of
  exceptional transport properties

abstract:
  Atomic dynamics takes a fundamental part in numbers of physical properties of
solids like high-Tc superconductivity, semiconducting transports, and
thermoelectricity. Perovskite CH3NH3PbI3 exhibits outstanding photovoltaic
performances, but the exact physical scenario has not been established yet, due
to the inadequate understanding of the atomic dynamics and exceptional
transport properties. We present a complete atomic dynamic picture consisting
of phonons, rotational modes of protons and molecular vibrational modes, which
is constructed by carrying out high-resolution time-of-flight inelastic neutron
scattering measurements in a wide energy window ranging from 0.0036 to 54 meV
on a large single crystal sample. A three-fold rotational mode of protons
activated around 80 K reduces the lifetimes of acoustic and optical phonons
down to about 4.5 ps and below 1 ps at 150 K, respectively. The orthorhombic to
tetragonal phase transition takes place with a slower four-fold rotational mode
of the C-N axis concomitantly setting in at ~ 165 K, above which the optical
phonons are too broadened to be distinguished whereas the acoustic ones are
still robust. The significantly reduced lifetimes of optical phonons are linked
to the smaller mobility of charge carriers while the ultralow lattice thermal
conductivity is attributed to nanoscale mean free paths of acoustic phonons.
These microscopic insights provide a solid standing point, on which perovskite
solar cells can be understood more accurately and their performances are
perhaps further optimized. The revealed rotor-phonon coupling opens up an
emergent opportunity to create unprecedented functionalities of materials.


title:
Phase diagram and aggregation dynamics of a monolayer of paramagnetic
  colloids

abstract:
  We have developed a tunable colloidal system and a corresponding simulation
model for studying the phase behavior of particles assembling under the
influence of long-range magnetic interactions. A monolayer of paramagnetic
particles is subjected to a spatially uniform magnetic field with a static
perpendicular component and rapidly rotating in-plane component. The sign and
strength of the interactions vary with the tilt angle $\theta$ of the rotating
magnetic field. For a purely in-plane field, $\theta=90^{\circ}$, interactions
are attractive and the experimental results agree well with both equilibrium
and out-of-equilibrium predictions based on a two-body interaction model. For
tilt angles $50^{\circ}\lesssim \theta\lesssim 55^{\circ}$, the two-body
interaction gives a short-range attractive and long-range repulsive (SALR)
interaction, which predicts the formation of equilibrium microphases. In
experiments, however, a different type of assembly is observed. Inclusion of
three-body (and higher-order) terms in the model does not resolve the
discrepancy. We thus further characterize the anomalous behavior by measuring
the time-dependent cluster size distribution.


title:
Error Suppression for Hamiltonian Quantum Computing in Markovian
  Environments

abstract:
  Hamiltonian quantum computing, such as the adiabatic and holonomic models,
can be protected against decoherence using an encoding into stabilizer subspace
codes for error detection and the addition of energy penalty terms. This method
has been widely studied since it was first introduced by Jordan, Farhi, and
Shor (JFS) in the context of adiabatic quantum computing. Here we extend the
original result to general Markovian environments, not necessarily in Lindblad
form. We show that the main conclusion of the original JFS study holds under
these general circumstances: assuming a physically reasonable bath model, it is
possible to suppress the initial decay out of the encoded ground state with an
energy penalty strength that grows only logarithmically in the system size, at
a fixed temperature.


title:
Pulsational Pair-Instability Model for Superluminous Supernova PTF12dam:
  Interaction and Radioactive Decay

abstract:
  Being a superluminous supernova (SLSN), PTF12dam can be explained by a
$^{56}$Ni-powered model, a magnetar-powered model or an interaction model. We
propose that PTF12dam is a pulsational pair instability supernova, where the
outer envelope of a progenitor is ejected during the pulsations. Thus, it is
powered by double energy source: radioactive decay of $^{56}$Ni and a radiative
shock in a dense circumstellar medium. To describe multicolor light curves and
spectra we use radiation hydrodynamics calculations of STELLA code. We found
that light curves are well described in the model with 40M$_{\odot}$ ejecta and
20-40M$_{\odot}$ circumstellar medium. The ejected $^{56}$Ni mass is about
6M$_{\odot}$ which results from explosive nucleosynthesis with large explosion
energy (2-3)$\cdot$10$^{52}$ ergs. In comparison with alternative scenarios of
pair-instability supernova and magnetar-powered supernova, in interaction model
all the observed main photometric characteristics are well reproduced:
multicolor light curves, color temperatures, and photospheric velocities.


title: Learning to Detect Multiple Photographic Defects

abstract:
  In this paper, we introduce the problem of simultaneously detecting multiple
photographic defects. We aim at detecting the existence, severity, and
potential locations of common photographic defects related to color, noise,
blur and composition. The automatic detection of such defects could be used to
provide users with suggestions for how to improve photos without the need to
laboriously try various correction methods. Defect detection could also help
users select photos of higher quality while filtering out those with severe
defects in photo curation and summarization.
  To investigate this problem, we collected a large-scale dataset of user
annotations on seven common photographic defects, which allows us to evaluate
algorithms by measuring their consistency with human judgments. Our new dataset
enables us to formulate the problem as a multi-task learning problem and train
a multi-column deep convolutional neural network (CNN) to simultaneously
predict the severity of all the defects. Unlike some existing single-defect
estimation methods that rely on low-level statistics and may fail in many cases
on natural photographs, our model is able to understand image contents and
quality at a higher level. As a result, in our experiments, we show that our
model has predictions with much higher consistency with human judgments than
low-level methods as well as several baseline CNN models. Our model also
performs better than an average human from our user study.


title:
A Stochastic Geometry-based Demand Response Management Framework for
  Cellular Networks Powered by Smart Grid

abstract:
  In this paper, the production decisions across multiple energy suppliers in
smart grid, powering cellular networks are investigated. The suppliers are
characterized by different offered prices and pollutant emissions levels. The
challenge is to decide the amount of energy provided by each supplier to each
of the operators such that their profitability is maximized while respecting
the maximum tolerated level of CO2 emissions. The cellular operators are
characterized by their offered quality of service (QoS) to the subscribers and
the number of users that determines their energy requirements. Stochastic
geometry is used to determine the average power needed to achieve the target
probability of coverage for each operator. The total average power requirements
of all networks are fed to an optimization framework to find the optimal amount
of energy to be provided from each supplier to the operators. The generalized
$\alpha$-fair utility function is used to avoid production bias among the
suppliers based on profitability of generation. Results illustrate the
production behavior of the energy suppliers versus QoS level, cost of energy,
capacity of generation, and level of fairness.


title: Type Annotation for Adaptive Systems

abstract:
  We introduce type annotations as a flexible typing mechanism for graph
systems and discuss their advantages with respect to classical typing based on
graph morphisms. In this approach the type system is incorporated with the
graph and elements can adapt to changes in context by changing their type
annotations. We discuss some case studies in which this mechanism is relevant.


title: An EMOF-Compliant Abstract Syntax for Bigraphs

abstract:
  Bigraphs are an emerging modeling formalism for structures in ubiquitous
computing. Besides an algebraic notation, which can be adopted to provide an
algebraic syntax for bigraphs, the bigraphical theory introduces a visual
concrete syntax which is intuitive and unambiguous at the same time; the
standard visual notation can be customized and thus tailored to domain-specific
requirements. However, in contrast to modeling standards based on the
Meta-Object Facility (MOF) and domain-specific languages typically used in
model-driven engineering (MDE), the bigraphical theory lacks a precise
definition of an abstract syntax for bigraphical modeling languages. As a
consequence, available modeling and analysis tools use proprietary formats for
representing bigraphs internally and persistently, which hampers the exchange
of models across tool boundaries. Moreover, tools can be hardly integrated with
standard MDE technologies in order to build sophisticated tool chains and
modeling environments, as required for systematic engineering of large systems
or fostering experimental work to evaluate the bigraphical theory in real-world
applications. To overcome this situation, we propose an abstract syntax for
bigraphs which is compliant to the Essential MOF (EMOF) standard defined by the
Object Management Group (OMG). We use typed graphs as a formal underpinning of
EMOF-based models and present a canonical mapping which maps bigraphs to typed
graphs in a natural way. We also discuss application-specific variation points
in the graph-based representation of bigraphs. Following standard techniques
from software product line engineering, we present a framework to customize the
graph-based representation to support a variety of application scenarios.


title: A Graph Grammar for Modelling RNA Folding

abstract:
  We propose a new approach for modelling the process of RNA folding as a graph
transformation guided by the global value of free energy. Since the folding
process evolves towards a configuration in which the free energy is minimal,
the global behaviour resembles the one of a self-adaptive system. Each RNA
configuration is a graph and the evolution of configurations is constrained by
precise rules that can be described by a graph grammar.


title: Towards a Step Semantics for Story-Driven Modelling

abstract:
  Graph Transformation (GraTra) provides a formal, declarative means of
specifying model transformation. In practice, GraTra rule applications are
often programmed via an additional language with which the order of rule
applications can be suitably controlled.
  Story-Driven Modelling (SDM) is a dialect of programmed GraTra, originally
developed as part of the Fujaba CASE tool suite. Using an intuitive,
UML-inspired visual syntax, SDM provides usual imperative control flow
constructs such as sequences, conditionals and loops that are fairly simple,
but whose interaction with individual GraTra rules is nonetheless non-trivial.
In this paper, we present the first results of our ongoing work towards
providing a formal step semantics for SDM, which focuses on the execution of an
SDM specification.


title:
Incremental View Maintenance for Deductive Graph Databases Using
  Generalized Discrimination Networks

abstract:
  Nowadays, graph databases are employed when relationships between entities
are in the scope of database queries to avoid performance-critical join
operations of relational databases. Graph queries are used to query and modify
graphs stored in graph databases. Graph queries employ graph pattern matching
that is NP-complete for subgraph isomorphism. Graph database views can be
employed that keep ready answers in terms of precalculated graph pattern
matches for often stated and complex graph queries to increase query
performance. However, such graph database views must be kept consistent with
the graphs stored in the graph database.
  In this paper, we describe how to use incremental graph pattern matching as
technique for maintaining graph database views. We present an incremental
maintenance algorithm for graph database views, which works for imperatively
and declaratively specified graph queries. The evaluation shows that our
maintenance algorithm scales when the number of nodes and edges stored in the
graph database increases. Furthermore, our evaluation shows that our approach
can outperform existing approaches for the incremental maintenance of graph
query results.


title:
On High-Order Capacity Statistics of Spectrum Aggregation Systems over
  $\kappa$-$\mu$ and $\kappa$-$\mu$ shadowed Fading Channels

abstract:
  The frequency scarcity imposed by fast growing demand for mobile data service
requires promising spectrum aggregation systems. The so-called higher-order
statistics (HOS) of the channel capacity is a suitable metric on the system
performance. While prior relevant works have improved our knowledge on the HOS
characterization of spectrum aggregation systems, an analytical framework
encompassing generalized fading models of interest is not yet available. In
this paper, we pursue a detailed HOS analysis of $\kappa$-$\mu$ and
$\kappa$-$\mu$ shadowed fading channels by deriving novel and exact
expressions. Furthermore, the simplified HOS expressions for the asymptotically
low and high signal-to-noise regimes are derived. Several important statistical
measures, such as amount of fading, amount of dispersion, reliability,
skewness, and kurtosis, are obtained by using the HOS results. More
importantly, the useful implications of system and fading parameters on
spectrum aggregation systems are investigated for channel selection. Finally,
all derived expressions are validated via Monte-Carlo simulations.


title:
Dark matter physics, flavor physics and LHC constraints in the dark
  matter model with a bottom partner

abstract:
  In the scenario that a dark matter (DM) is a weakly interacting massive
particle, there are many possibilities of the interactions with the Standard
Model (SM) particles to achieve the relic density of DM. In this paper, we
consider one simple DM model where the DM candidate is a complex scalar and
interacts with the SM particles via exchange of the Higgs particle and an extra
quark, named bottom partner. The extra quark carries the same quantum number as
the right-handed down-type quarks and has Yukawa couplings with the DM
candidate and the right-handed down-type quarks. The Yukawa interactions are
not only relevant to the thermal relic density of the DM, but also contribute
to the flavor physics, such as the $\Delta F=2$ processes. In addition, the
flavor alignment of the Yukawa couplings is related to the decay modes of the
extra quark. Then, we can find the explicit correlations among the physical
observables in DM physics, flavor physics and the signals at the LHC. Based on
the numerical analyses of the thermal relic density, the direct detection of
the DM and the current LHC bounds using the latest results, we survey our
predictions for the $\Delta F=2$ processes. We investigate the perturbative
bound on the Yukawa coupling, as well. Study of a fermionic DM model with extra
scalar quarks is also given for comparison.


title: Probing Lepton Flavor Violation at the 13 TeV LHC

abstract:
  We investigate the bounds on tau-mu lepton flavor violation (LFV). Our main
focus is on the collider constrains on tau-mu LFV. We use the Type-III
Two-Higgs-Doublet-Model (2HDM) as a set up for our study. While the LFV
branching fraction of the 125 GeV is well constrained by current LHC searches,
the heavier neutral states could have a large branching fraction to tau and
muon. We estimate the LHC reach for the 13 TeV center of mass energy with 300
$\text{fb}^{-1}$ luminosity for a neutral boson decaying into a tau and a muon.
We identify parts of the LFV parameter space where the searches for heavy
scalar and pseudoscalar decaying into a tau and a muon are more sensitive than
the similar search for the 125 GeV boson.


title:
Ci\^ensa\c{c}\~ao: Gaining a feeling for sciences --- Ciensaci\'on:
  sentir la ciencia --- Ci\^ensa\c{c}\~ao: despertando um sentimento por
  ci\^encias

abstract:
  Ci\^ensa\c{c}\~ao, an open online repository for hands-on experiments, has
been developed to convince teachers in Latin America that science is best
experienced first hand. Permitting students to experiment autonomously in small
groups can be a challenging endeavour for educators in these countries. We
analyse the reasons that make teachers hesitate to apply hands-on experiments
in class, and discuss how Ci\^ensa\c{c}\~ao was implemented to overcome these
obstacles. The resulting student research activities are specifically designed
to be easily integrated in formal science education at school, to foster
research skills and, most importantly, to let young people get to know science
as an engaging creative activity.
  ----------
  Ciensaci\'on es un compilado abierto y en l\'inea de experimentos pr\'acticos
que ha sido creado para convencer a los docentes latinoamericanos de que la
mejor forma de vivir la ciencia es en primera persona. Permitir que los alumnos
realicen experimentos de forma aut\'onoma y en peque\~nos grupos es una tarea
desafiante para los educadores de estos pa\'ises. Analizamos los motivos por
los cuales los docentes se resisten a utilizar experimentos pr\'acticos en
clase y debatimos c\'omo se implement\'o Ciensaci\'on para sortear esos
obst\'aculos. El resultado fue la creaci\'on de actividades de investigaci\'on
para los alumnos, que pueden integrarse f\'acilmente a la educaci\'on
cient\'ifica formal de las escuelas, con el objetivo de desarrollar habilidades
cient\'ificas y, m\'as importante a\'un, para que los j\'ovenes puedan ver la
ciencia como una actividad creativa e interesante.
  ----------
  Ci\^ensa\c{c}\~ao, uma cole\c{c}\~ao aberta de experimentos pr\'aticos, foi
desenvolvida para convencer a professores da Am\'erica Latina que ci\^encia \'e
melhor entendida quando manuseada.


title: The Marginal Value of Networked Energy Storage

abstract:
  We consider the problem of characterizing the locational marginal value of
energy storage capacity in electric power networks with stochastic renewable
supply and demand. The perspective taken is that of a system operator, whose
objective is to minimize the expected cost of firm supply required to balance a
stochastic net demand process over a finite horizon, subject to transmission
and energy storage constraints. The value of energy storage capacity is defined
in terms of the optimal value of the corresponding constrained stochastic
control problem. It is shown to be concave and non decreasing in the vector of
location-dependent storage capacities -- implying that the greatest marginal
value of storage is derived from initial investments in storage capacities. We
also provide a characterization of said marginal value, which reveals its
explicit dependency on a specific measure of nodal price variation. And, more
generally, we derive an upper bound on the locational marginal value of energy
storage capacity in terms of the total variation of the corresponding nodal
price process, and provide conditions under which this bound is tight.


title: Hyper-Selective Plasmonic Color Filters

abstract:
  The subwavelength mode volumes of plasmonic filters are well matched to the
small size of state-of-the-art active pixels (~ 1 {\mu}m) in CMOS image sensor
arrays used in portable electronic devices. Typical plasmonic filters exhibit
broad (> 100 nm) transmission bandwidths. Dramatically reducing the peak width
of filter transmission spectra would allow for the realization of CMOS
hyperspectral imaging arrays, which demand the FWHM of transmission peaks to be
less than 30 nm. We find that the design of 5 layer
metal-insulator-metal-insulator-metal structures gives rise to multi-mode
interference phenomena that suppresses spurious transmission features gives
rise to a single narrow transmission band with FWHM as small as 17 nm. The
transmission peaks of these multilayer slot-mode plasmonic filters (MSPFs) can
be systematically varied throughout the visible and near infrared spectrum, so
the same basic structure can serve as a filter over a large range of
wavelengths.


title: 1.3 mm ALMA Observations of the Fomalhaut Debris System

abstract:
  We present ALMA Band 6 observations (1.3 mm/233 GHz) of Fomalhaut and its
debris disc. The observations achieve a sensitivity of 17 $\mu$Jy and a
resolution of 0.28 arcsec (2.1 au at a distance of 7.66 pc), which are the
highest resolution observations to date of the millimetre grains in Fomalhaut's
main debris ring. The ring is tightly constrained to $139^{+2}_{-3}$ au with a
FWHM of $13\pm3$ au, following a Gaussian profile. The millimetre spectral
index is constrained to $\alpha_{mm} = -2.62\pm0.12$. We explore fitting debris
disc models in the image plane, as well as fitting models using visibility data
directly. The results are compared and the potential advantages/disadvantages
of each approach are discussed.
  The detected central emission is indistinguishable from a point source, with
a most probable flux of $0.90\pm 0.12$ mJy (including calibration
uncertainties). This implies that any inner debris structure, as was inferred
from far-Infrared observations, must contribute little to the total central
emission. Moreover, the stellar flux is less than 70\% of that predicted by
extrapolating a black body from the constrained stellar photosphere
temperature. This result emphasizes that unresolved inner debris components
cannot be fully characterized until the behaviour of the host star's intrinsic
stellar emission at millimetre wavelengths is properly understood.


title:
Enhanced Structural Stability and Photo Responsiveness of CH3NH3SnI3
  Perovskite via Pressure-Induced Amorphization and Recrystallization

abstract:
  An organic-inorganic halide perovskite of CH3NH3SnI3 with significantly
improved structural stability is obtained via pressure-induced amorphization
and recrystallization. In situ high-pressure resistance measurements reveal an
increased electrical conductivity by 300% in the pressure-treated perovskite.
Photocurrent measurements also reveal a substantial enhancement in
visible-light responsiveness. The mechanism underlying the enhanced properties
is demonstrated to be associated with the improved structural stability.


title: Closed-Chain Manipulation of Large Objects by Multi-Arm Robotic Systems

abstract:
  Closed kinematic chains are created whenever multiple robot arms concurrently
manipulate a single object. The closed-chain constraint, when coupled with
robot joint limits, dramatically changes the connectivity of the configuration
space. We propose a regrasping move, termed "IK-switch", which allows
efficiently bridging components of the configuration space that are otherwise
mutually disconnected. This move, combined with several other developments,
such as a method to stabilize the manipulated object using the environment, a
new tree structure, and a compliant control scheme, enables us to address
complex closed-chain manipulation tasks, such as flipping a chair frame, which
is otherwise impossible to realize using existing multi-arm planning methods.


title: Derived Recollements and Generalised AR Formulas

abstract:
  The Defect Recollement, Restriction Recollement, Auslander-Gruson-Jensen
Recollement, and others, are shown to be instances of a general construction
using derived functors and methods from stable module theory. The right derived
functors $\textsf{W}_k:=R_k(\hspace{0.05cm}\underline{\ \ }\hspace{0.1cm} )^*$
are computed and it is shown that the functor
$\textsf{W}_2:=R_2(\hspace{0.05cm}\underline{\ \ }\hspace{0.1cm} )^*$ is right
exact and restricts to a duality $\textsf{W}$ of the defect zero functors. The
duality $\textsf{W}$ satisfies two identities which we call the Generalised
Auslander-Reiten formulas. We show that $\textsf{W}$ restricts to the
generalised Auslander-Bridger transpose and show that the Generalised
Auslander-Reiten formulas reduce to the well-known Auslander-Reiten formulas.


title: Experimental Study of Forrelation in Nuclear Spins

abstract:
  Correlation functions are often employed to quantify the relationships among
interdependent variables or sets of data. Recently, a new class of correlation
functions, called Forrelation, has been introduced by Aaronson and Ambainis for
studying the query complexity of quantum devices. It was found that there
exists a quantum query algorithm solving 2-fold Forrelation problems with an
exponential quantum speedup over all possible classical means, which represents
essentially the largest possible separation between quantum and classical query
complexities. Here we report an experimental study probing the 2-fold and
3-fold Forrelations encoded in nuclear spins. The major experimental challenge
is to control the spin fluctuation to within a threshold value, which is
achieved by developing a set of optimized GRAPE pulse sequences. Overall, our
small-scale implementation indicates that the quantum query algorithm is
capable of determine the values of Forrelations within an acceptable accuracy
required for demonstrating quantum supremacy, given the current technology and
in the presence of experimental noise.


title:
Adiabatic quantum parameter amplification for generic robust quantum
  sensing

abstract:
  Quantum enhanced sensing provides a powerful tool for the precise measurement
of physical parameters that is applicable in many areas of science and
technology. The achievable gain in sensitivity is largely limited by the
influence of noise and decoherence. Here, we propose a paradigm of adiabatic
quantum parameter amplification to overcome this limitation. We demonstrate
that it allows to achieve generic robust quantum sensing, namely it is robust
against noise that may even acting on the same degree of freedom as the field.
Furthermore, the proposal achieves entanglement-free Heisenberg limit
sensitivity that surpasses the limit of classical statistics.


title:
Geometric intersection number of simple closed curves on a surface and
  symplectic expansions of free groups

abstract:
  For two oriented simple closed curves on a compact orientable surface with a
connected boundary we introduce a simple computation of a value in the first
homology group of the surface, which detects in some cases that the geometric
intersection number of the curves is greater than zero when their algebraic
intersection number is zero. The value, computed from two elements of the
fundamental group of the surface corresponding to the curves, is found in the
difference between one of the elements and its image of the action of Dehn
twist along the other. To give a description of the difference symplectic
expansions of free groups is an effective tool, since we have an explicit
formula for the action of Dehn twist on the target space of the expansion due
to N.\ Kawazumi and Y.\ Kuno.


title:
Fine-grained Recurrent Neural Networks for Automatic Prostate
  Segmentation in Ultrasound Images

abstract:
  Boundary incompleteness raises great challenges to automatic prostate
segmentation in ultrasound images. Shape prior can provide strong guidance in
estimating the missing boundary, but traditional shape models often suffer from
hand-crafted descriptors and local information loss in the fitting procedure.
In this paper, we attempt to address those issues with a novel framework. The
proposed framework can seamlessly integrate feature extraction and shape prior
exploring, and estimate the complete boundary with a sequential manner. Our
framework is composed of three key modules. Firstly, we serialize the static 2D
prostate ultrasound images into dynamic sequences and then predict prostate
shapes by sequentially exploring shape priors. Intuitively, we propose to learn
the shape prior with the biologically plausible Recurrent Neural Networks
(RNNs). This module is corroborated to be effective in dealing with the
boundary incompleteness. Secondly, to alleviate the bias caused by different
serialization manners, we propose a multi-view fusion strategy to merge shape
predictions obtained from different perspectives. Thirdly, we further implant
the RNN core into a multiscale Auto-Context scheme to successively refine the
details of the shape prediction map. With extensive validation on challenging
prostate ultrasound images, our framework bridges severe boundary
incompleteness and achieves the best performance in prostate boundary
delineation when compared with several advanced methods. Additionally, our
approach is general and can be extended to other medical image segmentation
tasks, where boundary incompleteness is one of the main challenges.


title: ATLAS SM VH(bb) Run-2 Search

abstract:
  The Higgs boson discovered at the LHC in 2012 has been observed coupling
directly to $W$ and $Z$ bosons and to $\tau$ leptons, and indirectly to top
quarks. In order to probe whether it is indeed the particle predicted by the
Standard Model, direct couplings of the Higgs boson to quarks must also be
measured. The Higgs boson decays most often to a pair of bottom quarks (with a
branching ratio of 58%). When the Higgs boson is produced alone in gluon-gluon
fusion, the signal in this decay mode is overwhelmed by the regular multi-jet
background. By requiring the Higgs boson to be produced in association with a
vector boson $V$ ($W$ or $Z$), which is further required to decay leptonically,
data events can be selected using charged-lepton or missing transverse energy
triggers. The Tevatron experiments presented combined results showing evidence
for the $VH(b\bar{b})$ process at a significance level of about 3 standard
deviations, while the combined LHC results from Run-1 data show a 2.6 standard
deviation evidence for the $H\rightarrow b\bar{b}$ decay mode. In this poster,
the ATLAS $VH(b\bar{b})$ search using Run-2 data is summarised.


title: Binary Subspace Coding for Query-by-Image Video Retrieval

abstract:
  The query-by-image video retrieval (QBIVR) task has been attracting
considerable research attention recently. However, most existing methods
represent a video by either aggregating or projecting all its frames into a
single datum point, which may easily cause severe information loss. In this
paper, we propose an efficient QBIVR framework to enable an effective and
efficient video search with image query. We first define a
similarity-preserving distance metric between an image and its orthogonal
projection in the subspace of the video, which can be equivalently transformed
to a Maximum Inner Product Search (MIPS) problem.
  Besides, to boost the efficiency of solving the MIPS problem, we propose two
asymmetric hashing schemes, which bridge the domain gap of images and videos.
The first approach, termed Inner-product Binary Coding (IBC), preserves the
inner relationships of images and videos in a common Hamming space. To further
improve the retrieval efficiency, we devise a Bilinear Binary Coding (BBC)
approach, which employs compact bilinear projections instead of a single large
projection matrix. Extensive experiments have been conducted on four real-world
video datasets to verify the effectiveness of our proposed approaches as
compared to the state-of-the-arts.


title:
Thermal conductivity of local moment models with strong spin-orbit
  coupling

abstract:
  We study the magnetic and lattice contributions to the thermal conductivity
of electrically insulating strongly spin-orbit coupled magnetically ordered
phases on a two-dimensional honeycomb lattice using the Kitaev-Heisenberg
model. Depending on model parameters, such as the relative strength of the
spin-orbit induced anisotropic coupling, a number of magnetically ordered
phases are possible. In this work, we study two distinct regimes of thermal
transport depending on whether the characteristic energy of the phonons or the
magnons dominates, and focus on two different relaxation mechanisms, boundary
scattering and magnon-phonon scattering. For spatially anisotropic magnetic
phases, the thermal conductivity tensor can be highly anisotropic when the
magnetic energy scale dominates, since the magnetic degrees of freedom dominate
the thermal transport for temperatures well below the magnetic transition
temperature. In the opposite limit in which the phonon energy scale dominates,
the thermal conductivity will be nearly isotropic, reflecting the isotropic (at
low temperatures) phonon dispersion assumed for the honeycomb lattice. We
further discuss the extent to which thermal transport properties are influenced
by strong spin-orbit induced anisotropic coupling in the local moment regime of
insulating magnetic phases. The developed methodology can be applied to any 2D
magnon-phonon system, and more importantly to systems where an analytical
Bogoliubov transformation cannot be found and magnon bands are not necessarily
isotropic.


title: Fractal Intersections and Products via Algorithmic Dimension

abstract:
  Algorithmic fractal dimensions quantify the algorithmic information density
of individual points and may be defined in terms of Kolmogorov complexity. This
work uses these dimensions to bound the classical Hausdorff and packing
dimensions of intersections and Cartesian products of fractals in Euclidean
spaces. This approach shows that two prominent, fundamental results about the
dimension of Borel or analytic sets also hold for arbitrary sets.


title: Radiative 3He(2H,g)5Li capture at low deuterium energy

abstract:
  The results are presented on the total cross sections, astrophysical
S-factor, reaction rate of the deuteron radiative capture on 3He at the
temperatures from 0.03 up to 3 T9 calculated in the framework of the potential
cluster model with the forbidden states coming from the classification of the
orbital states by the Young diagrams. Within the used model and exploited Young
diagram classification made it possible to reproduce the general features of
the available experimental data on the cross section and reconstructed
astrophysical S-factor in the energy range from 200 keV up to 1.4 MeV. The
parametrization of the obtained reaction rate has been found and been compared
with some other actual reactions with light clusters.


title:
Topological transitions induced by antiferromagnetism in a thin-film
  topological insulator

abstract:
  Ferromagnetism in topological insulators (TIs) opens a topologically
non-trivial exchange band gap, providing an exciting platform to manipulate the
topological order through an external magnetic field. Here, we experimentally
show that the surface of an antiferromagnetic thin film can independently
control the topological order of the top and the bottom surface states of a TI
thin film through proximity couplings. During the magnetization reversal in a
field scan, two intermediate spin configurations stem from unsynchronized
magnetic switchings of the top and the bottom AFM/TI interfaces. These magnetic
configurations are shown to result in new topological phases with non-zero
Chern numbers for each surface, introducing two counter-propagating chiral edge
modes inside the exchange gap. This change in the number of transport channels,
as the result of the topological transitions, induces antisymmetric
magneto-resistance spikes during the magnetization reversal. With the high Neel
ordering temperature provided by the antiferromagnetic layers, the signature of
the induced topological transition persists in transport measurements up to a
temperature of around 90 K, a factor of three over the Curie temperature in a
typical magnetically doped TI thin film.


title: A slip wave solution in anti-plane elasticity

abstract:
  It is shown that a slip wave solution exists for anti-plane sliding of an
elastic layer on an elastic half-space. It is a companion solution to the
well-known Love wave solution.


title:
Efficient Non-oblivious Randomized Reduction for Risk Minimization with
  Improved Excess Risk Guarantee

abstract:
  In this paper, we address learning problems for high dimensional data.
Previously, oblivious random projection based approaches that project high
dimensional features onto a random subspace have been used in practice for
tackling high-dimensionality challenge in machine learning. Recently, various
non-oblivious randomized reduction methods have been developed and deployed for
solving many numerical problems such as matrix product approximation, low-rank
matrix approximation, etc. However, they are less explored for the machine
learning tasks, e.g., classification. More seriously, the theoretical analysis
of excess risk bounds for risk minimization, an important measure of
generalization performance, has not been established for non-oblivious
randomized reduction methods. It therefore remains an open problem what is the
benefit of using them over previous oblivious random projection based
approaches. To tackle these challenges, we propose an algorithmic framework for
employing non-oblivious randomized reduction method for general empirical risk
minimizing in machine learning tasks, where the original high-dimensional
features are projected onto a random subspace that is derived from the data
with a small matrix approximation error. We then derive the first excess risk
bound for the proposed non-oblivious randomized reduction approach without
requiring strong assumptions on the training data. The established excess risk
bound exhibits that the proposed approach provides much better generalization
performance and it also sheds more insights about different randomized
reduction approaches. Finally, we conduct extensive experiments on both
synthetic and real-world benchmark datasets, whose dimension scales to
$O(10^7)$, to demonstrate the efficacy of our proposed approach.


title:
On the existence of optimal controls for backward stochastic partial
  differential equations

abstract:
  This paper is concerned with the existence of optimal controls for backward
stochastic partial differential equations with random coefficients, in which
the control systems are represented in an abstract evolution form, i.e.
backward stochastic evolution equations. Under some growth and monotonicity
conditions on the coefficients and suitable assumptions on the Hamiltonian
function, the existence of the optimal control boils down to proving the
uniqueness and existence of a solution to the stochastic Hamiltonian system,
i.e. a fully coupled forward-backward stochastic evolution equation. Using some
a prior estimates, we prove the uniqueness and existence via the method of
continuation. Two examples of linear-quadratic control are solved to
demonstrate our results.


title: The first Pontrjagin classes of homotopy complex projective spaces

abstract:
  Let $M^{2n}$ be a closed smooth manifold homotopy equivalent to the complex
projective space $\mathbb{C}P(n)$. The purpose of this paper is to show that
when $n$ is even, the difference of the first Pontrjagin classes between
$M^{2n}$ and $\mathbb{C}P(n)$ is divisible by 16.


title:
Optical suppression of electron motion in low-dimensional correlated
  electron system

abstract:
  Suppression of electron motion under an alternating current (AC) electric
field is examined in a one-dimensional Hubbard model. Utilizing three
complementary calculation methods, it is found unambiguously that magnitudes of
the kinetic-energy suppressions are influenced sensitively by the Coulomb
interaction as well as the electron density. The phase and frequency in the AC
field do not bring about major effects. The results are interpreted as a
combined effect of the Coulomb interaction and the AC field, and provide a
guiding principle for the photocontrol of correlated electron motion.


title:
Ternary fission within the temperature dependent relativistic mean field
  approach

abstract:
  For the first time, we apply the temperature dependent relativistic mean
field (TRMF) model to study the ternary fission of heavy nucleus using level
density approach. The probability of yields of a particular fragment is
obtained by evaluating the convolution integrals which employ the excitation
energy and the level density parameter for a given temperature calculated
within the TRMF formalism. To illustrate, we have considered the ternary
fissions in 252Cf, 242Pu and 236U with fixed third fragment A3 = 48Ca, 20O and
16O respectively. The relative yields are studied for the temperatures T = 1, 2
and 3 MeV. For the comparison, the relative yields are also calculated from the
single particle energies of the finite range droplet model (FRDM). In general,
the larger phase space for the ternary fragmentation is observed indicating
that such fragmentations are most probable ones. For T = 2 and 3 MeV, the Sn +
Ni + Ca is the most probable combination for the nucleus 252Cf. However, for
the nuclei 242Pu and 236U, the maximum fragmentation yields at T = 2 MeV differ
from those at T = 3 MeV. For T = 3 MeV, the closed shell (Z = 8) light mass
fragments with its corresponding partners has larger yield values. But, at T =
2 MeV Si/P/S are favorable fragments with the corresponding partners. It is
noticed that the symmetric binary fragmentation along with the fixed third
fragment for 242Pu and 236U are also favored at T = 1 MeV. The temperature
dependence of the nuclear shape and the single particle energies are also
discussed.


title:
Necessary and Sufficient Condition for Asymptotic Standard Normality of
  the Two Sample Pivot

abstract:
  The asymptotic solution to the problem of comparing the means of two
heteroscedastic populations, based on two random samples from the populations,
hinges on the pivot underpinning the construction of the confidence interval
and the test statistic being asymptotically standard Normal. The pivot is known
to converge to the standard Normal distribution if the two samples are
independent and the ratio of the sample sizes converges to a finite positive
number. We show, without any restriction on the asymptotic behavior of the
ratio of the sample sizes, that Cesaro convergence of the sequence of cross
sample correlation coefficients to 0 is necessary and sufficient for the
aforesaid pivotal convergence. We also obtain, without any assumption on the
cross sample dependence structure, that both iterated limits of the pivot are
standard Normal and if the joint distribution of the standardized sample means
converges to a spherically symmetric distribution, then that distribution must
be bivariate standard Normal.


title: MarioQA: Answering Questions by Watching Gameplay Videos

abstract:
  We present a framework to analyze various aspects of models for video
question answering (VideoQA) using customizable synthetic datasets, which are
constructed automatically from gameplay videos. Our work is motivated by the
fact that existing models are often tested only on datasets that require
excessively high-level reasoning or mostly contain instances accessible through
single frame inferences. Hence, it is difficult to measure capacity and
flexibility of trained models, and existing techniques often rely on ad-hoc
implementations of deep neural networks without clear insight into datasets and
models. We are particularly interested in understanding temporal relationships
between video events to solve VideoQA problems; this is because reasoning
temporal dependency is one of the most distinct components in videos from
images. To address this objective, we automatically generate a customized
synthetic VideoQA dataset using {\em Super Mario Bros.} gameplay videos so that
it contains events with different levels of reasoning complexity. Using the
dataset, we show that properly constructed datasets with events in various
complexity levels are critical to learn effective models and improve overall
performance.


title: Abelian spatial string tension in finite temperature SU(2) gauge theory

abstract:
  We investigate Abelian and monopole contributions to spatial string tension
in the deconfined phase of finite temperature SU(2) gauge theory without
imposing any gauge fixing conditions. Lattice calculations of non-Abelian and
Abelian spatial string tensions from the Wilson action at gauge coupling
$\beta=2.74$ and lattice volume $24^3\times{N_t}$ $(N_{t}=\left\{
24,8,6,4,2)\right\}$ show that these string tensions agree with each other
within error bars at any adopted value of $N_t$, which implies Abelian
dominance. From measurements of non-Abelian, Abelian, and monopole forces that
arise from the corresponding spatial string tension, furthermore, we find the
tendency that the monopole contribution to the spatial string tension can be
almost as large as the non-Abelian and Abelian ones. The temperature dependence
of the calculated non-Abelian and Abelian spatial string tensions allows us to
conclude that the concept of dimensional reduction holds both for non-Abelian
and Abelian sectors at temperatures higher than twice the critical temperature.


title:
First-principles electrostatic potentials for reliable alignment at
  interfaces and defects

abstract:
  Alignment of electrostatic potential between different atomic configurations
is necessary for first-principles calculations of band offsets across
interfaces and formation energies of charged defects. However, strong
oscillations of this potential at the atomic scale make alignment challenging,
especially when atomic geometries change considerably from bulk to the vicinity
of defects and interfaces. We introduce a method to suppress these strong
oscillations by eliminating the deep wells in the potential at each atom. We
demonstrate that this method considerably improves the system-size convergence
of a wide range of first-principles predictions that depend on alignment of
electrostatic potentials, including band offsets at solid-liquid interfaces,
and formation energies of charged vacancies in solids and at solid surfaces in
vacuum. Finally, we use this method in conjunction with continuum solvation
theories to investigate energetics of charged vacancies at solid-liquid
interfaces. We find that for the example of an NaCl (001) surface in water,
solvation reduces the formation energy of charged vacancies by 0.5 eV:
calculation of this important effect was previously impractical due to
computational cost in molecular-dynamics methods.


title: On Systolic Zeta Functions

abstract:
  We define Dirichlet type series associated with homology length spectra of
Riemannian, or Finsler, manifolds, or polyhedra, and investigate some of their
analytical properties. As a consequence we obtain an inequality analogous to
Gromov's classical intersystolic inequality, but taking the whole homology
length spectrum into account rather than just the systole.


title: On linearity of pan-integral and pan-integrable functions space

abstract:
  $L\sp{p}$ space is a crucial aspect of classical measure theory. For
nonadditive measure, it is known that $L\sp{p}$ space theory holds for the
Choquet integral whenever the monotone measure $\mu$ is submodular and
continuous from below. The main purpose of this paper is to generalize
$L\sp{p}$ space theory to $+,\cdot$-based pan-integral. Let $(X, {\cal A},
\mu)$ be a monotone measure space. We prove that the $+,\cdot$-based
pan-integral is additive with respect to integrands if $\mu$ is subadditive.
Then we introduce the pan-integral for real-valued functions(not necessarily
nonnegative), and prove that this integral possesses linearity if $\mu$ is
subadditive. By using the linearity of pan-integral, we finally show that all
of the pan-integrable functions form a Banach space. Since the $+,\cdot$-based
pan-integral coincides with the concave integral for subadditive measure, the
results obtained in this paper remain valid for the concave integral. Noticing
that an outer measure is subadditive, we can define a Lebesgue-like
integral(possesses linearity) from an outer measure, and the $L\sp{p}$ theory
holds for this integral.
  {\it Keywords:} Monotone measure; Subadditivity; Pan-integral; Linearity;
Pan-integrable space; Completeness


title: Anatomy of chiral magnetic effect in and out of equilibrium

abstract:
  We identify a new contribution to the chiral magnetic conductivity at finite
frequencies -- the magnetization current. This allows to quantitatively
reproduce the known field-theoretic time-dependent (AC) chiral magnetic
response in terms of kinetic theory. We evaluate the corresponding AC chiral
magnetic conductivity in two flavor QCD plasma at weak coupling. The
magnetization current results from the spin response of chiral quasiparticles
to magnetic field, and is thus proportional to the quasiparticle's $g$-factor.
In condensed matter systems, where the chiral quasi-particles are emergent and
the $g$-factor can significantly differ from 2, this opens the possibility to
tune the AC chiral magnetic response.


title: Managing Usability and Reliability Aspects in Cloud Computing

abstract:
  Cloud computing provides a great opportunity for scientists, as it enables
large-scale experiments that cannot are too long to run on local desktop
machines. Cloud-based computations can be highly parallel, long running and
data-intensive, which is desirable for many kinds of scientific experiments.
However, to unlock this power, we need a user-friendly interface and an
easy-to-use methodology for conducting these experiments. For this reason, we
introduce here a formal model of a cloud-based platform and the corresponding
open-source implementation. The proposed solution allows to conduct experiments
without having a deep technical understanding of cloud-computing, HPC, fault
tolerance, or data management in order to leverage the benefits of cloud
computing. In the current version, we have focused on biophysics and structural
chemistry experiments, based on the analysis of big data from synchrotrons and
atomic force microscopy. The domain experts noted the time savings for
computing and data management, as well as user-friendly interface.


title:
Numerical determination of the $\Lambda$-parameter in SU(3) gauge theory
  from the twisted gradient flow coupling

abstract:
  We estimate the $\Lambda$-parameter in the $\overline{\mathrm{MS}}$ scheme
for the SU(3) pure gauge theory with the twisted gradient flow method
non-perturbatively. We obtain
$\Lambda_{\overline{\mathrm{MS}}}/\sqrt{\sigma}=0.527(13)(10)$ and
$r_{0}\Lambda_{\overline{\mathrm{MS}}}=0.605(15)(5)$ which are consistent with
the known values.This demonstrates the validity of the present method.


title:
High-resolution Collinear Chiral Sum Frequency Generation Microscopy by
  Using Vectorial Beam

abstract:
  In chiral sum frequency generation (C-SFG), the chiral nature of
${\chi}^{(2)}$ requires the three involved electric fields to be pairwise
non-parallel, leading to the traditional non-collinear configuration which is a
hindrance for achieving diffraction limited resolution while utilizing it as a
label-free imaging contrast mechanism . Here we propose a collinear C-SFG
(CC-SFG) microscopy modality by using longitudinal z-polarized vectorial field.
Label-free chiral imaging with enhanced spatial resolution (~1.4 times
improvement in one lateral and the longitudinal directions over the traditional
non-collinear scheme) is demonstrated, providing a new path for SFG microscopy
with diffraction-limited resolution for mapping chirality.


title: Supervised topic models for clinical interpretability

abstract:
  Supervised topic models can help clinical researchers find interpretable
cooccurence patterns in count data that are relevant for diagnostics. However,
standard formulations of supervised Latent Dirichlet Allocation have two
problems. First, when documents have many more words than labels, the influence
of the labels will be negligible. Second, due to conditional independence
assumptions in the graphical model the impact of supervised labels on the
learned topic-word probabilities is often minimal, leading to poor predictions
on heldout data. We investigate penalized optimization methods for training
sLDA that produce interpretable topic-word parameters and useful heldout
predictions, using recognition networks to speed-up inference. We report
preliminary results on synthetic data and on predicting successful
anti-depressant medication given a patient's diagnostic history.