title:
Protected ground states in short chains of coupled spins in circuit
  quantum electrodynamics

abstract:
  The two degenerate ground states of the anisotropic Heisenberg (XY) spin
model of a chain of qubits (pseudo-spins) can encode quantum information, but
their degree of protection against local perturbations is known to be only
partial. We examine the properties of the system in the presence of non-local
spin-spin interactions, possibly emerging from the quantum electrodynamics of
the device. We find a phase distinct from the XY phase admitting two ground
states which are highly protected against all local field perturbations,
persisting across a range of parameters. In the context of the XY chain we
discuss how the coupling between two ground states can be used to observe
signatures of topological edge states in a small controlled chain of
superconducting transmon qubits.


title: Asymptotic stability of the Cauchy and Jensen functional equations

abstract:
  The aim of this note is to investigate the asymptotic stability behaviour of
the Cauchy and Jensen functional equations. Our main results show that if these
equations hold for large arguments with small error, then they are also valid
everywhere with a new error term which is a constant multiple of the original
error term. As consequences, we also obtain results of hyperstability character
for these two functional equations.


title:
Inertial manifolds for 1D reaction-diffusion-advection systems. Part I:
  Dirichlet and Neumann boundary conditions

abstract:
  This is the first part of our study of inertial manifolds for the system of
1D reaction-diffusion-advection equations which is devoted to the case of
Dirichlet or Neumann boundary conditions. Although this problem does not
initially possess the spectral gap property, it is shown that this property is
satisfied after the proper non-local change of the dependent variable. The case
of periodic boundary conditions where the situation is principally different
and the inertial manifold may not exist is considered in the second part of our
study.


title: On the relativistic mass function and averaging in cosmology

abstract:
  The general relativistic description of cosmological structure formation is
an important challenge from both the theoretical and the numerical point of
views. In this paper we present a brief prescription for a general relativistic
treatment of structure formation and a resulting mass function on galaxy
cluster scales in a highly generic scenario. To obtain this we use an exact
scalar averaging scheme together with the relativistic generalization of
Zel'dovich's approximation (RZA) that serves as a closure condition for the
averaged equations.


title:
Label Transfer from APOGEE to LAMOST: Precise Stellar Parameters for
  450,000 LAMOST Giants

abstract:
  In this era of large-scale stellar spectroscopic surveys, measurements of
stellar attributes ("labels," i.e. parameters and abundances) must be made
precise and consistent across surveys. Here, we demonstrate that this can be
achieved by a data-driven approach to spectral modeling. With The Cannon, we
transfer information from the APOGEE survey to determine precise Teff, log g,
[Fe/H], and [$\alpha$/M] from the spectra of 450,000 LAMOST giants. The Cannon
fits a predictive model for LAMOST spectra using 9952 stars observed in common
between the two surveys, taking five labels from APOGEE DR12 as ground truth:
Teff, log g, [Fe/H], [\alpha/M], and K-band extinction $A_k$. The model is then
used to infer Teff, log g, [Fe/H], and [$\alpha$/M] for 454,180 giants, 20% of
the LAMOST DR2 stellar sample. These are the first [$\alpha$/M] values for the
full set of LAMOST giants, and the largest catalog of [$\alpha$/M] for giant
stars to date. Furthermore, these labels are by construction on the APOGEE
label scale; for spectra with S/N > 50, cross-validation of the model yields
typical uncertainties of 70K in Teff, 0.1 in log g, 0.1 in [Fe/H], and 0.04 in
[$\alpha$/M], values comparable to the broadly stated, conservative APOGEE DR12
uncertainties. Thus, by using "label transfer" to tie low-resolution (LAMOST R
$\sim$ 1800) spectra to the label scale of a much higher-resolution (APOGEE R
$\sim$ 22,500) survey, we substantially reduce the inconsistencies between
labels measured by the individual survey pipelines. This demonstrates that
label transfer with The Cannon can successfully bring different surveys onto
the same physical scale.


title:
An N-barrier maximum principle for autonomous systems of $n$ species and
  its application to problems arising from population dynamics

abstract:
  We show that the N-barrier maximum principle (NBMP) remains true for $n$
$(n>2)$ species. In addition, a stronger lower bound in NBMP is given by
employing an improved tangent line method. As an application of NBMP, we
establish a nonexistence result for traveling wave solutions to the four
species Lotka-Volterra system.


title: Thermalization in many-particle quantum walks

abstract:
  Many-particles quantum walks of particles obeying Bose statistics moving on
graphs of various topologies are introduced. A single coin tossing commands the
conditional shift operation over the whole graph. Vertices particle densities,
the mean values of the phase space variables, second order spatial correlation
and counting statistics are evaluated and simulated. Evidence of an universal
dynamics is presented.


title: Topological Insulators at Strong Disorder

abstract:
  Topological insulators are newly discovered materials with the defining
property that any boundary cut into such crystal supports spectrum which is
immune to the Anderson localization. The present paper summarizes our efforts
on the rigorous characterization of these materials in the regime of weak and
strong disorder. In particular, the defining property is rigorously proven
under certain relevant conditions, for more than half of the classification
table of topological insulators.


title: Bit-Planes: Dense Subpixel Alignment of Binary Descriptors

abstract:
  Binary descriptors have been instrumental in the recent evolution of
computationally efficient sparse image alignment algorithms. Increasingly,
however, the vision community is interested in dense image alignment methods,
which are more suitable for estimating correspondences from high frame rate
cameras as they do not rely on exhaustive search. However, classic dense
alignment approaches are sensitive to illumination change. In this paper, we
propose an easy to implement and low complexity dense binary descriptor, which
we refer to as bit-planes, that can be seamlessly integrated within a
multi-channel Lucas & Kanade framework. This novel approach combines the
robustness of binary descriptors with the speed and accuracy of dense alignment
methods. The approach is demonstrated on a template tracking problem achieving
state-of-the-art robustness and faster than real-time performance on consumer
laptops (400+ fps on a single core Intel i7) and hand-held mobile devices (100+
fps on an iPad Air 2).


title: On the Rankin-Selberg method for higher genus string amplitudes

abstract:
  Closed string amplitudes at genus $h\leq 3$ are given by integrals of Siegel
modular functions on a fundamental domain of the Siegel upper half-plane. When
the integrand is of rapid decay near the cusps, the integral can be computed by
the Rankin-Selberg method, which consists of inserting an Eisenstein series
$E_h(s)$ in the integrand, computing the integral by the orbit method, and
finally extracting the residue at a suitable value of $s$. String amplitudes,
however, typically involve integrands with polynomial or even exponential
growth at the cusps, and a renormalization scheme is required to treat infrared
divergences. Generalizing Zagier's extension of the Rankin-Selberg method at
genus one, we develop the Rankin-Selberg method for Siegel modular functions of
degree 2 and 3 with polynomial growth near the cusps. In particular, we show
that the renormalized modular integral of the Siegel-Narain partition function
of an even self-dual lattice of signature $(d,d)$ is proportional to a residue
of the Langlands-Eisenstein series attached to the $h$-th antisymmetric tensor
representation of the T-duality group $O(d,d,Z)$.


title: Bandits meet Computer Architecture: Designing a Smartly-allocated Cache

abstract:
  In many embedded systems, such as imaging sys- tems, the system has a single
designated purpose, and same threads are executed repeatedly. Profiling thread
behavior, allows the system to allocate each thread its resources in a way that
improves overall system performance. We study an online resource al-
locationproblem,wherearesourcemanagersimulta- neously allocates resources
(exploration), learns the impact on the different consumers (learning) and im-
proves allocation towards optimal performance (ex- ploitation). We build on the
rich framework of multi- armed bandits and present online and offline algo-
rithms. Through extensive experiments with both synthetic data and real-world
cache allocation to threads we show the merits and properties of our al-
gorithms


title: Learning a low-rank shared dictionary for object classification

abstract:
  Despite the fact that different objects possess distinct class-specific
features, they also usually share common patterns. Inspired by this
observation, we propose a novel method to explicitly and simultaneously learn a
set of common patterns as well as class-specific features for classification.
Our dictionary learning framework is hence characterized by both a shared
dictionary and particular (class-specific) dictionaries. For the shared
dictionary, we enforce a low-rank constraint, i.e. claim that its spanning
subspace should have low dimension and the coefficients corresponding to this
dictionary should be similar. For the particular dictionaries, we impose on
them the well-known constraints stated in the Fisher discrimination dictionary
learning (FDDL). Further, we propose a new fast and accurate algorithm to solve
the sparse coding problems in the learning step, accelerating its convergence.
The said algorithm could also be applied to FDDL and its extensions.
Experimental results on widely used image databases establish the advantages of
our method over state-of-the-art dictionary learning methods.


title: Squarefree integers in large arithmetic progressions

abstract:
  We show that the exponent of distribution of the sequence of squarefree
numbers in arithmetic progressions of prime modulus is $\geq 2/3 + 1/57$,
improving a result of Prachar from 1958. Our main tool is an upper bound for
certain bilinear sums of exponential sums which resemble Kloosterman sums,
going beyond what can be obtained by the Polya-Vinogradov completion method.


title: The Case for PSR J1614-2230 as a NICER Target

abstract:
  The Neutron star Interior Composition ExploreR (NICER) is expected to launch
in early 2017 and will gather X-ray data on neutron stars and other high-energy
sources from a berth on the International Space Station. Its prime scientific
goal is to measure the masses and radii of non-accreting neutron stars via fits
to the energy-dependent waveforms produced by the rotation of hot spots on
their surfaces. These measurements will provide valuable input to theoretical
models of cold matter beyond nuclear density. Here we propose that PSR
J1614$-$2230, despite its low count rate, is a promising source to observe with
NICER. The reason is that XMM-Newton observations suggest that the fractional
oscillation amplitude from PSR J1614$-$2230 could be high enough that this star
cannot be very compact. We show that if we analyze 0.5 Ms of NICER data and 0.1
Ms of nearby off-source data and combine that analysis with the known mass of
this star, we would find a robust lower limit to the radius with a statistical
uncertainty of only $\sim 0.5-0.7$ km. We also show that even if there is an
unmodeled nonthermal component modulated at the pulsation frequency, good
statistical fits could rule out significant biases. The low count rate will
make reliable upper limits on the radius difficult, but the lower limit could
rule out some equations of state that are currently being discussed. This
analysis would require a good estimate of the non-source background, so Chandra
observations of the vicinity of PSR J1614$-$2230 would be helpful.


title:
Role of charged defects on the electrical and electro-mechanical
  properties of rhombohedral Pb(Zr,Ti)O3 with oxygen octahedra tilts

abstract:
  Oxygen octahedra tilting is a common structural phenomenon in perovskites and
has been subject of intensive studies, particularly in rhombohedral Pb(Zr,Ti)O3
(PZT). Early reports suggest that the tilted octahedra may strongly affect the
domain switching behavior, dielectric and piezoelectric properties of PZT
ceramics. In a way similar to that proposed for tilts, however, charged
defects, associated with oxygen vacancies, may also inhibit the motion of the
domain walls, resulting macroscopically in pinched hysteresis loops and reduced
piezoelectric response. Here, we revisit the early studies on rhombohedral PZT
ceramics with tilted octahedra by considering a possible role of both tilts and
charged defects on domain-wall motion. We show that the observed pinched
hysteresis loops are likely associated with the presence of defect complexes
containing charged oxygen vacancies, and not tilts as suggested in some cases.
Regardless of the presence or absence of long-range ordered tilts in
rhombohedral PZT, the effect of charged defects is also prominent in weak-field
permittivity and piezoelectric properties, particularly at sub-Hz driving
conditions where the conductivity, related to the motion of oxygen vacancies,
gives rise to strong frequency dispersion.


title: On Hilbert's irreducibility theorem

abstract:
  In this paper we obtain new quantitative forms of Hilbert's Irreducibility
Theorem. In particular, we show that if $f(X, T_1, \ldots, T_s)$ is an
irreducible polynomial with integer coefficients, having Galois group $G$ over
the function field $\mathbb{Q}(T_1, \ldots, T_s)$, and $K$ is any subgroup of
$G$, then there are at most $O_{f,
\varepsilon}(H^{s-1+|G/K|^{-1}+\varepsilon})$ specialisations $\mathbf{t} \in
\mathbb{Z}^s$ with $|\mathbf{t}| \le H$ such that the resulting polynomial
$f(X)$ has Galois group $K$ over the rationals.


title: Unpredictable Points and Chaos

abstract:
  It is revealed that a special kind of Poisson stable point, which we call an
unpredictable point, gives rise to the existence of chaos in the quasi-minimal
set. The existing definitions of chaos are formulated in sets of motions. This
is the first time that description of chaos is initiated from a single motion.
The theoretical results are exemplified by means of the symbolic dynamics.


title: On Certain Generalizations of Rogers-Ramanujan Type Identities

abstract:
  We state and prove a number of unilateral and bilateral $q$-series identities
and explore some of their consequences. Those include certain generalizations
of the $q$-binomial sum which also generalize the $q$-Airy function introduced
by Ramanujan, as well as certain identities with an interesting
variable-parameter symmetry based on limiting cases of Heine's transformation
of basic hypergeomteric functions.


title:
Photoluminescence and the gallium problem for highest-mobility
  GaAs/AlGaAs-based 2d electron gases

abstract:
  The quest for extremely high mobilities of 2d electron gases in MBE-grown
heterostructures is hampered by the available purity of the starting materials,
particularly of the gallium. Here we compare the role of different Ga lots
having nominally the highest possible quality on the mobility and the
photoluminescence (PL) of modulation doped single interface structures and find
significant differences. A weak exciton PL reveals that the purity of the Ga is
insufficient. No high mobility can be reached with such a lot with a reasonable
effort. On the other hand, a strong exciton PL indicates a high initial Ga
purity, allowing to reach mobilities of 15 million (single interface) or 28
million $cm^2/Vsec$ (doped quantum wells) in our MBE systems. We discuss
possible origins of the inconsistent Ga quality. Furthermore, we compare
samples grown in different MBE systems over a period of several years and find
that mobility and PL is correlated if similar structures and growth procedures
are used.


title:
Effective equidistribution of circles in the limit sets of Kleinian
  groups

abstract:
  Consider a general circle packing $\mathcal{P}$ in the complex plane
$\mathbb{C}$ invariant under a Kleinian group $\Gamma$. When $\Gamma$ is
convex-cocompact or its critical exponent is greater than 1, we obtain an
effective equidistribution for small circles in $\mathcal{P}$ intersecting any
bounded connected regular set in $\mathbb{C}$; this provides an effective
version of an earlier work of Oh-Shah. In view of the recent result of
McMullen-Mohammadi-Oh, our effective circle counting theorem applies to the
circles contained in the limit set of a convex-cocompact but non-cocompact
Kleinian group whose limit set contains at least one circle. Moreover consider
the circle packing $\mathcal{P}(\mathcal{T})$ of the ideal triangle attained by
filling in largest inner circles. We give an effective estimate to the number
of disks whose hyperbolic areas are greater than $t$, as $t\to 0$,
effectivising the work of Oh.


title:
Study of the atmospheric conditions at Cerro Armazones using
  astronomical data

abstract:
  Aims: We studied the precipitable water vapour (PWV) content near Cerro
Armazones and discuss the potential use of our technique of modelling the
telluric absorbtion lines for the investigation of other molecular layers. The
site is designated for the European Extremely Large Telescope (E-ELT) and the
nearby planned site for the Cherenkov Telescope Array (CTA). Methods:
Spectroscopic data from the Bochum Echelle Spectroscopic Observer (BESO)
instrument were investigated by using line-by-line radiative transfer model
(LBLRTM) radiative transfer models for the Earths atmosphere with the telluric
absorption correction tool molecfit. All observations from the archive in the
period from December 2008 to the end of 2014 were investigated. The dataset
completely covers the El Nino event registered in the period 2009-2010. Models
of the 3D Global Data Assimilation System (GDAS) were used for further
comparison. Moreover, for those days with coincidence of data from a similar
study with VLT/X-shooter and microwave radiometer LHATPRO data at Cerro
Paranal, a direct comparison is presented. Results: This analysis shows that
the site has systematically lower PWV values, even after accounting for the
decrease in PWV expected from the higher altitude of the site with respect to
Cerro Paranal, using the average atmosphere found with radiosondes. We found
that GDAS data are not a suitable method for predicting of local atmospheric
conditions - they usually systematically overestimate the PWV values. Due to
the large sample, we were furthermore able to characterize the site with
respect to symmetry across the sky and variation with the years and within the
seasons. This kind of technique of studying the atmospheric conditions is shown
to be a promising step into a possible monitoring equipment for CTA.


title:
Charge-noise-insensitive gate operations for always-on, exchange-only
  qubits

abstract:
  We introduce an always-on, exchange-only qubit made up of three localized
semiconductor spins that offers a true "sweet spot" to fluctuations of the
quantum dot energy levels. Both single- and two-qubit gate operations can be
performed using only exchange pulses while maintaining this sweet spot. We show
how to interconvert this qubit to other three-spin encoded qubits as a new
resource for quantum computation and communication.


title: BSDEs with nonlinear weak terminal condition

abstract:
  In a recent paper, Bouchard, Elie and Reveillac \cite{BER} have studied a new
class of Backward Stochastic Differential Equations with weak terminal
condition, for which the $T$-terminal value $Y_T$ of the solution $(Y,Z)$ is
not fixed as a random variable, but only satisfies a constraint of the form
$E[\Psi(Y_T)] \geq m.$ The aim of this paper is to introduce a more general
class of BSDEs with {\em nonlinear weak terminal condition}. More precisely,
the constraint takes the form $\mathcal{E}^f_{0,T}[\Psi(Y_T)] \geq m,$ where
$\mathcal{E}^f$ represents the $f$-conditional expectation associated to a {\em
nonlinear driver} $f$.
  We carry out a similar analysis as in \cite{BER} of the value function
corresponding to the minimal solution $Y$ of the BSDE with nonlinear weak
terminal condition: we study the regularity, establish the main properties, in
particular continuity and convexity with respect to the parameter $m$, and
finally provide a dual representation and the existence of an optimal control
in the case of concave constraints. From a financial point of view, our study
is closely related to the approximative hedging of an European option under
dynamic risk measures constraints. The nonlinearity $f$ raises subtle
difficulties, highlighted throughout the paper, which cannot be handled by the
arguments used in the case of classical expectations constraints studied in
\cite{BER}.


title:
The Rossiter-McLaughlin effect reloaded: Probing the 3D spin-orbit
  geometry, differential stellar rotation, and the spatially-resolved stellar
  spectrum of star-planet systems

abstract:
  When a planet transits its host star, it blocks regions of the stellar
surface from view; this causes a distortion of the spectral lines and a change
in the line-of-sight (LOS) velocities, known as the Rossiter-McLaughlin (RM)
effect. Since the LOS velocities depend, in part, on the stellar rotation, the
RM waveform is sensitive to the star-planet alignment (which provides
information on the system's dynamical history). We present a new RM modelling
technique that directly measures the spatially-resolved stellar spectrum behind
the planet. This is done by scaling the continuum flux of the (HARPS) spectra
by the transit light curve, and then subtracting the in- from the
out-of-transit spectra to isolate the starlight behind the planet. This
technique does not assume any shape for the intrinsic local profiles. In it, we
also allow for differential stellar rotation and centre-to-limb variations in
the convective blueshift. We apply this technique to HD189733 and compare to 3D
magnetohydrodynamic (MHD) simulations. We reject rigid body rotation with high
confidence (> 99% probability), which allows us to determine the occulted
stellar latitudes and measure the stellar inclination. In turn, we determine
both the sky-projected (lambda ~ -0.4 +/- 0.2 degrees) and true 3D obliquity
(psi ~ 7^+12_-4 degrees). We also find good agreement with the MHD simulations,
with no significant centre-to-limb variations detectable in the local profiles.
Hence, this technique provides a new powerful tool that can probe stellar
photospheres, differential rotation, determine 3D obliquities, and remove
sky-projection biases in planet migration theories. This technique can be
implemented with existing instrumentation, but will become even more powerful
with the next generation of high-precision radial velocity spectrographs.


title:
Advances and Outlooks of Heat Transfer Enhancement by Longitudinal
  Vortex Generators

abstract:
  In the last several decades, heat transfer enhancements using extended
surface (fins) has received considerable attentions. A new heat transfer
enhancement technique, longitudinal vortex generators (LVG), has received
significant attention since the 1990s. It is activated by a special type of
extended surface that can generate vortices with axes parallel to the main flow
direction. The vortices result from strong swirling secondary flow caused by
flow separation and friction. The state-of-the-art on research and applications
of LVG are described here. The topical coverage includes heat transfer
enhancement in straight channels and in heat exchangers. Among the latter are
plate and wavy fin-and-tube heat exchangers, fin-and-oval-tube heat exchangers,
and fin-and-tube heat exchangers with multiple rows of tubes. The trends and
future directions of heat transfer enhancement by means of LVG are discussed.


title: Threshold expansion of the three-particle quantization condition

abstract:
  We recently derived a quantization condition for the energy of three
relativistic particles in a cubic box. Here we use this condition to study the
energy level closest to the three-particle threshold when the total
three-momentum vanishes. We expand this energy in powers of $1/L$, where $L$ is
the linear extent of the finite volume. The expansion begins at ${\cal
O}(1/L^3)$, and we determine the coefficients of the terms through ${\cal
O}(1/L^6)$. As is also the case for the two-particle threshold energy, the
$1/L^3$, $1/L^4$ and $1/L^5$ coefficients depend only on the two-particle
scattering length $a$. These can be compared to previous results obtained using
nonrelativistic quantum mechanics and we find complete agreement. The $1/L^6$
coefficients depend additionally on the two-particle effective range $r$ (just
as in the two-particle case) and on a suitably defined threshold three-particle
scattering amplitude (a new feature for three particles). A second new feature
in the three-particle case is that logarithmic dependence on $L$ appears at
$\mathcal O(1/L^6)$. Relativistic effects enter at this order, and the only
comparison possible with the nonrelativistic result is for the coefficient of
the logarithm, where we again find agreement. For a more thorough check of the
$1/L^6$ result, and thus of the quantization condition, we also compare to a
perturbative calculation of the threshold energy in relativistic $\lambda
\phi^4$ theory, which we have recently presented. Here all terms can be
compared and we find full agreement.


title: Interlayer excitons with tunable dispersion relation

abstract:
  Interlayer excitons, comprising an electron in one material bound by Coulomb
attraction to a hole in an adjacent material, are composite bosons that can
assume a variety of many-body phases. The phase diagram of the bosonic system
is largely determined by the dispersion relation of the bosons, which itself
arises as a combination of the dispersion relations of the electron and hole
separately. Here I show that in situations where either the electron or the
hole has a non-monotonic, "Mexican hat-shaped" dispersion relation, the exciton
dispersion relation can have a range of qualitatively different forms, each
corresponding to a different many-body phase at low temperature. This diversity
suggests a novel platform for continuously tuning between different quantum
phases using an external field.


title:
First-Principles Molecular Dynamics Investigation of the Atomic-Scale
  Energy Transport: From Heat Conduction to Thermal Radiation

abstract:
  First-principles molecular dynamics simulation based on a plane
wave/pseudopotential implementation of density functional theory is adopted to
investigate atomic scale energy transport for semiconductors (silicon and
germanium). By imposing thermostats to keep constant temperatures of the
nanoscale thin layers, initial thermal non-equilibrium between the neighboring
layers is established under the vacuum condition. Models with variable gap
distances with an interval of lattice constant increment of the simulated
materials are set up and statistical comparisons of temperature evolution
curves are made. Moreover, the equilibration time from non-equilibrium state to
thermal equilibrium state of different silicon or/and germanium layers
combinations are calculated. The results show significant distinctions of heat
transfer under different materials and temperatures combinations. Further
discussions on the equilibrium time are made to explain the simulation results.
As the first work of the atomic scale energy transport spanning from heat
conduction to thermal radiation, the simulation results here highlights the
promising application of the first-principles molecular dynamics in thermal
engineering.


title: On semigroup rings with decreasing Hilbert function

abstract:
  In this paper we study the Hilbert function HR of one-dimensional semigroup
rings R = k[[S]]. For some classes of semigroups, by means of the notion of
support of the elements in S, we give conditions on the generators of S in
order to have decreasing HR. When the embedding dimension v and the
multiplicity e verify v + 3 ? e ? v + 4, the decrease of HR gives explicit
description of the Apery set of S. In particular for e = v+3, we classify the
semigroups with e = 13 and HR decreasing, further we show that HR is
non-decreasing if e < 12. Finally we deduce that HR is non-decreasing for every
Gorenstein semigroup ring with e ? v + 4.


title: Novel Views of Objects from a Single Image

abstract:
  Taking an image of an object is at its core a lossy process. The rich
information about the three-dimensional structure of the world is flattened to
an image plane and decisions such as viewpoint and camera parameters are final
and not easily revertible. As a consequence, possibilities of changing
viewpoint are limited. Given a single image depicting an object, novel-view
synthesis is the task of generating new images that render the object from a
different viewpoint than the one given. The main difficulty is to synthesize
the parts that are disoccluded; disocclusion occurs when parts of an object are
hidden by the object itself under a specific viewpoint. In this work, we show
how to improve novel-view synthesis by making use of the correlations observed
in 3D models and applying them to new image instances. We propose a technique
to use the structural information extracted from a 3D model that matches the
image object in terms of viewpoint and shape. For the latter part, we propose
an efficient 2D-to-3D alignment method that associates precisely the image
appearance with the 3D model geometry with minimal user interaction. Our
technique is able to simulate plausible viewpoint changes for a variety of
object classes within seconds. Additionally, we show that our synthesized
images can be used as additional training data that improves the performance of
standard object detectors.


title: Lempel-Ziv Decoding in External Memory

abstract:
  Simple and fast decoding is one of the main advantages of LZ77-type text
encoding used in many popular file compressors such as gzip and 7zip. With the
recent introduction of external memory algorithms for Lempel-Ziv factorization
there is a need for external memory LZ77 decoding but the standard algorithm
makes random accesses to the text and cannot be trivially modified for external
memory computation. We describe the first external memory algorithms for LZ77
decoding, prove that their I/O complexity is optimal, and demonstrate that they
are very fast in practice, only about three times slower than in-memory
decoding (when reading input and writing output is included in the time).


title:
Structural, Dynamic, and Vibrational Properties during Heat Transfer in
  Si/Ge Superlattices: A Car-Parrinello Molecular Dynamics Study

abstract:
  The structural, dynamic, and vibrational properties during the heat transfer
process in Si/Ge superlattices, are studied by analyzing the trajectories
generated by the ab initio Car-Parrinello molecular dynamics simulation. The
radial distribution functions and mean square displacements are calculated and
further discussions are made to explain and probe the structural changes
relating to the heat transfer phenomenon. Furthermore, the vibrational density
of states of the two layers (Si/Ge) are computed and plotted to analyze the
contributions of phonons with different frequencies to the heat conduction.
Coherent heat conduction of the low frequency phonons is found and their
contributions to facilitate heat transfer are confirmed. The Car-Parrinello
molecular dynamics simulation outputs in the work show reasonable
thermophysical results of the thermal energy transport process and shed light
on the potential applications of treating the heat transfer in the
superlattices of semiconductor materials from a quantum mechanical molecular
dynamics simulation perspective.


title:
Synthetic Frequency Protocol in the Ramsey Spectroscopy of Clock
  Transitions

abstract:
  We develop an universal method to significantly suppress probe-induced shifts
in any types of atomic clocks using the Ramsey spectroscopy. Our approach is
based on adaptation of the synthetic frequency concept [V. I. Yudin, et al.,
Phys. Rev. Lett. 107, 030801 (2011)] (previously developed for BBR shift
suppression) to the Ramsey spectroscopy with the use of interrogations for
different dark time intervals. Universality of the method consists in
arbitrariness of the possible Ramsey schemes. However, most extremal results
are obtained in combination with so-called hyper-Ramsey spectroscopy [V. I.
Yudin, et al., Phys. Rev. A 82, 011804(R) (2010)]. In the latter case, the
probe-induced frequency shifts can be suppressed considerably below a
fractional level of 10$^{-18}$ practically for any optical atomic clocks, where
this shift previously was metrologically significant. The main advantage of our
method in comparison with other radical hyper-Ramsey approaches [R. Hobson, et
al., Phys. Rev. A 93, 010501(R) (2016); T. Zanon-Willette, et al., Phys. Rev. A
93, 042506 (2016)] consist in much greater efficiency and resistibility in the
presence of decoherentization.


title:
Femtosecond Laser Processing of Germanium: An Ab Initio Molecular
  Dynamics Study

abstract:
  An ab initio molecular dynamics study of femtosecond laser processing of
germanium is presented in this paper. The method based on the finite
temperature density functional theory is adopted to probe the structural
change, thermal motion of the atoms, dynamic property of the velocity
autocorrelation, and the vibrational density of states. Starting from a cubic
system at room temperature (300 K) containing 64 germanium atoms with an
ordered arrangement of 1.132 nm in each dimension, the femtosecond laser
processing is simulated by imposing the Nose Hoover thermostat to the
electronic subsystem lasting for ~100 fs and continuing with microcanonical
ensemble simulation of ~200 fs. The simulation results show solid, liquid and
gas phases of germanium under adjusted intensities of the femtosecond laser
irradiation. We find the irradiated germanium distinguishes from the usual
germanium crystal by analyzing their melting and dynamic properties.


title:
The Geometric Mean Squared Displacement and the Stokes-Einstein Scaling
  in a Supercooled Liquid

abstract:
  It is proposed that the rate of relaxation in a liquid is better described by
the geometric mean of the van Hove distribution function, rather than the
standard arithmetic mean used to obtain the mean squared displacement. The
difference between the two means is shown to increase significantly with an
increase in the non-Gaussian character of the displacement distribution.
Preliminary results indicate that the geometric diffusion constant results in a
substantial reduction of the deviation from Stokes-Einstein scaling.


title: One-dimensional Gorenstein local rings with decreasing Hilbert function

abstract:
  In this paper we solve a problem posed by M.E. Rossi: {\it Is the Hilbert
function of a Gorenstein local ring of dimension one not decreasing? } More
precisely, for any integer $h>1$, $h \notin\{14+22k, \, 35+46k \ | \
k\in\mathbb{N} \}$, we construct infinitely many one-dimensional Gorenstein
local rings, included integral domains, reduced and non-reduced rings, whose
Hilbert function decreases at level $h$; moreover we prove that there are no
bounds to the decrease of the Hilbert function. The key tools are numerical
semigroup theory, especially some necessary conditions to obtain decreasing
Hilbert functions found by the first and the third author, and a construction
developed by V. Barucci, M. D'Anna and the second author, that gives a family
of quotients of the Rees algebra. Many examples are included.


title: Trees of multidisks as Gromov boundaries of amalgamated products

abstract:
  We describe, under some additional technical assumptions, the Gromov boundary
of the free product of several $G_i$'s amalgamated wrt. $H$, where $G_i$ are
hyperbolic groups with boundary homeomorphic to a densely punctured $n$-sphere,
and $H$ is their common subgroup corresponding to a peripheral sphere in each
of the $\partial G_i$'s.


title: Rapidly Convergent Summation Formulas involving Stirling Series

abstract:
  This paper presents a family of rapidly convergent summation formulas for
various finite sums of analytic functions. These summation formulas are
obtained by applying a series acceleration transformation involving Stirling
numbers of the first kind to the asymptotic, but divergent, expressions for the
corresponding sums coming from the Euler-Maclaurin summation formula. While it
is well-known that the expressions obtained from the Euler-Maclaurin summation
formula diverge, our summation formulas are all very rapidly convergent and
thus computationally efficient.


title: Universal volume of groups and anomaly of Vogel's symmetry

abstract:
  We show that integral representation of universal volume function of compact
simple Lie groups gives rise to six analytic functions on $CP^2$, which
transform as two triplets under group of permutations of Vogel's projective
parameters. This substitutes expected invariance under permutations of
universal parameters by more complicated covariance. We provide an analytical
continuation of these functions and particularly calculate their change under
permutations of parameters. This last relation is universal generalization, for
an arbitrary simple Lie group and an arbitrary point in Vogel's plane, of the
Kinkelin's reflection relation on Barnes' $G(1+N)$ function. Kinkelin's
relation gives asymmetry of the $G(1+N)$ function (which is essentially the
volume function for $SU(N)$ groups) under $N\leftrightarrow -N$ transformation
(which is equivalent of the permutation of parameters, for $SU(N)$ groups), and
coincides with universal relation on permutations at the $SU(N)$ line on
Vogel's plane. These results are also applicable to universal partition
function of Chern-Simons theory on three-dimensional sphere. This effect is
analogous to modular covariance, instead of invariance, of partition functions
of appropriate gauge theories under modular transformation of couplings.


title:
Coulomb drag in anisotropic systems: a theoretical study on a
  double-layer phosphorene

abstract:
  We theoretically study the Coulomb drag resistivity in a double-layer
electron system with highly anisotropic parabolic band structure using
Boltzmann transport theory. As an example, we consider a double-layer
phosphorene on which we apply our formalism. This approach, in principle, can
be tuned for other double-layered systems with paraboloidal band structures.
Our calculations show the rotation of one layer with respect to another layer
can be considered a way of controlling the drag resistivity in such systems. As
a result of rotation, the off-diagonal elements of drag resistivity tensor have
non-zero values at any temperature. In addition, we show that the anisotropic
drag resistivity is very sensitive to the direction of momentum transfer
between two layers due to highly anisotropic inter-layer electron-electron
interaction and also the plasmon modes. In particular, the drag anisotropy
ratio, \r{ho}yy/\r{ho}xx, can reach up to ~ 3 by changing the temperature.
Furthermore,our calculations suggest that including the local field correction
in dielectric function changes the results significantly. Finally, We examine
the dependence of drag resistivity and its anisotropy ratio on various
parameters like inter-layer separation, electron density, short-range
interaction and insulating substrate/spacer.


title:
Distributed Multi-Relay Selection in Accumulate-then-Forward Energy
  Harvesting Relay Networks

abstract:
  This paper investigates a wireless-powered cooperative network (WPCN)
consisting of one source-destination pair and multiple decode-and-forward (DF)
relays. We develop an energy threshold based multi-relay selection (ETMRS)
scheme for the considered WPCN. The proposed ETMRS scheme can be implemented in
a fully distributed manner as the relays only need local information to switch
between energy harvesting and information forwarding modes. By modeling the
charging/discharging behaviours of the finite-capacity battery at each relay as
a finite-state Markov Chain (MC), we derive an analytical expression for the
system outage probability of the proposed ETMRS scheme over mixed Nakagami-$m$
and Rayleigh fading channels. Based on the derived expression, the optimal
energy thresholds for all the relays corresponding to the minimum system outage
probability can be obtained via an exhaustive search. However, this approach
becomes computationally prohibitive when the number of relays and the
associated number of battery energy levels is large. To resolve this issue, we
propose a heuristic approach to optimize the energy threshold for each relay.
To gain some useful insights for practical relay design, we also derive the
upper bound for system outage probability corresponding to the case that all
relays are equipped with infinite-capacity batteries. Numerical results
validate our theoretical analysis. It is shown that the proposed heuristic
approach can achieve a near-optimal system performance and our ETMRS scheme
outperforms the existing single-relay selection scheme and common energy
threshold scheme.


title:
Springer correspondence for exceptional Lie algebras and their duals in
  small characteristic

abstract:
  We describe the Springer correspondence explicitly for exceptional Lie
algebras of type $G_2$ and $F_4$ and their duals in bad characteristics, i.e.
in characteristics 2 and 3.


title:
Reduced drift-kinetics with thermal velocity distribution across
  magnetic field

abstract:
  The goal of this study is to develop an approximate self-consistent
description of particle motion in strongly magnetised solar corona. We derive a
set of reduced drift-kinetic equations based on the assumption that the
gyro-velocity distribution is Maxwellian. The equations are tested using simple
1D models.


title:
Inferring Interaction Rules From Observations of Evolutive Systems I:
  The Variational Approach

abstract:
  In this paper we are concerned with the learnability of nonlocal interaction
kernels for first order systems modeling certain social interactions, from
observations of realizations of their dynamics. This paper is the first of a
series on learnability of nonlocal interaction kernels and presents a
variational approach to the problem. In particular, we assume here that the
kernel to be learned is bounded and locally Lipschitz continuous and that the
initial conditions of the systems are drawn identically and independently at
random according to a given initial probability distribution. Then the
minimization over a rather arbitrary sequence of (finite dimensional) subspaces
of a least square functional measuring the discrepancy from observed
trajectories produces uniform approximations to the kernel on compact sets. The
convergence result is obtained by combining mean-field limits, transport
methods, and a $\Gamma$-convergence argument. A crucial condition for the
learnability is a certain coercivity property of the least square functional,
majoring an $L_2$-norm discrepancy to the kernel with respect to a probability
measure, depending on the given initial probability distribution by suitable
push forwards and transport maps. We illustrate the convergence result by means
of several numerical experiments.


title: Weakly mixing sets and polynomial equations

abstract:
  We investigate polynomial patterns which can be guaranteed to appear in
\emph{weakly mixing} sets introduced by introduced by Furstenberg and studied
by Fish. In particular, we prove that if $A \subset \mathbb N$ is a weakly
mixing set and $p(x) \in \mathbb Z[x]$ a polynomial of odd degree with positive
leading coefficient, then all sufficiently large integers $N$ can be
represented as $N = n_1 + n_2$, where $p(n_1) + m,\ p(n_2) + m \in A$ for some
$m \in A$.


title: Sparse solutions of linear Diophantine equations

abstract:
  We present structural results on solutions to the Diophantine system
$A{\boldsymbol y} = {\boldsymbol b}$, ${\boldsymbol y} \in \mathbb Z^t_{\ge 0}$
with the smallest number of non-zero entries. Our tools are algebraic and
number theoretic in nature and include Siegel's Lemma, generating functions,
and commutative algebra. These results have some interesting consequences in
discrete optimization.


title:
Hadoop on HPC: Integrating Hadoop and Pilot-based Dynamic Resource
  Management

abstract:
  High-performance computing platforms such as supercomputers have
traditionally been designed to meet the compute demands of scientific
applications. Consequently, they have been architected as producers and not
consumers of data. The Apache Hadoop ecosystem has evolved to meet the
requirements of data processing applications and has addressed many of the
limitations of HPC platforms. There exist a class of scientific applications
however, that need the collective capabilities of traditional high-performance
computing environments and the Apache Hadoop ecosystem. For example, the
scientific domains of bio-molecular dynamics, genomics and network science need
to couple traditional computing with Hadoop/Spark based analysis. We
investigate the critical question of how to present the capabilities of both
computing environments to such scientific applications. Whereas this questions
needs answers at multiple levels, we focus on the design of resource management
middleware that might support the needs of both. We propose extensions to the
Pilot-Abstraction to provide a unifying resource management layer. This is an
important step that allows applications to integrate HPC stages (e.g.
simulations) to data analytics. Many supercomputing centers have started to
officially support Hadoop environments, either in a dedicated environment or in
hybrid deployments using tools such as myHadoop. This typically involves many
intrinsic, environment-specific details that need to be mastered, and often
swamp conceptual issues like: How best to couple HPC and Hadoop application
stages? How to explore runtime trade-offs (data localities vs. data movement)?
This paper provides both conceptual understanding and practical solutions to
the integrated use of HPC and Hadoop environments.


title:
Efficient moment calculations for variance components in large
  unbalanced crossed random effects models

abstract:
  Large crossed data sets, described by generalized linear mixed models, have
become increasingly common and provide challenges for statistical analysis. At
very large sizes it becomes desirable to have the computational costs of
estimation, inference and prediction (both space and time) grow at most
linearly with sample size. Both traditional maximum likelihood estimation and
numerous Markov chain Monte Carlo Bayesian algorithms take superlinear time in
order to obtain good parameter estimates. We propose moment based algorithms
that, with at most linear cost, estimate variance components, measure the
uncertainties of those estimates, and generate shrinkage based predictions for
missing observations. When run on simulated normally distributed data, our
algorithm performs competitively with maximum likelihood methods.


title: The asymptotic behavior of the correspondence chromatic number

abstract:
  Alon proved that for any graph $G$, $\chi_\ell(G) = \Omega(\ln d)$, where
$\chi_\ell(G)$ is the list chromatic number of $G$ and $d$ is the average
degree of $G$. Dvo\v{r}\'{a}k and Postle recently introduced a generalization
of list coloring, which they called correspondence coloring. We establish an
analogue of Alon's result for correspondence coloring; namely, we show that
$\chi_c(G) = \Omega(d/\ln d)$, where $\chi_c(G)$ denotes the correspondence
chromatic number of $G$. We also prove that for triangle-free $G$, $\chi_c(G) =
O(\Delta/\ln \Delta)$, where $\Delta$ is the maximum degree of $G$ (this is a
generalization of Johansson's result about list colorings). This implies that
the correspondence chromatic number of a regular triangle-free graph is, up to
a constant factor, determined by its degree.


title:
Fuel treatment planning: fragmenting high fuel load areas while
  maintaining availability and connectivity of faunal habitat

abstract:
  Reducing the fuel load in fire-prone landscapes is aimed at mitigating the
risk of catastrophic wildfires but there are ecological consequences.
Maintaining habitat for fauna of both sufficient extent and connectivity while
fragmenting areas of high fuel loads presents land managers with seemingly
contrasting objectives. Faced with this dichotomy, we propose a Mixed Integer
Programming (MIP) model that can optimally schedule fuel treatments to reduce
fuel hazards by fragmenting high fuel load regions while considering critical
ecological requirements over time and space. The model takes into account both
the frequency of fire that vegetation can tolerate and the frequency of fire
necessary for fire-dependent species. Our approach also ensures that suitable
alternate habitat is available and accessible to fauna affected by a treated
area. More importantly, to conserve fauna the model sets a minimum acceptable
target for the connectivity of habitat at any time . These factors are all
included in the formulation of a model that yields a multi-period
spatially-explicit schedule for treatment planning. Our approach is then
demonstrated in a series of computational experiments with hypothetical
landscapes, a single vegetation type and a group of faunal species with the
same habitat requirements. Our experiments show that it is possible to reduce
the risk of wildfires while ensuring sufficient connectivity of habitat over
both space and time. Furthermore, it is demonstrated that the habitat
connectivity constraint is more effective than neighbourhood habitat
constraints. This is critical for the conservation of fauna and of special
concern for vulnerable or endangered species.


title: Interval Linear Algebra and Computational Complexity

abstract:
  This work connects two mathematical fields - computational complexity and
interval linear algebra. It introduces the basic topics of interval linear
algebra - regularity and singularity, full column rank, solving a linear
system, deciding solvability of a linear system, computing inverse matrix,
eigenvalues, checking positive (semi)definiteness or stability. We discuss
these problems and relations between them from the view of computational
complexity. Many problems in interval linear algebra are intractable, hence we
emphasize subclasses of these problems that are easily solvable or decidable.
The aim of this work is to provide a basic insight into this field and to
provide materials for further reading and research.


title: Universal formula for Hilbert series of minimal nilpotent orbits

abstract:
  We show that the Hilbert series of the projective variety $X=P(O_{min}),$
corresponding to the minimal nilpotent orbit $\mathcal O_{min},$ is universal
in the sense of Vogel: it is written uniformly for all simple Lie algebras in
terms of Vogel's parameters $\alpha,\beta,\gamma$ and represents a special case
of the generalized hypergeometric function ${}_{4}F_{3}.$ A universal formula
for the degree of $X$ is then deduced.


title: Adaptive Subgradient Methods for Online AUC Maximization

abstract:
  Learning for maximizing AUC performance is an important research problem in
Machine Learning and Artificial Intelligence. Unlike traditional batch learning
methods for maximizing AUC which often suffer from poor scalability, recent
years have witnessed some emerging studies that attempt to maximize AUC by
single-pass online learning approaches. Despite their encouraging results
reported, the existing online AUC maximization algorithms often adopt simple
online gradient descent approaches that fail to exploit the geometrical
knowledge of the data observed during the online learning process, and thus
could suffer from relatively larger regret. To address the above limitation, in
this work, we explore a novel algorithm of Adaptive Online AUC Maximization
(AdaOAM) which employs an adaptive gradient method that exploits the knowledge
of historical gradients to perform more informative online learning. The new
adaptive updating strategy of the AdaOAM is less sensitive to the parameter
settings and maintains the same time complexity as previous non-adaptive
counterparts. Additionally, we extend the algorithm to handle high-dimensional
sparse data (SAdaOAM) and address sparsity in the solution by performing lazy
gradient updating. We analyze the theoretical bounds and evaluate their
empirical performance on various types of data sets. The encouraging empirical
results obtained clearly highlighted the effectiveness and efficiency of the
proposed algorithms.


title: C-system of a module over a $Jf$-relative monad

abstract:
  Let $F$ be the category with the set of objects $\bf N$ and morphisms being
the functions between the standard finite sets of the corresponding
cardinalities. Let $Jf:F\rightarrow Sets$ be the obvious functor from this
category to the category of sets. In this paper we construct, for any relative
monad $\bf RR$ on $Jf$ and a left module $\bf LM$ over $\bf RR$, a C-system
$C({\bf RR},{\bf LM})$ and explicitly compute the action of the B-system
operations on its B-sets.
  In the following paper it is used to provide a rigorous mathematical approach
to the construction of the C-systems underlying the term models of a wide class
of dependent type theories.
  This paper is a result of evolution of arXiv:1407.3394. However this paper is
much more detailed and contains a lot of material that is not contained in
arXiv:1407.3394. It also does not cover some material that is covered in
arXiv:1407.3394.


title: Algebras with a negation map

abstract:
  Our objective in this project is three-fold, the first two covered in this
paper. In tropical mathematics, as well as other mathematical theories
involving semirings, when trying to formulate the tropical versions of
classical algebraic concepts for which the negative is a crucial ingredient,
such as determinants, Grassmann algebras, Lie algebras, Lie superalgebras, and
Poisson algebras, one often is challenged by the lack of negation. Following an
idea originating in work of Gaubert and the Max-Plus group and brought to
fruition by Akian, Gaubert, and Guterman, we study algebraic structures with
negation maps, called \textbf{systems}, in the context of universal algebra,
showing how these unify the more viable (super)tropical versions, as well as
hypergroup theory and fuzzy rings, thereby "explaining" similarities in their
theories. Special attention is paid to \textbf{meta-tangible} $\mathcal
T$-systems, whose algebraic theory includes all the main tropical examples and
many others, but is rich enough to facilitate computations and provide a host
of structural results.
  Basic results also are obtained in linear algebra, linking determinants to
linear independence.
  Formulating the structure categorically enables us to view the
tropicalization functor as a morphism, thereby further explaining the
mysterious link between classical algebraic results and their tropical analogs,
as well as with hyperfields. We utilize the tropicalization functor to propose
tropical analogs of classical algebraic notions.
  The systems studied here might be called "fundamental," since they are the
underlying structure which can be studied via other "module" systems, which is
to be the third stage of this project, involving a theory of sheaves and
schemes and derived categories with a negation map.


title: Active Learning Algorithms for Graphical Model Selection

abstract:
  The problem of learning the structure of a high dimensional graphical model
from data has received considerable attention in recent years. In many
applications such as sensor networks and proteomics it is often expensive to
obtain samples from all the variables involved simultaneously. For instance,
this might involve the synchronization of a large number of sensors or the
tagging of a large number of proteins. To address this important issue, we
initiate the study of a novel graphical model selection problem, where the goal
is to optimize the total number of scalar samples obtained by allowing the
collection of samples from only subsets of the variables. We propose a general
paradigm for graphical model selection where feedback is used to guide the
sampling to high degree vertices, while obtaining only few samples from the
ones with the low degrees. We instantiate this framework with two specific
active learning algorithms, one of which makes mild assumptions but is
computationally expensive, while the other is more computationally efficient
but requires stronger (nevertheless standard) assumptions. Whereas the sample
complexity of passive algorithms is typically a function of the maximum degree
of the graph, we show that the sample complexity of our algorithms is provable
smaller and that it depends on a novel local complexity measure that is akin to
the average degree of the graph. We finally demonstrate the efficacy of our
framework via simulations.

categories: stat.ML cs.IT cs.LG math.IT math.ST stat.TH


title: A Spectral Series Approach to High-Dimensional Nonparametric Regression

abstract:
  A key question in modern statistics is how to make fast and reliable
inferences for complex, high-dimensional data. While there has been much
interest in sparse techniques, current methods do not generalize well to data
with nonlinear structure. In this work, we present an orthogonal series
estimator for predictors that are complex aggregate objects, such as natural
images, galaxy spectra, trajectories, and movies. Our series approach ties
together ideas from kernel machine learning, and Fourier methods. We expand the
unknown regression on the data in terms of the eigenfunctions of a kernel-based
operator, and we take advantage of orthogonality of the basis with respect to
the underlying data distribution, P, to speed up computations and tuning of
parameters. If the kernel is appropriately chosen, then the eigenfunctions
adapt to the intrinsic geometry and dimension of the data. We provide
theoretical guarantees for a radial kernel with varying bandwidth, and we
relate smoothness of the regression function with respect to P to sparsity in
the eigenbasis. Finally, using simulated and real-world data, we systematically
compare the performance of the spectral series approach with classical kernel
smoothing, k-nearest neighbors regression, kernel ridge regression, and
state-of-the-art manifold and local regression methods.


title: Some results on an algebro-geometric condition on graphs

abstract:
  Paolo Aluffi, inspired by an algebro-geometric problem, asked when the
Kirchhoff polynomial of a graph is in the Jacobian ideal of the Kirchhoff
polynomial of the same graph with one edge deleted.
  We give some results on which graph-edge pairs have this property. In
particular we show that multiple edges can be reduced to double edges, we
characterize which edges of wheel graphs satisfy the property, we consider a
stronger condition which guarantees the property for any parallel join, and we
find a class of series-parallel graphs with the property.


title: DeepCare: A Deep Dynamic Memory Model for Predictive Medicine

abstract:
  Personalized predictive medicine necessitates the modeling of patient illness
and care processes, which inherently have long-term temporal dependencies.
Healthcare observations, recorded in electronic medical records, are episodic
and irregular in time. We introduce DeepCare, an end-to-end deep dynamic neural
network that reads medical records, stores previous illness history, infers
current illness states and predicts future medical outcomes. At the data level,
DeepCare represents care episodes as vectors in space, models patient health
state trajectories through explicit memory of historical records. Built on Long
Short-Term Memory (LSTM), DeepCare introduces time parameterizations to handle
irregular timed events by moderating the forgetting and consolidation of memory
cells. DeepCare also incorporates medical interventions that change the course
of illness and shape future medical risk. Moving up to the health state level,
historical and present health states are then aggregated through multiscale
temporal pooling, before passing through a neural network that estimates future
outcomes. We demonstrate the efficacy of DeepCare for disease progression
modeling, intervention recommendation, and future risk prediction. On two
important cohorts with heavy social and economic burden -- diabetes and mental
health -- the results show improved modeling and risk prediction accuracy.


title: Trading Strategy with Stochastic Volatility in a Limit Order Book Market

abstract:
  In this paper, we employ the Heston stochastic volatility model to describe
the stock's volatility and apply the model to derive and analyze the optimal
trading strategies for dealers in a security market. We also extend our study
to option market making for options written on stocks in the presence of
stochastic volatility. Mathematically, the problem is formulated as a
stochastic optimal control problem and the controlled state process is the
dealer's mark-to-market wealth. Dealers in the security market can optimally
determine their ask and bid quotes on the underlying stocks or options
continuously over time. Their objective is to maximize an expected profit from
transactions with a penalty proportional to the variance of cumulative
inventory cost.


title: Confidence intervals for means under constrained dependence

abstract:
  We develop a general framework for conducting inference on the mean of
dependent random variables given constraints on their dependency graph. We
establish the consistency of an oracle variance estimator of the mean when the
dependency graph is known, along with an associated central limit theorem. We
derive an integer linear program for finding an upper bound for the estimated
variance when the graph is unknown, but topological and degree-based
constraints are available. We develop alternative bounds, including a
closed-form bound, under an additional homoskedasticity assumption. We
establish a basis for Wald-type confidence intervals for the mean that are
guaranteed to have asymptotically conservative coverage. We apply the approach
to inference from a social network link-tracing study and provide statistical
software implementing the approach.


title: Semi-supervised K-means++

abstract:
  Traditionally, practitioners initialize the {\tt k-means} algorithm with
centers chosen uniformly at random. Randomized initialization with uneven
weights ({\tt k-means++}) has recently been used to improve the performance
over this strategy in cost and run-time. We consider the k-means problem with
semi-supervised information, where some of the data are pre-labeled, and we
seek to label the rest according to the minimum cost solution. By extending the
{\tt k-means++} algorithm and analysis to account for the labels, we derive an
improved theoretical bound on expected cost and observe improved performance in
simulated and real data examples. This analysis provides theoretical
justification for a roughly linear semi-supervised clustering algorithm.


title:
Phase constants in the Fock-Goncharov quantization of cluster varieties:
  long version

abstract:
  A cluster variety of Fock and Goncharov is a scheme constructed from the data
related to the cluster algebras of Fomin and Zelevinsky. A seed is a
combinatorial data which can be encoded as an $n\times n$ matrix with integer
entries, or as a quiver in special cases, together with $n$ formal variables. A
mutation is a certain rule for transforming a seed into another seed; the new
variables are related to the previous variables by some rational expressions.
To each seed one attaches an $n$-dimensional torus, and by gluing the tori
along the birational maps defined by the mutation formulas, one constructs a
cluster variety. Quantization of a cluster variety assigns to each seed a
non-commutative ring which deforms the classical ring of functions on the torus
attached to the seed, as well as to each mutation an isomorphism of skew fields
of fractions of these non-commutative rings. A representation realizes the
non-commutative rings as algebras of operators on Hilbert spaces, and the
quantum mutation isomorphisms as unitary maps between the Hilbert spaces that
intertwine the operators for the rings. These unitary intertwiners are one of
the major results of the Fock-Goncharov quantization of cluster varieties, and
are given by the special function called the quantum dilogarithm. The classical
mutations satisfy certain algebraic relations, which were known to be satisfied
also by the corresponding intertwiners up to complex constants of modulus $1$.
The present paper shows by computation that these constants are all $1$. One
implication is that the mapping class group representations resulting from the
application of the Fock-Goncharov quantization to the quantum Teichm\"uller
theory are genuine, not projective.


title: Equisingularity and EIDS

abstract:
  The study of Essentially Isolated Determinantal Singularites or EIDS was
initiated by Ebeling and Gusein-Zade. They are non-smoothable as determinantal
singularities, and in general have non-isolated singularities. Their
singularities are generic in a deleted neighborhood of the origin, hence their
description as "essentially isolated". In this paper we study these
singularities from the "landscape" point of view introduced in MathArxiv
1501.00201. Using this point of view we show a connection between invariants
coming from the topology of the stabilization and invariants coming from the
infinitesimal geometry of the singularity. This gives us a criterion for the
Whitney equisingularity of EIDS families.


title:
INSQ: An Influential Neighbor Set Based Moving kNN Query Processing
  System

abstract:
  We revisit the moving k nearest neighbor (MkNN) query, which computes one's k
nearest neighbor set and maintains it while at move. Existing MkNN algorithms
are mostly safe region based, which lack efficiency due to either computing
small safe regions with a high recomputation frequency or computing larger safe
regions but with a high cost for each computation. In this demonstration, we
showcase a system named INSQ that adopts a novel algorithm called the
Influential Neighbor Set (INS) algorithm to process the MkNN query in both
two-dimensional Euclidean space and road networks. This algorithm uses a small
set of safe guarding objects instead of safe regions. As long as the the
current k nearest neighbors are closer to the query object than the safe
guarding objects are, the current k nearest neighbors stay valid and no
recomputation is required. Meanwhile, the region defined by the safe guarding
objects is the largest possible safe region. This means that the recomputation
frequency is also minimized and hence, the INS algorithm achieves high overall
query processing efficiency.


title:
Solar neutrino interactions with liquid scintillators used for double
  beta decay experiments

abstract:
  Solar neutrinos interact with double beta decay detectors (DBD) and hence
will contribute to backgrounds (BG) for DBD experiments. Background
contributions due to solar neutrinos are evaluated for their interactions with
atomic electrons and nuclei in liquid scintillation detectors used for DBD
experiments. They are shown to be serious backgrounds for high sensitivity DBD
experiments to search for the Majorana neutrino masses in the inverted and
normal hierarchy regions.


title: Operational extreme points of unital completely positive maps

abstract:
  Two notions for linear maps (operational convex combinations and operational
exetreme points) are introduced. The set S of ucp maps on the n times n matrix
algebra is the operational convex combinations of the identity map. An
operational extreme point of S is an extreme point of S but the converse does
not hold, and every automorphism is an operational extreme point of S.


title:
Multi-Channel MAC Protocol for Full-Duplex Cognitive Radio Networks with
  Optimized Access Control and Load Balancing

abstract:
  In this paper, we propose a multi-channel full-duplex Medium Access Control
(MAC) protocol for cognitive radio networks (MFDC-MAC). Our design exploits the
fact that full-duplex (FD) secondary users (SUs) can perform spectrum sensing
and access simultaneously, and we employ the randomized dynamic channel
selection for load balancing among channels and the standard backoff mechanism
for contention resolution on each available channel. Then, we develop a
mathematical model to analyze the throughput performance of the proposed
MFDC-MAC protocol. Furthermore, we study the protocol configuration
optimization to maximize the network throughput where we show that this
optimization can be performed in two steps, namely optimization of access and
transmission parameters on each channel and optimization of channel selection
probabilities of the users. Such optimization aims at achieving efficient
self-interference management for FD transceivers, sensing overhead control, and
load balancing among the channels. Numerical results demonstrate the impacts of
different protocol parameters and the importance of parameter optimization on
the throughput performance as well as the significant performance gain of the
proposed design compared to traditional design.

categories: cs.IT cs.DC cs.NI math.IT math.ST stat.AP stat.TH


title:
Efficient Character-level Document Classification by Combining
  Convolution and Recurrent Layers

abstract:
  Document classification tasks were primarily tackled at word level. Recent
research that works with character-level inputs shows several benefits over
word-level approaches such as natural incorporation of morphemes and better
handling of rare words. We propose a neural network architecture that utilizes
both convolution and recurrent layers to efficiently encode character inputs.
We validate the proposed model on eight large scale document classification
tasks and compare with character-level convolution-only models. It achieves
comparable performances with much less parameters.


title:
Rigidity of entire self-shrinking solutions to K\"ahler-Ricci flow on
  complex plane

abstract:
  We show that every entire self-shrinking solution on $\mathbb{C}^1$ to the
K\"ahler-Ricci flow must be generated from a quadratic potential.


title:
Rigidity of entire self-shrinking solutions to K\"ahler-Ricci flow with
  strictly real convex potential

abstract:
  We prove that every entire self-shrinking solution on $\mathbb{C}^n$ to the
K\"{a}hler-Ricci flow with strictly real convex potential must be quadratic.
The very same argument also gives a pointwise proof for the rigidity of entire
self-shrinking solutions to Lagrangian mean curvature flow in pseudo-Euclidean
space obtained by Q. Ding and Y.L. Xin. Furthermore, we show that our argument
works for a larger class of equations.


title: Visualizing Large-scale and High-dimensional Data

abstract:
  We study the problem of visualizing large-scale and high-dimensional data in
a low-dimensional (typically 2D or 3D) space. Much success has been reported
recently by techniques that first compute a similarity structure of the data
points and then project them into a low-dimensional space with the structure
preserved. These two steps suffer from considerable computational costs,
preventing the state-of-the-art methods such as the t-SNE from scaling to
large-scale and high-dimensional data (e.g., millions of data points and
hundreds of dimensions). We propose the LargeVis, a technique that first
constructs an accurately approximated K-nearest neighbor graph from the data
and then layouts the graph in the low-dimensional space. Comparing to t-SNE,
LargeVis significantly reduces the computational cost of the graph construction
step and employs a principled probabilistic model for the visualization step,
the objective of which can be effectively optimized through asynchronous
stochastic gradient descent with a linear time complexity. The whole procedure
thus easily scales to millions of high-dimensional data points. Experimental
results on real-world data sets demonstrate that the LargeVis outperforms the
state-of-the-art methods in both efficiency and effectiveness. The
hyper-parameters of LargeVis are also much more stable over different data
sets.


title: Screening fifth forces in generalized Proca theories

abstract:
  For a massive vector field with derivative self-interactions, the breaking of
the gauge invariance allows the propagation of a longitudinal mode in addition
to the two transverse modes. We consider generalized Proca theories with
second-order equations of motion in a curved space-time and study how the
longitudinal scalar mode of the vector field gravitates on a spherically
symmetric background. We show explicitly that cubic-order self-interactions
lead to the suppression of the longitudinal mode through the Vainshtein
mechanism. Provided that the dimensionless coupling of the interaction is not
negligible, this screening mechanism is sufficiently efficient to give rise to
tiny corrections to gravitational potentials consistent with solar-system tests
of gravity. We also study the quartic interactions with the presence of
non-minimal derivative coupling with the Ricci scalar and find the existence of
solutions where the longitudinal mode completely vanishes. Finally, we discuss
the case in which the effect of the quartic interactions dominates over the
cubic one and show that local gravity constraints can be satisfied under a mild
bound on the parameters of the theory.


title: Dynamic Scheduling for Charging Electric Vehicles: A Priority Rule

abstract:
  We consider the scheduling of multiple tasks with pre-determined deadlines
under random processing cost. This problem is motivated by the potential of
large scale adoption of plug-in (hybrid) electric vehicles (PHEVs) in the near
future. The charging requests of PHEVs usually have deadline constraints, and
the electricity cost associated with PHEV charging is usually random due to the
uncertainty in both system load and renewable generation. We seek to properly
schedule the battery charging of multiple PHEVs so as to minimize the overall
cost, which is derived from the total charging cost and the penalty for not
completing charging before requested deadlines. Through a dynamic programming
formulation, we establish the Less Laxity and Longer remaining Processing time
(LLLP) principle that improves any charging policy on a sample-path basis, when
the non-completion penalty is a convex function of the additional time needed
to fulfill the uncompleted request. Specifically, the LLLP principle states
that priority should be given to vehicles that have less laxity and longer
remaining processing times. Numerical results demonstrate that heuristic
policies that violate the LLLP principle, for example, the earliest deadline
first (EDF) policy, can result in significant performance loss.


title: Distribution of the transfer matrix in disordered wires

abstract:
  A closed expression is derived for the probability distribution of the
transfer matrix of a particle moving in a one-dimensional system with
delta-correlated, weak disorder. The change in the distribution as a function
of wire length is described by a diffusion equation on the $SU(1,1)$ group,
which is solved through the decomposition of the regular representation into
irreducible components. The expression generalizes a number of well-known
results, including the distributions of the transmission coefficient and local
density of states. As an application, the average single energy-level
contribution to the persistent current in a flux-threaded ring is derived.


title:
ConfidentCare: A Clinical Decision Support System for Personalized
  Breast Cancer Screening

abstract:
  Breast cancer screening policies attempt to achieve timely diagnosis by the
regular screening of apparently healthy women. Various clinical decisions are
needed to manage the screening process; those include: selecting the screening
tests for a woman to take, interpreting the test outcomes, and deciding whether
or not a woman should be referred to a diagnostic test. Such decisions are
currently guided by clinical practice guidelines (CPGs), which represent a
one-size-fits-all approach that are designed to work well on average for a
population, without guaranteeing that it will work well uniformly over that
population. Since the risks and benefits of screening are functions of each
patients features, personalized screening policies that are tailored to the
features of individuals are needed in order to ensure that the right tests are
recommended to the right woman. In order to address this issue, we present
ConfidentCare: a computer-aided clinical decision support system that learns a
personalized screening policy from the electronic health record (EHR) data.
ConfidentCare operates by recognizing clusters of similar patients, and
learning the best screening policy to adopt for each cluster. A cluster of
patients is a set of patients with similar features (e.g. age, breast density,
family history, etc.), and the screening policy is a set of guidelines on what
actions to recommend for a woman given her features and screening test scores.
ConfidentCare algorithm ensures that the policy adopted for every cluster of
patients satisfies a predefined accuracy requirement with a high level of
confidence. We show that our algorithm outperforms the current CPGs in terms of
cost-efficiency and false positive rates.


title: On the p-pseudoharmonic map heat flow

abstract:
  In this paper, we consider the heat flow for p-pseudoharmonic maps from a
closed Sasakian manifold M into a compact Riemannian manifold N. We prove
global existence and asymptotic convergence of the solution for the
p-pseudoharmonic map heat flow, provided that the sectional curvature of the
target manifold N is nonpositive. Moreover, without the curvature assumption on
the target manifold, we obtain global existence and asymptotic convergence of
the p-pseudoharmonic map heat flow as well when its initial p-energy is
sufficiently small.


title:
Beyond Countable Alphabets: An Extension of the Information-Spectrum
  Approach

abstract:
  A general approach is established for deriving one-shot performance bounds
for information-theoretic problems on general alphabets beyond countable
alphabets. It is mainly based on the quantization idea and a novel form of
"likelihood ratio". As an example, one-shot lower and upper bounds for random
number generation from correlated sources on general alphabets are derived.


title:
Cellular Underwater Wireless Optical CDMA Network: Potentials and
  Challenges

abstract:
  Underwater wireless optical communications is an emerging solution to the
expanding demand for broadband links in oceans and seas. In this paper, a
cellular underwater wireless optical code division multiple-access (UW-OCDMA)
network is proposed to provide broadband links for commercial and military
applications. The optical orthogonal codes (OOC) are employed as signature
codes of underwater mobile users. Fundamental key aspects of the network such
as its backhaul architecture, its potential applications and its design
challenges are presented. In particular, the proposed network is used as
infrastructure of centralized, decentralized and relay-assisted underwater
sensor networks for high-speed real-time monitoring. Furthermore, a promising
underwater localization and positioning scheme based on this cellular network
is presented. Finally, probable design challenges such as cell edge coverage,
blockage avoidance, power control and increasing the network capacity are
addressed.


title:
Tether-cutting Reconnection between Two Solar Filaments Triggering
  Outflows and a Coronal Mass Ejection

abstract:
  Triggering mechanisms of solar eruptions have long been a challenge. A few
previous case studies have indicated that preceding gentle filament merging via
magnetic reconnection may launch following intense eruption, according with the
tether-cutting (TC) model. However, detailed process of TC reconnection between
filaments has not been exhibited yet. In this work, we report the high
resolution observations from the Interface Region Imaging Spectrometer (IRIS)
of TC reconnection between two sheared filaments in NOAA active region 12146.
The TC reconnection commenced since 15:35 UT on 2014 August 29 and triggered an
eruptive GOES C4.3-class flare 8 minutes later. An associated coronal mass
ejection appeared in the field of view of SOHO/LASCO C2 about 40 minutes later.
Thanks to the high spatial resolution of IRIS data, bright plasma outflows
generated by the TC reconnection are clearly observed, which moved along the
subarcsecond fine-scale flux tube structures in the erupting filament. Based on
the imaging and spectral observations, the mean plane-of-sky and line-of-sight
velocities of the TC reconnection outflows are separately measured to be 79 and
86 km/s, which derives an average real speed of 120 km/s. In addition, it is
found that spectral features, such as peak intensities, Doppler shifts, and
line widths in the TC reconnection region evidently enhanced compared with
those in the nearby region just before the flare.


title: IR-improved Soft-wall AdS/QCD Model for Baryons

abstract:
  We construct an infrared-improved soft-wall AdS/QCD model for baryons by
considering the infrared-modified 5D conformal mass and Yukawa coupling of the
bulk baryon field. The model is also built by taking into account the
parity-doublet pattern for the excited baryons. When taking the bulk vacuum
structure of the meson field to be the one obtained consistently in the
infrared-improved soft-wall AdS/QCD model for mesons, we arrive at a consistent
prediction for the baryon mass spectrum in even and odd parity. The prediction
shows a remarkable agreement with the experimental data. We also perform a
calculation for the $\rho(a_1)$ meson-nucleon coupling constant and obtain a
consistent result in comparison with the experimental data and many other
models.


title:
Reduction of the effective thermal conductivity by circulation of the
  quasi-ballistic heat-flux

abstract:
  For a thermal conductivity that is spatially uniform and independent of
temperature, Fourier's law of heat transfer predicts a curl-free heat-flux. In
the quasi-ballistic phonon transport regime, where the Fourier law breaks down,
it has been proven starting from the Boltzmann transport equation that the
constitutive relation for the heat-flux contains a solenoidal (circulatory)
term with zero divergence and non-zero curl. In this paper we show how to
reduce the effective thermal conductivity of a material with dimensions on the
same scale as the phonon mean-free path, by exploiting the solenoidal term in
the constitutive relation.


title: An electrical probe of the phonon mean-free path spectrum

abstract:
  Most studies of the mean-free path accumulation function (MFPAF) rely on
optical techniques to probe heat transfer at length scales on the order of the
phonon mean-free path. In this paper, we propose and implement a purely
electrical probe of the MFPAF that relies on photo-lithographically defined
heater-thermometer separation to set the length scale. An important advantage
of the proposed technique is its insensitivity to the thermal interfacial
impedance and its compatibility with a large array of temperature-controlled
chambers that lack optical ports. Detailed analysis of the experimental data
based on the enhanced Fourier law (EFL) demonstrates that heat-carrying phonons
in gallium arsenide have a much wider mean-free path spectrum than originally
thought.


title:
Distributed Constrained Recursive Nonlinear Least-Squares Estimation:
  Algorithms and Asymptotics

abstract:
  This paper focuses on the problem of recursive nonlinear least squares
parameter estimation in multi-agent networks, in which the individual agents
observe sequentially over time an independent and identically distributed
(i.i.d.) time-series consisting of a nonlinear function of the true but unknown
parameter corrupted by noise. A distributed recursive estimator of the
\emph{consensus} + \emph{innovations} type, namely $\mathcal{CIWNLS}$, is
proposed, in which the agents update their parameter estimates at each
observation sampling epoch in a collaborative way by simultaneously processing
the latest locally sensed information~(\emph{innovations}) and the parameter
estimates from other agents~(\emph{consensus}) in the local neighborhood
conforming to a pre-specified inter-agent communication topology. Under rather
weak conditions on the connectivity of the inter-agent communication and a
\emph{global observability} criterion, it is shown that at every network agent,
the proposed algorithm leads to consistent parameter estimates. Furthermore,
under standard smoothness assumptions on the local observation functions, the
distributed estimator is shown to yield order-optimal convergence rates, i.e.,
as far as the order of pathwise convergence is concerned, the local parameter
estimates at each agent are as good as the optimal centralized nonlinear least
squares estimator which would require access to all the observations across all
the agents at all times. In order to benchmark the performance of the proposed
distributed $\mathcal{CIWNLS}$ estimator with that of the centralized nonlinear
least squares estimator, the asymptotic normality of the estimate sequence is
established and the asymptotic covariance of the distributed estimator is
evaluated. Finally, simulation results are presented which illustrate and
verify the analytical findings.

categories: math.OC cs.IT math.IT math.PR math.ST stat.TH


title: Topological full groups of etale groupoids

abstract:
  This is a survey of the recent development of the study of topological full
groups of etale groupoids on the Cantor set. Etale groupoids arise from
dynamical systems, e.g. actions of countable discrete groups, equivalence
relations. Minimal Z-actions, minimal Z^N-actions and one-sided shifts of
finite type are basic examples. We are interested in algebraic, geometric and
analytic properties of topological full groups. More concretely, we discuss
simplicity of commutator subgroups, abelianization, finite generation,
cohomological finiteness properties, amenability, the Haagerup property, and so
on. Homology groups of etale groupoids, groupoid C*-algebras and their K-groups
are also investigated.


title: On (conditional) positive semidefiniteness in a matrix-valued context

abstract:
  In a nutshell, we intend to extend Schoenberg's classical theorem connecting
conditionally positive semidefinite functions $F\colon \mathbb{R}^n \to
\mathbb{C}$, $n \in \mathbb{N}$, and their positive semidefinite exponentials
$\exp(tF)$, $t > 0$, to the case of matrix-valued functions $F \colon
\mathbb{R}^n \to \mathbb{C}^{m \times m}$, $m \in \mathbb{N}$. Moreover, we
study the closely associated property that $\exp(t F(- i \nabla))$, $t>0$, is
positivity preserving and its failure to extend directly in the matrix-valued
context.


title:
Classification and Ranking of Fermi LAT Gamma-ray Sources from the 3FGL
  Catalog using Machine Learning Techniques

abstract:
  We apply a number of statistical and machine learning techniques to classify
and rank gamma-ray sources from the Third Fermi Large Area Telescope (LAT)
Source Catalog (3FGL), according to their likelihood of falling into the two
major classes of gamma-ray emitters: pulsars (PSR) or Active Galactic Nuclei
(AGN). Using 1904 3FGL sources that have been identified/associated with AGN
(1738) and PSR (166), we train (using 70% of our sample) and test (using 30%)
our algorithms and find that the best overall accuracy (>96%) is obtained with
the Random Forest (RF) technique, while using a logistic regression (LR)
algorithm results in only marginally lower accuracy. We apply the same
techniques on a sub-sample of 142 known gamma-ray pulsars to classify them into
two major subcategories: young (YNG) and millisecond pulsars (MSP). Once more,
the RF algorithm has the best overall accuracy (~90%), while a boosted LR
analysis comes a close second. We apply our two best models (RF and LR) to the
entire 3FGL catalog, providing predictions on the likely nature of {\it
unassociated} sources, including the likely type of pulsar (YNG or MSP). We
also use our predictions to shed light on the possible nature of some gamma-ray
sources with known associations (e.g. binaries, SNR/PWN). Finally, we provide a
list of plausible X-ray counterparts for some pulsar candidates, obtained using
Swift, Chandra, and XMM. The results of our study will be of interest for both
in-depth follow-up searches (e.g. pulsar) at various wavelengths, as well as
for broader population studies.


title:
Scene Invariant Crowd Segmentation and Counting Using Scale-Normalized
  Histogram of Moving Gradients (HoMG)

abstract:
  The problem of automated crowd segmentation and counting has garnered
significant interest in the field of video surveillance. This paper proposes a
novel scene invariant crowd segmentation and counting algorithm designed with
high accuracy yet low computational complexity in mind, which is key for
widespread industrial adoption. A novel low-complexity, scale-normalized
feature called Histogram of Moving Gradients (HoMG) is introduced for highly
effective spatiotemporal representation of individuals and crowds within a
video. Real-time crowd segmentation is achieved via boosted cascade of weak
classifiers based on sliding-window HoMG features, while linear SVM regression
of crowd-region HoMG features is employed for real-time crowd counting.
Experimental results using multi-camera crowd datasets show that the proposed
algorithm significantly outperform state-of-the-art crowd counting algorithms,
as well as achieve very promising crowd segmentation results, thus
demonstrating the efficacy of the proposed method for highly-accurate,
real-time video-driven crowd analysis.


title:
$\textit{Ab initio}$ evidence for nonthermal characteristics in
  ultrafast laser melting

abstract:
  Laser melting of semiconductors has been observed for almost 40 years;
surprisingly, it is not well understood where most theoretical simulations show
a laser-induced thermal process. $\textit{Ab initio}$ nonadiabatic simulations
based on real-time time-dependent density functional theory reveal intrinsic
nonthermal melting of silicon, at a temperature far below the thermal melting
temperature of 1680 K. Both excitation threshold and time evolution of
diffraction intensity agree well with experiment. Nonthermal melting is
attributed to excitation-induced drastic changes in bonding electron density,
and the subsequent decrease in the melting barrier, rather than lattice heating
as previously assumed in the two-temperature models.


title:
Infinitesimal cranking for triaxial angular-momentum-projected
  configuration-mixing calculation and its application to the gamma vibrational
  band

abstract:
  Inclusion of time-odd components into the wave function is important for
reliable description of rotational motion by the angular-momentum-projection
method; the cranking procedure with infinitesimal rotational frequency is an
efficient way to realize it. In the present work we investigate the effect of
this infinitesimal cranking for triaxially deformed nucleus, where there are
three independent cranking axes. It is found that the effects of cranking about
three axes on the triaxial energy spectrum are quite different and inclusion of
all of them considerably modify the resultant spectrum from the one obtained
without cranking. Employing the Gogny D1S force as an effective interaction, we
apply the method to the calculation of the multiple gamma vibrational bands in
$^{164}$Er as a typical example, where the angular-momentum-projected
configuration-mixing with respect to the triaxial shape degree of freedom is
performed. With this method, both the $K=0$ and $K=4$ two-phonon gamma
vibrational bands are obtained with considerable anharmonicity. Reasonably good
agreement, though not perfect, is obtained for both the spectrum and transition
probabilities with rather small average triaxial deformation $\gamma\approx
9^\circ$ for the ground state rotational band. The relation to the wobbling
motion at high-spin states is also briefly discussed.


title: Reverse Nearest Neighbor Heat Maps: A Tool for Influence Exploration

abstract:
  We study the problem of constructing a reverse nearest neighbor (RNN) heat
map by finding the RNN set of every point in a two-dimensional space. Based on
the RNN set of a point, we obtain a quantitative influence (i.e., heat) for the
point. The heat map provides a global view on the influence distribution in the
space, and hence supports exploratory analyses in many applications such as
marketing and resource management. To construct such a heat map, we first
reduce it to a problem called Region Coloring (RC), which divides the space
into disjoint regions within which all the points have the same RNN set. We
then propose a novel algorithm named CREST that efficiently solves the RC
problem by labeling each region with the heat value of its containing points.
In CREST, we propose innovative techniques to avoid processing expensive RNN
queries and greatly reduce the number of region labeling operations. We perform
detailed analyses on the complexity of CREST and lower bounds of the RC
problem, and prove that CREST is asymptotically optimal in the worst case.
Extensive experiments with both real and synthetic data sets demonstrate that
CREST outperforms alternative algorithms by several orders of magnitude.


title:
A semigroup approach to Finsler geometry: Bakry-Ledoux's isoperimetric
  inequality

abstract:
  We develop the celebrated semigroup approach \`a la Bakry et al on Finsler
manifolds, where natural Laplacian and heat semigroup are nonlinear, based on
the Bochner-Weitzenb\"ock formula established by Sturm and the author. We show
the $L^1$-gradient estimate on Finsler manifolds (under some additional
assumptions in the noncompact case), which is equivalent to a lower weighted
Ricci curvature bound and the improved Bochner inequality. As a geometric
application, we prove Bakry-Ledoux's Gaussian isoperimetric inequality, again
under some additional assumptions in the noncompact case. This extends
Cavalletti-Mondino's inequality on reversible Finsler manifolds to
non-reversible metrics, and improves the author's previous estimate, both based
on the localization (also called needle decomposition) method.


title: Higher order test of Lorentz invariance with an optical ring cavity

abstract:
  We have developed an apparatus to search for the higher-order Lorentz
violation in photons by measuring the resonant frequency difference between two
counterpropagating directions of an asymmetric optical ring cavity. From the
year-long data taken between 2012 and 2013, we found no evidence for the light
speed anisotropy at the level of $\delta c/c \lesssim 10^{-15}$. Limits on the
dipole components of the anisotropy are improved by more than an order of
magnitude, and limits on the hexapole components are obtained for the first
time. An overview of our apparatus and the data analysis in the framework of
the spherical harmonics decomposition of anisotropy are presented. We also
present the status of the recent upgrade of the apparatus.


title: Underdamped stochastic heat engine at maximum efficiency

abstract:
  We investigate the performance of an underdamped stochastic heat engine for a
time-dependent harmonic oscillator. We analytically determine the optimal
protocol that maximizes the efficiency at fixed power. The maximum efficiency
reduces to the Curzon-Ahlborn formula at maximum power and the Carnot formula
at zero power. We further establish that the efficiency at maximum power is
universally given by the Curzon-Ahlborn efficiency in the weakly damped regime.
Finally, we show that even small deviations from operation at maximum power may
result in a significantly increased efficiency.


title:
Collusive Attacks to "Circle-Type" Multi-party Quantum Key Agreement
  Protocols

abstract:
  We find that existing multi-party quantum key agreement (MQKA) protocols
designed for fairness of the key are, in fact, unfair. Our analysis shows that
these protocols are sensitive to collusive attacks; that is, dishonest
participants can collaborate to predetermine the key without being detected. In
fact, the transmission structures of the quantum particles in those unfair MQKA
protocols, three of which have already been analyzed, have much in common. We
call these unfair MQKA protocols circle-type MQKA protocols. Likewise, the
transmission structures of the quantum particles in MQKA protocols that can
resist collusive attacks are also similar. We call such protocols
complete-graph-type MQKA protocols. A MQKA protocol also exists that can resist
the above attacks but is still not fair, and we call it the tree-type MQKA
protocol. We first point out a common, easily missed loophole that severely
compromises the fairness of present circle-type MQKA protocols. Then we show
that two dishonest participants at special positions can totally predetermine
the key generated by circle-type MQKA protocols. We anticipate that our
observations will contribute to secure and fair MQKA protocols, especially
circle-type protocols.