title:
NGC 1068: No change in the mid-IR torus structure despite X-ray
  variability

abstract:
  Context. Recent NuSTAR observations revealed a somewhat unexpected increase
in the X-ray flux of the nucleus of NGC 1068. We expect the infrared emission
of the dusty torus to react on the intrinsic changes of the accretion disk.
  Aims. We aim to investigate the origin of the X-ray variation by
investigating the response of the mid-infrared environment.
  Methods. We obtained single-aperture and interferometric mid-infrared
measurements and directly compared the measurements observed before and
immediately after the X-ray variations. The average correlated and
single-aperture fluxes as well as the differential phases were directly
compared to detect a possible change in the structure of the nuclear emission
on scales of $\sim$ 2 pc.
  Results. The flux densities and differential phases of the observations
before and during the X-ray variation show no significant change over a period
of ten years. Possible minor variations in the infrared emission are $\lesssim$
8 %.
  Conclusions. Our results suggest that the mid-infrared environment of NGC
1068 has remained unchanged for a decade. The recent transient change in the
X-rays did not cause a significant variation in the infrared emission. This
independent study supports previous conclusions that stated that the X-ray
variation detected by NuSTAR observations is due to X-ray emission piercing
through a patchy section of the dusty region.


title:
The Role of Baryons in Creating Statistically Significant Planes of
  Satellites around Milky Way-Mass Galaxies

abstract:
  We investigate whether the inclusion of baryonic physics influences the
formation of thin, coherently rotating planes of satellites such as those seen
around the Milky Way and Andromeda. For four Milky Way-mass simulations, each
run both as dark matter-only and with baryons included, we are able to identify
a planar configuration that significantly maximizes the number of plane
satellite members. The maximum plane member satellites are consistently
different between the dark matter-only and baryonic versions of the same run
due to the fact that satellites are both more likely to be destroyed and to
infall later in the baryonic runs. Hence, studying satellite planes in dark
matter-only simulations is misleading, because they will be composed of
different satellite members than those that would exist if baryons were
included. Additionally, the destruction of satellites in the baryonic runs
leads to less radially concentrated satellite distributions, a result that is
critical to making planes that are statistically significant compared to a
random distribution. Since all planes pass through the centre of the galaxy, it
is much harder to create a plane from a random distribution if the satellites
have a low radial concentration. We identify Andromeda's low radial satellite
concentration as a key reason why the plane in Andromeda is highly significant.
Despite this, when co-rotation is considered, none of the satellite planes
identified for the simulated galaxies are as statistically significant as the
observed planes around the Milky Way and Andromeda, even in the baryonic runs.


title:
Eigenstate phase transitions and the emergence of universal dynamics in
  highly excited states

abstract:
  We review recent advances in understanding the universal scaling properties
of non-equilibrium phase transitions in non-ergodic disordered systems. We
discuss dynamical critical points (also known as eigenstate phase transitions)
between different many-body localized (MBL) phases, and between MBL and thermal
phases.


title: Horizon Thermodynamics from Einstein's Equation of State

abstract:
  By regarding the Einstein equations as equation(s) of state, we demonstrate
that a full cohomogeneity horizon first law can be derived in horizon
thermodynamics. In this approach both the entropy and the free energy are
derived concepts, while the standard (degenerate) horizon first law is
recovered by a Legendre projection from the more general one we derive. These
results readily generalize to higher curvature gravities and establish a way of
how to formulate consistent black hole thermodynamics without conserved
charges.


title:
Systematic comparison of photoionised plasma codes with application to
  spectroscopic studies of AGN in X-rays

abstract:
  Atomic data and plasma models play a crucial role in the diagnosis and
interpretation of astrophysical spectra, thus influencing our understanding of
the universe. In this investigation we present a systematic comparison of the
leading photoionisation codes to determine how much their intrinsic differences
impact X-ray spectroscopic studies of hot plasmas in photoionisation
equilibrium. We carry out our computations using the Cloudy, SPEX, and XSTAR
photoionisation codes, and compare their derived thermal and ionisation states
for various ionising spectral energy distributions. We examine the resulting
absorption-line spectra from these codes for the case of ionised outflows in
active galactic nuclei. By comparing the ionic abundances as a function of
ionisation parameter $\xi$, we find that on average there is about 30%
deviation between the codes in $\xi$ where ionic abundances peak. For H-like to
B-like sequence ions alone, this deviation in $\xi$ is smaller at about 10% on
average. The comparison of the absorption-line spectra in the X-ray band shows
that there is on average about 30% deviation between the codes in the optical
depth of the lines produced at log $\xi$ ~ 1 to 2, reducing to about 20%
deviation at log $\xi$ ~ 3. We also simulate spectra of the ionised outflows
with the current and upcoming high-resolution X-ray spectrometers, on board
XMM-Newton, Chandra, Hitomi, and Athena. From these simulations we obtain the
deviation on the best-fit model parameters, arising from the use of different
photoionisation codes, which is about 10 to 40%. We compare the modelling
uncertainties with the observational uncertainties from the simulations. The
results highlight the importance of continuous development and enhancement of
photoionisation codes for the upcoming era of X-ray astronomy with Athena.


title:
Large curvature and background scale independence in single-metric
  approximations to asymptotic safety

abstract:
  In single-metric approximations to the exact renormalization group (RG) for
quantum gravity, it has been not been clear how to treat the large curvature
domain beyond the point where the effective cutoff scale $k$ is less than the
lowest eigenvalue of the appropriate modified Laplacian. We explain why this
puzzle arises from background dependence, resulting in Wilsonian RG concepts
being inapplicable. We show that when properly formulated over an ensemble of
backgrounds, the Wilsonian RG can be restored. This in turn implies that
solutions should be smooth and well defined no matter how large the curvature
is taken. Even for the standard single-metric type approximation schemes, this
construction can be rigorously derived by imposing a modified Ward identity
(mWI) corresponding to rescaling the background metric by a constant factor.
However compatibility in this approximation requires the space-time dimension
to be six. Solving the mWI and flow equation simultaneously, new variables are
then derived that are independent of overall background scale.


title: Vector Approximate Message Passing

abstract:
  The standard linear regression (SLR) problem is to recover a vector
$\mathbf{x}^0$ from noisy linear observations
$\mathbf{y}=\mathbf{Ax}^0+\mathbf{w}$. The approximate message passing (AMP)
algorithm recently proposed by Donoho, Maleki, and Montanari is a
computationally efficient iterative approach to SLR that has a remarkable
property: for large i.i.d.\ sub-Gaussian matrices $\mathbf{A}$, its
per-iteration behavior is rigorously characterized by a scalar state-evolution
whose fixed points, when unique, are Bayes optimal. The AMP algorithm, however,
is fragile in that even small deviations from the i.i.d.\ sub-Gaussian model
can cause the algorithm to diverge. This paper considers a "vector AMP" (VAMP)
algorithm and shows that VAMP has a rigorous scalar state-evolution that holds
under a much broader class of large random matrices $\mathbf{A}$: those that
are right-orthogonally invariant. After performing an initial singular value
decomposition (SVD) of $\mathbf{A}$, the per-iteration complexity of VAMP can
be made similar to that of AMP. In addition, the fixed points of VAMP's state
evolution are consistent with the replica prediction of the minimum
mean-squared error recently derived by Tulino, Caire, Verd\'u, and Shamai.
Numerical experiments are used to confirm the effectiveness of VAMP and its
consistency with state-evolution predictions.


title:
On Metrizing Vague Convergence of Random Measures with Applications on
  Bayesian Nonparametric Models

abstract:
  This paper deals with studying vague convergence of random measures of the
form $\mu_{n}=\sum_{i=1}^{n} p_{i,n} \delta_{\theta_i}$, where
$(\theta_i)_{1\le i \le n}$ is a sequence of independent and identically
distributed random variables with common distribution $\Pi$, $(p_{i,n})_{1 \le
i \le n}$ are random variables chosen according to certain procedures and are
independent of $(\theta_i)_{i \geq 1}$ and $\delta_{\theta_i}$ denotes the
Dirac measure at $\theta_i$. We show that $\mu_{n}$ converges vaguely to
$\mu=\sum_{i=1}^{\infty} p_{i} \delta_{\theta_i}$ if and only if
$\mu^{(k)}_{n}=\sum_{i=1}^{k} p_{i,n} \delta_{\theta_i}$ converges vaguely to
$\mu^{(k)}=\sum_{i=1}^{k} p_{i} \delta_{\theta_i}$ for all $k$ fixed. The
limiting process $\mu$ plays a central role in many areas in statistics,
including Bayesian nonparametric models. A finite approximation of the beta
process is derived from the application of this result. A simulated example is
incorporated, in which the proposed approach exhibits an excellent performance
over several existing algorithms.


title: On the b-continuity of the lexicographic product of graphs

abstract:
  A b-coloring of the vertices of a graph is a proper coloring where each color
class contains a vertex which is adjacent to each other color class. The
b-chromatic number of $G$ is the maximum integer $\chi_b(G)$ for which $G$ has
a b-coloring with $\chi_b(G)$ colors. A graph $G$ is b-continuous if $G$ has a
b-coloring with $k$ colors, for every integer $k$ in the interval
$[\chi(G),\chi_b(G)]$. It is known that not all graphs are b-continuous. Here,
we investigate whether the lexicographic product $G[H]$ of b-continuous graphs
$G$ and $H$ is also b-continuous. Using homomorphisms, we provide a new lower
bound for $\chi_b(G[H])$, namely $\chi_b(G[K_t])$, where $t=\chi_b(H)$, and
prove that if $G[K_\ell]$ is b-continuous for every positive integer $\ell$,
then $G[H]$ admits a b-coloring with $k$ colors, for every $k$ in the interval
$[\chi(G[H]),\chi_b(G[K_t])]$. We also prove that $G[K_\ell]$ is b-continuous,
for every positive integer $\ell$, whenever $G$ is a $P_4$-sparse graph, and we
give further results on the b-spectrum of $G[K_\ell]$, when $G$ is chordal.


title:
Density propagator for many-body localization: finite size effects,
  transient subdiffusion, and exponential decay

abstract:
  We investigate charge relaxation in quantum-wires of spin-less disordered
fermions ($t{-}V$-model). Our observable is the time-dependent density
propagator, $\Pi_{\varepsilon}(x,t)$, calculated in windows of different energy
density, $\varepsilon$, of the many-body Hamiltonian and at different disorder
strengths, $W$, not exceeding the critical value $W_\text{c}$. The width
$\Delta x_\varepsilon(t)$ of $\Pi_\varepsilon(x,t)$ exhibits a behavior $d\ln
\Delta x_\varepsilon(t) / d\ln t {=} \beta_\varepsilon(t)$, where the exponent
function $\beta_\varepsilon(t){\lesssim}1/2$ is seen to depend strongly on $L$
at all investigated parameter combinations. (i) We confirm the existence of a
region in phase space that exhibits subdiffusive dynamics in the sense that
$\beta_\varepsilon{<}1/2$ in large window of times. However, subdiffusion might
possibly be transient, only, finally giving way to a conventional diffusive
behavior with $\beta_{\varepsilon}{=}1/2$. (ii) We cannot confirm the existence
of many-body mobility edges even in regions of the phase-diagram that have been
reported to be deep in the delocalized phase. (iii) (Transient) subdiffusion
$0<\beta_\varepsilon(t)\lesssim 1/2$, coexists with an enhanced probability for
returning to the origin, $\Pi_\varepsilon(0,t)$, decaying much slower than
$1/\Delta x_\varepsilon (t)$. Correspondingly, the spatial decay of
$\Pi_\varepsilon(x,t)$ is far from Gaussian being exponential or even slower.
On a phenomenological level, our findings are broadly consistent with effects
of strong disorder and (fractal) Griffiths regions.


title: Option pricing with Legendre polynomials

abstract:
  Here we develop an option pricing method based on Legendre series expansion
of the density function. The key insight, relying on the close relation of the
characteristic function with the series coefficients, allows to recover the
density function rapidly and accurately. Based on this representation for the
density function, approximations formulas for pricing European type options are
derived. To obtain highly accurate result for European call option, the
implementation involves integrating high degree Legendre polynomials against
exponential function. Some numerical instabilities arise because of serious
subtractive cancellations in its formulation (96) in proposition 7.1. To
overcome this difficulty, we rewrite this quantity as solution of a
second-order linear difference equation and solve it using a robust and stable
algorithm from Olver. Derivation of the pricing method has been accompanied by
an error analysis. Errors bounds have been derived and the study relies more on
smoothness properties which are not provided by the payoff? functions, but
rather by the density function of the underlying stochastic models. This is
particularly relevant for options pricing where the payoff of the contract are
generally not smooth functions. The numerical experiments on a class of models
widely used in quantitative finance show exponential convergence.


title: Erratum to Viscosity solutions to complex Monge-Amp\`ere equations

abstract:
  The proof of the comparison principlein [EGZ11] is not complete. We provide
here an alternative proof, valid in the ample locus of any big cohomology
class, and discuss the resulting modifications.


title:
Machine learning techniques in searches for $t\bar{t}h$ in the $h
  \rightarrow b\bar{b}$ decay channel

abstract:
  Study of the production of pairs of top quarks in association with a Higgs
boson is one of the primary goals of the Large Hadron Collider over the next
decade, as measurements of this process may help us to understand whether the
uniquely large mass of the top quark plays a special role in electroweak
symmetry breaking. Higgs bosons decay predominantly to \bbbar, yielding
signatures for the signal that are similar to $t\bar{t}$ + jets with heavy
flavor. Though particularly challenging to study due to the similar kinematics
between signal and background events, such final states ($t\bar{t} b \bar{b}$)
are an important channel for studying the top quark Yukawa coupling. This paper
presents a systematic study of machine learning (ML) methods for detecting
$t\bar{t}h$ in the $h \rightarrow b\bar{b}$ decay channel. Among the eight ML
methods tested, we show that two models, extreme gradient boosted trees and
neural network models, outperform alternative methods. We further study the
effectiveness of ML algorithms by investigating the impact of feature set and
data size, as well as the structure of the models. While extended feature set
and larger training sets expectedly lead to improvement of performance, shallow
models deliver comparable or better performance than their deeper counterparts.
Our study suggests that ensembles of trees and neurons, not necessarily deep,
work effectively for the problem of $t\bar{t}h$ detection.


title:
Optimal Beamforming for MIMO Shared Relaying in Downlink Cellular
  Networks with ARQ

abstract:
  In this paper, we study the performance of the downlink of a cellular network
with automatic repeat-request (ARQ) and a half duplex decode-and-forward shared
relay. In this system, two multiple-input-multiple-output (MIMO) base stations
serve two single antenna users. A MIMO shared relay retransmits the lost
packets to the target users. First, we study the system with direct
retransmission from the base station and derive a closed form expression for
the outage probability of the system.We show that the direct retransmission can
overcome the fading, however, it cannot overcome the interference. After that,
we invoke the shared relay and design the relay beamforming matrices such that
the signal-to-interference-and-noise ratio (SINR) is improved at the users
subject to power constraints on the relay. In the case when the transmission of
only one user fails, we derive a closed form solution for the relay
beamformers. On the other hand when both transmissions fail, we pose the
beamforming problem as a sequence of non-convex feasibility problems. We use
semidefinite relaxation (SDR) to convert each feasibility problem into a convex
optimization problem. We ensure a rank one solution, and hence, there is no
loss of optimality in SDR. Simulation results are presented showing the
superior performance of the proposed relay beamforming strategy compared to
direct ARQ system in terms of the outage probability.


title: Dynamic Metric Learning from Pairwise Comparisons

abstract:
  Recent work in distance metric learning has focused on learning
transformations of data that best align with specified pairwise similarity and
dissimilarity constraints, often supplied by a human observer. The learned
transformations lead to improved retrieval, classification, and clustering
algorithms due to the better adapted distance or similarity measures. Here, we
address the problem of learning these transformations when the underlying
constraint generation process is nonstationary. This nonstationarity can be due
to changes in either the ground-truth clustering used to generate constraints
or changes in the feature subspaces in which the class structure is apparent.
We propose Online Convex Ensemble StrongLy Adaptive Dynamic Learning (OCELAD),
a general adaptive, online approach for learning and tracking optimal metrics
as they change over time that is highly robust to a variety of nonstationary
behaviors in the changing metric. We apply the OCELAD framework to an ensemble
of online learners. Specifically, we create a retro-initialized composite
objective mirror descent (COMID) ensemble (RICE) consisting of a set of
parallel COMID learners with different learning rates, demonstrate RICE-OCELAD
on both real and synthetic data sets and show significant performance
improvements relative to previously proposed batch and online distance metric
learning algorithms.


title: Constraining quantum collapse inflationary models with CMB data

abstract:
  The hypothesis of the self-induced collapse of the inflaton wave function was
proposed as responsible for the emergence of inhomogeneity and anisotropy at
all scales. This proposal was studied within an almost de Sitter space-time
approximation for the background, which led to a perfect scale-invariant power
spectrum, and also for a quasi-de Sitter background, which allows to
distinguish departures from the standard approach due to the inclusion of the
collapse hypothesis. In this work we perform a Bayesian model comparison for
two different choices of the self-induced collapse in a full quasi-de Sitter
expansion scenario. In particular, we analyze the possibility of detecting the
imprint of these collapse schemes at low multipoles of the anisotropy
temperature power spectrum of the Cosmic Microwave Background (CMB) using the
most recent data provided by the Planck Collaboration. Our results show that
one of the two collapse schemes analyzed provides the same Bayesian evidence of
the minimal standard cosmological model $\Lambda$CDM, while the other scenario
is weakly disfavoured with respect to the standard cosmology.


title: Superbubbles in the Multiphase ISM and the Loading of Galactic Winds

abstract:
  We use numerical simulations to analyze the evolution and properties of
superbubbles (SBs), driven by multiple supernovae (SNe), that propagate into
the two-phase (warm/cold), cloudy interstellar medium (ISM). We consider a
range of mean background densities n_avg=0.1-10 cm^{-3} and intervals between
SNe dt_sn=0.01-1 Myr, and follow each SB until the radius reaches (1-2)H, where
H is the characteristic ISM disk thickness. Except for embedded dense clouds,
each SB is hot until a time t_sf,m when the shocked warm gas at the outer front
cools and forms an overdense shell. Subsequently, diffuse gas in the SB
interior remains at T_h 10^6-10^7K with expansion velocity v_h~10^2-10^3km/s
(both highest for low dt_sn). At late times, the warm shell gas velocities are
several 10's to ~100km/s. While shell velocities are too low to escape from a
massive galaxy, they are high enough to remove substantial mass from dwarfs.
Dense clouds are also accelerated, reaching a few to 10's of km/s. We measure
the mass in hot gas per SN, M_h/N_SN, and the total radial momentum of the
bubble per SN, p_b/N_SN. After t_sf,m, M_h/N_SN 10-100M_sun (highest for low
n_avg), while p_b/N_SN 0.7-3x10^5M_sun km/s (highest for high dt_sn). If
galactic winds in massive galaxies are loaded by the hot gas in SBs, we
conclude that the mass-loss rates would generally be lower than star formation
rates. Only if the SN cadence is much higher than typical in galactic disks, as
may occur for nuclear starbursts, SBs can break out while hot and expel up to
10 times the mass locked up in stars. The momentum injection values, p_b/N_SN,
are consistent with requirements to control star formation rates in galaxies at
observed levels.


title:
A multi-wavelength characterization of proto-brown dwarf candidates in
  Serpens

abstract:
  We present results from a deep sub-millimeter survey in the Serpens Main and
Serpens/G3-G6 clusters, conducted with the Submillimetre Common-User Bolometer
Array (SCUBA-2) at the James Clerk Maxwell Telescope. We have combined Herschel
PACS far-infrared photometry, sub-millimeter continuum and molecular gas line
observations, with the aim to conduct a detailed multi-wavelength
characterization of `proto-brown dwarf' candidates in Serpens. We have
performed continuum and line radiative transfer modeling, and have considered
various classification schemes to understand the structure and the evolutionary
stage of the system. We have identified four proto-brown dwarf candidates, of
which the lowest luminosity source has an Lbol ~0.05 Lsun. Two of these
candidates show characteristics consistent with Stage 0/I systems, while the
other two are Stage I-T/Class Flat systems with tenuous envelopes. Our work has
also revealed a ~20% fraction of mis-identified Class 0/I/Flat sources that
show characteristics consistent with Class II edge-on disk systems. We have set
constraints on the mass of the central object using the measured bolometric
luminosities and numerical simulations of stellar evolution. Considering the
available gas+dust mass reservoir and the current mass of the central source,
three of these candidates are likely to evolve into brown dwarfs.


title:
Designing Model and Optimization of the Permanent Magnet for Joule
  Balance NIM-2

abstract:
  Permanent magnets with yokes are widely used in the watt and joule balances
to measure the Planck constant for the forthcoming redefinition of the unit of
mass, the kilogram. Recently, a permanent magnet system has been in
consideration for a further practice of NIM-2, the generalized joule balance.
In this paper, an analytical model to design the permanent magnet system is
presented. The presented model can be solved to obtain the preliminary
parameters and then is used as guidance for FEA software to optimize the
parameters of such magnetic system. As an instance for the application of the
designing model, the design of the permanent magnet system for NIM-2 is
described and the special design of opening shape makes the misalignment of the
top and middle yokes has little influence on the vertical component of the
magnetic field.


title:
Greedy Gauss-Newton algorithm for finding sparse solutions to nonlinear
  underdetermined systems of equations

abstract:
  We consider the problem of finding sparse solutions to a system of
underdetermined nonlinear system of equations. The methods are based on a
Gauss-Newton approach with line search where the search direction is found by
solving a linearized problem using only a subset of the columns in the
Jacobian. The choice of columns in the Jacobian is made through a greedy
approach looking at either maximum descent or an approach corresponding to
orthogonal matching for linear problems. The methods are shown to be convergent
and efficient and outperform the $\ell_1$ approach on the test problems
presented.


title:
On the astronomical origin of the Hallstatt oscillation found in
  radiocarbon and climate records throughout the Holocene

abstract:
  An oscillation with a period of about 2100-2500 years, the Hallstatt cycle,
is found in cosmogenic radioisotopes (C-14 and Be-10) and in paleoclimate
records throughout the Holocene. Herein we demonstrate the astronomical origin
of this cycle. Namely, this oscillation is coherent to the major stable
resonance involving the four Jovian planets - Jupiter, Saturn, Uranus and
Neptune - whose period is p=2318 yr. The Hallstatt cycle could derive from the
rhythmic variation of the circularity of the solar system disk assuming that
this dynamics could eventually modulate the solar wind and, consequently, the
incoming cosmic ray flux and/or the interplanetary/cosmic dust concentration
around the Earth-Moon system. The orbit of the planetary mass center (PMC)
relative to the Sun is used as a proxy. We analyzed how the instantaneous
eccentricity vector of this virtual orbit varies from 13,000 B. C. to 17,000 A.
D.. We found that it undergoes kind of pulsations as it clearly presents
rhythmic contraction and expansion patterns with a 2318 yr period together with
a number of already known faster oscillations associated to the planetary
orbital stable resonances. We found that a fast expansion of the Sun-PMC orbit
followed by a slow contraction appears to prevent cosmic rays to enter within
the system inner region while a slow expansion followed by a fast contraction
favors it. Similarly, the same dynamics could modulate the amount of
interplanetary/cosmic dust falling on Earth. These would then cause both the
radionucleotide production and climate change by means of a cloud/albedo
modulation. Other stable orbital resonance frequencies (e.g. at periods of 20
yr, 45 yr, 60 yr, 85 yr, 159-171-185 yr, etc.) are found in radionucleotide,
solar, aurora and climate records, as determined in the scientific literature.
Thus, the result supports a planetary theory of solar and/or climate variation.

categories: physics.geo-ph astro-ph.EP astro-ph.SR physics.ao-ph


title:
TeV Cosmic-Ray Anisotropy from the Magnetic Field at the Heliospheric
  Boundary

abstract:
  We performed numerical calculations to test the suggestion by Desiati &
Lazarian (2013) that the anisotropies of TeV cosmic rays may arise from their
interactions with the heliosphere. For this purpose, we used a magnetic field
model of the heliosphere and performed direct numerical calculations of
particle trajectories. Unlike earlier papers testing the idea, we did not
employ time-reversible techniques that are based on Liouville's theorem. We
showed numerically that for scattering by the heliosphere the conditions of
Liouville's theorem are not satisfied and the adiabatic approximation and
time-reversibility of the particle trajectories are not valid. Our results
indicate sensitivity to the magnetic structure of the heliospheric magnetic
field, and we expect that this will be useful for probing this structure in
future research.


title: Neural Paraphrase Generation with Stacked Residual LSTM Networks

abstract:
  In this paper, we propose a novel neural approach for paraphrase generation.
Conventional para- phrase generation methods either leverage hand-written rules
and thesauri-based alignments, or use statistical machine learning principles.
To the best of our knowledge, this work is the first to explore deep learning
models for paraphrase generation. Our primary contribution is a stacked
residual LSTM network, where we add residual connections between LSTM layers.
This allows for efficient training of deep LSTMs. We evaluate our model and
other state-of-the-art deep learning models on three different datasets: PPDB,
WikiAnswers and MSCOCO. Evaluation results demonstrate that our model
outperforms sequence to sequence, attention-based and bi- directional LSTM
models on BLEU, METEOR, TER and an embedding-based sentence similarity metric.


title: Ground state spin and excitation energies in half-filled Lieb lattices

abstract:
  We present detailed spectral calculations for small Lieb lattices having up
to $N=4$ number of cells, in the regime of half-filling, an instance of
particular relevance for the nano-magnetism of discrete systems such as quantum
dot arrays, due to the degenerate levels at mid-spectrum. While for the Hubbard
interaction model -and even number of sites- the ground state spin is given by
the Lieb theorem, the inclusion of long range interaction -or odd number of
sites- make the spin state not a priori known, which justifies our approach. We
calculate also the excitation energies, which are of experimental importance,
and find significant variation induced by the interaction potential. One
obtains insights on the mechanisms involved that impose as ground state the
Lieb state with lower spin rather than the Hund one with maximum spin for the
degenerate levels, showing this in the first and second order of the
interaction potential for the smaller lattices. The analytical results concorde
with the numerical ones, which are performed by exact diagonalization
calculations or by a combined mean-field and configuration interaction method.
While the Lieb state is always lower in energy than the Hund state, for strong
long-range interaction, when possible, another minimal spin state is imposed as
ground state.


title: Computer simulations of melts of randomly branching polymers

abstract:
  Randomly branching polymers with {\em annealed} connectivity are model
systems for ring polymers and chromosomes. In this context, the branched
structure represents transient folding induced by topological constraints. Here
we present computer simulations of melts of annealed randomly branching
polymers of $3 \le N \le 1800$ segments in $d=2$ and $d=3$ dimensions. In all
cases, we perform a detailed analysis of the observed tree connectivities and
spatial conformations. Our results are in excellent agreement with an
asymptotic scaling of the average tree size of $R \sim N^{1/d}$, suggesting
that the trees behave as compact, {\it territorial} fractals. The observed
swelling relative to the size of ideal trees, $R\sim N^{1/4}$, demonstrates
that excluded volume interactions are only partially screened in melts of
annealed trees. Overall, our results are in good qualitative agreement with the
predictions of Flory theory. In particular, we find that the trees swell by the
combination of modified branching and path stretching. However, the former
effect is subdominant and difficult to detect in $d=3$ dimensions.


title: The origin of the Milky Way globular clusters

abstract:
  We present a cosmological zoom-in simulation of a Milky Way-like galaxy used
to explore the formation and evolution of star clusters. We investigate in
particular the origin of the bimodality observed in the colour and metallicity
of globular clusters, and the environmental evolution through cosmic times in
the form of tidal tensors. Our results self-consistently confirm previous
findings that the blue, metal-poor clusters form in satellite galaxies which
are accreted onto the Milky Way, while the red, metal-rich clusters form mostly
in situ or, to a lower extent in massive, self-enriched galaxies merging with
the Milky Way. By monitoring the tidal fields these populations experience, we
find that clusters formed in situ (generally centrally concentrated) feel
significantly stronger tides than the accreted ones, both in the present-day,
and when averaged over their entire life. Furthermore, we note that the tidal
field experienced by Milky Way clusters is significantly weaker in the past
than at present-day, confirming that it is unlikely that a power-law cluster
initial mass function like that of young massive clusters, is transformed into
the observed peaked distribution in the Milky Way with relaxation-driven
evaporation in a tidal field.


title:
Inequivalence Between Passive Gravitational Mass and Energy for a
  Quantum Body: Theory and Suggested Experiment

abstract:
  Recently, we have suggested some semi-quantitative Hamiltonian for an
electron in a hydrogen atom in a weak gravitational field, which takes into
account quantum effects of electron motion in the atom. We have shown that this
Hamiltonian predicts breakdown of the equivalence between passive electron
gravitational mass and its energy. Moreover, as has been shown by us, the
latter phenomenon can be experimentally observed as unusual emission of
radiation from an ensemble of the atoms, provided that they are moved in the
Earth's gravitational field with constant velocity by some spacecraft. In this
article, we derive the above-mentioned Hamiltonian from the Dirac equation in a
curved spacetime. It is shown that it exactly coincides with the
semi-quantitative Hamiltonian, used in our previous papers. We extend the
obtained Hamiltonian to the case of a spacecraft, containing a macroscopic
ensemble of the atoms and moving with a constant velocity in the Earth's
gravitational field. On this basis, we discuss some idealized and realistic
experiments on the Earth's orbit. If such (realistic) experiment is done, it
will be the first direct observation of quantum effects in the General
Relativity.


title: Optimality Regions and Fluctuations for Bernoulli Last Passage Models

abstract:
  We study the sequence alignment problem and its independent version, the
discrete Hammersley process with an exploration penalty. We obtain rigorous
upper bounds for the number of optimality regions in both models near the soft
edge. At zero penalty the independent model becomes an exactly solvable model
and we identify cases for which the law of the last passage time converges to a
Tracy-Widom law.


title:
Slender Ca II H Fibrils Mapping Magnetic Fields in the Low Solar
  Chromosphere

abstract:
  A dense forest of slender bright fibrils near a small solar active region is
seen in high-quality narrowband Ca II H images from the SuFI instrument onboard
the Sunrise balloon-borne solar observatory. The orientation of these slender
Ca II H fibrils (SCF) overlaps with the magnetic field configuration in the low
solar chromosphere derived by magnetostatic extrapolation of the photospheric
field observed with Sunrise/IMaX and SDO/HMI. In addition, many observed SCFs
are qualitatively aligned with small-scale loops computed from a novel
inversion approach based on best-fit numerical MHD simulation. Such loops are
organized in canopy-like arches over quiet areas that differ in height
depending on the field strength near their roots.


title: A Secure Data Enclave and Analytics Platform for Social Scientists

abstract:
  Data-driven research is increasingly ubiquitous and data itself is a defining
asset for researchers, particularly in the computational social sciences and
humanities. Entire careers and research communities are built around valuable,
proprietary or sensitive datasets. However, many existing computation resources
fail to support secure and cost-effective storage of data while also enabling
secure and flexible analysis of the data. To address these needs we present
CLOUD KOTTA, a cloud-based architecture for the secure management and analysis
of social science data. CLOUD KOTTA leverages reliable, secure, and scalable
cloud resources to deliver capabilities to users, and removes the need for
users to manage complicated infrastructure. CLOUD KOTTA implements automated,
cost-aware models for efficiently provisioning tiered storage and automatically
scaled compute resources. CLOUD KOTTA has been used in production for several
months and currently manages approximately 10TB of data and has been used to
process more than 5TB of data with over 75,000 CPU hours. It has been used for
a broad variety of text analysis workflows, matrix factorization, and various
machine learning algorithms, and more broadly, it supports fast, secure and
cost-effective research.


title: Supervised Term Weighting Metrics for Sentiment Analysis in Short Text

abstract:
  Term weighting metrics assign weights to terms in order to discriminate the
important terms from the less crucial ones. Due to this characteristic, these
metrics have attracted growing attention in text classification and recently in
sentiment analysis. Using the weights given by such metrics could lead to more
accurate document representation which may improve the performance of the
classification. While previous studies have focused on proposing or comparing
different weighting metrics at two-classes document level sentiment analysis,
this study propose to analyse the results given by each metric in order to find
out the characteristics of good and bad weighting metrics. Therefore we present
an empirical study of fifteen global supervised weighting metrics with four
local weighting metrics adopted from information retrieval, we also give an
analysis to understand the behavior of each metric by observing and analysing
how each metric distributes the terms and deduce some characteristics which may
distinguish the good and bad metrics. The evaluation has been done using
Support Vector Machine on three different datasets: Twitter, restaurant and
laptop reviews.


title: Approaching a realistic force balance in geodynamo simulations

abstract:
  Earth sustains its magnetic field by a dynamo process driven by convection in
the liquid outer core. Geodynamo simulations have been successful in
reproducing many observed properties of the geomagnetic field. However, while
theoretical considerations suggest that flow in the core is governed by a
balance between Lorentz force, rotational force and buoyancy (called MAC
balance for Magnetic, Archimedean, Coriolis) with only minute roles for viscous
and inertial forces, dynamo simulations must employ viscosity values that are
many orders of magnitude larger than in the core due to computational
constraints. In typical geodynamo models viscous and inertial forces are not
much smaller than the Coriolis force and the Lorentz force plays a sub-dominant
role. This has led to conclusions that these simulations are viscously
controlled and do not represent the physics of the geodynamo. Here we show by a
direct analysis of the relevant forces that a MAC balance can be achieved when
the viscosity is reduced to values close to the current practical limit.
Lorentz force, buoyancy and the uncompensated (by pressure) part of the
Coriolis force are of very similar strength, whereas viscous and inertia are
smaller by a factor of at least 20 in the bulk of the fluid volume. Compared to
non-magnetic convection at otherwise identical parameters, the dynamo flow is
of larger scale, less invariant parallel to the rotation axis (less
geostrophic) and convection transports twice as much heat, all of which is
expected when the Lorentz force strongly influences the convection properties.


title: Cloud Kotta: Enabling Secure and Scalable Data Analytics in the Cloud

abstract:
  Distributed communities of researchers rely increasingly on valuable,
proprietary, or sensitive datasets. Given the growth of such data, especially
in fields new to data-driven, computationally intensive research like the
social sciences and humanities, coupled with what are often strict and complex
data-use agreements, many research communities now require methods that allow
secure, scalable and cost-effective storage and analysis. Here we present CLOUD
KOTTA: a cloud-based data management and analytics framework. CLOUD KOTTA
delivers an end-to-end solution for coordinating secure access to large
datasets, and an execution model that provides both automated infrastructure
scaling and support for executing analytics near to the data. CLOUD KOTTA
implements a fine-grained security model ensuring that only authorized users
may access, analyze, and download protected data. It also implements automated
methods for acquiring and configuring low-cost storage and compute resources as
they are needed. We present the architecture and implementation of CLOUD KOTTA
and demonstrate the advantages it provides in terms of increased performance
and flexibility. We show that CLOUD KOTTA's elastic provisioning model can
reduce costs by up to 16x when compared with statically provisioned models.


title:
A sensitive search for predicted methanol maser transitions with the
  Australia Telescope Compact Array

abstract:
  We have used the Australia Telescope Compact Array (ATCA) to search for a
number of centimetre wavelength methanol transitions which are predicted to
show weak maser emission towards star formation regions. Sensitive, high
spatial and spectral resolution observations towards four high-mass star
formation regions which show emission in a large number of class II methanol
maser transitions did not result in any detections. From these observations we
are able to place an upper limit of <~1300K on the brightness temperature of
any emission from the $3_1$A$^+$-$3_1$A$^-$, $17_{-2}$-$18_{-3}$E ($v_t=1$),
$12_4$-$13_3$A$^-$, $12_4$-$13_3$A$^+$ and $4_1$A$^+$-$4_1$A$^-$ transitions of
methanol in these sources on angular scales of 2 arcseconds. This upper limit
is consistent with current models for class II methanol masers in high-mass
star formation regions and better constraints than those provided here will
likely require observations with next-generation radio telescopes.


title: Characterizing variability in nonlinear recurrent neuronal networks

abstract:
  In this note, we develop semi-analytical techniques to obtain the full
correlational structure of a stochastic network of nonlinear neurons described
by rate variables. Under the assumption that pairs of membrane potentials are
jointly Gaussian -- which they tend to be in large networks -- we obtain
deterministic equations for the temporal evolution of the mean firing rates and
the noise covariance matrix that can be solved straightforwardly given the
network connectivity. We also obtain spike count statistics such as Fano
factors and pairwise correlations, assuming doubly-stochastic action potential
firing. Importantly, our theory does not require fluctuations to be small, and
works for several biologically motivated, convex single-neuron nonlinearities.


title:
An enhanced finite element method for a class of variational problems
  exhibiting the Lavrentiev gap phenomenon

abstract:
  This paper develops an enhanced finite element method for approximating a
class of variational problems which exhibit the \textit{Lavrentiev gap
phenomenon} in the sense that the minimum values of the energy functional have
a nontrivial gap when the functional is minimized on spaces $W^{1,1}$ and
$W^{1,\infty}$. To remedy the standard finite element method, which fails to
converge for such variational problems, a simple and effective cut-off
procedure is utilized to design the (enhanced finite element) discrete energy
functional. In essence the proposed discrete energy functional curbs the gap
phenomenon by capping the derivatives of its input on a scale of
$O(h^{-\alpha})$ (where $h$ denotes the mesh size) for some positive constant
$\alpha$. A sufficient condition is proposed for determining the
problem-dependent parameter $\a$. Extensive 1-D and 2-D numerical experiment
results are provided to show the convergence behavior and the performance of
the proposed enhanced finite element method.


title:
Leveraging Recurrent Neural Networks for Multimodal Recognition of
  Social Norm Violation in Dialog

abstract:
  Social norms are shared rules that govern and facilitate social interaction.
Violating such social norms via teasing and insults may serve to upend power
imbalances or, on the contrary reinforce solidarity and rapport in
conversation, rapport which is highly situated and context-dependent. In this
work, we investigate the task of automatically identifying the phenomena of
social norm violation in discourse. Towards this goal, we leverage the power of
recurrent neural networks and multimodal information present in the
interaction, and propose a predictive model to recognize social norm violation.
Using long-term temporal and contextual information, our model achieves an F1
score of 0.705. Implications of our work regarding developing a social-aware
agent are discussed.


title: Truncated Variational Expectation Maximization

abstract:
  We derive a novel variational expectation maximization approach based on
truncated posterior distributions. Truncated distributions are proportional to
exact posteriors within subsets of a discrete state space and equal zero
otherwise. The treatment of the distributions' subsets as variational
parameters distinguishes the approach from previous variational approaches. The
specific structure of truncated distributions allows for deriving novel and
mathematically grounded results, which in turn can be used to formulate novel
efficient algorithms to optimize the parameters of probabilistic generative
models. Most centrally, we find the variational lower bounds that correspond to
truncated distributions to be given by very concise and efficiently computable
expressions, while update equations for model parameters remain in their
standard form. Based on these findings, we show how efficient and easily
applicable meta-algorithms can be formulated that guarantee a monotonic
increase of the variational bound. Example applications of the here derived
framework provide novel theoretical results and learning procedures for latent
variable models as well as mixture models. Furthermore, we show that truncated
variation EM naturally interpolates between standard EM with full posteriors
and EM based on the maximum a-posteriori state (MAP). The approach can,
therefore, be regarded as a generalization of the popular `hard EM' approach
towards a similarly efficient method which can capture more of the true
posterior structure.


title: Equivariant symmetric monoidal structures

abstract:
  Building on structure observed in equivariant homotopy theory, we define an
equivariant generalization of a symmetric monoidal category: a $G$-symmetric
monoidal category. These record not only the symmetric monoidal products but
also symmetric monoidal powers indexed by arbitrary finite $G$-sets. We then
define $G$-commutative monoids to be the natural extension of ordinary
commutative monoids to this new context. Using this machinery, we then describe
when Bousfield localization in equivariant spectra preserves certain operadic
algebra structures, and we explore the consequences of our definitions for
categories of modules over a $G$-commutative monoid.


title: Note on Nordhaus-Gaddum problems for power domination

abstract:
  The upper and lower Nordhaus-Gaddum bounds over all graphs for the power
domination number follow from known bounds on the domination number and
examples. In this note we improve the upper sum bound for the power domination
number substantially for graphs having the property that both the graph and its
complement must be connected. For these graphs, our bound is tight and is also
significantly better than the corresponding bound for domination number. We
also improve the product upper bound for the power domination number for graphs
with certain properties.


title: Transport of Indirect Excitons in High Magnetic Fields

abstract:
  We present spatially- and spectrally-resolved photoluminescence measurements
of indirect excitons in high magnetic fields. Long indirect exciton lifetimes
give the opportunity to measure magnetoexciton transport by optical imaging.
Indirect excitons formed from electrons and holes at zeroth Landau levels (0e -
0h indirect magnetoexcitons) travel over large distances and form a ring
emission pattern around the excitation spot. In contrast, the spatial profiles
of 1e - 1h and 2e - 2h indirect magnetoexciton emission closely follow the
laser excitation profile. The 0e - 0h indirect magnetoexciton transport
distance reduces with increasing magnetic field. These effects are explained in
terms of magnetoexciton energy relaxation and effective mass enhancement.


title: Localization results for Minkowski contents

abstract:
  It was shown recently that the Minkowski content of a bounded set $A$ in
$\mathbb{R}^d$ with volume zero can be characterized in terms of the asymptotic
behaviour of the boundary surface area of its parallel sets $A_r$ as the
parallel radius $r$ tends to $0$. Here we discuss localizations of such
results. The asymptotic behaviour of the local parallel volume of $A$ relative
to a suitable second set $\Omega$ can be understood in terms of the suitably
defined local surface area relative to $\Omega$. Also a measure version of this
relation is shown: Viewing the Minkowski content as a locally determined
measure, this measure can be obtained as a weak limit of suitably rescaled
surface measures of close parallel sets. Such measure relations had been
observed before for self-similar sets and some self-conformal sets in
$\mathbb{R}^d$. They are now established for arbitrary closed sets, including
even the case of unbounded sets.
  The results are based on a localization of Stach\'o's famous formula relating
the boundary surface area of $A_r$ to the derivative of the volume function at
$r$.


title: A survey on duals of topological tensor products

abstract:
  We give a survey on classical and recent results on dual spaces of
topological tensor products as well as some examples where these are used.


title: Superfluid filaments of dipolar bosons in free space

abstract:
  We systematically investigate the zero temperature phase diagram of bosons
interacting via dipolar interactions in three dimensions in free space via path
integral Monte Carlo simulations with few hundreds of particles and periodic
boundary conditions based on the worm algorithm. Upon increasing the strength
of the dipolar interaction and at sufficiently high densities we find a wide
region where filaments are stabilized along the direction of the external
field. Most interestingly by computing the superfluid fraction we conclude that
superfluidity is anisotropic and is greatly suppressed along the orthogonal
plane. Finally we perform simulations at finite temperature confirming the
stability of filaments against thermal fluctuations and provide an estimate of
the superfluid fraction in the weak coupling limit in the framework of the
Landau two-fluid model.


title: Correlation-Based Method for Sentiment Classification

abstract:
  The classic supervised classification algorithms are efficient, but
time-consuming, complicated and not interpretable, which makes it difficult to
analyze their results that limits the possibility to improve them based on real
observations. In this paper, we propose a new and a simple classifier to
predict a sentiment label of a short text. This model keeps the capacity of
human interpret-ability and can be extended to integrate NLP techniques in a
more interpretable way. Our model is based on a correlation metric which
measures the degree of association between a sentiment label and a word. Ten
correlation metrics are proposed and evaluated intrinsically. And then a
classifier based on each metric is proposed, evaluated and compared to the
classic classification algorithms which have proved their performance in many
studies. Our model outperforms these algorithms with several correlation
metrics.


title:
Measuring and Modelling Crowd Flows - Fusing Stationary and Tracking
  Data

abstract:
  The two main data categories of vehicular traffic flow, stationary detector
data and floating-car data, are also available for many Marathons and other
mass-sports events: Loop detectors and other stationary data sources find their
counterpart in the RFID tags of the athletes recording the split times at
several stations during the race. Additionally, more and more athletes use
smart-phone apps generating track data points that are the equivalent of
floating-car data. We present a methodology to detect congestions and estimate
the location of jam-fronts, the delay times, and the spatio-temporal speed and
density distribution of the athlete's crowd flow by fusing these two data
sources based on a first-order macroscopic model with triangular fundamental
diagram. The method can be used in real-time or for analyzing past events.
Using synthetic "ground truth" data generated by simulations with the
Intelligent-Driver Model, we show that, in a real-time application, the
proposed algorithm is robust and effective with minimal data requirements.
Generally, two stationary data sources and about ten "floating-athlete"
trajectories per hour are sufficient.


title:
Determination of the resistivity anisotropy of orthorhombic materials
  via transverse resistivity measurements

abstract:
  Measurements of the resistivity anisotropy can provide crucial information
about the electronic structure and scattering processes in anisotropic and
low-dimensional materials, but quantitative measurements by conventional means
often suffer very significant systematic errors. Here we describe a novel
approach to measuring the resistivity anisotropy of orthorhombic materials,
using a single crystal and a single measurement, that is derived from a
$\frac{\pi}{4}$ rotation of the measurement frame relative to the
crystallographic axes. In this new basis the transverse resistivity gives a
direct measurement of the resistivity anisotropy, which combined with the
longitudinal resistivity also gives the in-plane elements of the conventional
resistivity tensor via a 5-point contact geometry. This is demonstrated through
application to the charge-density wave compound ErTe$_3$, and it is concluded
that this method presents a significant improvement on existing techniques in
many scenarios.


title: Spectator fields and their imprints on the Cosmic Microwave Background

abstract:
  When a subdominant light scalar field ends slow roll during inflation, but
well after the Hubble exit of the pivot scales, it may determine the
cosmological perturbations. This thesis investigates how such a scalar field,
the spectator, may leave its impact on the Cosmic Microwave Background (CMB)
radiation and be consequently constrained. We first introduce the observables
of the CMB, namely the power spectrum $P_\zeta$, spectral index $n_s$ and its
running $dn_s/d\ln k$, the non-Gaussianities $f_{NL}$, $g_{NL}$ and
$\tau_{NL}$, and the lack of isocurvature and polarization modes. Based on
these studies, we derive the cosmological predictions for the spectator
scenario, revealing its consistency with the CMB for inflection point
potentials, hyperbolic tangent potentials, and those with a sudden phase
transition. In the end, we utilize the spectator scenario to explain the CMB
power asymmetry, with a brief tachyonic fast-roll phase.


title:
Calibrating the Local and Platoon Dynamics of Car-following Models on
  the Reconstructed NGSIM Data

abstract:
  The NGSIM trajectory data are used to calibrate two car-following models -
the IDM and the FVDM. We used the I80 dataset which has already been
reconstructed to eliminate outliers, unphysical data, and internal and platoon
inconsistencies contained in the original data.We extract from the data
leader-follower pairs and platoons of up to five consecutive vehicles thereby
eliminating all trajectories that are too short or contain lane changes. Four
error measures based on speed and gap deviations are considered. Furthermore,
we apply three calibration methods: local or direct calibration, global
calibration, and platoon calibration. The last approach means that a platoon of
several vehicles following a data-driven leader is simulated and compared to
the observed dynamics.


title:
Tight Tradeoffs for Real-Time Approximation of Longest Palindromes in
  Streams

abstract:
  We consider computing a longest palindrome in the streaming model, where the
symbols arrive one-by-one and we do not have random access to the input. While
computing the answer exactly using sublinear space is not possible in such a
setting, one can still hope for a good approximation guarantee. Our
contribution is twofold. First, we provide lower bounds on the space
requirements for randomized approximation algorithms processing inputs of
length $n$. We rule out Las Vegas algorithms, as they cannot achieve sublinear
space complexity. For Monte Carlo algorithms, we prove a lower bounds of
$\Omega( M \log\min\{|\Sigma|,M\})$ bits of memory; here $M=n/E$ for
approximating the answer with additive error $E$, and $M= \frac{\log n}{\log
(1+\varepsilon)}$ for approximating the answer with multiplicative error $(1 +
\varepsilon)$. Second, we design three real-time algorithms for this problem.
Our Monte Carlo approximation algorithms for both additive and multiplicative
versions of the problem use $O(M)$ words of memory. Thus the obtained lower
bounds are asymptotically tight up to a logarithmic factor. The third algorithm
is deterministic and finds a longest palindrome exactly if it is short. This
algorithm can be run in parallel with a Monte Carlo algorithm to obtain better
results in practice. Overall, both the time and space complexity of finding a
longest palindrome in a stream are essentially settled.


title: Almost Engel linear groups

abstract:
  We prove that if a linear group $G$ is almost Engel, then $G$ is
finite-by-hypercentral. If $G$ is almost nil, then $G$ is finite-by-nilpotent.


title: Goodwillie calculus and Mackey functors

abstract:
  We show that the category of $n$-excisive functors from the $\infty$-category
of spectra to a target stable $\infty$-category $\mathbf{E}$ is equivalent to
the category of $\mathbf{E}$-valued Mackey functors on an indexing category
built from finite sets and surjections. This new classification of polynomial
functors arises from an investigation of the structure present on cross
effects. The path to this result involves a pair of surprising extension
theorems for polynomial functors and a discussion of some interesting topics in
semiadditive $\infty$- category theory, including a formula for the free
semiadditive $\infty$-category on an $\infty$-category.


title:
The Gould's Belt Distances Survey (GOBELINS) III. The distance to the
  Serpens/Aquila Molecular Complex

abstract:
  We report on new distances and proper motions to seven stars across the
Serpens/Aquila complex. The observations were obtained as part of the Gould's
Belt Distances Survey (GOBELINS) project between September 2013 and April 2016
with the Very Long Baseline Array (VLBA). One of our targets is the
proto-Herbig AeBe object EC 95, which is a binary system embedded in the
Serpens Core. For this system, we combined the GOBELINS observations with
previous VLBA data to cover a total period of ~8 years, and derive the orbital
elements and an updated source distance. The individual distances to sources in
the complex are fully consistent with each other, and the mean value
corresponds to a distance of $436.0\pm9.2$~pc for the Serpens/W40 complex.
Given this new evidence, we argue that Serpens Main, W40 and Serpens South are
physically associated and form a single cloud structure.


title: Tangled Splines

abstract:
  Extracting shape information from object bound- aries is a well studied
problem in vision, and has found tremen- dous use in applications like object
recognition. Conversely, studying the space of shapes represented by curves
satisfying certain constraints is also intriguing. In this paper, we model and
analyze the space of shapes represented by a 3D curve (space curve) formed by
connecting n pieces of quarter of a unit circle. Such a space curve is what we
call a Tangle, the name coming from a toy built on the same principle. We
provide two models for the shape space of n-link open and closed tangles, and
we show that tangles are a subset of trigonometric splines of a certain order.
We give algorithms for curve approximation using open/closed tangles, computing
geodesics on these shape spaces, and to find the deformation that takes one
given tangle to another given tangle, i.e., the Log map. The algorithms
provided yield tangles upto a small and acceptable tolerance, as shown by the
results given in the paper.


title: Asymptotically safe and free chiral theories with and without scalars

abstract:
  We unveil the dynamics of four dimensional chiral gauge-Yukawa theories
featuring several scalar degrees of freedom transforming according to distinct
representations of the underlying gauge group. We consider generalized
Georgi-Glashow and Bars-Yankielowicz theories. We determine, to the maximum
known order in perturbation theory, the phase diagram of these theories and
further disentangle their ultraviolet asymptotic nature according to whether
they are asymptotically free or safe. We therefore extend the number of
theories that are known to be fundamental in the Wilsonian sense to the case of
chiral gauge theories with scalars.


title: Single-particle excitation of core states in epitaxial silicene

abstract:
  Recent studies of core-level X-ray photoelectron spectroscopy (XPS) spectra
of silicene on ZrB$_2$(0001) were found to be inconsistent with the density of
states (DOS) of a planar-like structure that has been proposed as the ground
state by density functional theory (DFT). To resolve the discrepancy, a
reexamination of the XPS spectra and direct theoretical access of accurate
single-particle excitation energies are desired. By analyzing the XPS data
using symmetric Voigt functions, different binding energies and its sequence of
Si $2p$ orbitals can be assigned from previously reported ones where asymmetric
pseudo-Voigt functions are adopted. Theoretically, we have adopted an approach
developed very recently, which follows the sophisticated $\Delta$
self-consistent field ($\Delta$SCF) methods, to study the single-particle
excitation of core states. In the calculations, each single-particle energy and
the renormalized core-hole charge density are calculated straightforwardly via
two SCF calculations. By comparing the results, the theoretical core-level
absolute binding energies including the splitting due to spin-orbit coupling
are in good agreement with the observed high-resolution XPS spectra. The good
agreement not only resolves the puzzling discrepancy between experiment and
theory (DOS) but also advocates the success of DFT in describing many-body
interactions of electrons at the surface.


title: On smooth moduli space of Riemann surfaces

abstract:
  In this paper we study the smooth moduli space of closed Riemann surfaces.
This smooth moduli is an infinite cover of the usual moduli space
$\mathscr{M}_g$ of closed Riemann surfaces, and is identified with the Schottky
space of rank $g.$ The main theorem of the paper is: Closed Riemann surfaces
are uniformizable by Schottky groups of Hausdorff dimension less than one. This
work seem to be the only paper in literature to study question of Riemann
surface uniformization and its Hausdorff dimension. We develop new techniques
of rational norm of homological marking of Riemann surface and, decomposition
of probability measures to prove our result. As an application of our theorem
we have existence of period matrix of Riemann surface in coordinates of smooth
moduli space.

categories: math.GT math-ph math.CV math.DG math.GR math.MP


title: Compression of Quantum Multi-Prover Interactive Proofs

abstract:
  We present a protocol that transforms any quantum multi-prover interactive
proof into a nonlocal game in which questions consist of logarithmic number of
bits and answers of constant number of bits. As a corollary, this proves that
the promise problem corresponding to the approximation of the nonlocal value to
inverse polynomial accuracy is complete for QMIP*, and therefore NEXP-hard.
This establishes that nonlocal games are provably harder than classical games
without any complexity theory assumptions. Our result also indicates that gap
amplification for nonlocal games may be impossible in general and provides a
negative evidence for the possibility of the gap amplification approach to the
multi-prover variant of the quantum PCP conjecture.


title: The Contribution of Coronal Jets To The Solar Wind

abstract:
  Transient collimated plasma eruptions in the solar corona, commonly known as
coronal (or X-ray) jets, are among the most interesting manifestations of solar
activity. It has been suggested that these events contribute to the mass and
energy content of the corona and solar wind, but the extent of these
contributions remains uncertain. We have recently modeled the formation and
evolution of coronal jets using a three-dimensional (3D) magnetohydrodynamic
(MHD) code with thermodynamics in a large spherical domain that includes the
solar wind. Our model is coupled to 3D MHD flux-emergence simulations, i.e, we
use boundary conditions provided by such simulations to drive a time-dependent
coronal evolution. The model includes parametric coronal heating, radiative
losses, and thermal conduction, which enables us to simulate the dynamics and
plasma properties of coronal jets in a more realistic manner than done so far.
Here we employ these simulations to calculate the amount of mass and energy
transported by coronal jets into the outer corona and inner heliosphere. Based
on observed jet-occurrence rates, we then estimate the total contribution of
coronal jets to the mass and energy content of the solar wind to (0.4-3.0) %
and (0.3-1.0) %, respectively. Our results are largely consistent with the few
previous rough estimates obtained from observations, supporting the conjecture
that coronal jets provide only a small amount of mass and energy to the solar
wind. We emphasize, however, that more advanced observations and simulations
are needed to substantiate this conjecture.


title:
Semiclassical analysis of a magnetization plateau in a 2D frustrated
  ferrimagnet

abstract:
  We use a semiclassical large-$S$ expansion to study a plateau at $1/3$
saturation in the magnetization curve of a frustrated ferrimagnet on a
spatially anisotropic kagom\'{e} lattice. The spins have both ferromagnetic and
antiferromagnetic nearest-neighbor Heisenberg couplings, and a frustrating
next-nearest-neighbor coupling in one lattice direction. The magnetization
plateau appears at the classical level for a certain range of couplings, and
quantum fluctuations significantly broaden it at both ends. Near the region of
the phase diagram where the classical plateau destabilizes, we find an exotic
"chiral liquid" phase that preserves translational and $U(1)$ spin symmetry, in
which bound pairs of magnons with opposite spins are condensed. We show how
this state is obtained naturally from a relativistic field theory formulation.
We comment on the relevance of the model to the material
$\text{Cu}_3\text{V}_2\text{O}_7\text{(OH)}_2 \cdot 2\text{H}_2\text{O}$
(volborthite).


title: Products of several commutators in a Lie nilpotent associative algebra

abstract:
  Let $F$ be a field of characteristic $\ne 2,3$ and let $A$ be a unital
associative $F$-algebra. Define a left-normed commutator $[a_1, a_2, \dots ,
a_n]$ $(a_i \in A)$ recursively by $[a_1, a_2] = a_1 a_2 - a_2 a_1$, $[a_1,
\dots , a_{n-1}, a_n] = [[a_1, \dots , a_{n-1}], a_n]$ $(n \ge 3)$. For $n \ge
2$, let $T^{(n)} (A)$ be the two-sided ideal in $A$ generated by all
commutators $[a_1, a_2, \dots , a_n]$ ($a_i \in A )$. Define $T^{(1)} (A) = A$.
  Let $k, \ell$ be integers such that $k > 0$, $0 \le \ell \le k$. Let $m_1,
\dots , m_k$ be positive integers such that $\ell$ of them are odd and $k -
\ell $ of them are even. Let $N_{k \ell} = \sum_{i=1}^k m_i -2k + \ell + 2 $.
  The aim of the present note is to show that, for any positive integers $m_1,
\dots , m_k$, in general, \[ T^{(m_1)} (A) \dots T^{(m_k)} (A) \nsubseteq
T^{(N_{k \ell} +1)} (A). \] It is known that if $\ell < k$ (that is, if at
least one of $m_i$ is even) then, for each $A$, \begin{equation*}
\label{evenabstr} T^{(m_1)} (A) \dots T^{(m_k)} (A) \subseteq T^{(N_{k \ell} )}
(A) \end{equation*} so our result cannot be improved if $\ell <k$.
  Let $N_k = \sum_{i=1}^k m_i -k+1$. Recently Dangovski has proved that if
$m_1, \dots , m_k$ are any positive integers then, in general, \[ T^{(m_1)} (A)
\dots T^{(m_k)} (A) \nsubseteq T^{(N_k+1)} (A) . \] Since $ N_{k \ell} = N_k -
(k - \ell -1)$, Dangovski's result is stronger than ours if $\ell = k$ and is
weaker than ours if $\ell \le k-2$; if $\ell = k-1$ then $N_k = N_{k (k-1)}$ so
both results coincide. It is known that if $\ell = k$ (that is, if all $m_i$
are odd) then, for each $A$, \begin{equation*} \label{alloddabstr} T^{(m_1)}
(A) \dots T^{(m_k)} (A) \subseteq T^{(N_k)} (A) \end{equation*} so in this case
Dangovski's result cannot be improved.


title: Self-Learning Monte Carlo Method

abstract:
  Monte Carlo simulation is an unbiased numerical tool for studying classical
and quantum many-body systems. One of its bottlenecks is the lack of general
and efficient update algorithm for large size systems close to phase transition
or with strong frustrations, for which local updates perform badly. In this
work, we propose a new general-purpose Monte Carlo method, dubbed self-learning
Monte Carlo (SLMC), in which an efficient update algorithm is first learned
from the training data generated in trial simulations and then used to speed up
the actual simulation. We demonstrate the efficiency of SLMC in a spin model at
the phase transition point, achieving a 10-20 times speedup.


title: PCG-Based Game Design Patterns

abstract:
  People enjoy encounters with generative software, but rarely are they
encouraged to interact with, understand or engage with it. In this paper we
define the term 'PCG-based game', and explain how this concept follows on from
the idea of an AI-based game. We look at existing examples of games which
foreground their AI, put forward a methodology for designing PCG-based games,
describe some example case study designs for PCG-based games, and describe
lessons learned during this process of sketching and developing ideas.


title:
Scale-invariant helical magnetic field evolution and the duration of
  inflation

abstract:
  We consider a scale-invariant helical magnetic field generated during
inflation. We show that, if the mean magnetic helicity density of such a field
is measured, it can be used to determine a lower bound on the duration of
inflation. Upper bounds can be used to derive constraints on the minimal
duration of inflation if one assumes that the magnetic field generated during
inflation is helical. Using three-dimensional simulations, we show that an
initially scale-invariant field develops, which is similar both with and
without magnetic helicity. In the fully helical case, however, the magnetic
field appears to have a more pronounced folded structure.


title:
On the Global Dynamics of an Electroencephalographic Mean Field Model of
  the Neocortex

abstract:
  This paper investigates the global dynamics of a mean field model of the
electroencephalogram developed by Liley et al., 2002.
  The model is presented as a system of coupled ordinary and partial
differential equations with periodic boundary conditions.
  Existence, uniqueness, and regularity of weak and strong solutions of the
model are established in appropriate function spaces, and the associated
initial-boundary value problems are proved to be well-posed.
  Sufficient conditions are developed for the phase spaces of the model to
ensure nonnegativity of certain quantities in the model, as required by their
biophysical interpretation.
  It is shown that the semigroups of weak and strong solution operators possess
bounded absorbing sets for the entire range of biophysical values of the
parameters of the model.
  Challenges towards establishing a global attractor for the model are
discussed and it is shown that there exist parameter values for which the
constructed semidynamical systems do not possess a compact global attractor due
to the lack of the asymptotic compactness property.
  Finally, using the theoretical results of the paper, instructive insights are
provided into the complexity of the behavior of the model and computational
analysis of the model.


title:
Mode-locked pulse oscillation of a self-resonating enhancement optical
  cavity

abstract:
  A power enhancement optical cavity is a compelling means of realizing a
pulsed laser with a high peak power and high repetition frequency, which is not
feasible using a simple amplifier scheme. However, a precise feedback system is
necessary for maintaining the narrow resonance condition of the optical cavity;
this has become a major technical issue in developing such cavities. We have
developed a new approach that does not require any active feedback system, by
placing the cavity in the outer loop of a laser amplifier. We report on the
first demonstration of a mode-locked pulse oscillation using the new system.


title: Toward the Classification of Biangular Harmonic Frames

abstract:
  Equiangular tight frames (ETFs) and biangular tight frames (BTFs) - sets of
unit vectors with basis-like properties whose pairwise absolute inner products
admit exactly one or two values, respectively - are useful for many
applications. A well-understood class of ETFs are those which manifest as
harmonic frames - vector sets defined in terms of the characters of finite
abelian groups - because they are characterized by combinatorial objects called
difference sets.
  This work is dedicated to the study of the underlying combinatorial
structures of harmonic BTFs. We show that if a harmonic frame is generated by a
divisible difference set, a partial difference set or by a special structure
with certain Gauss summing properties - all three of which are generalizations
of difference sets that fall under the umbrella term "bidifference set" - then
it is either a BTF or an ETF. However, we also show that the relationship
between harmonic BTFs and bidifference sets is not as straightforward as the
correspondence between harmonic ETFs and difference sets, as there are examples
of bidifference sets that do not generate harmonic BTFs. In addition, we study
another class of combinatorial structures, the nested divisible difference
sets, which yields an example of a harmonic BTF that is not generated by a
bidifference set.


title:
On the Equivalence among Three Controllability Problems for a Networked
  System

abstract:
  A new proof is given for the mathematical equivalence among three $k$-sparse
controllability problems of a networked system, which plays key roles in
Olshevsky,2014, in the establishment of the NP-hardness of the associated
minimal controllability problems (MCP). Compared with the available ones, a
completely deterministic approach is adopted. Moreover, only primary algebraic
operations are utilized in all the derivations. These results enhance the
available conclusions about the NP-hardness of a MCP, and can also be directly
applied to the computational complexity analysis for a minimal observability
problem. In addition, the results of Olshevsky,2014, have also been extended to
situations in which there are also some other restrictions, such as bounded
element magnitude, etc., on the system input matrix.


title:
Analysis of the loss of boundary conditions for the diffusive
  Hamilton-Jacobi equation

abstract:
  We consider the diffusive Hamilton-Jacobi equation, with homogeneous
Dirichlet conditions and regular initial data. It is known from [Barles-DaLio,
2004] that the problem admits a unique, continuous, global viscosity solution,
which extends the classical solution in case gradient blowup occurs. We study
the question of the possible loss of boundary conditions after gradient blowup,
which seems to have remained an open problem till now.
  Somewhat surprisingly, our results show that the issue strongly depends on
the initial data and reveal a rather rich variety of phenomena. For any smooth
bounded domain, we construct initial data such that the loss of boundary
conditions occurs everywhere on the boundary, as well as initial data for which
no loss of boundary conditions occurs in spite of gradient blowup. Actually, we
show that the latter possibility is rather exceptional. More generally, we show
that the set of the points where boundary conditions are lost, can be
prescribed to be arbitrarily close to any given open subset of the boundary.


title:
Modeling the time-periodicity of in-degree distributions in scientific
  citation networks

abstract:
  In a range of citation networks, the in-degree distributions boast
time-periodicity---the distributions of citations per article published each
year present similar scale-free tails. This phenomenon can be regarded as a
consequence of the emergence of hot topics and the existence of the "burst"
phenomenon. With this inference considered, a geometric model based on our
previous study is established, in which the sizes of the influence zones of
nodes follow the same power-law distribution and decrease with their ages. The
model successfully reproduces the time-periodicity of the in-degree
distributions of the empirical data, and accounts for the presence of citation
burst as well. Moreover, a reasonable explanation for the emergence of the
scale-free tails by regarding the citation behavior between articles as a
"yes/no" experiment is presented. The model can also predict the
time-periodicity of the local clustering coefficients, which indicates that the
model is a good tool in researches on the evolutionary mechanism of citation
networks.


title: Pisot conjecture and Rauzy fractals

abstract:
  We provide a proof of Pisot conjecture, a classification problem in Ergodic
Theory on recurrent sequences generated by irreducible Pisot substitutions.


title: Context-Aware Online Learning for Course Recommendation of MOOC Big Data

abstract:
  The Massive Open Online Course (MOOC) has expanded significantly in recent
years. With the widespread of MOOC, the opportunity to study the fascinating
courses for free has attracted numerous people of diverse educational
backgrounds all over the world. In the big data era, a key research topic for
MOOC is how to mine the needed courses in the massive course databases in cloud
for each individual student accurately and rapidly as the number of courses is
increasing fleetly. In this respect, the key challenge is how to realize
personalized course recommendation as well as to reduce the computing and
storage costs for the tremendous course data. In this paper, we propose a big
data-supported, context-aware online learning-based course recommender system
that could handle the dynamic and infinitely massive datasets, which recommends
courses by using personalized context information and historical statistics.
The context-awareness takes the personal preferences into consideration, making
the recommendation suitable for people with different backgrounds. Besides, the
algorithm achieves the sublinear regret performance, which means it can
gradually recommend the mostly preferred and matched courses to students. In
addition, our storage module is expanded to the distributed-connected storage
nodes, where the devised algorithm can handle massive course storage problems
from heterogeneous sources of course datasets. Comparing to existing
algorithms, our proposed algorithms achieve the linear time complexity and
space complexity. Experiment results verify the superiority of our algorithms
when comparing with existing ones in the MOOC big data setting.


title: Skeletal Program Enumeration for Rigorous Compiler Testing

abstract:
  A program can be viewed as a syntactic structure P (syntactic skeleton)
parameterized by a collection of the identifiers V (variable names). This paper
introduces the skeletal program enumeration (SPE) problem: Given a fixed
syntactic skeleton P and a set of variables V , enumerate a set of programs P
exhibiting all possible variable usage patterns within P. It proposes an
effective realization of SPE for systematic, rigorous compiler testing by
leveraging three important observations: (1) Programs with different variable
usage patterns exhibit diverse control- and data-dependence information, and
help exploit different compiler optimizations and stress-test compilers; (2)
most real compiler bugs were revealed by small tests (i.e., small-sized P) ---
this "small-scope" observation opens up SPE for practical compiler validation;
and (3) SPE is exhaustive w.r.t. a given syntactic skeleton and variable set,
and thus can offer a level of guarantee that is absent from all existing
compiler testing techniques.
  The key challenge of SPE is how to eliminate the enormous amount of
equivalent programs w.r.t. $\alpha$-conversion. Our main technical contribution
is a novel algorithm for computing the canonical (and smallest) set of all
non-$\alpha$-equivalent programs. We have realized our SPE technique and
evaluated it using syntactic skeletons derived from GCC's testsuite. Our
evaluation results on testing GCC and Clang are extremely promising. In less
than six months, our approach has led to 217 confirmed bug reports, 104 of
which have already been fixed, and the majority are long latent bugs despite
the extensive prior efforts of automatically testing both compilers (e.g.,
Csmith and EMI). The results also show that our algorithm for enumerating
non-$\alpha$-equivalent programs provides six orders of magnitude reduction,
enabling processing the GCC test-suite in under a month.


title:
SN 1978K: An evolved supernova outside our Local Group detected at
  millimetre wavelengths

abstract:
  Supernova 1978K is one of the oldest-known examples of the class of Type IIn
supernovae that show evidence for strong interaction between the blast wave and
a dense, pre-existing circumstellar medium. Here we report detections of SN
1978K at both 34 GHz and 94 GHz, making it only the third extragalactic
supernova (after SN 1987A and SN 1996cr) to be detected at late-times at these
frequencies. We find SN 1978K to be >400 times more luminous than SN 1987A at
millimetre wavelengths in spite of the roughly nine year difference in ages,
highlighting the risk in adopting SN 1987A as a template for the evolution of
core-collapse supernovae in general. Additionally, from new VLBI observations
at 8.4 GHz, we measure a deconvolved diameter for SN 1978K of ~5 milli-arcsec,
and a corresponding average expansion velocity of <1500 km/s. These
observations provide independent evidence of an extremely dense circumstellar
medium surrounding the progenitor star.


title: Stabilizers, groups with f-generics in NTP2 and PRC fields

abstract:
  In this paper we develop three different subjects. We study and prove
alternative versions of Hrushovski's "Stabilizer Theorem", we generalize part
of the basic theory of definably amenable NIP groups to NTP2 theories, and
finally, we use all this machinery to study groups with f-generic types
definable in bounded PRC fields.


title:
FaceVR: Real-Time Facial Reenactment and Eye Gaze Control in Virtual
  Reality

abstract:
  We propose FaceVR, a novel image-based method that enables video
teleconferencing in VR based on self-reenactment. State-of-the-art face
tracking methods in the VR context are focused on the animation of rigged 3d
avatars. While they achieve good tracking performance the results look
cartoonish and not real. In contrast to these model-based approaches, FaceVR
enables VR teleconferencing using an image-based technique that results in
nearly photo-realistic outputs. The key component of FaceVR is a robust
algorithm to perform real-time facial motion capture of an actor who is wearing
a head-mounted display (HMD), as well as a new data-driven approach for eye
tracking from monocular videos. Based on reenactment of a prerecorded stereo
video of the person without the HMD, FaceVR incorporates photo-realistic
re-rendering in real time, thus allowing artificial modifications of face and
eye appearances. For instance, we can alter facial expressions or change gaze
directions in the prerecorded target video. In a live setup, we apply these
newly-introduced algorithmic components.


title:
Design and optimization of optical modulators based on
  graphene-on-silicon nitride microring resonators

abstract:
  In order to overcome the challenge of obtaining high modulation depth due to
weak graphene-light interaction, a graphene-on-silicon nitride (SiNx) microring
resonator based on graphene's gate-tunable optical conductivity is proposed and
studied. Geometrical parameters of graphene-on-SiNx waveguide are
systematically analyzed and optimized, yielding a loss tunability of 0.04
dB/{\mu}m and an effective index variation of 0.0022. We explicitly study the
interaction between graphene and a 40-{\mu}m-radius microring resonator, where
electro-absorptive and electro-refractive modulation are both taken into
account. By choosing appropriate graphene coverage and coupling coefficient, a
high modulation depth of over 40 dB with large fabrication tolerance is
obtained.


title: Determination of a structural break in a mean-reverting process

abstract:
  Determining accurately when regime and structural changes occur in various
time-series data is critical in many social and natural sciences. We develop
and show further the equivalence of two consistent estimation techniques in
locating the change point under the framework of a generalised version of the
Ornstein-Uhlehnbeck process. Our methods are based on the least sum of squared
error and the maximum log-likelihood approaches. The case where both the
existence and the location of the change point are unknown is investigated and
an informational methodology is employed to address these issues. Numerical
illustrations are presented to assess the performance of the methods.


title: A Root-Node Based Algebraic Multigrid Method

abstract:
  This paper provides a unified and detailed presentation of root-node style
algebraic multigrid (AMG). Algebraic multigrid is a popular and effective
iterative method for solving large, sparse linear systems that arise from
discretizing partial differential equations. However, while AMG is designed for
symmetric positive definite matrices (SPD), certain SPD problems, such as
anisotropic diffusion, are still not adequately addressed by existing methods.
Non-SPD problems pose an even greater challenge, and in practice AMG is often
not considered as a solver for such problems.
  The focus of this paper is on so-called root-node AMG, which can be viewed as
a combination of classical and aggregation-based multigrid. An algorithm for
root-node is outlined and a filtering strategy is developed, which is able to
control the cost of using root-node AMG, particularly on difficult problems.
New theoretical motivation is provided for root-node and energy-minimization as
applied to symmetric as well non-symmetric systems. Numerical results are then
presented demonstrating the robust ability of root-node to solve non-symmetric
problems, systems-based problems, and difficult SPD problems, including
strongly anisotropic diffusion, convection-diffusion, and upwind steady-state
transport, in a scalable manner. New, detailed estimates of the computational
cost of the setup and solve phase are given for each example, providing
additional support for root-node AMG over alternative methods.


title:
Multiple Instance Learning Convolutional Neural Networks for Object
  Recognition

abstract:
  Convolutional Neural Networks (CNN) have demon- strated its successful
applications in computer vision, speech recognition, and natural language
processing. For object recog- nition, CNNs might be limited by its strict label
requirement and an implicit assumption that images are supposed to be target-
object-dominated for optimal solutions. However, the labeling procedure,
necessitating laying out the locations of target ob- jects, is very tedious,
making high-quality large-scale dataset prohibitively expensive. Data
augmentation schemes are widely used when deep networks suffer the insufficient
training data problem. All the images produced through data augmentation share
the same label, which may be problematic since not all data augmentation
methods are label-preserving. In this paper, we propose a weakly supervised CNN
framework named Multiple Instance Learning Convolutional Neural Networks
(MILCNN) to solve this problem. We apply MILCNN framework to object recognition
and report state-of-the-art performance on three benchmark datasets: CIFAR10,
CIFAR100 and ILSVRC2015 classification dataset.


title: Visually pleasing knot projections in R

abstract:
  In this short article I introduce the knotR package, which creates two
dimensional knot diagrams optimized for visual appearance using the R
programming language. The knotR package is a systematic R-centric suite of
software for the creation of production-quality artwork of knot diagrams,
released under GPL2.


title:
Non-level semi-standard graded Cohen-Macaulay domain with $h$-vector
  $(h_0,h_1,h_2)$

abstract:
  Let $k$ be an algebraically closed field of characteristic 0, and $A$ a
Cohen-Macaulay graded domain with $A_0=k$. If $A$ is semi-standard graded
(i.e., $A$ is finitely generated as a $k[A_1]$-module), it has the $h$-vector
$(h_0, h_1, ..., h_s)$, which encodes the Hilbert function of $A$. From now on,
assume that $s=2$. It is known that if $A$ is standard graded (i.e.,
$A=k[A_1]$), then $A$ is level. We will show that, in the semi-standard case,
if $A$ is not level, then $h_1+1$ divides $h_2$. Conversely, for any positive
integers $h$ and $n$, there is a non-level $A$ with the $h$-vector $(1, h,
(h+1)n)$. Moreover, such examples can be constructed as Ehrhart rings
(equivalently, normal toric rings).


title: Equivariant compactifications of a nilpotent group by $G/P$

abstract:
  Let $G$ be a simple complex algebraic group, $P$ a parabolic subgroup of $G$
and $N$ the unipotent radical of $P.$ The so-called equivariant
compactification of $N$ by $G/P$ is given by an action of $N$ on $G/P$ with a
dense open orbit isomorphic to $N$. In this article, we investigate how many
such equivariant compactifications there exist. Our result says that there is a
unique equivariant compactification of $N$ by $G/P$, up to isomorphism, except
$\P^n$.


title: The Astropy Problem

abstract:
  The Astropy Project (http://astropy.org) is, in its own words, "a community
effort to develop a single core package for Astronomy in Python and foster
interoperability between Python astronomy packages." For five years this
project has been managed, written, and operated as a grassroots,
self-organized, almost entirely volunteer effort while the software is used by
the majority of the astronomical community. Despite this, the project has
always been and remains to this day effectively unfunded. Further, contributors
receive little or no formal recognition for creating and supporting what is now
critical software. This paper explores the problem in detail, outlines possible
solutions to correct this, and presents a few suggestions on how to address the
sustainability of general purpose astronomical software.


title:
Doping-induced perturbation and percolation in the two-dimensional
  Anderson lattice

abstract:
  We examine the doping effects in the two-dimensional periodic Anderson model
using the determinant Quantum Monte Carlo (DQMC) method. We observe bound
states around the Kondo hole site and find that the heavy electron states are
destroyed at the nearest-neighbor sites. Our results show no clear sign of
hybridization oscillation predicted in previous mean-field calculations. We
further study the electron transport with increasing doping and as a function
of temperature and obtain a critical doping at x_c~0.6 that marks a transition
from the Kondo insulator regime to the single-ion Kondo regime. The value of
x_c is in good agreement with the predicted threshold for the site percolation.
Our results confirm the percolative nature of the insulator-metal transition
observed in doped Kondo insulators.


title: Quantum Violation of Fluctuation-Dissipation Theorem

abstract:
  We study quantum measurements of temporal equilibrium fluctuations in
macroscopic quantum systems. It is shown that the fluctuation-dissipation
theorem, as a relation between observed quantities, is partially violated in
quantum systems, even if measurements are made in an ideal way that emulates
classical ideal measurements as closely as possible. This is a genuine quantum
effect that survives on a macroscopic scale. We also show that the state
realized during measurements of temporal equilibrium fluctuations is a
`squeezed equilibrium state,' which is macroscopically identical to the
pre-measurement equilibrium state but is squeezed by the measurement. It is a
time-evolving state, in which macrovariables fluctuate and relax. We also
explain some of subtle but important points, careless treatments of which often
lead to unphysical results, of the linear response theory.


title: Active Fault Tolerant Flight Control System Design - A UAV Case Study

abstract:
  Fault tolerance is achieved through multiply redundant hardware systems in
large civil aircraft. This means of achieving fault tolerance is infeasible for
small compact unmanned aerial vehicles. In this paper we apply a fault tolerant
control system which exploits analytical redundancy rather than hardware
redundancy to an actual UAV model currently in operation via model-in-the-loop
simulation. The fault tolerant control system comprises a nonlinear model
predictive controller integrated with an unscented Kalman filter for fault
detection and identification. The results show that our fault tolerant control
system design is able to identify engine failure within seconds of fault
occurrence and distribute control authority to the healthy actuators to
maintain safe flight.


title: Regularity of aperiodic minimal subshifts

abstract:
  At the turn of this century Durand, and Lagarias and Pleasants established
that key features of minimal subshifts (and their higher-dimensional analogues)
to be studied are linearly repetitive, repulsive and power free. Since then,
generalisations and extensions of these features, namely $\alpha$-repetitive,
$\alpha$-repulsive and $\alpha$-finite ($\alpha \geq 1$), have been introduced
and studied. We establish the equivalence of $\alpha$-repulsive and
$\alpha$-finite for general subshifts over finite alphabets. Further, we
studied a family of aperiodic minimal subshifts stemming from Grigorchuk's
infinite $2$-group $G$. In particular, we show that these subshifts provide
examples that demonstrate $\alpha$-repulsive (and hence $\alpha$-finite) is not
equivalent to $\alpha$-repetitive, for $\alpha > 1$. We also give necessary and
sufficient conditions for these subshifts to be $\alpha$-repetitive, and
$\alpha$-repulsive (and hence $\alpha$-finite). Moreover, we obtain an explicit
formula for their complexity functions from which we deduce that they are
uniquely ergodic.


title:
Navigational Instruction Generation as Inverse Reinforcement Learning
  with Neural Machine Translation

abstract:
  Modern robotics applications that involve human-robot interaction require
robots to be able to communicate with humans seamlessly and effectively.
Natural language provides a flexible and efficient medium through which robots
can exchange information with their human partners. Significant advancements
have been made in developing robots capable of interpreting free-form
instructions, but less attention has been devoted to endowing robots with the
ability to generate natural language. We propose a navigational guide model
that enables robots to generate natural language instructions that allow humans
to navigate a priori unknown environments. We first decide which information to
share with the user according to their preferences, using a policy trained from
human demonstrations via inverse reinforcement learning. We then "translate"
this information into a natural language instruction using a neural
sequence-to-sequence model that learns to generate free-form instructions from
natural language corpora. We evaluate our method on a benchmark route
instruction dataset and achieve a BLEU score of 72.18% when compared to
human-generated reference instructions. We additionally conduct navigation
experiments with human participants that demonstrate that our method generates
instructions that people follow as accurately and easily as those produced by
humans.


title:
Long Short-Term Memory based Convolutional Recurrent Neural Networks for
  Large Vocabulary Speech Recognition

abstract:
  Long short-term memory (LSTM) recurrent neural networks (RNNs) have been
shown to give state-of-the-art performance on many speech recognition tasks, as
they are able to provide the learned dynamically changing contextual window of
all sequence history. On the other hand, the convolutional neural networks
(CNNs) have brought significant improvements to deep feed-forward neural
networks (FFNNs), as they are able to better reduce spectral variation in the
input signal. In this paper, a network architecture called as convolutional
recurrent neural network (CRNN) is proposed by combining the CNN and LSTM RNN.
In the proposed CRNNs, each speech frame, without adjacent context frames, is
organized as a number of local feature patches along the frequency axis, and
then a LSTM network is performed on each feature patch along the time axis. We
train and compare FFNNs, LSTM RNNs and the proposed LSTM CRNNs at various
number of configurations. Experimental results show that the LSTM CRNNs can
exceed state-of-the-art speech recognition performance.


title: Renormalization group flows in gauge-gravity duality

abstract:
  This is a copy of the 2009 Princeton University thesis which examined various
aspects of gauge/gravity duality, including renormalization group flows, phase
transitions of the holographic entanglement entropy, and instabilities
associated with the breaking of supersymmetry. Chapter 5 contains new
unpublished material on various instabilities of the weakly curved
non-supersymmetric $AdS_4$ backgrounds of M-theory.