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Title: HONE: Higher-Order Network Embeddings,
Abstract: This paper describes a general framework for learning Higher-Order Network
Embeddings (HONE) from graph data based on network motifs. The HONE framework
is highly expressive and flexible with many interchangeable components. The
experimental results demonstrate the effectiveness of learning higher-order
network representations. In all cases, HONE outperforms recent embedding
methods that are unable to capture higher-order structures with a mean relative
gain in AUC of $19\%$ (and up to $75\%$ gain) across a wide variety of networks
and embedding methods. | [
1,
0,
0,
1,
0,
0
] | [
"Computer Science",
"Mathematics"
] |
Title: Linear Progress with Exponential Decay in Weakly Hyperbolic Groups,
Abstract: A random walk $w_n$ on a separable, geodesic hyperbolic metric space $X$
converges to the boundary $\partial X$ with probability one when the step
distribution supports two independent loxodromics. In particular, the random
walk makes positive linear progress. Progress is known to be linear with
exponential decay when (1) the step distribution has exponential tail and (2)
the action on $X$ is acylindrical. We extend exponential decay to the
non-acylindrical case. | [
0,
0,
1,
0,
0,
0
] | [
"Mathematics"
] |
Title: Talbot-enhanced, maximum-visibility imaging of condensate interference,
Abstract: Nearly two centuries ago Talbot first observed the fascinating effect whereby
light propagating through a periodic structure generates a `carpet' of image
revivals in the near field. Here we report the first observation of the spatial
Talbot effect for light interacting with periodic Bose-Einstein condensate
interference fringes. The Talbot effect can lead to dramatic loss of fringe
visibility in images, degrading precision interferometry, however we
demonstrate how the effect can also be used as a tool to enhance visibility, as
well as extend the useful focal range of matter wave detection systems by
orders of magnitude. We show that negative optical densities arise from
matter-wave induced lensing of detuned imaging light -- yielding
Talbot-enhanced single-shot interference visibility of >135% compared to the
ideal visibility for resonant light. | [
0,
1,
0,
0,
0,
0
] | [
"Physics"
] |
Title: Hydrogen bonding characterization in water and small molecules,
Abstract: The prototypical Hydrogen bond in water dimer and Hydrogen bonds in the
protonated water dimer, in other small molecules, in water cyclic clusters, and
in ice, covering a wide range of bond strengths, are theoretically investigated
by first-principles calculations based on the Density Functional Theory,
considering a standard Generalized Gradient Approximation functional but also,
for the water dimer, hybrid and van-der-Waals corrected functionals. We compute
structural, energetic, and electrostatic (induced molecular dipole moments)
properties. In particular, Hydrogen bonds are characterized in terms of
differential electron densities distributions and profiles, and of the shifts
of the centres of Maximally localized Wannier Functions. The information from
the latter quantities can be conveyed into a single geometric bonding parameter
that appears to be correlated to the Mayer bond order parameter and can be
taken as an estimate of the covalent contribution to the Hydrogen bond. By
considering the cyclic water hexamer and the hexagonal phase of ice we also
elucidate the importance of cooperative/anticooperative effects in
Hydrogen-bonding formation. | [
0,
1,
0,
0,
0,
0
] | [
"Physics",
"Chemistry"
] |
Title: NOOP: A Domain-Theoretic Model of Nominally-Typed OOP,
Abstract: The majority of industrial-strength object-oriented (OO) software is written
using nominally-typed OO programming languages. Extant domain-theoretic models
of OOP developed to analyze OO type systems miss, however, a crucial feature of
these mainstream OO languages: nominality. This paper presents the construction
of NOOP as the first domain-theoretic model of OOP that includes full
class/type names information found in nominally-typed OOP. Inclusion of nominal
information in objects of NOOP and asserting that type inheritance in
statically-typed OO programming languages is an inherently nominal notion allow
readily proving that type inheritance and subtyping are completely identified
in these languages. This conclusion is in full agreement with intuitions of
developers and language designers of these OO languages, and contrary to the
belief that "inheritance is not subtyping," which came from assuming
non-nominal (a.k.a., structural) models of OOP.
To motivate the construction of NOOP, this paper briefly presents the
benefits of nominal-typing to mainstream OO developers and OO language
designers, as compared to structural-typing. After presenting NOOP, the paper
further briefly compares NOOP to the most widely known domain-theoretic models
of OOP. Leveraging the development of NOOP, the comparisons presented in this
paper provide clear, brief and precise technical and mathematical accounts for
the relation between nominal and structural OO type systems. NOOP, thus,
provides a firmer semantic foundation for analyzing and progressing
nominally-typed OO programming languages. | [
1,
0,
0,
0,
0,
0
] | [
"Computer Science",
"Mathematics"
] |
Title: Modelling wave-induced sea ice breakup in the marginal ice zone,
Abstract: A model of ice floe breakup under ocean wave forcing in the marginal ice zone
(MIZ) is proposed to investigate how floe size distribution (FSD) evolves under
repeated wave breakup events. A three-dimensional linear model of ocean wave
scattering by a finite array of compliant circular ice floes is coupled to a
flexural failure model, which breaks a floe into two floes provided the
two-dimensional stress field satisfies a breakup criterion. A closed-feedback
loop algorithm is devised, which (i)~solves wave scattering problem for a given
FSD under time-harmonic plane wave forcing, (ii)~computes the stress field in
all the floes, (iii)~fractures the floes satisfying the breakup criterion and
(iv)~generates an updated FSD, initialising the geometry for the next iteration
of the loop.The FSD after 50 breakup events is uni-modal and near normal, or
bi-modal. Multiple scattering is found to enhance breakup for long waves and
thin ice, but to reduce breakup for short waves and thick ice. A breakup front
marches forward in the latter regime, as wave-induced fracture weakens the ice
cover allowing waves to travel deeper into the MIZ. | [
0,
1,
0,
0,
0,
0
] | [
"Physics"
] |
Title: Safe Open-Loop Strategies for Handling Intermittent Communications in Multi-Robot Systems,
Abstract: In multi-robot systems where a central decision maker is specifying the
movement of each individual robot, a communication failure can severely impair
the performance of the system. This paper develops a motion strategy that
allows robots to safely handle critical communication failures for such
multi-robot architectures. For each robot, the proposed algorithm computes a
time horizon over which collisions with other robots are guaranteed not to
occur. These safe time horizons are included in the commands being transmitted
to the individual robots. In the event of a communication failure, the robots
execute the last received velocity commands for the corresponding safe time
horizons leading to a provably safe open-loop motion strategy. The resulting
algorithm is computationally effective and is agnostic to the task that the
robots are performing. The efficacy of the strategy is verified in simulation
as well as on a team of differential-drive mobile robots. | [
1,
0,
0,
0,
0,
0
] | [
"Computer Science",
"Robotics"
] |
Title: Scientific co-authorship networks,
Abstract: The paper addresses the stability of the co-authorship networks in time. The
analysis is done on the networks of Slovenian researchers in two time periods
(1991-2000 and 2001-2010). Two researchers are linked if they published at
least one scientific bibliographic unit in a given time period. As proposed by
Kronegger et al. (2011), the global network structures are examined by
generalized blockmodeling with the assumed
multi-core--semi-periphery--periphery blockmodel type. The term core denotes a
group of researchers who published together in a systematic way with each
other.
The obtained blockmodels are comprehensively analyzed by visualizations and
through considering several statistics regarding the global network structure.
To measure the stability of the obtained blockmodels, different adjusted
modified Rand and Wallace indices are applied. Those enable to distinguish
between the splitting and merging of cores when operationalizing the stability
of cores. Also, the adjusted modified indices can be used when new researchers
occur in the second time period (newcomers) and when some researchers are no
longer present in the second time period (departures). The research disciplines
are described and clustered according to the values of these indices.
Considering the obtained clusters, the sources of instability of the research
disciplines are studied (e.g., merging or splitting of cores, newcomers or
departures). Furthermore, the differences in the stability of the obtained
cores on the level of scientific disciplines are studied by linear regression
analysis where some personal characteristics of the researchers (e.g., age,
gender), are also considered. | [
1,
0,
0,
1,
0,
0
] | [
"Statistics",
"Quantitative Biology"
] |
Title: Proofs as Relational Invariants of Synthesized Execution Grammars,
Abstract: The automatic verification of programs that maintain unbounded low-level data
structures is a critical and open problem. Analyzers and verifiers developed in
previous work can synthesize invariants that only describe data structures of
heavily restricted forms, or require an analyst to provide predicates over
program data and structure that are used in a synthesized proof of correctness.
In this work, we introduce a novel automatic safety verifier of programs that
maintain low-level data structures, named LTTP. LTTP synthesizes proofs of
program safety represented as a grammar of a given program's control paths,
annotated with invariants that relate program state at distinct points within
its path of execution. LTTP synthesizes such proofs completely automatically,
using a novel inductive-synthesis algorithm.
We have implemented LTTP as a verifier for JVM bytecode and applied it to
verify the safety of a collection of verification benchmarks. Our results
demonstrate that LTTP can be applied to automatically verify the safety of
programs that are beyond the scope of previously-developed verifiers. | [
1,
0,
0,
0,
0,
0
] | [
"Computer Science",
"Mathematics"
] |
Title: Coastal flood implications of 1.5 °C, 2.0 °C, and 2.5 °C temperature stabilization targets in the 21st and 22nd century,
Abstract: Sea-level rise (SLR) is magnifying the frequency and severity of coastal
flooding. The rate and amount of global mean sea-level (GMSL) rise is a
function of the trajectory of global mean surface temperature (GMST).
Therefore, temperature stabilization targets (e.g., 1.5 °C and 2.0 °C
of warming above pre-industrial levels, as from the Paris Agreement) have
important implications for coastal flood risk. Here, we assess differences in
the return periods of coastal floods at a global network of tide gauges between
scenarios that stabilize GMST warming at 1.5 °C, 2.0 °C, and 2.5
°C above pre-industrial levels. We employ probabilistic, localized SLR
projections and long-term hourly tide gauge records to construct estimates of
the return levels of current and future flood heights for the 21st and 22nd
centuries. By 2100, under 1.5 °C, 2.0 °C, and 2.5 °C GMST
stabilization, median GMSL is projected to rise 47 cm with a very likely range
of 28-82 cm (90% probability), 55 cm (very likely 30-94 cm), and 58 cm (very
likely 36-93 cm), respectively. As an independent comparison, a semi-empirical
sea level model calibrated to temperature and GMSL over the past two millennia
estimates median GMSL will rise within < 13% of these projections. By 2150,
relative to the 2.0 °C scenario, GMST stabilization of 1.5 °C
inundates roughly 5 million fewer inhabitants that currently occupy lands,
including 40,000 fewer individuals currently residing in Small Island
Developing States. Relative to a 2.0 °C scenario, the reduction in the
amplification of the frequency of the 100-yr flood arising from a 1.5 °C
GMST stabilization is greatest in the eastern United States and in Europe, with
flood frequency amplification being reduced by about half. | [
0,
1,
0,
0,
0,
0
] | [
"Physics",
"Statistics"
] |
Title: Unsupervised Learning of Disentangled and Interpretable Representations from Sequential Data,
Abstract: We present a factorized hierarchical variational autoencoder, which learns
disentangled and interpretable representations from sequential data without
supervision. Specifically, we exploit the multi-scale nature of information in
sequential data by formulating it explicitly within a factorized hierarchical
graphical model that imposes sequence-dependent priors and sequence-independent
priors to different sets of latent variables. The model is evaluated on two
speech corpora to demonstrate, qualitatively, its ability to transform speakers
or linguistic content by manipulating different sets of latent variables; and
quantitatively, its ability to outperform an i-vector baseline for speaker
verification and reduce the word error rate by as much as 35% in mismatched
train/test scenarios for automatic speech recognition tasks. | [
1,
0,
0,
1,
0,
0
] | [
"Computer Science",
"Statistics"
] |
Title: Room-Temperature Ionic Liquids Meet Bio-Membranes: the State-of-the- Art,
Abstract: Room-temperature ionic liquids (RTIL) are a new class of organic salts whose
melting temperature falls below the conventional limit of 100C. Their low vapor
pressure, moreover, has made these ionic compounds the solvents of choice of
the so-called green chemistry. For these and other peculiar characteristics,
they are increasingly used in industrial applications. However, studies of
their interaction with living organisms have highlighted mild to severe health
hazards. Since their cytotoxicity shows a positive correlation with their
lipo-philicity, several chemical-physical studies of their interaction with
biomembranes have been carried out in the last few years, aiming to identify
the microscopic mechanisms behind their toxicity. Cation chain length and anion
nature have been seen to affect the lipo-philicity and, in turn, the toxicity
of RTILs. The emerging picture, however, raises new questions, points to the
need to assess toxicity on a case-by-case basis, but also suggests a potential
positive role of RTILs in pharmacology, bio-medicine, and, more in general,
bio-nano-technology. Here, we review this new subject of research, and comment
on the future and the potential importance of this new field of study. | [
0,
1,
0,
0,
0,
0
] | [
"Quantitative Biology"
] |
Title: HyperMinHash: MinHash in LogLog space,
Abstract: In this extended abstract, we describe and analyze a lossy compression of
MinHash from buckets of size $O(\log n)$ to buckets of size $O(\log\log n)$ by
encoding using floating-point notation. This new compressed sketch, which we
call HyperMinHash, as we build off a HyperLogLog scaffold, can be used as a
drop-in replacement of MinHash. Unlike comparable Jaccard index fingerprinting
algorithms in sub-logarithmic space (such as b-bit MinHash), HyperMinHash
retains MinHash's features of streaming updates, unions, and cardinality
estimation. For a multiplicative approximation error $1+ \epsilon$ on a Jaccard
index $ t $, given a random oracle, HyperMinHash needs $O\left(\epsilon^{-2}
\left( \log\log n + \log \frac{1}{ t \epsilon} \right)\right)$ space.
HyperMinHash allows estimating Jaccard indices of 0.01 for set cardinalities on
the order of $10^{19}$ with relative error of around 10\% using 64KiB of
memory; MinHash can only estimate Jaccard indices for cardinalities of
$10^{10}$ with the same memory consumption. | [
1,
0,
0,
0,
0,
0
] | [
"Computer Science",
"Statistics"
] |
Title: Asynchronous stochastic price pump,
Abstract: We propose a model for equity trading in a population of agents where each
agent acts to achieve his or her target stock-to-bond ratio, and, as a feedback
mechanism, follows a market adaptive strategy. In this model only a fraction of
agents participates in buying and selling stock during a trading period, while
the rest of the group accepts the newly set price. Using numerical simulations
we show that the stochastic process settles on a stationary regime for the
returns. The mean return can be greater or less than the return on the bond and
it is determined by the parameters of the adaptive mechanism. When the number
of interacting agents is fixed, the distribution of the returns follows the
log-normal density. In this case, we give an analytic formula for the mean rate
of return in terms of the rate of change of agents' risk levels and confirm the
formula by numerical simulations. However, when the number of interacting
agents per period is random, the distribution of returns can significantly
deviate from the log-normal, especially as the variance of the distribution for
the number of interacting agents increases. | [
0,
0,
0,
0,
0,
1
] | [
"Quantitative Finance",
"Statistics"
] |
Title: Improving Bi-directional Generation between Different Modalities with Variational Autoencoders,
Abstract: We investigate deep generative models that can exchange multiple modalities
bi-directionally, e.g., generating images from corresponding texts and vice
versa. A major approach to achieve this objective is to train a model that
integrates all the information of different modalities into a joint
representation and then to generate one modality from the corresponding other
modality via this joint representation. We simply applied this approach to
variational autoencoders (VAEs), which we call a joint multimodal variational
autoencoder (JMVAE). However, we found that when this model attempts to
generate a large dimensional modality missing at the input, the joint
representation collapses and this modality cannot be generated successfully.
Furthermore, we confirmed that this difficulty cannot be resolved even using a
known solution. Therefore, in this study, we propose two models to prevent this
difficulty: JMVAE-kl and JMVAE-h. Results of our experiments demonstrate that
these methods can prevent the difficulty above and that they generate
modalities bi-directionally with equal or higher likelihood than conventional
VAE methods, which generate in only one direction. Moreover, we confirm that
these methods can obtain the joint representation appropriately, so that they
can generate various variations of modality by moving over the joint
representation or changing the value of another modality. | [
0,
0,
0,
1,
0,
0
] | [
"Computer Science",
"Statistics"
] |
Title: Matching neural paths: transfer from recognition to correspondence search,
Abstract: Many machine learning tasks require finding per-part correspondences between
objects. In this work we focus on low-level correspondences - a highly
ambiguous matching problem. We propose to use a hierarchical semantic
representation of the objects, coming from a convolutional neural network, to
solve this ambiguity. Training it for low-level correspondence prediction
directly might not be an option in some domains where the ground-truth
correspondences are hard to obtain. We show how transfer from recognition can
be used to avoid such training. Our idea is to mark parts as "matching" if
their features are close to each other at all the levels of convolutional
feature hierarchy (neural paths). Although the overall number of such paths is
exponential in the number of layers, we propose a polynomial algorithm for
aggregating all of them in a single backward pass. The empirical validation is
done on the task of stereo correspondence and demonstrates that we achieve
competitive results among the methods which do not use labeled target domain
data. | [
1,
0,
0,
0,
0,
0
] | [
"Computer Science",
"Statistics"
] |
Title: On the affine random walk on the torus,
Abstract: Let $\mu$ be a borelian probability measure on
$\mathbf{G}:=\mathrm{SL}_d(\mathbb{Z}) \ltimes \mathbb{T}^d$. Define, for $x\in
\mathbb{T}^d$, a random walk starting at $x$ denoting for $n\in \mathbb{N}$, \[
\left\{\begin{array}{rcl} X_0 &=&x\\ X_{n+1} &=& a_{n+1} X_n + b_{n+1}
\end{array}\right. \] where $((a_n,b_n))\in \mathbf{G}^\mathbb{N}$ is an iid
sequence of law $\mu$.
Then, we denote by $\mathbb{P}_x$ the measure on $(\mathbb{T}^d)^\mathbb{N}$
that is the image of $\mu^{\otimes \mathbb{N}}$ by the map $\left((g_n) \mapsto
(x,g_1 x, g_2 g_1 x, \dots , g_n \dots g_1 x, \dots)\right)$ and for any
$\varphi \in \mathrm{L}^1((\mathbb{T}^d)^\mathbb{N}, \mathbb{P}_x)$, we set
$\mathbb{E}_x \varphi((X_n)) = \int \varphi((X_n))
\mathrm{d}\mathbb{P}_x((X_n))$.
Bourgain, Furmann, Lindenstrauss and Mozes studied this random walk when
$\mu$ is concentrated on $\mathrm{SL}_d(\mathbb{Z}) \ltimes\{0\}$ and this
allowed us to study, for any hölder-continuous function $f$ on the torus, the
sequence $(f(X_n))$ when $x$ is not too well approximable by rational points.
In this article, we are interested in the case where $\mu$ is not
concentrated on $\mathrm{SL}_d(\mathbb{Z}) \ltimes \mathbb{Q}^d/\mathbb{Z}^d$
and we prove that, under assumptions on the group spanned by the support of
$\mu$, the Lebesgue's measure $\nu$ on the torus is the only stationary
probability measure and that for any hölder-continuous function $f$ on the
torus, $\mathbb{E}_x f(X_n)$ converges exponentially fast to $\int
f\mathrm{d}\nu$.
Then, we use this to prove the law of large numbers, a non-concentration
inequality, the functional central limit theorem and it's almost-sure version
for the sequence $(f(X_n))$.
In the appendix, we state a non-concentration inequality for products of
random matrices without any irreducibility assumption. | [
0,
0,
1,
0,
0,
0
] | [
"Mathematics",
"Statistics"
] |
Title: Neutral evolution and turnover over centuries of English word popularity,
Abstract: Here we test Neutral models against the evolution of English word frequency
and vocabulary at the population scale, as recorded in annual word frequencies
from three centuries of English language books. Against these data, we test
both static and dynamic predictions of two neutral models, including the
relation between corpus size and vocabulary size, frequency distributions, and
turnover within those frequency distributions. Although a commonly used Neutral
model fails to replicate all these emergent properties at once, we find that
modified two-stage Neutral model does replicate the static and dynamic
properties of the corpus data. This two-stage model is meant to represent a
relatively small corpus (population) of English books, analogous to a `canon',
sampled by an exponentially increasing corpus of books in the wider population
of authors. More broadly, this mode -- a smaller neutral model within a larger
neutral model -- could represent more broadly those situations where mass
attention is focused on a small subset of the cultural variants. | [
1,
1,
0,
0,
0,
0
] | [
"Quantitative Biology",
"Statistics"
] |
Title: On Statistically-Secure Quantum Homomorphic Encryption,
Abstract: Homomorphic encryption is an encryption scheme that allows computations to be
evaluated on encrypted inputs without knowledge of their raw messages. Recently
Ouyang et al. constructed a quantum homomorphic encryption (QHE) scheme for
Clifford circuits with statistical security (or information-theoretic security
(IT-security)). It is desired to see whether an
information-theoretically-secure (ITS) quantum FHE exists. If not, what other
nontrivial class of quantum circuits can be homomorphically evaluated with
IT-security? We provide a limitation for the first question that an ITS quantum
FHE necessarily incurs exponential overhead. As for the second one, we propose
a QHE scheme for the instantaneous quantum polynomial-time (IQP) circuits. Our
QHE scheme for IQP circuits follows from the one-time pad. | [
1,
0,
0,
0,
0,
0
] | [
"Computer Science",
"Physics"
] |
Title: Quantum torus algebras and B(C) type Toda systems,
Abstract: In this paper, we construct a new even constrained B(C) type Toda hierarchy
and derive its B(C) type Block type additional symmetry. Also we generalize the
B(C) type Toda hierarchy to the $N$-component B(C) type Toda hierarchy which is
proved to have symmetries of a coupled $\bigotimes^NQT_+ $ algebra ( $N$-folds
direct product of the positive half of the quantum torus algebra $QT$). | [
0,
1,
1,
0,
0,
0
] | [
"Mathematics",
"Physics"
] |
Title: A Decidable Intuitionistic Temporal Logic,
Abstract: We introduce the logic $\sf ITL^e$, an intuitionistic temporal logic based on
structures $(W,\preccurlyeq,S)$, where $\preccurlyeq$ is used to interpret
intuitionistic implication and $S$ is a $\preccurlyeq$-monotone function used
to interpret temporal modalities. Our main result is that the satisfiability
and validity problems for $\sf ITL^e$ are decidable. We prove this by showing
that the logic enjoys the strong finite model property. In contrast, we also
consider a `persistent' version of the logic, $\sf ITL^p$, whose models are
similar to Cartesian products. We prove that, unlike $\sf ITL^e$, $\sf ITL^p$
does not have the finite model property. | [
0,
0,
1,
0,
0,
0
] | [
"Computer Science",
"Mathematics"
] |
Title: A simple proof that the $(n^2-1)$-puzzle is hard,
Abstract: The 15 puzzle is a classic reconfiguration puzzle with fifteen uniquely
labeled unit squares within a $4 \times 4$ board in which the goal is to slide
the squares (without ever overlapping) into a target configuration. By
generalizing the puzzle to an $n \times n$ board with $n^2-1$ squares, we can
study the computational complexity of problems related to the puzzle; in
particular, we consider the problem of determining whether a given end
configuration can be reached from a given start configuration via at most a
given number of moves. This problem was shown NP-complete in Ratner and Warmuth
(1990). We provide an alternative simpler proof of this fact by reduction from
the rectilinear Steiner tree problem. | [
1,
0,
0,
0,
0,
0
] | [
"Computer Science",
"Mathematics"
] |
Title: Is Proxima Centauri b habitable? -- A study of atmospheric loss,
Abstract: We address the important question of whether the newly discovered exoplanet,
Proxima Centauri b (PCb), is capable of retaining an atmosphere over long
periods of time. This is done by adapting a sophisticated multi-species MHD
model originally developed for Venus and Mars, and computing the ion escape
losses from PCb. The results suggest that the ion escape rates are about two
orders of magnitude higher than the terrestrial planets of our Solar system if
PCb is unmagnetized. In contrast, if the planet does have an intrinsic dipole
magnetic field, the rates are lowered for certain values of the stellar wind
dynamic pressure, but they are still higher than the observed values for our
Solar system's terrestrial planets. These results must be interpreted with due
caution, since most of the relevant parameters for PCb remain partly or wholly
unknown. | [
0,
1,
0,
0,
0,
0
] | [
"Physics",
"Quantitative Biology"
] |
Title: A Geometric Perspective on the Power of Principal Component Association Tests in Multiple Phenotype Studies,
Abstract: Joint analysis of multiple phenotypes can increase statistical power in
genetic association studies. Principal component analysis, as a popular
dimension reduction method, especially when the number of phenotypes is
high-dimensional, has been proposed to analyze multiple correlated phenotypes.
It has been empirically observed that the first PC, which summarizes the
largest amount of variance, can be less powerful than higher order PCs and
other commonly used methods in detecting genetic association signals. In this
paper, we investigate the properties of PCA-based multiple phenotype analysis
from a geometric perspective by introducing a novel concept called principal
angle. A particular PC is powerful if its principal angle is $0^o$ and is
powerless if its principal angle is $90^o$. Without prior knowledge about the
true principal angle, each PC can be powerless. We propose linear, non-linear
and data-adaptive omnibus tests by combining PCs. We show that the omnibus PC
test is robust and powerful in a wide range of scenarios. We study the
properties of the proposed methods using power analysis and eigen-analysis. The
subtle differences and close connections between these combined PC methods are
illustrated graphically in terms of their rejection boundaries. Our proposed
tests have convex acceptance regions and hence are admissible. The $p$-values
for the proposed tests can be efficiently calculated analytically and the
proposed tests have been implemented in a publicly available R package {\it
MPAT}. We conduct simulation studies in both low and high dimensional settings
with various signal vectors and correlation structures. We apply the proposed
tests to the joint analysis of metabolic syndrome related phenotypes with data
sets collected from four international consortia to demonstrate the
effectiveness of the proposed combined PC testing procedures. | [
0,
0,
0,
1,
0,
0
] | [
"Statistics",
"Mathematics",
"Quantitative Biology"
] |
Title: Development of ICA and IVA Algorithms with Application to Medical Image Analysis,
Abstract: Independent component analysis (ICA) is a widely used BSS method that can
uniquely achieve source recovery, subject to only scaling and permutation
ambiguities, through the assumption of statistical independence on the part of
the latent sources. Independent vector analysis (IVA) extends the applicability
of ICA by jointly decomposing multiple datasets through the exploitation of the
dependencies across datasets. Though both ICA and IVA algorithms cast in the
maximum likelihood (ML) framework enable the use of all available statistical
information in reality, they often deviate from their theoretical optimality
properties due to improper estimation of the probability density function
(PDF). This motivates the development of flexible ICA and IVA algorithms that
closely adhere to the underlying statistical description of the data. Although
it is attractive minimize the assumptions, important prior information about
the data, such as sparsity, is usually available. If incorporated into the ICA
model, use of this additional information can relax the independence
assumption, resulting in an improvement in the overall separation performance.
Therefore, the development of a unified mathematical framework that can take
into account both statistical independence and sparsity is of great interest.
In this work, we first introduce a flexible ICA algorithm that uses an
effective PDF estimator to accurately capture the underlying statistical
properties of the data. We then discuss several techniques to accurately
estimate the parameters of the multivariate generalized Gaussian distribution,
and how to integrate them into the IVA model. Finally, we provide a
mathematical framework that enables direct control over the influence of
statistical independence and sparsity, and use this framework to develop an
effective ICA algorithm that can jointly exploit these two forms of diversity. | [
0,
0,
0,
1,
0,
0
] | [
"Computer Science",
"Statistics",
"Mathematics"
] |
Title: Observability of characteristic binary-induced structures in circumbinary disks,
Abstract: Context: A substantial fraction of protoplanetary disks forms around stellar
binaries. The binary system generates a time-dependent non-axisymmetric
gravitational potential, inducing strong tidal forces on the circumbinary disk.
This leads to a change in basic physical properties of the circumbinary disk,
which should in turn result in unique structures that are potentially
observable with the current generation of instruments.
Aims: The goal of this study is to identify these characteristic structures,
to constrain the physical conditions that cause them, and to evaluate the
feasibility to observe them in circumbinary disks.
Methods: To achieve this, at first two-dimensional hydrodynamic simulations
are performed. The resulting density distributions are post-processed with a 3D
radiative transfer code to generate re-emission and scattered light maps. Based
on these, we study the influence of various parameters, such as the mass of the
stellar components, the mass of the disk and the binary separation on
observable features in circumbinary disks.
Results: We find that the Atacama Large (sub-)Millimetre Array (ALMA) as well
as the European Extremely Large Telescope (E-ELT) are capable of tracing
asymmetries in the inner region of circumbinary disks which are affected most
by the binary-disk interaction. Observations at submillimetre/millimetre
wavelengths will allow the detection of the density waves at the inner rim of
the disk and the inner cavity. With the E-ELT one can partially resolve the
innermost parts of the disk in the infrared wavelength range, including the
disk's rim, accretion arms and potentially the expected circumstellar disks
around each of the binary components. | [
0,
1,
0,
0,
0,
0
] | [
"Physics"
] |
Title: Chaotic zones around rotating small bodies,
Abstract: Small bodies of the Solar system, like asteroids, trans-Neptunian objects,
cometary nuclei, planetary satellites, with diameters smaller than one thousand
kilometers usually have irregular shapes, often resembling dumb-bells, or
contact binaries. The spinning of such a gravitating dumb-bell creates around
it a zone of chaotic orbits. We determine its extent analytically and
numerically. We find that the chaotic zone swells significantly if the rotation
rate is decreased, in particular, the zone swells more than twice if the
rotation rate is decreased ten times with respect to the "centrifugal breakup"
threshold. We illustrate the properties of the chaotic orbital zones in
examples of the global orbital dynamics about asteroid 243 Ida (which has a
moon, Dactyl, orbiting near the edge of the chaotic zone) and asteroid 25143
Itokawa. | [
0,
1,
0,
0,
0,
0
] | [
"Physics"
] |
Title: Structure and Evolution of Internally Heated Hot Jupiters,
Abstract: Hot Jupiters receive strong stellar irradiation, producing equilibrium
temperatures of $1000 - 2500 \ \mathrm{Kelvin}$. Incoming irradiation directly
heats just their thin outer layer, down to pressures of $\sim 0.1 \
\mathrm{bars}$. In standard irradiated evolution models of hot Jupiters,
predicted transit radii are too small. Previous studies have shown that deeper
heating -- at a small fraction of the heating rate from irradiation -- can
explain observed radii. Here we present a suite of evolution models for HD
209458b where we systematically vary both the depth and intensity of internal
heating, without specifying the uncertain heating mechanism(s). Our models
start with a hot, high entropy planet whose radius decreases as the convective
interior cools. The applied heating suppresses this cooling. We find that very
shallow heating -- at pressures of $1 - 10 \ \mathrm{bars}$ -- does not
significantly suppress cooling, unless the total heating rate is $\gtrsim 10\%$
of the incident stellar power. Deeper heating, at $100 \ \mathrm{bars}$,
requires heating at only $1\%$ of the stellar irradiation to explain the
observed transit radius of $1.4 R_{\rm Jup}$ after 5 Gyr of cooling. In
general, more intense and deeper heating results in larger hot Jupiter radii.
Surprisingly, we find that heat deposited at $10^4 \ \mathrm{bars}$ -- which is
exterior to $\approx 99\%$ of the planet's mass -- suppresses planetary cooling
as effectively as heating at the center. In summary, we find that relatively
shallow heating is required to explain the radii of most hot Jupiters, provided
that this heat is applied early and persists throughout their evolution. | [
0,
1,
0,
0,
0,
0
] | [
"Physics"
] |
Title: Inference-Based Distributed Channel Allocation in Wireless Sensor Networks,
Abstract: Interference-aware resource allocation of time slots and frequency channels
in single-antenna, halfduplex radio wireless sensor networks (WSN) is
challenging. Devising distributed algorithms for such task further complicates
the problem. This work studiesWSN joint time and frequency channel allocation
for a given routing tree, such that: a) allocation is performed in a fully
distributed way, i.e., information exchange is only performed among neighboring
WSN terminals, within communication up to two hops, and b) detection of
potential interfering terminals is simplified and can be practically realized.
The algorithm imprints space, time, frequency and radio hardware constraints
into a loopy factor graph and performs iterative message passing/ loopy belief
propagation (BP) with randomized initial priors. Sufficient conditions for
convergence to a valid solution are offered, for the first time in the
literature, exploiting the structure of the proposed factor graph. Based on
theoretical findings, modifications of BP are devised that i) accelerate
convergence to a valid solution and ii) reduce computation cost. Simulations
reveal promising throughput results of the proposed distributed algorithm, even
though it utilizes simplified interfering terminals set detection. Future work
could modify the constraints such that other disruptive wireless technologies
(e.g., full-duplex radios or network coding) could be accommodated within the
same inference framework. | [
1,
0,
0,
0,
0,
0
] | [
"Computer Science",
"Statistics"
] |
Title: Schrödinger operators periodic in octants,
Abstract: We consider Schrödinger operators with periodic potentials in the positive
quadrant for dim $>1$ with Dirichlet boundary condition. We show that for any
integer $N$ and any interval $I$ there exists a periodic potential such that
the Schrödinger operator has $N$ eigenvalues counted with the multiplicity on
this interval and there is no other spectrum on the interval. Furthermore, to
the right and to the left of it there is a essential spectrum.
Moreover, we prove similar results for Schrödinger operators for other
domains. The proof is based on the inverse spectral theory for Hill operators
on the real line. | [
0,
0,
1,
0,
0,
0
] | [
"Mathematics",
"Physics"
] |
Title: Optimized Quantification of Spin Relaxation Times in the Hybrid State,
Abstract: Purpose: The analysis of optimized spin ensemble trajectories for relaxometry
in the hybrid state.
Methods: First, we constructed visual representations to elucidate the
differential equation that governs spin dynamics in hybrid state. Subsequently,
numerical optimizations were performed to find spin ensemble trajectories that
minimize the Cramér-Rao bound for $T_1$-encoding, $T_2$-encoding, and their
weighted sum, respectively, followed by a comparison of the Cramér-Rao bounds
obtained with our optimized spin-trajectories, as well as Look-Locker and
multi-spin-echo methods. Finally, we experimentally tested our optimized spin
trajectories with in vivo scans of the human brain.
Results: After a nonrecurring inversion segment on the southern hemisphere of
the Bloch sphere, all optimized spin trajectories pursue repetitive loops on
the northern half of the sphere in which the beginning of the first and the end
of the last loop deviate from the others. The numerical results obtained in
this work align well with intuitive insights gleaned directly from the
governing equation. Our results suggest that hybrid-state sequences outperform
traditional methods. Moreover, hybrid-state sequences that balance $T_1$- and
$T_2$-encoding still result in near optimal signal-to-noise efficiency. Thus,
the second parameter can be encoded at virtually no extra cost.
Conclusion: We provide insights regarding the optimal encoding processes of
spin relaxation times in order to guide the design of robust and efficient
pulse sequences. We find that joint acquisitions of $T_1$ and $T_2$ in the
hybrid state are substantially more efficient than sequential encoding
techniques. | [
0,
1,
0,
0,
0,
0
] | [
"Physics",
"Mathematics"
] |
Title: Reviving and Improving Recurrent Back-Propagation,
Abstract: In this paper, we revisit the recurrent back-propagation (RBP) algorithm,
discuss the conditions under which it applies as well as how to satisfy them in
deep neural networks. We show that RBP can be unstable and propose two variants
based on conjugate gradient on the normal equations (CG-RBP) and Neumann series
(Neumann-RBP). We further investigate the relationship between Neumann-RBP and
back propagation through time (BPTT) and its truncated version (TBPTT). Our
Neumann-RBP has the same time complexity as TBPTT but only requires constant
memory, whereas TBPTT's memory cost scales linearly with the number of
truncation steps. We examine all RBP variants along with BPTT and TBPTT in
three different application domains: associative memory with continuous
Hopfield networks, document classification in citation networks using graph
neural networks and hyperparameter optimization for fully connected networks.
All experiments demonstrate that RBPs, especially the Neumann-RBP variant, are
efficient and effective for optimizing convergent recurrent neural networks. | [
0,
0,
0,
1,
0,
0
] | [
"Computer Science"
] |
Title: A family of Dirichlet-Morrey spaces,
Abstract: To each weighted Dirichlet space $\mathcal{D}_p$, $0<p<1$, we associate a
family of Morrey-type spaces ${\mathcal{D}}_p^{\lambda}$, $0< \lambda < 1$,
constructed by imposing growth conditions on the norm of hyperbolic translates
of functions. We indicate some of the properties of these spaces, mention the
characterization in terms of boundary values, and study integration and
multiplication operators on them. | [
0,
0,
1,
0,
0,
0
] | [
"Mathematics"
] |
Title: Fast Characterization of Segmental Duplications in Genome Assemblies,
Abstract: Segmental duplications (SDs), or low-copy repeats (LCR), are segments of DNA
greater than 1 Kbp with high sequence identity that are copied to other regions
of the genome. SDs are among the most important sources of evolution, a common
cause of genomic structural variation, and several are associated with diseases
of genomic origin. Despite their functional importance, SDs present one of the
major hurdles for de novo genome assembly due to the ambiguity they cause in
building and traversing both state-of-the-art overlap-layout-consensus and de
Bruijn graphs. This causes SD regions to be misassembled, collapsed into a
unique representation, or completely missing from assembled reference genomes
for various organisms. In turn, this missing or incorrect information limits
our ability to fully understand the evolution and the architecture of the
genomes. Despite the essential need to accurately characterize SDs in
assemblies, there is only one tool that has been developed for this purpose,
called Whole Genome Assembly Comparison (WGAC). WGAC is comprised of several
steps that employ different tools and custom scripts, which makes it difficult
and time consuming to use. Thus there is still a need for algorithms to
characterize within-assembly SDs quickly, accurately, and in a user friendly
manner.
Here we introduce a SEgmental Duplication Evaluation Framework (SEDEF) to
rapidly detect SDs through sophisticated filtering strategies based on Jaccard
similarity and local chaining. We show that SEDEF accurately detects SDs while
maintaining substantial speed up over WGAC that translates into practical run
times of minutes instead of weeks. Notably, our algorithm captures up to 25%
pairwise error between segments, where previous studies focused on only 10%,
allowing us to more deeply track the evolutionary history of the genome.
SEDEF is available at this https URL | [
0,
0,
0,
0,
1,
0
] | [
"Quantitative Biology",
"Computer Science"
] |
Title: Cross validation for locally stationary processes,
Abstract: We propose an adaptive bandwidth selector via cross validation for local
M-estimators in locally stationary processes. We prove asymptotic optimality of
the procedure under mild conditions on the underlying parameter curves. The
results are applicable to a wide range of locally stationary processes such
linear and nonlinear processes. A simulation study shows that the method works
fairly well also in misspecified situations. | [
0,
0,
1,
1,
0,
0
] | [
"Statistics",
"Mathematics"
] |
Title: Weyl nodes in Andreev spectra of multiterminal Josephson junctions: Chern numbers, conductances and supercurrents,
Abstract: We consider mesoscopic four-terminal Josephson junctions and study emergent
topological properties of the Andreev subgap bands. We use symmetry-constrained
analysis for Wigner-Dyson classes of scattering matrices to derive band
dispersions. When scattering matrix of the normal region connecting
superconducting leads is energy-independent, the determinant formula for
Andreev spectrum can be reduced to a palindromic equation that admits a
complete analytical solution. Band topology manifests with an appearance of the
Weyl nodes which serve as monopoles of finite Berry curvature. The
corresponding fluxes are quantified by Chern numbers that translate into a
quantized nonlocal conductance that we compute explicitly for the
time-reversal-symmetric scattering matrix. The topological regime can be also
identified by supercurrents as Josephson current-phase relationships exhibit
pronounced nonanalytic behavior and discontinuities near Weyl points that can
be controllably accessed in experiments. | [
0,
1,
0,
0,
0,
0
] | [
"Physics"
] |
Title: RPC: A Large-Scale Retail Product Checkout Dataset,
Abstract: Over recent years, emerging interest has occurred in integrating computer
vision technology into the retail industry. Automatic checkout (ACO) is one of
the critical problems in this area which aims to automatically generate the
shopping list from the images of the products to purchase. The main challenge
of this problem comes from the large scale and the fine-grained nature of the
product categories as well as the difficulty for collecting training images
that reflect the realistic checkout scenarios due to continuous update of the
products. Despite its significant practical and research value, this problem is
not extensively studied in the computer vision community, largely due to the
lack of a high-quality dataset. To fill this gap, in this work we propose a new
dataset to facilitate relevant research. Our dataset enjoys the following
characteristics: (1) It is by far the largest dataset in terms of both product
image quantity and product categories. (2) It includes single-product images
taken in a controlled environment and multi-product images taken by the
checkout system. (3) It provides different levels of annotations for the
check-out images. Comparing with the existing datasets, ours is closer to the
realistic setting and can derive a variety of research problems. Besides the
dataset, we also benchmark the performance on this dataset with various
approaches. The dataset and related resources can be found at
\url{this https URL}. | [
1,
0,
0,
0,
0,
0
] | [
"Computer Science"
] |
Title: KiDS-450: Tomographic Cross-Correlation of Galaxy Shear with {\it Planck} Lensing,
Abstract: We present the tomographic cross-correlation between galaxy lensing measured
in the Kilo Degree Survey (KiDS-450) with overlapping lensing measurements of
the cosmic microwave background (CMB), as detected by Planck 2015. We compare
our joint probe measurement to the theoretical expectation for a flat
$\Lambda$CDM cosmology, assuming the best-fitting cosmological parameters from
the KiDS-450 cosmic shear and Planck CMB analyses. We find that our results are
consistent within $1\sigma$ with the KiDS-450 cosmology, with an amplitude
re-scaling parameter $A_{\rm KiDS} = 0.86 \pm 0.19$. Adopting a Planck
cosmology, we find our results are consistent within $2\sigma$, with $A_{\it
Planck} = 0.68 \pm 0.15$. We show that the agreement is improved in both cases
when the contamination to the signal by intrinsic galaxy alignments is
accounted for, increasing $A$ by $\sim 0.1$. This is the first tomographic
analysis of the galaxy lensing -- CMB lensing cross-correlation signal, and is
based on five photometric redshift bins. We use this measurement as an
independent validation of the multiplicative shear calibration and of the
calibrated source redshift distribution at high redshifts. We find that
constraints on these two quantities are strongly correlated when obtained from
this technique, which should therefore not be considered as a stand-alone
competitive calibration tool. | [
0,
1,
0,
0,
0,
0
] | [
"Physics",
"Astrophysics"
] |
Title: Tidal disruptions by rotating black holes: relativistic hydrodynamics with Newtonian codes,
Abstract: We propose an approximate approach for studying the relativistic regime of
stellar tidal disruptions by rotating massive black holes. It combines an exact
relativistic description of the hydrodynamical evolution of a test fluid in a
fixed curved spacetime with a Newtonian treatment of the fluid's self-gravity.
Explicit expressions for the equations of motion are derived for Kerr spacetime
using two different coordinate systems. We implement the new methodology within
an existing Newtonian Smoothed Particle Hydrodynamics code and show that
including the additional physics involves very little extra computational cost.
We carefully explore the validity of the novel approach by first testing its
ability to recover geodesic motion, and then by comparing the outcome of tidal
disruption simulations against previous relativistic studies. We further
compare simulations in Boyer--Lindquist and Kerr--Schild coordinates and
conclude that our approach allows accurate simulation even of tidal disruption
events where the star penetrates deeply inside the tidal radius of a rotating
black hole. Finally, we use the new method to study the effect of the black
hole spin on the morphology and fallback rate of the debris streams resulting
from tidal disruptions, finding that while the spin has little effect on the
fallback rate, it does imprint heavily on the stream morphology, and can even
be a determining factor in the survival or disruption of the star itself. Our
methodology is discussed in detail as a reference for future astrophysical
applications. | [
0,
1,
0,
0,
0,
0
] | [
"Physics"
] |
Title: A promise checked is a promise kept: Inspection Testing,
Abstract: Occasionally, developers need to ensure that the compiler treats their code
in a specific way that is only visible by inspecting intermediate or final
compilation artifacts. This is particularly common with carefully crafted
compositional libraries, where certain usage patterns are expected to trigger
an intricate sequence of compiler optimizations -- stream fusion is a
well-known example.
The developer of such a library has to manually inspect build artifacts and
check for the expected properties. Because this is too tedious to do often, it
will likely go unnoticed if the property is broken by a change to the library
code, its dependencies or the compiler. The lack of automation has led to
released versions of such libraries breaking their documented promises.
This indicates that there is an unrecognized need for a new testing paradigm,
inspection testing, where the programmer declaratively describes non-functional
properties of an compilation artifact and the compiler checks these properties.
We define inspection testing abstractly, implement it in the context of Haskell
and show that it increases the quality of such libraries. | [
1,
0,
0,
0,
0,
0
] | [
"Computer Science"
] |
Title: Linear-Time Sequence Classification using Restricted Boltzmann Machines,
Abstract: Classification of sequence data is the topic of interest for dynamic Bayesian
models and Recurrent Neural Networks (RNNs). While the former can explicitly
model the temporal dependencies between class variables, the latter have a
capability of learning representations. Several attempts have been made to
improve performance by combining these two approaches or increasing the
processing capability of the hidden units in RNNs. This often results in
complex models with a large number of learning parameters. In this paper, a
compact model is proposed which offers both representation learning and
temporal inference of class variables by rolling Restricted Boltzmann Machines
(RBMs) and class variables over time. We address the key issue of
intractability in this variant of RBMs by optimising a conditional
distribution, instead of a joint distribution. Experiments reported in the
paper on melody modelling and optical character recognition show that the
proposed model can outperform the state-of-the-art. Also, the experimental
results on optical character recognition, part-of-speech tagging and text
chunking demonstrate that our model is comparable to recurrent neural networks
with complex memory gates while requiring far fewer parameters. | [
1,
0,
0,
1,
0,
0
] | [
"Computer Science",
"Statistics"
] |
Title: A central $U(1)$-extension of a double Lie groupoid,
Abstract: In this paper, we introduce a notion of a central $U(1)$-extension of a
double Lie groupoid and show that it defines a cocycle in the certain triple
complex. | [
0,
0,
1,
0,
0,
0
] | [
"Mathematics"
] |
Title: The NIEP,
Abstract: The nonnegative inverse eigenvalue problem (NIEP) asks which lists of $n$
complex numbers (counting multiplicity) occur as the eigenvalues of some
$n$-by-$n$ entry-wise nonnegative matrix. The NIEP has a long history and is a
known hard (perhaps the hardest in matrix analysis?) and sought after problem.
Thus, there are many subproblems and relevant results in a variety of
directions. We survey most work on the problem and its several variants, with
an emphasis on recent results, and include 130 references. The survey is
divided into: a) the single eigenvalue problems; b) necessary conditions; c)
low dimensional results; d) sufficient conditions; e) appending 0's to achieve
realizability; f) the graph NIEP's; g) Perron similarities; and h) the
relevance of Jordan structure. | [
0,
0,
1,
0,
0,
0
] | [
"Mathematics"
] |
Title: Synthesizing Bijective Lenses,
Abstract: Bidirectional transformations between different data representations occur
frequently in modern software systems. They appear as serializers and
deserializers, as database views and view updaters, and more. Manually building
bidirectional transformations---by writing two separate functions that are
intended to be inverses---is tedious and error prone. A better approach is to
use a domain-specific language in which both directions can be written as a
single expression. However, these domain-specific languages can be difficult to
program in, requiring programmers to manage fiddly details while working in a
complex type system.
To solve this, we present Optician, a tool for type-directed synthesis of
bijective string transformers. The inputs to Optician are two ordinary regular
expressions representing two data formats and a few concrete examples for
disambiguation. The output is a well-typed program in Boomerang (a
bidirectional language based on the theory of lenses). The main technical
challenge involves navigating the vast program search space efficiently enough.
Unlike most prior work on type-directed synthesis, our system operates in the
context of a language with a rich equivalence relation on types (the theory of
regular expressions). We synthesize terms of a equivalent language and convert
those generated terms into our lens language. We prove the correctness of our
synthesis algorithm. We also demonstrate empirically that our new language
changes the synthesis problem from one that admits intractable solutions to one
that admits highly efficient solutions. We evaluate Optician on a benchmark
suite of 39 examples including both microbenchmarks and realistic examples
derived from other data management systems including Flash Fill, a tool for
synthesizing string transformations in spreadsheets, and Augeas, a tool for
bidirectional processing of Linux system configuration files. | [
1,
0,
0,
0,
0,
0
] | [
"Computer Science"
] |
Title: Embedding for bulk systems using localized atomic orbitals,
Abstract: We present an embedding approach for semiconductors and insulators based on
or- bital rotations in the space of occupied Kohn-Sham orbitals. We have
implemented our approach in the popular VASP software package. We demonstrate
its power for defect structures in silicon and polaron formation in titania,
two challenging cases for conventional Kohn-Sham density functional theory. | [
0,
1,
0,
0,
0,
0
] | [
"Physics",
"Computer Science"
] |
Title: Particle trapping and conveying using an optical Archimedes' screw,
Abstract: Trapping and manipulation of particles using laser beams has become an
important tool in diverse fields of research. In recent years, particular
interest is given to the problem of conveying optically trapped particles over
extended distances either down or upstream the direction of the photons
momentum flow. Here, we propose and demonstrate experimentally an optical
analogue of the famous Archimedes' screw where the rotation of a
helical-intensity beam is transferred to the axial motion of optically-trapped
micro-meter scale airborne carbon based particles. With this optical screw,
particles were easily conveyed with controlled velocity and direction, upstream
or downstream the optical flow, over a distance of half a centimeter. Our
results offer a very simple optical conveyor that could be adapted to a wide
range of optical trapping scenarios. | [
0,
1,
0,
0,
0,
0
] | [
"Physics"
] |
Title: Scalable Inference for Nested Chinese Restaurant Process Topic Models,
Abstract: Nested Chinese Restaurant Process (nCRP) topic models are powerful
nonparametric Bayesian methods to extract a topic hierarchy from a given text
corpus, where the hierarchical structure is automatically determined by the
data. Hierarchical Latent Dirichlet Allocation (hLDA) is a popular instance of
nCRP topic models. However, hLDA has only been evaluated at small scale,
because the existing collapsed Gibbs sampling and instantiated weight
variational inference algorithms either are not scalable or sacrifice inference
quality with mean-field assumptions. Moreover, an efficient distributed
implementation of the data structures, such as dynamically growing count
matrices and trees, is challenging.
In this paper, we propose a novel partially collapsed Gibbs sampling (PCGS)
algorithm, which combines the advantages of collapsed and instantiated weight
algorithms to achieve good scalability as well as high model quality. An
initialization strategy is presented to further improve the model quality.
Finally, we propose an efficient distributed implementation of PCGS through
vectorization, pre-processing, and a careful design of the concurrent data
structures and communication strategy.
Empirical studies show that our algorithm is 111 times more efficient than
the previous open-source implementation for hLDA, with comparable or even
better model quality. Our distributed implementation can extract 1,722 topics
from a 131-million-document corpus with 28 billion tokens, which is 4-5 orders
of magnitude larger than the previous largest corpus, with 50 machines in 7
hours. | [
1,
0,
0,
1,
0,
0
] | [
"Computer Science",
"Statistics"
] |
Title: Equations of $\,\overline{M}_{0,n}$,
Abstract: Following work of Keel and Tevelev, we give explicit polynomials in the Cox
ring of $\mathbb{P}^1\times\cdots\times\mathbb{P}^{n-3}$ that, conjecturally,
determine $\overline{M}_{0,n}$ as a subscheme. Using Macaulay2, we prove that
these equations generate the ideal for $n=5, 6, 7, 8$. For $n \leq 6$ we give a
cohomological proof that these polynomials realize $\overline{M}_{0,n}$ as a
projective variety, embedded in $\mathbb{P}^{(n-2)!-1}$ by the complete log
canonical linear system. | [
0,
0,
1,
0,
0,
0
] | [
"Mathematics"
] |
Title: Characterizing a CCD detector for astronomical purposes: OAUNI Project,
Abstract: This work verifies the instrumental characteristics of the CCD detector which
is part of the UNI astronomical observatory. We measured the linearity of the
CCD detector of the SBIG STXL6303E camera, along with the associated gain and
readout noise. The linear response to the incident light of the detector is
extremely linear (R2 =99.99%), its effective gain is 1.65 +/- 0.01 e-/ADU and
its readout noise is 12.2 e-. These values are in agreement with the
manufacturer. We confirm that this detector is extremely precise to make
measurements for astronomical purposes. | [
0,
1,
0,
0,
0,
0
] | [
"Physics"
] |
Title: Testing small scale gravitational wave detectors with dynamical mass distributions,
Abstract: The recent discovery of gravitational waves by the LIGO-Virgo collaboration
created renewed interest in the investigation of alternative gravitational
detector designs, such as small scale resonant detectors. In this article, it
is shown how proposed small scale detectors can be tested by generating
dynamical gravitational fields with appropriate distributions of moving masses.
A series of interesting experiments will be possible with this setup. In
particular, small scale detectors can be tested very early in the development
phase and tests can be used to progress quickly in their development. This
could contribute to the emerging field of gravitational wave astronomy. | [
0,
1,
0,
0,
0,
0
] | [
"Physics"
] |
Title: Mining within-trial oscillatory brain dynamics to address the variability of optimized spatial filters,
Abstract: Data-driven spatial filtering algorithms optimize scores such as the contrast
between two conditions to extract oscillatory brain signal components. Most
machine learning approaches for filter estimation, however, disregard
within-trial temporal dynamics and are extremely sensitive to changes in
training data and involved hyperparameters. This leads to highly variable
solutions and impedes the selection of a suitable candidate for,
e.g.,~neurotechnological applications. Fostering component introspection, we
propose to embrace this variability by condensing the functional signatures of
a large set of oscillatory components into homogeneous clusters, each
representing specific within-trial envelope dynamics.
The proposed method is exemplified by and evaluated on a complex hand force
task with a rich within-trial structure. Based on electroencephalography data
of 18 healthy subjects, we found that the components' distinct temporal
envelope dynamics are highly subject-specific. On average, we obtained seven
clusters per subject, which were strictly confined regarding their underlying
frequency bands. As the analysis method is not limited to a specific spatial
filtering algorithm, it could be utilized for a wide range of
neurotechnological applications, e.g., to select and monitor functionally
relevant features for brain-computer interface protocols in stroke
rehabilitation. | [
0,
0,
0,
1,
1,
0
] | [
"Computer Science",
"Quantitative Biology"
] |
Title: Neural Architecture Search with Bayesian Optimisation and Optimal Transport,
Abstract: Bayesian Optimisation (BO) refers to a class of methods for global
optimisation of a function $f$ which is only accessible via point evaluations.
It is typically used in settings where $f$ is expensive to evaluate. A common
use case for BO in machine learning is model selection, where it is not
possible to analytically model the generalisation performance of a statistical
model, and we resort to noisy and expensive training and validation procedures
to choose the best model. Conventional BO methods have focused on Euclidean and
categorical domains, which, in the context of model selection, only permits
tuning scalar hyper-parameters of machine learning algorithms. However, with
the surge of interest in deep learning, there is an increasing demand to tune
neural network \emph{architectures}. In this work, we develop NASBOT, a
Gaussian process based BO framework for neural architecture search. To
accomplish this, we develop a distance metric in the space of neural network
architectures which can be computed efficiently via an optimal transport
program. This distance might be of independent interest to the deep learning
community as it may find applications outside of BO. We demonstrate that NASBOT
outperforms other alternatives for architecture search in several cross
validation based model selection tasks on multi-layer perceptrons and
convolutional neural networks. | [
0,
0,
0,
1,
0,
0
] | [
"Computer Science",
"Statistics"
] |
Title: An improved parametric model for hysteresis loop approximation,
Abstract: A number of improvements have been added to the existing analytical model of
hysteresis loop defined in parametric form. In particular, three phase shifts
are included in the model, which permits to tilt the hysteresis loop smoothly
by the required angle at the split point as well as to smoothly change the
curvature of the loop. As a result, the error of approximation of a hysteresis
loop by the improved model does not exceed 1%, which is several times less than
the error of the existing model. The improved model is capable of approximating
most of the known types of rate-independent symmetrical hysteresis loops
encountered in the practice of physical measurements. The model allows building
smooth, piecewise-linear, hybrid, minor, mirror-reflected, inverse, reverse,
double and triple loops. One of the possible applications of the model
developed is linearization of a probe microscope piezoscanner. The improved
model can be found useful for the tasks of simulation of scientific instruments
that contain hysteresis elements. | [
1,
1,
1,
0,
0,
0
] | [
"Physics",
"Mathematics"
] |
Title: To prune, or not to prune: exploring the efficacy of pruning for model compression,
Abstract: Model pruning seeks to induce sparsity in a deep neural network's various
connection matrices, thereby reducing the number of nonzero-valued parameters
in the model. Recent reports (Han et al., 2015; Narang et al., 2017) prune deep
networks at the cost of only a marginal loss in accuracy and achieve a sizable
reduction in model size. This hints at the possibility that the baseline models
in these experiments are perhaps severely over-parameterized at the outset and
a viable alternative for model compression might be to simply reduce the number
of hidden units while maintaining the model's dense connection structure,
exposing a similar trade-off in model size and accuracy. We investigate these
two distinct paths for model compression within the context of energy-efficient
inference in resource-constrained environments and propose a new gradual
pruning technique that is simple and straightforward to apply across a variety
of models/datasets with minimal tuning and can be seamlessly incorporated
within the training process. We compare the accuracy of large, but pruned
models (large-sparse) and their smaller, but dense (small-dense) counterparts
with identical memory footprint. Across a broad range of neural network
architectures (deep CNNs, stacked LSTM, and seq2seq LSTM models), we find
large-sparse models to consistently outperform small-dense models and achieve
up to 10x reduction in number of non-zero parameters with minimal loss in
accuracy. | [
1,
0,
0,
1,
0,
0
] | [
"Computer Science"
] |
Title: Connecting Software Metrics across Versions to Predict Defects,
Abstract: Accurate software defect prediction could help software practitioners
allocate test resources to defect-prone modules effectively and efficiently. In
the last decades, much effort has been devoted to build accurate defect
prediction models, including developing quality defect predictors and modeling
techniques. However, current widely used defect predictors such as code metrics
and process metrics could not well describe how software modules change over
the project evolution, which we believe is important for defect prediction. In
order to deal with this problem, in this paper, we propose to use the
Historical Version Sequence of Metrics (HVSM) in continuous software versions
as defect predictors. Furthermore, we leverage Recurrent Neural Network (RNN),
a popular modeling technique, to take HVSM as the input to build software
prediction models. The experimental results show that, in most cases, the
proposed HVSM-based RNN model has a significantly better effort-aware ranking
effectiveness than the commonly used baseline models. | [
1,
0,
0,
0,
0,
0
] | [
"Computer Science",
"Statistics"
] |
Title: Constructive Euler hydrodynamics for one-dimensional attractive particle systems,
Abstract: We review a (constructive) approach first introduced in [6] and further
developed in [7, 8, 38, 9] for hydrodynamic limits of asymmetric attractive
particle systems, in a weak or in a strong (that is, almost sure) sense, in an
homogeneous or in a quenched disordered setting. | [
0,
0,
1,
0,
0,
0
] | [
"Mathematics",
"Physics"
] |
Title: Cyber Insurance for Heterogeneous Wireless Networks,
Abstract: Heterogeneous wireless networks (HWNs) composed of densely deployed base
stations of different types with various radio access technologies have become
a prevailing trend to accommodate ever-increasing traffic demand in enormous
volume. Nowadays, users rely heavily on HWNs for ubiquitous network access that
contains valuable and critical information such as financial transactions,
e-health, and public safety. Cyber risks, representing one of the most
significant threats to network security and reliability, are increasing in
severity. To address this problem, this article introduces the concept of cyber
insurance to transfer the cyber risk (i.e., service outage, as a consequence of
cyber risks in HWNs) to a third party insurer. Firstly, a review of the
enabling technologies for HWNs and their vulnerabilities to cyber risks is
presented. Then, the fundamentals of cyber insurance are introduced, and
subsequently, a cyber insurance framework for HWNs is presented. Finally, open
issues are discussed and the challenges are highlighted for integrating cyber
insurance as a service of next generation HWNs. | [
1,
0,
0,
0,
0,
0
] | [
"Computer Science",
"Quantitative Finance"
] |
Title: Combining Contrast Invariant L1 Data Fidelities with Nonlinear Spectral Image Decomposition,
Abstract: This paper focuses on multi-scale approaches for variational methods and
corresponding gradient flows. Recently, for convex regularization functionals
such as total variation, new theory and algorithms for nonlinear eigenvalue
problems via nonlinear spectral decompositions have been developed. Those
methods open new directions for advanced image filtering. However, for an
effective use in image segmentation and shape decomposition, a clear
interpretation of the spectral response regarding size and intensity scales is
needed but lacking in current approaches. In this context, $L^1$ data
fidelities are particularly helpful due to their interesting multi-scale
properties such as contrast invariance. Hence, the novelty of this work is the
combination of $L^1$-based multi-scale methods with nonlinear spectral
decompositions. We compare $L^1$ with $L^2$ scale-space methods in view of
spectral image representation and decomposition. We show that the contrast
invariant multi-scale behavior of $L^1-TV$ promotes sparsity in the spectral
response providing more informative decompositions. We provide a numerical
method and analyze synthetic and biomedical images at which decomposition leads
to improved segmentation. | [
1,
0,
1,
0,
0,
0
] | [
"Computer Science",
"Mathematics"
] |
Title: PaccMann: Prediction of anticancer compound sensitivity with multi-modal attention-based neural networks,
Abstract: We present a novel approach for the prediction of anticancer compound
sensitivity by means of multi-modal attention-based neural networks (PaccMann).
In our approach, we integrate three key pillars of drug sensitivity, namely,
the molecular structure of compounds, transcriptomic profiles of cancer cells
as well as prior knowledge about interactions among proteins within cells. Our
models ingest a drug-cell pair consisting of SMILES encoding of a compound and
the gene expression profile of a cancer cell and predicts an IC50 sensitivity
value. Gene expression profiles are encoded using an attention-based encoding
mechanism that assigns high weights to the most informative genes. We present
and study three encoders for SMILES string of compounds: 1) bidirectional
recurrent 2) convolutional 3) attention-based encoders. We compare our devised
models against a baseline model that ingests engineered fingerprints to
represent the molecular structure. We demonstrate that using our
attention-based encoders, we can surpass the baseline model. The use of
attention-based encoders enhance interpretability and enable us to identify
genes, bonds and atoms that were used by the network to make a prediction. | [
0,
0,
0,
0,
1,
0
] | [
"Computer Science",
"Quantitative Biology"
] |
Title: Multi-Path Region-Based Convolutional Neural Network for Accurate Detection of Unconstrained "Hard Faces",
Abstract: Large-scale variations still pose a challenge in unconstrained face
detection. To the best of our knowledge, no current face detection algorithm
can detect a face as large as 800 x 800 pixels while simultaneously detecting
another one as small as 8 x 8 pixels within a single image with equally high
accuracy. We propose a two-stage cascaded face detection framework, Multi-Path
Region-based Convolutional Neural Network (MP-RCNN), that seamlessly combines a
deep neural network with a classic learning strategy, to tackle this challenge.
The first stage is a Multi-Path Region Proposal Network (MP-RPN) that proposes
faces at three different scales. It simultaneously utilizes three parallel
outputs of the convolutional feature maps to predict multi-scale candidate face
regions. The "atrous" convolution trick (convolution with up-sampled filters)
and a newly proposed sampling layer for "hard" examples are embedded in MP-RPN
to further boost its performance. The second stage is a Boosted Forests
classifier, which utilizes deep facial features pooled from inside the
candidate face regions as well as deep contextual features pooled from a larger
region surrounding the candidate face regions. This step is included to further
remove hard negative samples. Experiments show that this approach achieves
state-of-the-art face detection performance on the WIDER FACE dataset "hard"
partition, outperforming the former best result by 9.6% for the Average
Precision. | [
1,
0,
0,
0,
0,
0
] | [
"Computer Science"
] |
Title: Naturally occurring $^{32}$Si and low-background silicon dark matter detectors,
Abstract: The naturally occurring radioisotope $^{32}$Si represents a potentially
limiting background in future dark matter direct-detection experiments. We
investigate sources of $^{32}$Si and the vectors by which it comes to reside in
silicon crystals used for fabrication of radiation detectors. We infer that the
$^{32}$Si concentration in commercial single-crystal silicon is likely
variable, dependent upon the specific geologic and hydrologic history of the
source (or sources) of silicon "ore" and the details of the silicon-refinement
process. The silicon production industry is large, highly segmented by refining
step, and multifaceted in terms of final product type, from which we conclude
that production of $^{32}$Si-mitigated crystals requires both targeted silicon
material selection and a dedicated refinement-through-crystal-production
process. We review options for source material selection, including quartz from
an underground source and silicon isotopically reduced in $^{32}$Si. To
quantitatively evaluate the $^{32}$Si content in silicon metal and precursor
materials, we propose analytic methods employing chemical processing and
radiometric measurements. Ultimately, it appears feasible to produce silicon
detectors with low levels of $^{32}$Si, though significant assay method
development is required to validate this claim and thereby enable a quality
assurance program during an actual controlled silicon-detector production
cycle. | [
0,
1,
0,
0,
0,
0
] | [
"Physics"
] |
Title: A Syllable-based Technique for Word Embeddings of Korean Words,
Abstract: Word embedding has become a fundamental component to many NLP tasks such as
named entity recognition and machine translation. However, popular models that
learn such embeddings are unaware of the morphology of words, so it is not
directly applicable to highly agglutinative languages such as Korean. We
propose a syllable-based learning model for Korean using a convolutional neural
network, in which word representation is composed of trained syllable vectors.
Our model successfully produces morphologically meaningful representation of
Korean words compared to the original Skip-gram embeddings. The results also
show that it is quite robust to the Out-of-Vocabulary problem. | [
1,
0,
0,
0,
0,
0
] | [
"Computer Science"
] |
Title: On discrete homology of a free pro-$p$-group,
Abstract: For a prime $p$, let $\hat F_p$ be a finitely generated free pro-$p$-group of
rank $\geq 2$. We show that the second discrete homology group $H_2(\hat
F_p,\mathbb Z/p)$ is an uncountable $\mathbb Z/p$-vector space. This answers a
problem of A.K. Bousfield. | [
0,
0,
1,
0,
0,
0
] | [
"Mathematics"
] |
Title: Conceptual Modeling of Inventory Management Processes as a Thinging Machine,
Abstract: A control model is typically classified into three forms: conceptual,
mathematical and simulation (computer). This paper analyzes a conceptual
modeling application with respect to an inventory management system. Today,
most organizations utilize computer systems for inventory control that provide
protection when interruptions or breakdowns occur within work processes.
Modeling the inventory processes is an active area of research that utilizes
many diagrammatic techniques, including data flow diagrams, Universal Modeling
Language (UML) diagrams and Integration DEFinition (IDEF). We claim that
current conceptual modeling frameworks lack uniform notions and have inability
to appeal to designers and analysts. We propose modeling an inventory system as
an abstract machine, called a Thinging Machine (TM), with five operations:
creation, processing, receiving, releasing and transferring. The paper provides
side-by-side contrasts of some existing examples of conceptual modeling
methodologies that apply to TM. Additionally, TM is applied in a case study of
an actual inventory system that uses IBM Maximo. The resulting conceptual
depictions point to the viability of FM as a valuable tool for developing a
high-level representation of inventory processes. | [
1,
0,
0,
0,
0,
0
] | [
"Computer Science"
] |
Title: 11 T Dipole for the Dispersion Suppressor Collimators,
Abstract: Chapter 11 in High-Luminosity Large Hadron Collider (HL-LHC) : Preliminary
Design Report. The Large Hadron Collider (LHC) is one of the largest scientific
instruments ever built. Since opening up a new energy frontier for exploration
in 2010, it has gathered a global user community of about 7,000 scientists
working in fundamental particle physics and the physics of hadronic matter at
extreme temperature and density. To sustain and extend its discovery potential,
the LHC will need a major upgrade in the 2020s. This will increase its
luminosity (rate of collisions) by a factor of five beyond the original design
value and the integrated luminosity (total collisions created) by a factor ten.
The LHC is already a highly complex and exquisitely optimised machine so this
upgrade must be carefully conceived and will require about ten years to
implement. The new configuration, known as High Luminosity LHC (HL-LHC), will
rely on a number of key innovations that push accelerator technology beyond its
present limits. Among these are cutting-edge 11-12 tesla superconducting
magnets, compact superconducting cavities for beam rotation with ultra-precise
phase control, new technology and physical processes for beam collimation and
300 metre-long high-power superconducting links with negligible energy
dissipation. The present document describes the technologies and components
that will be used to realise the project and is intended to serve as the basis
for the detailed engineering design of HL-LHC. | [
0,
1,
0,
0,
0,
0
] | [
"Physics"
] |
Title: Spectral Analysis of Jet Substructure with Neural Networks: Boosted Higgs Case,
Abstract: Jets from boosted heavy particles have a typical angular scale which can be
used to distinguish them from QCD jets. We introduce a machine learning
strategy for jet substructure analysis using a spectral function on the angular
scale. The angular spectrum allows us to scan energy deposits over the angle
between a pair of particles in a highly visual way. We set up an artificial
neural network (ANN) to find out characteristic shapes of the spectra of the
jets from heavy particle decays. By taking the Higgs jets and QCD jets as
examples, we show that the ANN of the angular spectrum input has similar
performance to existing taggers. In addition, some improvement is seen when
additional extra radiations occur. Notably, the new algorithm automatically
combines the information of the multi-point correlations in the jet. | [
0,
0,
0,
1,
0,
0
] | [
"Physics",
"Computer Science"
] |
Title: UTD-CRSS Submission for MGB-3 Arabic Dialect Identification: Front-end and Back-end Advancements on Broadcast Speech,
Abstract: This study presents systems submitted by the University of Texas at Dallas,
Center for Robust Speech Systems (UTD-CRSS) to the MGB-3 Arabic Dialect
Identification (ADI) subtask. This task is defined to discriminate between five
dialects of Arabic, including Egyptian, Gulf, Levantine, North African, and
Modern Standard Arabic. We develop multiple single systems with different
front-end representations and back-end classifiers. At the front-end level,
feature extraction methods such as Mel-frequency cepstral coefficients (MFCCs)
and two types of bottleneck features (BNF) are studied for an i-Vector
framework. As for the back-end level, Gaussian back-end (GB), and Generative
Adversarial Networks (GANs) classifiers are applied alternately. The best
submission (contrastive) is achieved for the ADI subtask with an accuracy of
76.94% by augmenting the randomly chosen part of the development dataset.
Further, with a post evaluation correction in the submitted system, final
accuracy is increased to 79.76%, which represents the best performance achieved
so far for the challenge on the test dataset. | [
1,
0,
0,
0,
0,
0
] | [
"Computer Science"
] |
Title: Basis Adaptive Sample Efficient Polynomial Chaos (BASE-PC),
Abstract: For a large class of orthogonal basis functions, there has been a recent
identification of expansion methods for computing accurate, stable
approximations of a quantity of interest. This paper presents, within the
context of uncertainty quantification, a practical implementation using basis
adaptation, and coherence motivated sampling, which under assumptions has
satisfying guarantees. This implementation is referred to as Basis Adaptive
Sample Efficient Polynomial Chaos (BASE-PC). A key component of this is the use
of anisotropic polynomial order which admits evolving global bases for
approximation in an efficient manner, leading to consistently stable
approximation for a practical class of smooth functionals. This fully adaptive,
non-intrusive method, requires no a priori information of the solution, and has
satisfying theoretical guarantees of recovery. A key contribution to stability
is the use of a presented correction sampling for coherence-optimal sampling in
order to improve stability and accuracy within the adaptive basis scheme.
Theoretically, the method may dramatically reduce the impact of dimensionality
in function approximation, and numerically the method is demonstrated to
perform well on problems with dimension up to 1000. | [
0,
0,
1,
1,
0,
0
] | [
"Mathematics",
"Statistics"
] |
Title: Deep Learning Methods for Efficient Large Scale Video Labeling,
Abstract: We present a solution to "Google Cloud and YouTube-8M Video Understanding
Challenge" that ranked 5th place. The proposed model is an ensemble of three
model families, two frame level and one video level. The training was performed
on augmented dataset, with cross validation. | [
1,
0,
0,
1,
0,
0
] | [
"Computer Science"
] |
Title: Low-level Active Visual Navigation: Increasing robustness of vision-based localization using potential fields,
Abstract: This paper proposes a low-level visual navigation algorithm to improve visual
localization of a mobile robot. The algorithm, based on artificial potential
fields, associates each feature in the current image frame with an attractive
or neutral potential energy, with the objective of generating a control action
that drives the vehicle towards the goal, while still favoring feature rich
areas within a local scope, thus improving the localization performance. One
key property of the proposed method is that it does not rely on mapping, and
therefore it is a lightweight solution that can be deployed on miniaturized
aerial robots, in which memory and computational power are major constraints.
Simulations and real experimental results using a mini quadrotor equipped with
a downward looking camera demonstrate that the proposed method can effectively
drive the vehicle to a designated goal through a path that prevents
localization failure. | [
1,
0,
0,
0,
0,
0
] | [
"Computer Science",
"Robotics"
] |
Title: Detecting Cyber-Physical Attacks in Additive Manufacturing using Digital Audio Signing,
Abstract: Additive Manufacturing (AM, or 3D printing) is a novel manufacturing
technology that is being adopted in industrial and consumer settings. However,
the reliance of this technology on computerization has raised various security
concerns. In this paper we address sabotage via tampering with the 3D printing
process. We present an object verification system using side-channel
emanations: sound generated by onboard stepper motors. The contributions of
this paper are following. We present two algorithms: one which generates a
master audio fingerprint for the unmodified printing process, and one which
computes the similarity between other print recordings and the master audio
fingerprint. We then evaluate the deviation due to tampering, focusing on the
detection of minimal tampering primitives. By detecting the deviation at the
time of its occurrence, we can stop the printing process for compromised
objects, thus save time and prevent material waste. We discuss impacts on the
method by aspects like background noise, or different audio recorder positions.
We further outline our vision with use cases incorporating our approach. | [
1,
0,
0,
0,
0,
0
] | [
"Computer Science"
] |
Title: Short-wavelength out-of-band EUV emission from Sn laser-produced plasma,
Abstract: We present the results of spectroscopic measurements in the extreme
ultraviolet (EUV) regime (7-17 nm) of molten tin microdroplets illuminated by a
high-intensity 3-J, 60-ns Nd:YAG laser pulse. The strong 13.5 nm emission from
this laser-produced plasma is of relevance for next-generation nanolithography
machines. Here, we focus on the shorter wavelength features between 7 and 12 nm
which have so far remained poorly investigated despite their diagnostic
relevance. Using flexible atomic code calculations and local thermodynamic
equilibrium arguments, we show that the line features in this region of the
spectrum can be explained by transitions from high-lying configurations within
the Sn$^{8+}$-Sn$^{15+}$ ions. The dominant transitions for all ions but
Sn$^{8+}$ are found to be electric-dipole transitions towards the $n$=4 ground
state from the core-excited configuration in which a 4$p$ electron is promoted
to the 5$s$ sub-shell. Our results resolve some long-standing spectroscopic
issues and provide reliable charge state identification for Sn laser-produced
plasma, which could be employed as a useful tool for diagnostic purposes. | [
0,
1,
0,
0,
0,
0
] | [
"Physics"
] |
Title: Compact Cardinals and Eight Values in Cichoń's Diagram,
Abstract: Assuming three strongly compact cardinals, it is consistent that \[ \aleph_1
< \mathrm{add}(\mathrm{null}) < \mathrm{cov}(\mathrm{null}) < \mathfrak{b} <
\mathfrak{d} < \mathrm{non}(\mathrm{null}) < \mathrm{cof}(\mathrm{null}) <
2^{\aleph_0}.\] Under the same assumption, it is consistent that \[ \aleph_1 <
\mathrm{add}(\mathrm{null}) < \mathrm{cov}(\mathrm{null}) <
\mathrm{non}(\mathrm{meager}) < \mathrm{cov}(\mathrm{meager}) <
\mathrm{non}(\mathrm{null}) < \mathrm{cof}(\mathrm{null}) < 2^{\aleph_0}.\] | [
0,
0,
1,
0,
0,
0
] | [
"Mathematics"
] |
Title: Bootstrapping single-channel source separation via unsupervised spatial clustering on stereo mixtures,
Abstract: Separating an audio scene into isolated sources is a fundamental problem in
computer audition, analogous to image segmentation in visual scene analysis.
Source separation systems based on deep learning are currently the most
successful approaches for solving the underdetermined separation problem, where
there are more sources than channels. Traditionally, such systems are trained
on sound mixtures where the ground truth decomposition is already known. Since
most real-world recordings do not have such a decomposition available, this
limits the range of mixtures one can train on, and the range of mixtures the
learned models may successfully separate. In this work, we use a simple blind
spatial source separation algorithm to generate estimated decompositions of
stereo mixtures. These estimates, together with a weighting scheme in the
time-frequency domain, based on confidence in the separation quality, are used
to train a deep learning model that can be used for single-channel separation,
where no source direction information is available. This demonstrates how a
simple cue such as the direction of origin of source can be used to bootstrap a
model for source separation that can be used in situations where that cue is
not available. | [
1,
0,
0,
0,
0,
0
] | [
"Computer Science"
] |
Title: Origin of the pressure-dependent T$_c$ valley in superconducting simple cubic phosphorus,
Abstract: Motivated by recent experiments, we investigate the pressure-dependent
electronic structure and electron-phonon (\emph{e-ph}) coupling for simple
cubic phosphorus by performing first-principle calculations within the full
potential linearized augmented plane wave method. As a function of increasing
pressure, our calculations show a valley feature in T$_c$, followed by an
eventual decrease for higher pressures. We demonstrate that this T$_c$ valley
at low pressures is due to two nearby Lifshitz transitions, as we analyze the
band-resolved contributions to the \emph{e-ph} coupling. Below the first
Lifshitz transition, the phonon hardening and shrinking of the $\gamma$ Fermi
surface with $s$ orbital character results in a decreased T$_c$ with increasing
pressure. After the second Lifshitz transition, the appearance of $\delta$
Fermi surfaces with $3d$ orbital character generate strong \emph{e-ph}
inter-band couplings in $\alpha\delta$ and $\beta\delta$ channels, and hence
lead to an increase of T$_c$. For higher pressures, the phonon hardening
finally dominates, and T$_c$ decreases again. Our study reveals that the
intriguing T$_c$} valley discovered in experiment can be attributed to Lifshitz
transitions, while the plateau of T$_c$ detected at intermediate pressures
appears to be beyond the scope of our analysis. This strongly suggests that
besides \emph{e-ph} coupling, electronic correlations along with plasmonic
contributions may be relevant for simple cubic phosphorous. Our findings hint
at the notion that increasing pressure can shift the low-energy orbital weight
towards $d$ character, and as such even trigger an enhanced importance of
orbital-selective electronic correlations despite an increase of the overall
bandwidth. | [
0,
1,
0,
0,
0,
0
] | [
"Physics"
] |
Title: V-cycle multigrid algorithms for discontinuous Galerkin methods on non-nested polytopic meshes,
Abstract: In this paper we analyse the convergence properties of V-cycle multigrid
algorithms for the numerical solution of the linear system of equations arising
from discontinuous Galerkin discretization of second-order elliptic partial
differential equations on polytopal meshes. Here, the sequence of spaces that
stands at the basis of the multigrid scheme is possibly non nested and is
obtained based on employing agglomeration with possible edge/face coarsening.
We prove that the method converges uniformly with respect to the granularity of
the grid and the polynomial approximation degree p, provided that the number of
smoothing steps, which depends on p, is chosen sufficiently large. | [
1,
0,
0,
0,
0,
0
] | [
"Mathematics",
"Computer Science"
] |
Title: Average Case Constant Factor Time and Distance Optimal Multi-Robot Path Planning in Well-Connected Environments,
Abstract: Fast algorithms for optimal multi-robot path planning are sought after in
many real-world applications. Known methods, however, generally do not
simultaneously guarantee good solution optimality and fast run time (e.g.,
polynomial). In this work, we develop a low-polynomial running time algorithm,
called SplitAndGroup (SAG),that solves the multi-robot path planning problem on
grids and grid-like environments and produces constant factor makespan-optimal
solutions in the average case. That is, SAG is an average case
O(1)-approximation algorithm. SAG computes solutions with sub-linear makespan
and is capable of handling cases when the density of robots is extremely high -
in a graph-theoretic setting, the algorithm supports cases where all vertices
of the underlying graph are occupied by robots. SAG attains its desirable
properties through a careful combination of divide-and-conquer technique and
network flow based methods for routing the robots. Solutions from SAG, in a
weaker sense, is also a constant factor approximation on total distance
optimality. | [
1,
0,
0,
0,
0,
0
] | [
"Computer Science",
"Mathematics"
] |
Title: Gaussian Process based Passivation of a Class of Nonlinear Systems with Unknown Dynamics,
Abstract: The paper addresses the problem of passivation of a class of nonlinear
systems where the dynamics are unknown. For this purpose, we use the highly
flexible, data-driven Gaussian process regression for the identification of the
unknown dynamics for feed-forward compensation. The closed loop system of the
nonlinear system, the Gaussian process model and a feedback control law is
guaranteed to be semi-passive with a specific probability. The predicted
variance of the Gaussian process regression is used to bound the model error
which additionally allows to specify the state space region where the
closed-loop system behaves passive. Finally, the theoretical results are
illustrated by a simulation. | [
1,
0,
0,
0,
0,
0
] | [
"Computer Science",
"Mathematics"
] |
Title: A Bayesian Method for Joint Clustering of Vectorial Data and Network Data,
Abstract: We present a new model-based integrative method for clustering objects given
both vectorial data, which describes the feature of each object, and network
data, which indicates the similarity of connected objects. The proposed general
model is able to cluster the two types of data simultaneously within one
integrative probabilistic model, while traditional methods can only handle one
data type or depend on transforming one data type to another. Bayesian
inference of the clustering is conducted based on a Markov chain Monte Carlo
algorithm. A special case of the general model combining the Gaussian mixture
model and the stochastic block model is extensively studied. We used both
synthetic data and real data to evaluate this new method and compare it with
alternative methods. The results show that our simultaneous clustering method
performs much better. This improvement is due to the power of the model-based
probabilistic approach for efficiently integrating information. | [
1,
0,
0,
1,
0,
0
] | [
"Computer Science",
"Statistics"
] |
Title: Pointwise-generalized-inverses of linear maps between C$^*$-algebras and JB$^*$-triples,
Abstract: We study pointwise-generalized-inverses of linear maps between
C$^*$-algebras. Let $\Phi$ and $\Psi$ be linear maps between complex Banach
algebras $A$ and $B$. We say that $\Psi$ is a pointwise-generalized-inverse of
$\Phi$ if $\Phi(aba)=\Phi(a)\Psi(b)\Phi(a),$ for every $a,b\in A$. The pair
$(\Phi,\Psi)$ is Jordan-triple multiplicative if $\Phi$ is a
pointwise-generalized-inverse of $\Psi$ and the latter is a
pointwise-generalized-inverse of $\Phi$. We study the basic properties of this
maps in connection with Jordan homomorphism, triple homomorphisms and strongly
preservers. We also determine conditions to guarantee the automatic continuity
of the pointwise-generalized-inverse of continuous operator between
C$^*$-algebras. An appropriate generalization is introduced in the setting of
JB$^*$-triples. | [
0,
0,
1,
0,
0,
0
] | [
"Mathematics"
] |
Title: A constrained control-planning strategy for redundant manipulators,
Abstract: This paper presents an interconnected control-planning strategy for redundant
manipulators, subject to system and environmental constraints. The method
incorporates low-level control characteristics and high-level planning
components into a robust strategy for manipulators acting in complex
environments, subject to joint limits. This strategy is formulated using an
adaptive control rule, the estimated dynamic model of the robotic system and
the nullspace of the linearized constraints. A path is generated that takes
into account the capabilities of the platform. The proposed method is
computationally efficient, enabling its implementation on a real multi-body
robotic system. Through experimental results with a 7 DOF manipulator, we
demonstrate the performance of the method in real-world scenarios. | [
1,
0,
0,
0,
0,
0
] | [
"Computer Science",
"Mathematics"
] |
Title: Lagrangian for RLC circuits using analogy with the classical mechanics concepts,
Abstract: We study and formulate the Lagrangian for the LC, RC, RL, and RLC circuits by
using the analogy concept with the mechanical problem in classical mechanics
formulations. We found that the Lagrangian for the LC and RLC circuits are
governed by two terms i. e. kinetic energy-like and potential energy-like
terms. The Lagrangian for the RC circuit is only a contribution from the
potential energy-like term and the Lagrangian for the RL circuit is only from
the kinetic energy-like term. | [
0,
1,
0,
0,
0,
0
] | [
"Physics"
] |
Title: A note on recent criticisms to Birnbaum's theorem,
Abstract: In this note, we provide critical commentary on two articles that cast doubt
on the validity and implications of Birnbaum's theorem: Evans (2013) and Mayo
(2014). In our view, the proof is correct and the consequences of the theorem
are alive and well. | [
0,
0,
1,
1,
0,
0
] | [
"Statistics"
] |
Title: On the radius of spatial analyticity for the quartic generalized KdV equation,
Abstract: Lower bound on the rate of decrease in time of the uniform radius of spatial
analyticity of solutions to the quartic generalized KdV equation is derived,
which improves an earlier result by Bona, Grujić and Kalisch. | [
0,
0,
1,
0,
0,
0
] | [
"Mathematics",
"Physics"
] |
Title: Calibrating Noise to Variance in Adaptive Data Analysis,
Abstract: Datasets are often used multiple times and each successive analysis may
depend on the outcome of previous analyses. Standard techniques for ensuring
generalization and statistical validity do not account for this adaptive
dependence. A recent line of work studies the challenges that arise from such
adaptive data reuse by considering the problem of answering a sequence of
"queries" about the data distribution where each query may depend arbitrarily
on answers to previous queries.
The strongest results obtained for this problem rely on differential privacy
-- a strong notion of algorithmic stability with the important property that it
"composes" well when data is reused. However the notion is rather strict, as it
requires stability under replacement of an arbitrary data element. The simplest
algorithm is to add Gaussian (or Laplace) noise to distort the empirical
answers. However, analysing this technique using differential privacy yields
suboptimal accuracy guarantees when the queries have low variance. Here we
propose a relaxed notion of stability that also composes adaptively. We
demonstrate that a simple and natural algorithm based on adding noise scaled to
the standard deviation of the query provides our notion of stability. This
implies an algorithm that can answer statistical queries about the dataset with
substantially improved accuracy guarantees for low-variance queries. The only
previous approach that provides such accuracy guarantees is based on a more
involved differentially private median-of-means algorithm and its analysis
exploits stronger "group" stability of the algorithm. | [
1,
0,
0,
0,
0,
0
] | [
"Computer Science",
"Statistics"
] |
Title: The Lyman-alpha forest power spectrum from the XQ-100 Legacy Survey,
Abstract: We present the Lyman-$\alpha$ flux power spectrum measurements of the XQ-100
sample of quasar spectra obtained in the context of the European Southern
Observatory Large Programme "Quasars and their absorption lines: a legacy
survey of the high redshift universe with VLT/XSHOOTER". Using $100$ quasar
spectra with medium resolution and signal-to-noise ratio we measure the power
spectrum over a range of redshifts $z = 3 - 4.2$ and over a range of scales $k
= 0.003 - 0.06\,\mathrm{s\,km^{-1}}$. The results agree well with the
measurements of the one-dimensional power spectrum found in the literature. The
data analysis used in this paper is based on the Fourier transform and has been
tested on synthetic data. Systematic and statistical uncertainties of our
measurements are estimated, with a total error (statistical and systematic)
comparable to the one of the BOSS data in the overlapping range of scales, and
smaller by more than $50\%$ for higher redshift bins ($z>3.6$) and small scales
($k > 0.01\,\mathrm{s\,km^{-1}}$). The XQ-100 data set has the unique feature
of having signal-to-noise ratios and resolution intermediate between the two
data sets that are typically used to perform cosmological studies, i.e. BOSS
and high-resolution spectra (e.g. UVES/VLT or HIRES). More importantly, the
measured flux power spectra span the high redshift regime which is usually more
constraining for structure formation models. | [
0,
1,
0,
0,
0,
0
] | [
"Physics"
] |
Title: Conditional Independence, Conditional Mean Independence, and Zero Conditional Covariance,
Abstract: Investigation of the reversibility of the directional hierarchy in the
interdependency among the notions of conditional independence, conditional mean
independence, and zero conditional covariance, for two random variables X and Y
given a conditioning element Z which is not constrained by any topological
restriction on its range, reveals that if the first moments of X, Y, and XY
exist, then conditional independence implies conditional mean independence and
conditional mean independence implies zero conditional covariance, but the
direction of the hierarchy is not reversible in general. If the conditional
expectation of Y given X and Z is "affine in X," which happens when X is
Bernoulli, then the "intercept" and "slope" of the conditional expectation
(that is, the nonparametric regression function) equal the "intercept" and
"slope" of the "least-squares linear regression function", as a result of which
zero conditional covariance implies conditional mean independence. | [
0,
0,
1,
1,
0,
0
] | [
"Statistics",
"Mathematics"
] |
Title: Gradient descent GAN optimization is locally stable,
Abstract: Despite the growing prominence of generative adversarial networks (GANs),
optimization in GANs is still a poorly understood topic. In this paper, we
analyze the "gradient descent" form of GAN optimization i.e., the natural
setting where we simultaneously take small gradient steps in both generator and
discriminator parameters. We show that even though GAN optimization does not
correspond to a convex-concave game (even for simple parameterizations), under
proper conditions, equilibrium points of this optimization procedure are still
\emph{locally asymptotically stable} for the traditional GAN formulation. On
the other hand, we show that the recently proposed Wasserstein GAN can have
non-convergent limit cycles near equilibrium. Motivated by this stability
analysis, we propose an additional regularization term for gradient descent GAN
updates, which \emph{is} able to guarantee local stability for both the WGAN
and the traditional GAN, and also shows practical promise in speeding up
convergence and addressing mode collapse. | [
1,
0,
1,
1,
0,
0
] | [
"Computer Science",
"Mathematics"
] |
Title: Transition rates and radiative lifetimes of Ca I,
Abstract: We tabulate spontaneous emission rates for all possible 811
electric-dipole-allowed transitions between the 75 lowest-energy states of Ca
I. These involve the $4sns$ ($n=4-8$), $4snp$ ($n=4-7$), $4snd$ ($n=3-6$),
$4snf$ ($n=4-6$), $4p^2$, and $3d4p$ electronic configurations. We compile the
transition rates by carrying out ab initio relativistic calculations using the
combined method of configuration interaction and many-body perturbation theory.
The results are compared to the available literature values. The tabulated
rates can be useful in various applications, such as optimizing laser cooling
in magneto-optical traps, estimating various systematic effects in optical
clocks and evaluating static or dynamic polarizabilities and long-range
atom-atom interaction coefficients and related atomic properties. | [
0,
1,
0,
0,
0,
0
] | [
"Physics"
] |
Title: Local and collective magnetism of EuFe$_2$As$_2$,
Abstract: We present an experimental study of the local and collective magnetism of
$\mathrm{EuFe_2As_2}$, that is isostructural with the high temperature
superconductor parent compound $\mathrm{BaFe_2As_2}$. In contrast to
$\mathrm{BaFe_2As_2}$, where only Fe spins order, $\mathrm{EuFe_2As_2}$ has an
additional magnetic transition below 20 K due to the ordering of the Eu$^{2+}$
spins ($J =7/2$, with $L=0$ and $S=7/2$) in an A-type antiferromagnetic texture
(ferromagnetic layers stacked antiferromagnetically). This may potentially
affect the FeAs layer and its local and correlated magnetism. Fe-K$_\beta$
x-ray emission experiments on $\mathrm{EuFe_2As_2}$ single crystals reveal a
local magnetic moment of 1.3$\pm0.15~\mu_B$ at 15 K that slightly increases to
1.45$\pm0.15~\mu_B$ at 300 K. Resonant inelastic x-ray scattering (RIXS)
experiments performed on the same crystals show dispersive broad (in energy)
magnetic excitations along $\mathrm{(0, 0)\rightarrow(1, 0)}$ and $\mathrm{(0,
0)\rightarrow(1, 1)}$ with a bandwidth on the order of 170-180 meV. These
results on local and collective magnetism are in line with other parent
compounds of the $\mathrm{AFe_2As_2}$ series ($A=$ Ba, Ca, and Sr), especially
the well characterized $\mathrm{BaFe_2As_2}$. Thus, our experiments lead us to
the conclusion that the effect of the high magnetic moment of Eu on the
magnitude of both Fe local magnetic moment and spin excitations is small and
confined to low energy excitations. | [
0,
1,
0,
0,
0,
0
] | [
"Physics"
] |
Title: Newton slopes for twisted Artin--Schreier--Witt Towers,
Abstract: We fix a monic polynomial $f(x) \in \mathbb F_q[x]$ over a finite field of
characteristic $p$ of degree relatively prime to $p$. Let $a\mapsto \omega(a)$
be the Teichmüller lift of $\mathbb F_q$, and let $\chi:\mathbb{Z}\to \mathbb
C_p^\times$ be a finite character of $\mathbb Z_p$. The $L$-function associated
to the polynomial $f$ and the so-called twisted character $\omega^u\times \chi$
is denoted by $L_f(\omega^u,\chi,s)$. We prove that, when the conductor of the
character is large enough, the $p$-adic Newton slopes of this $L$-function form
arithmetic progressions. | [
0,
0,
1,
0,
0,
0
] | [
"Mathematics"
] |
Title: End-to-end distance and contour length distribution functions of DNA helices,
Abstract: We present a computational method to evaluate the end-to-end and the contour
length distribution functions of short DNA molecules described by a mesoscopic
Hamiltonian. The method generates a large statistical ensemble of possible
configurations for each dimer in the sequence, selects the global equilibrium
twist conformation for the molecule and determines the average base pair
distances along the molecule backbone. Integrating over the base pair radial
and angular fluctuations, we derive the room temperature distribution functions
as a function of the sequence length. The obtained values for the most probable
end-to-end distance and contour length distance, providing a measure of the
global molecule size, are used to examine the DNA flexibility at short length
scales. It is found that, also in molecules with less than $\sim 60$ base
pairs, coiled configurations maintain a large statistical weight and,
consistently, the persistence lengths may be much smaller than in kilo-base
DNA. | [
0,
0,
0,
0,
1,
0
] | [
"Quantitative Biology",
"Physics"
] |
Title: Online Estimation of Multiple Dynamic Graphs in Pattern Sequences,
Abstract: Many time-series data including text, movies, and biological signals can be
represented as sequences of correlated binary patterns. These patterns may be
described by weighted combinations of a few dominant structures that underpin
specific interactions among the binary elements. To extract the dominant
correlation structures and their contributions to generating data in a
time-dependent manner, we model the dynamics of binary patterns using the
state-space model of an Ising-type network that is composed of multiple
undirected graphs. We provide a sequential Bayes algorithm to estimate the
dynamics of weights on the graphs while gaining the graph structures online.
This model can uncover overlapping graphs underlying the data better than a
traditional orthogonal decomposition method, and outperforms an original
time-dependent full Ising model. We assess the performance of the method by
simulated data, and demonstrate that spontaneous activity of cultured
hippocampal neurons is represented by dynamics of multiple graphs. | [
1,
0,
0,
1,
1,
0
] | [
"Computer Science",
"Statistics",
"Quantitative Biology"
] |
Title: Fluid Communities: A Competitive, Scalable and Diverse Community Detection Algorithm,
Abstract: We introduce a community detection algorithm (Fluid Communities) based on the
idea of fluids interacting in an environment, expanding and contracting as a
result of that interaction. Fluid Communities is based on the propagation
methodology, which represents the state-of-the-art in terms of computational
cost and scalability. While being highly efficient, Fluid Communities is able
to find communities in synthetic graphs with an accuracy close to the current
best alternatives. Additionally, Fluid Communities is the first
propagation-based algorithm capable of identifying a variable number of
communities in network. To illustrate the relevance of the algorithm, we
evaluate the diversity of the communities found by Fluid Communities, and find
them to be significantly different from the ones found by alternative methods. | [
1,
1,
0,
0,
0,
0
] | [
"Computer Science",
"Statistics"
] |
Title: Identification of Dynamic Systems with Interval Arithmetic,
Abstract: This paper aims to identify three electrical systems: a series RLC circuit, a
motor/generator coupled system, and the Duffing-Ueda oscillator. In order to
obtain the system's models was used the error reduction ratio and the Akaike
information criterion. Our approach to handle the numerical errors was the
interval arithmetic by means of the resolution of the least squares estimation.
The routines was implemented in Intlab, a Matlab toolbox devoted to arithmetic
interval. Finally, the interval RMSE was calculated to verify the quality of
the obtained models. The applied methodology was satisfactory, since the
obtained intervals encompass the system's data and allow to demonstrate how the
numerical errors affect the answers. | [
1,
0,
0,
0,
0,
0
] | [
"Computer Science",
"Mathematics"
] |
Title: Safety-Aware Apprenticeship Learning,
Abstract: Apprenticeship learning (AL) is a kind of Learning from Demonstration
techniques where the reward function of a Markov Decision Process (MDP) is
unknown to the learning agent and the agent has to derive a good policy by
observing an expert's demonstrations. In this paper, we study the problem of
how to make AL algorithms inherently safe while still meeting its learning
objective. We consider a setting where the unknown reward function is assumed
to be a linear combination of a set of state features, and the safety property
is specified in Probabilistic Computation Tree Logic (PCTL). By embedding
probabilistic model checking inside AL, we propose a novel
counterexample-guided approach that can ensure safety while retaining
performance of the learnt policy. We demonstrate the effectiveness of our
approach on several challenging AL scenarios where safety is essential. | [
1,
0,
0,
0,
0,
0
] | [
"Computer Science",
"Statistics"
] |
Title: Solitary wave solutions and their interactions for fully nonlinear water waves with surface tension in the generalized Serre equations,
Abstract: Some effects of surface tension on fully-nonlinear, long, surface water waves
are studied by numerical means. The differences between various solitary waves
and their interactions in subcritical and supercritical surface tension regimes
are presented. Analytical expressions for new peaked travelling wave solutions
are presented in the case of critical surface tension. The numerical
experiments were performed using a high-accurate finite element method based on
smooth cubic splines and the four-stage, classical, explicit Runge-Kutta method
of order four. | [
0,
1,
1,
0,
0,
0
] | [
"Physics",
"Mathematics"
] |
Title: Relative weak mixing of W*-dynamical systems via joinings,
Abstract: A characterization of relative weak mixing in W*-dynamical systems in terms
of a relatively independent joining is proven. | [
0,
0,
1,
0,
0,
0
] | [
"Mathematics"
] |
Title: A note on minimal dispersion of point sets in the unit cube,
Abstract: We study the dispersion of a point set, a notion closely related to the
discrepancy. Given a real $r\in (0,1)$ and an integer $d\geq 2$, let $N(r,d)$
denote the minimum number of points inside the $d$-dimensional unit cube
$[0,1]^d$ such that they intersect every axis-aligned box inside $[0,1]^d$ of
volume greater than $r$. We prove an upper bound on $N(r,d)$, matching a lower
bound of Aistleitner et al. up to a multiplicative constant depending only on
$r$. This fully determines the rate of growth of $N(r,d)$ if $r\in(0,1)$ is
fixed. | [
1,
0,
0,
0,
0,
0
] | [
"Mathematics"
] |
Title: Snyder Like Modified Gravity in Newton's Spacetime,
Abstract: This work is focused on searching a geodesic interpretation of the dynamics
of a particle under the effects of a Snyder like deformation in the background
of the Kepler problem. In order to accomplish that task, a newtonian spacetime
is used. Newtonian spacetime is not a metric manifold, but allows to introduce
a torsion free connection in order to interpret the dynamic equations of the
deformed Kepler problem as geodesics in a curved spacetime. These geodesics and
the curvature terms of the Riemann and Ricci tensors show a mass and a
fundamental length dependence as expected, but are velocity independent. In
this sense, the effect of introducing a deformed algebra is examinated and the
corresponding curvature terms calculated, as well as the modifications of the
integrals of motion. | [
0,
1,
0,
0,
0,
0
] | [
"Physics",
"Mathematics"
] |
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