text
stringlengths 6
128k
|
|---|
Developing ontologies can be expensive, time-consuming, as well as difficult
to develop and maintain. This is especially true for more expressive and/or
larger ontologies. Some ontologies are, however, relatively repetitive, reusing
design patterns; building these with both generic and bespoke patterns should
reduce duplication and increase regularity which in turn should impact on the
cost of development.
Here we report on the usage of patterns applied to two biomedical ontologies:
firstly a novel ontology for karyotypes which has been built ground-up using a
pattern based approach; and, secondly, our initial refactoring of the SIO
ontology to make explicit use of patterns at development time. To enable this,
we use the Tawny-OWL library which enables full-programmatic development of
ontologies. We show how this approach can generate large numbers of classes
from much simpler data structures which is highly beneficial within biomedical
ontology engineering.
|
Improved mobility not only contributes to more intensive human activities but
also facilitates the spread of communicable disease, thus constituting a major
threat to billions of urban commuters. In this study, we present a multi-city
investigation of communicable diseases percolating among metro travelers. We
use smart card data from three megacities in China to construct
individual-level contact networks, based on which the spread of disease is
modeled and studied. We observe that, though differing in urban forms, network
layouts, and mobility patterns, the metro systems of the three cities share
similar contact network structures. This motivates us to develop a universal
generation model that captures the distributions of the number of contacts as
well as the contact duration among individual travelers. This model explains
how the structural properties of the metro contact network are associated with
the risk level of communicable diseases. Our results highlight the
vulnerability of urban mass transit systems during disease outbreaks and
suggest important planning and operation strategies for mitigating the risk of
communicable diseases.
|
Modern high load applications store data using multiple database instances.
Such an architecture requires data consistency, and it is important to ensure
even distribution of data among nodes. Load balancing is used to achieve these
goals.
Hashing is the backbone of virtually all load balancing systems. Since the
introduction of classic Consistent Hashing, many algorithms have been devised
for this purpose.
One of the purposes of the load balancer is to ensure storage cluster
scalability. It is crucial for the performance of the whole system to transfer
as few data records as possible during node addition or removal. The load
balancer hashing algorithm has the greatest impact on this process.
In this paper we experimentally evaluate several hashing algorithms used for
load balancing, conducting both simulated and real system experiments. To
evaluate algorithm performance, we have developed a benchmark suite based on
Unidata MDM~ -- a scalable toolkit for various Master Data Management (MDM)
applications. For assessment, we have employed three criteria~ -- uniformity of
the produced distribution, the number of moved records, and computation speed.
Following the results of our experiments, we have created a table, in which
each algorithm is given an assessment according to the abovementioned criteria.
|
This study examines the relationship between globalization and income
inequality, utilizing panel data spanning from 1992 to 2020. Globalization is
measured by the World Bank global-link indicators such as FDI, Remittance,
Trade Openness, and Migration while income inequality is measured by Gini
Coefficient and the median income of 50% of the population. The fixed effect
panel data analysis provides empirical evidence indicating that globalization
tends to reduce income inequality, though its impact varies between developed
and developing countries. The analysis reveals a strong negative correlation
between net foreign direct investment (FDI) inflows and inequality in
developing countries, while no such relationship was found for developed
countries.The relationship holds even if we consider an alternative measure of
inequality. However, when dividing countries by developed and developing
groups, no statistically significant relationship was observed. Policymakers
can use these findings to support efforts to increase FDI, trade, tourism, and
migration to promote growth and reduce income inequality.
|
Maximum likelihood estimation of a log-concave probability density is
formulated as a convex optimization problem and shown to have an equivalent
dual formulation as a constrained maximum Shannon entropy problem. Closely
related maximum Renyi entropy estimators that impose weaker concavity
restrictions on the fitted density are also considered, notably a minimum
Hellinger discrepancy estimator that constrains the reciprocal of the
square-root of the density to be concave. A limiting form of these estimators
constrains solutions to the class of quasi-concave densities.
|
The effects of ground-state correlations on the dipole and quadrupole
excitations are studied for $^{40}$Ca and $^{48}$Ca using the extended random
phase approximation (ERPA) derived from the time-dependent density-matrix
theory. Large effects of the ground-state correlations are found in the
fragmentation of the giant quadrupole resonance in $^{40}$Ca and in the
low-lying dipole strength in $^{48}$Ca. It is discussed that the former is due
to a mixing of different configurations in the ground state and the latter is
from the partial occupation of the neutron single-particle states. The dipole
and quadrupole strength distributions below 10 MeV calculated in ERPA are in
qualitatively agreement with experiment.
|
Many challenging image processing tasks can be described by an ill-posed
linear inverse problem: deblurring, deconvolution, inpainting, compressed
sensing, and superresolution all lie in this framework. Traditional inverse
problem solvers minimize a cost function consisting of a data-fit term, which
measures how well an image matches the observations, and a regularizer, which
reflects prior knowledge and promotes images with desirable properties like
smoothness. Recent advances in machine learning and image processing have
illustrated that it is often possible to learn a regularizer from training data
that can outperform more traditional regularizers. We present an end-to-end,
data-driven method of solving inverse problems inspired by the Neumann series,
which we call a Neumann network. Rather than unroll an iterative optimization
algorithm, we truncate a Neumann series which directly solves the linear
inverse problem with a data-driven nonlinear regularizer. The Neumann network
architecture outperforms traditional inverse problem solution methods,
model-free deep learning approaches, and state-of-the-art unrolled iterative
methods on standard datasets. Finally, when the images belong to a union of
subspaces and under appropriate assumptions on the forward model, we prove
there exists a Neumann network configuration that well-approximates the optimal
oracle estimator for the inverse problem and demonstrate empirically that the
trained Neumann network has the form predicted by theory.
|
The Rashba effect leads to a chiral precession of the spins of moving
electrons while the Dzyaloshinskii-Moriya interaction (DMI) generates
preference towards a chiral profile of local spins. We predict that the
exchange interaction between these two spin systems results in a 'chiral'
magnetoresistance depending on the chirality of the local spin texture. We
observe this magnetoresistance by measuring the domain wall (DW) resistance in
a uniquely designed Pt/Co/Pt zigzag wire, and by changing the chirality of the
DW with applying an in-plane magnetic field. A chirality-dependent DW
resistance is found, and a quantitative analysis shows a good agreement with a
theory based on the Rashba model. Moreover, the DW resistance measurement
allows us to independently determine the strength of the Rashba effect and the
DMI simultaneously, and the result implies a possible correlation between the
Rashba effect, the DMI, and the symmetric Heisenberg exchange.
|
We find the free-energy in the thermodynamic limit of a one dimensional XY
model associated to a system of N qubits. The coupling among the sigma_i^z is a
long range two bodies random interaction. The randomness in the couplings is
the typical interaction of the Hopfield model with p patterns (p<<N), with the
patterns being p sequences of independent identically distributed (i.i.d.)
random variables assuming values \pm 1 with probability 1/2. We show also that
in the case p < alpha N the free-energy is asymptotically independent from the
choice of the patterns, i.e. it is self-averaging. The Hamiltonian is the one
used by (Neigovzen et al. 2009) in their experiment.
|
The ABC-stacked N-layer-graphene family of two-dimensional electron systems
is described at low energies by two remarkably flat bands with Bloch states
that have strongly momentum-dependent phase differences between carbon
pi-orbital amplitudes on different layers, and large associated momentum space
Berry phases. These properties are most easily understood using a simplified
model with only nearest-neighbor inter-layer hopping which leads to gapless
semiconductor electronic structure, with p^N dispersion in both conduction and
valence bands. We report on a study of the electronic band structures of
trilayers which uses ab initio density functional theory and k*p theory to fit
the parameters of a pi-band tight-binding model. We find that when remote
interlayer hopping is retained, the triple Dirac point of the simplified model
is split into three single Dirac points located along the three KM directions.
External potential differences between top and bottom layers are strongly
screened by charge transfer within the trilayer, but still open an energy gap
at overall neutrality.
|
The ability that one system immediately affects another one by using local
measurements is regarded as quantum steering, which can be detected by various
steering criteria. Recently, Mondal et al. [Phys. Rev. A 98, 052330 (2018)]
derived the complementarity relations of coherence steering criteria, and
revealed that the quantum steering of system can be observed through the
average coherence of subsystem. Here, we experimentally verify the
complementarity relations between quantum steering criteria by employing
two-photon Bell-like states and three Pauli operators. The results demonstrate
that if prepared quantum states can violate two setting coherence steering
criteria and turn out to be steerable states, then it cannot violate the
complementary settings criteria. Three measurement settings inequality, which
establish a complementarity relation between these two coherence steering
criteria, always holds in experiment. Besides, we experimentally certify that
the strengths of coherence steering criteria dependent on the choice of
coherence measure. In comparison with two setting coherence steering criteria
based on l1 norm of coherence and relative entropy of coherence, our
experimental results show that the steering criterion based on skew information
of coherence is more stronger in detecting the steerability of quantum states.
Thus, our experimental demonstrations can deepen the understanding of the
relation between the quantum steering and quantum coherence.
|
In the $d$-Scattered Set problem we are asked to select at least $k$ vertices
of a given graph, so that the distance between any pair is at least $d$. We
study the problem's (in-)approximability and offer improvements and extensions
of known results for Independent Set, of which the problem is a generalization.
Specifically, we show:
- A lower bound of $\Delta^{\lfloor d/2\rfloor-\epsilon}$ on the
approximation ratio of any polynomial-time algorithm for graphs of maximum
degree $\Delta$ and an improved upper bound of $O(\Delta^{\lfloor d/2\rfloor})$
on the approximation ratio of any greedy scheme for this problem.
- A polynomial-time $2\sqrt{n}$-approximation for bipartite graphs and even
values of $d$, that matches the known lower bound by considering the only
remaining case.
- A lower bound on the complexity of any $\rho$-approximation algorithm of
(roughly) $2^{\frac{n^{1-\epsilon}}{\rho d}}$ for even $d$ and
$2^{\frac{n^{1-\epsilon}}{\rho(d+\rho)}}$ for odd $d$ (under the randomized
ETH), complemented by $\rho$-approximation algorithms of running times that
(almost) match these bounds.
|
We explore the two-dimensional motion of relativistic electrons when they are
trapped in magnetic fields having spatial power-law variation. Its impacts
include lifting of degeneracy that emerged in the case of the constant magnetic
field, special alignment of Landau levels of spin-up and spin-down electrons
depending on whether the magnetic field is increasing or decreasing from the
centre, splitting of Landau levels of electrons with zero angular momentum from
that of positive one and the change in the equation of state of matter. Landau
quantization (LQ) in variable magnetic fields has interdisciplinary
applications in a variety of disciplines ranging from condensed matter to
quantum information. As examples, we discuss the increase in quantum speed of
the electron in presence of spatially increasing magnetic field; and the
attainment of super Chandrasekhar mass of white dwarfs by taking into account
LQ and Lorentz force simultaneously.
|
The quasielastic charged current (CCQE) $\nu_e n \rightarrow e^- p$
scattering is the dominant mechanism to detect appearance of a $\nu_e$ in an
almost $\nu_\mu$ flux at the 1 GeV scale. Actual experiments show a precision
below 1% and between less known background contributions, but necessary to
constraint the event excess, we have the radiative corrections. A consistent
model recently developed for the simultaneous description of elastic and
radiative $\pi N$ scattering, pion-photoproduction and single pion production
processes, both for charged and neutral current neutrino-nucleon scattering, is
extended for the evaluation of the radiative $\nu_l N\rightarrow \nu_l N
\gamma$ cross section. Our results are similar to a previous (but inconsistent)
theoretical evaluation in the low energy region, and show an increment in the
upper region where the $\Delta$ resonance becomes relevant.
|
Seasonality is one of the oldest and most elucidation-resistant issues in
suicide epidemiological research. Despite winter depression (also known as
Seasonal Affective Disorder, SAD) is known and treated since many years,
worldwide cross-sectional data from 28 countries show a lower frequency of
suicide attempts around the equinoxes and a higher frequency in spring (both in
Northern and Southern Hemisphere). This peak is not compatible with the SAD
explanation. However, in recent years epidemiological research has yielded new
results, which provide new perspectives on the matter. In fact, the discovery
of a new pathology called Post-Series Depression (PSD) could provide an
explanation of the suicide attempts pattern. The aim of this study is to
analyse weekly data in order to compare them with the TV series broadcasting.
Since medical observations in our sample are distributed over many years, in
order to compare them as best as we can with the television programming, Grey's
Anatomy series was chosen. This medical drama has been in the top 10 of most
viewed TV series since 12 years and it is broadcast all over the world, so that
it can be considered a universal and homogeneous phenomenon. A full season of
the series is split into two separate units with a hiatus around the end of the
calendar year, and it runs from September through May. Data analysis was made
in order to prove the correlation between PSD and the increase of suicide
attempts. Surprisingly, the data analysis shows that the increase of rate of
suicide attempts does not coincide with the breaks in Grey's Anatomy
scheduling, but with the series broadcasting. This therefore suggests that it
is the series itself to increase the viewer's depression.
|
In this paper, we introduce the notions of logarithmic Poisson structure and
logarithmic principal Poisson structure; we prove that the latter induces a
representation by logarithmic derivation of the module of logarithmic Kahler
differentials; therefore, it induces a differential complex from which we
derive the notion of logarithmic Poisson cohomology. We prove that Poisson
cohomology and logarithmic Poisson cohomology are equal when the Poisson
structure is logsymplectic. We give an example of non logsymplectic but
logarithmic Poisson structure for which these cohomologies are equal. We also
give an example for which these cohomologies are different. We discuss and
modify the K. Saito definition of logarithmic forms. The notes end with an
application to a prequantization of the logarithmic Poisson algebra: (C[x; y];
{x; y} = x):
|
Learning vector representations (aka. embeddings) of users and items lies at
the core of modern recommender systems. Ranging from early matrix factorization
to recently emerged deep learning based methods, existing efforts typically
obtain a user's (or an item's) embedding by mapping from pre-existing features
that describe the user (or the item), such as ID and attributes. We argue that
an inherent drawback of such methods is that, the collaborative signal, which
is latent in user-item interactions, is not encoded in the embedding process.
As such, the resultant embeddings may not be sufficient to capture the
collaborative filtering effect.
In this work, we propose to integrate the user-item interactions -- more
specifically the bipartite graph structure -- into the embedding process. We
develop a new recommendation framework Neural Graph Collaborative Filtering
(NGCF), which exploits the user-item graph structure by propagating embeddings
on it. This leads to the expressive modeling of high-order connectivity in
user-item graph, effectively injecting the collaborative signal into the
embedding process in an explicit manner. We conduct extensive experiments on
three public benchmarks, demonstrating significant improvements over several
state-of-the-art models like HOP-Rec and Collaborative Memory Network. Further
analysis verifies the importance of embedding propagation for learning better
user and item representations, justifying the rationality and effectiveness of
NGCF. Codes are available at
https://github.com/xiangwang1223/neural_graph_collaborative_filtering.
|
Let (\rho_\lambda)_{\lambda\in \Lambda} be a holomorphic family of
representations of a finitely generated group G into PSL(2,C), parameterized by
a complex manifold \Lambda . We define a notion of bifurcation current in this
context, that is, a positive closed current on \Lambda describing the
bifurcations of this family of representations in a quantitative sense. It is
the analogue of the bifurcation current introduced by DeMarco for holomorphic
families of rational mappings on the Riemann sphere. Our definition relies on
the theory of random products of matrices, so it depends on the choice of a
probability measure \mu on G.
We show that under natural assumptions on \mu, the support of the bifurcation
current coincides with the bifurcation locus of the family. We also prove that
the bifurcation current describes the asymptotic distribution of several
codimension 1 phenomena in parameter space, like accidental parabolics or new
relations, or accidental collisions between fixed points.
|
We generalize Brudno's theorem of $1$-dimensional shift dynamical system to
$\mathbb{Z}^d$ (or $\mathbb{Z}_+^d$) subshifts. That is to say, in
$\mathbb{Z}^d$ (or $\mathbb{Z}^d_+$) subshift, the Kolmogorov-Sinai entropy is
equivalent to the Kolmogorov complexity density almost everywhere for an
ergodic shift-invariant measure.
|
In this paper we prove the existence of solutions for a second order sweeping
process with a Lipschitz single valued perturbation by transforming it to a
first order problem.
|
In this paper, we present our first attempts in building a multilingual
Neural Machine Translation framework under a unified approach. We are then able
to employ attention-based NMT for many-to-many multilingual translation tasks.
Our approach does not require any special treatment on the network architecture
and it allows us to learn minimal number of free parameters in a standard way
of training. Our approach has shown its effectiveness in an under-resourced
translation scenario with considerable improvements up to 2.6 BLEU points. In
addition, the approach has achieved interesting and promising results when
applied in the translation task that there is no direct parallel corpus between
source and target languages.
|
We study the light quark-mass dependence of charmed baryon masses as measured
by various QCD lattice collaborations. A global fit to such data based on the
chiral SU(3) Lagrangian is reported on. All low-energy constants that are
relevant at next-to-next-to-next-to-leading order (N$^3$LO) are determined from
the lattice data sets where constraints from sum rules as they follow from
large-Nc QCD at subleading order are considered. The expected hierarchy for the
low-energy constants in the 1/Nc expansion is confirmed by our global fits to
the lattice data. With our results the low-energy interaction of the Goldstone
bosons with the charmed baryon ground states is well constrained and the path
towards realistic coupled-channel computations in this sector of QCD is
prepared.
|
In this survey, we provide a comprehensive review of more than 200 papers,
technical reports, and GitHub repositories published over the last 10 years on
the recent developments of deep learning techniques for iris recognition,
covering broad topics on algorithm designs, open-source tools, open challenges,
and emerging research. First, we conduct a comprehensive analysis of deep
learning techniques developed for two main sub-tasks in iris biometrics:
segmentation and recognition. Second, we focus on deep learning techniques for
the robustness of iris recognition systems against presentation attacks and via
human-machine pairing. Third, we delve deep into deep learning techniques for
forensic application, especially in post-mortem iris recognition. Fourth, we
review open-source resources and tools in deep learning techniques for iris
recognition. Finally, we highlight the technical challenges, emerging research
trends, and outlook for the future of deep learning in iris recognition.
|
The topology transition problem of transmission networks is becoming
increasingly crucial with topological flexibility more widely leveraged to
promote high renewable penetration. This paper proposes a novel methodology to
address this problem. Aiming at achieving a bumpless topology transition
regarding both static and dynamic performance, this methodology utilizes
various eligible control resources in transmission networks to cooperate with
the optimization of line-switching sequence. Mathematically, a composite
formulation is developed to efficiently yield bumpless transition schemes with
AC feasibility and stability both ensured. With linearization of all
non-convexities involved and tractable bumpiness metrics, a convex
mixed-integer program firstly optimizes the line-switching sequence and partial
control resources. Then, two nonlinear programs recover AC feasibility, and
optimize the remaining control resources by minimizing the $\mathcal{H}_2$-norm
of associated linearized systems, respectively. The final transition scheme is
selected by accurate evaluation including stability verification using
time-domain simulations. Finally, numerical studies demonstrate the
effectiveness and superiority of the proposed methodology to achieve bumpless
topology transition.
|
In Landau gauge QCD the Kugo-Ojima confinement criterion and its relation to
the infrared behaviour of the gluon and ghost propagators are reviewed. It is
demonstrated that the realization of this confinement criterion (which is
closely related to the Gribov-Zwanziger horizon condition) results from quite
general properties of the ghost Dyson-Schwinger equation. The numerical
solutions for the gluon and ghost propagators obtained from a truncated set of
Dyson--Schwinger equations provide an explicit example for the anticipated
infrared behaviour. The results are in good agreement, also quantitatively,
with corresponding lattice data obtained recently. The resulting running
coupling approaches a fixed point in the infrared, $\alpha(0) = 8.915/N_c$.
Solutions for the coupled system of Dyson--Schwinger equations for the quark,
gluon and ghost propagators are presented. Dynamical generation of quark masses
and thus spontaneous breaking of chiral symmetry takes place. In the quenched
approximation the quark propagator functions agree well with those of
corresponding lattice calculations. For a small number of light flavours the
quark, gluon and ghost propagators deviate only slightly from the ones in
quenched approximation. While the positivity violation of the gluon spectral
function is manifest in the gluon propagator, there are no clear indications of
analogous positivity violations for quarks so far.
|
We use a recent implementation of the large $D$ expansion in order to
construct the higher-dimensional Kerr-Newman black hole and also new charged
rotating black bar solutions of the Einstein-Maxwell theory, all with rotation
along a single plane. We describe the space of solutions, obtain their
quasinormal modes, and study the appearance of instabilities as the horizons
spread along the plane of rotation. Generically, the presence of charge makes
the solutions less stable. Instabilities can appear even when the angular
momentum of the black hole is small, as long as the charge is sufficiently
large. We expect that, although our study is performed in the limit
$D\to\infty$, the results provide a good approximation for charged rotating
black holes at finite $D\geq 6$.
|
G\"ottsche gave a formula for the dimension of the cohomology of Hilbert
schemes of points on a smooth projective surface $S$. When $S$ admits an action
by a finite group $G$, we describe the action of $G$ on the Hodge structure. In
the case that $S$ is a K3 surface, each element of $G$ gives a trace on
$\sum_{n=0}^{\infty}\sum_{i=0}^{\infty}(-1)^{i}H^{i}(S^{[n]},\mathbb{C})q^{n}$.
When $G$ acts faithfully and symplectically on $S$, the resulting generating
function is of the form $q/f(q)$, where $f(q)$ is a cusp form. We relate the
Hodge structure of Hilbert schemes of points to the Hodge structure of the
compactified Jacobian of the tautological family of curves over an integral
linear system on a K3 surface as $G$-representations. Finally, we give a
sufficient condition for a $G$-orbit of curves with nodal singularities not to
contribute to the representation.
|
The mechanism of Cooper pair formation in iron-based superconductors remains
a controversial topic. The main question is whether spin or orbital
fluctuations are responsible for the pairing mechanism. To solve this problem,
a crucial clue can be obtained by examining the remarkable enhancement of
magnetic neutron scattering signals appearing in a superconducting phase. The
enhancement is called spin resonance for a spin fluctuation model, in which
their energy is restricted below twice the superconducting gap value (2Ds),
whereas larger energies are possible in other models such as an orbital
fluctuation model. Here we report the doping dependence of low-energy magnetic
excitation spectra in Ba1-xKxFe2As2 for 0.5<x<0.84 studied by inelastic neutron
scattering. We find that the behavior of the spin resonance dramatically
changes from optimum to overdoped regions. Strong resonance peaks are observed
clearly below 2Ds in the optimum doping region, while they are absent in the
overdoped region. Instead, there is a transfer of spectral weight from energies
below 2Ds to higher energies, peaking at values of 3Ds for x = 0.84. These
results suggest a reduced impact of magnetism on Cooper pair formation in the
overdoped region.
|
If edge devices are to be deployed to critical applications where their
decisions could have serious financial, political, or public-health
consequences, they will need a way to signal when they are not sure how to
react to their environment. For instance, a lost delivery drone could make its
way back to a distribution center or contact the client if it is confused about
how exactly to make its delivery, rather than taking the action which is "most
likely" correct. This issue is compounded for health care or military
applications. However, the brain-realistic temporal credit assignment problem
neuromorphic computing algorithms have to solve is difficult. The double role
weights play in backpropagation-based-learning, dictating how the network
reacts to both input and feedback, needs to be decoupled. e-prop 1 is a
promising learning algorithm that tackles this with Broadcast Alignment (a
technique where network weights are replaced with random weights during
feedback) and accumulated local information. We investigate under what
conditions the Bayesian loss term can be expressed in a similar fashion,
proposing an algorithm that can be computed with only local information as well
and which is thus no more difficult to implement on hardware. This algorithm is
exhibited on a store-recall problem, which suggests that it can learn good
uncertainty on decisions to be made over time.
|
The channeling of the ion recoiling after a collision with a WIMP changes the
ionization signal in direct detection experiments, producing a larger signal
scintillation or ionization than otherwise expected. We give estimates of the
fraction of channeled recoiling ions in CsI crystals using analytic models
produced since the 1960's and 70's to describe channeling and blocking effects.
|
It is well known that the cohomology groups of a closed manifold $M$ can be
reconstructed using the gradient dynamical of a Morse-Smale function $f\colon
M\to \R$. A direct result of this construction are Morse inequalities that
provide lower bounds for the number of critical points of $f$ in term of Betti
numbers of $M$. These inequalities can be deduced through a purely analytic
method by studying the asymptotic behaviour of the deformed Laplacian operator.
This method was introduced by E. Witten and has inspired a numbers of great
achievements in Geometry and Topology in few past decades. In this paper,
adopting the Witten approach, we provide an analytic proof for; the so called;
equivariant Morse inequalities when the underlying manifold is acted on by the
Lie group $G=S^1$ and the Morse function $f$ is invariant with respect to this
action.
|
It is a central prediction of renormalisation group theory that the critical
behaviours of many statistical mechanics models on Euclidean lattices depend
only on the dimension and not on the specific choice of lattice. We investigate
the extent to which this universality continues to hold beyond the Euclidean
setting, taking as case studies Bernoulli bond percolation and lattice trees.
We present strong numerical evidence that the critical exponents governing
these models on transitive graphs of polynomial volume growth depend only on
the volume-growth dimension of the graph and not on any other large-scale
features of the geometry. For example, our results strongly suggest that
percolation, which has upper-critical dimension six, has the same critical
exponents on the four-dimensional hypercubic lattice $\mathbb{Z}^4$ and the
Heisenberg group despite the distinct large-scale geometries of these two
lattices preventing the relevant percolation models from sharing a common
scaling limit.
On the other hand, we also show that no such universality should be expected
to hold on fractals, even if one allows the exponents to depend on a large
number of standard fractal dimensions. Indeed, we give natural examples of two
fractals which share Hausdorff, spectral, topological, and topological
Hausdorff dimensions but exhibit distinct numerical values of the percolation
Fisher exponent $\tau$. This gives strong evidence against a conjecture of
Balankin et al. [Phys. Lett. A 2018].
|
The medical field is creating large amount of data that physicians are unable
to decipher and use efficiently. Moreover, rule-based expert systems are
inefficient in solving complicated medical tasks or for creating insights using
big data. Deep learning has emerged as a more accurate and effective technology
in a wide range of medical problems such as diagnosis, prediction and
intervention. Deep learning is a representation learning method that consists
of layers that transform the data non-linearly, thus, revealing hierarchical
relationships and structures. In this review we survey deep learning
application papers that use structured data, signal and imaging modalities from
cardiology. We discuss the advantages and limitations of applying deep learning
in cardiology that also apply in medicine in general, while proposing certain
directions as the most viable for clinical use.
|
Supermassive black holes (BHs) residing in the brightest cluster galaxies are
over-massive relative to the stellar bulge mass or central stellar velocity
dispersion of their host galaxies. As BHs residing at the bottom of the galaxy
cluster's potential well may undergo physical processes that are driven by the
large-scale characteristics of the galaxy clusters, it is possible that the
growth of these BHs is (indirectly) governed by the properties of their host
clusters. In this work, we explore the connection between the mass of BHs
residing in the brightest group/cluster galaxies (BGGs/BCGs) and the virial
temperature, and hence total gravitating mass, of galaxy groups/clusters. To
this end, we investigate a sample of 17 BGGs/BCGs with dynamical BH mass
measurements and utilize XMM-Newton X-ray observations to measure the virial
temperatures and infer the $M_{\rm 500}$ mass of the galaxy groups/clusters. We
find that the $M_{\rm BH} - kT$ relation is significantly tighter and exhibits
smaller scatter than the $M_{\rm BH} - M_{\rm bulge}$ relations. The
best-fitting power-law relations are $ \log_{10} (M_{\rm BH}/10^{9} \
\rm{M_{\odot}}) = 0.20 + 1.74 \log_{10} (kT/1 \ \rm{keV}) $ and $ \log_{10}
(M_{\rm BH}/10^{9} \ \rm{M_{\odot}}) = -0.80 + 1.72 \log_{10} (M_{\rm
bulge}/10^{11} \ M_{\odot})$. Thus, the BH mass of BGGs/BCGs may be set by
physical processes that are governed by the properties of the host galaxy
group/cluster. These results are confronted with the Horizon-AGN simulation,
which reproduces the observed relations well, albeit the simulated relations
exhibit notably smaller scatter.
|
We present a novel numerical solver for the systems of coupled non-linear
elliptical differential equations. The solver partitions the computational
domain into a set of rectangular pseudo-spectral collocation subdomains and is
especially well-suited for working with stiff solutions such as almost
shell-like solitonic boson stars. The method can be used in any number of
dimensions although is practical for one- to three-dimensional problems. We
apply the method to rotating and spherically symmetric solitonic boson stars
and demonstrate that it displays exponential convergence. In the spherical
symmetric case we explore families of almost shell-like solitonic boson stars
and get the results that conform with the well-known analytic approximation.
|
The problem of forced convection along an isothermal moving plate is a
classical problem of fluid mechanics that has been solved for the first time in
1961 by Sakiadis (1961). It appears that the first work concerning mixed
convection along a moving plate is that of Moutsoglou and Chen (1980).
Thereafter, many solutions have been obtained for different aspects of this
class of boundary layer problems. In the previous works the fluid properties
have been assumed constant. Ali (2006) in a recent paper treated, for the first
time, the mixed convection problem with variable viscosity. He used the local
similarity method to solve this problem but there are doubts about the validity
of his results. For that reason we resolved the above problem with the direct
numerical solution of the boundary layer equations without any transformation.
|
Besides the use as cold matrix for spectroscopic studies, superfluid helium
droplets have served as a cold environment for the synthesis of molecules and
clusters. Since vibrational frequencies of molecules in helium droplets exhibit
almost no shift compared to the free molecule values, one could assume the
solvated particles move frictionless and undergo a reaction as soon as their
paths cross. There have been a few unexplained observations that seemed to
indicate cases of two species on one droplet not forming bonds but remaining
isolated. In this work, we performed a systematic study of helium droplets
doped with one rubidium and one strontium atom showing that besides a reaction
to RbSr, there is a probability of finding separated Rb and Sr atoms on one
droplet that only react after electronic excitation. Our results further
indicate that ground-state Sr atoms can reside at the surface as well as inside
the droplet.
|
This paper solves exit problems for spectrally negative Markov additive
processes and their reflections. A so-called scale matrix, which is a
generalization of the scale function of a spectrally negative \levy process,
plays a central role in the study of exit problems. Existence of the scale
matrix was shown in Thm. 3 of Kyprianou and Palmowski (2008). We provide a
probabilistic construction of the scale matrix, and identify the transform. In
addition, we generalize to the MAP setting the relation between the scale
function and the excursion (height) measure. The main technique is based on the
occupation density formula and even in the context of fluctuations of
spectrally negative L\'{e}vy processes this idea seems to be new. Our
representation of the scale matrix $W(x)=e^{-\Lambda x}\eL(x)$ in terms of nice
probabilistic objects opens up possibilities for further investigation of its
properties.
|
Photoreflectance is used for the characterisation of semiconductor samples,
usually by sweeping the monochromatized probe beam within the energy range
comprised between the highest value set by the pump beam and the lowest
absorption threshold of the sample. There is, however, no fundamental upper
limit for the probe beam other than the limited spectral content of the source
and the responsivity of the detector. As long as the modulation mechanism
behind photoreflectance does affect the complete electronic structure of the
material under study, sweeping the probe beam upstream towards higher energies
from that of the pump source is equally effective in order to probe high energy
critical points. This fact, up to now largely overseen, is shown experimentally
in this work. E1 and E0+{\Delta}0 critical points of bulk GaAs are
unambiguously resolved using pump light of lower energy. Upstream modulation
may widen further applications of the technique.
|
We introduce a weak notion of $2\times 2$-minors of gradients of a suitable
subclass of $BV$ functions. In the case of maps in
$BV(\mathbb{R}^2;\mathbb{R}^2)$ such a notion extends the standard definition
of Jacobian determinant to non-Sobolev maps.
We use this distributional Jacobian to prove a compactness and
$\Gamma$-convergence result for a new model describing the emergence of
topological singularities in two dimensions, in the spirit of Ginzburg-Landau
and core-radius approaches. Within our framework, the order parameter is an
$SBV$ map $u$ taking values in $\mathbb{S}^1$ and the energy is made by the sum
of the squared $L^2$ norm of $\nabla u$ and of the length of (the closure of)
the jump set of $u$ multiplied by $\frac 1 \varepsilon$. Here, $\varepsilon$ is
a length-scale parameter. We show that, in the $|\log\varepsilon|$ regime, the
Jacobian distributions converge, as $\varepsilon\to 0^+$, to a finite sum $\mu$
of Dirac deltas with weights multiple of $\pi$, and that the corresponding
effective energy is given by the total variation of $\mu$.
|
Crystal structure prediction is one of the major unsolved problems in
materials science. Traditionally, this problem is formulated as a global
optimization problem for which global search algorithms are combined with first
principle free energy calculations to predict the ground-state crystal
structure given only a material composition or a chemical system. These ab
initio algorithms usually cannot exploit a large amount of implicit
physicochemical rules or geometric constraints (deep knowledge) of atom
configurations embodied in a large number of known crystal structures. Inspired
by the deep learning enabled breakthrough in protein structure prediction,
herein we propose AlphaCrystal, a crystal structure prediction algorithm that
combines a deep residual neural network model that learns deep knowledge to
guide predicting the atomic contact map of a target crystal material followed
by reconstructing its 3D crystal structure using genetic algorithms. Based on
the experiments of a selected set of benchmark crystal materials, we show that
our AlphaCrystal algorithm can predict structures close to the ground truth
structures. It can also speed up the crystal structure prediction process by
predicting and exploiting the predicted contact map so that it has the
potential to handle relatively large systems. We believe that our deep learning
based ab initio crystal structure prediction method that learns from existing
material structures can be used to scale up current crystal structure
prediction practice. To our knowledge, AlphaCrystal is the first neural network
based algorithm for crystal structure contact map prediction and the first
method for directly reconstructing crystal structures from materials
composition, which can be further optimized by DFT calculations.
|
We present the first broad-band X-ray study of the nuclei of 14 hard X-ray
selected giant radio galaxies, based both on the literature and on the analysis
of archival X-ray data from NuSTAR, XMM-Newton, Swift and INTEGRAL. The X-ray
properties of the sources are consistent with an accretion-related X-ray
emission, likely originating from an X-ray corona coupled to a radiatively
efficient accretion flow. We find a correlation between the X-ray luminosity
and the radio core luminosity, consistent with that expected for AGNs powered
by efficient accretion. In most sources, the luminosity of the radio lobes and
the estimated jet power are relatively low compared with the nuclear X-ray
emission. This indicates that either the nucleus is more powerful than in the
past, consistent with a restarting of the central engine, or that the giant
lobes are dimmer due to expansion losses.
|
Previous work introduced a lower-dimensional numerical model for the
geometric nonlinear simulation and optimization of compliant pressure actuated
cellular structures. This model takes into account hinge eccentricities as well
as rotational and axial cell side springs. The aim of this article is twofold.
First, previous work is extended by introducing an associated continuum model.
This model is an exact geometric representation of a cellular structure and the
basis for the spring stiffnesses and eccentricities of the numerical model.
Second, the state variables of the continuum and numerical model are linked via
discontinuous stress constraints on the one hand and spring stiffness, hinge
eccentricities on the other hand. An efficient optimization algorithm that
fully couples both sets of variables is presented. The performance of the
proposed approach is demonstrated with the help of an examples.
|
In this data paper we present the results of an extensive 21cm-line synthesis
imaging survey of 43 spiral galaxies in the nearby Ursa Major cluster using the
Westerbork Synthesis Radio Telescope. Detailed kinematic information in the
form of position-velocity diagrams and rotation curves is presented in an atlas
together with HI channel maps, 21cm continuum maps, global HI profiles, radial
HI surface density profiles, integrated HI column density maps, and HI velocity
fields. The relation between the corrected global HI linewidth and the
rotational velocities Vmax and Vflat as derived from the rotation curves is
investigated. Inclination angles obtained from the optical axis ratios are
compared to those derived from the inclined HI disks and the HI velocity
fields. The galaxies were not selected on the basis of their HI content but
solely on the basis of their cluster membership and inclination which should be
suitable for a kinematic analysis. The observed galaxies provide a
well-defined, volume limited and equidistant sample, useful to investigate in
detail the statistical properties of the Tully-Fisher relation and the dark
matter halos around them.
|
Food supply chain plays a vital role in human health and food prices. Food
supply chain inefficiencies in terms of unfair competition and lack of
regulations directly affect the quality of human life and increase food safety
risks. This work merges Hyperledger Fabric, an enterprise-ready blockchain
platform with existing conventional infrastructure, to trace a food package
from farm to fork using an identity unique for each food package while keeping
it uncomplicated. It keeps the records of business transactions that are
secured and accessible to stakeholders according to the agreed set of policies
and rules without involving any centralized authority. This paper focuses on
exploring and building an uncomplicated, low-cost solution to quickly link the
existing food industry at different geographical locations in a chain to track
and trace the food in the market.
|
Quantum and private communications are affected by a fundamental limitation
which severely restricts the optimal rates that are achievable by two distant
parties. To overcome this problem, one needs to introduce quantum repeaters
and, more generally, quantum communication networks. Within a quantum network,
other problems and features may appear when we move from the basic unicast
setting of single-sender/single-receiver to more complex multi-end scenarios,
where multiple senders and multiple receivers simultaneously use the network to
communicate. Assuming various configurations, including multiple-unicast,
multicast, and multiple-multicast communication, we bound the optimal rates for
transmitting quantum information, distributing entanglement, or generating
secret keys in quantum networks connected by arbitrary quantum channels. These
bounds cannot be surpassed by the most general adaptive protocols of quantum
network communication.
|
In this paper we are concerned with the 2D incompressible Navier-Stokes
equations driven by space-time white noise. We establish existence of
infinitely many global-in-time probabilistically strong and analytically weak
solutions $u$ for every divergence free initial condition $u_0\in L^p\cup
C^{-1+\delta},\ p\in(1,2),\delta>0$. More precisely, there exist infinitely
many solutions such that $u-z\in C([0,\infty);L^p)\cap
L^2_{\rm{loc}}([0,\infty);H^\zeta)\cap
L^1_{\rm{loc}}([0,\infty);W^{\frac13,1})$ for some $\zeta\in(0,1)$, where $z$
is the solution to the linear equation. This result in particular implies
non-uniqueness in law. Our result is sharp in the sense that the solution
satisfying $u-z\in C([0,\infty);L^2)\cap L^2_{\rm{loc}}([0,\infty);H^\zeta)$
for some $\zeta\in(0,1)$ is unique.
|
Results of recent observations of the Galactic bulge demand that we discard a
simple picture of its formation, suggesting the presence of two stellar
populations represented by two peaks of stellar metallicity distribution (MDF)
in the bulge. To assess this issue, we construct Galactic chemical evolution
models that have been updated in two respects: First, the delay time
distribution (DTD) of type Ia supernovae (SNe Ia) recently revealed by
extensive SN Ia surveys is incorporated into the models. Second, the
nucleosynthesis clock, the s-processing in asymptotic giant branch (AGB) stars,
is carefully considered in this study. This novel model first shows that the
Galaxy feature tagged by the key elements, Mg, Fe, Ba for the bulge as well as
thin and thick disks is compatible with a short-delay SN Ia. We present a
successful modeling of a two-component bulge including the MDF and the
evolutions of [Mg/Fe] and [Ba/Mg], and reveal its origin as follows. A
metal-poor component (<[Fe/H]>~-0.5) is formed with a relatively short
timescale of ~1 Gyr. These properties are identical to the thick disk's
characteristics in the solar vicinity. Subsequently from its remaining gas
mixed with a gas flow from the disk outside the bulge, a metal-rich component
(<[Fe/H]>~+0.3) is formed with a longer timescale (~4 Gyr) together with a
top-heavy initial mass function that might be identified with the thin disk
component within the bulge.
|
The effect of disorder on a class of transition metal oxides described by a
single orbital Hubbard model at half filling is investigated. The phases are
characterized by the nature of the electronic and spin excitations. The
frequency and temperature-dependent conductivity and spin susceptibility as
functions of disorder are calculated. The interplay of disorder and
electron-electron interaction produces unusual behavior in this system. For
example, the dc conductivity, which is vanishingly small at low disorder in the
Mott phase and at high disorder in the localized phase, gets surprisingly
enhanced at intermediate disorder in a "metallic" phase. Moreover, the spin
susceptibility in this "metallic" phase is not the expected Pauli-behavior but
Curie-$1/T$ due to the presence of local moments.
|
It is notoriously difficult to securely configure HTTPS, and poor server
configurations have contributed to several attacks including the FREAK, Logjam,
and POODLE attacks. In this work, we empirically evaluate the TLS security
posture of popular websites and endeavor to understand the configuration
decisions that operators make. We correlate several sources of influence on
sites' security postures, including software defaults, cloud providers, and
online recommendations. We find a fragmented web ecosystem: while most websites
have secure configurations, this is largely due to major cloud providers that
offer secure defaults. Individually configured servers are more often insecure
than not. This may be in part because common resources available to individual
operators -- server software defaults and online configuration guides -- are
frequently insecure. Our findings highlight the importance of considering SaaS
services separately from individually-configured sites in measurement studies,
and the need for server software to ship with secure defaults.
|
This paper presents a high-performance general-purpose no-reference (NR)
image quality assessment (IQA) method based on image entropy. The image
features are extracted from two domains. In the spatial domain, the mutual
information between the color channels and the two-dimensional entropy are
calculated. In the frequency domain, the two-dimensional entropy and the mutual
information of the filtered sub-band images are computed as the feature set of
the input color image. Then, with all the extracted features, the support
vector classifier (SVC) for distortion classification and support vector
regression (SVR) are utilized for the quality prediction, to obtain the final
quality assessment score. The proposed method, which we call entropy-based
no-reference image quality assessment (ENIQA), can assess the quality of
different categories of distorted images, and has a low complexity. The
proposed ENIQA method was assessed on the LIVE and TID2013 databases and showed
a superior performance. The experimental results confirmed that the proposed
ENIQA method has a high consistency of objective and subjective assessment on
color images, which indicates the good overall performance and generalization
ability of ENIQA. The source code is available on github
https://github.com/jacob6/ENIQA.
|
Energy densities of relativistic electrons and protons in extended galactic
and intracluster regions are commonly determined from spectral radio and
(rarely) $\gamma$-ray measurements. The time-independent particle spectral
density distributions are commonly assumed to have a power-law (PL) form over
the relevant energy range. A theoretical relation between energy densities of
electrons and protons is usually adopted, and energy equipartition is invoked
to determine the mean magnetic field strength in the emitting region. We show
that for typical conditions, in both star-forming and starburst galaxies, these
estimates need to be scaled down substantially due to significant energy losses
that (effectively) flatten the electron spectral density distribution,
resulting in a much lower energy density than deduced when the distribution is
assumed to have a PL form. The steady-state electron distribution in the
nuclear regions of starburst galaxies is calculated by accounting for Coulomb,
bremsstrahlung, Compton, and synchrotron losses; the corresponding emission
spectra of the latter two processes are calculated and compared to the
respective PL spectra. We also determine the proton steady-state distribution
by taking into account Coulomb and pion production losses, and briefly discuss
implications of our steady-state particle spectra for estimates of proton
energy densities and magnetic fields.
|
A graph $G$ is $(a,b)$-choosable if for any color list of size $a$ associated
with each vertices, one can choose a subset of $b$ colors such that adjacent
vertices are colored with disjoint color sets. This paper shows an equivalence
between the $(a,b)$-choosability of a graph and the $(a,b)$-choosability of one
of its subgraphs called the extended core. As an application, this result
allows to prove the $(5,2)$-choosability and $(7,3)$-colorability of
triangle-free induced subgraphs of the triangular lattice.
|
The electronic and structural properties of Li$B$O$_3$ ($B$=V, Nb, Ta, Os)
are investigated via first-principles methods. We show that Li$B$O$_3$ belong
to the recently proposed hyperferroelectrics, i.e., they all have unstable
longitudinal optic phonon modes. Especially, the ferroelectric-like instability
in the metal LiOsO$_3$, whose optical dielectric constant goes to infinity, is
a limiting case of hyperferroelectrics. Via an effective Hamiltonian, we
further show that, in contrast to normal proper ferroelectricity, in which the
ferroelectric instability usually comes from long-range coulomb interactions,
the hyperferroelectric instability is due to the structure instability driven
by short-range interactions. This could happen in systems with large ion size
mismatches, which therefore provides a useful guidance in searching for novel
hyperferroelectrics.
|
The EditLens is an interactive lens technique that supports the editing of
graphs. The user can insert, update, or delete nodes and edges while
maintaining an already existing layout of the graph. For the nodes and edges
that are affected by an edit operation, the EditLens suggests suitable
locations and routes, which the user can accept or adjust. For this purpose,
the EditLens requires an efficient routing algorithm that can compute results
at interactive framerates. Existing algorithms cannot fully satisfy the needs
of the EditLens. This paper describes a novel algorithm that can compute
orthogonal edge routes for incremental edit operations of graphs. Tests
indicate that, in general, the algorithm is better than alternative solutions.
|
The aim of this paper is to develop and test metrics to quantitatively
identify technological discontinuities in a knowledge network. We developed
five metrics based on innovation theories and tested the metrics by a
simulation model-based knowledge network and hypothetically designed
discontinuity. The designed discontinuity is modeled as a node which combines
two different knowledge streams and whose knowledge is dominantly persistent in
the knowledge network. The performances of the proposed metrics were evaluated
by how well the metrics can distinguish the designed discontinuity from other
nodes on the knowledge network. The simulation results show that the
persistence times # of converging main paths provides the best performance in
identifying the designed discontinuity: the designed discontinuity was
identified as one of the top 3 patents with 96~99% probability by Metric 5 and
it is, according to the size of a domain, 12~34% better than the performance of
the second best metric. Beyond the simulation analysis, we tested the metrics
using a patent set representative of the Magnetic information storage domain.
The three representative patents associated with a well-known breakthrough
technology in the domain, the giant magneto-resistance (GMR) spin valve sensor,
were selected based on the qualitative studies, and the metrics were tested by
how well the metrics identify the selected patents as top-ranked patents. The
empirical results fully support the simulation results and therefore the
persistence times # of converging main paths is recommended for identifying
technological discontinuities for any technology.
|
We apply the theory of finite-type invariants of homology 3-spheres to
investigate the structure of the Torelli group. We construct natural cocycles
in the Torelli group and show that the lower central series quotients of the
Torelli group map onto a vector space of trivalent graphs. We also have
analogous results for two other natural subgroups of the mapping class group.
|
Considering the physics potential of an e-e- collider in the TeV energy
range, we indicate a few interesting examples for exotic processes and discuss
the standard model backgrounds. Focussing on pair production of weak gauge
bosons, we report some illustrative predictions.
|
When the scattering length is proportional to the distance from the center of
the system, two particles are shown to be trapped about the center.
Furthermore, their spectrum exhibits discrete scale invariance, whose scale
factor is controlled by the slope of the scattering length. While this
resembles the Efimov effect, our system has a number of advantages when
realized with ultracold atoms. We also elucidate how the emergent discrete
scaling symmetry is violated for more than two bosons, which may shed new light
on Efimov physics. Our system thus serves as a tunable model system to
investigate universal physics involving scale invariance, quantum anomaly, and
renormalization group limit cycle, which are important in a broad range of
quantum physics.
|
In this paper, we consider the iterative method of subspace corrections with
random ordering. We prove identities for the expected convergence rate, which
can provide sharp estimates for the error reduction per iteration. We also
study the fault-tolerant feature of the randomized successive subspace
correction method by simply rejecting all the corrections when error occurs and
show that the results iterative method converges with probability one.
Moreover, we also provide sharp estimates on the expected convergence rate for
the fault-tolerant, randomized, subspace correction method.
|
Transition metal doping is known to increase the photosensitivity to visible
light for photocatalytically active ZnO. We report on the electronic structure
of nano-crystalline Fe:ZnO, which has recently been shown to be an efficient
photocatalyst. The photo-activity of ZnO reduces Fe from 3+ to 2+ in the
surface region of the nano-crystalline material. Electronic states
corresponding to low-spin Fe 2+ are observed and attributed to crystal field
modification at the surface. These states can be important for the
photocatalytic sensitivity to visible light due to their deep location in the
ZnO bandgap. X-ray absorption and x-ray photoemission spectroscopy suggest that
Fe is only homogeneously distributed for concentrations up to 3%. Increased
concentrations does not result in a higher concentration of Fe ions in the
surface region. This is a crucial factor limiting the photocatalytic
functionality of ZnO, where the most efficient doping concentration have been
shown to be 2-4% for Fe doping. Using resonant photoemission spectroscopy we
determine the location of Fe 3d states with sensitivity to the charge states of
the Fe ion even for multi-valent and multi-coordinated Fe.
|
We derive a novel formulation for the interaction potential between
deformable fibers due to short-range fields arising from intermolecular forces.
The formulation improves the existing section-section interaction potential law
for in-plane beams by considering an offset between interacting cross sections.
The new law is asymptotically consistent, which is particularly beneficial for
computationally demanding scenarios involving short-range interactions like van
der Waals and steric forces. The formulation is implemented within a framework
of rotation-free Bernoulli-Euler beams utilizing the isogeometric paradigm. The
improved accuracy of the novel law is confirmed through thorough numerical
studies. We apply the developed formulation to investigate the complex behavior
observed during peeling and pull-off of elastic fibers interacting via the
Lennard-Jones potential.
|
Almost all of the most successful quantum algorithms discovered to date
exploit the ability of the Fourier transform to recover subgroup structure of
functions, especially periodicity. The fact that Fourier transforms can also be
used to capture shift structure has received far less attention in the context
of quantum computation.
In this paper, we present three examples of ``unknown shift'' problems that
can be solved efficiently on a quantum computer using the quantum Fourier
transform. We also define the hidden coset problem, which generalizes the
hidden shift problem and the hidden subgroup problem. This framework provides a
unified way of viewing the ability of the Fourier transform to capture subgroup
and shift structure.
|
We consider various configurations of T-branes which are non-abelian bound
states of branes and were recently introduced by Cecotti, Cordova, Heckman and
Vafa. They are a refinement of the concept of monodromic branes featured in
phenomenological F-theory models. We are particularly interested in the
T-branes corresponding to Z3 and Z4 monodromies, which are used to break E7 or
E8 gauge groups to SU(5) GUT. Our results imply that the up-type and down-type
Yukawa couplings for the breaking of E7 are zero, whereas up-type and down-type
Yukawa couplings, together with right handed neutrino Yukawas are non-zero for
the case of the breaking of E8. The dimension four proton decay mediating term
is avoided in models with either E7 or E8 breaking.
|
We explore the convergence of the light-front coupled-cluster (LFCC) method
in the context of two-dimensional quenched scalar Yukawa theory. This theory is
simple enough for higher-order LFCC calculations to be relatively
straightforward. The quenching is to maintain stability; the spectrum of the
full theory with pair creation and annihilation is unbounded from below. The
basic interaction in the quenched theory is only emission and absorption of a
neutral scalar by the complex scalar. The LFCC method builds the eigenstate
with one complex scalar and a cloud of neutrals from a valence state that is
just the complex scalar and the action of an exponentiated operator that
creates neutrals. The lowest order LFCC operator creates one; we add the next
order, a term that creates two. At this order there is a direct contribution to
the wave function for two neutrals and one complex scalar and additional
contributions to all higher Fock wave functions from the exponentiation.
Results for the lowest order and this new second-order approximation are
compared with those obtained with standard Fock-state expansions. The LFCC
approach is found to allow representation of the eigenstate with far fewer
functions than the number of wave functions required in a converged Fock-state
expansion.
|
We present some entropy and temperature relations of multi-horizons, even
including the "virtual" horizon. These relations are related to product,
division and sum of entropy and temperature of multi-horizons. We obtain the
additional thermodynamic relations of both static and rotating black holes in
three and four dimensional (A)dS spacetime. Especially, a new dimensionless,
charges-independence and $T_+S_+=T_-S_-$ like relation is presented. This
relation does not depend on the mass, electric charge, angular momentum and
cosmological constant, as it is always a constant. These relations lead us to
get some interesting thermodynamic bound of entropy and temperature, including
the Penrose inequality which is the first geometrical inequality of black
holes. Besides, based on these new relations, one can obtain the first law of
thermodynamics and Smarr relation for all horizons of black hole.
|
Recent work has identified cosmic ray events as an error source limiting the
lifetime of quantum data. These errors are correlated and affect a large number
of qubits, leading to the loss of data across a quantum chip. Previous works
attempting to address the problem in hardware or by building distributed
systems still have limitations. We approach the problem from a different
perspective, developing a new hybrid hardware-software-based strategy based on
the 2-D surface code, assuming the parallel development of a hardware strategy
that limits the phonon propagation radius. We propose to flee the area: move
the logical qubits far enough away from the strike's epicenter to maintain our
logical information. Specifically, we: (1) establish the minimum hardware
requirements needed for our approach; (2) propose a mapping for moving logical
qubits; and (3) evaluate the possible choice of the code distance. Our analysis
considers two possible cosmic ray events: those far from both ``holes'' in the
surface code and those near or overlapping a hole. We show that the probability
that the logical qubit will be destroyed can be reduced from 100% to the range
4% to 15% depending on the time required to move the logical qubit.
|
We present constraints on extensions of the minimal cosmological models
dominated by dark matter and dark energy, $\Lambda$CDM and $w$CDM, by using a
combined analysis of galaxy clustering and weak gravitational lensing from the
first-year data of the Dark Energy Survey (DES Y1) in combination with external
data. We consider four extensions of the minimal dark energy-dominated
scenarios: 1) nonzero curvature $\Omega_k$, 2) number of relativistic species
$N_{\rm eff}$ different from the standard value of 3.046, 3) time-varying
equation-of-state of dark energy described by the parameters $w_0$ and $w_a$
(alternatively quoted by the values at the pivot redshift, $w_p$, and $w_a$),
and 4) modified gravity described by the parameters $\mu_0$ and $\Sigma_0$ that
modify the metric potentials. We also consider external information from Planck
CMB measurements; BAO measurements from SDSS, 6dF, and BOSS; RSD measurements
from BOSS; and SNIa information from the Pantheon compilation. Constraints on
curvature and the number of relativistic species are dominated by the external
data; when these are combined with DES Y1, we find
$\Omega_k=0.0020^{+0.0037}_{-0.0032}$ at the 68% confidence level, and $N_{\rm
eff}<3.28\, (3.55)$ at 68% (95%) confidence. For the time-varying
equation-of-state, we find the pivot value $(w_p, w_a)=(-0.91^{+0.19}_{-0.23},
-0.57^{+0.93}_{-1.11})$ at pivot redshift $z_p=0.27$ from DES alone, and $(w_p,
w_a)=(-1.01^{+0.04}_{-0.04}, -0.28^{+0.37}_{-0.48})$ at $z_p=0.20$ from DES Y1
combined with external data; in either case we find no evidence for the
temporal variation of the equation of state. For modified gravity, we find the
present-day value of the relevant parameters to be $\Sigma_0=
0.43^{+0.28}_{-0.29}$ from DES Y1 alone, and $(\Sigma_0,
\mu_0)=(0.06^{+0.08}_{-0.07}, -0.11^{+0.42}_{-0.46})$ from DES Y1 combined with
external data, consistent with predictions from GR.
|
In this article, we will explore the fundamental concepts, including various
basic concepts on $d$-complex manifolds, along with several differential
operators and examine the relationships between them. A $d$-K\"ahler manifold
is a $d$-complex manifold equipped with a metric that satisfies a specific
condition. We prove the Hodge decomposition theorem on compact $d$-K\"ahler
manifolds, which establishes a crucial relationship between certain de-Rham
cohomology groups and Dolbeault cohomology groups on a compact $d$-K\"ahler
manifold .
|
We conducted an exploration of 12CO molecular outflows in the Orion A giant
molecular cloud to investigate outflow feedback using 12CO (J = 1-0) and 13CO
(J = 1-0) data obtained by the Nobeyama 45-m telescope. In the region excluding
the center of OMC 1, we identified 44 12CO (including 17 newly detected)
outflows based on the unbiased and systematic procedure of automatically
determining the velocity range of the outflows and separating the cloud and
outflow components. The optical depth of the 12CO emission in the detected
outflows is estimated to be approximately 5. The total momentum and energy of
the outflows, corrected for optical depth, are estimated to be 1.6 x 10 2 M km
s-1 and 1.5 x 10 46 erg, respectively. The momentum and energy ejection rate of
the outflows are estimated to be 36% and 235% of the momentum and energy
dissipation rates of the cloud turbulence, respectively. Furthermore, the
ejection rates of the outflows are comparable to those of the expanding
molecular shells estimated by Feddersen et al. (2018, ApJ, 862, 121). Cloud
turbulence cannot be sustained by the outflows and shells unless the energy
conversion efficiency is as high as 20%.
|
We consider the Yamada model for an excitable or self-pulsating laser with
saturable absorber, and study the effects of delayed optical self-feedback in
the excitable case. More specifically, we are concerned with the generation of
stable periodic pulse trains via repeated self-excitation after passage through
the delayed feedback loop, as well as their bifurcations. We show that onset
and termination of such pulse trains correspond to the simultaneous bifurcation
of countably many fold periodic orbits with infinite period in this delay
differential equation. We employ numerical continuation and the concept of
reappearance of periodic solutions to show that these bifurcations coincide
with codimension-two points along families of connecting orbits and fold
periodic orbits in a related advanced differential equation. These points
include heteroclinic connections between steady states, as well as homoclinic
bifurcations with non-hyperbolic equilibria. Tracking these codimension-two
points in parameter space reveals the critical parameter values for the
existence of periodic pulse trains. We use the recently developed theory of
temporal dissipative solitons to infer necessary conditions for the stability
of such pulse trains.
|
The nature of the pseudogap phase is a central problem in the quest to
understand high-Tc cuprate superconductors. A fundamental question is what
symmetries are broken when that phase sets in below a temperature T*. There is
evidence from both polarized neutron diffraction and polar Kerr effect
measurements that time- reversal symmetry is broken, but at temperatures that
differ significantly. Broken rotational symmetry was detected by both
resistivity and inelastic neutron scattering at low doping and by scanning
tunnelling spectroscopy at low temperature, but with no clear connection to T*.
Here we report the observation of a large in-plane anisotropy of the Nernst
effect in YBa2Cu3Oy that sets in precisely at T*, throughout the doping phase
diagram. We show that the CuO chains of the orthorhombic lattice are not
responsible for this anisotropy, which is therefore an intrinsic property of
the CuO2 planes. We conclude that the pseudogap phase is an electronic state
which strongly breaks four-fold rotational symmetry. This narrows the range of
possible states considerably, pointing to stripe or nematic orders.
|
In this experiment, three different search algorithms are implemented for the
purpose of extracting a task tree from a large knowledge graph, known as the
Functional Object-Oriented Network (FOON). Using a universal FOON, which
contains knowledge extracted by annotating online cooking videos, and a desired
goal, a task tree can be retrieved. The process of searching the universal FOON
for task tree retrieval is tested using iterative deepening search and greedy
best-first search with two different heuristic functions. The performance of
these three algorithms is analyzed and compared. The results of the experiment
show that iterative deepening performs strongly overall. However, different
heuristics in an informed search proved to be beneficial for certain
situations.
|
We present new abundances and radial velocities for stars in the field of the
open cluster Tombaugh 2, which has been suggested to be associated with the
Galactic Anticenter Stellar Structure (also known as the Monoceros stream).
Using VLT/FLAMES with the UVES and GIRAFFE spectrographs, we find a radial
velocity (RV) of <V_{r}> = 121 \pm 0.4 km/s using eighteen Tombaugh 2 cluster
stars. Our abundance analysis of RV-selected members finds that Tombaugh 2 is
more metal-rich than previous studies have found; moreover, unlike the previous
work, our larger sample also reveals that stars with the velocity of the
cluster show a relatively large spread in chemical properties (e.g.,
Delta[Fe/H] > 0.2). This is the first time a possible abundance spread has been
observed in an open cluster, though this is one of several possible
explanations for our observations. While there is an apparent trend of
[alpha/Fe] with [Fe/H], the distribution of abundances of these "RV cluster
members" also may hint at a possible division into two primary groups with
different mean chemical characteristics -- namely (<[Fe/H]>,<[Ti/Fe]>) ~
(-0.06, +0.02) and (-0.28, +0.36). Based on position and kinematics Tombaugh 2
is a likely member of the GASS/Monoceros stream, which makes Tombaugh 2 the
second star cluster within the originally proposed GASS/Monoceros family.
However, we explore other possible explanations for the observed spread in
abundances and two possible sub-populations, with the most likely explanation
being that the metal-poor ([Fe/H] = -0.28), more centrally-concentrated
population being the true Tombaugh 2 clusters stars and the metal-rich ([Fe/H]
= -0.06) population being an overlapping, and kinematically associated, but
"cold" (sigma_V < 2 km/s) stellar stream at R_{gc} >= 15 kpc.
|
The hydrodynamic response of the inviscid small shearing box model of a
midplane section of a rotationally supported astrophysical disk is examined. An
energy functional ${\cal E}$ is formulated for the general nonlinear problem.
It is found that the fate of disturbances is related to the conservation of
this quantity which, in turn, depends on the boundary conditions utilized:
${\cal E}$ is conserved for channel boundary conditions while it is not
conserved in general for shearing box conditions. Linearized disturbances
subject to channel boundary conditions have normal-modes described by Bessel
Functions and are qualitatively governed by a quantity $\Sigma$ which is a
measure of the ratio between the azimuthal and vertical wavelengths. Inertial
oscillations ensue if $\Sigma >1$ - otherwise disturbances must in general be
treated as an initial value problem. We reflect upon these results and offer a
speculation.
|
Two-dimensional metal-halide perovskites are highly versatile for
light-driven applications due to their exceptional variety in material
composition, which can be exploited for tunability of mechanical and
optoelectronic properties. The band edge emission is defined by structure and
composition of both organic and inorganic layers, and electron-phonon coupling
plays a crucial role in the recombination dynamics. However, the nature of the
electron-phonon coupling and which kind of phonons are involved is still under
debate. Here we investigate the emission, reflectance and phonon response from
single two-dimensional lead-iodide microcrystals with angle-resolved polarized
spectroscopy. We find an intricate dependence of the emission polarization with
the vibrational directionality in the materials, which reveals that several
bands of the low-frequency phonons with non-orthogonal directionality
contribute to the band edge emission. Such complex electron-phonon coupling
requires adequate models to predict the thermal broadening of the emission and
provides opportunities to design its polarization properties.
|
This paper studies the vertices, in the sense defined by J. A. Green, of
Specht modules for symmetric groups. The main theorem gives, for each
indecomposable non-projective Specht module, a large subgroup contained in one
of its vertices. A corollary of this theorem is a new way to determine the
defect groups of symmetric groups. We also use it to find the Green
correspondents of a particular family of simple Specht modules; as a corollary,
we get a new proof of the Brauer correspondence for blocks of the symmetric
group. The proof of the main theorem uses the Brauer homomorphism on modules,
as developed by M. Brou{\'e}, together with combinatorial arguments using Young
tableaux.
|
From resonant Raman scattering on isolated nanotubes we obtained the optical
transition energies, the radial breathing mode frequency and Raman intensity of
both metallic and semiconducting tubes. We unambiguously assigned the chiral
index (n_1,n_2) of approximately 50 nanotubes based solely on a third-neighbor
tight-binding Kataura plot and find omega_RBM=214.4cm^-1nm/d+18.7cm^-1. In
contrast to luminescence experiments we observe all chiralities including
zig-zag tubes. The Raman intensities have a systematic chiral-angle dependence
confirming recent ab-initio calculations.
|
We prove that the theory of the models constructible using finitely many
cofinality quantifiers - $C_{\lambda_{1},...,\lambda_{n}}^{*}$ and
$C_{<\lambda_{1},...,<\lambda_{n}}^{*}$ for $\lambda_{1},...,\lambda_{n}$
regular cardinals - is set-forcing absolute under the assumption of class many
Woodin cardinals, and is independent of the regular cardinals used. Towards
this goal we prove some properties of the generic embedding induced from the
stationary tower restricted to $<\mu$-closed sets.
|
We introduce and study a simple model capturing the main features of
unbalanced optimal transport. It is based on equipping the conical extension of
the group of all diffeomorphisms with a natural metric, which allows a
Riemannian submersion to the space of volume forms of arbitrary total mass. We
describe its finite-dimensional version and present a concise comparison study
of the geometry, Hamiltonian features, and geodesics for this and other
extensions. One of the corollaries of this approach is that along any geodesic
the total mass evolves with constant acceleration, as an object's height in a
constant buoyancy field.
|
Neural networks has been successfully used in the processing of Lidar data,
especially in the scenario of autonomous driving. However, existing methods
heavily rely on pre-processing of the pulse signals derived from Lidar sensors
and therefore result in high computational overhead and considerable latency.
In this paper, we proposed an approach utilizing Spiking Neural Network (SNN)
to address the object recognition problem directly with raw temporal pulses. To
help with the evaluation and benchmarking, a comprehensive temporal pulses
data-set was created to simulate Lidar reflection in different road scenarios.
Being tested with regard to recognition accuracy and time efficiency under
different noise conditions, our proposed method shows remarkable performance
with the inference accuracy up to 99.83% (with 10% noise) and the average
recognition delay as low as 265 ns. It highlights the potential of SNN in
autonomous driving and some related applications. In particular, to our best
knowledge, this is the first attempt to use SNN to directly perform object
recognition on raw Lidar temporal pulses.
|
The notion of weighted $(b,c)$-inverse of an element in rings were
introduced, very recently [Comm. Algebra, 48 (4) (2020): 1423-1438]. In this
paper, we further elaborate on this theory by establishing a few
characterizations of this inverse and their relationships with other $(v,
w)$-weighted $(b,c)$-inverses. We introduce some necessary and sufficient
conditions for the existence of the hybrid $(v, w)$-weighted $(b,c)$-inverse
and annihilator $(v, w)$-weighted $(b,c)$-inverse of elements in rings. In
addition to this, we explore a few sufficient conditions for the reverse-order
law of the annihilator $(v, w)$-weighted $(b,c)$-inverses.
|
Mobile Ad hoc Network (MANET) is a distributed, infrastructure-less and
decentralized network. A routing protocol in MANET is used to find routes
between mobile nodes to facilitate communication within the network. Numerous
routing protocols have been proposed for MANET. Those routing protocols are
designed to adaptively accommodate for dynamic unpredictable changes in
network's topology. The mobile nodes in MANET are often powered by limited
batteries and network lifetime relies heavily on the energy consumption of
nodes. In consequence, the lack of a mobile node can lead to network
partitioning. In this paper we analyse, evaluate and measure the energy
efficiency of three prominent MANET routing protocols namely DSR, AODV and OLSR
in addition to modified protocols. These routing protocols follow the reactive
and the proactive routing schemes. A discussion and comparison highlighting
their particular merits and drawbacks are also presented. Evaluation study and
simulations are performed using NS-2 and its accompanying tools for analysis
and investigation of results.
|
Human face-to-face conversation is an ideal model for human-computer
dialogue. One of the major features of face-to-face communication is its
multiplicity of communication channels that act on multiple modalities. To
realize a natural multimodal dialogue, it is necessary to study how humans
perceive information and determine the information to which humans are
sensitive. A face is an independent communication channel that conveys
emotional and conversational signals, encoded as facial expressions. We have
developed an experimental system that integrates speech dialogue and facial
animation, to investigate the effect of introducing communicative facial
expressions as a new modality in human-computer conversation. Our experiments
have shown that facial expressions are helpful, especially upon first contact
with the system. We have also discovered that featuring facial expressions at
an early stage improves subsequent interaction.
|
Layered thallium copper chalcogenides can form single, double, or triple
layers of Cu-Ch separated by Tl sheets. Here we report on the preparation and
properties of Tl-based materials of TlCu2Se2, TlCu4S3, TlCu4Se3 and TlCu6S4,
and compare to reports on layered ACu2nChn+1 materials with A = Ba, K, Rb, and
Cs, and Ch = S, Se. Having no long-range magnetism for these materials is quite
surprising considering the possibilities of inter- and intra-layer exchange
interactions through Cu 3d, and we measure by magnetic susceptibility and
confirm by neutron diffraction. First principles density-functional theory
calculations for both the single-layer TlCu2Se2 (isostructural to the 122
iron-based superconductors) and the double-layer TlCu4Se3 suggest a lack of
Fermi-level spectral weight that is needed to drive a magnetic or
superconducting instability. The electronic structure calculations show a much
greater likelihood of magnetism for multiple structural layers with Fe.
|
We introduce graph gamma process (GGP) linear dynamical systems to model
real-valued multivariate time series. For temporal pattern discovery, the
latent representation under the model is used to decompose the time series into
a parsimonious set of multivariate sub-sequences. In each sub-sequence,
different data dimensions often share similar temporal patterns but may exhibit
distinct magnitudes, and hence allowing the superposition of all sub-sequences
to exhibit diverse behaviors at different data dimensions. We further
generalize the proposed model by replacing the Gaussian observation layer with
the negative binomial distribution to model multivariate count time series.
Generated from the proposed GGP is an infinite dimensional directed sparse
random graph, which is constructed by taking the logical OR operation of
countably infinite binary adjacency matrices that share the same set of
countably infinite nodes. Each of these adjacency matrices is associated with a
weight to indicate its activation strength, and places a finite number of edges
between a finite subset of nodes belonging to the same node community. We use
the generated random graph, whose number of nonzero-degree nodes is finite, to
define both the sparsity pattern and dimension of the latent state transition
matrix of a (generalized) linear dynamical system. The activation strength of
each node community relative to the overall activation strength is used to
extract a multivariate sub-sequence, revealing the data pattern captured by the
corresponding community. On both synthetic and real-world time series, the
proposed nonparametric Bayesian dynamic models, which are initialized at
random, consistently exhibit good predictive performance in comparison to a
variety of baseline models, revealing interpretable latent state transition
patterns and decomposing the time series into distinctly behaved sub-sequences.
|
In this paper, we studied the ``hyperon puzzle", a problem that nevertheless
the large number of studies is still an open problem. The solution of this
issue requires one or more mechanisms that could eventually provide the
additional repulsion needed to make the EoS stiffer and, therefore, the value
of $M_{\rm{max}, T}$ compatible with the current observational limits. In this
paper we proposed that including dark matter (DM) admixed with ordinary matter
in neutron stars (NSs), change the hydrostatic equilibrium and may explain the
observed discrepancies, regardless to hyperon multi-body interactions, which
seem to be unavoidable.
We have studied how non-self-annihilating, and self-interacting, DM admixed
with ordinary matter in NSs changes their inner structure, and discussed the
mass-radius relations of such NSs. We considered DM particle masses of 1, 10,
and 100 GeV, while taking into account a rich list of the DM interacting
strengths, $y$.
By analyzing the multidimensional parameter space, including several
quantities like: a. the DM interacting strength, b. the DM particle mass as
well as the quantity of DM in its interior, and c. the DM fraction, ${\rm
f}_{DM}$, we put constraints in the parameter space ${\rm f}_{DM} -
p^{\prime}_{\rm DM}/p^{\prime}_{\rm OM}$. Our bounds are sensitive to the
recently observed NSs total masses.
|
Guided wave dispersion is commonly assessed by Fourier analysis of the field
along a line, resulting in frequency-wavenumber dispersion curves. In
anisotropic plates, a point source can generate multiple dispersion branches
pertaining to the same modal surface, which arise due to the angle between the
power flux and the wave vector. We show that this phenomenon is particularly
pronounced near zero-group-velocity points, entailing up to six contributions
along a given direction. Stationary phase points accurately describe the
measurements conducted on a monocrystalline silicon plate.
|
Light-weight camera localization in existing maps is essential for
vision-based navigation. Currently, visual and visual-inertial odometry
(VO\&VIO) techniques are well-developed for state estimation but with
inevitable accumulated drifts and pose jumps upon loop closure. To overcome
these problems, we propose an efficient monocular camera localization method in
prior LiDAR maps using direct 2D-3D line correspondences. To handle the
appearance differences and modality gaps between LiDAR point clouds and images,
geometric 3D lines are extracted offline from LiDAR maps while robust 2D lines
are extracted online from video sequences. With the pose prediction from VIO,
we can efficiently obtain coarse 2D-3D line correspondences. Then the camera
poses and 2D-3D correspondences are iteratively optimized by minimizing the
projection error of correspondences and rejecting outliers. Experimental
results on the EurocMav dataset and our collected dataset demonstrate that the
proposed method can efficiently estimate camera poses without accumulated
drifts or pose jumps in structured environments.
|
We review a recently proposed theory of random packings. We describe the
volume fluctuations in jammed matter through a volume function, amenable to
analytical and numerical calculations. We combine an extended statistical
mechanics approach 'a la Edwards' (where the role traditionally played by the
energy and temperature in thermal systems is substituted by the volume and
compactivity) with a constraint on mechanical stability imposed by the
isostatic condition. We show how such approaches can bring results that can be
compared to experiments and allow for an exploitation of the statistical
mechanics framework. The key result is the use of a relation between the local
Voronoi volume of the constituent grains and the number of neighbors in contact
that permits a simple combination of the two approaches to develop a theory of
random packings. We predict the density of random loose packing (RLP) and
random close packing (RCP) in close agreement with experiments and develop a
phase diagram of jammed matter that provides a unifying view of the disordered
hard sphere packing problem and further shedding light on a diverse spectrum of
data, including the RLP state. Theoretical results are well reproduced by
numerical simulations that confirm the essential role played by friction in
determining both the RLP and RCP limits. Finally we present an extended
discussion on the existence of geometrical and mechanical coordination numbers
and how to measure both quantities in experiments and computer simulations.
|
Bayesian phylogenetic inference is currently done via Markov chain Monte
Carlo (MCMC) with simple proposal mechanisms. This hinders exploration
efficiency and often requires long runs to deliver accurate posterior
estimates. In this paper, we present an alternative approach: a variational
framework for Bayesian phylogenetic analysis. We propose combining subsplit
Bayesian networks, an expressive graphical model for tree topology
distributions, and a structured amortization of the branch lengths over tree
topologies for a suitable variational family of distributions. We train the
variational approximation via stochastic gradient ascent and adopt gradient
estimators for continuous and discrete variational parameters separately to
deal with the composite latent space of phylogenetic models. We show that our
variational approach provides competitive performance to MCMC, while requiring
much fewer (though more costly) iterations due to a more efficient exploration
mechanism enabled by variational inference. Experiments on a benchmark of
challenging real data Bayesian phylogenetic inference problems demonstrate the
effectiveness and efficiency of our methods.
|
Multi-hop reading comprehension (RC) questions are challenging because they
require reading and reasoning over multiple paragraphs. We argue that it can be
difficult to construct large multi-hop RC datasets. For example, even highly
compositional questions can be answered with a single hop if they target
specific entity types, or the facts needed to answer them are redundant. Our
analysis is centered on HotpotQA, where we show that single-hop reasoning can
solve much more of the dataset than previously thought. We introduce a
single-hop BERT-based RC model that achieves 67 F1---comparable to
state-of-the-art multi-hop models. We also design an evaluation setting where
humans are not shown all of the necessary paragraphs for the intended multi-hop
reasoning but can still answer over 80% of questions. Together with detailed
error analysis, these results suggest there should be an increasing focus on
the role of evidence in multi-hop reasoning and possibly even a shift towards
information retrieval style evaluations with large and diverse evidence
collections.
|
Precoded polar product codes are proposed, where selected component codes
enable successive cancellation list decoding to generate bit-wise soft messages
efficiently for iterative decoding while targeting optimized distance spectrum
as opposed to eBCH or polar component codes. Rate compatibility is a byproduct
of $1$-bit granularity in the component code design.
|
We develop a new approach to production of the spectator nucleons in the
heavy ion collisions. The energy transfer to the spectator system is calculated
using the Monte Carlo based on the updated version of our generator of
configurations in colliding nuclei which includes a realistic account of
short-range correlations in nuclei. The transferred energy distributions are
calculated within the framework of the Glauber multiple scattering theory,
taking into account all the individual inelastic and elastic collisions using
an independent realistic calculation of the potential energy contribution of
each of the nucleon-nucleon pairs to the total potential. We show that the
dominant mechanism of the energy transfer is tearing apart pairs of nucleons
with the major contribution coming from the short-range correlations. We
calculate the momentum distribution of the emitted nucleons which is strongly
affected by short range correlations including its dependence on the azimuthal
angle. In particular, we predict a strong angular asymmetry along the direction
of the impact parameter b, providing a unique opportunity to determine the
direction of b. Also, we predict a strong dependence of the shape of the
nucleon momentum distribution on the centrality of the nucleus-nucleus
collision.
|
In this paper, we present an approach for combining non-rigid
structure-from-motion (NRSfM) with deep generative models,and propose an
efficient framework for discovering trajectories in the latent space of 2D GANs
corresponding to changes in 3D geometry. Our approach uses recent advances in
NRSfM and enables editing of the camera and non-rigid shape information
associated with the latent codes without needing to retrain the generator. This
formulation provides an implicit dense 3D reconstruction as it enables the
image synthesis of novel shapes from arbitrary view angles and non-rigid
structure. The method is built upon a sparse backbone, where a neural regressor
is first trained to regress parameters describing the cameras and sparse
non-rigid structure directly from the latent codes. The latent trajectories
associated with changes in the camera and structure parameters are then
identified by estimating the local inverse of the regressor in the neighborhood
of a given latent code. The experiments show that our approach provides a
versatile, systematic way to model, analyze, and edit the geometry and
non-rigid structures of faces.
|
This work explores the dynamic properties of test particles surrounding a
distorted, deformed compact object. The astrophysical motivation was to choose
such background, which could constitute a more reasonable model of a real
situation that arises in the vicinity of compact objects with the possibility
of having parameters as the extra physical degrees of freedom. This can
facilitate associating observational data with astrophysical systems. This
work's main goal is to study the dynamic regime of motion and quasi-periodic
oscillation in this background, depending on different parameters of the
system. Also, we exercise the resonant phenomena of the radial and vertical
oscillations at their observed quasi-periodic oscillations frequency ratio of
3:2.
|
Threshold behavior of the cross sections of ultraperipheral nuclear
interactions is studied. Production of $e^+e^-$ and $\mu ^+\mu ^-$ pairs as
well as $\pi ^0$ and parapositronium is treated. The values of corresponding
energy thresholds are presented and the total cross sections of these processes
at the newly constructed NICA and FAIR facilities are estimated.
|
We study how an autonomous agent learns to perform a task from demonstrations
in a different domain, such as a different environment or different agent. Such
cross-domain imitation learning is required to, for example, train an
artificial agent from demonstrations of a human expert. We propose a scalable
framework that enables cross-domain imitation learning without access to
additional demonstrations or further domain knowledge. We jointly train the
learner agent's policy and learn a mapping between the learner and expert
domains with adversarial training. We effect this by using a mutual information
criterion to find an embedding of the expert's state space that contains
task-relevant information and is invariant to domain specifics. This step
significantly simplifies estimating the mapping between the learner and expert
domains and hence facilitates end-to-end learning. We demonstrate successful
transfer of policies between considerably different domains, without extra
supervision such as additional demonstrations, and in situations where other
methods fail.
|
The Boltzmann constant was measured by comparing the Johnson noise of a
resistor at the triple point of water with a quantum-based voltage reference
signal generated with a superconducting Josephson-junction waveform
synthesizer. The measured value of k = 1.380651(18) \times 10^-23 J/K is
consistent with the current CODATA value and the combined uncertainties. This
is our first measurement of k with this electronic technique, and the first
noise thermometry measurement to achieve a relative combined uncertainty of 13
parts in 10^6. We describe the most recent improvements to our Johnson Noise
Thermometer that enabled the statistical uncertainty contribution to be reduced
to seven parts in 10^6, as well as the further reduction of spurious systematic
errors and EMI effects. The uncertainty budget for this measurement is
discussed in detail.
|
$ $As a result of bad eating habits, humanity may be destroyed. People are
constantly on the lookout for tasty foods, with junk foods being the most
common source. As a consequence, our eating patterns are shifting, and we're
gravitating toward junk food more than ever, which is bad for our health and
increases our risk of acquiring health problems. Machine learning principles
are applied in every aspect of our lives, and one of them is object recognition
via image processing. However, because foods vary in nature, this procedure is
crucial, and traditional methods like ANN, SVM, KNN, PLS etc., will result in a
low accuracy rate. All of these issues were defeated by the Deep Neural
Network. In this work, we created a fresh dataset of 10,000 data points from 20
junk food classifications to try to recognize junk foods. All of the data in
the data set was gathered using the Google search engine, which is thought to
be one-of-a-kind in every way. The goal was achieved using Convolution Neural
Network (CNN) technology, which is well-known for image processing. We achieved
a 98.05\% accuracy rate throughout the research, which was satisfactory. In
addition, we conducted a test based on a real-life event, and the outcome was
extraordinary. Our goal is to advance this research to the next level, so that
it may be applied to a future study. Our ultimate goal is to create a system
that would encourage people to avoid eating junk food and to be
health-conscious. \keywords{ Machine Learning \and junk food \and object
detection \and YOLOv3 \and custom food dataset.}
|
Subsets and Splits