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arxiv_dataset-110001903.07614 | HexaShrink, an exact scalable framework for hexahedral meshes with
attributes and discontinuities: multiresolution rendering and storage of
geoscience models
cs.GR cs.CV cs.DS physics.data-an physics.geo-ph
With huge data acquisition progresses realized in the past decades and
acquisition systems now able to produce high resolution grids and point clouds,
the digitization of physical terrains becomes increasingly more precise. Such
extreme quantities of generated and modeled data greatly impact computational
performances on many levels of high-performance computing (HPC): storage media,
memory requirements, transfer capability, and finally simulation interactivity,
necessary to exploit this instance of big data. Efficient representations and
storage are thus becoming "enabling technologies'' in HPC experimental and
simulation science. We propose HexaShrink, an original decomposition scheme for
structured hexahedral volume meshes. The latter are used for instance in
biomedical engineering, materials science, or geosciences. HexaShrink provides
a comprehensive framework allowing efficient mesh visualization and storage.
Its exactly reversible multiresolution decomposition yields a hierarchy of
meshes of increasing levels of details, in terms of either geometry, continuous
or categorical properties of cells. Starting with an overview of volume meshes
compression techniques, our contribution blends coherently different
multiresolution wavelet schemes in different dimensions. It results in a global
framework preserving discontinuities (faults) across scales, implemented as a
fully reversible upscaling at different resolutions. Experimental results are
provided on meshes of varying size and complexity. They emphasize the
consistency of the proposed representation, in terms of visualization,
attribute downsampling and distribution at different resolutions. Finally,
HexaShrink yields gains in storage space when combined to lossless compression
techniques.
| arxiv topic:cs.GR cs.CV cs.DS physics.data-an physics.geo-ph |
arxiv_dataset-110011903.07714 | A RAD approach to deep mixture models
cs.LG stat.ML
Flow based models such as Real NVP are an extremely powerful approach to
density estimation. However, existing flow based models are restricted to
transforming continuous densities over a continuous input space into similarly
continuous distributions over continuous latent variables. This makes them
poorly suited for modeling and representing discrete structures in data
distributions, for example class membership or discrete symmetries. To address
this difficulty, we present a normalizing flow architecture which relies on
domain partitioning using locally invertible functions, and possesses both real
and discrete valued latent variables. This Real and Discrete (RAD) approach
retains the desirable normalizing flow properties of exact sampling, exact
inference, and analytically computable probabilities, while at the same time
allowing simultaneous modeling of both continuous and discrete structure in a
data distribution.
| arxiv topic:cs.LG stat.ML |
arxiv_dataset-110021903.07814 | Anti-chiral edge states in an exciton polariton strip
cond-mat.mes-hall
We present a scheme to obtain anti-chiral edge states in an exciton-polariton
honeycomb lattice with strip geometry, where the modes corresponding to both
edges propagate in the same direction. Under resonant pumping the effect of a
polariton condensate with nonzero velocity in one linear polarization is
predicted to tilt the dispersion of polaritons in the other, which results in
an energy shift between two Dirac cones and the otherwise flat edge states
become tilted. Our simulations show that due to the spatial separation from the
bulk modes the edge modes are robust against disorder.
| arxiv topic:cond-mat.mes-hall |
arxiv_dataset-110031903.07914 | Dynamical Decoupling of Quantum Two-Level Systems by Coherent Multiple
Landau-Zener Transitions
cond-mat.dis-nn cond-mat.mes-hall quant-ph
Increasing and stabilizing the coherence of superconducting quantum circuits
and resonators is of utmost importance for various technologies ranging from
quantum information processors to highly sensitive detectors of low-temperature
radiation in astrophysics. A major source of noise in such devices is a bath of
quantum two-level systems (TLSs) with broad distribution of energies, existing
in disordered dielectrics and on surfaces. Here we study the dielectric loss of
superconducting resonators in the presence of a periodic electric bias field,
which sweeps near-resonant TLSs in and out of resonance with the resonator,
resulting in a periodic pattern of Landau-Zener transitions. We show that at
high sweep rates compared to the TLS relaxation rate, the coherent evolution of
the TLS over multiple transitions yields a significant reduction in the
dielectric loss relative to the intrinsic value. This behavior is observed both
in the classical high-power regime and in the quantum single-photon regime,
possibly suggesting a viable technique to dynamically decouple TLSs from a
qubit.
| arxiv topic:cond-mat.dis-nn cond-mat.mes-hall quant-ph |
arxiv_dataset-110041903.08014 | Independent Range Sampling, Revisited Again
cs.DS cs.CG
We revisit the range sampling problem: the input is a set of points where
each point is associated with a real-valued weight. The goal is to store them
in a structure such that given a query range and an integer $k$, we can extract
$k$ independent random samples from the points inside the query range, where
the probability of sampling a point is proportional to its weight.
This line of work was initiated in 2014 by Hu, Qiao, and Tao and it was later
followed up by Afshani and Wei. The first line of work mostly studied
unweighted but dynamic version of the problem in one dimension whereas the
second result considered the static weighted problem in one dimension as well
as the unweighted problem in 3D for halfspace queries.
We offer three main results and some interesting insights that were missed by
the previous work: We show that it is possible to build efficient data
structures for range sampling queries if we allow the query time to hold in
expectation (the first result), or obtain efficient worst-case query bounds by
allowing the sampling probability to be approximately proportional to the
weight (the second result). The third result is a conditional lower bound that
shows essentially one of the previous two concessions is needed. For instance,
for the 3D range sampling queries, the first two results give efficient data
structures with near-linear space and polylogarithmic query time whereas the
lower bound shows with near-linear space the worst-case query time must be
close to $n^{2/3}$, ignoring polylogarithmic factors. Up to our knowledge, this
is the first such major gap between the expected and worst-case query time of a
range searching problem.
| arxiv topic:cs.DS cs.CG |
arxiv_dataset-110051903.08114 | Exact Gaussian Processes on a Million Data Points
cs.LG cs.DC stat.ML
Gaussian processes (GPs) are flexible non-parametric models, with a capacity
that grows with the available data. However, computational constraints with
standard inference procedures have limited exact GPs to problems with fewer
than about ten thousand training points, necessitating approximations for
larger datasets. In this paper, we develop a scalable approach for exact GPs
that leverages multi-GPU parallelization and methods like linear conjugate
gradients, accessing the kernel matrix only through matrix multiplication. By
partitioning and distributing kernel matrix multiplies, we demonstrate that an
exact GP can be trained on over a million points, a task previously thought to
be impossible with current computing hardware, in less than 2 hours. Moreover,
our approach is generally applicable, without constraints to grid data or
specific kernel classes. Enabled by this scalability, we perform the first-ever
comparison of exact GPs against scalable GP approximations on datasets with
$10^4 \!-\! 10^6$ data points, showing dramatic performance improvements.
| arxiv topic:cs.LG cs.DC stat.ML |
arxiv_dataset-110061903.08214 | A tighter bound on the number of relevant variables in a bounded degree
Boolean function
cs.DM
A classical theorem of Nisan and Szegedy says that a boolean function with
degree $d$ as a real polynomial depends on at most $d2^{d-1}$ of its variables.
In recent work by Chiarelli, Hatami and Saks, this upper bound was improved to
$C \cdot 2^d$, where $C = 6.614$. Here we refine their argument to show that
one may take $C = 4.416$.
| arxiv topic:cs.DM |
arxiv_dataset-110071903.08314 | Inequalities related to some types of entropies and divergences
cs.IT math.CA math.IT
The aim of this paper is to discuss new results concerning some kinds of
parametric extended entropies and divergences. As a result of our studies for
mathematical properties on entropy and divergence, we give new bounds for the
Tsallis quasilinear entropy and divergence by applying the Hermite-Hadamard
inequality. We also give bounds for biparametrical extended entropies and
divergences which have been given in \cite{7}. In addition, we study
$(r,q)$-quasilinear entropies and divergences as alternative biparametrical
extended entropy and divergence, and then we give bounds for them. Finally we
obtain inequalities for an extended Lin's divergence and some characterizations
of Fermi-Dirac entropy and Bose-Einstein entropy.
| arxiv topic:cs.IT math.CA math.IT |
arxiv_dataset-110081903.08414 | On the modeling of brain fibers in the EEG forward problem via a new
family of wire integral equations
physics.med-ph physics.comp-ph
Source localization based on electroencephalography (EEG) has become a widely
used neuroimagining technique. However its precision has been shown to be very
dependent on how accurately the brain, head and scalp can be electrically
modeled within the so-called forward problem. The construction of this model is
traditionally performed by leveraging Finite Element or Boundary Element
Methods (FEM or BEM). Even though the latter is more computationally efficient
thanks to the smaller interaction matrices it yields and near-linear solvers,
it has traditionally been used on simpler models than the former. Indeed, while
FEM models taking into account the different media anisotropies are widely
available, BEM models have been limited to isotropic, piecewise homogeneous
models. In this work we introduce a new BEM scheme taking into account the
anisotropies of the white matter. The boundary nature of the formulation allows
for an efficient discretization and modelling of the fibrous nature of the
white matter as one-dimensional basis functions, limiting the computational
impact of their modelling. We compare our scheme against widely used
formulations and establish its correctness in both canonical and realistic
cases.
| arxiv topic:physics.med-ph physics.comp-ph |
arxiv_dataset-110091903.08514 | A Novel Monocular Disparity Estimation Network with Domain
Transformation and Ambiguity Learning
eess.IV cs.LG
Convolutional neural networks (CNN) have shown state-of-the-art results for
low-level computer vision problems such as stereo and monocular disparity
estimations, but still, have much room to further improve their performance in
terms of accuracy, numbers of parameters, etc. Recent works have uncovered the
advantages of using an unsupervised scheme to train CNN's to estimate monocular
disparity, where only the relatively-easy-to-obtain stereo images are needed
for training. We propose a novel encoder-decoder architecture that outperforms
previous unsupervised monocular depth estimation networks by (i) taking into
account ambiguities, (ii) efficient fusion between encoder and decoder features
with rectangular convolutions and (iii) domain transformations between encoder
and decoder. Our architecture outperforms the Monodepth baseline in all
metrics, even with a considerable reduction of parameters. Furthermore, our
architecture is capable of estimating a full disparity map in a single forward
pass, whereas the baseline needs two passes. We perform extensive experiments
to verify the effectiveness of our method on the KITTI dataset.
| arxiv topic:eess.IV cs.LG |
arxiv_dataset-110101903.08614 | Maximum Nullity and Forcing Number on Graphs with Maximum Degree at most
Three
math.CO
A dynamic coloring of the vertices of a graph $G$ starts with an initial
subset $F$ of colored vertices, with all remaining vertices being non-colored.
At each time step, a colored vertex with exactly one non-colored neighbor
forces this non-colored neighbor to be colored. The initial set $F$ is called a
forcing set of $G$ if, by iteratively applying the forcing process, every
vertex in $G$ becomes colored. The forcing number of a graph $G$, denoted by
$F(G)$, is the cardinality of a minimum forcing set of $G$. The maximum nullity
of $G$, denoted by $M(G)$, is defined to be the largest possible nullity over
all real symmetric matrices $A$ whose $a_{ij} \neq 0$ for $i \neq j$, whenever
two vertices $u_{i}$ and $u_{j}$ of $G$ are adjacent. In this paper, we
characterize all graphs $G$ of order $n$, maximum degree at most three, and
$F(G)=3$. Also we classify these graphs with their maximum nullity.
| arxiv topic:math.CO |
arxiv_dataset-110111903.08714 | The Astrophysical Multimessenger Observatory Network (AMON): Performance
and Science Program
astro-ph.IM astro-ph.HE
The Astrophysical Multimessenger Observatory Network (AMON) has been built
with the purpose of enabling near real-time coincidence searches using data
from leading multimessenger observatories and astronomical facilities. Its
mission is to evoke discovery of multimessenger astrophysical sources, exploit
these sources for purposes of astrophysics and fundamental physics, and explore
multimessenger datasets for evidence of multimessenger source population AMON
aims to promote the advancement of multimessenger astrophysics by allowing its
participants to study the most energetic phenomena in the universe and to help
answer some of the outstanding enigmas in astrophysics, fundamental physics,
and cosmology. The main strength of AMON is its ability to combine and analyze
sub-threshold data from different facilities. Such data cannot generally be
used stand-alone to identify astrophysical sources. The analyses algorithms
used by AMON can identify statistically significant coincidence candidates of
multimessenger events, leading to the distribution of AMON alerts used by
partner observatories for real-time follow-up that may identify and,
potentially, confirm the reality of the multimessenger association. We present
the science motivation, partner observatories, implementation and summary of
the current status of the AMON project.
| arxiv topic:astro-ph.IM astro-ph.HE |
arxiv_dataset-110121903.08814 | Prostate Segmentation from Ultrasound Images using Residual Fully
Convolutional Network
cs.CV
Medical imaging based prostate cancer diagnosis procedure uses
intra-operative transrectal ultrasound (TRUS) imaging to visualize the prostate
shape and location to collect tissue samples. Correct tissue sampling from
prostate requires accurate prostate segmentation in TRUS images. To achieve
this, this study uses a novel residual connection based fully convolutional
network. The advantage of this segmentation technique is that it requires no
pre-processing of TRUS images to perform the segmentation. Thus, it offers a
faster and straightforward prostate segmentation from TRUS images. Results show
that the proposed technique can achieve around 86% Dice Similarity accuracy
using only few TRUS datasets.
| arxiv topic:cs.CV |
arxiv_dataset-110131903.08914 | Implementing zonal harmonics with the Fueter principle
math.CV math.CA
By exploiting the Fueter theorem, we give new formulas to compute zonal
harmonic functions in any dimension. We first give a representation of them as
a result of a suitable ladder operator acting on the constant function equal to
one. Then, inspired by recent work of A. Perotti, using techniques from slice
regularity, we derive explicit expressions for zonal harmonics starting from
the 2 and 3 dimensional cases. It turns out that all zonal harmonics in any
dimension are related to the real part of powers of the standard Hermitian
product in $\mathbb{C}$. At the end we compare formulas, obtaining interesting
equalities involving the real part of positive and negative powers of the
standard Hermitian product. In the two appendices we show how our computations
are optimal compared to direct ones.
| arxiv topic:math.CV math.CA |
arxiv_dataset-110141903.09014 | Asymptotically flat extensions with charge
math.DG gr-qc
The Bartnik mass is a notion of quasi-local mass which is remarkably
difficult to compute. Mantoulidis and Schoen [2016] developed a novel technique
to construct asymptotically flat extensions of minimal Bartnik data in such a
way that the ADM mass of these extensions is well-controlled, and thus, they
were able to compute the Bartnik mass for minimal spheres satisfying a
stability condition. In this work, we develop extensions and gluing tools, \`a
la Mantoulidis and Schoen, for time-symmetric initial data sets for the
Einstein-Maxwell equations that allow us to compute the value of an ad-hoc
notion of charged Barnik mass for suitable charged minimal Bartnik data.
| arxiv topic:math.DG gr-qc |
arxiv_dataset-110151903.09114 | Inferring Explosion Properties from Type II-Plateau Supernova Light
Curves
astro-ph.SR astro-ph.HE
We present advances in modeling Type IIP supernovae using MESA for evolution
to shock breakout coupled with STELLA for generating light and radial velocity
curves. Explosion models and synthetic light curves can be used to translate
observable properties of supernovae (such as the luminosity at day 50 and the
duration of the plateau, as well as the observable quantity $ET$, defined as
the time-weighted integrated luminosity that would have been generated if there
was no ${\rm ^{56}Ni}$ in the ejecta) into families of explosions which produce
the same light curve and velocities on the plateau. These predicted families of
explosions provide a useful guide towards modeling observed SNe, and can
constrain explosion properties when coupled with other observational or
theoretical constraints. For an observed supernova with a measured ${\rm
^{56}Ni}$ mass, breaking the degeneracies within these families of explosions
(ejecta mass, explosion energy, and progenitor radius) requires independent
knowledge of one parameter. We expect the most common case to be a progenitor
radius measurement for a nearby supernova. We show that ejecta velocities
inferred from the Fe II$\lambda$ 5169 line measured during the majority of the
plateau phase provide little additional information about explosion
characteristics. Only during the initial shock cooling phase can photospheric
velocity measurements potentially aid in unraveling light curve degeneracies.
| arxiv topic:astro-ph.SR astro-ph.HE |
arxiv_dataset-110161903.09214 | Multi-person Articulated Tracking with Spatial and Temporal Embeddings
cs.CV
We propose a unified framework for multi-person pose estimation and tracking.
Our framework consists of two main components,~\ie~SpatialNet and TemporalNet.
The SpatialNet accomplishes body part detection and part-level data association
in a single frame, while the TemporalNet groups human instances in consecutive
frames into trajectories. Specifically, besides body part detection heatmaps,
SpatialNet also predicts the Keypoint Embedding (KE) and Spatial Instance
Embedding (SIE) for body part association. We model the grouping procedure into
a differentiable Pose-Guided Grouping (PGG) module to make the whole part
detection and grouping pipeline fully end-to-end trainable. TemporalNet extends
spatial grouping of keypoints to temporal grouping of human instances. Given
human proposals from two consecutive frames, TemporalNet exploits both
appearance features encoded in Human Embedding (HE) and temporally consistent
geometric features embodied in Temporal Instance Embedding (TIE) for robust
tracking. Extensive experiments demonstrate the effectiveness of our proposed
model. Remarkably, we demonstrate substantial improvements over the
state-of-the-art pose tracking method from 65.4\% to 71.8\% Multi-Object
Tracking Accuracy (MOTA) on the ICCV'17 PoseTrack Dataset.
| arxiv topic:cs.CV |
arxiv_dataset-110171903.09314 | Time-dependent numerical model for simulating internal oscillations in a
sea organ
physics.flu-dyn
This paper presents a one-dimensional time-dependent numerical model of a sea
organ, which generates music driven by the motion of the sea. The governing
equations are derived by coupling hydrodynamic and thermodynamic equations for
water level and air pressure oscillations in a sea organ pipe system forced by
irregular waves. The model was validated by comparing numerical results to
experimental data obtained from a scaled physical model. Furthermore, the
models' capabilities are presented by simulating internal oscillations in the
Sea Organ in Zadar, Croatia. The response of the Sea Organ varies between
segments and for different wave conditions. The strongest air pressure and
water level response is found near resonance frequencies.
| arxiv topic:physics.flu-dyn |
arxiv_dataset-110181903.09414 | Ratiometric control for differentiation of cell populations endowed with
synthetic toggle switches
cs.SY
We consider the problem of regulating by means of external control inputs the
ratio of two cell populations. Specifically, we assume that these two cellular
populations are composed of cells belonging to the same strain which embeds
some bistable memory mechanism, e.g. a genetic toggle switch, allowing them to
switch role from one population to another in response to some inputs. We
present three control strategies to regulate the populations' ratio to
arbitrary desired values which take also into account realistic physical and
technological constraints occurring in experimental microfluidic platforms. The
designed controllers are then validated in-silico using stochastic agent-based
simulations.
| arxiv topic:cs.SY |
arxiv_dataset-110191903.09514 | Many-Body Effective Energy Theory: photoemission at strong correlation
cond-mat.str-el
In this work we explore the performance of a recently derived many-body
effective energy theory for the calculation of photoemission spectra in the
regime of strong electron correlation. We apply the theory to paramagnetic MnO,
FeO, CoO, and NiO, which are typical examples of strongly correlated materials
and, therefore, a challenge for standard theories. We show that our methods
open a correlation gap in all the oxides studied without breaking the symmetry.
Although the materials seem similar, we show that an analysis of the occupation
numbers reveals that the nature of the gap is not the same for these materials.
Overall the results are very promising, although improvements are clearly
required, since the band gap is overestimated for all the systems studied. We
indicate some possible strategies to further develop the theory.
| arxiv topic:cond-mat.str-el |
arxiv_dataset-110201903.09614 | Optimizing the Access to Healthcare Services in Dense Refugee Hosting
Urban Areas: A Case for Istanbul
cs.CY
With over 3.5 million refugees, Turkey continues to host the world's largest
refugee population. This introduced several challenges in many areas including
access to healthcare system. Refugees have legal rights to free healthcare
services in Turkey's public hospitals. With the aim of increasing healthcare
access for refugees, we looked at where the lack of infrastructure is felt the
most. Our study attempts to address these problems by assessing whether Migrant
Health Centers' locations are optimal. The aim of this study is to improve
refugees' access to healthcare services in Istanbul by improving the locations
of health facilities available to them. We used call data records provided by
Turk Telekom.
| arxiv topic:cs.CY |
arxiv_dataset-110211903.09714 | Graph Temporal Logic Inference for Classification and Identification
cs.LO
Inferring spatial-temporal properties from data is important for many complex
systems, such as additive manufacturing systems, swarm robotic systems and
biological networks. Such systems can often be modeled as a labeled graph where
labels on the nodes and edges represent relevant measurements such as
temperatures and distances. We introduce graph temporal logic (GTL) which can
express properties such as "whenever a node's label is above 10, for the next 3
time units there are always at least two neighboring nodes with an edge label
of at most 2 where the node labels are above 5". This paper is a first attempt
to infer spatial (graph) temporal logic formulas from data for classification
and identification. For classification, we infer a GTL formula that classifies
two sets of graph temporal trajectories with minimal misclassification rate.
For identification, we infer a GTL formula that is informative and is satisfied
by the graph temporal trajectories in the dataset with high probability. The
informativeness of a GTL formula is measured by the information gain with
respect to given prior knowledge represented by a prior probability
distribution. We implement the proposed approach to classify the graph patterns
of tensile specimens built from selective laser sintering (SLS) process with
varying strengths, and to identify informative spatial-temporal patterns from
experimental data of the SLS cooldown process and simulation data of a swarm of
robots.
| arxiv topic:cs.LO |
arxiv_dataset-110221903.09814 | Feedback Network for Image Super-Resolution
cs.CV
Recent advances in image super-resolution (SR) explored the power of deep
learning to achieve a better reconstruction performance. However, the feedback
mechanism, which commonly exists in human visual system, has not been fully
exploited in existing deep learning based image SR methods. In this paper, we
propose an image super-resolution feedback network (SRFBN) to refine low-level
representations with high-level information. Specifically, we use hidden states
in an RNN with constraints to achieve such feedback manner. A feedback block is
designed to handle the feedback connections and to generate powerful high-level
representations. The proposed SRFBN comes with a strong early reconstruction
ability and can create the final high-resolution image step by step. In
addition, we introduce a curriculum learning strategy to make the network well
suitable for more complicated tasks, where the low-resolution images are
corrupted by multiple types of degradation. Extensive experimental results
demonstrate the superiority of the proposed SRFBN in comparison with the
state-of-the-art methods. Code is avaliable at
https://github.com/Paper99/SRFBN_CVPR19.
| arxiv topic:cs.CV |
arxiv_dataset-110231903.09914 | Gradient estimates for divergence form elliptic systems arising from
composite material
math.AP
In this paper, we show that $W^{1,p}$ $(1\leq p<\infty)$ weak solutions to
divergence form elliptic systems are Lipschitz and piecewise $C^{1}$ provided
that the leading coefficients and data are of piecewise Dini mean oscillation,
the lower order coefficients are bounded, and interfacial boundaries are
$C^{1,\text{Dini}}$. This extends a result of Li and Nirenberg (\textit{Comm.
Pure Appl. Math.} \textbf{56} (2003), 892-925). Moreover, under a stronger
assumption on the piecewise $L^{1}$-mean oscillation of the leading
coefficients, we derive a global weak type-(1,1) estimate with respect to
$A_{1}$ Muckenhoupt weights for the elliptic systems without lower order terms.
| arxiv topic:math.AP |
arxiv_dataset-110241903.10014 | Optical Spectroscopic Observations of Gamma-Ray Blazar Candidates. VII.
Follow-up Campaign in the Southern Hemisphere
astro-ph.GA astro-ph.HE
Searching for low energy counterparts of gamma-ray sources is one of the
major challenges in modern gamma-ray astronomy. In the third Fermi source
catalog about 30 % of detected sources are unidentified/unassociated Gamma-ray
Sources (UGSs). We recently started an optical spectroscopic follow up campaign
to confirm the blazar-like nature of candidates counterparts of UGSs. Here we
report the spectra of 61 targets collected with the Southern Astrophysical
Research Telescope (SOAR) between 2014 and the 2017. Our sample includes 33
potential counterparts of UGSs, selected on the basis of WISE colors, and 27
blazar candidates of uncertain type associated with gamma-ray sources of the
last release of the Fermi catalog. We confirm the BZB nature of 20 sources
lying within the positional uncertainty region of the UGSs. All the observed
BCUs show blazar-like spectra, classified as 2 BZQs and 25 BZBs, for which we
obtained 6 redshift estimates. Within the BCUs observations we report the
redshift estimate for the BZB associated with, 3FGL J1106.4-3643 that is the
second most distant BL Lac known to date, at z>1.084.
| arxiv topic:astro-ph.GA astro-ph.HE |
arxiv_dataset-110251903.10114 | Transfer matrices for discrete Hermitian operators and absolutely
continuous spectrum
math.SP math-ph math.FA math.MP
We introduce a transfer matrix method for the spectral analysis of discrete
Hermitian operators with locally finite hopping. Such operators can be
associated with a locally finite graph structure and the method works in
principle on any such graph. The key result is a spectral averaging formula
well known for Jacobi or 1-channel operators giving the spectral measure at a
root vector by a weak limit of products of transfer matrices. Here, we assume
an increase in the rank for the connections between spherical shells which is a
typical situation and true on finite dimensional lattices $\mathbb{Z}^d$. The
product of transfer matrices are considered as a transformation of the
relations of 'boundary resolvent data' along the shells. The trade off is that
at each level or shell with more forward then backward connections
(rank-increase) we have a set of transfer matrices at a fixed spectral
parameter. Still, considering these products we can relate the minimal norm
growth over the set of all products with the spectral measure at the root and
obtain several criteria for absolutely continuous spectrum. Finally, we give
some example of operators on stair-like graphs (increasing width) which has
absolutely continuous spectrum with a sufficiently fast decaying random
shell-matrix-potential.
| arxiv topic:math.SP math-ph math.FA math.MP |
arxiv_dataset-110261903.10214 | Towards New Requirements Engineering Competencies
cs.SE
Many of the requirements engineering (RE) difficulties have been argued to be
due to the evolving nature of design problems in dynamic environments,
characterized by high levels of uncertainty, ambiguity and emergence. It has
also been argued that these challenges cannot be solved by focusing primarily
on notations, tools, and methods. The purpose of this vision paper is to
understand better what kinds of new competencies are needed when expanding RE
practices to cope with complex systems in dynamic environments. We intend to
achieve our goal by discussing: 1) how increased complexity affects RE
practices, and 2) what viewpoints have been found most salient when aligning RE
practices with the design problem at hand. Based on our findings, we argue for
the importance of contextual intelligence, the ability to recognize and
diagnose contextual factors and then intentionally and intuitively adjust
behavior. We also outline some of the important competencies that need to be
developed for future RE practitioners to deal with complex problems.
| arxiv topic:cs.SE |
arxiv_dataset-110271903.10314 | The Roman Colonia Marciana Ulpia Traiana Thamugadi (Timgad) and Trajan's
Birthday
physics.pop-ph physics.hist-ph
It is told that the Roman Colonia Marciana Ulpia Traiana Thamugadi, that is
Timgad in Algeria, had been oriented to the sunrise on the day of Trajan's
birthday, that is 18 September 100 AD. Here we use software CalSKY to
investigate the sunrise azimuth and compare it to the direction of the
decumanus of the Roman town.
| arxiv topic:physics.pop-ph physics.hist-ph |
arxiv_dataset-110281903.10414 | Statistical study of hard X-ray emitting electrons associated with
flare-related coronal jets
astro-ph.SR
We present the statistical analysis of 33 flare-related coronal jets, and
discuss the link between the jet and the flare properties in these events. We
selected jets that were observed between 2010 and 2016 by the Atmospheric
Imaging Assembly (AIA) on board the Solar Dynamic Observatory (SDO) and are
temporally and spatially associated to flares observed by the Reuven Ramaty
High Energy Solar Spectrometric Imager (RHESSI). For each jet, we calculated
the jet duration and projected velocity in the plane of sky. The jet duration
distribution has a median of 18.8 minutes. The projected velocities are between
31 km/s and 456 km/s with a median at 210 km/s. For each associated flare, we
performed X-ray imaging and spectroscopy and identify non-thermal emission.
Non-thermal emission was detected in only 1/4 of the event considered. We did
not find a clear correlation between the flare thermal energy or SXR peak flux
and the jet velocity. A moderate anti-correlation was found between the jet
duration and the flare SXR peak flux. There is no preferential time delay
between the flare and the jet. The X-ray emission is generally located at the
base of the jet. The analysis presented in this paper suggests that the flare
and jet are part of the same explosive event, that the jet is driven by the
propagation of an Alfvenic perturbation, and that the energy partition between
flare and jets varies substantially from one event to another.
| arxiv topic:astro-ph.SR |
arxiv_dataset-110291903.10514 | The Fornax 3D project: a two-dimensional view of the stellar initial
mass function in the massive lenticular galaxy FCC 167
astro-ph.GA
The stellar initial mass function (IMF) regulates the baryonic cycle within
galaxies, and is a key ingredient to translate observations into physical
quantities. Although for decades it was assumed to be universal, there is now
growing observational evidence showing that the center of massive early-type
galaxies host an enhanced population of low-mass stars compared to the
expectations from the Milky Way. Moreover, these variations in the IMF have
been found to be related to the radial metallicity variations in massive
galaxies. We present here a two-dimensional stellar population analysis of the
massive lenticular galaxy FCC 167 (NGC 1380) as part of the Fornax3D project.
Using a newly developed stellar population fitting scheme, we derive a full
two-dimensional IMF map of an early-type galaxy. This two-dimensional analysis
allows us go further than a radial analysis, showing how the metallicity
changes along a disc-like structure while the IMF follows a distinct, less
disky distribution. Thus, our findings indicate that metallicity cannot be the
sole driver of the observed radial IMF variations. In addition, a comparison
with the orbital decomposition shows suggestive evidence of a coupling between
stellar population properties and the internal dynamical structure of FCC 167,
where metallicity and IMF maps seem to track the distribution of cold and warm
orbits, respectively.
| arxiv topic:astro-ph.GA |
arxiv_dataset-110301903.10614 | On Using Retrained and Incremental Machine Learning for Modeling
Performance of Adaptable Software: An Empirical Comparison
cs.SE cs.LG
Given the ever-increasing complexity of adaptable software systems and their
commonly hidden internal information (e.g., software runs in the public cloud),
machine learning based performance modeling has gained momentum for evaluating,
understanding and predicting software performance, which facilitates better
informed self-adaptations. As performance data accumulates during the run of
the software, updating the performance models becomes necessary. To this end,
there are two conventional modeling methods: the retrained modeling that always
discard the old model and retrain a new one using all available data; or the
incremental modeling that retains the existing model and tunes it using one
newly arrival data sample. Generally, literature on machine learning based
performance modeling for adaptable software chooses either of those methods
according to a general belief, but they provide insufficient evidences or
references to justify their choice. This paper is the first to report on a
comprehensive empirical study that examines both modeling methods under
distinct domains of adaptable software, 5 performance indicators, 8 learning
algorithms and settings, covering a total of 1,360 different conditions. Our
findings challenge the general belief, which is shown to be only partially
correct, and reveal some of the important, statistically significant factors
that are often overlooked in existing work, providing evidence-based insights
on the choice.
| arxiv topic:cs.SE cs.LG |
arxiv_dataset-110311903.10714 | `Controlled' versions of the Collatz-Wielandt and Donsker-Varadhan
formulae
math.OC
This is an overview of the work of the authors and their collaborators on the
characterization of risk sensitive costs and rewards in terms of an abstract
Collatz-Wielandt formula and in case of rewards, also a controlled version of
the Donsker-Varadhan formula. For the finite state and action case, this leads
to useful linear and dynamic programming formulations in the reducible case.
| arxiv topic:math.OC |
arxiv_dataset-110321903.10814 | Time-Dependent Polarization Tensors: Derivation of Asymptotic Expansions
for the Transient Wave Equation
math.AP
This report aims at establishing a theoretical framework for dealing with the
reconstruction problem of a small acoustic inclusion. The objective is to
introduce the new concept of time-dependent polarization tensors for the
Helmholtz equation, which will be fully investigated in a forthcoming work.
| arxiv topic:math.AP |
arxiv_dataset-110331903.10914 | Estimation of a regular conditional functional by conditional
U-statistics regression
math.ST stat.TH
U-statistics constitute a large class of estimators, generalizing the
empirical mean of a random variable $X$ to sums over every $k$-tuple of
distinct observations of $X$. They may be used to estimate a regular functional
$\theta(P_{X})$ of the law of $X$. When a vector of covariates $Z$ is
available, a conditional U-statistic may describe the effect of $z$ on the
conditional law of $X$ given $Z=z$, by estimating a regular conditional
functional $\theta(P_{X|Z=\cdot})$. We prove concentration inequalities for
conditional U-statistics. Assuming a parametric model of the conditional
functional of interest, we propose a regression-type estimator based on
conditional U-statistics. Its theoretical properties are derived, first in a
non-asymptotic framework and then in two different asymptotic regimes. Some
examples are given to illustrate our methods.
| arxiv topic:math.ST stat.TH |
arxiv_dataset-110341903.11014 | A Dynamic Routing Framework for Shared Mobility Services
math.OC
Travel time in urban centers is a significant contributor to the quality of
living of its citizens. Mobility on Demand (MoD) services such as Uber and Lyft
have revolutionized the transportation infrastructure, enabling new solutions
for passengers. Shared MoD services have shown that a continuum of solutions
can be provided between the traditional private transport for an individual and
the public mass transit based transport, by making use of the underlying
cyber-physical substrate that provides advanced, distributed, and networked
computational and communicational support. In this paper, we propose a novel
shared mobility service using a dynamic framework. This framework generates a
dynamic route for multi-passenger transport, optimized to reduce time costs for
both the shuttle and the passengers and is designed using a new concept of a
space window. This concept introduces a degree of freedom that helps reduce the
cost of the system involved in designing the optimal route. A specific
algorithm based on the Alternating Minimization approach is proposed. Its
analytical properties are characterized. Detailed computational experiments are
carried out to demonstrate the advantages of the proposed approach and are
shown to result in an order of magnitude improvement in the computational
efficiency with minimal optimality gap when compared to a standard Mixed
Integer Quadratically Constrained Programming based algorithm.
| arxiv topic:math.OC |
arxiv_dataset-110351903.11114 | SuSi: Supervised Self-Organizing Maps for Regression and Classification
in Python
cs.LG cs.CV stat.ML
In many research fields, the sizes of the existing datasets vary widely.
Hence, there is a need for machine learning techniques which are well-suited
for these different datasets. One possible technique is the self-organizing map
(SOM), a type of artificial neural network which is, so far, weakly represented
in the field of machine learning. The SOM's unique characteristic is the
neighborhood relationship of the output neurons. This relationship improves the
ability of generalization on small datasets. SOMs are mostly applied in
unsupervised learning and few studies focus on using SOMs as supervised
learning approach. Furthermore, no appropriate SOM package is available with
respect to machine learning standards and in the widely used programming
language Python. In this paper, we introduce the freely available Supervised
Self-organizing maps (SuSi) Python package which performs supervised regression
and classification. The implementation of SuSi is described with respect to the
underlying mathematics. Then, we present first evaluations of the SOM for
regression and classification datasets from two different domains of geospatial
image analysis. Despite the early stage of its development, the SuSi framework
performs well and is characterized by only small performance differences
between the training and the test datasets. A comparison of the SuSi framework
with existing Python and R packages demonstrates the importance of the SuSi
framework. In future work, the SuSi framework will be extended, optimized and
upgraded e.g. with tools to better understand and visualize the input data as
well as the handling of missing and incomplete data.
| arxiv topic:cs.LG cs.CV stat.ML |
arxiv_dataset-110361903.11214 | On free boundary minimal surfaces in the Riemannian Schwarzschild
manifold
math.DG
Is it possible to obtain unbounded minimal surfaces in certain asymptotically
flat 3-manifolds as a limit of solutions to a natural mountain pass problem
with diverging boundaries? In this work, we give evidence that this might be
true by analyzing related aspects in the case of the exact Riemannian
Schwarzschild manifold.
More precisely, we observe that the simplest minimal surface in this space
has Morse index one. We prove also a relationship between the length of the
boundary and the density at infinity of general minimal surfaces satisfying a
free-boundary condition along the horizon.
| arxiv topic:math.DG |
arxiv_dataset-110371903.11314 | Scalable Deep Learning on Distributed Infrastructures: Challenges,
Techniques and Tools
cs.DC cs.AI
Deep Learning (DL) has had an immense success in the recent past, leading to
state-of-the-art results in various domains such as image recognition and
natural language processing. One of the reasons for this success is the
increasing size of DL models and the proliferation of vast amounts of training
data being available. To keep on improving the performance of DL, increasing
the scalability of DL systems is necessary. In this survey, we perform a broad
and thorough investigation on challenges, techniques and tools for scalable DL
on distributed infrastructures. This incorporates infrastructures for DL,
methods for parallel DL training, multi-tenant resource scheduling and the
management of training and model data. Further, we analyze and compare 11
current open-source DL frameworks and tools and investigate which of the
techniques are commonly implemented in practice. Finally, we highlight future
research trends in DL systems that deserve further research.
| arxiv topic:cs.DC cs.AI |
arxiv_dataset-110381903.11414 | Materials Physics and Spin Glasses
cond-mat.dis-nn cond-mat.mtrl-sci
Comparisons and analogies are drawn between materials ferroic glasses and
conventional spin glasses, in terms of both experiment and theoretical
modelling, with inter-system conceptual transfers leading to suggestions of
further issues to investigate.
| arxiv topic:cond-mat.dis-nn cond-mat.mtrl-sci |
arxiv_dataset-110391903.11514 | Global eigenvalue distribution of matrices defined by the skew-shift
math-ph math.DS math.MP math.PR math.SP
We consider large Hermitian matrices whose entries are defined by evaluating
the exponential function along orbits of the skew-shift $\binom{j}{2}
\omega+jy+x \mod 1$ for irrational $\omega$. We prove that the eigenvalue
distribution of these matrices converges to the corresponding distribution from
random matrix theory on the global scale, namely, the Wigner semicircle law for
square matrices and the Marchenko-Pastur law for rectangular matrices. The
results evidence the quasi-random nature of the skew-shift dynamics which was
observed in other contexts by Bourgain-Goldstein-Schlag and
Rudnick-Sarnak-Zaharescu.
| arxiv topic:math-ph math.DS math.MP math.PR math.SP |
arxiv_dataset-110401903.11614 | The Gravitational waves merger time distribution of binary neutron star
systems
astro-ph.HE astro-ph.SR
Binary neutron stars (BNS) mergers are prime sites for $r$-process
nucleosynthesis. Their rate determines the chemical evolution of heavy elements
in the Milky Way. The merger rate of BNS is a convolution of their birth rate
and the gravitational radiation spiral-in delay time. Using the observed
population of Galactic BNS we show here that the lifetimes of pulsars in
observed BNSs are sufficiently short that the ages of BNSs have little to no
effect on the observed merger time distribution. We find that at late times
($t\gtrsim 1$ Gyr) the gravitational wave delay time distribution (DTD) follows
the expected $ t^{-1}$. However, a significant excess of rapidly merging
systems (between $40-60\%$ of the entire population) is apparent at shorter
times. Although the exact shape of the DTD cannot be determined with the
existing data, in all models that adequately describe the data we find at least
$40\%$ of BNSs with merger times less than 1Gyr. This population of rapid
mergers implies a declining deposition rate of $r$-process materials that is
consistent with several independent observations of heavy element abundances in
the Milky Way. At the same time this population that requires initial binary
separations of roughly one solar radius clearly indicates that these binaries
had common envelope progenitors. Our results suggest that a significant
fraction of future LIGO/Virgo BNS mergers would reside in star forming
galaxies.
| arxiv topic:astro-ph.HE astro-ph.SR |
arxiv_dataset-110411903.11714 | High Performance Monte Carlo Simulation of Ising Model on TPU Clusters
cs.DC physics.comp-ph
Large-scale deep learning benefits from an emerging class of AI accelerators.
Some of these accelerators' designs are general enough for compute-intensive
applications beyond AI and Cloud TPU is one such example. In this paper, we
demonstrate a novel approach using TensorFlow on Cloud TPU to simulate the
two-dimensional Ising Model. TensorFlow and Cloud TPU framework enable the
simple and readable code to express the complicated distributed algorithm
without compromising the performance. Our code implementation fits into a small
Jupyter Notebook and fully utilizes Cloud TPU's efficient matrix operation and
dedicated high speed inter-chip connection. The performance is highly
competitive: it outperforms the best published benchmarks to our knowledge by
60% in single-core and 250% in multi-core with good linear scaling. When
compared to Tesla V100 GPU, the single-core performance maintains a ~10% gain.
We also demonstrate that using low precision arithmetic---bfloat16---does not
compromise the correctness of the simulation results.
| arxiv topic:cs.DC physics.comp-ph |
arxiv_dataset-110421903.11814 | Hybrid Satellite-Terrestrial Communication Networks for the Maritime
Internet of Things: Key Technologies, Opportunities, and Challenges
cs.NI
With the rapid development of marine activities, there has been an increasing
number of maritime mobile terminals, as well as a growing demand for high-speed
and ultra-reliable maritime communications to keep them connected.
Traditionally, the maritime Internet of Things (IoT) is enabled by maritime
satellites. However, satellites are seriously restricted by their high latency
and relatively low data rate. As an alternative, shore & island-based base
stations (BSs) can be built to extend the coverage of terrestrial networks
using fourth-generation (4G), fifth-generation (5G), and beyond 5G services.
Unmanned aerial vehicles can also be exploited to serve as aerial maritime BSs.
Despite of all these approaches, there are still open issues for an efficient
maritime communication network (MCN). For example, due to the complicated
electromagnetic propagation environment, the limited geometrically available BS
sites, and rigorous service demands from mission-critical applications,
conventional communication and networking theories and methods should be
tailored for maritime scenarios. Towards this end, we provide a survey on the
demand for maritime communications, the state-of-the-art MCNs, and key
technologies for enhancing transmission efficiency, extending network coverage,
and provisioning maritime-specific services. Future challenges in developing an
environment-aware, service-driven, and integrated satellite-air-ground MCN to
be smart enough to utilize external auxiliary information, e.g., sea state and
atmosphere conditions, are also discussed.
| arxiv topic:cs.NI |
arxiv_dataset-110431903.11914 | Improving convergence of volume penalised fluid-solid interactions
math.NA cs.NA
We analyse and improve the volume-penalty method, a simple and versatile way
to model objects in fluid flows. The volume-penalty method is a kind of
fictitious-domain method that approximates no-slip boundary conditions with
rapid linear damping inside the object. The method can then simulate complex,
moving objects in general numerical solvers without specialised algorithms or
boundary-conforming grids. Volume penalisation pays for this simplicity by
introducing an equation-level error, the $\textit{model error}$, that is
related to the damping time $\eta \ll 1$. While the model error has been proven
to vanish as the damping time tends to zero, previous work suggests convergence
at a slow rate of $\mathcal{O}(\eta^{1/2})$. The stiffness of the damping
implies conventional volume penalisation only achieves first order numerical
accuracy. We analyse the volume-penalty method using multiple-scales
matched-asymptotics with a signed-distance coordinate system valid for
arbitrary smooth geometries. We show the dominant model error stems from a
displacement length that is proportional to a Reynolds number $\text{Re}$
dependent boundary layer of size $\mathcal{O}(\eta^{1/2}\text{Re}^{-1/2})$. The
relative size of the displacement length and damping time leads to multiple
error regimes. Our key finding derives a simple smoothing prescription for the
damping that eliminates the displacement length and reduces the model error to
$\mathcal{O}(\eta)$ in all regimes. This translates to second order numerical
accuracy. We validate our findings in several comprehensive benchmark problems
and finally combine Richardson extrapolation of the model error with our
correction to further improve convergence to $\mathcal{O}(\eta^{2})$.
| arxiv topic:math.NA cs.NA |
arxiv_dataset-110441903.12014 | Fano mirror periods from the Frobenius structure conjecture
math.AG
The Fano classification program proposed by
Coates-Corti-Galkin-Golyshev-Kasprzyk is based on the mirror symmetry
prediction that the regularized quantum period of a Fano should be equivalent
to the classical period of its mirror Landau-Ginzburg potential. We prove that
this mirror equivalence follows from versions of the Frobenius structure
conjecture of Gross-Hacking-Keel. We also find that the regularized quantum
period, which is defined in terms of descendant Gromov-Witten numbers, is in
fact given by certain naive curve counts.
| arxiv topic:math.AG |
arxiv_dataset-110451903.12114 | Probing dark matter particles at CEPC
hep-ph astro-ph.CO astro-ph.HE hep-ex
We investigate the capability of the future electron collider CEPC in probing
the parameter space of several dark matter models, including millicharged dark
matter models, $Z'$ portal dark matter models, and effective field theory dark
matter models. In our analysis, the monophoton final state is used as the
primary channel to detect dark matter models at CEPC. To maximize the signal to
background significance, we study the energy and angular distributions of the
monophoton channel arising from dark matter models and from the standard model
to design a set of detector cuts. For the $Z'$ portal dark matter, we also
analyze the $Z'$ boson visible decay channel which is found to be complementary
to the monophoton channel in certain parameter space. The CEPC reach in the
parameter space of dark matter models is also put in comparison with Xenon1T.
We find that CEPC has the unprecedented sensitivity to certain parameter space
for the dark matter models considered; for example, CEPC can improve the limits
on millicharge by one order of magnitude than previous collider experiments for
${\cal O}(1)-100$ GeV dark matter.
| arxiv topic:hep-ph astro-ph.CO astro-ph.HE hep-ex |
arxiv_dataset-110461903.12214 | Complete achromatic and robustness electro-optic switch between two
integrated optical waveguides
physics.app-ph
In this paper, we present a novel design of electro-optic modulator and
optical switching device, based on current integrated optics technique. The
advantages of our optical switching device are broadband of input light
wavelength, robustness against varying device length and operation voltages,
with reference to previous design. Conforming to our results of previous paper
[Huang et al, phys. lett. a, 90, 053837], the coupling of the waveguides has a
hyperbolic-secant shape. while detuning has a sign flip at maximum coupling, we
called it as with a sign flip of phase mismatch model. The a sign flip of phase
mismatch model can produce complete robust population transfer. In this paper,
we enhance this device to switch light intensity controllable, by tuning
external electric field based on electro-optic effect.
| arxiv topic:physics.app-ph |
arxiv_dataset-110471903.12314 | Relation-Aware Graph Attention Network for Visual Question Answering
cs.CV cs.AI
In order to answer semantically-complicated questions about an image, a
Visual Question Answering (VQA) model needs to fully understand the visual
scene in the image, especially the interactive dynamics between different
objects. We propose a Relation-aware Graph Attention Network (ReGAT), which
encodes each image into a graph and models multi-type inter-object relations
via a graph attention mechanism, to learn question-adaptive relation
representations. Two types of visual object relations are explored: (i)
Explicit Relations that represent geometric positions and semantic interactions
between objects; and (ii) Implicit Relations that capture the hidden dynamics
between image regions. Experiments demonstrate that ReGAT outperforms prior
state-of-the-art approaches on both VQA 2.0 and VQA-CP v2 datasets. We further
show that ReGAT is compatible to existing VQA architectures, and can be used as
a generic relation encoder to boost the model performance for VQA.
| arxiv topic:cs.CV cs.AI |
arxiv_dataset-110481903.12414 | Lasso in infinite dimension: application to variable selection in
functional multivariate linear regression
math.ST stat.TH
It is more and more frequently the case in applications that the data we
observe come from one or more random variables taking values in an infinite
dimensional space, e.g. curves. The need to have tools adapted to the nature of
these data explains the growing interest in the field of functional data
analysis. The model we study in this paper assumes a linear dependence between
a quantity of interest and several covariates, at least one of which has an
infinite dimension. To select the relevant covariates in this context, we
investigate adaptations of the Lasso method. Two estimation methods are
defined. The first one consists in the minimization of a Group-Lasso criterion
on the multivariate functional space H. The second one minimizes the same
criterion but on a finite dimensional subspaces of H whose dimension is chosen
by a penalized least squares method. We prove oracle inequalities of sparsity
in the case where the design is fixed or random. To compute the solutions of
both criteria in practice, we propose a coordinate descent algorithm. A
numerical study on simulated and real data illustrates the behavior of the
estimators.
| arxiv topic:math.ST stat.TH |
arxiv_dataset-110491903.12514 | Evaluating Built-in ECC of FPGA on-chip Memories for the Mitigation of
Undervolting Faults
cs.AR cs.LG
Voltage underscaling below the nominal level is an effective solution for
improving energy efficiency in digital circuits, e.g., Field Programmable Gate
Arrays (FPGAs). However, further undervolting below a safe voltage level and
without accompanying frequency scaling leads to timing related faults,
potentially undermining the energy savings. Through experimental voltage
underscaling studies on commercial FPGAs, we observed that the rate of these
faults exponentially increases for on-chip memories, or Block RAMs (BRAMs). To
mitigate these faults, we evaluated the efficiency of the built-in
Error-Correction Code (ECC) and observed that more than 90% of the faults are
correctable and further 7% are detectable (but not correctable). This
efficiency is the result of the single-bit type of these faults, which are then
effectively covered by the Single-Error Correction and Double-Error Detection
(SECDED) design of the built-in ECC. Finally, motivated by the above
experimental observations, we evaluated an FPGA-based Neural Network (NN)
accelerator under low-voltage operations, while built-in ECC is leveraged to
mitigate undervolting faults and thus, prevent NN significant accuracy loss. In
consequence, we achieve 40% of the BRAM power saving through undervolting below
the minimum safe voltage level, with a negligible NN accuracy loss, thanks to
the substantial fault coverage by the built-in ECC.
| arxiv topic:cs.AR cs.LG |
arxiv_dataset-110501903.12614 | SOAP: A generalised application of the Viterbi algorithm to searches for
continuous gravitational-wave signals
astro-ph.IM
All-sky and wide parameter space searches for continuous gravitational waves
are generally template-matching schemes which test a bank of signal waveforms
against data from a gravitational wave detector. Such searches can offer
optimal sensitivity for a given computing cost and signal model, but are
highly-tuned to specific signal types and are computationally expensive, even
for semi-coherent searches. We have developed a search method based on the
well-known Viterbi algorithm which is model-agnostic and has a computational
cost several orders of magnitude lower than template methods, with a modest
reduction in sensitivity. In particular, this method can search for signals
which have an unknown frequency evolution. We test the algorithm on three
simulated and real data sets: gapless Gaussian noise, Gaussian noise with gaps
and real data from the final run of initial LIGO (S6). We show that at 95%
efficiency, with a 1% false alarm rate, the algorithm has a depth sensitivity
of $\sim 33$, $10$ and $13$ ,Hz$^{-1/2}$ with corresponding SNRs of $\sim 60$,
$72$ and $74$ in these datasets. we discuss the use of this algorithm for
detecting a wide range of quasi-monochromatic gravitational wave signals and
instrumental lines.
| arxiv topic:astro-ph.IM |
arxiv_dataset-110511904.0006 | Black Holes and Conformal Regge Bootstrap
hep-th
Highly energetic particles traveling in the background of an asymptotically
AdS black hole experience a Shapiro time delay and an angle deflection. These
quantities are related to the Regge limit of a heavy-heavy-light-light
four-point function of scalar operators in the dual CFT. The Schwarzschild
radius of the black hole in AdS units is proportional to the ratio of the
conformal dimension of the heavy operator and the central charge. This ratio
serves as a useful expansion parameter; its power counts the number of stress
tensors in the multi-stress tensor operators which contribute to the four-point
function. In the cross-channel the four-point function is determined by the OPE
coefficients and anomalous dimensions of the heavy-light double-trace
operators. We explain how this data can be obtained and explicitly compute the
first and second order terms in the expansion of the anomalous dimensions. We
observe perfect agreement with known results in the lightcone limit, which were
obtained by computing perturbative corrections to the energy eigenstates in AdS
spacetimes.
| arxiv topic:hep-th |
arxiv_dataset-110521904.0016 | Machine translation considering context information using
Encoder-Decoder model
cs.CL cs.LG
In the task of machine translation, context information is one of the
important factor. But considering the context information model dose not
proposed. The paper propose a new model which can integrate context information
and make translation. In this paper, we create a new model based Encoder
Decoder model. When translating current sentence, the model integrates output
from preceding encoder with current encoder. The model can consider context
information and the result score is higher than existing model.
| arxiv topic:cs.CL cs.LG |
arxiv_dataset-110531904.0026 | Covariant action for bouncing cosmologies in modified Gauss-Bonnet
gravity
gr-qc astro-ph.CO hep-th
Cyclic universes with bouncing solutions are candidates for solving the big
bang initial singularity problem. Here we seek bouncing solutions in a modified
Gauss-Bonnet gravity theory, of the type $R+f(G)$, where $R$ is the Ricci
scalar, $G$ is the Gauss-Bonnet term, and $f$ some function of it. In finding
such a bouncing solution we resort to a technique that reduces the order of the
differential equations of the $R+f(G)$ theory to second order equations. As
general relativity is a theory whose equations are of second order, this order
reduction technique enables one to find solutions which are perturbatively
close to general relativity. We also build the covariant action of the order
reduced theory.
| arxiv topic:gr-qc astro-ph.CO hep-th |
arxiv_dataset-110541904.0036 | Deep learning inter-atomic potential model for accurate irradiation
damage simulations
physics.comp-ph
We propose a hybrid scheme that interpolates smoothly the
Ziegler-Biersack-Littmark (ZBL) screened nuclear repulsion potential with a
newly developed deep learning potential energy model. The resulting DP-ZBL
model can not only provide overall good performance on the predictions of
near-equilibrium material properties but also capture the right physics when
atoms are extremely close to each other, an event that frequently happens in
computational simulations of irradiation damage events. We applied this scheme
to the simulation of the irradiation damage processes in the
face-centered-cubic aluminium system, and found better descriptions in terms of
the defect formation energy, evolution of collision cascades, displacement
threshold energy, and residual point defects, than the widely-adopted ZBL
modified embedded atom method potentials and its variants. Our work provides a
reliable and feasible scheme to accurately simulate the irradiation damage
processes and opens up new opportunities to solve the predicament of lacking
accurate potentials for enormous newly-discovered materials in the irradiation
effect field.
| arxiv topic:physics.comp-ph |
arxiv_dataset-110551904.0046 | Spectral density of equitable core-periphery graphs
cs.SI physics.soc-ph
Core-periphery structure is an emerging property of a wide range of complex
systems and indicate the presence of group of actors in the system with an
higher number of connections among them and a lower number of connections with
a sparsely connected periphery. The dynamics of a complex system which is
interacting on a given graph structure is strictly connected with the spectral
properties of the graph itself, nevertheless it is generally extremely hard to
obtain analytic results which will hold for arbitrary large systems. Recently a
statistical ensemble of random graphs with a regular block structure, i.e. the
ensemble of equitable graphs, has been introduced and analytic results have
been derived in the computationally-hard context of graph partitioning and
community detection. In this paper, we present a general analytic result for a
ensemble of equitable core-periphery graphs, yielding a new explicit formula
for the spectral density of networks with core-periphery structure.
| arxiv topic:cs.SI physics.soc-ph |
arxiv_dataset-110561904.0056 | Scene Graph Generation with External Knowledge and Image Reconstruction
cs.CV
Scene graph generation has received growing attention with the advancements
in image understanding tasks such as object detection, attributes and
relationship prediction,~\etc. However, existing datasets are biased in terms
of object and relationship labels, or often come with noisy and missing
annotations, which makes the development of a reliable scene graph prediction
model very challenging. In this paper, we propose a novel scene graph
generation algorithm with external knowledge and image reconstruction loss to
overcome these dataset issues. In particular, we extract commonsense knowledge
from the external knowledge base to refine object and phrase features for
improving generalizability in scene graph generation. To address the bias of
noisy object annotations, we introduce an auxiliary image reconstruction path
to regularize the scene graph generation network. Extensive experiments show
that our framework can generate better scene graphs, achieving the
state-of-the-art performance on two benchmark datasets: Visual Relationship
Detection and Visual Genome datasets.
| arxiv topic:cs.CV |
arxiv_dataset-110571904.0066 | Subsurface diffusion in crystals and effect of surface permeability on
the atomic step motion
cond-mat.mtrl-sci
Atomic mechanism of the bulk and surface point defect generation and
annihilation on surface sinks is considered theoretically on the base of the
Burton, Cabrera and Frank model. We show that the creation and annihilation of
self-interstitials and vacancies at crystal surfaces can be described by
introducing a diffusive layer of the bulk point defects adsorbed just below the
surface. The effect of the surface permeability on the atomic step rate advance
is analyzed. We conclude that the surface permeability, as well as the
supersaturation of point defects in both gas and bulk phases, control the
dynamic of the crystal surface morphology.
| arxiv topic:cond-mat.mtrl-sci |
arxiv_dataset-110581904.0076 | Approximating CNNs with Bag-of-local-Features models works surprisingly
well on ImageNet
cs.CV cs.LG stat.ML
Deep Neural Networks (DNNs) excel on many complex perceptual tasks but it has
proven notoriously difficult to understand how they reach their decisions. We
here introduce a high-performance DNN architecture on ImageNet whose decisions
are considerably easier to explain. Our model, a simple variant of the
ResNet-50 architecture called BagNet, classifies an image based on the
occurrences of small local image features without taking into account their
spatial ordering. This strategy is closely related to the bag-of-feature (BoF)
models popular before the onset of deep learning and reaches a surprisingly
high accuracy on ImageNet (87.6% top-5 for 33 x 33 px features and Alexnet
performance for 17 x 17 px features). The constraint on local features makes it
straight-forward to analyse how exactly each part of the image influences the
classification. Furthermore, the BagNets behave similar to state-of-the art
deep neural networks such as VGG-16, ResNet-152 or DenseNet-169 in terms of
feature sensitivity, error distribution and interactions between image parts.
This suggests that the improvements of DNNs over previous bag-of-feature
classifiers in the last few years is mostly achieved by better fine-tuning
rather than by qualitatively different decision strategies.
| arxiv topic:cs.CV cs.LG stat.ML |
arxiv_dataset-110591904.0086 | Accessible quantitative phase imaging in confocal microscopy with
sinusoidal-phase synthetic optical holography
physics.optics physics.bio-ph
We present a technically simple implementation of quantitative phase imaging
in confocal microscopy based on synthetic optical holography with
sinusoidal-phase reference waves. Using a Mirau interference objective and
low-amplitude vertical sample vibration with a piezo-controlled stage, we
record synthetic holograms on commercial confocal microscopes (Nikon, model:
A1R; Zeiss: model: LSM-880), from which quantitative phase images are
reconstructed. We demonstrate our technique by stain-free imaging of cervical
(HeLa) and ovarian (ES-2) cancer cells and stem cell (mHAT9a) samples. Our
technique has the potential to extend fluorescence imaging applications in
confocal microscopy by providing label-free cell finding, monitoring cell
morphology, as well as non-perturbing long-time observation of live cells based
on quantitative phase contrast.
| arxiv topic:physics.optics physics.bio-ph |
arxiv_dataset-110601904.0096 | A characterization of 3D steady Euler flows using commuting zero-flux
homologies
math.DG math.AP math.DS
We characterize, using commuting zero-flux homologies, those
volume-preserving vector fields on a $3$-manifold that are steady solutions of
the Euler equations for some Riemannian metric. This result extends Sullivan's
homological characterization of geodesible flows in the volume-preserving case.
As an application, we show that the steady Euler flows cannot be constructed
using plugs (as in Wilson's or Kuperberg's constructions). Analogous results in
higher dimensions are also proved.
| arxiv topic:math.DG math.AP math.DS |
arxiv_dataset-110611904.0106 | The gravitational redshift monitored with RadioAstron from near Earth up
to 350,000 km
gr-qc astro-ph.IM
We report on our efforts to test the Einstein Equivalence Principle by
measuring the gravitational redshift with the VLBI spacecraft RadioAstron, in
an eccentric orbit around Earth with geocentric distances as small as $\sim$
7,000 km and up to 350,000 km. The spacecraft and its ground stations are each
equipped with stable hydrogen maser frequency standards, and measurements of
the redshifted downlink carrier frequencies were obtained at both 8.4 and 15
GHz between 2012 and 2017. Over the course of the $\sim$ 9 d orbit, the
gravitational redshift between the spacecraft and the ground stations varies
between $6.8 \times 10^{-10}$ and $0.6 \times 10^{-10}$. Since the clock offset
between the masers is difficult to estimate independently of the gravitational
redshift, only the variation of the gravitational redshift is considered for
this analysis. We obtain a preliminary estimate of the fractional deviation of
the gravitational redshift from prediction of $\epsilon = -0.016 \pm 0.003_{\rm
stat} \pm 0.030_{\rm syst}$ with the systematic uncertainty likely being
dominated by unmodelled effects including the error in accounting for the
non-relativistic Doppler shift. This result is consistent with zero within the
uncertainties. For the first time, the gravitational redshift has been probed
over such large distances in the vicinity of Earth. About three orders of
magnitude more accurate estimates may be possible with RadioAstron using
existing data from dedicated interleaved observations combining uplink and
downlink modes of operation.
| arxiv topic:gr-qc astro-ph.IM |
arxiv_dataset-110621904.0116 | Curls & Whey: Boosting Black-Box Adversarial Attacks
cs.CV
Image classifiers based on deep neural networks suffer from harassment caused
by adversarial examples. Two defects exist in black-box iterative attacks that
generate adversarial examples by incrementally adjusting the noise-adding
direction for each step. On the one hand, existing iterative attacks add noises
monotonically along the direction of gradient ascent, resulting in a lack of
diversity and adaptability of the generated iterative trajectories. On the
other hand, it is trivial to perform adversarial attack by adding excessive
noises, but currently there is no refinement mechanism to squeeze redundant
noises. In this work, we propose Curls & Whey black-box attack to fix the above
two defects. During Curls iteration, by combining gradient ascent and descent,
we `curl' up iterative trajectories to integrate more diversity and
transferability into adversarial examples. Curls iteration also alleviates the
diminishing marginal effect in existing iterative attacks. The Whey
optimization further squeezes the `whey' of noises by exploiting the robustness
of adversarial perturbation. Extensive experiments on Imagenet and
Tiny-Imagenet demonstrate that our approach achieves impressive decrease on
noise magnitude in l2 norm. Curls & Whey attack also shows promising
transferability against ensemble models as well as adversarially trained
models. In addition, we extend our attack to the targeted misclassification,
effectively reducing the difficulty of targeted attacks under black-box
condition.
| arxiv topic:cs.CV |
arxiv_dataset-110631904.0126 | The Fornax 3D project: Thick disks in a cluster environment
astro-ph.GA
We used deep MUSE observations to perform a stellar-kinematic and population
analysis of FCC 153 and FCC 177, two edge-on S0 galaxies in the Fornax cluster.
The geometrical definition of the different structural components of these two
galaxies allows us to describe the nature of their thick disks. These are both
old, relatively metal poor and [Mg/Fe]-enhanced, and their star formation
history (SFH) reveals a minor younger component whose chemical properties
suggest its later accretion. Moreover, the outer regions of these geometrically
defined thick disks show higher values of metallicity and lower values of
[Mg/Fe]. These stars probably formed in the thin-disk region and they were
dynamically heated to form the flares present in these two galaxies. We propose
different formation scenarios for the three populations of these thick disks:
in-situ formation, accretion and disk heating. A clear distinction in age is
found between the metal poor and [Mg/Fe]-enhanced thick disks (old, $\sim
12-13$ Gyr), and the metal rich and less [Mg/Fe]-enhanced thin disks (young,
$\sim 4-5$ Gyr). These two galaxies show signs of relatively recent star
formation in their thin disks and nuclear regions. While the thin disks show
more continuous SFHs, the nuclei display a rather bursty SFH. These two
galaxies are located outside of the densest region of the Fornax cluster where
FCC 170 resides. This other edge-on S0 galaxy was studied by \citet{Pinna2019}.
We compare and discuss our results with this previous study. The differences
between these three galaxies, at different distances from the cluster center,
suggest that the environment can have a strong effect on the galaxy
evolutionary path.
| arxiv topic:astro-ph.GA |
arxiv_dataset-110641904.0136 | Melting transitions in biomembranes
physics.bio-ph
We investigated melting transitions in biological membranes in their native
state that include their membrane proteins. These membranes originated from
\textit{E. coli}, \textit{B. subtilis}, lung surfactant and nerve tissue from
the spinal cord of several mammals. For some preparations, we studied the
pressure, pH and ionic strength dependence of the transition. For porcine
spine, we compared the transition of the native membrane to that of the
extracted lipids. All preparations displayed melting transitions of 10-20
degrees below physiological or growth temperature, independent of the organism
of origin and the respective cell type. The position of transitions in
\textit{E. coli} membranes depends on the growth temperature. We discuss these
findings in the context of the thermodynamic theory of membrane fluctuations
that leads to largely altered elastic constants, an increase in fluctuation
lifetime and in membrane permeability associated with the transitions. We also
discuss how to distinguish lipid transitions from protein unfolding
transitions. Since the feature of a transition slightly below physiological
temperature is conserved even when growth conditions change, we conclude that
the transitions are likely to be of major biological importance for the
survival and the function of the cell.
| arxiv topic:physics.bio-ph |
arxiv_dataset-110651904.0146 | Leveraging Machine Learning and Big Data for Smart Buildings: A
Comprehensive Survey
cs.CY cs.LG stat.ML
Future buildings will offer new convenience, comfort, and efficiency
possibilities to their residents. Changes will occur to the way people live as
technology involves into people's lives and information processing is fully
integrated into their daily living activities and objects. The future
expectation of smart buildings includes making the residents' experience as
easy and comfortable as possible. The massive streaming data generated and
captured by smart building appliances and devices contains valuable information
that needs to be mined to facilitate timely actions and better decision making.
Machine learning and big data analytics will undoubtedly play a critical role
to enable the delivery of such smart services. In this paper, we survey the
area of smart building with a special focus on the role of techniques from
machine learning and big data analytics. This survey also reviews the current
trends and challenges faced in the development of smart building services.
| arxiv topic:cs.CY cs.LG stat.ML |
arxiv_dataset-110661904.0156 | On the nature of the core of $\alpha$ Centauri A: the impact of the
metallicity mixture
astro-ph.SR
Forward asteroseismic modelling plays an important role towards a complete
understanding of the physics taking place in deep stellar interiors. With a
dynamical mass in the range over which models develop convective cores while in
the main sequence, the solar-like oscillator $\alpha$ Centauri A presents
itself as an interesting case study. We address the impact of varying the
metallicity mixture on the determination of the energy transport process at
work in the core of $\alpha$ Centauri A. We find that $\gtrsim$ 70$\%$ of
models reproducing the revised dynamical mass of $\alpha$ Centauri A have
convective cores, regardless of the metallicity mixture adopted. This is
consistent with the findings of Nsamba et al., where nuclear reaction rates
were varied instead. Given these results, we propose that $\alpha$ Centauri A
be adopted in the calibration of stellar model parameters when modelling
solar-like stars with convective cores.
| arxiv topic:astro-ph.SR |
arxiv_dataset-110671904.0166 | The Narrow-beam Diffuser Subsystem of a Prototype Optical Calibration
System for the Hyper-Kamiokande Detector
physics.ins-det hep-ex
The Hyper-Kamiokande neutrino detector is set to begin construction in 2020,
succeeding Super-Kamiokande as the world's largest water Cerenkov detector.
Research and development are well underway for an integrated light injection
system for Hyper-Kamiokande which will provide in-situ monitoring of
photo-sensor responses and water transparency. In summer 2018, optical hardware
forming an iteration of this system was installed in Super-Kamiokande. We
present details of the narrow-beam diffuser hardware and testing procedures, in
addition to a brief summary of the installed light injection system.
| arxiv topic:physics.ins-det hep-ex |
arxiv_dataset-110681904.0176 | Total Variation and Tight Frame Image Segmentation with Intensity
Inhomogeneity
eess.IV
Image segmentation is an important task in the domain of computer vision and
medical imaging. In natural and medical images, intensity inhomogeneity, i.e.
the varying image intensity, occurs often and it poses considerable challenges
for image segmentation. In this paper, we propose an efficient variational
method for segmenting images with intensity inhomogeneity. The method is
inspired by previous works on two-stage segmentation and variational Retinex.
Our method consists of two stages. In the first stage, we decouple the image
into reflection and illumination parts by solving a convex energy minimization
model with either total variation or tight-frame regularisation. In the second
stage, we segment the original image by thresholding on the reflection part,
and the inhomogeneous intensity is estimated by the smoothly varying
illumination part. We adopt a primal dual algorithm to solve the convex model
in the first stage, and the convergence is guaranteed. Numerical experiments
clearly show that our method is robust and efficient to segment both natural
and medical images.
| arxiv topic:eess.IV |
arxiv_dataset-110691904.0186 | Obstacles to quantum annealing in a planar embedding of XORSAT
cond-mat.stat-mech cond-mat.str-el
We introduce a planar embedding of the k-regular k-XORSAT problem, in which
solutions are encoded in the ground state of a classical statistical mechanics
model of reversible logic gates arranged on a square grid and acting on bits
that represent the Boolean variables of the problem. The special feature of
this embedding is that the resulting model lacks a finite-temperature phase
transition, thus bypassing the first-order thermodynamic transition known to
occur in the random graph representation of XORSAT. In spite of this attractive
feature, the thermal relaxation into the ground state displays remarkably slow
glassy behavior. The question addressed in this paper is whether this planar
embedding can afford an efficient path to solution of k-regular k-XORSAT via
quantum adiabatic annealing. We first show that our model bypasses an avoided
level crossing and consequent exponentially small gap in the limit of small
transverse fields. We then present quantum Monte Carlo results for our
embedding of the k-regular k-XORSAT that strongly support a picture in which
second-order and first-order transitions develop at a finite transverse field
for k = 2 and k = 3, respectively. This translates into power-law and
exponential dependences in the scaling of energy gaps with system size,
corresponding to times-to-solution which are, respectively, polynomial and
exponential in the number of variables. We conclude that neither classical nor
quantum annealing can efficiently solve our reformulation of XORSAT, even
though the original problem can be solved in polynomial time by Gaussian
elimination.
| arxiv topic:cond-mat.stat-mech cond-mat.str-el |
arxiv_dataset-110701904.0196 | Computing Dixmier Invariants and Some Geometric Configurations of
Quartic Curves with 2 Involutions
math.AG
In this paper we consider plane quartics with to involutions. We compute the
Dixmier invariants, the bitangents and the Matrix representation problem of
these curves, showing that they have symbolic solutions for the last two
questions.
| arxiv topic:math.AG |
arxiv_dataset-110711904.0206 | The contribution of effective quantum gravity to the high energy
scattering in the framework of modified perturbation theory and one loop
approximation
hep-th
The asymptotic behavior of the scattering amplitude for two scalar particles
at high energies with fixed momentum transfers is studied. The study is done
within the effective theory of quantum gravity based on quasi-potential
equation. By using the modified perturbation theory, a systematic method is
developed to find the leading eikonal scattering amplitudes together with
corrections to them in the one-loop gravitational approximation. The relation
is established and discussed between the solutions obtained by means of the
operator and functional approaches applied to quasi-potential equation. The
first non-leading corrections to the leading eikonal amplitude are found.
| arxiv topic:hep-th |
arxiv_dataset-110721904.0216 | Non-Hermitian topology of spontaneous magnon decay
cond-mat.str-el
Spontaneous magnon decay is a generic feature of the magnetic excitations of
anisotropic magnets and isotropic magnets with non-collinear order. In this
paper, we argue that the effect of interactions on one-magnon states can, under
many circumstances, be treated in terms of an effective, energy independent,
non-Hermitian Hamiltonian for the magnons. In the vicinity of Dirac or Weyl
touching points, we show that the spectral function has a characteristic
anisotropy arising from topologically protected exceptional points or lines in
the non-Hermitian spectrum. Such features can, in principle, be detected using
inelastic neutron scattering or other spectroscopic probes. We illustrate this
physics through a concrete example: a honeycomb ferromagnet with
Dzyaloshinskii-Moriya exchange. We perform interacting spin wave calculations
of the structure factor and spectral function of this model, showing good
agreement with results from a simple effective non-Hermitian model for the
splitting of the Dirac point. Finally, we argue that the zoo of known
topological protected magnon band structures may serve as a nearly ideal
platform for realizing and exploring non-Hermitian physics in solid-state
systems.
| arxiv topic:cond-mat.str-el |
arxiv_dataset-110731904.0226 | Contextuality Test of the Nonclassicality of Variational Quantum
Eigensolvers
quant-ph
Contextuality is an indicator of non-classicality, and a resource for various
quantum procedures. In this paper, we use contextuality to evaluate the
variational quantum eigensolver (VQE), one of the most promising tools for
near-term quantum simulation. We present an efficiently computable test to
determine whether or not the objective function for a VQE procedure is
contextual. We apply this test to evaluate the contextuality of experimental
implementations of VQE, and determine that several, but not all, fail this test
of quantumness.
| arxiv topic:quant-ph |
arxiv_dataset-110741904.0236 | A highly accurate determination of absorbed power during nanomagnetic
hyperthermia
physics.app-ph
Absorbed power of nanoparticles during magnetic hyperthermia can be well
determined from changes in the quality factor ($Q$ factor) of a resonator, in
which the radiofrequency (RF) absorbent is placed. We present an order of
magnitude improvement in the $Q$ factor measurement accuracy over conventional
methods by studying the switch-on and off transient signals of the resonators.
A nuclear magnetic resonance (NMR) console is ideally suited to acquire the
transient signals and it also allows to employ the so-called pulse
phase-cycling to remove transient artifacts. The improved determination of the
absorbed power is demonstrated on various resonators in the 1-30 MHz range
including standard solenoids and also a birdcage resonator. This leads to the
possibility to detect minute amounts of ferrite nanoparticles which are
embedded in the body and also the amount of the absorbed power. We demonstrate
this capability on a phantom study, where the exact location of an embedded
ferrite is clearly detected.
| arxiv topic:physics.app-ph |
arxiv_dataset-110751904.0246 | Agility Measurements Mismatch: A Validation Study on Three Agile Team
Assessments in Software Engineering
cs.SE
Many tools have been created for measuring the agility of software teams,
thus creating a saturation in the field. Three agile measurement tools were
selected in order to validate whether they yield sim-ilar results. The surveys
of the tools were given to teams in Company A (N = 30). The questions were
grouped into agile practices which were checked for correlation in order to
establish convergent validity. In addition, we checked whether the questions
identified to be the same among the tools would be given the same replies by
the respondents. We could not establish convergent validity since the
correlations of the data gathered were very few and low. In addition, the
questions which were identified to have the same meaning among the tools did
not have the same answers from the respondents. We conclude that the area of
measuring agility is still immature and more work needs to be done. Not all
tools are applicable to every team but they should be selected on the basis of
how a team has transitioned to agile.
| arxiv topic:cs.SE |
arxiv_dataset-110761904.0256 | The Minimal Simple Composite Higgs Model
hep-ph
Most of the analysis of composite Higgs have focussed on the Minimal
Composite Higgs Model, based on the coset
SO(5)$\times$U(1)$_X$/SO(4)$\times$U(1)$_X$. We consider a model based on the
coset of simple groups SO(7)/SO(6), with SO(4)$\times$U(1)$_X$ embedded into
SO(6). This extension of the minimal model leads to a new complex pNGB that has
hypercharge and is a singlet of SU(2)$_L$, with properties mostly determined by
the pattern of symmetry breaking and a mass of order TeV. Composite electroweak
unification also leads to new bosonic and fermion resonances with exotic
charges, not present in the minimal model. The lightest of these resonances is
stable, and in some cases could provide candidates for dark matter. A new rich
phenomenology is expected at LHC.
| arxiv topic:hep-ph |
arxiv_dataset-110771904.0266 | Recommendations for Datasets for Source Code Summarization
cs.CL
Source Code Summarization is the task of writing short, natural language
descriptions of source code. The main use for these descriptions is in software
documentation e.g. the one-sentence Java method descriptions in JavaDocs. Code
summarization is rapidly becoming a popular research problem, but progress is
restrained due to a lack of suitable datasets. In addition, a lack of community
standards for creating datasets leads to confusing and unreproducible research
results -- we observe swings in performance of more than 33% due only to
changes in dataset design. In this paper, we make recommendations for these
standards from experimental results. We release a dataset based on prior work
of over 2.1m pairs of Java methods and one sentence method descriptions from
over 28k Java projects. We describe the dataset and point out key differences
from natural language data, to guide and support future researchers.
| arxiv topic:cs.CL |
arxiv_dataset-110781904.0276 | An End-to-End Conversational Style Matching Agent
cs.HC
We present an end-to-end voice-based conversational agent that is able to
engage in naturalistic multi-turn dialogue and align with the interlocutor's
conversational style. The system uses a series of deep neural network
components for speech recognition, dialogue generation, prosodic analysis and
speech synthesis to generate language and prosodic expression with qualities
that match those of the user. We conducted a user study (N=30) in which
participants talked with the agent for 15 to 20 minutes, resulting in over 8
hours of natural interaction data. Users with high consideration conversational
styles reported the agent to be more trustworthy when it matched their
conversational style. Whereas, users with high involvement conversational
styles were indifferent. Finally, we provide design guidelines for multi-turn
dialogue interactions using conversational style adaptation.
| arxiv topic:cs.HC |
arxiv_dataset-110791904.0286 | Deep Tree Learning for Zero-shot Face Anti-Spoofing
cs.CV
Face anti-spoofing is designed to keep face recognition systems from
recognizing fake faces as the genuine users. While advanced face anti-spoofing
methods are developed, new types of spoof attacks are also being created and
becoming a threat to all existing systems. We define the detection of unknown
spoof attacks as Zero-Shot Face Anti-spoofing (ZSFA). Previous works of ZSFA
only study 1-2 types of spoof attacks, such as print/replay attacks, which
limits the insight of this problem. In this work, we expand the ZSFA problem to
a wide range of 13 types of spoof attacks, including print attack, replay
attack, 3D mask attacks, and so on. A novel Deep Tree Network (DTN) is proposed
to tackle the ZSFA. The tree is learned to partition the spoof samples into
semantic sub-groups in an unsupervised fashion. When a data sample arrives,
being know or unknown attacks, DTN routes it to the most similar spoof cluster,
and make the binary decision. In addition, to enable the study of ZSFA, we
introduce the first face anti-spoofing database that contains diverse types of
spoof attacks. Experiments show that our proposed method achieves the state of
the art on multiple testing protocols of ZSFA.
| arxiv topic:cs.CV |
arxiv_dataset-110801904.0296 | A New Approach to Speed up Combinatorial Search Strategies Using Stack
and Hash Table
cs.SE
Owing to the significance of combinatorial search strategies both for
academia and industry, the introduction of new techniques is a fast growing
research field these days. These strategies have really taken different forms
ranging from simple to complex strategies in order to solve all forms of
combinatorial problems. Nonetheless, despite the kind of problem these
approaches solve, they are prone to heavy computation with the number of
combinations and growing search space dimensions. This paper presents a new
approach to speed up the generation and search processes using a combination of
stack and hash table data structures. This approach could be put to practice
for the combinatorial approaches to speed up the generation of combinations and
search process in the search space. Furthermore, this new approach proved its
performance in diverse stages better than other known strategies.
| arxiv topic:cs.SE |
arxiv_dataset-110811904.0306 | On the integer part of the reciprocal of the Riemann zeta function tail
at certain rational numbers in the critical strip
math.NT
We prove that the integer part of the reciprocal of the tail of $\zeta(s)$ at
a rational number $s=\frac{1}{p}$ for any integer with $p \geq 5$ or
$s=\frac{2}{p}$ for any odd integer with $p \geq 5$ can be described
essentially as the integer part of an explicit quantity corresponding to it. To
deal with the case when $s=\frac{2}{p},$ we use a result on the finiteness of
integral points of certain curves over $\mathbb{Q}$.
| arxiv topic:math.NT |
arxiv_dataset-110821904.0316 | Discrete Fourier Transform Improves the Prediction of the Electronic
Properties of Molecules in Quantum Machine Learning
quant-ph cond-mat.mtrl-sci physics.comp-ph
High-throughput approximations of quantum mechanics calculations and
combinatorial experiments have been traditionally used to reduce the search
space of possible molecules, drugs and materials. However, the interplay of
structural and chemical degrees of freedom introduces enormous complexity,
which the current state-of-the-art tools are not yet designed to handle. The
availability of large molecular databases generated by quantum mechanics (QM)
computations using first principles open new venues for data science to
accelerate the discovery of new compounds. In recent years, models that combine
QM with machine learning (ML) known as QM/ML models have been successful at
delivering the accuracy of QM at the speed of ML. The goals are to develop a
framework that will accelerate the extraction of knowledge and to get insights
from quantitative process-structure-property-performance relationships hidden
in materials data via a better search of the chemical compound space, and to
infer new materials with targeted properties. In this study, we show that by
integrating well-known signal processing techniques such as discrete Fourier
transform in the QM/ML pipeline, the outcomes can be significantly improved in
some cases. We also show that the spectrogram of a molecule may represent an
interesting molecular visualization tool.
| arxiv topic:quant-ph cond-mat.mtrl-sci physics.comp-ph |
arxiv_dataset-110831904.0326 | Pixels to Plans: Learning Non-Prehensile Manipulation by Imitating a
Planner
cs.RO
We present a novel method enabling robots to quickly learn to manipulate
objects by leveraging a motion planner to generate "expert" training
trajectories from a small amount of human-labeled data. In contrast to the
traditional sense-plan-act cycle, we propose a deep learning architecture and
training regimen called PtPNet that can estimate effective end-effector
trajectories for manipulation directly from a single RGB-D image of an object.
Additionally, we present a data collection and augmentation pipeline that
enables the automatic generation of large numbers (millions) of training image
and trajectory examples with almost no human labeling effort.
We demonstrate our approach in a non-prehensile tool-based manipulation task,
specifically picking up shoes with a hook. In hardware experiments, PtPNet
generates motion plans (open-loop trajectories) that reliably (89% success over
189 trials) pick up four very different shoes from a range of positions and
orientations, and reliably picks up a shoe it has never seen before. Compared
with a traditional sense-plan-act paradigm, our system has the advantages of
operating on sparse information (single RGB-D frame), producing high-quality
trajectories much faster than the "expert" planner (300ms versus several
seconds), and generalizing effectively to previously unseen shoes.
| arxiv topic:cs.RO |
arxiv_dataset-110841904.0336 | Hypersonic limit of two-dimensional steady compressible Euler flows
passing a straight wedge
math.AP math-ph math.MP physics.flu-dyn
We formulated a problem on hypersonic limit of two-dimensional steady
non-isentropic compressible Euler flows passing a straight wedge. It turns out
that Mach number of the upcoming uniform supersonic flow increases to infinite
may be taken as the adiabatic exponent $\gamma$ of the polytropic gas decreases
to $1$. We proposed a form of the Euler equations which is valid if the
unknowns are measures and constructed a measure solution contains Dirac
measures supported on the surface of the wedge. It is proved that as $\gamma
\to1$, the sequence of solutions of the compressible Euler equations that
containing a shock ahead of the wedge converge vaguely as measures to the
measure solution we constructed. This justified the Newton theory of hypersonic
flow passing obstacles in the case of two-dimensional straight wedges. The
result also demonstrates the necessity of considering general measure solutions
in the studies of boundary-value problems of systems of hyperbolic conservation
laws.
| arxiv topic:math.AP math-ph math.MP physics.flu-dyn |
arxiv_dataset-110851904.0346 | The prospects of gravitational waves on constraining the anisotropy of
the Universe
gr-qc
The observation of GW150914 indicated a new independent measurement of the
luminosity distance of a gravitational wave event. In this paper, we constrain
the anisotropy of the Universe by using gravitational wave events. We simulate
hundreds of events of binary neutron star merging that may be observed by
Einstein Telescope. Full simulation for producing process of gravitational wave
data is employed. We find that 200 of binary neutron star merging in redshift
$(0,1)$ observed by Einstein Telescope may constrain the anisotropy with an
accuracy comparable to the result from Union2.1 supernovae. This result shows
that gravitational waves can be a powerful tool in investigating the
cosmological anisotropy.
| arxiv topic:gr-qc |
arxiv_dataset-110861904.0356 | An Asynchronous, Decentralized Solution Framework for the Large Scale
Unit Commitment Problem
cs.DC
With increased reliance on cyber infrastructure, large scale power networks
face new challenges owing to computational scalability. In this paper we focus
on developing an asynchronous decentralized solution framework for the Unit
Commitment(UC) problem for large scale power networks. We exploit the inherent
asynchrony in a region based decomposition arising out of imbalance in regional
subproblems to boost computational efficiency. A two phase algorithm is
proposed that relies on the convex relaxation and privacy preserving valid
inequalities in order to deliver algorithmic improvements. Our algorithm
employs a novel interleaved binary mechanism that locally switches from the
convex subproblem to its binary counterpart based on consistent local
convergent behavior. We develop a high performance computing (HPC) oriented
software framework that uses Message Passing Interface (MPI) to drive our
benchmark studies. Our simulations performed on the IEEE 3012 bus case are
benchmarked against the centralized and a state of the art synchronous
decentralized method. The results demonstrate that the asynchronous method
improves computational efficiency by a significant amount and provides a
competitive solution quality rivaling the benchmark methods.
| arxiv topic:cs.DC |
arxiv_dataset-110871904.0366 | Fermion parity gap and exponential ground state degeneracy of the
one-dimensional Fermi gas with intrinsic attractive interaction
cond-mat.str-el cond-mat.quant-gas quant-ph
We examine the properties of a one-dimensional (1D) Fermi gas with attractive
intrinsic (Hubbard) interactions in the presence of spin-orbit coupling and
Zeeman field by numerically computing the pair binding energy, excitation gap,
and susceptibility to local perturbations using the density matrix
renormalization group. Such a system can, in principle, be realized in a system
of ultracold atoms confined in a 1D optical lattice. We note that, in the
presence of spatial interfaces introduced by a smooth parabolic potential, the
pair binding and excitation energy of the system decays exponentially with the
system size, pointing to the existence of an exponential ground state
degeneracy, and is consistent with recent works. However, the susceptibility of
the ground state degeneracy of this number-conserving system to local
impurities indicates that the energy gap vanishes as a power law with the
system size in the presence of local perturbations. We compare this system with
the more familiar system of an Ising antiferromagnet in the presence of a
transverse field realized with Rydberg atoms and argue that the exponential
splitting in the clean number-conserving 1D Fermi system is similar to a phase
with only conventional order.
| arxiv topic:cond-mat.str-el cond-mat.quant-gas quant-ph |
arxiv_dataset-110881904.0376 | Time Domain Audio Visual Speech Separation
eess.AS cs.SD
Audio-visual multi-modal modeling has been demonstrated to be effective in
many speech related tasks, such as speech recognition and speech enhancement.
This paper introduces a new time-domain audio-visual architecture for target
speaker extraction from monaural mixtures. The architecture generalizes the
previous TasNet (time-domain speech separation network) to enable multi-modal
learning and at meanwhile it extends the classical audio-visual speech
separation from frequency-domain to time-domain. The main components of
proposed architecture include an audio encoder, a video encoder that extracts
lip embedding from video streams, a multi-modal separation network and an audio
decoder. Experiments on simulated mixtures based on recently released LRS2
dataset show that our method can bring 3dB+ and 4dB+ Si-SNR improvements on
two- and three-speaker cases respectively, compared to audio-only TasNet and
frequency-domain audio-visual networks
| arxiv topic:eess.AS cs.SD |
arxiv_dataset-110891904.0386 | A shape optimization algorithm for cellular composites
math.OC
We propose and investigate a mesh deformation technique for PDE constrained
shape optimization. Introducing a gradient penalization to the inner product
for linearized shape spaces, mesh degeneration can be prevented within the
optimization iteration allowing for the scalability of employed solvers. We
illustrate the approach by a shape optimization for cellular composites with
respect to linear elastic energy under tension. The influence of the gradient
penalization is evaluated and the parallel scalability of the approach
demonstrated employing a geometric multigrid solver on hierarchically
distributed meshes.
| arxiv topic:math.OC |
arxiv_dataset-110901904.0396 | Boundary values of holomorphic semigroups and fractional integration
math.FA
The concept of boundary values of holomorphic semigroups in a general Banach
space is studied. As an application, we consider the Riemann-Liouville
semigroup of integration operator in the little H\"older spaces
$\rm{lip}_0^\alpha[0,\, 1] , \, 0<\alpha<1$ and prove that it admits a strongly
continuous boundary group, which is the group of fractional integration of
purely imaginary order. The corresponding result for the $L^p$-spaces
($1<p<\infty$) has been known for some time, the case $p=2$ dating back to the
monograph by Hille and Phillips. In the context of $L^p$ spaces, we establish
the existence of the boundary group of the Hadamard fractional integration
operators using semigroup methods. In the general framework, using a suitable
spectral decomposition,we give a partial treatment of the inverse problem,
namely: Which $C_0$-groups are boundary values of some holomorphic semigroup of
angle $\pi/2$?
| arxiv topic:math.FA |
arxiv_dataset-110911904.0406 | Difference of source regions between fast and slow coronal mass
ejections
astro-ph.SR
Coronal mass ejections (CMEs) are tightly related to filament eruptions and
usually are their continuation in the upper solar corona. It is common practice
to divide all observed CMEs into fast and slow ones. Fast CMEs usually follow
eruptive events in active regions near big sunspot groups and associated with
major solar flares. Slow CMEs are more related to eruptions of quiescent
prominences located far from active regions. We analyze ten eruptive events
with particular attention to the events on 2013 September 29 and on 2016
January 26, one of which was associated with a fast CME, while another was
followed by a slow CME. We estimated the initial store of free magnetic energy
in the two regions and show the resemblance of pre-eruptive situations. The
difference of late behaviour of the two eruptive prominences is a consequence
of the different structure of magnetic field above the filaments. We estimated
this structure on the basis of potential magnetic field calculations. Analysis
of other eight events confirmed that all fast CMEs originate in regions with
rapidly changing with height value and direction of coronal magnetic field.
| arxiv topic:astro-ph.SR |
arxiv_dataset-110921904.0416 | Background driving distribution functions and series representation for
log-gamma selfdecomposable random variables
math.PR
For the selfdecomposable distributions (random variables) we identified
background driving probability distributions in their random integral
representations. For log-gamma and their background driving random variables
series representations are found.
| arxiv topic:math.PR |
arxiv_dataset-110931904.0426 | Estimating the dark matter velocity anisotropy to the cluster edge
astro-ph.CO
Dark matter dominates the properties of large cosmological structures such as
galaxy clusters, and the mass profiles of the dark matter have been measured
for these equilibrated structures for years using X-rays, lensing or galaxy
velocities. A new method has been proposed, which should allow us to estimate a
dynamical property of the dark matter, namely the velocity anisotropy. For the
gas a similar velocity anisotropy is zero due to frequent collisions, however,
the collisionless nature of dark matter allows it to be non-trivial. Numerical
simulations have for years found non-zero and radially varying dark matter
velocity anisotropies. Here we employ the method proposed by Hansen and
Pifaretti (2007), and developed by Host et al. (2009) to estimate the dark
matter velocity anisotropy in the bright galaxy cluster Perseus, to near 5
times the radii previously obtained. We find the dark matter velocity
anisotropy to be consistent with the results of numerical simulations, however,
still with large error-bars. At half the virial radius we find the velocity
anisotropy to be non-zero at 1.7 standard deviations, lending support to the
collisionless nature of dark matter.
| arxiv topic:astro-ph.CO |
arxiv_dataset-110941904.0436 | Optimizing Majority Voting Based Systems Under a Resource Constraint for
Multiclass Problems
cs.AI cs.LG
Ensemble-based approaches are very effective in various fields in raising the
accuracy of its individual members, when some voting rule is applied for
aggregating the individual decisions. In this paper, we investigate how to find
and characterize the ensembles having the highest accuracy if the total cost of
the ensemble members is bounded. This question leads to Knapsack problem with
non-linear and non-separable objective function in binary and multiclass
classification if the majority voting is chosen for the aggregation. As the
conventional solving methods cannot be applied for this task, a novel
stochastic approach was introduced in the binary case where the energy function
is discussed as the joint probability function of the member accuracy. We show
some theoretical results with respect to the expected ensemble accuracy and its
variance in the multiclass classification problem which can help us to solve
the Knapsack problem.
| arxiv topic:cs.AI cs.LG |
arxiv_dataset-110951904.0446 | Attention-based Multi-instance Neural Network for Medical Diagnosis from
Incomplete and Low Quality Data
cs.LG cs.CL
One way to extract patterns from clinical records is to consider each patient
record as a bag with various number of instances in the form of symptoms.
Medical diagnosis is to discover informative ones first and then map them to
one or more diseases. In many cases, patients are represented as vectors in
some feature space and a classifier is applied after to generate diagnosis
results. However, in many real-world cases, data is often of low-quality due to
a variety of reasons, such as data consistency, integrity, completeness,
accuracy, etc. In this paper, we propose a novel approach, attention based
multi-instance neural network (AMI-Net), to make the single disease
classification only based on the existing and valid information in the
real-world outpatient records. In the context of a patient, it takes a bag of
instances as input and output the bag label directly in end-to-end way.
Embedding layer is adopted at the beginning, mapping instances into an
embedding space which represents the individual patient condition. The
correlations among instances and their importance for the final classification
are captured by multi-head attention transformer, instance-level multi-instance
pooling and bag-level multi-instance pooling. The proposed approach was test on
two non-standardized and highly imbalanced datasets, one in the Traditional
Chinese Medicine (TCM) domain and the other in the Western Medicine (WM)
domain. Our preliminary results show that the proposed approach outperforms all
baselines results by a significant margin.
| arxiv topic:cs.LG cs.CL |
arxiv_dataset-110961904.0456 | Thinkey: A Scalable Blockchain Architecture
cs.CR
This paper presents Thinkey, an efficient, secure, infinitely scalable and
decentralized blockchain architecture. It ensures system correctness and
liveness by a multi-layer structure. In particular, the system is based on a
double-chain architecture and uses a multi-layer consensus protocol to
guarantee consistency. Thinkey also uses a novel account model which is based
on Actor Model to support the complex logic in the multi-chain structure.
Experiment results show that the proposed Thinkey architecture can achieve
higher throughput as the number of nodes increases.
| arxiv topic:cs.CR |
arxiv_dataset-110971904.0466 | Cylindrical symmetric, non-rotating and non-static or static black hole
solutions and the naked singularities
physics.gen-ph
In this work, a four-dimensional cylindrical symmetric and non-static or
static space-times in the backgrounds of anti-de Sitter (AdS) space with
perfect stiff fluid, anisotropic fluid and electromagnetic field as the
stress-energy tensor, is presented. For suitable parameter conditions in the
metric function, the solution represents non-static or static non-rotating
black hole solution. In addition, we show for various parameter conditions, the
solution represents static and/or non-static models with a naked singularity
without an event horizon.
| arxiv topic:physics.gen-ph |
arxiv_dataset-110981904.0476 | $T\bar{T}$ deformations with $\mathcal{N}=(0,2)$ supersymmetry
hep-th
We investigate the behaviour of two-dimensional quantum field theories with
$\mathcal{N}=(0,2)$ supersymmetry under a deformation induced by the
`$T\bar{T}$' composite operator. We show that the deforming operator can be
defined by a point-splitting regularisation in such a way as to preserve
$\mathcal{N}=(0,2)$ supersymmetry. As an example of this construction, we work
out the deformation of a free $\mathcal{N}=(0,2)$ theory and compare to that
induced by the Noether stress-energy tensor. Finally, we show that the
$\mathcal{N}=(0,2)$ supersymmetric deformed action actually possesses
$\mathcal{N}=(2,2)$ symmetry, half of which is non-linearly realised.
| arxiv topic:hep-th |
arxiv_dataset-110991904.0486 | Bridging between 0/1 and Linear Programming via Random Walks
cs.DS cs.CC
Under the Strong Exponential Time Hypothesis, an integer linear program with
$n$ Boolean-valued variables and $m$ equations cannot be solved in $c^n$ time
for any constant $c < 2$. If the domain of the variables is relaxed to $[0,1]$,
the associated linear program can of course be solved in polynomial time. In
this work, we give a natural algorithmic bridging between these extremes of
$0$-$1$ and linear programming. Specifically, for any subset (finite union of
intervals) $E \subset [0,1]$ containing $\{0,1\}$, we give a random-walk based
algorithm with runtime $O_E((2-\text{measure}(E))^n\text{poly}(n,m))$ that
finds a solution in $E^n$ to any $n$-variable linear program with $m$
constraints that is feasible over $\{0,1\}^n$. Note that as $E$ expands from
$\{0,1\}$ to $[0,1]$, the runtime improves smoothly from $2^n$ to polynomial.
Taking $E = [0,1/k) \cup (1-1/k,1]$ in our result yields as a corollary a
randomized $(2-2/k)^{n}\text{poly}(n)$ time algorithm for $k$-SAT. While our
approach has some high level resemblance to Sch\"{o}ning's beautiful algorithm,
our general algorithm is based on a more sophisticated random walk that
incorporates several new ingredients, such as a multiplicative potential to
measure progress, a judicious choice of starting distribution, and a time
varying distribution for the evolution of the random walk that is itself
computed via an LP at each step (a solution to which is guaranteed based on the
minimax theorem). Plugging the LP algorithm into our earlier polymorphic
framework yields fast exponential algorithms for any CSP (like $k$-SAT,
$1$-in-$3$-SAT, NAE $k$-SAT) that admit so-called `threshold partial
polymorphisms.'
| arxiv topic:cs.DS cs.CC |
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