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arxiv_dataset-108001901.10453 | Simulating the DNA String Graph in Succinct Space
cs.DS
Converting a set of sequencing reads into a lossless compact data structure
that encodes all the relevant biological information is a major challenge. The
classical approaches are to build the string graph or the de Bruijn graph. Each
has advantages over the other depending on the application. Still, the ideal
setting would be to have an index of the reads that is easy to build and can be
adapted to any type of biological analysis. In this paper, we propose a new
data structure we call rBOSS, which gets close to that ideal. Our rBOSS is a de
Bruijn graph in practice, but it simulates any length up to k and can compute
overlaps of size at least m between the labels of the nodes, with k and m being
parameters. If we choose the parameter k equal to the size of the reads, then
we can simulate a complete string graph. As most BWT-based structures, rBOSS is
unidirectional, but it exploits the property of the DNA reverse complements to
simulate bi-directionality with some time-space trade-offs. We implemented a
genome assembler on top of rBOSS to demonstrate its usefulness. Our
experimental results show that using k = 100, rBOSS can assemble 185 MB of
reads in less than 15 minutes and using 110 MB in total. It produces contigs of
mean sizes over 10,000, which is twice the size obtained by using a pure de
Bruijn graph of fixed length k.
| arxiv topic:cs.DS |
arxiv_dataset-108011901.10553 | Quantifying Legibility of Indoor Spaces Using Deep Convolutional Neural
Networks: Case Studies in Train Stations
cs.CY cs.CV
Legibility is the extent to which a space can be easily recognized.
Evaluating legibility is particularly desirable in indoor spaces, since it has
a large impact on human behavior and the efficiency of space utilization.
However, indoor space legibility has only been studied through survey and
trivial simulations and lacks reliable quantitative measurement. We utilized a
Deep Convolutional Neural Network (DCNN), which is structurally similar to a
human perception system, to model legibility in indoor spaces. To implement the
modeling of legibility for any indoor spaces, we designed an end-to-end
processing pipeline from indoor data retrieving to model training to spatial
legibility analysis. Although the model performed very well (98% top-1
accuracy) overall, there are still discrepancies in accuracy among different
spaces, reflecting legibility differences. To prove the validity of the
pipeline, we deployed a survey on Amazon Mechanical Turk, collecting 4,015
samples. The human samples showed a similar behavior pattern and mechanism as
the DCNN models. Further, we used model results to visually explain legibility
in different architectural programs, building age, building style, visual
clusterings of spaces and visual explanations for building age and
architectural functions.
| arxiv topic:cs.CY cs.CV |
arxiv_dataset-108021901.10653 | Evaluating Bregman Divergences for Probability Learning from Crowd
cs.LG cs.AI stat.ML
The crowdsourcing scenarios are a good example of having a probability
distribution over some categories showing what the people in a global
perspective thinks. Learn a predictive model of this probability distribution
can be of much more valuable that learn only a discriminative model that gives
the most likely category of the data. Here we present differents models that
adapts having probability distribution as target to train a machine learning
model. We focus on the Bregman divergences framework to used as objective
function to minimize. The results show that special care must be taken when
build a objective function and consider a equal optimization on neural network
in Keras framework.
| arxiv topic:cs.LG cs.AI stat.ML |
arxiv_dataset-108031901.10753 | Deterministic multi-mode nonlinear coupling for quantum circuits
quant-ph
We present a general technique for deterministic implementation of a
multi-mode nonlinear coupling between several propagating microwave or optical
modes in quantum circuits. The measurement induced technique combines
specifically prepared resource states together with feasible feed-forward
operations. We explore several ways of generating the suitable resource states
and discuss their difference on an illustrative example of cubic coupling
between two modes. We also show that the required entangled states with
requisite nonlinear properties can be already generated in the present day
experiments.
| arxiv topic:quant-ph |
arxiv_dataset-108041901.10853 | Sub-GHz linewidths ensembles of SiV centers in a diamond nano-pyramid
revealed by charge state conversion
quant-ph cond-mat.mes-hall
Producing nano-structures with embedded bright ensembles of lifetime-limited
emitters is a challenge with potential high impact in a broad range of physical
sciences. In this work, we demonstrate controlled charge transfer to and from
dark states exhibiting very long lifetimes in high density ensembles of SiV
centers hosted in a CVD-grown diamond nano-pyramid. Further, using a
combination of resonant photoluminescence excitation and a frequency-selective
persistent hole burning technique that exploits such charge state transfer, we
could demonstrate close to lifetime-limited linewidths from the SiV centers.
Such a nanostructure with thousands of bright narrow linewidth emitters in a
volume much below $\lambda^3$ will be useful for coherent light-matter
coupling, for biological sensing, and nanoscale thermometry.
| arxiv topic:quant-ph cond-mat.mes-hall |
arxiv_dataset-108051901.10953 | On the Instability of Saturn's Hypothetical Retrograde Co-orbitals
astro-ph.EP
We find an interesting fact that fictitious retrograde co-orbitals of Saturn,
or small bodies inside the retrograde 1:1 resonance with Saturn, are highly
unstable in our numerical simulations. It is shown that in the presence of
Jupiter, the retrograde co-orbitals will get ejected from Saturn's co-orbital
space within a timescale of 10 Myr. This scenario reminds us of the instability
of Saturn Trojans caused by both the Great Inequality and the secular
resonances. Therefore, we carry out in-depth inspections on both mechanisms and
prove that the retrograde resonance overlap, raised by Great Inequality, cannot
serve as an explanation for the instability of retrograde co-orbitals, due to
the weakness of the retrograde 2:5 resonance with Jupiter at a low
eccentricity. However, we discover that both $\nu_5$ and $\nu_6$ secular
resonances contribute to the slow growth of the eccentricity, therefore, are
possibly the primary causes of the instability inside Saturn's retrograde
co-orbital space.
| arxiv topic:astro-ph.EP |
arxiv_dataset-108061901.11053 | Software solutions for form-based collection of data and the semantic
enrichment of form data
cs.CY
Data collection is an important part of many citizen science projects as well
as other fields of research, particularly in life sciences. Mobile applications
with form-based surveys are increasingly used to support this, due to the large
number of mobile devices and their growing number of built-in sensors. Since
the composition of form-based surveys from scratch can be a tedious task,
multiple tools have been published that can help with their design and
distribution as well as the data collection via mobile devices and the data
storage. Some even support simple data analysis. With this increasing number of
software options project leaders will often face the question, which tool is
most suitable for their current use case.
With that in mind, this project pursues two main objectives:
1. To present an overview of a selection of survey design tools and their
capabilities in order to provide a clear foundation for such a decision.
2. To examine if any tool provides the capability to collect and export data
in a way that can easily be used and interpreted by other applications or
persons. This aspect includes the supply of metadata about the data collection
process and the data itself, information about the meaning of the data as well
as an export format that can easily be processed.
| arxiv topic:cs.CY |
arxiv_dataset-108071901.11153 | Pix2Vox: Context-aware 3D Reconstruction from Single and Multi-view
Images
cs.CV
Recovering the 3D representation of an object from single-view or multi-view
RGB images by deep neural networks has attracted increasing attention in the
past few years. Several mainstream works (e.g., 3D-R2N2) use recurrent neural
networks (RNNs) to fuse multiple feature maps extracted from input images
sequentially. However, when given the same set of input images with different
orders, RNN-based approaches are unable to produce consistent reconstruction
results. Moreover, due to long-term memory loss, RNNs cannot fully exploit
input images to refine reconstruction results. To solve these problems, we
propose a novel framework for single-view and multi-view 3D reconstruction,
named Pix2Vox. By using a well-designed encoder-decoder, it generates a coarse
3D volume from each input image. Then, a context-aware fusion module is
introduced to adaptively select high-quality reconstructions for each part
(e.g., table legs) from different coarse 3D volumes to obtain a fused 3D
volume. Finally, a refiner further refines the fused 3D volume to generate the
final output. Experimental results on the ShapeNet and Pix3D benchmarks
indicate that the proposed Pix2Vox outperforms state-of-the-arts by a large
margin. Furthermore, the proposed method is 24 times faster than 3D-R2N2 in
terms of backward inference time. The experiments on ShapeNet unseen 3D
categories have shown the superior generalization abilities of our method.
| arxiv topic:cs.CV |
arxiv_dataset-108081901.11253 | Fermion Localization and Degenerate Resonances on Brane Array
hep-th
In this work, we consider the multi-wall braneworld arisen from multi-scalar
fields, and investigate the localization and resonances of spin-1/2 fermion on
the multi-walls. We build two analytic multi-wall solutions with a polynomial
superpotential and a modified sine-Gordon superpotential respectively. The
massless fermion is the only bound state and localized between the two
outermost sub-branes. The factors affecting the number of massive resonant
fermions are analyzed. What interesting is that all the fermion resonant states
are non-degenerate for the cases of single- and two-walls, however,
doubly-degenerate fermion resonant states emerge for the cases of three- and
four-walls. This novel phenomenon could be potentially interesting in
phenomenology.
| arxiv topic:hep-th |
arxiv_dataset-108091901.11353 | Intensive Monitoring Survey of Nearby Galaxies (IMSNG)
astro-ph.GA astro-ph.HE astro-ph.IM
Intensive Monitoring Survey of Nearby Galaxies (IMSNG) is a high cadence
observation program monitoring nearby galaxies with high probabilities of
hosting supernovae (SNe). IMSNG aims to constrain the SN explosion mechanism by
inferring sizes of SN progenitor systems through the detection of the
shock-heated emission that lasts less than a few days after the SN explosion.
To catch the signal, IMSNG utilizes a network of 0.5-m to 1-m class telescopes
around the world and monitors the images of 60 nearby galaxies at distances D <
50 Mpc to a cadence as short as a few hours. The target galaxies are bright in
near-ultraviolet (NUV) with M_NUV < -18.4 AB mag and have high probabilities of
hosting SNe (0.06 SN/yr per galaxy). With this strategy, we expect to detect
the early light curves of 3.4 SNe per year to a depth of R ~ 19.5 mag, enabling
us to detect the shock-heated emission from a progenitor star with a radius as
small as 0.1 R_sun. The accumulated data will be also useful for studying faint
features around the target galaxies and other science projects. So far, 18 SNe
have occurred in our target fields (16 in IMSNG galaxies) over 5 years,
confirming our SN rate estimate of 0.06 SN/yr per galaxy.
| arxiv topic:astro-ph.GA astro-ph.HE astro-ph.IM |
arxiv_dataset-108101901.11453 | The SuperM-Tree: Indexing metric spaces with sized objects
cs.DS
A common approach to implementing similarity search applications is the usage
of distance functions, where small distances indicate high similarity. In the
case of metric distance functions, metric index structures can be used to
accelerate nearest neighbor queries. On the other hand, many applications ask
for approximate subsequences or subsets, e.g. searching for a similar partial
sequence of a gene, for a similar scene in a movie, or for a similar object in
a picture which is represented by a set of multidimensional features. Metric
index structures such as the M-Tree cannot be utilized for these tasks because
of the symmetry of the metric distance functions. In this work, we propose the
SuperM-Tree as an extension of the M-Tree where approximate subsequence and
subset queries become nearest neighbor queries. In order to do this, we
introduce metric subset spaces as a generalized concept of metric spaces.
Various metric distance functions can be extended to metric subset distance
functions, e.g. the Euclidean distance (on windows), the Hausdorff distance (on
subsets), the Edit distance and the Dog-Keeper distance (on subsequences). We
show that these examples subsume the applications mentioned above.
| arxiv topic:cs.DS |
arxiv_dataset-108111902.00016 | Network Parameter Learning Using Nonlinear Transforms, Local
Representation Goals and Local Propagation Constraints
cs.LG cs.AI cs.DC cs.NE stat.ML
In this paper, we introduce a novel concept for learning of the parameters in
a neural network. Our idea is grounded on modeling a learning problem that
addresses a trade-off between (i) satisfying local objectives at each node and
(ii) achieving desired data propagation through the network under (iii) local
propagation constraints. We consider two types of nonlinear transforms which
describe the network representations. One of the nonlinear transforms serves as
activation function. The other one enables a locally adjusted, deviation
corrective components to be included in the update of the network weights in
order to enable attaining target specific representations at the last network
node. Our learning principle not only provides insight into the understanding
and the interpretation of the learning dynamics, but it offers theoretical
guarantees over decoupled and parallel parameter estimation strategy that
enables learning in synchronous and asynchronous mode. Numerical experiments
validate the potential of our approach on image recognition task. The
preliminary results show advantages in comparison to the state-of-the-art
methods, w.r.t. the learning time and the network size while having competitive
recognition accuracy.
| arxiv topic:cs.LG cs.AI cs.DC cs.NE stat.ML |
arxiv_dataset-108121902.00116 | Generalized uncertainty principle in graphene
hep-th cond-mat.other
We show that, by going beyond the low-energy approximation for which the
dispersion relations of graphene are linear, the corresponding emergent field
theory is a specific generalization a Dirac field theory. The generalized Dirac
Hamiltonians one obtains are those compatible with specific generalizations of
the uncertainty principle. We also briefly comment on the compatibility of the
latter with noncommuting positions, $[x_i,x_j] \neq 0$, and on their possible
physical realization.
| arxiv topic:hep-th cond-mat.other |
arxiv_dataset-108131902.00216 | An Extension of Linear-size Suffix Tries for Parameterized Strings
cs.DS
In this paper, we propose a new indexing structure for parameterized strings
which we call PLSTs, by generalizing linear-size suffix tries for ordinary
strings. Two parameterized strings are said to match if there is a bijection on
the symbol set that makes the two coincide. PLSTs are applicable to the
parameterized pattern matching problem, which is to decide whether the input
parameterized text has a substring that matches the input parameterized
pattern. The size of PLSTs is linear in the text size, with which our algorithm
solves the parameterized pattern matching problem in linear time in the pattern
size. PLSTs can be seen as a compacted version of parameterized suffix tries
and a combination of linear-size suffix tries and parameterized suffix trees.
We experimentally show that PLSTs are more space efficient than parameterized
suffix trees for highly repetitive strings.
| arxiv topic:cs.DS |
arxiv_dataset-108141902.00316 | Purification and time-reversal deny entanglement in LOCC-distinguishable
orthonormal bases
quant-ph
We give a simple proof, based on time-reversibility and purity, that a
complete orthonormal family of pure states which can be perfectly distinguished
by LOCC cannot contain any entangled state. Our results are really about the
shape of certain states and processes, and are valid in arbitrary categorical
probabilistic theories with time-reversal. From the point of view of the
resource theory of entanglement, our results can be interpreted to say that
free processes can distinguish between the states in a complete orthonormal
family only when the states themselves are all free.
| arxiv topic:quant-ph |
arxiv_dataset-108151902.00416 | The Role of Internal Photons on the Chemistry of the Circumstellar
Envelopes of AGB Stars
astro-ph.SR astro-ph.GA
Recent high spatial resolution observations of gas and dust in the
circumstellar envelopes (CSEs) of AGB stars indicate morphologies much more
complex than the smooth density distributions generated by spherically
symmetric, constant mass loss rates. In particular, the observation of spiral
arcs and disks indicate the likely presence of a binary companion which in some
cases give rise to the UV photons detected by GALEX. In this Article, we extend
our recent model of the chemistry in a clumpy, porous CSE around an AGB star to
include the influence of stellar blackbody photons on the CSE chemistry. Our
results indicate that internal photons, in a clumpy, porous CSE, can alter
chemistry within a few stellar radii and, for some molecules, alter abundances
out to several hundred stellar radii. They further suggest that harder
radiation from companion stars or accretion disks will have a substantial
impact on chemistry in the dust formation zones and inner CSEs of AGB stars.
| arxiv topic:astro-ph.SR astro-ph.GA |
arxiv_dataset-108161902.00516 | Glass-induced enhancement of superconducting $T_c$: Pairing via
dissipative mediators
cond-mat.supr-con cond-mat.dis-nn cond-mat.str-el
With substantial evidence of glassy behavior in the phase diagram of high
$T_c$ superconductors and its co-existence with superconductivity, we attempt
to answer the question: what are the properties of a superconducting state
where the force driving cooper pairing becomes dissipative? We find that when
the bosonic mediator is local, dissipation acts to reduce the superconducting
critical temperature ($T_c$). On the other hand, contrary to na\"{i}ve
expectations, $T_c$ behaves non-monotonically with dissipation for a non-local
mediator -- weakly dissipative bosons at different energy scales act coherently
to give rise to an increase in $T_c$ and eventually destroy superconductivity
when the dissipation exceeds a critical value. The critical value occurs when
dissipative effects become comparable to the energy scale associated with the
spatial stiffness of the mediator, at which point, $T_c$ acquires a maximum. We
outline consequences of our results to recent proton irradiation experiments
(M. Leroux et al.,~\cite{Welp2018}) on the cuprate superconductor
La$_{2-x}$Ba$_x$CuO$_4$ (LBCO) which observe a disorder induced increase in
$T_c$ even when the transition temperature of the proximate charge density wave
(CDW) is unaffected by the presence of irradiation. Our mechanism is a novel
way to raise $T_c$ that does not require a `tug-of-war' -type scenario between
two competing phases.
| arxiv topic:cond-mat.supr-con cond-mat.dis-nn cond-mat.str-el |
arxiv_dataset-108171902.00616 | Application Specific Drone Simulators: Recent Advances and Challenges
cs.RO
Over the past two decades, Unmanned Aerial Vehicles (UAVs), more commonly
known as drones, have gained a lot of attention, and are rapidly becoming
ubiquitous because of their diverse applications such as surveillance, disaster
management, pollution monitoring, film-making, and military reconnaissance.
However, incidents such as fatal system failures, malicious attacks, and
disastrous misuses have raised concerns in the recent past. Security and
viability concerns in drone-based applications are growing at an alarming rate.
Besides, UAV networks (UAVNets) are distinctive from other ad-hoc networks.
Therefore, it is necessary to address these issues to ensure proper functioning
of these UAVs while keeping their uniqueness in mind. Furthermore, adequate
security and functionality require the consideration of many parameters that
may include an accurate cognizance of the working mechanism of vehicles,
geographical and weather conditions, and UAVNet communication. This is
achievable by creating a simulator that includes these aspects. A performance
evaluation through relevant drone simulator becomes indispensable procedure to
test features, configurations, and designs to demonstrate superiority to
comparative schemes and suitability. Thus, it becomes of paramount importance
to establish the credibility of simulation results by investigating the merits
and limitations of each simulator prior to selection. Based on this motivation,
we present a comprehensive survey of current drone simulators. In addition,
open research issues and research challenges are discussed and presented.
| arxiv topic:cs.RO |
arxiv_dataset-108181902.00716 | Centrality anomalies in complex networks as a result of model
over-simplification
physics.soc-ph cs.SI
Tremendous advances have been made in our understanding of the properties and
evolution of complex networks. These advances were initially driven by
information-poor empirical networks and theoretical analysis of unweighted and
undirected graphs. Recently, information-rich empirical data complex networks
supported the development of more sophisticated models that include edge
directionality and weight properties, and multiple layers. Many studies still
focus on unweighted undirected description of networks, prompting an essential
question: how to identify when a model is simpler than it must be? Here, we
argue that the presence of centrality anomalies in complex networks is a result
of model over-simplification. Specifically, we investigate the well-known
anomaly in betweenness centrality for transportation networks, according to
which highly connected nodes are not necessarily the most central. Using a
broad class of network models with weights and spatial constraints and four
large data sets of transportation networks, we show that the unweighted
projection of the structure of these networks can exhibit a significant
fraction of anomalous nodes compared to a random null model. However, the
weighted projection of these networks, compared with an appropriated null
model, significantly reduces the fraction of anomalies observed, suggesting
that centrality anomalies are a symptom of model over-simplification. Because
lack of information-rich data is a common challenge when dealing with complex
networks and can cause anomalies that misestimate the role of nodes in the
system, we argue that sufficiently sophisticated models be used when anomalies
are detected.
| arxiv topic:physics.soc-ph cs.SI |
arxiv_dataset-108191902.00816 | Sound Event Detection Using Graph Laplacian Regularization Based on
Event Co-occurrence
cs.SD eess.AS
The types of sound events that occur in a situation are limited, and some
sound events are likely to co-occur; for instance, ``dishes'' and ``glass
jingling.'' In this paper, we propose a technique of sound event detection
utilizing graph Laplacian regularization taking the sound event co-occurrence
into account. In the proposed method, sound event occurrences are represented
as a graph whose nodes indicate the frequency of event occurrence and whose
edges indicate the co-occurrence of sound events. This graph representation is
then utilized for sound event modeling, which is optimized under an objective
function with a regularization term considering the graph structure.
Experimental results obtained using TUT Sound Events 2016 development, 2017
development, and TUT Acoustic Scenes 2016 development indicate that the
proposed method improves the detection performance of sound events by 7.9
percentage points compared to that of the conventional CNN-BiGRU-based method
in terms of the segment-based F1-score. Moreover, the results show that the
proposed method can detect co-occurring sound events more accurately than the
conventional method.
| arxiv topic:cs.SD eess.AS |
arxiv_dataset-108201902.00916 | Discovering Implicational Knowledge in Wikidata
cs.AI
Knowledge graphs have recently become the state-of-the-art tool for
representing the diverse and complex knowledge of the world. Examples include
the proprietary knowledge graphs of companies such as Google, Facebook, IBM, or
Microsoft, but also freely available ones such as YAGO, DBpedia, and Wikidata.
A distinguishing feature of Wikidata is that the knowledge is collaboratively
edited and curated. While this greatly enhances the scope of Wikidata, it also
makes it impossible for a single individual to grasp complex connections
between properties or understand the global impact of edits in the graph. We
apply Formal Concept Analysis to efficiently identify comprehensible
implications that are implicitly present in the data. Although the complex
structure of data modelling in Wikidata is not amenable to a direct approach,
we overcome this limitation by extracting contextual representations of parts
of Wikidata in a systematic fashion. We demonstrate the practical feasibility
of our approach through several experiments and show that the results may lead
to the discovery of interesting implicational knowledge. Besides providing a
method for obtaining large real-world data sets for FCA, we sketch potential
applications in offering semantic assistance for editing and curating Wikidata.
| arxiv topic:cs.AI |
arxiv_dataset-108211902.01016 | Global well-posedness, dissipation and blow up for semilinear heat
equations in energy spaces associated with self-adjoint operators
math.AP
The purpose in this paper is to determine the global behavior of solutions to
the initial-boundary value problems for energy-subcritical and critical
semilinear heat equations by initial data with lower energy than the mountain
pass level in energy spaces associated with self-adjoint operators satisfying
Gaussian upper bounds. Our self-adjoint operators include the Dirichlet
Laplacian on an open set, Robin Laplacian on an exterior domain, and
Schr\"odinger operators, etc.
| arxiv topic:math.AP |
arxiv_dataset-108221902.01116 | Notes on bilinear multipliers on Orlicz spaces
math.FA
Let $\Phi_1 , \Phi_2 $ and $ \Phi_3$ be Young functions and let
$L^{\Phi_1}(\mathbb{R})$, $L^{\Phi_2}(\mathbb{R})$ and $L^{\Phi_3}(\mathbb{R})$
be the corresponding Orlicz spaces. We say that a function $m(\xi,\eta)$
defined on $\mathbb{R}\times \mathbb{R}$ is a bilinear multiplier of type
$(\Phi_1,\Phi_2,\Phi_3)$ if \[ B_m(f,g)(x)=\int_\mathbb{R} \int_\mathbb{R}
\hat{f}(\xi) \hat{g}(\eta)m(\xi,\eta)e^{2\pi i (\xi+\eta) x}d\xi d\eta \]
defines a bounded bilinear operator from $L^{\Phi_1}(\mathbb{R}) \times
L^{\Phi_2}(\mathbb{R})$ to $L^{\Phi_3}(\mathbb{R})$. We denote by
$BM_{(\Phi_1,\Phi_2,\Phi_3)}(\mathbb{R})$ the space of all bilinear multipliers
of type $(\Phi_1,\Phi_2,\Phi_3)$ and investigate some properties of such a
class. Under some conditions on the triple $(\Phi_1,\Phi_2,\Phi_3)$ we give
some examples of bilinear multipliers of type $(\Phi_1,\Phi_2,\Phi_3)$. We will
focus on the case $m(\xi,\eta)=M(\xi-\eta) $ and get necessary conditions on
$(\Phi_1,\Phi_2,\Phi_3)$ to get non-trivial multipliers in this class. In
particular we recover some of the the known results for Lebesgue spaces.
| arxiv topic:math.FA |
arxiv_dataset-108231902.01216 | Laser refrigeration using exciplex resonances in gas filled hollow-core
fibres
quant-ph physics.atom-ph
We theoretically study prospects and limitations of a new route towards
macroscopic scale laser refrigeration based on exciplex-mediated frequency
up-conversion in gas filled hollow-core fibres. Using proven quantum optical
rate equations we model the dynamics of a dopant-buffer gas mixture filling an
optically pumped waveguide. In the particular example of alkali-noble gas
mixtures, recent high pressure gas cell setup experiments have shown that
efficient kinetic energy extraction cycles appear via the creation of transient
exciplex excited electronic bound states. The cooling cycle consists of
absorption of lower energy laser photons during collisions followed by
blue-shifted spontaneous emission on the atomic line of the alkali atoms. For
any arbitrary dopant-buffer gas mixture, we derive scaling laws for cooling
power, cooling rates and temperature drops with varying input laser power,
dopant and buffer gas concentration, fibre geometry and particularities of the
exciplex ground and excited state potential landscapes.
| arxiv topic:quant-ph physics.atom-ph |
arxiv_dataset-108241902.01316 | A giant impact as the likely origin of different twins in the Kepler-107
exoplanet system
astro-ph.EP astro-ph.SR
Measures of exoplanet bulk densities indicate that small exoplanets with
radius less than 3 Earth radii ($R_\oplus$) range from low-density sub-Neptunes
containing volatile elements to higher density rocky planets with Earth-like or
iron-rich (Mercury-like) compositions. Such astonishing diversity in observed
small exoplanet compositions may be the product of different initial conditions
of the planet-formation process and/or different evolutionary paths that
altered the planetary properties after formation. Planet evolution may be
especially affected by either photoevaporative mass loss induced by high
stellar X-ray and extreme ultraviolet (XUV) flux or giant impacts. Although
there is some evidence for the former, there are no unambiguous findings so far
about the occurrence of giant impacts in an exoplanet system. Here, we
characterize the two innermost planets of the compact and near-resonant system
Kepler-107. We show that they have nearly identical radii (about
$1.5-1.6~R_\oplus$), but the outer planet Kepler-107c is more than twice as
dense (about $12.6~\rm g\,cm^{-3}$) as the innermost Kepler-107b (about
$5.3~\rm g\,cm^{-3}$). In consequence, Kepler-107c must have a larger iron core
fraction than Kepler-107b. This imbalance cannot be explained by the stellar
XUV irradiation, which would conversely make the more-irradiated and
less-massive planet Kepler-107b denser than Kepler-107c. Instead, the
dissimilar densities are consistent with a giant impact event on Kepler-107c
that would have stripped off part of its silicate mantle. This hypothesis is
supported by theoretical predictions from collisional mantle stripping, which
match the mass and radius of Kepler-107c.
| arxiv topic:astro-ph.EP astro-ph.SR |
arxiv_dataset-108251902.01416 | Hubble Space Telescope photometry of multiple stellar populations in the
inner parts of NGC 2419
astro-ph.SR astro-ph.GA
We present new deep imaging of the central regions of the remote globular
cluster NGC 2419, obtained with the F343N and F336W filters of HST/WFC3. The
new data are combined with archival imaging to constrain nitrogen and helium
abundance variations within the cluster. We find a clearly bimodal distribution
of the nitrogen-sensitive F336W-F343N colours of red giants, from which we
estimate that about 55% of the giants belong to a population with about normal
(field-like) nitrogen abundances (P1), while the remaining 45% belong to a
nitrogen-rich population (P2). On average, the P2 stars are more He-rich than
the P1 stars, with an estimated mean difference of Delta Y = 0.05, but the P2
stars exhibit a significant spread in He content and some may reach Delta Y =
0.13. A smaller He spread may be present also for the P1 stars. Additionally,
stars with spectroscopically determined low [Mg/Fe] ratios ([Mg/Fe]<0) are
generally associated with P2. We find the P2 stars to be slightly more
centrally concentrated in NGC 2419 with a projected half-number radius of about
10% less than for the P1 stars, but the difference is not highly significant
(p=0.05). We find evidence of rotation for the P1 stars, whereas the results
are inconclusive for the P2 stars, which are consistent with no rotation as
well as the same average rotation found for the P1 stars. Because of the long
relaxation time scale of NGC 2419, the radial trends and kinematic properties
of the populations are expected to be relatively unaffected by dynamical
evolution. Hence, they provide constraints on formation scenarios for multiple
populations, which must account not only for the presence of He spreads within
sub-populations identified via CNO variations, but also for the relatively
modest differences in the spatial distributions and kinematics of the
populations.
| arxiv topic:astro-ph.SR astro-ph.GA |
arxiv_dataset-108261902.01516 | A Model for Phased Array Feed
astro-ph.IM
In this report we present a model for phased array feed (PAF) and compare the
model predictions with measurements. A theory for loss-less PAF is presented
first. To develop the theory we ask the question -- what is the best
$T_{sys}/\eta_{ap}$ that can be achieved when a PAF is used on a telescope to
observe a source at an angle $\theta_s, \phi_s$ from the boresight direction ?
We show that a characteristic matrix for the {\em system} (i.e.
PAF+telescope+receiver) can be constructed starting from the signal-to-noise
ratio of the observations and the best $T_{sys}/\eta_{ap}$ can be obtained from
the maximum eigenvalue of the characteristic matrix. For constructing the
characteristic matrix, we derive the open-circuit voltage at the output of the
antenna elements in the PAF due to (a) radiation from source, (b) radiation
from ground (spillover), (c) radiation from sky background and (d) noise due to
the receiver. The characteristic matrix is then obtained from the correlation
matrices of these voltages. We then describe a modeling program developed to
implement the theory presented here. Finally the model predictions are compared
with results from test observations made toward Virgo A with a prototype PAF
(Kite array) on the GBT (Roshi et al. 2015).
| arxiv topic:astro-ph.IM |
arxiv_dataset-108271902.01616 | TDHF Theory and Its Extensions for the Multinucleon Transfer Reaction: a
Mini Review
nucl-th nucl-ex
Time-dependent Hartree-Fock (TDHF) theory has been a powerful tool in
describing a variety of complex nuclear dynamics microscopically without
empirical parameters. In this contribution, recent advances in nuclear dynamics
studies with TDHF and its extensions are briefly reviewed, along the line with
the study of multinucleon transfer (MNT) reactions. The latter lies at the core
of this Research Topic, whose application for production of extremely
neutron-rich nuclei has been extensively discussed in recent years. Having in
mind the ongoing theoretical developments, it is envisaged how microscopic
theories may contribute to the future MNT study.
| arxiv topic:nucl-th nucl-ex |
arxiv_dataset-108281902.01716 | Multirevolution integrators for differential equations with fast
stochastic oscillations
math.NA cs.NA
We introduce a new methodology based on the multirevolution idea for
constructing integrators for stochastic differential equations in the situation
where the fast oscillations themselves are driven by a Stratonovich noise.
Applications include in particular highly-oscillatory Kubo oscillators and
spatial discretizations of the nonlinear Schr\"odinger equation with fast white
noise dispersion. We construct a method of weak order two with computational
cost and accuracy both independent of the stiffness of the oscillations. A
geometric modification that conserves exactly quadratic invariants is also
presented.
| arxiv topic:math.NA cs.NA |
arxiv_dataset-108291902.01816 | Conformal wave equations for the Einstein-tracefree matter system
gr-qc math-ph math.MP
Inspired by a similar analysis for the vacuum conformal Einstein field
equations by Paetz [Ann. H. Poincar\'e 16, 2059 (2015)], in this article we
show how to construct a system of quasilinear wave equations for the geometric
fields associated to the conformal Einstein field equations coupled to matter
models whose energy-momentum tensor has vanishing trace. In this case, the
equation of conservation for the energy-momentum tensor is conformally
invariant. Our analysis includes the construction of a subsidiary evolution
system which allows to prove the propagation of the constraints. We discuss how
the underlying structure behind these systems of equations is the integrability
conditions satisfied by the conformal field equations. The main result of our
analysis is that both the evolution and subsidiary equations for the geometric
part of the conformal Einstein-tracefree matter field equations close without
the need of any further assumption on the matter models other than the
vanishing of the trace of the energy-momentum tensor. Our work is supplemented
by an analysis of the evolution and subsidiary equations associated to three
basic tracefree matter models: the conformally invariant scalar field, the
Maxwell field and the Yang-Mills field. As an application we provide a global
existence and stability result for de Sitter-like spacetimes. In particular,
the result for the conformally coupled scalar field is new in the literature.
| arxiv topic:gr-qc math-ph math.MP |
arxiv_dataset-108301902.01916 | The Fuglede conjecture holds in $\mathbb{Z}^3_5$
math.CA math.CO math.NT
The Fuglede conjecture states that a set is spectral if and only if it tiles
by translation. The conjecture was disproved by T. Tao for dimensions 5 and
higher by giving a counterexample in $\mathbb{Z}_3^5$. We present a computer
program that determines that the Fuglede conjecture holds in $\mathbb{Z}_5^3$
by exhausting the search space. A. Iosevich, A. Mayeli and J. Pakianathan
showed that the Fuglede conjecture holds over prime fields when the dimension
does not exceed 2. The question for dimension 3 was previously addressed by
Aten et al. for $p=3$. In this paper we build upon the results of their work to
allow a computer to carry out the lengthy computations.
| arxiv topic:math.CA math.CO math.NT |
arxiv_dataset-108311902.02016 | Restriction enzymes use a 24 dimensional coding space to recognize 6
base long DNA sequences
q-bio.QM cs.IT math.IT
Restriction enzymes recognize and bind to specific sequences on invading
bacteriophage DNA. Like a key in a lock, these proteins require many contacts
to specify the correct DNA sequence. Using information theory we develop an
equation that defines the number of independent contacts, which is the
dimensionality of the binding. We show that EcoRI, which binds to the sequence
GAATTC, functions in 24 dimensions. Information theory represents messages as
spheres in high dimensional spaces. Better sphere packing leads to better
communications systems. The densest known packing of hyperspheres occurs on the
Leech lattice in 24 dimensions. We suggest that the single protein EcoRI
molecule employs a Leech lattice in its operation. Optimizing density of sphere
packing explains why 6 base restriction enzymes are so common.
| arxiv topic:q-bio.QM cs.IT math.IT |
arxiv_dataset-108321902.02116 | Accelerating spin-space sampling by auxiliary spin-dynamics and
temperature-dependent spin-cluster expansion
cond-mat.stat-mech physics.comp-ph
Atomistic simulations of thermodynamic properties of magnetic materials rely
on an accurate modelling of magnetic interactions and an efficient sampling of
the high-dimensional spin space. Recent years have seen significant progress
with a clear trend from model systems to material specific simulations that are
usually based on electronic-structure methods. Here we develop a Hamiltonian
Monte Carlo framework that makes use of auxiliary spin-dynamics and an
auxiliary effective model, the temperature-dependent spin-cluster expansion, in
order to efficiently sample the spin space. Our method does not require a
specific form of the model and is suitable for simulations based on
electronic-structure methods. We demonstrate fast warm-up and a reasonably
small dynamical critical exponent of our sampler for the classical Heisenberg
model. We further present an application of our method to the magnetic phase
transition in bcc iron using magnetic bond-order potentials.
| arxiv topic:cond-mat.stat-mech physics.comp-ph |
arxiv_dataset-108331902.02216 | On Integrability and Exact Solvability in Deterministic and Stochastic
Laplacian Growth
math-ph cond-mat.stat-mech math.MP math.PR nlin.PS nlin.SI
We review applications of theory of classical and quantum integrable systems
to the free-boundary problems of fluid mechanics as well as to corresponding
problems of statistical mechanics. We also review important exact results
obtained in the theory of multi-fractal spectra of the stochastic models
related to the Laplacian growth: Schramm-Loewner and Levy-Loewner evolutions.
| arxiv topic:math-ph cond-mat.stat-mech math.MP math.PR nlin.PS nlin.SI |
arxiv_dataset-108341902.02316 | A low-order nonconforming method for linear elasticity on general meshes
math.NA
In this work we construct a low-order nonconforming approximation method for
linear elasticity problems supporting general meshes and valid in two and three
space dimensions. The method is obtained by hacking the Hybrid High-Order
method, that requires the use of polynomials of degree $k\ge1$ for stability.
Specifically, we show that coercivity can be recovered for $k=0$ by introducing
a novel term that penalises the jumps of the displacement reconstruction across
mesh faces. This term plays a key role in the fulfillment of a discrete Korn
inequality on broken polynomial spaces, for which a novel proof valid for
general polyhedral meshes is provided. Locking-free error estimates are derived
for both the energy- and the $L^2$-norms of the error, that are shown to
convergence, for smooth solutions, as $h$ and $h^2$, respectively (here, $h$
denotes the meshsize). A thorough numerical validation on a complete panel of
two- and three-dimensional test cases is provided.
| arxiv topic:math.NA |
arxiv_dataset-108351902.02416 | Fast Hyperparameter Tuning using Bayesian Optimization with Directional
Derivatives
cs.LG stat.ML
In this paper we develop a Bayesian optimization based hyperparameter tuning
framework inspired by statistical learning theory for classifiers. We utilize
two key facts from PAC learning theory; the generalization bound will be higher
for a small subset of data compared to the whole, and the highest accuracy for
a small subset of data can be achieved with a simple model. We initially tune
the hyperparameters on a small subset of training data using Bayesian
optimization. While tuning the hyperparameters on the whole training data, we
leverage the insights from the learning theory to seek more complex models. We
realize this by using directional derivative signs strategically placed in the
hyperparameter search space to seek a more complex model than the one obtained
with small data. We demonstrate the performance of our method on the tasks of
tuning the hyperparameters of several machine learning algorithms.
| arxiv topic:cs.LG stat.ML |
arxiv_dataset-108361902.02516 | ILD MC production for detector optimization
physics.ins-det
A large scale Monte Carlo production has been pursued since spring 2018 for
the ILD detector optimization studies based on physics benchmark processes. A
production system based on ILCDirac has been developed to produce samples in
timely manner. The system and its performance are presented.
| arxiv topic:physics.ins-det |
arxiv_dataset-108371902.02616 | Schauder estimates for drifted fractional operators in the supercritical
case
math.AP math.PR
We consider a non-local operator $L_{{ \alpha}}$ which is the sum of a
fractional Laplacian $\triangle^{\alpha/2} $, $\alpha \in (0,1)$, plus a first
order term which is measurable in the time variable and locally
$\beta$-H\"older continuous in the space variables. Importantly, the fractional
Laplacian $\Delta^{ \alpha/2} $ does not dominate the first order term. We show
that global parabolic Schauder estimates hold even in this case under the
natural condition $\alpha + \beta >1$. Thus, the constant appearing in the
Schauder estimates is in fact independent of the $L^{\infty}$-norm of the first
order term. In our approach we do not use the so-called extension property and
we can replace $\triangle^{\alpha/2} $ with other operators of $\alpha$-stable
type which are somehow close, including the relativistic $\alpha$-stable
operator. Moreover, when $\alpha \in (1/2,1)$, we can prove Schauder estimates
for more general $\alpha$-stable type operators like the singular cylindrical
one, i.e., when $\triangle^{\alpha/2} $ is replaced by a sum of one dimensional
fractional Laplacians $\sum_{k=1}^d (\partial_{x_k x_k}^2 )^{\alpha/2}$.
| arxiv topic:math.AP math.PR |
arxiv_dataset-108381902.02716 | Cluster realizations of Weyl groups and higher Teichm\"uller theory
math.RT math.AG math.GT
For a symmetrizable Kac-Moody Lie algebra $\mathfrak{g}$, we construct a
family of weighted quivers $Q_m(\mathfrak{g})$ ($m \geq 2$) whose cluster
modular group $\Gamma_{Q_m(\mathfrak{g})}$ contains the Weyl group
$W(\mathfrak{g})$ as a subgroup. We compute explicit formulae for the
corresponding cluster $\mathcal{A}$- and $\mathcal{X}$-transformations. As a
result, we obtain green sequences and the cluster Donaldson-Thomas
transformation for $Q_m(\mathfrak{g})$ in a systematic way when $\mathfrak{g}$
is of finite type. Moreover if $\mathfrak{g}$ is of classical finite type with
the Coxeter number $h$, the quiver $Q_{kh}(\mathfrak{g})$ ($k \geq 1$) is
mutation-equivalent to a quiver encoding the cluster structure of the higher
Teichm\"uller space of a once-punctured disk with $2k$ marked points on the
boundary, up to frozen vertices. This correspondence induces the action of
direct products of Weyl groups on the higher Teichm\"uller space of a general
marked surface. We finally prove that this action coincides with the one
constructed in [GS18] from the geometrical viewpoint.
| arxiv topic:math.RT math.AG math.GT |
arxiv_dataset-108391902.02816 | Revec: Program Rejuvenation through Revectorization
cs.PL cs.PF
Modern microprocessors are equipped with Single Instruction Multiple Data
(SIMD) or vector instructions which expose data level parallelism at a fine
granularity. Programmers exploit this parallelism by using low-level vector
intrinsics in their code. However, once programs are written using vector
intrinsics of a specific instruction set, the code becomes non-portable. Modern
compilers are unable to analyze and retarget the code to newer vector
instruction sets. Hence, programmers have to manually rewrite the same code
using vector intrinsics of a newer generation to exploit higher data widths and
capabilities of new instruction sets. This process is tedious, error-prone and
requires maintaining multiple code bases. We propose Revec, a compiler
optimization pass which revectorizes already vectorized code, by retargeting it
to use vector instructions of newer generations. The transformation is
transparent, happening at the compiler intermediate representation level, and
enables performance portability of hand-vectorized code.
Revec can achieve performance improvements in real-world performance critical
kernels. In particular, Revec achieves geometric mean speedups of 1.160$\times$
and 1.430$\times$ on fast integer unpacking kernels, and speedups of
1.145$\times$ and 1.195$\times$ on hand-vectorized x265 media codec kernels
when retargeting their SSE-series implementations to use AVX2 and AVX-512
vector instructions respectively. We also extensively test Revec's impact on
216 intrinsic-rich implementations of image processing and stencil kernels
relative to hand-retargeting.
| arxiv topic:cs.PL cs.PF |
arxiv_dataset-108401902.02916 | Complete Glauber calculations for proton-nucleus inelastic cross
sections
nucl-th
We perform a parameter-free calculation for the high-energy proton-nucleus
scattering based on the Glauber theory. A complete evaluation of the so-called
Glauber amplitude is made by using the factorization of the single-particle
wave functions. The multiple-scattering or multistep processes are fully taken
into account within the Glauber theory. We demonstrate that proton- $^{12}$C,
$^{20}$Ne, and $^{28}$Si elastic and inelastic scattering ($J^\pi=0^+ \to 2^+$
and $0^+ \to 4^+$) processes are very well described in a wide range of the
incident energies from $\sim$50 MeV to $\sim$ 1 GeV. We evaluate the validity
of a simple one-step approximation andfind that the approximation works fairly
well for the inelastic $0^+ \to 2^+$ processes but not for $0^+ \to 4^+$ where
the multistep processes become more important. As an application, we quantify
the difference between the total reaction and interaction cross sections of
proton-$^{12}$C, $^{20}$Ne, and $^{28}$Si collisions.
| arxiv topic:nucl-th |
arxiv_dataset-108411902.03016 | Spatial eco-evolutionary feedbacks mediate coexistence in prey-predator
systems
q-bio.PE cond-mat.stat-mech nlin.AO
Eco-evolutionary frameworks can explain certain features of communities in
which ecological and evolutionary processes occur over comparable timescales.
Here, we investigate whether an evolutionary dynamics may interact with the
spatial structure of a prey-predator community in which both species show
limited mobility and predator perceptual ranges are subject to natural
selection. In these conditions, our results unveil an eco-evolutionary feedback
between species spatial mixing and predators perceptual range: different levels
of mixing select for different perceptual ranges, which in turn reshape the
spatial distribution of prey and its interaction with predators. This emergent
pattern of interspecific interactions feeds back to the efficiency of the
various perceptual ranges, thus selecting for new ones. Finally, since
prey-predator mixing is the key factor that regulates the intensity of
predation, we explore the community-level implications of such feedback and
show that it controls both coexistence times and species extinction
probabilities.
| arxiv topic:q-bio.PE cond-mat.stat-mech nlin.AO |
arxiv_dataset-108421902.03116 | Learning Gaussian Graphical Models by symmetric parallel regression
technique
stat.ME
In this contribution we deal with the problem of learning an undirected graph
which encodes the conditional dependence relationship between variables of a
complex system, given a set of observations of this system. This is a very
central problem of modern data analysis and it comes out every time we want to
investigate a deeper relationship between random variables, which is different
from the classical dependence usually measured by the covariance.
In particular, in this contribution we deal with the case of Gaussian
Graphical Models (GGMs) for which the system of variables has a multivariate
gaussian distribution. We study all the existing techniques for such a problem
and propose a smart implementation of the symmetric parallel regression
technique which turns out to be very competitive for learning sparse GGMs under
high dimensional data regime.
| arxiv topic:stat.ME |
arxiv_dataset-108431902.03216 | Intervention Pathway Discovery via Context-Dependent Dynamic Sensitivity
Analysis
q-bio.MN q-bio.QM
The sensitivity analysis of biological system models can significantly
contribute to identifying and explaining influences of internal or external
changes on model and its elements. We propose here a comprehensive framework to
study sensitivity of intra-cellular networks and to identify key intervention
pathways, by performing both static and dynamic sensitivity analysis. While the
static sensitivity analysis focuses on the impact of network topology and
update functions, the dynamic analysis accounts for context-dependent transient
state distributions. To study sensitivity, we use discrete models, where each
element is represented as a discrete variable and assigned an update rule,
which is a function of element's known direct and indirect regulators. Our
sensitivity analysis framework allows for assessing the effect of context on
individual element sensitivity, as well as on element criticality in reaching
preferred outcomes. The framework also enables discovery of most influential
pathways in the model that are essential for satisfying important system
properties, and thus, could be used for interventions. We discuss the role of
nine different network attributes in identifying key elements and intervention
pathways, and evaluate their performance using model checking method. Finally,
we apply our methods on the model of naive T cell differentiation, and further
demonstrate the importance of context-based sensitivity analysis in identifying
most influential elements and pathways.
| arxiv topic:q-bio.MN q-bio.QM |
arxiv_dataset-108441902.03316 | Bayesian Model Selection with Graph Structured Sparsity
stat.ME stat.CO
We propose a general algorithmic framework for Bayesian model selection. A
spike-and-slab Laplacian prior is introduced to model the underlying structural
assumption. Using the notion of effective resistance, we derive an EM-type
algorithm with closed-form iterations to efficiently explore possible
candidates for Bayesian model selection. The deterministic nature of the
proposed algorithm makes it more scalable to large-scale and high-dimensional
data sets compared with existing stochastic search algorithms. When applied to
sparse linear regression, our framework recovers the EMVS algorithm [Rockova
and George, 2014] as a special case. We also discuss extensions of our
framework using tools from graph algebra to incorporate complex Bayesian models
such as biclustering and submatrix localization. Extensive simulation studies
and real data applications are conducted to demonstrate the superior
performance of our methods over its frequentist competitors such as $\ell_0$ or
$\ell_1$ penalization.
| arxiv topic:stat.ME stat.CO |
arxiv_dataset-108451902.03416 | A Comparative Study of 2017 July and 2012 July Complex Eruptions: Are
Solar Superstorms "Perfect Storms" in Nature?
astro-ph.SR physics.space-ph
It is paramount from both scientific and societal perspectives to understand
the generation of extreme space weather. We discuss the formation of solar
superstorms based on a comparative study of the 2012 July 23 and 2017 July 23
eruptions. The first one is Carrington-class, and the second could rival the
1989 March event that caused the most intense geomagnetic storm of the space
age. Observations of these events in the historically weak solar cycle 24
indicate that a solar superstorm can occur in any solar cycle and at any phase
of the cycle. Recurrent patterns are identified in both cases, including the
long-lived eruptive nature of the active region, a complex event composed of
successive eruptions from the same active region, and in-transit interaction
between the successive eruptions resulting in exceptionally strong ejecta
magnetic fields at 1 AU. Each case also shows unique characteristics.
Preconditioning of the upstream solar wind leading to unusually high solar wind
speeds at 1 AU is observed in the first case whereas not in the latter. This
may suggest that the concept of "preconditioning" appears to be necessary for
making a Carrington-class storm. We find a considerable deflection by nearby
coronal holes in the second case but not in the first. On the basis of these
results, we propose a hypothesis for further investigation that superstorms are
"perfect storms" in nature, i.e., a combination of circumstances that results
in an event of unusual magnitude. Historical records of some extreme events
seem to support our hypothesis.
| arxiv topic:astro-ph.SR physics.space-ph |
arxiv_dataset-108461902.03516 | Skew-Polynomial Rings and Skew-Cyclic Codes
cs.IT math.IT math.RA
This is a survey on the theory of skew-cyclic codes based on skew-polynomial
rings of automorphism type. Skew-polynomial rings have been introduced and
discussed by Ore (1933). Evaluation of skew polynomials and sets of (right)
roots were first considered by Lam (1986) and studied in great detail by Lam
and Leroy thereafter. After a detailed presentation of the most relevant
properties of skew polynomials, we survey the algebraic theory of skew-cyclic
codes as introduced by Boucher and Ulmer (2007) and studied by many authors
thereafter. A crucial role will be played by skew-circulant matrices. Finally,
skew-cyclic codes with designed minimum distance are discussed, and we report
on two different kinds of skew-BCH codes, which were designed in 2014 and
later.
| arxiv topic:cs.IT math.IT math.RA |
arxiv_dataset-108471902.03616 | ELKI: A large open-source library for data analysis - ELKI Release 0.7.5
"Heidelberg"
cs.LG stat.ML
This paper documents the release of the ELKI data mining framework, version
0.7.5.
ELKI is an open source (AGPLv3) data mining software written in Java. The
focus of ELKI is research in algorithms, with an emphasis on unsupervised
methods in cluster analysis and outlier detection. In order to achieve high
performance and scalability, ELKI offers data index structures such as the
R*-tree that can provide major performance gains. ELKI is designed to be easy
to extend for researchers and students in this domain, and welcomes
contributions of additional methods. ELKI aims at providing a large collection
of highly parameterizable algorithms, in order to allow easy and fair
evaluation and benchmarking of algorithms.
We will first outline the motivation for this release, the plans for the
future, and then give a brief overview over the new functionality in this
version. We also include an appendix presenting an overview on the overall
implemented functionality.
| arxiv topic:cs.LG stat.ML |
arxiv_dataset-108481902.03716 | Braiding of Majorana corner states in electric circuits and its
non-Hermitian generalization
cond-mat.supr-con cond-mat.mes-hall physics.app-ph
We propose to realize Majorana edge and corner states in electric circuits.
First, we simulate the Kitaev model by an LC electric circuit and the
$p_{x}+ip_{y}$ model by an LC circuit together with operational amplifiers.
Zero-energy edge states emerge in the topological phase, which are detectable
by measuring impedance. Next, we simulate the Bernevig-Hughes-Zhang model by
including an effective magnetic field without breaking the particle-hole
symmetry, where zero-energy corner states emerge in the topological phase. It
is demonstrated that they are Ising anyons subject to the braiding. Namely we
derive $\sigma ^{2}=-1$ for them, where $\sigma $ denotes the single-exchange
operation. They may well be called Majorana states. We also study non-Hermitian
generalizations of these models by requiring the particle-hole symmetry. It is
shown that the braiding holds in certain reciprocal non-Hermitian
generalizations.
| arxiv topic:cond-mat.supr-con cond-mat.mes-hall physics.app-ph |
arxiv_dataset-108491902.03816 | Convergence properties of detonation simulations
physics.flu-dyn physics.comp-ph
We present a high-resolution convergence study of detonation initiated by a
temperature gradient in a stoichiometric hydrogen-oxygen mixture using the
Pencil Code and compare with a code that employs a fifth order weighted
essentially non-oscillating (WENO) scheme. With Mach numbers reaching 10-30, a
certain amount of shock viscosity is needed in the Pencil Code to remove or
reduce numerical pressure oscillations on the grid scale at the position of the
shock. Detonation is found to occur for intermediate values of the shock
viscosity parameter. At fixed values of this parameter, the numerical error
associated with those small wiggles in the pressure profile is found to
decrease with decreasing mesh width $\delta x$ like $\delta x^{-1.4}$ down to
$\delta x=0.2\mu$m. With the WENO scheme, solutions are smooth at $\delta
x=10\mu$m, but no detonation is obtained for $\delta x=5\mu$m. This is argued
to be an artifact of a decoupling between pressure and reaction fronts.
| arxiv topic:physics.flu-dyn physics.comp-ph |
arxiv_dataset-108501902.03916 | Homogeneous and Mixed Energy Communities Discovery with Spatial-Temporal
Net Energy
cs.SY
Smart grid has integrated an increasing number of distributed energy
resources to improve the efficiency and flexibility of power generation and
consumption as well as the resilience of the power grid. The energy consumers
on the power grid (e.g., households) equipped with the distributed energy
resources can be considered as "microgrids" that both generate and consume
electricity. In this paper, we study the energy community discovery problems
which identify multiple kinds of energy communities for the microgrids to
facilitate energy management (e.g., power supply adjustment, load balancing,
energy sharing) on the grid, such as homogeneous energy communities (HECs),
mixed energy communities (MECs), and self-sufficient energy communities (SECs).
Specifically, we present efficient algorithms to discover such communities of
microgrids by taking into account not only their geo-locations but also their
net energy over any period. Finally, we experimentally validate the performance
of the algorithms using both synthetic and real datasets.
| arxiv topic:cs.SY |
arxiv_dataset-108511902.04016 | The two-dimensional analogue of the Lorentzian catenary and the
Dirichlet problem
math.DG
In this paper we generalize in Lorentz-Minkowski space $\l^3$ the
two-dimensional analogue of the catenary of Euclidean space. We solve the
Dirichlet problem for bounded mean convex domains and spacelike boundary data
that have a spacelike extension to the domain. We also classify all singular
maximal surfaces of $\l^3$ invariant by a uniparametric group of translations
and rotations.
| arxiv topic:math.DG |
arxiv_dataset-108521902.04116 | Gaia-2MASS 3D maps of Galactic interstellar dust within 3 kpc
astro-ph.GA
Gaia data are revolutionizing our knowledge of the evolutionary history of
the Milky Way. 3D maps of the interstellar dust provide complementary
information and are a tool for a wide range of uses. We aimed at building 3D
maps of the dust in the Local arm and surrounding regions. To do so, Gaia DR2
photometric data were combined with 2MASS measurements to derive extinction
towards stars that possess accurate photometry and relative uncertainties on
DR2 parallaxes smaller than 20\%. We applied to the extinctions a new
hierarchical inversion algorithm adapted to large datasets and to a
inhomogeneous target distribution. Each step associates regularized Bayesian
inversions along radial directions and a subsequent inversion in 3D of their
results. Each inverted distribution serves as a prior for the subsequent step
and the spatial resolution is progressively increased. We present the resulting
3D distribution of the dust in a 6 x 6 x 0.8 kpc3 volume around the Sun. Its
main features are found to be elongated along different directions that vary
from below to above the mid-plane: the outer part of Carina-Sagittarius, mainly
located above the mid-plane, the Local arm/Cygnus Rift around and above the
mid-plane and the fragmented Perseus arm are oriented close to the direction of
circular motion. The long spur (nicknamed the split) that extends between the
Local Arm and Carina-Sagittarius, the compact near side of Carina-Sagittarius
and the Cygnus Rift below the Plane are oriented along l=40 to 55 deg. Dust
density images in vertical planes reveal in some regions a wavy pattern and
show that the solar neighborhood within 500 pc remains atypical by its extent
above and below the Plane. We show several comparisons with the locations of
molecular clouds, HII regions, O stars and masers. The link between the dust
concentration and these tracers is markedly different from one region to the
other.
| arxiv topic:astro-ph.GA |
arxiv_dataset-108531902.04216 | Emission of photon pairs by mechanical stimulation of the squeezed
vacuum
quant-ph
To observe the dynamical Casimir effect (DCE) induced by a moving mirror is a
long-standing challenge because the mirror velocity needs to approach the speed
of light. Here, we present an experimentally feasible method for observing this
mechanical DCE in an optomechanical system. It employs a detuned, parametric
driving to squeeze a cavity mode, so that the mechanical mode, with a typical
resonance frequency, can parametrically and resonantly couple to the squeezed
cavity mode, thus leading to a resonantly amplified DCE in the squeezed frame.
The DCE process can be interpreted as {\it mechanically-induced two-photon
hyper-Raman scattering} in the laboratory frame. Specifically, {\it a photon
pair} of the parametric driving absorbs a single phonon and then is scattered
into an anti-Stokes sideband. We also find that the squeezing, which
additionally induces and amplifies the DCE, can be extremely small. Our method
requires neither an ultra-high mechanical-oscillation frequency (i.e., a mirror
moving at nearly the speed of light) nor an ultrastrong single-photon
optomechanical coupling and, thus, could be implemented in a wide range of
physical systems.
| arxiv topic:quant-ph |
arxiv_dataset-108541902.04316 | Novel mechanisms to enhance the capacitance beyond the classical limits
in capacitors with free-electron-like electrodes
cond-mat.mes-hall cond-mat.mtrl-sci
The so-called negative electron compressibility refers to the lowering of the
chemical potential of a metallic system when the carrier density increases.
This effect has often been invoked in the past to explain the enhancement of
the capacitance beyond the classical limits in capacitors with two-dimensional
electron gases as electrodes. Based on experiments on strongly confined
semiconductor quantum wells (QWs), it has been traditionally ascribed to the
electron exchange energy as the main driving force. Recent research, however,
has revealed that analogous effects can occur in other classes of materials
systems, such as polar oxide interfaces, whose characteristics drastically
depart from those of the previously considered cases. To rationalize these new
results, it is necessary to revisit the established theory of confined electron
gases, and test whether its conclusions are valid beyond the specifics of
semiconductor-based QWs. Here we find, based on first-principles calculations
of jellium slabs, that one must indeed be very careful when extrapolating
existing results to other realistic physical systems. In particular, we
identify a number of additional, previously overlooked mechanisms (e.g.,
related to the displacement of the electronic cloud and to the multiband
structure of the delocalized gas), that enter into play and become new sources
of negative capacitance in the weak-confinement regime. Our detailed analysis
of these emerging contributions, supported by analytic models and multiple test
cases, will provide a useful guidance in the ongoing quest for nanometric
capacitors with enhanced performance.
| arxiv topic:cond-mat.mes-hall cond-mat.mtrl-sci |
arxiv_dataset-108551902.04416 | Examining Adversarial Learning against Graph-based IoT Malware Detection
Systems
cs.CR cs.AI
The main goal of this study is to investigate the robustness of graph-based
Deep Learning (DL) models used for Internet of Things (IoT) malware
classification against Adversarial Learning (AL). We designed two approaches to
craft adversarial IoT software, including Off-the-Shelf Adversarial Attack
(OSAA) methods, using six different AL attack approaches, and Graph Embedding
and Augmentation (GEA). The GEA approach aims to preserve the functionality and
practicality of the generated adversarial sample through a careful embedding of
a benign sample to a malicious one. Our evaluations demonstrate that OSAAs are
able to achieve a misclassification rate (MR) of 100%. Moreover, we observed
that the GEA approach is able to misclassify all IoT malware samples as benign.
| arxiv topic:cs.CR cs.AI |
arxiv_dataset-108561902.04516 | Lower bounds on the dimension of the Rauzy gasket
math.DS
The Rauzy gasket $R$ is the maximal invariant set of a certain
renormalization procedure for special systems of isometries naturally appearing
in the context of Novikov's problem in conductivity theory for monocrystals. It
was conjectured by Novikov and Maltsev in 2003 that the Hausdorff dimension
$\dim_{\mathrm{H}}(R)$ of Rauzy gasket is strictly comprised between $1$ and
$2$. In 2016, Avila, Hubert and Skripchenko confirmed that
$\dim_{\mathrm{H}}(R)<2$. In this note, we use some results by Cao--Pesin--Zhao
in order to show that $\dim_{\mathrm{H}}(R)>1.19$.
| arxiv topic:math.DS |
arxiv_dataset-108571902.04616 | The impact of the crust equation of state on the analysis of GW170817
gr-qc
The detection of GW170817, the first neutron star-neutron star merger
observed by Advanced LIGO and Virgo, and its following analyses represent the
first contributions of gravitational wave (GW) data to understanding dense
matter. Parameterizing the high density section of the equation of state (EOS)
of both neutron stars through spectral decomposition, and imposing a lower
limit on the maximum mass value, led to an estimate of the stars' radii of $R_1
= 11.9_{- 1.4}^{+ 1.4}$ km and $R_2 = 11.9_{- 1.4}^{+ 1.4}$ km. These values do
not, however, take into account any uncertainty owed to the choice of the crust
low-density EOS, which was fixed to reproduce the SLy EOS model. We here
re-analyze GW170817 data and establish that different crust models do not
strongly impact the mass or tidal deformability of a neutron star: it is
impossible to distinguish between low-density models with GW analysis. However,
the crust does have an effect on the inferred radius. We predict the systematic
error due to this effect using neutron star structure equations, and compare
the prediction to results from full parameter estimation runs. For GW170817,
this systematic error affects the radius estimate by 0.3 km, approximately
$3\%$ of the NS radii.
| arxiv topic:gr-qc |
arxiv_dataset-108581902.04716 | Coherent Transition Radiation from Relativistic Beam-Foil Interaction in
the Terahertz and Optical Range
physics.plasm-ph
Coherent transition radiation (CTR) from relativistic electron beam
interaction with an overdense plasma foil is investigated by making use of
two-dimensional particle-in-cell simulations. Well-defined single electron beam
either of uniform profile or having substructures is considered for various
beam-plasma parameters. The main purpose is to mimic the complicated
beam-plasma conditions that is often found, for example, in intense laser
plasma interactions. Key properties of the CTR concerning their temporal,
angular and spectral profiles are identified. Several saturation effects due to
the beam energy, size and foil density are found for the CTR energy, and the
dependences vary for different spectral components such as in the Terahertz
(THz) and optical range. The detailed substructure of the beam also affects
greatly the radiation generation, leading to distinctive high harmonic
components. Electrons with kinetic energy from sub MeV to tens of GeV are
explored. For few MeV electron beams, the effects of the foil plasma on the
beam dynamics and associated CTR generation, resembles closely the CTR from hot
electrons produced in intense laser-plasma interactions. These results may find
important applications in beam diagnostics either in laser-plasma based
acceleration or conventional accelerators. They may also be employed to design
novel THz radiation sources using tunable electron beams.
| arxiv topic:physics.plasm-ph |
arxiv_dataset-108591902.04816 | A Suitable Conjugacy for the l0 Pseudonorm
math.OC
The so-called l0 pseudonorm on R d counts the number of nonzero components of
a vector. It is well-known that the l0 pseudonorm is not convex, as its Fenchel
biconjugate is zero. In this paper, we introduce a suitable conjugacy, induced
by a novel coupling, Caprac, having the property of being constant along primal
rays, like the l0 pseudonorm. The Caprac coupling belongs to the class of
one-sided linear couplings, that we introduce. We show that they induce
conjugacies that share nice properties with the classic Fenchel conjugacy. For
the Caprac conjugacy, induced by the coupling Caprac, we prove that the l0
pseudonorm is equal to its biconjugate: hence, the l0 pseudonorm is
Caprac-convex in the sense of generalized convexity. As a corollary, we show
that the l0 pseudonorm coincides, on the sphere, with a convex lsc function. We
also provide expressions for conjugates in terms of two families of dual norms,
the 2-k-symmetric gauge norms and the k-support norms.
| arxiv topic:math.OC |
arxiv_dataset-108601902.04916 | Two-mediator dark matter models and cosmic electron excess
hep-ph astro-ph.CO astro-ph.HE
The cosmic electron energy spectrum recently observed by the DAMPE experiment
exhibits two interesting features, including a break around 0.9 TeV and a sharp
resonance near 1.4 TeV. In this analysis, we propose a dark matter explanation
to both exotic features seen by DAMPE. In our model, dark matter annihilates in
the galaxy via two different channels that lead to both a narrow resonance
spectrum near 1.4 TeV and electron excess events over an extended energy range
thus generating the break structure around TeV. The two annihilation channels
are mediated by two gauge bosons that interact both with dark matter and with
the standard model fermions. Dark matter annihilations through the s-channel
process mediated by the heavier boson produce monoenergetic electron-positron
pairs leading to the resonance excess. The lighter boson has a mass smaller
than the dark matter such that they can be on-shell produced in dark matter
annihilations in the galaxy; the lighter bosons in the final state subsequently
decay to generate the extended excess events due to the smeared electron energy
spectrum in this process. We further analyze constraints from various
experiments, including HESS, Fermi, AMS, and LHC, to the parameter space of the
model where both excess events can be accounted for. In order to interpret the
two new features in the DAMPE data, dark matter annihilation cross sections in
the current galaxy are typically much larger than the canonical thermal cross
section needed for the correct dark matter relic abundance. This discrepancy,
however, is remedied by the nonperturbative Sommerfeld enhancement because of
the existence of a lighter mediator in the model.
| arxiv topic:hep-ph astro-ph.CO astro-ph.HE |
arxiv_dataset-108611902.05016 | On the number of zeros of functions in analytic quasianalytic classes
math.CA math.CV
A space of analytic functions in the unit disc with uniformly continuous
derivatives is said to be quasianalytic if the boundary value of a non-zero
function from the class can not have a zero of infinite multiplicity. Such
classes were described in the 1950-s and 1960-s by Carleson, Rodrigues-Salinas
and Korenblum. A non-zero function from a quasianalytic space of analytic
functions can only have a finite number of zeros in the closed disc. Recently,
Borichev, Frank, and Volberg proved an explicit estimate on the number of
zeros, for the case of quasianalytic Gevrey classes. Here, an estimate of
similar form for general analytic quasianalytic classes is proved using a
reduction to the classical quasianalyticity problem.
| arxiv topic:math.CA math.CV |
arxiv_dataset-108621902.05116 | Probabilistic Neural Architecture Search
stat.ML cs.LG
In neural architecture search (NAS), the space of neural network
architectures is automatically explored to maximize predictive accuracy for a
given task. Despite the success of recent approaches, most existing methods
cannot be directly applied to large scale problems because of their prohibitive
computational complexity or high memory usage. In this work, we propose a
Probabilistic approach to neural ARchitecture SEarCh (PARSEC) that drastically
reduces memory requirements while maintaining state-of-the-art computational
complexity, making it possible to directly search over more complex
architectures and larger datasets. Our approach only requires as much memory as
is needed to train a single architecture from our search space. This is due to
a memory-efficient sampling procedure wherein we learn a probability
distribution over high-performing neural network architectures. Importantly,
this framework enables us to transfer the distribution of architectures learnt
on smaller problems to larger ones, further reducing the computational cost. We
showcase the advantages of our approach in applications to CIFAR-10 and
ImageNet, where our approach outperforms methods with double its computational
cost and matches the performance of methods with costs that are three orders of
magnitude larger.
| arxiv topic:stat.ML cs.LG |
arxiv_dataset-108631902.05216 | A Cross-Repository Model for Predicting Popularity in GitHub
cs.SI
Social coding platforms, such as GitHub, can serve as natural laboratories
for studying the diffusion of innovation through tracking the pattern of code
adoption by programmers. This paper focuses on the problem of predicting the
popularity of software repositories over time; our aim is to forecast the time
series of popularity-related events (code forks and watches). In particular, we
are interested in cross-repository patterns-how do events on one repository
affect other repositories? Our proposed LSTM (Long Short-Term Memory) recurrent
neural network integrates events across multiple active repositories,
outperforming a standard ARIMA (Auto-Regressive Integrated Moving Average) time
series prediction based on the single repository. The ability of the LSTM to
leverage cross-repository information gives it a significant edge over standard
time series forecasting.
| arxiv topic:cs.SI |
arxiv_dataset-108641902.05316 | A Novel Just-Noticeable-Difference-based Saliency-Channel Attention
Residual Network for Full-Reference Image Quality Predictions
cs.CV
Recently, due to the strength of deep convolutional neural networks (CNN),
many CNN-based image quality assessment (IQA) models have been studied.
However, previous CNN-based IQA models likely have yet to utilize the
characteristics of the human visual system (HVS) fully for IQA problems when
they simply entrust everything to the CNN, expecting it to learn from a
training dataset. However, in this paper, we propose a novel saliency-channel
attention residual network based on the just-noticeable-difference (JND)
concept for full-reference image quality assessments (FR-IQA). It is referred
to as JND-SalCAR and shows significant improvements in large IQA datasets with
various types of distortion. The proposed JND-SalCAR effectively learns how to
incorporate human psychophysical characteristics, such as visual saliency and
JND, into image quality predictions. In the proposed network, a SalCAR block is
devised so that perceptually important features can be extracted with the help
of saliency-based spatial attention and channel attention schemes. In addition,
a saliency map serves as a guideline for predicting a patch weight map in order
to afford stable training of end-to-end optimization for the JND-SalCAR. To the
best of our knowledge, our work presents the first HVS-inspired trainable
FR-IQA network that considers both visual saliency and the JND characteristics
of the HVS. When the visual saliency map and the JND probability map are
explicitly given as priors, they can be usefully combined to predict IQA scores
rated by humans more precisely, eventually leading to performance improvements
and faster convergence. The experimental results show that the proposed
JND-SalCAR significantly outperforms all recent state-of-the-art FR-IQA methods
on large IQA datasets in terms of the Spearman rank order coefficient (SRCC)
and the Pearson linear correlation coefficient (PLCC).
| arxiv topic:cs.CV |
arxiv_dataset-108651902.05416 | The AtLarge Vision on the Design of Distributed Systems and Ecosystems
cs.DC
High-quality designs of distributed systems and services are essential for
our digital economy and society. Threatening to slow down the stream of working
designs, we identify the mounting pressure of scale and complexity of
\mbox{(eco-)systems}, of ill-defined and wicked problems, and of unclear
processes, methods, and tools. We envision design itself as a core research
topic in distributed systems, to understand and improve the science and
practice of distributed (eco-)system design. Toward this vision, we propose the
AtLarge design framework, accompanied by a set of 8 core design principles. We
also propose 10 key challenges, which we hope the community can address in the
following 5 years. In our experience so far, the proposed framework and
principles are practical, and lead to pragmatic and innovative designs for
large-scale distributed systems.
| arxiv topic:cs.DC |
arxiv_dataset-108661902.05516 | Quantized conductance through a spin-selective atomic point contact
cond-mat.quant-gas cond-mat.mes-hall physics.atom-ph
We implement a microscopic spin filter for cold fermionic atoms in a quantum
point contact (QPC) and create fully spin-polarized currents while retaining
conductance quantization. Key to our scheme is a near-resonant optical tweezer
inducing a large effective Zeeman shift inside the QPC while its local
character limits dissipation. We observe a renormalization of this shift due to
interactions of a few atoms in the QPC. Our work represents the analog of an
actual spintronic device and paves the way to studying the interplay between
spin-splitting and interactions far from equilibrium.
| arxiv topic:cond-mat.quant-gas cond-mat.mes-hall physics.atom-ph |
arxiv_dataset-108671902.05616 | Dualizing Le Cam's method for functional estimation, with applications
to estimating the unseens
math.ST cs.IT math.IT stat.TH
Le Cam's method (or the two-point method) is a commonly used tool for
obtaining statistical lower bound and especially popular for functional
estimation problems. This work aims to explain and give conditions for the
tightness of Le Cam's lower bound in functional estimation from the perspective
of convex duality. Under a variety of settings it is shown that the
maximization problem that searches for the best two-point lower bound, upon
dualizing, becomes a minimization problem that optimizes the bias-variance
tradeoff among a family of estimators.
For estimating linear functionals of a distribution our work strengthens
prior results of Donoho-Liu \cite{DL91} (for quadratic loss) by dropping the
H\"olderian assumption on the modulus of continuity. For exponential families
our results extend those of Juditsky-Nemirovski \cite{JN09} by characterizing
the minimax risk for the quadratic loss under weaker assumptions on the
exponential family.
We also provide an extension to the high-dimensional setting for estimating
separable functionals. Notably, coupled with tools from complex analysis, this
method is particularly effective for characterizing the ``elbow effect'' -- the
phase transition from parametric to nonparametric rates. As the main
application we derive sharp minimax rates in the Distinct elements problem
(given a fraction $p$ of colored balls from an urn containing $d$ balls, the
optimal error of estimating the number of distinct colors is $\tilde
\Theta(d^{-\frac{1}{2}\min\{\frac{p}{1-p},1\}})$) and the Fisher's species
problem (given $n$ iid observations from an unknown distribution, the optimal
prediction error of the number of unseen symbols in the next (unobserved) $r
\cdot n$ observations is $\tilde
\Theta(n^{-\min\{\frac{1}{r+1},\frac{1}{2}\}})$).
| arxiv topic:math.ST cs.IT math.IT stat.TH |
arxiv_dataset-108681902.05716 | Comparison of Splitting methods for Gross-Pitaevskii Equation
math.NA physics.comp-ph
In this paper, we discuss the different splitting approaches to solve the
Gross-Pitaevskii equation numerically. We consider conservative
finite-difference schemes and spectral methods for the spatial discretisation.
Further, we apply implicit or explicit time-integrators and combine such
schemes with different splitting approaches. The numerical solutions are
compared based on the conservation of the $L_2$-norm with the analytical
solutions. The advantages of the splitting methods for large time-domains are
presented in several numerical examples of different solitons applications.
| arxiv topic:math.NA physics.comp-ph |
arxiv_dataset-108691902.05816 | Microstructure and thermal properties of unalloyed tungsten deposited by
Wire + Arc Additive Manufacturing
physics.app-ph
Tungsten is considered as one of the most promising materials for nuclear
fusion reactor chamber applications. Wire + Arc Additive Manufacturing has
already demonstrated the ability to deposit defect-free large-scale tungsten
structures, with considerable deposition rates. In this study, the
microstructure of the as-deposited and heat-treated material has been
characterised; it featured mainly large elongated grains for both conditions.
The heat treatment at 1273 K for 6 hours had a negligible effect on
microstructure and on thermal diffusivity. Furthermore, the linear coefficient
of thermal expansion was in the range of 4.5x10-6 micron m-1 K-1 to 6.8x10-6
micron m-1 K-1; the density of the deposit was as high as 99.4% of the
theoretical tungsten density; the thermal diffusivity and the thermal
conductivity were measured and calculated, respectively, and seen to decrease
considerably in the temperature range between 300 K to 1300 K, for both testing
conditions. These results showed that Wire + Arc Additive Manufacturing can be
considered as a suitable technology for the production of tungsten components
for the nuclear sector.
| arxiv topic:physics.app-ph |
arxiv_dataset-108701902.05916 | Outer functions and divergence in de Branges-Rovnyak spaces
math.CV
In most classical holomorphic function spaces on the unit disk in which the
polynomials are dense, a function $f$ can be approximated in norm by its
dilates $f_r(z):=f(rz)~(r<1)$, in other words, $\lim_{r\to1^-}\|f_r-f\|=0$. We
construct a de Branges-Rovnyak space ${\mathcal H}(b)$ in which the polynomials
are dense, and a function $f\in{\mathcal H}(b)$ such that
$\lim_{r\to1^-}\|f_r\|_{{\mathcal H}(b)}=\infty$. The essential feature of our
construction lies in the fact that $b$ is an outer function.
| arxiv topic:math.CV |
arxiv_dataset-108711902.06016 | Approximate Green's Function Coupled Cluster Method Employing Effective
Dimension Reduction
physics.comp-ph
The Green's function coupled cluster (GFCC) method is a powerful many-body
tool for computing the electronic structure of molecular and periodic systems,
especially when electrons of the system are strongly correlated. However, for
the GFCC to be routinely used in the electronic structure calculations, robust
numerical techniques and approximations must be employed to reduce its high
computational overhead. In our recent studies, we demonstrated that the GFCC
equations can be solved directly in the frequency domain using iterative linear
solvers, which can be easily distributed in a massively parallel environment.
In the present work, we demonstrate a successful application of
model-order-reduction (MOR) techniques in the GFCC framework. Briefly, for a
frequency regime which requires high resolution spectral function, instead of
solving GFCC linear equation of full dimension for every single frequency
point, an efficiently-solvable linear system model of a reduced dimension may
be built upon projecting the original GFCC linear system onto a subspace. From
this reduced order model is obtained a reasonable approximation to the full
dimensional GFCC linear equations in both interpolative and extrapolative
spectral regions. Here, we show that the subspace can be properly constructed
in an iterative manner from the auxiliary vectors of the GFCC linear equations
at some selected frequencies within the spectral region of interest. During the
iterations, the quality of the subspace and the linear system model can be
systematically improved. The method is tested in terms of the efficiency and
accuracy of computing spectral functions for some typical molecular systems
such as carbon monoxide, 1,3-butadiene, benzene, and adenine. As a byproduct,
the obtained reduced order model may provide a high quality initial guess which
improves the convergence rate for the existing iterative linear solver.
| arxiv topic:physics.comp-ph |
arxiv_dataset-108721902.06116 | Motility-induced temperature difference in coexisting phases
cond-mat.soft cond-mat.stat-mech
In nature, objects which are in thermal contact with each other, usually
approach the same temperature, unless a heat source (or sink) cherishes a
persistent flow of heat. Accordingly, in a well-isolated apartment flat, most
items are at a similar temperature. This is a general consequence of
equilibrium thermodynamics, requiring coexisting phases to have identical
temperatures. Opposing this generic situation, here we identify a system
showing different temperatures in coexisting phases, which are separated from
each other by a sharp and persistent temperature gradient. Thermodynamically,
such a "hot" and a "cold" phase are allowed to coexist, as the system we
consider comprises "active" particles which self-propel relative to their
environment and are thus intrinsically out-of-equilibrium. Although these
microparticles are well known to spontaneously phase-separate into a liquid-
and a gas-like state, different kinetic temperatures in coexisting phases occur
if and only if inertia is introduced, which is neglected in standard models
describing active particles. Our results, therefore, exemplify a novel route to
use active particles to create a self-sustained temperature gradient across
coexisting phases, a phenomenon, which is fundamentally beyond equilibrium
physics.
| arxiv topic:cond-mat.soft cond-mat.stat-mech |
arxiv_dataset-108731902.06216 | Poisson's fundamental theorem of calculus via Taylor's formula
math.HO
We use Taylor's formula with Lagrange remainder to make a modern adaptation
of Poisson's proof of a version of the fundamental theorem of calculus in the
case when the integral is defined by Euler sums, that is Riemann sums with left
(or right) endpoints which are equally spaced. We discuss potential benefits
for such an approach in basic calculus courses.
| arxiv topic:math.HO |
arxiv_dataset-108741902.06316 | On The Expected Total Curvature of Confined Equilateral Quadrilaterals
math.MG math.PR
In this paper, we prove that the total expected curvature for random spatial
equilateral quadrilaterals with diameter at most $r$ decreases as $r$
increases. To do so, we prove several curvature monotonicity inequalities and
stochastic ordering lemmas in terms the of the action-angle coordinates. Using
these, we can use Baddeley's extension of Crofton's differential equation to
show that the derivative of the expected total curvature is non-positive.
| arxiv topic:math.MG math.PR |
arxiv_dataset-108751902.06416 | Fluctuation-dominated phase ordering at a mixed order transition
cond-mat.stat-mech
Mixed order transitions are those which show a discontinuity of the order
parameter as well as a divergent correlation length. We show that the behaviour
of the order parameter correlation function along the transition line of mixed
order transitions can change from normal critical behaviour with power law
decay, to fluctuation-dominated phase ordering as a parameter is varied. The
defining features of fluctuation-dominated order are anomalous fluctuations
which remain large in the thermodynamic limit, and correlation functions which
approach a finite value through a cusp singularity as the separation scaled by
the system size approaches zero. We demonstrate that fluctuation-dominated
order sets in along a portion of the transition line of an Ising model with
truncated long-range interactions which was earlier shown to exhibit mixed
order transitions, and also argue that this connection should hold more
generally.
| arxiv topic:cond-mat.stat-mech |
arxiv_dataset-108761902.06516 | Pre-asymptotic dynamics of the infinite size Neumann (p=2 spherical)
model
cond-mat.stat-mech
In this contribution we further study the classical disordered p=2 spherical
model with Hamiltonian dynamics, or in integrable systems terms, the Neumann
model, in the infinite size limit. We summarise the asymptotic results that
some of us presented in a recent publication, and we deepen the analysis of the
pre-asymptotic dynamics. We also discuss the possible description of the
asymptotic steady state with a Generalised Gibbs Ensemble.
| arxiv topic:cond-mat.stat-mech |
arxiv_dataset-108771902.06616 | Some non-abelian covers of knots with non-trivial Alexander polynomial
math.GT
Let $K$ be a tame knot embedded in $\mathbf{S}^3$. We address the problem of
finding the minimal degree non-cyclic cover $p:X \rightarrow \mathbf{S}^3
\smallsetminus K$. When $K$ has non-trivial Alexander polynomial we construct
finite non-abelian representations $\rho:\pi_1\left(\mathbf{S}^3 \smallsetminus
K\right) \rightarrow G$, and provide bounds for the order of $G$ in terms of
the crossing number of $K$ which is an improvement on a result of Broaddus in
this case. Using classical covering space theory along with the theory of
Alexander stratifications we establish an upper and lower bound for the first
betti number of the cover $X_\rho$ associated to the $\text{ker}(\rho)$ of
$\mathbf{S}^3 \smallsetminus K$, consequently showing that it can be
arbitrarily large. We also demonstrate that $X_\rho$ contains non-peripheral
homology for certain computable examples, which mirrors a famous result of
Cooper, Long, and Reid when $K$ is a knot with non-trivial Alexander
polynomial.
| arxiv topic:math.GT |
arxiv_dataset-108781902.06716 | Holograms to focus arbitrary ultrasonic fields through the skull
physics.app-ph
We report 3D-printed acoustic holographic lenses for the formation of
ultrasonic fields of complex spatial distribution inside the skull. Using
holographic lenses, we experimentally, numerically and theoretically produce
acoustic beams whose spatial distribution matches target structures of the
central nervous system. In particular, we produce three types of targets of
increasing complexity. First, a set of points are selected at the center of
both right and left human hippocampi. Experiments using a skull phantom and 3D
printed acoustic holographic lenses show that the corresponding bifocal lens
simultaneously focuses acoustic energy at the target foci, with good agreement
between theory and simulations. Second, an arbitrary curve is set as the target
inside the skull phantom. Using time-reversal methods the holographic beam
bends following the target path, in a similar way as self-bending beams do in
free space. Finally, the right human hippocampus is selected as a target
volume. The focus of the corresponding holographic lens overlaps with the
target volume in excellent agreement between theory in free-media, and
experiments and simulations including the skull phantom. The precise control of
focused ultrasound into the central nervous system is mainly limited due to the
strong phase aberrations produced by refraction and attenuation of the skull.
Using the present method, the ultrasonic beam can be focused not only at a
single point but overlapping one or various target structures simultaneously
using low-cost 3D-printed acoustic holographic lens. The results open new paths
to spread incoming biomedical ultrasound applications including blood-brain
barrier opening or neuromodulation.
| arxiv topic:physics.app-ph |
arxiv_dataset-108791902.06816 | A Six-moment Multi-fluid Plasma Model
physics.comp-ph physics.plasm-ph
We present a six-moment multi-fluid model, which solves the governing
equations for both ions and electrons, with pressure anisotropy along and
perpendicular to the magnetic field direction, as well as the complete set of
Maxwell equations. This set of equations includes the Hall effect, different
temperatures for different species and pressure anisotropy. It is more
comprehensive than the five-moment equations with isotropic pressures and
significantly less expensive than the ten-moment equations with a full pressure
tensors. Similarly to the five- and ten-moment equations, the wave speeds are
naturally limited by the speed of light, which eliminates the issue of
unlimited whistler wave speeds present in Hall magnetohydrodynamics (MHD). It
is also possible to simulate multiple negatively charged fluids, which cannot
be done in MHD models. The six-moment model is a reasonable description of the
plasma outside magnetic reconnection regions and therefore well-suited to be
coupled with an embedded particle-in-cell model that covers the reconnection
region. Our numerical implementation uses a point-implicit scheme for the stiff
source terms, and we use a second-order accurate Rusanov-type scheme with
carefully selected wave speeds. For the plasma variables and the magnetic field
the maximum wave speed is based on the fast magnetosonic speed of MHD with
anisotropic pressures that we derive. For the electric field related variables
the speed of light is used. The divergence of the magnetic field and Gauss's
law are controlled with a hyperbolic-parabolic scheme. We present a number of
numerical tests to demonstrate that this numerical model is robust without
being excessively diffusive.
| arxiv topic:physics.comp-ph physics.plasm-ph |
arxiv_dataset-108801902.06916 | Universality of Computational Lower Bounds for Submatrix Detection
math.ST cs.CC cs.LG math.PR stat.TH
In the general submatrix detection problem, the task is to detect the
presence of a small $k \times k$ submatrix with entries sampled from a
distribution $\mathcal{P}$ in an $n \times n$ matrix of samples from
$\mathcal{Q}$. This formulation includes a number of well-studied problems,
such as biclustering when $\mathcal{P}$ and $\mathcal{Q}$ are Gaussians and the
planted dense subgraph formulation of community detection when the submatrix is
a principal minor and $\mathcal{P}$ and $\mathcal{Q}$ are Bernoulli random
variables. These problems all seem to exhibit a universal phenomenon: there is
a statistical-computational gap depending on $\mathcal{P}$ and $\mathcal{Q}$
between the minimum $k$ at which this task can be solved and the minimum $k$ at
which it can be solved in polynomial time. Our main result is to tightly
characterize this computational barrier as a tradeoff between $k$ and the KL
divergences between $\mathcal{P}$ and $\mathcal{Q}$ through average-case
reductions from the planted clique conjecture. These computational lower bounds
hold given mild assumptions on $\mathcal{P}$ and $\mathcal{Q}$ arising
naturally from classical binary hypothesis testing. Our results recover and
generalize the planted clique lower bounds for Gaussian biclustering in Ma-Wu
(2015) and Brennan et al. (2018) and for the sparse and general regimes of
planted dense subgraph in Hajek et al. (2015) and Brennan et al. (2018). This
yields the first universality principle for computational lower bounds obtained
through average-case reductions.
| arxiv topic:math.ST cs.CC cs.LG math.PR stat.TH |
arxiv_dataset-108811902.07016 | DDF operators, open string coherent states and their scattering
amplitudes
hep-th
We study interactions of string coherent states in the DDF (after Di Vecchia,
Del Giudice, Fubini) formalism. For simplicity we focus on open bosonic
strings. After reviewing basic properties of DDF operators and of excited open
strings, we present some classical profiles and show how they become more and
more compact as the number of harmonics increases at fixed mass. We then
compute various three- and four-point amplitudes with insertions of coherent
states, tachyons and vector bosons on the boundary of the disk relying on a
convenient choice of reference null momenta. We find that the amplitudes
exponentiate in a rather subtle and interesting way. We then study the
high-energy fixed-angle limit, dominated by a saddle-point when coherent states
are present, and the soft behaviour as the momentum of a vector boson is taken
to zero. We briefly comment on generalisation of our analysis to multiple
intersecting and magnetised D-branes and to closed strings.
| arxiv topic:hep-th |
arxiv_dataset-108821902.07116 | Wave Chaos in a Cavity of Regular Geometry with Tunable Boundaries
physics.app-ph nlin.CD
Wave chaotic systems underpin a wide range of research activities, from
fundamental studies of quantum chaos via electromagnetic compatibility up to
more recently emerging applications like microwave imaging for security
screening, antenna characterisation or wave-based analog computation. To
implement a wave chaotic system experimentally, traditionally cavities of
elaborate geometries (bowtie shapes, truncated circles, parallelepipeds with
hemispheres) are employed because the geometry dictates the wave field's
characteristics. Here, we propose and experimentally verify a radically
different paradigm: a cavity of regular geometry but with tunable boundary
conditions, experimentally implemented by leveraging a reconfigurable
metasurface. Our results set new foundations for the use and the study of chaos
in wave physics.
| arxiv topic:physics.app-ph nlin.CD |
arxiv_dataset-108831902.07216 | Extended stellar systems in the solar neighborhood - III. Like ships in
the night: the Coma Berenices neighbor moving group
astro-ph.GA
We report the discovery of a kinematically cold group of stars, located in
the immediate neighborhood of the well-known star cluster Coma Berenices (Mel
111). The new group identified in tangential velocity space as measured by Gaia
contains at least 177 coeval members distributed in two subgroups, and appears
as a flattened structure parallel to the plane, stretching for about 50 pc.
More remarkably, the new group, which appears to have formed about 300 Myr
later than Mel 111 in a different part of the Galaxy, will share essentially
the same volume with the older cluster when the centers of both groups will be
at their closest in 13 Myr. This will result in the mixing of two unrelated
populations with different metallicities. The phase of cohabitation for these
two groups is about 20-30 Myr, after which the two populations will drift
apart. We estimate that temporal cohabitation of such populations is not a rare
event in the disk of the Milky Way, and of the order of once per Galactic
revolution. Our study also unveils the tidal tails of the Mel 111 cluster.
| arxiv topic:astro-ph.GA |
arxiv_dataset-108841902.07316 | Deep Modulation Embedding
eess.SP cs.LG stat.ML
Deep neural network has recently shown very promising applications in
different research directions and attracted the industry attention as well.
Although the idea was introduced in the past but just recently the main
limitation of using this class of algorithms is solved by enabling parallel
computing on GPU hardware. Opening the possibility of hardware prototyping with
proven superiority of this class of algorithm, trigger several research
directions in communication system too. Among them cognitive radio, modulation
recognition, learning based receiver and transceiver are already given very
interesting result in simulation and real experimental evaluation implemented
on software defined radio. Specifically, modulation recognition is mostly
approached as a classification problem which is a supervised learning
framework. But it is here addressed as an unsupervised problem with introducing
new features for training, a new loss function and investigating the robustness
of the pipeline against several mismatch conditions.
| arxiv topic:eess.SP cs.LG stat.ML |
arxiv_dataset-108851902.07416 | On AKKT optimality conditions for cone-constrained vector optimization
problems
math.OC
In this paper, we introduce a kind of approximate Karush--Kuhn--Tucker
condition (AKKT) for a smooth cone-constrained vector optimization problem. We
show that, without any constraint qualification, the AKKT condition is a
necessary for a local weak efficient solution of the considered problem. For
convex problems, we prove that the AKKT condition is a necessary and sufficient
optimality condition for a global weak efficient solution. We also introduce
some strict constraint qualifications associated with the AKKT condition.
| arxiv topic:math.OC |
arxiv_dataset-108861902.07516 | Emergence of order in random languages
cond-mat.dis-nn cs.CL cs.FL
We consider languages generated by weighted context-free grammars. It is
shown that the behaviour of large texts is controlled by saddle-point equations
for an appropriate generating function. We then consider ensembles of grammars,
in particular the Random Language Model of E. DeGiuli, Phys. Rev. Lett., 122,
128301, 2019. This model is solved in the replica-symmetric ansatz, which is
valid in the high-temperature, disordered phase. It is shown that in the phase
in which languages carry information, the replica symmetry must be broken.
| arxiv topic:cond-mat.dis-nn cs.CL cs.FL |
arxiv_dataset-108871902.07616 | De Donder Form for Second Order Gravity
math-ph math.DG math.MP
We show that the De Donder form for second order gravity, defined in terms of
Ostrogradski's version of the Legendre transformation applied to all
independent variables, is globally defined by its local coordinate
descriptions. It is a natural differential operator applied to the
diffeomorphism invariant Lagrangian of the theory.
| arxiv topic:math-ph math.DG math.MP |
arxiv_dataset-108881902.07716 | Photoinduced Floquet topological magnons in Kitaev magnets
cond-mat.str-el
We study periodically driven pure Kitaev model and ferromagnetic phase of the
Kitaev-Heisenberg model on the honeycomb lattice by off-resonant linearly and
circularly-polarized lights at zero magnetic field. Using a combination of
linear spin wave and Floquet theories, we show that the effective
time-independent Hamiltonians in the off-resonant regime map onto the
corresponding anisotropic static spin model, plus a tunable photoinduced
magnetic field along the $[111]$ direction, which precipitates Floquet
topological magnons and chiral magnon edge modes. They are tunable by the light
amplitude and polarization. Similarly, we show that the thermal Hall effect
induced by the Berry curvature of the Floquet topological magnons can also be
tuned by the laser field. Our results pave the way for ultrafast manipulation
of topological magnons in irradiated Kitaev magnets, and could play a pivotal
role in the investigation of ultrafast magnon spin current generation in Kitaev
materials.
| arxiv topic:cond-mat.str-el |
arxiv_dataset-108891902.07816 | Mixture Models for Diverse Machine Translation: Tricks of the Trade
cs.CL cs.LG
Mixture models trained via EM are among the simplest, most widely used and
well understood latent variable models in the machine learning literature.
Surprisingly, these models have been hardly explored in text generation
applications such as machine translation. In principle, they provide a latent
variable to control generation and produce a diverse set of hypotheses. In
practice, however, mixture models are prone to degeneracies---often only one
component gets trained or the latent variable is simply ignored. We find that
disabling dropout noise in responsibility computation is critical to successful
training. In addition, the design choices of parameterization, prior
distribution, hard versus soft EM and online versus offline assignment can
dramatically affect model performance. We develop an evaluation protocol to
assess both quality and diversity of generations against multiple references,
and provide an extensive empirical study of several mixture model variants. Our
analysis shows that certain types of mixture models are more robust and offer
the best trade-off between translation quality and diversity compared to
variational models and diverse decoding approaches.\footnote{Code to reproduce
the results in this paper is available at
\url{https://github.com/pytorch/fairseq}}
| arxiv topic:cs.CL cs.LG |
arxiv_dataset-108901902.07916 | ZMCintegral: a Package for Multi-Dimensional Monte Carlo Integration on
Multi-GPUs
physics.comp-ph
We have developed a Python package ZMCintegral for multi-dimensional Monte
Carlo integration on multiple Graphics Processing Units(GPUs). The package
employs a stratified sampling and heuristic tree search algorithm. We have
built three versions of this package: one with Tensorflow and other two with
Numba, and both support general user defined functions with a user-friendly
interface. We have demonstrated that Tensorflow and Numba help inexperienced
scientific researchers to parallelize their programs on multiple GPUs with
little work. The precision and speed of our package is compared with that of
VEGAS for two typical integrands, a 6-dimensional oscillating function and a
9-dimensional Gaussian function. The results show that the speed of ZMCintegral
is comparable to that of the VEGAS with a given precision. For heavy
calculations, the algorithm can be scaled on distributed clusters of GPUs.
| arxiv topic:physics.comp-ph |
arxiv_dataset-108911902.08016 | Derivation of viscous Burgers equations from weakly asymmetric exclusion
processes
math.PR
We consider weakly asymmetric exclusion processes whose initial density
profile is a small perturbation of a constant. We show that in the diffusive
time-scale, in all dimensions, the density defect evolves as the solution of a
viscous Burgers equation.
| arxiv topic:math.PR |
arxiv_dataset-108921902.08116 | On the image of polynomials evaluated on incidence algebras: a
counter-example and a solution
math.RA
In this paper, we investigate the subset obtained by evaluations of a fixed
multilinear polynomial on a given algebra. We provide an example of a
multilinear polynomial, whose image is not a vector subspace; namely, the
product of two commutators need not to be a subspace whenever evaluated on
certain subalgebras of upper triangular matrices (the so-called incidence
algebras).
In the last part of the paper, given that the field is infinite, we reduce
the problem of the description of the image of a polynomial evaluated on an
incidence algebra to the study of evaluations of a certain family of
polynomials on its Jacobson radical. In particular, we are able to describe the
image of multilinear polynomials evaluated on the algebra of upper triangular
matrices.
| arxiv topic:math.RA |
arxiv_dataset-108931902.08216 | Environmental Effect on the Interstellar Medium in Galaxies across the
Cosmic Web at z=0.73
astro-ph.GA
We present new ALMA dust continuum observations of 101 $\log(\mathrm{M}_* /
\mathrm{M}_\odot)$ > 9.5 galaxies in the COSMOS field to study the effect of
environment on the interstellar medium at z ~ 0.7. At this redshift, our
targets span a wide range of environments allowing for a diverse sample of
galaxies with densities, $\Sigma$ = 0.16-10.5 Mpc$^{-2}$ (per $\Delta$ z =
0.024). Using the ALMA observations, we calculate the total ISM mass and look
for depletion as a function of galaxy density in order to understand the
quenching or triggering of star formation in galaxies in different
environments. ISM mass is found to have a small dependence on environment,
while the depletion timescale remains constant (~200 Myrs) across all
environments. We find elevated ISM mass values at intermediate densities and
lower values at high densities compared to low (field) densities. Our observed
evolution in gas fraction with density in this single redshift slice is
equivalent to the observed evolution with cosmic time over 2-3 Gyr. To explain
the change in gas mass fraction seen in galaxies in intermediate and high
densities, these results suggest environmental processes such as mergers and
ram pressure stripping are likely playing a role in dense filamentary-cluster
environments.
| arxiv topic:astro-ph.GA |
arxiv_dataset-108941902.08316 | Mixed temperature-dependent order parameters in the extended Hubbard
model
cond-mat.supr-con
The extended Hubbard model can host s-wave, d-wave and p-wave superconducting
phases depending on the values of the on-site and nearest-neighbour
interactions. Upon detailed examination of the free energy functional of the
gap in this model, we show that these symmetries are often dependent on
temperature. The critical points of this functional are constrained by symmetry
and allow us to formulate stringent conditions on the temperature profile of
the gap function, applicable to other models as well. We discuss the finite
temperature phase diagram of the extended Hubbard model, and point out the
existence of symmetry transitions below $T_c$. Understanding the nature of
these transitions is crucial to assessing the symmetry of unconventional
superconductors.
| arxiv topic:cond-mat.supr-con |
arxiv_dataset-108951902.08416 | Large deviations and dynamical phase transitions in stochastic chemical
networks
cond-mat.stat-mech
Chemical reaction networks offer a natural nonlinear generalisation of linear
Markov jump processes on a finite state-space. In this paper, we analyse the
dynamical large deviations of such models, starting from their microscopic
version, the chemical master equation. By taking a large-volume limit, we show
that those systems can be described by a path integral formalism over a
Lagrangian functional of concentrations and chemical fluxes. This Lagrangian is
dual to a Hamiltonian, whose trajectories correspond to the most likely
evolution of the system given its boundary conditions. The same can be done for
a system biased on time-averaged concentrations and currents, yielding a biased
Hamiltonian whose trajectories are optimal paths conditioned on those
observables. The appropriate boundary conditions turn out to be mixed, so that,
in the long time limit, those trajectories converge to well-defined attractors.
We are then able to identify the largest value that the Hamiltonian takes over
those attractors with the scaled cumulant generating function of our
observables, providing a non-linear equivalent to the well-known
Donsker-Varadhan formula for jump processes. On that basis, we prove that
chemical reaction networks that are deterministically multistable generically
undergo first-order dynamical phase transitions in the vicinity of zero bias.
We illustrate that fact through a simple bistable model called the Schl\"ogl
model, as well as multistable and unstable generalisations of it, and we make a
few surprising observations regarding the stability of deterministic fixed
points, and the breaking of ergodicity in the large-volume limit.
| arxiv topic:cond-mat.stat-mech |
arxiv_dataset-108961902.08516 | Lattice Density-Functional Theory for Quantum Chemistry
cond-mat.str-el physics.chem-ph
We propose a lattice density-functional theory for {\it ab initio} quantum
chemistry or physics as a route to an efficient approach that approximates the
full configuration interaction energy and orbital occupations for molecules
with strongly-correlated electrons. We build on lattice density-functional
theory for the Hubbard model by deriving Kohn-Sham equations for a reduced then
full quantum chemistry Hamiltonian, and demonstrate the method on the potential
energy curves for the challenging problem of modelling elongating bonds in a
linear chain of six hydrogen atoms. Here the accuracy of the Bethe-ansatz
local-density approximation is tested for this quantum chemistry system and we
find that, despite this approximate functional being designed for the Hubbard
model, the shapes of the potential curves generally agree with the full
configuration interaction results. Although there is a discrepancy for very
stretched bonds, this is lower than when using standard density-functional
theory with the local-density approximation.
| arxiv topic:cond-mat.str-el physics.chem-ph |
arxiv_dataset-108971902.08616 | Fermionic multicriticality near Kekul\'{e} valence-bond ordering in
honeycomb lattice
cond-mat.str-el cond-mat.mes-hall hep-th
We analyze the possibility of emergent quantum multicritical points (MCPs)
with enlarged chiral symmetry, when strongly interacting gapless Dirac fermions
acquire comparable propensity toward the nucleation of Kekul\'{e} valence-bond
solid (KVBS) and charge-density-wave ($N_b=1$) or $s$-wave pairing ($N_b=2$) or
anti-ferromagnet ($N_b=3$) in honeycomb lattice, where $N_b$ counts the number
of bosonic order parameter components. Besides the cubic terms present in the
order parameter description of KVBS due to the breaking of a discrete $Z_3$
symmetry, quantum fluctuations generate new cubic vertices near the high
symmetry MCPs. All cubic terms are strongly relevant at the bare level near
three spatial dimensions, about which we perform a leading order
renormalization group analysis of coupled Gross-Neveu-Yukawa field theory. We
show that due to non-trivial Yukawa interactions among gapless bosonic and
fermionic degrees of freedom, all cubic terms ultimately become irrelevant at
an $O(2+N_b)$ symmetric MCP, near two spatial dimensions, where $N_b=1,2,3$.
Therefore, MCPs with an enlarged $O(2+N_b)$ symmetry near KVBS ordering are
stable.
| arxiv topic:cond-mat.str-el cond-mat.mes-hall hep-th |
arxiv_dataset-108981902.08716 | Spatio-Temporal Convolutional LSTMs for Tumor Growth Prediction by
Learning 4D Longitudinal Patient Data
cs.CV
Prognostic tumor growth modeling via volumetric medical imaging observations
can potentially lead to better outcomes of tumor treatment and surgical
planning. Recent advances of convolutional networks have demonstrated higher
accuracy than traditional mathematical models in predicting future tumor
volumes. This indicates that deep learning-based techniques may have great
potentials on addressing such problem. However, current 2D patch-based modeling
approaches cannot make full use of the spatio-temporal imaging context of the
tumor's longitudinal 4D (3D + time) data. Moreover, they are incapable to
predict clinically-relevant tumor properties, other than volumes. In this
paper, we exploit to formulate the tumor growth process through convolutional
Long Short-Term Memory (ConvLSTM) that extract tumor's static imaging
appearances and capture its temporal dynamic changes within a single network.
We extend ConvLSTM into the spatio-temporal domain (ST-ConvLSTM) by jointly
learning the inter-slice 3D contexts and the longitudinal or temporal dynamics
from multiple patient studies. Our approach can incorporate other non-imaging
patient information in an end-to-end trainable manner. Experiments are
conducted on the largest 4D longitudinal tumor dataset of 33 patients to date.
Results validate that the ST-ConvLSTM produces a Dice score of 83.2%+-5.1% and
a RVD of 11.2%+-10.8%, both significantly outperforming (p<0.05) other compared
methods of linear model, ConvLSTM, and generative adversarial network (GAN)
under the metric of predicting future tumor volumes. Additionally, our new
method enables the prediction of both cell density and CT intensity numbers.
Last, we demonstrate the generalizability of ST-ConvLSTM by employing it in 4D
medical image segmentation task, which achieves an averaged Dice score of
86.3+-1.2% for left-ventricle segmentation in 4D ultrasound with 3 seconds per
patient.
| arxiv topic:cs.CV |
arxiv_dataset-108991902.08816 | Augmenting Neural Machine Translation with Knowledge Graphs
cs.CL
While neural networks have been used extensively to make substantial progress
in the machine translation task, they are known for being heavily dependent on
the availability of large amounts of training data. Recent efforts have tried
to alleviate the data sparsity problem by augmenting the training data using
different strategies, such as back-translation. Along with the data scarcity,
the out-of-vocabulary words, mostly entities and terminological expressions,
pose a difficult challenge to Neural Machine Translation systems. In this
paper, we hypothesize that knowledge graphs enhance the semantic feature
extraction of neural models, thus optimizing the translation of entities and
terminological expressions in texts and consequently leading to a better
translation quality. We hence investigate two different strategies for
incorporating knowledge graphs into neural models without modifying the neural
network architectures. We also examine the effectiveness of our augmentation
method to recurrent and non-recurrent (self-attentional) neural architectures.
Our knowledge graph augmented neural translation model, dubbed KG-NMT, achieves
significant and consistent improvements of +3 BLEU, METEOR and chrF3 on average
on the newstest datasets between 2014 and 2018 for WMT English-German
translation task.
| arxiv topic:cs.CL |
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