  Attractor, supposed to be one of the possible answer for the early
applicability of hydrodynamics in the evolution with different initial
conditions, has attracted great attention to the fast decreasing of degrees of
freedom in heavy ion collision. We found attractor behaviors for 1+1D viscous
hydrodynamics with general rapidity distribution based on MIS theory.
Meanwhile, we also observe that a rapid expansion in the fluid velocity is
essential for a rapid early time attractor.


  Topological Lifshitz phase transition characterizes an abrupt change of the
topology of the Fermi surface through a continuous deformation of parameters.
Recently, Lifshitz transition has been predicted to separate two types of Weyl
points: type-I and type-II (or called structured Weyl points), which has
attracted considerable attention in various fields. Although recent
experimental investigation has seen a rapid progress on type-II Weyl points, it
still remains a significant challenge to observe their characteristic Lifshitz
transition. Here, we propose a scheme to realize both type-I and type-II Weyl
points in three-dimensional ultracold atomic gases by introducing an
experimentally feasible configuration based on current spin-orbit coupling
technology. In the resultant Hamiltonian, we find three degenerate points: two
Weyl points carrying a Chern number $-1$ and a four-fold degenerate point
carrying a Chern number $2$. Remarkably, by continuous tuning of a convenient
experimental knob, all these degenerate points can transition from type-I to
type-II, thereby providing an ideal platform to study different types of Weyl
points and directly probe their Lifshitz phase transition.


  Here we analyze the first simultaneous X-ray, ultraviolet, optical, infrared,
and centimeter observations of a T Tauri star (TTS). We present three epochs of
simultaneous Spitzer and VLA data of GM Aur separated by ~1 wk. These data are
compared to previously published HST and Chandra observations from which mass
accretion rates ($\dot M$) and X-ray luminosities, respectively, were measured.
The mid-infrared emission increases along with $\dot M$, and we conclude that
this is due to an increase in the mass in the inner disk. The cm emission,
which probes the jet, also appears to increase as $\dot M$ increases, and the
changes in the cm flux are consistent with the variability in $\dot M$ assuming
the mass-loss rate is ~10% $\dot M$. The 3 cm emission morphology also appears
changed compared with observations taken three years previously, suggesting
that for the first time, we may be tracking changes in the jet morphology of a
TTS. The X-ray luminosity is constant throughout the three epochs, ruling out
variable high-energy stellar radiation as the cause for the increases in the
mid-infrared or cm emission. Tying together the multiwavelength variability
observed, we conclude that an increase in the surface density in the inner disk
resulted in more mass loading onto the star and therefore a higher $\dot M$,
which led to a higher mass-loss rate in the jet. These results stress the
importance of coordinated multiwavelength work to better understand the
star-disk-jet connection.


  We present VIVACE, the VIrac VAriable Classification Ensemble, a catalogue of
variable stars extracted from an automated classification pipeline for the
Vista Variables in the V\'ia L\'actea (VVV) infrared survey of the Galactic
bar/bulge and southern disc. Our procedure utilises a two-stage hierarchical
classifier to first isolate likely variable sources using simple variability
summary statistics and training sets of non-variable sources from the Gaia
early third data release, and then classify candidate variables using more
detailed light curve statistics and training labels primarily from OGLE and
VSX. The methodology is applied to point-spread-function photometry for
$\sim490$ million light curves from the VIRAC v2 astrometric and photometric
catalogue resulting in a catalogue of $\sim1.4$ million likely variable stars,
of which $\sim39,000$ are high-confidence (classification probability $>0.9$)
RR Lyrae ab stars, $\sim8000$ RR Lyrae c/d stars, $\sim187,000$
detached/semi-detached eclipsing binaries, $\sim18,000$ contact eclipsing
binaries, $\sim1400$ classical Cepheid variables and $\sim2200$ Type II Cepheid
variables. Comparison with OGLE-4 suggests a completeness of around $90\,\%$
for RRab and $\lesssim60\%$ for RRc/d, and a misclassification rate for known
RR Lyrae stars of around $1\%$ for the high confidence sample. We close with
two science demonstrations of our new VIVACE catalogue: first, a brief
investigation of the spatial and kinematic properties of the RR Lyrae stars
within the disc/bulge, demonstrating the spatial elongation of bar-bulge RR
Lyrae stars is in the same sense as the more metal-rich red giant population
whilst having a slower rotation rate of
$\sim40\,\mathrm{km\,s}^{-1}\mathrm{kpc}^{-1}$; and secondly, an investigation
of the Gaia EDR3 parallax zeropoint using contact eclipsing binaries across the
Galactic disc plane and bulge.


  We adopt a global optimization method to predict two-dimensional (2D)
nanostructures through the particle-swarm optimization (PSO) algorithm. By
performing PSO simulations, we predict new stable structures of 2D boron-carbon
(B-C) compounds for a wide range of boron concentrations. Our calculations show
that: (1) All 2D B-C compounds are metallic except for BC3 which is a magic
case where the isolation of carbon six-membered ring by boron atoms results in
a semiconducting behavior. (2) For C-rich B-C compounds, the most stable 2D
structures can be viewed as boron doped graphene structures, where boron atoms
typically form 1D zigzag chains except for BC3 in which boron atoms are
uniformly distributed. (3) The most stable 2D structure of BC has alternative
carbon and boron ribbons with strong in-between B-C bonds, which possesses a
high thermal stability above 2000K. (4) For B-rich 2D B-C compounds, there is a
novel planar-tetracoordinate carbon motif with an approximate C2v symmetry.


  We analyse, following recent work of Roehner, changes in house prices for
both the UK and Ireland. We conclude that prices in London have reached a
tipping point and prices relative to inflation are set to fall over the next
few years. If inflation does not rise then a hard landing seems likely. House
prices in the Irish Republic are shown to have broken away from the moderate
rise still to be found in Northern Ireland and Dublin has emerged as another
global 'hot spot'. An evolution of Dublin house prices similar to that in
London can be anticipated. Keywords: Econophysics, house prices, real estate,
prediction PACS: 89.65.Gh, 89.90.+n


  We construct rich vector spaces of continuous functions with prescribed
curved or linear pathwise quadratic variations. We also construct a class of
functions whose quadratic variation may depend in a local and nonlinear way on
the function value. These functions can then be used as integrators in
F\"ollmer's pathwise It\=o calculus. Our construction of the latter class of
functions relies on an extension of the Doss--Sussman method to a class of
nonlinear It\=o differential equations for the F\"ollmer integral. As an
application, we provide a deterministic variant of the support theorem for
diffusions. We also establish that many of the constructed functions are
nowhere differentiable.


  It is pointed out that the 60 complex rays in four dimensions associated with
a system of two qubits yield over 10^9 critical parity proofs of the
Kochen-Specker theorem. The geometrical properties of the rays are described,
an overview of the parity proofs contained in them is given, and examples of
some of the proofs are exhibited.


  Optimizing one's observing strategy while at the telescope relies on knowing
the current observing conditions and the obtained data quality. In particular
the latter is not straight forward with current wide-field imagers, such as the
WIYN One Degree Imager (ODI), currently consisting of 13 detectors, each of
them read out in 64 independent cells.
  Here we present a fast data reduction software for ODI, optimized for a first
data inspection during acquisition at the the telescope, but capable enough for
science-quality data reductions. The pipeline is coded in pure python with
minimal additional requirements. It is installed on the ODI observer's
interface and publicly available from the author's webpage. It performs all
basic reduction steps as well as more advanced corrections for pupil-ghost
removal, fringe correction and masking of persistent pixels. Additional
capabilities include adding an accurate astrometric WCS solution based on the
2MASS reference system as well as photometric zeropoint calibration for frames
covered by the SDSS foot-print.
  The pipeline makes use of multiple CPU-cores wherever possible, resulting in
an execution time of only a few seconds per frame. As such this QuickReduce
pipeline offers the ODI observer a convenient way to closely monitor data
quality, a necessity to optimize the observing strategy during the night.


  This volume contains the proceedings of the Fifth International Workshop on
Intersection Types and Related Systems (ITRS 2010). The workshop was held in
Edinburgh, Scotland, on July 9th 2010, as part of FLoC 2010 and affiliated with
LICS 2010.
  The ITRS workshop series aim at bringing together researchers working on both
the theory and practical applications of systems based on intersection types
and related approaches (e.g., union types, refinement types, behavioral types).


  Iron ilmenene is a new two-dimensional material that has recently been
exfoliated from the naturally-occurring iron titanate found in ilmenite ore, a
material that is abundant on earth surface. In this work, we theoretically
investigate the structural, electronic and magnetic properties of 2D
transition-metal-based ilmenene-like titanates. The study of magnetic order
reveals that these ilmenenes usually present intrinsic antiferromagnetic
coupling between the 3d magnetic metals decorating both sides of the Ti-O
layer. Furthermore, the ilmenenes based on late 3d brass metals, such as
CuTiO$_3$ and ZnTiO$_3$, become ferromagnetic and spin compensated,
respectively. Our calculations including spin-orbit coupling reveal that the
magnetic ilmenenes have large magnetocrystalline anisotropy energies when the
3d shell departs from being either filled or half-filled, with their spin
orientation being out-of-plane for elements below half-filling of 3d states and
in-plane above. These interesting magnetic properties of ilmenenes make them
useful for future spintronic applications because they could be synthesized as
already realized in the iron case.


  We present an ab-initio formalism for the calculation of transport properties
in compositionally disordered systems within the framework of the
Korringa-Kohn-Rostoker non-local coherent potential approximation. Our
formalism is based upon the single-particle Kubo-Greenwood linear response and
provides a natural means of incorporating the effects of short-range order upon
the transport properties. We demonstrate the efficacy of the formalism by
examining the effects of short-range order and clustering upon the transport
properties of disordered $AgPd$ and $CuZn$ alloys.


  The Fermi-Watson theorem is generalized to the case of two coupled channels
with different masses and applied to final state interaction in $K_{e4}$
decays. The impact of considered effect on the phase of the $\pi\pi$ scattering
is estimated and shown that it can be crucial for scattering lengths extraction
from experimental data on $K_{e4}$ decays.


  Concept-to-text generation typically employs a pipeline architecture, which
often leads to suboptimal texts. Content selection, for example, may greedily
select the most important facts, which may require, however, too many words to
express, and this may be undesirable when space is limited or expensive.
Selecting other facts, possibly only slightly less important, may allow the
lexicalization stage to use much fewer words, or to report more facts in the
same space. Decisions made during content selection and lexicalization may also
lead to more or fewer sentence aggregation opportunities, affecting the length
and readability of the resulting texts. Building upon on a publicly available
state of the art natural language generator for Semantic Web ontologies, this
article presents an Integer Linear Programming model that, unlike pipeline
architectures, jointly considers choices available in content selection,
lexicalization, and sentence aggregation to avoid greedy local decisions and
produce more compact texts, i.e., texts that report more facts per word.
Compact texts are desirable, for example, when generating advertisements to be
included in Web search results, or when summarizing structured information in
limited space. An extended version of the proposed model also considers a
limited form of referring expression generation and avoids redundant sentences.
An approximation of the two models can be used when longer texts need to be
generated. Experiments with three ontologies confirm that the proposed models
lead to more compact texts, compared to pipeline systems, with no deterioration
or with improvements in the perceived quality of the generated texts.


  We have been undertaking a programme on the Gemini 8-m telescopes to
demonstrate the power of integral field spectroscopy, using the optical GMOS
spectrograph, and the new CIRPASS instrument in the near-infrared. Here we
present some preliminary results from 3D spectroscopy of extra-galactic
objects, mapping the emission lines in a 3CR radio galaxy and in a
gravitationally lensed arc, exploring dark matter sub-structure through
observations of an Einstein Cross gravitational lens, and the star formation
time-scales of young massive clusters in the starburst galaxy NGC 1140.


  We have studied the O 2p valence-band structure of Nb-doped SrTiO3, in which
a dilute concentration of electrons are doped into the d0 band insulator, by
angle-resolved photoemission spectroscopy (ARPES) measurements. We found that
ARPES spectra at the valence band maxima at the M [k = (pi/a, pi/a, 0)]and R [k
= (pi/a, pi/a, pi/a)] points start from ~ 3.3 eV below the Fermi level (EF),
consistent with the indirect band gap of 3.3 eV and the EF position at the
bottom of the conduction band. The peak position of the ARPES spectra were,
however, shifted toward higher binding energies by ~ 500 meV from the 3.3 eV
threshold. Because the bands at M and R have pure O 2p character, we attribute
this ~ 500 meV shift to strong coupling of the oxygen p hole with optical
phonons in analogy with the peak shifts observed for d-electron photoemission
spectra in various transition-metal oxides.


  We investigate the quantum mechanical origin of resistive phase transitions
in solids driven by a constant electric field in the vicinity of a
metal-insulator transition. We perform a nonequilibrium mean-field analysis of
a driven-dissipative anti-ferromagnet, which we solve analytically for the most
part. We find that the insulator-to-metal transition (IMT) and the
metal-to-insulator transition (MIT) proceed by two distinct electronic
mechanisms: Landau-Zener processes, and the destabilization of metallic state
by Joule heating, respectively. However, we show that both regimes can be
unified in a common effective thermal description, where the effective
temperature $T_{\rm eff}$ depends on the state of the system. This explains
recent experimental measurements in which the hot-electron temperature at the
IMT was found to match the equilibrium transition temperature. Our analytic
approach enables us to formulate testable predictions on the non-analytic
behavior of $I$-$V$ relation near the insulator-to-metal transition. Building
on these successes, we propose an effective Ginzburg-Landau theory which paves
the way to incorporating spatial fluctuations, and to bringing the theory
closer to a realistic description of the resistive switchings in correlated
materials.


  We analyze a sample of 58 multi-wavelength, Very Long Baseline Array
observations of active galactic nuclei (AGN) to determine their scattering
properties. Approximately 75% of the sample consists of AGN that exhibit
centimeter-wavelength intraday variability (interstellar scintillation) while
the other 25% do not show intraday variability. We find that interstellar
scattering is measurable for most of these AGN, and the typical broadening
diameter is 2 mas at 1 GHz. We find that the scintillating AGN are typically at
lower Galactic latitudes than the non-scintillating AGN, consistent with the
scenario that intraday variability is a propagation effect from the Galactic
interstellar medium. The magnitude of the inferred interstellar broadening
measured toward the scintillating AGN, when scaled to higher frequencies, is
comparable to the diameters inferred from analyses of the light curves for the
more well-known intraday variable sources. However, we find no difference in
the amount of scattering measured toward the scintillating versus
non-scintillating AGN. A consistent picture is one in which the scintillation
results from localized regions ("clumps") distributed throughout the Galactic
disk, but which individually make little contribution to the angular
broadening. Of the 58 AGN observed, 37 (64%) have measured redshifts. At best,
a marginal trend is found for scintillating (non-scintillating) AGN to have
smaller (larger) angular diameters at higher redshifts. We also use our
observations to try to constrain the possibility of intergalactic scattering.
While broadly consistent with the scenario of a highly turbulent intergalactic
medium, our observations do not place significant constraints on its
properties.


  We present an analytic study of the physics of the glasma which is a strong
classical gluon field created at early stage of high-energy heavy-ion
collisions. Our analysis is based on the picture that the glasma just after the
collision is made of color electric and magnetic flux tubes extending in the
longitudinal direction with their diameters of the order of 1/Q_s (Q_s is the
saturation scale of the colliding nuclei). We find that both the electric and
magnetic flux tubes expand outwards and the field strength inside the flux tube
decays rapidly in time. Next we investigate whether there exist instabilities
against small rapidity-dependent perturbations for a fixed color configuration.
We find that the magnetic background field exhibits an instability induced by
the fluctuations in the lowest Landau level, and it grows in the time scale of
1/Q_s. For the electric background field we find no apparent instability while
the possible relation to the Schwinger mechanism for particle pair creations is
suggested.


  The Noether isomorphism theorems and the Zassenhaus Lemma from group theory
have a non-pointed version in a suitable categorical context first considered
by W. Tholen in his PhD thesis. This article leads to a unification of these
results with the ones in the pointed categorical context considered by O.
Wyler, by working in the framework of star-regular categories introduced by M.
Gran, Z. Janelidze and A. Ursini. Some concrete examples of categories where
these results hold are examined in detail.


  Inference of community structure in probabilistic graphical models may not be
consistent with fairness constraints when nodes have demographic attributes.
Certain demographics may be over-represented in some detected communities and
under-represented in others. This paper defines a novel $\ell_1$-regularized
pseudo-likelihood approach for fair graphical model selection. In particular,
we assume there is some community or clustering structure in the true
underlying graph, and we seek to learn a sparse undirected graph and its
communities from the data such that demographic groups are fairly represented
within the communities. In the case when the graph is known a priori, we
provide a convex semidefinite programming approach for fair community
detection. We establish the statistical consistency of the proposed method for
both a Gaussian graphical model and an Ising model for, respectively,
continuous and binary data, proving that our method can recover the graphs and
their fair communities with high probability.


  Transferring energy without transferring mass is a powerful paradigm to
address the challenges faced when the access to, or the deployment of, the
infrastructure for energy conversion is locally impossible or impractical.
Laser beaming holds the promise of effectively implementing this paradigm. With
this perspective, this work evaluates the optical-to-electrical power
conversion that is created when a collimated laser beam illuminates a silicon
photovoltaic solar cell that is located kilometers away from the laser. The
laser is a CW high-energy Yb-doped fiber laser emitting at a center wavelength
of 1075 nm with ~1 m2 of effective beam area. For 20 kW illumination of a solar
panel having 0.6 m2 of area, optical simulations and thermal simulations
indicate electrical output power of 3000 Watts at a panel temperature of 550 K.
Our investigations show that thermo-radiative cells are rather inefficient. In
contrast, an optimized approach to harvest laser energy is achieved by using a
hybrid module consisting of a photovoltaic cell and a thermo-electric
generator. Finally, practical considerations related to infrared power beaming
are discussed and its potential applications are outlined.


  On 21 March 2013 high-resolution slit spectrographs of comet C/2011 L4
(Panstarrs), at the heliocentric distance r = 0.46 Astronomical Units (AU),
were obtained at the Osservatorio Astronomico Campo dei Fiori, Italy. Emission
lines of sodium were the strongest in the spectrum as is common in comets, but
also potassium lines were detected. These have been rarely observed in comets
since the apparition of brightest comet C/1965 S1 (Ikeya-Seki). Lithium was not
detected, and stringent upper limits of its abundance compared to other alkali
were derived. We obtain abundance ratios Na/K = 54 +/-14 and Na/Li > 8000. As
well as in Mercury exosphere (Leblanc & Douressoundiram 2011)}, we show that
photoionization at the beginning of the alkali tails may increase the solar
ratio Na/K = 15.5 (Asplund et al 2009) by a factor 3, close to that required to
match the observed value. In the same tail position the Na/Li ratio increases
by a factor 2 only, very far from the factor > 8 required to match an original
meteoritic ratio. We apply the same model to similar alkali data (Preston 1967)
of comet C/1965 S1 (Ikeya-Seki), obtaining consistent results. An original
solar Na/K ratio fits the observed value at the beginning of the alkali tails
within the slit size, whereas Li is depleted by a factor > 8.


  We tackle a nonlinear optimal control problem for a stochastic differential
equation in Euclidean space and its state-linear counterpart for the
Fokker-Planck-Kolmogorov equation in the space of probabilities. Our approach
is founded on a novel concept of local optimality surpassing Pontryagin's
minimum, originally crafted for deterministic optimal ensemble control
problems. A key practical outcome is a rapidly converging numerical algorithm,
which proves its feasibility for problems involving Markovian and open-loop
strategies.


  As the complexity of deep neural networks (DNNs) trend to grow to absorb the
increasing sizes of data, memory and energy consumption has been receiving more
and more attentions for industrial applications, especially on mobile devices.
This paper presents a novel structure based on functional hashing to compress
DNNs, namely FunHashNN. For each entry in a deep net, FunHashNN uses multiple
low-cost hash functions to fetch values in the compression space, and then
employs a small reconstruction network to recover that entry. The
reconstruction network is plugged into the whole network and trained jointly.
FunHashNN includes the recently proposed HashedNets as a degenerated case, and
benefits from larger value capacity and less reconstruction loss. We further
discuss extensions with dual space hashing and multi-hops. On several benchmark
datasets, FunHashNN demonstrates high compression ratios with little loss on
prediction accuracy.


  In 1995, Stiebitz asked the following question: For any positive integers
$s,t$, is there a finite integer $f(s,t)$ such that every digraph $D$ with
minimum out-degree at least $f(s,t)$ admits a bipartition $(A, B)$ such that
$A$ induces a subdigraph with minimum out-degree at least $s$ and $B$ induces a
subdigraph with minimum out-degree at least $t$? We give an affirmative answer
for tournaments, multipartite tournaments, and digraphs with bounded maximum
in-degrees. In particular, we show that for every $\epsilon$ with
$0<\epsilon<1/2$, there exists an integer $\delta_0$ such that every tournament
with minimum out-degree at least $\delta_0$ admits a bisection $(A, B)$, so
that each vertex has at least $(1/2-\epsilon)$ of its out-neighbors in $A$, and
in $B$ as well.


  Via the BGG correspondence a simplicial complex Delta on [n] is transformed
into a complex of coherent sheaves on P^n-1. We show that this complex reduces
to a coherent sheaf F exactly when the Alexander dual Delta^* is
Cohen-Macaulay. We then determine when both Delta and Delta^* are
Cohen-Macaulay. This corresponds to F being a locally Cohen-Macaulay sheaf.
Lastly we conjecture for which range of invariants of such Delta it must be a
cone.


  We present a comparative multi-wavelength analysis of water maser-emitting
regions and non-maser-emitting luminous 24 micron star-forming regions in the
Andromeda Galaxy (M31) to identify the sites most likely to produce luminous
water masers useful for astrometry and proper motion studies. Included in the
analysis are Spitzer 24 micron photometry, Herschel 70 and 160 micron
photometry, H$\alpha$ emission, dust temperature, and star formation rate. We
find significant differences between the maser-emitting and non-maser-emitting
regions: water maser-emitting regions tend to be more IR-luminous and show
higher star formation rates. The five water masers in M31 are consistent with
being analogs of water masers in Galactic star-forming regions and represent
the high-luminosity tail of a larger (and as yet undetected) population. Most
regions likely to produce water masers bright enough for proper motion
measurements using current facilities have already been surveyed, but we
suggest three ways to detect additional water masers in M31: (1) Re-observe the
most luminous mid- or far-IR sources with higher sensitivity than was used in
the Green Bank Telescope survey; (2) Observe early-stage star-forming regions
selected by mm continuum that have not already been selected by their 24 micron
emission, and (3) Re-observe the most luminous mid- or far-IR sources, and rely
on maser variability for new detections.


  In two previous articles [Phys. Rev. D71 (2005) 124307 (gr-qc/0503007), and
gr-qc/0607001] we have discussed several "algorithmic" techniques that permit
one (in a purely mechanical way) to generate large classes of general
relativistic static perfect fluid spheres. Working in Schwarzschild curvature
coordinates, we used these algorithmic ideas to prove several
"solution-generating theorems" of varying levels of complexity. In the present
article we consider the situation in other coordinate systems: In particular,
in general diagonal coordinates we shall generalize our previous theorems, in
isotropic coordinates we shall encounter a variant of the so-called "Buchdahl
transformation", while in other coordinate systems (such as Gaussian polar
coordinates, Synge isothermal coordinates, and Buchdahl coordinates) we shall
find a number of more complex "Buchdahl-like transformations" and
"solution-generating theorems" that may be used to investigate and classify the
general relativistic static perfect fluid sphere. Finally by returning to
general diagonal coordinates and making a suitable ansatz for the functional
form of the metric components we place the Buchdahl transformation in its most
general possible setting.


  Mining textual patterns in news, tweets, papers, and many other kinds of text
corpora has been an active theme in text mining and NLP research. Previous
studies adopt a dependency parsing-based pattern discovery approach. However,
the parsing results lose rich context around entities in the patterns, and the
process is costly for a corpus of large scale. In this study, we propose a
novel typed textual pattern structure, called meta pattern, which is extended
to a frequent, informative, and precise subsequence pattern in certain context.
We propose an efficient framework, called MetaPAD, which discovers meta
patterns from massive corpora with three techniques: (1) it develops a
context-aware segmentation method to carefully determine the boundaries of
patterns with a learnt pattern quality assessment function, which avoids costly
dependency parsing and generates high-quality patterns; (2) it identifies and
groups synonymous meta patterns from multiple facets---their types, contexts,
and extractions; and (3) it examines type distributions of entities in the
instances extracted by each group of patterns, and looks for appropriate type
levels to make discovered patterns precise. Experiments demonstrate that our
proposed framework discovers high-quality typed textual patterns efficiently
from different genres of massive corpora and facilitates information
extraction.


  Motivated by experiments, we performed a systematic study on the one
dimensional zone center phonons in $O_{h}$ space groups. All the one
dimensional phonon modes for different Wyckoff positions are tabulated. We show
that at least four (inequivalent) atoms (in one set of Wyckoff positions) are
needed to carry a single one dimensional phonon. A general restriction rule on
the number of atoms and the number of one dimensional phonons is obtained. The
same restriction applies to phonons of all cubic crystal systems ($T$, $T_{h}$,
$T_{d}$, $O$, $O_{h}$) and to magnons for crystals whose unitary symmetry
elements are in ($T$, $T_{h}$, $T_{d}$, $O$, $O_{h}$). Crystals with $A15$
structure are found to satisfy experimental requirements (to have a
$\Gamma_{2}^{+}$ phonon) while most crystals of $O_{h}$ space groups do not.
$A15$ is also used to demonstrate the rules we found regarding the phonon
structure in $O_{h}$ space groups.


  Deep learning and big data algorithms have become widely used in industrial
applications to optimize several tasks in many complex systems. Particularly,
deep learning model for diagnosing and prognosing machinery health has
leveraged predictive maintenance (PdM) to be more accurate and reliable in
decision making, in this way avoiding unnecessary interventions, machinery
accidents, and environment catastrophes. Recently, Transformer Neural Networks
have gained notoriety and have been increasingly the favorite choice for
Natural Language Processing (NLP) tasks. Thus, given their recent major
achievements in NLP, this paper proposes the development of an automatic fault
classifier model for predictive maintenance based on a modified version of the
Transformer architecture, namely T4PdM, to identify multiple types of faults in
rotating machinery. Experimental results are developed and presented for the
MaFaulDa and CWRU databases. T4PdM was able to achieve an overall accuracy of
99.98% and 98% for both datasets, respectively. In addition, the performance of
the proposed model is compared to other previously published works. It has
demonstrated the superiority of the model in detecting and classifying faults
in rotating industrial machinery. Therefore, the proposed Transformer-based
model can improve the performance of machinery fault analysis and diagnostic
processes and leverage companies to a new era of the Industry 4.0. In addition,
this methodology can be adapted to any other task of time series
classification.


  For the category of group codes, that generalizes the category of linear
codes over a finite field, and with the generalized notions of direct sums and
ndecomposable group codes, we prove that every MDS non trivial code, every
perfect non trivial code, and every constant weight nondegenerate group code
are indecomposable. We prove that every group code is a direct sum of
indecomposable group codes, and using this result we obtain the automorphism
groups of any group code in terms of its decomposition in indecomposable
components. We conclude with the determination of the structure of decomposable
cyclic group codes.


  Kelvin's Theorem on conservation of circulations is an essential ingredient
of G. I. Taylor's theory of turbulent energy dissipation by the process of
vortex-line stretching. In previous work, we have proposed a nonlinear
mechanism for the breakdown of Kelvin's Theorem in ideal turbulence at infinite
Reynolds number. We develop here a detailed physical theory of this ``cascade
of circulations''. Our analysis is based upon an effective equation for
large-scale ``coarse-grained'' velocity, which contains a turbulent-induced
``vortex-force'' that can violate Kelvin's Theorem. We show that singularities
of sufficient strength, which are observed to exist in turbulent flow, can lead
to non-vanishing dissipation of circulation for an arbitrarily small filtering
length in the effective equations. This result is an analogue for circulation
of Onsager's theorem on energy dissipation for singular Euler solutions. The
physical mechanism of the breakdown of Kelvin's Theorem is diffusion of lines
of large-scale vorticity out of the advected loop. This phenomenon can be
viewed as a classical analogue of the Josephson-Anderson phase-slip phenomenon
in superfluids due to quantized vortex lines. We show that the circulation
cascade is local in scale and use this locality to develop concrete expressions
for the turbulent vortex-force by a multi-scale gradient-expansion. We discuss
implications for Taylor's theory of turbulent dissipation and we point out some
related cascade phenomena, in particular for magnetic-flux in
magnetohydrodynamic (MHD) turbulence.


  The coeffective differential complex on a symplectic manifold is extended
both in length and in scope, unifying the constructions of various other
authors.


  In this paper, we present an efficient visual SLAM system designed to tackle
both short-term and long-term illumination challenges. Our system adopts a
hybrid approach that combines deep learning techniques for feature detection
and matching with traditional backend optimization methods. Specifically, we
propose a unified convolutional neural network (CNN) that simultaneously
extracts keypoints and structural lines. These features are then associated,
matched, triangulated, and optimized in a coupled manner. Additionally, we
introduce a lightweight relocalization pipeline that reuses the built map,
where keypoints, lines, and a structure graph are used to match the query frame
with the map. To enhance the applicability of the proposed system to real-world
robots, we deploy and accelerate the feature detection and matching networks
using C++ and NVIDIA TensorRT. Extensive experiments conducted on various
datasets demonstrate that our system outperforms other state-of-the-art visual
SLAM systems in illumination-challenging environments. Efficiency evaluations
show that our system can run at a rate of 73Hz on a PC and 40Hz on an embedded
platform.


  All of the PT-symmetric potentials that have been studied so far have been
local. In this paper nonlocal PT-symmetric separable potentials of the form
$V(x,y)=i\epsilon[U(x)U(y)-U(-x)U(-y)]$, where $U(x)$ is real, are examined.
Two specific models are examined. In each case it is shown that there is a
parametric region of the coupling strength $\epsilon$ for which the PT symmetry
of the Hamiltonian is unbroken and the bound-state energies are real. The
critical values of $\epsilon$ that bound this region are calculated.


  This article represents a major step in the unification of the theory of
algebraic, topological and singular transition matrices by introducing a
definition which is a generalization that encompasses all of the previous
three. When this more general transition matrix satisfies the additional
requirement that it covers flow-defined Conley-index isomorphisms, one proves
algebraic and connection-existence properties. These general transition
matrices with this covering property are referred to as generalized topological
transition matrices and are used to consider connecting orbits of Morse-Smale
flows without periodic orbits, as well as those in a continuation associated to
a dynamical spectral sequence.


  We propose an approximation scheme for a class of semilinear parabolic
equations that are convex and coercive in their gradients. Such equations arise
often in pricing and portfolio management in incomplete markets and, more
broadly, are directly connected to the representation of solutions to backward
stochastic differential equations. The proposed scheme is based on splitting
the equation in two parts, the first corresponding to a linear parabolic
equation and the second to a Hamilton-Jacobi equation. The solutions of these
two equations are approximated using, respectively, the Feynman-Kac and the
Hopf-Lax formulae. We establish the convergence of the scheme and determine the
convergence rate, combining Krylov's shaking coefficients technique and
Barles-Jakobsen's optimal switching approximation.


  A blockchain is an append-only linked-list of blocks, which is maintained at
each participating node. Each block records a set of transactions and their
associated metadata. Blockchain transactions act on the identical ledger data
stored at each node. Blockchain was first perceived by Satoshi Nakamoto as a
peer-to-peer digital-commodity (also known as crypto-currency) exchange system.
Blockchains received traction due to their inherent property of
immutability-once a block is accepted, it cannot be reverted.


  We present time resolved CCD photometry of 15 cataclysmic variables (CVs)
identified by the Sloan Digital Sky Survey (SDSS). The data were obtained as
part of the 2004/05 International Time Programme on La Palma. We discuss the
morphology of the light curves and the CV subtypes and give accurate orbital
periods for 11 systems. Nine systems are found below the 2-3h orbital period
gap, of which five have periods within a few minutes of the ~80min minimum
orbital period. One system each is found within and above the gap. This
confirms the previously noted trend for a large fraction of short-period
systems among the SDSS CVs. Objects of particular interest are SDSSJ0901+4809
and SDSSJ1250+6655 which are deeply eclipsing. SDSSJ0854+3905 is a polar with
an extremely modulated light curve, which is likely due to a mixture of
cyclotron beaming and eclipses of the accretion region by the white dwarf. One
out of five systems with white-dwarf dominated optical spectra exhibits
non-radial pulsations.


  Recent observations of the deeply embedded L1551 IRS5 system permit the
detailed examination of the properties of both the stellar binary and the
binary jet. For the individual components of the stellar binary, we determine
their masses, mass accretion rates, effective temperatures and luminosities.
For the atomic wind/jet flow, we determine the mass loss rate, yielding
observationally determined values of the ratio of the mass loss to the mass
accretion rate, f. For the X-ray emitting region in the northern jet, we have
obtained the jet-velocity and derive the extinction and the densities on
different spatial scales. Examining the observational evidence within the
framework of the x-wind theory leads us to conclude that these models are
indeed potentially able to account for the observational data for this deeply
embedded source.


  Photophoretic force due to the optically-induced thermal effect provides an
effective way to manipulate the light-absorbing particles suspended in ambient
gases. However, how this force temporally responds to the intensity modulation
of the illumination light is unclear. Here, by vertically trapping a
micron-sized absorbing particle with a negative photophoretic force generated
by a focused Gaussian beam, we demonstrate that the temporal change in the
photophoretic force in response to the intensity modulation is remarkably slow
(with a time constant up to ~1 s) due to the slow change in the particle's
temperature. When the trapping beam is turned off for a few tens or hundreds of
milliseconds, the trapped particle is found to be pulled up towards the light
source by the remained photophoretic force, whereas when the intensity of the
trapping beam is increased for a short duration, the particle is pushed off by
the radiation pressure. The instantaneous position of the trapped particles
following the intensity modulation of the trapping laser is tracked and
theoretically modeled. The understanding of the temporal behavior of the
photophoretic force would be useful for the control of photophoretic-based
optical pulling, transportation, and manipulation of atmospheric particles.


  Artificial Intelligence and Digital Twins play an integral role in driving
innovation in the domain of intelligent driving. Long short-term memory (LSTM)
is a leading driver in the field of lane change prediction for manoeuvre
anticipation. However, the decision-making process of such models is complex
and non-transparent, hence reducing the trustworthiness of the smart solution.
This work presents an innovative approach and a technical implementation for
explaining lane change predictions of layer normalized LSTMs using Layer-wise
Relevance Propagation (LRP). The core implementation includes consuming live
data from a digital twin on a German highway, live predictions and explanations
of lane changes by extending LRP to layer normalized LSTMs, and an interface
for communicating and explaining the predictions to a human user. We aim to
demonstrate faithful, understandable, and adaptable explanations of lane change
prediction to increase the adoption and trustworthiness of AI systems that
involve humans. Our research also emphases that explainability and
state-of-the-art performance of ML models for manoeuvre anticipation go hand in
hand without negatively affecting predictive effectiveness.


  Automated test generation has helped to reduce the cost of software testing.
However, developing effective test oracles for these automatically generated
test inputs is a challenging task. Therefore, most automated test generation
tools use trivial oracles that reduce the fault detection effectiveness of
these automatically generated test cases. In this work, we provide results of
an empirical study showing that utilizing metamorphic relations can increase
the fault detection effectiveness of automatically generated test cases.


  We discuss the codimension-1 defects of (2+1)D bosonic topological phases,
where the defects can support fermionic degrees of freedom. We refer to such
defects as fermionic defects, and introduce a certain subclass of invertible
fermionic defects called "gauged Gu-Wen SPT defects" that can shift
self-statistics of anyons. We derive a canonical form of a general fermionic
invertible defect, in terms of the fusion of a gauged Gu-Wen SPT defect and a
bosonic invertible defect decoupled from fermions on the defect. We then derive
the fusion rule of generic invertible fermionic defects. The gauged Gu-Wen SPT
defects give rise to interesting logical gates of stabilizer codes in the
presence of additional ancilla fermions. For example, we find a realization of
the CZ logical gate on the (2+1)D $\mathbb{Z}_2$ toric code stacked with a
(2+1)D ancilla trivial atomic insulator, which is implemented by a finite depth
circuit. We also investigate a gapped fermionic interface between (2+1)D
bosonic topological phases realized on the boundary of the (3+1)D Walker-Wang
model. In that case, the gapped interface can shift the chiral central charge
of the (2+1)D phase. Among these fermionic interfaces, we study an interesting
example where the (3+1)D phase has a spatial reflection symmetry, and the
fermionic interface is supported on a reflection plane that interpolates a
(2+1)D surface topological order and its orientation-reversal. We construct a
(3+1)D exactly solvable Hamiltonian realizing this setup, and find that the
model generates the $\mathbb{Z}_8$ classification of the (3+1)D invertible
phase with spatial reflection symmetry and fermion parity on the reflection
plane. We make contact with an effective field theory, known in literature as
the exotic invertible phase with spacetime higher-group symmetry.


  Focus of this work is to recognize standards and further features directly
from 3D CAD models. For this reason, a neural network was trained to recognize
nine classes of machine elements. After the system identified a part as a
standard, like a hexagon head screw after the DIN EN ISO 8676, it accesses the
geometrical information of the CAD system via the Application Programming
Interface (API). In the API, the system searches for necessary information to
describe the part appropriately. Based on this information standardized parts
can be recognized in detail and supplemented with further information.


  In this paper we first obtain Friedmann equations for the $(n-1)$-dimensional
brane embedded in the $(n+1)$-dimensional bulk, with intrinsic curvature term
of the brane included in the action (DGP model). Then, we show that one can
always rewrite the Friedmann equations in the form of the first law of
thermodynamics, $dE=TdS+WdV$, at apparent horizon on the brane, regardless of
whether there is the intrinsic curvature term on the brane or a cosmological
constant in the bulk. Using the first law, we extract the entropy expression of
the apparent horizon on the brane. We also show that in the case without the
intrinsic curvature term, the entropy expressions are the same by using the
apparent horizon on the brane and by using the bulk geometry. When the
intrinsic curvature appears, the entropy of apparent horizon on the brane has
two parts, one part follows the $n$-dimensional area formula on the brane, and
the other part is the same as the entropy in the case without the intrinsic
curvature term. As an interesting result, in the warped DGP model, the entropy
expression in the bulk and on the brane are not the same. This is reasonable,
since in this model gravity on the brane has two parts, one induced from the
$(n+1)$-dimensional bulk gravity and the other due to the intrinsic curvature
term on the brane.


  Recent developments in face restoration have achieved remarkable results in
producing high-quality and lifelike outputs. The stunning results however often
fail to be faithful with respect to the identity of the person as the models
lack necessary context. In this paper, we explore the potential of personalized
face restoration with diffusion models. In our approach a restoration model is
personalized using a few images of the identity, leading to tailored
restoration with respect to the identity while retaining fine-grained details.
By using independent trainable blocks for personalization, the rich prior of a
base restoration model can be exploited to its fullest. To avoid the model
relying on parts of identity left in the conditioning low-quality images, a
generative regularizer is employed. With a learnable parameter, the model
learns to balance between the details generated based on the input image and
the degree of personalization. Moreover, we improve the training pipeline of
face restoration models to enable an alignment-free approach. We showcase the
robust capabilities of our approach in several real-world scenarios with
multiple identities, demonstrating our method's ability to generate
fine-grained details with faithful restoration. In the user study we evaluate
the perceptual quality and faithfulness of the genereated details, with our
method being voted best 61% of the time compared to the second best with 25% of
the votes.


  Canonical correlation analysis is a family of multivariate statistical
methods for the analysis of paired sets of variables. Since its proposition,
canonical correlation analysis has for instance been extended to extract
relations between two sets of variables when the sample size is insufficient in
relation to the data dimensionality, when the relations have been considered to
be non-linear, and when the dimensionality is too large for human
interpretation. This tutorial explains the theory of canonical correlation
analysis including its regularised, kernel, and sparse variants. Additionally,
the deep and Bayesian CCA extensions are briefly reviewed. Together with the
numerical examples, this overview provides a coherent compendium on the
applicability of the variants of canonical correlation analysis. By bringing
together techniques for solving the optimisation problems, evaluating the
statistical significance and generalisability of the canonical correlation
model, and interpreting the relations, we hope that this article can serve as a
hands-on tool for applying canonical correlation methods in data analysis.


  Self-gravitating accretion discs in a gravitoturbulent state, including
radiation and gas pressures, are studied using a set of new analytical
solutions. While the Toomre parameter of the disc remains close to its critical
value for the onset of gravitational instability, the dimensionless stress
parameter is uniquely determined from the thermal energy reservoir of the disc
and its cooling rate. Our solutions are applicable to the accretion discs with
dynamically important radiation pressure like in the quasars discs. We show
that physical quantities of a gravitoturbulent disc in the presence of
radiation are significantly modified compared to solutions with only gas
pressure. We show that the dimensionless stress parameter is an increasing
function of the radial distance so that its steepness strongly depends on the
accretion rate. In a disc without radiation its slope is 4.5, however, we show
that in the presence of radiation, it varies between 2 and 4.5 depending on the
accretion rate and the central mass. As for the surface density, we find a
shallower profile with an exponent -2 in a disc with sub-Eddington accretion
rate compared to a similar disc, but without radiation, where its surface
density slope is -3 independent of the accretion rate. We then investigate
gravitational stability of the disc when the stress parameter reaches to its
critical value. In order to self-consistently determine the fragmentation
boundary, however, it is shown that the critical value of the stress parameter
is a power-law function of the ratio of gas pressure and the total pressure and
its exponent is around 1.7. We also estimate the maximum mass of the central
black hole using our analytical solutions.


  The in-situ metalorganic chemical vapor deposition (MOCVD) growth of
Al$_2$O$_3$ dielectrics on $\beta$-Ga$_2$O$_3$ and
$\beta$-(Al$_x$Ga$_{1-x}$)$_2$O$_3$ films is investigated as a function of
crystal orientations and Al compositions of $\beta$-(Al$_x$Ga$_{1-x}$)$_2$O$_3$
films. The interface and film qualities of Al$_2$O$_3$ dielectrics are
evaluated by high resolution X-ray diffraction (HR-XRD) and scanning
transmission electron microscopy (HR-STEM) imaging, which indicate the growth
of high quality amorphous Al$_2$O$_3$ dielectrics with abrupt interfaces on
(010), (100) and (-201) oriented $\beta$-(Al$_x$Ga$_{1-x}$)$_2$O$_3$ films. The
surface stoichiometries of Al$_2$O$_3$ deposited on all orientations of
$\beta$-(Al$_x$Ga$_{1-x}$)$_2$O$_3$ are found to be well maintained with a
bandgap energy of 6.91 eV as evaluated by high resolution x-ray photoelectron
spectroscopy, which is consistent with the atomic layer deposited (ALD)
Al$_2$O$_3$ dielectrics. The evolution of band offsets at both in-situ MOCVD
and ex-situ ALD deposited Al$_2$O$_3$/$\beta$-(Al$_x$Ga$_{1-x}$)$_2$O$_3$ are
determined as a function of Al composition, indicating the influence of the
deposition method, orientation, and Al composition of
$\beta$-(Al$_x$Ga$_{1-x}$)$_2$O$_3$ films on resulting band alignments. Type II
band alignments are determined at the MOCVD grown
Al$_2$O$_3$/$\beta$-(Al$_x$Ga$_{1-x}$)$_2$O$_3$ interfaces for (010) and (100)
orientations, whereas type I band alignments with relatively lower conduction
band offsets are observed along (-201) orientation. Results from this work
revealed that the in-situ MOCVD deposited high quality Al$_2$O$_3$ dielectrics
with sharp interfaces can be considered as a viable alternative of commonly
used ex-situ deposited (ALD) Al$_2$O$_3$ for developing high performance
$\beta$-Ga$_2$O$_3$ and $\beta$-(Al$_x$Ga$_{1-x}$)$_2$O$_3$ based devices.


  We study here the behavior of the solutions to a $2\times 2$ semi-linear
cooperative system involving Schr\" odinger operators (considered in its
variational form): $$LU:=(-\Delta + q(x))U = AU+\mu U + F(x,U) \quad{\rm in}\
\mathbb{R}^N$$ $$U(x)_{|x|\rightarrow \infty} \rightarrow 0$$ where $q$ is a
continuous positive potential tending to $+\infty$ at infinity; $\mu$ is a real
parameter varying near the principal eigenvalue of the system; $U$ is a column
vector with components $u_1$ and $u_2$ and $A$ is a square cooperative matrix
with constant coefficient. $F$ is a column vector with components $f_1$ and
$f_2$ depending eventually on $U$.


  This paper is concerned with the deployment of multiple mobile robots in
order to autonomously cover a region Q. The region to be covered is described
using a density function which may not be apriori known. In this paper, we pose
the coverage problem as an optimization problem over some space of functions on
Q. In particular, we look at L 2 -distance based coverage algorithm and derive
adaptive control laws for the same. We also propose a modified adaptive control
law incorporating consensus for better parameter convergence. We implement the
algorithms on real differential drive robots with both simulated density
function as well as density function implemented using light sources. We also
compare the L 2 -distance based method with the locational optimization method
using experiments.


  The littlest Higgs model is the most economical one among various little
Higgs models. In the context of the littlest Higgs(LH) model, we study the
process $e^{-}\gamma\to \nu_{e}W^{-}H$ and calculate the contributions of the
LH model to the cross section of this process. The results show that, in most
of parameter spaces preferred by the electroweak precision data, the value of
the relative correction is larger than 10%. Such correction to the process
$e^{-}\gamma\to \nu_{e}W^{-}H$ is large enough to be detected via $e^{-}\gamma$
collisions in the future high energy linear $e^{+}e^{-}$ collider($LC$)
experiment with the c.m energy $\sqrt{s}$=500 GeV and a yearly integrated
luminosity $\pounds=100fb^{-1}$, which will give an ideal way to test the
model.


  We consider QCD radiative corrections to the production of a heavy-quark pair
in hadronic collisions. We present the computation of the soft-parton
contributions at low transverse momentum of the heavy-quark pair up to second
order in the QCD coupling $\alpha_s$. These results complete the evaluation at
the next-to-next-to-leading order (NNLO) of the transverse-momentum resummation
formula for this process. Moreover, they give all the ingredients that are
needed for the NNLO implementation of the qT subtraction formalism for
heavy-quark production. We discuss the details of the computation and we
provide a code that can be used to obtain the relevant results in numerical
form.


  We study the nature of the hidden charm pentaquarks, i.e. the $P_c(4312)$,
$P_c(4440)$ and $P_c(4457)$, with a neural network approach in pionless
effective field theory. In this framework, the normal $\chi^2$ fitting approach
cannot distinguish the quantum numbers of the $P_c(4440)$ and $P_c(4457)$. In
contrast to that, the neural network-based approach can discriminate them. In
addition, we also illustrate the role of each experimental data bin of the
invariant $J/\psi p$ mass distribution on the underlying physics in both neural
network and fitting methods. Their similarities and differences demonstrate
that neural network methods can use data information more effectively and
directly. This study provides more insights about how the neural network-based
approach predicts the nature of exotic states from the mass spectrum.


  In this paper we complete the proof of the existence of multiple solutions
(and, in particular, non minimal ones), to the epsilon-Dirichlet problem
obtained as a variational problem for the SU(2)-epsilon-Yang Mills functional.
This is equivalent to proving the existence of multiple solutions to the
Dirichlet problem for the SU(2)-Yang Mills functional with small boundary data.
In the first paper of this series this non-compact variational problem is
transformed into the finite dimensional problem of finding the critical points
of the function J(q), which is essentially the Yang Mills functional evaluated
on the approximate solutions, constructed via a gluing technique. In the
present paper, we establish a Morse theory for this function, by means of
Ljusternik-Schnirelmann theory, thus complete the proofs of the existence
theorems (Theorems 1-3).


  We introduce the spectral influence and spectral cyclicality based on the
largest eigenvalue of a graph adjacency matrix, two novel concepts of
centrality capturing diffusion and interdependence from a local and a global
point of view respectively. We define a new clustering algorithm to distinguish
communities with high cyclicality and interdependence, allowing overlapping,
and we conclude our study with an application to the input-output analysis in
the case of the Moroccan economy.


  Advanced driver assistance systems (ADAS) relying on multiple cameras are
increasingly prevalent in vehicle technology. Yet, conventional imaging sensors
struggle to capture clear images in conditions with intense illumination
contrast, such as tunnel exits, due to their limited dynamic range. Introducing
high dynamic range (HDR) sensors addresses this issue. However, the process of
converting HDR content to a displayable range via tone mapping often leads to
inefficient computations, when performed directly on pixel data. In this paper,
we focus on HDR image tone mapping using a lightweight neural network applied
on image histogram data. Our proposed TinyML-based global tone mapping method,
termed as TGTM, operates at 9,000 FLOPS per RGB image of any resolution.
Additionally, TGTM offers a generic approach that can be incorporated to any
classical tone mapping method. Experimental results demonstrate that TGTM
outperforms state-of-the-art methods on real HDR camera images by up to 5.85 dB
higher PSNR with orders of magnitude less computations.


  Anisotropic dark energy model with dynamic pressure anisotropies along
different spatial directions is constructed at the backdrop of a spatially
homogeneous diagonal Bianchi type $V$ $(BV)$ space-time in the framework of
General Relativity. A time varying deceleration parameter generating a hybrid
scale factor is considered to simulate a cosmic transition from early
deceleration to late time acceleration. We found that the pressure anisotropies
along the $y-$ and $z-$ axes evolve dynamically and continue along with the
cosmic expansion without being subsided even at late times. The anisotropic
pressure along the $x-$axis becomes equal to the mean fluid pressure. At a late
phase of cosmic evolution, the model enters into a phantom region. From a state
finder diagnosis, it is found that the model overlaps with $\Lambda$CDM at late
phase of cosmic time.


  We theoretically study valley-filtering in pristine graphene irradiated by
bicircular counter-rotating laser drive. The dynamical symmetry of the graphene
and laser drive disrupts graphene's inversion symmetry, which results distinct
quasi-energy states and Floquet band occupations in the two valleys.
Controlling the relative phase between the bicircular laser drive ultimately
allows to blocks the contribution from one valley while allowing the opposite
valley currents in the system. For practical realization of valley-based
device, we propose configurational setup for valley filters and valley valve
consisting of two graphene nanoribbons irradiated by two bicircular
counter-rotating laser drives with a relative phase shift. It is observed that
the relative phase between the two bicircular laser drives offer a control knob
to generate valley-selective currents and transport responses with very high
efficiency by an all-optical way. In addition, our findings about valley filter
and valley valve are robust against moderate disorder and modest changes in
driving laser parameters. Present work opens an avenue to realise light-based
valleytronics devices in reality.


  An implementation of full self-consistency over the electronic density in the
DFT+DMFT framework on the basis of a plane wave-projector augmented wave (PAW)
DFT code is presented. It allows for an accurate calculation of the total
energy in DFT+DMFT within a plane wave approach. In contrast to frameworks
based on the maximally localized Wannier function, the method is easily applied
to f electron systems, such as cerium, cerium oxide (Ce2O3) and plutonium oxide
(Pu2O3). In order to have a correct and physical calculation of the energy
terms, we find that the calculation of the self-consistent density is
mandatory. The formalism is general and does not depend on the method used to
solve the impurity model. Calculations are carried out within the Hubbard I
approximation, which is fast to solve, and gives a good description of strongly
correlated insulators. We compare the DFT+DMFT and DFT+U solutions, and
underline the qualitative differences of their converged densities. We
emphasize that in contrast to DFT+U, DFT+DMFT does not break the spin and
orbital symmetry. As a consequence, DFT+DMFT implies, on top of a better
physical description of correlated metals and insulators, a reduced occurrence
of unphysical metastable solutions in correlated insulators in comparison to
DFT+U.


  Training networks to perform metric relocalization traditionally requires
accurate image correspondences. In practice, these are obtained by restricting
domain coverage, employing additional sensors, or capturing large multi-view
datasets. We instead propose a self-supervised solution, which exploits a key
insight: localizing a query image within a map should yield the same absolute
pose, regardless of the reference image used for registration. Guided by this
intuition, we derive a novel transform consistency loss. Using this loss
function, we train a deep neural network to infer dense feature and saliency
maps to perform robust metric relocalization in dynamic environments. We
evaluate our framework on synthetic and real-world data, showing our approach
outperforms other supervised methods when a limited amount of ground-truth
information is available.


  The capacity of the linear time-varying (LTV) channel, a continuous-time LTV
filter with additive white Gaussian noise, is characterized by waterfilling in
the time-frequency plane. Similarly, the rate distortion function for a related
nonstationary source is characterized by reverse waterfilling in the
time-frequency plane. Constraints on the average energy or on the squared-error
distortion, respectively, are used. The source is formed by the white Gaussian
noise response of the same LTV filter as before. The proofs of both
waterfilling theorems rely on a Szego theorem for a class of operators
associated with the filter. A self-contained proof of the Szego theorem is
given. The waterfilling theorems compare well with the classical results of
Gallager and Berger. In the case of a nonstationary source, it is observed that
the part of the classical power spectral density is taken by the Wigner-Ville
spectrum. The present approach is based on the spread Weyl symbol of the LTV
filter, and is asymptotic in nature. For the spreading factor, a lower bound is
suggested by means of an uncertainty inequality.


  The density of states of Dirac fermions with a random mass on a
two-dimensional lattice is considered. We give the explicit asymptotic form of
the single-electron density of states as a function of both energy and
(average) Dirac mass, in the regime where all states are localized. We make use
of a weak-disorder expansion in the parameter g/m^2, where g is the strength of
disorder and m the average Dirac mass for the case in which the evaluation of
the (supersymmetric) integrals corresponds to non-uniform solutions of the
saddle point equation. The resulting density of states has tails which deviate
from the typical pure Gaussian form by an analytic prefactor.


  We report on new 1.41 GHz Green Bank Telescope and 352 MHz Westerbork
Synthesis Radio Telescope observations of the Coma cluster and its environs. At
1.41 GHz we tentatively detect an extension to the Coma cluster radio relic
source 1253+275 which makes its total extent ~2 Mpc. This extended relic is
linearly polarized as seen in our GBT data, the NVSS, and archival images,
strengthening a shock interpretation. The extended relic borders a previously
undetected "wall" of galaxies in the infall region of the Coma cluster. We
suggest that the radio relic is an infall shock, as opposed to the outgoing
merger shocks believed responsible for other radio relics. We also find a sharp
edge, or "front", on the western side of the 352 MHz radio halo. This front is
coincident with a similar discontinuity in the X-ray surface brightness and
temperature in its southern half, suggesting a primary shock-acceleration
origin for the local synchrotron emitting electrons. The northern half of the
synchrotron front is less well correlated with the X-ray properties, perhaps
due to projection effects. We confirm the global pixel-to-pixel power-law
correlation between the 352 MHz radio brightness and X-ray brightness with a
slope that is inconsistent with predictions of either primary shock
acceleration or secondary production of relativistic electrons in Giant Radio
Halos, but is allowable in the framework of the turbulent re-acceleration of
relic plasma. The failure of these first order models and the need for a more
comprehensive view of the intracluster medium energization is also highlighted
by the very different shapes of the diffuse radio and X-ray emission. We note
the puzzling correspondence between the shape of the brighter regions of the
radio halo and the surface mass density derived from weak lensing.


  Generative models such as generative adversarial networks and autoencoders
have gained a great deal of attention in the medical field due to their
excellent data generation capability. This paper provides a comprehensive
survey of generative models for three-dimensional (3D) volumes, focusing on the
brain and heart. A new and elaborate taxonomy of unconditional and conditional
generative models is proposed to cover diverse medical tasks for the brain and
heart: unconditional synthesis, classification, conditional synthesis,
segmentation, denoising, detection, and registration. We provide relevant
background, examine each task and also suggest potential future directions. A
list of the latest publications will be updated on Github to keep up with the
rapid influx of papers at
https://github.com/csyanbin/3D-Medical-Generative-Survey.


  If detected, dark matter particles such as WIMPs and sterile neutrinos will
be the earliest relics we can study, the first coming from before Big Bang
Nucleosynthesis, an epoch from which we have no data so far. Here we discuss
how different pre-BBN cosmological models affect the properties of these
particles, and how these properties could thus allow to determine the evolution
of the Universe before BBN.


  We bound the smoothed running time of the FLIP algorithm for local Max-Cut as
a function of $\alpha$, the arboricity of the input graph. We show that, with
high probability and in expectation, the following holds (where $n$ is the
number of nodes and $\phi$ is the smoothing parameter):
  1) When $\alpha = O(\log^{1-\delta} n)$ FLIP terminates in $\phi poly(n)$
iterations, where $\delta \in (0,1]$ is an arbitrarily small constant. Previous
to our results the only graph families for which FLIP was known to achieve a
smoothed polynomial running time were complete graphs and graphs with
logarithmic maximum degree.
  2) For arbitrary values of $\alpha$ we get a running time of $\phi
n^{O(\frac{\alpha}{\log n} + \log \alpha)}$. This improves over the best known
running time for general graphs of $\phi n^{O(\sqrt{ \log n })}$ for $\alpha =
o(\log^{1.5} n)$. Specifically, when $\alpha = O(\log n)$ we get a
significantly faster running time of $\phi n^{O(\log \log n)}$.


  It is proposed that the vacuum admits two different phases as described by
the Chaplygin equation of state or its generalised version: a phase where the
energy density behaves as if dominated by non-relativistic matter and a de
Sitter phase. The particle production due to the expansion that takes place at
the matter-like phase can generate entanglement entropy and provide, through
interactions, the environment that turn gravitational quantum features into
classical ones. In the ensued de Sitter phase, the cosmological constant can be
suppressed by inflation.


  Instabilities are predicted for a sufficiently long hollow photonic optical
fiber, or "cavity", containing a one dimensional Bose-gas in the presence of a
classical, far red-detuned, confined weak electromagnetic mode. We examine both
a single beam with Bose gas (a type of Brillouin instability) and the case of a
standing wave, or optical lattice. The instabilities of these driven systems
have pronounced spatial structure, of combined modulational instabilities in
the electromagnetic and Bose density fields. Near the critical wave vectors for
the instability the coupled modes of the BEC and light can be interpreted as
"phonons" of the optical lattice. We conjecture these spatially-structured
instabilities for the optical lattice, which we predict at weak fields, develop
into the source of spatially homogeneous heating predicted for strong fields.


  The complexity of large language model (LLM) serving workloads has
substantially increased due to the integration with external tool invocations,
such as ChatGPT plugins. In this paper, we identify a new opportunity for
efficient LLM serving for requests that trigger tools: tool partial execution
alongside LLM decoding. To this end, we design Conveyor, an efficient LLM
serving system optimized for handling requests involving external tools. We
introduce a novel interface for tool developers to expose partial execution
opportunities to the LLM serving system and a request scheduler that
facilitates partial tool execution. Our results demonstrate that tool partial
execution can improve request completion latency by up to 38.8%.


  We prove necessary and sufficient conditions for the weak-$L^p$ boundedness,
for $p \in (1,\infty)$, of a maximal operator on the infinite-dimensional
torus. In the endpoint case $p=1$ we obtain the same weak-type inequality
enjoyed by the strong maximal function in dimension two. Our results are
quantitatively sharp.


  Proteins are the "work horses" in biological systems. In almost all functions
specific proteins are involved. They control molecular transport processes,
stabilize the cell structure, enzymatically catalyze chemical reactions; others
act as molecular motors in the complex machinery of molecular synthetization
processes. Due to their significance, misfolds and malfunctions of proteins
typically entail disastrous diseases, such as Alzheimer's disease and bovine
spongiform encephalopathy (BSE). Therefore, the understanding of the trinity of
amino acid composition, geometric structure, and biological function is one of
the most essential challenges for the natural sciences. Here, we glance at
conformational transitions accompanying the structure formation in protein
folding processes.


  We study the implications of $R^n$ extension of Starobinsky model on
dynamical instability of Vorticity-free axially symmetric gravitating body. The
matter distribution is considered to be anisotropic for which modified field
equations are formed in context of $f(R)$ gravity. In order to achieve the
collapse equation, we make use of the dynamical equations, extracted from
linearly perturbed contracted Bianchi identities. The collapse equation carries
adiabatic index $\Gamma$ in terms of usual and dark source components, defining
the range of stability/insatbility in Newtonian (N) and post-Newtonian (pN)
eras. It is found that supersymmetric supergravity $f(R)$ model represents the
more practical substitute of higher order curvature corrections.


  In this paper, we give a complete classification of symplectic structures on
six-dimensional Frobeniusian solvable Lie algebras, up to symplectomorphism. We
provide a scheme to classify the isomorphism classes of six-dimensional
Frobeniusian solvable Lie algebras whose exact form has a Lagrangian ideal. We
complete our classification by considering Frobeniusian solvable Lie algebras
without Lagrangian ideal.


  We address the impact of sterile fermions on charged lepton electric dipole
moments. We show that in order to have a non-vanishing contribution to electric
dipole moments, the minimal extension necessitates the addition of at least two
sterile fermion states. Sterile neutrinos can give significant contributions to
the charged lepton electric dipole moments if the masses of the non-degenerate
sterile states are both above the electroweak scale. In addition, the Majorana
nature of neutrinos is also important. Furthermore, we apply the computations
of the electric dipole moments for the most minimal realisation of the Inverse
Seesaw mechanism, in which the Standard Model is extended by two right-handed
neutrinos and two sterile fermion states. We show that the two pairs of (heavy)
pseudo-Dirac mass eigenstates can give significant contributions to the
electron electric dipole moment, lying close to future experimental
sensitivity. We further discuss the possibility of beyond the minimal Inverse
Seesaw models and of having a successful leptogenesis in this framework.


  This paper proposes a parallel in time (called also time parareal) method to
solve Volterra integral equations of the second kind. The parallel in time
approach follows the same spirit as the domain decomposition that consists of
breaking the domain of computation into subdomains and solving iteratively the
sub-problems in a parallel way. To obtain high order of accuracy, a spectral
collocation accuracy enhancement in subdomains will be employed. Our main
contributions in this work are two folds: (i) a time parareal method is
designed for the integral equations, which to our knowledge is the first of its
kind. The new method is an iterative process combining a coarse prediction in
the whole domain with fine corrections in subdomains by using spectral
approximation, leading to an algorithm of very high accuracy; (ii) a rigorous
convergence analysis of the overall method is provided. The numerical
experiment confirms that the overall computational cost is considerably reduced
while the desired spectral rate of convergence can be obtained.


  The maximum independent set problem is known to be NP-hard in the class of
subcubic graphs, i.e. graphs of vertex degree at most 3. We present a
polynomial-time solution in a subclass of subcubic graphs generalizing several
previously known results.


  The concept of \emph{complexity} has become pivotal in multiple disciplines,
including quantum information, where it serves as an alternative metric for
gauging the chaotic evolution of a quantum state. This paper focuses on
\emph{Krylov complexity}, a specialized form of quantum complexity that offers
an unambiguous and intrinsically meaningful assessment of the spread of a
quantum state over all possible orthogonal bases. Our study is situated in the
context of Gaussian quantum states, which are fundamental to both Bosonic and
Fermionic systems and can be fully described by a covariance matrix. We show
that while the covariance matrix is essential, it is insufficient alone for
calculating Krylov complexity due to its lack of relative phase information.
Our findings suggest that the relative covariance matrix can provide an upper
bound for Krylov complexity for Gaussian quantum states. We also explore the
implications of Krylov complexity for theories proposing complexity as a
candidate for holographic duality by computing Krylov complexity for the
thermofield double States (TFD) and Dirac field.


  With the rapid development of network-based services and applications,
current data plane solutions of network node, which focus on packets forwarding
traditionally, are not optimally addressing new requirements such as function
flexibility, performance expansibility and resource utilization, etc. In this
paper, we propose a novel data plane structure called Resource Pooling Switch
Architecture (RPSA), which utilizes global shared resource pool to provide
different processing functionalities and capacities to different packets/flows.
As all network functions are instantiated by the resources connected to the
switching fabric and constructed in the form of Service Function Chains (SFC),
the traffic patterns changed a lot. We design Balanced Service Capacity based
FIRM algorithm (BSC-FIRM) to overcome the deficiencies of classical scheduler
in RPSA. Simulation results show that our algorithm outperforms on the aspect
of packet switching delay and loss rate compared with FIRM and iSLIP algorithm.


  We report detailed dc and ac magnetic susceptibilities, specific heat, and
thermal conductivity measurements on the frustrated magnet ZnCr$_2$Se$_4$. At
low temperatures, with increasing magnetic field, this spinel material goes
through a series of spin state transitions from the helix spin state to the
spiral spin state and then to the fully polarized state. Our results indicate a
direct quantum phase transition from the spiral spin state to the fully
polarized state. As the system approaches the quantum criticality, we find
strong quantum fluctuations of the spins with the behaviors such as an
unconventional $T^2$-dependent specific heat and temperature independent mean
free path for the thermal transport. We complete the full phase diagram of
ZnCr$_2$Se$_4$ under the external magnetic field and propose the possibility of
frustrated quantum criticality with extended densities of critical modes to
account for the unusual low-energy excitations in the vicinity of the
criticality. Our results reveal that ZnCr$_2$Se$_4$ is a rare example of 3D
magnet exhibiting a field-driven quantum criticality with unconventional
properties.


  We calculate ion distributions near a planar oil-water interface within
non-linear Poisson-Boltzmann theory, taking into account the Born self-energy
of the ions in the two media. For unequal self-energies of cations and anions,
a spontaneous charge separation is found such that the water and oil phase
become oppositely charged, in slabs with a typical thickness of the Debye
screening length in the two media. From the analytical solutions, the
corresponding interfacial charge density and the contribution to the
interfacial tension is derived, together with an estimate for the
Yukawa-potential between two spherical water droplets in oil. The parameter
regime is explored where the plasma coupling parameter exceeds the
crystallization threshold, i.e. where the droplets are expected to form
crystalline structures due to a strong Yukawa repulsion, as recently observed
experimentally. Extensions of the theory that we discuss briefly include
numerical calculations on spherical water droplets in oil, and analytical
calculations of the linear PB-equation for a finite oil-water interfacial
width.


  We study incentive designs for a class of stochastic Stackelberg games with
one leader and a large number of (finite as well as infinite population of)
followers. We investigate whether the leader can craft a strategy under a
dynamic information structure that induces a desired behavior among the
followers. For the finite population setting, under convexity of the leader's
cost and other sufficient conditions, we show that there exist symmetric
\emph{incentive} strategies for the leader that attain approximately optimal
performance from the leader's viewpoint and lead to an approximate symmetric
(pure) Nash best response among the followers. Leveraging functional analytic
tools, we further show that there exists a symmetric incentive strategy, which
is affine in the dynamic part of the leader's information, comprising partial
information on the actions taken by the followers. Driving the follower
population to infinity, we arrive at the interesting result that in this
infinite-population regime the leader cannot design a smooth ``finite-energy''
incentive strategy, namely, a mean-field limit for such games is not
well-defined. As a way around this, we introduce a class of stochastic
Stackelberg games with a leader, a major follower, and a finite or infinite
population of minor followers. For this class of problems, we establish the
existence of an incentive strategy and the corresponding mean-field Stackelberg
game. Examples of quadratic Gaussian games are provided to illustrate both
positive and negative results. In addition, as a byproduct of our analysis, we
establish the existence of a randomized incentive strategy for the class
mean-field Stackelberg games, which in turn provides an approximation for an
incentive strategy of the corresponding finite population Stackelberg game.


  We report mid- to far-infrared imaging and photomety from 7 to 37 microns
with SOFIA/FORCAST and 2 micron adaptive optics imaging with LBTI/LMIRCam of a
large sample of red supergiants (RSGs) in four Galactic clusters; RSGC1,
RSGC2=Stephenson 2, RSGC3, and NGC 7419. The red supergiants in these clusters
cover their expected range in luminosity and initial mass from approximately 9
to more than 25 Solar masses. The population includes examples of very
late-type RSGs such as MY Cep which may be near the end of the RSG stage, high
mass losing maser sources, yellow hypergiants and post-RSG candidates. Many of
the stars and almost all of the most luminous have spectral energy
distributions (SEDs) with extended infrared excess radiation at the longest
wavelengths. To best model their SEDs we use DUSTY with a variable radial
density distribution function to estimate their mass loss rates. Our mass loss
rate -- luminosity relation for 42 RSGs basically follows the classical de
Jager curve, but at luminosities below 10^5 Solar luminosities we find a
significant population of red supergiants with mass loss rate below the de
Jager relation. At luminosities above 10^5 Solar luminosities there is a rapid
transition to higher mass loss rates that approximates and overlaps the de
Jager curve. We recommend that instead of using a linear relation or single
curve, the empirical mass loss rate -- luminosity relation is better
represented by a broad band. Interestingly, the transition to much higher mass
loss rates at about 10^5 Lsun corresponds approximately to an initial mass of
18 --20 Msun which is close to the upper limit for RSGs becoming Type II SNe.


  A formalism for describing the dynamics of Genetic Algorithms (GAs) using
methods from statistical mechanics is applied to the problem of generalization
in a perceptron with binary weights. The dynamics are solved for the case where
a new batch of training patterns is presented to each population member each
generation, which considerably simplifies the calculation. The theory is shown
to agree closely to simulations of a real GA averaged over many runs,
accurately predicting the mean best solution found. For weak selection and
large problem size the difference equations describing the dynamics can be
expressed analytically and we find that the effects of noise due to the finite
size of each training batch can be removed by increasing the population size
appropriately. If this population resizing is used, one can deduce the most
computationally efficient size of training batch each generation. For
independent patterns this choice also gives the minimum total number of
training patterns used. Although using independent patterns is a very
inefficient use of training patterns in general, this work may also prove
useful for determining the optimum batch size in the case where patterns are
recycled.


  We present an analytical description of the nonlocal optical response of
plasmonic nanowire metamaterials that enable negative refraction, subwavelength
light manipulation, and emission lifetime engineering. We show that dispersion
of optical waves propagating in nanowire media results from coupling of
transverse and longitudinal electromagnetic modes supported by the composite
and derive the nonlocal effective medium approximation for this dispersion. We
derive the profiles of electric field across the unit cell, and use these
expressions to solve the long-standing problem of additional boundary
conditions in calculations of transmission and reflection of waves by nonlocal
nanowire media. We verify our analytical results with numerical solutions of
Maxwell's equations and discuss generalization of the developed formalism to
other uniaxial metamaterials.


  We discuss and measure the phase shift imposed onto a radially polarized
light beam when focusing it onto an $^{174}\text{Yb}^{+}$ ion. In the
derivation of the expected phase shifts we include the properties of the
involved atomic levels. Furthermore, we emphasize the importance of the
scattering cross section and its relation to the efficiency for coupling the
focused light to an atom. The phase shifts found in the experiment are
compatible with the expected ones when accounting for known deficiencies of the
focusing optics and the motion of the trapped ion at the Doppler limit of laser
cooling.


  Ultra-intense laser-matter interaction experiments (>10$^{18}$ W/cm$^{2}$)
with dense targets are highly sensitive to the effect of laser "noise" (in the
form of pre-pulses) preceding the main ultra-intense pulse. These
system-dependent pre-pulses in the nanosecond and/or picosecond regimes are
often intense enough to modify the target significantly by ionizing and forming
a plasma layer in front of the target. Time resolved interferometry offers a
robust way to characterize the expanding plasma during this period. We have
developed a novel pump-probe interferometry system for an ultra-intense laser
experiment that uses two short-pulse amplifiers synchronized by one ultra-fast
seed oscillator to achieve 40-femtosecond time resolution over hundreds of
nanoseconds, using a variable delay line and other techniques. The first of
these amplifiers acts as the pump and delivers maximal energy to the
interaction region. The second amplifier is frequency shifted and then
frequency doubled to generate the femtosecond probe pulse. After passing
through the laser-target interaction region, the probe pulse is split and
recombined in a laterally sheared Michelson interferometer. Importantly, the
frequency shift in the probe allows strong plasma self-emission at the second
harmonic of the pump to be filtered out, allowing plasma expansion near the
critical surface and elsewhere to be clearly visible in the interferograms.
Three-phase reconstructions of the electron densities are then inferred by Abel
inversion. This interferometric system delivers precise measurements of
pre-plasma expansion that can identify the condition of the target at the
moment that the ultra-intense pulse arrives. Such measurements are
indispensable for correlating laser pre-pulse measurements with instantaneous
plasma profiles and for enabling realistic Particle-in-Cell simulations of the
ultra-intense laser-matter interaction.


  In this paper, a new approach for decoding low-rate Reed-Solomon codes beyond
half the minimum distance is considered and analyzed. Unlike the Sudan
algorithm published in 1997, this new approach is based on multi-sequence
shift-register synthesis, which makes it easy to understand and simple to
implement. The computational complexity of this shift-register based algorithm
is of the same order as the complexity of the well-known Berlekamp-Massey
algorithm. Moreover, the error correcting radius coincides with the error
correcting radius of the original Sudan algorithm, and the practical decoding
performance observed on a q-ary symmetric channel (QSC) is virtually identical
to the decoding performance of the Sudan algorithm. Bounds for the failure and
error probability as well as for the QSC decoding performance of the new
algorithm are derived, and the performance is illustrated by means of examples.


  In this paper we study the inverse of so-called unfair permutations, and
explore various properties of them. Our investigation begins with comparing
this class of permutations with uniformly random permutations, and showing that
they behave very much alike for locally dependent random variables. As an
example of a globally dependent statistic we use the number of inversions, and
show that this statistic satisfies a central limit theorem after proper
centering and scaling. A secondary example of a globally dependent statistic to
be studied will be the number of fixed points. Finally, we introduce two
different generalizations of inverse-unfair permutations.


  The Erd\H{o}s-Faber-Lov\'{a}sz conjecture (posed in 1972) states that the
chromatic index of any linear hypergraph on $n$ vertices is at most $n$. In
this paper, we prove this conjecture for every large $n$. We also provide
stability versions of this result, which confirm a prediction of Kahn.


  Attenuated total reflection (ATR) by surface plasmon polariton (SPP) is a
method for evaluating the dispersion relation of SPP from the position of a dip
in the reflection spectrum. However, recent studies have shown that the dips
are displaced from SPP resonance because they are produced by a type of Fano
resonance, i.e., the interference between the resonant reflection process
accompanied by resonant excitation of SPP and the direct reflection process
without resonant excitation. This result suggests that the system properties
difficult to be achieved in the dispersion relation of SPP can be characterized
using the ATR method. In this study, we investigate the effect of surface
roughness due to nanosized dimples created in the initial stage of pitting
corrosion on the ATR spectrum, from the viewpoint of Fano resonance. Using the
temporal coupled-mode method, it is shown that the Fano resonance in ATR is
caused by the phase change of direct reflection because of the absorption on
the metal surface, and the spectral shape is determined by this phase, along
with the ratio of the external (radiative) decay rate to the total decay rate
of the resonant mode. Moreover, it is clarified that the internal and external
decay rates extracted from the ATR spectrum provide information on corrosion,
such as the effective thickness of the metal film and the randomness in dimple
distribution.


  A key challenge in scaling Gaussian Process (GP) regression to massive
datasets is that exact inference requires computation with a dense n x n kernel
matrix, where n is the number of data points. Significant work focuses on
approximating the kernel matrix via interpolation using a smaller set of m
inducing points. Structured kernel interpolation (SKI) is among the most
scalable methods: by placing inducing points on a dense grid and using
structured matrix algebra, SKI achieves per-iteration time of O(n + m log m)
for approximate inference. This linear scaling in n enables inference for very
large data sets; however the cost is per-iteration, which remains a limitation
for extremely large n. We show that the SKI per-iteration time can be reduced
to O(m log m) after a single O(n) time precomputation step by reframing SKI as
solving a natural Bayesian linear regression problem with a fixed set of m
compact basis functions. With per-iteration complexity independent of the
dataset size n for a fixed grid, our method scales to truly massive data sets.
We demonstrate speedups in practice for a wide range of m and n and apply the
method to GP inference on a three-dimensional weather radar dataset with over
100 million points.


  In this paper, an optimal output consensus problem is studied for
discrete-time linear multiagent systems subject to external disturbances. Each
agent is assigned with a local cost function which is known only to itself.
Distributed protocols are to be designed to guarantee an output consensus for
these high-order agents and meanwhile minimize the aggregate cost as the sum of
these local costs. To overcome the difficulties brought by high-order dynamics
and external disturbances, we develop an embedded design and constructively
present a distributed rule to solve this problem. The proposed control includes
three terms: an optimal signal generator under a directed information graph, an
observer-based compensator to reject these disturbances, and a reference
tracking controller for these linear agents. It is shown to solve the
formulated problem with some mild assumptions. A numerical example is also
provided to illustrate the effectiveness of our proposed distributed control
laws.


  This is part of a collection of discussion pieces on David Donoho's paper 50
Years of Data Science, appearing in Volume 26, Issue 4 of the Journal of
Computational and Graphical Statistics (2017).


  A dynamic agent model is introduced with an annual random wealth
multiplicative process followed by taxes paid according to a linear
wealth-dependent tax rate. If poor agents pay higher tax rates than rich
agents, eventually all wealth becomes concentrated in the hands of a single
agent. By contrast, if poor agents are subject to lower tax rates, the economic
collective process continues forever.


  For researching effects of gamification in foreign language learning for
children in the "Say It Again, Kid!" project we developed a feedback paradigm
that can drive gameplay in pronunciation learning games. We describe our
scoring system based on the difference between a reference phone sequence and
the output of a multilingual CTC phoneme recogniser. We present a white-box
scoring model of mapped weighted Levenshtein edit distance between reference
and error with error weights for articulatory differences computed from a
training set of scored utterances. The system can produce a human-readable list
of each detected mispronunciation's contribution to the utterance score. We
compare our scoring method to established black box methods.


  In this paper we analyse the vacuum polarization effects associated with
massive scalar quantum fields in a higher-dimensional de Sitter space in the
presence of a global monopole. Because this analysis has been developed in a
pure de Sitter space, here we are mainly interested on the effects induced by
the presence of the global monopole. So, in order to achieve this objective we
calculate the corresponding Wightman function, which is expressed in an
integral representation and explicitly depends on the parameters associated
with the presence of the monopole and the cosmological constant. Admitting that
the former is closed to the unity, which corresponds to a realistic value
predicted by Grand Unified Theories, it is possible to express this function as
the sum of two terms: the first one corresponds to the Wightman function on the
bulk where the global monopole is absent, and the second one is a contribution
induced by the presence of the monopole.


  Let W be a finite Coxeter group. In this paper, we show that the properties
of the Solomon algebra homomorphism Phi (from the Solomom descent algebra to
the algebra of class functions) are strongly related to enumerative results:
certain joint statistics on W may be enumerated by the scalar products of
appropriate characters.


  Starting from the $C_{\lambda}$-extended oscillator algebras, we obtain a new
deformed $w_{\infty}$-algebra. More precisely, we show that the
$C_{\lambda}$-extended $w_{\infty}$-algebra generators may be expressed via the
annihilation and creation operators of the $C_{\lambda}$-extended oscillator
algebras $a$ and $a^{\dagger}$ as an infinite-dimensional extension of the
realization of $sp(2)$ algebra.


  We develop a variational calculus for a certain free energy functional on the
space of all probability measures on a Kahler manifold X. This functional can
be seen as a generalization of Mabuchi's K-energy functional and its twisted
versions to more singular situations. Applications to Monge-Amp\`ere equations
of mean field type, twisted Kahler-Einstein metrics and Moser-Trudinger type
inequalities on Kahler manifolds are given. Tian's \alpha- invariant is
generalized to singular measures, allowing i particular the construction of
Kahler-Einstein metrics with positive Ricci curvature that are singular along a
given anti-canonical divisor (as proposed in a very recent program of
Donaldson). As another application we show that if the Calabi flow in the
(anti-) canonical class exits for all times then it converges to a
Kahler-Einstein metric, when one exists. Applications to the
probabilistic/statistical mechanical approach to the construction of
Kahler-Einstein metrics, very recently introduced by the author, will appear
elsewhere.


  We exhibit two distinct renormalization scenarios in many-parameter families
of piecewise isometries (PWI) of a rhombus. The rotational component, defined
over the quadratic field $\mathbb{K}=\mathbb{Q}(\sqrt{5})$, is fixed. The
translations are specified by affine functions of the parameters, with
coefficients in $\mathbb{K}$. In each case the parameters range over a convex
domain. In one scenario the PWI is self-similar if and only if one parameter
belongs to $\mathbb{K}$, while the other is free. Such a continuous
self-similarity is due to the possibility of merging adjacent atoms of an
induced PWI, a common phenomenon in the Rauzy-Veech induction for interval
exchange transformations. In the second scenario, the phase space splits into
several disjoint (non-convex) invariant components. We show that each component
has continuous self-similarity, but due to the transversality of the
corresponding foliations, full self-similarity in phase space is achieved if
and only if both parameters belong to $\mathbb{K}$. All our computations are
exact, using algebraic numbers.