text
stringlengths 6
128k
|
|---|
The cosmological case for a next generation radio observatory, the Square
Kilometer Array, is discussed and reviewed. An instrument like the SKA would be
able to measure galaxy redshifts of normal late-type galaxies, via the 21 cm
line of HI, out to redshifts of $\sim 3$. Not only would such very deep
redshift surveys enable us to map the large scale galaxy distribution and probe
the large scale structure of the universe out to previously unexplored scales,
it would also allow for the first time to obtain direct observational data on
the evolution of this structure. Other promising applications concern the
mapping of the local velocity field of the universe, study of the formation and
evolution of galaxies, and determining the global cosmological parameters
$H_0$, $q_0$ and $\Lambda$ through the application of classical cosmological
tests like source counts. Particularly emphasized is the redshift survey
capability of the SKA. A review is given of the current knowledge of the galaxy
distribution, starting from an inventarisation of nearby cosmic structures,
through a discussion of how it all fits together in a coherent ``foamlike
pattern''. After providing a short overview of the basics of theories of
structure formation, a description is provided of different observational
strategies to probe the structure of the universe out to larger depths, ranging
from pencil-beam surveys and cluster surveys out to the new and ambitious
complete and deep galaxy redshift surveys like the 2dF and the Sloan survey. It
is argued that a survey with the SKA would be a natural and complementary
follow-up. We finally conclude with a specification of the technical
requirements for the SKA to make it into an instrument ideally suited for these
purposes.
|
We present a non-perturbative computation of the running of the coupling
alpha_s in QCD with two flavours of dynamical fermions in the Schroedinger
functional scheme. We improve our previous results by a reliable continuum
extrapolation. The Lambda-parameter characterizing the high-energy running is
related to the value of the coupling at low energy in the continuum limit. An
estimate of Lambda*r_0 is given using large-volume data with lattice spacings a
from 0.07 fm to 0.1 fm. It translates into Lambda_{MSbar}^{(2)}=245(16)(16) MeV
[assuming r_0=0.5 fm]. The last step still has to be improved to reduce the
uncertainty.
|
We study the $O(N)^3$ symmetric quantum field theory of a bosonic tensor
$\phi^{abc}$ with sextic interactions. Its large $N$ limit is dominated by a
positive-definite operator, whose index structure has the topology of a prism.
We present a large $N$ solution of the model using Schwinger-Dyson equations to
sum the leading diagrams, finding that for $2.81 < d < 3$ and for $d<1.68$ the
spectrum of bilinear operators has no complex scaling dimensions. We also
develop perturbation theory in $3-\epsilon$ dimensions including eight $O(N)^3$
invariant operators necessary for the renormalizability. For sufficiently large
$N$, we find a "prismatic" fixed point of the renormalization group, where all
eight coupling constants are real. The large $N$ limit of the resulting
$\epsilon$ expansions of various operator dimensions agrees with the
Schwinger-Dyson equations. Furthermore, the $\epsilon$ expansion allows us to
calculate the $1/N$ corrections to operator dimensions. The prismatic fixed
point in $3-\epsilon$ dimensions survives down to $N\approx 53.65$, where it
merges with another fixed point and becomes complex. We also discuss the $d=1$
model where our approach gives a slightly negative scaling dimension for
$\phi$, while the spectrum of bilinear operators is free of complex dimensions.
|
We give an asymptotic evaluation of the complexity of spherical p-spin
spin-glass models via random matrix theory. This study enables us to obtain
detailed information about the bottom of the energy landscape, including the
absolute minimum (the ground state), the other local minima, and describe an
interesting layered structure of the low critical values for the Hamiltonians
of these models. We also show that our approach allows us to compute the
related TAP-complexity and extend the results known in the physics literature.
As an independent tool, we prove a LDP for the k-th largest eigenvalue of the
GOE, extending the results of Ben Arous, Dembo and Guionnett (2001).
|
We propose new nonparametric accordance R\'enyi-$\alpha$ and $\alpha$-Tsallis
divergence estimators for continuous distributions. We discuss this approach
with a view to the selection model (on al\'etoire and autoregressive AR (1)).
We lestimateur used by kernel density esttimer underlying. Nevertheless, we are
able to prove that the estimators are consistent under certain conditions. We
also describe how to apply these estimators and demonstrate their effectiveness
through numerical experiments.
|
Large Language Models (LLMs) are gaining popularity among software engineers.
A crucial aspect of developing effective code-generation LLMs is to evaluate
these models using a robust benchmark. Evaluation benchmarks with quality
issues can provide a false sense of performance. In this work, we conduct the
first-of-its-kind study of the quality of prompts within benchmarks used to
compare the performance of different code generation models. To conduct this
study, we analyzed 3,566 prompts from 9 code generation benchmarks to identify
quality issues in them. We also investigated whether fixing the identified
quality issues in the benchmarks' prompts affects a model's performance. We
also studied memorization issues of the evaluation dataset, which can put into
question a benchmark's trustworthiness. We found that code generation
evaluation benchmarks mainly focused on Python and coding exercises and had
very limited contextual dependencies to challenge the model. These datasets and
the developers' prompts suffer from quality issues like spelling and
grammatical errors, unclear sentences to express developers' intent, and not
using proper documentation style. Fixing all these issues in the benchmarks can
lead to a better performance for Python code generation, but not a significant
improvement was observed for Java code generation. We also found evidence that
GPT-3.5-Turbo and CodeGen-2.5 models possibly have data contamination issues.
|
We theoretically investigate the spectrum of a single electron double quantum
dot, defined by top gates in a graphene with a substrate induced gap. We
examine the effects of electric and magnetic fields on the spectrum of
localized states, focusing on the tunability of the inter-dot coupling. We find
that the substrate induced gap allows for electrostatic control, with some
limitations that for a fixed inter-dot distance, the inter-dot coupling can not
be made arbitrarily small due to the Klein tunneling. On the other hand, the
proximity of the valence band in graphene allows for new regimes, such as an
$npn$ double dot, which have no counterparts in GaAs.
|
This Letter reports measurements of differential cross sections for the
production of two Z bosons in association with jets in proton-proton collisions
at $\sqrt{s} =$ 8 and 13 TeV. The analysis is based on data samples collected
at the LHC with the CMS detector, corresponding to integrated luminosities of
19.7 and 35.9 fb$^{-1}$ at 8 and 13 TeV, respectively. The measurements are
performed in the leptonic decay modes ZZ $\to\ell^+ \ell^- \ell'^+ \ell'^-$,
where $\ell,\ell' =$ e, $\mu$. The differential cross sections as a function of
the jet multiplicity, the transverse momentum $p_\mathrm{T}$, and
pseudorapidity of the $p_\mathrm{T}$-leading and subleading jets are presented.
In addition, the differential cross sections as a function of variables
sensitive to the vector boson scattering, such as the invariant mass of the two
$p_\mathrm{T}$-leading jets and their pseudorapidity separation, are reported.
The results are compared to theoretical predictions and found in good agreement
within the theoretical and experimental uncertainties.
|
Let $q \in \mathbb{Z} [i]$ be prime and $\chi $ be the primitive quadratic
Hecke character modulo $q$. Let $\pi$ be a self-dual Hecke automorphic cusp
form for $\mathrm{SL}_3 (\mathbb{Z} [i] )$ and $f$ be a Hecke cusp form for
$\Gamma_0 (q) \subset \mathrm{SL}_2 (\mathbb{Z} [i])$. Consider the twisted
$L$-functions $ L (s, \pi \otimes f \otimes \chi) $ and $L (s, \pi \otimes
\chi)$ on $\mathrm{GL}_3 \times \mathrm{GL}_2$ and $\mathrm{GL}_3$. We prove
the subconvexity bounds
\begin{equation*}
L \big(\tfrac 1 2, \pi \otimes f \otimes \chi \big) \ll_{\, \varepsilon, \pi,
f } \mathrm{N} (q)^{5/4 + \varepsilon}, L \big(\tfrac 1 2 + it, \pi \otimes
\chi \big) \ll_{\, \varepsilon, \pi, t } \mathrm{N} (q)^{5/8 + \varepsilon},
\end{equation*} for any $\varepsilon > 0$.
|
We developed a model with no adjustable parameter for retention loss at short
and long time scale in ferroelectric thin-film capacitors. We found that the
predictions of this model are in good agreement with the experimental
observations in the literature. In particular, it explains why a power-law
function shows better fitting than a linear-log relation on a short time scale
(10^-7 s to 1 s) and why a stretched exponential relation gives more precise
description than a linear-log plot on a long time scale (>100 s), as reported
by many researchers in the past. More severe retention losses at higher
temperatures and in thinner films have also been correctly predicted by the
present theory.
|
This paper presents the Real-time Adaptive and Interpretable Detection (RAID)
algorithm. The novel approach addresses the limitations of state-of-the-art
anomaly detection methods for multivariate dynamic processes, which are
restricted to detecting anomalies within the scope of the model training
conditions. The RAID algorithm adapts to non-stationary effects such as data
drift and change points that may not be accounted for during model development,
resulting in prolonged service life. A dynamic model based on joint probability
distribution handles anomalous behavior detection in a system and the root
cause isolation based on adaptive process limits. RAID algorithm does not
require changes to existing process automation infrastructures, making it
highly deployable across different domains. Two case studies involving real
dynamic system data demonstrate the benefits of the RAID algorithm, including
change point adaptation, root cause isolation, and improved detection accuracy.
|
Low complexity joint estimation of synchronization impairments and channel in
a single-user MIMO-OFDM system is presented in this letter. Based on a system
model that takes into account the effects of synchronization impairments such
as carrier frequency offset, sampling frequency offset, and symbol timing
error, and channel, a Maximum Likelihood (ML) algorithm for the joint
estimation is proposed. To reduce the complexity of ML grid search, the number
of received signal samples used for estimation need to be reduced. The
conventional channel estimation methods using Least-Squares (LS) fail for the
reduced sample under-determined system, which results in poor performance of
the joint estimator. The proposed ML algorithm uses Compressed Sensing (CS)
based channel estimation method in a sparse fading scenario, where the received
samples used for estimation are less than that required for an LS based
estimation. The performance of the estimation method is studied through
numerical simulations, and it is observed that CS based joint estimator
performs better than LS based joint estimator
|
New applications of liquid crystalline materials have increased the need for
precise engineering of elastic properties. Recently, Sidky et al. presented
methods by which the elastic coefficients of molecular models with atomistic
detail can be accurately calculated, demonstrating the result for the
ubiquitous mesogen 5CB. In this work, these techniques are applied to the
homologous series of nCB materials, focusing on the standard bend, twist, and
splay deformations, using an entirely automated process. Our results show
strong agreement with published experimental measurements for the nCBs and
present a path forward to computational molecular engineering of liquid crystal
elasticity for novel molecules and mixtures.
|
We report on a multi-year study of student attitudes measured with the
Colorado Learning Attitudes about Science Survey (CLASS) in calculus-based
introductory physics taught with the Modeling Instruction curriculum. We find
that five of six instructors and eight of nine sections using Modeling
Instruction showed significantly improved attitudes from pre to post-course.
Cohen's d effect sizes range from 0.08 - 0.95 for individual instructors. The
average effect was d = 0.45, with a 95% confidence interval of (0.26 - 0.64).
These results build on previously published results showing positive shifts in
attitudes from Modeling Instruction classes. We interpret these data in light
of other published positive attitudinal shifts and explore mechanistic
explanations for similarities and differences with other published positive
shifts.
|
We show that minimal models of nondegenerated hypersufaces defined by Laurent
polynomials with a $d$-dimensional Newton polytope $\Delta$ are Calabi-Yau
varieties $X$ if and only if the Fine interior of $\Delta$ consists of a single
lattice point. We give a combinatorial formula for computing the stringy Euler
number of $X$. This formula allows to test mirror symmetry in cases when
$\Delta$ is not a reflexive polytope. In particular we apply this formula to
pairs of lattice polytopes $(\Delta, \Delta^{\vee})$ that appear in the
Mavlyutov's generalization of the polar duality for reflexive polytopes. Some
examples of Mavlyutov's dual pairs $(\Delta, \Delta^{\vee})$ show that the
stringy Euler numbers of the corresponding Calabi-Yau varieties $X$ and
$X^{\vee}$ may not satisfy the expected topological mirror symmetry test:
$e_{\rm st}(X) = (-1)^{d-1} e_{\rm st}(X^{\vee})$. This shows the necessity of
an additional condition on Mavlyutov's pairs $(\Delta, \Delta^\vee)$.
|
Hot Jupiters may have formed in situ, or been delivered to their observed
short periods through one of two categories of migration mechanisms: disk
migration or high-eccentricity migration. If hot Jupiters were delivered by
high-eccentricity migration, we would expect to observe some "super-eccentric"
Jupiters in the process of migrating. We update a prediction for the number of
super-eccentric Jupiters we would expect to observe in the Kepler sample if all
hot Jupiters migrated through high-eccentricity migration and estimate the true
number observed by Kepler. We find that the observations fail to match the
prediction from high-eccentricity migration with 94.3% confidence and show that
high-eccentricity migration can account for at most ~62% of the hot Jupiters
discovered by Kepler.
|
Ditopic bis-(triazole-pyridine)viologens are bidentate ligands that
self-assemble into coordination polymers. In such photo-responsive materials,
light irradiation initiates photo-induced electron transfer to generate
pi-radicals that can self-associate to form pi-dimers. This leads to a cascade
of events: processes at the supramolecular scale associated with mechanical and
structural transition at the macroscopic scale. By tuning the irradiation power
and duration, we evidence the formation of aggregates and gels. Using
microscopy, we show that the aggregates are dense polydisperse micron size
spindle shaped particles which grow in time. Using microscopy and time resolved
micro-rheology, we follow the gelation kinetics which leads to a gel
characterized by a correlation length of a few microns and a weak elastic
modulus. The analysis of the aggregates and the gel states vouch for an
arrested phase separation process.
|
We study the effect of periodic hopping modulation on a Su-Schrieffer-Heeger
(SSH) chain that exhibits non-Hermiticity in presence of an onsite staggered
imaginary potential. This dissipative, non-Hermitian (NH) extension amply
modifies the features of the topological trivial phase (TTP) and the
topological nontrivial phase (TNP) of the SSH chain. Though a weak potential
can respect the parity-time ($\mathcal{PT}$) symmetry keeping the energy
eigenvalues real, a strong potential breaks $\mathcal{PT}$ conservation leading
to imaginary end state and complex bulk state energies in the system.
Furthermore for large commensurate periodicity of the hopping, in-gap states
appear that take either purely real or purely imaginary eigenvalues depending
on the strenth of both NH potential and hopping modulation. In particular, this
paper is engaged with hopping periodicities of 2, 4 and 8 lattice spacings. The
localization of end states and in-gap states at the boundaries are investigated
for those hopping periodicities. Though we find that topology and
$\mathcal{PT}$ symmetry are not very directly connected, distinguishing
distribution of $\mathcal{PT}$ broken and unbroken phases are clearly observed
within TNP and TTP in our systems.
|
We investigate the early onset of pionic color transparency ($\pi$CT)
observed at Jefferson Laboratory (JLAB) in semi--exclusive pion
electroproduction reaction $A(e,e'\pi^+)$ off nuclei. In the present
description the primary $\gamma^*p \to \pi^+ n$ interaction is described very
well both for the longitudinal and the transverse polarizations. For the final
state interactions a coupled--channel treatment of the interactions of
transmitted hadrons allows to go beyond the Glauber approximation. We show that
a proper distinction between the soft hadronic and hard partonic components of
the electroproduction amplitude is essential for a quantitative description of
the measured nuclear transparency. The data are well reproduced if one assumes
that point--like configurations are produced in the regime of hard
deep--inelastic scattering (DIS) off partons and dominate the transverse
channel.
|
Nonlinear electromagnetic (EM) inverse scattering is a quantitative and
super-resolution imaging technique, in which more realistic interactions
between the internal structure of scene and EM wavefield are taken into account
in the imaging procedure, in contrast to conventional tomography. However, it
poses important challenges arising from its intrinsic strong nonlinearity,
ill-posedness, and expensive computation costs. To tackle these difficulties,
we, for the first time to our best knowledge, exploit a connection between the
deep neural network (DNN) architecture and the iterative method of nonlinear EM
inverse scattering. This enables the development of a novel DNN-based
methodology for nonlinear EM inverse problems (termed here DeepNIS). The
proposed DeepNIS consists of a cascade of multi-layer complexvalued residual
convolutional neural network (CNN) modules. We numerically and experimentally
demonstrate that the DeepNIS outperforms remarkably conventional nonlinear
inverse scattering methods in terms of both the image quality and computational
time. We show that DeepNIS can learn a general model approximating the
underlying EM inverse scattering system. It is expected that the DeepNIS will
serve as powerful tool in treating highly nonlinear EM inverse scattering
problems over different frequency bands, involving large-scale and
high-contrast objects, which are extremely hard and impractical to solve using
conventional inverse scattering methods.
|
We report on the design and performance of a double-sided coincidence
velocity map imaging spectrometer optimized for electron-ion and ion-ion
coincidence experiments studying inner-shell photoionization of gas-phase
molecules with soft X-ray synchrotron radiation. The apparatus employs two
microchannel plate detectors equipped with delay-line anodes for coincident,
time- and position-resolved detection of photo- and Auger electrons with
kinetic energies up to 300\,eV on one side of the spectrometer and photoions up
to 25\,eV per unit charge on the opposite side. We demonstrate its capabilities
by measuring valence photoelectron and ion spectra of neon and nitrogen, and by
studying channel-resolved photoelectron and Auger spectra along with
fragment-ion momentum correlations for chlorine $2p$ inner-shell ionization of
\textit{cis}- and \textit{trans}-1,2-dichloroethene.
|
We use quantum Monte Carlo simulations and numerical analytic continuation to
study high-energy spin excitations in the two-dimensional S=1/2 Heisenberg
antiferromagnet at low temperature. We present results for both the transverse
and longitudinal dynamic spin structure factor S(q,w) at q=(pi,0) and
(pi/2,pi/2). Linear spin-wave theory predicts no dispersion on the line
connecting these momenta. Our calculations show that in fact the magnon energy
at (pi,0) is 10% lower than at (pi/2,pi/2). We also discuss the transverse and
longitudinal multi-magnon continua and their relevance to neutron scattering
experiments.
|
TOI-732 is an M dwarf hosting two transiting planets that are located on the
two opposite sides of the radius valley. By doubling the number of available
space-based observations and increasing the number of radial velocity (RV)
measurements, we aim at refining the parameters of TOI-732 b and c. We also use
the results to study the slope of the radius valley and the density valley for
a well-characterised sample of M-dwarf exoplanets. We performed a global MCMC
analysis by jointly modelling ground-based light curves and CHEOPS and TESS
observations, along with RV time series both taken from the literature and
obtained with the MAROON-X spectrograph. The slopes of the M-dwarf valleys were
quantified via a Support Vector Machine (SVM) procedure. TOI-732 b is an
ultrashort-period planet ($P\sim0.77$ d) with a radius
$R_b=1.325_{-0.058}^{+0.057}$ $R_{\oplus}$ and a mass $M_b=2.46\pm0.19$
$M_{\oplus}$ (mean density $\rho_b=5.8_{-0.8}^{+1.0}$ g cm$^{-3}$), while the
outer planet at $P\sim12.25$ d has $R_c=2.39_{-0.11}^{+0.10}$ $R_{\oplus}$,
$M_c=8.04_{-0.48}^{+0.50}$ $M_{\oplus}$, and thus $\rho_c=3.24_{-0.43}^{+0.55}$
g cm$^{-3}$. Also taking into account our interior structure calculations,
TOI-732 b is a super-Earth and TOI-732 c is a mini-Neptune. Following the SVM
approach, we quantified
$\mathrm{d}\log{R_{p,{\mathrm{valley}}}}/\mathrm{d}\log{P}=-0.065_{-0.013}^{+0.024}$,
which is flatter than for Sun-like stars. In line with former analyses, we note
that the radius valley for M-dwarf planets is more densely populated, and we
further quantify the slope of the density valley as
$\mathrm{d}\log{\hat{\rho}_{\mathrm{valley}}}/\mathrm{d}\log{P}=-0.02_{-0.04}^{+0.12}$.
Compared to FGK stars, the weaker dependence of the position of the radius
valley on the orbital period might indicate that the formation shapes the
radius valley around M dwarfs more strongly than the evolution mechanisms.
|
We examined the Wilson-Bappu effect, a relationship between the absolute
magnitude of the star, $M_V$, and the logarithm of the Ca {\sc ii} emission
width, $W_0$, over the largest $M_V$ range to date, +13 to -5, covering
M-dwarfs to type Ia supergiants. We used an extensive literature, the latest
Hipparcos reduction, data from two globular clusters, and new observations from
Apache Point Observatory to compile a sample that allowed us to study the
effect of [Fe/H] on the Wilson-Bappu relationship. Our results include
reporting the deviations from linearity and demonstrating that the Wilson-Bappu
relationship is insensitive to metallicity.
|
Cosmological information is usually extracted from the Lyman-$\alpha$ forest
correlations using only either large-scale information interpreted through
linear theory or using small-scale information interpreted by means of
expensive hydrodynamical simulations. A complete cosmological interpretation of
the 3D correlations at all measurable scales is challenged by the need of more
realistic models including the complex growth of non-linear small scales that
can only be studied within large hydrodynamical simulations. Past work were
often limited by the trade off between the simulated cosmological volume and
the resolution of the low-density intergalactic medium from which the
Lyman-$\alpha$ signal originates. We conduct a suite of hydrodynamical
simulations of the intergalactic medium, including one of the largest
Lyman-$\alpha$ simulations ever performed in terms of volume (640
$h^{-1}\mathrm{Mpc}$), alongside simulations in smaller volumes with
resolutions up to 25 $h^{-1}\mathrm{kpc}$. We compare the 3D Lyman-$\alpha$
power spectra predicted by those simulations to different non-linear models.
The inferred Lyman-$\alpha$ bias and RSD parameters, $b_\alpha$ and
$\beta_\alpha$ are in remarkable agreement with those measured in SDSS and DESI
data. We find that, contrary to intuition, the convergence of large-scale modes
of the 3D Lyman-$\alpha$ power spectra, which determines $\beta_\alpha$, is
primarily influenced by the resolution of the simulation box through mode
coupling, rather than the box size itself. Finally, we study the BAO signal
encoded in the 3D Lyman-$\alpha$ power spectra. For the first time with a
hydrodynamical simulation, we clearly detect the BAO signal, however we only
marginally detect its damping, associated with the non-linear growth of the
structures.
|
We construct phenomenologically viable supersymmetric models where CP is an
approximate symmetry. The full high energy theory has exact CP and horizontal
symmetries that are spontaneously broken with a naturally induced hierarchy of
scales, $\Lambda_{CP}\ll\Lambda_H$. Consequently, the effective low energy
theory, that is the supersymmetric Standard Model, has CP broken explicitly but
by a small parameter. The $\epsilon_K$ parameter is accounted for by
supersymmetric contributions. The predictions for other CP violating
observables are very different from the Standard Model. In particular, CP
violating effects in neutral B decays into final CP eigenstates such as
$B\ra\psi K_S$ and in $K\ra\pi\nu\bar\nu$ decays are very small.
|
The NEXT-White detector, a high-pressure gaseous xenon time projection
chamber, demonstrated the excellence of this technology for future neutrinoless
double beta decay searches using photomultiplier tubes (PMTs) to measure energy
and silicon photomultipliers (SiPMs) to extract topology information. This
analysis uses $^{83m}\text{Kr}$ data from the NEXT-White detector to measure
and understand the energy resolution that can be obtained with the SiPMs,
rather than with PMTs. The energy resolution obtained of (10.9 $\pm$ 0.6) $\%$,
full-width half-maximum, is slightly larger than predicted based on the photon
statistics resulting from very low light detection coverage of the SiPM plane
in the NEXT-White detector. The difference in the predicted and measured
resolution is attributed to poor corrections, which are expected to be improved
with larger statistics. Furthermore, the noise of the SiPMs is shown to not be
a dominant factor in the energy resolution and may be negligible when noise
subtraction is applied appropriately, for high-energy events or larger SiPM
coverage detectors. These results, which are extrapolated to estimate the
response of large coverage SiPM planes, are promising for the development of
future, SiPM-only, readout planes that can offer imaging and achieve similar
energy resolution to that previously demonstrated with PMTs.
|
Hyperbolic metamaterials were originally introduced to overcome the
diffraction limit of optical imaging. Soon thereafter it was realized that
hyperbolic metamaterials demonstrate a number of novel phenomena resulting from
the broadband singular behavior of their density of photonic states. These
novel phenomena and applications include super resolution imaging, new stealth
technologies, enhanced quantum-electrodynamic effects, thermal
hyperconductivity, superconductivity, and interesting gravitation theory
analogues. Here we briefly review typical material systems, which exhibit
hyperbolic behavior and outline important applications of hyperbolic
metamaterials.
|
Using numerical methods we discuss the effects of open boundary conditions on
condensation phenomena in the zero-range process (ZRP) and transport processes
with pair-factorized steady states (PFSS), an extended model of the ZRP with
nearest-neighbor interaction. For the zero-range process we compare to
analytical results in the literature with respect to criticality and
condensation. For the extended model we find a similar phase structure, but
observe supercritical phases with droplet formation for strong boundary drives.
|
Hierarchies allow feature sharing between objects at multiple levels of
representation, can code exponential variability in a very compact way and
enable fast inference. This makes them potentially suitable for learning and
recognizing a higher number of object classes. However, the success of the
hierarchical approaches so far has been hindered by the use of hand-crafted
features or predetermined grouping rules. This paper presents a novel framework
for learning a hierarchical compositional shape vocabulary for representing
multiple object classes. The approach takes simple contour fragments and learns
their frequent spatial configurations. These are recursively combined into
increasingly more complex and class-specific shape compositions, each exerting
a high degree of shape variability. At the top-level of the vocabulary, the
compositions are sufficiently large and complex to represent the whole shapes
of the objects. We learn the vocabulary layer after layer, by gradually
increasing the size of the window of analysis and reducing the spatial
resolution at which the shape configurations are learned. The lower layers are
learned jointly on images of all classes, whereas the higher layers of the
vocabulary are learned incrementally, by presenting the algorithm with one
object class after another. The experimental results show that the learned
multi-class object representation scales favorably with the number of object
classes and achieves a state-of-the-art detection performance at both, faster
inference as well as shorter training times.
|
We study the evolution of the cosmological perturbations after inflation in
curvaton models where the non-relativistic curvaton decays into both radiation
and a cold dark matter component. We calculate the primordial curvature and
correlated isocurvature perturbations inherited by the radiation and cold dark
matter after the curvaton has decayed. We give the transfer coefficient in
terms of the initial curvaton density relative to the curvaton decay rate.
|
We study the correlation of top asymmetries that are sensitive to the
different origin of (a new contribution to) the total asymmetry: loop- or
tree-level origins. We find that both the size and sign of the correlation
between total and $t\bar{t}j$ inclusive asymmetries are inherently different
depending on the origin. We demonstrate the correlation by using the
color-singlet $Z^\prime$ and the pure axigluon taken as representative models
of loop- and tree-induced total asymmetries. We calculate the next-to-leading
order QCD corrections to the $Z^\prime$ and perform Monte-Carlo event
generation. The correlation is understood in the QCD eikonal approximation
using its color structure.
|
The finite temperature lattice QCD with N_f=2 nonperturbatively improved
Wilson fermions is studied on 16^3 8 lattice. Using abelian projection after
fixing to MA gauge we determine the transition temperature for m_{\pi}/m_{\rho}
\sim 0.8.
|
Recent work on the quantization of Maxwell theory has used a non-covariant
class of gauge-averaging functionals which include explicitly the effects of
the extrinsic-curvature tensor of the boundary, or covariant gauges which,
unlike the Lorentz case, are invariant under conformal rescalings of the
background four-metric. This paper studies in detail the admissibility of such
gauges at the classical level. It is proved that Euclidean Green functions of a
second- or fourth-order operator exist which ensure the fulfillment of such
gauges at the classical level, i.e. on a portion of flat Euclidean four-space
bounded by three-dimensional surfaces. The admissibility of the axial and
Coulomb gauges is also proved.
|
We analyse the quantization procedure of the spinor field in the Rindler
spacetime, showing the boundary conditions that should be imposed to the field,
in order to have a well posed theory. Because of these boundary conditions we
argue that this construction and the usual one in Minkowski spacetime are
qualitatively different and can not be compared and consequently the
conventional interpretation of the Unruh effect, that is the thermal nature of
the Minkowski vacuum state from the point of view of an accelerated observer,
is questionable. We also analyse in detail the Unruh quantization scheme and we
show that it is not valid in the whole Minkowski space but only in the double
Rindler wedge, and it cannot be used as a basis for a quantum theoretical proof
of the Unruh effect.
|
I review a recently proposed scaling analysis of hadron suppression in Deeply
Inelastic Scattering on nuclear targets measured at the HERMES experiment. The
analysis can distinguish 2 competing explanations for the observed suppression,
namely, quark radiative energy loss with long hadron formation times, and
prehadron nuclear absorption with hadronization starting inside the nucleus.
Experimental data are shown to favor short formation times and prehadron
absorption.
|
Using an adapted Sn-flux growth technique we obtained comparatively large
CeFeAsO single crystals of better quality than previously reported polycrystals
or single crystals, as evidenced by much sharper anomalies at the structural
and magnetic phase transitions as well as a much higher residual resistivity
ratio of 12. In the magnetically ordered phase we observe a very pronounced
metallic behavior of the in-plane resistivity, which excludes a Mott insulator
regime at low temperature. The separation Delta_T = T_0 - T_N between
structural and magnetic ordering temperatures decreases with increasing sample
quality, from 18 K in the initial reports to 6 K in the present single
crystals, demonstrating that this separation is not an intrinsic property of
the RFeAsO systems. Our results indicate that the coupling between magnetic
ordering and structural distortion is very similar in AFe2As2 and RFeAsO type
of compounds, much more similar than previously thought. The implications of
our experimental results give arguments both in favor and against the nematic
phase model.
|
The radiative ortho-para transition in the molecular hydrogen is studied.
This highly forbidden transition is very sensitive to relativistic and subtle
nonadiabatic effects. Our result for the transition rate in the ground
vibrational level $\Gamma(J=1\to J=0) = 6.20(62)\cdot 10^{-14} \iyr$ is
significantly lower in comparison to all the previous approximate calculations.
Experimental detection of such a weak line by observation of, for example, the
cold interstellar molecular hydrogen is at present unlikely.
|
We propose a new family of message passing techniques for MAP estimation in
graphical models which we call {\em Sequential Reweighted Message Passing}
(SRMP). Special cases include well-known techniques such as {\em Min-Sum
Diffusion} (MSD) and a faster {\em Sequential Tree-Reweighted Message Passing}
(TRW-S). Importantly, our derivation is simpler than the original derivation of
TRW-S, and does not involve a decomposition into trees. This allows easy
generalizations. We present such a generalization for the case of higher-order
graphical models, and test it on several real-world problems with promising
results.
|
As a part of this project, we have developed an IoT-based instrument
utilizing the NODE MCU-ESP8266 module, MQ135 gas sensor, and DHT-11 sensor for
measuring CO$_2$ levels in parts per million (ppm), temperature, and humidity.
The escalating CO$_2$ levels worldwide necessitate constant monitoring and
analysis to comprehend the implications for human health, safety, energy
efficiency, and environmental well-being. Thus, an efficient and cost-effective
solution is imperative to measure and transmit data for statistical analysis
and storage. The instrument offers real-time monitoring, enabling a
comprehensive understanding of indoor environmental conditions. By providing
valuable insights, it facilitates the implementation of measures to ensure
health and safety, optimize energy efficiency, and promote effective
environmental monitoring. This scientific endeavor aims to contribute to the
growing body of knowledge surrounding CO$_2$ levels, temperature, and humidity,
fostering sustainable practices and informed decision-making
|
The primary objective of this paper is to revisit and make a case for the
merits of R.A. Fisher's objections to the decision-theoretic framing of
frequentist inference. It is argued that this framing is congruent with the
Bayesian but incongruent with the frequentist inference. It provides the
Bayesian approach with a theory of optimal inference, but it misrepresents the
theory of optimal frequentist inference by framing inferences solely in terms
of the universal quantifier `for all values of theta in the parameter space'.
This framing is at odds with the primary objective of model-based frequentist
inference, which is to learn from data about the true value of theta (unknown
parameter(s)); the one that gave rise to the particular data. The frequentist
approach relies on factual (estimation, prediction), as well as hypothetical
(testing) reasoning whose primary aim is to learn from data about the true
theta. The paper calls into question the appropriateness of admissibility and
reassesses Stein's paradox as it relates to the capacity of frequentist
estimators to pinpoint the true theta. The paper also compares and contrasts
loss-based errors with traditional frequentist errors, such as coverage, type I
and II; the former are attached to {\theta}, but the latter to the inference
procedure itself.
|
We discuss the possibility of observing CPT violation from top anti-top
production in hadronic colliders. We study a general approach by analyzing
constraints on the mass difference between the top and anti-top quarks. We
present current bounds from Tevatron data, and comment on the prospects for
improving these bounds at the LHC and the ILC.
|
Although autoregressive models have achieved promising results on image
generation, their unidirectional generation process prevents the resultant
images from fully reflecting global contexts. To address the issue, we propose
an effective image generation framework of Draft-and-Revise with Contextual
RQ-transformer to consider global contexts during the generation process. As a
generalized VQ-VAE, RQ-VAE first represents a high-resolution image as a
sequence of discrete code stacks. After code stacks in the sequence are
randomly masked, Contextual RQ-Transformer is trained to infill the masked code
stacks based on the unmasked contexts of the image. Then, Contextual
RQ-Transformer uses our two-phase decoding, Draft-and-Revise, and generates an
image, while exploiting the global contexts of the image during the generation
process. Specifically. in the draft phase, our model first focuses on
generating diverse images despite rather low quality. Then, in the revise
phase, the model iteratively improves the quality of images, while preserving
the global contexts of generated images. In experiments, our method achieves
state-of-the-art results on conditional image generation. We also validate that
the Draft-and-Revise decoding can achieve high performance by effectively
controlling the quality-diversity trade-off in image generation.
|
We investigate the quantum phase transitions of a two-dimensional
Bose-Hubbard model in the presence of a Rashba spin-orbit coupling with and
without thermal fluctuations. The interplay of single-particle hopping,
strength of spin-orbit coupling, and interspin interaction leads to superfluid
phases with distinct properties. With interspin interactions weaker than
intraspin interactions, the spin-orbit coupling induces two finite-momentum
superfluid phases. One of them is a phase-twisted superfluid that exists at low
hopping strengths and reduces the domain of insulating phases. At comparatively
higher hopping strengths, there is a transition from the phase-twisted to a
finite momenta stripe superfluid. With interspin interactions stronger than the
intraspin interactions, the system exhibits phase-twisted to ferromagnetic
phase transition. At finite temperatures, the thermal fluctuations destroy the
phase-twisted superfluidity and lead to a wide region of normal-fluid states.
These findings can be observed in recent quantum gas experiments with
spin-orbit coupling in optical lattices.
|
Contemporary wisdom based on empirical studies suggests that standard
recurrent neural networks (RNNs) do not perform well on tasks requiring
long-term memory. However, precise reasoning for this behavior is still
unknown. This paper provides a rigorous explanation of this property in the
special case of linear RNNs. Although this work is limited to linear RNNs, even
these systems have traditionally been difficult to analyze due to their
non-linear parameterization. Using recently-developed kernel regime analysis,
our main result shows that linear RNNs learned from random initializations are
functionally equivalent to a certain weighted 1D-convolutional network.
Importantly, the weightings in the equivalent model cause an implicit bias to
elements with smaller time lags in the convolution and hence, shorter memory.
The degree of this bias depends on the variance of the transition kernel matrix
at initialization and is related to the classic exploding and vanishing
gradients problem. The theory is validated in both synthetic and real data
experiments.
|
A model is developed for electromagnetic form factor of the pion. One-loop
corrections are included in the linear sigma-model. The rho-meson contribution
is added in an extended VMD model. The form factor, calculated without fitting
parameters, is in a good agreement with experiment for space-like and time-like
photon momenta. Loop corrections to the two-pion hadronic contribution a^{(had,
\pi)}_\mu to the muon anomalous magnetic moment are calculated. The optimal
value of the sigma-meson mass appears to be close to the rho-meson mass.
|
In this work we evaluate the $^1S_0$ energy gap of $\Sigma^-$ hyperons in
$\beta$-stable neutron star matter. We solve the BCS gap equation for an
effective $\Sigma^-\Sigma^-$ pairing interaction derived from the most recent
parametrization of the hyperon-hyperon interaction constructed by the Nijmegen
group. We find that the $\Sigma^-$ hyperons are in a $^1S_0$ superfluid state
in the density region $\sim 0.27-0.7$ fm$^{-3}$, with a maximum energy gap of
order 8 MeV at a total baryon number density of $\sim 0.37$ fm$^{-3}$ and a
$\Sigma^-$ fraction of about 8%. We examine the implications on neutron star
cooling.
|
We present a new approach aimed at constraining the typical size and optical
properties of carbon dust grains in Circumstellar envelopes (CSEs) of
carbon-rich stars (C-stars) in the Small Magellanic Cloud (SMC). To achieve
this goal, we apply our recent dust growth description, coupled with a
radiative transfer code to the CSEs of C-stars evolving along the TP-AGB, for
which we compute spectra and colors. Then we compare our modeled colors in the
near- and mid-infrared (NIR and MIR) bands with the observed ones, testing
different assumptions in our dust scheme and employing several data sets of
optical constants for carbon dust available in the literature. Different
assumptions adopted in our dust scheme change the typical size of the carbon
grains produced. We constrain carbon dust properties by selecting the
combination of grain size and optical constants which best reproduces several
colors in the NIR and MIR at the same time. The different choices of optical
properties and grain size lead to differences in the NIR and MIR colors greater
than two magnitudes in some cases. We conclude that the complete set of
observed NIR and MIR colors are best reproduced by small grains, with sizes
between $\sim$0.035 and $\sim$0.12~$\mu$m, rather than by large grains between
$\sim0.2$ and $0.7$~$\mu$m. The inability of large grains to reproduce NIR and
MIR colors seems independent of the adopted optical data set. We also find a
possible trend of the grain size with mass-loss and/or carbon excess in the
CSEs of these stars.
|
Patient privacy is a major barrier to healthcare AI. For confidentiality
reasons, most patient data remains in silo in separate hospitals, preventing
the design of data-driven healthcare AI systems that need large volumes of
patient data to make effective decisions. A solution to this is collective
learning across multiple sites through federated learning with differential
privacy. However, literature in this space typically focuses on differentially
private statistical estimation and machine learning, which is different from
the causal inference-related problems that arise in healthcare. In this work,
we take a fresh look at federated learning with a focus on causal inference;
specifically, we look at estimating the average treatment effect (ATE), an
important task in causal inference for healthcare applications, and provide a
federated analytics approach to enable ATE estimation across multiple sites
along with differential privacy (DP) guarantees at each site. The main
challenge comes from site heterogeneity -- different sites have different
sample sizes and privacy budgets. We address this through a class of per-site
estimation algorithms that reports the ATE estimate and its variance as a
quality measure, and an aggregation algorithm on the server side that minimizes
the overall variance of the final ATE estimate. Our experiments on real and
synthetic data show that our method reliably aggregates private statistics
across sites and provides better privacy-utility tradeoff under site
heterogeneity than baselines.
|
In this article, we consider the ratio of structure functions for heavy quark
pair production at low values of $x$. The importance of this ratio for charm
and beauty pair production is examined according to the Hadron Electron Ring
Accelerator (HERA) data. The behavior of these ratios considers due to the
hard-pomeron behavior of the gluon distribution function. The results are in
good agreement with respect to the HERA data. Expanding this data to the range
of new energies underscore the importance of these measurements for heavy
quarks. The ratio of charm and beauty structure functions at the proposed Large
Hadron electron Collider (LHeC) is considered as a function of invariant
center-of-mass energy. For top pair production this ratio is extracted with
known kinematics of the LHeC and Future Circular Collider electron-hadron
(FCC-eh) colliders. Comparison of the results obtained for the ratio of top
structure functions in LHeC and FCC-eh are proportional to the specified
inelasticity $y$ range.
|
Self-supervised learning (SSL) has recently attracted significant attention
in the field of recommender systems. Contrastive learning (CL) stands out as a
major SSL paradigm due to its robust ability to generate self-supervised
signals. Mainstream graph contrastive learning (GCL)-based methods typically
implement CL by creating contrastive views through various data augmentation
techniques. Despite these methods are effective, we argue that there still
exist several challenges: i) Data augmentation (e.g., discarding edges or
adding noise) necessitates additional graph convolution (GCN) or modeling
operations, which are highly time-consuming and potentially harm the embedding
quality. ii) Existing CL-based methods use traditional CL objectives to capture
self-supervised signals. However, few studies have explored obtaining CL
objectives from more perspectives and have attempted to fuse the varying
signals from these CL objectives to enhance recommendation performance.
To overcome these challenges, we propose a High-Order Fusion Graph
Contrastive Learning (HFGCL) framework for recommendation. Specifically, we
discards the data augmentations and instead high-order information from GCN
process to create contrastive views. Additionally, to integrate self-supervised
signals from various CL objectives, we propose an advanced CL objective. By
ensuring that positive pairs are distanced from negative samples derived from
both contrastive views, we effectively fuse self-supervised signals from
distinct CL objectives, thereby enhancing the mutual information between
positive pairs. Experimental results on three public datasets demonstrate the
superior effectiveness of HFGCL compared to the state-of-the-art baselines.
|
In this paper, we study the production of isolated-photon plus a jet in $pp$
and $PbPb$ collisions, which can be used as an important probe to the jet
transport property in quark gluon plasma created in heavy ion collisions.
Normally, there are two types of observables associated with the production of
isolated-photon plus a jet, namely, the azimuthal angular correlation and the
transverse momentum imbalance. To understand both observables in the full
kinematical region, we need to employ the perturbative QCD calculation, which
takes into account the hard splitting of partons, together with the Sudakov
resummation formalism, which resums soft gluon splittings. Furthermore, by
introducing energy-loss into the system, we calculate the enhancement of the
momentum imbalance distribution for $AA$ as compared to $pp$ collisions and
make predictions for future unfolded experimental data. In addition, in order
to extract the jet transport coefficient more precisely in our numerical
calculation, we also distinguish quark jets from gluon jets, since they
interact with quark gluon plasma with different strengths. This work provides a
reliable theoretical tool for the calculation of the gamma-jet correlation,
which can lead us to a more precise extraction of the jet transport coefficient
in relativistic heavy-ion collisions.
|
In this paper, we reveal a new connection between approximation numbers of
periodic Sobolev type spaces, where the smoothness weights on the Fourier
coefficients are induced by a (quasi-)norm $\|\cdot\|$ on $\mathbb{R}^d$, and
entropy numbers of the embedding $\textrm{id}: \ell_{\|\cdot\|}^d \to
\ell_\infty^d$. This connection yields preasymptotic error bounds for
approximation numbers of isotropic Sobolev spaces, spaces of analytic
functions, and spaces of Gevrey type in $L_2$ and $H^1$, which find application
in the context of Galerkin methods. Moreover, we observe that approximation
numbers of certain Gevrey type spaces behave preasymptotically almost identical
to approximation numbers of spaces of dominating mixed smoothness. This
observation can be exploited, for instance, for Galerkin schemes for the
electronic Schr\"odinger equation, where mixed regularity is present.
|
This paper studies the proposed green (energy-efficient) coverage
probability, link and network energy efficiencies in the downlink of a
heterogeneous cellular network (HetNet) consisting of $K$ independent Poisson
point processes (PPPs) of base stations (BSs). The important statistical
properties of the universal (general) cell association functions are first
studied and the cell load statistics for power-law cell association functions,
which can characterize the accurate void cell probability of a BS in every
tier, is also derived. A simple and feasible green channel-aware cell
association (GCA) scheme is proposed and the green coverage probability is also
proposed for any particular cell association scheme, such as the maximum
received power association (MRPA) and nearest base station association (NBA)
schemes. Then the link and network energy efficiencies are proposed to
characterize the mean spectrum efficiency per unit power consumption for a BS
and the mean area spectrum efficiency for a HetNet, respectively. All the tight
bounds on the green coverage probability, link and network energy efficiencies
for the GCA, MRPA and NBA schemes are found. They are theoretically shown to
pose the fundamental maximum limits on the link and network energy efficiencies
achieved by any other cell association schemes and such a fact is validated by
numerical results as well.
|
We derive a set of Leggett-Garg inequalities (temporal Bell's inequalities)
for the moment generating function of charge transferred through a conductor.
Violation of these inequalities demonstrates the absence of a macroscopic-real
description of the transport process. We show how these inequalities can be
violated by quantum-mechanical systems and consider transport through normal
and superconducting single-electron transistors as examples.
|
We show that a class of divergence-form elliptic problems with quadratic
growth in the gradient and non-coercive zero order terms are solvable, under
essentially optimal hypotheses on the coefficients in the equation. In
addition, we prove that the solutions are in general not unique. The case where
the zero order term has the opposite sign was already intensively studied and
the uniqueness is the rule.
|
Two-dimensional alloys of carbon and nitrogen represent an urgent interest
due to prospective applications in nanomechanical and optoelectronic devices.
Stability of these chemical structures must be understood as a function of
their composition. The present study employs hybrid density functional theory
and reactive molecular dynamics simulations to get insights regarding how many
nitrogen atoms can be incorporated into the graphene sheet without destroying
it. We conclude that (1) C:N=56:28 structure and all nitrogen-poorer structures
maintain stability at 1000 K; (2) stability suffers from N-N bonds; (3)
distribution of electron density heavily depends on the structural pattern in
the N-doped graphene. Our calculations support experimental efforts on the
production of highly N-doped graphene and tuning mechanical and optoelectronic
properties of graphene.
|
We study the spatially homogeneous time dependent solutions and their
bifurcations of the Gray-Scott model. We find the global map of bifurcations by
a combination of rigorous verification of the existence of Takens Bogdanov and
a Bautin bifurcations, in the space of two parameters k and F. With the aid of
numerical continuation of local bifurcation curves we give a global description
of all the possible bifurcations
|
We present a QCD sum rule analysis for the newly observed resonance
$X_{c}(3250)$ by assuming it as a $D_{0}^{*}(2400)N$ molecular state.
Technically, contributions of operators up to dimension 12 are included in the
operator product expansion (OPE). We find that it is difficult to find the
conventional OPE convergence in this work. By trying releasing the rigid OPE
convergence criterion, one could find that the OPE convergence is still under
control in the present work and the numerical result for $D_{0}^{*}(2400)N$
state is $3.18\pm0.51 {GeV}$, which is in agreement with the experimental data
of $X_{c}(3250)$. In view of that the conventional OPE convergence is not
obtained here, thus only weak conclusions can be drawn regarding the
explanation of $X_{c}(3250)$ in terms of a $D_{0}^{*}(2400)N$ molecular state.
As a byproduct, the mass for the bottom counterpart $\bar{B}_{0}^{*}N$ state is
predicted to be $6.50\pm0.49 {GeV}$.
|
We complete the set of string vertices of non-negative dimension by
introducing in a consistent manner those moduli spaces which had previously
been excluded. As a consequence we obtain a `geometrised' string action taking
the simple form $S=f(\B)$ where `$\B$' is the sum of the string vertices. That
the action satisfies the B-V master equation follows from the recursion
relations for the string vertices which take the form of a `geometrical'
quantum master equation.
|
Max-stable random fields can be constructed according to Schlather (2002)
with a random function or a stationary process and a kind of random event
magnitude. These are applied for the modelling of natural hazards. We simply
extend these event-controlled constructions to random fields of maxima with
non-max-stable dependence structure (copula). The theory for the variant with a
stationary process is obvious; the parameter(s) of its correlation function
is/are determined by the event magnitude. The introduced variant with random
functions can only be researched numerically. The scaling of the random
function is exponentially determined by the event magnitude. The location
parameter of the Gumbel margins depends only on this exponential function in
the researched examples; the scale parameter of the margins is normalized. In
addition, we propose a method for the parameter estimation for such
constructions by using Kendall's tau. The spatial dependence in relation to the
block size is considered therein. Finally, we briefly discuss some issues like
the sampling.
|
Structural and superconducting properties of high quality Niobium nanofilms
with different thicknesses are investigated on silicon oxide and sapphire
substrates. The role played by the different substrates and the superconducting
properties of the Nb films are discussed based on the defectivity of the films
and on the presence of an interfacial oxide layer between the Nb film and the
substrate. The X-ray absorption spectroscopy is employed to uncover the
structure of the interfacial layer. We show that this interfacial layer leads
to a strong proximity effect, specially in films deposited on a SiO$_2$
substrate, altering the superconducting properties of the Nb films. Our results
establish that the critical temperature is determined by an interplay between
quantum-size effects, due to the reduction of the Nb film thicknesses, and
proximity effects.
|
We investigate baryon-baryon (BB) interactions in the 3-flavor full QCD
simulations with degenerate quark masses for all flavors. The BB potentials in
the orbital S-wave are extracted from the Nambu-Bethe-Salpeter wave functions
measured on the lattice. We observe strong flavor-spin dependences of the BB
potentials at short distances. In particular, a strong repulsive core exists in
the flavor-octet and spin-singlet channel (the 8_s representation), while an
attractive core appears in the flavor singlet channel (the 1 representation).
We discuss a relation of such flavor-spin dependence with the Pauli exclusion
principle in the quark level. Possible existence of an H-dibaryon resonance
above the Lambda-Lambda threshold is also discussed.
|
This paper concerns what Background Independence itself is (as opposed to
some particular physical theory that is background independent). The notions
presented mostly arose from a layer-by-layer analysis of the facets of the
Problem of Time in Quantum Gravity. Part of this coincides with two relational
postulates which are thus identified as classical precursors of two of the
facets of the Problem of Time. These are furthemore tied to the forms of each
of the GR Hamiltonian and momentum constraints. Other aspects of Background
Independence include the algebraic closure of these constraints, expressing
physics in terms of beables, foliation independence as implemented by
refoliation invariance, the reconstruction of spacetime from space. The final
picture is that Background Independence - a philosophically desirable and
physically implementable feature for a theory to have - has the facets of the
Problem of Time among its consequences. Thus these arise naturally and are
problems to be resolved, as opposed to avoided `by making one's physics
background-dependent in order not to have these problems'. This serves as a
selection criterion that limits the use of a number of model arenas and
physical theories.
|
By using images taken with WFCAM on UKIRT and SofI on the NTT and combining
them with 2MASS we have measured proper motions for 126 L and T dwarfs in the
dwarf archive. Two of these L dwarfs appear to have M dwarf common proper
motion companions, and 2 also appear to be high velocity dwarfs, indicating
possible membership of the thick disc. We have also compared the motion of
these 126 objects to that of numerous moving groups, and have identified new
members of the Hyades, Ursa Major and Pleiades moving groups. These new
objects, as well as those identified in Jameson et al. (2008) have allowed us
to refine the L dwarf sequence for Ursa Major that was defined by Jameson et
al. (2008).
|
We construct and thoroughly study a new integrable example of the AdS/CFT
correspondence with Schr\"{o}dinger symmetry. On the gravity side, the
supergravity solution depends on two parameters and is obtained by marginally
deforming the internal space of the Schr\"{o}dinger background through a series
of TsT transformations. On the field theory side, we identify the dual field
theory which also depends on two parameters. We find a point-like string
solution and derive its dispersion relation. A non-trivial test of the
correspondence is provided by using the Landau-Lifshitz coherent state approach
to reproduce the leading, in the deformation parameters, terms of that
relation. Then, we calculate the Wilson loop, describing the quark/anti-quark
potential at strong coupling. It exhibits confining behaviour when the
separation length is much less than the Schr\"{o}dinger parameter. When the
separation length is much greater than the Schr\"{o}dinger parameter the
behaviour is that of a conformal theory. Subsequently, we take the Penrose
limit along a certain null geodesic of the constructed background and calculate
the bosonic spectrum. Based on that spectrum, we make an educated guess for the
exact, in the 't Hooft coupling, dispersion relation of the magnon excitations
in the original doubly deformed background. This provides us with an exact
prediction for the dimensions of the dual field theory operators.
|
We postulate a new type of operator algebra with a non-abelian extension.
This algebra generalizes the Kac--Moody algebra in string theory and the
Mickelsson--Faddeev algebra in three dimensions to higher-dimensional extended
objects ($p$-branes). We then construct new BRST operators, covariant
derivatives and curvature tensors in the higher-dimensional generalization of
loop space.
|
Yang's theorem states that an initial J=1 state cannot decay into two
photons. Because of this result some reactions relating to elementary particles
or atomic transitions can be ruled out. The theorem is not valid in the
presence of background electric or magnetic fields. In this work we show that
the decay of a J=1 particle into two photons is permitted by Bose symmetry and
rotational invariance when the background of the decay process is not pure
vacuum but contains an external classical magnetic/electric field. We also
discuss constraints on these amplitudes from {\bf CP} invariance.
|
Zero-knowledge circuits are sets of equality constraints over arithmetic
expressions interpreted in a prime field; they are used to encode computations
in cryptographic zero-knowledge proofs. We make the following contributions to
the problem of ensuring that a circuit correctly encodes a computation: a
formal framework for circuit correctness; an ACL2 library for prime fields; an
ACL2 model of the existing R1CS (Rank-1 Constraint Systems) formalism to
represent circuits, along with ACL2 and Axe tools to verify circuits of this
form; a novel PFCS (Prime Field Constraint Systems) formalism to represent
hierarchically structured circuits, along with an ACL2 model of it and ACL2
tools to verify circuits of this form in a compositional and scalable way;
verification of circuits, ranging from simple to complex; and discovery of bugs
and optimizations in existing zero-knowledge systems.
|
Prokaryotic gene prediction plays an important role in understanding the
biology of organisms and their function with applications in medicine and
biotechnology. Although the current gene finders are highly sensitive in
finding long genes, their sensitivity decreases noticeably in finding shorter
genes (<180 nts). The culprit is insufficient annotated gene data to identify
distinguishing features in short open reading frames (ORFs). We develop a deep
learning-based method called ProtiGeno, specifically targeting short
prokaryotic genes using a protein language model trained on millions of evolved
proteins. In systematic large-scale experiments on 4,288 prokaryotic genomes,
we demonstrate that ProtiGeno predicts short coding and noncoding genes with
higher accuracy and recall than the current state-of-the-art gene finders. We
discuss the predictive features of ProtiGeno and possible limitations by
visualizing the three-dimensional structure of the predicted short genes. Data,
codes, and models are available at https://github.com/tonytu16/protigeno.
|
We show that the usual Born-Oppenheimer type of approximation used in quantum
gravity, in which a semiclassical time parameter emerges from a weak-coupling
expansion of the Wheeler-DeWitt constraint, leads to a unitary theory at least
up to the next-to-leading order in minisuperspace models. As there are no
unitarity-violating terms, this settles the issue of unitarity at this order,
which has been much debated in the literature. Furthermore, we also show that
the conserved inner product is gauge-fixed in the sense that the measure is
related to the Faddeev-Popov determinant associated with the choice of
semiclassical time as a reparametrization gauge. This implies that the
Born-Oppenheimer approach to the problem of time is, in fact, an instance of a
relational quantum theory, in which transition amplitudes can be related to
conditional probabilities.
|
The variation of the solar diameter in time and in position angle has
implications in astrophysics and in general relativity, as the long series of
studies attest. The Transits of Venus in 2004 and 2012 have been carefully
studied because of the rarity of the phenomenon and its historical importance
due the AU measure and to the discovery of Venus atmosphere. The
characterization of Venus atmosphere and the measure of the solar diameter to
the milliarcsecond level of precision have been studied also from satellite
images. The results of the solar diameter measurements made with the
observations in Athens (2004) and at the Huairou Solar Observing Station in
China (2012) are presented. The topic of the oblateness of the Sun at sunset
and its intrinsic value is drafted to introduce the general public to the
relativistic relevance of measuring the solar figure, in the occasion of the
International Year of Light 2015.
|
Theoretical and experimental investigations of water vapor interaction with
porous materials are carried out both at the macro level and at the micro
level. At the macro level, the influence of the arrangement structure of
individual pores on the processes of water vapor interaction with porous
material as a continuous medium is studied. At the micro level, it is very
interesting to investigate the dependence of the characteristics of the water
vapor interaction with porous media on the geometry and dimensions of the
individual pore.
In this paper, a study was carried out by means of mathematical modelling of
the processes of water vapor interaction with suffering pore of the cylindrical
type. The calculations were performed using a model of a hybrid type combining
a molecular-dynamic and a macro-diffusion approach for describing water vapor
interaction with an individual pore. The processes of evolution to the state of
thermodynamic equilibrium of macroscopic characteristics of the system such as
temperature, density, and pressure, depending on external conditions with
respect to pore, were explored. The dependence of the evolution parameters on
the distribution of the diffusion coefficient in the pore, obtained as a result
of molecular dynamics modelling, is examined. The relevance of these studies is
due to the fact that all methods and programs used for the modelling of the
moisture and heat conductivity are based on the use of transport equations in a
porous material as a continuous medium with known values of the transport
coefficients, which are usually obtained experimentally.
|
The 3D Human Pose Estimation (3D HPE) task uses 2D images or videos to
predict human joint coordinates in 3D space. Despite recent advancements in
deep learning-based methods, they mostly ignore the capability of coupling
accessible texts and naturally feasible knowledge of humans, missing out on
valuable implicit supervision to guide the 3D HPE task. Moreover, previous
efforts often study this task from the perspective of the whole human body,
neglecting fine-grained guidance hidden in different body parts. To this end,
we present a new Fine-Grained Prompt-Driven Denoiser based on a diffusion model
for 3D HPE, named \textbf{FinePOSE}. It consists of three core blocks enhancing
the reverse process of the diffusion model: (1) Fine-grained Part-aware Prompt
learning (FPP) block constructs fine-grained part-aware prompts via coupling
accessible texts and naturally feasible knowledge of body parts with learnable
prompts to model implicit guidance. (2) Fine-grained Prompt-pose Communication
(FPC) block establishes fine-grained communications between learned part-aware
prompts and poses to improve the denoising quality. (3) Prompt-driven Timestamp
Stylization (PTS) block integrates learned prompt embedding and temporal
information related to the noise level to enable adaptive adjustment at each
denoising step. Extensive experiments on public single-human pose estimation
datasets show that FinePOSE outperforms state-of-the-art methods. We further
extend FinePOSE to multi-human pose estimation. Achieving 34.3mm average MPJPE
on the EgoHumans dataset demonstrates the potential of FinePOSE to deal with
complex multi-human scenarios. Code is available at
https://github.com/PKU-ICST-MIPL/FinePOSE_CVPR2024.
|
High-precision calculations of hadron spectroscopy are a crucial task for
Lattice QCD. State-of-the-art techniques are needed to disentangle the
contributions from different energy states, such as solving the generalized
eigenvalue problem (GEVP) for zero-momentum hadron correlators in an efficient
way. We review the method and discuss its application in the determination of
the $B_s$-meson spectrum using (quenched) nonperturbative HQET at order
$1/m_b$.
|
The amplitudes for one-pion mediated transitions between heavy meson excited
states are obtained in the framework of the relativistic chiral quark model.
The effective coupling constants to pions and the decay widths of excited heavy
mesons with l<=2 for non-radially excited, and the l=0 radially excited mesons
are presented for both charmed and beauty mesons. We also discuss the allowed
decays of strange excited heavy mesons by emission of a K-meson.
|
Circadian clocks play a pivotal role in orchestrating numerous physiological
and developmental events. Waveform shapes of the oscillations of protein
abundances can be informative about the underlying biochemical processes of
circadian clocks. We derive a mathematical framework where waveforms do reveal
hidden biochemical mechanisms of circadian timekeeping. We find that the cost
of synthesizing proteins with particular waveforms can be substantially reduced
by rhythmic protein half-lives over time, as supported by previous plant and
mammalian data, as well as our own seedling experiment. We also find that
previously-enigmatic, cyclic expression of positive arm components within the
mammalian and insect clocks allows both a broad range of peak time differences
between protein waveforms and the symmetries of the waveforms about the peak
times. Such various peak-time differences may facilitate tissue-specific or
developmental stage-specific multicellular processes. Our waveform-guided
approach can be extended to various biological oscillators, including
cell-cycle and synthetic genetic oscillators.
|
The formalism to treat quantization and evolution of cosmological
perturbations of multiple fluids is described. We first construct the
Lagrangian for both the gravitational and matter parts, providing the necessary
relevant variables and momenta leading to the quadratic Hamiltonian describing
linear perturbations. The final Hamiltonian is obtained without assuming any
equations of motions for the background variables. This general formalism is
applied to the special case of two fluids, having in mind the usual radiation
and matter mix which made most of our current Universe history. Quantization is
achieved using an adiabatic expansion of the basis functions. This allows for
an unambiguous definition of a vacuum state up to the given adiabatic order.
Using this basis, we show that particle creation is well defined for a suitable
choice of vacuum and canonical variables, so that the time evolution of the
corresponding quantum fields is unitary. This provides constraints for setting
initial conditions for an arbitrary number of fluids and background time
evolution. We also show that the common choice of variables for quantization
can lead to an ill-defined vacuum definition. Our formalism is not restricted
to the case where the coupling between fields is small, but is only required to
vary adiabatically with respect to the ultraviolet modes, thus paving the way
to consistent descriptions of general models not restricted to single-field (or
fluid).
|
The introduction of ChatGPT has led to a significant increase in the
utilization of Large Language Models (LLMs) for addressing downstream tasks.
There's an increasing focus on cost-efficient training and deployment within
this context. Low-cost training and deployment of LLMs represent the future
development trend. This paper reviews the evolution of large language model
training techniques and inference deployment technologies aligned with this
emerging trend. The discussion on training includes various aspects, including
data preprocessing, training architecture, pre-training tasks, parallel
training, and relevant content related to model fine-tuning. On the inference
side, the paper covers topics such as model compression, parallel computation,
memory scheduling, and structural optimization. It also explores LLMs'
utilization and provides insights into their future development.
|
Using Spitzer Space Telescope photometric observations of the eclipsing,
interacting binary WZ Sge, we have discovered that the accretion disk is far
more complex than previously believed. Our 4.5 and 8 micron time series
observations reveal that the well known gaseous accretion disk is surrounded by
an asymmetric disk of dusty material with a radius approximately 15 times
larger than the gaseous disk. This dust ring contains only a small amount of
mass and is completely invisible at optical and near-IR wavelengths, hence
consisting of "dark matter". We have produced a model dust ring using 1 micron
spherical particles with a density of 3 g/cm$^3$ and with a temperature profile
ranging from 700-1500K. Our discovery about the accretion disk structure and
the presence of a larger, outer dust ring have great relevance for accretion
disks in general, including those in other interacting binary systems, pre-main
sequence stars, and active galaxies.
|
In this work we present the $\alpha'$-exact background equations of motion of
the bosonic chiral string (also known as Hohm-Siegel-Zwiebach model), with the
spin two ghost fields integrated out. This is the first instance of a
worldsheet model in which all corrections are fully determined in a generic
curved spacetime. As a concrete cross-check, we find complete agreement between
all three-point and a sample of four-point tree level scattering amplitudes
computed using field theory methods and the chiral string prescription. These
equations of motion provide a field theoretical shortcut to compute worldsheet
correlators in conventional bosonic strings (with arbitrary number of massless
and mass level one states), and outline a new perspective on massive resonances
in string theory.
|
We present a solution to the Burnside Problem for 2 generator groups of
prime-power exponent that does not rely on induced maps as in [2]. As before,
we construct a surjective map of a rank 2 free group to a solvable group G and
finish by showing that the Burnside group is an image of G. Theorem B in the
paper with H. A. Heilbronn and H. Y. Mochizuki [9] is indispensable in the
proof.
|
Commercial and industrial deployments of robot fleets at Amazon, Nimble, Plus
One, Waymo, and Zoox query remote human teleoperators when robots are at risk
or unable to make task progress. With continual learning, interventions from
the remote pool of humans can also be used to improve the robot fleet control
policy over time. A central question is how to effectively allocate limited
human attention. Prior work addresses this in the single-robot, single-human
setting; we formalize the Interactive Fleet Learning (IFL) setting, in which
multiple robots interactively query and learn from multiple human supervisors.
We propose Return on Human Effort (ROHE) as a new metric and Fleet-DAgger, a
family of IFL algorithms. We present an open-source IFL benchmark suite of
GPU-accelerated Isaac Gym environments for standardized evaluation and
development of IFL algorithms. We compare a novel Fleet-DAgger algorithm to 4
baselines with 100 robots in simulation. We also perform a physical
block-pushing experiment with 4 ABB YuMi robot arms and 2 remote humans.
Experiments suggest that the allocation of humans to robots significantly
affects the performance of the fleet, and that the novel Fleet-DAgger algorithm
can achieve up to 8.8x higher ROHE than baselines. See
https://tinyurl.com/fleet-dagger for supplemental material.
|
In this paper we propose a process of Lagrangian reduction and reconstruction
for symmetric discrete-time mechanical systems acted on by external forces,
where the symmetry group action on the configuration manifold turns it into a
principal bundle. We analyze the evolution of momentum maps and Poisson
structures under different conditions.
|
We introduce two extensions of the Segal-Bargmann coherent state transform
from $L^2({\mathbb R},dx)$ to Hilbert spaces of slice monogenic and axial
monogenic functions and study their properties. These two transforms are
related by the dual Radon transform. Representation theoretic and quantum
mechanical aspects of the new representations are studied.
|
We give arguments that in the 1+1 dimensional abelian Higgs model the
classical approximation can be good for the leading high temperature behavior
of real time processes. The Chern-Simons diffusion rate (`sphaleron rate') is
studied numerically in this approximation. New results at high temperature show
a $T^{2/3}$ behavior of the rate at sufficiently small lattice spacing.
|
We examine the effect of spatial resolution on initial mass ejection in
grid-based hydrodynamic simulations of binary neutron star mergers. The subset
of the dynamical ejecta with velocities greater than $\sim 0.6$c can generate
an ultraviolet precursor to the kilonova on $\sim$hr timescales and contribute
to a years-long non-thermal afterglow. Previous work has found differing
amounts of this fast ejecta, by one- to two orders of magnitude, when using
particle-based or grid-based hydrodynamic methods. Here we carry out a
numerical experiment that models the merger as an axisymmetric collision in a
co-rotating frame, accounting for Newtonian self-gravity, inertial forces, and
gravitational wave losses. The lower computational cost allows us to reach
spatial resolutions as high as $4$m, or $\sim 3\times 10^{-4}$ of the stellar
radius. We find that fast ejecta production converges to within $10\%$ for a
cell size of $20$m. This suggests that fast ejecta quantities found in existing
grid-based merger simulations are unlikely to increase to the level needed to
match particle-based results upon further resolution increases. The resulting
neutron-powered precursors are in principle detectable out to distances
$\lesssim 200$Mpc with upcoming facilities. We also find that head-on
collisions at the free-fall speed, relevant for eccentric mergers, yield fast
and slow ejecta quantities of order $10^{-2}M_\odot$, with a kilonova signature
distinct from that of quasi-circular mergers.
|
Results of systematic measurements of Sr-90 activity concentrations in milk
for the period 1961 - 2001 are summarized. An exponential decline of
radioactivity followed the moratorium on atmospheric nuclear testing. The
highest activity of Sr-90 deposited by fallout, being 1060 Bq/m2, was recorded
in 1963, while the peak Sr-90 activity concentration in milk, 1.42 +/-0.17
Bq/L, was recorded in 1964. The values in year 2001 for fallout deposition and
milk were 7.7 Bq/m2 and 0.07 +/- 0.03 Bq/L, respectively. The reactor accident
at Chernobyl caused higher Sr-90 levels only in 1986. Sr-90 fallout activity
affects milk activity, the coefficient of correlation between Sr-90 fallout
activity and Sr-90 activity concentrations in milk being 0.80. The transfer
coefficient from fallout deposition to milk was estimated to be 2.5 mBqy/L per
Bq/m2. The dose incurred by milk consumption was estimated for the Croatian
population, the annual collective effective dose in 2001 being approximately
2.0 man-Sv.
|
Molecular dynamics (MD) simulations are used to determine the diffusion
coefficients, electrophoretic mobilities and electrical conductivity of a
charged colloidal suspension in the salt-free regime as a function of the
colloid charge. The behavior of the colloidal particles' diffusion constant can
be well understood in terms of two coupled effects: counterion 'condensation'
and slowdown due to the relaxation effect. We find that the conductivity
exhibits a maximum which approximately separates the regimes of
counterion-dominated and colloid-dominated conduction. We analyze the
electrophoretic mobilities and the conductivity in terms of commonly employed
assumptions about the role of "free" and "condensed" counterions, and discuss
different interpretations of this approach.
|
As a rising star in the field of natural language processing, question
answering systems (Q&A Systems) are widely used in all walks of life. Compared
with other scenarios, the applicationin financial scenario has strong
requirements in the traceability and interpretability of the Q&A systems. In
addition, since the demand for artificial intelligence technology has gradually
shifted from the initial computational intelligence to cognitive intelligence,
this research mainly focuses on the financial numerical reasoning dataset -
FinQA. In the shared task, the objective is to generate the reasoning program
and the final answer according to the given financial report containing text
and tables. We use the method based on DeBERTa pre-trained language model, with
additional optimization methods including multi-model fusion, training set
combination on this basis. We finally obtain an execution accuracy of 68.99 and
a program accuracy of 64.53, ranking No. 4 in the 2022 FinQA Challenge.
|
Open Source Software (OSS) often relies on large repositories, like
SourceForge, for initial incubation. The OSS repositories offer a large variety
of meta-data providing interesting information about projects and their
success. In this paper we propose a data mining approach for training
classifiers on the OSS meta-data provided by such data repositories. The
classifiers learn to predict the successful continuation of an OSS project. The
`successfulness' of projects is defined in terms of the classifier confidence
with which it predicts that they could be ported in popular OSS projects (such
as FreeBSD, Gentoo Portage).
|
The optical filaments found in many cooling flows in galaxy clusters consist
of low density ($\sim 10^3 \pcc$) cool ($\sim 10^3$ K) gas surrounded by
significant amounts of cosmic-ray and magnetic-field energy. Their spectra show
anomalously strong low-ionization and molecular emission lines when compared
with galactic molecular clouds exposed to ionizing radiation such as the Orion
complex. Previous studies have shown that the spectra cannot be produced by
O-star photoionization. Here we calculate the physical conditions in dusty gas
that is well shielded from external sources of ionizing photons and is
energized either by cosmic rays or dissipative MHD waves. Strong molecular
hydrogen lines, with relative intensities similar to those observed, are
produced. Selection effects introduced by the microphysics produce a
correlation between the \htwo line upper level energy and the population
temperature. These selection effects allow a purely collisional gas to produce
\htwo emission that masquerades as starlight-pumped \htwo but with intensities
that are far stronger. This physics may find application to any environment
where a broad range of gas densities or heating rates occur.
|
Recent developments in multiscale computation allow the solution of ``coarse
equations'' for the expected macroscopic behavior of
microscopically/stochastically evolving particle distributions without ever
obtaining these coarse equations in closed form. The closure is obtained ``on
demand'' through appropriately initialized bursts of microscopic simulation.
The effective coupling of microscopic simulators with macrosocopic behavior
embodied in this approach requires certain decisions about the nature of the
unavailable ``coarse equation''. Such decisions include (a) the determination
of the highest spatial derivative active in the equation, (b) whether the
coarse equation satisfies certain conservation laws, and (c) whether the coarse
dynamics is Hamiltonian. These decisions affect the number and type of boundary
conditions as well as the nature of the algorithms employed in good solution
practice. In the absence of an explicit formula for the temporal derivative, we
propose, implement and validate a simple scheme for deciding these and other
similar questions about the coarse equation using only the microscopic
simulator. Microscopic simulations under periodic boundary conditions are
carried out for appropriately chosen families of random initial conditions;
evaluating the sample variance of certain statistics over the simulation
ensemble allows us to infer the highest order of spatial derivatives active in
the coarse equation. In the same spirit we show how to determine whether a
certain coarse conservation law exists or not, and we discuss plausibility
tests for the existence of a coarse Hamiltonian or integrability. We argue that
such schemes constitute an important part of the equation-free approach to
multiscale computation.
|
Interest in van der Waals materials often stems from a desire to miniaturise
existing technologies by exploiting their intrinsic layered structure to create
near atomically-thin components that do not suffer from surface defects. One
appealing property is easily-switchable yet robust magnetic order, a quality
only sparsely demonstrated in the case of in-plane anisotropy. In this work, we
use widefield nitrogen-vacancy (NV) center magnetic imaging to measure the
properties of individual flakes of CuCrP$_2$S$_6$, a multiferroic van der Waals
magnet known to exhibit weak easy-plane anisotropy in the bulk. We chart the
crossover between in-plane ferromagnetism in thin flakes down to the trilayer,
and the bulk behaviour dominated by a low-field spin-flop transition. Further,
by exploiting the directional dependence of NV center magnetometry, we are able
to observe an instance of a predominantly out-of-plane ferromagetic phase near
zero field, in contradiction with expectation and previous experiments on the
bulk material. We attribute this to the presence of surface anisotropies
arising from the sample preparation process or exposure to the ambient
environment, which is expected to have more general implications for a broader
class of weakly anisotropic van der Waals magnets.
|
Mobile video consumption is increasing and sophisticated video quality
adaptation strategies are required to deal with mobile throughput fluctuations.
These adaptation strategies have to keep the switching frequency low, the
average quality high and prevent stalling occurrences to ensure customer
satisfaction. This paper proposes a novel methodology for the design of machine
learning-based adaptation logics named HASBRAIN. Furthermore, the performance
of a trained neural network against two algorithms from the literature is
evaluated. We first use a modified existing optimization formulation to
calculate optimal adaptation paths with a minimum number of quality switches
for a wide range of videos and for challenging mobile throughput patterns.
Afterwards we use the resulting optimal adaptation paths to train and compare
different machine learning models. The evaluation shows that an artificial
neural network-based model can reach a high average quality with a low number
of switches in the mobile scenario. The proposed methodology is general enough
to be extended for further designs of machine learning-based algorithms and the
provided model can be deployed in on-demand streaming scenarios or be further
refined using reward-based mechanisms such as reinforcement learning. All
tools, models and datasets created during the work are provided as open-source
software.
|
A Massey-like inequality is any useful lower bound on guessing entropy in
terms of the computationally scalable Shannon entropy. The asymptotically
optimal Massey-like inequality is determined and further refined for
finite-support distributions. The impact of these results are highlighted for
side-channel attack evaluation where guessing entropy is a key metric. In this
context, the obtained bounds are compared to the state of the art.
|
Based on symmetry consideration of migration and shape deformations, we
formulate phenomenologically the dynamics of cell crawling in two dimensions.
Forces are introduced to change the cell shape. The shape deformations induce
migration of the cell on a substrate. For time-independent forces we show that
not only a stationary motion but also a limit cycle oscillation of the
migration velocity and the shape occurs as a result of nonlinear coupling
between different deformation modes. Time-dependent forces are generated in a
stochastic manner by utilizing the so-called coherence resonance of an
excitable system. The present coarse-grained model has a flexibility that it
can be applied, e.g., both to keratocyte cells and to Dictyostelium cells,
which exhibit quite different dynamics from each other. The key factors for the
motile behavior inherent in each cell type are identified in our model.
|
Time-resolved angle-resolved photoemission spectroscopy is one of the most
powerful pump-probe measurements of materials driven far from equilibrium.
Unlike the linear-response regime, where the frequency-dependent response
function is independent of time, in a far-from-equilibrium experiment, the
response function depends on two times in the time domain. In this work, we
describe how one can use time-dependent frequency response functions and how
they involve contributions from times that are near to each other. This implies
that they should not be thought of as a frequency-dependent response at a
single definite time. Instead, the Fourier uncertainty relations show that they
involve contributions from ranges of times and must be interpreted in this
light. We use this insight to help understand what time-resolved photoemission
measurements actually measure.
|
Black-box variational inference performance is sometimes hindered by the use
of gradient estimators with high variance. This variance comes from two sources
of randomness: Data subsampling and Monte Carlo sampling. While existing
control variates only address Monte Carlo noise, and incremental gradient
methods typically only address data subsampling, we propose a new "joint"
control variate that jointly reduces variance from both sources of noise. This
significantly reduces gradient variance, leading to faster optimization in
several applications.
|
Graphs are a fundamental data structure used to represent relationships in
domains as diverse as the social sciences, bioinformatics, cybersecurity, the
Internet, and more. One of the central observations in network science is that
real-world graphs are globally sparse, yet contains numerous "pockets" of high
edge density. A fundamental task in graph mining is to discover these dense
subgraphs. Most common formulations of the problem involve finding a single (or
a few) "optimally" dense subsets. But in most real applications, one does not
care for the optimality. Instead, we want to find a large collection of dense
subsets that covers a significant fraction of the input graph.
We give a mathematical formulation of this problem, using a new definition of
regularly triangle-rich (RTR) families. These families capture the notion of
dense subgraphs that contain many triangles and have degrees comparable to the
subgraph size. We design a provable algorithm, RTRExtractor, that can discover
RTR families that approximately cover any RTR set. The algorithm is efficient
and is inspired by recent results that use triangle counts for community
testing and clustering.
We show that RTRExtractor has excellent behavior on a large variety of
real-world datasets. It is able to process graphs with hundreds of millions of
edges within minutes. Across many datasets, RTRExtractor achieves high coverage
using high edge density datasets. For example, the output covers a quarter of
the vertices with subgraphs of edge density more than (say) $0.5$, for datasets
with 10M+ edges. We show an example of how the output of RTRExtractor
correlates with meaningful sets of similar vertices in a citation network,
demonstrating the utility of RTRExtractor for unsupervised graph discovery
tasks.
|
Subsets and Splits