2,516 research outputs found
Numerical Strategies of Computing the Luminosity Distance
We propose two efficient numerical methods of evaluating the luminosity
distance in the spatially flat {\Lambda}CDM universe. The first method is based
on the Carlson symmetric form of elliptic integrals, which is highly accurate
and can replace numerical quadratures. The second method, using a modified
version of Hermite interpolation, is less accurate but involves only basic
numerical operations and can be easily implemented. We compare our methods with
other numerical approximation schemes and explore their respective features and
limitations. Possible extensions of these methods to other cosmological models
are also discussed.Comment: 4 pages, 2 figures. v2: A minor error in the last equation has been
corrected (conclusions are not affected). v3: Accepted by MNRA
The New Formulation of Higgs Effective Field Theory
We present the explicit construction of the effective field theory (EFT) of
standard model mass eigenstates. The EFT, which is invariant under
, is constructed based on the on-shell method
and Young Tableau technique. This EFT serves as a new formulation of the Higgs
EFT (HEFT), which can describe the infrared effects of new physics at the
electroweak symmetry-breaking phase with greater conciseness. The current HEFT
operator basis has a clear physical interpretation, making it more accessible
for research in phenomenology. A complete list of HEFT operator bases for
any-point vertices up to any dimension could be provided, and three- and
four-point bases are provided as examples. Additionally, this framework
realized as a Mathematica program can be used to construct the EFT of any type
of dark matter or particles with any spin
Dynamical signature of fractionalization at a deconfined quantum critical point
Deconfined quantum critical points govern continuous quantum phase transitions at which fractionalized (deconfined) degrees of freedom emerge. Here we study dynamical signatures of the fractionalized excitations in a quantum magnet (the easy-plane J-Q model) that realize a deconfined quantum critical point with emergent O(4) symmetry. By means of large-scale quantum Monte Carlo simulations and stochastic analytic continuation of imaginary-time correlation functions, we obtain the dynamic spin-structure factors in the
S
x
and
S
z
channels. In both channels, we observe broad continua that originate from the deconfined excitations. We further identify several distinct spectral features of the deconfined quantum critical point, including the lower edge of the continuum and its form factor on moving through the Brillouin zone. We provide field-theoretical and lattice model calculations that explain the overall shapes of the computed spectra, which highlight the importance of interactions and gauge fluctuations to explain the spectral-weight distribution. We make further comparisons with the conventional Landau O(2) transition in a different quantum magnet, at which no signatures of fractionalization are observed. The distinctive spectral signatures of the deconfined quantum critical point suggest the feasibility of its experimental detection in neutron scattering and nuclear magnetic resonance experiments.First author draf
Flare-Aware Cross-modal Enhancement Network for Multi-spectral Vehicle Re-identification
Multi-spectral vehicle re-identification aims to address the challenge of
identifying vehicles in complex lighting conditions by incorporating
complementary visible and infrared information. However, in harsh environments,
the discriminative cues in RGB and NIR modalities are often lost due to strong
flares from vehicle lamps or sunlight, and existing multi-modal fusion methods
are limited in their ability to recover these important cues. To address this
problem, we propose a Flare-Aware Cross-modal Enhancement Network that
adaptively restores flare-corrupted RGB and NIR features with guidance from the
flare-immunized thermal infrared spectrum. First, to reduce the influence of
locally degraded appearance due to intense flare, we propose a Mutual Flare
Mask Prediction module to jointly obtain flare-corrupted masks in RGB and NIR
modalities in a self-supervised manner. Second, to use the flare-immunized TI
information to enhance the masked RGB and NIR, we propose a Flare-Aware
Cross-modal Enhancement module that adaptively guides feature extraction of
masked RGB and NIR spectra with prior flare-immunized knowledge from the TI
spectrum. Third, to extract common informative semantic information from RGB
and NIR, we propose an Inter-modality Consistency loss that enforces semantic
consistency between the two modalities. Finally, to evaluate the proposed
FACENet in handling intense flare, we introduce a new multi-spectral vehicle
re-ID dataset, called WMVEID863, with additional challenges such as motion
blur, significant background changes, and particularly intense flare
degradation. Comprehensive experiments on both the newly collected dataset and
public benchmark multi-spectral vehicle re-ID datasets demonstrate the superior
performance of the proposed FACENet compared to state-of-the-art methods,
especially in handling strong flares. The code and dataset will be released
soon
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