We study the large scale fluctuations of the solution of a nonlinear stochastic heat equation (SHE) in dimensions $d \geq 3$ driven by a multiplicative Gaussian noise, white in time and coloured in space with non-integrable spatial covariance decaying at the rate of $|x|^{-\kappa}$, with $\kappa \in (2, d)$. Motivated by recent works on SHE and KPZ driven by noise with compactly supported spatial correlation, we show that the fluctuations converge to the solution of a stochastic heat equation with an explicit additive spatially correlated noise that has a Riesz kernel of degree $-\kappa$ as its spatial covariance. The convergence of the fluctuations is shown to take place in the optimal H\"older topologies.

We introduce a new class of spatially stochastic physics and data informed deep latent models for parametric partial differential equations (PDEs) which operate through scalable variational neural processes. We achieve this by assigning probability measures to the spatial domain, which allows us to treat collocation grids probabilistically as random variables to be marginalised out. Adapting this spatial statistics view, we solve forward and inverse problems for parametric PDEs in a way that leads to the construction of Gaussian process models of solution fields. The implementation of these random grids poses a unique set of challenges for inverse physics informed deep learning frameworks and we propose a new architecture called Grid Invariant Convolutional Networks (GICNets) to overcome these challenges. We further show how to incorporate noisy data in a principled manner into our physics informed model to improve predictions for problems where data may be available but whose measurement location does not coincide with any fixed mesh or grid. The proposed method is tested on a nonlinear Poisson problem, Burgers equation, and Navier-Stokes equations, and we provide extensive numerical comparisons. We demonstrate significant computational advantages over current physics informed neural learning methods for parametric PDEs while improving the predictive capabilities and flexibility of these models.

We derive a parameterization formula for the partial wave analyses of charmed meson semi-leptonic decays while considering the effects of lepton mass. Because the proposed super-tau-charm factory will reach a significantly enhanced luminosity and BESIII is collecting new $ \psi(3770)\to D\bar{D} $ data, our results will help improve the measurement precision of future partial wave analyses of charmed meson semi-muonic decays.

In this paper, a version of the Polyakov-Nambu-Jona-Lasinio (PNJL) model based on nonextensive statistical mechanics is presented. This new statistics summarizes all possible factors that violate the assumptions of the Boltzmann-Gibbs (BG) statistics to a dimensionless nonextensivity parameter q. Thus, when q tends to 1, it returns to the BG case. Within the nonextensive PNJL model, we found that as q increases, the location of the critical end point (CEP) exhibits non-monotonic behavior. That is, for $ q<1.15 $ , CEP moves in the direction of lower temperature and larger quark chemical potential. However, for $ q<1.15 $ , CEP turns to move in the direction of lower temperature and lower quark chemical potential. In addition, we studied the moments of the net-baryon number distribution, that is, variance ( $ q<1.15 $ ), skewness (S), and kurtosis (κ). Our results are generally consistent with the latest experimental data reported, especially for $ q<1.15 $ , when q is set to $ q<1.15 $ .

We study the mass spectra of D-wave excited $ cs\bar{c}\bar{s} $ tetraquark states with $ cs\bar{c}\bar{s} $ and $ cs\bar{c}\bar{s} $ in both symmetric $ cs\bar{c}\bar{s} $ and antisymmetric $ cs\bar{c}\bar{s} $ color configurations using the QCD sum rule method. We construct the D-wave diquark-antidiquark type of $ cs\bar{c}\bar{s} $ tetraquark interpolating currents in various excitation structures with $ cs\bar{c}\bar{s} $ . Our results support the interpretation of the recently observed $ cs\bar{c}\bar{s} $ resonance as a D-wave $ cs\bar{c}\bar{s} $ tetraquark state with $ cs\bar{c}\bar{s} $ in the $ cs\bar{c}\bar{s} $ or $ cs\bar{c}\bar{s} $ excitation mode, although some other possible excitation structures cannot be excluded exhaustively within theoretical errors. Moreover, our results provide the mass relations $ cs\bar{c}\bar{s} $ and $ cs\bar{c}\bar{s} $ for the positive and negative $ cs\bar{c}\bar{s} $ -parity D-wave $ cs\bar{c}\bar{s} $ tetraquarks, respectively. We suggest searching for these possible D-wave $ cs\bar{c}\bar{s} $ tetraquarks in both the hidden-charm channels $ cs\bar{c}\bar{s} $ and $ cs\bar{c}\bar{s} $ , as well as open-charm channels such as $ cs\bar{c}\bar{s} $ and $ cs\bar{c}\bar{s} $ .

We propose to use affect as a proxy for mood in literary texts. In this study, we explore the differences in computationally detecting tone versus detecting mood. Methodologically we utilize affective word embeddings to look at the affective distribution in different text segments. We also present a simple yet efficient and effective method of enhancing emotion lexicons to take both semantic shift and the domain of the text into account producing real-world congruent results closely matching both contemporary and modern qualitative analyses.

The production of vector boson tagged heavy quark jets potentially provides new tools to probe the jet quenching effect. In this paper, we present the first theoretical study on the angular correlations ( $ \Delta\phi_{bZ} $ ), transverse momentum imbalance ( $ \Delta\phi_{bZ} $ ), and nuclear modification factor ( $ \Delta\phi_{bZ} $ ) of $ \Delta\phi_{bZ} $ boson tagged b-jets in heavy-ion collisions, which was performed using a Monte Carlo transport model. We find that the medium modification of the $ \Delta\phi_{bZ} $ for $ \Delta\phi_{bZ} $ + b-jet has a weaker dependence on $ \Delta\phi_{bZ} $ than that for $ \Delta\phi_{bZ} $ + jet, and the modification patterns are sensitive to the initial jet $ \Delta\phi_{bZ} $ distribution. Additionally, with the high purity of the quark jet in $ \Delta\phi_{bZ} $ + (b-) jet production, we calculate the momentum imbalance $ \Delta\phi_{bZ} $ and the nuclear modification factor $ \Delta\phi_{bZ} $ of $ \Delta\phi_{bZ} $ + b-jet in Pb+Pb collisions. We observe a smaller $ \Delta\phi_{bZ} $ and larger $ \Delta\phi_{bZ} $ of $ \Delta\phi_{bZ} $ + b-jet in Pb+Pb collisions relative to those of $ \Delta\phi_{bZ} $ + jet, which may be an indication of the mass effect of jet quenching and can be tested in future measurements.

Deep learning based image enhancement models have largely improved the readability of fundus images in order to decrease the uncertainty of clinical observations and the risk of misdiagnosis. However, due to the difficulty of acquiring paired real fundus images at different qualities, most existing methods have to adopt synthetic image pairs as training data. The domain shift between the synthetic and the real images inevitably hinders the generalization of such models on clinical data. In this work, we propose an end-to-end optimized teacher-student framework to simultaneously conduct image enhancement and domain adaptation. The student network uses synthetic pairs for supervised enhancement, and regularizes the enhancement model to reduce domain-shift by enforcing teacher-student prediction consistency on the real fundus images without relying on enhanced ground-truth. Moreover, we also propose a novel multi-stage multi-attention guided enhancement network (MAGE-Net) as the backbones of our teacher and student network. Our MAGE-Net utilizes multi-stage enhancement module and retinal structure preservation module to progressively integrate the multi-scale features and simultaneously preserve the retinal structures for better fundus image quality enhancement. Comprehensive experiments on both real and synthetic datasets demonstrate that our framework outperforms the baseline approaches. Moreover, our method also benefits the downstream clinical tasks.

The CDF collaboration recently announced a new measurement result for the W boson mass, and it is in tension with the standard model prediction. In this paper, we explain this anomaly in the vector-like quark (VLQ) $ (X,T,B)_{L,R} $ and leptoquark (LQ) $ (X,T,B)_{L,R} $ extended model. In this model, both the VLQ and LQ have positive corrections to the W boson mass. Moreover, it may be a solution to the $ (X,T,B)_{L,R} $ anomaly because of the chiral enhancements from top, T, and B quarks.

Theorists have given various explanations for the discovery of Y(4630). We find that if Y(4630) is interpreted as the D-wave resonant state of the $ \Lambda_c \bar {\Lambda}_c $ system, the particle mass, decay width, and all quantum numbers are consistent with experimental observations. We use the Bonn approximation to obtain the interaction potential of the one boson exchange model. Then, we extend the complex scaling method to calculate the bound and resonant states. The results indicate that the $ \Lambda_c \bar {\Lambda}_c $ system can form not only the bound state of the S wave but also the resonant state of the high angular momentum, and the $ \Lambda_c \bar {\Lambda}_c $ wave resonant state can explain the structure of Y(4630) very well.