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In this talk, we present a new interpretation for the recently observed $\Xi(1820)$ resonance. We recall that the chiral unitary approach for the interaction of pseudoscalar mesons with the baryons of the decuplet predicts two states for the $\Xi(1820)$ resonance, one with a narrow width and the other one with a large width. We contrast this fact with the recent BESIII measurement of the $K^- \Lambda$ mass distribution in the $\psi(3686)$ decay to $K^- \Lambda \bar\Xi^+ $, which demands a width much larger than the average of the PDG, and show how the consideration of the two $\Xi(1820)$ states provides a natural explanation to this apparent contradiction., Comment: Proceeding of the QNP 2024 Conference. 6 pages, 3 figures, 1 table. arXiv admin note: substantial text overlap with arXiv:2309.03618

We report on the reactions $\psi(3770)\to \bar{\Omega}^+ \bar{K} \Xi $ and $\psi(3770)\to \bar{\Omega}^+ \bar{K}\Xi^*(1530)~(\Xi^*(1530)\to \pi\Xi $), and calculate the mass distributions $\frac{{\rm d}\Gamma}{{\rm d}M_\text{inv}(\bar{K}\Xi)}$ and $\frac{{\rm d}\Gamma}{{\rm d}M_\text{inv}(\bar{K}\Xi^*)}$, respectively. We obtain clear peaks corresponding to the $\Omega(2012)$. From the decay of $\psi(3770)\to \bar{\Omega}^+ \bar{K}\Xi^*$, we also get a second, broader, peak around $2035\,\rm MeV$, which comes from the $\Omega(2012)$ decay to $\bar{K}\Xi^*$. This second peak is closely tied to the molecular picture of the $\Omega(2012)$ with the $\bar{K}\Xi^*(1530)$ and $\eta\Omega$ components. Its observation would provide a boost to the molecular picture of the $\Omega(2012)$., Comment: 6 pages, 5 figures;V2: new reference and footnote added

We analyze the clean cusp, seen in the $\eta \pi$ mass distribution with high precision of the $\chi_{c1} \to \eta \pi^+ \pi^-$ reaction in the BESIII experiment, with the aim of making a precise determination of the scattering length $a$ and effective range $r_0$ of $K^+ \bar{K}^{0}$. For that, we follow a previous theoretical work that gave a good reproduction of these data using the chiral unitary approach for the meson-meson interaction, and allow some flexibility in the input to carry a better fit to the data. The important task of determining the uncertainties in the scattering parameters is done using the resampling method and an accuracy in $a$ and $r_0$ is obtained better than $20\%$. The effective range is determined for the first time with this analysis., Comment: 7 pages, 4 figures, 3 tables; V2: New fit with background included

We calculate the correlation functions for the $\bar K^0 p, \pi^+ \Sigma^0, \pi^0 \Sigma^+, \pi^+ \Lambda$, and $\eta \Sigma^+$ states, which in the chiral unitary approach predict an excited $\Sigma^*(1/2^-)$ state at the $\bar K N$ threshold, recently observed by the Belle collaboration. Once this is done, we tackle the inverse problem of seeing how much information one can obtain from these correlation functions. With the resampling method, one can determine the scattering parameters of all the channels with relative precision by means of the analysis in a general framework, and find a clear cusp-like structure corresponding to the $\Sigma^*(1/2^-)$ in the different amplitudes at the $\bar{K}N$ threshold., Comment: 10 pages, 4 figures, 7 tables

We start from a recently favored picture in which the $\Lambda_c(2940)$ and $\Lambda_c(2910)$ correspond mostly to $ND^*$ bound states with $J^P = 1/2^-,\, 3/2^-$ and then add a $D$ as a third particle, looking for the possible binding of the $DND^*$ three body system within the framework of the Fixed Center Approximation. We find that the system is bound with respect to the corresponding $\Lambda_c^* D$ threshold with a binding of about $60$ MeV and a width of about $90$ MeV. Alternatively we assume a cluster of $ND$ and a $D^*$ meson interacting with the cluster and we find similar results. The observation of these states of $J^P = 1/2^+,\, 3/2^+$ would provide new and valuable information concerning the $DN$ and $D^* N$ interaction, an issue of current debate., Comment: 9 pages, 4 figures

We propose the reaction $\psi(3686) \to \bar{\Xi}^+ \bar{K}^0 \Sigma^{*-}$, with the $\Sigma^{*-}$ decaying to $\pi^- \Lambda$ in order to show evidence for the existence of two $\Xi(1820)$ states, one around $1824$ MeV and narrow, and another one around $1875$ MeV and wide. The phase space for $\bar{K}^0 \Sigma^{*-}$ production reduces the effect of the lower mass resonance, magnifying the effect of the higher mass resonance that shows clearly over the phase space. The estimated rate of the production is bigger than the one of the $\psi(3686) \to \bar{\Xi}^+ K^- \Lambda$ reaction, where a clear peak for $\Xi(1820)$ was observed by the BESIII collaboration, what makes the Beijing facility ideal to carry out the reaction proposed., Comment: 4 pages, 2 figures, 1 table

We have studied the $\Omega_c \to \pi^+ (\pi^0, \eta) \pi \Xi^*$ decays, where the final $\pi \Xi^*$ comes from the decay of two resonances around the nominal $\Xi(1820)$, which are generated from the interaction of coupled channels made of a pseudoscalar and a baryon of the decuplet. The $\pi \Xi^*$ mass distributions obtained in the six different reactions studied are quite different and we single out four of them, which are free of a tree level contribution, showing more clearly the effect of the resonances. The lower mass resonance is clearly seen as a sharp peak, but the higher mass resonance manifests itself through an interference with the lower one that leads to a dip in the mass distribution around $1850 \, {\rm MeV}$. Such a feature is similar to the dip observed in the $s$-wave $\pi \pi$ cross section around the $980 \, {\rm MeV}$ coming from the interference of the $f_0(500)$ and $f_0(980)$ resonances. Its observation in coming upgrades of present facilities will shed light on the existence of these two resonances and their nature., Comment: 7 pages, 4 figures

In the AI-for-science era, scientific computing scenarios such as concurrent learning and high-throughput computing demand a new generation of infrastructure that supports scalable computing resources and automated workflow management on both cloud and high-performance supercomputers. Here we introduce Dflow, an open-source Python toolkit designed for scientists to construct workflows with simple programming interfaces. It enables complex process control and task scheduling across a distributed, heterogeneous infrastructure, leveraging containers and Kubernetes for flexibility. Dflow is highly observable and can scale to thousands of concurrent nodes per workflow, enhancing the efficiency of complex scientific computing tasks. The basic unit in Dflow, known as an Operation (OP), is reusable and independent of the underlying infrastructure or context. Dozens of workflow projects have been developed based on Dflow, spanning a wide range of projects. We anticipate that the reusability of Dflow and its components will encourage more scientists to publish their workflows and OP components. These components, in turn, can be adapted and reused in various contexts, fostering greater collaboration and innovation in the scientific community.

Recently, the proximal Newton-type method and its variants have been generalized to solve composite optimization problems over the Stiefel manifold whose objective function is the summation of a smooth function and a nonsmooth function. In this paper, we propose an adaptive quadratically regularized proximal quasi-Newton method, named ARPQN, to solve this class of problems. Under some mild assumptions, the global convergence, the local linear convergence rate and the iteration complexity of ARPQN are established. Numerical experiments and comparisons with other state-of-the-art methods indicate that ARPQN is very promising. We also propose an adaptive quadratically regularized proximal Newton method, named ARPN. It is shown the ARPN method has a local superlinear convergence rate under certain reasonable assumptions, which demonstrates attractive convergence properties of regularized proximal Newton methods., Comment: 38 pages, 6 figures. Comput Optim Appl (2024)

In quantum information, the Werner state is a benchmark to test the boundary between quantum mechanics and classical models. There have been three well-known critical values for the two-qubit Werner state, i.e., $V_{\rm c}^{\rm E}=1/3$ characterizing the boundary between entanglement and separable model, $V_{\rm c}^{\rm B}=1/K_G(3)$ characterizing the boundary between Bell's nonlocality and the local-hidden-variable model, while $V_{\rm c}^{\rm S}=1/2$ characterizing the boundary between Einstein-Podolsky-Rosen (EPR) steering and the local-hidden-state model. So far, the problem of $V_{\rm c}^{\rm E}=1/3$ has been completely solved by an inequality involving in the positive-partial-transpose criterion, while how to reveal the other two critical values by the inequality approach are still open. In this work, we focus on EPR steering, which is a form of quantum nonlocality intermediate between entanglement and Bell's nonlocality. By proposing the optimal $N$-setting linear EPR-steering inequalities, we have successfully obtained the desired value $V_{\rm c}^{\rm S}=1/2$ for the two-qubit Werner state, thus resolving the long-standing problem., Comment: Main text: 6 pages, 2 figures; SM: 8 pages, 5 figures. Adding some references

In 2019, Neutron star Interior Composition ExploreR (NICER) mission released its findings on the mass and radius of the isolated neutron star (INS) PSR J0030+0451, revealing a mass of approximately 1.4 solar masses ($M_{\odot}$) and a radius near 13 kilometers. However, the recent re-analysis by the NICER collaboration \citep{vinciguerra2024updated} suggests that the available data primarily yields a precise inference of the compactness for this source while the resulting mass and radius are strongly model-dependent and diverse (the 68.3\% credible regions just overlap slightly for the ST+PDT and PDT-U models). By integrating this compactness data with the equation of state (EoS) refined by our latest investigations, we have deduced the mass and radius for PSR J0030+0451, delivering estimates of $M=1.48^{+0.09}_{-0.10}~M_\odot$ and $R=12.38_{-0.70}^{+0.51}~{\rm km}$ for the compactness found in ST+PDT model, alongside $M=1.47^{+0.14}_{-0.20}~M_\odot$ and $R=12.37_{-0.69}^{+0.50}~{\rm km}$ for the compactness in PDT-U model. These two groups of results are well consistent with each other and the direct X-ray data inference within the ST+PDT model seems to be favored. Additionally, we have calculated the tidal deformability, moment of inertia, and gravitational binding energy for this NS. Furthermore, employing these refined EoS models, we have updated mass-radius estimates for three INSs with established gravitational redshifts., Comment: 10 pages,6 figures, Accepted for publication in ApJ

The measurements of the bulk properties of most isolated neutron stars (INSs) are challenging tasks. Tang et al. (2020) have developed a new method, based on the equation of state (EoS) of neutron star (NS) material constrained by the observational data, to infer the gravitational masses of a few INSs whose gravitational redshifts are available. However, in that work, the authors only considered the constraints on the EoS from nuclear experiments/theories and the gravitational wave data of GW170817; the possible phase transition has not been taken into account. In this work, we adopt three EoS models (including the one incorporates a first-order strong phase transition) that are constrained by the latest multimessenger NS data, including in particular the recent mass\textendash radius measurements of two NSs by Neutron Star Interior Composition Explorer, to update the estimation of the gravitational masses of RBS 1223, RX J0720.4-3125, and RX J1856.5-3754. In comparison to our previous approach, the new constraints are tighter, and the gravitational masses are larger by about $0.1M_\odot$. All the inferred gravitational masses are within the range of the NS masses measured in other ways. We have also calculated the radius, tidal-deformability, and moment of inertia of these sources. The inclusion of the first-order strong phase transition has little influence on modifying the results., Comment: 8pages,4figures

We study the $D^+ \to \bar K^0 \pi^+ \eta$ reaction where the $a_0(980)$ excitation plays a dominant role. We consider mechanisms of external and internal emission at the quark level, hadronize the $q \bar q$ components into two mesons and allow these mesons to undergo final state interaction where the $a_0(980)$ state is generated. While the $a_0(980)$ production is the dominant term, we also find other terms in the reaction that interfere with this production mode and, through interference with it, lead to a shape of the $a_0(980)$ significantly different from the one observed in other experiments, with an apparently much larger width., Comment: 8 pages, 12 figures

We study the correlation functions of the $B^0 D^+, B^+ D^0$ system, which develops a bound state of approximately $40$ MeV, using inputs consistent with the $T_{cc}(3875)$ state. Then we address the inverse problem starting from these correlation functions to determine the scattering observables related to the system, including the existence of the bound state and its molecular nature. The important output of the approach is the uncertainty with which these observables can be obtained, considering errors in the $B^0 D^+, B^+ D^0$ correlation functions typical of current values in present correlation functions. We find that it is possible to obtain scattering lengths and effective ranges with relative high precision and the existence of a bound state. Although the pole position is obtained with errors of the order of $50 \%$ of the binding energy, the molecular probability of the state is obtained with a very small error of the order of $6\%$. All these findings can serve as motivation to perform such measurements in future runs of high energy hadron collisions., Comment: 16 pages, 3 figures, 7 tables; V2: version to be published in Chinese Physics C

Image segmentation is a clustering task whereby each pixel is assigned a cluster label. Remote sensing data usually consists of multiple bands of spectral images in which there exist semantically meaningful land cover subregions, co-registered with other source data such as LIDAR (LIght Detection And Ranging) data, where available. This suggests that, in order to account for spatial correlation between pixels, a feature vector associated with each pixel may be a vectorized tensor representing the multiple bands and a local patch as appropriate. Similarly, multiple types of texture features based on a pixel's local patch would also be beneficial for encoding locally statistical information and spatial variations, without necessarily labelling pixel-wise a large amount of ground truth, then training a supervised model, which is sometimes impractical. In this work, by resorting to label only a small quantity of pixels, a new semi-supervised segmentation approach is proposed. Initially, over all pixels, an image data matrix is created in high dimensional feature space. Then, t-SNE projects the high dimensional data onto 3D embedding. By using radial basis functions as input features, which use the labelled data samples as centres, to pair with the output class labels, a modified canonical correlation analysis algorithm, referred to as RBF-CCA, is introduced which learns the associated projection matrix via the small labelled data set. The associated canonical variables, obtained for the full image, are applied by k-means clustering algorithm. The proposed semi-supervised RBF-CCA algorithm has been implemented on several remotely sensed multispectral images, demonstrating excellent segmentation results.

Starting from the molecular picture for the $D_{s1}(2460)$ and $D_{s1}(2536)$ resonances, which are dynamically generated by the interaction of coupled channels, the most important of which are the $D^*K$ for the $D_{s1}(2460)$ and $DK^*$ for the $D_{s1}(2536)$, we evaluate the ratio of decay widths for the $\bar{B}_s^0 \to D_{s1}(2460)^+ K^-$ and $\bar{B}_s^0 \to D_{s1}(2536)^+ K^-$ decays, the latter of which has been recently investigated by the LHCb collaboration, and we obtain a ratio of the order of unity. The present results should provide an incentive for the related decay into the $D_{s1}(2460)$ resonance to be performed, which would provide valuable information on the nature of these two resonances., Comment: 14 pages, 4 figures, 2 tables; V2: discussions added, references added, version to appear in Eur.Phys.J.C

We make a study of the $\Omega_c(3120)$, one of the five $\Omega_c$ states observed by the LHCb collaboration, which is well reproduced as a molecular state from the $\Xi^*_c \bar K$ and $\Omega^*_c \eta$ channels mostly. The state with $J^P = 3/2^-$ decays to $\Xi_c \bar K$ in $D$-wave and we include this decay channel in our approach, as well as the effect of the $\Xi^*_c$ width. With all these ingredients, we determine the fraction of the $\Omega_c(3120)$ width that goes into $\Xi_c \pi \bar K$, which could be a measure of the $\Xi^*_c \bar K$ molecular component, but due to a relatively big binding, compared to its analogous $\Omega(2012)$ state, we find only a small fraction of about 3%, which makes this measurement difficult with present statistics. As an alternative, we evaluate the scattering length and effective range of the $\Xi^*_c \bar K$ and $\Omega^*_c \eta$ channels which together with the binding and width of the $\Omega_c(3120)$ state, could give us an answer to the issue of the compositeness of this state when these magnitudes are determined experimentally, something feasible nowadays, for instance, measuring correlation functions., Comment: 6 pages, 2 figures, 2 tables; References added

In this work we compare the predictions for the scattering length and effective range of the channels $K^0 \Sigma^+, K^+ \Sigma^0 , K^+ \Lambda$ and $\eta p$, assuming the $N^*(1535)$ state as a molecular state of these channels, or an original genuine state, made for instance from three quarks. Looking at very different scenarios, what we conclude is that the predictions of these two pictures are drastically different, to the point that we advise the measurement of these magnitudes, accessible for instance by measuring correlation functions, in order to gain much valuable information concerning the nature of this state.

IMPORTANCE The response effectiveness of different large language models (LLMs) and various individuals, including medical students, graduate students, and practicing physicians, in pediatric ophthalmology consultations, has not been clearly established yet. OBJECTIVE Design a 100-question exam based on pediatric ophthalmology to evaluate the performance of LLMs in highly specialized scenarios and compare them with the performance of medical students and physicians at different levels. DESIGN, SETTING, AND PARTICIPANTS This survey study assessed three LLMs, namely ChatGPT (GPT-3.5), GPT-4, and PaLM2, were assessed alongside three human cohorts: medical students, postgraduate students, and attending physicians, in their ability to answer questions related to pediatric ophthalmology. It was conducted by administering questionnaires in the form of test papers through the LLM network interface, with the valuable participation of volunteers. MAIN OUTCOMES AND MEASURES Mean scores of LLM and humans on 100 multiple-choice questions, as well as the answer stability, correlation, and response confidence of each LLM. RESULTS GPT-4 performed comparably to attending physicians, while ChatGPT (GPT-3.5) and PaLM2 outperformed medical students but slightly trailed behind postgraduate students. Furthermore, GPT-4 exhibited greater stability and confidence when responding to inquiries compared to ChatGPT (GPT-3.5) and PaLM2. CONCLUSIONS AND RELEVANCE Our results underscore the potential for LLMs to provide medical assistance in pediatric ophthalmology and suggest significant capacity to guide the education of medical students., Comment: 6 figures, 1 table

Purpose: The performance of three different large language models (LLMS) (GPT-3.5, GPT-4, and PaLM2) in answering ophthalmology professional questions was evaluated and compared with that of three different professional populations (medical undergraduates, medical masters, and attending physicians). Methods: A 100-item ophthalmology single-choice test was administered to three different LLMs (GPT-3.5, GPT-4, and PaLM2) and three different professional levels (medical undergraduates, medical masters, and attending physicians), respectively. The performance of LLM was comprehensively evaluated and compared with the human group in terms of average score, stability, and confidence. Results: Each LLM outperformed undergraduates in general, with GPT-3.5 and PaLM2 being slightly below the master's level, while GPT-4 showed a level comparable to that of attending physicians. In addition, GPT-4 showed significantly higher answer stability and confidence than GPT-3.5 and PaLM2. Conclusion: Our study shows that LLM represented by GPT-4 performs better in the field of ophthalmology. With further improvements, LLM will bring unexpected benefits in medical education and clinical decision making in the near future.

We perform a theoretical study of the $J/\psi \to \omega (\phi) K^* \bar{K} + c.c. \to \omega (\phi) K^0 \pi^+ K^-$ reactions with the assumption that the $f_1(1285)$ is dynamically generated from a single channel $K^* \bar{K} + c.c$ interaction in the chiral unitary approach. Two peaks in the $K^0 \pi^+ K^-$ invariant mass distribution are observed, one clear peak locates at the $f_1(1285)$ nominal mass, the other peak locates at around $1420\; \rm MeV$ with about $70 \;\rm MeV$ width. We conclude that the former peak is associated with the $f_1(1285)$ and the latter peak is not a genuine resonance but a manifestation of the kinematic effect in the higher energy region caused by the $K^* \bar{K} + c.c.$ decay mode of the $f_1(1285)$., Comment: 17 pages, 5 figures; v2: discussion added, references added, version to appear in Eur.Phys.J.C

The $N^*(1535)$ can be dynamically generated in the chiral unitary approach with the coupled channels, $K^0 \Sigma^+, K^+ \Sigma^0, K^+ \Lambda$ and $\eta p$. In this work we evaluate the correlation functions for every channel and face the inverse problem. Assuming the correlation functions to correspond to real measurements, we conduct a fit to the data within a general framework in order to extract the information contained in these correlation functions. The bootstrap method is used to determine the uncertainties of the different observables, and we find that, assuming errors of the same order than in present measurements of correlation functions, one can determine the scattering length and effective range of all channels with a very good accuracy. Most remarkable is the fact that the method predicts the existence of a bound state of isospin $\frac{1}{2}$ nature around the mass of the $N^*(1535)$ with an accuracy of $6\; \rm MeV$. These results should encourage the actual measurement of these correlation functions (only the $K^+ \Lambda$ one is measured so far), which can shed valuable light on the relationship of the $ N^*(1535)$ state to these coupled channels, a subject of continuous debate., Comment: 18 pages, 2 figures, 5 tables; v2: discussions added, references added

We study the decays $\bar B^0 \to \bar K^0 \, X$, $B^- \to K^- \, X$, $\bar B^0_s \to \eta (\eta')\, X$, $\bar B^0 \to \bar K^{*0} \, X$, $B^- \to K^{*-} \, X$ , $\bar B_s^0 \to \phi \, X$, with $X \equiv X(3872)$, from the perspective of the $X(3872)$ being a molecular state made from the interaction of the $D^{*+} D^-, D^{*0} \bar D^0$ and $c.c.$ components. We consider both the external and internal emission decay mechanisms and find an explanation for the $\bar K^0 \, X$ and $K^- \, X$ production rates, based on the mass difference of the charged and neutral $D^* \bar D$ components. We also find that the internal and external emission mechanisms add constructively in the $\bar B^0 \to \bar K^0 \, X$, $B^- \to K^- \, X$ reactions, while they add destructively in the case of $\bar B^0 \to \bar K^{*0} \, X$, $B^- \to K^{*-} \, X$ reactions. This feature explains the decay widths of the present measurements and allows us to make predictions for the unmeasured modes of $\bar B^0_s \to \eta (\eta')\, X(3872)$ and $B^- \to K^{*-} \, X(3872)$. The future measurement of these decay modes will help us get a better perspective on the nature of the $X(3872)$ and the mechanisms present in production reactions of that state., Comment: 15 pages, 5 figures, 2 tables; V2: discussions added, references added, version published in Phys. Rev. D

Deep neural networks have become a standard building block for designing models that can perform multiple dense computer vision tasks such as depth estimation and semantic segmentation thanks to their ability to capture complex correlations in high dimensional feature space across tasks. However, the cross-task correlations that are learned in the unstructured feature space can be extremely noisy and susceptible to overfitting, consequently hurting performance. We propose to address this problem by introducing a structured 3D-aware regularizer which interfaces multiple tasks through the projection of features extracted from an image encoder to a shared 3D feature space and decodes them into their task output space through differentiable rendering. We show that the proposed method is architecture agnostic and can be plugged into various prior multi-task backbones to improve their performance; as we evidence using standard benchmarks NYUv2 and PASCAL-Context., Comment: 3D-aware Multi-task Learning, Code will be available at https://github.com/VICO-UoE/MTPSL

We recall that the chiral unitary approach for the interaction of pseudoscalar mesons with the baryons of the decuplet predicts two states for the $\Xi(1820)$ resonance, one with a narrow width and the other one with a large width. We contrast this fact with the recent BESIII measurement of the $K^- \Lambda$ mass distribution in the $\psi(3686)$ decay to $K^- \Lambda \bar\Xi^+ $, which demands a width much larger than the average of the PDG, and show how the consideration of the two $\Xi(1820)$ states provides a natural explanation to this apparent contradiction., Comment: 9 pages, 3 figures

We study the Belle reaction $\Xi_c^+ \to \Xi^- \pi^+ \pi^+$ looking at the mass distribution of $\pi^+ \Xi$, where clear signals for the $\Xi(1620)$ and $\Xi(1690)$ resonances are seen. These two resonances are generated dynamically from the interaction in coupled channels of $\pi \Xi, \bar K \Lambda, \bar K \Sigma$ and $\eta \Xi$ within the chiral unitary approach. Yet, the weak decay process at the quark level, together with the hadronization to produce pairs of mesons, does not produce the $\pi \pi \Xi$ final state. In order to produce this state one must make transitions from the $\bar K \Lambda, \bar K \Sigma$ and $\eta \Xi$ components to $\pi \Xi$, and this interaction is what produces the resonances. So, the reaction offers a good test for the molecular picture of these resonances. Adding the contribution of the $\Xi^*(1530)$ and some background we are able to get a good reproduction of the mass distribution showing the signatures of the two resonances as found in the experiment., Comment: 15 pages, 8 figures, 2 tables; v2: discussion added, references added, version to appear in Eur.Phys.J.C

Computing the discrete rational minimax approximation in the complex plane is challenging. Apart from Ruttan's sufficient condition, there are few other sufficient conditions for global optimality. The state-of-the-art rational approximation algorithms, such as the adaptive Antoulas-Anderson (AAA), AAA-Lawson, and the rational Krylov fitting (RKFIT) method, perform highly efficiently, but the computed rational approximations may not be minimax solutions. In this paper, we propose a convex programming approach, the solution of which is guaranteed to be the rational minimax approximation under Ruttan's sufficient condition. Furthermore, we present a new version of Lawson's iteration for solving this convex programming problem. The computed solution can be easily verified as the rational minimax approximation. Our numerical experiments demonstrate that this updated version of Lawson's iteration generally converges monotonically with respect to the objective function of the convex optimization. It is an effective competitive approach for computing the rational minimax approximation, compared to the highly efficient AAA, AAA-Lawson, and the stabilized Sanathanan-Koerner iteration., Comment: 40 pages, 11 figures

We study the possibly-existing molecular pentaquark states with open charm and bottom flavors, {\it i.e.}, the states with the quark contents $c\bar{b}qqq$ and $b\bar{c}qqq$ ($q=u,d,s$). We investigate the meson-baryon interactions through the coupled-channel unitary approach within the local hidden-gauge formalism, and extract the poles by solving the Bethe-Salpeter equation in coupled channels. These poles qualify as molecular pentaquark states, which are dynamically generated from the meson-baryon interactions through the exchange of vector mesons. Our results suggest the existence of the $\Sigma_c^{(*)} B^{(*)}$ and $\Sigma_b^{(*)} \bar{D}^{(*)}$ molecular states with isospin $I=1/2$, the $\Xi_c^{(\prime,*)} B^{(*)}$ and $\Xi_b^{(\prime,*)} \bar{D}^{(*)}$ molecular states with isospin $I=0$ and $I=1$, as well as the $\Omega_c^{(*)} B^{(*)}$ and $\Omega_b^{(*)} \bar D^{(*)}$ molecular states with isospin $I=1/2$., Comment: 25 pages, 6 figures, 7 tables, revised version to be published in EPJA

Using artificial intelligent (AI) to re-design and enhance the current wireless communication system is a promising pathway for the future sixth-generation (6G) wireless network. The performance of AI-enabled wireless communication depends heavily on the quality of wireless air-interface data. Although there are various approaches to data quality assessment (DQA) for different applications, none has been designed for wireless air-interface data. In this paper, we propose a DQA framework to measure the quality of wireless air-interface data from three aspects: similarity, diversity, and completeness. The similarity measures how close the considered datasets are in terms of their statistical distributions; the diversity measures how well-rounded a dataset is, while the completeness measures to what degree the considered dataset satisfies the required performance metrics in an application scenario. The proposed framework can be applied to various types of wireless air-interface data, such as channel state information (CSI), signal-to-interference-plus-noise ratio (SINR), reference signal received power (RSRP), etc. For simplicity, the validity of our proposed DQA framework is corroborated by applying it to CSI data and using similarity and diversity metrics to improve CSI compression and recovery in Massive MIMO systems.

While many dashboards for visualizing COVID-19 data exist, most separate geospatial and temporal data into discrete visualizations or tables. Further, the common use of choropleth maps or space-filling map overlays supports only a single geospatial variable at once, making it difficult to compare the temporal and geospatial trends of multiple, potentially interacting variables, such as active cases, deaths, and vaccinations. We present CoronaViz, a COVID-19 visualization system that conveys multilayer, spatiotemporal data in a single, interactive display. CoronaViz encodes variables with concentric, hollow circles, termed geocircles, allowing multiple variables via color encoding and avoiding occlusion problems. The radii of geocircles relate to the values of the variables they represent via the psychophysically determined Flannery formula. The time dimension of spatiotemporal variables is encoded with sequential rendering. Animation controls allow the user to seek through time manually or to view the pandemic unfolding in accelerated time. An adjustable time window allows aggregation at any granularity, from single days to cumulative values for the entire available range. In addition to describing the CoronaViz system, we report findings from a user study comparing CoronaViz with multi-view dashboards from the New York Times and Johns Hopkins University. While participants preferred using the latter two dashboards to perform queries with only a geospatial component or only a temporal component, participants uniformly preferred CoronaViz for queries with both spatial and temporal components, highlighting the utility of a unified spatiotemporal encoding. CoronaViz is open-source and freely available at http://coronaviz.umiacs.io.

Mid-infrared spectroscopy probes molecular vibrations to identify chemical species and functional groups. Therefore, mid-infrared hyperspectral imaging is one of the most powerful and promising candidates for chemical imaging using optical methods. Yet high-speed and entire bandwidth mid-infrared hyperspectral imaging has not been realized. Here we report a mid-infrared hyperspectral chemical imaging technique that uses chirped pulse upconversion of sub-cycle pulses at the image plane. This technique offers a lateral resolution of 15 $\mu$m, and the field of view is adjustable between 800 $\mu$m $\times$ 600 $\mu$m to 12 mm $\times$ 9 mm. The hyperspectral imaging produces a 640 $\times$ 480 pixel image in 8 s, which covers a spectral range of 640-3015 cm$^{-1}$, comprising 1069 wavelength points and offering a wavenumber resolution of 2.6-3.7 cm$^{-1}$. For discrete frequency mid-infrared imaging, the measurement speed reaches a frame rate of 5 kHz, the repetition rate of the laser. As a demonstration, we effectively identified and mapped different components in a microfluidic device, plant cell, and mouse embryo section. The great capacity and latent force of this technique in chemical imaging promise to be applied to many fields such as chemical analysis, biology, and medicine., Comment: 22 pages, 10 figures

We present a mechanism for $\Omega_c \to \pi^+ \Omega(2012)$ production through an external emission Cabibbo favored weak decay mode, where the $\Omega(2012)$ is dynamically generated from the interaction of $\bar{K}\Xi^*(1530)$, $\eta\Omega$, with $\bar{K}\Xi$ as the main decay channel. The $\Omega(2012)$ decays later to $\bar{K}\Xi$ in this picture, with results compatible with Belle data. The picture has as a consequence that one can evaluate the direct decay $\Omega_c^0 \to \pi^+K^- \Xi^0$ and the decay $\Omega_c^0 \to \pi^+\bar{K} \Xi^*$, $\pi^+\eta\Omega$ with direct coupling of $\bar{K}\Xi^*$ and $\eta\Omega$ to $K^- \Xi^0$. We show that, within uncertainties and using data from a recent Belle measurement, all these three channels account for about (12-20)\% of the total $\Omega_c \to \pi^+K^- \Xi^0$ decay rate. The consistency of the molecular picture with all the data is established by showing that $\Omega_c \to \Xi^0 \bar{K}^{*0} \to \Xi^0K^- \pi^+$ together with $\Omega_c \to \pi^+ \Omega^* \to \pi^+K^- \Xi^0 $ account for about 85\% of the total $\Omega_c \to \pi^+K^- \Xi^0 $., Comment: 12 pages, 5 figures, 3 tables

We propose a unified look at jointly learning multiple vision tasks and visual domains through universal representations, a single deep neural network. Learning multiple problems simultaneously involves minimizing a weighted sum of multiple loss functions with different magnitudes and characteristics and thus results in unbalanced state of one loss dominating the optimization and poor results compared to learning a separate model for each problem. To this end, we propose distilling knowledge of multiple task/domain-specific networks into a single deep neural network after aligning its representations with the task/domain-specific ones through small capacity adapters. We rigorously show that universal representations achieve state-of-the-art performances in learning of multiple dense prediction problems in NYU-v2 and Cityscapes, multiple image classification problems from diverse domains in Visual Decathlon Dataset and cross-domain few-shot learning in MetaDataset. Finally we also conduct multiple analysis through ablation and qualitative studies., Comment: Multi-task Learning, Multi-domain Learning, Cross-domain Few-shot Learning, Universal Representation Learning, Balanced Optimization, Dense Prediction, Code and models are available at https://github.com/VICO-UoE/UniversalRepresentations. arXiv admin note: text overlap with arXiv:2103.13841

We study the $\bar B_s^0 \to J/\psi f_0(980)$ and $\bar B_s^0 \to J/\psi a_0(980)$ reactions, and pay attention to the different sources of isospin violation and mixing of $f_0(980)$ and $a_0(980)$ resonances where these resonances are dynamically generated from meson-meson interaction. We find that the main cause of isospin violation is the isospin breaking in the meson-meson transition $T$ matrices, and the other source is that the loops involving kaons in the production mechanism do not cancel due to the different masses of the charged and neutral kaons. We obtain a branching ratio for $a_0(980)$ production of the order of $5 \times 10^{-6}$. Future experiments can address this problem, and the production rate and shape of the $\pi^0 \eta$ mass distribution will definitely help to better understand the nature of scalar resonances., Comment: 12 pages, 4 figures; v2: version published in Chin. Phys. C

Remarkable development of cosmology is benefited from the increasingly improved measurements of cosmic distances including absolute distances and relative distances. In recent years, however, the emerged cosmological tensions motivate us to explore the independent and precise late-universe probes. The two observational effects of strong gravitational lensing (SGL), the velocity dispersions of lens galaxies and the time delays between multiple images, can provide measurements of relative and absolute distances respectively, and their combination is possible to break the degeneracies between cosmological parameters and enable tight constraints on cosmological parameters. In this paper, we combine the observed 130 SGL systems with velocity-dispersion measurements and 7 SGL systems with time-delay measurements to constrain dark-energy cosmological models. It is found that the combination of the two effects does not significantly break the degeneracies between cosmological parameters as expected. However, with the simulations of 8000 SGL systems with well-measured velocity dispersions and 55 SGL systems with well-measured time delays based on the forthcoming LSST survey, we find that the combination of two effects can significantly break the parameter degeneracies, and make the constraint precision of cosmological parameters meet the standard of precision cosmology. We conclude that the observations of SGL will become a useful late-universe probe for precisely measuring cosmological parameters., Comment: 18 pages, 6 figures; to appear in Universe

Strongly lensed type Ia supernovae (SNe Ia) are expected to have some advantages in measuring time delays of multiple images, and so they have a great potential to be developed into a powerful late-universe cosmological probe. In this paper, we simulate a sample of lensed SNe Ia with time-delay measurements in the era of the Legacy Survey of Space and Time (LSST). Based on the distance sum rule, we use lensed SNe Ia to implement model-independent constraints on the Hubble constant $H_0$ and cosmic curvature parameter $\Omega_K$ in the late universe. We find that if 20 lensed SNe Ia could be observed, the constraint on $H_{0}$ is better than the measurement by the SH0ES collaboration. When the event number of lensed SNe Ia increases to 100, the constraint precision of $H_{0}$ is comparable with the result from Planck 2018 data. Considering 200 lensed SNe Ia events as the optimistic estimation, we obtain $\Delta H_0=0.33$ $\rm km\ s^{-1}\ Mpc^{-1}$ and $\Delta\Omega_K=0.053$. In addition, we also simulate lensed quasars in different scenarios to make a comparison and we find that they are still a useful cosmological probe even though the constraint precision from them is much less than that obtained from lensed SNe Ia. In the era of LSST, the measurements of time delay from both lensed SNe Ia and lensed quasars are expected to yield the results of $\Delta H_0=0.26 ~\rm km\ s^{-1}\ Mpc^{-1}$ and $\Delta\Omega_K=0.044$., Comment: 11 pages, 3 figures; accepted for publication in Physical Review D

Despite the recent advances in multi-task learning of dense prediction problems, most methods rely on expensive labelled datasets. In this paper, we present a label efficient approach and look at jointly learning of multiple dense prediction tasks on partially annotated data (i.e. not all the task labels are available for each image), which we call multi-task partially-supervised learning. We propose a multi-task training procedure that successfully leverages task relations to supervise its multi-task learning when data is partially annotated. In particular, we learn to map each task pair to a joint pairwise task-space which enables sharing information between them in a computationally efficient way through another network conditioned on task pairs, and avoids learning trivial cross-task relations by retaining high-level information about the input image. We rigorously demonstrate that our proposed method effectively exploits the images with unlabelled tasks and outperforms existing semi-supervised learning approaches and related methods on three standard benchmarks., Comment: CVPR2022, Multi-task Partially-supervised Learning, Code will be available at https://github.com/VICO-UoE/MTPSL

We perform a study of the $D_s^+ \to a_0(980)(f_0(980)) e^+ \nu_e$ reactions investigating the different sources of isospin violation which make the production of the $a_0(980)$ possible. We find that loops involving kaons in the production mechanism provide a source of isospin violation since they do not cancel due to the different mass of charged and neutral kaons, but we also find that the main source comes from the breaking of isospin in the meson-meson transition $T$ matrices, which contain information on the nature of the low lying scalar mesons. The reaction is thus very sensitive to the nature of the $a_0(980)$ and $f_0(980)$ resonances. Our results are consistent with the present upper bound for $a_0(980)$ production and only a factor three smaller, indicating that future runs with more statistics should find actual numbers for this reaction from where we can learn more about the origin of the scalar resonances and their nature., Comment: 17 pages, 4 figures, 3 tables; v2: discussion added, references added, version to appear in Eur.Phys.J.C

In this paper, we look at the problem of cross-domain few-shot classification that aims to learn a classifier from previously unseen classes and domains with few labeled samples. Recent approaches broadly solve this problem by parameterizing their few-shot classifiers with task-agnostic and task-specific weights where the former is typically learned on a large training set and the latter is dynamically predicted through an auxiliary network conditioned on a small support set. In this work, we focus on the estimation of the latter, and propose to learn task-specific weights from scratch directly on a small support set, in contrast to dynamically estimating them. In particular, through systematic analysis, we show that task-specific weights through parametric adapters in matrix form with residual connections to multiple intermediate layers of a backbone network significantly improves the performance of the state-of-the-art models in the Meta-Dataset benchmark with minor additional cost., Comment: CVPR2022, Code will be available at https://github.com/VICO-UoE/URL

We present a framework for learning multimodal representations from unlabeled data using convolution-free Transformer architectures. Specifically, our Video-Audio-Text Transformer (VATT) takes raw signals as inputs and extracts multimodal representations that are rich enough to benefit a variety of downstream tasks. We train VATT end-to-end from scratch using multimodal contrastive losses and evaluate its performance by the downstream tasks of video action recognition, audio event classification, image classification, and text-to-video retrieval. Furthermore, we study a modality-agnostic, single-backbone Transformer by sharing weights among the three modalities. We show that the convolution-free VATT outperforms state-of-the-art ConvNet-based architectures in the downstream tasks. Especially, VATT's vision Transformer achieves the top-1 accuracy of 82.1% on Kinetics-400, 83.6% on Kinetics-600, 72.7% on Kinetics-700, and 41.1% on Moments in Time, new records while avoiding supervised pre-training. Transferring to image classification leads to 78.7% top-1 accuracy on ImageNet compared to 64.7% by training the same Transformer from scratch, showing the generalizability of our model despite the domain gap between videos and images. VATT's audio Transformer also sets a new record on waveform-based audio event recognition by achieving the mAP of 39.4% on AudioSet without any supervised pre-training. VATT's source code is publicly available., Comment: Published in the 35th Conference on Neural Information Processing Systems (NeurIPS 2021)

In this paper, we look at the problem of few-shot classification that aims to learn a classifier for previously unseen classes and domains from few labeled samples. Recent methods use adaptation networks for aligning their features to new domains or select the relevant features from multiple domain-specific feature extractors. In this work, we propose to learn a single set of universal deep representations by distilling knowledge of multiple separately trained networks after co-aligning their features with the help of adapters and centered kernel alignment. We show that the universal representations can be further refined for previously unseen domains by an efficient adaptation step in a similar spirit to distance learning methods. We rigorously evaluate our model in the recent Meta-Dataset benchmark and demonstrate that it significantly outperforms the previous methods while being more efficient. Our code will be available at https://github.com/VICO-UoE/URL., Comment: Code will be available at https://github.com/VICO-UoE/URL

In this work, we investigate the reaction of $\gamma\gamma \to D\bar{D}$, taking into account the s-wave $D\bar{D}$ final state interaction. By fitting to the $D\bar{D}$ invariant mass distributions measured by the Belle and BaBar Collaborations, we obtain a good reproduction of the data by means of a $D\bar{D}$ amplitude that produces a bound $D\bar{D}$ state with $I=0$ close to threshold. The error bands of the fits indicate, however, that more precise data on this reaction are needed to be more assertive about the position and width of such state., Comment: 9 pages, 7 figures, and 1 table

The equation of state (EoS) of the neutron star (NS) matter remains an enigma. In this work we perform the Bayesian parameter inference with the gravitational wave data (GW170817) and mass-radius observations of some NSs (PSR J0030+0451, PSR J0437-4715, and 4U 1702-429) using the phenomenologically constructed EoS models to search for a potential first-order phase transition. Our phenomenological EoS models take the advantages of current widely used parametrizing methods, which are flexible enough to resemble various theoretical EoS models. We find that the current observation data are still not informative enough to support/rule out phase transition, due to the comparable evidences for models with and without phase transition. However, the bulk properties of the canonical $1.4\,M_\odot$ NS and the pressure at around $2\rho_{\rm sat}$ are well constrained by the data, where $\rho_{\rm sat}$ is the nuclear saturation density. Moreover, strong phase transition at low densities is disfavored, and the $1\sigma$ lower bound of transition density is constrained to $1.84\rho_{\rm sat}$., Comment: 9 pages, 5 figures, published in PRD

We address the weakly supervised video highlight detection problem for learning to detect segments that are more attractive in training videos given their video event label but without expensive supervision of manually annotating highlight segments. While manually averting localizing highlight segments, weakly supervised modeling is challenging, as a video in our daily life could contain highlight segments with multiple event types, e.g., skiing and surfing. In this work, we propose casting weakly supervised video highlight detection modeling for a given specific event as a multiple instance ranking network (MINI-Net) learning. We consider each video as a bag of segments, and therefore, the proposed MINI-Net learns to enforce a higher highlight score for a positive bag that contains highlight segments of a specific event than those for negative bags that are irrelevant. In particular, we form a max-max ranking loss to acquire a reliable relative comparison between the most likely positive segment instance and the hardest negative segment instance. With this max-max ranking loss, our MINI-Net effectively leverages all segment information to acquire a more distinct video feature representation for localizing the highlight segments of a specific event in a video. The extensive experimental results on three challenging public benchmarks clearly validate the efficacy of our multiple instance ranking approach for solving the problem.

Multi-task learning (MTL) is to learn one single model that performs multiple tasks for achieving good performance on all tasks and lower cost on computation. Learning such a model requires to jointly optimize losses of a set of tasks with different difficulty levels, magnitudes, and characteristics (e.g. cross-entropy, Euclidean loss), leading to the imbalance problem in multi-task learning. To address the imbalance problem, we propose a knowledge distillation based method in this work. We first learn a task-specific model for each task. We then learn the multi-task model for minimizing task-specific loss and for producing the same feature with task-specific models. As the task-specific network encodes different features, we introduce small task-specific adaptors to project multi-task features to the task-specific features. In this way, the adaptors align the task-specific feature and the multi-task feature, which enables a balanced parameter sharing across tasks. Extensive experimental results demonstrate that our method can optimize a multi-task learning model in a more balanced way and achieve better overall performance., Comment: We propose a knowledge distillation method for addressing the imbalance problem in multi-task learning

Important people detection is to automatically detect the individuals who play the most important roles in a social event image, which requires the designed model to understand a high-level pattern. However, existing methods rely heavily on supervised learning using large quantities of annotated image samples, which are more costly to collect for important people detection than for individual entity recognition (eg, object recognition). To overcome this problem, we propose learning important people detection on partially annotated images. Our approach iteratively learns to assign pseudo-labels to individuals in un-annotated images and learns to update the important people detection model based on data with both labels and pseudo-labels. To alleviate the pseudo-labelling imbalance problem, we introduce a ranking strategy for pseudo-label estimation, and also introduce two weighting strategies: one for weighting the confidence that individuals are important people to strengthen the learning on important people and the other for neglecting noisy unlabelled images (ie, images without any important people). We have collected two large-scale datasets for evaluation. The extensive experimental results clearly confirm the efficacy of our method attained by leveraging unlabelled images for improving the performance of important people detection.

With the rapid continuing spread of COVID-19, it is clearly important to be able to track the progress of the virus over time in order to be better prepared to anticipate its emergence and spread in new regions as well as declines in its presence in regions thereby leading to or justifying "reopening" decisions. There are many applications and web sites that monitor officially released numbers of cases which are likely to be the most accurate methods for tracking the progress of the virus; however, they will not necessarily paint a complete picture. To begin filling any gaps in official reports, we have developed the NewsStand CoronaViz web application (https://coronaviz.umiacs.io) that can run on desktops and mobile devices that allows users to explore the geographic spread in discussions about the virus through analysis of keyword prevalence in geotagged news articles and tweets in relation to the real spread of the virus as measured by confirmed case numbers reported by the appropriate authorities. NewsStand CoronaViz users have access to dynamic variants of the disease-related variables corresponding to the numbers of confirmed cases, active cases, deaths, and recoveries (where they are provided) via a map query interface. It has the ability to step forward and backward in time using both a variety of temporal window sizes (day, week, month, or combinations thereof) in addition to user-defined varying spatial window sizes specified by direct manipulation actions (e.g., pan, zoom, and hover) as well as textually (e.g., by the name of the containing country, state or province, or county as well as textually-specified spatially-adjacent combinations thereof), and finally by the amount of spatio-temporally-varying news and tweet volume involving COVID-19., Comment: For associated demonstration website see https://coronaviz.umiacs.io

We analyze theoretically the $D^+\to \nu e^+ \rho \bar K$ and $D^+\to \nu e^+ \bar K^* \pi$ decays to see the feasibility to check the double pole nature of the axial-vector resonance $K_1(1270)$ predicted by the unitary extensions of chiral perturbation theory (UChPT). Indeed, within UChPT the $K_1(1270)$ is dynamically generated from the interaction of a vector and a pseudoscalar meson, and two poles are obtained for the quantum numbers of this resonance. The lower mass pole couples dominantly to $K^*\pi$ and the higher mass pole to $\rho K$, therefore we can expect that different reactions weighing differently these channels in the production mechanisms enhance one or the other pole. We show that the different final $VP$ channels in $D^+\to \nu e^+ V P$ weigh differently both poles, and this is reflected in the shape of the final vector-pseudoscalar invariant mass distributions. Therefore, we conclude that these decays are suitable to distinguish experimentally the predicted double pole of the $K_1(1270)$ resonance., Comment: 7 pages, 3 figures

Cerebral blood volume (CBV) is a hemodynamic correlate of oxygen metabolism and reflects brain activity and function. High-resolution CBV maps can be generated using the steady-state gadolinium-enhanced MRI technique. Such a technique requires an intravenous injection of exogenous gadolinium based contrast agent (GBCA) and recent studies suggest that the GBCA can accumulate in the brain after frequent use. We hypothesize that endogenous sources of contrast might exist within the most conventional and commonly acquired structural MRI, potentially obviating the need for exogenous contrast. Here, we test this hypothesis by developing and optimizing a deep learning algorithm, which we call DeepContrast, in mice. We find that DeepContrast performs equally well as exogenous GBCA in mapping CBV of the normal brain tissue and enhancing glioblastoma. Together, these studies validate our hypothesis that a deep learning approach can potentially replace the need for GBCAs in brain MRI.

We study the $\bar K p \to Y K\bar K \pi$ reactions with $\bar K = \bar K^0, K^-$ and $Y=\Sigma^0, \Sigma^+, \Lambda$, in the region of $K\bar K \pi$ invariant masses of $1200-1550$ MeV. The strong coupling of the $f_1(1285)$ resonance to $K^* \bar K$ makes the mechanism based on $K^*$ exchange very efficient to produce this resonance observed in the $K\bar K \pi$ invariant mass distribution. In addition, in all the reactions one observes an associated peak at $1420$ MeV which comes from the $K^* \bar K$ decay mode of the $f_1(1285)$ when the $K^*$ is placed off shell at higher invariant masses. We claim this to be the reason for the peak of the $K^* \bar K$ distribution seen in the experiments which has been associated to the "$f_1(1420)$" resonance., Comment: 11 pages, 4 figures