Grand-canonical variational approach for the t-J model

Gutzwiller-projected BCS wave function or the resonating-valence-bond (RVB) state in the 2D extended t-J model is investigated by using the variational Monte Carlo technique. We show that the results of ground-state energy and excitation spectra calculated in the grand-canonical scheme allowing particle number to fluctuate are essentially the same as previous results obtained by fixing the number of particle in the canonical scheme if the grand thermodynamic potential is used for minimization. To account for the effect of Gutzwiller projection, a fugacity factor proposed by Laughlin and Anderson few years ago has to be inserted into the coherence factor of the BCS state. Chemical potential, particle number fluctuation, and phase fluctuation of the RVB state, difficult or even impossible to be calculated in the canonical ensemble, have been directly measured in the grand-canonical picture. We find that except for La-214 materials, the doping dependence of chemical potential is consistent with experimental findings on several cuprates. Similar to what has been reported by scanning tunneling spectroscopy experiments, the tunneling asymmetry becomes much stronger as doping decreases. We found a very large enhancement of phase fluctuation in the underdoped regime.Comment: 9 pages, 6 figure

A new description of transverse momentum spectra of identified particles produced in proton-proton collisions at high energies

The transverse momentum spectra of identified particles produced in high energy proton-proton ($p+p$) collisions are empirically described by a new method with the framework of participant quark model or the multisource model at the quark level, in which the source itself is exactly the participant quark. Each participant (constituent) quark contributes to the transverse momentum spectrum, which is described by the TP-like function, a revised Tsallis--Pareto-type function. The transverse momentum spectrum of the hadron is the convolution of two or more TP-like functions. For a lepton, the transverse momentum spectrum is the convolution of two TP-like functions due to two participant quarks, e.g. projectile and target quarks, taking part in the collisions. A discussed theoretical approach seems to describe the $p+p$ collisions data at center-of-mass energy $\sqrt{s}=200$ GeV, 2.76 TeV, and 13 TeV very well.Comment: 19 pages, 7 figures. Advances in High Energy Physics, accepte

Comparing a few distributions of transverse momenta in high energy collisions

Transverse momentum spectra of particles produced in high energy collisions are very important due to their relations to the excitation degree of interacting system. To describe the transverse momentum spectra, one can use more than one probability density functions of transverse momenta, which are simply called the functions or distributions of transverse momenta in some cases. In this paper, a few distributions of transverse momenta in high energy collisions are compared with each other in terms of plots to show some quantitative differences. Meanwhile, in the framework of Tsallis statistics, the distributions of momentum components, transverse momenta, rapidities, and pasudorapidities are obtained according to the analytical and Monte Carlo methods. These analyses are useful to understand carefully different distributions in high energy collisions.Comment: 11 pages, 7 figures. Results in Physics, Accepte

HIV-1 Gag-specific immunity induced by a lentivector-based vaccine directed to dendritic cells

Lentivectors (LVs) have attracted considerable interest for their potential as a vaccine delivery vehicle. In this study, we evaluate in mice a dendritic cell (DC)-directed LV system encoding the Gag protein of human immunodeficiency virus (HIV) (LV-Gag) as a potential vaccine for inducing an anti-HIV immune response. The DC-directed specificity is achieved through pseudotyping the vector with an engineered Sindbis virus glycoprotein capable of selectively binding to the DC-SIGN protein. A single immunization by this vector induces a durable HIV Gag-specific immune response. We investigated the antigen-specific immunity and T-cell memory generated by a prime/boost vaccine regimen delivered by either successive LV-Gag injections or a DNA prime/LV-Gag boost protocol. We found that both prime/boost regimens significantly enhance cellular and humoral immune responses. Importantly, a heterologous DNA prime/LV-Gag boost regimen results in superior Gag-specific T-cell responses as compared with a DNA prime/adenovector boost immunization. It induces not only a higher magnitude response, as measured by Gag-specific tetramer analysis and intracellular IFN-γ staining, but also a better quality of response evidenced by a wider mix of cytokines produced by the Gag-specific CD8^+ and CD4^+ T cells. A boosting immunization with LV-Gag also generates T cells reactive to a broader range of Gag-derived epitopes. These results demonstrate that this DC-directed LV immunization is a potent modality for eliciting anti-HIV immune responses

When Causal Intervention Meets Adversarial Examples and Image Masking for Deep Neural Networks

Discovering and exploiting the causality in deep neural networks (DNNs) are crucial challenges for understanding and reasoning causal effects (CE) on an explainable visual model. "Intervention" has been widely used for recognizing a causal relation ontologically. In this paper, we propose a causal inference framework for visual reasoning via do-calculus. To study the intervention effects on pixel-level features for causal reasoning, we introduce pixel-wise masking and adversarial perturbation. In our framework, CE is calculated using features in a latent space and perturbed prediction from a DNN-based model. We further provide the first look into the characteristics of discovered CE of adversarially perturbed images generated by gradient-based methods \footnote{~~https://github.com/jjaacckkyy63/Causal-Intervention-AE-wAdvImg}. Experimental results show that CE is a competitive and robust index for understanding DNNs when compared with conventional methods such as class-activation mappings (CAMs) on the Chest X-Ray-14 dataset for human-interpretable feature(s) (e.g., symptom) reasoning. Moreover, CE holds promises for detecting adversarial examples as it possesses distinct characteristics in the presence of adversarial perturbations.Comment: Noted our camera-ready version has changed the title. "When Causal Intervention Meets Adversarial Examples and Image Masking for Deep Neural Networks" as the v3 official paper title in IEEE Proceeding. Please use it in your formal reference. Accepted at IEEE ICIP 2019. Pytorch code has released on https://github.com/jjaacckkyy63/Causal-Intervention-AE-wAdvIm