A Finite Exact Representation of Register Automata Configurations

A register automaton is a finite automaton with finitely many registers ranging from an infinite alphabet. Since the valuations of registers are infinite, there are infinitely many configurations. We describe a technique to classify infinite register automata configurations into finitely many exact representative configurations. Using the finitary representation, we give an algorithm solving the reachability problem for register automata. We moreover define a computation tree logic for register automata and solve its model checking problem.Comment: In Proceedings INFINITY 2013, arXiv:1402.661

New Insights on Low Energy πN\pi N Scattering Amplitudes

The $S$- and $P$- wave phase shifts of low-energy pion-nucleon scatterings are analysed using Peking University representation, in which they are decomposed into various terms contributing either from poles or branch cuts. We estimate the left-hand cut contributions with the help of tree-level perturbative amplitudes derived in relativistic baryon chiral perturbation theory up to $\mathcal{O}(p^2)$. It is found that in $S_{11}$ and $P_{11}$ channels, contributions from known resonances and cuts are far from enough to saturate experimental phase shift data -- strongly indicating contributions from low lying poles undiscovered before, and we fully explore possible physics behind. On the other side, no serious disagreements are observed in the other channels.Comment: slightly chnaged version, a few more figures added. Physical conclusions unchange

Detach and Adapt: Learning Cross-Domain Disentangled Deep Representation

While representation learning aims to derive interpretable features for describing visual data, representation disentanglement further results in such features so that particular image attributes can be identified and manipulated. However, one cannot easily address this task without observing ground truth annotation for the training data. To address this problem, we propose a novel deep learning model of Cross-Domain Representation Disentangler (CDRD). By observing fully annotated source-domain data and unlabeled target-domain data of interest, our model bridges the information across data domains and transfers the attribute information accordingly. Thus, cross-domain joint feature disentanglement and adaptation can be jointly performed. In the experiments, we provide qualitative results to verify our disentanglement capability. Moreover, we further confirm that our model can be applied for solving classification tasks of unsupervised domain adaptation, and performs favorably against state-of-the-art image disentanglement and translation methods.Comment: CVPR 2018 Spotligh

Charmless Two-body B(Bs)→VPB(B_s)\to VP decays In Soft-Collinear-Effective-Theory

We provide the analysis of charmless two-body $B\to VP$ decays under the framework of the soft-collinear-effective-theory (SCET), where $V(P)$ denotes a light vector (pseudoscalar) meson. Besides the leading power contributions, some power corrections (chiraly enhanced penguins) are also taken into account. Using the current available $B\to PP$ and $B\to VP$ experimental data on branching fractions and CP asymmetry variables, we find two kinds of solutions in $\chi^2$ fit for the 16 non-perturbative inputs which are essential in the 87 $B\to PP$ and $B\to VP$ decay channels. Chiraly enhanced penguins can change several charming penguins sizably, since they share the same topology. However, most of the other non-perturbative inputs and predictions on branching ratios and CP asymmetries are not changed too much. With the two sets of inputs, we predict the branching fractions and CP asymmetries of other modes especially $B_s\to VP$ decays. The agreements and differences with results in QCD factorization and perturbative QCD approach are analyzed. We also study the time-dependent CP asymmetries in channels with CP eigenstates in the final states and some other channels such as $\bar B^0/B^0\to\pi^\pm\rho^\mp$ and $\bar B_s^0/B_s^0\to K^\pm K^{*\mp}$. In the perturbative QCD approach, the $(S-P)(S+P)$ penguins in annihilation diagrams play an important role. Although they have the same topology with charming penguins in SCET, there are many differences between the two objects in weak phases, magnitudes, strong phases and factorization properties.Comment: 34 pages, revtex, 2 figures, published at PR