Contracting Graphs to Split Graphs and Threshold Graphs

We study the parameterized complexity of Split Contraction and Threshold Contraction. In these problems we are given a graph G and an integer k and asked whether G can be modified into a split graph or a threshold graph, respectively, by contracting at most k edges. We present an FPT algorithm for Split Contraction, and prove that Threshold Contraction on split graphs, i.e., contracting an input split graph to a threshold graph, is FPT when parameterized by the number of contractions. To give a complete picture, we show that these two problems admit no polynomial kernels unless NP\subseteq coNP/poly.Comment: 14 pages, 4 figure

Confidence Intervals for High-Dimensional Linear Regression: Minimax Rates and Adaptivity

Confidence sets play a fundamental role in statistical inference. In this paper, we consider confidence intervals for high dimensional linear regression with random design. We first establish the convergence rates of the minimax expected length for confidence intervals in the oracle setting where the sparsity parameter is given. The focus is then on the problem of adaptation to sparsity for the construction of confidence intervals. Ideally, an adaptive confidence interval should have its length automatically adjusted to the sparsity of the unknown regression vector, while maintaining a prespecified coverage probability. It is shown that such a goal is in general not attainable, except when the sparsity parameter is restricted to a small region over which the confidence intervals have the optimal length of the usual parametric rate. It is further demonstrated that the lack of adaptivity is not due to the conservativeness of the minimax framework, but is fundamentally caused by the difficulty of learning the bias accurately.Comment: 31 pages, 1 figur

Classification of Cosmological Trajectories

In the context of effective Friedmann equation we classify the cosmologies in multi-scalar models with an arbitrary scalar potential $V$ according to their geometric properties. It is shown that all flat cosmologies are geodesics with respect to a conformally rescaled metric on the `augmented' target space. Non-flat cosmologies with V=0 are also investigated. It is shown that geodesics in a `doubly-augmented' target space yield cosmological trajectories for any curvature $k$ when projected onto a given hypersurface.Comment: 10 page

Self-supervised CNN for Unconstrained 3D Facial Performance Capture from an RGB-D Camera

We present a novel method for real-time 3D facial performance capture with consumer-level RGB-D sensors. Our capturing system is targeted at robust and stable 3D face capturing in the wild, in which the RGB-D facial data contain noise, imperfection and occlusion, and often exhibit high variability in motion, pose, expression and lighting conditions, thus posing great challenges. The technical contribution is a self-supervised deep learning framework, which is trained directly from raw RGB-D data. The key novelties include: (1) learning both the core tensor and the parameters for refining our parametric face model; (2) using vertex displacement and UV map for learning surface detail; (3) designing the loss function by incorporating temporal coherence and same identity constraints based on pairs of RGB-D images and utilizing sparse norms, in addition to the conventional terms for photo-consistency, feature similarity, regularization as well as geometry consistency; and (4) augmenting the training data set in new ways. The method is demonstrated in a live setup that runs in real-time on a smartphone and an RGB-D sensor. Extensive experiments show that our method is robust to severe occlusion, fast motion, large rotation, exaggerated facial expressions and diverse lighting

A high order semi-Lagrangian discontinuous Galerkin method for Vlasov-Poisson simulations without operator splitting

In this paper, we develop a high order semi-Lagrangian (SL) discontinuous Galerkin (DG) method for nonlinear Vlasov-Poisson (VP) simulations without operator splitting. In particular, we combine two recently developed novel techniques: one is the high order non-splitting SLDG transport method [Cai, et al., J Sci Comput, 2017], and the other is the high order characteristics tracing technique proposed in [Qiu and Russo, J Sci Comput, 2017]. The proposed method with up to third order accuracy in both space and time is locally mass conservative, free of splitting error, positivity-preserving, stable and robust for large time stepping size. The SLDG VP solver is applied to classic benchmark test problems such as Landau damping and two-stream instabilities for VP simulations. Efficiency and effectiveness of the proposed scheme is extensively tested. Tremendous CPU savings are shown by comparisons between the proposed SL DG scheme and the classical Runge-Kutta DG method

A self-organized particle moving model on scale free network with 1/f21/f^{2} behavior

In this paper we propose a self-organized particle moving model on scale free network with the algorithm of the shortest path and preferential walk. The over-capacity property of the vertices in this particle moving system on complex network is studied from the holistic point of view. Simulation results show that the number of over-capacity vertices forms punctuated equilibrium processes as time elapsing, that the average number of over-capacity vertices under each local punctuated equilibrium process has power law relationship with the local punctuated equilibrium value. What's more, the number of over-capacity vertices has the bell-shaped temporal correlation and $1/f^{2}$ behavior. Finally, the average lifetime $L(t)$ of particles accumulated before time $t$ is analyzed to find the different roles of the shortest path algorithm and the preferential walk algorithm in our model.Comment: 8 pages, 5 figure

Non-parametric threshold estimation for classical risk process perturbed by diffusion

In this paper,we consider a macro approximation of the flow of a risk reserve, The process is observed at discrete time points. Because we cannot directly observe each jump time and size then we will make use of a technique for identifying the times when jumps larger than a suitably defined threshold occurred. We estimate the jump size and survival probability of our risk process from discrete observations

Hidden Messenger from Quantum Geometry: Towards Information Conservation in Quantum Gravity

The back reactions of Hawking radiation allow nontrivial correlations between consecutive Hawking quanta, which gives a possible way of resolving the paradox of black hole information loss known as the hidden messenger method. In a recent work of Ma {\it et al} [arXiv:1711.10704], this method is enhanced by a general derivation using small deviations of the states of Hawking quanta off canonical typicality. In this paper, we use this typicality argument to study the effects of generic back reactions on the quantum geometries described by spin network states, and discuss the viability of entropy conservation in loop quantum gravity. We find that such back reactions lead to small area deformations of quantum geometries including those of quantum black holes. This shows that the hidden-messenger method is still viable in loop quantum gravity, which is a first step towards resolving the paradox of black hole information loss in quantum gravity.Comment: 13 page

A high order semi-Lagrangian discontinuous Galerkin method for the two-dimensional incompressible Euler equations and the guiding center Vlasov model without operator splitting

In this paper, we generalize a high order semi-Lagrangian (SL) discontinuous Galerkin (DG) method for multi-dimensional linear transport equations without operator splitting developed in Cai et al. (J. Sci. Comput. 73: 514-542, 2017) to the 2D time dependent incompressible Euler equations in the vorticity-stream function formulation and the guiding center Vlasov model. We adopt a local DG method for Poisson's equation of these models. For tracing the characteristics, we adopt a high order characteristics tracing mechanism based on a prediction-correction technique. The SLDG with large time-stepping size might be subject to extreme distortion of upstream cells. To avoid this problem, we propose a novel adaptive time-stepping strategy by controlling the relative deviation of areas of upstream cells.Comment: arXiv admin note: text overlap with arXiv:1709.0253

Proof of a congruence on sums of powers of qq-binomial coefficients

We prove that, if $m,n\geqslant 1$ and $a_1,\ldots,a_m$ are nonnegative integers, then \begin{align*} \frac{[a_1+\cdots+a_m+1]!}{[a_1]!\ldots[a_m]!}\sum^{n-1}_{h=0}q^h\prod_{i=1}^m{h\brack a_i} \equiv 0\pmod{[n]}, \end{align*} where $[n]=\frac{1-q^n}{1-q}$, $[n]!=[n][n-1]\cdots[1]$, and ${a\brack b}=\prod_{k=1}^b\frac{1-q^{a-k+1}}{1-q^k}$. The $a_1=\cdots=a_m$ case confirms a recent conjecture of Z.-W. Sun. We also show that, if $p>\max\{a,b\}$ is a prime, then \begin{align*} \frac{[a+b+1]!}{[a]![b]!}\sum_{h=0}^{p-1}q^h{h\brack a}{h\brack b} \equiv (-1)^{a-b} q^{ab-{a\choose 2}-{b\choose 2}}[p]\pmod{[p]^2}. \end{align*}Comment: 5 page