Method for interactive, real-time animation of soft body dynamics

There is presented a method for interactive, real-time animation of soft body dynamics , comprising the steps of: providing a 3D model of a soft body, the model comprising a set of vertices connected by edges ; defining a set of physical constraints between vertices in the 3D model , the set of constraints forming a system of linear equations comprising a set of unknowns representing the positions of the vertices ; applying a Brooks-Vizing node coloring algorithm in order to partition the system of linear equations into a set of partitions each including an independent subset of unknowns; for each partition , applying a Gauss - Seidel based solver in parallel in order to determine an approximation of the unknowns ; and using the determined approximation of the unknowns to update the 3D model . There is also pre sented an animation system configured to perform the above-described method

Measurable Vizing's theorem

We prove a full measurable version of Vizing's theorem for bounded degree Borel graphs, that is, we show that every Borel graph $\mathcal{G}$ of degree uniformly bounded by $\Delta\in \mathbb{N}$ defined on a standard probability space $(X,\mu)$ admits a $\mu$-measurable proper edge coloring with $(\Delta+1)$-many colors. This answers a question of Marks [Question 4.9, J. Amer. Math. Soc. 29 (2016)] also stated in Kechris and Marks as a part of [Problem 6.13, survey (2020)], and extends the result of the author and Pikhurko [Adv. Math. 374, (2020)] who derived the same conclusion under the additional assumption that the measure $\mu$ is $\mathcal{G}$-invariant

Distributed (Δ+1)(\Delta+1)-Coloring in Sublogarithmic Rounds

We give a new randomized distributed algorithm for $(\Delta+1)$-coloring in the LOCAL model, running in $O(\sqrt{\log \Delta})+ 2^{O(\sqrt{\log \log n})}$ rounds in a graph of maximum degree~$\Delta$. This implies that the $(\Delta+1)$-coloring problem is easier than the maximal independent set problem and the maximal matching problem, due to their lower bounds of $\Omega \left( \min \left( \sqrt{\frac{\log n}{\log \log n}}, \frac{\log \Delta}{\log \log \Delta} \right) \right)$ by Kuhn, Moscibroda, and Wattenhofer [PODC'04]. Our algorithm also extends to list-coloring where the palette of each node contains $\Delta+1$ colors. We extend the set of distributed symmetry-breaking techniques by performing a decomposition of graphs into dense and sparse parts

Borel versions of the Local Lemma and LOCAL algorithms for graphs of finite asymptotic separation index

Asymptotic separation index is a parameter that measures how easily a Borel graph can be approximated by its subgraphs with finite components. In contrast to the more classical notion of hyperfiniteness, asymptotic separation index is well-suited for combinatorial applications in the Borel setting. The main result of this paper is a Borel version of the Lov\'asz Local Lemma -- a powerful general-purpose tool in probabilistic combinatorics -- under a finite asymptotic separation index assumption. As a consequence, we show that locally checkable labeling problems that are solvable by efficient randomized distributed algorithms admit Borel solutions on bounded degree Borel graphs with finite asymptotic separation index. From this we derive a number of corollaries, for example a Borel version of Brooks's theorem for graphs with finite asymptotic separation index

Parallel iterative solvers for real-time elastic deformations

Physics-based animation of elastic materials allows to simulate dynamic deformable objects such as fabrics, human tissue, hair, etc. Due to their complex inner mechanical behaviour, it is difficult to replicate their motions interactively and accurately at the same time. This course introduces students and practitioners to several parallel iterative techniques to tackle this problem and achieve elastic deformations in real-time. We focus on techniques for applications such as video games and interactive design, with\ua0fixed and small hard time budgets\ua0available for physically-based animation, and where responsiveness and stability are often more important than accuracy, as long as the results are believable. The course focuses on solvers able to fully exploit the computational capabilities of modern GPU architectures, effectively solving systems of hundreds of thousands of nonlinear equations in a matter of few milliseconds. The course introduces the basic concepts concerning physics-based elastic objects, and provide an overview of the different types of numerical solvers available in the literature. Then, we show how some variants of traditional solvers can address real-time animation and assess them in terms of accuracy, robustness and performance. Practical examples are provided throughout the course, in particular how to apply the depicted solvers to Projective Dynamics and Position-based Dynamics, two recent and popular physics models for elastic materials

Algorithms for Fundamental Problems in Computer Networks.

Traditional studies of algorithms consider the sequential setting, where the whole input data is fed into a single device that computes the solution. Today, the network, such as the Internet, contains of a vast amount of information. The overhead of aggregating all the information into a single device is too expensive, so a distributed approach to solve the problem is often preferable. In this thesis, we aim to develop efficient algorithms for the following fundamental graph problems that arise in networks, in both sequential and distributed settings. Graph coloring is a basic symmetry breaking problem in distributed computing. Each node is to be assigned a color such that adjacent nodes are assigned different colors. Both the efficiency and the quality of coloring are important measures of an algorithm. One of our main contributions is providing tools for obtaining colorings of good quality whose existence are non-trivial. We also consider other optimization problems in the distributed setting. For example, we investigate efficient methods for identifying the connectivity as well as the bottleneck edges in a distributed network. Our approximation algorithm is almost-tight in the sense that the running time matches the known lower bound up to a poly-logarithmic factor. For another example, we model how the task allocation can be done in ant colonies, when the ants may have different capabilities in doing different tasks. The matching problems are one of the classic combinatorial optimization problems. We study the weighted matching problems in the sequential setting. We give a new scaling algorithm for finding the maximum weight perfect matching in general graphs, which improves the long-standing Gabow-Tarjan's algorithm (1991) and matches the running time of the best weighted bipartite perfect matching algorithm (Gabow and Tarjan, 1989). Furthermore, for the maximum weight matching problem in bipartite graphs, we give a faster scaling algorithm whose running time is faster than Gabow and Tarjan's weighted bipartite {it perfect} matching algorithm.PhDComputer Science and EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/113540/1/hsinhao_1.pd

On the Lovász theta function for independent sets in sparse graphs

We consider the maximum independent set problem on graphs with maximum degree~$d$. We show that the integrality gap of the Lov\'asz $\vartheta$-function based SDP is $\widetilde{O}(d/\log^{3/2} d)$. This improves on the previous best result of $\widetilde{O}(d/\log d)$, and almost matches the integrality gap of $\widetilde{O}(d/\log^2 d)$ recently shown for stronger SDPs, namely those obtained using poly-$(\log(d))$ levels of the $SA^+$ semidefinite hierarchy. The improvement comes from an improved Ramsey-theoretic bound on the independence number of $K_r$-free graphs for large values of $r$. We also show how to obtain an algorithmic version of the above-mentioned $SA^+$-based integrality gap result, via a coloring algorithm of Johansson. The resulting approximation guarantee of $\widetilde{O}(d/\log^2 d)$ matches the best unique-games-based hardness result up to lower-order poly-$(\log\log d)$ factors