Event Stream Processing with Multiple Threads

Current runtime verification tools seldom make use of multi-threading to speed up the evaluation of a property on a large event trace. In this paper, we present an extension to the BeepBeep 3 event stream engine that allows the use of multiple threads during the evaluation of a query. Various parallelization strategies are presented and described on simple examples. The implementation of these strategies is then evaluated empirically on a sample of problems. Compared to the previous, single-threaded version of the BeepBeep engine, the allocation of just a few threads to specific portions of a query provides dramatic improvement in terms of running time

Quantum complexity of minimum cut

The minimum cut problem in an undirected and weighted graph G is to find the minimum total weight of a set of edges whose removal disconnects G. We completely characterize the quantum query and time complexity of the minimum cut problem in the adjacency matrix model. If G has n vertices and edge weights at least 1 and at most τ, we give a quantum algorithm to solve the minimum cut problem using Õ(n3/2√τ) queries and time. Moreover, for every integer 1 ≤ τ ≤ n we give an example of a graph G with edge weights 1 and τ such that solving the minimum cut problem on G requires Ω(n3/2√τ) queries to the adjacency matrix of G. These results contrast with the classical randomized case where Ω(n2) queries to the adjacency matrix are needed in the worst case even to decide if an unweighted graph is connected or not. In the adjacency array model, when G has m edges the classical randomized complexity of the minimum cut problem is Θ̃(m). We show that the quantum query and time complexity are Õ(√mnτ) and Õ(√mnτ + n3/2), respectively, where again the edge weights are between 1 and τ. For dense graphs we give lower bounds on the quantum query complexity of Ω(n3/2) for τ > 1 and Ω(τn) for any 1 ≤ τ ≤ n. Our query algorithm uses a quantum algorithm for graph sparsification by Apers and de Wolf (FOCS 2020) and results on the structure of near-minimum cuts by Kawarabayashi and Thorup (STOC 2015) and Rubinstein, Schramm and Weinberg (ITCS 2018). Our time efficient implementation builds on Karger's tree packing technique (STOC 1996)

Contracting Public Transport Infrastructure: Recent experience with the Dutch High Speed Line and the Amsterdam North-South Metro Line

Institute of Transport and Logistics Studies. Faculty of Economics and Business. The University of Sydne

Finding the KT partition of a weighted graph in near-linear time

In a breakthrough work, Kawarabayashi and Thorup (J.~ACM'19) gave a near-linear time deterministic algorithm for minimum cut in a simple graph $G = (V,E)$. A key component is finding the $(1+\varepsilon)$-KT partition of $G$, the coarsest partition $\{P_1, \ldots, P_k\}$ of $V$ such that for every non-trivial $(1+\varepsilon)$-near minimum cut with sides $\{S, \bar{S}\}$ it holds that $P_i$ is contained in either $S$ or $\bar{S}$, for $i=1, \ldots, k$. Here we give a near-linear time randomized algorithm to find the $(1+\varepsilon)$-KT partition of a weighted graph. Our algorithm is quite different from that of Kawarabayashi and Thorup and builds on Karger's framework of tree-respecting cuts (J.~ACM'00). We describe applications of the algorithm. (i) The algorithm makes progress towards a more efficient algorithm for constructing the polygon representation of the set of near-minimum cuts in a graph. This is a generalization of the cactus representation initially described by Bencz\'ur (FOCS'95). (ii) We improve the time complexity of a recent quantum algorithm for minimum cut in a simple graph in the adjacency list model from $\widetilde O(n^{3/2})$ to $\widetilde O(\sqrt{mn})$. (iii) We describe a new type of randomized algorithm for minimum cut in simple graphs with complexity $O(m + n \log^6 n)$. For slightly dense graphs this matches the complexity of the current best $O(m + n \log^2 n)$ algorithm which uses a different approach based on random contractions. The key technical contribution of our work is the following. Given a weighted graph $G$ with $m$ edges and a spanning tree $T$, consider the graph $H$ whose nodes are the edges of $T$, and where there is an edge between two nodes of $H$ iff the corresponding 2-respecting cut of $T$ is a non-trivial near-minimum cut of $G$. We give a $O(m \log^4 n)$ time deterministic algorithm to compute a spanning forest of $H$

A Single-Center Comparison of Extended and Restricted THROMBOPROPHYLAXIS with LMWH after Metabolic Surgery

IntroductionMorbid obesity is an important risk factor for developing a venous thromboembolic events (VTE) after surgery. Fast-track protocols in metabolic surgery can lower the risk of VTE in the postoperative period by reducing the immobilization period. Administration of thromboprophylaxis can be a burden for patients. This study aims to compare extended to restricted thromboprophylaxis with low molecular weight heparin (LMWH) for patients undergoing metabolic surgery.MethodsIn this single center retrospective cohort study, data was collected from patients undergoing a primary Roux-en-Y gastric bypass (RYGB) or sleeve gastrectomy (SG) between 2014 and 2018. Patients operated in 2014-2017 received thromboprophylaxis for two weeks. In 2018, patients only received thromboprophylaxis during hospital admission. Patients already using anticoagulants were analyzed as a separate subgroup. The primary outcome measure was the rate of clinically significant VTEs within three months. Secondary outcome measures were postoperative hemorrhage and reoperations for hemorrhage.Results3666 Patients underwent a primary RYGB or SG following the fast-track protocol. In total, two patients in the 2014-2017 cohort were diagnosed with VTE versus zero patients in the 2018 cohort. In the historic group, 34/2599 (1.3%) hemorrhages occurred and in the recent cohort 8/720 (1.1%). Postoperative hemorrhage rates did not differ between the two cohorts (multivariable analysis, p=0.475). In the subgroup of patients using anticoagulants, 21/347(6.1%) patients developed a postoperative hemorrhage. Anticoagulant use was a significant predictor of postoperative hemorrhage (

A unified framework of quantum walk search

Many quantum algorithms critically rely on quantum walk search, or the use of quantum walks to speed up search problems on graphs. However, the main results on quantum walk search are scattered over different, incomparable frameworks, such as the hitting time framework, the MNRS framework, and the electric network framework. As a consequence, a number of pieces are currently missing. For example, recent work by Ambainis et al. (STOC’20) shows how quantum walks starting from the stationary distribution can always find elements quadratically faster. In contrast, the electric network framework allows quantum walks to start from an arbitrary initial state, but it only detects marked elements. We present a new quantum walk search framework that unifies and strengthens these frameworks, leading to a number of new results. For example, the new framework effectively finds marked elements in the electric network setting. The new framework also allows to interpolate between the hitting time framework, minimizing the number of walk steps, and the MNRS framework, minimizing the number of times elements are checked for being marked. This allows for a more natural tradeoff between resources. In addition to quantum walks and phase estimation, our new algorithm makes use of quantum fast-forwarding, similar to the recent results by Ambainis et al. This perspective also enables us to derive more general complexity bounds on the quantum walk algorithms, e.g., based on Monte Carlo type bounds of the corresponding classical walk. As a final result, we show how in certain cases we can avoid the use of phase estimation and quantum fast-forwarding, answering an open question of Ambainis et al.</p

The Wellesley News (01-19-1933)

https://repository.wellesley.edu/news/1936/thumbnail.jp

Petersen's Hernia after Mini (One Anastomosis) Gastric Bypass

info:eu-repo/semantics/publishedVersio

On analog quantum algorithms for the mixing of Markov chains

The problem of sampling from the stationary distribution of a Markov chain finds widespread applications in a variety of fields. The time required for a Markov chain to converge to its stationary distribution is known as the classical mixing time. In this article, we deal with analog quantum algorithms for mixing. First, we provide an analog quantum algorithm that given a Markov chain, allows us to sample from its stationary distribution in a time that scales as the sum of the square root of the classical mixing time and the square root of the classical hitting time. Our algorithm makes use of the framework of interpolated quantum walks and relies on Hamiltonian evolution in conjunction with von Neumann measurements. There also exists a different notion for quantum mixing: the problem of sampling from the limiting distribution of quantum walks, defined in a time-averaged sense. In this scenario, the quantum mixing time is defined as the time required to sample from a distribution that is close to this limiting distribution. Recently we provided an upper bound on the quantum mixing time for Erd\"os-Renyi random graphs [Phys. Rev. Lett. 124, 050501 (2020)]. Here, we also extend and expand upon our findings therein. Namely, we provide an intuitive understanding of the state-of-the-art random matrix theory tools used to derive our results. In particular, for our analysis we require information about macroscopic, mesoscopic and microscopic statistics of eigenvalues of random matrices which we highlight here. Furthermore, we provide numerical simulations that corroborate our analytical findings and extend this notion of mixing from simple graphs to any ergodic, reversible, Markov chain.Comment: The section concerning time-averaged mixing (Sec VIII) has been updated: Now contains numerical plots and an intuitive discussion on the random matrix theory results used to derive the results of arXiv:2001.0630