265 research outputs found
Sound ranking algorithms for XML search
Ranking algorithms for XML should reflect the actual combined content and structure constraints of queries, while at the same time producing equal rankings for queries that are semantically equal. Ranking algorithms that produce different rankings for queries that are semantically equal are easily detected by tests on large databases: We call such algorithms not sound. We report the behavior of different approaches to ranking content-and-structure queries on pairs of queries for which we expect equal ranking results from the query semantics. We show that most of these approaches are not sound. Of the remaining approaches, only 3 adhere to the W3C XQuery Full-Text standard
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
A Unified Framework of Quantum Walk Search
The main results on quantum walk search are scattered over different, incomparable frameworks, most notably the hitting time framework, originally by Szegedy, the electric network framework by Belovs, and the MNRS framework by Magniez, Nayak, Roland and Santha. As a result, a number of pieces are currently missing. For instance, the electric network framework allows quantum walks to start from an arbitrary initial state, but it only detects marked elements. In recent work by Ambainis et al., this problem was resolved for the more restricted hitting time framework, in which quantum walks must start from the stationary distribution.
We present a new quantum walk search framework that unifies and strengthens these frameworks. This leads to a number of new results. For instance, the new framework not only detects, but finds marked elements in the electric network setting. The new framework also allows one to interpolate between the hitting time framework, which minimizes the number of walk steps, and the MNRS framework, which minimizes the number of times elements are checked for being marked. This allows for a more natural tradeoff between resources. Whereas the original frameworks only rely on quantum walks and phase estimation, our new algorithm makes use of a technique called quantum fast-forwarding, similar to the recent results by Ambainis et al. As a final result we show how in certain cases we can simplify this more involved algorithm to merely applying the quantum walk operator some number of times. This answers an open question of Ambainis et al
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 . A key component is finding the -KT partition of ,
the coarsest partition of such that for every
non-trivial -near minimum cut with sides it
holds that is contained in either or , for .
Here we give a near-linear time randomized algorithm to find the
-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 to
. (iii) We describe a new type of randomized algorithm
for minimum cut in simple graphs with complexity . For
slightly dense graphs this matches the complexity of the current best algorithm which uses a different approach based on random
contractions.
The key technical contribution of our work is the following. Given a weighted
graph with edges and a spanning tree , consider the graph whose
nodes are the edges of , and where there is an edge between two nodes of
iff the corresponding 2-respecting cut of is a non-trivial near-minimum cut
of . We give a time deterministic algorithm to compute a
spanning forest of
A sublinear time quantum algorithm for s-t minimum cut on dense simple graphs
An minimum cut in a graph corresponds to a minimum
weight subset of edges whose removal disconnects vertices and . Finding
such a cut is a classic problem that is dual to that of finding a maximum flow
from to . In this work we describe a quantum algorithm for the minimum
cut problem on undirected graphs. For an undirected
graph with vertices, edges, and integral edge weights bounded by ,
the algorithm computes with high probability the weight of a minimum
cut in time , given adjacency list access to . For simple graphs this
bound is always , even in the dense case when . In contrast, a randomized algorithm must make queries
to the adjacency list of a simple graph even to decide whether and
are connected
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
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