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We prove better lower bounds on additive spanners and emulators, which are lossy compression schemes for undirected graphs, as well as lower bounds on shortcut sets, which reduce the diameter of directed graphs. We show that any $O(n)$-size shortcut set cannot bring the diameter below $Omega(n^{1/6})$, and that any $O(m)$-size shortcut set cannot bring it below $Omega(n^{1/11})$. These improve Hesses [Hesse03] lower bound of $Omega(n^{1/17})$. By combining these constructions with Abboud and Bodwins [AbboudB17] edge-splitting technique, we get additive stretch lower bounds of $+Omega(n^{1/11})$ for $O(n)$-size spanners and $+Omega(n^{1/18})$ for $O(n)$-size emulators. These improve Abboud and Bodwins $+Omega(n^{1/22})$ lower bounds.
It was recently found that there are very close connections between the existence of additive spanners (subgraphs where all distances are preserved up to an additive stretch), distance preservers (subgraphs in which demand pairs have their distance p
We consider a range of simply stated dynamic data structure problems on strings. An update changes one symbol in the input and a query asks us to compute some function of the pattern of length $m$ and a substring of a longer text. We give both condit
Among the most important graph parameters is the Diameter, the largest distance between any two vertices. There are no known very efficient algorithms for computing the Diameter exactly. Thus, much research has been devoted to how fast this parameter
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We give lower bounds on the performance of two of the most popular sampling methods in practice, the Metropolis-adjusted Langevin algorithm (MALA) and multi-step Hamiltonian Monte Carlo (HMC) with a leapfrog integrator, when applied to well-condition