We prove upper and lower bounds for computing Merkle tree
traversals, and display optimal trade-offs between time
and space complexity of that problem.

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We consider the problem of traversing skew (unbalanced) Merkle
trees and design an algorithm for traversing a skew Merkle tree
in time O(log n/log t) and space O(log n (t/log t)), for any choice
of parameter t\geq 2.
This algorithm can be of special interest in situations when
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We show that quantum algorithms of time T and space $S \ge \log T$ with intermediate measurements can be simulated by quantum algorithms of time $T\cdot \mathrm{poly}(S)$ and space $O(S\cdot \log T)$ without intermediate measurements. The best simulations prior to this work required either $\Omega(T)$ space (by the deferred measurement ... more >>>

Time efficient decoding algorithms for error correcting codes often require linear space. However, locally decodable codes yield more efficient randomized decoders that run in time $n^{1+o(1)}$ and space $n^{o(1)}$. In this work we focus on deterministic decoding.
Gronemeier showed that any non-adaptive deterministic decoder for a good code running ... more >>>