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Quantum and Classical Communication-Space Tradeoffs from Rectangle Bounds
"... We derive bounds on the product of the communication C and space S for communicating circuits. The first bound applies to quantum circuits and follows from a "bipartite product" result for the discrepancy of communication problems. If for any problem f : XY the multicolor discrepancy of the co ..."
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Cited by 6 (2 self)
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We derive bounds on the product of the communication C and space S for communicating circuits. The first bound applies to quantum circuits and follows from a "bipartite product" result for the discrepancy of communication problems. If for any problem f : XY the multicolor discrepancy of the communication matrix of f is 1/2 then the problem in which Alice receives some l inputs, Bob r inputs, and their task is to compute f(x i , y j ) for the l r pairs of inputs (x i , y j ), has a quantum communication-space tradeo# CS (lrd log |Z|).
Quantum time-space tradeoffs for sorting
- Proceedings of 35th ACM STOC
, 2003
"... We investigate the complexity of sorting in the model of sequential quantum circuits. While it is known that a quantum algorithm based on comparisons alone cannot outperform classical sorting algorithms by more than a constant factor in time complexity, this is wrong in a space bounded setting. We o ..."
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Cited by 6 (1 self)
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We investigate the complexity of sorting in the model of sequential quantum circuits. While it is known that a quantum algorithm based on comparisons alone cannot outperform classical sorting algorithms by more than a constant factor in time complexity, this is wrong in a space bounded setting. We observe that for all storage bounds S, one can devise a quantum algorithm that sorts n numbers (using comparisons only) in time T = O(n
Comparison-Based Time–Space Lower Bounds for Selection
"... We establish the first nontrivial lower bounds on timespace tradeoffs for the selection problem. We prove that any comparison-based randomized algorithm for finding the median requires Ω(n log logS n) expected time in the RAM model (or more generally in the comparison branching program model), if we ..."
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Cited by 1 (0 self)
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We establish the first nontrivial lower bounds on timespace tradeoffs for the selection problem. We prove that any comparison-based randomized algorithm for finding the median requires Ω(n log logS n) expected time in the RAM model (or more generally in the comparison branching program model), if we have S bits of extra space besides the read-only input array. This bound is tight for all S ≫ log n, and remains true even if the array is given in a random order. Our result thus answers a 16-year-old question of Munro and Raman, and also complements recent lower bounds that are restricted to sequential access, as in the multi-pass streaming model [Chakrabarti et al., SODA 2008]. We also prove that any comparison-based, deterministic, multi-pass streaming algorithm for finding the median requires Ω(n log ∗ (n/s) + n log s n) worst-case time (in scanning plus comparisons), if we have s cells of space. This bound is also tight for all s ≫ log 2 n. We get deterministic lower bounds for I/O-efficient algorithms as well. All proofs in this paper involve “elementary ” techniques only. 1

