2021
DOI: 10.1142/s0129054121500246
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Error-Free Affine, Unitary, and Probabilistic OBDDs

Abstract: We introduce the affine OBDD model and show that zero-error affine OBDDs can be exponentially narrower than bounded-error unitary and probabilistic OBDDs on certain problems. Moreover, we show that Las-Vegas unitary and probabilistic OBDDs can be quadratically narrower than deterministic OBDDs. We also obtain the same results for the automata counterparts of these models.

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Cited by 8 publications
(4 citation statements)
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“…where t < 2k, m > 0, each x i ∈ {0, 1} for 1 ≤ i ≤ m, and m i=1 x i = 1. It was shown [13] that MODXOR k for k > 0 is recognized by a (2k + 1)-state AfA with zero error. Due to Theorem 5, the same results can also be obtained by designing a 2k-state NFA, which accepts each member on a single path.…”
Section: ⊓ ⊔mentioning
confidence: 99%
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“…where t < 2k, m > 0, each x i ∈ {0, 1} for 1 ≤ i ≤ m, and m i=1 x i = 1. It was shown [13] that MODXOR k for k > 0 is recognized by a (2k + 1)-state AfA with zero error. Due to Theorem 5, the same results can also be obtained by designing a 2k-state NFA, which accepts each member on a single path.…”
Section: ⊓ ⊔mentioning
confidence: 99%
“…The computational power of AfAs and their generalizations have been examined and compared with their probabilistic and quantum counterparts in a series of papers [23,5,9,18,12,24,10,11,13,14]. In the unbounded-error and boundederror language recognition modes, AfAs are more powerful than PFAs and QFAs, where the latter models recognize all and only stochastic and regular languages, respectively [20,19,16,27,17].…”
Section: Introductionmentioning
confidence: 99%
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“…One of them is quantum online algorithms with repeated test [22]; another one is quantum online algorithms with restriction on the size of memory [23,24]; quantum algorithms with a buffer [25,26] and others. The question of comparing quantum and classical models was explored for data stream processing models by different researches [27][28][29][30][31][32][33][34][35][36][37][38][39][40].…”
Section: Introductionmentioning
confidence: 99%