2021
DOI: 10.48550/arxiv.2110.06665
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Constructions on Real Approximate Mutually Unbiased Bases

Abstract: Mutually unbiased bases (MUB) have many applications in quantum information processing and quantum cryptography. Several complex MUB's in C d for some dimension d and with larger size have been constructed. On the other hand, real MUB's with larger size are rare which lead to consider constructing approximate MUB (AMUB). In this paper we present a general and useful way to get real AMUB in R 2d from any complex AMUB in C d . From this method we present many new series of real AMUB's with parameters better than… Show more

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Cited by 2 publications
(3 citation statements)
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“…Nevertheless, not all overlaps are the same, hence the eigenvectors corresponding to q ̸ = q ′ are not MUB. However, the modulus square of their overlap is bounded by twice the inverse of the system's dimension, therefore in large Hlibert spaces the corresponding eigenbases are AMUB [6][7][8][9][10][11]. It is natural to ask what happens for non-prime d. We observed that for some choices of q ̸ = q ′ the overlaps between the corresponding bases are bounded by 2/D as well, however in general this overlap exceeds 2/D.…”
Section: Resultsmentioning
confidence: 90%
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“…Nevertheless, not all overlaps are the same, hence the eigenvectors corresponding to q ̸ = q ′ are not MUB. However, the modulus square of their overlap is bounded by twice the inverse of the system's dimension, therefore in large Hlibert spaces the corresponding eigenbases are AMUB [6][7][8][9][10][11]. It is natural to ask what happens for non-prime d. We observed that for some choices of q ̸ = q ′ the overlaps between the corresponding bases are bounded by 2/D as well, however in general this overlap exceeds 2/D.…”
Section: Resultsmentioning
confidence: 90%
“…In realistic situations perfect MUB are hard to implement. This lead to the concept of approximate MUB (AMUB) [6,7] in complex [8,9] and in real spaces [10,11]. In case of AMUB one relaxes the condition (1) and instead looks for bases whose vectors obey…”
Section: Introductionmentioning
confidence: 99%
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