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International Computing and Combinatorics Conference

COCOON 2018: Computing and Combinatorics pp 579–591Cite as

Amplitude Amplification for Operator Identification and Randomized Classes

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 10976))

Abstract

Amplitude amplification (AA) is tool of choice for quantum algorithm designers to increase the success probability of query algorithms that reads its input in the form of oracle gates. Geometrically speaking, the technique can be understood as rotation in a specific two-dimensional space. We study and use a generalized form of this rotation operator to design algorithms in a geometric manner. Specifically, we apply AA to algorithms that take their input in the form of input states and in which rotations with different angles and directions are used in a unified manner. We show that AA can be used to sequentially discriminate between two unitary operators, both without error and with bounded-error, in an asymptotically optimal manner. We also show how to reduce error probability in one and two-sided bounded error algorithms more efficiently than the usual parallel repetitions technique; in particular, errors can be completely eliminated from the exact error algorithms.

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Notes

  1. 1.

    A similar question on exact two-sided-error classical class was asked in http://cstheory.stackexchange.com/questions/20027.

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Author information

Authors and Affiliations

  1. Indraprastha Institute of Information Technology-Delhi (IIIT-D), New Delhi, India

    Debajyoti Bera

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  1. Debajyoti Bera
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Correspondence to Debajyoti Bera .

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Editors and Affiliations

  1. City University of Hong Kong, Hong Kong, China

    Lusheng Wang

  2. Shandong University, Jinan, China

    Daming Zhu

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Bera, D. (2018). Amplitude Amplification for Operator Identification and Randomized Classes. In: Wang, L., Zhu, D. (eds) Computing and Combinatorics. COCOON 2018. Lecture Notes in Computer Science(), vol 10976. Springer, Cham. https://doi.org/10.1007/978-3-319-94776-1_48

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  • DOI: https://doi.org/10.1007/978-3-319-94776-1_48

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-94775-4

  • Online ISBN: 978-3-319-94776-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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