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Tight bounds on quantum searching

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arxiv quant-ph/9605034 v1 pith:6W7CY54O submitted 1996-05-23 quant-ph

classification quant-ph
keywords algorithmnumberquantumgroversearchingallowsdatabaseelement
verification ladder T0 review T1 audit T2 compute T3 formal
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We provide a tight analysis of Grover's recent algorithm for quantum database searching. We give a simple closed-form formula for the probability of success after any given number of iterations of the algorithm. This allows us to determine the number of iterations necessary to achieve almost certainty of finding the answer. Furthermore, we analyse the behaviour of the algorithm when the element to be found appears more than once in the table and we provide a new algorithm to find such an element even when the number of solutions is not known ahead of time. Using techniques from Shor's quantum factoring algorithm in addition to Grover's approach, we introduce a new technique for approximate quantum counting, which allows to estimate the number of solutions. Finally we provide a lower bound on the efficiency of any possible quantum database searching algorithm and we show that Grover's algorithm nearly comes within a factor 2 of being optimal in terms of the number of probes required in the table.

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Cited by 4 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Constraint-Aware Quantum Optimization of Defect Configurations in Doped ZrO2: XY-Mixer QAOA and Grover Adaptive Search

    quant-ph 2026-06 unverdicted novelty 7.0 of 10

    Presents an end-to-end constraint-aware quantum optimization pipeline using XY-mixer QAOA and Grover Adaptive Search for low-energy defect configurations in doped ZrO2, with QAOA validated against exact enumeration on...

  2. Quantum Communication Advantage for Leader Election and Agreement

    cs.DC 2025-02 conditional novelty 7.0 of 10

    Quantum communication reduces the message complexity of leader election and agreement in CONGEST networks below classical lower bounds.

  3. QSCI-CMP: Quantum-Selected Configuration Interaction with Chemically Motivated Preselection

    quant-ph 2026-08 accept novelty 6.0 of 10

    QSCI-CMP cuts the quantum sampling cost of SQD-AA by classically preselecting low-excitation, low-seniority determinants and using a compact oracle that checks those properties in superposition.

  4. Nested Grover's Algorithm for Tree Search

    quant-ph 2025-09 reject novelty 4.0 of 10

    A nested Grover algorithm for tree search claims cost O(m*2^(m/4)) using partial candidate solutions, but the speedup relies on an unexamined assumption that the candidate set contains the solution.

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