Quantum Information Processing · 2018 · 70 citations · 22 references
ComputingComputer EngineeringComputer ScienceAlgorithmsCryptographyParallel ComputingAlgorithm AnalysisCircuit ComplexityComputational ComplexityQuantum CircuitsSpace ComplexityTime ComplexityComplexity AnalysisCryptanalysisParallelizationQuantum CryptanalysisQuantum Query ComplexityQuantum Search AlgorithmsQuery ComplexitySpace Complexity Analysis
Performance of cryptanalytic quantum search algorithms is mainly inferred from query complexity which hides overhead induced by an implementation. To shed light on quantitative complexity analysis removing hidden factors, we provide a framework for estimating time–space complexity, with carefully accounting for characteristics of target cryptographic functions. Processor and circuit parallelization methods are taken into account, resulting in the time–space trade-off curves in terms of depth and qubit . The method guides how to rank different circuit designs in order of their efficiency. The framework is applied to representative cryptosystems NIST referred to as a guideline for security parameters, reassessing the security strengths of AES and SHA-2.
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Elementary gates for quantum computation
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