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Research PaperResearchia:202610.01075

A Noise Operator Approach to Quantum Query Complexity and Time-Space Tradeoff Lower Bounds

Paul Beame

Abstract

Time and space (memory) are two of the most important measures of cost in computation, even more so for quantum computation. In quantum computation our tools for proving unconditional tradeoffs between time and space are surprisingly limited. The first quantum time-space tradeoff lower bounds were proven for sorting by Klauck, Špalek and de Wolf. Unfortunately, their method is limited to proving output-oblivious lower bounds (i.e. the lower bounds only apply to algorithms with a non-adaptive o...

Submitted: October 1, 2026Subjects: Quantum Physics; Quantum Computing

Description / Details

Time and space (memory) are two of the most important measures of cost in computation, even more so for quantum computation. In quantum computation our tools for proving unconditional tradeoffs between time and space are surprisingly limited. The first quantum time-space tradeoff lower bounds were proven for sorting by Klauck, Špalek and de Wolf. Unfortunately, their method is limited to proving output-oblivious lower bounds (i.e. the lower bounds only apply to algorithms with a non-adaptive output schedule) and other methods have yielded nothing beyond output-oblivious lower bounds for sorting.We prove the first fully general quantum time-space tradeoff lower bound for sorting. We do so by introducing a novel method based on the noise operator to add to the analysis toolkit for proving quantum query and time space tradeoff lower bounds. By combining our resulting quantum noise stability bound with quantum recording query methods, we prove an Ω(n4/3(log⁡log⁡n)/(S1/3log⁡n))Ω(n^{4/3} (\log \log n)/(S^{1/3} \log n)) lower bound on the number of queries that a fully general quantum algorithm with at most SS qubits of memory requires to sort nn numbers from [n2][n^2]. Applying our noise operator argument involves purely classical arguments, which makes it particularly simple to use. We also us it to prove that, for any strongly universal (pairwise independent) hash function family HH from nn bits to mm bits, almost all hash functions in HH require a quantum algorithm with at most SS qubits of memory to make Ω(nm/S)Ω(nm/S) queries to an input xx in order to compute h(x)h(x), even with very small success probability. Previously, Mansour, Nisan, and Tiwari had shown a similar classical lower bound using their hash mixing lemma. Our noise operator method allows us to use a related but simpler property of hash functions to prove our lower bounds.


Source: arXiv:2609.40334v1 - http://arxiv.org/abs/2609.40334v1 PDF: https://arxiv.org/pdf/2609.40334v1 Original Link: http://arxiv.org/abs/2609.40334v1

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Date:
Oct 1, 2026
Topic:
Quantum Computing
Area:
Quantum Physics
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