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arXiv:1207.4537 · Quantum Information and Computation

Reduction from non-injective hidden shift problem to injective hidden shift problem

Mirmojtaba Gharibi

Published Mar 1, 2013• 3 citations
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Abstract

We introduce a simple tool that can be used to reduce non-injective instances of the hidden shift problem over arbitrary group to injective instances over the same group. In particular, we show that the average-case non-injective hidden shift problem admit this reduction. We show similar results for (non-injective) hidden shift problem for bent functions. We generalize the notion of influence and show how it relates to applicability of this tool for doing reductions. In particular, these results can be used to simplify the main results by Gavinsky, Roetteler, and Roland about the hidden shift problem for the Boolean-valued functions and bent functions, and also to generalize their results to non-Boolean domains (thereby answering an open question that they pose).

DOI
10.26421/qic13.3-4-4

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We introduce a simple tool that can be used to reduce non-injective instances of the hidden shift problem over arbitrary group to injective instances over the same group. In particular, we show that the average-case non-injective hidden shift problem admit this reduction. We show similar results for (non-injective) hidden shift problem for bent functions. We generalize the notion of influence and show how it relates to applicability of this tool for doing reductions. In particular, these results can be used to simplify the main results by Gavinsky, Roetteler, and Roland about the hidden shift problem for the Boolean-valued functions and bent functions, and also to generalize their results to non-Boolean domains (thereby answering an open question that they pose).
In this work, we mostly concentrate on the hidden shift problem for non-injective functions. It is worthwhile to know that the query complexity of the non-injective hidden shift problem is exponential in the worst case by the well known bounds on the unstructured search problem. Hence, we can make this problem more tractable by imposing additional constraints on the problem. Perhaps the first constraint that comes to mind is to address the average case problem. In this work, we show that the average case non-injective hidden shift problem can be reduced to the injective hidden shift problem by giving one such reduction. The reduction is based on a tool we developed called injectivization. The result is strong in the sense that the underlying group can be any finite group and that the non-injective functions for which we have defined the hidden shift problem can have range in an arbitrary finite set. Using this tool, we simplify the main result of a recent paper by about the hidden shift problem for Boolean-valued functions by reducing that problem to Simon's problem. They also posed an open question which is subject to personal interpretation. We answer the seemingly most general interpretation of the question. However, we use our own techniques in doing so (the authors ask if their techniques can be used for addressing that problem). Another constraint that one can consider is to have a promise on the structure of the functions. In this work we consider the hidden shift problem for c-almost generalized bent functions. A class of functions which we defined that includes the generalized bent functions. Then we turn our attention toward the generalized hidden shift problem which is easier than injective hidden shift problem and hence more tractable. We state some of our observations about this problem. Finally we show that the average classical query complexity of the non-injective hidden shift problem over groups of form (Z/mZ)^n when m is a constant is exponential, which also immediately implies that the classical average query complexity of the non-injective hidden shift problem is exponential. We also show that the worst-case classical query complexity of the generalized injective hidden shift problem over the same group is high, which implies that the classical query complexity of the hidden shift problem is high.
We study quantum algorithms for the hidden shift problem of complex scalar- and vector-valued functions on finite abelian groups. Given oracle access to a shifted function and the Fourier transform of the unshifted function, the goal is to find the hidden shift. We analyze the success probability of our algorithms when using a constant number of queries. For bent functions, they succeed with probability 1, while for arbitrary functions the success probability depends on the `bentness' of the function.
A new quantum algorithm for the hidden shift problem in Z2tn\mathbb{Z}_{2^t}^nZ2tn​
In this paper we make a step towards a time and space efficient algorithm for the hidden shift problem for groups of the form Zkn\mathbb{Z}_k^nZkn​. We give a solution to the case when kkk is a power of 2, which has polynomial running time in nnn, and only uses quadratic classical, and linear quantum space in nlog⁡(k)n\log (k)nlog(k). It can be a useful tool in the general case of the hidden shift and hidden subgroup problems too, since one of the main algorithms made to solve them can use this algorithm as a subroutine in its recursive steps, making it more efficient in some instances.
An important special case of the hidden subgroup problem is equivalent to the hidden shift problem over abelian groups. An efficient solution to the latter problem could serve as a building block of quantum hidden subgroup algorithms over solvable groups. The main idea of a promising approach to the hidden shift problem is a reduction to solving systems of certain random disequations in finite abelian groups. By a disequation we mean a constraint of the form f(x)≠0f(x)\neq 0f(x)=0. In our case, the functions on the left hand side are generalizations of linear functions. The input is a random sample of functions according to a distribution which is up to a constant factor uniform over the "linear" functions fff such that f(u)≠0f(u)\neq 0f(u)=0 for a fixed, although unknown element u∈Au\in Au∈A. The goal is to find uuu, or, more precisely, all the elements u′∈Au'\in Au′∈A satisfying the same disequations as uuu. In this paper we give a classical probabilistic algorithm which solves the problem in an abelian ppp-group AAA in time polynomial in the sample size NNN, where $N=(\log\size{A})^{O(q^2)}$, and qqq is the exponent of AAA.