Difference sets are basic combinatorial structures that have applications in signal processing, coding theory, and cryptography. We consider the problem of identifying a shifted version of the characteristic function of a (known) difference set and present a general algorithm that can be used to tackle any hidden shift problem for any difference set in any abelian group. We discuss special cases of this framework which include a) Paley difference sets based on quadratic residues in finite fields which allow to recover the shifted Legendre function quantum algorithm, b) Hadamard difference sets which allow to recover the shifted bent function quantum algorithm, and c) Singer difference sets which allow us to define instances of the dihedral hidden subgroup problem which can be efficiently solved on a quantum computer.Difference sets are basic combinatorial structures that have applications in signal processing, coding theory, and cryptography. We consider the problem of identifying a shifted version of the characteristic function of a (known) difference set and present a general algorithm that can be used to tackle any hidden shift problem for any difference set in any abelian group. We discuss special cases of this framework which include a) Paley difference sets based on quadratic residues in finite fields which allow to recover the shifted Legendre function quantum algorithm, b) Hadamard difference sets which allow to recover the shifted bent function quantum algorithm, and c) Singer difference sets which allow us to define instances of the dihedral hidden subgroup problem which can be efficiently solved on a quantum computer.

Leibniz international proceedings in informaticsJan 1, 20160 citations

Quantum algorithm for a generalized hidden shift problem

Andrew M. Childs, Wim van Dam

Consider the following generalized hidden shift problem: given a function f on {0,...,M-1} x Z_N satisfying f(b,x)=f(b+1,x+s) for b=0,1,...,M-2, find the unknown shift s in Z_N. For M=N, this problem is an instance of the abelian hidden subgroup problem, which can be solved efficiently on a quantum computer, whereas for M=2, it is equivalent to the dihedral hidden subgroup problem, for which no efficient algorithm is known. For any fixed positive epsilon, we give an efficient (i.e., poly(log N)) quantum algorithm for this problem provided M > N^epsilon. The algorithm is based on the "pretty good measurement" and uses H. Lenstra's (classical) algorithm for integer programming as a subroutine.Consider the following generalized hidden shift problem: given a function f on {0,...,M-1} x Z_N satisfying f(b,x)=f(b+1,x+s) for b=0,1,...,M-2, find the unknown shift s in Z_N. For M=N, this problem is an instance of the abelian hidden subgroup problem, which can be solved efficiently on a quantum computer, whereas for M=2, it is equivalent to the dihedral hidden subgroup problem, for which no efficient algorithm is known. For any fixed positive epsilon, we give an efficient (i.e., poly(log N)) quantum algorithm for this problem provided M > N^epsilon. The algorithm is based on the "pretty good measurement" and uses H. Lenstra's (classical) algorithm for integer programming as a subroutine.

arXiv:quant-ph/0507190Symposium on Discrete AlgorithmsJul 19, 200542 citations

Dihedral Hidden Subgroup Problem: A Survey

Hirotada Kobayashi, François Le Gall

After Shor's discovery of an efficient quantum algorithm for integer factoring, hidden subgroup problems play a central role in developing efficient quantum algorithms. In spite of many intensive studies, no efficient quantum algorithms are known for hidden subgroup problems for many non-Abelian groups. Of particular interest are the hidden subgroup problems for the symmetric group and for the dihedral group, because an efficient algorithm for the former implies an efficient solution to the graph isomorphism problem, and that for the latter essentially solves a certain lattice-related problem whose hardness is assumed in cryptography. This paper focuses on the latter case and gives a comprehensive survey of known facts related to the dihedral hidden subgroup problem.After Shor's discovery of an efficient quantum algorithm for integer factoring, hidden subgroup problems play a central role in developing efficient quantum algorithms. In spite of many intensive studies, no efficient quantum algorithms are known for hidden subgroup problems for many non-Abelian groups. Of particular interest are the hidden subgroup problems for the symmetric group and for the dihedral group, because an efficient algorithm for the former implies an efficient solution to the graph isomorphism problem, and that for the latter essentially solves a certain lattice-related problem whose hardness is assumed in cryptography. This paper focuses on the latter case and gives a comprehensive survey of known facts related to the dihedral hidden subgroup problem.

IPSJ Digital CourierJan 1, 20057 citations

Quantum algorithms and the fourier transform

Lawrence Ip, Umesh V. Vazirani

The search for practical problems that can be solved exponentially faster on a quantum computer is one of the primary goals in research into algorithms for quantum computers. It has long been known that such speedups are only possible for highly structured problems. We consider two problems with algebraic structure: (1) the hidden subgroup problem, where we have an unknown subgroup, a function that is constant on cosets of the subgroup, and the task is to find the unknown subgroup; (2) the hidden shift problem, where we have an unknown element of a group, a function that has been shifted by that group element, and the task is to find the unknown group element. We show that the Fourier transform is intimately connected to both these problems. This is because the Fourier transform respects group symmetries. For the hidden subgroup problem, we introduce the idea of using information theoretic techniques to design quantum algorithms. This consists of first finding an optimal set of measurements for distinguishing between different subgroups, followed by attempts to implement this set of measurements. We show that the standard algorithm for the abelian hidden subgroup problem is optimal. For the nonabelian hidden subgroup problem, the optimal measurements respect the Fourier transform in that they can be implemented by first performing a Fourier transform on each coset state, measuring the name of the irreducible representation for each state, followed by a joint measurement over the resulting lower dimensional space. This shows that the “strong standard method” cannot be used to implement the optimal set of measurements. For some instances of the hidden shift problem, we give a quantum algorithms that are exponentially faster than the best known classical algorithm. The algorithms make use of the Fourier transform in a way that may be interpreted as solving a deconvolution problem. As evidence of hardness, we give a reduction from algebraically homomorphic cryptosystems to the shifted Legendre symbol problem. This is an example of a problem which admits an exponential quantum speedup yet is not an instance of the abelian hidden subgroup problem.The search for practical problems that can be solved exponentially faster on a quantum computer is one of the primary goals in research into algorithms for quantum computers. It has long been known that such speedups are only possible for highly structured problems. We consider two problems with algebraic structure: (1) the hidden subgroup problem, where we have an unknown subgroup, a function that is constant on cosets of the subgroup, and the task is to find the unknown subgroup; (2) the hidden shift problem, where we have an unknown element of a group, a function that has been shifted by that group element, and the task is to find the unknown group element. We show that the Fourier transform is intimately connected to both these problems. This is because the Fourier transform respects group symmetries. For the hidden subgroup problem, we introduce the idea of using information theoretic techniques to design quantum algorithms. This consists of first finding an optimal set of measurements for distinguishing between different subgroups, followed by attempts to implement this set of measurements. We show that the standard algorithm for the abelian hidden subgroup problem is optimal. For the nonabelian hidden subgroup problem, the optimal measurements respect the Fourier transform in that they can be implemented by first performing a Fourier transform on each coset state, measuring the name of the irreducible representation for each state, followed by a joint measurement over the resulting lower dimensional space. This shows that the “strong standard method” cannot be used to implement the optimal set of measurements. For some instances of the hidden shift problem, we give a quantum algorithms that are exponentially faster than the best known classical algorithm. The algorithms make use of the Fourier transform in a way that may be interpreted as solving a deconvolution problem. As evidence of hardness, we give a reduction from algebraically homomorphic cryptosystems to the shifted Legendre symbol problem. This is an example of a problem which admits an exponential quantum speedup yet is not an instance of the abelian hidden subgroup problem.

Jan 1, 20040 citations

The Hidden Subgroup Problem in Semidirect Products and Quasi-Hamiltonian Groups

Mauro E. S. Morales

Several early quantum algorithms, including Simon's algorithm and Shor's period-finding are instances of the hidden subgroup problem (HSP) over finite abelian groups. No polynomial-time quantum algorithm is known for the HSP over arbitrary non-abelian finite groups. The non-Abelian case is of particular interest because some instances, such as the dihedral and symmetric group HSPs, are connected to lattice problems and graph isomorphism, respectively. In this work, we give polynomial-time quantum algorithms for two further families containing non-Abelian groups. First, we consider groups of the form $G=A\rtimes_{\varphi} \mathbb{Z}_{p^k}$ , with $A$ finite Abelian, $p$ prime, $k\in \mathbb{N}$ and the action of $\mathbb Z_{p^k}$ is generated by the scalar automorphism $a\mapstoμa$ , for some $μ\in\mathbb Z_{\operatorname{Exp}(A)}^\times$ , where $\mathrm{Exp}(A)$ is the exponent of $A$ . Our algorithm is efficient when $A$ has bounded generator rank and $\mathrm{Exp}(A)/p=\mathrm{polylog}(|G|)$ . This includes the case $A=\mathbb{Z}_N$ for $N\in\mathbb{N}$ and $k=1$ , studied by Bacon, Childs and van Dam (FOCS 2005), and $A=\mathbb{Z}_{q^r}$ with $q$ prime and $r\in \mathbb{N}$ studied by van Dam and Dey (TQC 2014). Second, we give a polynomial-time quantum algorithm for finite quasi-Hamiltonian groups under a mild assumption on the input structure. Quasi-Hamiltonian groups are finite nilpotent groups with modular subgroup lattice, or equivalently the finite groups in which every subgroup is permutable. As far as we know, this is the first quantum algorithm to exploit the modularity of the subgroup lattice for solving the HSP. This extends, under the aforementioned structured input assumption, the quantum algorithm for Dedekind groups given by Hallgren, Russell, and Ta-Shma (SIAM J. Comput. 32, 2003).Several early quantum algorithms, including Simon's algorithm and Shor's period-finding are instances of the hidden subgroup problem (HSP) over finite abelian groups. No polynomial-time quantum algorithm is known for the HSP over arbitrary non-abelian finite groups. The non-Abelian case is of particular interest because some instances, such as the dihedral and symmetric group HSPs, are connected to lattice problems and graph isomorphism, respectively. In this work, we give polynomial-time quantum algorithms for two further families containing non-Abelian groups. First, we consider groups of the form $G=A\rtimes_{\varphi} \mathbb{Z}_{p^k}$, with $A$ finite Abelian, $p$ prime, $k\in \mathbb{N}$ and the action of $\mathbb Z_{p^k}$ is generated by the scalar automorphism $a\mapstoμa$, for some $μ\in\mathbb Z_{\operatorname{Exp}(A)}^\times$, where $\mathrm{Exp}(A)$ is the exponent of $A$. Our algorithm is efficient when $A$ has bounded generator rank and $\mathrm{Exp}(A)/p=\mathrm{polylog}(|G|)$. This includes the case $A=\mathbb{Z}_N$ for $N\in\mathbb{N}$ and $k=1$, studied by Bacon, Childs and van Dam (FOCS 2005), and $A=\mathbb{Z}_{q^r}$ with $q$ prime and $r\in \mathbb{N}$ studied by van Dam and Dey (TQC 2014). Second, we give a polynomial-time quantum algorithm for finite quasi-Hamiltonian groups under a mild assumption on the input structure. Quasi-Hamiltonian groups are finite nilpotent groups with modular subgroup lattice, or equivalently the finite groups in which every subgroup is permutable. As far as we know, this is the first quantum algorithm to exploit the modularity of the subgroup lattice for solving the HSP. This extends, under the aforementioned structured input assumption, the quantum algorithm for Dedekind groups given by Hallgren, Russell, and Ta-Shma (SIAM J. Comput. 32, 2003).

quant-pharXiv:2608.05321Aug 7, 20260 citations

Hidden subgroup problem in quantum computing

Shuhong Gao, Prasit Limbupasiriporn

We study quantum algorithms for the hidden subgroup problem (HSP). The HSP provides a unified framework for many important problems, including factoring integers, graph isomorphism problem, etc. It has been known that the problem for abelian groups can be efficiently solved. However, for non-abelian groups, it remains widely open. In this dissertation we study the problem for some specific non-abelian groups, called q-hedral groups. We start with a quantum algorithm, proposed by Moore et al. (2003), for finding some hidden conjugate subgroups of affine groups, a special case of q-hedral groups for large q. We then adapt their algorithm to construct an algorithm for solving the hidden conjugate problem for q-hedral groups for large q and point out a difficulty in complexity analysis that involves certain exponential sums. We discuss certain bounds on these sums and present some computational data on their values to make a conjecture. For small q, Regev (2003) gave an efficient algorithm for solving the HSP for dihedral groups (q = 2) using an oracle that solves a certain subset sum problem (SSP). A crucial step of his algorithm relies on the probability that elements in a cyclic group ZN can be expressed as sums of random elements in the group. We generalize this problem to any finite group and prove the following theorem: for any finite group G and r ≥ 32 log2 |G| + 5, if r elements from G are chosen randomly, then the 2r possible sums (or products) of the r elements will cover all the elements in G with high probability. Also, by making a further generalization of the SSP, we show that Regev's algorithm can be generalized for q-hedral groups for any fixed q. We also study this generalized subset sum problem. In addition to the algorithm developing for small q, we give an efficient quantum algorithm for solving the coset problem and an efficient quantum algorithm for solving the hidden conjugate problem. Furthermore, we also give a survey of an algorithm for finding the largest normal subgroup in a hidden subgroup of any finite group, introduced by Hallgren et al. (2000) and provide a simplified and unified proof.We study quantum algorithms for the hidden subgroup problem (HSP). The HSP provides a unified framework for many important problems, including factoring integers, graph isomorphism problem, etc. It has been known that the problem for abelian groups can be efficiently solved. However, for non-abelian groups, it remains widely open. In this dissertation we study the problem for some specific non-abelian groups, called q-hedral groups. We start with a quantum algorithm, proposed by Moore et al. (2003), for finding some hidden conjugate subgroups of affine groups, a special case of q-hedral groups for large q. We then adapt their algorithm to construct an algorithm for solving the hidden conjugate problem for q-hedral groups for large q and point out a difficulty in complexity analysis that involves certain exponential sums. We discuss certain bounds on these sums and present some computational data on their values to make a conjecture. For small q, Regev (2003) gave an efficient algorithm for solving the HSP for dihedral groups (q = 2) using an oracle that solves a certain subset sum problem (SSP). A crucial step of his algorithm relies on the probability that elements in a cyclic group ZN can be expressed as sums of random elements in the group. We generalize this problem to any finite group and prove the following theorem: for any finite group G and r ≥ 32 log2 |G| + 5, if r elements from G are chosen randomly, then the 2r possible sums (or products) of the r elements will cover all the elements in G with high probability. Also, by making a further generalization of the SSP, we show that Regev's algorithm can be generalized for q-hedral groups for any fixed q. We also study this generalized subset sum problem. In addition to the algorithm developing for small q, we give an efficient quantum algorithm for solving the coset problem and an efficient quantum algorithm for solving the hidden conjugate problem. Furthermore, we also give a survey of an algorithm for finding the largest normal subgroup in a hidden subgroup of any finite group, introduced by Hallgren et al. (2000) and provide a simplified and unified proof.

Jan 1, 20050 citations

G=A\rtimes_{\varphi} \mathbb{Z}_{p^k}

, with

A

finite Abelian,

p

prime,

k\in \mathbb{N}

and the action of

\mathbb Z_{p^k}

is generated by the scalar automorphism

a\mapstoμa

, for some

μ\in\mathbb Z_{\operatorname{Exp}(A)}^\times

, where

\mathrm{Exp}(A)

is the exponent of

A

. Our algorithm is efficient when

A

has bounded generator rank and

\mathrm{Exp}(A)/p=\mathrm{polylog}(|G|)

. This includes the case

A=\mathbb{Z}_N

for

N\in\mathbb{N}

and

k=1

, studied by Bacon, Childs and van Dam (FOCS 2005), and

A=\mathbb{Z}_{q^r}

with

q

prime and

r\in \mathbb{N}

studied by van Dam and Dey (TQC 2014). Second, we give a polynomial-time quantum algorithm for finite quasi-Hamiltonian groups under a mild assumption on the input structure. Quasi-Hamiltonian groups are finite nilpotent groups with modular subgroup lattice, or equivalently the finite groups in which every subgroup is permutable. As far as we know, this is the first quantum algorithm to exploit the modularity of the subgroup lattice for solving the HSP. This extends, under the aforementioned structured input assumption, the quantum algorithm for Dedekind groups given by Hallgren, Russell, and Ta-Shma (SIAM J. Comput. 32, 2003).