Abstract
Simon’s problem is one of the most important problems demonstrating the power of quantum algorithms, as it greatly inspired the proposal of Shor’s algorithm. The generalized Simon’s problem is a natural extension of Simon’s problem and also a special hidden subgroup problem: Given a function \(f:\{0,1\}^n \rightarrow \{0,1\}^m\), it is promised that there exists a hidden subgroup \(S\le \mathbb {Z}_2^n\) of rank k such that for any \(x, y\in {\{0, 1\}}^n\), \(f(x) = f(y)\) iff \(x \oplus y \in S\). The goal of generalized Simon’s problem is to find the hidden subgroup S. In this paper, we present two key contributions. Firstly, we characterize the structure of the generalized Simon’s problem in distributed scenario and introduce a corresponding distributed quantum algorithm. Secondly, we refine the algorithm to ensure exactness due to the application of quantum amplitude amplification technique. Our algorithm offers exponential speedup compared to the distributed classical algorithm. When contrasted with the quantum algorithm for the generalized Simon’s problem, our algorithm’s oracle requires fewer qubits, thus making it easier to be physically implemented. Particularly, the exact distributed quantum algorithm we develop for the generalized Simon’s problem outperforms the best previously proposed distributed quantum algorithm for Simon’s problem in terms of generalizability and exactness.
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Acknowledgements
The authors are grateful to the anonymous referees for important comments and suggestions that help us improve the quality of the paper. This work is supported in part by the National Natural Science Foundation of China (Nos. 61876195, 61572532), the Natural Science Foundation of Guangdong Province of China (No. 2017B030311011), and the Shenzhen Science and Technology Program (Grant No. JCYJ20220818102003006).
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Fundação para a Ciência e Tecnologia, Instituto de Telecomunicações Research Unit, ref. UIDB/50008/2020, UIDP/50008/2020.
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HL designs the exact distributed algorithm for generalized Simon’s problem; DQ proposes the problem and gives the ideas and methods for designing algorithm, as well as check the details; LL checks the manuscript and gives improvement; PM further revises the manuscript with improvement.
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Proof of Lemma 3
Proof of Lemma 3
Lemma 3
Let \(\phi =2\arctan {\left( \sqrt{\frac{2^{n-t-r-k_l}}{3\cdot 2^{n-t-r-k_l}-4}}\right) }\), \(\varphi = \arccos {\left( \frac{2^{n-t-r-k_l-1}-1}{2^{n-t-r-k_l}-1}\right) }\), where \(r=|Y|-1\). Then
In line 6 of Algorithm 3, the measurement result z is obtained and satisfies \(z\in S_l^{\perp }{\setminus } \langle Y \rangle \) conditions with certainty.
Proof
From Eq. (39), we can write \(\mathcal {R}_{0}(\phi )\) as follows.
From the definitions of \(\mathcal {R}_{\mathcal {A}}(\varphi , Y)\), \(\Big \vert \Psi _{X}\Big \rangle \) and \(\Big \vert \Psi _{Y}\Big \rangle \), we have
Let \(\mathcal {U}(\mathcal {A}, \phi ) = -\mathcal {A}\mathcal {R}_{0}(\phi )\mathcal {A}^{\dagger }\), then based on Eq. (41), \(\mathcal {Q}\) can be written as
For \(\mathcal {U}(\mathcal {A}, \phi )\), we have
Since \(| \langle Y \rangle | = 2 ^ {r} \)and \(| S_l ^ {\perp } | = 2 ^ {n-t - k_l} \), according to the definitions of \(\Big \vert \Psi _ {X}\Big \rangle \) and \(\Big \vert \Psi _ {Y}\Big \rangle \), we have
Thus, we can obtain the following equations.
By making sure the resulting superposition \(\mathcal {Q}(\Big \vert \Psi _{X}\Big \rangle +\Big \vert \Psi _{Y}\Big \rangle )\) has inner product zero with \(\Big \vert \Psi _{Y}\Big \rangle \), then based on Eqs. (A7) and (A8), we can obtain the following equation.
Denote by
Then according to Eq. (A9), we have
Taking the square of b, we can further have
Arrange Eq. (A12) to get
From Eq. (A13), we can obtain
Since b is a real number, Eq. (A11) also needs to be a real number, and we can further obtain
Thus, from the above derivation, it follows that if \(\phi =2\arctan {\left( \sqrt{\frac{2^{n-t-r-k_l}}{3\cdot 2^{n-t-r-k_l}-4}}\right) }\), \(\varphi = \arccos {\left( \frac{2^{n-t-r-k_l-1}-1}{2^{n-t-r-k_l}-1}\right) }\), where \(r=|Y|-1\), we have \(\mathcal {Q}\Big \vert S_l^{\perp },0^{2^tm},S(T)\Big \rangle =\Big \vert \Psi _{X}\Big \rangle \), and \(z\in X={S_l^{\perp }}{\setminus } \langle Y \rangle \) is obtained in line 6 of Algorithm 3, after measuring the first register of the quantum state \(Q\Big \vert S_l^{\perp },0^{2^tm}, S(T)\Big \rangle \). \(\square \)
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Li, H., Qiu, D., Luo, L. et al. Exact distributed quantum algorithm for generalized Simon’s problem. Acta Informatica (2024). https://doi.org/10.1007/s00236-024-00455-x
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DOI: https://doi.org/10.1007/s00236-024-00455-x