arXiv subjects

Ligang Xiao

Publications and source records attributed to Ligang Xiao.

7 recordsLinked to original sources

arXiv2026

Distributed Quantum Discrete Logarithm Algorithm

Solving the discrete logarithm problem (DLP) with quantum computers is a fundamental task with important implications. Beyond Shor's algorithm, many researchers have proposed alternative solutions in recent years. However, due to current hardware limitations, the scale of DLP instances that can be addressed by quantum computers remains insufficient. To overcome this limitation, we propose a distributed quantum discrete logarithm algorithm that reduces the required quantum register size for solving DLPs. Specifically, we design a distributed quantum algorithm to determine whether the solution is contained in a given set. Based on this procedure, our method solves DLPs by identifying the intersection of sets containing the solution. Compared with Shor's original algorithm, our approach reduces the register size and can improve the success probability, while requiring no quantum communication.

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arXiv2025

Universal Error Correction for Distributed Quantum Computing

In distributed quantum computing, the final solution of a problem is usually achieved by catenating these partial solutions resulted from different computing nodes, but intolerable errors likely yield in this catenation process. In this paper, we propose a universal error correction scheme to reduce errors and obtain effective solutions. Then, we apply this error correction scheme to designing a distributed phase estimation algorithm that presents a basic tool for studying distributed Shor's algorithm and distributed discrete logarithm algorithm as well as other distributed quantum algorithms. Our method may provide a universal strategy of error correction for a kind of distributed quantum computing.

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arXiv2024

Distributed Phase Estimation Algorithm and Distributed Shor's Algorithm

Shor's algorithm is one of the most significant quantum algorithms. Shor's algorithm can factor large integers with a certain success probability in polynomial time. However, Shor's algorithm requires an unbearable amount of qubits in the NISQ (Noisy Intermediate-scale Quantum) era. To reduce the resources required for Shor's algorithm, in this paper we first propose a new distributed phase estimation algorithm. Our distributed phase estimation algorithm does not require quantum communication and it reduces the number of qubits of a single node compared to the traditional phase estimation algorithm (non-iterative version). Then we apply our distributed phase estimation algorithm to form a distributed order-finding algorithm for Shor's algorithm. Compared with the traditional Shor's algorithm (non-iterative version), the maximum number of qubits required by a single node of our dristributed order-finding algorithm is reduced by $(2-\dfrac{2}{k})L-\log_2k-O(1)$ when factoring an $L$-bit integer ($k$ is the number of compute nodes). The communication complexity of our distributed order-finding algorithm is $O(kL)$.

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arXiv2022

Distributed Grover's algorithm

Let Boolean function $f:\{0,1\}^n\longrightarrow \{0,1\}$ where $|\{x\in\{0,1\}^n| f(x)=1\}|=a\geq 1$. To search for an $x\in\{0,1\}^n$ with $f(x)=1$, by Grover's algorithm we can get the objective with query times $\lfloor \fracπ{4}\sqrt{\frac{2^n}{a}} \rfloor$. In this paper, we propose a distributed Grover's algorithm for computing $f$ with lower query times and smaller number of input bits. More exactly, for any $k$ with $n>k\geq 1$, we can decompose $f$ into $2^k$ subfunctions, each which has $n-k$ input bits, and then the objective can be found out by computing these subfunctions with query times at most $\sum_{i=1}^{r_i} \lfloor \fracπ{4}\sqrt{\frac{2^{n-k}}{b_i}} \rfloor+\lceil\sqrt{2^{n-k}}\rceil+2t_a+1$ for some $1\leq b_i\leq a$ and $r_i\leq 2t_a+1$, where $t_a=\lceil 2π\sqrt{a}+11\rceil$. In particular, if $a=1$, then our distributed Grover's algorithm only needs $\lfloor \fracπ{4}\sqrt{2^{n-k}} \rfloor$ queries, versus $\lfloor \fracπ{4}\sqrt{2^{n}} \rfloor$ queries of Grover's algorithm. %When $n$ qubits belong to middle scale but still are a bit difficult to be processed in practice, $n-k$ qubits are likely feasible for appropriate $k$ in physical realizability. Finally, we propose an efficient algorithm of constructing quantum circuits for realizing the oracle corresponding to any Boolean function with conjunctive normal form (CNF).

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arXiv2022

Distributed Shor's algorithm

Shor's algorithm is one of the most important quantum algorithm proposed by Peter Shor [Proceedings of the 35th Annual Symposium on Foundations of Computer Science, 1994, pp. 124--134]. Shor's algorithm can factor a large integer with certain probability and costs polynomial time in the length of the input integer. The key step of Shor's algorithm is the order-finding algorithm. Specifically, given an $L$-bit integer $N$, we first randomly pick an integer $a$ with $gcd(a,N)=1$, the order of $a$ modulo $N$ is the smallest positive integer $r$ such that $a^r\equiv 1 (\bmod N)$. The order-finding algorithm in Shor's algorithm first uses quantum operations to obtain an estimation of $\dfrac{s}{r}$ for some $s\in\{0, 1, \cdots, r-1\}$, then $r$ is obtained by means of classical algorithms. In this paper, we propose a distributed Shor's algorithm. The difference between our distributed algorithm and the traditional order-finding algorithm is that we use two quantum computers separately to estimate partial bits of $\dfrac{s}{r}$ for some $s\in\{0, 1, \cdots, r-1\}$. To ensure their measuring results correspond to the same $\dfrac{s}{r}$, we need employ quantum teleportation. We integrate the measuring results via classical post-processing. After that, we get an estimation of $\dfrac{s}{r}$ with high precision. Compared with the traditional Shor's algorithm that uses multiple controlling qubits, our algorithm reduces nearly $\dfrac{L}{2}$ qubits and reduces the circuit depth of each computer.

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arXiv2022

Distributed quantum algorithm for Simon's problem

Limited by today's physical devices, quantum circuits are usually noisy and difficult to be designed deeply. The novel computing architecture of distributed quantum computing is expected to reduce the noise and depth of quantum circuits. In this paper, we study the Simon's problem in distributed scenarios and design a distributed quantum algorithm to solve the problem. The algorithm proposed by us has the advantage of exponential acceleration compared with the classical distributed computing, and has the advantage of square acceleration compared with the best distributed quantum algorithm proposed before. In particular, the previous distributed quantum algorithm for Simon's problem can not be extended to the case of more than {\it two computing nodes} (i.e. two subproblems), but our distributed quantum algorithm can be extended to the case of {\it multiple computing nodes} (i.e. multiple subproblems) as well.

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arXiv2021

State complexity of one-way quantum finite automata together with classical states

One-way quantum finite automata together with classical states (1QFAC) proposed in [Journal of Computer and System Sciences 81(2) (2015) 359--375] is a new one-way quantum finite automata (1QFA) model that integrates quantum finite automata (QFA) and deterministic finite automata (DFA). This model uses classical states to control the evolution and measurement of quantum states. As a quantum-classical hybrid model, 1QFAC recognize all regular languages. It was shown that the state complexity of 1QFAC for some languages is essentially superior to that of DFA and other 1QFA. In this paper, our goal is to clarify state complexity problems for 1QFAC. We obtain the following results: (1) We optimize the bound given by Qiu et al. that characterizes the relationship between quantum basis state number and classical state number of 1QFAC as well as the state number of its corresponding minimal DFA for recognizing any given regular language. (2) We give an upper bound showing that how many classical states are needed if the quantum basis states of 1QFAC are reduced without changing its recognition ability. (3) We give a lower bound of the classical state number of 1QFAC for recognizing any given regular language, and the lower bound is exact if the given language is finite. (4) We show that 1QFAC are exponentially more succinct than DFA and probabilistic finite automata (PFA) for recognizing some regular languages that can not be recognized by measure-once 1QFA (MO-1QFA), measure-many 1QFA (MM-1QFA) or multi-letter 1QFA. (5) We reveal essential relationships between 1QFAC, MO-1QFA and multi-letter 1QFA, and induce a result regarding a quantitative relationship between the state number of multi-letter 1QFA and DFA.

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