Faster Database search in Quantum Computing

Quantum Database Search can do without Sorting

Sorting is a fundamental computational process, which facilitates subsequent searching of a database. It can be thought of as factorisation of the search process. The location of a desired item in a sorted database can be found by classical queries that inspect one letter of the label at a time. For an unsorted database, no such classical quick search algorithm is available. If the database permits quantum queries, however, then mere digitisation is sufficient for efficient search. Sorting becomes redundant with the quantum superposition of states. A quantum algorithm is written down which loc…

The Measurement Based Quantum Computing Search Algorithm is Faster than Grover's Algorithm

We find that the Measurement Based Quantum Computing (MBQC) search algorithm on an unsorted list is not the same as Grover's search algorithm (GSA).

Computing with a single qubit faster than the computation quantum speed limit

The possibility to save and process information in fundamentally indistinguishable states is the quantum mechanical resource that is not encountered in classical computing. I demonstrate that, if energy constraints are imposed, this resource can be used to accelerate information-processing without relying on entanglement or any other type of quantum correlations. In fact, there are computational problems that can be solved much faster, in comparison to currently used classical schemes, by saving intermediate information in nonorthogonal states of just a single qubit. There are also error corre…

容错前量子计算效用的证据的快速经典模拟

Fast classical simulation of evidence for the utility of quantum computing before fault tolerance

本文提出基于稀疏Pauli动力学的经典算法，高效模拟了IBM Eagle处理器127量子比特实验中的量子电路，模拟速度比量子模拟快数个数量级且与零噪声外推实验结果一致。

Experimental implementation of quantum algorithm for association rules mining

Recently, a quantum algorithm for a fundamentally important task in data mining, association rules mining (ARM), called qARM for short, has been proposed. Notably, qARM achieves significant speedup over its classical counterpart for implementing the main task of ARM, i.e., finding frequent itemsets from a transaction database. In this paper, we experimentally implement qARM on both real quantum computers and a quantum computing simulator via the IBM quantum computing platform. In the first place, we design quantum circuits of qARM for a 2$\times$2 transaction database (i.e., a transaction data…

Generalization of Grover's Algorithm to Multiobject Search in Quantum Computing, Part I: Continuous Time and Discrete Time

L. K. Grover's search algorithm in quantum computing gives an optimal, quadratic speedup in the search for a single object in a large unsorted database. In this paper, we generalize Grover's algorithm in a Hilbert-space framework for both continuous and discrete time cases that isolates its geometrical essence to the case where more than one object satisfies the search criterion.

Almost-Everywhere Superiority for Quantum Computing

Simon as extended by Brassard and Høyer shows that there are tasks on which polynomial-time quantum machines are exponentially faster than each classical machine infinitely often. The present paper shows that there are tasks on which polynomial-time quantum machines are exponentially faster than each classical machine almost everywhere.

Generalization of Grover's Algorithm to Multiobject Search in Quantum Computing, Part II: General Unitary Transformations

There are major advantages in a newer version of Grover's quantum algorithm utilizing a general unitary transformation in the search of a single object in a large unsorted database. In this paper, we generalize this algorithm to multiobject search. We show the techniques to achieve the reduction of the problem to one on an invariant subspace of dimension just equal to two.

Grover's Algorithm for Multiobject Search in Quantum Computing

L. K. Grover's search algorithm in quantum computing gives an optimal, square-root speedup in the search for a single object in a large unsorted database. In this paper, we expound Grover's algorithm in a Hilbert-space framework that isolates its geometrical essence, and we generalize it to the case where more than one object satisfies the search criterion.

Optimization of Partial Search

Quantum Grover search algorithm can find a target item in a database faster than any classical algorithm. One can trade accuracy for speed and find a part of the database (a block) containing the target item even faster, this is partial search. A partial search algorithm was recently suggested by Grover and Radhakrishnan. Here we optimize it. Efficiency of the search algorithm is measured by number of queries to the oracle. The author suggests new version of Grover-Radhakrishnan algorithm which uses minimal number of queries to the oracle. The algorithm can run on the same hardware which is us…

Group Theoretical Formulation of Quantum Partial Search Algorithm

Searching and sorting used as a subroutine in many important algorithms. Quantum algorithm can find a target item in a database faster than any classical algorithm. One can trade accuracy for speed and find a part of the database (a block) containing the target item even faster, this is partial search. An example is the following: exact address of the target item is given by a sequence of many bits, but we need to know only some of them. More generally partial search considers the following problem: a database is separated into several blocks. We want to find a block with the target item, not …

ZX-DB：基于ZX-演算的量子电路化简与重写图数据库

ZX-DB: A Graph Database for Quantum Circuit Simplification and Rewriting via the ZX-Calculus

针对量子电路编译优化需求，本文提出基于ZX-演算的图数据库系统ZX-DB，将重写规则编码为openCypher查询在Memgraph上执行，相较PyZX最高实现一个数量级的独立重写加速，开辟了数据库支撑量子计算流水线的新方向。

QCE'24 教程：量子退火——数据库优化的新兴探索

QCE'24 Tutorial: Quantum Annealing -- Emerging Exploration for Database Optimization

本教程系统介绍量子退火技术，并演示其在数据库优化中的应用，包括连接顺序优化、事务调度和虚拟机分配，旨在为数据库领域提供量子计算优化的理论与实践指导。

Faster classical Boson Sampling

Since its introduction Boson Sampling has been the subject of intense study in the world of quantum computing. The task is to sample independently from the set of all $n \times n$ submatrices built from possibly repeated rows of a larger $m \times n$ complex matrix according to a probability distribution related to the permanents of the submatrices. Experimental systems exploiting quantum photonic effects can in principle perform the task at great speed. In the framework of classical computing, Aaronson and Arkhipov (2011) showed that exact Boson Sampling problem cannot be solved in polynomial…

非结构化数据库的经典耗散搜索

Classical dissipative search of unstructured database

提出基于经典耗散球面自旋模型的非结构化数据库搜索物理实现，通过自旋耦合实现搜索，弛豫时间标度为O(M^a)且a<1/2，快于Grover搜索。