Quantum Query Complexity for Searching Multiple Marked States from an Unsorted Database

An important and usual sort of search problems is to find all marked states from an unsorted database with a large number of states. Grover＇s original quantum search algorithm is for finding single marked state with uncertainty, and it has been generalized to the case of multiple marked states, as well as been modified to find single marked state with certainty. However, the query complexity for finding all multiple marked states has not been addressed. We use a generalized Long＇s algorithm with high precision to solve such a problem. We calculate the approximate query complexity, which increases with the number of marked states and with the precision that we demand. In the end we introduce an algorithm for the problem on a ＂duality computer＂ and show its advantage over other algorithms.     

Experimental quantum deletion in an NMR quantum information processor

We report an NMR experimental realization of a rapid quantum deletion algorithm that deletes marked states in an unsorted database.Unlike classical deletion,where search and deletion are equivalent,quantum deletion can be implemented with only a single query,which achieves exponential speed-up compared to the optimal classical analog.In the experimental realization,the GRAPE algorithm was used to obtain an optimized NMR pulse sequence,and the efficient method of maximum-likelihood has been used to reconstruct the experimental output state.     

Robust Quantum Search with Uncertain Number of Target States

The quantum search algorithm is one of the milestones of quantum algorithms. Compared with classical algorithms, it shows quadratic speed-up when searching marked states in an unsorted database. However, the success rates of quantum search algorithms are sensitive to the number of marked states. In this paper, we study the relation between the success rate and the number of iterations in a quantum search algorithm of given λ=M/N, where M is the number of marked state and N is the number of items in the dataset. We develop a robust quantum search algorithm based on Grover–Long algorithm with some uncertainty in the number of marked states. The proposed algorithm has the same query complexity ON as the Grover’s algorithm, and shows high tolerance of the uncertainty in the ratio M/N. In particular, for a database with an uncertainty in the ratio M±MN, our algorithm will find the target states with a success rate no less than 96%.     

An Exact Quantum Search Algorithm with Arbitrary Database

In standard Grover’s algorithm for quantum searching, the probability of finding a marked state is not exactly 1, and some modified versions of Grover’s algorithm that search a marked state from an evenly distributed database with full successful rate have been presented. In this article, we present a generalized quantum search algorithm that searches M marked states from an arbitrary distributed N-item quantum database with a zero theoretical failure rate, where N is not necessary to be the power of 2. We analyze the general properties of our search algorithm, we find that our algorithm has periodicity with a period of 2J + 1, and it is effective with certainty for J + (2J + 1)m times of iteration, where m is an arbitrary nonnegative number.     

混合态数据库的Grover算法数学形式及其搜索成功率

Grover提出了容量为N的数据库量子搜索法.只需进行O(平方根N)次迭代就能以几乎为1的概率实现对目标的搜索.本文将文献[1]的Grover搜索法推广到混合态情形,给出了一个基于混合态的Grover搜索法,并分析了该搜索法成功的概率上界.进一步发现搜索法成功的概率完全依赖于所使用的初态(混合态).该结论为了解量子噪声对Grover搜索法的影响提供一定的理论依据.最后通过例子说明了如何实施基于混合态的Grover搜索法.     

Quantum walk search algorithm for multi-objective searching with iteration auto-controlling on hypercube

Shenvi et al. have proposed a quantum algorithm based on quantum walking called Shenvi-Kempe-Whaley (SKW) algorithm, but this search algorithm can only search one target state and use a specific search target state vector. Therefore, when there are more than two target nodes in the search space, the algorithm has certain limitations. Even though a multi-objective SKW search algorithm was proposed later, when the number of target nodes is more than two, the SKW search algorithm cannot be mapped to the same quotient graph. In addition, the calculation of the optimal target state depends on the number of target states m. In previous studies, quantum computing and testing algorithms were used to solve this problem. But these solutions require more Oracle calls and cannot get a high accuracy rate. Therefore, to solve the above problems, we improve the multi-target quantum walk search algorithm, and construct a controllable quantum walk search algorithm under the condition of unknown number of target states. By dividing the Hilbert space into multiple subspaces, the accuracy of the search algorithm is improved from p_c=(1/2)-O(1/n) to p_c=1-O(1/n). And by adding detection gate phase, the algorithm can stop when the amplitude of the target state becomes the maximum for the first time, and the algorithm can always maintain the optimal number of iterations, so as to reduce the number of unnecessary iterations in the algorithm process and make the number of iterations reach $ t_{\rm f}=(\pi /2)\sqrt{2^{n-2}} $.     

Quantum communication complexity of establishing a shared reference frame

We discuss the aligning of spatial reference frames from a quantum communication complexity perspective. This enables us to analyze multiple rounds of communication and give several simple examples demonstrating tradeoffs between the number of rounds and the type of communication. Using a distributed variant of a quantum computational algorithm, we give an explicit protocol for aligning spatial axes via the exchange of spin-1/2 particles which makes no use of either exchanged entangled states, or of joint measurements. This protocol achieves a worst-case fidelity for the problem of "direction finding" that is asymptotically equivalent to the optimal average case fidelity achievable via a single forward communication of entangled states.     

基于散射量子行走的完全图上结构异常搜索算法

完全图K_N 上某个顶点连接到图G将破坏其对称性. 为加速定位这类结构异常, 基于散射量子行走模型设计搜索算法, 首先给出了算法酉算子的定义, 在此基础上利用完全图的对称性, 将算法的搜索空间限定为一个低维的坍缩图空间. 以G为一个顶点的情况为例, 利用硬币量子行走模型上的研究结论简化了坍缩图空间中酉算子的计算, 并借助矩阵扰动理论分析算法演化过程. 针对星图S_N 上结构异常的研究表明, 以星图中心节点为界将整个图分为左右两个部分, 当且仅当两部分在N→∞时具有相同的特征值, 搜索算法可以获得量子加速. 本文说明星图上的分析方法和结论可以推广至完全图的坍缩图上. 基于此, 本文证明无论完全图连接的图G结构如何, 搜索算法均可在O(√N) 时间内定位到目标顶点, 成功概率为1-O(1√N), 即量子行走搜索该类异常与经典搜索相比有二次加速.     

Arbitrary Phase Rotation of the Marked State Cannot Be Used for Grover's Quantum Search Algorithm

A misunderstanding that an arbitrary phase rotation of the marked state together with the inversion about average operation can be used to construct a (less efficient) quantum search algorithm is cleared. The π rotation of the phase of the marked state is not only the choice for efficiency, but also vital in Grover's quantum search algorithm. The results also show that Grover's quantum search algorithm is robust.     

First experimental demonstration of an exact quantum search algorithm in nuclear magnetic resonance system

The success probability of searching an objective item from an unsorted database using standard Grover's algorithm is usually not exactly 1. It is exactly 1 only when it is used to find the target state from a database with four items. Exact search is always important in theoretical and practical applications. The failure rate of Grover's algorithm becomes big when the database is small, and this hinders the use of the commonly used divide-and-verify strategy. Even for large database, the failure rate becomes considerably large when there are many marked items. This has put a serious limitation on the usability of the Grover's algorithm. An important improved version of the Grover's algorithm, also known as the improved Grover algorithm, solves this problem. The improved Grover algorithm searches arbitrary number of target states from an unsorted database with full success rate. Here, we give the first experimental realization of the improved Grover algorithm, which finds a marked state with certainty, in a nuclear magnetic resonance system. The optimal control theory is used to obtain an optimized control sequence. The experimental results agree well with the theoretical predictions.     

Implementation of quantum search scheme by adiabatic passage in a cavity--laser--atom system

This paper proposes a scheme for implementing the adiabatic quantum search algorithm of different marked items in an unsorted list of N items with atoms in a cavity driven by lasers. N identical three-level atoms are trapped in a single-mode cavity. Each atom is driven by a set of three pulsed laser fields. In each atom, the same level represents a database entry. Two of the atoms are marked differently. The marked atom has an energy gap between its two ground states. The two different marked states can be sought out respectively starting from an initial entangled state by controlling the ratio of three pulse amplitudes. Moreover, the mechanism, based on adiabatic passage, constitutes a decoherence-free method in the sense that spontaneous emission and cavity damping are avoided since the dynamics follows the dark state. Furthermore, this paper extends the algorithm with m (m>2) atoms marked in an ideal situation. Any different marked state can be sought out.     

Direct Observation of Dissipation in Dynamical Search Algorithm using Transmon Qubits

Following recent work [Fortschritte der Physik 66, 1700080 (2018)], the dissipation effect of the dynamical quantum search algorithm (DQSA) is investigated. Such an algorithm is realized with the interaction of multi superconducting transmon qubits inside a 3D bus cavity. The dissipation of such system is caused by managing the sensitivity to charge noise via tuning the qubit frequency by employing Josephson energy. The probabilities of marked and unmarked states for the present algorithm have been calculated analytically and numerically. Such probabilities of marked states are sensitive to any change in the dissipation parameter. A deficiency causes the dissipation for the marked states, and that deficiency is added to the unmarked states. It is interesting to mention that one of the datasets at large dissipation rates gives an observation of the marked states probabilities which is related to the decoherence free subspace. It is predicted that the algorithm can be successfully implemented in the current experiments.     

On Models of Nonlinear Evolution Paths in Adiabatic Quantum Algorithms

In this paper,we study two different nonlinear interpolating paths in adiabatic evolution algorithms for solving a particular class of quantum search problems where both the initial and final Hamiltonian are one-dimensional projector Hamiltonians on the corresponding ground state.If the overlap between the initial state and final state of the quantum system is not equal to zero,both of these models can provide a constant time speedup over the usual adiabatic algorithms by increasing some another corresponding "complexity".But when the initial state has a zero overlap with the solution state in the problem,the second model leads to an infinite time complexity of the algorithm for whatever interpolating functions being applied while the first one can still provide a constant running time.However,inspired by a related reference,a variant of the first model can be constructed which also fails for the problem when the overlap is exactly equal to zero if we want to make up the "intrinsic" fault of the second model - an increase in energy.Two concrete theorems are given to serve as explanations why neither of these two models can improve the usual adiabatic evolution algorithms for the phenomenon above.These just tell us what should be noted when using certain nonlinear evolution paths in adiabatic quantum algorithms for some special kind of problems.     

Entropy of a needle in a haystack

In a quantum search algorithm, the initial state which is a linear superposition of all possible basis states is a separable state. At each iteration, the state becomes more and more entangled until eventually it disentangles and reverts to a separable state consisting of the marked state. It is therefore interesting to study how entanglement changes in a Grover search algorithm.     

General Quantum Meet-in-the-Middle Search Algorithm Based on Target Solution of Fixed Weight

Similar to the classical meet-in-the-middle algorithm, the storage and computation complexity are the key factors that decide the efficiency of the quantum meet-in-the-middle algorithm. Aiming at the target vector of fixed weight, based on the quantum meet-in-the-middle algorithm, the algorithm for searching all n-product vectors with the same weight is presented, whose complexity is better than the exhaustive search algorithm. And the algorithm can reduce the storage complexity of the quantum meet-in-the-middle search algorithm. Then based on the algorithm and the knapsack vector of the Chor-Rivest public-key crypto of fixed weight d, we present a general quantum meet-in-the-middle search algorithm based on the target solution of fixed weight, whose computational complexity is ∑_j^d=(0(√C_n-k+1^d-j)+O(C_k^jlogC_k^j)) with ∑_i=0^dC_kⁱ memory cost. And the optimal value of k is given. Compared to the quantum meet-in-the-middle search algorithm for knapsack problem and the quantum algorithm for searching a target solution of fixed weight, the computational complexity of the algorithm is lower. And its storage complexity is smaller than the quantum meet-in-the-middle-algorithm.     

Improved locality-sensitive hashing method for the approximate nearest neighbor problem

In recent years, the nearest neighbor search(NNS) problem has been widely used in various interesting applications.Locality-sensitive hashing(LSH), a popular algorithm for the approximate nearest neighbor problem, is proved to be an efficient method to solve the NNS problem in the high-dimensional and large-scale databases. Based on the scheme of p-stable LSH, this paper introduces a novel improvement algorithm called randomness-based locality-sensitive hashing(RLSH) based on p-stable LSH. Our proposed algorithm modifies the query strategy that it randomly selects a certain hash table to project the query point instead of mapping the query point into all hash tables in the period of the nearest neighbor query and reconstructs the candidate points for finding the nearest neighbors. This improvement strategy ensures that RLSH spends less time searching for the nearest neighbors than the p-stable LSH algorithm to keep a high recall. Besides, this strategy is proved to promote the diversity of the candidate points even with fewer hash tables. Experiments are executed on the synthetic dataset and open dataset. The results show that our method can cost less time consumption and less space requirements than the p-stable LSH while balancing the same recall.     

Design of quantum VQ iteration and quantum VQ encoding algorithm taking O（√N） steps for data compression

Vector quantization (VQ) is an important data compression method. The key of the encoding of VQ is to find the closest vector among N vectors for a feature vector. Many classical linear search algorithms take $O(N)$ steps of distance computing between two vectors. The quantum VQ iteration and corresponding quantum VQ encoding algorithm that takes $O(\sqrt N )$ steps are presented in this paper. The unitary operation of distance computing can be performed on a number of vectors simultaneously because the quantum state exists in a superposition of states. The quantum VQ iteration comprises three oracles, by contrast many quantum algorithms have only one oracle, such as Shor's factorization algorithm and Grover's algorithm. Entanglement state is generated and used, by contrast the state in Grover's algorithm is not an entanglement state. The quantum VQ iteration is a rotation over subspace, by contrast the Grover iteration is a rotation over global space. The quantum VQ iteration extends the Grover iteration to the more complex search that requires more oracles. The method of the quantum VQ iteration is universal.     

On the Role of Prior Probability in Adiabatic Quantum Algorithms

In this paper, we study the role of prior probability on the efficiency of quantum local adiabatic search algorithm. The following aspects for prior probability are found here: firstly, only the probabilities of marked states affect the running time of the adiabatic evolution; secondly, the prior probability can be used for improving the efficiency of the adiabatic algorithm; thirdly, like the usual quantum adiabatic evolution, the running time for the case of multiple solution states where the number of marked elements are smaller enough than the size of the set assigned that contains them can be significantly bigger than that of the case where the assigned set only contains all the marked states.     

The Quantum Search Algorithms for All Solutions

Two quantum search algorithms are proposed for known and unknown number of solutions. The first algorithm begins with an arbitrary rotation phase Grover search algorithm by recursive equations, then a sub-algorithm (G _α algorithm) and the corresponding quantum circuits are designed, the probability of success and expected number of iterations of the sub-algorithm to find a solution are analyzed. Based on these results, we design the whole algorithm and estimate the expected number of iterations to search all solutions. The design of the second algorithm follows the same steps. We firstly study a quantum counting algorithm, then design a sub-algorithm (QCG algorithm), and analyze the probability of success and the expected number of iterations to find a solution. Finally the whole algorithm for all solutions is designed and analyzed. The analysis results show that these two algorithms find all solutions in the expected times of $O(t\sqrt{N})$ (t is a number of solutions and N is a total of states).     

NMR analogue of the generalized Grover‘s algorithm of multiple marked states and its application

The generalized Grover's algorithm for the case in which there are multiple marked states is demonstrated on a nuclear magnetic resonance (NMR) quantum computer. The Walsh－Hadamard transform and the phase inversion are all replaced. NMR analogues of Einstein－Podolsky－Rosen states (pseudo-EPR states) are synthesized using the above algorithm.