In general, a quantum algorithm wants to avoid decoherence or perturbation, since such factors may cause errors in the algorithm. In this letter, we will supply the answer to the interesting question: can the factors seemingly harmful to a quantum algorithm(for example, perturbations) enhance the algorithm? We show that some perturbations to the generalized quantum search Hamiltonian can reduce the running time and enhance the success probability. We also provide the narrow bound to the perturbation which can be beneficial to quantum search. In addition, we show that the error induced by a perturbation on the Farhi and Gutmann Hamiltonian can be corrected by another perturbation.
In this paper, we study decoherence in Grover's quantum searching algorithm using a perturbative method. We assume that each two-state system (qubit) suffers ${\ensuremath{\sigma}}_{z}$ error with probability
p(0< p< 1) independently at every step in the algorithm. Considering an n-qubit density operator to which Grover's operation is applied M times, we expand it in powers of
2Mnp and derive its matrix element order by order under the $\stackrel{\ensuremath{\rightarrow}}{n}\ensuremath{\infty}$ limit. (In this large-n limit, we assume p is small enough, so that
2Mnp(> 0) can take any real positive value or
0.) This approach gives us an interpretation about creation of new modes caused by ${\ensuremath{\sigma}}_{z}$ error and an asymptotic form of an arbitrary-order correction. Calculating the matrix element up to the fifth-order term numerically, we investigate a region of
2Mnp (perturbative parameter), where the algorithm finds the correct item with a threshold of probability
Pth or more. It satisfies $2Mnp<(8/5)(1\ensuremath{-}{P}_{\mathrm{th}})$ around $2Mnp\ensuremath{\simeq}0$ and ${P}_{\mathrm{th}}\ensuremath{\simeq}1,$ and this linear relation is applied to a wide range of
Pth approximately. This observation is similar to a result obtained by Bernstein and Vazirani concerning accuracy of quantum gates for general algorithms. We cannot investigate a quantum-to-classical phase transition of the algorithm, because it is outside the reliable domain of our perturbation theory.
We examine the driving Hamiltonian in the analog analogue of Grover's algorithm by Farhi and Gutmann. For a quantum system with a given Hamiltonian
E∣w><w∣, we explicitly show that while the driving Hamiltonian
E∣s><s∣ optimally produces the state
∣w> from an initial state
∣s>, the driving Hamiltonian
E′∣s><s∣(E′=E) does not provide any speedup compared even with a classical computation.
Abstract When quantum computing becomes a wide-spread commercial reality, Quantum Search Algorithms (QSA) and especially Grover’s QSA will inevitably be one of their main applications, constituting their cornerstone. Most of the literature assumes that the quantum circuits are free from decoherence. Practically, decoherence will remain unavoidable as is the Gaussian noise of classic circuits imposed by the Brownian motion of electrons, hence it may have to be mitigated. In this contribution, we investigate the effect of quantum noise on the performance of QSAs, in terms of their success probability as a function of the database size to be searched, when decoherence is modelled by depolarizing channels’ deleterious effects imposed on the quantum gates. Moreover, we employ quantum error correction codes for limiting the effects of quantum noise and for correcting quantum flips. More specifically, we demonstrate that, when we search for a single solution in a database having 4096 entries using Grover’s QSA at an aggressive depolarizing probability of 10−3, the success probability of the search is 0.22 when no quantum coding is used, which is improved to 0.96 when Steane’s quantum error correction code is employed. Finally, apart from Steane’s code, the employment of Quantum Bose-Chaudhuri-Hocquenghem (QBCH) codes is also considered.
A major challenge in the implementation of quantum computers is mitigating the impact of undesired couplings with the environment that lead to decoherence.Here, we discuss an error-avoiding strategy that is based upon freedoms inherent in decomposing a quantum algorithm into fundamental gates.Although this approach is specific to a particular algorithm and a collective noise model, it does not the require complicated encodings or significant additional qubit resources of more general error-correcting codes.This paper also includes an overview of quantum computation, including a discussion of the quantum search algorithm.
Abstract In quantum computing, Grover's technique is extremely vulnerable to several kinds of quantum noise in practice, which can seriously impair its functionality. This study examines how the algorithm's success probabilities is affected by several types of noise, such as rotational error, thermal noise, Two-State Purity (TSP) error, decay and decoherence, and depolarization variables. The findings demonstrate that the algorithm can accomplish flawless amplification of the goal state with negligible mistakes in non-target states when it is executed without noise. The most notable decrease among the noise kinds is caused by decay and decoherence errors and depolarization factors, which lower the likelihood of correctly detecting the target state from 1.0 to roughly 0.885 and 0.968, respectively. Thermal noise, TSP error, and rotational error, on the other hand, have less severe impacts and result in lesser deviations in both target and non-target states. These results demonstrate how crucial quantum error correction and noise reduction techniques are to guaranteeing Grover's algorithm's scalability and dependability in noisy quantum environments. To fully utilize the algorithm's promise in practical applications on both present-day and next quantum technology, these issues must be mitigated.