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arXiv:2406.09450

Grover's algorithm on two-way quantum computer

Grzegorz Czelusta, Verma, Dev Rishi, Wanjalkar, Govind

Published Jun 12, 2024• 0 citations
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Abstract

Two-way quantum computing (2WQC) represents a novel approach to quantum computing that introduces a CPT version of state preparation. This paper analyses the influence of this approach on Grover's algorithm and compares the behaviour of typical Grover and its 2WQC version in the presence of noise in the system. Our findings indicate that, in an ideal scenario without noise, the 2WQC Grover algorithm exhibits a constant complexity of $\mathcal{O}(1)$. In the presence of noise, the 2WQC Grover algorithm demonstrates greater resilience to different noise models than the standard Grover's algorithm.

DOI
10.48550/arxiv.2406.09450

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Two-way quantum computing (2WQC) represents a novel approach to quantum computing that introduces a CPT version of state preparation. This paper analyses the influence of this approach on Grover's algorithm and compares the behaviour of typical Grover and its 2WQC version in the presence of noise in the system. Our findings indicate that, in an ideal scenario without noise, the 2WQC Grover algorithm exhibits a constant complexity of O(1)\mathcal{O}(1)O(1). In the presence of noise, the 2WQC Grover algorithm demonstrates greater resilience to different noise models than the standard Grover's algorithm.
Two-way quantum computers (2WQC) are proposed extension of standard 1WQC: adding conjugated state preparation operation ⟨0∣\langle 0|⟨0∣ similar to postselection $|0\ra \langle 0|$, by performing a process which from perspective of CPT symmetry is the original state preparation process, for example by reversing EM impulses used for state preparation. As there were concerns that this extension might violate no-cloning theorem for example for attacks on quantum cryptographic protocols like BB84, here we extend the original proof to show this theorem still holds for 2WQC and postselection.
In order to understand the bounds of utilization of Grover's search algorithm for large unstructured data in the presence of quantum computer noise, we undertake a series of simulations by inflicting various types of noise, modeled by the IBM qiskit. We apply three forms of Grover's algorithm: (i) the standard one, with 4--10 qubits; (ii) a recently published modified Grover's algorithm, set to reduce the circuit depth; and (iii) the algorithms in (i) and (ii) with multicontrol Toffoli's gates modified by the addition of an ancilla qubit. Based on these simulations, we find the upper bound of noise for these cases, establish its dependence on the quantum depth of the circuit, and provide comparison among them. By extrapolation of the fitted thresholds, we predict what would be the typical gate error bounds when applying Grover's algorithms for the search of data in a data set as large as 32 000.
In this paper we will analyse two quantum algorithms that sparked interest in the potential of quantum computers. The first is Lov Grover's algorithm which may be used to conduct a type of database search. The second is Peter Shor's algorithm which may be used to factor large numbers and provides an exponential speed up over the best current classical algorithms. In the context of these two algorithms we will discuss the benefits and weaknesses of quantum computation. We will show that in exchange for a quantum computer's greater speed we must accept an inherent level of uncertainty in our results.
Quantum computing represents the leading edge of computational technology, leveraging the principles of quantum mechanics to execute targeted computations much faster than classical computers. In contrast to classical bits, which are limited to representing either 0 or 1, qubits, or quantum bits, exhibit the extraordinary property of superposition. This distinctive characteristic enables qubits to simultaneously occupy multiple states, empowering quantum computers to explore numerous potential solutions to a problem concurrently. This feature makes quantum computing particularly potent for specific tasks. Recent research endeavors have been sparked by the potential of advanced quantum computing technology, leading to the creation of simulations of quantum computers using classical hardware. Grover's quantum search algorithm serves as a notable illustration of quantum computing application, enabling quantum computers to conduct a database search within an unsorted array with a quadratic speedup in time efficiency compared to classical computers. This document presents the quantum Grover search algorithm and its application through 5-qubit quantum circuits, as well as a design framework to simplify the creation of an oracle for a greater number of qubits.
We study imperfection effects on time evolution of Grover's algorithm on quantum computer. We introduce an effective two-level model with dissipation and stochasty, which is based upon the idea that ideal Grover's algorithm operates in 2 dimensional Hilbert space. The simulation results of both are compared and it is found that they are in good agreement for appropriately tuned parameters. It turns out that the main features of Grover's algorithm with imperfections can be understood in terms of two basic mechanisms, i.e., a diffusion of probability density into full Hilbert space and a stochastic rotation within the original 2 dimensional Hilbert space.