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arXiv:quant-ph/9602018

Effects of Loss and Decoherence on a Simple Quantum Computer

Isaac L. Chuang, Raymond Laflamme, J.M. Zárate Paz

Published Feb 27, 1996• 5 citations
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Abstract

We investigate the impact of loss (amplitude damping) and decoherence (phase damping) on the performance of a simple quantum computer which solves the one-bit Deutsch problem. The components of this machine are beamsplitters and nonlinear optical Kerr cells, but errors primarily originate from the latter. We develop models to describe the effect of these errors on a quantum optical Fredkin gate. The results are used to analyze possible error correction strategies in a complete quantum computer. We find that errors due to loss can be avoided perfectly by appropriate design techniques, while decoherence can be partially dealt with using projective error correction.

DOI
10.48550/arxiv.quant-ph/9602018

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We investigate the impact of loss (amplitude damping) and decoherence (phase damping) on the performance of a simple quantum computer which solves the one-bit Deutsch problem. The components of this machine are beamsplitters and nonlinear optical Kerr cells, but errors primarily originate from the latter. We develop models to describe the effect of these errors on a quantum optical Fredkin gate. The results are used to analyze possible error correction strategies in a complete quantum computer. We find that errors due to loss can be avoided perfectly by appropriate design techniques, while decoherence can be partially dealt with using projective error correction.
This article presents a comprehensive study of the impact of decoherence on the average correlation for pure quantum states. We explore two primary mechanisms of decoherence: phase damping and amplitude damping, each having distinct effects on quantum systems. Phase damping, which describes the loss of quantum coherence without energy loss, primarily affects the phase relationships between the components of a quantum system while amplitude damping involves energy dissipation and also affects the state's occupation probabilities. We show that the average correlation follows a predictable decaying pattern in both scenarios. Our analysis can be understood in the context of quantum computing, by focusing on how phase damping influences the entanglement and correlation between qubits, key factors in quantum computational efficiency and error correction protocols.
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Quantum error correction is a key challenge for the development of practical quantum computers, a direction in which significant experimental progress has been made in recent years. In solid-state qubits, one of the leading information loss mechanisms is dephasing, usually modeled by phase-flip errors. Here, we introduce quasistatic phase damping, a more subtle error model which describes the effect of Larmor frequency fluctuations due to 1/f1/f1/f noise. We show how this model is different from a simple phase-flip error model, in terms of multicycle error correction. Considering the surface code, we provide numerical evidence for an error threshold, in the presence of quasistatic phase damping and readout errors. We discuss the implications of our results for spin qubits and superconducting qubits.
The Hybrid Quantum Neural Networks (HyQNNs) hold great promise for various quantum machine learning tasks, but their performance can be significantly affected by the quantum noise in NISQ devices. In this paper, we comprehensively analyze the influence of different quantum noise gates, including Phase Flip, Bit Flip, Phase Damping, Amplitude Damping, and the Depolarizing Channel, on the performance of HyQNNs. Our results reveal distinct and significant effects on HyQNNs training and validation accuracies across different probabilities of noise. For instance, the Phase Flip gate introduces phase errors, and we observe that HyQNNs exhibit resilience at higher probability (p = 1.0), adapting effectively to consistent noise patterns, whereas at intermediate probabilities, the performance declines. Bit Flip errors, represented by the Pauli X gate, impact HyQNNs in a similar way to that Phase Flip error gate. The HyQNNs, can adapt such kind of errors at maximum probability (p = 1.0). Unlike Phase and Bit Flip error gates, Phase Damping and Amplitude Damping gates disrupt quantum information, with HyQNNs demonstrating resilience at lower probabilities but facing challenges at higher probabilities. Amplitude Damping, in particular, poses efficiency and accuracy issues at higher probabilities, however with lowest probability (p =0.1),it has the least effect, i.e., HyQNNs, although not very effectively, but still tends to learn. The Depolarizing Channel proves most detrimental to HyQNNs performance, with limited or no training improvements. There was no training potential observed regardless of the probability of this noise gate. These findings underscore the critical need for advanced quantum error mitigation and resilience strategies in the design and training of HyQNNs, especially in environments prone to depolarizing noise. This paper quantitatively investigate that understanding the impact of quantum noise gates is essential for harnessing the full potential of quantum computing in practical applications.
Quantum technologies have shown immeasurable potential to effectively solve several information processing tasks such as prime number factorization, unstructured database search or complex macromolecule simulation. As a result of such capability to solve certain problems that are not classically tractable, quantum machines have the potential revolutionize the modern world via applications such as drug design, process optimization, unbreakable communications or machine learning. However, quantum information is prone to suffer from errors caused by the so-called decoherence, which describes the loss in coherence of quantum states associated to their interactions with the surrounding environment. This decoherence phenomenon is present in every quantum information task, be it transmission, processing or even storage of quantum information. Consequently, the protection of quantum information via quantum error correction codes (QECC) is of paramount importance to construct fully operational quantum computers. Understanding environmental decoherence processes and the way they are modeled is fundamental in order to construct effective error correction methods capable of protecting quantum information. In this thesis, the nature of decoherence is studied and mathematically modelled; and QECCs are designed and optimized so that they exhibit better error correction capabilities.