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arXiv:quant-ph/0307165 · Lecture notes in physics

Measurement and Information Extraction in Complex Dynamics Quantum Computation

Giulio Casati, Simone Montangero

Published Dec 9, 2003• 0 citations
arXivHTMLPDF
DOI
10.1007/978-3-540-40968-7_24

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Giulio Casati, Simone Montangero

Quantum Information processing has several different applications: some of them can be performed controlling only few qubits simultaneously (e.g. quantum teleportation or quantum cryptography) [1]. Usually, the transmission of large amount of information is performed repeating several times the scheme implemented for few qubits. However, to exploit the advantages of quantum computation, the simultaneous control of many qubits is unavoidable [2]. This situation increases the experimental difficulties of quantum computing: maintaining quantum coherence in a large quantum system is a difficult task. Indeed a quantum computer is a many-body complex system and decoherence, due to the interaction with the external world, will eventually corrupt any quantum computation. Moreover, internal static imperfections can lead to quantum chaos in the quantum register thus destroying computer operability [3]. Indeed, as it has been shown in [4], a critical imperfection strength exists above which the quantum register thermalizes and quantum computation becomes impossible. We showed such effects on a quantum computer performing an efficient algorithm

•Jan 1, 2003•0 citations
We present experimental results on the measurement of fidelity decay under contrasting system dynamics using a nuclear magnetic resonance quantum information processor. The measurements were performed by implementing a scalable circuit in the model of deterministic quantum computation with only one quantum bit. The results show measurable differences between regular and complex behavior and for complex dynamics are faithful to the expected theoretical decay rate. Moreover, we illustrate how the experimental method can be seen as an efficient way for either extracting coarse-grained information about the dynamics of a large system or measuring the decoherence rate from engineered environments.
Quantum measurement protocols are inherently complex, requiring careful consideration of the measurement space to maximize information gained. Traditional approaches often assume a fixed measurement space, limiting the potential for optimization. This paper introduces Adaptive Topology of Quantum Measurement Spaces (ATQM), a novel protocol that dynamically reshapes the quantum state based on machine learning, leading to significant improvements in information extraction from quantum measurements. This adaptive approach offers a more intelligent and flexible framework for measurement design, addressing limitations of existing protocols and opening new avenues for quantum computation.
Quantum Information processing has several different applications: some of them can be performed controlling only few qubits simultaneously (e.g. quantum teleportation or quantum cryptography) [1]. Usually, the transmission of large amount of information is performed repeating several times the scheme implemented for few qubits. However, to exploit the advantages of quantum computation, the simultaneous control of many qubits is unavoidable [2]. This situation increases the experimental difficulties of quantum computing: maintaining quantum coherence in a large quantum system is a difficult task. Indeed a quantum computer is a many-body complex system and decoherence, due to the interaction with the external world, will eventually corrupt any quantum computation. Moreover, internal static imperfections can lead to quantum chaos in the quantum register thus destroying computer operability [3]. Indeed, as it has been shown in [4], a critical imperfection strength exists above which the quantum register thermalizes and quantum computation becomes impossible. We showed such effects on a quantum computer performing an efficient algorithm