Measurement-based quantum computation from Clifford quantum cellular automata

Abstract

Measurement-based quantum computation (MBQC) is a paradigm for quantum computation where computation is driven by local measurements on a suitably entangled resource state. In this work we show that MBQC is related to a model of quantum computation based on Clifford quantum cellular automata (CQCA). Specifically, we show that certain MBQCs can be directly constructed from CQCAs which yields a simple and intuitive circuit model representation of MBQC in terms of quantum computation based on CQCA. We apply this description to construct various MBQC-based Ansätze for parameterized quantum circuits, demonstrating that the different Ansätze may lead to significantly different performances on different learning tasks. In this way, MBQC yields a family of Hardware-efficient Ansätze that may be adapted to specific problem settings and is particularly well suited for architectures with translationally invariant gates such as neutral atoms.

arXiv comment16 pages, 12 figures

References in corpus (8)

• Supervised learning with quantum enhanced feature spaces
• Persistent entanglement in arrays of interacting particles
• Power of data in quantum machine learning
• Diagnosing Barren Plateaus with Tools from Quantum Optimal Control
• A computationally universal phase of quantum matter
• Subsystem symmetries, quantum cellular automata, and computational phases of quantum matter
• Quantum computation via translation-invariant operations on a chain of qubits
• On the structure of Clifford quantum cellular automata

Cited by in corpus (3)

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• Minimally Universal Parity Quantum Computing
• Classification of qubit cellular automata on hypercubic lattices