Measurement-based quantum computation

By Hans J. Briegel, Dan E. Browne, Wolfgang Dür, Robert Raussendorf, Maarten Van den Nest. 2009

1,060 citations recorded by the source corpus.

Quantum computation offers a promising new kind of information processing, where the non-classical features of quantum mechanics are harnessed and exploited. A number of models of quantum computation exist. These models have been shown to be formally equivalent, but their underlying elementary concepts and the requirements for their practical realization can differ significantly. A particularly exciting paradigm is that of measurement-based quantum computation, where the processing of quantum information takes place by rounds of simple measurements on qubits prepared in a highly entangled state. We review recent developments in measurement-based quantum computation with a view to both fundamental and practical issues, in particular the power of quantum computation, the protection against noise (fault tolerance) and steps towards experimental realization. Finally, we highlight a number of connections between this field and other branches of physics and mathematics. So-called one-way schemes have emerged as a powerful model to describe and implement quantum computation. This article reviews recent progress, highlights connections to other areas of physics and discusses future directions.

Subfields: Artificial Intelligence, Atomic and Molecular Physics, and Optics

View Paper: https://www.semanticscholar.org/paper/7389fe01fdee8536402c08294cf789855a15c810

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In Atomic and Molecular Physics, and Optics

Citations in the corpus

The classical-quantum boundary for correlations: Discord and related measures (2011, background): “(Chaves and de Melo, 2011) analyze the correlations in a noisy implementation of one-way (measurement-based) quantum computation due to (Briegel et al., 2009).”
Photonic quantum information processing: A concise review (2019, background): “6,308 The key idea is that, in the absence of deterministic two-photon operations, the cluster state can be built up ofﬂine using nondeterministic interactions, and then the computation progresses via those deterministic single-qubit operations for which optics is especially suited.”
Midcircuit Operations Using the omg Architecture in Neutral Atom Arrays (2023, background): “” Salient areas where these so-called midcircuit operations are enabling include quantum error correction, measurement-based quantum computing, metrology, entanglement generation, and quantum simulation, to name a few [4 – 13].”
Fusion-based quantum computation (2021, methodology): “Quantum computation based on resource state generation and fusion has been studied previously [1–7] by mapping operations onto a model of circuit-based quantum computing or measurement-based quantum computing (MBQC) [8, 9].”
Cavity-based quantum networks with single atoms and optical photons (2014, methodology): “The second approach, known as measurement based quantum computing (Briegel et al., 2009), instead relies on the generation of a highly entan- gled state, and any processing task can be implemented with local measurements and feedback in form of unitary operations.”
The quest for a Quantum Neural Network (2014, background): “Other alternatives to coherent quantum computing that could be highly interesting for QNN research are measurement-based quantum computing [37], adiabatic quantum computing [38] or duality quantum computing [39].”
Macroscopic quantum states: Measures, fragility, and implementations (2017, methodology): “Note that the choice of free operations is crucial in this respect, as measurements play a central role in MBQC but are usually not considered to be free in the context of measures for quantum macroscopicity.”
Flux-controlled quantum computation with Majorana fermions (2013, methodology): “The ramm can be used to efficiently create maximally entangled multiqubit states, such as 2D cluster states [41–43], which make it possible to realize any quantum circuit by means of single-qubit operations and measurements [44].”
Predicting many properties of a quantum system from very few measurements (2020, background): “Applications range from quantum error correction [56], to measurement-based quantum computation [11, 61] and randomized benchmarking [23, 44, 53].”
An introduction to quantum machine learning (2014, background): “ adiabatic quantum computing might lend itself to learning as an optimisation problem [15]. Other alternatives of quantum computation, such as dissipative [70] and measurement-based quantum computing [71] might also oer an interesting framowork for quantum learning. In summary, even though there is ”
Private quantum computation: an introduction to blind quantum computing and related protocols (2016, positive): “In measurement-based quantum computation (MBQC), a quantum computation is expressed as a sequence of single-qubit measurements to be performed on a fixed resource state.(32) These resource states are known as graph states, due to their correspondence to simple graphs.”