Cluster state preparation using gates operating at arbitrary success probabilities

Several physical architectures allow for measurement-based quantum computing using sequential preparation of cluster states by means of probabilistic quantum gates. In such an approach, the order in which partial resources are combined to form the final cluster state turns out to be crucially important. We determine the influence of this classical decision process on the expected size of the final cluster. Extending earlier work, we consider different quantum gates operating at various probabilites of success. For finite resources, we employ a computer algebra system to obtain the provably optimal classical control strategy and derive symbolic results for the expected final size of the cluster. We identify two regimes: When the success probability of the elementary gates is high, the influence of the classical control strategy is found to be negligible. In that case, other figures of merit become more relevant. In contrast, for small probabilities of success, the choice of an appropriate strategy is crucial.Comment: 7 pages, 9 figures, contribution to special issue of New J. Phys. on "Measurement-Based Quantum Information Processing". Replaced with published versio

Brokered Graph State Quantum Computing

We describe a procedure for graph state quantum computing that is tailored to fully exploit the physics of optically active multi-level systems. Leveraging ideas from the literature on distributed computation together with the recent work on probabilistic cluster state synthesis, our model assigns to each physical system two logical qubits: the broker and the client. Groups of brokers negotiate new graph state fragments via a probabilistic optical protocol. Completed fragments are mapped from broker to clients via a simple state transition and measurement. The clients, whose role is to store the nascent graph state long term, remain entirely insulated from failures during the brokerage. We describe an implementation in terms of NV-centres in diamond, where brokers and clients are very naturally embodied as electron and nuclear spins.Comment: 5 pages, 3 figure

Experimental measurement-based quantum computing beyond the cluster-state model

The paradigm of measurement-based quantum computation opens new experimental avenues to realize a quantum computer and deepens our understanding of quantum physics. Measurement-based quantum computation starts from a highly entangled universal resource state. For years, clusters states have been the only known universal resources. Surprisingly, a novel framework namely quantum computation in correlation space has opened new routes to implement measurement-based quantum computation based on quantum states possessing entanglement properties different from cluster states. Here we report an experimental demonstration of every building block of such a model. With a four-qubit and a six-qubit state as distinct from cluster states, we have realized a universal set of single-qubit rotations, two-qubit entangling gates and further Deutsch's algorithm. Besides being of fundamental interest, our experiment proves in-principle the feasibility of universal measurement-based quantum computation without using cluster states, which represents a new approach towards the realization of a quantum computer.Comment: 26 pages, final version, comments welcom

Strategies for the preparation of large cluster states using non-deterministic gates

The cluster state model for quantum computation has paved the way for schemes that allow scalable quantum computing, even when using non-deterministic quantum gates. Here the initial step is to prepare a large entangled state using non-deterministic gates. A key question in this context is the relative efficiencies of different 'strategies', i.e. in what order should the non-deterministic gates be applied, in order to maximize the size of the resulting cluster states? In this paper we consider this issue in the context of 'large' cluster states. Specifically, we assume an unlimited resource of qubits and ask what the steady state rate at which 'large' clusters are prepared from this resource is, given an entangling gate with particular characteristics. We measure this rate in terms of the number of entangling gate operations that are applied. Our approach works for a variety of different entangling gate types, with arbitrary failure probability. Our results indicate that strategies whereby one preferentially bonds together clusters of identical length are considerably more efficient than those in which one does not. Additionally, compared to earlier analytic results, our numerical study offers substantially improved resource scaling