Temporal and statistical information in causal structure learning

Three experiments examined children’s and adults’ abilities to use statistical and temporal information to distinguish between common cause and causal chain structures. In Experiment 1, participants were provided with conditional probability information and/or temporal information and asked to infer the causal structure of a three-variable mechanical system that operated probabilistically. Participants of all ages preferentially relied on the temporal pattern of events in their inferences, even if this conflicted with statistical information. In Experiments 2 and 3, participants observed a series of interventions on the system, which in these experiments operated deterministically. In Experiment 2, participants found it easier to use temporal pattern information than statistical information provided as a result of interventions. In Experiment 3, in which no temporal pattern information was provided, children from 6-7 years, but not younger children, were able to use intervention information to make causal chain judgments, although they had difficulty when the structure was a common cause. The findings suggest that participants, and children in particular, may find it more difficult to use statistical information than temporal pattern information because of its demands on information processing resources. However, there may also be an inherent preference for temporal information.

Solving Decision Problems with Limited Information

We present a new algorithm for exactly solving decision-making problems represented as an influence diagram. We do not require the usual assumptions of no forgetting and regularity, which allows us to solve problems with limited information. The algorithm, which implements a sophisticated variable elimination procedure, is empirically shown to outperform a state-of-the-art algorithm in randomly generated problems of up to 150 variables and 10^64 strategies.

High Performance Real-time Pre-Processing for Fixed-Complexity Sphere Decoder

Pre-processing (PP) of received symbol vector and channel matrices is an essential pre-requisite operation for Sphere Decoder (SD)-based detection of Multiple-Input Multiple-Output (MIMO) wireless systems. PP is a highly complex operation, but relative to the total SD workload it represents a relatively small fraction of the overall computational cost of detecting an OFDM MIMO frame in standards such as 802.11n. Despite this, real-time PP architectures are highly inefficient, dominating the resource cost of real-time SD architectures. This paper resolves this issue. By reorganising the ordering and QR decomposition sub operations of PP, we describe a Field Programmable Gate Array (FPGA)-based PP architecture for the Fixed Complexity Sphere Decoder (FSD) applied to 4 × 4 802.11n MIMO which reduces resource cost by 50% as compared to state-of-the-art solutions whilst maintaining real-time performance.

Entanglement distribution with global control in a star-shaped multi-splitter

Distributed quantum information processing (QIP) is a promising way to bypass problems due to unwanted interactions between elements. However, this strategy presupposes the engineering of protocols for remote processors. In many of them, pairwise entanglement is a key resource. We study a model which distributes entanglement among elements of a delocalized network without local control. The model is efficient both in finite- and infinite-dimensional Hilbert spaces. We suggest a setup of electromechanical systems to implement our proposal.

Identification of tone duration, line length and letter position: An experimental approach to timing and working memory deficits in schizophrenia.

Patients with schizophrenia display numerous cognitive deficits, including problems in working memory, time estimation, and absolute identification of stimuli. Research in these fields has traditionally been conducted independently. We examined these cognitive processes using tasks that are structurally similar and that yield rich error data. Relative to healthy control participants (n = 20), patients with schizophrenia (n = 20) were impaired on a duration identification task and a probed-recall memory task but not on a line-length identification task. These findings do not support the notion of a global impairment in absolute identification in schizophrenia. However, the authors suggest that some aspect of temporal information processing is indeed disturbed in schizophrenia.

Entanglers: Beam splitters and thermal fields

Entanglement is an important ingredient for quantum information processing. We discuss some sources of entanglement, namely a beam splitter and a thermal field. For the generation of entangled continuous-variable states, we consider a beam splitter and find some conditions for input fields to see entanglement in the output. While a beam splitter is a unitary device to generate an entangled state for a bipartite continuous-variable system, a thermal field is shown to mediate entanglement of two qubits.

Experimentally realizable characterizations of continuous- variable Gaussian states

Measures of entanglement, fidelity, and purity are basic yardsticks in quantum-information processing. We propose how to implement these measures using linear devices and homodyne detectors for continuous-variable Gaussian states. In particular, the test of entanglement becomes simple with some prior knowledge that is relevant to current experiments.

Entanglement between two superconducting qubits via interaction with nonclassical radiation

We propose a scheme to physically interface superconducting nanocircuits and quantum optics. We address the transfer of quantum information between systems having different physical natures and defined in Hilbert spaces of different dimensions. In particular, we investigate the transfer of the entanglement initially in a nonclassical state of an infinite dimensional system to a pair of superconducting charge qubits. This setup is able to drive an initially separable state of the qubits into an almost pure, highly entangled state suitable for quantum information processing.

Dynamical and steady-state requirements for effective entanglement transfer

Entanglement transfer processes from a continuous-variable (CV) to a qubit system have primary importance in quantum information processing due to some practical implications in the realization of a quantum network. A CV system can propagate entanglement while a qubit system is easy to manipulate. We study conditions to entangle two atomic qubits with a two-mode squeezed field driving two cavities containing the atoms.

Single-photon tunneling via localized surface plasmons

Strong evidence of a single-photon tunneling effect, a direct analog of single-electron tunneling, has been obtained in the measurements of light tunneling through individual subwavelength pinholes in a gold film covered with a layer of polydiacetylene. The transmission of some pinholes reached saturation because of the optical nonlinearity of polydiacetylene at a very low light intensity of a few thousand photons per second. This result is explained theoretically in terms of a "photon blockade," similar to the Coulomb blockade phenomenon observed in single-electron tunneling experiments. Single-photon tunneling may find applications in the fields of quantum communication and information processing.

Classical computation with quantum systems

As semiconductor electronic devices scale to the nanometer range and quantum structures (molecules, fullerenes, quantum dots, nanotubes) are investigated for use in information processing and storage, it, becomes useful to explore the limits imposed by quantum mechanics on classical computing. To formulate the problem of a quantum mechanical description of classical computing, electronic device and logic gates are described as quantum sub-systems with inputs treated as boundary conditions, outputs expressed.is operator expectation values, and transfer characteristics and logic operations expressed through the sub-system Hamiltonian. with constraints appropriate to the boundary conditions. This approach, naturally, leads to a description of the subsystem.,, in terms of density matrices. Application of the maximum entropy principle subject to the boundary conditions (inputs) allows for the determination of the density matrix (logic operation), and for calculation of expectation values of operators over a finite region (outputs). The method allows for in analysis of the static properties of quantum sub-systems.

One-way quantum computing in a decoherence-free subspace

We introduce a novel scheme for one-way quantum computing (QC) based on the use of information encoded qubits in an effective cluster state resource. With the correct encoding structure, we show that it is possible to protect the entangled resource from phase damping decoherence, where the effective cluster state can be described as residing in a decoherence-free subspace (DFS) of its supporting quantum system. One-way QC then requires either single or two-qubit adaptive measurements. As an example where this proposal can be realized, we describe an optical lattice set-up where the scheme provides robust quantum information processing. We also outline how one can adapt the model to provide protection from other types of decoherence.

Nested entangled states for distributed quantum channels

We find a coupling-strength configuration for a linear chain of N spins which gives rise to simultaneous multiple Bell states. We suggest a way such an interesting entanglement pattern can be used in order to distribute maximally entangled channels to remote locations and generate multipartite entanglement with a minimum-control approach. Our proposal thus provides a way to achieve the core resources in distributed information processing. The schemes we describe can be efficiently tested in chains of coupled cavities interacting with three-level atoms.