Scaling of multiple postselected quantum gates in optics

We show that interesting multigate circuits can be constructed using a postselected controlled-sign gate that works with a probability (1/3)(n), where n-1 is the number of controlled-sign gates in the circuit, rather than (1/9)(n-1), as would be expected from a sequence of such gates. We suggest some quantum information tasks which could be demonstrated using these circuits, such as parity checking and cluster-state computation.

Frequency and temporal effects in linear optical quantum computing

Typically linear optical quantum computing (LOQC) models assume that all input photons are completely indistinguishable. In practice there will inevitably be nonidealities associated with the photons and the experimental setup which will introduce a degree of distinguishability between photons. We consider a nondeterministic optical controlled-NOT gate, a fundamental LOQC gate, and examine the effect of temporal and spectral distinguishability on its operation. We also consider the effect of utilizing nonideal photon counters, which have finite bandwidth and time response.

Quantum-gate characterization in an extended Hilbert space

We describe an approach for characterizing the process performed by a quantum gate using quantum process tomography, by first modeling the gate in an extended Hilbert space, which includes nonqubit degrees of freedom. To prevent unphysical processes from being predicted, present quantum process tomography procedures incorporate mathematical constraints, which make no assumptions as to the actual physical nature of the system being described. By contrast, the procedure presented here assumes a particular class of physical processes, and enforces physicality by fitting the data to this model. This allows quantum process tomography to be performed using a smaller experimental data set, and produces parameters with a direct physical interpretation. The approach is demonstrated by example of mode matching in an all-optical controlled-NOT gate. The techniques described are general and could be applied to other optical circuits or quantum computing architectures.

High-fidelity measurement and quantum feedback control in circuit QED

Circuit QED is a promising solid-state quantum computing architecture. It also has excellent potential as a platform for quantum control-especially quantum feedback control-experiments. However, the current scheme for measurement in circuit QED is low efficiency and has low signal-to-noise ratio for single-shot measurements. The low quality of this measurement makes the implementation of feedback difficult, and here we propose two schemes for measurement in circuit QED architectures that can significantly improve signal-to-noise ratio and potentially achieve quantum-limited measurement. Such measurements would enable the implementation of quantum feedback protocols and we illustrate this with a simple entanglement-stabilization scheme.

'Hybrids' and the gendering of computing jobs in Australia

This paper presents recent Australian evidence on the extent to which women are entering “hybrid” computing jobs combining technical and communication or “people management” skills, and the way these skill combinations are valued at organisational level. We draw on a survey of detailed occupational roles in large IT firms to examine the representation of women in a range of jobs consistent with the notion of “hybrid”, and analyse the discourse around these sorts of skills in a set of organisational case studies. Our research shows a traditional picture of labour market segmentation, with limited representation of women in high status jobs, and their relatively greater prevalence in more routine areas of the industry. While our case studies highlight perceptions of the need for hybrid roles and assumptions about the suitability of women for such jobs, the ongoing masculinity of core development functions appears untouched by this discourse.

Efficiently computing weighted proximity relationships in spatial databases

Spatial data mining recently emerges from a number of real applications, such as real-estate marketing, urban planning, weather forecasting, medical image analysis, road traffic accident analysis, etc. It demands for efficient solutions for many new, expensive, and complicated problems. In this paper, we investigate the problem of evaluating the top k distinguished “features” for a “cluster” based on weighted proximity relationships between the cluster and features. We measure proximity in an average fashion to address possible nonuniform data distribution in a cluster. Combining a standard multi-step paradigm with new lower and upper proximity bounds, we presented an efficient algorithm to solve the problem. The algorithm is implemented in several different modes. Our experiment results not only give a comparison among them but also illustrate the efficiency of the algorithm.