Kondo Resonance of a Microwave Photon

We emulate renormalization group models, such as the Spin-Boson Hamiltonian or the anisotropic Kondo model, from a quantum optics perspective by considering a superconducting device. The infra-red confinement involves photon excitations of two tunable transmission lines entangled to an artificial spin-1/2 particle or double-island charge qubit. Focusing on the propagation of microwave light, in the underdamped regime of the Spin-Boson model, we identify a many-body resonance where a photon is absorbed at the renormalized qubit frequency and reemitted forward in an elastic manner. We also show that asymptotic freedom of microwave light is reached by increasing the input signal amplitude at low temperatures which allows the disappearance of the transmission peak.Comment: Final Version: Main text and Supplementary Materia

Ridgelet-based signature for natural image classification

This paper presents an approach to grouping natural scenes into (semantically) meaningful categories. The proposed approach exploits the statistics of natural scenes to define relevant image categories. A ridgelet-based signature is used to represent images. This signature is used by a support vector classifier that is well designed to support high dimensional features, resulting in an effective recognition system. As an illustration of the potential of the approach several experiments of binary classifications (e.g. city/landscape or indoor/outdoor) are conducted on databases of natural scenes

Pre-classification for automatic image orientation

In this paper, we propose a novel method for automatic orientation of digital images. The approach is based on exploiting the properties of local statistics of natural scenes. In this way, we address some of the difficulties encountered in previous works in this area. The main contribution of this paper is to introduce a pre-classification step into carefully defined categories in order to simplify subsequent orientation detection. The proposed algorithm was tested on 9068 images and compared to existing state of the art in the area. Results show a significant improvement over previous work

Valuing the voluntary sector: rethinking economic analysis

The voluntary sector plays an important role in the sports industry, as a provider of sporting opportunities and in the development of sport, from increasing participation through to supporting excellence and elite performance. However, despite this importance, research on its contribution to sport-related economic activity is limited, with information on this sector remaining the weakest part of current economic assessments of the UK sports industry. The research presented in this article examines the economic importance of the voluntary sector, using a case study of Sheffield. It demonstrates that the sports voluntary sector in the city is considerably smaller than was predicted when using national estimates, and that this is largely a consequence of methodological issues relating to previous research. The article suggests that in the light of the findings and the increasing use of sport in urban policy, there is a need to rethink the methodology used to evaluate the economic contribution of the voluntary sector in the future.</p