Macquarie University

About: Macquarie University is a education organization based out in Sydney, New South Wales, Australia. It is known for research contribution in the topics: Population & Context (language use). The organization has 14075 authors who have published 47673 publications receiving 1416184 citations. The organization is also known as: Macquarie uni.

Integrated spatial multiplexing of heralded single-photon sources

Abstract: The non-deterministic nature of photon sources is a key limitation for single-photon quantum processors. Spatial multiplexing overcomes this by enhancing the heralded single-photon yield without enhancing the output noise. Here the intrinsic statistical limit of an individual source is surpassed by spatially multiplexing two monolithic silicon-based correlated photon pair sources in the telecommunications band, demonstrating a 62.4% increase in the heralded single-photon output without an increase in unwanted multipair generation. We further demonstrate the scalability of this scheme by multiplexing photons generated in two waveguides pumped via an integrated coupler with a 63.1% increase in the heralded photon rate. This demonstration paves the way for a scalable architecture for multiplexing many photon sources in a compact integrated platform and achieving efficient two-photon interference, required at the core of optical quantum computing and quantum communication protocols.

Genre and Field in Critical Discourse Analysis: A Synopsis

Abstract: This paper relates the concepts of genre and field, as developed in the context of systemic-functional linguistics, to the broader concepts of discourse and discursive practice. Generic structure is described in terms of the sequencing of speech acts, and as realizing the activity sequences which form the core of discursive practices. Field structure is reinterpreted as the recontextualization of social practice and as realizing discourses, that is, context-specific knowledge constructions about social practices. The theory is extended to the multimodal text, the text which uses more than one semiotic, e.g. verbal text and images. It is applied in a critical analysis of the discursive practices constituted by a certain kind of professional guidance writing in the press, and of discourses about `going to school for the first time'.

Improving Topic Models with Latent Feature Word Representations

Abstract: Probabilistic topic models are widely used to discover latent topics in document collections, while latent feature vector representations of words have been used to obtain high performance in many NLP tasks. In this paper, we extend two different Dirichlet multinomial topic models by incorporating latent feature vector representations of words trained on very large corpora to improve the word-topic mapping learnt on a smaller corpus. Experimental results show that by using information from the external corpora, our new models produce significant improvements on topic coherence, document clustering and document classification tasks, especially on datasets with few or short documents.