Publication

Twin Photon Source: Spatio-temporal Properties

2015
Conference Papers

Abstract

We propose a method to study and characterize the spatial and temporal properties of degenerate photon pairs emitted in SPDC, using a filtering system combined with temperature variation of the nonlinear crystal. The photons can be distinguished. We relate these to the measured Hong-Ou-Mandel interference dip of the photons, measured in a parallel experiment. The theoretical plots match very well with the experimental results.

Official source

https://infoscience.epfl.ch/entities/publication/30c6bdc4-0361-4379-aca2-e0ac457bba57

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2015
Conference Papers

Abstract

Official source

https://infoscience.epfl.ch/entities/publication/30c6bdc4-0361-4379-aca2-e0ac457bba57

About this result

Related concepts (19)

Collaborative filtering

Collaborative filtering (CF) is a technique used by recommender systems. Collaborative filtering has two senses, a narrow one and a more general one. In the newer, narrower sense, collaborative filtering is a method of making automatic predictions (filtering) about the interests of a user by collecting preferences or taste information from many users (collaborating). The underlying assumption of the collaborative filtering approach is that if a person A has the same opinion as a person B on an issue, A is more likely to have B's opinion on a different issue than that of a randomly chosen person.

Kalman filter

For statistics and control theory, Kalman filtering, also known as linear quadratic estimation (LQE), is an algorithm that uses a series of measurements observed over time, including statistical noise and other inaccuracies, and produces estimates of unknown variables that tend to be more accurate than those based on a single measurement alone, by estimating a joint probability distribution over the variables for each timeframe. The filter is named after Rudolf E. Kálmán, who was one of the primary developers of its theory.

Recommender system

A recommender system, or a recommendation system (sometimes replacing 'system' with a synonym such as platform or engine), is a subclass of information filtering system that provide suggestions for items that are most pertinent to a particular user. Typically, the suggestions refer to various decision-making processes, such as what product to purchase, what music to listen to, or what online news to read. Recommender systems are particularly useful when an individual needs to choose an item from a potentially overwhelming number of items that a service may offer.

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