ABSTRACT
This paper presents a study of the performances of different Mach-Zehnder modulation technologies with applications in microwave polarimeters based on a near-infrared (NIR) frequency up-conversion stage, allowing for optical correlation and signal detection at a wavelength of 1550 nm. Commercial Mach-Zehnder modulators (MZMs) are traditionally implemented using LiNbO3 technology, which does not enable integration for the fabrication of MZMs. In this work, we propose the use of an alternative technology based on InP, which allows for integration in the fabrication process. In this way, it is possible to obtain advantages in terms of bandwidth, cost, and size reductions, which yield results that are very interesting for wide-band applications such as microwave instrumentation for the study of the cosmic microwave background (CMB). Here, we describe and compare the modulation performances of different MZMs, with one commercial unit presenting a higher bandwidth than those in previous works, and another three InP integrated units provided by the Fraunhofer Institute for Telecommunications, Heinrich-Hertz-Institute (HHI). Then, these modulators were coupled to a microwave polarimeter demonstrator, which has also been presented previously, to compare the polarization measurement performances of each of the MZMs.
ABSTRACT
Cosmic Microwave Background (CMB) B-modes detection is the main focus of future CMB experiments because of the valuable information it contains, particularly to probe the physics of the very early universe. For this reason, we have developed an optimized polarimeter demonstrator sensitive to the 10-20 GHz band in which the signal received by each antenna is modulated into a Near Infrared (NIR) laser by a Mach-Zehnder modulator. Then, these modulated signals are optically correlated and detected using photonic back-end modules consisting of voltage-controlled phase shifters, a 90-degree optical hybrid, a pair of lenses, and an NIR camera. During laboratory tests, a 1/f-like noise signal related to the low phase stability of the demonstrator has been found experimentally. To solve this issue, we have developed a calibration method that allows us to remove this noise in an actual experiment, until obtaining the required accuracy level in the measurement of polarization.
ABSTRACT
BACKGROUND: In this paper we present a model of parameters to aesthetically characterize films using a multi-disciplinary approach: by combining film theory, visual low-level video descriptors (modeled in order to supply aesthetic information) and classification techniques using machine and deep learning. METHODS: Four different tests have been developed, each for a different application, proving the model's usefulness. These applications are: aesthetic style clustering, prediction of production year, genre detection and influence on film popularity. RESULTS: The results are compared against high-level information to determine the accuracy of the model to classify films without knowing such information previously. The main difference with other film characterization approaches is that we are able to isolate the influence of high-level descriptors to really understand the relevance of low-level features and, accordingly propose a useful set of low-level visual descriptors for that purpose. This model has been tested with a representative number of films to prove that it can be used for different applications.