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Título:
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Spectral retrieval techniques for high-resolution Fourier-transform micro-spectrometers
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Autores:
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Herrero-Bermello, Alaine ;
Villafranca Velasco, Aitor ;
Podmore, Hugh ;
Cheven, Pavel ;
Schmid, Jens H. ;
Janz, Siegfried ;
Calvo Padilla, María Luisa ;
Xu, Dan-Xia ;
Scott, Alan ;
Lee, Regina
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Tipo de documento:
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texto impreso
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Editorial:
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SPIE - International Society for Optical Engineering, 2018
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Dimensiones:
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application/pdf
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Nota general:
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info:eu-repo/semantics/openAccess
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Idiomas:
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Palabras clave:
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Estado = Publicado
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Materia = Ciencias: Física: Optica
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Tipo = Artículo
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Resumen:
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Spatial heterodyne Fourier transform (SHFT) spectroscopy is based on simultaneous interferometric measurements implementing linearly increasing optical path differences, hence circumventing the need for mechanical components of traditional Fourier transform spectroscopy schemes. By taking advantage of the high mode confinement of the Silicon-on-Insulator (SOI). platform, great interferometric lengths can be implemented in a reduced footprint, hence increasing the resolution of the device. However, as resolution increases, spectrometers become progressively more sensitive to environmental conditions, and new spectral retrieval techniques are required. In this work, we present several software techniques that enhance the operation of high-resolution SHFT micro-spectrometers. Firstly, we present two techniques for mitigating and correcting the effects of temperature drifts, based on a temperature-sensitive calibration and phase errors correction. Both techniques are demonstrated experimentally on a 32 Mach-Zehnder interferometers array fabricated in a Silicon-on-insulator chip with microphotonic spirals of linearly increasing length up to 3.779 cm. This configuration provides a resolution of 17 pm in a compact device footprint of 12 mm(2). Secondly, we propose the application of compressive-sensing (CS) techniques to SHFT micro-spectrometers. By assuming spectrum sparsity, an undersampled discrete Fourier interferogram is inverted using l1-norm minimization to retrieve the input spectrum. We demonstrate this principle on a subwavelength-engineered SHFT with 32 MZIs and a 50 pm resolution. Correct retrieval of three sparse input signals was experimentally demonstrated using data from 14 or fewer MZIs and applying common CS reconstruction techniques to this data.
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En línea:
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https://eprints.ucm.es/id/eprint/50581/1/CalvoML132libre.pdf
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