Memorandum of the Will-Burt Company Submitted to the Commission on the Future of Worker-Management Relations

Memo_Will_Burt_071993.pdf: 177 downloads, before Oct. 1, 2020

Ultrafast electrooptic dual-comb interferometry

The femtosecond laser frequency comb has enabled the 21st century revolution in optical synthesis and metrology. A particularly compelling technique that relies on the broadband coherence of two laser frequency combs is dual-comb interferometry. This method is rapidly advancing the field of optical spectroscopy and empowering new applications, from nonlinear microscopy to laser ranging. Up to now, most dual-comb interferometers were based on modelocked lasers, whose repetition rates have restricted the measurement speed to ~ kHz. Here we demonstrate a novel dual-comb interferometer that is based on electrooptic frequency comb technology and measures consecutive complex spectra at a record-high refresh rate of 25 MHz. These results pave the way for novel scientific and metrology applications of frequency comb generators beyond the realm of molecular spectroscopy, where the measurement of ultrabroadband waveforms is of paramount relevance

Revisiting the Hubble sequence in the SDSS DR7 spectroscopic sample: a publicly available bayesian automated classification

We present an automated morphological classification in 4 types (E,S0,Sab,Scd) of ~700.000 galaxies from the SDSS DR7 spectroscopic sample based on support vector machines. The main new property of the classification is that we associate to each galaxy a probability of being in the four morphological classes instead of assigning a single class. The classification is therefore better adapted to nature where we expect a continuos transition between different morphological types. The algorithm is trained with a visual classification and then compared to several independent visual classifications including the Galaxy Zoo first release catalog. We find a very good correlation between the automated classification and classical visual ones. The compiled catalog is intended for use in different applications and can be downloaded at http://gepicom04.obspm.fr/sdss_morphology/Morphology_2010.html and soon from the CasJobs database.Comment: A&A in press, english corrections from language editor adde

Gramaticalización y dialectología comparada. Una isoglosa sintáctico-semántica del español

The paper shows how the pragmatic semantics of a language is a fundamental level in a grammaticalization process. The paper examines four changes in Spanish, comparing the Spanish and the Mexican dialects in four different grammatical areas: nominal possesion, diminutives, leismo, and perfect tenses. The proposal of the paper is that a 1 Una versión preliminar y abreviada de este trabajo fue leída en la reunión científica El Patrimonio Documental y la Filología, llevada a cabo en la Universidad de Valladolid, en el mes de noviembre de 2001. Los cambios 3.1.1, 3.1.2, y 3.2.1 fueron leídos en versiones parciales en el Coloquio de Gramática y Pragmática realizado en la Universidad de Buenos Aires en agosto de 1999, y están expuestos en mi artículo «Motivaciones distintas para una gramaticalización», actualmente en prensa en Signo & Seña. Revista de Lingüística de la Universidad de Buenos Aires. Agradezco a Rosa María Espinosa y a Jeanett Reynoso los atinados comentarios críticos.El trabajo intenta mostrar cómo la semántica pragmática es un nivel decisivo en los procesos de gramaticalización. Analiza cuatro cambios de la historia del español, en una comparación diacrónica y diatópica estricta entre español peninsular y español de México, y propone que se produjo una gran isoglosa sintáctico-semántica, que engloba cuatro zonas distintas de la gramática (posesión nominal, diminutivos, leísmo y pretérito perfecto), debido a diferentes perfilamientos de un mismo espacio categorial semántico, esto es, la escisión dialectal fue causada por la diferente selección de rasgos semánticos para codificar una misma área funcional. Las diferentes frecuencias relativas de uso de las formas que realiza cada uno de los dialectos examinados son el único síntoma de que se produjeron distintas gramaticalizaciones en cada uno de ellos

Electro-optic dual-comb interferometry over 40-nm bandwidth

Dual-comb interferometry is a measurement technique that uses two laser frequency combs to retrieve complex spectra in a line-by-line basis. This technique can be implemented with electro-optic frequency combs, offering intrinsic mutual coherence, high acquisition speed and flexible repetition-rate operation. A challenge with the operation of this kind of frequency comb in dual-comb interferometry is its limited optical bandwidth. Here, we use coherent spectral broadening and demonstrate electro-optic dual-comb interferometry over the entire telecommunications C band (200 lines covering ~ 40 nm, measured within 10 microseconds at 100 signal-to-noise ratio per spectral line). These results offer new prospects for electro-optic dual-comb interferometry as a suitable technology for high-speed broadband metrology, for example in optical coherence tomography or coherent Raman microscopy

Algorithmic Perception of Vertices in Sketched Drawings of Polyhedral Shapes

In this article, visual perception principles were used to build an artificial perception model aimed at developing an algorithm for detecting junctions in line drawings of polyhedral objects that are vectorized from hand-drawn sketches. The detection is performed in two dimensions (2D), before any 3D model is available and minimal information about the shape depicted by the sketch is used. The goal of this approach is to not only detect junctions in careful sketches created by skilled engineers and designers but also detect junctions when skilled people draw casually to quickly convey rough ideas. Current approaches for extracting junctions from digital images are mostly incomplete, as they simply merge endpoints that are near each other, thus ignoring the fact that different vertices may be represented by different (but close) junctions and that the endpoints of lines that depict edges that share a common vertex may not necessarily be close to each other, particularly in quickly sketched drawings. We describe and validate a new algorithm that uses these perceptual findings to merge tips of line segments into 2D junctions that are assumed to depict 3D vertices

Optical Frequency Comb Noise Characterization Using Machine Learning

A novel tool, based on Bayesian filtering framework and expectation maximization algorithm, is numerically and experimentally demonstrated for accurate frequency comb noise characterization. The tool is statistically optimum in a mean-square-error-sense, works at wide range of SNRs and offers more accurate noise estimation compared to conventional methods