High Finesse Fiber Fabry-Perot Cavities: Stabilization and Mode Matching Analysis

Fiber Fabry-Perot cavities, formed by micro-machined mirrors on the end-facets of optical fibers, are used in an increasing number of technical and scientific applications, where they typically require precise stabilization of their optical resonances. Here, we study two different approaches to construct fiber Fabry-Perot resonators and stabilize their length for experiments in cavity quantum electrodynamics with neutral atoms. A piezo-mechanically actuated cavity with feedback based on the Pound-Drever-Hall locking technique is compared to a novel rigid cavity design that makes use of the high passive stability of a monolithic cavity spacer and employs thermal self-locking and external temperature tuning. Furthermore, we present a general analysis of the mode matching problem in fiber Fabry-Perot cavities, which explains the asymmetry in their reflective line shapes and has important implications for the optimal alignment of the fiber resonators. Finally, we discuss the issue of fiber-generated background photons. We expect that our results contribute towards the integration of high-finesse fiber Fabry-Perot cavities into compact and robust quantum-enabled devices in the future.Comment: The Supplemental Material is included in the source code of the article that can be downloaded from this arXiv page (see "Other formats"). Peer-reviewed version with changes to text and figure

Bayesian feedback control of a two-atom spin-state in an atom-cavity system

We experimentally demonstrate real-time feedback control of the joint spin-state of two neutral Caesium atoms inside a high finesse optical cavity. The quantum states are discriminated by their different cavity transmission levels. A Bayesian update formalism is used to estimate state occupation probabilities as well as transition rates. We stabilize the balanced two-atom mixed state, which is deterministically inaccessible, via feedback control and find very good agreement with Monte-Carlo simulations. On average, the feedback loops achieves near optimal conditions by steering the system to the target state marginally exceeding the time to retrieve information about its state.Comment: 4 pages, 4 figure

Deep-Learning-Based Methodology for Fault Diagnosis in Electromechanical Systems

Fault diagnosis in manufacturing systems represents one of the most critical challenges dealing with condition-based monitoring in the recent era of smart manufacturing. In the current Industry 4.0 framework, maintenance strategies based on traditional data-driven fault diagnosis schemes require enhanced capabilities to be applied over modern production systems. In fact, the integration of multiple mechanical components, the consideration of multiple operating conditions, and the appearance of combined fault patterns due to eventual multi-fault scenarios lead to complex electromechanical systems requiring advanced monitoring strategies. In this regard, data fusion schemes supported with advanced deep learning technology represent a promising approach towards a big data paradigm using cloud-based software services. However, the deep learning models’ structure and hyper-parameters selection represent the main limitation when applied. Thus, in this paper, a novel deep-learning-based methodology for fault diagnosis in electromechanical systems is presented. The main benefits of the proposed methodology are the easiness of application and high adaptability to available data. The methodology is supported by an unsupervised stacked auto-encoders and a supervised discriminant analysis

3er. Coloquio: Fortalecimiento de los Colectivos de Docencia

Las memorias del 3er. Coloquio de Fortalecimiento de Colectivos de Docencia deben ser entendidas como un esfuerzo colectivo de la comunidad de académicos de la División de Ciencias y Artes para el Diseño, en medio de la pandemia COVID-19, con el fin de: • Analizar y proponer acciones concretas que promuevan el mejoramiento de la calidad docente en la División. • Proponer acciones que permitan continuar fortaleciendo los cursos con modalidad a distancia (remotos). • Ante un escenario que probablemente demandará en el mediano plazo, transitar del modelo remoto a un modelo híbrido, proponer acciones a considerar para la transición de los cursos. • Planear y preparar cursos de nivelación de conocimientos, para cuando se transite a la impartición de la docencia de manera mixta o presencial, dirigidos a los alumnos que no hayan tenido oportunidad de desarrollar actividades relevantes para su formación, como prácticas de talleres y laboratorios, visitas, o alguna otra actividad relevante