10 research outputs found
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