Photostatistics Reconstruction via Loop Detector Signatures

Photon-number resolving detectors are a fundamental building-block of optical quantum information processing protocols. A loop detector, combined with appropriate statistical processing, can be used to convert a binary on/off photon counter into a photon-number-resolving detector. Here we describe the idea of a signature of photon-counts, which may be used to more robustly reconstruct the photon number distribution of a quantum state. The methodology is applied experimentally in a 9-port loop detector operating at a telecommunications wavelength and compared directly to the approach whereby only the number of photon-counts is used to reconstruct the input distribution. The signature approach is shown to be more robust against calibration errors, exhibit reduced statistical uncertainty, and reduced reliance on a-priori assumptions about the input state.Comment: 13 pages, 12 figure

Mass transfer simulation for concentration of kiwi juice by osmotic distillation using finite volume method

Osmotic distillation (OD) is a membrane process used to separate water from fruit juices at ambient temperatures. The current mathematical models presented in literature for OD [1] are based on phenomenological equations and empirical correlations, which describe the global effects of the flow rate and concentration of the fluids in the transmembrane flux, and starting from this the total productivity and efficiency of the process. These models are unable of describe the local variations in the mass transfer which are product of geometric variables. If these variations were known this would allow improve predictions that can deliver information to build membrane modules whith optimal geometries which is very important for efficiency, scalability and durability of these modules. In this work, a general mathematical model adapted to one cylindrical hollow fiber was solved with the finite volume method. The numerical results allowed to reproduce the experimental data of transmembrane flux in OD using as flow feed a kiwi juice and calculate the variation in the concentration of water and other volatile compunds in the feed (juice) to the process. These studies may be used to predict and optimize the mass transfer in osmotica distillation process. References [1] Zambra, C., Romero, J., Pino, L., Saavedra, A., Sanchez, J. Concentration of cranberry juice by osmotic distillation process. Journal of Food Engineering 144 (2015) 58-65

Mass transfer simulation for concentration of kiwi juice by osmotic distillation using finite volume method

Osmotic distillation (OD) is a membrane process used to separate water from fruit juices at ambient temperatures. The current mathematical models presented in literature for OD [1] are based on phenomenological equations and empirical correlations, which describe the global effects of the flow rate and concentration of the fluids in the transmembrane flux, and starting from this the total productivity and efficiency of the process. These models are unable of describe the local variations in the mass transfer which are product of geometric variables. If these variations were known this would allow improve predictions that can deliver information to build membrane modules whith optimal geometries which is very important for efficiency, scalability and durability of these modules. In this work, a general mathematical model adapted to one cylindrical hollow fiber was solved with the finite volume method. The numerical results allowed to reproduce the experimental data of transmembrane flux in OD using as flow feed a kiwi juice and calculate the variation in the concentration of water and other volatile compunds in the feed (juice) to the process. These studies may be used to predict and optimize the mass transfer in osmotica distillation process. References [1] Zambra, C., Romero, J., Pino, L., Saavedra, A., Sanchez, J. Concentration of cranberry juice by osmotic distillation process. Journal of Food Engineering 144 (2015) 58-65

Learning Object Arrangements in 3D scenes

Trabajo sobre modelos probabilísticos para el aprendizaje de arreglos de objetos en escenas 3D.Agencia Nacional de Investigación e Innovació

Learning Object Arrangements in 3D scenes

Trabajo sobre modelos probabilísticos para el aprendizaje de arreglos de objetos en escenas 3D.Agencia Nacional de Investigación e Innovació

Emergence of network motifs in deep neural networks

Network science can offer fundamental insights into the structural and functional properties of complex systems. For example, it is widely known that neuronal circuits tend to organize into basic functional topological modules, called network motifs. In this article, we show that network science tools can be successfully applied also to the study of artificial neural networks operating according to self-organizing (learning) principles. In particular, we study the emergence of network motifs in multi-layer perceptrons, whose initial connectivity is defined as a stack of fully-connected, bipartite graphs. Simulations show that the final network topology is shaped by learning dynamics, but can be strongly biased by choosing appropriate weight initialization schemes. Overall, our results suggest that non-trivial initialization strategies can make learning more effective by promoting the development of useful network motifs, which are often surprisingly consistent with those observed in general transduction networks

Emergence of Network Motifs in Deep Neural Networks

Network science can offer fundamental insights into the structural and functional properties of complex systems. For example, it is widely known that neuronal circuits tend to organize into basic functional topological modules, called "network motifs". In this article we show that network science tools can be successfully applied also to the study of artificial neural networks operating according to self-organizing (learning) principles. In particular, we study the emergence of network motifs in multi-layer perceptrons, whose initial connectivity is defined as a stack of fully-connected, bipartite graphs. Our simulations show that the final network topology is primarily shaped by learning dynamics, but can be strongly biased by choosing appropriate weight initialization schemes. Overall, our results suggest that non-trivial initialization strategies can make learning more effective by promoting the development of useful network motifs, which are often surprisingly consistent with those observed in general transduction networks

“Comunidad” En La Obra De Álvaro Mutis

 (Ponencia presentada al X Congreso Internacional de la Sociedad Chilena de Estudios Literarios) "Alza tu voz en el blando silencio de la noche, cuando todo ha callado en espera del alba; alza, entonces, tu voz y gime la miseria del mundo y sus criaturas. Pero que nadie sepa de tu llanto, ni descifre el sentido de tus lamentos" (1). Textos como éste escriben (en los muros, en los bordes de folletos comerciales, en el suelo) la multitud de personajes que pueblan la obra del poeta colombiano Álvaro Mutis (Bogotá, 1923), textos en los que denuncian el desorden en que viven y el absurdo del mundo, a través de observaciones paradójicas, indescifrables, esquivas a la interpretación unívoca y absoluta. Sus sentencias, sus oraciones y sus canciones son literatura, esto es, discurso que se resiste al lugar común, que se sabe opaco, oscuro y sabe además que en esa opacidad reside su carácter espléndido. Y la posibilidad de comunicar(se) efectivamente, realmente, con otros hombres y mujeres que también aceptan las zonas vacías, inexplicables, que aceptan y saben que son otros, distintos de quienes se supone que son y de quienes quisieran o hubieran podido ser. Los personajes de la obra de Mutis creen en la comunicación tardía de la palabra escrita y la llevan a cabo incluso con nosotros, bastante más tarde aun, a través de un narrador que transcribe sus palabras, a la manera de un filólogo del romanticismo, aunque muy poco interesado en señalar o siquiera insinuar al lector las fuentes o el significado de aquello que muestra