Development of resonant cavity-based microwave filters for axion detection

[SPA] Esta tesis doctoral aborda varias investigaciones para la detección de axiones y para la mejora de comunicaciones satelitales mediante el uso de cavidades resonantes en tecnología guía de onda. El axión es una partícula hipotética teorizada para resolver el problema CP fuerte (Charge conjugation Parity symmetry) en la cromodinámica cuántica (QCD) y que, de existir, podría ser componente de la materia oscura. En esta línea, el desarrollo de detectores axiónicos de materia oscura, comúnmente denominados haloscopios, se ha encontrado en auge en los últimos 20 años. En este trabajo se han desarrollado diversos métodos para la mejora de estos haloscopios empleando estructuras basadas en subcavidades conectadas por irises. Por otro lado, es bien sabido que el espectro electromagnético en las comunicaciones por satélite se encuentra saturado debido a la alta demanda de radiocomunicaciones hoy en día. Además, el coste de puesta en órbita de un satélite crece exponencialmente con el peso abordo de éste, cuya reducción será clave en cualquier programa espacial. Así, en esta tesis se abordan diversos diseños de filtros paso banda en guía de onda para la optimización del peso, volumen y huella abordo de los futuros satélites de comunicaciones. El espectro frecuencial barrido por la comunidad axiónica en busca de la ansiada partícula (el axión) es cada día mayor y hace que exista una alta competencia para participar en esta búsqueda con detectores de altas prestaciones. Además, las condiciones extremas a las que debe ser sometido un detector de axiones de materia oscura para que se cumplan las condiciones de detección (temperaturas criogénicas, campo magnetoestático alto, etc.) complican aún más esta tarea. Algunos de los parámetros que rigen el rendimiento de un haloscopio basado en cavidades resonantes son su volumen, factor de calidad y factor de forma. Durante la elaboración de este trabajo se han diseñado, fabricado y caracterizado diversas topologías novedosas para la creación de estos detectores, optimizando los tres parámetros mencionados, consiguiendo resultados satisfactorios. Esta tesis doctoral ha sido realizada en el marco de trabajo del grupo axiónico RADES (Relic Axion Detector Exploratory System). Se han llevado a cabo tareas de investigación para la mejora del factor de calidad en estructuras fabricadas en las primeras etapas por este grupo experimental mediante la aplicación de diversos tratamientos, como la aplicación de soldaduras. Además de la optimización de los parámetros en haloscopios, estos necesitarán escanear un espectro de frecuencias, como se ha mencionado anteriormente, para lo cual se deberá implementar sistemas de sintonía que permita el cambio de frecuencia de resonancia y otros sistemas para el ajuste del acoplamiento de entrada / salida del sistema (otro de los parámetros críticos del detector). Existen dos tipos de sintonía frecuencial, mecánica y electrónica. Para los sistemas de sintonía mecánicos, se han realizado estudios del comportamiento de los prototipos fabricados cuando estos se abren mediante un corte vertical, lo cual cambiará su frecuencia de búsqueda del axión. Por otro lado, para los sistemas de sintonía electrónicos se han desarrollado diversos diseños para la introducción de materiales ferromagnéticos y ferroeléctricos, que cambiarán la frecuencia de operación mediante el cambio de permeabilidad y permitividad del medio, respectivamente, aplicando un cambio de voltaje o temperatura. Se ha hecho un estudio mucho más extenso para estos últimos. Los sistemas electrónicos permiten evitar ciertos problemas que ocurren en los de tipo mecánico, como pueden ser fallos de movimiento a temperaturas criogénicas o la falta de escalabilidad. Para los elementos ferroeléctricos, se ha llegado a un diseño novedoso que ha aportado gran valor a la comunidad científica para la aplicación de este tipo de materiales en cualquier haloscopio. Además, se han desarrollado sistemas de acoplamiento entre subcavidades con láminas ferroeléctricas, evitando la fabricación de irises, los cuales pueden dar problemas en ciertos sistemas. Para los sistemas de ajuste de acoplamiento de entrada / salida, se ha desarrollado un prototipo preliminar que ha aportado buenos resultados experimentales. Asimismo, se han llevado a cabo otras tareas de investigación para el desarrollo de otras técnicas de mejora de haloscopios. Una de ellas es la del rechazo de resonancias no deseados cerca del modo axiónico por medio de la combinación de varios puertos coaxiales con el método phase-matching, para el cual se han realizado diversas simulaciones y fabricaciones, extrayendo resultados positivos que hacen viable dicho método. Otros estudios secundarios han sido los de la implementación de QuBits para reducir la temperatura del sistema (parámetro clave para el rendimiento), el uso de elementos HTS (High Temperature Superconductor) para aumentar el factor de calidad, el diseño de haloscopios a frecuencias en las bandas UHF y W, y el análisis electromagnético del acoplamiento axion-photon en haloscopios mediante el método BI-RME (Boundary Integral-Resonant Mode Expasion) 3D. Finalmente, como spin-off del desarrollo de haloscopios, se han realizado diversos estudios para el diseño, fabricación, caracterización y mejora de filtros paso banda para comunicaciones satelitales empleando la misma tecnología (cavidades resonantes acopladas por irises en guía de onda). Se ha han desarrollado varios filtros evanescentes basados en impresión 3D o fabricación aditiva de bajo coste, y mecanizado CNC (Computer Numerical Control). A estos filtros se les ha aplicado un sistema de sintonía de tornillos que ha permitido la mejora de la respuesta eléctrica de filtrado. Por otro lado, se ha llevado a cabo el diseño de un filtro asimétrico doblado horizontalmente para la implementación de ceros de transmisión, consiguiente un alto rechazo fuera de la banda de paso. Estos filtros son gran valor para la comunidad científica ya que permiten avanzar en el estado del arte de filtros con altas prestaciones (bajo peso, volumen y huella) para comunicaciones satelitales. [ENG] This PhD thesis addresses several investigations for the detection of axions and for the improvement of satellite communications using resonant cavities in waveguide technology. The axion is a hypothetical particle theorized that could explain the strong CP problem (Charge conjugation Parity symmetry) in quantum chromodynamics (QCD) and which, if it exists, could be a component of dark matter. In this line, the development of axion dark matter detectors, commonly called haloscopes, has been booming in the last 20 years. In this work, several methods have been developed for the improvement of these haloscopes using structures based on subcavities coupled by irises. On the other hand, it is well known that the electromagnetic spectrum in satellite communications is saturated due to the high demand for radio communication systems. In addition, the cost of putting a satellite into orbit grows exponentially with the weight on board, the reduction of which will be key in any space program. Thus, this PhD thesis deals with different waveguide bandpass filter designs for optimizing the weight, volume, and on-board footprint of future communication satellites. The frequency spectrum swept by the axion community in search of the coveted particle is increasing day by day, which means that there is a high level of competition to develop high-performance detectors. In addition, the extreme conditions to which a dark matter axion detector must be subjected in order to meet the detection conditions (cryogenic temperatures, high magnetostatic field, etc.) further complicate this task. Some of the parameters that govern the performance of a haloscope based on resonant cavities are its volume, quality factor and form factor. During the development of this work, several novel topologies have been designed, manufactured, and characterized for the creation of these detectors, optimizing the three above-mentioned parameters, achieving satisfactory results. This PhD thesis has been carried out within the framework of the RADES (Relic Axion Detector Exploratory System) axion group. Research work has been carried out to improve the quality factor in structures manufactured in the first stages of this experimental group through the application of various treatments, such as soldering. In addition, as the axion mass is unknown, it is important to scan in frequency to search for the axion over a range as large as possible, as mentioned above, for which tuning systems must be implemented to allow resonant frequency shift and other arrangements for adjusting the input / output coupling of the system (another key haloscope parameter). There are two types of frequency tuning, mechanical and electronic. For mechanical tuning systems, studies have been carried out on the behaviour of the fabricated prototypes when they are opened by a vertical cut, which will change their axion search frequency. On the other hand, for electronic tuning systems, various designs have been developed for the introduction of ferromagnetic and ferroelectric materials, which will change the operating frequency by changing the permeability and permittivity of the medium, respectively, by applying a change of voltage or temperature. A much more extensive study has been made for the use of ferroelectric tuning systems. Electronic systems avoid certain problems that occur in mechanical systems, such as motion failure at cryogenic temperatures or lack of scalability. For ferroelectric elements, a novel design as been achieved which has brought great value to the scientific community for the application of this type of material in any haloscope. Also, coupling systems have been developed between subcavities with ferroelectric films, avoiding the need to manufacture irises, which can cause problems in certain systems. For the input / output coupling adjustment systems, a preliminary prototype has been developed which has provided good experimental results. Other research works have also been carried out on the development of other haloscope enhancement techniques. One of them is the rejection of unwanted resonances near the axion mode by means of the combination of several coaxial ports with the phase-matching method, for which several simulations and fabrications have been carried out, obtaining positive results that make this method feasible. Other secondary studies have been the implementation of QuBit devices to reduce the system temperature (another key parameter for haloscope performance), the use of HTS (High Temperature Superconductor) elements to increase the quality factor, the haloscope design at frequencies in the UHF and W bands, and the electromagnetic analysis of axion-photon coupling in haloscopes using the BI-RME (Boundary Integral-Resonant Mode Expansion) 3D method. Finally, as a spin-off from the development of haloscopes, several studies have been carried out for the design, manufacture, characterization, and improvement of bandpass filters for satellite communications using the same technology (resonant cavities coupled by irises in waveguide). Several evanescent filters based on 3D printing or low-cost additive manufacturing and CNC (Computer Numerical Control) machining have been developed. A screw tuning system has been applied to these filters to improve the electrical filtering response. On the other hand, the design of a horizontally folded asymmetric filter for the implementation of transmission zeros, to increase the rejection capabilities of the filter, has been carried out. These filters could be of great value to the scientific community as they allow to advance in the state of the art of high-performance filters (low weight, volume, and footprint) for satellite communications.Escuela Internacional de Doctorado de la Universidad Politécnica de CartagenaUniversidad Politécnica de CartagenaPrograma Doctorado en Tecnologías de la Información y las Comunicacione

Microwave Filter Design Using 3D Manufacturing Techniques for Space Applications

Las técnicas de fabricación aditivia se han desarrollado enormemente en los últimos años. Ello ha propiciado que empresas del sector espacial hayan puesto su interés en la posibilidad de utilizar estas técnicas para mejorar los dispositivos pasivos a embarcar en los satélites. El presente proyecto pretende evaluar estos aspectos, y fabricar algunos prototipos para evaluar las potencias prestaciones y uso en aplicaciones espaciales. El objetivo del proyecto será diseñar varios filtros para aplicaciones espaciales usando técnicas de fabricación 3D [1]. Nos centraremos en filtros paso-banda y paso-bajo combinando la tecnología guía-onda con piezas dieléctricas que serán fabricadas con técnicas de fabricación aditiva. El proyecto abarcará todas las fases, incluyendo el diseño de los dispositivos, la fabricación y caracterización eléctrica de los mismosEscuela Técnica Superior de Ingeniería de TelecomunicaciónUniversidad Politécnica de Cartagen

A comparative study of calibration methods for low-cost ozone sensors in IoT platforms

© 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes,creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.This paper shows the result of the calibration process of an Internet of Things platform for the measurement of tropospheric ozone (O 3 ). This platform, formed by 60 nodes, deployed in Italy, Spain, and Austria, consisted of 140 metal–oxide O 3 sensors, 25 electro-chemical O 3 sensors, 25 electro-chemical NO 2 sensors, and 60 temperature and relative humidity sensors. As ozone is a seasonal pollutant, which appears in summer in Europe, the biggest challenge is to calibrate the sensors in a short period of time. In this paper, we compare four calibration methods in the presence of a large dataset for model training and we also study the impact of a limited training dataset on the long-range predictions. We show that the difficulty in calibrating these sensor technologies in a real deployment is mainly due to the bias produced by the different environmental conditions found in the prediction with respect to those found in the data training phase.Peer ReviewedPostprint (author's final draft

Review of linear algebra and applications to data science

Lectures notes of the "Review of linear algebra and applications to data science" of the course SANS (Statistical Analysis of Networks and Systems) at Master in Innovation and Research in Informatics (MIRI) at FIB, UPC.2023/202

Graph signal reconstruction techniques for IoT air pollution monitoring platforms

Air pollution monitoring platforms play a very important role in preventing and mitigating the effects of pollution. Recent advances in the field of graph signal processing have made it possible to describe and analyze air pollution monitoring networks using graphs. One of the main applications is the reconstruction of the measured signal in a graph using a subset of sensors. Reconstructing the signal using information from neighboring sensors is a key technique for maintaining network data quality, with examples including filling in missing data with correlated neighboring nodes, creating virtual sensors, or correcting a drifting sensor with neighboring sensors that are more accurate. This paper proposes a signal reconstruction framework for air pollution monitoring data where a graph signal reconstruction model is superimposed on a graph learned from the data. Different graph signal reconstruction methods are compared on actual air pollution data sets measuring O3, NO2, and PM10. The ability of the methods to reconstruct the signal of a pollutant is shown, as well as the computational cost of this reconstruction. The results indicate the superiority of methods based on kernel-based graph signal reconstruction, as well as the difficulties of the methods to scale in an air pollution monitoring network with a large number of low-cost sensors. However, we show that the scalability of the framework can be improved with simple methods, such as partitioning the network using a clustering algorithm.This work is supported by the National Spanish funding PID2019-107910RB-I00, by regional project 2017SGR-990, and with the support of Secretaria d’Universitats i Recerca de la Generalitat de Catalunya i del Fons Social Europeu.Peer ReviewedPostprint (author's final draft

Review of probability theory

Lectures notes of the review of probability theory of the course SANS (Statistical Analysis of Networks and Systems) at Master in Innovation and Research in Informatics (MIRI) at FIB, UPC.2023/202

Machine Learning (ML) module

Lectures notes of the machine learning content of the course TOML (Topics on Optimization and Machine Learning) at Master in Innovation and Research in Informatics (MIRI) at FIB, UPC.2023/202

Volterra graph-based outlier detection for air pollution sensor networks

Today's air pollution sensor networks pose new challenges given their heterogeneity of low-cost sensors and high-cost instrumentation. Recently, with the advent of graph signal processing, sensor network measurements have been successfully represented by graphs depicting the relationships between sensors. However, one of the main problems of these sensor networks is their reliability, especially due to the inclusion of low-cost sensors, so the detection and identification of outliers is extremely important for maintaining the quality of the network data. In order to better identify the outliers of the sensors composing a network, we propose the Volterra graph-based outlier detection (VGOD) mechanism, which uses a graph learned from data and a Volterra-like graph signal reconstruction model to detect and localize abnormal measurements in air pollution sensor networks. The proposed unsupervised decision process is compared with other outlier detection methods, state-of-the-art graph-based methods and non-graph-based methods, showing improvements in both detection and localization of anomalous measurements, so that anomalous measurements can be corrected and malfunctioning sensors can be replaced.This work is supported by the National Spanish funding PID2019-107910RB-I00, by regional project 2017SGR-990, and with the support of Secretaria d’Universitats i Recerca de la Generalitat de Catalunya i del Fons Social Europeu.Peer ReviewedPostprint (author's final draft

Raw data collected from NO2, O3 and NO air pollution electrochemical low-cost sensors

Recently, the monitoring of air pollution by means of lowcost sensors has become a growing research field due to the study of techniques based on machine learning to improve the sensors’ data quality. For this purpose, sensors undergo a calibration process, where these are placed in-situ nearby a regulatory reference station. The data set explained in this paper contains data from two self-built low-cost air pollution nodes deployed for four months, from January 16, 2021 to May 15, 2021, at an official air quality reference station in Barcelona, Spain. The goal of the deployment was to have five electrochemical sensors at a high sampling rate of 0.5 Hz; two NO2 sensors, two O3 sensors, and one NO sensor. It should be noted that the reference stations publish air pollution data every hour, thus at a rate of 2.7 × 10-4 Hz. In addition, the nodes have also captured temperature and relative humidity data, which are typically used as correctors in the calibration of low-cost sensors. The availability of the sensors’ time series at this high resolution is important in order to be able to carry out analysis from the signal processing perspective, allowing the study of sensor sampling strategies, sensor signal filtering, and the calibration of low-cost sensors among others.This work was supported by National Spanish project PID2019-107910RB-I00, and regional project 2017SGR-990, and with the support of Secretaria d’Universitats i Recerca de la Generalitat de Catalunya i del Fons Social Europeu.Peer ReviewedPostprint (published version

Temporal pattern-based denoising and calibration for low-cost sensors in IoT monitoring platforms

The introduction of low-cost sensors (LCSs) in air quality Internet of Things (IoT) monitoring platforms presents the challenge of improving the quality of the data that these sensors provide. In this article, we propose two algorithms to perform denoising and calibration for LCSs used in IoT monitoring platforms. Sensors are first calibrated in situ using linear or nonlinear machine learning models that only take into account instantaneous measurements. The best calibration model is used to estimate the values measured by the sensor during the sensor deployment. To improve the values of the estimates produced by the in situ calibration model, we propose to take into account the temporal patterns present in signals, such as temperature or tropospheric ozone that have regular patterns, e.g., daily. The first method, which we call temporal pattern-based denoising (TPB-D), performs signal denoising by projecting the daily signals of the in situ calibrated LCS onto a subspace generated by the daily signals stored in a database taken by reference instruments. The second method, which we call temporal pattern-based calibration (TPB-C), considers that if we also have a reference instrument colocated to the LCSs over a period of time, we can correct with a linear mapping with regularization the daily LCS signals projected in the subspace produced by the reference database to be as similar as possible to the projected signals of the colocated reference instrument. The results show that the TPB-D improves the estimates made by in situ calibration by up to 10%–20%, while the TPB-C improves the estimates made by in situ calibration by up to 20%–40%.This work was supported in part by the National Spanish Funding under Grant PID2019-107910RB-I00 and in part by the Regional Project under Grant 2021 SGR 01059.Peer ReviewedPostprint (author's final draft