Public display of deposited theses

DOCTORAL DEGREE IN APPLIED MATHEMATICS

• VILAR ALGUERÓ, RICARD: QUANTUM ANALOGS OF CLASSICAL CODES
  
  Author: VILAR ALGUERÓ, RICARD
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN APPLIED MATHEMATICS
  Department: School of Mathematics and Statistics (FME)
  Mode: Normal
  Deposit date: 07/03/2025
  Deposit END date: 20/03/2025
  Thesis director: BALL MARKS, SIMEON MICHAEL
  Thesis abstract: The main focus of this thesis are stabilizer codes, a type of error-correcting code used to correct quantum information that has been corrupted by noise. We introduce several new general constructions of stabilizer codes. In particular we use one of the constructions to construct quantum cyclic redundancy check codes, an error-correcting code which is used in classical information to correct burst errors. We show how to use a quantum version of such codes to correct burst errors on systems of quantum bits. We include a geometric description of stabilizer codes, extending previous constructions which work only for the qubit case to quantum systems in which the quantum particles have local dimension p, where p is any prime number. Finally, we reduce the problem of ascertaining when a generalised Reed-Solomon code is contained in its Hermitian dual and therefore can be used to construct a stabilizer code. This reduction allows us to determine the shortest and longest length of generalised Reed-Solomon codes which are contained in their Hermitian dual, verifying a conjecture of Grassl and Rotteler.
  

DOCTORAL DEGREE IN AUTOMATIC CONTROL, ROBOTICS AND VISION

• DELMAS, GINGER: Linking Human Poses With Natural Language
  
  Author: DELMAS, GINGER
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN AUTOMATIC CONTROL, ROBOTICS AND VISION
  Department: Institute of Robotics and Industrial Informatics (IRI)
  Mode: Normal
  Deposit date: 10/03/2025
  Deposit END date: 21/03/2025
  Thesis director: MORENO NOGUER, FRANCESC D'ASSIS | WEINZAEPFEL, PHILIPPE
  Thesis abstract: Human pose is key to multiple human-centric applications, in a wide range of domains such as art (person depiction), sport (fitness coaching), robotics (skill teaching), entertainment (motion capture in movies, digital animation) or digitization (avatar design). In order to materialize such systems, researchers have designed deep learning models which address the related, underlying tasks of pose-guided image synthesis, 3D human pose estimation, human motion generation, mesh synthesis, pose prior production, and so forth.Until very recently, human pose had mostly been studied in conjunction with images. The field twitched with the arrival of efficient language models, which fostered the incorporation of linguistic in vision frameworks, and thereby powered multi-modal applications.This thesis fits into this dynamic. We aim to leverage Natural Language (NL) to bud human pose understanding in human-centric tasks. In contrast to prior endeavors, we juggle with static 3D human poses, images and detailed NL texts all together. We further explore novel multi-modal applications, requiring fine-grained understanding of the human pose.First, to alleviate the lack of data, we introduce new datasets linking 3D human poses with NL texts. We notably investigate two settings. One where the text is a description of the target pose, and another where the text provides modification instructions to reach the target pose from a source pose. These datasets result both from (i) the collection of crowd-sourced annotations, and (ii) the automatic, rule-based generation of texts, which consists in the incorporation of classified pose measurements into templates sentences. Next, we use these datasets to develop several cross-modal generation models like text-driven pose synthesis, pose captioning, text-guided pose editing and generation of textual posture feedback. Eventually, we connect 3D, text and images through a novel combinating framework, so as to derive a versatile, multi-modal pose representation, to be leveraged for downstream tasks akin to pose estimation or NL posture feedback from visual input.In summary, we tackle multiple machine learning tasks entailing human pose understanding, thanks to the connection of human pose and Natural Language.
  
• PÉREZ I GONZALO, RAÜL: End-to-end learning for wind turbine blades: from imagery data to defect repair recommendations
  
  Author: PÉREZ I GONZALO, RAÜL
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN AUTOMATIC CONTROL, ROBOTICS AND VISION
  Department: Institute of Industrial and Control Engineering (IOC)
  Mode: Normal
  Deposit date: 26/02/2025
  Deposit END date: 11/03/2025
  Thesis director: AGUDO MARTÍNEZ, ANTONIO
  Thesis abstract: The European Union's (EU) reliance on external energy sources underscores the urgent need for energy security and affordability, driving the transition to renewable energy with wind power as a key renewable solution. However, wind turbine operation and maintenance still account for 30% of energy production costs, due to their prolonged exposure to harsh environmental conditions. Timely defect detection and repair are critical, as turbines must often be halted during visual inspections and repairs. Streamlining the process from inspection to decision-making is essential to reduce downtime and operational costs.This thesis presents a comprehensive end-to-end blade assessment system designed to determine defect severity, quantify their impact on energy production, and deliver actionable repair recommendations. By enabling wind turbine owners to act proactively, this system helps minimize operational costs. The framework emphasizes efficient image transmission that preserves quality, followed by the generation of detailed blade assessments to establish a consistent and effective repair strategy.To this end, this project proposes first segmenting images to isolate blade regions, simplifying subsequent tasks through algorithms tailored for imagery acquired under diverse conditions. These include a Blade U-Net model, which introduces dense conditional-random-field regularization to enhance segmentation accuracy, and advanced post-processing involving iterative refinement through hole-filling and noise reduction via an unsupervised random forest. Two deep discriminant analysis frameworks integrate class separability and probabilistic modeling into robust non-linear architectures to derive precise defect boundaries, handle complex textures, and improve generalization across varied inspection data. Additional contributions include a modular region-growing classifier for efficient segmentation in data-scarce conditions and diffusion-based models with dual-space augmentation to improve generalization and robustness, leading to substantial superior performance than competing techniques. Together, these segmentation methods form the foundation for automated defect detection and diagnostics.In the second part, to address the challenge of handling large volumes of high-resolution inspection data, this work also presents a novel region-of-interest (ROI) image compression framework. Traditional methods often compromise critical defect information. The proposed framework leverages segmentation outputs to ensure high-fidelity compression in blade regions, employing lossless or high-quality lossy techniques while aggressively compressing non-relevant areas. Key innovations include multi-layer nested latent variable models for lossy coding and parallelized bits-back coding optimized for industrial-scale applications. These advancements achieve state-of-the-art performance while significantly reducing computational costs. By coupling compression with our proposed multi-task defect detection model, this approach supports timely and accurate diagnostics, ensuring minimal disruption to turbine operations.In summary, this thesis contributes a hierarchy of low-level to high-level algorithms designed to streamline wind turbine maintenance processes. The combination of advanced segmentation and compression enables a fully automated pipeline for blade defect assessment, encompassing defect localization, classification, and repair prioritization, directly improving energy efficiency by reducing downtime, optimizing maintenance schedules, and minimizing repair costs.
  

DOCTORAL DEGREE IN BIOMEDICAL ENGINEERING

• ZIVANIC, MILICA: Cold plasma-treated hydrogels for multimodal cancer therapy
  
  Author: ZIVANIC, MILICA
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN BIOMEDICAL ENGINEERING
  Department: Department of Materials Science and Engineering (CEM)
  Mode: Change of supervisor
  Deposit date: 10/03/2025
  Deposit END date: 21/03/2025
  Thesis director:
  Thesis abstract: Cold atmospheric plasma (hereon just plasma) is a weakly ionized gas that gained attention as a cost-efficient and well-tolerated cancer treatment that selectively targets the altered redox metabolism of malignant cells. The short penetration depth of direct plasma treatment limits its clinical applications to surface targets. Plasma-treated hydrogels (PTHs) emerge as vehicles for local delivery of therapeutic plasma-derived reactive oxygen and nitrogen species (RONS) to internal targets. To prepare a PTH, an aqueous solution containing low concentrations of polymers is exposed to plasma to enrich it with RONS and is then crosslinked into the three-dimensional hydrogel network entrapping RONS inside. Once in contact with the target, RONS can diffuse from PTH and, above a cell-specific threshold, cause irreversible damage and death to cancer cells. Importantly, PTHs could broaden the clinical application of plasma not only by acting as RONS vehicles but also by being a versatile physicochemical platform that can incorporate different bioactive polymers or drugs for combined therapeutic effects, as explored for the first time in this Thesis.This Thesis proposes and follows an iterative workflow cycle for the development and characterization of PTHs. Here, alginate was chosen as a biopolymer for the preparation of PTHs, due to its biocompatibility, relevance, and versatility in biomedical research, as well as the ability to crosslink under mild conditions. In the first place, an optimized protocol for the preparation of alginate-based PTHs was identified, in order to ensure high retention of therapeutic RONS during the crosslinking process and obtain an injectable, shear-thinning formulation useful for minimally-invasive delivery and shape-adaptability of the PTH. Before this Thesis, biological characterization of PTHs was limited to cancer cytotoxicity reports. Here, the ability of a PTH to induce immunogenic cell death was demonstrated for the first time. As a result, PTH-treated osteosarcoma cells were increasingly phagocytized when co-cultured with immature dendritic cells derived from human monocytes isolated from healthy blood donors. Following the initial physicochemical and biological characterization, the feasibility and efficacy of incorporating a secondary therapeutic modality to the PTH were investigated. For this, a bioactive polymer or a chemotherapeutic drug was introduced into the alginate PTH formulation to achieve biological effects beyond or in synergy with plasma-derived RONS. Importantly, these effects were studied in a relevant model: an in ovo cancer model, where three-dimensional and vascularized tumors were grown on the membrane of a fertilized chicken egg (in ovo). This enabled the assessment of cancer cells in an environment more similar to a native, clinical one. In ovo tumor models emerge as cost- and time-effective models and can help replace, reduce, and refine in vivo experiments in preclinical research. In contrast to mono-therapy with PTH or drug alone, which showed no effect in ovo, a single administration of PTH-drug co-therapy could diminish osteosarcoma tumor weight and the expression of a protein linked to treatment resistance.Altogether, the work presented in this PhD Thesis helped characterize and establish PTHs within the plasma community as a novel modality that can broaden the clinical application of plasma. Furthermore, it provided a proof of concept that PTHs can be used as versatile dual platforms for multimodal cancer management.
  

DOCTORAL DEGREE IN CONSTRUCTION ENGINEERING

• RAMONELL CAZADOR, CARLOS: Graph-driven digital twins as assistants to bridge maintenance
  
  Author: RAMONELL CAZADOR, CARLOS
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN CONSTRUCTION ENGINEERING
  Department: Department of Civil and Environmental Engineering (DECA)
  Mode: Normal
  Deposit date: 10/03/2025
  Deposit END date: 21/03/2025
  Thesis director: CHACÓN FLORES, ROLANDO ANTONIO
  Thesis abstract: Bridges are vital components of transport infrastructure networks which are facing a widespread lack of resilience due to aging and changing environmental conditions. Finding more efficient methods for monitoring bridge networks and effectively planning their maintenance is crucial for maintaining reasonable serviceability levels. Simultaneously, digital twins are emerging across industries as dynamic digital replicas of physical assets. These are continuously updated with information from their physical counterparts and serve as the foundation for digital tools that enhance workflows in decision-making processes throughout the lifecycle of any product.This dissertation translates the concept of digital twins to the bridge maintenance domain and presents a framework for developing graph-driven digital twin systems to assist bridge managers in tracking the state of their asset portfolio.For this purpose, two different proof-of-concept systems are presented: System A and System B. Both systems are cloud-based, modular, and use graphs to integrate multiple data sources describing the bridges, their context, and relevant maintenance information. The systems are tested with real data corresponding to two demonstration cases of road and railway bridges in the Spanish infrastructure network. Through these demonstrators, the digital twin systems are developed to integrate BIM, GIS, sensor time-series data, and data related to the results of monitoring processes that is structured according to regional standards.System A focuses on hosting digital twins of individual bridges. It uses a labelled property graph (LPG) to interconnect IFC data with IoT sensor data and the results from visual inspections and load tests. Data integration is achieved by matching GUIDs of data contained the graph with data stored in the different databases and systems connected. The implementation of the system is demonstrated through a web-based digital twin platform, containing applications that allow visualizing and interacting with contextualized inspection and load test data.System B focuses on interconnecting multiple bridge digital twins within the same network. It employs a knowledge graph built from Resource Description Framework (RDF)-based graphs and a set of ontologies. The system integrates geographical data according to INSPIRE data models, IFC models, and data from visual inspections. The system presents a data management approach based on strata, which manage and compartmentalize information subsets, and implements the information containers for linked document delivery (ICDD) standard for exchanging graph data with linked documents. The system is demonstrated through a set of fictitious scenarios that simulate interactions between bridge administrators and third parties.Through these systems, this dissertation demonstrates the usefulness of graph technologies in developing digital twins of bridges that are aligned with current industry standards and practices. It emphasizes the advantages of the Knowledge Graph-based approach for simplifying interactions with connected applications, enabling decoupled application development, and enhancing the system scalability and expandability with new datasets. Notwithstanding, real implementation of these systems requires further validation and use cases, as well as collaboration among system developers, administrators, academia, and industry stakeholders to generate a coherent digital ecosystem that enhances the efficiency and productivity of bridge maintenance practices.
  

DOCTORAL DEGREE IN ELECTRICAL ENGINEERING

• AL HANAINEH, WAEL HASAN AHMAD: Designing and Development of Secure Protection Strategies for Distribution Network Integrated with Distributed Energy Resources
  
  Author: AL HANAINEH, WAEL HASAN AHMAD
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN ELECTRICAL ENGINEERING
  Department: Department of Electrical Engineering (DEE)
  Mode: Article-based thesis
  Deposit date: 10/03/2025
  Deposit END date: 21/03/2025
  Thesis director: MATAS ALCALA, JOSE | GUERRERO ZAPATA, JOSEP MARIA
  Thesis abstract: Global electricity generation increasingly incorporates Distributed Generation (DG) resources, such as solar and wind, into distribution systems (DS), offering benefits like improved reliability, power quality, rapid integration, and reduced payback periods, while lowering greenhouse gas emissions. However, their integration presents challenges, including overvoltage, voltage fluctuations, and imbalances caused by improper synchronization with the grid. DGs alter short-circuit currents, necessitating updates to protection relay settings. As DG penetration rises, distribution networks become more complex, requiring advanced protection systems to handle bidirectional power flows, which challenge existing schemes. Inverter-based DGs, such as solar and wind, generate lower fault currents due to inverter power electronics, diminishing the effectiveness of traditional fault detection methods, leading to potential protection blinding or false tripping. These challenges highlight the need for precise fault detection, accurate localization, and rapid protective responses. Disconnecting DGs during faults is increasingly undesirable, requiring innovative protection schemes to minimize unnecessary disconnections and address limitations like fault resistance, pre-fault load conditions, and noise interference. Traditional fault location techniques, often computationally intensive, struggle with accuracy, prolonging restoration times and increasing downtime, further emphasizing the need for advanced fault protection systems. Total Harmonic Distortion (THD) analysis has proven effective for fault detection in systems with complex harmonic profiles caused by DG integration. Faults induce increased harmonic distortion, making THD monitoring a valuable indicator. Despite its promise, protection systems for grids with high DG penetration, especially those using inverter-based DGs, are underexplored, and existing protection algorithms rarely incorporate THD. To address this, three novel protection systems utilizing grid voltage harmonic content for fault detection and localization in medium-voltage (MV) DS are proposed. The first system combines THD measurements with voltage amplitude and zero-sequence components using a finite state machine (FSM)-based algorithm. It focuses on third harmonic (triple-n) components, unique to inverter neutral points and unaffected by other grid harmonics. Fault-induced voltage dips excite harmonic components, amplifying THD, making it an effective fault indicator. THD is calculated using the Multiple Second Order Generalized Integrator (MSOGI) method. However, this system relies on communication channels, which could fail, limiting its robustness. To mitigate this, a two-layered protection system is introduced. The first layer employs the SOGI-FLL grid monitoring technique, optimizing computational efficiency by reducing the number of required SOGIs while maintaining accurate THD calculations. Fault detection is achieved by filtering the THD signal and comparing pre-fault and fault-time averages, with significant deviations indicating faults. The second layer implements a communication-less fault localization algorithm based on positive and negative voltage sequence components to determine fault symmetry. This approach enables each protection device (PD) to operate independently, ensuring reliable fault localization even without communication, albeit with slightly slower detection times compared to communication-based methods. To enhance overall reliability, especially during communication failures, a third system, priority system, is proposed. It integrates the two-layered protection, with the first layer as the primary fault detection and communication-based trip signal initiator. If communication fails, the second layer provides backup protection by analyzing voltage sequence components locally. The effectiveness of these systems is validated against different protection method under various conditions.
  

DOCTORAL DEGREE IN ENVIRONMENTAL ENGINEERING

• BERGAS MASSÓ, ELISA: Modelling the atmospheric iron cycle in a changing climate
  
  Author: BERGAS MASSÓ, ELISA
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN ENVIRONMENTAL ENGINEERING
  Department: Department of Civil and Environmental Engineering (DECA)
  Mode: Normal
  Deposit date: 26/02/2025
  Deposit END date: 11/03/2025
  Thesis director: PEREZ GARCIA-PANDO, CARLOS | GONÇALVES AGEITOS, MARIA
  Thesis abstract: Iron is a ubiquitous element that plays a critical role in the Earth system. It is an essential micronutrient required by most organisms for vital processes such as respiration, photosynthesis, and nitrogen fixation. Consequently, iron bioavailability is crucial, particularly in aquatic ecosystems, where approximately one-third of open ocean waters are iron-limited, restricting the biological activity of microorganisms. This shapes ocean productivity and affects the ocean's ability to capture atmospheric carbon dioxide. Understanding and quantifying the atmospheric supply of bioavailable iron to the ocean is critical, especially in the context of human-induced climate change.Despite its significance, knowledge gaps remain regarding the atmospheric iron cycle and its implications for ocean biogeochemistry. Uncertainties persist, for instance, in the contributions of key sources such as dust, biomass burning, and fossil fuel combustion to bioavailable iron deposition, the influence of anthropogenic activities on future iron supply, and the interactions between atmospheric iron deposition and marine ecosystems.This Thesis seeks to address these gaps by proposing the following objectives: (1) to evaluate the relative contributions of different sources and processes to soluble iron deposition under the present climate; (2) to characterize the extent and magnitude of bioavailable iron’s effects on surface ocean ecosystems; (3) to quantify changes in soluble iron deposition across past, present, and future climates; and (4) to constrain the impacts of future fire activity, underrepresented in commonly used emission datasets, on soluble iron deposition and ocean biogeochemistry.To achieve these objectives, the EC-Earth3-Iron model is used; an Earth System Model that incorporates advanced iron emission and solubilization mechanisms, as well as the latest emission inventories. Conducted simulations across pre-industrial, present-day, and future climates quantify soluble iron deposition and explore its sensitivity to uncertainties in future socioeconomic pathways and dust and fire emissions. Additionally, comparisons between present-day modeled deposition fields and satellite observations provide insights into the links between atmospheric iron deposition and surface ocean productivity.This work's findings provide novel insights into the atmospheric iron cycle and its implications for ocean biogeochemistry. This includes a detailed description of present-day soluble iron fluxes and their spatial distribution. This analysis reveals that non-dust sources, such as biomass burning and fossil fuel combustion, contribute over 75% of soluble iron deposition in iron-limited regions like the Southern Ocean and equatorial Pacific during certain seasons. These present-day estimates are further analyzed to highlight the impact of pulsed deposition events on global ocean biogeochemistry, with widespread positive responses in satellite-derived surface chlorophyll concentrations observed in the days following major iron input events. Another key finding is the sensitivity of soluble iron deposition to aerosol acidity and organic ligands, with simulations showing that socioeconomic trends have significantly altered deposition fluxes since the Industrial Revolution and will likely continue to do so until the century's end. Additionally, improved estimates of future wildfire emissions indicate significant changes in the patterns of soluble iron deposition, suggesting an approximate 20% increase in the North Atlantic under certain future scenarios.This work enhances the community’s understanding of the atmospheric iron cycle and its role in regulating ocean productivity. It also underscores the importance of improving the representation of atmospheric iron processes in Earth System Models to better predict future climate scenarios, while outlining pathways for future research.
  

DOCTORAL DEGREE IN MARINE SCIENCES

• RAYA RODRIGÁLVAREZ, VANESA MARIA: Spatial and temporal dynamics of larval fish communities in relation to environmental variability in the NW Mediterranean
  
  Author: RAYA RODRIGÁLVAREZ, VANESA MARIA
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN MARINE SCIENCES
  Department: Department of Civil and Environmental Engineering (DECA)
  Mode: Normal
  Deposit date: 10/03/2025
  Deposit END date: 21/03/2025
  Thesis director: SABATÉS FREIJÓ, ANA MARIA
  Thesis abstract: The early developmental stages of fish, eggs and larvae, found in the planktonic environment are subject to a high mortality. Thus, the study of larval survival has been a key issue in fisheries science since the early 20th century. Spatial patterns in the larval fish communities are influenced by a complex array of environmental processes that interacts with fish biology at different temporal and spatial scales. These processes include those of large scale, such as climate patterns and seasonal and interannual environmental variability, which determine adults’ distribution and their spawning strategies. At local and short time scale, larval fish communities are shaped by the hydrodynamics that influence fish larval dispersal and retention, and by biologic factors, such as food concentration and predation, that ultimately determine their survival.This thesis characterises the structure of the larval fish community in summer and winter in the Catalan coast (NW Mediterranean), an area with a wide array of environmental conditions and high hydrodynamic activity. The aim is to understand its spatial and interannual variability in response to changes in environmental conditions, including oceanographic variables and hydrodynamic processes. Within the context of climate change, the thesis describes long-term changes in the structure of the summer larval fish communities and aims to understand the interactions between larvae of established species and species that are expanding northwards in the area.To investigate the influence of winter environmental conditions on the structure of fish larval communities, two winters, 2017 and 2018, with contrasting environmental conditions were compared. 2017 was mild, while 2018 was more severe, with intense vertical mixing and deep-water formation and cascading events that enhanced shelf-slope water exchanges. Differences in the structure of larval fish community were found in relation to shelf-slope water exchange processes.A high spatial heterogeneity in larval fish communities was detected in the summers of 2003, 2004 and 2012, related to environmental factors, such as the continental shelf structure, latitudinal difference in surface temperature, primary productivity, and stratification level. Hydrodynamic structures such as instabilities of the Northern Current and anticyclonic eddies, also played an important role in the configuration of these communities.In summer, over three decades, 1980s, 2000s and 2010s, an increase in sea water temperature and a decrease in chlorophyll were detected. Changes in the composition and abundance of the larval fish community were also detected. These were mainly due to the presence of warm water species in the area for the first time, or to their increase in abundance, in the 2000s in relation to the northward expansion of the adults' range. Other species showed a decline in abundance over time, probably due to the decrease in chlorophyll.This work quantitatively compared the survival chances for larvae of E. encrasicolus (a established species) and S. aurita (a species expanding northwards). To this aim, a new method, the Box-Balance Model, was developed to evaluate the role of hydrodynamic structures in their mortality. The model revealed that despite the warming trend would contribute to the expansion of S. aurita, it has not yet developed an adaptation strategy as successful as that of E. encrasicolus, a well-established species in the area.
  

DOCTORAL DEGREE IN MECHANICAL, FLUIDS AND AEROSPACE ENGINEERING

• MORENO MARTÍN, SIRO: Collocation methods for the synthesis of graceful robot motions
  
  Author: MORENO MARTÍN, SIRO
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN MECHANICAL, FLUIDS AND AEROSPACE ENGINEERING
  Department: Department of Mechanical Engineering (EM)
  Mode: Normal
  Deposit date: 10/03/2025
  Deposit END date: 21/03/2025
  Thesis director: CELAYA LLOVER, ENRIC | ROS GIRALT, LLUIS
  Thesis abstract: Graceful motion can be loosely defined as the one we observe in natural movements executed by animals and humans, which are characterized by being agile, efficient, and fluid. The generation of graceful robot motions is typically sought through the minimization of cost functions involving not only path length, but also aspects related to smoothness, like the time derivative of acceleration, called jerk, or that of the controls. A widely used approach to compute optimal trajectories is through direct collocation, a technique that converts the continuous-time optimal control problem into a finite-dimensional NLP problem. Collocation proceeds by discretizing the trajectory using so-called collocation points, and imposing the dynamics constraints at such points. The formulation of most collocation methods, however, assumes that the system is governed by a first order ODE, whereas robotic systems are typically described by second or higher order ODEs. As a result, the usual practice is to initially convert those ODEs into first order form via introducing new variables, and adding new equations that link these variables with their integral counterparts. An often overlooked effect of this transformation is that it generates inconsistencies between the trajectory of each variable and that of its time derivative. This is so because a collocation method only imposes the differential relationships at the collocation points, but not in between such points. A closer examination of this effect reveals that the dynamic equations, which should be satisfied in the collocation points, are actually violated in them, despite apparently having been enforced. This thesis introduces new collocation methods designed to overcome these problems. Specifically, we develop improved versions of the most popular piecewise and pseudospectral collocation schemes, including the trapezoidal and Hermite-Simpson methods, as well as the LG, LGR, and LGL methods. The new algorithms are able to treat differential equations of arbitrary order M ≥ 1 without having to convert them into first order form. In all of them, the trajectory obtained for each variable coincides exactly with the time derivative of its corresponding integral variable, and the dynamic constraints are satisfied accurately at the collocation points. These properties allow a drastic reduction of the dynamics error of the obtained trajectories in many cases, meaning that the governing equations are better respected along the continuous time horizon of the problem. Our methods also provide trajectories that are smoother than those of conventional ones, and easily treat variables such as jerk or the time derivative of the controls in the cost function. An hp adaptive refinement algorithm is also proposed to combine the benefits of our piecewise and pseudospectral methods so as to speed up convergence to the solutions.
  

DOCTORAL DEGREE IN PHOTONICS

• BEATTIE EIZAGUIRRE, EDUARDO: Single rare earth ions for quantum computing nodes
  
  Author: BEATTIE EIZAGUIRRE, EDUARDO
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN PHOTONICS
  Department: Institute of Photonic Sciences (ICFO)
  Mode: Normal
  Deposit date: 10/03/2025
  Deposit END date: 21/03/2025
  Thesis director: DE RIEDMATTEN, HUGUES
  Thesis abstract: Despite decades of research, practical quantum computing and long-distance quantum communication remain elusive, hindered by significant challenges in current platforms. Single rare earth ions (SREI) in the solid state offer a promising alternative, with potential to form quantum computing nodes containing around 100 highly connected qubits capable of photonic networking. Nanoparticles are ideal for this system, as they enable high doping concentrations for strong interactions while maintaining the required spectral distinguishability.SREI experiments benefit from optical cavities that enhance emission via the Purcell effect. The open-access Fabry–Perot fiber cavity, formed by a fiber-tip micromirror and a planar or fiber mirror, is particularly versatile: a wide range of emitters can be integrated on the mirror surface, optical access is easy via the fiber, and three-dimensional tunability is possible. This flexibility has enabled studies across various quantum emitters and 2D materials.This thesis presents our work developing the SREI platform using nanoparticles in fiber cavities. It begins with an introduction to quantum computing, quantum communication with quantum repeaters, and rare earth ions as a basis for quantum computers, along with an overview of our experimental design. A review of background knowledge follows, covering optical cavities, the Purcell effect, the optical Bloch equations, and single-photon light statistics.The absence of commercial nanopositioners suitable for controlling our fiber cavity led us to design our own. This positioner enabled the first detection of single ions in nanoparticles. We studied the ⁴I15/2 → ⁴I13/2 transition at 1535 nm in 20 ppm erbium-doped 150 nm Y₂O₃ nanoparticles, and identified an ion with excellent spectral stability, a linewidth of 3.8(3) MHz, and a g(2)(0) compatible with a perfect single emitter.We then developed a significantly improved second positioner with 2.5 pm RMS stability, 130 µm × 130 µm XY scan range, and MHz-rate cavity modulation, all at 1.65 K in a closed-cycle cryostat. The broad potential of fiber cavities enhances this device's impact, marking it as one of the thesis's main contributions.Equipped with this improved positioner, we proceeded with a new experiment to detect interactions between single ions. We studied the ³H₄ → ¹1D₂ transition at 619 nm in two sets of praseodymium-doped Y₂O₃ nanoparticles, but were so far unable to observe any praseodymium emission in the cavity. To diagnose why this was happening, we performed additional experiments with a confocal microscope, which confirmed the presence of praseodymium in a majority of objects and found the absorption resonance near where we expected.The thesis ends with conclusions and future directions, including emission shaping and a novel microscopy technique. A closing reflection on this work and recent breakthroughs in the field paints a promising future for quantum information technologies.
  
• LI, GENG: Fourier Transform Infrared Spectroscopy of Twisted Bilayer Graphene
  
  Author: LI, GENG
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN PHOTONICS
  Department: Institute of Photonic Sciences (ICFO)
  Mode: Normal
  Deposit date: 10/03/2025
  Deposit END date: 21/03/2025
  Thesis director: KOPPENS, FRANK
  Thesis abstract: The goal of this thesis is to probe the infrared optical response of twisted bilayer graphene (TBG) using Fourier transform infrared spectroscopy (FTIR). First, I used a commercial FTIR to measure the TBG in the mid-infrared range at room temperature. I improved the device fabrication technique and fabricated the TBG devices with a large area and simultaneously a low inhomogeneity. I observe that the TBG has abundant optical absorption features originating from the interband transitions that are uniquely determined by the twist angle. Then, I want to probe the interband transition of the TBG that lies in the terahertz range, which evolves the flat band of the TBG that hosts strongly correlated effects. I built a homemade FTIR that works in both the mid-infrared and terahertz range. I wired the cryostat carefully and achieved an electrical noise level approaching the Johnson noise limit. By guiding the light from the FITR into the cryostat, I successfully measured the exciton states in the Bernal bilayer graphene device over a broad spectral range, demonstrating that the system is ready for future experimental study of TBG.
  

DOCTORAL DEGREE IN SIGNAL THEORY AND COMMUNICATIONS

• HERNÁNDEZ CHULDE, CARLOS EFRÉN: Software defined networking for autonomous and secure optical networks
  
  Author: HERNÁNDEZ CHULDE, CARLOS EFRÉN
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN SIGNAL THEORY AND COMMUNICATIONS
  Department: Department of Signal Theory and Communications (TSC)
  Mode: Normal
  Deposit date: 04/03/2025
  Deposit END date: 17/03/2025
  Thesis director: CASELLAS REGI, RAMON | MARTINEZ RIVERA, RICARDO VICTOR
  Thesis abstract: The increasing complexity and demands of modern telecommunications networks necessitate the development of autonomous and secure systems to ensure efficient, reliable, and secure communications. The integration of advanced technologies such as Artificial Intelligence (AI) and Machine Learning (ML) together with Quantum Key Distribution (QKD) into optical networks addresses these needs. This integration enables the creation of networks that can efficiently automate their operations while ensuring the highest standards of security. In this context, this thesis explores the use of Software Defined Networking (SDN) for the advancement of autonomous and secure optical networks, in particular Elastic Optical Networks (EONs). The research focuses on enhancing network efficiency and security to meet the growing complexity and demands for high-capacity, low-latency, and secure communications.The PhD thesis investigates the application of ML, specifically Deep Reinforcement Learning (DRL) and Graph Neural Networks (GNN) to tackle key challenges in the management and optimization of EONs. The primary goal is to develop autonomous and intelligent solutions for dynamic service provisioning, resource allocation, and spectrum management. A significant contribution of this work is the development of novel DRL-based approaches for Routing and Spectrum Assignment (RSA). These methods are designed to adaptively manage network resources in real-time, overcoming the limitations of traditional, static RSA algorithms. By considering latency as a key factor, the DRL-based RSA mechanism ensures the efficient provisioning of latency-sensitive applications and improves overall network performance metrics, such as latency and throughput. The thesis also examines the dynamic provisioning and optimal placement of Virtual Network Functions (VNFs) using DRL and GNNs. This combination of technologies enables a more efficient mapping of resource requirements to the physical infrastructure, facilitating scalable and flexible network management systems.The research also includes an experimental validation of the proposed solutions. A proof-of-concept (PoC) was implemented to demonstrate the integration of DRL models within an SDN control plane framework. This involved externalizing path computation to a dedicated entity that assists the SDN controller in the path and spectrum selection function. The experimental results confirmed the practical applicability of the DRL approach in supporting selected control functions in operational EON infrastructures.Furthermore, the research explores the coexistence of Continuous Variable Quantum Key Distribution (CV-QKD) and classical channels within EONs, which is essential for ensuring secure communications in the quantum computing era. To address the challenge of noise interference from high-power classical channels on sensitive quantum channels, the thesis introduces dynamic spectrum allocation strategies leveraging SDN. These strategies optimize the use of spectrum resources and minimize noise interference, ensuring secure and efficient operation of the integrated network.In summary, this thesis provides significant advancements in the field of autonomous and secure optical networks by integrating advanced ML techniques, contributing to the development of agile, high-capacity, reliable, and secure EONs for future telecommunications.
  

DOCTORAL DEGREE IN THEORY AND HISTORY OF ARCHITECTURE

• LIZÁRRAGA SÁNCHEZ, SALVADOR: Bacardí Tultitlán, México. Mies van der Rohe
  
  Author: LIZÁRRAGA SÁNCHEZ, SALVADOR
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN THEORY AND HISTORY OF ARCHITECTURE
  Department: Department of History and Theory of Architecture and Communication Techniques (THATC)
  Mode: Normal
  Deposit date: 03/03/2025
  Deposit END date: 14/03/2025
  Thesis director: GARCIA ESTEVEZ, CAROLINA BEATRIZ | ROVIRA GIMENO, JOSE MARIA | ROVIRA GIMENO, JOSE MARIA
  Thesis abstract: This thesis focuses on the office building for Bacardí y Cía S. A. in Tultitlán, Mexico, which Mies van der Rohe and his team designed and built from 1958 to 1961. Several Mexican companies – Knoll Internacional de México S. A., Constructora Maya, Campos hermanos and SACMAG de México– were involved in the process. For its construction, Mies’ architects –Gene Summers, Jan Lippert and Friedrich Wagner– made dozens of trips from Chicago to Tultitlán, while Mies visited Mexico only once. The thesis has two main objects of study. The first is the archive of the building, which contains about a thousand documents related to the Mexican building stored in the Mies van der Rohe archive at MoMA –hundreds of letters, telegrams, photographs, sketches and plans. The second is the architecture itself, whose peculiar materiality is contrasted with the information in the archive.The Tultitlán building is placed on the margins of the history of Mexican architecture, of Mies' history and, therefore, of Western architectural history. However, by extracting the object from that marginal position and forcing it to take a central position, it drags with it an entire architectural culture and forces the hegemonic discourses of those histories to reconstruct themselves, or at least to be questioned. The unprejudiced dissection of the archive and its building puts to the test historian Manfredo Tafuri's dictum that positioning oneself at “a particular angle of observation allows facts mute in themselves to be forced to become eloquent.” Among others, the archive forces us to place ourselves in the particular angle of vision of its secondary characters in order to understand them as principal and eloquent; from the foreshortening of a marginal city for the history of Western architecture that shows us that it became actually an international center; in the standpoint of a technological and constructive reality that allowed the materialization of a Mies building, but with methods different from those of a rich country; among many others. The research does not hide an inevitable conflict between the “historical word” of our present and that of the documents of another era -because the letters, plans, publications and films used in this research were created in a reality that no longer exists-. In other words, on the one hand, the documents were forced to speak in a language unknown to them –ours– and, at the same time, they were allowed to speak freely, without trying to hide their contradictions for the sake of a supposed historical or scientific congruence acceptable for the present. The collision of times forced to seek support in other languages, disciplines and characters –from Florence Schust Knoll and Lina Bo, to popular office cinema– to make intelligible the transnational context that allowed the existence of the objects of study of this thesis: the archive of the Bacardi offices in Tultitlán and its architecture.