60 research outputs found
Structural Restricted Boltzmann Machine for image denoising and classification
Restricted Boltzmann Machines are generative models that consist of a layer
of hidden variables connected to another layer of visible units, and they are
used to model the distribution over visible variables. In order to gain a
higher representability power, many hidden units are commonly used, which, in
combination with a large number of visible units, leads to a high number of
trainable parameters. In this work we introduce the Structural Restricted
Boltzmann Machine model, which taking advantage of the structure of the data in
hand, constrains connections of hidden units to subsets of visible units in
order to reduce significantly the number of trainable parameters, without
compromising performance. As a possible area of application, we focus on image
modelling. Based on the nature of the images, the structure of the connections
is given in terms of spatial neighbourhoods over the pixels of the image that
constitute the visible variables of the model. We conduct extensive experiments
on various image domains. Image denoising is evaluated with corrupted images
from the MNIST dataset. The generative power of our models is compared to
vanilla RBMs, as well as their classification performance, which is assessed
with five different image domains. Results show that our proposed model has a
faster and more stable training, while also obtaining better results compared
to an RBM with no constrained connections between its visible and hidden units
Face recognition by means of advanced contributions in machine learning
Face recognition (FR) has been extensively studied, due to both scientific fundamental challenges and current and potential applications where human identification is needed. FR systems have the benefits of their non intrusiveness, low cost of equipments and no useragreement requirements when doing acquisition, among the most important ones.
Nevertheless, despite the progress made in last years and the different solutions proposed, FR performance is not yet satisfactory when more demanding conditions are required (different viewpoints, blocked effects, illumination changes, strong lighting states, etc). Particularly, the effect of such non-controlled lighting conditions on face images leads to one of the strongest distortions in facial appearance.
This dissertation addresses the problem of FR when dealing with less constrained illumination situations. In order to approach the problem, a new multi-session and multi-spectral face database has been acquired in visible, Near-infrared (NIR) and Thermal infrared (TIR) spectra,
under different lighting conditions.
A theoretical analysis using information theory to demonstrate the complementarities between different spectral bands have been firstly carried out. The optimal exploitation of the information provided by the set of multispectral images has been subsequently addressed by
using multimodal matching score fusion techniques that efficiently synthesize complementary meaningful information among different spectra.
Due to peculiarities in thermal images, a specific face segmentation algorithm has been required and developed. In the final proposed system, the Discrete Cosine Transform as dimensionality reduction tool and a fractional distance for matching were used, so that the cost in processing time and memory was significantly reduced. Prior to this classification task, a selection of the relevant frequency bands is proposed in order to optimize the overall system, based on identifying and maximizing independence relations by means of discriminability
criteria. The system has been extensively evaluated on the multispectral face database specifically performed for our purpose. On this regard, a new visualization procedure has been suggested in order to combine different bands for establishing valid comparisons and giving statistical information about the significance of the results. This experimental framework has more easily enabled the improvement of robustness against training and testing illumination mismatch. Additionally, focusing problem in thermal spectrum has been also addressed, firstly, for the more general case of the thermal images (or thermograms), and then for the case of facialthermograms from both theoretical and practical point of view. In order to analyze the quality of such facial thermograms degraded by blurring, an appropriate algorithm has been successfully developed.
Experimental results strongly support the proposed multispectral facial image fusion, achieving very high performance in several conditions. These results represent a new advance in providing a robust matching across changes in illumination, further inspiring highly accurate
FR approaches in practical scenarios.El reconeixement facial (FR) ha estat àmpliament estudiat, degut tant als reptes fonamentals científics que suposa com a les aplicacions actuals i futures on requereix la identificació de les persones. Els sistemes de reconeixement facial tenen els avantatges de ser no intrusius,presentar un baix cost dels equips d’adquisició i no la no necessitat d’autorització per part de l’individu a l’hora de realitzar l'adquisició, entre les més importants. De totes maneres i malgrat els avenços aconseguits en els darrers anys i les diferents solucions proposades, el rendiment del FR encara no resulta satisfactori quan es requereixen condicions més exigents (diferents punts de vista,
efectes de bloqueig, canvis en la il·luminació, condicions de llum extremes, etc.). Concretament, l'efecte d'aquestes variacions no controlades en les condicions d'il·luminació sobre les imatges facials condueix a una de les distorsions més accentuades sobre l'aparença
facial.
Aquesta tesi aborda el problema del FR en condicions d'il·luminació menys restringides. Per tal d'abordar el problema, hem adquirit una nova base de dades de cara multisessió i multiespectral en l'espectre infraroig visible, infraroig proper (NIR) i tèrmic (TIR), sota diferents condicions d'il·luminació. En primer lloc s'ha dut a terme una anàlisi teòrica utilitzant la teoria de la informació per demostrar la complementarietat entre les diferents bandes espectrals objecte d’estudi. L'òptim aprofitament de la informació proporcionada pel conjunt d'imatges multiespectrals s'ha abordat posteriorment mitjançant l'ús de tècniques de fusió de puntuació multimodals, capaces de sintetitzar de manera eficient el conjunt d’informació significativa complementària entre els diferents espectres. A causa de les característiques particulars de les imatges tèrmiques, s’ha requerit del desenvolupament d’un algorisme específic per la segmentació de les mateixes. En el sistema proposat final, s’ha utilitzat com a eina de reducció de la dimensionalitat de les imatges, la Transformada del Cosinus Discreta i una distància fraccional per realitzar les tasques de classificació de manera que el cost en temps de processament i de memòria es va reduir de
forma significa. Prèviament a aquesta tasca de classificació, es proposa una selecció de les bandes de freqüències més rellevants, basat en la identificació i la maximització de les relacions d'independència per mitjà de criteris discriminabilitat, per tal d'optimitzar el conjunt del
sistema. El sistema ha estat àmpliament avaluat sobre la base de dades de cara multiespectral, desenvolupada pel nostre propòsit. En aquest sentit s'ha suggerit l’ús d’un nou procediment de visualització per combinar diferents bandes per poder establir comparacions vàlides i donar informació estadística sobre el significat dels resultats. Aquest marc experimental ha permès més fàcilment la millora de la robustesa quan les condicions d’il·luminació eren diferents entre els processos d’entrament i test.
De forma complementària, s’ha tractat la problemàtica de l’enfocament de les imatges en l'espectre tèrmic, en primer lloc, pel cas general de les imatges tèrmiques (o termogrames) i posteriorment pel cas concret dels termogrames facials, des dels punt de vista tant teòric com
pràctic. En aquest sentit i per tal d'analitzar la qualitat d’aquests termogrames facials degradats per efectes de desenfocament, s'ha desenvolupat un últim algorisme. Els resultats experimentals recolzen fermament que la fusió d'imatges facials multiespectrals proposada assoleix un rendiment molt alt en diverses condicions d’il·luminació. Aquests resultats representen un nou avenç en l’aportació de solucions robustes quan es contemplen canvis en la il·luminació, i esperen poder inspirar a futures implementacions de sistemes de reconeixement facial precisos en escenaris no controlats.Postprint (published version
3D face recognition with wireless transportation
In this dissertation, we focus on two related parts of a 3D face recognition system with wireless transportation. In the first part, the core components of the system, namely, the feature extraction and classification component, are introduced. In the feature extraction component, range images are taken as inputs and processed in order to extract features. The classification component uses the extracted features as inputs and makes classification decisions based on trained classifiers. In the second part, we consider the wireless transportation problem of range images, which are captured by scattered sensor nodes from target objects and are forwarded to the core components (i.e., feature extraction and classification components) of the face recognition system. Contrary to the conventional definition of being a transducer, a sensor node can be a person, a vehicle, etc. The wireless transportation component not only brings flexibility to the system but also makes the “proactive” face recognition possible.
For the feature extraction component, we first introduce the 3D Morphable Model. Then a 3D feature extraction algorithm based on the 3D Morphable Model is presented. The algorithm is insensitive to facial expression. Experimental results show that it can accurately extract features. Following that, we discuss the generic face warping algorithm that can quickly extract features with high accuracy. The proposed algorithm is robust to holes, facial expressions and hair. Furthermore, our experimental results show that the generated features can highly differentiate facial images.
For the classification component, a classifier based on Mahalanobis distance is introduced. Based on the classifier, recognition performances of the extracted features are given. The classification results demonstrate the advantage of the features from the generic face warping algorithm.
For the wireless transportation of the captured images, we consider the location-based wireless sensor networks (WSN). In order to achieve efficient routing perfor¬mance, a set of distributed stateless routing protocols (PAGER) are proposed for wireless sensor networks. The loop-free and delivery-guaranty properties of the static version (PAGER-S) are proved. Then the performance of PAGER protocols are compared with other well-known routing schemes using network simulator 2 (NS2). Simulation results demonstrate the advantages of PAGER
Computationally efficient deformable 3D object tracking with a monocular RGB camera
182 p.Monocular RGB cameras are present in most scopes and devices, including embedded environments like robots, cars and home automation. Most of these environments have in common a significant presence of human operators with whom the system has to interact. This context provides the motivation to use the captured monocular images to improve the understanding of the operator and the surrounding scene for more accurate results and applications.However, monocular images do not have depth information, which is a crucial element in understanding the 3D scene correctly. Estimating the three-dimensional information of an object in the scene using a single two-dimensional image is already a challenge. The challenge grows if the object is deformable (e.g., a human body or a human face) and there is a need to track its movements and interactions in the scene.Several methods attempt to solve this task, including modern regression methods based on Deep NeuralNetworks. However, despite the great results, most are computationally demanding and therefore unsuitable for several environments. Computational efficiency is a critical feature for computationally constrained setups like embedded or onboard systems present in robotics and automotive applications, among others.This study proposes computationally efficient methodologies to reconstruct and track three-dimensional deformable objects, such as human faces and human bodies, using a single monocular RGB camera. To model the deformability of faces and bodies, it considers two types of deformations: non-rigid deformations for face tracking, and rigid multi-body deformations for body pose tracking. Furthermore, it studies their performance on computationally restricted devices like smartphones and onboard systems used in the automotive industry. The information extracted from such devices gives valuable insight into human behaviour a crucial element in improving human-machine interaction.We tested the proposed approaches in different challenging application fields like onboard driver monitoring systems, human behaviour analysis from monocular videos, and human face tracking on embedded devices
Computationally efficient deformable 3D object tracking with a monocular RGB camera
182 p.Monocular RGB cameras are present in most scopes and devices, including embedded environments like robots, cars and home automation. Most of these environments have in common a significant presence of human operators with whom the system has to interact. This context provides the motivation to use the captured monocular images to improve the understanding of the operator and the surrounding scene for more accurate results and applications.However, monocular images do not have depth information, which is a crucial element in understanding the 3D scene correctly. Estimating the three-dimensional information of an object in the scene using a single two-dimensional image is already a challenge. The challenge grows if the object is deformable (e.g., a human body or a human face) and there is a need to track its movements and interactions in the scene.Several methods attempt to solve this task, including modern regression methods based on Deep NeuralNetworks. However, despite the great results, most are computationally demanding and therefore unsuitable for several environments. Computational efficiency is a critical feature for computationally constrained setups like embedded or onboard systems present in robotics and automotive applications, among others.This study proposes computationally efficient methodologies to reconstruct and track three-dimensional deformable objects, such as human faces and human bodies, using a single monocular RGB camera. To model the deformability of faces and bodies, it considers two types of deformations: non-rigid deformations for face tracking, and rigid multi-body deformations for body pose tracking. Furthermore, it studies their performance on computationally restricted devices like smartphones and onboard systems used in the automotive industry. The information extracted from such devices gives valuable insight into human behaviour a crucial element in improving human-machine interaction.We tested the proposed approaches in different challenging application fields like onboard driver monitoring systems, human behaviour analysis from monocular videos, and human face tracking on embedded devices
Exploring quantum many-body systems from an entanglement and nonlocality perspective
Entanglement and non-local correlations give rise to unprecedented phenomena with no classical analogue. As a result, they have settled themselves as fundamental properties in the study of quantum many-body systems, as well as key resources for emerging quantum technologies. However, the lack for general and efficient criteria to characterize them in many-body systems poses many challenges, often intractable. Consequently, despite the growing interest in their properties, the role of entanglement and non-local correlations in many-body systems remains largely unexplored.
The subject of the present Thesis is to explore quantum many-body systems from an entanglement and non-local correlations perspective, aiming at expanding the interplay between quantum information processing and quantum many-body physics. We examine adequate properties, like symmetries, that allow us to delve into entanglement and non-local correlations in many-body systems of physical relevance. The original results that we present are achieved at the fundamental level, even though many practical methods that can be experimentally implemented stem from them.
First, we explore the complexity to characterize entanglement in simplified cases. In particular, we consider the separability problem for diagonal symmetric states. We establish a connection with the field of quadratic conic optimization that allows us to provide significant sufficient criteria. Furthermore, it allows us to prove that obtaining necessary and sufficient criteria remains an NP-hard problem, even for a case with such a simplified structure.
Second, the elusiveness of the characterization of entanglement motivates certification criteria for its detection, specially in the multipartite scenario. By means of non-local correlations, we provide device-independent certification criteria that characterizes the amount of entanglement present on a quantum many-body system. This type of certification does not rely on assumptions about the internal workings of the measuring device nor about the system itself. Moreover, by relying solely on non-local correlations, the criteria dismisses all the correlations that have a classical analogue, thus being a natural candidate as a certifier for emerging quantum technologies.
Third, we explore non-local correlations in the vicinity of quantum critical points, which are known to stabilize large-scale entanglement. We show the presence of non-local correlations across the phase diagram via a certain Bell inequality. Furthermore, we show that the Bell inequality is maximally violated at the quantum critical point, hinting at a possible connection between many-body Bell correlators and quantum phase transitions.
Fourth, we present a solution to the quantum marginal problem restricted to symmetric states. This allows to partially circumvent the inefficient representability inherent to the multipartite Hilbert space in cases of interest. In addition, we illustrate some of the applications that our solution brings on central quantum information problems. Namely, (i) as an undemanding and efficient variational method to optimize local Hamiltonians over symmetric states, (ii) to optimize few-body symmetric Bell inequalities over symmetric states and (iii) to explore which symmetric states cannot be self-tested solely from their marginals.
Finally, we conclude by presenting a methodology to derive two-body symmetric Bell inequalities for three-outcomes. These novel Bell inequalities are natural candidates to explore the role of non-local correlations on quantum phenomena tailored to qutrit or spin-1 many-body systems. We select a particular Bell inequality to characterize and show that it reveals non-local correlations in the ground state of many-body Hamiltonians physically relevant to, e.g., nuclear physics.: L'entrellaçament i les correlacions no-locals donen lloc a fenòmens sense precedents ni analogia clàssica. Aquests fenòmens els han portat a establir-se com a propietats primordials per a l'estudi de sistemes quàntics amb molts cossos, així com a recursos primordials per a les tecnologies quàntiques emergents. Tanmateix, la manca de criteris generals i eficients per caracteritzar-los en sistemes de molts cossos suposa molts reptes, sovint intractables. Per consegüent, tot i l'interès creixent en les seves propietats, el rol de l'entrellaçament i les correlacions no-locals en sistemes de molts cossos continuen, en gran part, inexplorats. L'objectiu d'aquesta Tesi és explorar sistemes quàntics de molts cossos des de la perspectiva de l'entrellaçament i les correlacions no-locals, amb la voluntat d'ampliar la reciprocitat entre els camps del processament d'informació quàntica i la física quàntica de molts cossos. Examinem propietats adequades, com ara simetries, que ens permeten investigar l'entrellaçament i les correlacions no-locals en sistemes de molts cossos i d'interès físic. Els resultats originals que presentem s'obtenen en l'àmbit fonamental, al mateix temps que es proposen un seguit de mètodes pràctics que permeten ser experimentalment implementats. En primer lloc, explorem la complexitat en caracteritzar l'entrellaça-ment inclús en casos simplificats. En particular, considerem el problema de la separabilitat en estats simètrics diagonals. Establim una connexió amb el camp d'optimització cònica quadràtica que ens permet proporcionar diversos criteris suficients de separabilitat. A més, ens permet demostrar que criteris necessaris i suficients segueixen sent un problema NP-hard, fins i tot per a un cas amb una estructura tan simplificada. En segon lloc, l'evasivitat de la caracterització de l'entrellaçament motiva criteris de certificació per a la seva detecció, especialment en l'escenari multipartit. Mitjançant correlacions no-locals, proporcionem criteris independents del dispositiu que caracteritzen la quantitat d'ent-rellaçament present en un sistema quàntic de molts cossos. Aquest tipus de certificació no es basa en suposicions sobre el funcionament intern del dispositiu de mesura ni del mateix sistema. A més, al basar-se únicament en correlacions no-locals el criteri descarta totes les correlacions que tenen un anàleg clàssic, sent així un candidat natural com a certificador de tecnologies quàntiques. En tercer lloc, explorem correlacions no-locals en l'entorn de punts crítics quàntics, coneguts per estabilitzar l'entrellaçament a gran escala. A través de desigualtats de Bell, mostrem la presència de correlacions no-locals al llarg del diagrama de fase d'un model d'espins. A més, mostrem que la desigualtat de Bell es viola màximament en el punt crític, donant indicis d'una possible connexió entre la violació de certes desigualtats de Bell i transicions de fase quàntiques. En quart lloc, presentem una solució pel problema del marginal quàntic restringit a estats simètrics. La solució ens permet eludir parcialment la ineficient representabilitat inherent a l'espai de Hilbert multipartit en casos d'interès. A més, il·lustrem algunes de les aplicacions que la solució ofereix en problemes centrals d'informació quàntica. Concretament, (i) com a mètode variacional poc exigent i eficaç que ofereix optimitzar Hamiltonians locals respecte estats simètrics, (ii) per optimitzar desigualtats de Bell de pocs cossos i simètriques respecte d'estats simètrics i (iii) per explorar quins estats simètrics no es poden auto-validar només a partir dels seus marginals. Finalment, concloem presentant una metodologia que permet obtenir desigualtats de Bell simètriques de pocs cossos amb tres possibles resultats de mesura. Aquestes noves desigualtats de Bell permeten explorar el rol de les correlacions no-locals en fenòmens quàntics específics per a sistemes de molts cossos formats per qutrits o amb àtoms d'espín-1. Seleccionem una desigualtat de Bell a caracteritzar i mostrem que detecta correlacions no-locals en l'estat fonamental d'Hamiltonians físicament rellevant en, e.g., física nuclear.El entrelazamiento y las correlaciones no-locales dan lugar a fenómenos
sin precedentes ni analogía clásica. Estos fenómenos les ha llevado a
establecerse como propiedades clave para el estudio de sistemas cuánticos
con muchos cuerpos, además de convertirse en recursos primordiales
para las tecnologías cuánticas emergentes. Sin embargo, la falta
de criterios generales y eficientes para caracterizarlos en sistemas de
muchos cuerpos suponen muchos retos, a menudo intratables. Por consiguiente, a pesar del creciente interés en sus propiedades, el rol del
entrelazamiento y las correlaciones no-locales en sistemas de muchos
cuerpos siguen, en gran parte, inexplorados.
El objetivo de esta Tesis es explorar sistemas cuánticos de muchos
cuerpos desde la perspectiva del entrelazamiento y las correlaciones
no-locales, con la voluntad de ampliar la sinergia entre el campo del
procesamiento de información cuántica y la física cuántica de muchos
cuerpos. Examinamos propiedades adecuadas, como simetrías, que nos
permiten investigar el entrelazamiento y las correlaciones no-locales en
sistemas de muchos cuerpos y de interés físico. Los resultados originales
que presentamos se obtienen en el ámbito fundamental, al mismo
tiempo que se proponen varios métodos prácticos que permiten ser
experimentalmente implementados.
En primer lugar, exploramos la complejidad en caracterizar el entrelazamiento
en casos simplificados. En particular, consideramos el problema de la separabilidad en estados simétricos diagonales. Establecemos una conexión con el campo de la optimización cónica cuadrática que nos permite demostrar que obtener criterios necesarios y suficientes sigue siendo un problema NP-hard, incluso para un caso con una estructura tan simplificada.
En segundo lugar, la evasividad de la caracterización del entrelazamiento
motiva criterios de certificación para su detección, especialmente
en el escenario multipartito. Mediante correlaciones no-locales,
proporcionamos criterios independientes del dispositivo que certifican
la cantidad de entrelazamiento presente en un sistema cuántico de muchos
cuerpos. Este tipo de certificación no se basa en suposiciones sobre el funcionamiento interno del dispositivo de medida ni del mismo sistema. Además, al basarse únicamente en correlaciones no-locales, el criterio descarta todas las correlaciones que tienen un análogo clásico, siendo así un candidato natural como certificador de tecnologías cuánticas.
En tercer lugar, exploramos correlaciones no-locales alrededor de puntos críticos cuánticos, de los cuáles es sabido que estabilizan el entrelazamiento a gran escala. A través de desigualdades de Bell, mostramos la presencia de correlaciones no-locales a lo largo del diagrama de fase de un modelo de espines. Además, mostramos que la desigualdad de Bell se viola máximamente en el punto crítico, dando indicios de una posible conexión entre la violación de ciertas desigualdades de Bell y transiciones de fase cuánticas.
En cuarto lugar, presentamos una solución para el problema del marginal cuántico restringido a estados simétricos. La solución nos permite eludir parcialmente la ineficiente representabilidad intrínseca del espacio de Hilbert en casos de interés. Además, ilustramos algunas de las aplicaciones que la solución ofrece en problemas centrales de información cuántica. Concretamente, (i) como método variacional poco exigente y eficaz que ofrece optimizar Hamiltonianos locales respecto a estados simétricos, (ii) para optimizar desigualdades de Bell de pocos cuerpos y simétricas respecto estados simétricos y (iii) para explorar qué estados simétricos no se pueden auto-validar sólo a partir de sus marginales
Finalmente, concluimos presentando una metodología que permite obtener desigualdades de Bell de pocos cuerpos y simétricas con tres posibles resultados de medida. Estas nuevas desigualdades de Bell permiten explorar el rol de las correlaciones no-locales en fenómenos cuánticos específicos para sistemas de muchos cuerpos formados por qutrits o con átomos de espín-1. Seleccionamos una desigualdad de Bell específica para caracterizar y mostramos que detecta correlaciones no-locales en el estado fundamental de Hamiltonianos físicamente relevante en, e.g., física nuclearPostprint (published version
Machine Learning Methods with Noisy, Incomplete or Small Datasets
In many machine learning applications, available datasets are sometimes incomplete, noisy or affected by artifacts. In supervised scenarios, it could happen that label information has low quality, which might include unbalanced training sets, noisy labels and other problems. Moreover, in practice, it is very common that available data samples are not enough to derive useful supervised or unsupervised classifiers. All these issues are commonly referred to as the low-quality data problem. This book collects novel contributions on machine learning methods for low-quality datasets, to contribute to the dissemination of new ideas to solve this challenging problem, and to provide clear examples of application in real scenarios
A Queer Politics of Imperceptibility: A Philosophy of Resistance to Contemporary Sexual Surveillance
This thesis journeys through a series of events to develop a concept of “imperceptibility” as a mode of resistance to contemporary sexual surveillance. The events I examine include biometric recognition of gender and race at airport security checkpoints, the heteropatriarchal colonial surveillance of Indigenous peoples at Standing Rock, various protest actions, and the political potentials of glitch art. Exploring their unexpected points of connection, my goal is to bring into view acts of resistance against sexual surveillance that already operate below and above the threshold of everyday perception.
The project advocates for a philosophy of resistance that underscores the political importance of creating new modes of existence. Rather than engaging in the problematic of devising a new model of subjectivity, I argue that what is needed to escape from contemporary systems of capture and control is to turn from the Self as the primary site of concern and affirm instead the potentials of becoming-imperceptible. Imperceptibility signals not invisibility, but the act of relinquishing identity in favour of moving toward becoming everybody/everything. Far from a homogenizing or unitary endeavour, I propose imperceptibility as a radical celebration of difference that surges a revolutionary desire for social transformation through interconnectedness.
Activating Gilles Deleuze and Félix Guattari’s pragmatic philosophy and style of writing, which emphasize multiple relations over binary oppositions, I introduce “a queer politics of imperceptibility” as a conceptual framework that takes a both/and approach to consider resistance. That is, I work with and between the tensions of feminist theories of recognition and Deleuze and Guattari’s nonrepresentational philosophy. I develop this framework in each chapter by mapping a constellation of interacting forces and affective intensities between bodies, both human and non-human. A Queer Politics of Imperceptibility makes an important intervention into the fields of feminist surveillance studies, posthumanism, affect theory, postcolonial theory and queer theory by revealing the ways in which imperceptible relations of resistance cascade into the political to generate new potentials to act in the world
Theory of ultrafast electron transfer from localized quantum states at surfaces .
190 p.The ability of materials to transfer electrons is a basic property controlling the functionality and performance of devices at the nanoscale. Of particular importance is the tranfor of electros at surfaces as a fundamental process in catalytic and photocatalytic applications. This work aims along these lines at a theoretical description of resonant charge injection at surfaces using a combination of density functional theory and Green's functions. A close comparison with available data from core-hole-clock experiments is maintained throughout the work and confirms the validity and predictive power of our first-principles approach. This is demonstrated on the basis of three prototypical systems where we study fundamental aspects of charge transfer, providing additional, often complementary information to the interpretation of the experiments. First, we present a detailed study of the effects of structural fluctuations on elastic charge transfer for isonicotinic acid adsorbed on rutile (110) in relation to photovoltaic applications. Second we explore spin-dependent charge injection from core-excited argon resonances on Co(0001) and Fe(110), with possible implications for spintronics. Third, we examine the directionality of charge transfer from sulfur related resonances at surfaces of layered 1T-TaS2 in the commensurate charge density wave phase.DIPC
CSIC
CICnanoGune
CFM
Marie Curie Action
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