This Thesis focuses on different aspects of quantum computation theory: adiabatic quantum algorithms, decoherence during the adiabatic evolution and quantum simulators. After an overview on the area of quantum computation and setting up the formal ground for the rest of the Thesis we derive a general error estimate for adiabatic quantum computing. We demonstrate that the first-order correction, which has frequently been used as a condition for adiabatic quantum computation, does not yield a good estimate for the computational error. Therefore, a more general criterion is proposed, which includes higher-order corrections and shows that the computational error can be made exponentially small – which facilitates significantly shorter evolution times than the first-order estimate in certain situations. Based on this criterion and rather general arguments and assumptions, it can be demonstrated that a run-time of order of the inverse minimum energy gap is sufficient and necessary. Furthermore, exploiting the similarity between adiabatic quantum algorithms and quantum phase transitions, we study the impact of decoherence on the sweep through a second-order quantum phase transition for the prototypical example of the Ising chain in a transverse field and compare it to the adiabatic version of Grover’s search algorithm. It turns out that (in contrast to first-order transitions) the impact of decoherence caused by a weak coupling to a rather general environment increases with system size (i.e., number of spins/qubits), which might limit the scalability of the system. Finally, we propose the use of electron systems to construct laboratory systems based on present-day technology which reproduce and thereby simulate the quantum dynamics of the Ising model and the O(3) nonlinear sigma model.

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The future is here. New digital, disruptive innovations are changing and affecting industries across society. And the emerging Quantum Computing (QC) industry is not an exception. Billions of dollars have been invested by actors such as governments, large enterprises like IBM and AWS, and by smaller to medium firms towards achieving a fully working QC-technology. Therefore, firms who are looking to adopt it must address the barriers that come with it. This thesis therefore explores what barriers, with the objective on key ones, that exist when firms are adopting QC-technology as a service into their business strategy. The geographical scope of this study is the European and North American industries. The applied method is qualitative and based on the methodology of grounded theory where six semi-structured interviews are carried out with key experts in the field . Furthermore, the analytical PESTLE-framework was used to systemically code and categorize the barriers found from the interviews to analyze the political, economic, social, technological, legal, and environmental factors connected to the research question. By using key experts from different parts of the industry and this framework, it resulted in a holistic view of the industry’s barriers. The findings of this study are that the QC-industry is still in its early era with 34 barriers of adoption identified and eight of them deemed to be the key ones because of their significance and frequency of mentions. The eight key barriers are QC-technology is costly, impatient investors, funding issues, lack of consistent revenue streams, lack of awareness from top management, insufficient ecosystem, lack of skilled labor and immature technology. The most important minor barriers of the other 26 include lack of standardization and benchmarks, lack of collaboration between certain geographical parties, misinformation from vendors and not using external advisors. Nonetheless, the QC-technology is on the up-rise and is projected to affect industries across the world. Firms in these industries must therefore learn to adopt to the dynamic changes that come with what the QC industry brings. Therefore again, it is the intention of this thesis to explore the key barriers and mitigation strategies to overcome them. / Framtiden är här. Nya digitala, disruptiva innovationer håller just nu på att förändra och påverka industrier över hela samhället. Den växande kvantdatorindustrin är inte ett undantagsfall. Flertalet miljarder dollar med målet att uppnå en fullt funktionell kvantdator har investerats av aktörer som stater, stora företag som IBM och AWS samt små till medelstora företag. Därför bör företag som kommer att påverkas av effekterna adressera barriärerna som finns. Den här uppsatsen undersöker därför vilka barriärer, med fokus på de essentiella, som existerar för företag när de ska adaptera kvantdatorteknologi som en service i deras affärsstrategi. Den geografiska omfattningen berör den nordamerikanska samt den europeiska marknaden. Metodiken som användes var ”Grounded theory”- metodologin där sex semi-strukturerade intervjuer utfördes med nyckelexperter i industrin. Fortsättningsvis så användes PESTLE-ramverket för att systematiskt koda samt kategorisera de identifierade barriärerna utifrån politiska-, ekonomiska-, sociala- , teknologiska-, legala- samt miljöaspekterna. Genom att ha erhållit data från nyckelexperter från olika delar av industrin samt använt ramverket så gav det en holistisk bild av industrins barriärer. Resultatet av studien är att kvantdatorindustrin är i ett tidigt skede med 34 barriärer identifierade och åtta av dem som anses vara de mest essentiella på grund av deras signifikans samt frekvens av omnämnanden. De åtta nyckelbarriärerna inkluderar att kvantdatorteknologin är dyr att investera i, otåliga finansiella investerare, finansieringsproblem, brist på konsistenta intäktsflöden, brist på medvetenhet av ledningen, bristfällande ekosystem, brist på kompetent personal och icke-mogen teknologi. De viktigaste mindre barriärerna utav de 26 inkluderar brist på standardisering samt riktmärken, brist på samarbete mellan vissa geografiska områden, felaktig information från industrin till köparna, samt att inte ta hjälp av externa rådgivare. Vidare, så är kvantdatorteknologin samt industrin i helhet i en uppgång och förväntat att förändra industrier över hela världen. Företagen i dessa industrier bör därför lära sig redan idag att adaptera sig till de dynamiska förändringarna som kvantdator industrin medför. Därför är syftet för det här examensarbetet att utforska nyckelbarriärerna och strategierna som i syfte för att överkomma dem.

<p> The Bias-Variance Trade-off, where restricting the size of a hypothesis class can limit the generalization error of a model, is a canonical problem in Machine Learning, and a particular issue for high-variance models like Neural Networks that do not have enough parameters to enter the interpolating regime. Regularization techniques add bias to a model to lower testing error at the cost of increasing training error. This paper applies quantum circuits as activation functions in order to regularize a Feed-Forward Neural Network. The network using Quantum Activation Functions is compared against a network of the same dimensions except using Rectified Linear Unit (ReLU) activation functions, which can fit any arbitrary function. The Quantum Activation Function network is then shown to have comparable training performance to ReLU networks, both with and without regularization, for the tasks of binary classification, polynomial regression, and regression on a multicollinear dataset, which is a dataset whose design matrix is rank-deficient. The Quantum Activation Function network is shown to achieve regularization comparable to networks with L2-Regularization, the most commonly used method for neural network regularization today, with regularization parameters in the range of λ ∈ [.1, .5], while still allowing the model to maintain enough variance to achieve low training error. While there are limitations to the current physical implementation of quantum computers, there is potential for future architecture, or hardware-based, regularization methods that leverage the aspects of quantum circuits that provide lower generalization error. </p>

<p>The recent groundbreaking demonstrations of quantum supremacy in noisy intermediate scale quantum (NISQ) computing era has triggered an intense activity in establishing finer boundaries between classical and quantum computing. In this dissertation, we use established techniques based on quantum Monte Carlo (QMC) to map quantum problems into probabilistic networks where the fundamental unit of computation, p-bit, is inherently probabilistic and can be tuned to fluctuate between ‘0’ and ‘1’ with desired probability. We can view this mapped network as a Boltzmann machine whose states each represent a Feynman path leading from an initial configuration of q-bits to a final configuration. Each such path, in general, has a complex amplitude, ψ which can be associated with a complex energy. The real part of this energy can be used to generate samples of Feynman paths in the usual way, while the imaginary part is accounted for by treating the samples as complex entities, unlike ordinary Boltzmann machines where samples are positive. This mapping of a quantum circuit onto a Boltzmann machine with complex energies should be particularly useful in view of the advent of special-purpose hardware accelerators known as Ising Machines which can obtain a very large number of samples per second through massively parallel operation. We also demonstrate this acceleration using a recently used quantum problem and speeding its QMC simulation by a factor of ∼ 1000× compared to a highly optimized CPU program. Although this speed-up has been demonstrated using a graph colored architecture in FPGA, we project another ∼ 100× improvement with an architecture that utilizes clockless analog circuits. We believe that this will contribute significantly to the growing efforts to push the boundaries of the simulability of quantum circuits with classical/probabilistic resources and comparing them with NISQ-era quantum computers. </p>

Tesis por compendio / [ES] En esta tesis doctoral se propone y evalúa un sistema para detectar señales débiles (weak signals) relacionadas con cambios futuros trascendentales. Si bien la mayoría de las soluciones conocidas se basan en el uso de datos estructurados, el sistema propuesto detecta cuantitativamente estas señales utilizando información heterogénea y no estructurada de fuentes científicas, periodísticas y de redes sociales. La predicción de nuevas tendencias en un medio tiene muchas aplicaciones. Por ejemplo, empresas y startups se enfrentan a cambios constantes en sus mercados que son muy difíciles de predecir. Por esta razón, el desarrollo de sistemas para detectar automáticamente cambios futuros significativos en una etapa temprana es relevante para que cualquier organización tome decisiones acertadas a tiempo. Este trabajo ha sido diseñado para obtener señales débiles del futuro en cualquier campo dependiendo únicamente del conjunto de datos de entrada de documentos. Se aplican técnicas de minería de textos y procesamiento del lenguaje natural para procesar todos estos documentos. Como resultado, se obtiene un mapa con un ranking de términos, una lista de palabras clave clasificadas automáticamente y una lista de expresiones formadas por múltiples palabras. El sistema completo se ha probado en cuatro sectores diferentes: paneles solares, inteligencia artificial, sensores remotos e imágenes médicas. Este trabajo ha obtenido resultados prometedores, evaluados con dos metodologías diferentes. Como resultado, el sistema ha sido capaz de detectar de forma satisfactoria nuevas tendencias en etapas muy tempranas que se han vuelto cada vez más importantes en la actualidad. La computación cuántica es un nuevo paradigma para una multitud de aplicaciones informáticas. En esta tesis doctoral también se presenta un estudio de las tecnologías disponibles en la actualidad para la implementación física de qubits y puertas cuánticas, estableciendo sus principales ventajas y desventajas, y los marcos disponibles para la programación e implementación de circuitos cuánticos. Con el fin de mejorar la efectividad del sistema, se describe un diseño de un circuito cuántico basado en máquinas de vectores de soporte (SVM) para la resolución de problemas de clasificación. Este circuito está especialmente diseñado para los ruidosos procesadores cuánticos de escala intermedia (NISQ) que están disponibles actualmente. Como experimento, el circuito ha sido probado en un computador cuántico real basado en qubits superconductores por IBM como una mejora para el subsistema de minería de texto en la detección de señales débiles. Los resultados obtenidos con el experimento cuántico muestran también conclusiones interesantes y una mejora en el rendimiento de cerca del 20% sobre los sistemas convencionales, pero a su vez confirman que aún se requiere un desarrollo tecnológico continuo para aprovechar al máximo la computación cuántica. / [CA] En aquesta tesi doctoral es proposa i avalua un sistema per detectar senyals febles (weak signals) relacionats amb canvis futurs transcendentals. Si bé la majoria de solucions conegudes es basen en l'ús de dades estructurades, el sistema proposat detecta quantitativament aquests senyals utilitzant informació heterogènia i no estructurada de fonts científiques, periodístiques i de xarxes socials. La predicció de noves tendències en un medi té moltes aplicacions. Per exemple, empreses i startups s'enfronten a canvis constants als seus mercats que són molt difícils de predir. Per això, el desenvolupament de sistemes per detectar automàticament canvis futurs significatius en una etapa primerenca és rellevant perquè les organitzacions prenguen decisions encertades a temps. Aquest treball ha estat dissenyat per obtenir senyals febles del futur a qualsevol camp depenent únicament del conjunt de dades d'entrada de documents. S'hi apliquen tècniques de mineria de textos i processament del llenguatge natural per processar tots aquests documents. Com a resultat, s'obté un mapa amb un rànquing de termes, un llistat de paraules clau classificades automàticament i un llistat d'expressions formades per múltiples paraules. El sistema complet s'ha provat en quatre sectors diferents: panells solars, intel·ligència artificial, sensors remots i imatges mèdiques. Aquest treball ha obtingut resultats prometedors, avaluats amb dues metodologies diferents. Com a resultat, el sistema ha estat capaç de detectar de manera satisfactòria noves tendències en etapes molt primerenques que s'han tornat cada cop més importants actualment. La computació quàntica és un paradigma nou per a una multitud d'aplicacions informàtiques. En aquesta tesi doctoral també es presenta un estudi de les tecnologies disponibles actualment per a la implementació física de qubits i portes quàntiques, establint-ne els principals avantatges i desavantatges, i els marcs disponibles per a la programació i implementació de circuits quàntics. Per tal de millorar l'efectivitat del sistema, es descriu un disseny d'un circuit quàntic basat en màquines de vectors de suport (SVM) per resoldre problemes de classificació. Aquest circuit està dissenyat especialment per als sorollosos processadors quàntics d'escala intermèdia (NISQ) que estan disponibles actualment. Com a experiment, el circuit ha estat provat en un ordinador quàntic real basat en qubits superconductors per IBM com una millora per al subsistema de mineria de text. Els resultats obtinguts amb l'experiment quàntic també mostren conclusions interessants i una millora en el rendiment de prop del 20% sobre els sistemes convencionals, però a la vegada confirmen que encara es requereix un desenvolupament tecnològic continu per aprofitar al màxim la computació quàntica. / [EN] In this doctoral thesis, a system to detect weak signals related to future transcendental changes is proposed and tested. While most known solutions are based on the use of structured data, the proposed system quantitatively detects these signals using heterogeneous and unstructured information from scientific, journalistic, and social sources. Predicting new trends in an environment has many applications. For instance, companies and startups face constant changes in their markets that are very difficult to predict. For this reason, developing systems to automatically detect significant future changes at an early stage is relevant for any organization to make right decisions on time. This work has been designed to obtain weak signals of the future in any field depending only on the input dataset of documents. Text mining and natural language processing techniques are applied to process all these documents. As a result, a map of ranked terms, a list of automatically classified keywords and a list of multi-word expressions are obtained. The overall system has been tested in four different sectors: solar panels, artificial intelligence, remote sensing, and medical imaging. This work has obtained promising results that have been evaluated with two different methodologies. As a result, the system was able to successfully detect new trends at a very early stage that have become more and more important today. Quantum computing is a new paradigm for a multitude of computing applications. This doctoral thesis also presents a study of the technologies that are currently available for the physical implementation of qubits and quantum gates, establishing their main advantages and disadvantages and the available frameworks for programming and implementing quantum circuits. In order to improve the effectiveness of the system, a design of a quantum circuit based on support vector machines (SVMs) is described for the resolution of classification problems. This circuit is specially designed for the noisy intermediate-scale quantum (NISQ) computers that are currently available. As an experiment, the circuit has been tested on a real quantum computer based on superconducting qubits by IBM as an improvement for the text mining subsystem in the detection of weak signals. The results obtained with the quantum experiment show interesting outcomes with an improvement of close to 20% better performance than conventional systems, but also confirm that ongoing technological development is still required to take full advantage of quantum computing. / Griol Barres, I. (2022). Modelling of a System for the Detection of Weak Signals Through Text Mining and NLP. Proposal of Improvement by a Quantum Variational Circuit [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/183029 / Compendio

Yes / This survey provides an insightful overview of recent advancements in facial recognition technology, mainly focusing on multi-modal face recognition and its applications in security biometrics and identity verification. Central to this study is the Sejong Face Database, among other prominent datasets, which facilitates the exploration of intricate aspects of facial recognition, including hidden and heterogeneous face recognition, cross-modality analysis, and thermal-visible face recognition. This paper delves into the challenges of accurately identifying faces under various conditions and disguises, emphasising its significance in security systems and sensitive sectors like banking. The survey highlights novel contributions such as using Generative Adversarial Networks (GANs) to generate synthetic disguised faces, Convolutional Neural Networks (CNNs) for feature extractions, and Fuzzy Extractors to integrate biometric verification with cryptographic security. The paper also discusses the impact of quantum computing on encryption techniques and the potential of post-quantum cryptographic methods to secure biometric systems. This survey is a critical resource for understanding current research and prospects in biometric authentication, balancing technological advancements with ethical and privacy concerns in an increasingly digital society. / European Union’s Horizon-Marie Skłodowska-Curie Actions (MSCA)-RISE-2019-2023, Marie Skłodowska-Curie, Research, and Innovation Staff Exchange (RISE), titled: Secure and Wireless Multimodal Biometric Scanning Device for Passenger Verification Targeting Land and Sea Border Control

<p dir="ltr">The limitations of the traditional von Neumann computing architecture, particularly evident in the slowdown of Moore's law, have spurred the development of alternative domain-specific computing paradigms. This dissertation explores novel materials-physics based solutions for two promising alternatives: quantum computing and probabilistic computing, with a specific focus on leveraging magnetic spin textures and their unique properties. We demonstrate that magnetic spin textures, with their inherent topology and chirality, offer distinctive advantages in addressing key challenges in both computing paradigms. These textures' ability to couple with various degrees of freedom, such as electrical, thermal, mechanical, and optical, makes them particularly suitable for hybrid device implementations. Our work presents four contributions to the field.</p><p dir="ltr">First, we propose a novel approach of using skyrmions --- topologically protected rigid-object like spin textures --- to nucleate and braid Majorana modes in topological superconductor-magnetic multilayer heterostructures. We show analytically and numerically that skyrmion--vortex bound pairs can be braided in experimentally relevant timescales. Inspired by circuit quantum electrodynamics methods, we propose a novel readout scheme based on the dispersive coupling between vortex confinement states and Majorana bound states. This work paves the way for experimentally demonstrating the non-Abelian statistics of Majorana bound states, which might be a crucial step towards the development of fault-tolerant topological quantum computers.</p><p dir="ltr">Second, we study thermal relaxation mechanisms and timescales of spin-split chiral antiferromagnets. The class of spin-split antiferromagnets, including altermagnets, have recently emerged as excellent candidates for ultra-fast and low-energy spintronics applications. Due the lack of dipolar order, they are unaffected by stray fields. However, the spin-split bands still offer electrical control and readout of these antiferromagnets unlike the conventional antiferromagnets. While a lot of promising phenomena in these materials has already been experimentally demonstrated, thermal relaxation mechanisms of such magnets remain unexplored. Using reaction rate theories and statistical physics tools, we study the thermal dynamics of chiral antiferromagnets. We show that these materials thermally relax at ultra-fast picosecond-order timescales. Further, by building on the analogy between XY magnets and current biased Josephson junctions, we propose a novel approach to electrically tune the thermal barrier in chiral antiferromagnets. Although such chiral antiferromagnets may not be suitable for non-volatile memory type of applications, they emerge as promising candidates for the building blocks of probabilistic computers.</p><p dir="ltr">We then turn our attention to the strongly correlated quantum system of quantum spin liquids. We show that spin textures exchange coupled to a Kitaev spin liquid (KSL) can induce emergent gauge fields on the Majorana fermions in the spin liquid. These emergent gauge fields may trap zero energy modes if they are able to thread a net flux through the KSL. We derive analytical expressions for the gauge fields in the presence of spin textures and outline the conditions to obtain a net flux. Zero energy Majorana fermion modes trapped on such spin textures may eventually be used for fault tolerant quantum computing.</p><p dir="ltr">Finally, in the last project, we bring the quantum and probabilistic computing paradigms together by proposing a quantum two level system as a sensor for the building blocks of a probabilistic computer. we show that quantum spin defects such as Nitrogen vacancy centers (NV) can be used as novel probes for characterizing probabilistic bits. We show that various NV sensing protocols can be leveraged to create a complete picture of this nascent magnet based probabilistic bits including their energy barrier and attempt times.</p><p dir="ltr">Our findings suggest that magnetic spin textures, particularly their topological and chiral properties, could provide crucial solutions to current challenges in alternative computing platforms. This work bridges the gap between materials physics, device physics and the applications in alternative computing platforms.</p>

Conventional computing faces a huge technical challenge as traditional transistors will soon reach their size limitations. This will halt progress in reaching faster processing speeds and to overcome this problem, require an entirely new approach. Quantum computing (QC) is a natural solution offering a route to miniaturisation by, for example, storing information in electron or nuclear spin states, whilst harnessing the power of quantum physics to perform certain calculations exponentially faster than its classical counterpart. However, QCs face many difficulties, such as, protecting the quantum-bit (qubit) from the environment and its irreversible loss through the process of decoherence. Hybrid systems provide a route to harnessing the benefits of multiple degrees of freedom through the coherent transfer of quantum information between them. In this thesis I show coherent qubit transfer between electron and nuclear spin states in a ¹⁵N@C₆₀ molecular system (comprising a nitrogen atom encapsulated in a carbon cage) and a solid state system, using phosphorous donors in silicon (Si:P). The propagation uses a series of resonant mi- crowave and radiofrequency pulses and is shown with a two-way fidelity of around 90% for an arbitrary qubit state. The transfer allows quantum information to be held in the nuclear spin for up to 3 orders of magnitude longer than in the electron spin, producing a ¹⁵N@C₆₀ and Si:P ‘quantum memory’ of up to 130 ms and 1.75 s, respectively. I show electron and nuclear spin relaxation (T₁), in both systems, is dominated by a two-phonon process resonant with an excited state, with a constant electron/nuclear T₁ ratio. The thesis further investigates the decoherence and relaxation properties of metal atoms encapsulated in a carbon cage, termed metallofullerenes, discovering that exceptionally long electron spin decoherence times are possible, such that these can be considered a viable QC candidate.

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