627 research outputs found

    LIPIcs, Volume 251, ITCS 2023, Complete Volume

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    LIPIcs, Volume 251, ITCS 2023, Complete Volum

    Investigating the learning potential of the Second Quantum Revolution: development of an approach for secondary school students

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    In recent years we have witnessed important changes: the Second Quantum Revolution is in the spotlight of many countries, and it is creating a new generation of technologies. To unlock the potential of the Second Quantum Revolution, several countries have launched strategic plans and research programs that finance and set the pace of research and development of these new technologies (like the Quantum Flagship, the National Quantum Initiative Act and so on). The increasing pace of technological changes is also challenging science education and institutional systems, requiring them to help to prepare new generations of experts. This work is placed within physics education research and contributes to the challenge by developing an approach and a course about the Second Quantum Revolution. The aims are to promote quantum literacy and, in particular, to value from a cultural and educational perspective the Second Revolution. The dissertation is articulated in two parts. In the first, we unpack the Second Quantum Revolution from a cultural perspective and shed light on the main revolutionary aspects that are elevated to the rank of principles implemented in the design of a course for secondary school students, prospective and in-service teachers. The design process and the educational reconstruction of the activities are presented as well as the results of a pilot study conducted to investigate the impact of the approach on students' understanding and to gather feedback to refine and improve the instructional materials. The second part consists of the exploration of the Second Quantum Revolution as a context to introduce some basic concepts of quantum physics. We present the results of an implementation with secondary school students to investigate if and to what extent external representations could play any role to promote students’ understanding and acceptance of quantum physics as a personal reliable description of the world

    Advances and Applications of DSmT for Information Fusion. Collected Works, Volume 5

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    This fifth volume on Advances and Applications of DSmT for Information Fusion collects theoretical and applied contributions of researchers working in different fields of applications and in mathematics, and is available in open-access. The collected contributions of this volume have either been published or presented after disseminating the fourth volume in 2015 in international conferences, seminars, workshops and journals, or they are new. The contributions of each part of this volume are chronologically ordered. First Part of this book presents some theoretical advances on DSmT, dealing mainly with modified Proportional Conflict Redistribution Rules (PCR) of combination with degree of intersection, coarsening techniques, interval calculus for PCR thanks to set inversion via interval analysis (SIVIA), rough set classifiers, canonical decomposition of dichotomous belief functions, fast PCR fusion, fast inter-criteria analysis with PCR, and improved PCR5 and PCR6 rules preserving the (quasi-)neutrality of (quasi-)vacuous belief assignment in the fusion of sources of evidence with their Matlab codes. Because more applications of DSmT have emerged in the past years since the apparition of the fourth book of DSmT in 2015, the second part of this volume is about selected applications of DSmT mainly in building change detection, object recognition, quality of data association in tracking, perception in robotics, risk assessment for torrent protection and multi-criteria decision-making, multi-modal image fusion, coarsening techniques, recommender system, levee characterization and assessment, human heading perception, trust assessment, robotics, biometrics, failure detection, GPS systems, inter-criteria analysis, group decision, human activity recognition, storm prediction, data association for autonomous vehicles, identification of maritime vessels, fusion of support vector machines (SVM), Silx-Furtif RUST code library for information fusion including PCR rules, and network for ship classification. Finally, the third part presents interesting contributions related to belief functions in general published or presented along the years since 2015. These contributions are related with decision-making under uncertainty, belief approximations, probability transformations, new distances between belief functions, non-classical multi-criteria decision-making problems with belief functions, generalization of Bayes theorem, image processing, data association, entropy and cross-entropy measures, fuzzy evidence numbers, negator of belief mass, human activity recognition, information fusion for breast cancer therapy, imbalanced data classification, and hybrid techniques mixing deep learning with belief functions as well

    Interaction of elastomechanics and fluid dynamics in the human heart : Opportunities and challenges of light coupling strategies

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    Das menschliche Herz ist das hochkomplexe Herzstück des kardiovaskulären Systems, das permanent, zuverlässig und autonom den Blutfluss im Körper aufrechterhält. In Computermodellen wird die Funktionalität des Herzens nachgebildet, um Simulationsstudien durchzuführen, die tiefere Einblicke in die zugrundeliegenden Phänomene ermöglichen oder die Möglichkeit bieten, relevante Parameter unter vollständig kontrollierten Bedingungen zu variieren. Angesichts der Tatsache, dass Herz-Kreislauf-Erkrankungen die häufigste Todesursache in den Ländern der westlichen Hemisphäre sind, ist ein Beitrag zur frühzeit- igen Diagnose derselben von großer klinischer Bedeutung. In diesem Zusammenhang können computergestützte Strömungssimulationen wertvolle Einblicke in die Blutflussdynamik liefern und bieten somit die Möglichkeit, einen zentralen Bereich der Physik dieses multiphysikalischen Organs zu untersuchen. Da die Verformung der Endokardoberfläche den Blutfluss antreibt, müssen die Effekte der Elastomechanik als Randbedingungen für solche Strömungssimulationen berücksichtigt werden. Um im klinischen Kontext relevant zu sein, muss jedoch ein Mittelweg zwischen dem Rechenaufwand und der erforderlichen Genauigkeit gefunden werden, und die Modelle müssen sowohl robust als auch zuverlässig sein. Daher werden in dieser Arbeit die Möglichkeiten und Herausforderungen leichter und daher weniger komplexer Kopplungsstrategien mit Schwerpunkt auf drei Schlüsselaspekten bewertet: Erstens wird ein auf dem Immersed Boundary-Ansatz basierender Fluiddynamik-Löser implementiert, da diese Methode mit einer sehr robusten Darstellung von bewegten Netzen besticht. Die grundlegende Funktionalität wurde für verschiedene vereinfachte Geometrien verifiziert und zeigte eine hohe Übereinstimmung mit der jeweiligen analytischen Lösung. Vergleicht man die 3D-Simulation einer realistischen Geometrie des linken Teils des Herzens mit einem körperangepassten Netzbeschreibung, so wurden grundlegende globale Größen korrekt reproduziert. Allerdings zeigten Variationen der Randbedingungen einen großen Einfluss auf die Simulationsergebnisse. Die Anwendung des Lösers zur Simulation des Einflusses von Pathologien auf die Blutströmungsmuster ergab Ergebnisse in guter Übereinstimmung mit Literaturwerten. Bei Simulationen der Mitralklappeninsuffizienz wurde der rückströmende Anteil mit Hilfe einer Partikelverfolgungsmethode visualisiert. Bei hypertropher Kardiomyopathie wurden die Strömungsmuster im linken Ventrikel mit Hilfe eines passiven Skalartransports bewertet, um die lokale Konzentration des ursprünglichen Blutvolumens zu visualisieren. Da in den vorgenannten Studien nur ein unidirektionaler Informationsfluss vom elas- tomechanischen Modell zum Strömungslöser berücksichtigt wurde, wird die Rückwirkung des räumlich aufgelösten Druckfeldes aus den Strömungssimulationen auf die Elastomechanik quantifiziert. Es wird ein sequenzieller Kopplungsansatz eingeführt, um fluiddynamische Einflüsse in einer Schlag-für-Schlag-Kopplungsstruktur zu berücksichtigen. Die geringen Abweichungen im mechanischen Solver von 2 mm verschwanden bereits nach einer Iteration, was darauf schließen lässt, dass die Rückwirkungen der Fluiddynamik im gesunden Herzen begrenzt ist. Zusammenfassend lässt sich sagen, dass insbesondere bei Strömungsdynamiksimula- tionen die Randbedingungen mit Vorsicht gewählt werden müssen, da sie aufgrund ihres großen Einflusses die Anfälligkeit der Modelle erhöhen. Nichtsdestotrotz zeigten verein- fachte Kopplungsstrategien vielversprechende Ergebnisse bei der Reproduktion globaler fluiddynamischer Größen, während die Abhängigkeit zwischen den Lösern reduziert und Rechenaufwand eingespart wird

    The long-range Falicov-Kimball model and the amorphous Kitaev model: Quantum many-body systems I have known and loved

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    Large systems of interacting objects can give rise to a rich array of emergent behaviours. Make those objects quantum and the possibilities only expand. Interacting quantum many-body systems, as such systems are called, include essentially all physical systems. Luckily, we don't usually need to consider this full quantum many-body description. The world at the human scale is essentially classical (not quantum), while at the microscopic scale of condensed matter physics we can often get by without interactions. Strongly correlated materials, however, do require the full description. Some of the most exciting topics in modern condensed matter fall under this umbrella: the spin liquids, the fractional quantum Hall effect, high temperature superconductivity and much more. Unfortunately, strongly correlated materials are notoriously difficult to study, defying many of the established theoretical techniques within the field. Enter exactly solvable models, these are interacting quantum many-body systems with extensively many local symmetries. The symmetries give rise to conserved charges. These charges break the model up into many non-interacting quantum systems which are more amenable to standard theoretical techniques. This thesis will focus on two such exactly solvable models. The first, the Falicov-Kimball (FK) model is an exactly solvable limit of the famous Hubbard model which describes itinerant fermions interacting with a classical Ising background field. Originally introduced to explain metal-insulator transitions, it has a rich set of ground state and thermodynamic phases. Disorder or interactions can turn metals into insulators and the FK model features both transitions. We will define a generalised FK model in 1D with long-range interactions. This model shows a similarly rich phase diagram to its higher dimensional cousins. We use an exact Markov Chain Monte Carlo method to map the phase diagram and compute the energy resolved localisation properties of the fermions. This allows us to look at how the move to 1D affects the physics of the model. We show that the model can be understood by comparison to a simpler model of fermions coupled to binary disorder. The second, the Kitaev Honeycomb (KH) model, was the one of the first solvable 2D models with a Quantum Spin Liquid (QSL) ground state. QSLs are generally expected to arise from Mott insulators, when frustration prevents magnetic ordering all the way to zero temperature. The QSL state defies the traditional Landau-Ginzburg-Wilson paradigm of phases being defined by local order parameters. It is instead a topologically ordered phase. Recent work generalising non-interacting topological insulator phases to amorphous lattices raises the question of whether interacting phases like the QSLs can be similarly generalised. We extend the KH model to random lattices with fixed coordination number three generated by Voronoi partitions of the plane. We show that this model remains solvable and hosts a chiral amorphous QSL ground state. The presence of plaquettes with an odd number of sides leads to a spontaneous breaking of time reversal symmetry. We unearth a rich phase diagram displaying Abelian as well as a non-Abelian QSL phases with a remarkably simple ground state flux pattern. Furthermore, we show that the system undergoes a phase transition to a conducting thermal metal state and discuss possible experimental realisations.Open Acces

    LIPIcs, Volume 261, ICALP 2023, Complete Volume

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    LIPIcs, Volume 261, ICALP 2023, Complete Volum

    Histograms: An educational eye

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    Many high-school students are not able to draw justified conclusions from statistical data in histograms. A literature review showed that most misinterpretations of histograms are related to difficulties with two statistical key concepts: data and distribution. The review also pointed to a lack of knowledge about students’ strategies when solving histogram tasks. As the literature provided little guidance for the design of lesson materials, several studies were conducted in preparation. In a first study, five solution strategies were found through qualitative analysis of students’ gazes when solving histograms and case-value plot tasks. Quantitative analysis of several histogram tasks through a mathematical model and a machine learning algorithm confirmed these results, which implied that these strategies could reliably and automatically be identified. Literature also suggested that dotplot tasks can support students’ learning to interpret histograms. Therefore, gazes on histogram tasks were compared before and after students solved dotplot tasks. The "after" tasks contained more gazes associated with correct strategies and fewer gazes associated with incorrect strategies. Although answers did not improve significantly, students’ verbal descriptions suggest that some students changed to a correct strategy. Newly designed materials thus started with dotplot tasks. From the previous studies, we conjectured that students lacked embodied experiences with actions related to histograms. Designed from an embodied instrumentation perspective, the tested materials provide starting points for scaling up. Together, the studies address the knowledge gaps identified in the literature. The studies contribute to knowledge about learning histograms and use in statistics education of eye-tracking research, interpretable models and machine learning algorithms, and embodied instrumentation design

    From visuomotor control to latent space planning for robot manipulation

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    Deep visuomotor control is emerging as an active research area for robot manipulation. Recent advances in learning sensory and motor systems in an end-to-end manner have achieved remarkable performance across a range of complex tasks. Nevertheless, a few limitations restrict visuomotor control from being more widely adopted as the de facto choice when facing a manipulation task on a real robotic platform. First, imitation learning-based visuomotor control approaches tend to suffer from the inability to recover from an out-of-distribution state caused by compounding errors. Second, the lack of versatility in task definition limits skill generalisability. Finally, the training data acquisition process and domain transfer are often impractical. In this thesis, individual solutions are proposed to address each of these issues. In the first part, we find policy uncertainty to be an effective indicator of potential failure cases, in which the robot is stuck in out-of-distribution states. On this basis, we introduce a novel uncertainty-based approach to detect potential failure cases and a recovery strategy based on action-conditioned uncertainty predictions. Then, we propose to employ visual dynamics approximation to our model architecture to capture the motion of the robot arm instead of the static scene background, making it possible to learn versatile skill primitives. In the second part, taking inspiration from the recent progress in latent space planning, we propose a gradient-based optimisation method operating within the latent space of a deep generative model for motion planning. Our approach bypasses the traditional computational challenges encountered by established planning algorithms, and has the capability to specify novel constraints easily and handle multiple constraints simultaneously. Moreover, the training data comes from simple random motor-babbling of kinematically feasible robot states. Our real-world experiments further illustrate that our latent space planning approach can handle both open and closed-loop planning in challenging environments such as heavily cluttered or dynamic scenes. This leads to the first, to our knowledge, closed-loop motion planning algorithm that can incorporate novel custom constraints, and lays the foundation for more complex manipulation tasks

    Information limits of imaging through highly diffusive materials using spatiotemporal measurements of diffuse photons

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    Conventional medical imaging instruments are bulky, expensive, and use harmful ionising radiation. Combining ultrafast single-photon detectors and pulsed laser sources at optical wavelengths has the potential to offer inexpensive, safe, and potentially wearable alternatives. However, photons at optical wavelengths are strongly scattered by biological tissue, which corrupts direct imaging information about regions of absorbing interactions below the tissue surface. The work in this thesis studies the potential of measuring indirect imaging information by resolving diffuse photon measurements in space and time. The practical limits of imaging through highly diffusive material, e.g., biological tissue, is explored and validated with experimental measurements. The ill-posed problem of using the information in diffuse photon measurements to reconstruct images at the limits of the highly diffusive regime is tackled using probabilistic machine learning, demonstrating the potential of migrating diffuse optical imaging techniques beyond the currently accepted limits and underlining the importance of uncertainty quantification in reconstructions. The thesis is concluded with a challenging biomedical optics experiment to transmit photons diametrically through an adult human head. This problem was tackled experimentally and numerically using an anatomically accurate Monte Carlo simulation which uncovered key practical considerations when detecting photons at the extreme limits of the highly diffusive regime. Although the experimental measurements were inconclusive, comparisons with the numerical results were promising. More in-depth numerical simulations indicated that light could be guided in regions of low scattering and absorption to reach deep areas inside the head, and photons can, in principle, be transmitted through the entire diameter of the head. The collective evidence presented in this thesis reveals the potential of diffuse optical imaging to extend beyond the currently accepted limits to non-invasively image deep regions of the human body and brain using optical wavelengths
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