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Recent developments in theoretical physics have led to new insights for gauge theory and gravity scattering amplitudes.The color-kinematics duality, in particular, describes an intriguing set of identities obeyed by the kinematic numerators of gauge-theory scattering amplitudes, mirroring the Jacobi identity of the color factors. The kinematic Jacobi identities suggest the existence of some unknown kinematic algebra underlying the gauge-theory Feynman rules. However, as of yet, there is no complete Lagrangian construction of duality-satisfying numerators, nor an off-shell realization of a kinematic algebra even for pure Yang-Mills gauge theory. This thesis presents substantial progress on these open problems, first through a Lagrangian whose Feynman rules compute duality-satisfying numerators in the NMHV sector of Yang-Mills theory. In addition, Chern-Simons gauge theory is shown to obey the color-kinematics duality completely off shell, giving rise to a kinematic algebra of volume preserving diffeomorphisms. Similar structures are also identified in the pure-spinor description of super Yang-Mills theory. The recent detection of gravitational waves by the LIGO/Virgo/KAGRA collaboration, as well as anticipated improvement in sensitivity of future detectors, call for improved precision of the theoretical predictions for binary merger events. Analytical computations involving gravitating and rotating compact objects require both increased classical loop orders in the gravitational coupling as well as the incorporation of spin effects, which have important contributions to the dynamics. For this purpose, an extension of the worldline quantum field theory is presented, based on the effective worldline action of a classical spinning compact object. The formalism is used to compute tree and one-loop amplitudes up to fourth order in spin, and coefficients in the effective worldline action are fixed such that it reproduces known Kerr observables from black hole perturbation

Network science provides very powerful tools for extracting information from interacting data. Although recently the unsupervised detection of phases of matter using machine learning has raised significant interest, the full prediction power of network science has not yet been systematically explored in this context. Here we fill this gap by providing an in-depth statistical, combinatorial, geometrical, and topological characterization of 2D Ising snapshot networks (IsingNets) extracted from Monte Carlo simulations of the 2⁢D Ising model at different temperatures, going across the phase transition. Our analysis reveals the complex organization properties of IsingNets in both the ferromagnetic and paramagnetic phases and demonstrates the significant deviations of the IsingNets with respect to randomized null models. In particular percolation properties of the IsingNets reflect the existence of the symmetry between configurations with opposite magnetization below the critical temperature and the very compact nature of the two emerging giant clusters revealed by our persistent homology analysis of the IsingNets. Moreover, the IsingNets display a very broad degree distribution and significant degree-degree correlations and weight-degree correlations demonstrating that they encode relevant information present in the configuration space of the 2⁢D Ising model. The geometrical organization of the critical IsingNets is reflected in their spectral properties deviating from the one of the null model. This work reveals the important insights that network science can bring to the characterization of phases of matter. The set of tools described hereby can be applied as well to numerical and experimental data.

At-wavelength metrology of X-ray optics plays a crucial role in evaluating the performance of optics under actual beamline operating conditions, enabling in situ diagnostics and optimization. Techniques utilizing a wavefront random modulator have gained increasing attention in recent years. However, accurately mapping the measured wavefront slope to a curved X-ray mirror surface when the modulator is downstream of the mirror has posed a challenge. To address this problem, an iterative method has been developed in this study. The results demonstrate a significant improvement compared with conventional approaches and agree with offline measurements obtained from optical metrology. We believe that the proposed method enhances the accuracy of at-wavelength metrology techniques, and empowers them to play a greater role in beamline operation and optics fabrication.

This paper explores the application of quantum nonlocality, a renowned and unique phenomenon acknowledged as a valuable resource. Focusing on an alternative application, we demonstrate its quantum advantage for mobile agents engaged in specific distributed tasks without communication. The research addresses the significant challenge of rendezvous on graphs and introduces a distributed task for mobile agents grounded in the graph domination problem. Through an investigation across various graph scenarios, we showcase the quantum advantage. Additionally, we scrutinize deterministic strategies, highlighting their comparatively lower efficiency compared to quantum strategies. The paper concludes with a numerical analysis, providing further insights into our findings.

We show that weakly entangled states can improve communication over a qubit channel using only separate, interference-free, measurements of individual photons. We introduce a communication task corresponding to the cryptographic primitive known as secret sharing and show that all steerable two-qubit isotropic states provide a quantum advantage in the success rate using only product measurements. Furthermore, we show that such measurements can even reveal communication advantages from noisy partially entangled states that admit no quantum steering. We then go further and consider a stochastic variant of secret sharing based on more-sophisticated, yet standard, partial Bell-state analyzers, and show that this reveals advantages also for a range of unsteerable isotropic states. By preparing polarization qubits in unsteerable states, we experimentally demonstrate increased success rates of both secret-sharing tasks beyond the best entanglement-unassisted qubit protocol. Our results reveal the capability of simple and scalable measurements in entanglement-assisted quantum communication to overcome large amounts of noise.

Researchers generally agree that physics experts use mathematics in a way that blends mathematical knowledge with physics intuition. However, the use of mathematics in physics education has traditionally tended to focus more on the computational aspect (manipulating mathematical operations to get numerical solutions) to the detriment of building conceptual understanding and physics intuition. Several solutions to this problem have been suggested; some authors have suggested building conceptual understanding before mathematics is introduced, while others have argued for the inseparability of the two, claiming instead that mathematics and conceptual physics need to be taught simultaneously. Although there is a body of work looking into how students employ mathematical reasoning when working with equations, the specifics of how physics experts use mathematics blended with physics intuition remain relatively underexplored. In this paper, we describe some components of this blending, by analyzing how physicists perform the rearrangement of a specific equation in cosmology. Our data consist of five consecutive forms of rearrangement of the equation, as observed in three separate higher education cosmology courses. This rearrangement was analyzed from a conceptual reasoning perspective using Sherin's framework of symbolic forms. Our analysis clearly demonstrates how the number of potential symbolic forms associated with each subsequent rearrangement of the equation decreases as we move from line to line. Drawing on this result, we suggest an underlying mechanism for how physicists reason with equations. This mechanism seems to consist of three components: narrowing down meaning potential, moving aspects between the background and the foreground and purposefully transforming the equation according to the discipline's questions of interest. In the discussion section we highlight the potential that our work has for generalizability and how being aware of the components of thi

In this work, we introduce a generalization of the Landauer bound for erasure processes that stems from absolutely irreversible dynamics. Assuming that the erasure process is carried out in an absolutely irreversible way so that the probability of observing some trajectories is zero in the forward process but finite in the reverse process, we derive a generalized form of the bound for the average erasure work, which is valid also for imperfect erasure and asymmetric bits. The generalized bound obtained is tighter than or, at worst, as tight as existing ones. Our theoretical predictions are supported by numerical experiments and the comparison with data from previous works.

Hyper-ballistic diffusion is shown to arise from a simple model of microswimmers moving through a porous media while competing for resources. By using a mean-field model where swimmers interact through the local concentration, we show that a non-linear Fokker-Planck equation arises. The solution exhibits hyper-ballistic superdiffusive motion, with a diffusion exponent of four. A microscopic simulation strategy is proposed, which shows excellent agreement with theoretical analysis.

We investigate the transport and entanglement properties exhibited by quantum walks with coin operators concatenated in a space-time fractal structure. Inspired by recent developments in photonics, we choose the paradigmatic Sierpinski gasket. The 0-1 pattern of the fractal is mapped into an alternation of the generalized Hadamard-Fourier operators. This two-state coin-operator approach overcomes the intricacies caused by the utilization of high-dimensional coin operators required in prior studies of discrete-time quantum walks on fractals. In fulfilling the blank space on the analysis of the impact of inhomogeneity in quantum walk properties, specifically, fractal deterministic inhomogeneity, our results show a robust effect of entanglement enhancement as well as an interesting road to superdiffusive spreading with a tunable scaling exponent attaining robust superdiffusion, subballistic though. Explicitly, with this fractal approach it is possible to obtain an increase in quantum entanglement with reduced impact on standard quantum walk theoretical spreading. Alongside those features, we analyze further properties such as the degree of interference and visibility. The present model corresponds to an application of fractals in an experimentally viable setting, namely, the building block for the construction of photonic patterned structures.

We consider the effects of backreaction on axion-SU(2) dynamics during inflation. We use the linear evolution equations for the gauge field modes and compute their backreaction on the background quantities numerically using the Hartree approximation. We show that the spectator chromo-natural inflation attractor is unstable when back-reaction becomes important. Working within the constraints of the linear mode equations, we find a new dynamical attractor solution for the axion field and the vacuum expectation value of the gauge field, where the latter has an opposite sign with respect to the chromo-natural inflation solution. Our findings are of particular interest to the phenomenology of axion-SU(2) inflation, as they demonstrate the instability of the usual trajectory due to large backreaction effects. The viable parameter space of the model becomes significantly altered, provided future non-Abelian lattice simulations confirm the existence of the new dynamical attractor. In addition, the backreaction effects lead to characteristic oscillatory features in the primordial gravitational wave background that are potentially detectable with upcoming gravitational wave detectors.

We introduce a systematic and quantitative methodology for establishing the presence of neutrino oscillatory signals due to the hadron-quark phase transition (PT) in failing core-collapse supernovae from the observed neutrino event rate in water- or ice-based neutrino detectors. The methodology uses a likelihood ratio in the frequency domain as a test-statistic; it is employed for quantitative analysis of neutrino signals without assuming the frequency, amplitude, starting time, and duration of the PT-induced oscillations present in the neutrino events and thus it is suitable for analyzing neutrino signals from a wide variety of numerical simulations. We test the validity of this method by using a core-collapse simulation of a 17 solar-mass star by Zha et al. [Astrophys. J. 911, 74 (2021) ]. Based on this model, we further report the presence of a PT-induced oscillations quantitatively for a core-collapse supernovae out to a distance of ∼10 kpc, ∼5 kpc for IceCube and to a distance of ∼10 kpc, ∼5 kpc, and ∼1 kpc for a 0.4 Mt mass water Cherenkov detector. This methodology will aid the investigation of a future galactic supernova and the study of hadron-quark phase in the core of core-collapse supernovae.

Integreringen av AI inom utbildning har intensifierats sedan företaget OpenAI släppte AI-verktyget ChatGPT. Diskussioner har förts om huruvida, och i så fall hur, AI bör integreras med undervisningen. Lärare kan använda verktyget för att generera lektionsplaneringar, men måste alltid vara kritiska till vad AI:n genererar, eftersom den i grunden är stokastisk. Syftet med arbetet var att undersöka vilka uppfattningar, mer specifikt vilka dispositioner som framkommer när lärare diskuterar AI-genererat undervisningsmaterial i fysik, i det här fallet lektionsplaneringar. Studien utfördes i Uppsala och intervjuade lärare inom Uppsala län och Stockholms län. Studien bygger på semistrukturerade intervjuer av tre lärare. All transkriberad data analyserades därefter genom en induktiv tematisk analys. Utifrån analysen framkommer det att lärare har följande dispositioner: Det är viktigt att presentera ytterligare innehåll utöver det centrala för lektionerna. Detta för att placera in kunskapen i en större kontext och utveckla kunskaper i något eleverna redan förstår. Tydlighet i aktiviteters innehåll och utförande är viktigt för att effektivisera lärarens arbete och för att eleverna ska förstå aktivitetens syfte. Lärarna anser det viktigt att undervisning presenterar innehåll i en korrekt ordning och att eleverna har de kunskaper som är nödvändiga för att förstå Newtons lagar. Att konceptuell förståelse är viktig för att förstå fysiken på en djupare nivå, men att fysiken är mycket mer än konceptuell. Träning att utföra matematiska beräkningar är viktig för relationen mellan elever och fysikinnehåll och det saknas i de AI-genererade lektionsplaneringarna. Lärarna anser det viktigt att förstå vilka förmågor eleverna har och planera utifrån dem, vilket de AI-genererade lektionsplaneringar inte kunde göra. Lärarna anser det viktigt att kunna använda sig av kognitiva konflikter för att skapa nyfikenhet, intresse och grund för kunskap hos eleverna, vilket AI:n inte kunde planera fö

The concept of compactifications is used in theoretical physics to perform a dimensional reduction of a theory -- often needed in string theory which is formulated in more than four dimensions. This report provides a concise and pedagogical introduction to the idea of compactifications which is accessible to students. We compute the three established massive AdS4 x S6 vacua, discussed recently in e.g. a paper by Bomans et al. from 2021: Starting from the ten-dimensional type IIA supergravity action and employing the AdS4 x S6 ansatz, we perform a dimensional reduction to derive the corresponding four-dimensional effective theory. We analyse two scenarios: Initially, we only consider the field strengths F0 and F6; later, we include all possible field strengths, i.e. also H, F2 and F4. For both cases, we identify the potential and search for its minima. The comparison with the paper by Bomans et al. shows that we can reproduce the three AdS4 x S6 minima that they find: two non-supersymmetric and one supersymmetric one. For all minima, we calculate the zero mode of the Kaluza Klein tower and show that they fulfil the BF bound.

In this work, we examine a spacetime model proposed in a paper by Chamseddine et al. from 1993 based on techniques from Connes' noncommutative geometry. We start by introducing the language of fibre bundles and Clifford algebras in order to define spin structures. These allow to work with spinors on manifolds. After reviewing some basics of module theory we introduce noncommutative geometry as a generalisation of ordinary differential geometry based on operator theoretic data. There the notion of spectral triples will be central. Using this machinery we develop the cited spacetime model based on the Cartesian product of a compact four-dimensional spin manifold and a two-point space. Within the noncommutative geometric language, we are able to compute the torsion and curvature. We finish the work by presenting a generalised Einstein-Hilbert action for the model proposed in the paper and discuss the physical implications.

Denna studie utforskar användningen av undersökande arbetssätt inom fysikundervisning utifrån ett lärarperspektiv. Förankrad inom lärarprogrammet vid Karlstads universitet, strävar denna forskning efter att noggrant undersöka användningen av systematiska undersökningar i grundskolans fysikundervisning och att tydliggöra lärarnas åsikter kring dessa. Genom att använda den kvalitativa forskningsmetoden fenomenografi får vi fram resultat som framhäver en allmänt förekommande positiv inställning bland lärarna till användningen av undersökande arbetssätt i fysik-klassrummet. I korthet visar denna undersökning att lärarna möter olika utmaningar när de implementerar undersökande arbetssätt i fysikundervisningen. De flestalärarna i denna studie är entusiastiska över att integrera detta arbetssätt och ser den som en chans för eleverna att aktivt utforska vetenskapliga koncept. De framhäver att elevernas engagemang fördjupar deras förståelse och stärker deras förmåga att tänka kritiskt och lösa problem. Samtidigt står vissa inför hinder som brist på tid, resurser och osäkerhet kring genomförandet av undersökande arbetssätt. Det är viktigt att betona att lärarnas behov av resurser inte får bli en anledning till att undvika praktiskt arbete. Skolledningen bör stödja lärarna genom att tillhandahålla de nödvändiga resurserna. Genom att hantera dessa utmaningar kan skolor skapa en miljö där elevernas lärande främjas på bästa sätt.

In this project a qutrit tripod system is studied to implement quantum gates using non-Abelian geometric phases, allowing for holonomic quantum computation which in turn results in more robust computations. First, a general foundation of the theory is presented. This includes the relevant theory of matrices in Hilbert space, as well as theory of the quantum mechanics used in the report. The method is then described in depth, showing how the pulse area is fixed. Using properties of the Hamiltonian as well as the time-evolution operator of the tripod system the computational subspace can be derived. These findings are combined to show how the computational subspace evolves in time, resulting in the unitary matrix used to form quantum gates. Using educated guesses to find the necessary parameters or utilizing iterative methods to find the parameters are the two main approaches used for constructing the considered gates. Three of the suggested quantum gates are successfully implemented through educated guesses, namely X, T and Z using an angle parametrization of the phase and amplitude of the pulses. The last desired gate is the Hadamard-gate, but the implementation of said gate required numerical approximation. The reasons as to why this is the case, are later discussed.

The exploding foil initiator (EFI) is a high voltage detonator used to initiate explosions. It is designed to improvesafety standards by lowering the risk of accidental detonation and in doing so allows for in-line integration in, forexample, weapon systems that minimizes their complexity and thus reduces the number of possible failures. It ishighly reliable in terms of timing and avoids that functionality of the detonator deteriorates over time, which has beena problem in earlier designs of detonators. This thesis aims to develop an understanding of each part of the initiationprocess by means of computer simulations. The proportions of the electrically conducting bridge is varied in order tofind relations that optimize the design. Success depends on the simulated pressure generated inside a hexanitrostilbene(HNS) primer.The results showed that increasing the dimensions of the bridge greatly affects the pressure produced in the primer,but its proportions were still important. Unfortunately the simulations of the electrical explosion and the accelerationof the flyer suffered from convergence issues that rendered the flyer’s velocity graphs incomplete. But even with theseshortcomings, thanks to empirical data from earlier studies that analysed EFI prototypes, it was possible to makepredictions about the success of various set ups. The information gathered in this thesis should serve as a foundationfor future development of computer models of the EFI technology that will aid the production of prototypes that meetthe specific requirements.i, Den explosiva folieinitieraren (EFI) är en högspänningsdetonator som används för att initiera explosiva förlopp. Denär designad för att förbättra säkerheten genom att sänka risken för oavsiktlig detonering och till följd av detta möjligörför in-line integrering i, till exempel, vapensystem. Detta minimerar komplexiteten av sådanna system och sänker antaletmöjliga fel som kan uppstå. Denna teknolgi är högst pålitlig när det gäller timing och undviker att detonatorns funktionförsämras över tid, vilket har varit ett problem i tidigare konstruktioner av detonatorer. Denna avhandling syftar tillatt utveckla en förståelse för varje del av initieringsprocessen genom datorsimuleringar. Proportionerna av den elektrisktledande bryggan varierades för att hitta relationer som optimerar designen. Framgången beror på det simulerade trycketsom genereras inuti en primer av det explosiva materialet hexanitrostilben (HNS).Resultaten visade att ökade dimensioner på bryggan kraftigt påverkar trycket som produceras i primern, men dessproportioner var fortfarande viktiga. Tyvärr led simuleringarna av den elektriska explosionen och accelerationen avflyern av konvergensproblem som gjorde att flyerns hastighetsgrafer blev ofullständiga. Men även med dessa brister,tack vare empiriska data från tidigare studier som analyserade EFI-prototyper, var det möjligt att göra förutsägelserom framgången för olika uppsättningar. Informationen som samlats in i denna avhandling bör tjäna som en grund förframtida utveckling av dator modeller av EFI-teknologi som kommer att underlätta produktionen av prototyper somuppfyller specifika krav.ii

Nuclear power is a foundational part of our electrical grid in the present and through our transition towards more sustainable and renewable alternatives. However, given the serious consequences of reckless and/or dangerous operation of nuclear power plants, they are subject to strict regulation and supervision by the Swedish radiation protection authority (SSM) and other regulating bodies (e.g. IAEA). In order to prove that a nuclear power plant is operating in a safe and accident preventative manner, the “Safety Analysis Report” (SAR) is created and submitted. The SAR categorizes and ranks all possible incidents and operation affecting events in terms of risk and available countermeasures to ensure that the radioactive release from the power plant and impact on a third party from any event is at acceptable levels. This projects limits its analysis to flooding of the reactor building or “internal flooding events” as described in the SAR. To determine the affected areas and impacted systems of any flooding event, deterministic safety analyses (DSA) are employed. The goal of this project is to develop a comprehensive thermohydraulic model of the Forsmark 2 reactor building and evaluate its performance with respect to the previously used MATLAB model. The model should allow for a detailed nodalisation of the reactor building as well as realistic modelling of structural components such as doors, hatches, stairwells and drainage systems. The resulting thermohydraulic model can be used to evaluate different flooding incidents dynamically and follow the spread of water and/or steam throughout the reactor building. Furthermore, the resulting pressure changes and heat generation in the reactor building can also be evaluated. The model allows for the possibility to couple the thermohydraulic reactor building model with the existing power plant systems model to holistically evaluate the power plant response to flooding related incidents., Kärnkraft är en grundläggande del av vårt elnät i nuläget och under vår övergång mot mer hållbara och förnybara alternativ. Men med tanke på de allvarliga konsekvenserna av vårdslös och/eller farlig drift av kärnkraftverk, är de föremål för strikt reglering och tillsyn av Strålsäkerhetsmyndigheten (SSM) och andra reglerande organ (t.ex. IAEA). För att bevisa att ett kärnkraftverk drivs på ett säkert och olycksförebyggande sätt, upprättas och inlämnas "Strålsäkerhetsanalysrapport" (SAR). SAR kategoriserar och rangordnar alla möjliga incidenter och händelser som påverkar driften i termer av risk och tillgängliga motåtgärder för att säkerställa att radioaktiva utsläpp från kraftverket och påverkan på tredje person från någon händelse är på acceptabla nivåer. Detta projekt begränsar sin analys till översvämning av reaktorbyggnaden eller "interna översvämningshändelser" enligt beskrivningen i SAR. För att fastställa de påverkade områdena och drabbade systemen vid en översvämningshändelse, används deterministiska säkerhetsanalyser (DSA). Målet med detta projekt är att utveckla en omfattande termohydraulisk modell av Forsmark 2 reaktorbyggnad och utvärdera dess prestanda i förhållande till den tidigare använda MATLAB-modellen. Modellen ska möjliggöra en detaljerad nodalisering av reaktorbyggnaden samt realistisk modellering av strukturella komponenter som dörrar, luckor, trapphus och dräneringssystem. Den resulterande termohydrauliska modellen kan användas för att dynamiskt utvärdera olika översvämningsincidenter och följa spridningen av vatten och/eller ånga genom reaktorbyggnaden. Dessutom kan de resulterande tryckförändringarna och värmegenereringen i reaktorbyggnaden också utvärderas. Modellen möjliggör koppling av den termohydrauliska reaktorbyggnadsmodellen med den befintliga kraftverkssystemmodellen för att holistiskt utvärdera kraftverkets respons på översvämningsrelaterade händelser.

Green hydrogen has an important role in the process of making the world carbon-free. Today, companies use and produce hydrogen gas in various commercial and industrial applications. However, less than 5% is produced with energy from a sustainable source such as wind, water, or solar power. This thesis focuses on the utilization of solar energy for green hydrogen productionand tracks the energy provided by the sun through a photovoltaics-electrolyzer system. The thesis includes an introductory literature review as well as a MATLAB program constructed to evaluate the rate of hydrogen production for a generic Photovoltaics-Electrolyzer system (PV-EL), given a certain area of photovoltaic cells. In collaboration with Växjö Energi AB, a local sustainable energy-oriented company, the potential hydrogen production for an area of 170 000 square meters located near Småland Airport, Sweden could be estimated. The data shows a significant difference for the potential production rate in the summer compared to during winter times, a result of the yearly variation of solar radiation in Sweden. Further investigation is necessary to find the optimal sizing for such a project and how best to utilize the solar energy all year round. Furthermore, the thesis closes with a brief review of future prospects within the area of producing green hydrogen from a PV-EL system, such as the possibility of utilizing waste heat to increase the total energy efficiency.

The focus of this work is on the Ising model and its role in computational devices. This report delves into realm of quantum computers and the Ising model's part within it. However, the main objective of the project was to investigate the Ising model as a foundation for a computational device by simulating the model in Python. To achieve this, two NP-complete problems, Graph Coloring and Clique Cover, were simulated using Monte Carlo methods. The results of the simulations demonstrated the potential of the Ising model as a foundation for a computational device. However, during the simulation, the system encountered some fundamental issues. Specifically, the simulation had a tendency to get stuck in local minima, preventing it from finding the solution. This led to the development of the dynamic beta function, which enabled the simulation to escape local minima and continue toward finding a solution. As a final conclusion of the rapport, an outlook of the Ising model as a foundation for a quantum computer was discussed. The switch from normal spin-variables of the Ising model to quantum bits, or qubits, would transition the model to a quantum model, hence enabling it to take advantage quantum behavior, and function as a quantum computer., Huvudinnehållet i det här arbetet ligger på Ising-modellen och dess roll i beräkningsenheter. Rapporten dyker in i kvantdatorernas värld och utforskar Ising-modellens plats däri. Huvudsyftet med rapporten är dock att undersöka Ising-modellen som utgångspunkt för en beräkningsenhet genom att simulera modellen i Python. Detta utfördes genom att två NP-fullständiga problem, graffärgning och clique-täckning, simulerades med Monte Carlo-metoder. Resultaten från simuleringarna visade Isingmodellen styrka och potential som grund för beräkningsenheter. Emellertid uppstod det under simuleringarna några fundamentala brister i implementeringen. Ett av problemen var att simueringen fastnade i lokala minima, vilket hindrade den från att närma sig en lösning. Följden av detta blev utvecklandet av den dynamiska beta-funktionen, vilket möjliggjorde att simuleringen kunde ta sig ur de lokala minima och fortsätta sträva mot en lösning. Som en avslutande sammanfattning i rapporten diskuteras Ising-modellens plats inom kvantdatorer som en utblick. Övergången från vanliga spinnvariabler till kvantbitar förflyttar modellen till en kvantmodell, vilket möjliggör att utnyttja fördelarna med kvantbitar och därmed fungera som en kvantdator.

The unitary representations of the Poincaré group are of physical interest since this is how Poincaré invariance is implemented in quantum mechanics, which is required for compatibility with the special theory of relativity. In this thesis we review the algebraic structure of the Lorentz and Poincaré groups before moving onto classifying the (physical) unitary representations of the Poincaré group. We find that there are two types of representations that correspond to massive and massless particles. In the massive case we find that these particles must carry the internal degree of freedom of spin. On the other hand in the massless case we find that these particles must carry helicity., Unitära representationer av Poincaré-gruppen är av fysikaliskt intresse eftersom det är på detta sätt som Poincaré-invarians kan implementeras i kvantmekaniken, vilket krävs för kompatibilitet med den speciella relativitetsteorin. I denna avhandling granskar vi den algebraiska strukturen hos Lorentz- och Poincarégrupperna innan vi går vidare till att klassificera de (fysikaliska) unitära representationerna av Poincarégruppen. Vi finner att det finns två typer av representationer som motsvarar massiva och masslösa partiklar. I det massiva fallet finner vi att dessa partiklar måste bära den interna frihetsgraden spinn. Medan vi i det masslösa fallet finner att dessa partiklar måste bära helicitet.

This thesis showcases the development of a numerical solver for the Navier-Stokes equations in two dimensions to simulate fluid flow in a lid-driven cavity problem. The primary objective was to create an efficient and accurate solver using the Finite DifferenceMethod (FDM ) and the Explicit Euler Step Method (EESM ) for solving the differentialequations. Additionally, the Artificial Compressibility Method (ACM ) was employed forsolving the pressure gradient. The solver was developed and tested in MATLAB, withplans for future implementation into a web-based environment using Three.js and GLSL. To validate the simulation, results of the velocity field vectors, for various Reynoldsnumbers, were compared against benchmark data. The comparison aimed to assess theaccuracy and performance of the developed solver by analyzing how closely the simulatedvelocity profiles matched the benchmark data across different Reynolds numbers. Despitesome discrepancies, primarily attributed to numerical diffusion and grid resolution, theoverall trends in the simulated data showed good agreement with the benchmark datafor laminar flow, indicating that the solver appears to capture the essential behavior ofthe fluid flow in the lid-driven cavity problem. Furthermore, an error analysis was performed using Absolute Difference and PercentageRelative Error (PRE), the results indicated that the errors were within an acceptablerange for the lid-driven cavity problem. However, due to time constraints, the integrationinto Three.js and GLSL was not fully completed and remains a task for future work.Moreover, the resulting plots of both the pressure and the velocity vector field did notmeet expectation. They have non-physical characteristics, which suggests that the solvermade in this thesis is not fully functional. However, for aesthetic fluid-like flow, thissolver should work to capture the overall trends of fluids that can fit a web applicationto make it more interesting.

The aim of this report is to introduce the reader to the field of integrability in classical and quantum physics. The report begins with a reminder of Hamiltonian mechanics and explains the notion of Liouville integrability. The introduction of the Lax formalism is then used to show a method for generating conserved quantities that lends itself well to a generalisation to classical field theory. In this context, the fundamental concepts of r-matrix, monodromy and transfer matrix are presented. To close the section on classical integrability, the classical inverse scattering method is presented on the example of the Korteweg - de Vries equation. Solving the spin chain XXX 1/2 using the coordinate Bethe ansatz is then used to open the door to the field of quantum integrability. The generalisation of the classical concepts introduced previously to the quantum domain will allow us to implement the algebraic Bethe ansatz method, which is a more general approach. Using this procedure, the examples of the spin chains XXX s and XXZ s are treated, clearly highlighting the importance of symmetries in the field of integrability. Finally, a brief overview of the Gauge/Bethe correspondence is presented.

Light Detection and Ranging (Lidar) is a kind of active sensor that emits a laser pulse and primarily measures the time of flight of the returning pulse and uses it to construct a 3D point cloud of the scene around the lidar sensor. The constructed point cloud is an essential asset for the control of autonomous vehicles, and especially today, an essential basis for the training of autonomous vehicle control models. However, it remains time-consuming, high-risk and expensive to acquire the amounts of data necessary to train the rather complex modern control models. As such, generating the point cloud through simulations becomes a natural solution. Yet, many lidar simulations today produce ideal point clouds, corrected only by random noise, without considering the physical reasons behind the imperfections visible in real lidar point clouds. The aim of this study was to investigate real-time simulation models for disturbances that may cause imperfections in lidar data. From a base investigation of lidar, disturbances were found, models were investigated and finally a real-time implementation of Atmospheric Effects and attenuation from Beam Divergence was evaluated. It was found that the implemented models could produce physically accurate lidar point placement while keeping the computational time low enough for real-time evaluation. However, to achieve correct separation of target hit rates under Atmospheric Effects, as high as 34% of the points had to be dropped. Additionally, the intensity of the return points could not be properly verified. From these results it can be concluded that, with additional verification and adjustment, the presented models can achieve good results for evaluation in real-time. The results of this study thus serve as a support for future developments of realistic real-time lidar simulations, for use in development of autonomous vehicle control models and implementation of digital twins.

This master’s thesis project investigates the utilization of a low-cost hyperspectral (HS) imaging rig to identify and classify drought stress in pine plants. Drought stress is a widespread environmental challenge affecting global forestry, requiring more resources as the industry grows and global warming rises. This provokes a need for affordable, and efficient monitoring methods. HS imaging, with its ability to capture a wide range of spectral information, offers promising methods for quick and precise measurements of plant stress. The project methodology is comprised of redesigning an existing HS imaging rig, with the camera employing push-broom technology, to yield precise and consistent HS images. This involved exploring the camera’s spectral range, designing components to ensure consistent artificial lighting using blackbody radiation sources, and calibrating the HS camera for focal depth and aberrations like smile and keystone. Two experiments were conducted to obtain the data for pine stress detection, first for two binary categories: Control, and 100% Drought, and later introducing a third semi-drought category in the second experiment. The data analysis encompassed preprocessing the HS images to correct the lighting intensity distributions and normalization of pixel values. Accompanied by filtering, resampling spectral data, and feature extraction facilitating consistent drought identification, and data management. To identify stress patterns in pine plants and temporal decay rates, methods such as spectral reflectance analysis, various vegetation indices (VI), and statistical learning techniques like discriminant analysis and logistic regression were evaluated for distinguishing between stressed and healthy plants. The results demonstrate the accuracy of the HS imaging rig in measuring spectral reflectances from plants, capturing changes between 550 − 670 nm in the visible spectrum and 750 − 890 nm in the near-infrared (NIR) spectrum due to increasing str

This study explores the application of GPU-based algorithms in radiowave propagation modeling, specifically through the scope of solving parabolic wave equations. Radiowave propagation models are crucial in the field of wireless communications, where they help predict how radio waves travel through different environments, which is vital for planning and optimization. The research specifically examines the implementation of two numerical methods: the Split Step Method and the Finite Difference Method. Both methods are adapted to utilize the parallel processing capabilities of modern GPUs, harnessing a parallel computing framework known as CUDA to achieve considerable speed enhancements compared to traditional CPU-based methods.Our findings reveal that the Split Step method generally achieves higher speedup factors, especially in scenarios involving large system sizes and high-frequency simulations, making it particularly effective for expansive and complex models. In contrast, the Finite Difference Method shows more consistent speedup across various domain sizes and frequencies, suggesting its robustness across a diverse range of simulation conditions. Both methods maintained high accuracy levels, with differences in computed norms remaining low when comparing GPU implementations against their CPU counterparts.

In this project, we compute the Hagedorn temperature in N=4 supersymmetric Yang-Mills theory and in pure Yang-Mills theory by determining the temperature at which the partition function becomes non-analytic. The gauge group is taken to be either SU(N) or O(N) in the large N limit. We derive the partition function with combinatorics, counting the single-trace operators (and thereby the gauge invariant states) allowed by the theory. Then we determine the single-particle partition functions associated with fermions, bosons, and gluons, whose contributions make up the full partition function. These single-particle functions are derived independently using two different approaches (both producing the same result), where the first method relies on the state-operator correspondence of conformal field theories, and the second relies on the spin representations of the particles. We also derive the partition function on a compact space by integrating over the gauge group manifold. By using random matrix theory and standard large N methods, the integral simplifies. The resulting Hagedorn temperature matches that derived from combinatorics. We compute the precise temperature in two theories.

Tracked vehicles are designed to operate in various terrains, ranging from soft mud to hard tarmac. This wide range of terrains presents significant challenges for the suspension system, as its components must be suitable for all types of terrain. The selection of these components is crucial for minimizing acceleration levels within the vehicle, ensuring that personnel can comfortably endure extended durations inside. BAE Systems Hägglunds AB develops and produces an armored tracked vehicle called the CV90. Within the CV90’s suspension system, a key component known as the torsion bar, a rotational spring, plays a primary role in reducing the vehicle’s motion. The CV90 vehicle has seven wheels on each side, with each wheel having its dedicated torsion bar. To measure the whole-body vibration experienced within the vehicle, a measurement called the Vibrational Dose Value (VDV) is utilized. The main objective of this thesis is to develop a data-driven model to optimize the suspension system by identifying the combination of torsion bars that generates the smallest VDV. The data used for optimization is based on simulations of the CV90 vehicle in a virtual environment. In the simulation, the CV90 vehicle, with its full dynamics, is driven over a specific virtual road at a particular velocity. The simulation itself cannot be manipulated; only the input values can be adjusted. Thus, we consider the simulation as a black box, which led us to implement the black-box optimization algorithm known as Particle-Swarm. In this thesis, four different roads, each with velocities ranging from four to seven different levels, were provided to the optimization model. The results show that the model identifies a combination of torsion bars that generates a small VDV for all combinations of velocities and roads, with an average VDV improvement of around 20% - 60% compared to a reference case. Since this thesis serves as a proof of concept, the conclusion is that the devised method is ef

This paper presents the design of an electromagnetic metasurface (MS) to be employed as a matching layer to improve the electric field transmission inside the human body, for microwave imaging and sensing. The approach used to develop the matching layer is based on the transmission line model and it can be useful to tailor the metasurface properties for different applications. In particular, by retrieving the MS impedance and tuning it in order to compensate for the body impedance, the reflection coefficient at the air-tissues interface can be minimized. Through accurate full-wave simulations performed over a preliminary test-case, we demonstrated that the conceived MS is capable of improving the transmitted electric field by 6.6 dB at 1.61 GHz. Moreover, the array reduced dimensions (56 mm x 56 mm) allow to realize systems suitable for different anatomical districts. The obtained results show the possibility to improve the electric field transmission inside human body at microwaves, leading to safer and more effective solutions with respect to the actual state-of-the-art.

There is a need for expanding research on upper-division physics courses, in particular topics such as thermal physics. Our study took a grounded approach to exploring challenges that arose when small student groups engaged in collaborative problem solving on statistical mechanics content. We found that the students struggled to navigate around the abstract and subtle concepts of statistical mechanics. Additionally, challenges related to problem-solving strategies was prevalent in our data. Here we will summarize our identified categories of student challenges, which emerged from our data, and present a few illustrative examples. Particularly, we will discuss the educational implications of our findings and the possible connections to other upper-division courses with a similar reliance on abstract physics concepts and demanding mathematics.

Intuition has been reported as being pivotal in guiding students' problem solving. In this ongoing project, we employ a grounded approach to investigate how students use intuition during problem solving in beyond-intro chemistry and physics courses. We adopt a dynamic perspective on intuition, recognizing its context-dependency, to examine how students respond to their intuitions. In a case study, we inductively analyze existing video data of problem-solving sessions, and show that students' responses to intuition can be productive or unproductive, regardless of the intuition's appropriateness. This highlights the need to equip students with strategies to manage their intuitions productively. Based on our findings, we recommend teachers to: adopt a flexible stance toward intuition; explicitly incorporate the topic of intuition in classroom discussions; and encourage students to actively reflect on their intuitions. Future studies should consider the processes governing the development of intuition and expand research on students' epistemological views on intuition.

The two-state paramagnet has previously been proposed as a valuable pedagogical tool for teaching statistical mechanics. In this study, we focused on the role that the two-state paramagnet example played in student discussions while solving problems in statistical mechanics. Students' use of the example was both advantageous and challenging. While we saw students using the two-state paramagnet example to reason analogically about similar systems, we also saw a general lack of in-depth reflection of what makes the model transferable to other contexts. We suggest some considerations for teachers to better leverage this example and facilitate student learning in statistical mechanics.

Problem solving at the interface of mathematics and other scientific disciplines is known to pose substantial challenges for students at the university level. In our research, we employ lenses from physics, chemistry, and mathematics education research, to explore students' approaches to math-intensive problem solving beyond introductory level physics and chemistry. Preliminary findings indicate that effective problem-solving activities in these contexts require students to combine their understanding of concepts and problem-solving skills from both mathematics and chemistry or physics. Interestingly, this includes their intuition or 'gut feelings' related to these disciplines. At TUK2024, we will present illustrative examples that emerged from our empirical data, highlighting the influence of students' intuition on how they navigate uncertain problem-solving situations. While our findings originated within the realms of chemistry and physics, we believe that their implications for teaching extend to, and are relevant to, students' problem-solving tendencies in other scientific disciplines.

Efficient energy harvesting through full solar spectrum utilization has been considered a promising solution to world energy and environmental issues. In this direction, lead sulphide (PbS) quantum dot (QD) based hybrid materials find greater application due to their near-infrared (NIR) active photo response. Slower charge injection and inefficient charge separation limit photoactive response of such NIR active low band gap semiconductor like PbS QDs. Moreover, constructing dual charge transfer pathways in a PbS QDs based nanocomposite through the formation of hybrids with suitable materials can be advantageous in suppressing the charge recombination. In this work, we have synthesized a nanocomposite after decorating the PbS-QDs with semiconducting TiO2 nanoparticles modified with multiwall carbon nanotubes (MWCNT) and thus forming the tri-hybrid (PbS-TiO2-MWCNT) nanocomposites. The enhanced photo-activities of the tri-hybrid, as compared to di-hybrids like PbS-TiO2, PbS-MWCNT were confirmed by the steady state, time-resolved photoluminescence (TRPL) measurements and reactive oxygen species (ROS) generation measurements. Higher ROS generation in the tri-hybrid has been correlated with a faster interfacial electron transfer due to the dual charge injection pathway of PbS QD to TiO2 and MWCNT. The enhanced activity of the trio-hybrid has also been analyzed from the first principal calculations in light of an efficient interfacial electron transfer as a result of the dual charge injection pathway. The photoelectrochemical water-spilling response of the photoanodes in terms of photocurrent density, electrochemical impedance, and Mott-Schottky measurements on PbS-TiO2 and PbS-TiO2-MWCNT photoanodes reveal that a combination of MWCNT and TiO2 exhibits an increase in electrical double layer capacitance, decrease in series resistance and enhancement of carrier density with NIR illumination at the heterojunction. Overall, all the dynamical studies at the interface of the tri

Magic-angle twisted bilayer graphene (MATBG) has been extensively explored both theoretically and experimentally as a suitable platform for a rich and tunable phase diagram that includes ferromagnetism, charge order, broken symmetries, and unconventional superconductivity. In this paper, we investigate the intricate interplay between long-range electron-electron interactions, spin fluctuations, and superconductivity in MATBG. By employing a low-energy model for MATBG that captures the correct shape of the flat bands, we explore the effects of short- and long-range interactions on spin fluctuations and their impact on the superconducting (SC) pairing vertex in the matrix random phase approximation (matrix RPA). We find that the SC state is notably influenced by the strength of long-range Coulomb interactions. Interestingly, our matrix-RPA calculations indicate that there is a regime where the system can traverse from a magnetic phase to the SC phase by increasing the relative strength of long-range interactions compared to the on-site ones. These findings underscore the relevance of electron-electron interactions in shaping the intriguing properties of MATBG and offer a pathway for designing and controlling its SC phase.

Incorporating functionalized TiO2 microarchitectures or upconversion nanoparticles (UCNPs) into photoanodes is deemed to be two effective ways to boost the photovoltaic performance of dye-sensitized solar cells (DSSCs). Nonetheless, studies combining functionalized TiO2 and UCNPs for the development of composite photoanode films in DSSCs still remain scarce. In view of this, we present a facile strategy for the design and preparation of a multifunctional composite photoanode containing P25 nanoparticles, peanut-like (PN) TiO2 microstructures, and NaYF4:Yb,Er@NaYF4:Nd@SiO2 core–shell–shell UCNPs. It is found that the DSSC containing a dual-functional photoanode using PN TiO2 as a light-scattering layer and P25 as a transparent layer can achieve a photovoltaic efficiency of 9.01%, presenting a 26.37% enhancement over the blank device. More importantly, the addition of UCNPs can further enhance the photoelectric performance of the DSSC device, realizing an optimal photovoltaic efficiency of 10.58%, one of the highest reported efficiencies for UCNP-based DSSCs with the common N719 photosensitizer. Such a remarkable improvement is mainly due to a synergetic effect of the UCNPs absorbing the near-infrared light and of the PN TiO2 presenting excellent light-scattering potency. Specifically, steady-state experiments reveal that the best-performing device shows only a small efficiency loss after 120 h of testing, exhibiting good device stability. The present work demonstrates the importance of composite photoanodes in enhancing the photovoltaic performances of solar cells.

Density Functional Theory (DFT) is the prevalent first principles computational method for determining the stacking fault energy (SFE) of face centered cubic (fcc) metals and alloys. Due to several theoretical and computational challenges, SFE determination for interstitial alloys with alloying elements such as carbon, nitrogen, and hydrogen, has so far been limited to few studies at relatively high interstitial content. We propose a new method, rooted in the axial interaction model, that allows rapid and robust mapping of SFE for virtually arbitrary interstitial contents. Instead of computing the total energy of a very large supercell to represent dilute interstitial solutions, representative interstitial-affected and bulk regions are treated separately at the equivalent volume. The SFE is obtained by balancing the SFE values of the regions with a lever rule approach. The method matches SFE values from the axial interaction model within ≤4 mJ.m−2 error, as validated for non-magnetic fcc Fe-N and paramagnetic fcc Fe-N and AISI 304 alloys. The significantly reduced computational workload and equidistant SFE mapping vs. interstitial content down to extremely low values allows accurate fitting of the SFE vs. interstitial content with only few datapoints. This further improves the computational efficiency. So far DFT-based SFE mapping was limited to purely substitutional alloys; we demonstrate the first-time DFT-based SFE mapping in fcc AISI 304 vs. N and Ni, revealing a non-additive contribution of N and Ni to the SFE. Finally, the remaining challenges and future application for high-throughput DFT SFE computation in interstitial alloys is discussed.

MoS2 is widely praised as a promising replacement for Pt as an electrocatalyst for the hydrogen evolution reaction (HER), but even today, it still suffers from low performance. This issue is tackled by using Mn3+ as a surface modifier to trigger sulfur vacancy formation and enhance electron transport in few-layered 2H MoS2. Only 10% of Mn is sufficient to transform the semiconductive MoS2 into an active HER electrocatalyst. The insertion of Mn reduces both HER onset potential and Tafel slope which allows reaching 100 mA/cm2 at an overpotential of 206 mV, ten times larger of what undoped MoS2 can achieve. The enhanced activity arises because Mn3+ introduces electronic states near the conduction band, promotes sulfur vacancies, and increases the hydrogen adsorption. In addition to its facile production and extended shelf-life, Mn–MoS2 exhibits an efficiency of 73% at 800 mA/cm2 and 2.0 V when used in proton exchange membrane water electrolyzers.

The ability to detect and inactivate spore-forming bacteria is of significance within, for example, industrial, healthcare, and defense sectors. Not only are stringent protocols necessary for the inactivation of spores but robust procedures are also required to detect viable spores after an inactivation assay to evaluate the procedure’s success. UV radiation is a standard procedure to inactivate spores. However, there is limited understanding regarding its impact on spores’ spectral and morphological characteristics. A further insight into these UV-induced changes can significantly improve the design of spore decontamination procedures and verification assays. This work investigates the spectral and morphological changes to Bacillus thuringiensis spores after UV exposure. Using absorbance and fluorescence spectroscopy, we observe an exponential decay in the spectral intensity of amino acids and protein structures, as well as a logistic increase in dimerized DPA with increased UV exposure on bulk spore suspensions. Additionally, using micro-Raman spectroscopy, we observe DPA release and protein degradation with increased UV exposure. More specifically, the protein backbone’s 1600–1700 cm–1 amide I band decays slower than other amino acid-based structures. Last, using electron microscopy and light scattering measurements, we observe shriveling of the spore bodies with increased UV radiation, alongside the leaking of core content and disruption of proteinaceous coat and exosporium layers. Overall, this work utilized spectroscopy and electron microscopy techniques to gain new understanding of UV-induced spore inactivation relating to spore degradation and CaDPA release. The study also identified spectroscopic indicators that can be used to determine spore viability after inactivation. These findings have practical applications in the development of new spore decontamination and inactivation validation methods., Published as part of The Journal of Physical Chemistry B virtual special issue “Advances in Cellular Biophysics”.

We consider the relationship between symmetries of two-dimensional autonomous dynamical systems in two common formulations; as a set of differential equations for the derivative of each state with respect to time, and a single differential equation in the phase plane representing the dynamics restricted to the state space of the system. Both representations can be analysed with respect to their symmetries, and we establish the correspondence between the set of infinitesimal generators of the respective formulations. We show that every generator of a symmetry of the autonomous system induces a well-defined vector field generating a symmetry in the phase plane and, conversely, that every symmetry generator in the phase plane can be lifted to a generator of a symmetry of the original system, which is unique up to constant translations in time. We exemplify the lift of symmetries in two cases; a mass conserved linear model and a non-linear oscillator.

Many strains among spore-forming bacteria species are associated with food spoilage, foodborne disease, and hospital-acquired infections. Understanding the impact of environmental conditions and decontamination techniques on the metabolic activity, viability, and biomarkers of these spores is crucial for combatting them. To distinguish and track spores and to understand metabolic mechanisms, spores must be labeled. Staining or genetic modification are current methods for this, however, these methods can be time-consuming, and affect the viability and function of spore samples. In this work, we investigate the use of heavy water for permanent isotope labeling of spores and Raman spectroscopy for tracking sporulation/germination mechanisms. We also discuss the potential of this method in observing decontamination. We find that steady-state deuterium levels in the spore are achieved after only ∼48 h of incubation with 30% D2O-infused broth and sporulation, generating Raman peaks at cell silent region of 2200 and 2300 cm−1. These deuterium levels then decrease rapidly upon spore germination in non-deuterated media. We further find that unlike live spores, spores inactivated using various methods do not lose these Raman peaks upon incubation in growth media, suggesting these peaks may be used to indicate the viability of a spore sample. We further observe several Raman peaks exclusive to deuterated DPA, a spore-specific chemical biomarker, at e.g. 988 and 2300 cm−1, which can be used to track underlying changes in spores involving DPA. In conclusion, permanent spore labeling using deuterium offers a robust and non-invasive way of labeling bacterial spores for marking, viability determination, and characterising spore activity.

Researchers generally agree that physics experts use mathematics in a way that blends mathematical knowledge with physics intuition. However, the use of mathematics in physics education has traditionally tended to focus more on the computational aspect (manipulating mathematical operations to get numerical solutions) to the detriment of building conceptual understanding and physics intuition. Several solutions to this problem have been suggested; some authors have suggested building conceptual understanding before mathematics is introduced, while others have argued for the inseparability of the two, claiming instead that mathematics and conceptual physics need to be taught simultaneously. Although there is a body of work looking into how students employ mathematical reasoning when working with equations, the specifics of how physics experts use mathematics blended with physics intuition remain relatively underexplored. In this presentation, we describe some components of this blending, by analyzing how physicists perform the rearrangement of a specific equation in cosmology. Our data consist of five consecutive forms of rearrangement of the equation, as observed in three separate higher education cosmology courses. This rearrangement was analyzed from a conceptual reasoning perspective using Sherin’s framework of symbolic forms. Our analysis demonstrates how the number of potential symbolic forms associated with each subsequent rearrangement of the equation decreases as we move from line to line. Drawing on this result, we suggest an underlying mechanism for how physicists reason with equations. This mechanism seems to consist of three components: narrowing down meaning potential, moving aspects between the background and the foreground and purposefully transforming the equation according to the discipline’s questions of interest. Finally, we discuss how being aware of the components of this underlying mechanism can potentially affect physics teachers’ practice when

The GTG Mathematics in Physics Education follows the philosophy of supporting physics understanding by the conscious use of mathematical structures in physics teaching. We discuss the possible roles of digital tools in promoting physics understanding by fostering sense making of computational models, using geometrical visualizations or interpreting app-generated diagrams in a physics context. We look into three types of digital tools: (a) Smartphone apps that allow data collection from the phone’s internal sensors to effortlessly produce graphical representations of the data. (b) GeoGebra, that combines different mathematical representations and allows their visualization and manipulation. (c) Computational modeling via Vpython where students can build or manipulate a computational model and compare it to experimental results. We will describe the potential of these tools to improve understanding of different mathematical features in physics, as well as obstacles that educators should take into account. In addition we present some empirical findings concerning graphs from smartphone apps and experiences from teacher professional development.

Electron magnetic circular dichroism (EMCD) is a powerful technique for estimating element-specific magnetic moments of materials on nanoscale with the potential to reach atomic resolution in transmission electron microscopes. However, the fundamentally weak EMCD signal strength complicates quantification of magnetic moments, as this requires very high precision, especially in the denominator of the sum rules. Here, we employ a statistical resampling technique known as bootstrapping to an experimental EMCD dataset to produce an empirical estimate of the noise-dependent error distribution resulting from application of EMCD sum rules to bcc iron in a 3-beam orientation. We observe clear experimental evidence that noisy EMCD signals preferentially bias the estimation of magnetic moments, further supporting this with error distributions produced by Monte-Carlo simulations. Finally, we propose guidelines for the recognition and minimization of this bias in the estimation of magnetic moments.

This paper describes the creation and description of a nuclear fuel isotopics dataset for irradiated fuel salt from a Molten Salt Reactor (MSR). The dataset has been created using the Monte-Carlo particle transport code, Serpent 2.1.32 (released February 24, 2021) and the calculation code SOURCES 4C (released October 09, 2002). The dataset comprises isotopic mass densities of 1362 isotopes (including fission products and major and minor actinides) and their corresponding contributions to decay heat, gamma activity, and spontaneous fission rates computed by Serpent 2.1.32 as well as overall neutron emission rates from spontaneous fission and (ɑ, n) reactions computed by SOURCES 4C. These quantities are computed for a model MSR core utilizing a full-core 3D model of the Seaborg Compact Molten Salt Reactor (CMSR) . The dataset spans a wide range of values of burnup (BU), initial enrichment (IE) and cooling time (CT) over which the above-mentioned quantities are reported. The structure of the dataset includes isotopic mass densities (in g/cm3), followed by isotope-wise contributions to decay heat (denoted by suffix ‘DH’ and reported in Watts), gamma photon emission rates (denoted by suffix ‘GS’ and reported photos per second), and spontaneous fission rates (denoted by suffix ‘SF’ and reported in fissions per second). In addition to these columns, the data also includes total neutron emission rates from 1) spontaneous fission (denoted by ‘SF’ and reported in neutrons per second per cm3), and 2) (ɑ, n) reactions (denoted by ‘AN’ and reported in neutrons per second per cm3). In total, the dataset has 310,575 rows of different combinations of fuel burnup, initial enrichment, and cooling time (BIC) values spanning the realistic possible range of these parameters. The dataset is made available for public use in a comma-separated value file that can be easily read using one of the numerous popular data analysis tools such as NumPy or Pandas.

The representation of atomic configurations through cluster correlations, along with the cluster expansion approach, has long been used to predict formation energies and determine the thermodynamic stability of alloys. In this work, a comparison is conducted between the traditional cluster expansion method based on density functional theory and other potential machine learning models, including decision tree-based ensembles and multi-layer perceptron regression, to explore the alloying behavior of different elements in multi-component alloys. Specifically, these models are applied to investigate the thermodynamic stability of triple transition-metal ((Ti-Mo-V)(3)C-2 MXenes, a multi-component alloy in the largest family of 2D materials that are gaining attention for several outstanding properties. The findings reveal the triple transition-metal ground-state configurations in this system and demonstrate how the configuration of transition metal atoms (Ti, Mo, and V atoms) influences the formation energy of this alloy. Moreover, the performance of machine learning algorithms in predicting formation energies and identifying ground-state structures is thoroughly discussed from various aspects., Funding Agencies|Royal Government of Thailand; Thailand Science Research and Innovation Fund Chulalongkorn University [IND66230003]; NSRF via the Program Management Unit for Human Resources & Institutional Development, Research and Innovation [B37G660011]; Asahi Glass Foundation [RES_66_104_2300_016]; Swedish Government Strategic Research Area in Materials Science on Functional Materials at Linkoeping University, Faculty Grant SFOMatLiU [2009 00971]; Swedish Foundation for Strategic Research through the Future Research Leaders 6 program [FFL 15-0290]; Swedish Research Council (VR) [2019-05403]; Knut and Alice Wallenberg Foundation; Sweden (Wallenberg Scholar) [KAW-2018.0194]; National Research Council of Thailand (NRCT) [NRCT5-RSA63001-04]; National Infrastructure for Supercomputing in Sweden (NAISS) at the National Supercomputer Center (NSC) -Swedish Research Council [2022-06725]

In this study, we address selection rules with respect to the polarization of the optical excitation of two color centers in 4 H -SiC and 6 H -SiC with potential for applications in quantum technology, the divacancy and the nitrogen -vacancy pair. We show that the photoluminescence of the axial configurations of higher symmetry ( C 3 v ) than the basal ones ( C 1 h ) can be canceled using any excitation (resonant or nonresonant) with polarization parallel to the crystal axis ( E L || c ). The polarization selection rules are determined using group -theoretical analysis and simple physical arguments showing that phonon -assisted absorption with E L || c is prohibited despite being formally allowed by group theory. A comparison with the selection rules for the silicon vacancy, another defect with C 3 v symmetry, is also carried out. Using the selection rules, we demonstrate selective excitation of only one basal divacancy configuration in 4 H -SiC, the PL3 line, and discuss the higher contrast and increased Debye-Waller factor in the selectively excited spectrum., Funding Agencies|Knut and Alice Wallenberg Foundation [KAW 2018.0071]; EU H2020 Project QuanTELCO [862721]; AFM (CeNano) [2021]; Swedish e-science Research Centre (SeRC); Swedish Research Council (VR) [2022-00276]; Japan Society for the Promotion of Science JSPS KAKENHI [20H00355, 21H04553]