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The skills taught in introductory programming courses are categorized into 1) \textit{explaining} the purpose of code, 2) the ability to arrange lines of code in correct \textit{sequence }, and 3) the ability to \textit{trace} through the execution of a program, and 4) the ability to \textit{write} code from scratch. Knowing if a programming skill is a prerequisite to another would benefit students, particularly those new to programming, by allowing them to encounter new topics in the optimal skill sequence. In this study, we used the conviction measure from association rule mining to perform pair-wise comparisons of five skills: Write, Trace, Reverse trace, Sequence, and Explain code. We used the data from four exams with more than 600 participants in each exam from a public university in the United States, where students solved programming assignments of different skills for several programming topics. Our findings matched the previous finding that tracing is a prerequisite for students to learn to write code. But, contradicting the previous claims, our analysis showed that writing code is a prerequisite skill to explaining code and that sequencing code is not a prerequisite to writing code. Our research can help instructors by systematically arranging the skills students exercise when encountering a new topic. The goal is to reduce the difficulties students experience when learning that topic.

Ni particle coarsening is a primary degradation mechanism in Ni/YSZ solid oxide cells, limiting the lifespan of these devices. In this study, we demonstrate the use of Scanning 3D X-ray diffraction (S3DXRD) with an unprecedented spatial resolution of 100 nm, to monitor the microstructural evolution within the 3D volume of a solid oxide cell subjected to ex situ heat treatment. Unlike conventional tomography, S3DXRD combines crystallographic information with spatial maps, enabling precise identification of grain boundaries and the determination of local curvature changes in the Ni microstructure. Our study reveals that the Ni phase undergoes significant structural changes during annealing, driven by grain growth. This transformation is characterized by a reduction in local curvature, particularly in regions where grains disappear. We observe that the disappearing grains are the smallest grains in the size distribution and are often located near pores. As a result, the most notable reduction in local curvature occurs at the Ni-pore interface. The quantitative characterization of polycrystalline microstructural evolution in Ni/YSZ system provides new insights into the mechanisms of Ni particle coarsening in SOC devices, potentially guiding strategies to enhance the long-term stability of SOC devices.

McXtrace is an established Monte Carlo based ray-tracing tool to simulate synchrotron beamlines and X-ray laboratory instruments. This work explains and demonstrates the new capability of GPU-accelerated McXtrace ray-tracing simulations. The openACC implementation is presented, followed by a demonstration of the achieved speed-up factor for several types of instruments across different types of hardware. The instruments achieve speed-up factors around \SIrange{250}{600}{} dependent on the instrument complexity. Instruments requiring repeated memory access might require optimised memory access procedures to avoid severe penalties in the simulation time when using GPUs. The importance of reducing the simulations was demonstrated for an aviation security application by comparing the simulation time of a projection of an energy-dispersive X-ray computed tomography instrument.

Quantum simulators are ideal platforms to investigate quantum phenomena that are inaccessible through conventional means, such as the limited resources of classical computers to address large quantum systems or due to constraints imposed by fundamental laws of nature. Here, through a digitized adiabatic evolution, we report an experimental simulation of antiferromagnetic (AFM) and ferromagnetic (FM) phase formation induced by spontaneous symmetry breaking (SSB) in a three-generation Cayley tree-like superconducting lattice. We develop a digital quantum annealing algorithm to mimic the system dynamics, and observe the emergence of signatures of SSB-induced phase transition through a connected correlation function. We demonstrate that the signature of phase transition from classical AFM to quantum FM happens in systems undergoing zero-temperature adiabatic evolution with only nearest-neighbor interacting systems, the shortest range of interaction possible. By harnessing properties of the bipartite Renyi entropy as an entanglement witness, we observe the formation of entangled quantum FM and AFM phases. Our results open perspectives for new advances in condensed matter physics and digitized quantum annealing.

Any quantum computation consists of a sequence of unitary evolutions described by a finite set of Hamiltonians. When this set is taken to consist of only products of Pauli operators, we show that the minimal such set generating $\mathfrak{su}(2^{N})$ contains $2N+1$ elements. We provide a number of examples of such generating sets and furthermore provide an algorithm for producing a sequence of rotations corresponding to any given Pauli rotation, which is shown to have optimal complexity., Comment: 6+12 pages, comments welcome! v2: addition example, minor edits throughout

Many programming languages allow programmers to regulate accessibility; i.e., annotating a declaration with keywords such as export and private to indicate where it can be accessed. Despite the importance of name accessibility for, e.g., compilers, editor auto-completion and tooling, and automated refactorings, few existing type systems provide a formal account of name accessibility. We present a declarative, executable, and language-parametric model for name accessibility, which provides a formal specification of name accessibility in Java, C#, C++, Rust, and Eiffel. We achieve this by defining name accessibility as a predicate on resolution paths through scope graphs. Since scope graphs are a language-independent model of name resolution, our model provides a uniform approach to defining different accessibility policies for different languages. Our model is implemented in Statix, a logic language for executable type system specification using scope graphs. We evaluate its correctness on a test suite that compares it with the C#, Java, and Rust compilers, and show we can synthesize access modifiers in programs with holes accurately.

End of semester student evaluations of teaching are the dominant mechanism for providing feedback to academics on their teaching practice. For large classes, however, the volume of feedback makes these tools impractical for this purpose. This paper explores the use of open-source generative AI to synthesise factual, actionable and appropriate summaries of student feedback from these survey responses. In our setup, we have 742 student responses ranging over 75 courses in a Computer Science department. For each course, we synthesise a summary of the course evaluations and actionable items for the instructor. Our results reveal a promising avenue for enhancing teaching practices in the classroom setting. Our contribution lies in demonstrating the feasibility of using generative AI to produce insightful feedback for teachers, thus providing a cost-effective means to support educators' development. Overall, our work highlights the possibility of using generative AI to produce factual, actionable, and appropriate feedback for teachers in the classroom setting., Comment: Accepted to SEFI 2024

In this project we explore the geometry of general metric spaces, where we do not necessarily have the tools of differential geometry on our side. Some metric spaces (X,d) allow us to define geodesics, permitting us to compare geodesic triangles in (X,d) to geodesic triangles in a so called model space. In Chapters 1 and 2 we first discuss how to define the length of curves, and geodesics on (X,d), and then using these to portray the notion of ``non-positive curvature'' for a metric space. Chapter 3 concerns itself with special cases of such non-positively curved metric spaces, called CAT(0) spaces. These satisfy particularly nice properties, such as being uniquely geodesic, contractible, and having a convex metric, among others. We mainly follow the book by Martin R. Bridson and Andr\'e Haefliger, with some differences. Firstly, we restrict ourselves to using the Euclidean plane E^2 as our model space, which is all that is necessary to define CAT(0) spaces. Secondly, we skip many sections of the mentioned book, as many are not relevant for our specific purposes. Finally, we add details to some of the proofs, which can be sparse in details or completely non-existent in the original literature. In this way we hope to create a more streamlined, self-contained, and accessible introduction to CAT(0) spaces., Comment: Mathematical project

During plastic deformation of metals and alloys, dislocations self-organise in cells, which subsequently continuously decrease in size. How and when these processes take place has remained elusive, because observations of the structural dynamics in the bulk have not been feasible. We here present X-ray diffraction microscopy movies of the structural evolution during tensile deformation of a mm-sized aluminium (111) single crystal. The formation and subsequent development of 40,000 cells are visualised. We reveal that cells form in a stochastic and isotropic manner already at 1% strain. We show that the cell size and dislocation density distributions are log-normal and bi-modal Gaussian distributions, respectively, throughout. This insight leads to an interpretation of the formation and evolution steps in terms of universal stochastic multiplicative processes. This work will guide dislocation dynamics modelling, as it provides unique results on cell formation.

In mathematical proof education, there remains a need for interventions that help students learn to write mathematical proofs. Research has shown that timely feedback can be very helpful to students learning new skills. While for many years natural language processing models have struggled to perform well on tasks related to mathematical texts, recent developments in natural language processing have created the opportunity to complete the task of giving students instant feedback on their mathematical proofs. In this paper, we present a set of training methods and models capable of autograding freeform mathematical proofs by leveraging existing large language models and other machine learning techniques. The models are trained using proof data collected from four different proof by induction problems. We use four different robust large language models to compare their performances, and all achieve satisfactory performances to various degrees. Additionally, we recruit human graders to grade the same proofs as the training data, and find that the best grading model is also more accurate than most human graders. With the development of these grading models, we create and deploy an autograder for proof by induction problems and perform a user study with students. Results from the study shows that students are able to make significant improvements to their proofs using the feedback from the autograder, but students still do not trust the AI autograders as much as they trust human graders. Future work can improve on the autograder feedback and figure out ways to help students trust AI autograders.

In [4] Sturmfels linked the Hilbert Nullstellensatz to Gr\"obner bases through final polynomials. In (loc. cit.) it was claimed that final polynomials always appear in a lexicographic Gr\"obner basis of a certain ideal. In this paper, we give a counterexample to this claim. We also show how the introduction of an extra variable restores the claim in a deformed setup, which we call extended final polynomials., Comment: 3 pages

Strength, ductility, and failure properties of metals are tailored by plastic deformation routes. Predicting these properties requires modeling of the structural dynamics and stress evolution taking place on several length scales. Progress has been hampered by a lack of representative 3D experimental data at industrially relevant degrees of deformation. We present an X-ray imaging based 3D mapping of an aluminum polycrystal deformed to the ultimate tensile strength (32% elongation). The extensive dataset reveals significant intra-grain stress variations (36 MPa) up to at least half of the inter-grain variations (76 MPa), which are dominated by grain orientation effects. Local intra-grain stress concentrations are candidates for damage nucleation. Such data are important for models of structure-property relations and damage.

Algorithm design is a vital skill developed in most undergraduate Computer Science (CS) programs, but few research studies focus on pedagogy related to algorithms coursework. To understand the work that has been done in the area, we present a systematic survey and literature review of CS Education studies. We search for research that is both related to algorithm design and evaluated on undergraduate-level students. Across all papers in the ACM Digital Library prior to August 2023, we only find 94 such papers. We first classify these papers by topic, evaluation metric, evaluation methods, and intervention target. Through our classification, we find a broad sparsity of papers which indicates that many open questions remain about teaching algorithm design, with each algorithm topic only being discussed in between 0 and 10 papers. We also note the need for papers using rigorous research methods, as only 38 out of 88 papers presenting quantitative data use statistical tests, and only 15 out of 45 papers presenting qualitative data use a coding scheme. Only 17 papers report controlled trials. We then synthesize the results of the existing literature to give insights into what the corpus reveals about how we should teach algorithms. Much of the literature explores implementing well-established practices, such as active learning or automated assessment, in the algorithms classroom. However, there are algorithms-specific results as well: a number of papers find that students may under-utilize certain algorithmic design techniques, and studies describe a variety of ways to select algorithms problems that increase student engagement and learning. The results we present, along with the publicly available set of papers collected, provide a detailed representation of the current corpus of CS Education work related to algorithm design and can orient further research in the area.

Optimizing grain boundary characteristics in polycrystalline materials can improve their properties. Many processing methods have been developed for grain boundary manipulation, including the use of intense radiation in certain applications. In this work, we used X-ray free electron laser pulses to irradiate single-crystalline bismuth selenide (Bi2Se3) and observed grain boundary formation and subsequent grain rotation in response to the X-ray radiation. Our observations with simultaneous transmission X-ray microscopy and X-ray diffraction demonstrate how intense X- ray radiation can rapidly change size and texture of grains., Comment: 37 pages, 11 figures including 6 supplemental figures

Cadmium Telluride (CdTe) solar cell technology is a promising candidate to help boost green energy production. However, impurities and structural defects are major barriers to improving the solar power conversion efficiency. Grain boundaries often act as aggregation sites for impurities, resulting in strain localization in areas of high diffusion. In this study, we demonstrate the use of scanning 3D X-ray diffraction microscopy to non-destructively make 3D maps of the grains, their phase, orientation, and local strain within a CdTe solar cell absorber layer with a resolution of 100 nm. We quantify twin boundaries and suggest how they affect grain size and orientation distribution. Local strain analysis reveals that strain is primarily associated with high misorientation grain boundaries, whereas twin boundaries do not show high strain values. We also observe that high-strain grain boundaries form a continuous pathway connected to the CdS layer. Hence, this high-strain region is believed to be associated with the diffusion of sulfur from the CdS layer along grain boundaries. This hypothesis is supported by SEM EDS and X-ray fluorescence experiments. The method and analysis demonstrated in this work can be applied to different polycrystalline materials where the characterization of grain boundary properties is essential to understand the microstructural phenomena.

With the approaching second quantum revolution, the study of quantum thermodynamics, particularly heat flow, has become even more relevant for two main reasons. First, understanding heat and other types of noise is essential for protecting quantum information and preventing decoherence. Second, the ability to manufacture and control quantum systems developed for the quantum computer allows for experimental study of quantum thermodynamics in entirely new settings. In this thesis, several systems involving quantum systems in contact with baths are studied theoretically in experimentally available settings. First, two rectification or diode setups for heat currents are proposed using a dark-state mechanism. In one system, the dark-state mechanism is imperfect but very robust. In the other system, the dark-state mechanism relies on quantum entanglement and is much better but more fragile towards decoherence. Next, a quantum version of the Wheatstone bridge is built using the same entanglement-powered dark state mechanism. After having studied several boundary-driven quantum systems, the lessons learned are generalized into resonance conditions using a general linear chain of weakly interacting chains of strongly interacting spins. The final two chapters focus on the ability to study statistical physics in realizable quantum systems. First, a Maxwell's demon setup is proposed. A demon-controlled qutrit is coupled to two non-Markovian baths. The information back-flow from the non-Markovian baths allows the demon to more effectively transfer heat from the cold bath to the hot bath. Second, the Mott insulator to superfluid phase transition in a lattice of transmons is examined. The ground state has a variable particle number and is prepared using adiabatic state preparation. This allows for the exploration of the entire phase diagram., Comment: PhD thesis

We report the discovery of two directly imaged, giant planet candidates orbiting the metal-rich DAZ white dwarfs WD 1202-232 and WD 2105-82. JWST's Mid-Infrared Instrument (MIRI) data on these two stars show a nearby resolved source at a projected separation of 11.47 and 34.62 au, respectively. Assuming the planets formed at the same time as their host stars, with total ages of 5.3 and 1.6Gyr, the MIRI photometry is consistent with giant planets with masses about 1-7 Jupiter Masses. The probability of both candidates being false positives due to red background sources is approximately 1 in 3000. If confirmed, these would be the first directly imaged planets that are similar in both age and separation to the giant planets in our own solar system, and they would demonstrate that widely separated giant planets like Jupiter survive stellar evolution. Giant planet perturbers are widely used to explain the tidal disruption of asteroids around metal-polluted white dwarfs. Confirmation of these two planet candidates with future MIRI imaging would provide evidence that directly links giant planets to metal pollution in white dwarf stars., Comment: 9 Pages, 3 Figures, 2 Tables, Accepted for Publication in The Astrophysical Journal Letters

Measurement-based quantum computation (MBQC) is a paradigm for quantum computation where computation is driven by local measurements on a suitably entangled resource state. In this work we show that MBQC is related to a model of quantum computation based on Clifford quantum cellular automata (CQCA). Specifically, we show that certain MBQCs can be directly constructed from CQCAs which yields a simple and intuitive circuit model representation of MBQC in terms of quantum computation based on CQCA. We apply this description to construct various MBQC-based Ans\"atze for parameterized quantum circuits, demonstrating that the different Ans\"atze may lead to significantly different performances on different learning tasks. In this way, MBQC yields a family of Hardware-efficient Ans\"atze that may be adapted to specific problem settings and is particularly well suited for architectures with translationally invariant gates such as neutral atoms., Comment: 16 pages, 12 figures