Papers

Active learning has been shown to be more beneficial for student learning than lecturing. Consequently, researchers have developed named active learning strategies for use in physics instruction. To increase adoption and support implementation of these named methods, it is important to understand the backgrounds and experiences of instructors who use them. In this study, we interviewed 20 introductory physics and astronomy instructors who use one of Student-Centered Active Learning Environment with Upside-Down Pedagogies (SCALE-UP), Investigative Science Learning Environment (ISLE), Tutorials in Introductory Physics and Astronomy, or Peer Instruction to gain insight into their teaching experiences, professional development, pathways to learning about their method, and supports for and difficulties in implementation. We find for our sample that all implementers are involved with the discipline-based education research community, but there is variation in the extent of engagement. While instructors identify a variety of supports for their implementation, such as from the broader education community and departmental administration, the difficulties they experience are representative of both long-standing issues associated with active learning adoption (e.g., timing constraints) and new issues related to emergent technologies (e.g., Artificial Intelligence). Finally, we uncover differences in implementers across the four named methods, particularly related to their training for the method and the supports they received for implementation. Together, these findings underscore the importance of supporting multiple dissemination avenues for named active learning methods, point to a possible need for more training opportunities for SCALE-UP and ISLE in particular, and identify nascent issues in the contemporary active learning classroom that future work may further characterize and address.

Students often perceive scientific experiments as clean, straightforward procedures with predictable outcomes. Students' beliefs about the nature of experimental physics typically remain inconsistent through the initial stages of undergraduate education. In reality, experimental work in physics involves hands-on activities such as soldering circuits, assembling provisional setups, and building functional mock-ups from simple materials before reliable measurements can be achieved. To address this gap, we designed a laboratory activity in which students were completely involved in the experiment design, construction and operation with the final goal of measuring the speed of light with a low-cost and compact setup. The educational objective of this activity was double: firstly, to make students aware of the importance of experimental choices and constraints in the setup design and secondly, to discover the potentiality of semiconductor technologies. As far back as the 1990s, with the spread of compact disk players, laser diodes and photodiodes capable of fast timing performance in the order of nanoseconds became largely available. In the last decades, consumer electronic devices made high performance technologies ubiquitous. Nevertheless, the idea of measuring ultrashort time intervals and the relevance of such measurements in science and technology remain unknown to most students. Nowadays, digital instruments with significant performance such as waveform generators and oscilloscopes are affordable for high school physics labs, paving the way to a closer contact with the world of experimental physics.

Effective models make complex quantum dynamics tractable by retaining only the states, processes, and timescales relevant to a given physical question. Their predictive power, however, depends on treating the retained manifold, initial state, observables, micromotion, dissipative channels, and eliminated degrees of freedom consistently. We develop a unified framework for constructing and validating effective descriptions using projection methods, Schrieffer–Wolff transformations, Magnus expansions, adiabatic elimination, small rotations, time coarse graining, and Floquet theory. The quantum Rabi model and its dispersive limits serve as recurring benchmarks for identifying control parameters, virtual processes, spectral corrections, observable dressing, and breakdown. Higher-order resonances and applications to collective light–matter coupling, Raman processes, spin-chain buses, lossy mediators, and driven lattices illustrate how effective interactions can be interpreted and designed. A physical prediction is organized into three order-consistent steps: encoding into the retained description, evolution under the effective dynamics, and reconstruction of the physical observable. This viewpoint exposes failures caused by leakage, small denominators, neglected micromotion, inconsistent observables, memory effects, or incorrectly transformed dissipation, while linking derivation, physical interpretation, and mechanism-guided discovery. Companion notebooks provide QuTiP implementations, convergence tests, and microscopic-to-effective comparisons.

Interactive quantum circuit simulators are increasingly used to support introductory quantum computing education for learners from varied disciplinary backgrounds. These environments can also generate detailed response logs of submitted circuits, but such data are rarely transformed into evidence that instructors can use for course redesign and development. We present a learning analytics framework for quantum circuit simulator tasks and report its task-level branch on anonymised logs from an introductory quantum computing course delivered in the TIM learning environment. The task branch characterises exercises through participation, completion, first-attempt accuracy, valid-attempt counts, sessionised active time, and observed answer-space reporting of common correct and incorrect constructions. The dataset covers the 2024-2025 cohort of 492 learners, 47,533 valid submissions, and 21 obligatory quantum circuit exercises. The framework identifies bottleneck tasks, broad solution spaces, and recurring wrong-answer patterns that are not visible from final scores alone. Its most distinctive output is a plain-text representation of the observed answer space, designed to make open-ended circuit submissions directly interpretable to instructors. We show how response logs can reveal actionable task-design issues and support concrete course redesign. A learner-level branch is retained only as an ongoing research extension and is not a central empirical contribution of the present paper.

I propose a simple visualization for pure two-qubit states, constructed from three components: two Bloch balls for the marginal qubits (the mixed states obtained by ignoring the other qubit, respectively) and an entanglement component consisting of a rotoreflection and a contraction. I prove that this picture accurately captures the local and global structure of the relevant state space without gaps or degeneracies: the underlying parametrization is a global diffeomorphism onto the state space. Finally, I use this picture to visualize conditional states, the entanglement degree(s) of freedom, and single qubit rotations.

The moving-coil meter provides a simple context in which to model deterministic electromechanical dynamics, thermal fluctuations, and electronic readout. The movement is a linear electromechanical system in which electrical resistance and intrinsic mechanical damping act as two independent dissipative channels, each accompanied by thermal fluctuations. The stored energy provides a Lyapunov function for stability, and the algebraic Lyapunov equation yields the stationary covariance in closed form. The result exhibits equipartition among the energy terms; damping is shown to reshape the temporal memory of the fluctuations without changing their steady-state variance, giving a thermal floor of a few picoamperes for a representative movement. Exact stochastic integration reproduces the stationary covariance and autocorrelation structure; the covariance is also recovered by spectral integration. Embedding the movement in an active current-drive readout shifts attention to the noise of the complete readout, which a design-stage estimate expresses as a few parts per million of full scale, growing as the input sensitivity increases. The example illustrates that measurement sensitivity and resolution cannot be considered independently. The treatment is aimed at master's-level students in physics with some background in statistical physics and stochastic processes, and basic familiarity with analog electronics.

The CosmicWatch Desktop Muon Detector (v3X) is a compact and low-cost scintillator-based instrument designed to detect ionizing radiation, including cosmic-ray muons. Built around a plastic scintillator, a silicon photomultiplier (SiPM), and a dual-core Raspberry Pi Pico microcontroller, the v3X achieves a 400 microsecond dead time per event, sustained event logging at 700 Hz, and two-detector coincidence triggering for more accurate counts. This paper first summarizes the design, firmware, and demonstrated performance of the v3X prototype. It then outlines the design changes needed to prepare the detector for operation aboard a satellite, including a passive copper thermal strap that conducts heat from the microcontroller to the spacecraft chassis, a dedicated flight enclosure, material changes to meet outgassing standards, and a Controller Area Network (CAN) bus interface to connect the detector to the host spacecraft. The flight unit is targeted for launch via Oligo Space.

In a bilateral electromechanical transducer, energy exchange across the electromechanical interface allows the electrical termination to modify the mechanical response through electromagnetic feedback. The paper develops this idea from a simple magnetic pendulum, describing the electromechanical coupling through the flux linkage as a function of rotation angle. Torque and back electromotive force then follow from the same coupling function, making the bilateral nature of the energy conversion explicit. A radial-field moving-coil system provides a particularly simple realization in which the coupling becomes independent of angular position and the resulting electromagnetic damping is controlled by the electrical termination. A two-port representation then identifies this damping as an impedance-reflection effect and provides a quantitative criterion for separating the electrical and mechanical time scales. A numerical example compares ideal current drive with critical electrical termination and confirms the reduced second-order description against the full third-order dynamics. The resulting treatment provides a systematic and physically transparent route from familiar undergraduate electromagnetism and oscillator dynamics to electromechanical feedback, bilateral transduction, and the effect of loading in coupled physical systems.

In physics instruction, equations are often treated primarily as tools for obtaining numerical results. Yet physicists also use them to describe dependencies, explain why those dependencies hold, predict what happens in new situations, test expressions against physical knowledge, and explore consequences that are not immediately apparent. Although such uses appear throughout the physics education literature, they have not been brought together in a systematic account, and the terminology used to describe them remains inconsistent. Drawing on research in mathematics education on symbol sense and the function concept, we distinguish six epistemic functions of physics equations: calculating, describing, explaining, predicting, evaluating, and exploring. We then characterize six strategies through which these functions can be realized: dimensional analysis, order of magnitude analysis, covariational analysis, special case analysis, limiting case analysis, and formal analogies, illustrating each with examples from introductory physics. To examine how these strategies are viewed within the discipline, we surveyed 31 physicists at one university faculty about five of the strategies. Respondents regarded the strategies as indispensable to physics, judged limiting case analysis to be more difficult for students than dimensional analysis, and reported that their own courses could devote more time to them. By distinguishing what physicists use equations for from the strategies by which they do so, the paper provides a vocabulary for sensemaking of physics equations and specifies what explicit instruction in these strategies involves.

Public Exams are an assessment system designed in the context of Biology Education Research to increase student engagement in the exam design process. Students are shown incomplete versions of test questions ahead of time, with the format of the question revealed but some details withheld. Students are also given the chance to provide feedback on the questions, refining them for clarity before the actual exam. In this study, we examined the impact of Public Exams on the experiences and outcomes of N = 42 students in an introductory physics course at New Mexico State University. Using a combination of online numerical surveys, open-ended written responses, and student grade data, we conducted a mixed-methods analysis of the impact of Public Exams on students in this class. We also applied our method to re-analyze the publicly available data of Wiggins et al. Students reported various benefits of Public Exams, including reduced test anxiety and directing to core concepts, and we observed a significant positive correlation between the participation rate of students in editing public exam questions and their average exam grade. But students also expressed dissatisfaction with the incomplete information provided on problems, and they had a less positive response rate than the control sample. In other qualitative responses, students also consistently highlighted the applications of procedural knowledge as most helpful to their learning and a recommendation for the future. Our findings suggest that physics students at NMSU do benefit from Public Exams through reduced anxiety and directing to core concepts, but that the Public Exam system, as previously described, is not optimized for use in physics. We attribute this to the particular emphasis in physics on applying procedural knowledge and suggest modifications of the Public Exam system to better tailor it to a physics context.

Earth's ionosphere is primarily generated by the Sun's ionization of atoms in the upper atmosphere. This plasma environment is highly dynamic, exhibits strong spatial and temporal, variations and significantly impacts power systems, navigation, and satellite and ground communications. The University of Delaware Ionospheric Probe (UDIP) was developed as a hands-on learning experience for University of Delaware students on the ionosphere itself and on the development of space technology. Students (mostly undergraduates) have led all aspects of the experiment including mission planning, electronics development, mechanical development, software development, and scientific data analysis. The present study is intended as a guide to readers on how the development of space and near-space flight missions can be successfully incorporated into an undergraduate physics curriculum. The fourth version of the experiment (UDIP-4) flew along with student experiments from across the USA on the 2024 RockSat-C sounding rocket, which was launched from NASA Wallops Flight Facility. During the flight, UDIP-4's Langmuir probe successfully measured the ionosphere's density profile – electron density as a function of altitude – up to an apogee of 114 km. Though the measured density profile agrees well overall with the predictions of theoretical models, UDIP-4 identified a thin layer of enhanced electron density at an altitude of approximately 110 km that is consistent with a sporadic E layer.

Multiple-choice questions are a staple of educational assessment due to their efficiency, but their diagnostic ability is inherently limited. Traditional psychometric techniques infer misconceptions by fitting models to predetermined data patterns, making them ineffective for analysing small, novel, or non-standardised samples where such prior trends are absent. To address this, we introduce a new distractor analysis method based on Information Theory, which treats the randomness in incorrect answers not as noise but as a measurable signal in student answer patterns. By examining the entropy of distractor choices alongside overall accuracy, our approach offers a sample-sized-independent framework for classifying performance. Cross-referencing low-scoring item-level response data against independently documented misconceptions on a standard mechanics inventory shows that, for items identified as most concentrated (lowest degree of randomness), a majority of incorrect responses select the exact response coded to that item's named, interview-validated misconception. Furthermore, items independently flagged elsewhere as diagnostically unreliable are exactly the items the measure identifies as having the highest degree of randomness. The pedagogically actionable cases are those with low degree of randomness in a class's incorrect answers, signalling a shared, re-teachable misconception, whereas a high degree of randomness chiefly serves as the null case against which that concentration is judged. Our analysis is intended as a fast, single-administration triage step: a practical, theory-driven complement to established distractor-analysis methods that helps instructors flag which items warrant closer, more resource-intensive investigation.

Science teachers frequently search for documentary excerpts not by describing what appears on screen, but by querying the abstract concepts they intend to teach. This use case exposes a limitation of existing language-based video moment retrieval methods, which typically assume that queries describe observable events, whereas instructional search requires retrieving concrete visual phenomena that instantiate an underlying scientific principle. We study this setting as concept-to-example video retrieval, an abstract-needle-in-a-haystack problem where compact curriculum concepts must be grounded in temporally sparse documentary evidence. To bridge this abstraction gap, we propose Concept-Driven Domain Adaptation (CDDA), a three-stage framework for adapting two-tower vision-language models to concept-level retrieval. CDDA treats concepts as intermediate semantic anchors: it first structures the textual embedding space with textbook and teacher-handbook example-concept pairs, then transfers this concept-aware geometry to documentary visuals under a frozen visual encoder, and finally jointly adapts both encoders with sparse visual concept supervision. From a geometric perspective, this staged alignment reduces text-concept and vision-concept angular gaps, thereby encouraging concept-level adaptation while preserving the pretrained model's concrete image description alignment. On a curated middle-school physics retrieval benchmark, CDDA achieves stronger pedagogically oriented concept retrieval than several competitive multimodal baselines, including Qwen3-VL-Embedding-2B, while maintaining concrete image-text matching after adaptation.

Undergraduate research experiences provide students with an opportunity to apply knowledge learned in the classroom to authentic scientific problems. In this work, we describe the development of a special-topics course in Plasma Physics and Engineering (PPE) at a small liberal arts college using a Course-Based Undergraduate Research Experiences (CUREs). During the first half of the semester, students learned fundamental plasma physics and dusty plasma concepts through traditional lectures and homework. During the second half, they applied this knowledge to investigate an unanswered research question: why does the levitation time of growing nanoparticles decrease in the presence of a magnetic field? Students learned and used Langmuir probe and optical emission spectroscopy diagnostics to characterize an argon plasma over a range of magnetic-field strengths. Their measurements showed a general decrease in electron density with increasing magnetic field strength, while optical emission measurements confirmed a reduction in carbonaceous nanoparticle growth-cycle time from acetylene. Using the measured plasma parameters, students estimated the nanoparticle charge and developed the hypothesis that a reduction in electron density leads to a smaller negative dust charge and consequently a weaker electric force available to levitate the particles as a function of increasing magnetic field strength between 50 and 330 Gauss. Students subsequently disseminated their results through research poster presentations at conferences. Course evaluations and E-CLASS responses also indicated positive student experiences with the laboratory and research components of the course. This work demonstrates one approach for integrating plasma physics education and authentic research in an undergraduate curriculum at a small liberal arts institution.

The rapid adoption of generative artificial intelligence (GenAI) in higher education has introduced a critical pedagogical paradox: while these systems possess extraordinary capacity for information retrieval and synthesis, their default operational mode of supplying immediate, unprompted answers actively undermines the cognitive processes upon which genuine scientific understanding is built. This paper presents NuPaD (Nuclear & Particle Physics – Deep Learning Tutor), a novel pedagogical framework designed for the graduate-level subatomic physics curriculum. For such advanced courses, instruction naturally shifts toward inquiry-driven, problem-based learning, making it an ideal environment to use GenAI to explore complex, open-ended physical questions rather than merely querying established facts. The framework consists of three tightly coupled and easy-to-use components: a primary agent instruction file that enforces a structured problem-based learning protocol, a purpose-built textbook optimized for precise parsing by privacy-preserving local GenAI, and a concise companion file that bridges the knowledge gap between the textbook and GenAI, alongside a comprehensive dynamic skill set for specialized tasks. We explain in detail the architectural principles of the modular NuPaD framework, the design philosophy of the Markdown-native textbook format, and the underlying GenAI regulation principles. By redefining the interaction loop between student and model, this framework transforms GenAI from a passive answer engine into an active, personalized tutor, ensuring that it accelerates rather than bypasses the development of deep learning and scientific reasoning.

We present a traceable instructional module that maps documented learner difficulties in quantum superposition and measurement to explicit learning goals, classroom activities, and assessment evidence. Using the general two-level Hamiltonian as the organizing physics framework, the module implements this mapping through a five-activity classroom sequence and grading rubric targeting four recurrent difficulties: interpreting superposition as physical splitting, confusing a quantum state with its representation or measurement context, mixing theoretical probabilities with finite-sample frequencies, and using inconsistent notation across states, amplitudes, probabilities, and measurement outcomes. The instructional design is organized through a reversible mapping from documented barriers to learning goals, activity responses, and assessment evidence, allowing each assessment item to be traced back to the specific difficulty it is intended to address. The module uses the standard general two-level Hermitian Hamiltonian, represented by a \(2\times2\) matrix, as the physical framework connecting its eigenstates, computational-basis amplitudes, Born probabilities, and sampled outcomes. The contribution is a challenge-targeted instructional design that organizes standard quantum mechanics into a traceable classroom sequence linking documented learner difficulties to learning goals, activities, assessment criteria, and implementation guidance. The mathematical structure uses standard Hamiltonian and measurement conventions, supporting direct incorporation into an undergraduate quantum-mechanics course.

STEM student competitions aim to identify capable, science-interested students and further support them in developing their STEM-related abilities and interests. When such students do not participate, they may appear to be missed not only by the competition but by this form of support altogether; unless they are reached through other competitions. The present study therefore investigated to what extent students who would likely have succeeded in the German Physics Olympiad are missed by it. The study sample comprised 282 Olympiad participants and 1,103 non-participants from academic-track secondary schools, all assessed on 31 indicators spanning sociodemographic background, cognitive abilities, self-related beliefs, motivational variables, personality traits, vocational interests, and prior participation across other STEM competitions. Three machine learning models (elastic net, random forest, gradient boosting) were trained on the participant sample to predict first-round success based on those indicators. The elastic net was found to perform best. Although predictive accuracy was modest, the model proved well-calibrated, supporting valid group-level inferences. Only a few variables predicted success: mathematics skills, physics- and engineering-related skills, and having skipped a grade were positive predictors, whereas conventional vocational interests were a negative predictor. When applied to the non-participants, the model identified 43 students (3.9%) as potentially successful. Crucially, 74% of these students had previously entered at least one selective STEM competition, leaving only 11 students (ca. 1% of all non-participants) entirely unreached by the selective STEM competition system. These findings indicate that the majority of potentially successful non-participants are not absent from the selective STEM competition system but are engaged by it through other domains.

The idea of engaging critically and creatively with physics theories is a stretch for many physicists and physics educators. Most physicists become enculturated into the belief that physics definitions, laws, and equations are read from the book of nature. However, this belief obscures how theories are collectively negotiated by people in specific socio-political and personal conditions, and how students' particular ideas and intuitions will inevitably shape their own practice of science. To help students build their skills for collective theory-building, we suggest a pedagogy for physics in which students actively negotiate the laws and definitions of theories.

The African School of Fundamental Physics and Applications, also known as the African School of Physics (ASP), was initiated in 2010, as a three-week biennial event, to offer additional training in fundamental and applied physics to African students with a minimum of three-year university education. Since its inception, ASP has grown to be much more than a school. ASP has become a series of activities and events to support academic development of African students, teachers, high school pupils (learners) and faculties. We report on the ninth African School of Physics, ASP2026, organized in Kenya, on July 5–19, 2026. ASP2026 included programs for university students, high school teachers and learners.

Can a system with more stored energy cool faster than one with less? An overdamped resistor–inductor–capacitor (RLC) circuit offers a classical, experimentally accessible spectral Mpemba analogue: both states lose energy monotonically, yet the initially higher-energy state can cross below the lower-energy one. The reason is that initial energy alone does not determine the relaxation path; initial charge and current set how strongly the slow and fast decay modes are excited. We develop this mechanism from deterministic to stochastic and open-system descriptions. For the classical circuit, we derive the modal preparation conditions and crossing criterion, explain geometrically why equal-energy states can relax differently, and confirm the effect experimentally by reconstructing charge, current, and energy from oscilloscope traces. The inversion survives when the circuit is driven by externally injected white noise. An equilibrium Ornstein–Uhlenbeck treatment separates information carried by the ensemble mean from that stored in its covariance: centered Gibbs preparations preserve mean-energy ordering, while displaced or anisotropic Gaussian states can encode distinct slow and fast sectors. A Fokker–Planck generator then bridges to Markovian quantum dynamics. For a thermally damped quantum harmonic oscillator, the mean bare-energy excess decays with a single exponential factor, forbidding energy-order inversion for finite mean occupation. A below-threshold parametric oscillator restores slow and fast quadrature sectors, allowing crossings controlled by displacement and covariance. The Liouvillian formulation shows that observed relaxation depends jointly on the generator spectrum, the modes populated by preparation, and the modes visible to the observable.

The paper examines the energy-mass relation of Special Relativity (SR), its status and interpretation, through the lens of classical/non-quantum relativistic field theory. The latter arguably constitutes the fullest embodiment of SR as what Einstein labelled a "principle theory". It forms, we propose, the most appropriate perspective also for understanding the energy-mass relation. In a field-theoretic setting, the key notion is a system's energy-momentum (in local/differential or global/integral form, defined via a suitable energy-stress complex). The energy-mass relation then expresses the role that a system's _rest_-energy (provided it exists) plays as the functional counterpart of mass: thanks to important theorems, rest-energy qualifies as its field-theoretic generalisation or successor term. That is, while mass is dispensed with as a fundamental notion, rest-energy retains some—but not all—of its salient functional roles; for special cases, it turns out to be directly correlated with mass. In field theory as a general framework for more specific relativistic theories, energy-momentum replaces mass as the essential notion—a profound, yet often overlooked revision in basic physical concepts. Conservation in particular is guaranteed only for energy-momentum, but no longer for mass. In several regards, energy-momentum fuses energy, momentum and mass, with novel connections amongst them and concomitant physical effects. Situating the energy-mass relation within field theory is a surprisingly neglected, but deeply insightful vista for clarifying and philosophically reflecting on SR's foundations. The field-theoretic interpretation achieves a compelling inner coherence and unifying power, and ties it to the rich heuristic resources of field theory, crucial for post-1905 developments in physics.

The Tangent Galvanometer (TG) is a standard undergraduate laboratory experiment for estimating the horizontal component of Earth's magnetic field (BH) by measuring the angle of deflection of a magnetic needle corresponding to the current flowing through a circular coil. In this study, an artificial neural network (ANN) is used as a complementary data-driven model to predict the value of BH. A dataset comprising 225 observations obtained using 50-turn and 500-turn coils was used for developing the ANN model. After quality control, 223 observations were retained and divided into training (70%), validation (15%), and testing (15%) subsets. The model was optimized using a feed-forward neural network with Tanh activation. Three different models (Models A, B, and C) with different input variables were compared for optimum performance. Model C used five input variables: current, deflection angle, tan(theta), magnetic field produced by the coil, and number of turns. The addition of tan(theta) produced a substantial improvement in prediction performance, which was further improved by including the magnetic field produced by the coil. Model C gave the best test performance, with R2 = 0.99053, RMSE = 0.54076 microT, and MAE = 0.32940 microT. The experimental and ANN-predicted values of BH were also compared with an adopted local geomagnetic reference value of 39.0 microT. The mean experimental and ANN-predicted values were 37.38898 microT and 37.32161 microT, respectively. The results demonstrate the usefulness of ANN as a complementary tool for analyzing experimental variability and nonlinear relationships in an undergraduate physics laboratory experiment.

The speed of sound in air can be determined from the resonance frequencies of the harmonic waves inside a thin cylindrical tube. A pressure wave is generated in the tube by striking several times one of its ends with an open hand and keeping the hand in place. In this way pulses of short duration are produced which propagate along the tube and decompose into a superposition of harmonic waves whose frequencies are determined by the harmonics present in a tube open at one end and closed at the other. The tube thus acts as a filter that reinforces those harmonic waves exhibiting an antinode of acoustic pressure at the closed end and a node at the open end. Their frequencies are determined by these boundary conditions, while waves with different frequencies cancel out by destructive interference. Recording the sound with a microphone connected to a computer and analyzing its spectrum with freely available software, the resonance frequencies are obtained and the speed of sound is determined with an accuracy better than $0.5\%$. The whole experiment requires nothing but a tube, a microphone and free software, so it is inexpensive, takes a few minutes to set up and is well suited to introductory physics laboratories.

FireworksWeb is a web-based event display utilizing a C++ ROOT-Eve backend with SAPUI5 frontend for interactive 3D visualization of particle physics events directly in the browser. Building upon ROOT-Eve and RenderCore, it eliminates local software installation while maintaining professional-grade event display capabilities. FireworksWeb is currently deployed for live event monitoring in the CMS control room, demonstrating its reliability for real-time data visualization in production environments. The CMS experiment has made a large amount of collision datasets publicly available through the CERN Open Data portal, which are the valuable resources for education, outreach, and research. We have extended FireworksWeb to enable visualization of these open datasets, making particle physics data accessible to diverse audiences without requiring local software installation. Our prototype implementation includes standalone cameras, event filters, configurable collection settings, and projection controls with fish-eye distortion for cylindrical geometries. The web architecture communicating via CGI enables dataset queries and filtered event selection based on physics criteria. We demonstrate the prototype with CMS Open Data events, discuss the technical architecture, and outline applications for education, public outreach, and exploratory physics analysis.

Quantum physics underpins the emerging quantum technology era, yet its counterintuitive principles remain challenging for beginners. Video games offer a promising medium to make these principles accessible through an interactive experience. Conventional gameplay, even when featuring extraordinary abilities of the protagonist, largely draws on classical intuition, shaping the player's reflexes through familiar expectations of motion, action, and consequence. Here, we propose extending these reflexes into the quantum domain by embedding superposition, unitary evolution, quantum gates, and measurement into the game. Central to this approach is a new controller action, the Gate of Fate, which allows players to engage in quantum operations through their gaming decisions. We demonstrate the concept in a Tetris-based prototype, with progressively structured levels that introduce quantum operations and their consequences. We also outline extensions to role playing games, in which the behavior and difficulty of antagonists can respond to player's developing quantum gaming reflexes. By turning abstract quantum concepts into actionable game mechanics, this approach aims to cultivate quantum intuition through play, offering opportunities for both quantum pedagogy and more sophisticated game design.

The Starterkit Lessons online and Starterkit Workshops held in Geneva each year have been the main method of onboarding newcomers to the LHCb experiment since its founding in 2015. The new software corresponding to Upgrade 1 of the LHCb and Run 3 of datataking at the LHC has necessitated a new version of this Starterkit to be written. This new version has made several improvements over the old one, with increased maintainability through testing of examples in CI pipelines, and has also allowed for translations of the Starterkit Lessons. In late 2025 the Run 3 Starterkit lessons were translated into Mandarin Chinese, to allow for a sibling Starterkit event to take place in China, with a dedicated liaison role set up to ensure synchronization between the two translations. To measure the success of the Chinese Starterkit Lessons, analytics have been added revealing that roughly 22% of all visits to the Starterkit website will access at least one Chinese-language page.

This study examines the extent to which physics graduate teaching assistants (TAs) are aware of introductory physics student thinking and the types of challenges introductory students commonly have with energy and momentum concepts, which is important for implementing active learning methodologies and supporting diverse learners in physics courses. We present findings from a TA professional development course and discuss an approach to investigate TAs' pedagogical content knowledge, specifically their ability to recognize introductory student conceptual difficulties. We investigated 70 first-year graduate TAs' ability to identify common introductory physics student difficulties on the Energy and Momentum Conceptual Survey (EMCS). The TAs participated in a professional development course that emphasized reflection on introductory student thinking patterns to promote evidence-based pedagogical practices. TAs predicted the most common incorrect answers introductory students would select after lecture-based instruction, then compared their predictions with actual data from introductory students followed by a class discussion. Results reveal gaps between TAs' perceptions and introductory student thinking, with TAs performing poorly on many of the analyzed questions. For example, TAs consistently overestimated that introductory physics students would use novice-like thinking in many situations posed in EMCS problems, i.e., they expected introductory physics students to make more novice-like errors than they did. These findings have important implications for effective instructional design, e.g., physics TAs who misunderstand introductory physics student capabilities may inadvertently create barriers to learning by spending valuable class time on either over-scaffolding or under-challenging introductory physics learners and not spending time on pedagogical issues that are important to address.

We propose a simple experiment for measuring the charge of the electron based on Faraday's law of electrolysis, assuming the known value of Avogadro's number. The experimental setup consists of electrolytic cells connected in series, so that the same electric current passes through each electrolyte. By measuring the mass deposited at the electrodes and relating it to the total electric charge transferred through the electrolyte using Faraday's law, the charge of the electron can be determined. The experiment requires only standard laboratory equipment, and its performance and analysis are within the skills and knowledge of most students taking algebra-based general physics courses. It is therefore particularly suitable for instructional laboratories in high schools and two- and four-year colleges. We demonstrate that students can obtain a reasonable value for the charge of the electron from simple measurements, providing a direct experimental connection between Faraday's law, Avogadro's number, and the electron charge.

Introductory physics students benefit from learning to integrate new physics knowledge with prior knowledge related to their interests. Writing assignments that offer high epistemic agency can foster this integration, and provide rich artifacts for qualitative analysis. Physics education researchers are increasingly interested in studying such artifacts using computer-based textual analysis. In this paper, we use lexical methods to look for evidence of knowledge integration in written assignments from a Physics of Music course. These assignments require students to communicate to an external audience a clear and cohesive narrative that synthesizes concepts from music and physics. To apply this methodology, we first establish a lexicon of music, physics, and integrated keywords that 10 students used across 6 writing assignments. Then, we visualize this word usage in a series of network diagrams based on which keywords were used in proximity to each other in each assignment. We find that students most strongly connected ideas from music and physics using keywords related to the physical structure of sound (sound, frequency, and wave). Applying these methods to each assignment prompt and its resulting student submissions, we find that, in assignments with a lower degree of epistemic agency (assessed qualitatively by our experience teaching the course), students primarily followed the example of integration modeled by the assignment prompt, but in assignments with a higher degree of epistemic agency, they explored music-physics integration to a greater degree. We use this analysis to offer a pedagogical contribution to introductory physics courses centered around students' interests, a theoretical contribution by illustrating a means of quantifying epistemic agency, and a methodological contribution that complements textual analysis and offers the scalability sought in such approaches.

We describe a simple, visually compelling demonstration/laboratory of astronomical interferometry using a standard planetary telescope and a thin piece of opaque plastic punched with two small holes. By observing the disappearance of interference fringes as the hole spacing is increased, students can directly estimate the angular diameter of Venus. The demonstration is a tabletop analogue of the landmark 1921 Michelson-Pease measurement of Betelgeuse and scales naturally from that measurement: where Michelson and Pease required a 6.1 m baseline to resolve a disk 47 mas (milli-arcsecond) across, a 15 mm baseline suffices for Venus, when it is approximately 10-15$''$ (arc seconds). The lab works reliably in ordinary atmospheric seeing conditions, and a side-by-side comparison of Venus (or Jupiter) with a bright star such as Sirius provides an immediate visual demonstration of the difference between extended and point sources. It works equally well as a laboratory at a variety of difficulty levels. Furthermore, it does not require advanced knowledge or skills with optical telescopes. While the underlying ideas are well known, we are unaware of any source that presents them in an accessible, unified form.