Papers

Premixed flames in stagnation point flows are traditionally described using Navier–Stokes equations where inertia and density variations play an important part in determining the flame structure. However, in porous media or Hele-Shaw configurations, Darcy's law replaces the momentum balance, shifting the governing physics to a balance between pressure and viscous forces. This study investigates non-adiabatic strained premixed flames under Darcy's law, pertinent in particular to confined flames in Hele-Shaw burners, accounting for non-unity Lewis numbers and volumetric heat losses. The flame is established in a planar counterflow formed by impinging a cold unburnt gas and a hot burnt gas maintained at the adiabatic flame temperature. We show that the jump in the strain rate across the flame is associated with a jump in viscosity, rather than, as in the classical Navier–Stokes case, a jump in density. Furthermore, the ratio of viscosity to the density-permeability product $\mu/\rho \kappa$, i.e., kinematic viscous resistance, is identified as a key coordinate stretching factor in the mathematical description of the flame structure. This ratio increases significantly across the flame. As a result: (1) the burnt gas acts as a strong viscous barrier, (2) for an increasing strain rate, flame migration towards the burnt gas is hindered, (3) for a decreasing strain rate, migration towards the unburnt gas is promoted, and (4) streamline refraction is augmented. By analysing the burning rate across varying strain rates and heat-loss parameters, we identify distinct extinction and ignition regimes that fundamentally differ from classical combustion theory, thereby providing new insights into flame stabilisation in friction-dominated environments and under confinement.

Full-field measurement techniques such as digital image correlation and infrared thermography are prevalent in experimental solid mechanics. Digital image correlation is used to analyze surface deformation, while infrared thermography quantifies surface temperature fields. However, sophisticated procedures are necessary to express both datasets in the same Lagrangian frame, especially when analyzing non-flat surfaces. In this study, we propose an external projection-based coupling that uses the pinhole camera model to relate two-dimensional temperature data measured by infrared thermography to three-dimensional point coordinates from stereocorrelation-based digital image correlation. Unlike existing multiview approaches, we utilize two independently calibrated industrial-grade systems and augment the experimental evaluation with the pinhole camera model. The projection matrix of the camera model is calibrated using a single image of a reference object. Through this projection, temperature fields are accurately represented at material points. Our method is particularly suited for, but not restricted to, curved surfaces and is straightforward to embed in existing experimental protocols, as the image registration is kept as is. Additionally, we use radial basis functions as a global interpolation ansatz in both space and time to compute in-plane temperature gradients and even temperature rates on curved surfaces, thereby providing an extensive and information-rich full-field dataset.

Microwave SQUID multiplexing ($\mu$MUX) is a widely used readout technique for large-scale transition-edge sensor (TES) arrays. It uses radio-frequency (RF) probe tones to interrogate cryogenic resonators, requiring frequency conversion between the baseband electronics and the cryogenic RF signal chain. This work describes the RF Board, a room-temperature frequency-conversion board deployed in the AliCPT $\mu$MUX readout system. The board up-converts 0-4 GHz baseband I/Q signals to the 4-8 GHz RF band for injection into the cryogenic chain and down-converts returned RF signals to baseband I/Q for ADC digitization. For the current 1000-tone operation, with a DAC output tone power of -30 dBm/tone, the required power windows are -35 to -25 dBm/tone for the RF tones transmitted to the cryostat and -45 to -35 dBm/tone at the ADC input for the returned tones. The RF Board is characterized using swept single-tone measurements covering up-conversion, down-conversion, and RF loopback. Based on these measurements, the RF output power is calculated to be -31.06 to -25.53 dBm, satisfying the RF output window. Assuming a representative cryogenic-chain transmission of -40 dB, the loopback result gives an estimated returned power of -45 to -35 dBm, within the target range. These results show that the RF Board meets the wideband frequency-conversion and tone-power requirements for the $\mu$MUX readout system.

We investigate linear lumping for parameter-dependent mass action reaction networks, distinguishing between generic and critical parameter regimes. For generic parameters – those ranging in some non-empty open subset of parameter space – we prove that exact linear lumping yields only "obvious" reductions: elimination of non-reactant species or projections along stoichiometric first integrals. This characterization extends to reaction networks with product-form kinetics, including Michaelis-Menten and Hill-type rate laws. For mass action systems we proceed to develop an algorithmic approach to identify critical parameter sets – algebraic subvarieties in parameter space where non-trivial lumpings become available. This procedure reduces the determination of lumping maps to a system of finitely many polynomial equations. It also applies to constrained lumping scenarios (which are frequently motivated by chemical considerations). We then review and extend results about proper lumpings. Finally, we discuss lumpings of a self-replicator system, and of a two-pathway enzyme mechanism, to document the viability of our methods in relevant scenarios. Our results clarify the relationship between structural (parameter-independent) and fine-tuned (parameter-dependent) reductions, with implications for approximate lumping when system parameters lie near critical values

Moment closure is a central problem in reduced descriptions of stochastic, kinetic, and quantum dynamics, where equations for low-order observables are coupled to an unresolved hierarchy of higher-order moments. Existing closures usually impose a prescribed form on the distribution or directly truncate the hierarchy, which can become inaccurate or unstable for strongly non-Gaussian states. Here we introduce unit-circle moment closure, which recasts the problem as analytic continuation. Raw moments are mapped to bounded unit-circle moments, whose unresolved tail is reconstructed by a Takagi-Prony procedure from the effective pole structure of a mapped generating function. The resulting continuation yields stable higher-order moments without assuming a fixed distributional ansatz. Illustrative static and dynamical examples demonstrate accurate reconstruction of non-Gaussian distributions and stable evolution of moment hierarchies. Our approach provides a general perspective for moment closure based on analytic structure rather than direct truncation.

Text embeddings are increasingly used in physics education research to organize, compare, and cluster large collections of written text. Their appeal is clear: once student responses have been mapped into a vector space, similarity comparisons and clustering become computationally inexpensive. However, in assessment contexts, the relevant question is not merely whether clusters can be produced, but whether the geometry of the embedding space preserves grading-relevant distinctions. We tested this premise using 992 handwritten student-problem solutions from a high-stakes engineering thermodynamics exam, transcribed into five textual representations and embedded using nine embedding mechanisms. We compared embedding similarity and embedding-based hierarchical clusters against human-assigned scores. Across models, representations, and clustering choices, embedding similarity showed a consistent but modest relationship to score similarity, and the resulting clusters were score-enriched but not score-equivalent. Experiments with a synthetic data set suggest that this may be due to embeddings behaving like novices when categorizing physics-problem solutions, that is, their similarity geometry is strongly influenced by surface features rather than conceptual, semantic structure. These findings suggest that state-of-the-art embeddings can support exploratory organization and human-in-the-loop review of physics solutions, but they do not provide an unsupervised basis for grading without external validation against the assessment construct of interest.

Predicting the aerodynamic performance (e.g. lift, drag, and moment coefficients) of an aircraft is challenging – computational models are biased and direct simulations are prohibitive. A pragmatic way to overcome this limitation is by calibrating low-fidelity computational predictions with experimental measurements. This, however, requires calibrating against sparse measurements contaminated with uncertainty in both the control inputs and the measured aerodynamic response. We develop a methodology to address this problem based on Gaussian process surrogates and the classical Kennedy-O'Hagan calibration. A surrogate model learned on abundant-but-cheap low-fidelity data is calibrated with a sparse set of measurement data. Crucialy, we develop a Bayesian latent Gaussian process based approach that marginalizes the calibrated surrogate model over the input uncertainty, while also matching the marginal mean and variance of the measured output uncertainty. Once calibrated, our surrogate model predicts the uncertainty in aerodynamic coefficients with very high accuracy, including at extrapolative input settings. We validate our calibrated surrogate model predictions against measurement data with true uncertainty intervals to demonstrate that the model places $94.2-95.8\%$ of its predictive samples inside the released $95\%$ truth intervals, with endpoint cumulative probabilities very close to the nominal 0.025 and 0.975 levels.

The "cathetus rule" in optics alleges that the image of an object-point, formed by reflection or refraction at a surface, lies on the perpendicular ("cathetus") from the object-point to or through the surface. The first known statement of the rule, attributed to Euclid, was for a plane or spherical mirror. The rule was extended to refraction by Ptolemy.... Kepler was universally credited with the first disproof-and-salvage of the cathetus rule until 2018, when Benedetti's priority was exposed by Goulding. Kepler notwithstanding, the rule was reaffirmed by Tacquet for plane and spherical mirrors, except for the case in which the rays converge toward a point behind the eye; this became known as the "Barrovian case" because it troubled Barrow, in spite of his modern concept of an image. Barrow demolished the cathetus rule for the tangential image except in the paraxial limit, and Newton salvaged it for the sagittal image. The rule then seems to fade from history. But the rule is equivalent to the assumption that the image is stigmatic and the cathetus well defined. This narrow assumption is approximately true in the first-order (paraxial, "Gaussian") analysis of lenses and mirrors; and unacknowledged applications of the ancient rule can indeed be discerned in modern expositions of that subject. Moreover, the validity of the rule for the sagittal image fills a critical gap in meridional ray-tracing through spherical surfaces: by tracing the chief ray from an off-axis object-point, then applying the cathetus rule to the successive surfaces, one can locate successive sagittal image-points on the chief ray (produced rectilinearly through surfaces as necessary), and hence assess astigmatism to leading order, without tracing any rays outside the meridional plane.

In previous work it was argued that the cells of a multicellular organism form a classically coherent system and that such coherence is essential for life. Here we make this claim precise by introducing an explicit classical formalism in which a many-cell system is represented by a single state vector in an abstract DNA code space. Using Dirac's bra-ket notation purely as a compact representation of classical states, we construct an analogue of the center-of-mass coordinate that encodes the organismal identity and show how a common genetic code shared by all cells corresponds to a coherent phase in this space. We then map this structure onto DNA sequence space by introducing a classical Biological Hamiltonian whose generalized coordinates encode DNA codes and their cell-wise distribution, so that the organismal identity is represented by a global code state rather than by individual molecular constituents. Within this framework we define a time-dependent maintenance operator with code-correcting and code-breaking terms, weighted by coefficients $A(t)$ and $B(t)$, which captures the balance between restorative dynamics and environment-induced damage to the code. Aging is described as a slow drift in these control parameters: as $A(t)$ decreases and $B(t)$ increases, the identity state becomes less stable and the organism moves from robust code coherence to stochastic code variability. In this picture, death appears as a transition in which the global identity state can no longer be maintained.

Spin-photon interfaces based on solid-state defects are key building blocks for scalable quantum networks and hybrid quantum platforms. Optimizing light-matter coupling in these systems requires precise knowledge of the optical transition dipole polarization, yet for many promising quantum emitters this quantity is hard to determine and therefore remains poorly characterized. Here, we develop a framework for reconstructing electric transition dipole polarization in spin-1/2 solid-state defects directly from ensemble spectroscopy. The approach combines the response of photoluminescence spectra to magnetic field, optical polarization, and strain. Applied to erbium ions in silicon, a particularly challenging system containing multiple crystallographic subsites, the framework identifies strain-induced shifts as the origin of asymmetric ensemble spectra and enables simultaneous determination of the optical dipole polarization and strain-orbital coupling tensor. The resulting model predicts how cavity-ion coupling depends on crystallographic orientation and magnetic-field direction, which we verify using single erbium ions coupled to a nanophotonic cavity. Together, these results establish a broadly applicable route for extracting microscopic properties of solid-state quantum emitters from ensemble spectroscopy and for engineering optimized spin-photon and spin-phonon interfaces.

Boundary vorticity dynamics provides a rigorous theoretical foundation for understanding vorticity creation at boundaries, vorticity-boundary interactions, as well as the rational design of effective boundary flow control strategies. It cornerstone is the boundary vorticity flux (BVF), first introduced by Lighthill in 1963, which quantities the local rate of vorticity production at a boundary, and thereby serves as a mathematical measure of distributed vorticity source strength. By adopting a differential-geometric approach, we develop a general theory of the intrinsic decomposition of BVF for compressible Newtonian fluid interacting with an arbitrarily moving and deforming boundary surface. The analyses are further extended to the decomposition of boundary enstrophy dynamics, centered on the boundary enstrophy flux (BEF). Beyond the existing literature, the new theory explicitly identifies a complete set of boundary sources for the rigid-rotation and spin modes, as well as for various enstrophy constituents, arising from the interplay among external force, surface geometry and kinematics, and both longitudinal and transverse physical processes on a deformable boundary. It is noteworthy that introducing a conjugate curvature tensor pair consistently yields compact mathematical representations for all source terms, manifesting as bilinear (or quadratic-form-type) couplings between fundamental vortcity modes and the surface curvature tensors, irrespective of the complexity or generality of the boundary kinematics.

First introduced by Lighthill in 1963 for two-dimensional flows and later generalized by Jie-Zhi Wu to three-dimensional scenarios since 1986, the boundary vorticity flux (BVF) is the cornerstone of boundary vorticity dynamics, which quantifies the vorticity source strength on a solid boundary. Recent advances in vorticity and vortex dynamics have revealed both the rigid-rotation and spin modes of vorticity from multiple perspectives. In the present study, we propose a novel quadruple decomposition of the BVF on a stationary solid wall, which essentially uncovers the boundary creation rates of the elementary vorticity modes for both the tangential and wall-normal BVF components, respectively. The proposed framework is illustrated through skin-friction and surface-pressure measurements for flow over a hill model in a low-speed wind tunnel, revealing a set of intriguing BVF patterns for the first time. These theoretical results are expected to be valuable for global surface flow diagnostics when combined with experiments, as well as for understanding the formation mechanisms of near-wall coherent structures and flow-induced noise.

Temporal boundaries in time-modulated media provide a powerful route toward wave manipulation beyond conventional spatial boundaries. Here, we investigate nonlinear temporal boundaries generated by interaction quenches in a synthetic lattice with exactly solvable interacting dynamics. Unlike conventional temporal boundaries arising from abrupt changes of single-particle dispersion, the present system realizes a self-induced temporal medium in which the propagating wave packet dynamically determines its own effective dispersion and transport properties. By solving the nonlinear Schrödinger dynamics analytically, we show that the interaction generates an emergent wave-packet-dependent band structure and a state-dependent temporal refractive response while preserving fully controllable evolution. Based on this framework, we establish a nonlinear temporal-scattering picture and uncover phenomena including amplitude-dependent temporal reflection/refraction and nonlinear temporal birefringence. Furthermore, we demonstrate that gradient-induced Bloch oscillations suppress wave-packet diffusion and enable coherent periodic transport with exact state reconstruction. Our results extend temporal reflection and refraction from dispersion-quenched linear systems to interaction-quenched nonlinear media and provide a tractable framework for nonlinear wave manipulation in synthetic lattices.

The complex and nonlinear load characteristics of Hall thrusters remain a key challenge in the design of propulsion power-supply output stages. In existing power-supply simu-lations for electric propulsion systems, the Hall thruster is often simplified as a fixed im-pedance or a prescribed current source, which makes it difficult to capture the real-time interaction between the power-supply output stage and the thruster discharge process. To address this issue, this study encapsulates a one-dimensional discharge model as an externally callable thruster slave and proposes a HallThruster.jl-Saber-Simulink co-simu-lation method. The proposed method enables synchronized closed-loop exchange be-tween the power-port voltage Vcmd and the thruster discharge current Iout . The results show that the discharge current under the co-simulation condition exhibits a sustained low-frequency response at approximately 11 kHz. Compared with a fixed-voltage standalone simulation, the co-simulation shows observable differences in port waveforms, spectral characteristics, and internal field distributions. This method provides a co-simu-lation basis for realistic load analysis of propulsion power supplies and subsequent stress evaluation of key components.

Objective evaluation of quantitative-imaging (QI) methods based on how reliably they measure true values is important for clinical translation. Performing such evaluation with patient data is highly desirable but hindered by the lack of gold standards. To address this challenge, advancing on previous studies, we propose a no-gold-standard evaluation technique, NGSE-Corr, that objectively evaluates QI methods without true values. The technique assumes a linear stochastic relationship between true and measured values, characterized by a slope, bias, and multivariate Gaussian-distributed noise term that models correlated noise across QI methods. We derive a maximum-likelihood approach to estimate these parameters using only measured values. From the estimates, we compute noise-to-slope ratio (NSR) to rank QI methods based on precision. Numerical experiments showed that NGSE-Corr reliably estimated the NSR, accurately ranked methods, and maintained performance even when assumptions made by the technique were partially violated. We also validated NGSE-Corr in an in silico imaging trial to rank three quantitative SPECT methods for measuring regional activity uptake in patients with bone metastatic castrate-resistant prostate cancer treated with radium-223. NGSE-Corr correctly identified the most precise QI method and ranked the methods for 95% (95% CI, 89%-98%) and 91% (95% CI, 84%-95%) of trials, respectively, with data from 50 patients. Performance further improved with larger cohorts. With 200 patients, NGSE-Corr yielded same rankings as those obtained with true values across all trial instances. These findings demonstrate the ability of NGSE-Corr to accurately rank QI methods without gold standards and motivate clinical validation and broader applications.

Standard epidemiological models rely on physical mobility and policy indicators, which fail when physical movement decouples from actual transmission risk. To address this, we establish a unified theoretical framework governed by risk-mediated transmission dynamics. Rather than treating societal responses as independent phenomenological proxies, we embed the underlying risk-avoidance tendency directly into the transmission mechanism. This is parsimoniously formulated via the Weber-Fechner law as a logarithmically scaled response to disease incidence, alongside behavioral fatigue. Analyzing multi-regional COVID-19 data, our risk-mediated model significantly outperforms traditional frameworks. While mobility metrics merely track movement volume, our approach directly captures unobserved qualitative contact changes, such as mask-wearing. By integrating this intrinsic behavioral principle, our framework provides a robust, mobility-independent baseline for predicting future epidemic trajectories.

We propose a new Brownian bridge construction for our newly devised Coherent States Path Integral Monte Carlo algorithm. We apply it to the numerically exact calculation of the thermodynamic properties of the Helium fluid on a plane at low non zero temperature. We find very good agreement with the conventional plane waves path integral Monte Carlo results.

Supporting and nurturing early career members is a vital component of succession planning for any profession or associations. Ensuring the thoughts and needs of newly-joined and early-career members of the Australasian College of Physical Sciences and Engineering in Medicine (ACPSEM) were represented and optimally met were key drivers in the creation of the New and Early career Special Interest Group (NESIG) in 2021. NESIG was incepted through the networking and collaboration of early career ACPSEM members who felt there was a need for such a group. The formation of this group was also motivated by data acquired from recent surveys highlighting motivation for initiatives that supported early career ACPSEM members. For example, the 2021 ACPSEM Radiation Oncology Medical Physics workforce survey showed overwhelming desire of early career members to be involved in student supervision, academic work and research. Similar themes have been identified in a Better Healthcare Technology survey on actions that would reduce barriers to ACPSEM members research and development work, and within other ACPSEM groups. Through consultation and guided by the findings of these surveys and discussions, NESIG will identify opportunities and initiatives for early career ACPSEM members that complement the existing ACPSEM training and mentoring programs. The development of this special interest group has been supported not only by the college but also other established groups, senior members of the field in both Australia and New Zealand and existing international early career groups. NESIG aims to provide stronger networking and collaboration amongst newly joined and early career members and on-going support and encouragement of activities tailored to NESIG members, to further support and nurture early career members for the benefit of individuals and the wider profession.

Truck-drone delivery is an emerging last-mile logistics mode combining the long-haul capacity of trucks with the flexible service capability of drones. In locker-based operations, smart lockers serve not only as temporary parcel storage facilities but also as automated drone docking and service nodes. These automated nodes support drone takeoff, landing, parcel handover, and battery replacement, thereby significantly extending the service range and operational flexibility of drone-assisted delivery networks. However, practical locker-based delivery systems face complex real-world challenges, requiring the integrated coordination of not only parcel delivery, return pickup, battery-constrained and load-dependent drone flights, but also necessary detours around restricted airspace. To address this practical and multifaceted challenge, this paper introduces a locker-based truck-drone routing problem with integrated considerations of pickups, deliveries, and no-fly zones (LTDRP-PDNF), with the objective of minimizing the total operational cost of a fleet of drone-equipped trucks. We formulate the route construction process as a Markov Decision Process and develop a two-stage deep reinforcement learning-based neural heuristic. The first stage utilizes an attention-based encoder and a Bidirectional Gated Recurrent Unit decoder to solve the truck-only routing problem, formulated as a capacitated vehicle routing problem. The second stage combines a policy-transfer strategy with a hybrid dispatch assignment heuristic to construct fully coordinated truck and drone routes for LTDRP-PDNF. Experiments on instances of different scales demonstrate that the proposed method outperforms metaheuristic and neural heuristic baselines in most cases while maintaining exceptionally short computation times, offering an effective, scalable solution framework under practical operational constraints.

The "new" Système international d'unités (SI), which became effective May 20, 2019, defines and is defined by a set of constants. These include the speed of light, the Planck constant, the Boltzmann constant, and the constant relating the elementary electric charge to the coulomb. Interpreting such constants as conversion factors organizes the units they relate into a unifying geometric framework. In this framework, units appear (perhaps raised to some power) either as rows/columns in a single conversion table or as entries in a list of dimensionless numbers. This organization clarifies the distinction between "fundamental" physical constants with values that are set by people, like those defined in the SI, and those with values that are set by nature. It also reveals geometry permeating our theories of physics that is normally hidden by a surplus of units.

This article outlines 'NanoVer', an open-source software framework which enables groups of people to co-habit the same virtual space and manipulate real-time MD (Molecular Dynamics) simulations of flexible 3D molecular structures with atomic-level precision as if they were tangible objects, an approach that we call 'interactive Molecular Dynamics in eXtended Reality' (iMD-XR). Distinct from our earlier iMD work that relied on tethered PC-VR systems with large graphics cards, NanoVer represents a change in philosophy, emphasizing compatibility with standalone mobile consumer XR hardware and corresponding software APIs. The NanoVer architecture enables multiple XR clients and/or Python clients to simultaneously communicate with a flexible server architecture that can carry out a range of tasks, including for example: recording iMD-XR sessions, static structure visualization, and MD trajectory visualization. NanoVer allows researchers, educators, and students to fluidly move between AR and VR environments, to explore creative new approaches to molecular research and education, including for example: molecular conformational sampling, protein-ligand binding, molecular psychophysics, training AI agents to sample molecular transitions, and a new interface which allows iMD-XR participants to sketch 3D conformational paths which automated agents can then follow. As an immersive platform that offers new ways to understand, engineer, communicate, and interact with dynamical behaviour at the nanoscale, NanoVer invites us to imagine new ways for combining human intelligence (e.g., spatial cognition and design reasoning) with machine intelligence. To expand NanoVer's accessibility, we have published a version to the Meta Horizon Store, for easy download by those with a Meta Quest 3/3S headset, to explore pre-recorded iMD-XR trajectory visualizations and set up their own multi-user system.

The rapid growth of energy-intensive technologies, including artificial intelligence, large-scale computing, and thermal management systems, has intensified global energy demand amid accelerating climate change. Meeting these demands requires innovative, low-carbon thermal management strategies that improve energy efficiency while minimizing environmental impact. This review revisits the underexplored phenomenon of bioconvection, a self-organized fluid motion generated by motile microorganisms, as a bio-inspired approach to sustainable heat transfer. Drawing on studies from natural ecosystems and laboratory experiments, we synthesize current knowledge of microorganism-induced hydrodynamics, pattern formation, and thermofluidic transport to assess the feasibility of harnessing bioconvection for thermal management. We further support this assessment through quantitative analyses of the thermal performance of bioconvective systems and discuss this in the framework of relevant non-dimensional numbers. By generating spontaneous convective plumes through density stratification, motile microorganisms enhance heat and mass transfer without external mechanical forcing. These self-organized flows provide a promising route toward hybrid bio-engineered cooling systems that reduce pumping energy, disrupt thermal boundary layers, and improve heat transfer efficiency. We conclude the review with the key challenges on the way to practical implementation, including microbial stability, material compatibility, controllability, scalability, as well as integration with existing cooling technologies. Finally, we identify critical research directions spanning heat transfer, microbiology, and nonlinear fluid mechanics within the broad context of sustainability, positioning bioconvection as a promising strategy for environmentally responsible thermal management in an era of rapidly increasing energy demand.

We formulate a continuity equation for the Schrödinger equation in the complex space. We define a complex momentum by normalizing the complex current by the particle density. This momentum is a quantum analog of the classical, kinematic momentum analytically continued into the complex plane. The kinematic momentum and the gradient of the wavefunction's phase each represent a fluid-like flow in the complex plane; the phase-gradient flow is incompressible. The zeros of the wavefunction give rise to simple poles in the momentum. The poles manifest as irrotational vortexes in the phase-gradient flow, while critical points of the wavefunction present as rigid body-like rotational flows of the kinematic momentum. A discrete nature of elementary excitations comes about inherently because the quantity of the poles is automatically integer. An exact quantization condition is subsequently formulated, which reduces to the Bohr-Sommerfeld condition in the semiclassical limit. We establish a priori that the Bohr-Sommerfeld condition must be exact for the Harmonic Oscillator. We show that the kinetic energy is a sum of contributions of the average value and fluctuations, respectively, of the kinematic momentum. The zero-point vibrations within bound states are solely due to the fluctuations of the momentum and manifest as rigid-body flows at infinity. The momentum poles – and hence the wavefunction's zeros – can be viewed as emergent, consistent with the remarkable property of quantum entanglement exhibited by standing wave solutions of the Schrödinger equation.

Lambertson method is a classical approach that can indirectly measure the electrical center offset in the beam position monitor (BPM) due to imperfections in the pickup buttons. It applies to BPMs that are symmetric in both the horizontal and vertical directions. In this paper, we present our extension of this method to BPMs that are asymmetric in the horizontal direction, and we apply it to such BPMs in ALS Upgrade project at Lawrence Berkeley National Laboratory.

The inherent spatial randomness and broad spectral heterogeneity of epitaxial quantum dots (QDs) – one of the most mature classes of solid-state quantum emitters – remains a major obstacle to their scalable deployment in integrated photonic quantum technologies. Overcoming this challenge requires deterministic fabrication strategies capable of precisely aligning nanophotonic structures with high-quality emitters, which in turn demands efficient and automated single-QD characterization. Despite substantial progress in optical measurement techniques, a platform capable of autonomous, data-efficient, and sufficiently versatile characterization of single quantum dots at the chip scale remains lacking. Here, we introduce an automated cryogenic measurement platform that combines wide-field photoluminescence imaging with vector-stage-scanning confocal spectroscopy to enable high-throughput, chip-scale targeted optical characterization of individual QDs. Using this platform, we automatically acquire photoluminescence data from thousands of GaAs/AlGaAs QDs on a single chip. We demonstrate how this extensive dataset enables identification of high-performance emitters for future deterministic device fabrication, while simultaneously revealing statistical trends across the QD ensemble. By uniting data-efficient targeted measurements with scalable automation, our platform establishes a foundation for large-scale quantum photonic integration and the high throughput characterization framework needed to accelerate materials optimization.

Magnetic switchbacks (SB) – the localized magnetic structures with magnetic field direction inclined at an angle $\theta$ relative to the background $B_0$ – in the young solar wind have been associated with enhanced ion-scale wave activity and local plasma heating. It remains debated whether the apparent wave-power increase is intrinsic or mainly caused by sampling geometry. In this work, we analyze magnetic and electric field fluctuations measured by Parker Solar Probe, focusing on the 0.1–3~\(f_{cp}\) frequency band that spans the transition from the MHD inertial range to ion-kinetic scales. By decomposing magnetic fluctuations into field-aligned and transverse components and comparing SB and non-SB intervals at the same local magnetic field angle, we test whether SBs sample an anisotropic cascade from different viewing angles or host intrinsically amplified wave activity. We find that the transverse magnetic power $\delta B_{\perp}$ is systematically enhanced inside switchbacks across a wide range of magnetic field rotation angles $\theta$. The enhancement persists even at small and intermediate deflections, where geometric projection alone predicts weak power, indicating an intrinsic origin beyond sampling geometry. The inertial-range spectral indices also remain similar between SB and non-SB intervals despite the enhanced wave power inside SBs, suggesting that the underlying turbulence cascade is largely preserved. This excess $\delta B_{\perp}$ coincides with elevated proton temperatures and enhanced electric-field fluctuations, supporting the interpretation that SBs act as localized sites of cross-scale energy transfer and ion-scale dissipation in the near-Sun solar wind.

Nonlinear time-dependent computation of macroscale dynamics in stellarators is motivated by laboratory results showing the possibility of robust operation in conditions where magnetohydrodynamic (MHD) modes are linearly unstable. A new formulation of semi-implicit MHD computation for toroidally shaped magnetic confinement systems uses 2D nodal spectral elements over the poloidal plane and Fourier representation over a generalized toroidal angle. Geometric mappings and steady-state (equilibrium) fields are expanded in the same 3D representation as the time-evolved fields to model non-axisymmetric configurations. For accuracy at large timestep, the semi-implicit operator is based on the ideal-MHD energy integral using 3D pressure and magnetic fields. The nodal spectral elements allow numerical convergence through either h-refinement or p- refinement. Our implementation (NIMSTELL) with the continuous H1 expansion of magnetic-field components and diUusive divergence control is a generalization of the NIMROD code [JCOMP 195, 355]. The NIMSTELL implementation is verified linearly and nonlinearly on resonant ideal interchange, where convergence from the stable side results from the stabilization method used in NIMROD [JCOMP 319, 61]. Optionally, NIMSTELL may use an H(curl) representation for vector potential, and both magnetic representations are verified with respect to results from JOREK [Phys. Plasmas 29, 063901] on linear and nonlinear magnetic tearing in the W7-A rotating-ellipse configuration. Application of the existing vector-potential implementation to interchange shows that it needs a minimum level of electrical resistivity to avoid numerical noise for a given level of spatial resolution. Solving the algebraic systems from the implicit parts of the time advance is facilitated by including the Fourier components of stellarator mode families in each preconditioning operation.

Bubble bursting is a major source of aerosol generation in a wide range of natural and industrial systems. While the resulting jet dynamics have been extensively studied in deep liquid pools, bubble bursting often occurs in shallow liquid layers where the influence of the nearby solid boundary remains poorly understood. Here, we show numerically that a shallow liquid layer produces smaller and more numerous jet drops, even when the initial bubble shape is unchanged. We identify a wall-induced viscous sticking effect that suppresses the upward motion of the cavity bottom, leading to a steeper cavity geometry during capillary-wave focusing. We further develop a semi-empirical scaling law that predicts the jet drop radius as a function of the Ohnesorge number and the initial bubble-wall distance. Our results establish geometric confinement as a governing factor in bubble bursting and provide a framework for predicting and controlling aerosol generation in shallow liquid environments.

Parity-time (PT) symmetry in time-delay oscillators such as lasers and optoelectronic oscillators provides a potential route to enhanced spectral purity, including reduced phase noise and improved sidemode suppression. Existing theoretical descriptions are typically based on coupled-mode formulations derived under slowly varying envelope and near-degeneracy assumptions, which restrict their validity to weak coupling, small gain/loss contrast, and small detuning. In this work, a non-perturbative formulation of PT symmetric time-delay oscillators is developed based on a delay-difference equation and a scattering matrix representation of the coupling network. The approach treats propagation delay explicitly and does not rely on modal truncation, remaining valid for arbitrary coupling strength, gain/loss imbalance, and resonance detuning. The exact eigenvalue structure of the system is obtained in closed form, yielding a complete characterization of the unbroken and broken PT symmetric regimes as well as the associated exceptional points. A dimensionless order parameter is introduced that governs the symmetry transition over the full parameter space. It is further shown that conventional coupled-mode theory is recovered as an asymptotic limit of the exact formulation for small parameters. The results provide a unified and physically transparent framework for analysing PT symmetric delay systems beyond the weak-coupling limit, with direct implications for the design and optimisation of low-noise oscillators and photonic systems.

We develop a constructor-theoretic formulation of optical time in which delay, phase, temporal ordering, synchronization, and detector records are described as physical tasks rather than as consequences of a primitive time parameter. An optical delay is treated as an operational attribute defined by comparison and record-forming tasks, while phase becomes temporal only through a reference-dependent phase-delay equivalence relation. Within this framework, the Fisher information associated with delay estimation is interpreted as a distinguishability resource, and the Cramer-Rao bound becomes a task-impossibility statement: for a specified optical substrate, reference, detector, photon budget, bandwidth, visibility, and noise model, no constructor can estimate a delay with variance below the inverse Fisher information. We illustrate the approach using interferometric delay estimation, dispersive group-delay propagation, and double-slit diffraction, where the standard Fraunhofer pattern is recovered as a record distribution generated by a phase-delay task. The framework does not replace Maxwellian optics; it reorganizes optical dynamics as a means of determining which temporal tasks are physically possible or impossible.