Fluid Dynamics
Applications of a moving surface drag model: From Stokes waves to offshore wind farms
Manuel Ayala, Zein Sadek, Raul. B Cal et al. (+2 more)
Offshore wind farms operate within the marine atmospheric boundary layer, where ocean waves can modify air-sea momentum transfer, turbine inflow, and wake recovery. Wave-resolved simulations can capture phase-dependent wind–wave interactions, but their computational cost and implementation complexity limit their use in large atmospheric and wind-farm domains. This study describes applications and tests of the recently proposed moving surface drag (MOSD) model, a flat-bottom wall-stress formulation for horizontally resolved moving waves, to a sequence of increasingly complex wind–wave and offshore wind-energy applications. The model is first evaluated for turbulent flow over Stokes-like waves using laboratory measurements, where it reproduces mean velocity profiles and captures the qualitative structure of wave-induced motions, although their amplitude is underpredicted. MOSD is then applied to broadband wave spectra fields and offshore wind-farm boundary layers, showing good agreement with mean velocity profiles from wave-resolved simulations across different wave ages, grid resolutions, and turbine spacings. Finally, exploratory offshore wind-farm simulations using MOSD under conventionally neutral conditions demonstrate its application at wind-farm scale. Large-scale waves leave detectable signatures in near-surface velocity spectra, but these signatures decay with height and do not produce clear peaks in temporal spectra of aggregate turbine power. Overall, the results demonstrate that the MOSD model provides a tractable framework for incorporating resolved wave effects in wind-wave and offshore wind-farm simulations.
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All authors Manuel Ayala, Zein Sadek, Raul. B Cal, Dennice. F Gayme, Charles Meneveau
Physics and Society · Cross-listed from stat.AP
County-Level Heterogeneity in Opioid Harm Reduction and Treatment Effects: A Simulation Modeling Analysis
Abdulrahman A. Ahmed, M. Amin Rahimian, Qiushi Chen et al. (+1 more)
Opioid overdose deaths remain a severe public health crisis in the US, with heterogeneous burden across counties that differ in epidemic trajectory, baseline resources, and local context. While harm reduction through naloxone distribution and buprenorphine treatment are both evidence-based strategies, limited information on county-level effects hinders the ability of policymakers to prioritize resources across counties. We developed a simulation model of opioid use disorder (OUD), calibrated separately to six Pennsylvania counties spanning large urban (Allegheny, Philadelphia), intermediate-sized (Erie, Dauphin), and rural (Clearfield, Columbia) settings. We projected county-specific overdose mortality trajectories under three levels of increase in buprenorphine dispensing and naloxone distribution (10%, 20%, and 30% above each county's baseline), over a five-year horizon from 2025 to 2029. A 30% increase in naloxone distribution above observed county baseline levels was projected to reduce 2029 overdose deaths by approximately 70% (95% uncertainty interval, UI: 55-81%) in Allegheny County, 11% (95% UI:4-17%) in Erie County, and 28% (95% UI:2-64%) in Clearfield County. Projected reductions in overdose deaths from increasing buprenorphine were consistently smaller (10%-23%), except that in Erie buprenorphine produced larger projected reduction by 20% vs 11% for naloxone. Heterogeneity in naloxone responsiveness was strongly associated with each county's historical naloxone dispensing variability. The same proportional increase in naloxone distribution yields substantially different projected mortality reductions across counties depending on each county's baseline distribution history, a pattern invisible from mortality statistics alone. County-level context is important for informing harm reduction and treatment prioritization at the county level.
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All authors Abdulrahman A. Ahmed, M. Amin Rahimian, Qiushi Chen, Praveen Kumar
Physics Education
AI-Assisted Assessment of Experimental Physics Laboratory Reports: Potential, Limitations, and Support for Teaching Practice
Marcos Abreu, Cecilia Stari and Arturo C. Marti
The incorporation of AI into the assessment of physics laboratory reports offers opportunities to support the review of student work and the provision of feedback. This article revisits an experience involving the use of ChatGPT models to analyze laboratory reports and examines the conditions that influence their usefulness in teaching practice. The analysis considers the
evolution of AI models, document-processing procedures, and different modes of interaction, with particular
attention to the effective availability of evidence contained in student reports. The findings indicate that differences between AI-generated and teacher assessments may be related not only to model capabilities but also to difficulties in retrieving and interpreting equations, graphs, tables, units, and other visual elements. The possibilities of systematic processing of sets of reports and conversational review of cases requiring more focused analysis are also examined. Based on these observations, a working strategy is proposed in which AI serves as a complementary resource for organizing assessment, supporting feedback, and identifying recurring difficulties in student work. The analysis highlights the importance of document-processing conditions and evidence availability, as well as the teacher's role in interpreting AI-generated information and making evaluative and pedagogical decisions.
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Accelerator Physics
Persistent homology of Hamiltonian orbits with applications to beam physics: Euler-Betti classification and topological chaos indicators
D. Iglesias Tinoco and B. Erdélyi
Estimating the dynamic aperture of circular particle accelerators typically requires expensive long-term tracking. Using classical homology, we construct a two-dimensional theoretical classification of regular and chaotic orbits and use persistent homology for its numerical implementation on short orbit segments. In four dimensions, we introduce topological chaos indicators based on persistent homology and use normal-form theory to apply the classification to two symplectic-plane projections. The methods reproduce the expected organization of regular and chaotic motion in several canonical
Hamiltonian systems. Applied to symplectified one-turn maps of a nonlinear
lattice model of the Integrable Optics Test Accelerator, the results obtained from the first 200 turns identify the central connected stability region and its surrounding transition to chaos. They are consistent with the short-term dynamic aperture of the electron configuration obtained from $10^4$ turns and the long-term dynamic aperture of the
proton configuration obtained from $10^8$ turns. For the configurations studied, persistent homology of short orbit segments predicts the dynamic aperture obtained by substantially longer tracking, potentially reducing the need for exhaustive simulations in studies of existing accelerators and the design of future facilities. The methods could also complement classical chaos indicators and modern approaches based on artificial intelligence.
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Fluid Dynamics
An experimental and numerical study of the circular hydraulic jump
Arnab Kumar Mallik, Hrvoje Jasak, D. Ian Wilson et al. (+2 more)
This paper describes experiments and numerical simulations on the normal impact of a round
liquid jet onto a horizontal surface, such as when water from a tap hits the bottom of a kitchen sink. In this case the
liquid impacting on the surface spreads as a fast-flowing thin film and, at some distance from the point of impact, the thickness of the flow abruptly increases and the speed of the flow is reduced. In the experiments studied here the flow is axisymmetric about the axis of the jet, and the abrupt change in depth occurs at a given radius and is known as a circular hydraulic jump (CHJ). We present new experiments in which we measure the thickness of the
liquid film inside and beyond the jump and use these measurements to estimate the governing parameters, the Weber, Froude and Reynolds numbers that determine the influence of surface tension,
gravity and viscosity, respectively. We also carry out numerical simulations of the flow that show excellent agreement with the experiments and provide independent estimates of these dimensionless parameters. We find that, on the scale of a kitchen sink, and for water at high Reynolds number and low Bond number, at the jump the Weber number is of order unity while the Froude number is large, implying that the jump is controlled by surface tension. We also define a critical dimensionless jet flow rate at which this control no longer holds and
gravity plays a significant role.
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All authors Arnab Kumar Mallik, Hrvoje Jasak, D. Ian Wilson, P. F. Linden, Rajesh K. Bhagat
History and Philosophy of Physics · Cross-listed from math.HO
Descartes' Circle Theorem, Princess Elizabeth, and Spinors
Daniel Parrochia
In this article, on Descartes' famous "circle
theorem," we first attempt to explain how the philosopher could have arrived at the equation that he presents without demonstration in a letter to Princess Palatine Elizabeth of Bohemia in November 1643 (a previously unpublished proof, to our knowledge). Then we report some stages of the subsequent generalization of this
theorem, whose Cliffordian flavor, via the equivalence of a quadratic form and the square of a linear form, still mobilizes mathematicians today. This statement, which, over time, has undergone different extensions, Euclidean and non-Euclidean, has found, in fine, a spinor formalization. We see there the proof of what we may call, in a Bachelardian style, an "inductive value" of the truth, which extends by successive generalizations. We conclude, more briefly, with the contacts between Elizabeth and Descartes, and the perhaps symbolic meaning of these considerations on "kissing circles," as they are called in Anglo-Saxon countries, in the context of their correspondence on the soul and the body, and the question of passions.
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Fluid Dynamics
Stabilization of Yih's Viscosity Jump Interface in a Channel
Miroslav Krstic
Two immiscible viscous fluids in pressure-driven channel flow can be unstable through their interface when their viscosities differ, at arbitrarily small Reynolds number — the instability Yih found in 1967. The unstable state is the interface itself: a curve inside the domain, separating the two fluids, whose displacement is governed by a partial differential equation of its own and which moves the fluid domain with it. Actuation is at one wall only, so the state to be controlled is reached across a fluid. We stabilize this interface at any rate below the limit set by the streamwise mean flow, by static feedback of the two velocity components of that wall, through a Fredholm backstepping transformation acting jointly on the two layers. The target is the two-fluid Stokes problem, shifted, with the transmission of stress between the fluids kept and the coupling of the interface into them removed. Two findings about the two-fluid spectrum carry the design: joined at the interface, the
eigenvalue sequences of the two layers, which collide for a dense set of layer ratios when the layers are uncoupled, avoid each other uniformly, so no degeneracy has to be assigned; and the slowest mode left to viscosity is not a bulk mode but the capillary relaxation of the interface, whose rate is linear rather than quadratic in the wavenumber, which sets the band of actuated wavenumbers. The controller is tested on the nonlinear two-fluid channel, switched on against a saturated interfacial wave.
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Popular Physics
Mass in the Light of Special Relativity
Francisco Caruso and Vitor Oguri
The text analyzes the concept of mass within Special Relativity, initially deconstructing the interpretation of Einstein's equation ($\varepsilon_\circ = m c^2$) as a principle of equivalence. Based on the adoption of the conservation laws of momentum and energy, the non-additivity of mass in composite systems is established. While in atomic and nuclear systems the total mass is less than the sum of its constituents, in the subnuclear domain the opposite occurs: the positive potential energy of confinement of
quarks causes the mass of a
hadron to be greater than the sum of the masses of its
quarks; in the case of nucleons, it is much greater. It is concluded, then, that the mass of baryonic matter in the observable Universe comes, for the most part, from the energy associated with strong interactions.
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Atomic Physics · Cross-listed from quant-ph
Persistent Quantum-Enhanced Frequency Sensing with T^{-3/2} Scaling
Clayton Z.C. Ho, Hao Wu, Grant D. Mitts et al. (+2 more)
Quantum sensing uses nonclassical states to improve measurement sensitivity, but the same states that provide metrological gain also decohere more rapidly. This limits the usable interrogation time and, in practice, often precludes improvement in ultimate sensitivity - realized useful
quantum advantage has consequently remained rare. Here, we restore persistent
quantum advantage by
embedding Fock-state enhancement within a
quantum heterodyne (Qdyne) protocol, decoupling sensitivity from the decoherence-limited interrogation time {\tau}. Measurements are acquired at short {\tau} where the
quantum-enhanced gain is optimal, while precision accumulates with the total measurement time. Demonstrated on the motional mode of a trapped 40Ca+ ion, we observe
quantum-enhanced precision that persists to measurement times seven orders of magnitude beyond the dephasing limit, scaling as T^{-3/2} with no indication of saturation. Using the n=3 Fock state, we reach a frequency precision of 0.5uHz relative to an 86MHz carrier, achieving a fractional precision ~6x10^{-15}. This represents a
quantum-enhanced gain of 7.1(10) dB over the n=0 state, in agreement with Fisher information predictions. This is the first demonstration of Qdyne beyond solid-state
spin-defects. Further, by using the
quantum harmonic oscillator to perform frequency mixing, we extend operation beyond 1GHz, two orders of magnitude above the ceiling of pulsed dynamical-decoupling implementations. These results recover
quantum advantage at the long timescales required to improve ultimate sensitivity, with direct implications for nanoscale NMR and
quantum logic spectroscopy.
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All authors Clayton Z.C. Ho, Hao Wu, Grant D. Mitts, Joshua A. Rabinowitz, Eric R. Hudson
Accelerator Physics
Moderator Modeling for High Intensity Slow Positron Sources
Sophie Crisp, Ryland Goldman and Spencer Gessner
Slow positron beams enable diverse applications, from surface-sensitive materials studies to positronium physics, but progress is limited by source intensity and brightness. In linac-based sources, mono-energetic, slow positrons are produced by moderating the broad, divergent distribution of fast positrons produced by high-energy electrons incident on a high-Z target. This process is intrinsically inefficient. Conventional linac-based designs place the moderator close to the target. Tungsten moderators become less efficient when heated by high-power, fast positrons, leading to defect-related losses. Cryogenic moderators, like solid neon, melt when exposed to high-power, fast positrons. Following the method of O'Rourke et al., we use Monte Carlo simulations combined with a
diffusion model to investigate how moderator geometry, material, and incident fast positron energy affect slow positron production. We compare single tungsten foil and multi-foil configurations with solid neon moderators in reflection and transmission geometries. We find that for fast positron energies below 300 keV, solid neon offers order-of-magnitude higher efficiency than tungsten due to its larger
diffusion length, whereas at MeV-scale energies multi-foil tungsten has higher efficiency due to the maximization of scattering. We also find that including a target proxy in simulation increases low-energy efficiency up to fourfold by allowing a fraction of initially reflected positrons to return to the moderator. We conclude that substantial gains in start-to-end efficiency at linac sources will likely require combining a decelerating cavity with a decoupled cryogenic moderator.
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Optics · Cross-listed from quant-ph
Cavity-QED analysis of InAs quantum-dot single photon production
W. W. Chow, S. Peana, D. I. Herman et al. (+6 more)
Cavity
quantum electrodynamics is used to study the extent cavity enhancement affects single
photon performance of an InAs
quantum dot, in terms of emission rate, purity and indistinguishability at different temperatures. Parametric studies show a tradeoff between single
photon production rate and purity, as well as between indistinguishability and purity. The results indicate the importance of
quantum carrier-
photon correlations that yield substantial corrections to mean-field treatments, especially at high light-matter coupling strength, where cavity enhancement is most effective.
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All authors W. W. Chow, S. Peana, D. I. Herman, K. Y. Lee, A. Cejan, C. Shang, G. Moody, J. E. Bowers, F. Jahnke
Chemical Physics
cboamd: A Machine Learning Molecular Dynamics Framework for Vibrational Strong Coupling
Yifan Li, Roberto Car and Johannes Flick
Under vibrational strong coupling (VSC), molecular vibrations hybridize with an optical cavity mode to form polaritons, offering a route to modify chemical and material properties without external driving. In this work, we develop a machine-learning interatomic potential (MLIP) based framework to study VSC inside optical cavities. By using the cavity Born-Oppenheimer approximation and treating the photonic degrees of freedom as an effective electric field, we provide a framework that can describe VSC solely based on the electronic ground-state potential energy surfaces (PES), electronic dipole moment, and polarizability, all quantities obtained outside the cavity. We train PES, polarization, and polarizability models to drive the molecular dynamics (MD) simulations of systems under VSC. We demonstrate the approach for both a single CO$_2$ molecule and
liquid CO$_2$, showing that the polarizability renormalizes the effective cavity resonance: at fixed cavity frequency this renormalization renders the Rabi splitting strongly asymmetric, while with renormalized cavity frequency the symmetric splitting is capped by polarizability screening. The collective Rabi splitting of the
liquid is connected quantitatively to the single-molecule splitting involving the $\sqrt{N/3}$ orientational enhancement and the local-field enhanced effective charges of the coupled vibration, while the
equilibrium pair structure of the CO$_2$
liquid remains unchanged. These simulations are the first MLIP-driven simulations of collective VSC in the condensed phase and open further pathways to the exploration of chemical effects under VSC.
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Chemical Physics
ReaxKit: A Modular Python Toolkit for Preparing, Parsing, and Analyzing ReaxFF Molecular Dynamics Simulations
Ali Mohammadi Dinani, Alireza Sepehrinezhad, Anirban Phukan et al. (+7 more)
Empirical reactive force field (RFF) molecular dynamics enables atomistic simulation of bond breaking, bond formation, charge redistribution, and structural
evolution in chemically complex systems. The ReaxFF method is arguably the most popular and transferable of the currently available RFF methods. However, routine use of ReaxFF often requires substantial manual effort to prepare inputs, interpret engine-specific outputs, organize simulation artifacts, and develop custom analysis scripts, limiting reproducibility and scalability. Here, we present ReaxKit, a modular Python toolkit for preparing, parsing, analyzing, and managing ReaxFF molecular dynamics simulations. ReaxKit uses a separation-of-concerns architecture that distinguishes engine-specific input/output handling, canonical domain data models, scientific analysis, workflow orchestration, presentation, storage, and graphical interaction. Engine adapters convert outputs from supported simulation environments into typed, engine-independent data structures, allowing analysis modules to operate independently of native file formats. User requests are executed through consistent command-line, functional Python, and browser-based graphical interfaces, while a dedicated workspace preserves raw data, normalized
datasets, analysis settings, results, logs, caches, and provenance information. Representative applications demonstrate the breadth of the toolkit, including automated generation of elastic and equation-of-state training data from Materials Project structures and mechanical properties, characterization of active sites and local structural environments, and execution of simulation campaigns through YAML-defined study workflows. These capabilities show that ReaxKit supports all essential stages of the ReaxFF workflow.
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All authors Ali Mohammadi Dinani, Alireza Sepehrinezhad, Anirban Phukan, Asma Ul Hosna, Jupjeet Dhingra, Mozhdeh Mirakhory, Seyed Mahmoud Mortazavi, Yun Kyung Shin, Swarit Dwivedi, Adri C.T. van Duin
Optics
Optical Mode Sorting with a Programmable Diffractive Neural Network
Qian Zhang, Shiyue Chen and Juergen W Czarske
Programmable diffractive optical processors are particularly attractive for spatial light manipulation because their optical transformations can be dynamically reconfigured and adapted without modifying the physical hardware. However, their practical performance is often limited by the gap between simulation and experiment caused by optical aberrations,
alignment errors, and nonideal phase responses. In this paper, we introduce a hybrid optimization framework that combines high-dimensional numerical design with low-dimensional hardware-in-the-loop calibration, enabling programmable diffractive optical networks to compensate experimentally for mismatch without retraining their underlying optical transformations. We demonstrate a programmable optical diffractive neural network (ODNN) designed by back-propagation to spatially sort six linearly polarized modes supported by a multimode fiber. The experimental distortions are represented using a truncated Zernike basis with only 19 correction coefficients per layer. These coefficients are optimized directly on the physical system using
stochastic parallel gradient descent, avoiding re-optimization of the full pixelated phase masks. Experimentally, the proposed calibration yields an SNR improvement of approximately 3.26 dB, and a decrease in amplitude error of 0.04. This separation of high-dimensional optical-function design from low-dimensional physical calibration provides a scalable route towards adaptive and reconfigurable spatial-mode processors for optical router on spatial modes and wavelengths, programmable photonic computer systems and
quantum information processing.
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Optics
All-Optical Control over Nonlocality for Ultrafast Image Processing with an Excitonic Metasurface
Bernardo S. Dias, Romain Tirole, Michele Guizzardi et al. (+4 more)
Image processing lies at the foundation of many modern technologies, such as augmented reality and autonomous driving, yet conventional digital approaches remain energy-intensive and limited in speed. Nonlocal metasurfaces - 2D structures engineered at the nanoscale to support delocalized, dispersion engineered resonances - provide a fast, energy-efficient and ultrathin platform to perform image processing directly on the light path. Introducing tunability in this platform is an outstanding challenge, and would enable dynamic real-time control over the implemented processing operation, facilitating flexible integration into adaptive and multifunctional photonic architectures. Here, we demonstrate optically tunable edge detection at ultrafast speeds by integrating a dielectric nonlocal metasurface with multilayer WS2, whose strong
exciton-driven optical response enables dynamic control of the metasurface nonlocality at sub-ps speeds. Using resonant optical pumping of the A-
exciton in WS2, the metasurface transfer function is rapidly switched from edge detection to bright-field imaging by tuning its spatial nonlocality. Operating in the visible spectral range at a wavelength around 700 nm, the device shows ultrafast switching times and reaches an amplitude modulation depth of 11.5 dB for normal incident light. This approach provides a reconfigurable, ultrathin, all-optical platform for adaptive optical computing systems and highlights the potential of the highly nonlinear properties of 2D materials for active metasurfaces at ultrafast speeds.
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All authors Bernardo S. Dias, Romain Tirole, Michele Guizzardi, Andrea Cordaro, Albert Polman, Andrea Alù, Jorik van de Groep
Chemical Physics
Development of a Non-Empirical Exchange-Hole Dipole Moment Dispersion Model
Alastair J. A. Price and Alberto Otero-de-la-Roza
The inclusion of dispersion effects is important in density-functional theory (DFT) to model non-covalent interactions correctly, a task that is essential in many applications of the theory. Many dispersion functionals have been proposed in the past. The exchange-hole dipole moment (XDM) model combines the simplicity of a damped pairwise asymptotic expression for the dispersion energy with a theory-grounded approach to calculate the dispersion coefficients. XDM is, arguably, the most accurate dispersion correction for the description of molecular
crystals and it has been thoroughly tested for other applications across a wide range of chemistries. Here, we address the two main shortcomings of XDM. First, XDM relies on the use of experimentally determined free-atom polarizabilities. Second, because the XDM atom-in-molecule properties (volumes, polarizabilities, exchange-hole dipole moments) use the Hirshfeld partition method, XDM describes systems with large atomic partial charges, like alkali cations or halide anions, poorly. We propose neXDM, a non-empirical variant of XDM that removes the experimental parameters by using the Kirkwood polarizability formula, thereby making neXDM a pure meta-GGA dispersion functional. In addition, following previous work by Bučko et al. on the similar Tkatchenko–Scheffler (TS) method, we replace the Hirshfeld partitioning with its iterative counterpart. The performance of neXDM is shown to be on par with XDM in standard molecular and
crystal benchmark sets, and greatly improves the modeling of ionic systems. The new neXDM method sets a new record for the best dispersion-corrected generalized-gradient approximation (GGA) functional for molecular
crystal lattice energies in the X23 set (0.700~kcal/mol).
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Fluid Dynamics · Cross-listed from cond-mat.soft
Active colloidal rafts perform swimming strokes that propel their host droplets
Airi N. Kato, Julien Brémont, Etienne Harté et al. (+3 more)
Active particles confined in droplets can set their host droplet into motion. This phenomenon is usually attributed to direct hydrodynamic forcing by the enclosed particles. Here we reveal a different mechanism: we show that a self-propelled raft of active colloids confined in a thin oil droplet at the surface of water typically follows an off-centered orbit, thus periodically deforming the droplet's contact line in an anisotropic way. This non-reciprocal deformation acts as a swimming stroke and propels the droplet according to the principles of low-Reynolds-number swimming. The effect is absent for a single colloid and arises from the intrinsically many-body dynamics of the raft, which we capture with a dynamical model coupling viscous hydrodynamics and many-body active dynamics. Our results show how collective internal activity can be converted into locomotion through deformation of a soft confining boundary.
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All authors Airi N. Kato, Julien Brémont, Etienne Harté, Jean-Michel Rampnoux, Jean-François Joanny, Hamid Kellay
Atomic Physics · Cross-listed from quant-ph
Single-atom-based asynchronous photonic interconnect for scalable modular quantum computing
Jérémy Raskop, Nadav Kandel, Geva Arwas et al. (+6 more)
Scaling
quantum computation beyond the capacity of a single
quantum processing unit requires
quantum interconnects between modular processors. Optical
photons are natural carriers for distributing
entanglement between these processors. Most loss-resilient protocols use photonic Bell-state measurements based on the linear-optics type-II fusion gate. The resulting
entanglement rate scales quadratically with each processor's typically low
photon-delivery probability. Here we analyze a
memory-assisted
quantum interconnect using a near-deterministic, robust
photon–atom controlled-$Z$ gate via a single atom trapped in a high-finesse cavity. Detecting and measuring a
photon from one processor heralds
entanglement between that processor and the atom. This
entanglement is preserved while the process repeats with the second processor until the second
photon is detected and measured. Reading out the atomic
qubit finalizes the
entanglement between the processors. As the
entanglement is mediated by the atom, the
photons from both processors do not need to be indistinguishable, removing a major source of infidelity. Furthermore, by removing the simultaneous
photon-arrival requirement, the protocol allows the
entanglement rate to scale linearly rather than quadratically with
photon-arrival probability over a wide parameter range. We derive
entanglement rates under realistic parameters, accounting for decay of the atom's
entanglement with the first processor and for decoherence caused by unheralded
photon interactions. The nanosecond-scale of the gate and read-out operations leads to orders-of-magnitude
entanglement-rate gain over linear optics, removing a key bottleneck in modular
quantum computing.
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All authors Jérémy Raskop, Nadav Kandel, Geva Arwas, Yaniv Amichy, Yaron Jarach, Tal Kanonich, Andrei Militaru, Johannes Fink, Barak Dayan
Optics
Momentum microscopy of a holey nanostructure
Kerstin Harland, Julia Altenburg, Xiaofei Wu et al. (+10 more)
Momentum microscopy records the three-dimensional momentum distribution of photoelectrons emitted from a solid sample and, by utilizing sufficiently high
photon energies in the ultraviolet spectral range, offers direct access to the electronic band structure of a material. By employing a pump-probe scheme, this method provides a femtosecond view of light-matter interaction and the subsequent relaxation and transport dynamics in a broad range of material systems. However, momentum microscopy has so far been mostly limited to flat and spatially extended surfaces. Photoelectron emission from different three-dimensional facets, in combination with inhomogeneous electric fields around these structures, makes the analysis of the momentum distribution significantly more challenging. Here, we extend the state-of-the-art to a substantially more complex structure and show that a careful analysis of the electron distribution recorded with a momentum microscope provides rich information about both the spatial and momentum distributions on a few-nm and few-mÅ$^{-1}$ scale, respectively. Combined with prior knowledge of the three-dimensional structure, momentum-resolved photoelectrons can be assigned to nano-localized emission spots, permitting a new level of insight into spatio-temporal charge carrier dynamics.
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All authors Kerstin Harland, Julia Altenburg, Xiaofei Wu, Zsuzsanna Pápa, Leon David Schwarz, Lina Hansen, Katrin Meier, Arvid Klösgen, Bert Hecht, Germann Hergert, Péter Dombi, Jer-Shing Huang, Jan Vogelsang
Plasma Physics
Azimuthal mode decomposition Particle in Cell algorithm for cylindrical plasma sources
Matteo Ripoli, Eduardo Ahedo and Mario Merino
An efficient Particle-in-
Cell numerical approach to perform full-dimensional kinetic simulations of low temperature
plasmas is presented. Taking advantage of the cylindrical geometry of most
plasma sources, a
Fourier mode decomposition of the fields is carried out in the azimuthal ($\theta$) direction up to a chosen maximum number of modes $N_m$. Macroparticles are pushed in all $D$ dimensions and weighed, for each mode $m$, onto a $(D-1)$ dimensional grid. The computation of the electric field for each mode is independent and reduces to solving $(N_m+1)$ $(D-1)$ dimensional Poisson problems. The approach brings spectral accuracy in the azimuthal direction, while the computational cost is comparable to that of a simulation with $(D-1)$ dimensions. We verify this approach against a planar test case based on a Penning discharge, widely used for benchmarking and validation purposes in the low-temperature
plasma community. Our approach allows us to reduce the 2D problem into a collection of coupled 1D problems and to naturally perform spectral analysis of the different azimuthal modes, recovering the contribution of each mode to radial transport, with a computational time saving of one order of magnitude with respect to state of the art 2D particle-in-
cell codes.
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Chemical Physics
fix uvt and fix pimd/uvt: A Unified LAMMPS Framework for Constant-Potential Constant-Temperature Molecular Dynamics
Li Fu, Yifan Li and Shenzhen Xu
Accurate simulations of electrochemical interfaces require the simultaneous treatment of constant-potential conditions, nuclear
quantum effects, and sufficient configurational sampling. Integrating these capabilities within a general and efficient molecular dynamics (MD) framework remains challenging. In this work, we implement fix uvt and fix pimd/uvt in LAMMPS for constant-potential classical MD and path integral molecular dynamics (PIMD), respectively. We organize the class hierarchy to reuse LAMMPS's existing Nosé–Hoover chain thermostat routines and share nuclear propagation routines across PIMD integrators. A common interface connects these integrators to models that provide the electron-number derivative of the potential energy. We present three examples with accompanying input commands to guide users through constant-potential classical MD, thermostatted PIMD, and constant-potential PIMD, covering analytical models,
liquid water, and electrochemical interfaces described by machine learning potentials. This work provides practical tools and guidance for large-scale constant-potential simulations incorporating nuclear
quantum effects.
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Plasma Physics · Cross-listed from astro-ph.HE
Nonlinearly Causal General-Relativistic Two-Fluid Dissipative Magnetohydrodynamics
Elias R. Most and Samuel J. Dunham
We present a formulation of general-relativistic (GR) 19-moment dissipative magnetohydrodynamics (MHD), capable of handling all first-order dissipative terms (viscosity, heat conductivity, resistivity and Hall terms), as well as all ideal electron degrees of freedom (number density, momentum and energy) in a GR astrophysical two-fluid
plasma. We derive necessary and sufficient nonlinear causality conditions for the constrained first-order 19-moment system, as well as both necessary and sufficient conditions for strong hyperbolicity. To assess the formulation numerically, we develop a high-resolution shock-capturing scheme that solves these equations in a performance-portable fashion. The scheme expresses all
evolution equations, including the dissipative and electron sectors, in flux-divergence form, allowing us to model systems with scales separated by orders of magnitude without resolving kinetic scales everywhere on the grid. In addition, we use implicit integration methods to systematically overstep kinetic scales in MHD regions, such as cyclotron and
plasma frequencies. To make the scheme as robust as GRMHD codes, we construct necessary and sufficient conditions for a conserved state to be physically admissible, and based on these construct a new physicality-enforcement scheme. As an exact validation comparison, we formulate and derive a full solution to dissipative two-fluid Bondi
accretion in general relativity. We then validate the equations against a series of results from kinetic particle-in-
cell models of black hole
accretion and magnetospheric dynamics, demonstrating that our formulation and scheme can correctly capture major features relevant for feedback on global scales of these solutions, including dimensionless reconnection rates of order $0.1$ and Braginskii-like anisotropic pressures and heat fluxes.
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Optics
Quantized Transport of Gap Solitons in the Harper-Hofstadter Model
Oliver Ashfield, Henry Davenport, Tom Sheppard et al. (+6 more)
We investigate the dynamics of gap
solitons found in the Harper-Hofstadter model with an additional cubic nonlinearity, such as that describing weakly-interacting cold atoms or a Kerr nonlinearity in an optical platform. We find that certain
solitons with frequencies deep in the band gap travel with a robust, quantized velocity perpendicular to the applied force and maintain their spatial profile over long timescales. Crucially, this velocity is linearly proportional to the applied force, allowing for arbitrary steering of the nonlinear wavepacket, without breakdown, using only a tunable external force. This quantized transport persists despite a highly non-uniform occupation of the linear Bloch states, and contrasts with
solitons near the band edge, which deform and delocalize under the same force. These results point to a robust and highly controllable mechanism for steering nonlinear
solitons in experimentally accessible platforms.
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All authors Oliver Ashfield, Henry Davenport, Tom Sheppard, David G. Reid, Holly A. J. Middleton-Spencer, A. C. Berceanu, Frank Schindler, Iacopo Carusotto, Hannah M. Price
Chemical Physics
Orbital-Free Surrogate Functionals Yield Transferable Interatomic Potentials and Electron Densities
Simon Wagner, Marc K. Ickler, Manuel V. Klockow et al. (+2 more)
Orbital-free density functional theory seeks to compute the energy of an electronic system directly from its electron density, avoiding one-electron wave functions and thereby offering a route to scalable electronic structure calculations. Machine-learned orbital-free density functionals have recently achieved promising results on small organic molecules, predicting energies with sub-millihartree accuracy. However, their convergence in density optimization remains sensitive to hyperparameter tuning and architectural choices. Here, we extend the recently introduced (weak) surrogate functional framework - designed to predict ground-state electron densities only - to also yield their energy, resulting in "strong" surrogate functionals. We find that these learned functionals enable stable convergence across all tested neural network backbones, reducing electron density errors relative to the Kohn-Sham reference by an order of magnitude compared to previous OF-DFT methods. More importantly, the predicted energies are competitive with state-of-the-art machine-learned interatomic potentials (MLIPs) trained only on energies, while exhibiting superior generalization to larger, unseen systems.
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All authors Simon Wagner, Marc K. Ickler, Manuel V. Klockow, Fred A. Hamprecht, Roman Remme
Instrumentation and Detectors
Proof-of-Concept and User Perspective on Photon-to-Digital Converter Applications in Particle Physics
M. Á. García-Peris, B. Palmeiro, G. Lessard et al. (+7 more)
Photon-to-Digital Converters (PDCs) are photosensors with single
photon resolution and large dynamic range that digitise the output of individual single-
photon avalanche diodes directly on-chip, offering potential advantages with respect to analogue Silicon Photo-Multipliers (SiPMs). In this work, we assess the PDC technology from the perspective of particle physics, using early, low-coverage PDC prototypes for proof-of-concept studies in calorimetry and tracking. Under simple, but extrapolable, detector conditions, we qualitatively compare PDCs with SiPM-based systems to illustrate their potential in terms of detector performance and readout. As the first application of this technology to particle physics instrumentation, we place particular emphasis on the user perspective, reporting on the practical experience of operating PDCs, from setup and calibration to data handling, and highlighting the relative ease of integration compared to conventional SiPM readout. We discuss the potential of PDCs to address key challenges in large-scale instrumentation, and their prospective integration into next-generation high-energy physics experiments.
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All authors M. Á. García-Peris, B. Palmeiro, G. Lessard, R. Guenette, S. A. Charlebois, E. Gramellini, J.-F. Pratte, T. Rossignol, N. Roy, F. Vachon
Instrumentation and Detectors
A Deep Neural Network based Level-1 Trigger for the Magnetic Monopole Search in the SCEP Experiment
Changqing Ye, Yunhan Wang, Yifan Qiao et al. (+4 more)
The Search for
Cosmic Exotic Particles (SCEP) experiment proposes a multilayer
magnetic monopole (MM) detection array with a target exposure of O(10^4) m^2 year. Continuously recording the raw waveforms at this scale would generate approximately O(10) EB of data per year, making full waveform storage impractical. A Level-1 trigger is therefore required to reduce the stored-data volume while retaining rare MM signals. MM waveforms vary with particle velocity and trajectory, so a single filter kernel cannot match all possible signals. A mismatch between the kernel and the signal waveform can reduce the detection probability. This work therefore develops a compact template-bank construction method for MM detection. Each incoming waveform is filtered with all kernels in the bank, and the best-matched kernel is identified from their responses. A multilayer perceptron (MLP) trigger is further developed to combine all template responses and improve signal detection. With a 31-sample window and a stored-data fraction of 10^(-3), the MLP increases the mean net acceptance P_net from 6.72% for the conventional template-bank trigger to 8.79%, a relative improvement of 30.8%. The network is then implemented on a Xilinx AC701 board equipped with a field-programmable gate array (FPGA) to process a 20-bit input waveform sampled at 1 MHz using 200 MHz trigger logic. At the target stored-data fraction, the fixed-point implementation reduces P_net by only 3/(3.2 x 10^6) relative to the floating-point reference. On-board tests reproduce the bit-accurate reference trigger outputs and sustain continuous 1 MHz processing without dropped input samples, verifying the functional correctness and real-time operation of the FPGA-based Level-1 trigger.
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All authors Changqing Ye, Yunhan Wang, Yifan Qiao, Zhe Cao, Beige Liu, Qing Lin, Lei Zhao
Optics
Performance of Capacitively Loaded RF Electrodes on SiO2/Si Substrates for High-Speed Electro-Optic Modulators
Ayed Sayem, Ting-Chen Hu, Mark Cappuzzo et al. (+3 more)
We experimentally investigate conventional and capacitively loaded traveling-wave RF electrodes fabricated on thermally grown SiO$_2$ on high-resistivity silicon substrates for high-speed electro-optic modulators. The capacitively loaded electrodes exhibit RF attenuation coefficients as low as approximately $0.23~\mathrm{dB/cm}/\sqrt{\mathrm{GHz}}$, comparable to values reported for electrodes fabricated on insulating quartz substrates, while retaining the silicon handle and avoiding substrate removal or undercut processing. By varying the SiO$_2$ buried-oxide (BOX) thickness and the capacitive-loading geometry, the microwave effective index can be engineered over a broad range while maintaining low RF propagation loss. This enables microwave-optical velocity matching over a wide range of optical wavelengths, from the ultraviolet to the telecom C-band. These results demonstrate that thermally oxidized silicon provides a simple and scalable substrate platform for low-loss traveling-wave electrodes in thin-film lithium niobate and thin-film lithium tantalate electro-optic modulators, as well as for high-speed RF interconnects in integrated transceivers and co-packaged optical systems.
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All authors Ayed Sayem, Ting-Chen Hu, Mark Cappuzzo, Alaric Tate, Rose Kopf, Mark Earnshaw
Computational Physics · Cross-listed from cond-mat.mtrl-sci
Multivalley 3D Electronic Structure of PbSe from Soft-X-Ray ARPES and First-Principles Calculations
Zefeng Cai, Valentine V. Volobuev, Jędrzej Korczak et al. (+7 more)
PbSe is a narrow-gap IV-VI
semiconductor, whose multivalley valence bands, with maxima at the L, $\Sigma$, and $\Delta$ points, underpin its intermediate-temperature thermoelectric properties. We combine soft-X-ray angle-resolved photoemission spectroscopy (SX-ARPES) with first principles simulations to study the valence band structure of bulk PbSe. High resolution measurements are conducted at
photon energies of 400-900 eV to map the valence
manifold along X$\Gamma$X, WXW, and K$\Gamma$K, and iso-energy surfaces are collected in the $k_z=0$ plane. Comparison to ARPES enables a rigorous assessment of the performance of density functional theory (DFT), using semi-local and hybrid functionals, as well as many-body perturbation theory within the quasiparticle self-consistent $GW$ approximation. We find that the Heyd-Scuseria-Ernzerhof (HSE) hybrid functional and QP$GW$ reproduce the measured band dispersions to within 0.1-0.2 eV over the entire valence band. In contrast, the semi-local Perdew-Burke-Ernzerhof (PBE) functional compresses the band width and deviates from experiment by up to 0.6 eV. We further show that an accurate band structure and band gap are vital to obtaining a correct description of the dependence of the Seebeck coefficient of p-type PbSe on the hole concentration (Pisarenko relation). This has implications for computational efforts to discover thermoelectric materials.
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All authors Zefeng Cai, Valentine V. Volobuev, Jędrzej Korczak, Enrico Della Valle, Hantian Liu, Moritz Hoesch, Sergey M. Frolov, Tomasz Story, Vladimir N. Strocov, Noa Marom
Physics Education
"I don't have a good metric for what other people think:" Unpacking the double empathy problem in neurodivergent physics problem-solving
Liam G. McDermott, Frank T. Dachille, George R. Keefe et al. (+3 more)
Learning is a social act and requires communication between interlocutors. Learning also is a process that takes place in a socially constructed neuro-normative system. These neuro-normative systems can marginalize neurodivergent (i.e., autistic, dyslexic, epileptic) students, who oftentimes have non-normative socio-cognitive differences. In this paper, we investigate 3 neurodivergent physics students' experiences solving physics problems and in navigating physics culture. We use a Double-Empathy Problem lens to uncover how communication, particularly communication breakdowns, can manifest for neurodivergent students in physics. We find that the 3 neurodivergent students, experience communication breakdowns in their interactions with peers and instructors, and in interpreting problem statements. Furthermore, we find that participants experience fear of being misinterpreted or feeling as though they are viewed as stupid on account of communication breakdowns. We advocate for the need for a more neuro-inclusive physics culture and suggest actions that can be done by instructors to create more inclusive spaces in physics.
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All authors Liam G. McDermott, Frank T. Dachille, George R. Keefe, Mason D. Moenter, Daryl McPadden, Erin Scanlon
Fluid Dynamics
An improved periodic activation for PINNs reconstructing convective flows
Michael Mommert, Marie-Christine Volk and Christian Bauer
Architectures with periodic activation functions have already been shown to be beneficial in comparison to monotonic counterparts for a wide range of applications of physics-informed neural networks. Here, we investigate a network architecture which uses the complex exponential function, generating pairs of sine and cosine outputs as activation functions. Testing it against comparable, sine-activated multi-layer perceptrons for the task of temperature reconstruction from sparse velocity data for cubic Rayleigh-Bénard convection reveals significant improvements in the reconstruction quality without a substantial increase in computational cost per training step. Vice versa, the improved architecture enables reaching similar reconstruction qualities for a fraction of the expense. Analyzing the mathematical structure of these networks points to the improvements being rooted in the property of passing both a sine and cosine function forward. This way, the subsequent layer is able to adapt the phase of the provided latent periodic functions, and doing it individually for each of its
neurons.
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