Chemical Physics · Cross-listed from quant-ph
Explicitly Correlated Gaussian Basis Approach to Periodic Systems
Kalman Varga
Closed-form expressions for all
matrix elements required for variational calculation of the electronic structure of periodic solids have been derived using a basis of explicitly correlated Gaussians (ECGs). Periodic basis functions are constructed by summing shifted correlated Gaussians over all composite
lattice translations, where a generalized unfolding
theorem reduces the resulting double
lattice sum to a single sum through a unified computational framework for overlap, kinetic energy, and Coulomb potential operators. The formalism has been validated through application to an infinite one-dimensional hydrogen chain, where the ground-state energy per atom computed in the thermodynamic limit is shown to agree with finite-chain results extrapolated by other many-body methods.
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Physics and Society · Cross-listed from q-bio.PE
The interplay of network structure and correlated infectious traits in epidemic models
Abhay Gupta and Nicholas W. Landry
Individual contributions to the spread of an epidemic vary widely due to an individual's location in a social network and their intrinsic ability to spread or contract diseases. While the effect of heterogeneous population structure and infection rates is well-understood, less studied is the impact of population-level covariance between susceptibility and transmissibility, despite empirical evidence showing that both susceptibility and transmission vary across individuals. We introduce a mathematical modeling framework incorporating population subgroups, each with its own joint distribution of susceptibility and transmissibility. We apply this framework to the susceptible-infected-recovered (SIR) model to examine the effect of community structure and degree heterogeneity. We derive analytical expressions for the basic reproduction number, which, when reduced, corroborates prior results and validate these results with numerical simulations. We pair these estimates with simulations exploring first, the temporal dynamics of this model with the homogeneous SIR model, and second, implications for effective social intervention. This analysis provides a foundation for future studies exploring the interplay between structural and dynamical heterogeneity in infectious disease transmission.
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Atomic Physics
Radioactive Molecules as Laboratories of Fundamental Physics
A. Jadbabaie, S. Ebadi, R.F. Garcia Ruiz et al. (+3 more)
Radioactive molecules provide a powerful new platform in the search for new physics at energy scales complementary to high-energy particle
colliders. By combining enhancements from
nuclear properties with the sensitivity and control offered by molecular structure, experiments with radioactive molecules offer great reach in the search for new physics beyond the Standard Model. Rapid progress in this field is being driven by advances in the production and control of radioactive molecules, alongside the development of new experimental tools and theoretical techniques. In this Perspective, we discuss the current status and future prospects of this rapidly developing, interdisciplinary field at the intersection of
nuclear physics, atomic and molecular physics, and particle physics.
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All authors A. Jadbabaie, S. Ebadi, R.F. Garcia Ruiz, N. R. Hutzler, A. M. Jayich, J. T. Singh
Physics Education
A Framework for institutional change in the age of AI
David Perl-Nussbaum and Noah D. Finkelstein
Generative AI is rapidly reshaping STEM higher education. Not only are our educational practices changing, but how we think about educational transformation must adapt. Existing models of institutional change in STEM, aimed at interactive engagement, have largely followed an adoption logic: relatively stable, well-researched educational practices are evaluated and then scaled. These assumptions do not hold for generative AI, which is an arrival technology – entering classrooms before a sufficient pedagogical evidence base could form. Building on recent decades of work on STEM institutional change, we propose a framework identifying six dimensions along which prior change models must be reconsidered in light of AI: three concerning the tools at the center of reform (the tool's evidence base, rate of change, and scope), and three concerning the people involved in change (faculty, change
agents, and students). For each dimension, we examine how AI-era assumptions differ from those underlying prior interactive engagement reforms and derive design implications, including: privileging humble and local inquiries; organizing reform around pedagogical approaches rather than specific tools; repositioning change
agents as facilitators of collective inquiry; and engaging students as partners in reform. Collectively, the six dimensions and design implications constitute a new framework for adapting change models to support institutions under conditions of genuine uncertainty. Finally, we illustrate how the framework may be applied through a brief case-study of a faculty workshop series carried out in a university physics department to support instructors adapting to this modern AI era.
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Computational Physics
Quantifying Multidimensional Transport Effects on Permeability Inference in FLiBe Systems Using a Validation-Informed Modeling Framework
Huihua Yang, Abhishek Saraswat, Weiyue Zhou et al. (+6 more)
Permeability of hydrogen isotopes in molten salts is commonly inferred from permeation experiments using simplified one-dimensional interpretations, which may not capture the coupled transport pathways present in realistic systems. In this work, a multi-dimensional, multi-material hydrogen isotope transport modeling framework implemented in FESTIM is benchmarked against permeation measurements from the HYPERION experiment conducted at the MIT
Plasma Science and Fusion Center.The model explicitly resolves transport across molten salt and nickel structures, as well as external boundary conditions, enabling system-level interpretation of the measured permeation fluxes over the temperature range 773-973K. Rather than relying on idealized one-dimensional formulations for permeability estimation, this study employs a validation-informed inverse framework to assess how multidomain transport and external boundary assumptions influence the permeability inferred from experimental fluxes.Two limiting external boundary conditions, representing ideal coating and uncoated vessel behavior, are used to define a physically motivated envelope for hydrogen isotope exchange with the environment.The model captures the observed magnitude and temperature dependence of permeation fluxes under both conditions, while revealing significant lateral transport and sidewall leakage pathways that are not represented in one-dimensional interpretations.The inferred FLiBe permeability exhibits consistent Arrhenius behavior but spans a range that depends strongly on the assumed boundary conditions, demonstrating that using one-dimensional formulations to describe a permeation experiment may not be adequate to extract accurate permeability.These results provide a physically grounded framework for interpreting permeation measurements in coupled
liquid-metal systems and highlight the importance of multidomain transport modeli
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All authors Huihua Yang, Abhishek Saraswat, Weiyue Zhou, Kevin Woller, James Dark, Chirag Khurana, Kaelyn Dunnell, Ethan Peterson, Remi Delaporte-Mathurin
Chemical Physics · Cross-listed from cond-mat.soft
Activity enhances transport while competing interactions preserve structure in colloidal microphase formers
Horacio Serna, José Martín-Roca, Ariel G. Meyra et al. (+1 more)
Colloidal models with short-range attraction and long range repulsion (SALR) have been extensively studied using theoretical and simulations methods due to their rich and universal
equilibrium phase behavior. Using Brownian Dynamics simulations, we study the dynamical phase behavior of active suspensions in which colloidal particles interact with each other via a SALR potential. Upon increasing the self-propulsion force of the particles, we observed that the structural transitions the active suspension undergoes resemble those observed in its passive counterpart by increasing the temperature of the thermal bath. However, when looking at the transport properties of active and passive suspensions with similar structure, we observed a clear mismatch. We demonstrated that increasing the activity enhances the particles mobility within the SALR fluid when simultaneously preserves the structure. This leads to a structure-dynamics decoupling induced by the activity whereas at the same time highlights the structural
memory of SALR potentials under non-
equilibrium conditions.
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All authors Horacio Serna, José Martín-Roca, Ariel G. Meyra, Eva G. Noya
Physics and Society · Cross-listed from cs.AI
BEHAVE: Real-Time Modeling of Human Systems as Observable Complex Dynamical Systems and Operational Objects for Physical AI
Helene Malyutina
A
robot can track every person and still fail to see the system those people form. BEHAVE treats an interacting human group as a complex dynamical system: a HumanSystem, an observable, persistent, relational object whose state is carried partly by interaction structure. It is therefore neither explicit in independent individual-track representations nor reducible to simple aggregates. We call this operational emergence. On public pedestrian data, interaction evidence improves group discrimination beyond proximity (AUC 0.896->0.933). On 24 bottleneck runs, future-calm and future-breakdown moments matched on density, mean speed, flow and speed dispersion differ in neighbour-level organization under run-level inference (p=0.028). From interaction evidence K, BEHAVE constructs conservative routing P and local dynamics J=-D+GP, separating routing from gain and relaxation. Stability, critical modes and response become explicit model quantities. We derive exact bounds on what
topology can change in collective stability, and conditions under which an observable is blind to the mode becoming unstable. In a causal real-data stress test, the coupled operator improves held-out local dynamics over self-only relaxation by 4.5%. The fitted stability margin St is prospectively associated with future throughput loss but overlaps with lag-1 autocorrelation and self-only relaxation; we read it as a model-based early-warning quantity, not a superior scalar alarm. For Physical AI, the HumanSystem provides a real-time human-side object between perception and action. A
robot or scheduler can query group state, structure, critical modes and forced response. Action-conditioned stability changes are reported only when supported by identified changes in human dynamics or signed human-machine coupling. Mixed human-machine systems are represented through a joint Jacobian.
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Computational Physics
Reduction of finite-size effects for second-order Møller-Plesset perturbation theory with singularity subtraction
Stephen Jon Quiton, Juan D. F. Pottecher, Martin Head-Gordon et al. (+1 more)
Second-order Moller–Plesset perturbation theory (MP2) for periodic systems suffers from finite-size errors (FSEs) that have inverse volume scaling due to the Coulomb kernel singularity in reciprocal space. This error scaling limits the routine applicability of MP2 and other methods that rely on it to real materials, requiring prohibitively dense k-point meshes for convergence toward the thermodynamic limit (TDL). We introduce MP2 singularity subtraction (MP2SS), a systematic approach that applies the singularity subtraction strategy to reduce MP2 FSEs. The method employs auxiliary functions and fitting procedures that consider both the singularities present at the origin in reciprocal space and also the discontinuities in the MP2 structure factor that arise from finite k-point sampling. We present three possible MP2SS configurations (Gaussian, exponential, and tuned) which use different combinations of decay functions and demonstrate their performance for gapped systems. Across a range of extended solids and molecular
crystals at large basis sets, MP2SS reduces the prefactor in MP2 FSEs and subsequently the computational resources required to converge to the TDL. MP2SS with the Gaussian auxiliary function provides the most robust corrections. Our results establish singularity subtraction as a powerful and flexible approach for mitigating finite-size errors in periodic correlation methods and provide a foundation for extending the technique to higher-order perturbation theories and other post-Hartree-Fock (HF) methods.
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All authors Stephen Jon Quiton, Juan D. F. Pottecher, Martin Head-Gordon, Lin Lin
Fluid Dynamics
Shock-Centered Low-Rank Structure and Neural-Operator Representation of Rarefied Micro-Nozzle Flows
Ehsan Roohi and Amirmehran Mahdavi
We examine the structure of Direct Simulation Monte Carlo (DSMC)-resolved internal compression layers in rarefied micro-nozzle flows and show that their apparent parametric complexity is largely a registration and finite-thickness scaling effect. A density-gradient diagnostic identifies the compression-layer station \(x_s\), while a jump-based thickness \(\delta_j=\Delta\rho/\max|\partial\rho/\partial x|\) defines a shock-centered coordinate \(\xi_j=(x-x_s)/\delta_j\). In physical coordinates, the leading proper orthogonal decomposition (POD) mode of the centerline density profiles captures only \(83.33\%\) of the fluctuation energy, whereas the jump-scaled coordinate increases this value to \(98.33\%\). A two-dimensional shock-window POD further confirms that this compactness is not a centerline artifact: in the registered \((\xi_j,\eta)\) frame, the first density mode captures \(94.98\%\) and the first two modes capture \(99.05\%\) of the fluctuation energy. The same region is identified by density-gradient and gradient-length Knudsen-number diagnostics, linking the reduced representation to localized short-gradient-length rarefaction rather than to shock motion alone. We then use this structure as an inductive bias in a shock-aligned Fusion–Deep Operator Network (DeepONet) surrogate for density, velocity components, temperature, Mach number, and pressure. For held-out back-pressure cases, density, temperature, and pressure errors remain below \(6.8\%\), \(4.3\%\), and \(6.8\%\), respectively, and the hardest case reduces the shock-window mean error from \(9.75\%\)–\(22.27\%\) for standard baselines to \(4.51\%\). The results show that improved prediction follows from the reduced shock-centered structure of the DSMC fields rather than from network capacity alone.
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Fluid Dynamics
Time-Resolved Pore-Scale Imaging of Multiphase Dissolution during CO2-Saturated Brine Injection into a Carbonate: Competition between Hydrocarbon Mobilisation and Swelling
Qianqian Ma, Rukuan Chai, Zhuangzhuang Ma et al. (+3 more)
We present time-resolved pore-scale experiments in which CO2-saturated brine was injected into a water-wet Ketton limestone sample containing residual hydrocarbon under reservoir conditions (8 MPa, 50 {\deg}C) and monitored by 4D X-ray microtomography. Equivalent pore-network models were extracted at each scan time to track pore geometry,
topology, and fluid occupancy, while fluid-fluid and fluid-rock interfacial areas and the effective reaction rate were determined from segmented images. The dissolution rate is non-monotonic in time and proceeds through three regimes, consistent with a shifting balance between hydrocarbon swelling and ganglion mobilisation, which control advective access to reactive surfaces. In the initial advection-dominated regime, pore-throat widening leads to ganglia mobilisation and efficient acidic brine delivery to reactive surfaces. The second, dissolution-inhibited regime is marked by up to two orders of magnitude reduction in effective reaction rate. Pore-network analysis shows that swollen hydrocarbon ganglia persistently occupy the largest throats throughout this regime. This occupancy is associated with a reorganisation of the advective flow field into preferential flow paths and stagnant zones. We interpret the rate suppression as primarily reflecting a path-dependent loss of advective access to reactive surfaces, with subordinate contributions from localised H+ depletion near ganglia and reduced near-wall mass transfer in widened flow paths. The inhibited state persists until hydrocarbon is displaced from the largest throats, after which, in the third stage, advective access improves and rock dissolution accelerates. These results show that the effective dissolution rate in residual-hydrocarbon-bearing carbonate depends dynamically on the competition between hydrocarbon swelling and ganglion mobilisation, governing advective access to surfaces.
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All authors Qianqian Ma, Rukuan Chai, Zhuangzhuang Ma, Yanghua Wang, Martin J. Blunt, Branko Bijeljic
Optics · Cross-listed from cond-mat.mtrl-sci
On-demand steering of hyperbolic chiral polaritons
Andrea S. Dai, Fuyang Tay, Ding Xu et al. (+11 more)
Control of light polarization and propagation in sub-wavelength architectures is foundational to nanophotonic technologies. A frontier direction is to leverage strong optical
spin-orbit interactions to realize polarization-selective light steering, known as the photonic
spin Hall effect. In this context,
hyperbolic plasmon polaritons (HPPs) are of particular interest as they offer large optical
spin-orbit coupling from strong confinement and dielectric anisotropy, as well as ray-like propagation. Despite theoretical predictions, however, the
hyperbolic spin Hall effect in natural materials has remained elusive. Here, we demonstrate the
hyperbolic spin Hall effect in the visible and near-infrared range in the natural
hyperbolic van der Waals metal MoOCl2. Enabling this discovery is a novel far-field pump-probe microscope that facilitates the launching and imaging of HPPs with exceptional sensitivity through interference with a high-momentum reference field. This approach preserves excellent control over light polarization, overcoming a key barrier to polarization-selective interrogation of
hyperbolic materials. We show that both
hyperbolic and surface plasmons in MoOCl2 display
chiral fields, and that their propagation direction can be completely switched upon light helicity reversal. Our results demonstrate on-demand steering of
chiral plasmons, firmly establishing natural
hyperbolic materials as ideal components for reconfigurable nanophotonics and
chiral light-matter coupling.
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All authors Andrea S. Dai, Fuyang Tay, Ding Xu, Inki Lee, Noah Bussell, Daria Balatsky, Francesco L. Ruta, Emma Lian, Colin Nuckolls, Xavier Roy, James G. Analytis, Andrew J. Millis, D. N. Basov, Milan Delor
Computational Physics · Cross-listed from cs.LG
Parallel-in-Time Training of Recurrent Neural Networks for Dynamical Systems Reconstruction
Florian Hess, Florian Götz and Daniel Durstewitz
Reconstructing nonlinear dynamical systems (DS) from data (DSR) is a fundamental challenge in science and engineering, but it inherently relies on sequential models. Recent breakthroughs for sequential models have produced
algorithms that parallelize computation along sequence length $T$, achieving logarithmic time complexity, $\mathcal{O}(\log T)$. Since sequence lengths have been practically limited due to the linear runtime complexity $\mathcal{O}(T)$ of classical backpropagation through time, this opens new avenues for DSR. This paper studies two prominent classes of parallel-in-time
algorithms for this task, both of which leverage parallel associative scans as their core computational primitive. The first class comprises models with linear yet non-autonomous dynamics and a nonlinear readout, such as modern State Space Models (SSMs), while the second consists of general nonlinear models which can be parallelized using the DEER framework. We find that the linear training-time recurrence of the first class of models imposes limitations that often hinder learning of accurate nonlinear dynamics. To address this, we augment DEER with Generalized Teacher Forcing (GTF), a novel variant within the more general nonlinear framework that ensures stable and effective learning of nonlinear dynamics across arbitrary sequence lengths. Using GTF-DEER, we investigate the benefits of training on extremely long sequences ($T>10^4$) for DSR. Our results show that access to such long trajectories significantly improves DSR if the data features long time scales. This work establishes GTF-DEER as a robust tool for data-driven discovery and underscores the largely untapped potential of long-sequence learning in modeling complex DS.
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Optics
Insights into the Nature of Quantum Emitters in Electron-Irradiated hexagonal Boron Nitride
Mouli Hazra, Anna Rupp, Mohammad N. Mishuk et al. (+10 more)
Quantum emitters in hexagonal boron nitride (hBN) have emerged as a promising solid-state platform for
quantum technology applications. However, a persistent challenge in the field is the unclear origin of many observed emission lines, particularly in the visible range, which can be difficult to distinguish from signals arising from organic or process-induced contamination during sample preparations and handling. This ambiguity limits both the reproducibility of emitter generation and the reliable identification of truly intrinsic
quantum defects. This work provides a step-by-step framework to assess whether
quantum emitters in electron-irradiated hBN are associated with organic contaminants introduced during sample preparation. We employ hyperspectral imaging, thermal annealing, and oxygen
plasma etching to investigate the origin of the green-yellow emitters in electron-irradiated hBN. The combined results not only rule out organic contamination as the source of emission but also provide insight into the spectral variability, thermal stability, and vertical localization of the emitters generated in electron-irradiated hBN that was created without any pre- or post-processing. In addition, our experiments demonstrate the feasibility of creating stable emitters in hBN with thicknesses below 10 nm. These findings provide practical guidance for the identification and controlled implementation of hBN-based single-
photon emitters in
quantum photonic devices.
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All authors Mouli Hazra, Anna Rupp, Mohammad N. Mishuk, Josefine Krause, Anand Kumar, Julien Chénedé, Mingi Kang, Bayarjargal N. Tugchin, Marijn Rikers, Isabelle Staude, Thomas Pertsch, Alexander Högele, Tobias Vogl
Fluid Dynamics
Turbulent oscillation in unbalanced T-junction flows
Dongjie Jia and Arezoo Ardekani
The T-junction impinging flow occurs in many fluid dynamics systems. In particular, the T-junction micromixer has recently been widely used for nanoparticle production, where the two inlet streams operate at a significant flow-rate imbalance and the Reynolds number is in the turbulent regime. This operating condition exposes a gap in the existing literature on the fluid dynamics of the T-junction. In this study, we used high-fidelity numerical simulations to investigate high-Reynolds-number unbalanced T-junction flows. We discover a new oscillatory behavior between the two inlet streams at the T-junction, leading to a new
turbulence-production mode. We will present detailed evidence of this new behavior, in contrast to the existing understanding of balanced turbulent T-junction flows. This oscillatory behavior also persists across a range of Reynolds numbers simulated, where the Strouhal number is approximately constant, indicating a self-similar phenomenon. As a result, many of the fluid dynamics parameters follow a power-law relation with the Reynold number. The discovery in this paper affects real-world applications, where process design and product quality are affected by
turbulence and mixing dynamics.
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Optics
Visible-NIR-Frequency Hyperbolic Response in Nodal-Line Semimetal PbTaSe$_2$
Vivian J. Santamaria-Garcia, Morgan G. Blevins, Simo Pajovic et al. (+2 more)
Natural
hyperbolic materials offer a powerful platform for light-matter interactions by supporting highly anisotropic electromagnetic modes without the need for artificial patterning. In this work, we experimentally demonstrate that the nodal-line semimetal PbTaSe$_2$ exhibits robust
hyperbolic optical behavior in the visible to near-infrared spectral range, which arises intrinsically from its anisotropic electronic structure and layered
crystal symmetry. By combining first-principles calculations, ellipsometry, Drude-Lorentz modeling, and reflectance measurements, we establish a consistent experimental and theoretical picture of bulk hyperbolicity in this material. This hyperbolicity is of plasmonic origin and is characterized by a competitive quality factor ($Q_\mathrm{max} \approx 2.8$) and a very large anisotropy parameter ($|R| \approx 231$) at 0.78 eV.
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All authors Vivian J. Santamaria-Garcia, Morgan G. Blevins, Simo Pajovic, Carolina Orona-Navar, Svetlana V. Boriskina
Physics Education
Power, Prescription, and Postpositivism: Considerations for collecting and representing neurodiversity demographic information in physics education research
Mason D. Moenter, George R. Keefe, Liam G. E. McDermott et al. (+1 more)
Demographic data collection is essential in education research, as demographic data allows researchers to better describe the participant population they study and to contextualize findings. However, current research practices for neurodiversity demographics often rely on prescriptive methods (e.g., requiring participants to report official diagnoses) rather than allowing participants to self-identify. This approach can: a) not allow participants to express their intersecting identities in ways that are authentic; and b) limit trustworthiness and reliability of the data and interpretation. In addition, inconsistent dissemination and representation of demographic data across studies hinder the accessibility and usability of this work. Through a literature review of neurodivergent student experiences with learning and performing STEM, we identified widespread discrepancies in how demographic information is collected and reported. This paper explores how neurodivergent identities can be more accurately and inclusively represented in education research. We present findings of a thematic analysis on the ways neurodivergent demographic data collection is done in the literature using data from a systematic literature review on neurodivergent science, technology, engineering, and mathematics (STEM) learning and performance. We call on the PER community to contribute to the development of a framework that centers participant autonomy while supporting clarity, consistency, and future research use.
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All authors Mason D. Moenter, George R. Keefe, Liam G. E. McDermott, Erin M. Scanlon
Computational Physics · Cross-listed from cond-mat.dis-nn
The critical slowing down in training diffusion models
Luca Maria Del Bono, Giulio Biroli, Patrick Charbonneau et al. (+1 more)
Computational sampling has been central to the sciences since the mid-20th century. While machine-learning-based approaches have recently enabled major advances, their behavior remains poorly understood, with limited theoretical control over when and why they succeed. Here we provide such insight for
diffusion models—a class of generative schemes highly effective in practice—by analyzing their application to the $O(n)$ model of statistical field theory in the Gaussian limit $n \to \infty$. In this analytically tractable setting, we show that training a score model with a one-layer network architecture matching the exact solution exhibits a form of critical slowing down in parameter learning. This slowing down also impacts the generation process, indicating that the well-known difficulties of sampling near criticality persist even for learned generative models. To overcome this bottleneck, we consider the power of architectural depth. We find that using a two-layer architecture drastically reduces the critical slowing down, with the training time scaling logarithmically rather than quadratically with system size. Using a
Fourier implementation of the architecture, we further show that this acceleration in training time can be achieved without drastically increasing operational complexity. Taken together, these results demonstrate that
diffusion models can overcome the critical slowing down through appropriate architectural design, and establish a controlled framework for understanding and improving learned sampling methods in statistical physics and beyond.
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All authors Luca Maria Del Bono, Giulio Biroli, Patrick Charbonneau, Marylou Gabrié
History and Philosophy of Physics
On the Anticipation of Lunar Travel in the Early 20th Century: A Pedagogical Exercise
Tina A. Harriott and Cherif F. Matta
This article examines, from historical and pedagogical perspectives, Alphonse Berget's anticipation of Earth-Moon travel in Le Ciel (Larousse, 1923), decades before the beginning of the space age. The discussion is triggered by Le Ciel, a richly illustrated French popular science work, which has a devoted chapter examining lunar and interplanetary travel within a Newtonian framework. Although Berget's treatment was not developed in isolation and reflects a broader early 20th century context that included pioneers such as French aero-engineer Robert Esnault-Pelterie, the book provides a striking pedagogical synthesis of elementary celestial mechanics and scientific popularization. Unlike earlier fictional treatments such as Jules Verne's De la Terre a la Lune, Berget approached space travel using physical
reasoning grounded in Newtonian gravitation. Using qualitative and semi-quantitative arguments based on the inverse-square law, he identified the principal phases of an Earth-Moon trajectory: escape from Earth, inertial translunar motion, transition through competing Earth-Moon gravitational fields, and final lunar capture and deceleration. His estimated Earth-Moon travel time of approximately 49 hours is of the same order of magnitude as Apollo mission transit times (approx. 72 h). We compare these early ideas with modern elementary concepts of astrodynamics, including restricted three-body trajectories, Lagrange-point dynamics, and distant retrograde orbits associated with the Artemis program. We also examine Berget's discussion of interplanetary travel, lunar landscapes, and human factors associated with prolonged voyages, including confinement, food supply, and travel duration. The analysis highlights the pedagogical value of historically grounded scientific
reasoning underpinning spaceflight mechanics.
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Computational Physics · Cross-listed from cond-mat.soft
Designing Coulombic Contact Interactions between Polarizable Particles through Asymmetry
Yanyu Duan and Zecheng Gan
Polarizable particle systems, including charged colloids, polarizable ions, biomolecular assemblies, and soft nanomaterials, can exhibit contact electrostatic interactions that depart strongly from Coulomb behavior when dielectric mismatch and
geometric singularities amplify polarization effects. Here we use charged dielectric spheres as a model system and show that these polarization contributions can be canceled by jointly tuning size, charge, and dielectric asymmetries. By extending a recently developed image-charge formula to contacting dielectric spheres, we derive analytical conditions under which the contact interaction reduces to the bare Coulomb form. Accurate two-sphere calculations validate the resulting contact design rules with relative errors below $3\%$. Strikingly, many-body molecular dynamics simulations reveal that systems satisfying these two-body rules self-assemble into structures that closely match their pure Coulomb references. These results establish asymmetry as a route for turning electrostatic complexity into Coulombic simplicity at contact, with implications for controlled self-assembly and materials design.
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Geophysics
Effects of global core-mantle boundary topography on outer-core convection and topographic torques
Tobias G. Oliver, Eric G. Blackman, John A. Tarduno et al. (+1 more)
Topography at the core-mantle boundary (CMB) couples the outer core to the mantle and likely generates observable variations in the length of day ($\Delta$LOD) and the geomagnetic field, though these effects remain poorly understood. We use direct numerical simulations of rotating shell convection with finite-amplitude CMB topography to investigate dynamical effects on the outer core. A range of topographic shapes is used, including individual spherical harmonics and a model representing seismically inferred heterogeneities in the deep mantle. As predicted by prior linear theory in the rotating annulus model, a new instability arises for Rayleigh numbers below the onset of convection; we confirm its existence in a global geometry, though the predicted scalings are quantitatively modified. The shape of the geostrophic contours – lines of constant axial height – plays a central role: deformed contours allow buoyancy to do work on the time-averaged flow, driving increases in Reynolds and Nusselt numbers of up to $\sim$100% relative to a spherical boundary. Previous work showed that topographic torques scale linearly with topographic amplitude and quadratically with flow speeds; we confirm this scaling and extend it with new theory that estimates the torques for global, spectrally broad topography. When extrapolated to core conditions, the predicted torques are consistent with the magnitude required to drive observed decadal and subdecadal $\Delta$LOD variations.
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All authors Tobias G. Oliver, Eric G. Blackman, John A. Tarduno, Michael A. Calkins
Atomic Physics
Axion-Exchange Contribution to the Energy of Lithium-Like Ions
R. R. Abdullin, A. V. Volotka, D. A. Glazov et al. (+3 more)
Axions and
axion-like particles are among the most promising candidates for dark matter and for manifestations of new physics beyond the Standard Model. In the present work, the contribution of
axion exchange to the energy of lithium-like ions is investigated within the framework of relativistic bound-state
quantum electrodynamics. A formalism for the interelectronic interaction mediated by
axion exchange is developed in the Furry picture with finite
nuclear size taken into account. Energy shifts are calculated for a wide range of
nuclear charge numbers \(Z\) and
axion masses. The magnitude of the
axion-induced contribution is shown to increase with increasing \(Z\) for all states considered. Based on the analysis of lithium-like bismuth, constraints on the
axion-electron interaction parameters are obtained in the high-mass region. The results indicate that precision spectroscopy of highly charged ions is a promising tool for searches for new physics associated with the exchange of pseudoscalar
bosons.
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All authors R. R. Abdullin, A. V. Volotka, D. A. Glazov, M. G. Kozlov, A. D. Moshkin, D. V. Chubukov
Biological Physics
Kinetics of Mycoprotein Production from Alternative Carbon Substrates
Mason Banks, Nipon Sarmah, Yiying He et al. (+3 more)
High throughput screening was used to study of the biokinetics of F. venenatum A3/5 cultivation on alternative carbon substrates, including monosaccharides, disaccharides and mixtures relevant to food & beverage, dairy and agricultural waste streams. Expired functional drink from the beverage sector was also assessed as the primary carbon source for mycoprotein production. Growth data was analysed using modified single and multiphase Gompertz models for comparison of maximum specific growth rate and progression milestones across diverse growth regimes. Time-series substrate and byproduct data was analysed using comparative metrics, providing an explanatory basis for the different growth phenotypes observed. Substrate type strongly influenced the apparent carbon allocation strategies, with rapidly consumed sugars such as glucose and sucrose supporting high growth rates, low biomass yield and a high degree of fermentative byproduct formation. Fructose and xylose cultivations led to slower overall growth but higher biomass yield and lower byproduct formation. Galactose and lactose showed distinct dynamics that suggested co-existence of transport and metabolic induction limitations. In all dual-substrate systems, sequential utilisation was observed. However, metabolic inheritance and environmental shift effects were highlighted as potential kinetic limitations. These conditions exhibited stunted diauxic growth and low yield from secondary sugars, with glucose-dominated primary growth significantly reshaping secondary substrate efficiencies relative to their study in silo. The expired functional drink supported highly rapid growth and achieved the highest maximum specific growth rate and biomass titre of all conditions examined, alongside reduced fermentative overflow and enhanced ethanol reassimilation relative to a compositionally matched synthetic control.
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All authors Mason Banks, Nipon Sarmah, Yiying He, Thomas Vinestock, Mark Taylor, Miao Guo
Data Analysis and Statistics · Cross-listed from math-ph
An analytical approach to calculating stationary PDFs for reflected random walks with an application to BESS-based ramp-rate control
Carlos Colchero, Diego Jiménez-Arreguín, Álvaro Herrera et al. (+2 more)
A Wiener-
Hopf-type integral equation for the stationary PDF of a reflected random walk is derived rigorously based on modern probability theory, and an application to battery energy storage systems (BESS), specifically the sizing of the inverter, is discussed in depth. The methodological steps include the construction of a Markov kernel, the derivation of a Fredholm integral equation of the second kind for the PDF of the BESS power, and an analytical solution of the equation based on a Neumann series. The analytical results were compared against numerical solutions obtained with the Nystrom method, as well as against the results of an algorithmic simulation using simulated input time series. The use of truncated versions of the analytic solution allows for the construction of simplified design rules for the power systems practitioner. General insights into inverter sizing criteria of storage systems for ramp-rate control of variable renewable energy (VRE) sources such as wind and
solar are provided.
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All authors Carlos Colchero, Diego Jiménez-Arreguín, Álvaro Herrera, Jorge E. Pérez-García, Oliver Probst
Fluid Dynamics · Cross-listed from cond-mat.soft
Variational approach to droplet motion on uneven solid surfaces, including contact line dynamics and evaporation
Gyula I Tóth, David N Sibley, Agnes J Bokányi-Tóth et al. (+2 more)
We show how dynamical equations for
liquid films and drops on uneven surfaces, including contact line dynamics and evaporation/condensation effects, may be formulated as a variational dynamics, generated via Onsager's variational principle. The theory applies in the isothermal overdamped-dynamics limit. We apply this general approach to obtain several well-known results on contact line dynamics and to study drops pinning and sliding on inclined corrugated surfaces. This approach constructs the dynamical equations starting from the free energy of the system and therefore has the advantage that it naturally incorporates the correct
equilibrium properties.
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All authors Gyula I Tóth, David N Sibley, Agnes J Bokányi-Tóth, Dmitri Tseluiko, Andrew J Archer
Computational Physics
Tangent-Plane Evidential Uncertainty in Active Learning for Magnetic Interatomic Potentials
Yang Cheng, Hongyu Yu and Hongjun Xiang
Magnetic interatomic potentials need to account for coupled
lattice and
spin degrees of freedom, yet constructing reliable training sets remains costly because noncollinear first-principles labels are expensive. Active learning can mitigate this cost, provided that the uncertainty estimate is physically meaningful for the
magnetic-response targets that drive
spin reorientation. Here we extend the $\mathrm{e}^2\mathrm{IP}$ evidential framework to
magnetic machine-learning interatomic potentials by formulating the projected
spin-force likelihood and the corresponding epistemic uncertainty in the tangent plane orthogonal to the local
spin direction. This construction prevents the uncertainty model from allocating probability mass to a radial
spin component that is absent from the constrained-moment supervision. Using bulk BiFeO$_3$ and monolayer CrTe$_2$ as
benchmark systems, we show that the resulting tangent-plane epistemic uncertainty indicator $U_{\mathrm{epi}}^{\mathrm{sf}}$ correlates strongly with prediction error and selects more informative configurations than random sampling, simultaneously improving energy, force, and projected
spin-force accuracy. These results demonstrate a physically interpretable and data-efficient route for constructing uncertainty-aware
magnetic machine-learning interatomic potentials.
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Optics
Transmission of signals in the 300 GHz band with a bit-error rate below ${10}^{-9}$ using a soliton comb
Mantaro Imamura, Ryo Sugano, Ayaka Yomoda et al. (+5 more)
To address the increasing demand for ultra-high-capacity wireless communication, terahertz (THz) frequencies near 300 GHz are attracting
attention as a new spectral frontier. This work presents the first experimental demonstration of error-free (BER $< 1\times10^{-9}$) 10 Gbps transmission in the 300 GHz band using a
soliton microcomb generated in an integrated silicon nitride (SiN) microring resonator. While many previous microcomb-based THz demonstrations have focused on coherent modulation formats and operation near the forward-error-correction (FEC) limit, this work investigates a simple intensity-modulation/direct-detection (IM-DD) on-off keying (OOK) architecture suitable for low-complexity THz links and fiber-wireless integrated systems. Although the experiment was conducted in a short back-to-back waveguide configuration, the generated THz wave enabled stable low-BER transmission without FEC or advanced offline signal processing. Analysis of the error-free threshold power indicates the feasibility of free-space transmission over several tens of meters with high-gain
antennas and THz-band amplifiers. These results demonstrate the feasibility of robust low-complexity THz photonic links based on
soliton microcombs for short-range fiber-wireless integrated systems.
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All authors Mantaro Imamura, Ryo Sugano, Ayaka Yomoda, Atsuro Shirasaki, Koya Tanikawa, Soma Kogure, Shun Fujii, Takasumi Tanabe
Optics
General and concise operator approach to the dyadic Green's function of layered media
Aliaksandr Arlouski, Lei Gao, Dongliang Gao et al. (+1 more)
Dyadic Green's function is an important tool of computational photonics, giving deeper insights into light-matter interaction. We present an operator approach to the derivation of the dyadic Green's function of a generic anisotropic planarly-layered medium for both electric and
magnetic fields. The resulting Green's function is expressed through the
evolution operators (a kind of transfer
matrices) of the comprising layers and the surface impedance tensors, the singular term being naturally separated from other terms. The operator approach to the Green's function simplifies both the conceptual understanding of the problem and the subsequent practical applications, some of which are demonstrated here. The proposed approach can be easily generalized to the case of spherical and cylindrical layers, as well as bi-anisotropic layered media. The obtained results can be applied in nanophotonics engineering problems.
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All authors Aliaksandr Arlouski, Lei Gao, Dongliang Gao, Andrey Novitsky
Geophysics
Calibration of stress-jump conditions for arbitrary flow directions in fluid-porous systems
Philippe Angot and Joscha Nickl
A numerical validation of the stress-jump coupling conditions for Stokes-Darcy flow in two dimensions is presented, addressing a gap that has remained since their introduction by Angot et al.. These conditions, formulated for arbitrary flow directions at the interface between a porous medium and an adjacent free-flow region, involve a friction tensor whose coefficients are not known a priori. We calibrate these parameters for a range of porous-medium configurations and flow regimes by matching the macroscopic model to reference solutions derived from processed pore-scale simulations. Several optimization strategies are assessed for this calibration task. The results show that, although three parameters are formally required, exploiting structural properties of the porous medium enables an effective reduction to a one-dimensional calibration with negligible loss in accuracy. A regional sensitivity analysis further indicates that even coarse parameter estimates can yield a well-performing model, highlighting the robustness and practical applicability of the stress-jump formulation.
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Atomic and Molecular Clusters
Natural and Dyson orbitals in small helium drops
N.K. Timofeyuk
The natural and Dyson orbitals are studied for small helium drops comprising 5 to 20 helium atoms interacting via a soft two-body gaussian potential. The wave functions of these drops have been obtained in the hyperspherical cluster model (HCM) which provides a correct description of the single-particle behaviour at large separations from the system. The natural orbitals are obtained from diagonalization of the nonlocal one-body density
matrix, while Dyson orbitals are constructed by direct overlap of the wave functions of two drops differing by one
boson. This overlap converges with increasing basis of the HCM. The shapes and occupancies of the natural orbitals as well as their link to Dyson overlaps and
evolution with increasing number of atoms are discussed. Both natural and Dyson orbitals can be used to represent the density of the system. However, the natural orbitals representation is demonstrated to be superior. With increasing
boson numbers the difference between Dyson and natural orbitals becomes less prominent and it is expected to disappear in infinitely large systems of identical
bosons.
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Atmospheric and Oceanic Physics
Acidification of Water by CO2
W. A. van Wijngaarden, P. Ridd, M. Cornell et al. (+1 more)
Fundamental inorganic chemistry shows that increasing concentrations of atmospheric CO2 will have no harmful effect on organisms that live in the natural waters of the Earths, and may well benefit them. Alkalinity and dissolved CO2 give high buffering capacity to most natural waters and minimize the change of pH from external influences. For example, doubling the atmospheric concentration of CO2 from 430 ppm to 860 ppm would reduce the pH of representative sea water at a temperature of 25 C from pH = 8.18 to pH = 7.93. This change is comparable to diurnal pH changes in biologically productive surface waters, due to photosynthetic fixation of dissolved inorganic carbon during the day and respiration at night. The change is also less than the variations of pH with latitude, longitude and depth in the oceans. This paper includes a quantitative review of the carbonate chemistry of seawater and freshwater, the buffering capacity, the Revelle factor, the transport of calcium carbonate in ground water, the formation of flowstone, and the classic use of limewater to detect gaseous CO2. The paper concludes with a brief review of those parts of chemical thermodynamics that are involved in ocean acidification.
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All authors W. A. van Wijngaarden, P. Ridd, M. Cornell, W. Happer