Optics
Enhanced Enantioselective Optical Trapping enabled by Longitudinal Mie Resonances in Silicon Nanodisks
Guillermo Serrera and Pablo Albella
Optical enantioseparation of nanoscale matter is fundamentally limited by the intrinsic weakness of chiroptical forces compared to the dominant achiral gradient forces and thermal fluctuations. Conventional plasmonic approaches typically enhance chirality at the cost of amplifying achiral attraction and heating. Here, we overcome this trade-off by exploiting longitudinal Mie resonances in silicon nanodisks. By employing an Azimuthally-Radially Polarized Beam (ARPB) illumination, we selectively excite longitudinal Mie resonances, with strong optical chirality gradients and comparatively uniform electric field intensities. Specifically,
magnetic quadrupole (MQ) resonances, effectively decouple enantioselective forces from the achiral background, providing uniquely favorable conditions for enantioselective optical trapping. Combining full-wave simulations with Kramers' escape-rate theory, we demonstrate a robust trapping system that is both thermally stable and highly selective. We predict trapping selectivity ratios above 100 for particles with Pasteur parameters $|\kappa| \geq$ 0.03 and maintain selectivities above 2 even for weakly
chiral analytes ($|\kappa| \approx$ 0.006). These results establish longitudinal Mie resonances in high-index dielectric nanostructures as a promising, non-invasive platform for all-optical
chiral analysis and enantiomer separation.
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Optics
Micromolar chemical imaging by high-energy low-photodamage Coherent Anti-stokes Raman Scattering (HELP-CARS)
Guangrui Ding, Dingcheng Sun, Yifan Zhu et al. (+5 more)
Coherent anti-Stokes Raman scattering (CARS) microscopy offers label-free chemical imaging capabilities, but its performance is constrained by small Raman scattering cross-section, strong non-resonant background (NRB), and limited signal-to-noise ratio (SNR). Here, we introduce a high-energy, low-photodamage CARS (HELP-CARS) platform designed to overcome these physical limitations. By employing a 1-MHz non-collinear optical parametric amplifier (NOPA) with extensive pulse chirping, HELP-CARS increases the coherent Raman excitation efficiency by ~300 times and improves the signal-to-nonresonant background ratio by 11 times, while inducing negligible damage during live
cell imaging. Furthermore, to remove non-independent noise and physically entangled non-resonant background, we incorporate self-supervised deep-learning denoising and background removal based on the Kramers-Kronig relationship, yielding sensitivity improvement by an additional order of magnitude. Together, these advances provide a micromolar imaging sensitivity (160 uM for Dimethyl sulfoxide-d6) corresponding to 1000 molecules in the focal volume. Such high sensitivity enables high-fidelity chemical imaging in both fingerprint and silent windows. Hyperspectral HELP-CARS imaging of deuterated fatty acids allowed first observation of chemical separation with single lipid droplet. Together, HELP-CARS offers a powerful and generalizable approach for ultrasensitive and quantitative vibrational imaging of biological systems.
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All authors Guangrui Ding, Dingcheng Sun, Yifan Zhu, Rong Tang, Hongli Ni, Yuhao Yuan, Haonan Lin, Ji-Xin Cheng
Chemical Physics
Electronic Strong Coupling of Gas-Phase Molecular Iodine
Jane C. Nelson, Trevor H. Wright, Neo Lin et al. (+2 more)
Molecular polaritons, hybrid light-matter states formed from the strong coupling of molecular transitions and discrete photonic modes, are a compelling platform for optical control of chemical reactivity. Despite the origins of the field of polaritonics in atomic gases, strong coupling of molecular gases remains underexplored. The pristine, solvent-free gas-phase environment may prove ideal for gaining mechanistic understanding of molecular behavior under strong light-matter coupling. In this work, we achieve electronic strong coupling of the B-X, $\nu_1$ = 0$\rightarrow$32, J = 53$\rightarrow$52 and B-X, $\nu_1$ = 0$\rightarrow$34, J = 103$\rightarrow$102 rovibronic transitions of gas-phase iodine (I$_2$) lying near 532.2 nm. We access a range of coupling strengths and detuning conditions with fine control over molecular number density and cavity length stabilization. This effort represents the first demonstration of electronic polaritons in a molecular gas and opens a new platform for polariton photochemistry and photophysics.
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All authors Jane C. Nelson, Trevor H. Wright, Neo Lin, Madeline Rohde, Marissa L. Weichman
Plasma Physics
Development of a Reduced Multi-Fluid Equilibrium Model and Its Application to Proton-Boron Spherical Tokamaks
Huasheng Xie, Xingyu Li, Jiaqi Dong et al. (+8 more)
Proton-Boron fusion requires extreme ion temperatures and robust confinement, making Spherical Tokamaks (ST) with high-power neutral beam injection primary candidates. In these devices, strong toroidal rotation and the large mass disparity between
protons and boron ions drive complex multi-fluid effects - specifically centrifugal species separation and electrostatic polarization - that standard single-fluid magnetohydrodynamic (MHD) models fail to capture. While comprehensive multi-fluid models are often numerically stiff, we develop a reduced model balancing physical fidelity with computational robustness. By retaining dominant toroidal rotation and self-consistent potential while neglecting poloidal inertia and pressure anisotropy, the model couples a generalized Grad-Shafranov equation with species-specific Bernoulli relations and a quasi-neutrality constraint. The model is applied to two representative p-B ST configurations: the experimental EHL-2 and reactor-scale EHL-3B. Simulation results demonstrate that
equilibrium modifications are governed by the ion Mach number ($M$). In the low-rotation regime ($M < 0.5$), multi-fluid effects are weak and solutions approach the single-fluid limit. However, at $M > 2$, strong centrifugal forces drive significant boron accumulation at the low-field side (LFS) and generate an internal electrostatic potential on the order of 10 kV. These findings confirm the necessity of multi-fluid modeling for accurate p-$^{11}$B reactor design and establish a theoretical foundation for future investigations into stability, transport, and free-boundary dynamics.
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All authors Huasheng Xie, Xingyu Li, Jiaqi Dong, Zhiwei Ma, Yunfeng Liang, Yuejiang Shi, Wenjun Liu, Yueng-Kay Martin Peng, Lai Wei, Zhengxiong Wang, Hanyue Zhao
Optics
Reconfigurable Curved Beams at Terahertz Frequencies Using Inverse-Designed Bilayer Diffractive Structures
Wei Jia, Miguel Gomez, Steve Blair et al. (+1 more)
Curved electromagnetic beams at terahertz (THz) frequencies have recently emerged as a powerful example of wavefront engineering, with applications in imaging and high-capacity wireless communications. Unlike canonical self-accelerating solutions such as Airy beams, general curved-beam propagation enables arbitrary, application-specific trajectories that are not constrained by analytic beam families. Here, we demonstrate a passive and reconfigurable approach for generating trajectory-engineered THz curved beams using inverse-designed
bilayer diffractive optical elements (DOEs). Two phase-only diffractive layers are optimized using gradient-based inverse design to produce predetermined curved propagation paths. Reconfiguration is achieved by a 180{\deg} rotation of the second layer, which modifies the effective phase profile of the cascaded structure without altering the incident wave or individual layer designs. The proposed system can produce distinct curved trajectories with controlled transverse displacement and beam confinement, as confirmed by scalar diffraction simulations and experimental measurements. Overall, this work establishes inverse-designed cascaded DOEs as a compact and scalable platform for reconfigurable trajectory control of THz beams, providing a flexible alternative to analytic self-accelerating beams for radiative near-field THz communications.
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All authors Wei Jia, Miguel Gomez, Steve Blair, Berardi Sensale-Rodriguez
Optics
MoOCl$_2$ as a Hyperbolic Planar Platform for Nanooptics at Telecom Frequencies
Haozhe Tong, Clara Clemente-Marcuello, Kirill V. Voronin et al. (+2 more)
On-chip optoelectronics is fundamental to modern telecommunication, yet the diffraction limit of light remains a major obstacle to the extreme miniaturization of photonic integrated
circuits (PICs).
Hyperbolic polaritons (HPs) $-$ hybrid light-matter excitations in materials with opposite-signed dielectric permittivity tensor components $-$ offer a solution through their ability to support deep sub-wavelength confinement and unique optical phenomena such as canalization and negative refraction. To date, however, the most widely studied
hyperbolic van der Waals (vdW)
crystals, including hBN and $\alpha$-MoO$_3$, operate mainly in the mid-infrared, leaving the telecommunication bands (1260$-$1675 nm) largely uncovered. Here, we predict HPs operating directly in the telecommunication window in the vdW
crystal molybdenum oxychloride (MoOCl$_2$). Building on recent evidence that MoOCl$_2$ can support plasmon polaritons in the visible, we theoretically investigate its optical response at telecom wavelengths and identify the conditions under which strongly confined, canalized HPs modes emerge. Beyond establishing a telecom platform, we outline device-level opportunities enabled by these modes, including diffraction-free waveguides based on canalization, tunable polaritonic
crystals, and high-efficiency spontaneous emission-enhancement platforms. These paradigms cover the essential pillars of on-chip information processing: emission, propagation, modulation and detection. Our results establish MoOCl$_2$ as a potentially transformative material that bridges physics of
hyperbolic PPs with potential practical implementations, opening avenues for ultra-compact, high-density, and low-power photonic components.
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All authors Haozhe Tong, Clara Clemente-Marcuello, Kirill V. Voronin, Pablo Alonso-González, Alexey Y. Nikitin
Optics
Launching of Visible-Range Hyperbolic Polaritons by Gold Nanoantennas in a natural van der Waals crystal
Clara Clemente-Marcuello, Haozhe Tong, Kirill V. Voronin et al. (+2 more)
Anisotropic van der Waals materials provide a powerful platform for nanoscale optoelectronics, enabling strong light$-$matter interaction and deep electromagnetic field confinement mediated by polaritons, hybrid light$-$matter excitations with unique dispersion properties. While polaritonic phenomena in van der Waals
heterostructures have been extensively explored in the mid-infrared frequency range, their behaviour at the visible frequencies remains largely unexplored, in part due to the lack of knowledge on natural materials supporting anisotropic and highly confined visible-range polaritons. In this context, MoOCl$_2$, an anisotropic van der Waals metal, is particularly interesting, since it supports
hyperbolic plasmon polaritons (PPs) that enable directional propagation and subwavelength light compression. Here, we investigate the strategy for launching anisotropic PPs in MoOCl$_2$ in the visible frequency range using gold rod nanoantennas. The nanoantennas, placed on top of the MoOCl$_2$
crystal, excite in-plane anisotropic PP modes, effectively overcoming the momentum mismatch between waves in free-space and nanoscale PPs. We demonstrate a strong electromagnetic field confinement, angle-dependent absorption, and controlled anisotropic PP launching enabled by gold nanoantennas, highlighting the potential of MoOCl$_2$ as a compact platform for nanoscale waveguiding and optical signal processing. By providing a practical
antenna-based strategy for exciting visible-range PPs, this work addresses the lack of compact elements for optical signal manipulation and opens new opportunities for optoelectronic devices based on van der Waals polaritonics.
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All authors Clara Clemente-Marcuello, Haozhe Tong, Kirill V. Voronin, Pablo Alonso-González, Alexey Y. Nikitin
Accelerator Physics
Synchrotron-based Photonuclear Neutron Source for Energy, Medicine and Radiation Testing
Antonio Cammi, Lorenzo Loi, Andrea Missaglia et al. (+2 more)
Neutron source availability is constrained by the declining number of research reactors and the challenging cost of spallation facilities, while compact accelerator-based sources remain limited to beam powers below 100~kW due to severe thermal loads from charged particle-target interactions. Here we demonstrate that synchrotron-driven photonuclear production overcomes this fundamental limitation through architectural decoupling: electrons circulating in a storage ring generate MeV-range synchrotron radiation that drives external
neutron production targets, completely isolating targets from primary charged-particle power. This separation enables continuous-wave
photon beam powers exceeding 200~kW per beamline while drastically reducing localized heating and reducing thermal shocks. Through systematic Monte Carlo optimization across three independent codes (OpenMC, MCNPX, FLUKA), we identify optimal target configurations delivering single-beamline
neutron intensities of $3$–$13 \times 10^{14}$~n/s with inherent spectral tunability: low-Z targets (Be, D$_2$O) produce epithermal-to-thermal spectra for medical applications, while high-Z converters (W, U) generate fast
neutrons for subcritical reactors. Multi-beamline architecture enables facility-scale outputs exceeding $6 \times 10^{16}$~n/s, being competitive with research reactors, while supporting simultaneous parallel
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All authors Antonio Cammi, Lorenzo Loi, Andrea Missaglia, David Alesini, Hans Heinrich Braun
Plasma Physics · Cross-listed from gr-qc
Optical Signatures of a Schwarzschild Black Hole in a Dehnen-Type Dark Matter Halo
Javokhir Sharipov, Jonibek Khasanov, Pankaj Sheoran et al. (+2 more)
In this paper, the optical effects that occur near a Schwarzschild-like black hole (BH) with a Dehnen-type $(1,4,2)$ dark matter (DM)
halo are explored. We first derive the
photon sphere radius and obtain an analytical expression for the deflection angle in the weak-field regime by applying the Gauss-Bonnet
theorem (GBT). For the strong-field regime, we perform ray-tracing calculations to examine the behavior of light trajectories and determine the corresponding number of orbits. We further compute the BH shadow and gravitational
lensing in a
plasma medium and provide constraints arising from the DM
halo parameters. We also extend our analysis to weak gravitational
lensing within
plasma environments, considering both uniform and singular isothermal sphere (SIS) distributions. We find the analytical expressions for the deflection angle in the presence of
plasma and examine the resulting effects on image magnification. The overall results highlight how DM
halo properties and
plasma characteristics jointly alter observable
lensing signatures.
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All authors Javokhir Sharipov, Jonibek Khasanov, Pankaj Sheoran, Sanjar Shaymatov, Bobomurat Ahmedov
Atomic Physics
Charge Exchange Dynamics in Cold Collisions of $^{40}$CaH$^+$ and $^{39}$K
Swapnil Patel, Dibyendu Sardar, Jyothi Saraladevi et al. (+2 more)
We report the observation of charge-exchange collisions between trapped calcium monohydride molecular ions ($^{40}$CaH$^+$) and ultracold potassium atoms ($^{39}$K) in a hybrid ion-atom trap. The measured charge-exchange rate coefficient is significantly suppressed relative to the Langevin rate constant for the system. We use $\mathit{ab\ initio}$
quantum-chemical calculations to model the (CaH-K)$^+$ complex in the ground and excited electronic states and to identify possible charge-exchange mechanisms. Our calculations rule out a direct non-radiative charge-exchange reaction and instead point to a radiative mechanism, but do not quantitatively reproduce the measured rate, highlighting the need for a full-dimensional
quantum dynamics treatment that includes vibrational motion and intermediate complex formation. Our work demonstrates that cold hybrid ion-atom platforms with molecular ions enable access to richer chemical complexity and collisional dynamics inaccessible in purely atomic systems.
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All authors Swapnil Patel, Dibyendu Sardar, Jyothi Saraladevi, Michał Tomza, Kenneth R. Brown
Fluid Dynamics
From oblique-wave forcing to streak reinforcement: A perturbation-based frequency-response framework
Dušan Božić, Anubhav Dwivedi and Mihailo R. Jovanović
We develop a perturbation-based frequency-response framework for analyzing amplification mechanisms that are central to subcritical routes to transition in wall-bounded shear flows. By systematically expanding the input-output dynamics of fluctuations about the laminar base flow with respect to forcing amplitude, we establish a rigorous correspondence between linear resolvent analysis and higher-order nonlinear interactions. At second order, quadratic interactions of unsteady oblique waves generate steady streamwise streaks via the lift-up mechanism. We demonstrate that the spatial structure of these streaks is captured by the second output singular function of the streamwise-constant resolvent operator. At higher orders, nonlinear coupling between oblique waves and induced streaks acts as structured forcing of the laminar linearized dynamics, yielding additional streak components whose relative phase governs reinforcement or attenuation of the leading-order streak response. Our analysis identifies a critical forcing amplitude marking the breakdown of the weakly nonlinear regime, beyond which direct numerical simulations exhibit sustained unsteadiness. We show that this breakdown coincides with the onset of secondary instability, revealing that the nonlinear interactions responsible for streak formation also drive the modal growth central to classical transition theory. The resulting framework provides a mechanistically transparent and computationally efficient description of transition that unifies non-modal amplification, streak formation, and modal instability within a single formulation derived directly from the Navier-Stokes equations.
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Optics
Lithium niobate quadratic integrated nonlinear photonics: enabling ultra-wide bandwidth and ultrafast photonic engines
Meng Tian, Guanyu Han, Ziyao Feng et al. (+5 more)
Integrated photonic coherent light sources capable of generating emission with broad spectral coverage and ultrashort pulse durations are critical for both fundamental science and emerging technologies. In this Perspective, we start by discussing emerging
quantum and classical photonic applications from the standpoint of operating wavelength and timescale, highlighting the technological gaps that persist in current integrated photonic light sources. Next, we introduce the unique properties of lithium niobate-based integrated quadratic nonlinear photonics, and discuss several promising strategies that exploit this platform to realize wavelength-tunable continuous wave light sources and broadband, ultra-short light pulse generation. We also assessed their advantages and limitations while discussing potential solutions. Finally, we outline future prospects and challenges that need to be addressed, aiming at inspiring continued research and innovation in this rapidly evolving field.
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All authors Meng Tian, Guanyu Han, Ziyao Feng, Yu Liu, Yu Wang, Wenjun Deng, Ayed Al Sayem, Qiushi Guo
Physics and Society · Cross-listed from cs.LG
Importance inversion transfer identifies shared principles for cross-domain learning
Daniele Caligiore
The capacity to transfer knowledge across scientific domains relies on shared organizational principles. However, existing transfer-learning methodologies often fail to bridge radically heterogeneous systems, particularly under severe data scarcity or
stochastic noise. This study formalizes Explainable Cross-Domain Transfer Learning (X-CDTL), a framework unifying network science and explainable artificial intelligence to identify structural invariants that generalize across biological, linguistic, molecular, and social networks. By introducing the Importance Inversion Transfer (IIT) mechanism, the framework prioritizes domain-invariant structural anchors over idiosyncratic, highly discriminative features. In anomaly detection tasks, models guided by these principles achieve significant performance gains - exhibiting a 56% relative improvement in decision stability under extreme noise - over traditional baselines. These results provide evidence for a shared organizational signature across heterogeneous domains, establishing a principled paradigm for cross-disciplinary knowledge propagation. By shifting from opaque latent representations to explicit structural laws, this work advances machine learning as a robust engine for scientific discovery.
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Fluid Dynamics · Cross-listed from cond-mat.mtrl-sci
Fixed-grid sharp-interface numerical solutions to the three-phase spherical Stefan problem
Yavkreet Swami, Jacob Barajas and Amneet Pal Singh Bhalla
Many metal manufacturing processes involve phase change phenomena, which include melting, boiling, and vaporization. These phenomena often occur concurrently. A prototypical 1D model for understanding the phase change phenomena is the Stefan problem. There is a large body of literature discussing the analytical solution to the two-phase Stefan problem that describes only the melting or boiling of phase change materials (PCMs) with one moving interface. Density-change effects that induce additional fluid flow during phase change are generally neglected in the literature to simplify the math of the Stefan problem. In our recent work [1], we provide analytical and numerical solutions to the three-phase Stefan problem with simultaneous occurrences of melting, solidification, boiling, and condensation in Cartesian coordinates. Our current work builds on our previous work to solve a more challenging problem: the three-phase Stefan problem in spherical coordinates for finite-sized particles. There are three moving interfaces in this system: the melt front, the boiling front, and the outer boundary which is in contact with the atmosphere. Although an analytical solution could not be found for this problem, we solved the governing equations using a fixed-grid sharp-interface method with second-order spatio-temporal accuracy. Using a small-time analytical solution, we predict a reasonably accurate estimate of temperature (in the three phases) and interface positions and velocities at the start of the simulation. Our numerical method is validated by reproducing the two-phase nanoparticle melting results of Font et al. [2]. Lastly, we solve the three-phase Stefan problems numerically to demonstrate the importance of kinetic energy terms during phase change of smaller (nano) particles. In contrast, these effects diminish for large particles (microns and larger).
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Popular Physics
World without Viscosity
Mohammad-Reza Alam
Viscosity, the internal friction of fluids, is among the most consequential yet underappreciated properties in physics. This paper explores what would happen if viscosity vanished from all fluids while other material properties remained unchanged. The consequences are catastrophic and universal. Aircraft cannot generate lift because circulation around wings requires viscous action. Rotating machinery seizes without lubricating fluid films. Cardiovascular systems lose the resistance necessary for pressure regulation. Rivers become violent torrents, aquifers drain in hours, and storms persist indefinitely without frictional dissipation. The pedagogical value lies in illuminating viscosity's role providing resistance, damping, and control across all scales - from cellular interiors to planetary atmospheres.
Evolution, engineering, and
climate have exploited viscous dissipation for billions of years; its absence would render complex life impossible and Earth uninhabitable. By imagining a world without viscosity, we better understand the viscous world we inhabit.
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Physics and Society
When do neural ordinary differential equations generalize on complex networks?
Moritz Laber, Tina Eliassi-Rad and Brennan Klein
Neural ordinary differential equations (neural ODEs) can effectively learn dynamical systems from time series data, but their behavior on graph-structured data remains poorly understood, especially when applied to graphs with different size or structure than encountered during training. We study neural ODEs ($\mathtt{nODE}$s) with vector fields following the Barabási-Barzel form, trained on synthetic data from five common dynamical systems on graphs. Using the $\mathbb{S}^1$-model to generate graphs with realistic and tunable structure, we find that degree heterogeneity and the type of dynamical system are the primary factors in determining $\mathtt{nODE}$s' ability to generalize across graph sizes and properties. This extends to $\mathtt{nODE}$s' ability to capture fixed points and maintain performance amid missing data. Average clustering plays a secondary role in determining $\mathtt{nODE}$ performance. Our findings highlight $\mathtt{nODE}$s as a powerful approach to understanding complex systems but underscore challenges emerging from degree heterogeneity and clustering in realistic graphs.
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Fluid Dynamics
Dimensional regimes in Kolmogorov Flow
Melisa Y. Vinograd, Joaquin Cullen and Patricio Clark di Leoni
We study the dimensionality of two-dimensional Kolmogorov flows over a wide range of Reynolds numbers and forcing wavenumbers $k_f=\{2,4,8\}$ using two complementary approaches: convolutional autoencoders and a Kaplan-Yorke estimation based on Lyapunov analysis. As the Reynolds number increases, two distinct transitions are observed: the first corresponds to the destabilization of a periodic orbit, while the second marks the saturation of the large-scale motions. When expressed in terms of the forcing Reynolds number, these transitions occur at nearly the same value for all forcing wavenumbers, suggesting a universal scaling with respect to the forcing scale. By filtering the data to retain only the large-scale range ($k < k_f$), we show that the dimensionality estimated by the autoencoders also saturates at the second transition, implying that once the large scales are fully developed, the subsequent increase in dynamical activity occurs predominantly at smaller scales. At higher Reynolds numbers, the Kaplan-Yorke dimension ceases to grow, revealing its limited sensitivity to the nonlinear interactions that dominate in this regime. Both the Kaplan-Yorke saturation dimension and the filtered large-scale dimensionalities exhibit a linear dependence on $k_f$, indicating that the number of active degrees of freedom scales with the forcing scale rather than with the total number of available
Fourier modes.
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Chemical Physics
Colloidal logic-gate circuits can process environmental signals and autonomously perform tasks
Jiang-Xing Chen, Jia-Qi Hu and Raymond Kapral
Cooperative collective dynamics is a principal determinant of the ability of synthetic micromotors to perform specific functions. However, realizing controllable and predictable collective behavior in complex physiological environments remains a significant challenge. Here, we show that collections of enzyme-coated colloids can be designed as various chemical logic gates, which subsequently can be organized into functional logic
circuits. These
circuits take environmental information as input signals and process it to produce output chemical species needed to achieve specific goals. The chemical computation performed by the
circuit endows the active colloidal system with the ability to sense its surroundings and autonomously coordinate its collective motion. The results of simulations of several examples are presented, where self-assembled colloidal
circuits can identify invasive threats by their signals, produce and deliver chemicals to the targets to suppress their activity. The results of this work can aid in the design of experimental chemical logic
circuits through micromotor self-assembly that autonomously respond to environmental cues to execute specific tasks.
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History and Philosophy of Physics
Spacetime singularities and incompleteness: epistemic and ontological remarks
Gustavo E. Romero
I argue that spacetime singularities entail no ontological commitment to material entities. First, I show that Penrose's singularity
theorem is best understood as a
theorem of incompleteness, it demonstrates the failure of specific spacetime models within General Relativity (or any theory incorporating the Raychaudhuri equation) under certain general conditions. Although this has been done before, I adopt a novel approach based on differentiating between physical and purely formal assumptions in the axiomatic foundation of general relativity. Next, I compare Penrose's result with Gödel's incompleteness
theorem, highlighting key similarities and differences. Finally, I draw philosophical conclusions regarding the limits and prospects of our epistemic reconstructions of the physical world.
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Medical Physics
An in vivo validation dataset for dynamic volumetric MRI
Max H.C. van Riel, David G.J. Heesterbeek, Martijn Froeling et al. (+2 more)
Dynamic volumetric MRI provides valuable information on in vivo motion and biomechanics, with applications spanning cardiac, musculoskeletal, or pulmonary imaging, amongst others. Developing reconstruction methods for time-resolved volumetric MRI is challenging due to the inherently slow acquisition process of MRI, which makes it an active area of research. However, in vivo validation of these methods remains challenging due to the lack of publicly available
datasets with fully sampled ground-truth images. Here, we present a publicly available in vivo
dataset designed to facilitate the development and validation of dynamic volumetric MRI reconstruction
algorithms. Controlled and repeatable deformations of the muscles in the thigh were induced using a pneumatic pressure cuff, enabling the acquisition of both undersampled dynamic data and fully sampled validation images. The
dataset comprises multichannel undersampled k-space data from nine healthy volunteers across four different dynamic deformations, with fully sampled validation data for one deformation. Additionally, an anatomical reference scan and muscle
segmentation masks are provided for each subject. To illustrate a possible image reconstruction and validation approach, a binning-based reconstruction was performed on the undersampled data from six dynamic repetitions. The resulting images were consistent with the corresponding fully sampled validation images. This
dataset offers possibilities for validating and advancing time-resolved volumetric MRI reconstruction methods.
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All authors Max H.C. van Riel, David G.J. Heesterbeek, Martijn Froeling, Cornelis A.T. van den Berg, Alessandro Sbrizzi
Applied Physics · Cross-listed from eess.SP
Denoise Stepwise Signals by Diffusion Model Based Approach
Xingdi Tong and Chenyu Wen
Stepwise signals are ubiquitous in single-molecule detections, where abrupt changes in signal levels typically correspond to molecular conformational changes or state transitions. However, these features are inevitably obscured by noise, leading to uncertainty in estimating both signal levels and transition points. Traditional frequency-domain filtering is ineffective for denoising stepwise signals, as edge-related high-frequency components strongly overlap with noise. Although Hidden Markov Model-based approaches are widely used, they rely on stationarity assumptions and are not specifically designed for signal denoising. Here, we propose a
diffusion model-based
algorithm for stepwise signal denoising, named the Stepwise Signal
Diffusion Model (SSDM). During training, SSDM learns the statistical structure of stepwise signals via a forward
diffusion process that progressively adds noise. In the following reverse process, the model reconstructs clean signals from noisy observations, integrating a multi-scale convolutional network with an
attention mechanism. Training data are generated by simulating stepwise signals through a Markov process with additive Gaussian noise. Across a broad range of signal-to-noise ratios, SSDM consistently outperforms traditional methods in both signal level reconstruction and transition point detection. Its effectiveness is further demonstrated on experimental data from single-molecule Forster Resonance Energy Transfer and nanopore DNA translocation measurements. Overall, SSDM provides a general and robust framework for recovering stepwise signals in various single-molecule detections and other physical systems exhibiting discrete state transitions.
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Physics Education
AI-based Verbal and Visual Scaffolding in a Serious Game: Effects on Learning and Cognitive Load
Caroline Wermann, Karina E. Avila, Sebastian André et al. (+8 more)
Due to their interactive nature, serious games offer valuable opportunities for supporting learning in educational contexts. Recent advances in large
language models (LLMs) have further opened the door to new forms of personalized scaffolding in education. In this study, we combine both worlds and study three types of AI-based scaffolding designs in a serious game: (i) no scaffolding, (ii) chat-based (verbal) scaffolding provided by an AI-based non-player character (NPC), and (iii) combined chat-(verbal) and action-based (visual) scaffolding in which the AI may both try to explain or demonstrate the next step towards a solution. The scaffolding conditions are embedded in Qookies, a serious game designed to introduce fundamental concepts of
quantum technologies. A total of 152 school students, university students, and members of the general public were randomly assigned to one of the three conditions. The results show that all groups experience significant learning gains, confirming the overall effectiveness of the serious game itself. No significant differences in learning outcomes emerged between scaffolding conditions. However, intrinsic cognitive load was lower in the combined chat-and-action (verbal+visual) scaffolding condition compared to the chat (verbal)-only condition, suggesting that visual demonstrations may offer more accessible support. Interaction analyses further revealed that players engaged with the AI character primarily for level-related questions and action recommendations, while deeper interactions were relatively rare.
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All authors Caroline Wermann, Karina E. Avila, Sebastian André, Julia C. Draeger, Alvar Goetze, Jochen Kuhn, Maite Maurer, Sascha Mehlhase, Nikola Merkas, Fabian Schrodt, Stefan Küchemann
Plasma Physics
Weak and reversed magnetic shear effects on internal kink and fishbone modes
Weikang Cai, Ping Zhu, Zhi Zhang et al. (+2 more)
Advanced tokamak scenarios often feature weak or reversed
magnetic shear configurations. In this study, the hybrid kinetic-MHD model implemented in the NIMROD code is used to investigate the effects of reversed
magnetic shear on internal kink and fishbone mode in a circular shaped limiter tokamak. In the absence of energetic particles (EPs), the mode growth rate initially increases and then decreases as the
magnetic shear changes from positive to negative, indicating stabilizing effects of the reversed
magnetic shear on the internal kink mode. In the presence of EPs, when the reversed
magnetic shear region is sufficiently narrow, the transition from internal kink/fishbone modes to double kink/fishbone modes takes place, and the stabilizing effects of the reversed
magnetic shear can significantly dominate the destabilization of EPs. For non-resonant modes, the EP beta fraction $\beta_f$ for excitation increases with $q_{min}$, concurrent with progressively lower growth rates in non-resonant fishbone modes. When the
equilibrium profile has an internal transport barrier (ITB), broader ITB widths suppress internal kink modes more effectively, whereas steeper temperature gradients strengthen EP stabilization.
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All authors Weikang Cai, Ping Zhu, Zhi Zhang, Shiwei Xue, Sui Wan
Chemical Physics · Cross-listed from quant-ph
Error compensation without a time penalty: robust spin-lock-induced crossing in solution NMR
Mohamed Sabba, Christian Bengs, Urvashi D. Heramun et al. (+1 more)
A modification of the widely-used
spin-lock-induced crossing (SLIC) procedure is proposed for the solution
nuclear magnetic resonance (NMR) of strongly coupled
nuclear spin systems, including singlet NMR and parahydrogen-enhanced hyperpolarised NMR experiments. The compensated-SLIC (cSLIC) scheme uses a repetitive sequence where the repeated element employs two different radiofrequency field amplitudes. Effective compensation for deviations in the radiofrequency field amplitude is achieved without increasing the overall duration of the SLIC sequence. The advantageous properties of cSLIC are demonstrated by numerical simulations and by representative experiments.
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All authors Mohamed Sabba, Christian Bengs, Urvashi D. Heramun, Malcolm H. Levitt
Physics and Society · Cross-listed from cs.IR
Whose Name Comes Up? II: Benchmarking and Intervention-Based Auditing of LLM-Based Scholar Recommendation
Lisette Espín-Noboa and Gonzalo Gabriel Méndez
Large
language models (LLMs) are now used for academic expert recommendation. Existing audits typically evaluate such recommendations in isolation, ignoring end-user inference-time interventions. Thus, it remains unclear whether failures (e.g., refusals,
hallucinations, uneven coverage) stem from model choice or deployment decisions. We introduce LLMScholarBench, a
benchmark for
auditing LLM-based scholar recommendation that jointly evaluates model infrastructure and end-user interventions across multiple tasks. LLMScholarBench measures technical quality and social representation using nine metrics. We instantiate the
benchmark in physics expert recommendation and audit 22 LLMs under temperature variation, representation-constrained prompting, and
retrieval-augmented generation (RAG) via web search. Our results show that each intervention entails distinct tradeoffs. Higher temperature degrades validity, consistency, and factuality. Representation-constrained prompting improves diversity at the expense of factuality, while RAG primarily improves technical quality while reducing diversity and parity. Overall, end-user interventions reshape trade-offs rather than providing uniform gains. LLMScholarBench makes all these dynamics auditable across models and interventions in LLM-based scholar recommendations.
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Applied Physics · Cross-listed from quant-ph
Spin-active chlorine-related centers in 4H-SiC with telecom-band emissions
Danial Shafizadeh, Misagh Ghezellou, Viktor M. Bobal et al. (+5 more)
A photoluminescence (PL) and
magnetic resonance investigation of a defect in chlorine-implanted 4H-SiC is presented. This Cl-related center emits light at telecom wavelengths with zero-
phonon lines in the range 1350-1540 nm. Its four configurations exhibit stable PL spectra characterized by narrow zero-
phonon lines. For the two configurations that emit light at the C-band, a Debye-Waller factor in the range 22-25% is estimated. Optically detected
magnetic resonance confirms that the Cl-related center is
spin active and stable at room temperature with the zero-field splitting in the range of 1.0-1.4 GHz. The combined optical and
spin properties suggest this center to be a highly promising candidate for scalable
quantum networks.
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All authors Danial Shafizadeh, Misagh Ghezellou, Viktor M. Bobal, Lasse Vines, Jawad Ul-Hassan, Valdas Jokubavicius, Nguyen T. Son, Ivan G. Ivanov
Physics and Society
Cooperative Sovereignty on Mars: Lessons from the International Telecommunication Union and Universal Postal Union
Alexander H. Ferdinand Ferguson and Jacob Haqq-Misra
As humans make ambitious efforts toward long-duration activities beyond Earth, new challenges will continue to emerge that highlight the need for governance frameworks capable of managing shared resources and technical standards in order to sustain human life in these hostile environments. Earth-based governance models of cooperative sovereignty can inform governance mechanisms for future Mars settlements, particularly regarding inter-settlement relations and the technical coordination required for multiple independent settlements to coexist. This study analyzes the International Telecommunication Union (ITU) and the Universal Postal Union (UPU), two of the oldest international organizations, which have successfully established evolving standards across sovereign nations. This analysis of the development and governance structures of these two organizations, and how they resolved key sovereignty issues, reveals principles that could be applicable to future settlements beyond Earth, particularly on Mars. Key insights include the strategic necessity of institutional neutrality, the management of asymmetric power relations, and the governance of shared resources under conditions of mutual vulnerability. The study distinguishes between a "Survival Layer" of technical standards essential for immediate safety and an "Operational Layer" governing economic and political activities, suggesting different governance approaches for each. Although some of these examples of cooperative sovereignty on Earth might not be sufficient for Mars due to its unique environment, lessons from the ITU and UPU case studies offer valuable strategies for designing flexible and sustainable governance models that can function from inception through explicit Earth-based coordination.
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Chemical Physics · Cross-listed from stat.ML
Cutting Through the Noise: On-the-fly Outlier Detection for Robust Training of Machine Learning Interatomic Potentials
Terry C. W. Lam, Niamh O'Neill, Christoph Schran et al. (+1 more)
The accuracy of machine learning interatomic potentials suffers from reference data that contains numerical noise. Often originating from unconverged or inconsistent electronic-structure calculations, this noise is challenging to identify. Existing mitigation strategies such as manual filtering or iterative refinement of outliers, require either substantial expert effort or multiple expensive retraining cycles, making them difficult to scale to large
datasets. Here, we introduce an on-the-fly outlier detection scheme that automatically down-weights noisy samples, without requiring additional reference calculations. By tracking the loss distribution via an exponential moving average, this unsupervised method identifies outliers throughout a single training run. We show that this approach prevents overfitting and matches the performance of iterative refinement baselines with significantly reduced overhead. The method's effectiveness is demonstrated by recovering accurate physical observables for
liquid water from unconverged reference data, including
diffusion coefficients. Furthermore, we validate its scalability by training a foundation model for organic chemistry on the SPICE
dataset, where it reduces energy errors by a factor of three. This framework provides a simple, automated solution for training robust models on imperfect
datasets across
dataset sizes.
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All authors Terry C. W. Lam, Niamh O'Neill, Christoph Schran, Lars L. Schaaf
Medical Physics
Test-retest Reliability of Psychophysical Tasks Using Structured Light-Induced Entoptic Phenomena
Taranjit Singh, Mukhit Kulmaganbetov, Zhangting Wang et al. (+8 more)
Structured light (SL)-induced polarization perception presents a promising method for the early detection of macular diseases such as age-related macular degeneration. We investigated the test-retest reliability of a psychophysical task using SL-based stimuli to induce entoptic patterns in individuals with healthy
vision. Twenty-eight participants underwent thorough eye examinations to confirm they had healthy eyes and good
vision (logMAR BCVA ~0.00). Of these, 25 participants (n=50 eyes) aged 21 to 75 completed two identical tasks separated by 1 to 14 days. Using SL-based stimuli that produced a rotating entoptic pattern containing 22 azimuthal brushes, we measured the retinal eccentricity threshold $R_T$ at which participants could reliably identify the direction of rotation by varying the size of a central obstruction. This threshold reflects the visual angle of the pattern for each participant. We calculated the reliability coefficient (intraclass correlation coefficient, ICC) using a two-way mixed-effects model and conducted a Bland-Altman analysis to assess test-retest reliability. The ICC was 0.83 [95% CI: 0.62 - 0.93] for right eyes (RE) and 0.93 [95% CI: 0.84 - 0.97] for left eyes (LE), indicating good reliability. The Bland-Altman analysis showed a mean difference of -0.32{\deg} (SD: 1.51) and -0.12{\deg} (SD: 1.03) for RE and LE respectively between the first and second sessions, with limits of agreement ranging from -3.28{\deg} to 2.64{\deg} and -2.14{\deg} to 1.89{\deg} for RE and LE respectively, confirming strong agreement and no significant bias. These results demonstrate that SL-based psychophysical tasks are a reliable method for assessing polarization perception, potentially improving screening for diseases affecting macular health.
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All authors Taranjit Singh, Mukhit Kulmaganbetov, Zhangting Wang, Dmitry Pushin, Benjamin Thompson, Andrew Silva, Melanie Mungalsingh, Iman Salehi, Davis Garrad, David Cory, Dusan Sarenac
Applied Physics
Perfect all-angle asymmetric transmission via normal susceptibilities: exact spatial derivative by local meta-atoms and nonlocal metasurfaces
Amit Shaham and Ariel Epstein
We present a systematic methodology for realizing accurate asymmetric all-angle transmission in nonlocal metasurfaces. As a representative example, we derive closed-form susceptibility conditions for exact first-order spatial differentiation of unity numerical aperture, clarifying the role of each underlying balance. We provide rigorous and detailed designs of physically meaningful structures that directly feature such susceptibilities: a conceptual local meta-atom and a realistic nonlocal multilayered printed
circuit board (PCB). Importantly, the latter leverages an intricate system of nearfield coupling beyond standard homogenization. Validated in simulations, our results provide a general and modular route to high-resolution asymmetric nonlocal metasurfaces for optical analog processing.
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