Popular Physics
Entropy and Frenesy: the arrow and the bustle of time
Christian Maes
Nonequilibrium statistical mechanics is the science of time as it manifests itself in the transient or steady
entropy producing dynamical condition of many-body systems. Beyond the vivid multiformity of the phenomena themselves, three foundational issues lie at its heart. The first question concerns the very origin of
entropy production, which gives macroscopic processes their direction and thereby defines the arrow of time: how does an atomistic mechanical world give rise to dissipated heat, thermalization, and time-reversal
symmetry breaking? The second asks why, far beyond the familiar behavior of
equilibrium systems, driving or agitation may produce and select stable and functionally rich structures: what is it about far-from-
equilibrium, low-
entropy driving that unleashes the wealth and intricacy of the natural world? The third issue is partly methodological: to determine how, and for which subclass of such wildly diverse nonequilibrium systems, a systematic, unified description and modeling from first principles remains possible. This essay addresses these issues in an informal, semi-popular-science style, offering a personally engaging yet wide-ranging introduction to the complementary roles of
entropy production and the less familiar, more recently coined notion of frenesy in the dynamical fluctuations of steadily driven systems. Together, we argue, they provide a more complete starting point for understanding physical time on mesoscopic to macroscopic scales.
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Fluid Dynamics
Modelling flow-driven pore closure of weakening poroelastic media
Matthew V. Ghosh, Matthew G. Hennessy, Andreas Münch et al. (+1 more)
Poroelastic materials, such as
polymer tissue scaffolds, porous rocks, and hydrogels, can weaken due to interactions between the solid skeleton and chemical species in the interstitial fluid. We develop a mathematical model for a poroelastic material to provide fundamental mechanistic insight into how weakening the material can affect the time-varying mechanics of the system. Our model couples large-deformation poroelasticity with an advection-
diffusion equation for the solute. Furthermore, we introduce a decay equation for the material stiffness, whose rate of decay depends on the solute concentration. In this way, we describe a three-way coupling between poroelastic deformation, weakening of the skeleton and transport of solute through the material. We exploit numerical and analytical techniques to reveal the flow-driven uniaxial compression of a weakening poroelastic material and determine parameter regimes for which weakening the material facilitates pore closure at the downstream boundary. We identify parameter regimes in which (1) a steady state is attained without pore closure, (2) pore closure occurs at a finite time or (3) the pores close instantaneously; we uncover case (2) through the introduction of weakening into the system. We provide insights into the relationship between the differing behaviours and the separation between the timescales of the system. For systems with slow weakening, we derive a leading-order approximation for the time of pore closure, treating the ratio of the timescales of poroelastic relaxation and weakening as a small parameter, and investigate the accuracy of this approximation and the new behaviours that arise when these timescales become comparable.
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All authors Matthew V. Ghosh, Matthew G. Hennessy, Andreas Münch, Sarah L. Waters
Optics
Parallel single-pixel imaging based on modulation region expansion and overlapping reconstruction
Yinran Shen, Xuri Yao, Shijian Li et al. (+4 more)
Parallel single-pixel imaging (PSPI) enhances the data acquisition efficiency of single-pixel imaging, but its reconstruction quality depends on a cumbersome and noise-sensitive calibration process. To address this challenge, a PSPI strategy was introduced that leverages modulation region expansion and overlapping reconstruction. This method results in the calibration of modulation of the subregion for each detector, enabling robust operations with undersampled data. It compensates for misalignment via modulation region expansion and overlapping reconstruction, achieving seamless and high-quality imaging that surpasses conventional PSPI in simulations and experiments. Furthermore, this strategy exhibits remarkable robustness, maintaining high imaging quality under extremely nonideal conditions, such as large deflection angles between the array detector and the modulator. This work provides a simple, efficient, and robust framework that simplifies the PSPI workflow and offers broad applicability in high-resolution, high-speed computational imaging.
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All authors Yinran Shen, Xuri Yao, Shijian Li, Chao Shen, Yuhao Wang, Chongwu Shao, Qing Zhao
Chemical Physics
Operando multidimensional spectroscopy reveals A-site-dependent carrier cooling in perovskite solar cells
Edoardo Amarotti, Luca Bolzonello, Qi Shi et al. (+6 more)
Understanding how photogenerated carriers dissipate excess energy in operating perovskite
solar cells is essential for connecting ultrafast photophysics with photovoltaic function and provides design principles for engineering next-generation
cell architectures. Here we use photocurrent-detected two-dimensional electronic spectroscopy (PC-2DES) to resolve energy-dependent carrier relaxation in fully encapsulated, functioning metal halide perovskite
solar cells. By comparing devices with identical architecture but different absorber compositions - MAPbI3, mixed FAMA, and FAPbI3 - we directly follow the redistribution of photoexcited carriers from initially populated high-energy states toward lower-energy band-edge states. The multidimensional photocurrent response reveals a cascade-like intraband cooling process whose rate depends strongly on absorber composition, with the slowest relaxation in MA-based devices, intermediate behaviour in mixed-cation devices, and fastest relaxation in FA-based devices. A reduced kinetic model incorporating
phonon-mediated intraband scattering, supplemented by a phenomenological many-body contribution, captures the main energy-dependent trends. These results establish action-detected multidimensional spectroscopy as a device-level probe of ultrafast energy dissipation and show that subtle changes in perovskite composition can substantially reshape the carrier relaxation pathways that precede charge extraction.
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All authors Edoardo Amarotti, Luca Bolzonello, Qi Shi, Sun-Ho Lee, Torbjörn Pascher, Donatas Zigmantas, Niek van Hulst, Nam-Gyu Park, Tönu Pullerits
Atomic Physics
Magic-wavelength matter-wave interferometry with optical clock states
Jianing Li, Swarup Das, Xinyuan Ma et al. (+4 more)
Optical clocks and atom interferometers provide complementary ways to measure time, motion and
gravity. Combining these capabilities requires matter-wave beam splitters that manipulate different clock states in the same way, so that optical internal energy becomes a controlled degree of freedom rather than a source of systematic phase shifts. Here we realized a dual matter-wave interferometer operating simultaneously on the two states of the $^{88}$Sr optical clock transition, $^1S_0$ and $^3P_0$. The interferometer is driven by Bragg pulses at the 813 nm magic wavelength, for which the two clock states experience the same optical coupling strength. This realizes a common matter-wave beam splitter for atoms whose internal energies differ by an optical excitation. With a sensitivity of 30 mrad, our measurement is consistent with a zero differential phase shift between the two clock-state Mach-Zehnder interferometers, translating to an absence of state-dependent acceleration in free fall at the level of $10^{-5}$. We further used the same interferometer to measure state-dependent optical dipole forces and determine a tune-out wavelength of the metastable $^3P_0$ state to be 478.95(8) nm. These results establish magic-wavelength clock-state interferometry as a platform for differential force sensing, excited-state polarizability metrology and future
quantum-clock tests of
gravity.
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All authors Jianing Li, Swarup Das, Xinyuan Ma, Thomas Zanon-Willette, Shau-Yu Lan, Chang Chi Kwong, David Wilkowski
Plasma Physics
Bright dual-pulse betatron X-ray generation from a laser wakefield accelerator
Bo Guo, Yang Wan, Shuang Liu et al. (+3 more)
Pump-probe experiments using dual ultrashort X-ray pulses provide unique opportunities for resolving non-
equilibrium dynamics initiated by intense X-ray excitation. Betatron radiation from
laser wakefield accelerators offers femtosecond duration, micrometer-scale source size, and intrinsic synchronization with the driving
laser, making it a promising candidate for compact ultrafast X-ray sources. Here, we experimentally demonstrate a high-flux, dual-pulse betatron X-ray source based on a density-tailored gas-mixture target. Two electron bunches are generated within a single
plasma wakefield through ionization-induced and shock-front-triggered injection, subsequently producing twin X-ray pulses. The measured electron spectra and dual-component X-ray angular profiles, together with particle-in-
cell simulations, identify the contributions of the two electron populations to the radiation. The total X-ray
photon yield reaches the level of 10^{10}
photons per shot with a 40-TW
laser system. These results establish a compact, single-stage route toward high-flux dual-pulse betatron sources for laboratory-scale ultrafast X-ray spectroscopy.
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All authors Bo Guo, Yang Wan, Shuang Liu, Xiaonan Ning, Jianfei Hua, Wei Lu
Accelerator Physics
Field deployment of a laser wakefield accelerator for on-site application
Bo Guo, Xiaonan Ning, Dexiang Liu et al. (+7 more)
Successive innovations in particle accelerators have continually expanded the frontiers of scientific discovery.
Laser wakefield accelerators promise to transform science, medicine, and industry, yet moving them from laboratory demonstrations to reliable real-world operation has remained a central, long-standing challenge. Here we report a field-deployable system that produced 100-MeV-class electron beams with 1%-level energy stability during 72 hours of continuous operation and supported routine full-power use throughout a seven-month field trial in an industrial setting. Applied to in situ micro-nondestructive testing, the system generated tens-of-MeV bremsstrahlung X-rays that enabled three-dimensional microtomography of dense materials at sub-50-{\mu}m spatial resolution and revealed 100-{\mu}m-scale internal defects in large composite structures, extending the capabilities beyond those of existing high-energy X-ray sources. These results mark a transition of
laser wakefield acceleration from laboratory proof of concept toward practical deployment in scientific and industrial applications.
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All authors Bo Guo, Xiaonan Ning, Dexiang Liu, Yue Ma, Weiwang Zeng, Mingyuan Wei, Shengtai Wei, Jianfei Hua, Yang Wan, Wei Lu
Optics
The vanishing distance: a depth-range boundary for dynamic wavefront shaping
Hugo Lassiette, Léa Testé, Léa Krafft et al. (+6 more)
Optical imaging and transmission through scattering media conventionally rely on ballistic light, whose power decays exponentially with the optical thickness. Although ballistic light cannot be exploited beyond a certain depth, no simple criterion currently identifies this limit. Therefore, we introduce here the vanishing distance that is defined as the propagation length at which the ballistic power equals the power carried by a single diffuse optical mode. Beyond the vanishing distance, multiply scattered light dominates, which can be harnessed by optical wavefront shaping or by computational reconstructions. We present a simple semi-analytical model for radiance propagation, validated by Monte Carlo simulations and by experiments in both monodisperse and heterogeneous scattering media. From these data, we estimate the vanishing distance and the associated minimum source power. Across representative scattering environments, ballistic light vanishes after about 20 to 40 scattering mean free paths. Unlike the transport mean free path that characterizes the angular randomization of the scattered light, the vanishing distance identifies the loss of the ballistic channel on a modal-power basis. The vanishing distance is thus a two-sided bound: ballistic approaches cannot be efficiently applied beyond it, whereas wavefront shaping of scattered light offers no advantage below it.
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All authors Hugo Lassiette, Léa Testé, Léa Krafft, Geoffrey Maulion, Vincent Michau, Romain Pierrat, Sébastien Popoff, Willem L. Vos, Serge Meimon
Fluid Dynamics
Roughness-controlled layer in oscillatory turbulent boundary layers over densely packed uniform roughness
Xuchen Liu, Yuan Gao, Yiyong Dong et al. (+1 more)
In coastal wave boundary layers over gravel-scale roughness, with near-bed orbital excursions ten to a hundred times the roughness height, the boundary layer is only a few roughness heights thick. A roughness-controlled layer (RCL) of the steady-flow extent two to five element heights would then leave no room for a logarithmic layer, yet experiments over densely packed marbles recover logarithmic profiles within millimetres of the crests. We resolve this contradiction by re-analysing previous Particle Image Velocimetry (PIV) records with a triple decomposition that separates the marble-locked dispersive motion from the
stochastic turbulence, across eleven wave, current and wave-current conditions. The boundary layer organises into an RCL, a transition region, and a logarithmic profile layer, with the RCL only one to two tenths of a marble diameter deep. This thinness is kinematic: above a periodic bed, the dispersive field decays over a length fixed by the element spacing, so close packing caps the layer at a fraction of a diameter. The layer is destroyed and rebuilt every half-cycle, tracking the near-bed velocity quasi-steadily, while the eddies within it stay locked to the inter-crest gap. Thinness does not imply weakness: within the layer, the dispersive kinetic energy rivals the turbulent kinetic energy, and the dispersive stress matches, near the crests exceeds, the Reynolds stress, showing that separated wakes carry organised momentum. The logarithmic layer survives because the decay length imposed by the packing is far smaller than the boundary-layer thickness, a margin set by the bed geometry rather than by the forcing.
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All authors Xuchen Liu, Yuan Gao, Yiyong Dong, Jing Yuan
Computational Physics · Cross-listed from cond-mat.stat-mech
Conditional-path Monte Carlo for rare stochastic dynamics on networks: Details and derivations
Thomas Barthel, Jiazheng Sun and Jhao-Hong Peng
The simulation of rare macroscopic events in
stochastic network dynamics, such as widespread epidemic outbreaks, cascading failures in communication networks, or the escape from metastable states in many-body systems, is severely hindered by methodological challenges like catastrophic rejection rates, weight degeneracy, genealogical correlations, and critical slowing down inherent to standard forward-time
algorithms, splitting methods, and transition-path sampling. Conditional-path Monte Carlo (CPMC) overcomes these limitations by employing non-local Swendsen-Wang-like cluster updates that operate directly on full-system trajectories. Serving as the technical companion to [Sun, Moody, and Barthel, arXiv:2608.16171], this paper provides the rigorous mathematical foundations and algorithmic details underlying the CPMC framework. We formally define the joint path-graph probability weights and derive the transition and uniformization sum rules that guarantee detailed balance. Applying the framework to susceptible-infectious-susceptible (SIS) models, we systematically construct and optimize single-node and edge graph vertex sets specifically designed to prevent lock avalanches and maintain the structural mobility of the epidemic trunk. Furthermore, we detail a dynamic programming scheme to exactly implement complex boundary conditions - including patient-zero and macroscopic outbreak-size constraints - enabling the rejection-free generation of valid trajectories. Finally, we assess the computational complexity of the
algorithm, describe parallelization strategies, and validate CPMC against exact solutions for dynamics on small networks.
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Optics · Cross-listed from quant-ph
Engineering of Dual Wavelength, Polarization Selective Metalenses in Silicon Carbide
Xiaoying Huang, Ziwei Yang, Konosuke Shimazaki et al. (+7 more)
Spin defects in silicon carbide (SiC) are promising candidates for integrated
quantum photonics, offering long-lived
spin states and near-infrared emission suitable for low-loss photonic integration and fibre-based
quantum communication. However, light extraction from these defects remains challenging due the relatively high refractive index of SiC. Metalenses offer a compact approach to enhance light collection by engineering the wavefront directly at the material interface. Here, we design and fabricate monolithic metalenses from SiC bulk material that simultaneously operate at 860 and 1240 nm, matching with emission from the nitrogen vacancy and silicon vacancy colour centers. By independently engineering the phase response at both wavelengths, the metalens enables collection and polarization manipulation of the emitted light. We further employ the metalenses to demonstrate optically detected
magnetic resonance of both defects simultaneously. These multifunctional metalenses provide a compact optical interface for scalable integrated SiC photonic devices.
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All authors Xiaoying Huang, Ziwei Yang, Konosuke Shimazaki, Kritsana Saego, Otto Cranwell Schaeper, Evan Williams, Dragomir Neshev, Hark Hoe Tan, Igor Aharonovicha, Mehran Kianinia
Computational Physics
Agentic Porting, Construction and Initial Verification and Validation of Libraries within the Open Source Unified TRAnsient Multi-Phase Advanced Reactor simulation Kit (Outram Park) Part I: A Software Engineering Log for Thermal Hydraulics
Theodore Kay Chen Ong and Sicong Xiao
Agentic porting of multiple open-source libraries into Rust, with human in the loop, has been performed for construction of modules within the Open-source Unified TRAnsient Multi-Phase Advanced Reactor simulation Kit (Outram Park). With this new methodology, verification and validation with human expertise, rather than code generation, has become the bottleneck in developing reliable simulation codes. In this work, we present the porting of OpenFOAM libraries into the Outram-Foam Rust libraries, their preliminary verification and validation (V&V) efforts, and their subsequent use in the development of open-source two-phase homogeneous-
equilibrium (HEM) choked-flow solvers for the Thermo-hydraulic AI Multi-Phase INtegrated Emulator System (TAMPINES) libraries within Outram Park, such as tampines-steam-tables. V&V efforts of Outram-Foam show that the cavity and Sod shock tube cases agree with literature values to within acceptable margin. Moreover, the preliminary development of tampines-steam-tables shows good agreement with Moody's HEM charts. Thereafter, the 1D HEM solver, developed agentically, is presented and preliminarily validated against the Edwards blowdown case. Productivity increases were observed with the use of Claude Code, but domain expertise supplied by human experts remains critically required to ensure the generated code can solve the problem effectively. Further work remains to be done in V&V, but the agentic coding methodology described here demonstrates considerable potential to speed up production and development of open-source libraries such as Outram Park.
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Fluid Dynamics
Steady transport of active particles under continuous release in confined shear flow
Hanhan Zeng and Guoqian Chen
Continuous release is a fundamental source condition in transport, yet theoretical treatments have focused on downstream concentration development for passive solutes or fully developed cross-sectional distributions of active particles. We develop a spatial theory for the steady transport of active particles under continuous release in confined shear flows, resolving the concentration field from the inlet to the far field. Based on the Smoluchowski equation, we formulate a boundary-value problem with point-source inlet flux and boundary conditions. Separation of the streamwise coordinate from the cross-sectional variables yields a non-self-adjoint generalized
eigenvalue problem, whose spatial modes are superposed to construct the solution. The eigenproblem is solved within a Galerkin spectral framework; downstream-admissible modes are retained and their coefficients determined from the inlet flux through a weighted biorthogonal expansion. Excellent agreement with individual-based simulations validates the theory. For plane Poiseuille flow under convection-dominated conditions, we find pronounced position–orientation coherence for spherical particles in the early developing region: swimming and shear reorientation drive the population through successive angular stages, generating alternating off-centre and centreline accumulation regions downstream, while dispersion progressively weakens this coherence. Particle elongation enhances orientational
alignment, producing an early three-peaked vertical profile and stronger, more persistent lateral accumulation downstream, while reducing the coherence of centreward migration and thereby suppressing secondary centreline accumulation. The streamwise marginal concentration varies non-monotonically, reflecting changes in the mean streamwise velocity, with its far-field limit given by the reciprocal of the asymptotic drift velocity.
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Chemical Physics
Chiral rotational dynamics in the molecular frame: Breaking symmetry with angular momentum
Alexander Blech, Monika Leibscher and Christiane P. Koch
Achiral molecules can be prepared in superposition states that are
chiral. Here, we propose angular momentum orientation in the molecular frame to achieve the required
symmetry breaking, exerting rotational control without the need for laboratory frame orientation. We derive the conditions for
chiral rotational dynamics from the requirement to simultaneously break the continuous spatial rotational
symmetry and the molecular point group
symmetry. This can be achieved by three microwave pulses as well as two non-resonant optical pulses in combination with a THz pulse or three THz pulses, all with mutually orthogonal polarization directions, and the ensuing dynamics can be probed by photoelectron circular dichroism. Our results open the way for distinguishing structural from dynamical enantioselectivity and investigating time-odd chiroptical phenomena in randomly oriented molecules.
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History and Philosophy of Physics
Mutual Recognition in the Philosophy of Physics: QBism, Phenomenology, Hegel
George Webster
Recent discussions of QBism have turned increasingly toward the question of its ontology. I argue that key insights into QBism's ontology of agency can be identified by reconstructing its response to Wigner's friend paradox. I clarify the relation between two formulations of that response: one grounded in the claim that
quantum states are
agents' personal probability assignments, and another grounded in the injunction to treat all users of
quantum theory as
agents on equal footing. Once disambiguated, these formulations reveal an implicit commitment to a mutually recognitive conception of agency, according to which the agential status of a user of
quantum theory depends constitutively on the acknowledgement of other
agents. This analysis clarifies what is at stake in recent QBist engagements with phenomenology - namely, the search for a more philosophically robust account of this conception of agency. I show how Merleau-Ponty's account of intersubjectivity underpins the recognitive structure implicated in QBism before tracing these themes to Hegel's account of mutual recognition. By locating QBism within a longstanding tradition of mutual recognition, I claim that we not only illuminate its theoretical structure but also open up novel conceptual resources for the rigorous articulation and justification of its ontology.
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Biological Physics
MolDStruct: benchmarking a hybrid Monte Carlo/Molecular Dynamics model for X-ray free-electron laser ionisation and fragmentation dynamics
Friederike Krüger, Simon Liljeblad, Sebastian Cardoch et al. (+6 more)
Single Particle Imaging with intense X-ray free-electron
laser pulses requires modelling of the resulting ionisation and Coulomb explosion dynamics of biomolecules to optimise experimental parameters and enable correct structural reconstruction, yet simulating the complete dynamics at
protein scale is beyond the reach of
quantum-mechanical methods. To address this, we developed \moldstruct, a hybrid Monte Carlo/Molecular Dynamics code built on GROMACS that couples high intense X-ray ionisation dynamics modelled through a Monte Carlo module with classical Molecular Dynamics for atomic propagation. Benchmarked against
quantum mechanical calculations for di-alanine, MolDStruct agrees in fragmentation patterns above a mean charge per atom of $\bar{z} \approx 1.35$. Compared with Coulomb explosion imaging experimental data for 2-iodopyridine, simulated momentum distributions reproduce the experimental Newton plots in fragment direction and fall within the range of experimental absolute momenta, with a moderate overestimation. We further apply MolDStruct to
Protein Explosion Imaging, a method that classifies molecular structures from explosion ion maps recorded on a detector, demonstrating via dimensionality reduction that conformers of the 16-residue peptide $\mathrm{Ala}_16$ and five chromophore-labelled ubiquitin mutants are distinguishable. These results establish MolDStruct as a practical tool for simulating radiation damage and Coulomb explosion dynamics of biomolecules at
protein scale, where
quantum-mechanical methods are computationally infeasible.
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All authors Friederike Krüger, Simon Liljeblad, Sebastian Cardoch, Måns Rosenbaum, Lasse Eisenach, Ibrahim Dawod, Nicuşor Tîmneanu, Carl Caleman, Tomas André
Fluid Dynamics
Optimal control of a swimming robot based on Purcell's microswimmer model
Noam Berkovich Lahav, Oren Wiezel and Yizhar Or
Purcell's swimmer is a well-known planar model of a swimming microorganism, governed by low Reynolds number hydrodynamics, which is comprised of three rigid links connected by actuated rotary joints. This model has been analyzed as a robotic locomotion system governed by first-order nonlinear dynamics with a periodic input (gait) of the two joint angles. In this work, we present a robotic macro-scale realization of this three-link swimmer moving in a highly viscous fluid. We propose a simple variant of Purcell's theoretical model with non-slender links and a central rigid sphere which represents the added drag of the
robot's central flotation block, and calibrate the model's parameters to fit experimental measurements. Next, we apply optimal control formulation based on Pontryagin's Maximum Principle (PMP) in order to find optimal gaits that maximize the displacement per cycle under bounds on the joint angles. Employing a differential
geometric method that transforms the problem to area integral enclosed by the gait trajectory in the plane of joint angles, enables visual interpretation which explains topological changes in displacement-optimal gaits upon varying the bound on the joint angles. We then apply PMP formulation to the problem of maximizing Lighthill's energy efficiency in order to obtain a boundary value problem (BVP) whose solution gives efficiency-optimal gaits for Purcell's swimmer model, as well as its variant with a central sphere. Finally, we utilize numerical methods such as parameterizing the input gait as a truncated
Fourier series, as well as GPOPS-II solver, to produce sufficient initial guess values for solving the BVPs and obtaining efficiency-optimal gaits.
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Optics
Fiber Nonlinearity Compensation of Coherent Signals Using Deep Photonic Reservoir Computer
Yi-Wei Shen, Rui-Qian Li, Zheng-Can Sun et al. (+4 more)
Photonic reservoir computer (PRC) is a promising optical computing framework for high-speed optical signal processing, and various reports have shown its functionality of linear equalization for intensity-modulation direct-detection communication links. However, coherent communication links suffer more from nonlinear impairment, whereas its nonlinear equalization is very challenging. Here we demonstrate the nonlinear equalization of coherent 16-level quadrature amplitude modulation (16-QAM) signals using a deep PRC in experiment. The deep PRC consists of cascading injection-locked
semiconductor lasers with optical feedback loops. For 16-QAM signals with a transmission rate of 240 Gbps and a launch power of 12 dBm, the single-channel PRC with 3 hidden layers raises the Q factor by as high as 0.58 dB, while the dual-channel PRC with 2 hidden layers raises the Q factor by 0.55 dB. In addition, we prove that the deep PRC is able to equalize 16-QAM signals of different launch powers and transmission distances.
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All authors Yi-Wei Shen, Rui-Qian Li, Zheng-Can Sun, Xing Li, Xinyu Liu, Shanshan Yu, Cheng Wang
Plasma Physics
Sub-Second Collisionless Gyrokinetic Eigenvalue Solutions via Orbit-Invariant Decomposition
Anrui Luo, Jingyi Yu, Huasheng Xie et al. (+1 more)
Fast analysis of microscopic drift-wave instabilities based on linear gyrokinetic simulations is desirable for modeling anomalous transport in fusion devices. In this work, we present an orbit-invariant decomposition method for solving collisionless gyrokinetic
eigenvalue problems. By discretizing velocity space along orbit invariants using particle energy and
magnetic moment, the full
eigenvalue matrix is separated into independent orbit blocks that couple with each other through the field equation, greatly reducing both
matrix dimension and computational cost without sacrificing physics. Based on this method, we extend the MGK code [Phys.\
Plasmas 24, 072106 (2017)] with both CPU and GPU implementations, supporting collisionless electrostatic and electromagnetic linear simulations in $s$–$\alpha$ and Miller
equilibrium models. For kinetic ion temperature gradient (ITG) and trapped electron mode (TEM)
eigenvalue problems, the solver reduces single-solution times to the 0.01–0.1~s range—more than three orders of magnitude faster than CGYRO on the same hardware—enabling efficient large-scale parameter scans. For fully electromagnetic KBM cases, it also achieves a speedup of three orders of magnitude over CGYRO and HD7. The eigenfrequencies and mode structures are verified by comparing with CGYRO results. The method is generally applicable to all collisionless gyrokinetic
eigenvalue formulations and has been extended to fully electromagnetic simulations. [Python code available at: https://github.com/FusionAlpha/mgk]
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All authors Anrui Luo, Jingyi Yu, Huasheng Xie, Jian Bao
Applied Physics · Cross-listed from cond-mat.mtrl-sci
Giant Bandgap Pulsation Driven by Hotspot Breathing Phonons in a Flat-Band Solid
Wenjie Liu, Huaxin Wu and Jiyang Fan
The electronic bandgap of solids is conventionally viewed as a static property at a given temperature, with only weak and
stochastic thermal fluctuations under
equilibrium conditions. Here, using ab initio molecular dynamics and first-principles electron-
phonon calculations, we reveal a pronounced room-temperature bandgap pulsation at about 7.8 THz in a perovskite-like flat-band solid, with a maximum peak-to-peak variation approaching 0.95 eV. This behavior originates from a dual selection mechanism: the A1g-like breathing branch couples much more strongly to the flat conduction-band edge than other
phonon branches, while real-space phase selectivity distinguishes its hotspot gamma-point and finite-q components. Although finite-q modes retain appreciable microscopic coupling, their intercell phase shifts produce smaller-amplitude shorter-recurrence-period responses, leaving the unit-
cell-synchronous gamma-point A1g component to dominate the fundamental-period bandgap pulsation. The resulting band-edge dynamics further modulates the optical response on femtosecond timescales. These findings demonstrate that an unexpectedly ordered electronic response can emerge from intrinsically disordered thermal
lattice fluctuations.
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Applied Physics · Cross-listed from quant-ph
Quantum sensors that compute: quantum computational magnetic-field sensing using a superconducting qubit
Purnendu Sen, Mathieu Ouellet, Saeed A. Khan et al. (+6 more)
A measurement of a single-
qubit quantum sensor reveals at most 1 bit of information about the signal that was sensed. To perform a classification task on the signal, the conventional approach is to repeat a sensing protocol many times, averaging the measurement results to obtain a high-precision estimate of the sensed signal, and then to apply classical postprocessing.
Quantum computational sensing (QCS) is an alternative approach that breaks with the paradigm of first obtaining a classical estimate of the signal and then computing a function of the estimated signal in postprocessing. QCS instead combines
quantum sensing with
quantum computing to concentrate information about the signal relevant to the task into the solitary bit revealed by each measurement. Here, we report on the experimental demonstration of QCS where sensing and computing were both performed by the same single superconducting transmon
qubit. We consider various binary classification tasks based on static and oscillating
magnetic fields induced by current through a flux line. The fields were sensed through a double-junction superconducting
quantum interference device (SQUID) loop that was part of the
qubit. We used a protocol based on
quantum signal processing to preprocess the sensed signals in the
quantum domain prior to measurement. For tasks on static
magnetic fields, our protocol outperformed the conventional baseline of Ramsey-based phase estimation by as much as 15 percentage points. For tasks on oscillating
magnetic fields, we classified signal amplitude and frequency with up to 20 and 15 percentage points higher accuracy, respectively, compared to the conventional baseline of optimized dynamical-decoupling protocols. Our results illustrate how
quantum computing can enhance
quantum sensing even with a minimally sized
quantum system subject to the practical limitations of decoherence and error-prone operations.
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All authors Purnendu Sen, Mathieu Ouellet, Saeed A. Khan, Wayne Wang, Sridhar Prabhu, Alen Senanian, William P. Banner, William D. Oliver, Peter L. McMahon
Optics
Machine Learning-Assisted Analysis and Inverse Design of Prism-Based Surface Plasmon Resonance Sensors
R. Runthala, S. Murai and P. Arora
In this work, we demonstrate a data-driven machine learning (ML) framework for the efficient design and optimization of Kretschmann-configuration-based surface plasmon resonance (SPR) sensors. A physics-based
dataset was generated using a MATLAB-based transfer
matrix method (TMM), covering diverse material properties, layer thicknesses, and multilayer configurations. Optical properties and layer thicknesses were used as input features, while figure of merit (FOM) and minimum reflectance (Rmin) were the target performance parameters. Four ML models, namely CatBoost, XGBoost, LightGBM, and multilayer perceptron (MLP), were benchmarked using R2, mean absolute error (MAE), and root mean squared error (RMSE). The framework integrates ML benchmarking, SHAP explainability, robustness analysis, and optimization-driven inverse design. SHAP-weighted perturbation experiments assessed the model's robustness to input variations. Four optimization
algorithms were employed for inverse sensor design, followed by an analysis of parameter recovery and performance. The optimizers were also evaluated using an independent forward-design task, in which repeated runs converged on a common configuration. The optimized designs agreed closely with direct TMM calculations, with FOM errors of 0.6-0.9 percent and Rmin errors below 0.7 percent. The ML models achieved R2 values greater than 0.99 while reducing computational cost from seconds to milliseconds, corresponding to an acceleration of approximately 10^3 to 10^4 times compared with direct TMM simulations. Overall, the results demonstrate that physics-based surrogate ML models combined with explainability and optimization provide a computationally efficient and interpretable framework for rapid SPR sensor analysis, inverse design, and optimization.
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History and Philosophy of Physics · Cross-listed from gr-qc
Ostrogradsky's Theorem is Incompatible with Background Independence in Quantum Gravity
Ken-ji Hamada
Ostrogradsky's
theorem shows that higher-derivative dynamical systems inevitably yields a
Hamiltonian featuring a ghost mode that is unbounded from below. However, we argue that this
theorem is inapplicable to gravitational systems, as the
Hamiltonian constraint, which encodes background independence by dictating that the total
Hamiltonian vanishes, holds strictly. The ghost mode obeying this constraint constitutes an indispensable component in the construction of space and time. Nevertheless, it should be underscored that the use of the weak-field (graviton) approximation, being a background-dependent scheme presupposing the existence of absolute time, invokes this
theorem; consequently, it is allowed only in the domain below the Planck scale, where second derivative terms dominate.
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Medical Physics
LV-CARE-Diff: A Conditional Anatomy-Aware Diffusion Model for Left Ventricular Shape Reconstruction and Function Quantification from Ultra-Sparse Cine Slices
Xinwang Li, Yu Lian, Bowei Liu et al. (+5 more)
Left ventricular functional quantification is an essential examination and is routinely performed using cardiovascular
magnetic resonance (CMR) cine imaging. However, conventional CMR cine protocols require the acquisition of multiple short-axis (SAX) slices to cover the entire left ventricle (LV) along with two long-axis (LAX) slices, which is time-consuming and places a considerable burden on patients who are unable to sustain repeated breath-holds, limiting its suitability for large-scale early screening. In this study, a Conditional Anatomy-Aware
Diffusion Model (LV-CARE-Diff) was developed using a coarse-to-fine strategy to reconstruct the complete LV shape from ultra-sparse cine slices, namely three short-axis and two long-axis slices, with the aim of accelerating CMR cine examination. LV-CARE-Diff employs a 3DUNet to generate a coarse initial shape, which is subsequently refined through a residual
diffusion model. A condition-guided input incorporating imaging plane orientation and positional metadata was constructed to enable spatial awareness, and a multi-objective training strategy jointly supervising shape, function, and anatomy was incorporated to guide high-fidelity reconstruction. LV-CARE-Diff was compared against a standalone 3DUNet, a standalone
diffusion model, and a 3D UNet with
diffusion-based refinement. Testing results indicated that complete LV shape could be robustly reconstructed by all deep learning models, with the highest reconstruction performance achieved by the proposed LV-CARE-Diff. Deep learning models reconstructing LV shape from sparse cine slices preserved 96% of functional quantification accuracy while reducing imaging time by 73%. The LV-CARE-Diff framework established in this study enables ultra-sparse cine acquisition to shorten CMR examination duration without sacrificing quantitative functional accuracy.
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All authors Xinwang Li, Yu Lian, Bowei Liu, Yifei Jiang, Jingjing Xiao, Haiyan Ding, Xiangchuang Kong, Rui Guo
Optics
Spectral design of confining optical structures by supersymmetry techniques
Samantha Cervantes-Neri, Zulema Gress-Mendoza, Daniel O-Campa et al. (+2 more)
In this work, we apply supersymmetric transformations to an optical medium with quadratic index distributions on both transversal coordinates defining an
elliptic profile. In particular, we implement first- and second-order transformations to construct new multi-parametric gradient index patterns that may host one or two subsidiary guided modes with a wide range of spectral properties and transversal intensity and phase distributions. These transformations may be continued up to an arbitrary order enabling the possibility to control the spectral and propagation properties of light beams.
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All authors Samantha Cervantes-Neri, Zulema Gress-Mendoza, Daniel O-Campa, Erik Díaz-Bautista, Sara Cruz y Cruz
Optics
Inductively Scalable, Single-Step Neural Surrogates for Wave-Scattering Inverse Problems
Charles Dove and Laura Waller
Neural network surrogates are an emerging alternative to traditional electromagnetic wave simulators like finite-difference time-domain (FDTD); their goal is to replace rigorous physical simulations with pre-trained neural networks that solve wave-scattering forward and inverse problems orders of magnitude faster. However, nonrecurrent, single-step surrogates have scaled only to a few tens of simulation variables. Here, we show that this barrier can be overcome by dynamically generating salient training examples during training, rather than randomly sampling the large space of possible examples. We introduce an
algorithm that runs in parallel with surrogate training, using gradient ascent to search refractive-index and source configurations for cases where the surrogate disagrees with a full-wave ground-truth simulator. We also use source and ground-truth normalization with an evolving replay
dataset to stabilize and accelerate learning. Using this approach, we train a fast, single-step surrogate for two-dimensional wave scattering with up to 41,772 controllable variables, including dense, freely configurable grids of refractive indices and complex-valued sources. The resulting neural surrogate is robustly accurate across diverse structured and unstructured examples and generalizes inductively to larger domains, reaching over 3 million controllable variables without retraining, a $73.8\times$ increase. We demonstrate the surrogate on large-scale forward simulations and inverse design of freeform beam splitters and gradient-index (GRIN) lenses up to 98 wavelengths wide, showing comparable or better performance than FDTD-based designs, with speedups from $1.29\times$ to $26.5\times$. These results demonstrate a practical path toward fast, robustly accurate, inductively scalable neural simulators for photonic inverse design and other wave-scattering inverse problems.
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Chemical Physics
Temporally Distinguishing Photocatalytic Dynamics
Catherine J. Fabiano, Shan Deneen, Yigao Yuan et al. (+4 more)
Light can induce both photothermal and nonthermal catalytic activity in plasmonic nanoparticles, but the extent, timescale, and efficacy of these two mechanisms remain unresolved. Here we introduce pump-pump photocatalysis, an adaptation of ultrafast excitation correlation spectroscopy in which incident
laser pulses are split into two spatially and energetically equivalent pulses separated by a variable time delay. For a given reaction and catalyst, time-sensitive nonlinear enhancements in photocatalytic activity may be distinguished from time-insensitive responses as a function of time delay, pulse power, excitation wavelength, applied temperature, reactant pressure, and pulse asymmetry. In this way, the timescales of photothermal and nonthermal activity of any photocatalyst may be monitored on sub picosecond to nanosecond timescales, and the conditions for optimal chemical reactivity may be discovered. Here we report ultrafast measurements of the ammonia decomposition reaction using a Cu-Ru
antenna-reactor photocatalyst. Photothermal contributions exhibit little sensitivity to pulse delay, while nonthermal contributions are most apparent at low excitation intensity, moderate temperatures, and sub-nanosecond timescales. Here, nonlinear, nonthermal mechanisms enhance H$_2$ production by a factor up to eleven compared to when pulses overlap. This technique may be used to provide unprecedented in operando diagnostics and control of any photocatalyst for any chemical reaction. Most importantly, these measurements allow us to ascertain the optimal distribution of light to maximize photocatalytic activity.
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All authors Catherine J. Fabiano, Shan Deneen, Yigao Yuan, Luke Kay, Peter Nordlander, Naomi J. Halas, Henry O. Everitt
Plasma Physics
The FLARE Facility
Hantao Ji, Jongsoo Yoo, Peiyun Shi et al. (+53 more)
The Facility for Laboratory Reconnection Experiments (
FLARE) has been constructed to study
magnetic reconnection in multiple X-line regimes relevant to space, astrophysical, and fusion
plasmas. Building upon the successful design of the
Magnetic Reconnection Experiment (MRX),
FLARE features a larger physical volume, stronger
magnetic fields, and an independent ohmic heating drive to significantly extend the accessible parameter space, targeting Lundquist numbers up to S ~ 10^5 and normalized system sizes up to \lambda ~ 10^3. This paper details the facility's core engineering components, including the primary
vacuum vessel, internal flux cores, highly segmented external coil systems, modular capacitor banks, and the safety interlock and control architecture. An initial diagnostic suite is presented, comprising high-resolution 2D
magnetic probe arrays, triple Langmuir probes, a fully fiber-coupled interferometer, ion Doppler spectroscopy, and fast camera imaging. Initial operations demonstrate the device's experimental flexibility and reliability, successfully executing symmetric push-pull reconnection, spheromak merging, and asymmetric downstream configurations. Currently operating within "Stage 2.5" with S ~ 2,500 and \lambda ~ 60 for anti-parallel reconnection,
FLARE provides immediate access to the multiple X-line regimes. Planned hardware upgrades, advanced diagnostic additions, and integration with fully kinetic simulations will further expand its capabilities as it transitions into a collaborative user facility for the broader
plasma science community.
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All authors Hantao Ji, Jongsoo Yoo, Peiyun Shi, Euichan Jung, Kush Maheshwari, Adam Robbins, Sunghyun Son, Adam Stanier, Yang Ren, Sayak Bose, Dylan Corl, Keith Corrigan, Robert Cutler, William Daughton, Robert Ellis, Geoffrey Gettelfinger, Ronald Hatcher, Philip Heitzenroeder, Frank Hoffmann, Jonathan Jara-Almonte, Michael Kalish, Thomas Kozub, Enrique Merino, Weiguo Que, Benjamin Smith, John Wallace, Xin Zhao, Sofia Avrutsky, Neal Crocker, Seth Dorfman, Yuka Doke, Corina Dunn, William Fox, Boting Li, Xiaocan Li, Clayton Myers, Shohgo Okazaki, Joshua Pawlak, Tongnyeol Rhee, Byonghoon Seo, Taiju Suzuki, Yang Zhang, Stuart Bale, Amitava Bhattacharjee, Troy Carter, Chuanfei Dong, James Drake, Jan Egedal, Erik Gilson, Michiaki Inomoto, Jonathan Menard, Yasushi Ono, Stewart Prager, John Sarff, Hiroshi Tanabe, Masaaki Yamada
Physics and Society
Reputation and institutional certification as complementary trust mechanisms in a single online market
Yuta Kido and Yohsuke Ohtsubo
Reputation and institutional certification are the two main trust mechanisms under information asymmetry, yet their interaction remains poorly understood. Here we analyze nearly one million eBay listings of Pokemon trading cards. Each listing pairs the seller's reputation with their signal choice, that is, whether they used costly third-party certification, their own costless claim (self-grading), or neither to convey the card's quality. First, we find that certification and self-grading partition the
market. Self-grading prevails where reputation is high and value low, whereas certification prevails in the
market's opposite corner. Furthermore, seller reputation raises the price premium of self-grading but not of certification. We then show that both empirical patterns follow from a signaling model in which false self-grading damages reputation, whereas certification requires an up-front fee. These results suggest that, even within a single
market, trust rests not on a choice between reputation and institutions but on a division of labor.
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Fluid Dynamics
Noise-separated evidence for a slow collective displacement in a rarefied hypersonic bow-shock layer
Ahmad Shoja-sani and Ehsan Roohi
Time-resolved direct simulation Monte Carlo (DSMC) fields are used to test whether a detached rarefied hypersonic bow shock contains a slow collective displacement that can be separated from correlated particle-sampling fluctuations. Mach-10 rotationally relaxing nitrogen flow over a circular cylinder is analysed for diameter-based Knudsen number $0.01\leq \KnD\leq1$, where $\KnD=\lambda_\infty/D$, $\lambda_\infty$ is the freestream mean free path and $D$ is the cylinder diameter. A density half-jump front is extracted on body-normal rays, unsupported solid-side points are excluded, and temporal coarse graining is performed before feature extraction. Persistent and sampling covariance components are compared using a penalized composite-fit score, design-scale cross-validation, block resampling, synthetic controls and complementary full-field matched filters. Corrected field proper orthogonal decomposition (POD) is high rank at every Knudsen number, yet a weak, same-signed angular displacement is resolved at $\KnD=0.01$ and $0.025$. Independent random-seed and simulator-particle-loading repeats recover the angular shape and relaxation time while the raw sampling variance changes with loading. Across the two resolved states the mean density layer broadens by $82\%$, while the angular shapes remain strongly aligned. Density and pressure recover the marker motion most strongly; the reduced Mach-number and translational-temperature participation at $\KnD=0.025$ is evidence consistent with moment-selective weakening, although observable-dependent signal-to-noise remains a possible contributor. The signal is interpreted as a low-pass bow-layer response embedded in broadband kinetic fluctuations, not as a newly discovered discrete oscillation or a demonstrated linear instability. The higher-Knudsen records are not sufficiently sensitive to establish physical disappearance.
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