Instrumentation and Detectors
PhotonPix: Single-Photon Detector with 10 ps timing precision and high dynamic range
D.A. Orlov, Y. Prokazov, E. Turbin et al. (+1 more)
A plug-and-play PhotonPix single-
photon detector with a logical signal output is developed for applications requiring ultimate timing precision down to 10 ps over a wide dynamic
photon flux range. The heart of the detector is an Exosens Fast Timing Microchannel Plate Photomultiplier (FT MCP-PMT) with a large 8 mm diameter sensitive area, which can accommodate various Hi-QE photocathodes optimized for high
quantum efficiency (QE) and low dark rates. The detector dead time, timing accuracy, and counting efficiency of the PhotonPix are measured and analyzed over a wide dynamic
photon flux range up to about 1 GHz in burst mode and up to 100~MHz in continuous operation mode.
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All authors D.A. Orlov, Y. Prokazov, E. Turbin, E.Kernen
Computational Physics · Cross-listed from cond-mat.mtrl-sci
A Unified Heterogeneous Implementation of Numerical Atomic Orbitals-Based Real-Time TDDFT within the ABACUS Package
Taoni Bao, Yuanbo Li, Zichao Deng et al. (+6 more)
We present a unified heterogeneous computing framework for real-time time-dependent density functional theory (RT-TDDFT) based on numerical atomic orbitals (NAOs), implemented in the ABACUS package. We introduce three co-designed abstraction layers, including unified data containers, unified linear
algebra operators, and unified grid integration interfaces. These layers collectively accelerate the two most demanding parts of NAO-based RT-TDDFT: explicit real-time wavefunction propagation and real-space grid operations such as
Hamiltonian construction and force evaluation under external fields. We validate the method by computing optical properties for systems ranging from finite molecules to periodic solids, showing excellent agreement with standard
benchmarks. Performance evaluations on bulk silicon demonstrate that a single GPU can achieve substantial wall-clock speedup over a fully utilized dual-socket CPU node. Furthermore, distributed multi-GPU strong-scaling tests confirm high parallel efficiency over tens of GPUs. This work establishes a high-performance, portable platform for large-scale first-principles simulations of ultrafast electron dynamics.
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All authors Taoni Bao, Yuanbo Li, Zichao Deng, Haotian Zhao, Denghui Lu, Yike Huang, Chao Lian, Lixin He, Mohan Chen
Plasma Physics
Geodesic extended modes in low magnetic shear tokamaks and stellarators
Richard Nies and Felix Parra
Theories of ion-scale microinstabilities in tokamaks and stellarators typically assume that the passing electrons respond adiabatically due to their fast propagation speed. However, when the
magnetic shear becomes sufficiently small, ion-scale modes can extend far along the
magnetic field and the non-adiabatic response of passing electrons becomes important. We derive a theory of extended modes at low
magnetic shear through a multiscale expansion of the gyrokinetic equation. The theory elucidates the physics of the geodesic extended mode, a new type of microinstability. The new mode couples the non-adiabatic physics of both electrons and ions, unlike extended modes at
magnetic shear of order unity. The theory is validated against gyrokinetic simulations and the parameter dependences of the new mode are studied.
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Atmospheric and Oceanic Physics · Cross-listed from nlin.PS
Diffraction of deep-water solitons
Filip Novkoski, Loïc Fache, Félicien Bonnefoy et al. (+6 more)
Solitons are localized nonlinear wave packets that propagate without spreading because nonlinearity balances dispersion. Their robustness is well understood in effectively one-dimensional systems, but introducing additional spatial dimensions is generally expected to destabilize them or destroy their coherent character. Here we experimentally investigate how deep-water
gravity-wave
solitons behave when a controlled transverse degree of freedom is introduced through diffraction. Using a large-scale water-wave facility, we generate solitonic wave packets whose transverse structure is imposed across a segmented wavemaker through either a sharp slit or a smooth Gaussian apodization. The resulting two-dimensional wave fields are measured with high spatial resolution. Diffraction reshapes the transverse profile of the wave packet while its longitudinal dynamics retain the characteristic features of a
soliton. Nonlinear spectral analysis confirms that the solitonic content is preserved along the direction of propagation, whereas the transverse
evolution follows the linear Fresnel laws of diffraction. These observations reveal an unexpected coexistence of nonlinear
soliton dynamics and classical wave diffraction.
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All authors Filip Novkoski, Loïc Fache, Félicien Bonnefoy, Guillaume Ducrozet, Jason Barckicke, François Copie, Pierre Suret, Eric Falcon, Stéphane Randoux
Plasma Physics
Wakefield amplification via coherent Resonant excitation with two copropagating laser pulses in homogeneous plasma
Abhishek Kumar Maurya, Dinkar Mishra, Bhupesh Kumar et al. (+4 more)
In the present study, wakefield amplification via coherent resonant excitation using two co propagating
laser pulses in a homogeneous
plasma is investigated. The proposed scheme is based on linearly polarized leading seed pulse followed by a trailing pulse with identical or controlled parameters, enabling phase synchronized energy transfer to the
plasma wave. By systematically varying the temporal pulse widths and inter pulse separation, conditions for resonant enhancement of the wakefield are established. Analytical modelling, supported by particle in
cell simulations, reveals that maximum amplification occurs when the pulse separation approaches a quarter of the
plasma wavelength, ensuring constructive interference of the
plasma oscillations driven by successive pulses. Under optimal conditions, the coherent resonant excitation leads to a significant enhancement of the wakefield amplitude, reaching up to three times of that produced by a single
laser pulse. The results demonstrate that precise control of pulse spacing and duration enables efficient energy coupling into
plasma waves, providing a robust pathway for enhanced wakefield generation in
laser plasma interaction regimes.
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All authors Abhishek Kumar Maurya, Dinkar Mishra, Bhupesh Kumar, Ramesh C Sharma, Lal C Mangal, Binoy K Das, Brijesh Kumar
Fluid Dynamics · Cross-listed from math.AP
Viscous evolution of a point vortex in a half-plane
Anne-Laure Dalibard and Thierry Gallay
As a model for
vortex-wall interactions, we consider the two-dimensional incompressible Navier–Stokes equations in the half-plane $R^2_+$ with no-slip boundary condition and point
vortices as initial data. We focus on the paradigmatic example of a single
vortex in an otherwise stagnant fluid, which is already quite challenging from a mathematical point of view. We prove that this system has a unique global solution for all values of the Reynolds number $|\Gamma|/\nu$, where $\Gamma$ is the circulation of the
vortex and $\nu$ the kinematic viscosity of the fluid. The solution we construct has finite energy for positive times and converges to zero in energy norm as $t \to +\infty$. Uniqueness holds under the assumption that the solution is close to a Lamb–Oseen
vortex for small times. To our knowledge, all previous results in domains with boundaries assume that the initial vorticity has small or zero atomic part. In our particular situation, we remove the smallness condition by decomposing the solution into a
vortex and a boundary layer term, so that we can apply the techniques developed in the whole plane $R^2$ to avoid the difficulties related to the large circulation of the
vortex.
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Fluid Dynamics
A Lego Block Approach to Flow in Complex Microfluidic Networks
Etienne Boulais and Richard D. Braatz
We present a new way to construct analytical solutions for flow in complex microfluidic channel networks, as well as planar disordered media. Using a combination of Schwarz-Christoffel maps and
segmentation techniques inspired by integrated
circuit analysis, we build a library of base building blocks which can be reassembled to model complex geometries, in the style of “Lego Blocks”. Our approach requires minimal numerical computation, and can then generate analytical solutions for any combination of inlet and outlet flow rates. Moreover, our method can tackle multiply connected domains which are usually difficult to model using typical conformal transform approaches. The solutions are developed for microfluidic Hele-Shaw
cell devices, but also apply to ideal flow and Darcy flow in complex geometries, or any other flow problem adequately modeled by Laplace's equation. We end by showing how the procedure can be used to model complex disordered media, fractal-like flow geometries, as well as problems of steady advection-
diffusion in microfluidic mixers.
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Optics
Nonlinear Electro-Optic Visible Photonic Circuits for Solid-State Quantum Defects
Yongchan Park, Yong Soo Lee, Hansol Kim et al. (+11 more)
Integrated visible photonic engines for solid-state
quantum defects provide a foundation for scalable
quantum networks. While miniaturization is advancing, active manipulation remains limited by the difficulty of achieving simultaneous milliwatt-scale visible light generation and high-contrast modulation. Despite extensive efforts, the concurrent chip-scale realization of nonlinear frequency conversion and fast temporal gating for high-fidelity
quantum control has remained elusive. Here, we demonstrate a monolithic thin-film lithium niobate (TFLN) platform integrating periodically poled frequency conversion with GHz-bandwidth electro-optic (EO) switching. The device delivers off-chip green-light power exceeding 1 mW with an extinction ratio (ER) of 42.2 dB, enabling coherent
spin control and time-resolved lifetime measurements of individual nitrogen-vacancy (NV) centers in diamond through nanosecond gating. System performance is validated through pulsed optically detected
magnetic resonance (ODMR), Rabi oscillations, and Ramsey interference, supported by time-tagged
photon counting with nanosecond resolution. By unifying sufficient nonlinear light generation with high-speed active manipulation, this platform establishes a scalable framework for the realization of high-rate
quantum communication nodes.
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All authors Yongchan Park, Yong Soo Lee, Hansol Kim, Jaepil Park, Junhyung Lee, Hye-yoon Jeon, Jinil Lee, Yong-gwon Kim, Yeeun Choi, Min-Kyo Seo, Dae-Hwan Ahn, Hojoong Jung, Dongyeon Daniel Kang, Hyounghan Kwon
Optics
Highly-efficient perturbative Raman shifting by engineering the nonlinear temporal response
Yi-Hao Chen, Wenchao Wang, Shaodong Hou et al. (+4 more)
Raman scattering underlies a broad range of spectroscopic and light-generation techniques, yet its conventional description, based on the Raman gain spectrum, accurately describes only long-pulse, steady-state dynamics. We employ a time-domain theoretical approach to account for spectrotemporal aspects of continuous frequency-shifting, which are not addressed by prior theories. In particular, molecules with strong Raman responses do not produce an efficient
soliton self-frequency shift in gas-filled hollow-core fibers. The time-domain analysis exposes temporal and spectral distortions from the Raman response that impact frequency-shifting detrimentally, and identifies how these distortions can be suppressed by reducing the Raman interaction to a perturbation on the electronic response. Experiments that employ gas mixtures with tunable Raman fractions of the nonlinear response demonstrate up to a four-fold increase in
quantum efficiency (from 20 to 80%) compared to the pure molecular gas, and unity-efficiency Raman shifting will be possible. The time-domain framework uncovers phenomena that are inaccessible through the frequency-domain treatment of Raman scattering, and it applies to Raman interactions in solids,
liquids, and gases across Raman temporal regimes.
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All authors Yi-Hao Chen, Wenchao Wang, Shaodong Hou, Jose Enrique Antonio-Lopez, Rodrigo Amezcua-Correa, Chris Xu, Frank Wise
Medical Physics
Hyperspectral imaging solutions for brain tissue metabolic and haemodynamic monitoring: an updated perspective
Luca Giannoni, Frédéric Lange and Ilias Tachtsidis
Since the publication of our review article Hyperspectral imaging solutions for
brain tissue metabolic and hemodynamic monitoring: past, current and future developments in 2018, the technological and applicational landscape of the use of hyperspectral imaging (HSI) in
brain sciences has evolved and transformed significantly. The number of studies and works where HSI has been deployed in its many forms to map and monitor the haemodynamic and metabolic states of cerebral tissues have grown exponentially, to such a point where an update on the cur-rent state of the art is timely, and we believe would be desirable for both long-term experts in the field, as well as for any new researcher approaching it for the first time. In this commentary, we provide a renewed perspective on the newest and latest developments in
brain haemodynamic and metabolic monitoring with HSI over the past eight years. Our hope is that even greater breakthroughs and broader, more numerous novel applications will come forward in the future for the technology, that may benefit from this new overview, as they did from the original one.
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Optics
Highly-efficient, narrow-linewidth Brillouin microlasers implemented in compact thin-film lithium niobate microresonators
Yingnuo Qiu, Chuntao Li, Renhong Gao et al. (+5 more)
Stimulated Brillouin microlasers offer chip-scale light sources with high spectral purity and low phase noise–key attributes for applications spanning precision metrology,
quantum technologies, and coherent information processing. However, simultaneously bringing both pump and scattered waves into resonance often compromises
photon confinement or modal volume, resulting in limited conversion efficiency and elevated thresholds. In this work, a novel approach is proposed to generate Brillouin microlasers with high efficiency, low threshold, and narrow linewidth, by combining a cross-polarized stimulated Brillouin scattering scheme with intentional Stokes mode splitting to compensate for mode detuning. Triple-resonance and phase-matching conditions are simultaneously achieved in a 114-um-diameter thin-film lithium niobate (TFLN) microresonator, enabling precise
alignment with both the ~10-GHz Brillouin shift and the ~100-MHz narrow gain bandwidth. The resulting Brillouin microlaser achieves a narrow intrinsic linewidth of 2.88 Hz, a short-term integral linewidth of 185 Hz, an on-chip conversion efficiency of 57.92%, and a pump threshold as low as 1.03 mW. Both the conversion efficiency and the lasing threshold represent record-high performance for the TFLN platform to date.
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All authors Yingnuo Qiu, Chuntao Li, Renhong Gao, Xiaochao Luo, Lingling Qiao, Min Wang, Jintian Lin, Ya Cheng
Medical Physics
Comprehensive Dosimetric Verification and Positional Sensitivity Analysis in Brachytherapy: A Unified ESAPI Tool for HDR and LDR Treatments
J. A. Valgoma
This study presents the development and validation of an independent software tool based on the Varian Eclipse Scripting API (ESAPI) for multi-modal brachytherapy Quality Assurance (QA). The tool addresses GEC-ESTRO HDR protocols and LDR positional uncertainty analysis. Engineered in C#, the application interfaces with BrachyVision, Vitesse, and Variseed, enabling independent TG-43 dose calculations – comparing point and line source models – integrated with EQD2-based radiobiological summation. In HDR cervical cancer, the tool successfully automated EMBRACE II protocol reporting, streamlining clinical workflows by combining dosimetric QA with predictive and prospective planning. For LDR prostate treatments, a
stochastic simulation module quantified the impact of systematic (rigid-body) versus random seed displacements on target coverage ($D_{90\%}$) and Organs at Risk (OAR) safety ($D_{0.1cc}$). Sensitivity analysis in LDR prostate implants was benchmarked using two clinical cases (prostate volumes 31 cc and 71.3 cc). LDR simulations revealed that systematic displacements ($\pm$ 2 mm) yielded significantly higher dosimetric deviations than
stochastic movements. In the 31 cc case, systematic shifts resulted in a rectal ($D_{0.1cc}$) standard deviation (SD) of 24.3 Gy, whereas random displacements reduced this to 12.4 Gy. In the 71.3 cc case, random displacements resulted in a rectal $D_{0.1cc}$ SD of 7.6 Gy, confirming that smaller volumes exhibit heightened sensitivity to errors. Technical analysis demonstrated that the point source model overestimated bladder $D_{10\%}$ by 8% relative to the line source model. Our findings confirm that systematic rigid-body shifts represent a greater clinical risk for OAR toxicity than
stochastic migration. Integrating predictive sensitivity analysis into the clinical workflow significantly enhances patient safety through robust plan verification.
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Computational Physics
SPINONet: Scalable Spiking Physics-informed Neural Operator for Computational Mechanics Applications
Shailesh Garg, Luis Mandl, Somdatta Goswami et al. (+1 more)
Energy efficiency remains a critical challenge in deploying physics-informed operator learning models for computational mechanics and scientific computing, particularly in power-constrained settings such as edge and embedded devices, where repeated operator evaluations in dense networks incur substantial computational and energy costs. To address this challenge, we introduce the Separable Physics-informed Neuroscience-inspired Operator Network (SPINONet), a neuroscience-inspired framework that reduces redundant computation across repeated evaluations while remaining compatible with physics-informed training. SPINONet incorporates regression-friendly neuroscience-inspired spiking
neurons through an architecture-aware design that enables sparse, event-driven computation, improving energy efficiency while preserving the continuous, coordinate-differentiable pathways required for computing spatio-temporal derivatives. We evaluate SPINONet on a range of partial differential equations representative of computational mechanics problems, with spatial, temporal, and parametric dependencies in both time-dependent and steady-state settings, and demonstrate predictive performance comparable to conventional physics-informed operator learning approaches despite the induced sparse communication. In addition, limited data supervision in a hybrid setup is shown to improve performance in challenging regimes where purely physics-informed training may converge to spurious solutions. Finally, we provide an analytical discussion linking architectural components and design choices of SPINONet to reductions in computational load and energy consumption.
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All authors Shailesh Garg, Luis Mandl, Somdatta Goswami, Souvik Chakraborty
Fluid Dynamics
Combined thermographic measurement and heat-flux compensation methods for aerodynamic heating evaluation in hypersonic flight
Kento Inokuma, Aiko Yakeno, Yoshiyuki Watanabe et al. (+1 more)
Novel thermographic measurement and heat-flux compensation methods combined for evaluating aerodynamic heating in hypersonic flight were developed using high-speed thermography. A hypersonic spherical projectile with a diameter of 8 mm was launched at approximately Mach 5 in the test section of a ballistic range. Shadowgraph imaging was conducted to visualize the flight trajectory and the shock layer. Thermographic measurement was performed using a high-speed infrared (IR) camera to obtain the surface temperature distribution of the projectile. The temperature distribution on the spherical surface was reconstructed from the thermographic data, by considering the photoresponse time of the photodetector of the IR camera and the
geometric characteristics of the projectile trajectory. Furthermore, to validate the shock-layer geometry and aerodynamic heating characteristics, a computational fluid dynamics (CFD) simulation was also performed. The shadowgraph results showed that a detached shock wave and a shock layer were formed in front of the projectile, consistent with the CFD result. From the thermographic result, it was found that the maximum surface temperature rise during the flight was 24.4 K above the ambient temperature and it decreased with increasing distance from the stagnation point. The Stanton number distribution was estimated from the reconstructed surface temperature by assuming a one-dimensional transient heat conduction caused during the flight. The stagnation Stanton number was calculated to be 0.00366, which was also consistent with both the CFD result and a previously reported empirical correlation.
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All authors Kento Inokuma, Aiko Yakeno, Yoshiyuki Watanabe, Kiyonobu Ohtani
Computational Physics
Utilising a learned forward operator in the inverse problem of photoacoustic tomography
Karoliina Puronhaara, Teemu Sahlström, Andreas Hauptmann et al. (+1 more)
We study the use of a learned forward operator in the inverse problem of photoacoustic
tomography. The
Fourier neural operator to approximate the photoacoustic wave propagation is used. Further, the inverse problem is solved using a gradient-based approach with automatic differentiation. The methodology is evaluated using numerical simulations, and the results are compared to a conventional approach, where the forward operator is approximated using the pseudospectral $k$-space method. The results show that the learned forward operator can be used to approximate the photoacoustic wave propagation with good accuracy, and that it can be utilised as a computationally efficient forward operator in solving the inverse problem of photoacoustic
tomography.
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All authors Karoliina Puronhaara, Teemu Sahlström, Andreas Hauptmann, Tanja Tarvainen
Optics
Quantitative Dynamic Phase Mapping via Single-Arm Field-Correlation Ghost Imaging
Chaoran Wang, Jinquan Qi, Shuang Liu et al. (+2 more)
We demonstrate a single-arm optical platform for phase-
retrieval-free, quantitative dynamic phase mapping of continuous transparent media via field-correlation ghost imaging. By modeling the medium as a dynamic pure-phase object, we spatially encode and compress its two-dimensional (2D) complex transmittance into a single bucket detector. Balanced heterodyne detection downconverts the optical frequencies for direct digitization. Crucially, by mapping spatial information into the temporal domain, this single-pixel architecture exploits high-speed digitization to continuously resolve 2D phase dynamics, effectively bypassing the frame-rate bottlenecks of traditional array sensors. Coupled with intermediate-frequency spectral analysis, this establishes a direct linear mapping from the recorded signal to the physical phase. The complex amplitude is thus deterministically extracted via field-correlation, enabling the spatial reconstruction of 2D acoustic pressure distributions using a pseudo-inverse
algorithm. Experimental validations in an acoustic levitator confirm that the optically extracted acoustic wavelengths strictly match theoretical dispersion models, exhibiting a robust linear correlation between the retrieved phase shift and local sound pressure levels. This deterministic methodology provides a real-time-capable metrological tool for characterizing rapidly evolving phenomena, including transient aeroacoustic flows, shockwaves, and microfluidic biological dynamics.
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All authors Chaoran Wang, Jinquan Qi, Shuang Liu, Xingzhao Jiang, Shensheng Han
Optics
Breaking the Limitations of Temporal Modulation via Mixed Continuity Conditions
Yongge Wang, Jingfeng Yao, Ying Wang et al. (+2 more)
The conventional description of time-varying media assumes that electromagnetic fields evolve according to fixed continuity conditions during parameter jumps. Here we reveal that these conditions are not physical constraints but tunable design degrees of freedom. By developing a unified framework that treats continuity rules as engineerable parameters, we expand the scope of time-varying metamaterials and enable wave phenomena previously considered impossible. For instance, non-resonant, reflectionless wave amplification without momentum bandgaps, and reversible conversion between propagating waves and static fields for optical
memory, etc. This work opens a new dimension for controlling light-matter interactions.
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All authors Yongge Wang, Jingfeng Yao, Ying Wang, Chengxun Yuan, Zhongxiang Zhou
Optics
Theoretical proof of the constancy of the speed of light in a vacuum
D.N. Makarov
The constancy of the speed of light (the maximum velocity of interaction) is the second postulate of Albert Einstein's special theory of relativity. Currently, there is no correct theoretical proof of this constancy in all inertial frames of reference. This paper presents such a proof, demonstrating that
quantum mechanics (
quantum field theory) can only be formulated under the condition of the constancy of the speed of light in a
vacuum. It has been established that this constancy is determined by the minimum energy of the particles. When this minimum is reached, two identical solutions emerge – one with positive and one with negative energies. Thus, within the framework of classical physics, the existence of particles and antiparticles is demonstrated. It is shown that matter dominates over antimatter.
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Chemical Physics
TERS-ABNet: A Deep Learning Approach for Automated Single-Molecule Structure Reconstruction with Atomic Precision from TERS Mapping
Jie Cui, Yao Zhang, Yang Zhang et al. (+2 more)
Determining the chemical structure for a single molecule on surface from spectroscopic data represents a challenging high-dimensional inverse problem. Tip-enhanced Raman spectroscopy (TERS) enables chemically specific imaging of single molecules with sub-nanometer spatial resolution, yet reconstructing complete molecular structures from TERS maps remains difficult owing to the ambiguous vibrational signatures and reliance on expert interpretation. Here, we introduce TERS-ABNet, a deep-learning framework that formulates single-molecule structure determination from spectroscopic images as an image-to-graph inference task. Using a "two-track" architecture, the model jointly predicts probabilistic atom and bond maps, enabling direct construction of explicit atom-bond graphs without relying on predefined chemical rules. Trained on simulated
datasets, TERS-ABNet achieves about 94% atom-type classification accuracy (with a mean coordinate error of about 0.23 Å), enabling to reliably recovering molecular connectivity and fully reconstruct single-molecule structure from its TERS maps. The framework generalizes across varying spatial resolutions and structural complexity through transfer learning, and successfully reconstructs the atomic structure of a single porphyrin molecule from experimental TERS data. This work establishes a general deep-learning strategy for inferring explicit atom-bond graph representations from high-dimensional spectroscopic imaging data, providing a new pathway towards automated molecular structure determination in nanoscale characterization.
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All authors Jie Cui, Yao Zhang, Yang Zhang, Yi Luo, Zhen-Chao Dong
Optics
PRISM: Breaking the O(n) Memory Wall in Long-Context LLM Inference via O(1) Photonic Block Selection
Hyoseok Park and Yeonsang Park
Long-context LLM inference is bottlenecked not by compute but by the O(n)
memory bandwidth cost of scanning the KV cache at every decode step – a wall that no amount of arithmetic scaling can break. Recent photonic accelerators have demonstrated impressive throughput for dense
attention computation; however, these approaches inherit the same O(n)
memory scaling as electronic
attention when applied to long contexts. We observe that the real leverage point is the coarse block-selection step: a
memory-bound similarity search that determines which KV blocks to fetch. We identify, for the first time, that this task is structurally matched to the photonic broadcast-and-weight paradigm – the query fans out to all candidates via passive splitting, signatures are quasi-static (matching electro-optic MRR programming), and only rank order matters (relaxing precision to 4-6 bits). Crucially, the photonic advantage grows with context length: as N increases, the electronic scan cost rises linearly while the photonic evaluation remains O(1). We instantiate this insight in PRISM (Photonic Ranking via Inner-product Similarity with Microring weights), a thin-film lithium niobate (TFLN) similarity engine. Hardware-impaired needle-in-a-haystack evaluation on Qwen2.5-7B confirms 100% accuracy from 4K through 64K
tokens at k=32, with 16x traffic reduction at 64K context. PRISM achieves a four-order-of-magnitude energy advantage over GPU baselines at practical context lengths (n >= 4K).
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Biological Physics
Tuning microswimmer motility by liposome encapsulation: swimming and cargo transport of Chlamydomonas-encapsulating liposome
Koichiro Akiyama, Sota Hamaguchi, Hiromasa Shiraiwa et al. (+4 more)
Inspired by biology's use of vesicles for targeted transport, many studies have propelled liposomes with active matter, creating synthetic systems that can be viewed as microscale biohybrid
robots. Nevertheless, the underlying motility mechanisms from a hydrodynamic perspective are often unresolved, and reliable velocity control remains challenging. Here we present a chlamylipo formed by encapsulating the motile alga Chlamydomonas reinhardtii within a
giant liposome. We quantify how the characters of swimming change under controlled perturbations and, from a fluid-mechanical perspective, derive a deformation-velocity expression that incorporates liposome radius, beating frequency, and membrane protrusion. We further show that motility can be reversibly switched by incorporating light-responsive lipids, with the liposome acting as a "clutch" that modulates membrane-coupled propulsion. Thus, liposome encapsulation can function not only as a cargo compartment but also as a tunable motility regulator, enabling speed adjustment and reversible transitions between motile and non-motile states.
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All authors Koichiro Akiyama, Sota Hamaguchi, Hiromasa Shiraiwa, Shunsuke Shiomi, Tomoyuki Kaneko, Masahito Hayashi, Daiki Matsunaga
Physics and Society
Emergent Detailed Balance in Human Mobility under Temporal Coarse-Graining
Lei Dong
A fundamental question in nonequilibrium statistical physics is whether effective
equilibrium behavior can emerge at coarse-grained scales in strongly driven systems. Here, we investigate this question in the context of human mobility by analyzing five years of intercity flow data covering millions of travelers. While short-term flows are highly asymmetric, temporal coarse-graining reveals that over half of all city pairs converge toward effective flow balance, with normalized directional imbalance decaying as a power law. The remaining pairs either exhibit persistent drift-dominated currents or a crossover between these two extremes. A
stochastic model decomposing mobility into directional drift and correlated fluctuations quantitatively captures the coexistence of all three regimes. Directly measured variance scaling of the fluctuation process confirms near-diffusive behavior with regime-dependent deviations. These results demonstrate that large-scale mobility networks exhibit a scale-dependent transition from broken to restored flow
symmetry, with direct implications for modeling transport and spreading dynamics.
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Fluid Dynamics · Cross-listed from math-ph
A linear-algebraic formulation of dimensional analysis with constraints
Umpei Miyamoto
Dimensional analysis, especially Buckingham's $\pi$
theorem, reduces the number of variables by rewriting a relation in terms of dimensionless quantities. When variables are tied by definitions, constitutive laws, or other constraints, however, eliminating variables in advance can be awkward. We formulate dimensional analysis with constraints as linear
algebra in logarithmic variables. Dimensional transformations and constraints are represented by subspaces, the effective number of independent dimensionless quantities is characterized by their intersection, and a
matrix representation yields a systematic redundancy elimination procedure. Examples from falling motion, drag force, and stock-
market indicators illustrate the scope and limitations of the method.
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Optics · Cross-listed from cs.IT
Ultrafast microwave sensing and automatic recognition of dynamic objects in open world using programmable surface plasmonic neural networks
Qian Ma, Ze Gu, Zi Rui Feng et al. (+6 more)
The
evolution toward next-generation intelligent sensing requires microwave systems to move beyond static detection and achieve high-speed and adaptive perception of dynamic scenes. However, the existing microwave sensing systems have bottlenecks owing to their sequential digital processing chain, limiting the refresh rates to hundreds of hertz, while the existing integrated microwave processors are lack of programmable and scalable capabilities for robust and open-world deployment. To break the bottlenecks, here we report a programmable surface plasmonic neural network (P-SPNN) that enables real-time microwave sensing and automatic recognition of dynamic objects in open-world environment. With a perception latency of 25 ns and a refresh rate exceeding 10 kHz, the P-SPNN system operates more than two orders of magnitude faster than the conventional millimeter-wave sensors, while achieving an energy efficiency of 17 TOPS per W. With 288 programmable phase-modulated
neurons, we demonstrate real time and robust classification of persons and cars with 91-97% accuracy in the open road scenarios. By further integrating beam-scanning function, P-SPNN enables multi-dimensional spatial temporal frequency sensing without the digital preprocessing. These results establish P-SPNN as a programmable, scalable, and low-power platform for high-speed perception tasks in realistic world, with broad implications for autonomous driving, intelligent sensing, and next-generation artificial intelligence hardware.
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All authors Qian Ma, Ze Gu, Zi Rui Feng, Qian Wen Wu, Yu Ming Ning, Zhi Qiao Han, Rui Si Li, Xinxin Gao, Tie Jun Cui
Physics and Society
Delineating hierarchical activity space from high-resolution urban mobility flows
Zhicheng Deng, Zhaoya Gong, Jean-Claude Thill et al. (+1 more)
Current studies on activity space are limited by the conceptualization of absolute physical space that fails to consider the heterogeneity of relational spaces reconstructed from spatial interactions of human movements between locations and falls short in incorporating the inherent hierarchical property of human mobility. Consequently, these approaches cannot faithfully reflect how people interact with urban spaces through travels. From the lens of relational space, this study proposes the new Hierarchical Activity Region Model (HARM) to derive the space and hierarchical properties of activity spaces perceived by various urban groups. We demonstrate the enhanced validity of our model on travel behavior in Manhattan, New York City, before, during, and after Hurricane Sandy on the basis of taxi data. Empirical results show that intra-urban travel retains clear hierarchical organization, even under disruption of a major weather event. Yet, travel undergoes a compression effect in travel hierarchies, characterized by fewer hierarchical levels and enlarged characteristic scales, followed by a rebound. Clustering the derived hierarchies reveals pronounced heterogeneity that stems from differences in population profiles; some groups sustain deeper structures or recover quickly, while others experience a persistent loss of levels. This study provides valuable insights into the functional hierarchies of urban mobility, which could inform more sustainable, resilient and equitable urban planning. The proposed methodological framework is generic for studying human mobility in broader contexts.
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All authors Zhicheng Deng, Zhaoya Gong, Jean-Claude Thill, Elizabeth C. Delmelle
Optics
Programmable Electromagnetic Space via Metasurface Clusters
Min Li, Lixiang Meng, Gongxu Dong et al. (+7 more)
The rapid
evolution of next-generation communications and the Internet of Things (IoT) has catalyzed an urgent demand for governing expansive spatial environments as functional electromagnetic (EM) entities. However, deterministically programming such open EM spaces remains a formidable challenge, as current methodologies are largely confined to localized interfaces that lack the collective coordination required to orchestrate unbounded environments. Here, we introduce a general framework for the deterministic programming of EM space via cooperative metasurface clusters, achieved by mapping volumetric field interference landscapes onto a virtual nodal network. By representing excitations and meta-atoms as fully interconnected nodes, we transform intricate non-local interactions into tractable nodal states, enabling the precise quantitative synthesis of spatial scattering. This framework bridges local meta-atoms with global EM environment to program space as a functional entity, as demonstrated by a deeply coupled meta-emitter for programmable collective radiation and metasurface clusters that sculpt angle-resolved illusion spaces. By transitioning from individual components to cooperative multi-body assemblies, our work provides a scalable foundation for next-generation wireless networks, wave-based analog computing, and ambient intelligence, where space itself becomes a coherent functional and reconfigurable entity capable of holistic information management.
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All authors Min Li, Lixiang Meng, Gongxu Dong, Xiaobo Zhou, Lu Song, Puti Yan, Dashuang Liao, Chao Qian, Zuojia Wang, Hongsheng Chen
Optics · Cross-listed from cs.RO
A Framework for Closed-Loop Robotic Assembly, Alignment and Self-Recovery of Precision Optical Systems
Seou Choi, Sachin Vaidya, Caio Silva et al. (+4 more)
Robotic automation has transformed scientific workflows in domains such as chemistry and materials science, yet free-space optics, which is a high precision domain, remains largely manual. Optical systems impose strict spatial and angular tolerances, and their performance is governed by tightly coupled physical parameters, making generalizable automation particularly challenging. In this work, we present a robotics framework for the autonomous construction,
alignment, and maintenance of precision optical systems. Our approach integrates hierarchical computer
vision systems, optimization routines, and custom-built tools to achieve this functionality. As a representative demonstration, we perform the fully autonomous construction of a tabletop
laser cavity from randomly distributed components. The system performs several tasks such as
laser beam centering, spatial
alignment of multiple beams, resonator
alignment,
laser mode selection, and self-recovery from induced misalignment and disturbances. By achieving closed-loop autonomy for highly sensitive optical systems, this work establishes a foundation for autonomous optical experiments for applications across technical domains.
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All authors Seou Choi, Sachin Vaidya, Caio Silva, Shiekh Zia Uddin, Sajib Biswas Shuvo, Shrish Choudhary, Marin Soljačić
Optics
Freeform Spectrally Stable Topological Photonic Vortex Resonators
Yuma Kawaguchi, Daria Smirnova, Filipp Komissarenko et al. (+6 more)
Topological concepts have been at the forefront of materials research in recent years, driving a revolution in our understanding of the response of
quantum materials and enabling new ways to manipulate light and sound in topological metamaterials. Topological defects and topological boundaries of different dimensions have driven a paradigm shift in photonics, where topological photonic
crystals and metamaterials can be engineered to create one-way flow of energy robust to defects or to control such flows with synthetic degrees of freedom along topological domain walls. More recently, topological point singularities encoded into photonic structures have been shown to enable confinement of optical modes with the topologically nontrivial nature of the cavity imprinted into the vorticity of optical far fields. Here we demonstrate that the two latter concepts - domain wall and point singularities - can be unified into an even more powerful tool to enable arbitrarily shaped resonant cavities of any dimension supporting spectrally stable zero-energy modes. We experimentally confirm that such modes, whose existence is guaranteed by topological principles, allow an unprecedented degree of control over the optical field, which appears to have no phase modulation across space, can have any desirable radiation pattern, and enables spectral stability regardless of shape or length.
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All authors Yuma Kawaguchi, Daria Smirnova, Filipp Komissarenko, Daria Kafeeva, Svetlana Kiriushechkina, Jeffery Allen, Monica Allen, Andrea Alù, Alexander Khanikaev
Fluid Dynamics · Cross-listed from math.NA
Local linear stability of dual-pairing summation-by-parts methods for nonlinear conservation laws
Dougal Stewart and Kenneth Duru
A recent study by Gassner et al. [J. Sci. Comput. 90:79 (2022)] demonstrates that local energy stability–that is, ensuring the asymptotic numerical growth rate does not exceed the continuous growth rate–is crucial for achieving accurate numerical simulations of nonlinear conservation laws. While nonlinear
entropy stability is necessary for numerical stability (i.e., ensuring the boundedness of nonlinear numerical solutions), local energy stability is essential to prevent unresolved high-frequency wave modes from dominating the simulation. Currently, it remains an open question whether high-order numerical methods for nonlinear conservation laws can be simultaneously
entropy-stable and locally energy-stable. In this work, we examine the local energy-stability properties of recently developed
entropy-stable, high-order accurate dual-pairing (DP) SBP methods, as introduced by Duru et al. [arXiv: 2411.06629], for nonlinear conservation laws. Our analysis indicates that the
entropy-stable volume upwind filter inherent in these methods can ensure local energy stability. This approach offers a novel numerical strategy for designing reliable high-order methods for nonlinear conservation laws that are provably
entropy-stable and locally energy-stable. The theoretical findings are supported by numerical experiments involving the inviscid Burgers equation and nonlinear shallow water equations, in 1D and 2D. Furthermore, we present accurate numerical simulations of 2D barotropic shear instability, with fully developed
turbulence, demonstrating the efficiency of the DP SBP method in resolving turbulent scales.
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Optics
Compressive single-pixel imaging via a wavelength-multiplexed spatially incoherent diffractive optical processor
Xiao Wang, Yiyang Wu, Yuntian Wang et al. (+8 more)
Despite offering high sensitivity, a high signal-to-noise ratio, and a broad spectral range, single-pixel imaging (SPI) is limited by low measurement efficiency and long data-acquisition times. To address this, we propose a wavelength-multiplexed, spatially incoherent diffractive optical processor combined with a compact/shallow digital artificial neural network (ANN) to implement compressive SPI. Specifically, we model the bucket detection process in conventional SPI as a linear intensity transformation with spatially and spectrally varying point-spread functions. This transformation
matrix is treated as a learnable parameter and jointly optimized with a shallow digital ANN composed of 2 hidden nonlinear layers. The wavelength-multiplexed diffractive processor is then configured via data-free optimization to approximate this pre-trained transformation
matrix; after this optimization, the diffractive processor remains static/fixed. Upon multi-wavelength illumination and diffractive modulation, the target spatial information of the input object is spectrally encoded. A single-pixel detector captures the output spectral power at each illumination band, which is then rapidly decoded by the jointly trained digital ANN to reconstruct the input image. In addition to our numerical analyses demonstrating the feasibility of this approach, we experimentally validated its proof-of-concept using an array of light-emitting diodes (LEDs). Overall, this work demonstrates a computational imaging framework for compressive SPI that can be useful in applications such as biomedical imaging, autonomous devices, and remote sensing.
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All authors Xiao Wang, Yiyang Wu, Yuntian Wang, Md Sadman Sakib Rahman, Paloma Casteleiro Costa, Guangdong Ma, Shiqi Chen, Yuzhu Li, Jingxi Li, Cagatay Isil, Aydogan Ozcan