Optics
Volumetric Optical Scattering Neural Networks
Xuhao Luo, Qiang Song, Weiwei Cai et al. (+7 more)
Optical neural networks rely on planar photonic
circuits or spatially separated diffractive planes, limiting volumetric integration and requiring precise
alignment. Here we propose a volumetric optical scattering neural network (OSNN) comprising densely packed refractive-index
neurons with weak contrast $\Delta n = 0.006$. Direction-dependent first-order Born scattering provides local coupling, while ordered propagation accumulates these weak updates into global task-specific transformations. Fabrication-aware training and two-
photon nanolithography produced a sub-$4 \times 10^{-4}$ mm$^3$ device containing 376,320
neurons at $1.0 \times 10^9$/mm$^3$ in a continuously written, intrinsically registered volume. Experimentally, a classifier performed class-selective energy routing with 95.8% blind-test accuracy on MNIST. The calculated passive optical transit time is below 1 ps. A separately optimized imager provided fourfold full-field spatial-sampling compression, resolved 1-$\mu$m features and enabled cross-domain transfer. An OSNN co-designed for multiple tasks encoded single-
cell fluorescence-derived images into measured output maps, which were pooled into a 16-dimensional representation supporting organelle classification, morphology reconstruction, doublet detection and morphology regression, with all reported metrics exceeding 0.92. Volumetric weak scattering thus establishes an ultracompact, intrinsically registered optical computing architecture, opening a new route to scalable machine
vision and biomedical analysis.
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All authors Xuhao Luo, Qiang Song, Weiwei Cai, Lei Chen, Enbo Yang, Hao Wang, Zhipei Sun, Yueqiang Hu, Joel K.W. Yang, Huigao Duan
Chemical Physics · Cross-listed from cond-mat.mtrl-sci
Helium Bubbles in Liquid Lead Lithium Solutions: Pressure Inhomogeneities at Interfaces and Non Ideal Mixture Effects
Edgar Alvarez-Galera, Jordi Marti and Lluis Batet
The extremely low solubility of helium in
liquid metals may lead to rapid supersaturation, promoting spontaneous formation of helium bubbles by nucleation. Once nucleated, the stability of these bubbles is governed by the properties of the helium
liquid metal interface. In particular, interfacial tension between the immiscible phases controls bubble interactions and induces local pressure inhomogeneities. This work is motivated by the need of a better understanding of helium bubble formation in
liquid Pb Li
alloys, which are of particular relevance for the design of breeding blankets in the future
nuclear fusion reactors. We employ classical molecular dynamics simulations to investigate helium segregation in a range of lead lithium systems, including the limiting cases of pure lead and pure lithium. Changes in local pressure are evaluated from direct mechanical calculations, enabling the characterization of interfacial properties. Interfacial tension and radius of the bubble are subsequently determined across multiple thermodynamic conditions, spanning temperatures starting near the melting points of the constituent metals up to 1021 K. The impact of
curvature and composition of the
alloy on the interfacial behaviour are also investigated.
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Instrumentation and Detectors
Sumaira Ikram, Maxime Lagrange, Donya Ahmadi et al. (+17 more)
We report on a feasibility study conducted at the ELBA facility at ELI Beamlines in 2025 to investigate the possible production of
muons from high-energy electron beams generated by extended
laser-
plasma interactions in optically generated
plasma waveguides. Our team operated a portable, autonomous, and compact
telescope based on Resistive Plate Chamber (RPC) detectors, positioned to detect high-penetration charged particles originating from the beam dump. The campaign demonstrated that RPC detectors can operate reliably and safely in the ELBA environment, even under intense radiation and electromagnetic conditions. The collected
datasets, though statistically limited and affected by lack of beam control, allow detailed characterization of the background and validated the detectors' stability and tracking performance. These results confirm the feasibility of the approach and provide the foundation for a dedicated future run under optimized beam conditions, where
muon detection sensitivity will be substantially improved.
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All authors Sumaira Ikram, Maxime Lagrange, Donya Ahmadi, Uddhab Chaulagain, Anna Cimmino, Eduardo Cortina Gil, Pavel Demin, Gabriele M. Grittani, Sebastian Lorenz, Michal Nevrkla, Ela Rockafellow, Jaron E. Shrock, Jiri Sisma, Ari J. Sloss, Michael Tytgat, Roberto Versaci, Filip Vitha, Illia Zymak, Howard M. Milchberg, Andrea Giammanco
Optics · Cross-listed from cond-mat.mes-hall
Observation of end-to-end pumping in a quasiperiodic Fibonacci-type photonic chain
Arnob Kumar Ghosh, Ang Chen, Ashraf El Hassan et al. (+3 more)
End-to-end pumps utilizing edge-localized states offer a promising route to operate as connecting buses, supplying efficient and robust connectivity between non-neighboring elements in a network. Here, we investigate a finite quasiperiodic Fibonacci-type photonic chain and demonstrate its ability for end-to-end pumping, with only small and simple changes to the system. First, we use a tight-binding formalism to numerically show that a localized pumping state can be transferred between opposite ends of the system, with only a small structural change to the chain. Then, we experimentally implement this end-to-end pump in an array of coupled optical waveguides, where light propagation is effectively described by the tight-binding model under the paraxial approximation, enabling direct correspondence between theory and experiment. We numerically simulate and experimentally demonstrate pumping by injecting light into a single waveguide at one end of the setup, which activates a localized pumping state. As the light propagates along the wave guide array, it is also pumped to the other end. We further show that pumping remains robust against structural deformation, such as controlled defects in the waveguide array. Our results establish that quasiperiodic Fibonacci-type photonic
lattices are a robust and experimentally viable platform for disorder-resilient state transfer.
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All authors Arnob Kumar Ghosh, Ang Chen, Ashraf El Hassan, Patric Holmvall, Mohamed Bourennane, Annica M. Black-Schaffer
Biological Physics · Cross-listed from q-bio.CB
3D mechano-geometric multicellular model of apical stem cell-driven plant morphogenesis
Naoya Kamamoto and Koichi Fujimoto
The orientation of
cell division is a major determinant of three-dimensional plant morphogenesis. Whether and how a simple division orientation rule explains the establishment of symmetric body plans is a fundamental question. Testing such hypotheses is facilitated by a modeling framework that combines realistic three-dimensional
cell mechanics, irreversible
cell-wall growth, and a deformable tissue geometry. We recently introduced such a framework, a 3D mechano-
geometric multicellular model of apical stem
cell-driven morphogenesis. Here we document how the model is built from physiological and computational perspectives. We describe the triangulated thin-shell representation of
cells, the treatment of turgor pressure,
cell-wall elasticity and strain-driven wall growth, the
cell-division
algorithm together with its two pluggable division-rule implementations, and the remeshing operations that keep the triangulation well-conditioned as
cells grow, divide, and deform. The aim of this paper is to make the present model accessible and customizable to experimental plant biologists.
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Accelerator Physics
Longitudinal Localized Kick Driven Fast Extraction Method and Rapid Cycling Synchrotron Design for 3D PBS Proton FLASH Delivery
Yang Xiong, Hongjuan Yao and Shuxin Zheng
This paper presents the design of a rapid cycling synchrotron (RCS) featuring a longitudinal localized kick driven fast extraction system for three-dimensional (3D) pencil beam scanning (PBS)
proton FLASH delivery. The extraction method is designed to accommodate a novel scanning scheme that addresses the stringent requirement for substantially shorter delivery time compared to current solutions, where the scanning layer is parallel to the
proton beam direction. In this method, the kicker pulse waveform is applied selectively to specific longitudinal segments of the
proton bunch. For each scanning spot, the functional region of the kicker along the longitudinal direction is dynamically adjusted based on real-time beam longitudinal line density measured by a beam current monitor. The corresponding region-determination
algorithm is provided. We analyze the spot dose accuracy and the beam loss at the septum, indentifying increased particle longitudinal line density will reduce spot dose accuracy and increase beam loss. A total number of particles of $2\times10^{10}$ can satisfy the requirements of spot dose accuracy and the beam loss due to the septum is less than 1%. The extraction system comprises a stripline kicker, an electric septum (ESe), and a
magnetic septum (MSe), imposing specific requirements on the RCS
lattice design. The RCS is carefully designed to meet these constraints, and the parameters of the extraction elements are detailed. By integrating a novel scanning scheme with a specially designed RCS and fast extraction method, this work demonstrates the feasibility of achieving 3D PBS
proton FLASH delivery.
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Chemical Physics
Rotational energy levels in the ground vibrational state of methane with kHz-level accuracy from comb-referenced double-resonance and Lamb-dip spectroscopies
Vinicius Silva de Oliveira, Isak Silander, Hiroyuki Sasada et al. (+4 more)
Methane is a key spherical-top molecule, yet restrictive selection rules for one-
photon transitions have prevented determination of its ground state (GS) energies with state-of-the-art kHz-level accuracy. We report the GS rotational energy level differences with kHz-level accuracy from two frequency-comb-referenced sub-Doppler methods: optical-optical double-resonance spectroscopy in the ${\Lambda}$-type configuration, and Lamb-dip spectroscopy of allowed and forbidden transitions. A
Hamiltonian fit to the data yields GS term values with rotational numbers up to $\it{J}$ = 12 with kHz level accuracy.
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All authors Vinicius Silva de Oliveira, Isak Silander, Hiroyuki Sasada, Sho Okubo, Hajima Inaba, Kevin K. Lehmann, Aleksandra Foltynowicz
Applied Physics
Identifiability Limits in Ultrasonic Microstructure Characterisation: A Canonical and Stochastic Framework
Wei Yi Yeoh
Ultrasound for microstructure characterisation is increasingly studied and is often assessed through inversion performance. However, the framework is fundamentally constrained by the information content available in the measured response. Hence, this work examines identifiability directly by analysing the geometry of the forward operator in both a canonical pulse-echo model and a
stochastic surrogate microstructure. For the canonical model, a closed-form sensitivity analysis reveals information limits arising from parameter coupling, dimensional restriction, and interface-driven saturation. For the surrogate microstructures represented by Gaussian random fields, the forward map from correlation length $D$ and texture-coherence parameter $T$ to the attenuation and velocity observables remains structurally full rank. However, the sensitivity geometry is strongly anisotropic, with uneven parameter influence across the observable space. When intrinsic microstructural variability is incorporated, practical identifiability is further reduced. A variance-weighted Fisher framework shows that recoverability is governed by the balance between sensitivity magnitude and
stochastic variability, rather than by structural rank alone. Inversion results confirm this behaviour: single observables produce elongated and weakly constrained objective landscapes, whereas combined observables improve conditioning through complementary sensitivities. These results show that, within the feature-level framework considered here, identifiability limits are governed primarily by forward-map structure and intrinsic variability, with direct implications for observable selection and measurement design.
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Plasma Physics · Cross-listed from astro-ph.SR
Resonant shear-flow instability in anisotropic supersonic plasmas with heat flux
Namig S. Dzhalilov
This work is devoted to the study of the influence of temperature anisotropy and parallel heat flux on the stability of supersonic shear flow in collisionless
plasmas. Within a fluid-based framework, we employ the 16-moment transport equations – derived from the Vlasov-Maxwell system – to describe the
plasma dynamics. By performing a modal analysis we investigate the oblique propagation of linear disturbances within a magnetized
plasma characterized by a shear flow of arbitrary profile aligned with the ambient
magnetic field. In the unperturbed state, both the
plasma density and the
magnetic field are assumed to be homogeneous. For a smooth,
hyperbolic velocity profile representing supersonic shear, the governing wave equation is reduced to a form amenable to an exact analytical solution. Analytical solutions are expressed in terms of special functions that yield an infinite discrete spectrum of complex eigenfrequencies ($n = 0, 1, 2, \dots$). The instability is identified as resonant, peaking when the wave phase velocity matches the mean flow velocity, with the growth rate decreasing for higher-order modes. The results indicate that, while heat flux exerts a negligible influence under conditions of supersonic flow, the growth rate decreases and approaches an asymptotic value as the Mach number increases. Notably, the instability vanishes in the
vortex sheet limit, distinguishing it from the classical Kelvin-Helmholtz mechanism. These findings suggest that this specific instability holds significant potential for explaining the problem of observed boundaries between isotropic and anisotropic
proton temperature regions in a low-beta
solar wind
plasma.
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Atomic and Molecular Clusters · Cross-listed from gr-qc
The Gravitational Spectral Radio Forest: A Signature of Primordial Black Holes
P. George Christopher, K. Hari and S. Shankaranarayanan
We propose a novel gravitational signature to detect
Primordial Black Hole (PBH) dark matter by treating interstellar hydrogen as a
quantum sensor for spacetime
curvature. Focusing on H II regions, we demonstrate that the Riemann
tidal tensor of an asteroid-mass PBH induces a symmetric splitting of the $2P_{3/2}$ state in bound hydrogen atoms. This relativistic effect redistributes $9.9\,\mathrm{GHz}$ absorption line into a gravitational spectral
radio forest with a bandwidth $\sim 2\,\mathrm{GHz}$. By accounting for active
accretion of Hydrogen atoms and the resulting density-squared emission measure within the Bondi radius, we find a relatively enhanced absorption spectrum. This feature presents a concrete, high-contrast target for upcoming
radio-surveys to constrain PBH populations in the dark matter sector.
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Biological Physics · Cross-listed from q-bio.PE
Conditioning as a route to stereotyped behavior in growing populations
Riccardo Ravasio, Kabir Husain, Constantine G. Evans et al. (+4 more)
Biological systems perform complex multi-step processes in a reproducible way despite underlying stochasticity. The standard explanation is micromanagement by molecular machinery that recognizes and corrects specific errors. Here we study conditioning, a qualitatively different strategy in which attempts failing a coarse criterion are destroyed and do not leave a physical record. The surviving, i.e., conditioned, ensemble is narrower and therefore more ordered. We model conditioning through
stochastic resets in a ”socks-before-shoes” model of a growing population, where $n$ actions must be completed in any order to replicate and any replication attempt not finished by a threshold time is discarded. We find that resets impose hierarchical temporal ordering of the $n$ actions without microscopic control over which action happens when. When disorder carries a sufficient time penalty, this ordering is free: the fastest-growing population is automatically the most ordered, with no direct selection for order required. Save points, at which verified progress is preserved across resets, allow conditioning to scale to complex multi-step processes. Conditioning provides a minimal route to reliable behavior, requiring only a clock rather than molecular machinery that recognizes specific errors. For the right class of processes, it pays for itself.
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All authors Riccardo Ravasio, Kabir Husain, Constantine G. Evans, Rob Phillips, Marco Ribezzi-Crivellari, Jack W. Szostak, Arvind Murugan
Fluid Dynamics · Cross-listed from math.NA
Fully Discrete Active Flux Method based on Transported Acoustic Increments for the Compressible Euler Equations
Karthik Duraisamy
A fully discrete Active Flux method is proposed for the two-dimensional compressible Euler equations. The method builds on the
evolution-operator formulation of multidimensional Active Flux proposed by Roe in which conservative
cell averages are updated by unsplit flux quadrature while primitive point values are evolved by acoustic and advective subsolvers. This has recently been extended to the Euler equations by Barsukow, who developed an efficient approach by adding acoustic increments at the Eulerian target point. The proposed method reconstructs the acoustic increment as a cellwise Q2 field, using vertex, edg–midpoint, and
cell-center acoustic increments, and evaluates this field at the convective foot of the target point. For constant frozen coefficients, the resulting point update reduces to the transported composition, eliminating the additive split defect and yielding the exact unsplit frozen
evolution when the acoustic and advective generators commute. The resulting method preserves the exact locally linearized acoustic
evolution operator of Barsukow, the compact stencil, and the conservative one-stage average update. Numerical experiments probe several facets of the numerical method. A mixed
Fourier wave packet with the linearized Euler equations isolates the split error and shows third-order point accuracy for the transported update. Isentropic
vortex convection confirms reduced error constants, and an enlarged empirical CFL range. Nonlinear Gaussian acoustic pulse
evolution demonstrates preservation of radial
symmetry and near-third-order decay of the
symmetry error. Low-Mach shear-layer tests show coherent vorticity
evolution, low
entropy dissipation, and absence of the coarse-grid secondary
vortices seen in displayed DG/CG comparisons. A compressible under-resolved Kelvin-Helmholtz test demonstrates robust
evolution with consistent
entropy dissipation.
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Accelerator Physics
Quasi-Strong-Strong Beam-Beam Modeling of Bootstrapping Injection in FCC-ee
Takashi Mori, Katsunobu Oide and Frank Zimmermann
The FCC-ee is designed to operate with exceptionally strong beam–beam interactions, making continuous injection a critical and non-trivial aspect of its operation. During the injection process, an unavoidable charge imbalance between the two colliding beams leads to asymmetric beam–beam forces, potentially compromising transverse stability. In this paper, we introduce a quasi-strong-strong (QSS) beam–beam scheme, implemented in the SAD simulation framework. The method preserves a self-consistent beam–beam lens by coupling paired weak–strong simulations, while avoiding the computational cost of full strong–strong tracking. The injection process is modeled as a gradual increase of the stored bunch population, allowing the isolated study of beam–beam–driven optics deformation under charge imbalance. Using the QSS approach, we investigate the feasibility of bootstrapping injection in the Z, W, and H operating modes of FCC-ee. Stable injection paths up to the nominal bunch population are identified in the W and H modes. In contrast, in the explored parameter region, the Z mode exhibits saturation of the stored population below the nominal value.
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Medical Physics
Evaluating a Large Language Model for Radiotherapy Patient Scheduling under Realistic Clinical and Operational Constraints: a Feasibility Study
Eric Zhang, Youfang Lai, Wen Li et al. (+4 more)
Radiotherapy scheduling must balance clinical constraints and operational objectives. We evaluated the feasibility of using a large
language model (LLM) to generate treatment schedules through simulation and retrospective clinical comparison. A one-year simulation modeled 1,400 new patients across 12 treatment categories and three linear accelerators (LINACs). Structured
prompts provided ChatGPT with patient information, schedule status, clinical rules, and operational objectives. Scenarios assessed treatment-time consistency, LINAC continuity, gap reduction, and handling of infeasible requests. LLM schedules were compared with heuristic and constraint programming (CP-SAT) approaches under two objective settings. A six-week retrospective analysis included 2,043 clinical appointments. LLM-generated schedules met all predefined feasibility constraints in the evaluated scenarios, with 98.6-98.8% of fractions within preferred treatment-time windows. Prioritizing LINAC continuity reduced switching from 52.4 +/- 2.6% to 9.4 +/- 0.6%. Gap-constrained temporal relaxation reduced average daily gaps to 47.1 +/- 8.5 minutes and Friday gaps to 89.2 +/- 18.4 minutes while maintaining low overtime. The framework identified predefined violations in infeasible requests and suggested corrective actions. Heuristic and CP-SAT methods also generated feasible schedules, with performance dependent on objective weighting. In retrospective evaluation, all approaches scheduled appointments without overtime; LLM strategies reduced mean gaps by 50.8-77.1% and improved treatment-time consistency from 86.7% to 99.5-99.9%. These findings support further evaluation of structured LLM scheduling as a human-in-the-loop decision-support approach for radiotherapy.
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All authors Eric Zhang, Youfang Lai, Wen Li, Annette Souranis, Georgia Paparoidamis, Michael Roumeliotis, Xun Jia
Medical Physics
Dynamic Modulated Arc Therapy (DMAT): A Time Aware, Modulation Steered Optimization Framework for Next Generation Radiotherapy Delivery
Taoran Li, Esa Kuusela, Emmi Ruokokoski et al. (+10 more)
Background: Conventional VMAT optimization treats delivery time and deliverability as emergent properties of control-point-centric models that ignore finite acceleration and other dynamic limits. As linacs gain axis speed and dose rate, the plan quality-time trade-off must become explicit and steerable. Purpose: To introduce Dynamic Modulated Arc Therapy (DMAT), a time-aware, modulation-steered framework that jointly optimizes dosimetric quality, delivery time, and modulation complexity. Methods: DMAT couples direct machine emulation (axis synchronization, finite acceleration), dynamic modulation control, and clinical metrics used directly as cost functions. A user-selected modulation level (-3 to +3) governs leaf-travel allowance, total MU, aperture complexity, and control-point (CP) density. Plans are generated by progressive-resolution optimization alternating dosimetric with sequencing/deliverability updates, with non-uniform CP redistribution and complexity-reducing post-processing. DMAT was evaluated on head-and-neck, lung SBRT, and prostate SBRT cases using a hypothetical accelerated system (2.5 RPM gantry, 6.25 cm/s MLC, 3000 MU/min). Results: Increasing modulation level raised modulation surrogates (MU/Gy, aperture complexity) and delivery time, with additional CPs concentrated in arc sectors where finer angular resolution was most beneficial. The trade-off was site dependent: head-and-neck gained substantial plan quality, whereas prostate and lung SBRT gained little beyond baseline. Negative levels predictably shortened delivery time at a fixed CP budget, with quantifiable quality loss. Conclusions: DMAT co-optimizes plan quality and modulation complexity under machine-aware timing and explicit user control, making quality-time trade-offs transparent and navigable and supporting time-constrained workflows such as motion management and adaptive radiotherapy.
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All authors Taoran Li, Esa Kuusela, Emmi Ruokokoski, Heini Hyvönen, Jerry Jaboin, Mirko Myllykoski, Jussi Nurminen, Riku Paananen, Jarkko Peltola, Marko Rusanen, Martin Sabel, Kevin Moore, Christopher Boylan
Optics
Ultrafast wide-field 3D topography with extended depth of field
Qianyi Wei, Jielei Ni, Yuquan Zhang et al. (+6 more)
Ultrafast optical imaging has enabled direct observation of femtosecond-nanosecond dynamics, yet three-dimensional (3D) dynamic measurements at high numerical aperture (NA) remain hindered by the intrinsically shallow depth of field (DoF) of conventional microscopes. Here, we propose an ultrafast, wide-field pump-probe interferometric microscope on a telecentric platform that significantly extends the effective DoF to ~18 micrometer at a high NA of 0.9 while maintaining high spatial resolution (down to 235 nm) and temporal resolution (~170 fs). The system enables single-frame 3D topography reconstruction without axial scanning or multi-view acquisition. We demonstrate these capabilities by capturing axial material flow during
laser-induced microsphere melting that remain unobservable with conventional narrow-DoF systems, and by tracking the azimuthal rotation of ablation lobes during axial propagation of temporal focused spatiotemporal optical
vortex (TF-STOV) pulses, directly revealing the spatiotemporal
evolution of STOV-matter interactions
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All authors Qianyi Wei, Jielei Ni, Yuquan Zhang, Zhangyu Zhou, Shuoshuo Zhang, Zhiyong Tan, Jiahui Pan, Xiaocong Yuan, Changjun Min
Chemical Physics · Cross-listed from cond-mat.soft
PACSim: A Flexible Simulation Framework for Polymer-Attenuated Coulombic Self-Assembly
Philipp Höllmer, Nicole Smina, John P. Marquardt et al. (+4 more)
Polymer-Attenuated Coulombic Self-Assembly (PACS) is a flexible experimental approach for generating
crystals from simple colloidal building blocks. The central components are charged spherical particles coated with a
polymer brush that prevents irreversible aggregation. Whether oppositely charged colloids crystallize, and which structures they form, depends on several factors, including colloid concentration, charge, and size, as well as the salt concentration of the solution. Molecular dynamics (MD) simulations are a powerful tool for predicting the outcomes of PACS assembly experiments and also provide particle-level insight into the assembly processes. Here, we present an open-source simulation framework, PACSim, that enables MD simulation studies of assembly by PACS across a range of experimentally relevant scenarios. PACSim is built on top of OpenMM, a flexible MD simulation framework that readily supports the implementation of different interaction potentials, as well as integration with other tools such as enhanced-sampling and machine-learning frameworks. We describe the motivation for PACSim, outline its features, report methodological advancements inspired by this framework, and provide examples of its use.
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All authors Philipp Höllmer, Nicole Smina, John P. Marquardt, Michael S. Chen, Steven van Kesteren, Stefano Sacanna, Glen M. Hocky
Physics and Society
Empirical confirmation of bosonic wealth statistics in Bitcoin UTXOs
Chanhee Park, Claudio J. Tessone, Yu Zhang et al. (+1 more)
Digitalisation transforms money from distinguishable physical objects into fungible informational units. A recent theoretical framework predicts that such indistinguishable wealth obeys bosonic occupancy statistics, leading to
geometric ownership distributions and enhanced inequality. Using Bitcoin blockchain data, we test this prediction on 63 UTXO denominations across 72 monthly snapshots (2018–2023). A one-parameter
geometric model describes the ownership distributions, reproducing both mean holdings and their temporal
evolution; Jensen–Shannon divergence values lie below $0.08$ in $99.74\%$ of cases. The inferred inverse-temperature parameter satisfies the analytic mean–temperature relation to better than $0.1\%$ in every sample – a self-consistency test that two-parameter alternatives cannot pass – and remains within a narrow band across eight orders of magnitude in denomination and over six years. Bitcoin UTXO ownership statistics are therefore consistent with bosonic occupancy laws, suggesting that the informational nature of electronic money may act as a structural driver of inequality in digital economies.
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All authors Chanhee Park, Claudio J. Tessone, Yu Zhang, Jeong-Hyuck Park
Applied Physics
Dispersion Engineered Frequency Tunable Delay Platform based on Magnetostatic Surface Waves
Chin-Yu Chang, Xingyu Du, Shun Yao et al. (+3 more)
Reconfigurable
radio-frequency front ends in modern radar and wireless systems require delay elements that simultaneously offer low-loss, low noise, compact form factor, and wideband frequency agility. However, electromagnetic, acoustic, photonic, and active-
circuit delay technologies each fail to deliver this combination. Here we report a microwave delay platform based on magnetostatic surface waves (MSSWs) in microfabricated 18 $\mu$m yttrium iron garnet (YIG) waveguides, in which co-engineering the
spin wave dispersion with the radiation impedance of meander-line transducers grants pitch-controlled access to distinct dispersive or near-constant group-delay regimes. Tuned continuously from 6 to 19.6 GHz under
magnetic bias, the delay lines deliver group delays of 3.3 to 42.8 ns at insertion losses of 2.5 to 10.1 dB and nonreciprocal isolation of 24 to 39 dB, all measured directly into 50 $\Omega$ without external impedance matching. Length-resolved characterization yields unit-time propagation losses of 56 to 109 dB/$\mu$s and propagation Q-factors that rise monotonically from 3002 to 4893 across the operating range, exceeding state-of-the-art fixed frequency acoustic delay lines at every benchmarked frequency. These results establish microfabricated YIG as a versatile, low-loss microwave platform for next-generation reconfigurable RF signal processing.
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All authors Chin-Yu Chang, Xingyu Du, Shun Yao, Tao Wang, Shuxian Wu, Roy H. Olsson III
Classical Physics
Natural frequency estimation using complex-frequency excitations
Wenbo Li and Raj Kumar Pal
Complex frequency excitations, oscillating signals whose amplitude decreases exponentially in time, have recently been demonstrated to significantly increase the effective quality factor of mechanical resonators. In this work, we investigate the accuracy of natural frequency estimation in mechanical systems under noise using such excitations. The analysis is performed on an underdamped linear time-invariant single-degree-of-freedom spring-mass-damper system. We employ tools from information theory, namely Fisher information, to systematically quantify the sensitivity of complex-frequency excitation to measurement noise. Explicit closed-form expressions are derived relating Fisher information to excitation and system parameters under both Gaussian white and colored noise. The theoretical predictions are verified through Monte Carlo numerical simulations. The results indicate that appropriate selection of excitation parameters can significantly enhance the Fisher information, leading to improved estimation accuracy under complex-frequency excitations compared with conventional harmonic excitations. Experimental results demonstrate the advantages of complex-frequency excitation in terms of both accuracy and robustness of natural-frequency estimation. These findings establish a foundation for the development of high-performance sensors and novel nondestructive evaluation methods.
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Computational Physics
A practical investigation on time integration in the quantized tensor train format
Erika Ye
Quantized tensor trains (QTTs) are a multiscale computational framework that can potentially reduce the computational cost of solving partial differential equations and initial value problems by making low-rank approximations. However, its use is somewhat limited in practice, in part due to the challenges that arise when making low-rank approximations of the quantized data. For example, when performing long-time dynamical numerical simulations, it has been observed that the accumulation of numerical errors arising from both the discretization of the partial differential equation itself and the low-rank approximation can lead to increased rank and noise-dominated results. Focusing on a set of advection-dominated test problems relevant to electromagnetic
plasmas and electromagnetic fields, this work investigates how the choice in time integrator, the addition of numerical dissipation, and the choice in problem representation can affect the efficiency and success of the QTT calculations.
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