Optics · Cross-listed from quant-ph
Nanoscale graphitization and defect evolution in silicon-vacancy center-containing nanodiamonds under high-pressure high-temperature annealing
M. De Feudis, B. Yavkin, L. Henry et al. (+6 more)
Group-IV color centers, such as the silicon-vacancy (SiV) defect, are highly promising for solid-state
quantum technologies. However, nanodiamonds typically exhibit significant
lattice strain and structural disorder, which degrade their optical properties and hinder the resolution of the fine spectral structure at cryogenic temperatures. High-pressure high-temperature (HPHT) annealing offers a potential route to relax internal strain, although the phase stability of diamond at the nanoscale under such conditions remains poorly constrained. Here, we investigate the structural
evolution of nanodiamonds during HPHT annealing using a Paris-Edinburgh press coupled with in situ synchrotron X-ray diffraction at SOLEIL. A dedicated sample assembly combining nanodiamonds - NaCl - Pt enabled accurate pressure-temperature calibration and real-time monitoring of phase transformations. The diffraction data reveal that the onset of diamond-to-graphite transition occurs at approximately 1800 K at 2 GPa and 2120 K at 4 GPa under the applied HPHT heating protocol. These experimentally determined graphitization onsets define a practical pressure-temperature processing window for HPHT annealing of nanodiamonds while avoiding detectable graphitization and provide a calibrated framework for reliable off-beam annealing treatments that avoid graphitization. Photoluminescence measurements on samples annealed below the graphitization threshold show improved optical response, with partial resolution of the SiV fine structure at 12 K. These optical measurements suggest a relationship between nanoscale phase stability and the optical response of individual SiV-containing nanodiamonds following HPHT annealing. The experimentally established HPHT processing window provides a practical framework for the controlled processing of
quantum nanodiamonds while avoiding graphitization.
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All authors M. De Feudis, B. Yavkin, L. Henry, K.O. Ho, M.-P. Adam, P. Goldner, F. Benedic, S. Desgreniers, J.-F. Roch
Fluid Dynamics · Cross-listed from stat.AP
Evaluating the Role of Blockage Deficit Models in Robust Wind Farm Design
Manh Cuong Ngo and Alexander Meyer Forsting
Uncertainty in wind farm layout optimization regarding model choice and the impact of global blockage always exists. This paper evaluates these interactions by extending a multi-objective approach that maximizes mean Annual Energy Production (AEP) from a model ensemble while minimizing their variance. By incorporating the Self Similar blockage model into an ensemble of five wake models, we assess the impact of blockage physics on layout robustness. Results from a linear mixed-effects model indicate that including blockage leads to a non-significant average AEP reduction of 0.0624 GWh ($p$-value = 0.323). Conversely, it caused a highly statistically significant increase in uncertainty, with model disagreement rising by 0.177 GWh ($p$-value < 0.001). Additionally, computational runtime increased nearly nine times. These findings highlight an accuracy vs. certainty paradox, where theoretically necessary physics can compromise model consensus if implemented without re-calibration. Ultimately, this work suggests that simple blockage couplings act as a diagnostic for model incompatibility, emphasizing the necessity of careful model tuning for wind farm design.
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Optics
Direct experimental measurement of femtonewton-scale momentum transfer force from electron beams
Chunbo Lin, Xinggang Shang, Xijun Li et al. (+6 more)
Electron beams (e-beams) are ubiquitous in imaging, patterning, and propulsion. This prevalence is rooted in the profound mastery of their wave-particle duality and energy-transfer pathways. Yet, a fundamental dimension remains largely unexplored: while the mechanical effect (i.e., the momentum transfer to a target) is theoretically known, quantification of its femtonewton-range force has remained elusive. This discrepancy represents a missing piece of the puzzle toward a comprehensive understanding of e-beam-matter interactions, and ultimately limits the multi-dimensional exploitation of e-beams. A force sensor combining femtonewton sensitivity, immunity to electromagnetic noise, compatibility with
vacuum, and absolute calibration is critical to bridge the gap between theory and experiment. Here the FINEST (Femtonewton Interferometric Nanomechanical Electron-beam Sensing Technology) sensor is proposed and successfully tested to measure the force of an e-beam. FINEST is an optical-pressure-calibrated 3D spring-type optical sensor that operates reliably under e-beam conditions. Femtonewton-scale forces from 2-30 keV e-beams are directly measured, ranging from 505 fN to 13 pN. Both linear scaling with beam current and a non-monotonic energy dependence (peaking near 10 keV) are observed. Based on this calibrated force, the mechanical contribution to e-beam ice etching was quantitatively confirmed; its effect is orders of magnitude lower than the total etch depth and lacks noticeable energy dependence. By achieving the first direct experimental measurement of e-beam momentum transfer, this work adds a long-missing dimension to the physical landscape of e-beam processes. These findings provide a quantitative basis for furthering the multi-dimensional exploitation of e-beams, potentially transforming our approach to precision nanofabrication, sensing, and fundamental electron physics research.
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All authors Chunbo Lin, Xinggang Shang, Xijun Li, Xiaoyu Sun, Kang Zhao, Xujie Wang, Yang Yu, Wenjing Cao, Min Qiu
Plasma Physics
Gas Flow Rate Influence on Gas Temperature Regulation in a Reinforced Radio-Frequency Cross-Field Atmospheric Plasma Jet
Radhika T. P. and Satyananda Kar
This study investigates the effect of gas flow rate on the gas temperature and discharge characteristics of a reinforced
radio frequency cross-field atmospheric pressure
plasma jet (APPJ) with an additional floating electrode. The
plasma jet length, electron excitation temperature, electron density, and reactivity were enhanced by introducing copper floating electrodes of varying widths. However, this enhancement was accompanied by an undesired rise in gas temperature, limiting the
plasma's application for heat- sensitive materials. To control this temperature rise, the gas flow rate varied from 1.5 to 9 lpm, showing a significant reduction in gas temperature from 438 K to 402 K as the flow rate increased, particularly at higher input powers. The study reveals that while an increase in gas flow rate initially improves ionization and reactivity by increasing electron excitation temperature and density, the insufficient input power for ionization at higher flow rates causes a decline in these parameters due to reduced ionization efficiency. Further optimization was achieved by increasing input power, which allowed better utilization of neutral atoms and improved
plasma reactivity even at higher flow rates. The findings highlight the importance of tuning both gas flow rate and input power to maintain optimal
plasma performance for various applications, particularly where controlled gas temperature and high reactivity are essential.
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Plasma Physics
Potential of Atmospheric Pressure Thermal Plasma Technology towards Waste Processing: A Comprehensive Review
Tejashwi Rana, Aishik Basu Mallick, Radhika T P et al. (+3 more)
The enhancement of living standards has significantly contributed to the rapid growth of urban populations, resulting in a substantial increase in municipal solid waste (MSW) generation. This trend underscores the critical need for sustainable, environmentally friendly, cost-effective, and highly efficient waste management solutions. This study highlights the pressing necessity for effective MSW management and examines
plasma pyrolysis/gasification as an emerging technology to address this challenge. The article provides a detailed analysis of thermal
plasma generation techniques employing diverse power sources, including direct current, alternating current, radiofrequency inductively coupled, and microwave-based systems. A comparative evaluation of various
plasma torch designs is conducted, emphasizing their applicability in waste-to-energy and waste treatment processes. A comprehensive overview of the treatment of a broad spectrum of waste materials, such as MSW, sewage sludge, coal, wood, plastics, tyres, and rubber, using thermal arc
plasma technology is presented. The process predominantly converts waste into a combustible gas (syngas) with a calorific value ranging from 5 to 15 MJ/Nm3 and produces vitrified slag or ash as a by-product. The findings suggest that thermal
plasma pyrolysis/gasification offers a promising approach to waste management, facilitating energy generation and material recovery while addressing the challenges of increasing MSW generation.
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All authors Tejashwi Rana, Aishik Basu Mallick, Radhika T P, Suryasunil Rath, Pratyay Chattopadhyay, Satyananda Kar
Biological Physics · Cross-listed from q-bio.NC
How many labels can a biological oscillator carry? A quality-factor screen for proposed information carriers
Eran Kopel
How many distinguishable labels can a biological oscillator carry? Proposals invoking collective vibrational modes, endogenous electromagnetic fields, microtubule excitations and oscillatory phase codes are each debated on grounds particular to themselves, with no shared standard for comparison. We show that spectral distinguishability alone bounds the number of labels by the quality factor, M <= Q = 2 pi nu tau. This follows from the relation between linewidth and coherence time, so it is independent of substrate, of mechanism, and of any position on
quantum effects in biology, and it can be evaluated from two published quantities. Applied to a recently proposed 30 GHz intracolumnar microwave field in cortex, it gives Q = 0.19: the linewidth exceeds the carrier five-fold. The obvious rescue, that a driven emitter can be spectrally narrower than its gain medium, requires a resonant cavity, and the model's own geometry forbids one. An independent bound on metabolic power is exceeded by five to nine orders of magnitude. Six further criteria follow from the same standpoint, including a two-sided persistence window requiring a label to be both readable and rewritable. Screening eleven carriers, only the low-frequency neural rhythms pass. High-frequency molecular carriers are eliminated by brevity, not by the fragility the debate has assumed.
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Optics
Dispersion Control of Chiral Exciton-Polariton Transport with Dielectric Metasurfaces
Juhyeong Jeon, Kehan Wang, Yu-Chen Wei et al. (+6 more)
Exciton-polaritons provide a powerful platform for manipulating hybrid light-matter states with low effective masses and strong nonlinearities. Introducing chirality into these quasiparticles enables selective control over their
spin and propagation, opening new opportunities for
chiral transport and
spin-selective polaritonic devices. We exploit the strong
chiral light-matter coupling in silicon metasurfaces composed of tilted nanorod dimers to demonstrate selective transport of organic
chiral exciton-polaritons. The metasurface supports surface
lattice resonances and quasi-bound states in the continuum that simultaneously provide high photonic confinement and extrinsic chirality, giving rise to
chiral exciton-polaritons in the achiral molecules. These
exciton-polaritons exhibit a large magnitude of the dissymmetry factor, reaching a value of 0.93. Using photoluminescence
Fourier microscopy and real-space imaging, we show that
chiral exciton-polaritons propagate over distances exceeding 50 um without significant degradation of their dissymmetry, with characteristic propagation lengths of approximately 6-13 um. These propagation lengths correspond to an enhancement of 3 orders of magnitude compared to bare
excitons. This work constitutes the first demonstration of enhanced and selective
chiral transport of organic
exciton-polaritons, driven by strong light-matter coupling, in achiral metasurfaces, paving the way for
spin-selective polaritonic technologies using simple metasurfaces.
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All authors Juhyeong Jeon, Kehan Wang, Yu-Chen Wei, Francesca Cussiol, Matthijs Berghuis, Fan Xu, Shunsuke Murai, E. W. Meijer, Jaime Gómez Rivas
Plasma Physics
Development and Characterization of a Microwave Atmospheric Pressure Plasma Jet
Suryasunil Rath and Satyananda Kar
Over the past decade, atmospheric pressure discharges in the microwave frequency range have gained significant
attention due to their promising applications in material processing, CO2 dissociation, waste management, hydrogen production, water treatment, and more. This study presents the development and characterization of a waveguide-based microwave atmospheric pressure
plasma jet (MW-APPJs), focusing on its design, diagnostics, and operational parameters. The setup incorporates a microwave power source, microwave waveguide networks, including the applicator section, and diagnostic tools for measuring
plasma properties. Optical emission spectroscopy (OES) is employed to analyze the reactive species and determine
plasma parameters which include electron excitation temperature (Texc) and electron number density (ne). The characterization highlights the influence of spatial and temporal gradients, gas flow rates, and power input on
plasma behaviour. From OES, the Texc and ne variations were against the power increment. The thermocouple variations are also plotted with power.
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Data Analysis and Statistics · Cross-listed from cs.NI
Link-adaptive digital twin for robust physical-layer modeling in hybrid-amplified ultra-wideband optical networks
Xiaoxuan Gao, Rentao Gu, Yingchun Wang et al. (+3 more)
Accurate physical-layer modeling is increasingly essential for reliable ultra-wideband operation and capacity optimization, especially under the intensified inter-channel stimulated Raman scattering (ISRS) effect. This paper proposes the link-adaptive digital twin (LA-DT) for hybrid-amplified ultra-wideband links to overcome the generalization and speed limitations of existing methods, achieving accurate modeling and robust generalized signal-to-noise ratio (GSNR) estimation across diverse links. First, to address EDFA heterogeneity, the GSNR modeling task is decomposed into three key power predictions: ASE, NLI, and signal powers before EDFA entry. Second, to enhance cross-scenario generalization, three dedicated DT models are developed using a novel neural architecture with linear modulation layers (LMLs). Third, for rapid adaptation to unseen scenarios with limited data, three domain discriminators guide few-shot fine-tuning of the LMLs. Fourth, the LA-DT explicitly accounts for Raman amplifier (RA) insertion loss, improving practical deployment reliability. Results across 35 scenarios show that LA-DT reduces RMSE for NLI, ASE, and signal power predictions to 0.151, 0.111, and 0.113 dBm with improvements of 56.0%, 58.4%, and 52.7% over the baseline,and achieves an average GSNR estimation RMSE of 0.114 dBm (55.8% improvement). For 12 unseen scenarios, the LA-DT maintains high accuracy through few-shot fine-tuning with only 20 samples per scenario, achieving an average GSNR RMSE of 0.159 dB and demonstrating strong adaptability and robustness.
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All authors Xiaoxuan Gao, Rentao Gu, Yingchun Wang, Xinyi Liu, Junshi Gao, Yuefeng Ji
Optics
730-nm optical parametric conversion from near- to short-wave infrared band
J. M. Chavez Boggio, J. R. Windmiller, M. Knutzen et al. (+6 more)
A record 730 nm parametric conversion in silica fiber from the near-infrared to the short-wave infrared band is reported and analyzed. A parametric gain in excess of 30 dB was measured for a signal at 1300 nm (with corresponding idler at 2030 nm). This conversion was performed in a travelling single-pass one-pump parametric architecture and high efficiency is achieved by a combination of high peak power and a nonlinear fiber with a reduced fourth-order dispersion coefficient.
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All authors J. M. Chavez Boggio, J. R. Windmiller, M. Knutzen, R. Jiang, C. Bres, N. Alic, B. Stossel, K. Rottwitt, S. Radic
Optics
Toward a Thermodynamic Framework for Dissipative Solitons: From Photonics to Turbulence and Bose–Einstein Condensate Analogies
Vladimir L. Kalashnikov and Irina T. Sorokina
# Abstract Thermodynamic concepts are increasingly used in nonlinear photonics to describe Rayleigh–Jeans thermalization, optical wave
turbulence, condensation, negative-temperature states, and statistical mode locking. This raises a broader question: how far can thermodynamic
reasoning be extended to localized structures maintained far from
equilibrium by a balance of gain, loss, dispersion, and nonlinearity? We address this question using strongly chirped dissipative
solitons (DSs) of the complex cubic–quintic Ginzburg–Landau equation (CQGLE) as a model system. Their internal energy flows and separation of correlation scales connect coherent solitary waves with semi-incoherent wave kinetics, driven open systems, and Bose–Einstein-condensation analogies. We review thermodynamic-like descriptions based on spectral
entropy, internal energy, effective temperature, and condensation-like spectral restructuring, relating them to dissipative-
soliton resonance (DSR),
stochastic mode-locking self-start, and redistribution between single- and multipulse attractors. Normal and anomalous group-delay dispersion (NGD and AGD) provide complementary realizations: in NGD, DSR is accompanied by spectral localization, scale separation, and increasing accessibility of multipulse states; in AGD, the spectrum has extended wings and dynamical robustness occupies only part of the existence domain. These results distinguish general features of nonequilibrium state selection from effects tied to a particular localization mechanism. We argue that thermodynamic-like observables are best viewed as coarse-grained structural diagnostics rather than
equilibrium state variables, while DSs provide a photonic platform linking nonequilibrium thermodynamics, wave
turbulence, driven condensates, and statistical phase-transition concepts.
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Chemical Physics
Benchmark measurements of absolute frequencies and collisional line-shape parameters in the CO-Ar system using comb-based FTS
Akiko Nishiyama, Grzegorz Kowzan, Dominik Charczun et al. (+2 more)
We report absolute frequency measurements of the CO fundamental band, together with high-precision Ar-induced collisional line-shape parameters using comb-based
Fourier-transform spectroscopy. High-quality spectra were obtained with a stable mid-IR optical frequency comb source and careful suppression of technical noise. By applying analysis methods that fully exploit the advantages of optical frequency comb spectroscopy, precise frequency calibration and robust multi-line fitting were achieved, resulting line-center fitting errors below 0.00001 cm$^{-1}$ for most transitions. The measured transition frequencies agree with HITRAN within 0.0001 cm$^{-1}$, supporting the reliability of the semi-empirical database. Multi-line fits using a speed-dependent Voigt profile yield collisional parameters for approximately 40 P- and R-branch lines, providing a reliable experimental
benchmark for CO-Ar line-shape modeling.
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All authors Akiko Nishiyama, Grzegorz Kowzan, Dominik Charczun, Roman Ciuryło, Piotr Masłowski
Fluid Dynamics
Low-dimensional structure and online tracking of POD subspaces on the Grassmann manifold: application to flow around an airfoil
Shintaro Sato, Yoshitsugu Naka, Rei Sasaki et al. (+2 more)
Representing flow states over a wide range of flow parameters and control inputs in a low-dimensional state space is a central challenge in fluid mechanics. Rather than representing the instantaneous flow field in a fixed subspace spanned by the leading proper orthogonal decomposition (POD) modes, this study regards the POD subspace itself as the flow state at each flow condition. The set of POD subspaces associated with flow conditions defines a state space on the Grassmann
manifold.
Diffusion maps identify the intrinsic low-dimensional structure of the family of POD subspaces, while Grassmannian rank-one update subspace estimation tracks the temporal
evolution of a POD subspace online. The framework is experimentally demonstrated for flow around an airfoil. POD subspaces are extracted from wall-pressure fluctuations measured by a microphone array over a range of angles of attack and under different control inputs. The subspaces are found to lie on a one-dimensional submanifold of the Grassmann
manifold. Moreover, the transition from separated to attached flow, induced by a
plasma actuator, follows a reproducible trajectory along the same submanifold identified from statistically stationary flow data. The temporal
evolution of the subspace is consistent with the transient
evolution of the flow field observed using particle image velocimetry. These results show that POD subspaces can serve as representative flow states, enabling their temporal
evolution across a wide range of flow conditions to be tracked online in a low-dimensional space based on wall-pressure fluctuations. This low-dimensional representation provides a basis for real-time flow-state estimation and feedback control.
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All authors Shintaro Sato, Yoshitsugu Naka, Rei Sasaki, Rion Handa, Naofumi Ohnishi
Applied Physics · Cross-listed from cond-mat.mes-hall
Dynamics of amorphous membranes in the two-dimensional limit
Liga Jasulaneca, Alberto Martín-Pérez, Hongji Zhang et al. (+7 more)
Atomically thin mechanical resonators have been realized predominantly in crystalline two-dimensional (2D) materials, such as
graphene, where long-range crystalline order sets their elastic properties and defines their nonlinear resonant behavior. Extending these concepts to the amorphous 2D limit has remained largely unexplored. Here, we demonstrate that monolayer amorphous carbon (MAC) forms suspended membranes that support optothermal actuation and sensitive interferometric readout across both linear and nonlinear regimes of its resonant motion. We resolve thermomechanical motion, driven resonances, and multimode spectra in MAC nanodrums. The frequencies of fundamental vibration modes correspond to unusually low pretensions, placing monolayer MAC nanodrums in a regime where
geometric nonlinearities, stress heterogeneity, and mode coupling emerge at comparatively low drive powers. Consistently, we observe pronounced nonlinear dynamics, including hardening, softening, and mixed Duffing responses, nonlinear damping, parametrically excited modes, and signatures of intermodal coupling. These results establish MAC as a robust nanoelectromechanical platform and open an experimental route to disorder-governed nanomechanics in the 2D amorphous limit.
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All authors Liga Jasulaneca, Alberto Martín-Pérez, Hongji Zhang, Prertahn Munireternam, Natalia A. Mamchik, Chee-Tat Toh, Artem K. Grebenko, Barbaros Özyilmaz, Makars Šiškins, Farbod Alijani
Medical Physics · Cross-listed from cs.CV
Lesion-Aware Adaptive Fourier Neural Operator for CT-to-PSMA PET Synthesis in Prostate Cancer
Rashmi Bhaskara, Waleed M. Almutairi, Matthew Gopaulchan et al. (+5 more)
Deep learning models that synthesize PET from CT or MRI can reduce patient dose and scanner demand, but are typically optimized with global losses such as L1 or mean squared error (MSE) that treat all voxels similarly. In whole-body PSMA-PET, tumor voxels occupy only a small fraction of the volume, yet carry the clinically relevant activity signal; as a result, models can achieve high structural similarity index measure (SSIM) and peak signal-to-noise ratio (PSNR) while still underestimating lesion activity or failing to preserve tumor-specific structure. Radiomics provides biologically meaningful descriptors of tumor intensity and texture, but direct radiomics conditioning is time-consuming because it requires feature extraction from delineated lesion regions. We propose LAFNO, a Lesion-Aware Adaptive
Fourier Neural Operator for CT-to-PSMA-PET synthesis that replaces high-dimensional radiomics conditioning with two efficient CT-derived proxy channels. Motivated by radiomics analysis of PSMA-avid tumor core and peritumoral regions, LAFNO uses a contrast proxy for local density variation and a disorder proxy for local texture heterogeneity, both injected into the model bottleneck. LAFNO combines whole-volume reconstruction with lesion-level total lesion activity (TLA), tumor-core contrast, and peritumoral supervision. We evaluated LAFNO against four baseline architectures on the TCIA PSMA-PET-CT-Lesions
dataset. LAFNO remained competitive on whole-volume image quality, achieving SSIM of 0.960 and 0.938 for 18F- and 68Ga-PSMA, respectively, while reducing per-patient TLA error to 48.3% and 64.0% for 18F- and 68Ga-PSMA, respectively, and achieving the highest tumor-core radiomics reproducibility across all feature classes for both tracers. Peritumoral reproducibility remained tracer-dependent, indicating that biological fidelity in synthetic PSMA-PET remains challenging.
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All authors Rashmi Bhaskara, Waleed M. Almutairi, Matthew Gopaulchan, Maram Musaad Alqurashi, Francis Asamoah, Alex Ocana, Clinton D. Bahler, Oluwaseyi M. Oderinde
Optics
Causality Sum Rules in Conventional Scattering Matrices
Ning Han, Rui Zhao, Shuxing Yang et al. (+3 more)
Scattering
matrices are the standard experimental and computational description of photonic and electromagnetic devices. Passivity is explicit in the conventional incoming-outgoing
matrix, whereas causality sum rules are usually formulated only after transforming the response into auxiliary variables. Here we show that these rules can be written directly in the conventional scattering
matrix by removing the time advance introduced by the reference domain. Using the earliest-arrival delay of each channel, we define a domain-delayed
matrix that preserves real-frequency passivity while restoring the causal time origin. Under explicit analyticity, transparency, and regularity assumptions, this
matrix becomes a Schur function, enabling a Cayley-Herglotz construction. The resulting projected and determinant bounds constrain coherent channel superpositions and aggregate multichannel loss. The framework recovers Rozanov's absorber limit and spherical-multipole sum rules, while extending causality bounds to measurable quantities including insertion loss, suppressed singular-value channels, and conditional lossless delay-bandwidth trade-offs. Our work directly connects fundamental causality theory with experimentally accessible scattering data. The initial theoretical route is autonomously explored by Qiushi Engine, an AI research system for open-ended scientific discovery, and subsequently verified, refined, and developed by the authors, demonstrating a hybrid AI-human discovery workflow.
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All authors Ning Han, Rui Zhao, Shuxing Yang, Mingzhu Li, Hongsheng Chen, Yihao Yang
Accelerator Physics
Realizing A Hard X-Ray Storage Ring Free Electron Laser Oscillator at the APS-U
Emmanuel Aneke, Kent Wootton, Ryan Lindberg et al. (+1 more)
We show that the APS-U could support a hard X-ray storage ring free electron
laser oscillator, providing a promising avenue toward high repetition rate, narrow bandwidth coherent light sources. The results of our numerical simulations demonstrate that a transverse gradient undulator yields ~8% and ~6% single-pass gain at 8.05 keV and 10 keV respectively. We further identify a configuration at 5 keV that does not require a TGU but still exceeds a 5% gain threshold despite the relatively short 5-meter long insertion device. All cases presented retain spectral purity on the order of meV and reach a steady-state output whose
equilibrium is consistent with the Renieri Saturation Limit. We have calculated the 5 keV case to have an average brightness of ~10^26
photons/(s * mm2 * mrad2 * 0.1% BW), representing an increase in more than four orders of magnitude from the standard APS-U undulator. These results indicate that a storage ring free electron
laser oscillator at multi-keV
photon energies is feasible with nominal APS-U parameters and standard x-ray cavity optics.
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All authors Emmanuel Aneke, Kent Wootton, Ryan Lindberg, Chris Jacobsen
Atmospheric and Oceanic Physics
Observational Evidence Revises Presumed Large Ozone Worsening from Nitrogen Oxides Cuts
Xiang Weng, Xiao Lu, Jiawei Li et al. (+8 more)
Many air quality models indicate that rapid reductions in nitrogen
oxides (NOx), without comparable controls on volatile organic compounds, have worsened summertime ozone pollution in urban China, producing a short-term strong ozone penalty. Other models, however, simulate the opposite response, suggesting that cutting down NOx has already helped mitigate ozone pollution. This contradiction obscures understanding of atmospheric chemistry and weakens guidance on control policy design. Here, we reconcile this disagreement and reveal the underestimated benefits of NOx emission reductions using a machine learning framework integrated with an observational constraint. We first constrain ozone responses under a 30% NOx reduction, comparable to the magnitude of NOx emission declines across major Chinese city clusters between 2015 and 2023. The constrained results indicate that ozone decreases prevail across urban China, with only small increases mainly in July 2015. This challenges the widespread ozone worsening that many models predict. We then extend the constraint across 10-60% NOx reductions, establishing its use for rapid ozone sensitivity diagnosis without exhaustive scenario modeling. This diagnosis shows that sustained NOx control increasingly favored ozone mitigation during 2015-2023, benefiting a growing share of China's population. These results underscore that continued NOx reductions can deliver larger ozone mitigation benefits than many models suggest.
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All authors Xiang Weng, Xiao Lu, Jiawei Li, Grant Forster, Jessica Chapman, Beckie George, Yunbo Lu, Guowen He, Haofan Wang, Jingcheng Lai, Peer Nowack
Optics · Cross-listed from quant-ph
Private Correlations Certify Sensing Capability
Yunkai Wang, Peixue Wu, Graeme Smith et al. (+1 more)
We show that private correlations in a bipartite
quantum state constitute a metrological resource for distributed sensing assisted by a possibly noisy channel from one party to the other. We begin with an example with distillable secret key but poor locally accessible sensing performance and show that an assisting channel substantially improves its performance. We then show that any shared state yielding positive private information can serve as a sensing resource after appropriate local coherent processing, and derive a quantitative lower bound on the locally accessible sensing capability after assistance. We further show that classical correlations alone provide no analogous guarantee. Finally, in a channel formulation, we show that a channel with positive private information allows nonzero locally accessible sensitivity when paired with a suitable assisting channel.
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All authors Yunkai Wang, Peixue Wu, Graeme Smith, Sisi Zhou
Optics
Outdoor 100-m-scale air waveguides
Andrew Goffin, Gregory Babic, Andrew DeRusha et al. (+3 more)
Optical power densities for standoff spectroscopy, remote sensing, directed energy, and free-space optical communications are limited by diffraction and adverse atmospheric conditions such as
turbulence, fog, and wind. Air waveguides, generated by ultrashort-pulsed
laser filamentation, are a promising approach for transmission and collection of optical signals over long distances, overcoming beam diffraction and, for point-like sources, inverse square signal falloff with distance. In this work, we demonstrate outdoor guiding for the first time over a record length of ~100 m, exceeding the prior (indoor) record of 42 m. We correlate air waveguide performance to a range of real atmospheric conditions including turbulent refractive index structure parameter ($C_n^2$) values up to ~$2.5\times10^{-14} m^{-2/3}$, crosswind speeds up to ~2 m/s, as well as temperature, pressure, and humidity variations. Accompanying propagation simulations provide insight into the real effects of these environmental perturbations, particularly crosswind, on waveguide performance and lifetime. Our results pave the way for quasi-continuous air waveguiding with kHz-scale repetition rate filaments in challenging outdoor environments.
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All authors Andrew Goffin, Gregory Babic, Andrew DeRusha, Maksim Livshits, Howard Milchberg, Patrick Skrodzki
Applied Physics · Cross-listed from cond-mat.stat-mech
Equilibrium Distributions for Strongly Nonlinear Many-Body Systems
Jialin Zhang, Yong Zhang and Hong Zhao
Obtaining
equilibrium distributions of nonlinear systems is essential for accurately computing macroscopic observables. Conventional theoretical corrections are typically limited to weak nonlinearities, where interaction terms can be treated as effectively uncorrelated perturbations and the random phase approximation applies. In this Letter, we develop a framework to determine
equilibrium distributions based on the generalized energy equipartition principle. Our approach recovers existing corrections in the weakly nonlinear regime and, crucially, remains valid for strong nonlinearities, where perturbative contributions become correlated and conventional approaches break down. Numerical simulations of the nonlinear Schrödinger equation, the Majda-McLaughlin-Tabak model, and the
Fermi-Pasta-Ulam-Tsingou model demonstrate accurate corrections for nonlinearities more than an order of magnitude stronger than those accessible to conventional theories.
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Medical Physics · Cross-listed from cs.CV
Efficient Noise Context-Aware Representation for Low-Dose CT Denoising
Minwoo Yu, N. Robert Bennett, Jongduk Baek et al. (+1 more)
While deep learning-based denoising has become widely adopted in low-dose CT, conventional models use generic architectures designed for natural images, failing to account for non-stationary and spatially correlated CT noise characteristics. To address this, we propose an Efficient Noise COntext-aware REpresentation (ENCORE) framework that explicitly leverages CT noise characteristics and anatomical features. First, we reformulate the noise synthesis procedure based on a realistic noise distribution beyond the conventional Gaussian approximation, establishing a rigorous foundation for training pair generation. Next, we extract local noise power and correlation contexts to guide the denoising process. To fully leverage the potential of noise context, we propose a FlyingConv module, which adaptively changes convolution weights for each local image region. Notably, our approach demonstrates substantial gains in both denoising quality and computational efficiency. Furthermore, manipulating the intensity of the noise context maps at inference time enables zero-shot conditional denoising, allowing for dynamic control over the output image texture. The entire pipeline is available at https://github.com/minwoo-yu/ENCORE.git
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All authors Minwoo Yu, N. Robert Bennett, Jongduk Baek, Adam S. Wang
Biological Physics · Cross-listed from q-bio.TO
History Matters: Damage-Mediated Amplification of Brain Deformation and Injury Risk under Repeated Head Impacts
Carson Cooper, Anu Tripathi, Genevieve Palardy et al. (+1 more)
Computational head models are typically applied to isolated impacts, leaving repeated head loading largely unexplored. An Ogden-Roxburgh Mullins damage formulation was implemented in a high-fidelity finite element head model to represent loading-history-dependent softening during cyclic
brain-tissue deformation. Repeated-loading histories derived from mixed martial arts head-impact data were applied and compared with damage-free hyperelastic (HE) and linear visco-hyperelastic (LVHE) model variants. Under five identical single-axis cycles, Mullins-type softening progressively increased strain and strain rate metrics relative to the HE model. Mullins-based injury probabilities progressively exceeded strain-based HE predictions and diverged from unchanged kinematics-based predictions, indicating that neglecting prior softening may underestimate injury risk. In a randomized twenty-cycle multiaxial sequence, cycles of similar kinematic intensity produced different deformation and injury-risk estimates depending on prior softening. HE and LVHE models predicted higher injury probabilities initially, whereas the Mullins-based model produced the largest later-cycle estimates and highest probability of at least one injury over the sequence. Regional amplification depended on loading direction and prior softening, with no direction-independent trend among
brain substructures. Gyral elements exhibited higher cumulative maximum principal strain than sulcal elements, which showed greater amplification relative to initial responses. These findings demonstrate that short-term damage-mediated softening can substantially amplify tissue deformation and injury-risk estimates beyond damage-free head models under the same loading histories. Further experimental characterization of cyclic
brain-tissue softening is needed to improve models of repeated head loading and traumatic
brain injury.
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All authors Carson Cooper, Anu Tripathi, Genevieve Palardy, Kshitiz Upadhyay