Optics · Cross-listed from cs.CV
Mismatch reconstruction theory for unknown measurement matrix in imaging through multimode fiber bending
Le Yang
Multimode fiber imaging requires strict matching between measurement value and measurement
matrix to achieve image reconstruction. However, in practical applications, the measurement
matrix often cannot be obtained due to unknown system configuration or difficulty in real-time
alignment after arbitrary fiber bending, resulting in the failure of traditional reconstruction
algorithms. This paper presents a novel mismatch reconstruction theory for solving the problem of image reconstruction when measurement
matrix is unknown. We first propose mismatch equation and design matched and calibration solution
algorithms to construct a new measurement
matrix. In addition, we also provide a detailed proof of these equations and
algorithms in the appendix. The experimental results show that under low noise levels, constructed
matrix can be used for matched pair in traditional reconstruction
algorithms, and reconstruct the original image successfully. Then, we analyze the impact of noise, computational precision and orthogonality on reconstruction performance. The results show that proposed
algorithms have a certain degree of robustness. Finally, we discuss the limitations and potential applications of this theory. The code is available: https://github.com/yanglebupt/mismatch-solution.
Read the full abstract ▾
General Physics
Optimal control approach to Olympic weightlifting exercise: Minimal model of the snatch pull
Hiroyuki Tajima, Hideyuki Nagao, Kenya Tanaka et al. (+4 more)
We theoretically investigate the biomechanical aspects of Olympic weightlifting within the framework of optimal control theory. The squared force and the rate of force development (RFD) defined by the time derivative of the force are taken into account in the evaluation functions of the first and second pull phases of the snatch motion. Focusing on the vertical trajectory of the barbell, we develop a minimal model to describe the mechanical characteristics of the weightlifting exercise. The calculated barbell trajectory agrees well with the experimental data obtained by
video analysis. Our study would be useful for the further development of mathematical models for weightlifting motions and related exercises.
Read the full abstract ▾
All authors Hiroyuki Tajima, Hideyuki Nagao, Kenya Tanaka, Hideaki Nishikawa, Eishiro Murakami, Akito Ida, Masataka Watanabe
Chemical Physics
Space charge and ion transport in aerosol neutralization: Toward a concentration-dependent alternative to the $N_it$ product
Kunal. Ghosh, Gargi Sengupta, Rukhsar Parveen et al. (+1 more)
In this study, we quantify how charged particle concentration affects the neutralization rate of aerosol particles, focusing on the role of ion dynamics shaped by internal electric fields arising from net space charge. Conventional neutralizer performance is typically evaluated using the $N_it$ product, which assumes quasi-neutral conditions and neglects electric fields from small charge imbalances. We demonstrate that internal electric fields become increasingly important at high aerosol concentrations and significantly influence neutralization dynamics. We develop a coupled ion–aerosol transport model in a two-dimensional axisymmetric geometry that includes ion generation, convection,
diffusion, recombination, attachment to aerosols, and wall loss, with self-consistent electric fields obtained from the Poisson equation. Results show that even small net charges generate electric fields that enhance ion drift and accelerate neutralization, effects not captured by traditional $N_it$-based approaches. Using a neutralization time metric, we find that neutralization becomes slower with increasing aerosol number concentration $N_p$, higher initial particle charge $q_0$, and smaller particle diameter $d_p$ when space charge is absent. When space charge is included, the influence of $q_0$ and $d_p$ diminishes, while $N_p$ becomes the dominant factor governing neutralization behavior. Accordingly, we propose a concentration-dependent analytical expression for mean charge relaxation that captures coupled ion–aerosol transport and space charge effects. The modeling framework presented here is applicable to laboratory instruments, industrial processes, and atmospheric environments where electrostatic interactions govern aerosol behavior.
Read the full abstract ▾
All authors Kunal. Ghosh, Gargi Sengupta, Rukhsar Parveen, Y. S. Mayya
Classical Physics
Note on Jackson's formalism of gauge transformation
V. Hnizdo
An outline is given of how Jackson may have obtained the inhomogeneous wave equations for the auxiliary functions $\Psi$ and $\bf V$ in his influential 2002 AJP paper on the transformation from the Lorenz gauge to other electromagnetic gauges. It clarifies the roles of these functions in the calculation of the Coulomb-gauge vector potential ${\bf A}_C$ by showing that while ${\bf A}_C$ is given directly $\nabla\times{\bf V}$, only the subtraction of $\nabla\Psi$ from the Lorenz-gauge vector potential ${\bf A}_L$ yields ${\bf A}_C$.
Read the full abstract ▾
Fluid Dynamics
Long-lived versus nocturnal stable atmospheric boundary layers: DNS characterisation, similarity theory, and regime classification
K. Chand, Cheng-Nian Xiao and Inanc Senocak
The stable atmospheric boundary layer (SABL) is broadly classified into two subtypes: the nocturnal SABL, driven primarily by surface cooling, and the long-lived SABL, in which ambient stratification coexists with surface cooling and persists well beyond a single diurnal cycle. Despite its prevalence in polar regions and over open oceans, the long-lived SABL has received comparatively little
attention, and a systematic direct numerical simulation (DNS) study distinguishing it from the nocturnal SABL has not previously been reported. Here we present DNS of long-lived SABLs at $Re_D=900$, contrasting weak and strong ambient stratification cases against a nocturnal SABL. A striking feature of the long-lived SABLs is the emergence of a multi-layered thermal structure – including an intermediate layer of reduced static stability capped by a buoyancy inversion – driven not by enhanced turbulent mixing, but by a stratification-induced reorganisation of the buoyancy field. Budget analyses identify a turbulent potential energy-centred transport mechanism absent in nocturnal SABLs, lending support to total-energy-based closure approaches. Assessment of an extended Monin–Obukhov similarity theory incorporating a composite length scale $L_*$ shows strong collapse of dimensionless gradients of velocity $\phi_m$ and potential temperature $\phi_h$, and a new similarity function for $\phi_h$ is proposed. Combining DNS with linear stability analysis, we construct a regime map delineating linearly stable, weakly stable, and very stable regimes within a two-parameter dimensionless space, demonstrating the inherently multi-parameter nature of long-lived SABLs and the limitations of single-parameter subgrid-scale parameterisations.
Read the full abstract ▾
Medical Physics
Optimizing Transmission FLASH Radiotherapy for Large-Field Post-Mastectomy Breast Treatment
Ahmal Jawad Zafar, Sunil William Dutta, Matthew Joseph Case et al. (+5 more)
We investigated the effects of scanning speed, beam configuration, and dose-rate modeling on the FLASH effect in post-mastectomy
proton transmission-beam (TB) planning and evaluated whether optimizing the spot-scanning path can enhance FLASH. Five left-sided post-mastectomy patients (32 Gy in 5 fractions) were replanned with single-energy (249 MeV) tangential TBs plus a clinical en face background beam. FLASH was evaluated with two models: Krieger's FLASH effectiveness model (FEM) and Folkerts' average dose-rate (ADR) framework. Plans used conventional pencil-beam scanning, split-field delivery, and GA-optimized spot sequences, with vertical scan speeds varied from 10 to 20 mm/ms. FLASH in normal tissues was defined as the percentage of voxels meeting the threshold (>= 4 Gy at >= 40 Gy/s); once a voxel met the criterion, a dose-adjustment factor of 0.67 was applied. The FLASH effect was highly sensitive to scanning pattern and model choice. Increasing vertical scan speed from 10 to 20 mm/ms increased FLASH in the CTV by 22% (ADR) and 12% (FEM); in skin it rose from 41.4% to 58.8% (ADR) and from 8.4% to 13.1% (FEM). Split-field delivery increased the temporal separation between vertical spot columns and yielded superior FLASH, including up to a 9.2 Gy reduction in CTV Dmean with ADR. GA-based optimization shortened scan time and achieved FLASH comparable to split-field delivery, with a CTV Dmean reduction of 7.87 Gy (ADR-GA) and skin Dmean reductions of 2-3 Gy. These findings indicate that FLASH outcomes depend strongly on scanning trajectory, scan speed, and model selection. In addition, path-minimizing spot-delivery optimization (e.g., GA) can further improve dose-rate distributions in healthy voxels.
Read the full abstract ▾
All authors Ahmal Jawad Zafar, Sunil William Dutta, Matthew Joseph Case, Zachary Diamond, Duncan Bohannon, Reshma Jagsi, Xiaofeng Yang, Jun Zhou
Atomic Physics · Cross-listed from cond-mat.quant-gas
Collisional relaxation in shielded dipolar molecular gases
Reuben R. W. Wang and John L. Bohn
We discuss the influence of collisions on the dynamics of an ultracold gas whose constituents interact via dipolar forces. This dynamics is governed by the elastic scattering cross section of the molecules, which is to some extent under the experimentalist's control. We compare side-by-side several different situations, highlighting their similarities and differences. These situations are collisions between: 1) point dipoles; 2) electric-field-shielded polar molecules; and 3) microwave-shielded polar molecules, including the effect of microwave ellipticity.
Read the full abstract ▾
Applied Physics · Cross-listed from q-bio.PE
Ambush strategy impacts species predominance and coexistence in rock-paper-scissors models
J. Menezes and R. Barbalho
We investigate the adaptive Ambush strategy in cyclic models following the rules of the spatial rock-paper-scissors game. In our model, individuals of one species possess cognitive abilities to perceive environmental cues and assess the local density of the species they dominate in the spatial competition for natural resources. Based on this assessment, they either initiate a direct attack or, if the local concentration of target individuals does not justify the risk, reposition strategically to prepare an ambush. To quantify the evolutionary consequences of these behavioural strategies, we perform
stochastic simulations, analysing emergent spatial patterns and the dependence of species densities on the threshold used by individuals to decide between immediate attack or anticipation. Our findings reveal that, despite being designed to enhance efficiency, cognitive strategies can reduce the abundance of the species due to the constraints of cyclic dominance. We identify an optimal decision threshold: attacking only when the local density of target individuals exceeds 15% provides the best balance between selection risk and long-term persistence. Furthermore, the Ambush strategy benefits low-mobility organisms, increasing coexistence probabilities by up to 53%. These results deepen the understanding of adaptive decision-making in spatial ecology, linking cognitive complexity to ecosystem resilience and extinction risk.
Read the full abstract ▾
Space Physics · Cross-listed from astro-ph.SR
HelioFill: Diffusion-Based Model for EUV Reconstruction of the Solar Farside
Firas Ben Ameur, Rayan Dhib, Yahia Battach et al. (+4 more)
The loss of STEREO-B in 2014 created a persistent blind spot in Extreme Ultraviolet (EUV) imaging of the
solar farside. We present HelioFill, to the authors' knowledge, the first denoising-
diffusion inpainting model that restores full-Sun EUV coverage by synthesizing the STEREO-B sector from Earth-side (SDO) and STEREO-A views. Trained on full-Sun maps from 2011-2014 (when SDO+STEREO-A+B provided 360 degrees coverage), HelioFill couples a latent
diffusion backbone with domain-specific additions: spectral gating, confidence weighting, and auxiliary regularizers, to produce operationally suitable 304 Angstrom reconstructions. On held-out data, the model preserves the observed hemisphere with mean SSIM 0.871 and mean PSNR 25.56 dB, while reconstructing the masked hemisphere with mean SSIM 0.801 and mean PSNR 17.41 dB and reducing boundary error by approximately 21 percent (Seam L2) compared to a state-of-the-art
diffusion inpainting model. The generated maps maintain cross-limb continuity and coronal morphology (loops, active regions, and coronal-hole boundaries), supporting synoptic products and cleaner inner-boundary conditions for coronal/heliospheric models. By filling observational gaps with observationally consistent EUV emission, HelioFill maintains continuity of full-Sun monitoring and complements helioseismic farside detections, illustrating how
diffusion models can extend the effective utility of existing
solar imaging assets for space-weather operations.
Read the full abstract ▾
All authors Firas Ben Ameur, Rayan Dhib, Yahia Battach, Andrea Lani, Matteo Parsani, Omar Knio, Stefaan Poedts
Atomic Physics · Cross-listed from quant-ph
Fractatomic Physics: An Invitation with Atomic Stability and Rydberg States in Fractal Spaces
Nhat A. Nghiem and Trung V. Phan
We explore the physical
quantum properties of atoms in fractal spaces, both as a theoretical generalization of normal integer-dimensional Euclidean spaces and as an experimentally realizable setting. We identify the threshold of fractality at which Ehrenfest atomic instability emerges, where the Schrödinger equation describing the wave-function of a single electron orbiting around an atom becomes scale-free, and discuss the potential of observing this phenomena in laboratory settings. We then study the Rydberg states of stable atoms using the Wentzel-Kramers-Brillouin approximation, along with a proposed extension for the Langer modification, in general fractal dimensionalities. We show that fractal space atoms near instability explode in size even at low-number excited state, making them highly suitable to induce strong entanglements and foster long-range many-body interactions. We argue that atomic physics in fractal spaces – “fractatomic physics” – is a rich research avenue deserving of further theoretical and experimental investigations.
Read the full abstract ▾
Medical Physics · Cross-listed from cs.CV
Foundation Models in Medical Image Analysis: A Systematic Review and Meta-Analysis
Praveenbalaji Rajendran, Mojtaba Safari, Wenfeng He et al. (+4 more)
Recent advancements in foundation models (FMs) have catalyzed a paradigm shift in medical image analysis. Unlike traditional task-specific artificial intelligence (AI) models, FMs leverage large-scale
datasets to learn generalized representations that can be adapted to downstream clinical applications. Despite the rapid proliferation of FM research in medical imaging, there is a lack of unified synthesis that systematically maps the
evolution of architectures, training paradigms, and clinical applications across modalities. To address this gap, this review provides a comprehensive and structured synthesis of FMs in medical image analysis by systematically organizing studies into two primary categories:
vision-only foundation models (VFMs) and
vision-
language foundation models (VLFMs), based on their architectural foundations, training strategies, and downstream clinical tasks. A quantitative analysis was conducted on both VFMs and VLFMs to characterize temporal trends in
dataset utilization and application domains, along with pooled performance and subgroup analyses. We also critically discuss persistent challenges, including cross-domain generalization, computational scalability, FM evaluation,
fairness, and deployment. Finally, we identify key future research directions aimed at enhancing the robustness, interpretability, and clinical integration of FMs, thereby accelerating their translation into real-world medical practice.
Read the full abstract ▾
All authors Praveenbalaji Rajendran, Mojtaba Safari, Wenfeng He, Mingzhe Hu, Shansong Wang, Jun Zhou, Xiaofeng Yang
Classical Physics
The nonlinearity of helical springs: An energy-based approach
Saša Ilijić, Ana Babić, Dora Ivrlač et al. (+1 more)
A general expression for the elastic potential energy of a helical spring is derived using the basic concepts of elasticity theory and geometry. Both the translational and the rotational displacement of the spring's moving ends are considered. The resulting expression is employed to derive the general relation between force and spring height, and corrections to Hooke's law are discussed. The results can be used to estimate the magnitude of non-linear effects in realistic situations, to predict how springs unwind under load, and to determine the spring constant when spring ends are allowed to rotate freely. This energy-based approach is suitable for inclusion in advanced mechanics courses. The results are validated via measurements on steel springs using a simple experimental setup appropriate for use in physics laboratories at all levels.
Read the full abstract ▾
All authors Saša Ilijić, Ana Babić, Dora Ivrlač, Andrew DeBenedictis
Computational Physics · Cross-listed from cond-mat.mtrl-sci
Intermediate-Band Formation in Tm3+-doped Ca2SnO4: A Wide-Gap Oxide Host for Visible-Light Absorption and Energy Applications
Shah Hussain, Sikander Azam, Umme Habiba et al. (+4 more)
Rare earth doping is an effective way to convert chemically stable
oxides into multifunctional materials with coupled electronic, optical, and
magnetic properties. We present first principles calculations of pristine and Tm3+ doped Ca2SnO4 to understand how localized 4f states change the structural, electronic,
magnetic, and optical behavior of the host. Pristine Ca2SnO4 is a mechanically stable, wide band gap
insulator with mostly ionic covalent bonding and diamagnetic character. Replacing Ca2+ with Tm3+ introduces several key changes: (i) localized Tm 4f states create intermediate levels inside the wide gap, reducing the optical band gap; (ii) exchange and
spin orbit interactions generate strong local
magnetic moments and
spin asymmetry near the conduction band; (iii) electron localization function analysis shows enhanced covalency and electron pockets that stabilize luminescent centers; and (iv) the optical response shows visible range absorption, refractive index features, and low energy plasmon peaks while maintaining high energy dielectric stability. These effects make Tm doped Ca2SnO4 a mechanically robust, optically tunable, and magnetically active
oxide phosphor suitable for red emission, intermediate band photovoltaics, and
spin photon coupling. More broadly, our results show how targeted rare earth substitution can enable multifunctionality in wide gap stannates and guide the design of next generation spintronic photonic
oxides.
Read the full abstract ▾
All authors Shah Hussain, Sikander Azam, Umme Habiba, Qaiser Rafiq, Amin Ur Rahman, Hamada H. Amer, Yasir Saeed
Data Analysis and Statistics · Cross-listed from astro-ph.IM
On the use of the Derivative Approximation for Likelihoods for Gravitational Wave Inference
Josiel Mendonça Soares de Souza and Miguel Quartin
Posterior inference on the more than a dozen parameters governing a gravitational wave (GW) event is challenging. A typical MCMC analysis can take around $100$ CPU hours, and next generation GW observatories will detect many thousands of events. Here we present a thorough comparison of the accuracy and computational cost of the Fisher
Matrix, Derivative Approximation for Likelihoods (DALI) and traditional MCMC methods. We find that using DALI, which extends the traditional Fisher
Matrix (FM) method to higher orders, allows for a good approximation of the posterior with a $55$ times smaller computational cost, and that the cost-benefit of the doublet-DALI is better than that of the triplet-DALI. We also show that the singlet-DALI, a hybrid MCMC-Fisher method, is much more accurate than the traditional FM and 10 times faster than the doublet-DALI. A large effort has been invested in
forecasting the science case of different detector configurations, and the ability of making fast yet accurate estimations of the posteriors is an important step forward. We also introduce version 1.0 of the public GWDALI code, which incorporates automatic differentiation, modern waveforms and an optimized parameter decomposition.
Read the full abstract ▾
Plasma Physics
Probing Flying-Focus Wakefields
Aaron Liberman, Anton Golovanov, Sheroy Tata et al. (+2 more)
Flying-focus wakefields, which can propagate with a tunable velocity along the optical axis, are promising solutions to electron dephasing in
laser-wakefield accelerators. This is accomplished by a combination of spatio-temporal couplings and focusing with an axiparabola, a specialized optical element which produces a quasi-Bessel beam. If implemented, dephasingless acceleration would allow for a hitherto unachievable mixture of high acceleration gradients and long acceleration lengths. Here, we conduct an in-depth study of the structure and behavior of such a flying-focus wakefield, through a combination of direct imaging and simulations. We show the stability of the wakefield structures, explore how the wakefield evolves with changes of density, study the effects of ionization on the wakefield structure with a variety of gases, and analyze the importance of the focusing position. These insights shed light onto this novel wakefield regime and bring understanding that is important to the realization of dephasingless acceleration.
Read the full abstract ▾
All authors Aaron Liberman, Anton Golovanov, Sheroy Tata, Anda-Maria Talposi, Victor Malka
Fluid Dynamics
Cavitation onset in transient pressure fields
Pierre Coulombel and Fabian Denner
While it is well known that cavitation occurs in
liquids under tension, no universally accepted criterion for its onset in transient pressure fields exists. We propose a precise definition of the critical tension for cavitation in transient pressure fields that bridges the gap between quasi-static and dynamic regimes, identifying cavitation as the transition of the bubble radius to a dynamically unstable state. This threshold depends on the instantaneous state of the gas-
liquid system and, when combined with an appropriate set of dimensionless parameters, yields a self-similar description of cavitation onset. Phase maps for different
liquids reveal a minimum tension required for the onset of cavitation, determined by the duration of the tension event and the initial bubble size, whereby the well-known Blake threshold is the lower bound for cavitation across all conditions.
Read the full abstract ▾
Instrumentation and Detectors
Ionization quenching factors and W-values of low-energy H$_2^+$ and He$^+$ ions in Ar gas at low pressure measured with a bulk resistive MICROMEGAS
A. Foresi, G. Antonelli, C. Avanzini et al. (+15 more)
The ionization quenching factor, the fraction of an ion's initial kinetic energy lost through ionization in a medium, was measured for H$_2^+$ and He$^+$ ions within the 2.5-5 keV energy range in an Ar/CO$_2$ gas mixture at pressures between 75 and 150 mbar. The mixture was contained in the active volume of a MICROMEGAS type Micro Pattern Gaseous Detector (MPGD), which was connected to an ion source via a high
vacuum system. The results showed a significant decrease in ionization as the ion energy decreased, although no dependence on gas pressure was observed within the low pressure range studied. Additionally, significant deviations from the predictions of SRIM (Stopping and Range of Ions in Matter) simulations were found. These measurements also allowed the first determination of $W$ values (the average energy required to create an electron-ion pair in the gas) for H$_2^+$ and He$^+$ ions in Ar at this particular energy range, which had not been previously explored for these projectile-target combinations. These findings are essential for accurate ion energy reconstruction in low-pressure MPGDs, with particular relevance for space-based energetic neutral atom detection, as proposed by the Italian Space Agency's SWEATERS project.
Read the full abstract ▾
All authors A. Foresi, G. Antonelli, C. Avanzini, G. Balestri, G. Bigongiari, E. Bossini, M.G. Callaini, R. Carosi, E. De Angelis, F. Frasconi, P. Maestro, F. Morsani, A. Mura, L. Orsini, G. Petragnani, F. Pilo, R. Rispoli, G. Terreni
Optics
Ultra High Sensitivity Soil Moisture Detection Using Photonic Crystal Cavity with SIW Technology
Justin Jose and Nikhil Kumar
Soil nutrients and water content are two crucial factors that significantly affect agricultural production yields. Hence, monitoring and measuring the water content and soil type are critical requirements. This study proposes a two-dimensional structure of photonic
crystals centered around a symmetrical cross-shaped slot. The cross-slots act as resonators, and the photonic
crystals surrounding the slots tune the resonance frequency of the resonators to enhance mode confinement within the resonator. The various resonant modes are located in the 2.1 GHz, 5.2 GHz, and 8.1 GHz bands, which correspond to the S band, C band, and X band, respectively. These bands are used to compare the absorption, whereas the upper resonant mode is of the order of 20 GHz. Band structure analysis was performed using the Plane Wave Method (PWM). The resonant frequency is computed using a 3D electromagnetic (EM) simulation software that utilizes the Finite Element Method (FEM) and lies in the radiation mode region of the band structure of the photonic
crystal. Varying the incident angle had a negligible effect on the absorption characteristics of the sensor, allowing it to produce accurate sensing results regardless of the incident angle. The sensor's sensitivity is maximized using this design, which results in a sensitivity of 85.4 % in the 2.1 GHz resonant frequency, which is much higher than that of a single column of photonic
crystal-based SIW, resulting in 50.6 % of sensitivity at 2.1 GHz, at which there is a frequency shift of the order of GHz. In contrast, in the proposed design, the frequency shift is on the order of MHz, resulting in ultra-high sensitivity.
Read the full abstract ▾
Medical Physics
Real-time MRI-based fetal femur length measurement
Johannes Barcsay, Sara Neves Silva, Jordina Aviles Verdera et al. (+4 more)
Purpose: To develop and evaluate a real-time method for automatic planning and measurement of fetal femur length - an important indicator of antenatal growth - during MRI. While routinely assessed by ultrasound, MRI-based femur length measurements remain challenging due to bone-slice misalignment, fetal motion, and the need for manual assessment. Methods: A low-latency 3D U-Net was trained on 59 scans acquired at 0.55T (gestational age 18-40 weeks) to localise the proximal and distal endpoints of the femur. These coordinates were employed to automatically adapt a 30-second EPI sequence for in-plane femur coverage in real-time. Retrospective evaluation was performed in 72 scans (19-39 weeks, including 19 pathological cases), and real-time testing in 24 cases (17-39 weeks). Automated results were compared with manual expert annotations and, in 57/72 cases, with matched clinical ultrasound measurements. Precision was evaluated against inter-observer variability and analysed across gestational age and maternal BMI. Furthermore, bilateral femur length consistency was evaluated. Results: Retrospective analysis demonstrated a mean endpoint localisation error of 5.5 mm and femur length deviation of 3.0 mm. Among the 49/72 cases with both femora automatically extracted, the left-right difference was 2.8+-2.7 mm. Precision was unaffected by maternal BMI (p>0.05), but correlated with gestational age (p<0.05). Real-time planning and assessment were successful in 22/24 cases, with a mean deviation of 4.2 mm. Conclusions: A real-time, automated method for MRI-based femur length measurement was developed, enabling precise, motion-robust, and operator-independent growth assessment, supporting future large-scale evaluation in growth-compromised pregnancies.
Read the full abstract ▾
All authors Johannes Barcsay, Sara Neves Silva, Jordina Aviles Verdera, Charline Bradshaw, Mary Rutherford, Susanne Schulz-Heise, Jana Hutter
Fluid Dynamics
State estimation in homogeneous isotropic turbulence using super-resolution with a 4DVar training algorithm
Markus Weyrauch, Moritz Linkmann and Jacob Page
Variational data assimilation and machine-learning based super-resolution are two alternative approaches to state estimation in turbulent flows. The former is an optimisation problem featuring a time series of coarse observations, the latter usually requires a library of high-resolution 'ground truth' data. We show that the classic '4DVar' data assimilation
algorithm can be used to train neural networks for super-resolution in three-dimensional isotropic
turbulence without the need for high-resolution reference data. To do this, we adapt a pseudo-spectral version of the fully-differentiable JAX-CFD solver (Kochkov et al, Proc. Nat. Acad. Sci. 118, 2021) to three-dimensional flows and combine it with a convolutional neural network for super-resolution. As a result we are able to include entire trajectories in our loss function which is minimised with gradient-based optimisation to define the neural network weights. We show that the resulting neural networks outperform 4DVar for state estimation at initial time over a wide variety of metrics, though 4DVar leads to more robust predictions towards the end of its assimilation window. We also present a hybrid approach in which the trained neural network output is used to initialise 4DVar. The resulting performance is more than twice as accurate as other state estimation strategies for all times and performs well even beyond known limiting lengthscales, all without requiring access to high-resolution measurements at any point.
Read the full abstract ▾
Optics · Cross-listed from quant-ph
Countermeasures for Trojan-Horse Attacks on self-compensating all-fiber polarization modulator
Alberto De Toni, Aynur Cemre Aka, Costantino Agnesi et al. (+3 more)
Quantum Key Distribution (QKD) leverages the principles of
quantum mechanics to exchange a secret key between two parties. Unlike classical cryptographic systems, the security of QKD is not reliant on computational assumptions but is instead rooted in the fundamental laws of physics. In a QKD protocol, any attempt by an eavesdropper to intercept the key is detectable: this provides an unprecedented level of security, making QKD an attractive solution for secure communication in an era increasingly threatened by the advent of
quantum computers and their potential to break classical cryptographic systems. However, QKD also faces several practical challenges such as transmission loss and noise in
quantum channels, finite key size effects, and implementation flaws in QKD devices. Addressing these issues is crucial for the large-scale deployment of QKD and the realization of a global
quantum internet. A whole body of research is dedicated to the hacking of the
quantum states source, for example using Trojan-Horse attacks (THAs), where the eavesdropper injects light into the system and analyzes the back-reflected signal. In this paper, we study the vulnerabilities against THAs of the iPOGNAC encoder, first introduced in Avesani, Agnesi et al., to propose adapted countermeasures that can mitigate such attacks.
Read the full abstract ▾
All authors Alberto De Toni, Aynur Cemre Aka, Costantino Agnesi, Davide Giacomo Marangon, Giuseppe Vallone, Paolo Villoresi
Optics · Cross-listed from quant-ph
Long-term analysis of efficient-BB84 4-node network with optical switches in metropolitan environment
Alberto De Toni, Edoardo Bortolozzo, Alessandro Emanuele et al. (+5 more)
Quantum Key Distribution (QKD) is a leading technology for enabling information-theoretic secure communication, with protocols such as BB84 and its variants already deployed in practical field implementations. As QKD evolves from point-to-point links to multi-node networks, scalability and cost-effectiveness become central challenges. Among the approaches to address these issues, efficient-BB84 has shown durable and reliable performances, while optical switching techniques enable flexible, scalable, and cost-efficient integration of QKD into existing infrastructures. In this work, we present an active QKD network in a production environment, employing efficient-BB84 and optical switching, orchestrated in a coordinated manner, emphasizing their potential to support robust, future-proof
quantum-secure communication systems.
Read the full abstract ▾
All authors Alberto De Toni, Edoardo Bortolozzo, Alessandro Emanuele, Marco Venturini, Luca Calderaro, Marco Avesani, Giuseppe Vallone, Paolo Villoresi
Atmospheric and Oceanic Physics · Cross-listed from astro-ph.IM
Optical turbulence forecast for ground-based astronomy and free-space optical communication
Elena Masciadri, Alessio Turchi, Camilo Weinberger et al. (+2 more)
Forecasting optical
turbulence in the Earth's atmosphere has been an ambitious challenge for the astronomical scientific community for several decades. While earlier research primarily focused on whether it was possible to predict optical
turbulence and its vertical distribution, current efforts are more concentrated on the accuracy achievable at different timescales, the efficiency of various
forecasting methods and the contributions of new statistical approaches, such as auto-regression and machine learning to this field. In this contribution, I will present the state of the art of the research conducted by our group, positioned within the international research scenery. Most of our past activity has been primarily focused on ground-based astronomy but recent advancements in space research opened new opportunities for applications in the free-space optical communication.
Read the full abstract ▾
All authors Elena Masciadri, Alessio Turchi, Camilo Weinberger, Marlene De Sepibus, Luca Fini
Computational Physics · Cross-listed from cs.LG
Efficient High-Accuracy PDEs Solver with the Linear Attention Neural Operator
Ming Zhong and Zhenya Yan
Neural operators offer a powerful data-driven framework for learning mappings between function spaces, in which the
transformer-based neural operator architecture faces a fundamental scalability-accuracy trade-off: softmax
attention provides excellent fidelity but incurs quadratic complexity $\mathcal{O}(N^2 d)$ in the number of mesh points $N$ and hidden dimension $d$, while linear
attention variants reduce cost to $\mathcal{O}(N d^2)$ but often suffer significant accuracy degradation. To address the aforementioned challenge, in this paper, we present a novel type of neural operators, Linear
Attention Neural Operator (LANO), which achieves both scalability and high accuracy by reformulating
attention through an
agent-based mechanism. LANO resolves this dilemma by introducing a compact set of $M$
agent tokens $(M \ll N)$ that mediate global interactions among $N$
tokens. This
agent attention mechanism yields an operator layer with linear complexity $\mathcal{O}(MN d)$ while preserving the expressive power of softmax
attention. Theoretically, we demonstrate the universal approximation property, thereby demonstrating improved conditioning and stability properties. Empirically, LANO surpasses current state-of-the-art neural PDE solvers, including Transolver with slice-based softmax
attention, achieving average $19.5\%$ accuracy improvement across standard
benchmarks. By bridging the gap between linear complexity and softmax-level performance, LANO establishes a scalable, high-accuracy foundation for scientific machine learning applications.
Read the full abstract ▾
Physics and Society
Generalizing Condorcet's Jury Theorem to Social Networks
Dan Braha and Marcus A.M. de Aguiar
We generalize Condorcet's jury
theorem (CJT) to socially connected populations in which
agents revise discrete choices on a network in the presence of zealots. Free
agents receive privately informative signals about the correct alternative and, at each update, either retain their state or imitate a uniformly chosen neighbor (free or zealot). For finite networks, we derive closed-form stationary laws for vote counts, and we characterize the corresponding vote-share limits as the number of free voters tends to infinity. For majority rule – both in binary and multi-alternative settings – we obtain an exact accuracy limit in closed form via the regularized incomplete beta function. For plurality rule, we establish sharp closed-form lower bounds on accuracy, expressed in terms of regularized incomplete beta functions. Under an absolute-majority condition for the correct alternative, both majority and plurality accuracies strictly exceed the accuracy of any single voter, showing that informative signals, coupled through social interaction, are amplified at the group level. These results extend CJT beyond independence and provide closed-form accuracy
benchmarks for networked decision systems in social, biological, and engineered settings.
Read the full abstract ▾
Computational Physics · Cross-listed from math.OC
Equivalence of additive and parametric pinning control protocols for systems of weakly coupled oscillators
Riccardo Muolo and Yuzuru Kato
Controlling the behavior of nonlinear systems on networks is a paramount task in control theory, in particular the control of synchronization, given its vast applicability. In this work, we focus on pinning control and we examine two different approaches: the first, more common in engineering applications, where the control is implemented through an external input (additive pinning); the other, where the parameters of the pinned nodes are varied (parametric pinning). By means of the phase reduction technique, we show that the two pinning approaches are equivalent for weakly coupled systems exhibiting periodic oscillatory behaviors. Through numerical simulations, we validate the claim for a system of coupled Stuart–Landau oscillators. Our results pave the way for further applications of pinning control in real-world systems.
Read the full abstract ▾
Computational Physics
Thermal Conductivity Estimation of Thermoelectric Materials with Uncertainty Quantification Using Bayesian Physics-Informed Neural Networks
Hyeonbin Moon, Hanbin Cho, Wabi Demeke et al. (+2 more)
Characterizing the temperature-dependent thermal conductivity is challenging because the property varies strongly with temperature and reliable heat flow measurement, not just temperature sensing, is difficult under experimental conditions. Here, we present a physics informed deep learning framework that infers conductivity solely from sparse electric potential measurements. We first develop a deterministic physics-informed neural network (PINN) that embeds coupled thermoelectric transport equations as soft constraints, enabling simultaneous recovery of spatial temperature, voltage, and conductivity profiles without temperature data. The deterministic PINN achieves accurate inference under noise-free conditions, yet its predictions degrade when measurement noise is introduced. To address this, we extend the framework to a
Bayesian PINN, which models network parameters probabilistically and employs
Hamiltonian Monte Carlo (HMC) sampling for posterior inference. This extension produces robust thermal conductivity estimates and, importantly, provides credible intervals that quantify uncertainty from sparse and noisy data. Numerical experiments confirm that the
Bayesian PINN not only preserves predictive accuracy under noise but also reveals inference bias and enables uncertainty aware interpretation of material properties. Together, the deterministic and
Bayesian formulations establish a scalable and generalizable alternative to conventional methods for determining temperature-dependent properties, offering physics- consistent and risk-aware property inference for thermoelectric systems and other functional materials where direct temperature sensing is impractical
Read the full abstract ▾
All authors Hyeonbin Moon, Hanbin Cho, Wabi Demeke, Byungki Ryu, Seunghwa Ryu
Computational Physics
Scalable cell filter nudged elastic band (CFNEB) for large-scale transition-path calculations
Qiuhan Jia, Jiuyang Shi and Jian Sun
The nudged elastic band (NEB) method is one of the most widely used techniques for determining minimum-energy reaction pathways and activation barriers between known initial and final states. However, conventional implementations face steep computational scaling with system size, which makes nucleation-type transitions in realistically large supercells practically inaccessible. In this work, we develop a scalable
cell-filter nudged elastic band (CFNEB) framework that enables efficient transition-path calculations in systems containing up to $10^5$ atoms. The method combines a deformation-based
cell filtering scheme, which treats
lattice vectors as generalized coordinates while removing spurious rotational degrees of freedom, with an adaptive image insertion and deletion strategy that dynamically refines the reaction path. We implement CFNEB both within the ASE environment and in a fully GPU-accelerated version using the Graphics Processing Units Molecular Dynamics (GPUMD) engine, achieving throughput on the order of $10^6$ atom$\cdot$steps per second on consumer GPUs. We demonstrate the method on two representative systems: the layer-by-layer $\beta$-$\lambda$ transition in $Ti_3O_5$ and the nucleation-driven graphite-to-diamond transformation. These examples illustrate that CFNEB not only reproduces known concerted pathways but also captures spontaneous
symmetry breaking toward nucleated mechanisms when the simulation
cell is sufficiently large. Our results establish CFNEB as a practical route to exploring realistic transition mechanisms in large-scale solid-state systems.
Read the full abstract ▾
Space Physics · Cross-listed from astro-ph.SR
Properties of current sheets in two-dimensional tearing-mediated incompressible magnetohydrodynamic turbulence
Chen Shi, Marco Velli, Nikos Sioulas et al. (+1 more)
It is well known that the nonlinear
evolution of magnetohydrodynamic (MHD)
turbulence generates current sheets. In the
solar wind
turbulence, current sheets are frequently observed and they are believed to be an important pathway for the
turbulence energy to dissipate and heat the
plasma. In this study, we perform a comprehensive analysis of current sheets in a high-resolution two-dimensional simulation of balanced, incompressible MHD
turbulence. The simulation parameters are selected such that tearing mode instability is triggered and plasmoids are generated throughout the simulation domain. We develop an automated method to identify current sheets and accurately quantify their key parameters including thickness ($a$), length ($L$), and Lundquist number ($S$). Before the triggering of tearing instability, the current sheet lengths are mostly comparable to the energy injection scale. After the tearing mode onsets, smaller current sheets with lower Lundquist numbers are generated. While power-law scaling relations between $L$ and $a$ and between $a/L$ and $S$ are observed, no clear correlation is found between the upstream
magnetic field strength and thickness $a$. Finally, although the
turbulence energy shows anisotropy between the directions parallel and perpendicular to the local
magnetic field increment, we do not observe a direct correspondence between the shape of the current sheets and that of the
turbulence “eddies.” These results suggest that one needs to be cautious when applying the scale-dependent dynamic
alignment model to the analysis of current sheets in MHD
turbulence.
Read the full abstract ▾
All authors Chen Shi, Marco Velli, Nikos Sioulas, Zijin Zhang
Optics
Hybrid Integration of InGaN Lasers in a Foundry-Fabricated Visible-Light Photonics Platform
Xin Mu, Frank Weiss, Hongyao Chua et al. (+9 more)
Visible-spectrum photonic integrated
circuits (PICs) present compact and scalable solutions for emerging technologies including
quantum computing, biosensing, and virtual/augmented reality. Realizing their full potential requires the development of scalable visible-light-source integration methods compatible with high-volume manufacturing and capable of delivering high optical coupling efficiencies. Here, we demonstrate passive-
alignment flip-chip bonding of 450-nm InGaN
laser diodes onto a foundry-fabricated visible-light silicon (Si) photonics platform with silicon nitride (SiN) waveguides, thermo-optic (TO) devices, and photodetectors. Hybrid
laser integration is realized using a sub-micron-precision die bonder equipped with a
vision alignment system and a heatable pickup tool, allowing independent placement of multiple
lasers onto a single Si chip. Co-design of the
lasers and Si photonics, with lithographically defined
alignment marks and mechanical stoppers, enables precise postbonding
alignment. Efficient optical coupling between
lasers and the SiN waveguides is demonstrated, with a minimum measured coupling loss of 1.1 dB. We achieve a maximum on-chip optical power of 60.7 mW and an on-chip wall-plug efficiency of 7.8%, the highest reported for hybrid-integrated visible-spectrum
lasers, to our knowledge. An active PIC is also shown, integrating a bonded
laser, an on-chip photodetector for power monitoring, and a thermo-optic switch for optical routing and variable attenuation. Overall, this work highlights passive-
alignment flip-chip bonding as a practical, high-performance approach for integrating
lasers onto visible-spectrum PICs. We envision that continued refinement of this technique within our photonics platform will support increasingly complex PICs with integrated
lasers spanning the visible spectrum.
Read the full abstract ▾
All authors Xin Mu, Frank Weiss, Hongyao Chua, Robert Lawrowski, Jared C. Mikkelsen, John N. Straguzzi, Hannes Wahn, Piyush Kumar, Guo-Qiang Lo, Joyce K. S. Poon, Mariel Jama, Wesley D. Sacher