Physics and Society
Modeling the spatial growth of cities
Ulysse Marquis and Marc Barthelemy
The growth of cities has traditionally been studied from a population perspective, while urban expansion-its spatial growth-has often been approached qualitatively. However, characterizing and modeling this spatial expansion is crucial, particularly given its parallels with surface growth extensively studied in physics. Despite these similarities, approaches to urban expansion modeling are fragmented and scattered across various disciplines and contexts. In this review, we provide a comprehensive overview of the mathematical modeling of this complex phenomenon. We discuss the key challenges hindering progress and examine models inspired by statistical physics, economics and geography, and theoretical ecology. Finally, we highlight critical directions for future research in this interdisciplinary field.
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History and Philosophy of Physics
An account of the arrow of time when scale is surplus
Sean Gryb and Simon Friederich
Existing accounts of the cosmological arrow of time face a dilemma: generalist approaches that posit time-asymmetric laws lack independent motivation, while particularist approaches that invoke a Past Hypothesis face serious conceptual and explanatory problems. We propose a novel account that dispenses with the need for both time-asymmetric laws and a Past Hypothesis. Instead, it is centred around a
symmetry argument that reveals attractors and so-called 'Janus points'. The main idea is that the global spatial scale of the Universe is not empirically accessible, and should therefore be treated as surplus structure. By contrast, the Hubble parameter, which encodes the relative rate of change of scale, is empirically accessible. Once the scale redundancy is eliminated, the empirically meaningful description of
cosmic dynamics involves a drag-like variable that transforms in a way that preserves time-reversal invariance. The resulting space of dynamical possibilities possesses universal attractors and Janus points, giving rise to particular states in which observers experience a cosmological arrow of time akin to our own. We illustrate the proposal by applying it to cosmological and gravitational N-body models, showing how it accounts, respectively, for the rapid cooling of the early universe and its relative smoothness.
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Optics
When Higher Resolution Reduces Precision: Quantum Limits of Off-Axis Interferometric Scattering Microscopy
Felix Hitzelhammer, Jonathan Dong, Ulrich Hohenester et al. (+1 more)
Coherent interferometric scattering microscopy (iscat) enables nanoparticle tracking on microsecond timescales and with nanometer precision, and has become a key tool in structural and cellular biophysics. The achievable localization precision in such experiments is fundamentally limited by
photon shot noise. Here, we analyze three-dimensional localization precision under oblique illumination in iscat using the framework of (
Quantum) Fisher Information. We show that tilting the illumination can enhance localization precision and accuracy per detected
photon, while increasing robustness to defocusing. Surprisingly, rotating coherent scattering microscopy (rocs), which incoherently averages oblique illuminations, achieves higher spatial resolution but lower localization precision. Our results establish the
quantum limits of off-axis interferometric imaging and reveal that resolution and precision can behave in opposite ways – a key insight for designing next-generation coherent microscopes.
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All authors Felix Hitzelhammer, Jonathan Dong, Ulrich Hohenester, Thomas Juffmann
Atmospheric and Oceanic Physics
Global impacts of organic aerosol acidity on sulfate and cloud formation
Gargi Sengupta, Kunal Ghosh, Prithvi R. Jallu et al. (+1 more)
Organic aerosols (OA) comprise a major fraction of atmospheric particulate matter and frequently contain acidic species, yet their contribution to overall aerosol acidity has not been explicitly considered in global
climate models. We implement concentration-dependent OA acid dissociation, including recently demonstrated surface-specific effects, into the ECHAM-HAMMOZ global
climate model and assess the impacts on aqueous aerosol sulfate chemistry and aerosol–cloud–
climate interactions. We show that enhanced aerosol acidity from OA acid dissociation drives increased sulfate formation from aqueous-phase oxidation of $\mathrm{SO_2}$. The microphysics of additional secondary sulfate aerosol changes global cloud droplet number concentrations (CDNC), with enhancements up to $13.9\%$. Increased cloud formation leads to a significant global mean cooling effect with a shortwave cloud radiative forcing (SWCRF) up to $-0.97~\mathrm{W\,m^{-2}}$. We also find that surface-specific acid dissociation effects can further modify both aerosol chemistry and resulting aerosol–cloud–
climate responses, in some cases with even stronger impact than bulk acidity conditions. Our results demonstrate significant effects of considering OA acidity, as well as surface-specific phenomena, in global
climate models.
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All authors Gargi Sengupta, Kunal Ghosh, Prithvi R. Jallu, Nønne L. Prisle
Atomic Physics · Cross-listed from quant-ph
Non-reciprocal Synchronization in Thermal Rydberg Ensembles
Yunlong Xue and Zhengyang Bai
Optical non-reciprocity is a fundamental phenomenon in photonics. It is crucial for developing devices that rely on directional signal control, such as optical isolators and circulators. However, most research in this field has focused on systems in
equilibrium or steady states. In this work, we demonstrate a room-temperature Rydberg atomic platform where the unidirectional propagation of light acts as a switch to mediate time-crystalline-like collective oscillations through atomic synchronization. We find that thermal-motion-induced coupling asymmetry, enabled by counterpropagating probe and control fields, generates persistent oscillations; conversely, co-propagation quenches this effect. We identify, through both numerical and analytical approaches, the criteria for realizing optical non-reciprocity within a synchronization regime. These results provide key insights for
chiral quantum optics and promote the on-chip integration of non-reciprocal devices in nonequilibrium many-body systems.
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Accelerator Physics
Status of the MARS code
Igor Rakhno, Igor Tropint, Dali Georgobiani et al. (+1 more)
This report describes major features of the most recent version of the MARS code as well as ongoing developments. The list of features includes various options for geometry models, a beam line builder based on MADX code, import of geometry models in GDML format, use of structured and unstructured meshes for scoring purposes, an update to the recent TENDL library for a number of projectiles at low energies (up to 250 MeV), and a recently implemented method to calculate spatial distribution of residual dose in a single computer run without an intermediate source. Examples of the code application to various projects are presented as well.
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All authors Igor Rakhno, Igor Tropint, Dali Georgobiani, Alajos Makovec
Fluid Dynamics
oRANS: Online optimisation of RANS machine learning models with embedded high-fidelity data generation
Daniel Dehtyriov, Jonathan F. MacArt and Justin Sirignano
Deep learning (DL) has shown promise for flow simulations, but progress is constrained by the scarcity of high-fidelity training data, which is costly to generate and limited to few flow conditions. Closures trained offline on such data tend to overfit and fail to generalise to new regimes. We introduce an online optimisation framework for DL-based Reynolds-averaged Navier-Stokes (RANS) closures. Training data is generated by a simulation at direct numerical simulation (DNS) resolution embedded in a subdomain of the RANS domain. The RANS solution supplies boundary conditions to the embedded simulation, which provides the mean velocity and
turbulence statistics used to update the closure, which thereby adapts to the target flow without precomputed
datasets. The approach is developed on the stochastically forced Burgers equation and on turbulent channel flow at $Re_\tau=180$, 270, 395 and 590 with embedded domain lengths $1\leq L_0/L\leq 8$, and is then applied to spanwise-rotating channel flow at $Ro_b=0.15$ and $0.5$, a flow in which the Coriolis force vanishes from the equations of a linear eddy-viscosity closure. Online-optimised RANS models outperform offline-trained and literature-calibrated closures with modest embedded subdomains, and in the rotating channel recover the rotation-induced asymmetry from non-rotating inflow
turbulence and a rotation-blind closure. The learned coefficients are interpretable, recovering near-wall damping and, under rotation, the collapse of the eddy viscosity on the stabilised side. Performance degrades when boundary contamination dominates or domains are too short to capture low-wavenumber modes. This framework provides a route to data-adaptive machine learning closures without large precomputed training
datasets.
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Atmospheric and Oceanic Physics · Cross-listed from astro-ph.IM
Multi-faceted light pollution modelling and its application to the decline of artificial illuminance in France
Rolf Buhler, Philippe Deverchère, Christophe Plotard et al. (+1 more)
Artificial Light At Night (ALAN) has been increasing steadily over the past century, particularly during the last decade. This leads to rising light pollution, which is known to have adverse effects on living organisms, including humans. We present a new software package to model light pollution from ground radiance measurements. The software is called Otus 3 and incorporates innovative ALAN
diffusion models with different atmospheric profiles, cloud covers and urban emission functions. To date, light pollution modelling typically focused on calculating the zenith luminance of the skyglow produced by city lights. In Otus 3 we extend this and additionally model the horizontal illuminance on the ground, including the contributions from skyglow and the direct illumination. We applied Otus 3 to France using ground radiance data from the Visible Infrared Imaging Radiometer Suite (VIIRS). We calibrated our models using precise sky brightness measurements we obtained over 6 years at 139 different locations and make this
dataset publicly available. We produced the first artificial illuminance map for France for the periods of 2013-2018 and 2019-2024. We found that the artificial ground illuminance in the middle of the night decreased by 23 % between these two periods, in stark contrast to the global trend.
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All authors Rolf Buhler, Philippe Deverchère, Christophe Plotard, Sébastien Vauclair
Instrumentation and Detectors · Cross-listed from astro-ph.IM
Millimeter-Wavelength Lens-Absorber-Coupled Ti/Al Kinetic Inductance Detectors
Alejandro Pascual Laguna, Victor Rollano, Aimar Najarro-Fiandra et al. (+4 more)
This work presents Ti/Al bi-layer Microwave Kinetic Inductance Detectors (MKIDs) based on lens-coupled spiral absorbers as the quasi-optical coupling mechanism for millimeter-wavelength radiation detection. From simulations, the lens-coupled absorbers provide a 70% lens aperture efficiency in both polarizations over an octave band with a spiral array absorber and over 10% relative bandwidth with a single spiral. We have fabricated and measured two devices with bare Ti/Al MKIDs: a 3x3 cm chip with 9 pixels to characterize the optical response at 85 GHz of the two variations of the absorber; and a large format demonstrator with 253 spiral-array pixels showing potential towards a large format millimeter-wavelength camera. We estimate a sensitivity of 1 $\mathrm{mK}\cdot\mathrm{Hz}^{-0.5}$ and a 95% detector yield.
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All authors Alejandro Pascual Laguna, Victor Rollano, Aimar Najarro-Fiandra, David Rodriguez, Maria T. Magaz, Daniel Granados, Alicia Gomez
Atomic Physics
QED vacuum polarization in the Coulomb field of a nucleus: a method of high-order calculation
Sergey Volkov
A calculation of the QED
vacuum polarization potential in the Coulomb field of a pointlike
nucleus was presented in an earlier publication by the author and his collaborators. Corrections up to order $\alpha^2 (Z\alpha)^7$ were evaluated, where $Z$ is the
nuclear charge number and $Z\alpha$ is treated as an independent variable. These corrections correspond to two-loop Feynman graphs with proper propagators of
fermions in the external field. The calculation employed a reduction to free QED, leading to free QED Feynman graphs with up to eight independent loops. The method of calculation is described here in detail.
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Fluid Dynamics · Cross-listed from math.AP
On the existence of fibered three-dimensional perfect fluid equilibria without continuous Euclidean symmetry
Theodore D. Drivas, Tarek M. Elgindi and Daniel Ginsberg
Following Lortz, we construct a family of smooth steady states of the ideal, incompressible Euler equation in three dimensions that possess no continuous Euclidean
symmetry. As in Lortz, they do possess a planar reflection
symmetry and, as such, all the orbits of the velocity are closed. Different from Lortz, our construction has a discrete m-fold
symmetry and is foliated by invariant cylindrical level sets of a non-degenerate Bernoulli pressure. Such examples narrow the scope of validity of Grad's
conjecture that the only solutions with a continuous
symmetry can be fibered by pressure surfaces.
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Chemical Physics
Linear Response Selected Configuration Interaction
Peter Reinholdt, Erik Kjellgren and Jacob Kongsted
In this work, we extend selected configuration interaction (SCI) methods beyond energies and expectation values by introducing a linear response (LR) framework for molecular response properties. Existing SCI approaches are capable of approximating the energy of the full configuration interaction (FCI) wave function with high accuracy but at a much lower cost. However, conventional determinant selection will, by design, mainly select determinants that are expected to improve energies, and this can lead to the omission of many determinants that are important for wave function response. We address this by introducing two new selection criteria motivated by linear response theory. Using these extended determinant selection criteria, we demonstrate that LR-SCI can systematically converge toward the FCI limit for static polarizabilities. Using a damped LR formulation, we compute the water K-edge X-ray absorption spectrum in active spaces up to (10e, 58o). Finally, we use LR-SCI to compute NMR
spin-
spin coupling constants for water, where we find that accuracy beyond that offered by CCSDT can be achieved. Overall, LR-SCI offers a promising route to compute response properties with near-FCI accuracy to systems beyond the reach of exact FCI.
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Fluid Dynamics
A numerical stabilization scheme for the shallow shelf approximation
Tilda Westling Dolling, A. Clara J. Henry and Josefin Ahlkrona
We present the Thickness Stabilization Scheme (TSS), a numerical stabilization scheme suitable for the Shallow Shelf Approximation (SSA), one of the most widely-used models for large-scale Antarctic and Greenland ice sheet simulations. The TSS is constructed by inserting an adapted, explicit Euler thickness
evolution equation into the driving stress term, thereby treating the term implicitly. We investigate the applicability of TSS across low- and high-shear idealized scenarios, by altering the inflow velocity and initial ice thickness. TSS demonstrates an increase in the numerical stability of SSA, allowing large time-step sizes of dt = 50-100 years to remain numerically stable and accurate, while time-step sizes of dt > 5 in high-shear simulations show significant error without TSS. Remarkably, a time step size as large as dt = 10 000 years is numerically stable with TSS, albeit with a reduction in accuracy. TSS offers greater flexibility for ice-sheet modeling by allowing the re-allocation of computational resources. This method is applicable not only to ice-sheet modeling, including in coupled frameworks, but also to other vertically-integrated computational fluid dynamics problems that couple momentum and geometry
evolution equations.
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Instrumentation and Detectors · Cross-listed from astro-ph.IM
Measurements of the Birks' coefficient of GAGG:Ce using hard X-rays
Merlin Kole and Nicolas De Angelis
Inorganic scintillators continue to be widely used within astrophysical X-ray and gamma-ray detectors. This is in part thanks to the development of new scintillators, such as GAGG:Ce, as well as the availability of new scintillator readout sensors such as Silicon Photomultipliers and Silicon Drift Detectors. In order to use such scintillator materials for spectrometry or polarimetry, a detailed understanding of their response is important. One parameter that can affect the scintillator performance, particularly at lower
photon energies, is their Birks' coefficient, which correlates the relative light yield to the ionization energy density. While for many high-Z inorganic scintillators this effect can be ignored, for GAGG:Ce this appears to not be the case. Here we provide a measurement of the Birks' coefficient for GAGG:Ce using data from a detector irradiated in the 20-80~keV energy range at the LARIX-A X-ray beam in Ferrara, Italy. While the effects due to Birks' law are visible below 30 keV, they also significantly influence the performance of GAGG:Ce performance near one of the K-edges, affecting both the measured gain and the energy resolution. Here, we use beam test data to derive the Birks' coefficient from GAGG:Ce. The results indicate that for usage in hard X-ray and soft gamma-ray missions, this coefficient has a significant effect on the measurements.
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Optics
Probing a theoretical framework for a Photonic Extreme Learning Machine
Vicente Rocha, Duarte Silva, Felipe C. Moreira et al. (+3 more)
The development of computing paradigms alternative to von Neumann architectures has recently fueled significant progress in novel all-optical processing solutions. In this work, we investigate how the coherence properties can be exploited for computing by expanding information onto a higher-dimensional space in the photonic extreme learning machine framework. A theoretical framework is provided based on the transmission
matrix formalism, mapping the input plane onto the output camera plane, resulting in the establishment of the connection with complex extreme learning machines and derivation of upper bounds for the hidden space dimensionality as well as the form of the activation functions. Experiments using free-space propagation through a diffusive medium, performed in low-dimensional input space regimes, validate the model and the proposed
estimator for the dimensionality. Overall, the framework presented and the findings enclosed have the potential to foster further research in a multitude of directions, from the development of robust general-purpose all-optical hardware to a full-stack integration with optical sensing devices toward edge computing solutions.
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All authors Vicente Rocha, Duarte Silva, Felipe C. Moreira, Catarina S. Monteiro, Tiago D. Ferreira, Nuno A. Silva
Physics and Society
Dynamic roughening of cities driven by multiplicative noise
Martin Hendrick and Gabriele Manoli
The
evolution of urban landscapes is rapidly altering the surface of our
planet. Yet, our understanding of the urbanisation phenomenon remains far from complete. A fundamental challenge is to describe spatiotemporal changes in the built environment. A dynamic theory of urban
evolution should account for both vertical and horizontal city expansion, analogous to the dynamical behaviour of surface growth in physical and biological systems. Here we show that building-height dynamics in cities around the world are well described by a zero-dimensional
geometric Brownian motion (GBM), where multiplicative noise drives
stochastic fluctuations around a deterministic drift associated with economic growth. To account for intra-city correlations, we extend the GBM with spatial coupling, revealing how local interactions effectively mitigate noise-driven fluctuations and shape urban morphology. The continuum limit of this spatial model can be recasted into the Kardar-Parisi-Zhang (KPZ) equation and we find that empirical estimates of the roughness exponent are in the range of the KPZ prediction for most cities. Together, these results show that multiplicative noise, moderated by local interactions, governs the
evolution of urban roughness, anchoring spatiotemporal city dynamics in a well-established statistical physics framework.
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Optics
Impact of nonlinear spectral broadening on the phase noise properties of electro-optic frequency comb
Aleksandr Razumov, Yijia Cai, Jasper Riebesehl et al. (+5 more)
Electro-optic modulation is an attractive approach for generating flat, stable, and low-noise optical frequency combs with relatively high power per comb line. However, a key limitation of electro-optic combs is the restricted number of comb lines imposed by the available RF source power. To overcome this limitation, a nonlinear spectral broadening stage is typically employed. The phase noise characteristics of an electro-optic comb are well described by the standard phase noise model, which depends on two parameters: the seed
laser and the RF source phase noise. A fundamental question that arises is how nonlinear broadening processes affect the phase noise properties of the expanded comb. To address this, we employ coherent detection, digital signal processing, and subspace tracking. Our experimental results show that the nonlinearly broadened comb preserves the standard phase noise model of the input electro-optic comb. In other words, the nonlinear processes neither introduce additional phase noise terms nor amplify the existing contributions from the seed
laser and RF source. Hence, nonlinear broadening can be viewed as equivalent to driving the electro-optic comb with a much higher RF modulation power.
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All authors Aleksandr Razumov, Yijia Cai, Jasper Riebesehl, Eric Sillekens, Ronit Sohanpal, Francesco Da Ros, Zhixin Liu, Darko Zibar
Medical Physics
Dipolar order mapping based on spin-lock magnetic resonance imaging
Zijian Gao, Qianxue Shan, Ziqin Zhou et al. (+2 more)
Purpose: Inhomogeneous magnetization transfer (ihMT) effect reflects dipolar order with a dipolar relaxation time ($T_{1D}$), specific to motion-restricted macromolecules. We aim to quantify $T_{1D}$ using
spin-lock MRI technique. Methods: In the proposed method, we introduce a $T_{1D}$-specific ratio, denoted as $RATIO_{dosl}$. This ratio is derived from the distinct relaxation rate $R_{dosl}$, calculated as the difference between dual-frequency relaxation $R_{1\rho}^{dual}$ and single-frequency $R_{1\rho}^{single}$ relaxation measurements. A novel rotary-echo
spin-lock sequence was developed to enable dual-frequency
spin-lock acquisition. We established a framework to estimate $T_{1D}$, as well as the macromolecular pool fraction (MPF) map. The proposed approach was validated via numerical simulations, phantom studies, and demonstrated in vivo in human white matter. Results: Simulations revealed the high sensitivity of $RATIO_{dosl}$ to $T_{1D}$, and substantiated the accuracy and robustness of the proposed methods. Phantom experiments demonstrated robust ihMT contrast and confirmed the capability of $T_{1D}$ quantification via $RATIO_{dosl}$. In vivo studies supported the clinical viability of this approcah, achieving simultaneous $T_{1D}$ and MPF mapping using only three
spin-lock prepared images. Across ten healthy volunteers, the mean white matter $T_{1D}$ ranged from approximately 3.70 to 4.80 ms. Conclustion: We propose a novel method for $T_{1D}$ quantification based on
spin-lock MRI. By requiring only three contrast-prepared images, this technique provides a promising pathway for robust, rapid, and simultaneous $T_{1D}$ and MPF quantification with fewer confounds
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All authors Zijian Gao, Qianxue Shan, Ziqin Zhou, Ziqiang Yu, Weitian Chen
Optics
Plasmonic metamaterial time crystal
Tingwen Guo, Jules Sueiro, Gian Marcello Andolina et al. (+18 more)
Periodically driven optical materials and metamaterials have recently emerged as a promising platform for realizing photonic time
crystals (PTCs), which are systems whose optical properties are strongly and periodically modulated on timescales comparable to the optical cycle of light. These time-varying structures are the temporal counterparts of spatial photonic
crystals (SPCs), for which a large and periodic dielectric contrast is achieved spatially on wavelength scales. Just as SPCs have revolutionized control over light-matter interactions by engineering the photonic density of states in space, PTCs promise comparable breakthroughs from a fundamentally new perspective: a temporal one. However, harnessing such phenomena all-optically poses severe experimental challenges, as it requires order-unity modulation depths of a material's optical properties on ultrafast timescales comparable to the light cycle, a regime that has remained elusive to date. Here, we demonstrate the first all-optical realization of a photonic time
crystal, achieved with a surface plasmon cavity metamaterial operating at Terahertz (THz) frequencies. We demonstrate strong (near-unity) and coherent (sub-optical cycle) periodic driving of the plasmonic metamaterial enabled by field-induced dynamical modulation of the carriers' kinetic energy and effective mass - reaching up to 80% of their rest mass. Our spectroscopic measurements reveal a transition into the PTC regime mediated by an exceptional point, at which two Floquet-driven optical eigenmodes coalesce. In the PTC regime, emergent gain is shown to reduce plasmonic losses by more than 50% and we predict plasmonic lasing to be within experimental reach. These results pave the way for temporal engineering of losses and light-matter interactions in plasmonic systems, and establish a robust new platform for time-domain photonics.
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All authors Tingwen Guo, Jules Sueiro, Gian Marcello Andolina, Artem Levchuk, Stefano Ponzoni, Romain Grasset, Donald Monthe, Ian Aupiais, Dmitri Daineka, Javier Briatico, Thales VAG de Oliveira, Alexey Ponomaryov, Atiqa Arshad, Arjun Karimbana-Kandy, Gulloo Lal Prajapati, Igor Ilyakov, Jan-Christoph Deinert, Sebastian F. Maehrlein, Luca Perfetti, Marco Schiro, Yannis Laplace
Biological Physics
Elastic Energy Storage Mechanism in Hovering Animal Flight: A Discriminative Method Based on Wing Kinematics
Shijie Sheng, Jianghao Wu, Renxuan Bo et al. (+2 more)
Existing research has yet to reach a consensus on whether and how small flying animals utilize elastic energy storage mechanisms to reduce flight energy expenditure, and there is a lack of systematic and universal methods for assessment. To address these gaps, this study proposes a method to evaluate elastic energy storage capacity based on wing kinematic parameters (flapping amplitude and flapping frequency), grounded in the hypothesis that animals tend to minimize flight energy expenditure. By establishing a simplified power model, the study calculates the optimal kinematic parameters corresponding to the minimum mechanical power requirements under two extreme conditions: no elastic energy storage and complete elastic energy storage. These optimal parameters are then compared with measured data from various small flying animals. The results show that the measured parameters of hummingbirds, ladybugs, and rhinoceros beetles are close to the no-storage optimum, indicating relatively weak elastic energy storage capacity; whereas hoverflies, bumblebees, and honeybees align closely with the complete-storage optimum, suggesting strong elastic energy storage ability. Furthermore, the wing kinematic adjustment strategies these animals employ in response to changes in load or air density are consistent with the predicted elastic storage capacities. This study provides a systematic new approach for assessing biological elastic energy storage capacity and offers a theoretical basis for the low-power design of flapping wing micro air vehicles.
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All authors Shijie Sheng, Jianghao Wu, Renxuan Bo, Long Chen, Yanlai Zhang
Chemical Physics · Cross-listed from quant-ph
Any type of spectroscopy can be efficiently simulated on a quantum computer
Liam P. Flew and Ivan Kassal
Spectroscopy is the most important method for probing the structure of molecules. However, predicting molecular spectra on classical computers is computationally expensive, with the most accurate methods having a cost that grows exponentially with molecule size.
Quantum computers have been shown to simulate simple types of optical spectroscopy efficiently – with a cost
polynomial in molecule size – using methods such as time-dependent simulations of photoinduced wavepackets. Here, we show that any type of spectroscopy can be efficiently simulated on a
quantum computer using a time-domain approach, including spectroscopies of any order, any frequency range, and involving both electric and
magnetic transitions. Our method works by computing any spectroscopic correlation function based on the corresponding double-sided Feynman diagram, the canonical description of spectroscopic interactions. The approach can be used to simulate spectroscopy of both closed and open molecular systems using both digital and analog
quantum computers.
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Instrumentation and Detectors
Development of Deep Neural Network First-Level Hardware Track Trigger for the Belle II Experiment
Y. -X. Liu, T. Koga, H. Bae et al. (+20 more)
The Belle II experiment at the SuperKEKB accelerator is designed to explore physics beyond the Standard Model with unprecedented luminosity. As the beam intensity increased, the experiment faced significant challenges due to higher beam-induced background, leading to a high trigger rate and placing limitations on further luminosity increases. To address this problem, we developed trigger logic for tracking using deep neural network (DNN) technology on an FPGA for the Belle II hardware trigger system, employing high-level synthesis techniques. By leveraging drift time and hit pattern information from the Central Drift Chamber and incorporating a simplified self-
attention architecture, the DNN track trigger significantly improves track reconstruction performance at the hardware level. Compared to the existing neural track trigger, our implementation reduces the total track trigger rate by 37% while improving average efficiency for the signal tracks from 96% to 98% for charged tracks with transverse momentum > 0.3 GeV. This upgrade ensures the long-term viability of the Belle II data acquisition system as luminosity continues to increase.
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All authors Y. -X. Liu, T. Koga, H. Bae, Y. Yang, C. Kiesling, F. Meggendorfer, K. Unger, S. Hiesl, T. Forsthofer, A. Ishikawa, Y. Ahn, T. Ferber, I. Haide, G. Heine, C.-L. Hsu, A. Little, H. Nakazawa, M. Neu, L. Reuter, V. Savinov, Y. Unno, J. Yuan, Z. Xu
Computational Physics
A review on the Parameter Space Concept and its use for crystal structure determination
Matthias Zschornak, Muthu Vallinayagam, Melanie Nentwich et al. (+2 more)
We present a comprehensive review of the emerging
crystal structure determination method Parameter Space Concept (PSC), which solves and refines either partial or complete
crystal structures by mapping each experimental or theoretical observation as a
geometric interpretation, bypassing the conventional
Fourier inversion. The PSC utilizes only a few \xray (equivalently
neutron) diffraction amplitudes or intensities and turns them into piecewise analytic hyper-surfaces, called isosurfaces, embedded in a higher-dimensional orthonormal Cartesian space (Parameter Space (PS)). It reformulates the
crystal determination task into a
geometric interpretation, searching for a common intersection point of different isosurfaces. The art of defining various kinds of isosurfaces, based on signs, amplitude or intensity values, normalized ratios, and ranking of reflections, offers multiple choices of adapting methods in PSC based on available experimental or theoretical observations. The elegance of PSC stems from one-dimensional projections of atomic coordinates, enabling the construction of full three-dimensional
crystal structures by combining multiple projections. By these means, the user may explore homometric and non-homometric solutions within both centric and acentric structures with spatial resolution remarkably down to pm, even with a limited number of diffraction reflections. Having demonstrated the potential of PSC for various synthetic structures and exemplarily verified direct application to realistic
crystals, the origin and development of PSC methods are coherently discussed in this review. Notably, this review emphasizes the theoretical foundations, computational strategies, and potential extensions of PSC, outlining the roadmap for future applications of PSC in the broader context of structure determination from experimental diffraction observations.
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All authors Matthias Zschornak, Muthu Vallinayagam, Melanie Nentwich, Dirk C. Meyer, Karl Fischer
Computational Physics
Fully automated inverse co-optimization of templates and block copolymer blending recipes for DSA lithography
Yuhao Zhou, Huangyan Shen, Qingliang Song et al. (+3 more)
The directed self-assembly (DSA) of block copolymers (BCPs) offers a highly promising approach for the fabrication of contact holes or vertical interconnect access at sub-7nm technology nodes. To fabricate circular holes with precisely controlled size and positions, the self-assembly of block copolymers requires guidance from a properly designed template. Effectively parameterizing the template shape to enable efficient optimization remains a critical yet challenging problem. Moreover, the optimized template must possess excellent manufacturability for practical applications. In this work, we propose a Gaussian descriptor for characterizing the template shape with only two parameters. We further propose to use AB/AB binary blends instead of pure diblock copolymer to improve the adaptability of the block copolymer system to the template shape. The
Bayesian optimization (BO) is applied to co-optimize the binary blend and the template shape. Our results demonstrate that BO based on the Gaussian descriptor can efficiently yield the optimal templates for diverse multi-hole patterns, all leading to highly matched self-assembled morphologies. Moreover, by imposing constraints on the variation of
curvature of the template during optimization, superior manufacturability is ensured for each optimized template. It is noteworthy that each key parameter of the blend exhibits a relatively wide tunable window under the requirement of rather high precision. Our work provides valuable insights for advancing DSA technology, and thus potentially propels its practical applications forward.
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All authors Yuhao Zhou, Huangyan Shen, Qingliang Song, Qingshu Dong, Jianfeng Li, Weihua Li
Biological Physics · Cross-listed from math-ph
Ohta-Kawasaki Model Reveals Patterns on Multicomponent Vesicles
Wangbo Luo, Zhonghua Qiao and Yanxiang Zhao
We present a new mechanochemical modeling framework to explore the shape deformation and pattern formation in multicomponent vesicle membranes. In this framework, the shape of the membrane is described by an elastic bending model, while phase separation of membrane-bound activator
proteins is determined by an Ohta-Kawasaki (OK) model. The coupled dynamics consist of an overdamped force-balanced equation for the membrane geometry and an OK-type advection-reaction-
diffusion equation on the deformable membrane. We implement efficient spectral methods to simulate these dynamics in both two- and three-dimensions. Numerical experiments show that the model successfully reproduces a wide range of experimentally observed membrane morphologies \cite{baumgart2003imaging}. Taken together, the framework unifies
curvature mechanics, microphase separation, and active forcing, providing new insight into membrane-bounded multicomponent vesicle dynamics and a practical platform for studying multicomponent biomembrane morphology.
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Applied Physics · Cross-listed from quant-ph
Construction of the Complete Set of Maximally Entangled Basis Vectors for N-Qubit Systems
Chi-Chuan Hwang
In this study, we first use a three-
qubit system as an example to demonstrate the construction of
quantum circuits for the eight maximally entangled basis vectors, subsequently extending the approach to N-
qubit systems. We employ a random-number approach to generate maximally entangled basis vectors and their corresponding
circuits, while also detailing the required number of single-
qubit and CNOT gates. This approach not only provides a solid theoretical foundation but also establishes a practical technique for technological applications, bypassing the difficulty of storing large-scale encoding data.
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Optics
Focusing Terawatt-Scale Lasers Using Holographic Gaseous Lenses
Devdigvijay Singh, Ke Ou, Sida Cao et al. (+13 more)
The capabilities of the world's highest energy and peak-power pulsed
lasers are limited by optical damage, and further advances in high-intensity
laser science will require optics that are substantially more robust than existing components. We describe here the experimental demonstration of off-axis diffractive gaseous lenses capable of withstanding extreme
laser fluence and immune to cumulative damage. We used less than 8 mJ of energy from interfering ultraviolet
laser pulses to holographically write millimeter-scale diffractive gas lenses into an ozone, oxygen, and carbon-dioxide gas mixture. These lenses allowed us to focus, defocus, and collimate 532-nm, 210-mJ nanosecond
laser pulses at fluences up to 35 J/cm$^2$ and 800-nm, 35-fs, 28-mJ femtosecond pulses at intensities up to 55 TW/cm$^2$, achieving greater than 80% diffraction efficiency. We also show that that beam pointing, divergence, and diffraction efficiency are stable while operating at 10 Hz. These diffractive lenses are simple holograms, and the principles demonstrated here extended to other types of optics suggests that gaseous optics could enable arbitrary, damage-resistant manipulation of intense light for next-generation ultra-high-power
lasers.
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All authors Devdigvijay Singh, Ke Ou, Sida Cao, Victor M. Perez-Ramirez, Harsha Rajesh, Debolina Chakraborty, Elaine Koh, Caleb Redshaw, Pelin Dedeler, Albertine Oudin, Michelle M. Wang, Julia M. Mikhailova, Livia Lancia, Caterina Riconda, Pierre Michel, Matthew R. Edwards
Physics and Society
Homophily-induced Emergence of Biased Structures in LLM-based Multi-Agent AI Systems
Aliakbar Mehdizadeh and Martin Hilbert
This study examines how interactions among artificially intelligent (AI)
agents, guided by large
language models (LLMs), drive the
evolution of collective network structures. We ask LLM-driven
agents to grow a network by informing them about current link constellations. Our observations confirm that
agents consistently apply a preferential attachment mechanism, favoring connections to nodes with higher degrees. We systematically solicited more than a million decisions from four different LLMs, including Gemini, ChatGPT, Llama, and Claude. When social attributes such as age, gender, religion, and political orientation are incorporated, the resulting networks exhibit heightened assortativity, leading to the formation of distinct homophilic communities. This significantly alters the network
topology from what would be expected under a pure preferential attachment model alone. Political and religious attributes most significantly fragment the collective, fostering polarized subgroups, while age and gender yield more gradual structural shifts. Strikingly, LLMs also reveal asymmetric patterns in heterophilous ties, suggesting embedded directional biases reflective of societal norms. As autonomous AI
agents increasingly shape the architecture of online systems, these findings contribute to how algorithmic choices of generative AI collectives not only reshape network
topology, but offer critical insights into how AI-driven systems co-evolve and self-organize.
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