Chemical Physics
A Density-Based Continuous Local Symmetry Measure
Duc Anh Lai and Devin A. Matthews
Although continuous
symmetry theory has attracted increasing
attention in modern chemistry, local
symmetry remains under-investigated. As a consequence, the relationship between
symmetry and chemical behavior is often obscured, limiting the practical use of fuzzy
symmetry measures. In this study, we introduce a novel framework for evaluating local
symmetry based on electron density localization, and present continuous
symmetry representations for several representative molecules. Our approach not only quantitatively captures global
symmetry, but also reveals distinctive features of
symmetry in a local chemical environment. The related concept, local chirality or chirotopicity, is also discussed. Overall, the proposed local
symmetry and chirality measures provide valuable insights into molecular structure and structure-property relationships.
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Optics · Cross-listed from quant-ph
Boundary Floquet Control of Bulk non-Hermitian Systems
Yu-Min Hu, Yu-Bo Shi, Linhu Li et al. (+5 more)
Boundary perturbations are generally irrelevant for bulk properties in the thermodynamic limit, as they are edge-confined and subextensive. We show that this expectation breaks down in boundary-driven systems exhibiting the non-Hermitian skin effect, where arbitrarily weak boundary Floquet driving reconstructs bulk quasienergy spectra and dynamics. We develop a Floquet non-Bloch band theory that extends generalized Brillouin-zone methods to boundary-driven systems at arbitrary driving frequencies, overcoming the lack of a general framework beyond high-frequency approximations. With representative single- and two-band models, we demonstrate that the boundary driving frequency tunes non-Bloch parity-time
symmetry breaking, while its amplitude acts as a finite-size control parameter. Our work establishes boundary Floquet control as a general route for manipulating bulk properties, opening a new avenue for dynamical engineering in driven open systems.
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All authors Yu-Min Hu, Yu-Bo Shi, Linhu Li, Gianluca Teza, Ching Hua Lee, Roderich Moessner, Shu Zhang, Sen Mu
Instrumentation and Detectors · Cross-listed from hep-ph
Dark Matter Detection Using Phonon Sensing in Amorphous Materials
Itay M. Bloch, Simon Knapen, Xinran Li et al. (+2 more)
We present a concept for a tabletop-scale detector with an amorphous target designed to search for dark matter absorption into
phonon excitations. In crystalline materials, absorption occurs only at narrow resonances where the dark matter mass matches a zero momentum optical
phonon mode, whereas amorphous targets provide a broadband response that can substantially enhance the absorption rate away from these resonances. The predicted backgrounds arise from the relaxation of disorder-induced metastable defects in the amorphous target, as well as from low-energy noise intrinsic to superconducting
phonon sensors. A prototype detector with a target mass of only a few $\mu$g could provide broadband sensitivity to dark
photon absorption across the 50 meV-200 meV mass range, probing up to two orders of magnitude beyond existing constraints.
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All authors Itay M. Bloch, Simon Knapen, Xinran Li, Amalia Madden, Giacomo Marocco
Geophysics · Cross-listed from cs.LG
Unveiling the Mechanism of Continuous Representation Full-Waveform Inversion: A Wave Based Neural Tangent Kernel Framework
Ruihua Chen, Yisi Luo, Bangyu Wu et al. (+1 more)
Full-waveform inversion (FWI) estimates physical parameters in the wave equation from limited measurements and has been widely applied in geophysical exploration, medical imaging, and non-destructive testing. Conventional FWI methods are limited by their notorious sensitivity to the accuracy of the initial models. Recent progress in continuous representation FWI (CR-FWI) demonstrates that representing parameter models with a coordinate-based neural network, such as implicit neural representation (INR), can mitigate the dependence on initial models. However, its underlying mechanism remains unclear, and INR-based FWI shows slower high-frequency convergence. In this work, we investigate the general CR-FWI framework and develop a unified theoretical understanding by extending the neural tangent kernel (NTK) for FWI to establish a wave-based NTK framework. Unlike standard NTK, our analysis reveals that wave-based NTK is not constant, both at initialization and during training, due to the inherent nonlinearity of FWI. We further show that the
eigenvalue decay behavior of the wave-based NTK can explain why CR-FWI alleviates the dependency on initial models and shows slower high-frequency convergence. Building on these insights, we propose several CR-FWI methods with tailored
eigenvalue decay properties for FWI, including a novel hybrid representation combining INR and multi-resolution grid (termed IG-FWI) that achieves a more balanced trade-off between robustness and high-frequency convergence rate. Applications in geophysical exploration on Marmousi, 2D SEG/EAGE Salt and Overthrust, 2004 BP model, and the more realistic 2014 Chevron models show the superior performance of our proposed methods compared to conventional FWI and existing INR-based FWI methods.
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All authors Ruihua Chen, Yisi Luo, Bangyu Wu, Deyu Meng
Computational Physics
Development and large-scale benchmarks of a protein–ligand absolute binding free energy toolkit
Yu Liu, Ailun Wang, Yu Xia et al. (+2 more)
Absolute binding free energy (ABFE) calculations offer a theoretically rigorous approach for predicting
protein–ligand binding affinities without the scaffold constraints of relative binding free energy (RBFE) perturbations. However, broad adoption of ABFE in high-throughput hit discovery campaigns has been hindered by high computational costs and a lack of large-scale validation. Here, we present Felis, an open-source, automated, and scalable toolkit designed for high-throughput ABFE calculations. Paired with ByteFF, a previously developed data-driven molecular mechanics force field for drug-like molecules, Felis achieves ranking performance comparable to state-of-the-art RBFE methods on a diverse
dataset comprising 43
protein targets and 859 ligands. Furthermore, we demonstrate robust convergence and ranking performance of Felis on a more challenging KRAS(G12D)
dataset, where some ligands and the cofactor are highly charged. Crucially, all Felis predictions in this study were generated in a strict zero-shot manner, eschewing custom force-field modifications and alchemical schedule fine-tuning. This demonstrates the viability of Felis as an effective, ready-to-use tool for computational structure-based drug design.
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All authors Yu Liu, Ailun Wang, Yu Xia, Zhi Wang, Wen Yan
Chemical Physics
An Accurate Tensorial Model for Prediction of Full Zeolite NMR Spectra
Carlos Bornes, Chiheb Ben Mahmoud, Volker L. Deringer et al. (+2 more)
Solid state
nuclear magnetic resonance (ss-NMR) is one of the most sensitive and popular techniques for structure elucidation in geometrically complex crystalline materials, such as zeolites. Synergistic support from computational modelling is vital to interpret experimental spectra, and relate ss-NMR to atomistic models. Nevertheless, computational predictions are hindered by the high expense of calculating
magnetic shielding (MS) and electric field gradient (EFG) tensors from first principles. In this work, we leverage a novel tensorial machine learning approach to train a general model for predicting complete NMR tensors. We demonstrate the utility of the approach for a diverse
dataset of zeolitic materials and NMR-active
nuclei ($^{27}$Al, $^{29}$Si, $^{17}$O, $^{23}$Na and $^{1}$H), predicting all NMR observables to a high degree of precision. These observables are then translated into predictions of the full $^{27}$Al and $^{29}$Si ss-nMR spectra for the exemplary zeolite RTH. Thus, this work opens a pathway to accurate, high-throughput NMR simulation for large-scale and realistic models of chemically complex zeolites.
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All authors Carlos Bornes, Chiheb Ben Mahmoud, Volker L. Deringer, Christopher J. Heard, Lukáš Grajciar
Chemical Physics
Microscopic view of materials properties of liquids: An atomic scale perspective
Jaeyun Moon
Microscopic understanding of
liquid properties is essential for advancing a wide range of applications from energy applications such as
nuclear reactors and batteries to biomedical applications including drug delivery and microfluidics. However, intrinsic dynamic disorder and lack of structural periodicity in
liquids have presented fundamental challenges in developing rigorous microscopic theories of their thermodynamic and dynamic behavior. Recent breakthroughs in computational power and experimental metrologies have driven significant progress in unraveling the complex atomic scale dynamics of
liquids. In this Review, we provide a brief historical context of
liquid state physics and explore recent advances through theoretical, computational, and experimental approaches. For theoretical and computational approaches, instantaneous normal mode and velocity autocorrelation function calculations are discussed. For experiments, we focus on X-ray and
neutron scattering techniques that probe
liquid dynamics at the atomic level. Finally, we highlight emerging opportunities and future directions in the study of
liquid atomic dynamics.
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Atomic and Molecular Clusters · Cross-listed from cond-mat.mtrl-sci
Characterizing High-Capacity Janus Aminobenzene-Graphene Anode for Sodium-Ion Batteries with Machine Learning
Claudia Islas-Vargas, L. Ricardo Montoya, Carlos A. Vital-José et al. (+3 more)
Sodium-ion batteries require anodes that combine high capacity, low operating voltage, fast Na-ion transport, and mechanical stability, which conventional anodes struggle to deliver. Here, we use the SpookyNet machine-learning force field (MLFF) together with all-electron density-functional theory calculations to characterize Na storage in aminobenzene-functionalized Janus
graphene (Na$_x$AB) at room-temperature. Simulations across state of charge reveal a three-stage storage mechanism-site-specific adsorption at aminobenzene groups and Na$_n$@AB$_m$ structure formation, followed by interlayer gallery filling-contrasting the multi-stage pore-, graphite-interlayer-, and defect-controlled behavior in hard carbon. This leads to an OCV profile with an extended low-voltage plateau of 0.15 V vs. Na/Na$^{+}$, an estimated gravimetric capacity of $\sim$400 mAh g$^{-1}$, negligible volume change, and Na diffusivities of $\sim10^{-6}$ cm$^{2}$ s$^{-1}$, two to three orders of magnitude higher than in hard carbon. Our results establish Janus aminobenzene-
graphene as a promising, structurally defined high-capacity Na-ion anode and illustrate the power of MLFF-based simulations for characterizing electrode materials.
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All authors Claudia Islas-Vargas, L. Ricardo Montoya, Carlos A. Vital-José, Oliver T. Unke, Klaus-Robert Müller, Huziel E. Sauceda
Applied Physics · Cross-listed from quant-ph
Polymer identification via undetected photons using a low footprint nonlinear interferometer
Atta Ur Rehman Sherwani, Emma Pearce, Philipp Hildenstein et al. (+5 more)
Plastic pollution has become a critical global challenge, with microplastics pervading ecosystems and entering human food chains. Effectively monitoring this widespread contamination demands rapid, reliable, and portable material identification techniques that often elude conventional Raman and FTIR spectroscopy. Undetected
photon spectroscopy within a nonlinear interferometer (NLI) offers a solution, allowing the
retrieval of mid-infrared absorption spectra by detecting only near-infrared signal
photons using standard silicon-based technology. Here, we demonstrate a highly compact, micro-integrated, thermally-stabilised NLI with a Michelson-like geometry designed for the rapid spectroscopy of plastics. We benchmarked its room-temperature performance, demonstrating a signal-to-noise ratio of 34 with a measurement rate of 100 Hz and a spectral resolution of 6 cm$^{-1}$. We show that we can accurately and rapidly retrieve the characteristic vibrational absorption spectra of common
polymers such as polypropylene, polyethene, and polystyrene, without using mid-infrared technology. These results establish our compact module as a promising field-deployable platform for robust, real-time environmental monitoring systems and other mid-infrared spectroscopy applications.
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All authors Atta Ur Rehman Sherwani, Emma Pearce, Philipp Hildenstein, Felix Mauerhoff, Alexander Sahm, Katrin Paschke, Helen M. Chrzanowski, Sven Ramelow
Physics and Society · Cross-listed from cs.IT
Parametric and structure-aware information theory for multi-scale analysis of composition
Rohit Sahasrabuddhe and Renaud Lambiotte
Compositional data is common across the natural and social sciences, requiring methods to measure the diversity of compositions and the heterogeneity of collections of them. Via Bregman geometry, a strictly concave diversity index induces a measure of heterogeneity that decomposes across scales. A canonical example is Shannon
entropy inducing mutual information. We develop this framework by incorporating category similarity into $\alpha$-logarithmic
entropy, a parametric diversity index. We disprove an existing general concavity result and prove that, for $\alpha=3$, the region of strict concavity is always convex, complementing previous results for $\alpha=1$ and $2$. The resulting geometry provides methods to compare compositions substantially faster than optimal transport. Applied to occupation compositions across England and Wales, they reveal distinct regionalisations based on different notions of occupation relatedness. Applied to ecological data, they recover established patterns of functional and taxonomic $\beta$-diversity, and reveal sensitivity to the diversity parameter.
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Optics
Broadband Asymmetric Transmission with Wide Spectral Tunability based on Substrate-Embedded Silicon Nanoring Arrays
Ruihan Ma, Yuqing Cheng and Mengtao Sun
In this work, we theoretically propose a broadband asymmetric transmission (AT) device based on periodic Si nanoring arrays embedded in a SiO2 substrate. Results indicate that the device achieves a remarkable broadband AT effect in the near-infrared region (1750-2400 nm), with forward transmissivity exceeding 0.8 (maximum of 0.98), backward transmissivity less than 0.15 (minimum of 0.015) and an isolation ratio (IR) reaching a maximum of 17.8 dB at 2280 nm. Furthermore, the transmissivity spectrum exhibits excellent scalability and tunability through uniform scaling of the structure, allowing the operational band to be tailored across a wide spectral range, from 890 to 3300 nm. This Si-based nanostructure offers a robust and flexible platform for applications in optical isolation, multi-channel sensing, and integrated photonic
circuits.
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Plasma Physics
Optical smoothing broadens cross beam energy transfer resonance
Y. Lalaire, C. Ruyer, A. Debayle et al. (+7 more)
We use the theoretical framework introduced in the companion paper to provide simple formulas as regards the resonance conditions for CBET with smoothed
laser beams.Our analytical CBET model with optical smoothing shows that these fusion-critical
lasers produce a significantly broader resonance than conventional plane wave models predict. In particular, temporal smoothing, as used in many high energy
laser facilities, and flow components normal to the CBET ion acoustic waves, significantly modify the power transfer between smoothed beams. Our model predicts that the energy transfer rate out of resonance is substantially higher with optical smoothing than without, a result that has profound implications for optimizing predicting and interpreting future fusion experiments. We provide a simple criterion which pinpoints the
laser and
plasma parameters for which
laser smoothing impacts CBET. These findings pave the way for experimental investigations in high-energy-density physics and fusion energy.
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All authors Y. Lalaire, C. Ruyer, A. Debayle, G. Bouchard, R. Capdessus, A. Fusaro, P. Loiseau, L. Masse, P. E. Masson-Laborde, D. Bénisti
Applied Physics · Cross-listed from cond-mat.mtrl-sci
Universal inverse-cube thickness scaling of projectile penetration energy in ultrathin films
Alessio Zaccone and Tim W. Sirk
Ultrathin films of widely different materials exhibit a dramatic enhancement of projectile penetration resistance under high–velocity impact. Despite extensive simulations and experiments, a unifying physical explanation has remained elusive. Here we show that the thickness dependence of the specific penetration energy obeys a universal law, $E_p^*(h)=E_{p,\infty}^*+B h^{-3}$, independent of chemical composition and degree of disorder. The inverse–cube scaling is traced back to a finite–size correction to the effective shear modulus arising from the suppression of long–wavelength nonaffine deformation modes in confined solids. The scaling quantitatively describes impact data for multilayer
graphene,
graphene oxide, and
polymer thin films, revealing a common elastic origin for nanoscale impact resistance.
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Medical Physics
First Standard Quantification of Ultrasound Attenuation in Healthy Periodontal Soft Tissues In Vivo
Daria Poul, Amanda Rodriguez Betancourt, Ankita Samal et al. (+6 more)
This study presents the first quantifications of ultrasound attenuation in oral soft tissues using validated standard techniques and serves as foundational step in advancing quantitative ultrasound (QUS) imaging in dentistry. Current standards of care in clinics for diagnosing periodontal diseases such as inflammation are limited by subjectivity, qualitive assessment, and late-stage indication. As a result, the application of ultrasonography is emerging as a surrogate for non-invasive and quantitative assessments and a relatively new research area with significant potential biomarkers to be explored. Many QUS analyses rely on quantifying ultrasound attenuation coefficient (UAC), as a confounding factor. Here, in a swine cohort (N=10), we characterized the high-frequency (24 MHz) UAC of healthy periodontal tissues (gingiva) in vivo. UAC were estimated using spectral difference method. Five interproximal oral sites were imaged from four oral quadrants: Premolar 3-Mesial, Premolar3-Distal, Premolar4-Distal, Molar1-Distal, and Molar2-Distal. A total of 162 oral sites were analyzed. The respective medians (1st-quartile|3rd-quartile) UACs for these oral sites were 1.66 (1.25|1.99), 1.37 (1.06|1.64), 0.99 (0.8|1.25), 1.08 (0.89|1.47), and 1.28 (0.94|1.24) dB/MHz.cm. The gingival attenuation mean at Premolar3-Mesial was significantly higher than any other oral sites while the rest of them showed non-significance difference in their means. Across all non-significant oral sites, the average UAC was 1.17 dB/MHz.cm with a standard deviation of 0.49 dB/MHz.cm. This work not only characterized an important acoustic property of oral tissues for the first time but also contributes to future development of a number of QUS biomarkers for periodontal/dental healthcare that rely on accurate attenuation knowledge.
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All authors Daria Poul, Amanda Rodriguez Betancourt, Ankita Samal, Carole Quesada, Ted Lynch, Cristel Baiu, J. Brian Fowlkes, Hsun-Liang Chan, Oliver D. Kripfgans
Physics and Society
The benefits and biases of seeing the world's cities through marathons
Andrew Renninger
Marathons are now common ways of seeing cities, yet little is known about how representative their routes are. Using 311 marathon routes across five continents, we compare landmarks and amenities along the course with those elsewhere in the same city, finding that museums are 15.7 times denser near the route and that the median city has about 8.5 times more luxury brands near the route than elsewhere in the city. These patterns persist under perturbed routes with the same start and finish lines: monuments and landmarks, in particular, are more prevalent on the race course than on similar alternative routes, suggesting that marathons function as intentionally selective urban portraits.
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Plasma Physics
On the influence of optical smoothing techniques on cross-beam energy transfer
Y. Lalaire, C. Ruyer, A. Debayle et al. (+6 more)
In the context of inertial confinement fusion (ICF) experiments, spatial and temporal
laser beam smoothing techniques are used to control the beams propagation in hohlraum
plasmas. Currently, spatial and temporal smoothing are either neglected or not properly taken into account in the inline cross beam energy transfer (CBET) models included in the hydrodynamic codes dedicated to the design of these experiments. In some cases, which we will highlight in this study, this simplification leads to important errors in the power transfer of importance for the implosion
symmetry of the capsule, either in the direct or indirect drive ICF configurations. In a recent study [A. Oudin et al., Phys.
Plasmas 32, 042706 (2025)], we demonstrated the necessity of accounting for spatial smoothing when modeling CBET, provided that the beams do not have the same wavelength. This work presents a linear kinetic model compared with Hera paraxial fluid simulations and compared with the Smilei particle-in-
cell code, demonstrating the important influence of smoothing by spectral dispersion on CBET. Moreover, we demonstrate the importance of accounting for the
plasma velocity profile, the beam modulation bandwidth, and the spectral dispersion to better predict the power exchanged between the beams. Additionally, we reveal a strong sensitivity of this power transfer to the synchronization of the phase modulators.
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All authors Y. Lalaire, C. Ruyer, A. Debayle, G. Bouchard, A. Fusaro, P. Loiseau, L. Masse, P. E. Masson-Laborde, D. Bénisti
Optics
Phonon-polaritonic skyrmions: Transition from bubble- to Néel-type
Florian Mangold, Enrico Baù, Lin Nan et al. (+6 more)
Optical skyrmions are members of the emerging topological branch of solid-state physics and photonics, allowing for control over topological light textures through light-matter interactions. However, in nanophotonics their practical application has been severely limited by high inherent losses in plasmonic materials, resulting in the lack of tunability between different topological properties. Here, we utilize the strong dispersion of silicon carbide thin films to realize highly confined surface
phonon-polariton skyrmion
lattices, which we image via near-field microscopy. We experimentally demonstrate topological tuning between bubble- and Néel-type skyrmions, a unique advantage that polar dielectrics offer over most existing approaches. Changing the excitation wavelength by only 10% switches the skyrmion type, revealed by examination of the skyrmion number density contrast. Analysis of domain wall size and steepness in analogy to
magnetic materials also confirms this transition. Our results are a starting point to investigate other topological features in phononic systems such as merons, skyrmion bags, and other complex structured light fields. Furthermore, strong light-matter hybridization and nonlinear effects owing to anharmonicity of the
phonons may be observed in the future, possibly leading towards the discovery of polaritonic skyrmion-skyrmion interactions and hence applications in
topology-based information processing.
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All authors Florian Mangold, Enrico Baù, Lin Nan, Julian Schwab, Thorsten Gölz, Andrea Mancini, Bettina Frank, Andreas Tittl, Harald Giessen
Physics and Society
Gender shapes the relationship between productivity and journal prestige in science
Vitor H. Ribeiro, Andre S. Sunahara, Golnaz Shahtahmassebi et al. (+2 more)
Gender disparities in academia manifest and persist in various aspects of the scientific enterprise, yet their influence on the interplay between research productivity and journal prestige remains underexplored. Here we analyze the academic trajectories of over 6,000 elite Brazilian researchers by jointly tracking their annual productivity and the average prestige of the journals in which they publish. By projecting individual career years onto a standardized productivity-prestige plane and applying
Bayesian hierarchical modeling, we find that male researchers are more likely to follow productivity-oriented trajectories and are markedly overrepresented in the hyperprolific region of this plane. Female peers, in contrast, more often occupy regions that prioritize journal prestige over publication quantity. Although male researchers publish more throughout their careers, their female counterparts achieve comparable or higher average journal prestige, particularly in later career stages and among outlier individuals. Male researchers also exhibit greater temporal persistence in their productivity and impact levels and are especially averse to simultaneously changing both metrics compared to their female peers. Among non-outliers, productivity and career age have a negative overall impact on the average journal prestige of researchers of both genders, with slightly stronger effects observed among female researchers; however, these patterns vary across disciplines, highlighting the complexity and heterogeneity of academic careers.
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All authors Vitor H. Ribeiro, Andre S. Sunahara, Golnaz Shahtahmassebi, Matjaz Perc, Haroldo V. Ribeiro
Physics and Society · Cross-listed from q-bio.PE
Epidemic reproduction numbers in spatial networks
Zahra Ghadiri, Jari Saramäki and Takayuki Hiraoka
The basic and effective reproduction numbers are widely used metrics for characterizing the dynamics of infectious disease epidemics. However, the interpretation of these numbers is based on the assumption of homogeneous mixing and may not hold in real-world populations where the contact patterns deviate from that assumption. In this paper, we present a network-based framework to compare reproduction numbers in populations with and without spatial structure, while other parameters of the disease remain fixed. Using this framework, we show that in homogeneously mixed populations, in the absence of external interventions, the effective reproduction number decreases exponentially as the susceptible population declines. In contrast, in spatially structured populations, the basic reproduction number is smaller, and the effective reproduction number initially decreases faster but eventually converges to unity. We show that the reproduction number is determined by the level of competition between infectious nodes, which is governed by the network structure. Our results suggest that without knowledge of the network structure, reproduction numbers may not be informative for parameterizing the contagiousness of the disease or predicting the behavior of epidemic spreading.
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Chemical Physics · Cross-listed from cond-mat.mtrl-sci
Decoupling Precipitation and Surface Complexation during Mn(II) Removal by Biochar via Experiments and Atomistic Simulations
Audrey Ngambia, Anastasiia Gavrilova, Haitao Huang et al. (+4 more)
Manganese(II) mobilised by mining activity poses a persistent water-quality challenge, yet the mechanisms by which low-cost sorbents, such as biochar, sequester Mn(II) remain poorly resolved. This study identifies the specific chemical drivers of Mn(II) sequestration by combining fixed-bed column and batch experiments with atomistic molecular dynamics simulations. Oilseed rape straw biochars, produced at 350\textdegree C, 550\textdegree C, and 700\textdegree C, removed 20-50% of dissolved Mn from acidic influent (pH 4, 5 ppm). High-temperature biochar achieved the greatest removal ($\sim$50%) and rapidly increased effluent pH to 9, triggering alkaline precipitation. Conversely, lower-temperature biochars removed 20-30% of Mn while maintaining a near-neutral pH (7-7.5). Enhanced \ce{K+} release in these systems indicates significant cation exchange and non-precipitative pathways. Molecular simulations confirmed that while neutral surfaces show weak Mn(II) association, deprotonated sites drive strong adsorption through inner-sphere complexation ($\sim$50% removal) and outer-sphere association ($\sim$10%). These results establish a mechanistic framework to distinguish between precipitation-led and surface-complexation-led removal. By providing specific chemical criteria for Mn-targeted sequestration, this work enables the rational design of engineered biochars for sustainable water remediation.
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All authors Audrey Ngambia, Anastasiia Gavrilova, Haitao Huang, Zhuodong Lyu, Ondřej Mašek, Margaret Graham, Valentina Erastova
Chemical Physics
Stable, Fast, and Accurate Kohn-Sham Inversion in Gaussian Basis for Open Shell Molecular and Condensed Phase Systems via Density Matrix Penalization
Ziwei Chai and Sandra Luber
Here we present a density
matrix based KS inversion method formulated entirely within a Gaussian basis representation to optimize a KS potential
matrix that reproduces a target electron density. Inverse Kohn-Sham (KS) density functional theory (DFT) aims to determine the effective local KS potential that reproduces a target electron density, and is important both for electronic structure analysis and for the development of orbital based correction methods. In finite Gaussian basis implementations, however, conventional inverse KS-DFT approaches such as the Zhao-Morrison-Parr (ZMP) method often become poorly constrained and inefficient, because the real space penalty potential is projected onto a limited number of Gaussian basis
matrix elements, which can strongly coarse-grain its spatial variation. In the present method, the density
matrix mismatch is defined in a Lowdin orthogonalized basis, which yields a penalty energy invariant under
unitary rotations in that basis. The corresponding penalty potential contribution to the KS
Hamiltonian is derived analytically in the original nonorthogonal Gaussian basis. Across a wide range of penalty strengths, the self consistent field (SCF) optimization remains robust and efficient for various open shell systems, while progressively tightening the penalty drives the electron density into accurate agreement with the target.
Benchmarks on molecules and condensed phase systems show that the method achieves substantially smaller attainable density deviations than the conventional ZMP method. The method provides a fast and accurate route to KS inversion in finite Gaussian basis sets and may also be useful for future orbital based correction schemes.
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Chemical Physics · Cross-listed from cond-mat.mtrl-sci
Adsorption energies and decomposition barrier heights for ethylene carbonate on the surface of lithium from cluster-based quantum chemistry
Ethan A. Vo, Hung T. Vuong, Zachary K. Goldsmith et al. (+7 more)
For ethylene carbonate on the (100) surface of lithium, we calculate the adsorption energy in two binding motifs as well as the barrier height for a ring-opening decomposition reaction. We validate a scheme for producing results in the thermodynamic limit by correcting results obtained on finite lithium clusters containing only 40-100 atoms, which enables the use of hybrid density functionals, the random-phase approximation, and correlated wavefunction theories such as coupled-cluster theory and auxiliary-field
quantum Monte Carlo. We find that the high-level theories agree to within 2-5 kcal/mol and can therefore serve as
benchmarks for more affordable methods. Using our reference data, we demonstrate that generalized gradient approximation functionals, such as PBE, are not sufficiently accurate for reaction barrier heights, and we identify $\omega$B97X-V as an especially promising functional for the interfacial chemistry of electrolyte solvents at lithium metal anodes.
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All authors Ethan A. Vo, Hung T. Vuong, Zachary K. Goldsmith, Hong-Zhou Ye, Yujing Wei, Sohang Kundu, Ardavan Farahvash, Garvit Agarwal, Richard A. Friesner, Timothy C. Berkelbach
Computational Physics · Cross-listed from cond-mat.str-el
Tangent equations of motion for nonlinear response functions
Atsushi Ono
Nonlinear response functions, formulated as multipoint correlation functions or Volterra kernels, encode the dynamical and spectroscopic properties of physical systems and underpin a wide range of nonlinear transport and optical phenomena. However, their evaluation rapidly becomes prohibitive at high orders because of combinatorial (often factorial) scaling or severe numerical errors. Here, we establish a systematic and efficient framework to compute nonlinear response functions directly from real-time dynamics, without explicitly constructing multipoint correlators or relying on numerically unstable finite-difference methods for order-resolved extraction. Our approach is based on the Gateaux derivative with respect to the external field in function space, which yields a closed hierarchy of tangent equations of motion (TEOM). Propagating the TEOM alongside the original dynamics isolates each perturbative order with high accuracy, providing a term-by-term decomposition of physical contributions. The computational cost scales exponentially with response order in the fully general setting and reduces to
polynomial complexity when all perturbation directions are identical; both regimes avoid the factorial scaling of explicit multipoint-correlator evaluations. We demonstrate the power of TEOM by computing frequency-resolved fifth-order response functions for a solid-state electron model and by obtaining nonlinear response functions up to the 49th order with controlled accuracy in a classical Duffing oscillator. We further show that our time-
evolution formulation allows optical conductivities to be evaluated directly while remaining numerically stable even near zero frequency. TEOM can be incorporated seamlessly into existing real-time
evolution methods, yielding a general framework for computing nonlinear response functions in
quantum and classical dynamical systems.
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Optics · Cross-listed from quant-ph
Non-Markovian renormalization of optomechanical exceptional points
Aritra Ghosh and M. Bhattacharya
We investigate how non-Markovian mechanical dissipation affects exceptional points in linearized optomechanical systems with red-sideband drive. For a chosen non-Ohmic mechanical bath, we derive analytical conditions for the
memory-renormalized exceptional point by employing a pseudomode mapping, thereby demonstrating that structured environments displace the mode coalescence away from the Markovian prediction. Crucially, we reveal that failing to account for this
memory-induced shift suppresses the divergent Petermann factor by orders of magnitude, showing that accurate bath modeling is essential for the successful operation of exceptional-point-based devices whenever reservoir-induced
memory is non-negligible. We finally show that non-Markovianity modifies the cavity reflection spectrum, manifesting as a shallower optomechanically-induced-transparency dip, providing therefore an experimentally-accessible signature of structured mechanical environments.
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Atomic Physics
An alternative representation of multichannel Rydberg spectra: a modified K-matrix and Lu-Fano plot, applied to manganese spectroscopy
Justin D. Piel and Chris H. Greene
The well-known graphical representation called the Lu-Fano plot was originally developed for multi-channel Rydberg spectroscopy, especially in
quantum defect theory. The present study shows some of the limitations of this traditional Lu-Fano plot that are desirable to improve on, when there are closely split ionization thresholds as in many current generation
quantum information applications involving hyperfine-split thresholds, or when there are more than two ionization threshold energies. The modified representation introduced here is especially simplifying in the situation where one is exploring the bound states lying very far below those closely split thresholds. Moreover, it overcomes one limitation, namely that in contrast to the traditional Lu-Fano plot, the modified representation developed here can be utilized for problems where there more than two ionization thresholds. An example application to Rydberg series of the manganese atom illuminates its use in a practical problem.
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Fluid Dynamics
Edge-Stabilized Rotating Flames in a Circular Hele-Shaw Cell
Xiangyu Nie and Shengkai Wang
In this study, we report direct experimental observations of self-sustaining CH4-air rotating flames formed spontaneously in an unheated, open, circular Hele-Shaw
cell. These flames are observed under fuel-rich conditions and exhibit stable traveling-wave patterns, with edge velocities that can significantly exceed the nominal flame speed of the unburned mixture. PLIF measurements across the central plane reveal that the flame front consists of a bibrachial structure, with a
diffusion branch gliding along the side edges of the
cell and a premixed branch extending into the interior. Complementary numerical simulations suggest that the formation of rotating flames is driven by a dynamic balance between local flame speed and unburned-gas velocity near the
cell edges, where both wall heat loss and flow expansion play critical roles in stabilizing the rotation pattern. A parametric study is conducted for various equivalence ratios, flow rates, and gap distances, from which the regime diagrams of flame modes and rotation frequencies are obtained. At low flow rates, the rotating state is characterized by a single rotating flame wave, whose rotation frequency increases with flow rate. For this type of flames, a semi-empirical model is established to predict their rotation frequencies and shapes as functions of mass flow rate and surface temperature. At elevated flow rates, multiple rotating waves appear with approximately equal azimuthal spacing, and the product of the wave number and rotation frequency increases with flow rate. Mode transition from rotating flames to steady ring-shaped flames anchored at the burner edges occurs at sufficiently high flow rates, while at sufficiently low flow rates, flame extinction occurs due to thermal quenching. These findings can provide useful guidance for the advancement of micro-combustion technologies.
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Applied Physics · Cross-listed from cond-mat.mes-hall
Landau-Level-Resolved Mode Mixing and Shot Noise in Gate-Defined Graphene Quantum Point Contacts
Shakthidhar Vilvanathan, Jerin Saji, Kristiana Frei et al. (+2 more)
Graphene quantum point contacts (QPCs) in the
quantum Hall regime host competing transport mechanisms including
chiral edge propagation, valley degeneracy, and gate-induced mode mixing. Their interplay is not visible in conductance alone. Shot noise directly probes the statistics of transmission
eigenvalues, revealing microscopic mode partitioning that conductance cannot access. We develop a hybrid framework combining tight-binding simulations of gate-defined
graphene QPCs with random
matrix theory (RMT) to predict shot noise and Fano factor signatures across different
quantum Hall regimes, validated against experimental conductance maps of hBN-encapsulated
graphene Hall bars. Three distinct regimes are identified: adiabatic propagation, sharp mode filtering, and multi-mode mixing driven by localized states beneath the split gate. For higher Landau levels ($N_L > 0$), complete mode mixing produces the universal chaotic-cavity limit $F \simeq 1/4$. Strikingly, the zeroth Landau level ($N_L = 0$) converges to $F = 1/3$. This distinct value originates in the sublattice polarization of the $N_L = 0$ edge state: coupling to mixed-sublattice localized states beneath the gate is suppressed, confining transport to an effective single channel ($N = 1$). Complete mixing within this single channel yields a flat transmission
eigenvalue distribution and hence exactly $F = 1/3$ from single-channel RMT, numerically coincident with but mechanistically distinct from pseudo-diffusive zero-field
graphene transport. The $F = 1/3$ versus $F = 1/4$ crossover is a Landau-level-resolved noise signature absent in conductance, providing a direct discriminator between single-channel and multi-channel chaotic transport in
graphene QPCs.
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All authors Shakthidhar Vilvanathan, Jerin Saji, Kristiana Frei, Jakub Tworzydlo, Manohar Kumar
Chemical Physics
Overcoming sampling limitations using machine-learned interatomic potentials: the case of water-in-salt electrolytes
Luca Brugnoli, Mathieu Salanne, A. Marco Saitta et al. (+2 more)
Machine-learned interatomic potentials hold the promise to enable the modeling of highly concentrated
liquids over meaningful timescales, far from reach for current ab initio electronic structure methods. Here we evaluate the performances of various MACE potentials in modeling a $21 m$ water-in-salt electrolyte based on lithium bis(trifluoromethanesulfonyl)imide. We test out-of-the-box foundation models, as well as both fine tuning and from scratch training strategies. Our simulations demonstrate that surrogate models allow to overcome sampling limitations of ab initio molecular dynamics, reaching an excellent agreement with experimental observables such as the structure factor. We also demonstrate the benefit of fine tuning a foundation model over training from scratch: in terms of data efficiency, but most importantly as a means to provide information regarding configurations hard to sample, such as short Li$^+$–Li$^+$ distances. Finally, we show that depending on the reference exchange-correlation functional, empirical dispersion correction schemes can be detrimental. All in all, our work shows that machine-learned interatomic potentials are a good fit for the modeling of highly concentrated electrolytes over long timescales.
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All authors Luca Brugnoli, Mathieu Salanne, A. Marco Saitta, Alessandra Serva, Arthur France-Lanord
Medical Physics
T$_2$* and Susceptibility Mapping as Indicators of Placental Health
Amy Turnbull, George Hutchinson, Louise Dewick et al. (+8 more)
Objective(s): T$_2$* and susceptibility ($\chi$) MRI mapping provide complimentary measures of the haemodynamic environment in the placenta. The aims of this work were to use these simultaneously obtained measures to investigate the role of oxygen distribution on the well-established reduction of T$_2$* with gestational age found in healthy pregnancies and explore differences in both measures in compromised placentas. Methods: T$_2$* and $\chi$ were measured simultaneously from a double echo, echo planar scan of the whole placenta, across a range of gestational ages and pregnancy complications. Regional variations across the placenta were investigated. Results: Whole placental mean T$_2$* was more correlated with standard deviation of $\chi$ than mean $\chi$ indicating it is more driven by increasing local inhomogeneities rather than bulk deoxygenation with healthy gestation. Compromised placentas also showed increased standard deviation of $\chi$ as well as lower mean T$_2$* suggesting flow/uptake mismatch and reduced oxygenation. Regionally, the susceptibility was lowest (most oxygenated) and least variable in the central region of the placenta indicating good mixing and refreshment of blood in this area. The susceptibility was highest (most deoxygenated) and most variable at the fetal side, suggesting less effective perfusion in this region. Compromised cases showed the greatest difference on the fetal side for both mean and standard deviation of $\chi$. T$_2$* was lowest at the fetal side for healthy and compromised cases but the maternal and central regions better distinguished between the two groups. Conclusion(s): T$_2$* and susceptibility can be mapped simultaneously from a single MRI scan and provide complimentary information about the function of the placenta across healthy gestational development, and as a potential indicator of placental compromise.
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All authors Amy Turnbull, George Hutchinson, Louise Dewick, Ruizhe Li, Chris Bradley, Lopa Leach, Dimitrios Amantis, Xin Chen, Grazziela Figueredo, Kate F Walker, Penny Gowland
Physics and Society · Cross-listed from cond-mat.stat-mech
Feedback percolation on complex networks
Hoseung Jang, Ginestra Bianconi and Byungjoon Min
Traditional percolation theory assumes static microscopic rules, limiting its ability to describe real-world complex systems where macroscopic order actively regulates local interactions. Here, we introduce feedback percolation, an unified framework that dynamically couples the microscopic activation probability to the macroscopic size of the
giant component. We show that this simple feedback mechanism produces a rich variety of behaviors both analytically and numerically. Depending on the feedback functions, the system exhibits explosive discontinuous jumps, hybrid transitions, limit-cycle oscillations, and routes to chaos, absent in classical percolation. Our findings establish that macroscopic feedback provides a unifying physical mechanism for phenomena ranging from self-regulating oscillations to systemic infrastructure collapse.
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