Geophysics
Disentangling the soil and atmospheric stress on carbon sequestration in a Mediterranean pine forest
Rafat Qubaja, Murray Moinester and Joel Kronfeld
Sequestration of atmospheric CO$_2$ in a Mediterranean semi-arid Aleppo Pine Forest (Pinus halepensis) close to the border of the semi-arid timberline was characterized and quantified under field conditions. Measurements of organic and inorganic CO$_2$ sequestration with gas exchange and stock counting approaches were made in both rainfed control (approximately 12$\%$ average annual soil moisture) and summer irrigated plots (approximately 24$\%$ annual average soil moisture), providing the opportunity to separate the effects of atmospheric water demand from soil water stress on the atmospheric CO$_2$ sequestration responses. Measurements yield an organic carbon sequestration (OCS) rate of approximately 550 g CO$_2$ m$^{-2}$ yr$^{-1}$, two-thirds in soil and one-third in biomass. In addition, measurements yield an inorganic carbon sequestration (ICS) rate of approximately 216 g CO$_2$ m$^{-2}$ yr$^{-1}$; via calcite (CaCO$_3$) precipitation in the soil due to root exhalation of CO$_2$ (60$\%$) and microbial activity (40$\%$). The drip irrigated plot showed approximately 3 times higher organic CO$_2$ sequestration than the control plot. The organic sequestration is divided equally between the soil and the biomass. For the irrigated plot, the inorganic CO$_2$ was approximately 1.8 times higher than that of the control plot. However, for inorganic CO$_2$ sequestration, the soil moisture would need to be maintained lower than that of the study plot to preclude dissolving precipitated calcite. For many drylands, irrigation could be achieved by using fossil water reserves. These measured values demonstrate the relatively high potential carbon sequestration in Mediterranean drylands forests under irrigated and non-irrigated conditions.
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Optics
Long-range evanescent coupling through photonic molecules
Romina Abarca-Ramírez, Diego Román-Cortés, Maxim Mazanov et al. (+4 more)
Photonic molecules support the excitation of higher-order states, which are otherwise hard to access at individual waveguides. In this work, we demonstrate the resonant excitation of photonic molecular states which evanescently couple to single-mode waveguides. We implement the experiments on femtosecond
laser written photonic structures and demonstrate an efficient resonant excitation of higher-orbital states, optimized at specific wavelengths and propagation distances. We suggest the use of long photonic molecules as long-distance photonic links, and demonstrate strong coupling for very distant waveguides separated by 127 {\mu}m. We apply this concept to a one-dimensional
lattice and demonstrate the excitation of topological edge states emerging due to the third-order next-neighbour interactions. Our findings demonstrate effective long-range evanescent coupling which could be a concrete solution for fiber-based photonic chips, topological physics emerging from long-range interactions, or fundamental studies of initially uncoupled systems.
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All authors Romina Abarca-Ramírez, Diego Román-Cortés, Maxim Mazanov, Vlad Simonyan, Konstantin Rodionenko, Maxim A. Gorlach, Rodrigo A. Vicencio
Medical Physics
The Biologically Effective Particle Number Ratio (BPNR): a new framework to quantify the therapeutic window in SFRT and other modalities
Niels Bassler, Giuseppe Schettino, Hugo Palmans et al. (+4 more)
Spatially Fractionated Radiation Therapy (SFRT) produces highly heterogeneous dose distributions, for which conventional metrics such as peak, valley, or average dose can yield ambiguous or inconsistent estimates of therapeutic window changes. These dose descriptors are not uniquely linked to biological outcome, complicating comparisons between modalities. We introduce the Biologically Effective Particle Number Ratio (BPNR), a model-independent and outcome-based framework that quantifies therapeutic window changes using directly measurable delivery quantities rather than spatial dose metrics. BPNR is defined as the ratio of total particle numbers (proportional to monitor units, MU) required to reach specified levels of tumor control probability (TCP) and normal tissue complication probability (NTCP). The relative BPNR (RBPNR) compares therapeutic windows across modalities and avoids ambiguities of spatial dose averaging by relying solely on biological endpoints. As an illustration, we apply the framework to preclinical
proton minibeam radiotherapy (pMBRT) versus conventional
proton therapy. The absence of normal tissue complications at the highest tested MU in the pMBRT arm yields an RBPNR > 1.4, indicating a widened therapeutic window. The BPNR/RBPNR methodology provides a concise, experimentally grounded, and modality-agnostic way to quantify therapeutic window changes, with potential applications across SFRT, FLASH, high-LET radiation, and combination therapies.
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All authors Niels Bassler, Giuseppe Schettino, Hugo Palmans, Thomas Friedrich, Kelvin Ng Wei Siang, Emanuele Scifoni, Fardous Reaz
Optics
Integrated polarization-entangled photon source for wavelength-multiplexed quantum networks
Xiaodong Shi, Yue Li, Jinyi Du et al. (+13 more)
Entangled
photons are fundamental resources for
quantum communication, computing, and networking. Among them, polarization-entangled
photon pairs play an important role due to their straightforward state manipulation and direct use in
quantum key distribution, teleportation, and network protocols. However, realizing compact, efficient, and scalable polarization-entangled sources that meet the requirements of practical deployment remains a major challenge. Here, we present a simple yet high-performance on-chip polarization-entangled
photon-pair source on thin-film lithium niobate (TFLN). Our device employs dual quasi-phase matching (D-QPM) that sequentially supports type-0 and type-I spontaneous parametric down-conversion in a single nanophotonic waveguide, eliminating the need for interferometers, polarization rotators, or other complex
circuits. The source directly produces high-fidelity Bell states with broad bandwidth, high brightness, and low noise. Using this integrated platform, we realize wavelength-multiplexed
entanglement distribution in a four-user
quantum network deployed over metropolitan fiber links up to 50 km. These results establish a robust and scalable pathway toward practical
quantum communication systems and multi-user
quantum mesh networks based on integrated photonics.
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All authors Xiaodong Shi, Yue Li, Jinyi Du, Lin Zhou, Ran Yang, En Teng Lim, Sakthi Sanjeev Mohanraj, Mengyao Zhao, Xu Chen, Xiaojie Wang, Guangxing Wu, Hao Hao, Veerendra Dhyani, Sihao Wang, Alexander Ling, Di Zhu
Computational Physics · Cross-listed from cond-mat.mtrl-sci
A Finite Element Method for Simulation of Coupled Dynamics of Dislocations and Fracture
Boyang Gu, Adrian Diaz, Yang Li et al. (+1 more)
This work presents a finite element method for simulating dynamic processes that involve the coupled
evolution of dislocation motion and crack propagation. The method numerically solves the Concurrent Atomistic-Continuum (CAC) formulation of the conservation of linear momentum. A crystalline material is discretized at the unit-
cell level using 6-node prism elements whose geometry allows dislocations and cracks to nucleate and propagate along element facets. Nanoscale simulations of single-
crystal Cu, Fe, and Si demonstrate the initiation and propagation of dislocations and cracks, and these results are reproduced by the finite element method in excellent agreement with fully atomistic molecular dynamics simulations. Mesoscale simulations of single-
crystal Cu further demonstrate the ability of the method to capture size-dependent brittle and ductile behavior. Under plane-strain conditions the Cu model fractures in a brittle manner, while a fully three-dimensional model exhibits curved and intersecting dislocations that blunt the crack tip and prevent crack propagation, resulting in ductile behavior. The accuracy, efficiency, and applicability of the method are discussed.
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All authors Boyang Gu, Adrian Diaz, Yang Li, Youping Chen
Chemical Physics
A Machine Learning Model for the Chemistry of a Solvated Electron
Ruiqi Gao, Pinchen Xie and Roberto Car
In molecular simulations, machine-learning force fields can achieve ab initio accuracy at a lower cost but remain limited in the explicit modeling of electrons. In this work, we develop an electron-aware machine-learning force field, in which an excess electron of interest is modeled
quantum mechanically, while the remaining short-range interactions and long-range Coulombic forces are machine-learned to reproduce a density functional theory calculation. We demonstrate the method on the solvated electron in bulk water and its reaction with a hydronium ion. We identify a
proton transfer mechanism by which the excess
proton recombines with the electron. We determine the forward reaction rates between 350 K and 450 K from first-passage survival functions, which yield an Arrhenius relationship with an activation energy of 3.2 kcal$\cdot$mol$^{-1}$, in good agreement with experiment. From an enhanced sampling simulation, we determine the
equilibrium constant, and thus the reaction free energy, which is also consistent with experimental measurements.
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Optics
A 160 {\deg} x 160 {\deg} Dynamic Holographic Meta-Projector
Feng-Jun Li, Ruixing Xia, Qianmei Deng et al. (+6 more)
Holography can reconstruct immersive light fields for virtual and augmented reality by modulating optical wavefront. Due to huge pixel sizes, current spatial light modulators (SLMs) have small field-of-view (FOV) for
holographic displays. Despite various methods for etendue expansion, the largest full-screen FOV for dynamic holography is only 70 {\deg} X 70 {\deg}, which remains insufficient for large-scale, high-resolution, three-dimensional displays. Here, we report a pixel-interpolation-assisted
holographic meta-projector that substantially expands the FOV by integrating multiple subwavelength metasurface pixels within each microscale pixel of a traditional SLM. Leveraging large-angle diffraction of the metasurface and implementing k-space distortion correction for ultra-wide angles, we experimentally demonstrate dynamic
holographic image reconstruction with a FOV of 160 {\deg} X 160 {\deg} -equivalent to a system numerical aperture of 0.985-at a high framerate of 60 Hz, surpassing the temporal resolution threshold of human
vision. This system represents the state-of-the-art near-full-screen
holographic dynamic display, thereby opening the door to high-dynamic-range and large-FOV
holographic displays.
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All authors Feng-Jun Li, Ruixing Xia, Qianmei Deng, Yuze Lu, Xiangping Li, Fangwen Sun, Dong Zhao, Zi-Lan Deng, Kun Huang
Chemical Physics
How Thermostats Influence Dynamics Across Time Scales: A Systematic Study from Fast Motions to Slow Transitions
Frederick Heinz, Sascha Jähnigen, Joana-Lysiane Schäfer et al. (+1 more)
Reliable dynamical properties from molecular dynamics simulations require careful control of thermostatting artifacts. We systematically assess how NVE, deterministic thermostats, velocity-rescale dynamics, and
stochastic Langevin-type thermostats affect time-correlation functions across
liquids of varying complexity. The analysis spans vibrational spectra, velocity and pressure autocorrelations,
diffusion coefficients, shear viscosities, and Markov state models. Deterministic thermostats and velocity-rescale dynamics closely reproduce NVE reference data over all observables. In contrast, strongly coupled
stochastic thermostats (tau less 1 ps) systematically distort dynamical properties. By constrast, moderate
stochastic coupling (tau eq. 1 ps) restores near-NVE behavior while maintaining canonical sampling. Our results provide practical guidelines for selecting thermostat schemes when accurate dynamical properties or Markov models are required.
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All authors Frederick Heinz, Sascha Jähnigen, Joana-Lysiane Schäfer, Bettina G. Keller
Data Analysis and Statistics · Cross-listed from quant-ph
A reconciliation of the Pryce-Ward and Klein-Nishina statistics for semi-classical simulations of annihilation photons correlations
Petar Žugec, Eric Andreas Vivoda, Mihael Makek et al. (+1 more)
Two
photons from the ground state para-positronium annihilation are emitted in a maximally entangled singlet state of orthogonal polarizations. In case of the Compton scattering of both
photons the phenomenon of
quantum entanglement leads to a measurable increase in the azimuthal correlations of scattered
photons, as opposed to a classical description treating the two scattering events as independent. The probability of the scattering of the system of the entangled
photons is described by the Pryce-Ward cross section dependent on a difference of the azimuthal scattering angles in the fixed coordinate frame, while the independent scattering of single
photons is described by the Klein-Nishina cross section dependent on the azimuthal angle relative to each
photon's initial polarization. Since the singlet state of orthogonal polarizations is rotationally invariant, it does not carry any physical information on the initial polarizations of the single annihilation
photons. In such bipartite state the angular origin for the Klein-Nishina cross section is undefined, making the Pryce-Ward and Klein-Nishina descriptions mutually exclusive. However, semi-classical simulations of the joint Compton scattering of entangled
photons - implementing the Pryce-Ward cross section, but still treating the two
photons as separate entities - can reconcile the Pryce-Ward correlations with the Klein-Nishina statistics for single
photons by implementing a modified version of a scattering cross section presented in this work.
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All authors Petar Žugec, Eric Andreas Vivoda, Mihael Makek, Ivica Friščić
Atmospheric and Oceanic Physics
Super-resolution of satellite-derived SST data via Generative Adversarial Networks
Claudia Fanelli, Tiany Li, Luca Biferale et al. (+4 more)
In this work, we address the super-resolution problem of satellite-derived sea surface temperature (SST) using deep generative models. Although standard gap-filling techniques are effective in producing spatially complete
datasets, they inherently smooth out fine-scale features that may be critical for a better understanding of the ocean dynamics. We investigate the use of deep learning models as Autoencoders (AEs) and generative models as Conditional-Generative
Adversarial Networks (C-GANs), to reconstruct small-scale structures lost during interpolation. Our supervised – model free – training is based on SST observations of the Mediterranean Sea, with a focus on learning the conditional distribution of high-resolution fields given their low-resolution counterparts. We apply a tiling and merging strategy to deal with limited observational coverage and to ensure spatial continuity. Quantitative evaluations based on mean squared error metrics, spectral analysis, and gradient statistics show that while the AE reduces reconstruction error, it fails to recover high-frequency variability. In contrast, the C-GAN effectively restores the statistical properties of the true SST field at the cost of increasing the pointwise discrepancy with the ground truth observation. Our results highlight the potential of deep generative models to enhance the physical and statistical realism of gap-filled satellite data in oceanographic applications.
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All authors Claudia Fanelli, Tiany Li, Luca Biferale, Bruno Buongiorno Nardelli, Daniele Ciani, Andrea Pisano, Michele Buzzicotti
Computational Physics · Cross-listed from cond-mat.supr-con
Machine-Learned Interatomic Potentials for Structural and Defect Properties of YBa$_2$Cu$_3$O$_{7-\delta}$
Niccolò Di Eugenio, Ashley Dickson, Flyura Djurabekova et al. (+9 more)
High-Temperature
Superconductors (HTS) such as YBa2Cu3O7-delta (YBCO) are essential for next-generation Tokamak fusion reactors, where Rare-Earth Barium Copper
Oxides (REBCO) form the functional layers in HTS magnets. Because YBCO's superconductivity depends strongly on oxygen stoichiometry and defect structure, atomistic simulations can provide crucial insight into radiation-damage mechanisms and pathways to maintain material performance. In this work, we develop and
benchmark four Machine-Learned Interatomic Potentials (MLPs) for YBCO: the Atomic Cluster Expansion (ACE), the Message-Passing Atomic Cluster Expansion (MACE), the Gaussian Approximation Potential (GAP), and the Tabulated Gaussian Approximation Potential (tabGAP), trained on an extensive Density Functional Theory (DFT) database explicitly designed to include irradiation-damaged-like configurations. The resulting models achieve DFT-level accuracy across a wide range of atomic environments, faithfully capturing the interatomic forces relevant to radiation damage processes. Among the tested models, MACE delivers the highest accuracy, although at greater computational cost, while ACE and tabGAP provide an excellent balance between efficiency and fidelity. These machine-learned potentials establish a robust foundation for large-scale molecular dynamics simulations of radiation-induced defect
evolution in complex superconducting materials
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All authors Niccolò Di Eugenio, Ashley Dickson, Flyura Djurabekova, Francesco Laviano, Federico Ledda, Daniele Torsello, Erik Gallo, Mark R. Gilbert, Duc Nguyen-Manh, Antonio Trotta, Samuel T. Murphy, Davide Gambino
Biological Physics · Cross-listed from cond-mat.soft
Active flow-driven DNA remodeling generates millimeter-scale mechanical oscillations
Maya Levanon, Noa S. Goldberg, Dvir Cohen et al. (+3 more)
In living systems, DNA undergoes continuous and rhythmic mechanical remodeling through condensation, looping, and disentangling to regulate gene expression, segregate chromosomes, and guide morphogenesis. Here, we demonstrate a purely mechanical route to rhythmic DNA reorganization in a minimal active composite of microtubules, kinesin motors, and DNA. We embed a DNA
polymer in an active turbulent microtubule-kinesin fluid, creating a self-morphing material. The active flows stretch and entangle the DNA, forming a self-organized viscoelastic network that resists active stresses and affects flow over large length scales. This mechanical feedback loop progressively amplifies velocity correlations and drives a nonequilibrium phase transition tuned by DNA contour length: from disordered flow to synchronized, millimeter-scale oscillations with
vortices. We rationalize the phase transition with an active-gel model that predicts a growing length scale and an oscillatory instability emerging from the interplay between activity, orientational order, and self-generated viscoelasticity, rather than chemical signaling. The dependence of the oscillation frequency on system size and activity quantitatively agrees with experiment. Thus, flow-driven DNA remodeling provides a minimal physical route to autonomous, system-spanning oscillations in three dimensions and suggests design principles for programmable soft matter that coordinates, actuates, and reshapes itself.
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All authors Maya Levanon, Noa S. Goldberg, Dvir Cohen, Eran Bouchbinder, Ram M. Adar, Alexandra M. Tayar
Optics
Acoustically control of integrated optical microrings: from photonic molecule to Mobius strip
Zheng-Xu Zhu, Yuan-Hao Yang, Xin-Biao Xu et al. (+10 more)
Microring resonators (MRRs) are fundamental building blocks of photonic integrated
circuits, yet their dynamic reconfiguration has been limited to tuning refractive index or absorption. Here, we demonstrate acoustic control over optical path
topology on a lithium niobate on sapphire platform. By launching gigahertz acoustic waves into a hybrid phononic-photonic waveguide, a dynamic Bragg mirror (DBM) is created within the optical path, coupling forward and backward propagating light. Employing a pair of coupled MRRs, we achieve strong coupling between supermodes of the photonic molecule with only milliwatt-level drive power, yielding a cooperativity of 2.46 per milliwatt. At higher power, DBM reflectivity up to 24% is achieved, revealing breakdowns of both the photonic molecule picture and perturbative coupled mode theory, indicating the transformation toward Mobius strip
topology. Our work establishes a new dimension for controlling photonic devices, opening pathways toward fully reconfigurable photonic
circuits through acoustic drive.
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All authors Zheng-Xu Zhu, Yuan-Hao Yang, Xin-Biao Xu, Jia-Qi Wang, Yu Zeng, Jia-Hua Zou, Juanjuan Lu, Weiting Wang, Ming Li, Yan-Lei Zhang, Guang-Can Guo, Luyan Sun, Chang-Ling Zou
Medical Physics
PET Rapid Image Reconstruction Challenge (PETRIC)
Casper da Costa-Luis, Matthias J. Ehrhardt, Christoph Kolbitsch et al. (+4 more)
Introduction: We describe the foundation of PETRIC, an image reconstruction challenge to minimise the computational runtime of related
algorithms for Positron Emission
Tomography (PET). Purpose: Although several similar challenges are well-established in the field of medical imaging, there have been no prior challenges for PET image reconstruction. Methods: Participants are provided with open-source software for implementation of their reconstruction
algorithm(s). We define the objective function and reconstruct "gold standard" reference images, and provide metrics for quantifying algorithmic performance. We also received and curated phantom
datasets (acquired with different scanners, radionuclides, and phantom types), which we further split into training and evaluation
datasets. The automated computational framework of the challenge is released as open-source software. Results: Four teams with nine
algorithms in total participated in the challenge. Their contributions made use of various tools from optimisation theory including preconditioning,
stochastic gradients, and artificial intelligence. While most of the submitted approaches appear very similar in nature, their specific implementation lead to a range of algorithmic performance. Conclusion: As the first challenge for PET image reconstruction, PETRIC's solid foundations allow researchers to reuse its framework for evaluating new and existing image reconstruction methods on new or existing
datasets. Variant versions of the challenge have and will continue to be launched in the future.
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All authors Casper da Costa-Luis, Matthias J. Ehrhardt, Christoph Kolbitsch, Evgueni Ovtchinnikov, Edoardo Pasca, Kris Thielemans, Charalampos Tsoumpas
Optics
Broadband Low-Frequency Near-Perfect Sound Absorber via Coupled Metasurfaces
Keqiang Lyu, Mohamed Farhat and Ying Wu
We propose a simple yet effective method for low-frequency broadband acoustic absorption. The absorber consists of two concentric space-coiling resonators with distinct resonance frequencies, with the inner resonator characterized by a low-quality factor (Q) and the outer resonator by a high Q factor. The coupling between the two resonators enables efficient broadband absorption within a deep-subwavelength range exceeding 15 times the structural thickness. Numerical simulations, theoretical analysis, and experimental measurements demonstrate that highly efficient (greater than 80 percent) low-frequency broadband absorption is achieved in the range of 198-315 Hz, as well as a 58 percent fractional bandwidth spanning 183-334 Hz. Furthermore, with the outer dimension fixed, adjusting the parameters of the internal resonators enables flexible tuning of the absorption band across a broad frequency range. This work presents a powerful design methodology that eliminates the need for traditional complex spatially arranged multi-resonator assemblies. By employing a single class of resonant units, thin and efficient broadband absorbers can be achieved, offering various application prospects in the field of low-frequency sound absorption.
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Fluid Dynamics
Influence of Fluid Rheology on Fluid Flow in a Natural Fracture Network
Cuong Mai Bui and Stephan K. Matthai
Non-Newtonian rheology is widely acknowledged in subsurface fluids, yet its presence and effects are largely ignored in current fracture-flow studies. Here, we simulate fracture flow of non-Newtonian
polymer solutions on a several metre-wide millimetre-aperture network of fractures, examining the complex interplay between fluid rheology, fracture geometry, and fluid inertia. Non-Newtonian fluid characteristics, including a yield stress and shear-thinning behaviour, are modelled using the Herschel-Bulkley-Papanastasiou approach. For the investigated flow rates, our Navier-Stokes simulations reveal significant viscosity variations, resulting in complex flow patterns at both aperture- and network scale. At low rates, non-yielded fluid forms rigid zones occupying up to ~65% of the network cross-sectional area, reducing fracture flow connectivity. At high rates, shear-thinning promotes inertia-dominated flow with circulations near fracture intersections. Regarding flow partitioning, yield stress confines flow to dominant pathways while shear-thinning promotes a broader fluid distribution as compared with a Newtonian fluid. Observed
multimodal velocity distributions and nonlinear pressure drop-flow rate relationships underscore that fluid rheology must be considered during fracture-flow modelling.
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Chemical Physics
Anomalous double-layer restructuring in water-in-salt electrolytes at graphitic interfaces governs capacitance
Hannah O. Wood, Fulu Zhou, Jan Dočkal et al. (+5 more)
The structure and thickness of the electrical double layer (EDL) at carbon electrodes strongly influence electrochemical performance, yet remain poorly understood in super-concentrated aqueous electrolytes. Here we combine classical and
quantum-mechanical molecular dynamics simulations to resolve the interfacial organisation of aqueous LiCl from dilute to water-in-salt (WiS) (1–$20~\mathrm{mol~kg^{-1}}$) concentrations at graphitic electrodes, and compare with electrochemical differential-capacitance measurements from which the potential of zero charge (PZC) is obtained. We uncover a concentration-driven restructuring of the EDL: below $6~\mathrm{mol~kg^{-1}}$, solvated Li$^+$ dominates the outer Helmholtz plane (OHP), but at higher concentrations co-adsorption of Cl$^-$ through solvent-separated ion pairs enforces a near 1:1 Li:Cl ratio at the interface. This transition expands the effective EDL thickness, redistributes the interfacial potential drop, and drives a decrease in the PZC, matching the trend inferred from differential-capacitance measurements on electrolyte-graphite interfaces. Capacitance calculations reveal that while both EDL and
quantum contributions vary strongly with concentration, their opposing trends make the total capacitance appear nearly constant for pristine few-layer graphite; for electrodes with smaller
quantum capacitance, however, the concentration dependence of the EDL capacitance would be directly reflected in the total capacitance. Solvent-separated ion pairing is identified as the key driver of anomalous EDL behaviour in LiCl WiS electrolytes, establishing design considerations for tuning interfacial capacitance and stability in next-generation aqueous energy-storage systems.
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All authors Hannah O. Wood, Fulu Zhou, Jan Dočkal, Martin Lísal, Filip Moučka, Sittipong Kaewmorakot, Robert A. W. Dryfe, Paola Carbone
Instrumentation and Detectors
A nonlinear multiphysics model for the design validation of the ASTAROTH copper-steel cryogenic chamber
F. Alessandria, F.B. Armani, S. Coelli et al. (+8 more)
Among the global efforts to directly detect dark matter, the only positive claim so far relies on NaI(Tl)
crystal detectors, making this technology of particular interest. ASTAROTH is a project aimed at developing the next generation of such detectors by reading out their scintillation light with SiPM
matrices operated at cryogenic temperatures. This paper describes the innovative design of the ASTAROTH cryostat, consisting of a double-walled copper-steel cryogenic chamber that cools the detectors by means of a
liquid argon bath. The detectors are thermalized in a helium atmosphere at a temperature tunable from 87 to 150 K. The design has been validated in terms of heat transfer efficiency and mechanical stress, developing a nonlinear multiphysics model. The mechanical properties of OFHC copper were experimentally evaluated on dedicated tensile samples. The simulation results show that the structural integrity is guaranteed. At the highest operating temperature, the region with the steepest temperature gradient exhibits stresses that slightly exceed the yield strength of copper (localized strain-hardened condition). Following construction, the cryostat was commissioned and has been in regular operation for over 30 cooling cycles, with no signs of degradation. The temperature can be tuned across the full target range and remains stable within 0.1 K. These results demonstrate that this is a viable design for next-generation dark matter detectors, as well as for a variety of applications requiring uniform and tunable gas-conducted cooling of instrumentation.
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All authors F. Alessandria, F.B. Armani, S. Coelli, D. Cortis, D. D'Angelo, E. Martinenghi, M. Monti, D. Orlandi, M. Sorbi, V. Toso, A. Zani
Instrumentation and Detectors
Accurate simulations of magnetic excitations in the neutron simulation package McStas
Silas B. Schack, Kristine M. L. Krighaar, Emma Y. Lenander et al. (+1 more)
A new component for the accurate simulation of
neutron scattering from
magnetic excitations has been developed for the
neutron ray-tracing software McStas. The component SpinWave_BCO simulates inelastic
neutron scattering from ferro-, antiferro-, and altermagnetic excitations in a body-centered orthorhombic
crystal structure, where the dispersion relation and scattered
neutron intensities are derived using linear
spin wave theory. Data from a simulated Triple-Axis Spectrometer with an extremely high resolution have been verified by direct comparison with theory and by comparison to data simulated using the package SpinW. The component serves as a proof-of-concept for the implementation of a more general linear
spin wave component in McStas.
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All authors Silas B. Schack, Kristine M. L. Krighaar, Emma Y. Lenander, Kim Lefmann
Optics · Cross-listed from quant-ph
Mixed cat states at low purity of light
N.I. Petrov
Pure states are usually used to observe
quantum phenomena. In this study, we show that a
quantum superposition of spatially displaced mixed cat states can be generated within an optical waveguide via nonparaxial
unitary evolution of the initial low coherence (low purity) light beam. It is shown that highly mixed Schrodinger cat states can be observed at a well-defined propagation distance. The importance of the long-term decoherence and recoherence of the original wave packet in observing the mixed cat states is demonstrated. The Heisenberg and Schrodinger-Robertson uncertainty relations for mixed cat states are evaluated. We have demonstrated the feasibility of our method using accurate numerical simulations for the parameters of the source and optical waveguide available in practice.
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Computational Physics
Efficient Pseudo-spectral Algorithms for Statistical Field Theories
Martin Kjøllesdal Johnsrud and Navdeep Rana
We present
stochastic variants of the exponential time differencing schemes for stiff
stochastic differential equations. We derive three explicit schemes that offer better stability compared to Euler-Maruyama and Milstein's method, and achieve strong convergence up to order O(h) in the time step h. We combine these schemes with a pseudo-spectral approach to outline efficient
algorithms for simulating
stochastic field theories with additive noise. To illustrate the effectiveness of this approach, we study several systems in and out of
equilibrium, including Model A, Model B, the Kardar-Parisi-Zhang equation, and the Complex Ginzburg-Landau equation. We outline procedures for computing physical observables such as the critical exponents, correlation functions, and dynamic linear response, and provide our implementation as open source code.
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Plasma Physics
The Machine Learning Approach to Moment Closure Relations for Plasma: A Review
Samuel Burles and Enrico Camporeale
The requirement for large-scale global simulations of
plasma is an ongoing challenge in both space and laboratory
plasma physics. Any simulation based on a fluid model inherently requires a closure relation for the high order
plasma moments. This review compiles and analyses the recent surge of machine learning approaches developing improved
plasma closure models capable of capturing kinetic phenomena within
plasma fluid models. We survey two methodological families: neural-network surrogates (from multilayer perceptrons to
Fourier neural operators, the latter recently reproducing both linear and non-linear Landau damping online within a fluid solver) and equation-discovery methods such as sparse regression; and organise the studies by whether they are tested offline against reference data or online within a time-evolving solver. We outline the challenges associated with machine-learning closures, including off-diagonal pressure-tensor accuracy, generalisation beyond the training distribution, and stable integration into large-scale simulations, and the directions future research might take to address them.
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Space Physics · Cross-listed from astro-ph.SR
The Solar Close Observations and Proximity Experiments (SCOPE) mission
Jun Lin, Jing Feng, Zhenhua Ge et al. (+31 more)
The
Solar Close Observations and Proximity Experiments (SCOPE) mission will send a spacecraft into the
solar atmosphere at a low altitude of just 5 R_sun from the
solar center. It aims to elucidate the mechanisms behind
solar eruptions and coronal heating, and to directly measure the coronal
magnetic field. The mission will perform in situ measurements of the current sheet between coronal mass ejections and their associated
solar flares, and energetic particles produced by either reconnection or fast-mode shocks driven by coronal mass ejections. This will help to resolve the nature of reconnections in current sheets, and energetic particle acceleration regions. To investigate coronal heating, the mission will observe nano-
flares on scales smaller than 70 km in the
solar corona and regions smaller than 40 km in the photosphere, where magnetohydrodynamic waves originate. To study
solar wind acceleration mechanisms, the mission will also track the process of ion charge-state freezing in the
solar wind. A key achievement will be the observation of the coronal
magnetic field at unprecedented proximity to the
solar photosphere. The polar regions will also be observed at close range, and the inner edge of the
solar system
dust disk may be identified for the first time. This work presents the detailed background, science, and mission concept of SCOPE and discusses how we aim to address the questions mentioned above.
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All authors Jun Lin, Jing Feng, Zhenhua Ge, Jiang Tian, Yuhao Chen, Xin Cheng, Hui Tian, Jiansen He, Alexei Pevtsov, Haisheng Ji, Shangbin Yang, Parida Hashim, Bin Zhou, Yiteng Zhang, Shenyi Zhang, Xi Lu, Yuan Yuan, Liu Liu, Haoyu Wang, Hu Jiang, Lei Deng, Xingjian Shi, Lin Ma, Jingxing Wang, Shanjie Huang, Xiaoshi Zhang, Hao Yang, Zhonghua Yao, He Zhang, Yuanming Miao, Lei Ni, Zhixing Mei, Jing Ye, Yan Li
Chemical Physics
Predicting complete basis set limit quasiparticle energies from triple-$\zeta$ calculations
Dario Baum, Lucas Visscher and Arno Förster
We present a simple linear model to estimate the basis set incompleteness errors (BSIE) of (vertex-corrected) $GW$ QP energies based on the kinetic energy of the corresponding orbital only. We parametrise the model for $G_0W_0$, quasi-particle self-consistent $GW$ (qs$GW$), and vertex-corrected ($\Sigma^{BSE}@L^{BSE}$) QP energies on a large set of molecules containing 10 different elements for which we calculate complete basis set (CBS) limit extrapolated reference values with correlation-consistent basis sets ranging from triple- to hextuple-$\zeta$ (TZ/6Z). Based on these accurate reference values, we obtain model parameters for Gaussian-type and Slater-type orbital (GTO/STO) basis sets which allow for the extrapolation of QP energies calculated with TZ basis sets to the CBS limit with errors of 20 to 30 meV. Analysing extrapolation errors, we show the commonly used extrapolation method which assumes an inverse linear dependence of the BSIE on the inverse number of basis functions to be valid, but to produce larger errors, even when a quadruple-$\zeta$ calculation is used in the extrapolation.
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Data Analysis and Statistics · Cross-listed from astro-ph.GA
Galaxy and Mass Assembly (GAMA): The Properties of Quasar Host Galaxies: Star Formation Histories and Stellar Populations
Maria B. Stone, Roberto De Propris, Clare Wethers et al. (+5 more)
We investigated the
star formation history and
stellar populations of a sample of 205 Type I
quasar host
galaxies (0.1$<$z$<$0.35) and compared with normal (non-active)
galaxies of the same mass and
redshift within the volume of the
Galaxy and Mass Assembly (GAMA)
redshift survey. We find that
quasar host
galaxies tend to be
star-forming
galaxies ($\sim$ 80%) lying on the
star-forming MS; the fraction of
quasar host
galaxies that are quiescent ($\sim$ 20%) is lower than the fraction of quiescent
galaxies in the comparison sample of normal
galaxies (54%). We find that the mean
star formation rate of
quasar host
galaxies has increased over the past 100 Myr by a factor of 2–3, but these
galaxies were
star-forming at all times previously. Our data are more consistent with
quasar activity originating together with an increase in the
star formation rate of otherwise normal
galaxies, similar to episodic
star formation in normal spirals. We argue that this indicates that secular processes and minor mergers may be the favored triggers of
nuclear activity in the local Universe.
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All authors Maria B. Stone, Roberto De Propris, Clare Wethers, Jari Kotilainen, Nischal Acharya, Benne Holwerda, Andrew M. Hopkins, Kevin Pimbblet
Optics
Metasurface-Enhanced Mid-Infrared Imaging Spectroscopy with Broadband Quantum Cascade Lasers
Ivan Sinev, Alessio Cargioli, Diego Piciocchi et al. (+3 more)
Mid-infrared (mid-IR) spectroscopy offers unparalleled opportunities in sensing through chemically specific detection of molecular absorption fingerprints. Yet, its practical applications are limited by the weak light-matter interaction in the mid-IR range and low brightness of mid-IR light sources. Surface-enhanced infrared absorption (SEIRA) spectroscopy addresses the sensitivity limitations by leveraging resonant photonic structures, in particular, plasmonic and frequency-selective dielectric metasurfaces. However, current implementations of SEIRA approach mainly rely on complex instruments and scanning components such as
Fourier-transform infrared spectroscopy and tunable external cavity
quantum cascade
lasers (EC QCLs). Here, we present a compact and high-throughput imaging-based SEIRA platform that combines broadband gradient metasurfaces with a radiofrequency-modulated QCL that generates remarkably broad instantaneous emission spectrum (250 cm$^{-1}$) covering absorption bands of multiple distinct molecular vibrational modes. By matching the resonance spectrum of the compact (1 mm$^2$) broadband gradient metasurface with the
laser emission projected on its surface through a dispersive element, we ensure that every QCL spectral component is uniquely addressed for an efficient targeted enhancement of the electromagnetic field. This enables us to use a low-cost and room-temperature mid-IR camera, acquiring in a single frame the enhanced absorption signatures of analytes deposited on the metasurface as a barcode image, thus reducing the acquisition time by up to 3 orders of magnitude compared to the FTIR and EC QCL based measurements. Eliminating the need for tunable light sources, bulky spectrometers, and expensive low-temperature detectors, our approach enables high-throughput, miniaturized, and highly specific molecular diagnostics for diverse chemical and biological applications.
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All authors Ivan Sinev, Alessio Cargioli, Diego Piciocchi, Felix Ulrich Brikh, Jerome Faist, Hatice Altug
Applied Physics · Cross-listed from cond-mat.mes-hall
Photoionization current spectroscopy of individual silicon vacancies in silicon carbide
Kazuki Okajima, Tetsuri Nishikawa, Hiroshi Abe et al. (+5 more)
Defect charge-state dynamics are central to both
spin-
photon interfaces and photoelectrical
spin readout. Despite the significance of silicon vacancies (V1/V2) in silicon carbide (4H-SiC) for both applications, their ionization behavior has remained unclear because their lack of optical blinking prevents conventional charge-state analysis. Here, we employ photocurrent spectroscopy of individual defects to measure the wavelength dependence of their excitation and ionization cross-sections. We reveal that V1 and V2 exhibit similar ionization cross-sections that increase toward shorter wavelengths, while carbon vacancies dominate the more steeply increasing background photocurrent. These results indicate that V2 and its surrounding environment appear more robust than V1 under resonant excitation. We also identify wavelength regimes that optimize defect-origin photocurrent for photoelectrical
spin readout relative to background contributions, which differ between single-defect and ensemble measurements. Our results establish photocurrent spectroscopy as a powerful complement to optical methods, advancing the development of defect-based
quantum devices.
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All authors Kazuki Okajima, Tetsuri Nishikawa, Hiroshi Abe, Koichi Murata, Takeshi Ohshima, Hidekazu Tsuchida, Naoya Morioka, Norikazu Mizuochi
Plasma Physics
Solving the six-dimensional Vlasov-Maxwell System with Active Flux and Splitting Methods
G. Grünwald, L. Hensel, M. Deisenhofer et al. (+3 more)
Active Flux (AF) is a modified Finite Volume method that evolves additional Degrees of Freedom (DoF) located on the
cell interfaces to compute high-order approximations to the numerical fluxes through the respective interface. We present an AF-based scheme for the simulation of collisionless
plasmas described by the Vlasov equation coupled with Maxwell's equations. In order to limit the DoF in high dimensional settings we employ operator splitting. The resulting one-dimensional advection equations can be solved efficiently and with low implementation complexity, making it a very fast alternative to standard Finite Volume methods. We compare our scheme's performance with a related Finite Volume method based on the semi-Lagrangian approach. We find that, as a consequence of its compact stencil, the AF scheme has significantly lower dissipation and reduced anisotropy, and thus produces results on par with or even superior to the
benchmark for standard test cases reproducing important kinetic phenomena, while also offering lower computational cost.
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All authors G. Grünwald, L. Hensel, M. Deisenhofer, S. Lautenbach, K. Kormann, R. Grauer
Classical Physics · Cross-listed from cond-mat.stat-mech
Exact four-vector work distribution and covariant fluctuation theorems of work for a relativistic particle in an expanding piston
Tingzhang Shi, Chentong Qi and H. T. Quan
We investigate the non-
equilibrium four-vector work in an expanding relativistic piston. We derive the exact work distribution in this pedagogical model and find that the joint distribution of four-vector work $(W^0, W^1)$ concentrates on the origin and some curves in the $(W^0, W^1)$ space, rather than being smoothly distributed. In the non-relativistic limit, our model consistently recovers the non-relativistic dynamics. We further demonstrate that the momentum component of four-vector work remains significant in both the Lorentz-relativistic and Galilean-relativistic frameworks. On top of the work distribution, we verify a family of covariant fluctuation
theorems of work. In addition, we introduce a novel geometrical technique for analyzing the dynamics of relativistic collision processes, which can be straightforwardly extended to multi-dimensional piston models.
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Optics
Universal convolution from wave dynamics: photonic processing and encryption in synthetic dimension
Xiaolong Su, Weiwei Liu, Ruiqian Cheng et al. (+6 more)
Convolution, a cornerstone of signal processing and optical neural networks, has traditionally been implemented by mapping mathematical operations onto complex hardware. Here, we overcome this challenge by revealing that wave dynamics in translation-symmetric
lattices intrinsically performs convolution, with the dispersion relation uniquely defining the complex-valued kernel. Leveraging this universal principle, we develop a convolutional architecture of minimal complexity through wave
evolution in programmable photonic synthetic
lattices, delivering high-throughput, multifunctional capabilities at a rate of 13.5 tera-operations per second (TOPS) for image processing. Beyond convolution acceleration, the kernel's complex nature facilitates the photonic simulation of both irreversible
diffusion and reversible
unitary quantum dynamics under classical incoherent excitation. Capitalizing on the physics-based reversibility and undetectable phase information, we demonstrate a novel convolution-driven optical encryption strategy. This work establishes a unified framework for photonic computing by grounding convolution in wave dynamics, opening avenues toward scalable, multifunctional photonic processors with high integration potential.
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All authors Xiaolong Su, Weiwei Liu, Ruiqian Cheng, Haoru Zhang, Xinyao Guo, He Huang, Chengzhi Qin, Peixiang Lu, Bing Wang