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Physics Physics

physics Watch Physics

Friday 4 September

Computational Physics · Cross-listed from nucl-th

FUSION: a skill-based research agent for publicly obtainable nuclear-physics codes

Jin Lei

Running an unfamiliar nuclear-physics code is rarely difficult because of the physics alone. One must find and build the program, learn its input conventions, and decide whether a plausible output is actually correct. A general-purpose coding agent helps with the first two tasks but may make the last one harder: it can write an input file that runs with the wrong physical convention. FUSION addresses this problem with code-specific skills. A skill obtains the code from its public source, starts from a verified input, runs and parses the calculation, records known failure modes, and must reproduce a stated benchmark to a stated tolerance before reporting a result. The current release covers twenty codes, spanning optical models and reactions, nuclear structure, fission and statistical models, astrophysics and R-matrix analysis, and heavy-ion transport. It also includes an offline, searchable collection of 61 167 pages derived from the nucl-th literature. User notes and credentials remain outside the public repository. FUSION is available under the MIT license at https://github.com/jinleiphys/FUSION; documentation is at https://vibeinscience.com. Here I describe the design, the checks behind the current release, and one complete calculation from input to comparison with measured data.
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Plasma Physics

Activated carbon-assisted anionic dye decomposition using a dual-liquid post-double dielectric barrier discharge plasma reactor

Krishna V S, Surya and Mangilal Choudhary

Non-thermal Plasma (NTP) technology, including the Dielectric Barrier Discharge (DBD) reactor, has emerged as an effective advanced oxidation process (AOP) for treating persistent organic pollutants in industrial wastewater. Based on this objective, a dual-liquid dielectric-barrier-discharge plasma reactor was built and used to degrade a ternary anionic dye mixture comprising Reactive Red 120, Congo Red, and Methyl Orange in its post-discharge configuration. The adjustable length of the outer liquid electrode (grounded) provides flexibility in controlling the discharge length and cooling, thereby achieving higher degradation efficiency and greater reactor stability. The conducting-liquid high-voltage electrode (a dielectric tube filled with a conductive solution) helps mitigate metal corrosion and oxidation caused by reactive species in the discharge zone. A detailed study of the degradation of ternary anionic dye mixtures (simulated dye wastewater samples) in the presence of activated carbon (AC) was performed to explore the potential applications of post-discharge treatment. The activated carbon (granules) enhances the degradation rate of ternary anionic dye mixtures in basic solutions rather than in acidic or neutral solutions. A comparative study of the degradation reaction kinetics of the ternary anionic dye mixtures in acidic and basic solutions was conducted after analyzing UV-Vis absorption spectra. The role of other parameters, such as solution pH, the mass and size of AC particles, dye concentrations, and AC reuse, was investigated in relation to degradation efficiency. The degradation mechanism was elucidated by the formation of strong oxidizer (hydroxyl radicals) on the surface of activated carbon during post-discharge treatment. However, in acidic or neutral anionic dye solutions, the degradation mechanism was dominated by ozone.
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Optics · Cross-listed from quant-ph

Nitrogen Vacancy Centers in Diamond for Quantum Biosensing: Magnetometry Techniques, Platforms and Applications

Sirsendu Ghosal, Umakant Prajapati, Sachin Negi et al. (+3 more)

Quantum sensing using nitrogen-vacancy (NV) centers in diamond has emerged as a powerful platform for detecting ultra-low magnetic fields under ambient conditions. Owing to their long spin coherence times, optical addressability, and compatibility with aqueous environments, it has found widespread applications in biosensing and bio-imaging. This review presents the fundamental principles and recent advances in NV-based quantum magnetometry for biosensing applications, with a particular focus on measurements in aqueous medium and at cellular and molecular length scales. We discuss the underlying spin physics of NV centers and highlight two primary detection modalities: optically detected magnetic resonance (ODMR) and T1 relaxometry-based sensing and how these approaches aids in the detection of both static magnetic fields and dynamic magnetic noise arising from biological processes. The review explores key application areas, including nanoscale nuclear magnetic resonance (NMR), monitoring of neural activity, detection of abnormal or rogue cells using NV-based platforms etc. In addition, strategies for enhancing sensitivity, such as surface functionalization of nanodiamonds, femtosecond (fs) laser-written photonic structures, and integration with microfluidic and lab-on-chip systems have also been discussed in depth. We also address the critical challenges, including surface-induced decoherence, charge-state instability, and signal-to-noise limitations in biofluids associated with NV-based biosensing applications. Finally, we outline future prospects, highlighting how NV-based magnetic biosensing provides a promising pathway for translating quantum sensing technologies into practical biomedical applications.
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All authors Sirsendu Ghosal, Umakant Prajapati, Sachin Negi, Saifian Farooq Bhat, Thejas B, Vibhav Bharadwaj

Physics Education · Cross-listed from cs.SE

Building a research-software catalog with a coding agent: from hackathon prototype to public deployment

Kazuyoshi Yoshimi, Satoshi Terasaki and Gotai Yamada

Generative AI and coding agents can accelerate research software development, but they also increase the need for efficient software discovery and maintenance. We developed a repository catalog during a three-day hackathon and subsequently examined the engineering required to make it suitable for public deployment, including adversarial review, data-quality checks, browser-level validation, and publication safeguards. We then explored whether the lessons learned from this prototype could be transferred to a much larger, human-curated portal, through a retrieval agent under development for MateriApps that combines curated portal metadata, external documentation, vector search, and local language-model generation. Implementation with coding agents was rapid, but achieving reliable operation required substantial additional engineering: the most consequential problems were not crashes but silent failures that produced plausible yet incomplete or incorrect outputs, arising from incomplete data acquisition, misleading assessments, and retrieval or preprocessing failures. These observations suggest that AI-assisted software portals require explicit validation, monitoring, and repeated review, and that curated metadata and maintained documentation remain essential. The MateriApps work is exploratory and remains under active development, so the observations reported for it are preliminary; a comparable combination of curated metadata, automatically collected documentation, and retrieval-based assistance may nevertheless be useful for extending other research-software portals.
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Chemical Physics

Voltage-embedded equivariant machine learning potential for open system simulations

Yiming Guan, Rongzhi Gao, ChiYung Yam et al. (+2 more)

Modeling electrochemical interfaces under operational non-equilibrium conditions is vital for energy technologies but remains bottlenecked by the expensive cost of ab initio methods. Current machine learning potentials, largely designed for closed systems under homogeneous electric fields, are limited in open quantum transport applications. To overcome this, we present an E(3)-equivariant graph neural network that embeds voltage bias for open-system simulations. Our approach decouples the system energy and forces into zero-bias and bias-dependent contributions, assigning distinct vector encodings to electrode and scattering-region atoms to capture non-equilibrium conditions. Trained on limited discrete bias data, the model achieves high predictive accuracy and robust extrapolation transferability. When applied to a lithium/water interface, our model successfully captures the field-induced dynamic reorientation of water molecules and reproduces asymmetric electrochemical behavior at different electrodes.
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All authors Yiming Guan, Rongzhi Gao, ChiYung Yam, GuanHua Chen, Ziyang Hu

Physics and Society

Low-Dimensional Phase Diagram of Higher-Order Networked Systems

Jia-Jie Qin, Jack Murdoch Moore, Xiaozhu Zhang et al. (+1 more)

Higher-order networks exhibit rich critical phenomena that cannot be captured by traditional pairwise models. Here, we develop an analytical dimension-reduction framework that maps higher-order networked dynamics onto an effective low-dimensional system, allowing accurate prediction of tipping boundaries, bistability regions, and the nature of phase transitions. We demonstrate the power of this framework across a range of dynamical processes, revealing distinct effects of higher-order interactions on transition continuity and hysteresis. Furthermore, we find that system resilience exhibits a profound dependence on the alignment between pairwise and higher-order connectivity, with assortative mixing enhancing tipping toward active states. Our findings establish a general theory for understanding the critical transitions in higher-order networks, offering new insights for anticipating and managing systemic risk in complex systems.
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All authors Jia-Jie Qin, Jack Murdoch Moore, Xiaozhu Zhang, Gang Yan

Computational Physics · Cross-listed from math.NA

A class of high-order discontinuous-Galerkin methods satisfying infinitely many entropy conditions with provable error estimates and strong convergence for general nonlinear conservation laws

Yuanzhe Wei and Chi-Wang Shu

We propose a novel framework for deriving semi-discrete discontinuous-Galerkin (DG) methods using operator semigroups for scalar conservation laws, then apply it to construct a class of high-order OFDG-type schemes [13] satisfying infinitely many local entropy inequalities with general E-fluxes on non-uniform meshes. Such schemes are further generalized to systems of conservation laws in any number of space dimensions by using entropy stable numerical fluxes in the sense of [1]. Finally, we prove optimal error estimates for smooth solutions to nonlinear scalar conservation laws, and prove strong convergence for discontinuous solutions to strictly convex conservation laws via compensated compactness.
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Optics

Research and simulation of analytical polarization control enabled by optical computing on an integrated photonics chip

Xueying Ren, Meinan Guo, Xuyang Wang et al. (+8 more)

Dynamic polarization controllers are key devices with broad applications in many fields. However, most on-chip polarization controllers still rely on traditional blind-search methods, whereas analytical optical-computing approaches remain insufficiently explored, particularly with respect to calibration and endless polarization control. With the accurate relative phase of Mach-Zehnder interferometer (MZI) being fully controllable on an integrated photonics chip, we present an analytical polarization control (APC) method using four phase shifters and optical computing, eliminating the need for the traditional inefficient blind-search procedure. The basic structures and operations of APC are clarified. The proposed calibration method and endless control method enable continuous APC while compensating for phase differences within the MZI structures. We simulate the influence of the endless control unit on polarization control and quantify the effect of the fourth phase difference on the output extinction ratio. With the fourth phase shifter, the phase difference encountered during Stokes vector measurement can be effectively compensated, and rotations around all three axes on the Poincaré sphere can be realized. These results establish a practical APC architecture based on optical computing for photonics chips. The proposed APC methods, combined with a FPGA-based hardware acceleration, will enable high speed on-chip polarization controllers.
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All authors Xueying Ren, Meinan Guo, Xuyang Wang, Bailin Shen, Lingyan Zhang, Minyue Yang, Nannan Ning, Jiaxin Huang, Lv Lv, Jun Zou, Yongmin Li

Optics

High-Performance Photonic Crystal Biosensors using Sub-wavelength Nanopillars

Zhengzheng Zhai and Sajeev John

Photonic-crystal (PC) slabs composed of subwavelength silicon pillars erected on a thin silicon backing layer, with heights of only one or half lattice constant, are simulated for optical biosensing by numerical solution of Maxwell's equations. Localized optical cavity modes that form waveguides in the direction of biofluid flow, with quality factors surpassing \(10^4\), are embedded within the 2D photonic band gap of the 3D structure. Remarkable sensitivity to analyte binding is achieved using fragmented thin silicon pillars in regions of maximum localized optical-field intensity. Exceptional quality factors are realized through destructive wave interference of vertical radiation loss. This provides a rare combination of high sensitivity and low limit of detection in a device with minimal time requirement for analyte binding. The sensitivity to analyte binding is a frequency shift of nearly \(0.004\,[2\pi c/a]\) per analyte-thickness increment \(0.1a\). The sensitivity to background biofluid change is about \(4800\) nm per refractive index unit (RIU) for a specific lattice constant \(a = 5\,\mu\mathrm{m}\) using light of wavelength \(16.5\,\mu\mathrm{m}\).
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Applied Physics · Cross-listed from cond-mat.mtrl-sci

4 MV/cm (010) $\beta$-Ga$_2$O$_3$ Heterojunction Diodes Realized by Low-Damage e-Beam NiO$_x$ Interlayers

Carl Peterson, Yizheng Liu, Chinmoy Nath Saha et al. (+3 more)

We report on the utilization of a low-damage e-beam NiO$_x$ deposition process to realize field-plated heterojunction diodes (FP-HJDs) on (010) $\beta$-Ga$_2$O$_3$ films with high critical breakdown field strengths beyond 4 MV/cm and power figure of merits (PFOM) of >1 GW/cm$^2$. Diodes were fabricated on a 2.67 $\times$ 10$^{16}$ cm$^{-3}$ intentionally doped 6.2 $\mu$m thick epitaxial layer grown by metalorganic chemical vapor deposition (MOCVD) on a conductive Sn-doped $\beta$-Ga$_2$O$_3$ (010) substrate using TMGa, O$_2$, Ar carrier gas, and SiH$_4$ as the silicon dopant source. The mesa etched FP-HJD devices utilized a thin 7 nm e-beam NiO$_x$ interlayer before the sputtered NiO$_x$ layers to eliminate the effects of sputter-induced ion damage on the (010) epilayers. Current-Voltage measurements resulted in a forward current density of 700 A/cm$^2$ at 4 V, HJD ideality factor of 1.29, a V$_{bi}$ of 2 V, rectification ratio of 10$^{11}$, and a differential specific on resistance (R$_{on,sp}$) value of 2.36 m$\Omega$ $\times$ cm$^2$. Breakdown of the (010) FP-HJDs was 1.64 kV, leading to a parallel plane electric field at breakdown (E$_{||,max}$) of 4.02 MV/cm and a PFOM of 1.14 GW/cm$^2$, which is a state-of-the-art result for diodes on MOCVD-grown (010) drift layers.
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All authors Carl Peterson, Yizheng Liu, Chinmoy Nath Saha, Rachel Kahler, Akhila Mattapalli, Sriram Krishnamoorthy

Atmospheric and Oceanic Physics

Impact of extremely high temperature on future photovoltaic power potential over East Asia

Changyong Park, Ana Juzbasic, Dong-Hyun Cha et al. (+5 more)

As global warming intensifies, the frequency and intensity of extremely high temperatures are expected to increase. This will impact the production of photovoltaics (PVs), which are increasingly adopted as an effective alternative to replace fossil fuel-based energy sources and reduce CO2 emissions. Furthermore, extremely high temperature days account for a considerable proportion of days with high PV power potential (PVpot). Therefore, this study investigates changes in PVpot on future extremely high temperature days over East Asia, a region with high greenhouse gas emissions and vulnerability to extreme climatic events. The East Asia-averaged PVpot for extremely high temperature days was estimated to decrease across all scenarios and future periods. The East Asia-averaged PVpot for extremely high temperature days was predicted to decrease more substantially toward the late 21st century, with a larger magnitude of decrease expected under the high-carbon emissions scenario compared to the low-carbon emissions scenario. By the mid-and late 21st century, PVpot for extremely high temperature days was projected to decrease in PV hotspot areas, particularly in the regions of northern China and southern Mongolia, by up to -7.2 %. The signs of PVpot projections vary across sub-regions under summer mean conditions, while on extremely high temperature days, PVpot is consistently expected to decrease in all regions. This suggests that extremely high temperatures further intensify the decrease in PVpot. Moreover, under extremely high-temperature conditions, near-surface air temperature has been identified as the primary driver of projected decreases in PVpot among the climate variables considered; its influence is expected to intensify over time, thereby accelerating PVpot decreases under the high-carbon emissions scenario.
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All authors Changyong Park, Ana Juzbasic, Dong-Hyun Cha, Seung-Ki Min, Joong-Bae Ahn, Eun-Chul Chang, Young-Hwa Byun, Youngeun Choi

Fluid Dynamics

Elastic turbulence in straight confined geometries

Giulio Foggi Rota, Daulet Izbassarov, Aditya Tekriwal et al. (+1 more)

Elastic turbulence (ET) in straight geometries has been extensively studied in idealised configurations such as periodic shear and planar channel flow, yet experiments are typically restricted to confined systems like ducts and pipes. While chaotic elastic fluctuations are observed in ducts, their onset in pipes is debated due to geometric constraints. Here we report sustained chaotic dynamics in both geometries and show they correspond to the same ET state identified in idealised setups. Our results establish ET as a geometry-independent attractor and point to a distinct transition mechanism in pipes.
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All authors Giulio Foggi Rota, Daulet Izbassarov, Aditya Tekriwal, Marco Edoardo Rosti

Fluid Dynamics

Transport fidelity and domain of validity of compact Gaussian kinetic representations for rarefied flows

Ehsan Roohi

Compact representations of rarefied flows must retain nonequilibrium transport information while identifying their range of validity. We investigate a common localized-Gaussian strategy for discrete-velocity-method (DVM) states in monatomic normal shocks and lid-driven cavities. The strategy is specialized to the available kinetic state: a positive phase-space mixture represents shock distributions and regenerates their moment hierarchy by quadrature, whereas a shared-support physical-space map represents 20 cavity fields. Localized support, continuous evaluation, transport fidelity, and coefficient-count accounting therefore provide the common structure across the two benchmarks. For separately fitted Mach-3 and Mach-5 shocks, the method gives sub-percent errors in conserved quantities and approximately 1–2% errors in transport and higher-order moments. At the same 4608-coefficient budget, the tested multilinear grids produce 89–98% errors in these nonequilibrium quantities. For both cavity cases, the Gaussian map also outperforms matched bilinear and singular-value-decomposition baselines, reducing maximum errors by factors of approximately 7–24. In the Mach-conditioned tests, a correspondence-preserving local basis reduces the withheld Mach-6 distribution error from $42.86\pm5.40\%$ to $11.45\pm0.94\%$ at fixed storage, while its transport errors remain 30–40%; a normalized-coordinate guard rejects Mach 12 outside the training range. Independent grid studies confirm that these trends are not dominated by DVM discretization error. The results establish localized Gaussian representations as storage-efficient transport-fidelity maps for fitted kinetic states and provide quantitative acceptance criteria for parametric use.
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Optics

Band Gaps and Localization of Surface Waves at Hyperbolic Material and Topological Insulator Interfaces

Andrei I. Maimistov, Ildar R. Gabitov and Ilia Kuk

We develop analytical criteria for surface electromagnetic waves at interfaces between hyperbolic materials and topological insulators. The analysis identifies propagation conditions, field penetration depths, and spectral band gaps. In the lossless model, the band edge is governed primarily by dielectric contrast, while the bulk topological coupling produces only a small shift and a weak correction to the dispersion. For structures combining hexagonal boron nitride with bismuth selenide, a thin topological insulator film on a dielectric substrate with low permittivity can substantially broaden the accessible propagation window. We also analyze a dissipative titanium and silicon hyperbolic effective medium interfaced with bismuth selenide. To make the complex branch structure visible, this lossy calculation uses an intentionally enhanced interface response and is therefore illustrative rather than a quantitative prediction for a conventional topological insulator. In the lossy case, a root of the dispersion relation represents a physical guided mode only when the fields decay away from the interface, attenuate consistently along the propagation direction, have finite penetration depths, and exhibit a consistent energy flow profile. Apparent gaps and jumps can occur when the complex quantities controlling transverse decay approach square root branch cuts. These results provide design guidelines for controlling dispersion, confinement, band gaps, and propagation loss in mid-infrared photonic structures.
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Classical Physics

Cartesian isotropic tensors revisited

Antonio O. Bouzas

An alternative, streamlined methodology is presented for deriving the isotropic Cartesian tensor bases under the special orthogonal group $\text{SO}(3)$. By shifting the traditional interpretation of the isotropy condition to analyze it as an algebraic system of equations for the rotation matrices themselves rather than the tensor components, lower-rank bases can be explicitly established in just a few lines without requiring finite coordinate rotations or complicated contractions of infinitesimal generators. Furthermore, a transparent combinatorial interpretation is provided for the number of tensors in the general higher-rank spanning sets. Finally, the Gram-matrix method is advocated as an efficient computational sieve to resolve the subsequent linear dependence.
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Thursday 3 September

Data Analysis and Statistics

Theoretical–operational modelling of complex experiments: parameter robustness and degeneracy in muon–electron conversion

Vitaly Pronskikh

Complex experiments infer theory parameters through a coupled chain of physical models and data reduction. We formulate the theoretical–operational model (TOM) as a typed factorization of this forward prediction and study how changes of preparation, phenomenon modelling, readout, backgrounds, and analysis project onto the local manifold generated by the physics parameters. For a smooth prediction and a locally identifiable weighted least-squares estimate, the resulting response map separates each model deformation into a parameter-equivalent component and a residual component that cannot be absorbed by a change of the fitted physics parameters. This gives local criteria for robustness, exact degeneracy, and partial degeneracy of parameter inference. The construction is applied to charged-lepton-flavour-violating muon–electron conversion in aluminium. A one-bin conversion-rate model exhibits an exact normalization degeneracy. In a two-template model of the elastic–inelastic spectrum, a common signal normalization is absorbed by the fitted conversion rate without changing an operator-sensitive nuclear-response ratio, whereas a relative elastic–inelastic efficiency change is exactly parameter-equivalent to a change of that ratio at first order. A numerical Run-I example based on published Mu2e spectra shows that a \(100\,\mathrm{keV}/c\) momentum-scale mismatch is only partially parameter-equivalent: its projection ratio onto the local tangent space generated by the elastic normalization \(R_0\) and the logarithmic inelastic-to-elastic response ratio \(\rho\) is \(\eta=0.331\), while most of the weighted spectral deformation remains as a residual shape. TOM thereby provides a local theoretical description of parameter robustness and degeneracy at the interface of particle/nuclear phenomenology and experimental realization.
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Atmospheric and Oceanic Physics

Calibrating subgrid parametrizations of single-column ocean models via simulation-based inference

Luben M. C. Cabezas, Sacha Wendling, Aurèle Gallard et al. (+3 more)

Subgrid parametrizations of vertical mixing in ocean models depend on free coefficients that cannot be measured directly and must be calibrated against high-fidelity references such as large-eddy simulations (LES). Existing approaches return point estimates and leave the associated uncertainty unquantified, a limitation when the inverse problem is ill-posed or when distinct parameter configurations fit the data comparably well. Simulation-based inference (SBI) addresses exactly this: given a prior and access to the simulator, it approximates the full posterior over parameters without requiring a tractable likelihood, at a cost set by the number of simulator evaluations. We apply it to tunax, a JAX-based single-column ocean model, to calibrate the coefficients of its $k$–$\varepsilon$ closure. A blockwise PCA summary statistic compresses the simulator output along the depth axis while preserving its forcing–horizon–variable structure, making inference tractable at modest budgets. We compare neural posterior estimation and its sequential variants against a recent training-free approach built on a tabular foundation model. The latter recovers informative posteriors from a few hundred simulator calls, outperforming the trained estimators at every budget considered.
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All authors Luben M. C. Cabezas, Sacha Wendling, Aurèle Gallard, Gabriel Mouttapa, Julien Le Sommer, Pedro L. C. Rodrigues

General Physics

Cosmological Constraints on Interacting Scalar-Field Dark Matter and Early Dark Energy mediated by a Kinetic Kernel

Gabriela Garcia-Arroyo, L. Arturo Ureña-López and J. Alberto Vázquez

In this work, we build a general framework for constraining interacting scalar fields with cosmological observations, applicable to a broad family of scalar–field potentials and interaction kernels. As a representative example, we derive constraints on a model in which dark matter is described by a scalar field $\phi$ with a quadratic potential and dark energy by a scalar field $\psi$ with the Albrecht–Skordis potential, considering both the uncoupled case and a more general scenario in which the exchange of energy occurs through an interaction kernel proportional to the kinetic energies of the scalar fields $Q \propto \dot{\phi}^2 \dot{\psi}^2$. The scalar field parameters are constrained by using Planck 2018 CMB data, DESI BAO measurements, Ly-$\alpha$ forest constraints, and SNeIa observations, and we find that the scalar field parameters are driven toward their $\Lambda$CDM-like limits; the early dark energy fraction is largely suppressed, and the SFDM mass is bounded to values for which the field behaves close to cold dark matter. In the interacting case, the results show no significant preference for the transfer of energy between dark energy and dark matter at 95% C.L. In general, the model keeps $H_0$ close to the Planck-$\Lambda$CDM range and provides best-fit $\chi^2$ values comparable to those of the corresponding $\Lambda$CDM fits.
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General Physics

Observational constraints on Diffusion Cosmologies in Unimodular Gravity from DESI DR2

Gabriel Gomez, Guillermo Palma and Norman Cruz

Diffusion functions in unimodular gravity induce a dynamical effective cosmological constant, providing an appealing framework in light of recent DESI observations. In this work, we investigate the observational viability of a general class of diffusion models using baryon acoustic oscillation measurements from DESI DR2, Type Ia supernova compilations (Pantheon+, DES-Dovekie, and DESY5), and Cosmic Chronometer data. We find that diffusion models systematically achieve lower best-fit $\chi^{2}$ values than $\Lambda$CDM across all dataset combinations considered, indicating a modest but persistent improvement in goodness of fit. Nevertheless, the reduction in $\chi^{2}$ is insufficient to offset the larger parameter space, leading standard information criteria to favor the simpler $\Lambda$CDM model. Despite this result, all dataset combinations consistently prefer a nonvanishing diffusion contribution corresponding to approximately $20\%$ of the present dark-energy budget, with a posterior probability $P(f_Q>0.05) =96.78\%$. From an observational perspective, diffusion models therefore remain a viable extension of the standard cosmological scenario and motivate the exploration of simpler diffusion parameterizations, particularly in light of upcoming high-precision cosmological surveys.
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General Physics

Cosmological constraints on the interacting viscous dark matter and decaying vacuum energy models

Lokesh Chander and C P Singh

We investigate an interacting dark sector scenario in which a deviation from the standard dilution law of cold dark matter is parametrized by a perturbative correction $\epsilon$, thereby inducing a dynamical vacuum component. We extend this framework by allowing dark matter to behave as an imperfect fluid with bulk viscosity. Within the Eckart formalism, we consider a power-law dependence of the bulk viscous coefficient on the dark matter energy density which yields an effective density scaling for the viscous pressure. We obtain the parameter constraints using multi-nested sampling with Dynesty, employing DES 5YR Type Ia Supernovae, DESI Baryon Acoustic Oscillations, Cosmic Chronometers, the local $H_0$ measurement from H0DN, and Cosmic Microwave Background distance priors. Redshift Space Distortion measurements from SDSS-IV and the DES weak-lensing constraint on $S_8$ are included to probe structure formation. We also examine the thermodynamic consistency of the cosmological scenarios and find that they satisfy the Generalized Second Law of thermodynamics. We find that bulk viscous effects can modify the late-time interaction dynamics, while their contribution is suppressed once early-Universe information is included. These results provide observational and thermodynamic constraints on departures from the standard cold dark matter evolution and a constant vacuum energy.
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Fluid Dynamics · Cross-listed from math.NA

Geometry Parameterisation via a Structural Modal Basis for Aerodynamic Shape Optimisation

Alwin Wang, Robert Carrese, Luca Brown et al. (+2 more)

Aircraft outer mould lines are often heavily constrained early by payload requirements, manufacturability limits, and low-observability considerations. The remaining aerodynamic design space is typically small, highly constrained, and difficult to represent using a concise and physically meaningful set of design variables. A structural modal parameterisation method (MPM) is introduced for such problems. The method constructs a tunable pseudo-structure and solves its eigenvalue problem to obtain a modal basis, from which a selected subset of modes parameterises the geometry. Boundary conditions, stiffness distribution, density, thickness, and added masses are treated as intentional basis-design variables that shape the admissible deformation space prior to optimisation. The resulting design coordinates are independent of any specific flow solver, making the approach broadly applicable. For tightly constrained aerodynamic shape optimisation problems, it provides a practical balance of parameter conciseness, robust constraint awareness, and geometric flexibility.
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All authors Alwin Wang, Robert Carrese, Luca Brown, Joel Collins, Pier Marzocca

Physics and Society

Response-Aware Coarse-Graining in Summary-Mediated Opinion Dynamics

Ruben E. Araújo

Interacting populations increasingly respond to compressed representations generated from their own collective state. We ask which information such an endogenous coarse-graining must preserve in order to reproduce the collective dynamics. The question has two complementary answers for continuous opinions with attraction, indifference, and repulsion. Inside any strict $K$-bloc response cell where every represented stance attracts every bloc, the dynamics reduce exactly to translation and disagreement. The represented distribution's shape cancels from all disagreement modes, which form a homogeneously anchored weighted signed-Laplacian system, while represented-mean error acts only on translation. This reduction yields a geometry-dependent stability boundary and shows that prevalence bias produces secular drift at marginal stability only through its projection onto the neutral eigenspace. Outside that common linear-response regime, threshold geometry makes distributional information observable. The induced force discrepancy is a behavior-defined integral probability metric; restricted force probes identify generic finite empirical discussions, and for finitely supported candidates uniform force error controls total-variation and Wasserstein error while support reduction incurs a nonzero distortion floor. A cumulative-discrepancy characterization further explains why transport-small summaries can remain behaviorally inaccurate at response thresholds. Mode-resolved integrations, projected particle simulations, finite-size ensembles, and threshold-crossing experiments test these two regimes. As a deployment consequence, broadcast summary error survives as collective noise whereas independently personalized error self-averages. The model is stylized and not empirically calibrated; generated discussion summaries motivate the general problem of endogenous, response-aware coarse-graining.
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Geophysics

Estimating subsurface water mass changes with ground-based gravimetry

Isabelle Schmidt, Jackson Ang'ong'a, Peter Bauer-Gottwein et al. (+10 more)

Gravitational force is proportional to the mass of an attracting body; therefore, changes in subsurface mass can be detected using gravimetry. In the near subsurface, mass variations are primarily driven by changes in water storage, meaning that gravity measurements provide direct information on variations in water mass. Traditionally, groundwater and soil water dynamics are monitored using point-scale instruments that require direct installation into the subsurface. In contrast, gravimetry is a non-invasive method that integrates signals over a larger spatial extent. Recent advancements in gravimeter technology have significantly improved measurement accuracy and long-term stability under field conditions, thereby expanding their potential for hydrological applications. This review summarizes recent developments in gravimetric instrumentation and provides essential background on gravimeters used for ground-based measurements and their application in hydrology, aiming to facilitate their broader use. In addition, it presents an overview of studies in hydrology and hydrogeology that have successfully applied gravimetry to quantify subsurface water storage changes, estimate hydrological parameters, and constrain numerical models. A perspective on future advancement in gravimetry and resulting potential applications is given.
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All authors Isabelle Schmidt, Jackson Ang'ong'a, Peter Bauer-Gottwein, Stephan Costabel, Christian Freier, Bastian Leykauf, Tina Lundgren, Miguel Martinez-Dorantes, Achim Peters, Ernst Rasel, Enrico Vogt, Gregor Willkommen, Vladimir Schkolnik

Classical Physics

Symmetry Promotion in Electromagnetism

Hunter Swan and Jason M. Hogan

A symmetric distribution of charges or currents typically produces an electromagnetic field having the same symmetry group. However, under special circumstances we show that a discrete symmetry of the source distribution leads to a larger continuous symmetry for the resulting field in restricted regions. The conditions for this promotion from discrete to continuous symmetry are that the fields be affine linear and the symmetry of the source distribution act irreducibly on the ambient space. We illustrate this effect with many examples. This phenomenon is pedagogically interesting both as a source of inspiration in electro- and magnetostatics and as an accessible example of group representation theory.
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Optics

Nonlinear Photoemission for Bright Beams in X-Band Photoinjectors

Casey Timms, Lucas Malin, Kevin Eckrosh et al. (+15 more)

The ongoing development of low-cost and compact x-ray light sources is vital for increasing the number of experiments that can be performed at the atomic scale. One option for a compact and simple photoinjector is to operate in blow-out mode, in which a high-charge, short-bunch length electron beam self-expands by space-charge forces into a uniformly ellipsoidal shape. This mode necessitates a photoinjector whose initial electron pulse has a pulse duration on the order of $100$ fs. A photoinjector utilizing linear photoemission with an ultraviolet laser in this regime presents significant technical challenges, as many optical substrates degrade at these wavelengths. In this paper, we present an alternative design that uses nonlinear photoemission to produce electron beams with high charge and short bunch length in an X-band (9300 MHz) photoinjector. This photoinjector design produces an electron beam with a bunch charge of up to $200$ pC, an RMS bunch length of $291$ fs, a normalized transverse emittance of $1$ to $1.4$ mm$\cdot$mrad, and an energy spread of $10^{-4}$. This results in a beam brightness of $10^{18}$ A/m$^2$, which is bright enough for our beamline's purposes. We also present ongoing efforts are aimed at further increasing the electron beam brightness by using a spatial light modulator to shape the laser profile at the cathode.
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All authors Casey Timms, Lucas Malin, Kevin Eckrosh, Sean E. Tilton, Lidia C. Santander, Hyung Seo Lee, Rejul Jaswal, Alex Gardeck, Eric Everett, Alan Dupre, Mukhtar Hussain, Sami Tantawi, William Graves, Henrik Loos, Mark Holl, Arvinder Sandhu, Robert Kaindl, Samuel Teitelbaum

Chemical Physics · Cross-listed from cs.AI

La Agente Óptima: Towards Agentic Self-Driving Laboratories

Marcel Müller, Jiaru Bai, Willi Gottstein et al. (+14 more)

Self-driving laboratories (SDLs) combine automated experimentation with adaptive decision-making to accelerate scientific discovery. Their operation nevertheless often depends on human specialists who translate scientific objectives into executable closed-loop campaigns. Specialists adjust them as data and operating conditions change. Here, we present La Agente Óptima, an agentic framework that constructs and supervises Bayesian optimization campaigns across computational and experimental systems while maintaining a persistent optimization state. By separating large language model (LLM) reasoning from executed campaigns, Óptima runs repetitive optimization loops consistently, returns control to the agent only when progress requires interpretation or campaign revision, and keeps every decision auditable. We evaluate Óptima across ablation studies, five digital discovery tasks, and two physical platforms. Throughout, Óptima maintained executable campaigns as both the scientific problem and execution environment evolved. In a closed-loop contact angle optimization campaign, Óptima identified and corrected a mid-run measurement failure, bringing the contact angle from 71.4 to 67.8 degrees, just above the 64-66 degree range. From this result, Óptima correctly inferred that the target was likely unattainable with the available reagents and recommended changing the formulation. In a five-day multi-objective flow-chemistry campaign, Óptima increased the yield from 30% to 59% over 23 experiments. Despite substantial inference costs, it cost less and used substantially less starting material than a human-directed campaign, while selecting a more mass-efficient operating point. These results show that LLM-based agents can make rigorous, long-running optimization campaigns accessible to domain scientists without specialist setup, expanding the scope of SDLs.
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All authors Marcel Müller, Jiaru Bai, Willi Gottstein, Abhijoy Mandal, Mohammad Nazeri, Elia Savino, Yanlin Fang, Sujoy Das, Sergio Pablo García Carrillo, Yeonghun Kang, Juan B. Pérez-Sánchez, Simone Pilon, Martin Fitzner, Timothy Noël, Frank Gu, Varinia Bernales, Alán Aspuru-Guzik

Atmospheric and Oceanic Physics

When a high-mountain slope failure cascades downstream: physical footprint and evolving exposure of the 2026 Gyirong mixed rock-ice cascade

Rui Li

The 26 August 2026 Gyirong cascade connected a high-mountain failure to developed downstream valleys. Event-bracketing observations delineate a preferred changed/source surface of 1.01 km^2, within alternative interpreted envelopes of 0.49-1.84 km^2, and a representative 21.8 km source-to-port route descending 3.40 km. Across two precipitation products, five antecedent windows and six fixed spatial supports, all 60 matched-year ranks remain below the 90th-percentile wet threshold. The source-nearest 7-day temperature mean of 9.43 degrees C exceeds all 25 matched years from 2001-2025. Positive temperature anomalies extend to every tested support, but ranks vary from the 88th percentile to above all historical values. Within the subsequently affected 37.354 km^2 UNOSAT footprint, modelled built-up surface increases from 0.036 to 0.441 km^2 between 1975 and 2020; its fraction of the fixed area rises from 0.096% to 1.181%. Delivered rapid maps contain 695 building points and 15.671 km of roads graded destroyed. These measurements connect the physical footprint with environmental context and historical exposure development. They complement existing process reconstruction while leaving the initiation mechanism and the mechanical role of warming unresolved.
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Atomic and Molecular Clusters

X-ray photoelectron spectroscopy of Ar and Kr clusters formed in He nanodroplets

N. S. Blaj, N. Scheel, R. Rajni et al. (+7 more)

We report the first soft x-ray photoelectron spectroscopy (XPS) measurements of Ar and Kr clusters formed inside superfluid helium nanodroplets (HNDs) through consecutive pickup of dopant atoms. Ar and Kr atoms and clusters are selectively inner-shell ionized (Ar 2p, Kr 3d) using monochromatic soft x-ray synchrotron radiation. In the regime of strong doping, the electron spectra exhibit features characteristic of free Ar and Kr atoms as well as their clusters. The Kr cluster spectra agree well with literature data for bare Kr clusters. Backed by detailed simulations of the pickup process, this agreement indicates that the observed spectra originate from nearly bare Ar and Kr clusters, from which most or all He has evaporated in the course of cluster aggregation. These results establish HNDs as a platform for XPS of various types of molecular complexes and nanostructures.
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All authors N. S. Blaj, N. Scheel, R. Rajni, A. Ø. Lægdsmand, J. Sadasivan, S. De, S. R. Krishnan, J. Bozek, A. R. Milosavljević, M. Mudrich

Plasma Physics

Assessing the effect of error field penetration during plasma current ramp-up in the DIII-D tokamak

C. F. B. Zimmermann, E. M. Bursch, C. Paz-Soldan et al. (+4 more)

This work provides evidence that established error field penetration threshold scalings remain applicable during plasma current ramp-up. In dedicated DIII-D experiments with imposed $n=1$ perturbations during extended $I_p$ ramps, an apparent empirical threshold is found between $2$ and $3$~kA of applied 3D coil current, above which MHD modes are seeded. The imposed perturbation couples to the rational surfaces present during the ramp, seeding near the $q=4$ surface and penetrating as an $m/n=3/1$ mode by the end of the perturbation phase. To interpret these observations, multi-machine penetration threshold scalings are combined with equilibrium-based overlap metrics from the GPEC code, including the in-situ error fields of the device. This modeling reproduces the observed onset in the amplitude scan and classifies mode seeding across a database of 12 ramp-up discharges spanning a range of plasma currents and densities. Across this database, the seeding appears to be controlled primarily by the applied 3D coil current rather than by the plasma current or its ramp rate. Accounting for the in-situ error fields is found to be important for reliable prediction. These results are consistent with the robustness of scaling-based penetration metrics when coupled to detailed 3D field modeling under transient ramp-up conditions, and suggest the importance of accounting for in-situ error fields when assessing additional externally induced perturbations. This work is motivated by future tokamaks in which transient, non-axisymmetric error fields can arise during startup, for example from runaway electron mitigation coils.
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All authors C. F. B. Zimmermann, E. M. Bursch, C. Paz-Soldan, J. M. Hanson, N. Leuthold, N. C. Logan, A. O. Nelson

Fluid Dynamics

Lagrangian dynamics unveil polymer conformation in viscoelastic flows

Louison Thorens, Gabriel Juarez, Jeffrey S. Guasto et al. (+1 more)

The complex flow behavior of viscoelastic fluids emerges from a feedback between fluid stress and the out-of-equilibrium conformational dynamics of their constituent polymer chains. While constitutive models can predict flow and stress fields in simple geometries, a fundamental understanding of the mechanisms regulating viscoelastic flows with mixed kinematics and non-trivial polymer dynamics remains elusive. Quantifying the history-dependent conformation of polymer chains in flow is essential to resolve these complex systems. To address this knowledge gap, we employ direct Lagrangian tracking of individual DNA molecules to reveal their conformational dynamics in microfluidic viscoelastic flows for different polymer contour lengths and concentrations. Comparing the measured molecular extension and orientation reveals discrepancies with canonical constitutive models, which do not fully capture the transient dynamics. Our measurements show a distinct anisotropy in polymer relaxation and shape, which couple the polymer's rotation and extension through hydrodynamic drag, regulating their Lagrangian mechanics. These findings emphasize the importance of Lagrangian polymer history and the need to account for non-trivial intra-molecular mechanics to improve constitutive descriptions of viscoelastic flows.
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All authors Louison Thorens, Gabriel Juarez, Jeffrey S. Guasto, Paulo E. Arratia