Fluid Dynamics · Cross-listed from cond-mat.soft
Diffusion from particle-coated drops: the subtle role of particle size
Alexandros T. Oratis, Matteo Camagna, Timo J.J.M. van Overveld et al. (+1 more)
Many natural and industrial systems involve particle-laden interfaces. Because interfacial particles prevent the coalescence and coarsening of drops, they hold promise for various applications requiring stable emulsions. Despite their remarkable ability to stabilize emulsions, it remains challenging to characterize how particles influence the interfacial transport of dissolved solutes. Here, we quantify the
diffusion from a single particle-coated drop by confining it to a two-dimensional configuration. Using fluorescence microscopy, we extract the intensity profiles of the fluorescent dye as it diffuses from the drop, yielding spatio-temporal measurements of the concentration field. Over a range of particle sizes, the particles impose minimal resistance to
diffusion. We rationalize this counterintuitive result with a mathematical model that couples interfacial mass transfer to a particle-coated interface. We show that the particle monolayer controls the temporal dynamics of the flux across the interface, hindering transport only at extreme coverage fractions beyond the close-packing limit. This framework reveals why particles often fail to hinder
diffusion, offering new pathways to harness mass transfer in particle-stabilized emulsions.
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All authors Alexandros T. Oratis, Matteo Camagna, Timo J.J.M. van Overveld, Valeria Garbin
Optics
Frequency combs and coherent dissipative structures in nonlinear optical microresonators
Tobias Herr, Alexey Tikan and Tobias J. Kippenberg
Laser-driven high-Q Kerr-nonlinear optical microresonators enable parametric oscillation with low-power continuous-wave
lasers and host a variety of coherent dissipative structures, including dissipative Kerr
solitons and switching waves. These time-periodic structures constitute coherent optical frequency combs, and photonic-chip integration has miniaturized them to the chip scale. Such photonic-integrated, microresonator-based frequency combs - often termed 'microcombs' or 'Kerr combs' - have been demonstrated in various system-level and scientific applications. They complement femtosecond-
laser-based frequency combs when high repetition rates, broad bandwidths, or high power per comb line are needed. This review introduces the field of microcombs and outlines the fundamental physical principles governing the generation of coherent frequency combs in microresonators.
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Instrumentation and Detectors
A Data-Driven Fast Simulation Approach for MAPS-based Detectors and their Optimization
Dumitru Vlad Berlea, Lucian Fasselt, Prafulla Behera et al. (+21 more)
A parametric simulation tool for pixel sensors is presented. A realistic pixel response is simulated purely based on measurement input, without requiring detailed knowledge of the underlying manufacturing process. As such, it provides an efficient alternative to the use of Technology Computer-Aided Design simulations, which typically depend on proprietary process information. Due to its parametric approach, the package is fast and thus particularly useful for larger detector systems and high hit rate environments. This work presents measurements, simulation and its validation for the MALTA2 sensor. It is a small collection electrode monolithic active pixel sensor produced in the Tower 180nm Complementary Metal-
Oxide-
Semiconductor imaging process. Modifications to the sensor's periphery, mainly in the hit merger, are studied in order to optimize the performance for tracking and calorimetry. This optimization is of special interest as part of the MALTA3 sensor redesign in the 65nm Tower Partners
Semiconductor Co. process.
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All authors Dumitru Vlad Berlea, Lucian Fasselt, Prafulla Behera, Daniela Bortoletto, Craig Buttar, Theertha Chembakan, Valerio Dao, Ganapati Dash, Sebastian Haberl, Tomohiro Inada, Fuat Kerem Isik, Cigdem Issever, Xuan Li, Long Li, Heinz Pernegger, Petra Riedler, Walter Snoeys, Carlos Solans Sánchez, Anna Swoboda, Ilkay Turk Cakir, Milou van Rijnbach, Anusree Vijay, Julian Weick, Steven Worm
Fluid Dynamics
Elasto-inertial transitions in viscoelastic flows through cylinder arrays
Jack R. C. King, Henry M. Broadley and Miguel Beneitez
For dilute solutions of
polymers, chaotic flow states can occur at lower Reynolds numbers than required for inertial
turbulence in Newtonian fluids, offering the potential for increased mixing efficiency. These states may be promoted by the flow geometry, and in recent years, porous media have gained
attention as a promising setting in which viscoelastic instabilities may be exploited, although studies have primarily been in the creeping flow regime. Cylinder arrays serve as a prototypical porous media, giving a controlled setting in which to investigate flow dynamics. Here we explore the transition to elasto-inertial
turbulence (EIT) in cylinder arrays via detailed numerical simulations. With increasing elasticity, EIT is reached via an initial sub-critical saddle-node bifurcation from the Newtonian state and then follows a series of supercritical bifurcations, in a Ruelle-Takens-Newhouse route to chaos. This transition is driven by the interaction between
vortex shedding in cylinder wakes, and the bulk flow between cylinders. Within the EIT regime, we observe an interaction between slow dynamics in cylinder wakes, and fast dynamics in channels between cylinders, leading to two distinct slopes in the energy spectra. At low Reynolds numbers arrowhead structures are present, but these are suppressed at higher inertia. In the present configuration, we find no direct connection between EIT and purely elastic instabilities.
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Computational Physics · Cross-listed from cs.DC
JZ-Tree: GPU friendly neighbour search and friends-of-friends with dual tree walks in JAX plus CUDA
Jens Stücker, Oliver Hahn, Lukas Winkler et al. (+2 more)
Algorithms based on spatial tree traversal are widely regarded as among the most efficient and flexible approaches for many problems in CPU-based high-performance computing (HPC). However, directly transferring these
algorithms to GPU architectures often yields substantially smaller performance gains than expected in light of the high computational throughput of modern GPUs. The branching nature of tree
algorithms leads to thread divergence and irregular
memory access patterns – both of which may severely limit GPU performance. To address these challenges, we propose a Morton (z-order) 'plane-based tree hierarchy' that is specifically designed for GPU architectures. The resulting flattened data layout enables efficient dual-tree traversal with collaborative execution across thread groups, leading to highly coalesced
memory access patterns. Based on this framework we present implementations of two important spatial
algorithms – exact $k$-nearest neighbour search and friends-of-friends (FoF) clustering. For both cases, we observe more than an order-of-magnitude performance improvement over the closest competing GPU libraries for large problem sizes ($N \gtrsim 10^7$), together with strong scaling to distributed multi-GPU systems. We provide an open-source implementation, 'JZ-Tree' (JAX z-order tree), which serves as a foundation for efficient GPU implementations of a broad class of tree-based
algorithms.
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All authors Jens Stücker, Oliver Hahn, Lukas Winkler, Adrian Gutierrez Adame, Thomas Flöss
Physics and Society · Cross-listed from nlin.AO
Symmetry-Breaking and Hysteresis in a Duplex Voter Model
Christian Kluge and Christian Kuehn
We introduce and analyze a voter-type model on a two-layer multiplex network, where the presence of a state on one layer acts as a catalyst or inhibitor to the propagation of that state on the other layer. Despite the model's simplicity, our mathematical analysis reveals a rich phase diagram that includes spontaneous
symmetry-breaking and a cusp bifurcation, which arises when noise is introduced into the model. In particular, this bifurcation mechanism can be viewed as a prototypical unfolding of the change between explosive and non-explosive transitions observed in various other network models. We cross-validate our analytic results by numerical simulations.
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Medical Physics
Development and Performance of an Instrumentation Laboratory for Infrared Medical Imaging
Anna Frixou, Efstathios Stiliaris and Costas N. Papanicolas
We present an experimental setup and methodology designed to facilitate high-precision thermal measurements required for infrared medical
tomography. The approach which is best suited for the study of specialized hardware phantoms comprises a controlled environmental enclosure, infrared detection, internal thermal reference elements, and a comprehensive data acquisition counting chain and protocol. Temporal and spatial corrections applied to sequential thermal images and panoramic projections reduce measurement fluctuations resulting in measurement uncertainty to approximately 25~mK. The capability to resolve weak surface temperature variations, well below 0.1~K, meets the requirement of medical imaging sensitivity. The methodology was validated using wax phantoms with elevated-temperature sources ($\Delta T$ = 1.5 to 10~K). Reconstructed 3D thermal tomographic images of hot spots embedded in hardware phantoms are found to be in quantitative agreement with thermocouple measurements and $\mu CT$ derived source positions. The results demonstrate that the proposed setup and methodology enable high-precision thermal measurements and establish the feasibility of detecting surface temperature variations below 0.1 K, consistent with low-temperature localized internal contrasts ($\Delta T =$ 1-3 K) at subsurface depths of a few centimeters, relevant to biological tissue.
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Instrumentation and Detectors
Noise budget of Cryogenic sub-Hz cROss torsion bar detector with quantum NOn-demolition Speed meter (CHRONOS)
Mario Juvenal S. Onglao III, Hsiang-Yu Huang, Yuki Inoue et al. (+2 more)
CHRONOS is a proposed gravitational-wave detector designed to operate in the sub-Hz frequency range (0.1 to 10 Hz), a largely unexplored band due to strong noise sources that hamper ground-based detectors. It employs cryogenic operation, a cross torsion-bar configuration, a triangular Sagnac interferometer, and a speed meter readout scheme to overcome key noise limitations, targeting a strain sensitivity of $h \sim 10^{-18} Hz^{-1/2}$ around 2 Hz and a
stochastic gravitational wave background of $\Omega_{GW}$ approximately $2 \times 10^{-3}$ at 2 Hz. Using analytical and interferometric simulations with FINESSE3, we evaluate the noise budget of CHRONOS and characterize the relative contributions of
quantum, thermal, and environmental noise sources. Our results demonstrate that CHRONOS achieves competitive sensitivity at low frequencies. The feasibility of using CHRONOS in an earthquake early-warning system by detecting
prompt gravity-gradient signals is also investigated, and is predicted to be faster by approximately 2.92 to 6.90 seconds within 40 km. These findings highlight the scientific potential of CHRONOS, bridging gravitational-wave astronomy and geophysical monitoring, and motivating further development of low-frequency detector technologies.
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All authors Mario Juvenal S. Onglao III, Hsiang-Yu Huang, Yuki Inoue, Vivek Kumar, Daiki Tanabe
Chemical Physics
Dissociative Single and Double Ionization of Pyridine
Sitanath Mondal, Brendan Wouterlood, Gustavo A. Garcia et al. (+3 more)
Dissociative ionization processes of simple heterocyclic molecules like pyridine are relevant for an understanding of radiation damage processes in biological material that occur naturally in complex condensed environments. Pyridine can thereby be considered a simple analogue of nucleobases and related ring structures are included in many important biomolecules. We present here a detailed study of dissociative single-
photon single and double ionization processes using double imaging photoelectron photoion coincidence spectroscopy, supported by
quantum chemical calculations. In the case of single ionization we correlate previously described cationic states to their corresponding ionic dissociation products observed at a
photon energy of 23 eV, providing additional information beyond previously reported ion appearance energies. For the case of double ionization by 36 eV
photons the analysis of electron-ion-ion triple coincidences provides detailed information on the onsets of various dissociative double ionization pathways, often only different by the locations of single hydrogen atoms. The detailed understanding of dissociative single and double ionization of pyridine is a prerequisite for future studies addressing radiation damage processes of such molecules in complex environments.
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All authors Sitanath Mondal, Brendan Wouterlood, Gustavo A. Garcia, Laurent Nahon, Frank Stienkemeier, Sebastian Hartweg
Accelerator Physics
Introduction to Mechanics and Structures
Martina Scapin
This work provides a comprehensive overview of the fundamental concepts in continuum mechanics, focusing on the behaviour of materials under mechanical loads. It discusses the distinction between elastic and plastic, highlighting their atomic origins and macroscopic implications. Elastic behaviour is examined via Hooke's law and constitutive
matrices, while plasticity is treated through yield surfaces, flow rules, and hardening laws, including isotropic and kinematic hardening. In addition, the theoretical foundations and design principles of pressure vessels and thin axisymmetric shells, focusing on their mechanical behaviour under internal or external pressure, is discussed. The analysis is based on shell theory, assuming thin walls and axisymmetric geometry, which simplifies the stress distribution into membrane stresses. The work also addresses buckling phenomena under external pressure, secondary stresses at
geometric discontinuities, and design provisions from the EN 13445 standard.
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Chemical Physics
Valence and Rydberg excited state bond dissociation curves of CO2 from orbital-optimized density functional calculations
Darío Barreiro-Lage, Gianluca Levi, Hannes Jonssón et al. (+1 more)
Calculations of the lowest valence {\pi}* as well as the 3s and higher energy 3p{\sigma} Rydberg excited states of the CO2 molecule are carried out using density functionals with variational optimization of the orbitals, an approach involving relatively little computational effort. Five functionals with varying degree of exchange are used in combination with real or complex-valued orbitals that are optimized by finding saddle points on the electronic energy surface corresponding to the excited states. When the PBE functional is used in combination with complex orbitals, the calculated excitation energy is found to be within 0.3 eV of multireference configuration interaction reference values, and the results are further improved with hybrid functionals. In contrast, linear-response time-dependent density functional theory calculations give errors up to 1.9 eV for the most diffuse 3p{\sigma} excitation and exhibit stronger dependence on both the excitation character and the functional used. Calculated C-O dissociation curves using the PBE functional and the orbital-optimized approach compare remarkably well with the reported multireference configuration interaction and equation-of-motion coupled-cluster singles and doubles calculations. Thanks to the low computational cost, these results demonstrate that orbital-optimized density functional calculations can be a promising route for modelling photorelaxation in condensed-phase CO2, for example in the context of interstellar
cosmic-ray radiation driven process involving high-energy Rydberg states.
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All authors Darío Barreiro-Lage, Gianluca Levi, Hannes Jonssón, Thanja Lamberts
Optics · Cross-listed from cond-mat.mes-hall
Controlled dewetting and phase transition hysteresis of VO2 nanostructures
Peter Kepič, Petra Kalousková, Tomáš Šikola et al. (+1 more)
As artificial intelligence continues to grow, so does the need for more efficient ways to process data. Besides moving from electronic to photonic
circuits, a promising approach is to integrate phase-change materials. Vanadium dioxide (VO$_2$) exhibits an ultrafast, near-room-temperature phase transition, characterized by hysteresis and large optical modulation – making it a promising candidate for short-term
memories and for mimicking neural behavior in
brain-like computing systems. While the hysteresis behavior of VO$_2$ has been well studied in thin films and nanostructures, practical control and device integration have been limited only to thin films. Here, we demonstrate control over the phase transitions of VO$_2$ nanocylinders via lithographic patterning, controlled crystallization, and controlled dewetting. Because nanostructures are easier to address and consume less power than films, the ability to fabricate them with tailored geometry and hysteresis properties directly on integrated platforms is a key step toward scalable, energy-efficient
memory and neuromorphic photonic devices.
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All authors Peter Kepič, Petra Kalousková, Tomáš Šikola, Filip Ligmajer
Classical Physics · Cross-listed from hep-ph
Scalar axion field of toroidal electromagnetic pulses
Wangke Yu, Nikitas Papasimakis, Nikolay I. Zheludev et al. (+1 more)
Axion electrodynamics extends Maxwell's theory by postulating a hypothetical pseudoscalar
axion field sourced by a scalar product of electric and
magnetic fields. In this work, we demonstrate that a superposition of toroidal electromagnetic pulses propagating in free space naturally exhibits localized regions, where $\bm{E}\cdot\bm{B}\ne0$. As a consequence of
axion electrodynamics, these structured light pulses generate a space-time localized pseudoscalar field co-propagating with the pulses. This result should not be interpreted as a mechanism for generating
axion particles by light, but rather as a consequence of adopting the
axion electrodynamics extension to Maxwell's equations.
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All authors Wangke Yu, Nikitas Papasimakis, Nikolay I. Zheludev, Yijie Shen
Atomic Physics · Cross-listed from quant-ph
Nonlinear atomic tunnelling boosted by bright squeezed vacuum
Zhejun Jiang, Shengzhe Pan, Jianqi Chen et al. (+12 more)
Nonlinear optical processes, mediated by multiphoton interactions rather than single-
photon response, are routinely exploited to enable a range of light-based functionalities in devices and applications. Nonlinear effects are enhanced through higher intensity fields, which is a limiting strategy owing to potential radiation damage. An alternative strategy relies on the fluctuation redistribution typical of
quantum light, but experimental demonstrations at the most fundamental level have been limited. Here we report experimental nonlinear tunnelling ionization of isolated atoms, a pivotal nonlinear process that drives high-harmonic generation and forms the basis of attosecond science, boosted by
quantum light – bright squeezed
vacuum (BSV). A BSV light with an average pulse energy of 300 nJ achieves an effective intensity equivalent to that of a coherent light with 7.1 {\textmu}J, demonstrating a more than 20-fold
quantum boost in nonlinear effect from BSV light. This boost is revealed by matching the peaks of the photoelectron momentum spectra produced by the BSV and coherent light using angular streaking. Furthermore, we demonstrate control of the effective intensity of the BSV by tuning the correlation function at fixed average pulse energy, establishing a robust method to tailor nonlinear processes via
quantum statistics rather than classical intensity scaling. These findings may facilitate the development of
quantum-controlled strong-field dynamics using tailored
quantum light sources.
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All authors Zhejun Jiang, Shengzhe Pan, Jianqi Chen, Mingyu Zhu, Chenhao Zhao, Yiwen Wang, Ru Zhang, Jianshi Lu, Lulu Han, Suwen Xiong, Dian Wu, Wenxue Li, Shicheng Jiang, Hongcheng Ni, Jian Wu
Chemical Physics · Cross-listed from math.DS
Effective Dynamics and Transition Pathways from Koopman-Inspired Neural Learning of Collective Variables
Alexander Sikorski, Luca Donati, Marcus Weber et al. (+1 more)
The ISOKANN (Invariant Subspaces of Koopman Operators Learned by Artificial Neural Networks) framework provides a data-driven route to extract collective variables (CVs) and effective dynamics from complex molecular systems. In this work, we integrate the theoretical foundation of Koopman operators with Krylov-like subspace
algorithms, and reduced dynamical modeling to build a coherent picture of how to describe metastable transitions in high-dimensional systems based on CVs. Starting from the identification of CVs based on dominant invariant subspaces, we derive the corresponding effective dynamics on the latent space and connect these to transition rates and times, committor functions, and transition pathways. The combination of Koopman-based learning and reduced-dimensional effective dynamics yields a principled framework for computing transition rates and pathways from simulation data. Numerical experiments on one-, two-, and three-dimensional
benchmark potentials illustrate the ability of ISOKANN to reconstruct the coarse-grained kinetics and reproduce transition times across enthalpic and entropic barriers.
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All authors Alexander Sikorski, Luca Donati, Marcus Weber, Christof Schütte
Accelerator Physics
Electron Acceleration in a Flying-Focus Laser Wakefield Accelerator
Aaron Liberman, Anton Golovanov, Slava Smartsev et al. (+3 more)
Structured light pulses hold significant promise for their ability to overcome dephasing in
laser-wakefield accelerators, that should facilitate applications in high-energy physics and XFEL. Numerical studies have shown that sculpting a pulse into a flying focus and using it to drive a wakefield can achieve dephasing-free acceleration of electrons, with gain in excess of 100\,GeV within reachable with existing
laser facilities. This work reports on novel experiments using a flying-focus generated
laser-wakefield accelerator to accelerate electrons to relativistic energies. The flying-focus pulse is achieved by sculpting the
laser-pulse before focusing using spatio-temporal couplings and generating a quasi-Bessel beam with an axiparabola. This combination allows for the tuning of the propagation velocity of the wakefield, which, we demonstrate, has an impact on the maximum achievable electron energy. Optical and particle-in-
cell simulations are used to support the data and to provide direct evidence of the partial mitigation of dephasing through this flying-focus scheme. These results are further elucidated in our companion letter [1].
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All authors Aaron Liberman, Anton Golovanov, Slava Smartsev, Anda-Maria Talposi, Sheroy Tata, Victor Malka
Chemical Physics
ORION: Unifying Top-Down and Bottom-Up Chemical Space Sampling for a Universal Organic Force Field
Zherui Chen, Jiayu Zhang, Yuxuan Tian et al. (+7 more)
Empirical force fields remain the primary tool for large-scale molecular simulation, yet their limited flexibility and transferability often hinder predictive modeling in chemically complex condensed-phase systems. Here we present ORION, a universal machine-learning force field for C, H, O, N, S, and P systems developed within the Neuroevolution Potential (NEP) framework. To enhance transferability across diverse chemical environments, ORION was trained on a chemically rich
dataset constructed through an integrated top-down and bottom-up strategy, enabling accurate descriptions of complex organic configurations, reactive intermediates, and weak intermolecular interactions. ORION achieves near-density-functional-theory accuracy while retaining the efficiency required for large-scale molecular dynamics simulations. On the test set, it predicts atomic forces with substantially higher accuracy than ReaxFF while running 215.5 times faster under identical hardware conditions, making simulations on the hundreds-of-nanoseconds timescale readily accessible. The model provides a balanced description of bond breaking and formation, aromatic growth, hydrogen bonding, van der Waals interactions, and {\pi}-stacking, demonstrating strong transferability across both reactive and nonreactive systems. These results establish ORION as a practical and general force field for predictive simulations in chemistry and materials science, and provide an effective route toward universal machine-learning force fields with both high accuracy and broad applicability.
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All authors Zherui Chen, Jiayu Zhang, Yuxuan Tian, Zhoulin Liu, Sining Dai, Yanghui Li, Cong Chen, Dingyuan Tang, Yajun Deng, Qingxia Liu
Physics and Society
Network Reconstruction via Jeffreys Prior under Missing Sufficient Statistics
Minh Duc Duong and Diego Garlaschelli
Methods for the reconstruction of economic networks from aggregate information are important for modeling, analysis and policymaking. The traditional Fitness Model (FM) achieves good performance by using node-specific variables that are easily accessible (e.g., GDP for countries or total assets for banks or firms) and the overall link density as the only sufficient statistics. However, it often ignores additional contextual or mesoscopic features which may be more difficult to observe. Here we extend the framework by incorporating block structure as in the Fitness-Corrected Block Model (FCBM), which allows for heterogeneous densities within and across blocks, but in the deliberately more challenging setting where such block-specific densities are not empirically available. Our method uses a Jeffreys prior to provide an unbiased distribution of all compatible solutions and associated
entropies, that are otherwise left unidentified, and selects a single reconstruction at the median of this
entropy distribution to compensate for the missing sufficient statistics. We evaluate the procedure on nine international-trade networks using GDP as node fitness and World Bank regions as an externally specified partition. The method systematically outperforms the baseline Block-Agnostic FM (which uses the same observed network input statistic) and sometimes even the FCBM (which always uses more information). Controlled synthetic networks confirm that the median is the best of four
entropy-based representatives for a range of densities and regional effects similar to the empirical ones, while other representatives can perform better when parameters are pushed far from their realistic range. Overall, our method compensates for missing sufficient statistics via a median-
entropy estimate that is empirically very robust within a realistic range of parameters.
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Fluid Dynamics
The spatio-temporal statistical structure of the turbulent dissipation field and its stochastic representation as a Gaussian Multiplicative Chaos
Wandrille Ruffenach and Laurent Chevillard
The present article concerns the
stochastic modeling of the turbulent dissipation field and in particular its temporal
evolution. To do so, we will be calling for a random distribution, ubiquitous in several aspects of physics and probability theory, known as the Gaussian Multiplicative Chaos (GMC), that takes its roots in the phenomenology of fluid
turbulence. Firstly introduced by Mandelbrot, shortly after Yaglom's discrete multiplicative cascade models, and rigorously studied by Kahane, the GMC appears as an appropriate statistically homogeneous model of the turbulent dissipation field. In this article, we will be recalling several ingredients of the associated turbulent phenomenology and its
stochastic representation as a GMC, and propose a generalization to a spatio-temporal framework. All along the presentation of known properties in space, and in order to support new propositions concerning the temporal
evolution, we will be calling for a comparison against Direct Numerical Simulations of the Navier-Stokes equations extracted from a publicly accessible database.
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Chemical Physics
Does the total energy difference method for modelling core level photoemission fail for bigger molecules?
Marta Berholts, Tanel Käämbre, Arvo Tõnisoo et al. (+3 more)
The $\Delta$-Self-Consistent-Field ($\Delta$SCF) method permits calculations of core electron binding energies in materials and molecules at a modest computational cost. However, it has been reported that whilst this method works well for small molecules, its accuracy drops off dramatically when larger systems are considered. Particularly large errors have been reported for the anthrone molecule, which consists of 25 atoms. In this work, the gas-phase photoelectron spectrum of anthrone is revisited both computationally and experimentally. The measured C 1s binding energies in anthrone differ markedly from previously published values, and the new experimental results are in good agreement with $\Delta$SCF calculations based on the SCAN functional. In addition, the performance of the $\Delta$SCF method is evaluated for a
dataset of 44 core electron binding energies from medium sized molecules containing between 10 and 40 atoms. The mean absolute error for this
dataset - 0.19 eV - is comparable to the results of previous computational
benchmarks. Overall, these results and general theoretical considerations indicate that the $\Delta$SCF method is suitable for modelling localized excitations in both small and large molecules, and applications to other extended systems are also promising.
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All authors Marta Berholts, Tanel Käämbre, Arvo Tõnisoo, Rainer Pärna, Vambola Kisand, Juhan Matthias Kahk
Chemical Physics
Assessing the Performance of CC2 for Excited-State Dynamics: A Benchmark Study with Pyrazine
Rui-Hao Bi, Chongxiao Zhao, Ruixin Sun et al. (+1 more)
During the ultrafast electronic relaxation of pyrazine, the bright state undergoes rapid decay accompanied by coupled electronic and
nuclear motion. We investigate the vibrational modes associated with this process using trajectory surface hopping simulations. To enable accurate ab initio excited-state dynamics, we apply CC2 analytical gradients and nonadiabatic coupling vectors within the Q-Chem package. Using both a reduced vibronic coupling model and full-dimensional simulations, we demonstrate that CC2 predicts that the dark $A_\text{1u}$ state actively participates in the initial relaxation and the subsequent dynamics. The full-dimensional simulations yield a $B_\text{2u}$ decay time of 25–26 fs, in good agreement with the experimental measurement of $22\pm3$ fs. Furthermore, we identify the $Q_\text{8a}$ and $Q_\text{9a}$ modes as dominant tuning coordinates whose motions are phase-locked to the population oscillations between the $A_{1u}$ and $B_{3u}$ states.
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All authors Rui-Hao Bi, Chongxiao Zhao, Ruixin Sun, Wenjie Dou
Plasma Physics
Modeling complex plasma instabilities in space plasmas - Three-component electron formalism of heat-flux instabilities
Dustin L. Schröder, Marian Lazar, Horst Fichtner et al. (+2 more)
Despite the fact that electrons observed in situ in space
plasmas have three major components-the quasi-thermal core, suprathermal
halo, and strahl-the analysis of instabilities triggered by kinetic, velocity-space anisotropies (such as relative drifts and temperature anisotropy) generally considers only two. We demonstrate that realistic modeling with all three components is achievable in the present analysis focusing on heat-flux instabilities. In the absence of particle collisions, these instabilities regulate the heat flux carried mainly by suprathermal electrons. The velocity distributions were modeled according to in situ observations, with a Maxwellian core and Kappa-distributed
halo and strahl. We exploited advanced numerical codes capable of solving the linear dispersion and stability properties of
plasma systems with Maxwellian and Kappa distributions. The unstable solutions differ significantly from those obtained with simplified two-component models (such as core-strahl or core-beam). The growth rates predict the excitation and interplay of two unstable modes, whistler and/or firehose heat-flux instabilities. The numerical solver 'ALPS' was successfully applied to systems with regularized Kappa distributions, for which analytical derivation of dispersion relations is not straightforward. The two instabilities are triggered by the relative drifts, core-strahl and
halo-strahl, and may have new consequences for heat-flux regulation. Particularly important are cases when the core-strahl instability is in competition with the instability driven by the
halo-strahl drift, as well as when the two instabilities have the same nature and accumulate. Future studies are motivated to confirm these predictions in quasilinear theories and numerical simulations.
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All authors Dustin L. Schröder, Marian Lazar, Horst Fichtner, Rodrigo A. López, Stefaan Poedts
Physics and Society
Publish and Perish: How AI-Accelerated Writing Without Proportional Verification Investment Degrades Scientific Knowledge
Seok Joon Kwon
Artificial intelligence tools are accelerating manuscript production far faster than peer review capacity can expand. Applying the theory of constraints from manufacturing science, we formalize this asymmetry through a minimal two-variable ordinary differential equation model coupling review queue
evolution and verification quality degradation via an endogenous, queue-pressure-driven review AI adoption mechanism. The causal chain is: writing AI adoption increases submissions, growing the review queue, which drives reviewer AI adoption under pressure, degrading verification quality and reducing net knowledge output. Under empirically informed parameters (writing acceleration {\gamma} = 2.0, review acceleration {\delta} = 0.5), the model predicts a deceptive honeymoon where knowledge output peaks at 1.10K0 (circa 2026), followed by paradox onset at t = 6 years (2028) and long-term degradation to 0.68K0 (32% loss), approaching a steady state of 0.60K0 (40% loss). The critical condition for net benefit is {\delta} > {\gamma}; the current operating point lies deep in the paradox regime. Empirical validation against NeurIPS, ICLR, arXiv, and bioRxiv submission data shows qualitative consistency with observed post-ChatGPT acceleration patterns. Policy analysis reveals that only combined interventions such as review infrastructure investment paired with institutional quality standards can restore positive knowledge production.
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Physics and Society · Cross-listed from eess.SY
Network Reconstruction in Consensus Algorithms with Hidden Agents
Melvyn Tyloo
Reconstructing the parameters that encode the influence between model variables based on time-series measurements represents an outstanding question in the theory of complex network-coupled systems. Here, we propose a solution to this problem for a class of noisy leader-follower consensus
algorithms, where one has access to measurements only from the followers but not from the leaders. Leveraging the directed
Laplacian coupling of such systems, we present an autoregressive expansion of the observed dynamics which can be truncated at different orders, depending on the
memory of the leaders. When their
memory is short, this allows one to correctly reconstruct the full dynamical
matrix with hidden leader
agents, provided some additional assumption on the system to lift the degeneracy in the reconstruction. We illustrate and check the theory using numerical simulations for the cases of both a single and multiple hidden leaders.
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Medical Physics
Untargeted analysis of volatile markers of post-exercise fat oxidation in exhaled breath
André Homeyer, Júlia Blanka Sziládi, Jan-Philipp Redlich et al. (+2 more)
Breath acetone represents a promising non-invasive biomarker for monitoring fat oxidation during exercise. However, its utility is limited by confounding factors, as well as by the fact that significant changes in concentration occur only hours post-exercise, which makes real-time assessment difficult. We performed an untargeted screening for volatile organic compounds (VOCs) that could serve as markers of fat oxidation beyond acetone, and investigated whether breath measurements taken during exercise could predict post-exercise changes in fat oxidation. Nineteen participants completed two 25-min cycling sessions separated by a brief 5-min rest period. VOC emissions were analysed using
proton-transfer-reaction time-of-flight mass spectrometry (PTR-TOF-MS) during exercise and after a 90-min recovery period. Blood $\beta$-hydroxybutyrate (BOHB) concentrations served as the reference marker for fat oxidation. Among 773 relevant analytical features detected in the PTR-TOF-MS measurements, only four signals exhibited strong correlations with BOHB ($\rho$ $\geq$ 0.82, p = 0.0002)-all attributable to acetone or its isotopologues or fragments. End-of-exercise measurements of these signals enabled accurate prediction of participants with substantial post-exercise BOHB changes (F1 score $\geq$ 0.83, accuracy = 0.89). Our study did not reveal any novel breath-based biomarkers of fat oxidation, but it confirmed acetone as the key marker. Moreover, our findings suggest that breath acetone measurements during exercise may already enable basic predictions of post-exercise fat oxidation.
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All authors André Homeyer, Júlia Blanka Sziládi, Jan-Philipp Redlich, Jonathan Beauchamp, Y Lan Pham
Accelerator Physics
Terahertz and Optical Acceleration Techniques
Franz X. Kärtner
The use of terahertz (THz) and optical radiation for electron acceleration and manipulation of electron bunches has progressed over the last decade to a level where practical devices for THz guns, THz and optical acceleration modules and a wide range of beam manipulations have become possible. Here, we discuss recent progress in optical driven Terahertz generation and its use in charged particle acceleration and beam manipulation devices. The advantages of using shorter wavelength radiation for acceleration are in overcoming breakdown phenomena, therefore enabling higher acceleration gradients than in conventional RF-accelerators albeit with lower bunch charge. The lower pulse energies needed to power the smaller cross section of the accelerating structures is also advantageous. In addition, the shorter wavelengths enable tighter timing control of the generated electron bunches but in return also need more precise timing when multiple stage interactions are required. Early results on THz guns, beam manipulation devices and accelerator structures are discussed as well as basic working principles of dielectric
laser accelerators.
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Fluid Dynamics · Cross-listed from math.AP
Asymptotic models for viscoelastic one-dimensional blood flow
Diego Alonso-Orán, Rafael Granero-Belinchón and Carlos Yanes Pérez
We derive a unidirectional asymptotic model for one-dimensional blood flow in viscoelastic arteries. We prove local well-posedness of strong solutions in Sobolev spaces for general parameters and mean-zero periodic data. In the purely elastic BBM regime we further establish global existence and exponential decay for sufficiently small initial data. We also present a numerical study of the reduced model, including comparisons across different viscoelastic and amplitude regimes, and discuss the observed dynamics in connection with the continuation criterion.
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Chemical Physics
Two-colour coherent control of nuclear and electron dynamics in photoionization of molecular hydrogen with FEL pulses
Fabian Holzmeier, Alberto Gonzalez-Castrillo, Thomas M. Baumann et al. (+12 more)
The extension of coherent $\omega$-$2\omega$ control schemes, recently implemented in free-electron
lasers (FELs), to molecular systems offers new opportunities to control chemical dynamics on the electronic timescale, potentially allowing for the steering of reactions along previously inaccessible pathways. We have implemented such a scheme at the seeded
FERMI FEL to retrieve the relative phases between one-
photon (frequency $2\omega$) and two-
photon (frequency $\omega$) ionization paths in the hydrogen molecule as a function of photoelectron energy and emission angle. The narrow bandwidth of the XUV pulses enables selective excitation of vibrational levels of neutral intermediate H$_2$ states in the two-
photon ionization path. Here we focus on $\omega$–$2\omega$ ionization of H$_2(X\,^{1}\Sigma_g^{+},\,v=0)$ into the H$_2^{+}(X\,^{2}\Sigma_g^{+},\,v_f)$ ground state involving the H$_2(B\,^{1}\Sigma_u^{+},\,v'=6)$ intermediate state. The relative phases of the $\omega$ and $2\omega$ interfering photoionization amplitudes exhibit a strong dependence on photoelectron energy, i.e.\ on the final vibrational state $v_f$ in the H$_2^{+}$ cation. With the help of accurate theoretical calculations, the observed phase jumps are assigned to the coupled electronic and
nuclear dynamics at play in the two-
photon process, significantly influenced by H$_2(^{1}\Sigma_g^{+}$ and $^{1}\Pi_g)$ autoionizing states and the mapping of the H$_2(B\,^{1}\Sigma_u^{+},\,v'=6)$ intermediate-state
nuclear wavefunction into the final vibrational states of H$_2^{+}(X\,^{2}\Sigma_g^{+})$. The present work establishes the fundamental concepts required to access coupled electron–
nuclear dynamics in molecules using $\omega$–$2\omega$ coherent control schemes currently available at free-electron
laser facilities.
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All authors Fabian Holzmeier, Alberto Gonzalez-Castrillo, Thomas M. Baumann, Roger Y. Bello, Carlo Callegari, Michele Di Fraia, Matteo Lucchini, Michael Meyer, Oksana Plekan, Kevin C. Prince, Eleonore Roussel, Rene Wagner, Fernando Martin, Alicia Palacios, Danielle Dowek
Fluid Dynamics
Multiscale Physics-Informed Neural Network for Complex Fluid Flows with Long-Range Dependencies
Prashant Kumar and Rajesh Ranjan
Fluid flows are governed by the nonlinear Navier-Stokes equations, which can manifest multiscale dynamics even from predictable initial conditions. Predicting such phenomena remains a formidable challenge in scientific machine learning, particularly regarding convergence speed, data requirements, and solution accuracy. In complex fluid flows, these challenges are exacerbated by long-range spatial dependencies arising from distant boundary conditions, which typically necessitate extensive supervision data to achieve acceptable results. We propose the Domain-Decomposed and Shifted Physics-Informed Neural Network (DDS-PINN), a framework designed to resolve such multiscale interactions with minimal supervision. By utilizing localized networks with a unified global loss, DDS-PINN captures global dependencies while maintaining local precision. The robustness of the approach is demonstrated across a suite of
benchmarks, including a multiscale linear differential equation, the nonlinear Burgers' equation, and data-free Navier-Stokes simulations of flat-plate boundary layers. Finally, DDS-PINN is applied to the computationally challenging backward-facing step (BFS) problem; for laminar regimes (Re = 100), the model yields results comparable to computational fluid dynamics (CFD) without the need for any data, accurately predicting boundary layer thickness, separation, and reattachment lengths. For turbulent BFS flow at Re = 10,000, the framework achieves convergence to O(10^-4) using only 500 random supervision points (< 0.3 % of the total domain), outperforming established methods like Residual-based
Attention-PINN in accuracy. This approach demonstrates strong potential for the super-resolution of complex turbulent flows from sparse experimental measurements.
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Applied Physics
Determination of the mass transport parameters in thin membranes by phase-sensitive photoacoustics in the optically transparent and mixed regimes
Pawel Rochowski
The research complements and extends the scope of the work reported in the article "LED-based multibeam photoacoustics combined with electrical
circuit-based modeling for the analysis of multispecies mass transport through thin membranes" (arXiv:2602.20902). In particular, this work investigates the impact of the sample's absorption properties on the ability to quantify slow mass transport processes in thin membranes under optically transparent and semi-opaque conditions. The theoretical framework is based on the Green's function approach as formalized by Mandelis. Owing to the separation of photoacoustic and mass transport timescales, the heat distributions are assumed to follow the temporal mass concentration profiles predicted by a Fickian
diffusion process. The approach is further examined and validated using experimental data on pigment transport into a thin porous membrane. Detailed experimental results are provided in the referenced paper.
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