Chemical Physics · Cross-listed from cond-mat.stat-mech
Exact and variational identities for free energy differences in strongly coupled open systems
Mohammad Rahbar and Christopher J. Stein
We derive exact identities for open systems connecting two
equilibrium endpoints without imposing microscopic reversibility, detailed balance (DB), fluctuation-dissipation structure, or local detailed balance (LDB) on the driven dynamics. The identities express the
Hamiltonian of mean force (HMF) free energy differences through exponential moments and an explicit chi-squared overlap between the endpoint marginals. In the frozen-coupling regime, the HMF shift reduces to a bare-system increment and admits a trajectory-level heat-work-reference decomposition. The exact relations then reduce the problem to a scalar-action law. A maximum-
entropy construction gives a Bessel-form scalar-action law, independent of the microscopic system, environment, and number of degrees of freedom at the level of the variational reconstruction. This law provides three outputs from the same sampled configurations: the HMF free energy difference, the endpoint-overlap burden, and a Hessian uncertainty estimate. Since many systems in biology, chemistry, physics and engineering violate the underlying assumptions of the standard Jarzynski identity, we validate the framework on a reduced-dimensional model with a non-Liouvillian, phase-space-compressing ramp followed by underdamped Langevin relaxation. The standard Jarzynski work
estimator fails for this ramp because phase-space preservation is broken and no compensating Jacobian correction is included, whereas the present endpoint identities recover the exact HMF free energy difference, and the variational construction reproduces it within its local uncertainty.
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Optics
Dynamic full-field swept-source optical coherence microscope for cellular-resolution, long-depth, and intratissue-activity imaging
Nobuhisa Tateno, Yue Zhu, Suzuyo Komeda et al. (+8 more)
Optical coherence
tomography (OCT) microscope (OCM) uses a high-numerical-aperture objective to achieve cellular-level lateral resolution. However, its practical imaging depth range is limited by the depth of focus (DOF). Although computational refocusing can potentially provide sharp images outside the DOF, signal reduction by the confocal effect still limits the imaging depth in practice in point-scanning OCT. In addition, standard OCT cannot visualize intra-tissue activities. To overcome these limitations, we demonstrated a spatially coherent full-field OCM (SC-FFOCM) with computational refocusing. In addition, a repetitive acquisition protocol was designed to visualize intra-tissue activities (i.e., dynamic OCT imaging). The in-focus lateral resolution is 1.4 um, and the axial resolution is 6.5 um (in air) at full-width at half-maximum intensity. Three-dimensional structure and the dynamic OCT imaging using SC-FFOCM with computational refocusing was applied to human breast adenocarcinoma spheroids (MCF-7
cell line). Volumetric dynamic imaging with cellular-level lateral resolution was demonstrated over the full depth of the spheroid.
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All authors Nobuhisa Tateno, Yue Zhu, Suzuyo Komeda, Mahiro Ishikawa, Xibo Wang, Ibrahim Abd El-Sadek, Rion Morishita, Atsuko Furukawa, Satoshi Matsusaka, Shuichi Makita, Yoshiaki Yasuno
Biological Physics · Cross-listed from cs.LG
Fractional neural attention for efficient multiscale sequence processing
Cheng Kevin Qu, Andrew Ly and Pulin Gong
Attention mechanisms underpin the computational power of
Transformer models, which have achieved remarkable success across diverse domains. Yet understanding and extending the principles underlying self-
attention remains a key challenge for advancing artificial intelligence. Drawing inspiration from the multiscale dynamics of biological
attention and from dynamical systems theory, we introduce Fractional Neural
Attention (FNA), a principled, neuroscience-inspired framework for multiscale information processing. FNA models
token interactions through Lévy
diffusion governed by the fractional
Laplacian, intrinsically realizing simultaneous short- and long-range dependencies across multiple scales. This mechanism yields greater expressivity and faster information mixing, advancing the foundational capacity of
Transformers. Theoretically, we show that FNA's dynamics are governed by the fractional
diffusion equation, and that the resulting
attention networks exhibit larger spectral gaps and shorter path lengths – mechanistic signatures of enhanced computational efficiency. Empirically, FNA achieves competitive text-classification performance even with a single layer and a single head; it also improves performance in image processing and neural machine translation. Finally, the
diffusion map
algorithm from
geometric harmonics enables dimensionality reduction of FNA weights while preserving the intrinsic structure of
embeddings and hidden states. Together, these results establish FNA as a principled mechanism connecting self-
attention,
stochastic dynamics, and geometry, providing an interpretable, biologically grounded foundation for powerful, neuroscience-inspired AI.
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Physics and Society
Population-mobility coevolution drives spatial heterogeneity of cities
Hao Huang, Yuming Lin and Jiazhen Liu
The spatial heterogeneity of cities – the uneven distribution of population and activities – is fundamental to urban dynamics and related to critical issues such as infrastructure overload, housing affordability, and social inequality. Despite sharing similar scaling laws of population and mobility, cities exhibit vastly different spatial patterns. This paradox call for a mechanistic explanation for the emergence of spatial heterogeneity, while existing qualitative or descriptive studies fail to capture the underlying mechanisms. Here, we propose a coupled dynamical model that describe the intra-city population-mobility coevolution, explaining spatial heterogeneity as an emergent outcome of mutual feedback between the fast-changing mobility and the slow-adapting population. Our model is validated on over 388 million records from eight diverse global cities, successfully reproduces both the statistical laws and realistic spatial patterns. We find out realistic heterogeneity emerges as a distinct stable state, intermediate between disordered homogeneity and unsustainable super-hub dominance. Moreover, we theoretically and empirically show that populated areas are predominantly shaped by coevolution strength, while the increasing distance decay leads cities through a three-phase transition of homogeneity-heterogeneity-homogeneity. Besides, functional attractiveness between areas consistently enhances the ordered heterogeneous structure. Simulations of real-world planning scenarios – including crisis-induced lockdown, planned zone expansions, and dispersal from congested centers – indicate that integrated population-mobility policies are more cost-effective than single interventions. Our model can provides mechanistic, high-resolution insights to rigorously inform policy design.
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Physics and Society
Reputation assimilation mechanism for sustaining cooperation
Siyu He, Qin Li, Minyu Feng et al. (+1 more)
Keeping a high reputation, by contributing to common efforts, plays a key role in explaining the
evolution of collective cooperation among unrelated
agents in a complex society. Nevertheless, it is not necessarily an individual feature, but may also reflect the general state of a local community. Consequently, a person with a high reputation becomes attractive not just because we can expect cooperative acts with higher probability, but also because such a person is involved in a more efficient group venture. These observations highlight the cumulative and socially transmissible nature of reputation. Interestingly, these aspects were completely ignored by previous works. To reveal the possible consequences, we introduce a spatial public goods game in which we use an assimilated reputation simultaneously characterizing the individual and its neighbors' reputation. Furthermore, a reputation-dependent synergy factor is used to capture the high (or low) quality of a specific group. Through extensive numerical simulations, we investigate how cooperation and extended reputation co-evolve, thereby revealing the dynamic influence of the assimilated reputation mechanism on the emergence and persistence of cooperation. By fostering social learning from high-reputation individuals and granting payoff advantages to high-reputation groups via an adaptive multiplier, the assimilated reputation mechanism promotes cooperation, ultimately to the systemic level.
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All authors Siyu He, Qin Li, Minyu Feng, Attila Szolnoki
Biological Physics
Theoretical Analysis of Resource-Induced Phase Transitions in Estimation Strategies
Takehiro Tottori and Tetsuya J. Kobayashi
Organisms adapt to volatile environments by integrating sensory information with internal
memory, yet their information processing is constrained by resource limitations. Such limitations can fundamentally alter optimal estimation strategies in biological systems. For example, recent experiments suggest that organisms exhibit nonmonotonic phase transitions between memoryless and
memory-based estimation strategies depending on sensory reliability. However, an analytical understanding of these resource-induced phase transitions is still missing. This Letter presents an analytical characterization of resource-induced phase transitions in optimal estimation strategies. Our result identifies the conditions under which resource limitations alter estimation strategies and analytically reveals the mechanism underlying the emergence of discontinuous, nonmonotonic, and scaling behaviors. These results provide a theoretical foundation for understanding how limited resources shape information processing in biological systems.
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Applied Physics
Diamond-based sensing of stray fields from the bulk of thin-film magnets via nano-indentation
Ming-Zhong Ai, Kang-Yuan Liu, Biao Zhang et al. (+8 more)
Measurement of the magnetization in the bulk of thin-film or two-dimensional materials is important for understanding their intrinsic properties without the complications from edges or domain walls. However, the stray fields from the bulk vanish or are very weak, which limits the application of direct measurement methods. Here, we develop a non-destructive approach to directly measuring the stray fields from the bulk of thin-film magnets at arbitrarily designatable locations, with nanoscale spatial resolution. We employ nano-indentation to induce the leakage of stray fields from the materials and use nano-diamond magnetometers to measure them. We apply the method to iron thin films and determine the intrinsic magnetization in the bulk of the materials. This work provides direct access to the intrinsic
magnetic properties of thin-film and low-dimensional materials, as well as a method to study the mechanical effects on magnetization in nanomaterials.
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All authors Ming-Zhong Ai, Kang-Yuan Liu, Biao Zhang, Weng-Hang Leong, Yao Gao, Yue Cui, Guoli Zhu, Licong Peng, Yanglong Hou, Quan Li, Ren-Bao Liu
Optics
M3Scope a 3D multimode multiplane microscope for imaging nanoscale dynamics in soft matter
Steven Huysecom, Francisco Bevilacqua, Roger Bresoli Obach et al. (+6 more)
Fast, volumetric imaging that integrates multiple imaging modalities is essential for probing dynamic, heterogeneous soft and biological matter. Here, we present the M3Scope, a simple yet versatile multiplane microscope that extends widefield detection with a modular multimode cube to enable dual color fluorescence, polarization-resolved, and correlative brightfield fluorescence imaging while (i) preserving simultaneous 3D acquisition at high frame rates (100 fps) and (ii) requiring minimal realignment. We demonstrate its potential by investigating
polymer dynamics across multiple spatial and temporal scales. In an acrylamide type polymerizing network, dual color tracking of 100 nm and 300 nm fluorescent probes revealed size dependent viscosities diverging from 15 mPa.s to 40 mPa.s after gelation. Polarization resolved rotational tracking of gold bipyramids yielded viscosities within 10 percent of theoretical values in 80 to 95 percent glycerol and remained accurate in the high-viscosity regime (bigger than 400 mPa.s) where translational motion is undetectable. Fluorescence brightfield imaging correlated structural changes during poly(isopropyl acrylamide) (pNIPAM) phase separation as well as variations in tracer diffusivity, linking morphology and dynamics in 3D. Taken together, these results show that the M3Scope delivers high speed volumetric imaging with flexible modality switching, providing a powerful platform for studying dynamic, heterogeneous systems across disciplines, from
polymer physics to
cell mechanobiology.
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All authors Steven Huysecom, Francisco Bevilacqua, Roger Bresoli Obach, Sudipta Seth, Luis M. Liz-Marzan, Dagmar R. D hooge, Johan Hofkens, Susana Rocha, Boris Louis
Optics
Rotational Jamming of Plasmonic Optical Matter Driven by Chiral Light
Ashutosh Shukla, Sneha Boby, Rahul Chand et al. (+1 more)
Plasmonic Optical matter (OM), composed of optically bound metallic particles, can be rotated by transferring the
spin angular momentum (SAM) of
chiral light to the assembly. Rotating OM is a promising platform for optical micromachines, with potential applications in plasmofluidics and soft robotics. Understanding the dynamic states of such Brownian, micro-mechanical systems is a relevant issue. One key problem is understanding kinetic jamming and clogging. Studies of driven multiparticle systems have revealed that under suboptimal driving, the systems can stop moving, showing jamming transitions. It is important to identify dynamic regimes where crowding competes with driving and is susceptible to jamming in the context of optical micromachines. Through experiments supported by numerical simulations, we reveal assemblies with well-defined hexagonal or triangular
symmetry that efficiently harness the SAM of incident
chiral light, resulting in stable rotation. However, as the plasmonic-particle assembly grows and its dimensions approach the beam waist, new particles can disrupt this order. This causes a transition to a fluid-like state with less-defined
symmetry, correlated with a significant reduction in transferred torque, causing rotation to stagnate or cease. We suggest this behaviour is analogous to a rotational jamming transition, where the rotational motion is arrested. Our findings establish a clear relationship between the structural
symmetry of the OM assembly and its ability to harness SAM, providing new insights into controlling
chiral light-matter interactions and offering a novel platform for studying jamming transitions.
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All authors Ashutosh Shukla, Sneha Boby, Rahul Chand, G. V. Pavan Kumar
Optics
The $N$-achromat and beyond: a unified variational framework for optimal chromatic aberration correction
Bastien Laville and Benjamin Aymard
In this article, we present novel and effective methods for reducing chromatic aberrations in cemented lens systems. We derive an analytical solution coined the pentachromat, which corrects five distinct colors. This method can naturally be extended to accommodate an arbitrary number of lenses and to correct for a customized selection of spectral lines. Since correcting for specific rays rather than the entire residual spectrum can overconstrain the system, we introduce a variational formulation. This approach tames the residual spectrum by several orders of magnitude compared to conventional designs like the superachromat, while giving theoretical guarantees to reach the optimal solutions. Furthermore, this innovative methodology opens up previously uncharted design possibilities, such as multiple-focal-length achromatic systems. This allows for the selection of specific optical powers paired with desired bandwidths, enabling the design of highly specialized and tailored optical systems. Finally, we couple our variational framework with a combinatorial search, allowing to find the type of glasses and their geometry such that it reaches the best residual spectrum over an available catalogue.
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Optics
Surface Plasmon Mediated Giant Goos-Hanchen and Imbert-Fedorov Shifts on a Corrugated Metal Surface
Arani Maiti, Sauvik Roy, Abhi Mondal et al. (+3 more)
Enhanced beam shifts mediated by surface plasmon resonance (SPR) at metal-dielectric interfaces have been widely investigated. However, research on the associated Imbert-Fedorov or
spin Hall shifts, driven by the
spin-orbit interaction of structured light in structured interfaces, has been comparatively scarce and limited. We explore the reflection characteristics of generic polarized, non-paraxial light beams from a corrugated silver (Ag) interface, since surface corrugation can naturally couple the incident radiation modes to the surface excitations. In the vicinity of SPR, we report a significant enhancement in the beam shifts, attributed to the rapid variation of the specular reflection coefficient near its minima, resulting in amplified weak values. By carefully selecting the incident and projected polarization states of the beam, we achieve a pronounced spatial
spin Hall effect. We also investigate
vortex-induced beam shifts within this resonant regime, revealing distinctive signatures of the angular momentum of the beam. Furthermore, a comprehensive analysis is also presented for the conical diffraction geometry, wherein polarization conversions between p and s states are fully incorporated. Our work establishes the interplay of the
spin-orbit interaction of light and the weak measurement approach as an important methodology in amplifying SPR effects, which may have important connotations in applications involving light at nanoscales.
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All authors Arani Maiti, Sauvik Roy, Abhi Mondal, Ayan Banerjee, Nirmalya Ghosh, Subhasish Dutta Gupta
Plasma Physics
Data-driven multi-species heat flux closures for two-stream-unstable plasmas with nonlinear sparse regression
Emil R. Ingelsten, Madox C. McGrae-Menge, E. Paulo Alves et al. (+1 more)
The dual aims of accuracy and computational efficiency in computational
plasma physics lend themselves well to the use of fluid models. The first of these goals, however, is only satisfied for such models insofar as the utilized closure can capture the neglected kinetic physics – something which has proven challenging for multi-scale collisionless processes. In a recent article [E. R. Ingelsten et al. (2025) J.
Plasma Phys. 91 E64], we used the data-driven method of sparse regression to discover a novel heat flux closure for electrostatic phenomena. Here, we generalize the six-term closure model found in that work from single- to multi-species modeling. Using data from OSIRIS particle-in-
cell simulations over a range of initial conditions, we then demonstrate how the unknown coefficients in front of the three most important terms in the closure can be estimated from box-averaged fluid quantities. Both neural networks and a newly developed framework for nonlinear sparse regression are showcased. The resulting models predict the heat flux for each species with a typical accuracy of 80-90 % and regularly account for 85-95 % of the rate of change in the pressure. The models are also compared with results from multi-species linear collisionless theory.
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All authors Emil R. Ingelsten, Madox C. McGrae-Menge, E. Paulo Alves, Istvan Pusztai
Classical Physics · Cross-listed from math.NA
Accelerating the Serviceability-Based Design of Reinforced Concrete Rail Bridges under Geometric Uncertainties induced by unforeseen events: A Surrogate Modeling approach
Mouhammed Achhab, Pierre Jehel and Fabrice Gatuingt
Reinforced concrete rail bridges are essential components of railway infrastructure, where reliability, durability, and adaptability are key design priorities. However, the design process is often complicated by uncertainties stemming from unforeseen construction constraints, such as the need to reposition piers or alter
geometric characteristics. These design adaptations can lead to repeated redesigns, added costs, and project delays if not anticipated in the early design stages, as well as significant computational overhead when using traditional finite element (FE) simulations. To address this and anticipate such unexpected events, this study adopts surrogate modeling as an efficient probabilistic design approach. This methodology integrates key
geometric parameters as random variables, capturing the uncertainties that may arise during the design and construction phases and propagating them on the bridge's performance functions. By doing so, we aim to enable the efficient exploration of a large number of design scenarios with minimal reliance on time-consuming finite element (FE) simulations, represent the performance functions of a reinforced concrete bridge as a function of our variable design parameters, and classify the overall design scenarios into failure and safe scenarios In this study, a four-span reinforced concrete bridge deck is modeled using a multi-fiber finite element approach in Cast3M software. This FE model is used to generate the required design of experiments to train the surrogate models. Within this framework, a comparative performance assessment is conducted to evaluate the performance of the Kriging surrogate against alternative methods, including
polynomial chaos expansion (implemented in UQLab) and support vector regression (SVR). This methodology supports early-stage uncertainty-informed design, enhancing the robustness and adaptability of reinforced concrete rail bridges in the face of practical constraints and changing site conditions.
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Plasma Physics
Microscopy X-ray Imaging enriched with Small Angle X-ray Scattering for few nanometer resolution reveals shock waves and compression in intense short pulse laser irradiation of solids
Thomas Kluge, Arthur Hirsch-Passicos, Jannis Schulz et al. (+23 more)
Understanding how
laser pulses compress solids into high-energy-density states requires diagnostics that simultaneously resolve macroscopic geometry and nanometer-scale structure. Here we present a combined X-ray imaging (XRM) and small-angle X-ray scattering (SAXS) approach that bridges this diagnostic gap. Using the Matter in Extreme Conditions end station at LCLS, we irradiated 25-micrometer copper wires with 45-fs, 0.9-J, 800-nm pulses at 3.5e19 W/cm2 while probing with 8.2-keV XFEL pulses. XRM visualizes the
evolution of ablation, compression, and inward-propagating fronts with about 200-nm resolution, while SAXS quantifies their nanometer-scale sharpness through the time-resolved
evolution of scattering streaks. The joint analysis reveals that an initially smooth compression steepens into a nanometer-sharp shock front after roughly 18 ps, consistent with an analytical steepening model and hydrodynamic simulations. The front reaches a velocity of about 25 km/s and a lateral width of several tens of micrometers, demonstrating for the first time the direct observation of shock formation and decay at solid density with few-nanometer precision. This integrated XRM-SAXS method establishes a quantitative, multiscale diagnostic of
laser-driven shocks in dense
plasmas relevant to inertial confinement fusion, warm dense matter, and planetary physics.
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All authors Thomas Kluge, Arthur Hirsch-Passicos, Jannis Schulz, Mungo Frost, Eric Galtier, Maxence Gauthier, Jörg Grenzer, Christian Gutt, Lingen Huang, Uwe Hübner, Megan Ikeya, Hae Ja Lee, Dimitri Khaghani, Willow Moon Martin, Brian Edward Marré, Motoaki Nakatsutsumi, Paweł Ordyna, Franziska-Luise Paschke-Brühl, Alexander Pelka, Lisa Randolph, Hans-Peter Schlenvoigt, Christopher Schoenwaelder, Michal Šmíd, Long Yang, Ulrich Schramm, Thomas E. Cowan
Medical Physics
Using an instrumented hammer during Summers osteotomy: an animal model
Yasuhiro Homma, Manon Bas Dit Nugues, Arnaud Dubory et al. (+5 more)
Summers osteotomy is a technique used to increase bone height and to improve bone density in dental implant surgery. The two main risks of this surgery, which is done by impacting an osteotome in bone tissue, are i) to perforate the sinus membrane and ii) the occurrence of benign paroxysmal vertigo, which are both related to excessive impacts during the osteotomy. Therefore, impacts must be carefully modulated. The aim of this study is to determine whether an instrumented hammer can predict bone damage before the total osteotome protrusion. 35 osteotomies were performed in 9 lamb palate samples using a hammer instrumented with a force sensor to record the variation of the force as a function of time s(t). A signal processing was developed to determine the parameter $\tau$ corresponding to the time between the first two peaks of s(t). A camera was used to determine the impact number for damage: NVideo. The surgeon determined when damage occurred, leading to NSurg. An
algorithm was developed to detect bone damage based on the variation of $\tau$ as a function of the impact number, leading to Ncrit. The
algorithm was always able to detect bone damage before total protrusion of the osteotome. We obtained NVideo -NCrit > -2 (respectively NSurg -NCrit > -2) for 97 % (respectively 94 %) of the cases, which indicates the
algorithm was almost always able to detect bone damage at most one impact after the
video (respectively the surgeon). Our results pave the way to safer Summers osteotomy.
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All authors Yasuhiro Homma, Manon Bas Dit Nugues, Arnaud Dubory, Charles-Henri Flouzat-Lachaniette, Jean- Paul Meningaud, Barbara Hersant, Emmanuel Gouet, Guillaume Haïat
Medical Physics
Estimation of the surface mechanical properties of soft tissues mimicking phantoms using impact analyses: a comparative study
Arthur Bouffandeau, Sabine Bensamoun, Robert Schleip et al. (+4 more)
Background: Palpation is the most widely used approach to empirically assess the mechanical properties of superficial tissues. While elastography is used for volume measurements, it remains difficult to assess skin properties with non-invasive methods. This study aimed to compare the performances of an impact-based analysis method (IBAM) consisting in studying the dynamic response of a punch in contact with the tissue with other approaches available on the
market. Materials and Methods: IBAM consists in analyzing the time dependent force signal induced when a hammer instrumented with a force sensor impacts a cylindrical punch placed in contact with soft tissue. Sensitivities to stiffness changes and to spatial variations were compared between IBAM and four other mechanical surface characterization techniques: IndentoPro (macroindentation), Cutometer (suction), MyotonPro (damped oscillation) and Shore Durometer (durometry) using soft tissue phantoms based on polyurethane gel. Results: For stiffness discrimination in homogeneous phantoms, IBAM was slightly better than IndentoPro and MyotonPro (by 20 % and 35 % respectively), and outperformed the Shore Durometer and Cutometer by a factor of 2 to 4. Furthermore, for stiffness and thickness variations in
bilayer phantoms, the axial sensitivity of IBAM was between 2.5 and 4.5 times better than that of MyotonPro and IndentoPro. In addition, the Cutometer appeared to be severely limited by its measurement depth. Conclusion: IBAM seems to be a promising technique for characterizing the mechanical properties of soft tissue phantoms at relatively low depth after future ex vivo and in vivo validation studies with biological tissues (with both animal and in human experiments). This work could pave the way to the development of a decision support system in the field of dermatology and cosmetics.
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All authors Arthur Bouffandeau, Sabine Bensamoun, Robert Schleip, Giuseppe Rosi, Charles-Henri Flouzat-Lachaniette, Jean-Paul Meningaud, Guillaume Haiat
Medical Physics
An Instrumented Hammer to Detect the Bone Transitions During an High Tibial Osteotomy: An Animal Study
Bas-Dit-Nugues Manon, Teddy Ketani, Claire Bastard et al. (+5 more)
High tibial osteotomy is a common procedure for knee osteoarthritis during which the surgeon partially opens the tibia and must stop impacting when cortical bone is reached by the osteotome. Surgeons rely on their proprioception and fluoroscopy to conduct the surgery. Our group has developed an instrumented hammer to assess the mechanical properties of the material surrounding the osteotome tip. The aim of this ex vivo study is to determine whether this hammer can be used to detect the transition from cortical to trabecular bone and vice versa. Osteotomies were performed until rupture in pig tibia using the instrumented hammer. An
algorithm was developed to detect both transitions based on the relative variation of an indicator derived from the time variation of the force. The detection by the
algorithm of both transitions was compared with the position of the osteotome measured with a
video camera and with surgeon proprioception. The difference between the detection of the
video and the
algorithm (respectively, the
video and the surgeon; the surgeon and the
algorithm) is 1.0$\pm$1.5 impacts (respectively, 0.5$\pm$0.6 impacts; 1.4$\pm$1.8 impacts), for the detection of the transition from the cortical to trabecular bone. For the transition from the trabecular to cortical bone, the difference is 3.6$\pm$2.6 impacts (respectively, 3.9$\pm$2.4 impacts; 0.8$\pm$0.9 impacts), and the detection by the
algorithm was always done before the sample rupture. This ex vivo study demonstrates that this method could prevent impacts leading to hinge rupture.
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All authors Bas-Dit-Nugues Manon, Teddy Ketani, Claire Bastard, Giuseppe Rosi, Hugues Albini Lomani, Charles-Henri Flouzat-Lachaniette, Arnaud Dubory, Guillaume Haïat
Medical Physics
Lanthanides-Based Nanoparticles Conjugated with Rose Bengal for FRET-Mediated X-Ray-Induced PDT
Batoul Dhaini, Joël Daouk, Hervé Schohn et al. (+8 more)
In order to find a good candidate for Förster Resonance Energy Transfer (FRET)-mediated X-ray-induced photodynamic therapy (X-PDT) for the treatment of cancer, lanthanide (Ln)-based AGuIX nanoparticles (NPs) conjugated with Rose Bengal (RB) as a photosensitizer (PS) were synthesized. X-PDT overcomes the problem of the poor penetration of visible light into tissues, which limits the efficacy of PDT in the treatment of deep-seated tumors. It is essential to optimize FRET efficiency by maximizing the overlap integral between donor emission and acceptor absorption and lengthening the duration of the donor emission. In this study, we optimized energy transfer between a scintillator (Sc) as a donor and a PS as an acceptor. Terbium (Tb) and Gadolinium (Gd) as Scs and Rose RB as a PS were chosen. The study of energy transfer between Tb, Gd and RB in solution and chelated on AGuIX NPs proved to be FRET-like. RB was conjugated directly onto AGuIX NPs (i.e., AGuIX Ln@RB), and the use of a spacer arm (i.e., AGuIX Ln@spacer arm-RB) increased FRET efficiency. Singlet oxygen production by these NPs was observed under UV–visible illumination and X-ray irradiation. The in vitro bioassay demonstrated 52%
cell death of U-251MG derived from human malignant glioblastoma multiforme at a concentration of 1 $\mu$M RB after illumination and irradiation (2 Gy, 320 kV, 10 mA, 3 Gy/min at 47 cm). In addition, the RB-coupled NRP-1-targeting peptide (i.e., K(RB)DKPPR) was conjugated onto AGuIX NPs by a thiol-maleimide click chemistry reaction, and an affinity in the nM range was observed.
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All authors Batoul Dhaini, Joël Daouk, Hervé Schohn, Philippe Arnoux, Valérie Jouan-Hureaux, Albert Moussaron, Agnès Hagege, Mathilde Achard, Samir Acherar, Tayssir Hamieh, Céline Frochot
Atomic and Molecular Clusters · Cross-listed from cond-mat.quant-gas
Generalized Gross-Pitaevskii Equation for 2D Bosons with Attractive Interactions
Michał Suchorowski, Fabian Brauneis, Hans-Werner Hammer et al. (+2 more)
We introduce a generalized Gross-Pitaevskii equation that provides a nonlinear framework for studying two-dimensional (2D) attractive Bose systems. Its defining feature is the logarithmic density dependence of the coupling constant, which breaks the scale invariance inherent in the standard mean-field equations. This framework allows straightforward calculations of the system properties arising from the
quantum anomaly. As a first illustration, we study universal bound states in free space, commonly referred to as
quantum droplets. Then, we analyze breathing modes and quench dynamics in trapped systems, paving the way for a systematic exploration of non-
equilibrium phenomena in 2D attractive Bose systems. Finally, we predict the existence of universal excited states, including
vortex configurations, which may be more accessible to experimental investigation than the ground state. Our results provide a robust theoretical foundation for studying both static and dynamical properties of finite systems, and offer guidance for the design of future experiments.
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All authors Michał Suchorowski, Fabian Brauneis, Hans-Werner Hammer, Michał Tomza, Artem G. Volosniev
History and Philosophy of Physics · Cross-listed from hep-th
Zeno's paradox and black hole information loss problem
Xian-Hui Ge
We develop a conceptual parallel between the black hole information problem and Zeno's paradox, highlighting the role of limiting procedures that turn formally infinite constructions into finite physical observables. Building on the replica–wormhole paradigm, we move beyond unitarity restoration to formulate a quantitative notion of irreversibility in Hawking radiation. Our main result is a modular thermodynamic framework for black-hole evaporation, in which modular
entropy,
entanglement capacity, and relative
entropy assume thermodynamic roles. The monotonicity of relative
entropy furnishes a generalized second law that determines the arrow of
evolution in replica space. We further resolve the apparent tension between the replica method and the
quantum no-cloning
theorem by interpreting replicas as ensemble representations rather than physical copies of an unknown state, thereby clarifying the operational meaning of gravitational path integrals. A key message of this work is that non-additivity in Tsallis statistics provides an information-theoretic analogue of the correlations induced by replica wormholes.
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Physics Education
On the design of a profession-oriented course on Theoretical Mechanics for physics education students
Marianne Korner and Christos N. Likos
We report on a profession-oriented course we offered at the University of Vienna, aimed at physics education teacher students. The course on Theoretical Classical Mechanics has been conceived and designed from its outset with the explicit goal of bridging the gap between the abstract, mathematical notions employed in Theoretical Physics with the concrete future needs of prospective teachers in their profession. We aimed at countering both the negative attitudes of students towards Theoretical Physics and the interrelated skepticism of professors regarding the students mathematical proficiency. Our main findings are that these goals can indeed be achieved through a careful selection of course material and the associated mathematical tools, by closely interwoven lecture topics and exercises, and thorough planning according to principles for high-school teaching known from science education research. Establishing close connections between the material taught in the course and the students future occupation as high-school teachers has proven to be of utmost importance. This is possible without any sacrifice of mathematical rigor or of the quality of Physics presented.
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Plasma Physics
Tailored Three Dimensional Betatron Dynamics in UltraStable Hybrid Laser Plasma RF Accelerators
A. A. Molavi Choobini and M. Shahmansouri
The detailed theoretical and numerical investigation of hybrid
laser plasma RF accelerators, elucidating the mechanisms governing transverse beam dynamics, betatron polarization, and radiation reaction in ultra-relativistic electron bunches is presented. This framework combines analytical models of spatiotemporal
plasma wakefield modulation, phase-dependent RF-driven oscillations, and
quantum-corrected Landau Lifshitz radiation reaction with fully self-consistent 3D particle in
cell simulations using EPOCH. The results demonstrate that RF amplitude, frequency, and phase enable precise control over transverse focusing strengths, betatron oscillation amplitudes, and polarization states. Resonant
alignment between RF fields and natural betatron frequencies amplifies transverse excursions while damping parasitic oscillations through enhanced focusing gradients and radiation reaction, yielding reductions in emittance and mitigation of synchrotron-like energy losses. Stability maps and 3D force landscapes reveal strong phase sensitivity, where initial conditions and RF component ratios govern the temporal
evolution of betatron amplitudes, and longitudinal field gradients modulate {\gamma} growth rates. These findings provide a comprehensive picture of nonlinear, resonant, and damping phenomena in hybrid
laser plasma RF systems, highlighting the full spectrum of controllable transverse, longitudinal, and polarization dynamics in ultra relativistic electron beams.
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Instrumentation and Detectors
Temperature Dependence of the Time Resolution in a SiPM-Readout Plastic Scintillator for Cosmic-Ray Applications
José Reyes Castillo, Saúl Aguilar Salazar and Diego Mauricio Gomez Coral
Balloon- and space-borne
cosmic-ray experiments employ plastic scintillators read out by silicon photomultipliers (SiPMs) to achieve picosecond-level time resolutions for triggering and particle identification. The performance of these systems can be affected by temperature variations encountered in flight. In this work, a time-of-flight (TOF) prototype consisting of a BC418 plastic scintillator bar coupled to Onsemi MICROFC-30050 SiPMs was constructed and tested under a controlled thermal environment between -20 and 20$^{\circ}$C. Electrons from a $^{90}\text{Sr}$ source were used as a beam, and a dedicated differential preamplifier and coincidence triggering were implemented to study the detector response. A minimum time resolution of 160ps was achieved at an overvoltage of 3V, remaining stable across the tested temperature range and uniform along the scintillator bar.
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Geophysics
2.5D Transformer: An Efficient 3D Seismic Interpolation Method without Full 3D Training
Changxin Wei, Xintong Dong and Xinyang Wang
Transformer has emerged as a powerful deep-learning technique for two-dimensional (2D) seismic data interpolation, owing to its global modeling ability. However, its core operation introduces heavy computational burden due to the quadratic complexity, hindering its further application to higher-dimensional data. To achieve
Transformer-based three-dimensional (3D) seismic interpolation, we propose a 2.5-dimensional
Transformer network (T-2.5D) that adopts a cross-dimensional transfer learning (TL) strategy, so as to adapt the 2D
Transformer encoders to 3D seismic data. The proposed T-2.5D is mainly composed of 2D
Transformer encoders and 3D seismic dimension adapters (SDAs). Each 3D SDA is placed before a
Transformer encoder to learn spatial correlation information across seismic lines. The proposed cross-dimensional TL strategy comprises two stages: 2D pre-training and 3D fine-tuning. In the first stage, we optimize the 2D
Transformer encoders using a large amount of 2D data patches. In the second stage, we freeze the 2D
Transformer encoders and fine-tune the 3D SDAs using limited 3D data volumes. Extensive experiments on multiple
datasets are conducted to assess the effectiveness and efficiency of T-2.5D. Experimental results demonstrate that the proposed method achieves comparable performance to that of full 3D
Transformer at a significantly low cost.
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Classical Physics
Revisiting Koehler's experiment of measuring the ratio of the specific heats of air by self-sustained oscillations
Yujun Shi and Xiaoting Fen
We revisit Koehler's experiment, a clever modification of Ruchardt's experiment designed to measure the ratio of specific heats of gas. However, the lengthy and dense analysis shared by Koehler in his 1950 paper may pose challenges to readers due to the complexity of the calculations. Following Koehler's approximation for pressure changes, we explicitly present the model equations as piecewise linear differential systems and qualitatively analyze the periodic solutions from a
geometric perspective. This concise and transparent approach addresses a fundamental question about Koehler's experiment: why is the oscillation frequency nearly equal to the Ruchardt frequency? Our analysis avoids intricate calculations and should help educators introduce Koehler's experiment in general physics laboratory classes
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Instrumentation and Detectors
Autonomous X-ray Fluorescence Mapping of Chemically Heterogeneous Systems via a Correlative Feature Detection Framework
Carlos Deleon, Dmitri Gavrilov, Peggy ODay et al. (+1 more)
We present X-AutoMap, a modular framework for autonomous X-ray fluorescence (XRF) mapping that enables chemically informed targeting of regions of interest through a correlative feature detection strategy. The system integrates classical computer
vision and rule-based logic to identify features based on spatial relationships across multiple elemental maps, rather than relying solely on intensity or morphology. Tight integration with the Bluesky control infrastructure at the NSLS-II Hard X-ray Nanoprobe (HXN) beamline enables real-time, closed-loop scan orchestration. Applied to a chemically heterogeneous urban PM2.5 sample, X-AutoMap reduced high-resolution acquisition time from over 44 hours to approximately 10 hours by targeting compositionally significant features identified from coarse scans. High-resolution results revealed diverse particle types, including fully mixed, partially overlapping, and spatially distinct multi-element structures, demonstrating the ability of the framework to isolate chemically relevant features with minimal user intervention. The framework supports interactive and autonomous modes, operates within hardware constraints via grid-based scanning, and is robust across varying sample conditions. Future extensions will incorporate machine learning and probabilistic sampling to further improve detection sensitivity and scan efficiency. X-AutoMap is currently in active use at HXN and provides a flexible foundation for scalable, intelligent imaging workflows at synchrotron beamlines.
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All authors Carlos Deleon, Dmitri Gavrilov, Peggy ODay, Ajith Pattammattel
Instrumentation and Detectors
High-throughput Parasitic-independent Probe Thermal Resistance Calibration for Robust Thermal Mapping with Scanning Thermal Microscopy
Ram Munde, Heng-Ray Chuang and Raisul Islam
Nanostructured materials, critical for thermal management in
semiconductor devices, exhibit a strong size dependence in thermal transport. Studying thermal resistance variation across grain boundaries is critical for designing effective thermal interface materials. Frequency-domain Thermoreflectance (FDTR)-based techniques can provide thermal resistance mapping at the micrometer ({\mu}m) scale. Scanning Thermal Microscopy (SThM) enables quantification of local thermal transport with significantly higher spatial resolution (<100 nm). However, challenges in quantifying the raw signal to thermal conductivity and surface sensitivity limit its widespread adoption for understanding nanoscale heat transport and defect-mediated thermal properties in nanostructured films. Here, we introduce a
circuit-based probe thermal resistance (R_p) calibration technique independent of parasitic heat pathways, enabling accurate determination of probe heat dissipation and tip temperature rise, thereby allowing extraction of local thermal resistance. SThM achieved sub-100 nm spatial resolution in mapping thermal resistance across a 15 nm-thick Al film deposited via e-beam evaporation on SiO_2 substrate. The thermal resistance maps are converted to thermal conductivity using robust analytical and finite element models that account for tip-sample geometry, lateral heat spreading, and buried interface effects. Gaussian distribution fitting of pixel-level thermal resistance values yields k_Al = 45.1(+4.7/-3.6) W/(m.K) for the ultra-thin Al film (13-15 nm), representing a 5.3-fold reduction from bulk aluminum (237 W/(m.K)). These results agree with published experimental data and theoretical frameworks explaining thickness-dependent heat transport in ultra-thin metallic films.
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Optics · Cross-listed from eess.IV
Learning phase diversity for solving ill-posed inverse problems in imaging
Jasleen Birdi, Tamal Majumder, Debanjan Halder et al. (+2 more)
Inverse problems in imaging are typically ill-posed and are usually solved by employing regularized optimization techniques. The usage of appropriate constraints can restrict the solution space, thus making it feasible for a reconstruction
algorithm to find a meaningful solution. In recent years, deep network based ideas aimed at learning the end-to-end mapping between the raw measurements and the target image have gained popularity. In the learning approach, the functional relationship between the measured raw data and the solution image are learned by training a deep network with prior examples. While this approach allows one to significantly increase the real-time operational speed, it does not change the nature of the underlying ill-posed inverse problem. It is well-known that availability of diverse non-redundant data via additional measurements can generically improve the robustness of the reconstruction
algorithms. The multiple data measurements, however, typically demand additional hardware and complex system setups that are not desirable. In this work, we note that in both incoherent and coherent optical imaging, the irradiance patterns corresponding to two phase diverse measurements associated with the same test object have implicit local correlation which may be learned. A physics informed data augmentation scheme is then described where a trained network is used for generating a phase diverse pseudo-data based on a ground truth data frame. The true data along with the augmented pesudo-data are observed to provide high quality inverse solutions with simpler reconstruction
algorithms. We validate this approach for both incoherent and coherent optical imaging (or phase
retrieval) configurations with
vortex phase as a diversity mechanism. Our results may open new avenues for leaner high-fidelity computational imaging systems across a broad range of applications.
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All authors Jasleen Birdi, Tamal Majumder, Debanjan Halder, Muskan Kularia, Kedar Khare
Plasma Physics
$\pi$-PIC: a framework for modular particle-in-cell developments and simulations
Frida Brogren, Christoffer Olofsson, Joel Magnusson et al. (+1 more)
Particle-in-
cell (PIC) codes are indispensable tools for studying
plasma-based interactions across a wide range of physical regimes. The predictive capabilities of these codes have dramatically increased by continuous advances in
algorithms and computing hardware. Nevertheless, greater computational performance and broader framework capabilities often lead to increased software complexity, hindering the adoption, evaluation, and comparison of new numerical developments. In this work, we present a Python-controlled framework designed to facilitate the dissemination and adoption of novel PIC developments by providing a unified interface for accommodation, cross-testing, and comparison of PIC
algorithms. To demonstrate the flexibility of the proposed interface, we implement and discuss a range of PIC schemes together with applications involving absorbing boundary layers, moving-window simulations, and tight
laser focusing.
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All authors Frida Brogren, Christoffer Olofsson, Joel Magnusson, Arkady Gonoskov
Chemical Physics · Cross-listed from cs.MS
SeQuant Framework for Symbolic and Numerical Tensor Algebra. I. Core Capabilities
Bimal Gaudel, Robert G. Adam, Ajay Melekamburath et al. (+5 more)
SeQuant is an open-source library for symbolic
algebra of tensors over commutative (scalar) and non-commutative (operator) rings. The key innovation supporting most of its functionality is a graph-theoretic tensor network (TN) canonicalizer that can handle tensor networks with
symmetries faster than their standard group-theoretic counterparts. The TN canonicalizer is used for routine simplification of conventional tensor expressions, for optimizing application of Wick's
theorem (used to canonicalize products of tensors over operator fields), and for manipulation of the intermediate representation leading to the numerical evaluation. Notable features of SeQuant include support for noncovariant tensor networks (which often arise from tensor decompositions) and for tensors with modes that depend parametrically on indices of other tensor modes (such dependencies between degrees of freedom are naturally viewed as nesting of tensors, "tensors of tensors" arising in block-wise data compressions in data science and modern
quantum simulation). SeQuant blurs the line between pure symbolic manipulation/code generation and numerical evaluation by including compiler-like components to optimize and directly interpret tensor expressions using external numerical tensor
algebra frameworks. The SeQuant source code is available at https://github.com/ValeevGroup/SeQuant.
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All authors Bimal Gaudel, Robert G. Adam, Ajay Melekamburath, Conner Masteran, Nakul Teke, Azam Besharatnik, Andreas Köhn, Edward F. Valeev