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Physics Physics

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Monday 9 February

Popular Physics

Roadmap to Quantum Aesthetics

Ivan C. H. Liu and Hsiao-Yuan Chen

Quantum mechanics occupies a central position in contemporary science while remaining largely inaccessible to direct sensory experience. This paper proposes a roadmap to quantum aesthetics that examines how quantum concepts become aesthetic phenomena through artistic mediation rather than direct representation. Two complementary and orthogonal approaches are articulated. The first, a pioneering top-down approach, employs text-prompt-based generative AI to probe quantum aesthetics as a collective cultural construct embedded in large-scale training data. By systematically modulating the linguistic weight of the term "quantum," generative models are used as experimental environments to reveal how quantum imaginaries circulate within contemporary visual culture. The second, a bottom-up approach, derives aesthetic form directly from quantum-mechanical structures through the visualization of quantum-generated data, exemplified here by hydrogen atomic orbitals calculated from the Schrödinger equation. These approaches are framed not as competing methods but as intersecting paths within a navigable field of artistic research. They position quantum aesthetics as an emergent field of artistic research shaped by cultural imagination, computational mediation, and physical law, opening new directions for artistic practice and pedagogy at the intersection of art, data, artificial intelligence and quantum science.
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Optics

Room Temperature Collective Blinking and Photon Bunching from CsPbBr3 Quantum Dot Superlattice

Qiwen Tan, Sudipta Seth, Boris Louis et al. (+7 more)

Development of quantum light sources and search for quantum systems capable of supporting collective many-body states are crucial for further progress of modern quantum technologies. Metal halide perovskite quantum dots (QDs) have emerged as a promising candidate for quantum light sources, as individual QDs are reliable single photon emitters even at room temperature. However, photon bunching, a key signature of collective many-body states, has been so far largely observed at cryogenic temperatures in perovskite materials, limiting their applications under ambient conditions. Here, we report the observation of collective blinking and photon bunching in perovskite QD superlattices at room temperature. Sub-wavelength-sized (100 - 500 nm) CsPbBr3 QD superlattices, fabricated via a self-assembly process, exhibit an unusual two-level blinking behavior similar to that of single QDs, and demonstrate photon bunching with a degree of up to 2.75. Time-resolved photoluminescence (PL) measurements and super-resolution imaging reveal that the superlattices have a significantly longer PL lifetime than individual QDs and that their emission is spatially confined to regions tens of nanometers in size. These observations suggest long-range exciton migration to a localized energy trap within the superlattice. Excitation power dependent degree of bunching and analysis of the bunching dynamics indicate that the photon bunching originates from exciton-biexciton cascade emission, a key mechanism for generating entangled photons. These findings establish perovskite QD superlattices as a promising platform for room-temperature collective optical phenomena and quantum light generation, advancing scalable quantum photonic technologies.
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All authors Qiwen Tan, Sudipta Seth, Boris Louis, Xiayan Wu, Nithin Pathoor, Toranosuke Takagi, Shun Omagari, Takumi Sannomiya, Johan Hofkens, Martin Vacha

Optics

2.5D co-packaged optical I/O chipsets on a SiON/Si interposer for 4 $\times$ 100G optical interconnection

Daibao Hou, Yuntian Yao, Xiaotian Cheng et al. (+9 more)

Optical I/O technologies have emerged as a potential industrial solution for high-performance data interconnection in AI/ML computing acceleration. While optical I/Os are deployed at the edge of computational chips by co-packaged optics (CPO), flexible and high-performance integration architectures need to be explored to address system-level challenges. In this work, we present and experimentally demonstrate a SiON/Si-based optical interposer that integrates high-bandwidth and energy-efficient optical I/O chipsets. High-performance photonic and electronic components are co-packaged on the interposer, leading to low-loss, signal-integrity-friendly, and thermally efficient characteristics. The optical interposer incorporates low-loss SiON photonic circuits to realize scalable waveguide routing and wavelength-division multiplexing (WDM) with polarization-insensitive operation and high fabrication tolerance, while supporting flip-chip integration with InP-based active devices, including electro-absorption modulated lasers (EMLs) and photodetectors (PDs). Based on this architecture, a 400-Gb/s single-fiber optical transceiver is implemented and experimentally evaluated. Clear eye diagrams and high receiver sensitivity demonstrate reliable high-speed data transmission, which offers scalable, high-bandwidth optical I/Os in future high-performance computational clusters.
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All authors Daibao Hou, Yuntian Yao, Xiaotian Cheng, Shuning Ding, Qiyou Wu, Yonghong Hu, Wei Pan, Chao Huang, Huihui Zhu, Yongzhen Huang, Chenhui Li, Chaoyuan Jin

Fluid Dynamics

A few-shot and physically restorable symbolic regression turbulence model based on normalized general effective-viscosity hypothesis

Ziqi Ji, Penghao Duan and Gang Du

Turbulence is a complex, irregular flow phenomenon ubiquitous in natural processes and engineering applications. The Reynolds-averaged Navier-Stokes (RANS) method, owing to its low computational cost, has become the primary approach for rapid simulation of engineering turbulence problems. However, the inaccuracy of classical turbulence models constitutes the main drawback of the RANS framework. With the rapid development of data-driven approaches, many data-driven turbulence models have been proposed, yet they still suffer from issues of generalizability and accuracy. In this work, we propose a few-shot, physically restorable, symbolic regression turbulence model based on the normalized general effective-viscosity hypothesis. Few-shot indicates that our model is trained on limited flow configurations spanning only a narrow subset of turbulent flow physics, yet can still outperform the baseline model in substantially different turbulent flows. Physically restorable means our model can nearly revert to the baseline model in regimes satisfying specific physical conditions, using only the symbolic regression training results. The normalized general effective-viscosity hypothesis was proposed in our previous study. Specifically, we first formalize the concept of few-shot data-driven turbulence models. Second, we train our symbolic regression turbulence models using only direct numerical simulation (DNS) data for three-dimensional periodic hill flow slices. Third, we evaluate our models on periodic hill flows, zero pressure gradient flat plate flow, NACA0012 airfoil flows, and NASA Rotor 37 transonic axial compressor flows. One of our symbolic regression turbulence models consistently outperforms the baseline model, and we further demonstrate that this model can nearly revert to baseline behavior in certain flow regimes.
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Biological Physics · Cross-listed from cond-mat.soft

Quo vadis biophotonics? Wearing serendipity and slow science as a badge of pride, and embracing biology

G.E. Schroeder-Turk

This article is a reflection on the themes of the Faraday Discussion meeting on "Biological and bio-inspired optics" held from 20 to 22 July 2020. It is a personal perspective on the nature of this field as a broad and interdisciplinary field that has led to a sound understanding of the material properties of biological nanostructured and optical materials. The article describes how the nature of the field and the themes of the conference are reflected in particular in work on the 3D bicontinuous biophotonic nanostructures known as single gyroids and in bicontinuous structures more broadly. Such single gyroid materials are found for example in the butterfly Thecla opisena, where the questions of biophotonic response, of bio-inspired optics, of the relationship between structure and function, and of the relationship between natural and synthetic realisations are closely interlinked. This multitude of facets of research on single gyroid structures reflects the beauty of the broader field of biophotonics, namely as a field that lives through embracing the serendipitous discovery of the biophotonic marvels that nature offers to us as seeds for in-depth analysis and understanding. The meandering nature of its discoveries, and the need to accept the slowness that comes from exploration of intellectually new or foreign territory, mean that the field shares some traits with biological evolution itself. Looking into the future, I consider that a closer engagement with living tissue and with the biological questions of function and formation, rather than with the materials science of biological materials, will help ensure the continuing great success of this field.
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Applied Physics

Infrared photonics for healthcare: A roadmap for proactive and predictive health management

Borislav Hinkov, Johannes Kunsch, Werner Mäntele et al. (+82 more)

The field of infrared (IR) photonics is currently undergoing remarkable progress, moving rapidly towards practical sensing applications demanded by medical therapy and diagnostics (theranostics). The Developments can be divided into three main categories: (i) novel devices and measurement concepts including advanced updates of classical approaches that push medical sensing into the spotlight; (ii) new demonstrations of photonic integrated circuit (PIC-)based IR devices enabling highly miniaturized sensors for point-of-care application as well as medical and wellness wearables; and (iii) technologically-mature IR demonstrators that enable first medical sensing and treatment applications. This roadmap paper provides a consolidated overview of this highly dynamic and interdisciplinary research field with a focus on the major roadblocks that limit the widespread adoption of IR photonics in large-scale medical diagnostics. Special attention is given to the ambivalence between the molecular-level spectroscopic interpretation and a broader health-state assessment, highlighting the need for a common framework. Additionally, the paper discusses the critical importance of unified measurement standards, calibration protocols, and medical certification processes to ensure the validity of experimental results, reproducibility, and clinical trust, particularly when novel experimental techniques and AI algorithms are involved. Perspectives from major past and current contributors to application-oriented IR photonics will be provided.
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All authors Borislav Hinkov, Johannes Kunsch, Werner Mäntele, Lukasz Sterczewski, Ángel Sánchez-Illana, Jaume Béjar-Grimalt, Víctor Navarro-Esteve, David Perez-Guaita, Alexander Mittelstädt, Philippa Clark, Valentino Lepro, Sergius Janik, Thorsten Lubinski, Luis Felipe das Chagas e Silva de Carvalho, Hugh James Byrne, Filiz Korkmaz, Michael Kaluza, Mattia Saita, Lars Melchior, Alicja Dabrowska, Georg Ramer, Bernhard Lendl, Nathalie Woitzik, Klaus Gerwert, Peter Gardner, Hugues Tariel, Olivier Sire, Margaux Petay, Elisabeth Holub, Markus Brandstetter, Kristina Duswald, Verena Karl, Florian Meirer, Lukas Kenner, Gabriela Flores Rangel, Boris Mizaikoff, Mohamed Sy, Aamir Farooq, Liudmila Voronina, Marinus Huber, Tarek Eissa, Katharina Dietmann, Lorenzo Gatto, Mihaela Žigman, Joseph Rebel, Frank Fleischmann, Jakub Mnich, Jarosław Sotor, Bassam Saadany, Matthias Budden, Thomas Gebert, Marco Schossig, Shankar Baliga, Timothy Olsen, Christopher Harrower, Ivan Zorin, Chiara Lindner, Shigeki Takeuchi, Sven Ramelow, Paul Gattinger, David Stark, Réka-Eszter Vass, Killian Keller, Alessio Cargioli, Mattias Beck, Jérôme Faist, Robert Weih, Josephine Nauschütz, Julian Scheuermann, Jordan Fordyce, Johannes Koeth, Ka Fai Mak, Alexander Weigel, Ryszard Piramidowicz, Stanisław Stopiński, Mircea Guina, Jukka Viheriälä, Felix Jaeschke, Polina Fomina, Alexander Novikov, Viacheslav Artyushenko, Ivan Sinev, Nikita Glebov, Berkay Dagli, Hatice Altug

Physics Education

Relating visual attention and learning in an online instructional physics module

Razan Hamed, N. Sanjay Rebello and Jeremy Munsell

Learning using Computer-Assisted Instruction (CAI) demands a high level of attention given the tendency to be distracted and mind-wander. How does the online STEM instructor know when learners are having attentional problems and the extent to which these problems affect learning? In the present study, the visual attentional and cognitive state of physics graduate students were probed while they went through a multimedia instructional module to refresh their knowledge of Newton's II Law. Data from an eye tracker, webcam, egocentric glasses, screen recording, and mouse and keyboard events were integrated to record learners' attention overt attention to the learning environment (+/-) and thinking about learning content (+/-) to analyze students' attention spans during learning from this module. On average, learners were found to be on-task and on-screen for a vast majority of time, with evidence of mind wandering. The learning module improved the participants efficiency with which they answered the questions correctly on a post-test relative to the pre-test. Further, there is a positive albeit statistically non-significant correlation between the improvement from pre- to post-test efficiency and the time spent on-screen and on-task during the module.
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Fluid Dynamics · Cross-listed from cond-mat.soft

Constitutive flow law for hydrogel granular rafts near the brittle-ductile transition

Yuto Sasaki and Hiroaki Katsuragi

Spatially varying flow laws have been identified in dry granular flow, yet their applicability to unjammed suspensions remains unclear. This study demonstrates that the quasistatic suspension flow combines dry granular rheology with nonlocal effects in the shear band and damped viscous flow in the outer creep region. Through rotary shear experiments on a hydrogel granular raft, we observe that the flow decays from the interface in the quasistatic regime, where the particles remain mobile even below the yield stress. These findings suggest the universal flow law across the transition between jammed/brittle granular behavior and unjammed/ductile viscous flow.
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Optics

Amplified up-conversion of electromagnetic waves using time-varying metasurfaces

Fedor Kovalev, Stanislav Maslovski, Abdelghafour Abraray et al. (+1 more)

Time-varying metamaterials and photonic time crystals offer a powerful route to wave amplification through temporal modulation of material parameters. Here, we experimentally demonstrate amplified up-conversion of free-space electromagnetic waves in the microwave regime using a time-varying metasurface composed of varactor-loaded coupled split-ring resonators. The metasurface supports a cascaded parametric process in which temporal modulation enhances the resonant response near the signal frequency and subsequently enables efficient radiation at higher sum-frequency components. Direct measurements in degenerate and non-degenerate regimes show amplified up-conversion exceeding the single-step conversion estimate based on the Manley-Rowe frequency ratio. These results establish time-varying metasurfaces as an efficient platform for amplification, generation, and frequency conversion of electromagnetic waves in the microwave and terahertz bands, with potential extension to higher frequencies using ultrafast modulation mechanisms.
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All authors Fedor Kovalev, Stanislav Maslovski, Abdelghafour Abraray, Ilya Shadrivov

Popular Physics · Cross-listed from q-bio.PE

The Great Filter hypothesis – a new Great Filter?

Darren J. Dougan

The Great Filter hypothesis is an extension of the Fermi Paradox: "If life is so common in the universe, why don't we see it?" The Great Filter theory posits there are multiple obstacles or filters life must pass through which ultimately sifts out intelligent life. This paper identifies a new filter: depopulation. As an exospecies advances and reaches the top of the food chain on its planet, Darwinian evolution selects the species to breed fewer offspring due to a lack of predation. As the species evolves intelligence, this leads to medicines and most notably contraception, enabling the species to reduce infant mortality while controlling reproduction. Finally, economic, social and educational factors add to the conscious decision of the intelligent life to slow reproduction. These factors are currently contributing to a human global population peak mid century with subsequent population collapse in less than 500 years. Noting that population growth and decline is exponential, our modelling forecasts human extinction thresholds being tested sometime after the year 2500. There is no reason to assume depopulation dynamics (exodepopulation) would not apply to exocivilizations (exodemography), thus providing a possible resolution of the Fermi Paradox. Furthermore, as machines and AI inevitably supplement humans as depopulation accelerates, the Fermi Paradox can be restated as "Why don't we see machines and AI colonising the galaxy?" A plausible answer is machines will not become conscious and will continue to operate only as tools, tools that will cease operating once humanity is extinct. The Fermi Paradox can then be restated as "Machines will not become conscious, otherwise we would see them colonising the galaxy".
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Sunday 8 February

General Physics

Cosmological Bounce Relics: Black Holes, Gravitational Waves, and Dark Matter

Enrique Gaztanaga

We propose a new mechanism for generating cosmological relics – black holes, gravitational waves (GWs), and possibly dark matter (DM) – in a bouncing Universe. Relics arise through two channels: (i) compact objects and GWs produced during pre-bounce collapse that remain super-horizon and re-enter after the bounce, and (ii) dark-matter halos formed during collapse that exit the horizon and collapse into black holes upon re-entry. Unlike inflationary primordial black holes, these relic black holes originate from nonlinear structure formation during collapse. We derive the particle horizon and horizon-crossing conditions in bouncing cosmology and show that perturbations or compact objects larger than 90 m survive the bounce. The resulting population of relic black holes and GWs spans a wide mass range, offering a unified origin for dark matter, gravitational-wave backgrounds, and the early growth of supermassive black holes and galaxies.
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Fluid Dynamics

Collective and nonlinear structure of wind power correlations

Samy E. Lakhal, J. E. Sardonia and M. M. Bandi

We describe the correlation structure of wind power fluctuations in a farm of 80 turbines, sampled over 5 years. We report the presence of universal, collective, and nonlinear correlations, responsible for the excess persistency and intermittency of farm-aggregated power output. A first cross-correlation analysis of turbine production reveals a dynamical scaling transition (à la Family-Vicszek) from local decoherence to large-scale turbulence-driven scaling, and responsible for the geographical smoothing effect, previously reported beyond farm scale [M. M. Bandi, Phys. Rev. Lett. 118, 028301 (2017)]. A second bivariate analysis shows the long-range correlation of non-Gaussian features, responsible for their amplification in total farm output. These findings provide a new perspective on wind power variability, highlighting the importance of nonlinear correlations in power production dynamics. By better characterising these fluctuations, our results can inform strategies for grid management, storage optimization, and wind farm design, ultimately improving the integration of wind energy into modern power systems.
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Physics and Society

Effect of Electoral Seat Bias on Political Polarization: A Computational Perspective

Daria Boratyn and Dariusz Stolicki

Research on the causes of political polarization points towards multiple drivers of the problem, from social and psychological to economic and technological. However, political institutions stand out, because – while capable of exacerbating or alleviating polarization – they can be re-engineered more readily than others. Accordingly, we analyze one class of such institutions – electoral systems – investigating whether the large-party seat bias found in many common systems (particularly plurality and Jefferson-D'Hondt) exacerbates polarization. Cross-national empirical data being relatively sparse and heavily confounded, we use computational methods: an agent-based Monte Carlo simulation. We model voter behavior over multiple electoral cycles, building upon the classic spatial model, but incorporating other known voter behavior patterns, such as the bandwagon effect, strategic voting, preference updating, retrospective voting, and the thermostatic effect. We confirm our hypothesis that electoral systems with a stronger large-party bias exhibit significantly higher polarization, as measured by the Mehlhaff index.
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Chemical Physics · Cross-listed from quant-ph

Spinor Double-Quantum Excitation in the Solution NMR of Near-Equivalent Spin-1/2 Pairs

Urvashi D. Heramun, Mohamed Sabba, Dolnapa Yamano et al. (+5 more)

A family of double-quantum excitation schemes is described for the solution nuclear magnetic resonance (NMR) of near-equivalent spin-1/2 pairs. These new methods exploit the spinor behaviour of 2-level systems, whose signature is the change of sign of a quantum state upon a $2\pi$ rotation. The spinor behaviour is used to manipulate the phases of single-quantum coherences, in order to prepare a double-quantum precursor state which is rapidly converted into double-quantum coherence by a straightforward $\pi/2$ rotation. One set of spinor-based methods exploits symmetry-based pulse sequences, while the other set exploits SLIC (spin-lock-induced crossing), in which the nutation frequency under a resonant radiofrequency field is matched to the spin-spin coupling. A variant of SLIC is introduced which is well-compensated for deviations in the radiofrequency field amplitude. The methods are demonstrated by performing double-quantum-filtered $^{19}$F NMR on a molecular system containing a pair of diastereotopic $^{19}$F nuclei. The new methods are compared with existing techniques.
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All authors Urvashi D. Heramun, Mohamed Sabba, Dolnapa Yamano, Christian Bengs, Bonifac Legrady, Giuseppe Pileio, Sam Thompson, Malcolm H. Levitt

Optics

Brillouin Spectroscopy Reveals Mechanical Properties Beyond Hydration

Zhe Wang, Maria Regato Herbella, Fereydoon Taheri et al. (+3 more)

Brillouin light scattering is a noncontact technique for probing the micromechanical properties of cells and tissues through the GHz-frequency longitudinal modulus. Interpreting Brillouin spectra in hydrated biological materials remains challenging because the Brillouin shift is influenced not only by water content but also by polymer network mechanics, relaxation processes, and viscous dissipation. Here, we investigated two model hydrogels with distinct network chemistry, together with a binary solvent mixture, to disentangle these contributions. Time- and space-resolved measurements of a hydrating hydrogel further show that Brillouin microscopy captures local mechanical changes that bulk rheometry only partially resolves. Experiments on ethanol-water mixtures further demonstrate that the Brillouin shift does not vary monotonically with hydration but instead reflects changes in the mixture's mechanical properties. In addition, by comparing longitudinal, bulk, and shear viscosities, we identify bulk viscous dissipation as an important contributor to the Brillouin response. Together, these results show that hydration modulates Brillouin spectra but does not fully determine them. Our findings provide a mechanical framework for interpreting Brillouin measurements in hydrated and biomolecular systems.
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All authors Zhe Wang, Maria Regato Herbella, Fereydoon Taheri, Maria de los Angeles De la Cruz Garcia, Gaurav Dave, Christine Selhuber-Unkel

General Physics

Bouncing cosmology, $F(T)$ teleparallel gravity and entropy of apparent horizon

S. I. Kruglov

Two parameters scale factor leading to bouncing cosmology is considered. We show that at some model parameters we obtain the deceleration parameter $q_0\approx -0.535$ at the current epoch which is in agreement with the Planck data. The equation for the transition point when the universe expands from acceleration to deceleration phases is obtained. We find the equation for the function $F(T)$ within the teleparallel gravity with torsion field $T$ which provides bouncing cosmology. For some parameters of the model the function $F(T)$ was computed. At the same time, in the framework of entropic cosmology, the associated entropy was obtained for particular model parameters. The equation of state for dark energy was obtained.
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Physics Education

Student sensemaking on electrostatics problems involving the method of images through the lens of epistemic game framework

Jaya Shivangani Kashyap and Chandralekha Singh

Understanding the mechanisms of student sensemaking while navigating the physics problem-solving process can play an important role in developing approaches to helping students become proficient problem solvers. Since most prior studies on student sensemaking in physics have focused on introductory physics, this study sheds light on a relatively unexplored research area involving the sensemaking of advanced physics students. We conducted individual interviews with graduate students to investigate their sensemaking while solving upper-level undergraduate electrostatics problems in the context of the method of images. Analysis through the lens of the epistemic game framework proposed by Tuminaro and Redish shows that the central part of student sensemaking can be mapped on to the Pictorial Analysis game with other epistemic games also playing a role, but the ontological components of some games require refinement. The study involves an in-depth comparison of sensemaking on related but distinct problems for individual graduate students and comparison between multiple students solving the same problems. It provides insights into how graduate students transfer and translate strategies between different problems while sensemaking. Graduate students showed persistence in activating different knowledge resources and consistent use of reasoning primitives across different problems sensemaking. The study investigated the impact of small nudging and scaffolding that resulted in significant improvements in the problem-solving approaches of graduate students. Another novel finding is that problem-solving approaches of graduate students significantly improved with successive attempts and multiple drawings for the same problem and across problems.
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Data Analysis and Statistics · Cross-listed from quant-ph

An efficient method for spot-checking quantum properties with sequential trials

Yanbao Zhang, Akshay Seshadri and Emanuel Knill

In practical situations, the reliability of quantum resources can be compromised due to complex generation processes or adversarial manipulations during transmission. Consequently, the trials generated sequentially in an experiment may exhibit non-independent and non-identically distributed (non-i.i.d.) behavior. This non-i.i.d. behavior can introduce security concerns and result in faulty estimates when performing information tasks such as quantum key distribution, self-testing, verifiable quantum computation, and resource allocation in quantum networks. To certify the performance of such tasks, one can make a random decision in each trial, either spot-checking some desired property or utilizing the quantum resource for the given task. However, a general method for certification with a sequence of non-i.i.d. spot-checking trials is still missing. Here, we develop such a method. This method not only works efficiently with a finite number of trials but also yields asymptotically tight certificates of performance. Our analysis shows that even as the total number of trials approaches infinity, only a constant number of trials needs to be spot-checked on average to certify the average performance of the remaining trials at a specified confidence level.
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Data Analysis and Statistics · Cross-listed from cs.LG

Mutual information and task-relevant latent dimensionality

Paarth Gulati, Eslam Abdelaleem, Audrey Sederberg et al. (+1 more)

Estimating the dimensionality of the latent representation needed for prediction – the task-relevant dimension – is a difficult, largely unsolved problem with broad scientific applications. We cast it as an Information Bottleneck question: what embedding bottleneck dimension is sufficient to compress predictor and predicted views while preserving their mutual information (MI). This repurposes neural MI estimators for dimensionality estimation. We show that standard neural estimators with separable/bilinear critics systematically inflate the inferred dimension, and we address this by introducing a hybrid critic that retains an explicit dimensional bottleneck while allowing flexible nonlinear cross-view interactions, thereby preserving the latent geometry. We further propose a one-shot protocol that reads off the effective dimension from a single over-parameterized hybrid model, without sweeping over bottleneck sizes. We validate the approach on synthetic problems with known task-relevant dimension. We extend the approach to intrinsic dimensionality by constructing paired views of a single dataset, enabling comparison with classical geometric dimension estimators. In noisy regimes where those estimators degrade, our approach remains reliable. Finally, we demonstrate the utility of the method on multiple physics datasets.
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All authors Paarth Gulati, Eslam Abdelaleem, Audrey Sederberg, Ilya Nemenman

Physics and Society

Large language models for spreading dynamics in complex systems

Shuyu Jiang, Hao Ren, Yichang Gao et al. (+6 more)

Spreading dynamics is a central topic in the physics of complex systems and network science, providing a unified framework for understanding how information, behaviors, and diseases propagate through interactions among system units. In many propagation contexts, spreading processes are influenced by multiple interacting factors, such as information expression patterns, cultural contexts, living environments, cognitive preferences, and public policies, which are difficult to incorporate directly into classical modeling frameworks. Recently, large language models (LLMs) have exhibited strong capabilities in natural language understanding, reasoning, and generation, enabling explicit perception of semantic content and contextual cues in spreading processes, thereby supporting the analysis of the different influencing factors. Beyond serving as external analytical tools, LLMs can also act as interactive agents embedded in propagation systems, potentially influencing spreading pathways and feedback structures. Consequently, the roles and impacts of LLMs on spreading dynamics have become an active and rapidly growing research area across multiple research disciplines. This review provides a comprehensive overview of recent advances in applying LLMs to the study of spreading dynamics across two representative domains: digital epidemics, such as misinformation and rumors, and biological epidemics, including infectious disease outbreaks. We first examine the foundations of epidemic modeling from a complex-systems perspective and discuss how LLM-based approaches relate to traditional frameworks. We then systematically review recent studies from three key perspectives, which are epidemic modeling, epidemic detection and surveillance, and epidemic prediction and management, to clarify how LLMs enhance these areas. Finally, open challenges and potential research directions are discussed.
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All authors Shuyu Jiang, Hao Ren, Yichang Gao, Yi-Cheng Zhang, Li Qi, Dayong Xiao, Jie Fan, Rui Tang, Wei Wang

Data Analysis and Statistics · Cross-listed from astro-ph.IM

DerivKit: stable numerical derivatives bridging Fisher forecasts and MCMC

Nikolina Šarčević, Matthijs van der Wild and Cynthia Trendafilova

DerivKit is a Python package for derivative-based statistical inference. It implements stable numerical differentiation and derivative assembly utilities for Fisher-matrix forecasting and higher-order likelihood approximations in scientific applications, supporting scalar- and vector-valued models including black-box or tabulated functions where automatic differentiation is impractical or unavailable. These derivatives are used to construct Fisher forecasts, Fisher bias estimates, and non-Gaussian likelihood expansions based on the Derivative Approximation for Likelihoods (DALI). By extending derivative-based inference beyond the Gaussian approximation, DerivKit forms a practical bridge between fast Fisher forecasts and more computationally intensive sampling-based methods such as Markov chain Monte Carlo (MCMC).
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Applied Physics

Spatially and Temporally Resolved Mapping of Contact Electrification on Stand-Alone Ultrathin Glass Materials via Kelvin Probe Force Microscopy

Aayush Nayyar, Ruizhe Yang, Vashin Gautham et al. (+7 more)

Contact electrification (CE) remains a critical challenge in advanced material technologies where uncontrolled surface charging can compromise manufacturability, reliability, and performance in practical applications. Ultrathin glass with micrometer-scale thickness is a state-of-the-art specialty oxide material for flexible touchscreens in next-generation electronic devices. Here, we visualize and quantify CE-induced surface charges on ultrathin glass using sideband-mode Kelvin probe force microscopy (KPFM). Nanoscale atomic force microscopy (AFM) probes are used to scan and induce triboelectric charges on stand-alone glass surfaces under ultra-pure N$_2$ conditions. Time-dependent measurements reveal that surface charges on a 30~$\mu$m-thick glass sample decay from 4.47~V to 0.37~V over 240~minutes. Furthermore, electrostatic charges are found to exhibit capacitor-like discharging behavior primarily through the bulk material, yielding a long relaxation time constant of approximately 41~minutes. This behavior differs from the lateral surface discharging observed in thermally grown SiO$2$ thin films reported previously. A self-capacitance analytical model is developed to estimate the corresponding surface charge density ($\sigma$), yielding comparable values of 136.26~$\pm$~16.25~$\mu$C/m$^2$ at 30~$\mu$m and 131.44~$\pm$~28.41~$\mu$C/m$^2$ at 100~$\mu$m. Additionally, external bias applied to AFM tips can be used to enhance, suppress, or invert the intrinsic CE response of glass materials.
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All authors Aayush Nayyar, Ruizhe Yang, Vashin Gautham, Sagnik Das, Haiqing Lin, Andrew C. Antony, Dean Thelen, Mayukh Nath, Gabriel Agnello, Jun Liu

Fluid Dynamics

A Wind Turbine Efficiency Limit Higher than the Lanchester (Betz) Limit

Thad S. Morton

A generalized actuator-disk analysis is developed that retains both the axial and tangential velocity components of the flow through the blade passage. Unlike the classical one-dimensional formulation, the present theory distinguishes between the flow immediately upstream and downstream of the rotor, accounts explicitly for the rotation imparted to the flow, and derives turbine performance from the coupled conservation of mass, linear momentum, angular momentum, and energy. Optimization of the resulting power coefficient reveals two distinct solution branches. At lower blade-speed ratios, the optimum lies on the constraint curve defined by recovery of the velocity magnitude at the rotor-exit plane to the freestream value. Above a critical blade-speed ratio, however, the optimum leaves this constraint boundary and follows a second branch characterized by an exit speed below the freestream value. The transition between these branches is obtained analytically as the intersection of the unconstrained optimum and the boundary-constrained optimum, yielding a quartic equation whose physically admissible root determines the transition point. The optimized solutions predict power coefficients that exceed the classical Betz limit (reaching 78% at its peak) while remaining fully consistent with the governing conservation laws. The analysis shows that the classical efficiency limit is a consequence of the one-dimensional flow assumption rather than a fundamental upper limit imposed by the governing conservation laws.
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Atmospheric and Oceanic Physics · Cross-listed from cond-mat.stat-mech

Linear Response and Optimal Fingerprinting for Nonautonomous Systems

Valerio Lucarini

We provide a link between response theory, pullback measures, and optimal fingerprinting method that paves the way for a) predicting the impact of acting forcings on time-dependent systems and b) attributing observed anomalies to acting forcings when the reference state is not time-independent. We derive formulas for linear response theory for time-dependent Markov chains and diffusion processes. We discuss existence, uniqueness, and differentiability of the equivariant measure under general (not necessarily slow or periodic) perturbations of the transition kernels. Our results allow for extending the theory of optimal fingerprinting for detection and attribution of climate change (or change in any complex system) when the background state is time-dependent amd when the optimal solution is sought for multiple time slices at the same time. We provide numerical support for the findings by applying our theory to a modified version of the Ghil-Sellers energy balance model. We verify the precision of response theory - even in a coarse-grained setting - in predicting the impact of increasing CO$_2$ concentration on the temperature field. Additionally, we show that the optimal fingerprinting method developed here is capable to attribute the climate change signal to multiple acting forcings across a vast time horizon.
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Optics

Topological photonics in one-dimensional settings

Shiqi Xia, Ziteng Wang, Domenico Bongiovanni et al. (+7 more)

Over the past decade, topological photonics has emerged as a vibrant field, attracting significant attention and witnessing remarkable advancements. This growth can be attributed to its fundamental appeal and the unique opportunities it offers for unconventional control of light, promising innovations in next-generation photonic devices. At the heart of topological photonics lies the one-dimensional (1D) SSH model. Originally conceived to elucidate the physics of a molecular chain of polyacetylene, this model has found widespread applications in exploring a wide range of topological phenomena in photonics and beyond. In this chapter, we aim to provide an overview of topological photonics in one-dimensional (1D) settings. After briefly introducing paradigmatic 1D models, including the SSH, Rice-Mele, and AAH models, we review recent advances in experimental studies and applications of topological photonics based on 1D platforms. Our discussion highlights demonstrated examples, such as the nonlinear tuning of topological states in both Hermitian and non-Hermitian photonic SSH lattices, as well as nonlinear harmonic generation and topological lasing in SSH-type photonic microstructures. We further discuss characteristic topological phenomena in other representative 1D settings, including Floquet systems, topological pumping, quasicrystals, and synthetic non-Hermitian systems. Finally, we examine selected examples of two-dimensional (2D) photonic topological crystalline insulators that are closely linked to the SSH model. Towards the end, we summarize the chapter and provide a list of key contributions, together with an outlook on possible future directions in 1D topological photonics. While this review focuses specifically on 1D topological photonics, it is not intended to be comprehensive or exhaustive.
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All authors Shiqi Xia, Ziteng Wang, Domenico Bongiovanni, Dario Jukić, Daohong Song, Liqin Tang, Jingjun Xu, Roberto Morandotti, Hrvoje Buljan, Zhigang Chen

Optics · Cross-listed from quant-ph

Full Schmidt characterization of spatiotemporally entangled states produced from spontaneous parametric down-conversion

Rakesh Pradhan and Girish Kulkarni

The full Schmidt decomposition of spatiotemporally entangled states generated from spontaneous parametric down-conversion (SPDC) has not been carried out until now due to the immense computational complexity arising from the large dimensionalities of the states. In this Letter, we utilize the rotational symmetry of the states to reduce the complexity by at least four orders of magnitude and carry out the decomposition to reveal the precise forms of the spatiotemporal Schmidt modes and the Schmidt spectrum spanning over 10^4 modes. We show that the Schmidt modes have a phase profile with a transverse spatial vortex structure that endows them with orbital angular momentum at all frequencies. In the high-gain regime, these Schmidt modes broaden and the Schmidt spectrum narrows with increasing pump strength. Our work can spur novel applications at the intersection of quantum imaging and spectroscopy that utilize entangled states produced from SPDC.
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Computational Physics

dewi-kadita: A Python Library for Idealized Fish Schooling Simulation with Entropy-Based Diagnostics

Sandy H. S. Herho, Iwan P. Anwar, Faruq Khadami et al. (+5 more)

Collective motion in fish schools exemplifies emergent self-organization in active matter systems, yet computational tools for simulating and analyzing these dynamics remain fragmented across research groups. We present dewi-kadita, an open-source Python library implementing the three-dimensional Couzin zone-based model with comprehensive entropy diagnostics tailored for marine collective behavior research. The library introduces seven information-theoretic metrics – school cohesion entropy, polarization entropy, depth stratification entropy, angular momentum entropy, nearest-neighbor entropy, velocity correlation entropy, and school shape entropy – that characterize distinct organizational features inaccessible to classical order parameters. These metrics combine into an Oceanic Schooling Index (OSI) providing a single scalar measure of collective disorder. Validation across four canonical configurations (swarm, torus, dynamic parallel, highly parallel) confirms correct reproduction of known phase behaviors: the swarm maintains disorder with polarization $P < 0.1$ and OSI $\approx 0.71$, while the highly parallel state achieves $P = 0.998$ with OSI $= 0.24$ and velocity correlation entropy vanishing to zero. The entropy framework successfully discriminates the torus and dynamic parallel configurations that exhibit comparable order parameter magnitudes through different organizational mechanisms. Numba just-in-time (JIT) compilation accelerates pairwise interaction calculations by $10$–$100\times$, enabling simulations of $150$–$250$ agents over $1000$–$2000$ time steps within five minutes on standard workstation hardware. NetCDF4 output ensures interoperability with oceanographic analysis tools. The library addresses the need for standardized, reproducible infrastructure in collective behavior modeling analogous to established molecular dynamics codes.
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All authors Sandy H. S. Herho, Iwan P. Anwar, Faruq Khadami, Alfita P. Handayani, Karina A. Sujatmiko, Kamaluddin Kasim, Rusmawan Suwarman, Dasapta E. Irawan

Computational Physics · Cross-listed from math.NA

A quantum-inspired multi-level tensor-train monolithic space-time method for nonlinear PDEs

N. R. Rapaka, R. Peddinti, E. Tiunov et al. (+5 more)

We propose a multilevel tensor-train (TT) framework for solving nonlinear partial differential equations (PDEs) in a global space-time formulation. While space-time TT solvers have demonstrated significant potential for compressed high-dimensional simulations, the literature contains few systematic comparisons with classical time-stepping methods, limited error convergence analyses, and little quantitative assessment of the impact of TT rounding on numerical accuracy. Likewise, existing studies fail to demonstrate performance across a diverse set of PDEs and parameter ranges. In practice, monolithic Newton iterations may stagnate or fail to converge in strongly nonlinear, stiff, or advection-dominated regimes, where poor initial guesses and severely ill-conditioned space-time Jacobians hinder robust convergence. We overcome this limitation by introducing a coarse-to-fine multilevel strategy fully embedded within the TT format. Each level refines both spatial and temporal resolutions while transferring the TT solution through low-rank prolongation operators, providing robust initializations for successive Newton solves. Residuals, Jacobians, and transfer operators are represented directly in TT and solved with the adaptive-rank DMRG algorithm. Numerical experiments for a selection of nonlinear PDEs including Fisher-KPP, viscous Burgers, sine-Gordon, and KdV cover diffusive, convective, and dispersive dynamics, demonstrating that the multilevel TT approach consistently converges where single-level space-time Newton iterations fail. In dynamic, advection-dominated (nonlinear) scenarios, multilevel TT surpasses single-level TT, achieving high accuracy with significantly reduced computational cost, specifically when high-fidelity numerical simulation is required.
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All authors N. R. Rapaka, R. Peddinti, E. Tiunov, N. J. Faraj, A. N. Alkhooori, L. Aolita, Y. Addad, M. K. Riahi

Accelerator Physics

Three-frequency helical undulator as a source of photons in composite twisted states

O.V. Bogdanov, S.V. Bragin, P.O. Kazinski et al. (+1 more)

The properties of radiation from a three-frequency helical undulator are thoroughly investigated. It is shown that such undulators can be employed for generating photons in the so-called composite twisted states – the states that are linear superpositions of modes with definite projections of the total angular momentum, amplitudes, relative phases, and polarizations. We find the explicit expressions and the selection rules for these parameters and establish that they can be governed in a predictable way by adjusting the parameters of the multifrequency helical undulator. In particular, the phases of three arbitrary modes admissible by selection rules in the composite state with definite energy can be made arbitrary by tuning the phases of one-frequency undulators comprising the three-frequency one. By solving Diophantine equations, we obtain simple expressions for the complex amplitude of coherent state of photons emitted by a three-frequency helical undulator and for the average number of radiated twisted photons in the case when the ratios of frequencies of the three-frequency undulator are rational numbers. The development of resonances and the control of composite states of radiated photons are studied numerically confirming the theoretical conclusions.
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All authors O.V. Bogdanov, S.V. Bragin, P.O. Kazinski, V.A. Ryakin

Applied Physics

Physics Guided Exponential Model Design of High Ge Content SiGe Selective Epitaxy for Gate All Around Source/Drain Applications

Zhigang Li, Guobin Bai, Hengwei Cui et al. (+9 more)

High germanium content silicon germanium (SiGe) epitaxy is critical for strain engineering in advanced gate all around (GAA) transistors. This paper demonstrates a physics guided exponential function model that quantitatively links selective epitaxial growth (SEG) parameters to Ge incorporation kinetics in nanoscale trenches. By coupling surface diffusion limited transport, gradient strain, and competitive adsorption dynamics, the model predicts optimal conditions for bottom-up filling with maximal Ge content. For trenches with widths of approximately 60 nm, the optimized process achieved a maximum Ge content of 57.93% and demonstrated 100% selectivity against silicon nitride (SiN) and silicon dioxide (SiO). Cross sectional TEM and EDS analyses reveal a graded Ge profile that minimizes interfacial defects and strain energy. Our results show that the established process physics correlation will significantly facilitate the development of GAA devices with 5nm CMOS technology nodes and beyond.
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All authors Zhigang Li, Guobin Bai, Hengwei Cui, Wenlong Yao, Jianfeng Gao, Qifeng Jiang, Junjie Li, Junfeng Li, Yongliang Li, Huaxiang Yin, Xiaolei Wang, Jun Luo