Peer Revenue Impact factor: volatile

Papers

Fresh from arXiv, typeset properly. Highlighted words trade on the market.

Physics Physics

physics Watch Physics

Wednesday 8 October

Physics and Society

Consensus as cooling: a granular gas model for continuous opinions on structured networks

Carlos Uriarte, Pablo Rodriguez-Lopez and Nagi Khalil

A continuous-opinion model accounting for the social compromise propensity is theoretically and numerically analysed. An agent's opinion is represented by a real number that can be changed through social interactions with her neighbours. The proposed dynamics depends on two fundamental parameters, $\alpha\in[-1,1]$ and $\beta\ge 0$. If an interaction takes place between two agents, their relative opinions decreases an amount given by $\alpha$. The probability of two neighbours to interact is proportional to the $\beta$-power of their relative opinions. We unveil the behaviour of the system for all physical relevant values of the parameters and several representative interaction networks. When $\alpha\in(-1,1)$ and $\beta\ge 0$, the system always reaches consensus, with all agents having the mean initial opinion, provided the interaction network is connected. The approach to consensus can be characterized by means of the mean opinion and the temperature (or opinion dispersion) of each agent. Three scenarios have been identified. When the agents are well mixed, as with all-to-all interactions, a pre-consensus regime is seen, with all agents having zero mean opinion and the same temperature, following the Haff's law of granular gases. A similar regime is observed with Erdös-Rényi and Barabási-Albert networks: mean opinions are zero but agents with different degrees have different temperatures, though still following the Haff's law. Finally, the case of a square 2D lattice has been carefully analyzed, by starting from the derivation of closed set of hydrodynamic-like equations using the Chapman-Enskog method ...
Read the full abstract

Fluid Dynamics

CFD analysis of microfluidic droplet formation in non-Newtonian liquid

Somasekhara Goud Sontti and Arnab Atta

A three-dimensional, volume-of-fluid (VOF) based CFD model is presented to investigate droplet formation in a microfluidic T-junction. Genesis of Newtonian droplets in non-Newtonian liquid is numerically studied and characterized in three different regimes, viz., squeezing, dripping and jetting. Various influencing factors such as, continuous and dispersed phase flow rates, interfacial tension, and non-Newtonian rheological parameters are analyzed to understand droplet formation mechanism. Droplet shape is reported by defining a deformation index. Near spherical droplets are realized in dripping and jetting regimes. However, plug shaped droplets are observed in squeezing regime. It is found that rheological parameters have significant effect on the droplet length, volume, and its formation regime. The formation frequency increases with increasing effective viscosity however, the droplet volume decreases. This work effectively provides the fundamental insights into microfluidic droplet formation characteristics in non-Newtonian liquids.
Read the full abstract

Plasma Physics

3D simulations of negative streamers in CO$_2$ with admixtures of C$_4$F$_7$N

Thomas J.G. Smits, Jannis Teunissen and Ute Ebert

CO$_2$ with an admixture of C$_4$F$_7$N could serve as an eco-friendly alternative to the extreme greenhouse gas SF$_6$ in high-voltage insulation. Streamer discharges in such gases are different from those in air due to the rapid conductivity decay in the streamer channels. Furthermore, since no effective photoionisation mechanism is known, we expect discharge growth to be more stochastic than in air. In this paper we investigate whether conventional fluid models can be used to simulate streamers in CO$_2$ with admixtures of C$_4$F$_7$N of 1 or 10%. We focus on 3D simulations of negative streamers. First we review cross section databases for C$_4$F$_7$N and CO$_2$. Then we compare a two-term Boltzmann solver with a Monte Carlo method to compute reaction and transport coefficients from the cross sections. Afterwards we compare 3D fluid simulations with the local field (LFA) or local energy approximation (LEA) against particle simulations. In general, we find that the results of particle and fluid models are quite similar. One difference we observe is that particle simulations are intrinsically stochastic, leading to more branching. Furthermore, the LEA model does not show better agreement with the particle simulations than the LFA model. We also discuss the effect and choice of different boundary conditions on the negative rod electrode.
Read the full abstract

Plasma Physics

Influence of coil geometry and coil-plasma distance on the magnetic field approximation error

Wadim Gerner

We investigate analytically two questions: 1) How does the coil geometry influence the effect of electric current noise on the induced magnetic field? 2) How does the coil-plasma distance influence our ability to control the pointwise magnetic field error in terms of the average magnetic field error? Regarding (1), we argue that the main geometric quantities of interest are the notion of reach and the volume of the region enclosed by the coils. Our main finding is a quantitative formula which shows that the larger the reach and the smaller the volume of the region enclosed by the coils, the smaller is the influence of the electric current uncertainty on the magnetic fields. Regarding (2), we show that the pointwise magnetic field error can be controlled (modulo an explicit constant) by the average square-magnetic field-error times $(\text{coil-plasma distance})^{-\frac{3}{2}}$.
Read the full abstract

Instrumentation and Detectors · Cross-listed from astro-ph.IM

Low-noise Fourier Transform Spectroscopy Enabled by Superconducting On-Chip Filterbank Spectrometers

Chris S. Benson, Peter S. Barry, Patrick Ashworth et al. (+4 more)

Historically employed spectroscopic architectures used for large field of view mapping spectroscopy in millimetere and sub-millimetre astronomy suffer from significant drawbacks. On-chip filterbank spectrometers are a promising technology in this respect; however, they must overcome an orders-of-magnitude increase in detector counts, efficiency loss due to dielectric properties, and stringent fabrication tolerances that currently limit scaling to resolutions of order 1000 over a large array. We propose coupling a medium-resolution Fourier transform spectrometer to a low-resolution filterbank spectrometer focal plane, which serves as a post-dispersion element. In this arrangement, medium resolution imaging spectroscopy is provided by the Fourier transform spectrometer, while the low resolution filterbank spectrometer serves to decrease the photon noise inherent in typical broadband Fourier transform spectrometer measurements by over an order of magnitude. This is achieved while maintaining the excellent imaging advantages of both architectures. We present predicted mapping speeds for a filterbank-dispersed Fourier transform spectrometer from a ground-based site and a balloon-borne platform. We also demonstrate the potential that an instrument of this type has for an R~1000 line intensity mapping experiment using the James Clerk Maxwell Telescope as an example platform. We demonstrate that a filterbank-dispersed Fourier transform spectrometer would be capable of R~1000 measurements of CO power spectra with a signal-to-noise ratio of 10–100 with surveys of $10^5$–$10^6$ spectrometer hours.
Read the full abstract

All authors Chris S. Benson, Peter S. Barry, Patrick Ashworth, Harry Gordon-Moys, Kirit S. Karkare, Izaak Morris, Gethin Robson

Instrumentation and Detectors · Cross-listed from cond-mat.mtrl-sci

Modular Reactor for In Situ X-ray Scattering, Spectroscopy, and ATR-IR Studies of Solvothermal Nanoparticle Synthesis

Sani Y. Harouna-Mayer, Melike Gumus Akcaalan, Jagadesh Kopula Kesavan et al. (+14 more)

Understanding the chemical processes that occur during the solvothermal synthesis of functional nanomaterials is essential for their rational design and optimization for specific applications. However, these processes remain poorly understood, primarily due to the limitations of conventional ex situ characterization techniques and the technical challenges associated with in situ studies, particularly the design and implementation of suitable reactors. Here, we present a versatile cell suitable for in situ X-ray scattering, X-ray spectroscopy, and infrared spectroscopy studies performed during solvothermal synthesis under autoclave-like, inert conditions. The reactor enables precise control of the temperature between -20 C and 200 C, pressures up to 8 bar, magnetic stirring, and injection of gas or liquids. The reactor's capabilities are demonstrated by comprehensively studying the solvothermal synthesis of magnetite nanoparticles from iron acetylacetonate in benzyl alcohol through in situ X-ray scattering and spectroscopy, and ATR-IR spectroscopy.
Read the full abstract

All authors Sani Y. Harouna-Mayer, Melike Gumus Akcaalan, Jagadesh Kopula Kesavan, Tjark R. L. Groene, Lars Klemeyer, Sarah-Alexandra Hussak, Lukas Grote, a Davide Derelli, Francesco Caddeo, Cecilia Zito, Paul Stützle, Dorota Speer, Ann-Christin Dippel, Blanka Detlefs, Yannik Appiarius, Axel Jacobi von Wangelin, Dorota Koziej

Medical Physics

High-speed proton therapy within a short breath-hold

Vivek Maradia, Nick Yue, Adam Molzahn et al. (+4 more)

Proton therapy provides superior dose conformity compared with photon radiotherapy, concentrating radiation within the tumor while sparing adjacent healthy tissue. This advantage has been most effectively realized for static tumors in anatomically stable regions, such as the head and neck. For thoracic and abdominal sites, however, physiological motion remains a critical challenge: because the proton dose distribution is highly sensitive to density variations, long delivery times relative to respiratory motion can compromise accuracy. Existing strategies to accelerate delivery often require substantial hardware modifications or are difficult to translate into routine practice. Here we report an optimization that enables high-speed proton delivery (5 to 10 sec per field) on a commercial synchrocyclotron platform without hardware changes. The method combines high-energy shoot-through beams with Bragg-peak delivery, an optimized nearest-neighbor scanning sequence, and a two-pulse dose regulation scheme. Applied to eight lung cancer cases (target volumes 100 to 1000 cc), the approach achieved full field delivery in under 10 sec compatible with a short breath hold while preserving conformity, dose accuracy, and sparing of organs at risk. This framework provides a practical route to motion robust proton therapy, improving precision, efficiency and patient tolerance. More broadly, it opens a pathway toward widespread clinical adoption of high-speed proton delivery for moving tumors.
Read the full abstract

All authors Vivek Maradia, Nick Yue, Adam Molzahn, Jingqian Wang, Mark Pankuch, Serdar Charyyev, Billy W. Loo Jr

Fluid Dynamics

CFD Analysis of Taylor Bubble in a Co-Flow Microchannel with Newtonian and Non-Newtonian Liquid

Somasekhara Goud Sontti and Arnab Atta

We present a CFD based model to understand the Taylor bubble behavior in Newtonian and non-Newtonian liquids flowing through a confined co-flow microchannel. Systematic investigation is carried out to explore the influence of surface tension, inlet velocities, and apparent viscosity on the bubble length, shape, velocity, and film thickness around the bubble. Aqueous solutions of carboxymethyl cellulose (CMC) with different concentrations are considered as power-law liquid to address the presence of non-Newtonian continuous phase on Taylor bubble. In all cases, bubble length was found to decrease with increasing Capillary number, inlet gas-liquid velocity ratio, and CMC concentration. However, bubble velocity increased due to increasing liquid film thickness around the bubble. At higher Capillary number and inlet velocity ratio, significant changes in bubble shapes are observed. With increasing CMC concentration, bubble formation frequency and velocity increased, but length decreased.
Read the full abstract

Computational Physics · Cross-listed from astro-ph.CO

Benchmarking AI-evolved cosmological structure formation

Xiaofeng Dong, Nesar Ramachandra, Salman Habib et al. (+1 more)

The potential of deep learning-based image-to-image translations has recently attracted significant attention. One possible application of such a framework is as a fast, approximate alternative to cosmological simulations, which would be particularly useful in various contexts, including covariance studies, investigations of systematics, and cosmological parameter inference. To investigate different aspects of learning-based cosmological mappings, we choose two approaches for generating suitable cosmological matter fields as datasets: a simple analytical prescription provided by the Zel'dovich approximation, and a numerical N-body method using the Particle-Mesh approach. The evolution of structure formation is modeled using U-Net, a widely employed convolutional image translation framework. Because of the lack of a controlled methodology, validation of these learned mappings requires multiple benchmarks beyond simple visual comparisons and summary statistics. A comprehensive list of metrics is considered, including higher-order correlation functions, conservation laws, topological indicators, and statistical independence of density fields. We find that the U-Net approach performs well only for some of these physical metrics, and accuracy is worse at increasingly smaller scales, where the dynamic range in density is large. By introducing a custom density-weighted loss function during training, we demonstrate a significant improvement in the U-Net results at smaller scales. This study provides an example of how a family of physically motivated benchmarks can, in turn, be used to fine-tune optimization schemes – such as the density-weighted loss used here – to significantly enhance the accuracy of scientific machine learning approaches by focusing attention on relevant features.
Read the full abstract

All authors Xiaofeng Dong, Nesar Ramachandra, Salman Habib, Katrin Heitmann

Chemical Physics · Cross-listed from cond-mat.soft

SAOS and LAOS rheology for differentiating chemical and physical crosslinking: A case study on PVA hydrogels

David Kogan and Moshe Gottlieb

In this work, we have studied the viscoelastic behavior of chemically and physically crosslinked Poly(vinyl alcohol) (PVA) hydrogels near the critical gel point (GP) as well as further away from it, by means of small amplitude (SAOS) and large amplitude (LAOS) oscillatory shear experiments. Chemical crosslinking involved covalent bonding by means of glutaraldehyde as a crosslinker, while physical crosslinking was induced by freeze-thaw cycles. SAOS data analysis allowed evaluation of critical parameters such as the critical relaxation exponent n, gel strength S, and equilibrium modulus Ge, based on the dynamic self-similarity and fractal network structures at the GP. LAOS rheological data analysis showed that the chemically crosslinked system exhibited moderate strain-dependance due to the permanent covalent bonds, whereas the physically crosslinked system displayed significant strain-dependent nonlinearity due to strain dependent interactions at the crosslink entities. LAOS experiments, supported by Chebyshev coefficients and Lissajous-Bowditch plots, highlighted pronounced differences in nonlinear responses, underscoring the influence of crosslinking mechanisms on the network rheological behavior. The findings establish LAOS as a powerful tool for differentiating polymeric network structures, providing insights beyond those attained by conventional linear rheology. 50 pages 1 figures
Read the full abstract

Optics

Developing a Cost-Effective Spectrometer: A Practical Approach

Zafrin Jahan Nikita, Mohammad Tahsin Alam, Yasir Mahmud et al. (+4 more)

The paper demonstrates the design and execution of a low-cost optical spectrometer that employs a webcam, diffraction grating & Python (a free, open-source programming language). The device's design prioritized economy and usability, with a black box casing to reduce stray light and increase measurement accuracy. A diffraction grating made from a DVD was used to split light into its constituent wavelengths, which were then collected by the camera. The calibration procedure used a RED TIDE USB650 Fiber Optic Spectrometer to set calibration values for various wavelength ranges, which ensured that the spectrometer's results closely matched those derived from the former, a high-cost industry-standard model. Spectrums of several light sources, such as red, green, blue, yellow, white, magenta, orange, and UV LEDs, as well as a green laser, were studied and compared. The results showed a high level of precision, with minimal divergence from industry-standard spectrometer measurements. This comparison was carried out utilizing Origin software, which allowed for extensive analysis and display of the spectrum data. In addition, the spectrometer captured data in real time, allowing users to watch live spectrum changes and ensure instant accessibility of results. Despite its simplicity and low cost, the spectrometer provides significant value for instructional and practical applications, making it a valuable tool in cost-constrained situations.
Read the full abstract

All authors Zafrin Jahan Nikita, Mohammad Tahsin Alam, Yasir Mahmud, Rafichha Yasmin, Fairuz Darimi Bushra, Sheikh Hasib Cheragee, Redwanul Talukder Zeem

Fluid Dynamics

Elasto-viscous regime in coalescence of viscoelastic droplets

Pallavi Katre, Bimalendu Mahapatra, Manaswita Karmakar et al. (+3 more)

We report a regime transition in the coalescence of concentrated polymeric droplets in a pendant-pendant configuration. While Newtonian droplet coalescence has been extensively studied with distinct identification of viscous and inertial regimes, the presence of polymers introduces additional regimes governed by elasticity and molecular relaxation effects. The coalescence process is typically characterized by the neck radius, $R$, of the liquid bridge connecting the two droplets, following a power-law relation with time: $R=at^{b}$. Most of the existing studies, including Newtonian and non-Newtonian fluids, report a unique value of $b$ for a given fluid. In contrast, our findings reveal that elasticity induces a temporal transition from one $b$ values to another, marking a shift in the coalescence regime. In particular, our measured $b$ value falls in the sub-Newtonian regime, highlighting the role of elasticity in governing the dynamics. We conducted two-dimensional simulations using a volume-of-fluid framework with the exponential Phan-Thien-Tanner model, which quantitatively reproduced Newtonian benchmarks and accurately captured viscoelasticity induced neck growth in close agreement with experiments. Furthermore, we determined the curvature experimentally, as the assumptions typically employed in the literature to approximate axial curvature are not universally valid.
Read the full abstract

All authors Pallavi Katre, Bimalendu Mahapatra, Manaswita Karmakar, Sarang Jagdish, Navin Kumar Chandra, Aloke Kumar

Instrumentation and Detectors

Doping of a Borexino-like Liquid Scintillator with Tellurium-Diols

Hans Th. J. Steiger, Marco Beretta, Manuel Böhles et al. (+8 more)

One promising approach for future neutrinoless double beta decay ($0\nu\beta\beta$) searches is the incorporation of candidate isotopes into liquid scintillator detectors. In this work, a sample of the high-performance 1,2,4-trimethylbenzene-based liquid scintillator used in the Borexino experiment was loaded with different concentrations of Te-diol compounds. To realize the loading, a modified water-free synthesis procedure in a non-acidic organic environment at room temperature was employed. The loaded scintillator mixtures were characterized with respect to their emission spectra, optical absorbance, light yield, and scintillation time profiles under $\alpha$ excitation. Within the experimental uncertainties, only comparatively small changes in the spectral emission shape and optical transmission were observed for Te-loadings up to 2%. At the same time, a systematic reduction of the scintillation light yield with increasing Te concentration was measured. At 1% Te-loading, an estimated light yield of approximately 8400\,photons/MeV$_{\mathrm{ee}}$ was obtained. Furthermore, the scintillation time profile measurements indicate systematically shorter effective decay time constants for increasing Te-loading, consistent with enhanced non-radiative de-excitation processes introduced by the Te-diol complexes. Overall, the results demonstrate that the investigated loading technique can be successfully applied to a pseudocumene-based liquid scintillator while preserving the principal scintillation characteristics of the system.
Read the full abstract

All authors Hans Th. J. Steiger, Marco Beretta, Manuel Böhles, Alberto Garfagnini, Arsenii Gavrikov, Paolo Lombardi, Kai Loo, Elena Pasini, Benedetta Rasera, Andrea Serafini, Michael Wurm

Optics

A laser with instability reaching $4 \times 10^{-17}$ based on a 10-cm-long silicon cavity at sub-5-K temperatures

Zhi-Ang Chen, Hao-Ran Zeng, Wen-Wei Wang et al. (+6 more)

The realization of ultra-stable lasers with $10^{-17}$-level frequency stability has enabled a wide range of researches on precision metrology and fundamental science, where cryogenic single-crystalline cavities constitute the heart of such ultra-stable lasers. For further improvements in stability, increasing the cavity length at few-kelvin temperatures provides a promising alternative to utilizing relatively short cavities with novel coating, but has yet to be demonstrated with state-of-the-art stability. Here we report on the realization of a relatively long ultra-stable silicon cavity with a length of 10 cm and sub-5-K operating temperatures. We devise a dynamical protocol of cool-quiet quench measurement that reveals the inherent $10^{-17}$-level frequency instability of the silicon cavity despite the substantially larger frequency noise induced by the cryostat vibration. We further develop a method for suppressing the cryostat-vibration-induced frequency noise under continuous cooling, and observe an average frequency instability of $4.3(2) \times 10^{-17}$ for averaging times of 4 to 12 seconds. Using the measured noise power spectral density, we compute a median linewidth of 9.6(3) mHz for the silicon cavity laser at 1397 nm, which is supported by an empirically determined linewidth of 5.7(3) mHz based on direct optical beat measurements. These results establish a new record for optical cavities within a closed-cycle cryocooler at sub-5-K temperatures and provide a prototypical system for using long cryogenic cavities to enhance frequency stabilities to the low-$10^{-17}$ or better level.
Read the full abstract

All authors Zhi-Ang Chen, Hao-Ran Zeng, Wen-Wei Wang, Han Zhang, Run-Qi Lei, Jian-Zhang Li, Cai-Yin Pang, She-Song Huang, Xibo Zhang

Fluid Dynamics · Cross-listed from nlin.CD

Ultra-chaotic property of Navier-Stokes turbulence

Shijie Qin, Kun Xu and Shijun Liao

A chaotic system is called ultra-chaos when its statistics have sensitivity dependence on initial condition and/or other small disturbances. In this paper, using two-dimensional turbulent Kolmogorov flow as an example, we illustrate that tiny variation of initial condition of Navier-Stokes equations can lead to huge differences not only in spatiotemporal trajectory but also in flow symmetry and its statistics. Here, in order to avoid the influence of artificial numerical noise, we apply “clean numerical simulation” (CNS) which can guarantee that the numerical noise can be reduced to such a desired low level that they are negligible in a time interval long enough for calculating statistics. This discovery highly suggests that the Navier-Stokes turbulence (i.e. turbulence governed by the Navier-Stokes equations) might be an ultra-chaos, say, small disturbances must be considered even from viewpoint of statistics. This however leads to a paradox in logic, since small disturbances, which are unavoidable in practice, are unfortunately neglected by the Navier-Stokes turbulence. Some fundamental characteristics of turbulence model are discussed and suggested in general meanings.
Read the full abstract

Applied Physics · Cross-listed from cond-mat.mes-hall

Intrinsic ultrafast edge photocurrent dynamics in WTe$_2$ driven by broken crystal symmetry

Subhashri Chatterjee, Katsumasa Yoshioka, Taro Wakamura et al. (+2 more)

Directional photocurrents in two-dimensional materials arise from broken crystal symmetry, offering pathways to high-speed, bias-free photodetection beyond conventional devices. Tungsten ditelluride (WTe$_2$), a type-II Weyl semimetal, exhibits robust symmetry-breaking-induced edge photocurrents from competing nonlinear optical and photothermoelectric mechanisms, whose intrinsic dynamics have remained experimentally inaccessible. Here, we directly resolve sub-picosecond edge photocurrent dynamics in WTe$_2$ through ohmic contacts over temperatures from 300 K to 4 K. We demonstrate ultrafast optical-to-electrical conversion with a 3 dB bandwidth of $\sim$250 GHz and reveal picosecond-timescale switching of the net photocurrent direction below 150 K, linked to a Lifshitz transition. This transient bipolar response arises from non-equilibrium Seebeck effects due to asymmetric cooling of hot electrons and holes. These findings reveal previously hidden ultrafast dynamics in symmetry-engineered materials, offering new strategies to disentangle competing photocurrent mechanisms and enabling the development of self-powered, ultrafast optoelectronic devices.
Read the full abstract

All authors Subhashri Chatterjee, Katsumasa Yoshioka, Taro Wakamura, Vasili Perebeinos, Norio Kumada

Instrumentation and Detectors

Design, waterproofing, and mass production of the 3-inch PMT frontend system of JUNO

Jilei Xu, Miao He, Cédric Cerna et al. (+631 more)

Over 25,600 3-inch photomultiplier tubes (PMTs) have been instrumented for the central detector of the Jiangmen Underground Neutrino Observatory. Each PMT is equipped with a high-voltage divider and a frontend cable with waterproof sealing. Groups of sixteen PMTs are connected to the underwater frontend readout electronics via specialized multi-channel waterproof connectors. This paper outlines the design and mass production processes for the high-voltage divider, the cable and connector, as well as the waterproof potting of the PMT bases. The results of the acceptance tests of all the integrated PMTs are also presented.
Read the full abstract

All authors Jilei Xu, Miao He, Cédric Cerna, Yongbo Huang, Thomas Adam, Shakeel Ahmad, Rizwan Ahmed, Fengpeng An, Costas Andreopoulos, Giuseppe Andronico, João Pedro Athayde Marcondes de André, Nikolay Anfimov, Vito Antonelli, Tatiana Antoshkina, Didier Auguste, Weidong Bai, Nikita Balashov, Andrea Barresi, Davide Basilico, Eric Baussan, Marco Beretta, Antonio Bergnoli, Nikita Bessonov, Daniel Bick, Lukas Bieger, Svetlana Biktemerova, Thilo Birkenfeld, Simon Blyth, Anastasia Bolshakova, Mathieu Bongrand, Matteo Borghesi, Dominique Breton, Augusto Brigatti, Riccardo Brugnera, Riccardo Bruno, Antonio Budano, Jose Busto, Marcel Büchner, Anatael Cabrera, Barbara Caccianiga, Hao Cai, Xiao Cai, Yanke Cai, Zhiyan Cai, Stéphane Callier, Steven Calvez, Antonio Cammi, Chuanya Cao, Guofu Cao, Jun Cao, Yaoqi Cao, Rossella Caruso, Vanessa Cerrone, Jinfan Chang, Yun Chang, Auttakit Chatrabhuti, Chao Chen, Guoming Chen, Jiahui Chen, Jian Chen, Jing Chen, Junyou Chen, Pingping Chen, Shaomin Chen, Shiqiang Chen, Xin Chen, Yiming Chen, Yixue Chen, Yu Chen, Ze Chen, Zhangming Chen, Zhiyuan Chen, Jie Cheng, Yaping Cheng, Yu Chin Cheng, Alexander Chepurnov, Alexey Chetverikov, Davide Chiesa, Pietro Chimenti, Po-Lin Chou, Ziliang Chu, Artem Chukanov, Gérard Claverie, Catia Clementi, Barbara Clerbaux, Claudio Coletta, Simon Csakli, Chenyang Cui, Olivia Dalager, Zhi Deng, Ziyan Deng, Xiaoyu Ding, Xuefeng Ding, Yayun Ding, Bayu Dirgantara, Carsten Dittrich, Sergey Dmitrievsky, David Doerflinger, Dmitry Dolzhikov, Haojie Dong, Jianmeng Dong, Evgeny Doroshkevich, Marcos Dracos, Frédéric Druillole, Ran Du, Shuxian Du, Yujie Duan, Katherine Dugas, Stefano Dusini, Hongyue Duyang, Jessica Eck, Timo Enqvist, Andrea Fabbri, Ulrike Fahrendholz, Lei Fan, Jian Fang, Wenxing Fang, Elia Stanescu Farilla, Dmitry Fedoseev, Li-Cheng Feng, Qichun Feng, Federico Ferraro, Daniela Fetzer, Marcellin Fotzé, Amélie Fournier, Aaron Freegard, Feng Gao, Alberto Garfagnini, Arsenii Gavrikov, Marco Giammarchi, Nunzio Giudice, Maxim Gonchar, Guanghua Gong, Hui Gong, Yuri Gornushkin, Marco Grassi, Maxim Gromov, Vasily Gromov, Minhao Gu, Xiaofei Gu, Yu Gu, Mengyun Guan, Yuduo Guan, Nunzio Guardone, Rosa Maria Guizzetti, Cong Guo, Wanlei Guo, Caren Hagner, Hechong Han, Ran Han, Yang Han, Vidhya Thara Hariharan, Jinhong He, Wei He, Xinhai He, Ziou He, Tobias Heinz, Patrick Hellmuth, Yuekun Heng, YuenKeung Hor, Shaojing Hou, Yee Hsiung, Bei-Zhen Hu, Hang Hu, Jun Hu, Tao Hu, Yuxiang Hu, Guihong Huang, Hexiang Huang, Jinhao Huang, Junting Huang, Kaixuan Huang, Shengheng Huang, Tao Huang, Xin Huang, Xingtao Huang, Jiaqi Hui, Lei Huo, Cédric Huss, Safeer Hussain, Leonard Imbert, Ara Ioannisian, Adrienne Jacobi, Arshak Jafar, Beatrice Jelmini, Xiangpan Ji, Xiaolu Ji, Huihui Jia, Junji Jia, Cailian Jiang, Wei Jiang, Xiaoshan Jiang, Xiaozhao Jiang, Yijian Jiang, Yixuan Jiang, Xiaoping Jing, Cécile Jollet, Li Kang, Rebin Karaparabil, Narine Kazarian, Ali Khan, Amina Khatun, Khanchai Khosonthongkee, Denis Korablev, Konstantin Kouzakov, Alexey Krasnoperov, Sergey Kuleshov, Sindhujha Kumaran, Nikolay Kutovskiy, Loïc Labit, Tobias Lachenmaier, Haojing Lai, Cecilia Landini, Lorenzo Lastrucci, Sébastien Leblanc, Matthieu Lecocq, Frederic Lefevre, Ruiting Lei, Rupert Leitner, Jason Leung, Demin Li, Fei Li, Fule Li, Gaosong Li, Hongjian Li, Huang Li, Jiajun Li, Min Li, Nan Li, Qingjiang Li, Ruhui Li, Rui Li, Shanfeng Li, Tao Li, Teng Li, Weidong Li, Xiaonan Li, Yi Li, Yichen Li, Yifan Li, Yufeng Li, Zhaohan Li, Zhibing Li, Zi-Ming Li, Zonghai Li, An-An Liang, Jiajun Liao, Minghua Liao, Yilin Liao, Ayut Limphirat, Bo-Chun Lin, Guey-Lin Lin, Shengxin Lin, Tao Lin, Xianhao Lin, Xingyi Lin, Jiajie Ling, Xin Ling, Ivano Lippi, Caimei Liu, Fang Liu, Fengcheng Liu, Haidong Liu, Haotian Liu, Hongbang Liu, Hongjuan Liu, Hongtao Liu, Hongyang Liu, Jianglai Liu, Jiaxi Liu, Jinchang Liu, Kainan Liu, Min Liu, Qian Liu, Runxuan Liu, Shenghui Liu, Shulin Liu, Xiaowei Liu, Xiwen Liu, Xuewei Liu, Yankai Liu, Zhen Liu, Lorenzo Loi, Alexey Lokhov, Paolo Lombardi, Claudio Lombardo, Kai Loo, Selma Conforti Di Lorenzo, Haoqi Lu, Junguang Lu, Meishu Lu, Shuxiang Lu, Xianguo Lu, Bayarto Lubsandorzhiev, Sultim Lubsandorzhiev, Livia Ludhova, Arslan Lukanov, Fengjiao Luo, Guang Luo, Jianyi Luo, Shu Luo, Wuming Luo, Xiaojie Luo, Vladimir Lyashuk, Bangzheng Ma, Bing Ma, Qiumei Ma, Si Ma, Wing Yan Ma, Xiaoyan Ma, Xubo Ma, Jihane Maalmi, Jingyu Mai, Marco Malabarba, Yury Malyshkin, Roberto Carlos Mandujano, Fabio Mantovani, Xin Mao, Stefano M. Mari, Agnese Martini, Matthias Mayer, Davit Mayilyan, Yue Meng, Anselmo Meregaglia, Lino Miramonti, Marta Colomer Molla, Michele Montuschi, Iwan Morton-Blake, Massimiliano Nastasi, Dmitry V. Naumov, Elena Naumova, Igor Nemchenok, Elisabeth Neuerburg, Alexey Nikolaev, Feipeng Ning, Zhe Ning, Yujie Niu, Hiroshi Nunokawa, Lothar Oberauer, Juan Pedro Ochoa-Ricoux, Sebastian Olivares, Alexander Olshevskiy, Domizia Orestano, Fausto Ortica, Rainer Othegraven, Yifei Pan, Alessandro Paoloni, George Parker, Yatian Pei, Luca Pelicci, Anguo Peng, Yu Peng, Zhaoyuan Peng, Elisa Percalli, Willy Perrin, Frédéric Perrot, Pierre-Alexandre Petitjean, Fabrizio Petrucci, Oliver Pilarczyk, Artyom Popov, Pascal Poussot, Ezio Previtali, Fazhi Qi, Ming Qi, Xiaohui Qi, Sen Qian, Xiaohui Qian, Zhonghua Qin, Shoukang Qiu, Manhao Qu, Zhenning Qu, Gioacchino Ranucci, Thomas Raymond, Alessandra Re, Abdel Rebii, Mariia Redchuk, Bin Ren, Yuhan Ren, Cristobal Morales Reveco, Barbara Ricci, Komkrit Rientong, Mariam Rifai, Mathieu Roche, Narongkiat Rodphai, Fernanda de Faria Rodrigues, Aldo Romani, Bedřich Roskovec, Arseniy Rybnikov, Andrey Sadovsky, Paolo Saggese, Deshan Sandanayake, Anut Sangka, Ujwal Santhosh, Giuseppe Sava, Utane Sawangwit, Michaela Schever, Cédric Schwab, Konstantin Schweizer, Alexandr Selyunin, Andrea Serafini, Mariangela Settimo, Junyu Shao, Vladislav Sharov, Hangyu Shi, Hexi Shi, Jingyan Shi, Yanan Shi, Vitaly Shutov, Andrey Sidorenkov, Apeksha Singhal, Chiara Sirignano, Jaruchit Siripak, Monica Sisti, Mikhail Smirnov, Oleg Smirnov, Thiago Sogo-Bezerra, Sergey Sokolov, Julanan Songwadhana, Boonrucksar Soonthornthum, Albert Sotnikov, Warintorn Sreethawong, Achim Stahl, Luca Stanco, Konstantin Stankevich, Hans Steiger, Jochen Steinmann, Tobias Sterr, Matthias Raphael Stock, Virginia Strati, Mikhail Strizh, Alexander Studenikin, Aoqi Su, Jun Su, Guangbao Sun, Mingxia Sun, Xilei Sun, Yongzhao Sun, Zhengyang Sun, Narumon Suwonjandee, Fedor Šimkovic, Christophe De La Taille, Akira Takenaka, Xiaohan Tan, Jian Tang, Jingzhe Tang, Qiang Tang, Quan Tang, Xiao Tang, Minh Thuan Nguyen Thi, Yuxin Tian, Igor Tkachev, Tomas Tmej, Marco Danilo Claudio Torri, Andrea Triossi, Wladyslaw Trzaska, Yu-Chen Tung, Cristina Tuve, Nikita Ushakov, Carlo Venettacci, Giuseppe Verde, Maxim Vialkov, Benoit Viaud, Cornelius Moritz Vollbrecht, Vit Vorobel, Dmitriy Voronin, Lucia Votano, Caishen Wang, Chung-Hsiang Wang, En Wang, Hanwen Wang, Jiabin Wang, Jun Wang, Li Wang, Meng Wang, Meng Wang, Mingyuan Wang, Qianchuan Wang, Ruiguang Wang, Sibo Wang, Tianhong Wang, Wei Wang, Wenshuai Wang, Xi Wang, Yangfu Wang, Yaoguang Wang, Yi Wang, Yi Wang, Yifang Wang, Yuanqing Wang, Yuyi Wang, Zhe Wang, Zheng Wang, Zhimin Wang, Apimook Watcharangkool, Wei Wei, Wei Wei, Yadong Wei, Yuehuan Wei, Zhengbao Wei, Liangjian Wen, Jun Weng, Christopher Wiebusch, Rosmarie Wirth, Bi Wu, Chengxin Wu, Diru Wu, Qun Wu, Yinhui Wu, Yiyang Wu, Zhaoxiang Wu, Zhi Wu, Michael Wurm, Jacques Wurtz, Dongmei Xia, Shishen Xian, Ziqian Xiang, Fei Xiao, Pengfei Xiao, Xiang Xiao, Wei-Jun Xie, Xiaochuan Xie, Yijun Xie, Yuguang Xie, Zhao Xin, Zhizhong Xing, Benda Xu, Cheng Xu, Donglian Xu, Fanrong Xu, Jiayang Xu, Jinghuan Xu, Meihang Xu, Shiwen Xu, Xunjie Xu, Yin Xu, Yu Xu, Jingqin Xue, Baojun Yan, Qiyu Yan, Taylor Yan, Xiongbo Yan, Yupeng Yan, Changgen Yang, Chengfeng Yang, Fengfan Yang, Jie Yang, Lei Yang, Pengfei Yang, Xiaoyu Yang, Yifan Yang, Yixiang Yang, Zekun Yang, Haifeng Yao, Jiaxuan Ye, Mei Ye, Ziping Ye, Frédéric Yermia, Jilong Yin, Weiqing Yin, Xiaohao Yin, Zhengyun You, Boxiang Yu, Chiye Yu, Chunxu Yu, Hongzhao Yu, Peidong Yu, Xianghui Yu, Zeyuan Yu, Zezhong Yu, Cenxi Yuan, Chengzhuo Yuan, Zhaoyang Yuan, Zhenxiong Yuan, Noman Zafar, Kirill Zamogilnyi, Jilberto Zamora, Vitalii Zavadskyi, Fanrui Zeng, Shan Zeng, Tingxuan Zeng, Liang Zhan, Yonghua Zhan, Aiqiang Zhang, Bin Zhang, Binting Zhang, Feiyang Zhang, Han Zhang, Haosen Zhang, Honghao Zhang, Jialiang Zhang, Jiawen Zhang, Jie Zhang, Jingbo Zhang, Junwei Zhang, Lei Zhang, Ping Zhang, Qingmin Zhang, Rongping Zhang, Shiqi Zhang, Shuihan Zhang, Siyuan Zhang, Tao Zhang, Xiaomei Zhang, Xin Zhang, Xu Zhang, Xuantong Zhang, Yibing Zhang, Yinhong Zhang, Yiyu Zhang, Yongpeng Zhang, Yu Zhang, Yuanyuan Zhang, Yumei Zhang, Zhenyu Zhang, Zhijian Zhang, Jie Zhao, Runze Zhao, Shujun Zhao, Tianhao Zhao, Hua Zheng, Yangheng Zheng, Li Zhou, Shun Zhou, Tong Zhou, Xiang Zhou, Xing Zhou, Jingsen Zhu, Kangfu Zhu, Kejun Zhu, Zhihang Zhu, Bo Zhuang, Honglin Zhuang, Liang Zong, Jiaheng Zou

Computational Physics

Integration of Silica in G4CMP for Phonon Simulations: Framework and Tools for Material Integration

Caitlyn Stone-Whitehead, Israel Hernandez, Connor Bray et al. (+10 more)

Superconducting detectors with sub-eV energy resolution have demonstrated success setting limits on Beyond the Standard Model (BSM) physics due to their unique sensitivity to low-energy events. G4CMP, a Geant4-based extension for condensed matter physics, provides a comprehensive toolkit for modeling phonon and charge dynamics in cryogenic materials. This paper introduces a technical formalism to support the superconducting qubit and low-threshold detector community in implementing phonon simulations in custom materials into the G4CMP. As a case study, we present the results of a detailed analysis of silica phonon transport properties relevant for simulating substrate backgrounds in Beryllium Electron capture in Superconducting Tunnel junctions (BeEST)-style experiments using G4CMP. Additionally, Python-based tools were developed to aid users in implementing their own materials and are available on the G4CMP repository.
Read the full abstract

All authors Caitlyn Stone-Whitehead, Israel Hernandez, Connor Bray, Allison Davenport, Spencer Fretwell, Abigail Gillespie, Joren Husic, Mingyu Li, Andrew Marino, Kyle Leach, Bismah Rizwan, Wouter Van De Pontseele, Grace Wagner

Optics

Non-invasive optical quantification of methanol in bottled spirits

Ané Kritzinger, George O. Dwapanyin, Ralf Mouthaan et al. (+2 more)

Food and beverage contamination poses a persistent global threat. A prime example is the presence of methanol in counterfeit or illicit spirits, causing severe and often fatal poisoning worldwide. Rapid, non-destructive, and on-site screening methods capable of molecular analysis directly through commercial packaging are therefore urgently needed for quality control and consumer safety. Here, we introduce a non-invasive optical approach based on Raman spectroscopy that judiciously combines wavefront shaping with wavelength modulation to enhance the signal-to-noise ratio and enable quantification of methanol in unopened bottled spirits. A limit of detection of 0.2% (v/v) methanol in 40% ethanol was achieved, well below the 2% (v/v) threshold for safe human consumption. This truly non-invasive method remains robust through coloured glass bottles, with calibration validated in a real spirit sample. By enabling through-container methanol detection, the technique offers a practical tool to protect consumers and streamline routine screening across the beverage supply chain. Moreover, this Raman geometry establishes a versatile platform for assessing authenticity, composition, and contaminants directly through packaging.
Read the full abstract

All authors Ané Kritzinger, George O. Dwapanyin, Ralf Mouthaan, Graham D. Bruce, Kishan Dholakia

Instrumentation and Detectors

Robustness of the smartpixels classifier for different simulated sensor geometries and non-ideal detector conditions

Danush Shekar, Ben Weiss, Morris Swartz et al. (+32 more)

Pixel tracking detectors at upcoming collider experiments will see unprecedented charged-particle densities. Real-time data reduction on the detector will enable higher granularity and faster readout, possibly enabling the use of the pixel detector in high-rate online event selection, such as the ATLAS or CMS first-level trigger systems. This data reduction can be accomplished with a neural network (NN) in the readout chip bonded with the sensor that recognizes and rejects tracks with low transverse momentum (p$_T$) based on the geometrical shape of the charge deposition (“cluster”). To design viable detectors for deployment, the dependence of the NN as a function of the sensor geometry, external magnetic field, irradiation, and noise must be understood. In this paper, we present first studies of the efficiency and data reduction for planar pixel sensors exploring these parameters. For the CMS HL-LHC sensor geometry, we obtain a signal efficiency of (91.9 $\pm$ 0.7)% and a data reduction of (29.7 $\pm$ 1.0)%. A smaller sensor pitch in the bending direction improves the p$_T$ discrimination, but a larger pitch can be partially compensated with detector thickness. Any accumulated radiation damage also changes the cluster shape, reducing the signal efficiency compared to the baseline by approximately 30\textendash{}60% in absolute terms, but nearly all of the performance can be recovered through retraining of the network and updating the weights. Finally, the impact of noise was investigated, and retraining the network on noise-injected datasets was found to maintain performance within 6% of the baseline network trained and evaluated on noiseless data.
Read the full abstract

All authors Danush Shekar, Ben Weiss, Morris Swartz, Corrinne Mills, Jennet Dickinson, Lindsey Gray, David Jiang, Mohammad Abrar Wadud, Daniel Abadjiev, Anthony Badea, Douglas Berry, Alec Cauper, Arghya Ranjan Das, Karri Folan DiPetrillo, Farah Fahim, Rachel Kovach Fuentes, Abhijith Gandrakota, Giuseppe Di Guglielmo, Eliza Howard, Shiqi Kuang, Carissa Kumar, Mia Liu, Petar Maksimovic, Nick Manganelli, Mark S Neubauer, Aidan Nicholas, Emily Pan, Benjamin Parpillon, Jannicke Pearkes, Ricardo Silvestre, Chinar Syal, Amit Trivedi, Keith Ulmer, Jieun Yoo, Eric You

Optics · Cross-listed from cond-mat.mes-hall

Nonlinear Optical Response in Pseudo-Hermitian Systems at Steady State

S. Sajad Dabiri and Reza Asgari

We establish a steady-state theory for nonlinear optical conductivity in pseudo-Hermitian systems. We derive compact formulas for the first and second order conductivity tensors in both the velocity and length gauges and prove their exact equivalence through generalized sum rules and Berry connection identities by formulating the nonlinear response in terms of a biorthogonal density matrix. Utilizing the formalism on parity-time symmetric two-level systems reveals nonlinear phenomena that are not present in Hermitian systems, such as extra terms in the conductivity, corrections to the velocity operator, photocurrent, and resonance structures with higher-order poles at one-photon transitions. These features yield qualitatively distinct harmonic generation responses like real second-order conductivities and nonzero DC limits. These results provide new insights into nonlinear light-matter interactions in active media characterized by balanced gain and loss, with implications for non-Hermitian photonics, dissipative topological systems, and quantum devices designed with engineered dissipation.
Read the full abstract

Chemical Physics

Accelerating Molecular Dynamics Simulations with Foundation Neural Network Models using Multiple Time-Step and Distillation

Côme Cattin, Thomas Plé, Olivier Adjoua et al. (+3 more)

We present a distilled multi-time-step (DMTS) strategy to accelerate molecular dynamics simulations using foundation neural network models. DMTS uses a dual-level neural network where the target accurate potential is coupled to a simpler but faster model obtained via a distillation process. The 3.5 Å-cutoff distilled model is sufficient to capture the fast-varying forces, i.e., mainly bonded interactions, from the accurate potential allowing its use in a reversible reference system propagator algorithms (RESPA)-like formalism. The approach conserves accuracy, preserving both static and dynamical properties, while enabling to evaluate the costly model only every 3 to 6 fs depending on the system. Consequently, large simulation speedups over standard 1 fs integration are observed: nearly 4-fold in homogeneous systems and 3-fold in large solvated proteins through leveraging active learning for enhanced stability. Such a strategy is applicable to any neural network potential and reduces their performance gap with classical force fields.
Read the full abstract

All authors Côme Cattin, Thomas Plé, Olivier Adjoua, Nicolaï Gouraud, Louis Lagardère, Jean-Philip Piquemal

Chemical Physics · Cross-listed from cond-mat.mtrl-sci

Real-Space Quantification of Exciton Localization in Acene Crystals Using Wannier Function Decomposition

Zui Tao, Jonah B. Haber and Jeffrey B. Neaton

We introduce the Wannier function decomposition of excitons (WFDX) method to quantify exciton localization in solids within the ab initio Bethe-Salpeter equation framework. By decomposing each Bloch exciton wavefunction into products of single-particle electron and hole maximally localized Wannier functions, this real-space approach provides well-defined orbital- and spatial- resolved measures of both Frenkel and charge-transfer excitons at low computational cost. We apply WFDX to excitons in acene crystals, quantifying how the number of rings, the exciton spin state, and the center-of-mass momntum affect spatial localization. Additionally, we show how this real-space representation reflects structural nonsymmorphic symmetries that are hidden in standard reciprocal-space descriptions. We demonstrate how the WFDX framework can be used to efficiently interpolate exciton expansion coefficients in reciprocal-space and outline how it may facilitate evaluation of observables involving position operators, highlighting its potential as a general tool for both analyzing and computing excitonic properties in solids.
Read the full abstract

Tuesday 7 October

Popular Physics

Propellantless space exploration

Roman Ya. Kezerashvili

Propellantless propulsion refers to methods of space travel that do not require onboard propellant, instead relying on natural forces or external energy sources. In this paper, I review different approaches that have been explored and discuss the pros and cons of each method for interstellar space exploration. Gravitational assist uses planetary gravity to change a spacecraft's speed and direction without fuel. It is effective but limited to specific alignments. Solar sails harness radiation pressure from sunlight for continuous, fuel-free acceleration. While effective over time, they require large, reflective materials that degrade in space. Speed can be enhanced by thermal desorption triggered by solar radiation. Magnetic sails generate thrust by interacting with the solar wind through superconducting loops that produce a magnetic field. They provide lower acceleration compared to solar sails, and their performance depends on the available power and the variability of solar wind conditions. Electric sails utilize charged tethers to repel solar wind protons, producing gradual acceleration. Their effectiveness depends on the successful deployment of very long, lightweight conductive wires. They can achieve higher acceleration than solar sails, and their performance is influenced by available power and solar wind conditions. Lastly, quantum effects, such as the Casimir force, offer a speculative but intriguing route to propellantless propulsion based on the vacuum energy of space.
Read the full abstract

Fluid Dynamics · Cross-listed from nlin.PS

Space-time resonances in the spatiotemporal spectrum of nonlinear dispersive waves

Michal Shavit, Fabio Pusateri, Zhou Zhang et al. (+4 more)

In weakly nonlinear dispersive wave systems, long-time dynamics are typically governed by time resonances, where wave phases evolve coherently due to exact frequency matching. Recent advances in spatio-temporal spectrum measurements, however, reveal prominent features that go beyond the predictions of time resonance theory. In this work, we develop a theoretical framework to interpret these signatures by identifying and characterizing an alternative mechanism: space resonances. These arise when wave packets share the same group velocity and remain co-located, leading to long-lived interactions. We further show that gauge-breaking terms in the Hamiltonian give rise to space resonances supported on negative frequencies. By combining sea-surface elevation data, numerical simulations, and analytical theory, we derive the leading-order spatio-temporal spectrum for weakly interacting water waves, providing a unified explanation for its observed features.
Read the full abstract

All authors Michal Shavit, Fabio Pusateri, Zhou Zhang, Yulin Pan, Davide Maestrini, Miguel Onorato, Jalal Shatah

Physics and Society

Multiscale Carbon Burden of Infrastructure in the United States

Jason Hawkins

Anthropogenic greenhouse gas (GHG) emissions vary spatially with development patterns, climate, economic structure, and energy systems. Using Vulcan v4.0 fossil-fuel CO2 (FFCO2) data for the United States at 1-km resolution, this study examines how land use and infrastructure shape emissions at local and metropolitan scales. I combine doubly robust Bayesian Additive Regression Tree estimators with multi-treatment spatial regression models to identify local and spillover effects by sector. A key methodological contribution is treating transportation emissions as production-based, capturing infrastructure carbon burden rather than household-attributed travel demand. Results show strong scale dependence and spatial interaction: in the preferred heteroscedasticity-robust SLX+SEM model with a 10-km distance band, residual spatial autocorrelation declines substantially. Local roadway design is a strong negative predictor of transportation FFCO2, while neighbouring land use diversity exceeds local diversity. In residential sectors, higher local density is consistently associated with lower per-capita emissions. These findings support coordinated multi-scale mitigation policy in the United States.
Read the full abstract

Instrumentation and Detectors

Bioinspired Tapered-Spring Turbulence Sensor for Underwater Flow Detection

Xiao Jin, Zhenhua Yu and Thrishantha Nanayakkara

This paper presents a bio-inspired underwater whisker sensor for robust hydrodynamic disturbance detection and efficient signal analysis based on Physical Reservoir Computing (PRC). The design uses a tapered nylon spring with embedded accelerometers to achieve spatially distributed vibration sensing and frequency separation along the whisker. Towing-tank experiments and computational fluid dynamics simulations confirmed that the whisker effectively distinguishes vortex regimes across different fin angles and maintains Strouhal scaling with flow velocity, where higher speeds increase vibration intensity without affecting the dominant frequencies. Frequency-domain analysis, Shannon entropy, and machine learning further validated the sensing performance: vortex shedding frequencies were identified with less than 10% error, entropy captured the transition from coherent vortex streets to turbulence, and logistic regression achieved 86.0% classification accuracy with millisecond-level inference. These results demonstrate that structurally encoded whisker sensing provides a scalable and real-time solution for underwater perception, wake tracking, and turbulence-aware navigation in autonomous marine robots.
Read the full abstract

Geophysics · Cross-listed from astro-ph.IM

An Introduction to Mars Terraforming, 2025 Workshop Summary

Devon Stork and Erika DeBenedictis

Terraforming Mars is an age old science fiction concept now worth revisiting through the lens of modern science and technology. This document serves as a summary of contemporary ideas about Mars terraforming, prepared for attendees of the 2025 Green Mars Workshop. It presents one illustrative story of how Mars might be transformed into a habitable world. The story is told in reverse, beginning with possible planetary endpoints and tracing backward to the steps required to reach them. Along the way, it highlights alternative approaches, critical unknowns and research priorities, and the near term applications and benefits of terraforming research for planetary science, climate engineering, and sustainable technologies on Earth.
Read the full abstract

General Physics

Plasma Core Rocket Engines

Gerald E. Marsh

The basic physics for plasma core rocket engines was already completed in 1985. At the time successful containment of a fissioning uranium hexafluoride U(93%)F6 plasma was achieved for ~120 seconds using an argon vortex. Unfortunately, hydrodynamic confinement of a fissioning fuel in a gas core nuclear rocket without uranium loss is probably unachievable. This article proposes a plasma core that is magnetically contained and uses one of many possible stable force-free magnetic field configurations.
Read the full abstract

Fluid Dynamics · Cross-listed from eess.SY

Nonlinear System Identification for Model-Based Control of Waked Wind Turbines

Sebastiano Randino, Lorenzo Schena, Nicolas Coudou et al. (+2 more)

This work presents a nonlinear system identification framework for modeling the power extraction dynamics of wind turbines, including both freestream and waked conditions. The approach models turbine dynamics using data-driven power coefficient maps expressed as combinations of compact radial basis functions and polynomial bases, parameterized in terms of tip-speed ratio and upstream conditions. These surrogate models are embedded in a first-order dynamic system suitable for model-based control. Experimental validation is carried out in two wind tunnel configurations: a low-turbulence tandem setup and a high-turbulence wind farm scenario. In the tandem case, the identified model is integrated into an adapted K\omega^2 controller, resulting in improved tip-speed ratio tracking and power stability compared to BEM-based and steady-state models. In the wind farm scenario, the model captures the statistical behavior of the turbines despite unresolved turbulence. The proposed method enables interpretable, adaptive control across a range of operating conditions without relying on black-box learning strategies.
Read the full abstract

All authors Sebastiano Randino, Lorenzo Schena, Nicolas Coudou, Emanuele Garone, Miguel Alfonso Mendez

2510.07336 · 7 Oct · Submitted to: Data-Centric Engineering Journal Length: 27 pages (including references) Figures: 14 numbered figures (from Fig. 1 to Fig. 14) Keywords: Wind Turbines, Wake Interaction, Nonlinear System Identification, Adaptive Control, RBF Regression, Model-Based Control, Wind Tunnel Experiments

Abstract PDF $TURB ×3$PLYN ×1