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Physics Physics

physics Watch Physics

Monday 20 July

Chemical Physics

Multireference Density Matrix Embedding for Spin-Phonon Relaxation

Shreya Verma, Antonio L. Mariano, Matthew R. Hermes et al. (+3 more)

Spin-phonon coupling governs magnetic relaxation in numerous systems including single-molecule magnets and molecular spin qubits. In most cases, the accurate prediction of spin relaxation rates requires multireference electronic structure methods, but their computational cost has largely restricted such calculations to isolated molecules. Here we show that spin-phonon relaxation rates can be computed within a multireference density matrix embedding framework. We apply the approach to three cobalt- and two dysprosium-based single-molecule magnets and to a cobalt-based molecular crystal. Across all systems, treating only the first coordination sphere of the magnetic center at the multireference level reproduces spin relaxation rates in good agreement with non-embedded CASSCF calculations while reducing the correlated problem to 10-68% of the total basis functions. Periodic calculations further demonstrate that spin relaxation rates can be computed for a molecular crystal using an embedded active space of only 259 basis functions out of a total of 2569. These results show that multireference density matrix embedding extends quantitative spin-phonon relaxation calculations from isolated molecules to molecular crystals.
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All authors Shreya Verma, Antonio L. Mariano, Matthew R. Hermes, Alessandro Lunghi, Giulia Galli, Laura Gagliardi

Instrumentation and Detectors

Final assessment of radioactive impurities in the JUNO detector

Thomas Adam, Fengpeng An, Costas Andreopoulos et al. (+571 more)

The Jiangmen Underground Neutrino Observatory (JUNO) collaboration has completed the construction of the 20,000-ton liquid scintillator detector and the associated muon veto detector system. To meet the physics objectives, the materials used in the detector must exhibit low radioactive contamination. The single-event rate in the fiducial volume (R $<$ 17.2 m) of the scintillator is required to be approximately 7 Hz for energies above 0.7 MeV, resulting in an accidental coincidence background of about 1 event per day for reactor neutrino physics analyses. Since the beginning of the construction phase, we have screened the natural radioactivity content of thousands of materials, to select those that meet the design background budget. The radioactive impurity concentrations of the materials ultimately used in the JUNO detector are summarized in this paper. The construction of the entire detector and the subsequent filling of the liquid scintillator were completed in August 2025. From the initial data, the total count rate of natural radioactivity within the detector's fiducial volume has met the requirements and is sufficient to support the reactor antineutrino analysis.
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All authors Thomas Adam, Fengpeng An, Costas Andreopoulos, Giuseppe Andronico, Nikolay Anfimov, Vito Antonelli, Tatiana Antoshkina, João Pedro Athayde Marcondes de André, Didier Auguste, Nikita Balashov, Andrea Barresi, Davide Basilico, Eric Baussan, Marco Beretta, Antonio Bergnoli, Nikita Bessonov, Daniel Bick, Lukas Bieger, Svetlana Biktemerova, Thilo Birkenfeld, Simon Blyth, Manuel Böhles, 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, Yi-zhou Cai, Stéphane Callier, Antonio Cammi, Guofu Cao, Jun Cao, Yaoqi Cao, Rossella Caruso, Cédric Cerna, Vanessa Cerrone, Jinfan Chang, Yun Chang, Tim Charisse, Chao Chen, Haotian Chen, Jiahui Chen, Jian Chen, Jing Chen, Junyou Chen, Pingping Chen, Shaomin Chen, Shiqiang Chen, Yixue Chen, Yu Chen, Ze Chen, Zhangming Chen, Zhiyuan Chen, Zhongchang Chen, Jie Cheng, Yaping Cheng, Yu Chin Cheng, Alexander Chepurnov, Alexey Chetverikov, Davide Chiesa, Ziliang Chu, Artem Chukanov, Gérard Claverie, Catia Clementi, Barbara Clerbaux, Claudio Coletta, Marta Colomer Molla, Selma Conforti Di Lorenzo, Chenyang Cui, Lorenzo Vincenzo D'Auria, Christophe De La Taille, Luis Delgadillo Franco, Ziyan Deng, Xiaoyu Ding, Xuefeng Ding, Yayun Ding, Sergey Dmitrievsky, Dmitry Dolzhikov, Chuanshi Dong, Haojie Dong, Jianmeng Dong, Marcos Dracos, Frédéric Druillole, Ran Du, Shuxian Du, Katherine Dugas, Stefano Dusini, Hongyue Duyang, Jessica Eck, Andrea Fabbri, Ulrike Fahrendholz, Gaofeng Fan, Lei Fan, Liangqianjin Fan, Jian Fang, Wenxing Fang, Dmitry Fedoseev, Qichun Feng, Shaoting Feng, Giovanni Ferrante, Daniela Fetzer, Marcellin Fotzé, Amélie Fournier, Aaron Freegard, Ying Fu, Feng Gao, Alberto Garfagnini, Arsenii Gavrikov, Diwash Ghimire, Marco Giammarchi, Nunzio Giudice, Maxim Gonchar, Guanda Gong, Guanghua 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, Yang Han, Chuanhui Hao, Miao He, Wei He, Xinhai He, Ziou He, Patrick Hellmuth, Yuekun Heng, YuenKeung Hor, Shaojing Hou, Fatima Houria, Yee Hsiung, Bei-Zhen Hu, Jun Hu, Tao Hu, Lian-Chen Huang, Guihong Huang, Jinhao Huang, Junlin Huang, Junting Huang, Kaixuan Huang, Shengheng Huang, Tao Huang, Xin Huang, Xingtao Huang, Yongbo Huang, Jiaqi Hui, Lei Huo, Cédric Huss, Ammad Ul Islam, Adrienne Jacobi, Arshak Jafar, Xiangpan Ji, Xiaolu Ji, Junji Jia, Cailian Jiang, Chengbo Jiang, Guangzheng Jiang, Junjie Jiang, Xiaoshan Jiang, Xiaozhao Jiang, Yijian Jiang, Yixuan Jiang, Xiaoping Jing, Cécile Jollet, Liam Jones, Amina Khatun, Khanchai Khosonthongkee, Denis Korablev, Alexey Krasnoperov, Sindhujha Kumaran, Chun-Hao Kuo, Nikolay Kutovskiy, Loïc Labit, Tobias Lachenmaier, Haojing Lai, Cecilia Landini, Lorenzo Lastrucci, Sébastien Leblanc, Matthieu Lecocq, Ruiting Lei, Rupert Leitner, Petr Lenskii, Demin Li, Fei Li, Gaosong Li, Jiajun Li, Meiou Li, Min Li, Nan Li, Ruhui Li, Rui Li, Shanfeng Li, Shuo Li, Teng Li, Weidong Li, Xiaonan Li, Yichen Li, Yifan Li, Yingke Li, Yufeng Li, Zhaohan Li, Zhibing Li, Zi-Ming Li, An-An Liang, Jiajun Liao, Minghua Liao, Yilin Liao, Ayut Limphirat, Bo-Chun Lin, Guey-Lin Lin, Shengxin Lin, Tao Lin, Xingyi Lin, Jiajie Ling, Xin Ling, Ivano Lippi, Caimei Liu, Fang Liu, Haidong Liu, Hongbang Liu, Hongjuan Liu, Jianglai Liu, Jiaxi Liu, Jinchang Liu, Kainan Liu, Min Liu, Qian Liu, Shenghui Liu, Shulin Liu, Ximing Liu, Xuewei Liu, Yankai Liu, Yiqi Liu, Zhipeng Liu, Zhuo Liu, Lorenzo Loi, Paolo Lombardi, Kai Loo, 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, 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, Stefano M. Mari, Agnese Martini, Johann Martyn, Matthias Mayer, Yue Meng, Anselmo Meregaglia, Lino Miramonti, Michele Montuschi, Cristobal Morales Reveco, Iwan Morton-Blake, Xiangyi Mu, Lakshmi Murgod, Massimiliano Nastasi, Dmitry V. Naumov, Elena Naumova, Igor Nemchenok, Elisabeth Neuerburg, Feipeng Ning, Zhe Ning, Yujie Niu, Lothar Oberauer, Juan Pedro Ochoa-Ricoux, 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, Fabrizio Petrucci, Oliver Pilarczyk, Pascal Poussot, Ezio Previtali, Fazhi Qi, Ming Qi, Sen Qian, Xiaohui Qian, Zhonghua Qin, Shoukang Qiu, Manhao Qu, Zhenning Qu, Gioacchino Ranucci, Thomas Raymond, Alessandra Re, Abdel Rebii, Bin Ren, Yuhan Ren, Barbara Ricci, Mariam Rifai, Mathieu Roche, Narongkiat Rodphai, Aldo Romani, Bedřich Roskovec, Félix Rosso, Peter Rudakov, Arseniy Rybnikov, Andrey Sadovsky, Sahar Safari, Ujwal Santhosh, Utane Sawangwit, Michaela Schever, Cédric Schwab, Konstantin Schweizer, Alexandr Selyunin, Andrea Serafini, Mariangela Settimo, Junyu Shao, Anurag Sharma, Vladislav Sharov, Hangyu Shi, Jingyan Shi, Yuan Shi, Hexi Shi, Dmitrii Shpotya, Yike Shu, Yuhan Shu, She Shuai, Vitaly Shutov, Randhir Singh, Apeksha Singhal, Chiara Sirignano, Jaruchit Siripak, Monica Sisti, Mikhail Smirnov, Oleg Smirnov, Sergey Sokolov, Julanan Songwadhana, Albert Sotnikov, Achim Stahl, Luca Stanco, Elia Stanescu Farilla, Hans Steiger, Jochen Steinmann, Tobias Sterr, Matthias Raphael Stock, Virginia Strati, Mikhail Strizh, Aoqi Su, Jun Su, Guangbao Sun, Mingxia Sun, Xilei Sun, Yongzhao Sun, Zhengyang Sun, Narumon Suwonjandee, Fedor Šimkovic, Akira Takenaka, Xiaohan Tan, Haozhong Tang, Jian Tang, Jingzhe Tang, Quan Tang, Xiao Tang, Vidhya Thara Hariharan, Yuxin Tian, Igor Tkachev, Tomas Tmej, Marco Danilo Claudio Torri, Andrea Triossi, Wladyslaw Trzaska, Andrei Tsaregorodtsev, Yu-Chen Tung, Cristina Tuve, Carlo Venettacci, Giuseppe Verde, Benoit Viaud, Vit Vorobel, Lucia Votano, Jiawei Wan, Caishen Wang, Chung-Hsiang Wang, En Wang, Hanwen Wang, Jiabin Wang, Jun Wang, Ke Wang, Li Wang, Meng Wang, Meng Wang, Mingyuan Wang, Ruiguang Wang, Sibo Wang, Tianhong Wang, Wei Wang, Wenshuai Wang, Wenyuan Wang, Xi Wang, Yangfu Wang, Yaoguang Wang, Yi Wang, Yifang Wang, Yuyi Wang, Zhe Wang, Zheng Wang, Zhimin Wang, Apimook Watcharangkool, Junya Wei, Jushang Wei, Wei Wei, Wei Wei, Yuehuan Wei, Zhengbao Wei, Liangjian Wen, Jun Weng, Rosmarie Wirth, Bi Wu, Chengxin Wu, Qun Wu, Yinhui Wu, Zhaoxiang Wu, Zhi Wu, Michael Wurm, Jacques Wurtz, Dongmei Xia, Shishen Xian, Ziqian Xiang, Fei Xiao, Pengfei Xiao, Tianying Xiao, Xiang Xiao, Wei-Jun Xie, Yuguang Xie, Zhizhong Xing, Benda Xu, Cheng Xu, Chuang Xu, Donglian Xu, Fanrong Xu, Jiayang Xu, Jilei Xu, Jinghuan Xu, Meihang Xu, Shiwen Xu, Xunjie Xu, Dongyang Xue, Jingqin Xue, Baojun Yan, Qiyu Yan, Taylor Yan, Xiongbo Yan, Changgen Yang, Chengfeng Yang, Dikun Yang, Fengfan Yang, Jie Yang, Kaiwei Yang, Lei Yang, Pengfei Yang, Xiaoyu Yang, Xuhui Yang, Yifan 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, Simi Yu, Zeyuan Yu, Cenxi Yuan, Chengzhuo Yuan, Noman Zafar, Vitalii Zavadskyi, Fanrui Zeng, Shan Zeng, Tingxuan Zeng, Liang Zhan, Bin Zhang, Feiyang Zhang, Han Zhang, Hangchang Zhang, Haosen Zhang, Honghao Zhang, Jiawen Zhang, Jie Zhang, Jingbo Zhang, Junwei Zhang, Lei Zhang, Ping Zhang, Qingmin Zhang, Rongping Zhang, Shiqi Zhang, Shuihan Zhang, Tao Zhang, Xiaomei Zhang, Xu Zhang, Xuantong Zhang, Yibing Zhang, Yinhong Zhang, Yiyu Zhang, Yongpeng Zhang, Yuanyuan Zhang, Yue Zhang, Yumei Zhang, Zhenyu Zhang, Zhicheng Zhang, Zhijian Zhang, Jie Zhao, Runze Zhao, Shujun Zhao, Yangheng Zheng, Li Zhou, Lishui Zhou, Shun Zhou, Xiang Zhou, Xing Zhou, Jingsen Zhu, Kangfu Zhu, Kejun Zhu, Bo Zhuang, Honglin Zhuang, Jiaheng Zou

Plasma Physics · Cross-listed from astro-ph.SR

Parker Solar Probe Observations of Preferential Heating of Protons over Alpha Particles near Turbulent Coherent Structures

Jiayang Xi, Tieyan Wang, Daniel Verscharen et al. (+15 more)

Solar wind alpha particles exhibit preferential heating and acceleration relative to protons; however, their behavior in the vicinity of turbulent coherent structures remains less understood. We report the first evidence of localized alpha particle and proton heating within coherent structures identified using the Partial Variance of Increments (PVI) method, based on Parker Solar Probe (PSP) observations. Our results show that high-PVI events are associated with significant, species-dependent temperature enhancements: protons undergo a relative larger temperature increase than alpha particles. This preferential proton heating produces a localized decrease in the alpha-to-proton temperature ratio, indicating that the plasma is driven toward thermal equilibration between species. The heating is also anisotropic, being dominated by enhancements in the perpendicular temperature. These temperature-signatures coincide with a pronounced reduction in the normalized alpha-proton differential flow speed and a localized minimum in the Coulomb collision age, suggesting that the relaxation is affected primarily by collisionless kinetic effects. These findings provide new insight into the intermittent energy conversion and ion thermodynamics in the solar wind.
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All authors Jiayang Xi, Tieyan Wang, Daniel Verscharen, Yan Yang, Luca Sorriso-Valvo, Xinyi Wang, Wenhao Chen, Zuzheng Chen, Zeren Zhima, Chao Xiao, Xiangcheng Dong, Jin Liu, Xiang Li, Guoqi Liu, Naifei Gou, Xiaoxiao Qin, Malcolm Dunlop, Jinbin Cao

Optics

Super-resolution technique enabled by higher-order Bessel beams in nanoscale optical structures

Apoorva D and M Ummal Momeen

In conventional optical microscopy, accessing subwavelength information is classically constrained by the Abbe diffraction limit which remains a significant challenge in nanophotonics. To overcome this limitation, we introduce a scheme that generates a tightly confined near-field focal spot under non-diffracting Bessel beam illumination, employing a series of high refractive-index nanoscale structures. Furthermore, the utilization of higher-order Bessel beams enables additional resolution enhancement beyond the diffraction limit. Our results demonstrate that the pyramidal nanostructure can generate a highly localized near-field confinement with a characteristic width of 10 nm, enabling subwavelength optical intensity localization. To elucidate the factors governing the localization behaviour, we systematically investigate the influence of different geometrical parameters related to the incident Bessel beam on the near field localization and shows that these factors critically determine the stability and spatial profile of the focal spot. These findings highlight the potential of the proposed approach for various applications in super-resolution techniques and quantum technology.
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Sunday 19 July

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

LatticeMind: A Validation-Gated Agentic Framework for Density Functional Theory Workflows

Nathaniel M. Vegh, Yu Zhu, Raphaël J. Prentki et al. (+3 more)

First-principles calculations are rarely single solver calls: they are multistage workflows in which structures, settings, and saved densities must pass correctly between dependent stages. Language models can write a valid single input, but reliability collapses once stages are chained: a dropped dependency, wrong file handoff, or hallucinated keyword can invalidate results even when the solver runs, and such errors surface only after costly execution. We introduce LatticeMind, a validation-gated agentic framework that converts natural-language requests into executable, checkable density functional theory (DFT) projects. A workflow contract specifies required stages, files, and dependencies; deterministic validators inspect the project before any solver launch; failed checks trigger bounded repair; and reports remain traceable to project files. On a 44-case RESCU benchmark spanning total-energy, density-of-states, band-structure, magnetic, phonon workflows, three non-flagship LLM backends reproduced every reference value; 119 of 132 runs passed on the first validated plan and the rest after one repair cycle. Ablations identify the workflow contract and pre-execution validation as the principal reliability mechanisms; a conventional trial-and-repair baseline reaches 71% at twice the token cost per success. The same architecture reproduces every reference value on a 19-case VASP benchmark, demonstrating transfer across solvers. Beyond these task families, LatticeMind generated and validated the 23 inputs of a multistage study of Rh-induced electronic responses at a Rh$_6$/In$_x$Ga$_{1-x}$N photocatalyst interface. These results establish workflow contracts, deterministic validation, bounded repair, and traceable records as a practical foundation for reliable AI-assisted scientific computing, where preventable errors are caught before execution and the solver is never the first validator.
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All authors Nathaniel M. Vegh, Yu Zhu, Raphaël J. Prentki, Félix Beaudoin, Shuaishuai Yuan, Hong Guo

Physics and Society

Time for unification: A single clock for Central and Eastern Europe

Chong Qi

The EU's effort to abolish biannual clock changes has stalled. We argue this deadlock presents a historic opportunity for continental unification. Astronomical analysis demonstrates that strict alignment between clock and solar time is unnecessary; at high latitudes, extreme seasonal variations render the morning-versus-evening daylight debate physically irrelevant. Real-world examples demonstrate that societies adapt seamlessly to permanent solar offsets. We propose establishing a unified Central and Eastern European Time (CEET) at UTC+2. This converges naturally if Central Europe adopts permanent summer time while the Finnish-Baltic bloc retains permanent standard time, synchronizing the vast majority of member states under a single clock and eliminating cross-border economic friction.
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General Physics

Boomeranging through the Earth: when free fall doesn't maximize proper time

Henrique Gomes

In teaching special relativity, John Bell emphasised the value of pre-relativistic intuitions. His famous spaceship puzzle showed that, in certain cases, the older heuristics of Lorentz and FitzGerald get the right answer to a genuinely relativistic problem more reliably than the principles of special relativity themselves. In teaching general relativity, John Wheeler emphasised the value of simplicity, illustrating curved-spacetime geometry with capsules boomeranging through a tunnel along the Earth's diameter. Here I put the two ideas together. I share a simple thought experiment, involving genuinely general-relativistic effects, in which the standard GR heuristic – “freely falling observers maximise proper time” – gives the wrong answer, while the older heuristic of velocity and gravitational time dilation, applied in a single frame, gets it right immediately. The resolution involves conjugate points and the distinction between local and global extremality of geodesics, but the moral is the same as Bell's: do not let a newer slogan overwrite a perfectly sound older intuition.
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Physics and Society · Cross-listed from cs.AI

Poor Man's Agentic Modeling: Simulating Large LLM-Agent Societies on a Laptop

Igor Itkin

Simulating societies of many large language model (LLM) agents is expensive, yet the questions asked of such simulations are usually macroscopic: phase behaviour, stylised facts, and scaling with the number of agents $N$, not the cognition of any single agent. We turn a statistical-physics observation into a method: replace each LLM agent by a low-parameter model fitted from a few hundred to a few thousand cheap queries, then run the society at any $N$ on a laptop. Whether this works is decided before the simulation runs, chiefly by what each agent perceives. We introduce an [interaction order x memory] taxonomy that maps perception and memory to an effective theory and a predicted $N$-trend of the surrogate error. We validate it on a faithful reimplementation of the LLM macroeconomy EconAgent and seven further named LLM simulations, with agent decisions cloned from genuine LLM elicitations (primarily DeepSeek) for a few dollars; the predicted error trends hold cell by cell, and the two refuted predictions, both on a strongly saturating response and traced to its curvature, are themselves matched quantitatively by the theory with no free parameters.
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Atomic Physics · Cross-listed from hep-ph

Relative enhancement of low-mass vector-boson exchange in higher waves matrix elements: parity non-conservation in hydrogen

V. A. Dzuba, V. V. Flambaum and G. K. Vong

Models of unification predict additional $Z'$ boson, which contributes to parity non-conservation (PNC) in atoms. If $Z'$ boson is light, ratio of $Z'$ boson contribution to the Standard Model $Z$ boson contribution to atomic PNC increases with decreasing nuclear charge $Z$ faster than $1/Z^2$. This motivated our previous study of PNC in hydrogen and deuterium proportional to the weak interaction matrix elements $<s|W|p> $. An enormous additional relative enhancement appears in the matrix elements between higher waves, such as $<p_{1/2,3/2} | W | d_{3/2,5/2}> $, since $p_{3/2}$ and $d_{3/2,5/2}$ wave functions vanish at $r \to 0$, suppressing matrix elements of the contact $Z$ boson mediated contact electron-nucleus interaction. Measurements of $<p_{1/2,3/2} | W | d_{3/2,5/2}> $ will simplify disentanglement of the $Z'$ contribution from the Standard Model background.
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Optics

Broadband suspended lithium tantalate Mach-Zehnder modulator achieving a 460 Gbit/s net data rate

Zihan Li, Alexander Kotz, Adrian Schwarzenberger et al. (+2 more)

Thin-film lithium tantalate photonic integrated circuits have recently been demonstrated as a promising next-generation electro-optic platform, offering favorable properties including reduced DC drift, higher optical power handling, and lower birefringence compared to lithium niobate. However, high-speed LiTaO3 modulators reported to date have predominantly relied on silicon substrates, whose large dielectric constant compromises microwave velocity matching and imposes RF conductor losses that limit the achievable electro-optic bandwidth. Here, we implement a silicon substrate undercut technique to suspend the electrode region of lithium-tantalate-on-insulator (LTOI) Mach-Zehnder modulators (MZMs), effectively decoupling the traveling-wave electrodes from the high-permittivity silicon handle wafer, thereby reducing microwave losses. In addition, the undercut removes any susceptibility to parasitic surface conductance (PSC) induced losses of the oxide-silicon interface. The fabricated MZM achieves a 3 dB electro-optic bandwidth of 110 GHz, with a half-wave voltage of 5.1 V for an 8 mm-long device. Exploiting the extended bandwidth, we demonstrate a high single-lane intensity-modulation and direct-detection (IMDD) net data rate of 460 Gbit/s using PAM8 signaling. These results establish silicon substrate undercut as an effective and process-compatible pathway to unlock the full electro-optic potential of lithium tantalate on its native silicon-based wafer platform.
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All authors Zihan Li, Alexander Kotz, Adrian Schwarzenberger, Christian Koos, Tobias J. Kippenberg

Chemical Physics · Cross-listed from cs.LG

Grounded verification of chemical and materials reasoning: detection is the bottleneck

Can Polat, Mustafa Kurban, Erchin Serpedin et al. (+1 more)

Language models are moving into chemistry and materials discovery workflows, where a wrong molecular formula, space group, or formation energy can silently propagate into downstream decisions. These confabulations hide inside fluent reasoning traces and concentrate on rare, long-tail entities, where model confidence is least trustworthy. Retrieving reference data for every prompt would catch them, but at a heavy coverage and abstention cost. We show that deterministic, database-grounded verification catches and repairs these errors selectively, and that the binding constraint is detection rather than repair. Our tiered verifier extracts each checkable claim, tests it against authoritative databases and physical law, and retrieves a reference value only when a check fails. Across four models and over five hundred prompts with pinned conditions, gated correction cuts the error rate of committed formulas from 22% to 4% with 3.2 times fewer retrievals than blanket augmentation, and it outperforms a conversational retrieval oracle when every answer, corrected or not, is scored. When a flag fires, repair almost always succeeds; the benefit reaches the final answer only where the verifier's scope covers it and where long-tail error exists. Checkable claims, checked cheaply, are a practical lever for trustworthy machine reasoning in chemistry.
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All authors Can Polat, Mustafa Kurban, Erchin Serpedin, Hasan Kurban

Applied Physics

Computationally-tractable synthesis of an MXene metamaterial absorber with a 3D-printable spatially variable substrate by a local approach

Maria-Thaleia Passia, Yilin Zhao, Haozhe Wang et al. (+1 more)

We introduce the LOCABINACONN3D methodology to enable the computationally tractable synthesis of MXene metamaterial absorbers (MMA) based on spatially variable 3D-printable substrates. Spatially variable substrates offer enhanced absorption bandwidth compared to constant ones. Such MXene MMAs are typically synthesized by inverse design, which may lead to non-manufacturable optimized dielectric substrates. To transform non-manufacturable dielectric substrates into manufacturable ones, existing methodologies either add manufacturing constraints to the optimization, which may lead to less optimized MMAs, or are computationally expensive, as they require full-wave simulations of the entire manufacturable MMA. We develop a computationally tractable methodology, LOCABINACONN3D, to render optimized MMAs manufacturable, preserving performance. Our methodology (i) accommodates detailed connectivity constraints across consecutive layers, thus facilitating multilayer fabrication, and (ii) enables scaling to larger MMAs, by requiring simulations only of smaller manufacturable MMA subareas and by using a semi-analytical method-of-lines (MoL) solver instead of full-wave methods to determine suitable manufacturable configurations. This work paves the way for synthesizing optimized larger-scale 3D-printable MMAs more efficiently.
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All authors Maria-Thaleia Passia, Yilin Zhao, Haozhe Wang, Steven Cummer

History and Philosophy of Physics

The History of Hilbert-Space Formulations of Classical Physics

Jacob A. Barandes

Hilbert-space techniques are widely used not only for quantum theory, but also for classical physics. Two important examples are the Koopman-von Neumann (KvN) formulation and the method of “classical” wave functions. As this paper explains, these two approaches are conceptually distinct. In particular, the method of classical wave functions was not due to Bernard Koopman and John von Neumann, but was developed independently by a number of later researchers, perhaps first by Mario Schönberg, with key contributions from Angelo Loinger, Giacomo Della Riccia, Norbert Wiener, and E. C. George Sudarshan. The primary goals of this paper are to explain these two approaches, describe the relevant history in detail, and give credit where credit is due.
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Applied Physics

Eigenmode analysis of a half-mode uniplanar metamaterial-inspired substrate integrated waveguide

Maria-Thaleia Passia, Kyriakos Katsaros-Gkouskos and Traianos V. Yioultsis

In this work, we systematically analyze the propagation characteristics of a new half-mode uniplanar substrate integrated waveguide (SIW) based on complementary split-ring resonators (CSRR), using a finite element method (FEM) eigenmode solver. The proposed half-mode CSRR SIW has a simpler fabrication than the SIW, since the via are substituted by CSRRs, and is more compact than the existing full uniplanar CSRR SIW, since its transverse size is reduced almost by half. To gain insight into the propagation characteristics of the proposed half-mode CSRR SIW and guide its synthesis process, we solve an eigenvalue problem that determines the complex propagation constant of the supported modes. By calculating the dispersion diagrams of the dominant mode, with all loss mechanisms included, we demonstrate that the half-mode uniplanar CSRR SIW retains the performance of the existing full CSRR SIW.
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Optics · Cross-listed from quant-ph

Broadband Polarization Compensation with Link Segment Reconstruction for Quantum Optical Links

Qingyu Shi, Erwan Trad, Julien Chénedé et al. (+1 more)

Polarization-encoded quantum communication requires compensation of polarization transformations induced by the optical links. If the compensator is embedded between two channel segments, the transformations before and after the compensator must be treated separately. Moreover, standard three-wave-plate polarization controllers can become non-universal when their retardances deviate from their ideal values. To address these two challenges, we introduce a four-wave plate compensator that synthesizes arbitrary SO(3) polarization transformations over a broad wavelength range, and an eight-Stokes vector protocol that reconstructs the two link-segment Mueller matrices on either side of the compensator. Our experiment reveals that the four-plate sequence suppresses polarization-induced excess quantum bit error rate (QBER) to the sub-percent level at an operating wavelength more than 100 nm from the design wavelength without further optimization. Combined with two auxiliary wavelengths, our scheme tracks the temperature-driven drift of a strongly wavelength-sensitive fiber spool while keeping the excess QBER below 1%. These results support flexible compensator placement and wavelength channel selection, as well as non-interruptive polarization control in wavelength-division-multiplexed quantum optical links.
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All authors Qingyu Shi, Erwan Trad, Julien Chénedé, Tobias Vogl

Physics and Society

The unintended consequences of large language models as a labor-augmenting technology in science

Eamon Duede, Kevin Gross, M.J. Crockett et al. (+1 more)

As a labor-augmenting technology, large language models (LLMs) have the potential to accelerate scientific activity across the research pipeline. But even if LLMs perform on par with human experts at selected tasks, their use will bring unintended consequences as they alter the balance of frictions and inducements that steer the allocation of research effort across projects. Here we develop a simple mathematical model to illustrate. In fields where LLMs are useful primarily as tools for discovering promising projects, researchers will become more selective about what they publish; where they facilitate the process of publishing existing data, researchers will become less selective. By allowing scientists to work more quickly, LLMs raise the opportunity cost of researcher time, creating incentives to refine papers less thoroughly before moving on. Enticing as it is to imagine that, by saving us time on mundane tasks, LLMs will provide us with more time to think deeply and develop projects completely, our results temper such hopes.
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All authors Eamon Duede, Kevin Gross, M.J. Crockett, Carl Bergstrom

Fluid Dynamics · Cross-listed from cs.CE

Modeling elasto-viscoplastic free-surface flows with different yield surfaces

Lars Blatny and Alexandre Pellet

Elasto-viscoplasticity provides a unified way of describing yield-stress fluids which may exhibit both solid-like and fluid-like behavior. In this work, we present a finite strain overstress-type elasto-viscoplastic framework designed to facilitate the incorporation of different yield surfaces. Within this framework, we compare several yield-surface choices and assess the associated challenges. We consider three representative yield surfaces: (i) pressure-independent, (ii) pressure-sensitive frictional and (iii) capped surfaces, corresponding to von Mises, Drucker–Prager, and modified Cam–clay models, respectively. In the case of von Mises, the proposed formulation naturally recovers the well-known Bingham and Herschel–Bulkley rheologies which are characterized by a single critical yield stress. We discuss in detail the singularity of the Drucker–Prager yield surface which requires a special treatment. In particular, we show that the modified Cam–clay model can be used to conveniently circumvent this singularity under the right conditions, retrieving the expected solution of Drucker–Prager. Implemented within a hybrid Eulerian–Lagrangian scheme, the general framework presented here enables efficient simulations of elasto-viscoplastic flows in two or three spatial dimensions, not requiring regularizing the solid-fluid transition nor a separate free-surface treatment. Numerical benchmark simulations illustrate how yield surface geometry affects velocity profiles, plug formation and compressibility.
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Fluid Dynamics

Solver-in-the-loop training of deep learning closures for large-eddy simulation of turbulent premixed jet flames

Priyesh Kakka and Jonathan F. MacArt

Large-eddy simulation (LES) turbulence models often fail to capture the effects of chemical heat release and the resulting modulation of turbulence in premixed flames, underscoring the need for a framework that remains accurate across a broad range of physical regimes. We develop an augmented eddy-viscosity closure, based on deep neural networks calibrated jointly with the LES solution using adjoint-based optimization and differentiable programming, ensuring consistency with the governing partial differential equations (PDEs). Several objective functions and training methods are examined, and each model is assessed for its capability to interpolate and extrapolate across a wide range of Damköhler numbers. Relative to the Smagorinsky-model baseline, the best neural network model improves a posteriori errors in the LES primitive variables by 25-50% and in the resolved Reynolds stress and scalar flux by more than 60%. Crucially, the model generalizes across Damköhler number regimes, maintaining stability and accuracy even for out-of-sample conditions. These results demonstrate that PDE-consistent deep learning closures can recover both mean fields and resolved turbulence statistics in LES of turbulent premixed flames and can therefore provide a broadly applicable framework for turbulent combustion modeling.
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Applied Physics

Reconfigurable Graphene-Metasurface Analysis via an Eigenmode-Free Method-of-Lines Formulation

Maria-Thaleia Passia, Dimitrios Floros and Traianos V. Yioultsis

We present an eigenmode-free (EF) method-of-lines (MoL) formulation for the fast synthesis of reconfigurable graphene metasurfaces (MS). As the complexity of MSs increases, analysis by full-wave methods becomes challenging. The MoL is a considerably faster semi-analytical method where the electromagnetic equations are solved analytically along the direction perpendicular to the MS layers and numerically on the MS plane, thereby substantially decreasing the degrees of freedom (DoFs). In existing MoL formulations, the eigendecomposition of the system matrix is calculated numerically, which becomes computationally demanding for MSs with larger cross-sections. To overcome this limitation, we introduce an EF MoL that calculates the S-parameter matrix by analytical closed-form expressions. We demonstrate the potential of the EF MoL by analyzing a reconfigurable graphene MS absorber. The EF MoL shows excellent agreement in the absorbance and is two orders of magnitude faster than the finite element method.
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Computational Physics · Cross-listed from cond-mat.mtrl-sci

Response-function-optimized phase field modeling of solute trapping and solute drag in rapid alloy solidification

Joni Kaipainen, Tatu Pinomaa and Nikolas Provatas

Quantitative prediction of rapid-solidification microstructures requires phase field models that represent the velocity dependence of interfacial properties, including solute partitioning, kinetic liquidus response, solute drag, and kinetic undercooling. These response functions control both microsegregation and morphology selection, but are difficult to prescribe accurately in phase field simulations that employ enlarged interfaces for numerical efficiency. We introduce an optimization-based calibration strategy that embeds target sharp-interface response functions into a dilute alloy phase field formulation by treating the interfacial diffusivity interpolation function as a response-matching degree of freedom. The optimized diffusivity functions are obtained from one-dimensional steady-state phase field solutions constrained to reproduce prescribed continuous-growth-model targets for velocity-dependent solute trapping and drag-modified liquidus kinetics. We demonstrate the accuracy and versatility of the calibrated model in dilute Al-Cu by reproducing the prescribed response functions for intermediate solute drag coefficients relevant to rapid solidification. Two-dimensional simulations are carried out over a range of drag coefficients and pulling velocities relevant to additive manufacturing, demonstrating that quantitative changes in the prescribed interface kinetics can systematically shift the morphology from cellular to banded growth. Additionally, we extend the formulation to dilute multicomponent alloys, enabling independent specification of equilibrium partition coefficients and liquidus slopes for multiple solute species. The framework separates the physical specification of nonequilibrium interface kinetics from their diffuse-interface realization and provides a practical route for embedding response functions into quantitative phase field computations.
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Optics · Cross-listed from astro-ph.IM

Tolerancing the PIAA-ZWFS: a practical and robust wavefront sensor that approaches the fundamental sensitivity limit

Adam K. Taras, Sebastiaan Y. Haffert and Louis Desdoigts

High-contrast imaging demands extremely sensitive wavefront sensing to correct atmospheric effects and surface errors. While the limits of the sensitivity of a wavefront sensor are well known, a practical, robust design that saturates these limits remains elusive. This work further investigates the PIAA-ZWFS (Phase-Induced Amplitude Apodization-Zernike Wavefront Sensor). In previous work, we developed a framework to optimise its design, maximising Fisher information per frame in the presence of phase aberrations. In these proceedings, we study the effect of various manufacturing and alignment errors in the system on the overall performance. We employ both traditional Monte Carlo sampling and a 2nd order expansion using our auto-differentiable simulator. The performance of the PIAA-ZWFS is not significantly degraded by these errors at values typical for manufacturing.
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Plasma Physics

ORB5X: a performance-portable global electromagnetic gyrokinetic PIC code in C++/Kokkos built using Agentic AI

Mohsen Sadr, Emmanuel Lanti, Alexey Mishchenko et al. (+2 more)

ORB5X is a C++17/Kokkos AI-assisted translation of ORB5, a global electromagnetic gyrokinetic particle-in-cell code for toroidal confined plasmas. The translation preserves the mathematical model and the main numerical algorithms of the Fortran implementation, i.e. a Lagrangian gyrokinetic formulation, marker-particle representation of the distribution functions, finite-element B-spline representation of the fields, Fourier filtering in the angular directions, MPI domain decomposition and cloning, and HDF5 diagnostic output. The main software change is the replacement of Fortran modules and allocatable arrays by typed C++ classes, structs, namespaces, and Kokkos Views and kernels for performance portability across multicore CPU and GPU backends. This paper summarizes the physical models, the numerical scheme, the distributed and shared-memory parallel design, the AI-assisted code translation workflow, and the validation path used to compare ORB5X against the original Fortran reference codebase. The initial tests for ITG, ITPA, and chirping show an agreement of almost machine accuracy between ORB5X and ORB5 for the electrostatic and electromagnetic field components. Furthermore, we demonstrate that with the modern CMake and Kokkos, ORB5X can be easily compiled and efficiently run on personal Linux and Mac laptops, as well as on high-performance computing clusters such as LUMI-G, Daint-ALPS, CINECA, and Discoverer.
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All authors Mohsen Sadr, Emmanuel Lanti, Alexey Mishchenko, Xin Wang, Laurent Villard

Optics

Quantitative Benchmarking of a Split-Field PML FDTD Solver: Slit Diffraction, and Scattering from PEC and Dielectric Cylinders

Sabrina Saima and Tasin Intisar

This paper presents a two-dimensional TMz finite-difference time-domain (FDTD) solver based on Yee's scheme for modeling radiation from an infinitely long z-directed line current, with the open region truncated by a Berenger split-field perfectly matched layer (PML). After validating cylindrical-wave propagation and negligible late-time reflections in free space, the solver is applied to three inhomogeneous configurations: (i) diffraction through a one-cell-thick perfectly electrically conducting (PEC) sheet with single and double slits; (ii) scattering from infinitely long PEC cylinders of circular and rectangular cross section; and (iii) scattering from infinitely long dielectric cylinders of varying cross section and permittivity. Beyond qualitative field maps, the diffraction case is characterized quantitatively: a steady-state phasor extracted by a running discrete Fourier transform yields the transmitted intensity, from which the fringe visibility and the far-field pattern are computed and compared against the closed-form Fraunhofer prediction. The single- and double-slit cases are cleanly separated by a visibility that rises from near zero to near unity, and the double-slit interference maxima agree with the grating condition arcsin(m \lambda_0 / d) to within a fraction of a degree. For dielectric cylinders, the field penetrates the obstacle with the expected reduced internal wavelength \lambda_0 / \sqrt{\epsilon_r}, and the scattered field strength grows with permittivity contrast. A reference-subtraction method isolates the scattered field throughout. The results confirm that the FDTD-PML framework accurately captures open-region diffraction and geometry- and material-dependent scattering.
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Geophysics · Cross-listed from cond-mat.stat-mech

Richards' equation as a hydrodynamic limit: Chapman–Enskog reduction of the continuum kinetic equation for unsaturated soil water

Riccardo Rigon

Richards' equation for unsaturated water flow is derived from the kinetic theory of the pore-filling distribution g(r,x,t) of a companion paper. It separates two limits that macroscopic theory usually conflates. The spatial limit is purely kinematic: contracting the representative elementary volume (REV) to a point yields the closed continuum kinetic equation (CKE) d_t g + div F = C[g], with F a pore-resolved pre-closure flux and C[g] the occupancy-gated redistribution operator. The dynamics lies in the temporal limit, the subject of this paper: a Chapman-Enskog (CE) reduction of the CKE controlled by the Damkohler number Da (redistribution time over forcing time), the structural analogue of the passage from Boltzmann to Navier-Stokes. The linearized redistribution operator J is self-adjoint and negative semidefinite in the mass inner product, with a one-dimensional kernel fixing a single invariant (water) and hence one macroscopic equation; the CE hierarchy inverts the same J at every order, only the source changing. Four results follow: the equilibrium step defines the retention curve; the linearized water budget plus the inter-REV source set the first-order equation; its solvability is mass conservation, i.e. Richards' equation; and the response function gives the macroscopic flux, identifying the conductivity K as a first-order transport coefficient, the counterpart of viscosity. Mean-field reduction recovers the standard integral formula; the serial-path correction gives Mualem's heterogeneity penalty. A bimodal pore-size distribution opens a gap in the relaxation spectrum; projecting onto the bands and applying CE within each, with cross-band relaxation surviving at O(1), derives the dual- and multiple-permeability models from first principles, the exchange coefficient set by inter-band connectivity. When Da is not small the expansion breaks down and the full CKE is needed.
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Fluid Dynamics

Differentiable Hybrid Neural-CFD Modelling of Wall-Bounded Turbulence: Coupled Learning of Subgrid-Scale and Wall Closures

Xiantao Fan, Yi Liu, Meng Wang et al. (+1 more)

Wall-modelled large-eddy simulation (WMLES) treats the subgrid-scale (SGS) closure, wall closure and numerical discretization as independent components, although their effects are coupled through the same resolved field. We present a differentiable hybrid neural–CFD framework in which the SGS and wall closures are learned jointly, end-to-end, within a differentiable flow solver, using only low-order statistics as training targets. Each closure is a composed neural operator: a trainable neural network followed by a fixed differentiable layer that preserves the structure of its conventional counterpart, so that the network learns only the functions left undetermined by the conventional form. Because every operation is differentiable, gradients of the training loss are back-propagated through the coupled solver, allowing both neural closures to be optimized consistently against the flow field, rather than fitted offline or in isolation. We demonstrate the framework, denoted Hybrid-Joint, on a zero-pressure-gradient turbulent boundary layer across a posteriori tests spanning Re_\theta = 600–6500, computational domains and mesh resolutions. The model outperforms WMLES baselines, extrapolates to more than four times the highest training Reynolds number, and transfers to grids and domains absent from training. It recovers a logarithmic mean-velocity region, not imposed by the wall closure, and reproduces the resolved energy spectra accurately, although spectral information is excluded from the training objective. Ablation studies show that learning either closure alone is insufficient and that only joint optimization recovers the full set of statistics, confirming that SGS closure, wall closure and discretization are coupled and must be trained jointly. Once trained, the closures are reused without retraining across all cases, so that training cost is amortized over repeated deployment.
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All authors Xiantao Fan, Yi Liu, Meng Wang, Jian-Xun Wang

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

Colored $\Delta_T$ noise probes the topological character of edge modes

Sachiraj Mishra and Colin Benjamin

We investigate colored $\Delta_T$ noise, i.e., finite-frequency $\Delta_T$ noise, as a probe of edge-mode (EM) transport in quantum Hall and quantum spin Hall systems. Colored $\Delta_T$ noise probes finite-frequency nonequilibrium current fluctuations and dynamical transport properties that are often obscured in DC measurements of conductance and noise. Since $\Delta_T$ noise is driven solely by a temperature and voltage bias under zero average charge current conditions, it eliminates current-induced Joule heating and directly probes intrinsic thermal fluctuations. We show that chiral, spin-conserving helical, and spin-flip helical (trivial) EMs exhibit distinct colored $\Delta_T$-noise signatures under appropriate bias protocols. Incorporating energy-dependent scattering through a quantum point contact, we demonstrate that electron-hole asymmetry significantly modifies the finite-frequency spectrum while preserving these distinguishing features. Notably, colored $\Delta_T$ noise exhibits a frequency-dependent sign reversal absent in the corresponding white ($\omega=0$) $\Delta_T$ noise. We further investigate zero-temperature colored quantum shot noise and find that it vanishes identically for chiral EMs, whereas the spin-conserving helical response changes sign with frequency. By contrast, spin-flip helical (trivial) EMs exhibit a positive colored shot-noise spectrum. However, the corresponding colored $\Delta_T$ noise retains its characteristic sign reversal, providing a robust distinction between spin-conserving helical and spin-flip helical (trivial) EM transport. These results establish colored $\Delta_T$ noise as a robust, experimentally accessible, complementary probe for identifying chiral, spin-conserving helical, and spin-flip helical (trivial) EM transport in mesoscopic topological systems.
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Optics · Cross-listed from quant-ph

Protecting Astronomical Interferometry through Quantum-Memory Scrambling

Jianqi Sheng

Preserving the complex visibility of coherently captured starlight is essential for quantum-assisted long-baseline interferometry, because this nonlocal coherence carries the spatial information needed to form astronomical images. Yet finite memory lifetime and imperfect retrieval inevitably produce storage failures; when a failed cell is heralded, its erased subsystem can leak which-node information to the environment and dephase the stored coherence. Strict finite-dimensional (\(U(1)\)) covariance further forbids uniform exact correction of all single-memory erasures. We address this combined physical and symmetry-imposed limit using local number-conserving quantum scrambling, parameter-independent pattern-conditioned recovery, and a fixed Gottesman–Jennewein–Croke receiver. We prove a channel-to-Fisher-information stability theorem that converts approximate logical recovery into an operational guarantee on receiver-accessible information over compact visibility regions. All-pattern finite-size simulations show that scrambling redistributes erasure risk and suppresses high-leakage events, while a separate equal-budget comparison identifies a shallow design that outperforms the tested deeper and charge-sector Haar-random benchmarks at the prespecified operating point. A separate compilation resolves every nontrivial recovery branch into abstract nearest-neighbor number-conserving gates. Although the present low-rate design does not yet improve fixed-total-memory throughput, it establishes a blueprint for converting spare memory capacity into protection of astronomical coherence, opening a path toward higher-rate, erasure-resilient quantum telescope architectures.
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Chemical Physics

Interpolative Separable Density-Fitting for Transcorrelated Hamiltonians

Ke Liao, Yifan Cheng, Werner Dobrautz et al. (+2 more)

The transcorrelated (TC) method dramatically accelerates the convergence of correlated calculations toward the complete-basis-set (CBS) limit by folding a Jastrow correlator into the Hamiltonian via a similarity transformation, incorporating the electron–electron cusp into the effective interaction. We make the TC framework practical for large systems and flexible, multi-center correlators by compressing the grid-evaluated TC integrals with the interpolative separable density-fitting (ISDF) approximation, combined with the effective two-body (xTC) treatment of the three-body operator. This low-rank representation reduces storage and integration costs by orders of magnitude, and a multi-GPU implementation with automatic differentiation of the correlator makes the construction routine for large basis sets. We demonstrate the resulting ISDF-xTC-CCSD method on the linear hydrogen chain, reaching the joint thermodynamic and CBS limits with basis sets up to cc-pV5Z in agreement with state-of-the-art many-body references to within about 1~mHa/atom, and on the benzene ground-state energy with up to 1200 orbitals (cc-pCV5Z), where the method attains state-of-the-art accuracy at the coupled cluster singles and doubles level and its CBS extrapolation is markedly more robust than that of conventional coupled-cluster methods.
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All authors Ke Liao, Yifan Cheng, Werner Dobrautz, Tianyu Zhu, Ali Alavi

Fluid Dynamics

Multi-Granularity Conformal Prediction for Reliable Neural-Operator Automotive Aerodynamic Surrogates

Chundong Jia, Chao Xia, Alexey Vdovin et al. (+3 more)

High-fidelity computational fluid dynamics (CFD) provides detailed aerodynamic data for vehicle design, but its cost limits design iteration. Neural-operator surrogates reduce this cost, yet their deterministic predictions do not indicate when a geometry or surface region is reliable. This study develops a conformal-prediction framework for reliability-aware automotive aerodynamic surrogate modeling on the DrivAerML dataset. GeoTransolver is the main backbone, while Transolver assesses transfer across neural-operator architectures. For drag coefficient prediction, conformalized quantile regression constructs calibrated case-level intervals. For surface pressure and wall shear stress (WSS), point prediction is combined with residual-scale estimation and residual-normalized conformal calibration to obtain spatially adaptive intervals. Global absolute, point-adaptive normalized, and case-wise normalized calibration are compared under split and cross-validation-assisted out-of-fold protocols. All experiments target 90% nominal coverage. Conformal calibration corrects the under-coverage of raw drag-coefficient quantile intervals, while out-of-fold score aggregation reduces the Monte Carlo coverage standard deviation from 10.41 to 3.10 percentage points. For surface fields, point-adaptive normalized calibration yields the narrowest near-nominal intervals, reducing mean width by 22.68% for pressure and 25.35%–27.09% for WSS under the out-of-fold protocol. Case-wise normalized calibration is more conservative but improves vehicle-level reliability. Smoothness regularization reduces the residual-scale local-variation score by 74.29% and lowers interval widths without material coverage loss. The framework converts deterministic neural-operator outputs into calibrated reliability indicators for prioritizing uncertain vehicle geometries and surface regions in follow-up CFD verification.
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All authors Chundong Jia, Chao Xia, Alexey Vdovin, Qing Jia, Simone Sebben, Zhigang Yang

Optics · Cross-listed from eess.SP

Broadband Content-Adaptive Moiré Meta-spectrometer

Arnab Ghosh, Johannes E. Fröch, Arka Majumdar et al. (+1 more)

Optical spectroscopy underpins material characterization, chemical sensing, and astronomy, but conventional instruments face a rigid trade-off between footprint, spectral range, and resolution. We demonstrate a content-adaptive spectrometer that overcomes this by co-designing dispersive Moiré meta-optics with a recursive sampling algorithm. Instead of using Moiré metalenses solely for varifocal tuning, we harness the strong chromatic aberration arising from phase-wrapping in their subwavelength metasurface architecture. This hyperchromaticity enables a deterministic, one-to-one mapping between the metasurfaces' mutual rotation angle and the sharply focused wavelength, repurposing the pair as a high-resolution spectral scanner. To accelerate data acquisition, we introduce a content-adaptive recursive sampling protocol that exploits the structural sparsity of physical spectra: a fast coarse sweep identifies high-information regions, followed by successively finer angular refinement only where needed. Using a laboratory prototype spanning 405-980 nm, we reconstruct diverse spectra – from smooth broadband to sparse multi-line laser emissions – with nearly 3x fewer measurements on average at matched fidelity (up to 7x for sparse line spectra), achieving 30 dB reconstruction 6.7x faster than conventional uniform sampling. This establishes a framework for intelligent, task-adaptive meta-optical sensors that tightly integrate physical dispersion with computational signal processing for real-time spectrometry.
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All authors Arnab Ghosh, Johannes E. Fröch, Arka Majumdar, Vishwanath Saragadam