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Physics Physics

physics Watch Physics

Monday 10 November

Optics

GiBS: Generative Input-side Basis-driven Structures

Reza Marzban, Ashkan Zandi and Ali Adibi

Designing large-scale metasurfaces with nonlocal optical effects remains challenging due to the immense dimensionality and fabrication constraints of conventional optimization methods. We introduce GiBS (Generative Input-side Basis-driven Structures), an inverse-design framework that represents the entire device using a compact set of coefficients from smooth parametric bases such as Fourier or Chebyshev functions. This formulation compresses the design space by more than an order of magnitude, enabling efficient optimization of complex, broadband, and aperiodic geometries. GiBS integrates this low-dimensional representation with an autoencoder-based manifold-learning workflow to map the relationship between geometry and optical response, facilitating rapid exploration, discovery of high-performance designs, and systematic analysis of fabrication sensitivity. The inherent smoothness of the basis functions ensures manufacturability while capturing the asymmetry required for nonlocal optical interactions. We experimentally validated the framework through the realization of a PEDOT:PSS broadband scattering metasurface, whose measured response closely matched full-wave simulations across 500-1100 nm. These results establish GiBS as a scalable, data-efficient, and fabrication-aware platform for the inverse design of multifunctional metasurfaces, bridging AI-guided representation learning with experimentally realizable photonic architectures.
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Instrumentation and Detectors

MPGD with a 3D-printed Thick-GEM as sole gain element

J. Collins and M. Hohlmann

We present the first micropattern gaseous detector that employs a small 3D-printed Thick-GEM as its sole gain element. The detector can achieve sufficient gas gain for regular operation without the need for pre-amplification by additional gain elements. We describe the design, quality control, assembly, and test of this detector. The 10 cm $\times$ 10 cm active area of the Thick-GEM features three separate sectors with different sizes of the clearance rim annuli (0.1 mm, 0.15 mm, 0.2 mm) around the 0.7 mm diameter holes. The gas gain is found to depend strongly on the rim size. When operated in Ar/CO$_2$ 70:30 gas, the sector with 0.15 mm annulus rims reaches a gain above 10$^4$ while operating in a stable manner with an acceptably low discharge rate. The gain reach under stable operation is found to be considerably lower in the other two sectors. The gas gain shows a characteristic time-dependence as it rises quickly in the first hour of operation and then drops slowly over the next 24 hours and subsequently stabilizes.
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Data Analysis and Statistics

Reverse Stress Testing for Supply Chain Resilience

Madison Smith, Michael Gaiewski, Sam Dulin et al. (+4 more)

Supply chains' increasing globalization and complexity have recently produced unpredictable disruptions, ripple effects, and cascading resulting failures. Proposed practices for managing these concerns include the advanced field of forward stress testing, where threats and predicted impacts to the supply chain are evaluated to harden the system against the most damaging scenarios. Such approaches are limited by the almost endless number of potential threat scenarios and cannot capture residual risk. In contrast to forward stress testing, this paper develops a reverse stress testing (RST) methodology that allows to predict which changes, with probabilistic certainty, across the supply chain network are most likely to cause a specified level of disruption at a specific entity in the network. The methodology was applied to the case of copper wire imports into the USA, a simple good which may have significant implications for national security. Results show that Canada, Chile, and Mexico are predicted to consistently be sources of disruptions at multiple loss levels. Other countries (e.g., Papua New Guinea) may contribute to small disruptions but be less important for the catastrophic losses of concern for decision makers. Other countries' disruptions would be catastrophic (e.g., Chile). The proposed methodology is the first case of reverse stress testing application in complex multilayered supply chains and can be used to address both risk and resilience.
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All authors Madison Smith, Michael Gaiewski, Sam Dulin, Laurel Williams, Jeffrey Keisler, Andrew Jin, Igor Linkov

Atmospheric and Oceanic Physics

An Efficient Regional Storm Surge Surrogate Model Training Strategy Under Evolving Landscape and Climate Scenarios

Ziyue Liu, Mohammad Ahmadi Gharehtoragh, Brenna Kari Losch et al. (+1 more)

Coastal communities face significant risk from storm-induced coastal flooding, which causes substantial societal and economic losses worldwide. Machine learning techniques have increasingly been integrated into coastal hazard modeling, particularly for storm surge prediction, due to advances in computational capacity. However, incorporating multiple projected future climate and landscape scenarios requires extensive numerical simulations of synthetic storm suites over large geospatial domains, resulting in rapidly escalating computational costs. This study proposes a cost-effective training data reduction strategy for machine learning based storm surge surrogate models that enables efficient incorporation of new future scenarios while minimizing computational burden. The proposed strategy reduces training data across three dimensions: grid points, input features, and storm suite size. Reducing the storm suite size for future scenario simulations is highly effective in guiding numerical simulations, yielding substantial reductions in simulation cost. The performance of surrogate models trained on reduced datasets was evaluated using different machine learning algorithms. Results demonstrate that the proposed reduction strategy is robust across different model types. When trained using 5,000 out of 80,000 grid points, 10 out of 12 input features, and 60 out of 90 storms, the total training dataset is reduced to approximately 5% of its original size. Despite this reduction, the trained model achieves a correlation coefficient of 0.94, comparable to models trained on the full dataset. In addition, storm selection methodologies are introduced to support efficient storm set expansion for future scenario analyses.
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All authors Ziyue Liu, Mohammad Ahmadi Gharehtoragh, Brenna Kari Losch, David R. Johnson

Chemical Physics

Offset-Free Robust Nonlinear Control Using Data-Driven Model: A Nonlinear Multi-Model Computationally Efficient Approach

Carine Menezes Rebello, Erbet Almeida Costa and Idelfonso B. R. Nogueira

Robust model predictive control (MPC) aims to preserve performance under model-plant mismatch, yet robust formulations for nonlinear MPC (NMPC) with data-driven surrogates remain limited. This work proposes an offset-free robust NMPC scheme based on symbolic regression (SR). Using a compact NARX structure, we identify interpretable surrogate models that explicitly represent epistemic (structural) uncertainty at the operating-zone level, and we enforce robustness by embedding these models as hard constraints. gest margins. The single-zone variant (RNMPC$_{SZ}$) was investigated. Synthetic data were generated within one operating zone to identify SR models that are embedded as constraints, while the nominal predictor remains fixed, and the multi-zone variant (RNMPC$_{MZ}$), zone-specific SR models from multiple operating zones are jointly enforced in the constraint set; at each set-point change, the nominal predictor is re-scheduled to the SR model of the newly active zone. In both cases, robustness is induced by the intersection of the admissible sets defined by the enforced SR models, without modifying the nominal cost or introducing ancillary tube dynamics. The approach was validated on a simulated pilot-scale electric submersible pump (ESP) system with pronounced nonlinearities and dynamically varying safety envelopes (downthrust and upthrust). RNMPC$_{SZ}$ and RNMPC$_{MZ}$ maintained disturbance tracking and rejection, and by intersecting models in the constraints, they increased margins and eliminated violations (especially near the upthrust), with a slight increase in settling time. Including up to four models per zone did not increase the time per iteration, maintaining real-time viability; RNMPC$_{MZ}$ presented the lar
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Chemical Physics · Cross-listed from cond-mat.mtrl-sci

A Linear-Scaling, Charge-Aware Foundation Potential for Atomistic Simulations

Tsz Wai Ko, Runze Liu, Adesh Rohan Mishra et al. (+3 more)

Electrostatics govern charge transfer and reactivity in materials. However, most foundation potentials (FPs) either neglect explicit electrostatic interactions or come at prohibitive computational cost. Here, we introduce charge-equilibrated TensorNet (QET), an equivariant, charge-aware architecture that achieves linear scaling with system size via an analytically solvable charge-equilibration scheme. We demonstrate that a trained QET FP matches state-of-the-art FPs on materials property benchmarks but delivers qualitatively different predictions in systems dominated by electrostatic interactions. The QET FP reproduces the correct structure and density of the NaCl-CaCl2 ionic liquid and the crystallization of Ge1Sb2Te4 phase change memory, which charge-agnostic FPs miss. We further show that a fine-tuned QET captures reactive processes at the Li/Li6PS5Cl solid-electrolyte interface and supports simulations under applied electrochemical potentials. These results remove a fundamental constraint in large-scale atomistic simulations of electrostatics and establish a general, data-driven framework for charge-aware FPs with transformative applications in energy storage, catalysis, and beyond.
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All authors Tsz Wai Ko, Runze Liu, Adesh Rohan Mishra, Zihan Yu, Ji Qi, Shyue Ping Ong

Geophysics · Cross-listed from hep-ex

Prospects for geoneutrino detection with JUNO

Thomas Adam, Shakeel Ahmad, Rizwan Ahmed et al. (+627 more)

Geoneutrinos, which are antineutrinos emitted during the decay of long-lived radioactive elements inside Earth, serve as a unique tool for studying the composition and heat budget of our planet. The Jiangmen Underground Neutrino Observatory (JUNO) experiment in China, which has recently completed construction, is expected to collect a sample comparable in size to the entire existing world geoneutrino dataset in less than a year. This paper presents an updated estimation of sensitivity to geoneutrinos of JUNO using the best knowledge available to date about the experimental site, the surrounding nuclear reactors, the detector response uncertainties, and the constraints expected from the TAO satellite detector. To facilitate comparison with present and future geological models, our results cover a wide range of predicted signal strengths. Despite the significant background from reactor antineutrinos, the experiment will measure the total geoneutrino flux with a precision comparable to that of existing experiments within its first few years, ultimately achieving a world-leading precision of about 8% over ten years. The large statistics of JUNO will also allow separation of the Uranium-238 and Thorium-232 contributions with unprecedented precision, providing crucial constraints on models of formation and composition of Earth. Observation of the mantle signal above the lithospheric flux will be possible but challenging. For models with the highest predicted mantle concentrations of heat-producing elements, a 3-sigma detection over six years requires knowledge of the lithospheric flux to within 15%. Together with complementary measurements from other locations, the geoneutrino results of JUNO will offer cutting-edge, high-precision insights into the interior of Earth, of fundamental importance to both the geoscience and neutrino physics communities.
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All authors Thomas Adam, Shakeel Ahmad, Rizwan Ahmed, Fengpeng An, João Pedro Athayde Marcondes de André, Costas Andreopoulos, Giuseppe Andronico, Nikolay Anfimov, Vito Antonelli, Tatiana Antoshkina, Didier Auguste, Marcel Büchner, 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, Manuel Boehles, Anastasia Bolshakova, Mathieu Bongrand, Matteo Borghesi, Dominique Breton, Augusto Brigatti, Riccardo Brugnera, Riccardo Bruno, Antonio Budano, Jose Busto, Anatael Cabrera, Barbara Caccianiga, Hao Cai, Xiao Cai, Stéphane Callier, Steven Calvez, Antonio Cammi, Guofu Cao, Jun Cao, Yaoqi Cao, Rossella Caruso, Cédric Cerna, Vanessa Cerrone, Jinfan Chang, Yun Chang, Tim Charisse, Auttakit Chatrabhuti, 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, Pietro Chimenti, Po-Lin Chou, Ziliang Chu, Artem Chukanov, Gérard Claverie, Catia Clementi, Barbara Clerbaux, Claudio Coletta, Marta Colomer Molla, Chenyang Cui, Ziyan Deng, Xiaoyu Ding, Xuefeng Ding, Yayun Ding, Bayu Dirgantara, Sergey Dmitrievsky, Dmitry Dolzhikov, Chuanshi Dong, Haojie Dong, Jianmeng Dong, Evgeny Doroshkevich, Marcos Dracos, Frédéric Druillole, Ran Du, Shuxian Du, Katherine Dugas, Stefano Dusini, Hongyue Duyang, Jessica Eck, Andrea Fabbri, Ulrike Fahrendholz, Lei Fan, Liangqianjin Fan, Jian Fang, Wenxing Fang, Elia Stanescu Farilla, Dmitry Fedoseev, Li-Cheng Feng, Qichun Feng, Shaoting Feng, Daniela Fetzer, Marcellin Fotzé, Amélie Fournier, Aaron Freegard, Ying Fu, Haonan Gan, Feng Gao, Ruohan Gao, Alberto Garfagnini, Arsenii Gavrikov, 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, Vidhya Thara Hariharan, Miao He, Wei He, Xinhai He, Ziou He, Tobias Heinz, Patrick Hellmuth, Yuekun Heng, YuenKeung Hor, Shaojing Hou, Fatima Houria, Yee Hsiung, Bei-Zhen Hu, Hang Hu, Jun Hu, Tao Hu, Yuxiang Hu, 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, Safeer Hussain, Leonard Imbert, Ara Ioannisian, Adrienne Jacobi, Arshak Jafar, Beatrice Jelmini, Xiangpan Ji, Xiaolu Ji, Junji Jia, Cailian Jiang, Guangzheng Jiang, Junjie Jiang, Xiaoshan Jiang, Xiaozhao Jiang, Yijian Jiang, Yixuan Jiang, Xiaoping Jing, Cécile Jollet, Liam Jones, Li Kang, 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, Petr Lenskii, Jason Leung, Demin Li, Fei Li, Gaosong Li, Jiajun Li, Meiou Li, Min Li, Nan Li, Ruhui Li, Rui Li, Shanfeng Li, Teng Li, Weidong Li, Xiaonan Li, Yi Li, Yichen Li, Yifan Li, Yingke Li, Yufeng Li, Zhaohan Li, Zhibing Li, Zhiwei 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, Fengcheng Liu, Haidong Liu, Hongbang Liu, Hongjuan Liu, Jianglai Liu, Jiaxi Liu, Jinchang Liu, Kainan Liu, Min Liu, Qian Liu, Runxuan Liu, Shenghui Liu, Shulin Liu, Ximing Liu, Xiwen Liu, Xuewei Liu, Yankai Liu, Yiqi Liu, Zhipeng Liu, Zhuo Liu, Lorenzo Loi, Alexey Lokhov, Paolo Lombardi, Kai Loo, Selma Conforti Di Lorenzo, Chuan Lu, 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, Johann Martyn, Matthias Mayer, Davit Mayilyan, William McDonough, Yue Meng, Anselmo Meregaglia, Lino Miramonti, Michele Montuschi, Iwan Morton-Blake, Xiangyi Mu, 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, 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, Mariam Rifai, Mathieu Roche, Narongkiat Rodphai, Fernanda de Faria Rodrigues, Aldo Romani, Bedřich Roskovec, Peter Rudakov, Arseniy Rybnikov, Andrey Sadovsky, Deshan Sandanayake, Anut Sangka, Ujwal Santhosh, Utane Sawangwit, Michaela Schever, Cédric Schwab, Konstantin Schweizer, Alexandr Selyunin, Andrea Serafini, Mariangela Settimo, Yanjun Shang, Junyu Shao, Anurag Sharma, Vladislav Sharov, Hangyu Shi, Hexi SHI, Jingyan Shi, Yuan Shi, Yike Shu, Yuhan Shu, She Shuai, Vitaly Shutov, Andrey Sidorenkov, Fedor Šimkovic, Randhir Singh, Apeksha Singhal, Chiara Sirignano, Jaruchit Siripak, Monica Sisti, Mikhail Smirnov, Oleg Smirnov, Thiago Sogo-Bezerra, Sergey Sokolov, Julanan Songwadhana, 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, Zhanxue Sun, Zhengyang Sun, Narumon Suwonjandee, Christophe De La Taille, Akira Takenaka, Xiaohan Tan, Haozhong Tang, Jian Tang, Jingzhe Tang, Quan Tang, Xiao Tang, Jihua Tao, Minh Thuan Nguyen Thi, Yuxin Tian, Igor Tkachev, Tomas Tmej, Marco Danilo Claudio Torri, Andrea Triossi, Wladyslaw Trzaska, Andrei Tsaregorodtsev, Yu-Chen Tung, Cristina Tuve, Nikita Ushakov, Carlo Venettacci, Giuseppe Verde, Maxim Vialkov, Benoit Viaud, Cornelius Moritz Vollbrecht, Vit Vorobel, Dmitriy Voronin, Lucia Votano, Andong Wang, 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, Yadong Wei, Yuehuan Wei, Zhengbao Wei, Liangjian Wen, Jun Weng, Scott Wipperfurth, Rosmarie Wirth, Bi Wu, Chengxin Wu, Qun Wu, Yinhui Wu, Zhaoxiang Wu, Zhi Wu, Michael Wurm, Jacques Wurtz, Yufei Xi, Dongmei Xia, Shishen Xian, Ziqian Xiang, Fei Xiao, Pengfei Xiao, Tianying Xiao, Xiang Xiao, Wei-Jun Xie, Xiaochuan Xie, Yuguang Xie, Zhao Xin, Zhizhong Xing, Benda Xu, Cheng Xu, Chuang Xu, Donglian Xu, Fanrong Xu, Jiayang Xu, Jie Xu, Jilei Xu, Jinghuan Xu, Meihang Xu, Shiwen Xu, Xunjie Xu, Ya Xu, Dongyang Xue, Jingqin Xue, Baojun Yan, Qiyu Yan, Taylor Yan, Xiongbo Yan, Yupeng 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, Jiaxaun 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, Noman Zafar, Jilberto Zamora, Vitalii Zavadskyi, Fanrui Zeng, Shan Zeng, Tingxuan Zeng, Liang Zhan, Bin Zhang, Feiyang Zhang, Han Zhang, Hangchang 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, 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, Liang Zhao, Runze Zhao, Shujun Zhao, Hua Zheng, Yangheng Zheng, Li Zhou, Lishui Zhou, Shun Zhou, Xiang Zhou, Xing Zhou, Jingsen Zhu, Kangfu Zhu, Kejun Zhu, Bo Zhuang, Honglin Zhuang, Jiaheng Zou

Optics

Directional Random Lasing in Liquid Crystal Infiltrated Metasurfaces

Khoi Anh Pham and Giuseppe Strangi

Random lasers (RL) emit light through multiple scattering in disordered gain media, typically resulting in isotropic emission with limited directionality control. Controlling RL emission direction in compact systems remains a challenge. Here we report directional random lasing achieved by infiltrating dye-doped nematic liquid crystals into a nanostructured silica metasurface. By adjusting pump energy, we induce a transition from uniform angular photoluminescence to a strongly directional emission peak at large angles in the amplified spontaneous emission and RL regimes. This directionality arises from enhanced spatial coherence in the strong scattering regime, enabling coupling of guided random-laser modes to high-angle diffraction through the metasurface grating. Our system demonstrates wide-angle RL beam steering at submicron scale without complex external components. These results provide a straightforward method to control RL emission directionality, advancing tunable coherent light sources and metasurface-based photonic applications.
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Biological Physics

Dynamic Vaccine Prioritization via Non-Markovian Final-state Optimization

Mi Feng, Liang Tian and Changsong Zhou

Effective vaccine prioritization is critical for epidemic control, yet real outbreaks exhibit memory effects that inflate state space and make long-term prediction and optimization challenging. As a result, many strategies are tuned to short-term objectives and overlook how vaccinating certain individuals indirectly protects others. We develop a general age-stratified non-Markovian epidemic model that captures memory dynamics and accommodates diverse epidemic models within one framework via state aggregation. Building on this, we map non-Markovian final states to an equivalent Markovian representation, enabling real-time fast direct prediction of long-term epidemic outcomes under vaccination. Leveraging this mapping, we design a dynamic prioritization strategy that continually allocates doses to minimize the predicted long-term final epidemic burden, explicitly balancing indirect transmission blocking with the direct protection of important groups and outperforming static policies and those short-term heuristics that target only immediate direct effects. We further uncover the underlying mechanism that drives shifts in vaccine prioritization as the epidemic progresses and coverage accumulates, underscoring the importance of adaptive allocations. This study renders long-term prediction tractable in systems with memory and provides actionable guidance for optimal vaccine deployment.
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Plasma Physics

Design and operation of APEX-LD: a compact levitated dipole for the confinement of electron-positron pair plasmas

A. Card, M.R. Stoneking, A. Deller et al. (+1 more)

The objective of the APEX (A Positron-Electron eXperiment) project is to magnetically confine and study electron–positron pair plasmas. For this purpose, a levitated dipole trap (APEX-LD) has been constructed. The magnetically levitated, compact (7.5-cm radius), closed-loop, high-temperature superconducting (HTS) floating (F-)coil consists exclusively of a No-Insulation (NI) Rare-earth Barium Copper Oxide (ReBCO) winding pack, solder-potted in a gold-plated-copper case. A resealable in-vacuum cryostat facilitates cooling (via helium gas) and inductive charging of the F-coil. The 70-minute preparation cycle reliably generates persistent currents of ~60 kA-turns and an axial magnetic flux density of B_0 ~ 0.5 T. We demonstrate levitation times in excess of three hours with a vertical stability of sigma_z < 20 um. Despite being subjected to routine quenches (and occasional mechanical shocks), the F-coil has proven remarkably robust. We present the results of preliminary experiments with electrons, and outline the next steps for injecting positron bunches into the device.
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All authors A. Card, M.R. Stoneking, A. Deller, E.V. Stenson

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

A Strain-Engineered 0D/1D Heterojunction of InVO4/Cu-TbFeO3 for High- Selectivity CO2 Photoreduction

Muneeb ur Rahman

The catalytic CO2 photoreduction to CO is significantly hindered by the pervasive kinetic bottleneck of *CO-desorption and inefficient charge separation. Surpassing the conventional single photocatalytic strategy, herein, a multi-synergetic 0D/1D S-scheme heterojunction by precisely assembling 0D InVO4 nanoparticles on 1D Cu-doped TbFeO3 (IVO/CTFO). This nano-heterojunction is rationally designed at multiple steps where Cu2+ substitution at the Fe3+ site induces a compression in lattice strain and oxygen vacancies (VO), acting as electron traps and CO2 chemisorption sites, which breaks spin-polarization of pristine TbFeO3 to facilitate multichannel charge flow. The 0D/1D strategy couples the maximum surface active-sites and short charge diffusion routes with directional charge migration. Moreover, a 0D/1D lattice mismatch creates a built-in electric field at the interface, resulting in an enhanced lifetime (64.70 ns) of charged species, an efficient CO yield (65.75 mmole g-1.h-1), and high selectivity (95.93%). DFT calculations and experimental findings confirmed the Fermi level shift toward the conduction band and the existence of spin-hybridization. Operando-DRIFTS and the free-energy diagram unveil a H+ mediated mechanism at the interface, alongside a reduction in energy barrier for CO2 photoreduction from *COOH to *CO. Thus, this study presents an excellent approach that integrates defect-engineering, strain-compression, and interfacial design in advancing solar fuels production.
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Computational Physics · Cross-listed from cond-mat.mtrl-sci

Effect of Misfit and Threading Dislocations on Surface Energies of PbTe-PbSe Interfaces

Emir Bilgili, Nicholas Taormina, Yang Li et al. (+3 more)

This work quantifies the effect of misfit and threading dislocations on the surface energies of PbTe-PbSe interfaces, with the defect structures of the interfaces being obtained from atomistic and multiscale simulations of their manufacturing processes. Simulation results show that direct bonding produces semi-coherent interfaces with two-dimensional misfit dislocation networks, while heteroepitaxial processes produce complex three-dimensional dislocation structures with both misfit and threading dislocations. Surface energies at these interfaces were determined by computing the interaction energies across these interfaces. Compared with coherent interfaces, directly bonded interfaces exhibit up to ~23% lower surface energy, while the surface energies of epitaxially grown interfaces can be nearly 50% lower. The results demonstrate the significant effects of dislocations on interfacial energy.
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All authors Emir Bilgili, Nicholas Taormina, Yang Li, Adrian Diaz, Simon R. Phillpot, Youping Chen

Computational Physics · Cross-listed from cs.LG

Guiding Generative Models to Uncover Diverse and Novel Crystals via Reinforcement Learning

Hyunsoo Park and Aron Walsh

Discovering functional crystalline materials entails navigating an immense combinatorial design space. While recent advances in generative artificial intelligence have enabled the sampling of chemically plausible compositions and structures, a fundamental challenge remains: the objective misalignment between likelihood-based sampling in generative modelling and targeted focus on underexplored regions where novel compounds reside. Here, we introduce a reinforcement learning framework that guides latent denoising diffusion models toward diverse and novel, yet thermodynamically viable crystalline compounds. Our approach integrates group relative policy optimisation with verifiable, multi-objective rewards that jointly balance creativity, stability, and diversity. Beyond de novo generation, we demonstrate enhanced property-guided design that preserves chemical validity, while targeting desired functional properties. This approach establishes a modular foundation for controllable AI-driven inverse design that addresses the novelty-validity trade-off across scientific discovery applications of generative models.
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Optics

Geometric phase metasurfaces for linearly polarized light

Yubin Gao, Qikai Chen and Yaoguang Ma

The geometric phase is a universal concept in modern physics and has enabled the development of metasurfaces for versatile wavefront shaping. However, its realization in metasurfaces has been restricted to circularly polarized light, confining geometric phase metasurfaces to helicity-dependent operation and excluding them from the linear-polarization domain that dominates modern optics. In this work, we overcome this limitation by harnessing exceptional points of non-Hermitian physics. We introduce and experimentally realize quasi-exceptional-point metasurfaces that exploit engineered singularities to directly impart a geometric phase onto linearly polarized light. Proof-of-principle demonstrations with gratings and holograms confirm broadband and high-fidelity wavefront shaping across arbitrary linear polarizations, which has not been achieved with previous phase modulation approaches. By revealing an intrinsic connection between geometric phase and non-Hermitian photonics, our work resolves a long-standing theoretical impasse and establishes a new framework for high-dimensional light control, opening opportunities for scalable polarization optics, advanced imaging, holography, optical communications, and integrated photonics.
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Atomic Physics · Cross-listed from cond-mat.quant-gas

Pattern formation in ring condensates subjected to bichromatic driving

Premabrata Manna, S. I. Mistakidis, P. G. Kevrekidis et al. (+1 more)

We investigate the dynamical formation of nonlinear patterns in one-dimensional ring condensates under bichromatic periodic modulation of the interaction strength. The stability phase diagram of the condensate's homogeneous density state is analytically derived through a suitable biharmonic variant of the Mathieu equation and computing the associated Floquet spectrum. It reveals the complex interplay between the driving parameters, i.e., amplitude, frequencies, and the so-called frequencies' mixing angle, which dictate the instability onset and the selective enhancement of higher-order resonance tongues, thus offering precise control over the excited modes. These results are in agreement with time-dependent mean-field simulations evidencing the emergence of density wave modulations of specific momenta, while enabling a deeper understanding of the nonlinear stage of the relevant instability. Further insights on the ensuing unstable nonlinear dynamics are provided through a reduced {five-mode} model which captures the instability onset, the oscillatory behavior of the mode populations and the phase-space dynamics, in agreement with the mean-field predictions. Our study highlights the versatility of bichromatic driving to generate and control complex nonlinear patterns that are within reach in present day ultracold atom experiments.
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All authors Premabrata Manna, S. I. Mistakidis, P. G. Kevrekidis, Pankaj Kumar Mishra

Optics

Scattering Induced Mode Chirality in Ring Resonators

Haochen Yan, Xu Guo, Arghadeep Pal et al. (+15 more)

Non-Hermitian physics can be used to break time reversal symmetry and is important for interactions in a wide range of systems, from active matter and neural networks to metamaterials and non-equilibrium thermodynamics. In integrated photonic devices, non-Hermitian physics can be used for direction-dependent light propagation, reconfigurable light paths, selective energy localization and optical isolators. In this work, we report previously unexplored direction-dependent mode splitting in ring microresonators, achieved by adding multiple scatterers around the cavity. Through experiments, simulations, and theoretical modeling, we unveil the underlying physics that changes the resonance shapes in resonant systems with backscattering. By engineering the spatial configuration of the scatterers, we can produce a predictable and repeatable direction-dependent mode splitting, enabling new ways to route light through optical resonators and photonic networks. In addition, the direction dependent mode-splitting can be used for precise near-field measurements, enhancing traditional sensing in integrated photonic chips.
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All authors Haochen Yan, Xu Guo, Arghadeep Pal, Xiaoyuan Huang, Alekhya Ghosh, Lewis Hill, Shuangyou Zhang, Nivedita Vishnukumar, Toby Bi, Masoud Kheyri, Jianming Mai, Hao Zhang, Yaojing Zhang, Jolly Xavier, Haihua Fan, Kok Wai Cheah, Peter Littlewood, Pascal DelHaye

Optics · Cross-listed from quant-ph

Biphoton state generation and engineering with bright hybrid III-V/Silicon photonic devices

Lorenzo Lazzari, Jérémie Schuhmann, Othmane Meskine et al. (+7 more)

Hybrid photonic circuits, harnessing the complementary strengths of multiple materials, represent a key resource to enable compact, scalable platforms for quantum technologies. In particular, the availability of bright sources of tunable biphoton states is eagerly awaited to meet the variety of applications currently under development. In this work we demonstrate a heterogeneously integrated device that merges biphoton generation and on-chip quantum state engineering, combining an AlGaAs photon-pair source with a CMOS-compatible silicon-on-insulator (SOI) circuit. Photon pairs are generated in the C telecom band via spontaneous parametric down-conversion and transferred to the SOI chip through a multimode evanescent coupling scheme. This design achieves a pair generation rate above 10$^{6}$ s$^{-1}$mW$^{-1}$ and a coincidence-to-accidental ratio up to 600. Crucially, the coupling design induces strong and predictable transformations of the biphoton joint spectral amplitude, enabling complex quantum state engineering entirely on-chip in a compact device compliant with electrical pumping.
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All authors Lorenzo Lazzari, Jérémie Schuhmann, Othmane Meskine, Martina Morassi, Aristide Lemaître, Maria I. Amanti, Frédéric Boeuf, Fabrice Raineri, Florent Baboux, Sara Ducci

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

Cathodoluminescence, light injection and EELS in STEM: From comparative to coincidence experiments

Luiz H. G. Tizei, Yves Auad, Florian Castioni et al. (+1 more)

Electron spectroscopy implemented in electron microscopes provides high spatial resolution, down to the atomic scale, of the chemical, electronic, vibrational and optical properties of materials. In this review, we will describe how temporal coincidence experiments in the nanosecond to femtosecond range between different electron spectroscopies involving photons, inelastic electrons and secondary electrons can provide information bits not accessible to independent spectroscopies. In particular, we will focus on nano-optics applications. The instrumental modifications necessary for these experiments are discussed, as well as the perspectives for these coincidence techniques.
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All authors Luiz H. G. Tizei, Yves Auad, Florian Castioni, Mathieu Kociak

Fluid Dynamics

Gravity current propagating against constant and pulsating counter flows

Cem Bingol, Matias Duran-Matute, Eckart Meiburg et al. (+1 more)

This paper describes the evolution of two-dimensional (2D) gravity currents that flow against a horizontally uniform laminar pulsating flow. We study the effect of opposing mean flow amplitude and the oscillatory velocity amplitude on the evolution of the gravity current, the emergence of instabilities due to shear at the interface of heavy and light fluid and unstable density stratification near the bottom wall, and the associated density redistributions. The velocity amplitudes and the oscillation frequency are reminiscent of tidal estuarine flows. This study revealed two key processes affecting the horizontal density transport of the heavy fluid, in addition to the buoyancy-driven propagation of the gravity current. The first process concerns the presence of shear-driven Kelvin-Helmholtz (KH) billows, depending on the strength of the opposing mean flow and the thickness of the gravity current. These KH billows are generated in the inertial phase of gravity current propagation and are responsible for coherent advective transport of heavy-fluid patches away from the gravity current head. The second process is related to the lifting of the gravity current head due to differential advection near the bottom wall when the propagation direction of the gravity current and the oscillating externally imposed flow are in the same direction. It generates a layer of light fluid below the heavy fluid of the gravity current head and becomes unstable when the ambient flow opposes the gravity current propagation, generating Rayleigh-Taylor-like (RT-like) instabilities. This results in a strong vertical redistribution of light and heavy fluid. Non-hydrostatic effects, such as the presence of KH billows and RT-like instabilities, with associated vertical density transport, have significant implications for large-scale horizontal density transport and modeling of salt intrusions in rivers and estuaries.
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All authors Cem Bingol, Matias Duran-Matute, Eckart Meiburg, Herman J.H. Clercx

Medical Physics · Cross-listed from eess.IV

Validation of Fully-Automated Deep Learning-Based Fibroglandular Tissue Segmentation for Efficient and Reliable Quantitation of Background Parenchymal Enhancement in Breast MRI

Yu-Tzu Kuo, Anum S. Kazerouni, Vivian Y. Park et al. (+5 more)

Background parenchymal enhancement (BPE) on breast dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) shows potential as a breast cancer risk marker. Clinically, BPE is qualitatively assessed by radiologists, but quantitative BPE measures offer potential for more precise risk evaluation. This study evaluated an existing open-source, fully-automated deep learning-based (DL-based) method for segmenting fibroglandular tissue (FGT) to quantify BPE and compared it to a semi-automated fuzzy c-means method. Using breast MRI examinations from 100 women, we evaluated segmentation agreement, concordance across quantitative BPE metrics, and associations with qualitative BPE. The quality of FGT segmentations from both methods was scored by a radiologist. While the DL-based and semi-automated methods showed good agreement for quantitative BPE measurements, DL-based measures more strongly correlated with qualitative BPE assessments and DL-based segmentations were scored as higher quality by the radiologist. Our findings suggest that DL-based FGT segmentation enhances efficiency for objective BPE quantification and may improve standardized breast cancer risk assessment.
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All authors Yu-Tzu Kuo, Anum S. Kazerouni, Vivian Y. Park, Wesley Surento, Suleeporn Sujichantararat, Daniel S. Hippe, Habib Rahbar, Savannah C. Partridge

Instrumentation and Detectors

The Use of O2 in Gas Mixtures for Drift Chambers

A.M. Baldini, L. Bianco, H. Benmansour et al. (+20 more)

The use of Oxygen in gas mixtures for drift chambers is highly discouraged because Oxygen, being strongly electronegative, is generally believed to lead, even in very small quantities, to extremely reduced drift electron survival probability, thus preventing the detector's operation.The drift chamber of the MEG II experiment at PSI has been operating for several years with a gas mixture that mainly contains He:Isobutane in relative proportions of 90:10% by molar concentration, in addition to 1.5% Isopropanol and 0.5% Oxygen. Oxygen and Isopropanol are essential for the proper functioning of the chamber. The electron attachment in the mixture used has proven negligible for the proper operation of the chamber and agrees well with the Garfield++ simulation after correctly accounting for the three-body attachment simulation.
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All authors A.M. Baldini, L. Bianco, H. Benmansour, G. Cavoto, F. Cei, M. Chiappini, A. Corvaglia, M. Francesconi, E. Gabbrielli, L. Galli, G. Gallucci, F. Grancagnolo, E.G. Grandoni, M. Grassi, F. Leonetti, D. Nicolo', M. Panareo, D. Pasciuto, A. Papa, F. Renga, S. Scarpellini, A. Venturini, C. Voena

Chemical Physics

Electron-nucleus Araki-Sucher correction in the hydrogen molecule isotopologues

Jacek Komasa

The quantum electrodynamic Araki-Sucher correction arising from the interaction between electrons and nuclei is calculated for rovibrational energy levels of the hydrogen molecule and its isotopologues. The corresponding expectation value $\langle r_{en}^{-3}\rangle$ is evaluated across a wide range of internuclear distances using the Born-Oppenheimer approximation. The electronic wave function is represented as a linear combination of explicitly correlated Gaussian basis functions. This correction contributes approximately tenths of a megahertz (about $10^{-5}$cm$^{-1}$) to the dissociation energy of rovibrational levels and to the transitions between them. Given recent spectroscopic measurements with an accuracy of 10 kHz, this correction is necessary to achieve sub-MHz agreement between theory and experiment.
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Optics

Fano-Like Resonances in Coupled Sagnac Interferometers Formed by a Self-Coupled Waveguide

Hamed Arianfard, Tim Weiss, Yang Yang et al. (+3 more)

We demonstrate Fano-like resonances in silicon-on-insulator (SOI) nanowire-based coupled Sagnac interferometers (SIs) formed by a self-coupled waveguide. By adjusting the reflectivity of the two SIs and coupling strength between them, we tailor coherent mode interference to achieve high-performance optical analogues of Fano resonance. The device is theoretically analyzed and experimentally fabricated on a SOI platform. Theoretical analysis predicts periodic Fano-like resonances with a high extinction ratio and a steep slope rate, arising from strong coherent optical mode interference within a compact resonator comprising two SIs and a connected feedback waveguide. Experimental results align with the theoretical model, validating the expected resonance behavior and confirming the effectiveness of the design. These findings underscore the potential of compact coupled SIs for generating Fano-like resonances, enabling broader applications in integrated photonics.
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All authors Hamed Arianfard, Tim Weiss, Yang Yang, Joshua Bader, Stefania Castelletto, Alberto Peruzzo

Optics

Quantum Thermodynamic Transformation Optics: A Unified Framework for Energy and Entropy with Application to the Casimir Force in Dissipative Metamaterials

Mohammad Mehdi Sadeghi

A novel idea, Quantum Thermodynamic Transformation Optics (QTTO), is introduced in this article. This theoretical framework integrates the geometric formalism of transformation optics with the thermodynamic principles found in quantum dissipative systems. This concept goes beyond traditional coordinate transformations by affecting the distribution of quantum energy and entropy in a coherent thermodynamic manner as well as reshaping electromagnetic fields. By employing the thermofield dynamics approach, we establish new rules that show how local energy and entropy densities are influenced by the Jacobian determinant of the mapping. This indicates that when the geometry is compressed, it increases the generation of quantum energy and entropy density, while expansion has the opposite effect, all while adhering to the laws of conservation and the second law of thermodynamics. As a practical test, we reformulate the Casimir effect within this framework, yielding a continuous pressure law that connects the quantum and classical realms via a thermal weighting function. This relationship illustrates how both geometry and temperature jointly determine quantum pressure. Additionally, our numerical results for Drude-Lorentz metamaterials support our analytical predictions and align closely with the comprehensive Lifshitz-Matsubara formulation. In fact, QTTO offers a powerful and coherent platform for exploring energy, entropy, and quantum pressure in real-world dissipative media. Beyond our immediate findings, it opens up a systematic pathway for managing quantum thermal processes and controlling field fluctuations in metamaterials and curved optical environments.
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History and Philosophy of Physics

The Geometric View of Theories

Sebastian De Haro

Recent critiques of the semantic conception of scientific theories suggest that a theory is not best formulated as a collection of models satisfying some set of kinematical or dynamical conditions. Thus it has been argued that additional structure on the set of models is required. Furthermore, there are calls for developing a `theory of theories', where what was formerly a `theory' is seen as a `model' within a larger theoretical structure. This paper makes a two-pronged proposal for the “shape” that physical theories should take, based on recent insights on dualities and quasi-dualities in physics. First, I develop a geometric view of theories, according to which a physical theory is a set of models equipped with topological and geometric structure. This general view is briefly illustrated in an example from quantum cosmology. Second, I make a more specific proposal for a natural structure that can encompass various `theories' as its models, with topological and algebraic-geometric structure on them. I call the latter more specific structure a `model bundle', where the models are in the fibres and there is a moduli space in the base. I illustrate my second proposal in an example from quantum field theory. This view highlights the important role of quasi-dualities as local transition functions between fibres; dualities are recovered as global transition functions when the bundle is trivial. I discuss some philosophical issues that this geometric view of physical theories opens up, such as its realist interpretation.
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Atomic Physics

Rejection of wavefront aberrations in an atomic gradiometer

Louis Pagot, Sébastien Merlet, Leonid A Sidorenkov et al. (+1 more)

One of the main residual limitations of inertial sensors based on atom interferometry stems from laser beam distortions, which cause parasitic phase shifts and non-homogeneous matter-light couplings. Here we present numerical simulations, accompanied by analytical calculations, which quantify the impact of these effects in a cold atom gradiometer. We demonstrate that the propagation of interferometric laser beam aberrations, combined with initial asymmetry and significant time-of-flight expansion of the the two atomic sources, limit the common-mode rejection of phase noise in a differential configuration. The resulting deviations in gravitational acceleration and its gradient are within reach of current experimental devices. Our study allows us to evaluate the surface quality requirements for retroreflective optics in cold-atom gradiometers of various baselines, and can be extended to other sensors based on different interferometer geometries.
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All authors Louis Pagot, Sébastien Merlet, Leonid A Sidorenkov, Franck Pereira dos Santos

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

Why Extensile and Contractile Tissues Could be Hard to Tell Apart

Jan Rozman, Sumesh P. Thampi and Julia M. Yeomans

Active nematic models explain the topological defects and flow patterns observed in epithelial tissues, but the nature of active stress-whether it is extensile or contractile, a key parameter of the theory-is not well established experimentally. Individual cells are contractile, yet tissue-level behavior often resembles extensile nematics. To address this discrepancy, we use a continuum theory with two-tensor order parameters that distinguishes cell shape from active stress. We show that correlating cell shape and flow, whether in coherent flows in channels, near topological defects, or at rigid boundaries, cannot unambiguously determine the type of active stress. Our results demonstrate that simultaneous measurements of stress and cell shape are essential to fully interpret experiments investigating the nature of the physical forces acting within epithelial cell layers.
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Optics

Digital Twin for Estimating QoT Statistics in Presence of PDL and Transceiver Imperfections

Ambashri Purkayastha, Camille Delezoide, Vinod Bajaj et al. (+3 more)

We propose a physics-based digital twin to predict the statistical QoT distribution of a realistic optical lightpath. We demonstrate up to 0.73 dB accuracy improvement in worst-case SNR prediction for short distance transmissions in linear regime.
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All authors Ambashri Purkayastha, Camille Delezoide, Vinod Bajaj, Mounia Lourdiane, Cédric Ware, Patricia Layec

Optics

Light Focusing through Dynamic Media via Real-Valued Intensity Transmission Matrix

Xuan Liu, Sebastien Ourselin and Tianrui Zhao

Precise light delivery through biological tissue is essential for deep-tissue imaging and phototherapeutic applications. Wavefront shaping enables control over scattered light by modulating the incident wavefront, but its application in living tissue is hindered by tissue-induced temporal decorrelation. This study systematically investigated the real-valued intensity transmission matrix (RVITM), a high-speed wavefront shaping method, for light focusing across a broad range of speckle decorrelation times. The inherent trade-off between static light focusing enhancement and implementation speed is characterized, which provided practical guidelines for implementing RVITM in real-time wavefront shaping under varying dynamic conditions. Effective optical focusing using a RVITM with 33 ms runtime was achieved through porcine liver with decorrelation times as short as 13 ms, demonstrating feasibility for biologically relevant dynamics and supporting the development of adaptive, non-invasive optical control for biomedical applications.
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Atomic Physics

Precision spectroscopy of the $A^2\Pi$ $\leftarrow$ $X^2\Sigma^+$ transition in BaF

M.C. Mooij, H.L. Bethlem, W. Ubachs et al. (+14 more)

High-resolution spectroscopy on the $A^2\Pi$ - $X^2\Sigma^+$ electronic system of $^{138}$Ba$^{19}$F is performed using a cold molecular beam produced by a buffer gas source. The hyperfine structure in both $X^2\Sigma^+$ ground and $A^2\Pi$ excited states is fully resolved and absolute transition frequencies of individual components are measured at the sub-MHz level making use of frequency-comb laser calibration. Sets of molecular constants for the $X^2\Sigma^+$($v=0,1$) and $A^2\Pi$($v=0,1$) levels are determined, with improved accuracy for the $T_{v',v''}$ band origins and spin-orbit interaction constants for the $A^2\Pi$ excited states, that represent the presently measured highly accurate transitions for low-$J$ states as well as previously determined transition frequencies in Fourier-transform emission studies for rotational levels as high as $J \geq 100$. The extracted molecular constants reproduce the measured transition frequencies at the experimental absolute accuracy of 1 MHz. The work is of relevance for future laser cooling schemes, and is performed in the context of a measurement of the electron dipole moment for which BaF is a target system.
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All authors M.C. Mooij, H.L. Bethlem, W. Ubachs, P. Aggarwal, A. Boeschoten, A. Borschevsky, Y. Chamorro, M. Denis, T.H. Fikkers, S. Hoekstra, J.W.F. van Hofslot, S.A. Jones, V.R. Marshall, T.B. Meijknecht, R.G.E. Timmermans, J. de Vries, L. Willmann