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Physics Physics

physics Watch Physics

Monday 13 October

Optics · Cross-listed from cond-mat.mtrl-sci

Deterministic hBN bubbles as a versatile platform for studies on single-photon emitters

Piotr Tatarczak, Tomasz Fąs, Jan Pawłowski et al. (+5 more)

Single-photon emitters (SPEs) in two-dimensional materials are highly promising candidates for quantum technologies. SPEs in hexagonal boron nitride (hBN) have been widely investigated, but mostly in exfoliated or powder samples that require an activation process, making it difficult to compare studies and reproduce results. Here, we address this problem and propose a platform based on large-area metaloraganic vapour phase epitaxy (MOVPE)-grown hBN, which combines reproducibility and scalability with the ability to readily host SPEs without activation. Through the creation of bubbles via electron-beam irradiation, we achieve additional functionalities, including an interference-mediated enhancement of emission by approximately 100-200%, dedicated structures that allow the relocation of individual emitters across different systems, and the opportunity to investigate strain-induced effects. Moreover, in contrast to other gas-filled bubbles that deflate at low temperatures, our bubbles remain stable under cryogenic conditions, allowing studies as a function of temperature. To improve the control over the shape and position of bubbles, we demonstrate a~mask-based method that enables deterministic control over bubble formation. The presented hBN bubbles constitute a versatile platform for reproducible studies of hBN-based emitters, providing a reliable insight into their nature and properties.
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All authors Piotr Tatarczak, Tomasz Fąs, Jan Pawłowski, Aleksandra Krystyna Dąbrowska, Jan Suffczyński, Piotr Wróbel, Andrzej Wysmołek, Johannes Binder

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

Ab-initio calculation of magnetic exchange interactions using the spin-spiral method in VASP: Self-consistent versus magnetic force theorem approaches

Umit Dogan Daglum, Maria Stamenova, Ersoy Sasioglu et al. (+1 more)

We present an ab initio investigation of magnetic exchange interactions using the spin-spiral method implemented in the VASP code, with a comparative analysis of the self-consistent (SC) and magnetic force theorem (MFT) approaches. Using representative 3d ferromagnets (Fe, Co, Ni) and Mn-based full Heusler compounds, we compute magnon dispersion relations directly from spin-spiral total energies and extract real-space Heisenberg exchange parameters via Fourier transformation. Curie temperatures are subsequently estimated within both the mean-field and random-phase approximations. The SC spin-spiral calculations yield exchange parameters and magnon spectra in excellent agreement with previous theoretical data, confirming their quantitative reliability across different classes of magnetic systems. In contrast, the MFT approach exhibits systematic quantitative deviations: it overestimates spin-spiral energies and exchange couplings in high-moment systems such as bcc Fe and the Mn-based Heuslers, while underestimating them in low-moment fcc Ni. The magnitude of these discrepancies increases strongly with magnetic moment size, exceeding several hundred percent in the high-moment compounds. These findings underscore the decisive role of self-consistency in accurately determining magnetic exchange parameters and provide practical guidance for future first-principles studies of spin interactions and excitations using the spin-spiral technique.
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All authors Umit Dogan Daglum, Maria Stamenova, Ersoy Sasioglu, Stefano Sanvito

Fluid Dynamics

A framework for realisable data-driven active flow control using model predictive control applied to a simplified truck wake

Alberto Solera-Rico, Carlos Sanmiguel Vila and Stefano Discetti

We present a data-driven active flow control framework designed for deployment with few non-intrusive sensors. The method builds upon Artificial Intelligence driven reduced-order predictive models based on Long-Short-Term Memory (LSTM) networks and efficient gradient-based Model Predictive Control (MPC). The model uses only surface-mounted pressure probes to infer the wake state, and is trained entirely offline on a dataset built with open-loop actuations, thus avoiding the complexities of online learning. Sparsification of the sensors needed for control from an initially large set is achieved using SHapley Additive exPlanations (SHAP). A parsimonious set of sensors is then deployed in closed-loop control with MPC. The framework is tested in numerical simulations of a two-dimensional truck model at Reynolds number 500, with pulsed-jet actuators placed in the rear of the truck to control the wake. The resulting LSTM-MPC achieved a drag reduction of 12.8%.
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Atomic Physics · Cross-listed from quant-ph

Telecom-compatible cross-band quantum memory via dual photon modes dark-state polaritons

Dounan Du and Eden Figueroa

Quantum memories are essential components of quantum networks, enabling synchronization, quantum repeaters, and long-distance entanglement distribution. Most ensemble-based realizations rely on dark-state polaritons (DSPs) in $\Lambda$-type systems that operate at near-infrared wavelengths, such as 795 nm in $^{87}$Rb, far from the telecom band where long fiber transmission is optimal. Here we identify a DSP in $^{87}$Rb that coherently couples two photonic modes at 795 nm and 1324 nm through a shared spin-wave coherence. We derive its field operator and group velocity, extending the Fleischhauer-Lukin model to a dual-wavelength regime, and formulate a memory protocol enabling bidirectional storage and retrieval between the two modes. Numerical simulations of the full six-level dynamics confirm two-way storage and retrieval for both same-mode and cross-mode operation between the two wavelengths. The results demonstrate a dual-wavelength memory that unifies node-band and telecom-band operation within a single ensemble, providing a potential route toward frequency-conversion-free quantum-network interfaces.
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Computational Physics · Cross-listed from cond-mat.soft

Disorder to Order Transition in 1D non-reciprocal Cahn-Hilliard Model

Navdeep Rana and Ramin Golestanian

We present the phenomenology of the one dimensional non-reciprocal Cahn Hilliard model for varying non-reciprocity $(\alpha)$ and different boundary conditions. At small $\alpha$, a perturbed uniform state evolves to a defect laden configuration that lacks global polar order. Defects are the sources and sinks of travelling waves. For a given $\alpha$, defects with a unique wave number that increases monotonically with $\alpha$ are selected. A critical threshold $\alpha_c$ marks the onset of a transition to states with finite global polar order. For periodic boundary conditions, above $\alpha_c$, the system shows travelling waves that are completely ordered. In contrast, travelling waves are incompatible with the Neumann and Dirichlet boundary conditions. Instead, for $\alpha \gtrsim \alpha_c$, we find fluctuating domains that show intermittent polar order and at large $\alpha$, the system partitions into two domains with opposite polar order.
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Applied Physics

Elastic Rod Origami (RodOri) for Programming Static and Dynamic Mechanical Properties

Sophie Leanza, Jeseung Lee and Ruike Renee Zhao

Reconfigurable mechanical systems enable precise programmable control over structural properties, opening new opportunities in architected materials, adaptive devices, and multifunctional structures. Here, we introduce elastic rod origami (RodOri), a platform that exploits remarkably simple elements (pre-stressed, naturally curved rods) into a system with an extraordinary degree of multistability and configurational richness. For example, a single 6-rod RodOri unit can easily access 11 distinct configurations, far exceeding the reconfigurability of conventional origami or general mechanical reconfigurable systems. Individual rods, constrained under clamped boundary conditions, undergo snapping transitions between discrete morphologies whose strain energy and stiffness are precisely prescribed by their natural curvature. Assembling these rods into modular multi-rod architectures yields metamaterials with numerous stable configurations that can be selectively and reversibly programmed. This configurational diversity enables tunable static stiffness, nonlinear force response, and thus enables tunable dynamic behaviors such as vibration filtering, wave-propagation switching, and mode conversion within a single, easily-manufactured platform. By leveraging curvature-induced mechanical instability, RodOri unlocks highly programmable static and dynamic mechanical behavior, offering new design strategies in reconfigurable structures, soft robotics, medical devices, and adaptive materials.
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Computational Physics

Optimal parallelisation strategies for flat histogram Monte Carlo sampling

Hubert J. Naguszewski, Christopher D. Woodgate and David Quigley

Flat histogram methods, such as Wang–Landau sampling, provide a means for high-throughput calculation of phase diagrams of atomistic/lattice model systems. Many parallelisation schemes with varying degrees of complexity have been proposed to accelerate such sampling simulations. In this study, several widely used schemes are benchmarked – both in isolation and in combination – to establish best practice. The schemes studied include energy domain decomposition with both static sizing of energy sub-domains, as well as a dynamic sub-domain sizing scheme which we propose. We also assess the benefits both of replica exchange and of including multiple random walkers per sub-domain, to determine which factors have the largest impact on parallel efficiency. Additionally, the influence of energy sub-domain overlap regions is discussed. As illustrative test cases, we implement and apply the aforementioned strategies to a lattice-based model describing the internal energy of a substitutional alloy, studying the AlTiCrMo refractory high-entropy superalloy as well as the binary CuZn system, both of which crystallographically order into a B2 (CsCl) structure with decreasing temperature. We find that – while all of the proposed strategies confer a non-negligible speedup – parallelisation across energy domains which are non-uniform in size offers the most appreciable performance improvements. This work offers concrete recommendations for which parallelisation strategies should be prioritised to optimally accelerate flat-histogram Monte Carlo simulations.
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Applied Physics

Unlocking High-Throughput Heterojunction Discovery

Thomas W. Gries, Davide Regaldo, Yanyan Duan et al. (+8 more)

Photoluminescence (PL) is a ubiquitous proxy for material quality in optoelectronic devices, widely used for high-throughput materials discovery. However, we demonstrate that in the presence of charge-selective contacts, PL loses its predictive reliability and can exhibit strong quenching even in highly efficient photovoltaic devices under open-circuit conditions. By combining steady-state and transient PL with contactless transient surface photovoltage measurements we disentangle the intertwined processes of extraction and recombination, clarifying the physical origin of this phenomenon. This joint approach reveals extraction dynamics not captured by PL alone. A digital replica of the interface shows that Coulomb attraction and interfacial recombination are the fundamental mechanisms driving quenching after charge extraction. Based on these insights, we present a decision tree for heterojunction classification and PL interpretation applicable across diverse optoelectronic systems, including photovoltaics, photodetectors, and LEDs. Our approach supports systematic screening and optimization of half-devices, bridging the gap between accelerated materials discovery and accelerated device discovery.
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All authors Thomas W. Gries, Davide Regaldo, Yanyan Duan, Florian Scheler, Maxim Simmonds, Valerio Stacchini, Annamaria Petrozza, Eva Unger, Antonio Abate, Jean-Paul Kleider, Artem Musiienko

History and Philosophy of Physics · Cross-listed from quant-ph

French on London and Bauer, and QBism

Jacques L. Pienaar

In this article I compare two interpretations of quantum mechanics (QM) that draw inspiration from phenomenology: the London-Bauer-French interpretation (hereafter LBF) as articulated by Steven French, and QBism. I give special attention to certain disagreements between QBism and LBF identified French's work, as well as French's related claims that QBism may be at odds with key ideas in phenomenology. My main finding is that QBism does not fare so badly with phenomenology as French makes out; in particular it can be made compatible with Zahavi's correlationism and Husserl's notion of intersubjectivity, both of which strongly inform LBF. Nevertheless, I concur with French's argument that QBism is incompatible with the conception of quantum measurement in LBF, hence also with that of Merleau-Ponty, as the latter based his own analysis on that of London and Bauer. I explain why I find QBism's account preferable in this case.
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Physics and Society

A Self-Organized Tower of Babel: Diversification through Competition

Riz Fernando Noronha and Kunihiko Kaneko

We introduce a minimal evolutionary model to show how local cooperation and global competition can create a transition to the diversity of communities such as linguistic groups. By using a lattice model with high-dimensional state agents and evolution under a fitness that depends on an agent's local neighborhood and global dissimilarity, clusters of diverse communities with different fitness are organized by equalizing the finesses on the boundaries, where their numbers and sizes are robust to parameters. We observe successive transitions over quasi-stationary states, as triggered by the emergence of new communities on the boundaries. Our abstract framework provides a simple mechanism for the diversification of culture.
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Optics

A review of cultural heritage inspection: Toward terahertz from mid-infrared region

Pengfei Zhu, Hai Zhang, Stefano Sfarra et al. (+2 more)

This review explores non-invasive imaging (NII) methods covering the mid- and far-infrared to the terahertz spectral regions (up to approximately 1000 um) for the detection and analysis of cultural heritage artifacts. In the thermal infrared domain, where radiation follows Planck's law, the self-emission of materials reveals intrinsic properties and internal degradation. By contrast, in the near-infrared range, external illumination enhances surface details and pigment differentiation. Far-infrared and terahertz techniques, operating in both transmission and reflection modes, provide complementary insights by penetrating surface layers to uncover subsurface structures and concealed features. Integrating visible and infrared imaging further enriches diagnostic capabilities by correlating conventional visual assessments with spectral information. Beyond reviewing the wide applications of these NII techniques in cultural heritage research, this work also summarizes recent advances in signal processing, encompassing both hardware and software developments. In particular, deep learning has revolutionized the field by enabling automated classification, feature extraction, defect detection, and super-resolution imaging. Through supervised and unsupervised learning strategies, neural networks can reliably identify subtle anomalies and material variations indicative of past restorations or early stages of deterioration. In conclusion, the convergence of advanced spectral imaging, sophisticated signal processing, and deep neural networks offers a transformative pathway toward more accurate, efficient, and data-driven cultural heritage analysis, ultimately supporting more informed conservation and restoration decisions.
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All authors Pengfei Zhu, Hai Zhang, Stefano Sfarra, Dazhi Yang, Xavier Maldague

Instrumentation and Detectors

Towards polarization-enhanced PET: Study of random background in polarization-correlated Compton events

Ana Marija Kožuljević, Tomislav Bokulić, Darko Grošev et al. (+5 more)

Positron Emission Tomography (PET) is a medical imaging modality that utilizes positron-emitting isotopes, such as Ga-68 and F-18, for many diagnostic purposes. The positron annihilates with an electron from the surrounding area, creating two photons of 511 keV energy and opposite momenta, entangled in their orthogonal polarizations. When each photon undergoes a Compton scattering process, the difference of their azimuthal scattering angles reflects the initial orthogonality of their polarizations, peaking at $\pm$90$^{\circ}$. This type of correlation is not yet utilized in conventional PET scanners, but could potentially offer an energy-independent method for background reduction. Measurements of these kinds of correlations can be achieved using Compton polarimeters, built from a single layer of segmented scintillating crystals such as Gadolinium Aluminium Gallium Garnet doped with Cerium (GAGG:Ce), read out by silicon photomultipliers (SiPMs). In this paper, we study the signal-to-random background ratios in measurements of these correlated annihilation photons from coincidence time spectra across clinically relevant source activities, from $\sim$200 MBq to $\sim$378 MBq. These are then compared to the standard single-pixel (photoelectric) measurements. We find that the signal-to-random background ratios (SBRs) obtained from the polarization-correlated events for Compton scattering angles $\theta_{1,2}\in[72^{\circ}, 90^{\circ}]$ and azimuthal angle difference $\Delta\phi=90^{\circ}\pm20^{\circ}$ are consistently higher than those from single-pixel events, with the ratio of their SBR values of 1.23. The SBR of the selected events also increases with the polarimetric modulation factor $\mu$, gaining $\sim$50% in value during the experiment.
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All authors Ana Marija Kožuljević, Tomislav Bokulić, Darko Grošev, Siddharth Parashari, Luka Pavelić, Marinko Rade, Marijan Žuvić, Mihael Makek

Computational Physics · Cross-listed from math.NA

Structure-preserving finite element approximations of a hybrid relativistic cold fluid-particle model

Tileuzhan Mukhamet and Katharina Kormann

We derive mixed finite element discretizations of a cold relativistics fluid model from approximations of the Poisson bracket that preserve mass, energy and the divergence constraints. For time-discretization we derive an implicit energy-conserving average-vector field method or apply an explicit strong-stability preserving Runge-Kutta scheme. We also consider a coupling of the fluid model to relativistic particles. We perform a numerical study of the scheme which shows convergence and conservation properties of the proposed methods and apply the new scheme to a plasma wake field simulation.
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Optics

Efficient Lasing in MoS$_2$/WSe$_2$-Based Metasurfaces Enabled by Quasi-Dark Magnetic Dipole Resonance

Georgios Nousios, Thomas Christopoulos, Emmanouil E. Kriezis et al. (+1 more)

The novel combination of a strongly-resonant optical metasurface with the MoS$_2$/WSe$_2$ hetero-bilayer is proposed for efficient free-space lasing enabled by the enhanced coupling between the optical and matter (exciton) states. The metasurface comprises silicon-rich nitride meta-atoms periodically arrayed in a subdiffractive lattice and overlaid with MoS$_2$/WSe$_2$, which provides optically-pumped gain around $1130~\mathrm{nm}$. Light emission is enabled by exploiting a quasi-bound state in the continuum in the form of a perturbed vertical magnetic dipole resonance. Following a meticulous design process guided by full-wave simulations and multipole expansion analysis, an ultralow lasing threshold of $\sim 6~\mathrm{kW/cm^2}$ is achieved. Moreover, the thermal stability of the lasing structure is examined through heat transfer simulations; stable operation with pump power densities up to a few MW/cm$^2$ (three orders of magnitude above the threshold) is predicted. These results demonstrate that MoS$_2$/WSe$_2$-based metasurface lasers can exhibit robust operation, paving the way for highly-performing ultrathin light-emitting surfaces. The lasing response is rigorously assessed through a highly-efficient temporal coupled-mode theory framework, verified by time-domain FEM simulations showing excellent agreement. Thus, an efficient and accurate approach to design and study metasurface lasers with arbitrary geometries and surface or bulk gain media is introduced, exhibiting significant advantages over cumbersome full-wave simulations.
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All authors Georgios Nousios, Thomas Christopoulos, Emmanouil E. Kriezis, Odysseas Tsilipakos

Instrumentation and Detectors

Optimised neural networks for online processing of ATLAS calorimeter data on FPGAs

Georges Aad, Raphael Bertrand, Lauri Laatu et al. (+4 more)

A study of neural network architectures for the reconstruction of the energy deposited in the cells of the ATLAS liquid-argon calorimeters under high pile-up conditions expected at the HL-LHC is presented. These networks are designed to run on the FPGA-based readout hardware of the calorimeters under strict size and latency constraints. Several architectures, including Dense, Recurrent (RNN), and Convolutional (CNN) neural networks, are optimised using a Bayesian procedure that balances energy resolution against network size. The optimised Dense, CNN, and combined Dense+RNN architectures achieve a transverse energy resolution of approximately 80 MeV, outperforming both the optimal filtering (OF) method currently in use and RNNs of similar complexity. A detailed comparison across the full dynamic range shows that Dense, CNN, and Dense+RNN accurately reproduce the energy scale, while OF and RNNs underestimate the energy. Deep Evidential Regression is implemented within the Dense architecture to address the need for reliable per-event energy uncertainties. This approach provides predictive uncertainty estimates with minimal increase in network size. The predicted uncertainty is found to be consistent, on average, with the difference between the true deposited energy and the predicted energy.
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All authors Georges Aad, Raphael Bertrand, Lauri Laatu, Emmanuel Monnier, Arno Straessner, Nairit Sur, Johann C. Voigt

Instrumentation and Detectors

Characterisation of the first wafer-scale prototype for the ALICE ITS3 upgrade: the monolithic stitched sensor (MOSS)

Omar Abdelrahman, Gianluca Aglieri Rinella, Luca Aglietta et al. (+136 more)

This paper presents the characterisation and testing of the first wafer-scale monolithic stitched sensor (MOSS) prototype developed for the ALICE ITS3 upgrade that is to be installed during the LHC Long Shutdown 3 (2026-2030). The MOSS chip design is driven by the truly cylindrical detector geometry that imposes that each layer is built out of two wafer-sized, bent silicon chips. The stitching technique is employed to fabricate sensors with dimensions of 1.4 $\times$ 25.9 cm, thinned to 50 $\mu$m. The chip architecture, in-pixel front-end, laboratory and in-beam characterisation, susceptibility to single-event effects, and series testing are discussed. The testing campaign validates the design of a wafer-scale stitched sensor and the performance of the pixel matrix to be within the ITS3 requirements. The MOSS chip demonstrates the feasibility of the ITS3 detector concept and provides insights for further optimisation and development.
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All authors Omar Abdelrahman, Gianluca Aglieri Rinella, Luca Aglietta, Giacomo Alocco, Matias Antonelli, Roberto Baccomi, Francesco Barile, Pascal Becht, Franco Benotto, Stefania Maria Beolè, Marcello Borri, Daniela Bortoletto, Naseem Bouchhar, Giuseppe Eugenio Bruno, Matthew Daniel Buckland, Szymon Bugiel, Paolo Camerini, Francesca Carnesecchi, Marielle Chartier, Domenico Colella, Angelo Colelli, Giacomo Contin, Giuseppe De Robertis, Wenjing Deng, Antonello Di Mauro, Vittorio Di Trapani, Maurice Donner, Ana Dorda Martin, Piotr Dorosz, Floarea Dumitrache, Lars Döpper, Gregor Hieronymus Eberwein, Domenico Elia, Simone Emiliani, Laura Fabbietti, Tommaso Fagotto, Xiaochao Fang, Henrik Fribert, Roman Gernhäuser, Piero Giubilato, Laura Gonella, Karl Gran Grodaas, Ola Slettevoll Groettvik, Vladimir Gromov, Malte Grönbeck, Philip Hauer, Hartmut Hillemanns, Guen Hee Hong, Yu Hu, Minyoung Chris Hwang, Marc Alain Imhoff, Barbara Jacak, Daniel Matthew Jones, Antoine Junique, Filip Křížek, Jetnipit Kaewjai, Anouk Kaiser, Jesper Karlsson Gumprecht, Markus Keil, Bernhard Ketzer, Jiyoung Kim, Lena Kirchner, Kritsada Kittimanapun, Alex Kluge, Chinorat Kobdaj, Artem Kotliarov, Thanushan Kugathasan, Marc König, Paola La Rocca, Natthawut Laojamnongwong, Lukas Lautner, Corentin Lemoine, Long Li, Beatrice Eva Liang-Gilman, Francesco Licciulli, Sanghoon Lim, Bong-Hwi Lim, Jian Liu, Flavio Loddo, Matteo Lupi, Magnus Mager, Philipp Mann, Georgios Mantzaridis, Davide Marras, Paolo Martinengo, Silvia Masciocchi, Annalisa Mastroserio, Soniya Mathew, Serena Mattiazzo, Marius Wilm Menzel, Nicola Minafra, Frederic Morel, Alice Mulliri, Anjali Ila Nambrath, Rajendra Nath Patra, Iaroslav Panasenko, Styliani Paniskaki, Caterina Pantouvakis, Cosimo Pastore, Stefania Perciballi, Francesco Piro, Adithya Pulli, Alexander Rachev, Alexander Rachevski, Ivan Ravasenga, Felix Reidt, Michele Rignanese, Giacomo Ripamonti, Isabella Sanna, Valerio Sarritzu, Umberto Savino, Iain Sedgwick, Serhiy Senyukov, Danush Shekar, Sabyasachi Siddhanta, David Silvermyr, Walter Snoeys, Joey Staa, Alessandro Sturniolo, Miljenko Šuljić, Timea Szollosova, Daniel Tapia Takaki, Livia Terlizzi, Nicolas Tiltmann, Antonio Trifirò, Christina Tsolanta, Rosario Turrisi, Berkin Ulukutlu, Gianluca Usai, Isabelle Valin, Giovanni Vecil, Pedro Vicente Leitao, Anna Villani, Chunzheng Wang, Zhenyu Ye, Emma Rose Yeats, Asli Yelkenci, Zijun Zhao, Alessandra Zingaretti

Optics

Astigmatism-free 3D Optical Tweezer Control for Rapid Atom Rearrangement

Yue-Hui Lu, Nathan Song, Tai Xiang et al. (+4 more)

Reconfigurable neutral-atom arrays are a promising platform for quantum computing, quantum simulation, and quantum metrology, but atom transport using frequency-chirped acousto-optic deflectors (AODs) is limited by chirp-induced acoustic lensing and trajectory distortion. We address these limitations using a three-dimensional acousto-optic deflector lens (3D-AODL), a design predicted to reduce long-range transport times by more than a factor of two. We further introduce fading-Shepard waveforms that circumvent finite AOD bandwidth, enabling sustained axial displacement. We demonstrate unrestricted three-dimensional optical-tweezer motion over a 200 $\mu$m $\times$ 200 $\mu$m $\times$ 136 $\mu$m volume with velocities exceeding 4.2 m/s. Arbitrary three-dimensional control of optical-tweezer trajectories enables rapid atom rearrangement and dynamical engineering of optical potentials in tweezer arrays and optical lattices. This capability advances quantum control and atom manipulation in neutral-atom quantum processors by enabling faster rearrangement, higher clock rates, and scalable sorting in complex geometries.
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All authors Yue-Hui Lu, Nathan Song, Tai Xiang, Jacquelyn Ho, Tsai-Chen Lee, Zhenjie Yan, Dan M. Stamper-Kurn

Geophysics

The impact of observation losses on IVS-R1/R4 VLBI sessions

Tiege McCarthy and Lucia McCallum

Global VLBI observations, to measure Earth orientation and station positions, are organised into 24-hour sessions. Each session has a bespoke schedule created, optimised for the particular time period and the station network that is available during it. Due to various factors, whether it be station outages, sensitivity issues or source effects, not all scheduled observations are available, or of sufficient quality, to be included in the final geodetic analysis. In this paper we derive statistics about the number of missing observations, as well as their effect on the expected precision of geodetic parameters such as station positions and Earth Orientation Parameters. We investigate the impact of observation loss on the weekly rapid turnaround IVS-R1 and IVS-R4 geodetic VLBI sessions over a decade period from 2014 - 2023. Across our 1030 sessions we find on average 25.3% of observations scheduled do not make it to analysis. This results in median performance losses, when compared to the scheduled versions, of 18.8%, 19.2%, 12.1/11.3% and 28.7/22.9% for UT1-UTC, 3D station position, X/Y nutation and x/y polar motion respectively. We find that the estimation of X/Y nutation is particularly robust to typical observation loss seen from these 24-hour sessions. Conversely, we see high-rates of critical degradation in performance (a doubling of the scheduled repeatability) for other geodetic parameters at observations losses of between 15 - 19%, which is less than the median loss of 25.3% that we find across this 10-year period.
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Applied Physics

Raman Microspectroscopy for Real-Time Structure Indicator in Ultrafast Laser Writing

Xingrui Cheng, Eugenio Picheo, Zhixin Chen et al. (+3 more)

Femtosecond laser fabrication enables the creation of a wide range of devices, but its scalability and yield can be limited by the lack of real-time, in-situ monitoring tools. In particular, there is a strong need for metrics that directly correlate with device performance. Raman microspectroscopy provides a non-destructive route for in-situ characterization. Here, we demonstrate its potential to assess the electrical performance of laser-written graphitic electrodes in diamond. By combining hyperspectral mapping with electrical testing, we show that depletion of the 1332 cm$^{-1}$ sp3 Raman line serves as a monotonic and robust predictor of resistance, offering clear advantages over commonly used spectral features. We further introduce hyperspectral unmixing as a label-free approach to identify relevant spectral signatures in fabrication processes where Raman markers are less defined. Importantly, the methodology we present is not restricted to diamond but can be adapted to other host materials and functionalities, offering a practical path toward specification-driven fs-laser microfabrication.
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All authors Xingrui Cheng, Eugenio Picheo, Zhixin Chen, Martin J. Booth, Patrick S. Salter, Álvaro Fernández-Galiana

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

Observational study of chromospheric jets in and around a sunspot observed by NVST and SDO

Guotang Wu, Xiaoli Yan, Zhike Xue et al. (+8 more)

To better understand the characteristics, driving mechanisms, and potential heating contributions of chromospheric jets, we analyze two contrasting types: one originating from within the sunspot penumbra (inside jets), and the other originating from outside the penumbra (outside jets). Statistical analysis of 100 jets (50 inside jets and 50 outside jets) reveals that inside jets have a projected velocity range of 4–14~km\,s$^{-1}$, a length range of 1–4~Mm, a width range of 0.2–0.6~Mm, and a lifetime range of 135–450~s, with mean values of 7.90~km\,s$^{-1}$, 2.61~Mm, 0.41~Mm, and 260~s, respectively. About 52% of inside jets are associated with brightenings in H$\alpha$ blue wing images, and some show high-temperature signatures, suggesting a connection with localized energy release. In contrast, outside jets have higher velocities (8–50~km\,s$^{-1}$, average 19.04~km\,s$^{-1}$), greater lengths (average 6.26~Mm, up to 27.27~Mm), slightly larger widths (average 0.46~Mm), and longer lifetimes (135–630~s, average 327~s). They typically originate from regions of opposite magnetic polarities and are associated with magnetic flux emergence and EUV brightenings. Some outside jets correspond to coronal jets with inverted Y-shaped structures and temperatures exceeding one million Kelvin. Our results suggest that both jet types are driven by magnetic reconnection occurring in distinct magnetic field configurations and contribute to chromospheric and coronal heating.
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All authors Guotang Wu, Xiaoli Yan, Zhike Xue, Jincheng Wang, Zhe Xu, Liheng Yang, Yian Zhou, Liping Yang, Xinsheng Zhang, Qifan Dong, Zongyin Wu

Fluid Dynamics

A novel spatial distribution method for wind farm parameterizations based on the Gaussian function

Bowen Du, Qi Li, Mingwei Ge et al. (+2 more)

Wind farm parameterizations are crucial for quantifying the wind-farm atmosphere interaction, where wind turbines are typically modeled as elevated momentum sinks and sources of turbulence kinetic energy (TKE). These quantities must be properly distributed to the mesoscale grid. Existing parameterizations use the single-column method. However, this method can easily lead to the errors of the spatial distribution of the sink and source, thereby impacting the accuracy of mesoscale flow simulations. To this end, we propose a multi-column spatial distribution method based on the Gaussian function. This method distributes the sink and source to multiple vertical grid columns based on the grid weights, which are analytically determined by integrating the two-dimensional Gaussian function over the mesoscale grid. We have applied this method to the classic Fitch model, proposed the improved Fitch-Gaussian model, and integrated it into the mesoscale Weather Research and Forecasting model. Using high-fidelity large eddy simulation as a benchmark, we compared the performance of the proposed method with the single-column method. The results show that the proposed method captures the spatial distribution of the sink and source more accurately, with a higher correlation coefficient and lower normalized root mean square error. Furthermore, the Fitch-Gaussian model better captures the overall spatial distribution patterns of velocity deficit and added TKE. Therefore, the proposed method is recommended for future mesoscale wind farm simulations, especially when the influence of the wind turbine rotor spans multiple mesoscale grid columns.
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All authors Bowen Du, Qi Li, Mingwei Ge, Xintao Li, Yongqian Liu

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

Electromagnetic Observables of Weakly Collisional Black Hole Accretion

Vedant Dhruv, Ben Prather, Mani Chandra et al. (+2 more)

The black holes in the Event Horizon Telescope sources Messier 87* and Sagittarius A* (SgrA*) are embedded in a hot, collisionless plasma that is fully described in kinetic theory yet is usually modeled as an ideal, magnetized fluid. In this Letter, we present results from a new set of weakly collisional fluid simulations in which leading order kinetic effects are modeled as viscosity and heat conduction. Consistent with earlier, lower-resolution studies, we find that overall flow dynamics remain very similar between ideal and non-ideal models. For the first time, we synthesize images and spectra of SgrA* from weakly collisional models – assuming an isotropic, thermal population of electrons – and find that these remain largely indistinguishable from ideal fluid predictions. However, most weakly collisional models exhibit lower light curve variability, with all magnetically dominated models showing a small but systematic decrease in variability.
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All authors Vedant Dhruv, Ben Prather, Mani Chandra, Abhishek V. Joshi, Charles F. Gammie

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

Electron-phonon coupling in magnetic materials using the local spin density approximation

Á. A. Carrasco Álvarez, M. Giantomassi, J. Lihm et al. (+4 more)

Magnetic materials are crucial for manipulating electron spin and magnetic fields, enabling applications in data storage, spintronics, charge transport, and energy conversion, while also providing insight into fundamental quantum phenomena. In numerous applications, the interaction between electrons and lattice vibrations, known as electron-phonon coupling, can be of significant importance. In that regard, we extend the EPW package to be able to interpolate the electron-phonon matrix elements combining perturbation theory and maximally localized Wannier functions. This allows to use dense momentum grids at a reasonable computational cost when computing electron-phonon-related quantities and physical properties. We validate our implementation considering ferromagnetic iron and nickel, where we explore the phonon induced mass enhancement and Eliashberg spectral function finding different importance of each spin channel for both compounds. Furthermore, we evaluate the carrier resistivity at finite temperatures for both systems, considering the role of the magnetic phase in carrier transport. Our findings indicate that in the case of Fe, the primary contributor to resistivity is electron-phonon scattering. In contrast, for Ni, electron-phonon scattering constitutes less than one-third of the resistivity, underscoring a fundamental difference in the transport properties of the two systems.
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All authors Á. A. Carrasco Álvarez, M. Giantomassi, J. Lihm, G. E. Allemand, M. Mignolet, M. Verstraete, S. Poncé

History and Philosophy of Physics · Cross-listed from quant-ph

Relative Information, Relative Facts

Andrea Di Biagio and Carlo Rovelli

We offer a fresh perspective on the relational interpretation of quantum mechanics as a way of thinking about the world described by quantum theory based on quantifiable notions of information. This allows us to provide a definition of a relative fact, with no addition to orthodox quantum theory and no fundamentally special role for observers. By associating perspectives with commutative observables rather than entire quantum systems, several previous problems with the interpretation are dissolved. As a side result, we show how a quantum measurement, properly described, is a continuous process.
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Biological Physics · Cross-listed from cond-mat.soft

Behavior of passive polymeric tracers of different topologies in a dilute bath of active Brownian particles

Ramanand Singh Yadav, Ralf Metzler and Rajarshi Chakrabarti

Using computer simulations in two dimensions we investigate the dynamics and structure of passive polymeric tracer with different topologies immersed in a low-density active particle bath. One of the key observations is that polymer exhibit faster dynamics compared to passive colloidal particles at high activity, for the same particle density, in both linear and star polymer topologies. This enhanced motion is attributed to the accumulation of active particles, which induces prolonged and persistent movement of the polymer. Further analysis reveals that star polymers exhibit more complex and intriguing behavior than their linear counterparts. Notably, the accumulation of active particles promotes the pairing of arms in star polymers. For instance, a three-armed star polymer adopts a conformation similar to a linear polymer with two-arms due to this pairing as a result, at high activity, the dynamics of both the polymers converge. Finally, we explore the dynamics of a linear polymer with the same total number of beads as the star polymer. Interestingly, at high activity – where arm pairing in the star polymer is significant – the star polymer demonstrates faster dynamics than the linear polymer, despite having the identical number of beads. These findings contribute to a broader understanding of the interactions between active and passive components of varying topologies in dilute systems and highlight their potential for innovative applications ranging from materials science to biomedicine.
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Applied Physics

A variational phase-field model for anisotropic fracture accounting for multiple cohesive lengths

Angela Maria Fajardo Lacave, Francesco Vicentini, Fabian Welschinger et al. (+1 more)

We propose a novel variational phase-field model for fracture in anisotropic materials. The model is specifically designed to allow a more flexible calibration of crack nucleation than existing anisotropic fracture formulations, while avoiding the introduction of multiple damage variables. In addition to the classical components of anisotropic phase-field models based on a single damage variable – namely, anisotropic elasticity and the extension of the fracture energy density via a second-order structural tensor – the proposed approach introduces fracture anisotropy through a cohesive degradation function with potentially distinct cohesive lengths along the principal material directions. For this reason, we refer to it as multi-cohesive model. This feature enables independent control of the critical stresses governing crack nucleation in each material direction. We analyze the homogeneous solution and its second-order stability, and we compare the resulting strength surfaces with those of two representative anisotropic phase-field models available in the literature. Finally, numerical simulations in two and three dimensions demonstrate the capability of the proposed model to independently control crack nucleation and propagation in anisotropic fracture problems of increasing complexity.
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All authors Angela Maria Fajardo Lacave, Francesco Vicentini, Fabian Welschinger, Laura De Lorenzis

Geophysics · Cross-listed from cs.CV

Evaluating the effects of preprocessing, method selection, and hyperparameter tuning on SAR-based flood mapping and water depth estimation

Jean-Paul Travert, Cédric Goeury, Sébastien Boyaval et al. (+2 more)

Flood mapping and water depth estimation from Synthetic Aperture Radar (SAR) imagery are crucial for calibrating and validating hydraulic models. This study uses SAR imagery to evaluate various preprocessing (especially speckle noise reduction), flood mapping, and water depth estimation methods. The impact of the choice of method at different steps and its hyperparameters is studied by considering an ensemble of preprocessed images, flood maps, and water depth fields. The evaluation is conducted for two flood events on the Garonne River (France) in 2019 and 2021, using hydrodynamic simulations and in-situ observations as reference data. Results show that the choice of speckle filter alters flood extent estimations with variations of several square kilometers. Furthermore, the selection and tuning of flood mapping methods also affect performance. While supervised methods outperformed unsupervised ones, tuned unsupervised approaches (such as local thresholding or change detection) can achieve comparable results. The compounded uncertainty from preprocessing and flood mapping steps also introduces high variability in the water depth field estimates. This study highlights the importance of considering the entire processing pipeline, encompassing preprocessing, flood mapping, and water depth estimation methods and their associated hyperparameters. Rather than relying on a single configuration, adopting an ensemble approach and accounting for methodological uncertainty should be privileged. For flood mapping, the method choice has the most influence. For water depth estimation, the most influential processing step was the flood map input resulting from the flood mapping step and the hyperparameters of the methods.
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All authors Jean-Paul Travert, Cédric Goeury, Sébastien Boyaval, Vito Bacchi, Fabrice Zaoui

Instrumentation and Detectors

In-situ Radiation Damage Study of Silicon Carbide Detectors Subjected to Clinical Proton Beams

Daniel Radmanovac, Andreas Gsponer, Simon Waid et al. (+5 more)

Silicon carbide (SiC) planar PiN diodes from two different manufacturers were irradiated with 252.7 MeV protons from a medical synchrotron. Over the course of two 8h irradiation shifts, the samples were exposed to increasing fluences ranging from 1.4e+11 to 3.5e+13 p+/cm^2. Electrical characterizations, including IV and CV measurements, were performed both before and after irradiation using probe stations, and for selected samples even in-situ between fluence steps directly at the irradiation facility. The results show a gradual compensation of the effective epitaxial doping concentration with each incremental fluence step, observed as a reduction in capacitance before full depletion and confirmed by the extracted effective doping concentration. From these measurements, linear donor removal rates are determined for all sample groups, with values ranging from 4.2/cm to 6.4/cm. These findings provide a quantitative basis for understanding radiation-induced charge carrier removal in 4H-SiC devices and are relevant for predicting the performance and lifetime of future radiation-hard detector technologies, including 4H-SiC LGADs.
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All authors Daniel Radmanovac, Andreas Gsponer, Simon Waid, Sebastian Onder, Matthias Knopf, Juergen Burin, Stefan Gundacker, Thomas Bergauer

Data Analysis and Statistics

Information-theoretic analysis of temporal dependence in discrete stochastic processes: Application to precipitation predictability

Juan De Gregorio, David Sánchez and Raúl Toral

Understanding the temporal dependence of precipitation is key to improving weather predictability and developing efficient stochastic rainfall models. We introduce an information-theoretic approach to quantify memory effects in discrete stochastic processes and apply it to daily precipitation records across the contiguous United States. The method is based on the predictability gain, a quantity derived from block entropy that measures the additional information provided by higher-order temporal dependencies. This statistic, combined with a bootstrap-based hypothesis testing and Fisher's method, enables a robust memory estimator from finite data. Tests with generated sequences show that this estimator outperforms other model-selection criteria such as Akaike Information Criterion and Bayesian Information Criterion. Applied to precipitation data, the analysis reveals that daily rainfall occurrence is well described by low-order Markov chains, exhibiting regional and seasonal variations, with stronger correlations in winter along the West Coast and in summer in the Southeast, consistent with known climatological patterns. Overall, our findings establish a framework for building parsimonious stochastic descriptions, useful when addressing spatial heterogeneity in the memory structure of precipitation dynamics, and support further advances in real-time, data-driven forecasting schemes.
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Medical Physics

An AI dose engine for fast carbon ion treatment planning

Anastasiia Quarz, Angelica De Gregorio, Gaia Franciosini et al. (+7 more)

Monte Carlo (MC) simulations provide gold-standard accuracy for carbon ion therapy dose calculations but are computationally intensive. Analytical pencil beam algorithms offer speed but reduced accuracy in heterogeneous tissues. We developed the first AI-based dose engine capable of predicting absorbed dose, the alpha and beta parameters for relative biological effectiveness (RBE)- weighted optimisation in carbon ion therapy, delivering MC-level accuracy with drastically reduced computation time. We extended the transformer-based DoTA model to predict absorbed dose (C-DoTA-d), alpha (C-DoTA-alpha), and beta (C-DoTA-beta), introducing a cross-attention mechanism for alpha and beta to combine dose and energy inputs. The training dataset consisted of ~70,000 pencil beams from 187 head-and-neck patients, with ground-truth values obtained using the GPU-accelerated MC toolkit FRED. Performance was evaluated on an independent test set using gamma pass rate (1%/1 mm), depth-dose, and isodose contour Dice coefficients. MC dropout-based uncertainty analysis was performed. Median gamma pass rates exceeded 98% for all predictions (99.76% for dose, 99.14% for alpha, and 98.74% for beta), with minima above 85% in the most heterogeneous anatomies. The Dice coefficient was 0.95 for 1% isodose contours, with slightly reduced agreement in high-gradient regions. Compared to MC FRED, inference was over 400x faster (0.032 s vs. 14 s per pencil beam) while maintaining accuracy. Uncertainty analysis showed high stability, with mean standard deviations below 0.5% for all models. C-DoTA achieves MC-quality predictions of absorbed dose and RBE model parameters in ~30 milliseconds per beam. Its speed and accuracy support online adaptive planning, paving the way for more effective carbon ion therapy workflows. Future work will expand to additional anatomical sites, beam geometries, and clinical beamlines.
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All authors Anastasiia Quarz, Angelica De Gregorio, Gaia Franciosini, Angelo Schiavi, Zoltán Perkó, Lennart Volz, Christoph Hoog Antink, Vincenzo Patera, Marco Durante, Christian Graeff