Optics
Exciton and biexciton preparation via coherent swing-up excitation in a GaAs quantum dot embedded in micropillar cavity
Claudia Piccinini, Aleksander Rodek, Abdulmalik A. Madigawa et al. (+9 more)
Coherent control of
quantum emitters is essential for scalable
quantum photonic technologies. The recently proposed swing-up of
quantum emitter (SUPER) scheme allows efficient and coherent preparation of single
photons via off-resonant, red-detuned
laser pulses, simplifying
laser suppression and enhancing
photon collection. We present a systematic study of SUPER excitation applied to a single GaAs
quantum dot in a low-Q micropillar cavity. We perform a comparison of the key figures of merit against the well-established two-
photon excitation (TPE). Despite requiring higher excitation powers, SUPER achieves near-unity population inversion of the
exciton state ($\sim$95%) and high single-
photon purity ($g^{(2)}=0.03$) comparable to that under TPE, while also exhibiting a shortened decay time ($\sim$200 ps) reducing the time jitter in the
exciton population. A polarization-resolved analysis reveals that when both excitation and collection are aligned with one of the
exciton dipoles, SUPER results in polarized single-
photon emission, exceeding the resonant TPE saturation by a factor of 1.45. Under optimized excitation conditions, we also observe biexciton preparation via a distinct SUPER resonance, confirmed by the appearance of the biexciton emission line, constituting the first experimental demonstration of biexciton preparation using SUPER. These findings are in good agreement with a proposed four-level theoretical model that incorporates the biexciton state. We also report that a slight misalignment of
laser polarization induces an additional SUPER resonance that selectively populates the orthogonal
exciton dipole, without altering the nominal excitation polarization. This unexpected behavior reveals a new degree of freedom for coherent state preparation. Our findings establish the SUPER scheme as a versatile tool for state-selective
exciton and biexciton control.
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All authors Claudia Piccinini, Aleksander Rodek, Abdulmalik A. Madigawa, Ailton Garcia Jr., Saimon F. Covre da Silva, Martin A. Jacobsen, Luca Vannucci, Gregor Weihs, Armando Rastelli, Vikas Remesh, Niels Gregersen, Battulga Munkhbat
Applied Physics · Cross-listed from cond-mat.mes-hall
Spin filtering on demand via localized states in an atomic-scale resonant tunneling magnetic tunnel junction
Maciej Bazarnik and Anika Schlenhoff
Spin filtering and its back-action
spin transfer torque (STT) are key ingredients of latest spintronic devices based on
magnetic tunnel junctions (MTJs). Resonant tunneling (RT), implemented by design or occurring as parasitic effects, is known to crucially affect macroscopic device performance, but direct experimental access to its individual microscopic processes has remained difficult. Here we apply the RT scheme from MTJs to
spin-polarized scanning tunneling microscopy (SP-STM) for ultimate miniaturization obtained by addressing distinct sites on individual nanomagnets. Combined with energy selectivity, our experimental model set-up enables to study the
spin filtering capabilities of RT through an individual
spin-split
vacuum resonance state and of the corresponding STT exerted on the nanomagnet. We find, that the sign and magnitude of the STT follow the effective
spin-polarization of the resonance state, which, as we show, can by tailored on demand either by adjusting the applied bias or the current injection point on the nanostructure. We anticipate, that our atomic-scale RT-MTJ approach and the discovery of a versatile tunable
spin-filter at smallest scale will prove invaluable for studying and designing next generation MTJs potentially based on recently discovered 2D van-der-Waals magnets or altermagnets.
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Data Analysis and Statistics · Cross-listed from gr-qc
Optimizing searches for gravitational wave bursts using coherent WaveBurst 2G
Alessandro Martini, Andrea Miani, Marco Drago et al. (+11 more)
The most general searches for gravitational wave transients (GWTs) rely on data analysis methods that do not assume prior knowledge of the signal waveform, direction, or arrival time on Earth. These searches provide data-driven signal reconstructions that are crucial both for testing available emission models and for discovering yet-to-be-uncovered sources. Here, we discuss progress in the detection performance of the coherent WaveBurst second-generation pipeline (cWB-2G), which is highly adaptable to both minimally modeled and model-informed searches for GWTs. Several search configurations for GWTs are examined using approximately 14.8 days of observation time from the third observing run by LIGO-Virgo-KAGRA (LVK). Recent enhancements include a ranking statistic fully based on multivariate classification with eXtreme Gradient Boosting, a thorough validation of the statistical significance accuracy of GWT candidates, and a measurement of the correlations of false alarms and simulated detections between different concurrent searches. For the first time, we provide a comprehensive comparison of cWB-2G performance on data from networks made of two and three detectors, and we demonstrate the advantage of combining concurrent searches for GWTs of generic morphology in a global observatory. This work offers essential insights for assessing our data analysis strategies in ongoing and future LVK searches for generic GWTs.
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All authors Alessandro Martini, Andrea Miani, Marco Drago, Claudia Lazzaro, Francesco Salemi, Sophie Bini, Osvaldo Freitas, Edoardo Milotti, Giacomo Principe, Shubhanshu Tiwari, Agata Trovato, Gabriele Vedovato, Yumeng Xu, Giovanni Andrea Prodi
Optics
Numerical simulation of light structures in bulk ENZ media with Kerr nonlinearity
Victor P. Ruban
A simplified mathematical model is suggested to describe the dynamics of a quasi-monochromatic optical wave in the bulk of an effectively isotropic metamaterial with averaged dielectrical permittivity near zero (ENZ medium), in the presence of a weak spatial nonuniformity, Kerr nonlinearity as well as linear gain due to external pumping. The model is a vector Ginzburg-Landau equation of the general kind, with the dominating curl-curl term in the dispersive operator, and it resembles the equation for electromagnetic waves in
plasma [E. A. Kuznetsov, 1974]. In the case of purely real Kerr coefficients, a split-step
Fourier method is appropriate for numerical simulations. It makes possible to observe various variants of nontrivial
evolution of both central-symmetric and toroidal vector wave structures trapped by a quadratic potential well, as well as nonlinear interaction between the longitudinal and transverse waves in the case of their combination.
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Biological Physics
Tracking phase synchronization between flagella in the time-frequency domain resolves photophobic response
Lucas Federspiel, Jorge Arrieta, Marco Polin et al. (+2 more)
The unicellular microalga Chlamydomonas reinhardtii (CR) is well known for its bi-flagellated swimming in response to light stimuli. This work aims to study the resynchronization of CR flagella after a high light intensity stimulus, known as photoshock. The synchronization is estimated thanks to a quantity defined as the Phase Synchronization Index (PSI). The originality of this approach is to perform a time-frequency computation of a complex PSI based on continuous wavelet transform. Thanks to this analysis, we distinguish three swimming stages involving different frequency bands and phase shifts: synchronized breaststroke swimming, undulatory backward swimming, and resynchronization. This approach also reveals the presence of signal harmonics that set the photoshock response, independently of
cell variability. Our results suggest that CR modulates the balance between spectral beating modes, providing a mechanism for robust adaptation to sudden environmental stresses.
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All authors Lucas Federspiel, Jorge Arrieta, Marco Polin, Francoise Argoul, Antoine Allard
Atomic Physics
Magneto-optical trapping of Zinc
Lukas Möller and Simon Stellmer
We report on
laser cooling and magneto-optical trapping of atomic zinc. The atoms are cooled using the 213.9\,nm $^1$S$_0$ $\rightarrow$ $^1$P$_1$ transition, making this the shortest wavelength employed for magneto-optical trapping thus far. We demonstrate trapping of all stable isotopes of zinc, including the fermionic isotope $^{67}$Zn, which features a very narrow $^1$S$_0$ $\rightarrow$ $^3$P$_0$ transition that could form the basis of an optical atomic clock. We characterize the influence of various parameters on the MOT population and loading rate. The results presented here constitute the first step towards the application of zinc for high-precision optical spectroscopy and
quantum information processing.
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Instrumentation and Detectors
Picosecond Precision Heavy-Ion Detector for {\Lambda} Hypernuclei Lifetime Studies
Simon Zhamkochyan, Sergey Abrahamyan, Amur Margaryan et al. (+18 more)
In this paper, we present the design and preliminary performance evaluation of a new heavy-ion detector for direct measurements of heavy {\Lambda} hypernuclei lifetime. The detector employs the previously developed 10 picosecond resolution
Radio Frequency (RF) Timer, which converts the temporal information of incident particles into spatial coordinates of secondary or photoelectrons on a position-sensitive detector by means of circular RF scanning in the 500-1000 MHz range. Here, we report the detector design to achieve efficient suppression of accidental background and effective separation of
prompt reaction products and delayed events from {\Lambda} hypernuclei decays, results of test studies carried out with RF synchronized
laser as well as preliminary results obtained by using alpha particles. Dedicated Monte-Carlo simulations have been performed to estimate the detector's performance under realistic experimental conditions at RF-driven electron,
photon, or
proton beams. The results confirm the feasibility of the proposed design and provide a basis for upcoming experimental measurements, based on the delayed fission detection.
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All authors Simon Zhamkochyan, Sergey Abrahamyan, Amur Margaryan, Hayk Elbakyan, Aram Kakoyan, Samvel Mayilyan, Artashes Papyan, Hasmik Rostomyan, Anna Safaryan, Gagik Sughyan, Narek Margaryan, Garnik Ayvazyan, John Annand, Kenneth Livingston, Rachel Montgomery, Patrick Achenbach, Josef Pochodzalla, Dimiter Balabanski, Satoshi Nakamura, Ani Aprahamian, Vanik Kakoyan
Chemical Physics
Efficient Exploration of Chemical Kinetics
Rohit Goswami
Estimating reaction rates and chemical stability is fundamental, yet efficient methods for large-scale simulations remain out of reach despite advances in modeling and exascale computing. Direct simulation is limited by short timescales; machine-learned potentials require large data sets and struggle with transition state regions essential for reaction rates. Reaction network exploration with sufficient accuracy is hampered by the computational cost of electronic structure calculations, and even simplifications like harmonic transition state theory rely on prohibitively expensive saddle point searches. Surrogate model-based acceleration has been promising but hampered by overhead and numerical instability. This dissertation presents a holistic solution, co-designing physical representations, statistical models, and systems architecture in the Optimal Transport Gaussian Process (OT-GP) framework. Using physics-aware optimal transport metrics, OT-GP creates compact, chemically relevant surrogates of the potential energy surface, underpinned by statistically robust sampling. Alongside EON software rewrites for long timescale simulations, we introduce reinforcement learning approaches for both minimum-mode following (when the final state is unknown) and nudged elastic band methods (when endpoints are specified). Collectively, these advances establish a representation-first, modular approach to chemical kinetics simulation. Large-scale
benchmarks and
Bayesian hierarchical validation demonstrate state-of-the-art performance and practical exploration of chemical kinetics, transforming a longstanding theoretical promise into a working engine for discovery.
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Medical Physics
Patient-specific AI for generation of 3D dosimetry imaging from two 2D-planar measurements
Alejandro Lopez-Montes, Robert Seifert, Astrid Delker et al. (+6 more)
In this work we explored the use of patient specific reinforced learning to generate 3D activity maps from two 2D planar images (anterior and posterior). The solution of this problem remains unachievable using conventional methodologies and is of particular interest for dosimetry in
nuclear medicine where approaches for post-therapy distribution of radiopharmaceuticals such as 177Lu-PSMA are typically done via either expensive and long 3D SPECT acquisitions or fast, yet only 2D, planar scintigraphy. Being able to generate 3D activity maps from planar scintigraphy opens the gate for new dosimetry applications removing the need for SPECT and facilitating multi-time point dosimetry studies. Our solution comprises the generation of a patient specific
dataset with possible 3D uptake maps of the radiopharmaceuticals withing the anatomy of the individual followed by an AI approach (we explored both the use of 3DUnet and
diffusion models) able to generate 3D activity maps from 2D planar images. We have validated our method both in simulation and real planar acquisitions. We observed enhanced results using patient specific reinforcement learning (~20% reduction on MAE and ~5% increase in SSIM) and better organ delineation and patient anatomy especially when combining
diffusion models with patient specific training yielding a SSIM=0.89 compared to the ground truth for simulations and 0.73 when compared to a SPECT acquisition performed half an hour after the planar. We believe that our methodology can set a change of paradigm for
nuclear medicine dosimetry allowing for 3D quantification using only planar scintigraphy without the need of expensive and time-consuming SPECT leveraging the pre-therapy information of the patients.
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All authors Alejandro Lopez-Montes, Robert Seifert, Astrid Delker, Guido Boening, Jiahui Wang, Christoph Clement, Ali Afshar-Oromieh, Axel Rominger, Kuangyu Shi
Optics · Cross-listed from cond-mat.mes-hall
Universal Thickness-Dependent Absorption in Solids at the Nanoscale: Anomalous Enhancement in the Ultrathin Limit
Bhumika Chauhan, Nikhil Singh, Subhrajit Dalai et al. (+5 more)
Through systematic experimental and theoretical studies of layer-thickness-dependent absorption in semiconducting MoSe$_2$ and WS$_2$ across the visible to near-infrared spectral range, we demonstrate a universal absorption behavior in solids at nanoscale thicknesses. With increasing thickness, a non-monotonic
evolution of absorption integrated over the measured spectral region is revealed which is accompanied by pronounced oscillatory features. This shows a strong deviation from the expected Beer-Lambert law. Below 10 nm, we observe a sharp anomalous increase in absorption, with deviations from Beer's law exceeding 50% in layered
semiconductors. Our conclusions hold irrespective of the presence of any optical resonances such as
excitons or plasmons within the spectral window. The observed behavior has origins in the electromagnetic interference effects taking place between the two surfaces of the thin
crystals. The present work on 2D
semiconductors is extendable to all kinds of solids such as conventional
semiconductors (e.g. Si, GaAs, GaN, InP), (semi) metals (e.g. Al, Ag, Au, c-HOPG) and 2D
magnetic materials (e.g. CrSBr and NiPS$_3$). Our results provide fundamental insights into light-matter interactions in solids at the nanoscale and are vital for optimally designing the new generation of absorption-based flexible optoelectronic devices.
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All authors Bhumika Chauhan, Nikhil Singh, Subhrajit Dalai, Abhisek Saidarsan, Sayantan Patra, Sourabh Jain, Aparna Deshpande, Ashish Arora
Physics Education
Analyzing Students Critical Thinking as a Basis for Developing Interactive Physics Multimedia with Generative Learning and Cognitive Conflict Strategies
Serli Ahzari and Akmam Akmam
The increasing complexity of abstract concepts in physics education and the low level of students critical thinking skills demand innovative instructional strategies aligned with 21st century competencies. This study aims to analyze students critical thinking skills as the foundation for developing physics interactive multimedia using a generative learning model integrated with a cognitive conflict strategy. The research was conducted in three public high schools in Lima Puluh Kota Regency using a quantitative descriptive survey method, involving 125 eleventh-grade students. Data were collected using five validated instruments: teacher questionnaires on instructional practices and critical thinking, student learning style and attitude surveys, a multimedia needs assessment, and a critical thinking skills test. Results show that current instruction relies heavily on static and non-interactive media such as PowerPoint and
videos, failing to support students varied learning styles especially the dominant visual preference (53.06). While students exhibit moderately positive attitudes toward physics learning (65.69), their critical thinking skills are critically low (average score 27.80), particularly in inference (24.00) and evaluation (28.00) indicators. These findings underscore the urgent need to develop visual and interactive multimedia that facilitates cognitive conflict and deeper reflection. The novelty of this study lies in linking multimedia design with cognitive strategies tailored to enhance critical thinking in physics. The study contributes to physics education by offering empirical evidence for the pedagogical integration of generative learning and cognitive conflict approaches in digital environments, paving the way for targeted multimedia interventions that promote critical
reasoning in conceptually demanding physics topics.
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Chemical Physics · Cross-listed from cond-mat.stat-mech
Faradaic and capacitive charging of an electrolyte-filled pore in response to a small applied potential
Timur Aslyamov, Massimiliano Esposito and Mathijs Janssen
Electrochemical devices often charge both through Faradaic reactions and electric double layer formation. Here, we study these coupled processes in a model system of a long electrolyte-filled pore subject to a small suddenly-applied potential, close to the
equilibrium potential $\Psi^\text{eq}$ at which there is no net Faradaic charge transfer. Specifically, we solve the coupled Poisson-Nernst-Planck and Frumkin-Butler-Volmer equations by asymptotic approximations, using the pore's small inverse aspect ratio as the small parameter. In the early-time limit, the reaction-
diffusion equations yield an extended Faradaic transmission line model that includes a voltage source, $\Psi_\text{eq}$, biasing the Faradaic reactions, captured by the resistance $R_F$. In the long-time limit, the model exhibits a nontrivial potential of zero charge, $\Psi_\text{pzc} = \Psi_\text{eq}[1 - \hat{Z}(0)/R_F]$, where $\hat{Z}(0)$ is the experimentally accessible zero-frequency impedance of the system. This expression provides a new means to experimentally measure the Faradaic contribution to $\Psi_\text{pzc}$.
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Atmospheric and Oceanic Physics
Space waste: An update of the anthropogenic matter injection into Earth atmosphere
Leonard Schulz, Karl-Heinz Glassmeier, Moritz Herberhold et al. (+4 more)
Large satellite constellations are one of the main reasons for an increasing amount of mass being brought into low Earth orbit in recent years. After end of life, the satellites, as well as rocket stages, reenter Earth's atmosphere. This space waste burns up and thus injects a substantial amount of its matter into the mesosphere and lower thermosphere. A first comprehensive analysis of the anthropogenic injection and a comparison to the natural injection by meteoroids was presented by Schulz & Glassmeier (2021). They found significant and even the dominant injection of several metal elements regularly used in spacecraft compared to the natural injection. The first observations of space waste remnants in stratospheric aerosol particles (Murphy et al., 2023) confirmed several of these estimates, but also revealed differences and new insights. The current study presents an update to the space waste injection estimates of Schulz & Glassmeier (2021), assessing the years from 2015 to 2025 but also considering future mass influx scenarios. 43 elements are considered and thus a much more detailed comparison to the meteoric injection is possible. Comparison of estimated elemental fluxes to stratospheric aerosol data shows excellent agreement. From 2020 onward, a strong rise in space waste mass influx to the atmosphere can be seen. Future scenarios discussed by Schulz & Glassmeier (2021) may already be reached by the end of 2025. In 2024, 24 elements were dominating the meteoric injection compared to 18 in 2015. Several of them are transition metals, which are known for their catalytic activity. This indicates a substantial risk of long-term adverse effects on the atmosphere such as ozone depletion, radiative effects and changes in cloud formation, if no action is taken. Research is urgently needed into the atmospheric accumulation, chemistry, and general atmospheric effects of specific elements.
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All authors Leonard Schulz, Karl-Heinz Glassmeier, Moritz Herberhold, Adam Mitchell, Daniel M. Murphy, John M. C. Plane, Ferdinand Plaschke
Biological Physics
Cell Competition Driven by Secreted Ligands: Modeling Liver Metastasis of Colorectal Cancer
Hossein Nemati, Saskia Jacoba Elisabeth Suijkerbuijk and Joost de Graaf
Cell competition in multicellular organisms has been shown to play a critical role during the development of organisms, cancer progression, and in the establishment and maintenance of tissue homeostasis. Various mechanisms of
cell competition have been identified, including active elimination via mechanical forces or induced apoptosis, as well as competition for nutrients and other beneficial factors. A recent experiment demonstrated hallmarks of
cell competition, associated with
cell cycle dynamics, between liver progenitor
cells and colorectal cancer
cells [Krotenberg Garcia et al., iScience 27, 109718 (2024)]. However, a mechanistic explanation for this form of competition remains lacking. Here, we present a mean-field model of competition for signaling ligands, coupled with
cell cycle dynamics, to provide such an understanding. Our model captures the salient features of the experiment, including population dynamics and
cell cycle variations. We demonstrate that secretion of a beneficial factor by
cells, coupled with the enhanced uptake efficiency of cancer
cells, suffices to reproduce the experimental outcome. Our model, reminiscent of competition for secreted growth factors, provides insight into the minimal level of complexity required to achieve the observed competitive outcome as well as its link to
cell cycle dynamics. It can also serve as a general framework for studying biological populations with growth-stage-dependent competition over consumer-produced products.
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Applied Physics
Combining metal dewetting and lateral etching for the scalable top-down fabrication of GaN nanowire arrays with independently tunable diameter and spacing
Jingxuan Kang, Rose-Mary Jose, Oliver Brandt et al. (+1 more)
The top-down fabrication of nanowires based on patterning via metal dewetting is a cost-effective and scalable approach that is particularly suited for applications requiring large arrays of nanowires. Advantageously, the nanowire diameter can be tailored by the initial metal film thickness. However, we show here that metal dewetting inherently leads to a coupling between the nanowire diameter and spacing. To overcome this limitation, we introduce two strategies that are exemplified for GaN nanowires: (i) modification of the surface and interface energies within the dewetting system, and (ii) thinning of the nanowires by lateral etching. In the first strategy, GaN(0001), SiOx, and SiNx substrate surfaces are combined with Au, Pt, and Pt-Au
alloy dewetting metals to tune the dewetting behavior. The differences in interface energies affect the relation between nanowire diameter and spacing, albeit within a limited range. The second strategy adds a lateral etching step to the conventional top-down nanowire fabrication process. This step at the same time reduces the nanowire diameter and increases the spacing, thus enabling combinations beyond the constraints of metal dewetting alone. When in addition different initial nanowire diameters are employed, it is possible to independently control diameter and spacing over a substantially extended range. Therefore, the inherent limitation of conventional dewetting-based patterning approaches for the top-down fabrication of nanowires is overcome.
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All authors Jingxuan Kang, Rose-Mary Jose, Oliver Brandt, Lutz Geelhaar
Chemical Physics
A complex Gaussian representation of continuum wavefunctions respectful of their asymptotic behaviour
Stéphanie Laure Egome Nana, Arnaud Leclerc and Lorenzo Ugo Ancarani
Complex Gaussian basis sets are optimized to accurately represent continuum radial wavefunctions over the whole space. First,
attention is put on the technical ability of the optimization method to get more flexible series of Gaussian exponents, in order to improve the accuracy of the fitting approach. Second, an indirect fitting method is proposed, allowing for the oscillatory behaviour of continuum functions to be conserved up to infinity as a factorized asymptotic function, while the Gaussian representation is applied to some appropriately defined distortion factor with limited spatial extension. As an illustration, the method is applied to radial Coulomb functions with realistic energy parameters. We also show that the indirect fitting approach keeps the advantageous analytical structure of typical one-electron transition integrals occurring in molecular ionization applications.
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Instrumentation and Detectors
Bayesian approach for spatial super-resolution of heterodyne wind lidars
Theo Martin, Laurent Mugnier, Matthieu Valla et al. (+2 more)
Wind speed measurements using heterodyne
lidars are limited in spatial resolution because of the current signal processing methods. This limit is equal to c $\tau$ ( c is the speed of light and $\tau$ is the
laser pulse duration) corresponding to the length of the atmosphere contributing to the wind speed measurement at one distance. To go beyond this limit, we use an inverse problem approach based on a model of the spectrogram (concatenation of periodograms of each range) and prior distributions on our unknowns: backscattering amplitude and wind speed at each range. We apply our inversion method to simulated and experimental spectrograms, demonstrating a gain in resolution by a factor of 2 to 2.5 depending on the signal-to-noise ratio.
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All authors Theo Martin, Laurent Mugnier, Matthieu Valla, Pierre Etienne Allain, David Tomline Michel
Plasma Physics
Benchmark for two-dimensional large scale coherent structures in partially magnetized ExB plasmas – Community collaboration & lessons learned
Andrew T. Powis, Eduardo Ahedo, Alejandro Álvarez Laguna et al. (+38 more)
Low-temperature
plasmas are essential to both fundamental scientific research and critical industrial applications. As in many areas of science, numerical simulations have become a vital tool for uncovering new physical phenomena and guiding technological development. Code benchmarking remains crucial for verifying implementations and evaluating performance. This work continues the Landmark
benchmark initiative, a series specifically designed to support the verification of low-temperature
plasma codes. In this study, seventeen simulation codes from a collaborative community of nineteen international institutions modeled a partially magnetized ExB Penning discharge. The emergence of large scale coherent structures, or rotating
plasma spokes, endows this configuration with an enormous range of time scales, making it particularly challenging to simulate. The codes showed excellent agreement on the rotation frequency of the spoke as well as key
plasma properties, including time-averaged ion density,
plasma potential, and electron temperature profiles. Achieving this level of agreement came with challenges, and we share lessons learned on how to conduct future benchmarking campaigns. Comparing code implementations, computational hardware, and simulation runtimes also revealed interesting trends, which are summarized with the aim of guiding future
plasma simulation software development.
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All authors Andrew T. Powis, Eduardo Ahedo, Alejandro Álvarez Laguna, Nicolas Barléon, Enrique Bello-Benítez, Lucas Beving, Jean-Pierre Boeuf, Guillaume Bogopolsky, Anne Bourdon, Filippo Cichocki, Bénédicte Cuenot, Andrew Denig, Zoltán Donkó, Paul-Quentin Elias, Miguel P. Encinar, Denis Eremin, Pablo Fajardo, Farbod Faraji, Gwenael Fubiani, Laurent Garrigues, Kentaro Hara, Peter Hartmann, Matthew Hopkins, Igor D. Kaganovich, Aaron Knoll, Giovanni Lapenta, Thierry E. Magin, Alberto Marín-Cebrián, Mario Merino, Pierpaolo Minelli, Mina Papahn Zadeh, Pietro Parodi, Federico Petronio, Maryam Reza, Andrei I. Smolyakov, Dmytro Sydorenko, Francesco Taccogna, Miles M. Turner, Olivier Vermorel, Willca Villafana, Liang Xu
Medical Physics
Light-sheet microscopy in cancer pathology: current applications, clinical challenges and future perspectives
Uma Pisarović, Taichi Ochi, Iryna Samarska et al. (+8 more)
Light-sheet fluorescence microscopy (LSFM) has emerged as a powerful research technology for three-dimensional (3D) visualization of biological tissues and is increasingly applied to human cancer specimens, including optically cleared biopsies and
surgical resection samples. In this Perspective article, we review current applications of LSFM in oncology, and discuss how recent developments in microscopy, tissue preparation, labelling, and computational analysis are expanding the possibilities of 3D cancer pathology. Although LSFM has demonstrated the feasibility of large-volume imaging in selected human specimens, its application remains predominantly within research and translational settings and is not currently part of routine clinical pathology. We therefore distinguish demonstrated applications from potential future uses. We discuss how LSFM could eventually contribute to selected diagnostic and
surgical workflows by providing 3D information on tumour architecture, spatial heterogeneity, metastatic dissemination, and
surgical margins. These applications remain prospective and will require substantial technical, clinical, regulatory, computational, and workflow validation before clinical implementation can be considered. Ultimately, LSFM may complement rather than replace conventional histopathology by extending pathological assessment from two-dimensional tissue sections towards 3D spatial analysis.
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All authors Uma Pisarović, Taichi Ochi, Iryna Samarska, Ludovico Silvestri, Thiemo J.A. van Nijnatten, Loes F.S. Kooreman, Tom Marcelissen, Mari van Hout, Francesco Missale, Axel zur Hausen, Anna Schueth
Fluid Dynamics
Sparse surface pressure-based reconstruction of the flow around a thick airfoil over a range of angles of attack
Quentin Bucquet, Bérengère Podvin, Caroline Braud et al. (+1 more)
We present an efficient neural-based approach to estimate the instantaneous flow field around an airfoil from limited surface pressure measurements. The model, denoted SNN-POD, relies on two independent shallow neural networks to predict the instantaneous flow over a wide range of angles of attack [10{\textdegree},20{\textdegree}]. At all angles the global model correctly recovers the average characteristics of the flow from single-time sensor data, thus allowing combination with local, angle-dependent models. The method is applied to 2D URANS simulations of a thick airfoil at a Reynolds number of Re=4.5e6. The training set consists of snapshots obtained from a coarse sampling (1-2{\textdegree}) of the angle of attack range. A variance-based criterion is used to determine the number and positions of sensors. Tests are carried out for unseen snapshots at angles of attack within the set (sampled angles) as well as outside the set (interpolated angles). The maximum MSE error of attack for sampled and interpolated angles is respectively 2.9% and 6.6%. This makes it possible to develop adaptive strategies to improve the estimation if necessary.
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All authors Quentin Bucquet, Bérengère Podvin, Caroline Braud, Emmanuel Guilmineau
Computational Physics · Cross-listed from cond-mat.mes-hall
Optimal spin-charge interconversion in graphene through spin-pseudospin entanglement control
Joaquín Medina Dueñas, Santiago Giménez de Castro, Jose H. Garcia et al. (+1 more)
The electrical generation of
spin signals is of central interest for spintronics, where
graphene stands as a relevant platform as its
spin-orbit coupling (SOC) is tuned by proximity effects. Here, we propose an enhancement of
spin-charge interconversion in
graphene by controlling the intraparticle
entanglement between the
spin and pseudospin degrees of freedom. We demonstrate that, although the
spin alone is not conserved in Rashba-Dirac systems, a combined
spin-pseudospin operator is conserved. This conserved quantity represents the interconversion between pure
spin and pseudospin textures to a
spin-pseudospin entangled structure, where Kane-Mele SOC tunes this balance. By these means, we achieve
spin-charge interconversion of 100% efficiency via the Rashba-Edelstein effect.
Quantum transport simulations in disordered micron-size systems demonstrate the robustness of this effect, and also reveal a disorder resilient
spin Hall effect generated by the interplay between Rashba and Kane-Mele SOC. Our findings propose a platform for maximally efficient
spin-charge interconversion, and establish
spin-pseudospin correlations as a mechanism to tailor spintronic devices.
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All authors Joaquín Medina Dueñas, Santiago Giménez de Castro, Jose H. Garcia, Stephan Roche
Plasma Physics
Laboratory formation of scaled astrophysical outflows
Shun-yi Yang, Guang-yue Hu, Chao Xiong et al. (+7 more)
Astrophysical systems exhibit a rich diversity of
outflow morphologies, yet their mechanisms and existence conditions remain among the most persistent puzzles in the field. Here we present scaled laboratory experiments based on
laser-driven
plasma outflow into magnetized ambient gas, which mimic five basic astrophysical
outflows regulated by interstellar medium, namely collimated jets, blocked jets, elliptical bubbles, as well as spherical winds and bubbles. Their morphologies and existence conditions are found to be uniquely determined by the external Alfvenic and sonic Mach numbers Me-a and Me-s, i.e. the relative strengths of the
outflow ram pressure against the
magnetic/thermal pressures in the interstellar medium, with transitions occurring at Me-a ~ 2 and 0.5, as well as Me-s ~ 1. These results are confirmed by magnetohydrodynamics simulations and should also be verifiable from existing and future astronomical observations. Our findings provide a quantitative framework for understanding astrophysical
outflows.
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All authors Shun-yi Yang, Guang-yue Hu, Chao Xiong, Tian-yi Li, Xue-cheng Li, Hui-bo Tang, Shuo-ting Shao, Xiang Lv, Chen Zhang, Ming-yang Yu
Optics
Optical Spin Effects Induced by Phase Conjugation at a Space-Time Interface
Carlo Rizza, Alessandra Contestabile, Maria Antonietta Vincenti et al. (+5 more)
Electromagnetic temporal boundaries, emerging when the constitutive parameters of a medium undergo abrupt temporal variations, have garnered significant interest for their role in facilitating unconventional wave phenomena and enabling sophisticated field manipulations. A key manifestation is temporal reflection in an unbounded spatial domain, where a sudden temporal discontinuity induces phase-conjugated backward waves alongside anomalous
spin conversion. This study explores distinctive
spin-conversion dynamics at a time-dependent spatial interface governed by Lorentz-type dispersion, in which the
plasma frequency undergoes rapid modulation over time. The interaction of a circularly polarized wave with a space-time interface excites electromagnetic signals at the system's natural resonance, allowing precise control over polarization states. The scattered field stems from the combined influence of temporal and spatial boundaries, yielding a superposition of the original incident wave's polarization and its phase-conjugated counterpart.
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All authors Carlo Rizza, Alessandra Contestabile, Maria Antonietta Vincenti, Giuseppe Castaldi, Marcello Ferrera, Alessandro Stroppa, Michael Scalora, Vincenzo Galdi
Computational Physics · Cross-listed from cs.CE
Linked Cell Traversal Algorithms for Three-Body Interactions in Molecular Dynamics
Jose Alfonso Pinzon Escobar, Markus Mühlhäußer, Hans-Joachim Bungartz et al. (+1 more)
In this work,
algorithms for the parallel computation of three-body interactions in molecular dynamics are developed. While traversals for the computation of pair interactions are readily available in the literature, here, such traversals are extended to allow for the computation between molecules stored across three
cells. A general framework for the computation of three-body interactions in linked
cells is described, and then used to implement the corresponding traversals. In addition, our analysis is combined with the commonly used cutoff conditions, because they influence the total workload of the computation of interactions. The combinations between traversals and truncation conditions are validated using the well-known Lennard-Jones fluid. Validation case studies are taken from the literature and configured into homogeneous and inhomogeneous scenarios. Finally, strong scalability and performance in terms of molecule updates are measured at node-level.
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All authors Jose Alfonso Pinzon Escobar, Markus Mühlhäußer, Hans-Joachim Bungartz, Philipp Neumann
Physics and Society
The effect of role-based resource allocation on epidemic dynamics
Hao-Xiang Jiang, Chao-Ran Cai, Ji-Qiang Zhang et al. (+1 more)
We propose a coupled dynamical model of resource allocation and epidemic spread, inspired by the hierarchical structure of real-world therapeutic resource allocation. In this framework, network nodes are assigned distinct roles as either resource allocators or resource recipients. As the average number of links per recipient from allocators increases, the prevalence exhibits one of four distinct response patterns across conditions: monotonically increasing, monotonically decreasing, U-shaped trend, or a sudden decrease with large fluctuations. A mechanistic analysis uncovers three central insights: (i) a trade-off between efficient resource allocation and infection risk faced by allocators, (ii) the critical need to avoid resource redundancy when therapeutic efficiency is high, and (iii) the emergence of cascade-induced bistability in the coupled system.
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All authors Hao-Xiang Jiang, Chao-Ran Cai, Ji-Qiang Zhang, Ming Tang
Optics
Classical field statistical phase-space analysis of passive turbulence mitigation using PMMA dielectric media
Shouvik Sadhukhan and C. S. Narayanamurthy
This study examines the influence of optical
turbulence on field statistics using a nonlinear reconstruction and
quantum phase-space formalism.
Turbulence-distorted intensity sequences were processed through a nonlinear P3-type partial differential equation to retrieve the embedded phase, thereby reconstructing the complete complex optical field. The recovered fields were subsequently projected onto a Gaussian local oscillator to generate quadrature ensembles, enabling Wigner function
tomography via Radon inversion.
Photon-number distributions were obtained from the overlap of the reconstructed Wigner functions with Fock-state kernels, allowing direct evaluation of statistical moments and the Fano factor. Comparative analysis across four experimental configurations, Set 1: uncorrected
turbulence, Set 2:
turbulence with a single PMMA slab, Set 3:
turbulence with dual PMMA slabs, and Set 4: free-space reference revealed the modification of phase noise and
photon statistics due to partial compensation. Notably, the
evolution of the Fano factor traced the transition among Poissonian, super-Poissonian, and near-sub-Poissonian regimes, quantitatively capturing the degree of
turbulence mitigation achieved by the PMMA elements. This framework establishes a quantitative link between
turbulence-induced phase distortions and
quantum statistical behavior of reconstructed optical fields.
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Computational Physics
Fast adaptive discontinuous basis sets for electronic structure
Yulong Pan and Michael Lindsey
We develop a discontinuous Galerkin (DG) framework for automatically constructing adaptive basis sets for electronic structure calculations. By allowing basis functions to be discontinuous across element interfaces, our approach supports flexible combinations of atom-centered and
polynomial basis sets, maintains favorable numerical conditioning, and induces structured sparsity of the one- and two-electron integrals, which we compute using specialised numerical integration strategies. In addition, we introduce a simple post-processing procedure to obtain continuous solutions if desired. We also introduce multigrid-preconditioned Poisson solvers that enable fast
algorithms for both Hartree-Fock (HF) and density functional theory (DFT) calculations within our DG basis sets. Moreover, these basis sets naturally support adaptive multigrid preconditioning for the linear eigensolvers employed within the self-consistent field iteration for HF and DFT. Numerical experiments for HF and DFT demonstrate that our approach achieves chemical accuracy with modest basis sizes that compare favorably to the sizes of ordinary GTO basis sets achieving similar accuracy, while offering additional structured sparsity and improved computational scalability in the size-extensive limit. The framework thus provides a flexible route toward the construction of systematically improvable and structured adaptive basis sets for electronic structure theory.
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Applied Physics · Cross-listed from cs.LG
On the flow matching interpretability
Francesco Pivi, Simone Gazza, Davide Evangelista et al. (+2 more)
Generative models based on flow matching have demonstrated remarkable success in various domains, yet they suffer from a fundamental limitation: the lack of interpretability in their intermediate generation steps. In fact these models learn to transform noise into data through a series of vector field updates, however the meaning of each step remains opaque. We address this problem by proposing a general framework constraining each flow step to be sampled from a known physical distribution. Flow trajectories are mapped to (and constrained to traverse) the
equilibrium states of the simulated physical process. We implement this approach through the 2D Ising model in such a way that flow steps become thermal
equilibrium points along a parametric cooling schedule. Our proposed architecture includes an encoder that maps discrete Ising configurations into a continuous latent space, a flow-matching network that performs temperature-driven
diffusion, and a projector that returns to discrete Ising states while preserving physical constraints. We validate this framework across multiple
lattice sizes, showing that it preserves physical fidelity while outperforming Monte Carlo generation in speed as the
lattice size increases. In contrast with standard flow matching, each vector field represents a meaningful stepwise transition in the 2D Ising model's latent space. This demonstrates that
embedding physical semantics into generative flows transforms opaque neural trajectories into interpretable physical processes.
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All authors Francesco Pivi, Simone Gazza, Davide Evangelista, Roberto Amadini, Maurizio Gabbrielli
Atmospheric and Oceanic Physics
Light scattering by random convex polyhedron in geometric optics approximation
Quan Mu
Based on the convex hull construction
algorithm, a new geometrical model of ice
crystals is proposed to investigate the scattering properties of cirrus clouds particles. Light scattering
matrices involving complete polarization information are calculated in
geometric optics approximation for randomly oriented large
crystals with random and given convex polyhedron shape. The proposed model construction method and computational scheme of light scattering
matrix works for any convex polyhedron within the scope of geometrical optics. To illustrate the broad applicability of the proposed ice
crystal model, scattering
matrices for three ice
crystal examples with different geometrical shapes are calculated under a unified computational framework. Diffraction and absorption are not considered in this work. The calculated results for the classical hexagonal column model show overall agreement with those reported by other authors. The
crystal model and scattering
matrix computational framework developed in this study are applicable to radiative transfer simulations and remote sensing data interpretation in terrestrial and planetary atmospheres.
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Geophysics
Cold-Diffusion Driven Downward Continuation of Gravity Data
Adarsh Jain, Pawan Bharadwaj and Chandra Sekhar Seelamantula
Gravity data can be better interpreted after enhancing high-frequency information via downward continuation. Downward continuation is an ill-posed deconvolution problem. It has been tackled using regularization techniques, which are sensitive to the choice of regularization parameters. More recently, convolutional neural networks such as the U-Net have been trained using synthetic data to potentially learn prior information and perform deconvolution without the need to adjust the regularization parameters. Our experiments reveal that the U-Net is highly sensitive to correlated noise, which is ubiquitously present in geophysical field data. In this paper, we develop a framework based on the $\textbf{cold-diffusion model}$ using the exponential kernel associated with downward continuation. The exponential form of the kernel allows us to train the U-Net to tackle multiple concurrent deconvolution problems with varying levels of blur. This allows our framework to be more robust and quantitatively outperform traditional U-Net-based approaches. The performances also closely matches that of $\textbf{oracle}$ Tikhonov reconstruction technique, which has access to the ground truth.
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