Popular Physics · Cross-listed from astro-ph.SR
Stellar engines and Dyson bubbles can be stable
Colin R McInnes
A range of speculative space ventures envisage the use of ultra-large structures for the collection and reflection of light. Given the length-scale of such structures they cannot be considered as point masses for the calculation of gravitational and radiation pressure forces. Using a simplified model it will be demonstrated that ultra-large reflectors in static
equilibrium levitating above a central
star (so-called
stellar engines) are always unstable if the reflector comprises a uniform disc. However, if the reflector has a non-uniform mass distribution, specifically a ring supporting a reflect or, a
stellar engine can in principle be passively stable. Moreover, while it can be shown that static swarms of reflectors levitating above a central
star (so-called Dyson bubbles) are unstable, in principle they can become passively self-stabilizing if arranged about the
star as a dense cloud. While such ventures are clearly speculative, understanding the orbital dynamics of ultra-large structures, and in particular the conditions for passive stability, can provide insights into the properties of potential technosignatures in search for extraterrestrial intelligence studies.
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Fluid Dynamics
Multi-Condition Digital Twin Calibration for Axial Piston Pumps : Compound Fault Simulation
Chang Dong, Jianfeng Tao and Chengliang Liu
Axial piston pumps are indispensable power sources in high-stakes fluid power systems, including aerospace, marine, and heavy machinery applications. Their operational reliability is frequently compromised by compound faults that simultaneously affect multiple friction pairs. Conventional data-driven diagnosis methods suffer from severe data scarcity for compound faults and poor generalization across varying operating conditions. This paper proposes a novel multi-condition physics-data coupled digital twin calibration framework that explicitly resolves the fundamental uncertainty of pump outlet flow ripple. The framework comprises three synergistic stages: in-situ virtual high-frequency flow sensing on a dedicated rigid metallic segment, surrogate model-assisted calibration of the 3D CFD source model using physically estimated ripple amplitudes, and multi-objective inverse transient analysis for viscoelastic unsteady-friction pipeline parameter identification. Comprehensive experiments on a test rig demonstrate that the calibrated digital twin accurately reproduces both single-fault and two representative compound-fault. These results establish a high-fidelity synthetic fault-generation capability that directly enables robust zero-shot fault diagnosis under previously unseen operating regimes and fault combinations, thereby advancing predictive maintenance in complex hydraulic systems.
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Data Analysis and Statistics · Cross-listed from hep-ph
Unfolding without Iterations, Adversaries, or Surrogates
Ayodele Ore and Tilman Plehn
Correcting measurements for detector effects and constructing appropriate public data representations is a pressing problem in LHC physics. Current methods solve this inverse problem by relying on iterations, minimax optimization, or a surrogate forward mapping. We introduce Adversary-free Unfolding SanS Iteration or Emulation (AUSSIE), which dispenses with these mechanisms while remaining asymptotically correct. AUSSIE replaces the second OmniFold step with a new loss function that directly yields solutions with minimal dependence on the reference simulation. We showcase AUSSIE on various unfolding tasks, including full-phase-space jet substructure.
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Geophysics · Cross-listed from astro-ph.SR
The First Four Ground-Level Enhancements in the 1940s: Investigation, Digitisation, and Analysis of Forgotten Data
Hisashi Hayakawa, Stepan Poluianov, Sergey Koldobskiy et al. (+4 more)
Intense
solar eruptions occasionally accelerate
solar energetic particles (SEPs) and can trigger ground-level enhancements (GLEs). Among the 77 known GLEs, the first four GLEs, #1 – 4 in the 1940s took place before the advent of the standard
neutron monitors and were missing from the International GLE Database. This data gap challenged their quantification. To overcome this difficulty, we systematically gathered, digitised, and quantified contemporaneous
cosmic-ray records pertaining to these GLEs. These data allow us to reconstruct the temporal
evolution, with the 1 – 15 min resolutions, of these GLEs, and broaden their geographical coverage to a global scale. GLEs #1 and #3 exhibited gradual increases in their rise times, measured at 45 +/- 15 and 105 +/- 15 min, respectively. In contrast, GLEs #2 and #4 both exhibited abrupt increases of 15 +/- 15 min. We also compared integral ionisation increase on the standard ionisation chambers and their local geomagnetic cutoff
rigidities Pc to qualitatively compare these GLE's spectral hardness: Our result indicates that their spectra are extremely hard for GLEs #2 and #4 and mildly hard for GLEs #1 and #3. GLE #3 showed the greatest integral ionisations for polar detectors among them.
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All authors Hisashi Hayakawa, Stepan Poluianov, Sergey Koldobskiy, Alexander Mishev, Nicholas Larsen, Inna Usoskina, Ilya Usoskin
Applied Physics · Cross-listed from cond-mat.mtrl-sci
Resolving the Metastable Si-XIII Structure through Convergent Theory and Experiment
Fabrizio Rovaris, Corrado Bongiorno, Anna Marzegalli et al. (+10 more)
Silicon is the undisputed cornerstone of modern technology, with applications ranging from micro- and opto-electronics to
quantum technologies. Recently, the exploration of its allotropes has emerged as a pivotal frontier for engineering materials with tailored optical and electronic functionalities. High-pressure experiments have revealed several metastable silicon phases, among which is Si-XIII. First observed more than 20 years ago, this phase has remained structurally unidentified, representing a significant gap in our understanding of elemental silicon allotropy. In this work, a convergent methodology is employed combining advanced theoretical modeling with experimental characterization to finally resolve the long-standing structural assignment of Si-XIII. Guided by careful experimental observations, a structural model validated through first-principles optimization and systematically tested against multiple experimental signatures is constructed. All the fingerprints of this phase are rationalized by our proposed
crystal structure: interplanar spacings, Raman frequencies, thermodynamic stability, and kinetic pathways. These findings provide a crucial missing piece in the high-pressure phase diagram of silicon and demonstrate the power of integrating computational predictions with experimental validation to resolve complex structural problems in materials science.
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All authors Fabrizio Rovaris, Corrado Bongiorno, Anna Marzegalli, Mouad Bikerouin, Davide Spirito, Gerald J. K. Schaffar, Mohamed Zaghloul, Agnieszka Anna Corley-Wiciak, Francesco Montalenti, Verena Maier-Kiener, Giovanni Capellini, Antonio M. Mio, Emilio Scalise
Chemical Physics
Relativistic Complete Active Space Self-consistent-Field Method with a Hierarchy of Exact Two-Component Hamiltonians
Xubo Wang, Sen Wang, Yixuan Wu et al. (+1 more)
The development of a novel exact two-component (X2C) scheme with the inclusion of the picture-change correction for the fluctuation potential, the X2Ccorr scheme, is reported, hereby establishing a hierarchy of X2C schemes with systematic improvement for the treatments of relativistic two-electron contributions. Using
benchmark X2C complete active space self-consistent-field (CASSCF) calculations for zero-field splittings in chalcogen diatomics, the contributions of two-electron
spin-orbit coupling, electron
spin-
spin coupling, and
quantum electrodynamics are carefully analyzed. The capability of the new Cholesky decomposition-based implementation for relativistic two-component CASSCF method using super-configuration-interaction
algorithms is further demonstrated with calculations for the low-lying electronic states of neodymium aqua-ions with up to the second coordination shells.
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All authors Xubo Wang, Sen Wang, Yixuan Wu, Lan Cheng
Fluid Dynamics
BLISSNet: Deep Operator Learning for Fast and Accurate Flow Reconstruction from Sparse Sensor Measurements
Maksym Veremchuk, K. Andrea Scott and Zhao Pan
Reconstructing fluid flows from sparse sensor measurements is a fundamental challenge in science and engineering. Widely separated measurements and complex, multiscale dynamics make accurate recovery of fine-scale structures difficult. In addition, existing methods face a persistent tradeoff: high-accuracy models are often computationally expensive, whereas faster approaches typically compromise fidelity. In this work, we introduce BLISSNet, a model that strikes a strong balance between reconstruction accuracy and computational efficiency for both flow reconstruction and nudging-based data assimilation. The model follows a DeepONet-like architecture, enabling zero-shot inference on domains of arbitrary size. After the first model call on a given domain, certain network components can be precomputed, leading to low inference cost for subsequent evaluations on large domains. Consequently, the model can achieve faster inference than classical interpolation methods such as radial basis function or bicubic interpolation. This combination of high accuracy, low cost, and zero-shot generalization makes BLISSNet well-suited for large-scale real-time flow reconstruction and data assimilation tasks.
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Optics
Electro-optic frequency combs for multi-wavelength digital holography with high dynamic range
Leonard Voßgrag, Annelie Schiller, Tobias Seyler et al. (+3 more)
Multi-wavelength digital holography enables surface-shape measurements with an exceptional dynamic range by combining interferometric resolution with synthetic wavelengths spanning multiple length scales. Although the concept promises measurement ranges of many orders of magnitude, its practical implementation is limited by the lack of light sources that allow fast, reliable, and calibration-free switching between synthetic wavelengths over a wide frequency range. Here, we present a synthetic-wavelength generator based on an electro-optic frequency comb with electronically tunable modulation frequency and a set of switchable band-pass filters. By combining discrete selection of comb-lines with continuous
radio-frequency tuning, the proposed scheme merges the advantages of single-sideband modulation and filter-based comb extraction. Using only off-the-shelf components, the system provides synthetic frequencies from 0.1-220GHz, corresponding to synthetic wavelengths from meters down to millimeters in the visible. The generator achieves MHz-level frequency accuracy, side-mode suppression exceeding 40dB, and switching times below 25ms, even without active stabilization. We characterize the spectral purity and frequency agility of the source and demonstrate rapid tuning of synthetic wavelengths over 3 orders of magnitude. We apply the light source to multi-wavelength digital holography and reconstruct the surface of an industrially machined metal part featuring height variations from 0.1-100mm. The measurements achieve ten-mum-level precision using 7 single wavelengths covering synthetic wavelengths from 1.36mm to 1.874m within an acquisition time < 2s. The presented architecture combines high dynamic measurement range of 50dB, fast electronic reconfigurability, and intrinsic frequency calibration, making it a promising light source for high-speed interferometric surface metrology.
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All authors Leonard Voßgrag, Annelie Schiller, Tobias Seyler, Jens Kießling, Daniel Carl, Ingo Breunig
Optics
A synergistic approach to optical modeling of PCSELs through rigorous methods and the coupled-wave theory
Arstan Bisianov and Andreas Waag
A wide range of numerical and semi-analytical approaches has been developed for optical modeling of photonic-
crystal surface-emitting
lasers (PCSELs). However, a systematic framework for comparing their predictive capabilities and identifying their respective validity limits remains largely unexplored. In this work, we introduce a comparative methodology in which four representative methods-including rigorous numerical and effective-index-based approaches-are analyzed and partially hybridized within a coupled-wave-theory framework. Using single- and double-
lattice PCSELs as representative models, we demonstrate that this approach not only reveals fundamental differences between predictions of rigorous methods and the coupled-wave-theory framework, but also captures leaky and
symmetry-broken phases of bound states in the continuum (BICs) relevant for
laser operation.
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Instrumentation and Detectors
A 200 dB Dynamic Range Radiation-Hard Delta-Sigma Current Digitizer for Beam Loss Monitoring
Luca Giangrande
This manuscript describes a radiation-hardened current-mode delta-sigma ADC fabricated in a standard 130 nm CMOS technology and qualified for total ionizing doses up to 100 Mrad. The operational signal range achieved with a 100 s integration window exceeds 200 dB. The converter is designed for beam loss monitoring applications in high-energy physics, where it must handle input currents spanning nine decades, from 1 mA down to 1 pA, while providing a fast 10 us response time for machine protection. To meet these conflicting requirements, the architecture exploits the inherent trade-off between resolution and acquisition time provided by delta-sigma conversion: a first-order architecture, sampling at 20 MHz, delivers 11-bit effective resolution within the critical 10 us window for critical currents around 1 mA. Integration times above 10 s enable the sub-picoampere resolution required for precise beam
alignment and background monitoring. The chip integrates two independent channels, consumes 25 mW from a 1.2 V supply, and relies on radiation-hardening techniques such as triple-redundant digital logic, custom ESD protections, and manual enclosed layout for critical analog transistors. Post-irradiation measurements up to 100 Mrad show no significant performance degradation, and the uncalibrated integral nonlinearity remains within [+4, -5] LSBs over the 1 mA to 5 uA range. The converter's flexibility and radiation tolerance make it suitable not only for the HL-LHC beam loss monitoring upgrade but also for other precision current measurement applications in harsh environments.
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Medical Physics
Gestational Stage Prediction from Cervical Tissue Analysis Using Imaging Mueller Polarimetry Data
Sooyong Chae, Ajmal Ajmal, Junzhu Pei et al. (+5 more)
Preterm birth is associated with premature cervical remodeling, yet current clinical assessments cannot detect the underlying microstructural changes in collagen organization. We apply imaging Mueller polarimetry to murine cervical tissue at three gestational stages (early, mid, late) and develop classification methods to predict gestational stage from polarimetric maps. Using Lu-Chipman decomposition, we extract orientation and azimuth local variability maps that capture collagen fiber
alignment and disorder. We evaluate two approaches under 20-fold leave-one-out cross-validation: an analytical threshold classifier on mean azimuth local variability, and a lightweight CNN ensemble (approximately 76k parameters) operating on spatially resolved maps. The ensemble achieves 70..0% sample-level accuracy, outperforming the analytical baseline (55.0%), with strong performance on early (71.0%) and late (86.0%) gestation. Spatial prediction maps confirm that classification accuracy is highest in the stroma, where collagen remodeling is most prominent. These results demonstrate that Mueller polarimetry combined with deep learning models can detect gestational collagen remodeling noninvasively, offering a potential pathway toward objective cervical assessment for preterm birth risk.
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All authors Sooyong Chae, Ajmal Ajmal, Junzhu Pei, Amanda Sanchez, Tananant Boonya-ananta, Andres Rodriguez, Tatiana Novikova, Jessica C. Ramella-Roman
Instrumentation and Detectors · Cross-listed from hep-ex
End-to-end Differentiable Calibration and Reconstruction for Optical Particle Detectors
Omar Alterkait, César Jesús-Valls, Ryo Matsumoto et al. (+2 more)
Large-scale homogeneous detectors with optical readouts are widely used in particle detection, with Cherenkov and scintillator
neutrino detectors as prominent examples. Analyses in experimental physics rely on high-fidelity simulators to translate sensor-level information into physical quantities of interest. This task critically depends on accurate calibration, which aligns simulation behavior with real detector data, and on tracking, which infers particle properties from optical signals. We present the first end-to-end differentiable optical particle detector simulator, enabling simultaneous calibration and reconstruction through gradient-based optimization. Our approach unifies simulation, calibration, and tracking, which are traditionally treated as separate problems, within a single differentiable framework. We demonstrate that it achieves smooth and physically meaningful gradients across all key stages of light generation, propagation, and detection while maintaining computational efficiency. We show that gradient-based calibration and reconstruction greatly simplify existing analysis pipelines while matching or surpassing the performance of conventional non-differentiable methods in both accuracy and speed. Moreover, the framework's modularity allows straightforward adaptation to diverse detector geometries and target materials, providing a flexible foundation for experiment design and optimization. The results demonstrate the readiness of this technique for adoption in current and future optical detector experiments, establishing a new paradigm for simulation and reconstruction in particle physics.
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All authors Omar Alterkait, César Jesús-Valls, Ryo Matsumoto, Patrick de Perio, Kazuhiro Terao
Biological Physics · Cross-listed from cond-mat.soft
MesoMem: A mesoscale membrane model based on an additive potential
Pietro Sillano, Siewert-Jan Marrink and Timon Idema
Bridging the gap between atomistic detail and continuum mechanics is a central challenge in modeling biological membranes, particularly for mesoscopic phenomena spanning large length and time scales. In this work, we introduce a new, solvent-free, one-particle-thick, coarse-grained model for lipid
bilayers, governed by an additive potential. Our approach treats orientational elasticity through distinct additive energy terms for tilt and splay, offering an unbiased potential form. The model is implemented in the LAMMPS molecular dynamics engine. Our simulations show spontaneous self-assembly of lamellar structures and stable vesicles from disordered states. We map the dynamical phase diagram of the system, identifying distinct gel-like, fluid, and gas regimes, controlled by temperature and the steepness of the isotropic attraction. The model accurately reproduces the theoretical $1/q^{4}$ fluctuation spectrum for tensionless membranes and exhibits tunable mechanical properties, including biologically relevant bending
rigidities. We show how we can include osmotic pressure and spontaneous
curvature in our model. Finally, we demonstrate the model's applicability to complex membrane remodeling by simulating the adhesive wrapping of colloidal nanoparticles, recovering the predicted dependency on particle size and adhesion strength.
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Optics
Spark-Induced Shockwave Dynamics Revealed via Nonresonant Four-Wave Mixing
Marios Kounalakis, Mikhail N. Shneider and Alexandros Gerakis
We report on the experimental detection of shockwave dynamics produced in a spark discharge, using a nonresonant four-wave mixing optical technique. In particular, we observe the spark-induced local density perturbation across a millimeter-range probe volume, centered on the discharge, via single-shot coherent Rayleigh-Brillouin scattering. We detect the emergence of shock-induced flow velocities, which appear as distinct features in the spectrum, and monitor their dynamic
evolution from a few hundred nanoseconds to microseconds after the spark. Finally, we
benchmark our measurements against simulations based on a one-dimensional compressible flow model. Our results pave the way for quantitative measurements of highly non-uniform transient flows in challenging environments featuring non-
equilibrium gas kinetics.
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Accelerator Physics
Efficient Acceleration of High-Quality GeV-Electron Bunches in a Hybrid Laser- and Beam-Driven Plasma Wakefield Accelerator
F. M. Foerster, M. Ayache, Z. Bi et al. (+24 more)
Plasma-based accelerators are compact and provide high gradients, yet their practical use has been limited by energy gain, stability, beam quality, and energy transfer efficiency. Here, we address several of these challenges simultaneously using a hybrid scheme in which an electron bunch from a
laser wakefield accelerator (LWFA) drives a subsequent
plasma wakefield accelerator (PWFA) stage with internal witness injection. Close to driver depletion in the PWFA stage, we obtain witness bunches with higher electron energy, reduced energy spread and divergence, and higher angular-spectral charge density compared to LWFA alone. We report energy
transformer ratios approaching~2, and about 20% of the initial energy in the drive beam was transferred to the witness bunch, thereby achieving a driver-to-witness energy transfer efficiency that largely surpasses that of all previous PWFA experiments.
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All authors F. M. Foerster, M. Ayache, Z. Bi, M. Cerchez, S. Corde, A. Döpp, F. Haberstroh, A. F. Habib, T. Heinemann, B. Hidding, A. Irman, F. Irshad, O. Kononenko, M. LaBerge, A. Martinez de la Ossa, A. Münzer, F. Peña, G. Schilling, S. Schöbel, U. Schramm, S. Sharan, E. Travac, P. Ufer, N. Weiße, M. Zeuner, J. Zirkelbach, S. Karsch
Fluid Dynamics
Bayesian inference of flame impulse responses
Matthew Yoko and Wolfgang Polifke
The impulse response of a flame to acoustic velocity perturbations is a key quantity for predicting thermoacoustic stability, but its identification from sparse, noisy observations requires solving an ill-posed inverse convolution problem. This is typically achieved with system identification methods, which require hand-tuning of regularization, model order, and sampling parameters, and provide no principled mechanism for incorporating prior physical knowledge. In this paper, we reformulate the identification problem within a
Bayesian framework. The impulse response is represented as a physically motivated distributed time delay model, whose parameters correspond to convective delays and dispersive broadening. For a given number of pulses, the model parameters are inferred from the data using
Bayesian parameter inference. The number of pulses is then selected using
Bayesian model comparison, which balances data fit against model complexity to identify the simplest model capable of explaining the data. The framework is demonstrated on broadband-forced large eddy simulation data from a turbulent swirl-stabilized burner.
Bayesian model comparison selects a three-Gaussian impulse response for this flame, consistent with physical interpretations in previous work. Compared with system identification, the
Bayesian approach produces impulse responses with fewer spurious features and enables straightforward enforcement of a known low-frequency gain. Finally, we show that the
Bayesian approach is robust to significant reductions in recording length, making it appealing for impulse response identification from costly simulations, where there is an incentive to minimize computational cost.
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Optics · Cross-listed from cond-mat.mes-hall
Integrated nanophotonic platform for on-chip quantum emitter interactions and entanglement
Yinhui Kan, Shailesh Kumar, Xujing Liu et al. (+2 more)
Entanglement between solid-state
quantum emitters (QEs) is a key resource for photonic
quantum technologies. Achieving such
entanglement requires strong and controllable long-range interactions between QEs. However, engineering such coupling remains challenging, particularly for on-chip distant solid-state QEs. Here, we introduce a forward-designed platform that enables ultracompact nanophotonic architectures to mediate enhanced long-range QE-QE interactions via engineered surface plasmon polariton interference. Using this strategy, we realize two distinct configurations: a phase-conjugated
elliptic design for energy funneling, and a co-radiating
hyperbolic design for its suppression. We experimentally demonstrate large enhancement and suppression of energy transfer rates compared to bare substrates. Furthermore, we predict transient
entanglement between spatially separated QEs with concurrence peaking at 0.493, approaching the theoretical bound in the transient regime. Extending to the multi-QE case, we observe enhanced energy funneling and predict QE-QE
entanglement in three-QE configurations. These results establish a compact and scalable framework for on-chip
entanglement engineering in integrated
quantum nanophotonic systems.
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All authors Yinhui Kan, Shailesh Kumar, Xujing Liu, Antonio I. Fernández-Domínguez, Sergey I. Bozhevolnyi
Computational Physics
Shaping the Digital Future of ErUM Research: Sustainability & Ethics
Luca Di Bella, Jan Bürger, Markus Demleitner et al. (+36 more)
This workshop report from "Shaping the Digital Future of ErUM Research: Sustainability & Ethics" (Aachen, 2025) reviews progress on sustainability measures in data-intensive ErUM-Data research since the 2023 call-to-action on resource-aware research. It evaluates short-, medium-, and long-term actions around monitoring and reducing CO2 emissions, improving data and software
FAIRness, optimizing workflows and computing infrastructures, and aligning operations with low-carbon energy availability, including concepts such as "breathing" computing centers, long-term data storage strategies, and software efficiency certification. The report stresses the need for systematic teaching, training, mentoring, and new support formats to establish sustainable coding and computing practices, particularly among students and early-career researchers, and highlights the importance of dedicated steering and funding instruments to embed sustainability in project planning. Ethical discussions focus on the transformative use of AI in ErUM-Data, addressing autonomy, bias, transparency, explainability, attribution of responsibility, and the risk of deskilling, while reaffirming that accountability for scientific outcomes remains with human researchers. Finally, the report emphasizes that sustainable transformation requires not only technical measures but also targeted awareness-building, communication strategies, incentives, and community-driven initiatives to move from awareness to action and to integrate sustainability and ethics into everyday scientific practice.
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All authors Luca Di Bella, Jan Bürger, Markus Demleitner, Torsten Enßlin, Johannes Erdmann, Martin Erdmann, Benjamin Fischer, Martin Gasthuber, Gabriele Gramelsberger, Wolfgang Gründinger, Prateek Gupta, Johannes Hartl, Maximilian Horzela, Vijay Kartik, Stefan Krischer, Eva Kröll, Thomas Kuhr, Katharina Kürschner, Inga Lakomiec, Valerie Lang, Kristin Lohwasser, Thomas Metcalf, Martin Möller, Saskia Nagel, Susanne Pfalzner, Rebecca Redlin, Christopher Schrader, Kathrin Schulz, Markus Schumacher, Kilian Schwarz, Fabian Sigler, Dwayne Spiteri, Achim Stahl, Judith Steinfeld, Wim Vanderbauwhede, Cyrus Walther, Angela Warkentin, Peter Wissmann, Eoin Woods
Biological Physics
Ecological memory of hydrodynamic cues shapes growth and migration of motile microorganisms
Narges Kakavand and Anupam Sengupta
Microorganisms live in inherently dynamic environments where fluctuations in biotic and abiotic factors shape their behaviour, physiology, and fitness. The concept of ecological
memory: the lasting imprint of prior environmental cues, suggests that past exposures can exert prolonged effects on microbial growth, resilience, and phenotypic expressions. For motile microbes in aquatic ecosystems, environmental variability is mediated by fluid motion, which may engender a form of hydrodynamic
memory, whereby prior exposure to specific spatio-temporal cues influence future growth and migratory behaviour. Yet, the emergence of such flow-induced
memory, or its long-term consequences for trait
evolution and population dynamics, remain unexplored. We integrate millifluidic flow control, high-resolution
cell tracking, and tunable hydrodynamic cues to quantify growth and migration of Heterosigma akashiwo, a model microbe, across growth stages. Using two complementary perturbation scenarios: standard (flow after static conditions) and reverse (flow before static growth), we test how the temporal structure of forcing shapes multigenerational responses. This combinatorial design disentangles exposure history from its duration, and reveals how prior flow modulates sensitivity, generating legacy effects. Compared with static controls, repeated hydrodynamic exposure alters doubling time, carrying capacity, gravitactic stability, and swimming speed distributions; shifting growth phase progression and tolerance to subsequent perturbations. These results establish a mechanistic framework for flow-induced
memory in motile microbes, revealing how past fluidic cues shape future growth and migration. Our study advances predictive understanding of motile microbes in natural and engineered hydrodynamic systems experiencing increasing variability under global environmental changes.
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Optics
All-optical control of second-harmonic generation in $\beta$-BaB$_2$O$_4$ via coherent, terahertz-driven acentric lattice displacement
Flavio Giorgianni, Nicola Colonna, Gabriel Nagamine et al. (+6 more)
Dynamical control of the nonlinear optical properties of solids – with light itself – will be essential for future ultrafast photonic technologies. Previously, methods to modulate nonlinear processes including second-harmonic generation (SHG) have relied primarily on non-resonant light-matter interaction or photo-generation of hot electrons in nanoscale materials. However, these approaches are typically constrained by limited interaction lengths and the initial frequency conversion is relatively weak under
equilibrium conditions. Here, an approximately 30% modulation of efficient phase-matched SHG in bulk beta-barium borate (beta-BaB2O4) is achieved through transient
lattice deformation by intense terahertz (THz) pulses that are tuned to resonance with an infrared-active
phonon mode. The effect originates from modification of the index of refraction ellipsiod and the corresponding nonlinear phase-matching conditions, rather than from direct modulation of the nonlinear susceptibility through THz-mediated chi^(3) processes. This mechanism, of resonant selective
lattice excitation, points toward novel THz-control schemes to tune the nonlinear optical response in materials.
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All authors Flavio Giorgianni, Nicola Colonna, Gabriel Nagamine, Leonie Spitz, Guy Matmon, Alexandre Trisorio, Nicolas Forget, Carlo Vicario, Adrian L. Cavalieri
Computational Physics · Cross-listed from quant-ph
Learning spectral density functions in open quantum systems
Felipe Peleteiro, João Victor Shiguetsugo Kawanami Lima, Pedro Marcelo Prado et al. (+2 more)
Spectral density functions quantify how environmental modes couple to
quantum systems and govern their open dynamics. Inferring such frequency-dependent functions from time-domain measurements is an ill-conditioned inverse problem. Here, we use exactly solvable
spin-
boson models with pure-dephasing and amplitude-damping channels to reconstruct spectral density functions from noisy simulated data. First, we introduce a parameter estimation approach based on machine learning regressors to infer Lorentzian and Ohmic-like spectral density parameters, quantifying robustness to noise. Second, we show that a cosine transform inversion yields a physics-consistent spectral prior estimation, which is refined by a constrained neural network enforcing positivity and correct asymptotic behaviour. Our neural network framework robustly reconstructs structured spectral densities by filtering simulated noisy signals and learning general functional dependencies.
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All authors Felipe Peleteiro, João Victor Shiguetsugo Kawanami Lima, Pedro Marcelo Prado, Felipe Fernandes Fanchini, Ariel Norambuena
Plasma Physics
Stellarator island divertor shape optimization for reduced peak heat fluxes
Avigdor Veksler, Aaron Bader, Heinke Frerichs et al. (+1 more)
An automated
algorithm to construct island divertors for stellarators is presented and used to find divertors that meet heat load requirements determined by material limits. The
algorithm uses just two initial conditions: two starting coordinates on the island separatrix chosen by the user. We leverage the simplicity of the
algorithm to explore the divertor parameter space in a fixed
magnetic equilibrium. Heat loads are approximated using the field line
diffusion model implemented in the
FLARE code. Divertor solutions that satisfy heat load requirements while maintaining a high power fraction captured are found using a parameter scan and a
Bayesian optimization routine. The optimization finds divertors that perform the same as the parameter scan, but with a 75% reduction in computational cost. The resulting divertors satisfy heat load requirements across varying cross-field heat diffusivities. Optimization over various islands in the
equilibrium shows that it is easiest to find divertors that satisfy heat flux requirements for low-elongation islands. This
algorithm presents a simple parameterization for island divertors and facilitates further physics and optimization studies.
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All authors Avigdor Veksler, Aaron Bader, Heinke Frerichs, Elizabeth Paul
Optics · Cross-listed from quant-ph
Saturable nonlinearities in a driven-dissipative bosonic quantum battery
João P. R. Leonel and Paulo A. Brandão
We investigate the charging of a nonlinear
quantum battery consisting of a single bosonic mode subject to a saturable nonlinearity, coherent driving, and dissipation. In contrast to Kerr-type anharmonicities, the saturable interaction induces a bounded and nonlinear distortion of the energy spectrum, leading to a progressive increase in the density of energy levels. We analyze the time
evolution of the energy and ergotropy of the battery by solving a Lindblad master equation and show that the nonlinear spectral structure significantly affects both transient charging behavior and steady-state properties. Our results reveal that, for a broad range of parameters, the saturable nonlinearity enhances the maximum stored energy and modifies the ergotropy generation in the presence of losses. The interplay between dissipation and bounded spectral nonlinearity provides a controllable mechanism to tune energy storage and work extraction in bosonic
quantum batteries.
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Applied Physics · Cross-listed from cond-mat.mes-hall
Nanoelectronics with Two Dimensional Magnets
Bing Zhao, Roselle Ngaloy, Lalit Pandey et al. (+3 more)
Two dimensional (2D) magnets have emerged as a compelling platform for
spin based nanoelectronics, enabling atomic scale control of
magnetic order, interfaces,
quantum geometry, and
symmetry. Here, we highlight recent advances in 2D ferromagnets, antiferromagnets, altermagnets, and related
magnetic phases, emphasizing how enhanced Curie temperatures, perpendicular
magnetic anisotropy, and unconventional
magnetic orders translate into device relevant functionality.
Spin dependent transport in vertical
magnetic tunnel junctions and lateral
spin valves based on 2D
heterostructures are discussed, where atomically sharp interfaces enable highly tunable
spin injection, propagation, and detection. We further focused on field free energy efficient
spin orbit torque magnetization switching in 2D
magnetic heterostructures, in which unconventional
spin currents originate from an adjacent low
symmetry spin orbit layer. Microscopic mechanisms involving
symmetry breaking, Berry
curvature, and orbital angular momentum transport are discussed, along with key challenges, including switching determinism and torque efficiency. Materials and device design strategies targeting neuromorphic, hybrid
quantum spintronic, and multifunctional architectures are outlined. Collectively, these developments position 2D magnets as a promising candidate for tunable, energy efficient integrated spintronic technologies that can harness intertwined
spin, charge, orbital, and topological degrees of freedom at the nanoscale.
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All authors Bing Zhao, Roselle Ngaloy, Lalit Pandey, Himanshu Bangar, Divya P. Dubey, Saroj P. Dash
Instrumentation and Detectors
Characterization of CMOS SPADs for future RICH Detectors
R. Dolenec, H.K. Yildirim, G.V. Tran et al. (+12 more)
In the planned or considered upgrades of LHCb, ALICE and Belle II experiments, the Ring imaging Cherenkov (RICH) detectors will have to be improved in order to function at increased beam interaction density. The photodetectors used in future RICH detector will have to provide high granularity, single
photon sensitivity and excellent timing, while being exposed to a couple of 10$^{13}$ 1-MeV
neutron equivalent/cm$^2$ of background irradiation during total experiment run time. The spadRICH project is developing a CMOS single-
photon avalanche diode (SPAD) based photodetector specifically optimized for the application of the planned RICH detectors, which includes
neutron radiation hardness and cryogenic operation. In this work we present recent experimental characterization studies of existing SPADs produced in 55 nm BCD and 110 nm CMOS image sensor technologies. Main results include dark count rate (DCR) measurements with SPADs irradiated up to 10$^{12}$ 1-MeV
neutron equivalent/cm$^2$ and cooled down to
liquid nitrogen temperature.
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All authors R. Dolenec, H.K. Yildirim, G.V. Tran, A. Domenech, B.C. Efe, W.Y. Ha, U. Karaca, P. Singh, G.G. Taylor, S. Korpar, P. Križan, R. Pestotnik, A. Seljak, E. Charbon, C. Bruschini
Applied Physics
Measurement and Modeling of Structure-Induced Surface Scattering on Terahertz Channel
Peian Li, Yapeng Ge, Jiacheng Liu et al. (+8 more)
As terahertz (THz) frequencies emerge as promising candidates for next-generation wireless networks, accurate characterization of propagation mechanisms in indoor/outdoor environments becomes essential for system design and performance optimization. This article presents an experimental and theoretical investigation of structure-induced indoor surface scattering on THz channels, examining how material properties and structural configurations jointly govern channel power and angular distribution. Six representative indoor surfaces are characterized, revealing that intrinsic structural inhomogeneity – particularly the quasi-periodic earlywood-latewood arrangement in pine wood – induces measurable angular scattering whose dominant lobes and angular shifts are reproduced by a beam-propagation modeling (BPM) framework. Material-covered surface configurations are further investigated, demonstrating that thin dielectric covering layers can substantially modify reflection characteristics through thickness- and frequency- dependent thin-film interference effects. Wide-angle bistatic measurements conducted in a conference-room environment reveal that structured indoor elements, such as folded curtains, can enhance angular scattering and extend spatial coverage. These findings establish that structure-induced surface scattering mechanisms offer potential for constructing non-line-of-sight THz links in indoor environments.
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All authors Peian Li, Yapeng Ge, Jiacheng Liu, Wenbo Liu, Jiayuan Cui, Jiabiao Zhao, Qiang Niu, Yuping Yang, Xiangzhu Meng, Yiming Zhao, Jianjun Ma
Physics and Society
Cross-order induced behaviors in contagion dynamics on higher-order networks
Kaloyan Danovski, Sandro Meloni and Michele Starnini
Recent studies have shown that novel collective behaviors emerge in complex systems due to higher-order interactions. However, the way in which the structural correlations of these interactions shape such behaviors remains a significant gap in current research. To address this, we use signatures of higher-order behaviors (HOBs) to identify the underlying dynamical rules, or higher-order mechanisms (HOMs). In this work, we compare several HOB measures derived from information theory. Utilizing a simplicial SIS contagion model, we demonstrate that simpler, computationally efficient measures can serve as robust indicators of HOMs. We uncover the novel phenomenon of cross-order induced behaviors, where behavioral signatures emerge at interaction orders where no direct mechanism is present. Crucially, these cross-order HOBs are not simply induced by structural correlations – such as nestedness and hyperedge overlap – but they appear in the neighborhood of any HOM. Among the information-theoretic measures we tested, synergy is the most reliable indicator of the true order where the underlying mechanism is at play. These findings offer new insights into the relationship between the network structure and observed dynamics of higher-order systems.
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Optics
Tunable Dynamic Speckle Generation for Random Illumination Microscopy
Lilian Magermans, Assia Benachir, Nathan P. Spiller et al. (+7 more)
Speckled illumination enhances widefield fluorescence microscopy by enabling optical sectioning and super resolution. In random illumination microscopy, sequences of speckled illumination patterns are used to excite fluorescent samples and images are reconstructed based on a statistical analysis of the intensity fluctuations. Although random illumination microscopy has been shown to give excellent performance, its widespread implementation is hindered by the high cost and complexity of the generation of suitable speckled illumination patterns, which is achieved using digital micro-mirror devices or spatial light modulators. Here, we present a zwitterion-doped
liquid crystal (LC) device capable of generating independent, high-contrast speckle patterns with a tunable decorrelation time in the 0.1 s to 0.1 ms range under visible
laser illumination. This LC-based dynamic speckle generator is applied to widefield random illumination fluorescence microscopy of tissue and
cell samples, where it enables optical sectioning with a 2 micron axial resolution, and a 1.5-fold improvement in lateral spatial resolution. Owing to its low cost and simplicity, this LC speckle generator offers an attractive alternative to digital micro-mirror and spatial light modulator devices for implementing widefield random illumination microscopy.
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All authors Lilian Magermans, Assia Benachir, Nathan P. Spiller, Tianxin Wang, Federico Vernuccio, Randy Bartels, Stephen M. Morris, Steve J. Elston, Martin J. Booth, Hervé Rigneault
Plasma Physics
Available Energy and Ground States of Convective Hydrodynamic and Hydromagnetic Instabilities
Kaixuan Fan and Yao Zhou
We propose a method for predicting the nonlinear saturation level of convective instabilities in neutral and magnetized fluids. The method combines Gardner's restacking
algorithm, which computes the available energy and ground states of collisionless
plasmas in phase space, and Lagrangian relaxation, where fluid elements find lower-energy
equilibria while preserving local invariants. For the incompressible Rayleigh-Taylor instability, the problem is formally equivalent to Gardner's and the restacking
algorithm directly applies in configuration space. To treat compressibility, we follow restacking with Lagrangian relaxation to obtain the ground state, and the results show excellent agreement with direct numerical simulations. Successful extension to the $m=0$ interchange instability in a Z-pinch demonstrates the method's potential as a general framework for estimating the nonlinear extent of convective instabilities, which can facilitate the design and operation of fusion reactors.
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Optics
Generation of High-order Laguerre-Gaussian modes in Coated and Uncoated Graded-Index and Step-Index Multimode Fibers
Wasyhun Asefa Gemechu, Umberto Minoni, Michela Borghetti et al. (+4 more)
We report an efficient experimental method for generating high-order Laguerre-Gauss (HOLG) modes by simply coupling a Gaussian beam into the cladding of a multimode fiber (MMF). In particular, the order of the HOLG mode remains invariant with respect to input power, propagation distance, and pulse duration. Furthermore, spectral and power measurements confirm that the beam-shaping mechanism is predominantly linear, whereas Kerr nonlinearity primarily affects the longitudinal phase-matching condition and conversion efficiency, without altering the generated mode order. Altogether, these findings establish our approach as a highly robust and scalable platform for generating tailored optical beams.
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All authors Wasyhun Asefa Gemechu, Umberto Minoni, Michela Borghetti, Fabrizio Frezza, Daniele Modotto, Stefan Wabnitz, Fabio Mangini