Instrumentation and Detectors
Time-domain anode-decoupling co-design for a floating microchannel plate detector readout
Robin F. Bonny, Lorenzo Obersnel, Martin Rubin et al. (+3 more)
We present a microchannel plate (MCP) detector for compact time-of-flight mass spectrometers (TOF-MS) that jointly optimizes the anode geometry and high-voltage AC-decoupling network for electrically floating operation. Undershoot-driven baseline artifacts and pulse broadening are addressed by a time-domain co-design of the anode geometry and decoupling network. The design is validated through a staged workflow that combines full-wave electromagnetic simulations, vector network analyzer measurements,
circuit-level transient models, and end-to-end mass spectra. The resulting planar circular patch anode with anode-proximal decoupling confines fields, preserves peak amplitude, and suppresses post-pulse energy, leading to fast settling and minimal baseline wander. We show that the effective high-pass corner set by the decoupling capacitance directly governs undershoot decay and baseline recovery. Measurements in a representative TOF-MS test setup demonstrate waveguide-level pulse fidelity at a fraction of the mass and volume of heritage waveguide-based detectors, with residual ripples in the measured response originating from downstream cable and digitizer terminations rather than the detector itself. By limiting detector-induced temporal broadening and inter-peak baseline coupling, the design supports high mass resolution and dynamic range in miniaturized TOF-MS architectures. Variants of this planar flight-ready architecture are being implemented in several next-generation spaceborne TOF-MS instruments currently under development at the University of Bern.
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All authors Robin F. Bonny, Lorenzo Obersnel, Martin Rubin, André Galli, Peter Wurz, Rico G. Fausch
Optics
Gold-polymer hybrid metasurface for polarization-independent enhanced third harmonic generation in the ultraviolet
Shroddha Mukhopadhyay, Ana Conde-Rubio, Jose Trull et al. (+4 more)
We present a combined experimental and theoretical study of nonlinear light-matter interactions in a three-dimensional gold-
polymer hybrid metasurface. In contrast to conventional two-dimensional designs, which by
symmetry may support either transverse electric (TE) or transverse
magnetic (TM) polarization, our volumetric architecture accepts both TE and TM modes simultaneously, reflecting the dimensionality and versatility required by the photonic devices. The metasurface comprises a periodic
lattice of gold nanostructures embedded in a dielectric
polymer matrix, creating complex metal-dielectric interfaces that sustain tightly confined plasmonic resonances. When driven by ultrafast near-infrared pulses, these resonances concentrate optical energy at the nanoscale, enabling efficient third-harmonic generation and upconversion of visible light into the ultraviolet (UV) and deep-UV regimes with enhanced conversion efficiency. We perform spatial and temporal mapping of the nonlinear response under both TE and TM excitation. Our measurements reveal polarization-agnostic field enhancement and spectral tunability arising from the three-dimensional morphology-capabilities unattainable in planar metasurfaces, where two-dimensional
symmetry inherently limits polarization flexibility and functional bandwidth. This 3D platform provides a flexible design toolbox for polarization-independent UV and deep-UV light sources. Potential applications include high-resolution UV spectroscopy, optical multiplexing, data storage, and emerging
quantum photonic architectures. By establishing fundamental insights into three-dimensional nonlinear metasurface behavior, our work paves the way for next-generation reconfigurable, multi-polarization nanophotonic devices.
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All authors Shroddha Mukhopadhyay, Ana Conde-Rubio, Jose Trull, Agustin Mihi, Michael Scalora, Maria Antonietta Vincenti, Crina Cojocaru
Data Analysis and Statistics · Cross-listed from hep-ex
Transformer-Based Approach to Enhance Positron Tracking Performance in MEG II
Lapo Dispoto, Fedor Ignatov, Atsushi Oya et al. (+2 more)
We developed a
Transformer-based pattern recognition method for positron track reconstruction in the MEG II experiment. The model acts as a classifier to remove pileup hits in the MEG II drift chamber, which operates under a high pileup occupancy of 35 - 50 %. The trained model significantly improved hit purity, leading to enhancements in tracking efficiency and resolution by 15 % and 5 %, respectively, at a
muon stopping rate of $5\times 10^7 \mu$/sec. This improvement translates into an approximately 10 % increase in the sensitivity of the $\mu\to e\gamma$ branching ratio measurement.
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All authors Lapo Dispoto, Fedor Ignatov, Atsushi Oya, Yusuke Uchiyama, Antoine Venturini
Medical Physics
MRI Simulation and Reconstruction Framework for Magnetic Vector Fields
Fabian Bschorr, Thomas Hüfken, Tobias Lobmeyer et al. (+1 more)
Purpose: Conventional MRI is relying on the assumption of the
magnetic field being homogeneous in direction and amplitude. However, with the growing interest in portable, affordable point-of-care MRI systems, these assumptions do not necessarily hold anymore due to compromises necessary to achieve a reduction in e.g. footprint, weight and portability. Simulation software may help by evaluating new encoding schemes which are optimized for non-ideal hardware but also with the design of new scanner designs. The goal of this work was to develop a MATLAB-based simulation software capable of dealing with deflected
magnetic fields during signal simulation and reconstruction and enabling the evaluation of arbitrary
magnetic field configurations for encoding in MRI. Methods: Conventional
matrix-based Bloch simulation is limited in its applicability to arbitrary
magnetic fields. We therefore adapted, evaluated, and validated a modified approach, achieving substantially shorter simulation time. Furthermore, it is used to predict image quality in 2D gradient echo experiments with deflected
magnetic fields. Results: The comparison of numerical Bloch and
matrix-based simulation revealed close agreement of both reconstructed images. Further, it was shown that compensation of the associated artifacts can be achieved by incorporating knowledge about the used
magnetic fields into the reconstruction process. Conclusion: The presented and validated software package enables full consideration of angular inhomogeneities of
magnetic vector fields used in MRI for signal simulation but also reconstruction removing the related artifacts. As such, the software might become a valuable tool for new low-field system designs and the investigation of new reconstruction
algorithms.
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All authors Fabian Bschorr, Thomas Hüfken, Tobias Lobmeyer, Volker Rasche
Physics and Society
A Mathematical Framework for Misinformation Propagation in Complex Networks: Topology-Dependent Distortion and Control
Saikat Sur, Rohitashwa Chattopadhyay, Jens Christian Claussen et al. (+1 more)
Misinformation is pervasive in natural, biological, social, and engineered systems, yet its quantitative characterization remains challenging. We develop a general mathematical framework for quantifying information distortion in distributed systems by modeling how local transmission errors accumulate along network geodesics and reshape each
agent's perceived global state. Through a drift-fluctuation decomposition of pathwise binomial noise, we derive closed-form expressions for node-level perception distributions and show that directional bias induces only a uniform shift in the mean, preserving the fluctuation structure. Applying the framework to canonical graph ensembles, we uncover strong topological signatures of misinformation: Erdős-Rényi random graphs exhibit a double-peaked distortion profile driven by connectivity transitions and geodesic-length fluctuations, scale-free networks suppress misinformation through hub-mediated integration, and optimally rewired small-world networks achieve comparable suppression by balancing clustering with short paths. A direct comparison across regular
lattices, Erdős-Rényi random graphs, Watts-Strogatz small-world networks, and Barabási-Albert scale-free networks reveals a connectivity-dependent crossover. In the extremely sparse regime, scale-free and Erdős-Rényi networks behave similarly. At intermediate sparsity, Watts-Strogatz small-world networks exhibit the lowest misinformation. In contrast, Barabás-Albert scale-free networks maintain low misinformation in sparse and dense regimes, while regular
lattices produce the highest distortion across connectivities. We additionally show how sparsity constraints, structural organization, and connection costs delineate regimes of minimal misinformation.
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All authors Saikat Sur, Rohitashwa Chattopadhyay, Jens Christian Claussen, Archan Mukhopadhyay
Optics
Gap-free Information Transfer in 4D-STEM via Fusion of Complementary Scattering Channels
Shengbo You, Georgios Varnavides, Sagar Khavnekar et al. (+12 more)
Linear phase-contrast scanning transmission electron microscopy (STEM) techniques compatible with high-throughput 4D-STEM acquisition are widely used to enhance phase contrast in weakly scattering and beam-sensitive materials. In these modalities, contrast transfer is often suppressed at low spatial frequencies, resulting in a characteristic contrast gap that limits quantitative imaging. Approaches that retain low-frequency phase contrast exist but typically require substantially increased experimental complexity, restricting routine use. Dark-field STEM imaging captures this missing low-frequency information through electrons scattered outside the bright-field disk, but discards a large fraction of the scattered signal and is therefore dose-inefficient. Fused Full-field STEM (FF-STEM) is introduced as a 4D-STEM imaging modality that overcomes this limitation by combining ptychographic phase reconstruction with tilt-corrected dark-field imaging within a single acquisition. Bright-field data are used to estimate probe aberrations and reconstruct a high-resolution phase image, while dark-field data provide complementary low-frequency contrast. The two channels are optimally fused in
Fourier space using minimum-variance weighting based on the spectral signal-to-noise ratio, yielding transfer-gap-free images with high contrast and quantitative fidelity. FF-STEM preserves the upsampling and depth-sectioning capabilities of ptychography, adds robust low-frequency contrast characteristic of dark-field imaging, and enables dose-efficient, near-real-time reconstruction.
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All authors Shengbo You, Georgios Varnavides, Sagar Khavnekar, Nikita Palatkin, Sihan Shao, Mingjian Wu, Daniel Stroppa, Darya Chernikova, Baixu Zhu, Ricardo Egoavil, Stefano Vespucci, Xingchen Ye, Florian K. M. Schur, Erdmann Spiecker, Philipp Pelz
Fluid Dynamics
Ferro-hydrodynamics of droplet necking filaments
Neeladri Sekhar Bera, Apurba Roy and Purbarun Dhar
We explore the necking, filament thinning, and pinchoff dynamics of ferrofluid droplets within a
magnetic field, via a simple and low-cost experimental method. In our studies, both the Ohnesorge number Oh and the Deborah number De are O1, a typically inaccessible regime with conventional extensional rheometers. Under
magnetic forcing, the nanoparticles assemble into field aligned, chainlike structures, that generate a tunable magnetoelastic response, and markedly alter the extensional flow. Although behaving as Newtonian
liquids in the absence of a
magnetic field, the field induces extensional thickening, and the emergence of beads on a string BOAS structures in the ferrofluid filaments, a non-Newtonian signature. By combining controlled elongation with high speed imaging, we directly quantify the
magnetic field-dependent extensional viscosity and relaxation time. Our findings underscore how magnetically induced microstructures govern filament stability and extensional dynamics in ferrofluids.
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Instrumentation and Detectors
Ultra-high precision high voltage system for PTOLEMY
R. Ammendola, A. Apponi, G. Benato et al. (+63 more)
The PTOLEMY project is prototyping a novel electromagnetic filter for high-precision $\beta$ spectroscopy, with the ultimate and ambitious long-term goal of detecting the
cosmic neutrino background through electron capture on tritium bound to
graphene. Intermediate small-scale prototypes can achieve competitive sensitivity to the effective
neutrino mass, even with reduced energy resolution. To reach an energy resolution better than \SI{500}{meV} at the tritium $\beta$-spectrum endpoint of \SI{18.6}{keV}, and accounting for all uncertainties in the filtering chain, the electrode voltage must be controlled at the level of a few parts per million and monitored in real time. In this work, we present the first results obtained in this effort, using a chain of commercial ultra-high-precision voltage references, read out by precision multimeters and a field mill device. The currently available precision on high voltage is, in the conservative case, as low as \SI{0.2}{ppm} per \SI{1}{kV} single board and $\lesssim$ \SI{50}{mV} over the \SI{10}{kV} series, presently limited by field mill read-out noise. However, assuming uncorrelated Gaussian noise extrapolation, the real precision could in principle be as low as \SI{0.05}{ppm} over \SI{20}{kV}.
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All authors R. Ammendola, A. Apponi, G. Benato, M.G. Betti, R. Biondim, P. Bos, G. Cavoto, M. Cadeddu, A. Casale, O. Castellano, E. Celasco, L. Cecchini, M. Chirico, W. Chung, A.G. Cocco, A.P. Colijn, B. Corcione, N. D'Ambrosio, M. D'Incecco, G. De Bellis, M. De Deo, N. de Groot, A. Esposito, M. Farino, S. Farinon, A.D. Ferella, L. Ferro, L. Ficcadenti, G. Galbato Muscio, S. Gariazzo, H. Garrone, F. Gatti, G. Korga, F. Malnati, G. Mangano, L.E. Marcucci, C. Mariani, J. Mead, G. Menichetti, M. Messina, E. Monticone, M. Naafs, V. Narcisi, S. Nagorny, G. Neri, F. Pandolfi, R. Pavarani, C. Pèrez de los Heros, O. Pisanti, C. Pepe, F.M. Pofi, A.D. Polosa, I. Rago, M. Rajteri N. Rossi, S. Ritarossi, A. Ruocco, G. Salina, A. Santucci, M. Sestu, A. Tan, V. Tozzini, C.G. Tully, I. van Rens, F. Virzi, G. Visser, M. Vivian
Plasma Physics
Optimization of the characteristics of a relativistic electron beam based on laser wake-field acceleration using a non-symmetric gas target profile
D. Mancelli, G. Andrianaki, I. Tazes et al. (+8 more)
We demonstrate a high-energy, high-charge, electron source produced by the irradiation of a novel gaseous target by an ultra-intense femtosecond
laser pulse. By exploiting a nonsymmetrical nozzle, we increased the total charge of the electron beam by at least an order of magnitude with respect to our previous experiments using symmetrical nozzles. In addition, the maximum energy of the accelerated electrons was enhanced by a factor of two. The electrons are accelerated via the
Laser Wake-Field Acceleration mechanism. Particle-in-
cell simulations indicate that electrons are injected via the ionization and the downramp injection mechanisms. Our measurements indicate that the demonstrated electron source is a considerable candidate for high dose, Very High Energy Electrons applications, such as radiotherapy.
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All authors D. Mancelli, G. Andrianaki, I. Tazes, C. Vlachos, I. Fitilis, I. Nikolos, M. Bakarezos, E. P. Benis, V. Dimitriou, N. A. Papadogiannis, M. Tatarakis
Optics
Hair-thin confocal fluorescence endo-microscopy for deep-brain in-vivo imaging
Tomáš Pikálek, Miroslav Stibůrek, Tereza Tučková et al. (+6 more)
Confocal and multi-
photon microscopy are widely used for in-vivo fluorescence imaging of biological tissues such as the
brain, offering non-invasive access up to ~1 mm depth without major loss in performance. A recently-developed alternative is
holographic endoscopy, which exploits controlled light transport through hair-thin optical fibres. With minimal invasiveness, it provides observations at comparable spatial resolution, while extending its applicability to unprecedented depths. It has been used to resolve details of sub-cellular structural connectivity, record neuronal signalling, and monitor blood flow from the deepest locations of the living
brain. Yet, its use, particularly in densely labelled
brain regions, has so far been constrained by significant contrast loss, primarily due to the absence of a practical mechanism for rejecting out-of-focus fluorescence light – a capability inherently provided by confocal and multi-
photon microscopy. Exploring opportunities in the structure of light modes of different MMF types we identify the possibility of achieving an analogue to confocal fluorescence microscopy through MMF-based endoscopes. Using a novel composite fibre probe that combines graded-index and step-index MMFs, we enable spatially resolved signal collection and selective rejection of out-of-focus light. This confocal filtering significantly enhances image contrast and resolution by suppressing background and off-plane signals. We demonstrate improved imaging performance on fine structural connectivity and intracellular calcium signalling in living mouse
brain.
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All authors Tomáš Pikálek, Miroslav Stibůrek, Tereza Tučková, Petra Kolbábková, Sergey Turtaev, Jana Krejčí, Petra Ondráčková, Hana Uhlířová, Tomáš Čižmár
Biological Physics · Cross-listed from q-bio.QM
Machine Learning of Temperature-dependent Chemical Kinetics Using Parallel Droplet Microreactors
Mamoru Saita and Yutaka Hori
Temperature is a fundamental regulator of chemical and biochemical kinetics, yet capturing nonlinear thermal effects directly from experimental data remains a major challenge due to limited throughput and model flexibility. Recent advances in machine learning have enabled flexible modeling beyond conventional physical laws, but most existing strategies remain confined to surrogate models of end-point yields rather than full kinetic dynamics. Consequently, an end-to-end framework that unifies systematic kinetic data acquisition with machine learning based modeling has been lacking. In this paper, we present a unified framework that integrates droplet microfluidics with machine learning for the systematic analysis of temperature-dependent reaction kinetics. The platform is specifically designed to enable stable immobilization and long-term time-lapse imaging of thousands of droplets under dynamic thermal gradients. This configuration yields massively parallel time-resolved
datasets across diverse temperature conditions that capture transient kinetics and provides particularly suitable inputs for training machine-learning models of reaction dynamics. Leveraging these
datasets, we train Neural ODE models, which embed neural networks within differential equations to flexibly represent nonlinear temperature dependencies beyond conventional formulations. We demonstrate accurate prediction of enzymatic kinetics across diverse thermal environments, highlighting the robustness and versatility of the approach. Our framework bridges high-throughput experimental data acquisition with data-driven modeling, establishing a versatile foundation for enhanced predictive ability and rational analysis and design of temperature-sensitive biochemical processes.
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Optics
Sculpting ultrafast mid-infrared light for solid-state high harmonic generation
Camilo Granados, Bálint Kiss, Eric Cormier et al. (+6 more)
The ability to sculpt light in space, time, and polarization has revolutionized studies of light-matter interaction and enabled breakthroughs in optical communication, imaging, and ultrafast science. Among the many degrees of freedom of light, orbital angular momentum (OAM) further expands these capabilities by unlocking new regimes of control in information encoding, particle trapping and manipulation, and
symmetry-driven selection rules. However, exploiting OAM to drive nonlinear, non-perturbative effects in solids remains challenging, especially in the mid-infrared (MIR) spectral regime-a key region for accessing these effects in ambient air, where spatial light modulators do not operate. Here, we circumvent this limitation by generating femtosecond, few-cycle MIR Bessel-Gauss
vortex (BGV) and perfect optical
vortices (POVs), using a robust, static spatial-shaping strategy. By utilizing these beams to drive nonlinear optical processes such as second-harmonic generation (SHG) and high-harmonic generation (HHG) in various solid-state materials, we show that the resulting harmonic beams faithfully inherit the structural characteristics of the drivers: the constant-intensity ring of the POVs is preserved across harmonic orders, while the BGV harmonic beams retain their intrinsic topological charge-dependent intensity profiles. Furthermore, by verifying the linear OAM up-scaling law, we confirm the conservation of OAM during SHG and HHG in solids. These results establish strong-field HHG in solids as a robust platform for synthesizing ultrafast structured harmonic light with controllable, high-value OAM.
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All authors Camilo Granados, Bálint Kiss, Eric Cormier, Bikash Kumar Das, Debobrata Rajak, Carmelo Rosales-Guzman, Rajaram Shrestha, Qiwen Zhan, Wenlong Gao
Computational Physics · Cross-listed from math.NA
A Cartesian Cut-Cell Two-Fluid Method for Two-Phase Diffusion Problems
Louis Libat, Can Selçuk, Eric Chénier et al. (+1 more)
We present a Cartesian cut-
cell finite-volume method for sharp-interface two-phase
diffusion problems in static geometries. The formulation follows a two-fluid approach: independent
diffusion equations are discretized in each phase on a fixed Cartesian grid, while the phases are coupled through embedded interface conditions enforcing continuity of diffusive flux and a general jump law. Cut
cells are treated by integrating the governing equations over phase-restricted control volumes and surfaces, yielding discrete divergence and gradient operators that are locally conservative within each phase. Interface coupling is achieved by introducing a small set of interfacial unknowns per cut
cell on the embedded boundary; the resulting algebraic system involves only bulk and interfacial averages. A key feature of the method is the use of a reduced set of
geometric information based solely on low-order moments (trimmed volumes, apertures and interface measures/centroids), allowing robust implementation without constructing explicitly cut-
cell polytopes. The method supports steady (Poisson) and unsteady (
diffusion) regimes and incorporates Dirichlet, Neumann, Robin boundary conditions and general jumps. We validate the scheme on one-, two- and three-dimensional single-phase and two-phase
benchmarks, including curved embedded boundaries, Robin conditions and strong property/jump contrasts. The results demonstrate a superlinear convergence behavior, sharp enforcement of interfacial laws and excellent conservation properties. Extensions to moving interfaces and Stefan-type free-boundary problems are natural perspectives of this framework.
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All authors Louis Libat, Can Selçuk, Eric Chénier, Vincent Le Chenadec
Data Analysis and Statistics · Cross-listed from astro-ph.HE
Machine learning for the early classification of broad-lined Ic supernovae
Laura Cotter, Antonio Martin-Carrillo, Joseph Fisher et al. (+3 more)
Science is currently at an age where there is more data than we know how to deal with. Machine learning (ML) is an emerging tool that is useful for drawing valuable science out of incomprehensibly large
datasets and identifying complex trends in data that may otherwise be overlooked. Moreover, ML can potentially enhance the quality and quantity of scientific data as they are collected. This paper explores how a new ML method can improve the rate of classification of rare broad-lined Ic (Ic-BL)
supernovae (SNe). We introduce new parameters called magnitude rates to train ML models to identify SNe Ic-BL in large
datasets and apply this same methodology to a population of SN Ia to test if our ML approach is reproducible. The information we required to train each ML model included three magnitudes, three time differences, two magnitude rates, and the second derivative of these rates using the first three available photometric data points in a single filter. Our initial investigations showed that the random forest
algorithm provides a strong foundation for the early classifications SNe Ic-BL and SNe Ia. Testing this model again on an unseen
dataset showed that the model can identify upward of 13.6% of the total true SN Ic-BL population, significantly improving on current methods. By implementing a dedicated observation campaign using this model, the number of SN Ic-BL classified and the quality of early-time data collected each year will see considerable growth in the near future.
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All authors Laura Cotter, Antonio Martin-Carrillo, Joseph Fisher, Gabriel Finneran, Gregory Corcoran, Jennifer Lebron
Fluid Dynamics
A Critical Assessment of Pattern Comparisons Between POD and Autoencoders in Intraventricular Flows
Eneko Lazpita, Andrés Bell-Navas, Jesús Garicano-Mena et al. (+2 more)
Understanding intraventricular hemodynamics requires compact and physically interpretable representations of the underlying flow structures, as characteristic flow patterns are closely associated with cardiovascular conditions and can support early detection of cardiac deterioration. Conventional visualization of velocity or pressure fields, however, provides limited insight into the coherent mechanisms driving these dynamics. Reduced-order modeling techniques, like Proper Orthogonal Decomposition (POD) and Autoencoder (AE) architectures, offer powerful alternatives to extract dominant flow features from complex
datasets. This study systematically compares POD with several AE variants (Linear, Nonlinear, Convolutional, and Variational) using left ventricular flow fields obtained from computational fluid dynamics simulations. We show that, for a suitably chosen latent dimension, AEs produce modes that become nearly orthogonal and qualitatively resemble POD modes that capture a given percentage of kinetic energy. As the number of latent modes increases, AE modes progressively lose orthogonality, leading to linear dependence, spatial redundancy, and the appearance of repeated modes with substantial high-frequency content. This degradation reduces interpretability and introduces noise-like components into AE-based reduced-order models, potentially complicating their integration with physics-based formulations or neural-network surrogates. The extent of interpretability loss varies across the AEs, with nonlinear, convolutional, and variational models exhibiting distinct behaviors in orthogonality preservation and feature localization. Overall, the results indicate that AEs can reproduce POD-like coherent structures under specific latent-space configurations, while highlighting the need for careful mode selection to ensure physically meaningful representations of cardiac flow dynamics.
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All authors Eneko Lazpita, Andrés Bell-Navas, Jesús Garicano-Mena, Petros Koumoutsakos, Soledad Le Clainche
Chemical Physics
Finding the best density functionals for water: benchmarking the forces
Shifan Cui
A DFT
benchmark on water including more than 50 functionals from GGA to double-hybrid levels is reported. The main metric is the accuracy of forces, allowing better structural coverage, higher statistical confidence, and fewer error sources compared to conventional
benchmarks. The input structures include water clusters of 4~128 molecules, with highly varied yet realistic configurations of water, ice, and their mixtures. The B97M-V, {\omega}B97M-V, and revDOD-PBEP86-D4 functionals are found to be best on the mGGA, hybrid, and double-hybrid levels, respectively. No satisfying GGA functionals are found, but it can be obtained by combining BLYP-D4 with a simple correction to O-H bonds, achieving accuracy comparable to B97M-V.
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Optics
A deterministic approach for integrating an emitter in a nanocavity with subwavelength light confinement
Valdemar Bille-Lauridsen, Rasmus Ellebæk Christiansen, Yi Yu et al. (+1 more)
We introduce a novel light-matter interface that integrates a nanoscale buried
heterostructure emitter into a dielectric bowtie cavity, co-localising the optical hotspot and the electronic wavefunction. This platform enables strong light-matter interaction through deep subwavelength confinement while remaining compatible with scalable fabrication. We show that in this regime an explicit treatment of the emitter's spatial extent is required, and that a confinement-factor approximation more accurately predicts the coupling, revealing design rules inaccessible to dipole-based metrics. For an InP/InGaAsP system, we predict coupling strengths of 0.4-0.7 meV for gap sizes of 50-10 nm, establishing the buried
heterostructure-bowtie architecture as a practical route to deterministic strong coupling in solid-state nanophotonics.
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All authors Valdemar Bille-Lauridsen, Rasmus Ellebæk Christiansen, Yi Yu, Jesper Mørk
Instrumentation and Detectors
Talking with a ghost: semi-virtual coupled levitated oscillators
Ronghao Yin, Yugang Ren, Deok Young Seo et al. (+4 more)
Mesoscopic particles levitated by optical, electrical or
magnetic fields act as mechanical oscillators with a range of surprising properties, such as tuneable oscillation frequencies, access to rotational motion, and remarkable quality factors. Coupled levitated particles display rich dynamics and non-reciprocal interactions, with applications in sensing and the exploration of non-
equilibrium and
quantum physics. In this work, we present a single levitated particle displaying coupled-oscillator dynamics by generating an interaction with a virtual or “ghost” particle. This ghost levitated particle is simulated on an analogue computer, and its properties can thus be dynamically varied. Our work represents a new angle on measurement-based bath engineering and physical simulation and, in the future, could lead to the generation of novel cooling mechanisms and complex physical simulation.
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All authors Ronghao Yin, Yugang Ren, Deok Young Seo, Anoushka Sinha, Jonathan D. Pritchett, Qiongyuan Wu, James Millen
Plasma Physics
Optimization of laser-driven proton acceleration in a near-critical-density plasma
Guanqi Qiu, Qianyi Ma, Deji Liu et al. (+5 more)
Optimizing
laser and
plasma parameters is crucial for enhancing accelerated
proton energy in
laser-driven
proton acceleration with finite
laser energy for applications such as cancer therapy. Tight focusing plays a significant role in improving
laser-driven
proton acceleration, which is generally believed as a result of the enhancement of
laser intensity. However, we find that even at a fixed
laser intensity, reducing the focal spot size still enhances the
proton energy. Through particle-in-
cell simulations and theoretical modeling, we find that at a small spot size (0.8 {\mu}m), the maximum
proton energy is enhanced by 56.3% compared to that obtained at a conventional spot size (3 {\mu}m). This improvement is attributed to the dominance of ponderomotive-force-driven electrons at reduced spot sizes, which generate stronger charge-separation fields that propagate at higher velocities. Furthermore, to optimize
proton acceleration, we analytically derive an ideal
plasma density profile that promotes phase-stable
proton acceleration, yielding an additional energy increase of 61.3% over the case of a tightly focused
laser interacting with a planar target of uniform density. These findings remain robust under parameter variations, indicating that advanced focusing techniques combined with optimized
plasma profiles could relax the demand for high
laser energies, thereby reducing the reliance on large-scale
laser facilities in medical and scientific applications.
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All authors Guanqi Qiu, Qianyi Ma, Deji Liu, Dongchi Cai, Zheng Gong, Yinren Shou, Jinqing Yu, Xueqing Yan
Data Analysis and Statistics · Cross-listed from hep-ex
The asymptotic distribution of the likelihood ratio test statistic in two-peak discovery experiments
Clara Bertinelli Salucci, Hedvig Borgen Reiersrud, A. L. Read et al. (+2 more)
Likelihood ratio tests are widely used in high-energy physics, where the test statistic is usually assumed to follow a chi-squared distribution with a number of degrees of freedom specified by Wilks'
theorem. This assumption breaks down when parameters such as signal or coupling strengths are restricted to be non-negative and their values under the null hypothesis lie on the boundary of the parameter space. Based on a recent clarification concerning the correct asymptotic distribution of the likelihood ratio test statistic for cases where two of the parameters are on the boundary, we revisit the the question of significance estimation for two-peak signal-plus-background counting experiments. In the high-energy physics literature, such experiments are commonly analyzed using Wilks' chi-squared distribution or the one-parameter Chernoff limit. We demonstrate that these approaches can lead to strongly miscalibrated significances, and that the test statistic distribution is instead well described by a chi-squared mixture with weights determined by the Fisher information
matrix. Our results highlight the need for boundary-aware asymptotics in the analysis of two-peak counting experiments.
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All authors Clara Bertinelli Salucci, Hedvig Borgen Reiersrud, A. L. Read, Anders Kvellestad, Riccardo De Bin
Instrumentation and Detectors
Optimal operating parameters for next-generation xenon gas time projection chambers
K. Mistry, Y. Mei and D.R. Nygren
The next-generation of $0\nu\beta\beta$ searches are targeting half-life sensitivities towards 10$^{27}$–10$^{28}$ years. Gaseous xenon time projection chamber (GXeTPC) detectors may be able to meet this challenge due to their excellent energy resolution and background rejection power through event visualization. This paper explores how the design choices of a next-generation GXeTPC time projection chamber can impact the overall performance of the experiment. We study the performance of systems using xenon enriched in the isotope $^{136}$Xe or natural xenon, focusing on scenarios that incorporate one tonne of $^{136}$Xe isotope. The detector size, copper shielding mass, energy resolution, density and corresponding levels of
diffusion are surveyed to evaluate the overall performance dependencies on these parameters. A detector optimized for using enriched xenon is preferred over natural, due primarily to a factor of 10 lower background rate driven by the large intrinsic backgrounds introduced by the copper shielding used in the detector. The performance of three types of gas TPC technologies was also explored based on different gas additives used to reduce
diffusion to different levels. For all TPC technologies, we find background rates of a fraction of a count per tonne year in the region of interest are achievable. These performance levels are contingent on suitable energy resolution and event position placement in the drift direction being achieved for the specific detector technology. Performance for enriched xenon TPCs varies mildly with pressure in the range 5 to 25 bars, reaching background levels below 0.2 events/tonne-year. Performance at one bar is worse by approximately a factor of four. When considerations for the construction of the detector in addition to the selection performance are included, there may be no clearly optimum pressure.
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Fluid Dynamics
Unifying formalism and closures for coarse-grained approaches to turbulence
A. Cimarelli, N. Marras, B. Niceno et al. (+1 more)
We propose the use of an unifying paradigm for the assessment and development of closed forms of the coarse-grained Navier-Stokes equations in approaches ranging from the statistical to the scale-resolving ones. It consists in the exact formalism provided by the temporally filtered Navier-Stokes equations. The fundamental idea is that the smoothing action of turbulent stresses can be described as a temporal filtering operator implicitly applied to the solution. Contrary to the average and spatial filtering operators, the temporal filter is an unifying operator smoothly varying within the statistical and scale-resolving realms. The potential of the temporal filtering paradigm is here highlighted by unveiling relevant algebraic properties and by deriving a new class of
turbulence closures. A dynamic procedure is derived and shown to provide an unifying closure for both scale-resolving and statistical approaches. Results show that an improved physics is captured. Challenging phenomena such as the laminar to
turbulence transition and the dependence of separation and reattachment on free-stream
turbulence applied through boundary conditions are captured.
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All authors A. Cimarelli, N. Marras, B. Niceno, Y. Tessier Urrecha
Accelerator Physics
Precise control of high-frequency ultrasounds in thin crystals for the development of tunable narrowband and directional gamma-ray sources
Emmanouil Kaniolakis-Kaloudis, Nektarios Papadogiannis, Yannis Orphanos et al. (+2 more)
This work presents a complete methodology for the precise characterization of the acoustic field inside
crystal-based devices driven by high-frequency ultrasounds towards the generation of tunable narrowband and directional gamma radiation via undulation of ultra-relativistic charged particles. Such gamma-ray sources have long been anticipated by the scientific community, as they promise new powerful tools for the study of high-energy physical phenomena and the development of novel
nuclear technologies. In such devices, a piezoelectric transducer induces tens of MHz harmonic waves inside a silicon monocrystal. Ultra-relativistic charged particles traversing the
crystal get trapped within the channels formed by the extremely strong electric fields of the acoustically modulated
lattice planes, undergoing undulation and emitting gamma radiation. Precise characterization of the acoustic field in the
crystal is crucial for the determination of the expected characteristics of the secondarily generated gamma rays. For this purpose, fast
laser refraction imaging is used here to image the acoustic waves by exploiting the spatial redistribution of a
laser beam optical intensity caused by the acoustic field. A dedicated computational model is developed for the estimation of the spatial distribution of the pressure and
lattice deformation inside the
crystal. This methodology provides a framework for future novel gamma-ray sources in high-energy facilities.
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All authors Emmanouil Kaniolakis-Kaloudis, Nektarios Papadogiannis, Yannis Orphanos, Makis Bakarezos, Konstantinos Kaleris
Optics · Cross-listed from quant-ph
Limitations of Entangled Two-Photon Absorption detection
René Pollmann, Franz Roeder, Christine Silberhorn et al. (+1 more)
We introduce a method for determining the sensitivity of any given Entangled Two-
Photon Absorption (ETPA) measurement. By modeling all signal and noise contributions to the measurement, we derive a single numerical value that describes the sensitivity of the ETPA measurement in Göppert-Mayer units. This allows us to directly compare vastly different experimental approaches and, determine whether ETPA will be detectable under the given conditions. Therefore, we can quantify the effect of any change to a given experimental apparatus and identify the ideal optimization pathway.
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All authors René Pollmann, Franz Roeder, Christine Silberhorn, Benjamin Brecht
Optics
Optical parametric free-electron–photon quantum interaction
Zetao Xie, Zehai Pang and Yi Yang
Optical parametric processes underpin
quantum photonics, while free-electron–
photon interactions offer agile pathways to generate nontrivial
quantum photonic states. These threads have so far largely progressed independently, whereas placing free electrons in a driven nonlinear system can potentially activate coherent parametric interaction channels for joint state engineering of both types of particles. Here we unify these paradigms by developing a general theoretical framework for parametric free-electron–
photon interactions in a nonlinear optical system driven by degenerate parametric down-conversion. Unlike free electrons in a linear bath, here they can couple to Bogoliubov quasiparticles through two detuned phase-matching channels, where the parametric process and free-electron interactions can
quantum amplify each other. Seeding the interaction with squeezed
vacuum yields gain-only or loss-only electron energy spectra, and enables electron-heralded squeezed Fock states; with bare
vacuum, postselecting electron energy sidebands generates high-fidelity Schrödinger cat states. Our results show how optical parametric interactions can
quantum shape free electrons and
photons, potentially enabling a
quantum parametric dielectric
laser accelerator that mitigates the need for temporal phase synchronization, thereby allowing acceleration probabilities to approach unity even for phase-random electrons.
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Fluid Dynamics
Formation of external particle jets on a spherical particle bed subjected to strong explosive loading
Yifeng He, Junsheng Zeng, Baolin Tian et al. (+1 more)
We report the mechanism for the formation of external particle jets on a spherical particle bed subjected to strong explosive loading, revealing a critical dependence on particle size. Under strong explosive loading, the formation of external particle jets is primarily driven by a drag-coupled mechanism. We conducted Eulerian-Lagrangian simulations, with up to $2048^3$ effective
cells and $1.8$ million tracked parcels on an adaptive mesh, for both small- and large-particle cases. Pronounced jets are observed only with small particles, alongside accelerated bed thickening. By defining characteristic inner and outer radii, the particle bed thickness
evolution is quantified, showing an initial linear growth followed by a nonlinear deceleration. Particle dynamics analysis indicates that drag force dominates particle motion and jet formation during the nonlinear stage. The initial angular non-uniformity of the particle bed induces a non-uniform gas radial velocity. Through drag coupling, this flow asymmetry generates a radial velocity difference in small particles, thereby promoting pronounced jet formation, whereas large particles resist this drag-induced effect. The greater drag-induced deceleration on smaller particles leads to an increased velocity difference across the particle bed, explaining the accelerated thickening. A characteristic radius model that integrates the Gurney model for the linear stage with a drag-dominated deceleration model for the nonlinear stage is established and shows good agreement with numerical results across different particle sizes.
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All authors Yifeng He, Junsheng Zeng, Baolin Tian, Yue Yang
Plasma Physics
Magnetically confined charged particles: From steep density profiles to the breaking of the adiabatic invariant
Aurélien Cordonnier, Yohann Lebouazda, Xavier Leoncini et al. (+1 more)
This study examines the stability of Vlasov
equilibrium solutions for magnetically confined
plasmas, derived through the principle of maximum
entropy. By treating the toroidal limit as a perturbation from an analytical cylindrical solution, we demonstrate that these
equilibria align well with the inviscid magnetohydrodynamic (MHD) description. Using the aspect ratio as a perturbation parameter, we compute particle trajectories sampled from the kinetic
equilibrium distribution, confirming the overall stability of the solutions. However, under burning
plasma conditions, chaotic dynamics emerge for particles with supra-thermal and even thermal energies. This destroys the adiabatic invariance of the
magnetic moment. The exact consequences are unclear, but they could undermine the foundational assumptions of gyrokinetic modelling in burning
plasmas. Nevertheless, these results suggest the possibility of unaccounted transport losses in future burning
plasma operations. The interplay between
turbulence and energetic particles in the presence of
Hamiltonian chaos certainly warrants further investigation.
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All authors Aurélien Cordonnier, Yohann Lebouazda, Xavier Leoncini, Guilhem Dif-Pradalier
Optics
Highly efficient multi-chromatic Raman microlasers from cavity polygon modes on thin-film lithium niobate platform
Yixuan Yang, Chuntao Li, Renhong Gao et al. (+5 more)
The integration of stimulated Raman scattering (SRS) and second order nonlinearity in non-centrosymmetric photonic microresonators presents a highly promising solution for developing on-chip coherent light sources with exceptional bandwidth and flexible tunability. Our study introduces an innovative methodology leveraging cavity polygon modes within an X-cut thin-film lithium niobate microdisk to achieve highly efficient multi-chromatic Raman microlasers. Specifically, high-Q square modes characterized by two parallel sides oriented perpendicularly relative to the optical axis of lithium niobate
crystal were excited. These modes offer distinct advantages, including enhancing both mode-field overlap and improved phase matching, achieved through the utilization of the largest second-order susceptibility component (d_33), which is critical for Raman-quadratic nonlinear interactions. The experimental results highlight significant advancements in multi-wavelength multi-wavelength
laser generation, with forward stimulated Raman
laser signals exhibiting a high conversion efficiency of up to 65.02% and an impressively narrow integral linewidth of only 5.2 kHz. Simultaneously, our system enables the generation of multi-wavelength Raman-quadratic
laser signals across the ~800 nm and ~530 nm spectral bands. These findings are further underscored by an impressive absolute conversion efficiency of 1.33% for the 797.4-nm Raman
laser, achieved at a remarkably low pump power of just 1.07 mW. This work not only extends the application scope of cavity polygon modes from single second/third-order nonlinear optical processes to cascaded processes but also establishes a foundation for realizing high-efficiency on-chip multi-chromatic
laser sources with versatile functionalities.
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All authors Yixuan Yang, Chuntao Li, Renhong Gao, Yingnuo Qiu, Lingling Qiao, Jielei Ni, Jintian Lin, Ya Cheng
Computational Physics
Adaptive Probability Flow Residual Minimization for High-Dimensional Fokker-Planck Equations
Xiaolong Wu and Qifeng Liao
Solving high-dimensional Fokker-Planck (FP) equations remains a challenging problem in computational physics and
stochastic dynamics, due to the curse of dimensionality, unbounded domains, and complex probability landscapes. In this work, we propose an adaptive probability flow residual minimization (A-PFRM) method for this problem. The second-order FP equation is reformulated as an equivalent first-order continuity equation associated with the probability flow ordinary differential equation, based on which a loss function is constructed to train neural network approximations without Hessian computation. To further improve the computational efficiency, the Hutchinson trace
estimator is applied to compute the divergence in the corresponding score function, such that the training time can be dimension-independent on GPUs. Adaptive sampling strategies are employed to generate the collocation points, and our analysis shows that the Kullback-Leibler divergence between our A-PFRM approximation and the exact solution is bounded by the residual loss weighted by the estimated density function. Numerical experiments are presented to demonstrate the performance of A-PFRM, which include Ornstein-Uhlenbeck (OU) processes problems, Brownian motions with time-varying
diffusion, and
Geometric OU processes featuring non-Gaussian solutions up to one hundred dimensions.
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Optics
Far- and near-field photon noise limits to the detectivity of nanometer-thick thermal detectors
Olivier Merchiers, Aapo Varpula, Kirsi Tappura et al. (+2 more)
Thermal-radiation detectors such as bolometers – often found as thin, suspended films – are intrinsically limited by their optical absorption properties and by their intrinsic thermal conductive and radiative losses. We analyze the impact of the
photon energy exchange between the film and a substrate located close to each other, noticing that the associated near-field exchange has been overlooked and could reduce the detectivity. In addition, we study how the nanometric thickness of the suspended film and its material impact the detectivity of such sensors. It is found that the blackbody-related
photon noise limit of the detectivity can be surpassed with thin films. These results emphasize pathways for improvements of thermal-radiation detectors.
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All authors Olivier Merchiers, Aapo Varpula, Kirsi Tappura, Pierre-Olivier Chapuis, Mika Prunnila