Medical Physics
Controlled release from polyurethane films: drug release mechanisms
N. Abbasnezhad, N. Zirak, M. Shirinbayan et al. (+4 more)
In this study, polyurethane-films loaded diclofenac were used to analyze the drug release kinetics and mechanisms. For this purpose, the experimental procedures were developed under static and dynamic conditions with different initial drug loads of 10, 20, and 30%. In the dynamic condition, to better simulate the biological flow, drug release measurements were investigated at flow rates of 7.5 and 23.5 ml/s. These values indicate the flow rate of the internal carotid artery (ICA) for a normal state of a body and for a person during the exercise, respectively. The experimental data were analyzed and adjusted by Higuchi, Korsmeyer-Peppas, First-order, zero-order, and Peppas-Sahlin models in order to understand the mechanisms contributed. Finally, Drug release mechanisms were specified by investigating the model correlation coefficients. Experimental results showed that increasing the flow rate and initial drug loads enhance drug liberation. In addition, the rate of release is more influenced by the drug dosage in the static state. The analysis revealed that
diffusion, burst, and osmotic pressure are the principal mechanisms contributed. Moreover, Fickian type was the dominant mechanism at all duration of release. However, it was discovered using Peppas-Sahlin model that the contribution of the
diffusion mechanism decreases with increasing flow rate and initial dosage. Furthermore, the tests at different drug dosages showed that the number of stages in medication release profile is independent of the flow rate and the medicine percentage. One can conclude that the drug release kinetic in static state is more influenced by drug dosage compare to dynamic state.
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All authors N. Abbasnezhad, N. Zirak, M. Shirinbayan, S. Kouidri, E. Salahinejad, A. Tcharkhtchi, F. Bakir
Applied Physics
Polyvinylpyrrolidone planarized liquid crystalline 1T-WS2/rGO hybrid nanocomposites-based humidity sensing platform
A. Vasilev, M. Zhezhu, S. Gyozalyan et al. (+7 more)
Two-dimensional hybrid nanocomposites combining
graphene-like materials and transition metal dichalcogenides (TMDCs) are created using various synthesis methods and are vital for environmental sensing due to the synergistic effects of their components. These hybrid materials offer enhanced sensitivity, selectivity, surface-to-volume ratio, tunable electronic properties, strong interaction with analytes, and fast detection capabilities, which address the limitations of individual materials. This is due to their outstanding surface-to-volume ratio, tunable electronic properties, strong interactions with analytes, as well as their high sensitivity, selectivity, and fast detection capabilities, which are crucial for environmental sensing. Herein, a hydrothermally synthesized and polyvinylpyrrolidone (PVP)-stabilized 1T phase tungsten disulfide/reduced
graphene oxide, 1T-WS2/PVP/rGO, hybrid nanocomposite is reported. The intrinsic
liquid crystalline behavior of the synthesized composite enables the formation of highly uniform films for effective humidity sensing. The optostructural characterization and key performance parameters, including response and recovery times, of the 1T-WS2/PVP/rGO hybrid nanocomposite-based structure are comprehensively analyzed and studied. This is the first to report on the synthesis of a 1T-WS2/PVP/rGO hybrid nanocomposite, its
liquid crystalline phase formation, and application in humidity sensing. The proposed sensing platform introduces a novel approach to humidity sensing using 1T-WS2/PVP/rGO
liquid crystalline films, which combine the metallic advantages of 1T-WS2, the stabilizing role of PVP and the conductive framework of rGO into aligned LC structures for enhanced sensitivity, rapid response and environmental robustness.
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All authors A. Vasilev, M. Zhezhu, S. Gyozalyan, L. Avanesyan, Y. Grigoryan, A.A. Kuzanyan, A.A. Hovhannisyan, Mohamed Aly Saad Aly, D.A. Ghazaryan, H. Gharagulyan
Computational Physics
Physics Constrained Neural Collision Operators for Variable Hard Sphere Surrogates and Ab Initio Angle Prediction in Direct Simulation Monte Carlo
Ehsan Roohi, Ahmad Shoja-Sani and Stefan Stefanov
The Direct Simulation Monte Carlo (DSMC) method is the gold standard for non-
equilibrium rarefied gas dynamics, yet its computational cost can be prohibitive, especially for near-continuum regimes and high-fidelity ab initio potentials. This work develops a unified, physics-constrained neural-operator framework that accelerates DSMC while preserving physical invariants and stochasticity required for long-time kinetic simulations. First, we introduce a local neural collision kernel replacing the phenomenological Variable Hard Sphere (VHS) model. To overcome the variance suppression and artificial cooling inherent to purely deterministic regression surrogates, we augment inference with a physics-constrained
stochastic layer. Controlled latent-noise injection restores thermal fluctuations, while
cell-wise moment-matching strictly enforces momentum and kinetic-energy conservation. Remarkably, this operator exhibits zero-shot spatial and thermodynamic generalization: a model trained exclusively on 1D Couette flow accurately simulates a complex 2D lid-driven cavity, capturing high-order non-
equilibrium moments without retraining.Second, to bypass the extreme cost of
quantum-mechanical scattering, we develop a dedicated ab initio neural operator for the Jäger interaction potential. Trained via a physics harvesting strategy on large-scale collision pairs, it efficiently captures the high-energy scattering dynamics dominating hypersonic regimes. Validated on a Mach~10 rarefied argon flow over a cylinder, the framework reproduces transport behaviors and shock features with high fidelity, achieving an approximate 20% cost reduction relative to direct numerical integration.
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Computational Physics
Distillation and Interpretability of Ensemble Forecasts of ENSO Phase using Entropic Learning
Michael Groom, Davide Bassetti, Illia Horenko et al. (+1 more)
This paper introduces a
distillation framework for an ensemble of
entropy-optimal Sparse Probabilistic Approximation (eSPA) models, trained exclusively on satellite-era observational and reanalysis data to predict ENSO phase up to 24 months in advance. While eSPA ensembles yield state-of-the-art forecast skill, they are harder to interpret than individual eSPA models. We show how to compress the ensemble into a compact set of "distilled" models by aggregating the structure of only those ensemble members that make correct predictions. This process yields a single, diagnostically tractable model for each forecast lead time that preserves forecast performance while also enabling diagnostics that are impractical to implement on the full ensemble. An analysis of the regime persistence of the distilled model "superclusters", as well as cross-lead clustering consistency, shows that the discretised system accurately captures the spatiotemporal dynamics of ENSO. By considering the effective dimension of the feature importance vectors, the complexity of the input space required for correct ENSO phase prediction is shown to peak when forecasts must cross the boreal spring predictability barrier. Spatial importance maps derived from the feature importance vectors are introduced to identify where predictive information resides in each field and are shown to include known physical precursors at certain lead times. Case studies of key events are also presented, showing how fields reconstructed from distilled model centroids trace the
evolution from extratropical and inter-basin precursors to the mature ENSO state. Overall, the
distillation framework enables a rigorous investigation of long-range ENSO predictability that complements real-time data-driven operational forecasts.
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All authors Michael Groom, Davide Bassetti, Illia Horenko, Terence J. O'Kane
Instrumentation and Detectors · Cross-listed from astro-ph.IM
GW-FALCON: A Novel Feature-Driven Deep Learning Approach for Early Warning Alerts of BNS and NSBH Inspirals in Next-Generation GW Observatories
Grigorios Papigkiotis, Georgios Vardakas and Nikolaos Stergioulas
Next-generation GW observatories such as the ET and CE will detect BNS and NSBH inspirals with high SNRs and long in-band durations, making systematic early-warning alerts both feasible and scientifically valuable. Such triggers are essential for coordinating rapid electromagnetic follow-up. In this work, we introduce GW-FALCON, a novel feature-driven DL framework for early-time detection between GW signal+noise and noise-only data in next-generation detectors. Instead of feeding raw time series to CNN or more complex neural network architectures, we first extract a large set of statistical, temporal, and spectral quantities from short observational time windows using the TSFEL library. The resulting fixed-length feature vectors are then used as input to feed-forward ANNs suitable for low-latency operation. We demonstrate the method using simulated BNS and NSBH inspiral waveforms injected into colored Gaussian noise generated from the ET and CE design PSDs. We train separate ANNs on feature sets extracted from partial-inspiral windows characterized by different maximum instantaneous frequencies, enabling early-warning triggers from tens to hundreds of seconds before merger. Across all detector configurations and
datasets, the resulting classifiers achieve high accuracy and detection efficiency, with ET-like networks typically reaching test accuracies of order 90% and CE-like ones exceeding 97% at low false-alarm probability. To the best of our knowledge, this work presents the first comprehensive feature-based DL detection framework for Next-generation GW observatories, connecting feature extraction from strain time series data to robust signal-noise classification within a setup that can be extended to real data and to more advanced neural network architectures.
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Atomic and Molecular Clusters · Cross-listed from astro-ph.EP
Formation and Survival of Complex Organic Molecules in the Jovian Circumplanetary Disk
Olivier Mousis, Clément Petetin, Tom Benest Couzinou et al. (+2 more)
Europa, Ganymede, and Callisto are key targets in the search for habitability due to the potential presence of subsurface oceans. Detecting complex organic molecules (COMs), essential for prebiotic chemistry, is crucial to assessing their potential. Though COMs remain undetected on these moons, ESA's JUICE and NASA's Europa Clipper missions aim to fill this gap with their science payloads. This study explores the formation and transport of COMs within Jupiter's circumplanetary disk (CPD), a critical environment for the formation of the Galilean moons. Using a time-dependent model that couples the evolving CPD structure with the dynamics of icy particles of varying sizes and release times, we assess two primary COM formation pathways: thermal processing of ices and UV photochemistry. The results indicate that heating, particularly of NH3:CO2 ices, occurs efficiently before substantial irradiation, making it the dominant pathway for COM formation in the Jovian CPD. However, the relative efficiencies of these two processes are governed by particle density, disk viscosity,
accretion rate, and UV flux, which collectively determine drift timescales and exposure to favorable thermodynamic environments. Existing models indicate that Europa's
accretion was relatively cold and prolonged, possibly allowing some COMs to survive incorporation, whereas Ganymede and Callisto likely formed under even cooler conditions conducive to preserving COM-rich material. These results highlight the potential inheritance of complex organics by the Galilean moons and offer a framework for interpreting upcoming compositional data from JUICE and Europa Clipper.
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All authors Olivier Mousis, Clément Petetin, Tom Benest Couzinou, Antoine Schneeberger, Yannis Bennacer
Atomic Physics · Cross-listed from cond-mat.quant-gas
Dirac Spin Liquid Candidate in a Rydberg Quantum Simulator
Guillaume Bornet, Marcus Bintz, Cheng Chen et al. (+10 more)
We experimentally investigate a frustrated
spin-exchange antiferromagnet in a
quantum simulator, composed of N = 114 dipolar Rydberg atoms arranged into a kagome array. Motivated by a recent theoretical proposal of a gapless U(1) Dirac
spin liquid ground state, we use local addressing to adiabatically prepare low-energy states. We measure the local polarization and
spin-
spin correlations over this adiabatic protocol, and observe our system move from a staggered product state, through an intermediate
magnetic crystal, and finally into a disordered, correlated
liquid. We estimate the
entropy density of this atomic
liquid to be similar to that of frustrated
magnetic insulators at
liquid nitrogen temperatures. We compare the correlations in our
liquid to those of a simple, parameter-free ansatz for the Dirac
spin liquid, and find good agreement in the sign structure and spatial decay. Finally, we probe the static susceptibility of our system to a local field perturbation and to a geometrical distortion. Our results establish Rydberg atom arrays as a promising platform for the preparation and microscopic characterization of
quantum spin liquid candidates.
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All authors Guillaume Bornet, Marcus Bintz, Cheng Chen, Gabriel Emperauger, Mu Qiao, Romain Martin, Daniel Barredo, Shubhayu Chatterjee, Vincent S. Liu, Thierry Lahaye, Michael P. Zaletel, Norman Y. Yao, Antoine Browaeys
Medical Physics
Complex Wavelet-Based Sinogram Segmentation for Metal Artifact Reduction in Cone-Beam CT
Siiri Rautio, Alexander Meaney, Salla-Maaria Latva-Äijö et al. (+4 more)
Metal objects pose a significant challenge in cone-beam computed
tomography, as their strong and energy-dependent X-ray attenuation leads to inconsistent projections and severe streaking and shading artifacts in reconstructed images. These artifacts degrade image quality and limit the reliability of subsequent medical analysis. We propose a projection-domain metal artifact reduction method based on analytical metal
segmentation in the three-dimensional sinogram using the three-dimensional Dual-Tree Complex Wavelet Transform, where directional wavelet coefficients are exploited to extract the wavefront set and singular support of metal structures. The resulting
segmentation enables projection-domain inpainting and artifact-reduced reconstruction by combining metal-free and metal-only reconstructions. The proposed approach is evaluated on both simulated and clinical cone-beam computed
tomography data and consistently reduces metal artifacts compared to conventional image-domain hard-thresholding methods. The results demonstrate improved visual quality and robustness in clinically realistic scenarios, highlighting the potential of analytically grounded, non-learned projection-domain
segmentation for metal artifact reduction.
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All authors Siiri Rautio, Alexander Meaney, Salla-Maaria Latva-Äijö, Harshit Agrawal, Mikael Brix, Dinidu Jayakody, Samuli Siltanen
Accelerator Physics
Cryogenics and the use of superfluid helium in high-energy particle accelerators (1980-2000)
Philippe Lebrun
The period 1980-2000 saw the impressive development of applied superconductivity in high-energy particle accelerators, from single components to long strings of superconducting magnets and high-frequency acceleration cavities. Large and powerful cryogenic systems were designed ancillary to superconducting devices operating generally close to the normal boiling point of helium, but also above 4.2 K in supercritical and below 2 K in superfluid. Low-temperature operation in accelerators also involves considerations of ultra-high
vacuum, limited stored energy and beam stability. We recall the rationale for cryogenics in high-energy particle accelerators and review its development over the period of interest, with reference to the main engineering domains of cryostat design and heat loads, cooling schemes, efficient power refrigeration and cryogenic fluid management. In view of its importance and novelty, a specific section is devoted to the developments that led to the LHC at CERN.
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Medical Physics · Cross-listed from cond-mat.stat-mech
Magnetocardiography measurements using an optically pumped magnetometer under ambient conditions
Kushal Patel, Kesavaraja C, Pranab Dutta et al. (+1 more)
In this work, we report the development of a rubidium-based single-beam scalar optically pumped magnetometer (OPM) and demonstrate its application in measuring human cardiac
magnetic fields in an unshielded environment. The developed magnetometers exhibit a noise floor below 15 pT/sqrt(Hz) in the frequency range of 1 to 35 Hz, with a measurement bandwidth of 100 Hz. When operated in a gradiometric configuration, the noise floor is further reduced to below 3 pT/sqrt(Hz) over the same frequency range. Magnetocardiography (MCG) signals were recorded at five different locations across the thorax. A clear polarity reversal of the QRS complex was observed across these measurement positions, confirming the spatial sensitivity of the system. The proposed system shows strong potential for clinical diagnostics, offering valuable physiological information through non-contact MCG measurements
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All authors Kushal Patel, Kesavaraja C, Pranab Dutta, Korak Biswas
Computational Physics · Cross-listed from cond-mat.supr-con
Topology optimization of low-temperature type-II superconductors with superconductor-dielectric/vacuum interfaces based on Ginzburg-Landau theory under Weyl gauge
Yongbo Deng and Jan G. Korvink
Geometrical design is a crucial and challenging strategy for improving the performance of type-II
superconductors, because the proper placement of intended defects in the current path contribute to flux pinning, a reduction in dissipation, and an increase in achievable current density.
Topology optimization is currently one of the most powerful approaches used to determine consistent structural geometries. Therefore, a
topology optimization approach is presented to inversely design structural geometries of low-temperature type-II
superconductors with
superconductor-dielectric/
vacuum interfaces.
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Optics
Revealing Hidden Topology of Complex Vector Beams via Plasmonic Interactions
Sahil Sahoo, Ahmed Lafeef EN, Andre Yaroshevsky et al. (+2 more)
Structured light beams with space-variant polarization can be efficiently generated using voltage-tunable nematic
liquid-
crystal (Q-plate). By appropriately selecting the input state and the retardation of the Q-plate, an optical field acquires a spatially structured polarization distribution that is capable of encoding non-trivial topological information across the beam profile. These features can be directly read out through interaction with plasmonic nano-structures, such as circular and spiral slits. Here we show that, upon illumination, polarization-dependent excitation of surface plasmons converts the hidden
topology of the polarization structure into observable intensity distributions, including plasmonic
vortices and characteristic interference patterns, while the tunability of the input parameters enables a rich variety of distinct topological forms.
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All authors Sahil Sahoo, Ahmed Lafeef EN, Andre Yaroshevsky, Peter Banzer, Yuri Gorodetski
Atomic Physics · Cross-listed from cond-mat.quant-gas
Optical transport of cold atoms to quantum degeneracy
Yanqing Tao, Yufei Wang, Ligeng Yu et al. (+1 more)
Efficient transport of cold atoms is essential for continuous operation, enabling applications ranging from atomic
lasers to continuously operated
qubits. However, deep potentials required to overcome vibrations, axial trap nonuniformity and insufficient cooling have limited transport of cold atoms near
quantum degeneracy. Here we demonstrate rapid optical transport of cold atoms to Bose-Einstein condensation using a moving optical
lattice formed by two Bessel beams. A gas of $3 \times 10^5$ ytterbium atoms at a temperature of $340\,$nK is transported over $34\,$cm in $350\,$ms with efficiency over $60\%$. Furthermore, a degenerate gas of $1 \times 10^5$ atoms with a $40\%$ condensate fraction emerges from the phase synchronization process driven by atomic interactions. This demonstration enables the fast preparation of ultracold atomic beams and large-scale atom arrays for
quantum sensing, simulation and computing.
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All authors Yanqing Tao, Yufei Wang, Ligeng Yu, Bo Song
Optics · Cross-listed from quant-ph
Fully integrated quantum frequency processor on a silicon chip
Sara Congia, Leopold Virot, Elena Rovetta et al. (+5 more)
Frequency-bin encoding has recently emerged as a powerful approach for photonic
quantum information processing, offering high dimensionality, gate-parallelization, and compatibility with existing telecommunication infrastructure. However, its scalable deployment has so far been hindered by the lack of an integrated platform capable of unifying
quantum state generation, coherent frequency mixing, and programmable spectral control.\\ Here, we report the first fully integrated
quantum frequency processor, monolithically integrating on the same silicon photonic chip a microresonator-based biphoton
quantum frequency comb source, a pump-rejection filter, high-speed phase modulators, and a four-channel, line-by-line pulse shaper. We demonstrate key functionalities, such as tunable frequency beamsplitters with success probabilities exceeding $94\%$ and fidelities above $99.9\%$, as well as the ability to synthesize more general single-
qubit gates. Finally, we generate and coherently manipulate high-dimensional frequency-bin entangled states entirely on chip, showcasing control over two-
photon quantum walks and performing the first on-chip frequency-bin
quantum state
tomography of a Bell-state with a fidelity of $95.7(3)\%$. By integrating all key functional elements on the same $4\times7\,\textrm{mm}^2$ chip, with the possibility of scaling to a larger number of modes, our work marks an important step toward large-scale frequency-domain photonic processors for both classical and
quantum applications.
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All authors Sara Congia, Leopold Virot, Elena Rovetta, Antonio Fincato, Frederic Boeuf, Matteo Galli, Daniele Bajoni, Massimo Borghi
Optics
Controlled non-volatile modulation of optical dispersion in monolayer tungsten disulfide via ferroelectric polarization patterning
Yuhong Cao, Zekun Hu, Jason Lynch et al. (+7 more)
The manipulation of optical properties, including reflection, refraction, polarization, phase, and frequency, has long been central to advancing photonic and optoelectronic technologies. However, existing electro-optical approaches rely on volatile mechanisms that require continuous power consumption. Here, we demonstrate strong, nonvolatile modulation of optical dispersion in monolayer tungsten disulfide (ML WS2) using patterned ferroelectric domains in aluminum scandium nitride (AlScN). By locally poling ferroelectric domains into opposite states, we achieve substantial manipulation of the complex refractive index (Delta n > 0.7, Delta k > 0.4) and excitonic energy shifts (~50 meV) in ML WS2, comparable to previous gate-tuning approaches while eliminating continuous power consumption. We introduce an asymmetric screening model that reveals how ferroelectric polarization induces carrier-density-dependent Coulomb screening, leading to distinct excitonic behaviors between electron- and hole-doped regions. Furthermore, we demonstrate a gate-free lateral p-n homojunction with a rectification ratio of 6e10^3, formed through spatial carrier redistribution. These findings establish ferroelectric/2D
heterostructures as a powerful platform for nonvolatile optical dispersion engineering, enabling energy-efficient, reconfigurable photonic and optoelectronic devices.
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All authors Yuhong Cao, Zekun Hu, Jason Lynch, Bongjun Choi, Kyung Min Yang, Hyunmin Cho, Chloe Leblanc, Chen Chen, Joan M. Redwing, Deep Jariwala
Geophysics · Cross-listed from hep-ph
Limits on the Carroll-Field-Jackiw electrodynamics from geomagnetic data
G. F. de Carvalho, M. Fillion, P. C. Malta et al. (+1 more)
Lorentz-
symmetry violation may be described via the CPT-odd, dimension-3, Carroll-Field-Jackiw term, which couples the electromagnetic fields to a constant 4-vector $k_{\rm AF}$ selecting a preferred direction in spacetime. We solve the field equations using the Green's method for a static point-like
magnetic dipole and find the $k_{\rm AF}$-dependent corrections to the standard dipolar
magnetic field that strongly dominates the near-Earth
magnetic field. Given the very good agreement between current models and ground- and satellite-based geomagnetic data, our strongest constraints on the components of $k_{\rm AF}$ in the Sun-centered frame read $|(k_{\rm AF})_Z| \lesssim 4 \times 10^{-25} \, {\rm GeV}$ for $|(k_{\rm AF})_X|, |(k_{\rm AF})_Y| \lesssim 10^{-24} \, {\rm GeV}$ at the two-sigma level. This represents an improvement of about four orders of magnitude over earlier bounds based on other geophysical phenomena.
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All authors G. F. de Carvalho, M. Fillion, P. C. Malta, C. A. D. Zarro
Chemical Physics
Neural Network Based Molecular Structure Retrieval from Coulomb Explosion Imaging Data
Amirhossein Ghanaatian, Aravinth K. Ravi, Joshua Stallbaumer et al. (+6 more)
Determining the structure and following the structural
evolution of molecules undergoing chemical reactions is one of the key goals of ultrafast molecular physics and chemistry. Recently, Coulomb explosion imaging has emerged as a promising technique for imaging the evolving structure of individual molecules in the gas phase. However, its practical application for structure determination is hampered by the lack of suitable
algorithms to directly retrieve the molecular structure from the measured fragment-ion momentum data. Here, we propose a scheme to solve the underlying inverse problem by employing neural networks to infer the initial atomic positions from the final ion momenta on an event-by-event basis. Using this scheme, we retrieve the structure of several polyhalomethane isomers from simulated Coulomb explosion imaging data with an average per-atom position error of approximately 0.1 atomic units, i.e., to within 5% of the typical bond lengths. This development paves the way for an automated structure
retrieval from Coulomb explosion data one molecule at a time, making it ideally suitable for analyzing pump-probe experiments where several products are formed that need to be distinguished.
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All authors Amirhossein Ghanaatian, Aravinth K. Ravi, Joshua Stallbaumer, Huynh V. S. Lam, Artem Rudenko, Loren Greenman, Nathan Albin, Doina Caragea, Daniel Rolles
Applied Physics · Cross-listed from eess.SP
Electromagnetic Bounds on Realizing Targeted MIMO Transfer Functions in Real-World Systems with Wave-Domain Programmability
Philipp del Hougne
A key question for most applications involving reconfigurable linear wave systems is how accurately a desired linear operator can be realized by configuring the system's tunable elements. The relevance of this question spans from hybrid-
MIMO analog combiners via computational meta-imagers to programmable wave-domain signal processing. Yet, no electromagnetically consistent bounds have been derived for the fidelity with which a desired operator can be realized in a real-world reconfigurable wave system. Here, we derive such bounds based on an electromagnetically consistent multiport-network model (capturing mutual coupling between tunable elements) and accounting for real-world hardware constraints (lossy, 1-bit-programmable elements). Specifically, we formulate the operator-synthesis task as a quadratically constrained fractional-quadratic problem and compute rigorous fidelity upper bounds based on semidefinite relaxation. We apply our technique to three distinct experimental setups. The first two setups are, respectively, a free-space and a rich-scattering $4\times 4$
MIMO channel at 2.45 GHz parameterized by a reconfigurable intelligent surface (RIS) comprising 100 1-bit-programmable elements. The third setup is a $4\times 4$
MIMO channel at 19 GHz from four feeds of a dynamic metasurface
antenna (DMA) to four users. We systematically study how the achievable fidelity scales with the number of tunable elements, and we probe the tightness of our bounds by trying to find optimized configurations approaching the bounds with standard discrete-optimization techniques. We observe a strong influence of the coupling strength between tunable elements on our fidelity bound. For the two RIS-based setups, our bound attests to insufficient wave-domain flexibility for the considered operator synthesis.
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Geophysics
Ice-free geomorphometry of Queen Maud Land, East Antarctica: 3. Belgica and Yamato (Queen Fabiola) Mountains
I.V. Florinsky and S.O. Zharnova
Geomorphometric modeling and mapping of ice-free Antarctic areas can be applied for obtaining new quantitative knowledge about the topography of these unique landscapes and for the further use of morphometric information in Antarctic research. Within the framework of a project of creating a physical geographical thematic scientific reference geomorphometric atlas of ice-free areas of Antarctica, we performed geomorphometric modeling and mapping of two, partly ice-free mountainous areas of the eastern Queen Maud Land, East Antarctica. These include the Belgica Mountains and Yamato (Queen Fabiola) Mountains. As input data, we used two fragments of the Reference Elevation Model of Antarctica (REMA). For the two ice-free areas and adjacent glaciers, we derived models and maps of eleven, most scientifically important morphometric variables (i.e., slope, aspect, horizontal
curvature, vertical
curvature, minimal
curvature, maximal
curvature, catchment area, topographic wetness index, stream power index, total insolation, and wind exposition index). The obtained models and maps describe the ice-free topography of the Belgica Mountains and Yamato (Queen Fabiola) Mountains in a rigorous, quantitative, and reproducible manner. New morphometric data can be useful for further geological, geomorphological, glaciological, ecological, and hydrological studies of these areas.
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Fluid Dynamics
Droplet impact on surfactant-laden thin liquid films: Vortex ring dynamics
Hatim Ennayar, Hyoungsoo Kim and Jeanette Hussong
Droplet impact on surfactant-laden thin
liquid films is investigated experimentally with emphasis on
vortex ring dynamics. Bottom- and side-view imaging reveal that increasing surfactant concentration progressively stabilize
vortex rings, suppress azimuthal instabilities and promote concentric mixing patterns. A regime map is established in terms of film thickness, Reynolds number, and surface-tension ratio, yielding an empirical instability threshold. Shadowgraphy observations suggest that Marangoni stresses modify early capillary-wave dynamics, potentially altering
vortex ring formation and delaying instability onset. These findings clarify the link between interfacial stresses,
vortex ring dynamics, and mixing patterns in thin-film droplet impact.
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Chemical Physics
An accurate theoretical framework for the optical and electronic properties of paracyclophanes
Vladislav Slama, Camila Negrete-Vergara, Elnaz Zyaee et al. (+5 more)
Aromatic $\pi$-stacking interactions play an important role in both natural and artificial systems, influencing processes such as charge separation in photosynthesis and charge transport in organic
semiconductors. Controlling the geometry and distance between aromatic units is therefore crucial for tuning intermolecular interactions and charge-transfer efficiency. Due to their well-defined stacking geometry, paracyclophanes (PCPs) composed of two or more aromatic units connected by rigid linkers, provide an ideal platform for a systematic study of such effects. Despite extensive experimental studies of PCPs, a comprehensive and quantitatively validated theoretical description linking the structure with the electronic and optical properties is still missing. Here, we present an extensive computational and experimental investigation of the electronic and optical properties of homo-PCPs containing naphthalene diimide (NDI) or pyrene chromophores linked by bridges of varying length and
rigidity. We introduce a robust methodology for an accurate simulation of the absorption and fluorescence spectra of PCPs based on a combined TD-DFT and CC2 approach, achieving excellent quantitative agreement with experiment. We also present and validate a fragment-based description of PCPs using the Frenkel
exciton model. Such approach is valuable not only for interpretation of the electronic and optical properties of PCPs, but it can also significantly reduce the cost of the calculation while maintaining the accuracy of the supermolecular approach. This work establishes a quantitatively reliable framework linking structure, excitonic coupling, and charge-transfer interactions in PCPs with optical properties, providing design principles for next-generation optoelectronic materials.
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All authors Vladislav Slama, Camila Negrete-Vergara, Elnaz Zyaee, Silvio Decurtins, Pascal Manuel Hanzi, Thomas Feurer, Shi-Xia Liu, Ursula Rothlisberger