Fluid Dynamics · Cross-listed from cond-mat.stat-mech
Some remarks on the objectivity and thermodynamic consistency of Korteweg-type fluids
Peter Ván
In this note we compare the
entropy principle and the objectivity arguments in the methodologies of Dunn and Serrin [1] and in the more recent weakly nonlocal thermodynamic analysis of Korteweg-type fluids in [2]. It is concluded that the different objectivity approaches lead to the same constitutive functions, and that the difference in the thermodynamically compatible pressure tensors of perfect Korteweg fluids is due to different
symmetry requirements.
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Optics
A Calibration Method for Indirect Time-of-Flight Cameras to Eliminate Internal Scattering Interference
Yansong Du, Jingtong Yao, Yuting Zhou et al. (+3 more)
In-camera light scattering is a typical form of non-systematic interference in indirect Time-of-Flight (iToF) cameras, primarily caused by multiple reflections and optical path variations within the camera body. This effect can significantly reduce the accuracy of background depth measurements. To address this issue, this paper proposes a calibration-based model derived from real measurement data, introducing three physically interpretable calibration parameters: a normal-exposure amplitude influence coefficient, an overexposure amplitude influence coefficient, and a scattering phase shift coefficient. These parameters are used to describe the effects of foreground size, exposure conditions, and optical path differences on scattering interference. Experimental results show that the depth values calculated using the calibrated parameters can effectively compensate for scattering-induced errors, significantly improving background depth recovery in scenarios with complex foreground geometries and varying illumination conditions. This approach provides a practical, low-cost solution for iToF systems, requiring no complex hardware modifications, and can substantially enhance measurement accuracy and robustness across a wide range of real-world applications.
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All authors Yansong Du, Jingtong Yao, Yuting Zhou, Feiyu Jiao, Zhaoxiang Jiang, Xun Guan
Instrumentation and Detectors
Estimation of the Inverse Compton Scattering Background in MeV Gamma-Gamma Collider
Ping Zhou, Meiyu Si, Yuanjie Bi et al. (+2 more)
The MeV Gamma-Gamma
Collider would provide a direct experimental platform for elastic light-by-light scattering ($\gamma\gamma \to \gamma\gamma$) and the Breit-Wheeler process with two real
photons ($\gamma\gamma \to e^+e^-$). A Monte Carlo code, the Genie Background Evaluation Tool (GBET), has been developed to fully simulate two successive inverse Compton scatterings in the linear regime, including $e^- + \text{laser} \to e^-+ \gamma$ and $e^- + \gamma \rightarrow e^- + \gamma$. GBET overcomes the inherent information loss in traditional luminosity-spectrum-based chain simulations, preserving full particle-level information and achieving higher physical fidelity. The effectiveness of the code is verified by benchmarking against the simulation results of CAIN. GBET shows that the event rate of background
photons generated by the first inverse Compton scattering is $6.24 \times 10^7$/s, with energies below 18 eV; the second inverse Compton scattering generates background electrons at 51.99/s and
photons at 0.99/s, both with energies below 11 MeV. In addition, Møller scattering contributes background electrons at 0.56/s with energies around 200 MeV. The count rates of background electrons and positrons originating from the Breit-Wheeler process are 1312.2/s and 1314.3/s, respectively, with energy distributions ranging from 511 to 720 keV.
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All authors Ping Zhou, Meiyu Si, Yuanjie Bi, Illya Drebot, Yongsheng Huang
Fluid Dynamics · Cross-listed from cs.LG
Interpretable Diagnostics and Adaptive Data Assimilation for Neural ODEs via Discrete Empirical Interpolation
Hojin Kim and Romit Maulik
We present a framework that leverages the Discrete Empirical Interpolation Method (DEIM) for interpretable deep learning and dynamical system analysis. Although DEIM efficiently approximates nonlinear terms in projection-based reduced-order models (POD-ROM), its fixed interpolation points are repurposed for identifying dynamically representative spatial structures in learned models. We apply DEIM as an interpretability tool to examine the learned dynamics of a pre-trained Neural Ordinary Differential Equation (NODE) for two-dimensional
vortex-merging and backward-facing step flows. DEIM trajectories reveal physically meaningful structures in NODE predictions and expose failure modes when extrapolating to unseen flow configurations. Building on this diagnostic capability, we further introduce a DEIM-guided data assimilation strategy that injects sparse, dynamically representative corrections into the NODE rollout. By allocating a limited nudging budget to DEIM-identified sampling locations, the framework significantly improves long-term stability and predictive accuracy in out-of-distribution scenarios for the two-dimensional
vortex-merging flow. Additional experiments for a flow over a backward-facing step reveal regime-dependent gains, with alternative sampling strategies performing competitively as well. These results demonstrate that DEIM can serve as an interpretable diagnostic and control framework for understanding and enhancing neural differential equation models.
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Applied Physics · Cross-listed from cond-mat.soft
Laser Patterning of Superhydrophobic transparent glass surfaces with anti-fogging and anti-icing applications
Laura Montes-Montañez, Fernando Nuñez-Galvez, Melania Sanchez-Villa et al. (+11 more)
This work addresses the fabrication of transparent glass surfaces with superior water-repellence (i.e., superhydrophobicity), and related functional properties such as omniphobicity, anti-fogging and anti-icing responses. Surfaces have been processed by means of mild femtosecond
laser patterning combined with the grafting of fluorinated tethered molecules. Controlling the
laser scan and ablation conditions permits the fabrication of under-design grooves with cross and lineal morphologies and separations between 10 and 500 um. These patterns provide a high transparency and repellence to
liquids and ice over large areas. The best performance is obtained for cross or parallel line patterned glass with microgrooves separated by 100 um and 15 um depth thanks to 5
laser scanning repetitions. These surfaces present a stable Cassie-Baxter wetting state and very low ice-adhesion strength while keeping up to 80 % of optical transmittance in the visible region. Anti-fouling tests, along with freezing and thawing cycles on these surfaces, have demonstrated a remarkable and durable self-cleaning response, even under environmentally stressful conditions. Water condensation experiments conducted under atmospheric conditions, as well as in an environmental electron scanning microscope, have revealed important issues related to the formation of supercooled water droplets. These experiments show that the patterned breakdown of surface properties effectively prevents extensive fogging and water accumulation. This feature is particularly crucial for outdoors and low temperature applications where the preservation of transparency is essential.
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All authors Laura Montes-Montañez, Fernando Nuñez-Galvez, Melania Sanchez-Villa, Luis A. Angurel, Heli Koivuluo-to, German F. de la Fuente, Víctor Trillaud, Philippe Steyer, Karine Masenelli-Varlot, Francisco J. Palomares, Ana Borrás, Agustín R. González-Elipe, Carmen López-Santos, Víctor Rico
Physics and Society
The 1979 Iranian Revolution and the Lost Decade of Science: A Counterfactual Scientometric Analysis
Ehsan Roohi
This paper presents a comprehensive scientometric analysis of the long-term impact of the 1979 Iranian Revolution on the nation scientific development. Using Scopus-indexed data from 1960 to 2024, we
benchmark Iran publication trajectory against a carefully selected peer group representing diverse development models, established scientific leaders, Netherlands, stable regional powers, Israel, and high-growth, Asian Tigers, South Korea, Taiwan, Singapore alongside Greece and China. The analysis reveals a stark divergence, in the late 1970s, Iran scientific output surpassed that of South Korea, China and Taiwan. The revolution, however, precipitated a collapse, followed by a lost decade of stagnation, precisely when its Asian peers began an unprecedented, state driven ascent. We employ counterfactual models based on pre revolutionary growth trends to quantify the resulting knowledge deficit. The findings suggest that, in an alternate, stable timeline, Iran scientific output could have rivaled South Korea today. We further outline a research agenda to analyze normalized impact metrics, such as FWCI, and collaboration patterns, complementing our findings on publication volume. By contextualizing Iran unique trajectory, this study contributes to a broader understanding of the divergent recovery patterns exhibited by national scientific systems following profound political shocks, offering insights into the enduring consequences of historical disruptions on the global scientific landscape.
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Atmospheric and Oceanic Physics
Projecting Hurricane Risk in Atlantic Canada under Climate Change
Saeed Saviz Naeini, Reda Snaiki and Alejandro Di Luca
Atlantic Canada faces significant hurricane threats from damaging winds and coastal flooding that are projected to intensify under
climate change. This study adopts a two-stage framework. First, the
evolution of wind and coastal-flood hazards is quantified from a historical baseline (1979-2014) to two future periods: a near future (2024-2059) and a far future (2060-2095). Hazard fields are constructed from large ensembles of physics-informed synthetic hurricane tracks, and changes are evaluated in return-period wind speeds and in inundation depth and extent, with sea-level rise included for flood projections. The second stage estimates hurricane risk using wind as an operational proxy for total loss, combining the simulated wind fields with exposure data and a vulnerability relationship to compute expected damages. This design clarifies how physical drivers change and how those shifts translate into loss potential without requiring fully coupled compound-loss modeling. Results indicate an intensification of wind extremes and a substantial amplification of coastal inundation, yielding higher wind-proxy risk for many coastal communities. Spatial patterns show a heterogeneous escalation of risk concentrated along exposed shorelines and urban corridors. This comprehensive analysis of both hazard
evolution and proxy risk provides decision-ready evidence on where and by how much hurricane losses are likely to grow. The approach clarifies the link between physical drivers and loss potential, ensuring compatibility with standard wind-centric workflows used in engineering and insurance practice.
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General Physics
Supersonic and Superluminal Energy and Speed of Information via Temporal Interference in a Dispersionless Environment
John L. Spiesberger and Eugene Terray
Numerical implementation of a theory yields acoustic wave packets whose peak-to-peak speeds, $c_{3d}$, are supersonic in a dispersionless medium due to temporal interference between direct and boundary-reflected paths. The effect occurs when the source and receiver are near each other and at least one is within $c\tilde{\delta t}/2$ of the boundary, where $c$ is the phase speed of propagation in the medium, and $\tilde{\delta t}$ is the smallest temporal separation between the paths at which interference first occurs. This direct+reflected path effect is distinct from previously-observed superluminal phenomena and theories including
quantum tunneling, cavity
vacuum fluctuations, and group speeds due to anomalous dispersion. For temporally interfering direct+reflected paths, simulations yield a speed of information less than $c$. The speed of information from the interfering paths can exceed the speed derived from propagation only along the direct path. We
conjecture these results will also hold for electromagnetic (EM) wave propagation. If so, we prove the speed of information is less than or equal to the speed of light in a
vacuum, so the effect does not violate special relativity. These theoretical and simulation results, as well as their conjectured EM extension, should be readily accessible to experimental verification.
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Optics
Demonstration of $\bf3.5\times10^{-13}$ laser frequency stability at 1000 s using an iodine-filled hollow-core fiber photonic microcell
Pengzhuo Wang, Jose Sanjuan, Moritz Mehmet et al. (+1 more)
We present a
laser frequency stabilization system based on an iodine-filled hollow-core photonic microcell (PMC), which is a sealed version of a hollow-core photonic
crystal fiber (HC-PCF). A 532 nm
laser is locked to the a1 component of the R(56) 32-0 transition of molecular iodine in the fiber
cell, and its frequency stability is compared to that of the same component in a free-space iodine
cell. Noise analysis reveals that the system is limited by parasitic beams that interfere with the beam of interest and degrade the error signal. We have identified and characterized three types of parasitic interference and designed suppression methods for each. After applying these suppression methods, the frequency stability improved by more than an order of magnitude. The system achieves fractional frequency stability of $3.5\times10^{-13}$ for integration times around 1000 s. To our knowledge, this represents the best frequency stability achieved using a gas-filled hollow-core photonic
crystal fiber frequency reference.
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All authors Pengzhuo Wang, Jose Sanjuan, Moritz Mehmet, Felipe Guzman
Physics and Society
When Networks Substitute for Outcome Surveillance? A Substitution-Complementarity Framework for Behavioral Signals in Predictive Monitoring
Sepehr Ilami, Qingtao Cao and Babak Heydari
Monitoring systems increasingly fuse dynamic behavioral data with outcome-based surveillance, raising a basic question: when does behavioral data carry predictive information that outcome history lacks? We study this using epidemic
forecasting on mobility networks, asking whether mobility networks provide independent predictive signal beyond local outcome-based surveillance. We formalize this as a substitution-complementarity problem over directed, weighted mobility networks. Using a Frisch-Waugh-Lovell variance decomposition, our analytical framework derives domain-agnostic conditions under which network-
topology features retain incremental explanatory power beyond autoregressive outcome histories. We instantiate the framework using town-level COVID-19
forecasting in Massachusetts (April 2020-April 2021), constructing mobility networks among 300+ towns from smartphone-derived origin-destination aggregates to extract centrality metrics. An
agent-based model on synthetic networks confirms that the regime boundary arises from a generic interaction between macro-scale epidemic state and network
topology, rather than
dataset-specific artifacts. Prevalence-gated interactions between statewide incidence and network features yield large out-of-sample gains when primary surveillance is degraded (Predict-R2 increases from about 0.60 to 0.83-0.89) but only marginal lift when granular local histories are available (+0.5 percentage points). Gains concentrate during epidemic waves when behavioral responses shift network connectivity rapidly. Framed as a value-of-information problem, the substitution gain reflects the marginal value of behavioral data relative to primary-channel quality. This yields a transferable, cost-aware design rule: integrate
topology-aware behavioral signals when primary surveillance is degraded or the network changes rapidly; otherwise, rely on autoregressive baselines.
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Computational Physics
Comparative Analysis of Mechanical Stability and Biomarkers of Commercial and Modified Intraocular Lens (IOL) Models: A Numerical and Experimental Approach
Taner Karateke and Abdullah Mevlut Mutluel
This study comprehensively investigates the mechanical stability of intraocular lenses (IOLs) - critical components in cataract surgery - by analyzing their haptic designs. Three commercial models (ALSEE, GF3, and UD613) and five
geometric variations (V1 to V5) derived from the GF3 model were comparatively evaluated in both dry and saline environments. The methodology utilized the Finite Element Method (FEM) to analyze computer-aided designs (CAD) created in SolidWorks under quasi-static compression forces (0.5 to 2.0 N). Mesh independence tests were performed to ensure simulation accuracy, and boundary conditions were defined according to physiological parameters. Numerical data were evaluated using key mechanical biomarkers: axial displacement, elastic modulus, stress, and strain. Results indicated that the UD613 model exhibited the highest compression force and stress values in both environments. While the V5 variation showed the highest elastic modulus in the dry environment, the V2 model outperformed others in this parameter within the saline environment. Notably, the GF3 model provided more balanced mechanical responses compared to its commercial counterparts, serving as the baseline for the developed
geometric variations. The findings demonstrate that even minor modifications in haptic arm geometry significantly impact the mechanical stability of the lens. Optimizing this stability is crucial in clinical applications to minimize decentration, tilt, and rotation, which degrade optical quality. Analysis concluded that the V4 model offers the most suitable
geometric structure for mechanical stability and potential patient comfort. This research establishes a validated simulation framework for manufacturers and R&D teams to develop next-generation IOL designs with superior optical performance and long-term durability.
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Biological Physics · Cross-listed from quant-ph
Morphological computational capacity of Physarum polycephalum
Suyash Bajpai, Aviva Lucas-DeMott, Nirosha J Murugan et al. (+2 more)
While computational capacity limits of the universe and carbon-based life have been estimated, a stricter bound for aneural organisms has not been established. Physarum polycephalum, a unicellular, multinucleated amoeba, is capable of complex problem-solving despite lacking
neurons. By analyzing growth dynamics from high-throughput imaging data-more than 500 samples tracked every 30 minutes for one to three days-across two distinct Physarum strains under diverse biological conditions, we map morphological
evolution to information processing. We revisit the Margolus-Levitin bound that constrains maximum computation rates, deriving a correction for these driven-dissipative living systems. Time-series data of Physarum's morphology-quantified through area, perimeter, circularity, and fractal dimension-enable the determination of upper bounds on the number of logical operations achievable through its hydromechanical, chemical, kinetic, and
quantum-optical degrees of freedom. The time-series trends of these morphological quantities remain statistically robust across 100,000 bootstrap resamples at both 95% and 99.5% confidence intervals. Based on the organism's explored areas and characteristic values of ATP available for work, the computational capacity of Physarum is upper bounded by ${\sim}10^{33}$ logical operations in 24 hours, scaling linearly in the non-
equilibrium steady state. This framework enables comparison of the computational capacities of life, exploiting either classical or
quantum degrees of freedom.
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All authors Suyash Bajpai, Aviva Lucas-DeMott, Nirosha J Murugan, Michael Levin, Philip Kurian
Fluid Dynamics
Guiding diffusion models to reconstruct flow fields from sparse data
Marc Amorós-Trepat, Luis Medrano-Navarro, Qiang Liu et al. (+2 more)
The reconstruction of unsteady flow fields from limited measurements is a challenging and crucial task for many engineering applications. Machine learning models are gaining popularity for solving this problem due to their ability to learn complex patterns from data and to generalize across diverse conditions. Among these,
diffusion models have emerged as being particularly powerful for generative tasks, producing high-quality samples by iteratively refining noisy inputs. In contrast to other methods, these generative models are capable of reconstructing the smallest scales of the fluid spectrum. In this work, we introduce a novel sampling method for
diffusion models that enables the reconstruction of high-fidelity samples by guiding the reverse process using the available sparse data. Moreover, we enhance the reconstructions with available physics knowledge using a conflict-free update method during training. To evaluate the effectiveness of our method, we conduct experiments on 2 and 3-dimensional turbulent flow data. Our method consistently outperforms other
diffusion-based methods in predicting the fluid's structure and in pixel-wise accuracy. This study underscores the remarkable potential of
diffusion models in reconstructing flow field data, paving the way for leveraging them in fluid dynamics research and applications ranging from super-resolution to reconstructions of experiments.
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All authors Marc Amorós-Trepat, Luis Medrano-Navarro, Qiang Liu, Luca Guastoni, Nils Thuerey
Chemical Physics
Applying R-Matrix Theory to Atom-Molecule Inelastic Collisions: the case study of H$_2$O + H
Ricardo Manuel García-Vázquez, Lisan David Cabrera-González, Otoniel Denis-Alpizar et al. (+2 more)
The present study presents a comprehensive theoretical investigation of atom and asymmetric top molecule inelastic scattering based on the R-
matrix formalism. The proposed methodology establishes a rigorous framework for treating inelastic collisions in the space-fixed coordinate system. The excellent numerical performance of the method is demonstrated through the comparison of state-to-state rotationally inelastic R-
matrix cross sections for the H + H$_2$O system with those obtained using conventional close-coupling (CC) theory. The R-
matrix approach is shown to deliver results of comparable accuracy while achieving substantially reduced computation times. The method is furthermore shown to achieve more than one order-of-magnitude speedup by exploiting GPU-accelerated diagonalisation through the MAGMA library. This combination of accuracy and computational efficiency positions the R–
matrix approach as a powerful and scalable tool for investigating inelastic scattering involving complex polyatomic systems, thereby paving the way for systematic studies of molecule-molecule interactions in astrophysical, atmospheric, and cold-matter environments.
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All authors Ricardo Manuel García-Vázquez, Lisan David Cabrera-González, Otoniel Denis-Alpizar, Philippe Halvick, Thierry Stoecklin
Fluid Dynamics · Cross-listed from cond-mat.soft
Coupled imbibition and evaporation of droplets deposited on a nanoporous layer
Joachim Trosseille, Hugo Bellezza and Olivier Vincent
Liquids in nanoscale hydrophilic pores generate capillary pressures so large that they could theoretically climb kilometers against
gravity. However, droplets on thin nanoporous layers form imbibition fronts stopping at millimeters or less due to evaporation competing with capillary flow. Such droplet infiltration dynamics is of growing interest for studying confined fluids and for applications such as water harvesting, printing, chemical delivery, actuation, and sensing. Here, we investigate theoretically and experimentally the spontaneous imbibition and evaporation of sessile droplets into thin mesoporous layers, focusing on their dependence on imposed relative humidity (RH). Theoretically, we provide a unified analytical approach for the dynamics of the wetted annulus ("
halo") around the droplet, accounting for arbitrary
halo dimensions and confinement-induced thermodynamic shifts (Kelvin effect). Experimentally, we study water droplets on oxidized porous silicon layers (pore diameter 3-4 nm, thickness 5 $\mu$m), systematically investigating how
halo and droplet dynamics depend on RH. We show that
halo formation timescales diverge at a critical RH due to the Kelvin effect, as illustrated by comparing RH-dependent evaporation rates in the
halo (confined
liquid) and in the droplet (bulk
liquid). Our analysis also reveals an apparent divergence of the imbibition coefficient, unexplained by standard capillary models, suggesting a key role for Kelvin-driven vapor transport along the porous surface. The complex couplings revealed by our study call for caution in interpreting
halo dynamics data. Our results also highlight RH as a powerful control parameter for tuning droplet imbibition behavior and infiltration patterns.
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Chemical Physics
Fokker-Planck equation governing the distribution of walkers in AFQMC
Alfred Li, Ankit Mahajan and Sandeep Sharma
Auxiliary-field
quantum Monte Carlo (AFQMC) is typically formulated as an open-ended random walk in an overcomplete space of Slater determinants, implemented through a Langevin equation. However, the explicit form of the underlying Fokker-Planck equation governing the walker population distribution has remained unknown. In this paper, we derive the Fokker-Planck equation for AFQMC and propose a novel numerical scheme to solve it. The solution of the Fokker-Planck equation reveals the wavefunction actually sampled by the AFQMC
algorithm. Interestingly, we find that even when the exact ground state is used as a guiding wavefunction in constrained path AFQMC, contrary to the common assumption, the wavefunction sampled by AFQMC is not exact. Beyond clarifying several fundamental aspects of AFQMC, the availability of a Fokker-Planck equation formulation opens new avenues for systematically improving its accuracy, which we outline in this paper.
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Atomic Physics · Cross-listed from gr-qc
Detecting White Dwarf Binary Mergers with Gravitational Waves
Giona Sala, Chiara Brandenstein, Sebastian Baum et al. (+1 more)
Mergers of white
dwarf binaries are a possible progenitor channel for Type Ia
supernovae. While white
dwarfs are abundant in the universe and relatively well understood, their gravitational wave signals have not yet been directly observed. In order to detect gravitational waves from merging white
dwarf binaries, a detector in the mid-band between LVK and LISA appears necessary. In this paper, we compute and discuss the gravitational waves emitted by inspiraling and merging white
dwarf binaries, and assess their detectability with proposed space-based atom-interferometer detectors such as MAGIS Space and AEDGE. Gravitational waves from massive white
dwarf binaries can be observed for many years before merger, offering a unique early warning of their final explosion. Our projections suggest that MAGIS Space could detect signals from Type Ia
supernova progenitors at least once every four years, while AEDGE could observe at least a few hundred such events annually. The prolonged gravitational wave emission captured by atom-interferometers provides precise sky localisation and can allow observation of the final explosion with electromagnetic
telescopes. The combined observation with electromagnetic radiation from the white
dwarf binary coalescence could open a new pathway for multi-messenger astronomy involving some of the brightest transient events in the universe.
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All authors Giona Sala, Chiara Brandenstein, Sebastian Baum, Peter W. Graham
Optics · Cross-listed from astro-ph.IM
On-sky Demonstration of Subdiffraction-limited Astronomical Measurement Using a Photonic Lantern
Yoo Jung Kim, Michael P. Fitzgerald, Sébastien Vievard et al. (+18 more)
Resolving fine details of astronomical objects provides critical insights into their underlying physical processes. This drives in part the desire to construct ever-larger
telescopes and interferometer arrays and to observe at shorter wavelength to lower the diffraction limit of angular resolution. Alternatively, one can aim to overcome the diffraction limit by extracting more information from a single
telescope's aperture. A promising way to do this is spatial mode-based imaging, which projects focal-plane field onto a set of spatial modes before detection, retaining focal-plane phase information crucial at small angular scales but typically lost in intensity imaging. However, the practical implementation of mode-based imaging in astronomy from the ground has been challenged by atmospheric
turbulence. Here, we present the first on-sky demonstration of a subdiffraction-limited, mode-based measurement using a photonic lantern (PL)-fed spectrometer installed on the SCExAO instrument at the Subaru
Telescope. We introduce a novel calibration strategy that mitigates time-varying wavefront error and misalignment effects, leveraging simultaneously recorded focal-plane images and using a spectral-differential technique that self-calibrates the data. Observing the classical Be
star $\beta$ CMi, we detected spectral-differential spatial signals and reconstructed images of its H$\alpha$-emitting disk. We achieved an unprecedented H$\alpha$ photocenter precision of 50$\mu$as in about 10-minute observation with a single
telescope, measuring the disk's near-far side asymmetry for the first time. This work demonstrates the high precision, efficiency, and practicality of photonic mode-based imaging techniques to recover subdiffraction-limited information, opening new avenues for high angular resolution spectroscopic studies in astronomy.
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All authors Yoo Jung Kim, Michael P. Fitzgerald, Sébastien Vievard, Jonathan Lin, Yinzi Xin, Miles Lucas, Olivier Guyon, Julien Lozi, Vincent Deo, Elsa Huby, Sylvestre Lacour, Manon Lallement, Rodrigo Amezcua-Correa, Sergio Leon-Saval, Barnaby Norris, Mathias Nowak, Steph Sallum, Jehanne Sarrazin, Adam Taras, Stephanos Yerolatsitis, Nemanja Jovanovic
Atmospheric and Oceanic Physics
Characterising the properties of the atmospheric emission at Teide Observatory in the 10-20 GHz range with QUIJOTE data
Apolline Chappard, José Alberto Rubiño-Martín and Ricardo Tanausú Génova Santos
QUIJOTE is a CMB experiment composed of two
telescopes, QT1 and QT2, located at the Teide Observatory in Tenerife, Spain. The MFI instrument (2012-2018), installed on QT1, observed the sky at four frequency bands (11, 13, 17, and 19 GHz) with one degree angular resolution. Its successor, MFI2, began operations in 2024 and operates in the same bands. This paper has two main goals: first, to characterise the atmospheric conditions at Teide Observatory to improve existing models at these frequencies, and second, to empirically characterise atmospheric
turbulence using QUIJOTE MFI and MFI2 observations. This work has implications for both atmospheric physics and CMB studies and can support future reanalyses of MFI data or the preparation of upcoming instruments such as the Tenerife Microwave Spectrometer. We used data from GPS
antennas, the STELLA observatory, and
radio soundings to derive median profiles and distributions of key atmospheric parameters for 2012-2018. MFI data were analysed to compute atmospheric structure functions at 17 and 19 GHz and to study the correlation properties of the atmospheric signal through cross-correlation between horns at the same frequency. MFI2 observations were used to estimate the atmospheric power spectrum and compare it with the structure function derived from MFI data. The water vapour density profile follows an exponential decay with a characteristic half-height of about 1000 m. Median PWV in 2012-2018 is 3.3 mm. For high PWV conditions, the structure function agrees with the Kolmogorov
turbulence model. The slope of the power spectrum also matches the model prediction, within the frequency range limited by the outer scale and instrument noise. Finally, from the correlation function, we find that atmospheric conditions remain stable for about 1-2 hours.
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Optics · Cross-listed from quant-ph
Atomic-superfluid heat engines controlled by twisted light
Aritra Ghosh, Nilamoni Daloi and M. Bhattacharya
We theoretically propose a
quantum heat engine using a setup consisting of a ring-trapped Bose-Einstein condensate placed in a Fabry-Pérot cavity where the optical field carries orbital angular momentum. We first show that the cavity-enhanced light-atom coupling leads to the emergence of polaritonic modes whose character can be reversibly switched between photonlike and phononlike by detuning sweeps, allowing work extraction governed by distinct reservoirs. We investigate the dependence of the engine efficiency on the orbital angular momentum. Beyond ideality, we discuss finite-time scenarios based on shortcuts to adiabaticity such that the efficiency retains its ideal-operation value, despite finite-time operation. Our analysis identifies orbital angular momentum as a control knob that can reconfigure the performance of such
quantum heat engines.
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Atomic Physics
Single Sr Atoms in Optical Tweezer Arrays for Quantum Simulation
Veronica Giardini, Luca Guariento, Andrea Fantini et al. (+6 more)
We report on the realization of a platform for trapping and manipulating individual $^{88}$Sr atoms in optical tweezers. A first cooling stage based on a blue shielded magneto-optical trap (MOT) operating on the $^1S_0$ -> $^1P_1$ transition at 461 nm enables us to trap approximately $4\times 10^6$ atoms at a temperature of 6.8 mK. Further cooling is achieved in a narrow-line red MOT using the $^1S_0$ -> $^3P_1$ intercombination transition at 689 nm, bringing $4\times 10^5$ atoms down to 5 $\mu$K and reaching a density of $\approx 10^{10}$ cm$^{-3}$. Atoms are then loaded into 813 nm tweezer arrays generated by crossed acousto-optic deflectors and tightly focused onto the atoms with a high-numerical-aperture objective. Through light-assisted collision processes we achieve the collisional blockade, which leads to single-atom occupancy with a probability of about $50\%$. The trapped atoms are detected via fluorescence imaging with a fidelity of $99.986(6)\%$, while maintaining a survival probability of $97(2)\%$. The release-and-recapture measurement provides a temperature of $12.92(5)$ $\mu$K for the atoms in the tweezers, and the ultra-high-
vacuum environment ensures a
vacuum lifetime higher than 7 min. These results demonstrate a robust alkaline-earth tweezer platform that combines efficient loading, cooling, and high-fidelity detection, providing the essential building blocks for scalable
quantum simulation and
quantum information processing with Sr atoms.
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All authors Veronica Giardini, Luca Guariento, Andrea Fantini, Shawn Storm, Massimo Inguscio, Jacopo Catani, Giacomo Cappellini, Vladislav Gavryusev, Leonardo Fallani
Accelerator Physics
First Observation of Dispersive Shock Waves in an Electron Beam
H. McCright, I.G. Abel, I. Haber et al. (+2 more)
Dispersive shock waves (DSWs) are expanding nonlinear wave trains that arise when dispersion regularizes a steepening front, a phenomenon observed in fluids,
plasmas, optics, and superfluids. Here we report the first experimental observation of DSWs in an intense electron beam, using the University of Maryland Electron Ring (UMER). A localized induction-
cell perturbation produced a negative density pulse that evolved into a leading
soliton-like peak followed by an expanding train of oscillations. The leading peak satisfied
soliton scaling laws for width^2 vs inverse amplitude and velocity vs amplitude, while the total wave-train width increased linearly with time, consistent with Korteweg–de Vries (KdV) predictions. Successive peaks showed decreasing amplitude and velocity toward the trailing edge, in agreement with dispersive shock ordering. These results demonstrate that intense charged particle beams provide a new laboratory platform for studying dispersive hydrodynamics, extending nonlinear wave physics into the high-intensity beam regime.
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All authors H. McCright, I.G. Abel, I. Haber, P.G. O'Shea, B.L. Beaudoin