Atomic Physics
An atom chip interferometer
B. Wirtschafter, C. I. Westbrook and M. Dupont-Nivet
We have realized an interferometer using a thermal cloud of magnetically trapped rubidium 87 atoms on a chip. The interferometer resembles a Ramsey interferometer with a state selective spatial splitting of the two internal states as proposed in [M. Ammar, and al., Phys. Rev. A, 91, 053623]. The splitting is effected by microwave fields from two on-chip waveguides while the atoms remain magnetically trapped. The inferred maximum separation is $1.2\pm 0.1~\mu$m. We observe interference fringes with a contrast around 8% limited by velocity difference of the two interferometer states when we close the interferometer. We develop a model describing this contrast decay.
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Optics
Enabling atom-clad waveguide operation in a microfabricated alkali vapor-photonic integrated circuit
Rahul Shrestha, Khoi Tuan Hoang, Peter Riley et al. (+5 more)
Integrating alkali atomic vapors with nanophotonic devices offers a scalable route to
quantum technologies that leverage strong atom-
photon interactions. While there have been many approaches to such integration, the general reliance on traditional glass vapor
cells, distilled alkali metals, and epoxy sealing limits reproducibility and scalability. Moreover, mitigating adverse Rb-photonics interactions is essential, particularly as devices become more compact and the alkali source lies in close proximity to the photonic elements. Here, we demonstrate the successful operation of compact and fully integrated devices that combine silicon nitride photonic integrated
circuits (PICs) with microfabricated borosilicate vapor
cells and pill-type rubidium (Rb) dispensers through hermetic seals via anodic bonding. We show how successful operation hinges on optically activating the dispenser in a low-power pulsed mode, releasing controlled amounts of Rb vapor on demand while mitigating photonic degradation. Simultaneously, a counter-propagating desorption
laser completely suppresses Rb-induced losses and enables waveguide-based atomic vapor spectroscopy. Using this approach, we demonstrate repeatable control of vapor density by tuning activation pulse length, duty cycle, and device temperature. These results establish a compact, manufacturable, and scalable vapor-PIC device, and set the stage for future demonstrations in cavity
quantum electrodynamics,
quantum nonlinear optics, and chip-scale atomic sensors.
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All authors Rahul Shrestha, Khoi Tuan Hoang, Peter Riley, Roy Zektzer, Daron Westly, Paul Lett, Matthew T. Hummon, Kartik Srinivasan
Physics and Society
European coastal wetlands datasets and their use in decision-support tools for policy restoration objectives
Bruna R.F. Oliveira, Antonio Camacho, Anis Guelmami et al. (+22 more)
Ecosystem restoration is a paramount policy priority for this decade, with ambitious global and European targets requiring unprecedented levels of data-driven implementation. Achieving effective and equitable restoration, particularly for coastal wetlands, hinges on spatially explicit socio-ecological information maps that integrate habitats, ecosystem services, human activities, and pressures to guide prioritization, stakeholder negotiation, and adaptive management. This study introduces an innovative multi-layered
dataset that bridges science and policy for six emblematic European coastal wetlands. The
dataset consolidates ecological mapping (EUNIS 2021 and 2022) human activity and pressure documentation (aligned with EU Habitats Directive, Water Framework Directive, and Marine Strategy Framework Directive) comprehensive ecosystem services mapping (CICES) alongside robust participatory community and stakeholder data. By illustrating practical pathways for participatory engagement, trade-off negotiation, and cross-scale integration, this research equips scientists, policymakers, practitioners, and communities with the scientific foundation to propel the Nature Restoration Regulation and Biodiversity Strategy 2030 objectives, fortifying Europe
climate adaptation trajectory. The approach showcased signals a new era for restoration science, where spatially explicit, multi-actor data supports policy, mobilizes citizen stewardship, and accelerates the transformative ambitions of Europe restoration decade.
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All authors Bruna R.F. Oliveira, Antonio Camacho, Anis Guelmami, Christoph Schroder, Nina Bègue, Martynas Bučas, Constantin Cazacu, Elisa Ciravegna, João Pedro Coelho, Relu Giuca Constantin, Samuel Hilaire, Marija Kataržytė, Daniel Morant, Antonio Picazo, Nico Polman, Marinka van Puijenbroek, Justine Raoult, Carlos Rochera, Michaël Ronse, Lisa Sella, Ana I. Sousa, Tudor Racoviceanu, Francesca S. Rota, Diana Vaičiūtė, Ana I. Lillebø
Optics
Designing low-loss cavities across the band-gap of photonic crystal slabs
Nadhia Monim, Wolfgang Langbein and Francesco Masia
Photonic
crystal cavities (PCCs) are defects in host photonic
crystals (PCs) which create bound states in the PC band gap. These bound states are resonant states of the electromagnetic field with a complex resonance frequency and can have very small mode volumes. PCCs are attractive for a variety of applications, from cavity
quantum electrodynamics to biosensing. A PC slab geometry is advantageous given its superior manufacturability compared to three-dimensional
crystals, and the accessibility of the surface allows sensing and coupling. However, the emission into the half spaces above and below the slab limits the bound state lifetime. Controlling this emission is thus crucial for applications, most of which benefiting from a long lifetime. A range of methods to find defect geometries suppressing the emission to increase the lifetime have been demonstrated in the past. However, they do not cater for a designed resonant frequency covering a wide addressable range, as needed for multiplexed devices. Here, we demonstrate a design method controlling both resonance frequency and emission, by minimising a cost function including both losses and target frequency. We show applications on PCCs in GaAs PC slabs immersed in water, relevant for biosensing. The reduced refractive index contrast in these structures compared to previously studied PCCs embedded in
vacuum renders the emission suppression more challenging. We optimize the quality factor of a standard L3 cavity from 1000 to 10^4-10^5, with an addressable resonance frequency range covering 12% relative bandwidth, spanning more than half of the band gap. We furthermore report optimised structures of H1 cavities, and provide the optimisation code for widespread use.
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Fluid Dynamics
Towards a Statistical Validation of the Critical Wave Groups Method for Free-Running Vessels in Beam Seas
Kevin M. Silva and Kevin J. Maki
Research on the statistics of extreme events using deterministic wave group methods has largely been simplified to vessels at zero or constant speed and heading. In contrast, free-running vessels move with six degrees-of-freedom (6-DoF), leading to more complex and varied extreme response events. This paper details the extension of the Critical Wave Groups (CWG) method to free-running vessels and demonstrates that the method produces probability calculations comparable to those from a limited Monte Carlo
dataset for a vessel in beam seas. This research is a critical first step in the formal validation of this free-running implementation of the CWG method.
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Optics
Power-Scalable Generation of High-Order Optical Vortices Via Coherent Beam Combining
Hossein Fathi, Rafael F. Barros and Regina Gumenyuk
Structured light beams, such as optical
vortices carrying orbital angular momentum, are essential for applications ranging from low-power optical communications to high-intensity
laser-matter interactions. However, scaling their power and energy while preserving complex phase and spatial structures remains a fundamental challenge. In this work, we demonstrate coherent beam combining as a versatile and scalable method for generating high-power structured beams without limitations on topological charge or spatial structure, while maintaining exceptionally high modal purity. We experimentally implement coherent beam combining for optical
vortex beams with topological charges l = 1, 5, and 8, achieving a combined average power of 100 W and a peak power of 100 kW, with combining efficiencies of 95.0%, 93.9%, and 91.2%, respectively. Off-axis digital holography confirms that the phase and intensity profiles of the combined beams retain high modal purity, even at high topological charges. These results establish coherent beam combining as an effective route to high modal purity structured light at high power levels, unlocking new opportunities for advanced photonics and high-intensity light-matter interaction studies.
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Computational Physics · Cross-listed from cs.LG
Reduced Order Modeling for Tsunami Forecasting with Bayesian Hierarchical Pooling
Shane X. Coffing, John Tipton, Arvind T. Mohan et al. (+1 more)
Reduced-order models (ROMs) can represent spatiotemporal processes in significantly fewer dimensions and can often be solved many orders of magnitude faster than their governing partial differential equations (PDEs). For example, proper orthogonal decomposition yields a ROM in which the state is represented as a low-dimensional linear combination of fixed spatial modes and time-dependent coefficients, but this representation remains constrained by the process used to construct the basis. In this work, we explore a new type of ROM that is not restricted to a single fixed coefficient trajectory. Specifically, we consider a corrected Galerkin-projection ROM, formulated as an initial value problem that encodes the physics of the governing PDEs and is calibrated through operator corrections to more accurately reproduce the coefficient dynamics. By combining this corrected reduced model with a
Bayesian hierarchical pooling framework over the initial reduced coefficients, we obtain new, statistically interpretable and physically grounded coefficient trajectories that generalize across related scenarios. When recombined with the spatial modes, these trajectories define a complete probabilistic physics surrogate, called a randPROM, for generating simulations that are distributionally consistent with a neighborhood of initial conditions near those used to construct the ROM. We apply the randPROM framework to tsunami modeling, a setting involving unpredictable, catastrophic, and strongly nonlinear dynamics, using both a synthetic case study near Fiji and the real-world 2011 Tohoku tsunami. We demonstrate that randPROMs can substantially reduce the number of full simulations required while providing statistically calibrated and physically defensible predictions of tsunami wave arrival times and heights.
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All authors Shane X. Coffing, John Tipton, Arvind T. Mohan, Darren Engwirda
Applied Physics · Cross-listed from quant-ph
High-efficiency loading of 2,400 Ytterbium atoms in optical tweezer arrays
Jiawen Zhu, Changfeng Chen, Li Zhou et al. (+10 more)
Neutral atom arrays have emerged as a powerful platform for
quantum computation, simulation, and metrology.Among them, alkaline-earth-like atoms exhibit distinct advantages, including long coherence time, high-fidelity Rydberg gates, and erasure correction for efficient
quantum error correction. However, their scalability has lagged behind that of the alkali atoms. Here, we report 2400 ytterbium-174 atoms trapped in an optical tweezer array with enhanced loading efficiency of 83.5(1)% via blue-detuned light-assisted collisions. We develop a quantitative model of the collision dynamics and find good agreement between the calculated inelastic collision rates and the experimentally measured loading efficiencies.Notably, the loading efficiency is largely maintained for array sizes ranging from dozens to thousands, exhibiting excellent scalability. We further demonstrate that the enhancement exists robustly across a range of interatomic potentials, suggesting its utility for other atomic species. To establish the capability of the $^{174}$Yb arrays toward universal
quantum computation, we propose to encode the
qubit in the ground-clock state
manifold and estimate a 99.9% two-
qubit gate fidelity with experimentally feasible parameters. Our work advances the prospects for realizing large-scale
quantum computers using alkaline-earth-like atoms.
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All authors Jiawen Zhu, Changfeng Chen, Li Zhou, Xiangru Xie, Chenyang Jiang, Zhuoli Ding, Fan Wu, Fan Yang, Guoqing Wang, Qihuang Gong, Peng Zhang, Sheng Zhang, Pai Peng
History and Philosophy of Physics · Cross-listed from quant-ph
Subsystem entanglement and separability in quantum reference frames
T. Rick Perche, Natália Salomé Móller and Guilherme Franzmann
We find a necessary condition for subsystems to become entangled after a
quantum reference frame transformation. We then distinguish between subsystems that admit separable descriptions relative to a
quantum reference frame, and those that do not. On the one hand, we show that separable descriptions maximize the
entanglement internal to the subsystem, and relate our results with the conservation of
entanglement and coherence under
quantum reference frame transformations. On the other hand, systems that do not admit a separable description relative to any subsystem display a form of
entanglement that is genuine to the
quantum reference frame formalism.
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Atomic Physics · Cross-listed from quant-ph
Theory of Scalable Spin Squeezing with Disordered Quantum Dipoles
Avi Kaplan-Lipkin, Philip J. D. Crowley, Jonathan N. Hallén et al. (+6 more)
Spin squeezed
entanglement enables metrological precision beyond the classical limit. Understood through the lens of continuous
symmetry breaking, dipolar
spin systems exhibit the remarkable ability to generate
spin squeezing via their intrinsic quench dynamics. To date, this understanding has primarily focused on
lattice spin systems; in practice however, dipolar
spin systems$\unicode{x2014}$ranging from ultracold molecules to
nuclear spin ensembles and solid-state color centers$\unicode{x2014}$often exhibit significant amounts of positional disorder. Here, we develop a theory for scalable
spin squeezing in a two-dimensional randomly diluted
lattice of
quantum dipoles, which naturally realize a dipolar XXZ model. Via extensive
quantum Monte Carlo simulations, we map out the phase diagram for finite-temperature XY order, and by extension scalable
spin squeezing, as a function of both disorder and Ising anisotropy. As the disorder increases, we find that scalable
spin squeezing survives only near the Heisenberg point. We show that this behavior is due to the presence of rare tightly-coupled dimers, which effectively heat the system post-quench. In the case of strongly-interacting nitrogen-vacancy centers in diamond, we demonstrate that an experimentally feasible strategy to decouple the problematic dimers from the dynamics is sufficient to enable scalable
spin squeezing.
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All authors Avi Kaplan-Lipkin, Philip J. D. Crowley, Jonathan N. Hallén, Zilin Wang, Weijie Wu, Sabrina Chern, Chris R. Laumann, Lode Pollet, Norman Y. Yao
Chemical Physics
Validation of Quantum Computing for Transition Metal Oxide-based Automotive Catalysis
Yuntao Gu, Louis Hector Jr, Paolo Giusto et al. (+4 more)
Quantum computing presents a promising alternative to classical computational methods for modeling strongly correlated materials with partially filled d orbitals. In this study, we perform a comprehensive
quantum resource estimation using
quantum phase estimation (QPE) and qubitization techniques for transition metal
oxide molecules and a Pd zeolite catalyst fragment. Using the binary
oxide molecules TiO, MnO, and FeO, we validate our active space selection and benchmarking methodology, employing classical multireference methods such as complete active space self-consistent field (CASSCF) and N-electron valence state perturbation theory (NEVPT2). We then apply these methods to estimate the
quantum resources required for a full-scale
quantum simulation of a $Z_2Pd$ ($Z=Al_2Si_{22}O_{48}$) fragment taken from the $Pd/2(Al_xSi_{(1-x)})$ catalyst family where x=Si/Al. Our analysis demonstrates that for large Pd zeolite systems, simulations achieving chemical accuracy would require ~$10^6-10^7$ physical
qubits, and range that is consistent with the projected capabilities of future fault-tolerant
quantum devices. We further explore the impact of active space size, basis set quality, and phase estimation error on the required
qubit and gate counts. These findings provide a roadmap for near-term and future
quantum simulations of industrially relevant catalytic materials, offering insights into the feasibility and scaling of
quantum chemistry applications in materials science.
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All authors Yuntao Gu, Louis Hector Jr, Paolo Giusto, Matthew Titsworth, Alok Warey, Dnyanesh Rajpathak, Eser Atesoglu
Chemical Physics
Rapid reduction of nitrophenols using reusable magnetic h-BN/Ni–NiO nanocomposites
Anjali Varshney, Ritesh Dubey, Sushil Kumar et al. (+2 more)
The efficient and cost-effective conversion of nitro compounds to amines is crucial for industrial processes and environmental remediation, highlighting the growing demand for earth-abundant metal-based catalysts. In this study,
magnetic Ni–NiO nanostructures and their composites with two-dimensional hexagonal boron nitride (h-BN) were synthesized via a simple and scalable combustion method. The structural, morphological, and compositional properties of the synthesized materials were systematically investigated using powder X-ray diffraction (PXRD), scanning electron microscopy (SEM), transmission electron microscopy (TEM), X-ray photoelectron spectroscopy (XPS), and UV–Vis spectroscopy. The catalytic activity of both Ni–NiO and h-BN/Ni–NiO nanostructures was evaluated using nitrophenol reduction as a model reaction. The h-BN/Ni–NiO nanocomposite exhibited significantly enhanced catalytic performance compared to pristine Ni–NiO, highlighting the synergistic interaction between h-BN and Ni–NiO nanoparticles. Notably, the
magnetic nature of the Ni–NiO core enabled facile recovery of the catalyst using an external
magnetic field, and the composite demonstrated excellent stability and reusability for up to six catalytic cycles with minimal loss of activity. The combination of high catalytic efficiency,
magnetic separability, and structural stability positions the h-BN/Ni–NiO nanocomposite as a promising candidate for green and sustainable catalytic applications, particularly in environmental remediation.
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All authors Anjali Varshney, Ritesh Dubey, Sushil Kumar, Tapas Goswami, Samar Layek
Chemical Physics
Phantom LAM and LLI: Resistance and Hysteresis Bias in Voltage-Curve Degradation Mode Analysis
Mohammed Asheruddin N, Matheus Leal De Souza, Thomas Holland et al. (+3 more)
Degradation mode analysis (DMA) is widely used to decompose capacity fade into loss of lithium inventory (LLI) and loss of active material (LAM) from low-rate voltage-capacity data. Yet the measured trace is a pseudo-OCV (pOCV) that includes two non-degradation contributions: an SOC-dependent ohmic drop and intrinsic charge-discharge hysteresis, especially in graphite–silicon
oxide (C/SiOx) negative electrodes. We show these can dominate attribution and generate Phantom LAM/LLI –apparent material loss created by curve registration, branch choice and voltage-windowing rather than true degradation. Using two commercial 21700
cells (LG M50T: higher resistance; Molicel P45B: lower resistance), we extract an SOC-dependent instantaneous resistance $R_\Omega(\mathrm{SOC})$ from the first $\sim$50,ms pulse step and apply an IR correction to pOCV before fitting. In LG M50T, IR correction lifts the low-rate discharge pOCV by $+13$–$27$,mV with ageing; without it, PE-LAM is increasingly under-diagnosed (to $-8.80%$ relative error at late life) and LLI is suppressed (median $-3.07%$), with compensating inflation of apparent graphite loss. In P45B, on a branch-fair $3.0$–$4.2$,V window, end-of-life charge-branch DMA reports higher PE-LAM ($+3.42$,pp) and LLI ($+5.36$,pp), while the discharge branch recovers larger Si-LAM (discharge–charge difference to $+14.38$,pp). Raising the lower cutoff ($2.5$–$4.2 \rightarrow 3.0$–$4.2$,V) further under-reports Si-LAM by $13.61$,pp by removing the Si-sensitive low-voltage tail. We propose a practical protocol: correct only the instantaneous ohmic term, harmonize the voltage window, and base quantitative attribution on the discharge branch, treating anomalous/negative component LAMs on charge as allocation artefacts rather than recovery.
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All authors Mohammed Asheruddin N, Matheus Leal De Souza, Thomas Holland, Catherine Folkson, Gregory Offer, Monica Marinescu
Classical Physics
A Dynamical-Time Framework for the Dynamics of Charged Particles
Zui Oporto and Gonzalo Marcelo Ramírez-Ávila
We present a dynamical framework for modeling the motion of point-like charged particles, with or without mass, in general external electromagnetic fields. A key feature of this formulation is the treatment of time coordinate as a dynamical variable. The framework applies to the relativistic regime while consistently admitting a nonrelativistic limit. We also introduce a representation of particle trajectories in velocity space, which provides clear insight into the nature and asymptotic behavior of the dynamics. As an application, we compare the motion of massive and massless particles in a constant electromagnetic field and find that, for identical field configurations, their asymptotic behavior is independent of both mass and initial conditions. Finally, we explore the computational advantages of the dynamical-time formulation over the conventional uniform-time approach in two case studies: a uniform electromagnetic field, and an elliptically polarized wave propagating along a uniform
magnetic field. In both scenarios, the proposed scheme exhibits improvements in accuracy and computational efficiency.
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Computational Physics · Cross-listed from cond-mat.str-el
2D coherent spectroscopy signatures of exciton condensation in Ta$_2$NiSe$_5$
Jiyu Chen, Jernej Mravlje, Denis Golež et al. (+1 more)
We show that the nonlinear optical response probed by two-dimensional coherent spectroscopy (2DCS) can discriminate between excitonic and
lattice driven order. In the excitonic regime of a realistic model of Ta$_2$NiSe$_5$, the third order 2DCS signals are strongly enhanced by the condensate's amplitude and phase modes, with negligible contributions from single-particle excitations. In the linear optical response, in contrast, single-particle and collective-mode contributions overlap. With increasing electron-
phonon coupling, the amplitude mode contribution to 2DCS initially remains robust, but then drops rapidly and remains small in the
phonon-dominated regime – even in systems with large order parameter. 2DCS also aids the detection of the massive relative phase mode, which is analogous to the Leggett mode in
superconductors. Our analysis, based on the time-dependent Hartree-Fock approach, demonstrates that 2DCS can track the emergence of the
symmetry-broken state and the crossover from Coulomb-driven to
phonon-driven order.
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All authors Jiyu Chen, Jernej Mravlje, Denis Golež, Philipp Werner
Computational Physics · Cross-listed from quant-ph
Partition Function Estimation Using Analog Quantum Processors
Thinh Le and Elijah Pelofske
We evaluate using programmable superconducting flux
qubit D-Wave
quantum annealers to approximate the partition function of Ising models. We propose the use of two distinct
quantum annealer sampling methods: chains of Monte Carlo-like reverse
quantum anneals, and standard linear-ramp
quantum annealing. The control parameters used to attenuate the quality of the simulations are the effective analog energy scale of the J coupling, the total annealing time, and for the case of reverse annealing the anneal-pause. The core estimation technique is to sample across the energy spectrum of the classical
Hamiltonian of interest, and therefore obtain a density of states estimate for each energy level, which in turn can be used to compute an estimate of the partition function with some sampling error. This estimation technique is powerful because once the distribution is sampled it allows thermodynamic quantity computation at arbitrary temperatures. On a $25$
spin $\pm J$ hardware graph native Ising model we find parameter regimes of the D-Wave processors that provide comparable result quality to two standard classical Monte Carlo methods, Multiple Histogram Reweighting and Wang-Landau. Remarkably, we find that fast quench-like anneals can quickly generate ensemble distributions that are very good estimates of the true partition function of the classical Ising model; on a Pegasus graph-structured QPU we report a logarithmic relative error of $7.6 \times 10^{-6}$, from $171,000$ samples generated using $0.2$ seconds of QPU time with an anneal time of $8$ nanoseconds per sample which is interestingly within the closed system dynamics timescale of the superconducting
qubits.
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Medical Physics · Cross-listed from cs.CV
Efficient Vision Mamba for MRI Super-Resolution via Hybrid Selective Scanning
Mojtaba Safari, Shansong Wang, Vanessa L Wildman et al. (+10 more)
Background: High-resolution MRI is critical for diagnosis, but long acquisition times limit clinical use. Super-resolution (SR) can enhance resolution post-scan, yet existing deep learning methods face fidelity-efficiency trade-offs. Purpose: To develop a computationally efficient and accurate deep learning framework for MRI SR that preserves anatomical detail for clinical integration. Materials and Methods: We propose a novel SR framework combining multi-head selective state-space models (MHSSM) with a lightweight channel MLP. The model uses 2D patch extraction with hybrid scanning to capture long-range dependencies. Each MambaFormer block integrates MHSSM, depthwise convolutions, and gated channel mixing. Evaluation used 7T
brain T1 MP2RAGE maps (n=142) and 1.5T prostate T2w MRI (n=334). Comparisons included Bicubic interpolation, GANs (CycleGAN, Pix2pix, SPSR),
transformers (SwinIR), Mamba (MambaIR), and
diffusion models (I2SB, Res-SRDiff). Results: Our model achieved superior performance with exceptional efficiency. For 7T
brain data: SSIM=0.951+-0.021, PSNR=26.90+-1.41 dB, LPIPS=0.076+-0.022, GMSD=0.083+-0.017, significantly outperforming all baselines (p<0.001). For prostate data: SSIM=0.770+-0.049, PSNR=27.15+-2.19 dB, LPIPS=0.190+-0.095, GMSD=0.087+-0.013. The framework used only 0.9M parameters and 57 GFLOPs, reducing parameters by 99.8% and computation by 97.5% versus Res-SRDiff, while outperforming SwinIR and MambaIR in accuracy and efficiency. Conclusion: The proposed framework provides an efficient, accurate MRI SR solution, delivering enhanced anatomical detail across
datasets. Its low computational demand and state-of-the-art performance show strong potential for clinical translation.
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All authors Mojtaba Safari, Shansong Wang, Vanessa L Wildman, Mingzhe Hu, Zach Eidex, Chih-Wei Chang, Erik H Middlebrooks, Richard L.J Qiu, Pretesh Patel, Ashesh B. Jani, Hui Mao, Zhen Tian, Xiaofeng Yang
Instrumentation and Detectors
Picosecond laser test unit for photosensor characterization at ambient and low temperatures
Matthias Raphael Stock, Hans Th. J. Steiger, Ulrike Fahrendholz et al. (+2 more)
Accurate single photoelectron (SPE) characterization of photosensors is essential for controlling systematic uncertainties in low-light
neutrino and dark matter detectors. We present a compact laboratory setup for the characterization of photosensors under controlled, low-light conditions. Specifically, we demonstrate its use with photomultiplier tubes (PMTs) operated at the SPE-level, using picosecond
laser pulses and waveform digitization to determine key PMT properties. Measurements as a function of supply voltage and temperature ($-50^\circ$C to $+20^\circ$C) are performed on ET Enterprises 9821(Q)B tubes and a Hamamatsu R9980 assembly, which show exponential gain-voltage behavior and device-to-device variation. Cooling increases the gain by $\sim 0.1\,\%/^\circ$C, while the transit time spread (TTS) and peak-to-valley ratio (P/V) exhibit no clear temperature dependence. TTS decreases with voltage. Late pulses remain at the percent level and prepulses at the sub-percent level. Cable length affects both apparent gain and TTS. A model-independent, data-driven self-convolution method is introduced to quantify double photoelectron contributions from pulse charge spectra. The procedures provide a reproducible, practice-oriented reference for SPE-level PMT characterization and can be extended to other photosensor types.
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All authors Matthias Raphael Stock, Hans Th. J. Steiger, Ulrike Fahrendholz, Luca Schweizer, Lothar Oberauer
Optics · Cross-listed from quant-ph
Quantum Imaging of Birefringent Samples using Hong-Ou-Mandel Interference
Carolina Gonçalves, Tiago D. Ferreira, Catarina S. Monteiro et al. (+1 more)
Two-
photon interference in a Hong-Ou-Mandel (HOM) interferometer can be used as a
quantum sensing mechanism due to the sensitivity of the interference dip to perturbations of the
photon indistinguishability. In particular, recent works have generalized this concept to microscopy setups, but the sensitivity to optical path differences constrains its application to samples with thickness variation typically below a few micrometers if tracking changes in the coincidences at a fixed delay. Extending the concept to polarization microscopy and circumventing this limitation, this manuscript explores the use of a narrowband
photon pair source with coherence length >1 mm to broaden the HOM dip. Thus, realistic sample-thickness variations introduce negligible temporal distinguishability, and changes in coincidence rate at the dip centre are then dominated by sample-induced polarization effects. To compute the polarization rotation, we develop a statistical model for the interferometer, derive the Fisher information, and establish a maximum-likelihood
estimator for the local fast-axis angle. Recording dip and baseline frames at each sample position via raster scanning, the experimental results validate the framework, agreeing with classical polarized-intensity images while demonstrating operation at a maximum-precision regime and insensitiveness to layer thickness. Overall, the approach enclosed provides a
quantum-based quantitative imaging of birefringent structures, which can motivate further advantageous applications, including enhanced signal-to-noise ratio and lower damage imaging of photosensitive samples.
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All authors Carolina Gonçalves, Tiago D. Ferreira, Catarina S. Monteiro, Nuno A. Silva
Computational Physics · Cross-listed from cond-mat.supr-con
Influence of Magnetic Order on Proximity-Induced Superconductivity in Mn Layers on Nb(110) from First Principles
Sohair ElMeligy, Balázs Újfalussy and Kyungwha Park
We investigate the influence of
magnetic order on the proximity-induced superconducting state in the Mn layers of a Mn-Nb(110)
heterostructure by using a first-principles method. For this study, we use the recently developed Bogoliubov-de Gennes (BdG) solver for superconducting
heterostructures [Csire et al., Phys. Rev. B 97, 024514 (2018)] within the first-principles calculations based on multiple scattering theory and the screened Korringa-Kohn-Rostoker (SKKR) Green's function method. In our calculations, we first study the normal-state density of states (DOS) in the single- and double-Mn-layer
heterostructures, and calculate the induced
magnetic moments in the Nb layers. Next, we compute the momentum-resolved spectral functions in the superconducting state for the
heterostructure with a single Mn layer, and find bands crossing the
Fermi level within the superconducting (SC) gap. We also study the SC state DOS in the single- and double-Mn-layer
heterostructures and compare some of our results with experimental findings, revealing secondary gaps, plateau-like regions, and central V-shaped in-gap states within the bulk SC Nb gap that are
magnetic-order-dependent. Finally, we compute the singlet and internally antisymmetric triplet (IAT) order parameters for each layer for both
heterostructures, and find an order of magnitude difference in the induced singlet part of the SC order parameter in the Mn layer/s between the FM and AFM cases in favor of the AFM pairing with the maximum still being only 4.44% of the bulk Nb singlet order parameter value. We also find a negligible induced triplet part, yet comparable to the induced singlet values, indicating some singlet-triplet mixing in the Mn layer/s.
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Biological Physics · Cross-listed from nlin.AO
Topological Flux on a Context Manifold Generates Nonreciprocal Collective Dynamics
Jyotiranjan Beuria and Venkatesh H. Chembrolu
Non-reciprocal interactions, where the influence of
agent $i$ on $j$ differs from that of $j$ on $i$, are fundamental in active and living matter. Yet, most models implement such asymmetry phenomenologically. Here we show that non-reciprocity can emerge from internal
topology alone.
Agents evolve on an internal “context
manifold” coupled to a Chern-Simons gauge field. Because the gauge field is first order in time, it relaxes rapidly; eliminating it yields an effective transverse, antisymmetric interaction kernel that generically produces
chiral waves, persistent vorticity, and irreversible state transitions. Numerical simulations reveal clear signatures of broken reciprocity: long-lived
vortex cores, finite circulation, asymmetric information flow, and a nonzero reciprocity residual. The dynamics further exhibit pronounced hysteresis under parameter sweeps, demonstrating
memory effects that cannot occur in reciprocal or potential-driven systems. These results identify Chern-Simons gauge fields as a minimal and universal source of directional influence and robust non-reciprocal collective behavior.
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Medical Physics · Cross-listed from eess.IV
Patlak Parametric Image Estimation from Dynamic PET Using Diffusion Model Prior
Ziqian Huang, Boxiao Yu, Siqi Li et al. (+5 more)
Dynamic PET enables the quantitative estimation of physiology-related parameters and is widely utilized in research and increasingly adopted in clinical settings. Parametric imaging in dynamic PET requires kinetic modeling to estimate voxel-wise physiological parameters based on specific kinetic models. However, parametric images estimated through kinetic model fitting often suffer from low image quality due to the inherently ill-posed nature of the fitting process and the limited counts resulting from non-continuous data acquisition across multiple bed positions in whole-body PET. In this work, we proposed a
diffusion model-based kinetic modeling framework for parametric image estimation, using the Patlak model as an example. The score function of the
diffusion model was pre-trained on static total-body PET images and served as a prior for both Patlak slope and intercept images by leveraging their patch-wise similarity. During inference, the kinetic model was incorporated as a data-consistency constraint to guide the parametric image estimation. The proposed framework was evaluated on total-body dynamic PET
datasets with different dose levels, demonstrating the feasibility and promising performance of the proposed framework in improving parametric image quality.
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All authors Ziqian Huang, Boxiao Yu, Siqi Li, Savas Ozdemir, Sangjin Bae, Jae Sung Lee, Guobao Wang, Kuang Gong
Applied Physics
Transient Vibroacoustic Control of a Shock-Loaded Inter-Connected Cylindrical Double Shell
Rahim Vesal, Seyyed Mohammad Hasheminejad and Hervé Lissek
Double-wall cylindrical shells are widely used in applications where resistance to acoustic shock loading is critical. While the transient vibroacoustic behavior of single-walled shells has been extensively investigated, extending these analyses to double-wall cylindrical configurations introduces increased complexity due to multiple inter-shell acoustic reflections and strong coupling between acoustic fields and structural vibrations. These structures often feature mechanical interconnections between the shells to ensure structural integrity, load sharing,
alignment, and enhanced resilience against static and dynamic loads. These links introduce additional pathways for vibration transmission and significantly influence the overall behavior of the system, thus making the analytical description of the coupled vibroacoustic response even more challenging. This study investigates the transient vibroacoustics of an inter-connected double-wall cylindrical shell subjected to an acoustic shock, considering fully coupled fluid-structure interactions. A comprehensive two-dimensional acoustoelastic model is developed in polar coordinates, incorporating the surrounding medium, the fluid occupying the inter-shell gap, and the fluid inside the inner shell. A semi-analytical solution method is employed to capture the time-domain
evolution of acoustic fields and shell vibrations. The model's accuracy is verified by benchmarking against available data reported in the literature. Leveraging the passive dynamics of the system, we present a hybrid mechanism that integrates optimized nonlinear vibration absorbers with piezoelectric actuators to control the vibroacoustic behavior. The results demonstrate the effectiveness of the proposed hybrid mechanism in mitigating shock-induced acoustic pressure waves and enhancing the structural resilience of the double-wall cylindrical shell.
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Computational Physics
Optimal Uncertainty Quantification under General Moment Constraints on Input Subdomains
Rong Jin and Xingsheng Sun
We present an optimal uncertainty quantification (OUQ) framework for systems whose uncertain inputs are characterized by truncated moment constraints defined over subdomains. Based on this partial information, rigorous optimal upper and lower bounds on the probability of failure (PoF) are derived over the admissible set of probability measures, providing a principled basis for system safety certification. We formulate the OUQ problem under general subdomain moment constraints and develop a high-performance computational framework to compute the optimal bounds. This approach transforms the original infinite-dimensional optimization problems into finite-dimensional unconstrained ones parameterized solely by free canonical moments. To address the prohibitive cost of PoF evaluation in high-dimensional settings, we incorporate inverse transform sampling (ITS), enabling efficient and accurate PoF estimation within the OUQ optimization. We also demonstrate that constraining inputs only by zeroth-order moments over subdomains yields a formulation equivalent to evidence theory. Three groups of numerical examples demonstrate the framework's effectiveness and scalability. Results show that increasing the number of subdomains or the moment order systematically tightens the bound interval. For high-dimensional problems, the ITS strategy reduces computational costs by up to two orders of magnitude while maintaining relative error below 1%. Furthermore, we identify regimes where optimal bounds are sensitive to subdomain partitioning or higher-order moments, guiding uncertainty reduction efforts for safety certification.
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Optics
Active Convolved Illumination with Deep Transfer Learning for Complex Beam Transmission through Atmospheric Turbulence
Adrian A. Moazzam, Anindya Ghoshroy, Breeanne Heusdens et al. (+2 more)
Atmospheric
turbulence imposes a fundamental limitation across a broad range of applications, including optical imaging, remote sensing, and free-space optical communication. Recent advances in adaptive optics, wavefront shaping, and machine learning, driven by synergistic progress in fundamental theories, optoelectronic hardware, and computational
algorithms, have demonstrated substantial potential in mitigating
turbulence-induced distortions. Recently, active convolved illumination (ACI) was proposed as a versatile and physics-driven technique for transmitting structured light beams with minimal distortion through highly challenging turbulent regimes. While distinct in its formulation, ACI shares conceptual similarities with other physics-driven distortion correction approaches and stands to benefit from complementary integration with data-driven deep learning (DL) models. Inspired by recent work coupling deep learning with traditional
turbulence mitigation strategies, the present work investigates the feasibility of integrating ACI with neural network-based methods. We outline a conceptual framework for coupling ACI with data-driven models and identify conditions under which learned representations can meaningfully support ACI's correlation-injection mechanism. As a representative example, we employ a convolutional neural network (CNN) together with a transfer-learning approach to examine how a learned model may operate in tandem with ACI. This exploratory study demonstrates feasible implementation pathways and establishes an early foundation for assessing the potential of future ACI-DL hybrid architectures, representing a step toward evaluating broader synergistic interactions between ACI and modern DL models.
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All authors Adrian A. Moazzam, Anindya Ghoshroy, Breeanne Heusdens, Durdu O. Guney, Roohollah Askari
Physics Education
Probability Conservation, Liouville Measure, and the Symplectic Origin of Hamiltonian Dynamics
Enmanuel Rodríguez-Brea and Melvin Arias
Liouville's
theorem – the preservation of phase-space volume – is often presented as a corollary of Hamilton's canonical equations. Here we adopt an ensemble-first viewpoint in which the starting point is local probability conservation on phase space. For a probability density $\rho$ on a $2N$-dimensional
symplectic manifold $(\mathcal{M},\omega)$, probability transport is expressed intrinsically with respect to the Liouville volume form $\Omega=\omega^N/N!$ through a continuity equation defined by the $\Omega$-divergence. For
Hamiltonian evolution, specified by $\iota_{X_H}\omega=\mathrm{d}H$, Cartan's identity implies $\mathcal{L}_{X_H}\omega=0$ and hence $\mathcal{L}_{X_H}\Omega=0$, so the
Hamiltonian flow is incompressible in the Liouville sense and the continuity law reduces to Liouville's equation. In canonical coordinates this reproduces Hamilton's equations. In particular, the canonical Poisson-bracket relations $\{q^i,p_j\}=\delta^i_{\ j}$ provide the kinematic input that fixes the
evolution of observables and underlies the canonical form of the continuity equation. The same organization clarifies the distinction between conservation of total probability and preservation of fine-grained information measures (Gibbs–Shannon
entropy), which holds specifically for Liouville-measure-preserving dynamics.
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Computational Physics · Cross-listed from cond-mat.mtrl-sci
Computational Design of Metal-Free Porphyrin Dyes for Sustainable Dye-Sensitized Solar Cells Informing Energy Informatics and Decision Support
Md Mahmudul Hasan, Chiara Bordin, Fairuz Islam et al. (+4 more)
This study aims to evaluate the optoelectronic properties of metal free porphyrin-based D-$\pi$-A dyes via in-silico performance investigation notifying energy informatics and decision support. To develop novel organic dyes, three acceptor/anchoring groups and five donating groups were introduced to strategic positions of the base porphyrin structure, resulting in a total of fifteen dyes. The singlet ground state geometries of the dyes were optimized utilizing density functional theory (DFT) with B3LYP and the excited state optical properties were explored through time-dependent DFT (TD-DFT) using the PCM model with tetrahydrofuran (THF) as solvent. Both DFT and TD-DFT calculations were carried out using the 6-311G(d,p) basis set. The HOMO energy levels of almost all the modified dyes are lower than the redox potential of I$^-$/I$3^-$ and LUMO energy levels are higher than the conduction band of TiO$2$. The absorption maxima values ranged from 690.64 to 975.55 nm. The dye N1 using triphenylamine group as donor and p-ethynylbenzoic acid group as acceptor, showed optimum optoelectronic properties ($\Delta G{reg}=-9.73$ eV, $\Delta G{inj}=7.18$ eV, $V_{OC}=1.47$ V and $J_{SC}=15.03$ mA/cm$^2$) with highest PCE 14.37%, making it the best studied dye. This newly modified organic dye with enhanced PCE is remarkably effective for the dye-sensitized
solar cells (DSSC) industry. Beyond materials discovery, this study highlights the role of high-performance computing in enabling predictive screening of dye candidates and generating performance indicators (HOMO-LUMO gaps, absorption spectra, charge transfer free energies, photovoltaic metrics). These outputs can serve as key parameters for energy informatics and system modelling.
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All authors Md Mahmudul Hasan, Chiara Bordin, Fairuz Islam, Tamanna Tasnim, Md. Athar Ishtiyaq, Md. Tasin Nur Rahim, Dhrubo Roy
Atmospheric and Oceanic Physics
Residential structure survivability to large wildfires in the United States
Mukesh Kumar, John T. Abatzoglou, Crystal A. Kolden et al. (+1 more)
Wildfire impacts on US communities have escalated in recent decades, highlighting the need to better understand factors that influence wildfire outcomes. We find that 567,000 homes were exposed to wildfires across the contiguous US during 2001-2020, two-thirds of which occurred and increased five-fold in the Western US. While residential structure survivability - the percent of structures within a wildfire perimeter that survive the fire - remained stable in the Eastern US in the past two decades, it declined by 10% in the West. Survivability was explained by structural age, surrounding fuels, and fire weather. Survivability was 87% for homes built pre-1990 compared to 92% for post-1990 homes in the West. Survivability was lowest in forests compared to grasslands and shrublands. Finally, survivability was markedly lower for fires coincident with extreme fire weather. Our results suggest that modern building codes, fuel management, and proactive planning can strengthen wildfire resilience.
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All authors Mukesh Kumar, John T. Abatzoglou, Crystal A. Kolden, Mojtaba Sadegh
Fluid Dynamics
Energy dissipation mechanisms in an acoustically-driven slit
Haocheng Yu, Tianyi Chu and Spencer H. Bryngelson
We quantify how incident acoustic energy is converted into vortical motion and viscous dissipation for a two-dimensional plane-wave passing through a slit geometry. We perform direct numerical simulations over a broad parameter space in incident sound pressure level (ISPL), Strouhal number (St), and Reynolds number (Re). Spectral proper orthogonal decomposition (SPOD) yields energy-ranked coherent structures at each frequency, from which we construct mode-by-mode fields for spectral kinetic energy (KE) and viscous loss (VL) components to examine the mechanisms of acoustic absorption. At ISPL=150dB, the acoustic-hydrodynamic energy conversion is highest when the acoustic displacement amplitude is comparable to the slit thickness, corresponding to a Keulegan-Carpenter number of order unity. In this regime, the oscillatory boundary layer undergoes periodic separation, resulting in
vortex shedding that dominates acoustic damping. VL accounts for 20-60% of the KE contribution. For higher acoustic frequencies, the confinement of the Stokes layer produces X-shaped near-slit modes, reducing the total energy input by approximately 50%. The influence of Re depends on amplitude. At ISPL=150dB, larger Re values correspond to suppressed broadband fluctuations and sharpened harmonic peaks. At ISPL = 120dB, the boundary layers remain attached,
vortex shedding is weak, absorption monotonically scales with viscosity, and the Re- and St-dependencies become comparable. Across all conditions, more than 99% of the VL is confined to a compact region surrounding the slit mouth. The KE-VL spectra describe parameter regimes that enhance or suppress acoustic damping in slit geometries, providing a physically interpretable basis for acoustic-based design.
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Accelerator Physics
A Collimation System Baseline Design for the Electron Storage Ring at the Electron-Ion Collider
Andrii Natochii, Elke-Caroline Aschenauer, Karim Hamdi et al. (+7 more)
We present the baseline design of the electron ring collimation system for the Electron-Ion
Collider (EIC) at Brookhaven National Laboratory (BNL). The system addresses beam losses in a high-current electron storage ring with superconducting (SC) final-focus magnets and sensitive detectors, where uncontrolled losses can generate heat loads, radiation, and detector backgrounds and damage. The proposed collimation insertion localizes
halo particle losses through reducing interaction region beam losses from beam-gas and Touschek scattering by several orders of magnitude while keeping detector backgrounds and cryostat heat loads within acceptable limits. Multi-turn particle tracking simulations show that the collimators do not significantly impact machine acceptance or beam lifetime, and their positions and apertures can be re-optimized for future
lattice configurations. Ongoing work includes incorporating crab cavities and solenoid fields into simulations, refining
vacuum conditions, and optimizing collimator geometry and materials. This design establishes a robust baseline for the EIC electron ring collimation system and supports continued
lattice optimization for machine operations.
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All authors Andrii Natochii, Elke-Caroline Aschenauer, Karim Hamdi, Charles Hetzel, Eric Link, Daniel Marx, Christoph Montag, Steven Tepikian, Yunhai Cai, Yuri Nosochkov