Fluid Dynamics
Hydroacoustic Attenuation and Amplification by Turbulence
Kai-Xin Hu and Yue-Jin Hu
Acoustic waves propagating through fluid media are significantly influenced by
turbulence. This paper experimentally investigates the influence of water
turbulence on the propagation characteristics of acoustic waves. It shows that acoustic waves can be obviously attenuated or amplified at frequencies far exceeding the turbulent fluctuation frequency, with no spectral broadening. The amplification factor depends on the wave frequency rather than its amplitude. The study covers two flow conditions: pipe flow and free jet, driven by either a pump or hydraulic head difference, while the wave propagation directions both parallel and perpendicular to the mean flow are considered.Turbulent fluctuations without mean motion can still alter the wave amplitude, while laminar flow has no effect on acoustic signals. Comparison with conventional theories and experiments indicates that mechanisms such as bubbles, resonance, scattering, multipath interference or viscous dissipation cannot explain the observed phenomena. This indicates that there exists an incompletely understood new mechanism in the interaction between
turbulence and acoustic waves.
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Fluid Dynamics · Cross-listed from cs.SE
CFD-copilot: leveraging domain-adapted large language model and model context protocol to enhance simulation automation
Zhehao Dong, Shanghai Du, Zhen Lu et al. (+1 more)
Configuring computational fluid dynamics (CFD) simulations requires significant expertise in physics modeling and numerical methods, posing a barrier to non-specialists. Although automating scientific tasks with large
language models (LLMs) has attracted
attention, applying them to the complete, end-to-end CFD workflow remains a challenge due to its stringent domain-specific requirements. We introduce CFD-copilot, a domain-specialized LLM framework designed to facilitate natural
language-driven CFD simulation from setup to post-processing. The framework employs a fine-tuned LLM to directly translate user descriptions into executable CFD setups. A multi-
agent system integrates the LLM with simulation execution, automatic error correction, and result analysis. For post-processing, the framework utilizes the model context protocol (MCP), an open standard that decouples LLM
reasoning from external tool execution. This modular design allows the LLM to interact with numerous specialized post-processing functions through a unified and scalable interface, improving the automation of data extraction and analysis. The framework was evaluated on
benchmarks including the NACA~0012 airfoil and the three-element 30P-30N airfoil. The results indicate that domain-specific adaptation and the incorporation of the MCP jointly enhance the reliability and efficiency of LLM-driven engineering workflows.
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All authors Zhehao Dong, Shanghai Du, Zhen Lu, Yue Yang
General Physics
Formal developments in curved momentum space: the quantum field theory roadmap
S.A. Franchino-Viñas
We advocate that the dual picture of spacetime noncommutativity , i.e. the existence of a curved momentum space, could be a way out to solve some of the open conceptual problems in the field, such as the basis dependence of observables. In this framework, we show how to build deformed Klein–Gordon and Dirac equations. In addition, we give an outlook of how one could define
quantum field theories, both free and interacting ones.
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Fluid Dynamics
Integral constraints on the linear instability of stratified flow with planar shear at an arbitrary angle to the vertical
Miguel A. C. Teixeira, Mohamed Foudad and Paul D. Williams
Integral constraints on the linear instability of stratified parallel flow with planar shear at an arbitrary angle to the vertical are derived using the analytical approach of Miles and Howard, for perturbations with 2D spatial structure, which are thought to be the most unstable. The general stability formulation reproduces the Miles-Howard stability criterion for vertical shear, but yields no stability condition for non-vertical shear, confirming expectations from earlier studies. This study also extends Howard's semicircle
theorem to non-vertical planar shear, and derives a new expression for the upper bound of the instability growth rate (extending that obtained by Howard), which is consistent with published numerical results.
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Chemical Physics
One-Body Properties and Their Perturbative Accuracy with Aufbau Suppressed Coupled Cluster Theory
Conor Bready, Harrison Tuckman and Eric Neuscamman
We derived and implemented the calculation of the one-body reduced density
matrix for Aufbau suppressed coupled cluster theory, from which excited state natural orbitals and one-body properties, like atomic populations and dipole moments, are obtained. We utilized the natural orbitals to refine the ASCC solution for simple valence and Rydberg systems, exploring the process of repeatedly solving the ASCC equations in successive natural orbital bases to achieve independence from the starting molecular orbitals. For dipole moments in small molecules where high-level comparison data is available, we find that the accuracy of ASCC essentially matches that of linear response and equation-of-motion coupled cluster as long as care is taken to preserve the response's perturbative completeness.
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Computational Physics · Cross-listed from nucl-th
Trapped Fermions Through Kolmogorov-Arnold Wavefunctions
Paulo F. Bedaque, Jacob Cigliano, Hersh Kumar et al. (+2 more)
We investigate a variational Monte Carlo framework for trapped one-dimensional mixture of
spin-$\frac{1}{2}$
fermions using Kolmogorov-Arnold networks (KANs) to construct universal neural-network wavefunction ansätze. The method can, in principle, achieve arbitrary accuracy, limited only by the Monte Carlo sampling and was checked against exact results at sub-percent precision. For attractive interactions, it captures pairing effects, and in the
impurity case it agrees with known results. We present a method of systematic transfer learning in the number of network parameters, allowing for efficient training for a target precision. We vastly increase the efficiency of the method by incorporating the short-distance behavior of the wavefunction into the ansätz without biasing the method.
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All authors Paulo F. Bedaque, Jacob Cigliano, Hersh Kumar, Srijit Paul, Suryansh Rajawat
Data Analysis and Statistics
Automating High Energy Physics Data Analysis with LLM-Powered Agents
Eli Gendreau-Distler, Joshua Ho, Dongwon Kim et al. (+3 more)
We present a proof-of-principle study demonstrating the use of large
language model (LLM)
agents to automate a representative high energy physics (HEP) analysis. Using the
Higgs boson diphoton cross-section measurement as a case study with ATLAS Open Data, we design a hybrid system that combines an LLM-based supervisor-coder
agent with the Snakemake workflow manager. In this architecture, the workflow manager enforces reproducibility and determinism, while the
agent autonomously generates, executes, and iteratively corrects analysis code in response to user instructions. We define quantitative evaluation metrics including success rate, error distribution, costs per specific task, and average number of API calls, to assess
agent performance across multi-stage workflows. To characterize variability across architectures, we
benchmark a representative selection of state-of-the-art LLMs spanning the Gemini and GPT-5 series, the Claude family, and leading open-weight models. While the workflow manager ensures deterministic execution of all analysis steps, the final outputs still show
stochastic variation. Although we set the temperature to zero, other sampling parameters (e.g., top-p, top-k) remained at their defaults, and some
reasoning-oriented models internally adjust these settings. Consequently, the models do not produce fully deterministic results. This study establishes the first LLM-
agent-driven automated data-analysis framework in HEP, enabling systematic benchmarking of model capabilities, stability, and limitations in real-world scientific computing environments. The baseline code used in this work is available at https://huggingface.co/HWresearch/LLM4HEP. This work was accepted as a poster at the Machine Learning and the Physical Sciences (ML4PS) workshop at NeurIPS 2025. The initial submission was made on August 30, 2025.
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All authors Eli Gendreau-Distler, Joshua Ho, Dongwon Kim, Luc Tomas Le Pottier, Haichen Wang, Chengxi Yang
Optics
Spatio-temporal equilibrium thermodynamics of guided optical waves at positive and negative temperatures
Lucas Zanaglia, Josselin Garnier, Claire Michel et al. (+5 more)
Optical thermalization has been recently studied in the 2D spatial
evolution of (quasi-)monochromatic light waves propagating in multimode waveguides. Here, we investigate the spatio-temporal
equilibrium properties of optical waves through the analysis of the (2+1)D Bose-Einstein thermal distribution and the corresponding classical Rayleigh-Jeans approximation. Numerical simulations of the nonlinear Schrödinger equation (NLSE) demonstrate relaxation toward the spatio-temporal Rayleigh-Jeans
equilibrium state, as described by the corresponding wave
turbulence kinetic equation. Remarkable adiabatic cooling phenomena stemming from the high-frequency tails of the Rayleigh-Jeans distribution are discussed and the consequent limitations of the classical approximation are highlighted. To overcome these issues, we make use of a
quantum version of the NLSE whose associated kinetic equation describes relaxation toward the spatio-temporal Bose-Einstein
equilibrium distribution. The analysis of thermodynamic properties reveals a strong dependence on the dispersion regime. In the anomalous dispersion regime, the system relaxes to positive-temperatures
equilibrium states: as the number of modes of the waveguide increases, the fundamental spatial mode becomes macroscopically populated, while its temporal spectrum undergoes significant narrowing, ultimately leading to complete (2+1)D spatio-temporal condensation in the thermodynamic limit. In the normal dispersion regime, the system evolves toward negative-temperature
equilibrium states characterized by an inverted spatial modal population. In this regime, we predict a phase transition to Bose-Einstein condensation at negative temperatures, which occurs by increasing the temperature above a negative critical value. Our work opens new avenues for future research and lay the groundwork for the development of spatiotemporal optical thermodynamics.
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All authors Lucas Zanaglia, Josselin Garnier, Claire Michel, Valérie Doya, Mario Ferraro, Stefan Wabnitz, Iacopo Carusotto, Antonio Picozzi
Optics
Widefield pump-probe microscopy with coherent background subtraction by angle-compensated temporal shearing
Matthew Sheinman, Mark Polkovnikov, Luke Saunders et al. (+9 more)
Pump-probe microscopy enables label-free imaging of structural and chemical features of samples. However, signals in pump-probe microscopy are typically small and often must be measured in the presence of large backgrounds. As a result, achieving measurements with a high signal-to-noise ratio is challenging, particularly when using sensors that are easily saturated, such as CMOS cameras. We present a method for enhancing signal-to-noise ratio while avoiding detector saturation. In this approach, temporally separated (sheared) reference and probe pulses transmit through a sample before and after the arrival of a pump pulse. The probe and reference pulses are then temporally recombined with opposing phases and nearly matched amplitudes, resulting in interferometric background subtraction. This recombining operation is performed by a novel common-path interferometer. Unlike previous techniques for temporal shearing, this interferometer demonstrates negligible phase and group delay dispersion with angle of incidence, allowing convenient widefield imaging. To our knowledge, this is the first common-path interferometer with such a property. We demonstrate the technique by measuring transient absorption signals in gold nanorod films with a signal-to-background ratio enhanced by over 100% and a signal-to-noise ratio enhanced by about 70%.
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All authors Matthew Sheinman, Mark Polkovnikov, Luke Saunders, Pajo Vujkovic-Cvijin, Shyamsunder Erramilli, Lawrence D. Ziegler, Koustav Kundu, Ramprasath Rajagopal, Bingying Zhao, Christopher McMahon, Mi K. Hong, Jerome Mertz
Optics · Cross-listed from quant-ph
Statistical properties of quantum jumps between macroscopic states of light: reading an operational coherence record
Th. K. Mavrogordatos
We propose an experimental apparatus to reveal the
quantum coherence manifested in downward
quantum jumps of amplitude bistability. The underlying coherent superposition of macroscopic
quantum states is translated into the statistical properties of the integrated charge deposited in the detector
circuit of a mode-matched heterodyne/homodyne detection scheme. At first, the dynamical
evolution of a signal transmitted from an auxiliary cavity is employed to pinpoint a macroscopic switching event in a bistable main cavity subject to direct photodetection. Once the decision is made on the occurrence of a downward switch, the main cavity mode is let to freely decay to the
vacuum, monitored to the production of an integrated charge. In the long-time limit, the charge distribution over an identical collection of pure states generated during the jumps converges to the Q function (heterodyne detection) or marginals of the Wigner function (homodyne detection) dictated by the phase of the local oscillator. When fluctuations over the ensemble step in, we connect the statistical properties of several switching events and the ensuing production of current records, to the cavity field correlations associated with the breakdown of
photon blockade.
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Applied Physics · Cross-listed from cond-mat.mes-hall
Temporal magnetic interfaces reveal damping-induced spin-wave amplification near the stripe-domain transition in ultrathin films with DMI
Krzysztof Sobucki and Pawel Gruszecki
Using micromagnetic simulations and analytical theory, we study temporal
magnetic interfaces in ultrathin CoFeB films with perpendicular
magnetic anisotropy and interfacial Dzyaloshinskii–Moriya interaction. We show that time refraction and reflection are governed by precession ellipticity, acting as a magnonic temporal impedance, while smooth field ramps suppress temporal reflections. Near the transition from a uniform state to stripe domains, the exceptional-point and critical fields delimit damping, slow-instability, and strong-instability regimes. In the slow-instability window, Gilbert damping counterintuitively drives
spin-wave growth with a rate proportional to the damping parameter. Micromagnetic simulations confirm that a temporal-slab protocol exploiting this regime achieves up to 175-fold frequency-preserving amplitude amplification without continuous power injection. Energy analysis indicates that the field ramp stores energy in the metastable uniform state below the stripe-domain transition, later released into growing
spin-wave excitations, consistent with the antimagnonic framework. These results establish temporal field modulation as a route to reconfigurable
spin-wave gain.
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Computational Physics
Conservative adaptive-precision interatomic potentials
David Immel, Ralf Drautz and Godehard Sutmann
Adaptive precision molecular dynamics simulations have developed along energy- and force-coupling approaches, which allow for a continuous transition between different particle descriptions or interaction potentials. Most approaches consider different (fixed) spatial regions, which control the transition between the descriptions and consequently avoid a consistent momentum-conserving
Hamiltonian description. We present here a new approach to fully integrate the coupling into a
Hamiltonian, therefore allowing for a conservative description, which, by design, guarantees both energy and momentum conservation. By coupling a fast EAM potential to a highly accurate ACE potential, we verify numerically the conservation properties and show that one can achieve - dependent on both the potential and the atomistic system - a speedup of one or two orders of magnitude compared to a pure ACE simulation.
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Chemical Physics
Mapping Still Matters: Coarse-Graining with Machine Learning Potentials
Franz Görlich and Julija Zavadlav
Coarse-grained (CG) modeling enables molecular simulations to reach time and length scales inaccessible to fully atomistic methods. For classical CG models, the choice of mapping, that is, how atoms are grouped into CG sites, is a major determinant of accuracy and transferability. At the same time, the emergence of machine learning potentials (MLPs) offers new opportunities to build CG models that can in principle learn the true potential of the mean force for any mapping. In this work, we systematically investigate how the choice of mapping influences the representations learned by equivariant MLPs by studying
liquid hexane, amino acids, and polyalanine. We find that when the length scales of bonded and nonbonded interactions overlap, unphysical bond permutations can occur. We also demonstrate that correctly encoding species and maintaining stereochemistry are crucial, as neglecting either introduces unphysical
symmetries. Our findings provide practical guidance for selecting CG mappings compatible with modern architectures and guide the development of transferable CG models.
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Plasma Physics
Collisional passing alpha energy transport in nearly quasisymmetric stellarators
Miguel Calvo-Carrera and Peter J. Catto
Recent advances in stellarator optimization have found nearly precise quasisymmetric configurations. These are expected to reduce the non-turbulent background
plasma transport to acceptable neoclassical levels while removing nearly all collisionless direct orbit losses of alpha particles. Yet, alpha particles under resonant conditions can be very sensitive to collisions, causing concerning energy losses and damaging
plasma facing components. For the passing alphas such resonances can happen near rational surfaces in the presence of helical error field departures from quasisymmetry that change the
magnetic field direction and magnitude. The cancellation between streaming motion and tangential drift of the alphas enhances the effective collision frequency, allowing the formation of a collisional boundary layer and giving rise to a perturbed distribution function. We develop an analytical model to illustrate and evaluate the resonant plateau transport this mechanism causes by formulating a drift kinetic treatment. The results indicate the associated energy losses can become significant in the vicinity of rational surfaces at values of q=m/n when error fields with poloidal and toroidal numbers m and n are present. In addition, we investigate the validity of the quasilinear approximation to the energy flux to show that it imposes a restriction on the error field amplitude that can be considered.
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Fluid Dynamics
Fold catastrophe in breaking waves
Francesco Fedele
We present a dynamical-systems perspective on wave breaking for ideal incompressible free-surface flows. By tracking the most energetic hotspot on the wave surface, we find that near breaking the surface slope m evolves on a fast timescale governed by the small parameter epsilon = (partial_z u)^(-1), the inverse vertical velocity gradient at the hotspot, while the focusing parameter A = (U - Ce)/(U - Creq) varies slowly and adiabatically. Here U is the horizontal fluid velocity at the energetic point, Ce its propagation speed, and Creq the equivalent crest speed. This slow-fast structure reveals a fold catastrophe in the (m, A) space whose boundary forms the
geometric skeleton organizing the dynamics near breaking. Finite-time blowup occurs when the trajectory crosses this boundary, marking the onset of breaking. The inception of breaking is further characterized by crossing the slope threshold theta* = arctan(sqrt(2) - 1) = 22.5 degrees. This critical angle marks the maximum anisotropy that can be sustained between the Hessians of the velocity and pressure fields, reflecting an imbalance between kinetic and potential energy fluxes. The anisotropy of the velocity Hessian also gives rise to the classical 30-degree slope observed at the inflection point of steep waves near breaking inception. The crest height is limited by the maximum excess of kinetic over potential energy that the flow can sustain, beyond which breaking becomes inevitable. Wave breaking can also be interpreted as a
gravity analogue of a collapsing black hole, with apparent and event horizons representing the onset and inception of breaking.
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Applied Physics
Optimization for growth condition of ultrathin hexagonal boron nitride on dielectric substrates via LPCVD
Meryem Bozkaya, Muhammet Nasuh Ar{\i}k, Ali Altuntepe et al. (+2 more)
Hexagonal Boron Nitride (h-BN) is a highly intriguing candidate for
heterostructure optoelectronic applications, such as Deep Ultraviolet photodetectors, UV sensing and communication systems and
solar cells. This is primarily due to its unique properties, including a layer dependent wide energy bandgap, superior mechanical strength, high thermal conductivity, high band-edge absorption coefficient, and exceptional transparency in the UV region. The widely adopted synthesis method for h-BN thin films is Chemical Vapor Deposition (CVD) Method, which often utilizes catalytic substrates like copper (Cu) and Nickel (Ni). However, integrating the synthesized h-BN into device applications requires a subsequent transfer process to the target substrate. This transfer step introduces significant material damage, such as folding, cracking and
polymer residues, which ultimately degrade the optoelectronic properties of the material and compromise device performance. To overcome this major challenge, there is a strong need to synthesize high-quality h-BN films directly onto dielectric substrates such as silicon (Si), SiO2, quartz, sapphire or AlN without the need for transfer. The primary difficulty in direct synthesis lies in achieving homogenous, high crystallinity films with controllable thickness due to the absence of a catalytic effect. In this work, we investigated the optimization of growth parameters for the direct synthesis of ultrathin h-BN films on non-catalytic quartz substrates, which are highly transparent in the UV region, using the Low-pressure Chemical Vapor Deposition (LPCVD) method. The optimal synthesis conditions were determined to be 1050oC for 60 min, achieved by the decomposition of 150 mg Ammonia Borane (AB) precursor at 80oC. This optimization is crucial for advancing large-scale, high-performance h-BN based DUV photodetector fabrication.
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All authors Meryem Bozkaya, Muhammet Nasuh Ar{\i}k, Ali Altuntepe, Hakan Ateş, Recep Zan
Applied Physics · Cross-listed from quant-ph
Enhanced charging power in nonreciprocal quantum battery by reservoir engineering
Qi-Yin Lin, Guang-Zheng Ye, Can Li et al. (+2 more)
We propose a scheme to achieve a nonreciprocal
quantum battery (QB) in the non-Hermitian (NH) system, which can overcome the intrinsic dissipation and reverse flow constraints. The design is based on a charger and a battery, which are coherently coupled and jointly interact with a bad cavity. By introducing the auxiliary bad cavity and exploiting the nonreciprocal condition, this model can harness the environmental dissipation to suppress the reverse energy transfer. Under resonant conditions, we have achieved a four ratio of the battery energy to the charger energy; in contrast, this ratio is significantly reduced under large detuning. Through damping optimization, high efficiency of the short-time charging power is attained. In comparison to the fully nonreciprocal scheme, the QB operating at the exceptional point (EP) exhibits greater resilience to parameter fluctuations. These findings highlight the potential of NH
quantum engineering for advancing QB technology, particularly in regimes involving directional energy transfer, controlled dissipation, and
entropy management in open
quantum systems.
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All authors Qi-Yin Lin, Guang-Zheng Ye, Can Li, Wan-Jun Su, Huai-Zhi Wu
Fluid Dynamics
Tensor Network Lattice Boltzmann Method for Data-Compressed Fluid Simulations
Lukas Gross, Elie Mounzer, David M. Wawrzyniak et al. (+2 more)
Resolving unsteady transport phenomena in geometrically complex domains is traditionally constrained by
polynomial scaling of computational cost with spatial resolution. While methods based on tensor-network data representations or
matrix-product states (MPS) data encodings have emerged as a technique to systematically reduce degrees of freedom, existing formulations do not extend to complex geometries and complex flow physics. Both capabilities are offered by
lattice Boltzmann methods, for which we develop a generalized MPS formulation. This development marks a paradigm shift from classical methods that rely on explicit grid refinement for data reduction. Instead, our approach exploits non-local correlations in the MPS representation to systemically compress the global fluid state directly without modifying the underlying grid. We
benchmark the proposed solver against classical LBM using three-dimensional flows through structured media and vascular geometries. The results confirm that the MPS formulation reproduces the reference solution with high fidelity while achieving compression ratios exceeding two orders of magnitude, positioning tensor networks or MPS encodings as a scalable paradigm for continuum mechanics on high-performance GPU hardware.
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All authors Lukas Gross, Elie Mounzer, David M. Wawrzyniak, Josef M. Winter, Nikolaus A. Adams
Plasma Physics
Efficient Simulation of Electron-Positron Pair Production in Foam Targets in the low \chi-Regime
Oliver Mathiak, Lars Reichwein and Alexander Pukhov
The generation of electron-positron pairs using direct
laser-accelerated electrons and a cone-shaped reflector target for the generation of strong electromagnetic fields is investigated using particle-in-
cell simulations. A newly implemented sub-sampling routine for the code vlpl is presented which allows for a better description of
quantum electrodynamical processes which would otherwise come at a high computational cost.
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Atomic Physics
Determination of nuclear quadrupole moments for $^{25}$Mg, $^{87}$Sr, and $^{135,137}$Ba via configuration-interaction combined with a coupled-cluster approach
Yong-Bo Tang
Using the configuration-interaction plus coupled-cluster approach, we calculate the electric-field gradients $q$ for the low-lying states of alkaline-earth atoms, including magnesium (Mg), strontium (Sr), and barium (Ba). These low-lying states specifically include the $3s3p~^3\!P_{1,2}$ states of Mg; the $5s4d~^1\!D_{2}$ and $5s5p~^3\!P_{1,2}$ states of Sr; as well as the $6s5d~^3\!D_{1,2,3}$, $6s5d~^1\!D_{2}$, and $6s6p~^1\!P_{1}$ states of Ba. By combining the measured electric quadrupole hyperfine-structure constants of these states, we accurately determine the
nuclear quadrupole moments of $^{25}$Mg, $^{87}$Sr, and $^{135,137}$Ba. These results are compared with the available data. The comparison shows that our
nuclear quadrupole moment of $^{25}$Mg is in perfect agreement with the result from the mesonic X-ray experiment. However, there are approximately 10% and 4% differences between our results and the currently adopted values [Pyykk$\rm \ddot{o}$, Mol. Phys. 116, 1328(2018)] for the
nuclear quadrupole moments of $^{87}$Sr and $^{135,137}$Ba respectively. Moreover, we also calculate the
magnetic dipole hyperfine-structure constants of these states, and the calculated results exhibit good agreement with the measured data.
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Chemical Physics · Cross-listed from cond-mat.mtrl-sci
Mid-infrared intraband transitions in InAs colloidal quantum dots
Shraman Kumar Saha and Philippe Guyot-Sionnest
III-V colloidal
quantum dots are widely studied for their applications as detectors and emitters from visible to short-wave infrared. They might also be used in the mid-infrared if they can be stably n-doped to access their intraband transitions. Mid-infrared intraband transitions are therefore studied for InAs, InAs/InP, and InAs/ZnSe colloidal
quantum dots with an energy gap at 1.4 micron. Using electrochemistry, the
quantum dot films show state-resolved mobility, state-resolved electron filling, and intraband absorption in the 3-8 micron range. The InAs/ZnSe films need a more reducing potential than InAs, but the InAs/InP films need a lower reduction potential. As a result, we found that dry films of InAs/InP dots show stable n-doping of the 1Se state, with a steady-state intraband absorption in the 3-5 micron range, and intraband luminescence at 5 micron. low-toxicity, high thermal stability, and stable n-doping, InAs
quantum dots become an interesting material for mid-infrared applications.
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Optics
Microfluidic gratings for X-ray Phase Contrast Imaging
Alessandro Rossi, Francesco Coccimiglio, Antonio Ferraro et al. (+8 more)
Fabrication of X-ray gratings has surged in the last two decades thanks to their vast employment in X-ray Phase Contrast Imaging, an imaging technique able to boost X-ray sensitivity to detect otherwise invisible details. These high aspect ratio devices are usually fabricated by complex, costly, multi-step processes that limit their size and volume scaling. These steps commonly involve UV or X-ray lithography,
semiconductor selective etching and high-Z metal plating, usually Au, which require expensive tools and materials. Here we present a proof-of-concept fabrication via soft lithography and Hg infusion of microfluidic X-ray absorption gratings and their performance in biomedical imaging. Such fabrication technique requires fewer, less expensive, and more scalable processes using alternative and more sustainable materials, while showing comparable visibility with their conventional Au-based, solid equivalent. Our results constitute a promising shift in X-ray optics fabrication that could significantly lower barriers to commercialization and accelerate the practical deployment of X-ray Phase Contrast Imaging.
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All authors Alessandro Rossi, Francesco Coccimiglio, Antonio Ferraro, Tiziana Ritacco, Alberto Astolfo, Michele Giocondo, Vincenzo Formoso, Raffaele Giuseppe Agostino, Francesco Iacoviello, Ioannis Papakonstantinou, Alessandro Olivo
Applied Physics
A Reconfigurable Circuit Strategy and Its Application in Low-Power Rectifier for Ambient Energy Harvesting
Zhongqi He, Haoming He, Liping Yan et al. (+1 more)
In ambient electromagnetic energy harvesting systems, the input power to the rectifier is low. To improve rectification efficiency, Schottky diodes, which are sensitive to low power, are commonly selected as rectifying devices to convert microwave power into dc power. However, low-power rectifying diodes typically have low reverse breakdown voltages, making them susceptible to reverse breakdown under high power conditions. This letter proposes a low-power rectifier with reconfigurable function. The rectifying diode is connected in parallel with the p-i-n diode. At low input power, the output dc voltage is low, and the p-i-n diode remains off, having no impact on the rectifier operation. As the input power increases, the p-i-n diode turns on, causing change in
circuit structure and impedance mismatch. This leads to increased reflected power, thereby preventing the rectifying diode from receiving excessive power. In addition, the turn-on voltage of the p-i-n diode is lower than the reverse breakdown voltage of the rectifying diode, protecting it from reverse breakdown.
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All authors Zhongqi He, Haoming He, Liping Yan, Changjun Liu
Applied Physics · Cross-listed from cond-mat.mes-hall
Spin-Texture Spin-valve with a van der Waals Magnet
Bing Zhao, Roselle Ngaloy, Lars Sjöström et al. (+1 more)
All-electrical methods for nucleating, detecting, and manipulating
spin textures in two-dimensional (2D) van der Waals (vdW) magnets can serve as fundamental building blocks for multi-state spintronic
memory, logic, and neuromorphic computing applications. Unlike conventional ferromagnets, vdW ferromagnets such as Fe5GeTe2 with strong Dzyaloshinskii-Moriya interactions stabilize nanoscale
chiral spin textures, including skyrmions and stripe domains. However, the sub-100 nm size of these
spin textures has limited their study to sophisticated microscopy techniques. Here, we demonstrate all-electrical detection of
spin textures in vdW itinerant ferromagnet Fe5GeTe2 using pure
spin transport in a lateral
graphene spin-valve device at room temperature. By engineering nanoscale constrictions or notches in Fe5GeTe2, we create
spin textures that inject distinct
spin polarizations into the
graphene channel, where they are nonlocally sensed by a reference conventional
ferromagnetic detector at room temperature. This enables the observation of anomalous multi-level
spin-valve switching and Hanle
spin precession signals, which are due to unique
spin textures in Fe5GeTe2 and in sharp contrast to single-domains and conventional magnet-based devices. This all-electrical approach can provide direct access to the
spin textures on an integrated 2D spintronic
circuit without the need for ex-situ microscopic characterizations.
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All authors Bing Zhao, Roselle Ngaloy, Lars Sjöström, Saroj P. Dash
Physics and Society
Synchronization of Weak Signals in Dynamic Systems
Mahmut Akilli
The present study proposes a methodology that combines the 'Duffing oscillator system' and the 'Kuramoto oscillator network' to explore the synchronization of weak signals in dynamic systems. The first step of the procedure is to detect weak periodic or quasi-periodic signals in noisy data collected from the quantifiable processes of any dynamical system using the Duffing oscillator system. The second step is to investigate how the interaction of these weak signals can be synchronized using the Kuramoto oscillator network model. This methodology was applied to seismic signals. The present study has shown that this methodology has great potential for investigating the weak signal synchronisation present within dynamic systems, as evidenced by the analysis of seismic data.
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Instrumentation and Detectors · Cross-listed from gr-qc
Long-wavelength UV-LEDs and charge management in the detection of gravitational waves in space
Yuandong Jia, Yinbowen Zhang, Suwen Wang et al. (+8 more)
For the charge management system in gravitational wave detection missions, a continuous discharge strategy is considered by continuously illuminating a test mass (TM) with weak light in such a way to strike a balance between the charging and discharging rates and at the same time avoids the requirement for frequent activation of charge measurements. Built on experiments by one of us based on a simple parallel plate model for inertial sensor, in the present work a more sophisticated inertial sensor model that mimics the surface properties and work function of a cubical TM of an inertial sensor in space (like that of the LISA Pathfinder) is employed to study bipolar charge management system that utilizes UV-LEDs with peak wavelengths of 269 nm, 275 nm, 280 nm, and 295 nm that are longer than the standard 255 nm commonly employed for direct TM illumination. Experimental results indicate that the 275 nm UV-LED achieves optimal performance, maintaining the TM potential closer to zero and at the same time accommodates both rapid discharge and continuous discharge strategies. The present work provides useful input in the future study of system design and optimization for the charge management system.
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All authors Yuandong Jia, Yinbowen Zhang, Suwen Wang, Guozhi Chai, Zemin Zhang, Yi Zhang, Hongxin Li, Shuanglin Huang, Hongqing Huo, Zongfeng Li, Yun Kau Lau
Chemical Physics
XMCQDPT2-Fidelity Transfer-Learning Potentials and a Wavepacket Oscillation Model with Power-Law Decay for Ultrafast Photodynamics
Ivan V. Dudakov, Pavel M. Radzikovitsky, Dmitry S. Popov et al. (+5 more)
A central pursuit in theoretical chemistry is the accurate simulation of photochemical reactions, which are governed by nonadiabatic transitions through conical intersections. Machine learning has emerged as a transformative tool for constructing the necessary potential energy surfaces, but applying it to excited states faces a fundamental barrier: the cost of generating high-level
quantum chemistry data. We overcome this challenge by developing machine-learning interatomic potentials (MLIPs) that achieve multi-state multi-reference perturbation theory accuracy through various techniques, such as transfer, multi-state, and $\Delta$-learning. Applied to the methaniminium cation, our highest-fidelity transfer-learning model uncovers its complete photodissociation landscape following S$_2$ photoexcitation. The comprehensive XMCQDPT2/SA(3)-CASSCF(12,12) electronic structure description captures all competing decay channels, including S$_1$ branching into photoisomerization and direct H$_2$-loss pathways. Our results show that the population dynamics generally depends on the MLIP model, correlating with its performance. At the same time, the introduction of MLIP-uncertainty corrections based on the predictions of an ensemble of models brings different approaches into agreement, validating this metric as essential for reliable dynamics. To interpret the population dynamics, we introduce a wavepacket oscillation model - a mechanistically transparent, power-law kinetics framework that extracts state-specific lifetimes directly from first-principles simulations. The model quantitatively reproduces the ultrafast decay, creating a direct link between
quantum transition probabilities and classical rate constants. The kinetic fits yield channel-specific lifetimes, supporting the recently discovered photochemical pathway mediated by a novel $\sigma\pi^*/S_0$ conical intersection.
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All authors Ivan V. Dudakov, Pavel M. Radzikovitsky, Dmitry S. Popov, Denis A. Firsov, Vadim V. Korolev, Daniil N. Chistikov, Vladimir E. Bochenkov, Anastasia V. Bochenkova
Optics
Site-controlled quantum dot arrays edge-coupled to integrated silicon nitride waveguides and devices
John O'Hara, Nicola Maraviglia, Mack Johnson et al. (+7 more)
The scalability of
quantum photonic integrated
circuits opens the path towards large-scale
quantum computing and communication. To date, this scalability has been limited by the
stochastic nature of the
quantum light sources. Moreover, hybrid integration of different platforms will likely be necessary to combine state-of-the-art devices into a functioning architecture. Here, we demonstrate the active
alignment and edge-coupling of arrays of ten site-controlled gallium arsenide
quantum dots to an array of ten silicon nitride single-mode waveguides, at cryogenic temperatures. The coupling is facilitated by the fabrication of nanopillars, deterministically self-aligned around each
quantum dot, leading to a high-yield and regular array of single-
photon sources. An on-chip beamsplitter verifies the triggered emission of single
photons into the silicon nitride chip. The low inhomogeneous broadening of the ensemble enables us to observe the spectral overlap of adjacent site-controlled emitters. Across the array of waveguides, the signal collected from each coupled
quantum dot is consistently and reproducibly 0.17 relative to the free-space collection from the very same single-
photon source. Comparing measurement with waveguide simulations, we infer that absolute coupling efficiencies of $\approx 5 \%$ are currently obtained between our
quantum dots and the waveguides.
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All authors John O'Hara, Nicola Maraviglia, Mack Johnson, Jesper Håkansson, Salvador Medina, Gediminas Juska, Luca Colavecchi, Frank H. Peters, Brian Corbett, Emanuele Pelucchi
Chemical Physics
Modular Construction of Jastrow Factors for the Transcorrelated Method
J. Philip Haupt, Maria-Andreea Filip, Evelin Martine Corvid Christlmaier et al. (+3 more)
In this work, we explore the reuse of terms in the Jastrow factor between systems for use in the transcorrelated method, to reduce the number of optimisable parameters for a given system. In particular, we propose a workflow in which atom-specific parts of Jastrow factors, optimised in atoms, may be reused in the molecule, with only a few parameters in the electron-electron part of the Jastrow left to optimise, while maintaining performance. We find that the modified workflow not only reduces the number of terms needing to be optimised, but also improves the accuracy of xTC-CCSD(T) energies.
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All authors J. Philip Haupt, Maria-Andreea Filip, Evelin Martine Corvid Christlmaier, Yifan Cheng, Johannes Hauskrecht, Ali Alavi
Instrumentation and Detectors
Self-Error Correcting Method for Magnetic-Array-Type Current Sensors in Multi-Core Cable Applications
Xiaohu Liu, Keyu Hou, Kang Ma et al. (+7 more)
Data-driven methods enable online assessment of error states in
magnetic-array-type current sensors, and long-term measurement stability can be enhanced through further self-error correction. However, when the
magnetic-array-type current sensors are applied to multi-conductor systems such as multi-core cables, the time-varying correlations among conductor currents may degrade the performance of multi-latent-variable data-driven models for error evaluation. To address this issue, this paper proposes a robust self-error correcting method for
magnetic-array-type current sensors even under significant variations in phase current correlations (e.g., large fluctuations in three-phase current imbalance). By incorporating phase current decoupling and principal component analysis (PCA), the correlation analysis of multi-latent variables (i.e., multi-conductor currents) is transformed into a single-latent-variable (corresponding to single phase current) modeling problem. Experimental results demonstrate that the proposed method effectively detects error drifts of
magnetic field sensors as low as $2\times10^{-3}$ in relative error and $2\times10^{-3}$ rad in phase error. Accurate evaluation and correction of each
magnetic field sensor's error drifts substantially eliminates the overall error drift in the
magnetic-array-type current sensor, validating the feasibility and effectiveness of the proposed self-error correcting method.
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All authors Xiaohu Liu, Keyu Hou, Kang Ma, Jian Liu, Angang Zheng, Zhengwei Qu, Wei Zhao, Lisha Peng, Songling Huang, Shisong Li