Optics
Remote dispersion scan: transformer-network retrieval of ultrafast pulses after non-linear propagation
Kevin Watson, Yutong Geng, Tobias Saule et al. (+2 more)
Accurate and rapid characterization of broadband electric fields is essential for all ultrafast applications and remains an active field of research. In this work, we introduce remote dispersion scan, a
transformer neural network enabled dispersion scan based pulse characterization method that can characterize femtosecond
laser pulses. A local scan of the non-linear spectral phase before several linear and nonlinear processes, including amplification, compression, and self phase modulation, allows for the field
retrieval remotely at the interaction region. We show that the reconstruction accuracy obtained from a single measurement of the fundamental and second harmonic is comparable to that of a full two dimensional scan. We confirm the technique experimentally by compressing a 300 W, 1.3 ps, 1030 nm pulse in a hollow core fiber to 100 fs and measuring the fundamental and second harmonic spectra while scanning the second order phase in a pulse shaper before power amplification. These results establish a simple, robust,
alignment insensitive live-view pulse reconstruction modality.
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All authors Kevin Watson, Yutong Geng, Tobias Saule, Thomas Weinacht, Carlos A. Trallero-Herrero
Medical Physics
Circularly polarized metamaterial cage for homogeneous signal-to-noise ratio enhancement in magnetic resonance imaging
Yuhan Liu, Xia Zhu, Ke Wu et al. (+2 more)
The signal-to-noise ratio (SNR) in
magnetic resonance imaging (MRI) governs the quality of signal detection and directly impacts the clarity and reliability of the acquired images. Recent advances in metamaterials have enabled lightweight solutions with selective
magnetic responses, offering a route to locally boost SNR in targeted anatomical regions but often with compromised field homogeneity. Here, a wireless metamaterial cage constructed from coaxial cables is engineered for homogeneous SNR enhancement at 3.0 T. With its cylindrical geometry and electromagnetic architecture, the device supports circularly polarized resonance through engineered phase-shifted currents, enabling selective and omnidirectional interaction with the rotating B_1^- field to achieve uniform
magnetic field distribution. Integrated with the body coil, the device yields a 32-fold SNR enhancement while maintaining comparable homogeneity to the body coil alone, exhibiting only 12.07% variation within the region of interest (ROI). Benchmarking against a state-of-the-art 16-channel extremity coil further shows that the metacage achieves at least 1.94-fold and 2.24-fold higher SNR in axial and coronal planes, respectively, and exhibits substantially lower SNR variation (12.07% compared to 54.83% for the extremity coil). The results establish the metacage as a compelling platform for next-generation wireless MRI technologies.
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All authors Yuhan Liu, Xia Zhu, Ke Wu, Stephan W. Anderson, Xin Zhang
Instrumentation and Detectors
Two-Stage Gamma-Neutron Source Classification in Water Cherenkov Detectors: Energy Threshold Screening and Machine Learning Pulse Analysis
Alejandro Núñez-Selin, Iván Sidelnik, Christian Sarmiento-Cano et al. (+2 more)
Water Cherenkov detectors offer a robust and economical solution for real-time radiation monitoring by detecting Cherenkov light from charged particles moving faster than light in water. This work presents a novel two-stage classification framework for gamma-
neutron discrimination: an initial physics-based energy threshold filters unambiguous low-energy gamma sources, followed by a machine learning ensemble that resolves ambiguities at higher energies. The detector response was characterized using $^{60}$Co (1.17/1.33~MeV), $^{137}$Cs (0.66~MeV), and a shielded $^{241}$AmBe source, with lead, paraffin, and cadmium shielding employed to isolate
neutron and gamma interactions. Energy calibration established a linear ADU to MeV conversion ($R^2 = 0.966$), enabling identification of a
neutron detection threshold at $2.62 \pm 0.77$~MeV via a $3\sigma$ significance analysis. Stage one categorizes sources as pure gamma (below threshold) or
neutron-emitting (at threshold). For ambiguous cases above threshold, a machine learning pipeline utilizing pulse shape analysis was developed. A soft voting ensemble (Bagging, CatBoost, and MLP) achieved an accuracy of 0.816 and an AUC of 0.921. This hybrid scheme combines physics-based filtering with ML refinement, offering an interpretable and scalable solution for
nuclear security, nonproliferation monitoring, and fundamental radiation research.
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All authors Alejandro Núñez-Selin, Iván Sidelnik, Christian Sarmiento-Cano, Hernán Asorey, Luis A. Núñez
Computational Physics · Cross-listed from cond-mat.mtrl-sci
Minimal model for vortex nucleation and reversal in spherical magnetic nanoparticles
Michael P. Adams and Andreas Michels
Magnetic nanoparticles beyond the single-domain limit often develop
vortex-like magnetization textures arising from the competition between exchange and magnetostatic energies. While such states are routinely studied using micromagnetic simulations, transparent analytical descriptions of
vortex-mediated hysteresis and nucleation remain scarce. Here, we develop a semi-analytical minimal framework for
vortex states in spherical
magnetic nanoparticles. Guided by micromagnetic simulations, we introduce a parametrized
vortex magnetization Ansatz based on
hyperbolic functions that continuously interpolates between uniform and
vortex states. In this way, we achieve a complexity reduction leading to a minimal
Hamiltonian, which enables the efficient computation of magnetization curves and provides insight into
vortex-mediated magnetization reversal. As an application, we derive analytical estimates for the critical
vortex nucleation radius and field, recovering the functional form of Brown's classic result and extending it within a variational framework.
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Medical Physics
Benchmarking Deep Learning-Based Reconstruction Methods for Photoacoustic Computed Tomography with Clinically Relevant Synthetic Datasets
Panpan Chen, Seonyeong Park, Gangwon Jeong et al. (+3 more)
Deep learning (DL)-based image reconstruction methods for photoacoustic computed
tomography (PACT) have developed rapidly in recent years. However, most existing methods have not employed standardized
datasets, and their evaluations rely on traditional image quality (IQ) metrics that may lack clinical relevance. The absence of a standardized framework for clinically meaningful IQ assessment hinders fair comparison and raises concerns about the reproducibility and reliability of reported advancements in PACT. A benchmarking framework is proposed that provides open-source, anatomically plausible synthetic
datasets and evaluation strategies for DL-based acoustic inversion methods in PACT. The
datasets each include over 11,000 two-dimensional (2D)
stochastic breast objects with clinically relevant lesions and paired measurements at varying modeling complexity. The evaluation strategies incorporate both traditional and task-based IQ measures to assess fidelity and clinical utility. A preliminary benchmarking study is conducted to demonstrate the framework's utility by comparing DL-based and physics-based reconstruction methods. The benchmarking study demonstrated that the proposed framework enabled comprehensive, quantitative comparisons of reconstruction performance and revealed important limitations in certain DL-based methods. Although they performed well according to traditional IQ measures, they often failed to accurately recover lesions. This highlights the inadequacy of traditional metrics and motivates the need for task-based assessments. The proposed benchmarking framework enables systematic comparisons of DL-based acoustic inversion methods for 2D PACT. By integrating clinically relevant synthetic
datasets with rigorous evaluation protocols, it enables reproducible, objective assessments and facilitates method development and system optimization in PACT.
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All authors Panpan Chen, Seonyeong Park, Gangwon Jeong, Refik Mert Cam, Umberto Villa, Mark A. Anastasio
Atomic Physics
Highly accurate semiclassical strong-field Herman-Kluk propagator method for high-harmonic generation
Phi-Hung Tran, Hao Quan Truong, R. Esteban Goetz et al. (+1 more)
We extend our recently developed semiclassical strong-field Herman-Kluk propagator (SFHK) method to calculate high-order harmonic generation (HHG) for atoms in intense
lasers. We show that our method, based on a combination of the Herman-Kluk propagator and the strong-field approximation, can provide highly accurate results for both HHG yield and phase, nearly identical to those from the exact numerical solutions of the time-dependent Schrödinger equation. We provide detailed analyses of our method and its applications to the HHG process, particularly the recombination time. The main computational task in this method is to solve the classical Newton equations for the active electron in the combined atomic potential and
laser-electron interaction. The motion of the centers of the electron wave packets, modeled by coherent states, is governed by independent classical trajectories so that the computation can therefore be parallelized very efficiently.
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All authors Phi-Hung Tran, Hao Quan Truong, R. Esteban Goetz, Anh-Thu Le
Chemical Physics
Degenerate coupled-cluster theory
So Hirata
A size-extensive, converging, black-box, ab initio coupled-cluster ($\Delta$CC) ansatz is introduced that computes the energies and wave functions of states from any degenerate or nondegenerate Slater-determinant references with any numbers of $\alpha$- and $\beta$-
spin electrons, any patterns of orbital occupancy, any
spin multiplicities, and any spatial
symmetries. For a nondegenerate reference, it reduces to the single-reference coupled-cluster ansatz. For a degenerate multireference, it is a natural coupled-cluster extension of degenerate Moeller-Plesset perturbation ($\Delta$MP) theory. For ionized and electron-attached references, it is a coupled-cluster Green's function, although the present theory is convergent toward the full-configuration-interaction (FCI) limits, while Feynman-Dyson many-body Green's function (MBGF) theory generally is not. Its single-excitation instance is a projection Hartree-Fock theory as per the Thouless
theorem, which may be useful for core ionizations, high-
spin states, and possibly electron affinities. A new multireference coupled-cluster theory for a general model space is also developed. This quasidegenerate coupled-cluster (QCC) theory is exactly converging, but not black-box, and intended for strong correlation. Determinant-based, general-order
algorithms of $\Delta$CC and QCC theories are implemented and compared with configuration-interaction (CI) and equation-of-motion coupled-cluster (EOM-CC) theories through octuple excitations and with $\Delta$MP and MBGF theories up to the nineteenth order. An algebraic, optimal-scaling
algorithm of $\Delta$CC theory is computer-synthesized at the levels of single excitations ($\Delta$CCS) and of single and double excitations ($\Delta$CCSD). The order of performance is: QCC $\approx$ $\Delta$CC > EOM-CC > CI at the same order or QCC $\approx$ $\Delta$CC > $\Delta$MP > MBGF at the same cost scaling.
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Instrumentation and Detectors
Industrial Deposition of Wavelength-Shifting Films for Liquid Argon Photon Detection Systems
Babak Azmoun, Aleksey Bolotnikov, Francesca Capocasa et al. (+8 more)
The Deep Underground
Neutrino Experiment (DUNE) Phase-II Far Detector is considering an approximately 2000\,m$^2$
photon detection system to achieve a target mean light yield of 180\,PE/MeV. Meeting this requirement demands scalable, cost-effective, and high-quality wavelength-shifter (WLS) coatings capable of converting 127\,nm
liquid-argon scintillation light into visible
photons with controlled and reproducible optical performance. We report on the successful realization of an industrial physical vapor deposition (PVD) process for p-terphenyl (pTP) coatings, adapted from
vacuum deposition techniques developed for OLED display manufacturing, to produce uniform WLS layers on large-area inorganic substrates, a task traditionally challenged by adhesion and uniformity issues at organic–inorganic interfaces. Surface characterization by profilometry and spectroscopic measurements demonstrates edge-region thickness variation below 10% and emission spectra consistent with high-quality pTP reference samples. The industrial process demonstrates reproducibility, scalability, and significantly reduced production time compared to laboratory-based methods, while maintaining optical characteristics consistent with established pTP reference samples. These results establish a viable pathway for mass production of high-performance pTP coatings for DUNE FD3 and future
neutrino experiments, from a coating manufacturing and process standpoint. Detector-level performance validation, including quantitative VUV conversion efficiency measurements at 127\,nm, is identified as future work.
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All authors Babak Azmoun, Aleksey Bolotnikov, Francesca Capocasa, Milind Diwan, Yimin Hu, Jay Hyun Jo, William Lenz, Yichen Li, Abdul Rumaiz, Vyara Tsvetkova, Matteo Vicenzi
Atomic Physics
General framework for quantifying entanglement production in ultracold molecular collisions and chemical reactions
Adrien Devolder, Paul Brumer and Timur Tscherbul
Entanglement, a defining feature of
quantum mechanics, arises naturally from interactions between molecular systems. Yet the precise nature and quantification of
entanglement in the products of molecular collisions and reactions remain largely unexplored. Here, we show that coupling between the external (motional) and internal degrees of freedom of the colliding molecules generates diverse forms of product-state
entanglement: discrete-discrete, continuum-continuum, and hybrid discrete-continuum. We develop a general theoretical framework to quantify these
entanglement forms directly from scattering S-
matrix elements and identify a novel class of entangled states-multimode hybrid cat states, that exhibit multimode discrete-continuum
entanglement. Although applicable at arbitrary collision energies, the formalism is illustrated in the ultracold and cold regimes for inelastic Rb+SrF and Rb+Sr$^+$ collisions, as well as the chemical reaction F+HD $\rightarrow$ HF+D, DF+H. We demonstrate that
entanglement can be efficiently controlled near
magnetic Feshbach resonances, paving the way for precise
magnetic control of product-state
entanglement generation in ultracold molecular collisions.
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Medical Physics · Cross-listed from eess.IV
Fully 3D Unrolled Magnetic Resonance Fingerprinting Reconstruction via Staged Pretraining and Implicit Gridding
Yonatan Urman, Mark Nishimura, Daniel Abraham et al. (+2 more)
Magnetic Resonance Fingerprinting (MRF) enables fast quantitative imaging, yet reconstructing high-resolution 3D data remains computationally demanding. Non-Cartesian reconstructions require repeated non-uniform FFTs, and the commonly used Locally Low Rank (LLR) prior adds computational overhead and becomes insufficient at high accelerations. Learned 3D priors could address these limitations, but training them at scale is challenging due to
memory and runtime demands. We propose SPUR-iG, a fully 3D deep unrolled subspace reconstruction framework that integrates efficient data consistency with a progressive training strategy. Data consistency leverages implicit GROG, which grids non-Cartesian data onto a Cartesian grid with an implicitly learned kernel, enabling FFT-based updates with minimal artifacts. Training proceeds in three stages: (1) pretraining a denoiser with extensive data augmentation, (2) greedy per-iteration unrolled training, and (3) final fine-tuning with gradient checkpointing. Together, these stages make large-scale 3D unrolled learning feasible within a reasonable compute budget. On a large in vivo
dataset with retrospective undersampling, SPUR-iG improves subspace coefficient maps quality and quantitative accuracy at 1-mm isotropic resolution compared with LLR and a hybrid 2D/3D unrolled baseline. Whole-
brain reconstructions complete in under 15-seconds, with up to $\times$111 speedup for 2-minute acquisitions. Notably, $T_1$ maps with our method from 30-second scans achieve accuracy on par with or exceeding LLR reconstructions from 2-minute scans. Overall, the framework improves both accuracy and speed in large-scale 3D MRF reconstruction, enabling efficient and reliable accelerated quantitative imaging.
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All authors Yonatan Urman, Mark Nishimura, Daniel Abraham, Xiaozhi Cao, Kawin Setsompop
Applied Physics · Cross-listed from eess.SP
Inverter-Based Differential Amplifiers With Back-Gate Feedback Linearization
Eric Danson and Jeffrey S. Walling
Feeding the common-source amplifier output to the back-gate terminal in fully depleted silicon on
insulator (FD-SOI) technology exploits the linearizing effect of negative feedback. Analysis and simulation results in 22 nm FD-SOI show that back-gate feedback sets the overall gain approximately independent of the load, contributes no additional noise, and improves linearity by the back-gate voltage gain. Third-order intercept point (IP3) enhancement is at least $60\times$ compared to without feedback in inverter-based, or complementary common-source, differential amplifiers.
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Accelerator Physics
Accelerating Molecular H$_2^+$ Beam in AGS and RHIC
Xiaodong Jiang
After the recent success of acceleration molecular H$_2^+$ beam (from EBIS) in Booster to 1.0 GeV/u kinetic energy, we propose to carry out tests to accelerate H$_2^+$ beam in AGS (up to 12 GeV/u) and to RHIC (up to 100 GeV/u). In this Note, we address the main effects that might hamper H$_2^+$ beam acceleration, outline the impacts and benefits of high energy H$_2^+$ beam to BNL.
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Instrumentation and Detectors · Cross-listed from cond-mat.mtrl-sci
Detecting the full photoemission cone from laser-based ARPES experiments by leveraging deflector technology
Nicolas Gauthier, Benson Kwaku Frimpong, Dario Armanno et al. (+8 more)
Angle-resolved photoemission spectroscopy (ARPES) provides a direct access to the electronic band structure of solid and molecular systems. The momentum range accessible by this technique depends directly on the
photon energy used, and low-
photon-energy sources are insufficient to photoemit electrons over the full Brillouin zone of most
quantum materials. In addition, while electrons are emitted over a 2$\pi$ solid angle, conventional hemispherical analyzers only collect a small subset of those electrons. A previous work [RSI 92, 123907 (2021)] demonstrated that electrons emitted over a larger field-of-view can be acquired in one fixed configuration by accelerating them towards the analyzer with a bias voltage. Here, we extend this work by leveraging the deflector technology of novel ARPES hemispherical analyzers. We demonstrate the ability to detect all $2\pi$ photoemitted electrons in a fixed configuration for various materials such as gold, cuprates and transition-metal dichalcogenides. This approach is especially advantageous for time-resolved ARPES, as electron dynamics over a large momentum range can be accessed with identical measurement conditions.
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All authors Nicolas Gauthier, Benson Kwaku Frimpong, Dario Armanno, Akib Jabed, Francesco Goto, Vicky Hasse, Claudia Felser, Genda Gu, Heide Ibrahim, Francois Légaré, Fabio Boschini
Classical Physics
The Soul of Waves: Physical Interpretation of Dispersion Relations
Renato Vieira dos Santos
This pedagogical paper presents a comprehensive framework for interpreting dispersion relations across fundamental physical systems. We adopt a novel approach that starts from the mathematical form $\omega(\mathbf{k})$ and systematically extracts its physical content, rather than deriving it from first principles. Through an in-depth case study of the massive Klein-Gordon dispersion relation $\omega^2 = \omega_0^2 + c^2k^2$, we demonstrate how this single equation encodes phase velocity, group velocity, density of states, effective mass, and impedance. The analysis reveals the universal nature of this dispersion form, which manifests in
quantum fields,
plasmas,
superconductors, and photonic
crystals with different physical interpretations of its parameters. We complement this with detailed examination of classical systems including mass-spring chains and hydrodynamic waves, providing tangible analogies that bridge conceptual understanding between
quantum and classical wave phenomena. The paper includes eleven carefully designed figures that visualize key concepts and a comprehensive catalog of dispersion relations in the Appendix. Aimed at advanced undergraduates and instructors, this work emphasizes conceptual understanding through physical interpretation, offering a unified pedagogical framework for teaching wave propagation across physics curricula while maintaining mathematical rigor and depth.
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Chemical Physics
ChemNavigator: Agentic AI Discovery of Design Rules for Organic Photocatalysts
Iman Peivaste, Ahmed Makradi and Salim Belouettar
The discovery of high-performance organic photocatalysts for hydrogen
evolution remains limited by the vastness of chemical space and the reliance on human intuition for molecular design. Here we present ChemNavigator, an agentic AI system that autonomously derives structure-property relationships through hypothesis-driven exploration of organic photocatalyst candidates. The system integrates large
language model
reasoning with density functional tight binding calculations in a multi-
agent architecture that mirrors the scientific method: formulating hypotheses, designing experiments, executing calculations, and validating findings through rigorous statistical analysis. Through iterative discovery cycles encompassing 200 molecules, ChemNavigator autonomously identified six statistically significant design rules governing frontier orbital energies, including the effects of ether linkages, carbonyl groups, extended conjugation, cyano groups, halogen substituents, and amine groups. Importantly, these rules correspond to established principles of organic electronic structure (resonance donation, inductive withdrawal, $\pi$-delocalization), demonstrating that the system can independently derive chemical knowledge without explicit programming. Notably, autonomous agentic
reasoning extracted these six validated rules from a molecular library where previous ML approaches identified only carbonyl effects. Furthermore, the quantified effect sizes provide a prioritized ranking for synthetic chemists, while feature interaction analysis revealed diminishing returns when combining strategies, challenging additive assumptions in molecular design. This work demonstrates that agentic AI systems can autonomously derive interpretable, chemically grounded design principles, establishing a framework for AI-assisted materials discovery that complements rather than replaces chemical intuition.
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Atmospheric and Oceanic Physics
Black Carbon scavenging in liquid Arctic clouds: the role of size and mixing state
Barbara Bertozzi, Robin L. Modini, Radovan Krejci et al. (+4 more)
Black carbon (BC) contributes to Arctic warming by absorbing sunlight and darkening snow. Its atmospheric lifetime critically determines its concentration and
climate impact, yet the processes controlling its removal remain poorly constrained in the Arctic. From 18 months of single-particle measurements at the Zeppelin Observatory (Svalbard), we analysed 37
liquid cloud events (~200 hours) to investigate the link between BC properties and in-cloud scavenging, providing the most extensive in-cloud single particle BC
dataset to date. While large BC cores (DrBC>200 nm) were consistently scavenged, smaller cores were only partly removed. However, even thin soluble coatings significantly enhanced their scavenging, showing that mixing state modulates BC scavenging in the CCN-limited regime typical of Arctic low-level clouds. Seasonal variability in clear sky BC mixing state further suggests corresponding changes in scavenging efficiency. Our results demonstrate that besides size, the size-resolved BC mixing state is a key variable for BC scavenging in the Arctic and models should take it into consideration to accurately predict BC-cloud interaction.
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All authors Barbara Bertozzi, Robin L. Modini, Radovan Krejci, Gabriel Pereira Freitas, Rosaria E. Pileci, Paul Zieger, Martin Gysel-Beer
Atomic Physics · Cross-listed from quant-ph
Engineering discrete local dynamics in globally driven dual-species atom arrays
Francesco Cesa, Andrea Di Fini, David Aram Korbany et al. (+4 more)
We introduce a method for engineering discrete local dynamics in globally-driven dual-species neutral atom experiments, allowing us to study emergent digital models through uniform analog controls. Leveraging the new opportunities offered by dual-species systems, such as species-alternated driving, our construction exploits simple Floquet protocols on static atom arrangements, and benefits of generalized blockade regimes (different inter- and intra-species interactions). We focus on discrete dynamical models that are special examples of
Quantum Cellular Automata (QCA), and explicitly consider a number of relevant examples, including the kicked-Ising model, the Floquet Kitaev honeycomb model, and the digitization of generic translation-invariant nearest-neighbor
Hamiltonians (e.g., for Trotterized
evolution). As an application, we study chaotic features of discretized many-body dynamics that can be detected by leveraging only demonstrated capabilities of globally-driven experiments, and
benchmark their ability to discriminate chaotic
evolution.
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All authors Francesco Cesa, Andrea Di Fini, David Aram Korbany, Roberto Tricarico, Hannes Bernien, Hannes Pichler, Lorenzo Piroli
Fluid Dynamics
Thermodynamically consistent large-eddy simulation models
Thomas Dubos
Filtered budgets for anelastic
turbulence and a general expression of the turbulent sensible heat flux are derived for a multicomponent fluid with an arbitrary equation of state. A family of subgrid-scale closures is then found under the constraint of consistency with (i) the first and second laws of thermodynamics and (ii) invariance with respect to irrelevant thermodynamic constants. A similar family of fully compressible models is also constructed heuristically. These models predict turbulent kinetic energy, assume down-gradient closures for three-dimensional turbulent fluxes and impose certain relationships between the closures for the turbulent fluxes of heat, matter,
entropy, and the work of buoyancy forces. A key finding is the explicit derivation of the local rate of
entropy production in the filtered model. Positive
entropy production is guaranteed whenever the turbulent
diffusions of heat and composition are positive and no cross-
diffusion occurs. Cross-diffusivities are admissible provided their magnitude is within the bounds of an explicit criterion. The filtered model is invariant under a wider class of transformations than the unfiltered model. Furthermore, in the special case of a single turbulent diffusivity, an arbitrary conservative variable can be prognosed while ignoring its precise relationship to
entropy. These findings show that down-gradient closures are consistent with the first and second law of thermodynamics even when they lead to a turbulent sensible heat flux up the temperature gradient. Indeed, while molecular conduction/
diffusion is spontaneous and energy-conserving, stratified turbulent mixing is driven by mechanical
turbulence and enabled by the consumption of turbulent kinetic energy.
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Chemical Physics
Simulating Electron Dynamics with GPU-Accelerated Real-Time Tamm-Dancoff Approximation
Thomas Knoll and Benjamin G. Levine
Time-dependent electronic structure methods provide an efficient, accurate, and robust alternative to traditional time dependent methods for computing both linear and non-linear optical properties. With this in mind, we have developed the real-time Tamm-Dancoff approximation (RT-TDA). This is an approach to model electron dynamics by propagating the linear-response time-dependent density functional theory (LR-TDDFT) amplitudes within the Tamm-Dancoff approximation (TDA) and adiabatic approximation. Because the electronic structure is propagated in real-time in a many-electron basis, RT-TDA overcomes known limitations of adiabatic Kohn-Sham RT-TDDFT for describing dynamics in intense fields. Acceleration by graphic processing units (GPUs) enables simulations of larger molecules and on longer timescales. To demonstrate the utility of our approach, we present the calculations of the linear absorption spectrum of a large organic molecule (120 heavy atoms), of Rabi oscillations, and of nonlinear 2-
photon absorption, in which we observe the AC Stark effect.
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Optics · Cross-listed from quant-ph
Quantum Fisher information analysis for absorption measurements with undetected photons
Martin Houde, Franz Roeder, Christine Silberhorn et al. (+2 more)
We theoretically compare the
quantum Fisher information (QFI) for three configurations of absorption spectroscopy with undetected idler
photons: an SU(1,1) interferometer with inter-source idler loss, an induced-coherence (IC) setup in which the idler partially seeds a second squeezer together with a
vacuum ancilla, and a distributed-loss (DL) scheme with in-medium attenuation. We calculate the QFI as a function of parametric gain for both full and signal-only detection access. For losses below 99% and low to moderate gain, the SU(1,1) configuration provides the largest QFI. At high gain and intermediate loss, the IC scheme performs best, while under extreme attenuation (transmission $<$ 1%) the DL model becomes optimal. These results delineate the measurement regimes in which each architecture is optimal in terms of information theory.
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All authors Martin Houde, Franz Roeder, Christine Silberhorn, Benjamin Brecht, Nicolás Quesada
Instrumentation and Detectors
Neutron spectrum measurement in the Yemi underground laboratory
Joong Hyun Kim, Sinchul Kang, HyeoungWoo Park et al. (+7 more)
We report on the measurement of
neutron energy spectra at the newly established Yemi Underground Laboratory (Yemilab) in the Republic of Korea, designed to host dark matter and rare-event search experiments. A high-sensitivity
neutron spectrometer was employed, consisting of ten cylindrical {}^{3}He proportional counters, eight of which were embedded in cylindrical high-density polyethylene moderators of various sizes. To quantify and mitigate contributions from internal \alpha-backgrounds, each detector underwent a dedicated background measurement using a cadmium-shielded box. These backgrounds, primarily originating from trace amounts of U and Th in the stainless-steel housings, were characterized and subtracted during data analysis.
Neutron measurements were carried out at three locations within the Yemilab between March to October 2023. After waveform-based event selection and correction for \alphasym-backgrounds,
neutron count rates were estimated and corresponding energy spectra were reconstructed using the unfolding method. The total
neutron fluence rates were measured ranged from (3.24 $\pm$ 0.11) to (4.01 $\pm$ 0.10) $\times~10^{-5}~ {cm}^{-2}~{s}^{-1}$, with thermal and fast
neutron components (1 - 10 MeV) ranging from (1.32 $\pm$ 0.05) to (1.51 $\pm$ 0.05) $\times 10^{-5}~{cm}^{-2}~{s}^{-1}$ and (0.27 $\pm$ 0.03) to (0.34 $\pm$ 0.10) $\times~10^{-5}~{cm}^{-2}~{s}^{-1}$, respectively.
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All authors Joong Hyun Kim, Sinchul Kang, HyeoungWoo Park, Jungho Kim, Hyeonseo Park, Young Soo Yoon, Hongjoo Kim, Yeongduk Kim, Jungho So, SungHyun Kim
Instrumentation and Detectors
Investigating ultra-thin 4H-SiC AC-LGADs for superior radiation-hard timing applications
Jaideep Kalani, Saptarshi Datta, Ganesh J Tambve et al. (+1 more)
The Low Gain Avalanche Diodes (LGADs) are promising particle detectors for timing resolution better than $50$ ps under a high radiation environment. This study investigates n-in-p LGAD architecture, focusing on ultra-thin sensors of thickness less than $50\ \mu$m using the WeightField2 program. The capabilities of WeightField2 are demonstrated by comparing its results with irradiation measurements from an FBK LGAD wafer, showing good agreement across unirradiated and
neutron-irradiated conditions. This paper presents device simulations in High Luminosity LHC conditions (lifetime integrated fluence $ \mathcal{O} (10^{14})\ \mathrm{n_{eq}~cm^{-2}}$, temperature $ \approx 243\ \mathrm{K} $), and taking into account radiation damage, gain reduction due to fluence, and
lattice defects. It is shown that a 20 $\mu$m thick sensor achieves the best timing performance. Among Silicon (Si), Diamond (C), and 4H-Silicon Carbide (4H-SiC), we found 4H-SiC to be the most promising: it provides the highest gain value for a fixed thickness and gain implant layer configuration, and best retains high charge collection value and timing capability under increasing fluence up to $50\times10^{14}\ \mathrm{n_{eq}~cm^{-2}}$. A time resolution less than 25 ps is reported with different gain implant concentrations for a $20 \mu$m 4H-SiC sensor. This work presents the potential of SiC-based LGADs in high-radiation
collider environments.
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All authors Jaideep Kalani, Saptarshi Datta, Ganesh J Tambve, Prabhakar Palni
Physics Education · Cross-listed from astro-ph.IM
CosmoSlider: An educational tool for cosmology
Andreas Nygaard, Steen Hannestad and Thomas Tram
Understanding how cosmological parameters influence the
cosmic microwave background (CMB) power spectra is a central component of modern cosmology education, but interactive exploration is often limited by computational cost or technical complexity. We present CosmoSlider, a lightweight visualization tool that enables real-time exploration of CMB power spectra as multiple cosmological parameters are varied simultaneously. The tool employs a neural-network emulator implemented using TensorFlow Lite, allowing rapid evaluation of spectra without relying on large grids of precomputed models or on-demand execution of Einstein–Boltzmann solvers. CosmoSlider is available both as an iOS application and as a web-based tool, making it accessible across platforms and suitable for use in classrooms, lectures, and self-guided study. By providing immediate visual feedback, CosmoSlider supports the development of intuition for the physical processes underlying CMB anisotropies and serves as a complementary resource to traditional theoretical instruction.
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Chemical Physics
Coarse-Grained Geometric Quantum Dynamics in the Tensor Network Representation
Mo Sha and Bing Gu
Quantum geometrical molecular dynamics provides a
quantum geometric picture for understanding reactive dynamics, especially excited-state conical intersection dynamics, and also a numerically exact method for strongly correlated electron-
nuclear dynamics. However, there are substantial challenges in describing medium-sized molecules with tens of
nuclear degrees of freedom. The main challenge is that it uses a discrete variable representation to discretize the molecular configuration space, and thus requires a tremendous number of
quantum chemistry calculations to construct the electronic overlap
matrix. Moreover, the expansion coefficients scale exponentially with molecular size for direct-product basis sets. We address these challenges by first introducing a coarse-grained local diabatic ansatz, followed by a tensor network representation of the expansion coefficients and the molecular time-
evolution operator. With a full 24-dimensional demonstration using the pyrazine molecule, we show that such developments provide a highly accurate and computationally tractable method for high-dimensional, fully
quantum, strongly coupled electron-
nuclear dynamics from first principles.
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Optics
Clinical Feasibility of Label-Free Digital Staining Using Mid-Infrared Microscopy at Subcellular Resolution
L. Duraffourg, H. Borges, M. Fernandes et al. (+9 more)
We present a rapid, large-field bimodal imaging platform that integrates conventional brightfield microscopy with a lensless IR imaging scanner, enabling whole-slide IR image stack acquisition in minutes. Using a dedicated deep learning model, we implement an optical HE staining strategy based on subcellular morpho-spectral fingerprinting.
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All authors L. Duraffourg, H. Borges, M. Fernandes, M. Beurrier-Bousquet, J. Baraillon, B. Taurel, J. Le Galudec, K. Vianey, C. Maisin, L. Samaison, F. Staroz, M. Dupoy
Computational Physics · Cross-listed from astro-ph.EP
The Origins of Planets for ArieL (OPAL) Key Science Project: the end-to-end planet formation campaign for the ESA space mission Ariel
Danae Polychroni, Diego Turrini, Romolo Politi et al. (+7 more)
The growing body of atmospheric observations of
exoplanets from space and ground-based facilities showcases how the great diversity of the planetary population is not limited to their physical properties but extends to their compositions. The ESA space mission Ariel will observe and characterise hundreds of exoplanetary atmospheres to explore and understand the roots of this compositional diversity. To lay the foundations for the Ariel mission, the OPAL Key Science Project is tasked with creating an unprecedented library of realistic synthetic atmospheres spanning tens of elements and hundreds of molecules on which the Ariel consortium will test and validate its codes and pipelines ahead of launch. In this work we describe the aims and the pipeline of codes of the OPAL project, as well as the process through which we trace the genetic link connecting
planets to their native protoplanetary disks and host
stars. We present the early results of this complex and unprecedented endeavour and discuss how they highlight the great diversity of outcomes that emerge from the large degeneracy in the parameter space of possible initial conditions to the
planet formation process. This, in turn, illustrates the growing importance of interdisciplinary modelling studies supported by high-performance computing methods and infrastructures to properly investigate this class of high-dimensionality problems.
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All authors Danae Polychroni, Diego Turrini, Romolo Politi, Sergio Fonte, Eugenio Schisano, Elenia Pacetti, Paolo Matteo Simonetti, Michele Zusi, Sergio Molinari, Stavro Ivanovski
Instrumentation and Detectors
Design and characterization of the POKERINO prototype for the POKER/NA64 experiment at CERN
Andrei Antonov, Pietro Bisio, Mariangela Bondì et al. (+3 more)
The NA64 experiment at CERN H4 beamline recently started a high-energy positron-beam program to search for light dark matter particles through a thick-target, missing-energy measurement. To fulfil the energy resolution requirement of the physics measurement $\sigma_E/E\simeq2.5\%/\sqrt{E\mathrm{[GeV}]} \oplus 0.5\%$ and cope with the constraints and performance requests of the NA64 setup, a new high-resolution homogeneous electromagnetic calorimeter PKR-CAL has been designed. The detector is based on PbWO$_4$
crystals, each read by multiple SiPM sensors to maximize the light collection. The PKR-CAL design has been optimized to mitigate and control unavoidable SiPM saturation effects at high light levels, as well as to minimize the gain fluctuations induced by instantaneous variations of the H4 beam intensity. The $R\&D$ program culminated in the construction of a small-scale prototype, POKERINO. In this work, we present the results from the experimental characterization campaign of the POKERINO aiming at demonstrating that the obtained performances are compatible with the application requirements.
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All authors Andrei Antonov, Pietro Bisio, Mariangela Bondì, Andrea Celentano, Anna Marini, Luca Marsicano
Optics
Ultrafast Dipolar Electrostatic Modeling of Plasmonic Nanoparticles with Arbitrary Geometry
Paulo S. S. dos Santos, João P. Mendes, José M. M M. de Almeida et al. (+1 more)
Accurate and fast calculations of localized surface plasmon resonances (LSPR) in metallic nanoparticles is essential for applications in sensing, nano-optics, and energy harvesting. Although full-wave numerical techniques such as the boundary element method (BEM) or the discrete dipole approximation (DDA) provide high accuracy, their computational cost often hinders rapid parametric studies. Here it is presented an ultrafast method that avoids solving large eigenproblems. Instead, only the dipolar component of the induced surface charge density \((\sigma_{dipolar})\) is retained through a expansion into Cartesion dipole basis, yielding a compact $3\times3$
geometric formulation that avoids full boundary-integral solves. The spectral response is obtained in a similar way, by projecting the Neumann–Poincaré surface operator onto the dipole subspace and evaluating a Rayleigh quotient, giving geometry-only
eigenvalues again without an $N\times N$ eigenproblem. A major advantage of this method is that all geometry-dependent quantities are computed once per nanoparticle, while material dispersion and environmental changes enter only through simple algebraic expressions for the polarizability, enabling rapid evaluation across wavelengths. Retardation effects are incorporated through the modified long-wavelength approximation (MLWA), extending accuracy into the weakly retarded regime. The resulting framework provides a valuable tool for fast modelling and optimization of plasmonic nanoparticles at a significant lesser computational cost than BEM, DDA, and other standard tools.
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All authors Paulo S. S. dos Santos, João P. Mendes, José M. M M. de Almeida, Luís C. C. Coelho
Plasma Physics
Improved Kelbg Potentials for $Z>1$ and Application to Carbon Plasmas
Heather D. Whitley, Michael S. Murillo, John I. Castor et al. (+5 more)
In this work, we present a general form for the electron-ion diffractive potential derived from the
quantum pair density
matrix and fit to the improved Kelbg potential for atomic numbers up to $Z = 54$. We apply classical molecular dynamics using the improved Kelbg potential for carbon with various forms of the Pauli potential to compute internal energies and pressures for hot, dense
plasma conditions. Our results are compared to an equation of state model based on path integral Monte Carlo and density functional theory simulations to examine the extent to which the improved Kelbg potential reproduces the internal energy and pressure of carbon
plasmas. The regions of validity for carbon agree generally with those derived previously for hydrogen once pressure ionization effects are incorporated. Based on our carbon results and previously published hydrogen studies, we discuss the general applicability and limitations of these potentials for equation of state studies in warm dense matter and high energy density
plasmas.
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All authors Heather D. Whitley, Michael S. Murillo, John I. Castor, Liam G. Stanton, Lorin X. Benedict, Philip A. Sterne, James N. Glosli, Frank R. Graziani
Computational Physics · Cross-listed from astro-ph.EP
Mercury-Ar$\chi$es: a high-performance n-body code for planet formation studies
Diego Turrini, Sergio Fonte, Romolo Politi et al. (+4 more)
Forming planetary systems are populated by large numbers of gravitationally interacting planetary bodies, spanning from massive
giant planets to small planetesimals akin to present-day asteroids and comets. All these planetary bodies are embedded in the gaseous embrace of their native protoplanetary disks, and their interactions with the disk gas play a central role in shaping their dynamical
evolution and the outcomes of
planet formation. These factors make realistic
planet formation simulations extremely computationally demanding, which in turn means that accurately modeling the formation of planetary systems requires the use of high-performance methods. The
planet formation code Mercury-Ar$\chi$es was developed to address these challenges and, since its first implementation, has been used in multiple exoplanetary and
Solar System studies. Mercury-Ar$\chi$es is a parallel n-body code that builds on the widely used Mercury code and is capable of modeling the growth and migration of forming
planets, the interactions between planetary bodies and the disk gas, as well as the evolving impact flux of planetesimals on forming
planets across the different stages of their formation process. In this work we provide the up-to-date overview of its physical modeling capabilities and the first detailed description of its high-performance implementation based on the OpenMP directive-based parallelism for shared
memory environments, to harness the multi-thread and vectorization features of modern processor architectures.
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All authors Diego Turrini, Sergio Fonte, Romolo Politi, Danae Polychroni, Scigé J. Liu, Paolo Matteo Simonetti, Simona Pirani