Atomic Physics
Reference Quadrupole Moments of Transition Elements from Lamb Shifts in Muonic Atoms
S. Rathi, K. von Schoeler, P. Indelicato et al. (+1 more)
We present a novel method for accurately measuring the absolute electric quadrupole moments of light transition elements $(23 \leq Z \leq 30 )$. Our approach is based on performing precision muonic x-ray spectroscopy of the $2s-2p$
manifold, which is also referred to as the Lamb shift. These transitions are too weak to be detected with dispersive methods and too overlapping to be resolved by solid-state detectors. Here, we propose the use of cryogenic microcalorimeters, which possess high efficiency and excellent energy resolution in the relevant energy regime, coupled with state-of-the-art theoretical calculations. We demonstrate the feasibility of this approach by performing extensive calculations and realistic simulations. In this way, we establish that the uncertainty in the absolute moment, which is transferred to the quadrupole moments of all isotopes in the chain, could be reduced by up to an order of magnitude within a day of measurement. These precise reference quadrupole moments serve as valuable inputs for
nuclear structure studies and for benchmarking state-of-the-art
quantum chemistry calculations in open-shell elements.
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All authors S. Rathi, K. von Schoeler, P. Indelicato, B. Ohayon
Instrumentation and Detectors
On the Measurability of True Coincidence Summing in the GRIFFIN Spectrometer
Liam Schmidt
The measurement of gamma-rays from decaying
nuclei allow for the investigation into
nuclear structure. True coincidence summing occurs when two gamma-rays from a single decay get detected in a single detector and their energies sum together to give false peaks in the energy spectrum. Corrections to this summing effect are crucial for an accurate determination of
nuclear decay events. The summing correction formalism of Semkow et al. is generalized here into the Semkow
matrix formalism and is extended into a multiplicity expansion. This formalism is used to calculate the
matrix probabilities for 180-degree coincidence events as a method for correcting coincidence summing; in doing so, the deviation between the full correction and this 180-degree correction is shown as a function of multiplicity. This formalism is extended to the partitioned
matrix formalism, to calculate probabilities for gated gamma rays; where two gamma-rays of interest are taken in multi-detector coincidence. The summing correction probabilities for gated gamma-rays are provided and the deviation is shown in a manner similar to that of the singles. Terms such as measurability, event equivalence, and ontic and epistemic events are defined. It is shown that within these definitions, coincidence summing is not sufficiently measurable, or rather, its sufficient measurability is statistically bounded by the deviations derived.
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Instrumentation and Detectors
From Commissioning to Precision Data-Taking: Resolving Operational Challenges in the Nab Detector Systems
L. J. Broussard, H. Acharya, R. Alarcon et al. (+36 more)
Our understanding of the weak mixing of
quarks, described by the Cabibbo Kobayashi Maskawa (CKM)
matrix, currently presents an anomaly. Thanks to major strides in both theory and experiment, improved precision in determinations of the first row of
matrix elements has revealed disagreement with the expectation of unitarity. The Nab experiment at the Spallation
Neutron Source is designed to precisely extract the first
matrix element $V_{ud}$ and shed light on experimental tensions within the
neutron beta decay
dataset. Nab's asymmetric spectrometer allows coincident reconstruction of the decay
proton and electron energies, which will be used to determine the electron-
neutrino correlation coefficient, and thus (with the
neutron lifetime) determine $V_{ud}$. This unique approach has provided a more comprehensive view of
neutron beta decay, including a first observation of the full momentum phase space of the decay above detector thresholds and limits on exotic
neutron states. Recent upgrades to the Nab detector system have improved the robustness and stability of the detector performance in terms of
proton detection efficiency, noise performance, and detector segment availability, setting the stage for high precision physics data-taking.
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All authors L. J. Broussard, H. Acharya, R. Alarcon, S. Baeßler, M. Benoit, K. Borah, C. L. Britton, E. Brown, J. Choi, S. Clymer, C. Crawford, N. Ericson, L. Fabris, N. Fomin, J. Fry, R. Godri, F. M. Gonzalez, A. Hagemeier, J. Hamblen, S. Hollander, A. Jezghani, K. Leung, N. Macsai, M. Makela, D. Mathews, P. L. McGaughey, A. Mendelsohn, J. Mirabal, P. E. Mueller, A. Nelsen, S. I. Penttilä, D. Počanić, J. C. Ramsey, K. Reed, L. Richburg, A. Saunders, W. Schreyer, A. Shelby, A. R. Young
General Physics
A microscopic model for the self-inductance of an ideal solenoid
Calin Galeriu
We derive the formula for the self-inductance of an ideal solenoid by calculating the total kinetic energy associated with the drift velocity of the conduction electrons.
Chemical Physics
Mamba-driven multi-perspective structural understanding for molecular ground-state conformation prediction
Yuxin Gou, Aming Wu, Richang Hong et al. (+1 more)
A comprehensive understanding of molecular structures is important for the prediction of molecular ground-state conformation involving property information. Meanwhile, state space model (e.g., Mamba) has recently emerged as a promising mechanism for long sequence modeling and has achieved remarkable results in various
language and
vision tasks. However, towards molecular ground-state conformation prediction, exploiting Mamba to understand molecular structure is underexplored. To this end, we strive to design a generic and efficient framework with Mamba to capture critical components. In general, molecular structure could be considered to consist of three elements, i.e., atom types, atom positions, and connections between atoms. Thus, considering the three elements, an approach of Mamba-driven multi-perspective structural understanding (MPSU-Mamba) is proposed to localize molecular ground-state conformation. Particularly, for complex and diverse molecules, three different kinds of dedicated scanning strategies are explored to construct a comprehensive perception of corresponding molecular structures. And a bright-channel guided mechanism is defined to discriminate the critical conformation-related atom information. Experimental results on QM9 and Molecule3D
datasets indicate that MPSU-Mamba significantly outperforms existing methods. Furthermore, we observe that for the case of few training samples, MPSU-Mamba still achieves superior performance, demonstrating that our method is indeed beneficial for understanding molecular structures.
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All authors Yuxin Gou, Aming Wu, Richang Hong, Meng Wang
Computational Physics · Cross-listed from cs.LG
Intelligent Optimization of Multi-Parameter Micromixers Using a Scientific Machine Learning Framework
Meraj Hassanzadeh, Ehsan Ghaderi, Mohamad Ali Bijarchi et al. (+1 more)
Multidimensional optimization has consistently been a critical challenge in engineering. However, traditional simulation-based optimization methods have long been plagued by significant limitations: they are typically capable of optimizing only a single problem at a time and require substantial computational time for meshing and numerical simulation. This paper introduces a novel framework leveraging cutting-edge Scientific Machine Learning (Sci-ML) methodologies to overcome these inherent drawbacks of conventional approaches. The proposed method provides instantaneous solutions to a spectrum of complex, multidimensional optimization problems. A micromixer case study is employed to demonstrate this methodology. An
agent, operating on a Deep Reinforcement Learning (DRL) architecture, serves as the optimizer to explore the relationships between key problem parameters. This optimizer interacts with an environment constituted by a parametric Physics-Informed Neural Network (PINN), which responds to the
agent's actions at a significantly higher speed than traditional numerical methods. The
agent's objective, conditioned on the Schmidt number is to discover the optimal
geometric and physical parameters that maximize the micromixer's efficiency. After training the
agent across a wide range of Schmidt numbers, we analyzed the resulting optimal designs. Across this entire spectrum, the achieved efficiency was consistently greater than the baseline, normalized value. The maximum efficiency occurred at a Schmidt number of 13.3, demonstrating an improvement of approximately 32%. Finally, a comparative analysis with a Genetic
Algorithm was conducted under equivalent conditions to underscore the advantages of the proposed method.
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All authors Meraj Hassanzadeh, Ehsan Ghaderi, Mohamad Ali Bijarchi, Siamak Kazemzadeh Hannani
Atomic Physics
Dual Magnetic and Electric Dipole Symmetry: Pseudo Angular Momentum in Parity Space and the Electric Landé $g$-Factor
Michael E. Tobar
Electric dipole moments (EDMs) are sensitive probes of fundamental
symmetries and central to searches for physics beyond the Standard Model. We present a
symmetry-based, Zeeman-analogue operator framework that places
magnetic and electric dipole physics on parallel footing under electromagnetic duality, and introduce a polar-sector pseudo-angular-momentum degree of freedom in parity space together with an associated electric Landé factor that organizes induced orbital dipoles. Following Ohanian's effective-current formulation of the Zeeman effect, we construct its electric dual: the wavefunction's microscopic polarization admits an equivalent effective
magnetic probability-current representation, providing a field-equivalence description of parity-mixed charge displacement. In this notation the total EDM expectation takes the unified form $\langle \hat{\vec d}_{\rm tot}\rangle= d_B(g_E\,\frac{\langle \hat{\vec J}_p\rangle}{\hbar}+ g_E^{e}\,\frac{\langle \hat{\vec S}\rangle}{\hbar})$, with $g_E^{e}=\frac{2d_{\rm int}}{d_B}$, where $\hat{\vec J}_p$ captures Stark-induced pseudo-angular momentum and $\hat{\vec S}$ encodes any intrinsic (
spin-aligned) EDM $d_{\rm int}$ from
symmetry-violating interactions. We define a natural electric dipole unit (the “Bohr EDM”) as $d_B \equiv e a_0=\frac{2\mu_B}{c\alpha}$ ($a_0$ the Bohr radius and $\mu_B$ the Bohr magneton). As a canonical analytic
benchmark, we show in the hydrogenic problem that a static electric field couples within a fixed $n$
manifold through the scaled Runge–Lenz structure, yielding a compact Landé-like description and reproducing the Stark doublet (e.g.\ $|\langle d_{\rm orb}\rangle|=3d_B$ for the $2s$–$2p_{m=0}$ mixing).
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Optics
Spatiotemporal Tracking of Persistent, Localized Speckles in Turbulent Atmospheric Propagation
Travis M. Crumpton and Luat T. Vuong
Light propagation through
turbulence produces speckles, whose ensemble behavior is typically characterized by snapshot intensity statistics. Here, we track the spatiotemporal
evolution of individual speckles and quantify fragmentation, localization, and persistence under different diffraction and
turbulence scales. Beam fragmentation coincides with complete spatial decorrelation defined by the magnitude-squared coherence. Fragmentation occurs closer to the source for larger beams, which indicates that smaller beams are more robust to decoherence. Subsequently, speckles are both spatially localized and persistent over distances significantly longer than their associated Rayleigh length. The combination of localization and persistence impacts the statistics of light relevant to their long-distance signaling and sensing.
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Chemical Physics
Kolmogorov-Arnold Chemical Reaction Neural Networks for learning pressure-dependent kinetic rate laws
Benjamin C. Koenig and Sili Deng
Chemical Reaction Neural Networks (CRNNs) have emerged as an interpretable machine learning framework for discovering reaction kinetics directly from data, while strictly adhering to the Arrhenius and mass action laws. However, standard CRNNs cannot represent pressure-dependent or mixture-based rate behavior, which is critical in many combustion and chemical systems and typically requires empirical falloff formulations such as Troe or SRI, or data-based interpolation or
polynomial fits such as PLOG or Chebyshev
Polynomials. Here, we develop Kolmogorov-Arnold Chemical Reaction Neural Networks (KA-CRNNs) that generalize CRNNs by modeling each kinetic parameter as a learnable function of third-body concentrations using Kolmogorov-Arnold activations. This structure maintains the Arrhenius and mass action interpretability and physical constraints of a vanilla CRNN while enabling assumption-free inference of global and
collider-specific pressure effects directly from data. Two proof-of-concept reaction studies are presented to highlight the capability of KA-CRNNs to accurately reproduce pressure-dependent and
collider-specific kinetics across a range of temperatures, pressures, and bath gas mixtures, extracting meaningful and generalizable models from sparse training data and significantly outperforming interpolative approaches (2.88x reduction in MSE). The framework establishes a foundation for data-driven discovery of extended kinetic behaviors in complex reacting systems, advancing interpretable and physics-constrained approaches for chemical model inference.
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Optics
Effective SU(2) gadget: holonomic walk on higher-order Poincaré sphere
Mohammad Umar, Sarvesh Bansal and Paramasivam Senthilkumaran
In a manner commensurate to the SU(2) gadget for the Poincaré sphere, which involves a combination of two quarter-wave plates and one half-wave plate regardless of their sequential order, an analogous construct for the higher-order Poincaré sphere had long remained elusive. To address this, we recently demonstrated, by modifying Euler-angle parameterization, that an optical gadget consisting of two quarter-wave $q$-plates and one half-wave $q$-plate, each endowed with the same topological charge $q$, operates as a viable SU(2) gadget for the higher-order Poincaré sphere, contingent upon the fulfillment of the holonomy condition. This work presents the controlled
navigation on the higher-order Poincaré sphere through the proposed architecture, formulated under the concept of an effective waveplate and thus can be referred to as an effective SU(2) gadget. The notion of an effective waveplate refers to a coaxial arrangement of multiple waveplates that, under specific constraints, can act as a single waveplate. In this gadget, the relative
alignment of the offset angles of the constituent $q$-plates emerges as the decisive parameter governing systematic
navigation on the higher-order Poincaré sphere. This study bear direct relevance to the deterministic control and engineering of structured light, encompassing polarization singularities, vector
vortex beams and topological optical fields. Moreover, these results holds potential applications in the contemporary research frontiers in singular optics,
spin-orbit photonics and
quantum communication.
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Plasma Physics
Response of a magnetically diverted tokamak plasma to a resonant magnetic perturbation
R. Fitzpatrick
The safety-factor profile of a magnetically diverted tokamak
plasma diverges logarithmically as the
magnetic separatrix (a.k.a. the last closed
magnetic flux-surface) is approached. At first sight, this suggests that, when determining the response of such a
plasma to a static, externally generated, resonant
magnetic perturbation (RMP), it is necessary to include an infinite number of rational
magnetic flux-surfaces in the calculation, the majority of which lie very close to the separatrix. In fact, when finite
plasma resistivity is taken into account, this turns out not to be the case. Instead, it is only necessary to include rational surfaces that lie in the region 0<Psi<Psi_c, where Psi is the normalized poloidal
magnetic flux, and Psi_c<1 can be calculated from the edge
plasma parameters. It is estimated that Psi_c= 0.9985 for an n=1 RMP, and Psi_c=0.9952 for an n=4 RMP, in a typical JET H-mode
plasma.
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Fluid Dynamics · Cross-listed from cond-mat.stat-mech
Random initial data and average shock time in the Fermi-Pasta-Ulam-Tsingou chain
Matteo Gallone, Ricardo Grande, Antonio Ponno et al. (+2 more)
We investigate the dynamics of the
Fermi–Pasta–Ulam–Tsingou chain with long-wavelength random initial data. When the energy per particle is small, thermal
equilibrium is not reached on a fast timescale and the system enters prethermalization. The formation of the prethermal state is characterized by the development of a Burgers-type shock and the onset of a turbulent-like spectrum with a time dependent exponent $\zeta(t)$ in the inertial range. We perform a significant step forward by demonstrating that these features are robust under generic long-wavelength random initial conditions. By employing advanced probabilistic techniques inspired by the works of Dudley and Talagrand, we derive a sharp asymptotic expression for the average shock time in the thermodynamic limit. For large $p$, this time scales as $(p \sqrt{\log p})^{-1}$, where $p$ is the number of excited modes proving that it is an intensive quantity up to a logarithmic correction in the size of the system.
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All authors Matteo Gallone, Ricardo Grande, Antonio Ponno, Stefano Ruffo, Erwan Druais
Applied Physics
Multimode structured neutron beams
Owen Lailey, Dusan Sarenac, Charles W. Clark et al. (+9 more)
The experimental realization of
neutron orbital angular momentum (OAM) states and
neutron Airy beams has opened new avenues for structured
neutron science in both materials characterization and fundamental physics. These additional degrees of freedom in scattering experiments enable the exploration of selection rules for
neutrons, the analysis of scattering properties in topological materials, and the generation of auto-focusing
neutron beams. In the effort to enhance the amount of spatial and angular-momentum information retrievable from a single measurement, and to overcome current phase-grating efficiency limits, here we demonstrate multimode structured
neutron beams that enable simultaneous access to multiple, well-defined OAM modes, and to hybrid combinations of OAM and Airy states. This multimode approach, analogous to wavelength- or OAM-multiplexing in optics, facilitates the efficient investigation of material scattering properties and
nuclear interactions with a
neutron source composed of a discretized OAM spectrum.
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All authors Owen Lailey, Dusan Sarenac, Charles W. Clark, David G. Cory, Lisa DeBeer-Schmitt, Huseyin Ekinci, Davis V. Garrad, Melissa E. Henderson, Michael G. Huber, Priyanka Vadnere, Kirill Zhernenkov, Dmitry A. Pushin
Fluid Dynamics
Resonant spectral cascade in Womersley flow triggered by arterial geometry
Khalid M. Saqr
Age-related arterial remodeling is dominated by progressive loss of elastic-fiber function and concomitant stiffening, and in many vascular beds it is also accompanied by measurable
geometric remodeling (e.g., elongation and tortuosity). These changes are clinically relevant because they modify pulsatile phase relationships, near-wall shear, and axial transport, yet the precise physical mechanisms by which geometry modulates spectral energy redistribution remain insufficiently resolved. While complex geometry is known to increase viscous resistance, its active role in modulating flow dynamics is not fully understood. Here we solve a mathematical model to show that arterial geometry can trigger a resonant transfer of energy to short-wavelength components of the flow. The investigation, conducted over a physiological range of Womersley numbers (Wo, a dimensionless measure of pulsation frequency), reveal a dual dynamic. The global wave energy consistently decays, confirmed by a negative growth rate (G < 0), indicating that the flow does not become exponentially unstable. However, a spectral broadening ratio (R), which quantifies the energy in high-wavenumber versus low-wavenumber modes, exhibits a sharp, non-monotonic peak at an intermediate Wo. This result identifies a resonant frequency at which geometry is maximally efficient at generating spectral complexity, even as the overall flow attenuates. These findings reframe the role of arterial geometry from a passive dissipator to an active modulator of the flow's spectral content, suggesting that spectral diagnostics could provide a sensitive marker for vascular health.
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Optics
L. Hallacy, D. Hallett, A. Fenzl et al. (+8 more)
We present a scalable method for electrically tuning multiple spatially separated
quantum dots embedded in photonic
crystal waveguides. Ion implantation into the top p-doped layer of a p-i-n diode creates high-resistivity tracks, providing electrical isolation between adjacent regions. Unlike physical etching, this method preserves the guided-mode profile of the photonic
crystal without introducing significant scattering, limiting refractive index perturbations to below 0.001 with 0.01% additional loss. In contrast, physical etching can reduce single-band transmission by more than 30% for an etch width of 100 nm. We demonstrate the applicability of our approach using
quantum dots embedded in a glideplane photonic
crystal waveguide, controlling the detuning between different
spin-state combinations of two highly
chiral quantum dots coupled to the same mode. Second-order
photon correlation measurements provide a sensitive probe of the chirality-dependent
photon statistics, which are in good agreement with a waveguide-QED master equation model. Our results mark an important step towards scalable, multi-emitter architectures for
chiral quantum networks.
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All authors L. Hallacy, D. Hallett, A. Fenzl, N.J. Martin, R. Dost, A.Verma, J. Fletcher, I. Farrer, L. Antwis, M.S. Skolnick, L.R. Wilson
Chemical Physics
Optimized tandem catalyst patterning for CO$_2$ reduction flow reactors
Jack Guo, Thomas Roy, Nitish Govindarajan et al. (+7 more)
Tandem catalysis involves two or more catalysts arranged in proximity within a single reaction vessel, with the aim of synergistically aligning the catalysts' reaction pathways to maximize overall system performance. This study presents a proof of concept showing the integration of continuum transport modeling with design optimization in a simplified two-dimensional flow reactor setup for electrochemical CO$_2$ reduction. Ag catalysts provide the CO$_2$ $\rightarrow$ CO reaction capability, and Cu catalysts provide the CO $\rightarrow$ high-value products reaction capability. Given a set of input parameters, the optimization
algorithm uses adjoint methods to modify the Ag/Cu surface patterning in order to maximize the current density toward high-value products, such as ethylene. The optimized designs yield significant performance enhancement especially at more negative applied voltages (i.e., stronger surface reactions) and for larger numbers of patterning sections. For an applied voltage of $-1.7$ V vs. SHE, the $12$-section optimized design increases the current density towards ethylene by up to $65$% compared to the unoptimized $2$-section design. For the optimized cases, observed differences in the production and consumption of CO (the key intermediate species) and minimized zones of low CO reactant surface concentration on Cu sections explain the improved reactor performance.
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All authors Jack Guo, Thomas Roy, Nitish Govindarajan, Joel B. Varley, Jonathan Raisin, Jinyoung Lee, Ji-Wook Jang, Dong Un Lee, Thomas F. Jaramillo, Tiras Y. Lin
Accelerator Physics
CW SRF Gun generating beam parameters sufficient for CW hard-X-ray FEL
Nikhil Bachhawat, Vladimir N. Litvinenko, Jean C. Brutus et al. (+7 more)
SRF CW accelerator constructed for Coherent electron Cooling (CeC) Proof-of-principle (POP) experiment at Brookhaven National Laboratory has frequently demonstrated record parameters using 1.5 nC 350 ps long electron bunches, typically compressed to FWHM of 30 ps using ballistic compression. We report experimental demonstration of CW electron beam with parameters fully satisfying requirements for hard X-ray FEL and significantly exceeding those demonstrated by APEX LCLS II electron gun. This was achieved using a 10-year-old SRF gun with a modest accelerating gradient of $\sim$15 MV/m, a bunching cavity followed by ballistic compression to generate 100 pC, $\sim$15 ps FWHM electron bunches with a normalized slice emittance of $\sim$0.2 mm-mrad and a normalized projected emittance of $\sim$0.25 mm-mrad. Hence, in this paper, we present an alternative method for generating CW electron beams for hard-X-ray FELs using existing and proven accelerator technology. We present a description of the accelerator system settings, details of projected and slice emittance measurements as well as relevant beam dynamics simulations.
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All authors Nikhil Bachhawat, Vladimir N. Litvinenko, Jean C. Brutus, Luca Cultrera, Patrick Inacker, Yichao Jing, Jun Ma, Igor Pinayev, John Skaritka, Gang Wang
Applied Physics
Passive Acoustic Monitoring of Underwater Well Leakages with Machine Learning: A Review
Guanlin Zhu, Zechun Deng, Jiaxin Shen et al. (+1 more)
Abandoned oil and gas wells pose significant environmental risks due to the potential leakage of hydrocarbons, brine and chemical pollutants. Detecting such leaks remains extremely challenging due to the weak acoustic emission and high ambient noise in the deep sea. This paper reviews the application of passive sonar systems combined with artificial intelligence (AI) in
underwater oil and gas leak detection. The advantages and limitations of traditional monitoring methods, including fibre optic, capacitive and pH sensors, are compared with those of passive sonar systems. Advanced AI methods that enhance signal discrimination, noise suppression and data interpretation capabilities are explored for leak detection. Emerging solutions such as embedded AI analogue-to-digital converters (ADCs), deep learning-based denoising networks and semantically aware
underwater optical communication (UOC) frameworks are also discussed to overcome issues such as low signal-to-noise ratio (SNR) and transmission instability. Furthermore, a hybrid approach combining non-negative
matrix factorisation (NMF), convolutional neural networks (CNN) and temporal models (GRU, TCN) is proposed to improve the classification and quantification accuracy of leak events. Despite challenges such as data scarcity and environmental change, AI-assisted passive sonar has shown great potential in real-time, energy-efficient and non-invasive
underwater monitoring, contributing to sustainable environmental protection and maritime safety management.
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All authors Guanlin Zhu, Zechun Deng, Jiaxin Shen, Junchi Yang
Accelerator Physics
Nanosecond Radio-Frequency Pulse Driven Photogun for Very Hard X-ray Free-electron Laser
Wei Hou Tan, River Robles, Juan Hernandez et al. (+2 more)
One pathway to producing high brightness electron beams is to use a
radio-frequency (rf) driven high field photogun to rapidly accelerate photoemitted electrons to the relativistic regime and preserve the brightness. However, the highest attainable field is limited by rf breakdowns of materials used in a photogun. Shortening rf pulse duration feeding into a photogun provides a viable pathway to achieve high field and prevent rf breakdowns. Here we propose and investigate Compressed Ultrashort Pulse Injector Demonstrator (CUPID), a nanosecond rf pulses driven photogun powered by a klystron and rf pulse compression system capable of achieving 300 MW at 20 ns duration, to produce bright electron beams with high electric field. We first introduce the design of the CUPID photogun and its expected rf performance at 500 MV/m driven by high power nanosecond rf pulses, followed by beam dynamics studies showing its capability for producing bright electron beams with 60 nm emittance when forming a photoinjector with a superconducting solenoid and downstream accelerating structures. Finally, we show a proof-of-concept start-to-end simulation of the CUPID photoinjector paired with the existing Linac Coherent Light Source (LCLS) copper accelerator free-electron
laser (FEL) to demonstrate achievable mJ pulse energy very hard x-ray
photons at 40 keV or higher.
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All authors Wei Hou Tan, River Robles, Juan Hernandez, Emilio Alessandro Nanni, Ankur Dhar
Chemical Physics
Seniority-Zero Canonical Transformation Theory: Reducing Truncation Error with Late Truncation
Daniel F. Calero-Osorio and Paul W. Ayers
We show how to add the effects of residual electron correlation to a reference seniority-zero wavefunction by making a
unitary transformation of the true electronic
Hamiltonian into seniority-zero form. The transformation is treated via the Baker Campbell Hausdorff (BCH) expansion and the seniority-zero structure of the reference is exploited to evaluate the first three commutators exactly; the remaining contributions are handled with a recursive commutator approximation, as is typical in canonical transformation methods. By choosing a seniority-zero reference and using parallel computation, this method is practical for small- to medium-sized systems. Numerical tests show high accuracy, with errors $\sim 10^{-4}$ Hartree.
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Fluid Dynamics
Shocks Under Control: Taming Transonic Compressible Flow over an RAE2822 Airfoil with Deep Reinforcement Learning
Trishit Mondal, Ricardo Vinuesa and Ameya D. Jagtap
Active flow control of compressible transonic shock-boundary layer interactions over a two-dimensional RAE2822 airfoil at Re = 50,000 is investigated using deep reinforcement learning (DRL). The flow field exhibits highly unsteady dynamics, including complex shock-boundary layer interactions, shock oscillations, and the generation of Kutta waves from the trailing edge. A high-fidelity CFD solver, employing a fifth-order spectral discontinuous Galerkin scheme in space and a strong-stability-preserving Runge-Kutta (5,4) method in time, together with adaptive mesh refinement capability, is used to obtain the accurate flow field. Synthetic jet actuation is employed to manipulate these unsteady flow features, while the DRL
agent autonomously discovers effective control strategies through direct interaction with high-fidelity compressible flow simulations. The trained controllers effectively mitigate shock-induced separation, suppress unsteady oscillations, and manipulate aerodynamic forces under transonic conditions. In the first set of experiments, aimed at both drag reduction and lift enhancement, the DRL-based control reduces the average drag coefficient by 13.78% and increases lift by 131.18%, thereby improving the lift-to-drag ratio by 121.52%, which underscores its potential for managing complex flow dynamics. In the second set, targeting drag reduction while maintaining lift, the DRL-based control achieves a 25.62% reduction in drag and a substantial 196.30% increase in lift, accompanied by markedly diminished oscillations. In this case, the lift-to-drag ratio improves by 220.26%.
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Fluid Dynamics · Cross-listed from astro-ph.IM
General Implicit Runge-Kutta Integrators for Multifluid Gas-Dust Aerodynamic Drag
Giovanni Tedeschi-Prades, Til Birnstiel, Klaus Dolag et al. (+2 more)
The integration of aerodynamic drag is a fundamental step in simulating
dust dynamics in hydrodynamical simulations. We propose a novel integration scheme, designed to be compatible with Strang splitting techniques, which allows for the straightforward integration of external forces and hydrodynamic fluxes in general-purpose hydrodynamic simulation codes. Moreover, this solver leverages an analytical solution to the problem of drag acceleration, ensuring linear complexity even in cases with multiple
dust grain sizes, as opposed to the cubic scaling of methods that require a
matrix inversion step. This new General Implicit Runge-Kutta integrator (GIRK) is evaluated using standard
benchmarks for
dust dynamics such as DUSTYBOX, DUSTYWAVE, and DUSTYSHOCK. The results demonstrate not only the accuracy of the method but also the expected scalings in terms of accuracy, convergence to
equilibrium, and execution time. GIRK can be easily implemented in hydrodynamical simulations alongside hydrodynamical steps and external forces, and is especially useful in simulations with a large number of
dust grain sizes.
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All authors Giovanni Tedeschi-Prades, Til Birnstiel, Klaus Dolag, Barbara Ercolano, Mark Hutchison
Atomic Physics · Cross-listed from hep-ph
Quantum Calculations of the Cavity Shift in Electron Magnetic Moment Measurements
Hannah Day, Roni Harnik, Yonatan Kahn et al. (+2 more)
The measurement of the anomalous electron
magnetic moment $g-2$ through
quantum transitions of a single trapped electron is the most stringent test of
quantum field theory. These experiments are now so precise that they must account for the effects of the cavity containing the electron. Classical calculations of this "cavity shift" must subtract the electron's divergent self-field, and thus require knowledge of the exact Green's function for the cavity's electromagnetic field. We perform the first fully
quantum calculation of the cavity shift in a closed cavity, which instead involves subtracting linearly divergent cavity mode sums and integrals. Using contour integration methods, we find perfect agreement with existing classical results for both spherical and cylindrical cavities, justifying their current use. Moreover, our mode-based results can be naturally generalized to account for systematic effects, necessary to push future measurements to the next order of magnitude in precision.
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All authors Hannah Day, Roni Harnik, Yonatan Kahn, Shashin Pavaskar, Kevin Zhou
History and Philosophy of Physics
From Heisenberg and Schrödinger to the P vs. NP Problem
Galina Weinstein
This essay offers an epistemological reinterpretation of the foundational divide between
matrix mechanics and wave mechanics. Though formally equivalent, the two theories embody distinct modes of knowing: procedural construction and recognitional verification. These epistemic architectures anticipate, in philosophical form, the logical asymmetry expressed by the P versus NP problem in computational complexity. Here, the contrast between efficient generation and efficient recognition is treated not as a mathematical taxonomy but as a framework for understanding how knowledge is produced and validated across physics, computation, and cognition. The essay reconstructs the mathematical history of
quantum mechanics through the original derivations of Werner Heisenberg, Max Born, Pascual Jordan, Paul Dirac, Erwin Schrödinger, Paul Ehrenfest, and Wolfgang Pauli, culminating in John von Neumann's unification of both approaches within the formalism of
Hilbert space. By juxtaposing Heisenberg's algorithmic formalism with Schrödinger's representational one, it argues that their divergence reveals a structural feature of scientific
reasoning itself-the enduring tension between what can be procedurally constructed and what can only be recognized.
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Computational Physics · Cross-listed from cond-mat.quant-gas
Toward fast, accurate and robust AI prediction of ground states in rotating BEC
Zhizhong Kong, Jerry Zhijian Yang, Cheng Yuan et al. (+1 more)
We propose an unsupervised deep learning approach for computing the ground state (GS) of rotating Bose-Einstein condensation. To minimize the energy under a mass constraint, our approach introduces two key and novel ingredients: a normalized loss function that exactly enforces the mass constraint, and a training strategy named virtual rotation acceleration that is essential for avoiding local minima and guiding the learning process to the correct quantized
vortex phase. Extensive numerical experiments demonstrate the proposed approach as an effective and accurate method to predict GS across physical conditions–from slow to fast rotation and from isotropic to anisotropic confinement. Through further
distillation, we establish a unified operator network capable of efficiently generalizing physical parameters across different phases. It enables rapid GS predictions while correctly capturing phase transitions and is applied for inverse problems.
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All authors Zhizhong Kong, Jerry Zhijian Yang, Cheng Yuan, Xiaofei Zhao
Applied Physics
Entanglement-driven responses through multiscale 3D-printed knits
Bradley Cline, Catherine Bai, Sehui Jeong et al. (+5 more)
For their resilience and toughness, filamentous entanglements are ubiquitous in both natural and engineered systems across length scales, from
polymer-chain- to collagen-networks and from cable-net structures to forest canopies. Textiles are an everyday manifestation of filamentous
entanglement: the remarkable resilience and toughness in knitted fabrics arise predominately from the
topology of interlooped yarns. Yet most architected materials do not exploit
entanglement as a design primitive, and industrial knitting fixes a narrow set of patterns for manufacturability. Additive manufacturing has recently enabled interlocking structures such as chainmail,
knot and woven assemblies, hinting at broader possibilities for entangled architectures. The general challenge is to treat knitting itself as a three-dimensional architected material with predictable and tunable mechanics across scales. Here, we show that knitted architectures fabricated additively can be recast as periodic entangled solids whose responses are both fabric-like and programmable. We reproduce the characteristic behavior of conventional planar knits and extend knitting into the third dimension by interlooping along three orthogonal directions, yielding volumetric knits whose stiffness and dissipation are tuned by prescribed pre-strain. We propose a simple scaling that unifies the responses across stitch geometries and constituent materials. Further, we realize the same
topology from centimeter to micrometer scales, culminating in the fabrication of what is, to our knowledge, the smallest knitted structure ever made. By demonstrating 3D-printed knits can be interpreted both as a traditional fabric, as well as a novel architected material with defined periodicity, this work establishes the dual nature of entangled filaments and paves the way towards a new form of material architectures with high degrees of
entanglement.
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All authors Bradley Cline, Catherine Bai, Sehui Jeong, Ling Xu, Yue Wang, James U. Surjadi, Carlos M. Portela, Tian Chen
Fluid Dynamics · Cross-listed from hep-th
The algebraic structure of the gradient expansion in linearised classical hydrodynamics
Sašo Grozdanov and Mile Vrbica
In this work, we systematically treat the ambiguities that generically arise in the gradient expansion of any hydrodynamic theory. While these ambiguities do not affect the physical content of the equations, they induce two types of transformations in the space of transport coefficients. The first type is known as the 'frame' transformations, and amounts to field redefinitions. The second type, which we introduce and formalise here, we term the 'on-shell' transformations. This identifies equivalence classes of hydrodynamic theories that provide an equally valid low-energy description of the underlying microscopic theory. We show that in any (classical) theory of hydrodynamics (at arbitrary order in derivatives), the action of such transformations on the dispersion relations and two-point correlation functions is universal. We explicitly construct invariants which can then be matched to a microscopic theory. Among them are, expectedly, the low-momentum expansions of the hydrodynamic modes. The (unphysical) gapped modes can, however, be added or removed at will. Finally, we show that such transformations assign a nilpotent Lie group to every hydrodynamic theory, and discuss the related algebraic properties underlying classical hydrodynamics.
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Applied Physics
Effect of shape on void growth: A coupled Extended Finite Element Method (XFEM) and Discrete Dislocation Plasticity (DDP) study
Muhammad Usman, Sana Waheed and Aamir Mubashar
Voids are one of the many material defects present at the microscopic length scale. They are primarily responsible for the formation of cracks and hence contribute to ductile fracture. Circular voids tend to deform into elliptical voids just before their coalescence to form cracks. The principle aim of this study is to investigate the effect of void shape on the micro-mechanism of void growth by using Discrete Dislocation Plasticity simulations. For voided
crystals, conventional DDP produces a continuous slip step throughout the material even if a dislocation escapes from a non-convex domain. To overcome this issue, the Extended Finite Element Method (XFEM) is used here to incorporate the displacement discontinuity. Different aspect ratios of elliptical voids are considered under uniaxial and biaxial deformation boundary conditions. The results suggest that voids having the largest surface area tend to have maximum growth rate as compared to void with lower surface area, i.e. "larger is faster". Under biaxial loading, a higher magnitude of strain hardening, and void growth rate are observed as compared to uniaxial loading. The results also suggest that the orientation of slip planes as well as voids, affect the overall plastic behavior of the voided-ductile material. Furthermore, circular void tends to induce minimum growth rate but have the maximum strain hardening effect as compared to other void shapes under both loading conditions. The results of this study provide a deeper understanding of ductile fracture with applications in manufacturing industry, aerospace industry and in the design of nano/micro-electromechanical devices i.e. NEMS/MEMS.
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Fluid Dynamics
Modeling Unsteady Aircraft Aerodynamics Using Lorenz Attractor: A Reduced-Order Approach for Wing Rock
Marcel Menner and Eugene Lavretsky
This paper presents a novel modeling approach for unsteady aircraft airflow, leveraging the Lorenz attractor framework. The proposed model is based on the force distribution exerted by a lift-generating wing on the surrounding fluid. It distinguishes between turbulent and nominal components of the force distribution, with the nominal force distribution modeled to peak at the wing and decay linearly into the free stream. This separation allows the turbulent component to be represented by a transport equation that is influenced by flight conditions, specifically dynamic pressure and angle of attack. Consequently, the Navier-Stokes equations, along with the
turbulence transport equation, can be transformed into a reduced-order model characterized by three scalar ordinary differential equations - similar to the Lorenz attractor. This resulting system effectively captures chaotic behavior, facilitating the exploration of complex dynamics without the computational demands of solving the full Navier-Stokes equations. A simulation trade study is conducted that models wing rock phenomena at high angles of attack, demonstrating the effectiveness of the proposed approach in capturing the intricate dynamics of unsteady aircraft aerodynamics.
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Computational Physics
Walsh-Hadamard Neural Operators for Solving PDEs with Discontinuous Coefficients
Giorgio M. Cavallazzi, Miguel Pérez Cuadrado and Alfredo Pinelli
Neural operators have emerged as powerful tools for learning solution operators of partial differential equations (PDEs). However, standard spectral methods based on
Fourier transforms struggle with problems involving discontinuous coefficients due to the Gibbs phenomenon and poor representation of sharp interfaces. We introduce the Walsh-Hadamard Neural Operator (WHNO), which leverages Walsh-Hadamard transforms-a spectral basis of rectangular wave functions naturally suited for piecewise constant fields-combined with learnable spectral weights that transform low-sequency Walsh coefficients to capture global dependencies efficiently. We validate WHNO on three problems: steady-state Darcy flow (preliminary validation), heat conduction with discontinuous thermal conductivity, and the 2D Burgers equation with discontinuous initial conditions. In controlled comparisons with
Fourier Neural Operators (FNO) under identical conditions, WHNO demonstrates superior accuracy with better preservation of sharp solution features at material interfaces. Critically, we discover that weighted ensemble combinations of WHNO and FNO achieve substantial improvements over either model alone: for both heat conduction and Burgers equation, optimal ensembles reduce mean squared error by 35-40 percent and maximum error by up to 25 percent compared to individual models. This demonstrates that Walsh-Hadamard and
Fourier representations capture complementary aspects of discontinuous PDE solutions, with WHNO excelling at sharp interfaces while FNO captures smooth features effectively.
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