Physics and Society
A differentiable model of supply-chain shocks
Saad Hamid, José Moran, Luca Mungo et al. (+2 more)
Modelling how shocks propagate in supply chains is an increasingly important challenge in economics. Its relevance has been highlighted in recent years by events such as Covid-19 and the Russian invasion of Ukraine.
Agent-based models (ABMs) are a promising approach for this problem. However, calibrating them is hard. We show empirically that it is possible to achieve speed ups of over 3 orders of magnitude when calibrating ABMs of supply networks by running them on GPUs and using automatic differentiation, compared to non-differentiable baselines. This opens the door to scaling ABMs to model the whole global supply network.
Read the full abstract ▾
All authors Saad Hamid, José Moran, Luca Mungo, Arnau Quera-Bofarull, Sebastian Towers
Data Analysis and Statistics · Cross-listed from hep-ex
Gradient-descent-based reconstruction for muon tomography based on automatic differentiation in PyTorch
Jean-Marco Alameddine, Felix Sattler, Maurice Stephan et al. (+1 more)
Muon scattering
tomography is a well-established, non-invasive imaging technique using
cosmic-ray
muons. Simple
algorithms, such as PoCA (Point of Closest Approach), are often utilized to reconstruct the volume of interest from the observed
muon tracks. However, it is preferable to apply more advanced reconstruction
algorithms to efficiently use the sparse
muon statistics that are available. One approach is to formulate the reconstruction task as a likelihood-based problem, where the material properties of the reconstruction volume are treated as an optimization parameter. In this contribution, we present a reconstruction method based on directly maximizing the underlying likelihood using automatic differentiation within the PyTorch framework. We will introduce the general idea of this approach, and evaluate its advantages over conventional reconstruction methods. Furthermore, first reconstruction results for different scenarios will be presented, and the potential that this approach inherently provides will be discussed.
Read the full abstract ▾
All authors Jean-Marco Alameddine, Felix Sattler, Maurice Stephan, Sarah Barnes
Chemical Physics
Fast Evaluation of Unbiased Atomic Forces in ab initio Variational Monte Carlo via the Lagrangian Technique
Kousuke Nakano, Stefano Battaglia and Jürg Hutter
Ab initio
quantum Monte Carlo (QMC) methods are state-of-the-art electronic structure calculations based on highly parallelizable
stochastic frameworks for accurate solutions of the many-body Schrödinger equation, suitable for modern many-core supercomputer architectures. Despite its potential, one of the major drawbacks that still hinders QMC applications, especially when targeting dynamical properties of large systems or extensive
datasets, is the lack of an affordable method to compute atomic forces that are consistent with the corresponding potential energy surfaces (PESs), also known as unbiased atomic forces. Recently, one of the authors in the present paper proposed a way to obtain unbiased forces with the Jastrow-correlated Slater determinant ansatz, where the determinant part is frozen to the values obtained by a mean-field method, such as Density Functional Theory. However, the proposed method has a significant drawback for its applications: for a system with $N$
nuclei, one requires 6$N$ additional DFT calculations to get unbiased forces. This paper presents a way to replace the 6$N$ DFT calculations with a single coupled-perturbed Kohn-Sham calculation, following the so-called Lagrangian technique established in
quantum chemistry. We also demonstrate that the developed unbiased VMC force calculation improves not only the consistency with PESs, but also its accuracy, by investigating three molecules from the rMD17
benchmark set, and comparing the unbiased VMC forces with those obtained by CCSD(T) calculations. We found that the bare VMC forces are biased from the CCSD(T) ones, while the unbiased ones give values closer to those of the CCSD(T) ones. Our
benchmark test also reveals that the unbiased VMC forces yield very consistent values with hybrid and meta GGAs, but do not necessarily yield values that are very close to those of CCSD(T).
Read the full abstract ▾
Optics · Cross-listed from quant-ph
Scaling behavior of dissipative systems with imaginary gap closing
Jinghui Pi, Xingli Li and Yangqian Yan
Point-gap
topology, characterized by spectral winding numbers, is crucial to non-Hermitian topological phases and dramatically alters real-time dynamics. In this paper, we study the
evolution of
quantum particles in dissipative systems with imaginary gap closing, using the saddle-point approximation method. For trivial point-gap systems, imaginary gap-closing points can also be saddle points. This leads to a single power-law decay of the local Green's function, with the asymptotic scaling behavior determined by the order of these saddle points. In contrast, for nontrivial point-gap systems, imaginary gap-closing points do not coincide with saddle points in general. This results in a dynamical behavior characterized by two different scaling laws for distinct time regimes. In the short-time regime, the local Green's function is governed by the dominant saddle points and exhibits an asymptotic exponential decay. In the long-time regime, however, the dynamics is controlled by imaginary gap-closing points, leading to a power-law decay envelope. Our findings advance the understanding of
quantum dynamics in dissipative systems and provide predictions testable in future experiments.
Read the full abstract ▾
Atomic Physics
Restricted-Geometry Quantum Models Beyond Atoms: Application of the Eckhardt-Sacha approach to NSDI in Diatomic Systems
Lars C. Bannow, Jan H. Thiede, Michał Ogryzek et al. (+2 more)
We present a (1+1)-dimensional
quantum model designed to describe nonsequential double ionization (NSDI) in homonuclear diatomic molecules exposed to strong linearly polarized
laser fields. Extending the restricted-geometry framework previously developed for atomic systems by Eckhardt and Sacha, our approach captures key features of NSDI, including the characteristic knee structure in double ionization yields. Despite its simplifying assumptions, the model shows good agreement with experimental data and proves particularly suitable for systems with $\sigma$-type orbital
symmetry. It offers a computationally efficient tool for exploring multi-electron dynamics in molecular systems.
Read the full abstract ▾
All authors Lars C. Bannow, Jan H. Thiede, Michał Ogryzek, Dmitry K. Efimov, Jakub S. Prauzner-Bechcicki
Chemical Physics
Complex-Energy Second-Order Approximate Coupled-Cluster Methods for Electronic Resonances
Cansu Utku, Garrette Pauley Paran and Thomas-C. Jagau
Electronic resonances are metastable states with finite lifetimes, encountered in processes such as photodetachment, electron transmission, and Auger decay. Resonances appear in Hermitian
quantum mechanics as increased density of states in the continuum rather than as discrete energy levels. To describe resonances accurately, including their coupling to the continuum, methods based on non-Hermitian
quantum mechanics can be used, which yield complex energies. In this work, we combine the complex absorbing potential (CAP) and complex basis functions (CBF) techniques with the RI-CC2 method. The second-order coupled cluster method (CC2) offers a good balance between accuracy and computational cost by approximating equation-of-motion coupled-cluster singles and doubles (EOM-CCSD) theory, making it suitable for studying of electronic resonances in larger molecules. The resolution-of-the-identity (RI) approximation further reduces computational demands without significant loss in accuracy. We investigate the numerical performance of the new complex-energy RI-CC2 methods focusing on temporary anions. Negative electron affinities and decay widths can be computed using the electron-attachment (EA) variant of RI-CC2. For N2, C2H4, CH2O, and HCOOH, EA-CC2 yields affinities about 0.1-0.2 eV smaller than EOM-EA-CCSD, while deviations reach 0.5 eV for larger anions such as uracil, naphthalene, cyanonaphthalene, and pyrene. As a result of these trends, EA-CC2 is in better agreement with experiment for the negative electron affinities than EOM-EA-CCSD for all studied anions. The corresponding resonance widths from EA-CC2 calculations are about 0.05-0.25 eV smaller compared to EOM-EA-CCSD. Semi-empirical
spin-scaling increases electron affinities by 0.3-0.5 eV and broadens resonance widths, improving the agreement with EOM-EA-CCSD but worsening the agreement with experiment.
Read the full abstract ▾
Atomic Physics
Rotational Splittings in Diatomic Molecules of Interest to Searches for New Physics
Ayaki Sunaga and Timo Fleig
Diatomic molecules with an energetically low-lying $^3 \Delta_1$ state are attractive platforms to detect new physics beyond the Standard Model, such as parity- and time-reversal violating phenomena. One of the advantages of using a $^3 \Delta_1$ state is its tiny $\Lambda$-splitting due to the coupling between the electronic and rotational angular momenta, which facilitates polarizing the molecules in small external electric fields. Theoretical estimation of the magnitude of the $\Lambda$-splitting is helpful for planning new experiments. In this study, we present a theoretical model to calculate the $\Lambda$-splitting. Our model integrates the relativistic four-component wavefunction and the traditional rotational
Hamiltonian based on Hund's case (a). The multireference character of the wavefunction is taken into account. Our calculations for PtH and ThF$^+$ molecules qualitatively agree with experiment. The $\Lambda$-splitting of TaO$^+$ for the rotational ground state is predicted to be around 9 kHz. This tiny splitting can reduce the systematic uncertainty, but in a practical experiment, it may cause depolarization during rotation ramp-up.
Read the full abstract ▾
Computational Physics · Cross-listed from cond-mat.mtrl-sci
Systematic global structure search of bismuth-based binary systems under pressure using machine learning potentials
Hayato Wakai, Shintaro Ishiwata and Atsuto Seko
Machine learning potentials (MLPs) have significantly advanced global
crystal structure prediction by enabling efficient and accurate property evaluations. In this study, global structure searches are performed for 11 bismuth-based binary systems, including Na-Bi, Ca-Bi, and Eu-Bi, under pressures ranging from 0 to 20 GPa, employing
polynomial MLPs developed specifically for these systems. The searches reveal numerous compounds not previously reported in the literature and identify all experimentally known compounds that are representable within the explored configurational space. These results highlight the robustness and reliability of the current MLP-based structure search. The study provides valuable insights into the discovery and design of novel bismuth-based materials under both ambient and high-pressure conditions.
Read the full abstract ▾
Instrumentation and Detectors
Proof-of-concept of a xenon-based cryogenic heat pump demonstrator for future liquid xenon observatories
P. Schulte, D. Wenz, L. Althueser et al. (+7 more)
This manuscript details the proof-of-concept of a small-scale cryogenic heat pump demonstrator, a technology designed to enable high-flow xenon
distillation systems for the removal of $^{222}$Rn in future
liquid xenon observatories such as the XLZD experiment. The heat pump demonstrator operates on a left-turning Clausius-Rankine cycle, utilizing xenon as a phase-changing working medium. The design aims to fully hermetically separate the heat pump from the radon removal system, simplifying material cleanliness and maintenance compared to currently operating systems. Two demonstration tests were conducted at nominal pressures of $3.3\,\mathrm{bar}$ and $4.3\,\mathrm{bar}$, utilizing a cold head and electrical heaters to mimic the behavior of a xenon
distillation system. In both measurements, the demonstrator achieved a cooling and heating power of $(118\pm3)\,\mathrm{W}$ and $(121\pm3)\,\mathrm{W}$, respectively. This is sufficient to operate a small
distillation system with a virtual purification mass flow of about $3.1\,\mathrm{kg/h}$, while consuming $386\pm1\,\mathrm{W}$ electrical power. Compered to currently operating applications using commercial cold heads driven by helium compressors, which typically require about $6\,\mathrm{kW}$ of electrical power, this is significantly lower. The presented proof-of-concept heat pump demonstrator is further put into perspective with the currently planned XLZD experiment using a simplified scaling model. This model indicates that a radon removal system with a purification mass flow of $1600\,\mathrm{kg/h}$ and a required cooling and heating power of about $60\,\mathrm{kW}$ each, will be sufficient to cover a variety of different detector masses and background conditions.
Read the full abstract ▾
All authors P. Schulte, D. Wenz, L. Althueser, R. Braun, V. Hannen, C. Huhmann, D. Koke, Y.-T. Lin, P. Unkhoff, C. Weinheimer
Optics · Cross-listed from quant-ph
Coherent control of quantum states by quadratically chirped short laser pulses
G.P. Djotyan, A.A. Avetisyan and A.P. Djotyan
We present a novel scheme for coherent manipulation of populations and robust creation of arbitrary coherent superposition of metastable states of a
quantum system with lambda configuration of operating energy levels using
laser pulses with a quadratically chirped carrier frequency. The case of a single broadband
laser pulse is considered, when the frequency spectrum of the pulse exceeds the frequency distance between the metastable energy levels of the system. The results of the dressed state analysis and numerical simulation are presented, demonstrating reliable and robust creation of an arbitrary coherent superposition of metastable states by changing the parameters of
laser pulses.
Read the full abstract ▾
Fluid Dynamics
A multiple-scales framework for branched channel filters
T. Fastnedge, C. J. W. Breward and I. M. Griffiths
Fibres shed from our clothes during a washing machine cycle constitute around 35% of the primary microplastics in our oceans. Current conventional dead-end washing machine filters clog relatively quickly and require frequent cleaning. We consider a new concept, ricochet separation, inspired by the feeding process of manta rays, to reduce the cleaning frequency. In such a device, some fluid is diverted through branched channels whilst particles ricochet off the wall structure, forcing them back into the main flow and then into the dead-end filter. In this paper, we consider a simple branched-channel filter structure beneath a high-Reynolds-number laminar flow, in the case where the branch separation is much larger than the thickness of the viscous boundary layer. We use multiple-scales techniques to derive an effective leakage boundary condition, which smooths out localised effects in the flow velocity and pressure that arise due to the discrete branched channels, and then use this boundary condition to explicitly determine the flow away from the boundary. We find that our explicit solution compares well with an analogous numerical solution containing a discrete set of branched channels. We further consider the behaviour of individual spherical particles in the device, with their trajectories determined via a simple force balance model with a wall-bounce condition. We explore the dependence of the fraction of particles that flow into the branched channels on the particle's Stokes number. The resulting combined model is able to predict the relationship between the efficiency of a ricochet filter device and the design and operating parameters, avoiding the need to conduct extensive numerically challenging simulations.
Read the full abstract ▾
Optics
The Geometry of Paraxial Vector Beams
Marco Ornigotti
This work unveils a novel and fundamental connection between structured light and topological field theory by showing how the natural geometrical setting for paraxial vector beams is that of a $SU(2)$ principal bundle over $\mathbb{R}^{2+1}$. Going beyond the usual high-order Poincaré sphere approach, we show how the nonseparable structure of polarisation and spatial modes in vector beams is naturally described by a non-Abelian Chern-Simons gauge theory. In this framework, we link the Chern-Simons charge to
spin-orbit coupling, and we propose a simple way to experimentally detect the presence of non-Abelian phases through Wilson lines. This new insight on vector beams opens new possibilities for realising and probing topological
quantum field theories using classical optics, as well as it lays the foundation for implementing topologically protected classical and
quantum information protocols with structured light.
Read the full abstract ▾
Atomic Physics
Enhanced One-Color-Two-Photon Resonant Ionization in Highly Charged Ions by Fine-Structure Effects
Moto Togawa, Chunhai Lyu, Chintan Shah et al. (+25 more)
Ultraintense pulses from X-ray free-electron
lasers can drive, within femtoseconds, multiple processes in the inner shells of atoms and molecules in all phases of matter. The ensuing complex ionization pathways of outer-shell electrons from the neutral to the final highly charged states make a comparison with theory enormously difficult. We resolve these pathways by preparing highly charged ions in an electron beam ion trap before exposing them to the pulsed radiation. This reveals how relativistic fine-structure effects shift electronic energies, largely compensate the core-screening potential, and enable the consecutive, resonant absorption of two quasi-monochromatic X-ray
photons that would generally be unfeasible. This doubly-resonant channel enhances the efficiency of two-
photon ionization by more than two orders of magnitude, dominating in this regime the nonlinear interaction of light and matter with possible application for future precision X-ray metrology.
Read the full abstract ▾
All authors Moto Togawa, Chunhai Lyu, Chintan Shah, Marc Botz, Joschka Goes, Jonas Danisch, Marleen Maxton, Kai Köbnick, Filipe Grilo, Pedro Amaro, Katharina Kubicek, Mohammed Sekkal, Awad Mohamed, Rebecca Boll, Alberto De Fanis, Simon Dold, Tommaso Mazza, Jacobo Montano, Nils Rennhack, Björn Senfftleben, Sergey Usenko, Zoltan Harman, Christoph H. Keitel, Maurice Leutenegger, Michael Meyer, Thomas Pfeifer, José R. Crespo López-Urrutia, Thomas M. Baumann
Fluid Dynamics
Settling dynamics of an oloid: experiments and simulations
Mees M. Flapper, Giulia Piumini, Roberto Verzicco et al. (+2 more)
This study presents a combined experimental and computational investigation of an oloid shaped particle settling in a quiescent fluid. The oloid, a unique convex shape with anisotropic geometry, provides a distinctive model for exploring how a particle's shape and orientation affect its settling dynamics. The settling oloids are tracked experimentally for Galileo numbers $48 \leq \text{Ga} \leq 5.4 \cdot 10^3$, using two particle sizes ($D_{\text{eq}}$ = 21.6 mm, and $D_{\text{eq}}$ = 10.8 mm). The density ratio between the particle and fluid $\Gamma$ = $\frac{\rho_p}{\rho_f}$ ranges from $1.11 \leq \Gamma \leq 1.30$ in the experiments. Computationally, the Galileo numbers $10 \leq \text{Ga} \leq 100$ are simulated, with $\Gamma = 2$. The experimental findings and numerical results are in good agreement, and give a consistent idea of the oloid settling dynamics. Our results indicate two distinct falling modes for the oloid, separated by Galileo number. The stable mode is characterised by a preferential orientation, with a rotation around the vertical axis, whereas the tumbling mode has randomly distributed orientation and rotation statistics. We characterise the falling velocity, orientation, and rotation dynamics of the oloids over a range of Galileo numbers. Additionally, the influence of the initial orientation is revealed to determine the rotation dynamics at low Galileo numbers.
Read the full abstract ▾
All authors Mees M. Flapper, Giulia Piumini, Roberto Verzicco, Sander G. Huisman, Detlef Lohse
Physics and Society · Cross-listed from cs.SI
Zoo of Centralities: Encyclopedia of Node Metrics in Complex Networks
Sergey Shvydun
Centrality is a fundamental concept in network science, providing critical insights into the structure and dynamics of complex systems such as social, transportation, biological and financial networks. Despite its extensive use, there is no universally accepted definition of centrality, leading to the development of a large variety of distinct centrality measures. These measures have grown so numerous that they resemble a 'zoo', each representing a unique approach to capturing node importance within a network. However, the increasing number of metrics being developed has led to several challenges, including issues of discoverability, redundancy, naming conflicts, validation and accessibility. This work aims to address these challenges by providing a comprehensive catalog of over 400 centrality measures, along with clear descriptions and references to original sources. While not exhaustive, this compilation represents the most extensive and systematic effort to date in organizing and presenting centrality measures. We also encourage readers to explore and contribute to the Centrality Zoo website at https://centralityzoo.github.io/, which provides an interactive platform for discovering and comparing centrality measures.
Read the full abstract ▾
Computational Physics · Cross-listed from eess.SY
Predicting and forecasting reactivity and flux using long short-term memory models in pebble bed reactors during run-in
Ian Kolaja, Ludovic Jantzen, Tatiana Siaraferas et al. (+1 more)
Pebble bed reactor (PBR) operation presents unique advantages and challenges due to the ability to continuously change the fuel mixture and excess reactivity. Each operation parameter affects reactivity on a different timescale. For example, fuel insertion changes may take months to fully propagate, whereas control rod movements have immediate effects. In-core measurements are further limited by the high temperatures, intense
neutron flux, and dynamic motion of the fuel bed. In this study, long short-term
memory (LSTM) networks are trained to predict reactivity, flux profiles, and power profiles as functions of operating history and synthetic batch-level pebble measurements, such as discharge burnup distributions. The model's performance is evaluated using unseen temporal data, achieving an $R^2$ of 0.9914 on the testing set. The capability of the network to forecast reactivity responses to future operational changes is also examined, and its application for optimizing reactor running-in procedures is explored.
Read the full abstract ▾
All authors Ian Kolaja, Ludovic Jantzen, Tatiana Siaraferas, Massimiliano Fratoni
Geophysics
Modelling dynamic strains on ice shelves resulting from flexural and extensional motions forced by ocean wave packets
Luke G. Bennetts and Jie Liang
The transient response of an ice shelf to an incident wave packet from the open ocean is studied with a model that allows for extensional waves in the ice shelf, in addition to the standard flexural waves. Results are given for strains imposed on the ice shelf by the incident packet, over a range of peak periods in the swell regime and a range of packet widths. In spite of the large difference in speeds of the extensional and flexural waves, it is shown that there is generally an interval of time during which they interact, and the coherent phases of the interactions generate the greatest ice shelf strain magnitudes. The findings indicate that incorporating extensional waves into models is potentially important for predicting the response of Antarctic ice shelves to swell, in support of previous findings based on frequency-domain analysis.
Read the full abstract ▾
Fluid Dynamics
Neural Network for Subgrid Turbulence Modeling for Large Eddy Simulations
Eduardo Vital, Jean-Marc Gratien, Yassine Ayoun et al. (+2 more)
When simulating multiscale systems, where some fields cannot be fully prescribed despite their effects on the simulation's accuracy, closure models are needed. This phenomenon is observed in turbulent fluid dynamics, where Large Eddy Simulations (LES) depict global behavior while
turbulence modeling introduces dissipation correspondent to smaller sub-grid scales. Recently, scientific machine learning techniques have emerged to address this problem by integrating traditional (physics-based) equations with data-driven (machine-learned) models, typically coupling numerical solvers with neural networks. This work presents a comprehensive workflow, encompassing high-fidelity data generation and post-processing, a priori learning, and a posteriori testing, where data-driven models enrich differential equations.
Read the full abstract ▾
All authors Eduardo Vital, Jean-Marc Gratien, Yassine Ayoun, Thibault Faney, Julien Bohbot
Medical Physics
A dispersal recolonisation 3D biofilm in vitro model based on co-assembled peptide amphiphiles and clinical wound fluid
Zhiquan Yu, Chenjia Zhao, Lingyun Xiong et al. (+9 more)
Chronic wound infections are sustained by dynamic 3D biofilm cycles involving maturation, dispersal, and recolonisation, yet existing in vitro models fail to reproduce these temporal and structural complexities. Here, we report a strategy that co-assembles a designed protease-inhibitory peptide amphiphile (PA-GF) with patient-derived wound fluid (WF) to reconstruct the complete biofilm life cycle in vitro. The PA-GF sequence incorporates an HWGF motif capable of binding and inhibiting
matrix metalloproteinase-9 (MMP-9), thereby preserving the integrity of recolonised biofilms under proteolytic stress. Co-assembling with WF generated a living material that faithfully mimicked the biochemical and mechanical microenvironment of chronic wounds, supporting the formation of stable 3D biofilms capable of dispersal and recolonisation. Furthermore, we established a controllable polymicrobial infection model and validated its translational relevance through antibiotic susceptibility profiling and spatial microbiological analyses. Notably, the antibiotic response patterns of the PA/WF-derived biofilms closely mirrored those observed in a rat wound infection in vivo model. Collectively, our findings demonstrate that co-assembling living materials can recapitulate the nutritional composition, 3D architecture, and recolonisation dynamics of in vivo infectious biofilms, offering a physiologically relevant and customisable platform for investigating chronic wound infections and accelerating anti-biofilm drug discovery.
Read the full abstract ▾
All authors Zhiquan Yu, Chenjia Zhao, Lingyun Xiong, Shanshan Su, Dawen Yu, Shilu Zhang, Yubin Ke, Hua Yang, Guo Zhang, Jiaming Sun, Nengqiang Guo, Yuanhao Wu
Instrumentation and Detectors
Optical studies of scintillation detectors for precision beta-energy measurements
S. Vanlangendonck, D. Atanasov, B. Blank et al. (+6 more)
This work presents optical calculations and simulations for scintillation detectors used in precision measurements of beta-particle energy spectra. Particular
attention is given to Cherenkov
photons and the impact of the light detection efficiency in the detector ensemble. We present an approach to estimate this light detection efficiency from the measured energy resolution of a detector. This is essential for the inclusion of scintillation
photons in optical tracking Monte-Carlo simulations. A method to account for possible saturation and cross-talk of silicon photo-multipliers is also discussed. The impact of these effects is quantified in terms of systematic shifts in the extraction of the Fierz interference term from measurements of beta-energy spectra using scintillator detectors.
Read the full abstract ▾
All authors S. Vanlangendonck, D. Atanasov, B. Blank, X. Fléchard, M. Kanafani, S. Lecanuet, O. Naviliat-Cuncic, N. Severijns, M. Versteegen
Atmospheric and Oceanic Physics
Improvement of a neural network convection scheme by including triggering and evaluation in present and future climates
Hugo Germain, Blanka Balogh, Olivier Geoffroy et al. (+1 more)
In this study, we improve a neural network (NN) parameterization of deep convection in the global atmosphere model ARP-GEM. To take into account the sporadic nature of convection, we develop a NN parameterization that includes a triggering mechanism that can detect whether deep convection is active or not within a grid-
cell. This new data-driven parameterization outperforms the existing NN parameterization in present
climate when replacing the original deep convection scheme of ARP-GEM. Online simulations with the NN parameterization run without stability issues. Then, this NN parameterization is evaluated online in a warmer
climate. We confirm that using relative humidity instead of the specific total humidity as input for the NN (trained with present data) improves the performance and generalization in warmer
climate. Finally, we perform the training of the NN parameterization with data from a warmer
climate and this configuration get similar results when used in simulations in present or warmer climates.
Read the full abstract ▾
All authors Hugo Germain, Blanka Balogh, Olivier Geoffroy, David Saint-Martin
Optics
Annular Channel Eigenmodes: A Physical-Layer Approach to Suppressing OAM Modal Crosstalk
Chenghao Li, Pengyang An, Ziao Huang et al. (+2 more)
Modal crosstalk is a fundamental limitation for orbital angular momentum (OAM)-based spatial-division multiplexing. Here, we introduce Annular Channel Eigenmodes (ACEs) - rigorously derived as the optimal band-limited solution for maximizing energy concentration within distinct annular channels. This approach reformulates the design as a Hermitian
eigenvalue problem, efficiently yielding optimal beams that are physically isolated in space. Numerical simulations demonstrate that under identical conditions, conventional Gaussian-enveloped perfect optical
vortices (POVs) exhibit an average modal crosstalk of -16 dB, whereas ACEs suppress crosstalk to nearly -30 dB. Moreover, the crosstalk suppression of ACEs continues to improve exponentially with increasing channel width, while that of POVs saturates at a fundamental limit. We experimentally generated ACEs and confirmed a 36% enhancement in energy confinement relative to POVs. ACEs thus provide a physically robust basis for high-fidelity, high-density OAM communications.
Read the full abstract ▾
All authors Chenghao Li, Pengyang An, Ziao Huang, Qiwen Zhan, Guanghui Yuan
Computational Physics · Cross-listed from nucl-th
Extrapolation to infinite model space of no-core shell model calculations using machine learning
Aleksandr Mazur, Roman Sharypov and Andrey Shirokov
An ensemble of neural networks is employed to extrapolate no-core shell model (NCSM) results to infinite model space for light
nuclei. We present a review of our neural network extrapolations of the NCSM results obtained with the Daejeon16 NN interaction in different model spaces and with different values of the NCSM basis parameter $\hbar\Omega$ for energies of
nuclear states and root-mean-square (rms) radii of
proton,
neutron and matter distributions in light
nuclei. The method yields convergent predictions with quantifiable uncertainties. Ground-state energies for $^{6}$Li, $^{6}$He, and the unbound $^{6}$Be, as well as the excited $(3^{+},0)$ and $(0^{+},1)$ states of $^{6}$Li, are obtained within a few hundred keV of experiment. The extrapolated radii of bound states converge well. In contrast, radii of unbound states in $^{6}$Be and $^{6}$Li do not stabilize.
Read the full abstract ▾
Applied Physics
kV-Class Lateral NiOx/GaN Super-Heterojunction Diode via Ammonia Molecular Beam Epitaxy (NH3-MBE)
Yizheng Liu, Zachary J. Biegler, Ashley E. Wissel-Garcia et al. (+2 more)
This work reports the demonstration of lateral p-NiOx/p-GaN/n-GaN-based super-heterojunction (SHJ) diodes using p-GaN with additional sputtered p-type nickel
oxide (NiOx) layers to realize charge-balanced structures. The heterojunction diode capacitance-voltage (C-V) model is applied to extract effective the acceptor concentration from the p-NiOx. Net donor and acceptor concentration in n-GaN and p-GaN are extracted by using metal-
oxide-
semiconductor (MOS) test structures. The fabricated p-NiOx/p-GaN/n-GaN SHJ diodes with charge-balanced region between anode and cathode exhibit a forward on-state current density of 10-30 mA/mm across an anode-to-cathode distance (LAC) from 16 {\mu}m to 80 {\mu}m. The SHJ diodes show rectifying behavior with a maximum on/off ratio of 10^9 and a low reverse leakage density. The highest breakdown voltage achieved for the SHJ diodes is ~2.8 kV with reverse leakage density of 10^-4 mA/mm at ~80% of devices catastrophic breakdown voltage. The SHJ diodes across all types of dimensions exhibit significant breakdown voltage improvements (~6X on average) with ultra-low reverse leakage current compared to corresponding reference structures without a charge-balanced extension, clearly demonstrating the superjunction effect for devices fabricated on GaN epitaxial layer with ~10^17 cm^-3 electron density.
Read the full abstract ▾
All authors Yizheng Liu, Zachary J. Biegler, Ashley E. Wissel-Garcia, James S. Speck, Sriram Krishnamoorthy
Plasma Physics · Cross-listed from math.NA
A dual grid geometric electromagnetic particle in cell method
Katharina Kormann and Eric Sonnendrücker
Geometric particle-in-
cell discretizations have been derived based on a discretization of the fields that is conforming with the de Rham structure of the Maxwell's equation and a standard particle-in-
cell ansatz for the fields by deriving the equations of motion from a discrete action principle. While earlier work has focused on finite element discretization of the fields based on the theory of Finite Element Exterior Calculus, we propose in this article an alternative formulation of the field equations that is based on the ideas conveyed by mimetic finite differences. The needed duality being expressed by the use of staggered grids. We construct a finite difference formulation based on degrees of freedom defined as point values, edge, face and volume integrals on a primal and its dual grid. Compared to the finite element formulation no mass
matrix inversion is involved in the formulation of the Maxwell solver. In numerical experiments, we verify the conservation properties of the novel method and study the influence of the various parameters in the discretization.
Read the full abstract ▾
Optics
Quasi-bound flat bands in the continuum
Haoyu Qin, Weixuan Zhang, Shaohu Chen et al. (+6 more)
Bound states in the continuum (BICs) are widely known spatially localized states experimentally implemented as quasi-BICs. Although they emerged as a promising solution for achieving high-quality resonances in photonic structures, quasi-BICs are confined to a very narrow range in k-space and are highly sensitive to disorder. Here, we introduce quasi-bound flat bands in the continuum (quasi-BFICs), a class of optical states where Bloch modes are found within a photonic flat band, leading to a quasi-BIC behaviour at every k-point above the light line. We analytically and numerically demonstrate the origin of quasi-BFICs from the disorder-induced band folding, mode localization and multiple topological charges in k-space, and identify the optimal strength of structural disorder to maximise their generation probability. Angle-resolved transmission and Q-factor measurements confirm the existence of quasi-BFICs, opening new avenues for designing devices with high quality factor and wide-angle response, presenting a counterintuitive strategy that leverages disorder to enhance optical performance.
Read the full abstract ▾
All authors Haoyu Qin, Weixuan Zhang, Shaohu Chen, Huizhen Zhang, Ruhao Pan, Junjie Li, Lei Shi, Jian Zi, Xiangdong Zhang
Popular Physics
Uncertainty quantification and parameter optimization of plasma etching process using heteroscedastic Gaussian process
Yongsu Jung, Minji Kang, Muyoung Kim et al. (+3 more)
This study presents a comprehensive framework for uncertainty quantification (UQ) and design optimization of
plasma etching in
semiconductor manufacturing. The framework is demonstrated using experimental measurements of etched depth collected at nine wafer locations under various
plasma conditions. A heteroscedastic Gaussian process (hetGP) surrogate model is employed to capture the complex uncertainty structure in the data, enabling distinct quantification of (a) spatial variability across the wafer and (b) process-related uncertainty arising from variations in chamber pressure, gas flow rate, and RF power. Epistemic uncertainty due to sparse data is further quantified and incorporated into a reliability-based design optimization (RBDO) scheme. The proposed method identifies optimal process parameters that minimize spatial variability of etch depth while maintaining reliability under both aleatory and epistemic uncertainties. The results demonstrate that this framework effectively integrates data-driven surrogate modeling with robust optimization, enhancing predictive accuracy and process reliability. Moreover, the proposed approach is generalizable to other
semiconductor processes, such as photolithography, where performance is highly sensitive to multifaceted uncertainties.
Read the full abstract ▾
All authors Yongsu Jung, Minji Kang, Muyoung Kim, Min Sup Choi, Hyeong-U Kim, Jaekwang Kim
Optics
Phase-sensitive tip-enhanced sum frequency generation spectroscopy using temporally asymmetric pulse for detecting weak vibrational signals
Atsunori Sakurai, Shota Takahashi, Tatsuto Mochizuki et al. (+3 more)
Vibrational sum frequency generation (SFG) spectroscopy is a powerful technique for investigating molecular structures, orientations, and dynamics at surfaces. However, its spatial resolution is fundamentally restricted to the micrometer scale by the optical diffraction limit. Tip-enhanced SFG (TE-SFG) using a scanning tunneling microscope has been developed to overcome this limitation. The acquired spectra exhibit characteristic dips originating from vibrational responses located within the strong broadband non-resonant background (NRB), which distorts and obscures the molecular signals. By making the second pulse temporally asymmetric and introducing a controlled delay between the first and second
laser pulses, the NRB was effectively suppressed, which in turn amplified the vibrational response through interference and facilitated the detection of weak vibrational signals. This interference also made the technique phase-sensitive, enabling the determination of absolute molecular orientations. Furthermore, forward- and backward-scattered signals were simultaneously detected, conclusively confirming that the observed signals originated from tip enhancement rather than far-field contributions. Finally, the signal enhancement factor in TE-SFG was estimated to be $6.3\times 10^6-1.3\times 10^7$, based on the experimental data. This phase-sensitive TE-SFG technique overcomes the optical diffraction limit and enables the investigation of molecular vibrations at surfaces with unprecedented detail.
Read the full abstract ▾
All authors Atsunori Sakurai, Shota Takahashi, Tatsuto Mochizuki, Tomonori Hirano, Akihiro Morita, Toshiki Sugimoto
Atmospheric and Oceanic Physics
Cracking the Code of Arctic Sea Ice: Why Models Fail to Predict Its Retreat?
Ruijian Gou, Gerrit Lohmann, Deliang Chen et al. (+4 more)
Arctic sea ice is rapidly retreating due to global warming, and emerging evidence suggests that the rate of decline may have been underestimated. A key factor contributing to this underestimation is the coarse resolution of current
climate models, which fail to accurately represent eddy floe interactions,
climate extremes, and other critical small scale processes. Here, we elucidate the roles of these dynamics in accelerating sea ice melt and emphasize the need for higher resolution models to improve projections of Arctic sea ice.
Read the full abstract ▾
All authors Ruijian Gou, Gerrit Lohmann, Deliang Chen, Shiming Xu, Ruiqi Shu, Shaoqing Zhang, Lixin Wu
Optics
Extend the waveband of high isolation ratio and narrow band asymmetric transmission based on grating-film-grating nanostructure
Ruihan Ma, Yuqing Cheng and Mengtao Sun
A serial asymmetric transmission (AT) nanodevices based on the grating-film-grating (G-F-G) structure are proposed and studied. By showing the results of three different nanodevices as examples, it is proved that this kind of G-F-G nanostructure can achieve high isolation ratio AT at arbitrary wavelength within a certain range by designing the parameters of the structure. These three nanodevices can achieve high forward transmittivities of 0.69, 0.71, and 0.87 at the wavelengths of 714, 810, and 905 nm, respectively, and the isolation ratio between forward and backward transmittivities are all more than 10 dB. In addition, the effects of the incidence angle and lateral displacement of upper gratings on device performance were also investigated, revealing that optimal AT is achieved under normal incidence and zero displacement. The proposed G-F-G structure provides a solution for passive and easy to manufacture optical isolators with potential applications in optical communication and sensing systems.
Read the full abstract ▾