Instrumentation and Detectors
Gamma Imagers for Nuclear Security and Nuclear Forensics: Recommendations based on results from a side-by-side intercomparison
L.E. Sinclair, P.R.B. Saull, A. McCann et al. (+4 more)
Nuclear security operations and forensic investigations require the utilization of a suite of instruments ranging from passive gamma spectrometers to high-precision laboratory sample analyzers. Gamma spectroscopy survey is further broken down into wide-area search performed with large-volume scintillator-based mobile survey spectrometers which are integrated with geographic position sensors for mapping and identification of hot zones, and high-precision long-dwell measurements using solid state spectrometers for follow-on characterization to establish isotopic content and ratios. While performing well at detecting the presence, quantity and type of radioactivity, all of these methods have limited ability to determine the location of a source of radioactivity. In recent years, technology advances have resulted in gamma imager devices which can create an image of the distribution of radioactive sources using the gamma emissions which accompany radioactive decay, and overlay this on an optical photograph of the environment. These gamma imaging devices have arisen out of methods developed for medical physics, experimental particle physics, and astrophysics, resulting in a proliferation of different technological approaches. Those responsible for establishing a
nuclear security concept of operations, require guidance to choose the proper gamma imager for each of the application spaces in a tiered response. Here the results of an intercomparison of two gamma imagers based on two widely different technologies,
semiconductor and scintillator detectors, are presented. The optimal utilization of these imaging technologies in a tiered response is discussed based on the results of the trial. Finally, an outlook on future directions for gamma imaging advances is provided.
Read the full abstract ▾
All authors L.E. Sinclair, P.R.B. Saull, A. McCann, A.M.L. MacLeod, N.J. Murtha, A. El-Jaby, G. Jonkmans
Applied Physics · Cross-listed from cond-mat.mes-hall
An Open-Source Framework for Measurement and Analysis of Nanoscale Ionic Transport
Yichao Wang, Munan Fang, Aziz Roshanbhai Lokhandwala et al. (+2 more)
Nanofluidic systems exploit nanometre-scale confinement in channels and pores to regulate ionic transport, enabling functionalities such as osmotic energy harvesting and neuromorphic ionic
memory. Studying such confined transport requires both precise electrical instrumentation and careful data analysis, yet, in practice, measurements are still often taken with vendor software, exported as files, and processed later in separate environments. In this work, we bring these steps together in a unified Python-based framework built around three interoperable graphical user interfaces (GUIs) for nanochannel, nanopore and memristor experiments. The framework is organised into two functional parts, measurement and analysis. On the measurement side, two GUIs drive Keithley Source Meters to run continuous voltage sweeps and user-defined memristive pulse sequences, while providing live plots, configuration management and controlled shutdown routines. On the analysis side, a dedicated nanochannel and nanopore GUI reads raw I-V
datasets, applies unit-consistent processing, extracts conductance and ion mobility, evaluates selectivity and osmotic power, and is complemented by a web-based calculator that performs the same mobility analysis without a local Python installation. All three GUIs are implemented in Python/Tkinter with modular plotting and logging layers so that flexible control sequences and physics-based post-processing share a common data format, improving reproducibility, timing stability and day-to-day efficiency in nanofluidic and electronic device studies.
Read the full abstract ▾
All authors Yichao Wang, Munan Fang, Aziz Roshanbhai Lokhandwala, Siddhi Vinayak Pandey, Boya Radha
Space Physics · Cross-listed from astro-ph.EP
Has Kronos devoured Planet Nine and its epigones?
Lorenzo Iorio
The
Planet Nine hypothesis encompasses a body of about 5-8 Earth's masses whose orbital plane would be inclined to the ecliptic by one or two tens of degrees and whose perihelion distance would be as large as about 240-385 astronomical units. Recently, a couple of his epigones have appeared:
Planet X and
Planet Y. The former is a sort of minor version of
Planet Nine in that all its physical and orbital parameters would be smaller. Instead, the latter would have a mass ranging from that of Mercury to the Earth's one and semimajor axis within 100-200 astronomical units. By using realistic upper bounds for the orbital precessions of Saturn, one can get insights on their position which, for
Planet Nine, appears approximately confined around its aphelion.
Planet Y can be just a Mercury-sized object at no less than about 125 astronomical units, while
Planet X appears to be ruled out. Dedicated data reductions by modeling such perturber(s) are required to check the present conclusions, to be intended as hints of what might be detectable should planetary ephemerides include them. A probe on the same route of Voyager 1 would be perturbed by
Planet Nine by about 20-40 km after some decades.
Read the full abstract ▾
Plasma Physics · Cross-listed from astro-ph.HE
Flow Generation via Catastrophic Loss of Equilibrium in Weakly-Rotating Self-Gravitating Fluids: A Minimal Idealized Model
L. Gudushauri, N.L. Shatashvili, G. Shekiladze et al. (+1 more)
This paper explores the catastrophic energy transformations, in particular the ones leading to the generation of a flow in a weakly rotating self-gravitating fluid/gas found, for instance, in the vicinity of a massive compact object. Because of the similarity in the governing equations, the system dynamics is worked out exactly in parallel to the methods developed for investigating catastrophic relaxation in
stellar plasmas [1-3]. In the latter a more “complex"
equilibrium state, on slow changes in the environment, can lose its
equilibrium (catastrophe), and transform to a less complex state with a very different energy mix from the original. It is shown that a similar transformation in the weakly rotating self-gravitating fluid/gas will convert much of its gravitation energy into kinetic energy in the flow. Since flows are a perennial ingredient of high-energy astrophysical systems, the energy transformation processes revealed in present study, can advance our understanding of a variety of them. Some particularly relevant examples are: macro-scale flows / structures in
galaxies,
accretion discs, and the dynamics and stability of a rotating
star / its atmosphere.
Read the full abstract ▾
All authors L. Gudushauri, N.L. Shatashvili, G. Shekiladze, S.M. Mahajan
Space Physics · Cross-listed from astro-ph.SR
A study of solar energetic particle transport on 30 March 2022 using multi-spacecraft data assimilation
Takashi Minoshima, Yoshizumi Miyoshi, Go Murakami et al. (+7 more)
We analyze a unique
solar energetic particle event observed simultaneously by the BepiColombo and STEREO-A spacecraft on March 30, 2022. The two spacecraft at heliocentric distances of 0.6 and 1.0 AU are expected to be aligned approximately along the same
magnetic field line, providing a valuable opportunity to investigate particle transport processes in the inner heliosphere.
Protons with energies above 1.0 MeV exhibit velocity dispersion during the rise phase, suggesting that the energetic particles are produced close to the Sun, possibly associated with a coronal mass ejection. In contrast,
protons during the decay phase are characterized by long-lasting time profiles with longer time scales at 1.0 AU than at 0.6 AU, suggesting that the particles deviate from ballistic propagation. By assimilating these multi-spacecraft observation data into numerical simulations of the focused transport equation, for the first time, we estimate the mean free path parallel to the
magnetic field as a time series. The inferred mean free path decreases over time and approaches around 0.5-1.0 AU at the STEREO-A location during the decay phase, suggesting an increasing influence of scattering on particle transport. This interpretation is qualitatively supported by independent STEREO-A observations that showed increasing
magnetic field fluctuations, suggesting the connection between the particle transport and the local field fluctuations. However, only a fraction of these fluctuations is expected to contribute to particle scattering, which may be due to the multidimensional nature of
magnetic field fluctuations.
Read the full abstract ▾
All authors Takashi Minoshima, Yoshizumi Miyoshi, Go Murakami, Marco Pinto, Daniel Schmid, Ayako Matsuoka, Wolfgang Baumjohann, David Fischer, Kazumasa Iwai, Shinsuke Imada
Optics
Energy Absorption Interferometry
Stafford Withington and Willem Jellema
Energy Absorption Interferometry (EAI) is a technique for measuring the responsivities and complex-valued spatial polarimetric forms of the individual degrees of freedom through which a many-body system can absorb energy. It was originally formulated using the
language of
quantum correlation functions, making it applicable to different kinds of excitation (electromagnetic, elastic and acoustic fields). EAI has been applied in a variety of theoretical and experimental ways. It is particularly effective at characterising the multimode behaviour of ultra-low-noise far-infrared and optical devices, imaging arrays, and complete instruments, where it can be used to ensure that a system is maximally responsive to those partially coherent fields that carry signal whilst avoiding those that only carry noise. Despite its utility there is no comprehensive overview of electromagnetic EAI. In this paper we describe the theoretical foundations of the method, and present a range of new techniques in areas relating to sampling, phase referencing, mode reconstruction and noise. We present, for the first time, an analysis of how noise propagates through an experiment resulting in errors and artefacts on spectral and modal plots. A noise model is essential, because it determines the signal to noise ratio needed to ensure a given level of experimental fidelity.
Read the full abstract ▾
Optics
Super-resolution Imaging of Limited-size Objects
Taeyong Chang, Giorgio Adamo and Nikolay I. Zheludev
Improvement of label-free far-field resolution of optical imaging is possible with prior knowledge of the object such as its sparsity or accumulated by a posteriori examination of a similar class of object1-4. We show that the sole knowledge of the object's limited size is another fundamental resource to achieve resolution beyond the Abbe-Rayleigh diffraction limit: a higher resolution can be achieved with smaller objects. To prove this, we developed an imaging method that involves the representation of light scattered from the object with orthonormal field-of-view-limited Slepian-Pollak functions and experimentally demonstrated {\lambda}/8 resolution of sub-wavelength objects. Our method requires no assumption of the shape and complexity of the object and its labelling allowing a wide range of applications in the studies of nanoparticles and isolated microorganisms.
Read the full abstract ▾
Atomic Physics
Spin interferometry in a beam of ultracold molecules
R. A. Jenkins, M. T. Ziemba, F. J. Collings et al. (+6 more)
We describe a
spin interferometer using ultracold YbF molecules and develop the complete set of techniques needed to measure the electron's electric dipole moment, $d_e$, with this apparatus. The molecules are cooled in an optical molasses and prepared in a single internal
quantum state. A Raman transition prepares a
spin superposition which evolves in parallel
magnetic and electric fields before a second Raman transition maps the phase onto the populations of two hyperfine states. These populations are read out using detectors that have spatial and temporal resolution and approach unit efficiency. We characterize the efficiencies and fidelities of all these steps and evaluate the sensitivity of this approach to measuring $d_e$.
Read the full abstract ▾
All authors R. A. Jenkins, M. T. Ziemba, F. J. Collings, X. S. Zheng, F. Castellini, E. Wursten, J. Lim, B. E. Sauer, M. R. Tarbutt
Optics
On-Chip Erbium-Doped Tantalum Oxide Microring Hybrid Cavity Single-Mode Laser
Like Shui, Ruixuan Yi, Chenyang Zhao et al. (+4 more)
We demonstrate a high-performance, single-mode Er:Ta2O5 microring
laser monolithically integrated on a silicon platform via a customized Damascene process. The Er:Ta2O5 gain medium exhibits a low propagation loss of 0.73 dB/cm and a high intrinsic Q-factor of 5.03 x 105. By utilizing a hybrid cavity_consisting of a microring coupled to a U-shaped waveguide at two symmetric points_we exploit the Vernier effect to achieve robust longitudinal mode selection. Under a non-resonant 1480 nm pumping scheme, the
laser yields a side_mode suppression ratio (SMSR) of 53.3 dB and a narrow linewidth of 9.5 pm. A slope efficiency of 2.76 % is achieved_the highest reported to date for Er:Ta2O5
lasers_with a lasing threshold of 3.3 mW. Furthermore, stable single-mode tuning is demonstrated across a temperature range of 18_68 celsius, consistently aligning with theoretical transfer
matrix models. This work provides a scalable pathway for high-efficiency, tunable on-chip light sources, bridging the gap for monolithic active-passive integration on the tantalum
oxide photonic platform.
Read the full abstract ▾
All authors Like Shui, Ruixuan Yi, Chenyang Zhao, Jinlong Lu, Xiaotong Zhang, Jiaqiao Zhang, Xuetao Gan
Medical Physics
Multi-Compartment Volume Conductor with Complete Electrode Model: Simulated Stereo-EEG Source Localization using Brainstorm-Zeffiro Plugin
Fernando Galaz Prieto, Takfarinas Medani, Chinmay Chinara et al. (+2 more)
This study introduces a novel integration of the Brainstorm (BST) software and the Zeffiro Interface (ZI) to enable whole-head, multi-compartment volume conductor modeling for electroencephalography (
EEG) source imaging, with a particular focus on stereotactic
EEG applications. We present the BST-2-ZI plugin, a MATLAB-based tool that facilitates seamless transfer of tissue
segmentations and anatomical atlases from BST into ZI for finite element (FE) mesh generation as well as forward and inverse modeling. The generated FE meshes support variable spatial resolution and implement the complete electrode model (CEM), allowing for precise modeling of both invasive depth electrodes and non-invasive scalp electrodes. Using the ICBM152 template and synthetic source simulation, we demonstrate the end-to-end pipeline from MRI data to lead field (LF) computation and source localization in a stereotactic
EEG (stereo-
EEG) setting. Our numerical experiments highlight the capability of the pipeline to accurately model multi-compartment head geometry and conductivity with a stereotactic CEM-based electrode configuration. Our preliminary source localization results show how a synthetic stereo-
EEG probe corresponding to a bidirectional deep
brain stimulation (DBS) probe with four omnidirectional contacts can, in principle, be coupled with scalp electrodes to improve source localization in its vicinity.
Read the full abstract ▾
All authors Fernando Galaz Prieto, Takfarinas Medani, Chinmay Chinara, Richard M. Leahy, Sampsa Pursiainen
Optics
Tuning of Localized Surface Plasmons in Vanadium Dioxide Nanoparticles via Size and Insulator-Metal Transition
Jiří Kabát, Rostislav Řepa, Jordan A. Hachtel et al. (+5 more)
Vanadium dioxide has been identified as a promising phase-changing material for use in tunable plasmonic devices. In this study, we present a comprehensive modal analysis of single-phase and multi-phase vanadium dioxide nanoparticles. In-situ high-resolution electron energy loss spectroscopy was utilized to experimentally resolve the dipole plasmon peak, higher-order and breathing plasmonic modes, and bulk losses as a function of nanoparticle size. Furthermore, the focus is directed toward capturing the dynamic nanoscale optical response throughout the metal-
insulator transition in a vanadium dioxide nanoparticle. This system possesses the ability to be gradually switched on and off in terms of the emergence of near-infrared plasmonic absorption. The switching is accompanied by a gradual spectral shift of the absorption peak, amounting to 0.18 eV for a 120 nm nanoparticle. It is envisioned that this phenomenon can be generalized to larger nanostructures with a higher aspect ratio, thereby introducing a wider tunability of the system, which is essential for functional nanodevices based on vanadium dioxide.
Read the full abstract ▾
All authors Jiří Kabát, Rostislav Řepa, Jordan A. Hachtel, Peter Kepič, Vlastimil Křápek, Andrea Konečná, Tomáš Šikola, Michal Horák
Medical Physics · Cross-listed from cs.CV
Improving Neuropathological Reconstruction Fidelity via AI Slice Imputation
Marina Crespo Aguirre, Jonathan Williams-Ramirez, Dina Zemlyanker et al. (+13 more)
Neuropathological analyses benefit from spatially precise volumetric reconstructions that enhance anatomical delineation and improve morphometric accuracy. Our prior work has shown the feasibility of reconstructing 3D
brain volumes from 2D dissection photographs. However these outputs sometimes exhibit coarse, overly smooth reconstructions of structures, especially under high anisotropy (i.e., reconstructions from thick slabs). Here, we introduce a computationally efficient super-resolution step that imputes slices to generate anatomically consistent isotropic volumes from anisotropic 3D reconstructions of dissection photographs. By training on domain-randomized synthetic data, we ensure that our method generalizes across dissection protocols and remains robust to large slab thicknesses. The imputed volumes yield improved automated
segmentations, achieving higher Dice scores, particularly in cortical and white matter regions. Validation on surface reconstruction and atlas registration tasks demonstrates more accurate cortical surfaces and MRI registration. By enhancing the resolution and anatomical fidelity of photograph-based reconstructions, our approach strengthens the bridge between neuropathology and neuroimaging. Our method is publicly available at https://surfer.nmr.mgh.harvard.edu/fswiki/mri_3d_photo_recon
Read the full abstract ▾
All authors Marina Crespo Aguirre, Jonathan Williams-Ramirez, Dina Zemlyanker, Xiaoling Hu, Lucas J. Deden-Binder, Rogeny Herisse, Mark Montine, Theresa R. Connors, Christopher Mount, Christine L. MacDonald, C. Dirk Keene, Caitlin S. Latimer, Derek H. Oakley, Bradley T. Hyman, Ana Lawry Aguila, Juan Eugenio Iglesias
Applied Physics · Cross-listed from quant-ph
Fidelity and quantum geometry approach to Dirac exceptional points in diamond nitrogen-vacancy centers
Chia-Yi Ju, Gunnar Möller and Yu-Chin Tzeng
Dirac exceptional points (EPs) represent a novel class of non-Hermitian singularities that, unlike conventional EPs, reside entirely within the parity-time unbroken phase and exhibit linear energy dispersion. Here, we theoretically investigate the
quantum geometry of Dirac EPs realized in nitrogen-vacancy centers in diamond, utilizing fidelity susceptibility as a probe. We demonstrate that despite the absence of a
symmetry-breaking phase transition, the Dirac EP induces a pronounced
geometric singularity, confirming the validity of the fidelity in characterizing non-Hermitian EPs. Specifically, the real part of the fidelity susceptibility diverges to negative infinity, which serves as a signature of non-Hermitian criticality. Crucially, however, we reveal that this divergence exhibits a distinct anisotropy, diverging along the non-reciprocal coupling direction while remaining finite along the detuning axis. Furthermore, we establish that this anisotropy, characterized by at least one exact dark direction coexisting with divergent directions, is a generic consequence of the Dirac EP structure whenever the parameter derivatives collectively span the off-diagonal operator space at the Dirac EP. This behavior stands in stark contrast to the omnidirectional divergence observed in conventional EPs. Our findings provide a comprehensive picture of the fidelity probe near the Dirac EP, highlighting the critical role of parameter directionality in exploiting Dirac EPs for
quantum control and sensing applications.
Read the full abstract ▾
Data Analysis and Statistics · Cross-listed from q-bio.BM
Phase Transitions in Unsupervised Feature Selection
Jonathan Fiorentino, Michele Monti, Dimitrios Miltiadis-Vrachnos et al. (+3 more)
Identifying minimal and informative feature sets is a central challenge in data analysis, particularly when few data points are available. Here we present a theoretical analysis of an unsupervised feature selection pipeline based on the Differentiable Information Imbalance (DII). We consider the specific case of structural and physico-chemical features describing a set of
proteins. We show that if one considers the features as coordinates of a (hypothetical) statistical physics model, this model undergoes a phase transition as a function of the number of retained features. For physico-chemical descriptors, this transition is between a glass-like phase when the features are few and a
liquid-like phase. The glass-like phase exhibits bimodal order-parameter distributions and Binder cumulant minima. In contrast, for structural descriptors the transition is less sharp. Remarkably, for physico-chemical descriptors the critical number of features identified from the DII coincides with the saturation of downstream binary classification performance. These results provide a principled, unsupervised criterion for minimal feature sets in
protein classification and reveal distinct mechanisms of criticality across different feature types.
Read the full abstract ▾
All authors Jonathan Fiorentino, Michele Monti, Dimitrios Miltiadis-Vrachnos, Vittorio Del Tatto, Alessandro Laio, Gian Gaetano Tartaglia
Computational Physics
An Oscillation-Free Real Fluid Quasi-Conservative Finite Volume Method for Transcritical and Phase-Change Flows
Haotong Bai, Wenjia Xie, Yixin Yang et al. (+2 more)
A new Real Fluid Quasi-Conservative (RFQC) finite volume method is developed to address the numerical simulation of real fluids involving shock waves in transcritical and phase-change flows. To eliminate the spurious pressure oscillations inherent in fully conservative schemes, we extend the classic quasi-conservative method, originally designed for two-phase flows, to real fluids governed by arbitrary equations of state (EoS). The RFQC method locally linearizes the real fluid EoS at each grid point and time step, constructing and evolving the frozen Grüneisen coefficient $\Gamma$ and the linearization remainder $E_0$ via two advection equations. At the end of each time step, the evolved $\Gamma$ and $E_0$ are utilized to reconstruct the oscillation-free pressure field, followed by a thermodynamic re-projection applied to the conserved variables. Theoretical analysis demonstrates that, in smooth regions, the energy conservation error introduced by the RFQC method is a second-order small term dominated by the time-step. In discontinuous regions, this error is determined by the
entropy increase rate, thereby maintaining consistency with the inherent truncation error of shock-capturing methods. A series of numerical tests verifies that the method can robustly simulate complex flow processes with only minor energy conservation errors, including transcritical flows, phase transitions, and shock-interface interactions. The RFQC method is proven to be both accurate and robust in capturing shock waves and phase transitions.
Read the full abstract ▾
All authors Haotong Bai, Wenjia Xie, Yixin Yang, Ping Yi, Mingbo Sun
Optics
Evolution of Geometric Phase of light since 1956: A Catalog Review
A. Srinivasa Rao
The
geometric phase of light is a fascinating phenomenon in optics and arises whenever there is a change in the polarization state of light. It is a fundamentally well-established concept and has recently found extensive applications, particularly in the development of
geometric phase elements that enable efficient manipulation of light. In this tutorial review, we discuss the
evolution of the
geometric phase of polarization on the Poincaré sphere, from its inception by Shivaramakrishnan Pancharatnam in 1956 to its recent advances and applications. This review article aims to focus on core papers related to the
geometric phase of polarization rather than providing an exhaustive literature survey. In this review, first, we introduced the basic parameters and corresponding parameter spheres involved in the
geometric phase of light. Then, we provide an in-depth analysis of
geometric phase in polarization modes, spatial modes, vector modes, and electromagnetic fields. A brief discussion of applications of the
geometric phase is also provided. The intriguing explanation given in this review can awaken new ideas related to the
geometric phase of light and can open new directions in fundamental and applied optics. Finally, the tutorial is structured as a comprehensive catalog of the
geometric phase of light.
Read the full abstract ▾
Plasma Physics
Central Equations and Band Structures of Linear Magnetohydrodynamic Waves in a Magneto-Lattice
Shiyu Sun, Peifeng Fan, Yulei Wang et al. (+3 more)
We investigate the band structures and propagation properties of linear ideal magnetohydrodynamic (MHD) waves in a
plasma with a spatially periodic background
magnetic field (a magneto-
lattice ). We develop a plane-wave expansion approach in two equivalent forms: one written using the usual linearized MHD perturbation variables and another written in terms of the fluid displacement. We validate both formulations with numerical tests, including an empty-
lattice limit that recovers the uniform-
plasma dispersion. The method enables efficient computation of dispersion relations and reveals intrinsic frequency band gaps and cutoff behavior caused by
magnetic periodicity. We show that the band gap width increases with the amplitude of the periodic
magnetic-field modulation (relative to the uniform background field), leading to suppression of selected wave modes. In addition, the
magnetic periodicity splits the Alfvén continuum into multiple branches, a feature absent in uniform
plasmas. These results provide a framework for tailoring MHD wave propagation in structured
plasmas and may be useful for future studies of
plasma metamaterials and topological
plasma waves.
Read the full abstract ▾
All authors Shiyu Sun, Peifeng Fan, Yulei Wang, Qiang Chen, Xingkai Li, Weihua Wang
Computational Physics · Cross-listed from quant-ph
From Block Diagrams to Bloch Spheres: Graphical Quantum Circuit Simulation in LabVIEW
Murtaza Vefadar
As
quantum computing transitions from theoretical physics to engineering applications, there is a growing need for accessible simulation tools that bridge the gap between abstract linear
algebra and practical implementation. While text-based frameworks (like Qiskit or Cirq) are standard, they often present a steep learning curve for students and engineers accustomed to graphical system design. This paper introduces QuVI (
Quantum Virtual Instrument), an open-source
quantum circuit toolkit developed natively within the NI LabVIEW environment. Moving beyond initial proof-of-concept models, QuVI establishes a robust framework that leverages LabVIEW's "dataflow" paradigm, in which wires represent data and nodes represent operations, to provide an intuitive, visual analog to standard
quantum circuit notation while enabling the seamless integration of classical control structures like loops and conditionals. The toolkit's capabilities are demonstrated by constructing and visualizing fundamental
quantum algorithms and verifying results against theoretical predictions. By translating "Block Diagrams" directly into
quantum state evolutions ("Bloch Spheres"), QuVI offers educators and researchers a powerful platform for prototyping
quantum logic without leaving the graphical engineering workspace.
Read the full abstract ▾
Atmospheric and Oceanic Physics
"What is a realistic forecast?" Assessing data-driven weather forecasts, a journey from verification to falsification
Zied Ben Bouallègue
The artificial intelligence revolution is fuelling a paradigm shift in weather
forecasting: forecasts are generated with machine learning models trained on large
datasets rather than with physics-based numerical models that solve partial differential equations. This new approach proved successful in improving forecast performance as measured with standard verification metrics such as the root mean squared error. At the same time, the realism of data-driven weather forecasts is often questioned and considered an Achilles' heel of machine learning models. How forecast realism can be defined and how this forecast attribute can be assessed are the two questions simultaneously addressed here. Inspired by the seminal work of Murphy (1993) on the definition of forecast goodness, we identify 3 types of realism: a functional realism measured by scoring functions, a structural realism related to the statistical characteristics of the forecasts, and a physical realism that is apprehended through the lenses of our scientific knowledge. This conceptual setting serves as a basis for the design of a new framework for the evaluation of data-driven weather models where falsification arises as a complementary process to the well-established diagnostic and verification tasks.
Read the full abstract ▾
Plasma Physics
von Neumann entropy of phase space structures in gyrokinetic plasma turbulence
Go Yatomi and Motoki Nakata
We introduce a data-driven diagnostic that combines the singular value decomposition (SVD) with an information-theoretic
entropy to quantify the phase-space complexity of perturbed distribution functions in gyrokinetic
turbulence. Applying this framework to nonlinear flux-tube simulations that solve the time
evolution of the ion distribution function represented by
Fourier modes with the wavenumber for real space, we define the von Neumann
entropy (vNE) to analyze the velocity-space structure. A global survey in the wavenumber space reveals a wavenumber-dependent variation of the vNE in velocity-space structure: the vNE remains low at low wavenumber but increases across $k_\perp\rho_{t\mathrm{i}}\sim 1$. Hermite/Laguerre decompositions revealed that the finite Larmor radius (FLR) phase mixing in the perpendicular (
magnetic-moment) direction is active. Simultaneously, the systematic increase in vNE for $k_\perp\rho_{t\mathrm{i}}$ correlates with the broadening of the Hermite spectrum, suggesting enhanced parallel phase mixing (Landau resonance) as the primary mechanism for the observed wave number dependence. These results demonstrate that the SVD-based vNE provides a compact measure of kinetic complexity without assuming a predefined basis and enables a global mapping of its wavenumber dependence of phase-mixing processes in gyrokinetic
turbulence.
Read the full abstract ▾
Atmospheric and Oceanic Physics
HybridOM: Hybrid Physics-Based and Data-Driven Global Ocean Modeling with Efficient Spatial Downscaling
Ruiqi Shu, Xiaohui Zhong, Qiusheng Huang et al. (+4 more)
Global ocean modeling is vital for
climate science but struggles to balance computational efficiency with accuracy. Traditional numerical solvers are accurate but computationally expensive, while pure deep learning approaches, though fast, often lack physical consistency and long-term stability. To address this, we introduce HybridOM, a framework integrating a lightweight, differentiable numerical solver as a skeleton to enforce physical laws, with a neural network as the flesh to correct subgrid-scale dynamics. To enable efficient high-resolution modeling, we further introduce a physics-informed regional downscaling mechanism based on flux gating. This design achieves the inference efficiency of AI-based methods while preserving the accuracy and robustness of physical models. Extensive experiments on the GLORYS12V1 and OceanBench
dataset validate HybridOM's performance in two distinct regimes: long-term subseasonal-to-seasonal simulation and short-term operational
forecasting coupled with the FuXi-2.0 weather model. Results demonstrate that HybridOM achieves state-of-the-art accuracy while strictly maintaining physical consistency, offering a robust solution for next-generation ocean digital twins. Our source code is available at https://github.com/ChiyodaMomo01/HybridOM.
Read the full abstract ▾
All authors Ruiqi Shu, Xiaohui Zhong, Qiusheng Huang, Ruijian Gou, Tianrun Gao, Hao Li, Xiaomeng Huang
Optics
Mitigating Electrode-Induced Polarization Artifacts in Miniaturized Terahertz Detectors via a Ring-Shaped Electrode Design
Hongjia Zhu, Shaojing Liu, Zhaolong Cao et al. (+5 more)
Terahertz (THz) polarization detection provides critical insights into material properties but faces a fundamental constraint upon miniaturization: subwavelength metallic electrodes induce strong localization and distortion of the incident field, thereby convoluting the intrinsic device response with electrode-induced artifacts. Here, we overcome this limitation with a ring-shaped electrode architecture that suppresses field perturbations across a broad bandwidth from 2.0 to 5.0 THz. The resonant frequency of the ring electrode can be flexibly detuned from the target operation frequency by adjusting its inner and outer radii, while the smooth, edge-free geometry minimizes the lightning-rod effect. These design features collectively lead to a pronounced suppression of localized THz field enhancement. Numerical simulations reveal an 8.48x reduction in the local field strength compared with conventional rod-shaped electrodes. Consistent with this, experimental measurements on
graphene-based detectors exhibit a 6.95x decrease in photocurrent for the ring-shaped electrode relative to the rod-shaped configuration. Moreover, the ring geometry effectively reduces the linear polarization ratio of the photocurrent from >3 to <1.4, confirming its effectiveness in mitigating electrode-induced polarization anisotropy. Our design decouples the detection response from electrode-induced artifacts, enabling compact THz detectors that preserve intrinsic signal fidelity for high-quality polarization-resolved imaging and diagnostics.
Read the full abstract ▾
All authors Hongjia Zhu, Shaojing Liu, Zhaolong Cao, Ximiao Wang, Runli Li, Yanlin Ke, Huanjun Chen, Shaozhi Deng
Data Analysis and Statistics · Cross-listed from cond-mat.mtrl-sci
Multimodal Machine Learning for Integrating Heterogeneous Analytical Systems
Shun Muroga, Hideaki Nakajima, Taiyo Shimizu et al. (+2 more)
Understanding structure-property relationships in complex materials requires integrating complementary measurements across multiple length scales. Here we propose an interpretable "
multimodal" machine learning framework that unifies heterogeneous analytical systems for end-to-end characterization, demonstrated on carbon nanotube (CNT) films whose properties are highly sensitive to microstructural variations. Quantitative morphology descriptors are extracted from SEM images via binarization, skeletonization, and network analysis, capturing
curvature, orientation, intersection density, and void geometry. These SEM-derived features are fused with Raman indicators of crystallinity/defect states, specific surface area from gas adsorption, and electrical surface resistivity. Multi-dimensional visualization using radar plots and UMAP reveals clear clustering of CNT films according to crystallinity and entanglements. Regression models trained on the
multimodal feature set show that nonlinear approaches, particularly XGBoost, achieve the best predictive accuracy under leave-one-out cross-validation. Feature-importance analysis further provides physically meaningful interpretations: surface resistivity is primarily governed by junction-to-junction transport length scales, crystallinity/defect-related metrics, and network connectivity, whereas specific surface area is dominated by intersection density and void size. The proposed
multimodal machine learning framework offers a general strategy for data-driven, explainable characterization of complex materials.
Read the full abstract ▾
All authors Shun Muroga, Hideaki Nakajima, Taiyo Shimizu, Kazufumi Kobashi, Kenji Hata
Chemical Physics · Cross-listed from cond-mat.soft
Unified origin of negative energetic elasticity in a lattice polymer chain: soft self-repulsion and bending stiffness
Nobu C. Shirai
We study a single
lattice polymer chain under a fixed end-to-end distance, incorporating both Domb–Joyce (DJ) soft-core self-repulsion between
polymer segments and a local bending-energy cost. By decomposing the stiffness into energetic and entropic contributions, we survey the parameter space defined by the self-repulsion strength and bending-energy cost. We find that the energetic contribution to stiffness is negative across the entire explored range, whereas the entropic contribution remains positive. These results unify two previously independent mechanisms of negative energetic elasticity – solvent-induced self-repulsion and bending stiffness – and demonstrate that either mechanism alone, as well as their combination, produces the same sign. Beyond this sign-level unification, we analyze the internal-energy scaling and show that, in the absence of the bending-energy term, the DJ (self-repulsion) limit exhibits a robust $(n-r)^{7/4}/n$ scaling collapse. In contrast, the introduction of finite bending stiffness progressively disrupts this scaling, providing an internal-energy-based diagnostic to distinguish between contributions from self-repulsion and bending stiffness.
Read the full abstract ▾
Plasma Physics
Drift-kinetic PIC model for simulations of longitudinal plasma confinement in mirror traps
V.V. Glinskiy, I.V. Timofeev and V.V. Prikhodko
The paper presents a 1D2V electrostatic PIC model with a drift-kinetic description of all particle types aiming at simulating classical longitudinal
plasma transport in axially symmetric open traps. The model generalizes the semi-implicit particle-in-
cell method with exact conservation of energy and charge to the case of collisional
plasma and adapts it to boundary conditions on perfectly conducting walls with a floating potential. Implementation of Coulomb collisions is tested on the problem of temperature relaxation in a two-component
plasma and demonstrates good agreement with the analytical theory. Since quasi-neutrality of
plasma is not strictly determined, the model is able to correctly reproduce the ambipolar electric potential profile up to the walls. At the same time, the main advantage of implicit PIC simulations - the ability to use large grid steps, many times larger than the Debye radius - does not prevent the correct modeling of the near-wall electric potential jump. The model satisfactorily reproduces the known results of the Debye sheath theory and the Bohm criterion. A comparison of stationary
plasma profiles formed in a mirror trap in the presence of a constant particle source with the results of simulations using the hybrid code MIDAS showed that self-consistent consideration of electron kinetics in expanders leads to noticeable (at the level of 15 %) differences in the electron temperature, potential, and density of the confined
plasma.
Read the full abstract ▾
Optics
High-Polarization-Extinction Raman Conversion in Gas-Filled Polarization-Maintaining Hollow-Core Fibers
Xianhao Qi, Pau Arcos, Yizhi Sun et al. (+4 more)
Gas-filled hollow-core fibers (HCFs) have emerged as a versatile platform for high-power nonlinear optics, enabling phenomena from ultrafast pulse compression to broadband frequency generation. However, the lack of robust polarization control has remained a critical obstacle to the deployment of gas-based fiber sources. Here, we overcome this bottleneck by demonstrating the generation of highly-polarized Stokes light via stimulated Raman scattering (SRS) in a nitrogen-filled polarization-maintaining anti-resonant hollow-core fiber (PM-HCF). By exploiting the strong structural birefringence of the fiber, the Raman interaction becomes polarization-decoupled along the principal birefringence axes, leading to threshold-selective Raman amplification and an intrinsic polarization purification mechanism. As a result, the vibrational Raman Stokes emission exhibits a polarization extinction ratio (PER) of 35 dB, even when the incident pump PER is as low as ~2 dB. Through analytical theory and numerical modeling, we validate the underlying polarization-selective Raman dynamics and identify the fiber platform as the dominant factor governing the observed PER saturation. We further show that this high polarization purity and high conversion efficiency is maintained under tight bending conditions with radii down to 5 cm, in stark contrast to conventional non-PM-HCF. These results establish PM-HCFs as a robust and scalable architecture for generating polarization-stable, frequency-shifted light, and indicate that polarization may be treated as an actively engineerable degree of freedom in gas photonics, paving the way toward deployment-ready gas-based fiber sources for precision metrology,
quantum communication, and coherent sensing.
Read the full abstract ▾
All authors Xianhao Qi, Pau Arcos, Yizhi Sun, Shoufei Gao, Wei Ding, David Novoa, Yingying Wang
Fluid Dynamics
Digital Twin Assessment of Filter Clogging Penalties in VFD-Driven Industrial Fan Systems
Wichai Pattanapol and Adam Gill
Industrial ventilation systems equipped with variable-frequency drives (VFDs) often mask the aerodynamic impact of filter clogging by automatically increasing fan speed to maintain airflow setpoints. While effective for process stability, this control strategy creates a "blind spot" in energy management, leading to unmonitored power spikes. This study applies a rapid digital twin workflow to quantify these hidden energy penalties in a standard 50 kW draw-through fan room. Using a specialized computational fluid dynamics (CFD) solver (AirSketcher), the facility was modeled under "Clean Filter" (baseline) and "Dirty Filter" (clogged) scenarios. The physics engine was first validated against wind tunnel experimental data, confirming high agreement with the theoretical inertial pressure-drop law ($\Delta P \propto U^2$). In the industrial case study, results indicate that severe clogging (modeled via a 50% effective porosity reduction) can push the fan system beyond its available pressure head or speed limits, forcing the VFD into a saturation regime. Under these conditions, effective airflow collapses by over 50% (3,806 CFM to 1,831 CFM) despite increased fan effort. The associated energy analysis predicts an annual energy penalty of 8,818 kWh ($1,058/yr). This study demonstrates how a physics-based simulation provides a defensible, ROI-driven metric for optimizing filter maintenance cycles. Keywords - industrial ventilation; digital twin; VFD optimization; filter maintenance; CFD; energy efficiency
Read the full abstract ▾
Accelerator Physics
KEK Accelerator Test Facility Low-Level RF and Timing Systems
Konstantin Popov, Alexander Aryshev, Hiroshi Kaji et al. (+1 more)
The KEK Accelerator Test Facility (ATF) is a dedicated testbed for nanobeam technologies in support of the International Linear
Collider (ILC). Stable pulsed operation requires synchronization of the facility timing system with the Low-Level RF (LLRF) system. The timing system distributes trigger and gate signals to key subsystems, including the DAQ, klystrons,
laser systems, pulsed kicker magnets, and interlocks. The LLRF system provides phase-coherent RF references and facility-wide clock distribution for synchronization. Achieving ~100 fs-level synchronization depends critically on the phase-noise power spectral density (PN-PSD) of the distributed clock signals and on preserving this performance throughout the distribution network. We present facility-wide measurements of the KEK ATF LLRF clock PN-PSD and discuss the resulting synchronization floor imposed by the stability of the ATF Linac and Damping Ring signal generators.
Read the full abstract ▾
All authors Konstantin Popov, Alexander Aryshev, Hiroshi Kaji, Toshiyuki Okugi
Biological Physics
Harnessing the Peripheral Surface Information Entropy from Globular Protein-Peptide Complexes
Tyler Grear and Donald J. Jacobs
Predicting favorable
protein-peptide binding events remains a central challenge in biophysics, with continued uncertainty surrounding how nonlocal effects shape the global energy landscape. Here, we introduce peripheral surface information (PSI)
entropy, a quantitative measure of the statistical variability in apolar and charged non-interacting surface (NIS) proportions across conformational ensembles. Using energy-directed molecular docking via HADDOCK3 and explicit-solvent molecular dynamics simulations, it is demonstrated that favorable binding partners exhibit emergent, low-
entropy N-states (discrete macrostates in NIS state space) indicative of preferential apolar/charged surface configurations. Across dozens of peptides and multiple receptor systems (WW, PDZ, and MDM2 domains), dominant N-states persisted under varied docking parameters and initial conditions. An experimental meta-ensemble of WW domains from 36 high-resolution structures confirmed the presence of dominant NIS modes independent of in silico methodology, suggesting an evolutionary selection pressure toward specific NIS fingerprints. These findings establish PSI
entropy as a thermoinformatic descriptor that encodes favorable binding constraints into unique statistical signatures of the NIS.
Read the full abstract ▾
Popular Physics · Cross-listed from gr-qc
Jacobson's thermodynamic approach to classical gravity applied to non-Riemannian geometries: remarks on the simplicity of Nature
Jhan N. Martinez, Jose F. Rodriguez-Ruiz and Yeinzon Rodriguez
Three decades ago, Ted Jacobson surprised us with a very appealing approach to classical
gravity. According to him, the gravitational field equations are the consequence of the first law of thermodynamics applied to a Rindler observer. Jacobson's approach being formulated for Riemannian geometries, we have wondered what its consequences would be for non-Riemannian geometries. The results of our quest have been particularly appealing: we have found that the theory that derives from the Einstein-
Hilbert action, arguably “the simplest one”, does not belong to the pool of gravitational theories available for Nature's selection (except in the Riemannian case). In the search of a unique alternative, we have considered the hypotheses employed in the formulation of the Lanczos-Lovelock theories of
gravity. Together, the two approaches point towards the theory that derives from the Einstein-
Hilbert action plus a term quadratic in the torsion vector as the one that would be selected by Nature in the non-Riemannian case without non metricity (when the energy-momentum tensor is identified as its metric version). The same strategy cannot be followed in the full non-Riemannian case (and in the previous case when the energy-momentum tensor is identified as its canonical version) as the two approaches are mutually inconsistent.
Read the full abstract ▾