Instrumentation and Detectors
Machine Learning Optimization of BEGe Detector Event Selection in the VIP Experiment
Simone Manti, Jason Yip, Massimiliano Bazzi et al. (+19 more)
The VIP collaboration operates a Broad Energy Germanium detector at the Gran Sasso National Laboratory to measure radiation in the few keV to 100 keV range, aiming to search for spontaneous collapse induced radiation and atomic transitions that violate the Pauli Exclusion Principle. Here we present a machine learning based upgrade for the BEGe detector using an event selection strategy aimed at improving the efficiency in detecting low energy events down to 10 keV. The method employs a denoising autoencoder to suppress electronic and microphonic noises and to reconstruct pulse shapes, followed by a convolutional neural network that classifies waveforms as normal single site or events with anomalies. The workflow was validated on a
dataset comprising more than 20000 waveforms recorded in 2021. The classifier achieves a receiver operating characteristic curve with an area under the curve of 0.99 and an accuracy of 95 percent. Applying this procedure lowers the minimum detectable energy of the final spectrum to approximately 10 keV. It also yields a measurable enhancement in spectral quality, including an improvement of about 14 percent in the signal to background ratio and a reduction of the energy resolution for the characteristic Pb and Bi gamma lines. These developments enhance the sensitivity of the BEGe detector to rare low energy signals and provide a scalable framework for future precision tests of
quantum foundations in low background environments.
Read the full abstract ▾
All authors Simone Manti, Jason Yip, Massimiliano Bazzi, Nicola Bortolotti, Mario Bragadireanu, Ivan Carnevali, Alberto Clozza, Luca De Paolis, Raffaele Del Grande, Carlo Guaraldo, Mihai Antoniu Iliescu, Matthias Laubenstein, Johan Marton, Federico Nola, Kristian Pischicchia, Alessio Porcelli, Alessandro Scordo, Francesco Sgaramella, Diana Sirghi, Florin Sirghi, Johann Zmeskal, Catalina Curceanu
Biological Physics · Cross-listed from nlin.AO
Origins of Instability in Dynamical Systems on Undirected Networks
Shraosi Dawn, Subrata Ghosh, Chandrakala Meena et al. (+2 more)
Robustness to perturbation is a key topic in the study of complex systems occurring across a wide variety of applications from epidemiology to biochemistry. Here we analyze the eigenspectrum of the Jacobian
matrices associated to a general class of networked dynamical systems, which contains information on how perturbations to a stationary state develop over time. We find that stability is always determined by a spectral outlier, but with pronounced differences to the corresponding eigenvector in different regimes. We show that, depending on model details, instability may originate in nodes of anomalously low or high degree, or may occur everywhere in the network at once. Importantly, the dependence on extremal degrees results in considerable finite-size effects with different scaling depending on the ensemble degree distribution. Our results have potentially useful applications in network monitoring to predict or prevent catastrophic failures, and we validate our analytical findings through applications to epidemic dynamics and gene regulatory systems.
Read the full abstract ▾
All authors Shraosi Dawn, Subrata Ghosh, Chandrakala Meena, Tim Rogers, Chittaranjan Hens
Atomic Physics · Cross-listed from quant-ph
Rotational excitation of molecules in the regime of strong ro-vibrational coupling: Comparison between an optical centrifuge and a transform-limited pulse
J. M. García-Garrido, V. Milner, C. P. Koch et al. (+1 more)
We investigate theoretically the ability of an optical centrifuge - a
laser pulse whose linear polarization is rotating at an accelerated rate, to control molecular rotation in the regime when the rigid-rotor approximation breaks down due to coupling between the vibrational and rotational degrees of freedom. Our analysis demonstrates that the centrifuge field enables controlled excitation of high rotational states while maintaining relatively low spread along the vibrational coordinate. We contrast this to the rotational excitation by a linearly polarized Gaussian pulse of equal spectral width and pulse energy which, although comparable to the centrifuge-induced rotation, is unavoidably accompanied by a substantial broadening of the vibrational wavepacket.
Read the full abstract ▾
All authors J. M. García-Garrido, V. Milner, C. P. Koch, R. González-Férez
Optics
Mode Control and Dynamic Population Gratings in Quantum-Dot Lasers
Xiangpeng Ou, Artem Prokoshin, Hongyan Yu et al. (+5 more)
Single-mode operation is essential for integrated
semiconductor lasers, yet most solutions rely on regrowth, etched gratings, or other complex fabrication steps that limit scalability. We show that
quantum-dot (QD)
lasers can achieve stable single-mode lasing through a simple cavity design using dynamic population gratings (DPGs). Owing to the low lateral carrier
diffusion of QDs, a strong standing-wave-induced carrier grating forms in a reverse-biased saturable absorber and provides self-aligned, mode-selective feedback not attainable in
quantum-well devices. A single-ring
laser achieves 46 dB side-mode suppression ratio (SMSR), while a dual-ring Vernier
laser delivers ($>$ 46 nm) tuning range and up to 52.6 dB SMSR, with continuous-wave operation up to $80\,^{\circ}\mathrm{C}$. The
laser remains single-mode under $-10.6$ dB external optical feedback and supports isolator-free data transmission at 32 Gbps. These results establish DPG-enabled QD
lasers as a simple and scalable route to tunable, feedback-resilient on-chip light sources for communication, sensing, and reconfigurable photonic systems.
Read the full abstract ▾
All authors Xiangpeng Ou, Artem Prokoshin, Hongyan Yu, Xin Yao, Ying Shi, William He, Zhican Zhou, Yating Wan
Space Physics · Cross-listed from astro-ph.SR
Predicting CME Arrivals with Heliospheric Imagers from L5: A Data Assimilation Approach
Tanja Amerstorfer, Justin Le Louëdec, David Barnes et al. (+5 more)
The
Solar TErrestrial RElations Observatory (STEREO) mission has laid a foundation for advancing real-time space weather
forecasting by enabling the evaluation of heliospheric imager (HI) data for predicting coronal mass ejection (CME) arrivals at Earth. This study employs the ELEvoHI model to assess how incorporating STEREO/HI data from the Lagrange 5 (L5) perspective can enhance prediction accuracy for CME arrival times and speeds. Our investigation, preparing for the upcoming ESA Vigil mission, explores whether the progressive incorporation of HI data in real-time enhances
forecasting accuracy. The role of human tracking variability is evaluated by comparing predictions based on observations by three different scientists, highlighting the influence of manual biases on
forecasting outcomes. Furthermore, the study examines the efficacy of deriving CME propagation directions using HI-specific methods versus coronagraph-based techniques, emphasising the trade-offs in prediction accuracy. Our results demonstrate the potential of HI data to significantly improve operational space weather
forecasting when integrated with other observational platforms, especially when HI data from beyond 35{\deg} elongation are used. These findings pave the way for optimising real-time prediction methodologies, providing valuable groundwork for the forthcoming Vigil mission and enhancing preparedness for CME-driven space weather events.
Read the full abstract ▾
All authors Tanja Amerstorfer, Justin Le Louëdec, David Barnes, Maike Bauer, Jackie A. Davies, Satabdwa Majumdar, Eva Weiler, Christian Möstl
Computational Physics · Cross-listed from cond-mat.mtrl-sci
Structural Optimization in Tensor LEED Using a Parameter Tree and $R$-Factor Gradients
Alexander M. Imre, Paul Haidegger, Florian Kraushofer et al. (+10 more)
Quantitative low-energy electron diffraction [LEED $I(V)$] is a powerful method for surface-structure determination, based on a direct comparison of experimentally observed $I(V)$ data with computations for a structure model. As the diffraction intensities $I$ are highly sensitive to subtle structural changes, local structure optimization is essential for assessing the validity of a structure model and finding the best-fit structure. The calculation of diffraction intensities is well established, but the large number of evaluations required for reliable structural optimization renders it computationally demanding. The computational effort is mitigated by the tensor-LEED approximation, which accelerates optimization by applying a perturbative treatment of small deviations from a reference structure. Nevertheless, optimization of complex structures is a tedious process. Here, the problem of surface-structure optimization is reformulated using a tree-based data structure, which helps to avoid redundant function evaluations. In the new tensor-LEED implementation presented in this work, intensities are computed on the fly, eliminating limitations of previous
algorithms that are limited to precomputed values at a grid of search parameters. It also enables the use of state-of-the-art optimization
algorithms. Implemented in Python with the JAX library, the method provides access to gradients of the $R$ factor and supports execution on graphics processing units (GPUs). Based on these developments, the computing time can be reduced by more than an order of magnitude.
Read the full abstract ▾
All authors Alexander M. Imre, Paul Haidegger, Florian Kraushofer, Ralf Wanzenböck, Tobias Hable, Sarah Tobisch, Marie Kienzer, Florian Buchner, Jesús Carrete, Georg K. H. Madsen, Michael Schmid, Ulrike Diebold, Michele Riva
Atmospheric and Oceanic Physics
Oceanic internal tides: do they get phased at the Equator?
Camille Moisset, Bruce Sutherland and Lois Baker
Low-mode baroclinic tides play a major role in ocean dynamics, especially for energy redistribution and deep ocean mixing. These internal waves, generated by
tidal flow over submarine topography, can propagate for thousands of kilometres across ocean basins, and become unstable through wave-mean flow or wave-wave interactions. Satellite observations of internal tides have shown that part of their lunar semidiurnal (M2) altimetry signal loses phase coherence in equatorial regions, thus affecting how we interpret their dynamics and energy distribution (Buijsman et al. 2017). We investigate the interaction of a baroclinic M2 internal tide wavepacket with an equatorial zonal jet, possibly of any horizontal or vertical structure. The dynamics of the low modes are explored as well as the potential excitation of higher vertical modes and how these interactions can generate incoherences in the baroclinic tide signal. We develop an idealized linear model using modal decomposition (Kelly et al. 2016), which is solved using Dedalus, to study the dynamics of a mode 1 M2 internal wavepacket on an equatorial beta plane. A zonal jet, with a uniform or a sheared vertical structure, is added at the equator to investigate potential wave-mean flow interaction. We find that a vertically uniform zonal jet affects the propagation of the mode 1 wavepacket. Depending on the strength of the jet, this can cause total reflection or strong distortion of the wavepacket. In contrast, a wavepacket entering a vertically sheared jet shows energy scattering into higher modes, which have lower phase and group speeds, shorter wavelengths, and are thus more susceptible to dissipation (and critical layers for non-uniform stratification). As the wavepacket exits the jet, reverse energy transfer occurs and the phase speed difference between the modes may explain part of the phase incoherence observed in altimetry data.
Read the full abstract ▾
Applied Physics
Innovation ARIMA models application to predict pressure variations in water supply networks with open-loop control. Case study in Noja (Cantabria, Spain)
David Munoz-Rodriguez, Manuel J. Gonzalez-Ortega, Maria-Jesus Aguilera-Urena et al. (+2 more)
Water utilities are increasingly concerned about losses, leaks, and illegal connections in their distribution networks. Pressure control is typically managed through pressure reducing valves with electrically controlled actuators based on predefined tables according to the pressure at the critical point control. This openloop control method lacks direct feedback between the PRV and CPC, making it challenging to distinguish whether pressure variations originate from normal head losses or abnormal network conditions. Unlike traditional applications of ARIMA focused on water demand
forecasting, this study explores its novel use in pressure management within distribution networks, aiming to predict P3 pressure based on head losses across a defined hydraulic sector. To achieve this objective, a predictive model based on the Box-Jenkins methodology and its variations is implemented to analyse time series data. An action path is established to determine the optimal model ARIMA, ARMA, ARMAX, etc. which is subsequently validated using real operational data from Noja, a coastal town in northern Spain characterized by significant seasonal population fluctuations. By accurately
forecasting CPC pressure, this system enhances the detection of anomalous patterns, enabling more efficient network pressure management. The study demonstrates the potential of advanced modelling techniques in optimizing water distribution networks, providing valuable insights to improve system efficiency, reliability, and sustainability in urban environments.
Read the full abstract ▾
All authors David Munoz-Rodriguez, Manuel J. Gonzalez-Ortega, Maria-Jesus Aguilera-Urena, Andres Ortega-Ballesteros, Alberto-Jesus Perea-Moreno
Chemical Physics · Cross-listed from cond-mat.mtrl-sci
Molecular Dynamics Simulations of $\gamma$-Belite(010)-Water Interfaces with High-Dimensional Neural Network Potentials
Bernadeta Prus and Jörg Behler
Belite – dicalcium silicate Ca$_2$SiO$_4$ – is a main constituent of low-carbon cement. In this work, we study several terminations of the (010) surface of $\gamma$-belite, its most stable polymorph, by molecular dynamics simulations. The energies and forces are provided by a high-dimensional neural network potential trained to density functional theory data. Water can interact in molecular form as well as dissociatively with the investigated interfaces, and the degree of dissociation is determined primarily by the protonation of SiO$_4$ groups accessible at the surface. A major part of the simultaneously formed hydroxide ions is adsorbed at surface calcium atoms, whose octahedral coordination spheres are completed by additional water molecules. The T3 termination, which is most stable in
vacuum, shows only little reactivity in water. For the only slightly less stable T2 termination, however, two distinct types of surface defects are observed. The type I defect is even stable in
vacuum and leads to a reconstruction of the entire surface, while the type II defect is only found in the presence of water. Overall, our results suggest that a variety of structures may be formed at the Ca$_2$SiO$_4$(010) surface, which are stabilized in the presence of water.
Read the full abstract ▾
Optics
Structures resistant to Manipulation by all Wavefronts in two dimensions
Asher Sabbagh, Michael Horodynski, Rida Khan et al. (+2 more)
Using light to manipulate small particles is a powerful tool with numerous practical applications across biophysics and nanotechnology. This experimental technique has achieved significant performance gains by employing shaped wavefronts, most commonly generated with spatial light modulators. Wavefront shaping has also enabled the manipulation of seemingly arbitrary objects beyond the reach of conventional beams. Contrary to this established assumption, we show here the existence of a wide variety of objects resistant to manipulation, even with the optimal wavefront shaping protocol. The counterintuitive shapes of these objects are found using inverse design in two dimensions, providing a foundation for their natural extension to three dimensions. Specifically, we show that the maximal pulling force is reduced by up to four orders of magnitude, and the maximal trapping stiffness is reduced by up to nearly two orders of magnitude. Our findings could prove useful for the development of micromachines that require a predictable mechanical response to arbitrary waves.
Read the full abstract ▾
All authors Asher Sabbagh, Michael Horodynski, Rida Khan, Brian Shi, Marin Soljačić
Optics
Constraint-Free Coherent Diffraction Imaging via Physics-Guided Neural Fields
Zhe Hu, Zisheng Yao, Yuhe Zhang et al. (+1 more)
CDI is a lensless imaging technique that enables atomic-resolution imaging of non-crystalline specimens and their dynamics. However, its broader implementation has been hindered by the instability and ill-posedness of its reconstruction process, known as phase
retrieval, which relies heavily on handcrafted, object-specific constraints. To overcome the key limitations, we propose CDIP, a robust phase-
retrieval framework that eliminates the need for such constraints by combining untrained coordinate-based neural fields for static and dynamic reconstructions and a physics-consistent forward model. We evaluate CDIP on simulated and experimental
datasets that involve both static samples and dynamic processes, demonstrating that it substantially outperforms classical iterative
algorithms and deep-learning baselines in terms of fidelity and stability. These results highlight a paradigm shift in both static and time-resolved CDI reconstruction, providing a broadly applicable framework for coherent imaging modalities such as ptychography and holography, across X-ray, electron, and optical probes.
Read the full abstract ▾
All authors Zhe Hu, Zisheng Yao, Yuhe Zhang, Pablo Villanueva-Perez
Optics
Self-Hybridized Exciton-Polariton Photodetectors From Layered Metal-Organic Chalcogenolates
Bongjun Choi, Adam D. Alfieri, Wangleong Chen et al. (+1 more)
Exciton-polaritons (EPs) arising from strong light-matter coupling offer new pathways for controlling optoelectronic properties. While typically requiring closed optical cavities for strong coupling, we demonstrate that 2D metal-organic chalcogenolates (MOCs), mithrene (AgSePh), with a high refractive index (~2.5) and strong
excitons enable self-hybridized polaritons photodetectors (PDs) without top mirrors, simplifying device architecture. Through thickness-tuned multimode polariton engineering, we achieve photodetection of sub-bandgap
photons via lower polariton states, validated through reflectance, photoluminescence (PL), and photocurrent spectroscopy with quantitative theoretical agreement. Trap-assisted two-
photon absorption enables sustained strong coupling even under sub-bandgap excitation. The polariton dispersion yields ultrafast group velocities (~65 {\mu}m/ps), extending
exciton diffusion lengths from hundreds of nanometers to several micrometers. Strong-coupling devices demonstrate a 2.38-fold enhancement in photo-to-dark current ratio compared to weak-coupling counterparts, establishing a practical route to polariton-enhanced photodetection and light harvesting.
Read the full abstract ▾
All authors Bongjun Choi, Adam D. Alfieri, Wangleong Chen, Deep Jariwala
Plasma Physics
Surface Ion-Sound Wave in Magnetic Arch With High Pressure Plasma
Sergey A. Koryagin, Mikhail E. Viktorov, Artem V. Korzhimanov et al. (+1 more)
The work analytically substantiates the parameters of the surface wave found in numerical modelling of the collision of two oncoming supersonic
plasma flows inside a
magnetic arc in application to the experiment on the laboratory setup “
Solar Wind” (Inst. Appl. Phys RAS). An ion-acoustic surface wave exists in the regime of dense
plasma flows when their dynamic pressure is of the order of the pressure of an undisturbed
magnetic field, so that the flows push the initial
magnetic field out of their volume. The wave frequency is in the range between the ion gyrofrequencies inside the
plasma bundle and in the outer region of the confining
magnetic field. In the external rarefied medium, the near-surface structure is a heterogeneous
magnetic sound, consistent in pressure and low total polarisation of the medium with the “isotropic” ion sound confined from the inside in a dense
plasma bundle. The energy of the structure is mainly contained in the kinetic energy of the wave motion of ions inside the tube. At the same time, the electric field strength is sharply increased outside. Firstly, the latter circumstance arises from the need to maintain a uniform electron electric drift velocity inside the transition layer. Secondly, the energetically weak ion sound propagating into the outer environment is close to electrostatic ion oscillations below the ion gyrofrequency in the external region, which are characterised by increased electric field strength across the ambient
magnetic field.
Read the full abstract ▾
All authors Sergey A. Koryagin, Mikhail E. Viktorov, Artem V. Korzhimanov, Andrey A. Elyasin
Applied Physics · Cross-listed from cond-mat.mtrl-sci
Resistance Switching Properties of Stoichiometric and Nitrogen Implanted Silicon Nitride Nanolayers on N and P-Type Si Substrates
A. E. Mavropoulis, P. Karakolis, N. Vasileiadis et al. (+6 more)
This paper examines the resistive switching characteristics of LPCVD SiNx MNOS ReRAM
cells on both heavily doped n- and p-type silicon substrates, focusing on the effects of nitrogen doping. Detailed comparisons of electrical properties through nitrogen implantation reveal variations in trap density and SET-RESET voltages between n and p conductivity Si substrates. Impedance spectroscopy further elucidates the conductive path formation and its resistance.
Read the full abstract ▾
All authors A. E. Mavropoulis, P. Karakolis, N. Vasileiadis, L. Sygellou, E. Stavroulakis, V. Ioannou-Sougleridis, P. Normand, G. Ch. Sirakoulis, P. Dimitrakis
Applied Physics · Cross-listed from cond-mat.mtrl-sci
Breakdown characteristics of SiNx with different stoichiometries for resistive memories
A.E. Mavropoulis, I. Kanellopoulos, G. Pissanos et al. (+6 more)
The breakdown characteristics of SiNx layers with different stoichiometries are explored. The stoichiometry of SiNx is modified by changing the gas flow rates during the LPCVD deposition. These layers are suitable for RRAM
cells.
Read the full abstract ▾
All authors A.E. Mavropoulis, I. Kanellopoulos, G. Pissanos, G. Samara, N. Vasileiadis, E. Stavroulakis, P. Normand, G. Ch. Sirakoulis, P. Dimitrakis
Applied Physics · Cross-listed from cond-mat.mtrl-sci
SiNx RRAMs performance with different stoichiometries
A.E. Mavropoulis, G. Pissanos, N. Vasileiadis et al. (+3 more)
The microstructure of SiNx is strongly affected by its stoichiometry, x. The stoichiometry of SiNx thin films can be modified by adjusting the gas flow rates during LPCVD deposition. The deficiency or excess of Si atoms enhance the formation of defects such as nitrogen vacancies, silicon dangling bonds etc., and thus can enable performance tuning of the resulting MIS RRAM devices. DC electrical characterization, impedance spectroscopy and constant voltage stress measurements were carried out to investigate the properties of non-stoichiometric silicon nitride films as resistive switching material. The average SET time for each device was measured by applying voltage ramps. Improvement in the SET/RESET voltages and SET time is observed. Finally, the stoichiometric film exhibits the lowest breakdown acceleration factor, while the Si-rich film the highest.
Read the full abstract ▾
All authors A.E. Mavropoulis, G. Pissanos, N. Vasileiadis, P. Normand, G.Ch. Sirakoulis, P. Dimitrakis
Accelerator Physics
Time Served
Evan Milton, Mark Austin and Dan McArthur
The following document provides a comprehensive look into the past, present, and future of Timing at Fermilab. By including historical context with technical implementation, this document seeks to help the reader gain a broader understanding of the facility and the mechanisms that enable the operation of Fermilab's accelerators
Read the full abstract ▾
Chemical Physics
Dark-State-Mediated Efficient Energy Trapping in a Model GFP Chromophore
Elisabeth Gruber, Lars H. Andersen, Laurence H. Stanley et al. (+3 more)
The functional properties of photoactive
proteins are governed by the interplay between bright and dark excited states. While the bright states are well-studied, the dark states, which are fundamental to photostability and light harvesting, are notoriously difficult to characterize. Here, we report the direct observation and full characterization of an optically dark, low-lying singlet excited state in the isolated anion of the meta green fluorescent
protein (GFP) chromophore. Using a combination of ultrafast time-resolved action-absorption and photoelectron spectroscopy, we have captured the formation of this state in 100 fs and measured its remarkably long lifetime of 94 ps. We unambiguously assign its charge-transfer character and reveal the precise trapping mechanism through high-level ab initio calculations. Our findings uncover a photoprotective mechanism in biomolecular anions where ultrafast internal conversion quenches electron emission, stabilizing long-lived electronic excitation even when the energy exceeds the electron detachment threshold.
Read the full abstract ▾
All authors Elisabeth Gruber, Lars H. Andersen, Laurence H. Stanley, Jan R. R. Verlet, Ivan S. Avdonin, Anastasia V. Bochenkova
Optics
Conservation of transverse orbital angular momentum for spatiotemporal optical vortices
Jordan Adams, Youngbin Park and Andy Chong
The transverse orbital angular momentum (OAM) of spatiotemporal optical
vortices (STOVs) has been a topic of active debate in recent years. Previous studies, relying on narrowband and paraxial approximations, resulted in unprecedented conclusions. Some researchers have proposed that electromagnetic waves require a modified definition of OAM to ensure conservation. In this work, we demonstrate that the transverse OAM of STOVs is highly sensitive to these commonly adopted approximations. Using the standard definition of OAM for electromagnetic waves, we demonstrate that the total transverse OAM is conserved during propagation once the narrowband and paraxial assumptions are removed.
Read the full abstract ▾
Atmospheric and Oceanic Physics
Rogue Vertical Drafts in the Mesosphere and Lower Thermosphere: Evidence and Implications
J. L. Chau, A. Berera and D. Huyghebaert
Observational evidence of extreme vertical velocities (|w| ge 12.5 m/s and at times greater than 50 m/s) in the mesosphere and lower thermosphere (MLT), has emerged in recent years. We refer to these events as Rogue Vertical Drafts (RVDs). They exceed five standard deviations of observed vertical velocities and appear as paired updraft-downdraft structures in varicose mode. Four-dimensional observations reveal that RVDs are intermittent, recurrent, and unpredictable. On average, they are expected to occur every sim 12 days during summer over Northern Norway, assuming a 1000 s interval. Different instruments may capture only portions of these events, for example, only upward or downward drafts when restricted to a single altitude range. Despite their rarity, their magnitudes and frequency suggest potential impacts on
dust-sized matter escaping from
planets, natural and anthropogenic space material, and MLT
climate and processes. We propose that RVDs are a fundamental yet under-recognized feature of the MLT, underscoring the need for global observations to assess their prevalence and significance.
Read the full abstract ▾
Geophysics
On the Fréchet interaction density of certain wave equations
Rafael Abreu and Chahana Nagesh
We extend the adjoint method to complex-valued PDEs and introduce the Fréchet interaction density, as the most fundamental interaction from which Fréchet sensitivity kernels can be derived. We apply this framework to four representative equations: two real-valued PDEs (the second-order wave equation and the Euler–Bernoulli beam equation) and two complex-valued PDEs (the complex transport equation and the Schrödinger equation with zero potential). We compute and analyze the Fréchet interaction densities for all four PDEs and show that the interaction shows consistent structure, with a waveform that depends on the initial conditions. For the Schrödinger equation, when the adjoint field is chosen as the complex conjugate of the forward wavefunction, the interaction density reduces algebraically to the Born probability density. Our results establish a unified approach to sensitivity analysis for real- and complex-valued PDEs.
Read the full abstract ▾
Physics and Society
A unified framework for identifying influential nodes in hypergraphs
Yajing Hao, Longzhao Liu, Xin Wang et al. (+4 more)
Identifying influential nodes plays a pivotal role in understanding, controlling, and optimizing the behavior of complex systems, ranging from social to biological and technological domains. Yet most centrality-based approaches rely on pairwise
topology and are purely structural, neglecting the higher-order interactions and the coupling between structure and dynamics. Consequently, the practical effectiveness of existing approaches remains uncertain when applied to complex spreading processes. To bridge this gap, we propose a unified framework, Initial Propagation Score (IPS), to directly embed propagation dynamics into influence assessment on higher-order networks. We analytically derive mechanism-aware influence measures by relating the early-stage dynamics and local topological characteristics to long-term outbreak sizes, and such explicit physical context endows IPS with robustness, transferability, and interpretability. Extensive experiments across multiple dynamics and more than 20 real-world hypergraphs show that IPS consistently outperforms other leading baseline centralities. Furthermore, IPS estimates node influence with only local neighborhood information, yielding computational efficiency and scalability to large-scale networks. This work underscores the necessity of considering dynamics for reliable identification of influential nodes and provides a concise principled basis for optimizing interventions in epidemiology, information
diffusion, and collective intelligence.
Read the full abstract ▾
All authors Yajing Hao, Longzhao Liu, Xin Wang, Zhihao Han, Ming Wei, Zhiming Zheng, Shaoting Tang
Instrumentation and Detectors
Advanced microwave SQUID multiplexer model incorporating readout power effects and Josephson junction inhomogeneities
Martin Neidig, Mathias Wegner and Sebastian Kempf
We present an advanced model for describing the readout power dependence of the resonance characteristics of a microwave SQUID multiplexer. Our model proves valid for SQUID screening parameters up to $\beta_\mathrm{L}<1$, hence covering the full range of practically relevant design parameters. We demonstrate that our model significantly improves agreement with experimental data compared to the existing models, thereby enabling optimization beyond the previously accessible parameter space. Moreover, our model supports non-sinusoidal current-phase relations of the rf-SQUID's Josephson junction, allowing, for the first time, for the modeling of devices based on Josephson tunnel junctions with inhomogeneous tunnel barriers. We show that the effects of such inhomogeneities are qualitatively similar to, yet distinct from, those of the screening parameter, making their inclusion essential for accurate characterization. Incorporating these effects yields great improved agreement with measurements, even at readout power conditions well beyond typical operating parameters.
Read the full abstract ▾
Fluid Dynamics
Noise dissipation mechanisms of an acoustic liner under grazing flow
Francesco Scarano, Angelo Paduano and Francesco Avallone
High-fidelity
lattice-Boltzmann very-large-eddy simulations are performed to describe the noise dissipation mechanisms in a single cavity acoustic liner subjected to grazing turbulent flow at a centreline Mach number of 0.3 and plane acoustic waves. The study examines the effects of sound pressure level (ranging from 130 to 160 dB) and source frequency, as well as of the direction of acoustic-wave propagation relative to the grazing flow. The acoustic energy dissipation mechanisms are the viscous losses within the shear layer forming along the internal walls of the orifice and the
vortex-shedding. The latter is quantified through Howe's energy corollary. In the absence of grazing flow, acoustic energy is dissipated almost equally during both inflow and
outflow phases, with
vortex shedding dominating at high SPL and viscous losses at low SPL. The introduction of a grazing flow alters the flow
topology; in particular, the shear layer past the orifice generates a quasi-steady
vortex that confines the acoustic-induced flow to the downstream half of the orifice. This topological change alters the two noise dissipation mechanisms: viscous losses increase at low SPL because the grazing flow pushes the fluid toward the downstream lip of the orifice;
vortex shedding becomes phase dependent, dissipating acoustic energy during the inflow phase and generating acoustic energy during the
outflow phase. This explains why the net acoustic dissipation decreases in the presence of grazing flow, highlighting the crucial role of near-wall flow
topology on liner performances.
Read the full abstract ▾
Atomic Physics
Table-top all-attosecond transient absorption spectroscopy
Mikhail Volkov, Evaldas Svirplys, Stefanos Carlström et al. (+4 more)
Attosecond transient absorption spectroscopy (ATAS) has emerged as a powerful technique within the field of attosecond science, combining extremely high temporal and excellent spectral resolution. So far, ATAS has been implemented in pump-probe experiments where an attosecond extreme-ultraviolet (XUV) pump or probe pulse was combined with a near-infrared (NIR) pulse in the femtosecond range, with the attosecond time resolution deriving from sub-cycle NIR-driven dynamics. Investigations of ultrafast electron dynamics in atoms, molecules and solids, with potential impact across physics, chemistry, and biology, would benefit significantly from the ability to perform all-attosecond transient absorption spectroscopy (AATAS). Here we demonstrate time-resolved AATAS using a table-top high-harmonic generation (HHG) source. The method is applied to investigate previously unresolved electronic coherences in Xe, revealing oscillatory valence hole motion with a 3-femtosecond period. In addition, systematic investigations of electron dynamics in Kr, Ar, and Ne are presented. Our work shows that, thanks to its broad bandwidth, high stability and easy accessibility, HHG is an ideal source for AATAS, offering the potential for replication in numerous laboratories.
Read the full abstract ▾
All authors Mikhail Volkov, Evaldas Svirplys, Stefanos Carlström, Serguei Patchkovskii, Misha Yu. Ivanov, Marc J. J. Vrakking, Bernd Schütte
Optics · Cross-listed from quant-ph
Exceptional points of arbitrary high orders induced by non-Markovian dynamics
Timofey T. Sergeev, Evgeny S. Andrianov and Alexander A. Zyablovsky
Exceptional points are singularities in the spectrum of non-Hermitian systems in which several eigenvectors are linearly dependent and their
eigenvalues are equal to each other. Usually it is assumed that the order of the exceptional point is limited by the number of degrees of freedom of a non-Hermitian system. In this letter, we refute this common opinion and show that non-Markovian effects can lead to dynamics characteristic of systems with exceptional points of higher orders than the number of degrees of freedom in the system. This takes place when the energy returns from reservoir to the system such that the dynamics of the system are divided into intervals in which it describes by the product of the exponential and a
polynomial function of ever-increasing order. We demonstrate that by choosing the observation time, it is possible to observe exceptional points of arbitrary high orders.
Read the full abstract ▾
Geophysics · Cross-listed from cs.CV
Seeing Soil from Space: Towards Robust and Scalable Remote Soil Nutrient Analysis
David Seu, Nicolas Longepe, Gabriel Cioltea et al. (+2 more)
Environmental variables are increasingly affecting agricultural decision-making, yet accessible and scalable tools for soil assessment remain limited. This study presents a robust and scalable modeling system for estimating soil properties in croplands, including soil organic carbon (SOC), total nitrogen (N), available phosphorus (P), exchangeable potassium (K), and pH, using remote sensing data and environmental
covariates. The system employs a hybrid modeling approach, combining the indirect methods of modeling soil through proxies and drivers with direct spectral modeling. We extend current approaches by using interpretable physics-informed
covariates derived from radiative transfer models (RTMs) and complex, nonlinear
embeddings from a foundation model. We validate the system on a harmonized
dataset that covers Europes cropland soils across diverse pedoclimatic zones. Evaluation is conducted under a robust validation framework that enforces strict spatial blocking, stratified splits, and statistically distinct train-test sets, which deliberately make the evaluation harder and produce more realistic error estimates for unseen regions. The models achieved their highest accuracy for SOC and N. This performance held across unseen locations, under both spatial cross-validation and an independent test set. SOC obtained a MAE of 5.12 g/kg and a CCC of 0.77, and N obtained a MAE of 0.44 g/kg and a CCC of 0.77. We also assess uncertainty through conformal calibration, achieving 90 percent coverage at the target confidence level. This study contributes to the digital advancement of agriculture through the application of scalable, data-driven soil analysis frameworks that can be extended to related domains requiring quantitative soil evaluation, such as carbon
markets.
Read the full abstract ▾
All authors David Seu, Nicolas Longepe, Gabriel Cioltea, Erik Maidik, Calin Andrei
Fluid Dynamics
Lazy Diffusion: Mitigating spectral collapse in generative diffusion-based stable autoregressive emulation of turbulent flows
Anish Sambamurthy and Ashesh Chattopadhyay
Turbulent flows posses broadband, power-law spectra in which multiscale interactions couple high-wavenumber fluctuations to large-scale dynamics. Although
diffusion-based generative models offer a principled probabilistic
forecasting framework, we show that standard DDPMs induce a fundamental spectral collapse: a
Fourier-space analysis of the forward SDE reveals a closed-form, mode-wise signal-to-noise ratio (SNR) that decays monotonically in wavenumber, $|k|$ for spectra $S(k)\!\propto\!|k|^{-\lambda}$, rendering high-wavenumber modes indistinguishable from noise and producing an intrinsic spectral bias. We reinterpret the noise schedule as a spectral regularizer and introduce power-law schedules $\beta(\tau)\!\propto\!\tau^\gamma$ that preserve fine-scale structure deeper into
diffusion time, along with Lazy
Diffusion, a one-step
distillation method that leverages the learned score geometry to bypass long reverse-time trajectories and prevent high-$k$ degradation. Applied to high-Reynolds-number 2D Kolmogorov
turbulence and $1/12^\circ$ Gulf of Mexico ocean reanalysis, these methods resolve spectral collapse, stabilize long-horizon autoregression, and restore physically realistic inertial-range scaling. Together, they show that naïve Gaussian scheduling is structurally incompatible with power-law physics and that physics-aware
diffusion processes can yield accurate, efficient, and fully probabilistic surrogates for multiscale dynamical systems.
Read the full abstract ▾
Optics · Cross-listed from quant-ph
Can Intense Quantum Light Beat Classical Uncertainty Relations?
Felipe Reibnitz Willemann, Mauro Antezza and Johannes Feist
Uncertainty relations are fundamental to
quantum mechanics, encoding limits on the simultaneous measurement of conjugate observables. Violations of joint uncertainty bounds can certify
entanglement – a resource critical for
quantum information protocols and increasingly relevant in strong-field physics. Here, we investigate the pairwise time-delay and frequency-bandwidth uncertainties for arbitrary multimode
quantum states of light, deriving a general lower bound for their joint product. We find that the nonclassical correction scales inversely with the average
photon number, a behavior rooted in the so-called “monogamy of
entanglement”. These results clarify the intensity scaling of
quantum advantages in nonclassical light states and highlight the interplay between
entanglement and
photon statistics.
Read the full abstract ▾
Applied Physics · Cross-listed from cond-mat.supr-con
Checkerboard-type Zhang-Rice States in Overdoped Cuprate Superconductors
Xiongfang Liu, Kun Han, Yan Peng et al. (+13 more)
Cuprate
superconductors remain central to condensed matter physics due to their technological relevance and unconventional, incompletely understood electronic behavior. While the canonical phase diagram and low-energy models have been shaped largely by studies of underdoped and moderately doped cuprates, the overdoped regime has received comparatively limited
attention.Here, we track the
evolution of the electronic structure from optimal to heavy overdoping in La2-xSrxCuO4(LSCO) using broadband optical spectroscopy across x=0.15-0.60. The measured spectral changes–including the redistribution of Zhang-Rice-related spectral weigh–are in qualitative agreement with determinant
quantum Monte Carlo simulations of the three-orbital Emery model, which together indicate a pronounced reconstruction of the electronic structure beyond hole concentrations x>0.2. Guided by these observations, we propose a spontaneous checkerboard-type Zhang-Rice electronic configuration that captures the coexistence of itinerant and localized carriers characteristic of the heavily overdoped state. Our results refine the doping-dependent Zhang-Rice-based framework for cuprates, illuminate how correlations persist deep into the overdoped regime, and provide new constraints on microscopic mechanisms of high-temperature superconductivity, with broader implications for correlated transition-metal
oxides.
Read the full abstract ▾
All authors Xiongfang Liu, Kun Han, Yan Peng, Yuanjie Ning, Jing Wu, Zhaoyang Luo, Difan Zhou, Zhigang Zeng, Qian He, Chuanbing Cai, Mark. B. H. Breese, Ariando Ariando, Chi Sin Tang, George A. Sawatzky, Mi Jiang, Xinmao Yin