Atmospheric and Oceanic Physics
Beyond Resolution: Multi-Scale Weather and Climate Data for Alpine Renewable Energy in the Digital Twin Era – First Evaluations and Recommendations
Irene Schicker, Marianne Bügelmayer-Blaschek, Annemarie Lexer et al. (+3 more)
When Austrian hydropower production plummeted by 44% in early 2025 due to reduced snowpack, it exposed a critical vulnerability: standard meteorological and climatological
datasets systematically fail in mountain regions that hold untapped renewable potential. This perspectives paper evaluates emerging solutions to the Alpine energy-
climate data gap, analyzing
datasets from global reanalyses (ERA5, 31 km) to kilometre-scale Digital Twins (
Climate DT, Extremes DT, 4.4 km), regional reanalyses (ARA, 2.5 km), and next-generation AI weather prediction models (AIFS, 31 km). The multi-resolution assessment reveals that no single
dataset excels universally: coarse reanalyses provide essential climatologies but miss valley-scale processes, while Digital Twins resolve Alpine dynamics yet remain computationally demanding. Effective energy planning therefore requires strategic
dataset combinations validated against energy-relevant indices such as population-weighted extremes, wind-gust return periods, and Alpine-adjusted storm thresholds. A key frontier is sub-hourly (10-15 min) temporal resolution to match grid-operation needs. Six evidence-based recommendations outline pathways for bridging spatial and temporal scales. As renewable deployment expands globally into complex terrain, the Alpine region offers transferable perspectives for tackling identical
forecasting and
climate analysis challenges in mountainous regions worldwide.
Read the full abstract ▾
All authors Irene Schicker, Marianne Bügelmayer-Blaschek, Annemarie Lexer, Katharina Baier, Kristofer Hasel, Paolo Gazzaneo
Instrumentation and Detectors · Cross-listed from cs.AR
Delay Time Characterization on FPGA: A Low Nonlinearity, Picosecond Resolution Time-to-Digital Converter on 16-nm FPGA using Bin Sequence Calibration
Sunwoo Park, Byungkwon Park, Eunsung Kim et al. (+3 more)
We present a Time-to-Digital Converter (TDC) implemented on a 16 nm Xilinx UltraScale Plus FPGA that achieves a resolution of 1.15 ps, RMS precision of 3.38 ps, a differential nonlinearity (DNL) of [-0.43, 0.24] LSB, and an integral nonlinearity (INL) of [-2.67, 0.15] LSB. This work introduces two novel hardware-independent post-processing techniques - Partial Order Reconstruction (POR) and Iterative Time-bin Interleaving (ITI) - that significantly enhance the performance of FPGA-based TDCs. POR addresses the missing code problem by inferring the partial order of each time bin through code density test data and directed acyclic graph (DAG) analysis, enabling near-complete recovery of usable bins. ITI further improves fine time resolution by merging multiple calibrated tapped delay lines (TDLs) into a single unified delay chain, achieving scalable resolution without resorting to averaging. Compared to state-of-the-art FPGA-based TDC architectures, the proposed methods deliver competitive or superior performance with reduced hardware overhead. These techniques are broadly applicable to high-resolution time measurement and precise delay calibration in programmable logic platforms.
Read the full abstract ▾
All authors Sunwoo Park, Byungkwon Park, Eunsung Kim, Jiwon Yune, Seungho Han, Seunggo Nam
Physics and Society
Establishing a pre-logical setting in a quantum model of psycho-analytic theory
Giulia Battilotti and Rosapia Lauro Grotto
A crucial issue both in cognitive and psychoanalytical theories deals with the origin of mental representations. In order to explore this issue, the paper analyzes a pre-logical setting, by considering a formalized approach to the foundations of psychoanalysis in logic, interpreting and integrating the views by Freud, Matte Blanco, Klein and Bion. The formalized approach derives from a
quantum model of
spin states. A representation of the
spin state of a particle in first order logic is abstracted to get a modality interpretable as an abstract projector. The last can be decomposed into a positive, negative and irreal component. The irreal component cannot emerge and, in logic, is absorbed by the two others, giving rise to logical duality. Due to its treatment of undefiniteness and coherence, the paper is meant to contribute to
quantum cognition, in its particular sense of affective
quantum cognition.
Read the full abstract ▾
Instrumentation and Detectors
Upgrade of Super-Kamiokande with Gadolinium
Yusuke Koshio, Masayuki Nakahata, Hiroyuki Sekiya et al. (+1 more)
Super-Kamiokande [SK] was upgraded through the addition of gadolinium sulfate to its ultrapure water, initiating the SK-Gd program. This development enables efficient
neutron tagging via the large capture cross section of gadolinium, greatly improving the identification of inverse beta decay events, the primary channel for detecting the diffuse
supernova neutrino background [DSNB]. The upgrade also enhances sensitivity to
galactic and pre-
supernova neutrinos, as well as atmospheric
neutrino interactions. To realize this capability, extensive work was performed, including the construction and operation of the EGADS demonstrator, the refurbishment of the SK tank, the development of radiopure gadolinium production methods, and the validation of the loading and uniformity of gadolinium in solution. Early SK-Gd operation has demonstrated high
neutron-tagging efficiency, reduced backgrounds, and world-leading limits on the DSNB flux. With these advances, SK-Gd now stands at the threshold of discovering the DSNB and opens a wide range of new opportunities in astrophysics and
neutrino physics.
Read the full abstract ▾
All authors Yusuke Koshio, Masayuki Nakahata, Hiroyuki Sekiya, Mark R. Vagins
Optics · Cross-listed from quant-ph
Controlled growth of rare-earth-doped TiO$_{2}$ thin films on III-V semiconductors for hybrid quantum photonic interfaces
Henry C. Hammer, Caleb Whittier, Nathan A. Helvy et al. (+3 more)
Quantum photonic networks require two distinct functionalities: bright single-
photon sources and long-lived
quantum memories. III-V
semiconductor quantum dots excel as deterministic and coherent
photon emitters, while rare-earth ions such as erbium (Er$^{3+}$) in crystalline
oxides offer exceptional
spin and optical coherence at telecom wavelengths. Combining these systems and their functionalities via direct epitaxy is challenging due to
lattice mismatch and incompatible growth conditions. Here we demonstrate low-temperature pulsed
laser deposition of Er$^{3+}$-doped TiO$_{2}$ thin films directly on GaAs and GaSb substrates. Controlled surface preparation with an arsenic cap and an oxygen-deficient buffer layer enables the growth of epitaxial anatase TiO$_{2}$ (001) at 390$^{o}$C with sub-300 pm surface roughness, while avoiding interface degradation. In contrast, high-temperature
oxide desorption or growth temperatures drive the transition to rough, polycrystalline rutile film, as confirmed by transmission electron microscopy. Minimal coincident interface area (MCIA) modeling explains the orientation-selective growth on GaAs and GaSb. Raman and cryogenic photoluminescence excitation spectroscopy verify the
crystal phase and optical activation of Er$^{3+}$ ions. This multi-parameter growth strategy helps preserve III-V
quantum dot functionality and yields smooth surfaces suitable for low-loss nanophotonic structures. Our results establish a materials platform for monolithically integrating rare-earth
quantum memories with
semiconductor photon sources, paving the way toward scalable hybrid
quantum photonic chips.
Read the full abstract ▾
All authors Henry C. Hammer, Caleb Whittier, Nathan A. Helvy, Christopher Rouleau, Nabil D. Bassim, Ravitej Uppu
Space Physics · Cross-listed from astro-ph.SR
Energy-dependent SEP Fe/O abundances during the May 2024 superstorm
G.D. Muro, C.M.S. Cohen, Z. Xu et al. (+16 more)
During mid-May 2024, active region (AR) 13664 produced a series of M- and X-class
flares along with several coronal mass ejections (CMEs) that resulted in exceptionally strong aurora at Earth. This study presents in-situ
solar energetic particle (SEP) ion composition data from
Solar Terrestrial Relations Observatory Ahead (STA), Advanced Composition Explorer (ACE), and Parker
Solar Probe (PSP) as their
magnetic connectivity to AR 13664 varied throughout the event period. Between 08 to 24 May, STA was separated by 12{\deg} in longitude from ACE at 0.96 AU. SEP intensities rose gradually due to merged CMEs from AR 13664. On 13 May, an M6
flare was followed by a rapid-onset SEP event at STA, although velocity dispersion analysis yielded no clear path length or release time. PSP, 95{\deg} longitudinally separated from Earth at 0.74 AU, observed gradually increasing SEP intensities beginning 11 May, followed by a jump in both SEP intensity and
magnetic field (>100 nT) on 16 May. These early event intervals display stepwise SEP increases, consistent with the passage of successive CMEs. On 20 May, an X16.5
flare from AR 13664 produced an Fe-rich SEP event observed at all three spacecraft despite their wide longitudinal separations. Throughout the period, Fe/O ratios ranged from <0.01 to >0.8 and increased with energy between 1 to 100 MeV/nuc. This trend deviates from the typical energy-dependent decrease expected from diffusive shock acceleration and suggests more complex scenarios, possibly involving variable suprathermal seed populations or species-dependent transport.
Read the full abstract ▾
All authors G.D. Muro, C.M.S. Cohen, Z. Xu, R.A. Leske, A.C. Cummings, S. Bale, G. D. Berland, E. R. Christian, M. E. Cuesta, M. I. Desai, F. Fraschetti, J. Giacalone, L. Y. Khoo, A. Labrador, D. J. McComas, J. G. Mitchell, M. Pulupa, N. A. Schwadron, M. M. Shen
Classical Physics
Coherent control of magnon-polaritons using an exceptional point
N. J. Lambert, A. Schumer, J. J. Longdell et al. (+2 more)
The amplitude of resonant oscillations in a non-Hermitian environment can either decay or grow in time, corresponding to a mode with either loss or gain. When two coupled modes have a specific difference between their loss or gain, a feature termed an exceptional point emerges in the excitations' energy
manifold, at which both the eigenfrequencies and eigenmodes of the system coalesce. Exceptional points have intriguing effects on the dynamics of systems due to their topological properties. They have been explored in contexts including optical, microwave, optomechanical, electronic and magnonic systems, and have been used to control systems including optical microcavities, the lasing modes of a PT-symmetric waveguide, and terahertz pulse generation. A challenging problem that remains open in all of these scenarios is the fully deterministic and direct manipulation of the systems' loss and gain on timescales relevant to coherent control of excitations. Here we demonstrate the rapid manipulation of the gain and loss balance of excitations of a magnonic hybrid system on durations much shorter than their decay rate, allowing us to exploit non-Hermitian physics for coherent control. By encircling an exceptional point, we demonstrate population transfer between coupled
magnon-polariton modes, and confirm the distinctive
chiral nature of exceptional point encircling. We then study the effect of driving the system directly through an exceptional point, and demonstrate that this allows the coupled system to be prepared in an equal superposition of eigenmodes. We also show that the dynamics of the system at the exceptional point are dependent on its generalised eigenvectors. These results extend the established toolbox of adiabatic transfer techniques with a new approach for coherent state preparation, and provide a new avenue for exploring the dynamical properties of non-Hermitian systems.
Read the full abstract ▾
All authors N. J. Lambert, A. Schumer, J. J. Longdell, S. Rotter, H. G. L. Schwefel
Fluid Dynamics
Variational Projection of Navier-Stokes: Fluid Mechanics as a Quadratic Programming Problem
Haithem Taha and Kshitij Anand
Gauss's principle of least constraint transforms a dynamics problem into a pure minimization problem, where the total magnitude of the constraint force is the cost function, minimized at each instant. Newton's equation is the first-order necessary condition for minimizing the Gaussian cost, subject to the given kinematic constraints. The principle of minimum pressure gradient (PMPG) is to incompressible fluid mechanics what Gauss's principle is to particle mechanics. The PMPG asserts that an incompressible flow evolves from one instant to another by minimizing the L2-norm of the pressure gradient force. A candidate flow field whose
evolution minimizes the pressure gradient cost at each instant is guaranteed to satisfy the Navier-Stokes equation. Consequently, the PMPG transforms the incompressible fluid mechanics problem into a pure minimization framework, allowing one to determine the
evolution of the flow field by solely focusing on minimizing the cost. In this paper, we show that the resulting minimization problem is a convex Quadratic Programming (QP) problem-one of the most computationally tractable classes in nonlinear optimization. Moreover, leveraging tools from analytical mechanics and the Moore-Penrose theory of generalized inverses, we derive an analytical solution for this QP problem. As a result, we present an explicit formula for the projected dynamics of the spatially discretized Navier-Stokes equation on the space of divergence-free fields. The resulting ODE is ready for direct time integration, eliminating the need for solving the Poisson equation in pressure at each time step. It is typically an explicit nonlinear ODE with constant coefficients. This compact form is expected to be highly valuable for both simulation and theoretical studies, including stability analysis and flow control design. We demonstrate the framework on the lid-driven cavity problem.
Read the full abstract ▾
Optics · Cross-listed from cond-mat.mes-hall
Measuring non-Abelian quantum geometry and topology in a multi-gap photonic lattice
Martin Guillot, Cédric Blanchard, Martina Morassi et al. (+8 more)
Recent discoveries in semi-metallic multi-gap systems featuring band singularities have galvanized enormous interest in particular due to the emergence of non-Abelian braiding properties of band nodes. This previously uncharted set of topological phases necessitates novel approaches to probe them in laboratories, a pursuit that intricately relates to evaluating non-Abelian generalizations of the Abelian
quantum geometric tensor (QGT) that characterizes
geometric responses. Here, we pioneer the direct measurement of the non-Abelian QGT. We achieve this by implementing a novel orbital-resolved polarimetry technique to probe the full Bloch
Hamiltonian of a six-band two-dimensional (2D) synthetic
lattice, which grants direct experimental access to non-Abelian quaternion charges, the Euler
curvature, and the non-Abelian
quantum metric associated with all bands.
Quantum geometry has been highlighted to play a key role on macroscopic phenomena ranging from superconductivity in flat-bands, to optical responses, transport, metrology, and
quantum Hall physics. Therefore, our work unlocks the experimental probing of a wide phenomenology of multi-gap systems, at the confluence of
topology, geometry and non-Abelian physics.
Read the full abstract ▾
All authors Martin Guillot, Cédric Blanchard, Martina Morassi, Aristide Lemaître, Luc Le Gratiet, Abdelmounaim Harouri, Isabelle Sagnes, Robert-Jan Slager, F. Nur Ünal, Jacqueline Bloch, Sylvain Ravets
Medical Physics · Cross-listed from eess.IV
Computed Tomography (CT)-derived Cardiovascular Flow Estimation Using Physics-Informed Neural Networks Improves with Sinogram-based Training: A Simulation Study
Jinyuxuan Guo, Gurnoor Singh Khurana, Alejandro Gonzalo Grande et al. (+2 more)
Background: Non-invasive imaging-based assessment of blood flow plays a critical role in evaluating heart function and structure. Computed
Tomography (CT) is a widely-used imaging modality that can robustly evaluate cardiovascular anatomy and function, but direct methods to estimate blood flow velocity from movies of contrast
evolution have not been developed. Purpose: This study evaluates the impact of CT imaging on Physics-Informed Neural Networks (PINN)-based flow estimation and proposes an improved framework, SinoFlow, which uses sinogram data directly to estimate blood flow. Methods: We generated pulsatile flow fields in an idealized 2D vessel bifurcation using computational fluid dynamics and simulated CT scans with varying gantry rotation speeds, tube currents, and pulse mode imaging settings. We compared the performance of PINN-based flow estimation using reconstructed images (ImageFlow) to SinoFlow. Results: SinoFlow significantly improved flow estimation performance by avoiding propagating errors introduced by filtered backprojection. SinoFlow was robust across all tested gantry rotation speeds and consistently produced lower mean squared error and velocity errors than ImageFlow. Additionally, SinoFlow was compatible with pulsed-mode imaging and maintained higher accuracy with shorter pulse widths. Conclusions: This study demonstrates the potential of SinoFlow for CT-based flow estimation, providing a more promising approach for non-invasive blood flow assessment. The findings aim to inform future applications of PINNs to CT images and provide a solution for image-based estimation, with reasonable acquisition parameters yielding accurate flow estimates.
Read the full abstract ▾
All authors Jinyuxuan Guo, Gurnoor Singh Khurana, Alejandro Gonzalo Grande, Juan C. del Alamo, Francisco Contijoch
Geophysics
Extending the Joint Probability Method to Compound Flooding: Transition Zone Delineation, Flood Depth Attribution, and Design Event Selection
Mark S. Bartlett, Nathan Geldner, Hugh J. Roberts et al. (+9 more)
Quantifying the frequency of compound flood depths is a fundamental challenge in low-gradient coastal watersheds, where flood hazards arise from the nonlinear interaction of storm surge, rainfall, and riverine flooding. Existing approaches often characterize either the joint occurrence of flood drivers or the flood response for prescribed events, but they do not derive the long-term frequency distribution of compound flood depths from probabilistic descriptions of rainfall and antecedent hydrologic conditions. Traditionally, coastal flood frequency has been quantified using the Joint Probability Method (JPM), which represents storm surge probabilistically. Although recent studies have incorporated rainfall into JPM-based analyses, rainfall is treated as a deterministic function of JPM storm characteristics rather than as a conditional probability distribution. Here, we extend the JPM by coupling its event-scale
stochastic description of storm characteristics with probabilistic rainfall realizations and
stochastic antecedent hydrologic conditions, thereby enabling propagation of these
stochastic processes through the flood response to derive the compound flood-depth distribution. The framework provides a statistical basis for delineating compound flood transition zones, probabilistically attributing flood depths to hydrologic and coastal processes, and selecting response-based design storms for specified annual exceedance probabilities (or return periods). Application to the Lake Maurepas basin, Louisiana, shows that the statistically defined compound flood transition zone is more than twice the area identified from event-based analyses and that compound interactions increase flood depths by up to 0.7 m. This extended JPM establishes a probabilistic foundation for compound flood hazard assessment and response-based design.
Read the full abstract ▾
All authors Mark S. Bartlett, Nathan Geldner, Hugh J. Roberts, Zach Cobell, Brett McMann, Luis Partida, Ovel Diaz, David R. Johnson, Hanbeen Kim, Gabriele Villarini, Shubra Misra, Muthukumar Narayanaswamy
Optics
Midinfrared Semiconductor Photonics - A Roadmap
J. R. Meyer, I. Vurgaftman, S.-Q. Yu et al. (+56 more)
Semiconductor photonic devices operating in the midwave infrared (mid-IR, which we roughly define here as wavelengths spanning 3 to 14 microns) uniquely address a wide range of current practical needs. These include chemical sensing, environmental monitoring, industrial process control, medical diagnostics, thermal imaging,
LIDAR, free space optical communication, and security monitoring. However, mid-IR device technologies are currently still works in progress that are generally much less mature than their near infrared and visible counterparts. Not only are most of the relevant materials more difficult to grow and process, but attainment of the desired optical device performance is often fundamentally more challenging. This Roadmap will review the leading applications for mid-IR optoelectronics, summarize the status and deficiencies of current device technologies, and then suggest possible roadmaps for improving and maturing the performance, manufacturability, and cost of each device type so the critical needs that are uniquely addressed by mid-IR photonics can be satisfied.
Read the full abstract ▾
All authors J. R. Meyer, I. Vurgaftman, S.-Q. Yu, R. Q. Yang, A. M. Andrews, G. Strasser, B. Schwarz, M. Razeghi, L. Shterengas, G. Kipshidze, G. Belenky, L. Sterczewski, W. Zhou, S. Lee, M. Pan, R. Szedlak, N. Schäfer, J. Koeth, R. Weih, A. Rogalski, A. Piotrowski, J. Sobieski, P. Leszcz, J. Piotrowski, M. R. Mirzaei, R. Kim, J. H. Park, D. Z. Ting, M. B. Santos, V. Trinite, S. Pes, J.-L. Reverchon, N. Gajowski, S. Krishna, W. Du, R. Soref, E. Tournié, J.-B. Rodriguez, L. Cerutti, A. Spott, S. Jung, N. Nookala, A. Vasanelli, B. Chomet, C. Sirtori, N. P. Li, M. A. Zondlo, S. Jain, J. Midkiff, M. Hlaing, K.-C. Fan, R. T. Chen, F. Grillot, S. Zaminga, P. T. Camp, P.-Y. Hsiao, G. Daligou, S. Molesky, O. Moutanabbir
Optics
Ultrafast, reconfigurable all-optical beam steering and spatial light modulation
Claudio U. Hail, Lior Michaeli and Harry A. Atwater
Achieving spatiotemporal control of light at subwavelength and subcycle scales is an important milestone in the development of new photonic materials and technologies. Ultrafast spatiotemporal light modulation currently relies on electronic interband and intraband transitions that yield pronounced refractive index changes but typically suffer from slow, picosecond response times due to carrier relaxation. Here we show that by leveraging resonant light-matter interactions in a high-quality factor metasurface it is possible to use the optical Kerr effect, a weaker, but instantaneous optoelectronic polarization effect, to achieve ultrafast, reconfigurable light modulation with unprecedented spatial and temporal control. By the subwavelength all-optical tuning of the refractive index of the dielectric metasurface unit
cells, we experimentally demonstrate pulse-limited beam steering with a 74-fs response time at angles up to $\pm $13{\deg} in the near-infrared. The steering originates from the Kerr effect with a background contribution arising from slower two-
photon-excited free carrier absorption. Additionally, we observe spatial back-action, linear frequency conversion, and demonstrate arbitrary ultrafast spatial light modulation in two dimensions. Our findings open the possibility of realizing new ultrafast physics in metastructures with applications in signal processing, pulse shaping, and ultrafast imaging.
Read the full abstract ▾
Instrumentation and Detectors
Challenges and strategies in verification of FastRICH ASIC for the LHCb RICH detector
M. Lupi, R. Ballabriga, F. N. Bandi et al. (+13 more)
The FastRICH ASIC provides high-precision, triggerless readout for the LS3 Enhancements and Upgrades II of the LHCb RICH detector. The demands of continuous data acquisition and varying hit rates across the detector impose unique challenges on the ASIC's design and verification. This work presents the verification strategy for FastRICH, focusing on functional correctness, timing performance, and operational robustness. The methodology includes simulations across occupancy scenarios, validation of timing precision, and stress testing under pile-up and high-rate conditions. Results demonstrate that FastRICH meets its performance requirements over the full range of expected occupancies. Key design and verification challenges specific to triggerless, fast-timing ASICs are discussed, along with lessons learned for future developments.
Read the full abstract ▾
All authors M. Lupi, R. Ballabriga, F. N. Bandi, G. Bergamin, D. Ceresa, D. Gascon, S. Gomez, J. Kaplon, R. Manera, J. Mauricio, A. Paternò, D. Peninon-Herbaut, A. Pulli, S. Scarfì, G. J. Wegrzyn, K. Wyllie
Biological Physics · Cross-listed from q-bio.CB
Diffusion Dynamics in Biofilms with Time-Varying Channels
Yanahan Paramalingam and Adam Noel
A biofilm is a self-contained community of bacteria that uses signaling molecules called autoinducers (AIs) to coordinate responses through the process of quorum sensing. Biofilms exhibit a dual role that drives interest in both combating antimicrobial resistance (AMR) and leveraging their potential in bioprocessing, since their products can have commercial potential. Previous work has demonstrated how the distinct anisotropic channel geometry in some biofilms affects AIs propagation therein. In this paper, a 2D anisotropic biofilm channel model is extended to be a time-varying channel (TVC), in order to represent the
diffusion dynamics during the maturation phase when water channels develop. Since maturation is associated with the development of anisotropy, the time-varying model captures the shift from isotropic to anisotropic
diffusion. Particle-based simulation results illustrate how the TVC is a hybrid scenario incorporating propagation features of both isotropic and anisotropic
diffusion. This hybrid behavior aligns with biofilm maturation. Further study of the TVC includes characterization of the mutual information (MI), which reveals that an increased AI count, reduced transmitter – receiver distance, greater degree of anisotropy, and shorter inter-symbol interference lengths increase the MI. Finally, a brief dimensional analysis demonstrates the scalability of the anisotropic channel results for larger biofilms and timescales.
Read the full abstract ▾
Geophysics
Advancing Subsurface Discovery and Geothermal Monitoring with an Agentic Artificial Intelligence Framework
Randy Harsuko, Zhengfa Bi, Guodong Chen et al. (+1 more)
Geothermal field development typically involves complex processes that require multi-disciplinary expertise in each process. Thus, decision-making often demands the integration of geological, geophysical, reservoir engineering, and operational data under tight time constraints. We present Geothermal Analytics and Intelligent
Agent, or
GAIA, an AI-based system for automation and assistance in geothermal field development.
GAIA consists of three core components:
GAIA Agent,
GAIA Chat, and
GAIA Digital Twin, or DT, which together constitute an agentic
retrieval-augmented generation (RAG) workflow. Specifically,
GAIA Agent, powered by a pre-trained large
language model (LLM), designs and manages task pipelines by autonomously querying knowledge bases and orchestrating multi-step analyses.
GAIA DT encapsulates classical and surrogate physics models, which, combined with built-in domain-specific subroutines and visualization tools, enable predictive modeling of geothermal systems. Lastly,
GAIA Chat serves as a web-based interface for users, featuring a ChatGPT-like layout with additional functionalities such as interactive visualizations, parameter controls, and in-context document
retrieval. To ensure
GAIA's specialized capability for handling complex geothermal-related tasks, we curate a
benchmark test set comprising various geothermal-related scenarios and rigorously evaluate the system's performance. Beyond task-level automation,
GAIA is a unified framework that tightly couples physics-based modeling with agentic
reasoning, which enables both domain-infused agentic evolutionary
algorithm (meta-
evolution) and end-to-end geothermal data processing within a single system. This integration highlights
GAIA's potential not only as an assistive tool but as a platform for accelerating scientific discovery and enabling more autonomous, data-driven geothermal field development.
Read the full abstract ▾
All authors Randy Harsuko, Zhengfa Bi, Guodong Chen, Nori Nakata
History and Philosophy of Physics · Cross-listed from cond-mat.stat-mech
Quantum Inaccessibility
Ira Wolfson
Loschmidt's paradox asks why macroscopic irreversibility is universal despite the time-reversal
symmetry of microscopic dynamics. We argue that irreversibility is not a property of the dynamics but of accessibility: chaotic
evolution drives phase-space structure below the
quantum resolution scale $\ell_\hbar$, at a critical time $t_c = \lambda^{-1}\ln(\delta_0/\ell_\hbar)$, after which the time-reversed microstate exists as a valid solution of Hamilton's equations but cannot be selected by any physically admissible operation. The mechanism operates entirely within the semiclassical regime $t_c \leq t_E$, where classical geometry is exact. This provides a dynamical resolution of the Loschmidt paradox. The
quantum foundation is established using a Krylov-complexity framework: we prove that for any $H(t)=H(-t)$, the
quantum Lyapunov exponent satisfies $\lambda_L^{\rm forward} = \lambda_L^{\rm backward}$. The arrow of time is not in the dynamics. The mechanism predicts sigmoid fidelity decay, logarithmic scaling of $t_c$ with $\lambda^{-1}$, and ensemble-size independence of the inaccessibility threshold – all consistent with three decades of Loschmidt echo experiments and confirmed in a stadium-billiard simulation reported here. Underlying everything:
quantum mechanics conserves information exactly.
Entropy, defined as the logarithm of the multiplicity $\Omega$ – the number of possibilities consistent with the available information – can only increase when information becomes operationally inaccessible. The second law reflects not a breakdown of microscopic reversibility, but the dynamical inaccessibility of the information required to reverse it.
Read the full abstract ▾
Instrumentation and Detectors
Quadrature-witness readout for backscatter mitigation in gravitational-wave detectors limited by back-action
Niels Böttner, Roman Schnabel and Mikhail Korobko
Disturbances in gravitational wave (GW) observational data are often caused by non-stationary noise in the detector itself, such as back-scattering of
laser stray light into the signal field. Unlike GW signals, non-stationary noise can appear in both the GW-signal quadrature and the orthogonal quadrature, which is usually not measured. Simultaneous sensing of this orthogonal quadrature provides a witness channel that can be used to reconstruct the disturbance in the signal quadrature enabling a subtraction of non-stationary noise. Here, we present the concept of quadrature witness that is compatible with frequency-dependent squeezing, which is already used to simultaneously reduce
photon shot noise and
photon radiation pressure noise. We demonstrate that implementing this approach in a GW detector could reduce noise caused by loud back-scatter events, thereby improving the overall sensitivity and robustness of GW observatories.
Read the full abstract ▾
Optics
Single-shot near-field reconstruction of metamaterial dispersion
Eugene Koreshin, Denis Sakhno, Jim A. Enriquez et al. (+1 more)
We present a single-shot near-field technique, where the near-field scan is performed on a single sample without repeating measurements or averaging over multiple samples, to reconstruct the isofrequency surfaces of metamaterials in the microwave regime. In our approach, we excite resonant modes using a fixed source in a resonator composed of the material under test and map the in-plane field distribution with a movable probe. Applying a fast
Fourier transform (FFT) to the measured field reveals the sample's in-plane dispersion. By extending this analysis over multiple frequencies and comparing the results with Fabry-Pérot resonances, we retrieve the full three-dimensional dispersion relation. When we apply the method to a double non-connected wire metamaterial, it accurately captures the low-frequency
hyperbolic isofrequency surface, providing both a precise experimental tool and conceptual insight into spatially dispersive metamaterials.
Read the full abstract ▾
All authors Eugene Koreshin, Denis Sakhno, Jim A. Enriquez, Pavel A. Belov
Optics
A broadband silicon photonic-integrated-circuit based RF spectrum analyzer with 10 MHz spectral resolution
Brandon Redding, Joseph B. Murray, Matthew J. Murray et al. (+10 more)
Designing miniaturized optical spectrometers is an increasingly active area of research as spectrometers are crucial components for a wide range of applications including chemical and material analysis, medical diagnostics, classical and
quantum sensing, characterization of light sources, and
radio frequency (RF) spectrum analysis. Among these applications, designing on-chip spectrometers for RF spectrum analysis is particularly challenging since it requires combining high resolution and large bandwidth with a fast update rate. Existing chip-scale spectrometers cannot achieve the resolution required for RF analysis, setting aside challenges in maintaining a fast update rate and broad bandwidth. In this work, we address these challenges by introducing a silicon photonic integrated
circuit (PIC)-based RF spectrum analyzer that combines an ultra-high-resolution speckle spectrometer with an interferometric RF-to-optical encoding scheme. The PIC-based speckle spectrometer uses a path-mismatched multimode interferometer with inverse designed splitters to compensate for waveguide loss, enabling a record-high resolution of 100 MHz (0.8 pm at a wavelength of 1550 nm). To further improve the resolution of the overall RF spectrum analyzer, we modify the RF-to-optical encoding scheme by directing the RF signal through a path mismatched interferometer and encoding the outputs of the RF interferometer on separate optical carriers. This further reduces the RF spectral correlation width of the combined system, enabling the RF spectrum analyzer to resolve RF tones separated by 10 MHz across a bandwidth of 10 GHz. Since this approach operates as a single-shot spectrometer, it can support fast update rates, providing a path to compact, persistent wideband RF spectrum analysis.
Read the full abstract ▾
All authors Brandon Redding, Joseph B. Murray, Matthew J. Murray, Ross T. Schermer, Nicholas Cox, Sean Pang, Kate Musick, Christopher Long, Jayson Briscoe, Lewis G. Carpenter, Saaketh Desai, Nick Karl, Raktim Sarma
Optics · Cross-listed from cond-mat.mes-hall
Unconventional quantization of 2D plasmons in cavities formed by gate slots
Ilia Moiseenko, Zhanna Devizorova, Olga Polischuk et al. (+2 more)
We demonstrate that the slot between parallel metal gates placed above two-dimensional electron system (2DES) forms a plasmonic cavity with unconventional mode quantization. The resonant plasmon modes are excited when the slot width $L$ and the plasmon wavelength $\lambda$ satisfy the condition $L = \lambda/8 +n \times \lambda/2$, where $n=0, 1, 2 \ldots$. The lowest resonance occurs at a surprisingly small cavity size, specifically one eighth of the plasmon wavelength, which contrasts with the conventional half-wavelength Fabry-Perot cavities in optics. This unique quantization rule arises from a non-trivial phase shift of $-\pi/4$ acquired by the 2D plasmon upon reflection from the edge of the gate. The slot plasmon modes exhibit weak decay into the gated 2DES region, with the decay rate being proportional to the square root of the separation between the gate and the 2DES. Absorption cross-section by such slots reaches $\sim 50$ % of the fundamental dipole limit without any matching strategies, and is facilitated by field enhancement at the metal edges.
Read the full abstract ▾
All authors Ilia Moiseenko, Zhanna Devizorova, Olga Polischuk, Viacheslav Muravev, Dmitry Svintsov
Optics
A quasi-bound band in the continuum in a photonic slab
Stanislav Tsoi, Nicholas Proscia, Marc Christophersen et al. (+6 more)
Bound states in the continuum (BIC) are localized waves in electronic, photonic and acoustic systems, which remain decoupled from surrounding propagating waves and hence maintain their oscillation for extraordinary long time [Nat Rev Mater 1, 16048 (2016)]. In photonic
crystals,
symmetry-protected quasi-BICs (SP-qBIC) have been realized at high
symmetry points of the Brillouin zone and utilized in photonic
crystal and distributed feedback
lasers. In the present work, we measure wavevector-resolved photoluminescence (PL) of monolayer WSe2 weakly coupled to a photonic slab, consisting of a square array of aluminum nanodisks. The results show that the slab supports a continuous band of
symmetry-protected quasi-bound states along the Gamma-X direction, extending from the previously reported SP-qBIC at the Gamma point. The spectral width of this quasi-bound band in the continuum remains narrow through at least a half of the Brillouin zone, indicating its long lifetime.
Read the full abstract ▾
All authors Stanislav Tsoi, Nicholas Proscia, Marc Christophersen, Joseph Christodoulides, Hsun-Jen Chuang, Michael Povolotskyi, Kathleen McCreary, Paul Cunningham, Igor Vurgaftman
Geophysics
Deep Learning-Driven Downscaling for Climate Risk Assessment of Projected Temperature Extremes in the Nordic Region
Parthiban Loganathan, Elias Zea, Ricardo Vinuesa et al. (+1 more)
Rapid changes and increasing climatic variability across the widely varied Koppen-Geiger regions of northern Europe generate significant needs for adaptation. Regional planning needs high-resolution projected temperatures. This work presents an integrative downscaling framework that incorporates
Vision Transformer (ViT), Convolutional Long Short-Term
Memory (ConvLSTM), and Geospatial Spatiotemporal
Transformer with
Attention and Imbalance-Aware Network (GeoStaNet) models. The framework is evaluated with a multicriteria decision system, Deep Learning-TOPSIS (DL-TOPSIS), for ten strategically chosen meteorological stations encompassing the temperate oceanic (Cfb), subpolar oceanic (Cfc), warm-summer continental (Dfb), and subarctic (Dfc)
climate regions. Norwegian Earth System Model (NorESM2-LM) Coupled Model Intercomparison Project Phase 6 (CMIP6) outputs were bias-corrected during the 1951-2014 period and subsequently validated against earlier observations of day-to-day temperature metrics and diurnal range statistics. The ViT showed improved performance (Root Mean Squared Error (RMSE): 1.01 degrees C; R^2: 0.92), allowing for production of credible downscaled projections. Under the SSP5-8.5 scenario, the Dfc and Dfb
climate zones are projected to warm by 4.8 degrees C and 3.9 degrees C, respectively, by 2100, with expansion in the diurnal temperature range by more than 1.5 degrees C. The Time of Emergence signal first appears in subarctic winter seasons (Dfc: approximately 2032), signifying an urgent need for adaptation measures. The presented framework offers station-based, high-resolution estimates of uncertainties and extremes, with direct uses for adaptation policy over high-latitude regions with fast environmental change.
Read the full abstract ▾
All authors Parthiban Loganathan, Elias Zea, Ricardo Vinuesa, Evelyn Otero
Medical Physics
Dexterous Intramyocardial Needle Ablation (d-INA): Design, Fabrication, and In-Vivo Validation
Chang Zhou, Charles P. Hong, Yifan Wang et al. (+4 more)
Radiofrequency ablation is widely used to prevent ventricular tachycardia (VT) by creating lesions to inhibit arrhythmias; however, the current surface ablation catheters are limited in creating lesions that are deeper within the left ventricle (LV) wall. Intramyocardial needle ablation (INA) addresses this limitation by penetrating the myocardium and delivering energy from within. Yet, existing INA catheters lack adequate dexterity to navigate the highly asymmetric, trabeculated LV chamber and steer around papillary structures, limiting precise targeting. This work presents a novel dexterous INA (d-INA) toolset designed to enable effective manipulation and creation of deep ablation lesions. The system consists of an outer sheath and an inner catheter, both bidirectionally steerable, along with an integrated ablation needle assembly. Benchtop tests demonstrated that the sheath and catheter reached maximum bending
curvatures of 0.088~mm$^{-1}$ and 0.114~mm$^{-1}$, respectively, and achieved stable C-, S-, and non-planar S-shaped configurations. Ex-vivo studies validated the system's stiffness modulation and lesion-creation capabilities. In-vivo experiments in two swine demonstrated the device's ability to reach previously challenging regions such as the LV summit, and achieved a 219% increase in ablation depth compared with a standard ablation catheter. These results establish the proposed d-INA as a promising platform for achieving deep ablation with enhanced dexterity, advancing VT treatment.
Read the full abstract ▾
All authors Chang Zhou, Charles P. Hong, Yifan Wang, Ehud J. Schmidt, Junichi Tokuda, Aravindan Kolandaivelu, Yue Chen
Physics and Society
The Normal, the Natural, and the Harmonic
Theodore Modis
Use is made of rigorous definitions for the terms normal, natural, and harmonic to reveal a number of unfamiliar aspects about them. The Gaussian distribution is not sufficient to determine who is normal, and fluctuations above or below a natural-growth curve may or may not be natural. A recipe for harmonically sustained natural growth requires that the overlap during the substitution process must be limited. As a consequence the overall growth process must experience good as well as bad 'seasons'.
Read the full abstract ▾
Physics and Society
Leveraging LLM-based agents for social science research: insights from citation network simulations
Jiarui Ji, Runlin Lei, Xuchen Pan et al. (+8 more)
The emergence of Large
Language Models (LLMs) demonstrates their potential to encapsulate the logic and patterns inherent in human behavior simulation by leveraging extensive web data pre-training. However, the boundaries of LLM capabilities in social simulation remain unclear. To further explore the social attributes of LLMs, we introduce the CiteAgent framework, designed to generate citation networks based on human-behavior simulation with LLM-based
agents. CiteAgent successfully captures predominant phenomena in real-world citation networks, including power-law distribution, citational distortion, and shrinking diameter. Building on this realistic simulation, we establish two LLM-based research paradigms in social science: LLM-SE (LLM-based Survey Experiment) and LLM-LE (LLM-based Laboratory Experiment). These paradigms facilitate rigorous analyses of citation network phenomena, allowing us to validate and challenge existing theories. Additionally, we extend the research scope of traditional science of science studies through idealized social experiments, with the simulation experiment results providing valuable insights for real-world academic environments. Our work demonstrates the potential of LLMs for advancing science of science research in social science.
Read the full abstract ▾
All authors Jiarui Ji, Runlin Lei, Xuchen Pan, Zhewei Wei, Hao Sun, Yankai Lin, Xu Chen, Yongzheng Yang, Yaliang Li, Bolin Ding, Ji-Rong Wen
Fluid Dynamics · Cross-listed from stat.ML
Bifidelity Karhunen-Loève Expansion Surrogate with Active Learning for Random Fields
Aniket Jivani, Cosmin Safta, Beckett Y. Zhou et al. (+1 more)
We present a bifidelity Karhunen–Loève expansion (KLE) surrogate model for field-valued quantities of interest (QoIs) under uncertain inputs. The QoIs considered here are scalar fields. The approach combines the spectral efficiency of the KLE with
polynomial chaos expansions (PCEs) to preserve an explicit mapping between input uncertainties and output fields. By coupling inexpensive low-fidelity (LF) simulations that capture dominant response trends with a limited number of high-fidelity (HF) simulations that correct for systematic bias, the proposed method can enable accurate and computationally affordable surrogate construction. To further improve surrogate accuracy, we develop an active learning strategy that adaptively selects new HF evaluations based on the surrogate's generalization error, estimated via cross-validation and modeled using Gaussian process regression. New HF samples are then acquired by maximizing an expected improvement criterion, targeting regions of high surrogate error. The resulting BF-KLE-AL framework is demonstrated on three examples of increasing complexity: a one-dimensional analytical
benchmark, a two-dimensional convection-
diffusion system, and a three-dimensional turbulent round jet simulation based on Reynolds-averaged Navier–Stokes (RANS) and enhanced delayed detached-eddy simulations (EDDES). The experiments show that bifidelity gains depend on LF accuracy, discrepancy approximation, and the allocation of simulation cost. Active learning improves prediction over random sampling in several settings, while the cost-matched comparisons identify both favorable regimes and cases where an HF-only surrogate is more accurate.
Read the full abstract ▾
All authors Aniket Jivani, Cosmin Safta, Beckett Y. Zhou, Xun Huan
Instrumentation and Detectors
Analytical Modeling of Asynchronous Event-Driven Readout Architectures Using Queueing Theory
Dominik S. Górni and Grzegorz W. Deptuch
Event-driven imagers and sensor arrays commonly employ asynchronous arbiter trees with a synchronous acknowledge to serialize requests. We present an analytical framework that models the root as an \(M/D/1\) queue with deterministic
quantum \(T\) and implements losses at the sources through one-slot gating. The admitted rate, loss probability, utilization, and mean sojourn time are coupled by self-consistent relations; a closed form for \(\mathbb{E}[S_t]\) separates fixed path delay \(\tau_0\) from queueing effects. The framework matches post-layout results of a physical prototype over light to heavy traffic, reproducing saturation at \(1/T\) and the observed latency growth, while classical \(M/G/1/K\) and Engset-type abstractions diverge at higher occupancy. Because all relations are algebraic, they enable rapid sizing at design time, including the impact of partitioning into independent tiles: reducing fan-in lowers arbitration depth and \(\tau_0\), decreases loss, and improves latency at fixed \(T\), with throughput adding across tiles. The model thereby links architectural parameters to performance metrics and supports selection of acknowledge period, tiling, and link count under practical constraints.
Read the full abstract ▾
Physics Education
Introducing Quantum Computing into Statistical Physics: Random Walks and the Ising Model with Qiskit
Zihan Li, Dan A. Mazilu and Irina Mazilu
Quantum computing offers a powerful new perspective on probabilistic and collective behaviors traditionally taught in statistical physics. This paper presents two classroom-ready modules that integrate
quantum computing into the undergraduate curriculum using Qiskit: the
quantum random walk and the Ising model. Both modules allow students to simulate and contrast classical and
quantum systems, deepening their understanding of concepts such as superposition, interference, and statistical distributions. We outline the
quantum circuits involved, provide sample code and student activities, and discuss how each example can be used to enhance student engagement with statistical physics. These modules are suitable for integration into courses in statistical mechanics, modern physics, or as part of an introductory unit on
quantum computing.
Read the full abstract ▾
Computational Physics · Cross-listed from cond-mat.mtrl-sci
Efficient GPU Parallelization of Electronic Transport and Nonequilibrium Dynamics from Electron-Phonon Interactions in the Perturbo Code
Shiyu Peng, Donnie Pinkston, Jia Yao et al. (+3 more)
The Boltzmann transport equation (BTE) with electron-
phonon (e-ph) interactions computed from first principles is widely used to study electronic transport and nonequilibrium dynamics in materials. Calculating the e-ph collision integral is the most important step in the BTE, but it remains computationally costly, even with current MPI+OpenMP parallelization. This challenge makes it difficult to study materials with large unit
cells and to achieve high resolution in momentum space. Here, we show acceleration of BTE calculations of electronic transport and ultrafast dynamics using graphical processing units (GPUs). We implement a novel data structure and
algorithm, optimized for GPU hardware and developed using OpenACC, to process scattering channels and efficiently compute the collision integral. This approach significantly reduces the overhead for data referencing, movement, and synchronization. Relative to the efficient CPU implementation in the open-source package Perturbo (v2.2.0), used as a baseline, this approach achieves a speed-up of 40 times for both transport and nonequilibrium dynamics on GPU hardware, and achieves nearly linear scaling up to 100 GPUs. The novel data structure can be generalized to other electron interactions and scattering processes. We released this GPU implementation in the latest public version (v3.0.0) of Perturbo. The new MPI+OpenMP+GPU parallelization enables sweeping studies of e-ph physics and electron dynamics in conventional and
quantum materials, and prepares Perturbo for exascale supercomputing platforms.
Read the full abstract ▾
All authors Shiyu Peng, Donnie Pinkston, Jia Yao, Sergei Kliavinek, Ivan Maliyov, Marco Bernardi