Accelerator Physics
Reinforcement Learning for Accelerator Beamline Control: a simulation-based approach
Anwar Ibrahim, Alexey Petrenko, Maxim Kaledin et al. (+3 more)
Particle accelerators play a pivotal role in advancing scientific research, yet optimizing beamline configurations to maximize particle transmission remains a labor-intensive task requiring expert intervention. In this work, we introduce RLABC (Reinforcement Learning for Accelerator Beamline Control), a Python-based library that reframes beamline optimization as a reinforcement learning (RL) problem. Leveraging the Elegant simulation framework, RLABC automates the creation of an RL environment from standard
lattice and element input files, enabling sequential tuning of magnets to minimize particle losses. We define a comprehensive state representation capturing beam statistics, actions for adjusting magnet parameters, and a reward function focused on transmission efficiency. Employing the Deep Deterministic Policy Gradient (DDPG)
algorithm, we demonstrate RLABC's efficacy on two beamlines, achieving transmission rates of 94% and 91%, comparable to expert manual optimizations. This approach bridges accelerator physics and machine learning, offering a versatile tool for physicists and RL researchers alike to streamline beamline tuning.
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All authors Anwar Ibrahim, Alexey Petrenko, Maxim Kaledin, Ehab Suleiman, Fedor Ratnikov, Denis Derkach
Physics and Society
Diversity legitimizes science: Holding basic research in the physical sciences accountable to the public
Kay T. Xia, Thayer L. Anderson and Phelan Yu
The American scientific community is reeling from funding cuts and policy directives that will debilitate scientific research and education. The underlying hostilities fueling these attacks have intensified in recent years as the COVID-19 pandemic increased suspicion of scientific experts and the institutional embrace of diversity, equity, and inclusion (DEI) policies in 2020 prompted a backlash along longstanding political fault lines. Under the banner of anti-elitism, opponents of science and DEI have formed a coalition that sees attacks on higher education as a strategic means to achieve their political ends. While some of their arguments contain legitimate criticisms, academics must resist these attacks that seek to dismantle higher education altogether. Instead, we should engage the public in our research process, build a scientific practice representative of and accountable to the communities we serve, and interrogate the aims of our work by critically studying the history of science.
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Physics and Society
Prejudice driven spite: A discontinuous phase transition in ultimatum game
Arunava Patra, C. F. Sagar Zephania and Sagar Chakraborty
In a mix of prejudiced and unprejudiced individuals engaged in strategic interactions, the individual intensity of prejudice is expected to have effect on overall level of societal prejudice. High level of prejudice should lead to discrimination that may manifest as unfairness and, perhaps, even spite. In this paper, we investigate this idea in the classical paradigm of the ultimatum game which we theoretically modify to introduce prejudice at the level of players, terming its intensity as prejudicity. The
stochastic evolutionary game dynamics, in the regime of replication-selection, reveals the emergence of spiteful behaviour as a dominant behaviour via a first order phase transition – a discontinuous jump in the frequency of spiteful individuals at a threshold value of prejudicity. The phase transition is quite robust and becomes progressively conspicuous in the limit of large population size where deterministic evolutionary game dynamics, viz., replicator dynamics, approximates the system closely. The emergence of spite driven by prejudice is also found to persist when one considers long-term evolutionary dynamics in the mutation-selection dominated regime.
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Fluid Dynamics · Cross-listed from cs.LG
Shock-Aware Physics-Guided Fusion-DeepONet Operator for Rarefied Micro-Nozzle Flows
Ehsan Roohi and Amirmehran Mahdavi
We present a comprehensive, physics aware deep learning framework for constructing fast and accurate surrogate models of rarefied, shock containing micro nozzle flows. The framework integrates three key components, a Fusion DeepONet operator learning architecture for capturing parameter dependencies, a physics-guided feature space that embeds a shock-aligned coordinate system, and a two-phase curriculum strategy emphasizing high-gradient regions. To demonstrate the generality and inductive bias of the proposed framework, we first validate it on the canonical viscous Burgers equation, which exhibits advective steepening and shock like gradients.
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Medical Physics · Cross-listed from cs.CV
Universal and Transferable Attacks on Pathology Foundation Models
Yuntian Wang, Xilin Yang, Che-Yung Shen et al. (+2 more)
We introduce Universal and Transferable
Adversarial Perturbations (UTAP) for pathology foundation models that reveal critical vulnerabilities in their capabilities. Optimized using deep learning, UTAP comprises a fixed and weak noise pattern that, when added to a pathology image, systematically disrupts the feature representation capabilities of multiple pathology foundation models. Therefore, UTAP induces performance drops in downstream tasks that utilize foundation models, including misclassification across a wide range of unseen data distributions. In addition to compromising the model performance, we demonstrate two key features of UTAP: (1) universality: its perturbation can be applied across diverse field-of-views independent of the
dataset that UTAP was developed on, and (2) transferability: its perturbation can successfully degrade the performance of various external, black-box pathology foundation models - never seen before. These two features indicate that UTAP is not a dedicated attack associated with a specific foundation model or image
dataset, but rather constitutes a broad threat to various emerging pathology foundation models and their applications. We systematically evaluated UTAP across various state-of-the-art pathology foundation models on multiple
datasets, causing a significant drop in their performance with visually imperceptible modifications to the input images using a fixed noise pattern. The development of these potent attacks establishes a critical, high-standard
benchmark for model robustness evaluation, highlighting a need for advancing defense mechanisms and potentially providing the necessary assets for
adversarial training to ensure the safe and reliable deployment of AI in pathology.
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All authors Yuntian Wang, Xilin Yang, Che-Yung Shen, Nir Pillar, Aydogan Ozcan
Optics
Strong-field Driven Sub-cycle Band Structure Modulation and Dephasing Control
Francis Walz, Shashank Kumar, Amirali Sharifi Olounabadi et al. (+6 more)
Over the past decade, ultrafast electron dynamics in the solid state have been extensively studied using various strong light-matter interaction techniques, such as high-harmonic generation. These studies lead to multiple interpretations of light-matter interaction in the strong-field regime, with exact mechanisms not yet fully understood. It is well known that strong-field interaction with a crystalline solid leads to significant modification of its band structure and, hence, its optical properties on ultrafast timescales. In this work, we present measurements of ultrafast electric-field observables in magnesium
oxide using a non-resonant nonlinear optical interaction. Using field observables, we show that strong
laser fields modulate the band structure on sub-cycle timescales, thereby altering the material's nonlinear optical response. We perform time-dependent perturbation theory calculations using a field-dependent dispersion relation and non-perturbative
semiconductor Bloch equation calculations, both of which agree with experimental observations. Furthermore, we directly extract dephasing times from the real-time signal electric field envelope and show sub-cycle control of dephasing times. Our work offers a new perspective on strong-field-driven electron dynamics in solids through electric-field observables. The demonstrated attosecond modulation of the nonlinear response could have important implications for
quantum light generation and
quantum spectroscopy using nonlinear optical processes.
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All authors Francis Walz, Shashank Kumar, Amirali Sharifi Olounabadi, Yuyan Zhong, Russell Zimmerman, Siddhant Pandey, Eric Liu, Liang Z. Tan, Niranjan Shivaram
Physics and Society
FlexBSS: A flexible multi-objective framework for bike-sharing station optimization
Jordi Grau-Escolano, David Duran-Rodas and Julian Vicens
Bike-sharing systems (BSS) are key components of urban mobility, promoting active travel and complementing public transport. This paper presents a flexible, data-driven framework for optimizing BSS station placement. Existing methods usually focus on a single planning objective, such as maximizing demand, or on a fixed set of two or three objectives, such as combining demand and social equity. This restricts their adaptability to evolving priorities and diverse contexts. Moreover, they often aggregate candidate sites into coarse spatial units and neglect features such as topography or directed cycling networks. The framework addresses these limitations through four components: (i) a multi-criteria decision-making model that evaluates candidate sites using configurable spatial factors and adjustable weights, thereby enabling planners to represent any combination of planning objectives rather than being limited to a fixed set; (ii) network-level metrics that explicitly balance station proximity and system-wide accessibility on directed bicycle networks; (iii) slope-adjusted distances that account for uphill effort and downhill facilitation; and (iv) a genetic
algorithm that generates feasible station sets while respecting minimum-distance constraints. A case study in Barcelona demonstrates its application using open data for scenarios focused on demand,
multimodal integration, and social equity. Results show that network-level metrics reshape the spatial arrangement of stations while keeping the same planning objectives, slope-adjusted distances improve station availability in hilly districts, and an expansion scenario in lEixample district produces coherent layouts complementing existing stations. By integrating spatial factors and network representation, the framework provides a versatile decision-support tool for BSS planning in complex urban environments.
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Computational Physics · Cross-listed from cond-mat.mtrl-sci
Unified Learning of Interatomic Potentials and Electronic Hamiltonians, with Applications in 2D Materials
Moon-ki Choi, Daniel Palmer, Shivam Sharma et al. (+1 more)
We introduce UnIPH, an equivariant graph neural network designed to jointly predict both interatomic potentials and tight-binding (TB)
Hamiltonians for an atomic structure. UnIPH is trained using density functional theory (DFT) calculations followed by Wannier projection to predict energies and forces as node-level targets and Wannier-projected TB
Hamiltonians as edge-level targets. This enables physically consistent modeling of coupled mechanical-electronic responses with near-DFT-level accuracy. After separately training two UnIPH models on DFT data for
bilayer graphene and monolayer MoS2, respectively, we find that these models capture key deformation-electronic effects: in twisted
bilayer graphene, the trained UnIPH reveals how interlayer spacing, in-plane strain, and out-of-plane corrugation drive isolated flat-band formation, and further shows that modulating substrate interaction strength can generate flat bands even away from the magic angle (approximately 1.1 degrees). For monolayer MoS2, UnIPH accurately reproduces
phonon dispersions and strain-dependent band-gap
evolution, and further predicts how a non-uniform substrate creates localized strain pockets that spatially modulate the conduction- and valence-band edges.
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All authors Moon-ki Choi, Daniel Palmer, Shivam Sharma, Harley T. Johnson
Instrumentation and Detectors · Cross-listed from astro-ph.IM
Readout of Microwave Kinetic Inductance Detector (MKID) Arrays for Habitable Worlds Observatory Using a Polyphase Filterbank Algorithm
Oketa Basha, Tracee Lynn Jamison-Hooks, Philip Mauskopf et al. (+12 more)
The Habitable Worlds Observatory (HWO), a nextgeneration ultraviolet/optical/infrared space
telescope, will require detector technologies capable of supporting substantially larger pixel-count arrays than those flown on previous missions. Microwave Kinetic Inductance Detectors (MKIDs) provide a scalable solution through microwave multiplexing and have already been demonstrated in balloon-borne instruments using Field-Programmable Gate Arrays (FPGAs) for real-time signal processing. A central element of MKID readout is the Polyphase Filter Bank (PFB) spectrometer, which converts digitized timedomain signals into finely resolved frequency channels for subsequent analysis. To meet the demands for broader bandwidths and higher spectral resolution driven by emerging science goals, efficient FPGA-based implementations of the PFB are essential. This work presents current results from a fixed-point digital design methodology for deploying the PFB architecture on spacequalified FPGAs. The approach emphasizes efficient resource utilization and numerical precision while satisfying stringent performance constraints, enabling scalable, high-resolution spectral processing for future space observatories and remote sensing applications.
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All authors Oketa Basha, Tracee Lynn Jamison-Hooks, Philip Mauskopf, Lynn Miles, Sanetra Newman-Bailey, Abarna Karthikeyan, Mohammad Samad, Mariya Taylor, Sarah E. Kay, Sean Bryan, Devika Band, Thomas Essinger-Hileman, Sumit Dahal, Adrian Sinclair, Caleb Distel
Fluid Dynamics · Cross-listed from cond-mat.soft
Reciprocal swimming in viscoelastic granular hydrogels
Hongyi Xiao, Jing Wang, Achim Sack et al. (+2 more)
We experimentally study a scallop-like swimmer with reciprocally flapping wings in a nearly frictionless, cohesive granular medium consisting of hydrogel spheres. Significant locomotion is found when the swimmer's flapping frequency matches the inverse relaxation time of the material. Remarkably, the swimmer moves in the opposite direction compared to its motion in a cohesion-free granular material of hard plastic spheres. At higher or lower frequencies, we observe no motion of the swimmer, apart from a short initial transient phase. X-ray radiograms reveal that the wing motions create low-density zones, which in turn give rise to a hysteresis in drag and propulsion forces. This time-dependent effect, combined with the swimmer's inertia, accounts for locomotion at intermediate frequencies.
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All authors Hongyi Xiao, Jing Wang, Achim Sack, Ralf Stannarius, Thorsten Pöschel
Optics · Cross-listed from cond-mat.mes-hall
High harmonic generation light source with polarization selectivity and sub-100-$\mu$m beam size for time- and angle-resolved photoemission spectroscopy
Haoyuan Zhong, Xuanxi Cai, Changhua Bao et al. (+9 more)
High-quality ultrafast light sources are critical for developing advanced time- and angle-resolved photoemission spectroscopy (TrARPES). While the application of high harmonic generation (HHG) light sources in TrARPES has increased significantly over the past decade, the optimization of the HHG probe beam size and selective control of the light polarization, which are important for TrARPES measurements, have been rarely explored. In this work, we report the implementation of high-quality HHG probe source with an optimum beam size down to 57 $\mu$m $\times$ 90 $\mu$m and selective light polarization control, together with mid-infrared (MIR) pumping source for TrARPES measurements using a 10 kHz amplifier
laser. The selective polarization control of the HHG probe source allows to enhance bands with different orbital contributions or
symmetries, as demonstrated by experimental data measured on a few representative transition metal dichalcogenide materials (TMDCs) as well as topological
insulator Bi$_2$Se$_3$. Furthermore, by combining the HHG probe source with MIR pumping at 2 $\mu$m wavelength, TrARPES on a
bilayer graphene shows a time resolution of 140 fs, allowing to distinguish two different relaxation processes in
graphene. Such high-quality HHG probe source together with the MIR pumping expands the capability of TrARPES in revealing the ultrafast dynamics and light-induced emerging phenomena in
quantum materials.
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All authors Haoyuan Zhong, Xuanxi Cai, Changhua Bao, Fei Wang, Tianyun Lin, Yudong Chen, Sainan Peng, Lin Tang, Chen Gu, Zhensheng Tao, Hongyun Zhang, Shuyun Zhou
Computational Physics
Extended phase-space symplectic integration for electron dynamics
Francois Mauger and Cristel Chandre
We investigate the use of extended phase-space
symplectic integration for simulating two different classes of electron dynamics. The first one, with one and a half degrees of freedom, comes from
plasma physics and describes the classical dynamics of a charged particle in a strong, constant, and uniform
magnetic field perturbed by a turbulent electrostatic potential. The second one, with an infinite number of degrees of freedom, comes from physical chemistry and corresponds to Kohn-Sham time-dependent density-functional theory. For both we lay out the extension procedure and stability condition for numerical integration of the dynamics using high-order
symplectic split-operator schemes. We also identify a computationally inexpensive metric that can be used for on-the-fly estimation of the accuracy of simulations. Our work paves the way for broad application of
symplectic split-operator integration of classical and
quantum Hamiltonian systems with finite and infinite number of degrees of freedom by comparing different modes of implementation of extended phase space integration.
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Applied Physics · Cross-listed from cond-mat.supr-con
Marginal Influence of Anomalous Josephson Current on Odd-Frequency Spin-Triplet Pairing in Ferromagnetic Josephson Diodes
Subhajit Pal and Colin Benjamin
We examine how an anomalous Josephson current influences odd-frequency superconducting correlations in two Josephson junction geometries. The first consists of two
ferromagnetic layers between conventional $s$-wave
superconductors, with magnetizations along the $x$- and $y$-axes, forming a
bilayer junction. The second contains three
ferromagnetic layers between two $s$-wave
superconductors, with magnetizations along the $x$-, $y$-, and $z$-axes, forming a trilayer junction. Both systems are analyzed in the short and long junction limits. In the
bilayer case, where no anomalous Josephson current is present, odd-frequency equal-
spin triplet correlations develop pronounced peaks at finite magnetizations in the short junction limit for both tunneling and transparent interfaces. The odd-frequency mixed-
spin triplet correlations also exhibit peaks at finite magnetizations for tunneling interfaces, whereas for transparent interfaces they display both peaks and zeros. In the trilayer case, where an anomalous Josephson current exists, similar peaks in both equal- and mixed-
spin odd-frequency triplet correlations occur at finite magnetizations for tunneling and transparent interfaces. The spatial profiles of these correlations remain largely unaffected by the anomalous current. The Josephson diode efficiency is finite and reaches its maximum at magnetizations corresponding to the peaks of the anomalous current. Overall, our results show that the anomalous Josephson current has only a marginal influence on odd-frequency
spin-triplet pairing. This indicates that the emergence of odd-frequency correlations and the Josephson diode effect are largely independent phenomena, contrary to earlier
conjectures. Analysis of the long junction limit leads to the same qualitative conclusions for both configurations.
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Atomic Physics · Cross-listed from quant-ph
Triphoton generation near atomic resonance via SSWM: Harmonic expansion for accurate optical response
Jianming Wen
Quantum correlations of time-frequency-entangled
photon pairs generated via parametric processes are critically influenced by both the linear and nonlinear optical responses of the medium. This sensitivity is especially significant in schemes utilizing atomic ensembles with well-defined energy level structures near resonance. However, conventional theoretical approaches often fall short in accurately calculating the optical responses–particularly when a single atomic transition is simultaneously driven by multiple light fields with (significantly) different intensities. To address this limitation, we generalize the harmonic expansion method originally introduced by Wen for biphoton generation near atomic resonance. As a case study, we apply this generalized approach to the reliable direct generation of time-energy-entangled W-state triphotons via spontaneous six-wave mixing in a five-level asymmetric-M atomic system. Our results demonstrate the method's superior accuracy and self-consistency, offering clear advantages over traditional calculation techniques.
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Optics
On-chip processing of optical orbital angular momentum
Charles Chen
Orbital angular momentum is an important concept in optics, thus numerous researches explore the principles and applications of light beams with orbital angular momentum. This type of light beam is also called
vortex beam, whose inherent infinite-dimensional feature has broad prospect in many fields like optical communications and optical computing. However, there are still a lot of problems in the propagation and processing of on-chip
vortex beams. Here, with inverse design method, we design four cross-shaped waveguide structures which can support
vortex beams with topological charge l = 1, 2, 3, 4 respectively. The four
vortex modes are momentum matched so the coupling between every two waveguides can happen, achieving the conversion of orbital angular momentum. The longest width of each waveguide is about 2 um, so the cross-shaped waveguides are able to be integrated on a photonic chip. All the cross-shaped waveguides are silicon-on-
insulator waveguide, and such silicon-based platform has the advantage of being compatible with complementary metal
oxide semiconductor technology. Moreover, in order to demonstrate the application prospect, we construct an XOR logic gate with the conversion of orbital angular momentum. Therefore, our work provides a new idea for the manipulation of orbital angular momentum, expands the applications of on-chip
vortex beams, and shows great potential.
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Optics
Design of a Dual Polarized Gold-Coated Four-Channel PCF-SPR Sensor with Ultra-High Sensitivity and Broad RI Coverage
Osama Haramine Sinan, Ifaz Ahmed Adan, Mohammad Tawsif et al. (+1 more)
Surface plasmon resonance (SPR) sensors built on photonic
crystal fibers (PCFs) have recently become a promising category of optical sensing platforms. This is primarily due to their high sensitivity, compact structural design and ability to work with a wide variety of analytes. The overall sensing performance can significantly be enhanced by carefully tailoring the fiber geometry to strengthen the coupling between the guided core mode and the plasmon mode. This study designs and thoroughly investigates a polarization-dependent SPR-based PCF sensor that delivers strong mode coupling, wide detection range and high refractive-index (RI) sensitivity using finite element method (FEM). In the proposed configuration, air holes with different diameters and a rectangular core slot are used to create birefringence along with four outer microchannels coated with a 30 nm gold film create distinct plasmonic regions that support multiple resonances. The simulated results yield maximum wavelength sensitivities of 77500 $nmRIU^-{1}$ and 92500 $nmRIU^-{1}$, along with amplitude sensitivities of 3930 $RIU^-{1}$ and 3139 $RIU^-{1}$ and figures of merit of 517 $RIU^-{1}$ and 356 $RIU^-{1}$ for the x- and y-polarizations respectively, over an analyte RI range of 1.32-1.42. The parametric study verifies that the design is highly tolerant to fabrication deviations and the coupling behavior is primarily sensitive to the smallest air holes and the height of the core slot. Since the sensing region is external, analytes can be reused conveniently. Consequently, the proposed sensor provides a compact, highly sensitive and practically realizable platform for biochemical and chemical sensing applications.
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All authors Osama Haramine Sinan, Ifaz Ahmed Adan, Mohammad Tawsif, Aditta Chowdhury
Fluid Dynamics · Cross-listed from math.NA
Improving performance estimation of a PCM-integrated solar chimney through reduced-order based data assimilation
Diego R. Rivera, Ernesto Castillo, Felipe Galarce et al. (+1 more)
This study evaluates a data assimilation framework based on reduced-order modeling (ROM-DA), complemented by a hybrid data-filling strategy, to reconstruct dynamic temperature fields in a phase-change-material (PCM) integrated
solar chimney from limited temperature measurements. The goal is to enhance the estimation accuracy of the outlet airflow velocity. A regularized least-squares formulation is employed to estimate temperature distributions within an inclined
solar chimney using RT-42 as the PCM. The methodology combines (i) a reduced-order model derived from high-fidelity finite-volume simulations of unsteady conjugate heat transfer with
liquid-solid phase change and surface radiation, and (ii) three experimental
datasets with 22, 135, and 203 measurement points. Missing data are reconstructed using a hybrid filling scheme based on boundary-layer and bicubic interpolations. The assimilated temperature fields are integrated into the thermally coupled forward solver to improve velocity predictions. Results show that the ROM-DA framework reconstructs the transient temperature fields in both the air and PCM domains with relative errors below 10 percent for sparse data and below 3 percent for expanded
datasets. When applied to experimental measurements, the approach enhances the fidelity of temperature and velocity fields compared with the baseline model, reducing the outlet velocity RMS error by 20 percent. This represents the first application of a ROM-DA framework to a coupled multiphysics
solar chimney with PCM integration, demonstrating its potential for near-real-time thermal state estimation and digital-twin development.
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All authors Diego R. Rivera, Ernesto Castillo, Felipe Galarce, Douglas R.Q. Pacheco
General Physics
Polaron versus Anderson Localization
Riccardo Fantoni
We compare two kinds of affine localizations in physics: the localization in a short range polaron and the one in a Wick rotated Anderson
stochastic model. The conditions on the interaction potential necessary to see the transnational
symmetry breaking localization phase transition is identical in the two problems. We therefore suggest that they should belong to the same universality class of the renormalization group for the localization phase transition.
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Physics and Society
Mastering Uncertainty: From Understanding to Prediction
Didier Sornette
Uncertainty defines our age: it shapes
climate, finance, technology, and society, yet remains profoundly misunderstood. We oscillate between the illusion of control and the paralysis of fatalism. This paper reframes uncertainty not as randomness but as ignorance: a product of poor models, institutional blindness, and cognitive bias. Drawing on insights from physics, complex systems, and decades of empirical research, I show that much of what appears unpredictable reveals structure near transitions, where feedbacks, critical thresholds, and early-warning signals emerge. Across domains from financial crises to industrial disasters, uncertainty is amplified less by nature than by human behavior and organizational failure. To master it, prediction must shift from prophecy to diagnosis, identifying precursors of instability rather than
forecasting exact outcomes. I propose a framework of dynamic foresight grounded in adaptive leadership, transparent communication, and systemic learning. Mastering uncertainty thus means transforming fear into foresight and building institutions that navigate, rather than deny, the complexity of change.
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Optics
Recover Biological Structure from Sparse-View Diffraction Images with Neural Volumetric Prior
Renzhi He, Haowen Zhou, Yubei Chen et al. (+1 more)
Volumetric reconstruction of label-free living
cells from non-destructive optical microscopic images reveals cellular metabolism in native environments. However, current optical
tomography techniques require hundreds of 2D images to reconstruct a 3D volume, hindering them from intravital imaging of biological samples undergoing rapid dynamics. This poses the challenge of reconstructing the entire volume of semi-transparent biological samples from sparse views due to the restricted viewing angles of microscopes and the limited number of measurements. In this work, we develop Neural Volumetric Prior (NVP) for high-fidelity volumetric reconstruction of semi-transparent biological samples from sparse-view microscopic images. NVP integrates explicit and implicit neural representations and incorporates the physical prior of diffractive optics. We validate NVP on both simulated data and experimentally captured microscopic images. Compared to previous methods, NVP significantly reduces the required number of images by nearly 50-fold and processing time by 3-fold while maintaining state-of-the-art performance. NVP is the first technique to enable volumetric reconstruction of label-free biological samples from sparse-view microscopic images, paving the way for real-time 3D imaging of dynamically changing biological samples. \href{https://xue-lab-cobi.github.io/Sparse-View-FDT/}{Project Page}
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All authors Renzhi He, Haowen Zhou, Yubei Chen, Yi Xue
General Physics
Temperature of the Vacuum
Riccardo Fantoni
In a recent trilogy we proposed a Statistical Theory of General Relativity spacetime. Here we apply our new theory to determine the (energy) “density” and (virial) “temperature” dependence of the structure of the spacetime
quantum vacuum working on the simple case of a real massless scalar field in a local Lorentz frame.
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Optics
Longwave-transparent low-emissivity material
Yue Zhang, Longnan Li, Junyan Dai et al. (+16 more)
Low emissivity (low-e) materials are crucial for conserving thermal energy in buildings, cold chain logistics and transportation by minimizing unwanted radiative heat loss or gain. However, their metallic nature intrinsically causes severe longwave attenuation, hindering their broad applications. Here, we introduce, for the first time, an all-dielectric longwave-transparent low-emissivity material (LLM) with ultra-broadband, high transmittance spanning 9 orders of magnitude, from terahertz to kilohertz frequencies. This meter-scale LLM not only achieves energy savings of up to 41.1% over commercial white paint and 10.2% over traditional low-e materials, but also unlocks various fundamentally new capabilities including high-speed wireless communication in energy-efficient buildings, wireless energy transfer with radiative thermal insulation, as well as non-invasive terahertz security screening and
radio frequency identification in cold chain logistics. Our approach represents a new photonic solution towards carbon neutrality and smart city development, paving the way for a more sustainable and interconnected future.
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All authors Yue Zhang, Longnan Li, Junyan Dai, Xiaowen Zhang, Qunyan Zhou, Naiqin Yi, Ruizhe Jian, Fei Zhu, Xiaopeng Li, Mengke Sun, Jiazheng Wu, Xinfeng Li, Xiangtong Kong, Ziai Liu, Yinwei Li, Qiang Cheng, Yiming Zhu, Tie Jun Cui, Wei Li
Plasma Physics
Relativistic Magnetohydrodynamic Wave Excitation by Laser Pulse in a Magnetized Plasma
Zohreh Hashempour, Mehdi Nasri Nasrabadi, Nora Nassiri-Mofakham et al. (+1 more)
In the study of
plasma, particularly in applications involving strong
laser-
plasma interactions, the propagation of a strong electromagnetic wave induces relativistic velocities in the electron flow. Given such conditions, the wave propagating through the
plasma experiences modulational instability. In this paper, we investigate this instability using magnetohydrodynamic (MHD) equations. In the relativistic limit, the motion of ions can be neglected due to their significant inertia, allowing us to treat the ions as a background fluid. This simplification enables us to apply perturbation techniques to the electron fluid equations, leading to the derivation of the nonlinear wave equation in the form of the Nonlinear Schrödinger Equation (NLSE). We also explore the relationship between wave dispersion and the conditions for instability. We derive the maximum growth rate of the modulational instability and analyze its dependence on
plasma parameters and wave intensity in the context of relativistic magnetized
plasma, providing quantitative insights into the instability dynamics. Finally, we examine aspects of the perturbed NLSE using the Bogoliubov-Mitropolsky perturbation approach, treating real and imaginary coefficients separately, which explicitly incorporates both Nonlinear Landau Damping (NLLD) and growth-damping effects.
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All authors Zohreh Hashempour, Mehdi Nasri Nasrabadi, Nora Nassiri-Mofakham, Hamidreza Daniali
Plasma Physics
Hamiltonian estimation of island width threshold for stochasticity onset on edge pedestal top in presence of a resonant magnetic perturbation
Zhifei Gui, Ping Zhu and Dominique Franck Escande
This study applies the
Hamiltonian method to analyze the nonlinear
magnetic topology induced by Resonant
Magnetic Perturbations (RMPs) in tokamaks. We investigate the system's chaotic behavior by comparing three methods: the renormalization method, Lyapunov exponents (LE), and weighted Birkhoff average (WBA). A strong consistency is found among these methods in predicting the large scale stochasticity threshold. The
magnetic island width threshold provides a quantitative criterion for optimizing RMP-based ELM control, bridging a critical gap in
plasma control strategies.
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Optics · Cross-listed from quant-ph
Scattering theory of frequency-entangled biphoton states facilitated by cavity polaritons
Andrei Piryatinski, Nishaant Jacobus, Sameer Dambal et al. (+3 more)
The use of
quantum light to probe
exciton properties in
semiconductor and molecular nanostructures typically occurs in the low-intensity regime. A substantial enhancement of
exciton-
photon coupling can be achieved with photonic cavities, where
excitons hybridize with cavity modes to form polariton states. To provide a theoretical framework for interpreting emerging experimental efforts in this direction, we develop a scattering theory describing the interaction of frequency-entangled
photon pairs with cavity polariton and bipolariton states under various coupling regimes. Employing the Tavis-Cummings model in combination with our scattering approach, we present a quantitative analysis of how the interaction of the entangled
photon pair with the polariton/bipolariton modifies its joint spectral amplitude (JSA). Specifically, we examine the effects of the cavity-mode steady-state population,
exciton-cavity coupling strength, and different forms of the input
photon JSA. Our results show that the
entanglement entropy of the scattered
photons is highly sensitive to the interplay between the input JSA and the spectral line shapes of the polariton resonances, emphasizing the cavity filtering effects. We suggest that biphoton scattering
quantum light spectroscopy best serves as a sensitive probe of polariton and bipolariton states in the
photon-
vacuum cavity state. Our approach is not only robust to various regimes of cavity-
exciton coupling, but also amenable to extensions beyond the Tavis-Cummings model, enabling the representation of a broad class of molecular systems and solid state
quantum materials.
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All authors Andrei Piryatinski, Nishaant Jacobus, Sameer Dambal, Eric R. Bittner, Yu Zhang, Ajay Ram Srimath Kandada
Computational Physics
Zekeriya Ender Eğer, Waris Khan, Priyabrata Maharana et al. (+5 more)
This article investigates the identification of
magnetic spin distributions in
ferromagnetic materials by minimizing the system's free energy.
Magnetic lattices of varying sizes are constructed, and the free energy is computed using an Ising model that accounts for
spin-to-
spin neighbor interactions and the influence of an external
magnetic field. The problem reduces to determining the state of each
spin, either up or down, leading to an optimization problem with $2^{n \times n}$ design variables for an $n \times n$
lattice. To address the high-dimensional and computationally intractable nature of this problem, particularly for large domains, we employ a
quantum optimization
algorithm, BQP. The BQP results are first validated against solutions obtained using a genetic
algorithm for smaller
lattices. Finally, the approach is extended to large-scale systems, including $50 \times 50$
lattices, where conventional methods become impractical.
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All authors Zekeriya Ender Eğer, Waris Khan, Priyabrata Maharana, Kandula Eswara Sai Kumar, Udbhav Sharma, Abhishek Chopra, Rut Lineswala, P{\i}nar Acar
Computational Physics · Cross-listed from cond-mat.mtrl-sci
Electron Localization in Non-Compact Covalent Bonds Captured by the r2SCAN+V Approach
Yubo Zhang, Da Ke, Rohan Maniar et al. (+4 more)
In density functional theory, the SCAN (Strongly Constrained and Appropriately Normed) and r2SCAN functionals significantly improve over generalized gradient approximation functionals such as PBE (Perdew-Burke-Ernzerhof) in predicting electronic,
magnetic, and structural properties across various materials, including transition-metal compounds. However, there remain puzzling cases where SCAN and r2SCAN underperform, such as in calculating the band structure of
graphene, the
magnetic moment of Fe, the potential energy curve of the Cr2 molecule, and the bond length of VO2. This research identifies a common characteristic among these challenging materials: non-compact covalent bonding through s-s, p-p, or d-d electron hybridization. While SCAN and r2SCAN excel at capturing electron localization at local atomic sites, they struggle to accurately describe electron localization in non-compact covalent bonds, resulting in a biased improvement. To address this issue, we propose the r2SCAN+V approach as a practical modification that improves accuracy across all the tested materials. The parameter V is 4 eV for metallic Fe, but substantially lower for the other cases. Our findings provide valuable insights for the future development of advanced functionals.
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All authors Yubo Zhang, Da Ke, Rohan Maniar, Timo Lebeda, Peihong Zhang, Jianwei Sun, John P. Perdew
Atomic Physics · Cross-listed from cond-mat.mtrl-sci
Infrared Absorption and Laser Spectroscopy of Ho$^{3+}$ Doped K$_2$YF$_5$ Microparticles
Pakwan Chanprakhon, Michael F. Reid and Jon-Paul R. Wells
High-resolution absorption and
laser spectroscopy are used to determine electronic energy levels for Ho$^{3+}$ ions in K$_2$YF$_5$ microparticles. A total of 72
crystal-field energy levels, distributed among 8 multiplets, are assigned. This optical data is used for
crystal-field modelling of the electronic structure of Ho$^{3+}$ in K$_2$YF$_5$. Partially-resolved hyperfine splittings are accurately reproduced by the model. The temperature dependence of the fluorescent lifetime of the $^5$F$_5$ multiplet is measured and the temperature dependence of the non-radiative relaxation is modelled by a five-
phonon process. Preliminary measurements of infra-red to visible upconversion in microparticles co-doped with Ho$^{3+}$ and Yb$^{3+}$ is reported.
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