Chemical Physics · Cross-listed from cond-mat.mtrl-sci
Tritium accumulation and ozone decontamination of tungsten and beryllium
Dominic Batzler, Robin Größle, Philipp Haag et al. (+5 more)
Tritium adsorption on surfaces creates a variety of issues, ranging from the fields of fusion applications to small and large-scale laboratory experiments using tritium. The extent to which tritium accumulates on surfaces is generally material-dependent and must be determined through experiments. Additionally, this surface contamination necessitates the implementation of appropriate decontamination procedures, preferably in-situ. A suitable method could be exposure to ozone during UV irradiation. However, it is currently not known if both components are necessary for the decontamination. At Tritium Laboratory Karlsruhe, both questions on contamination and decontamination can be addressed using a single experimental setup. With this, it is possible to expose solid samples to gaseous tritium to measure the temporal activity
evolution. Furthermore, the system can be filled with dry air, and dry air containing ozone to explore their decontamination effect. Both measurement modes were applied to beryllium and tungsten samples, which were chosen for their relevance in fusion. The beryllium surface was observed to accumulate tritium more than four times faster than tungsten when exposed to gaseous tritium. Concerning the decontamination, without simultaneous UV irradiation, exposure to ozone did not have any distinct effect on the surface activity compared to simply using dry air. This leads to the conclusion that UV illumination of the surfaces is required to achieve a significant decontamination factor.
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All authors Dominic Batzler, Robin Größle, Philipp Haag, Elizabeth Paine, Marco Röllig, Marie-Christine Schäfer, Marius Schaufelberger, Kerstin Trost
Instrumentation and Detectors
GPT-like transformer model for silicon tracking detector simulation
Tadej Novak and Borut Paul Kerševan
Simulating physics processes and detector responses is essential in high energy physics and represents significant computing costs. Generative machine learning has been demonstrated to be potentially powerful in accelerating simulations, outperforming traditional fast simulation methods. The efforts have focused primarily on calorimeters. This work presents the very first studies on using neural networks for silicon tracking detectors simulation. The GPT-like
transformer architecture is determined to be optimal for this task and applied in a fully generative way, ensuring full correlations between individual hits. Taking parallels from text generation, hits are represented as a flat sequence of feature values. The resulting tracking performance, evaluated on the Open Data Detector, is comparable with the full simulation.
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Instrumentation and Detectors
Performance of an LYSO-Based Active Converter for a Conversion Spectrometer aiming for 52.8 MeV photon detection in Future $\mu^+ \to e^+ \gamma$ Search Experiments
Sei Ban, Lukas Gerritzen, Fumihito Ikeda et al. (+5 more)
To facilitate future $\mu^+ \to e^+ \gamma$ search experiments with a branching-ratio sensitivity of $10^{-15}$, we are developing a conversion spectrometer that incorporates an active LYSO converter. The converter generates $e^+e^-$ pairs from incident
photons while simultaneously measuring their energy deposition and timing, thereby enabling precise reconstruction of 52.8 MeV
photons. The design goals include a time resolution of 30 ps and an energy resolution of 200 keV for the detection of 52.8 MeV
photons. Based on simulation studies, we optimized the converter thickness and segment dimensions, followed by the fabrication of prototype LYSO segments. The single-MIP detection performance of these prototypes was evaluated using an electron beam at the KEK PF-AR test beamline. The prototypes demonstrated excellent performance, achieving a time resolution of 25 ps and a light yield of $10^4$ photoelectrons, both of which significantly exceed the design requirements.
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All authors Sei Ban, Lukas Gerritzen, Fumihito Ikeda, Toshiyuki Iwamoto, Wataru Ootani, Atsushi Oya, Rei Sakakibara, Rintaro Yokota
Applied Physics · Cross-listed from cond-mat.mtrl-sci
Extending the Growth Temperature-N Concentration Regime Through Pd Doping in Fe4N Thin Films
Rohit Kumar Meena, Akhil Tayal, Andrei Gloskovskii et al. (+1 more)
Fe4N is a well-known anti-perovskite compound exhibiting high magnetization, high chemical stability, low coercivity, high Curie temperature, and high
spin-polarization ratio. Therefore, it is a viable candidate for applications in spintronic and
magnetic storage devices. However, the Fe4N phase is formed in a narrow substrate temperature (Ts)-N concentration (Nc) regime in the phase diagram of Fe-N. It has been observed that a slight N deficiency will lead to
impurity of alpha-Fe, and some N efficiency would result in epsilon-Fe3N phase. Through this work, it has been demonstrated that the doping of Pd can be suitably utilized to extend the Ts-Nc regime for the growth of Fe4N thin films. EXAFS analysis indicate that Pd atoms are substituting corner Fe atoms. Magnetization measurements reveal that the saturation magnetization reduces nominally with Pd doping up to 13 at.%. Therefore, it is foreseen that Pd doping is effective in extending the Fe4N phase formation regime without a significant impact on its structural, electronic, and
magnetic properties.
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All authors Rohit Kumar Meena, Akhil Tayal, Andrei Gloskovskii, Mukul Gupta
Atmospheric and Oceanic Physics
Mesoscale soil moisture heterogeneity can locally amplify humid heat
Guillaume Chagnaud, Chris M Taylor, Lawrence S Jackson et al. (+4 more)
Soil moisture is a key ingredient of humid heat through supplying moisture and modifying boundary layer properties. Soil moisture heterogeneity due to e.g., antecedent rainfall, can strongly influence weather patterns; yet, its effect on humid heat is poorly understood. Idealized numerical simulations are performed with a cloud-resolving ($\Delta x$=500 m), coupled land-atmosphere model wherein wet patches on length-scales $\lambda \in$ 25-150 km are prescribed. Compared to experiments with uniform soil moisture, humid heat is locally amplified by 1-4$^\circ$C, with maximum amplification for the critical soil moisture length-scale $\lambda_c=$ 50 km. Subsidence associated with a soil moisture-induced mesoscale circulation concentrates warm, humid air in a shallower boundary layer. The background wind and the magnitude of the wet-dry contrast control the relationship between $\lambda_c$ and the humid heat amplification. Based on observed soil moisture patterns, these results will help to predict extreme humid heat at city and county scales across the Tropics.
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All authors Guillaume Chagnaud, Chris M Taylor, Lawrence S Jackson, Anne Barber, Helen Burns, John H Marsham, Cathryn E Birch
History and Philosophy of Physics · Cross-listed from quant-ph
A short technical comment on Bub's There is No Quantum World (arXiv:2512.18400v2) and a brief remark on related Grangier's reply (arXiv:2512.22965v1)
Krzysztof Sienicki
This note is a friendly technical check of Jeffrey Bub's There is No
Quantum World (arXiv:2512.18400v2). I flag one unambiguous mathematical slip (a cardinality identity that implicitly assumes the Continuum Hypothesis) and then point out a few places where the discussion of infinite tensor products, “sectorization,” and measurement updates would benefit from sharper wording. Nothing here is meant as a critique of Bub's interpretive goals; the aim is simply to separate what is mathematically forced from what depends on choices of
algebra, representation, or philosophical stance. I end with a short remark on Philippe Grangier's reply (arXiv:2512.22965v1).
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Accelerator Physics · Cross-listed from cond-mat.mtrl-sci
Soft x-rays with Orbital Angular Momentum for resonant scattering experiments at the SOLEIL synchrotron
Pietro Carrara, Franck Fortuna, Renaud Delaunay et al. (+15 more)
The paper presents a comprehensive description of a new setup implemented and commissioned at the SEXTANTS beamline of the SOLEIL synchrotron for absorption and scattering experiments with x-ray beams carrying an orbital angular momentum, also known as twisted x-ray beams. Two alternative methods have been implemented, based on the use of either spiral zone plates or fork gratings devices, and we show how they can be used for both defining and assessing the orbital angular momentum of an x-ray beam. We show also how multiple devices can be used in sequence to define an integer arithmetic of the orbital angular momentum of the final x-ray beam. Finally, we report the results of the first resonant scattering pilot experiments in transmission and reflection mode, intended to assess the feasibility of future users measurements. The availability of twisted soft x-rays complements the range of experimental techniques in elastic, resonant and coherent scattering available at the SEXTANTS beamline of the SOLEIL synchrotron.
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All authors Pietro Carrara, Franck Fortuna, Renaud Delaunay, Joan Vila-Comamala, Benedikt Rösner, Christian David, Stefania Pizzini, Clément Fourniols, Laurent Vila, Matteo Pancaldi, Carlo Spezzani, Flavio Capotondi, Pierre Nonnon, Mauro Fanciulli, Thierry Ruchon, Nicolas Jaouen, Horia Popescu, Maurizio Sacchi
Fluid Dynamics
Transport and orientation of anisotropic particles settling in surface gravity waves
Himanshu Mishra and Anubhab Roy
We study the translation and orientation dynamics of an anisotropic particle settling in monochromatic linear surface
gravity waves. Recent work has shown that a neutrally buoyant spheroid attains a preferred mean orientation in such wave fields, independent of its initial state and determined solely by its aspect ratio. Comparing the settling parameter $\mathrm{Sv}$, the ratio of settling speed to wave speed, with the asymptotically small wave steepness $\epsilon$, we investigate the long time dynamics of a negatively buoyant particle. We examine the transition from aspect ratio-dependent
equilibrium orientation in the weak settling regime ($\mathrm{Sv} \ll \epsilon^2$) to initial-condition-dependent
alignment in the strong settling limit ($\mathrm{Sv} \gg 1$). Since translation and orientation are coupled for anisotropic particles, we use orientation dynamics to predict net horizontal transport. Fluid inertia induces an inertial torque that breaks the Stokesian degeneracy and drives broadside
alignment. We analyze the influence of this torque on drift and
alignment rate as functions of settling and wave parameters. Finally, we evaluate finite-size effects through the parameter $\sigma$, showing that a neutrally buoyant finite-size spheroid exhibits $\sigma$-dependent drift, validating the finite-size approximation when the spheroid size approaches the wavelength.
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Atomic Physics
High-flux cold lithium-6 and rubidium-87 atoms from compact two-dimensional magneto-optical traps
Yun-Xuan Lu, An-Wei Zhu, Christine E. Frank et al. (+2 more)
We report a compact setup with in-series two-dimensional magneto-optical traps (2D MOTs) that provides high-flux cold lithium and rubidium atoms. Thanks to the efficient short-distance Zeeman slowing, the maximum 3D MOT loading rate of lithium atoms reaches a record value of $6.6\times 10^{9}$ atoms/s at a moderate lithium-oven temperature of 372 degrees Celsius, which is 44 times higher than that without the Zeeman slowing light. The flux of rubidium is also as high as $2.3\times10^9$ atoms/s with the rubidium oven held at room temperature. Meanwhile, the entire
vacuum-chamber system, including an ultra-high-
vacuum science
cell, is within a small volume of $55\times65\times70~\mathrm{cm}^3$. Our work represents a substantial improvement over traditional bulky and complex dual-species cold-atom setups. It provides a good starting point for the fast production of a double-degenerate lithium-rubidium atomic mixture and large samples of ultracold lithium-rubidium ground-state molecules.
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All authors Yun-Xuan Lu, An-Wei Zhu, Christine E. Frank, Xin-Yi Huang, Xin-Yu Luo
Biological Physics
A biological hydraulic accumulator: How the squirting cucumber, Ecballium elaterium, squirts its seeds
Sergio Testón-Martínez, Carlos Gutierrez-Ariza, Francisco J. Ocaña et al. (+3 more)
Seed dispersal is a fundamental process that allows offspring to reach suitable habitats and colonize new environments. While most plants rely on external vectors, some have evolved mechanisms that employ the buildup of
liquid pressure in a closed compartment and its explosive release to disperse their seeds. This form of energy storage, reinvented by humans for engineering applications, is termed a hydraulic accumulator. Here we investigated the fluid mechanics involved in dispersal in the squirting cucumber, Ecballium elaterium integrating high-speed videography (up to 10 000 fps), microtomography, and internal pressure sensors. We recorded long-term pressure time series showing that E. elaterium exhibits circadian (24 hour) and ultradian (short-period) rhythms. Remarkably, the measurements revealed a lack of correlation between fruit and stem turgor; while the stem showed strong circadian cycles, the fruit often did not, suggesting isolated physiological processes in different tissues. The fruit's spongy wall tissue stores elastic potential energy as turgor pressure builds to nearly one atmosphere (92-99 kPa). Upon detachment, this energy is rapidly released to expel a turbulent, particle-laden
liquid jet. Microtomography revealed that the seeds are packed around a central funiculus, a configuration that optimizes their exit through the basal orifice at velocities of up to 30 m/s. Seeds eventually move faster than the
liquid droplets during the later stages of ejection as they shed their
liquid coating. This sophisticated mechanism ensures a broad dispersal cone, effectively spreading offspring across space and environmental conditions.
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All authors Sergio Testón-Martínez, Carlos Gutierrez-Ariza, Francisco J. Ocaña, Rafael Rubio de Casas, C. Ignacio Sainz-Díaz, Julyan H. E. Cartwright
Fluid Dynamics
Turbulence enhances bird tail aerodynamic performance
Ariane Gayout
Turbulence is omnipresent in the atmosphere and a long-standing scientific conundrum that makes flight complex. This complexity is little understood; surprisingly, when
turbulence arises, air vehicles struggle while birds seem to thrive. Birds often encounter intense
turbulence during takeoff and landing, because of turbulent boundary layer effects. During landing, birds respond by fanning their tail over a wide range of spreads and angles of attack. How their tail functions aerodynamically under these conditions is little understood. Here, we use a bio-hybrid feathered
robot model of a pigeon tail in a wind tunnel to compare its aerodynamics in laminar versus turbulent flow. We measured the lift and drag forces generated by the tail as a function of angle of attack, tail spread, and flow condition. We found tail spread scarcely changes tail aerodynamic lift and drag force coefficients, despite large aspect ratio variations. Consequently, tail spread primarily changes force via tail area modulation, simplifying flight control. The effect of laminar versus turbulent flow is pronounced; at the same tail spread and angle of attack,
turbulence increases lift and drag by approximately a factor two. Quantitative flow measurement analysis with proper orthogonal decomposition shows force enhancement is linked to modifications in the spatial and temporal structure of the wake. The results suggest a wake instability that arises in laminar flow is suppressed in turbulent flow, which enhances tail efficiency, benefiting flight control. These insights may inspire engineers to design aerial vehicle tails with improved flight control in
turbulence.
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Atomic Physics
Optical pumping and laser slowing of a heavy molecule
Shuhua Deng, Shoukang Yang, Zixuan Zeng et al. (+1 more)
Precision measurements of the electron's electric dipole moment (eEDM) are critical for testing fundamental
symmetries in particle physics, and heavy polar molecules-such as barium monofluoride (BaF)-have emerged as promising candidates for advancing the sensitivity. However, the achievement of a 3D magneto-optical trap (MOT) required slowing BaF molecules to near-zero velocity by scattering over 10^4
photons per molecule, demanding a quasi-cycling transition with minimal leakage. We present a detailed study of the leakage channels, including higher vibrational and rotational states. By combining microwave remixing with optical pumping of rotational and vibrational dark states, we reduced the total leakage fraction to 10^-5. Using frequency-chirped
laser slowing, we slowed a subset of buffer-gas-cooled BaF molecules from approximately 80 m/s to near-zero velocity, which is critical for efficient MOT loading. This work establishes the technical foundation for precision eEDM measurements using
laser-cooled heavy molecules.
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All authors Shuhua Deng, Shoukang Yang, Zixuan Zeng, Bo Yan
Biological Physics
Mechanical properties of chiral helical polymers-from single filaments to actin bundles
Amir Khosravanizadeh, François Nédélec and Serge Dmitrieff
The mechanical properties of biological
polymers are essential to their biological functions. Here, we introduce a highly coarse-grained model of helical filaments that preserves helicity and chirality while enabling mesoscale simulations. This is implemented in Cytosim, a widely-used open-source cytoskeleton simulation platform. We first show that we can predict the shape and mechanical properties of this helical filament, allowing for its fine control. We find the parameters that allow the resulting filament to accurately match the properties of actin filaments found experimentally}. Using this model of actin, we investigated the role of actin chirality in motor-driven dynamics. We first show that in two different experimental configurations, motor movement along a helical filament results in a
chiral motion of the filament. In a bundle of helical filaments, dimeric motors exert torques on each filament, inducing collective behaviors in the bundle such as rotation, coiling, and helical buckling, reminiscent of those observed in filopodia. Together, these results demonstrate the central role of helicity and chirality in actin mechanics and motor-driven dynamics, and establish our framework as a powerful tool for mesoscale simulations. This framework can also be used for other helical filaments beyond actin.
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Optics
Robust Physical Encryption and Unclonable Object Identification in Classical Optical Networks using Standard Integrated Photonic Components
Jack A. Smith and Michael J. Strain
Spectral complexity is a useful resource in physical device identification, disorder-enhanced spectroscopy, and machine learning, but is often achieved in chip-scale devices at the expense of propagation loss, scalability, or reconfigurability. In this work, we demonstrate that device specific spectral complexity can be achieved using completely standardized photonic building blocks. Using a waveguide Mach-Zehnder interferometer internally loaded with two sets of non-concentric dual ring resonators, we demonstrate the generation of unclonable keys for one-time pad encryption which can be reconfigured on the fly by applying small voltages to on-chip thermo-optic elements. With this method, we access a keyspace larger than 12 Tb for a single device with simple, single-mode waveguide input and output coupling. Using two devices at either end of a communication channel, we show that an eavesdropper tapping the channel fibre link would be unable to recover the same spectrum measured at either end of the link, providing physical encryption for key distribution. Furthermore, being purely classical, this form of secure communications does not require
quantum photonic sources or detectors, and can therefore be easily integrated into pre-existing telecommunication architectures.
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Optics
Photon Echo in Uniaxially Stressed Germanium with Antimony Donors
R.Kh. Zhukavin, V.D. Kukotenko, P.A. Bushuykin et al. (+8 more)
Photon echo is observed in n-type Ge uniaxially stressed along the [111] crystallographic direction, with a coherence relaxation time of 300 ps. The nonlinear polarization responsible for the effect originates from antimony donors. Uniaxial stress induces valley splitting of the donor states, substantially enhancing the coherence time and enabling the observation of
photon echo.
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All authors R.Kh. Zhukavin, V.D. Kukotenko, P.A. Bushuykin, Yu.Yu. Choporova, N.D. Osintseva, K.A. Kovalevsky, V.V. Tsyplenkov, V.V. Gerasimov, N. Dessmann, N.V. Abrosimov, V.N. Shastin
Chemical Physics
Bridging Visual Intuition and Chemical Expertise: An Autonomous Analysis Framework for Nonadiabatic Dynamics Simulations via Mentor-Engineer-Student Collaboration
Yifei Zhu, Jiahui Zhang, Binni Huang et al. (+1 more)
Analyzing nonadiabatic molecular dynamics trajectories traditionally heavily relies on expert intuition and visual pattern recognition, a process that is difficult to formalize. We present VisU, a
vision-driven framework that leverages the complementary strengths of two state-of-the-art large
language models to establish a "virtual research collective." This collective operates through a "Mentor-Engineer-Student" paradigm that mimics the collaborative intelligence of a professional chemistry laboratory. Within this ecosystem, the Mentor provides physical intuition through visual
reasoning, while the Engineer adaptively constructs analysis scripts, and the Student executes the pipeline and manages the data and results. VisU autonomously orchestrates a four-stage workflow comprising Preprocessing, Recursive Channel Discovery, Important-Motion Identification, and Validation/Summary. This systematic approach identifies reaction channels and key
nuclear motions while generating professional academic reports. By bridging visual insight with chemical expertise, VisU establishes a new paradigm for human-AI collaboration in the analysis of excited-state dynamics simulation results, significantly reducing dependence on manual interpretation and enabling more intuitive, scalable mechanistic discovery.
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All authors Yifei Zhu, Jiahui Zhang, Binni Huang, Zhenggang Lan
Optics
Unidirectional reflection lasing based on destructive interference and Bragg scattering modulation in defective atomic lattice
Xinfu Zheng, Chen Peng, Duanfu Chen et al. (+5 more)
The novel and ingenious scheme we propose for achieving unidirectional reflection lasing (URL) involves integrating a one-dimensional (1D) defective atomic
lattice with a coherent gain atomic system. Its physical essence lies in the fact that the right-side reflectivity is drastically reduced due to the destructive interference between primary and secondary reflections, whereas on the left-side primary reflection is effectively suppressed and the secondary reflection is efficiently enhanced, ultimately reaching the lasing threshold. Through numerical results and further analyses, we have elucidated how to precisely tailor the
lattice parameters and coupling fields to control destructive interference point (DIP), thereby realizing URL and enabling its active modulation. Our scheme is experimentally feasible and not only effectively circumvents the stringent conditions faced in directly realizing URL, providing a new pathway, but also beneficial for integrating active photonic devices into compact
quantum networks and may improve the efficiency of optical information transmission.
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All authors Xinfu Zheng, Chen Peng, Duanfu Chen, Tinggui Zhang, Hanxiao Zhang, Dong Yan, Jinhui Wu, Hong Yang
Physics and Society
The effect of HVDC lines in power-grids via Kuramoto modelling
Kristóf Benedek and Géza Ódor
We present a numerical study on the synchronization and cascade failure behaviour by solving the adaptive second-order Kuramoto model on a large high voltage (HV) European power-grid. This non-perturbative analysis takes into account non-linear effects, which occur even when phase differences are large, when the system is away from the steady state, and even during a blackout cascade. Our dynamical simulations show that improvements in the phase synchronziation stabilization as well as the in the cascade sizes can be related to the finite size scaling behaviour of the second order Kuramoto on graphs with $d_s<4$ spectral dimensions. On the other hand drawbacks in the frequency spread and Braess effects also occur by varying the total transmitted power at large and small global couplings, presumably when the fluctuations are small, causing a freezing in the dynamics. We compare simulations of the fully AC model with those of static or adaptive High Voltage Direct Current (HVDC) line replacements. The adaptive (local frequency difference-based) HVDC lines are more efficient in the steady state, at the expense of very long relaxation times.
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Optics
Li-Wei Wang, Bolun Hu, Haixiao Zhang et al. (+3 more)
The interplay between
topology and non-Hermiticity gives rise to exotic dynamic phenomena that challenge conventional wave-packet propagation and
entanglement dynamics. While recent studies have established the non-Hermitian skin effect (NHSE) as a key mechanism for anomalous wave dynamics, a unified framework for characterizing and controlling
entanglement evolution in non-Hermitian topological systems remains underdeveloped. Here, by combining theory and experiments, we demonstrate that
entanglement entropy (EE) and transport currents serve as robust dynamic probes to distinguish various non-Hermitian topological regimes. Using a generalized non-Hermitian Su-Schrieffer-Heeger model implemented in an acoustic analog platform, we identify three dynamic phases, bulk-like, edge-like, and skin-like regimes, each exhibiting unique EE signatures and transport characteristics. In particular, skin-like dynamics exhibit periodic information shuttling with finite, oscillatory EE, while edge-like dynamics lead to complete EE suppression. We further map the dynamic phase diagram and show that EE scaling and temporal profiles directly reflect the competition between coherent delocalization and NHSE-driven localization. Our results establish a programmable approach to steering
entanglement and transport via tailored non-Hermitian couplings, offering a pathway for engineering
quantum information dynamics in synthetic phononic, photonic, and
quantum simulators.
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All authors Li-Wei Wang, Bolun Hu, Haixiao Zhang, Kefan Sun, Ying Cheng, Jian-Hua Jiang
Optics
Exceptional Points in the Scattering Resonances of a Sphere Dimer
Emanuele Corsaro, Filippo Capolino and Carlo Forestiere
We investigate exceptional points of degeneracy (EPDs) in electromagnetic scattering of a sphere dimer from the electroquasistatic limit to the fully retarded regime. In the quasistatic limit, we prove that $\parity\trev$-symmetric configurations, realized by spheres with complex-conjugate susceptibilities, host EPDs. Beyond this limit, retardation breaks $\mathscr{PT}$-
symmetry; nevertheless, by jointly tuning the material dispersion of the two spheres, we derive analytic synthesis conditions for realizing EPDs at real frequencies. Near an EPD, we show that single-parameter perturbations yield the characteristic square-root splitting of the eigenfrequencies, and we quantify its impact on scattering, extinction, and absorption, clarifying sensing implications.
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Biological Physics
Protocellular energetics: Free energy estimates for all metabolic, self-assembly and vesicle fission processes
Steen Rasmussen, Thomas Frederiksen, Masayuki Imai et al. (+3 more)
As minimal
cells or protocells are dramatically simpler than modern unicells it is possible to quantitatively estimate free energy changes for every process in the lifecycle of a protocell and compare these with estimates of the free energy changes for lifecycles in modern unicells. We present quantitative estimates of all metabolic changes in part by new density function theory (DFT) estimations, in part by compiling previously measured or estimated free energy changes, and in part by new thermodynamic calculations for all self-assembly, vesicle bending, and fission energies.
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All authors Steen Rasmussen, Thomas Frederiksen, Masayuki Imai, Sheref S. Mansy, Sabine Muller, Marek Grzelczak
Optics · Cross-listed from quant-ph
5-GHz chip-based quantum key distribution with 1Mbps secure key rate over 150 km
Guo-Wei Zhang, Sheng-Teng Zheng, You Xiao et al. (+16 more)
Quantum key distribution (QKD) enables secure communication by harnessing the fundamental principles of
quantum physics, which inherently guarantee information-theoretic security and intrinsic resistance to
quantum computing attacks. However, the secure key rate of QKD typically decreases exponentially with increasing channel distance. In this work, by developing a novel polarization-state preparation method, an ultra-low time-jitter
laser source and superconducting nanowire single-
photon detectors, we demonstrate a 5-GHz integrated QKD system featuring ultra-low
quantum bit error rates (QBERs). The system achieves secure key rates of 1.076 Mbps at 150 km and 105 kbps at 200 km over standard single-mode fiber channels, respectively. Our system substantially enhances the secure key rate, enabling high-resolution
video calls with one-time-pad encryption over intercity backbone QKD links. This work represents a significant step forward in the development of high-performance practical QKD systems.
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All authors Guo-Wei Zhang, Sheng-Teng Zheng, You Xiao, Fang-Xiang Wang, Wen-Jing Ding, Dianpeng Wang, Penglei Hao, Li Zhang, Jia-Lin Chen, Yu-Yang Ding, Shuang Wang, De-Yong He, Zhen-Qiang Yin, Zheng Zhou, Hao Li, Lixing You, Guang-Can Guo, Wei Chen, Zheng-Fu Han
Optics
Intrinsic Meron Spin Textures in Generic Focused Fields
Di Liu, Han Liu and Zheng Xi
Optical
spin textures with nontrivial
topology hold promise for structured light and photonic information processing, yet their generation typically relies heavily on externally structured light with care. This raises questions about their universal existence and true robustness. Here, we uncover and experimentally verify a meron-like
spin texture that emerges intrinsically in focused fields, without any wavefront engineering. This intrinsic meron
spin texture, unlike their externally engineered counterparts, exhibits exceptional robustness against a wide range of inputs, including partially polarized and spatially disordered pupils corrupted by decoherence and depolarization. We attribute its resilience to topological protection from phase
vortices in the focal field. Our findings reveal a naturally occurring
spin structure that is intrinsic to the focused field with exceptional robustness against noise, which complements the existing externally engineered ones. It offers new ingredients into topological
spin textures in optics and enriches their potentials for disorder-resilient photonic applications.
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Optics
A two-dimensional terahertz smart wristband for integrated sensing and communication
Shaojing Liu, Yongsheng Zhu, Runli Li et al. (+7 more)
The development of wearable devices for terahertz (THz) integrated sensing and communication (
ISAC) is pivotal for forthcoming 6G Internet of Things (IoT) and wearable optoelectronics. However, existing THz system suffers from bulkiness, narrow spectral response and limited flexibility constrained by their dependence on external
antennas, complex coupling architectures and rigid components. Here, we present a 2D THz smart wristband based on a
graphene plasmon polariton atomic cavity (PPAC) array, which integrates sensing and communication within a monolithic microdetector. Operating without any external
antenna, the compact and flexible device enables self-powered, polarization-sensitive and frequency-selective THz detection across a broad response spectrum from 0.25 to 4.24 THz, with a responsivity of 6 V/W, a response time of 62 ms, and mechanical robustness maintained over 2000 bending cycles. Notably, we further exploit its multi-parameter THz responses for dual-purpose
ISAC functionality. For sensing, the polarization- and strain-dependent THz responses are utilized as high-dimensional features for a convolutional neural network (CNN), enabling
circuit fault diagnosis with 97% accuracy. For communication, the device implements secure encrypted communication under simulated on-body wearing condition through dual-channel encoding of THz polarization and on-off signals. This 2D
ISAC platform paves the way for miniaturized, intelligent wearable systems for advanced human-machine interaction.
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All authors Shaojing Liu, Yongsheng Zhu, Runli Li, Ximiao Wang, Hongjia Zhu, Shangdong Li, Hai Ou, Yanlin Ke, Runze Zhan, Huanjun Chen
Plasma Physics
The role of particle feedback on particle acceleration in magnetic reconnection
Shimin Liang and Nianyu Yi
Magnetic reconnection is a ubiquitous process in astrophysical
plasmas and an efficient mechanism for particle acceleration. Using 2.5D magnetohydrodynamic (MHD) simulations with a co-evolving fluid-particle framework, we investigate how particle feedback affects reconnection and acceleration. Our simulations demonstrate that particle feedback to the fluid amplifies shear flows within
magnetic islands, which strengthens the convective electric field and thereby boosts particle acceleration. This mechanism results in a higher maximum particle energy and a harder non-thermal energy spectrum. The guide field suppresses both the increase in gas internal energy and particle acceleration. These findings highlight the complex interplay between feedback, guide fields, and reconnection dynamics.
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Fluid Dynamics · Cross-listed from quant-ph
Towards Quantum Machine Learning of Lattice Boltzmann Collision Operators for Fluid Dynamic Simulations
Wael Itani and Katepalli R. Sreenivasan
We attempt the use of a
unitary operator to approximate the
lattice Boltzmann collision operator. We use a modified amplitude encoding to bypass the renormalization that would have required classical processing at every step (thus eroding any
quantum advantage to be had). We describe the hard-wiring of the
lattice Boltzmann
symmetries into the
quantum circuit and show that, for the specific case of the cavity flow, approximating the nonlinear system is limited to low velocities. These findings may help us understand better the possibilities of nonlinear simulations on a
quantum computer, and also pave the way for a discussion on how
quantum machine learning might be harnessed to address more complex problems.
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Geophysics · Cross-listed from cs.CV
Anomaly detection in satellite imagery through temporal inpainting
Bertrand Rouet-Leduc and Claudia Hulbert
Detecting surface changes from satellite imagery is critical for rapid disaster response and environmental monitoring, yet remains challenging due to the complex interplay between atmospheric noise, seasonal variations, and sensor artifacts. Here we show that deep learning can leverage the temporal redundancy of satellite time series to detect anomalies at unprecedented sensitivity, by learning to predict what the surface should look like in the absence of change. We train an inpainting model built upon the SATLAS foundation model to reconstruct the last frame of a Sentinel-2 time series from preceding acquisitions, using globally distributed training data spanning diverse
climate zones and land cover types. When applied to regions affected by sudden surface changes, the discrepancy between prediction and observation reveals anomalies that traditional change detection methods miss. We validate our approach on earthquake-triggered surface ruptures from the 2023 Turkey-Syria earthquake sequence, demonstrating detection of a rift feature in Tepehan with higher sensitivity and specificity than temporal median or Reed-Xiaoli anomaly detectors. Our method reaches detection thresholds approximately three times lower than baseline approaches, providing a path towards automated, global-scale monitoring of surface changes from freely available multi-spectral satellite data.
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Instrumentation and Detectors
Design, construction, and testing of the PandaX-xT cryogenics system
Xu Wang, Li Zhao, Xiang Xiao et al. (+3 more)
The PandaX-xT is a next-generation experiment with broad scientific goals, including the search for dark matter, Neutrinoless Double Beta Decay, and astrophysical
neutrinos, using a dual-phase time projection chamber with about 43 tons of
liquid xenon. A new cryogenics system of the PandaX-xT is described in this paper. It is developed to handle large mass of
liquid xenon efficiently and safely, including two cooling towers for normal operation and one
liquid-nitrogen coil for emergency case. Each cooling tower equipped with an AL600 Gifford-McMahon cryocooler features a 1300 W heater, specifically designed to maintain the cold finger's temperature at the desired setpoint. The performance of the cooling tower and the coil has been tested. The cryogenics system with two cooling towers has achieved about 1900~W cooling power at 178~K. The
liquid nitrogen coil provides emergency cooling power of more than 1500~W at
liquid xenon temperature. For the prototype of a 1-tonne
liquid xenon detector, the fluctuation of xenon saturated vapor pressure remains below 1 kPa over one month, while the pressure is around 210~kPa.
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All authors Xu Wang, Li Zhao, Xiang Xiao, Xiangyi Cui, Shuaijie Li, Jianglai Liu
Chemical Physics
Assessment of First-Principles Methods in Modeling the Melting Properties of Water
Yifan Li, Bingjia Yang, Chunyi Zhang et al. (+5 more)
First-principles simulations have played a crucial role in deepening our understanding of the thermodynamic properties of water, and machine learning potentials (MLPs) trained on these first-principles data widen the range of accessible properties. However, the capabilities of different first-principles methods are not yet fully understood due to the lack of systematic
benchmarks, the underestimation of the uncertainties introduced by MLPs, and the neglect of
nuclear quantum effects (NQEs). Here, we systematically assess first-principles methods by calculating key melting properties using path integral molecular dynamics (PIMD) driven by Deep Potential (DP) models trained on data from density functional theory (DFT) with SCAN, revPBE0-D3, SCAN0 and revPBE-D3 functionals, as well as from the MB-pol potential. We find that MB-pol is in qualitatively good agreement with the experiment in all properties tested, whereas the four DFT functionals incorrectly predict that NQEs increase the melting temperature. SCAN and SCAN0 slightly underestimate the density change between water and ice upon melting, but revPBE-D3 and revPBE0-D3 severely underestimate it. Moreover, SCAN and SCAN0 correctly predict that the maximum
liquid density occurs at a temperature higher than the melting point, while revPBE-D3 and revPBE0-D3 predict the opposite behavior. Our results highlight limitations in widely used first-principles methods and call for a reassessment of their predictive power in aqueous systems.
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All authors Yifan Li, Bingjia Yang, Chunyi Zhang, Axel Gomez, Pinchen Xie, Yixiao Chen, Pablo M. Piaggi, Roberto Car
Chemical Physics
Training Dataset Matters for Machine Learning Interatomic Potentials: Water Simulation as an Example
Yifan Li, Bingjia Yang, Chunyi Zhang et al. (+5 more)
Accurate predictions of machine learning interatomic potentials (MLIPs) rely on training
datasets covering relevant thermodynamic conditions and phases. Using water as an example, we show that insufficiently sampled
datasets of MLIPs lead to wrong predictions of densities, melting temperatures, and
nuclear quantum effects. In contrast, MLIPs trained on comprehensive
datasets with the same electronic structure method yield consistent property predictions agnostic of MLIP architecture, with densities in quantitative agreement with reference calculations.
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All authors Yifan Li, Bingjia Yang, Chunyi Zhang, Axel Gomez, Pinchen Xie, Yixiao Chen, Pablo M. Piaggi, Roberto Car