Biological Physics
Predictability can be dynamically constructed in deterministic systems
Lars Koopmans, Elinor M. Kay and Hyun Youk
A deterministic system's future can be fixed from the start yet remain unpredictable because of chaos or computational irreducibility. Here we reveal another source of unpredictability for non-chaotic deterministic systems: collective entities making the future legible are initially absent but dynamically constructed. In a generalized cellular automaton, disordered
lattices evolved into static configurations, rectilinear waves, or spiral waves. Although initial configurations fixed each fate, machine-learning models did no better than randomly guessing fates from them. Recoding
cell states geometrically revealed self-organization of prediction-enabling topological entities:
vortices, non-contractible-loop strings, and, most generally, a winding field describing how same-state regions wrap the
lattice. As the winding field self-organized, initially unpredictable fates became increasingly legible. Static and rectilinear-wave fates became progressively predictable, whereas spiral-wave fate became accurately predictable only near wave formation. These results establish that self-organization can build not merely order but entities that make certain futures visible, revealing a gap between determinism and practical predictability.
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Computational Physics · Cross-listed from quant-ph
Simulated Bifurcation Quantum Annealing
Jakub Pawłowski, Paweł Tarasiuk, Jan Tuziemski et al. (+2 more)
We introduce Simulated Bifurcation
Quantum Annealing (SBQA), a
quantum-inspired optimization
algorithm that extends simulated bifurcation by incorporating inter-replica interactions to mimic
quantum tunneling. SBQA retains the efficiency and parallelism of simulated bifurcation while improving performance on sparse and rugged energy landscapes. We derive its equations of motion, analyze parameter dependence, and propose a lightweight auto-tuning strategy. A comprehensive benchmarking study on both large-scale problems and smaller instances relevant for current
quantum hardware shows that SBQA systematically improves on SBM in the sparse and rugged regimes where SBM is known to struggle, while remaining competitive and versatile across a diverse set of tested problem families. These results position SBQA as a practical
quantum-inspired optimization heuristic and a stronger classical baseline for the sparse and rugged regimes studied here.
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All authors Jakub Pawłowski, Paweł Tarasiuk, Jan Tuziemski, Łukasz Pawela, Bartłomiej Gardas
Space Physics · Cross-listed from astro-ph.SR
A Non-Spherical Model for the Solar Coronal Magnetic Field
Ziqi Wu, Jiansen He, Chuanpeng Hou et al. (+7 more)
The coronal
magnetic field plays a fundamental role in governing coronal activities, driving space-weather events, and shaping the heliosphere. Due to a lack of direct observations, extrapolation models such as the Potential Field Source Surface (PFSS) model become the primary method to obtain the three-dimensional
magnetic field distribution in the corona. However, the PFSS model cannot solve the long-standing open-flux problem, in which the extrapolated open
magnetic flux is significantly lower than that inferred from in-situ measurements. To address this issue, we develop a Non-Spherical Potential Field (NSPF) model. The model introduces a Non-Spherical Source Surface (NSSS) defined as an isosurface of the total
magnetic field. The NSSS naturally forms concave structures beneath external current sheets, enabling the model to generate substantially more open
magnetic flux while yielding a physically plausible distribution of open field regions. As a result, the NSPF model successfully reproduces complex coronal
magnetic topologies, interplanetary
magnetic field properties, and
solar wind source mappings. Our refined coronal
magnetic model provides a useful framework for future research on
solar and heliospheric
magnetic coupling.
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All authors Ziqi Wu, Jiansen He, Chuanpeng Hou, Tom van Doorsselaere, Rui Zhuo, Tianhang Chen, Liping Yang, David Pontin, Daniel Verscharen, Fang Shen
Physics and Society
Car Dependency in Urban Accessibility
Bruno Campanelli, Francesco Marzolla, Matteo Bruno et al. (+2 more)
To achieve net-zero emissions, cities must transition away from reliance on private vehicles. However, car-centric urban growth has transformed the automobile from a convenience tool into a necessity for accessing essential services, creating significant "car dependency". This study introduces a novel Car Dependency Index (CDI) that quantifies the accessibility gap between private and public transport across 18 cities in Europe and North America. Utilising high-resolution geospatial data and numerical simulations, we reveal pronounced spatial inequalities, showing that car dependency remains a primary driver of car ownership even when accounting for income. A “what-if" simulation of the planned metro expansion in Rome predicts a reduction of approximately 60,000 commuting vehicles, yet highlights that isolated interventions have localised impacts. We conclude that systemic, network-level transit expansions are essential to dismantle car-based systems and foster equitable, sustainable urban mobility. Our framework provides policymakers with an objective, scalable tool to identify viable areas for car-free zones and target infrastructure investments effectively.
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All authors Bruno Campanelli, Francesco Marzolla, Matteo Bruno, Hygor Piaget Monteiro Melo, Vittorio Loreto
Computational Physics · Cross-listed from cond-mat.mtrl-sci
Parameter-Efficient Fine-Tuning of Machine-Learning Interatomic Potentials for Phonon and Thermal Properties
Jonas Grandel, Philipp Benner and Janine George
Machine-learning interatomic potentials are widely used as computationally efficient surrogates for density functional theory in atomistic simulations, enabling large-scale, long-time modeling of materials systems. We investigate how different fine-tuning strategies influence the prediction of harmonic
phonon band structures, thermal properties, and the potential energy surface along imaginary
phonon modes. We achieve substantial accuracy improvements with minimal additional data, with as few as 10 additional training structures already yielding significant gains. In addition to existing approaches, we introduce Equitrain, a finetuning framework that implements LoRA-based adaptation. Across 53 materials systems, we show that fine-tuned models consistently outperform both the underlying pretrained model and models trained from scratch. Equitrain achieves the best overall performance, and our results demonstrate that fine-tuning enables accurate
phonon predictions.
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Computational Physics · Cross-listed from quant-ph
Two-Qubit Implementation of QAOA for MAX-CUT on an NV-Center Quantum Processor
Leon E. Röscher, Talía L. M. Lezama, Luca Cimino et al. (+3 more)
We report a proof-of-principle implementation of the
quantum approximate optimization
algorithm (QAOA) for the smallest nontrivial MAX-CUT instance on an NV-center-based
quantum processor operating at room temperature. The two-
qubit register is encoded in the electron
spin and the ${}^{14}\mathrm{N}$
nuclear spin of a single NV$^-$ center. Using a minimization formulation of MAX-CUT, we implement a single-layer QAOA ansatz with native entangling and single-
qubit control operations. Because the optical readout of the NV$^-$ center is not projective in the computational basis, we reconstruct computational-basis populations from averaged fluorescence signals and use them to determine the experimental QAOA cost landscape by scanning the variational parameters. These results show that the core elements of QAOA can be realized on this platform and establish a baseline for future improvements in phase tracking, coherence-preserving control, and scaling to larger problem sizes.
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All authors Leon E. Röscher, Talía L. M. Lezama, Luca Cimino, Jonah vom Hofe, Riccardo Bassoli, Frank H. P. Fitzek
Physics and Society
Women's mobility networks enable more efficient travel
Sílvia de Sojo, Sune Lehmann and Laura Alessandretti
Our understanding of gender differences in mobility is marked by a clear tension: surveys portray women's movements as more complex than men's, while digital traces suggest less diverse travel. Here, we resolve the contradiction by modeling trajectories as networks of sequential visits, using smartphone traces linked to self-reported gender for 543,155 individuals across 10 countries. We show that the apparent conflict in the literature arises because women's mobility networks are simultaneously more clustered and more home-anchored – a nuance obscured by aggregate metrics. This pattern arises because women tend to link multiple destinations within single trips, for trips spanning up to 150 km and multiple days. This organization yields systematically higher travel efficiency, measured as distance saved through destination chaining over monthly sequences.
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Biological Physics · Cross-listed from cond-mat.stat-mech
Absence of $\mathrm{O} (2)$ symmetry in the Vicsek model
Yushin Takahashi, Kota Mitsui, Tsuyoshi Mizohata et al. (+1 more)
The phase transition in the Vicsek model is widely believed to be associated with spontaneous
symmetry breaking of the two-dimensional rotational
symmetry $\mathrm{O} (2)$. In this paper, we revisit the original Vicsek model introduced by Vicsek et al. [Phys.~Rev.~Lett.~75,~1226~(1995)] and demonstrate that the original angle-based update rule is not invariant under global phase shifts at the level of angular increments when it is implemented using the principal-value arctangent, as in the original definition. As a consequence, we numerically demonstrate that the phase transition reported in the original paper vanishes when the global phase is adaptively chosen.
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All authors Yushin Takahashi, Kota Mitsui, Tsuyoshi Mizohata, Hideyuki Miyahara
Space Physics · Cross-listed from astro-ph.SR
Imaging magnetically driven astrospheres: a forward modelling approach
Ziqi Wu, Tom Van Doorsselaere, Jiansen He et al. (+5 more)
An astrosphere is a vast, tailed bubble-like volume around a
star, formed through the interaction between the
stellar magnetic field, the
stellar wind, and the interstellar medium (ISM). Detecting and characterizing astrospheres are essential for constraining
stellar wind properties, understanding
stellar evolution, and assessing the habitability of surrounding exoplanetary systems. Charge exchanges between ionized
stellar wind particles and cold ISM hydrogen atoms populate the astrosphere with neutral hydrogen, which can leave observable signatures in the Lyman-$\alpha$ (Ly$\alpha$) line absorption profile. Previous studies have inferred
stellar mass-loss rates by measuring Ly$\alpha$ absorption in
stellar spectra caused by astrospheric neutral hydrogen. However, our knowledge of the global morphology of astrospheres remains limited and largely dependent on sometimes contradictory simulations. Here we investigate the feasibility of detecting Ly$\alpha$ emission generated by resonant scattering from \NH{} surrounding the
star, enabling the construction of a two-dimensional map of the astrosphere. With a three-dimensional magnetohydrodynamic astrosphere model, we perform forward modelling of the Ly$\alpha$ emission and assess the observation feasibility according to the observational limits of the Hubble Space
Telescope (HST). We further discuss the influence of varied line-of-sight orientations and averaged ISM velocity along the line-of-sight. The spatially resolved circumstellar Ly$\alpha$ emission could provide important constraints on the astrospheric configuration and
stellar wind properties, such as the bow shock standing distance, the
stellar wind
symmetry, and the shape of the astro-tail. Our results highlight Ly$\alpha$ astrosphere detections as a promising science case for HST and future missions such as the Habitable Worlds Observatory.}
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All authors Ziqi Wu, Tom Van Doorsselaere, Jiansen He, Hugues Sana, Nicholas Jannsen, Tianhang Chen, Weining Wang, Zheng Sun
Medical Physics
Design of a double breast gradient coil with controlled anterior posterior gradient variation for diffusion weighted imaging
Feng Jia, Gerrit Cornelis Arends, Philipp Amrein et al. (+5 more)
Introduction High performance gradients poses a promise for breast
diffusion weighted imaging (DWI) but are restricted by physiological limits in whole body scanners. While local nonlinear coils offer higher amplitudes, they often suffer from severe gradient reduction near the chest wall. Methods We introduced an optimization framework incorporating a constraint to control anterior posterior gradient variation. A width based figure of merit was defined to evaluate performance regarding coil efficiency and minimum wire width. A prototype was constructed to validate the design methodology. Results The optimized coil achieved a 2.35 fold efficiency increase over standard linear coils. Compared to previous nonlinear designs, the new constraint reduced spatial variation by 35.7% and improved minimum efficiency near the chest wall by 2.6 fold. Experimental field maps matched simulations with errors under 8%. Discussion The proposed method effectively mitigates the trade-off between gradient strength and spatial uniformity along anterior posterior direction. By enhancing performance in the posterior breast region, the design addresses a critical limitation of previous local coils. Conclusion This framework enables the development of high performance, robust local gradient coils, facilitating the clinical implementation of advanced DWI protocols for breast cancer screening.
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All authors Feng Jia, Gerrit Cornelis Arends, Philipp Amrein, Edwin Versteeg, Dennis W. J. Klomp, Maxim Zaitsev, Chantal M. W. Tax, Sebastian Littin
Optics
Scattering at Space-Time Interfaces between Dispersive Media
Klaas De Kinder and Christophe Caloz
Dynamic modulation of material properties in space and time enables powerful control over wave propagation, yet existing theories largely rely on idealized, nondispersive models. In realistic media, frequency dispersion can strongly reshape wave dynamics, especially near resonances in highly dispersive platforms such as epsilon-near-zero materials. Here, we develop a general frequency transition theory for electromagnetic scattering at moving interfaces between dispersive media. From phase continuity, we derive nonlinear frequency transition relations and show that dispersion fundamentally reshapes the space-time scattering landscape, enabling additional propagating solutions with no counterpart in nondispersive systems. Applied to Drude, Lorentz and double-Drude media, the theory reveals how resonant dispersion, material loss and negative-index branches reorganize the scattering channels. For the two-wave scattering class, we further introduce a mixed-domain formulation that combines time-domain interface kinematics with frequency-domain constitutive relations, yielding closed-form scattering coefficients. These results establish a unified framework for dispersive space-time scattering and open opportunities for dispersion-based transition engineering in realistic materials.
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Optics
A Non-Abelian Route to Z2 Non-Hermitian Skin Effects
Huiyan Tang, Yaxuan Zhang, Ziteng Wang et al. (+7 more)
The non-Hermitian skin effect (NHSE), characterized by extensive boundary accumulation of eigenstates under open boundary conditions, has emerged as a central phenomenon in non-Hermitian physics. Conventionally, the NHSE arises from either non-reciprocal couplings or onsite gain and loss combined with synthetic gauge fields. Existing studies, however, have been largely confined to frameworks with Abelian-coupling, leaving the role of non-Abelian couplings essentially unexplored. Here, we demonstrate that non-Abelian-couplings can generate the NHSE, giving rise to a time-reversal-
symmetry-protected Z2 skin effect with pseudospin-dependent boundary localization and dynamical pseudospin separation. Experimentally, we implement a representative four-level model using a programmable topolectrical
circuit and directly observe both the predicted NHSE and the boundary-induced pseudospin-inversion reflection. Our work establishes a fundamental link between non-Abelian coupling and non-Hermitian
topology, opening new avenues for realizing non-reciprocity-free topological materials and devices.
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All authors Huiyan Tang, Yaxuan Zhang, Ziteng Wang, Liqin Tang, Daohong Song, Jingjun Xu, Weixuan Zhang, Hrvoje Buljan, Xiangdong Zhang, Zhigang Chen
Instrumentation and Detectors
A MIDAS-based Data Acquisition System for Gaseous Detectors
Yuanchun Liu, Tao Li, Yu Chen et al. (+4 more)
We present a data acquisition~(DAQ) software based on the MIDAS framework, specifically for gaseous detectors to support the detector deployments and applications. It implements a comprehensive suite of functions, including parameter configuration, data acquisition, decoding, and storage, alongside web-based operation and real-time monitoring capabilities. We establish a fully unified workflow spanning data acquisition to offline analysis, enabling real-time visualization of signal waveforms and energy spectra. The system has been successfully deployed in the PandaX-III experiment, which utilized a high-pressure gaseous detector to search for neutrinoless double beta decay. Its performance and stability have been validated through tests involving two distinct electronics setups and joint commissioning with the detector.
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All authors Yuanchun Liu, Tao Li, Yu Chen, Ke Han, Leyan Li, Shaobo Wang, Wei Wang
Chemical Physics
Acep$K_{\rm a}$: Thermodynamics-Informed p$K_{\rm a}$ Prediction and Protonation-State Generation in PlayMolecule AI
Francesco Pesce, Stephen Farr and Gianni de Fabritiis
The acid dissociation constants (p$K_{\rm a}$) and the protonation states that they determine govern solubility, permeability, and
protein–ligand binding, making their accurate prediction essential in drug discovery. We present Acep$K_{\rm a}$, an application in the PlayMolecule AI platform that implements the Uni-p$K_{\rm a}$ framework, which couples statistical mechanics with representation learning. Rather than treating p$K_{\rm a}$ as a scalar regression target, Acep$K_{\rm a}$ models the complete protonation ensemble, enforcing thermodynamic consistency across coupled ionization sites. The application is built on an independently retrained Uni-Mol backbone that matches state-of-the-art accuracy on standard public
benchmarks. We further describe three engineering contributions: AceConfgen, a GPU-accelerated conformer generator approximately 7 times faster than other GPU implementations and more than an order of magnitude faster than multithreaded RDKit; a streamlined inference engine that protonates molecules directly; and a 3D-aware mode that applies predicted protonation states to bound ligand poses. Acep$K_{\rm a}$ supports library-scale prediction and provides a validated, ready-to-use implementation of this methodology, available at open.playmolecule.org.
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Optics
Double-Freeform Lens Design for Angular-Spatial Control of Light Fields
Yuou Sun, Bailin Deng and Juyong Zhang
Precise simultaneous control of both angular and spatial light-field distributions remains a longstanding challenge in optical design, often requiring complex multi-element configurations. In this work, we propose a compact single-lens solution that achieves unified angular-spatial modulation through the co-optimization of double freeform surfaces. The problem is formulated as an extended caustic design that enforces prescribed irradiance patterns on two distinct receptive planes, where the dual-plane constraint implicitly defines the directional characteristics of the light field while preserving spatial accuracy. This framework eliminates the need for auxiliary optical components while delivering performance comparable to that of conventional multi-lens systems. Comprehensive numerical simulations verify the method's effectiveness, demonstrating accurate and stable control of both angular and spatial light-field properties. The proposed approach establishes a practical foundation for compact, high-performance optical systems and provides a promising route toward integrated angular-spatial light-field engineering.
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Optics · Cross-listed from eess.SP
Novel Single Clad Ho-doped Fiber with High Slope Efficiency and Low Ion Pairing
Robert E. Tench, Wiktor Walasik, Alexandre Amavigan et al. (+3 more)
We report the design and experimental and simulated performance for a 2050 nm band fiber amplifier with high optical-optical slope efficiency and low ion pairing, using a novel high performance single clad Ho-doped fiber from the Naval Research Laboratory (NRL). We measure an optical-optical slope efficiency of 57% using 1 mW input signal power and 1860 nm pumping which we believe is the highest slope efficiency obtained to date for a single clad single stage copumped HDFA. A new method for non-destructive measurement of the ion pairing coefficient in Ho-doped fibers is introduced and validated. Using this method, we link our 57% slope efficiency to a low ion pairing coefficient of 4% in the NRL Ho-doped fiber as derived from our experimental data. We present an overview and survey of the ion pairing results for Ho-doped fiber amplifiers and
lasers reported so far in the literature.
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All authors Robert E. Tench, Wiktor Walasik, Alexandre Amavigan, Jean-Marc Delavaux, Colin C. Baker, Daniel Rhonehouse
Computational Physics
Stable Determinant Monte Carlo Simulations at Large Inverse Temperature $\beta$
Thomas Luu, Johann Ostmeyer, Petar Sinilkov et al. (+1 more)
At low temperatures $T$ where $1/T=\beta\gg1$ the naïve implementation of determinant
quantum Monte Carlo (DQMC) methods suffers from loss of precision and numerical instabilities when evaluating the
fermion determinant. This instability propagates into the calculation of observables that rely on the evaluation of the inverse of the
fermion matrix, or the Greens function. For DQMC methods that rely on the
Hamiltonian Monte Carlo (HMC)
algorithm, an additional complication comes from evaluating the force terms required for integrating Hamilton's equations of motion, since here loss of precision and numerical instabilities are also prevalent. We show how to address all these issues using various choices of
matrix decompositions, allowing us to simulate at $\beta\gtrsim 90$, which corresponds to room temperature for
graphene structures. Furthermore, our implementation has numerical costs that scale similarly to the naïve implementation, namely as $\mathcal{O}(N_x^3N_t)$, where $N_x$ ($N_t$) is the number of spatial (temporal) sites.
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All authors Thomas Luu, Johann Ostmeyer, Petar Sinilkov, Finn L. Temmen
Optics
Fractal hierarchy enables exponential scaling of topological boundary states
Limin Song, Zhichan Hu, Ziteng Wang et al. (+7 more)
Exponential growth describes an extremely rapid process ubiquitous across mathematics and diverse physical, biological, and technological systems. Here, we introduce a class of fractal-inspired
lattices that combine long-range periodic order with self-similar hierarchy, establishing a structural motif that enables exponential scaling of topological boundary states. We demonstrate this phenomenon in (i) a quasi-one-dimensional
lattice chain constructed from Koch-curve unit
cells and (ii) a two-dimensional periodic tiling
lattice composed of Sierpinski-gasket unit
cells. We show that, for suitable coupling parameters, both the number of topological boundary states $N_{\ell}$ and the number of topological minigaps $M_{\ell}$ grow exponentially with the fractal generation index $\ell$. We find that $N_{\ell}$ is an integer multiple of $M_{\ell}$, with the integer determined by the underlying
symmetry. This hierarchical scaling law is captured by multi-topological-phase theory and confirmed experimentally in
laser-written photonic
lattices. Our results identify fractal hierarchy as a materials architecture principle for controlling boundary-state multiplicity, revealing an interplay between
topology, self-similar geometry, and periodic order. More broadly, this work suggests a route to synthetic materials and integrated photonic platforms in which large numbers of robust boundary modes can be engineered within compact architectures.
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All authors Limin Song, Zhichan Hu, Ziteng Wang, Domenico Bongiovanni, Liqin Tang, Daohong Song, Roberto Morandotti, Jingjun Xu, Hrvoje Buljan, Zhigang Chen
Instrumentation and Detectors · Cross-listed from hep-ex
Potassium-40 geoneutrinos detection and the Earth's large-scale structures imaging by directional geoneutrino detection
Haozhe Sun, Zhe Wang and Shaomin Chen
Geoneutrinos, the electron (anti)
neutrinos generated in decays or decay chains of radioactive elements within the Earth, primarily K-40, U-238, and Th-232, serve as a unique probe of the Earth's inner chemical composition. A directional geoneutrino detection method with a Cherenkov
liquid scintillator is investigated in this work.
Neutrino-electron elastic scattering in the Cherenkov scintillator is employed to detect geoneutrinos. The direction reconstruction resolution for
neutrinos is studied. The radioactive and
solar neutrino backgrounds are taken into account. The intrinsic
neutrino background from the Sun is suppressed with an optimized
solar angle cut. The required exposure to reach a 3 sigma sensitivity to discover geoneutrinos in a potassium-dominated energy region is 6.9 kiloton-years. The potential to image Earth's large-scale structures using directional geoneutrino information is also studied. The required exposure to reject a uniform terrestrial angle distribution of geoneutrinos at the 3 sigma level exceeds 27 kiloton-years.
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Atomic Physics
Stern-Gerlach interferometry in three dimensions: the role of transverse fields
D. Meng, D. Z. Chan and J. D. D. Martin
We show that superficially similar implementations of Stern-Gerlach Interferometers (SGIs) are expected to differ dramatically in their sensitivity to fields transverse to the primary acceleration direction. These transverse fields unavoidably accompany any static
magnetic or electric field gradients, and have been shown by Comparat [Phys. Rev. A 101, 023606 (2020)] to limit the precision application of SGIs. As a concrete example, we consider SGIs with ultracold Rb Rydberg atoms accelerated by spatially-varying electric fields. We find that the deleterious effect of transverse fields imply that only some implementations (sequences of field gradients, internal state swaps, and so-on) may exhibit fringes with high visibility.
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Optics · Cross-listed from quant-ph
Vibrationally Induced Resonances in Lasing
Kai Müller, Kimmo Luoma and Christian Schäfer
Optical
circuits and light sources, such as
lasers, undergo continuous miniaturization. In its extreme, nanolasers might be comprised of only a few molecules confined in plasmonic nanoresonators. Few-emitter
lasers promise low energy requirements and fast responses in a footprint that can be inserted into any device or biological tissue. Utilizing the recently developed stacked hierarchy approach, informed from first principles, we demonstrate the impact of vibrational structure on lasing, using the example of few-molecule lasing in plasmonic cavities. Explicitly accounting for the entire vibrational
manifold unveils resonances in the
laser intensity that depend on the Stokes shift, drive strength, and the number of emitters. Our work identifies the limits of the omnipresent "incoherent drive"-approximation and paves the way for the understanding of nanolasers at the molecular scale.
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Computational Physics
A P-Adaptive Hybridizable Discontinuous Galerkin Spectral Element Method for Electrostatic Particle-in-Cell Simulations
Tobias Ott, Stephen Copplestone and Marcel Pfeiffer
This paper presents a p-adaptive high-order hybridizable discontinuous Galerkin spectral element method (HDG-SEM) for solving the Poisson equation in electrostatic
plasma simulations using particle-in-
cell (PIC) schemes. This approach enables element-local refinement of the
polynomial degree, concentrating computational effort specifically in regions with strong gradients. Thus, the method significantly reduces the global number of degrees of freedom compared to uniform high-order methods. The proposed method is implemented in the open-source framework PICLas and validated through a series of
benchmark test cases, including a dielectric sphere and a one-dimensional
plasma sheath. Finally, a two-dimensional axisymmetric simulation of an ion optic demonstrates the method's capability to efficiently model complex
plasma phenomena but also highlights current limitations.
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Plasma Physics
Real-time virtual circuits for plasma shape control via neural network emulators: dynamic validation in closed-loop simulations
K. Pentland, A. Ross, N. C. Amorisco et al. (+5 more)
Reliable confinement and stable performance of tokamak fusion
plasmas require accurate real-time
magnetic shape control. A promising route to reduced latency and increased flexibility in
plasma control systems (PCS) is to emulate physics-based controllers using neural networks (NNs). In prior work, we have demonstrated that virtual
circuits (VCs), which define the poloidal field coil current vectors able to modify each
plasma shape parameter independently, can be accurately emulated with NN models trained on a large library of simulated Grad-Shafranov
equilibria. This enables
magnetic controllers to accurately adapt to evolving
plasma equilibria using real-time VCs (RTVCs), in contrast to pre-set VC schedules whose performance degrades upon departure from their reference
equilibria. Here, we investigate the performance and robustness of these RTVCs in closed-loop simulations using the FreeGSNKE Pulse Design Tool (FPDT): a framework that couples the FreeGSNKE evolutive
equilibrium solver with a virtual PCS. The FPDT models the coupling between controllers,
plasma current and shape response, and actuator constraints. Using the RTVCs within the FPDT, we demonstrate effective in-silico control of MAST Upgrade (MAST-U)
plasma scenarios and show that the emulators are robust in the presence of input measurement uncertainty and under different update frequencies. These results establish the viability of RTVCs for closed-loop
plasma shape control, representing a key step toward real-time deployment in the MAST-U PCS.
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All authors K. Pentland, A. Ross, N. C. Amorisco, P. Cavestany, T. Nunn, A. Agnello, G. K. Holt, C. Vincent
Optics
Inverse-designed non-volatile phase change varifocal metalens at the edge of the visible spectrum
Subrahmanyam S. G. Mantha and Harish N. S. Krishnamoorthy
Reconfigurable metalenses capable of large focal length tuning, fast response times, and high focusing efficiency while maintaining diffraction-limited operation are highly desirable for next-generation adaptive imaging systems. Phase change chalcogenides provide a promising platform for such devices by exploiting the reversible amorphous-to-crystalline transition to achieve non-volatile tuning with relatively fast switching. However, extending these approaches towards the visible spectrum is challenging because of the reduced meta-atom dimensions, stringent phase coverage requirements, intrinsic material absorption and the need to simultaneously preserve focusing efficiency and image quality across multiple material states. Here, we present a dynamically tunable metalens based on $Sb_2$$S_3$ operating at the edge of the visible spectrum. The design framework combines finite element computations with a genetic
algorithm-based inverse design approach to achieve robust phase control in both amorphous and crystalline states. The resulting metalens shows near-diffraction-limited performance with a focal length tunability of $33\%$, Strehl ratios of $0.80$ and $0.77$ in the amorphous and crystalline states, respectively, and focusing efficiencies of approximately $40\%$ which are among the highest reported for metalenses designed entirely within an active phase-change chalcogenide medium.
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Atomic Physics
Probing topological edge states in a molecular synthetic dimension
Adarsh P. Raghuram, Francesca M. Blondell, Jonathan M. Mortlock et al. (+7 more)
Engineering synthetic dimensions, where the physics of additional spatial dimensions is simulated within the internal states of a
quantum system, allows the realisation of phenomena not otherwise accessible in experiments. Ultracold ground-state polar molecules are an ideal platform to encode synthetic dimensions, offering access to large
Hilbert spaces of long-lived internal states associated with the rotational and hyperfine degrees of freedom, that can be coupled together with microwave fields to simulate tunnelling. Here, to
benchmark the advantages of ultracold molecules, we encode a 1D synthetic
lattice in the rotational states of ultracold RbCs molecules and use it to investigate the well-known Su-Schrieffer-Heeger (SSH) model, a minimal model displaying topological properties. To probe the system, we perform spectroscopy using an auxiliary rotational state and study the time dynamics after deterministic state preparation. We demonstrate long coherence times, typically ~500 times the
lattice tunnelling period, even for a synthetic
lattice using 8 rotational states. Observations of dynamics at long times with full site-resolved readout of the synthetic dimension allow us to test the effects of
chiral and non-
chiral perturbations on the topologically protected edge states. Our work lays the foundation for further
quantum simulations using the rich internal structure of molecules, including dipolar string phases in interacting samples of molecules, and adiabatic state preparation of many-body
Hamiltonians.
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All authors Adarsh P. Raghuram, Francesca M. Blondell, Jonathan M. Mortlock, Benjamin P. Maddox, Sohail Dasgupta, Holly A. J. Middleton-Spencer, Kaden R. A. Hazzard, Hannah M. Price, Philip D. Gregory, Simon L. Cornish
Optics · Cross-listed from quant-ph
Engineering a Phase-Noise-Based Quantum Random Number Generator for Real-Time Secure Applications: Design, Validation, and Scalability
Anurag K. S. V., Shubham Chouhan, K. Srinivasan et al. (+2 more)
Random Number Generators (RNGs) are crucial for applications ranging from cryptography to simulations. Depending on the source of randomness, RNGs are classified into Pseudo-Random Number Generators (PRNGs), True Random Number Generators (TRNGs), and
Quantum Random Number Generators (QRNGs). This work presents the end-to-end development of a high-speed, high-efficiency, phase-noise-based QRNG system that taps into the
quantum phase noise of a single-frequency
laser, with randomness originating from spontaneous emission. Using a self-heterodyne measurement with a
semiconductor laser (linewidth $\approx$ 5.23 $GHz$) operated near threshold and a $\sim$48 $cm$ fiber delay line, a raw data generation rate of 2.0 $Gbps$ is achieved. To ensure uniform randomness in the QRNG output, robust extraction techniques developed in-house, such as the Toeplitz Strong Extractor (TSE), are used. Randomness validation using the NIST and Diehard test suites confirms that all statistical tests pass at standard confidence levels. The developed system achieves a post-processed generation rate of 1.0 $Gbps$ in operation and attains a Technology Readiness Level (TRL) of 7, approaching TRL 8, making it suitable for real-time secure applications such as cryptographic key generation and
stochastic modeling.
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All authors Anurag K. S. V., Shubham Chouhan, K. Srinivasan, G. Raghavan, Kanaka Raju P
Chemical Physics
Role of anisotropic electronic friction in laser-driven hydrogen recombination on copper
Alexander Spears, Wojciech G. Stark and Reinhard J. Maurer
Ultrafast light-driven chemical dynamics at surfaces are governed by energy transfer from excited electrons to vibrational degrees of freedom. When this nonadiabatic energy transfer is anisotropic, it can lead to dynamical steering effects that affect reaction probabilities or non-thermal final energy distributions in molecules. Here, enabled by a machine-learning-based simulation framework, we compare isotropic and anisotropic models of electronic friction during
laser-driven hydrogen
evolution on the (111) facet of copper. While anisotropic electronic friction determines the rate of energy transfer into the adsorbate and the fluence dependence of desorption probabilities, final translational, vibrational and rotational energy distributions are mainly governed by the potential energy landscape at the barrier and insensitive to nonadiabatic effects.
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Physics and Society
Public transport in the 15-minute city
Zsófia Zádor, Gergő Pintér, Máté Mizsák et al. (+3 more)
The 15-minute city is a powerful planning concept to counter car-dependence by promoting active mobility to amenities and fostering inclusive urban environments. However, this policy has challenges in amenity-poor urban peripheries. Public transport remains underexplored in this discourse despite its role in distant access. Here, we propose a framework that incorporates public transport into the 15-minute city model using openly available data. By comparing Helsinki, Madrid, and Budapest, we demonstrate that
multimodal mobility substantially increases access to amenities and enhances socio-spatial integration within a 15-minute reach. Although urban periphery benefit significantly from radial or high-speed public transport lines in their social mixing potential, such lines alone do not improve their access to amenities. These findings underscore the need to optimize polycentric public transport networks that can improve inclusive urban accessibility and complement active mobility in polycentric cities.
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All authors Zsófia Zádor, Gergő Pintér, Máté Mizsák, Bence Kovács, Imre Felde, Balázs Lengyel
Computational Physics
Procela: Epistemic Governance in Mechanistic Simulations Under Structural Uncertainty
Kinson Vernet
Mechanistic simulations typically assume fixed ontologies: variables, causal relationships, and resolution policies are static. This assumption fails when the true causal structure is contested or unidentifiable-as in antimicrobial resistance (AMR) spread, where contact, environmental, and selection ontologies compete. We introduce Procela, a Python framework where variables act as epistemic authorities that maintain complete hypothesis
memory, mechanisms encode competing ontologies as causal units, and governance observes epistemic signals and mutates system
topology at runtime. This is the first framework where simulations test their own assumptions. We instantiate Procela for AMR in a hospital network with three competing families. Governance detects coverage decay, policy fragility, and runs structural probes. Results show 20.4% error reduction and 69% cumulative regret improvement over baseline. All experiments are reproducible with full auditability. Procela establishes a new paradigm: simulations that model not only the world but their own modeling process, enabling adaptation under structural uncertainty.
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Physics and Society
Managing the Mismatch: The Role of Flexibility on the Path to a Carbon-Neutral Energy System
Julian Geis, Michael Lindner and Tom Brown
A rapid expansion of system flexibility is essential to integrate increasing shares of renewable energy into future energy systems. However, flexibility needs and technology-specific contributions to flexibility remain poorly quantified in energy system modelling. Existing methods are not widely applied, leaving key questions unanswered: which flexibility technologies are critical for
climate neutrality, and what are the cost implications of alternative deployment strategies? To address this gap, we apply a correlation-based flexibility metric to a high-resolution, sector-coupled model of the German energy system, covering its transformation towards
climate neutrality. For our default scenario, we find that daily flexibility needs increase by a factor of 3.7 between 2025 and 2045, driven primarily by the expansion of
solar PV. By 2045, stationary batteries provide 38% of daily flexibility, while flexible electric vehicle charging contributes 30%. Systems with constrained flexibility increase system costs by 6.9%, electricity prices by 14 EUR/MWh and trigger 47% higher hydrogen and e-fuel imports compared to an unconstrained system in 2045. In contrast, scenarios with high shares of flexible electric vehicle charging, vehicle-to-grid, and industrial demand-side management achieve system cost reductions of 3.3%, while also reducing import dependence. Higher flexibility also reduces electricity price ranges, decreases average electricity prices by 3 EUR/MWh, and reduces backup capacity by 22% (22 GW). Overall, our results highlight the decisive role of specific flexibility technologies in achieving cost-efficient and energy-secure
climate-neutral energy systems, providing quantitative guidance for policy and investment decisions.
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