Applied Physics · Cross-listed from cond-mat.mtrl-sci
Battery open-circuit voltage is not purely chemical
Andrea Giudici, Christoph Pohl, Alberto Salvadori et al. (+3 more)
Open-
circuit-voltage (OCV) curves are commonly treated as intrinsic chemical properties of electrode materials. However, this view is incomplete. In ion-insertion batteries, OCV also depends on mechanical state and microstructure. Using finite-element simulations and asymptotic analysis, we show that particle swelling and external loads promote particle–particle contact that generates compressive stresses, shifting the inserted-ion chemical potential. The OCV correction is nonlinear, follows Hertzian contact scaling, and depends on particle arrangement. Identical materials can therefore exhibit different OCV curves in different electrode microstructures. Furthermore, in full
cells, electrodes are mechanically coupled through the common stack stress. Thus,
cell OCV is a chemo-mechanical property of the entire battery architecture, not chemistry alone.
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All authors Andrea Giudici, Christoph Pohl, Alberto Salvadori, Colin Please, Manuel Landstorfer, Jon Chapman
Biological Physics · Cross-listed from q-bio.PE
Architecture-dependent Effects of Trade-offs on Evolutionary Navigability and Epistasis
Nandita Chaturvedi
The structure of the genotype-phenotype map plays a central role in determining how populations move through fitness landscapes, yet less is known about how this structure interacts with environmental constraints and fitness trade-offs. Here, we study
evolution on a tunable multilayer genotype-phenotype map in which binary genotypes are transformed through successive feed-forward layers before being evaluated by phenotype-level fitness functions. We explicitly model the phenotype to fitness transformation in order to compare an emergent trade-off fitness with a no-trade-off control. We explore different map architecture as models of more and less complex genotype-phenotype relationships by tuning the genotype length and number of layers. We find that ruggedness and navigability have a complex, architecture-dependent relationship. Landscapes with few local maxima can still have low navigability for wide and shallow maps, and navigability is high even at mean values of ruggedness for wide and deep maps. Trade-offs increase navigability in wide and shallow maps, while their effect is muted in other architectures. The effect of trade-offs on epistasis depends on evolutionary history. While trade-offs change which mutational neighborhoods are sampled by
evolution, the background degree of epistatic interactions is set by map architecture. Finally, we use our framework to investigate micro-
evolution of high-fitness populations and show that temporal covariance in allele-frequency changes can arise from the internal structure of a rugged genotype-phenotype map, producing signatures that resemble short-term alternating selection.
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Computational Physics · Cross-listed from cond-mat.stat-mech
Decoherence-controlled collective criticality in a two-dimensional quantum Stag Hunt
Rajdeep Tah
Physical decoherence can preserve the microscopic strategic neutrality (i.e. zero effective field and equal potential of the two homogeneous strategic orientations) of a
quantum game while changing the thermodynamic regime of the corresponding interacting population. We demonstrate this for an Eisert–Wilkens–Lewenstein (EWL) Stag Hunt embedded as independent nearest neighbor encounters on a square
lattice. For the restricted strategies $\mathsf{Q}=i\mathbb{Z}$ and $\mathsf{D}=i\mathbb{Y}$, noisy two-player payoff
matrices are determined for phase damping, depolarization, and amplitude damping and mapped exactly to channel dependent Ising parameters $\mathfrak{J}(\Gamma,p)$ and $\mathfrak{H}(\Gamma,p)$. Phase damping and depolarization show the clearest contrast: they share the same microscopic neutrality branch $\mathfrak{H}=0$, while only depolarization suppresses the interaction as $(1-p)^2$. At $\beta=1$, this produces an exact depolarization-driven square-
lattice critical point at $p_{*}\approx 0.233460\ldots$, whereas phase damping remains in the ordered coexistence regime along the same neutrality branch. Monte Carlo finite size scaling is consistent with two-dimensional Ising criticality and distinguishes field driven coexistence below $p_{*}$ from a smooth crossover above it. Amplitude damping additionally reveals a strong dependence on channel placement: the post-strategy neutrality branch reaches $\Gamma=0$ at $p=1/3$ and then disappears. Resource negativity further shows that microscopic two-
qubit entanglement and collective interaction strength are distinct quantities. The resulting extended
lattice remains an ordinary classical Ising system.
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Accelerator Physics
Controlling a digital twin of the CEBAF injector from EPICS
Jude Doredant and Volker Ziemann
The Experimental and Instrumental Control System EPICS is used to control magnets and to read data from diagnostic devices in the CEBAF accelerator. We describe a prototype system where an EPICS installation, local on a laptop or Raspberry Pi, controls beam optics simulations. They can be running on the same computer or on a separate computer connected via the network. The prototype focuses on modeling and controlling the moderately complex injector beam line of CEBAF, which only comprises a few dozen magnets and beam monitors.
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Applied Physics · Cross-listed from quant-ph
Exponential speedup of polarization stabilization for long distance DWDM quantum networks
Jinyi Du, En Teng Lim, Xingjian Zhang et al. (+4 more)
Fibre-based
quantum networks distributing polarization
entanglement require a stable and uninterrupted transmission basis for reliable operation. Bright classical reference light enables rapid polarization feedback but can introduce noise into
quantum channels. Entangled-
photon-based feedback avoids this noise, but typically interrupts the target
entanglement channel during calibration and becomes prohibitively slow over long distances due to the product loss of fibre links. Here, we overcome both limitations by combining wavelength-bracketed probing with switch-enabled path decomposition. Spectrally adjacent entangled-
photon sidebands track the polarization response of the central distribution channel without interrupting its transmission, while optical switches and local reference fibres independently determine the signal and idler network transformations. Transferring the resulting compensation settings to the central channel eliminates calibration-induced downtime and changes the acquisition-time scaling from the product of the link losses to the sum of losses. We demonstrate the method on a 133 km fibre testbed and achieve continuous closed-loop stabilization for more than 24 hours without classical reference light. The decomposition of multi-link
quantum feedback into single-link measurements provides a scalable stabilization strategy for wavelength-multiplexed
quantum networks.
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All authors Jinyi Du, En Teng Lim, Xingjian Zhang, Hongwei Gao, George F.R. Chen, Dawn T. H. Tan, Alexander Ling
Computational Physics
Learning Spectrally Optimised Mesh-Free Discretisations
Lucas Gerken Starepravo, Henry Broadley, Steven Lind et al. (+1 more)
Numerical methods for partial differential equations (PDEs) discretise differential operators, ideally reproducing the action of the continuous operators across all wavenumbers permitted by a given discretisation. Spectral-type methods approach this ideal, but rely on structured grids or high-order meshes that are hard to generate for complex geometries. In contrast, mesh-free methods are geometrically flexible, yet how faithfully they reproduce the operator across resolved scales is strongly influenced by a heuristically chosen kernel, which selects one of many weight sets satisfying the same consistency conditions without regard to the resulting spectral response. To address this, we introduce Spectrally optimised Neural Discretisations (SpeND), a framework that learns the map from local stencil geometry to discretisation weights on unstructured point clouds. A projection layer constrains every predicted stencil to the affine set defined by the discrete moment conditions, so
polynomial consistency, and hence formal order of accuracy, holds exactly. Since consistency is enforced by the architecture, the weights can additionally be optimised for accuracy on a prescribed function space. Herein, we use
Fourier modes and target the exact differentiation response over a chosen wavenumber band, so training is unsupervised. The loss function is a design interface: changing how it weights wavenumbers yields operators with distinct accuracy profiles. The trained discrete differential operators are PDE-agnostic and are applied without retraining to the Poisson, Burgers and Navier–Stokes equations, to near-boundary stencils, and across resolutions. At the same order and resolution, SpeND matches or improves on established mesh-free discretisations, and has been shown to reduce the wall-clock time between $3-20\times$ to achieve equivalent error as the baselines.
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All authors Lucas Gerken Starepravo, Henry Broadley, Steven Lind, Jack R. C. King
Chemical Physics
Low-Temperature Transport in Li-Ion Battery EC/EMC/FEC Electrolytes: Molecular Dynamics and Machine-Learning Modeling
İpek Yenda Ç{\i}nar, Oguzhan Orhan, M. Oluş Özbek et al. (+1 more)
Low-temperature operation imposes severe limitations on lithium-ion transport in battery electrolytes, yet the coupled effects of solvent composition and fluorinated additives in the cold-temperature regime remain insufficiently resolved. Here, we combine classical molecular dynamics (MD) and machine learning (ML) to investigate 1 M LiPF$_6$ electrolytes containing ethylene carbonate (EC), ethyl methyl carbonate (EMC), and EC/EMC (3:7), with 0-10 mol% fluoroethylene carbonate (FEC), from 298 to 233 K. MD simulations quantify Li$^+$ self-
diffusion, Nernst-Einstein (NE) and Green-Kubo (GK) conductivities and local coordination, while Gaussian-process surrogates model conductivity across composition and temperature. Cooling produces a pronounced transport penalty, particularly in EMC-containing electrolytes, whose GK conductivity decreases by more than 98% at 233 K, compared with approximately 90% in EC-rich systems. Li$^+$ self-
diffusion activation energies are 0.49-0.54 eV for EMC-containing systems and 0.27-0.29 eV for EC-based systems. Within the EC family, 0-2 mol% FEC gives comparable cold-temperature transport, whereas 5-10 mol% FEC shows lower conductivity retention at the coldest simulated temperature. The analyzed coordination channels remain solvent dominated, while direct Li$^+$-FEC coordination is not quantified in the present RDF set.The Gaussian-process surrogates achieve composition-disjoint cross-validated RMSE values of 0.56 and 0.57 mS cm$^{-1}$ for NE and GK conductivity. Within the simulated
liquid-state trajectories, temperature and host-solvent composition dominate the bulk-transport response, with FEC acting as a secondary modifier.
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All authors İpek Yenda Ç{\i}nar, Oguzhan Orhan, M. Oluş Özbek, Şener Özönder
Plasma Physics
Global Gyrokinetic Simulations of Electromagnetic Turbulence in STEP
Daniel Kennedy, Facundo Sheffield, Tobias Görler et al. (+6 more)
This paper presents gradient-driven global electromagnetic gyrokinetic simulations for a conceptual burning flat-top operating point of STEP [1], STEP-EC-HD, and investigates how non-local effects influence the nonlinear saturation and transport of the electromagnetic
turbulence at finite ${\beta}$. Local gyrokinetic simulations have shown that including ${\delta}B_{\parallel}$ is essential for the dominant hybrid kinetic ballooning modes, or hKBMs, to be unstable in STEP [2]. Using the long-wavelength ${\delta}B_{\parallel}$ solver [3] implemented in GENE [4], this work demonstrates that the linear mode spectrum can be accurately captured in global geometry, which results in good agreement with an ensemble of local flux-tube simulations. The global framework reproduces the hKBMs identified in [5], while microtearing modes remain challenging to resolve due to their shorter radial scales. Nonlinear simulations reveal clear evidence of an electromagnetic transition to states with extremely large heat fluxes, consistent with local simulations and with the predicted loss of zonal-flow regulation for this proposed operating point [6]. These findings establish the capability of global gyrokinetics to capture finite-${\beta}$ dynamics in STEP-like
plasmas and motivate future work to identify the conditions governing this transition.
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All authors Daniel Kennedy, Facundo Sheffield, Tobias Görler, Colin Roach, Maurizio Giacomin, Arka Bokshi, David Dickinson, Harry Dudding, Bhavin Patel
Chemical Physics · Cross-listed from cond-mat.soft
Relating solute interactions to interfacial properties
Varun Mandalaparthy, Benjamin M. Curlee and William G. Noid
Liquid interfaces are both ubiquitous and also critically important for many commercial products, modern technologies, biological processes, and environmental phenomena. The properties of these interfaces can depend quite sensitively upon the composition of the bulk
liquid phase. In this work, we develop a dilute solution theory (DST) for the influence of dilute cosolutes upon the interface between coexisting
liquid and vapor phases. We employ a grand canonical perturbation theory to rigorously relate the interfacial free energy to the concentration of the
liquid solution. We leverage a corresponding Gibbs ensemble to treat
liquid-vapor coexistence and to eliminate the contribution of the bulk phases from this free energy. We express the coefficients of the resulting expansion in terms of microscopic partition functions. By treating solute-solute interactions to lowest order, we distinguish between the intrinsic and effective interfacial preferences of solutes. While the former reflects only solute-solvent interactions, the latter depends upon the solution composition and reflects the influence of solute-solute interactions. We assess this DST with molecular dynamics simulations of binary and ternary mixtures of Lennard-Jones spheres. These simulations demonstrate that DST accurately models the interfacial properties of these systems up to relatively high concentrations. Moreover, the simulations illustrate the impact of attractive solute-solute interactions in converting weak intrinsic surfactants into weak effective depletants.
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Chemical Physics
HiPoly: a hierarchical polymer-native AI framework for property prediction and generative design
Ge Sun, Gervasio Zaldivar, Yuan Tian et al. (+5 more)
Polymeric materials are central to modern technologies, with applications ranging from energy to health and transportation. Although AI has made significant advances in materials discovery, the hierarchical structure of
polymers across multiple length scales makes them inherently difficult to represent in a unified and physically meaningful way. Here we introduce HiPoly, a
polymer-native AI framework that processes complete
polymer descriptions through a three-level hierarchical graph architecture built on the G2RINS representation. HiPoly encodes
stochastic inter-monomer connectivity, composition, and molecular weight directly within its architecture, using physically motivated design principles that mirror the multi-scale nature of polymeric systems. The framework establishes an end-to-end AI-driven workflow from experimental formulation data to property prediction, generative molecular design, and physics-based validation through molecular simulations, all unified by a single
polymer representation. We demonstrate state-of-the-art prediction accuracy for thermophysical properties of multi-component
polymer systems, with ablation studies confirming that each hierarchical design choice contributes independently to model performance. As an example, the generative design pathway is applied here to the discovery of sustainable alternatives to persistent fluorinated
polymers, where it is possible to identify and independently validate PFAS-free candidates with target surface-energy properties. This work demonstrates how
polymer-native AI can accelerate discovery by linking representation, prediction, and design across complex
polymer chemistries.
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All authors Ge Sun, Gervasio Zaldivar, Yuan Tian, Gustavo Perez Lemus, Juhae Park, Daryna Safarian, Ming Han, Juan J. de Pablo
Optics
Optical Reservoir Computing with Structural Nonlinearity for Forecasting Chaotic Time Series
Leandro R. Venâncio, Jonathan Dong, Mickael Mounaix et al. (+1 more)
Optical computing offers a promising route to high-speed, energy-efficient information processing. However, implementing nonlinear operations typically requires strong light-matter interactions. Here, we introduce structural nonlinearity into an optical reservoir computing architecture, using only linear components. A digital micromirror device acts as a reconfigurable scattering potential, while the propagation of light through a scattering medium provides the high-dimensional mode mixing. By enforcing a second interaction with the wavefront shaper, we obtain a quadratic mapping of the input within the reservoir. A single experimental apparatus simultaneously implements conventional and structurally nonlinear reservoir architectures, enabling a direct comparison on
forecasting of the chaotic Mackey-Glass time series. We demonstrate that the structurally nonlinear reservoir improves short-term prediction accuracy and better preserves the long-term dynamics of the chaotic system, demonstrating the potential of structural nonlinearity for low-power optical computing.
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All authors Leandro R. Venâncio, Jonathan Dong, Mickael Mounaix, Jacopo Bertolotti
Optics
Random-mapped intensity optical neural network: all-optical two-layer computing for multimodal optical-field inference
Gi-Hyun Go, Doeon Lee, Gookho Song et al. (+1 more)
Free-space optical neural networks offer distinct advantages for computational imaging and machine
vision because they can compute directly on incident optical fields. However, conventional ONNs composed of cascaded linear optical components are bound to a general linear input-output relation with square-law detection between the input field $\mathbf{x}$ and output score $\mathbf{y}$, $\mathbf{y}=|\mathbf{T}\mathbf{x}|^2$, where at best every complex-valued element of the transmission
matrix $\mathbf{T}$ is trainable. This restricts each output score to a quadratic form $\mathbf{x}^\dagger\mathbf{A}\mathbf{x}$ with rank-one decision
matrix $\mathbf{A}=\mathbf{t}^\dagger\mathbf{t}$. Here, we present a random-mapped intensity optical neural network (RMI-ONN) as an all-optical two-layer computational network that lifts this rank-one limit. We numerically demonstrate that a high-dimensional feature projection by a disordered medium, a programmable nonnegative intensity mask, and segmented spatial power summation together can surpass the rank-one ceiling through the expressivity of higher-rank quadratic decision boundaries. Furthermore, exploiting the vectorial coherent wave-mixing nature of the disordered medium, we experimentally validate
multimodal classification of amplitude, phase, and polarization on MNIST, Fashion-MNIST, and Quick Draw with the RMI-ONN, under a single optical configuration across all encoding domains. These results provide a practical and conceptual basis for scalable direct-field optical processors capable of exploiting amplitude, phase, and polarization information within a unified intensity-based inference framework.
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All authors Gi-Hyun Go, Doeon Lee, Gookho Song, Mooseok Jang
Biological Physics
A viscoelastic theory for ultrasound-induced intracellular streaming
Niels Gieseler, Falko Ziebert and Ulrich S. Schwarz
Ultrasound is increasingly used to control biological
cells, but its multiple physical effects, including radiation force, streaming, heating, and cavitation, require theoretical frameworks that can quantify their relative strengths. Here we develop a semi-analytical model to predict flow patterns and energy distributions of ultrasound-induced intracellular streaming.
Cells are modeled as viscoelastic droplets immersed in a fluid with different viscoelastic properties. For this geometry, the momentum equation with an Oldroyd-B constitutive law is solved using a perturbation expansion commonly applied in acoustofluidics. The resulting equations for the different orders of the expansion are solved using partial wave expansion and explicit integration. We investigate our model for a range of parameters which is relevant both for synthetic
polymer and for
protein solutions. We find a series of flow reversals that we can connect to the distribution of energy into the different modes. We also consider density and compressibility contrasts, which shift these transitions and introduce new ones. Finally, we discuss the potential biological relevance of our mathematical results for cellular sensing and signaling.
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Computational Physics
RBMD 2.0: Random batch molecular dynamics package for large-scale simulations on multi-GPU architectures
Qi Zhou, Yongfa Guo, Jincheng Zhong et al. (+3 more)
Large-scale molecular dynamics simulations of particle systems on multi-GPU architectures are often constrained by the computational and communication costs of nonbonded force evaluation. We present RBMD 2.0, a major new release of the random batch molecular dynamics package designed for cross-node multi-GPU simulations of large-scale systems. It combines the improved random batch Ewald method with three-dimensional domain decomposition and ghost-particle communication to accelerate multi-GPU nonbonded force evaluation, while the DTK CUDA framework facilitates portability across heterogeneous accelerator architectures. Numerical experiments on multiple
benchmark systems demonstrate both the accuracy and efficiency of simulations with RBMD 2.0. For simulations involving up to hundreds of millions of particles across multiple accelerator devices, one achieves speedups ranging from severalfold to approximately two orders of magnitude in nonbonded force evaluation while exhibiting over $97.5\%$ weak-scaling behavior. These results demonstrate the promising nature of RBMD 2.0 as a computational engine for future exascale molecular dynamics simulations.
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All authors Qi Zhou, Yongfa Guo, Jincheng Zhong, Shou-Hang Bo, Teng Zhao, Zhenli Xu
Applied Physics · Cross-listed from cond-mat.other
Topological Lithography via External Field: Creating Topological States Anywhere Beyond the Edge
Haoran Nie, Chaoran Jiang, Xiangying Shen et al. (+1 more)
Topological
insulators (TIs), recognized for their robust boundary states and unconventional phase transitions, have emerged as one of the most impactful discoveries in recent decades, attracting considerable interest across diverse fields. However, conventional TIs require topological contrasts between adjacent bulk regions, typically achieved by distinct
symmetries, which limits their flexibility and broader applicability. In this work, we introduce a "lithography" approach to inducing topological states by applying external fields in time-reversal-symmetric systems. These states transcend the conventional bulk
topology design paradigm and offer exceptional tunability: they can exist at
geometric edges, within the bulk, or even be induced remotely. Because the external field is highly controllable, the induced states are programmable, reconfigurable, and can be easily tailored into desirable patterns. Theoretically, we demonstrate that the external field modifies the Jackiw-Rebbi mechanism, inducing a real-space topological transition characterized by a local topological marker (LTM). We further establish an extended valley bulk-edge correspondence, which explains both the conventional scenario and our findings. Our results, validated across mechanical, electronic, and acoustic platforms, highlight the broad applicability of this approach to various systems. This work not only advances the theory of
topology but also enhances the diversity, tunability, and practical implementation of topological states and materials.
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All authors Haoran Nie, Chaoran Jiang, Xiangying Shen, Lei Xu
Chemical Physics · Cross-listed from cond-mat.soft
Liquid-liquid phase transitions in dipolar liquids. Insights into Supercooled Water
Maria Grazia Izzo
Dipolar
liquids combine two coupled degrees of freedom, translational and dipolar. Intriguingly, these two sectors can reside in distinct thermodynamic states, with the state of one sector possibly favoring a specific state of the other. The onset of ferroelectric order in dipolar
liquids is an example of this mutual stabilization. Since this coupling is often encoded in interaction potentials, projecting out one sector to derive an effective interaction for the other can uncover the microscopic mechanism underlying this phenomenon. A coarse-grained theory in which the distance between nearest-neighbor particles depends on their dipolar interaction through a density-dependent mechanical compliance shows that a ferroelectric transition can trigger a
liquid-
liquid transition. It also predicts a first-order
liquid-
liquid transition in the paraelectric phase that can in turn induce ferroelectric ordering. The anisotropic dipolar-dependent soft-core interaction is shown to lead to an effective Jagla-like isotropic two-length-scale interaction, known to support
liquid-
liquid phase transitions. Here, however, the two-length-scale pattern depends on density and dipolar configuration, becoming sensitive to dipolar order. Analysis of supercooled TIP4P/Ice water numerical simulations shows that first-coordination-shell features of pair correlation functions are sensitive to dipolar interaction, supporting the coarse-grained theory foundations. Comparison of low- and high-density
liquid water reveals enhanced spatial anisotropy of the first coordination shell in the low-density
liquid, with increased effective excluded volume, showing that the
liquid-
liquid transition involves structural changes within the first shell, beyond reorganization of the interstitial region and tetrahedral order. These findings point to a role for dipolar interactions in supercooled water
liquid-
liquid phase transition.
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Fluid Dynamics
Mapping-based exact-integral formulation of skin-friction transformations for zero-pressure-gradient compressible turbulent boundary layers
Xuke Zhu, Xiaoshuo Yang, Yongchao Ji et al. (+2 more)
A long-standing route to efficient surface-drag prediction in zero-pressure-gradient compressible turbulent boundary layers is to map the skin-friction coefficient $C_f$ and momentum-thickness Reynolds number $Re_\theta$ onto their `incompressible' counterparts. Reassessment against an extensive DNS database shows that existing formulations do not consistently recover the reference incompressible skin-friction behaviour, even when transformed data exhibit improved collapse. We define the mapped `incompressible' state as a constant-property counterpart of the physical compressible boundary layer and derive the transformation factors from prescribed mean-velocity and wall-normal-coordinate mappings. This definition-first approach links skin-friction scaling to the full-layer accuracy of the underlying velocity transformation and exposes inherited outer-layer errors. Van Driest's theory is recast in a finite-Re exact-integral form, with the classical vD I and II transformations recovered as leading-order asymptotic reductions. Their limitations at finite Reynolds numbers are quantified, and the historical success of vD II is traced to a fortuitous cancellation of truncation errors. The exact-integral formulation then yields modified transformations assessed through a priori scaling and standalone a posteriori prediction of $C_f$ from prescribed macroscopic and wall-thermal inputs. The VIPL-based modified transformation gives the best overall performance. Across $0.30 \leq M_\infty \leq 13.64$ and $-0.55 \leq \varTheta \leq 2.85$, its prediction errors remain below $11\%$, with a mean error of $3.07\%$. Overall, the analysis places skin-friction transformations on a mapping-based exact-integral footing, relating them directly to prescribed mean-flow mappings while avoiding the leading-order asymptotic truncations that limit classical van Driest theory at finite Reynolds numbers.
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All authors Xuke Zhu, Xiaoshuo Yang, Yongchao Ji, Shiyi Chen, Zhenhua Xia
Optics · Cross-listed from cond-mat.quant-gas
Dynamical stabilisation of a quantum fluid using a single topological defect
Deborah Capecchi, Paolo Comaron, Antonio Gianfrate et al. (+5 more)
The size and shape of a
quantum fluid in
equilibrium is strongly influenced by the inter-particle interactions. In the attractive interaction regime, atomic
quantum fluids ultimately collapse in a violent process that expels most of the particles from the macroscopically occupied state. Here, we use a
quantum fluid of light in propagating geometry as an analogue to a two-dimensional Bose-Einstein condensate (BEC) with large attractive interactions to show that non-trivial
topology significantly alters the dynamical behaviour of the collapse, enhancing the BEC stability and delaying the collapse time by an order of magnitude. We measure direct experimental signatures of
topology affecting
quantum hydrodynamics, unveiling the inherent competition between attractive nonlinearities, that lead to the collapse, and the preservation of topological charge from a multi-charged
vortex. We fully characterise the collapse process in coordinate space and the eventual `solitonification' of the system and connect it to the mode structure of the excitation spectrum.
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All authors Deborah Capecchi, Paolo Comaron, Antonio Gianfrate, Milena De Giorgi, Dario Ballarini, Daniele Sanvitto, Franco Dalfovo, Dimitrios Trypogeorgos
Medical Physics
The 2024 MRSI Data Processing and Quantification Challenge Synthetic Dataset
John T. LaMaster, Julian P. Merkofer, Dennis M. J. van de Sande et al. (+3 more)
Synthetic data is central to
magnetic resonance spectroscopy method development because they provide ground truths for software validation, reproducible benchmarking, and machine- and deep-learning training. In MRSI, synthetic data must capture spatially varying anatomy, field inhomogeneity, nuisance signals, and measurement effects. The 2024 MRSI Data Processing and Quantification Challenge Synthetic
Dataset is a simulated 3T
brain FID-MRSI resource with ground-truth metabolite maps developed as a controlled testbed for MRSI processing and quantification methods. Subject-specific simulations used anatomical images and field maps from Human Connectome Project subjects. Tissue masks,
quantum-mechanically simulated metabolite basis functions, in vivo-derived macromolecular components, Bloch-simulated post-WET residual water, registered in vivo lipid signals, spectral baseline, $B_0$-dependent frequency shifts, Voigt lineshape variations, and complex Gaussian noise were combined in a forward model. Water and lipid signals were synthesized on a high-resolution grid and
Fourier-truncated to the final echo-planar spectroscopic imaging grid to model the finite spatial point spread function. This resource has 24 training and 8 testing
datasets containing contaminated FID-MRSI data, anatomical images, $B_0$ maps, metadata, and ground-truth metabolite and component signals. Forward-model parameters are documented, including tissue-specific metabolite concentrations and relaxation times, macromolecular amplitude ratios, the water model, noise, and field-inhomogeneity ranges. This synthetic
benchmark supports development and comparison of MRSI processing, nuisance-signal removal, and metabolite-quantification methods, while enabling method evaluation. It illustrates how characterized synthetic data can support rigorous evaluation when ground truth is difficult or impossible to obtain.
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All authors John T. LaMaster, Julian P. Merkofer, Dennis M. J. van de Sande, Brian J. Soher, Bernhard Strasser, Chao Ma
Biological Physics · Cross-listed from cond-mat.soft
Pure FENE Bond Potential for Soft Matter and Biological Simulations: Theory, HOOMD-blue Implementation, and Applications to Polymer, Colloidal, and Membrane Systems
Anirban Polley
The finitely extensible nonlinear elastic (FENE) potential is widely used as a bonded interaction in coarse-grained simulations of
polymers, soft matter, colloids, and biological systems. In the classical Kremer–Grest framework, FENE bonding is combined with a short-range Weeks–Chandler–Andersen (WCA) interaction to provide finite bond extensibility together with excluded-volume repulsion. Although this combination is highly successful, it intrinsically couples bonded elasticity to the nonbonded interaction, limiting the ability to independently control these two contributions. Here, we introduce a standalone FENE bond potential in HOOMD-blue in which finite bond extensibility is implemented independently of the choice of nonbonded interaction. This formulation allows the same FENE bond potential to be combined with WCA, Lennard–Jones, or other pair interactions without modifying the bonded interaction itself. We demonstrate the utility of the standalone formulation in coarse-grained
polymer chains, colloidal networks, and mesh-based biological membrane models. Across these systems, Pure FENE bonding without short-range excluded-volume stabilization produces pronounced structural contraction, whereas the addition of WCA repulsion suppresses this collapse and preserves finite, spatially extended structures. These results demonstrate that separating finite bond extensibility from steric interactions provides independent control over local bond mechanics and collective structural organization. The standalone FENE formulation therefore provides a modular framework for coarse-grained simulations in which molecular connectivity and nonbonded interactions represent distinct physical mechanisms.
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Fluid Dynamics
Vortex promoters in MHD duct flow
Andreu Queralt, Dmitry Krasnov, Yuri Kolesnikov et al. (+1 more)
We use 3D direct numerical simulations to study the effects of
vortex promoters in
liquid metal duct flow to sustain Q2D states which are formed in the presence of strong
magnetic fields, such as those present in cooling blankets of fusion reactors. Both for electrically insulating and conducting walls. In case of insulating walls, disturbances are found to be sustained. For conducting walls, the disturbances may be extinguished immediately and replaced by a Walker- or Hunt-type flow with its own jet-detachment instability. Furthermore, we add heat transfer by imposing constant heat flux at the Shercliff walls. We classify and compare possible configurations with respect to their turbulent transport properties. For conducting ducts, no additional effect is observed. For insulating ducts in horizontal position, we observe a small effect. For vertical ducts, the buoyancy forces have a significant impact due to buoyancy-driven instabilities, which produce intermittent fluctuations. The analysis of the turbulent kinetic energy (TKE) and the Nusselt number show that flows with the largest TKE may not have the best heat transfer performance. This is caused by side jets removing heat faster than mixing the bulk flow. The buoyancy force and wall conductance ratio are found to play a key role in determining the flow structure. Part of our work is a parametric study at fixed Reynolds, Hartmann and Prandtl numbers, which allows us eventually to compose a phase diagram showcasing the different flow regimes.
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All authors Andreu Queralt, Dmitry Krasnov, Yuri Kolesnikov, Jörg Schumacher
Atmospheric and Oceanic Physics · Cross-listed from math-ph
Ruelle–Pollicott Theory for Metastable Systems: A Unified Framework for Tipping Transitions
Mickaël D. Chekroun and Valerio Lucarini
Tipping points—abrupt, potentially irreversible reorganizations of a system's statistical state—are commonly anticipated through critical slowing down: recovery slows, autocorrelation and variance rise, and spectra redden. This paradigm is powerful near simple
equilibrium bifurcations but is not a general theory for
stochastic, multistable, or metastable systems. We develop such a theory from the Ruelle–Pollicott (RP) spectrum of Kolmogorov generators of hypoelliptic Itô
diffusions. Resolving the sensitivity of invariant statistics on RP spectral blocks shows that each contribution factorizes into a spectral denominator and a residue coupling the block to both the observable and perturbation direction. Small denominators permit large responses; residues produce them. Thus a closing RP gap is not sufficient for an early warning, while growing residues can generate the classical signature with no gap closure. An early-warning signal is therefore a property of a triple: RP block, observable, and perturbation direction. We demonstrate this on a
stochastic non-normal system whose RP spectrum is exactly frozen, yet classical indicators become more alarming than during genuine gap closure. The RP decomposition attributes this to residue growth and yields an index $\mathcal{N}(f)$ satisfying $\mathcal{N}(f)\leq 1$ for reversible dynamics; hence $\mathcal{N}(f)>1$ certifies residue-driven amplification. For metastable systems, one killed problem yields two complementary spectral objects: the Doob $Q$-process isolates in-well recovery, while escape clocks and committor-weighted destination probabilities govern interwell transitions. In a one-dimensional fold, these scale as $(\epsilon_c-\epsilon)^{1/2}$ and $(\epsilon_c-\epsilon)^{3/2}$, separating bifurcation-induced from noise-induced tipping. Doob drift also connects to optimal Girsanov sampling.
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Optics
Spatially-resolved multiphoton photoemission from a lateral transition metal dichalcogenide heterostructure
Lina Hansen, Paul Martin, Sai Shradha et al. (+7 more)
Transition metal dichalcogenides (TMDs) in their monolayer form offer a premier platform for next-generation optoelectronics, particularly through the local manipulation of their robust excitonic states using nanoscale electric fields. These localized states can be dynamically controlled through spatial structuring as well as through ultrafast field modulations driven by tailored optical pulses. Characterizing the resulting rapid, nanoscale charge carrier dynamics requires a technique with exceptional spatial and temporal resolution. Here, we report on the spatio-temporally resolved investigation of ground state and excited state photoemission from a lateral
heterostructure built of monolayers of WSe$_2$ and MoSe$_2$ using few-cycle light pulses with a
photon energy of 0.62 eV. We utilize photoemission electron microscopy to spatially resolve the highly nonlinear photoemission from the monolayer structure with few tens of nanometer resolution. By varying the
laser pulse energy, we extract the nonlinearity of the photoemission process and thus the dynamic binding energy of the photoelectrons before and after optical excitation with high spatial and temporal resolution.
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All authors Lina Hansen, Paul Martin, Sai Shradha, Julian Picker, Arvid Klösgen, Kerstin Harland, Katrin Meier, Andrey Turchanin, Bernhard Urbaszek, Jan Vogelsang
Optics
Exceptional Topological Signatures of Non-Hermitian Photonic Hopf-Link Braids
Samit Kumar Gupta
Non-Hermitian physics endows the non-Abelian systems with exceptional
topology characterized by non-commutative braid patterns. Interplay of distinct competing sources of non-Hermiticity may induce novel topological effects. Here, we provide a generalized Hatano-Nelson model with higher-order nonreciprocal hoppings, non-Abelian gauge fields, and staggered gain-loss processes showing the exceptional topological structure of the
Hopf-link braids that undergoes a EP-mediated topological phase transition. We demonstrate that mixing multiple nonreciprocal channels drives the system into highly intricate, nested complex energy
Hopf-link braids and expands the topological landscape up to higher-order braiding sectors. Furthermore, utilizing biorthogonal eigenvector tracking, we map the structural
evolution of the exceptional phase boundaries via the maximum Petermann factor in the phase angle parameter planes. We show that the gain-loss non-Hermiticity drives a topological crossover where the extended exceptional contours constrict into isolated regimes. The demonstration of EP-mediated topological phase transition of
Hopf-link braids and the associated rich exceptional phase portraits may offer new physical insights with promising applications in robust, fault-tolerant communication channels and
quantum computing platforms.
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Atomic Physics · Cross-listed from cond-mat.quant-gas
Magnetic-Field-Calibration-Free Determination of the Hyperfine Constant $A$ in Ultracold Fermi gases of $^{40}$K
Yajing Yang, Biao Shan, Yuhang Zhao et al. (+8 more)
Hyperfine constant $A$ is a key parameter of the hyperfine structure and underpins precision spectroscopy and metrology. In this Letter, we develop a
magnetic-field-calibration-free method for determining the ground-state hyperfine constant $A$ in an ultracold $^{40}$K
Fermi gas by utilizing a pair of magnetically insensitive ("clock") transitions. This overcomes the stringent
magnetic-field calibration requirements of conventional methods. We measure the transition frequency between these two magnetically insensitive transitions with Hz-level resolution over a range of
magnetic fields, and obtain the ground-state hyperfine constant $A = -h\times 285.730536(2)\,\mathrm{MHz}$, corresponding to an absolute uncertainty of about $2\,\mathrm{Hz}$. Our value reduces the uncertainty by nearly three orders of magnitude compared with previous determinations, providing a substantially improved reference for high-precision spectroscopy and metrology with $^{40}$K.
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All authors Yajing Yang, Biao Shan, Yuhang Zhao, Jiahui Shen, Zhuxiong Ye, Liangchao Chen, Zengming Meng, Pengjun Wang, Wei Han, Jing Zhang, Lianghui Huang
Optics
Comparative study of noise-like pulse emission from Mamyshev oscillator and conventional passively mode-locked fiber laser
Oumaima Ougrige, Florent Bessin and François Sanchez
We perform an in-depth comparison of noise-like pulse emission from Mamyshev oscillator and mode-locking through nonlinear polarization rotation (NPR) in fiber
lasers. NLP's temporal and spectral characteristics are analyzed in both normal and anomalous dispersion regimes. The output coupling coefficient is modified to optimize the energy of the output pulses. It is demonstrated that the pulse energy is systematically higher in NPR-based mode-locking fiber
lasers than in Mamyshev oscillators. This is due to the filtering effect in the Mamyshev oscillator which rejects ultrashort pulses whose energy is insufficient to successfully pass through the two shifted optical filters.
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Atmospheric and Oceanic Physics
Did recent sea surface temperature warming reinforce the extreme East Asian summer monsoon precipitation in 2020?
Taeho Mun, Haerin Park, Dong-Hyun Cha et al. (+3 more)
We analyzed the possible effects of recent sea surface temperature (SST) warming on the extraordinary East Asian summer monsoon (EASM) precipitation in 2020 summer. The dynamic and thermodynamic impacts of SST are examined by conducting regional
climate model experiments with observed SST and cold SST where the 22-year SST trend is removed. In the presence of warm SST, precipitation increases in low latitudes but decreases in the EASM region. This dipolar precipitation change pattern opposes the precipitation anomalies in 2020 summer, indicating that the extraordinary 2020 EASM precipitation is not likely driven by recent SST warming. The warm SST suppresses the western North Pacific subtropical high expansion and weakens the southwesterly from the South China Sea toward the EASM region. In terms of large-scale atmospheric circulations, SST-induced wind changes strengthen the local Walker circulation in the South China Sea and the Philippines and the local Hadley circulation across the EASM region. These support the reduced EASM rainfall in the control experiment compared to the cold SST experiment and imply that the precipitation reduction by dynamical effects could exceed the precipitation increase by thermodynamic effects in the EASM region under warm SST.
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All authors Taeho Mun, Haerin Park, Dong-Hyun Cha, Chang-Keun Song, Seung-Ki Min, Seok-Woo Son
Applied Physics · Cross-listed from cond-mat.mtrl-sci
All-dry processing of 3C-SiC nanomechanical string resonators for extreme aspect ratios and high intrinsic quality factor
Felix David, Philipp Bredol, Yannick S. Klaß et al. (+1 more)
Conventional fabrication of suspended nanomechanical resonators typically relies on wet-chemical process steps and critical point drying, which can compromise sample yield and cleanliness. Here, we present an all-dry fabrication process for strongly stressed 3C-SiC nanomechanical string resonators that entirely avoids wet-chemical etching and cleaning. Using a negative-tone electron-beam resist as an etch mask and a three-step reactive-ion etching process for both structuring and release, we achieve high fabrication yield, clean suspended structures, and extreme aspect ratios of 8.500. We perform full mechanical characterization of the resulting doubly-clamped nanostring resonators, and establish a
benchmark intrinsic quality factor for dissipation-diluted 3C-SiC of Qintr = 4.200.
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All authors Felix David, Philipp Bredol, Yannick S. Klaß, Eva M. Weig
Atomic and Molecular Clusters · Cross-listed from cond-mat.mtrl-sci
A Wannier-first approach for extended chiral systems
Yashpal Singh, Juan E. Peralta, Koblar A. Jackson et al. (+1 more)
We present a real-space formulation of DFT for extended systems in which localized Wannier-like functions are constructed directly from localized Gaussian basis functions without explicitly computing canonical Bloch-like states during the self-consistent cycle. Building on the formalism of Pederson and Lin [Phys. Rev. B 35, 2273 (1987)], a variational set of Wannier-like functions is generated self-consistently within a finite Wannier domain and used to construct the charge density, electrostatic potential, and per
cell total energy of the extended system. The occupied space can be determined entirely from the Wannier-like functions. Electronic band structures can be recovered in a post-processing step by solving the full
Hamiltonian in a Bloch-like basis constructed from Gaussian orbitals. A key feature of the method is that it can incorporate combined translation–rotation, or screw,
symmetries, enabling efficient simulations of
chiral and helical systems with finite twist angles at essentially the same computational cost as systems described by pure translational
symmetry. The approach is validated through calculations on linear and twisted $\mathrm{{-}C{\equiv}C{-}}$ and $\mathrm{{-}Li{-}F{-}}$ chains, as well as
graphene, where total energies and band structures show excellent agreement with reference periodic calculations. To illustrate the ability of the method to treat three-dimensional systems, it is further applied to AA graphite, in which carbon atoms in adjacent
graphene layers are aligned directly above one another, as well as helically stacked AA graphite structures. The Wannier-first framework provides a practical route for treating extended systems with nontrivial translational, rotational, and screw
symmetries, and provides a natural foundation for the implementation of orbital-dependent functionals such as the Perdew–Zunger self-interaction correction.
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All authors Yashpal Singh, Juan E. Peralta, Koblar A. Jackson, Mark R. Pederson
Fluid Dynamics
Numerical Investigation of Mach 10 Kerosene-Fueled Oblique Detonation Waves at Different Flight Altitudes
Yunfeng Liu
The initiation and propagation mechanisms of kerosene-fueled oblique detonation waves are key issues in the development of oblique detonation wave engines. In this study, numerical simulations of kerosene-fueled oblique detonation at a flight Mach number of 10 were conducted using the two-dimensional conservative Euler equations and a second-order two-step global chemical reaction model. The objective was to compare wedge-induced initiation with bump-forced initiation. The results show that, at different flight altitudes, the oblique detonation flow field follows the h̊o}L binary scaling law. Wedge-induced initiation requires highly precise matching of parameters such as the inlet-exit conditions, wedge angle and length, and equivalence ratio. In contrast, bump-forced initiation exploits the high total temperature and total pressure at the stagnation point and therefore does not require precise matching of these parameters. Therefore, the bump-forced initiation method provides reliable oblique detonation initiation and a stable oblique detonation flow field.
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