Fluid Dynamics · Cross-listed from cs.LG
Staying on the Attractor: Supervising Neural Surrogates of 3D Turbulence Where They Leave It
Yilong Dai, Shaswata Mitra, Raj Patel et al. (+7 more)
Neural surrogates are trained to predict 3D turbulent flows in place of direct numerical simulation (DNS). For chaotic flows, the goal is short-term pointwise accuracy followed by long-term physical and statistical fidelity. However, small prediction errors can carry a surrogate away from the flow's attractor. Off-attractor states are poorly represented in training data, leaving their
evolution weakly constrained. The learned dynamics can then amplify deviations and lead to blow-up, freezing, or statistical drift. We propose off-attractor supervision (OAS) to supervise neural surrogates where they leave the attractor. OAS teaches the model how the true Navier-Stokes dynamics would evolve from these states. Each selected state is paired with its own future computed by DNS. Three generators select a few hundred states for relabeling. The first collects states from the surrogate's own rollouts. The second uses surrogate attacks to target freezing, excessive amplification, and violations of incompressibility and energy balance. The third perturbs training states along an amplified direction and a strongly damped random direction of the dynamics. All attacks run on the surrogate alone, and DNS relabeling is performed offline once per selected state. Experiments on $128^3$
turbulence show that OAS increases the median time to failure from 21 to 721 steps. The compared baselines achieve medians of at most 110 steps, and the advantage holds across training seeds. OAS also achieves the lowest pointwise error at step 15 and the best long-horizon statistics among the compared methods. OAS integrates physical models into neural simulation by extending supervision from fixed reference trajectories to states where the surrogate is likely to fail. This principle can guide the development of more reliable scientific surrogates when deployment takes models beyond the coverage of their training data.
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All authors Yilong Dai, Shaswata Mitra, Raj Patel, Yiming Sun, Shengyu Chen, Jiaqi Gong, Sudip Mittal, Shahram Rahimi, Xiaowei Jia, Runlong Yu
Physics and Society · Cross-listed from cond-mat.dis-nn
Trimers, pairs and localisation on disordered random graphs
Alexei Vazquez
Higher-order networks take group interactions as given. I ask what happens when a group interaction is made by pairwise dynamics on a graph, and follow it through the transition that decides whether it matters at large scale, Anderson localisation. An emergent hyperedge is a $k$-body bound state of a
Hamiltonian whose terms live on the vertices and edges of the graph, Borromean when none of its $(k-1)$-body faces is bound, detected on a finite graph by a $k$-fold coincidence that survives the thermodynamic limit while the $(k-1)$-fold ones vanish. Sparse random graphs produce one from the simplest pairwise dynamics: three distinguishable particles with on-site attraction $U$ and hopping $t$ bind into a trimer before any pair binds. The thresholds are obtained on the Bethe
lattice, in closed form for the pair, in both sectors that an expander graph has and a
lattice lacks, the one a condensate sees and the one a Fermi
liquid sees. On a disordered graph the emergent hyperedges nucleate on rare deep sites and localise before their parts: the compact trimer, with a narrow band and a threefold sensitivity to site energies, undergoes the Anderson transition at a disorder of $1.6t$, against $17t$ for a single particle and $4t$ for a pair, and the Fermi
liquid of trimers is a glass above a line between $1.5t$ and $1.7t$, where a
liquid of single particles at the same density needs $15t$ to $16t$. The transition is the single-particle cavity transition with the composite's hopping and effective disorder. A group interaction made by pairwise dynamics is an order of magnitude more fragile to heterogeneity than the network that makes it.
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Chemical Physics · Cross-listed from cond-mat.mtrl-sci
Site-Selective Yttrium Substitution in Ti3AlC2 Enables Interlayer Engineering and Li Transport in Ti3C2Tx cathodes for High-Power Energy Storage
Tetiana Boichuk, Andrii Boichuk, Mahesh Eledath Changarath et al. (+5 more)
In this work, we introduce a precursor-level strategy by substitutionally doping the Ti3AlC2 MAX precursor with a small amount of Yttrium during top-down MAX preparation. This allows permanent structural changes that are retained in the resulting Ti3C2Tx MXene. Density functional theory (DFT) calculations identify the outer Ti(4f) site, facing the Al layer, as the preferred incorporation site for Y under the Al-excess synthesis conditions used here, rather than the inner Ti(2a) or Al(2b) sites. This site-specific substitution is consistent with the experimentally observed
lattice expansion and carbide-like Y bonding and provides a microscopic basis for the structural changes retained in the resulting Ti3C2Tx MXene. Y incorporation expands the MXene interlayer spacing due to an increase in the amount of hydroxyl surface terminations, creating more favorable pathways for lithium-ion transport. Comprehensive structural characterization (including XRD, XPS and TEM) confirms these modifications. As a result, the Y-doped Ti3C2Tx cathode shows
diffusion-controlled charge storage with a Li
diffusion coefficient of 10-9-10-11 cm2/s. It delivers a reversible capacity of about 130 mAh/g at 0.2 C and retains 74 mAh/g after 1000 cycles at 2 C with nearly 100% Coulombic efficiency. The electrode also achieves a high power density of up to 3970 W/kg, outperforming the undoped MXene and previously reported multilayered MXene cathodes. These results show that substitutional doping of the MAX precursor is a promising strategy for controlling the interlayer structure of MXenes and improving ion transport, providing a new route for the development of high-power energy-storage electrodes.
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All authors Tetiana Boichuk, Andrii Boichuk, Mahesh Eledath Changarath, Joao Fonseca, Said Agouram, Marie Finas, Alejandro Molina-Sanchez, Juan F. Sanchez-Royo
Optics
Reconfigurable Linear Optical Transformations in a Single Integrated Multimode Waveguide
Manoah van der Worp, Jonas Krimmer, Ivo M. Vellekoop et al. (+2 more)
Wavefront shaping enables control over optical fields for applications ranging from imaging to photonic information processing. While conventional wavefront shaping relies on free-space systems comprising bulk optical components, compact and fully integrated approaches are comparatively unexplored. Here, we introduce a concept based on a single multimode waveguide with distributed thermo-optic perturbations for controlling multimode propagation. We develop a differentiable physical model and numerically demonstrate shaping the outgoing wavefront and programmable linear optical transformations, using gradient-based optimization. We achieve diffraction-limited focusing with 20 spatial modes and show that the theoretical focusing limit can be retained while maintaining more than $99\%$ of the input optical power. We extend this approach to complete input–output transformations and implement Sylvester–Hadamard
matrix operations with dimensions up to $32\times32$ with correlations exceeding $99\%$. Reducing the number of tunable elements requires stronger individual perturbations, resulting in stronger and broader mode coupling that extends beyond the target modes. To mitigate this effect, we consider ancillary modes and realize a $4\times4$ transformation that reaches $93.8\%\pm4.8\%$ correlation with only $5N^2$ tunable elements, where $N=4$ denotes the number of spatial modes. The best-performing realization reaches $98.3\%$ correlation with the target. Our results demonstrate that thermo-optic control of multimode waveguides offers an approach to fully-integrated wavefront shaping and programmable linear optical transformations, with potential applications in classical and
quantum photonic processing
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All authors Manoah van der Worp, Jonas Krimmer, Ivo M. Vellekoop, Pepijn W. H. Pinkse, Stefan Rothe
Computational Physics · Cross-listed from cond-mat.str-el
GEM: An implementation of the ghost-Gutzwiller approximation for simulating interacting quantum systems
Samuele Giuli, Tsung-Han Lee, Yong-Xin Yao et al. (+6 more)
We present GEM (Ghost
Embedding Method), an open-source software package written in Python for computing
equilibrium properties of strongly correlated electronic systems within the ghost-Gutzwiller approximation method. GEM provides a computationally efficient framework for studying multi-orbital
lattice models. It supports zero- and finite-temperature calculations and
symmetry broken phases. It is integrated with the TRIQS ecosystem, providing tools for model construction, self-consistent solution, and evaluation of physical observables. We first detail the method's theoretical formulation, then we present the software architecture, and finally we introduce some practical workflow, which also validates the implementation against established results. In particular, we illustrate the capabilities of GEM through multiorbital and finite-temperature applications and discuss its computational cost relative to more demanding
quantum embedding approaches.
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All authors Samuele Giuli, Tsung-Han Lee, Yong-Xin Yao, Ina Park, Harrison LaBollita, Ivan Pasqua, Nils Wentzell, Nicola Lanatà, Olivier Gingras
Biological Physics · Cross-listed from q-bio.QM
Structured Population Models for Follicular Development
Edilbert Christhuraj, Claudio Iuliano and Alexander Lange
Ovarian follicle development has been modeled either by compartmental models, where developmental stages are represented by discrete compartments, or by physiologically structured population models (PSPMs), formulated as transport PDEs describing follicles along a continuous maturation variable. Compartmental models reproduce full-cycle hormonal and follicular dynamics but cannot describe cellular features. PSPMs capture multiscale behavior, yet lack a direct link to compartmental descriptions, making hormonal feedback difficult to incorporate. Here, we introduce a class of ODE systems derived as finite-dimensional reductions of PSPMs via a perturbative moment closure. These systems provide backbone approximations of the structured dynamics, retaining key nonlinear mechanisms governing recruitment, selection for dominance, and atresia while projecting maturation onto macroscopic variables. Zero- and first-order moments, derived from phenomenological assumptions regarding follicular maturation, allow us to realistically model follicle sizes and blood estradiol concentrations over one follicular wave. This application is supported by bovine data and likely generalizable to other mammalian species.
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Fluid Dynamics
Spall Failure of Coral Skeleton beneath Gas-Laden Canopies: An Idealized Blast-Fishing Model
Sandy Hardian Susanto Herho, Agus Wahyu Jatmiko, Rizki Dimas Permana et al. (+7 more)
Improvised explosives used for fishing on shallow Indonesian reefs shatter coral skeleton, yet the damage they cause has been described largely through empirical radii and ecological surveys. We formulate an idealized model of how free gas held within a coral canopy modifies the shock loading that such a charge delivers to skeletal plates. The canopy is treated as a relaxed bubbly mixture whose shock impedance follows from the conservation of mass and momentum, and the reef is represented as a layered column of water, canopy, skeletal plate, and canopy struck at normal incidence. Three closed-form results emerge. Above a crossover pressure set by the void fraction and the stiffness of seawater, the canopy becomes nearly transparent to the shock. The impulse transmitted through any lossless layered stack is independent of the canopy, so gas redistributes the pulse in time without changing its total push. A plate carries tension after reflection from its lower face only when the canopy impedance falls below a threshold fixed by the plate thickness and the pulse duration, which defines a critical thickness. For a one-kilogram charge directly overhead, a gas-rich canopy more than triples the standoff at which a twelve-centimeter plate spalls while shortening the standoff at which it is crushed. A prescribed daily cycle of photosynthetic gas makes the same charge markedly more damaging at noon than at night. Bubble dynamics show that the canopy does not reach
equilibrium within the pulse, so the results are best read as upper bounds.
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All authors Sandy Hardian Susanto Herho, Agus Wahyu Jatmiko, Rizki Dimas Permana, Iwan Pramesti Anwar, Alfita Puspa Handayani, Faruq Khadami, Karina Aprilia Sujatmiko, Rusmawan Suwarman, Deny Juanda Puradimaja, Dasapta Erwin Irawan
Fluid Dynamics
Uncovering flame physics with machine learning: application to the reaction rate in hydrogen flames
Antonio Attili, Ludovico Nista, Tommaso Baffetti et al. (+6 more)
Convolutional Neural Networks (CNNs) are used as analytical tools to investigate the relationship between the progress variable field and the local chemical source term in lean premixed hydrogen flames. Rather than employing machine learning for modelling, CNNs are leveraged to analyse the physical information contained in spatially resolved fields from direct numerical simulations. CNNs are particularly well suited for this task because they exploit spatial correlations and multi-scale structures, allowing an assessment of how spatial organisation influences the source term. The analysis demonstrates that the progress variable based on water, $C_{\rm H_2O}$, contains all the information required to accurately parametrise the chemical source term whereas $C_{\rm H_2}$ alone does not. The inclusion of the mixture fraction $Z$ improves the accuracy of the latter but provides no significant additional information to the CNN when the spatial field of $C_{\rm H2O}$ is used as input. The same behaviour is observed in both a laminar thermodiffusively unstable flame and a turbulent slot-jet hydrogen flame, indicating that $C_{\rm H_2O}$ is a robust single variable for parametrisation. A complementary scale analysis in the laminar case shows that spatial features extending over at least two laminar flame thicknesses are required to reconstruct the source term accurately, thereby identifying the characteristic scale in the progress variable field that carries this information. These results demonstrate how machine learning can uncover physical dependencies that remain hidden to classical statistical analyses.
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All authors Antonio Attili, Ludovico Nista, Tommaso Baffetti, Geveen Arumapperuma, Sofiane Al Kassar, Lukas Berger, Christoph D. K. Schumann, Temistocle Grenga, Heinz Pitsch
Fluid Dynamics · Cross-listed from math.AP
Near-cancellation of enstrophy and strain requires shear or a balanced vortex
Jonathan Massey
In the nonlinear source of the pressure Poisson equation the fluctuating enstrophy and strain nearly cancel. We ask where the cancellation is complete, which we call silent, and how the source escapes it. Pointwise the source depends only on the
eigenvalues of the velocity gradient. Pure shear has none, so it is silent. It is the origin of the normalised invariant plane, whose second-invariant coordinate is the normalised source. Let $f$ be the shear fraction of the gradient and $m$ its distance from that origin. We prove that $m\le1-f\le3m$ at every point of every incompressible flow. Wherever the source nearly vanishes and the third invariant is small, the gradient is nearly pure shear. Otherwise the cancelling gradient is a balanced
vortex, a swirl its own strain cancels at any strength. At a no-slip wall the silent object is exact: the wall shear-stress fluctuation, a rank-one sheet. Away from the wall we assume the same sheet, dressed with a small residual, and derive how it escapes. The escape passes through one element of the residual, the along-sheet variation of the sheet-normal velocity. Its amplitude is the
geometric mean of sheet and residual, and its sign selects swirl or strain. A rank-two silent object has the same source through the same gates but balanced
eigenvalues, so the assumption fixes the escape's
topology, not its source. The shear fraction is thus a pointwise proxy for cancellation by shear, and a model of the source must be built on what escapes.
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Optics
Inverse-Designed Time-Varying Multilayers for Programmable Frequency-Momentum Light Scattering
Mohammad M. Asgari and Viktar Asadchy
Space-time-varying electromagnetic structures unlock wave-control mechanisms inaccessible to static media, including frequency conversion, harmonic generation, and joint control over frequency and momentum. Here, we introduce an inverse-design framework for multilayer space-time-periodic structures in which the spatial permittivity distribution and temporal modulation profile are optimized jointly. The proposed platform comprises multiple pixelated layers that are periodic along one or both transverse directions and harmonically modulated in time, enabling the direct synthesis of complex multichannel frequency-momentum scattering responses. We demonstrate two representative functionalities: independent control over the amplitudes and phases of three transmitted spatiotemporal channels and the generation of a frequency-momentum comb. Across these examples, we consider both continuous and binary permittivity distributions. To facilitate reproducibility and further development, we make the numerical implementation of the optimization framework freely available. These results demonstrate that inverse-designed time-varying multilayers provide a compact and versatile route toward programmable frequency-momentum multiplexing and the synthesis of space-time wave packets. The optimization code is made openly available to facilitate reproducibility and further development of the proposed inverse-design framework.
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Optics
Asymmetric Negative Refraction in Nonlocal Double-Wire Metamaterials
Tiago A. Morgado, Sylvain Lannebère, Enrico M. Renzi et al. (+2 more)
We demonstrate that heterogeneous double-wire metamaterials, comprising two dissimilar and nonconnected wire arrays, enable loss-asymmetric
hyperbolic dispersion and strongly asymmetric negative refraction. We unveil that, owing to their strongly nonlocal response and distinctive microstructure, such geometry supports two independent
hyperbolic propagation channels with unequal losses, which can be selectively excited by free-space propagating waves incident at opposite angles. This angular selectivity gives rise to asymmetric negative refraction at the air-metamaterial interfaces, characterized by strong angular asymmetry in transmission and absorption, while preserving reciprocity. This phenomenon is scalable and can be realized with metallic wire arrays over a broad frequency spectrum extending from microwave to infrared frequencies, showing that nonlocality can emulate shear-like dissipative asymmetry that, in local media, requires lower spatial
symmetry. Our findings open new avenues for directional energy transport and angle-selective wave control in photonic platforms.
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All authors Tiago A. Morgado, Sylvain Lannebère, Enrico M. Renzi, Andrea Alù, Mário G. Silveirinha
Data Analysis and Statistics · Cross-listed from cs.LG
Fast and Precise Learned Charged-Particle Trajectory Regression at the Large Hadron Collider
Jonathan Renusch, Benjamin Huth, Daniel Murnane et al. (+9 more)
We propose a training recipe that treats charged-particle trajectory parameter regression on high-energy physics detector data as a sequence-modeling task. Kalman filters and linearized least-squares fits have been the classical standard approach for this task: they are optimal
estimators for sparsely sampled linear-Gaussian data and are commonly used for trajectory parameter regression (fitting). The classical fitting techniques implemented for this domain reach a final precision of one part in $10^5$ through detailed modeling of detector geometry, material, detection effects and precise numerical integration of the equations of motion through the detector's inhomogeneous
magnetic field. With this study, we demonstrate that using a bidirectional gated linear recurrent encoder, one is able to reproduce the full precision of classical track fitting techniques. Using a custom kernel, we also achieve significantly higher throughput during GPU inference, compared to classical fitting software running on similarly priced multi-core CPU servers representing typically employed hardware. Such a speedup would lead to considerable cost savings for the pattern recognition at the Large
Hadron Collider. To our knowledge, this is the first end-to-end learned track fit to reach the full precision and, at the same time, offer the opportunity to reduce the computing costs.
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All authors Jonathan Renusch, Benjamin Huth, Daniel Murnane, Eleni Xochelli, Doğa Elitez, Paul Gessinger-Befurt, Andreas Stefl, Jeremy Couthures, Andreas Salzburger, Lukas Heinrich, Michael Kagan, Markus Elsing
Applied Physics
A 20-kV Optical-Injection-Enhanced 4H-SiC Reverse-Conducting IGBT With Snapback-Free Operation and Low On-State Voltage
Yujian Chen, Guoliang Zhang, Ruijun Zhang et al. (+4 more)
This letter proposes a 20-kV 4H-SiC optical-injection-enhanced reverse-conducting IGBT (OIE-RC-IGBT) with snapback-free operation and low on-state voltage. Light-emitting diodes (LEDs) are integrated into the gate structure to provide optical injection during forward conduction. The emitted light generates a high concentration of photogenerated carriers in the carrier-storage layer (CSL) and drift region, thereby reducing the resistance of the JFET and drift regions and increasing the device current. Consequently, the collector-side P+/N junction is turned on earlier, effectively suppressing the snapback effect and facilitating the transition to bipolar conduction. After bipolar conduction is established, the photogenerated carriers further enhance conductivity modulation, resulting in a reduced on-state voltage. TCAD simulation results show that, compared with the conventional RC-IGBT (C-RC-IGBT), the proposed device achieves snapback-free operation while reducing the required number of MOS
cells from 25 to 5. Moreover, the on-state voltage, turn-off fall time, and turn-off energy loss are reduced by 22.37%, 25.06%, and 19.69%, respectively. These results demonstrate the potential of optical injection for improving the conduction and turn-off performance of ultrahigh-voltage SiC RC-IGBTs.
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All authors Yujian Chen, Guoliang Zhang, Ruijun Zhang, Liangxun Yue, Zhanwei Shen, Feng Zhang, Rong Zhang
History and Philosophy of Physics
From Mass to Energy-Momentum: The Field-Theoretic Perspective on the Energy-Mass Relation
Patrick M. Duerr and J. Brian Pitts
The paper examines the energy-mass relation of Special Relativity (SR), its status and interpretation, through the lens of classical/non-
quantum relativistic field theory. The latter arguably constitutes the fullest embodiment of SR as what Einstein labelled a "principle theory". It forms, we propose, the most appropriate perspective also for understanding the energy-mass relation. In a field-theoretic setting, the key notion is a system's energy-momentum (in local/differential or global/integral form, defined via a suitable energy-stress complex). The energy-mass relation then expresses the role that a system's _rest_-energy (provided it exists) plays as the functional counterpart of mass: thanks to important
theorems, rest-energy qualifies as its field-theoretic generalisation or successor term. That is, while mass is dispensed with as a fundamental notion, rest-energy retains some—but not all—of its salient functional roles; for special cases, it turns out to be directly correlated with mass. In field theory as a general framework for more specific relativistic theories, energy-momentum replaces mass as the essential notion—a profound, yet often overlooked revision in basic physical concepts. Conservation in particular is guaranteed only for energy-momentum, but no longer for mass. In several regards, energy-momentum fuses energy, momentum and mass, with novel connections amongst them and concomitant physical effects. Situating the energy-mass relation within field theory is a surprisingly neglected, but deeply insightful vista for clarifying and philosophically reflecting on SR's foundations. The field-theoretic interpretation achieves a compelling inner coherence and unifying power, and ties it to the rich heuristic resources of field theory, crucial for post-1905 developments in physics.
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Physics and Society · Cross-listed from cs.LG
Editable Map-Conditioned Trajectory Generation for Human Mobility Simulation
Takayuki Mizuno, Shouji Fujimoto, Mikito Hiruki et al. (+1 more)
Geospatial simulation of infrastructure interventions requires mobility generators that respond directly to edited maps, yet many data-driven generators do not expose the map as an editable condition. We formulate this task as map-conditioned autoregressive generation of human mobility: a road raster conditions a decoder that emits nominal 31.25 m mesh-
cell tokens at one-minute intervals. The mesh-local vocabulary supports held-out and locally edited maps without retraining or vocabulary changes. We instantiate a ResNet-50 visual-prefix configuration and a
Vision Transformer (ViT) cross-
attention configuration, trained from scratch on 87,400 smartphone-derived trajectories from 874 meshes in Ishikawa Prefecture, Japan; 219 meshes are held out. We evaluate map sensitivity by comparing correct-map and within-split shuffled-map generations with held-out real trajectories. On the 110-mesh test split, for the ResNet-50 configuration, correct-map generations are closer than shuffled-map generations on 60% of meshes under Hausdorff-based energy distance (p = 0.021), while DTW is directional but inconclusive (57%, p = 0.074); correlation with real density is 0.38 with the correct map versus 0.01 with shuffled maps. The ViT configuration shows weaker trajectory-level sensitivity and smaller density gains. An illustrative bridge-removal edit changes generated continuations without retraining. Together, these results support the feasibility of editable-map human-mobility simulation.
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All authors Takayuki Mizuno, Shouji Fujimoto, Mikito Hiruki, Atushi Ishikawa
Computational Physics · Cross-listed from quant-ph
Conserved and relaxing modes enable polynomial-success coherent Carleman lattice Boltzmann evolution
Hua-Dong Yao and Sauro Succi
Carleman linearization represents nonlinear
lattice Boltzmann collision dynamics in a form amenable to
quantum block encoding, but low postselection probabilities in existing population-space encodings make coherent multi-step
evolution exponentially unlikely to succeed. We present a
quantum Carleman
lattice Boltzmann scheme based on the multi-relaxation-time collision operator in a weighted Hermite moment basis. In this basis, the lifted collision operator separates into small coupled blocks whose norm exceeds unity because of the coupling between conserved and relaxing modes. This block structure enables a norm-attaining block encoding with a single-step success probability close to unity. Crucially, scaling the pair sector for a prescribed
evolution horizon makes the combined encoding and sector-selection overhead grow polynomially rather than exponentially with the number of steps. For a hundred-step
evolution, the resulting complete-run success probability exceeds that of population-space encodings by orders of magnitude. Over horizons of several tens of steps, the truncated dynamics reproduces the nonlinearly generated modes of a
benchmark flow to within a few percent. We verify the combined preparation,
evolution and readout protocol as a single
unitary circuit and give a complete gate-level resource estimate for extracting a nonlinear observable of the
benchmark flow from a coherent Carleman
evolution. The block structure of conserved and relaxing modes holds equally on three-dimensional
lattices and provides a constructive route to norm-attaining encodings for
lattice Boltzmann models with quadratic
equilibria.
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Physics and Society
Hydrogen mon amour
Christophe Grojean and Patrick Janot
The FCC's projected average electricity consumption is 1.3 TWh per year. If supplied entirely by nuclear power, this would represent about 10% of the annual output of a large third-generation nuclear reactor, together with a corresponding share of its radioactive waste. By 2050, however, renewable sources could provide up to 80% of this electricity on a substantially decarbonised European grid, supported by long-term power-purchase agreements and flexible operation. This could reduce the residual nuclear requirement, and its associated waste, by up to a factor of five. This essay asks whether hydrogen could help bridge the remaining periods of low wind and solar generation. It examines production from renewable electricity, transport as hydrogen or ammonia, storage and conversion back into electricity, together with their efficiency losses and carbon footprints. It then considers the still uncertain prospect of naturally occurring hydrogen. None of these routes offers a ready-made solution. But the decades before the FCC begins operation leave time to develop one–and CERN could help accelerate that development by becoming a credible long-term customer.
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Fluid Dynamics
Benchmark of no-slip boundary conditions for meshless Lattice Boltzmann Method in Stokes flow
Dawid Strzelczyk, Pavel Eichler and Maciej Matyka
The introduction of the approximated streaming to the standard
Lattice Boltzmann Method (LBM) decouples the space and velocity discretizations. Although many no-slip implementations knwon from LBM can be directly adopted to the models with approximated streaming, their exact behavior in the off-
lattice setting remains unexplored. In this work, we investigate the meshfree off-
lattice D2Q9 model equipped with several no-slip implementations – non-
equilibrium extrapolation, simple and interpolated bounceback, and moment-based boundaries – applied to a Stokes flow around a cylinder. We compare the pressure, velocity and velocity gradient fields obtained with various no-slips, on polar and hybrid polar-scattered discretizations. We find that non-
equilibrium extrapolation performs the best of all the studied no-slip realizations, giving smooth stresses and zero velocity on the solid walls. Other no-slips suffer from oscillations and/or discontinuities in the hydrodynamic fields. Hybrid discretizations are found to give higher errors than the polar grid, but improve the stability of the solution. Finally, we simulate the deformation of an elastic ring under the stresses obtained with the studied no-slips to highlight the importance of the sensible choice of the no-slip realization in more complex problems.
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Plasma Physics
Review of LHD-ECRH activities and beyond
Masaki Nishiura, Hiroe Igami, Hiromi Takahashi et al. (+11 more)
The electron cyclotron resonance heating (ECRH) system on the Large Helical Device (LHD) played a key role in the progress of helical fusion research from the first
plasma in 1998 to the final discharge on December 25, 2025. This paper presents a historical review of ECRH activities on LHD, highlighting the stepwise advances in hardware, including gyrotrons, transmission lines, and launcher systems, together with the exploration of advanced
plasma regimes such as overdense heating and long-pulse steady-state operation. Beyond
plasma heating, the ECRH system was also used as a high-power probe for advanced diagnostics, including collective Thomson scattering (CTS) as well as correlation electron cyclotron emission (CECE), and as a flexible actuator for transport studies and real-time control experiments. Finally, we discuss how the technological assets and operational expertise accumulated over the nearly three decades of the LHD program are being further developed and applied to next-generation helical devices, particularly CHD and CHD-U, as well as to broader gyrotron and millimeter-wave applications.
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All authors Masaki Nishiura, Hiroe Igami, Hiromi Takahashi, Naoki Kenmochi, Ryoma Yanai, Kenji Ueda, Yoshinori Mizuno, Toshiki Takeuchi, Yasuo Yoshimura, Takashi Shimozuma, Shin Kubo, Toru Ii Tsujimura, Sakuji Kobayashi, Tsuyoshi Kariya
Chemical Physics
The Same and Not the Same: A Machine-Checked Genealogy of Photochemical Theory
Junyi Gong, Zijie Qiu and Ben Zhong Tang
Chemistry's phenomenological theories multiply with its observables: the same physical reality is repeatedly named in different measurement contexts, and the relations among theories have never had an auditable carrier. Here we present PhotoLean, a machine-checked genealogy of seventeen photochemical and photophysical theories formalized in Lean 4 over a shared kernel. Every pair of theories carries either a verified relation (equivalence, implication, composition with registered premises, definitional certificate) or a registered reason for its absence, covering all 136 pairs. Three adjudications resolve inherited conflations with if-and-only-if boundaries and witnesses: the
symmetry factor $\beta$ equals one-half exactly when reactant and product force constants coincide; Kasha's rule and the Kasha-Vavilov rule agree only under closed quantification with a loss channel; and intensity-only Stern-Volmer data cannot distinguish static from dynamic quenching, whereas the lifetime channel discriminates exactly. As proposition generation shifts to machines, such machine-checked relational ledgers offer a replicable audit layer for theory itself.
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Fluid Dynamics · Cross-listed from math.NA
Isothermal walls in the compressible Navier-Stokes equations: affine entropy, ballistic energy, and entropy-stable discrete formulations
Matteo Parsani, Rasha AlJahdali and Lisandro Dalcin
We develop
entropy-stable isothermal-wall conditions for the compressible Navier–Stokes equations at continuous and semi-discrete levels. For a stationary, impermeable, no-slip wall at constant positive temperature, adding total-energy density divided by wall temperature to the canonical convex
entropy cancels the wall contribution without suppressing heat transfer. This affine modification preserves the
entropy Hessian, relative
entropy, and volume
entropy production. It is proportional to total ballistic-energy density and yields a conditional $L_2$-type bound based on the initial field under the stated assumptions. Two wall formulations use a common discontinuous Galerkin discretization with the summation-by-parts property and simultaneous approximation terms. Both give zero adapted wall contribution without a penalty and a nonpositive contribution with it. The complete-residual formulation penalizes the full wall-data residual and balances fluid energy through its complete numerical wall flux. The
Fourier-energy-exact formulation combines an
entropy-neutral skew correction with a momentum-projected penalty so that the complete numerical outward energy flux equals the one-sided numerical
Fourier heat flux at every wall node and spatial resolution. Pointwise tests verify the local identities. Manufactured-solution studies with
entropy-stable interior coupling demonstrate convergence rates consistent with order $p_s+1$ in the discrete $L_2$ norm, where $p_s$ is the solution
polynomial degree. Thermal-relaxation calculations verify the semi-discrete energy and adapted-
entropy balances. Three-dimensional calculations demonstrate balance closure in a closed domain, convergence of curved-wall traces, and applicability to a complex supersonic separated flow.
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Plasma Physics · Cross-listed from math.NA
Positivity-preserving semi-Lagrangian discontinuous Galerkin methods for multi-species Vlasov-Ampère models of plasma
Dauda Gambo and James A. Rossmanith
We develop a high-order and positivity-preserving kinetic solver for the multi-species Vlasov-Ampère system that is built within a semi-Lagrangian discontinuous Galerkin (SLDG) framework. The method is designed for efficiency and accuracy across a broad range of conditions, including stiff, multi-scale regimes with strong ion-electron scale separation. Phase space is discretized via high-order discontinuous Galerkin finite elements; time stepping is handled via high-order operator splitting and a series of one-dimensional, unconditionally stable, semi-Lagrangian updates. To improve both accuracy and efficiency, each
plasma species is represented on a different phase-space mesh. On every element and for each species, local positivity-preserving limiters are applied to prevent spurious undershoots and rigorously ensure positivity of the
cell averages at the next time step. The accuracy and robustness of the resulting method are verified on several standard single- and two-species test cases, including manufactured solutions, two-stream instability, weak and strong Landau damping, ion-acoustic wave propagation, ion-acoustic shock formation, and KEEN wave dynamics.
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Fluid Dynamics
A deterministic Fokker–Planck/lattice-Boltzmann micro–macro solver for dilute Hookean polymer solutions
Xueqin Liu, Shi Shu, Yaolong Yu et al. (+3 more)
Deterministic micro–macro simulation of
polymer solutions requires the coupled
evolution and spatial transport of a configuration distribution, together with the conversion of its moments into macroscopic stress and feedback to the flow. We develop a Fokker–Planck/
lattice-Boltzmann solver for this coupling in two-dimensional dilute Hookean
polymer solutions. The solver represents the distribution on the unbounded configuration space by Hermite coefficient fields, advances local configuration dynamics and physical-space transport in separate steps, and recovers Kramers stress from the second moment to achieve two-way coupling with a purified two-relaxation-time
lattice-Boltzmann flow solver. To assess whether this configuration description recovers the corresponding macroscopic response, we use the exact second-moment closure of the continuous Hookean model as a macroscopic reference for comparison with analytical and independently discretized macroscopic solutions. The calculations reproduce velocity overshoot and damped oscillations in start-up Poiseuille flow, with velocity profiles approaching the analytical start-up transient under grid refinement; in four-roll flow with spatially nonuniform extension and stress feedback, the maximum full-domain relative differences in velocity and
polymer stress are approximately $0.0309\%$ and $3.84\%$, respectively, over the tested Weissenberg numbers at corresponding sampling times. These comparisons support the solver's ability to recover the Hookean macroscopic response from configuration-distribution
evolution. Further calculations of wall-bounded recirculation and open cross-slot flow exhibit the corresponding conformation responses and symmetric and asymmetric flow states, extending this deterministic micro–macro method to viscoelastic flows under different boundary constraints.
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All authors Xueqin Liu, Shi Shu, Yaolong Yu, Yuan Yu, Hao Zhang, Yuting Zhou
Geophysics
Efficient One-Step Surface-Wave Tomography through Implicit Differentiation and Jacobian Factorization
Yiran Jiang, Ping Tong and Jianwei Ma
Surface-wave
tomography provides important constraints on the crust and upper mantle, but directly inverting millions of measurements for three-dimensional structure remains computationally demanding. We develop an efficient Gauss–Newton framework for one-step surface-wave
tomography that jointly inverts multiperiod interstation traveltimes for shear-wave velocity, accounting for both lateral wave propagation and depth sensitivity. Implicit differentiation of the converged discrete Eikonal equations provides individual traveltime sensitivity kernels, which are constructed efficiently by reusing the Eikonal dependency structure across receivers. A factorized Jacobian retains these kernels separately from shared model and dispersion mappings, reducing storage and repeated-product costs within each linearized solve. Synthetic experiments show that the framework recovers three-dimensional velocity anomalies with fewer model updates and lower model errors than the tested comparison workflows at similar data fits. Computational
benchmarks demonstrate substantial savings in operator storage and the cost of linearized model updates compared with using explicitly assembled Jacobians. We apply the framework to 6.34 million Rayleigh-wave phase traveltimes across the contiguous United States. The recovered model captures major crustal and uppermost mantle velocity variations, including the broad contrast between the tectonically active western United States and the continental interior, consistent with previous surface-wave studies. These results demonstrate a practical Gauss–Newton approach to imaging the crust and upper mantle using large surface-wave data sets.
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Optics
Geometry-Controlled Polarization Photocurrents in Scalable PtSe2 Infrared Pixels
Eunice Y. Paik, Owen A. Vail, Madaline R. Marland et al. (+11 more)
Polarization-sensitive photodetectors provide multi-dimensional optical information beyond the capabilities of traditional intensity-based detectors. The noble metal dichalcogenide PtSe2 presents unique opportunities for tunable polarization detection due to its strong
spin-orbit coupling, material stability, customizable broadband polarization responses, and direct compatibility with a wide range of substrates for back-end-of-line silicon integration. In this work, we demonstrate room-temperature near-infrared to mid-wavelength infrared polarization photoresponses using scalable, as-grown, wide-area PtSe2 films, and we show that the measured polarization response is reshaped by device geometry. Finite-element current-flow simulations reproduce the observed spatial redistribution of the polarization-sensitive response and localize the transverse polarization response near the pixel center. This geometry-enabled separation allows wavelength-dependent
laser spot scans to distinguish
symmetry-allowed photocurrents from contact-proximate, dichroism-mediated photothermal contributions. At near-infrared wavelengths, we observe spatial response that is consistent with linear-dichroic photothermoelectric currents, whereas mid-wavelength infrared measurements reveal a helicity-dependent photothermal contribution under oblique illumination. These results identify pixel boundary engineering as both a design lever and a diagnostic tool for scalable PtSe2 polarization-sensitive infrared pixels.
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All authors Eunice Y. Paik, Owen A. Vail, Madaline R. Marland, William A. Beck, Antonio Llopis-Jepsen, Wendy L. Sarney, Jeffery H. Leach, Stefan Heiserer, Nikolas Dominik, Cormac Ó Coileáin, Paul B. Seifert, Georg S. Duesberg, Blair C. Connelly, George J. de Coster
Fluid Dynamics
Reconstruction of Molten Pool Flow Fields from High-Speed Video Using Physics-Informed Neural Networks
Yue Cao, Qin Su, Dung Hoang Tien et al. (+1 more)
Molten pool flow significantly influences bead geometry, defect formation, and solidification microstructure in wire-arc directed energy deposition (DED). However, direct flow sensing remains an open challenge due to extreme temperatures, intense arc illumination, and complex flow patterns. Traditional research has relied either on computationally intensive fluid dynamics simulations, which require assumed boundary conditions and lack empirical anchoring, or on
vision-based tracer particle tracking, which yields sparse, noisy, and physically unconstrained velocity estimates. This work bridges these two paradigms by reconstructing physics-constrained 2D surface flow fields from high-speed imaging of a GTAW-based wire-arc DED process under distinct flow regimes: quasi-steady convection and periodic droplet impact. The pipeline begins with homography correction to calibrate the oblique camera view, followed by dense optical flow extraction to provide raw velocity observations. For quasi-steady pools, a physics-informed neural network (PINN) reconstructs the surface velocity field by jointly enforcing data fidelity, incompressible Navier-Stokes momentum equations, no-penetration boundary conditions, and an arc-forcing prior through composite loss minimization. For pools subject to periodic droplet impact, a phase-conditioned time-dependent PINN is further developed to resolve the cyclic flow
evolution throughout the impact period. This work provides a unified framework that bridges high-speed visual sensing and fluid mechanics, enabling physics-grounded flow diagnostics for wire-arc DED processes.
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All authors Yue Cao, Qin Su, Dung Hoang Tien, Van Anh Nguyen
Applied Physics · Cross-listed from cond-mat.mes-hall
In-Memory AM Demodulation Using an All-Silicon Independent-Dual-Gate Gain-Cell Memory with $<10^{-22}$ A Leakage Determined by Single-Electron Counting
Katsuhiko Nishiguchi, Toshiaki Hayashi, Kensaku Chida et al. (+3 more)
Ultra-low-leakage
memories are attracting increasing
attention for in-
memory sensing and computing. However, achieving sufficiently long retention in silicon
memories for analog signal processing remains challenging because of leakage through the access transistor. In this work, we demonstrate an all-silicon independent-dual-gate
memory whose leakage current, inferred from single-electron counting statistics, is below $10^{-22}$ A, giving a measured retention time exceeding 1000 s. Owing to the extremely low leakage, the subthreshold nonlinearity of the access transistor can be exploited without disturbing the stored charge, enabling in-
memory amplitude-modulation (AM) demodulation. The proposed
memory provides a CMOS-compatible platform for ultra-low-power signal processing and in-
memory sensing.
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All authors Katsuhiko Nishiguchi, Toshiaki Hayashi, Kensaku Chida, Takase Shimizu, Gento Yamahata, Seiya Kasai
Instrumentation and Detectors
Enhancing Conversion Gain in HEB Mixers using Negative Differential Resistance
Boris S. Karasik and Changyun Yoo
This work investigates how negative differential resistance (NDR) can be utilized to enhance conversion gain in superconducting niobium nitride (NbN) hot-electron bolometer (HEB) mixers. Conventional HEB operation avoids NDR regions due to parasitic oscillations caused by interactions between thermal inertia and bias-line reactance. Recent experimental results show that reducing the bias-T inductance suppresses these oscillations and enables stable biasing within the NDR regime, thereby increasing the mixer conversion gain beyond levels achievable under positive differential resistance (PDR) bias. Using a lumped thermal-electrical model, we interpret these experimental findings, derive stability conditions for NDR-biased operation, and predict the future performance limits achievable through optimized bias
circuit designs. Our results indicate that further reductions in bias inductance, combined with appropriate load-line conditions, could yield several decibels of additional gain while maintaining practical IF bandwidths.
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