Soft Condensed Matter
Physics-Informed Neural Networks for Depth-Averaged Granular Avalanche Dynamics on Curved Topography
Pujan Pranavkumar Purohit, Pradyumn Singh Sikarwar, Vishal Sharma et al. (+1 more)
Physics-informed neural networks (PINNs) provide a mesh-free framework for solving governing equations, but their application to granular avalanche dynamics over curved terrain remains largely unexplored. This study extends a depth-averaged PINN formulation based on the Savage-Hutter equations to an exponentially curved chute with spatially varying inclination and a strain-rate-dependent Mohr-Coulomb earth-pressure closure. The model is validated against measured front- and rear-edge trajectories from a laboratory granular-avalanche experiment, with selected observations withheld from training. A staged temporal curriculum proved essential for accurate prediction, reducing the held-out trajectory error by approximately two orders of magnitude compared with training over the full time domain from the outset. Sparse-data experiments further showed that observation placement was more influential than observation number within the configurations tested. Four observations bracketing the transition from acceleration to deceleration achieved nearly the same accuracy as the eight-observation reference configuration, whereas observations clustered at early or late times performed poorly. The results demonstrate the importance of both training strategy and informative data placement when applying PINNs to granular flows over curved topography.
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All authors Pujan Pranavkumar Purohit, Pradyumn Singh Sikarwar, Vishal Sharma, Gaurav Bhutani
General Relativity and Quantum Cosmology
Coherent multipath wave response on Reissner-Nordström analogue surface
Peng-Yu Chen, Sen Guo, Qing-Quan Jiang et al. (+2 more)
To uncover how the intrinsic metric of a relativistic compact object governs macroscopic wave phenomena, we establish a theoretical framework mapping the charge dependent spatial geometry of a Reissner-Nordström (RN) black hole onto the coherent response of an analogue curved surface. By solving an exact spatial geodesic boundary value problem on an isometrically embedded equatorial slice, we extract the discrete multi-loop path-length spectrum and convert this
geometric backbone into a physical wave field via a finite-path surface Huygens-Fresnel construction. We analytically compute the arbitrary order winding trajectories alongside their high winding accumulation limits, demonstrating that the analogue charge acts as a precise physical dial that reconfigures the event horizon throat and fundamentally reorganizes the discrete path sequence. Furthermore, we find that this underlying
geometric deformation uniquely dictates the macroscopic interference, revealing that steady state spatial fringes, spectral resonance combs, and transient temporal echo ladders are intrinsically unified physical projections of a single charge controlled path spectrum. This systematic parameter to response methodology establishes a rigorous theoretical bridge between strong field gravitational
lensing and tabletop transformation optics, providing a highly tunable blueprint for future multi domain analogue
gravity experiments.
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All authors Peng-Yu Chen, Sen Guo, Qing-Quan Jiang, Yu Liang, Kai Lin
Mathematical Physics
Optimal bounds for embedded eigenvalues of one-dimensional discrete Schrödinger operators with decaying potentials
Jifeng Chu, Wencai Liu and Kang Lyu
In this paper, we consider one-dimensional discrete Schrödinger operators \begin{align} Hu(n)=(\Delta+V)u(n)\nonumber \end{align} on $\ell^2(\mathbb{N})$ with a self-adjoint boundary condition at $n=0$, where $\Delta$ denotes the discrete
Laplacian and $V(n)$ is a real-valued perturbation satisfying $$V(n)=\frac{O(1)}{1+n}.$$ We determine the sharp transition for the asymptotic coefficient of \(V\) governing the existence and nonexistence of embedded
eigenvalues.
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Materials Science
A Strategy Toward Room Temperature Topological Hall Effect via Local Moment Magnetism
Karthik Rao, Kevin Allen, Yuxiang Gao et al. (+10 more)
Topological
spin textures in local moment systems hold great promise for technological applications due to their large
magnetic moments, strong
spin-orbit coupling (SOC), and high tunability. Finding new
spin textures that are stable near room temperature is paramount to maximizing their potential for applications. Here, we provide a strategy for realizing topological
spin textures at high temperatures by identifying rare earth ($R$) magnets ordering at or near room temperature. We demonstrate the feasibility of this strategy in one of these magnets, hexagonal Gd$_5$Pb$_3$, which orders at $T_C$ = 285 K. The indication for topological
spin textures comes from topological
Hall effect (THE), which, in Gd$_5$Pb$_3$, occurs between $T$ = 100 - 200 K, an order of magnitude higher temperature than in other reported $R$-based systems. Our results present an opportunity to explore the role of SOC, anisotropic exchange,
geometric frustration, and
magnetic interactions in stabilizing topological
spin textures, and provide a pathway toward realizing them near room temperature in $R$-based magnets.
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All authors Karthik Rao, Kevin Allen, Yuxiang Gao, Arushi, Sanu Mishra, Birender Singh, Kenneth S. Burch, Liangzi Deng, Shanta R. Saha, Johnpierre Paglione, Minseong Lee, Vivien Zapf, Emilia Morosan
Quantum Physics
Discretization-Aware Fine-Tuning for Quantum Machine Learning with Chemical Foundation Models
Shunji Matsuura and Sonika Johri
A key challenge in practical
quantum machine learning (QML), particularly for discriminative tasks such as classification, is the limited capacity of near-term
quantum devices to encode high-dimensional classical data into small
quantum registers. In optimized basis-encoded (bit-bit) settings, this constraint leads to cross-class collisions, where samples with different labels are mapped to the same discrete bit-string and thus become indistinguishable to any downstream model. In this work, we investigate how data representation affects QML performance under such severe information bottlenecks. We introduce discretization-aware fine-tuning (DAFT), a method that adapts a pre-trained chemical foundation model to produce representations that remain informative after quantization. DAFT reduces collision probability through a differentiable soft collision loss. We evaluate both
quantum and classical models under a controlled setting in which they receive identical discretized bit-string inputs, isolating the effect of representation from model architecture. On the blood-
brain barrier penetration (BBBP) molecular property prediction
benchmark using ChemBERTa-77M, DAFT reduces collision counts by several orders of magnitude and improves
quantum classification accuracy by more than 12 percentage points compared to a frozen backbone. Importantly, without DAFT, classical models outperform QML under the same input constraints. With DAFT, however, this comparison reverses at higher
qubit counts. At 10
qubits, the
quantum model surpasses a matched classical baseline trained on identical bit-strings (0.883 vs. 0.855, $p = 0.026$). These results show that, in information-constrained regimes, achieving a
quantum advantage critically depends on aligning continuous representations with discrete
quantum encodings.
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Statistical Mechanics
Optimal Control of Periodic Nonequilibrium Mechanochemical Systems via Automatic Differentiation
W. Callum Wareham and David A. Sivak
Biological molecular machines are mesoscopic systems that act repeatedly and periodically to perform important cellular tasks while contending with strong fluctuations and operating in an overdamped regime. Optimal control theory is a tool that can be used to understand the design principles behind efficient operation of these machines; however, most studies on optimal control of classical mesoscopic systems have focused on control problems that do not repeat periodically. Here, we automatically differentiate Fokker-Planck simulations to design efficient nonequilibrium control strategies for simple models of periodic molecular machines with and without explicit changes in the machine's chemical state. The designed protocols and theoretical analysis provide insight into the design principles governing efficient driving in these nonequilibrium systems. Designed control protocols should seek to reduce mechanical heat by rotating the entire angular probability distribution at a constant speed without changing its shape, and should reduce chemical heat by reducing the proportion of chemical transitions with large heat.
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Materials Science
Thermal history controls the optoelectronic response of lead halide perovskites through structure and dynamics
Milos Dubajic, Xia Liang, Johan Klarbring et al. (+26 more)
Lead halide perovskites are promising optoelectronic materials for photovoltaics, light emission and detection. Their efficiencies in PV now approach the detailed-balance limit, leaving stability as the principal barrier. The intrinsic instabilities studied to date centre on ionic motion within a fixed, homogeneous
lattice. Here we identify a further source of intrinsic structural instability, hidden in the
lattice dynamics. Mapping caesium, methylammonium and formamidinium-based compositions with Cl, Br, I and mixed X-sites through all accessible phases, using single
crystal X-ray and
neutron diffuse scattering, machine-learning-assisted molecular dynamics, a phenomenological octahedral tilt model and hyperspectral photoluminescence, we find that nearly every composition hosts
equilibrium local structural fluctuations: dynamic nanodomains of correlated octahedral tilts, a few nanometres in size, that locally break the crystallographic
symmetry. Three complementary levers control them. The A-site cation sets their
symmetry, shape and anisotropy, from sparse, isotropic and tetragonal in formamidinium-based compositions to dense, anisotropic and orthorhombic in nominally cubic caesium-based ones, the most locally disordered we studied. The halide controls the dynamic disorder and the phase-transition sequence. Thermal history is the third: different ramp rates drive nominally identical compositions into distinct crystallographic phases, each with its own hidden local order. In MAPbI3, the heating rate alone changes the photoluminescence
quantum efficiency across the phase transition. Because these transitions lie within device operating ranges, from terrestrial thermal cycling to the extremes of space, thermal history may shape the local structure, and hence the optoelectronic response, throughout fabrication and operation, establishing it as a design variable alongside composition.
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All authors Milos Dubajic, Xia Liang, Johan Klarbring, Yang Lu, Thomas A. Selby, Erik Fransson, Philippe Holzhey, Benjamin M Gallant, Qichun Gu, Ganbaatar Tumen-Ulzii, Khasim Saheb Bayikadi, Isaiah Gilley, Martin v. Zimmermann, Christian Orr, Chwenhaw Liao, Josh S. Moon, Jacek Jasieniak, Makhsud Saidaminov, Michael P. Nielsen, Tom Wu, Stephen P. Bremner, Anita Ho-Baillie, Julia Wiktor, Paul Erhart, Steve Albrecht, Mercouri Kanatzidis, Henry J Snaith, Aron Walsh, Samuel D. Stranks
Atmospheric and Oceanic Physics
Improving global precipitation forecasts with an AI weather model trained on satellite observations
Julian F. Schmitt, Bertrand Delorme, Robert C. King et al. (+4 more)
Precipitation forecasts shape decision-making across the global economy, particularly in sectors such as agriculture. However, unlike variables such as temperature, precipitation is highly intermittent and localized, making it difficult to forecast. While recent advances in AI weather prediction systems have enabled them to surpass physical models on globally averaged metrics, improvements in mean error rarely translate to actionable forecasts of severe flooding or dry crop fields. Furthermore, most of these models are trained and evaluated against a reanalysis data product, ERA5, which has well-known biases. Here we retrain AIFS, ECMWF's widely-used, open-source operational 0.25{\deg} probabilistic graph-
transformer weather model, on satellite-based precipitation observations. Our model, Laxmi, improves global probabilistic accuracy by 19% and resolves systematic distributional biases in ERA5. Specifically, Laxmi reduces drizzle overprediction by 33% for amounts less than 3 mm per day. It also mitigates extreme rainfall underprediction, improving the global 95th percentile Brier skill score by 57%. Across a case study of 10 Indian tropical storms, Laxmi delivered the most accurate forecast of 150 mm event-total precipitation in 7 events, compared to 1 for AIFS and 2 for the leading physical model, IFS. Our results demonstrate that incorporating observation-based precipitation data directly into training can substantially improve forecasts.
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All authors Julian F. Schmitt, Bertrand Delorme, Robert C. King, Yashica Patodia, Tapio Schneider, Aditi Sheshadri, Ravi Jain
High Energy Physics (Phenomenology)
Quark Mixing Model with Three Higgs Doublets and $S_3$ Modular Symmetry at $\tau=i$
Carlos Cerón and Myriam Mondragón
We study the
quark sector of a model with three
Higgs electroweak doublets, complemented with a modular $S_3$
symmetry. We show that a proper assignment of the
quark and
Higgs fields in $S_3$ and their modular weights allows to write a mass
matrix with a phenomenologically viable texture. Moreover, by considering the conditions on the
Higgs VEVs derived from the minimization of the scalar potential together with evaluation of the Yukawa couplings at the fixed point $\tau=i$, leads to a significant reduction of the free parameters. We present two setups, one with three effective parameters, which is overly constrained, and one with four effective parameters, where the $V_{CKM}$
matrix can be fitted precisely.
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Mathematical Physics
Computational Algorithms for Invariant Reduction of Variational Forms
Kostya Druzhkov and Alexey Shevyakov
Symmetry reductions of partial differential equations (PDEs) inherit more
geometric structures than other types of reductions: invariant conservation laws, variational structures, and, under suitable conditions,
Hamiltonian-type structures of the original model descend to the reduced model through the mechanism of invariant reduction. This paper develops computational
algorithms that carry out such reductions explicitly. We use the interpretation of variational $p$-forms as conservation laws of an enlarged system — the (degree-shifted) tangent system — consisting of the original equations together with their linearizations, in which the perturbation variables are treated as anticommuting. This allows us to formulate the
algorithms using well-known concepts from the theory of conservation laws, naturally adapted to the graded-commutative setting. The reduction of conservation laws, variational $1$-forms, and presymplectic structures thereby becomes a single algorithmic procedure. We present (i) a homotopy-based reduction
algorithm for systems of
evolution equations, implemented in Maple; (ii) a descent reduction
algorithm applicable to general $\ell$-normal systems for $p>0$; and (iii) a simple reduction
algorithm available for point
symmetries under suitable conditions, including the description of reductions in terms of systems involving fewer independent variables. Examples include nonlinear
evolution equations in one and two spatial dimensions, the Laplace equation, the incompressible Euler equations, and the cotangent system of Pavlov's equation.
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Optics
Grammar-based topology search for reconfigurable integrated photonic spectrometers
Juejun Hu
Reconfigurable integrated photonic spectrometers can generate exponentially increasing measurement states from a small number of switching elements, making them a promising design class for high-performance portable spectroscopy. However, selecting a
circuit architecture remains largely intuition driven. We introduce a grammar-based
topology optimization framework that composes standard photonic building blocks, canonicalizes and physically prunes candidate
circuits, and jointly searches
topology and component parameters using a coherent scattering-
matrix model. Designs are screened by a decoder-independent architecture objective that combines absolute singular-value noise gain with multi-line conditioning, thereby accounting for response diversity and optical throughput. Direct held-out spectrum reconstruction confirms that this surrogate is a strong predictor of reconstruction quality at high incident signal-to-noise ratio (SNR). Across the nonresonant and resonator-augmented design spaces examined, dFT and its variants offer the best balanced performance; increased component loss favors a shallower dFT variant in which one differential-delay stage is replaced by an analog optical phase shifter. Passive and active rings provide no robust advantage attributable to resonant amplitude coding. The results identify balanced complementary interferometric responses, efficient terminal collection, and limited lossy
circuit depth as central design rules, and establish a systematic route for selecting task-optimized photonic
circuit topologies under technology-specific constraints.
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Quantum Physics
Experimental validation of a compact fault-tolerant architecture for trapped ions
Noah Berthusen, Ali Lavasani, Asmae Benhemou et al. (+11 more)
Quantum error correction (QEC) is beginning to enable logical operations that outperform their unencoded physical counterparts, but useful fault-tolerant computation will require more than low-error
quantum memory. An effective architecture must orchestrate efficient logical encoding, low-overhead logical operations, and access to the non-Clifford resources required for universal computation. Here, we introduce and experimentally validate such an architecture based on the $[[20,2,6]]$ $C_4$-Helix code, designed for the early fault-tolerant regime. Using Quantinuum Helios, a 98-
qubit trapped-ion
quantum processor, we experimentally demonstrate the principal components of this architecture: we perform repeated
quantum error correction with an error of $4.6^{+6.2}_{-2.6}\times10^{-5}$ per logical
qubit per QEC cycle. We
benchmark the complete Clifford group on the two logical
qubits of a single codeblock under active error correction, obtaining an error of $2.8^{+1.0}_{-1.6}\times 10^{-4}$ per two-
qubit logical Clifford. We further demonstrate a fault-tolerant chain-map interface between $C_4$-Helix and a distance-5 surface code, preparing a heterogeneous three-logical-
qubit GHZ state with a fidelity lower bound of $99.925^{+0.068}_{-0.245}\%$. In each case, the encoded implementation outperforms its corresponding unencoded physical baseline without relying on postselection.
Circuit-level simulations indicate that improvements in physical fidelity bring the same architecture into the $10^{-6}$-$10^{-8}$ logical-error regime targeted for early fault-tolerant computation. Together, these results establish $C_4$-Helix as a hardware-validated fault-tolerant architecture rather than a bare
quantum memory.
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All authors Noah Berthusen, Ali Lavasani, Asmae Benhemou, M.S. Allman, Joan Dreiling, Brian Estey, Cameron Foltz, Trent Jacobs, Michael Mills, Annie Jihyun Park, Adam P. Reed, David Hayes, Tzvetan S. Metodi, Andrew C. Potter
Statistical Mechanics
Generative Nested Sampling of Atomistic Thermodynamic Landscapes
Alessandro Coretti, Nico Unglert, Sebastian Falkner et al. (+2 more)
Nested sampling (NS) resolves the thermodynamics of an atomistic system from a single simulation, but its practical reach is limited by the Markov-chain updates needed to decorrelate walkers within each likelihood-constrained ensemble. Flow-based NS has reduced this bottleneck for gravitational-wave (GW) inference, yet its transfer to atomistic systems is not merely a change of application. Comparing a GW150914-like binary-black-hole likelihood with an eight-particle two-dimensional Lennard-Jones (LJ) system of comparable dimensionality, we show that the two landscapes differ fundamentally: atomistic multimodality is discrete and combinatorial, generated by particle permutations separated by hard collision walls, and its coordinate coupling is dense and collective, whereas the GW posterior exhibits smooth degeneracies and localized parameter coupling. Guided by this diagnosis, we introduce NS-Flows: a single conditional normalizing flow, conditioned on the NS energy bound and trained on a sliding window of recent live sets, that replaces MCMC by direct parallel draws corrected by importance-weighted rejection resampling. Live sets supply the data self-consistently, allowing flow training without structured priors or a pre-existing
dataset. For LJ disks under periodic boundary conditions, the
algorithm can reduce energy evaluations by two orders of magnitude and wall-clock time by about 30%, an advantage that becomes more favorable as the cost of the potential grows. The flow's generative efficiency further acts as a physical diagnostic: it varies non-monotonically along the annealing trajectory, is lowest in the dense disordered regime, and is quantitatively captured by the constrained ensemble's internal mode complexity together with target drift across the training window, identifying
liquid-like ensembles, not prior-target separation, as the hard case for current flow architectures.
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All authors Alessandro Coretti, Nico Unglert, Sebastian Falkner, Georg K. H. Madsen, Christoph Dellago
Medical Physics
Improving Clinical Target Volume Segmentation Accuracy using Anatomical Priors and Active Learning for the AGITG TOPGEAR Clinical Trial
Phillip Chlap, Mark Lee, Trevor Leong et al. (+11 more)
Training deep learning-based medical image
segmentation models is challenging with limited curated
datasets. For AGITG TOPGEAR, a gastric cancer trial, the Clinical Target Volume (CTV) is complex and defined by multiple anatomical landmarks, making upfront training data preparation difficult for an automated contour QA
segmentation model. We investigate anatomical priors, derived from surrounding organ
segmentations, to provide spatial context and improve TOPGEAR CTV
segmentation accuracy. We also evaluate active learning, iteratively expanding the training
dataset by selecting cases expected to improve performance. One hundred TOPGEAR CT scans were retrospectively analyzed. An initial set of 10 expert-contoured cases was used to train an nnU-Net model. TotalSegmentator generated a voxel-wise anatomical prior map from surrounding structures as an additional input channel. Active learning was simulated over four iterations, selecting cases by model uncertainty and
segmentation performance. All models used five-fold cross-validation for an ensemble uncertainty measure. Evaluation used a hold-out testing set of 50 cases. The anatomical prior improved CTV
segmentation accuracy, increasing mean Dice Similarity Coefficient (DSC) from 0.84 to 0.86. Active learning similarly improved performance to 0.86, with greatest benefit in the final round. Combining the anatomical prior with active learning achieved the highest accuracy, with a DSC of 0.87. Model uncertainty correlated with DSC, supporting its use in identifying suboptimal predictions and guiding active learning. Anatomical priors and active learning each improved CTV
segmentation accuracy and generalizability, with their combination achieving the best performance, supporting integration into
segmentation model development for automated contour QA in radiotherapy clinical trials.
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All authors Phillip Chlap, Mark Lee, Trevor Leong, Matthew Field, Jason Dowling, Hang Min, Julie Chu, Jennifer Tan, Phillip K. Tran, Tomas Kron, Annette Haworth, Martin A. Ebert, Shalini K. Vinod, Lois Holloway
Plasma Physics
Hall-MHD in driven turbulence FLASH simulations
A. Mohapatra, E. C. Hansen, A. Reyes et al. (+3 more)
The origin of
magnetic fields in turbulent astrophysical systems has long been a central problem in
plasma astrophysics. Fluctuation dynamos are a class of field amplification mechanisms that occur in turbulent magnetohydrodynamics whereby stochastically forced motions of
plasma at sufficiently high
magnetic Reynolds numbers exponentially amplify
magnetic energy. For steady forcing, such dynamos saturate with
magnetic energies at a sizable fraction of the turbulent kinetic energy. Although fluctuation dynamo is widely studied within the framework of resistive magnetohydrodynamics (MHD) and driven-
turbulence numerical simulations, this work explores the difference when the
Hall term is included in the magneto-fluid's generalized Ohm's law. The inclusion is motivated in part by recent high energy-density
plasma experiments studying fluctuation dynamo that are governed by an extended magnetohydrodynamics (xMHD) ansatz, which includes the
Hall term. We first discuss the details of the
Hall-MHD implementation in the FLASH code, the tool we use to model xMHD fluctuation dynamo. We then investigate the influence of the
Hall term on the fluctuation dynamo in a three-dimensional periodic box, driven with
stochastic forcing at the box scale. We compare cases with a
Hall term of varying magnitude to no-
Hall cases with respect to the
magnetic field growth rate, saturation level, and
magnetic field structure. The
Hall-MHD fluctuation dynamo is found to saturate at lower
magnetic energies and with fewer small-scale
magnetic structures than the no-
Hall cases. Both findings are consistent with the interpretation that the
Hall term acts as an additional, non-linear transport term, akin to an enhanced turbulent diffusivity.
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All authors A. Mohapatra, E. C. Hansen, A. Reyes, A. F. A. Bott, E. G. Blackman, P. Tzeferacos
Statistical Mechanics
Accelerating stochastic processes through nonequilibrium driving: Thermodynamic constraints on the maximum speed-up
Davide Santolin and Gianmaria Falasco
We derive a new set of bounds controlling the speed-up of the survival rate of trajectory-dependent observables induced by the application of a perturbation. Via the study of survival probabilities in two different contexts, continuous-time Markov jump processes and overdamped
diffusions, we obtain different fashions of the bound on the achievable boost. These bounds, obtained by a nonlinear response theory of constrained path probabilities, are explicitly linked to thermodynamics. For arbitrary time-dependent survival rates, we find a linear bound that depends on both the perturbation strength and the
entropy production rate prior to the perturbation. For rare processes characterized by a constant survival rate, the bound is exponential and is determined by the excess heat generated by the perturbation. We exemplify the inequalities on two prototypical model systems, namely, a unicyclic network and forced
diffusion in a bistable potential.
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Materials Science
An Ultrathin Laterally Conductive Mesh Interphase Enables Spatially Extended Zinc Deposition for Aqueous Zinc Batteries
Yirong Zhao, Xingyuan Chu, Bing Wu et al. (+15 more)
Zn metal anodes often suffer from nonuniform interfacial reactions during cycling, resulting in uneven deposition and dendrite growth. Existing artificial interphases can mitigate side reactions or regulate nucleation, but rarely achieve regulation of the interfacial electron/field distribution to sustain uniform deposition at the evolving Zn/electrolyte interface. Here, we develop an Au mesh interphase (AuMI), an ultrathin two-dimensional Au aerogel network that couples lateral electron redistribution with open pathways for ions. During Zn plating/stripping, the conductive AuMI distributes electron transport across the Zn surface, while its porous mesh preserves Zn$^{2+}$ access, enabling more uniform interfacial reactions. Experiments and simulations show that AuMI homogenizes the interfacial electric field and current distribution, promotes more uniform Zn plating/stripping, and limits dendrite growth. As a result, this regulated interfacial reaction mode enables AuMI Zn symmetric
cells to operate stably for 3000 h at 1 mA cm$^{-2}$/1 mAh cm$^{-2}$ and for 1100 h at 10 mA cm$^{-2}$/10 mAh cm$^{-2}$, while AuMI Zn||NVO (NaV$_3$O$_8$\cdot$1.5H$_2$O) full cells retain 80.8 % capacity after over 5000 cycles at 1 A g$^{-1}$. These findings highlight the importance of combining ultrathin architecture, lateral electron transport, and open Zn2+ access in artificial interphases for stable aqueous Zn metal anodes.
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All authors Yirong Zhao, Xingyuan Chu, Bing Wu, Pavel Khavlyuk, Johannes Kresse, Yue Dong, Jingwei Du, Xinmei Song, Songshan Bi, Vlastimil Mazanek, Xia Wang, Xiaodong Li, Shilei Liu, Shuangying Wei, Jan Luxa, Junming Zhang, Zdenek Sofer, Alexander Eychmuller
Mesoscale and Nanoscale Physics
Topological Boundary States and the Edge Chain in Semi-Infinite Two-Dimensional Insulators
Ilya Iakoub, Nicolas Levasseur and Richard MacKenzie
We show that it is possible to compute the adiabatically protected edge and corner states of semi-infinite, two-dimensional, topological
insulators by considering the first layer of
lattice sites, what we call the "edge chain," independently from the bulk. We start by accepting this claim as an ansatz, then, using the Shemesh
theorem, we show that the edge states one finds using our procedure are adiabatically protected, provided we restrict ourselves to adiabatic evolutions that do not break
chiral symmetry. We show explicit examples of our method in a 2D extension of the SSH model, the SSH3 model, the Haldane model and the Breathing Kagome
Lattice.
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Chemical Physics
Stochastic Tensor Contraction for Efficient MP2 Exchange
Jiace Sun and Garnet Kin-Lic Chan
Second-order Moller–Plesset perturbation theory (MP2) is one of the simplest correlated wave-function methods, but its conventional $O(N^5)$ cost limits its application to large systems.
Stochastic tensor contraction (STC) has recently appeared as a general technique to evaluate high-order tensor contractions in
quantum chemistry. Here, we apply STC to the exchange contribution of Laplace-transformed MP2, which is the source of $O(N^5)$ scaling in the formulation. The resulting STC exchange
algorithm has an $O(N^3)$ deterministic setup cost and an $O(N^2)$
stochastic cost at fixed absolute error. The
estimator is unbiased and provides a way to specify the target
stochastic error by estimating the number of required samples before the full calculation. We implement the
algorithm using a hybrid deterministic–
stochastic evaluation strategy, with grouped index sampling, to reduce the computational prefactor. Over a range of
benchmark molecules containing up to $\sim 7000$ basis functions, the
stochastic exchange evaluation takes as little as $1/270$ of the time of a complete DF-MP2 calculation on the same system. Within the Laplace-transformed formulation, the $O(N^4)$ scaling direct contribution is thus the only significant cost. Our results further substantiate the power of STC to serve as a general tensor-contraction engine for
quantum chemistry.
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Astrophysics of Galaxies
Multi-tracer exploration of molecular gas in main sequence galaxies at z~4.5
M. Dessauges-Zavadsky, M. Béthermin, M. Ginolfi et al. (+15 more)
Molecular gas masses in high-z
galaxies are inferred from indirect tracers, whose respective reliability remains poorly constrained. In particular, the bright [CII] 158$\mu$m line is now widely used as a molecular gas tracer at z>4, yet direct observational tests against CO remain scarce. We search for CO(4-3), CO(5-4), and [CI](1-0) lines in three of the most [CII]-luminous
galaxies at z~4.5 from the ALPINE survey to assess the detectability of these lines in high-z main-sequence (MS)
galaxies and to test the reliability of [CII] emission as a molecular gas tracer through the cross-comparison of molecular gas masses inferred from six tracers: CO(4-3), CO(5-4), [CI](1-0), [CII],
dust continuum, and [CII]-based dynamical mass, adopting standard calibrations and conversion factors. We detect CO(4-3) and CO(5-4) lines at high significance in the near-
solar metallicity galaxy DC873756, obtain a tentative CO(4-3) detection in the merging system DC818760, and detect no CO emission in the half-
solar metallicity galaxy VC5110377875. [CI] remains undetected in all three
galaxies. In DC873756 the molecular gas masses inferred from the six considered tracers agree within their uncertainties despite different systematics inherent to each tracer. The agreement suggests that, at least for some near-
solar metallicity MS
galaxies at z~4.5, the CO SLED and Milky Way CO-to-H2 conversion factor adopted for MS
galaxies at
cosmic noon remain applicable and that mid-J CO transitions trace a substantial fraction of the molecular gas reservoir. The CO non-detection in VC5110377875 is consistent with the reduced CO detectability expected at lower
metallicities. In DC818760 we find an inconsistency between the [CII]-based molecular gas mass and masses derived from the other tracers, indicating a [CII] excess possibly reflecting enhanced emission from shocks and/or diffuse ionized gas in merger-driven conditions.
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All authors M. Dessauges-Zavadsky, M. Béthermin, M. Ginolfi, L. Vallini, A. Faisst, M.-Y. Xiao, F. Pozzi, P. Cassata, Y. Fudamoto, C. Gruppioni, G. C. Jones, M. Kohandel, G. Rodighiero, M. Romano, P. Theulé, G. Zamorani, C. Accard, C. Guillaume
Instrumentation and Methods for Astrophysics
The Accretion Explorer Interferometer (AEI) Phase I NASA Innovative Advanced Concepts Final Report
Kimberly A. Weaver, Jenna M. Cann, Kenneth Carpenter et al. (+30 more)
We must create superb X-ray images to understand the detailed physical processes behind some of the most powerful astronomical objects. The need to achieve this capability has been known for decades. But as time proceeds, X-ray astronomy falls further behind other wavebands that are steadily increasing their imaging capacity.
Radio astronomy in particular has reached an angular resolution on the order of micro arcseconds via aperture synthesis interferometry, using the interference of electromagnetic waves from many small
telescopes together to simulate having a much larger
telescope. Developing an equivalent high-resolution capability in the X-ray band would be a game changer for high-energy astrophysics. We will understand how supermassive black holes grow and evolve. We will learn what powers astrophysical jets. We will learn how young, active
stars affect the habitability of their
planets. Technologically, our NIAC study has shown that the
Accretion Explorer Interferometer (AEI) concept, unlike the original MAXIM concept, is more feasible in operation, being only 2 km long, versus approximately 450 km. Our study has also shown that satellite station keeping is possible, leveraging from LISA pathfinder technology, and using large mirror flats plus an X-ray beamsplitter for enabling technology is feasible.
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All authors Kimberly A. Weaver, Jenna M. Cann, Kenneth Carpenter, Maurice Leutenegger, Takashi Okajima, Scott Rohrbach, Liz Matson, Craig Stevens, George Bussey, Jean-Etienne Dongmo, David Kim, Jess Lewis, Khashayar Parsay, Sharon Peabody, Alison Rao, Sara Riall, Marta Shelton, Kan Yang, Isabella Carlton, Webster Cash, Kaylee DeGennaro, Emma Kleiner, John Krizmanic, Erini Lambrides, Miranda McCarthy, Jeffrey McKaig, Atul Mohan, Teresa Monsue, Ryan Pfeifle, Mainak Singha, Melville Ulmer, Laura D. Vega, Kelly E. Whalen
High Energy Astrophysical Phenomena
Observational selection effects on radio pulsars are minimal for masses, but significant for orbits and spins
Lisa V. Drummond, Katerina Chatziioannou and Emmanuel Fonseca
The masses of
Galactic pulsars in binaries measured through
radio timing point to structure in the mass distribution with implications for dense matter and astrophysical formation processes: a bimodal shape with peaks at ${\sim} 1.3\,M_\odot$ and ${\sim} 1.6\,M_\odot$, with a cutoff above ${\sim}2\,M_\odot$. However, this observed population of
radio pulsars is shaped not only by intrinsic
pulsar properties, such as birth masses, binary evolutionary pathways and dense-matter constraints, but also by observational effects. In existing catalogs of
pulsar mass measurements, observational selection effects influence (i) which systems are detected in the first place (detectability) and (ii) which systems yield well-measured masses (measurability). In this work, we revisit the
radio pulsar population distribution in the context of observational effects associated with
pulsar radio timing. Simulating systems of
radio pulsars and timing observations, we track the process by which a given system ends up in an observational
dataset and estimate the impact of the binary and
pulsar parameters. We fold this selection function into hierarchical population inference and extract the intrinsic astrophysical distribution of
pulsars observed with
radio timing. We jointly infer the populations of
pulsar mass, companion mass, orbital eccentricity, orbital period and
pulsar spin period. Selection effects have minimal impact on the mass distributions, but more significantly affect other parameters. The ratio of circular-to-eccentric systems shifts from an observed $1\!:\!1$ to an astrophysical, selection-corrected $2\!:\!1$ ratio, while the true population is shifted toward longer orbital and
spin periods than observed.
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Computational Physics · Cross-listed from math.NA
A discontinuous Petrov-Galerkin finite-element framework for the simulation of microwave-heated flows
Oreste Marquis, Matthias Maier and Bruno Blais
We present a high-order multiphysics solver for the simulation of microwave-heated flows. The solver couples a discontinuous Petrov-Galerkin (DPG) finite element method for the time-harmonic Maxwell equations with continuous Galerkin finite element methods for the heat equation and the incompressible Navier-Stokes equations. We validate the electromagnetic solver against multiple
benchmark problems: wave propagation in a rectangular waveguide, a cavity problem with a singular solution, and a microwave-heated obstacle problem, comparing our results against numerical and experimental data from the literature. The results confirm the validity of the implementation and demonstrate its ability to perform adaptive mesh refinement using the DPG method's built-in error
estimator. The final part of the study showcases the capabilities of the multiphysics framework through simulations of microwave-heated flow around obstacles with singular
geometric features. These results highlight the potential of the proposed framework for the simulation and optimization of microwave-assisted chemical processes. Finally, the developed high-order multiphysics solver has a low
memory footprint, since the electromagnetic solver relies on a Conjugate Gradient (CG) iterative solver and the fluid solver is implemented in a
matrix-free fashion, making the overall approach scalable and well-suited for large-scale parallel simulations.
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High Energy Physics (Theory) · Cross-listed from math.AG
Experiments with membranes, maps and sheaves
Daniel Holmes and Yannik Schuler
Motivated by the conjectural existence of M-theory, we investigate a web of correspondences between enumerative invariants of a Calabi-Yau fivefold $Z$ with a
torus action. This includes a correspondence between the fivefold Gromov-Witten invariants and K-theoretic Pandharipande-Thomas invariants of a threefold $X \subset Z$, mediated by so-called membrane indices, which generalise Gopakumar-Vafa invariants. We establish the correspondence for strip geometries for restricted
torus actions and test it numerically for general
torus actions. Further numerical evidence is provided for the closed vertex, local surfaces and local projective spaces. For the latter we present conjectural formulae for their low-degree membrane indices. When the fivefold is the product of the affine plane with a suitable toric variety, we prove
geometric engineering and equate the generating series of Pandharipande-Thomas invariants with the corresponding instanton partition function while equality with the Gromov-Witten series is probed numerically.
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Chemical Physics
Overlimiting Ion Transport and Reaction Limitations in Charged Porous Media
Arjun V. Yennemadi, Junghyun Yoon and Martin Z. Bazant
Electrochemical reaction rates are controlled by both interfacial charge-transfer kinetics and reactive-ion transport. In charged porous media, fixed charges enrich reactive counterions near pore walls, enabling transport beyond the classical
diffusion limit via surface conduction (SC). Under overlimiting conditions, classical Butler-Volmer kinetics predict indefinitely increasing current with overpotential, contrasting with microscopic electron-transfer theories, which impose a finite reaction-limited current. Here, we couple the one-dimensional leaky membrane model to coupled ion-electron transfer (CIET) kinetics to examine the interplay between transport and reaction limitations. The limiting behavior is governed by the scaled surface charge $(\tilde{\rho}_s)$ and a Damköhler number $(Da)$ comparing reaction-limited and
diffusion-limited currents. We derive analytical limiting-current expressions for neutral, positive, and negatively charged porous media, mapping underlimiting-to-overlimiting transitions in the $(Da,\tilde{\rho}_s)$ plane. By preventing reactive-ion depletion, SC restores polarization-curve sensitivity to charge-transfer kinetics that would otherwise be obscured by
diffusion limitation. Fitting to published Cu electrodeposition data in charged AAO membranes yields $Da\approx24$. CIET parameters fitted to AAO($-$) also describe AAO($+$) and predict a finite AAO($-$) reaction limit beyond the applied voltage range. These results provide a framework for distinguishing transport-limited and reaction-limited responses in electrochemical systems and establish charged porous media as platforms to reveal electrochemical reaction-kinetic descriptors.
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Earth and Planetary Astrophysics
Evolutionary pathways toward survival of a thick CO2- or SO2-rich atmosphere on the lava world TOI-561 b
Emma Postolec, Tim Lichtenberg, Johanna K. Teske et al. (+10 more)
Rocky
planets evolve through the exchange of volatiles between their interiors and atmospheres, an interplay still poorly constrained by observations. Remarkably, highly irradiated ultrashort-period (USP)
exoplanets may offer a window into this exchange – some retain low bulk densities compatible with volatile-rich envelopes surrounding rocky interiors, indicating possible secondary atmospheres. TOI-561 b is a
prime example, with a bulk density of $4.3\pm0.4$ g cm$^{-3}$ and recent JWST observations favoring a thick volatile atmosphere overlying a dayside magma ocean. Here, we investigate the evolutionary pathways allowing TOI-561 b to retain a substantial atmosphere over gigayears using the PROTEUS coupled interior–atmosphere framework. We explore different core radius fractions, Bond albedos, atmospheric escape efficiencies, mantle redox states, and initial C–H–O–N–S volatile inventories, under in situ
evolution and late inward migration. Over half of our simulations leave a bare interior too dense to match observations. Successful cases favor a volatile-rich origin ($\lesssim200$ Earth oceans of hydrogen, S/H $\le10$, and N/H $\le1$), an oxidized mantle ($f$O$_2 \gtrsim \mathrm{IW}+4$), a small iron core ($\le 0.40$ for the core radius fraction), and low escape efficiency ($\epsilon \lesssim 10^{-3}$) in the hydrodynamic escape regime. At present, TOI-561 b is consistent with a global magma ocean beneath a thick (surface pressure $\approx 10^{3}$–$10^{4}$ bar), high mean molecular weight atmosphere ($38$–$60$ g mol$^{-1}$). Two archetypes emerge, differentiated by bulk sulfur content: a CO$_2$-dominated and an SO$_2$-dominated atmosphere. Migration is viable but not required to reproduce the observations. Our study illustrates how interior–atmosphere coupling governs atmospheric retention on irradiated rocky
planets.
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All authors Emma Postolec, Tim Lichtenberg, Johanna K. Teske, Harrison Nicholls, Mara Attia, Anjali Piette, Lisa Dang, Nicole L. Wallack, Mykhaylo Plotnykov, Alex McGinty, Samuel Boucher, Bo Peng, Diana Valencia
High Energy Astrophysical Phenomena
Thermal and non-thermal emission from supermassive black hole circumbinary disks: Disks, Coronae, Streams, and Cavities
Chris Nagele, Julian H. Krolik, Brooks E. Kinch et al. (+2 more)
The search for electromagnetic signals from supermassive black hole (SMBH) binary systems is one of the cornerstones of multi-messenger astrophysics, complementing gravitational wave observations of such systems by
pulsar timing arrays and LISA. Although extensive simulations have been run to understand the time variability of the bolometric luminosity from accreting binary SMBH systems, comparatively few spectral predictions have been made, and none that go beyond simple emission models. In this paper, we post-process a HARM3D simulation snapshot of a binary at $20 M$ separation accreting at 0.01 Eddington. For black hole masses $10^6$, $10^7$, and $10^8\, M_\odot$, we self-consistently solve for the radiated spectrum on the basis of time-steady radiation transfer, thermal balance, and ionization
equilibrium, including all relevant relativistic effects as well as emission and absorption processes. Although most of the bolometric luminosity is radiated thermally by the disk, the low density regions evacuated by the binary's quadrupole moment produce copious X-rays, with $\sim40\%$ of the observed luminosity in a soft X-ray power law ($\Gamma = 2.3$). We identify two modes of observed azimuthal variation. The X-ray continuum varies by $\sim10\%$ due to an underlying asymmetry in the gas temperature of spiral shocks in the disk. The Fe~K$\alpha$ equivalent width dips by $\sim25\%$ when the line of sight to the inner disk is partially obscured by the lump. These two effects share the same period and are $\sim \pi/2$ out of phase; the period is order days to weeks for typical AGN masses and a 20$M$ separation.
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All authors Chris Nagele, Julian H. Krolik, Brooks E. Kinch, Jeremy D. Schnittman, Scott C. Noble
Strongly Correlated Electrons
Antiferromagnetism-altered plasmon dynamics
Yifan Su, Suheng Xu, Rocco A. Vitalone et al. (+17 more)
The interaction between plasmons and
magnons is a long-sought phenomenon with implications for fundamental physics and spintronics applications. In three-dimensional systems, this coupling is suppressed by the large mismatch in energy scales, but two-dimensional (2D) plasmons with gapless dispersion can overlap with
magnons over a broad spectral range. Despite numerous theoretical predictions, experimental observation of
magnon-plasmon interaction has remained elusive. In this work, we study a first-of-its-kind hybrid plasmon-
magnon platform based on 2D materials. By deploying scattering-type scanning near-field optical microscopy (s-SNOM) with terahertz radiation, we image propagating plasmon wavepackets at a
graphene/NiPS$_3$ interface and track their dynamics across the
antiferromagnetic transition of NiPS$_3$. We observe a clear renormalization of the plasmon-polariton dispersion concurrent with the onset of
antiferromagnetic order. With complementary Raman scattering and nano-terahertz spectroscopy, we unveil spectral weight redistribution and dielectric screening changes, potentially associated with the multi-
magnon continuum, as the underlying mechanism. These results provide solid evidence of coupling between plasmon and
antiferromagnetic order, marking a cornerstone for a potential platform for hybrid
magnon-plasmon interactions in 2D materials, opening avenues for coherent
spin-plasmon devices and tunable terahertz spintronic components.
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All authors Yifan Su, Suheng Xu, Rocco A. Vitalone, Ziyu Liu, Emil Viñas Boström, Na Wu, Chun-Ying Huang, Zhuquan Zhang, Jaehoon Jung, Daniel G. Chica, Vinícius da Silveira Lan Avelar, Yiping Wang, Takashi Taniguchi, Kenji Watanabe, James C. Hone, Xiaoyang Zhu, Cory R. Dean, Xavier Roy, Angel Rubio, D. N. Basov
Plasma Physics
MGKDB: An IMAS-aligned multicode gyrokinetic simulation database for reproducible fusion turbulence modeling and data-driven analysis
Craig Michoski, David R. Hatch, Dongyang Kuang et al. (+14 more)
Expensive fusion simulations are commonly preserved in code-specific formats that limit discovery, comparison, and reuse. We present the Multiscale GyroKinetic DataBase (MGKDB), an open-source software framework and curated archive that converts heterogeneous simulation campaigns into traceable scientific records. Each record links code-native inputs and outputs to provenance and quality metadata, an IMAS-aligned physics representation, and derived diagnostics, preserving model-specific evidence while enabling common-field queries. Production pathways support linear and nonlinear GENE and CGYRO calculations and reduced quasilinear TGLF evaluations. At the September 1, 2026 snapshot, MGKDB contained 1,068,089 records, nearly all of which included a populated gyrokinetics IMAS branch. The software is openly available, while access to the NERSC-hosted production records is managed. Three demonstrations show how these linked representations support scientific reuse. Standardized quantities stored in the Diagnostics branch enable population-scale analysis of archived linear modes; common input coordinates reveal coverage, redundancy, and campaign-driven sampling structure across a multicode collection; and record-level
retrieval of native CGYRO inputs drives matched TGLF calculations and produces a traceable
dataset for exploratory surrogate modeling. Together, these examples demonstrate how MGKDB supports archive characterization, candidate cross-code and cross-fidelity comparisons, campaign planning, and reproducible data-driven modeling without treating different models as automatically equivalent.
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All authors Craig Michoski, David R. Hatch, Dongyang Kuang, Matthew Waller, Chris Holland, M.J. Pueschel, Joseph McClenaghan, Tom F. Neiser, Max T. Curie, Venkitesh Ayyar, Joseph Schmidt, Leonhard A. Leppin, Aaron Ho, Nathan T. Howard, Tapan Ganatma Nakkina, Bhavin Patel, Yann Camenen
Medical Physics
Beyond Dose in Boron Neutron Capture Therapy: Cellular $^{10}$B-Capture Statistics and Microdosimetric Context in Effect Prediction
Shuichi Furuya and Atsushi Fujimura
Boron
neutron capture therapy (BNCT) produces high-linear-energy-transfer, short-range particles through the $^{10}$B(n,$\alpha$)$^{7}$Li reaction. Conventional descriptors, including absorbed dose, compound biological effectiveness (CBE)-weighted dose, and
photon-isoeffective dose ($D_{\mathrm{isoE}}$), remain clinically useful but compress cellular heterogeneity, compartmental boron localization, and
stochastic reaction occurrence into macroscopic summaries. We propose a hierarchical framework that places
cell-associated $^{10}$B-capture reaction statistics upstream of microdosimetric effect modeling and links clinical observations to cellular-scale determinants of BNCT response. We synthesize published work on BNCT microdosimetry, CBE and $D_{\mathrm{isoE}}$,
stochastic microdosimetric kinetic modeling, PHITS-based cellular simulations, boron imaging, tissue microstructure, and boron-
agent characterization, reorganizing these elements into observational, latent-cellular, reaction-count, and biological-effect layers. Imaging, pathology,
agent-specific data, and
neutron-field information constrain latent variables such as cellular boron burden, compartmental localization, and geometry; these variables determine expected reaction burdens and distributions of realized reaction counts, which are then translated into
cell survival, tumor control, or normal-tissue injury by microdosimetric models.
Cell-associated reaction-count statistics thus provide an interpretable inferential bridge between macroscopic measurements and established BNCT effect models, supporting spatially resolved and uncertainty-aware effect prediction without replacing existing approaches based on CBE, $D_{\mathrm{isoE}}$, SMK, or PHITS.
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