Soft Condensed Matter
Contact-mediated asymmetric delay and rate memory in snapping beam pairs
Gavin Linton, Shima Mahmoudirad, Nidhi Pashine et al. (+1 more)
Slender structures in dense environments interact through contact, which alters how and when they become unstable. Here we show that contact makes snap-through history dependent, so that when and whether a beam pair snaps depends on how long the contact is loaded. Under cyclic compression, the pair snaps on loading, snaps on unloading, or stays packed, with the loading and unloading rates selecting among the three. Upon contact, one beam rolls along the other without slip, and faster driving lets it roll further before it slides and snaps: to larger compression on loading and to smaller compression on unloading. This delay is asymmetric between loading and unloading as the unloading branch carries a
memory of the loading rate. Interestingly, above a threshold compression the pair snaps even when the compression is stopped, with the time to snap diverging at that threshold. By exploiting this asymmetric, rate-dependent delay, we program ordered sequences of snap events in arrays of pairs with tunable gaps, and demonstrate that the energy dissipated per cycle becomes a two-parameter function of the loading and unloading rates, increasing fourfold when, at the fastest loading, the return is slowed.
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All authors Gavin Linton, Shima Mahmoudirad, Nidhi Pashine, Anupam Pandey
Optics
Observation of quadrature-dependent unidirectional flow of light
Jamison Sloan, Eran Lustig, Louise Schul et al. (+5 more)
Unidirectional transport of light is a central capability in photonics, enabling critical functionalities such as isolation and routing. Ordinarily, this directionality depends on the mode of light, but not its phase. In this work, we experimentally demonstrate phase-dependent unidirectional transport of light for the first time. Specifically, we realize a system where conjugate quadratures of an optical field decouple and propagate in opposite directions. Our all-optical approach uses multiple pump frequencies in a high-$Q$ nanophotonic micro-resonator to achieve
Hamiltonian programming through Kerr nonlinearity. Even though we rely on optical nonlinearity, our approach is not limited to any minimal power requirement on the signal. We demonstrate the ultimate limit of this by measuring the effect of quadrature-dependent transport on
vacuum fluctuations. Our approach unlocks a fundamental new capability for controlling light, and can enable previously inaccessible regimes of phase-sensitive directional amplification, sensing, and routing.
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All authors Jamison Sloan, Eran Lustig, Louise Schul, Trung Kien Le, Melissa A. Guidry, Daniil M. Lukin, Shanhui Fan, Jelena Vučković
Quantum Physics · Cross-listed from eess.IV
Generative Quantum Machine Learning Methods for Cancer Detection using Augmented Datasets
Sophia Knutson, Nandika Goyal, Gennaro De Luca et al. (+3 more)
Cancer detection using AI methods and image databases faces several challenges, including limited and imbalanced image
datasets, long
algorithm training times, and high-complexity feature generation. In particular, many cancer image
datasets contain very few malignant examples compared to benign ones, limiting the amount of minority-class data available for training. Although classical AI and especially deep learning methods have had some success in providing cancer diagnostics,
Quantum Machine Learning (QML) methods may offer advantages through high-dimensional feature representations, generative data augmentation, and the exploitation of feature correlations through
quantum properties such as
entanglement. In this paper, we propose using a generative QML method on the compressed breast ultrasound image
dataset (BUSI) to generate synthetic images and hence augmented
datasets for classifier training. In particular, we train a convolutional neural network with real, synthetic, and a combination of real and synthetic images. We test the
algorithm on real images and provide comparative results for all three training cases. Our results show that the classifier trained entirely on synthetic images achieved an AUC-ROC of 0.802 (80.2%), compared with 0.760 (76.0%) for the real-data baseline.
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All authors Sophia Knutson, Nandika Goyal, Gennaro De Luca, Glen Uehara, Tanay Kamlesh Patel, Andreas Spanias
Optics
Resonant dispersive wave emission: a route toward few-cycle, tunable strong-field drivers in the visible
Martin Gebhardt, Joleik Nordmann, Nikoleta Kotsina et al. (+4 more)
Intense ultrafast
lasers are the backbone of strong-field physics and enable table-top scale applications of coherent high-
photon energy radiation through high-harmonic generation (HHG). Using short-wavelength drivers in HHG promises highly efficient conversion into the extreme ultraviolet, but short pulse durations are essential to this approach. We generate multi-GW peak power, sub-10 fs pulses in the visible with broad spectral tunability (220–752 nm) by harnessing
soliton dynamics in large-core, gas-filled capillary fibers for high-energy resonant dispersive wave emission. This establishes the potential of resonant dispersive waves as a new class of driving
lasers for HHG and strong-field physics in addition to widespread applications in ultrafast spectroscopy.
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All authors Martin Gebhardt, Joleik Nordmann, Nikoleta Kotsina, Michael Heynck, Teodora Grigorova, Christian Brahms, John C. Travers
General Relativity and Quantum Cosmology
Non-Commutativity in Geodesic Congruences
Aarav Shah and Louis H. Kauffman
We propose a
geometric realization of spacetime non-commutativity where the spacetime
manifold remains smooth while the commutation relation between tangent and separation vectors of geodesic congruences is generalized via Frobenius'
theorem. This non-commutative kinematic deformation leads to a modified Raychaudhuri equation with a shifted expansion scalar $\tilde \theta=\theta+\theta^{\rm NC}$. We introduce a timelike and null-like Non-Commutative Energy Condition (NCEC) under which focusing and geodesic incompleteness can, in some regimes, persist even when the standard strong energy condition is violated. Using this, we generalize the key focusing lemmas, conjugate-point propositions, and singularity
theorems for both timelike geodesics orthogonal to a Cauchy surface and null geodesics orthogonal to a trapped surface. Applied to a FLRW spacetime, we argue that $\theta^{\rm NC}$ modifies both the Friedmann acceleration equation and the continuity equations. The non-commutative corrections separate into a universal modification of the dilution of the standard cosmological fluids and another contribution to the dark energy sector that is non-linear in energy density. Crucially, this provides a purely
geometric origin for the
evolution of dark energy, without introducing exotic dark energy fields or modifying Einstein's field equations.
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High Energy Physics (Phenomenology)
Theoretical calculations for $t{\bar t}H$ production
Nikolaos Kidonakis and Nodoka Yamanaka
We calculate higher-order perturbative corrections for $t{\bar t}H$ production. By adding second-order and third-order soft-gluon corrections to NLO QCD and NLO electroweak (EW) results, we present total and differential cross sections at LHC energies through approximate N$^3$LO (aN$^3$LO) in QCD and NLO in EW. Our aN$^3$LO QCD + NLO EW results provide significant enhancements and a reduced scale dependence for the cross section and the top-
quark transverse-momentum and rapidity distributions.
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High Energy Physics (Phenomenology)
BSMScanner: a lightweight framework for beyond-the-Standard-Model global fits
Mohamed Belfkir
We present BSMScanner, a framework in which a beyond-the-Standard-Model (BSM) parameter scan is specified as a set of declarative YAML documents rather than written as a program. The user declares the free parameters and their priors, the mass
matrices and the diagonalisations that act on them, the observables, the theory-validity conditions and the likelihood terms. The framework validates this specification, resolves it into a dependency graph and compiles it once into a typed C++ evaluation kernel, which is then driven by an independently chosen scanning engine: uniform sampling, two differential-
evolution engines, or a staged basin-discovery orchestrator, optionally followed by Markov-chain posterior refinement. Flavour physics
matrix diagonalisation, PMNS and CKM construction in fixed conventions, tabulated oscillation likelihoods and a library of common flavour observables are provided by the framework and imported by name, so that a model file contains only model-specific definitions; quantities without a closed form, such as a relic density, enter through a C++ or Python plugin interface. We describe the specification schema, the observable and likelihood library, the scanning engines and their configuration, and demonstrate the framework on six
benchmark models with $4$ to $26$ free parameters, giving for each the specification, the scan configuration, the resulting best fit and analytic cross-checks of the result.
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Plasma Physics
Plasma-neutral collision operators for hydrogen isotopes: kinetic and gyrokinetic descriptions, comparison to fluid
Matthieu Protais, Guilhem Dif-Pradalier, Yanick Sarazin et al. (+4 more)
Plasma-neutral interactions critically affect the edge dynamics of magnetically confined fusion devices. Neutral atoms modify ion and electron velocity distributions, potentially affecting local instabilities Standard fluid models simplify these processes (namely charge exchange, ionization and recombination) using Maxwellian assumptions and linearized source terms. We revisit these assumptions for a hydrogen
plasma interacting with hydrogen atoms. We derive
plasma-neutral interaction terms in the kinetic and gyrokinetic frameworks. Accounting for velocity-dependent differential cross-sections, the model captures the kinetic impact of inelastic collisions on ions and electrons beyond energy and momentum exchange. We demonstrate that the fluid moments of the kinetic model reduce to standard fluid source terms under the appropriate assumptions of Maxwellianity and linearity. We compare the kinetic model with fluid models through their effects on distribution functions and fluid moments. Substantial discrepancies are observed, even for Maxwellian distributions. For charge exchange, the kinetic model yields momentum and energy exchange rates up to twice those predicted by fluid descriptions. We show that a fluid treatment of ionization greatly overestimates the mean kinetic energy of the produced electrons. These results highlight the limitations of fluid descriptions and the importance of kinetic effects in edge-
plasma momentum and energy exchange.
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All authors Matthieu Protais, Guilhem Dif-Pradalier, Yanick Sarazin, Virginie Grandgirard, Yannick Marandet, Srikanth Sureshkumar, Naren Varadarajan
Materials Science
Role of defect trapping in the enhanced corrosion resistance of Ni-Mo alloys with yttrium and yttrium oxide additions
Jia-Hong Ke, Xinchang Zhang, Jingfan Yang et al. (+3 more)
Corrosion of structural
alloys remains a critical challenge for advanced molten salt reactors, where aggressive fluoride salts promote continuous dissolution at the salt-metal interface. While most mitigation strategies emphasize thermodynamic stability, kinetic control of atomic transport has received comparatively less
attention. Here, we propose a corrosion mitigation strategy based on
diffusion control and vacancy trapping by dilute yttrium (Y) solutes and yttrium oxide (Y$_2$O$_3$) dispersions in Ni
alloys. A combined computational and experimental approach integrates density functional theory (DFT), self-consistent mean-field (SCMF)
diffusion modeling, and an impurity trapping model to quantify the impact of defect trapping on effective vacancy mobility. Strong first-nearest-neighbor vacancy-Y binding, off-
lattice vacancy configurations, and elevated rotational and dissociation barriers result in pronounced suppression of vacancy diffusivity, while Y$_2$O$_3$-associated sites treated as fixed traps in the model further reduce the mobile vacancy population. Ni-Mo (NM), Y-modified (NMY), and Y$_2$O$_3$-containing (NMYO)
alloys were tested in molten fluoride salt at 750{\deg}C. Corrosion penetration decreases systematically from NM to NMY to NMYO, consistent with the predicted reduction in vacancy-mediated transport. The same trend is observed in mass change, with net weight loss decreasing from 0.52% for NM to 0.23% for NMY and 0.09% for NMYO. These results are consistent with an
alloy-side transport contribution from defect trapping and reduced atomic transport. This study therefore suggests point defect engineering as a promising
alloy design strategy for extreme nuclear environments.
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All authors Jia-Hong Ke, Xinchang Zhang, Jingfan Yang, Qiufeng Yang, Ruchi Gakhar, Rongjie Song
Quantum Physics
Generative learning of time series with holographic quantum circuit sampling
Bingzhi Zhang, Matthew W. Lee, Tom Finke et al. (+1 more)
Quantum generative models face growing
qubit requirements and concentrated loss landscapes when learning long time series. Here we introduce holographic
quantum circuit sampling (HQCS), which combines mid-
circuit measurements,
qubit reuse and independently parameterized temporal blocks to generate trajectories with a fixed number of
qubits. For Haar-random HQCS and a normalized exponential kernel, we prove inverse-
polynomial bounds on maximum mean discrepancy loss variance, contrasting with exponential concentration in global Haar-random generators. For generic members of a family of nonstationary Markov processes, temporal parameterization reduces exact-generation gate counts from quadratic to linear in sequence length relative to a specified class of repeated shared-block generators. Simulations demonstrate learning of Gaussian autoregressive processes and historical
Volatility Index (VIX) trajectories, with the latter achieving over tenfold lower maximum mean discrepancy than the tested classical
benchmarks. These results establish a framework for
quantum time-series generation with fixed
qubit requirements and provable avoidance of exponential loss concentration as sequence length grows.
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All authors Bingzhi Zhang, Matthew W. Lee, Tom Finke, Quntao Zhuang
Chemical Physics · Cross-listed from cs.LG
On the Theoretical Limits of Learning Unconstrained Interatomic Potentials
Prajwal Ananth and Shuwen Yue
Machine-learned interatomic potentials (MLIPs) accelerate molecular dynamics (MD) simulations by learning the energies and forces that govern atomic motion. Recent work has shown that relaxing physical inductive biases can improve computational efficiency and predictive accuracy, raising the question of whether energy-and-force matching alone is sufficient to ensure accurate sampling. We show that, for unconstrained hypothesis classes, the relationship between prediction error and sampling accuracy is exponentially ill-conditioned in dimension. In particular, prediction errors that decay exponentially with dimension can coexist with nearly maximal total variation distance between the learned and target distributions. We identify two failure mechanisms. The first is kinetic trapping, where relaxation to an accurate learned
equilibrium requires exponentially long times, even when simulations are initialized from training configurations at which energies and forces are matched exactly. The second is
equilibrium mismatch, where the learned stationary distribution itself remains far from the target. Under explicit assumptions, we show that
equilibrium mismatch can persist even in local,
symmetry-preserving models, where small per-atom errors coexist with a distributional discrepancy that approaches its maximum as system size increases. Finally, we establish global energy-control conditions that guarantee
equilibrium accuracy and identify additional conditions required for rapid relaxation.
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Plasma Physics · Cross-listed from cs.LG
Toward a Multimodal Foundation Model for Plasma State Reconstruction
Bin Xia, Chuanfei Dong, Boting Li et al. (+9 more)
Plasma experiments observe coupled physical states through sparse, heterogeneous, and incomplete diagnostics. We present a proof of concept toward a
multimodal foundation model for
plasma state reconstruction during
magnetic reconnection, motivated by the Facility for Laboratory Reconnection Experiments (
FLARE). Using 250 synthetic VPIC simulations at fixed reference electron beta $\beta_{e0}=0.2$, with 225 training runs and 25 disjoint validation runs, we train a 5.5M-parameter residual 3D U-Net to reconstruct three
magnetic-field components and electron density from incomplete observations. The model combines spatial-only pooling, which preserves all 24 temporal frames, with global spatiotemporal self-
attention and rotary positional encoding. Independently masking
magnetic and density modalities across random, grid, block, and temporal patterns enables sparse sensing, cross-modal completion, density super-resolution, and temporal completion with a single set of weights and no task-specific retraining. With density fully hidden, just 0.1%
magnetic spatial visibility reduces median density NRMSE from approximately 0.9 to 0.1. Conversely, observed density improves current-density reconstruction when
magnetic data are absent or extremely sparse. With no
magnetic observations, roughly 1% density visibility approaches the density reconstruction accuracy achieved with fully observed
magnetic fields, although current structure remains more dependent on direct
magnetic measurements. Full
magnetic conditioning also stabilizes completion of missing future density frames. These results demonstrate bidirectional cross-modal predictive coupling within this simulation regime. Generalization across
plasma regimes or to experimental measurements remains untested.
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All authors Bin Xia, Chuanfei Dong, Boting Li, Yilan Qin, Zikang Xie, Sung Hyun Son, Adam J. Stanier, Jongsoo Yoo, Hantao Ji, Ahmed Diallo, Han Ding, John Wise
High Energy Physics (Phenomenology)
Chiral mass corrections to decuplet hidden-charm pentaquark states
Yu-Quan Guo and Hao-Song Li
We calculate the masses of the $J^P=\frac{1}{2}^-$ hidden-charm pentaquark states in the $SU(3)$ decuplet within the heavy pentaquark chiral perturbation theory (HPChPT) up to the next-to-leading order (NLO). The one-loop self-energy corrections from the $\pi$, $K$, and $\eta$
mesons are evaluated. Taking $P_\psi^N(4312)$ and $P_{\psi s}^\Lambda(4459)$ as inputs, we predict the masses of the doubly-strange and triply-strange decuplet members $P_{\psi ss}^N$ and $P_{\psi sss}^\Lambda$ to be 4.607 GeV and 4.755 GeV, respectively. The mass splittings between adjacent strangeness layers are nearly constant at approximately 0.148 GeV. This equal-spacing pattern follows directly from the analytical structure of the NLO chiral corrections, while its actual magnitude is set by the low-energy constants (LECs). It indicates that the Gell–Mann–Okubo (GMO) relation, expected at the leading order of SU(3) flavor
symmetry breaking, persists to good accuracy at the NLO.
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Astrophysics of Galaxies
The NIVARIA-Local Group simulations: Unveiling the origin of rotation curve diversity in dwarf galaxies and its connection to galaxy morphology
A. Contreras-Santos, A. Di Cintio, A. Negri et al. (+7 more)
Dwarf
galaxies exhibit a large diversity in rotation curve shapes, challenging
galaxy formation models within the $\Lambda$CDM paradigm. We present NIVARIA-LG, a new suite of cosmological simulations studying dwarf
galaxy evolution in realistic Local Group environments. This intermediate-resolution pilot lays the groundwork for the full-scale NIVARIA project. The simulations combine constrained Local Group initial conditions from HESTIA with the NIHAO
galaxy formation model. The simulated
galaxies reproduce observed stellar-to-
halo mass relations, match the Baryonic Tully-Fisher relation, and capture the distribution of stellar effective radii, including compact and diffuse
galaxies. We analyse the structural and kinematic properties of isolated dwarf
galaxies with $10^7 \lesssim M_\star/M_\odot \lesssim 10^{10}$, focusing on rotation curve diversity. NIVARIA-LG naturally produces a broad range of rotation curve shapes, including slowly rising systems underrepresented in previous simulations and steep rotation curves. We find that rotation curve diversity is primarily associated with gas extent and inner dark matter structure: more extended gas and shallower inner density profiles correspond to more slowly rising curves, while stellar effective radius shows little independent association. Individual
galaxies show that rotation curve shapes change rapidly as gas is redistributed during assembly. Recent
accretion events are also associated with more slowly rising curves in the most massive dwarfs. Together, these results suggest that rotation curve diversity is linked to the baryonic cycle, which shapes the inner dark matter distribution. The Local Group environment and its filaments influence this
evolution by regulating gas
accretion and redistribution, producing the observed diversity in rotation curve shapes.
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All authors A. Contreras-Santos, A. Di Cintio, A. Negri, J. Sarrato-Alós, S. Cardona-Barrero, G. García-Bethencourt, C. Brook, N. I. Libeskind, A. Knebe, A. Macciò
High Energy Physics (Phenomenology)
Probing eV-scale sterile neutrinos with neutrinoless double-beta decay and beta decay
Ruisha Yang and Jiajun Liao
An eV-scale sterile Majorana
neutrino can suppress neutrinoless double-beta decay through destructive interference with the active-
neutrino contribution, weakening the resulting constraints on sterile-
neutrino parameters. We investigate how complementary beta-decay information restricts this cancellation in the 3+1 framework. Using updated oscillation parameters that include the first JUNO results, we determine the allowed sterile-
neutrino mass and mixing regions for both normal and inverted ordering. We show that an upper limit on the effective beta-decay mass $m_\beta$ of the three light
neutrinos strengthens the constraints from neutrinoless double-beta decay alone. The beta-decay bound restricts the light-
neutrino masses and hence the cancellation between the active and sterile contributions to $m_{\beta\beta}$. We derive analytic expressions for the resulting boundaries and use complex-plane geometry to explain the allowed values of the sterile Majorana phase $\alpha_4$ for a finite $|m_{\beta\beta}|$ limit. For the mixing considered, normal ordering allows a broad range of $\alpha_4$ at small sterile masses, whereas inverted ordering favors values near $\pi$. The allowed phase range narrows as the sterile mass approaches its upper bound or the limit on $|m_{\beta\beta}|$ becomes more stringent.
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Physics and Society
Multi-Agent Learning of Reactive Strategies in Iterated Games
James P. Wolfe and Joshua B. Plotkin
Learning
agents, whether humans or
algorithms, adapt to one another rather than to a fixed environment. Selfish learning need not produce a good outcome for the group, especially when learners face a social dilemma. The iterated prisoner's dilemma (IPD) is the classical example, but it is usually studied in populations of
agents who imitate successful strategies. Here, we instead study selfish gradient ascent learners on the two-dimensional space of reactive strategies. A reactive strategy is described by two continuous traits: reciprocity, the chance of cooperating after the co-player cooperates, and forgiveness, the chance of cooperating after the co-player defects. Each learner updates its strategy in the direction that most rapidly improves its payoff against all other learners, by an amount governed by its learning rate. We show that heterogeneity in learning rates can qualitatively change the long-term outcome: a population with uniform learning rates converges to always-defect (ALLD), whereas a population with variable learning rates approaches generous-tit-for-tat (GTFT), which produces nearly optimal collective payoffs. In simulations, every population passes through a transient state of minimal forgiveness, in which the distribution of reciprocity determines the outcome. Variable learning rates promote cooperation because slow learners preserve high reciprocity until the population reaches this state. We prove sufficient conditions on the distribution of reciprocity for convergence to ALLD or to tit-for-tat (TFT). Variable learning rates also allow cooperation to recover from perturbation, which is provably impossible under uniform learning. These results suggest that purely selfish and myopic learning can produce persistent cooperation provided the population has intrinsic variability in learning rates.
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General Relativity and Quantum Cosmology
Scalar wave dark matter imprints on binary black hole mergers: dependence on field mass and density
Yu-Peng Zhang, Shao-Wen Wei and Yu-Xiao Liu
Dark matter environments can modify binary black hole mergers and imprint their gravitational-wave signals. We perform numerical-relativity simulations of nonspinning binary black holes immersed in complex scalar-field clouds, considering mass ratios $q=1,2,3,$ and $4$ and varying both the dimensionless scalar-field mass $\hat m_{\Phi}=m_{\Phi}M_0$ and initial amplitude $\Pi_0$, which controls the density. Our initial data keep the scalar energy-density profile and binary geometry unchanged when varying $\hat m_{\Phi}$ at fixed $\Pi_0$, allowing the dynamical effect of the field mass to be isolated. We find that the scalar environment generally accelerates the merger and significantly modifies the gravitational-wave signal. For unequal-mass binaries, differential scalar-field
accretion changes the horizon-mass ratio during inspiral, weakly at low density but substantially at high density, thereby increasing the binary asymmetry before merger. Dense scalar environments suppress the energy and angular momentum carried by gravitational waves. Lighter scalar fields propagate more efficiently to large radii, whereas heavier fields remain more localized and show stronger inward energy transport. Scalar angular-momentum transport is more complex, showing nonmonotonic behavior and even direction reversal near the binary. For unequal-mass systems, gravitational and scalar radiation both carry net linear momentum, and their relative orientation determines whether the recoil is enhanced or suppressed. The largest kick is $2063.6~{\rm km,s^{-1}}$ for $q=2$, $\hat m_{\Phi}=0$, and $\Pi_0=0.0100$, compared with $137.8~{\rm km,s^{-1}}$ in
vacuum. These results show that the scalar-field mass and density jointly control the binary asymmetry, dynamics, radiative channels, and momentum balance.
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Fluid Dynamics
Nonlinear waves and conservative transport in soluble-surfactant falling films on compliant substrates
Sanghasri Mukhopadhyay and Asim Mukhopadhyay
We investigate finite-amplitude waves in a
liquid film containing a soluble surfactant as it flows down an inclined compliant substrate. The coupled motion of the
liquid and a spring-backed plate is described by a conservative weighted-residual model, which also accounts for surfactant transport in the bulk and at the free surface. The reduction retains viscous terms arising from wall motion, and its pressure closure recovers fluid added mass under uniform translation. Comparison with the coupled Orr-Sommerfeld problem gives a difference of approximately $1\%$ in the peak growth rate of the film mode at $Re=25$. Nonlinear computations are then used to examine travelling states and their dependence on substrate properties and surfactant coupling. Along the prescribed stiffness-damping path, substrate displacement decreases by more than four orders of magnitude, while wave speed changes by less than $1\%$. The extrema of free-surface elevation and
liquid thickness vary differently, so surface height alone does not reliably indicate film thinning over a deformable support. In the cases studied, Marangoni coupling reduces surfactant localisation and weakens the wave and substrate response. Moving-frame reconstruction reveals recirculation near the wave crest and distinguishes propagation of the deformation pattern from transverse substrate motion. The load-work budget identifies capillary pressure as the principal net source of substrate work for the two compliant supports considered. A control calculation in which stiffness is varied at fixed damping shows a substantial change in damping loss but a comparatively small change in deformation.
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Pattern Formation and Solitons
Extreme Localization via a Singular Edge Mode in an Asymmetric Linkage System
Myeonggyun Joo, Dongwook Kwak, Rajesh Chaunsali et al. (+2 more)
Mechanical localized modes generally retain exponentially decaying tails, whereas confinement to a single structural unit is difficult to achieve without resonators, flat-band
lattices or topological design. To address this need, an asymmetric linkage system is introduced in which geometry tunes a boundary mode from finite localization to its extreme limit. Each
cell comprises two unequal rigid bars connected by a torsional spring and is described by one generalized coordinate. Linearization and coordinate transformation yield a tridiagonal model and closed-form expressions for the edge mode frequency and spatial decay ratio. The analysis identifies the configurations supporting a singular edge mode at which its decay ratio vanishes, leaving only the boundary
cell active in the linear regime. Simulations show near-complete localization under finite-amplitude excitation, and experiments reproduce the configuration-dependent transition from bulk transmission to boundary confinement. These results establish a minimal and analytically tunable platform for mechanical localization
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All authors Myeonggyun Joo, Dongwook Kwak, Rajesh Chaunsali, Panayotis G. Kevrekidis, Jinkyu Yang
High Energy Physics (Experiment)
Detecting photons in radiative Bhabha interaction with Si-strip and LYSO crystals at future e+e- colliders
Chentao Bao, Hai Chen, Wang Chen et al. (+12 more)
Next-generation e+e-
colliders have been proposed for the Super Tau Charm Facility covering center-of-mass energies sqrt(s) = 2-7 GeV, and for the
Higgs Factories optimized for Z-pole physics and for HZ production. Luminosity can be determined by measuring forward Bhabha scattering. The QED cross-section calculation has reached a precision of better than 10^-3. Detecting radiative
photons in Bhabha events provides a tool for validating higher-order corrections in theory. We propose the Forward Detector for detecting Bhabha scattering events at the STCF. The design uses high-resolution silicon detectors and finely segmented LYSO
crystals to discriminate radiative
photons from closely associated electrons. Bhabha scattering events are simulated with the BHLUMI and BHWIDE programs, and the detector is modeled using GEANT. Systematic uncertainties due to multiple scattering and bremsstrahlung in the beam pipe were evaluated. The potential for achieving precise measurements of radiative processes in Bhabha events is investigated.
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All authors Chentao Bao, Hai Chen, Wang Chen, Zhujun Fang, Jiading Gong, Suen Hou, Xiaolin Kang, Mingyi Liu, Ming Qi, Liqing Qin, Weimin Song, Jie Wang, Yadi Wang, Lei Zhang, Linghua Zhang
Astrophysics of Galaxies
Photometric Identification and Dynamical Purification of Blue Horizontal Branch Stars in DESI MWS DR1
Shuai Zhang, Xiaolong Wang, Kai Xiao et al. (+5 more)
Blue horizontal-branch (BHB)
stars are ideal tracers for mapping the structure of the Galactic stellar
halo. However, traditional spectroscopic identification is limited by data quality and sample size, while broad-band photometric methods often achieve only moderate completeness and purity. Building upon the color-space BHB identification method of \citet{2025ApJS..278...62H}, we synthesize SkyMapper $(u,v,g,z)$ photometry from DESI MWS DR1 spectroscopy and identify 9,237 BHB candidates in the $(g-z)_0$–$(u-v)_0$ color space using the HDBSCAN clustering
algorithm. We then construct a Kernel Density Estimation (KDE)
Bayesian probability model with capture-recapture (C-R) prior to assign posterior membership probabilities, achieving a probability-weighted purity of 88.9% and completeness of 94.2%. Applying an escape-velocity cut based on the Galactic gravitational potential, we remove 1,461 contaminants with unphysical kinematic parameters, yielding a clean photometric BHB sample $\mathcal{S}_c$ of 7,776
stars (retention rate $R_{\rm keep} = 84.2\%$). Systematic analysis of the contaminants reveals that they are predominantly faint sources ($g\sim20$~mag) with very low signal-to-noise ratios (median SNR~$<$~5). When the BHB color–luminosity relation is incorrectly applied to these objects, their space velocities are amplified beyond the Galactic escape limit, confirming that the escape-velocity filter essentially acts as a physical detector of low-SNR–driven distance inflation.
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All authors Shuai Zhang, Xiaolong Wang, Kai Xiao, Guozhen Hu, Wenyuan Cui, Ce Cai, Shuai Feng, Jie Ju
Materials Science
Graphene-Confined Growth of Few-Layer PtSe2 via One-Step Selenization
Timea Ema Krajčovičová, Peter Kotrusz, Viera Skákalová et al. (+5 more)
Platinum diselenide (PtSe$_2$), a member of the transition metal dichalcogenide (TMD) family, is a promising material for next-generation electronic and optoelectronic applications due to its thickness-dependent properties, transitioning from semimetallic in bulk to semiconducting behavior at the few-layer limit. However, the scalable fabrication of large-area ultrathin PtSe$_2$ films remains challenging, as conventional selenization of pre-deposited Pt layers often leads to undesired three-dimensional clustered growth. This work explores a novel strategy for promoting two-dimensional growth of PtSe$_2$ by employing a
graphene-mediated confinement approach. The method involves coating a Pt layer with
graphene oxide (GO), followed by annealing in a selenium atmosphere, which results in the simultaneous formation of PtSe$_2$ and the reduction of GO to
graphene. The
graphene overlayer acts as a physical confinement layer, suppressing vertical growth and enabling the synthesis of
graphene-confined PtSe$_2$
heterostructures on centimetre-scale substrates and promoting lateral connectivity of PtSe$_2$ regions observed by STEM. Scanning transmission electron microscopy (STEM), including temperature-resolved in situ atomic-resolution measurements, was used to investigate the influence of selenization temperature on the growth mechanism and structural
evolution of PtSe$_2$ films. The results show that
graphene confinement stabilizes lateral growth and promotes the formation of few-layer films with improved structural ordering. Beyond PtSe$_2$, this
graphene-assisted approach provides a general strategy for fabricating and stabilizing ultrathin TMD layers, including those prone to environmental degradation, providing a new outlook for enabling detailed studies of their intrinsic properties.
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All authors Timea Ema Krajčovičová, Peter Kotrusz, Viera Skákalová, Agáta Laurenčíková, Igor Píš, Martin Hulman, Kimmo Mustonen, Michaela Sojková
Quantum Physics
Xingjian Zhang, Jiayi Wu, Jue Xu et al. (+1 more)
Quantum science and engineering increasingly target the exploitation and control of large-scale dynamical systems. As system size grows, novel phenomena and
quantum advantages emerge, but the resulting many-body dynamics become correspondingly harder to monitor and characterize. In particular, the underlying
Hamiltonian often lacks
symmetries, and the induced many-body dynamics quickly become hard to track. Focusing on one of the most important
quantum features—
entanglement—we demonstrate that, for a broad class of common
Hamiltonian models, one can design effective witnesses that detect both the presence and structure of
entanglement over relatively long
evolution times. Inspired by stabilizer-based simulation, we track the
evolution of generalized stabilizers of the underlying state and use them to construct linear
entanglement witnesses. Through numerical experiments on Heisenberg-type
Hamiltonians with up to twelve
qubits, we show that the required number of measurement settings can be kept at a modest scale as the system size increases, and
entanglement detection remains effective over
evolution times that significantly exceed those accessible to naive approaches. The corresponding calculations can be carried out largely symbolically. Furthermore, unlike accurate state simulation, the stabilizer-based design of
entanglement witnesses can be performed in a much more coarse-grained, digitized manner. We hope these results will stimulate further exploration of the
quantum control of large systems.
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All authors Xingjian Zhang, Jiayi Wu, Jue Xu, Qi Zhao
Astrophysics of Galaxies
The Galactic disk structure revealed by Gaia XP spectra
Zhenkang Tang, Jianhui Lian, Jialong Zhou et al. (+1 more)
The spatial structures of chemical populations constrain Galactic disk
evolution and its underlying physical processes. Gaia XP spectra provide one of the largest spectroscopic samples available. We use Gaia XP spectra to study Galactic disk mono-abundance populations (MAPs), measuring their scale heights as a function of radius and radial surface-mass-density profiles. We construct a red giant branch (RGB) sample and divide it into MAPs according to $[\alpha/{\rm M}]$ and $[{\rm M/H}]$. The sample covers a $6\times6$ kpc region centered on the Sun in the Galactic plane and extends to $|Z|<3.7$ kpc. We estimate XP completeness using a Gaia photometric parent sample and combine PARSEC isochrones with a Kroupa initial mass function (IMF) to calculate the selection function and convert observed stellar counts into intrinsic stellar mass densities. We fit vertical density profiles with an exponential model to derive scale heights and integrate the fitted profiles to obtain surface mass densities. The resulting profiles are generally consistent with those from APOGEE. All MAPs show flaring, with the high-$\alpha$ population exhibiting the strongest flaring and the metal-poor and sub-solar low-$\alpha$ populations showing the weakest. Surface-mass-density profiles differ significantly among MAPs: the high-$\alpha$ and metal-rich low-$\alpha$ populations show approximately exponential declines, whereas the other low-$\alpha$ populations exhibit plateau-like features, indicating that the Galactic disk cannot be described by a simple single-exponential profile. These differential structures suggest a complex Galactic disk assembly history likely regulated by birth conditions, secular dynamical heating, radial migration, and external perturbations.
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All authors Zhenkang Tang, Jianhui Lian, Jialong Zhou, Jiadong Li
Mathematical Physics · Cross-listed from math.PR
DisCo Algebra: Why Disintegration and Combination Are Not Inverses
Xuexing Lu
We present DisCo
algebra—a compositional framework for joint probability built from a symmetric cooperad (disintegration) and a symmetric operad (combination) on the bare family $\mathcal{P}_n=\mathrm{Prob}([0,1]^n)$. No probability integral transform, no external summary functions, no enrichment of objects with conditional kernels. The disintegration side uses block-wise joint CDFs as intrinsic, measure-determined 1D summaries, yielding a lossy compression. The combination side reads the same summaries and reconstructs via regular conditional measures, yielding a lossless
embedding. We prove that combination followed by disintegration is the identity on admissible inputs, but disintegration followed by combination is not—the information loss is exactly the conditional KL divergence between the true conditional distribution and the conditionally independent product. This asymmetry reveals a hard limit on how much cross-block dependence can be captured by scalar block summaries.
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Materials Science
DiffGA: Steering Frozen Diffusion Models for Materials Design via Evolutionary Search
Shivang Agarwal, Rodrigo Wang, Kevin Ryczko et al. (+1 more)
Steering candidate generation toward user-defined objectives is central to inverse materials design, yet remains difficult when objectives are black-box, changing, or non-differentiable, as in many simulation- and experiment-derived properties. Generative models offer a solution but typically require retraining or fine-tuning for each new objective, demanding labeled data and substantial compute, or rely on differentiable guidance that is brittle to gradient noise and undefined for many practical targets. We present DiffGA, a retraining-free framework that injects evolutionary search into the sampling trajectory of a retrained
diffusion model, evolving partially denoised states under an arbitrary black-box oracle. Because oracle evaluation often dominates campaign cost, we couple DiffGA with an on-the-fly
Bayesian surrogate that reuses representations from state-of-the-art machine-learned force fields (MLFFs). A Gaussian process is fit during the campaign on the force fields's graph
embeddings and, once it demonstrably ranks an unseen generation, replaces expensive property evaluations under an uncertainty-aware acquisition rule, reducing oracle cost with negligible loss of accuracy. Across three
crystal-design tasks using a frozen MatterGen backbone, DiffGA outperforms
diffusion-only, compute-matched, purely evolutionary, and fine-tuned baselines in oracle-assessed rates of stable, unique, and novel hits. Rather than proposing scientific compounds, we use density functional theory to quantify MLFF oracle fidelity, showing that it is a faithful proxy in key regimes but systematically biased in others, delineating when proxy-driven generative discovery can be trusted. On a representative sample, DiffGA's top hits survive first principles re-evaluation as physically realistic hits, while the surrogate-accelerated pipeline preserves this fidelity at a fraction of the cost.
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All authors Shivang Agarwal, Rodrigo Wang, Kevin Ryczko, Aayush R. Singh
Materials Science
EpNet-Si: Atomic Form Factors Learned from Band Structures
Qiang Zhu
The empirical pseudopotential method (EPM) computes band structures with one diagonalization per $k$ point and no self-consistency, but its fixed atomic form factors do not transfer between
crystal structures. To address this limitation, we introduce EpNet-Si, an EPM for silicon in which an equivariant network predicts each atom's plane-wave form factor from its local environment: a species potential plus monopole, dipole and quadrupole corrections, mixed by a learned router over atomic densities, together with an $s/p$ nonlocal projector. With 6{,}195 parameters, the model is trained through the eigensolver on reference density functional theory (DFT) band energies of only 77
cells. Among 231 distortions of the trained structure types, the 142 gapped
cells have mean band and gap errors of 15 and 8\,meV; among 192 unseen structures, the 165 gapped
cells have mean errors of 38 and 49\,meV. Physical properties derived from EpNet-Si, including effective masses, gap pressure coefficients, deformation potentials and the density of states at the Fermi level, agree with those obtained from the reference DFT calculations. These results suggest that the classical EPM, fitted to a small set of reference data, can be extended into a fast alternative for modern electronic band-structure calculations.
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Solar and Stellar Astrophysics
The $R$-Process Alliance: On J0010$-$1735, an Accreted, Chemically Unusual, Metal-poor Star with $R$-process Enhancement
Zoe Hackshaw, Rana Ezzeddine, Shivani P. Shah et al. (+11 more)
We present a detailed chemo-dynamical analysis of the chemically peculiar very metal-poor ([Fe/H]$=-2.22\pm 0.11$) Milky Way (MW)
halo star, 2MASS J00101758$-$1735387 (hereafter J0010-1735), discovered by the $R$-Process Alliance. We derive abundances for 45 elements, including 28
neutron-capture elements, and confirm that \thestar\ is highly $r$-process-enhanced, with [Eu/Fe]=$+1.30$. The light, $\alpha$, and Fe-peak element abundances ratios relative to Fe are all sub-solar, aside from C, Si, and most extremely, Ca. We investigate three possible formation scenarios based on the
star's chemical abundances and orbital kinematics: whether it formed in the in-situ MW
halo, in a MW dwarf
galaxy satellite, or in a satellite of the Magellanic Cloud system. Using the position of \thestar\ in the [Mg/Mn]–[Al/Fe] plane, the abundance pattern of both the light and heavy elements, and the kinematics, we conclude that J0010-1735 most plausibly originated in a now-disrupted ultra-faint dwarf
galaxy that was accreted into the MW
halo. We examine potential chemical enrichment scenarios of J0010-1735, including one similar to the $r$-process-enhanced UFD Reticulum II, or enrichment via a sub-Chandrasekhar Type Ia SNe, potentially supplemented by a Ca-rich gap transient and by a separate
neutron-rich site that facilitated $r$-process enrichment. A nuclear cosmochronometric age of $12.5\pm4.2$ Gyr is derived from the [Th/Eu] ratio, consistent with an ancient origin in one of the earliest
star-forming systems in the universe.
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All authors Zoe Hackshaw, Rana Ezzeddine, Shivani P. Shah, Terese T. Hansen, Ruijie Shi, Yangyang Li, Timothy C. Beers, Anna Frebel, Erika Holmbeck, Alexander P. Ji, Jeremy Kowkabany, Vinicius M. Placco, Ian U. Roederer, Charli M. Sakari
Soft Condensed Matter
Time-temperature-composition equivalence of the viscoelastic behavior through the glass transition of digitally mixed 3D-printed polymers
Beijun Shen, Sanat K. Kumar and Mary C. Boyce
The linear viscoelastic behavior of a
polymer shows an equivalence of loading frequency and temperature, the time-temperature equivalence (TTE). Horizontal shifting extends moduli measured over limited ranges to much wider ranges, through the glass transition. Multimaterial 3D printing has created digitally mixed
polymers, a new class in which elastomeric and glassy resins are mixed voxel by voxel in prescribed ratios. Composition shifts the location and breadth of the glass transition and increases the rubbery modulus. Here we extend TTE to a time-temperature-composition equivalence (TTCE). Across all measured temperatures, frequencies, and compositions, the storage modulus collapses onto one master curve. Composition translates the transition and stretches its breadth, both linearly. The phase angle and relaxation spectrum superpose under the same operations, so the family shares one distribution of relaxation times. A single closed-form TTCE gives the storage and loss moduli of the family, guiding graded and architected designs for elasticity and dissipation.
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Fluid Dynamics
Surfactant-induced Marangoni stresses and surface viscosity in Faraday instability
Bochang Wang and C. Ricardo Constante-Amores
We investigate the influence of insoluble-surfactant elasticity and Boussinesq-Scriven surface viscosity on the parametric instability of an interface separating two viscous fluids. The two-fluid Floquet formulation of Kumar& Tuckerman (J. Fluid Mech., vol. 279, 1994, pp. 49-68) is extended to include surfactant transport, Marangoni stresses and surface viscosity. For the parameter range considered, both mechanisms increase the onset acceleration relative to the clean interface state, but through distinct responses: Marangoni elasticity produces a non-monotonic threshold, whereas surface viscosity yields a monotonic increase towards saturation. Analysis of the corresponding unforced
gravity-capillary modes shows that both mechanisms modify modal damping and natural frequency. Wavenumber selection reduces the detuning from subharmonic resonance by approximately an order of magnitude relative to that evaluated at the clean interface critical wavenumber. Along the selected branches, variations in the onset acceleration closely follow those in modal damping, with residual detuning playing a secondary role. Despite their distinct interfacial stress mechanisms, both Marangoni elasticity and surface viscosity suppress tangential interfacial motion in the strong-rheology limit, approaching a common tangentially immobilized condition.
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