Disordered Systems and Neural Networks
q-Gaussian Crossover in Overlap Spectra towards 3D Edwards-Anderson Criticality
Yaprak Onder, Abbas Ali Saberi and Roderich Moessner
We introduce a spectral approach to characterizing the three-dimensional Edwards-Anderson
spin glass. By analyzing the
eigenvalue statistics of overlap
matrices constructed from two-dimensional cross-sections, we identify a crossover from the Wigner semicircle law at high temperatures towards a Gaussian distribution, which is consistently attained near the
spin-glass critical point. Visible for different distributions of the random coupling, the Gaussian distribution can potentially serve as a robust spectral indicator of criticality. Remarkably, the spectral density is well-described by Tsallis statistics, with the entropic index $q$ evolving from $q = -1$ (semicircle, $T=\infty$) to $q = 1$ (Gaussian) at $T_c$, revealing a statistical structure inside the paramagnetic phase. We find $q\le 1$ within numerical precision. While the local level statistics remain consistent with GOE statistics, reflecting standard level repulsion, the temperature dependence appears mainly in the global spectral density. Our results present spectral statistics as a computationally efficient complement to multi-replica correlator methods and provide a new perspective on cooperative and critical phenomena in disordered systems.
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Materials Science · Cross-listed from cs.LG
Orbital Transformers for Predicting Wavefunctions in Time-Dependent Density Functional Theory
Xuan Zhang, Haiyang Yu, Chengdong Wang et al. (+3 more)
We aim to learn wavefunctions simulated by time-dependent density functional theory (TDDFT), which can be efficiently represented as linear combination coefficients of atomic orbitals. In real-time TDDFT, the electronic wavefunctions of a molecule evolve over time in response to an external excitation, enabling first-principles predictions of physical properties such as optical absorption, electron dynamics, and high-order response. However, conventional real-time TDDFT relies on time-consuming propagation of all occupied states with fine time steps. In this work, we propose OrbEvo, which is based on an equivariant graph
transformer architecture and learns to evolve the full electronic wavefunction coefficients across time steps. First, to account for external field, we design an equivariant conditioning to encode both strength and direction of external electric field and break the
symmetry from SO(3) to SO(2). Furthermore, we design two OrbEvo models, OrbEvo-WF and OrbEvo-DM, using wavefunction pooling and density
matrix as interaction method, respectively. Motivated by the central role of the density functional in TDDFT, OrbEvo-DM encodes the density
matrix aggregated from all occupied electronic states into feature vectors via tensor contraction, providing a more intuitive approach to learn the time
evolution operator. We adopt a training strategy specifically tailored to limit the error accumulation of time-dependent wavefunctions over autoregressive rollout. To evaluate our approach, we generate TDDFT
datasets consisting of 5,000 different molecules in the QM9
dataset and 1,500 molecular configurations of the malonaldehyde molecule in the MD17
dataset. Results show that our OrbEvo model accurately captures
quantum dynamics of excited states under external field, including time-dependent wavefunctions, time-dependent dipole moment, and optical absorption spectra.
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All authors Xuan Zhang, Haiyang Yu, Chengdong Wang, Jacob Helwig, Shuiwang Ji, Xiaofeng Qian
Strongly Correlated Electrons
Kondo driven suppression of charge density wave in Van der Waals material UTe$_3$
Justin Shotton, Jiahui Zhu, David Martinez et al. (+22 more)
Competing electronic instabilities lie at the heart of emergent phenomena in
quantum materials. In low-dimensional metals,
Fermi-surface nesting can drive charge density wave (CDW) formation through a Peierls-like mechanism, while in strongly correlated systems, Kondo hybridization reconstructs the electronic structure by entangling localized moments with itinerant electrons. How these two fundamentally different instabilities interact$-$whether they coexist, compete, or mutually exclude each other$-$remains an open question. Here, we present suppression of charge density wave via the Kondo interaction in van der Waals material UTe$_3$. The angle-resolved photoemission spectroscopy (ARPES) data reveals
Fermi surface nesting under similar conditions as seen in RETe$_3$ compounds. Despite that, no CDW is found in UTe$_3$ after an extensive search. We demonstrate that strong hybridization between U 5$f$ electrons and Te $p$ states reconstructs the low-energy electronic structure, removes the instability, and preempts CDW formation. Our results reveal a rare example where Kondo hybridization preempts density wave formation, offering a new route to controlling ordering phenomena in correlated 2D materials.
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All authors Justin Shotton, Jiahui Zhu, David Martinez, Diana Golovanova, Dipanjan Chaudhuri, Xuefei Guo, Peter Abbamonte, Feng Ye, Yiqing Hao, Huibo Cao, Suk Hyun Sung, Carly Grossman, Ismail El Baggari, Gal Tuvia, Mengke Liu, Ruizhe Kang, Matt Boswell, Weiwei Xie, Debapratim Pal, Anil Kumar, Yun Suk Eo, Binghai Yan, Kai Sun, Jonathan Denlinger, Sheng Ran
Disordered Systems and Neural Networks · Cross-listed from cs.LG
Solving adversarial examples requires solving exponential misalignment
Alessandro Salvatore, Stanislav Fort and Surya Ganguli
Adversarial attacks - input perturbations imperceptible to humans that fool neural networks - remain both a persistent failure mode in machine learning, and a phenomenon with mysterious origins. To shed light, we define and analyze a network's perceptual
manifold (PM) for a class concept as the space of all inputs confidently assigned to that class by the network. We find, strikingly, that the dimensionalities of neural network PMs are orders of magnitude higher than those of natural human concepts. Since volume typically grows exponentially with dimension, this suggests exponential misalignment between machines and humans, with exponentially many inputs confidently assigned to concepts by machines but not humans. Furthermore, this provides a natural
geometric hypothesis for the origin of
adversarial examples: because a network's PM fills such a large region of input space, any input will be very close to any class concept's PM. Our hypothesis thus suggests that
adversarial robustness cannot be attained without dimensional
alignment of machine and human PMs, and therefore makes strong predictions: both robust accuracy and distance to any PM should be negatively correlated with the PM dimension. We confirmed these predictions across 18 different networks of varying robust accuracy. Crucially, we find even the most robust networks are still exponentially misaligned, and only the few PMs whose dimensionality approaches that of human concepts exhibit
alignment to human perception. Our results connect the fields of
alignment and
adversarial examples, and suggest the curse of high dimensionality of machine PMs is a major impediment to
adversarial robustness.
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Superconductivity
Limited coincidence between ultrahigh-field superconductivity and line of metamagnetic endpoints in UTe$_2$
Peter Czajka, Sylvia K. Lewin, Thomas Halloran et al. (+6 more)
The field-dependent magnetization of UTe$_2$ was measured through the metamagnetic transition at a variety of field angles, tracking how the step in magnetization evolves with fields tilted away from the $b$ axis. For fields oriented within the $ab$ plane, jumps in both $M_a$ and $M_b$ vanish approximately 18{\deg} away from the $b$ axis. From contactless conductivity measurements, we find that the
halo-like high-field superconducting region extends to the $ab$ plane, where it exists only within a very narrow ($<$1{\deg}) angular range near the termination of the metamagnetic phase boundary and extends beyond the highest measured field of 73 T. As the field orientation tilts towards the $c$ axis, the superconducting and metamagnetic phase boundaries no longer coincide and exhibit distinct trends.
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All authors Peter Czajka, Sylvia K. Lewin, Thomas Halloran, Corey E. Frank, Gicela Saucedo Salas, G. Timothy Noe II, Sheng Ran, John Singleton, Nicholas P. Butch
Superconductivity
Enhanced superconductivity in palladium hydrides by non-perturbative electron-phonon effects
Raffaello Bianco and Ion Errea
Palladium hydrides exhibit the largest isotope-effect anomaly in superconductivity: replacing hydrogen with heavier isotopes increases the superconducting critical temperature. Although this behavior is commonly attributed to strong anharmonic hydrogen vibrations, ab initio treatments have so far incorporated anharmonic effects only through
phonon renormalization, neglecting non-linear contributions to the electron-
phonon interaction vertices. While such approaches reproduce the anomalous isotope trend, they severely underestimate the critical temperatures. Here, we show that non-linear electron-
phonon coupling is essential in palladium hydrides. A straightforward inclusion of higher-order perturbative terms leads to a qualitative breakdown: the critical temperature is overestimated and the isotope anomaly is lost. We therefore adopt a non-perturbative framework based on an explicit evaluation of the ion-mediated electron-electron interaction, enabling anharmonic effects to be treated consistently in both the
phonon spectra and the interaction vertices. Applied to PdH and PdD, it restores the anomalous isotope effect and brings calculated critical temperatures into significantly improved agreement with experiments.
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Statistical Mechanics
Relaxation to nonequilibrium
Christian Maes and Karel Netočný
We describe the structure of relaxation for a steadily driven macroscopic body. The time-
evolution is characterized as the zero-cost flow for a nonequilibrium and nonlinear extension of the Onsager-Machlup action governing the dynamical fluctuations. The approach hinges on two main elements: the principle of local detailed balance, which identifies the relevant thermodynamic forces, and the canonical decomposition of the frenesy into a Legendre pair. Notably, it is the time-symmetric component of the Lagrangian, the frenesy, that shapes the structure of the macroscopic
evolution for given forcing. We add a simple argument for why the nonequilibrium
entropy, which governs the static macroscopic fluctuations of the system, is monotone in time. The results can be interpreted as the steady nonequilibrium extension of GENERIC where relaxation to
equilibrium is governed by a dissipative gradient flow superimposed on a
Hamiltonian flow.
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Mesoscale and Nanoscale Physics
Electrostatically-induced topological phase transitions in polyacetylene molecules
Tomás Suleiman, Aníbal Iucci and Alejandro Martín Lobos
We study the electronic properties of a linear trans-polyacetylene (tPA) molecule capacitively coupled to an external gate voltage $V_g$ of width $d$. We describe this system using the Takayama-Lin-Liu-Maki model, a continuum version of the Su-Schrieffer-Heeger model, and analyze it within the Abelian bosonization formalism, which allows us to treat both electronic and
lattice degrees of freedom and to incorporate the effects of repulsive Coulomb interactions among electrons. The global ground state describing simultaneously the electronic charge-density field as well as the
lattice dimerization field of a tPA molecule is shown to consist of multikink solutions of a modified sine-Gordon equation for the charge-density field, which is controlled by $V_g$, the width $d$, and the Luttinger parameter $K$ encoding the strength of electron-electron interactions. We show that these solutions belong to distinct topological sectors labeled by an integer invariant $q$ that simultaneously quantifies both the bound charge and the number of domain walls in the dimerization pattern induced at the gated region. Increasing $V_g$ drives a sequence of topological phase transitions characterized by abrupt changes in $q$. We further examine the effect of repulsive Coulomb interactions on the resulting topological phase diagram, and, finally, we discuss the relevance of our findings for potential nanoelectronic devices based on gated tPA molecules.
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Disordered Systems and Neural Networks · Cross-listed from cs.LG
Biased Generalization in Diffusion Models
Jerome Garnier-Brun, Luca Biggio, Davide Beltrame et al. (+2 more)
Generalization in generative modeling is defined as the ability to learn an underlying distribution from a finite
dataset and produce novel samples, with evaluation largely driven by held-out performance and perceived sample quality. In practice, training is often stopped at the minimum of the test loss, taken as an operational indicator of generalization. We challenge this viewpoint by identifying a phase of biased generalization during training, in which the model continues to decrease the test loss while favoring samples with anomalously high proximity to training data. By training the same network on two disjoint
datasets and comparing the mutual distances of generated samples and their similarity to training data, we introduce a quantitative measure of bias and demonstrate its presence on real images. We then study the mechanism of bias, using a controlled hierarchical data model where access to exact scores and ground-truth statistics allows us to precisely characterize its onset. We attribute this phenomenon to the sequential nature of feature learning in deep networks, where coarse structure is learned early in a data-independent manner, while finer features are resolved later in a way that increasingly depends on individual training samples. Our results show that early stopping at the test loss minimum, while optimal under standard generalization criteria, may be insufficient for
privacy-critical applications.
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All authors Jerome Garnier-Brun, Luca Biggio, Davide Beltrame, Marc Mézard, Luca Saglietti
Soft Condensed Matter
The Integration Host Factor is a pH-responsive protein that switches from DNA bending to DNA bridging in acidic biofilm-like conditions
Dinesh Parthasarathy, Saminathan Ramakrishnan, Georgia Tsang et al. (+9 more)
The Integration Host Factor (IHF) is a nucleoid-associated
protein critical for both DNA compaction and biofilm stability. While its role in DNA packaging within the
cell is well understood, its structural role in scaffolding biofilms is more puzzling and difficult to reconcile with its known DNA bending activity. Here, we investigated how IHF-DNA interactions are modulated across a pH spectrum mimicking the acidic microenvironments of bacterial biofilms. By performing all-atom calculations we discovered that low pHs lead to a change in protonation of IHF residues, which in turn exposes positively charged patches. We then conjectured that these positively charged residues could lead to intermolecular DNA bridging and tested this hypothesis through single-molecule and bulk assays. We discovered that while at physiological pH IHF mostly bends DNA, at pH < 5 there is clear evidence of IHF-mediated intermolecular crosslinking. Our results demonstrate that pH significantly modulates IHF-DNA interactions and explains the structural role played by IHF in supporting biofilm mechanics through intermolecular crosslinking.
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All authors Dinesh Parthasarathy, Saminathan Ramakrishnan, Georgia Tsang, Auro Varat Patnaik, Sabrina M.C. Hardy, Willem Vanderlinden, Jamieson Howard, Braden Bylett, James R. Law, Mark C. Leake, Agnes Noy, Davide Michieletto
Strongly Correlated Electrons
Mixed-state Phases from Higher-order SSPTs with Kramers-Wannier Symmetry
Aswin Parayil Mana, Zijian Song, Fei Yan et al. (+1 more)
Mixed-state phases have recently attracted significant
attention as a generalization beyond their pure-state counterparts. Prominent examples include mixed-state
symmetry-protected topological (mSPT) phases and the strong-to-weak
symmetry breaking (SWSSB) phases. It has been shown recently that mSPT phases admit a
holographic dual description in terms of higher-order subsystem SPT phases. In this work, we investigate the mixed-state phases obtained by tracing out the bulk degrees of freedom of higher-order subsystem SPT phases protected by non-invertible
symmetries. We find that the resulting mixed states exhibit the coexistence of the
symmetry-protected topological order and SWSSB. We also use the interface as a probe to characterize the mixed state phases, and specifically, when there is no local modification to preserve the
symmetries across the interface, the two sides of the interface are in distinct phases.
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All authors Aswin Parayil Mana, Zijian Song, Fei Yan, Tzu-Chieh Wei
Strongly Correlated Electrons · Cross-listed from hep-th
On the action of non-invertible symmetries on local operators in 3+1d
Pavel Putrov and Rajath Radhakrishnan
Most of the known non-invertible
symmetries of
quantum field theories in three and four spacetime dimensions act invertibly on local operators. An exception is coset
symmetries, which can be constructed from gauging a non-normal subgroup of an invertible
symmetry. In this paper, we study the action of a general finite non-invertible
symmetry on local operators in four dimensions. We show that non-invertible
symmetries without topological line operators necessarily act invertibly on local operators. Using this result, we argue that the action of a general non-invertible
symmetry in 3+1d on local operators can be decomposed into the invertible action of some operators composed with the action of a gauging interface. We use this result to study when such a
symmetry is anomaly-free. We find a necessary condition for a finite non-invertible
symmetry in 3+1d to be anomaly-free, and show that anomaly-free non-invertible
symmetries without topological line operators are non-intrinsically non-invertible.
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Strongly Correlated Electrons
Paul M. Neves, Chi Ian Jess Ip, Takashi Kurumaji et al. (+6 more)
EuAg$_4$Sb$_2$ is a model material to study the interplay of electronic and
spin texture degrees of freedom, exhibiting numerous multi-$q$
magnetic textures coupled with the electronic properties. It is generally understood that some combination of conduction-electron mediated interactions, frustration, and higher order interactions are responsible for complex incommensurate
spin textures in centrosymmetric lanthanide materials. Here, we refine an effective model of the
magnetic interactions in EuAg$_4$Sb$_2$ through measurements of diffuse
magnetic neutron scattering above the ordering temperature. These diffuse measurements reveal a ring of fluctuating
spin modulations that reflects a
manifold of nearly degenerate propagation vectors known as a spiral
spin liquid (SSL). We further identify that this approximate $U$(1) symmetric SSL emerges from
magnetic interactions mediated by a quasi-2D hole pocket and exhibits critical scaling of the spatial correlations. Further, Monte Carlo simulations reveal excellent agreement with experiment and provide a comprehensive understanding of the phase diagram. This study emphasizes the connection between the rich
spin textures in this material, the electronic structure, and
spin liquidity$\unicode{x2014}$uncovering new insights into design principles for nano-scale
spin texture materials with advantageous intertwined electronic,
magnetic, and topological properties, and new mechanisms for generating the physics of spiral
spin liquids.
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All authors Paul M. Neves, Chi Ian Jess Ip, Takashi Kurumaji, Shiang Fang, Joseph A. M. Paddison, Lisa M. DeBeer-Schmitt, Daniel G. Mazzone, Jonathan S. White, Joseph G. Checkelsky
Quantum Gases · Cross-listed from quant-ph
Bayesian post-correction of non-Markovian errors in bosonic lattice gravimetry
Bharath Hebbe Madhusudhana, Andrew Harter and Avadh Saxena
We study gravimetry with bosonic trapped atoms in the presence of random spatial inhomogeneity. The errors resulting from a random, shot-to-shot fluctuating spatial inhomogeneity are
quantum non-Markovian. We show that in a system with $L>2$ modes (i.e., trapping sites), these errors can be post-corrected using a
Bayesian inference. The post-correction is done via in situ measurements of the errors and refining the data-processing according to the measured error. We define an effective Fisher information $F_{\text{eff}}$ for such measurements with a
Bayesian post-correction and show that the Cramer-Rao bound for the final precision is $\frac{1}{\sqrt{F_{\text{eff}}}}$. Exploring the scaling of the effective Fisher information with the number of atoms $N$, we show that it saturates to a constant when there are too many sources of error and too few modes. That is, with $\ell$ independent sources of error, we show that the effective Fisher information scales as $F_{\text{eff}} \sim \frac{N^2}{a+bN^2}$ for constants $a, b>0$ when the number of modes is small: $L<\ell+2$, even after maximization over the
Hilbert space. With larger number of modes, $L\geq \ell+2$, we show that the effective Fisher information has a Heisenberg scaling $F_{\text{eff}}= O(N^2)$ when optimized over the
Hilbert space. Finally, we study the density of the effective Fisher information in the
Hilbert space and show that when $L\geq \ell+2$, almost any Haar random state has a Heisenberg scaling, i.e., $F_{\text{eff}}=O(N^2)$. Based on these results, we develop a Loschmidt echo-like experimental sequence for error mitigated gravimetry and gradiometry and discuss potential implementations. Finally, we argue that the effective Fisher information can be interpreted as the Fisher information corresponding to an equivalent non-Hertimitian
evolution.
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Materials Science
Quantum Theory of Functionally Graded Materials
Michael J. Landry, Ryotaro Okabe, Chuliang Fu et al. (+1 more)
Functionally graded materials (FGMs) are composites whose composition or microstructure varies continuously in space, producing position-dependent mechanical and functional properties. In recent years, FGMs have gained significant
attention due to advances in additive manufacturing, which enable precise spatial control of composition and orientation. However, their graded, aperiodic structure breaks the assumptions of Bloch's
theorem, making first-principles electronic and electromagnetic calculations challenging. Here we develop an ab initio
quantum theoretical framework for the electromagnetic properties of FGMs. Using a non-interacting electron model, we formulate a theory of modulated Bloch states, derive effective field equations, and solve them by proposing a generalized WKB (GWKB) method, an effective mass approximation, the Boltzmann equation, and numerical approaches. Our GWKB solution is not semiclassical but remains valid in the fully
quantum regime. We show that effective observables such as conductivity,
magnetic permeability, and electric permittivity generally do not admit a tensorial description in graded media, and that engineered orientational gradients enable precise control of Landau quantization. As a device example, we further develop a theory of graded p-n junctions with enhanced electronic tunability. This framework lays the
quantum foundation for predictive design of graded composite materials, enabling AI-accelerated discovery of next-generation functional architectures.
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All authors Michael J. Landry, Ryotaro Okabe, Chuliang Fu, Mingda Li
Materials Science
Computational discovery of bifunctional organic semiconductors for energy and biosensing
Patrick Sorrel Mvoto Kongo, Steve Cabrel Teguia Kouam, Jean-Pierre Tchapet Njafa et al. (+1 more)
The discovery of synthetically accessible organic
semiconductors with exceptional performance remains a critical bottleneck in materials science. While these materials offer compelling advantages - structural modularity, mechanical flexibility, and cost-effective solution processing - for applications in photovoltaics and biosensors, identifying candidates that balance high efficiency with practical synthesis presents significant challenges. To address this challenge, we developed a high-throughput screening approach using 17 458 molecules from the PubChemQC B3LYP/6-31G*//PM6
dataset. Our strategy employs a composite metric, PCESAScore = PCE - SAScore, which systematically balances power conversion efficiency (PCE) predictions from the Scharber model against synthetic accessibility scores. This approach successfully identified seven multi-functional candidates that demonstrate both exceptional photovoltaic performance (PCE up to 36.1 %) and strong
protein-binding affinity for biosensing applications. Notably, molecule 4550 emerged as the optimal candidate, exhibiting a ligand efficiency of 0.340 kcal/mol/heavy atom with 100 % target promiscuity. Our computational framework integrates machine learning, density functional theory, and molecular docking to bridge the gap between theoretical performance and experimental feasibility. These findings establish a systematic pathway for discovering synthetically compatible organic
semiconductors that can simultaneously address energy conversion and molecular recognition challenges.
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All authors Patrick Sorrel Mvoto Kongo, Steve Cabrel Teguia Kouam, Jean-Pierre Tchapet Njafa, Serge Guy Nana Engo
Statistical Mechanics
Will a Large Complex System be a Maxwell Demon?
Matthew P Leighton
Emerging evidence suggests that physical systems operating as Maxwell demons, in which some subsystem of a larger system extracts heat energy from its environment in an apparent local violation of the second law, are commonplace throughout biology. Should these findings surprise us, or is Maxwell demon behavior inevitable in sufficiently large complex systems? In this Letter we pose the question of how likely it is that a random
stochastic system with many degrees of freedom will operate as a Maxwell demon, considering null models for both continuous and discrete random dynamics. Our results show the probability of a finding a demon decreases at least exponentially, and in some cases double-exponentially, with the number of degrees of freedom, ultimately suggesting that large complex demons can only arise through a process of selection.
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Mesoscale and Nanoscale Physics
Anomalous Klein tunnelling with magnetic barriers in strained graphene
Edgardo Marin-Colli, Tonatiuh Gómez-Ramírez, O-Excell Gutierrez et al. (+3 more)
We study electron transport in a strained
graphene sheet subjected to a sequence of $N$ electrostatic and
magnetic barriers. Employing a modified and improved transfer-
matrix framework, we examine how the transmission and reflection coefficients evolve with variations in uniaxial strain and in the number of barriers. The interplay of mechanical deformation and external
magnetic fields is found to generate an anomalous Klein tunnelling, allowing the conductance to be effectively modulated through strain and barrier configurations. These findings highlight the role of strain engineering and
magnetic field modulation as powerful tools for tailoring charge transport in two-dimensional materials. More broadly, they underscore how mechanical and electromagnetic control can be used to design next-generation solid-state devices with tunable electronic properties.
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All authors Edgardo Marin-Colli, Tonatiuh Gómez-Ramírez, O-Excell Gutierrez, Yonatan Betancur-Ocampo, Alfredo Raya, Erik Díaz-Bautista
Soft Condensed Matter
Guiding isotropic active fluids with anisotropic friction
Cody D. Schimming and Brian A. Camley
Inspired by recent experiments of
cells accumulating on anisotropic substrates, we study a two-dimensional, compressible, isotropic, active fluid in the presence of anisotropic friction. We find that regions of anisotropic friction that are patterned as positive topological defects may drive accumulation of an active fluid into a clump, but the robustness of this behavior depends on the initial configuration. If the initial azimuthal
symmetry is sufficiently broken, we find that patterning asymmetry can instead lead to circular motion of accumulated clumps. We develop an approximate analytical model to qualitatively explain the motion. Finally, we use our simplified model to design a substrate pattern that creates directed motion of accumulated clusters along a given path.
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Materials Science · Cross-listed from physics.chem-ph
Expanding Universal Machine Learning Interatomic Potentials to 97 Elements Towards Nuclear Applications
Naoya Kuroda, Kenji Ishihara, Tomoya Shiota et al. (+1 more)
Machine learning interatomic potentials (MLIPs) evaluate potential energy surfaces orders of magnitude faster while maintaining accuracy comparable to first-principles calculations, and universal MLIPs that cover most of the periodic table are becoming increasingly commonplace. However, existing large-scale
datasets have limited or no coverage of heavy elements such as minor actinides crucial in the
nuclear field, and universal MLIPs are typically limited to 89 elements. Here, we constructed a heavy element
dataset HE26 containing minor actinides, based on experimental and computational literature data. By integrating this with existing molecular and
crystal datasets, we developed an open-source universal MLIP covering 97 elements, the broadest elemental coverage to date. The resulting model showed strong performance on the inorganic MPtrj and organic OFF23 test sets and promising accuracy on HE26. The
dataset and model open a pathway toward the development of energy resources and the design of novel materials, such as actinide-based high-
entropy ceramics, in the
nuclear field.
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All authors Naoya Kuroda, Kenji Ishihara, Tomoya Shiota, Wataru Mizukami
Superconductivity
Emergent superconducting phases in unconventional $p$-wave magnets: Topological superconductivity, Bogoliubov Fermi surfaces and superconducting diode effect
Amartya Pal, Paramita Dutta and Arijit Saha
The recent discovery of unconventional momentum-dependent
magnetic orders has expanded the landscape of magnetism beyond conventional ferromagnetism and antiferromagnetism. Among them, $p$-wave magnets ($p$WMs) represent a novel class of odd-parity, non-collinear compensated
magnetic order that generates
spin-split electronic bands. In this work, our theoretical investigation establishes $p$WMs as a versatile platform for realizing intriguing superconducting phases including topological superconductivity (TSC), Bogoliubov
Fermi surfaces (BFSs), and superconducting diode effect (SDE), within a unified microscopic framework. Employing a minimal model incorporating $p$-wave
magnetic order, exchange coupling, and Zeeman fields, we perform a self-consistent mean-field analysis and uncover a rich phase diagram featuring unconventional finite-momentum Fulde-Ferrell (FF) and Larkin-Ovchinnikov (LO) superconducting phases. Remarkably, we also show that $p$WMs can undergo a transition to a TSC phase anchoring Majorana flat edge modes, a hallmark of two-dimensional TSCs, even without Rashba
spin-orbit coupling and Zeeman field. Upon applying a Zeeman field, gapless FF and LO phases emerge with BFSs characterized by the appearance of finite zero-energy quasiparticle density of states. Furthermore, we demonstrate that SDE arises naturally in the asymmetric FF phase. Our analysis manifests that $p$WMs serve as a unique and novel platform to host TSC phase, gapless superconducting states, and non-reciprocal transport phenomena.
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Materials Science
Dynamical magnetic susceptibility of non-collinear magnets: A novel KKR-based ab initio scheme and its application
David Eilmsteiner, Arthur Ernst and Paweł A. Buczek
A novel implementation of the linear response time-dependent density functional theory addressing
spin excitations in non-collinear magnets based on the Korringa-Kohn-Rostoker Green's function method is presented. Following the exposition of the formalism based on the adiabatic local
spin density approximation to the exchange-correlation kernel generalized to the noncollinear case, the computational scheme is discussed in detail. The formation of the Goldstone modes in non-collinear susceptibility calculations is elaborated on formally and from the numerical convergence point of view. The scheme is deployed to study the dispersion and Landau damping of
magnons in the altermagnetic non-collinear kagome antiferromagnet Mn$_{3}$Ir. The non-monotonous dependence of the damping on the
magnon frequency makes the large momentum excitations attractive in the terahertz spintronics. To this end, we analyze the real-time and real-space dynamics of the
magnetic modes, including their strongly chirality-dependent attenuation.
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Strongly Correlated Electrons
Anisotropic magnetoelastic coupling in the honeycomb magnet Na$_3$Co$_2$SbO$_6$
Prashanta K. Mukharjee, Sebastian Erdmann, Lichen Wang et al. (+8 more)
We present magnetization and dilatometry measurements on the honeycomb cobaltate Na$_3$Co$_2$SbO$_6$ and map out its detailed field-temperature phase diagram down to sub-Kelvin temperatures. Our data for in-plane
magnetic fields show a strongly anisotropic $c^{*}$-axis
lattice response, which is dominated by the variation of Co–O–Co bond angles according to ab initio calculations. At $T = 0.4$~K, the magnetization $M(B)$ exhibits step-like features that are also highly anisotropic. In the case of $B \parallel b$, a small hysteresis observed around the second field-induced
magnetic transition ($B_{c2}$) indicates its first-order character, whereas divergence of the
magnetic Grüneisen parameter at $B_{c2}$ is suppressed upon cooling and signals the absence of
quantum critical behavior upon entering the field-polarized state. None of our thermodynamic measurements provide evidence for a field-induced
quantum spin liquid state near or above $B_{c2}$.
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All authors Prashanta K. Mukharjee, Sebastian Erdmann, Lichen Wang, Julian Kaiser, Anton Jesche, Pascal Puphal, Masahiko Isobe, Matthias Hepting, Bernhard Keimer, Philipp Gegenwart, Alexander A. Tsirlin
Disordered Systems and Neural Networks · Cross-listed from cs.NE
A Dynamical Theory of Sequential Retrieval in Input-Driven Hopfield Networks
Simone Betteti, Giacomo Baggio and Sandro Zampieri
Reasoning is the ability to integrate internal states and external inputs in a meaningful and semantically consistent flow. Contemporary machine learning (ML) systems increasingly rely on such sequential
reasoning, from
language understanding to multi-modal generation, often operating over dictionaries of prototypical patterns reminiscent of associative
memory models. Understanding
retrieval and sequentiality in associative
memory models provides a powerful bridge to gain insight into ML
reasoning. While the static
retrieval properties of associative
memory models are well understood, the theoretical foundations of sequential
retrieval and multi-
memory integration remain limited, with existing studies largely relying on numerical evidence. This work develops a dynamical theory of sequential
reasoning in Hopfield networks. We consider the recently proposed input-driven plasticity (IDP) Hopfield network and analyze a two-timescale architecture coupling fast associative
retrieval with slow
reasoning dynamics. We derive explicit conditions for self-sustained
memory transitions, including gain thresholds, escape times, and collapse regimes. Together, these results provide a principled mathematical account of sequentiality in associative
memory models, bridging classical Hopfield dynamics and modern
reasoning architectures.
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Mesoscale and Nanoscale Physics
Simultaneous anti-bunched and super-bunched photons from a GaAs Quantum dot in a dielectric metasurface
Sanghyeok Park, Oleg Mitrofanov, Kusal M. Abeywickrama et al. (+9 more)
Semiconductor quantum dots host a rich
manifold of excitonic complexes, including neutral
excitons that emit anti-bunched single
photons and charged
exciton complexes capable of producing super-bunched
photons via cascade emission. Accessing both emission regimes from a single emitter would open routes to novel
quantum protocols, including advanced
quantum imaging. In practice, however, emission from charged
exciton complexes is intrinsically weak, often orders of magnitude dimmer than neutral
excitons, placing simultaneous dual-mode operation out of reach. Here, we overcome this limitation by
embedding the
quantum dot in a dielectric Mie-resonant metasurface that provides order-of-magnitude photoluminescence enhancement across both neutral and charged
exciton transitions of a single GaAs
quantum dot. Under identical non-resonant pumping conditions, the emission from the neutral
exciton yields anti-bunched emission ($g^{(2)}(0) < 0.5$) and the emission from positively charged
exciton complexes shows super-bunched emission ($g^{(2)}(0) > 3.5$) with comparable count rates (~12 kHz). Crucially, super-bunching emerges only when charged
exciton emission spectrally overlaps with the Mie resonances and vanishes in un-patterned slabs, demonstrating that photonic engineering, is essential for accessing these weak
quantum light states. These results demonstrate a scalable, position-tolerant platform for harnessing the full excitonic structure of solid-state emitters.
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All authors Sanghyeok Park, Oleg Mitrofanov, Kusal M. Abeywickrama, Samuel Prescott, Jaeyeon Yu, Stephanie C Malek, Hyunseung Jung, Emma Renteria, Sadhvikas Addamane, Alisa Javadi, Igal Brener, Prasad P Iyer
Superconductivity
Enhancing the Energy Resolution in Scanning Tunneling Microscopy: from dynamical Coulomb blockade to cavity quantum electrodynamics
Xianzhe Zeng, Janis Siebrecht, Haonan Huang et al. (+4 more)
Scanning tunneling microscopy and spectroscopy have become indispensable tools for probing condensed matter at atomic length scales, yet achieving ultimate energy resolution remains a persistent challenge. At mK temperatures, the dynamical Coulomb blockade regime fundamentally limits spectroscopic precision through energy exchange between tunneling electrons and the electromagnetic environment. Here, we demonstrate that combining local electromagnetic shielding with low-pass filtering directly at the cryogenic scan head improves the energy resolution by nearly an order of magnitude, reaching
benchmark values as low as 3.7$\mu$eV at 10mK. We attribute this enhancement to efficient suppression of high-frequency radiation and capacitive shunting of the tunnel junction. Remarkably, this improved sensitivity reveals that the Josephson current couples to electromagnetic cavity modes of the centimeter-scale scan head, establishing a direct connection between atomic-scale tunneling processes and macroscopic cavity
quantum electrodynamics. These advances open pathways for exploring ultra-low-energy phenomena with unprecedented precision.
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All authors Xianzhe Zeng, Janis Siebrecht, Haonan Huang, Sujoy Karan, Joachim Ankerhold, Klaus Kern, Christian R. Ast
Statistical Mechanics
Dynamically Emergent Correlations
Satya N. Majumdar and Gregory Schehr
In this perspective article, we discuss the scenario of dynamically emergent correlation (DEC) arising in classical and
quantum noninteracting systems when they are subjected to a common fluctuating
stochastic environment. The key property of such systems is that the strong correlations between different particles emerge from the dynamics and not from built-in interactions. In many cases, these strong correlations persist even at long times in the stationary state. Computing observables explicitly for such strongly correlated states in general is very hard. Remarkably, the stationary states in several models of DEC exhibit an interesting analytical structure that allows to compute physical observables, despite being strongly correlated. Recent experiments on trapped colloidal particles have established that these DEC in the stationary state can in fact be measured. DEC is a rapidly emerging domain of strongly correlated out-of-
equilibrium statistical physics, with both theoretical and experimental, as well as classical and
quantum, components.
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Materials Science
Influence of stacking, coordination, and surface chemistry on Al intercalation in V$_2$CT$_2$ and Ti$_3$C$_2$T$_2$ MXenes for Al-ion batteries
Amal Raj Veluthedath Nair and Nuala M. Caffrey
As the energy storage ecosystem evolves beyond lithium, MXenes, a versatile family of 2D materials derived from MAX phases, have emerged as promising candidates for next-generation energy storage electrodes due to their tunable surface chemistry, large interlayer spacing, and excellent electronic conductivity. In this work, we use density functional theory to investigate Ti$_3$C$_2$ and V$_2$C MXenes as cathodes in Al-ion batteries. Four stacking configurations of the two-dimensional sheets and two different ion coordination sites are evaluated to understand their influence on ion intercalation and mobility. We find that the stacking configuration and surface chemistry critically impact interlayer spacing and electrochemical performance. O-terminated layers in an octahedral stacking exhibit remarkable structural stability with minimal interlayer expansion upon ion intercalation, particularly for Al intercalation in V$_2$C which exhibits an interlayer expansion of 0.1 angstrom, consistent with experimental findings. While octahedral stacking is observed to be energetically more favourable, it reduces ion mobility compared to prismatic stacking. Furthermore, O-terminated MXenes exhibit high theoretical specific capacities, reaching more than 270 mAh/g. F-terminated MXenes are considerably more unstable after intercalation and as a result exhibit much lower Al capacities. These findings highlight the importance of stacking configurations, termination and intercalant chemistry in MXenes for battery applications.
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Superconductivity
Fingerprint of $T_c$ advancement in Li-doped Bi-2223 superconductors prepared by cationic molecular mixing within Pechini sol-gel synthesis
N.K. Man, Huu T. Do, Nguyen V. Tu et al. (+1 more)
Trilayered Bi-2223
superconductor features the highest critical temperature $T_c$ among the bismuth-based cuprate collection and symbolizes an ideal prototype for studying intrinsic superconducting properties. The previous solid-state reaction method substantiated the growth of the high-quality Bi-2223 compounds but was accompanied by excessively laborious time and effort in terms of multiple grinding, pressing, as well as calcining stages, %causing risk of constituent loss, so finding a less tedious synthesis path is imperative. Here, we present an advanced sol-gel synthesis for assembling the multicomponent complexity of Bi1.4Pb0.6Sr2Ca2(Cu1-xLix)3O10
superconductors (Li-doped Bi-2223), with $x$ = 0.0–0.20, utilizing metallic cationic molecular mixing within the chemical Pechini polyesterization route followed by single-step pyrolysis and sintering stages. Although monovalent cations such as Li$^+$ pose limitations in establishing a perplex crosslinking network or chelating mechanism in the Pechini method, they represent a unique probe to elucidate the major chemical process during polymerization. We observe that a 5 molar~% Li-doped sample pronounces the highest $T_c$ = 111.4 K among the series of samples, as confirmed by both ac susceptibility and dc resistivity measurements, and is equivalent to the value obtained by our preceding solid state fabrication. In addition, we showcase a rare observation of layer-by-layer crystalline phase growth under microstructure probe. Through analyzing the reliable ac susceptibility data at low
magnetic fields in a wide range of frequency, we provide the
quantum flux formation and flux creep mechanism by Anderson-Müller's model and Cole-Cole plot.
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All authors N.K. Man, Huu T. Do, Nguyen V. Tu, Nguyen V. Quy
Mesoscale and Nanoscale Physics
All-Electrostatic Valley Filtering by Barrier Rotation in Tilted Dirac/Weyl Semimetals
Can Yesilyurt
Charge carriers in Dirac/Weyl semimetals with tilted anisotropic energy dispersion exhibit valley-dependent refraction and reflection at electrostatic barrier interfaces. Here, we show that an angled barrier interface provides a purely electrostatic route to valley filtering, producing finite valley-polarized conductance. We develop a generalized transfer-
matrix formalism for the tilted, anisotropic Dirac
Hamiltonian, extend it to treat electrostatic barriers at arbitrary angles, and calculate the transmission in the rotated-barrier frame. We also present simulated valley-resolved trajectories in a finite device geometry, demonstrating that one valley is selectively transmitted, while the other is predominantly reflected by the angled barrier, without invoking real or pseudomagnetic fields.
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