Disordered Systems and Neural Networks
High-Dimensional Latents Should Be Diagnosed Through Phase Structure
Alejandro Ascarate, Leo Lebrat, Rodrigo Santa Cruz et al. (+2 more)
We study autoencoder and variational-autoencoder latent spaces through the lens of
spin-glass theory. The paper has two components. First, we formalize a latent-space
spin-glass dictionary: for a fixed decoder, the reconstruction term together with a hyperspherical coordinates prior induces a
Hamiltonian on the latent sphere, where latent coordinates play the role of continuous
spins and the prior acts as an external
magnetic field. This allows us to import operational
spin-glass diagnostics – overlap distributions, susceptibility, and block-
spin coarse-graining – to detect ordered, disordered, and edge-of-stability phases in trained latent representations. Second, we show that deliberately driving the latent system toward the edge-of-stability of the topological trivialization regime has concrete downstream consequences. In generation, hyperspherical compression improves the reconstruction-generation trade-off on CIFAR-10 and CelebA64, yielding lower self-FID while preserving or improving reconstruction. In anomaly detection, the same semi-ordered latent geometry improves both fully unsupervised and conditional OOD detection, including real-world Mars Rover and
Galaxy Zoo
datasets, as well as CIFAR-10/100 and Imagenette-based OOD
benchmarks. We therefore advocate a phase-aware evaluation paradigm for AEs/VAEs, in which
spin-glass observables complement standard ML metrics and expose the latent regimes that underlie downstream success or failure in many cases.
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All authors Alejandro Ascarate, Leo Lebrat, Rodrigo Santa Cruz, Clinton Fookes, Olivier Salvado
Materials Science
Charge dynamics at nitrogen impurities and nitrogen-vacancy centers in diamond
Chandan Kumar Vishwakarma, J. K. Nangoi, Mark E. Turiansky et al. (+1 more)
The nitrogen-vacancy (NV) center in diamond is the prototype
quantum defect that enables a variety of diamond-based
quantum technologies. However, charge-state instability and spectral
diffusion, often induced by substitutional nitrogen
impurities (N$_{\rm C}$), remain key challenges for device performance. Here, we employ first-principles density functional theory calculations to quantitatively investigate nonradiative carrier capture processes mediated by multiphonon emission at both the NV center and the N$_{\rm C}$
impurity. For relevant cases, we also compute the rates of radiative and thermal emission processes. For N$_{\rm C}^0$ $\to$ N$_{\rm C}^-$, we obtain an electron capture coefficient of $2.2 \times 10^{-8}$ cm$^3$s$^{-1}$ at 300 K. Both the magnitude and temperature dependence are in excellent agreement with experimentally measured capture cross sections. Electron capture at N$_{\rm C}^+$ is even faster, with a capture coefficient of $1.0 \times 10^{-4}$ cm$^3$s$^{-1}$ at 300 K. For the NV center, we find that carrier capture rates involving only the ground states of NV$^0$ and NV$^-$ are negligibly slow. However, capture into the excited states (NV$^{0*}$ and NV$^{-*}$) is significantly faster. In particular, the capture coefficient for the hole capture process NV$^-$ $\to$ NV$^{0*}$ is as large as $1.8 \times 10^{-7}$ cm$^3$s$^{-1}$ and largely temperature-independent. Hole capture at NV$^-$ will thus occur via nonradiative capture into an excited state of NV$^{0}$ followed by fast radiative decay to the NV$^0$ ground state. Similarly, electron capture at NV$^0$ will occur via the NV$^0$ $\to$ NV$^{-*}$ $\to$ NV$^-$ pathway, but with a lower nonradiative capture coefficient ($2.1 \times 10^{-9}$ cm$^3$s$^{-1}$ at 300 K). Our calculated capture coefficients and rates provide essential information for analyzing charge-state dynamics.
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All authors Chandan Kumar Vishwakarma, J. K. Nangoi, Mark E. Turiansky, Chris G. Van de Walle
Materials Science
Proton-electron coupled catalyst for ionomer-free electrochemical energy conversion
Ao Zhang, Ran Wang, Mohammed O. Bazaid et al. (+14 more)
Efficient electrochemical energy devices are vital to renewable energy technology, yet coordinating the effective flow of electrons, ions, and chemical species continues to be a major challenge. In conventional
proton-exchange membrane fuel
cell (PEMFC) catalyst layers,
proton and electron transport are supplied separately through percolating carbon networks and ionomer binders, rendering the catalyst largely passive and imposing fundamental trade-offs between reactant accessibility, ionic conductivity, and catalyst activity. Here, we introduce a one-dimensional
proton-electron coupled catalyst (PECC) design, a transport-integrated electrocatalyst architecture in which the catalyst itself simultaneously supplies electronic and protonic transport to catalyst active sites. Using this PECC, PEMFCs can have an ionomer-free cathode catalyst layer (CCL), resulting in a dramatic 95% reduction in non-Fickian oxygen transport and boosting power density by 34% and 85% compared to traditional CCLs, with cathode Pt loadings of approximately 0.090 mg/cm^2 and 0.037 mg/cm^2, respectively. Meanwhile, PECC retains 65% of its mass activity and exhibits 32% higher power density than its ionomer-based CCL counterpart after 30k accelerated stressed test. Similar mass transport improvements have been observed in the electrochemical hydrogen pump (EHP) using PECC in the catalyst layers. Molecular dynamics simulations show the PECC's
proton conductivity is 249% higher than Nafion. This PECC catalyst structure addresses core transport problems in PEMFCs, leading to almost 20% improvement in fuel efficiency and opens up new possibilities for designing high-performance, cost-effective electrochemical devices.
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All authors Ao Zhang, Ran Wang, Mohammed O. Bazaid, Shiyi Wang, Ting-Jung Hsiao, Yibo Wang, Antonio Sorrentino, Yang Liu, Yu-Han Joseph Tsai, Boxuan Zhou, Bosi Peng, Zeyan Liu, Xiangfeng Duan, Adam Z. Weber, William A. Goddard III, Seung Soon Jang, Yu Huang
Materials Science
Redox behaviour of Fe impurities in BaTiO$_3$ based on many-body calculations
Zhiyuan Li, Hamza Zerdoumi, Hao Wang et al. (+2 more)
Based on detailed electronic structure and spectroscopy obtained using DFT-based many-body techniques, the redox behavior of Fe
impurities in BaTiO$_3$ is investigated. It is observed that Fe
impurities exhibit a mixed valence nature, comprising mostly Fe$^{2+}$ ($3d^6$) and Fe$^{3+}$ ($3d^5$) configurations, and such configurations can be tuned via oxygen vacancies which favor Fe$^{2+}$. The origin of such a redox behavior can be attributed to the charge transfer caused by shifting of the $d_{3z^2-r^2}$ orbitals. Furthermore, x-ray photoemission spectroscopy is evaluated by solving the Wannier function-derived local atomic
Hamiltonian using the
crystal field multiplet approach, with good agreements with recent experimental measurements.
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All authors Zhiyuan Li, Hamza Zerdoumi, Hao Wang, Ruiwen Xie, Hongbin Zhang
Mesoscale and Nanoscale Physics
Quantum Printing: Laguerre-Gaussian Beam Induced Topological Magnetic Textures
Yuefei Liu, Tien-Tien Yeh and Alexander V. Balatsky
Structured light has become a practical tool for controlling matter by applying tailored, space- and time-dependent electromagnetic fields. We show that Laguerre-Gaussian pulses imprint non-collinear
magnetic textures via the spatial structure of optical
magnetic field. Our route offers a direct spatial selectivity determined by the optical features without relying on material anisotropic interactions. The proposed printing approach does not require interfacial anisotropy or bulk chirality, current-driven torques, or thermal quenching. We use micromagnetic simulations to demonstrate the potential to create topological charge density emerging during the pulse and reveal control through the optical topological properties and polarization. These results suggest structured-light
quantum printing as a viable approach for magnonics and motivate studies toward reconfigurable topological textures enabled by ultrafast THz optics and non-thermal control.
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Statistical Mechanics · Cross-listed from nlin.AO
Self-consistent analysis of the Kuramoto model with higher-order interactions
Chanin Kumpeerakij and Juan G. Restrepo
The Kuramoto model with higher-order interactions has recently been shown to exhibit bistability, explosive synchronization transitions, and rich collective dynamics. Existing analytical approaches, however, typically rely on all-to-all coupling or mean-field approximations of the underlying hypergraph structure. While these methods describe typical networks in the thermodynamic limit, they generally fail to capture the effects of finite hypergraph and oscillator frequency realizations. To address this limitation, we develop a self-consistent analytical framework for the Kuramoto model with dyadic and triadic interactions on hypergraphs. We introduce generalized local order parameters that capture the combined effects of dyadic and triadic phase correlations, and derive a hierarchy of approximation schemes for the local and global synchronization order parameters. Using these approximations, we determine critical coupling strengths for the onset of synchronization and bistability. In particular, we show that the critical triadic coupling strength governing the onset of bistability depends on correlations between the eigenvectors of the dyadic adjacency
matrix and the triadic interaction structure. Numerical simulations on homogeneous and heterogeneous hypergraphs validate the theory and illustrate the distinct regimes of applicability of the approximation schemes.
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Disordered Systems and Neural Networks · Cross-listed from nlin.AO
Memory Uncertainty Relation and Harmonic Memory in Random Recurrent Networks
Taichi Haruna and Kohei Nakajima
We present an inequality that bounds the short-term
memory capability of dynamical systems from below. It can be interpreted as an uncertainty relation between a measure of short-term
memory and that of the size of state fluctuations induced by input signals. The lower bound can be achieved by a readout weight and thus represents a suboptimal
memory called harmonic
memory. We examine analytically and numerically the inequality in a number of reservoir systems subject to input noise. We illustrate cases in which equality is achieved exactly, equality holds asymptotically, and the inequality is strict. We also study the effect of a state-space regularization to elucidate the inequality in terms of the fluctuation structure of the state-space. We find that a certain strength of input noise induces extra
memory under the regularization, and we refer to this phenomenon as noise-induced
memory. We observe that the
memory uncertainty relation does not hold in general for the regularized
memory and harmonic
memory. This fact is explained in terms of the mechanism of noise-induced
memory.
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Materials Science
Ab-initio Crystal Structure Determination from Powder X-Ray Diffraction
Kaixiang Su, Osman Goni Ridwan, Hongfei Xue et al. (+1 more)
Determining
crystal structures from powder X-ray diffraction (PXRD) has been a significant challenge in materials science, particularly when experimental data contain noise or the target structure has a high complexity. While recent AI generative models show promise for rapid structure generation, they predominantly employ data-driven approaches to learn direct mappings between PXRD patterns and
crystal structures, often failing on complex or out-of-distribution cases. In this work, we present a hybrid ab-initio approach that decomposes structure determination into a two-stage optimization problem: (1) discrete selection of space group
symmetry, unit
cell parameters, and Wyckoff site combinations; and (2) continuous optimization of atomic coordinates within the selected Wyckoff positions. By integrating AI-based techniques for peak profile analysis, density estimation and energy minimization with physics-informed constraints, our method systematically overcomes limitations of purely data-driven PXRD solvers. We demonstrate that this hierarchical optimization framework enables robust structure determination even for challenging cases with high structural complexity or limited experimental data quality. Our approach provides a principled pathway for incorporating crystallographic knowledge into AI models for more reliable and generalizable
crystal structure determination.
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All authors Kaixiang Su, Osman Goni Ridwan, Hongfei Xue, Qiang Zhu
Mesoscale and Nanoscale Physics · Cross-listed from quant-ph
Dissipative acousto-mechanical parametric interface between high-overtone acoustics and flexural phonons
Xun Ji, Huanying Sun, Longhao Wu et al. (+4 more)
High-overtone bulk acoustic wave resonators (HBARs) promise advanced phononics, yet achieving nonlinearity remains challenging. We demonstrate a radiation-pressure-type parametric interaction between GHz HBARs and low-frequency flexural modes in a suspended silicon nitride membrane, where mechanical displacement modulates the external dissipation rate to enable dissipative acousto-mechanical coupling. Benefiting from the high quality factor, the system enters the resolved-sideband regime at room temperature, yielding acousto-mechanically induced transparency. We observe tunable Kerr nonlinearity and generate coherent HBAR frequency combs via two-tone driving. Notably, our dissipative coupling strength is 20 times larger than the dispersive coupling, the highest ratio among reported hybrid dissipative-dispersive coupling systems, resulting in the experimental observation of amplification in the reflection spectra under red-sideband driving. The ability to interface dense HBAR modes with a common mechanical resonator provides a scalable on-chip platform for multimode phononic information processing, with
quantum phononics potentially achievable at sub-Kelvin temperatures.
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All authors Xun Ji, Huanying Sun, Longhao Wu, Qichun Liu, Yulong Liu, Mika A. Sillanpää, Tiefu Li
Superconductivity
Theoretical study of superconductivity in freestanding infinite-layer nickelate membranes under pressure: mitigation of excess correlation enhances $T_c$
Mahiru Seki, Reo Kono, Naotaka Tanaka et al. (+5 more)
We theoretically investigate a freestanding membrane of infinite-layer nickelate Nd$_{0.85}$Sr$_{0.15}$NiO$_2$ under pressure by constructing a seven-orbital effective model based on first-principles calculations. By performing the fluctuation exchange (FLEX) approximation, we demonstrate that the seven-orbital model explains a monotonic increase in $T_c$ reported in a recent experiment. This enhancement of superconductivity is attributed to the mitigation of excessively strong electron correlations caused by exceptionally low valence of Ni atom. Furthermore, we examine the dynamical stability of the
crystal structure under pressure through
phonon calculation.
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All authors Mahiru Seki, Reo Kono, Naotaka Tanaka, Kensei Ushio, Daiki Nakaoka, Masayuki Ochi, Kazuhiko Kuroki, Hirofumi Sakakibara
Materials Science
Application and Performance Assessment of Annealing Methods for Electrostatic-Energy-Based Configuration Search in Mixed Crystals
Tack Saquai, Kenta Hongo, Ryo Maezono et al. (+1 more)
In first-principles design of solid solutions and disordered materials, exhaustive evaluation of all possible substitutional configurations is often impractical because the number of site occupations increases exponentially. Here, we develop a framework for pre-screening mixed-
crystal configurations using annealing methods, where the Ewald electrostatic energy is used as the objective function. Substitutional occupations are represented by binary variables, allowing the Ewald energy to be mapped onto an Ising-type
Hamiltonian and the search for low-energy configurations to be formulated as a combinatorial optimization problem. We implement this formulation using simulated annealing (SA) and
quantum annealing (QA), and
benchmark their performance against exhaustive search. For the small-scale system CaYAlO$_4$, SA achieved a speed-up of about 30 times, while QA achieved a speed-up of more than 100 times; both methods identified all lowest-energy configurations. For the medium-scale system $\beta$-KSbF$_4$ and the large-scale Ba-doped SiAlON system, SA achieved speed-ups of about 200-300 times while robustly identifying the lowest-energy structures. In contrast, QA was effective for the small-scale case but showed limited speed-up for medium-scale problems and missed some low-energy configurations due to chain breaks. These results indicate that SA is currently the most robust and general-purpose approach for rapid pre-screening of mixed-
crystal configurations based on electrostatic energy. The proposed formulation can be implemented automatically using publicly available libraries and provides a practical route for accelerating candidate-structure generation before first-principles calculations.
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All authors Tack Saquai, Kenta Hongo, Ryo Maezono, Tom Ichibha
Mesoscale and Nanoscale Physics · Cross-listed from quant-ph
Algebraic Tomography of Non-Hermitian Floquet Systems from Observable Traces
Syo Kamata
We formulate a framework of Floquet algebraic
tomography for finite-dimensional non-Hermitian monodromy
matrices from observable trace sequences $\zeta_n^{(O)}={\rm Tr}(OM^n)$. Since these sequences are constrained by the characteristic
polynomial of $M$, the inverse problem is a finite-dimensional algebraic reconstruction problem rather than a generic exponential fit. We organize the reconstruction through the observable resolvent, spectral determinant, and Dirichlet spectral data, separating the common spectral skeleton from observable-dependent dressing. Cayley–Hamilton and Hankel methods recover the similarity-invariant spectral data, while multi-observable and Liouville-space extensions connect the construction to realization theory and
tomography reconstruction. We further clarify the limits of identifiability from restricted observable
algebras: the data determine a visible representative, micromotion can enlarge the sampled visible operator space, and exact
symmetries impose residual invisible sectors. Two examples, a driven transmon qutrit and a finite non-Hermitian Floquet SSH chain, demonstrate leakage-induced visibility expansion, observable-dependent phase response, EP-accessible branch geometry, and disorder/probe-dependent observable-dimension readouts.
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Statistical Mechanics
Manipulation of information flow and thermodynamic performance in nonreciprocal quantum dot information engines
Hao Feng and Junjie Liu
Quantum information engines leverage information as a thermodynamic resource to facilitate energy conversion. In the operation of such engines, the information flow between the working substance and the controller is pivotal, however, strategies for its efficient manipulation remain largely unexplored. Here, we investigate an autonomous information engine based on a double-
quantum-dot setup, where a downstream dot coupled to two reservoirs acts as the working substance, and an upstream dot coupled to a single reservoir serves as the controller. By extending the second law of thermodynamics to incorporate the effects of nonreciprocal couplings between the dots and their electronic reservoirs, we develop a thermodynamic framework that allows us to demonstrate that nonreciprocity can significantly modulate the inter-dot information flow, thereby providing a robust control mechanism. We show that the influence of nonreciprocity can be equivalently understood through a mapping to an effective reciprocal system upon a reparameterization of chemical potentials and the electron-electron coupling strength. We further analyze the impact of nonreciprocity on the engine's performance and operation regime. Our findings establish nonreciprocal coupling as an effective control knob for designing and optimizing
quantum dot information engines, surpassing the capabilities of conventional reciprocal configurations.
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Statistical Mechanics
Rare events of small-noise Doob conditioned processes
Iago N. Mamede and Francesco Coghi
Doob fixed-time conditioning enables the sampling of rare trajectories of Markov processes by modifying the drift so that reaching a prescribed target at a given time is guaranteed. We study the statistics of this conditioned path ensemble through the moment generating function in the weak-noise large deviation regime. Since the Doob drift is rarely available in closed form, we reinterpret the conditioned ensemble as the original process post-selected on the terminal constraint, thereby avoiding explicit construction of the Doob transform. This viewpoint then yields an optimal-control representation for the leading exponential contribution to the generating function, expressed as a variational principle with terminal boundary conditions set by the Doob end-point constraint. We illustrate the framework with two analytical examples and with an application to heat dissipation of a minimal model of biomolecular folding.
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Superconductivity
Nonunitary triplet superconductivity in the Z2 topological metal SrPd2As2
Aarti, Dibyendu Samanta, Kartik Panda et al. (+9 more)
In Z2 topological metals, nontrivial band
topology and strong
spin-orbit coupling (SOC) impose
symmetry constraints that can stabilize unconventional superconducting states, even when thermodynamic probes indicate an isotropic gap. Here, we investigate the superconducting ground state of such a material, SrPd2As2, using
muon spin rotation and relaxation (muSR), first-principles calculations, and Ginzburg-Landau analysis. Transverse-field muSR indicates a fully gapped superconducting state below Tc = 0.94 K, while zero-field muSR detects spontaneous internal
magnetic fields below Tc, establishing time-reversal
symmetry (TRS) breaking. Electronic structure calculations identify SrPd2As2 as a Z2 topological metal with surface states crossing the
Fermi level. Standard anisotropic Migdal-Eliashberg calculations predict a nodal gap and overestimate Tc, indicating that a purely
phonon-mediated pairing mechanism is insufficient. We resolve this apparent contradiction by showing that the interplay of SOC, tetragonal
symmetry, and an open
Fermi surface
topology stabilizes a nonunitary triplet superconducting state whose
symmetry-imposed nodes lie in momentum-space regions devoid of electronic states. This yields a fully gapped thermodynamic response while naturally breaking TRS. Our results establish SrPd2As2 as a clean platform for bulk nonunitary triplet pairing and a promising candidate for intrinsic topological superconductivity.
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All authors Aarti, Dibyendu Samanta, Kartik Panda, Devashibhai Adroja, Daloo Ram, Zakir Hossain, Rhea Stewart, Adrian Hillier, Amitava Bhattacharyya, Samar Layek, Sudeep Kumar Ghosh, Vivek Kumar Anand
Strongly Correlated Electrons
Emergent Dispersive Multipolar Excitations in NaErSe$_{2}$
Zheng Zhang, Mingfang Shu, Mingtai Xie et al. (+6 more)
In most condensed-matter systems, local and collective excitations remain decoupled due to their distinct energy scales. Here, we identify coupled local-collective excitations in the triangular antiferromagnet NaErSe$_2$ by combining
neutron spectroscopy with total angular momentum modeling. The low-lying crystalline electric field (CEF) doublets include a dipolar $\Gamma_4$ ground state forming stripe-$x$ order and a $\Gamma_{5,6}$ excited state with dipole-octupole character. High-resolution spectra reveal emergent
symmetry-selected dispersions, where
magnon branches from the ground state are replicated on higher $\Gamma_4$ levels but couple with the $\Gamma_{5,6}$ levels to form a distinct multipolar band. An applied
magnetic field reconstructs the CEF wavefunctions and polarizes the system into a multipolar ferromagnet, further reshaping the spectra. This study demonstrates the emergent coupling of local and collective excitations driven by strong
spin-orbit coupling and establishes NaErSe$_2$ as a platform for field-tunable multipolar excitations in frustrated magnets.
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All authors Zheng Zhang, Mingfang Shu, Mingtai Xie, Weizhen Zhuo, Yanzhen Cai, Christian Balz, Jianting Ji, Feng Jin, Jie Ma
Superconductivity
Synchronization of Bloch Oscillations in array of parallel Josephson Junctions
R. Shaikhaidarov, R. Hussain, V.N. Antonov et al. (+1 more)
We demonstrate the synchronization of current quantization in a parallel array of weakly coupled Josephson Junctions operating in the regime of the coherent
quantum phase slip. The first quantized current step on the voltage-current characteristic of 69 parallel Josephson junctions, under microwave excitation at a frequency of f = 19.325 GHz, is observed at 426 nA. Experiments show that accuracy of quantization does not degrade with increasing number of combined Josephson junctions. This demonstration addresses the issue of quantized current amplitude requirements adopted for a practical
quantum standard, while leaving the question of accuracy for further research. At present, the
quantum current standard of accepted metrological accuracy in the triangle of electrical units is under development. The other two, the Volt and Ohm standards based on the Josephson and
Quantum Hall effects, respectively, are already well established in metrology.
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All authors R. Shaikhaidarov, R. Hussain, V.N. Antonov, E. Il'ichev
Statistical Mechanics
Strong Eigenstate Thermalization from Mean-Ergodic Non-chaotic Dynamics
Avadhut V. Purohit, Harshit Sharma and Udaysinh T. Bhosale
We report an example of a many-body system, derived from the double kicked top (DKT), with non-chaotic yet mean-ergodic dynamics that displays strong eigenstate thermalization hypothesis (ETH) in the
quantum regime. The analysis addresses a key open question: whether strong ETH is a
quantum analog of ergodicity (or mean-ergodicity). Despite non-chaotic dynamics, the fluctuations of the diagonal
matrix elements of an observable scale as $D^{-1/2}$, where $D$ denotes the
Hilbert space dimension. Furthermore, the off-diagonal
matrix elements show parameter-independent distribution, together with a smooth function $f_O(\bar{E}, \omega)$ that becomes nearly uniform in the large-$k_\theta$ domain. Our findings show that even mean-ergodic and non-chaotic systems can exhibit strong ETH.
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Statistical Mechanics
Implicit Binarization via Complex Phase Dynamics in Combinatorial Optimization
Khen Cohen, Mark Glass, Meir Feder et al. (+1 more)
We introduce a physics-inspired continuous relaxation framework that yields substantially improved solutions for NP-hard combinatorial optimization problems, including Quadratic Unconstrained Binary Optimization (QUBO), binary sparse coding, and planted-solution Ising models. By parameterizing discrete binary variables as continuous wave-like states on the complex unit circle, we inherently smooth highly non-convex energy landscapes. We show that representing binary variables as complex phases reveals an implicit regularization mechanism that promotes convergence toward discrete states. Extracting this mechanism yields significant improvements even within standard real-valued optimization frameworks, using this regularizer explicitly. Empirically, this regularization yields vastly higher ground-state convergence rates than standard real-valued alternatives. Our models achieved zero error in large-scale 160x160 QUBO tasks under severe noise (sigma=0.25), and outperformed traditional
algorithms (OMP and LASSO) in underdefined sparse coding with perfect recovery at sigma=0.15. The solver's robustness was further validated by recovering exact ground-state configurations in 8 out of 11 rigorously engineered planted-solution
benchmarks.
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All authors Khen Cohen, Mark Glass, Meir Feder, Yaron Oz
Materials Science
Techno-economic Analysis of Light Isotope-enriched Elements for Lightweighting Applications
Wenbo Bao, Zhihao Yang, Taeyoung Wang et al. (+2 more)
Lightweighting is critical to mass-sensitive applications such as aircraft and space transportation. Conventional lightweight strategies often rely on new designs of materials and structures. An alternative approach is to enrich the lightest stable isotopes in an element to reduce the elements atomic mass while having little effect on structural and chemical properties. However, the economic feasibility of this concept remains unclear. Here we present a techno-economic analysis of light isotope-enriched elements for lightweighting applications by estimating isotope enrichment cost and the economic gain from mass reduction. The enrichment cost is scaled from established large-scale processes. Twelve common aerospace-relevant elements are considered, including Li, B, C, Mg, Cl, Ti, Ni, Fe, Cu, Zn, Mo, and Sn. We find that nine elements, especially Li, B, Zn, Ni, Mo, and Sn, show potentially attractive economic benefit at moderate enrichment levels, whereas C, Mg, and Fe provide little or no benefit. With the optimized enrichment levels, an Airbus A380 is expected to save approximately USD 700 K over a 30-year operational lifetime, a SpaceX Falcon 9 could save USD 516 K, and a SpaceX Starship is expected to save USD 2.37 million over its whole lifetime. While the exact enrichment cost needs to be further investigated, these results provide an initial screening of promising candidate elements and highlight isotopic mass reduction as a potential drop-in lightweighting strategy.
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All authors Wenbo Bao, Zhihao Yang, Taeyoung Wang, Joseph F. Wild, Yuan Yang
Statistical Mechanics
The peculiar response of Kelvin-Voigt chains with a free end
Rupayan Saha and Matthias Krüger
We exactly solve a model of a heterogeneous chain of overdamped, harmonically coupled particles with momentum-conserving dissipation. Despite being governed by a non-symmetric drift operator, the system admits an analytical diagonalization by use of a forward-difference transformation. In case of one free end, the response
matrix shows a peculiar staircase form: the response of particle $i$ to a force acting on particle $j$ is independent of the properties and the length of the chain-part between $i$ and $j$. For rank-deficient interaction
matrices, the state space is decomposed into free and constrained subspaces. We demonstrate that this separation has clear physical consequences: the free subspace governs steady state responses, while the constraint subspace governs the relaxation after cessation of forcing. We further show that a Maxwell chain arises as a singular limiting
topology of the Kelvin-Voigt chain. These results establish a framework for analyzing heterogeneous overdamped dynamics with momentum conservation.
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Materials Science
Multi-Source Domain Transfer Learning for Accurate Property Prediction in Two-Dimensional Materials
Huiyang Zhang, Xinyu Chen, Qionghua Zhou et al. (+1 more)
Machine learning has revolutionized materials discovery, but data scarcity remains a critical bottleneck for complex functional properties. As emerging systems, two-dimensional (2D) materials possess limited overall data volumes. Evaluating their diverse functional properties requires time-consuming simulations, hindering unified high-throughput screening. Furthermore, restrictions in known structural prototypes lead to highly fragmented data distributions. To address these challenges, we propose a multi-source domain transfer learning framework to extract generalizable and complementary knowledge from diverse crystalline systems. To mitigate data scarcity, the framework employs a shared feature extractor that integrates
adversarial transfer learning with maximum mean discrepancy, mapping
crystal structures into a domain-invariant latent space while preserving underlying physical correlations. To resolve distribution fragmentation, a sample-adaptive weighted ensemble strategy is subsequently utilized to dynamically aggregate predictions from multiple source domains. Relying solely on
crystal structures, the framework predicts 2D carrier mobilities with an R2 score exceeding 0.90. The framework successfully screened 55 novel high-mobility 2D
semiconductors, which were validated via first-principles electron-
phonon coupling analysis, confirming their exceptional transport properties and stability. This work can potentially accelerate machine learning-assisted materials design and discovery with less data restriction.
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All authors Huiyang Zhang, Xinyu Chen, Qionghua Zhou, Jinlan Wang
Superconductivity
Emergence of Triplet Superconductivity from Cavity Vacuum Fluctuations
Xin-Xin Yang, Shuai Zhang, Kun Ding et al. (+1 more)
Engineering
quantum materials with cavity fields has emerged as a powerful route to manipulate phases of
quantum matter in solids. Here we demonstrate that cavity
vacuum fluctuations alone can drive the emergence of triplet superconductivity in an otherwise singlet
superconductor. The
vacuum field renormalizes the electronic band structure in a polarization dependent manner, reshaping the
Fermi surface and altering the competition among
symmetry allowed pairing channels. As a result, multiple superconducting phases arise from the cavity
vacuum fluctuations. Above a critical light matter coupling, the leading instability switches from singlet to triplet pairing, yielding a superconducting state absent in the bare material. This
vacuum induced
symmetry transition produces distinct modifications of the gap structure and low energy quasiparticle spectrum. Our results establish cavity
vacuum engineering as a mechanism for generating unconventional superconducting phases and stabilizing triplet states of potential relevance for topological superconductivity.
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All authors Xin-Xin Yang, Shuai Zhang, Kun Ding, Xiaopeng Li
Strongly Correlated Electrons
Superconfined Antiferromagnons on the Two-Dimensional Penrose Lattice
Takashi Inoue and Shoji Yamamoto
We find novel confined states in the
spin-$S$ nearest-neighbor
antiferromagnetic Heisenberg model on the two-dimensional Penrose
lattice. Linear
spin waves have massively degenerate eigenstates strictly confined to tricoordinated sites. They contrast with the well-known itinerant analogs in the tight-binding model, where electrons are confined but extended to both tricoordinated and pentacoordinated sites. It is the site potentials in the
spin-wave
Hamiltonian, originating from Coulomb interactions between electrons, that confine
spin waves to minimally coordinated sites only. Confined states in the tight-binding
Hamiltonian consist of six types of building blocks, whereas those in the
spin-wave
Hamiltonian consist of only four of them. Confined
spin waves are robust against $1/S$ corrections. Emergent $O(S^{0})$ interactions further confine – superconfine –
spin waves into two separate groups within tricoordinated sites.
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Materials Science
Termination-Dependent Surface States and Magnetic Fingerprints of Chiral Helimagnet Cr1/3TaS2
Bo Liang, Xue Li, Congcong Le et al. (+36 more)
Chiral helimagnets based on intercalated transition-metal dichalcogenides, characterized by nano-scale
spin ordering, provide a powerful route to engineer
chiral spin textures (e.g. the topologically protected
magnetic solitons) and emergent electronic functionality at reduced dimensions, where surface and interface states often dominate device operation. However, despite growing interest, direct experimental studies of termination-dependent surface electronic structures and their temperature-driven
magnetic evolution remain largely unexplored, hindering a microscopic understanding of the electronic states that is crucial for the development of low-dimensional spintronic devices. Here, for the first time, taking Cr1/3TaS2 as a representative example, we systematically investigate the termination-dependent surface electronic states of the
chiral helimagnets and uncover their distinct temperature
evolution across the
magnetic transition (TC~142K) by combining high-resolution ARPES with a micro-focused beam and surface-state-resolved first-principles calculations. The TaS2-terminated surface hosts folded monolayer-like TaS2 bands under the $\sqrt3\times\sqrt3$ superlattice potential and a shallow triangular electron pocket at the superlattice $\bar K$ point arising from Cr-Ta orbital hybridization. In contrast, the Cr-terminated surface exhibits reconstructed hole pockets with pronounced
magnetic band splitting. This splitting disappears above TC and closely follows the
chiral helimagnetic order parameter, providing a direct spectroscopic fingerprint of
chiral helimagnetic order. In addition, multiple ultranarrow Cr-d-derived surface flat bands are resolved. These findings establish Cr1/3TaS2 as a model system in which surface electronic states are strongly coupled to
chiral magnetism, opening new opportunities for
chiral spintronic and valleytronic micro/nanodevices.
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All authors Bo Liang, Xue Li, Congcong Le, Zirui Wu, Wenpei Zhu, Neng Cai, Yong-Chang Lau, Xianxin Wu, Jiayu Liu, Zhanfeng Liu, Hongen Zhu, Tongrui Li, Zhicheng Jiang, Yu Huang, Wenchuan Jing, Xun Ma, Qi Jiang, Hang Li, Zhihao Cai, Xuezhi Chen, Gexing Qu, Yiwei Cheng, Bing-Jie Chen, Zhengtai Liu, Dawei Shen, Mao Ye, Shengtao Cui, Zhe Sun, Koji Miyamoto, Taichi Okuda, Kenya Shimada, Yaobo Huang, Zhenhua Chen, Lin Zhao, Baojie Feng, Xinguo Ren, Wenhong Wang, Xingjiang Zhou, Guodong Liu
Strongly Correlated Electrons
Spiral and Mixed Plaquette-Dimer Phases in the $S=1$ and $3/2$ Shastry-Sutherland Heisenberg Model
Han-Qing Wu, Muwei Wu and Shou-Shu Gong
We investigate the ground-state phase diagram of the $S=1$ and $S=3/2$ Heisenberg model on the two-dimensional Shastry-Sutherland
lattice (SSL) using density
matrix renormalization group (DMRG) and cluster mean-field theory (CMFT). Between the dimer phase and Néel
antiferromagnetic phases, we identify two intermediate phases: a mixed plaquette-dimer (MPD) phase and a spiral phase. These phases are characterized via bond energies and
spin-
spin correlation functions; phase boundaries are located from the ground-state energy derivative and
entanglement entropy. The MPD phase exhibits strong intradimer correlations and weak tetramerization on the empty plaquettes, and its transitions to the dimer and spiral phases are first order. Combining our results with the known boundaries for $S=1/2$ and the classical limit $S\to\infty$, we construct a global $S$-$g$ phase diagram. This diagram reveals the progressive suppression of
quantum effects with increasing $S$ and offers a theoretical framework for larger-$S$ SSL materials.
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Statistical Mechanics · Cross-listed from quant-ph
Fermi-Dirac machines as quantizations of neurons
Alexander He, Nana Liu and Mark M. Wilde
Fermi-Dirac machines were proposed recently as an approach to solving semidefinite optimization problems on
quantum computers. Here, we reinterpret them as canonical quantizations of classical
neurons. By viewing a classical
neuron as an activation function applied to a parameterized classical
Hamiltonian, we quantize this model by replacing classical variables with operators whose
eigenvalues encode their possible values. This follows the standard approach to canonical quantization in
quantum mechanics. Crucially, when the
Hamiltonian consists of commuting operators, our construction reduces exactly to a classical
neuron. More generally, our approach yields an activation observable, defined as an activation function applied to a parameterized
quantum Hamiltonian. The output of this quantized
neuron is a random variable with expectation value equal to that of the activation observable with respect to an input state. We develop efficient hybrid
quantum-classical
algorithms for evaluating outputs and gradients of our quantized
neurons, enabling evaluation and training. These
algorithms rely on basic primitives that include random sampling,
Hamiltonian simulation, and the Hadamard test. We also quantize a whole host of other activation functions, including the smooth rectified linear unit (ReLU), sigmoid linear unit, Gaussian-smoothed ReLU, and Gaussian error linear unit (GeLU), which are known to be useful for deep learning applications. Numerical experiments indicate that
neurons based on
quantum Hamiltonians can learn functions that classical
neurons cannot. We further define a computational decision problem based on
Fermi-Dirac
neurons and prove that it is BQP-complete, providing complexity-theoretic evidence against efficient classical simulation. Finally, we generalize our approach to continuous
quantum variables and sketch two different ways of composing these
neurons into networks.
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Materials Science
Colossal Type-II Multiferroic Polarization Driven by Collinear Spin Orders
Chengxi Huang, Xinhai Tu, Jintao Jiang et al. (+2 more)
Achieving strong magnetoelectric coupling (MEC) together with large ferroelectric polarization remains a central challenge in type-II multiferroics. In conventional
spin-driven multiferroics, the induced polarization is usually mediated by
spin-orbit coupling (SOC) or
spin-
lattice coupling (SLC). Since many representative systems are based on 3d transition-metal ions, where SOC is relatively weak and SLC-induced
lattice distortions are often limited, their polarizations are typically much smaller than those of proper ferroelectrics. Moreover, electric polarizations in type-II multiferroics are generally induced by spiral
spin orders stabilized by competing
magnetic interactions, which often leads to relatively low
magnetic transition temperatures. In this Letter, using
spin-group
symmetry, we propose an SOC- and SLC-independent route to MEC in collinear 3d
magnetic systems. We show that, even for a noncentrosymmetric
lattice structure, different collinear
magnetic configurations can either forbid or allow electric polarization, indicating direct
magnetic control of polarization and hence strong MEC. The first-principles calculations excluding SOC on monolayer 2H-VS2 support this picture: a collinear stripy
antiferromagnetic order induces an in-plane ferroelectric polarization up to 25.00 {\mu}C/cm2, about two orders of magnitude larger than that of typical type-II multiferroics. Furthermore, our microscopic model suggests that the induced polarization originates from SOC-independent p-d hybridization governed by electronic hopping. Our results suggest a possible route toward type-II multiferroics combining strong MEC with large electronic polarization in collinear 3d
magnetic systems.
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All authors Chengxi Huang, Xinhai Tu, Jintao Jiang, Xiangang Wan, Erjun Kan
Materials Science
Light-Driven Ferroic Switching Enables Reversible Control of Hydrogen Adsorption Thermodynamics
Xueqing Wan, Zhenlong Zhang, Charles Paillard et al. (+5 more)
Reversible ultrafast switching of surface thermodynamics is highly desirable for hydrogen storage and catalysis yet remains elusive at the nanoscale. Here we demonstrate that photoinduced ferroic-order switching in two-dimensional ionic ferroelectric monolayers enables rapid, reversible control of hydrogen binding. In TiGeSe$_3$, carrier-density-driven redistribution of transition-metal 3d orbital occupations triggers a sequential
evolution from the ferroelectric ground state to paraelectric phases with staggered or Zig-Zag
antiferromagnetic order. This switch continuously tunes the hydrogen adsorption free energy from 0.33 to 1.11 eV, shifting the interface from near-thermoneutrality to spontaneous desorption. Nonadiabatic dynamics indicate that electron-
phonon coupling promotes nonthermal H release, while picosecond carrier recombination rapidly restores the initial ferroic order, closing an ultrafast reversible cycle. Generality is further validated in AgBiP$_2$Se$_6$ and CuInP$_2$S$_6$, establishing ferroic order as an optically addressable knob for dynamic thermodynamic reconfiguration beyond static design.
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All authors Xueqing Wan, Zhenlong Zhang, Charles Paillard, Jian Zhou, Jinyang Ni, Chuanlu Yang, Zhijun Jiang, Laurent Bellaiche
Materials Science
Dilute Magnetism and Edge-State Engineering in Monolayer SnO
Yuya Fukuta, Souren Adhikary, Kazuhito Tsukagoshi et al. (+1 more)
Tin monoxide (SnO) is a p-type
oxide semiconductor whose electronic properties can be widely modified via atomic-scale engineering. Using density functional theory, we investigate the electronic and
magnetic properties of transition-metal (TM = Mn, Fe, Co and W) doped SnO monolayer within a large supercell. We find that all dopants induce finite localized
magnetic moments, primarily originating from $d$-orbitals of the
impurity atoms. We show that these localized
magnetic states give rise to nearly dispersionless bands in the vicinity of the
Fermi energy (taking Co doped SnO as an example). In addition, we investigate dimensional effects by constructing nanoribbon geometries of SnO monolayer. The ribbons exhibit intrinsic edge-localized states that are largely independent of ribbon width. For
chiral nanoribbons oriented along a low-
symmetry direction of the square
lattice, we find that oxygen-rich edges are thermodynamically most stable and remain semiconducting, whereas Sn-terminated edges host metallic one-dimensional conduction channels. Our results demonstrate that transition-metal doping and edge engineering provide effective routes to tailor the electronic properties of SnO monolayer, making it a promising candidate for future spintronic and nanoelectronic applications.
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All authors Yuya Fukuta, Souren Adhikary, Kazuhito Tsukagoshi, Katsunori Wakabayashi