Mesoscale and Nanoscale Physics · Cross-listed from quant-ph
Measuring and correcting nanosecond pulse distortions in quantum-dot spin qubits
Jiheng Duan, Fernando Torres-Leal and John M. Nichol
Gate-defined
semiconductor quantum dots utilize fast electrical control to manipulate
spin and charge states of individual electrons. Electrical pulse distortions can limit control fidelities but are difficult to measure at the device level. Here, we use detuning-axis pulsed spectroscopy to characterize baseband pulse distortions in a silicon double
quantum-dot. We extract the gate-voltage impulse response and apply a digital pre-distortion filter to eliminate pulse distortions on timescales longer than 1~ns. With the pre-distortion, we reduce the frequency chirp of coherent exchange oscillations in a singlet-triplet
qubit. Our results suggest a scalable and tuning-efficient method for characterizing pulse distortions in
quantum-dot
spin qubits.
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Materials Science
Ab initio Monte Carlo prediction of order-to-disorder transitions in multicomponent MXenes
Noah Oyeniran and Chongze Hu
This letter predicts unprecedented order-to-disorder transition behaviors in multicomponent MXenes using an integrated and improved first-principles Monte Carlo (MC) framework. The improvements include (i) structural relaxation and (ii) selective atom swapping during MC iterations for more accurate and efficient predictions. Using (TiMo)-based double transition metal (DTM) carbide MXenes as a model system, ab initio MC simulations reveal that surface termination and coordination environments play critical roles in governing chemical ordering in MXenes. Specifically, the formation of out-of-plane MXene (o-MXenes) with Mo segregation to outermost metallic layers (M') is only driven by the oxygen (O) termination at prismatic sites. In contrast, O termination at octahedral sites and fluorine (F) termination at both prismatic and octahedral sites always promote the formation of o-MXenes with Ti-segregated to M' layers. Furthermore, changing the F/O ratio at prismatic termination sites or alternating the atomic coordination within the MXene
lattices can induce an order-to-disorder transition in DTM MXenes.
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Materials Science
El Agente Sólido: A New Age(nt) for Solid State Simulations
Sai Govind Hari Kumar, Yunheng Zou, Andrew Wang et al. (+8 more)
Quantum chemistry calculations are a key component of the materials discovery process. The results from first-principles explorations enable the prediction of material properties prior to experimental validation. Despite their impact, the practical use of first-principles methods remains limited by the expertise required to design, execute, and troubleshoot complex computational workflows. Even when workflows are successfully built, they are sometimes rigid and not adaptable to different use cases. Recent advances in large
language models (LLMs) and agentic systems offer a pathway to flexibly automate these processes and lower barriers to entry. Here, we introduce El Agente Sólido, a hierarchical multi-
agent framework for automating solid-state
quantum chemistry workflows using the open-source
Quantum ESPRESSO simulation package. The framework translates high-level scientific objectives expressed in natural
language into end-to-end computational pipelines that include structure generation, input file construction, workflow execution, and post-processing analysis. El Agente Sólido integrates density functional theory with
phonon calculations and machine-learning interatomic potentials to enable efficient and physically consistent simulations. Extensive benchmarking and case studies demonstrate that El Agente Sólido reliably executes a wide range of solid-state calculations, highlighting its potential to improve reproducibility and accelerate computational materials discovery
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All authors Sai Govind Hari Kumar, Yunheng Zou, Andrew Wang, Jesús Valdés-Hernández, Tsz Wai Ko, Nathan Yue, Olivia Leng, Hanyong Xu, Chris Crebolder, Alán Aspuru-Guzik, Varinia Bernales
Materials Science
Leveraging mechanical resonances for the selection of promising materials in complex phase spaces
Christopher A. Mizzi, Osman El-Atwani, Tannor T.J. Munroe et al. (+2 more)
The "high-
entropy" paradigm has been applied to a central challenge in materials science, the design of new functional materials with enhanced performance for targeted applications, with some notable successes over the last twenty years. However, the immensity of the high-
entropy design space remains a major impediment to discovering optimal compositions with tailored microstructures. Suites of high-throughput computational tools have been developed to address this problem, but there is a compelling need to inform these models with fast, economical, non-destructive, and versatile experimental guidance. In this work, we demonstrate mechanical resonance measurements can fulfill this need. Mechanical resonance measurements enable the rapid, non-destructive assessment of materials created by novel syntheses and/or processes and provide high-accuracy determinations of elastic constants to directly
benchmark models. We exemplify these capabilities on W-Ta-Cr-V-Hf and Mo-Nb-Ti-V-Zr refractory high-
entropy alloys and suggest methodologies for the wider adoption and application of mechanical resonance measurements.
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All authors Christopher A. Mizzi, Osman El-Atwani, Tannor T.J. Munroe, Saryu Fensin, Boris Maiorov
Materials Science
Precise Determination of the Long-Time Asymptotics of the Diffusion Spreadability of Two-Phase Media
Shaobing Yuan and Salvatore Torquato
The time-dependent
diffusion spreadability $\mathcal{S}(t)$ is a powerful dynamical probe of the microstructure of two-phase heterogeneous media across length scales [Torquato, S., Phys. Rev. E., 104 054102 (2021)]. It has been shown that when the spectral density takes the power-law form $\tilde{\chi}_{_V}(\mathbf{k})\sim |\mathbf{k}|^\alpha$ as the wavenumber $|\mathbf{k}|$ tends to zero, the normalized excess spreadability $\mathscr{s}^{ex}(t)$ [proportional to $\mathcal{S}(\infty)-\mathcal{S}(t)$] scales as $\mathscr{s}^{ex}(t)\sim t^{-\frac{d+\alpha}{2}}$ in the long-time limit $t\to\infty$, enabling one to determine the infinite-wavelength scaling exponent $\alpha$. An
algorithm that allows one to reliably extract the exponent $\alpha$ from long-time spreadability data was previously devised [Wang, H., Torquato, S., Phys. Rev. Appl., 17 034022 (2022)]. In this paper, we further improve this procedure to obtain $\alpha$ even more accurately by incorporating higher-order correction terms to the long-time asymptotics and by utilizing analyticity properties of $\tilde{\chi}_{_V}(k)$ at the origin. We illustrate our procedure by analyzing hyperuniform ($\alpha> 0$), typical nonhyperuniform ($\alpha=0$), and antihyperuniform ($-d < \alpha <0$) models of two-phase media. In addition, by combining the large-$t$ asymptotic expansion of $\mathscr{s}^{ex}(t)$ with the small-$t$ expansion, we have devised a two-point Padé approximant to approximate $\mathscr{s}^{ex}(t)$ for all $t$ with just a few parameters. Our findings facilitate the characterization of the microstructure of two-phase media across length scales as obtained from numerical spreadability data or experimental data obtained from NMR relaxation measurements. Our work can also be applied in the inverse design of two-phase microstructures with targeted spreadability behaviors.
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Strongly Correlated Electrons
Direct imaging of a Berry curvature nematic state in a spin-compensated magnet
Weihang Lu, Camron Farhang, Yuchuan Yao et al. (+6 more)
Density waves conventionally describe the periodic modulation of charge or
spin, yet the spatial modulation of electronic geometry has remained elusive. Here, we report subtle micrometer-scale spatial modulations of the magneto-optical Kerr signal in the noncollinear antiferromagnet Mn3NiN with compensated
spins, consistent with a
magnetic-field-induced Berry
curvature density wave . These Berry
curvature modulations exhibit orientations unpinned from the
crystal lattice, forming a nematic state that spontaneously breaks rotational
symmetry. We attribute this spatial instability to field-induced spatial variations of the
spin texture driven by competing
magnetic interactions. This discovery unveils a new class of collective order in
spin-compensated magnets mediated by the
geometric phase of the wavefunction itself. Its wavelength is controlled by chemical doping and its amplitude by
magnetic field, providing concrete tuning knobs for
antiferromagnetic and altermagnetic spintronics.
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All authors Weihang Lu, Camron Farhang, Yuchuan Yao, Pratap Pal, Hao Zhang, Shaofeng Han, Shi-Zeng Lin, Chang-Beom Eom, Jing Xia
Statistical Mechanics
Scaling invariance: a bridge between geometry, dynamics and criticality
Edson D. Leonel and Diego F. M. Oliveira
Scale invariance is a central organizing principle in physics, underlying phenomena that range from critical behaviour in statistical mechanics to transport and chaos in nonlinear dynamical systems. Here we present a unified and physically motivated exploration of scaling concepts, emphasizing how invariance under rescaling transformations emerges across systems of increasing dynamical complexity. Rather than adopting a purely abstract approach, we combine simple geometrical constructions, analytical arguments, and prototypical dynamical models to build physical intuition. We begin with elementary, easily reproducible examples governed by a single control parameter, showing how power-law behaviour naturally arises when characteristic scales are absent. We then extend the discussion to nonlinear dynamical systems exhibiting local bifurcations, where two scaling variables control the relaxation toward stationary states. In this context, scaling invariance manifests through critical exponents, crossover phenomena, and critical slowing down, allowing systems of different dimensionality to be grouped into universality classes. Finally, we address continuous phase transitions in chaotic dynamical systems, including transitions from integrability to non-integrability and from bounded to unbounded
diffusion. By drawing on concepts traditionally associated with statistical mechanics, such as order parameters, susceptibilities,
symmetry breaking, elementary excitations, and topological defects, we show how these transitions can be interpreted within a coherent scaling framework. Taken together, the examples discussed here demonstrate that scaling invariance provides a unifying
language for understanding structure, transport, and criticality in nonlinear systems, bridging deterministic dynamics and nonequilibrium statistical physics in a transparent and physically intuitive manner.
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Disordered Systems and Neural Networks · Cross-listed from q-bio.NC
Scaling and tuning to criticality in resting-state human magnetoencephalography
Irem Topal, Anna Poggialini, Marco Dal Maschio et al. (+3 more)
From 1/f noise to neuronal avalanches, evidence of scaling in
brain activity has been increasingly linked to tuning to or near criticality. The concept of scaling is intimately related to the renormalization group (RG), in essence providing coarse-grained, simplified descriptions that generalize to classes of diverse physical systems. Following the RG idea, scaling laws have been reported in populations of spiking
neurons at microscopic scales. Whether similar scaling principles govern large-scale neural activity in the human
brain and how they relate to underlying neural physiology remains unresolved. Here, we analyze large-scale electrophysiological recordings (MEG) of human resting-state
brain activity and apply a RG-inspired coarse-graining approach to track collective neural dynamics across spatial scales. We find that multiple observables exhibit robust scale-invariant behavior under coarse-graining: activity variance and correlations grow according to power laws, covariance eigenspectra follow a characteristic scaling relation, and neuronal avalanche statistics remain invariant. Using an analytically tractable neural network model, we show that the observed scaling signatures arise when the system operates slightly below criticality, and that the scaling exponents depend on the excitation-inhibition balance. These findings demonstrate that RG-inspired scaling analysis can uncover signatures of critical dynamics in non-invasive human electrophysiology and suggest a principled route toward estimating excitation-inhibition balance from large-scale
brain recordings.
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All authors Irem Topal, Anna Poggialini, Marco Dal Maschio, Daniele De Martino, Oren Shriki, Fabrizio Lombardi
Other Condensed Matter · Cross-listed from quant-ph
Shortcuts to Adiabaticity via Adaptive Quantum Zeno Measurements
Adolfo del Campo
Stroboscopic measurements of a time-dependent projector generate a
quantum Zeno dynamics whose effective
Hamiltonian is the Kato-Avron
Hamiltonian for parallel transport, which reduces to counterdiabatic driving in the case of a nonselective measurement of the instantaneous eigenprojectors of the system. The same generator arises under continuous monitoring of a time-dependent observable and under a time-varying complex absorbing potential. Departures from the ideal Zeno limit are governed, in all three settings, by a single positive leakage operator with a dynamical and a purely
geometric contribution. Matching the corresponding generators yields a model-independent generalized Schulman relation for the
quantum Zeno dynamics in the three scenarios, and a purely
geometric bound on the measurement resources needed to steer a subspace along a prescribed path.
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Quantum Gases
Families of localized modes of Bose-Einstein condensates enabled by incommensurate optical lattice and photon-atom interactions
Pedro S. Gil and Vladimir V. Konotop
We consider a Bose-Einstein condensate (BEC) loaded into a one-dimensional optical cavity under the combined action of an external potential and atom-cavity coupling with mutually incommensurate periods. Such configuration enables the localization of matter waves even in the absence of two-body interactions. We study families of localized modes within the mean-field approximation for red and blue detunings from atomic and cavity resonances in relatively shallow quasiperiodic
lattices, beyond the validity of the tight-binding approximation. The parameter regimes supporting localization of atomic wave packets are identified. The system exhibits two types of bistability manifested as distinct
photon numbers under otherwise identical conditions. One type arises from the coexistence of multiple families of localized modes, typical of conservative nonlinear systems, while the other stems from the multivalued dependence of the families on system parameters, characteristic of systems exhibiting hysteresis. BEC in a cavity may also display pseudodegeneracy, understood as the existence of two distinct atomic-density distributions corresponding to the same atomic and
photon numbers (although different chemical potentials). The stability of the localized modes is analyzed. It is shown that, owing to the strong impact of long-range interactions on stability, a two-localized-mode configuration can operate as an XOR logic gate.
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Disordered Systems and Neural Networks · Cross-listed from stat.ML
Topological Exploration of High-Dimensional Empirical Risk Landscapes: general approach, and applications to phase retrieval
Antoine Maillard, Tony Bonnaire and Giulio Biroli
We consider the landscape of empirical risk minimization for high-dimensional Gaussian single-index models (generalized linear models). The objective is to recover an unknown signal $\boldsymbol{\theta}^\star \in \mathbb{R}^d$ (where $d \gg 1$) from a loss function $\hat{R}(\boldsymbol{\theta})$ that depends on pairs of labels $(\mathbf{x}_i \cdot \boldsymbol{\theta}, \mathbf{x}_i \cdot \boldsymbol{\theta}^\star)_{i=1}^n$, with $\mathbf{x}_i \sim \mathcal{N}(0, I_d)$, in the proportional asymptotic regime $n \asymp d$. Using the Kac-Rice formula, we analyze different complexities of the landscape – defined as the expected number of critical points – corresponding to various types of critical points, including local minima. We first show that some variational formulas previously established in the literature for these complexities can be drastically simplified, reducing to explicit variational problems over a finite number of scalar parameters that we can efficiently solve numerically. Our framework also provides detailed predictions for properties of the critical points, including the spectral properties of the Hessian and the joint distribution of labels. We apply our analysis to the real phase
retrieval problem for which we derive complete topological phase diagrams of the loss landscape, characterizing notably BBP-type transitions where the Hessian at local minima (as predicted by the Kac-Rice formula) becomes unstable in the direction of the signal. We test the predictive power of our analysis to characterize gradient flow dynamics, finding excellent agreement with finite-size simulations of local optimization
algorithms, and capturing fine-grained details such as the empirical distribution of labels. Overall, our results open new avenues for the asymptotic study of loss landscapes and topological trivialization phenomena in high-dimensional statistical models.
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Mesoscale and Nanoscale Physics · Cross-listed from quant-ph
Topological Boundary Time Crystal Oscillations
Dominik Nemeth, Ahsan Nazir, Alessandro Principi et al. (+1 more)
Boundary time
crystals (BTCs) break time-translation
symmetry and exhibit long-lived, robust oscillations insensitive to initial conditions. We show that collective
spin BTCs can admit emergent topological winding numbers in operator space. Expanding the density operator in a spherical tensor basis, we map the Lindblad dynamics onto an effective local hopping problem, where collective degrees of freedom label sites of an emergent two-dimensional operator space
lattice and identify topological obstructions that enforce the delocalization of operator modes on the
lattice. The resulting spectral delocalization provides a natural explanation for the robust oscillatory dynamics observed in BTCs. When combined with non-reciprocal transport of operator weight across operator space, this mechanism moreover also leads to the universality of long-time dynamics across a broad class of initial states. Our results frame BTC dynamics as a form of topologically constrained operator space transport and suggest a close connection to non-Hermitian skin-effects.
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All authors Dominik Nemeth, Ahsan Nazir, Alessandro Principi, Robert-Jan Slager
Materials Science
Inelastic Constitutive Kolmogorov-Arnold Networks: A generalized framework for automated discovery of interpretable inelastic material models
Chenyi Ji, Kian P. Abdolazizi, Hagen Holthusen et al. (+2 more)
A key problem of solid mechanics is the identification of the constitutive law of a material, that is, the relation between strain history and stress. Machine learning has lead to considerable advances in this field lately. Here we introduce inelastic Constitutive Kolmogorov-Arnold Networks (iCKANs). This novel artificial neural network architecture can discover in an automated manner symbolic constitutive laws describing both the elastic and inelastic behavior of materials. That is, it can translate data from material testing into corresponding elastic and inelastic potential functions in closed mathematical form. We demonstrate the advantages of iCKANs using both synthetic data and experimental data of the viscoelastic
polymer materials VHB 4910 and VHB 4905. The results demonstrate that iCKANs accurately capture complex viscoelastic behavior while preserving physical interpretability. It is a particular strength of iCKANs that they can process not only mechanical data but also arbitrary additional information available about a material (e.g., about temperature-dependent behavior). This makes iCKANs a powerful tool to discover in the future also how specific processing or service conditions affect the properties of materials.
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All authors Chenyi Ji, Kian P. Abdolazizi, Hagen Holthusen, Christian J. Cyron, Kevin Linka
Materials Science
Fracture Properties of Green Nano Fibrous Network with Random and Aligned Fibre Distribution: A Hierarchical Molecular Dynamics and Peridynamics Approach
Razie Izadi, Raj Das, Nicholas Fantuzzi et al. (+1 more)
Polylactic acid (PLA) nanofibrous networks have gained substantial interest across various engineering and scientific disciplines, such as tissue engineering, drug delivery, and filtration, due to their unique and multifunctional attributes, including biodegradability, tunable mechanical properties, and surface functionality. However, predicting their mechanical behaviour remains challenging due to their structural complexity, multiscale features, and variability in material properties. This study presents a hierarchical approach to investigate fracture phenomena in both aligned and randomly oriented nanofibrous networks by integrating atomistic modelling and nonlocal continuum mechanics, namely peridynamics. At the nanoscale, all-atom molecular dynamics simulations are employed to apply tensile loads to freestanding pristine and silver-doped PLA nanofibres, where key mechanical properties such as Young's modulus, Poisson's ratio, and critical energy release rate are determined. A new method is introduced to transfer data from molecular dynamics to peridynamics by ensuring convergence of the tensile response of a single fiber in both frameworks. This nano-to-micro coupling technique is then used to examine the Young's modulus, fracture toughness in modes I and II, and crack propagation in PLA nanofibrous networks. The proposed framework can also incorporate the effects of surface coating and fiber arrangements on the measured properties. This research paves the way for the development of stronger and more durable eco-friendly nanofibrous networks with optimised performance.
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All authors Razie Izadi, Raj Das, Nicholas Fantuzzi, Patrizia Trovalusci
Strongly Correlated Electrons
Anisotropic marginal Fermi liquid for Coulomb interacting generalized Weyl fermions
Gabriel Malavé, Rodrigo Soto-Garrido, Bitan Roy et al. (+1 more)
Owing to the power-law anisotropy in the quasiparticle dispersion, yielding an enhanced density of states, the effects of long range Coulomb interaction get amplified in three-dimensional generalized Weyl semimetals, characterized by integer monopole charge $n>1$ of the underlying Weyl nodes. Using a Wilsonian renormalization group approach controlled by a large-$N$ expansion with $N$ as the number of Weyl
fermion flavors and a gauge-consistent regularization fixed by the Ward-Takahashi identity, we uncover for $n\ge 2$ an extended interaction-dominated scaling regime with intrinsically anisotropic dynamic Coulomb screening, a finite fermionic anomalous dimension, and a power-law suppression of the quasiparticle residue, yielding an anisotropic marginal non-
Fermi liquid at intermediate energies. Ultimately, the effective fine structure constant flows to zero, albeit only logarithmically slowly, so the marginal
Fermi liquid phenomenology emerges as a broad crossover, controlled by a slowly running coupling. By contrast, for $n=1$ the system retains an isotropic marginal Weyl-
liquid character. These predictions can be tested via scaling in thermodynamics (specific heat and compressibility), direction-dependent optical conductivity, and by anisotropic broadening of the single-particle spectral function in angle-resolved photoemission spectroscopy.
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All authors Gabriel Malavé, Rodrigo Soto-Garrido, Bitan Roy, Vladimir Juričić
Statistical Mechanics · Cross-listed from quant-ph
A Study of Entanglement and Ansatz Expressivity for the Transverse-Field Ising Model using Variational Quantum Eigensolver
Ashutosh P. Tripathi, Nilmani Mathur and Vikram Tripathi
The Variational
Quantum Eigensolver (VQE) is a leading hybrid
quantum-classical
algorithm for simulating many-body systems in the NISQ era. Its effectiveness, however, depends on the faithful preparation of eigenstates, which becomes challenging in degenerate and strongly entangled regimes. We study this problem using the transverse-field Ising model (TFIM) with periodic boundary conditions in one, two, and three dimensions, considering systems of up to 27
qubits. We employ different ansatzes: the hardware-efficient EfficientSU2 from Qiskit, the physics-inspired
Hamiltonian Variational Ansatz (HVA) and HVA with
symmetry breaking, and
benchmark their performance using energy variance,
entanglement entropy,
spin correlations, and magnetization.
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Quantum Gases
Realization of fractional Fermi seas
Yi Zeng, Alvise Bastianello, Sudipta Dhar et al. (+7 more)
The Pauli exclusion principle is a cornerstone of
quantum physics: it governs the structure of matter. Extensions of this principle, such as Haldane's generalized exclusion statistics, predict the existence of exotic
quantum states characterized by fractional
Fermi seas (FFS), i.e. momentum distributions with uniform but fractional occupancies. Here, we report the experimental realization of fractional
Fermi seas in an excited one-dimensional Bose gas prepared through ramping cycles in the interaction strength. The resulting excited yet stable Bose-gas states exhibit Friedel oscillations, smoking-gun signatures of the underlying FFS. The stabilization of these states offers an opportunity to deepen our understanding of
quantum thermodynamics in the presence of exotic statistics and paves the way for applications in
quantum information and sensing.
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All authors Yi Zeng, Alvise Bastianello, Sudipta Dhar, Zekui Wang, Xudong Yu, Milena Horvath, Grigori E. Astrakharchik, Yanliang Guo, Hanns-Christoph Nägerl, Manuele Landini
Quantum Gases
Exotic critical states as fractional Fermi seas in the one-dimensional Bose gas
Alvise Bastianello, Yi Zeng, Sudipta Dhar et al. (+7 more)
Critical
quantum field theories occupy a central position in modern theoretical physics for their inherent universality stemming from long-range correlations. As an example, the Tomonaga-Luttinger
liquid (TLL) describes a wealth of one-dimensional
quantum systems at low temperatures. Its behavior is deeply rooted in the emergence of an effective
Fermi sea, leading to power-law correlations and Friedel oscillations. A promising direction to realize systems exhibiting novel universal behavior beyond TLL is through the generalization of the underlying
Fermi sea. In this Letter, we show that fractional
Fermi seas with reduced occupancy arise in an integrable Bose gas driven out of
equilibrium by cyclic changes in interactions from repulsive to attractive. The correlation functions feature signatures of criticality incompatible with a conventional TLL, suggesting a novel critical phase. Our predictions, based on Generalized Hydrodynamics, are directly relevant to cold atoms.
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All authors Alvise Bastianello, Yi Zeng, Sudipta Dhar, Zekui Wang, Xudong Yu, Milena Horvath, Grigori E. Astrakharchik, Yanliang Guo, Hanns-Christoph Nägerl, Manuele Landini
Strongly Correlated Electrons
Planckian bound on the local equilibration time
Marvin Qi, Alexey Milekhin and Luca Delacrétaz
The local equilibration time $\tau_{\rm eq}$ of
quantum many-body systems is conjectured to be bounded below by the Planckian time $\hbar /T$. We formalize this
conjecture by defining $\tau_{\rm eq}$ as the time scale at which a hydrodynamic description emerges for conserved densities. Drawing on analytic properties of real time thermal correlators, we establish a rigorous lower bound $\tau_{\rm eq} \geq \alpha \hbar /T$ on the onset of hydrodynamic behavior in a `regulated' thermal two-point function. The dimensionless coefficient $\alpha $ depends only on dimensionality and the type of hydrodynamic or diffusive behavior that emerges, and is independent of the thermalization mechanism or other microscopic details. This bound applies universally to local
quantum many-body systems, with or without a quasiparticle description, including in the presence of inelastic scattering.
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Materials Science
First-principles Newns-Anderson Hamiltonian Construction for Chemisorbed Hydrogen at Metal Surfaces
Nils Hertl, Zsuszanna Koczor-Benda and Reinhard J. Maurer
The Newns-Anderson
Hamiltonian is widely used to describe adsorption at gas-solid interfaces, yet its construction typically relies on simplifying assumptions such as constant coupling and the wideband limit approximation. Here, we present a first-principles approach to construct Newns-Anderson
Hamiltonians by applying projection operator diabatisation to
Hamiltonian matrices obtained from Kohn-Sham density functional theory calculations. We demonstrate this method for chemisorbed hydrogen on three fcc metal(111) surfaces: Al, Cu, and Pt. To validate the electronic coupling between adsorbed hydrogen and the metal surface, we compute the projected density of states, electronic tunnelling lifetimes, and vibrational lifetimes from the constructed Newns-Anderson
Hamiltonians and find good agreement with reference calculations. Analysis of the chemisorption function reveals that the wideband limit approximation is valid for H/Al(111) but has limited applicability for H/Cu(111) and H/Pt(111).
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Superconductivity · Cross-listed from nucl-th
Yuan-Zhuo Ma, Georgios Palkanoglou, Joseph Carlson et al. (+7 more)
We present theoretical and experimental evidence for a new phase of matter in
neutron-rich systems that we call
multimodal superfluidity. Using ab initio
lattice calculations, we show that the condensate consists of coexisting s-wave pairs, p-wave pairs in entangled double pair combinations, and quartets composed of bound states of two s-wave pairs. We identify
multimodal superfluidity as a general feature of single-
flavor spin-1/2 fermionic systems with attractive s-wave and p-wave interactions, provided the system is stable against collapse into a dense droplet. Beyond
neutrons at sub-saturation densities, we demonstrate that this phase appears in generalized attractive extended Hubbard models in one, two, and three dimensions. We elucidate the mechanism for this coexistence using self-consistent few-body Cooper models and compare with Bardeen-Cooper-Schrieffer theory. We also derive the form of the effective action and show that
spin, rotational, and parity
symmetries remain unbroken. Finally, we analyze experimental data to show that p-wave pair gaps and quartet gaps are present in atomic
nuclei, and we discuss the consequences of this new phase for the structure and dynamics of
neutron star crusts.
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All authors Yuan-Zhuo Ma, Georgios Palkanoglou, Joseph Carlson, Stefano Gandolfi, Alexandros Gezerlis, Gabriel Given, Ashe Hicks, Dean Lee, Kevin E. Schmidt, Jiabin Yu
Quantum Gases
Measuring spectral functions of doped magnets with Rydberg tweezer arrays
Romain Martin, Mu Qiao, Ivan Morera et al. (+8 more)
Spectroscopic measurements of single-particle spectral functions provide crucial insight into strongly correlated
quantum matter by resolving the energy and spatial structure of elementary excitations. Here we introduce a spectroscopic protocol for single-charge injection with simultaneous spatial and energy resolution in a Rydberg tweezer array, effectively emulating scanning tunneling microscopy. By combining this protocol with single-atom-resolved imaging, we go beyond conventional spectroscopy by not only measuring the single-particle spectral function but also directly imaging the microscopic structure of the excitations underlying spectral resonances in frustrated $tJ$
Hamiltonians. We reveal resonances associated with the formation of bound
magnetic polarons – composite quasiparticles consisting of a mobile hole bound to a
magnon – and directly extract their binding energy, spatial extent, and
spin character. Finally, by exploiting the spatial tunability of our platform, we measure the local density of states across different
lattice geometries. Our work establishes Rydberg tweezer arrays as a powerful platform for spectroscopic studies of strongly correlated models, offering microscopic control and direct real-space access to emergent quasiparticles in engineered
quantum matter.
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All authors Romain Martin, Mu Qiao, Ivan Morera, Lukas Homeier, Bastien Gély, Lukas Klein, Yuki Torii Chew, Daniel Barredo, Thierry Lahaye, Eugene Demler, Antoine Browaeys
Materials Science
Discovery of Polymer Electrolytes with Bayesian Optimization and High-Throughput Molecular Dynamics simulations
Antonia S. Kuhn, Jurğis Ruža, KyuJung Jun et al. (+2 more)
Polymer electrolytes are critical for safe, high-energy-density solid-state batteries, yet discovering candidates that balance high ionic conductivity with high transference numbers remains a significant challenge. In this work, we develop a high-throughput screening platform that utilizes molecular dynamics simulations to navigate a chemical space of 1.7 million hypothetical
polymer electrolyte candidates. Data from previous literature is used to warm-start batch
Bayesian optimization for iteratively selecting new
polymer electrolytes to evaluate. We iteratively identified, evaluated and analyzed 767 homopolymers as potential candidates. Our results reveal several candidates with transport properties exceeding the
benchmark polyethylene
oxide (PEO)/LiTFSI system. Crucially, our optimization campaigns for ionic conductivity and Li-diffusivity demonstrate that branched architectures and ketone functional groups significantly enhance ion-hopping mechanisms within the
polymer matrix. We provide an in-depth mechanistic comparison of Li vs. Na cation transport and offer our open-source framework to accelerate the discovery of
liquid, gel, and multi-cation electrolyte systems.
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All authors Antonia S. Kuhn, Jurğis Ruža, KyuJung Jun, Pablo Leon, Rafael Gómez-Bombarelli
Materials Science
The influence of Y content on grain structure evolution in Mg-Y alloys
Qianying Shi, Vaidehi Menon, Liang Qi et al. (+1 more)
To advance the understanding of microstructural
evolution behavior in Mg-rare earth
alloys, the effect of yttrium (Y) addition on static recrystallization and grain growth in Mg
alloys was systematically investigated in extruded Mg-1wt.%Y and Mg-7wt.%Y
alloys. Y addition was found to significantly retard the microstructural
evolution, primarily due to its solute drag effect arising from Y segregation at grain boundaries. The relative intensity of solute drag effects from different alloying elements in Mg
alloys was further assessed from both thermodynamic and kinetic perspectives, considering their grain boundary segregation tendencies and diffusivities. Additionally, static recrystallization in Mg-Y
alloys was observed to proceed via a two-stage behavior characterized with two distinct JMAK exponents, indicating the heterogeneous nucleation of recrystallized grains. Abnormal grain growth (AGG) behavior was observed in these Mg-Y
alloys. Overall, this study highlights the critical role of Y segregation at grain boundaries in controlling recrystallization and grain growth kinetics in Mg-Y
alloys. This provides new insights into the design of thermally stable Mg
alloys with refined microstructures.
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All authors Qianying Shi, Vaidehi Menon, Liang Qi, John Allison
Strongly Correlated Electrons
Hybrid Monte Carlo for Fractional Quantum Hall States
Ting-Tung Wang, Ha Quang Trung, Qianhui Xu et al. (+3 more)
We develop a hybrid Monte Carlo method to efficiently compute the physical observables from the samplings of the Laughlin and the Moore-Read wave functions of fractional
quantum Hall (FQH) systems. With the advancements in methodology, including global updates and double stereographic projection on spherical geometry, our hybrid Monte Carlo simulation is significantly faster than the widely used Metropolis Monte Carlo scheme. As a result, we can readily simulate systems with electron numbers $N > 1000$ on both disk and sphere geometries. We apply this method to investigating the topological shift obtained from the edge dipole moment, computed from the density of the wave function on the disk. We also numerically computed the non-Abelian braiding
matrices for different braiding schemes of the Moore-Read quasiholes on the sphere. Results with much better quality compared with previous works have been achieved. With the thermodynamic limit results obtained at ease, we also discuss the future usage of our method to clarify the questions on the instability of fractional
quantum Hall states in an ideal Chern band setting or under
quantum decoherence.
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All authors Ting-Tung Wang, Ha Quang Trung, Qianhui Xu, Min Long, Bo Yang, Zi Yang Meng
Other Condensed Matter
Hybrid Surrogate-Based Multi-Objective Optimization of Graded BCC Lattices
Jaswanth V Gurudev and Ratna Kumar Annabattula
Functionally graded BCC
lattice structures hold promise for applications requiring simultaneous impact absorption and thermal dissipation, yet existing optimization frameworks rely on raw
geometric parameters that are spatially blind to features such as the orientation of design gradients. In this study, we optimize density-graded BCC
lattices for concurrent crashworthiness and heat dissipation via surrogate-based goal programming, initially using raw truss diameter as design variables. The
lattice is discretized into three zones to achieve optimal dimensionality, and Pareto-optimal designs were identified that improve specific energy absorption and peak stresses during collisions while also enhancing its Nusselt number and pressure drop under forced convection relative to a non-graded
lattice. Key insights of the effect of material distribution along the gradation axis on the performance are discussed in detail. We then introduce Physics-Informed
Geometric Operators (PIGOs), which are scalar quantities derived from both the diameter profile and the triangulated surface mesh as candidate surrogate design variables. Pearson correlation analysis reveals that the raw diameter variables remain competitive, with the porosity gradient emerging as the most broadly predictive PIGO, strongly capturing both peak stress and pressure drop. The Nusselt number resists prediction by all variables tested, confirming that heat transfer is irreducibly multidimensional in this configuration due to competing surface-area and flow-blockage effects. The PIGO framework is
topology-agnostic and extends naturally beyond the three-zone parameterization to finer gradations and alternative
lattice topologies.
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Soft Condensed Matter
Light-Activated Self-thermophoretic Janus Nanopropellers
Henri Truong, Chiara Moretti, Lionel Buisson et al. (+2 more)
Achieving controlled and directed motion of artificial nanoscale systems in three-dimensional fluid environments remains a key-challenge in active matter, primarily due to the prevailing thermal fluctuations that rapidly randomize the particle trajectories. While significant progress has been made with micrometer-sized particles, imparting sufficient mechanical energy, or self-propulsion, to nanometer-sized particles to overcome Brownian
diffusion and enable controlled transport remains a major issue for emerging applications in nanoscience and nanomedicine. Here, we address this challenge by demonstrating the fuel-free, reversible, and tunable active behavior of gold-silica (Au-SiO2) Janus nanoparticles (radius R=33 nm) induced by optical excitation. Using single particle tracking, we provide direct experimental evidence of self-thermophoresis, clearly distinguishing active motion from thermal noise. These light-driven Janus nanoparticles constitute a minimal yet robust photothermal system for investigating active matter and its manipulation at the nanoscale.
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All authors Henri Truong, Chiara Moretti, Lionel Buisson, Benjamin Abecassis, Eric Grelet
Soft Condensed Matter
Densely packed particle raft at vertically vibrated air-water interface
Xiuhe Yan, Tabitha C. Watson and Hongyi Xiao
We investigate the dynamics of a dense raft of millimeter-sized granular particles at a vertically vibrated air-water interface, which displays a rich set of patterns and particle dynamics as we vary the vibration amplitude, frequency, and particle packing fraction. While the classical parametric instability with standing waves still occurs over a certain range of parameters, the measured wave dispersion relations indicate an increasing role of the raft's emergent elasticity at higher packing fractions, where the effective surface tension decreases and the out-of-plane bending modulus increases. At higher vibration frequencies and lower amplitudes, we identify a regime without standing waves. Instead, individual particles exhibit thermal-like motion, with transport crossing over from diffusive to sub-diffusive as the packing fraction increases. The particle dynamics also display spatial and temporal heterogeneity, as in supercooled
liquids. Starting from this regime, when the vibration amplitude is further increased, a large cavity eventually forms inside the raft, whose size and shape depend on the vibration frequency and the injected vibration energy. The cavitation results in the coexistence of free-surface water waves inside the cavity and thermal-like particle motion in the surrounding raft.
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Materials Science
Interpretable Machine Learning of Nanoparticle Stability through Topological Layer Embeddings
Felipe Hawthorne, Leandro Seixas, James M. Almeida et al. (+2 more)
The stability of chemically complex nanoparticles is governed by an immense configurational space arising from heterogeneous local atomic environments across surface and interior regions. Efficiently identifying low-energy configurations within this space remains a central challenge for first-principles-based materials discovery, particularly when the available reference data are limited. Here, we introduce a data-efficient and physically interpretable machine-learning framework based on a fragmented, layer-resolved descriptor that explicitly decomposes nanoparticles into surface, intermediate, and core environments using a
topology-driven definition. This representation preserves a compact and fixed feature dimensionality while retaining spatial resolution, enabling controlled emphasis on different regions of the nanoparticle through physically motivated weighting schemes. Coupled with gradient-boosted decision tree models and a ranking-based learning strategy, the proposed framework enables accurate identification of the most stable nanoparticle configurations using only a few hundred density functional theory reference calculations. Ranking performance metrics demonstrate near-saturation of correlation, high top-k recall, and rapidly vanishing regret at moderate training-set sizes, highlighting the strong data efficiency of the approach. Beyond predictive performance, layer-weighting and SHAP-based interpretability analyses reveal how surface segregation, coordination
topology, and local chemical disorder contribute differently to stability across spatial regions of the nanoparticle. These insights provide a transparent physical interpretation of the learned models and establish a natural pathway toward active learning-driven exploration of complex nanoparticle configurational spaces.
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All authors Felipe Hawthorne, Leandro Seixas, James M. Almeida, Cristiano F. Woellner, Raphael M. Tromer