Materials Science
A One-Dimensional Reduction Method for Calculating Thermal Expansion in Solids: Application to Orthorhombic Systems
Dmitry Vasilyev
Anisotropic thermal expansion plays a critical role in the performance and reliability of functional materials, yet its theoretical description remains limited. Here, a computational framework that reduces the calculation of thermal expansion in solids to an effective one-dimensional problem is presented and applied to orthorhombic
lattice. Using this method, a comprehensive set of thermodynamic and mechanical properties is determined.
Read the full abstract ▾
Materials Science
Ferromagnetism above 200 K in organic-ion intercalated CrSBr
Sofia Ferreira-Teixeira, Daniel Tezze, Maria Ramos et al. (+11 more)
CrSBr is a van der Waals
magnetic semiconductor exhibiting
antiferromagnetic order below 140 K. It has emerged as a promising platform for engineering 2D magnetism because its intertwined electronic, optical, and
magnetic properties can be profoundly modified via external stimuli such as electrical gating or
magnetic fields. However, other strategies for tuning magnetism in layered materials, such as molecular intercalation, remain largely unexplored for CrSBr. Here, we demonstrate that the intercalation of tetramethylammonium (TMA) and tetrapropylammonium (TPA) ions into CrSBr induces a transition from
antiferromagnetic to
ferromagnetic order, while significantly enhancing the
magnetic transition temperature to 190 K (TMA) and 230 K (TPA). The resulting intercalates are air-stable and exhibit large, hysteretic magnetoresistance exceeding 60% at 50 K in the TPA case. Besides, intercalation introduces
symmetry-breaking structural changes in each CrSBr plane, revealed by Raman microscopy and corroborated by density functional theory (DFT) calculations. These findings highlight molecular intercalation as a powerful and versatile route to tailor the
magnetic properties of CrSBr and unlock its potential to fabricate robust, high-temperature 2D
magnetic devices.
Read the full abstract ▾
All authors Sofia Ferreira-Teixeira, Daniel Tezze, Maria Ramos, Covadonga Álvarez-García, Bertuğ Bay{\i}nd{\i}r, Junhyeon Jo, Beatriz Martín-García, Maider Ormaza, Fèlix Casanova, Samuel Mañas-Valero, Eugenio Coronado, Hasan Sahin, Luis E. Hueso, Marco Gobbi
Materials Science
Collective Phonon Mixing and Eigenvector Transport Under Isotope Substitution
Jeff Armstrong, Hamish Cavaye, Pankaj Sharma et al. (+1 more)
Isotopic substitution modifies
nuclear masses without altering the electronic potential energy surface to first order and is therefore often interpreted as a simple rescaling of vibrational frequencies. In solids with dense
phonon manifolds, however, mass substitution acts as a parametric Hermitian deformation of the mass-weighted dynamical
matrix, generating a continuous family of eigenproblems whose eigenvectors can undergo substantial rotation within coupled subspaces. Here we investigate protiated and deuterated ZIF-8 using inelastic
neutron scattering and density functional theory
lattice-dynamics calculations. While many vibrational modes exhibit near-ideal mass scaling and preserve their character across isotopic endpoints, modes embedded in spectrally congested regions display pronounced redistribution of vibrational character that cannot be inferred from frequency shifts alone. Because inelastic
neutron scattering intensity is directly weighted by hydrogen displacement amplitude, spectral sparsity and congestion provide experimental indicators of predictable frequency renormalisation or susceptibility to qualitative eigenvector reorganisation under deuteration. To establish physically meaningful mode correspondence, we develop an adiabatic eigenvector-continuation framework with overlap-based tracking and explicit stability diagnostics. These results show that vibrational identity in complex framework materials is best understood as a continuous trajectory in eigenvector space and provide a general framework for analysing isotope-induced spectral flow in dense
phonon systems.
Read the full abstract ▾
All authors Jeff Armstrong, Hamish Cavaye, Pankaj Sharma, Matthew E. Potter
Soft Condensed Matter
A constitutive model for discontinuous shear thickening in epithelial tissues
Tanmoy Ghosh, Kabir Ramola and Saroj Kumar Nandi
The rheological properties of biological tissues, though fundamental to many physiological and pathological processes such as embryonic development, wound healing, and tumor progression, remain poorly understood. A recent study showed that the active vertex model of biological tissues exhibits discontinuous shear thickening (DST), where stress and viscosity suddenly increase at a critical shear rate. What is the mechanism of DST here? Is it another nontrivial feature of activity or an inherent property of the system? To address this, we show that the thermal vertex model also exhibits DST at a small but non-zero temperature $T$. Solid-like and
liquid-like
cells coexist at the stress jump, and the stress-controlled flow curves exhibit the characteristic S-shape. We then introduce a constitutive model for DST in epithelial tissues. As $p_0$ increases, the theory predicts DST, followed by continuous shear thickening (CST), and finally Newtonian behavior, consistent with simulations. DST begins at the jamming point, $p_0^m$, and the Newtonian behavior starts at $p_0^*$, where the yield stress vanishes. Both $p_0^*$ and the
liquid-to-solid transition stress, $\sigma^*$, govern the DST-CST boundary. Furthermore, $p_0^*$ and $\sigma^*$ also depend on $T$. Increasing $T$ reduces $p_0^*$, narrows the shear-thickening regime, and eventually destroys DST when $p_0^* \leq p_0^m$. Thus, the primary ingredients of DST in tissue models are a finite yield stress in the unjammed regime and non-zero fluctuations, whose specific form is not important. The theory agrees well with our simulation data and also provides further testable predictions.
Read the full abstract ▾
Mesoscale and Nanoscale Physics
Flux-driven delocalization transition in disordered topological insulator nanowires
Shimon Arie Haver, Emuna Rimon and Eytan Grosfeld
Topological
insulator nanowires provide a tunable platform for studying the interplay between disorder,
quantum interference, and
symmetry-protected transport. Here we investigate
quantum transport in disordered topological
insulator nanowires threaded by an axial
magnetic flux. By computing the conductance as a function of wire length,
magnetic flux, chemical potential, and disorder strength, we extract the localization length to characterize the flux-driven delocalization transition near half-integer flux quanta. We find that the localization length diverges with a robust critical exponent $\nu=2$, independent of the chemical potential and disorder strength considered here. This exponent differs from that of the integer
quantum Hall transition, pointing to distinct scaling behavior. Near integer flux quanta, we further find that the conductance evolves from a weak-localization dip at low chemical potential to a weak anti-localization peak at higher chemical potential, which splits and is eventually suppressed as the system crosses over to the strongly localized regime.
Read the full abstract ▾
Mesoscale and Nanoscale Physics
Efficient two-color Floquet control of the RKKY interaction in altermagnets
Mohsen Yarmohammadi, Pei-Hao Fu and James K. Freericks
Magnetic impurities in real materials can mask the intrinsic
spin-dependent properties of hosts. They interact indirectly through the Ruderman-Kittel-Kasuya-Yosida (RKKY) mechanism, which limits the use of isolated
impurity spins in applications such as
qubits and spintronics. By suppressing the RKKY interaction, an effective control scheme should therefore enable access to the host's unperturbed behavior while simultaneously isolating the
impurity spins for functional use. Although beyond static approaches, single-color
laser driving can suppress the RKKY interaction, it typically requires strong fields that may be impractical or destabilizing. To overcome these limitations, we show that two-color
laser driving provides efficient and tunable control over all components of the RKKY interaction using two weak
laser fields. Focusing on two-dimensional Rashba altermagnets, we show that interference between one- and two-
photon processes produces altermagnet-specific Floquet corrections. These include additional AC Stark shifts, magnetizations,
spin-orbit renormalization, and emergent in-plane Zeeman fields, which are absent under single-color driving and in non-altermagnetic systems. Notably, two-color driving induces a finite $z$-component of the Dzyaloshinskii-Moriya (DM) interaction, stabilizing in-plane
chiral magnetism and related textures in Rashba altermagnets. These effects enable tunable, near-complete on-off switching of the Heisenberg, Ising, and DM interactions through a Lifshitz-like modulation of the
Fermi surface. We also show that the tuning process is highly sensitive to the chirality of both beams. We further map out phase diagrams for
ferromagnetic and
antiferromagnetic alignment of
impurities with clockwise and counterclockwise canting as a function of Rashba coupling and altermagnetic order. Finally, we discuss candidate material platforms and experimental feasibility.
Read the full abstract ▾
Superconductivity
Unconventional spin valve effect in altermagnets induced by Rashba spin orbit coupling and triplet superconductivity
Saumen Acharjee, Aklanta Dihingia, Nayanav Sonowal et al. (+1 more)
We theoretically investigate
spin dependent transport in altermagnet/triplet
superconductor/altermagnet (AM/TSC/AM) junctions in the presence of interfacial Rashba
spin orbit coupling (RSOC). Within a microscopic Bogoliubov de Gennes scattering formalism, we compute angle and energy resolved conductance,
spin polarization, zero bias response, and tunneling magnetoresistance (TMR) for nodal $p_x$ and
chiral $p_x+ip_y$
superconductors. Although altermagnets carry no net magnetization, the momentum dependent
spin splitting, combined with RSOC, enables a pronounced
spin valve effect without
ferromagnetic electrodes. We show that conductance,
spin polarization, and TMR exhibit distinct and robust fingerprints of the triplet pairing
symmetry. For nodal $p_x$
superconductor, sign change induced surface Andreev bound states dominate subgap transport, producing strongly anisotropic conductance,
giant zero bias
spin polarization, and a monotonic enhancement of TMR with increasing RSOC. In contrast, the
chiral $p_x+ip_y$ state exhibits smoother conductance and polarization profiles governed by topological edge modes, resulting in broader, lobe like TMR patterns with weaker sensitivity to interface transparency. Moreover, RSOC can acts as an electrically tunable
spin-mixing knob, while the barrier strength controls coherence and energy selectivity, together enabling large,
symmetry controlled
spin filtering and magnetoresistance. Our results establish AM/TSC/AM junctions as a
symmetry sensitive transport platform for realizing electrically tunable
spin valve functionality and probing triplet pairing without
ferromagnetic components.
Read the full abstract ▾
All authors Saumen Acharjee, Aklanta Dihingia, Nayanav Sonowal, Abyoy Anan Kashyap
Strongly Correlated Electrons
Parameterizing DFT+U+V from Hybrid Functionals: A Wannier-Function-Based Approach for Strongly Correlated Materials
Dmitry M. Korotin, Anna A. Anisimova and Vladimir I. Anisimov
We present an approach to parameterize DFT+$U$+$V$ from hybrid-functional calculations using Wannier-function projections. The method constructs a common localized Wannier basis for both semilocal DFT and hybrid-functional calculations, then determines effective on-site ($U$) and intersite ($V$) Hubbard parameters by minimizing the
Hamiltonian mismatch within the correlated subspace. This procedure yields interaction parameters that reproduce the hybrid-functional electronic structure at a fraction of the computational cost and allow efficient structural relaxations and further many-body calculations. We validate the workflow on three
oxide systems with different electronic characters: MgO (wide-gap
insulator), NiO (
antiferromagnetic charge-transfer
insulator), and V$_2$O$_5$ (d$^0$ transition-metal
oxide). In all cases, the mapped DFT+$U$+$V$ parameters reproduce hybrid-functional band gaps, densities of states, and
magnetic moments and improve upon semilocal DFT while maintaining computational efficiency.
Read the full abstract ▾
Soft Condensed Matter
Dynamic versus quasi-static response of a cantilevered beam rotated harmonically
Gilad Yakir, Eduardo Gutierrez-Prieto and Pedro M. Reis
We investigate a cantilevered elastic beam subjected to harmonic rotational motion. In the rotating frame, the beam experiences centrifugal and Euler fictitious forces, with negligible Coriolis effects. We validate a reduced-order elastica model through precision experiments on slender beams rotating with a controlled sinusoidal angular velocity. Systematically exploring the parameter space, we identify regimes where inertial effects are negligible, enabling a quasi-static treatment despite harmonic driving. We characterize the transition to dynamic response using two dimensionless parameters, the Euler and centrifugal numbers, which compare centrifugal and Euler forces to bending forces. Counterintuitively, the quasi-static regime expands as rotational speed increases: faster rotation produces less dynamic response. The critical Euler number separating these regimes remains constant at low centrifugal numbers but follows square-root scaling at higher rotation rates, a transition driven by centrifugal stiffening. Our results establish the conditions under which quasi-static approximations remain valid for rotating flexible beams under harmonic driving.
Read the full abstract ▾
Materials Science
Epitaxial Films as Model Platform for Understanding Compositionally Complex Electrocatalysts
Satyakam Kar, Alejandro E. Perez-Mendoza, Huixin Xiu et al. (+8 more)
Compositionally complex solid solutions provide a unique route for engineering high-performance electrocatalysts, where the polyelemental surface composition can be seamlessly tuned to optimize activity, selectivity, and stability. However, the mechanistic understanding of these electrocatalysts remains limited by the lack of a model system with a crystallographically-defined surface that is compatible with correlative, multi-scale characterization. Here, we present epitaxial films as a model platform for studying compositionally complex electrocatalysts. Using magnetron sputtering, we realize (111) epitaxial Ir-Pd-Pt-Rh-Ru films on (0001) sapphire substrate via a (111) Pt buffer layer, confirmed by X-ray diffraction and transmission electron microscopy. The growth approach is applicable across a broad composition range and produces smooth surfaces (root mean square roughness < 1 nm) with micrometer-sized grains in the nanoscale films. With these films, we demonstrate direct structure-activity mapping at the nanoscale through precise co-localization using micro-indents and performing correlative atomic force microscopy, electron backscatter diffraction, and scanning electrochemical
cell microscopy. Our work establishes a model platform for fundamental scalebridging characterization and paves the way for rational design of compositionally complex electrocatalysts.
Read the full abstract ▾
All authors Satyakam Kar, Alejandro E. Perez-Mendoza, Huixin Xiu, Miran Joo, Kirill V. Yusenko, Ulrich Hagemann, Christoph Somsen, Janine Pfetzing-Micklich, Christina Scheu, Corina Andronescu, Alfred Ludwig
Quantum Gases
Suppressed correlation-spreading in a one-dimensional Bose-Hubbard model with strong interactions
Jose Carlos Pelayo and Ippei Danshita
We investigate signatures of non-ergodic behavior in the real-time
evolution of a one-dimensional Bose-Hubbard model, where the initial state is a doubly occupied density-wave state. We show that the occupation dynamics at strong interactions is dominated by doublon-holon exchange which leads to a domain wall excitation and propagation. The latter manifests as a negated staggered pattern in the density-density correlations. While the single-particle and the pair correlation functions show highly localized correlations that decay rapidly away from the nearest neighbor. We show that the time scale of the domain-wall excitations depends on the inverse of the interaction strength and therefore dictates the slow relaxation dynamics. In the presence of a
parabolic trap, the occupation dynamics at the edges become frozen and further suppresses the propagation of correlations. This suppression happens even for trap strengths weaker than the tunneling rate. We also show that the model can be mapped to an
antiferromagnetic transverse-field Ising model in the limit of strong interactions and that the correlation-propagation velocity in the original model is well captured by the group velocity of the
spin-wave excitation in the effective
spin model.
Read the full abstract ▾
Materials Science
Machine Learning Modeling of Temperature-Dependent Optoelectronic Properties of Anharmonic Solid Solutions
Pol Benítez, Cibrán López, Edgardo Saucedo et al. (+1 more)
Leveraging strong optoelectronic responses to external stimuli, such as temperature and electric fields, is central to the development of advanced photonic technologies, including adaptive photodetectors and reconfigurable photovoltaic devices. However, only a limited number of semiconducting materials, typically characterized by strong electron-
phonon coupling, are known to exhibit such pronounced responsiveness, and their
equilibrium optoelectronic properties are often not optimally suited for targeted applications. Chemical engineering strategies, such as doping and solid-solution mixing, are therefore widely employed to fine-tune the electronic and optical properties of
semiconductors. Predicting the impact of such modifications, however, remains highly challenging due to the intrinsic complexity of chemically disordered and anharmonic systems, as well as the computational limitations of conventional first-principles approaches. In this work, we introduce a new computational framework that combines ab initio electronic-structure methods with machine-learning techniques to achieve first-principles precision in the prediction of optoelectronic properties of anharmonic solid solutions at finite temperature. We apply this approach to silver chalco-halide solid solutions, an emergent class of optoelectronic materials that have been experimentally shown to exhibit large band-gap tunability and strong responses to thermal excitations. Our results provide quantitative insight into the interplay between chemical disorder,
lattice dynamics, and electronic structure in these materials. More broadly, this study establishes a general strategy for the accurate modeling of optoelectronic functionality in chemically disordered
semiconductors.
Read the full abstract ▾
All authors Pol Benítez, Cibrán López, Edgardo Saucedo, Claudio Cazorla
Soft Condensed Matter
The Jammed Phase of Infinitely Persistent Active Matter
M. C. Gandikota, Rituparno Mandal, Pinaki Chaudhuri et al. (+2 more)
We study an extreme active matter system, which is essentially a dense assembly of athermal, soft and infinitely persistent active particles. Using extensive numerical simulations we obtain jammed configurations of this system in two dimensions and probe the stability of such structures under increasing active forcing magnitude. We show that the critical active forcing magnitude for the jammed phase to yield scales with virial pressure as $f_c\sim p^\alpha$, with $\alpha=1.17$, describing the yielding line. Using a
Laplacian framework, we redistribute the active forces into a modified contact force network. By analysing the statistics of these redistributed forces, we obtain a very robust scaling law consistent with the passive limit, not just near the unjamming line, but in the entire jammed active phase. The probability distribution of the magnitude of the contact force deviates from the power-law form found in passive systems for values smaller than the active force. Moreover, within the jammed phase, the system displays elastic, plastic, and yielding events with increasing active forcing. This active plasticity appears abruptly and can not be captured by the continuous softening of the Hessian spectrum. However, we demonstrate that the Hessian still retains the ability to predict relaxation times. These results clarify how activity modifies force distributions and leads to deformation, plasticity and yielding in dense, jammed, infinitely persistent active matter.
Read the full abstract ▾
All authors M. C. Gandikota, Rituparno Mandal, Pinaki Chaudhuri, Bulbul Chakraborty, Chandan Dasgupta
Other Condensed Matter · Cross-listed from quant-ph
Generative Deep Learning for the Two-Dimensional Quantum Rotor Model
Yanyang Wang, Feng Gao, Kui Tuo et al. (+1 more)
The advancement of diverse generative deep learning models and their variants has furnished substantial insights for investigating
quantum many-body problems. In this work, we design two models based on the foundational architecture of generative
adversarial networks (GANs) to investigate the ground-state properties and phase transition characteristics of the two-dimensional
quantum rotor model (QRM). Within a semi-supervised learning framework, we incorporate multiple layers of transposed convolutions in the generator, enabling the conditional GAN to more efficiently extract low-dimensional encoded information. Analysis of one-dimensional latent variables associated with ground-state samples for different system sizes allows us to pinpoint the location of the critical point. In addition, we introduce dynamically adaptive weighting factors related to the distributional characteristics into the loss function of the deep convolutional GAN, and utilize upsampling techniques to enlarge the generated sample sizes. Comparisons of the optimization processes for mean magnetization and potential energy density across different magnetization regimes of QRM demonstrate that our model can efficiently generate valid ground-state samples, significantly reducing computational time. Our results highlight the promising potential of generative deep learning in
quantum phase transition research, especially in critical point identification and the auxiliary generation of simulation data for
quantum many-body models.
Read the full abstract ▾
All authors Yanyang Wang, Feng Gao, Kui Tuo, Wei Li
Materials Science
Beyond Point-like Defects in Bulk Semiconductors: Junction Spectroscopy Techniques for Perovskite Solar Cells and 2D Materials
Ivana Capan
Junction spectroscopy techniques (JSTs) are powerful tools for investigating electrically active defects in
semiconductors. Originally developed to study point-like defects in bulk
semiconductors, JSTs have since been extended to increasingly complex systems, providing valuable insights into defect energetics and interactions. This review paper outlines the fundamental principles of JSTs and critically examines their application to emerging materials, such as perovskite
solar cells and two-dimensional (2D) materials. By highlighting both the capabilities and limitations of JSTs in these non-classical systems, the review demonstrates their continued relevance and important role in advancing next-generation
semiconductor materials and devices.
Read the full abstract ▾
Superconductivity
Fluctuation-enhanced electron-phonon coupling in FeSe
Jovan Blagojević, Ana Milosavljević, Tea Belojica et al. (+13 more)
The interactions among
lattice, charge, and
spin degrees of freedom fundamentally shape material properties. In FeSe,
symmetry-breaking perturbations serve as highly sensitive probes of these couplings. Previous work has shown that defects and isoelectronic substitution can substantially alter these interactions, giving rise to additional
phonon modes. In this study, uniaxial strain is employed as a tunable
symmetry-breaking control parameter to probe the intrinsic
lattice response in the absence of disorder. The temperature
evolution of
phonon excitations was examined with fine temperature resolution in the vicinity of the nemato-structural transition temperature $T_s$, under strain applied along the $\langle 110 \rangle$ and $\langle 100 \rangle$ crystallographic directions. A subtle asymmetry of the $A_{1g}^{ph}$ mode appears in the unstrained
crystal within a narrow temperature window around $T_s$, originating from the emergence of an additional mode in the fully symmetric channel. With applied strain, this feature becomes more distinctly resolved. The anomaly is attributed to modifications of the coupling between
lattice and electronic degrees of freedom driven by the ordering fluctuations right above the nematic transition. These fluctuations enhance susceptibility for
phonon-electron-
phonon coupling in the vicinity of the X and R points of the Brillouin zone and promote two-
phonon scattering close to the $A_{1g}^{ph}$ mode. The presence of this two-
phonon scattering depends on both the strength and the direction of the applied strain, indicating a high sensitivity of FeSe to local
symmetry breaking.
Read the full abstract ▾
All authors Jovan Blagojević, Ana Milosavljević, Tea Belojica, Marko Opačić, Andrijana Šolajić, Jelena Pešić, Enrico Di Lucente, Novica Paunović, Milorad V. Milošević, Emil S. Božin, Aifeng Wang, Cedomir Petrović, Zoran V. Popović, Rudi Hackl, Bojana Višić, Nenad Lazarević
Mesoscale and Nanoscale Physics
Topological Dislocation Response in Elementary Semiconductors
Yuteng Zhou, Alexandre Chaduteau and Frank Schindler
We study elementary
semiconductors and
insulators that are symmetric under spatial inversion: silicon, diamond, germanium, and black phosphorene. These materials are ideal candidates for realizing obstructed atomic
insulators, which differ from trivial atomic
insulators by a quantized spatial shift of their electronic Wannier centers with respect to the atomic
lattice. We use
symmetry indicator invariants that allow the prediction of non-trivial responses to
crystal dislocations in these materials. We find that edge dislocations generically exhibit a non-trivial response, while screw dislocations always display a trivial response. With the aid of numerical simulations of realistic tight-binding models, we confirm the presence of mid-gap polarization bands localized along dislocations in silicon, diamond, and germanium.
Read the full abstract ▾
Materials Science
Phonon frequency comb close to an isolated Einstein mode in InSiTe3
Tea Belojica, Jovan Blagojević, Sanja Djurdjić Mijin et al. (+10 more)
The emergence of
phonon frequency combs exemplifies a rare and intriguing phenomenon in
quantum solids. Materials with distinctive
phonon band structures are especially promising for hosting such states, as their vibrational dispersion landscape across the Brillouin zone can facilitate the formation of long-lived, collective
lattice excitations. In the layered Van der Waals compound InSiTe$_3$, polarization-resolved Raman spectroscopy reveals a pronounced anharmonicity in
symmetry-predicted modes and the formation of a self-organized frequency domain structure (coherent-like state), in the range of a localized highenergy A$_{1g}$
phonon mode near 500 cm$^{-1}$. This strong
phonon-
phonon coupling manifests itself as an anomalous temperature dependence around 200 K, coinciding with the appearance of higher-order excitations within the
phonon density of states gap. These findings position InSiTe$_3$ as an unconventional platform where intrinsic highly structured
phonon spectral correlations and unusually strong anharmonic effects coexist, opening new avenues for exploring emergent vibrational phenomena in low-dimensional materials.
Read the full abstract ▾
All authors Tea Belojica, Jovan Blagojević, Sanja Djurdjić Mijin, Andrijana Šolajić, Jelena Pešić, Emil S. Božin, Bojana Višić, Yu Liu, Cedomir Petrovic, Zoran V. Popović, Rudi Hackl, Ana Milosavljević, Nenad Lazarević
Mesoscale and Nanoscale Physics
Disorder-independent hole spin manipulation by hopping
Biel Martinez, Ana Sempere-Sanchis, José C. Abadillo-Uriel et al. (+1 more)
Spin manipulation by hopping has recently emerged as a promising strategy to control hole
spins in
quantum dots using exclusively baseband control, thereby mitigating power dissipation and high-frequency management constraints in large-scale architectures. Unlike conventional approaches such as electron dipole
spin resonance (EDSR), this mechanism exploits dot-to-dot variations of the
spin precession axes to enable
spin rotations. However, it is intrinsically disorder-dependent: in the absence of sufficient variability, the precession axes remain aligned and
spin manipulation becomes ineffective. This fundamental reliance on disorder raises concerns regarding its compatibility with the long-term
evolution of
spin-
qubit platforms toward improved material quality, cleaner interfaces, and enhanced device reproducibility. Here, we numerically assess the viability of
spin manipulation by hopping as a function of disorder strength and demonstrate that its implementation is indeed increasingly constrained as disorder is reduced. To overcome this limitation, we propose an alternative strategy based on hopping between intentionally squeezed
quantum dots. This approach retains the advantages of baseband control while being independent of disorder and robust against moderate variability, thereby offering improved prospects for scalable hole-
spin quantum computing architectures.
Read the full abstract ▾
All authors Biel Martinez, Ana Sempere-Sanchis, José C. Abadillo-Uriel, Yann-Michel Niquet
Soft Condensed Matter
The Kovacs memory effect in a thin granular layer: experimental evidence and its physical origin
Francisco Vega Reyes, Álvaro Rodríguez-Rivas, Pablo Maynar et al. (+1 more)
We report the experimental observation of
memory effects in a vertically vibrated thin granular layer. Following a quench in the input acceleration, the granular temperature exhibits an anomalous Kovacs
memory effect confined to the initial fast relaxation stage. This
memory vanishes shortly thereafter, yielding a time-dependent memoryless regime governed solely by the instantaneous temperature before the system reaches its final steady state. We develop a kinetic theory framework that quantitatively captures these features by identifying the initial
memory and subsequent memoryless regimes with the kinetic and hydrodynamic states, respectively (that are well established in kinetic theory). Our analysis reveals that
memory emerges during fast transients through coupling between horizontal and vertical temperatures, a mechanism that fundamentally constrains the accessible
memory phenomenology and precludes observation of the standard Kovacs effect in this system. Molecular dynamics simulations provide independent confirmation of all experimental and theoretical findings.
Read the full abstract ▾
All authors Francisco Vega Reyes, Álvaro Rodríguez-Rivas, Pablo Maynar, M. Isabel García de Soria
Statistical Mechanics · Cross-listed from q-bio.PE
Tipping points in complex ecological systems
Alan Hastings, Sergei Petrovskii, Valerio Lucarini et al. (+1 more)
Tipping points are one of the hot topics in the modern physics of complex systems. But what is a tipping point? One generic definition describes it as “a state of the system where a small change in its parameters can lead to a significant change in its properties”. Additional ingredients that often enter the definition of tipping point are the abruptness of the resulting change and its irreversibility, i.e. it is impossible to recover the initial state if one reverses the protocol of change of the parameters. However, there exists a number of different mathematical structures that can show this behavior, the one that was originally used nowadays often referred to as the bifurcation induced tipping is just one of many. Different preconditions and/or different level of detail included into the model, reflecting also different environmental forcing, can lead to a variety of tipping mechanisms. Furthermore, in a spatially extended system and/or a system with multiple scales, different parts can react to a change in environmental conditions differently or at a different time, interacting with each other to create a tipping cascade. In this paper, using ecosystems as a paradigm of complex nonlinear open systems, we provide a critical overview of the progress made in tipping point science over the last 15 years. We highlight the main findings, identify gaps in our knowledge, and outline a roadmap for further progress.
Read the full abstract ▾
All authors Alan Hastings, Sergei Petrovskii, Valerio Lucarini, Andrew Morozov
Statistical Mechanics · Cross-listed from quant-ph
Spatial Entanglement Sudden Death in Spin Chains at All Temperatures
Samuel O. Scalet
We prove a finite
entanglement length for the Gibbs state of any local
Hamiltonian on a
spin chain at any finite temperature: After removing an interval of size at least equal to the
entanglement length, the remaining left and right half-chains are in a separable state.
Materials Science
Disentangling the dynamics of transient spin and orbital magnetization in SrTiO$_3$ via the inverse Faraday effect from RT-TDDFT
Andri Darmawan, Markus E. Gruner and Rossitza Pentcheva
Motivated by recent evidence of ferroelectricity and even multiferroicity in the prototypical diamagnetic band
insulator SrTiO$_3$ from terahertz experiments, we investigate the carrier and magnetization dynamics of SrTiO$_3$ excited optically by linearly (LPL) and circularly polarized light (CPL). Our RT-TDDFT simulations show a pronounced site- and orbital-dependent charge transfer from O$2p$ to Ti $3d$ states. With LPL anti-phase oscillations of the electron-density lobes at O and Ti resemble the soft transverse optical
phonon mode and break dynamically inversion
symmetry. CPL instead drives a coherent rotation of the charge dipoles around oxygen, producing a helicity-dependent transient magnetization of opposite sign at O and Ti, even without ionic motion. The dominant effect stems from the transfer of angular momentum (AM) from light to the electronic orbital AM, while
spin-orbit coupling plays a key role in the transfer from orbital to
spin AM, the former being an order of magnitude larger than the latter. The real-time resolution allows us to disentangle the inverse Faraday effect, which follows the pulse envelope, from optical orientation, which builds up during the pulse and saturates afterwards. The results demonstrate that purely electronic processes without
lattice motion induce ultrafast magnetisation in a non
magnetic insulator, offering a tunable route for light controlled
magnetic functionalities.
Read the full abstract ▾
Materials Science
Large Photoelasticity in Topological Antiferromagnet Mn$_3$Sn Studied by Coherent Acoustic Phonon
Yuchen Wang, Takuya Matsuda, Yuta Murotani et al. (+5 more)
We investigate the role of ultrafast strain on the electronic and optical responses in topological antiferromagnet Mn$_3$Sn thin films using near-infrared femtosecond pump-probe spectroscopy. Coherent acoustic
phonons are generated and exhibit remarkably large oscillations in differential transmission exceeding 1% in amplitude. Our quantitative analysis reveals that Mn$_3$Sn possesses an unusually large near-infrared photoelastic coefficient, several times greater than those in conventional materials, indicating a remarkable sensitivity of the electronic states to
lattice distortions. This work establishes a quantitative framework for understanding and utilizing strain-induced responses in Mn$_3$Sn, paving a foundation for exploring coupled electron-
phonon-
magnon dynamics for ultrafast straintronics.
Read the full abstract ▾
All authors Yuchen Wang, Takuya Matsuda, Yuta Murotani, Hanyi Peng, Takumi Matsuo, Tomoya Higo, Satoru Nakatsuji, Ryusuke Matsunaga
Materials Science · Cross-listed from physics.app-ph
Integrating Domain-Specialized Language Models with AI Measurement Tools for Deterministic Atomic-Resolution Experimentation
Zhuo Diao, Kouma Matsumoto, Linfeng Hou et al. (+3 more)
Self-driving laboratories based on large
language models promise to transform scientific discovery through general experimental automation. However, realizing this
vision on precision platforms remains challenging, requiring deterministic execution and effective domain adaptation under strict physical constraints. We address these requirements through a framework that specializes in small
language models for autonomous control of scanning probe microscopy, coordinating task-specific models with AI-driven measurement tools. We demonstrate real-time, atomic-resolution SPM experiments at room temperature, achieving instruction-level control and multi-step experimental planning. Fine-tuning reduces perplexity from 1.44 to 1.20 and improves reliability, with the adapted model reaching 99.3% and 95.2% command accuracy, outperforming OpenAI o4-mini on domain-specific tasks. This architecture achieves lower computational cost while maintaining deterministic execution and enabling deployment on consumer-grade hardware. This work bridges probabilistic
language models with deterministic experimental control through a modular, domain-specialized architecture, providing a generalizable pathway toward scalable and trustworthy self-driving laboratories across diverse scientific platforms.
Read the full abstract ▾
All authors Zhuo Diao, Kouma Matsumoto, Linfeng Hou, Masahiro Ohara, Hayato Yamashita, Masayuki Abe
Soft Condensed Matter · Cross-listed from physics.bio-ph
Programming Shapes with Competing Layered Patterns
Wan Yee Yau and Carl D. Modes
Studying shape changing thick surfaces induced by differential growth helps us understand morphogenesis in biology and offers opportunities for device design. While ideal 2D differential growth maps have been well studied for both isotropic and anisotropic growth, scenarios involving gradients in thickness growth are far less explored. In this paper, we focus on a
bilayer system in which the two layers undergo independent but incompatible growth. We examine how the strength of the growth patterns and the aspect ratio of the
bilayer influence the resulting shapes. We first investigate the effect of global area difference in the
bilayer. Next, we make one of the two layers active and program it with positive or negative, localized or uniform
curvature. We then present examples involving competition between two active surfaces with opposite
curvature signs or different
curvature distributions and understand how the final configurations follow from the principles identified earlier. Finally, we demonstrate the ability to program biologically inspired shapes, such as dental epithelium and the ventral furrow in Drosophila, using a
bilayer with simple, distinct deformation gradients.
Read the full abstract ▾
Statistical Mechanics · Cross-listed from cs.AI
Physics-based phenomenological characterization of cross-modal bias in multimodal models
Hyeongmo Kim, Sohyun Kang, Yerin Choi et al. (+5 more)
The term 'algorithmic
fairness' is used to evaluate whether AI models operate fairly in both comparative (where
fairness is understood as formal equality, such as "treat like cases as like") and non-comparative (where unfairness arises from the model's inaccuracy, arbitrariness, or inscrutability) contexts. Recent advances in
multimodal large
language models (MLLMs) are breaking new ground in
multimodal understanding,
reasoning, and generation; however, we argue that inconspicuous distortions arising from complex
multimodal interaction dynamics can lead to systematic bias. The purpose of this position paper is twofold: first, it is intended to acquaint AI researchers with phenomenological explainable approaches that rely on the physical entities that the machine experiences during training/inference, as opposed to the traditional cognitivist symbolic account or metaphysical approaches; second, it is to state that this phenomenological doctrine will be practically useful for tackling algorithmic
fairness issues in MLLMs. We develop a surrogate physics-based model that describes
transformer dynamics (i.e., semantic network structure and self-/cross-
attention) to analyze the dynamics of cross-modal bias in MLLM, which are not fully captured by conventional
embedding- or representation-level analyses. We support this position through multi-input diagnostic experiments: 1) perturbation-based analyses of
emotion classification using Qwen2.5-Omni and Gemma 3n, and 2) dynamical analysis of Lorenz chaotic time-series prediction through the physical surrogate. Across two architecturally distinct MLLMs, we show that
multimodal inputs can reinforce modality dominance rather than mitigate it, as revealed by structured error-attractor patterns under systematic label perturbation, complemented by dynamical analysis.
Read the full abstract ▾
All authors Hyeongmo Kim, Sohyun Kang, Yerin Choi, Seungyeon Ji, Junhyuk Woo, Hyunsuk Chung, Soyeon Caren Han, Kyungreem Han
Materials Science
Combining Quasiparticle Self-Consistent $GW$ and Machine-Learned DFT+$U$ to Assess Half-Metallicity in Co- and Ni-Based Heuslers
Zefeng Cai, Malcolm J. A. Jardine, Maituo Yu et al. (+6 more)
Half-metallic Heusler compounds are of significant interest for spintronics. For device fabrication, compounds that can be epitaxially grown on III-V
semiconductors are particularly attractive. We present a first-principles investigation of four Co-based and two Ni-based Heusler compounds that are
lattice-matched to InAs. The results of density functional theory (DFT) using semi-local and hybrid functionals are compared to quasiparticle self-consistent $GW$ (QP$GW$). We also consider DFT with machine-learned Hubbard $U$ corrections [npj Computational Materials 6, 180 (2020)] with a new
Bayesian optimization (BO) objective function to determine the $U$ values that yield the closest agreement with the QP$GW$ band structure and
magnetic moments. We find that DFT+$U$(BO) can adequately reproduce the key QP$GW$ features in most cases. Our results reveal a strong method dependence of the degree of
spin polarization at the
Fermi level and, in some cases, even the dominant
spin channel (majority or minority). Of the materials studied here, Co$_2$TiSn and Co$_2$ZrAl are the most likely to be half-metals.
Read the full abstract ▾
All authors Zefeng Cai, Malcolm J. A. Jardine, Maituo Yu, Chenbo Min, Jiatian Wu, Hantian Liu, Derek Dardzinski, Christopher J. Palmstrøm, Noa Marom
Disordered Systems and Neural Networks
Construction of a Neural Network with Temperature-Dependent Recall Patterns
Munetaka Sasaki
We present a simple model that recalls two different patterns depending on the temperature. To realize a change in recall pattern due to temperature change, we embed two patterns to different graphs: the first pattern into a fully connected graph and the second pattern into a sparse graph. Because a fully connected graph is more resistant to thermal fluctuations than a sparse graph, we can realize a change in recall pattern by tuning relative weights of the two patterns properly. We demonstrate by
equilibrium Monte-Carlo simulations that such a temperature-dependent change in recall patterns does occur in our model. Simulation results strongly indicate that the system undergoes a first-order phase transition when the change in recall patterns occurs. It is also demonstrated by annealing simulations that the system fails to recall the pattern embedded in the sparse graph at low temperatures if the free-energy barrier is too high to overcome within the given simulation timescale.
Read the full abstract ▾
Strongly Correlated Electrons · Cross-listed from quant-ph
Non-Clifford symmetry protected topological hyper-cluster states and multi-qubit universal measurement-based quantum computation
Motohiko Ezawa
A cluster state is a highly entangled
quantum state that serves as a universal resource for measurement-based
quantum computation. It is generated by applying controlled-Z (CZ) gates to the product state $\left\vert ++\cdots +\right\rangle $, and its parent
Hamiltonian is the ZXZ model. This model exhibits a topological phase protected by the $\mathbb{Z}_{2}^{\text{even}}\times \mathbb{Z}_{2}^{\text{odd}}$\
symmetry. By applying general
quantum gates to the state $\left\vert ++\cdots +\right\rangle $, we systematically obtain a general short-range entangled cluster state. If we use the controlled-controlled Z (CCZ) gate instead of the CZ gate, we obtain hyper-cluster states featuring five-body interaction terms. These states enable the implementation of the CZ gate within measurement-based
quantum computation. Motivated by this, we propose a generalization to the C$^{N}$Z gate, leading to a hyper-cluster model, in which $(2N+1)$-body entangled states are generated. This model retains the $\mathbb{Z}_{2}^{\text{even}}\times \mathbb{Z}_{2}^{\text{odd}}$\
symmetry, which lies outside the Clifford group for $N\geq 3$. We demonstrate that an open chain in this model exhibits a $2^{2N}$ fold degenerate ground states protected by the
symmetry, corresponding to the emergence of $N$ effective free
spins at each edge. These boundary degrees of freedom can serve as $N$
qubits for measurement-based
quantum computation. In particular, this framework makes it possible to implement the C$^{N-1}$Z gate in measurement-based
quantum computation.
Read the full abstract ▾