Strongly Correlated Electrons
Beyond Hubbard: the role of correlated hopping interaction in superconductors and quantum dot devices
Karol I. Wysokiński and Marcin M. Wysokiński
We investigate the role of strong Coulomb interactions beyond the standard Hubbard model in two distinct physical contexts. First, we analyze the superconducting phase transition occurring near the Mott metal-
insulator transition. Second, we study transport properties of artificial nano-scale structures containing
quantum dots coupled to external electrodes. In both cases, we focus on the impact of the correlated (assisted) hopping (CH) interaction. For
superconductors, CH acts as a driving mechanism for the phase transition and modifies the spectral properties of the system. We present the
evolution of the spectral function as the system approaches the Mott-type transition under varying model parameters. In
quantum-dot-based devices, CH influences the tunneling amplitude between the dot and metallic leads. We demonstrate that the characteristic changes in the conductance of a normal metal-
quantum dot-normal metal structure provide a clear signature of the presence and sign of CH interaction.
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Materials Science · Cross-listed from quant-ph
Quantum solver for single-impurity Anderson models with particle-hole symmetry
Mariia Karabin, Tanvir Sohail, Dmytro Bykov et al. (+8 more)
Quantum embedding methods, such as dynamical mean-field theory (DMFT), provide a powerful framework for investigating strongly correlated materials. A central computational bottleneck in DMFT is in solving the Anderson
impurity model (AIM), whose exact solution is classically intractable for large bath sizes. In this work, we develop and
benchmark a
quantum-classical hybrid solver tailored for DMFT applications, using the variational
quantum eigensolver (VQE) to prepare the ground state of the AIM with shallow
quantum circuits. The solver uses a unified ansatz framework to prepare the particle and hole excitations of the ground-state from parameter-shifted
circuits, enabling the reconstruction of the
impurity Green's function through a continued-fraction expansion. We evaluate the performance of this approach across a few bath sizes and interaction strengths under noisy, shot-limited conditions. We compare three optimization routines (COBYLA, Adam, and L-BFGS-B) in terms of convergence and fidelity, assess the benefits of estimating a
quantum-computed moment (QCM) correction to the variational energies, and
benchmark the approach by comparing the reconstructed density of states (DOS) against that obtained using a classical pipeline. Our results demonstrate the feasibility of Green's function reconstruction on near-term devices and establish practical
benchmarks for
quantum impurity solvers embedded within self-consistent DMFT loops.
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All authors Mariia Karabin, Tanvir Sohail, Dmytro Bykov, Eduardo Antonio Coello Pérez, Swarnava Ghosh, Murali Gopalakrishnan Meena, Seongmin Kim, Amir Shehata, In-Saeng Suh, Hanna Terletska, Markus Eisenbach
Superconductivity
Superfluid Density, Penetration Depth, Condensate Density
Warren E. Pickett
Fascination with the concept of superconducting (SC) superfluid density $\rho_s$ has persisted since the beginning of superconductivity theory, with numerical values of an actual density rarely provided. Over time $\rho_s$, addressed mostly in cuprate and following high temperature
superconductors, has become synonymous with the normalized (unitless) inverse square of the
magnetic penetration depth $\lambda_L$ (the London expression, with superfluid density denoted $n_s$), with interest primarily on its temperature $T$ dependence that is expected to reflect the T-dependence of the SC gap amplitude and gap
symmetry. In conventional
superconductors, generalized expressions from the London penetration depth via Ginzburg-Landau theory, then to BCS theory provide updated pictures of the supercurrent density-vector potential relationship. The BCS value $\lambda_{band}$ is distinct from any particle density, instead involving particle availability at the
Fermi surface and
Fermi velocity as the determining factors, thus providing a basis for a more fundamental theory and understanding of what is being probed in penetration depth studies. The number density of superconducting electrons ${\cal N}_s(T$=0) – the scalar SC condensate density – is provided, first from a phenomenological estimate but then supported by BCS theory. A straightforward relation connecting ${\cal N}_s(0)$ to the density of dynamically transporting carriers in the normal state at $T_c$ is obtained. Numerical values of relevant material parameters including $\lambda_{band}$ and ${\cal N}_s$ are provided for a few conventional SCs.
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Strongly Correlated Electrons
Flat-band Ferromagnetism of SU$(N)$ Hubbard Model on the Kagome Lattices
Hao Jin and Wenxing Nie
The kagome
lattice, a well known example of the geometrically frustrated system, hosts a dispersionless flat band that offers a unique platform for studying correlation-driven
quantum phenomena. At appropriate particle concentrations, the existence of a flat band allows a representation of percolation with nontrivial weights. In this work, we investigate the paramagnetic-
ferromagnetic transition in the repulsive SU($N$) Hubbard model on the kagome
lattice within this percolation framework. In this representation, the model can be rigorously mapped to a classical $N$-state site-percolation problem on a triangular
lattice, with the SU($N$)
symmetry reflected in the nontrivial weights. By large-scale Monte Carlo simulations for SU($3$), SU($4$), and SU($10$)
symmetries, we demonstrate that the critical particle concentration for ferromagnetism exceeds the standard percolation threshold and increases with $N$, indicating a strengthening of the effective entropic repulsion.
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Mesoscale and Nanoscale Physics
Topologically switchable transport in a bundled cable of wires
Nirnoy Basak, Ritajit Kundu, Basudeb Mondal et al. (+1 more)
Advances in the next generation of mesoscopic electronics require an understanding of topological phases in inhomogeneous media and the principles that govern them. Motivated by the nature of motifs available in printable conducting inks, we introduce and study
quantum transport in a minimal model that describes a bundle of one-dimensional metallic wires that are randomly interconnected by semiconducting chains. Each of these interconnects is represented by a Su-Schrieffer-Heeger chain, which can reside in either a trivial or a topological phase. Using a tight-binding approach, we show that such a system can transit from an insulating phase to a robust metallic phase as the interconnects undergo a transition from a trivial to a topological phase. In the latter, despite the random interconnectedness, the metal evades Anderson localization and exhibits a ballistic conductance that scales linearly with the number of wires. We show that this behavior originates from hopping renormalization in the wire network. The zero-energy modes of the topological interconnects act as effective random dimers, giving rise to an energy-dependent localization length that diverges as $\sim 1/E^2$. Our work establishes that random networks provide a yet-unexplored platform to host intriguing phases of topological
quantum matter.
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All authors Nirnoy Basak, Ritajit Kundu, Basudeb Mondal, Adhip Agarwala
Strongly Correlated Electrons
Correlated states in charge-transfer heterostructures based on rhombohedral multilayer graphene
Yanran Shi, Min Li, Xin Lu et al. (+1 more)
Charge transfer is a common phenomenon in van der Waals
heterostructures with proper work function mismatch, which enables electrostatic gating to control band
alignment and interlayer charge distributions. This provides a tunable platform for studying coupled
bilayer correlated electronic systems. Here, we theoretically investigate
heterostructures of rhombohedral multilayer
graphene (RMG) and an insulating substrate with gate-tunable band
alignment. We first develop a self-consistent electrostatic theory for layer charge densities incorporating charge transfer, which reproduces the experimentally observed broadened and bent charge neutrality region. When the substrate's band edge has a much larger effective mass than RMG, its carriers may form a Wigner
crystal at low densities. This generates a
quantum superlattice that induces topological flat bands in the RMG layer through interlayer Coulomb interactions, which may further lead to Chern
insulators driven by Coulomb interactions within the RMG layers. Conversely, with comparable effective masses, we find an interlayer excitonic
insulator state at charge neutrality stabilized by interlayer Coulomb coupling. Our work establishes these charge-transfer
heterostructures as a rich platform for topological and excitonic correlated states.
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All authors Yanran Shi, Min Li, Xin Lu, Jianpeng Liu
Materials Science
Emergence of unconventional magnetic order in strain-engineered RuO2/TiO2 superlattices
Seung Gyo Jeong, Seungjun Lee, Jin Young Oh et al. (+8 more)
The
spin ordering in RuO2 remains a highly debated topic, owing to its elusive nature, with reports ranging from a nonmagnetic ground state to signatures of unconventional
magnetic order. Here we provide the first unambiguous, and direct evidence of unconventional magnetism in epitaxial, fully strained RuO2/TiO2 superlattices on TiO2 (110) substrate grown by hybrid molecular beam epitaxy. Polarized
neutron reflectometry reveals a finite
magnetic moment localized within the compressively strained RuO2 layers, consistent with predictions obtained from first-principles calculations. Complementary density functional theory and X-ray photoemission spectroscopy show that epitaxial strain drives the Ru 4d states toward the
Fermi level, triggering a Stoner-type instability that stabilizes non-compensated
magnetic order. These unique results reveal that RuO2 exhibits unconventional
magnetic states under epitaxial strain, which are not accessible in bulk and establish strain engineering as a powerful route to uncover and control
magnetic phases in RuO2 and related
oxides.
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All authors Seung Gyo Jeong, Seungjun Lee, Jin Young Oh, Bonnie Y.X. Lin, Anand Santhosh, James M. LeBeau, Alexander J. Grutter, Woo Seok Choi, Tony Low, Valeria Lauter, Bharat Jalan
Materials Science
Incipient modulated phase in Sr$_{1-x}$Ca$_{x}$TiO$_3$
Benoît Fauqué, Daniel A. Chaney, Philippe Bourges et al. (+8 more)
Nanometer-scale modulations can spontaneously emerge in complex materials when multiple degrees of freedom interact. Here we demonstrate that ferroelectric Sr$_{1-x}$Ca$_x$TiO$_3$ lies in close proximity to an incipient structurally modulated phase. Using inelastic
neutron and X-ray scattering, we show that upon cooling, dipolar fluctuations strongly couple to and soften the $c_{44}$ transverse acoustic mode. We identify the wavevector at which this softening is maximal, thereby defining the characteristic length scale of the modulation. Calcium substitution enhances both the amplitude and the wavevector of the softening by strengthening the ferroelectric and antiferrodistortive instabilities. Our results demonstrate that nonlinear flexoelectric
phonon coupling tends to stabilize a modulated state that cooperates with, rather than competes against, the other
lattice instabilities in SrTiO$_3$.
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All authors Benoît Fauqué, Daniel A. Chaney, Philippe Bourges, Stéphane Raymond, Arno Hiess, Paul Steffens, Benoît Baptiste, Luigi Paolasini, Alexeï Bosak, Kamran Behnia, Yasuhide Tomioka
Materials Science
Comprehensive parameter and electrochemical dataset for a 1 Ah graphite/LNMO battery cell for physical modelling as a blueprint for data reporting in battery research
Christina Schmitt, August Johansson, Xavier Raynaud et al. (+9 more)
While current technology has enabled their widespread use, further improvements are needed for stationary, portable, and mobile applications, for example by the development of novel cathode materials. Digitalization of battery development, combining both experimental and modelling efforts is extremely valuable in this development. This is addressed in the present paper, where the authors present a comprehensive
dataset for a graphite/LNMO 1 Ah pouch
cell, including material, design, and electrochemical data. The
dataset, validated through the BattMo modelling framework, supports physical modelling and aims to benefit the battery modelling community by offering a comprehensive resource for future studies. Both the
dataset and the accompanying software for numerical validation is openly available and processed in such a way that it can serve as blueprint for reporting of comparable research data.
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All authors Christina Schmitt, August Johansson, Xavier Raynaud, Eibar Joel Flores Cedeño, John Mugisa, Dane Sotta, Agathe Martin, Nicolas Schaeffer, Cédric Debruyne, Yvan Reynier, Simon Clark, Dennis Kopljar
Materials Science
Growth and Morphology of InN Nanowires on Si<111> and Si<100> at Back-End-Of-Line Compatible Temperatures
Andrea Orlando-cunnac, Arthur Arnaud, Martien Den Hertog et al. (+4 more)
InN nanowires were grown on Si<111> and Si<100> substrates by
plasma-assisted molecular beam epitaxy using a thin AlN buffer layer at temperatures compatible with the thermal budget limitation imposed by Back-End-Of-Line processing. Reflection high-energy electron diffraction reveals different nucleation behaviors on the two substrate orientations, with higher structural disorder in the case of Si<100>. However, vertically aligned nanowires with hexagonal cross section and N polarity are obtained on both substrates. A statistical analysis of nanowire morphology as a function of growth temperature indicates similar trends in diameter, density, and length on Si<111> and Si<100>, which are explained by adatom kinetics during growth. Nanowires on Si<100> exhibit improved uniformity and reduced tapering, attributed to the different nanowire nucleation due to microstructural properties of the AlN buffer layer. The results demonstrate the feasibility of growing high-quality InN nanowires on Si<100>, supporting their potential for monolithic integration of nanowire-based photodetectors on silicon.
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All authors Andrea Orlando-cunnac, Arthur Arnaud, Martien Den Hertog, Ettore Coccato, Vincent Calvo, Jonathan Steckel, Eva Monroy
Mesoscale and Nanoscale Physics
Plasmon dynamics in graphene
Suheng Xu, Birui Yang, Nishchhal Verma et al. (+15 more)
Plasmon are collective oscillations of mobile electrons with dynamics controlled by their charge stiffness("Drude weight"). Using terahertz spacetime metrology, we probe Plasmon dynamics of mono- and bi-layer
graphene. In both systems, the experimentally measured Drude weight systematically exceeds the prediction based on non-interacting electronic system. The relative enhancement increases as the carrier density decreases. We attribute the observed deviation to the interplay of interactions and wave function structure of the Dirac
fermions in multi-layer
graphene. Our results establish that pseudospin structure of the single-particle electronic wave function can directly influence collective excitations, with implications that extend beyond
graphene to a broad class of
quantum materials.
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All authors Suheng Xu, Birui Yang, Nishchhal Verma, Rocco A. Vitalone, Brian Vermilyea, Miguel Sánchez Sánchez, Julian Ingham, Ran Jing, Yinming Shao, Tobias Stauber, Angel Rubio, Milan Delor, Mengkun Liu, Michael M. Fogler, Cory R. Dean, Andrew Millis, Raquel Queiroz, D. N. Basov
Strongly Correlated Electrons
Magnetic-field-induced Tomonaga-Luttinger liquid and Bose-Einstein condensate phases in an organic S=1 Haldane chain
I. Jakovac, M. S. Grbić, M. Dupont et al. (+7 more)
We present a comprehensive low-temperature $^1$H
nuclear magnetic resonance (NMR) study of
magnetic field-induced phases and
spin fluctuations in an isotropic Haldane chain system $m$-NO$_2$PhBNO (BoNO) in fields up to 34 T. NMR spectral and $T_1^{-1}$ relaxation rate data are used to map out the transition temperature $T_c(B)$ and we show that it defines a complete phase boundary between the field-induced Bose-Einstein condensate (BEC) and Tomonaga-Luttinger
liquid (TLL) phases by reproducing its shape via
quantum Monte Carlo calculations. We also observe the theoretical critical behavior $T_c (B) \propto (B-B_\text{c2})^{\nu}$ with $\nu = 2/3$ and universal quasiparticle scaling in the low-temperature limit close to $B_\text{c2}$. The extensive
Bayesian inference analysis of the temperature and field dependence of $T_1 ^{-1} (T,B)$ reveals attractive interactions across the TLL phase of a Haldane chain. Our results are further corroborated by magnetostriction measurements in pulsed
magnetic fields and density
matrix renormalization group calculations.
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All authors I. Jakovac, M. S. Grbić, M. Dupont, N. Laflorencie, S. Capponi, Y. Hosokoshi, S. Krämer, Y. Skourski, S. Luther M. Takigawa, M. Horvatić
Disordered Systems and Neural Networks · Cross-listed from math.OC
High-Dimensional Analysis of Gradient Flow for Extensive-Width Quadratic Neural Networks
Simon Martin, Giulio Biroli and Francis Bach
We study the high-dimensional training dynamics of a shallow neural network with quadratic activation in a teacher-student setup. We focus on the extensive-width regime, where the teacher and student network widths scale proportionally with the input dimension, and the sample size grows quadratically. This scaling aims to describe overparameterized neural networks in which feature learning still plays a central role. In the high-dimensional limit, we derive a dynamical characterization of the gradient flow, in the spirit of dynamical mean-field theory (DMFT). Under l2-regularization, we analyze these equations at long times and characterize the performance and spectral properties of the resulting
estimator. This result provides a quantitative understanding of the effect of overparameterization on learning and generalization, and reveals a double descent phenomenon in the presence of label noise, where generalization improves beyond interpolation. In the small regularization limit, we obtain an exact expression for the perfect recovery threshold as a function of the network widths, providing a precise characterization of how overparameterization influences recovery.
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Superconductivity
Effects of Integrated Heatsinking on Superconductivity in Tantalum Nitride Nanowires at the 300 Millimeter Scale
Ekta Bhatia, Tharanga R. Nanayakkara, Chenyu Zhou et al. (+14 more)
We report the superconducting properties of tantalum nitride (TaN) nanowires and TaN/copper (TaN/Cu)
bilayer nanowires fabricated on 300 mm silicon wafers using CMOS-compatible processes. We evaluate how an integrated Cu heatsink modifies the superconducting response of TaN nanowires by improving thermal dissipation without significantly compromising key superconducting parameters. Through analysis of hysteresis in current-voltage curves, we demonstrate that Cu integration improves heat dissipation, supporting expectations of faster reset times in superconducting nanowire single-
photon detectors (SNSPDs), consistent with enhanced heat transfer away from the hot spot. Using the Skocpol-Beasley-Tinkham (SBT) hotspot model, we quantify the Cu-enabled improvement in heat transfer as an approximately 100x increase in the SBT slope parameter beta and effective interfacial heat-transfer efficiency compared to TaN nanowires. The near-unity ratio of critical to retrapping current in TaN/Cu
bilayer nanowires provides another evidence of efficient heat removal enabled by the integrated Cu layer. Our results show a zero-temperature Ginzburg-Landau coherence length of 7 nm and a critical temperature of 4.1 K for 39 nm thick TaN nanowires. The nanowires show <5% variation in critical dimensions, room-temperature resistance, residual resistance ratio, critical temperature, and critical current across the 300 mm wafer for all measured linewidths, demonstrating excellent process uniformity and scalability. These results indicate the trade-offs between superconducting performance and heat-sinking efficiency in TaN/Cu
bilayer nanowires. They also underscore the viability of wafer-scale fabrication for fast, large-area SNSPD arrays for applications in photonic
quantum computing, cosmology, and neuromorphic computing devices.
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All authors Ekta Bhatia, Tharanga R. Nanayakkara, Chenyu Zhou, Tuan Vo, Wenli Collison, Jakub Nalaskowski, Stephen Olson, Soumen Kar, Hunter Frost, John Mucci, Brian Martinick, Ilyssa Wells, Thomas Murray, Corbet Johnson, Charles T Black, Mingzhao Liu, Satyavolu S Papa Rao
Mesoscale and Nanoscale Physics
Quantum Theory and Unusual Dielectric Functions of Graphene
V. M. Mostepanenko and G. L. Klimchitskaya
We address the spatially nonlocal dielectric functions of
graphene at any frequency derived starting fromthe first principles of thermal
quantum field theory using the formalism of the polarization tensor. After a brief review of this formalism, the longitudinal and transverse dielectric functions are considered at any relationship between the frequency and the wave vector. The analytic properties of their real and imaginary parts are investigated at low and high frequencies. Emphasis is given to the double pole at zero frequency which arises in the transverse dielectric function. The role of this unusual property for solving the problem of disagreement between experiment and theory in the Casimir effect is discussed. We guess that a more complete dielectric response of ordinary metals should also be spatially nonlocal and its transverse part may possess the double pole in the region of evanescent waves.
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Quantum Gases · Cross-listed from quant-ph
Nonlinear quantum Kibble-Zurek ramps in open systems at finite temperature
Johannes N. Kriel, Emma C. King and Michael Kastner
We analyze
quantum systems under a broad class of protocols in which the temperature and a
Hamiltonian control parameter are ramped simultaneously and, in general, in a nonlinear fashion toward a
quantum critical point. Using an open-system version of a Kitaev
quantum wire as an example, we show that, unlike finite-temperature protocols at fixed temperature, these protocols allow us to probe, in an out-of-
equilibrium situation and at finite temperature, the universality class (characterized by the critical exponents $\nu$ and $z$) of an
equilibrium quantum phase transition at zero temperature. Key to this is the identification of ramps in which both coherent and incoherent parts of the open-system dynamics affect the excitation density in a non-negligible way. We also identify the specific ramps for which subleading corrections to the asymptotic scaling laws are suppressed, which serves as a guide to dynamically probing
quantum critical exponents in experimentally realistic finite-temperature situations.
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Other Condensed Matter · Cross-listed from quant-ph
Localization Landscape in Non-Hermitian and Floquet quantum systems
David Guéry-Odelin and François Impens
We propose a generalization of the Filoche–Mayboroda localization landscape that extends the theory well beyond the static,
elliptic and Hermitian settings while preserving its
geometric interpretability. Using the positive operator $H^\dagger H$, we obtain a landscape that predicts localization across non-Hermitian, Floquet, and topological systems without computing eigenstates. Singular-value collapse reveals spectral instabilities and skin effects, the Sambe formulation captures coherent destruction of tunneling, and topological zero modes emerge directly from the landscape. Applications to Hatano–Nelson chains, driven two-level systems, and driven Aubry–André–Harper models confirm quantitative accuracy, establishing a unified predictor for localization in
equilibrium and driven
quantum matter.
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Materials Science
The transformation mechanisms among cuboctahedra, Ino's decahedra and icosahedra structures of magic-size gold nanoclusters
Ehsan Rahmatizad Khajehpasha, Mohammad Ismaeil Safa, Nasrin Eyvazi et al. (+2 more)
Gold nanoclusters possess multiple competing structural motifs with small energy differences, enabling structural coexistence and interconversion. Using a high-accuracy machine learned potential trained on some 20'000 density functional theory reference data points, we investigate transformation pathways connecting both high-
symmetry and amorphous cuboctahedra, Ino's decahedra and icosahedra for Au55, Au147, Au309 and Au561 nanoclusters. Our saddle point searches reveal that high-
symmetry transformations from cuboctahedra and Ino's decahedra to icosahedra proceed through a single barrier and represent soft-mode-driven jitterbug-type and slip-dislocation motions. In addition, we identify lower-barrier asymmetric transformation pathways that drive the system into disordered, Jahn-Teller-stabilized amorphous icosahedra. Minima Hopping sampling further uncovers, in this context, many such low-
symmetry minima. Some of the newly identified global minima for Au309 and Au561 have energies that are up to 2.8 eV lower than the previously reported global minima. Hence, both the shapes and the transformation pathways studied in previous investigations are not the physically relevant ones. In contrast to the previously studied pathways, our transformation pathways give reasonable transformation times that are in rough agreement with experiments.
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All authors Ehsan Rahmatizad Khajehpasha, Mohammad Ismaeil Safa, Nasrin Eyvazi, Marco Krummenacher, Stefan Goedecker
Soft Condensed Matter
Spinodal decomposition in filled polymer blends exhibiting upper critical solution temperature behavior
A.I. Chervanyov
By extending the Sanchez-Lacombe
lattice-fluid model for mixtures to the case of
polymer blends containing solid fillers, we calculate the excess thermodynamic quantities arising from the presence of fillers. These results are then used to derive the spinodal stability condition of a filled
polymer blend. In the low-compressibility limit, this condition reduces to a remarkably simple analytical expression that is derived self-consistently within the present framework. Comparison between the exact and approximate spinodal curves shows excellent agreement, with deviations in the spinodal temperature of less than 4 K, thereby validating the proposed approximation. The obtained analytical approximation enables a straightforward evaluation of the spinodal temperature without the extensive numerical calculations required to determine the exact spinodal condition. Both the exact and approximate spinodal conditions yield good quantitative agreement with experimental data for filled and unfilled blends.
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Disordered Systems and Neural Networks
The eigenvalues and eigenvectors of finite-rank normal perturbations of large rotationally invariant non-Hermitian matrices
Pierre Bousseyroux and Marc Potters
We study finite-rank normal deformations of rotationally invariant non-Hermitian random
matrices. Extending the classical Baik-Ben Arous-Péché (BBP) framework, we characterize the emergence and fluctuations of outlier
eigenvalues in models of the form $\mathbf{A} + \mathbf{T}$, where $\mathbf{A}$ is a large rotationally invariant non-Hermitian random
matrix and $\mathbf{T}$ is a finite-rank normal perturbation. We also describe the corresponding eigenvector behavior. Our results provide a unified framework encompassing both Hermitian and non-Hermitian settings, thereby generalizing several known cases.
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Quantum Gases
Cloud parameter estimation for interacting BEC after time-of-flight
Rasmus Malthe Fiil Andersen, Stine Frederiksen, Laurits Stokholm et al. (+4 more)
Experiments on Bose-Einstein condensates at finite temperature typically extract the system parameters, such as temperature, atom number, and condensed fraction from time-of-flight images taken after a free expansion time. This paper systematically examines the effect of repulsive interactions between the condensed and thermal atoms in partially condensed clouds on the expansion profile of the thermal cloud. An analytical expression for the expansion can be obtained only if the interactions between the Bose-Einstein condensate and thermal atoms are neglected, resulting in a Bose-enhanced distribution for the thermal component. Here, the deformation of the cloud due to interactions and the effects on estimated parameters are investigated by simulating the expansion using a ballistic approximation. By fitting the simulated expansion profiles with a Bose-enhanced distribution, the errors of using such a fit are estimated, and the results are explained phenomenologically. The simulation was also used as a fitting function for experimental data, showing better agreement of the extracted condensed fraction with the semi-ideal model than results from a Bose-enhanced fit.
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All authors Rasmus Malthe Fiil Andersen, Stine Frederiksen, Laurits Stokholm, Ilja Zebergs, Mick Kristensen, Carrie Weidner, Jan Joachim Arlt
Strongly Correlated Electrons
Basal-plane anisotropy of field-induced multipolar order in tetragonal CeRh$_2$As$_2$
Konstantin Semeniuk, Burkhard Schmidt, Christophe Marcenat et al. (+6 more)
Unconventional superconductivity in Ce-based Kondo-
lattice materials emerges almost exclusively in the vicinity of weak dipolar
magnetic orders, while higher multipolar orders are only known to occur in a few Pr-based unconventional
superconductors and possibly URu$_2$Si$_2$. The multiphase
superconductor CeRh$_2$As$_2$ appears to be a notable exception from this trend. Showing clear signatures of magnetism, this tetragonal system is suspected to host a concomitant quadrupolar order, which could be causing the strong enhancement of the ordering temperature when a
magnetic field is applied perpendicular to the fourfold ($c$) axis of the
lattice. In this work, we show that the field-temperature phase diagram of CeRh$_2$As$_2$ has a remarkable basal-plane anisotropy. This finding supports the scenario of coupled
magnetic and multipolar ordering, which may have implications for the pairing mechanism of the superconductivity, and guides the development of the next iteration of theoretical models.
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All authors Konstantin Semeniuk, Burkhard Schmidt, Christophe Marcenat, Meike Pfeiffer, Albin Demuer, Lipsa Behera, Thierry Klein, Seunghyun Khim, Elena Hassinger
Materials Science · Cross-listed from hep-ex
A comparison of simulation tools for Muon-Induced X-ray Emission (MIXE) in thin films: a study case with lithium batteries
Maxime Lamotte, Michael W. Heiss, Thomas Prokscha et al. (+1 more)
We present a comparative study of three Monte Carlo simulation frameworks -SRIM, GEANT4, and PHITS- for modeling the transport, stopping, and atomic cascade of negative
muons in micrometer-scale, multilayer systems relevant to
Muon-Induced X-ray Emission (MIXE) experiments at the Paul Scherrer Institute (PSI). Using a lithium-ion battery as a
benchmark target, simulated implantation profiles are compared with experimental data from the
GIANT spectrometer. All three codes reproduce the overall
muon depth distributions with good consistency, even across sharp density contrasts. SRIM provides reliable implantation estimates for compact geometries, whereas PHITS reproduces GEANT4 results with comparable accuracy and additionally generates muonic X-ray spectra. These spectra, however, exhibit a systematic energy offset in the K-line transitions of medium- and high-Z elements relative to theoretical and experimental values. Despite this bias, PHITS accurately captures relative intensities and spectral shapes, enabling element-specific line identification. The results demonstrate that SRIM and PHITS constitute practical tools for rapid estimation of
muon implantation and stopping profiles, and that PHITS holds strong potential for predictive MIXE spectroscopy once its transition-energy bias is corrected.
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All authors Maxime Lamotte, Michael W. Heiss, Thomas Prokscha, Alex Amato
Soft Condensed Matter
Advanced Manufacturing with Renewable and Bio-based Materials: AI/ML workflows and Process Optimization
Rigoberto Advincula and Jihua Chen
Advanced manufacturing with new bio-derived materials can be achieved faster and more economically with first-principle-based artificial intelligence and machine learning (AI/ML)-derived models and process optimization. Not only is this motivated by increased industry profitability, but it can also be optimized to reduce waste generation, energy consumption, and gas emissions through additive manufacturing (AM) and AI/ML-directed self-driving laboratory (SDL) process optimization. From this perspective, the benefits of using 3D printing technology to manufacture durable, sustainable materials will enable high-value reuse and promote a better circular economy. Using AI/ML workflows at different levels, it is possible to optimize the synthesis and adaptation of new bio-derived materials with self-correcting 3D printing methods, and in-situ characterization. Working with training data and hypotheses derived from Large
Language Models (LLMs) and
algorithms, including ML-optimized simulation, it is possible to demonstrate more field convergence. The combination of SDL and AI/ML Workflows can be the norm for improved use of biobased and renewable materials towards advanced manufacturing. This should result in faster and better structure, composition, processing, and properties (SCPP) correlation. More agentic AI tasks, as well as supervised or unsupervised learning, can be incorporated to improve optimization protocols continuously. Deep Learning (DL), Reinforcement Learning (RL), and Deep Reinforcement Learning (DRL) with Deep Neural Networks (DNNs) can be applied to more generative AI directions in both AM and SDL, with bio-based materials.
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Materials Science
Topology-Directed Silicide Formation: An Explanation for the Growth of C49-TiSi$_2$ on the Si(100) Surface
Lukas Hückmann, Jonathon Cottom, Jörg Meyer et al. (+1 more)
Designing metal-
semiconductor junctions is essential for optimizing the performance of modern nanoelectronic devices. A widely used material is TiSi$_2$, which combines low electronic resistivity with good endurance. However, its multitude of polymorphs continues to pose a challenge for device fabrication. In particular, the naturally occurring formation of the metastable C49-TiSi$_2$ modification remains poorly understood and is problematic due to its unfavorable electronic properties. Based on extensive DFT calculations, we present a comprehensive model of Ti adsorption on Si(100) that highlights the pivotal role of surface
topology for the initial stages of the interfacial TiSi$_2$ formation process. We show that the interplay between Si surface dimers, the
symmetry of the Si(100) surface, and the incorporation of Ti adsorbates below the surface drives an adsorption pattern that yields a nucleation template for the C49-TiSi$_2$ phase. Our atomistic model rationalizes experimental observations like the Stranski-Krastanov growth mode, the preferential formation of C49-TiSi$_2$ despite it being less favorable than the competing C54 phase, and why disruption of the surface structure restores thermodynamically driven growth of the latter. Ultimately, this novel perspective on the unique growth of TiSi$_2$ will help to pave the way for next-generation electronic devices.
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All authors Lukas Hückmann, Jonathon Cottom, Jörg Meyer, Emilia Olsson
Soft Condensed Matter
Capillary Slinky: Equilibrium and Dynamics of Droplets in a Soft Spring
Bidisha Bhatt and Andreas Carlson
Springs can be found in many applications and biological systems, and when these are soft, they easily deform. At small scales, capillarity can induce a force leading to spring deformations when the elastocapillary number is small. We demonstrate through experiments the non-trivial
equilibrium shape
liquid droplets adopt in these soft springs, which form an annulus, Eruciform, and spherical shapes. When these droplets are set in motion, they display different flow regimes with significant dissipation generated by the internal rotational flow. The static and dynamics of droplets in such a capillary slinky is also used to demonstrate how surface tension can actuate springs by stretching/compression, while providing a way for active flow control in soft springs.
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Quantum Gases
Enhanced multi-parameter metrology in dissipative Rydberg atom time crystals
Bang Liu, Jun-Rong Chen, Yu Ma et al. (+10 more)
The pursuit of unprecedented sensitivity in
quantum enhanced metrology has spurred interest in non-
equilibrium quantum phases of matter and their
symmetry breaking. In particular, criticality-enhanced metrology through time-translation
symmetry breaking in many-body systems, a distinct paradigm compared to spatial
symmetry breaking, is a field still in its infancy. Here, we have investigated the enhanced sensing at the boundary of a continuous time-
crystal (CTC) phase in a driven Rydberg atomic gas. By mapping the full phase diagram, we identify the parameter-dependent phase boundary where the time-translation
symmetry is broken. This allows us to use a single setup for measuring multiple parameters, in particular frequency and amplitude of a microwave field. By increasing the microwave field amplitude, we first observe a phase transition from a thermal phase to a CTC phase, followed by a second transition into a distinct CTC state, characterized by a different oscillation frequency. Furthermore, we reveal the precise relationship between the CTC phase boundary and the scanning rate, displaying enhanced precision beyond the Standard
Quantum Limit. This work not only provides a promising paradigm rooted in the critical properties of time
crystals, but also advances a method for multi-parameter sensing in non-
equilibrium quantum phases.
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All authors Bang Liu, Jun-Rong Chen, Yu Ma, Qi-Feng Wang, Tian-Yu Han, Hao Tian, Yu-Hua Qian, Guang-Can Guo, Li-Hua Zhang, Bin-Bin Wei, Abolfazl Bayat, Dong-Sheng Ding, Bao-Sen Shi
Disordered Systems and Neural Networks
Computer Generation of Disordered Networks with Targeted Structural Properties
Florin Hemmann, Vincent Glauser, Ullrich Steiner et al. (+1 more)
Disordered spatial networks describe structures and interactions across multiple length scales. The scattering and interference of waves within these networks result in structural phase transitions, localization,
diffusion, and band gaps. Studying these phenomena requires efficient numerical methods for generating disordered networks with specific structural properties. The Wooten-Weaire-Winer
algorithm is an established method that introduces disorder into an initial network through a series of bond switch moves. However, the strain energies that govern this
evolution are conventionally limited to three-dimensional networks with coordination numbers of no more than four. We here introduce a maximum bond repulsion to produce networks with an arbitrary coordination number. We control the degree and type of disorder by adjusting the bond-bending force constant in the strain energy and the temperature profile. The effects of these variables are quantified through a list of order metrics that capture both direct and reciprocal space. A feedforward neural network predicts the structural characteristics from the
algorithm inputs, enabling efficient targeted network generation. As a case study, we statistically reproduce four disordered biophotonic networks that exhibit structural color. This work presents a versatile method for generating disordered networks with tailored structural properties. It will provide new insights into structure-property relations.
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All authors Florin Hemmann, Vincent Glauser, Ullrich Steiner, Matthias Saba
Materials Science · Cross-listed from physics.chem-ph
Molecular electrostatic potentials from machine learning models for dipole and quadrupole predictions
Kadri Muuga, Lisanne Knijff and Chao Zhang
The molecular electrostatic potential (MEP) is a key quantity for describing and predicting intermolecular and ion-molecule interactions. Here, we assess the ability of machine-learning (ML) models to infer the MEP, based on the equivariant graph-convolutional neural network architecture PiNet2 and trained on dipole and quadrupole moments. For the established QM9
dataset, we find that including the quadrupole contribution in the ML models substantially improves their ability to recover the MEP compared to dipole-only models. This trend is confirmed on the SPICE
dataset, which spans a much broader region of organic chemical space. Together, this study underscores the central role of the quadrupole moment as a fitting target for ML models aiming at rapid access to the MEP.
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Quantum Gases
Quantum Monte Carlo study of systems interacting via long-range interactions mediated by a cavity
Marta Domínguez-Navarro, Abel Rojo-Francàs, Bruno Juliá-Díaz et al. (+1 more)
We study one-dimensional
quantum gases in continuous space with cavity-mediated infinite-range interactions using the variational and the
diffusion Monte Carlo methods. Starting from the exact two-body solution, we construct a non-translationally invariant Jastrow wave function that accurately captures the spatial structure induced by the cavity field and provides an efficient many-body ansatz for both bosonic and fermionic systems. We analyze properties of three characteristic
quantum systems, subject to long-range interactions: (i) ideal Bose gas, (ii) interacting Bose gas, (iii) ideal
Fermi gas. In the absence of short-range interactions, we identify a crossover from a stable, weakly modulated phase realized at finite particle number for repulsive interactions to a self-organized state for attractive interactions, marked by clustering, loss of superfluidity, and, at fixed interaction strength, the absence of a thermodynamic limit. Introducing short-range repulsion, either through contact interactions or fermionic statistics, leads to the formation of a mesoscopic gas-like regime that disappears in the thermodynamic limit. A qualitative phase diagram is proposed to illustrate the combined effects of short- and long-range interactions, highlighting the emergence of distinct regimes with characteristic structural properties. Applying the Kac prescription, we obtain a well-defined thermodynamic limit and show that the periodic modulation found for a finite number of particles in the repulsive regime is a finite-size artifact, while the self-organized state survives with its onset shifted to substantially stronger coupling.
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All authors Marta Domínguez-Navarro, Abel Rojo-Francàs, Bruno Juliá-Díaz, Grigori E. Astrakharchik