Mesoscale and Nanoscale Physics · Cross-listed from quant-ph
Pairing-induced phase transition in the non-reciprocal Kitaev chain
Pietro Brighi and Andreas Nunnenkamp
Investigating the robustness of non-reciprocity in the presence of competing interactions is central to understanding non-reciprocal
quantum matter. In this work, we use reservoir engineering to induce non-reciprocal hopping and pairing in the fermionic Kitaev chain, and reveal the emergence of a pairing-induced phase transition. The two phases appear in the spectrum of the non-Hermitian Kitaev
Hamiltonian describing the dynamics of correlations, separated by an exceptional point. In the non-reciprocal phase, dynamics are characterized by directionality and slow relaxation, and the steady state supports non-reciprocal density and spatial correlations. At strong pairing, we uncover an unexpected density wave phase, featuring short relaxation times, a modulation in particle occupation and strikingly different correlation spreading depending on pairing non-reciprocity. Our work highlights the non-trivial breakdown of non-reciprocity due to superconducting pairing and invites experimental investigation of non-reciprocal fermionic systems.
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Strongly Correlated Electrons · Cross-listed from math-ph
How to Build Anomalous (3+1)d Topological Quantum Field Theories
Arun Debray, Weicheng Ye and Matthew Yu
We develop a systematic framework for constructing (3+1)-dimensional topological orders or topological
quantum field theories (TQFTs) that realize specified anomalies of finite
symmetries, as encountered in gauge theories with
fermions or in fermionic
lattice systems. Our approach generalizes the
symmetry-extension construction to the fermionic setting, and is grounded in recent advances in the categorical classification of anomalous TQFTs in (3+1)d. In this framework,
symmetry-extension data of a supercohomology theory are translated into a fusion 2-category, on which the anomalous TQFT is built. Building on this machinery, we demonstrate explicit calculations for various
symmetry groups and their associated anomalies, with the help of a hastened Adams spectral sequence for computing supercohomology groups which we will detail in a planned sequel. Finally, we prove that all supercohomology anomalies can be realized by fermionic topological orders, whereas beyond-supercohomology anomalies cannot, resolving a question of Córdova–Ohmori for fermionic (3+1)d systems with finite
symmetries.
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Statistical Mechanics · Cross-listed from math-ph
Liquid-vapor transition in a model of a continuum particle system with finite-range modified Kac pair potential
Qidong He, Ian Jauslin, Joel Lebowitz et al. (+1 more)
We prove the existence of a phase transition in dimension $d>1$ in a continuum particle system interacting with a pair potential containing a modified attractive Kac potential of range $\gamma^{-1}$, with $\gamma>0$. This transition is "close", for small positive $\gamma$, to the one proved previously by Lebowitz and Penrose in the van der Waals limit $\gamma\downarrow0$. It is of the type of the
liquid-vapor transition observed when a fluid, like water, heated at constant pressure, boils at a given temperature. Previous results on phase transitions in continuum systems with stable potentials required the use of unphysical four-body interactions or special
symmetries between the
liquid and vapor. The pair interaction we consider is obtained by partitioning space into cubes of volume $\gamma^{-d}$, and letting the Kac part of the pair potential be uniform in each cube and act only between adjacent cubes. The "short-range" part of the pair potential is quite general (in particular, it may or may not include a hard core), but restricted to act only between particles in the same cube. Our setup, the "boxed particle model", is a special case of a general "
spin" system, for which we establish a first-order phase transition using reflection positivity and the Dobrushin–Shlosman criterion.
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All authors Qidong He, Ian Jauslin, Joel Lebowitz, Ron Peled
Soft Condensed Matter
Positive Feedback Drives Sharp Swelling of Polymer Brushes near Saturation
Simon Schubotz, Eva Bittrich, Holger Merlitz et al. (+4 more)
We resolve the Schröder paradox for PNiPAAm brushes, showing experimentally that swelling at 100% relative humidity (RH) matches the
liquid state. This occurs via a sharp increase in swelling above 98%~RH, a behavior standard models fail to explain. Our extended mean-field theory explains this via a positive feedback between swelling and solvent quality, driven by a concentration-dependent $\chi$ parameter. The swelling isotherm quantitatively predicts the dynamic wetting crossover: the advancing contact angle at high velocities drops sharply as ambient humidity surpasses the 98%~RH threshold.
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All authors Simon Schubotz, Eva Bittrich, Holger Merlitz, Quinn A. Besford, Petra Uhlmann, Jens-Uwe Sommer, Günter K. Auernhammer
Statistical Mechanics · Cross-listed from quant-ph
Distinct Types of Parent Hamiltonians for Quantum States: Insights from the $W$ State as a Quantum Many-Body Scar
Lei Gioia, Sanjay Moudgalya and Olexei I. Motrunich
The construction of parent
Hamiltonians that possess a given state as their ground state is a well-studied problem. In this work, we generalize this notion by considering simple
quantum states and examining the local
Hamiltonians that have these states as exact eigenstates. These states often correspond to
Quantum Many-Body Scars (QMBS) of their respective parent
Hamiltonians. Motivated by earlier works on
Hamiltonians with QMBS, in this work we formalize the differences between three distinct types of parent
Hamiltonians, which differ in their decompositions into strictly local terms with the same eigenstates. We illustrate this classification using the $W$ state as the primary example, for which we rigorously derive the complete set of local parent
Hamiltonians, which also allows us to establish general results such as the existence of asymptotic QMBS, and distinct dynamical signatures associated with the different parent
Hamiltonian types. Finally, we derive more general results on the parent
Hamiltonian types that allow us to obtain some immediate results for simple
quantum states such as product states, where only a single type exists, and for short-range-entangled states, for which we identify constraints on the admissible types. Altogether, our work opens the door to classifying the rich structures and dynamical properties of parent
Hamiltonians that arise from the interplay between locality and QMBS.
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Statistical Mechanics
Memory-induced long-range order drag
Yuan-Hang Zhang, Chesson Sipling and Massimiliano Di Ventra
Recent research has shown that
memory, in the form of slow degrees of freedom, can induce a phase of long-range order (LRO) in locally-coupled fast degrees of freedom, producing power-law distributions of avalanches. In fact, such
memory-induced LRO (MILRO) arises in a wide range of physical systems. Here, we show that MILRO can be transferred to coupled systems that have no
memory of their own. As an example, we consider a stack of layers of
spins with local feedforward couplings: only the first layer contains
memory, while downstream layers are
memory-free and locally interacting. Analytical arguments and simulations reveal that MILRO can indeed drag across the layers, enabling downstream layers to sustain intra-layer LRO despite having neither
memory nor long-range interactions. This establishes a simple, yet generic mechanism for propagating collective activity through media without fine tuning to criticality, with testable implications for neuromorphic systems and laminar information flow in the
brain cortex.
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Disordered Systems and Neural Networks
Long-range resonances in quasiperiodic many-body localization
Ashirbad Padhan, Jeanne Colbois, Fabien Alet et al. (+1 more)
We investigate long-range resonances in quasiperiodic many-body localized (MBL) systems. Focusing on the Heisenberg chain in a deterministic Aubry-André potential, we complement standard diagnostics by analyzing the structure of long-distance pairwise correlations at high energy. Contrary to the expectation that the ergodic-MBL transition in quasiperiodic systems should be sharper due to the absence of Griffiths regions, we uncover a broad unconventional regime at strong quasiperiodic potential, characterized by fat-tailed distributions of longitudinal correlations at long distance. This reveals the presence of atypical eigenstates with strong long-range correlations in a regime where standard diagnostics indicate stable MBL. We further identify these anomalous eigenstates as quasi-degenerate pairs of resonant cat states, which exhibit
entanglement at long distance. These findings advance the understanding of quasiperiodic MBL and identify density-correlation measurements in ultracold atomic systems as a probe of long-range resonances.
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All authors Ashirbad Padhan, Jeanne Colbois, Fabien Alet, Nicolas Laflorencie
Mesoscale and Nanoscale Physics
Bonding Character as a Descriptor for Huang-Rhys Factors in Optically Active Defects
Fatimah Habis and Yuanxi Wang
The electron
phonon coupling of a defect characterized by its Huang Rhys (HR) factor is a crucial metric determining its excited-state dynamics, relevant to defect applications as
qubits and
quantum emitters. However, HR factors remain challenging to calculate from first principles, complicated by convergence issues in excited-state relaxation and time consuming
phonon calculations. Even when calculated, HR factors lack a rational design principle. Here we show that an orbital-based descriptor can be used to rationalize and efficiently estimate HR factors. Combining this descriptor with a ground state deformation technique allows circumventing both excited state relaxation and full
phonon calculations. Specifically, our descriptor for HR factors is constructed using bonding character differences obtained from ground state density functional theory, measured using
crystal orbital Hamilton populations. We demonstrate this descriptor for prototypical hBN defects and the diamond NV center. This orbital-based descriptor can be potentially used in high throughput computational screening to identify ideal candidates of
spin qubits and SPEs.
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Strongly Correlated Electrons
A light-induced charge order mode in a metastable cuprate ladder
Hari Padma, Prakash Sharma, Sophia F. R. TenHuisen et al. (+17 more)
We report the observation of an emergent charge order mode in the optically-excited cuprate ladder Sr$_{14}$Cu$_{24}$O$_{41}$. Near-infrared light in the ladder plane drives a
symmetry-protected electronic metastable state together with a partial melting of the
equilibrium charge order. Our time-resolved resonant inelastic x-ray scattering measurements at the upper Hubbard band reveal a gapless collective excitation dispersing from the charge-order wavevector up to 0.8 eV with a slope on the order of the quasiparticle velocity. These findings reveal a regime where correlated carriers acquire itinerant character at finite momentum, and charge order becomes dynamically fluctuating, offering a platform to explore light-induced pairing instabilities.
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All authors Hari Padma, Prakash Sharma, Sophia F. R. TenHuisen, Filippo Glerean, Antoine Roll, Pan Zhou, Sarbajaya Kundu, Arnau Romaguera, Elizabeth Skoropata, Hiroki Ueda, Biaolong Liu, Eugenio Paris, Yu Wang, Seng Huat Lee, Zhiqiang Mao, Mark P. M. Dean, Edwin W. Huang, Elia Razzoli, Yao Wang, Matteo Mitrano
Materials Science
Flat bands in ultra-wide gap two-dimensional germanium dioxide
Rafael Franco Ribeiro Reis, Gabriel Elyas Gama Araujo, Danilo Kuritza et al. (+3 more)
We employ first principles density-functional theory (DFT) and the Bethe-Salpeter equation (BSE) in the framework of tight-binding based maximally localized Wannier functions (MLWF-TB) model to investigate the electronic and optical properties of free-standing two-dimensional (2D) germanium dioxide phases. All investigated 2D GeO2 polymorphs exhibit ultra-wide band gaps and strong excitonic effects, with flat O-p-derived valence bands tunable under strain. These features allow the design of flat band materials with ultra large electronic gaps in low-dimensional systems, making these materials promising for devices operation at higher voltages and temperatures than conventional
semiconductor materials.
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All authors Rafael Franco Ribeiro Reis, Gabriel Elyas Gama Araujo, Danilo Kuritza, Alexandre Cavalheiro Dias, Andreia Luisa da Rosa, Renato Borges Pontes
Quantum Gases · Cross-listed from physics.atom-ph
Hyperfine-resolved optical spectroscopy of ultracold $^{87}$Rb$^{133}$Cs molecules: the $\mathrm{b}\,^3\Pi_0$ metastable state
Arpita Das, Albert Li Tao, Luke M. Fernley et al. (+6 more)
Using an ultracold gas of $^{87}$Rb$^{133}$Cs molecules, we perform hyperfine-resolved spectroscopy of transitions from the vibronic ground state to the lowest rovibrational states of the electronic state $\mathrm{b}\,^3\Pi_0$, as a function of
magnetic field. These transitions are
spin forbidden, resulting in narrow linewidths, and feature near-diagonal Franck-Condon factors. We develop a model of the hyperfine and Zeeman structure that includes coupling between the $0^+$ and $0^-$ components of $\mathrm{b}\,^3\Pi_0$. We fit the spectra to obtain rotational and hyperfine coupling constants. We measure transition dipole moments associated with specific transitions by directly observing Rabi oscillations as a function of a resonant
laser pulse duration. Using resonant $\pi$ pulses, we prepare molecules in the electronically excited state and directly measure the spontaneous emission rate.
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All authors Arpita Das, Albert Li Tao, Luke M. Fernley, Fritz von Gierke, Philip D. Gregory, Simon L. Cornish, Jeremy M. Hutson, Romain Vexiau, Olivier Dulieu
Mesoscale and Nanoscale Physics
Virtual Gates Enabled by Digital Surrogate of Quantum Dot Devices
Alexander Lidiak, Jacob Swain, David L. Craig et al. (+12 more)
Advances in
quantum technologies are often limited by slow device characterization, complex tuning requirements, and scalability challenges.
Spin qubits in electrostatically defined
quantum dots provide a promising platform but are not exempt from these limitations. Simulations enhance our understanding of such devices, and in many cases, rapid feedback between measurements and simulations can guide the development of optimal design and control strategies. Here, we introduce a modular, graph-based simulator that acts as a digital surrogate for a
semiconductor quantum dot device, where computationally expensive processes are accelerated using deep learning. We demonstrate its potential by estimating crosstalk effects between gate electrodes and applying these estimates to construct virtual gates in a
quantum dot device. We validate our approach through comparison with experiments on a double
quantum dot defined in a Ge/SiGe
heterostructure. We envision that this simulation framework will advance
semiconductor-based
quantum technologies by enabling more efficient design, characterization, and control of complex devices.
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All authors Alexander Lidiak, Jacob Swain, David L. Craig, Joseph Hickie, Yikai Yang, Federico Fedele, Jaime Saez-Mollejo, Andrea Ballabio, Daniel Chrastina, Giovanni Isella, Georgios Katsaros, Dominic T. Lennon, Vincent P. Michal, Erik M. Gauger, Natalia Ares
Materials Science
Comparative analysis of the lubrication performance of functionalized copolymers interacting with silicon, cobalt, and silver doped diamond-like carbon
Takeru Omiya, Enrico Pedretti, Pooja Sharma et al. (+5 more)
This study examines the tribological behavior of diamond-like carbon (DLC) coatings doped with silicon (Si), cobalt (Co), or silver (Ag) in the presence of an amine-functionalized block copolymer lubricant. Under boundary lubrication, Si-doped DLC (Si-DLC) exhibited the lowest coefficient of friction ($\approx$0.045) and nearly 45% lower wear than undoped DLC. Co-DLC showed moderate improvement, while Ag-DLC provided no significant benefit. Cross-sectional FIB-TEM revealed thin tribofilms, 12-17 nm in thickness, on Si- and Co-doped surfaces. As reported for Si-DLC, these films incorporate copolymer-derived fragments, suggesting a similar composition for Co-DLC. These results indicate that dopant-
polymer interactions are key to the development of self-organized boundary layers. To gain atomic-level insight, first-principles calculations were carried out on the adsorption of the dimethylaminoethyl methacrylate (DMAEMA) unit, the copolymer's functional group. The calculated adsorption energies were $-$2.27 to $-$0.57 eV for Si-DLC, $-$1.73 to $-$1.49 eV for Co(0001), and $-$1.21 to $-$1.08 eV for Ag(111). The order of stability (Si $>$ Co $>$ Ag) was consistent with the experimental tribological ranking. Chemical bonding dominated for Si-DLC, while Ag showed mainly weak physisorption. Simulated pull-off forces further reflected this hierarchy, with N-Si bonds requiring about twice the force of N-Co and nearly five times that of N-Ag. The correspondence between adsorption strength and tribological response highlights the decisive role of dopant species in tribofilm formation. These findings provide guidance for designing durable low-friction surfaces in applications such as electric drivetrains and precision mechanical systems.
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All authors Takeru Omiya, Enrico Pedretti, Pooja Sharma, Albano Cavaleiro, Arménio C. Serra, Jorge F. J. Coelho, Maria Clelia Righi, Fábio Ferreira
Mesoscale and Nanoscale Physics
Density-driven scattering and valley splitting in undoped Si/SiGe two-dimensional electron system
Lucky Donald Lyngdoh Kynshi, Umang Soni, Chithra H Sharma et al. (+7 more)
Undoped Si-SiGe two-dimensional electron gas (2DEG) provide an ideal platform for hosting
quantum-dot
spin-
qubits owing enhanced
spin dephasing times and compatibility with standard CMOS technology. The strained Si
quantum well reduces the valley degeneracy into two closely spaced ones. The existence of a near-degenerate valley state act as a leakage channel and compromises gate fidelity. A robust and uniform valley splitting across the entire chip is crucial for achieving scalability in the architecture and reliability in operation. Imperfections such as broadened interfaces,
alloy disorders and atomic steps significantly compromise the valley splitting. The associated scattering mechanisms play detrimental roles in the performance of the
qubits. In this manuscript, exploiting low-temperature magnetotransport measurements, we investigate the scattering mechanisms and valley splitting in a high-mobility undoped Si-SiGe 2DEG. At lower carrier densities, transport is limited by remote
impurity scattering, whereas at higher densities, background
impurity scattering near the
quantum well dominates. Both the transport and
quantum lifetimes of the charge carriers increase with carrier concentration, due to the enhancement in the
impurity screening.
Magnetic-field-induced confinement effect also is found to improve the valley splitting. Current-biasing measurements reveals the role of carrier heating in the visibility of valley splitting and reveal a temperature limited valley splitting of approximately 100 micro-eV. These results provide critical insight into scattering-dominated regimes and valley splitting in undoped Si-SiGe, advancing its potential for silicon-based
quantum devices.
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All authors Lucky Donald Lyngdoh Kynshi, Umang Soni, Chithra H Sharma, Yu Cheng, Kristian Deneke, Robert Zierold, Shengqiang Zhou, Robert H Blick, Anil Shaji, Madhu Thalakulam
Statistical Mechanics
Accelerated relaxation and Mpemba-like effect for operators in open quantum systems
Pitambar Bagui, Arijit Chatterjee and Bijay Kumar Agarwalla
Quantum Mpemba effect occurs when a
quantum system, residing far away from the steady state, relaxes faster than a relatively nearer state. We look for the presence of this highly counterintuitive effect in the relaxation dynamics of the operators within the open
quantum system setting. Since the operators evolve under a non-trace preserving map, the trace distance of an operator is not a monotonically decaying function of time, unlike its
quantum state counterpart. Consequently, the trace distance can not serve as a reliable measure for detecting the Mpemba effect in operator dynamics. We circumvent this problem by defining a dressed distance between operators that decays monotonically with time, enabling a generalized framework to explore the Mpemba-like effect for operators. Applying the formalism to various open
quantum system settings, we find that, interestingly, in the single
qubit case, only accelerated relaxation of operators is possible, while genuine Mpemba-like effects emerge in higher-dimensional systems such as qutrits and beyond. Furthermore, we demonstrate the existence of Mpemba-like effects in nonlocal, non-
equilibrium operators, such as current, in a double-
quantum-dot setup. Our results, besides offering fundamental insight about the occurrence of the Mpemba-like effect under non-trace preserving dynamics, open avenues for new experimental studies where quicker relaxation of observables could be of significant interest.
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Superconductivity
Enhanced Superconductivity in 2H-TaS2 Devices Through in-situ Molecular Intercalation
Jose M. Pereira, Daniel Tezze, Beatriz Martín-García et al. (+4 more)
The intercalation of guest species into the gap of van der Waals materials often leads to the emergence of intriguing phenomena, such as superconductivity. While intercalation-induced superconductivity has been reported in several bulk
crystals, reaching a zero-resistance state in flakes remains challenging. Here, we show a simple method for enhancing the superconducting transition in tens-of-nm thick 2H-TaS2
crystals contacted by gold electrodes through in-situ intercalation. Our approach enables measuring the electrical characteristics of the same flake before and after intercalation, permitting us to precisely identify the effect of the guest species on the TaS2 transport properties. We find that the intercalation of amylamine molecules into TaS2 flakes causes a suppression of the charge density wave and an increase in the superconducting transition, with an onset temperature above 3 K. Additionally, we show that a fully developed zero-resistance state can be achieved in flakes by engineering the conditions of the chemical intercalation. Our findings pave the way for the integration of chemically tailored intercalation compounds in scalable
quantum technologies.
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All authors Jose M. Pereira, Daniel Tezze, Beatriz Martín-García, Fèlix Casanova, Maider Ormaza, Luis E. Hueso, Marco Gobbi
Strongly Correlated Electrons
Equilibrium Spin Polarization Arising From Chirality
Pius M. Theiler and Matthew C. Beard
Chirality-induced
spin selectivity (CISS) describes how
chiral molecules and materials generate
spin polarization even at thermal
equilibrium. This observation has challenged established principles of microscopic reversibility and Onsager reciprocity. We resolve this paradox by formulating a pseudo-Hermitian
quantum framework in which structural chirality and electron correlations are sufficient to produce CISS observables. Chirality enters through a non-local metric that couples
spin and spatial motion, leading to real spectra,
unitary evolution, and thermodynamic consistency. The framework predicts a chirality-induced
spin magnetic ordering characterized by a
spin–displacement order $\langle \sigma \cdot x \rangle$, which reconciles
equilibrium spin polarization with detailed balance and explains the persistence of CISS in materials composed of light elements. We also derive generalized Onsager-Casimir relations that respect the observed parity ($\mathcal{P}$) and time-reversal ($\mathcal{T}$) breaking, while preserving combined $\mathcal{PT}$-
symmetry. This approach establishes a coherent foundation for
equilibrium CISS and provides a route to link chemical chirality with measurable
spin-to-charge conversion effects.
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Disordered Systems and Neural Networks · Cross-listed from stat.ML
Statistical physics of deep learning: Optimal learning of a multi-layer perceptron near interpolation
Jean Barbier, Francesco Camilli, Minh-Toan Nguyen et al. (+2 more)
For four decades statistical physics has been providing a framework to analyse neural networks. A long-standing question remained on its capacity to tackle deep learning models capturing rich feature learning effects, thus going beyond the narrow networks or kernel methods analysed until now. We positively answer through the study of the supervised learning of a multi-layer perceptron. Importantly, (i) its width scales as the input dimension, making it more prone to feature learning than ultra wide networks, and more expressive than narrow ones or ones with fixed
embedding layers; and (ii) we focus on the challenging interpolation regime where the number of trainable parameters and data are comparable, which forces the model to adapt to the task. We consider the matched teacher-student setting. Therefore, we provide the fundamental limits of learning random deep neural network targets and identify the sufficient statistics describing what is learnt by an optimally trained network as the data budget increases. A rich phenomenology emerges with various learning transitions. With enough data, optimal performance is attained through the model's "specialisation" towards the target, but it can be hard to reach for training
algorithms which get attracted by sub-optimal solutions predicted by the theory. Specialisation occurs inhomogeneously across layers, propagating from shallow towards deep ones, but also across
neurons in each layer. Furthermore, deeper targets are harder to learn. Despite its simplicity, the Bayes-optimal setting provides insights on how the depth, non-linearity and finite (proportional) width influence neural networks in the feature learning regime that are potentially relevant in much more general settings.
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All authors Jean Barbier, Francesco Camilli, Minh-Toan Nguyen, Mauro Pastore, Rudy Skerk
Materials Science
Tunable magnetism in 2D organic-ion-intercalated MnPS3 via molecule-dependent vacancy generation
Daniel Tezze, Jose M. Pereira, Dogukan Tutar et al. (+12 more)
The
magnetic properties of van der Waals materials are profoundly influenced by structural defects. The layered antiferromagnet MnPS3 offers a unique opportunity to explore defect-related magnetism, as Mn2+ vacancies can be generated by the intercalation of specific guest molecules. However, the effectiveness of this process in atomically thin flakes and the extent of the
magnetic tunability remain unclear. Here, we show that the
magnetic properties of MnPS3 can be tailored through the intercalation of different guest molecules. Notably, the insertion of four alkylammonium ions introduces different populations of Mn2+ vacancies, leading to a transition from the pristine
antiferromagnetic state to more complex
magnetic textures, including a ferrimagnetic state displaying a
magnetic saturation of 1 uB/atom. Moreover, we show that the intercalation of few-nm-thick flakes also leads to the emergence of a ferrimagnetic response. This in-flake intercalation, which can be monitored in real time using optical microscopy, can be interrupted before completion, generating lateral
heterostructures between pristine and intercalated areas. This approach opens the way to the use of partial intercalation to define regions with distinct
magnetic properties within a single flake.
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All authors Daniel Tezze, Jose M. Pereira, Dogukan Tutar, Maria Ramos, Jakub Regner, Pierluigi Gargiani, Frederik Schiller, Felix Casanova, Angel Alegria, Beatriz Martin-Garcia, Hasan Sahin, Zdenek Sofer, Maider Ormaza, Luis Hueso, Marco Gobbi
Disordered Systems and Neural Networks · Cross-listed from q-bio.PE
Learning to generalize in evolution through annealed population heterogeneity
Federica Ferretti, Mehran Kardar and Arvind Murugan
Evolutionary systems must learn to generalize, often extrapolating from a limited set of selective conditions to anticipate future environmental changes. The mechanisms enabling such generalization remain poorly understood, despite their importance to predict ecological robustness, drug resistance, or design future-proof vaccination strategies. Here, we demonstrate that annealed population heterogeneity, wherein distinct individuals in the population experience different instances of a complex environment over time, can act as a form of implicit regularization and facilitate evolutionary generalization. Mathematically, annealed heterogeneity introduces a variance-weighted demographic noise term that penalizes across-environment fitness variance and effectively rescales the population size, thereby biasing
evolution toward generalist solutions. This process is indeed analogous to a variant of the mini-batching strategy employed in
stochastic gradient descent, where an effective multiplicative noise produces an inductive bias by triggering noise-induced transitions. Through numerical simulations and theoretical analysis we discuss the conditions under which variation in how individuals experience environmental selection can naturally promote evolutionary strategies that generalize across environments and anticipate novel challenges.
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Soft Condensed Matter
Breaking Ion Clusters: Size Asymmetry for Faster Ion Transport in Polymer Electrolytes
Ganesh K Rajahmundry and Tarak K Patra
Solid
polymer electrolytes (SPEs) are ion-containing solid materials composed of a
polymer matrix that enables ionic transport while maintaining the mechanical stability. The conventional wisdom is that for a high ion concentration, ions microphase separate from the
polymer matrix, resulting in poor conductivity. Instead, we show that a high ion size ratio promotes better mixing of the ions with the
polymer matrix. Under these conditions, the ion-dipole moment interaction dominates over the ion-ion interaction and improves the ion dispersion in the
polymer matrix. The ion size ratio is thus a key to tailor the properties of these materials with immediate relevance to the development of SPEs for energy storage devices.
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Materials Science
Evolution of electronic and magnetic properties in Mn- and Co-alloyed ferromagnetic kagome metal Fe3Sn2
Prajwal M. Laxmeesha, Rajesh Dutta, Rajeev Kumar Rai et al. (+14 more)
Kagome metals are an intriguing class of
quantum materials as the presence of both flat bands and Dirac points provides access to functional properties present in strongly correlated and topological materials. To fully harness these electronic features, the ability to tune the
Fermi level relative to the band positions is needed. Here we explore the structural, electronic and
magnetic impacts of substitutional alloying within
ferromagnetic kagome metal Fe3Sn2 in thin films grown by molecular beam epitaxy. Transition metals Mn and Co are chosen as substitutes for Fe to reduce or increase the d-band electron count, thereby moving the
Fermi level accordingly. We find that Co is not incorporated into the Fe3Sn2 structure but instead results in a two-phase Fe-Co and (Fe,Co)Sn composite. In contrast, Fe3-xMnxSn2 films are realized with x up to 1.0, retaining crystalline quality comparable to the parent phase. The incorporation of Mn repositions the flat bands relative to the
Fermi level in a manner consistent with hole-doping, as revealed by hard x-ray photoemission and density functional theory. The Fe3-xMnxSn2 films retain room temperature ferromagnetism, with x-ray
magnetic circular dichroism measurements confirming that the Fe and Mn moments are ferromagnetically aligned. The ability to hole-dope this
magnetic kagome metal provides a platform for tuning properties such as anomalous
Hall and Nernst responses.
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All authors Prajwal M. Laxmeesha, Rajesh Dutta, Rajeev Kumar Rai, Sharup Sheikh, Michael F. DiScala, Uditha M. Jayathilake, Alexander Velič, Tarush Tandon, Tessa D. Tucker, Christoph Klewe, Haile Ambaye, Timothy Charlton, Tien-Lin Lee, Eric A. Stach, Kemp W. Plumb, Alexander X. Gray, Steven J. May
Strongly Correlated Electrons
Magnetic and phononic dynamics in the two-ladder quantum magnet (C5H9NH3)2CuBr4
J. Philippe, F. Elson, T. Arh et al. (+20 more)
In
quantum magnetic materials it is common to observe both static and dynamic
lattice effects on the
magnetic excitation spectrum. Less common is to find that the
magnetic correlations have a significant impact on the
phonon spectrum. Can such an interplay occur in a structurally soft system with comparable elastic and
magnetic energy scales? Here we study the metal-organic material (C5H9NH3)2CuBr4 (Cu-CPA), in which an explanation of the low-lying excitations depends crucially on a full understanding of both the
spin and
lattice subsystems. We report high-resolution
neutron spectroscopy enabled by large, deuterated single-
crystals that reveal how both sectors are affected by the recently discovered structural phase transition. By measuring over several Brillouin zones, we disentangle the vibrational contribution to the spectrum in order to obtain an accurate estimate of the quasi-one-dimensional
magnetic signal. The low-energy
magnetic excitations are dominated by two gaps, $\Delta$ b = 0.41 meV and $\Delta$ a = 0.55 meV, which contribute with equal intensity ratios, confirming that Cu-CPA realizes a two-ladder
spin Hamiltonian, and we deduce the
magnetic interaction parameters of both ladders. The
phonon spectrum contains a highly localized mode at an anomalously low-energy around 2 meV. This characteristic frequency drops by approximately 5 percent as
magnetic correlations become established with decreasing temperature, and we connect this behavior with the location and structure of the cyclopentylammonium rings.
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All authors J. Philippe, F. Elson, T. Arh, S. Sanz, M. Metzelaars, D. W. Tam, O. K. Forslund, O. Shliakhtun, C. Jiang, J. Lass, M. D. Le, J. Ollivier, P. Bouillot, T. Giamarchi, M. Bartkowiak, D. G. Mazzone, P. Kögerler, M. Månsson, A. M. Läuchli, Y. Sassa, M. Janoschek, B. Normand, G. Simutis
Quantum Gases
An efficient preconditioned conjugate-gradient solver for a two-component dipolar Bose-Einstein condensate
Weijing Bao, Zhenhao Wang, Jia-Rui Luo et al. (+1 more)
We develop a preconditioned nonlinear conjugate-gradient solver for ground states of binary dipolar Bose-Einstein condensates within the extended Gross-Pitaevskii equation including Lee-Huang-Yang corrections. The optimization is carried out on the product-of-spheres normalization
manifold and combines a
manifold-preserving analytic line search, derived from a second-order energy expansion and validated along the exact normalized path, with complementary
Fourier-space kinetic and real-space diagonal (Hessian-inspired) preconditioners. The method enforces monotonic energy descent and exhibits robust convergence across droplet, stripe, and supersolid regimes while retaining spectrally accurate discretizations and FFT-based evaluation of the dipolar term. In head-to-head
benchmarks against imaginary-time
evolution on matched grids and tolerances, the solver reduces iteration counts by one to two orders of magnitude and overall time-to-solution, and it typically attains slightly lower energies, indicating improved resilience to metastability. We reproduce representative textures and droplet-stability windows reported for dipolar mixtures. These results establish a reliable and efficient tool for large-scale parameter scans and phase-boundary mapping, and for quantitatively linking numerically obtained metastable branches to experimentally accessible states.
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All authors Weijing Bao, Zhenhao Wang, Jia-Rui Luo, Kui-Tian Xi
Soft Condensed Matter
Motile Escherichia coli-laden Droplets Exhibit Reduced Adhesion and Anomalous Wetting Behavior
Sirshendu Misra, Sudip Shyam, Priyam Chakraborty et al. (+1 more)
Hypothesis: Bacterial contamination of surfaces poses a major threat to public health. Designing effective antibacterial or self-cleaning surfaces requires understanding how bacteria-laden droplets interact with solid substrates and how readily they can be removed. We hypothesize that bacterial motility critically influences the early-stage surface interaction (i.e., surface adhesion) of bacteria-laden droplets, which cannot be captured by conventional contact angle goniometry. Experiments: Sessile droplets containing live and dead Escherichia coli (E. coli) were studied to probe their wetting and interfacial behavior. Contact angle goniometry was used to probe dynamic wetting, while a cantilever-deflection-based method was used to quantify adhesion. Internal flow dynamics were visualized using micro-particle image velocimetry (PIV) and analyzed statistically. Complementary sliding experiments on moderately wettable substrates were performed to assess contact line mobility under tilt. Findings: Despite lower surface tension, droplets containing live bacteria exhibited lower surface adhesion forces than their dead counterparts, with adhesion further decreasing at higher bacterial concentrations. Micro-PIV revealed that flagellated live E. coli actively resist evaporation-driven capillary flow via upstream migration, while at higher concentrations, collective dynamics emerge, producing spatially coherent bacterial motion despite temporal variability. These coordinated flows disrupt passive transport and promote depinning of the contact line, thereby reducing adhesion. Sliding experiments confirmed enhanced contact line mobility and frequent stick-slip motion in live droplets, even with lower receding contact angles and higher hysteresis. These findings provide mechanistic insight into droplet retention, informing the design of self-cleaning/antifouling surfaces.
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All authors Sirshendu Misra, Sudip Shyam, Priyam Chakraborty, Sushanta K. Mitra
Materials Science
Unsupervised Machine-Learning Pipeline for Data-Driven Defect Detection and Characterisation: Application to Displacement Cascades
Samuel Del Fré, Andrée de Backer, Christophe Domain et al. (+2 more)
Neutron irradiation produces, within a few picoseconds, displacement cascades that are sequences of atomic collisions generating point and extended defects which subsequently affects the long-term
evolution of materials. The diversity of these defects, characterized morphologically and statistically, defines what is called the "primary damage". In this work, we present a fully unsupervised machine learning (ML) workflow that detects and classifies these defects directly from molecular dynamics data. Local environments are encoded by the Smooth Overlap of Atomic Positions (SOAP) vector, anomalous atoms are isolated with autoencoder neural networks (AE), embedded with Uniform
Manifold Approximation and Projection (UMAP) and clustered using Hierarchical Density-Based Spatial Clustering of Applications with Noise (HDBSCAN). Applied to 80 keV displacement cascades in Ni, Fe$_7$0Ni$_{10}$Cr$_{20}$, and Zr, the AE successfully identify the small fraction of outlier atoms that participate in defect formation. HDBSCAN then partitions the UMAP latent space of AE-flagged SOAP descriptors into well defined groups representing vacancy- and interstitial-dominated regions and, within each, separates small from large aggregates, assigning 99.7 % of outliers to compact physical motifs. A signed cluster-identification score confirms this separation, and cluster size scales with net defect counts (R2 > 0.89). Statistical cross analyses between the ML outlier map and several conventional detectors (centrosymmetry, dislocation extraction, etc.) reveal strong overlap and complementary coverage, all achieved without template or threshold tuning. This ML workflow thus provides an efficient tool for the quantitative mapping of structural anomalies in materials, particularly those arising from irradiation damage in displacement cascades.
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All authors Samuel Del Fré, Andrée de Backer, Christophe Domain, Ludovic Thuinet, Charlotte S. Becquart
Statistical Mechanics
Dynamical typicality in classical lattice systems
Nicolas Nessi and Peter Reimann
Considering deterministic classical
lattice systems with continuous dynamical variables, we show that, if the initial conditions are sampled according to a probability distribution in which the dynamical variables are statistically independent, the temporal
evolution of any macroscopic observable is approximately the same for the vast majority of the randomly sampled initial states. Our proof relies on general concentration of measure results which provide tight bounds for the deviation from typical behavior in the case of large system sizes. The only requirement on the dynamics is that the influence of a local perturbation in the initial state decays, at any given instance of time, sufficiently fast with distance. Our results are relevant, in particular, to classical
Hamiltonian systems on a
lattice, but also apply to a large class of dissipative dynamics. We illustrate our general results with two analytical examples, a coupled map
lattice and a
Hamiltonian system of coupled rotors with long-range interactions.
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Strongly Correlated Electrons
Crossover from self-trapped bound states to perturbative scattering in the Heisenberg-Kondo lattice model
Tanmoy Mondal and Pinaki Majumdar
We map out the complete transport phase diagram of the
ferromagnetic Heisenberg-Kondo
lattice model in two dimensions. The model involves tight-binding electrons with hopping $t$, coupled to classical
spins with coupling $J'$, while the
spins have a nearest neighbour coupling $J$ between them. We work with a fixed, small $J/t$, and study the temperature dependence of resistivity for varying electron density $n$ and coupling $J'/t$. Our
magnetic configurations are generated by exact diagonalisation-based Langevin dynamics, while the conductivity is computed using the Kubo formula on exact eigenstates. We work on
lattices of size $20 \times 20$ and can access electron density down to $n \sim 0.01$. The electron system remains homogeneous either when the mean density is large or when the coupling $J'$ is small. In these situations, the resistivity $\rho(T)$ displays a monotonic increase with temperature and can be understood within a perturbative framework. However, at very low density $n \lesssim 0.05$, strong coupling $J'/t \gtrsim 1$, and for $T \sim T_c$, the electrons can locally polarise the
magnetic state, create a trapping potential, and form a bound state in it. The resistivity associated with this polaronic phase is distinctly non-monotonic, with a peak near $T_c$. We establish the boundary that separates the many-body polaronic window from traditional scattering and extract a universal form for the resistivity in the scattering regime. We suggest the origin of the `excess resistivity' in the polaronic regime in terms of an increasing fraction of localised states as the temperature tends to $T_c$. This pushes the mobility edge towards the chemical potential $\mu$ and results in enhanced scattering of momentum states near $k_F$. While our specific results are in two dimensions, the phenomenology we uncover should be valid even in three dimensions.
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Materials Science
Strain Engineering of van Hove Singularity and Coupled Itinerant Ferromagnetism in Quasi-2D Oxide Superlattices
Seung Gyo Jeong, Minjae Kim, Jin Young Oh et al. (+12 more)
Engineering van Hove singularities (vHss) near the
Fermi level, if feasible, offers a powerful route to control exotic
quantum phases in electronic and
magnetic behaviors. However, conventional approaches, which rely primarily on chemical and electrical doping, focus mainly on local electrical or optical measurements, limiting their applicability to coupled functionalities. In this study, a vHs-induced
insulator-metal transition coupled with a
ferromagnetic phase transition was empirically achieved in atomically designed quasi-2D SrRuO3 (SRO) superlattices via epitaxial strain engineering, which has not been observed in conventional 3D SRO systems. Theoretical calculations revealed that epitaxial strain effectively modulates the strength and energy positions of vHs of specific Ru orbitals, driving correlated phase transitions in the electronic and
magnetic ground states. X-ray absorption spectroscopy confirmed the anisotropic electronic structure of quasi-2D SRO modulated by epitaxial strain. Magneto-optic Kerr effect and electrical transport measurements demonstrated modulated
magnetic and electronic phases. Furthermore, magneto-electrical measurements detected significant anomalous
Hall effect signals and
ferromagnetic magnetoresistance, indicating the presence of magnetically coupled charge carriers in the 2D metallic regime. This study establishes strain engineering as a promising platform for tuning vHss and resultant itinerant ferromagnetism of low-dimensional correlated
quantum systems.
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All authors Seung Gyo Jeong, Minjae Kim, Jin Young Oh, Youngeun Ham, In Hyeok Choi, Seong Won Cho, Jihyun Kim, Huimin Jeong, Byungmin Sohn, Tuson Park, Suyoun Lee, Jong Seok Lee, Deok-Yong Cho, Bongjae Kim, Woo Seok Choi
Disordered Systems and Neural Networks
Deep-Learning-Empowered Programmable Topolectrical Circuits
Hao Jia, Shanglin Yang, Jiajun He et al. (+9 more)
Topolectrical
circuits provide a versatile platform for exploring and simulating modern physical models. However, existing approaches suffer from incomplete programmability and ineffective feature prediction and control mechanisms, hindering the investigation of physical phenomena on an integrated platform and limiting their translation into practical applications. Here, we present a deep learning empowered programmable topolectrical
circuits (DLPTCs) platform for physical modeling and analysis. By integrating fully independent, continuous tuning of both on site and off site terms of the
lattice Hamiltonian, physics graph informed inverse state design, and immediate hardware verification, our system bridges the gap between theoretical modeling and practical realization. Through flexible control and adiabatic path engineering, we experimentally observe the boundary states without global
symmetry in higher order topological systems, their adiabatic phase transitions, and the flat band like characteristic corresponding to Landau levels in the
circuit. Incorporating a physics graph informed mechanism with a generative AI model for physics exploration, we realize arbitrary, position controllable on board Anderson localization, surpassing conventional random localization. Utilizing this unique capability with high fidelity hardware implementation, we further demonstrate a compelling cryptographic application: hash based probabilistic information encryption by leveraging Anderson localization with extensive disorder configurations, enabling secure delivery of full ASCII messages.
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All authors Hao Jia, Shanglin Yang, Jiajun He, Shuo Liu, Haoxiang Chen, Ce Shang, Shaojie Ma, Peng Han, Ching Hua Lee, Zhen Gao, Yun Lai, Tie Jun Cui