2818 papers
Explore the fascinating intersection where quantum materials meet the complexity of everyday environments in the Cond-Mat — Mes-Hall section. This field investigates how tiny particles behave when caught between the orderly world of single atoms and the chaotic nature of bulk matter, revealing the hidden rules that govern electricity, magnetism, and heat in novel substances.
Gist.Science brings these cutting-edge discoveries to you directly from arXiv, the leading repository for physics preprints. We process every new submission in this category as soon as it appears, offering both straightforward, plain-language explanations and deep technical summaries to help researchers and curious minds alike grasp the latest breakthroughs without getting lost in dense equations.
Below are the most recent papers in this dynamic area of condensed matter physics, ready for you to explore.
Using time- and angle-resolved photoemission spectroscopy on EuCdAs, the study demonstrates that under high optical photo-doping, bulk plasmons can drive non-equilibrium energy transfer from bulk to surface states to stabilize a long-lived Mahan exciton, revealing a regime where collective modes mediate rather than merely dissipate correlated electronic states.
This paper introduces a unified geometric framework based on a generalized time-dependent quantum geometric tensor to derive compact expressions, sum rules, and fundamental bounds for optical, thermoelectric, and thermal transport in clean band insulators, revealing that geometry-driven effects persist even in topologically trivial systems.
This paper resolves the apparent contradiction between Kubo linear response predictions of odd elastic moduli in Hamiltonian systems and energy conservation by demonstrating that the geometry of strain perturbations introduces contact term corrections that reconcile quantum linear response with classical elasticity theory.
This paper proposes a statistical model integrating deep learning techniques, including convolutional and physics-informed neural networks, to predict the dynamic and static properties of magnetic materials with defects, thereby facilitating the discovery of new materials and the determination of minimal defect thresholds for desired magnetic states.
This paper identifies extrinsic population dynamics as the fundamental cause of discrepancies between theoretical and experimental lifetime estimates in multilevel systems, proposing a revised readout protocol and an integrated theory that successfully explains recent spin-valley measurements in bilayer graphene.
This paper introduces topological heavy-tailed networks by constructing a tight-binding model for the Apollonian network with nontrivial gauge fields to reveal the "Apollonian butterfly" spectrum, demonstrating how spectral localizers characterize its topological features as being governed by lower-degree nodes and bridging topological physics with network science for wave control.
This paper introduces a gauge transformation that eliminates time-dependent onsite potentials by renormalizing hopping terms with phase factors, thereby simplifying time-ordered integrals and facilitating the simulation of pulse propagation in scattering systems.
This paper demonstrates that atomic force nanolithography can precisely engineer tunable in-plane uniaxial magnetic anisotropy in permalloy films by creating nanoscale groove arrays, enabling controlled domain manipulation for applications in magnonic elements and anisotropic magnetoresistance sensors.
This study employs self-consistent Hartree-Fock calculations to demonstrate that proximity-induced spin-orbit coupling from a transition-metal dichalcogenide layer critically tunes the spin nature and symmetry-breaking patterns of correlated ground states in twisted mono-bilayer graphene, driving transitions between various magnetic orders and inducing chiral non-coplanar states depending on the specific type and combination of Rashba and Ising coupling.
This paper presents a computationally efficient microscopic screening theory for excitons in two-dimensional materials that bridges the gap between effective models and first-principles methods by employing an atomistic description with quantum-screened interactions to accurately estimate binding energies and address discrepancies in existing literature.