600 papers
This category explores the fascinating intersection where disorder meets quantum mechanics, specifically looking at how electrons behave when they get stuck in messy, irregular materials. Instead of the smooth flow found in perfect crystals, researchers here study systems where randomness creates surprising new states of matter, often leading to phenomena like insulation in materials that should conduct electricity. These studies help us understand the fundamental limits of quantum transport in real-world, imperfect environments.
Gist.Science processes every new preprint in this field as it appears on arXiv, ensuring you have immediate access to the latest breakthroughs. For each paper, we provide both a plain-language explanation to make the core ideas accessible and a detailed technical summary for those who need the full mathematical depth. Below are the latest papers in this specialized area of condensed matter physics, curated and summarized for your review.
This study reveals that a highly disordered fractal MgO/MgB2 nanocomposite achieves robust global phase coherence and bulk-like superconductivity through atomically clean interfaces and oxygen vacancy channels that facilitate long-range carrier transfer, despite a low MgB2 volume fraction.
This paper demonstrates that Transformer models can successfully learn and predict sequences from complex Permuted Congruential Generators (PCGs) through curriculum learning and by discovering bitwise rotationally-invariant representations, revealing a scaling law where the required context length grows as the square root of the modulus.
This paper establishes that preparing near-optimal ground states for random quantum -spin glasses requires circuits with depth growing logarithmically with system size or exceeding any fixed depth, thereby demonstrating that shallow circuits cannot generate the necessary entanglement to close the energy gap between product states and the optimum.
This paper derives a closed-form analytical expression for the full distribution of eccentricities in random regular graphs, revealing non-trivial variations in node eccentricities despite uniform degrees and providing precise formulas for the mean, mode, and variance that serve as benchmarks for analyzing large sparse networks.
This paper establishes a symmetry-guided, mechanism-resolved framework that identifies and quantitatively distinguishes 20 distinct mechanisms of third-order nonlinear transport in disordered materials by combining magnetic point group analysis with characteristic scaling laws between nonlinear and linear conductivities.
This paper numerically verifies that the Brownian Castle interface growth model belongs to a new universality class characterized by modified Family-Vicsek scaling with specific growth and roughness exponents, alongside non-Gaussian height distributions and Cauchy-Lorentz distributed height changes.
This study demonstrates that adding dilute flexible polymers to fluids flowing through porous media induces elastic instabilities that generate turbulent-like chaotic fluctuations, thereby significantly enhancing mixing efficiency and accelerating chemical reaction rates by stretching and folding solute lamellae within the pores.
This paper introduces Oscillatory Active Brownian Motion (OABM), a minimal theoretical model that extends standard active Brownian motion by incorporating periodic angular drives to accurately describe and predict the transport dynamics and motility characteristics of sperm cells across different physiological states.
This paper investigates the application of score-based and energy-based diffusion models to learn and characterize the probability distributions sampled by complex Langevin dynamics, aiming to address the challenges of understanding stochastic processes in theories with sign problems.
By combining experiments, simulations, and random-matrix theory, this study reveals that while the distribution of wavefront shaping enhancement factors aligns with theoretical predictions in weakly scattering media, strongly scattering systems exhibit giant fluctuations that serve as a sensitive probe for long-range mesoscopic correlations.