Condensed Matter · Physics & Astronomy
Disordered Systems & Neural Networks
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135 papers, from 4 September 2026 to 5 November 2026: 135 arXiv preprints.
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Newest papers, page 5
Determining the Number of Symmetry Sectors in Composite Quantum Spectra
The spectral fluctuations in complex quantum systems are modeled in terms of spectra from random matrices.Probabilistic Algorithms for Ising Machines from Optimization to Generative AI
Ising machines have emerged as promising hardware accelerators for intractable optimization and sampling problems, yet their practical impact increasingly hinges on the co-design of algorithms and…EP-Flow: Disordered Crystal Structure Prediction without Site-Level Annotations
Generative models have made rapid progress in ordered crystal structure prediction, yet many functional materials are intrinsically disordered, with substitutional mixing, vacancies, or interstitial…The hidden advantage of mask resampling: a theory of masked autoencoders
Why can masked prediction learn useful representations that unmasked reconstruction misses?In-context Learning of Single-index Targets: Comparing Kernel and Feature Learners
In-context learning (ICL) enables a pretrained model to infer a task from demonstrations without updating its parameters.Beyond Light Cones: State Preparation Complexity in Quantum Spin Glasses
We introduce a method for studying state preparation complexity in dense quantum $p$-spin Hamiltonians on $n$ qubits, going beyond bounds based only on circuit lightcones.Quantum transmission in 1D disordered stealthy hyperuniform Kronig--Penney-like models
Disordered stealthy hyperuniform (SHU) systems are emerging as platforms for controlling classical and quantum transport due to vanishing single-scattering contributions in the stealthy regime.Quantum-echo Markov process for combinatorial optimization
We introduce a quantum-echo Markov process for combinatorial optimization.Eigenstate thermalization at the edge of the many-body spectrum
It is well-known that thermalization breaks down in presence of an extensive number of symmetries or conservation laws that are mutually compatible or commuting with each other.Chiral quantum chaos around exponentially many zero modes in the quantum breakdown model
The quantum breakdown model is a model of randomly interacting fermions, motivated by the physics of dielectric breakdown.Gibbs Sampling in the Shattered Phase by Decoded Quantum Interferometry
We apply Decoded Quantum Interferometry (DQI) to sample from the Gibbs measures of classical Ising spin Hamiltonians.Walshness: an intrinsic neural-network representability metric for quantum states
Neural quantum states (NQS) have emerged as powerful representations of quantum states with rapidly expanding applications across quantum many-body physics.Quantum Simulation of Detuning-Controlled Proximity-Induced Localization and Reentrant Delocalization in a Quasiperiodic Ladder
We demonstrate proximity-induced localization and re-entrant delocalization in a detuned quasiperiodic ladder.Local autonomous inference machines for quantum LDPC codes
We introduce a local and distributed framework for decoding quantum LDPC codes.Breakdown of Local Denoising as Semantic Speciation
The dynamics of generative models exhibit two apparently distinct temporal windows: a speciation window, in which a sample commits to a semantic class, and a nonlocality window, in which local…Native implementation of the machine-learned Skala exchange-correlation functional in CP2K: Unified one-centre reconstruction for molecular and condensed-phase calculations
We implement the machine-learned Skala exchange-correlation (XC) functional natively in CP2K using its Gaussian and plane-wave (GPW) and Gaussian and augmented-plane-wave (GAPW) methods.Evolution of fairness in multi-objective reinforcement learning framework
Fairness, as a fundamental social norm, continues to pose a longstanding puzzle regarding its emergence.Pre-registered tests of solid-state-physics-inspired LLM compression: a cluster-level negative result at small-language-model scale
We report a three-month autonomous research-agent program testing five solid-state-physics-inspired compression mappings on pretrained language models, with predictions committed to git before any…Exact probability distributions of complex spacing ratios in non-Hermitian random matrices
The complex spacing ratio is the complex displacement from a reference eigenvalue to its nearest neighbor divided by the corresponding displacement to its next-to-nearest neighbor.Weighting Schedules Govern What and When Score-Based Generative Models Learn from Multimodal Data
Score-based generative models generate new samples by integrating a time-dependent drift that carries Gaussian noise onto the target distribution.