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 4
On the Statistical Mechanics of Attention
We revisit the statistical mechanics of Transformer attention via modern Hopfield models.Ergodicity breaking transition beyond qubits
The local Hilbert space dimension is a fundamental parameter in quantum many-body systems, but its role in controlling the ergodicity-breaking transition remains less explored.Eigenstate transitions and critical transport in 3D Aubry-André model
We numerically study spectral and wave-function properties, as well as time evolution, in finite-size commensurate approximations of the 3D Aubry-André model.Quantum Localization in Geometric Complex Networks
Quantum localization, the phenomenon by which wave diffusion is halted, here understood as the superposition of propagating waves, can have many different origins, such as onsite random potentials…The Rényi area law conjecture is false below $α=1$ in high dimensions
Area laws express the expectation that entanglement in gapped quantum ground states scales with a boundary rather than a volume.Percolation of Data Constraints and Reorganization of Boolean Function States in Parity Learning
We study how a neural network reorganizes its learned function as training proceeds and as previously unseen parity data accumulate.Some remarks on the connection between generative diffusion and optimal transport
We discuss three simple connections between generative diffusion and optimal transport.Encoding Matters: A Qubit-Efficient Reformulation for Quantum Resilient Routing
Qubits are powerful computational resources because each additional qubit doubles the size of the accessible state space.On physical implementability of reinforcement-learning-driven reasoning
In the machine learning community, the reinforcement-learning-driven reasoning process has been intensively studied since around 2025.Quantum annealing of the random transverse-field Ising model in one, two, and three dimensions
Quantum annealing must be sufficiently slow to prevent defect formation.Ecology of AI Agents: Collaboration Creates a Population Threshold for Takeoff
AI agents can now conduct real-world cyberattacks, scale up capabilities with the number of agents, and collectively pursue misaligned goals to obtain rewards.Structure alone supports efficient visual computation in the Drosophila visual system
Understanding the extent to which measured synaptic wiring determines computation remains a central challenge.Matching of signal, noise and hardware timescales for filtering and forecasting of correlated noise signals
Physical reservoir computing exploits the nonlinear dynamics of physical systems to process time-dependent data with greater energy efficiency than conventional machine learning approaches.Asymptotic Analysis of Empirical Risk Minimization on Entry-wise i.i.d. Heavy-Tailed Data
Many real-world datasets exhibit unusually large values far more frequently than predicted by Gaussian models.Classifications in modular restricted Boltzmann machines
We consider a modular associative neural network made of $L$ Hopfield models (HMs), coupled so that intra-module interactions are Hebbian and inter-module interactions are anti-Hebbian; this…Observing the magic Mpemba effect in localized dynamics on a digital quantum computer
The Mpemba effect challenges the intuition that states closer to equilibrium must relax faster.The Dichotomy Between Pattern Recognition and Step-by-Step Reasoning
We argue that pattern recognition and step-by-step reasoning are two ends of a spectrum.Fast mixing of the SYK model at high temperatures
The Sachdev-Ye-Kitaev (SYK) model is a strongly interacting fermionic system.A Solvable Model of Adaptive Learning Rate Rescaling: Acceleration, Stability & Scaling
A recurring design principle in modern optimizers is to decouple update magnitude from the raw gradient norm, yet its consequences for learning-curve and resource scaling remain unclear.Polynomial-time classical algorithms for mean-field models up to the glass transition
The Sachdev-Ye-Kitaev model is a strongly interacting fermionic system that has been well-studied in condensed matter and high energy physics.