Exploring Quantum Disorder with Multi-GPU Computing plus AI Expansion
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Quantum disordered systems, like quantum spin glasses with frustrated energy landscapes, present a complex challenge in condensed matter physics with implications for quantum computing. Numerically probing these systems requires significant computational resources to overcome finite size limitations. To address this, highly optimized GPU-based computational tools have been developed, employing both Monte Carlo simulations for large-scale statistical analysis and transfer matrix formalism for exact analysis of smaller systems. The synergy between these GPU-accelerated approaches allows for cross-validation and deeper understanding, advancing the exploration of quantum disorder and its technological potential.