arXiv:2602.04943v3 Announce Type: replace-cross
Abstract: We study the computational complexity of learning the ground state phase structure of Heisenberg antiferromagnets. Representing Hilbert space as a weighted graph, the variational energy defines a weighted XY model that, for $mathbbZ_2$ phases, reduces to a classical antiferromagnetic Ising model on that graph. For fixed amplitudes, reconstructing the signs of the ground state wavefunction thus reduces to a weighted Max-Cut instance. This establishes that ground state phase reconstruction for Heisenberg antiferromagnets is worst-case NP-hard and links the task to combinatorial optimization.
Measuring and reducing surgical staff stress in a realistic operating room setting using EDA monitoring and smart hearing protection
BackgroundStress is a critical factor in the operating room (OR) and affects both the performance and well-being of surgical staff. Measuring and mitigating this stress


