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cs.LG2026
Sample-efficient learning with Dense Associative Memories
Andrew Lucas, Dmitry Krotov
We analytically study the evolution of the energy function of Dense Associative Memories (DenseAMs) as they train on randomly sampled codewords of random expander low-density parit…
quant-ph2026
Preparing approximate -fold cat states with the phase space instruction set
Shuyan Zhou, Andrew Lucas
The phase space instruction set is a continuous-variable universal gate set involving single-qubit rotations and qubit-dependent displacements on a single boson. Using these gates,…
math-ph2026
Robust symmetry breaking in gapless quantum magnets
Chao Yin, Andrew Lucas
We prove the existence of spontaneous symmetry breaking in suitably low-energy eigenstates of certain gapless and frustrated many-body quantum systems, namely symmetric quantum per…