  We introduce universal, easy-to-reproduce generative models for the QUBO
instances to differentiate the performance of the hardware/solvers effectively.
Our benchmark process extends the well-known Hebb's rule of associative memory
with the asymmetric pattern weights. We provide a comprehensive overview of
calculations conducted across various scales and using different classes of
dynamical equations. Our aim is to analyze their results, including factors
such as the probability of encountering the ground state, planted state,
spurious state, or states falling outside the predetermined energy range.
Moreover, the generated problems show additional properties, such as the
easy-hard-easy complexity transition and complicated cluster structures of
planted solutions. Our method establishes a prospective platform to potentially
address other questions related to the fundamental principles behind device
physics and algorithms for novel computing machines.
