Classiq recently announced a collaboration with NVIDIA and the BMW Group in the field of quantum computing applications to optimize mechatronic systems. It aims to use advanced quantum algorithms such as QAOA and HHL to solve complex computational challenges and design electrical and mechanical systems with optimal architectures. The goal of the collaboration is to enhance efficiency and reduce energy waste, which can result – among other things – in the increased efficiency of electric vehicles.

Researchers at JPMorgan Chase, Argonne National Laboratory, and Quantinuum have collaborated to demonstrate clear evidence of quantum speedup in the Quantum Approximate Optimization Algorithm (QAOA). By applying the QAOA algorithm to the Low Autocorrelation Binary Sequence (LABS) problem, the research team found that the time required to solve increasingly larger problems using this algorithm grows slower than that of classical solvers. Furthermore, they also demonstrated a small-scale implementation of Quantinuum’s System Model H1 and H2 trapped-ion quantum computers.