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.

In January, Azure Quantum and Pacific Northwest National Laboratory (PNNL) researchers shared how HPC and AI were used to accelerate the scientific discovery of new energy storage solutions. Together, the teams discovered and synthesized a new electrolyte material candidate that showed potential for resource-efficient batteries. In less than nine months, the team built a battery proof of concept with the new electrolyte, which uses 70% less lithium than electrolytes in existing lithium-ion batteries.