Quantum computing has attracted intense interest due to its potential to tackle challenging problems that are difficult or impossible for traditional computing to handle. In quantum computing, the number of variables increases exponentially with the number of particles in the system. Stabilizer states are an important class of quantum states for efficient quantum computing. Previously, a linear combination of density-matrix terms is used for stabilizer-based simulation. The prior algorithm, however, takes too much calculation resources, less efficient and not compatible with parallel computing. Therefore, a new algorithm is needed for more efficient quantum simulation based on stabilizer states.
Novel Algorithms for Efficient Stabilizer-based Computation
Researchers at the University of Michigan have developed novel algorithms, which compute key steps in a novel technique for representing and simulating quantum states on digital computers, for quantum simulation based on stabilizer states. So far no existing algorithms can perform the same type of computation. The new algorithms allow a more compact computing and reduces resource requirement. In addition, with new algorithms, stabilizer states can be computed in parallel and lend themselves to distributed processing.
- quantum chemistry (medical and pharmaceutical applications)
- quantum physics
- energy modeling and simulation
- quantum circuit and algorithm design
- engineering of quantum computers
- More compact, reduce computation resource requirement
- Compatible with parallel computation