Quantum algorithms are emerging tools in the design of functional materials due to their powerful solution space search capability. How to balance the high price of quantum computing resources and the growing c
Quantum-inspired algorithms can simulate turbulent fluid flows on a classical computer much faster than existing tools, slashing computation times from several days on a large supercomputer to just hours on a regular laptop. This could improveweather forecastsand increase the efficiency of industrial pro...
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More significantly, we achieve these improvements by arguing that the previous quantum-inspired algorithms for these problems are doing leverage or ridge-leverage score sampling in disguise; these are powerful and standard techniques in randomized numerical linear algebra. With this recognition, we are...
Recently, the Hamiltonian formalism has been successfully used in the development of heuristic (quantum-inspired) algorithms for solving NP-hard optimization problems, where specific (Ising-like) quantum Hamiltonians are mapped onto relevant objective functions to be minimized20. In this regard, our ...
Recently, the work of combining quantum computing and evolutionary computing has stimulated the studies of quantum-inspired evolutionary algorithms and their applications. The most important work to classical computer was done by Han and Kim (2002). They proposed a quantum-inspired evolutionary algorithm...
The proposed QIGA contains a series of enhancements compared to conventional genetic algorithms (GAs) and can be considered as a better alternative when solving problems with a complex solution space. The QIGA is applied to a synthetic network, a subnetwork of a real-world road network, and a ...
used for quantitative evaluation of the proposed algorithms. The effectiveness and efficiency of the proposed quantum inspired algorithms have been established over their conventional counterparts and the three other competitive algorithms with regards to optimal computational time, convergence rate and ...
With this QUBO formulation, we are able to run the genome assembly task using quantum annealers and quantum-inspired algorithms. We note that the applicability of the method requires the existence of the Hamiltonian path in the corresponding graph, which is not universally the case for arbitrary ...
3,4, aiming at becoming more powerful than classical algorithms such as simulated annealing (SA)5,6. To use the current D-Wave’s QA device, a combinatorial optimization problem must be mapped to a quadratic unconstrained binary optimization (QUBO) problem. QUBO is an optimization problem of ...