Conveners
Quantum Enhanced Optimization I
- Juan Atalaya-Chavez (UC Berkeley)
Prof.
Hidetoshi Nishimori
(Tokyo Institute of Technology)
27/01/2019, 09:30
Quantum enhanced optimization
After an introduction and an overview of quantum annealing, I describe recent developments in non-traditional protocols to control quantum effects for enhanced performance: (i) non-stoquastic drivers [1], (ii) spatially inhomogeneous driving of the field [2], and (iii) reverse annealing [3]. I will show explicit examples in which first-order quantum phase transitions can be avoided by these...
Dr
Shunji Matsuura
(1QBit)
27/01/2019, 10:15
Quantum enhanced optimization
While quantum algorithms are believed to be more powerful than classical algorithms, the computational power of near term quantum devices is highly
restricted because of noise.
In order to overcome the limitations and exploit quantum advantages on noisy quantum devices, it is important to develop algorithms which complete each run of quantum computation within a short coherence...
Dr
Arjun Gambhir
(Lawrence Livermore National Laboratory)
27/01/2019, 10:45
Quantum enhanced optimization
Numerous fields require numerically solving a system of linear equations. For equations stemming from large, sparse matrices, this is classically done with iterative methods and judicious preconditioning. Convergence of such algorithms can be highly variable and depends in part, on the condition number of the matrix. With the arrival of quantum computing in the Noisy Intermediate-Scale Quantum...
