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Solving Optimization Problems Using Near Term Quantum Devices
DescriptionOptimization problems are among the most promising quantum applications that combine the use of quantum processor and classical processors. This tutorial is aimed at teaching the participants to solve optimization problems using two distinct quantum computing paradigms: (i) hybrid quantum-classical algorithms using gate-based systems, and (ii) neutral atom analog Hamiltonian simulations device. In gate-based systems, a parameterized quantum circuit is designed which is then used to compute value of an objective function and iteratively optimize via classical optimization algorithms. Such hybrid algorithms rely on rapid iterative computations of quantum and classical processors, requiring regular sharing of data between them. The analog Hamiltonian simulation quantum device comprises of an array of two-level neutral Rydberg atoms with ground state and excited Rydberg state. The atoms can be arranged in any 1D or 2D geometry and initially prepared in the ground state. The parameters of the driving Hamiltonian are then adiabatically varied and the state of each neutral atom is measured which represents the final solution. The tutorial will provide introduction to quantum computing and demonstrate the aforementioned solutions using hand-on sessions provided via free cloud access to quantum hardware.
Event Type
Tutorial
TimeMonday, 13 November 20238:30am - 12pm MST
Location303
Algorithms
Quantum Computing
TUT