Hybrid quantum computing architecture for solving quadratic unconstrained binary optimization problem

Abstract

The present disclosure relates to a method of driving a quantum computing network, the method for determining an extremum of a cost function of a solution to a quadratic unconstrained binary optimization problem, the method comprising: initializing a quantum bit; quantum gate layers are sequentially applied to the qubits, each layer comprising a multi-qubit quantum gate acting on a plurality of qubits and a plurality of variable component sub-gates having two feature values and a variable effect on the qubits, the variability of the variability sub-gate of the quantum gate layer forms a variability parameter set; and determining an output state of the quantum computing network to obtain a solution associated with the set of variational parameters, where each binary variable of the quadratic unconstrained binary optimization problem is associated with a computing ground state of the register qubit, and the solution is obtained by evaluating a probability of measuring a calculation ground state corresponding to the binary variable, and wherein the solution is iteratively improved by determining an output state of the altered variational parameter to evaluate a partial derivative with respect to a subset of the variational parameter, thereby determining a gradient of the cost function based on an output state of the altered variational parameter; and updating the variational parameter based on an update function of a moving average over a gradient of the cost function and a moving average over a square gradient of the cost function.

Description

technical field [0001] The invention belongs to the field of quantum computing. More precisely, the invention relates to a quantum computing architecture for finding solutions to discrete optimization problems. Background technique [0002] Quantum computers provide a platform for controllable quantum mechanical systems whose states and interactions can be controlled to perform computations. Computation is achieved through the deterministic evolution of a controllable quantum mechanical system, and the state of the quantum mechanical system can be measured to determine the outcome of the calculation. [0003] Quantum computers typically encode information in so-called qubits, which act as the quantum mechanical equivalent of classical bits. A qubit is a physical system whose quantum mechanical state can be (coherently) controlled during computation time and held (essentially) between two ground states, referred to below as |0> and |1>. As an example, a qubit can be ...

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Problems solved by technology

[0006] However, superposition / entangled states of quantum mechanical systems are inherently unstable (e.g., subject to decoherence) and control and measurement of these systems are subject to fidelity margins, such that state-of-the-art quantum computers are currently in controllable Quantum mechanical systems are limited in the number of systems (qubits) and in the number of control actions (quantum gates) that can be performed in succession

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