Hybrid Quantum-Classical Computing Noise Reduction
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Solution Overview
Problem
Current quantum computers with Josephson junctions suffer from imperfect control of qubits, leading to noise and limited scalability due to the accumulation of errors in quantum gate operations, especially when solving optimization problems that require a large number of gate operations.
Innovation Solution
A hybrid quantum-classical computing system is employed, where a classical computer computes a model Hamiltonian and sets a quantum processor with trapped ions to transform states using a reduced trial state preparation circuit, measuring expectation values and adjusting variational parameters to minimize error, thereby reducing the number of quantum gate operations and noise.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If the number of quantum gate operations is increased to solve larger optimization problems, then the problem-solving capability is improved, but the error accumulation and noise increase, reducing computation reliability
Solution Approach 1:
The patent divides the quantum computation process into distinct segments: a quantum subroutine executed on the NISQ device and a classical optimization routine executed on the classical computer. This segmentation allows the quantum processor to perform only essential quantum operations while delegating iterative optimization to the classical system, thereby reducing the number of sequential quantum gate operations and minimizing error accumulation.
Solution Approach 2:
The patent introduces a hybrid quantum-classical computing system where the classical computer acts as an intermediary between problem definition and quantum execution. The classical optimizer prepares input states, executes the quantum subroutine, processes measurement outcomes, and iteratively refines parameters, reducing the computational burden on the noisy quantum processor and enabling solution of larger problems with controlled error rates.
2Quantity of substance
If more qubits are added to increase the scale of quantum computer, then the capacity to handle complex problems is improved, but the control precision deteriorates due to increased noise and imperfect qubit control
Solution Approach 1:
The patent employs a variational approach where the quantum processor itself provides feedback about its performance through measurement of expectation values. The classical optimizer uses this feedback to automatically adjust variational parameters, creating a self-correcting system that adapts to the actual performance characteristics of the noisy quantum hardware, thereby maintaining effective computation despite imperfect qubit control.
Solution Approach 2:
The patent utilizes variable parameters in the quantum circuit design (such as rotation angles and gate timing) that can be optimized classically. By changing these parameters based on measured outcomes, the system adapts to the specific noise characteristics of the quantum processor, effectively compensating for control imperfections and enabling reliable computation with current NISQ devices.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach allows for more reliable computation by reducing noise and error accumulation, enabling the solution of complex optimization problems that would be impractical for classical computers alone, such as finding low-energy states of many-particle systems and combinatorial optimization problems.
Implementation Method 1
a series of Josephson junctions, each of which is formed by separating two superconducting electrodes with an insulating layer that is thin enough to allow pairs of electrons (Cooper pairs) to tunnel between the superconducting electrodes. Thus, current (referred to as Josephson current or persistent current) flows between the superconducting electrodes in the absence of a bias voltage applied between.
Implementation Method 2
two superconducting electrodes with an insulating layer that is thin enough to allow pairs of electrons (Cooper pairs) to tunnel between the superconducting electrodes
Implementation Method 3
A Josephson junction may be modelled as a non-linear resonator formed from a non-linear current-dependent inductance LJ (I) in parallel with a capacitance CJ. The capacitance CJ is determined by a ratio of the area of the Josephson junction to the thickness of the insulating layer. The inductance LJ (I) is determined by the Joseph current through the insulating layer, Thus, two lowest energy states of the non-linear resonator can be used as computational states of a qubit
Implementation Method 4
These states can be controlled via microwave irradiation of the superconducting circuit.
Data Source
AI summary
Embodiments described herein are generally related to a method and a system for performing a computation using a hybrid quantum-classical computing system, and, more specifically, to providing an approximate solution to an optimization problem using a hybrid quantum-classical computing system that includes a group of trapped ions. A hybrid quantum-classical computing system that is able to provide a solution to a combinatorial optimization problem may include a classical computer, a system controller, and a quantum processor. The methods and systems described herein include an efficient and noise resilient method for constructing trial states in the quantum processor in solving a problem in a hybrid quantum-classical computing system, which provides improvement over the conventional method for computation in a hybrid quantum-classical computing system.