Quantum Amplitude Estimation Under NISQ Circuit Depth Limits
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Noisy intermediate-scale quantum (NISQ) devices are limited by noise and circuit depth, making them incapable of performing amplitude estimation algorithms effectively, which require numerous sequential oracle calls, exceeding their operational capabilities.
Innovation Solution
The development of two new amplitude estimation algorithms, Power Law and QoPrime, that reduce the depth of quantum circuits while maintaining quantum speedup, allowing NISQ devices to perform amplitude estimation by optimizing oracle calls and circuit depth through power law schedules and number theoretic approaches, respectively.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If standard amplitude estimation algorithms are used, then quantum speedup is achieved, but circuit depth becomes too large for NISQ devices
Solution Approach 1:
The patent segments the amplitude estimation process by dividing the circuit depth into manageable blocks. Instead of executing the full-depth circuit required by standard amplitude estimation, the invention uses a truncated version of the circuit that achieves sufficient accuracy with fewer operations, making it suitable for NISQ devices while maintaining quantum speedup benefits
Solution Approach 2:
The invention changes the parameter of circuit depth by introducing a truncation level that balances computational requirements with hardware capabilities. By adjusting this parameter, the algorithm adapts to NISQ device limitations while preserving the essential quantum advantage for amplitude estimation
2Device complexity
If NISQ devices operate with limited circuit depth, then device capabilities are respected, but amplitude estimation accuracy deteriorates
Solution Approach 1:
The patent applies partial action by executing only a portion of the full amplitude estimation circuit. The truncated circuit performs sufficient oracle calls and unitary operations to achieve acceptable accuracy for practical applications on NISQ devices, rather than requiring the complete circuit depth that would be needed for perfect precision
Solution Approach 2:
The invention substitutes the mechanical execution of deep circuits with a hybrid approach that combines limited quantum circuit execution with classical post-processing. This replacement allows the system to achieve adequate accuracy by leveraging both quantum and classical computational resources, adapting to the limitations of NISQ hardware
3Measurement precision
If numerous sequential oracle calls are made, then amplitude estimation precision is improved, but noise accumulation increases
Solution Approach 1:
The patent reduces noise accumulation by limiting the number of sequential oracle calls to a manageable level. The truncated circuit executes only as many oracle calls as NISQ devices can reliably handle, balancing the need for precision with the reality of noise-induced errors that increase with each sequential operation
Solution Approach 2:
The invention incorporates feedback mechanisms that monitor the reliability of quantum operations and adjust the circuit execution accordingly. By feedback-based adaptation, the algorithm can determine when additional oracle calls would introduce more noise than useful information, and stop at the optimal point for precision
Data Source
AI summary
This disclosure relates to enhanced methods of operating quantum computing systems to perform amplitude estimation. More than that, the methods may be tuned to accommodate for specific noise levels (e.g., in given a quantum device). Embodiments also enable quantum computing systems to perform amplitude estimation faster than amplitude estimation algorithms performed using a classical (non-quantum) computer.