Counterdiabatic Quantum Algorithm Digitization for NISQ Hardware
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Solution Overview
Problem
Current noisy intermediate-scale quantum (NISQ) devices face limitations in solving real-world problems due to missing appropriate algorithms and hardware constraints, limiting their scalability and performance for general-purpose quantum computing.
Innovation Solution
A method is developed to transform analog quantum algorithms into digital quantum algorithms by adding approximated counterdiabatic terms and digitizing them, utilizing native gates and optimizing for specific hardware platforms like superconducting circuits, trapped ions, and others, reducing the number of qubit gates and operations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If general-purpose quantum algorithms are used on NISQ hardware, then algorithm versatility is maintained, but performance and scalability are insufficient for real-world problems
Solution Approach 1:
The invention segments the quantum algorithm into problem-specific components tailored to NISQ hardware capabilities. By dividing the algorithm into discrete quantum circuits optimized for specific hardware architectures (superconducting qubits, trapped ions, etc.), the system achieves high performance on real-world problems while maintaining adaptability through hardware-aware compilation and optimization layers.
2Ease of manufacture
If analog quantum algorithms are transformed into digital quantum algorithms, then hardware compatibility is improved, but algorithm complexity increases
Solution Approach 1:
The invention applies parameter changes by transforming analog algorithm parameters into digital representations suitable for quantum circuits. Through Hamiltonian discretization, continuous time evolution is converted into discrete time steps with specific gate sequences. This transformation improves hardware compatibility by matching digital quantum processors while managing complexity through optimized parameter selection and circuit compilation.
3Productivity
If counterdiabatic terms are added to the Hamiltonian, then algorithm efficiency is improved, but computational overhead increases
Solution Approach 1:
The invention applies partial action by incorporating counterdiabatic terms selectively rather than exhaustively. Instead of adding all possible counterdiabatic corrections, the system identifies and implements only the essential terms needed for the specific problem and hardware platform. This approach improves algorithm efficiency by reducing non-adiabatic transitions while minimizing computational overhead through targeted term selection and optimization.
Data Source
AI summary
The invention pertains to a method for providing a digital quantum algorithm comprising the steps of: a) Providing an analog adiabatic quantum algorithm that includes a Hamiltonian function (Hamiltonian Operator) that solves a given problem, b) Adding at least one approximated counterdiabatic (CD) term to the Hamiltonian function of the analog quantum algorithm to obtain a counterdiabatic-enhanced (CD) adiabatic quantum algorithm, and c) Digitizing the counterdiabatic-enhanced adiabatic quantum algorithm from step b) to obtain a digital quantum algorithm. The invention leads to a reduction in the number of qubits, quantum gates, and operations needed on a noisy intermediate scale quantum (NISQ) computer with digital and analog hardware.