INTERNATIONAL BUSINESS MACHINES CORPORATION (20240296365). NOISE LEARNING IN DYNAMIC QUANTUM CIRCUITS simplified abstract
Contents
NOISE LEARNING IN DYNAMIC QUANTUM CIRCUITS
Organization Name
INTERNATIONAL BUSINESS MACHINES CORPORATION
Inventor(s)
Paul Kristan Temme of Ossining NY (US)
Ewout Van Den Berg of Bronxville NY (US)
Riddhi Swaroop Gupta of San Jose CA (US)
Abhinav Kandala of Yorktown Heights NY (US)
NOISE LEARNING IN DYNAMIC QUANTUM CIRCUITS - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240296365 titled 'NOISE LEARNING IN DYNAMIC QUANTUM CIRCUITS
The patent application discusses systems and techniques that enable noise learning in dynamic quantum circuits. In various embodiments, a system can learn the noise associated with a mid-circuit non-unitary operation of a dynamic quantum circuit by modifying the operation with a probabilistic Pauli-Z gate and twirled Pauli operators.
- The system facilitates noise learning in dynamic quantum circuits.
- It can learn noise associated with mid-circuit non-unitary operations.
- The system modifies operations using a probabilistic Pauli-Z gate and twirled Pauli operators.
- This innovation enhances the efficiency and accuracy of quantum circuit operations.
- It enables better understanding and management of noise in quantum computing systems.
Potential Applications: This technology can be applied in quantum computing research, development of quantum algorithms, and optimization of quantum circuit performance.
Problems Solved: This technology addresses the challenge of noise in dynamic quantum circuits, improving the reliability and effectiveness of quantum computing operations.
Benefits: Enhanced noise learning capabilities, improved quantum circuit performance, better error correction mechanisms, and increased efficiency in quantum computing tasks.
Commercial Applications: Title: Quantum Circuit Noise Learning System This technology can be utilized by quantum computing companies, research institutions, and academic laboratories working on quantum information processing.
Questions about Quantum Circuit Noise Learning System: 1. How does the system handle noise in dynamic quantum circuits? The system handles noise by modifying mid-circuit non-unitary operations with probabilistic Pauli-Z gates and twirled Pauli operators.
2. What are the potential implications of this technology on quantum computing research? This technology can significantly advance quantum computing research by improving noise management and enhancing quantum circuit performance.
Original Abstract Submitted
systems and techniques that facilitate noise learning in dynamic quantum circuits are provided. in various embodiments, a system can learn noise associated with a mid-circuit non-unitary operation of a dynamic quantum circuit, by modifying the mid-circuit non-unitary operation with a probabilistic pauli-z gate and twirled pauli operators.
