Google LLC (20240289658). Enhancing Simulated Annealing with Quantum Annealing simplified abstract
Contents
Enhancing Simulated Annealing with Quantum Annealing
Organization Name
Inventor(s)
Hartmut Neven of Malibu CA (US)
Enhancing Simulated Annealing with Quantum Annealing - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240289658 titled 'Enhancing Simulated Annealing with Quantum Annealing
The abstract of this patent application describes methods and apparatus for enhancing simulated annealing with quantum fluctuations.
- Obtaining an input state
- Performing simulated annealing on the input state with a temperature reduction schedule
- Terminating the simulated annealing if the decrease in energy is below a first minimum value
- Outputting a first evolved state and first temperature value
- Reducing the temperature to a minimum value
- Performing quantum annealing on the first evolved state with a transversal field increase schedule
- Terminating the quantum annealing if a completion of a second event occurs
- Outputting a second evolved state as a subsequent input state for the simulated annealing
Potential Applications: - Optimization problems in various industries such as logistics, finance, and manufacturing - Machine learning and artificial intelligence algorithms - Cryptography and cybersecurity for enhanced encryption techniques
Problems Solved: - Improving the efficiency and effectiveness of optimization algorithms - Enhancing the speed and accuracy of solving complex problems - Combining classical and quantum computing techniques for better results
Benefits: - Faster convergence to optimal solutions - Increased scalability for larger problem sizes - Enhanced robustness and reliability in solving optimization problems
Commercial Applications: - Optimization software for businesses - Quantum computing services for research institutions - Consulting services for implementing advanced optimization techniques
Questions about Quantum Fluctuations: 1. How do quantum fluctuations improve the efficiency of simulated annealing?
Quantum fluctuations introduce randomness and uncertainty into the optimization process, allowing for exploration of a wider solution space and potentially avoiding local minima.
2. What are the key differences between simulated annealing and quantum annealing?
Simulated annealing is a classical optimization technique that simulates the annealing process in metallurgy, while quantum annealing leverages quantum mechanics principles to optimize solutions using quantum bits (qubits).
Original Abstract Submitted
methods and apparatus for enhancing simulated annealing with quantum fluctuations. in one aspect, a method includes obtaining an input state; performing simulated annealing on the input state with a temperature reduction schedule until a decrease in energy is below a first minimum value; terminating the simulated annealing in response to determining that the decrease in energy is below the first minimum level; outputting a first evolved state and first temperature value; reducing the temperature to a minimum temperature value; performing quantum annealing on the first evolved state with a transversal field increase schedule until a completion of a second event occurs; terminating the quantum annealing in response to determining that a completion of the second event has occurred; outputting a second evolved state as a subsequent input state for the simulated annealing, and determining that the completion of the first event has occurred.
