Stochastic Ising Optimization for Low-Cost Pseudo Quantum Annealing
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing optimization techniques, such as quantum annealing, face challenges in reducing calculation time and hardware costs, particularly in preparing an appropriate operating environment for quantum devices.
Innovation Solution
An optimization device and method using stochastic calculation on a quantum annealing model with a transverse magnetic field, applying a series of formulas satisfying specific state update conditions to optimize an Ising model, including conditions for spin states, relationships between spin states, and interactions between spins in different trotter layers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If quantum annealing technique is used, then calculation time is significantly reduced, but device mounting and operation cost increases
Solution Approach 1:
The patent applies the copying principle by implementing a classical computer system that simulates quantum annealing processes. Instead of requiring actual quantum hardware, the invention creates a software-based copy of quantum annealing behavior using classical stochastic calculation methods, thereby achieving quantum-like optimization performance without quantum device costs
Solution Approach 2:
The patent substitutes the quantum mechanical system with a classical computational system. By replacing quantum hardware requirements with classical stochastic algorithms that model quantum annealing behavior, the invention eliminates the need for complex quantum device mounting and operation while maintaining the computational benefits
2Productivity
If quantum annealing technique is used, then optimization performance is improved, but preparation of appropriate operating environment becomes difficult
Solution Approach 1:
The patent introduces an intermediary classical computational layer that mediates between the optimization problem and the solution. This intermediary system uses stochastic calculations to simulate quantum annealing effects, providing a bridge that achieves quantum-level optimization performance without requiring actual quantum hardware or complex quantum operating environments
3Device complexity
If classical computer optimization is used, then device cost is reduced, but calculation time increases
Solution Approach 1:
The patent applies parameter changes by modifying the computational approach to include stochastic elements that simulate quantum thermal effects. By changing the optimization algorithm parameters to incorporate probabilistic state transitions and temperature-like parameters, the classical system achieves faster convergence times comparable to quantum annealing while maintaining lower hardware costs
Data Source
AI summary
An aspect of the invention includes an optimization unit configured to perform optimization, by stochastic calculation, on a Hamiltonian of a quantum annealing model, which is an Ising model representing the optimization target in a state in which a transverse magnetic field is applied, in which the optimization unit performs the optimization by executing a series of formulas satisfying a state update condition, which is a condition related to an update of a spin state, until a predetermined end condition is satisfied, and the state update condition includes a first condition representing the spin state, a second condition representing a relationship between the spin states obtained at different times, a third condition representing a relationship between adjacent trotter layers, and a fourth condition including an amount representing an intensity of an interaction between the same or different spins existing in the same trotter layer, an amount representing a magnitude of energy of a spin itself, and an amount representing an intensity of an interaction between spins belonging to different trotter layers.