Semiconductor Circuit for Quantum Annealing Simulation
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Solution Overview
Problem
Quantum annealing computers face inefficiencies in solving discrete optimization problems due to limitations in transitioning physical systems to lowest energy states, particularly in controlling external potential fields over time.
Innovation Solution
A semiconductor circuit design comprising strings of device units and weight units, where input signals undergo logical operations and weight signals are used to produce output signals that represent energy states, enabling efficient computation of optimal solutions through quantum annealing principles.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If quantum annealing is used to solve discrete optimization problems, then computational efficiency is improved, but device complexity increases
Solution Approach 1:
The patent uses memory cells to copy and represent quantum states classically. Each memory cell stores a copy of the quantum state information, allowing classical computation to mimic quantum annealing behavior without requiring actual quantum hardware, thus improving computational efficiency for optimization problems while managing device complexity through software/firmware-level simulation
Solution Approach 2:
The patent replaces physical quantum mechanical systems with electronic memory and logic circuits. By substituting quantum mechanical effects with classical electronic operations in memory devices, the system achieves quantum-inspired computational efficiency without the complexity of maintaining actual quantum states, transitioning from quantum physics to solid-state electronics
2Measurement precision
If external potential fields are controlled over time to achieve lowest energy states, then optimization accuracy is improved, but operation time increases
Solution Approach 1:
The patent pre-computes and stores weight values in memory cells before the annealing process. These weight values represent the potential energy landscape in advance, allowing the system to quickly evaluate energy states during computation without requiring slow, gradual physical potential field adjustments, thus improving optimization accuracy while reducing operation time
Solution Approach 2:
The patent anticipates and pre-establishes the energy landscape configuration in memory before computation begins. By pre-configuring the weight signals that define the objective function, the system avoids time-consuming real-time potential field adjustments during the annealing process, achieving both high optimization accuracy and fast operation
3Productivity
If weight signals and input signals are processed through device units to produce output signals, then computational capability is improved, but energy consumption increases
Solution Approach 1:
The patent combines multiple functions (weight storage, input signal processing, logical operations, and output generation) into integrated memory cell structures. By merging these separate computational stages into unified memory devices, the system achieves high computational capability while reducing energy consumption through eliminated signal routing and reduced operational steps
Solution Approach 2:
The patent designs memory cells to perform multiple functions: storing weight signals, receiving input signals, performing logical operations (AND, OR, NOT), and generating output signals. This multi-functionality allows a single device structure to handle the entire computational process, improving computational capability while minimizing energy consumption by avoiding multiple specialized components
Data Source
AI summary
A semiconductor circuit and an operating method for the same are provided. The semiconductor circuit includes strings. The strings include a first string and a second string. The first string includes a first device unit and a second device unit in series. The first string has a weight signal W1. The first device unit has an input signal A. The second device unit has an input signal B. The second string includes a third device unit and a fourth device unit in series. The second string has a weight signal W2. The third device unit has an input signal Ā. The fourth device unit has an input signal B. An output signal of the semiconductor circuit is a sum of output string signals of the strings.