量子计算在食品污染物模式识别中的创新应用

Innovative Application of Quantum Computing in Food Contaminant Pattern Recognition

LIU Mengyao'，WANG Qianqian²， JIANG Yang² （1.Dalian Customs Technology Center， Dalian ， China; 2.SGS-CSTC Standards Technical Services Co.， Ltd.， Dalian Branch， Dalian 1160o0， China）

Abstract： As food contaminant detection faces complex challenges such as high-dimensional data processing， coexistence of multi-source polltants，and sample inequality，quantum computing has shown unique advantages in the feldof pattrnrecognitiondue toitsparalelism，entanglement，and high-dimensional mappingcapabilities. This paper systematically reviews the application progress of quantum computing in food contaminant patrn recognition， focusing on the role of key technologies such as amplitude coding， variational quantum circuits， entanglement mechanisms，and quantum similarity discrimination in pollutant clasification，feature compression，and modelrobustness improvement，andevaluates itspotential inimprovingdetectioneffciency，boundaryrecognition capabilities，and system adaptability.The recognition model under quantum thinking has the characteristics of compact structure，efficient calculation，and flexible deployment，which provides a theoretical basis and method reference for building a new generation of intelligent food contaminant detection system.

Keywords： quantum computing; food contaminants; patern recognition; quantum encoding; variational quantumcircuit

近年来，随着食品产业链的快速延伸与加工技术的多样化发展，食品污染物种类和来源日趋复杂，对检测技术的响应速度与识别精度提出了更高要求。（剩余4062字）