For physicists, statisticians, computer engineers, and other technical professionals, quantum information processing is an essential technology with many outstanding challenges. This chapter gives a brief overv
量子计算在机器学习中的应用 (Applications of Quantum Computing in Machine Learning) 机器学习是现代数据分析和人工智能的重要组成部分。量子计算为机器学习提供了新的思路和方法,尤其是在处理大规模数据集时。 量子支持向量机 (Quantum Support Vector Machine, QSVM) 支持向量机是一种经典的机器学习算法,用于分类和...
from qiskit_machine_learning.kernelsimportQuantumKernel from qiskit.circuitimportParameterVector # 创建一个两量子比特的量子电路,作为特征映射 feature_dimension=2x=ParameterVector('x',feature_dimension)feature_map=QuantumCircuit(feature_dimension)# 对量子比特应用Hadamard门和RZ旋转门foriinrange(feature_dimension...
Why should we look at quantum computing in machine learning? Apart from a speedup and increased storage capacity, quantum computing has further benefits for machine learning algorithms. Learning models lie at the core of data mining, a complex process of extracting meaningful information from large ...
Impact of Artificial Intelligence on Quantum Computing 人工智能技术的进步也能对量子计算产生影响,提升量子计算的性能和应用范围。 1.优化量子计算机的设计 Optimizing Quantum Computer Design 人工智能可以帮助优化量子计算机的设计,提高其性能和稳定性。 ·自动化设计与调整 ...
The use of quantum computing for machine learning is among the most exciting prospective applications of quantum technologies. However, machine learning tasks where data is provided can be considerably different than commonly studied computational tasks. In this work, we show that some problems that ar...
Machine learning algorithms based on parametrized quantum circuits are prime candidates for near-term applications on noisy quantum computers. In this direction, various types of quantum machine learning models have been introduced and studied extensivel
2. How Quantum Computing Enhances Machine Learning Quantum Computing may be utilized to accelerate the process of carrying out complicated computations and simulations in the realm of ML. For instance, a quantum computer may be used to swiftly examine huge data sets and spot patterns that would be...
Quantum Machine Learningbridges the gap between abstract developments in quantum computing and the applied research on machine learning. Paring down the complexity of the disciplines involved, it focuses on providing a synthesis that explains the most important machine learning algorithms in a quantum fra...
A universal scheme of quantum computing is the 'gate model'. A gate performs the state-to-state transfer, this process will physically last for a duration of time. In short, every gate has an underlying Hamiltonian. Let us write the time evolution operator of our physical system as:U^ ...