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 th
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
Exploration of New Quantum Algorithms 人工智能可以帮助发现新的量子算法,拓展量子计算的应用领域。 3.量子计算与AI的联合应用 Joint Applications of Quantum Computing and AI 量子计算和人工智能的结合可以带来创新的应用场景和解决方案。 ·量子计算加速的AI应用 AI Applications Accelerated by Quantum Computing 利用...
这些硬件进展使得量子计算机能够实现更高的量子位数目和更长的量子相干时间,从而提高了计算能力和稳定性。 量子算法的优化(Optimization of Quantum Algorithms) Optimization of Quantum Algorithms 量子算法的设计和优化是量子计算发展的另一个重要方面。近年来,许多高效的量子算法被提出,如Shor算法和Grover算法,这些算法能...
Quantum AI.Quantum computers have the potential to work with more advanced algorithms that could transformmachine learningacross a diverse range of industries, from automotive to pharmaceuticals. In particular, quantum computers could accelerate the arrival of self-driving vehicles. Companies such as Ford...
We also develop a quantum framework for simulated annealing algorithms which is used to show a quantum speedup in estimating the volumes of convex bodies. Finally, we demonstrate a quantum algorithm for solving matrix games, which can be applied to a variety of learning problems such as linear ...
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...
massive studies combined quantum computing with machine learning to explore more advanced algorithms, which have achieved distinguished improvements in parameter optimization, execution efficiency, and the reduction of error rates. Quantum machine learning provides new insights for the intersectional research of...
Increased accuracy:Quantum computing algorithms are able to operate in quantum superpositions, which results in increased accuracy in solving complex problems. Improved machine learning:Quantum computing can be used to train machine learning models faster and more accurately than traditional computing methods...
Quantum computing Quantum algorithms for NISQ and universal quantum computers Quantum error mitigation and quantum error correction Benchmarking and optimization for realistic quantum hardware Quantum foundation Quantum resource theory Coherence, entanglement, informati...