The use of quantum-mechanical phenomena to solve problems that traditional computers cannot solve is known as quantum computing. Every day, we reap the benefits of traditional computing. How-ever, there are some issues that classical computers cannot handle, and we lack the processing capability to address them. This calls for the development of quantum computing, which might drive the emergence of breakthroughs in numerous disciplines to tackle previously unsolved challenges. Certain computational problems, such as integer factorization (which forms the basis of RSA encryption), are thought to be solved significantly faster on quantum computers than on classical computers, because quantum computers harness the power of quantum mechanics to deliver massive leaps forward in processing power. The accuracy of the Approximation Ratio after the steps were found to be 89.8%, which was better than some of the existing algorithms.

错误:搜索内容不能为空,请输入英文关键词
错误:关键词超出字数限制,请精简
高级检索

NPQuant: A Robust Quantum Inspired Computation Algorithms as an Efficient Solution to NP-Complete Problems

  • Bali Devi,
  • Mehil Bimal Shah,
  • Venkatesh Gauri Shankar,
  • Gauri Sharma

摘要

The use of quantum-mechanical phenomena to solve problems that traditional computers cannot solve is known as quantum computing. Every day, we reap the benefits of traditional computing. How-ever, there are some issues that classical computers cannot handle, and we lack the processing capability to address them. This calls for the development of quantum computing, which might drive the emergence of breakthroughs in numerous disciplines to tackle previously unsolved challenges. Certain computational problems, such as integer factorization (which forms the basis of RSA encryption), are thought to be solved significantly faster on quantum computers than on classical computers, because quantum computers harness the power of quantum mechanics to deliver massive leaps forward in processing power. The accuracy of the Approximation Ratio after the steps were found to be 89.8%, which was better than some of the existing algorithms.