QUANTUM COMPUTING APPLICATIONS FOR ADDRESSING GLOBAL WARMING AND POLLUTION: A COMPREHENSIVE ANALYSIS

Authors

  • Mariana Filipova Computer science department, ULSIT (BG)
  • Genadiy Gospodinov Computer science department, ULSIT (BG)
  • Lyubomir Gotsev Computer science department, ULSIT (BG)
  • Eugenia Kovatcheva Computer science department, ULSIT (BG)
  • Boyan Jekov Computer science department, ULSIT (BG)

DOI:

https://doi.org/10.17770/etr2024vol1.8001

Keywords:

global warming, pollution, quantum algorithms, quantum computing

Abstract

Pollution and global warming become more and more of a threat recently, so creative solutions are required to tackle their overwhelming complexity, surpassing the limitations of traditional computational methods. Using the concepts of quantum physics, quantum computing presents a revolutionary approach for solving such environmental problems. With the help of a variety of data in usage from reputable global scientific sources, including world databases, pollution monitoring networks, and climate models in addition, the current scientific paper explores the quickly developing potential of quantum computing to reduce pollution and global warming. The complexities of quantum algorithms are object of our exploration, focusing on those that have relevance in resource management, in order to shed light on how quantum computers might transform decision-making processes toward global environmental sustainability. Techniques for quantum optimization show promise in maximizing energy grid distribution and reducing waste generation in complex supply chains.

Supporting Agencies
EXCELLCITY (STRENGTHENING THE SCIENTIFIC EXCELLENCE AND INNOVATION CAPACITY IN THE AREA OF SMART CITY THROUGH TWINNING) BG-RRP-2.005-0003.

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Published

2024-06-22

How to Cite

[1]
M. Filipova, G. Gospodinov, L. Gotsev, E. Kovatcheva, and B. Jekov, “QUANTUM COMPUTING APPLICATIONS FOR ADDRESSING GLOBAL WARMING AND POLLUTION: A COMPREHENSIVE ANALYSIS”, ETR, vol. 1, pp. 154–160, Jun. 2024, doi: 10.17770/etr2024vol1.8001.