The global loss due to natural disasters in the past 19 years accounted to be US$232 billion.

Humans have no control over natural disasters. Over the past few years, it has been witnessed that despite strategical planning, disasters such as forest fires, floods, Tsunamis have led to a huge economic, financial, and physical crisis. According to a report by Statistica, the global loss due to natural disasters in the past 19 years accounted to be US$232 billion.

The forest fires, flooding, and hurricanes are some of the natural disasters that the world has witnessed since the beginning of 2020. Most of the natural disasters occur due to climate change. The environmental organizations and activists have repeatedly warned about the impending doom associated with disasters, and scientists and researchers are working to thwart the loss stimulated due to the disasters. One of the most common approaches heavily researched to mitigate the effectiveness and early prediction of disasters is the utilization of Quantum Computing.

This technology is at a nascent stage but has been recognized as a powerful tool in mitigating future natural disasters. Researchers and scientists are already chalking out strategies that would help forecast the weather conditions and make an informed decision with the help of quantum computing.

Understanding Quantum Computing 

According to Gartner, Quantum computing is a type of non-classical computing that operates on the quantum states of subatomic particles. The particles represent information as elements denoted as quantum bits (qubits). A qubit can represent all possible values simultaneously (superposition) until reading. These qubits can be linked with other qubits, a property known as entanglement. Quantum algorithms manipulate linked qubits in their undetermined, entangled state, a process that can address problems with vast combinatorial complexity.

The global quantum computing market is expected to witness a CAGR of 34% between 2019-2025, thus reaching the market size of US$2.82 billion.

Forecasting With Quantum Computing

Forecasting is one of the greatest assets that can be utilized for the weather conditions to take necessary measures in disaster preparedness. Over the years, scientists and researchers have applied classical computing methods to forecast weather conditions.

A forecasting tool includes electric utilities, namely the power grid, to predict, respond, and recover from the extreme conditions. However, due to the complexity of the grids, when deployed, classical computing is unable to meet these challenges

Also, the operators remain uncertain about the availability of renewable resources and the supply and demand chain. An efficient strategy to prepare for natural disasters requests assessing areas of the grid that will have the most detrimental impact, deploying equipment to mitigate the damage and re-distribution of resources. The computation process can then aid in logistics and to manage the impact of the disaster. All these processes are timely and required to be achieved with accuracy and efficiency.

However, a classical computing model is unable to make timely and informed decisions with such demands. A quantum computing model increases the computational process and has been observed to show positive results while utilizing power grids' complexities in disaster management preparedness.

Analyzing the Behavior of the Power System

Researchers at the University of Denver, along with ComEd, the electric utility in Northern Illinois and Chicago, have launched a collaborative study Quantum computing for power systems, to aid in impactful decision making.

The researchers have observed that quantum computing can analyze the challenges associated with a fundamental power system. Even though a smaller power model is tested with few Qubits, which makes the process inexpensive and accurate, researchers are optimistic about the future applications of quantum computing in large power systems.

Quantum computing is a technology that is still evolving but carries massive potential in mitigating natural disasters.