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What is Quantum Computing?

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In fields such as cryptography and chemistry, material science, pharmaceuticals, and agriculture, quantum computing can be extremely useful.

There is no denying that by nature, quantum computing is complicated. However, this is exactly why it can be used to sort problems out in complex mathematical models that are important to the workings of the economy.

Quantum Computing- What is it?

According to research provided by Wikipedia, quantum computing is the “use of quantum-mechanical phenomena such as superposition and entanglement to perform computation.” The classical computer concept is completely redefined by quantum computing.

The workings of classical computers include key-like structures which are subject to opening and closing. These are known as bits. Quantum computers, on the other hand, use interdependent and nonlinear structures. These are known as qubits.

To put it simply, qubits have an entirely different working property system, making it extremely different from the concept behind classical computing. Qubits are dependent on each other due to a property known as entanglement. The tiniest change in the state of a qubit can cause a change in all the other qubits. According to superposition, qubits have the ability to hold 0 and 1 states together at the same time.

Why is Quantum Computing Important for the Future?

1.    The Rise of Complex Problems

The problems faced are getting more complicated as technology improves. Due to quantum computing, complicated problems such as protein modeling can be solved. When the global pandemic of 2020, coronavirus, hit, it was found that scientists require another tool so that a single protein could be modeled and deactivated.

Energy usage is another complicated problem that is on the rise. The increasing human population has caused a skyrocketing consumption rate. This has led to more problems like the optimization of sources. With quantum computers, the physics of quantum mechanics can be used to deal with the limitations of complicated problems.

2.    Supercomputers Only Solve Nonlinear Problems

If you want to perform some sequential operations and store information, classical computing is your best bet. However, it is not the best tool to use for finding the solution to complex issues because it is customized according to linear mathematics.

Based on its nonlinear properties of nature, quantum computing is great for resolving nonlinear problems. However, it must be kept in mind that quantum computers do have their limitations- they are not the best for all types of computation.

The Future of Computing

Optimization

There are my optimization problems that require a minimal global type of solution. Quantum annealing helps solve optimization issues faster than the use of supercomputers.

Machine Learning/ Big Data

Many machine learning researchers, as well as those who are a part of deep learning, are looking for efficient solutions to training and testing models with the help of large data sets.

Quantum computing helps make the training process easier while making the testing process faster and more efficient.

Simulation

One of the most useful and practical ways to deal with the possibility of errors is simulation. The simulation also helps you take efficient action.

With the help of quantum computing methods, many complicated systems can be simulated.

Material Science

Due to the calculations of complicated interactions of atomic structures, there is not a lot of chemistry and material science available.

However, if you are looking to deal with these interactions, quantum solutions are a promising way forward.

Challenges in the Future of Quantum Computing

1.    Figuring Out the Correct Approach

When it comes to quantum computing, there are loads of different approaches that you can implement. Trial and error for all approaches will be roughly the same in terms of time and money because both quantum computerization and quantum circuits yield heavy investment costs.

As of now, the best way possible is to ponder upon the different approaches available for different applications. Analog quantum model, universal quantum gate model, and quantum annealing are the most popular approaches that QC companies are currently exploring.

2.    Making Quantum Processors that are Stable and Correct Errors

The best way to make use of quantum mechanics is to use it to execute manipulations at a smaller scale. This must be even smaller than an atom. The advantage of small scales is that they ensure stability and help verify any possible errors.

According to quantum researchers, error correction in qubits is known to be more treasured than the total number of qubits that have been obtained. However, it must be kept in mind that qubits are not accurate; hence special attention must be paid when dealing with complicated problems.

3.    Ensuring Extreme Operating Conditions

The IBM must keep temperature cold so that stability and control can be ensured in qubits. This ensures that no noise or heat will excite the superconducting qubit, hence producing invalid results. However, keeping the temperature too low also brings about stability issues.

Operating conditions need to be paid special attention to when dealing with the broad commercialization of a quantum computer or processor. Currently, a lot of research is going into discovering ways in which quantum processors can be kept stable at high temperatures. Recently, the highest temperature was reached at –272 degrees. Yet, working these systems at room temperature seems to take longer.

When it comes to stability and error correction, special attention must be paid to technology investment, the number of resources available for research, and the advancements in quantum mechanics. There are loads of organizations that are currently trying to get their hands on the most accessible quantum computer technology with the help of a variety of methods. However, we believe that discovering which approach will ensure success may take some time.

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