Unfurling Significant Facts About Quantum Computing and Optimization

Optimization problems are almost everywhere and there are people who solve them instinctively. Whether it is about trying to figure out the shortest route, or puzzle out which line shall move faster while standing in the queue to pay bills, the story of optimization is everywhere. For more complex problems of optimization, classical computers are used to run different algorithms to get the best results. However, these problems can gradually become more difficult to solve and also the process could prove to be quite expensive. Quantum computers can come in handy in situations such as these.

Understanding quantum computing

So what is quantum computing exactly? Based on the different principles of quantum mechanics, quantum computing has its information represented as qubits or quantum bits. Information in the case of classical computing is represented as bits which can take the form of 0 or 1. On the other hand quantum bits can exist in a number of states simultaneously and this phenomenon is known as superposition. This property of the quantum bits enables a single quantum bit to process a number of possibilities simultaneously. This makes quantum computers work faster when compared with classical computers for some particular type of calculations.

More on Quantum Bits

Quantum bits are also entangled. This means that the state of one quantum bit is dependent on the state of the other even when they are separated by massive distances. This property further increases the processing power of the quantum computers and operations can be performed on multiple quantum bits by the quantum computers simultaneously. Quantum gates are used to perform operations such as addition and also multiplication.

The challenging part

One of the main disadvantages of quantum computing revolves around maintaining control over the quantum bits and this is so because the qubits are prone to a phenomenon called decoherence as a result of which the qubits tend to lose their quantum properties. Techniques associated with quantum error correction have been developed in order to mitigate this kind of problem but again qubits are required in large numbers for this and the control systems involved in the process are quite complex. 

Quantum Interference in brief

When talking about quantum interference, the benefit of interference in quantum computing deserves a mention. Quantum interference can be destructive as well as constructive. In case of constructive interference, the two in-phase waves that peak at the same time interfere in a constructive manner and when the resulting wave peaks it is twice as high. In the case of destructive interference, two out-of-phase waves that peak at opposite times interfere in a destructive manner and the resulting wave is completely flat. The benefits of quantum interference are as follows:

• Interference helps to improve the stability of the qubit and this is done by cancelling out the effects of the external noise that is known to interfere with the qubits. The qubits are allowed to attain a stable state by means of constructive and destructive interference.
• Interference is an important process and it helps quantum computers achieve computations that are much faster when compared to classical computers.
• Quantum computing is highly prone to errors arising from external and internal disturbances. Error correction codes are not always a feasible option. Interference which leads to the creation of the entangled states can simplify this process as these states act as error correcting codes.
• Interference can suppress the probability amplitudes of solutions that are incorrect ones by the creation of the phenomenon of destructive interference in between them.
• Similarly, with the help of constructive interference, the probability amplitudes of solutions that are correct ones can be amplified.

Some facts about Quantum Optimization

Quantum computing possesses the potential to bring about revolutionary changes in a number of fields and this includes cryptography, various problems associated with optimization, and also material science.

Mathematical formulations where the main aim is to retrieve the best solution among a set of possible solutions — that is what optimization problems are about. Quantum computing is preferred for solving optimization problems whose complexity levels are quite high. The main idea behind this is that by making use of the principles of entanglement and superposition, quantum computers hold the power to explore a solution space that is exponentially large in a simultaneous manner. This has in turn led to the building of various quantum algorithms for the purpose of solving optimization problems and this includes, the Quantum Approximate Optimization Algorithm (QAOA) and the Variational Quantum Eigensolver (VQE).

Recent studies have revealed that the different machine learning tactics can be used to enhance the performance of the quantum optimization algorithms. Quantum-inspired algorithms have been developed and in this the quantum computers are not required. Instead classical computing resources can be used to mimic certain quantum mechanics aspects.

Highlighting the significant differences

Quantum computer vs supercomputer — unveiling some key differences between supercomputer and quantum computer:

• Supercomputers make use of traditional computing approach and multiple processors are used to quickly process vast volumes of data and then give a single result
• When it comes to raw computing power, the supercomputers are the fastest.
• However supercomputers can handle only one task at a time and their processing capabilities are also limited
• Quantum computers makes judicious use of the principles of quantum mechanics to process data and information
• Quantum computers can handle multiple tasks at once and hold the ability to solve complex problems easily
• Significant maintenance is required in case of quantum computers as they are highly sensitive to temperature changes

Some associated problems

Quantum computers are prone to different errors because of the noisy nature of the quantum systems and this in turn could lead to incorrect solutions in case of optimization problems. There is also a lack of robust methods for the purpose of error correction and this hinders the process to scale up or enhance the entire system of quantum computers to handle complex problems of optimization.

There is also another problem and this revolves around mapping of classical problems of optimization onto quantum hardware. There is also a lack of standardization when it comes to quantum computing hardware as well as software and this hinders the very progress associated with the problems of optimization.

Final Note

Quantum optimization is expected to influence the field of logistics in a great way. Quantum optimization also holds immense promise in the realm of finance. Quantum optimization also has a lot to contribute when it comes to gaining understanding of complex systems. Quantum optimization also finds great use in the development of new materials that have unique properties. From machine learning to finance, quantum computing has a lot to give to the world.