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Quantum computing is on its way to being considered one of the most innovative technologies. Not only is this form of computing a better replacement for classical computing but also a potential complement for a specific set of applications. Considering how important quantum computing has become over a period of time, today it has reached a stage where it has the potential to solve a significant number of problems. On that note, have a look at 10 difficult problems quantum computers can solve easily.
Considering how intercepting the data would corrupt the communication, can anything get better than securing communication from interception or eavesdropping? Well, quantum encryption has to its rescue. With this in place, the person disrupting the particle cannot get usable information, and the recipient can be alerted to the eavesdropping attempt.
What cannot go unnoticed, is the fact that even if a few qubits of quantum systems are to simulate, it'd be extremely expensive when it comes to the resources required. This is where quantum computing serves to be no less than a blessing.
Classical computing is of very little help when the task to be accomplished pertains to ab initio calculations. With quantum computing in place, you have a quantum system simulating another quantum system. Furthermore, tasks such as modelling atomic bonding or estimating electron orbital overlaps can be done much more precisely.
Yet another difficult area that quantum computers cater to is that of solving difficult combinatorics problems. The algorithms within quantum computing aim at solving difficult combinatorics problems in graph theory, number theory, and statistics. Well, the list is likely to continue in the near future.
Logistics is more or less related to a set of problems that cannot be solved using a brute force algorithm. Rather than meeting the set objectives via numerous individual operations, quantum computers do it in the easiest manner possible.
One of the most difficult problems that quantum computers can solve is – "optimization". One major aspect of this includes determining optimal weights for neural nets, so a classifier would be as good as it can be on a set of training data.
Economics is associated with numerous sophisticated models of market behaviour in the hope of predicting important and disruptive events. With quantum computing, we can now process and retrieve data from incredibly large data sets and make predictions about markets that can have an outsized global impact.
The drug industry, without a doubt, has a lot of experimentation and discovery happening at the back end. This is not only time-consuming but also expensive. A quantum computer, on the other hand, can process all the variables concurrently and will greatly reduce the time and cost necessary to develop new drugs.
The growing data is posed as one of the biggest challenges for classical computing. This is where quantum computing came into play. Quantum computers have the ability to process large data sets in record time.
With many environmental variables in place, it becomes quite difficult for classical computers to forecast weather. However, a quantum computer can not only forecast near-term weather patterns well but also predict the effect of climate change.
