10 Difficult Problems Quantum Computers can Solve Easily (2024)

10 Difficult Problems Quantum Computers can Solve Easily (1)

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.

Quantum encryption

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.

ab initio calculations

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.

Solving difficult combinatorics problems

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.

Optimization

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.

Finance

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.

Drug development

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.

Data analysis

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.

Weather forecasting

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.

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10 Difficult Problems Quantum Computers can Solve Easily (2024)

FAQs

Which problem is effectively solved using quantum computing? ›

Searching unstructured databases: Quantum computers can search unstructured databases exponentially faster than classical computers, making it a potential solution for problems such as drug discovery or logistics optimization.

What can quantum computers do more efficiently? ›

Quantum computers are able to solve certain types of problems faster than classical computers by taking advantage of quantum mechanical effects, such as superposition and quantum interference.

What type of AI problems can a quantum computer solve? ›

Quantum computers do exceptionally well with problems that require calculating a large number of possible combinations. These types of problems can be found in many areas, such as quantum simulation, cryptography, quantum machine learning, and search problems.

Can quantum computers solve real world problems? ›

Quantum computing will also help us find the new optimum between design, maximum interior space, and best aerodynamics.” That's just the start. Modern business teems with optimization problems that are ideally suited to quantum algorithms and could save time, energy, and resources.

What can quantum computers break? ›

Researchers typically estimate that it will be many years until quantum computers can crack cryptographic keys—the strings of characters used in an encryption algorithm to protect data—faster than ordinary computers.

Which two major challenges do quantum computers face? ›

In this article we are going to dive deep into some of the main challenges: quantum decoherence, error correction and scalability. Compared with standard computers, quantum computers are extremely susceptible to noise.

What is the biggest problem with quantum computing? ›

Challenges of quantum computing

The three main challenges we'll look at include quantum decoherence, error correction, and scalability. Each is a major hurdle on the road to quantum computing, and must be overcome if the technology is to reach full potential.

Can quantum computers solve NP hard problems? ›

So, a quantum computer with bounded error can solve all types of problems in P and BPP in polynomial time. It can solve some NP types of problems in polynomial time, with factoring via Shor's algorithm serving as the most popular example.

What can quantum computers do that normal ones can't? ›

In classical computers, algorithms need a lot of parallel computations to solve problems. Quantum computers can account for multiple outcomes when they analyze data with a large set of constraints.

What will quantum computers improve? ›

Quantum computers are adept at simulating quantum systems, which could be beneficial for AI applications related to quantum chemistry, materials science, and drug discovery. This capability could lead to breakthroughs in understanding complex molecular interactions and designing new materials.

What is a real life example of quantum computing? ›

A real-life example of quantum computing is drug discovery. By making it easier to model the behavior of proteins, quantum computing can help researchers understand existing drugs and create new drugs to treat diseases like Alzheimer's and cancer.

What kind of problems can a quantum computer solve? ›

Quantum computers can solve NP-hard problems that classical computers are unable to solve. Currently, the two most important and notable complexity classes are “P” and “NP.” P represents problems that can be solved in polynomial time by a classical computer. For instance, asking if a number is prime belongs to P.

What human problems will computers solve in the near future? ›

AI algorithms will enhance everyday tasks, automate decision-making processes, and offer personalized user experiences. This technology will find applications in medical diagnostics, autonomous vehicles, and natural language understanding.

Can quantum computers do anything useful? ›

Quantum computers have the potential to revolutionize computation by making certain types of classically intractable problems solvable. While no quantum computer is yet sophisticated enough to carry out calculations that a classical computer can't, great progress is under way.

Does D wave say its quantum computers can solve otherwise impossible tasks? ›

Quantum computers can now solve problems with real-world applications faster than any ordinary computer, suggesting they could be commercially viable, say researchers at quantum computing firm D-Wave. However, outside observers are more cautious.

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