When you are at the entrance of a maze, you can choose to begin by turning right or left. A standard computer would pick one of these directions and pursue it. On the other hand, a quantum computer can pursue both directions at the same time and report back on which direction has the highest chance of getting you through the maze successfully. That is the logical mode of operation in a quantum computer that is known as a superposition.<\/p>\n
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On a deeper level, the superposition of a quantum computer is the undefined, random yet measurable condition in which multiple variables can exist and many results can be achieved. For example, a quantum computer can be queried about its superposition. To this, it can respond that it is either in state A, B, A+B, or A-B. In this case, it can achieve 4 different states at the same time. Fundamentally, it can solve problems four times as fast as a standard computer.<\/p>\n
A quantum computer can achieve this rate of processing with a single quantum processor. Should it be equipped with multiple processors and have them all running at the same time, the quantum computer can multiple its speed by the number of processors onboard. Furthermore, it can increase its performance through a process known as quantum entanglement.<\/p>\n
Standard computer systems often implement multiple processor cores to solve problems. If this mode of operation is applied in quantum computing, multiple superpositions can be combined to solve problems quicker. In this situation, the states can be entangled to create new ones for example state A+B can be combined with state A*B to create (A+B)(A*B) = (A2<\/sup>B + AB2<\/sup>). Knowing that each quantum processor can create any number of random states, the processing capability of quantum entanglement can be enormous!<\/p>\n In essence, a quantum computer needs to be able to maintain an object in a state of superposition for as long as possible so as to perform multiple processes upon it. If this object should come into contact with materials that are in a binary state, it immediately assumes their state and loses its superposition. This transforms it into a one (1) or a zero (0) in a process called decoherence.<\/p>\n Therefore, a quantum computer needs to have the primary capability of maintaining an object in its superposition. It also needs to have the ability to ensure that the objective is easy to read by eliminating the possibility of errors. This is accomplished in two ways; the quantum computer can be fitted with more powerful processors or programmed using more efficient commands that can find and eliminate errors quicker.<\/p>\n There are specific problems that quantum computers are best suited for. They include:<\/p>\n Due to the early nature of this technology, quantum computers are not yet being used for all these functions in real-world situations. Their still mysterious quality and unpredictable performance would make it very dangerous to apply them. However, there are some quantum computers in existence and they’re being applied in a pretty exciting way.<\/p>\n Quantum computers are currently being utilized in universities and scientific facilities for research and education. They are being used for Research and Development (R&D) for the purpose of molecular modeling of a very light molecule of lithium hydrogen. Researchers at IBM used the Q53 to model a beryllium hydride molecule successfully. Furthermore, the experts at IonQ used their quantum computer to model a water molecule.<\/p>\n In light of these achievements, strategic partnerships between quantum computing startups and leading companies in the pharmaceutical sector are being forged for example the one between 1Qbit and Biogen as well as another between ProteinQure and AstraZeneca for the molecular modeling of medication.<\/p>\n Quantum computers are utilized for this modeling to execute and perfect simulation. The results are compared to similar simulations performed using standard computer systems. In this way, the effectiveness and speed of quantum computing for simulation are ascertained.<\/p>\n The NISQ<\/strong><\/p>\n If they’re so powerful, why aren’t quantum computers being used for financial projection, real-time market analysis, and bio-chemical synthesis in the agricultural sector? The answer is NISQ, Noisy Intermediate Scale Quantum. This is the current level at which all quantum computers are at. In this level, the performance of these computing systems is erratic and very unpredictable hence the “noise”. While quantum computers are markedly light years faster than standard methods, they are extremely difficult ultimate to stabilize. As such, they produce digital noise that bars them from being trusted with critical, real-world systems.<\/p>\n There is considerable interest in the application of quantum computing in Artificial Intelligence (AI) but this,would require millions of qubits of processing power. Therefore, while an attractive time concept, this reality is still decades away.<\/p>\n Two main types of quantum computers are available today and they include:<\/p>\n The quantum annealer is a standard bearing computer that was developed by a Canadian company known as D-wave. It concentrates the power of superpositions to solve specific problems with tremendous accuracy and speed. Quantum annealers are 3,600 times faster than a supercomputer. Quantum annealers are therefore used to solve mathematical problems where an accurate, definite solution is required. While quantum annealers are extremely powerful, their scope of application is highly limited.<\/p>\n This type of quantum computer combines speed and generality. The universal quantum computer achieves exponentially numerous superpositions concurrently. In this way, it can perform calculations at lightspeed while maintaining a high level of versatility. That said, they can handle a wide variety of problems at the same time and still deliver accurate, correct results. Despite being so powerful, universal quantum computers pose immense technical difficulties to construct. This is because quantum particles activated in universally random superpositions are so erratic that the slightest variation in light, sound or environmental density can cause the computer to arrive at incorrect results.<\/p>\n A computer system that can perform billions of calculations thousands of times faster than modern supercomputers has numerous applications in today’s sectors of industry. It can be used to speed up the process of machine learning in Artificial Intelligence (AI) or make Cloud computing systems completely impossible to hack. Quantum computers can also be used in the medical research sector to speed up the process of finding cures for terminal diseases such as cancer or in the financial sector to speed up inter-market trading. Collectively, the quantum computing sector is worth trillions.<\/p>\n There are computations where the result of the first step becomes the input data for the next step and so forth. This is essentially a compounding calculation that grows more complex over time. Towards the hundredth sequence of calculation, the sheer amount of data generated can pose a heavy load on the system leading to a general slow down. A good example would be a macro in Excel sheet where the output serves as input for consequential computations. When left to run indefinitely, such a macro would eventually slow down the entire computer system.<\/p>\n This problem is also experienced in supercomputers where they can slow down under the weight of compounding computations. If you can check through a supercomputer’s logs, you can note consistently increasing processing periods. The nature of recalculating algorithms is that eventually, they’ll overload the system even in the most powerful computers.<\/p>\n A quantum computer can solve this problem easily because it can scale up its processing capability to match the increasing complexity of a computation. Thanks to its ability to create superpositions, a quantum computer has exponential processing potential. As such, it can linearly boost its processing capability.<\/p>\n Within the confines of a quantum environment, each increment in the complexity of the quantum algorithm prompts the quantum computer to create more entanglements and scale its computing ability to invest more processing power per calculation. Eventually, the difference between the algorithmic complexity and system capability is so small that these two elements are seemingly at par. In this way, the quantum computer can solve the problem of the immense workload resulting from compounding recalculating formulae.<\/p>\nFunctional Requirements of a Quantum Computer <\/strong><\/h3>\n
Applications of Quantum Computers<\/strong><\/h3>\n
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Real-life Quantum Computers<\/strong><\/h3>\n
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<\/p>\nTypes of Quantum Computers<\/strong><\/h3>\n
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Quantum Annealers <\/strong><\/h4>\n<\/li>\n<\/ol>\n
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Universal Quantum Computers<\/strong><\/h4>\n<\/li>\n<\/ol>\n
Value of the Quantum Computing Sector<\/strong><\/h3>\n
The Real Impact of Quantum Computers <\/strong><\/h3>\n
Most strategic applications of quantum computers <\/strong><\/h3>\n