Ever heard of the word “quantum”? Ever wondered what it actually means? Quantum is a term widely used in physics. Quantum, in physics, is a distinct natural unit of energy, charge, momentum, or any physical quantity.
If we try to look around us and find the applications of this simple-looking concept, we will get to know that we are surrounded by things that use quantum. From fluorescent lights to lasers, from our mobile phones to GPS, even the whole concept of microbiology is based on this physical concept.
Now, if we look at quantum and its applications in the world of the future, i.e. in the technological world, we will find out that almost every mobile phone and computer use the concept of quantization.
But, there is something that is much more than just quantum, it’s when it is applied in the concept of computing, and the term “QUANTUM COMPUTING” is formed.
Let us move ahead and get to know what this quantum computing means.
Quantum Computing is the process of computing using the concept of quantum mechanics, or simply, it uses quantum mechanics to provide a massive leap forward in computation to solve specific problems.
Defining it more, we can say that the processing of information represented by special quantum states is known as quantum computing.
These devices manage knowledge in a radically different way than “classical” computers like smartphones, tablets, or even today's most efficient supercomputers, thanks to quantum phenomena like “superposition” and “entanglement.”
The working of quantum computers is based on the theory that explains the behavior of energy at atomic or subatomic levels.
Quantum computers can solve even the most complex of problems in seconds that even supercomputers take time to solve. This is a feat known as “Quantum supremacy”.
As we have dived in to get some more knowledge, let us start with the history of quantum computing.
As early as 1959, American physicist and Nobel laureate Richard Feynman observed that as electronic components approach microscopic sizes, quantum mechanics-predicted effects emerge, which he proposed could be exploited in the development of more efficient computers.
Quantum scientists are particularly interested in harnessing a process known as superposition. The theory of quantum computers progressed far beyond Feynman's early speculations during the 1980s and 1990s.
In 1985, David Deutsch of the University of Oxford described the construction of quantum logic gates for a universal quantum computer, and in 1994, AT&T's Peter Shor devised a quantum computer factoring algorithm that required as few as six qubits.
The first quantum computer (2-qubit) that could be loaded with data and output a solution was developed in 1998 by Isaac Chuang of the Los Alamos National Laboratory, Neil Gershenfeld of the Massachusetts Institute of Technology (MIT), and Mark Kubinec of the University of California at Berkeley. (source).
This was a major breakthrough in the world of computers, all of a sudden, there was something even faster than the supercomputers. Something that can perform the most complex of processes in seconds.
Till now everywhere, every organization has relied on supercomputers for the answers to complex problems, knowing that they are LARGE classical computers. They contain thousands of large CPU and GPU cores.
The problem was that they were not efficient in solving a certain kind of problem, which looks easy even to a human mind. That is where the need for quantum computers was felt.
For example, if there are 10 people around a dinner table and we have to figure out the sitting arrangement, what will we do? At first, it looks like a simple problem of permutations and combinations which it actually is.
But as we get the answer we realize that the no. of combinations we have to look into is more than 3 million for just 10 people. This is where most of the supercomputers get bowled out. This is where quantum computing came into light.
The reason why we felt the need for quantum computing is here now in front of our eyes-
Working memory on supercomputers is insufficient to hold the countless variations of real-world problems.
Each combination must be analyzed one by one by supercomputers, which can take a long time.
Now, we all want to know about the working of quantum computing. So, let’s have a look at it. Before that, you want to know can quantum computing be used in machine learning?
Although a quantum computer can be used without looking into its working, knowing how it works is necessary, given its valuable presence in the world of computers.
Quantum computers, in contrast to classical computers, perform calculations based on the likelihood of an object's state before it is calculated, rather than just 1s or 0s, allowing them to process exponentially more data.
They use the quantum principle of superposition to compute these huge data sets. These superpositions may become intertwined with those of other objects, implying that their final outcomes will be mathematically connected, even though we don't know what they are yet.
A classical computer uses bits to function, while a quantum computer uses q-bits or quantum bits.
The complicated mathematics behind these unsettled states of a coin spinning in the air can be plugged into special algorithms to solve problems in a fraction of the time it would take a traditional machine if they could ever calculate them.
If we look inside a quantum computer, we will get nostalgic about the first computer ever made, that is only because of the size of it. The smallest quantum computer that exists is of the size of a refrigerator.
These quantum computers are made up of superconductors and to keep these superconductors cool during the working, superfluids are used. These fluids collide the superfluids to the lowest temperature possible.
Then numerous processes take place with these superconductors including superposition and entanglement. Making the machine a perfect quantum computer.
Everything has its own pros and cons. The same is the case with quantum computing, following are its key advantages;
Speed: speed is the main reason why quantum computers are preferred over supercomputers, they perform large processes really fast.
Detailed analysis: it analyzes every individual data and keeps details with accuracy.
High potential: researchers believe that quantum computing will take AI to a next level, and will be a huge leap in the field of technology.
And, the disadvantages of Quantum computing are
Bulky Design and Large Size: The main disadvantage of this new form of technology is its bulky design and large size. It can’t be taken along with yourself anywhere.
Complex and Expensive: The complex design and high cost are other huge problems.
High error rate and less security- the systems are not that secure and there is always a threat. Also, the error rate is really high and needs to be fixed.
(Most related: What is Neuromorphic Computing?)
Quantum computing is used in various sectors as of now and aims to see a spike. The sectors where it is used are-
Logistics sectors- to find the optimal delivery route in different cities.
Finance sector- for balancing the risk of investment portfolios.
Medicine sector- pharmaceutical companies used them to stimulate molecules for better drug interaction, for example, supercomputing along with AI is used in Chemistry for drug discovery.
The other fields where quantum computing is used include:
Weather Forecasting and Climate Change.
Quantum Computing is another gateway to the future. Making lives simpler, allows us to believe in the possibilities of a better and convenient tomorrow.
Today if we are able to calculate the huge data of arrangements and still if we are able to calculate the most optimal ones among them, then thanks to quantum computing.
(Recommend blog: Cloud computing guide)
With the hope that the mere disadvantages will get rid of soon, let us have a belief together that quantum computing is the revolution of today and the gateway to tomorrow.
Elasticity of Demand and its TypesREAD MORE
5 Factors Influencing Consumer BehaviorREAD MORE
What is PESTLE Analysis? Everything you need to know about itREAD MORE
An Overview of Descriptive AnalysisREAD MORE
What is Managerial Economics? Definition, Types, Nature, Principles, and ScopeREAD MORE
5 Factors Affecting the Price Elasticity of Demand (PED)READ MORE
Dijkstra’s Algorithm: The Shortest Path AlgorithmREAD MORE
6 Major Branches of Artificial Intelligence (AI)READ MORE
Scope of Managerial EconomicsREAD MORE
7 Types of Statistical Analysis: Definition and ExplanationREAD MORE