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An Introduction To Quantum Computing And Its Applications

Published:

Quantum computing is a beautiful fusion of quantum physics and computer science. Many large companies, including Google, Intel, IBM, and Microsoft, are already in the race to develop quantum computers and offer cloud-based quantum computing services. Let’s learn more about quantum computing and its potential applications. 

What Is Quantum Computing?

In order to perform computations, one must first enter data, manipulate that data in accordance with predetermined requirements, and then output the results. In classical computation, we do so using bits, the basic unit of data. However, in quantum computation, we use quantum bits or qubits. Qubits are represented by the spin of an electron or the polarization of a photon. Therefore, they are represented by unit vectors. That is to say, they are measurable in terms of both magnitude and orientation. Since there are an endless number of unit vectors, there are an infinite number of qubits. However, each qubit can only be in one of two states, 0 or 1, depending on the direction in which it is measured. In quantum computing, these qubits and the rules of quantum physics are used to perform computations. 

Fundamentals of Quantum Computing

Superposition

Contrary to the binary nature of traditional bits (0 or 1, true or false, on or off), qubits can take on any combination or superposition of these bits. A qubit is represented as a0|b0⟩ + a1|b1⟩. When we measure in a particular direction, the qubit collapses to either |b0⟩ or |b1⟩. a02 is the probability of it belonging to state b0 and a12 is the probability of it belonging to state b1. The b0 and b1 are basis vectors that can be associated with the binary states 0 and 1. 

Entanglement

A quantum phenomenon known as entanglement occurs when two or more qubits interact with one another despite their separation in space. In other words, if you measure one qubit in one direction, it will have an effect on the other qubit as well. When this occurs, we say that the two qubits are entangled. 

The 2022 Nobel Prize in Physics was given to a group of pioneering physicists whose experiments established the cornerstones of quantum mechanics. Explore this topic in greater detail here.

Quantum Computing Models

A computational model specifies the mathematical steps required to derive a result from a given input. Models of quantum computing span a wide variety of categories. Let’s take a look at the most widely used quantum models.

Quantum Circuits

The most widely accepted model for quantum computing is a network of quantum gates or quantum circuits. Quantum circuits are an extension of classical circuits wherein we use qubits to compute the output given a set of inputs, via quantum gates or binary operators. There is a finite number of binary operations that can be performed on a set of classical circuit variables, but in the quantum world, the number of possible operations is limitless. For instance, while classical circuits are limited to just two reversible binary operators (Identity and NOT), quantum circuits can include an infinite number of such operators. It’s possible to think of quantum computation as a generalization of classical computation. Shor’s algorithm and Grover’s algorithm are only two examples of the many quantum algorithms invented by pioneering quantum physicists using a mix of these gates to bring quantum speedup to a wide variety of practical applications.

Quantum Annealing

Quantum annealing is an optimization process for finding the low-energy state or optimal state of a problem with many solutions. The concepts of quantum tunneling, entanglement, and superposition form the basis of this model. The best option is identified by identifying the one with the lowest energy level across all possible solutions. Quantum computers following the quantum annealing model are produced by a pioneering quantum computing company, D-Wave Systems.

Read about the top 10 quantum computing companies disrupting the quantum space here.

Applications Of Quantum Computing

Cryptography

Quantum cryptography is not only a promising new field of use for the rapidly developing field of quantum computing but an absolute necessity. Each step of an online transaction, from initiating a chat on Whatsapp to withdrawing money, is encrypted to protect the user’s anonymity and security. These encryption methods are thought to be unbreakable since cracking them using classical computing would require a significant investment of time and resources. Due to their superiority over classical computers in solving integer factorization problems, quantum computers can crack modern encryption methods in seconds utilizing Shor’s algorithm. As a result, scientists have developed Quantum Key Distribution (QKD), a novel kind of encryption that uses quantum mechanics. Companies working in the quantum space have created and are improving upon quantum cryptography standards. Additionally, work has been done to protect the current classical cryptography protocol from quantum attacks.  

Machine Learning 

Speed and storage for machine learning algorithms are greatly improved by quantum computers due to their ability to do computations and mathematical operations significantly more quickly than classical computers. While traditional machine learning techniques can identify and reproduce complicated statistical patterns within a dataset, quantum-enhanced machine learning techniques can do the same but with much more complexity. Improved optimization and the ability to generate correlations between variables that would be computationally costly to describe individually using traditional methods are two examples. Cloud-based quantum computing services with 50-100 qubits are now widely available from industry leaders like Amazon, Google, and IBM, allowing scientists, engineers, and other professionals to take advantage of this cutting-edge technology and speed up their network model calculations.  

Computational Chemistry and Biology

Substantial advances in quantum computing will have far-reaching implications for the fields of computational chemistry and biology. Both of these areas require extensive computational work. It can help with quantum chemistry calculations that need an explicit wave function representation due to a high degree of entanglement or other factors requiring extremely precise simulations of characteristics. Due to the exponential expansion in dimensions, traditional computers are unable to efficiently manage and store such large wave functions. The field of computational biology has many potential uses, from genomics to computer-aided drug discovery. Given an amino acid sequence, it may predict the protein’s three-dimensional structure, providing valuable insight into cellular components for biologists.


It is difficult to foresee the effects of quantum computers on our society, just as it was impossible to foresee the effects of computers on our society back in the 1950s. Many obstacles must yet be overcome before commercial, general-purpose quantum computers may be produced. Though still in its infancy, scientists and quantum computing companies are working tirelessly to develop quantum computers, which might fundamentally alter the future of computing.

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