Today we are living with technologies like Artificial Intelligence, Cloud Computing, Robotics and Quantum Computing. This is just the beginning of these technologies, as they advance, there will be a lot of difference between our today and tomorrow. Quantum computing technology has not yet been fully developed, but what was once the subject of science fiction is now an emerging reality.
This revolutionary technology uses the principles of quantum mechanics to perform calculations previously unimaginable with classical computers. Quantum computers built on this technology are many times faster and more accurate than today’s computers. In this article, we will delve deeper into the world of quantum computing, exploring its concepts, capabilities, applications, and the challenges it presents.
Before proceeding further about quantum computers, it is important to know about some terms related to quantum so that its entire concept can be understood well. These terms include quantum bits, quantum supremacy.
Understanding Quantum Bits (Qubits)
Just as bits are at the core of today’s classical computers, qubits are at the core of quantum computing. Unlike classical bits, which can be 0 or 1, qubits can exist in multiple states simultaneously, due to a phenomenon called superposition. Due to this, quantum computers can process large amounts of information at the same time.
Quantum supremacy: what does it mean?
Quantum supremacy is the point where quantum computers outperform the most advanced classical supercomputers. It is said that in this state, quantum computers could be thousands of times faster than today’s most advanced supercomputers. Google claimed to have achieved this feat in 2019, although the debate continues.
Quantum vs Classical computer
To understand the potential of quantum technology it is necessary to compare quantum and classical computing. Quantum computers excel at solving specific problems, such as factorization and optimization, that would take classical computers ages to solve. However, for everyday tasks, classical computers are more efficient. There are several differences between the two which are given in the table below.
|Features||Classical Computer||Quantum Computer|
|Information storage||Information storage is based on “bit”||Information storage is based on Quantum Bit or “qubit”|
|Circuit behavior||Governed by classical physics||Governed by quantum physics or quantum mechanics.|
|Data processing||It is done in Central Processing Unit or CPU||It is done in Quantum Processing Unit or QPU|
|State||Either 0 or 1||Can be in multiple states simultaneously (superposition)|
|Speed||Limited by classical physics||Perform calculations much faster than classical computers|
|Error sensitivity||Not as sensitive||Extremely sensitive to noise and errors|
|Memory||Stored in binary digits||Stored in qubits|
|Entanglement||Not possible||Allows two or more qubits to be correlated|
|Logical Operations||Boolean Logic (AND, OR, NOT)||Quantum Gates (Hadamard, CNOT, etc.)|
|Applications||Software, gaming, simulations, etc.||Cryptography, chemistry, machine learning, etc.|
Quantum Algorithms and Their Applications
Quantum algorithms are special algorithms designed to run on quantum computers. However, quantum computing technology is still developing, and many of the algorithms below are in the research and development stage.
1. Shor’s algorithm
- Application: Integer Factorization
- Significance: Shor’s algorithm can factorize large numbers faster than the most famous classical algorithms.
2. Grover’s Algorithm:
- Application: Unstructured Search
- Significance: Grover’s algorithm can search an unsorted database of N items in O(√N) time. It has applications in optimization and database search problems.
3. Quantum Simulation:
- Application: Simulation of Quantum Systems
- Significance: It is used in materials science, drug discovery and understanding fundamental physics.
4. HHL Algorithm (Harrow-Hassidim-Lloyd Algorithm):
- Application: Solving Linear Systems of Equations
- Significance: It provides potentially exponential speedup for solving linear systems. It has applications in fields such as optimization, machine learning and quantum chemistry.
5. Quantum Approximate Optimization Algorithm (QAOA):
- Application: Combinatorial Optimization Problems
- Significance: It has potential applications in logistics, finance and supply chain management.
6. Quantum Machine Learning Algorithms:
- Applications: Machine Learning and Artificial Intelligence
- Significance: It speeds up tasks like training, clustering and classification of quantum neural networks.
7. Quantum Chemistry Algorithms:
- Application: Molecular Simulation
- Significance: Quantum computers can simulate complex molecular systems with high accuracy. It is important for drug discovery, material design and understanding chemical reactions.
Building Quantum Computers
Building a quantum computer is a complex process. It requires expertise in physics, engineering and computer science. These computers are quite different from today’s classical computer technology, they involve manipulating and exploiting the properties of quantum bits.
Building a quantum computer includes various processes like selecting Qubit Technology, Creating and Manipulating Qubit, Quantum Gate Operations, Qubit Interconnectivity, Error Correction and Quantum Software Development. Each of these processes is very complex and research is going on.
Companies like IBM, Google and Righetti are actively working on creating quantum processors. But Google is at the forefront in this technology race. According to some reports, Google has achieved quantum supremacy, although this is still under debate.
The latest Quantum system of Google has a total of 70 operational qubits that allow calculations to be performed at astonishing speeds. According to Google, the Frontier supercomputer will take only 6.18 seconds to perform the calculation with Google’s 53-qubit computer. However, it would take a staggering 47.2 years for the same machine to match the calculations performed by Google’s latest 70-qubit device.
Challenges and Limitations
Any new technology along with possibilities also brings challenges and limitations. Quantum computing also has great potential but faces challenges such as qubit stability, error correction, and maintaining quantum state for extended periods. Solving these is essential for practical quantum computing, and researchers and engineers are actively working on this.
Quantum computer Applications in various fields
Quantum computers are thousands of times faster than today’s supercomputers, so obviously their applications also have the potential to bring revolution. From cyber security, machine learning and AI to drug discovery, we can actively use this technology. Let us know about their applications:
Cryptography and Cyber Security:
Cyber security is extremely important in today’s digital age. For this, most social media, finance or payment companies use cryptography technology for secure communication. But quantum computers can break many encryption methods currently in use. However, they could also enable the development of quantum-safe encryption algorithms.
Example: When you send a message on WhatsApp, it gets converted into encrypted form. With this, no third party will be able to see your messages. With the help of quantum technology, this facility can become even more secure.
Drug Discovery and Materials Science:
Quantum computers can simulate molecular and chemical interactions with high precision using quantum chemistry algorithms and quantum simulations. This capability could significantly speed up drug discovery. This will help in finding new drugs and materials for various applications.
Quantum computers excel at solving complex optimization problems, such as route optimization for logistics, supply chain management, and portfolio optimization in finance.
Machine Learning and AI:
Quantum machine learning algorithms can process and analyze huge datasets more efficiently. This could lead to breakthroughs in AI, including better natural language processing and image recognition.
Today, machine learning and AI based applications dominate the market. These reduce human intervention and perform any task more efficiently. When quantum and AI join hands, they will change the world.
Quantum computing can optimize financial models and risk analysis. Its applications can lead to faster and more accurate predictions in the stock market, investment strategies and risk management. However, with this the responsibilities of cyber security are also going to increase.
- Climate Modeling and Simulation
- Quantum Chemistry
- Supply Chain and Inventory Management
- Astronomy and Space Exploration
- Health care and personalized medicine
- Energy and Materials Science
- Traffic and Urban Planning
- Advanced Cryptanalysis
- Scientific Research and Discovery
Frequently Asked questions
Quantum computing is primarily in the hands of research institutes and tech giants. But access is increasing with cloud-based quantum computing services.
Yes, quantum computers are a threat to current encryption methods. Researchers are working on post-quantum encryption to address this challenge.
Quantum computing could lead to advances in drug discovery, climate modeling, and personalized medicine, among other areas.
A quantum computer is a type of computer that uses the principles of quantum mechanics to perform certain types of calculations much faster than classical computers
Quantum entanglement is a phenomenon where the state of one qubit is dependent on the state of another, even when separated by large distances. It plays an important role in quantum computing and quantum communication.
Yes, quantum computers have the ability to break widely used encryption algorithms like RSA and ECC. This has led to the development of post-quantum cryptography to protect against quantum attacks.
Quantum programming languages and software libraries, such as Kiskit, Cirk, and Kuiper, are available for programming quantum computers. You can access cloud-based quantum processors to run your quantum programs.
The name of the quantum processor created by Google’s Artificial Intelligence Division is Sycamore. It currently holds 70 qubits and is approximately 241 million times more powerful than the previous model.