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In AI Last updated: April 21, 2023
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There is a lot of hype about quantum computing – about how it’s an exciting field and revolutionizing how we solve complex problems in various industries. Both statements hold true as quantum computing represents a new way to process information.

Organizations around the world are devoting significant resources toward the development of quantum computing technologies because of their capability to consider many possibilities and proffer potential solutions to complex problems.

What is Quantum Computing?


Quantum computing is a computer science field based on the principle of quantum physics (the study of how atomic particles exist and interact with each other). It explains the behavior of matter and energy on the atomic and subatomic levels.

Quantum computers use quantum bits or qubits (pronounced cue-bits), which can exist simultaneously in multiple states. This property allows quantum computers to solve problems that would take conventional computers an impractical amount of time or computational resources.

How does Quantum Computing Work?

Quantum computing uses qubits to develop quantum computers comprising quantum systems like photons and electrons. They are often used to perform computations that would ordinarily be impractical for classical computers. Additionally, quantum computing uses quantum logic gates to manipulate qubits and perform computations.

Quantum gates are analogous to the logic gates used in classical computers but operate on quantum bits – researchers use them to create and manipulate superpositions and entangle qubits.

It strives to improve computing capabilities and solve the complex problems that today’s classical computers cannot solve due to their binary approach and limited existence in two states – 0 and 1, whereas quantum computing can assume both states simultaneously.

Difference between Quantum Computing and Classic Computing

Quantum computing and classic computing differences lie in their computing capabilities and how they operate. While quantum computing is based on quantum theory.

Classical computing is based on binary digits or bits, which can take on the value of either 0 or 1. Quantum computers use qubits as their unit of data. Quantum computing could take on both values (0s and 1s) simultaneously — this act is known as superposition. A property that allows quantum computers to assume two states at once.

When it comes to power, classical computing has lesser computing power than quantum computing because its power increases based on 1:1 relationship with the available transistors. For quantum computing, power increases significantly based on the number of qubits.

Unlike classical computing, which can be implemented with codes written in programming languages like Java, SQL, PHP, C#, C++, and Python, among others, quantum computing combines code, mathematics, physics, and algorithms to serve its specific purpose.

Due to its complex architecture, fragility, and high development and implementation cost, quantum computing isn’t created as a general-purpose machine for public usage, they are designed for a specific purpose and use case. On the other hand, classical computers are widespread and easily accessible.

Quantum computers have higher error rates than classical computing and require extra care, such as being kept in an ultra-cold room to regulate heat. In contrast, classical computers can function at room temperature.

In terms of usability, quantum computing is suitable for complex tasks like simulation, optimization, machine learning, and other resource-intensive operations. Classical computing is suitable for tasks like word processing, spreadsheet calculations, and other non-resource-intensive tasks.

Benefits of Quantum Computing

The benefits of quantum computing are enormous when used correctly. We analyzed the top merits below.

  • Speed: They can process data a thousand times faster than conventional computers.
  • Security: Its algorithm can be used to improve digital encryption and protect an organization’s IT infrastructure.
  • Ability to solve complex problems: In 2019, Google claimed its Sycamore – a 54-qubit processor – performed a computation that would take the world’s fastest supercomputer 10,000 years to complete in 200 seconds.
  • Improve fraud detection: Financial institutions can use quantum computing to create better trading simulators, design efficient investment portfolios, and improve fraud detection.
  • Research: It helps scientists develop better models and approaches to solving problems in various industries, such as drug research in healthcare and chemical discovery in manufacturing.

Features of Quantum Computing


The following are the key features of quantum computing.


The ability of quantum systems to exist simultaneously in numerous states is known as superposition. Classical computers can only exist in one state at a time (0 or 1), meaning they lack superposition capability.


Entanglement occurs when two qubits are linked together, and the state of one particle affects the other, even though they are miles apart. It is often used to create a quantum network, allowing quantum computers to share information.

Interference In quantum systems, interference is a byproduct of superposition. It’s a wave phenomenon that occurs when subatomic particles interact with and influence.

It can either be constructive (when the waves reinforce each other or amplifies the right answer) or destructive (when they cancel each other out).



Quantum systems are fragile and sensitive to their surroundings; interferences from their environments can cause the quantum behavior of qubits to decay – making them lose their quantum capabilities.

For instance, noise can cause qubits to fall out of superposition. Not only that, even temperature changes can impact its performance. Hence the need to keep it in a highly regulated and controlled environment.

Limitations and Challenges of Quantum Computing

While quantum computing offers many advantages, it also has some drawbacks worth mentioning.

  • Decoherence: Unlike classical computers, quantum computers are sensitive to noise. Disturbance can cause it to fall out of superposition before it can complete its tasks.
  • Requires a specialist: Due to its complexity, it requires a diverse pool of quantum specialists.
  • Quantum error correction: Errors are likely to happen during computing operations, leading to questionable outputs. A fault-tolerant quantum system is required to withstand interference from surroundings.

Real-Life Applications and Uses of Quantum Computing

#1. Financial modeling


The financial market is volatile and highly unpredictable. With quantum computing, financial organizations can simulate financial systems and use the technology to model investments based on expected returns.

It can also be used in the aspects of portfolio optimization, risk reduction, and management, plus option pricing. Those who perform high-volume transactions can leverage quantum computing to predict markets and analyze the global financial economy.

#2. Logistics optimization

Quantum computers excel when it comes to gathering real-time data to optimize supply chain logistics, inventory, and transportation. Organizations need to continuously calculate and recalculate optimal routes of traffic management, fleet operations, air traffic control, freight, and distribution – this is doable with classical computing.

But for large organizations with complex supply chain needs, this process can become resource intensive, and quantum computing can be able to rescue the situation.

#3. Better batteries

With electric vehicles (EVs) becoming commonplace in our society, manufacturers are using quantum computing capability to simulate the behavior of molecules and materials and understand lithium compounds and battery chemistry in order to optimize batteries’ life span.

Aside from EVs, quantum computing also has applications in renewable energy storage and mobile devices.

#4. Manufacturing

Quantum computing is used to improve many aspects of manufacturing. An expert insight released by IBM Institute for Business Value divided quantum computing use cases in manufacturing into four categories.


  • Chemistry
  • Materials science
  • Condensed matter physics


  • Finite difference analysis
  • Structural analysis Hydro/aerodynamics


  • Optimization
  • Machine learning
  • Classification


  • Supply chain
  • optimization
  • Risk modeling

Those who adopt quantum computing in these key areas will gain a decisive edge, as it will help reduce manufacturing costs and increase production speed.

#5. Climate models development

Quantum computing could help solve persistent sustainability problems like climate change. According to Intergovernmental Panel on Climate Change (IPCC) report, greenhouse gas emissions must be significantly reduced before 2025 to avoid major climate catastrophes. Quantum computing can be used to reduce climate impact.

Ammonia manufacturing contributes between 1 and 2% of global carbon dioxide emissions — quantum computing can help be used to develop alternative clean energy, such as better batteries for electric vehicles, solar energy, and more, in order to facilitate the process of earth decarbonization. It can also facilitate model improvements in climate and weather forecasting as well as grid management.

#6. Automotive industry

The automotive industry is rapidly adopting quantum computing technology, this is evident in partnerships between quantum computing companies and car manufacturers, including D-Wave Systems and Volkswagen; Zapata Computing and Bosch; and even IBM Quantum and Mercedes-Benz.

Original equipment manufacturers (OEM) are looking to leverage quantum computing for route optimization and enhance material durability.

#7. Aircraft development

Aerospace companies can leverage quantum computing for many processes, from flight plan optimization to aircraft modeling and digitization. Airbus, an aerospace corporation that designs, manufactures, and sells commercial aircraft, invested in IonQ, Q-CTRL, and QC Ware to leverage quantum technologies in developing complex aircraft models.

#8. Drug development


Classical computers are currently used to run hundreds of millions of molecular simulations, but there’s a limit to the molecule size they can compute. Quantum computing allows research and development to simulate large and complex molecules to improve computer-assisted drug discovery (CADD).

McKinsey & Company reported in 2021 that pharma spends about 15 percent of its sales on R&D, which accounts for over 20 percent of total R&D spending across all industries worldwide.

This investment, in part, helps the pharmaceutical industry find efficient ways to develop micromolecules and macromolecules to help cure illnesses and diseases. With quantum computing, researchers can fail fast and accelerate the development of drugs with a higher chance of success.

#9. Machine learning

The ability of quantum computers to process large and complex data makes them a good candidate for machine learning. Quantum machine learning is a field of study that integrates quantum algorithms with machine learning programs.

Quantum algorithms can have a polynomial or super-polynomial (exponential) speed-up, which improves computational speed. With quantum machine learning, data practitioners can develop faster and more advanced algorithms, solve complex data patterns, and advance the development of computer vision applications and reinforcement learning.

Learning Resources: Quantum Computing

For further learning, we recommend the following resources.

#1. Dancing with Qubits

Authored by Robert S. Sutor, this book explains how quantum computing works and applies to scientific computing and AI. Dancing with Qubits covers the differences between classical and quantum computing and describes its use cases in various industries.

Readers will also learn concepts such as superposition, entanglement, and interference, as well as circuits and algorithms. This resource will teach you about the basics and essentials of quantum computing.

#2. Quantum Computing: An Applied Approach

Written by the CEO of SandboxAQ (Jack D. Hidary), a quantum technology company – this material combines the theory and practicality of quantum computing, including hands-on code.

Preview Product Rating Price
Quantum Computing: An Applied Approach Quantum Computing: An Applied Approach $25.49

The book has three parts: Part one covers quantum computing and quantum circuits basics, the second part explains quantum computing algorithms and provides code on current quantum computing methods, and part three covers the mathematical aspects of quantum computing.

#3. Quantum Computing for Everyone

Beginners looking for all-inclusive material will find this resource beneficial. It covers the basics of quantum computing and explains its key components, such as qubits, entanglement, and quantum teleportation.

Preview Product Rating Price
Quantum Computing for Everyone Quantum Computing for Everyone $11.99

The author of this book, Chris Bernhardt, simplifies the mathematics behind quantum computing and also explains how quantum computers are built, making it easy for those who are new to quantum computers to understand the process of developing the systems.


Companies like Google, IBM, and Microsoft are leading the innovation of quantum computing solutions — universities are also not left behind. The shortage of quantum computing specialists contributes to its slow progress, plus the cost of building a quantum computer is high, and not many organizations have the resources it takes to create one.

While quantum computing holds many promises, it’s not there yet. It will take a few years to realize its full potential and become commonplace like classical computers. 

You may also read about Fog Computing.

  • Aminu Abdullahi
    Aminu Abdullahi is an experienced B2B technology and finance writer and award-winning public speaker. He is the co-author of the e-book, The Ultimate Creativity Playbook, and has written for various publications, including Geekflare,… read more
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