Industry / Tech/BioTech

Top Quantum Computing Trends Happening Right Now

  • Austin Still

    Austin holds a Bachelor of Commerce from the University of Saskatchewan and brings over 10 years of investing experience. With a belief the most important decision investors make when buying stocks is the price paid, Austin aims to blend growth with value by finding companies with accelerating growth combined with a discounted valuation. More specifically, Austin’s expertise lies in the technology sector, identifying businesses showing strong growth, a lasting competitive advantage, and sound fundamentals, paired with a valuation that supports further stock price appreciation.

    View all posts

Quantum computing has been a popular trend in sci-fi movies, entertaining viewers with the amazing ability to process vast amounts of information, solve problems once thought impossible, and change the world in a positive way.

Now, however, these sci-fi movies are becoming a reality as quantum computing technology is developing at a rapid pace.

And with the advancement of quantum tech comes the importance for investors to understand how this new technology will shape industries, change the status quo, and present great investment opportunities in the years ahead.

That’s why today, we’re going to dive into the current state of quantum computing, examining the past success of quantum computers to date. Then, we’ll shift our focus to the future and perform a deep analysis of the top quantum computing trends for investors to pay attention to today.

Quantum Supremacy & Past Milestones

An uncertain path to quantum supremacy | Kaspersky official blog

Image Source: An uncertain path to quantum supremacy | Kaspersky official blog

Before we dive into the top trends driving the industry forward, let’s first go over what quantum supremacy is, as well as the top developments within quantum computing that have been accomplished so far.

Quantum supremacy represents a pivotal moment in the field of quantum computing, marking the point in time when quantum computers will be able to solve computing problems faster than the most powerful classical computers. This concept, first proposed by John Preskill in 2012, has evolved from a theoretical speculation to an actual goal many companies are pursuing in the quantum computing industry.

Quantum Milestones Achieved

Google’s Quantum Breakthrough: In 2019, Google announced a major milestone. Their quantum computer, Sycamore, reportedly achieved quantum supremacy by performing a specific quantum computation in 200 seconds, a task that would’ve taken the most powerful supercomputer approximately 10,000 years to complete. And although the computational problem Google’s quantum computer solved did not have any business or societal use, this achievement was a significant step forward, demonstrating the potential of quantum computers to solve once-impossible computing problems.

China’s Advancements: China has also emerged as a major player in quantum computing. In 2020, a team of Chinese scientists claimed to have also achieved quantum supremacy using a different approach than Google, utilizing photons in a process called boson sampling. Their experiment demonstrated the potential of alternative quantum computing models.

Top Quantum Computing Trends for Next Year (and Beyond)

Now that we have a brief background on what’s been accomplished today let’s go over some of the most important (and realistic) trends that quantum computing offers to businesses, consumers, and investors.

From quantum communications to the integration with artificial intelligence, these trends will be a focal point for the industry in the years to come.

Improved Scalability in Quantum Computing

Why 'erasure' could be key to practical quantum computing- Princeton  Engineering

Image Source: Why ‘erasure’ could be key to practical quantum computing- Princeton Engineering | Engineering.Princeton

One of the most critical and promising trends in quantum computing systems is the advancement in scalability.

This trend has the potential to turn quantum computing from a highly specialized, experimental technology into a broadly applicable and powerful computational tool.

Advancing large-scale quantum computers’ scalability comes down to two main factors:

Increasing Qubit Count: The power of a quantum computer is largely determined by the number of qubits it can effectively utilize. Current quantum computers operate with a relatively small number of qubits. However, to solve more complex problems and outperform classical computers in a wider range of tasks, significantly increasing the qubit count is critical.

Types of Qubits: Research is ongoing into various types of qubits, such as superconducting qubits, trapped ion qubits, topological qubits, and more. Each type has its strengths and challenges in terms of coherence, control, and scalability. The choice of qubit technology will have a significant impact on the scalability of quantum computers moving forward.

So, what does this trend mean for an investor?

Very simply, improving scalability is the first step to quantum technologies being widely used across different industries. As of today, quantum computers are limited in their use case based on the complexity and high associated costs of using quantum tech.

However, as scalability improves, it won’t be long before companies in different industries will be able to use quantum solutions to help improve efficiencies and solve problems.

Think of this first trend as the initial step towards quantum computing becoming a mainstream technology that can be applied and implemented into operations regardless of what industry a company specializes in.

Quantum Networking & Communication

Explainer: What is quantum communication? | MIT Technology Review

Image Source: Explainer: What is quantum communication? | MIT Technology Review

One of the most intriguing and potentially transformative trends is the development of quantum networking and communication. This trend will be a true transformational shift in not just how we compute but also in how we transmit and secure information.

Utilizing the principles of quantum mechanics, quantum networking will revolutionize our approach to data transmission, offering new levels of security and efficiency.

The Essence of Quantum Networking

At the heart of quantum networking lies the phenomenon of quantum entanglement. This unique property of quantum mechanics allows particles like photons to be connected in such a way that the state of one instantly influences the other, regardless of the distance separating them. This principle can be harnessed for creating communication channels that are fundamentally different from classical networking.

Quantum networking isn’t just about sending traditional data; it’s about teleporting quantum states. This process, known as quantum teleportation, involves transferring the quantum information of one particle to another over a distance.

To be clear, quantum teleportation is not the kind of teleportation portrayed in sci-fi movies. Rather, it’s an actual scientific framework that would allow for the direct exchange of quantum information between different nodes of a network from longer distances.

While the thought of quantum teleportation may be hard to grasp, the potential use cases are far-reaching.

Below, we’ll highlight how quantum networking/teleportation could be used in today’s world.

Quantum Networking and Its Use Cases

The most important benefit of quantum networking is the potential for ultra-secure communications. Quantum Key Distribution (QKD) uses the principles of quantum mechanics to enable two parties to produce a shared random secret key, which can then be used to encrypt and decrypt messages, ensuring secure communication.

The nature of quantum mechanics is such that any attempt to eavesdrop on quantum communication would inevitably alter the state of the quantum bits, thus revealing the presence of the intruder. This makes quantum networks an incredibly valuable technology in the fields of cybersecurity, military communications, banking transactions, and even a quantum-based internet.

Challenges and Progress

While quantum networking is incredibly promising, there are still some significant challenges scientists must overcome before this technology becomes widely used.

Distance Limitations: Currently, one of the main challenges in quantum networking is the distance over which quantum states can be maintained. Quantum signals tend to degrade over distance, making long-range quantum networking a significant technical challenge.

Integration with Existing Infrastructure: Another challenge is integrating quantum networking technology with existing classical networks. This requires the development of new protocols and devices capable of handling both quantum and classical data. As of now, the blend between classical and quantum tech is limited. However, if quantum networking is to become a reality, scientists will need to find a way to blend these technologies together.

Quantum Machine Learning and Artificial Intelligence

How Quantum Computers Will Revolutionise Artificial Intelligence, Machine  Learning And Big Data | Bernard Marr

Image Source: How Quantum Computers Will Revolutionise Artificial Intelligence, Machine Learning And Big Data | Bernard Marr

The next promising trend is quantum machine learning (QML) and artificial intelligence (AI).

This development combines the unique strengths of quantum computing—such as handling complex calculations at great speed—with the advanced capabilities of AI, setting the stage for a series of exciting developments.

Quantum Machine Learning: A New Transformation

Quantum computers, with their ability to handle and process vast datasets much more efficiently than classical computers, open up countless new avenues in machine learning.

By harnessing the principles of quantum mechanics, quantum machine learning algorithms can process and analyze data in ways that are fundamentally different from classical algorithms. This capability is particularly significant for tasks involving vast datasets or complex computation, where quantum computers can perform calculations much faster than their classical counterparts.

One of the key advantages of quantum machine learning is its ability to handle high-dimensional data efficiently.

Classical computers struggle with the “curse of dimensionality,” where the computational power needed increases exponentially with the number of dimensions in the data. Quantum computers, however, can exploit quantum states to process multiple possibilities simultaneously.

This ability makes them exceptionally well-suited for tasks such as pattern recognition, optimization, and classification in high-dimensional spaces, which are common in areas like finance, genomics, and climate modeling.

AI’s Quantum Leap

Quantum computing also holds the promise of revolutionizing artificial intelligence by significantly speeding up computations.

One of the most important impacts is expected in the area of deep neural network training. Currently, training these networks is a time-intensive task, often requiring days or even weeks to complete. With quantum computing, this process could be expedited dramatically, leading to more rapid iterations and advancements in AI research and practical applications.

Beyond just speed, quantum AI also has the potential to address other challenges that are currently beyond the reach of classical AI. For instance, simulating complex molecular structures for drug discovery is a task of incredible computational complexity, often hindered by the limitations of classical computing.

Quantum computers, with their unique ability to model and process quantum data naturally, can significantly enhance the accuracy and speed of these simulations. This advancement could lead to breakthroughs in understanding diseases and developing new pharmaceuticals.

Challenges of AI/ML with Quantum Computing

Like any new tech, integrating quantum physics and AI/ML comes with roadblocks. Some of the biggest challenges facing this trend include:

Quantum Hardware Limitations and Scalability: Quantum computers are still in their developmental stages, and many are not yet powerful or stable enough for complex AI and ML tasks. Issues such as error rates, qubit coherence time, and the physical size of quantum computers pose significant challenges to these two technologies. 

Algorithm Development and Optimization: While quantum algorithms have the potential to solve certain problems more efficiently than classical algorithms, creating these algorithms is a highly complex and specialized field. Many AI and ML algorithms will need to be reimagined or entirely redesigned to take advantage of quantum computing. 

Hybrid Quantum-Classical Systems

What is Hybrid Quantum Computing?

Image Source: What is Hybrid Quantum Computing? | Ionq

By now, you’ve probably noticed that a pivotal factor in many quantum computing trends is the ability of classical and quantum computing to work together.

Quantum technology has incredible potential. However, if this new tech lacks the ability to utilize information from classical computers, the ability to adopt this technology and its use cases in different industries will be extremely limited.

That’s why our final quantum computing trend happening right now is the continued development of combining classical and quantum-based computers together.

The Convergence of Quantum and Classical Computing

The improvement of quantum and classical computing through hybrid systems represents an important development in computational technology. These systems combine the unique strengths of quantum and classical computers to tackle a broad range of problems more effectively than either could on its own.

Quantum computers, with their ability to perform calculations based on quantum mechanics principles, are particularly good at solving specific types of problems like optimization and factorization. These tasks, which are extremely challenging and time-consuming for classical computers, can be addressed much more efficiently by quantum systems.

On the other hand, classical computers remain unmatched in their ability to perform extensive data processing and execute error correction reliably. They are well-suited for tasks that require handling large volumes of data, sequential processing, and executing well-established algorithms.

In hybrid quantum-classical systems, the roles of quantum and classical computers are complementary. Quantum computers are utilized to perform calculations that are inherently quantum or can be significantly accelerated by quantum algorithms. These might include simulating quantum physical processes, factoring large numbers for cryptography, or solving complex optimization problems found in logistics and resource allocation.

Once the quantum computer has performed its part of the computation, the results are then transferred to a classical computer. The classical system takes over to handle further data processing, refinement, and error correction.

This division of labor allows for the efficient handling of tasks that would be impractical for either type of computer to perform independently.

Applications of The Hybrid System

Chemical and Materials Science Simulations: Quantum computers excel at simulating molecular and atomic interactions, a task that is extremely resource-intensive for classical computers. In a hybrid system, quantum computers can perform the complex simulations of molecular structures, while classical computers handle tasks like data analysis and error correction checks. This synergy can accelerate the discovery of new materials and drugs and better understand complex chemical reactions.

Optimization Problems: Many real-world problems, like logistics, supply chain management, and traffic flow optimization, can be modeled as optimization problems. Quantum computers can explore multiple solutions simultaneously due to their quantum properties. In a hybrid setup, a quantum computer can quickly explore a large solution space, and a classical computer can refine these solutions and manage the problem’s constraints. This approach can lead to more efficient solutions in sectors like transportation, manufacturing, and financial services.

Cryptography and Cybersecurity: Quantum computers are capable of breaking many traditional encryption methods, but they can also create new, more secure cryptographic protocols. In a hybrid system, a quantum computer could be used to develop and manage quantum encryption methods, which ensures secure communication channels that are theoretically immune to hacking. The classical computing part would handle regular data processing and the implementation of conventional security protocols. This combination will enhance overall security in digital communications, making it extremely difficult for unauthorized parties to intercept or decode sensitive information.

Current Limitations & Challenges

Compatibility Issues: One of the primary challenges in developing hybrid systems is ensuring compatibility between quantum and classical computing components. Quantum and classical computers operate on fundamentally different principles, making seamless integration hard. This includes difficulties in efficiently translating quantum data into a form that can be processed by classical computers and vice versa.

Error Rates and Coherence Time: Quantum computers are prone to errors due to quantum decoherence and noise, which affect the reliability of their computations. While classical computers in a hybrid setup can assist with error correction, the high error rates and short coherence times of qubits in current quantum systems still pose significant challenges.

Out of all the trends identified today, perhaps the most important is the ability of quantum computing to blend successfully with traditional computers.

If society is to benefit from quantum computing technologies, companies will need to be able to transition data and information from quantum computing software to other forms of computing platforms, particularly classical systems, effectively and efficiently.

This transition will require the development of robust interoperability standards and protocols that can seamlessly integrate quantum computing outputs into classical computing environments.


Quantum computing, highlighted by advancements in scalability, quantum networking, AI integration, and hybrid systems, is ushering in a new technological revolution.

Each trend addresses unique challenges and unlocks new opportunities, pushing the boundaries of what’s computationally possible.

While quantum computing is still developing, its integration with various fields promises transformative changes across industries, offering solutions to complex problems from healthcare to cybersecurity to finance.

This opens the door to a great investment opportunity for those who are investing in trends that will shape our technological future.

Finding trends that are driving quantum computing forward is obviously important. However, the next step for investors is to find the companies that are at the forefront of this new technology.

And to help with your investment research, check out a previous article highlighting the top quantum computing penny stocks on the market today.

While quantum computing presents a remarkable investment opportunity, it’s crucial for investors to approach this emerging field with a blend of enthusiasm and caution. Given its early stage, quantum computing involves a certain level of risk and uncertainty.

Therefore, investors should conduct detailed research and possibly consult with technology and financial experts to better understand the risks and rewards.

This approach will ensure that investments not only contribute to the advancement of this cutting-edge technology but are also aligned with your long-term financial goals and risk tolerance.


We are not brokers, investment, or financial advisers; you should not rely on the information herein as investment advice. If you are seeking personalized investment advice, please contact a qualified and registered broker, investment adviser, or financial adviser. You should not make any investment decisions based on our communications. Our stock profiles are intended to highlight certain companies for YOUR further investigation; they are NOT recommendations. The securities issued by the companies we profile should be considered high risk and, if you do invest, you may lose your entire investment. Please do your own research before investing, including reading the companies’ public filings, press releases, and risk disclosures. The company provided information in this profile, extracted from public filings, company websites, and other publicly available sources. We believe the sources and information are accurate and reliable but we cannot guarantee it. The commentary and opinions in this article are our own, so please do your own research.

Copyright © 2023 Edge Investments, All rights reserved.

  • Austin Still

    Austin holds a Bachelor of Commerce from the University of Saskatchewan and brings over 10 years of investing experience. With a belief the most important decision investors make when buying stocks is the price paid, Austin aims to blend growth with value by finding companies with accelerating growth combined with a discounted valuation. More specifically, Austin’s expertise lies in the technology sector, identifying businesses showing strong growth, a lasting competitive advantage, and sound fundamentals, paired with a valuation that supports further stock price appreciation.

    View all posts

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