In a fascinating episode of the Energy Transition Talks podcast, host Maida Zahid sits down with quantum computing expert Curtis Nybo to demystify this groundbreaking technology. As Director, Consulting Expert of AI and Quantum Computing at CGI, Curtis shares his insights into how quantum computing works, key applications in Energy & Utilities and its potential to revolutionize industries.

How is quantum computing different?

Classical computers process data using binary bits, which are physically represented by tiny electrical charges or transistors, acting as switches existing as either 0 or 1. Quantum computers, however, use qubits, which can be physically realized using subatomic particles, such as trapped ions, photons, or electron spins. These qubits leverage three unique quantum principles:

  • Superposition: Qubits can exist in multiple states simultaneously, vastly increasing computational power.
  • Entanglement: Qubits can be intrinsically linked across vast distances, allowing for coordinated computations.
  • Interference: Quantum computers use interference to amplify correct solutions while canceling out incorrect ones.

These properties allow quantum computers to process information in ways that classical computers cannot, leading to faster and more complex problem-solving capabilities.

Different types of quantum computers

Not all quantum computers function the same way. Curtis explains two primary types:

  • Quantum annealers: Ideal for optimization problems, these computers seek the lowest energy state in a system.
  • Gate-based quantum computers: More universal, these computers leverage quantum gates for tasks like cryptography, complex simulations, and material discovery.

Real-world applications: The Energy & Utilities sector

Quantum computing is not just theoretical—it’s already making an impact across industries. In the Energy & Utilities sector, some of the key applications include: 

  • Optimization of infrastructure: Quantum annealing can help solve complex optimization problems, such as power grid efficiency, energy distribution, and load balancing. Ensuring more sustainable and cost-effective energy management.
  • Oil and gas optimization: Quantum computing can enhance subsurface modeling, reservoir simulations, and supply chain logistics, reducing environmental impact.
  • Battery technology: Quantum simulations can help discover new materials for high-density, more efficient batteries.
  • Renewable energy storage: Understanding battery chemistry at an atomic level can lead to better energy storage solutions for solar and wind energy.
  • Hydrogen fuel cells & carbon capture: Quantum computing aids in optimizing catalysts for hydrogen fuel cells and modeling carbon capture molecules for cleaner energy solutions.
  • Cybersecurity for critical infrastructure: Quantum cryptography can secure energy grids and infrastructure against future cyber threats, ensuring reliability and resilience.
     

"Quantum computers enable us to simulate molecules with much greater precision, opening doors to new materials and energy storage solutions." 

The future of quantum computing

While quantum computing isn’t a “magic solution” to all computing challenges, its potential is undeniable. Industries like pharmaceuticals, materials science and energy are already leveraging quantum advancements to push the boundaries of innovation.

As Curtis emphasizes, this is just the beginning of the quantum era, as the technology continues to evolve and unlock new possibilities. Stay tuned for part two of the discussion, coming soon.

Listen to other podcasts in this series to learn more about the energy transition

Read the transcript

1. Introduction
2. What is quantum computing?

Maida Zahid:
Thanks, Curtis. I’m very excited to have you here today. This is a really cool topic and very abstract for sure. As we get into it, can you kick it off by telling us what quantum computing even is?

Curtis Nybo:
Yeah, absolutely. It is quite abstract and it's a very exciting field. I get really pumped up about it when I talk about it. And as I go through it, feel free to interject and ask any questions. But what we'll probably do is compare it to classical computing and go through the differences between quantum and classical computing.

3. Differences between classical and quantum computing

Quantum computing is a relatively new field that leverages the principles of quantum mechanics to process information in fundamentally new ways. Although it's not really new—it has been around since about 1981—Richard Feynman and Paul Benioff, two well-renowned physicists, started thinking about how to simulate quantum phenomena more accurately than using conventional computing models. They built the framework for quantum computing and soon realized that it was quite effective at solving complex computational problems, in addition to simulating quantum phenomena.

To understand the difference between classical and quantum computers, let’s start with how classical computers work. A classical computer processes information using bits, which are in one of two states—either zero or one. Every operation is performed using this binary logic. The way these zeros and ones occur is through flipping a switch in your CPU or applying a voltage to a switch to execute calculations. 

A quantum computer, on the other hand, is similar in some ways but does not use classical bits. Instead, it uses quantum bits, or qubits. Qubits take advantage of several quantum mechanical phenomena. We’ll focus on three today: superposition, entanglement, and interference.  

4. Superposition, entanglement and interference: Quantum mechanical phenomena

Superposition allows qubits to exist in both the zero and one state simultaneously, unlike classical bits, which can only be in one state at a time. So if you imagine flipping a coin, a classical computer would register either heads or tails. In a quantum system, it’s like the coin is spinning in the air, existing in both heads and tails until it is observed or measured. This ability to exist in multiple states at once allows quantum computers to process multiple values simultaneously.

Entanglement is another crucial phenomenon. When two qubits become entangled, their states become intrinsically linked, regardless of the distance between them. If you measure one qubit, the state of the other is instantly determined, even if they are separated by vast distances. Einstein called this phenomenon “spooky action at a distance.” However, it does not allow faster-than-light travel because no actual information is transmitted between the entangled particles.

Interference plays a critical role in ensuring that quantum computers reach the correct answer efficiently. Qubits interfere with each other, canceling out incorrect solutions and amplifying the probability of the correct ones, similar to how waves in a pond interact.

Hopefully, that explanation helps, Maida. That was a lot of information!

5. Different types of quantum computers

Maida Zahid:
That was a lot, but it was very fascinating! The theory behind it is very applicable. That takes me to my next question: can you help take that theory and apply it to real-world use cases? What industries are applying these technologies? Let’s start with the Energy & Utilities sector.

Curtis Nybo:
Sure! Before talking about specific use cases, it’s important to note that there are different types of quantum computers. They are usually split between quantum annealers and gate-based quantum computers.

Quantum annealers use quantum fluctuations to find the global minimum of a given objective function, helping to solve optimization problems. They leverage the fundamental rule in physics that everything seeks a minimum energy state. They also use quantum tunneling, which allows particles to pass through an energy barrier even when they don’t have enough classical energy to overcome it.

Gate-based quantum computers, on the other hand, are more universal and operate similarly to classical computers but with quantum logic gates. They can handle cryptography, simulation problems, and a broader variety of computational problems.

Quantum computing applications in the Energy & Utilities sector

Now, in the Energy & Utilities sector, quantum computing has significant applications. One of the primary areas is simulating quantum mechanical systems. Richard Feynman originally proposed quantum computing to solve the Schrödinger equation, which describes quantum systems. Classical computers struggle to model large molecules accurately, but quantum computers can solve these equations precisely.

This is crucial for developments in battery technology, drug discovery and material science. For example, quantum computers can simulate different battery chemistries at an atomic level, leading to the discovery of new battery materials with higher energy densities and better electrode stability. This has major implications for electric vehicles and renewable energy storage.

Additionally, quantum computing is aiding in hydrogen fuel cell research by identifying new catalysts. It is also helping improve solar panel efficiency by optimizing photovoltaic materials. In Oil and oas, quantum computing is contributing to advancements in carbon capture technology by modeling molecular interactions more accurately.

That said, quantum computing is not a silver bullet or magic solution, but it is proving to be incredibly powerful in solving problems that classical computers struggle with.

Maida Zahid:
Well, thank you for your time, Curtis, and thanks, everybody, for listening. You can find the rest of the episodes in our series on CGI.com, and you can subscribe to our podcast on Apple Podcasts, Spotify, or wherever you get your podcasts. Thanks very much!