Transcript

Hi! Welcome to QuBites, your bite-sized pieces of quantum computing. In this first episode, we’re going to talk about the basics of quantum computing and making sure we’re all on the same page. So, we’ll talk a little bit about quantum mechanics, but don’t worry, you don’t need to have a PhD in math or physics to follow along. We’re really focusing on applied quantum computing and the impact we’re already seeing today with quantum computing and especially quantum-inspired computing.

My name is Rene Schulte. I’m the Director of Global Innovation at Valorem Reply where I lead Research and Innovation and pretty much focus on emerging technologies and of course quantum computing is very much an emerging technology. I’m also a Microsoft Regional Director and MVP which are community awards provided by Microsoft independent experts that share their knowledge. So, I do a lot of conference speaking, open-source projects, blogging, and I’m very active on social media.

So, what does quantum computing actually mean? Well, I think it’s fair to say that it’s one of the most disruptive technologies that we’re seeing right now in the 21st century. The hardware stack is still a bit in its infancy, but again, already amazing progress has been done and I’m sure we will see amazing things in the next couple of years there. We’re going to mainly focus on the software stack because this is where we’re seeing huge impact already today and quantum computing in general allows us to solve problems that have been unsolvable before or have been unsolvable in non-linear time. So, quantum computing provides us the opportunity to solve challenges that are just too complex with classical computers.

So, all the big vendors are working on quantum computing technology stacks, partly hardware as well as software. If we’re looking at Microsoft with their Azure Quantum offering, they’re, of course, also having partners like INQ, Honeywell, and so on, that you can use as part of Azure Quantum. Also, Microsoft is working on their own research, especially with topological qubits, which might be the winning technology in the future, but again, very much in the research phase, but you can already apply for all the access for Azure Quantum and if you have a need, you might be able to also leverage some of the hardware Microsoft is working with. Microsoft being Microsoft and having a strong developer community and focus on the developer stack, they have amazing offerings here with their QDK, the Quantum Development Kit, as well as this new programming language called QuSharp.

So, what is quantum computing [actually] based on? Well, it’s based on laws of physics and quantum mechanics. Which are laws of physics which were developed around 100 years ago as theories. But since then all of these theories have been proven in experiments to actually be true. Some of these things might be a little bit spooky and sound weird, but it has been proven in experiments that this is really how our universe, how the world around us operates at the smallest scale. So, we’re talking about molecules, atoms, and a subatomic particle size like photons, electrons, and so on. If you go to the small dimension, certain behavior can be observed that is happening. For example, entanglement and super position. If we’re looking at classical computers, they’re dealing with bits. They can be off or on, zero or one. With quantum computers, our basic unit of information is the qubit, and a qubit can be in super position, which means it cannot just be zero or one, but it can be zero or one at the same time. It sounds crazy, but that’s the case. So, if you look on the visualization here with the sphere of the qubit, basically a qubit can be all the values on the sphere, not just the north and the south pole with zero or one, but all the values and in super position. The awesome part is you can even compute while a qubit is in superposition. You can apply certain operations and gates to use qubits and basically run these operations in parallel. You can represent multiple values at the same time basically, and you can store a lot of stuff and you can compute a lot of stuff in parallel, and that’s why we can solve these crazy problems in almost linear time for certain problems and make them actually solvable.

This other thing is called entanglement, which you can see on the slide here, which is actually the first photographic proof of entanglement. Basically, what it means is you can take these particles or qubits in this case and tangle them together and then they will stay connected even if you split them apart or send them in different directions, they will still somehow be connected. If you apply change to one of these that you have separated, they’re still entangled and you can observe the same change on the one that was actually separated, because they were entangled initially. You can take advantage of that with qubit entanglement and can do a lot of computations at the same time. It’s a crazy concept, but it works, and it was proven, again this is the first photographic proof of entanglement in 2019. Anyway, Albert Einstein called, especially entanglement, a spooky action at a distance, so he was very skeptical, but again, since then, all of that has been proven and we can use it for computation, which allows us to solve complex issues.

So, some of the key areas of quantum computing and the ones we’re going to focus on in this series are quantum machine learning, basically using machine learning on quantum computers. These are these huge complex problems and they’re well suited for quantum computing. Then, quantum security. Also, a super interesting topic, because we can take advantage of the characteristics of quantum mechanics. For example, if you have your particle in the superposition state, fi you want to measure it, if you want to get the value, it has to be collapsed. So, it will fall down to a zero or one state, and you can take advantage of that with quantum security. For example, imagine a key exchange. You need to send a secure key from A to B and if there is someone eavesdropping in the middle, you will know it at the end because the state will collapse, so you cannot clone it and eavesdropping is basically not possible. Also, of course quantum cryptography is a very interesting part, because we have to imagine that in a few years when we have quantum computers with a lot of qubits, all of the current cryptography algorithms like ours will be obsolete. They will all be crackable in a short amount of time. Therefore, post-quantum cryptography is a very relevant research topic.

Mainly, we’re going to talk about quantum optimization in the next few episodes and quantum optimization is especially relevant when we’re talking about quantum-inspired computing and quantum-inspired optimization. What that means is basically, you can take advantage of quantum mechanical behavior, but don’t run it on a quantum computer, but run these quantum-inspired algorithms on classical hardware, like high performance computing or GPUs and so on. You can already see that algorithms, quantum-inspired algorithms, are outpacing classical algorithms on classical hardware. So, you can run quantum-inspired algorithms on classical hardware that are even faster than your state of the old optimization algorithms. Why is that the case? Well, if we look at quantum-inspired optimization, let’s actually think about what the challenge is. What are we looking at? In general, you have a so-called objective function which is typically a cost-savings function. You want to reduce the cost of your parameters or you want to reduce the energy or increase fitness, whatever. If you look at the slide here, you can see the energy and we want to find the least amount of energy we have to spend to solve the problem. We want to find the global minimal, which is always a challenge. Especially with classical algorithms, you sometimes get stuck in the local minimal, the non-optimal way. With quantum-inspired optimization, we can take advantage of behaviors that can be observed in quantum-mechanics like quantum-annealing and the quantum-tunneling effect. So, instead of having to go up and getting to a new energy level to get over the hill, if you will, to find the global minimal, you can tunnel through it. That’s pretty amazing actually and that can only be observed with quantum computers. We can also simulate those with tunnel annealing and other things and run these quantum-inspired optimization algorithms also on classical hardware.

[Quantum optimization] is already providing a huge value. We’re looking at use cases for smart cities, 5G mobile networks, financial optimization, or think about public transport schedule. You need to optimize how many people can be transported and how many trains you can run and so on, or workforce management, assigning working tasks to people, or you have a fleet of vehicles out there in the field. You want to optimize how to reduce the cost there, or think about how you load a ship, a place, or truck. Optimizing the loading of these kind of pieces. Financial optimization, portfolio optimization, and quantum-chemical challenges like folding molecules and creating new pharmaceutical fertilizers and other chemical processes. So, that’s what we’re going to focus on in the next few episodes.

Thanks for your attention today. I hope you find the sessions interesting. Stay with us for the next few episodes that will be about quantum-inspired computing where we’ll show you real projects where we’re seeing impact already today. Thank you and feel free to reach out. Take care my friends and stay safe.