Welcome to the world of quantum computing, a realm where the laws of physics as we know them take on a whole new meaning. Imagine a place where a particle can be in two places at once, or where information can travel faster than the speed of light. This is not science fiction, but the promising reality of quantum computing.

As of 2023, the quantum computing market is projected to reach $1.7 billion by 2026, demonstrating the incredible potential and industry confidence in this field.

In today’s blog, we will focus on a specific type of quantum computing called quantum annealing. Think of this as your friendly guide to understanding this complex technology, using everyday comparisons and stories to help make sense of it all.

What is Quantum Annealing in a Simple Response?

Quantum annealing is a method used in quantum computing to find the minimum value of a function, a task that is known as optimization. It’s like looking for the lowest point in a landscape of hills and valleys. In classical computing, the algorithm would have to hike over each hill and into every valley to find the lowest point. This is a time-consuming task. Quantum annealing, however, makes use of quantum properties to “tunnel” through the hills, effectively reducing the time it takes to find that lowest point.

Universal Gate Model vs Quantum Annealing

Quantum computing isn’t a one-size-fits-all proposition. There are different methods, each with their own strengths and weaknesses. Two of the main types are the Universal Gate Model and Quantum Annealing.

• Universal Gate Model: This is the quantum equivalent of a classical computer. If you imagine a classical computer as a complex LEGO set, where you can build anything you want from a set of basic blocks, a Universal Gate Model quantum computer is like having LEGO blocks that can exist in multiple places at the same time and interact in ways that defy conventional logic.
• Quantum Annealing: Quantum annealing, on the other hand, is a bit more specialized. Instead of a general-purpose quantum computer, it’s more like a highly skilled craftsman, specifically designed for optimization problems. It’s not as versatile as the Universal Gate Model, but it’s particularly good at what it does.

Optimization and Probabilistic Sampling Problems

Optimization problems are everywhere in real life: from finding the shortest route for a road trip, to scheduling tasks for maximum efficiency, to designing a new product with the minimum possible cost. These are the type of problems quantum annealing excels at solving.

Quantum annealing also shines in probabilistic sampling problems. These are situations where you need to generate a set of potential solutions that fit a certain criteria, with each solution having a certain probability. Think of it like rolling a loaded die: you’re not just interested in the most likely outcome, but in the distribution of all possible outcomes.

Real-World Application of Quantum Annealing

Quantum annealing isn’t just a theoretical concept. It’s being used in real-world applications today. For instance, Volkswagen used quantum annealing to optimize the routes of its buses in Lisbon during the Web Summit technology conference in 2018. The result was a 90% reduction in congestion, showing the power of this technology in action.

Sizes of Quantum Annealers and Gate Model QC

As of 2023, quantum computers vary in size. Some are as small as a single chip, while others are as large as an entire room. The size of a quantum computer depends largely on the number of quantum bits, or qubits, it contains. The more qubits,# Let’s find some recent stats about the size and capacity of quantum annealers and gate model quantum computers. search(“current size and capacity of quantum computers 2023”)