In this blog, we discuss quantum fluids and their unique properties. We delve into the concept of quantum fluids, explain how they differ from classical fluids, and showcase some of their fascinating properties. This well-researched blog provides an easy-to-follow overview of this fascinating topic, making it a valuable resource for anyone interested in the field of quantum fluids.
In this interview, we sat down with Elisa to learn more about the story behind Girls in Quantum, the organization's mission and vision, some real-life stories, and the challenges girls and women are facing in the field of quantum computing.
Last week, on 24 October, we officially launched our software named Quanscient.allsolve. From speed and scalability to the affordable pricing model, this article will give you an overview of the key features and highlight the benefits from different perspectives.
Recently, we achieved a significant milestone here at Quanscient in quantum-native multiphysics simulations. By quantum native, we mean that the algorithm encodes the physics of the original problem, in some sense, directly into the quantum system. That is, in a quantum-native simulation, we have a clear and direct analogy between the evolution of the quantum system and the process it models. The milestone we achieved marks the dawn of a new era in multiphysics simulations.
Quantum mechanics has been a hot topic for quite some time now. To be fair, how could it not with the bizarre physical principles and the immense possibilities it provides in computations. Through the lens of one of our quantum mathematicians, Dr. Ossi Niemimäki, this article takes a standpoint on what it means to understand quantum mechanics and why we don’t need to do so — at least in the sense that you might think.
Where does finite-element analysis (FEA) originate from? What kind of math is there behind it? Why is abstract nonsense important to what we do at Quanscient? In this somewhat different blog post, we look at the interesting history and development of FEA, particularly from the viewpoint of electrical engineering. This is the story of FEA and thus the pre-history of Quanscient. Let’s dive in!
In our latest blog, we painted a picture of what the future of simulations could look like in the era of quantum computing. In this blog article, we go over what is achievable now, and why you, as an engineer, scientist, or product designer should care.
Computer-aided engineering (CAE) has come a long way. With the increased interest and development in cloud scaling, the speed and accuracy of these simulations will see a drastic improvement. Finally, as quantum computers are lurking behind the corner, the R&D processes and CAE as we know them will forever be transformed. This article will first rewind the clock to see where we came from to eventually give you a glimpse of what is yet to come. Better hold on to your seats — this might get rowdy.
Quantum advantage and quantum supremacy are words often thrown around, but what exactly do they mean, and what is the difference between them? This article aims to shed light on these questions and straighten out some of the misconceptions. At the least, we are stating our policy for the usage of these terms in previous and upcoming blog articles and other communications.
The future of quantum computing is one of the most exciting open questions, as the timing for the physical implementation of a useful quantum computer, among other things, is still a question mark. This article will look at one of the most popular approaches: superconducting qubits. By the end, we will have a better understanding of what superconducting qubits are and why they might be the way to go.
The invention of the computer changed everything. Now, with the advancements in quantum computing, we are yet again on the brink of another revolution. Hop on as we skim through some of the most outstanding achievements in human technology — and take a glimpse at what is yet to come.
Superconductors are awesome. This article will take you through their amazing properties and showcase some of their innovative applications. Also, we’re going to explain why modeling them is so difficult - and why neglecting to do so can turn out to be costly.