Lifeboat Foundation

Topological superconductors are superconducting materials with unique characteristics, including the appearance of so-called in-gap Majorana states. These bound states can serve as qubits, making topological superconductors particularly promising for the creation of quantum computing technologies.

Some physicists have recently been exploring the potential for creating quantum systems that integrate superconductors with swirling configurations of atomic magnetic dipoles (spins), known as quantum skyrmion crystals. Most of these efforts suggested sandwiching quantum skyrmion crystals between superconductors to achieve topological superconductivity.

Kristian Mæland and Asle Sudbø, two researchers at the Norwegian University of Science and Technology, have recently proposed an alternative model system of topological superconductivity, which does not contain superconducting materials. This theoretical model, introduced in Physical Review Letters, would instead use a sandwich structure of a heavy metal, a magnetic insulator, and a normal metal, where the heavy metal induces a quantum skyrmion crystal in the magnetic insulator.

Advances in quantum computation for electronic structure, and particularly heuristic quantum algorithms, create an ongoing need to characterize the performance and limitations of these methods. Here we discuss some potential pitfalls connected with the use of hardware-efficient Ansätze in variational quantum simulations of electronic structure. We illustrate that hardware-efficient Ansätze may break Hamiltonian symmetries and yield nondifferentiable potential energy curves, in addition to the well-known difficulty of optimizing variational parameters. We discuss the interplay between these limitations by carrying out a comparative analysis of hardware-efficient Ansätze versus unitary coupled cluster and full configuration interaction, and of second-and first-quantization strategies to encode Fermionic degrees of freedom to qubits.

Computer simulations of a human brain under the influence of LSD show that entropy increases the most in regions responsible for processing vision and integrating sensory information.

By Karmela Padavic-Callaghan

Understanding the interactions between quantum physics and gravity within a black hole is one of the thorniest problems in physics, but quantum computers could soon offer an answer.

By Alex Wilkins

Universal computation has significant real-world implications in fields such as computer science, physics, biology, and beyond. It is highly relevant to simulation metaphysics and its idea that the physical world could be a type of computer simulation.

What does quantum computing have in common with the Oscar-winning movie “Everything Everywhere All at Once”? One is a mind-blowing work of fiction, while the other is an emerging frontier in computer science — but both of them deal with rearrangements of particles in superposition that don’t match our usual view of reality.

Fortunately, theoretical physicist Michio Kaku has provided a guidebook to the real-life frontier, titled “Quantum Supremacy: How the Quantum Computer Revolution Will Change Everything.”

Continue reading “How quantum computing could transform everything everywhere, but not all at once” »

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According to computational complexity theory, mathematical problems have different levels of difficulty in the context of their solvability. While a classical computer can solve some problems ℗ in polynomial time—i.e., the time required for solving P is a polynomial function of the input size—it often fails to solve NP problems that scale exponentially with the problem size and thus cannot be solved in polynomial time. Classical computers based on semiconductor devices are, therefore, inadequate for solving sufficiently large NP problems.

In this regard, quantum computers are considered promising as they can perform a large number of operations in parallel. This, in turn, speeds up the NP problem-solving process. However, many physical implementations are highly sensitive to thermal fluctuations. As a result, quantum computers often demand stringent experimental conditions such extremely low temperatures for their implementation, making their fabrication complicated and expensive.

Continue reading “Solving computationally complex problems with probabilistic computing” »

Want to learn about Quantum Computing? Here we discuss some commonly-asked questions about quantum computing and their answers.

“It was very curiosity-driven,” says Isak Engquist, a professor at Linköping University who led the effort. “We thought: ‘Can we do it? Let’s do it, let’s put it out there to the scientific community and hope that someone else has something where they see these could actually be of use in reality.’”

“I have colleagues who are at the forefront in a field we call electronic plants. … We have worked with dead woods for this project, but the next step might be to integrate it also into living plants.” —Isak Engquist, Linköping University.

Even though the wooden transistor still awaits its killer app, the idea to build wood-based electronics is not as crazy as it sounds. A recent review of wood-based materials reads, “Around 300 million years of tree evolution has yielded over 60,000 woody species, each of which is an engineering masterpiece of nature.” Wood has great structural stability while being highly porous and efficiently transporting water and nutrients. The researchers leveraged these properties to create conducting channels inside the wood’s pores and electrochemically modulate their conductivity with the help of a penetrating electrolyte.