Lifeboat Foundation

The “rank” of a graph is the number of loops it has; for each rank of graphs, there exists a moduli space. The size of this space grows quickly — if you fix the lengths of the graph’s edges, there are three graphs of rank 2, 15 of rank 3,111 of rank 4, and 2,314,204,852 of rank 10. On the moduli space, these lengths can vary, introducing even more complexity.

The shape of the moduli space for graphs of a given rank is determined by relationships between the graphs. As you walk around the space, nearby graphs should be similar, and should morph smoothly into one another. But these relationships are complicated, leaving the moduli space with mathematically unsettling features, such as regions where three walls of the moduli space pass through one another.

Mathematicians can study the structure of a space or shape using objects called cohomology classes, which can help reveal how a space is put together. For instance, consider one of mathematicians’ favorite shapes, the doughnut. On the doughnut, cohomology classes are simply loops.

Scientific and technological advances have enabled us to zoom into the biological world. We can get down to the biomolecular scale, a domain where quantum phenomena can take place and therefore cannot be neglected.

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Whether the light in our living spaces is on or off can be regulated in everyday life simply by reaching for the light switch. However, when the space for the light is shrunk to a few nanometers, quantum mechanical effects dominate, and it is unclear whether there is light in it or not. Both can even be the case at the same time, as scientists from the Julius-Maximilians-Universität Würzburg (JMU) and the University of Bielefeld show in the journal Nature Physics (“Identifying the quantum fingerprint of plasmon polaritons”).

“Detecting these exotic states of quantum physics on the size scales of electrical transistors could help in the development of optical quantum technologies of future computer chips,” explains Würzburg professor Bert Hecht. The nanostructures studied were produced in his group.

The technology of our digital world is based on the principle that either a current flows or it does not: one or zero, on or off. Two clear states exist. In quantum physics, on the other hand, it is possible to disregard this principle and create an arbitrary superposition of the supposed opposites. This increases the possibilities of transmitting and processing information many times over. Such superposition states have been known for some time, especially for the particles of light, so-called photons, and are used in the detection of gravitational waves.

For years, researchers have searched for the working principles of self-assembly that can build a cell (complex biological organism) as well as a crystal (far simpler inorganic material) in the same way.

Now, a team of scientists in Turkey has demonstrated the fundamental principles of a universal self-assembly process acting on a range of materials starting from a few atoms-large quantum dots up to nearly 100 trillion atoms-large human cells. Their method is highlighted in Nature Physics.

“To initiate self-assembly, either you force the system to deliver a specific outcome, or you use its inner dynamics to your advantage for universal outcomes. We followed the second approach,” says Dr. Serim Ilday of Bilkent University-UNAM, who lead the study.

Using lasers, researchers can directly control a property of nuclei called spin.

Physicists proposed that advanced extraterrestrial civilizations are using black holes in their quantum computers since they are abundant in quantum information. Read the article to learn more.

Quantum computing has entered a bit of an awkward period. There have been clear demonstrations that we can successfully run quantum algorithms, but the qubit counts and error rates of existing hardware mean that we can’t solve any commercially useful problems at the moment. So, while many companies are interested in quantum computing and have developed software for existing hardware (and have paid for access to that hardware), the efforts have been focused on preparation. They want the expertise and capability needed to develop useful software once the computers are ready to run it.

For the moment, that leaves them waiting for hardware companies to produce sufficiently robust machines—machines that don’t currently have a clear delivery date. It could be years; it could be decades. Beyond learning how to develop quantum computing software, there’s nothing obvious to do with the hardware in the meantime.

But a company called QuEra may have found a way to do something that’s not as obvious. The technology it is developing could ultimately provide a route to quantum computing. But until then, it’s possible to solve a class of mathematical problems on the same hardware, and any improvements to that hardware will benefit both types of computation. And in a new paper, the company’s researchers have expanded the types of computations that can be run on their machine.

It is truly an exciting time for the world of computing. Imagine being able to complete complex computing tasks in just a matter of hours, or even minutes, instead of waiting for days on end. L Venkata Subramaniam, a Quantum Distinguished Ambassador at IBM, tells AIM that this dream could become a reality thanks to the incredible power of quantum computing.

“Quantum naturally works in a higher dimensional space where data is better viewed or separated, or you can understand more about the data. Therefore, it is easier to work in quantum on AI problems,” said Subramaniam.

Quantum computing can also be effective in working with fundamental models, such as ChatGPT. Certain early observations suggest that quantum computing can achieve comparable results to classical AI using less training data and has the potential to accelerate the training process for AI models.

A new technical paper titled “A high-fidelity quantum matter-link between ion-trap microchip modules” was published by researchers at University of Sussex, Universal Quantum Ltd, University College London and University of Bristol.

“As quantum computers grow, we will eventually be constrained by the size of the microchip, which limits the number of quantum bits such a chip can accommodate. As such, we knew a modular approach was key to make quantum computers powerful enough to solve step-changing industry problems. In demonstrating that we can connect two quantum computing chips – a bit like a jigsaw puzzle – and, crucially, that it works so well, we unlock the potential to scale-up by connecting hundreds or even thousands of quantum computing microchips,” states Professor Winfried Hensinger, Professor of Quantum Technologies at the University of Sussex and Chief Scientist and Co-founder at Universal Quantum.