How to resolve AdBlock issue? Gas giant planets, such as Jupiter, can form rapidly by incorporating nearby icy bodies made from drifting pebbles born in the outer parts of young planetary systems – all in about 200,000 years. This finding has implications for understanding how habitable planets are created; not just in our solar system, but in others too. 
Gas giants are made of a massive solid core surrounded by an even larger mass of helium and hydrogen. But even though these planets are quite common in the Universe, scientists still don’t fully understand how they form. Now, astrophysicists Hiroshi Kobayashi of Nagoya University and Hidekazu Tanaka of Tohoku University have developed supercomputer simulations that simultaneously use multiple types of celestial matter to gain a more comprehensive understanding of how these colossal planets grow from specks of dust. Their findings were published in The Astrophysical Journal.
“We already know quite a bit about how planets are made,” says Kobayashi. “Dust lying within the far-reaching ‘protoplanetary disks’ surrounding newly formed stars collides and coagulates to make celestial bodies called planetesimals. These then amass together to form planets. Despite everything we know, the formation of gas giants, like Jupiter and Saturn, has long baffled scientists.”
This is a problem because gas giants play huge roles in the formation of potentially habitable planets within planetary systems.
For gas giants to form, they must first develop solid cores that have enough mass, about ten times that of Earth, to pull in the huge amounts of gas for which they are named. Scientists have long struggled to understand how these cores grow. The problem is two-fold. First, core growth from the simple amassing of nearby planetesimals would take longer than the several million years during which the dust-containing protoplanetary disks survive. Second, forming planetary cores interact with the protoplanetary disk, causing them to migrate inward towards the central star. This makes conditions impossible for gas accumulation.
To tackle this problem, Kobayashi and Tanaka used state-of-the-art computer technologies to develop simulations that can model how dust lying within the protoplanetary disk can collide and grow to form the solid core necessary for gas accumulation. A major issue with current programs was that they could only simulate planetesimal or pebble collisions separately. “The new program can handle celestial bodies of all sizes and simulate their evolution via collisions,” explains Kobayashi.
The simulations showed that pebbles from the outer parts of the protoplanetary disk drift inwards to grow into icy planetesimals at about 10 astronomical units (au) from the central star. A single astronomical unit represents the mean distance between the Earth and the Sun. Jupiter and Saturn are about 5.2au and 9.5au away from the Sun, respectively. Pebble growth into icy planetesimals increases their numbers in the region of the developing planetary system that is about 6-9 au from the central star. This encourages high core growth rates, resulting in the formation of solid cores massive enough to accumulate gas and develop into gas giants in about 200,000 years.
“We expect our research will help lead to the full elucidation of the origin of habitable planets, not only in the solar system but also in other planetary systems around stars,” says Kobayashi.
Researchers at the University of Surrey have successfully demonstrated proof-of-concept of using their multimodal transistor (MMT) in artificial neural networks, which mimic the human brain. This is an important step towards using thin-film transistors as artificial intelligence hardware and moves edge computing forward, with the prospect of reducing power needs and improving efficiency, rather than relying solely on computer chips.
The MMT, first reported by Surrey researchers in 2020, overcomes long-standing challenges associated with transistors and can perform the same operations as more complex circuits. This latest research, published in the peer-reviewed journal Scientific Reports, uses mathematical modeling to prove the concept of using MMTs in artificial intelligence systems, which is a vital step towards manufacturing.
Using measured and simulated transistor data, the researchers show that well-designed multimodal transistors could operate robustly as rectified linear unit-type (ReLU) activations in artificial neural networks, achieving practically identical classification accuracy as pure ReLU implementations. They used both measured and simulated MMT data to train an artificial neural network to identify handwritten numbers and compared the results with the built-in ReLU of the software. The results confirmed the potential of MMT devices for thin-film decision and classification circuits. The same approach could be used in more complex AI systems.
Unusually, the research was led by Surrey undergraduate Isin Pesch, who worked on the project during the final year research module of her BEng (Hons) in Electronic Engineering with Nanotechnology. Covid meant she had to study remotely from her home in Turkey, but she still managed to spearhead the development, complemented by an international research team, which also included collaborators in the University of Rennes, France, and UCL, London.
Isin Pesch, the lead author of the paper, which was written before she graduated in July 2021, said: “There is a great need for technological improvements to support the growth of low cost, large-area electronics which were shown to be used in artificial intelligence applications. Thin-film transistors have a role to play in enabling high processing power with low resource use. We can now see that MMTs, a unique type of thin-film transistor, invented at the University of Surrey, have the reliability and uniformity needed to fulfill this role.”
Dr. Radu Sporea, Senior Lecturer at the University of Surrey’s Advanced Technology Institute, said: “These findings are a reminder of how Surrey is a leader in AI research. Many of my colleagues focus on people-centred AI and how best to maximize the benefits for humans, including how to apply these new concepts ethically. Our research at the Advanced Technology Institute takes forward the physical implementation, as a stepping stone towards powerful yet affordable next-generation hardware. It’s fantastic that collaboration is resulting in such successes with researchers involved at all levels, from undergraduates like Isin when she led this research, to seasoned experts.”
