A team of scientists from GSI Helmholtzzentrum für Schwerionenforschung and Queen's University Belfast have produced a 3D supercomputer simulation of the light that is emitted after the merger of two neutron stars, similar to a kilonova that has been observed. The simulation brought together several areas of physics, such as the behavior of matter at high densities, properties of unstable heavy nuclei, and atom-light interactions of heavy elements. This breakthrough in research has provided new insights into the phenomenon of kilonovae.

Recent observations that combine both gravitational waves and visible light have pointed to neutron star mergers as the major site of this element production. According to Luke Shingles, a scientist at GSI/FAIR and the leading author, the unprecedented agreement between their simulations and the observation of kilonova AT2017gfo indicates a broad understanding of the event.

The light that we see through telescopes from the material ejected from a neutron-star merger is determined by the interactions between electrons, ions, and photons within it. Supercomputer simulations of radiative transfer can model these processes and the emitted light. Recently, researchers produced a three-dimensional simulation for the first time that can self-consistently follow the neutron-star merger, neutron-capture nucleosynthesis, energy deposited by radioactive decay, and radiative transfer with tens of millions of atomic transitions of heavy elements.

The 3D model can predict the observed light for any viewing direction. When viewed almost perpendicular to the orbital plane of the two neutron stars, as observational data indicates for the kilonova AT2017gfo, the model predicts a sequence of spectral distributions that look very similar to what has been observed for AT2017gfo. This research area will help us to understand the origins of elements heavier than iron (such as platinum and gold) that were mainly produced by the rapid neutron capture process in neutron star mergers, says Shingles.

Almost half of the elements heavier than iron are produced in an environment of extreme temperatures and neutron densities, as achieved when two neutron stars merge. When they spiral in and coalesce, the resulting explosion leads to the ejection of matter with the appropriate conditions to produce unstable neutron-rich heavy nuclei by a sequence of neutron captures and beta-decays. These nuclei decay to stability, releasing energy that powers an explosive ‘kilonova’ transient, a bright emission of light that rapidly fades in about a week.

The 3D simulation combines several areas of physics, including the behavior of matter at high densities, the properties of unstable heavy nuclei, and atom-light interactions of heavy elements. However, further challenges remain, such as accounting for the rate at which the spectral distribution changes and the description of material ejected at late times. Future progress in this area will increase the precision with which we can predict and understand features in the spectra and will further our understanding of the conditions in which heavy elements were synthesized. High-quality atomic and nuclear experimental data, provided by the FAIR facility, is a fundamental ingredient for these models.

There is currently a search for new materials to build computer microchips that are more energy-efficient and brain-like. However, no theory can guide this effort on a solid foundation. A theory for non-digital computers is necessary to take into account continuous and analog signals, physical effects at the nanoscale, and the fact that the devices created are often not identical. The paper published by Herbert Jaeger, Beatriz Noheda, and Wilfred G. van der Wiel is the first attempt to provide a sketch of what such a theory for neuromorphic computers might look like.

According to Herbert Jaeger, who is a professor of computing in cognitive materials at the University of Groningen in the Netherlands, there needs to be a solid theory behind the engineering of new microchips. Currently, computers rely on stable switches, usually transistors, that can be either on or off, making them logical machines with programming based on logical reasoning. However, the miniaturization of transistors, which has been the key to making computers more powerful, is reaching its physical limit, which is why scientists are now looking for new materials that can produce more versatile switches capable of using more values than just 0 or 1.

Jaeger is a member of the Groningen Cognitive Systems and Materials Center (CogniGron) which is devoted to creating neuromorphic (brain-like) computers. CogniGron brings together scientists with differing approaches, including experimental materials scientists, mathematical theorists, and computer science and AI specialists. Working closely with materials scientists has given Jaeger insight into the challenges they face when developing new computational materials. It has also made him aware of a dangerous pitfall: there is no established theory for the use of non-digital physical effects in computing systems.

Our brain functions differently than a logical system. Although we can reason logically, this is only a small aspect of what our brain can do. The majority of the time, our brain must figure out how to perform simple tasks such as lifting a cup or waving to a colleague. Jaeger explains that "a lot of the information-processing that our brain does is this non-logical stuff, which is continuous and dynamic. It is difficult to formalize this in a digital computer." Additionally, our brain can function despite external factors such as fluctuations in blood pressure, external temperature, and hormone balance. So, how can we create a computer that is both versatile and robust? Jaeger believes that "the brain is proof of principle that it can be done", and is optimistic that it can.

The brain is a source of inspiration for materials scientists who aim to produce materials that mimic the behavior of neurons. Scientists might create materials that oscillate, show bursts of activity, and resemble how neurons work. However, the field is missing a crucial piece of information: even neuroscientists don't fully understand how the brain works. The lack of a theory for neuromorphic computers is a problem, but the field doesn't seem to acknowledge this. In a recent paper, Jaeger, Noheda, and van der Wiel proposed a theory for non-digital computers. The theory suggests that instead of using stable 0/1 switches, non-digital computers should work with continuous, analog signals. It should also account for the various non-standard nanoscale physical effects that materials scientists are studying.

Neuromorphic computing devices made from new materials are difficult to construct, and if you make a hundred of them, they will not all be identical. This is similar to how our neurons are not all the same. Additionally, these devices are often brittle and sensitive to temperature. Therefore, any theory for neuromorphic computing should consider such characteristics. Importantly, a theory supporting neuromorphic computing will not be a single theory but will consist of many sub-theories, just like digital computer theory, which is a layered system of connected sub-theories. To create a theoretical description of neuromorphic computers, experimental materials scientists and formal theoretical modelers must collaborate closely. Computer scientists must be aware of the physics of all these new materials, and materials scientists should be familiar with the fundamental concepts in computing.

The University of Groningen established CogniGron to bridge the gap between materials science, neuroscience, computing science, and engineering. The aim is to bring together these different groups to work collaboratively. Jaeger, one of the researchers at CogniGron, explains that everyone has their blind spots and the biggest gap in their knowledge is the lack of a foundational theory for neuromorphic computing. To overcome this, their paper provides a first attempt at highlighting how such a theory could be formulated and how a common language can be created.