Astronomer Leverages Supercomputers to Study Black Holes, Galaxies

Image via WikipediaAn Ohio State University astronomer is working to unlock some of the mysteries surrounding the formation of vast galaxies and the evolution of massive black holes with his own large constellation of silicon wafers.

Over the last year, two research teams led by Stelios Kazantzidis, a Long-Term Fellow at the Center for Cosmology and Astro-Particle Physics (CCAPP) at The Ohio State University, have used what would average out to nearly 1,000 computing hours each day on the parallel high performance computing systems of the Ohio Supercomputer Center (OSC). To develop their detailed models and resulting simulations, Kazantzidis and his colleagues tapped OSC's flagship system, the Glenn IBM Cluster 1350, which features more than 9,600 Opteron cores and 24 terabytes of memory.

Kazantzidis and University of Zurich student Simone Callegari recently authored a paper, "Growing Massive Black Hole Pairs in Minor Mergers of Disk Galaxies," and submitted it for publication in the Astrophysical Journal. Their study involved a suite of high-resolution, smoothed-particle hydrodynamics simulations of merging disk galaxies with supermassive black holes (SMBHs). These simulations include the effects of star formation and growth of the SMBHs, as well as feedback from both processes.

"Binary SMBHs are very important, because once they form there is always the possibility that the two black holes may subsequently merge," Kazantzidis explained. "Merging SMBHs will produce the strongest signal of gravitational wave emission in the universe. Gravitational waves have not yet been directly detected, although Einstein predicted them in his Theory of General Relativity."

The astronomers found that the mass ratios of SMBH pairs in the centers of merged galaxies do not necessarily relate directly to the ratios they had to their original host galaxies, but are "a consequence of the complex interplay between accretion of matter (stars and gas) onto them and the dynamics of the merger process." As a result, one of the two SMBHs can grow in mass much faster than the other.

Kazantzidis believes simulations of the formation of binary SMBHs have the potential to open a new window into astrophysical and physical phenomena that cannot be studied in other ways and might help to verify general relativity, one of the most fundamental theories of physics.

Kazantzidis and his colleagues also recently developed sophisticated computer models to simulate the formation of dwarf spheroidal galaxies, which are satellites of our own galaxy, the Milky Way. The study concluded that, in a majority of cases, disk-like dwarf galaxies -- known in the field as disky dwarfs -- experience significant loss of mass as they orbit inside their massive hosts, and their stellar distributions undergo a dramatic morphological, as well as dynamical, transformation: from disks to spheroidal systems.

"These galaxies are very important for astrophysics, because they are the most dark matter-dominated galaxies in the universe," Kazantzidis said. "Understanding their formation can shed light into the very nature of dark matter. Environmental processes like the interactions between dwarf galaxies and their massive hosts we've been investigating should be included as ingredients in future models of dwarf galaxy formation and evolution."

For this project, Kazantzidis, Callegari, Ewa Lokas of the Nicolaus Copernicus Astronomical Center -- all of whom utilized the Glenn Cluster -- and the rest of the team have submitted to the Astrophysical Journal an article titled, "On the Efficiency of the Tidal Stirring Mechanism for the Origin of Dwarf Spheroidals: Dependence on the Orbital and Structural Parameters of the Progenitor Disky Dwarfs."

Supercomputing centers such as OSC allow astronomers to create extremely sophisticated models that are not feasible on desktop systems. However, even with supercomputers, Kazantzidis and his colleagues find that simulating the multitude of elements involved in these galactic processes remains an enormous challenge.

"Our models can only follow a small subset of, say, the stars in a galaxy," he explained. "For example, a galaxy like our Milky Way contains hundreds of billions of stars, and even the most sophisticated numerical simulations to date can only simulate a tiny fraction of this number. The situation becomes increasingly more difficult in simulations that involve dark matter. This is because the dark matter particle is an elementary particle and, therefore, it is much less massive than a star. A galaxy like the Milky Way contains of the order of 10⁶⁷ dark matter particles (that is, the number one followed by 67 zeros)."

The goal of Kazantzidis' team is to develop representations of galaxies that are as accurate as possible. Access to the Glenn Cluster increases the number of objects (or simulation particles) that can be depicted in the model, enhancing their ability to perform accurate and meaningful calculations.

"The powerful hardware and software available at OSC are particularly well-suited for cutting-edge astronomy research, such as that being conducted by Dr. Kazantzidis," said Ashok Krishnamurthy, interim co-executive director and director of research at OSC. "The results he and his colleagues have been able to achieve through their research projects are impressive and firmly demonstrate the Center's ability to help accelerate innovation and discovery."

Computers to Read Your Body Language?

Image via WikipediaCan a computer read your body language? A consortium of European researchers thinks so, and has developed a range of innovative solutions from escalator safety to online marketing.

The keyboard and mouse are no longer the only means of communicating with computers. Modern consumer devices will respond to the touch of a finger and even the spoken word, but can we go further still? Can a computer learn to make sense of how we walk and stand, to understand our gestures and even to read our facial expressions?

The EU-funded MIAUCE project (http://www.miauce.org/) set out to do just that. "The motivation of the project is to put humans in the loop of interaction between the computer and their environment," explains project coordinator Chaabane Djeraba, of CNRS in Lille.

"We would like to have a form of ambient intelligence where computers are completely hidden," he says. "This means a multimodal interface so people can interact with their environment. The computer sees their behaviour and then extracts information useful for the user."

It is hard to imagine a world where hidden computers try to anticipate our needs, so the MIAUCE project has developed concrete prototypes of three kinds of applications.

Escalator accidents

The first is to monitor the safety of crowds at busy places such as airports and shopping centres. Surveillance cameras are used to detect situations such as accidents on escalators.

"The background technology of this research is based on computer vision," says Djeraba. "We extract information from videos. This is the basic technology and technical method we use."

It's quite a challenge. First the video stream must be analysed in real time to extract a hierarchy of three levels of features. At its lowest, this is a mathematical description of shapes, movements and flows. At the next level this basic description is interpreted in terms of crowd density, speed and direction. At the highest level the computer is able to decide when the activity becomes 'abnormal' perhaps because someone has fallen on an escalator and caused a pile-up that needs urgent intervention.

It is at the second level and the third "semantic" level of interpretation that MIAUCE has been most concerned.

One of the MIAUCE partners is already working with a manufacturer of escalators to augment existing video monitoring systems at international airports where there may be hundreds of escalators. If a collapse can be detected automatically then the seconds saved in responding could save lives as well.

But safety is only one possible kind of application where computers could read our body language.

Face swapping

A second could be in marketing, specifically to monitor how customers behave in shops. "We would like to analyse how people walk around in a shop," Djeraba says, "and the behaviour of people in the shop, where they look, for example."

The same partner is developing two products. One will be a 'people counter' to monitor pedestrian flows in the street outside a shop. It is expected to be particularly attractive to fashion stores who wish to attract passers-by. Another is a 'heat map generator' to watch the movements of people inside the store, so that the manager can see which parts of the displays are attracting the most attention.

The third application addressed by MIAUCE is interactive web television, a technology of increasing interest where viewers can select what they want to see. As part of the project, the viewer's webcam is used to monitor their face to see which part of the screen they are looking at.

It could be used to feed the user further information based on the evidence of what they have shown an interest in. Project partner Tilde, a software company in Latvia, is commercialising this application.

MIAUCE has also developed a related technology of 'face swapping' in which the viewer's face can replace that of a model. This could be used for trying out hairstyles and clothing.

Ethics and anonymity

These are all ingenious applications but are there not ethical and legal worries about reading people's behaviour in this way?

Djeraba acknowledges that the project team took such issues very seriously and several possible applications of their technology were ruled out on such grounds.

They worked to some basic rules, such as placing cameras only on private premises and always with a warning notice, but the fundamental principle was anonymity. "We have to anonymise people," he says. "What we are doing here is analysing user behaviour without any identification, this is a fundamental requirement for such systems."

They also took account of whether the applications would be acceptable to society as a whole. No one would reasonably object to the monitoring of escalators, for example, if the aim was to improve public safety. But the technology must not identify individuals or even such characteristics as skin colour.

"Generally speaking, anonymity is the critical point. If we anonymise it's OK, if we don't anonymise it's not OK," Djeraba says.