Tyler O'Neal, Staff Editor HEALTH

Kavli IPMU research reveals history of temperature changes in the Universe

First measurement using the Sunyaev-Zeldovic

How hot is the Universe today? How hot was it before? A new study by an international team of researchers, including members of the Kavli Institute for the Physics and Mathematics of the Universe (Kavli IPMU), suggests that the mean temperature of gas in large structures of the Universe has increased about 3 times in the last 8 billion years, to reach about two million Kelvin today.

The large-scale structure of the Universe refers to the global pattern of how galaxies and galaxy clusters are distributed in space. This cosmic net formed from tiny irregularities in the matter distribution in the early Universe, which were amplified through gravitational attraction. "As the Universe evolves, gravity pulls dark matter and gas in space together into galaxies and clusters of galaxies," said Yi-Kuan Chiang, the lead author of the study, and a research fellow at the Ohio State University Center for Cosmology and AstroParticle Physics. "The drag is violent--so violent that more and more gas is shocked and heated up." CAPTION supercomputer simulation of the evolution of the large-scale structure (bottom) and the temperature (top) of the Universe. The time flows from the left to the right panels, with the rightmost panel showing the present-day epoch. CREDIT D. Nelson / Illustris Collaboration.{module INSIDE STORY}

This heated gas can then be used to measure the mean temperature of the Universe over cosmic time. In particular, the researchers used the so-called "Sunyaev-Zeldovich" effect, named after Rashid Sunyaev, director emeritus at the Max Planck Institute for Astrophysics, and Soviet-era physicist Yakov Zeldovich, who first predicted this phenomenon theoretically. This effect arises when low-energy photons of the cosmic microwave background radiation are scattered by hot electrons in the large-scale structure of the Universe. The scattering transfers energy from electrons to photons, making the hot electron gas visible. The intensity of the Sunyaev-Zeldovich effect is proportional to the thermal pressure of the gas, which, in turn, is proportional to the temperature of electrons.

While this measurement is straightforward in principle, collecting the necessary data was a major undertaking. The study, which has been published in the Astrophysical Journal, was done in a collaboration of researchers at the Kavli IPMU, the Ohio State University, the Johns Hopkins University, and the Max Planck Institute for Astrophysics.

The researchers used data collected by two observatories, the Planck satellite and the Sloan Digital Sky Survey (SDSS). Planck is the European Space Agency mission which measured the cosmic microwave background radiation. SDSS collected detailed images and light spectra of galaxies. Combining the two data sets, the scientists were able to measure the amount of thermal pressure around the locations of galaxies and clusters of galaxies.

"It took astronomers more than 15 years to collect the necessary data using a telescope on the ground and one in space," said Brice Ménard who led the analysis with Chiang. Ménard, who has been a visiting scientist at the Kavli IPMU since 2011, added: "On the analysis side, our team spent four years developing the algorithms necessary to extract the signal from these data."

What's more, interpretation of the data required a physical model, which was provided by Ryu Makiya, a research fellow at the Kavli IPMU. "Combining the latest data with a state-of-the-art theoretical model, we were able to reveal how the temperature of the Universe evolved, and how it was linked to formation of the large-scale structure of the Universe," Makiya said. "The next goal is to understand details of the physics of thermal and non-thermal phenomena."

Chiang, from the Ohio Stated University, added: "Our new measurement provides a direct confirmation of the seminal work by Jim Peebles--the 2019 Nobel Laureate in Physics--who laid out the theory of the emergence of large-scale structure of the Universe."

The study determined that about eight billion years ago (at a redshift z=1), the mean electron temperature was some 700,000 Kelvin, rising to about two million Kelvin today. Furthermore, the scientists determined that its evolution is almost entirely driven by the growth of structures, as gas is shock heated in collapsing large-scale structures.

Back in 2000, Eiichiro Komatsu, a Principal Investigator at the Kavli IPMU and Director at the Department of Physical Cosmology at the Max Planck Institute for Astrophysics, was also involved in a previous effort to calculate how the temperature of the Universe evolved. "For 20 years, we have been studying how to measure this using the Sunyaev-Zeldovich effect," he remembered. "We now have finally measured the temperature of the Universe, not only thanks to the remarkable progress in observational data, but also due to the dedicated efforts of brilliant young scientists such as Yi-Kuan Chiang and Ryu Makiya. This is very satisfying," Komatsu added.

New Cambridge Centre connects AI, medicine, UK life sciences sectors

Tyler O'Neal, Staff Editor HEALTH

A new center at the University of Cambridge, in collaboration with AstraZeneca and GSK, aims to use AI to make medical discoveries, accelerate the development of precision medicine and develop new treatments


On 10 November the University of Cambridge announced a five-year agreement with AstraZeneca and GSK to fund the Cambridge Centre for AI in Medicine (CCAIM). For the 5-year duration, AstraZeneca and GSK will support five new Ph.D. studentships per year. This program will enable the best and brightest young minds in machine learning and bioscience to partner with leaders in industry and academia, wherever they may be in the world.

CCAIM has been set up as a cutting-edge research group. Its faculty of 10 University of Cambridge researchers – in addition to world-class Ph.D. students, currently being recruited – have united to develop AI and machine learning (ML) technologies aiming to transform clinical trials, personalized medicine, and biomedical discovery. {module INSIDE STORY}

The center’s Director is Professor Mihaela van der Schaar, a world-leading researcher in machine learning (ML), and the Co-Director is researcher-clinician Professor Andres Floto (bios below). The faculty also includes Dr. Sarah Teichmann FMedSci FRS, Head of Cellular Genetics at the Wellcome Sanger Institute and founder and principal leader of the Human Cell Atlas international consortium.

Successfully bridging the gap between the disparate and complex fields of AI and medicine requires building from both sides simultaneously. CCAIM brings together a diverse coalition of leading Cambridge scientists and clinicians, with expertise in machine learning, engineering, mathematics, medicine, computer science, genetics, computational biology, biostatistics, clinical research, healthcare policy and more.

These multi-disciplinary experts from the University of Cambridge will work in close collaboration with scientists and leaders from AstraZeneca and GSK to identify critical challenges facing drug discovery and development that have the potential to be solved through cutting-edge academic research.

The centre’s research output and the implementation of its ML tools could be transformational not only for the pharmaceutical industry – including in clinical trials and drug discovery – but also for the clinical delivery of healthcare to patients. The CCAIM team already has deep research links with the NHS, and four of the centre’s members are NHS doctors.

Professor Mihaela van der Schaar said:
“Machine learning has the potential to truly revolutionize the delivery of healthcare, to the great benefit of patients, clinicians, and the wider medical ecosystem. But to realize this potential requires true and deep cross-disciplinary understanding – a great challenge because we speak different languages. CCAIM is designed to break down the barriers between machine learning and medical science, to create a unique forum in which we can work together to truly understand the challenges, formalize the problems, and develop practical solutions that can be readily implemented in healthcare.”

Professor Andre Floto said:
“We are thrilled that the Cambridge Centre for AI in Medicine is taking off. From tackling the immediate threats of COVID-19 to the long-term transformation of healthcare systems, our network of experts and incoming Ph.D. students will bring next-level AI to bear on the most pressing medical issues of our time.”

Professor Andy Neely OBE, Pro-Vice-Chancellor for Enterprise and Business Relations, University of Cambridge, said:
“The Cambridge Centre for AI in Medicine is a terrific and timely venture that builds on the strong relationships between the University of Cambridge and global leaders in the pharmaceutical industry, AstraZeneca and GSK.
“The depth and diversity of the CCAIM faculty’s expertise mean it is uniquely positioned to deliver and accelerate the breakthroughs in medical science and healthcare that AI has long promised. I anticipate the center’s impact will be nothing less than transformational.”
Jim Weatherall, Vice President, Data Science & AI, R&D, AstraZeneca, said:
“We know the best science doesn’t happen in isolation which is why collaboration is essential to the way we work. This new center combines world-class academia with real-world industrial challenges and will help to develop cutting-edge AI to potentially transform the way we discover and develop medicines.”

Kim Branson, Senior Vice President and Global Head of AI/ML, GSK, said:
“The new Cambridge Centre for AI in Medicine will recruit and train the next generation of practitioners at the intersection of AI, industry, and academia. The work of this institute will be critical to translating AI methods from theory to practice, so that we can keep improving our therapeutic discovery efforts and so that together we can make a tangible impact on patients, from diagnosis to treatment and beyond.”

German scientists use hydrodynamical simulations to determine black-hole formation in neutron star collisions

Tyler O'Neal, Staff Editor HEALTH

A new study lead by GSI scientists in Germany and international colleagues investigates black-hole formation in neutron star mergers. Supercomputer simulations show that the properties of dense nuclear matter play a crucial role, which directly links the astrophysical merger event to heavy-ion collision experiments at GSI and FAIR. These properties will be studied more precisely at the future FAIR facility. The results have now been published in Physical Review Letters. With the award of the 2020 Nobel Prize in Physics for the theoretical description of black holes and for the discovery of a supermassive object at the center of our galaxy the topic currently also receives a lot of attention.

But under which conditions does a black hole actually form? This is the central question of a study lead by the GSI Helmholtzzentrum für Schwerionenforschung in Darmstadt, Germany within an international collaboration. Using supercomputer simulations, the scientists focus on a particular process to form black holes namely the merging of two neutron stars (simulation movie). CAPTION Artistic representation: In a merger of neutron stars extreme temperatures and densities occur. CREDIT Dana Berry, SkyWorks Digital, Inc.{module INSIDE STORY}

Neutron stars consist of highly compressed dense matter. The mass of one and a half solar masses is squeezed to the size of just a few kilometers. This corresponds to similar or even higher densities than in the inner of atomic nuclei. If two neutron stars merge, the matter is additionally compressed during the collision. This brings the merger remnant on the brink to collapse into a black hole. Black holes are the most compact objects in the universe, even light cannot escape, so these objects cannot be observed directly.

"The critical parameter is the total mass of the neutron stars. If it exceeds a certain threshold the collapse to a black hole is inevitable" summarizes Dr. Andreas Bauswein from the GSI theory department. However, the exact threshold mass depends on the properties of highly dense nuclear matter. In detail, these properties of high-density matter are still not completely understood, which is why research labs like GSI collide atomic nuclei - like a neutron star merger but on a much smaller scale. In fact, the heavy-ion collisions lead to very similar conditions as mergers of neutron stars. Based on theoretical developments and physical heavy-ion experiments, it is possible to compute certain models of neutron star matter, so-call equations of state.

Employing numerous of these equations of state, the new study calculated the threshold mass for black-hole formation. If neutron star matter or nuclear matter, respectively, is easily compressible - if the equation of state is "soft" - already the merger a relatively light neutron stars lead to the formation of a black hole. If the nuclear matter is "stiffer" and less compressible, the remnant is stabilized against the so-called gravitational collapse and a massive rotating neutron star remnant forms from the collision. Hence, the threshold mass for collapse itself informs about the properties of high-density matter. The new study revealed furthermore that the threshold to collapse may even clarify whether during the collision nucleon dissolves into their constituents, the quarks.

"We are very excited about these results because we expect that future observations can reveal the threshold mass" adds Professor Nikolaos Stergioulas of the department of physics of Aristotle University Thessaloniki in Greece. Just a few years ago a neutron star merger was observed for the first time by measuring gravitational waves from the collision. Telescopes also found the "electromagnetic counterpart" and detected light from the merger event. If a black hole is directly formed during the collision, the optical emission of the merger is pretty dim. Thus, the observational data indicates if a black hole was created. At the same time, the gravitational-wave signal carries information about the total mass of the system. The more massive the stars the stronger is the gravitational-wave signal, which thus allows determining the threshold mass.

While gravitational-wave detectors and telescopes wait for the next neutron star mergers, the course is being set in Darmstadt for knowledge that is even more detailed. The new accelerator facility FAIR, currently under construction at GSI, will create conditions, which are even more similar to those in neutron star mergers. Finally, only the combination of astronomical observations, computer simulations and heavy-ion experiments can settle the questions about the fundamental building blocks of matter and their properties, and, by this, they will also clarify how the collapse to a black hole occurs.