In this year’s ranking of “Highly Cited Researchers”, three HITS scientists are named among the most cited researchers worldwide: Tilmann Gneiting (Mathematics), Volker Springel (Space Science) and, for the first time, Alexandros Stamatakis (Computer Science).

Three researchers from the Heidelberg Institute for Theoretical Studies (HITS) belong to the most cited researchers worldwide. The “Highly Cited Researchers” report 2016 states that the publications of Tilmann Gneiting, Volker Springel and Alexandros Stamatakis rank in the top 1 percent by citations in their field and publication year in the Web of Science. The three researchers have a primary affiliation with HITS, their secondary affiliations being with Heidelberg University or the Karlsruhe Institute of Technology (KIT), respectively. “Having a total of three highly cited researchers as a rather small research institute is evidence of the quality of our scientists and the work done here at HITS,” says Rebecca Wade, Scientific Director of HITS. Tilmann Gneiting and Volker Springel have been named “Highly Cited Researchers” in the last two years, but this year they are joined by Alexandros Stamatakis, who has been included in the list for the first time. The ranking is an important indicator of the impact of a researcher’s scientific publications, and lists around 3000 scientists from 21 different research fields. 

Prof. Tilmann Gneiting’s research focuses on the theory and practice of forecasts, as well as spatial statistics. He and his team are developing methods for real-time probabilistic weather forecasts amongst other applications. Gneiting cooperates with the German Weather Service and the European Centre for Medium-Range Weather Forecasts in Reading, UK. Since November 2013, he has been leading the research group “Computational Statistics” at HITS, and is a professor at the Institute for Stochastics at the Karlsruhe Institute of Technology (KIT). Tilmann Gneiting is one of only two German mathematicians selected in the ranking.

The astrophysicist Prof. Volker Springeldesigned and implemented the largest and most comprehensive computer simulations of the universe. He developed the “Arepo” code, which enables scientists to simulate the wide range of galaxy shapes and sizes with unique precision. An example of his work is “Illustris“, the most detailed computer simulation of galaxy formation to date, which was published in the journal “Nature”. Volker Springel has been group leader of the research group “Theoretical Astrophysics” at HITS since 2010, and is a professor for Astrophysics at Heidelberg University.

Prof. Alexandros Stamatakis works in the field of bioinformatics and develops software for processing large biological datasets. One primary research focus is the development of algorithms and software for reconstructing the evolutionary history of species based on their DNA data. Stamatakis has contributed to disentangling the evolutionary trees of insects and birds in two large scale research projects whose results were published in the journal “Science”. Alexandros Stamatakis has been in charge of the “Scientific Computing” research group at HITS since 2010, and is Professor of High Performance Computing in the Life Sciences at the Karlsruhe Institute of Technology (KIT), as well as Adjunct Professor at the University of Arizona Tuscon.

The citation frequency is an indicator of the scientific impact of a paper. The “Highly Cited Researchers” list is published by the U.S. company Clarivate Analytics (formerly part of Thomson Reuters). It is based on an analysis of how many of a scientist’s publications in the natural and social sciences – as well as in medicine – were frequently cited in their colleagues’ publications. Publications from the years 2004-2014 were evaluated. For more information, visit the website: highlycited.com

Marta Sales-Pardo and Roger Guimerà, researchers at the URV's Department of Chemical Engineering.

Researchers at the URV have created an algorithm that provides better predictions than existing algorithms. The algorithm can predict the resulting overlapping groups and preferences because it is able to predict individual preferences in large datasets

Antonia Godoy, Roger Guimerà and Marta Sales, researchers at the URV's Department of Chemical Engineering, and Cristopher Moore, of the Santa Fe Institute, have developed a collaborative filtering model with an associated scalable algorithm that makes accurate predictions of individuals' preferences. The new approach is based on the explicit assumption that there are groups of individuals and of items, and that the preferences of an individual for an item are determined only by their group memberships. The new tool allows each individual and each item to belong simultaneously to mixtures of different groups and, unlike many popular approaches, it does not assume implicitly or explicitly that the individuals in each group prefer items in a single group of items. The algorithm can predict the resulting overlapping groups and preferences because it is able to predict individual preferences in large datasets, and is thus considerably more accurate than the algorithms currently used for such large datasets.

There are many algorithms, and many are very quick and provide reasonable results; however, they are often based on unrealistic models. They mostly classify people into groups according to their preferences and make predictions on the basis of this group's behaviour. Consequently, the predictions reflect the overall preferences of the group but cannot predict the behavior of individuals because they do not take individual differences into account. These models are therefore unable to reproduce behavioural models of the population.

The new approach is based on a more sophisticated model and better reflects how people really behave. As such, in contrast to existing models, it is more flexible and can reproduce the behavioural patterns of an entire population. It was already known that the model could provide better predictions but up to now it has always been too slow to apply to large datasets. In a scientific article published in the journal Proceedings of the National Academy of Sciences of the United States of America, the URV researchers state that they have achieved the best of both worlds: a model that is quick and scalable that also better reflects the decisions that people take.

Researchers at Princeton, Columbia and Harvard have created a new method to analyze big data that better predicts outcomes in health care, politics and other fields.

The study appears this week in the journal Proceedings of the National Academy of Sciences. A PDF is available on request.

In previous studies, the researchers showed that significant variables might not be predictive and that good predictors might not appear statistically significant. This posed an important question: how can we find highly predictive variables if not through a guideline of statistical significance? Common approaches to prediction include using a significance-based criterion for evaluating variables to use in models and evaluating variables and models simultaneously for prediction using cross-validation or independent test data.

In an effort to reduce the error rate with those methods, the researchers proposed a new measure called the influence score, or I-score, to better measure a variable's ability to predict. They found that the I-score is effective in differentiating between noisy and predictive variables in big data and can significantly improve the prediction rate. For example, the I-score improved the prediction rate in breast cancer data from 70 percent to 92 percent. The I-score can be applied in a variety of fields, including terrorism, civil war, elections and financial markets.

"The practical implications are what drove the project, so they're quite broad," says lead author Adeline Lo, a postdoctoral researcher in Princeton's Department of Politics. "Essentially anytime you might be interested in predicting and identifying highly predictive variables, you might have something to gain by conducting variable selection through a statistic like the I-score, which is related to variable predictivity. That the I-score fares especially well in high dimensional data and with many complex interactions between variables is an extra boon for the researcher or policy expert interested in predicting something with large dimensional data."

Research networks to investigate topics such as practices of comparison, neutrinos, dark matter, and the robustness of vision; around €120 million in funding for an initial 4-year period

The Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) will establish 14 new Collaborative Research Centres (CRCs). This was decided by the responsible Grants Committee during its autumn session in Bonn. The new CRCs will receive a total of 117.4 million euros in funding. There will also be a 22 percent programme allowance for indirect project costs. Seven of the 14 networks set up are CRC/Transregios, which will be spread across multiple research sites. All of the new CRCs will be funded for an initial four-year period starting on 1 January 2017.

In addition to the 14 new Collaborative Research Centres, the Grants Committee also approved the extension of 15 existing CRCs for an additional funding period. As a result, the DFG will be funding a total of 268 Collaborative Research Centres from January 2017.

The new Collaborative Research Centres in detail (in alphabetical order by their host universities, including the name of the applicant universities):

Little is currently known about the history, social and cultural causes, functions and impacts of comparison - despite frequent speculation about the increase in comparisons in certain epochs and in modern societies. In the Collaborative Research Centre "Practices of Comparisons: Ordering and Changing the World", researchers from the fields of history, literature studies, philosophy, history of art, political science and law will investigate how the historically variable practices of comparison link to routines, rules, institutions and discourses - and can thus create structures but also trigger medium-range dynamics or overarching change. 
(Host university: Bielefeld University, Spokesperson: Professor Dr. Angelika Epple)

Industrial forming processes for metals cause damage within the material. It is not known how the damage caused by forming processes such as rolling or deep-drawing is influenced, how it changes throughout the process chain or what impact it has on subsequent component behaviour. The CRC/Transregio "Damage Controlled Forming Processes" therefore aims to develop new methods and technologies to control and predict damage as well as component characteristics. 
(Host university: Technical University of Dortmund, Spokesperson: Professor Dr.-Ing. A. Erman Tekkaya; additional applicant university: RWTH Aachen University)

The aim of the CRC/Transregio "Mobile Material Characterisation and Localisation by Electromagnetic Sensing" is to trial new approaches to mobile material detectors. This would enable the material properties of any object to be determined, even if it were concealed behind a wall, making it possible to locate unconscious persons in a building filled with smoke or contaminated with poisonous gases, or to detect burning cables inside walls, for example. To achieve this it is necessary to develop mobile detectors that record data in a frequency range from several gigahertz to terahertz, which can be used to precisely localise and characterise a complex environment. 
(Host university: University of Duisburg-Essen, Spokesperson: Professor Dr.-Ing. Thomas Kaiser; additional applicant university: University of Bochum)

Myeloid cells - the immune cells of the brain - play an important role in the function of the central nervous system. They are the focus of the work of the CRC/Transregio "Development, Function and Potential of Myeloid Cells in the Central Nervous System (NeuroMac)". Using some of the latest methods in molecular immunology and neuroscience, such as in-vivo microscopy and genome editing, the researchers will investigate the role of myeloid cells in diseases such as stroke, multiple sclerosis, Alzheimer's and Huntington's disease. 
(Host university: University of Freiburg, Spokesperson: Professor Dr. Marco Prinz; additional applicant universities: Free University of Berlin and Humboldt University of Berlin)

The Collaborative Research Centre "N-Heteropolycycles as Functional Materials" is concerned with the field of organic electronics and will investigate new, entirely organic semiconductors. As the fundamental building blocks for semiconductors, the research network will use what are known as N-heteropolycycles and study their characteristics. The researchers intend to address the complete spectrum of chemical synthesis, method development and the physical and theoretical characterisation of organic semiconductors, including the question of the effects of the material properties of N-heteropolycycles in optoelectronic components, such as solar cells. 
(Host university: University of Heidelberg, Spokesperson: Professor Dr. Lutz H. Gade)

In algebra, where exact calculations are essential, modern supercomputers with mathematical software have enormous computing potential which so far has not been fully exploited. The researchers in the CRC/Transregio "Symbolic Tools in Mathematics and their Application" plan to further develop existing computer algebra systems which they have largely developed themselves and in doing so, answer fundamental questions in mathematics. They also plan to make the software available as an open-source system. 
(Host university: Technical University of Kaiserslautern, Spokesperson: Professor Dr. Gunter Malle; additional applicant universities: RWTH Aachen University; Saarland University)

Symplectic geometry has its roots in classical mechanics, where it enables a coordinate-free formulation of the basic equations of motion and therefore a deeper understanding of the underlying dynamics. The CRC/Transregio "Symplectic Structures in Geometry, Algebra and Dynamics" will investigate symplectic structures and the application of symplectic techniques to topics in geometry, algebra, dynamic systems, topology, combinatorics and optimisation. The network will forge links with disciplines in which the potential of a symplectic approach has been little or not fully realised or which themselves can contribute new methodologies to the study of symplectic questions, for example computer science. 
(Host university: University of Cologne, Spokesperson: Professor Dr. Hansjörg Geiges; additional applicant university: University of Bochum)

How is information organised and structured in language? The factor of 'prominence' plays a central role in the formation of language structures. Through its formulated question, the Collaborative Research Centre "Prominence in Language" will bring together many areas of linguistics, such as phonetics/phonology, morphology, syntax, semantics, pragmatics and discourse. It will also investigate the relationships between linguistic prominence and general cognitive mechanisms such as the accentuation of attention, thus forging links with psychology and clinical linguistics. 
(Host university: University of Cologne, Spokesperson: Professor Dr. Klaus von Heusinger)

Contrary to a long-held view, bacteria are highly organised units whose function is guaranteed by the precise positioning of biomolecules inside them. The CRC/Transregio "Spatiotemporal Dynamics of Bacterial Cells" will consider many different aspects of cellular organisation, such as the spatiotemporal regulation of cell division, growth and morphogenesis, the organisation and segregation of chromosomal DNA and the dynamics of the formation of (membrane) protein complexes. In this way, the CRC/Transregio aims to identify the molecular systems responsible for controlling these cellular processes and better understand the spatiotemporal dynamics of bacterial cells. 
(Host university: University of Marburg, Spokesperson: Professor Dr. Martin Rudolf Thanbichler; additional applicant university: LMU Munich)

The CRC/Transregio "Rationality and Competition: The Economic Performance of Individuals and Firms" brings together representatives of behavioural economics and neoclassical economics. They aim to explain how distortions and anomalies in the behaviour of individuals and companies are connected and what economic policy measures can effectively protect consumers and employees against poor decisions and exploitation. 
(Host university: LMU Munich, Spokesperson: Professor Dr. Klaus Schmidt; additional applicant university: Humboldt University of Berlin)

A Munich-based Collaborative Research Centre will investigate "Neutrinos and Dark Matter in Astro- and Particle Physics (NDM)". The researchers are primarily interested in neutrinos, the most common particles of matter in the universe, and dark matter, which is responsible for cosmic dynamics on galactic and even larger scales. Among the topics they will address is the still unanswered question of whether neutrinos are their own antiparticles and whether they have sterile partners. The answer to this question could explain why our world consists of more matter than antimatter. 
(Host university: Technical University of Munich, Spokesperson: Professor Dr. Elisa Resconi)

The high resource demands of construction, a fast-growing world population, especially in urban areas, and the changing needs of inhabitants create a need for fundamentally new architectural concepts. The aim of the Collaborative Research Centre "Adaptive Envelopes and Structures for the Future Built Environment" is therefore to develop concepts for adaptive buildings. The network will investigate the potential of adaptive elements for load-bearing structures, envelope systems and interior fittings, with a view to designing buildings which can actively react to external influences. 
(Host university: University of Stuttgart, Spokesperson: Professor Dr.-Ing. Werner Sobek)

Our sense of sight enables us to identify objects reliably even under very different conditions; we therefore have robust visual inference. This ability demands complex calculations, which are performed by the nerve cells in the visual system. The aim of the Collaborative Research Centre "Robust Vision - Inference Principles and Neural Mechanisms" is to uncover the principles and algorithms that make robust vision possible. The researchers will also use technical algorithms of human learning and computer vision research to draw conclusions about biological vision. 
(Host university: University of Tübingen, Spokesperson: Professor Dr. Matthias Bethge)

Predicting the extent to which pollutants will remain in and alter our landscapes in the long term is a major challenge in geosciences and environmental research, all the more so as the extremely complex processes are very difficult to measure with laboratory experiments. The Collaborative Research Centre "Catchments as Reactors: Metabolism of Pollutants on the Landscape Scale (CAMPOS)" will therefore investigate the transport and conversion of pollutants in the large-scale and long-term process chains found in nature. The researchers will utilise innovative observation systems and numerical landscape models with a view to laying the foundations for more reliable predictions about future soil and water quality in the face of climate and land use change. 
(Host university: University of Tübingen, Spokesperson: Professor Dr. Peter Grathwohl)

Atomic force microscopy image of the end of a mono-atomic iron wire. The individual iron atoms are clear to see, as well as the “eye” of the Majorana fermions on the end. (Image: University of Basel, Department of Physics)

Majorana fermions are particles that could potentially be used as information units for a quantum supercomputer. An experiment by physicists at the Swiss Nanoscience Institute and the University of Basel’s Department of Physics has confirmed their theory that Majorana fermions can be generated and measured on a superconductor at the end of wires made from single iron atoms. The researchers also succeeded in observing the wave properties of Majoranas and, therefore, in making the interior of a Majorana visible for the first time. The results were published in the Nature journal npj Quantum Information.

Around 75 years ago, Italian physicist Ettore Majorana hypothesized the existence of exotic particles that are their own antiparticles. Since then, interest in these particles, known as Majorana fermions, has grown enormously given that they could play a role in creating a quantum supercomputer. Majoranas have already been described very well in theory. However, examining them and obtaining experimental evidence is difficult because they have to occur in pairs but are then usually bound to form one normal electron. Ingenious combinations and arrangements of various materials are therefore required to generate two Majoranas and keep them apart.

Collaboration between theory and practice

The group led by Professor Ernst Meyer has now used predictions and calculations by theoretical physicists Professor Jelena Klinovaja and Professor Daniel Loss (from the Swiss Nanoscience Institute and the University of Basel’s Department of Physics) to experimentally measure states that correspond to Majoranas. On a superconductor, the researchers evaporated single iron atoms with spin that, due to the row structure of the lead atoms, arrange themselves into a minute wire comprising one row of single atoms. The wires reached an astounding length of up to 70 nanometers.

Single Majoranas on the ends

The researchers examined these mono-atomic chains with the aid of scanning tunneling microscopy and, for the first time, with an atomic force microscope as well. Using the images and measurements, they found clear indications of the existence of single Majorana fermions on the ends of the wires under certain conditions and from a specific wire length on.

Despite the distance between them, the two Majoranas on the ends of the wires are still connected. Together, they form a new state extended across the whole wire that can either be occupied (“1”) or not occupied (“0”) by an electron. This binary property can then serve as the basis for a quantum bit (Qubit) and means that Majoranas, which are also very robust against a number of environmental influences, are promising candidates for creating a future quantum supercomputer.

Predicted wavefunction measured

The researchers from Basel have not only shown that single Majoranas can be generated and measured at the ends of an iron wire, they also performed the first experiment to show that Majoranas are extended quantum objects with an inner structure, as predicted by their theory colleagues. Over an area of several nanometers, the measurements showed the expected wavefunction with characteristic oscillations and twofold decay lengths, which have now been made visible for the first time.

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