Probing General Relativity with the Event Horizon Telescope

The first resolved images of the strong-gravity region of a black hole will soon be produced by the Event Horizon Telescope (EHT).  I will discuss the significant instrumental, observational, and theoretical efforts of the EHT collaboration that have come together in order to probe the strong-field gravity regime of the black hole in the center of our Galaxy in SgrA* and in the galaxy M87.  I will highlight the challenges of interpreting past and future observations, which require state-of-the-art computational physics simulations of the plasma, black hole, and the polarized radiation.  Such simulation models reveal a wealth of information that can be used to probe (and potentially test) Einstein's general relativity in the strong-field regime.

Economic Complexity

Economic Complexity (EC) is a new field of research that consists in a radically new methodology. It describes economics as evolutionary process of ecosystems made of industrial and financial technologies that are all globally interconnected. The approach is multidisciplinary addressing emerging phenomena in economics from different points of view: analysis of complex systems, scientific methods for systems and the recent developments in Big Data. This approach offers new opportunities to constructively describe technological ecosystems, analyse their structures, understand their internal dynamics, as well as to introduce new metrics. This approach provides a new paradigm for a fundamental economic science based on data and not on ideologies or interpretations, which is becoming a necessary choice in a highly interconnected and globalized world, especially after the great financial and economic crisis of recent years.

Economic Complexity, in addition to a new vision for a data-based scientific approach for fundamental economics, offers a new set of metrics able to quantify the competitiveness of countries, of technological sectors, measuring future development prospects for nations as well as for large companies. Those metrics have already shown to have a major impact for policy makers and for industry applications economics and finance. Over the last year, the World Bank (WB) has extensively tested and adopted this new methodology for its strategic analysis.

A crucial element of our methodology is a radically new approach to the problem of Big Data. Big Data is often associated with "big noise" as well as a subjective ambiguity related to how to structure the data and how to assign them a value that should reflect many arbitrary parameters. In the case of the evaluation of the industrial competitiveness of a country, the required parameters for such an analysis could more than one hundred. A key point approach EC is to go from 100 parameters to zero parameters and obtain results which can be tested in a scientific perspective. This is done by focusing on the data in which the signal to noise ratio is optimal and developing iterative algorithms in the spirit, but other than Google, and optimized to the economic problem in question. In particular the study of a country or a company is not done at the individual level but through the global network in which it is inserted. In this way you get the Fitness of the countries and the Complexity of the products.

The dynamics in the new GDP-Fitness space [1] (opens up to a completely new way for monitoring and forecasting. Then, the taxonomy of products and their evolutionary dynamics is built through machine learning methods. Finally, the same thing is applied to patents and technologies, two elements that open up the possibility of analyzing the core elements of the innovation process.

[1] M. Cristelli, A. Tacchella, L. Pietronero: The Heterogeneous Dynamics of Economic Complexity, PLOS One 10(2): e0117174 (2015) and Nature editorial on EC:

:http://www.nature.com/news/physicists-make-weather-forecasts-for-economies-1.16963

Luciano Pietronero studied physics in Rome and was a research scientist at Xerox Research in Webster (1974) and Brown Boveri Research Center (CH) 1975-1983. He then moved to Univ. of Groningen (NL), where he was professor ofCondensed Matter Theory (1983-87). Since 1987 he is professor of Physics at theUniversity of Rome. Founder and director of the Institute for ComplexSystems of CNR (2004-2014). Broad international experience in academic andindustrial enviroments. The scientific activity is of both fundamental and appliednature, with a problem oriented interdisciplinary perspective. Development of noveland original views in all the areas of activity. Leader of a generation of joungscientists who are protagonists of the complexity scene internationally.In 2008 he received the Fermi Prize (highest award of the Italian Physical Society).Research interests Condensed Matter Theory; High-temperature superconductivity;Statistical Physics; Fractal Growth; Self-Organized- Criticality; Complex Systems andits interdisciplinary applications. Recent activity: http://www.lucianopietronero.it/

New Interface between Quantum Optics and Nanoscience: the Bottom-Up Approach and Applications 

In this talk I will present a few recent advances from my group, centering on a new interface between ultrafast quantum optics and nanoscience through bottom-up materials design. I will particularly focus on development of emerging colloidal hybrid nanostructures that can allow desirable integration of multiple functionalities in one single nanoscale unit to create novel synergistic interactions. By combining ultrafast optical spectroscopy with this new materials advance, precise control of quantum optical interactions can thus be achieved at the nanoscale. This has further led to all optical spin manipulation and spin echo by light-matter interaction in well-designed hybrid semiconductor quantum structures, which is crucial for understanding many body spin physics and developing novel nanoscale quantum devices. Potential applications of such a bottom-up approach will also be described.

Life After Grad School for the Quantitatively Inclined -- Big Banks, Start-ups, and the Great In-between

Phase Transitions and Criticality in Biological Networks: Implications for Genes and Neurons

Moore’s Law and the Physics of Manufacturing Nanoscale Devices

Perturbation and Control of Human Brain Network Dynamics

 The human brain is a complex organ characterized by heterogeneous patterns of interconnections. New non-invasive imaging techniques now allow for these patterns to be carefully and comprehensively mapped in individual humans, paving the way for a better understanding of how wiring supports our thought processes. While a large body of work now focuses on descriptive statistics to characterize these wiring patterns, a critical open question lies in how the organization of these networks constrains the potential repertoire of brain dynamics.
In this talk, I will describe an approach for understanding how perturbations to brain dynamics propagate through complex writing patterns, driving the brain into new states of activity. Drawing on a range of disciplinary tools – from graph theory to network control theory and optimization – I will identify control points in brain networks, characterize trajectories of brain activity states following perturbation to those points, and propose a mechanism for how network control evolves in our brains as we grow from children into adults. Finally, I will describe how these computational tools and approaches can be used to better understand how the brain controls its own dynamics (and we in turn control our own behavior), but also how we can inform stimulation devices to control abnormal brain dynamics, for example in patients with severe epilepsy.

Quantum Information Processing and Raising Schrödinger’s Cat

Research on precise control of coherent quantum systems occurs in many laboratories throughout the world, for fundamental research, new measurement techniques, and more recently for the development of quantum computers. I will briefly describe experiments on these topics using trapped ions at the National Institute of Standards and Technology (NIST) but these just serve as examples of similar work being performed with many other atomic, molecular, optical (AMO) and condensed matter systems. This talk is, in part, the “story” of my involvement in these subjects which began when I entered graduate school.

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Hidden Momentum

Electromagnetic fields carry energy, momentum, and even angular momentum. The momentum density is εo(E×B), and it accounts (among other things) for the pressure of light. But even static fields can harbor momentum, and this would appear to contradict a general theorem: if the center of energy of a closed system is at rest, then its total momentum must be zero. Evidently in such cases there lurks some other momentum, not electromagnetic in nature, equal and opposite to the field momentum. But finding this “hidden momentum” can be surprisingly subtle. I’ll discuss a particularly nice example.

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From Einstein's Theory to Gravity's
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Plutopia