Curriculum Vitae
Total Page:16
File Type:pdf, Size:1020Kb
Load more
Recommended publications
-
Complexity” Makes a Difference: Lessons from Critical Systems Thinking and the Covid-19 Pandemic in the UK
systems Article How We Understand “Complexity” Makes a Difference: Lessons from Critical Systems Thinking and the Covid-19 Pandemic in the UK Michael C. Jackson Centre for Systems Studies, University of Hull, Hull HU6 7TS, UK; [email protected]; Tel.: +44-7527-196400 Received: 11 November 2020; Accepted: 4 December 2020; Published: 7 December 2020 Abstract: Many authors have sought to summarize what they regard as the key features of “complexity”. Some concentrate on the complexity they see as existing in the world—on “ontological complexity”. Others highlight “cognitive complexity”—the complexity they see arising from the different interpretations of the world held by observers. Others recognize the added difficulties flowing from the interactions between “ontological” and “cognitive” complexity. Using the example of the Covid-19 pandemic in the UK, and the responses to it, the purpose of this paper is to show that the way we understand complexity makes a huge difference to how we respond to crises of this type. Inadequate conceptualizations of complexity lead to poor responses that can make matters worse. Different understandings of complexity are discussed and related to strategies proposed for combatting the pandemic. It is argued that a “critical systems thinking” approach to complexity provides the most appropriate understanding of the phenomenon and, at the same time, suggests which systems methodologies are best employed by decision makers in preparing for, and responding to, such crises. Keywords: complexity; Covid-19; critical systems thinking; systems methodologies 1. Introduction No one doubts that we are, in today’s world, entangled in complexity. At the global level, economic, social, technological, health and ecological factors have become interconnected in unprecedented ways, and the consequences are immense. -
Fractal Expressionism—Where Art Meets Science
Santa Fe Institute. February 14, 2002 9:04 a.m. Taylor page 1 Fractal Expressionism—Where Art Meets Science Richard Taylor 1 INTRODUCTION If the Jackson Pollock story (1912–1956) hadn’t happened, Hollywood would have invented it any way! In a drunken, suicidal state on a stormy night in March 1952, the notorious Abstract Expressionist painter laid down the foundations of his masterpiece Blue Poles: Number 11, 1952 by rolling a large canvas across the oor of his windswept barn and dripping household paint from an old can with a wooden stick. The event represented the climax of a remarkable decade for Pollock, during which he generated a vast body of distinct art work commonly referred to as the “drip and splash” technique. In contrast to the broken lines painted by conventional brush contact with the canvas surface, Pollock poured a constant stream of paint onto his horizontal canvases to produce uniquely contin- uous trajectories. These deceptively simple acts fuelled unprecedented controversy and polarized public opinion around the world. Was this primitive painting style driven by raw genius or was he simply a drunk who mocked artistic traditions? Twenty years later, the Australian government rekindled the controversy by pur- chasing the painting for a spectacular two million (U.S.) dollars. In the history of Western art, only works by Rembrandt, Velazquez, and da Vinci had com- manded more “respect” in the art market. Today, Pollock’s brash and energetic works continue to grab attention, as witnessed by the success of the recent retro- spectives during 1998–1999 (at New York’s Museum of Modern Art and London’s Tate Gallery) where prices of forty million dollars were discussed for Blue Poles: Number 11, 1952. -
Laplace's Deterministic Paradise Lost ?
“We may regard the present state of the universe as the effect of its past and the cause of its future. An intellect which at a certain moment would know all forces that set nature in motion, and all positions of all items of which nature is composed, if this intellect were also vast enough to submit these data to analysis, it would embrace in a single formula the movements Laplace’s deterministic paradise lost of the greatest bodies of the universe and those of the tiniest atom; for such an intellect nothing would be uncertain and the future just like the past would be present before its eyes.” Miguel Angel Fuentes Santa Fe Institute, USA Pierre-Simon Laplace, ~1800 Instituto Balseiro and CONICET, Argentina Santa Fe Institute Santa Fe Institute Comments: Heisenberg uncertainty principle In the framework of quantum mechanics -one of the most successful created theories- is not possible to know -at the Einstein was very unhappy about this apparent randomness same time- the position and velocity of a given object. (~1927) in nature. His views were summed up in his famous phrase, 'God does not play dice.' ∆v ∆x m > h v v v (from Stephen Hawking’s lecture) ? Santa Fe Institute Santa Fe Institute In chaotic (deterministic) systems Same functionality (SAME ORGANISM) x(t) Not chaotic trajectory x(0) = c ∆x ± t ? Some expected initial condition + Mutations Santa Fe Institute Santa Fe Institute Same functionality (SAME ORGANISM) Many process can happen between regular-chaotic behavior Chaotic trajectory Some expected initial condition + Mutations Santa Fe Institute Santa Fe Institute 4.1 Parameter Dependence of the Iterates 35 4.1 Parameter Dependence of the Iterates 35 r values are densely interwr values oarevedenselyn andinterwoneovfindsen and onea sensitifinds a sensitive dependenceve dependence ononparameterparametervalues.values. -
Self-Organized Complexity in the Physical, Biological, and Social Sciences
Introduction Self-organized complexity in the physical, biological, and social sciences Donald L. Turcotte*† and John B. Rundle‡ *Department of Earth and Atmospheric Sciences, Cornell University, Ithaca, NY 14853; and ‡Cooperative Institute for Research in Environmental Sciences, University of Colorado, Boulder, CO 80309 he National Academy of Sciences convened an Arthur M. A complex phenomenon is said to exhibit self-organizing TSackler Colloquium on ‘‘Self-organized complexity in the phys- complexity only if it has some form of power-law (fractal) ical, biological, and social sciences’’ at the NAS Beckman Center, scaling. It should be emphasized, however, that the power-law Irvine, CA, on March 23–24, 2001. The organizers were D.L.T. scaling may be applicable only over a limited range of scales. (Cornell), J.B.R. (Colorado), and Hans Frauenfelder (Los Alamos National Laboratory, Los Alamos, NM). The organizers had no Networks difficulty in finding many examples of complexity in subjects Another classic example of self-organizing complexity is drain- ranging from fluid turbulence to social networks. However, an age networks. These networks are characterized by the concept acceptable definition for self-organizing complexity is much more of stream order. The smallest streams are first-order streams— elusive. Symptoms of systems that exhibit self-organizing complex- two first-order streams merge to form a second-order stream, ity include fractal statistics and chaotic behavior. Some examples of two second-order streams merge to form a third-order stream, such systems are completely deterministic (i.e., fluid turbulence), and so forth. Drainage networks satisfy the fractal relation Eq. -
Asian Nobel Prize' for Mapping the Universe 27 May 2010
Scientists win 'Asian Nobel Prize' for mapping the universe 27 May 2010 Three US scientists whose work helped map the category. universe are among the recipients of the one- million-US-dollar Shaw Prize, known as the "Asian (c) 2010 AFP Nobel," the competition's organisers said Thursday. Princeton University professors Lyman Page and David Spergel and Charles Bennett of Johns Hopkins University, won the award for an experiment that helped to determine the "geometry, age and composition of the universe to unprecedented precision." The trio will share the Shaw Prize's award for astronomy, with one-million-US-dollar prizes also awarded in the categories for mathematical sciences and life sciences and medicine. The University of California's David Julius won the award for life sciences and medicine for his "seminal discoveries" of how the skin senses pain and temperature, the organisers' statement said. "(Julius's) work has provided insights into fundamental mechanisms underlying the sense of touch as well as knowledge that opens the door to rational drug design for the treatment of chronic pain," the statement said. Princeton's Jean Bourgain won an award for his "profound work" in mathematical sciences, it said. The Shaw Prize, funded by Hong Kong film producer and philanthropist Run Run Shaw and first awarded in 2004, honours exceptional contributions "to the advancement of civilization and the well-being of humankind." The awards will be presented at a ceremony in Hong Kong on September 28. Last year, two scientists whose work challenged the assumption that obesity is caused by a lack of will power won the life sciences and medicine 1 / 2 APA citation: Scientists win 'Asian Nobel Prize' for mapping the universe (2010, May 27) retrieved 27 September 2021 from https://phys.org/news/2010-05-scientists-asian-nobel-prize-universe.html This document is subject to copyright. -
Professor Peter Goldreich Member of the Board of Adjudicators Chairman of the Selection Committee for the Prize in Astronomy
The Shaw Prize The Shaw Prize is an international award to honour individuals who are currently active in their respective fields and who have recently achieved distinguished and significant advances, who have made outstanding contributions in academic and scientific research or applications, or who in other domains have achieved excellence. The award is dedicated to furthering societal progress, enhancing quality of life, and enriching humanity’s spiritual civilization. Preference is to be given to individuals whose significant work was recently achieved and who are currently active in their respective fields. Founder's Biographical Note The Shaw Prize was established under the auspices of Mr Run Run Shaw. Mr Shaw, born in China in 1907, was a native of Ningbo County, Zhejiang Province. He joined his brother’s film company in China in the 1920s. During the 1950s he founded the film company Shaw Brothers (HK) Limited in Hong Kong. He was one of the founding members of Television Broadcasts Limited launched in Hong Kong in 1967. Mr Shaw also founded two charities, The Shaw Foundation Hong Kong and The Sir Run Run Shaw Charitable Trust, both dedicated to the promotion of education, scientific and technological research, medical and welfare services, and culture and the arts. ~ 1 ~ Message from the Chief Executive I warmly congratulate the six Shaw Laureates of 2014. Established in 2002 under the auspices of Mr Run Run Shaw, the Shaw Prize is a highly prestigious recognition of the role that scientists play in shaping the development of a modern world. Since the first award in 2004, 54 leading international scientists have been honoured for their ground-breaking discoveries which have expanded the frontiers of human knowledge and made significant contributions to humankind. -
David Spergel Is the Director of the Center for Computational Astrophysics and the Charles Young Professor of Astronomy at Princeton University
David Spergel is the director of the Center for Computational Astrophysics and the Charles Young Professor of Astronomy at Princeton University. He is the former chair of the Space Studies Board. Using microwave background observations from the Wilkinson Microwave Anisotropy Probe (WMAP) and the Atacama Cosmology Telescope, Spergel has measured the age, shape and composition of the universe. These observations have played a significant role in establishing the standard model of cosmology. He is one of the leaders of the Simons Observatory, which will include a planned millimeter-wave telescope that will allow us to take the next step in studying the microwave sky and probing the history of the universe. Spergel is currently co-chair of the Wide Field Infrared Survey Telescope (WFIRST) science team. WFIRST will study the nature of dark energy, complete the demographic survey of extrasolar planets, characterize the atmospheres of nearby planets and survey the universe with more than 100 times the field of view of the Hubble Space Telescope. Spergel has played a significant role in designing the coronagraph and in shaping the overall mission. Since completing my Ph.D. work, Spergel has been interested in using laboratory experiments and astronomical observations to probe the nature of dark matter and look for new physics. Recently, Spergel has been active in the exploration of data from the Gaia satellite and observations made by Subaru’s Hyper Suprime-Cam. Spergel serves as co-chair of the Global Coordination of Ground and Space Astrophysics working group of the International Astronomical Union. At Princeton, Spergel was department chair for a decade. -
Santa Fe Institute 2014 Complex Systems Summer School
Santa Fe Institute 2014 Complex Systems Summer School Introduction to Nonlinear Dynamics Instructor: Liz Bradley Department of Computer Science University of Colorado Boulder CO 80309-0430 USA [email protected] www.cs.colorado.edu/∼lizb Syllabus: 1. Introduction; Dynamics of Maps chs 1 & 10 of [52] • a brief tour of nonlinear dynamics [34] (in [18]) • an extended example: the logistic map – how to plot its behavior – initial conditions, transients, and fixed points – bifurcations and attractors – chaos: sensitive dependence on initial conditions, λ, and all that – pitchforks, Feigenbaum, and universality [23] (in [18]) – the connection between chaos and fractals [24], ch 11 of [52] – period-3, chaos, and the u-sequence [33, 36] (latter is in [18]) – maybe: unstable periodic orbits [3, 26, 51] 2. Dynamics of Flows [52], sections 2.0-2.3, 2.8, 5, and 6 (except 6.6 and 6.8) • maps vs. flows – time: discrete vs. continuous – axes: state/phase space [10] • an example: the simple harmonic oscillator – some math & physics review [9] – portraying & visualizing the dynamics [10] • trajectories, attractors, basins, and boundaries [10] • dissipation and attractors [44] • bifurcations 1 • how sensitive dependence and the Lyapunov exponent manifest in flows • anatomyofaprototypicalchaoticattractor: [24] – stretching/folding and the un/stable manifolds – fractal structure and the fractal dimension ch 11 of [52] – unstable periodic orbits [3, 26, 51] – shadowing – maybe: symbol dynamics [27] (in [14]); [29] • Lab: (Joshua Garland) the logistic map and the driven pendulum 3. Tools [2, 10, 39, 42] • ODE solvers and their dynamics [9, 35, 37, 46] • Poincar´esections [28] • stability, eigenstuff, un/stable manifolds and a bit of control theory • embedology [30, 31, 32, 41, 48, 49, 47, 54] ([41] is in [39] and [47] is in [55];) • Lab: (Joshua Garland) nonlinear time series analysis with the tisean package[1, 32]. -
The Impotent Fury of William Dembski
THE DESIGN REVOLUTION? How William Dembski Is Dodging Questions About Intelligent Design By Mark Perakh Who is William A. Dembski? We are told that he has PhD degrees in mathematics and philosophy plus more degrees - in theology and what not – a long list of degrees indeed. [1] To acquire all those degrees certainly required an unconventional penchant for getting as many degrees as possible. We all know that degrees alone do not make a person a scientist. Scientific degrees are not like ranks in the military where a general is always above a mere colonel. Degrees are only a formal indicator of a person’s educational status. A scientist’s reputation and authority are based on his degrees only to a negligible extent. What really attests to a person’s status in science is publications in professional journals and anthologies and references to one’s work by colleagues. This is the domain where Dembski has so far remained practically invisible. All his multiple publications have little or nothing to do with science. He is a mathematician who did not prove any theorem and derived not a single formula. When he writes about probability theory or information theory -- on which he is proclaimed to be an expert -- the real experts in these fields (using the words of the prominent mathematician David Wolpert) “squint, furrow one's brows, and then shrug.” [2] When encountering critique of his work, Dembski is selective in choosing when to reply to his critics and when to ignore their critique. His preferred targets for replies are those critics who do not boast comparable long lists of formal credentials – this enables him to contemptuously dismiss the critical comments by pointing to the alleged lack of qualification of his opponents while avoiding answering the essence of their critical remarks. -
MATTERS of GRAVITY Contents Editor
MATTERS OF GRAVITY The newsletter of the Topical Group on Gravitation of the American Physical Society Number 17 Spring 2001 Contents APS TGG News: APS Prize on gravitation, by Clifford Will .................. 3 TGG Elections, by David Garfinkle ...................... 3 We hear that, by Jorge Pullin ......................... 3 Research Briefs: Experimental Unruh Radiation?, by Matt Visser ............... 4 Why is the Universe accelerating?, by Beverly Berger ............ 6 The Lazarus Project, by Richard Price .................... 9 LIGO locks its first detector!, by Stan Whitcomb ............... 12 Progress on the nonlinear r-mode problem, by Keith Lockitch ........ 13 Conference Reports Analog Models of General Relativity, by Matt Visser ............. 17 Astrophysical Sources of Gravitational radiation, by Joan Centrella ..... 19 Numerical relativity at the 20th Texas meeting, by Pablo Laguna ...... 21 Editor Jorge Pullin Center for Gravitational Physics and Geometry The Pennsylvania State University University Park, PA 16802-6300 Fax: (814)863-9608 Phone (814)863-9597 Internet: [email protected] WWW: http://www.phys.psu.edu/~pullin ISSN: 1527-3431 1 Editorial Not much to report here. If you are burning to have Matters of Gravity with you all the time, the newsletter is now available for Palm Pilots, Palm PC's and web-enabled cell phones as an Avantgo channel. Check out http://www.avantgo.com under technology science. The next newsletter is due September 1st. If everything goes well this newsletter should! be available in the gr-qc Los Alamos archives (http://xxx.lanl.gov) under number gr-qc/yymmnnn. To retrieve it send email to [email protected] with Subject: get yymmnnn (numbers 2-16 are also available in gr-qc). -
Multi-Agent Economics and the Emergence of Critical Markets
Multi-agent Economics and the Emergence of Critical Markets Michael S. Harr´e1 1Complex Systems Research Group, Faculty of Engineering and IT, The University of Sydney, Sydney, Australia. Abstract The dual crises of the sub-prime mortgage crisis and the global financial crisis has prompted a call for explanations of non-equilibrium market dynamics. Recently a promising approach has been the use of agent based models (ABMs) to simulate aggregate market dynamics. A key aspect of these models is the endogenous emergence of critical transitions between equilibria, i.e. market collapses, caused by multiple equilibria and changing market parameters. Several research themes have developed microeconomic based models that include multiple equilibria: social decision theory (Brock and Durlauf), quantal response models (McKelvey and Palfrey), and strategic complementarities (Goldstein). A gap that needs to be filled in the literature is a unified analysis of the relationship between these models and how aggregate criticality emerges from the individual agent level. This article reviews the agent-based foundations of markets starting with the individual agent perspective of McFadden and the aggregate perspective of catastrophe theory emphasising connections between the different approaches. It is shown that changes in the uncertainty agents have in the value of their interactions with one another, even if these changes are one-sided, plays a central role in systemic market risks such as market instability and the twin crises effect. These interactions can endogenously cause crises that are an emergent phenomena of markets. 1 Introduction Multi-agent models have grown in popularity [2, 5, 64, 9, 34, 37] as a way in which to simu- late complex market dynamics that might have no closed form solutions. -
What Is Important About the No Free Lunch Theorems? 3
What is important about the No Free Lunch theorems? David H. Wolpert Abstract The No Free Lunch theorems prove that under a uniform distribution over induction problems (search problemsor learning problems), all induction algorithms perform equally. As I discuss in this chapter, the importanceofthe theoremsarises by using them to analyze scenarios involving non-uniform distributions, and to compare different algorithms, without any assumption about the distribution over problems at all. In particular, the theorems prove that anti-cross-validation (choosing among a set of candidate algorithms based on which has worst out-of-sample behavior) performs as well as cross-validation, unless one makes an assumption — which has never been formalized — about how the distribution over induction problems, on the one hand,is relatedto the set of algorithmsone is choosingamong using (anti-)cross validation, on the other. In addition, they establish strong caveats concerning the significance of the many results in the literature which establish the strength of a particular algorithm without assuming a particular distribution. They also motivate a “dictionary” between supervised learning and improve blackbox optimization, which allows one to “translate” techniques from supervised learning into the domain of blackbox optimization, thereby strengthening blackbox optimization algorithms. In addition to these topics, I also briefly discuss their implications for philosophy of science. 1 Introduction arXiv:2007.10928v1 [cs.LG] 21 Jul 2020 The first of what are now called the No Free Lunch (NFL) theorems were published in [1]. Soon after publication they were popularizedin [2], building on a preprint ver- sion of [1]. Those first theorems focused on (supervised) machine learning.