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MSDL presentation Complex Systems: Ideas from Physics Indrani A. Vasudeva Murthy Modelling, Simulation and Design Lab (MSDL) School of Computer Science, McGill University, Montr eal, Canada 29 April 2005. Complex Systems: Ideas from Physics


  1. MSDL presentation Complex Systems: Ideas from Physics Indrani A. Vasudeva Murthy Modelling, Simulation and Design Lab (MSDL) School of Computer Science, McGill University, Montr´ eal, Canada 29 April 2005. Complex Systems: Ideas from Physics 1/50

  2. Overview • What are complex systems ? – Examples; Common Characteristics. – Disorder to Order; Scale Invariance, fractals and power laws. – Critical Phenomena; self-organization and emergent behaviour. – Simplicity and Complexity; equilibrium and non-equilibrium. • Self Organized Criticality (SOC) – Examples and Models. • Concluding remarks. 29 April 2005. Complex Systems: Ideas from Physics 2/50

  3. What are Complex Systems ? Examples • The universe – galaxies – stars and planetary systems. • Weather, rainfall, earthquakes, forest fires, epidemics. • Traffic jams, the economy and stock market. • Biological evolution, ecoystems, social behaviour: insect colonies and swarms, flocking of birds and herding of animals; crowd behaviour; predator-prey systems. • Pattern formation: zebra stripes, insect wings, leopard spots, sea shells. • The human brain, the immune system. • Organs — tissues — cells. 29 April 2005. Complex Systems: Ideas from Physics 3/50

  4. Common Characteristics • A very large number of interacting units. • The emergence of ‘order’ from ‘disorder’: collective or co-operative behaviour not obvious from the individual behaviour – leading to self-organization and emergent behaviour. • Highly non-linear; feedback and adaptation. • Individual units obey simple local rules. Leads to optimization, with a parallel evaluation of options. • Hierarchical complexity - complexity on several length scales. • Power laws, scale invariance, self-similarity. 29 April 2005. Complex Systems: Ideas from Physics 4/50

  5. Common Characteristics • Driven dynamical systems which are far from thermodynamic equilibrium. • Computationally complex: computer models and simulation, interdisciplinary. • Mathematical techniques: non-linear differential equations, cellular automata and difference equations, probability and stochastic theory, graph theory, game theory, genetic algorithms... • Self-organized criticality : a possible mechanism explaining some features. 29 April 2005. Complex Systems: Ideas from Physics 5/50

  6. Disorder to Order • Equilibrium phase transitions or critical phenomena from a disordered phase to an ordered phase as some parameter is varied, such as temperature. • Disordered phase above a critical temperature T C , ordered phase below it. Spontaneous symmetry breaking: state of higher symmetry to lower symmetry ; higher entropy to lower entropy. • Gas – liquid and liquid – crystal transitions: first order, discontinous. • Paramagnet – ferromagnet; normal metal – superconductor, normal fluid – superfluid transitions; second order, continuous. • Can define an order parameter : zero in the disordered phase and non-zero in the ordered phase; discontinuous or continuous. 29 April 2005. Complex Systems: Ideas from Physics 6/50

  7. The Gas–Liquid–Solid Transition Disordered Gas Ordered Crystal T > Tc T < Tc 29 April 2005. Complex Systems: Ideas from Physics 7/50

  8. The Ferromagnetic Transition Paramagnet Ferromagnet T > Tc T < Tc After Chaikin and Lubensky, Principles of Condensed Matter Physics 29 April 2005. Complex Systems: Ideas from Physics 8/50

  9. Scale Invariance – Self Similarity • Scale Invariance or Self Similarity: an object ‘looks the same’ at any length scale. • Self similar objects: fractals : have fractional dimensions. • Fractals occur everywhere in nature; both spatial and temporal fractals. • Spatial fractals: coastlines, clouds, river networks, blood vessels in the lungs, folds in the brain, . . . • Temporal fractals: light emitted from quasars, highway traffic, sunspot activity, pressure variations in air caused by music, the height of the river Nile, . . . 29 April 2005. Complex Systems: Ideas from Physics 9/50

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  11. ➙ ➛Ý à Ø Ö ➝ß ➣ ❐ Ö ❒ ↕ ➙ ❒ ➝ ➜ ➛Ý ❐ ß Ö ➙ ↔ ➝ß Û ✃ Û ➙ ➙ ➮ ➛ Û ↕ Ø Ö ➝ß Û ➛ ➝ ➮ Ý ß Ö à ➱ Ø ➙ Ö Ø ➣ Û Ü Ó Ø ➣Ø × ➱ ➝ ÕÖ ➱ Ô Ó Ó Ö Ò Ñ ÏÐ Ï ❰ ❮ ❒ ✃❐ ↔ ➣ ➣ ➞ ➣ ➙➛ ➞ ➙ ➛ Þ ➷ ➛Ý ➙Ü ➛ Û ✃❐Û → ↔ ➣ ➙ Ø Ø Ú ➷ ➛ ÖÙ Ø ➝ ➣ ➮➱ ➛ ➝ ➜ ➛Ý ❒ ↕ Ý ➝ ➙ ➮ ➙ ❒ ➛ Ô ➱ Ö ➞ Ù ➙ ➝ Ûâ ➣ ➙ ➝➞ ❐ Û ➮ ↕❐ ➝ ✃ ❐ ➣ â Û ➛ ➝ ➞ ➮ ➙ ↕ ➮ Ø Ö ➣ ❒ ➙ ➛ ✃ ➜ Ý ❐ Û ß ➣ Ö ➞ ➙➛ ➛ ❒ ➣ ➝ ß ß Û ➣ ✃ ❐ ❐ Ö ✃ ❐ ➛Ý ➣ ❐ ➝ ➙ ❐ ➙ Ö ➮ ➝ á ➷ Ý ➛ ➛ Ö ❐ Ø Ö ß ↕ Ý ß Ö ❐ ❒ ➙ ➝ ➣ ➅ ➄ ➀ ➄ ➀➇ ❷ ❾ ➆ ❸ ➃➄ ➊ ➂ ➀➁ ❾❿ ❽ ❼❽ ❻ ❹❺ ❸ ❷ ➈➉ ➃ ⑩ ➎ ➉ ❸ ➬ ❸ ➄ ➀ ➐ ➉ ➏ ❾ ➀➋ ❸ ➍ ➉ ➁ ❾ ❸ ➃➌ ❿ ❾ ❶ ⑨ ➒ ➞ ➣ ➝ ß ➜ ➙ ➝ ✈ ✉ t ❐ Û ✃ ➛ãä å Þ ➙ ➛ Û Û ➷ Û ➣ ⑧ ➙ ⑤⑥⑦ ④ ②③ ✈ ① t ✈ ✇ t â ➞ ➙ ➣ ❐ ❐ ➛ ß ➮ ➛ ➙ ➊ ➑ ➏ ➨➩➯ ➶ ➾ ➤ ➩ ➠ ➢ ➶ ➾ ➩➪ ➦ ➺ ➵➚ ➤ ➤➭➾ ➨➫ ➩ ➺ ➓ ➯ ➢➤➥ ➯ ➺➼➽ ➭➘ ➤➭➷ ➫ ➨ ➩ ➨ ➦ ➩ ➘ ➴ ➩ ➡ ➶ ➾ ➥ ➡ ➨ ➾ ➳ ➹ ➽ ➦ ➤ ➡ ➏ ➊ ➉ ➧➨ ➑ ➄ ❸ ❿ ➐ ➁ ➒ →➣ ❾ ➊ ➉ ❸ ➑ ❸ ➈ ➔ ➐ ❾ ❸ ↔ ↕➙➛➜ ➦ ➥ ➢➤ ➡➻ ➧➺ ➨ ➩ ➤➵➸ ➳ ➨ ➧ ➩ ➡ ➩➯➲ ➤➭ ➨➫ ➧➨➩ ➦ ➠➡➢➤➥ ➙➝➞➟ ➙ 29 April 2005. 250 300 350 400 450 500 550 600 Statistical Fractals: Stock Index 1991 1992 S&P 500 - 5 Years 1993 440 460 480 500 520 540 560 1994.6 1994 Complex Systems: Ideas from Physics 1994.8 1995 S&P 500 - 1 Year 1995 150 200 250 300 350 400 450 500 550 1986 1995.2 1988 1995.4 S&P 500 - 10 Years 1990 1992 1994 11/50

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