Santa Fe Institute Events Wiki - User contributions [en]

Presentations 2012

2012-06-27T19:05:19Z

Duenas:

{{Complex Systems Summer School 2012}}

9:00 - 9:15: Christa Brelsford and Xin Lu: Changes in Social Network Structure in Response to Crisis: Using Twitter data to Explore the Effect of the Tōhoku Earthquake.

9:15 - 9:30: Piotr Milanowski and Georg F. Weber: Enzyme kinetics and the outcome of chemical reactions.

9:30 - 9:45: Fabio, Elena, Tom and Friederike: Collaboration in times of stress: an Agent Based Modelling approach

9:45 - 10:00: Joanne, Vikram, Matteo, Sanith: Price-time Dynamics of Contracts Traded on Prediction Markets

10:15 - 10:45: BREAK

10:45 - 11:00: Katrien, Jasmeen, Sandro, Cameron, Vanessa

11:15 - 11:30: Xue, Χλοε, Xiaoli

11:30 - 11:45: Seth, Daniel, Cameron: flocking in iterated reasoning.

12:00 - 1:15: LUNCH

1:15 - 1:30: Andres, Charlie, Gareth, and Nic G: We Got the Skills to Pay the Bills - Exploring the Link Between Occupation Diversity and Innovation

1:30 - 1:45: Xin and Abby

1:45 - 2:00: Sepehr

2:00 - 2:15: Ben, Laurent, Oscar, Georg: The Targeting and Timing of Treatment Influences the Emergence of Influenza Resistance in Structured Populations

2:15 - 2:30: Georg, Ben, Laurent, Oscar: Escaping the Poverty Trap: Modeling the Interplay Between Economic Growth and the Ecology of Infectious Disease

2:30 - 2:45: Ian, Marco, Oleksandr and Xin: Space of complex networks and robustness

2:45 - 3:00: BREAK

3:00 - 3:15: Marco and Matteo: Trade network formation: the role of technology and geography

5:00: Final Remarks & Farewell Dinner

Complex Systems Summer School 2012-Project Presentations

2012-06-27T06:59:44Z

Duenas:

{{Complex Systems Summer School 2012}}

Use this space to post project presentations and outlines. Include group members, a brief outline, and your slides.

=== Price-time Dynamics of Contracts Traded on Prediction Markets ===

Joanne, Vikram, Matteo, Sanith

Prediction markets have been shown to outperform traditional methods of polls and opinion surveys in forecasting future events. The futures contracts traded in these markets assess the expectation of occurrence of a variety of events spread across multiple domains (political, economic, entertainment, financial and weather). We explore the feasibility of 'predicting' the outcome of binary true/false prediction market contracts ahead of their expiry date using a neural-network based machine learning approach. In addition we focus on the characteristics of political-based contracts to establish whether they exhibit characteristic 'fundamental' properties.

=== How Complex Languages Replicate through Simple Brains ===

Katrien, Vanessa, Sandro, Cameron, Jasmeen

Through the use of an iterated learning experiment, we investigated the transmission of a "high entropy", randomised initial language through successive generations of participants. We want to see what features of the language replicated most easily, and what structure emerged by the end of the chain. Our hypothesis is that the language converges to a "low entropy" equilibrium state with a minimal number of words, morphemes, and form-meaning distinctions.

=== Collaboration in times of stress: an Agent Based Modelling approach ===

Fabio Cresto Aleina, Elena del Val, Tom Fennewald and Friederike Greb

We want to investigate the influence of exogenous stress on cooperative behaviour. We propose an agent based model in which the agents can be interpreted as farmers living in a water limited environment. With changes in precipitation patterns, the farmers undergo stress, and we observe how this impacts relationships among farmers and their properties.

=== Simple variation of the logistic map as a model to invoke questions on cellular protein trafficking ===
(Sepehr Ehsani, http://arxiv.org/abs/1206.5557)

Many open problems in biology, as in the physical sciences, display nonlinear and 'chaotic' dynamics, which, to the extent possible, cannot be reasonably understood. Moreover, mathematical models which aim to predict/estimate unknown aspects of a biological system cannot provide more information about the set of biologically meaningful (e.g., 'hidden') states of the system than could be understood by the designer of the model ab initio. Here, the case is made for the utilization of such models to shift from a 'predictive' to a 'questioning' nature, and a simple natural-logarithm variation of the logistic polynomial map is presented that can invoke questions about protein trafficking in eukaryotic cells.

===Changes in Social Network Structure in Response to Crisis: Using Twitter data to Explore the Effect of the Tōhoku Earthquake.===

Christa Brelsford and Xin Lu

Abstract:
We use twitter data from 7 days before and after the Tōhoku Earthquake to explore how cooperation rates, social network structure and connectivity, and social network vulnerability changed in Japan in response to the disaster. An English language data set is collected for the same time period to use as a control. Data is collected for a period of 96 hours starting from March 4th 2011 2:46pm JST and for 96 hours beginning March 11th 2011 2:46 pm JST. The rate of cooperative behavior, measured by the occurrence of helping words in tweets increases slightly in the English dataset and by an order of magnitude in the Japanese dataset. A network analysis is also performed. Network edges are retweets and direct messages. In future work, we hope to explore whether problem solving capacity in a social system changes in response to crises, based on changes in the rate of cooperation and information transfer in a network.

=== The CSSS Network ===

Tom & Riccardo (with JP and others)

We will investigate the questions you are dying to know: What interesting interactions are revealed from the first 3 weeks of the Complex System Summer School survey? Have barriers between academic disciplines been broken down? Do power laws fit the data!? ...

Let us know if you have specific questions or if you would like to be involved in data analysis!

=== Is there a method in the madness? the dynamic structures of human language use ===

Priya and Riccardo

Psychiatric anecdotal reports point to the monotony, lack of emotion and sometimes intelligibility in many clinical populations. Linear measures of fluency and prosody, however, present only controversial differences between patients and healthy controls and only in unnatural phonations (i.e. say "aaaaa" for 30 secs).
We therefore go complex and chaotic on a set of more ecological recordings and transcriptions from 4 clinical populations (Asperger's, Schizophrenics, Depressed and Right Hemisphere Damage patients) as well as from healthy controls.
We then set a classifier-driven race: will non-linear analyses outcompete linear analyses in discriminating between pathologies?

=== Escaping the Poverty Trap: Modeling the Interplay Between Economic Growth and the Ecology of Infectious Disease ===

Georg, Ben, Laurent, Oscar

The dynamics of economies and infectious disease are inexorably linked: economic well-being influences health (sanitation, nutrition, etc) and health influences economic well-being (labor productivity lost to sickness and disease). Often societies are locked into "poverty traps" of poor health and poor economy. Here, we demonstrate poverty traps formed in models of infection and endogenous growth, as well as ways to break out of poverty traps. We explore two mechanisms of escape: one, through an influx of capital, and another through changing the percentage of GDP spent on healthcare. We find large influxes of capital is successful, but increasing health spending does not. Our results have important policy implications in the distribution of aid and within-country healthcare spending.

=== The Targeting and Timing of Treatment Influences the Emergence of Influenza Resistance in Structured Populations ===

Ben, Laurent, Oscar, Georg

Evolution of antiviral resistance in influenza carries large societal impacts through morbidity and mortality caused by treatment failure. Several previous studies put forth theory regarding the optimal timing, targeting and absolute level of treatment in populations. Few of these studies, however, have considered populations with explicit structure. Here we present a model of antiviral resistance on networks and explore the timing, targeting and levels of treatment. Interestingly, we find bistability as a result of treatment leading to the existence of an unstable manifold, above which successful treatment (i.e.: no resistance) is impossible. We find, contrary to previous results, that degree-targeted treatment is not optimal, and leads to higher levels of resistance than random treatment. Additionally, in accordance with previous results, we find an optimum level of treatment which is less than 100%. These findings findings have important consequences in guiding policy behind influenza treatment. The bistability indicates that caution should be taken when treating populations when the absolute numbers of infections are unknown. Positively, our results indicate that putting resources into targeted treatment is not necessary, random treatment is preferable.

=== Learning in Random Boolean Networks ===

Nick A., Keegan, Matteo, Vikram, Sarah, Mark

Inspired by biochemical networks which adapt on evolutionary timescales, neural networks that adapt during development and learning, and universal computation in cellular automata, we have implemented several models of learning in Random Boolean Networks (RBNs) in order to better understand the relationships between network structure, node interaction rules, and network output.

=== Enzyme Catalysis and the Outcome of Chemical Reactions ===
Piotr and Georg W.
Enzymes are catalysts that accelerate chemical reactions but do not affect their outcome. This traditional paradism was developed under artificail test tube conditions. Our project investigates the possibility that the presence of an enzyme can alter the course of a reaction if it takes place under more physiologic conditions.

=== How Does a Stochastic Environment affect Community Assembly? ===

Xue, Χλοε, Xiaoli

We are interested in how exogenous temporal variability in resource availability affects the community structure of organisms with different resource-use strategies. Organisms induce additional resource stress on each other through competition. This is an abstraction of an arid environment with unreliable rainfall; the organisms themselves have been abstracted to four unitless parameters that allocate their resources to different parts of their lifecycles. The system has memory, as the previous presence of an organism affects the resource transport mechanism (an abstraction of soil).

=== How Does a Network’s Structure Influence its Traceability? ===

Xin and Abby

We are interested in systematically studying the problem of finding the source of a contamination spread through a network. We model a contamination spreading through the food distribution network, which we represent by interconnections between farmers, distributors, and retailers, and construct an estimator for the outbreak source given only this structure. We show how the ability of the estimator to narrow down the source identification problem changes with the connectivity and the number of observations. We propose a measure for traceability, or the overall ability to identify the source of spreading given any set of outbreak observations, based on entropy. We show how this measure appropriately reflects the range of uncertainty in identifying the source. We believe this measure may be useful in the design of networks that are conducive to accurate identification of the source of contamination.

=== We Got the Skills to Pay the Bills: Exploring the Link Between Occupation Diversity and Innovation===

Andrés, Charlie, Gareth, and Nick

Where does diversity in skills or occupations come from and why does it lead to more innovative cities? Previous work in this area has shown that there is a scaling behaviour which allows citizens of larger cities to earn an extra 15% in income whilst making use of 15% fewer gas stations, for example. Making use of occupation, patent, and population data of US Metropolitan Statistical Areas (MSA), we try to understand what factors make successful cities. Here we assume that successful cities are those cities which are most innovative as determined by the production of patents. In addition we use agent-based modelling to explore how and why people acquire new skills and whether this leads to more productive cities.

=== Space of complex networks and robustness ===
Ian, Marco, Xin, and Oleksandr

Complex networks have various properties which can be measured in real networks (WWW, social networks, biological networks), e.g. degree distribution, modularity, hierarchy, assortativity etc. Robustness of complex networks is a big question, however only some progress have been done in this direction. For example, it was shown that the scale-free networks are much more topologically robust to random attacks than random networks. Various characteristics of complex networks might influence the robustness differently. The question is how?

We generated continuous topological space of networks with respect to degree distribution (from random to scale-free) and clustering (from none to high). Then we attacked the network by removing vertices randomly and highly connected (hubs). The next step is to calculate network robustness, it is non-trivial task because there are many different ways to do it. So far we calculate the size of giant component during attack process for the entire space.

=== Trade network formation: the role of technology and geography ===

Marco and Matteo

Geography and technology play important roles in economic activities, e.g. international trade flows diminish dramatically with distance; salaries, prices, and factor endowments vary across locations; and productivities are really different across countries' industries. International trade theories have gained some non-negligible reputation explaining the sizes of aggregated trade flows, nonetheless few attention has being payed to the formation of the bilateral trade relations. We develop a network formation model that incorporates differences in technological capabilities across countries and the effect of the geographical distance as a proxy of trade barriers.

Complex Systems Summer School 2012-Project Presentations

2012-06-27T06:58:16Z

Duenas:

{{Complex Systems Summer School 2012}}

Use this space to post project presentations and outlines. Include group members, a brief outline, and your slides.

=== Price-time Dynamics of Contracts Traded on Prediction Markets ===

Joanne, Vikram, Matteo, Sanith

Prediction markets have been shown to outperform traditional methods of polls and opinion surveys in forecasting future events. The futures contracts traded in these markets assess the expectation of occurrence of a variety of events spread across multiple domains (political, economic, entertainment, financial and weather). We explore the feasibility of 'predicting' the outcome of binary true/false prediction market contracts ahead of their expiry date using a neural-network based machine learning approach. In addition we focus on the characteristics of political-based contracts to establish whether they exhibit characteristic 'fundamental' properties.

=== How Complex Languages Replicate through Simple Brains ===

Katrien, Vanessa, Sandro, Cameron, Jasmeen

Through the use of an iterated learning experiment, we investigated the transmission of a "high entropy", randomised initial language through successive generations of participants. We want to see what features of the language replicated most easily, and what structure emerged by the end of the chain. Our hypothesis is that the language converges to a "low entropy" equilibrium state with a minimal number of words, morphemes, and form-meaning distinctions.

=== Collaboration in times of stress: an Agent Based Modelling approach ===

Fabio Cresto Aleina, Elena del Val, Tom Fennewald and Friederike Greb

We want to investigate the influence of exogenous stress on cooperative behaviour. We propose an agent based model in which the agents can be interpreted as farmers living in a water limited environment. With changes in precipitation patterns, the farmers undergo stress, and we observe how this impacts relationships among farmers and their properties.

=== Simple variation of the logistic map as a model to invoke questions on cellular protein trafficking ===
(Sepehr Ehsani, http://arxiv.org/abs/1206.5557)

Many open problems in biology, as in the physical sciences, display nonlinear and 'chaotic' dynamics, which, to the extent possible, cannot be reasonably understood. Moreover, mathematical models which aim to predict/estimate unknown aspects of a biological system cannot provide more information about the set of biologically meaningful (e.g., 'hidden') states of the system than could be understood by the designer of the model ab initio. Here, the case is made for the utilization of such models to shift from a 'predictive' to a 'questioning' nature, and a simple natural-logarithm variation of the logistic polynomial map is presented that can invoke questions about protein trafficking in eukaryotic cells.

===Changes in Social Network Structure in Response to Crisis: Using Twitter data to Explore the Effect of the Tōhoku Earthquake.===

Christa Brelsford and Xin Lu

Abstract:
We use twitter data from 7 days before and after the Tōhoku Earthquake to explore how cooperation rates, social network structure and connectivity, and social network vulnerability changed in Japan in response to the disaster. An English language data set is collected for the same time period to use as a control. Data is collected for a period of 96 hours starting from March 4th 2011 2:46pm JST and for 96 hours beginning March 11th 2011 2:46 pm JST. The rate of cooperative behavior, measured by the occurrence of helping words in tweets increases slightly in the English dataset and by an order of magnitude in the Japanese dataset. A network analysis is also performed. Network edges are retweets and direct messages. In future work, we hope to explore whether problem solving capacity in a social system changes in response to crises, based on changes in the rate of cooperation and information transfer in a network.

=== The CSSS Network ===

Tom & Riccardo (with JP and others)

We will investigate the questions you are dying to know: What interesting interactions are revealed from the first 3 weeks of the Complex System Summer School survey? Have barriers between academic disciplines been broken down? Do power laws fit the data!? ...

Let us know if you have specific questions or if you would like to be involved in data analysis!

=== Is there a method in the madness? the dynamic structures of human language use ===

Priya and Riccardo

Psychiatric anecdotal reports point to the monotony, lack of emotion and sometimes intelligibility in many clinical populations. Linear measures of fluency and prosody, however, present only controversial differences between patients and healthy controls and only in unnatural phonations (i.e. say "aaaaa" for 30 secs).
We therefore go complex and chaotic on a set of more ecological recordings and transcriptions from 4 clinical populations (Asperger's, Schizophrenics, Depressed and Right Hemisphere Damage patients) as well as from healthy controls.
We then set a classifier-driven race: will non-linear analyses outcompete linear analyses in discriminating between pathologies?

=== Escaping the Poverty Trap: Modeling the Interplay Between Economic Growth and the Ecology of Infectious Disease ===

Georg, Ben, Laurent, Oscar

The dynamics of economies and infectious disease are inexorably linked: economic well-being influences health (sanitation, nutrition, etc) and health influences economic well-being (labor productivity lost to sickness and disease). Often societies are locked into "poverty traps" of poor health and poor economy. Here, we demonstrate poverty traps formed in models of infection and endogenous growth, as well as ways to break out of poverty traps. We explore two mechanisms of escape: one, through an influx of capital, and another through changing the percentage of GDP spent on healthcare. We find large influxes of capital is successful, but increasing health spending does not. Our results have important policy implications in the distribution of aid and within-country healthcare spending.

=== The Targeting and Timing of Treatment Influences the Emergence of Influenza Resistance in Structured Populations ===

Ben, Laurent, Oscar, Georg

Evolution of antiviral resistance in influenza carries large societal impacts through morbidity and mortality caused by treatment failure. Several previous studies put forth theory regarding the optimal timing, targeting and absolute level of treatment in populations. Few of these studies, however, have considered populations with explicit structure. Here we present a model of antiviral resistance on networks and explore the timing, targeting and levels of treatment. Interestingly, we find bistability as a result of treatment leading to the existence of an unstable manifold, above which successful treatment (i.e.: no resistance) is impossible. We find, contrary to previous results, that degree-targeted treatment is not optimal, and leads to higher levels of resistance than random treatment. Additionally, in accordance with previous results, we find an optimum level of treatment which is less than 100%. These findings findings have important consequences in guiding policy behind influenza treatment. The bistability indicates that caution should be taken when treating populations when the absolute numbers of infections are unknown. Positively, our results indicate that putting resources into targeted treatment is not necessary, random treatment is preferable.

=== Learning in Random Boolean Networks ===

Nick A., Keegan, Matteo, Vikram, Sarah, Mark

Inspired by biochemical networks which adapt on evolutionary timescales, neural networks that adapt during development and learning, and universal computation in cellular automata, we have implemented several models of learning in Random Boolean Networks (RBNs) in order to better understand the relationships between network structure, node interaction rules, and network output.

=== Enzyme Catalysis and the Outcome of Chemical Reactions ===
Piotr and Georg W.
Enzymes are catalysts that accelerate chemical reactions but do not affect their outcome. This traditional paradism was developed under artificail test tube conditions. Our project investigates the possibility that the presence of an enzyme can alter the course of a reaction if it takes place under more physiologic conditions.

=== How Does a Stochastic Environment affect Community Assembly? ===

Xue, Χλοε, Xiaoli

We are interested in how exogenous temporal variability in resource availability affects the community structure of organisms with different resource-use strategies. Organisms induce additional resource stress on each other through competition. This is an abstraction of an arid environment with unreliable rainfall; the organisms themselves have been abstracted to four unitless parameters that allocate their resources to different parts of their lifecycles. The system has memory, as the previous presence of an organism affects the resource transport mechanism (an abstraction of soil).

=== How Does a Network’s Structure Influence its Traceability? ===

Xin and Abby

We are interested in systematically studying the problem of finding the source of a contamination spread through a network. We model a contamination spreading through the food distribution network, which we represent by interconnections between farmers, distributors, and retailers, and construct an estimator for the outbreak source given only this structure. We show how the ability of the estimator to narrow down the source identification problem changes with the connectivity and the number of observations. We propose a measure for traceability, or the overall ability to identify the source of spreading given any set of outbreak observations, based on entropy. We show how this measure appropriately reflects the range of uncertainty in identifying the source. We believe this measure may be useful in the design of networks that are conducive to accurate identification of the source of contamination.

=== We Got the Skills to Pay the Bills: Exploring the Link Between Occupation Diversity and Innovation===

Andrés, Charlie, Gareth, and Nick

Where does diversity in skills or occupations come from and why does it lead to more innovative cities? Previous work in this area has shown that there is a scaling behaviour which allows citizens of larger cities to earn an extra 15% in income whilst making use of 15% fewer gas stations, for example. Making use of occupation, patent, and population data of US Metropolitan Statistical Areas (MSA), we try to understand what factors make successful cities. Here we assume that successful cities are those cities which are most innovative as determined by the production of patents. In addition we use agent-based modelling to explore how and why people acquire new skills and whether this leads to more productive cities.

== Space of complex networks and robustness ==
Ian, Marco, Xin, and Oleksandr

Complex networks have various properties which can be measured in real networks (WWW, social networks, biological networks), e.g. degree distribution, modularity, hierarchy, assortativity etc. Robustness of complex networks is a big question, however only some progress have been done in this direction. For example, it was shown that the scale-free networks are much more topologically robust to random attacks than random networks. Various characteristics of complex networks might influence the robustness differently. The question is how?

We generated continuous topological space of networks with respect to degree distribution (from random to scale-free) and clustering (from none to high). Then we attacked the network by removing vertices randomly and highly connected (hubs). The next step is to calculate network robustness, it is non-trivial task because there are many different ways to do it. So far we calculate the size of giant component during attack process for the entire space.

=== Trade network formation: the role of technology and geography ===

Marco and Matteo

Geography and technology play important roles in economic activities, e.g. international trade flows diminish dramatically with distance; salaries, prices, and factor endowments vary across locations; and productivities are really different across countries' industries. International trade theories have gained some non-negligible reputation explaining the sizes of aggregated trade flows, nonetheless few attention has being payed to the formation of the bilateral trade relations. We develop a network formation model that incorporates differences in technological capabilities across countries and the effect of the geographical distance as a proxy of trade barriers.

Complex Systems Summer School 2012-Project Presentations

2012-06-27T06:47:34Z

Duenas:

{{Complex Systems Summer School 2012}}

Use this space to post project presentations and outlines. Include group members, a brief outline, and your slides.

=== Price-time Dynamics of Contracts Traded on Prediction Markets ===

Joanne, Vikram, Matteo, Sanith

Prediction markets have been shown to outperform traditional methods of polls and opinion surveys in forecasting future events. The futures contracts traded in these markets assess the expectation of occurrence of a variety of events spread across multiple domains (political, economic, entertainment, financial and weather). We explore the feasibility of 'predicting' the outcome of binary true/false prediction market contracts ahead of their expiry date using a neural-network based machine learning approach. In addition we focus on the characteristics of political-based contracts to establish whether they exhibit characteristic 'fundamental' properties.

=== How Complex Languages Replicate through Simple Brains ===

Katrien, Vanessa, Sandro, Cameron, Jasmeen

Through the use of an iterated learning experiment, we investigated the transmission of a "high entropy", randomised initial language through successive generations of participants. We want to see what features of the language replicated most easily, and what structure emerged by the end of the chain. Our hypothesis is that the language converges to a "low entropy" equilibrium state with a minimal number of words, morphemes, and form-meaning distinctions.

=== Collaboration in times of stress: an Agent Based Modelling approach ===

Fabio Cresto Aleina, Elena del Val, Tom Fennewald and Friederike Greb

We want to investigate the influence of exogenous stress on cooperative behaviour. We propose an agent based model in which the agents can be interpreted as farmers living in a water limited environment. With changes in precipitation patterns, the farmers undergo stress, and we observe how this impacts relationships among farmers and their properties.

=== Simple variation of the logistic map as a model to invoke questions on cellular protein trafficking ===
(Sepehr Ehsani, http://arxiv.org/abs/1206.5557)

Many open problems in biology, as in the physical sciences, display nonlinear and 'chaotic' dynamics, which, to the extent possible, cannot be reasonably understood. Moreover, mathematical models which aim to predict/estimate unknown aspects of a biological system cannot provide more information about the set of biologically meaningful (e.g., 'hidden') states of the system than could be understood by the designer of the model ab initio. Here, the case is made for the utilization of such models to shift from a 'predictive' to a 'questioning' nature, and a simple natural-logarithm variation of the logistic polynomial map is presented that can invoke questions about protein trafficking in eukaryotic cells.

===Changes in Social Network Structure in Response to Crisis: Using Twitter data to Explore the Effect of the Tōhoku Earthquake.===

Christa Brelsford and Xin Lu

Abstract:
We use twitter data from 7 days before and after the Tōhoku Earthquake to explore how cooperation rates, social network structure and connectivity, and social network vulnerability changed in Japan in response to the disaster. An English language data set is collected for the same time period to use as a control. Data is collected for a period of 96 hours starting from March 4th 2011 2:46pm JST and for 96 hours beginning March 11th 2011 2:46 pm JST. The rate of cooperative behavior, measured by the occurrence of helping words in tweets increases slightly in the English dataset and by an order of magnitude in the Japanese dataset. A network analysis is also performed. Network edges are retweets and direct messages. In future work, we hope to explore whether problem solving capacity in a social system changes in response to crises, based on changes in the rate of cooperation and information transfer in a network.

=== The CSSS Network ===

Tom & Riccardo (with JP and others)

We will investigate the questions you are dying to know: What interesting interactions are revealed from the first 3 weeks of the Complex System Summer School survey? Have barriers between academic disciplines been broken down? Do power laws fit the data!? ...

Let us know if you have specific questions or if you would like to be involved in data analysis!

=== Is there a method in the madness? the dynamic structures of human language use ===

Priya and Riccardo

Psychiatric anecdotal reports point to the monotony, lack of emotion and sometimes intelligibility in many clinical populations. Linear measures of fluency and prosody, however, present only controversial differences between patients and healthy controls and only in unnatural phonations (i.e. say "aaaaa" for 30 secs).
We therefore go complex and chaotic on a set of more ecological recordings and transcriptions from 4 clinical populations (Asperger's, Schizophrenics, Depressed and Right Hemisphere Damage patients) as well as from healthy controls.
We then set a classifier-driven race: will non-linear analyses outcompete linear analyses in discriminating between pathologies?

=== Escaping the Poverty Trap: Modeling the Interplay Between Economic Growth and the Ecology of Infectious Disease ===

Georg, Ben, Laurent, Oscar

The dynamics of economies and infectious disease are inexorably linked: economic well-being influences health (sanitation, nutrition, etc) and health influences economic well-being (labor productivity lost to sickness and disease). Often societies are locked into "poverty traps" of poor health and poor economy. Here, we demonstrate poverty traps formed in models of infection and endogenous growth, as well as ways to break out of poverty traps. We explore two mechanisms of escape: one, through an influx of capital, and another through changing the percentage of GDP spent on healthcare. We find large influxes of capital is successful, but increasing health spending does not. Our results have important policy implications in the distribution of aid and within-country healthcare spending.

=== The Targeting and Timing of Treatment Influences the Emergence of Influenza Resistance in Structured Populations ===

Ben, Laurent, Oscar, Georg

Evolution of antiviral resistance in influenza carries large societal impacts through morbidity and mortality caused by treatment failure. Several previous studies put forth theory regarding the optimal timing, targeting and absolute level of treatment in populations. Few of these studies, however, have considered populations with explicit structure. Here we present a model of antiviral resistance on networks and explore the timing, targeting and levels of treatment. Interestingly, we find bistability as a result of treatment leading to the existence of an unstable manifold, above which successful treatment (i.e.: no resistance) is impossible. We find, contrary to previous results, that degree-targeted treatment is not optimal, and leads to higher levels of resistance than random treatment. Additionally, in accordance with previous results, we find an optimum level of treatment which is less than 100%. These findings findings have important consequences in guiding policy behind influenza treatment. The bistability indicates that caution should be taken when treating populations when the absolute numbers of infections are unknown. Positively, our results indicate that putting resources into targeted treatment is not necessary, random treatment is preferable.

=== Learning in Random Boolean Networks ===

Nick A., Keegan, Matteo, Vikram, Sarah, Mark

Inspired by biochemical networks which adapt on evolutionary timescales, neural networks that adapt during development and learning, and universal computation in cellular automata, we have implemented several models of learning in Random Boolean Networks (RBNs) in order to better understand the relationships between network structure, node interaction rules, and network output.

=== Enzyme Catalysis and the Outcome of Chemical Reactions ===
Piotr and Georg W.
Enzymes are catalysts that accelerate chemical reactions but do not affect their outcome. This traditional paradism was developed under artificail test tube conditions. Our project investigates the possibility that the presence of an enzyme can alter the course of a reaction if it takes place under more physiologic conditions.

=== How Does a Stochastic Environment affect Community Assembly? ===

Xue, Χλοε, Xiaoli

We are interested in how exogenous temporal variability in resource availability affects the community structure of organisms with different resource-use strategies. Organisms induce additional resource stress on each other through competition. This is an abstraction of an arid environment with unreliable rainfall; the organisms themselves have been abstracted to four unitless parameters that allocate their resources to different parts of their lifecycles. The system has memory, as the previous presence of an organism affects the resource transport mechanism (an abstraction of soil).

=== How Does a Network’s Structure Influence its Traceability? ===

Xin and Abby

We are interested in systematically studying the problem of finding the source of a contamination spread through a network. We model a contamination spreading through the food distribution network, which we represent by interconnections between farmers, distributors, and retailers, and construct an estimator for the outbreak source given only this structure. We show how the ability of the estimator to narrow down the source identification problem changes with the connectivity and the number of observations. We propose a measure for traceability, or the overall ability to identify the source of spreading given any set of outbreak observations, based on entropy. We show how this measure appropriately reflects the range of uncertainty in identifying the source. We believe this measure may be useful in the design of networks that are conducive to accurate identification of the source of contamination.

=== We Got the Skills to Pay the Bills: Exploring the Link Between Occupation Diversity and Innovation===

Andrés, Charlie, Gareth, and Nick

Where does diversity in skills or occupations come from and why does it lead to more innovative cities? Previous work in this area has shown that there is a scaling behaviour which allows citizens of larger cities to earn an extra 15% in income whilst making use of 15% fewer gas stations, for example. Making use of occupation, patent, and population data of US Metropolitan Statistical Areas (MSA), we try to understand what factors make successful cities. Here we assume that successful cities are those cities which are most innovative as determined by the production of patents. In addition we use agent-based modelling to explore how and why people acquire new skills and whether this leads to more productive cities.

== Space of complex networks and robustness ==
Ian, Marco, Xin, and Oleksandr

Complex networks have various properties which can be measured in real networks (WWW, social networks, biological networks), e.g. degree distribution, modularity, hierarchy, assortativity etc. Robustness of complex networks is a big question, however only some progress have been done in this direction. For example, it was shown that the scale-free networks are much more topologically robust to random attacks than random networks. Various characteristics of complex networks might influence the robustness differently. The question is how?

We generated continuous topological space of networks with respect to degree distribution (from random to scale-free) and clustering (from none to high). Then we attacked the network by removing vertices randomly and highly connected (hubs). The next step is to calculate network robustness, it is non-trivial task because there are many different ways to do it. So far we calculate the size of giant component during attack process for the entire space.

=== Trade network formation: the role of technology and geography ===
Marco and Matteo

Geography and technology play important roles in economic activities, e.g. international trade flows diminish dramatically with distance; salaries, prices, and factor endowments vary across locations; and productivities are really different across countries' industries. International trade theories have gained some non-negligible reputation explaining the sizes of aggregated trade flows, nonetheless few attention has being payed to the formation of the bilateral trade relations. We develop a network formation model that incorporates differences in technological capabilities across countries and the effect of the geographical distance as a proxy of trade barriers.

Complex Systems Summer School 2012-After Hours

2012-06-21T16:02:18Z

Duenas: /* Rodeo de Santa Fe */

{{Complex Systems Summer School 2012}}

Use this space to organize your own after hours activities.

==Rodeo de Santa Fe==

We are planning to head to the [http://rodeodesantafe.org/ Rodeo] today (June 21) at 6:00p.m. please meet drivers in the parking circle and post your car if you can drive:

Car 1: Juniper's Car 

1. Katrien

2. Nick A.

3. Xue

4. Mikkel

Car 1: JP's Car 

1. Matteo

2. Ben

3. Laurent

4. Marco

==Trip to Taos and alpaca farm==
I am planning to rent a car to visit Taos and a alpaca farm this saturday June 23.
The alpaca farm in my plan is Victory Ranch. http://victoryranch.com/
The car should be able to carry 5 people and let's share the cost.
1. Jianfeng Xu
2. Xin lu
3. Si Tang
4. Xiaoli Dong

==Trip to a museum==
On weekend (Saturday?) I'm planning to visit the Georgia O'Keeffe Museum; after that I'm going to see some more of Santa Fe (no plan yet -- waiting for proposals). Anyone interested?
Cheers,
Piotr

==Road Trip to Boulder, Colorado==

From Gareth: Hi all, I'm planning on making a trip up to Boulder, CO for the weekend. It's about a 6 1/2 hr drive from Santa Fe and I'll be renting a car. My main reason for the trip is to see a friend of mine so you might have to sort your own accommodation (camping/youth hostel/hotel). We're planning on a bit of hiking nearby. The plan is to leave straight from class on Friday evening and arrive back in Santa Fe on Sunday eve. If you're interested in splitting petrol and rental fee and joining me for some Springsteen singalongs then sign up:

1.

2.

3.

4.

==Some Banjo fun out on the town==

My brother will be having a concert this Saturday June 16 at the Second Street Brewery (original location) from 6-9p.m. I will be at the parking circle at 6p.m. For those who do not sign up for a car don't forget Friday and Saturday $5 cabs.

[http://www.secondstreetbrewery.com/2012/05/todd-the-fox-9/ Todd and the Fox Venue Details]

[http://www.toddandthefox.com/fr_home.cfm To hear their music]

If anyone would like to join:

Car 1: Juniper's Car 

1. Katrien (not sure if we'll be back from the lake trip by 6pm. Somebody can take my place if they want.) back up: Georg Weber

2. Marque

3. Sarah

4. Marco

==Dancing==

Swing dancing on Monday 18th June.
Lessons from 7 to 8 P.M.
Dancing from 8 on wards.
The cost is $8 including the lesson and dancing (or $3 for the dancing). Venue: Odd Fellows Hall, 1125 Cerrillos Road. We have not yet decided on transportation. We could either take a cab or walk -- Let's try to decide during dinner.
Sign up below if you are interested:

1.Vikram -- Slightly biased towards taking the lesson. 
2. Xue -- dancing, though not a strong preference. 
3. Mark - I could use a lesson, or twelve. Do we have transportation? 
4. Chloe -- would rather walk down with everyone than skip the lesson. 
5. Aleksandra -- would try lesson, may be stay for dancing. 

PS: If you are on the edge because you want to attend the session on "Introduction to Python". I would be happy to walk you through the basics of Python at a later time. -- Vikram

PPS: how about a Dancing Python lunch tomorrow? I can do intro tutoring too. --Chloe

Other varieties --

There's a contra on the 23rd; swing dancing most Mondays; this is supposed to be a great tango town, and the drop-in-friendly beginner class on Thursday PM was good ($20, though).

[http://www.santafenewmexican.com/Sidebar/Dance_fever_in_Santa_Fe swing, salsa, tango]

[http://www.folkmads.org/may_jun_calendar12.html contras, here and ABQ]

We've heard great Appalachian-style folk musicians here already, but I haven't found a ceili or hoedown locally.

--Chloe

==Trip to Taos==

JP and Tom are going to go to Taos on Saturday 6/16. Sights to see will include the High Road to Taos, Taos Pueblo, the Taos Gorge, Taos Earthships, and the plenty of Taos Hippies.
 
Car 1: JP's Camry 

1.[[JP]] 
2. 
3.Piotr 
4.Matteo 
5.Vikram 
 

Car 2: Tom's Car 
1 
2 Miguel 
3 Riccardo 
4 Priya 

From Andres: I'm sorry... I decided to stay tomorrow at St. John's. I'm very sorry to letting you know so late...! I want to rest, and there is some work I'd like to do...
From Nick: Same for me guys. I feel exhausted. Sorry for telling you so late. Enjoy!

==Trip to Abiquiu==

We are organizing a trip to lake Abiquiu this weekend. ATTENTION ATTENTION! Drivers (Christa, Fabio, John, Tom and David) will meet at 8:30 tomorrow morning (Saturday), and will go with Christa to town to rent 4 cars. We'll pick the others up at 9:30. Those in Christas car, meet at 9am. See you tomorrow!

Fabio

Friederike

Elena

Mikkel

John

Nona

Abby

Marco

Aleksandra

Jasmeen

Dan

Sandro

Ian (if there is any room)

Vanessa (ditto)

Christa (my car seats 5 including me, but I want to stop by Los Alamos to pick up my dog on the way. That adds ~30 min to the drive. "Christa's Honda has manual transmission. do we need a second driver on the car who can drive a stick shift car?" "Yes"- Christa

1. Christa

2. Xue (though I'm also willing to be a driver if necessary)

3. Katrien

4. Jianfeng Xu

5. Xin

Tom

Nick A

==Bandelier Field Trip==

Bandelier Field Trip
Trip to Bandelier National Monument on Sat. June 9.
We might string a visit to the Valles Caldera and Bradbury Science Museum/Los Alamos in as well. If another group would like to stay around Bandelier, we can split up.

Head over to the [[Bandelier Trip 2012 | Bandelier Trip]] Page to sign up!

==Mafia==

[[JP]] is a huge fan of Mafia/Werewolf. Let's play a game sometime in the lower commons.

Let's meet Saturday evening at 8:00 in the lower commons for our first game.

- [[Ryan_James|Ryan]] is down for this.

- Jasmeen is also a big fan of Mafia.

- Ian has never played, but is interested

- Vikram is interested in learning the game.

- Tom F. would like to join and can also teach "The Resistance" a very similar game

- Katrien wants to play too

==FOOTBALL!==

Anyone up for a friendly game of soccer? We can check out equipment from the gym.

[Team: Continuous!] 
1. [[Piotr Milanowski|Piotr]] 
2. [[Marco Duenas|Marco]] 
3.[[Oleksandr Ivanov|Alex]] 
4. 
5. 
[Team: Discrete!] 
1. [[Fabio Cresto Aleina|Fabio]] 
2. [[Matteo Chinazzi|Matteo]] 
3.[[JP]] 
4. 
5.

Experiment sign-up

2012-06-19T20:40:16Z

Duenas: /* Tuesday June 19 */

Hi! Please sign up for one slot below. The experiment will be held in the SENIOR Common Room (again) next to the great hall (YES, JP's office). Please arrive on time! Ta.

- Katrien, Vanessa, Sandro, Cameron & Jasmeen

==Monday June 18==

Morning Break:

10.20-10.30: Piotr X

10.30-10.40: Laurent X

Lunch Break:

12.05-12.15: Chloe X

'''12.15-12.25: Andres ???'''

12.25-12.35: Xue X

12.35-12.45: Oleksandr X

12.55-1.05: Nick A X

1.05-1.15: Fabio X

1.15-1.25: Priya X

Afternoon:

5.00-5.10: Matteo X

5.10-5.20: Abby X

5.20-5.30: Elena X

5.30-5.40: Riccardo X

5.40-5.50: [[JP]]! X

6.00-6.10: [[Xin]] X

6.10-6.20: Ian X

6.20-6.30: Keegan

6.30-6.40: Aleksandra

6.40-6.50: Tom X

6.50-7.00:Christa X

==Tuesday June 19==

Morning Break:

10.20-10.30: Vikram X

Afternoon:

4.30-4.40: dan

4.40-4.50: Georg W. / Ben

4.50-5.00: Sander Bais / Sepehr

5.00-5.10: Aleksandra

5.10-5.20: Marque

5.20-5.30: Sarah

5.30-5.40: Oscar

5.40-5.50: Marco

5.50-6.00:

6.00-6.10:

6.10-6.20:

6.20-6.30:

6.30-6.40:

6.40-6.50:

6.50-7.00:

Complex Systems Summer School 2012-After Hours

2012-06-14T21:47:21Z

Duenas: /* Trip to Abiquiu */

{{Complex Systems Summer School 2012}}

Use this space to organize your own after hours activities.

==Some Banjo fun out on the town==

My brother will be having a concert this Saturday June 16 at the Second Street Brewery (original location) from 6-9p.m.

[http://www.secondstreetbrewery.com/2012/05/todd-the-fox-9/ Todd and the Fox Venue Details]

[http://www.toddandthefox.com/fr_home.cfm To hear their music]

If anyone would like to join:

Car 1: Juniper's Car 

1. Katrien

2. Marque

3. Sarah

4. Marco

==Dancing==
Of particular varieties --

There's a contra on the 23rd; swing dancing most Mondays; this is supposed to be a great tango town, and I'm looking for drop-in-friendly beginner classes...

[http://www.santafenewmexican.com/Sidebar/Dance_fever_in_Santa_Fe swing, salsa, tango]

[http://www.folkmads.org/may_jun_calendar12.html contras, here and ABQ]

We've heard great Appalachian-style folk musicians here already, but I haven't found a ceili or hoedown locally.

--Chloe

==Trip to Taos==

JP and Tom are going to go to Taos on Saturday 6/16. Sights to see will include the High Road to Taos, Taos Pueblo, the Taos Gorge, Taos Earthships, and the plenty of Taos Hippies.
 
Car 1: JP's Camry 

1.[[JP]] 
2.Nick G 
3.Piotr 
4.Matteo 
5. 
 

Car 2: Tom's Car 
1 Andres G. 
2 Miguel 
3 Riccardo 
4 Priya 

==Trip to Abiquiu==

We are organizing a trip to lake Abiquiu this weekend. Google maps says it should take about 1:10 hour driving from Santa Fe. Who's interested? We'll have to rent cars to go there.

Fabio

Friederike

Elena

Mikkel

John

Nona

Abby

Marco

Christa (my car seats 5 including me, but I want to stop by Los Alamos to pick up my dog on the way. That adds ~30 min to the drive. "Christa's Honda has manual transmission. do we need a second driver on the car who can drive a stick shift car?"

1. Christa

2. Xue (though I'm also willing to be a driver if necessary)

3. Katrien

4. Jianfeng Xu

5.

==Bandelier Field Trip==

Bandelier Field Trip
Trip to Bandelier National Monument on Sat. June 9.
We might string a visit to the Valles Caldera and Bradbury Science Museum/Los Alamos in as well. If another group would like to stay around Bandelier, we can split up.

Head over to the [[Bandelier Trip 2012 | Bandelier Trip]] Page to sign up!

==Mafia==

[[JP]] is a huge fan of Mafia/Werewolf. Let's play a game sometime in the lower commons.

Let's meet Saturday evening at 8:00 in the lower commons for our first game.

- [[Ryan_James|Ryan]] is down for this.

- Jasmeen is also a big fan of Mafia.

- Ian has never played, but is interested

- Vikram is interested in learning the game.

- Tom F. would like to join and can also teach "The Resistance" a very similar game

- Katrien wants to play too

==FOOTBALL!==

Anyone up for a friendly game of soccer? We can check out equipment from the gym.

[Team: Continuous!] 
1. [[Piotr Milanowski|Piotr]] 
2. [[Marco Duenas|Marco]] 
3.[[Oleksandr Ivanov|Alex]] 
4. 
5. 
[Team: Discrete!] 
1. [[Fabio Cresto Aleina|Fabio]] 
2. [[Matteo Chinazzi|Matteo]] 
3.[[JP]] 
4. 
5.

Complex Systems Summer School 2012-After Hours

2012-06-14T21:44:48Z

Duenas: /* Some Banjo fun out on the town */

{{Complex Systems Summer School 2012}}

Use this space to organize your own after hours activities.

==Some Banjo fun out on the town==

My brother will be having a concert this Saturday June 16 at the Second Street Brewery (original location) from 6-9p.m.

[http://www.secondstreetbrewery.com/2012/05/todd-the-fox-9/ Todd and the Fox Venue Details]

[http://www.toddandthefox.com/fr_home.cfm To hear their music]

If anyone would like to join:

Car 1: Juniper's Car 

1. Katrien

2. Marque

3. Sarah

4. Marco

==Dancing==
Of particular varieties --

There's a contra on the 23rd; swing dancing most Mondays; this is supposed to be a great tango town, and I'm looking for drop-in-friendly beginner classes...

[http://www.santafenewmexican.com/Sidebar/Dance_fever_in_Santa_Fe swing, salsa, tango]

[http://www.folkmads.org/may_jun_calendar12.html contras, here and ABQ]

We've heard great Appalachian-style folk musicians here already, but I haven't found a ceili or hoedown locally.

--Chloe

==Trip to Taos==

JP and Tom are going to go to Taos on Saturday 6/16. Sights to see will include the High Road to Taos, Taos Pueblo, the Taos Gorge, Taos Earthships, and the plenty of Taos Hippies.
 
Car 1: JP's Camry 

1.[[JP]] 
2.Nick G 
3.Piotr 
4.Matteo 
5. 
 

Car 2: Tom's Car 
1 Andres G. 
2 Miguel 
3 Riccardo 
4 Priya 

==Trip to Abiquiu==

We are organizing a trip to lake Abiquiu this weekend. Google maps says it should take about 1:10 hour driving from Santa Fe. Who's interested? We'll have to rent cars to go there.

Fabio

Friederike

Elena

Mikkel

John

Nona

Abby

Christa (my car seats 5 including me, but I want to stop by Los Alamos to pick up my dog on the way. That adds ~30 min to the drive. "Christa's Honda has manual transmission. do we need a second driver on the car who can drive a stick shift car?"

1. Christa

2. Xue (though I'm also willing to be a driver if necessary)

3. Katrien

4. Jianfeng Xu

5.

==Bandelier Field Trip==

Bandelier Field Trip
Trip to Bandelier National Monument on Sat. June 9.
We might string a visit to the Valles Caldera and Bradbury Science Museum/Los Alamos in as well. If another group would like to stay around Bandelier, we can split up.

Head over to the [[Bandelier Trip 2012 | Bandelier Trip]] Page to sign up!

==Mafia==

[[JP]] is a huge fan of Mafia/Werewolf. Let's play a game sometime in the lower commons.

Let's meet Saturday evening at 8:00 in the lower commons for our first game.

- [[Ryan_James|Ryan]] is down for this.

- Jasmeen is also a big fan of Mafia.

- Ian has never played, but is interested

- Vikram is interested in learning the game.

- Tom F. would like to join and can also teach "The Resistance" a very similar game

- Katrien wants to play too

==FOOTBALL!==

Anyone up for a friendly game of soccer? We can check out equipment from the gym.

[Team: Continuous!] 
1. [[Piotr Milanowski|Piotr]] 
2. [[Marco Duenas|Marco]] 
3.[[Oleksandr Ivanov|Alex]] 
4. 
5. 
[Team: Discrete!] 
1. [[Fabio Cresto Aleina|Fabio]] 
2. [[Matteo Chinazzi|Matteo]] 
3.[[JP]] 
4. 
5.

Complex Systems Summer School 2012-Tutorials

2012-06-13T23:25:22Z

Duenas: /* Python */

{{Complex Systems Summer School 2012}}

CSSS participants come from a wide range of disciplines. Participants are encouraged to share their knowledge by organizing their own tutorials.

Also, please post requests for tutorials here.

==Python, Computational Mechanics, and Information Theory==

There has been interest in more discussion on a number of topics, and so i'm offering to have evening discussions on them. please sign up below so that i can get a feel for the number of people who would be attending. also, please put a preference for what day it should be.

===Python===
Sign up below if you'd like an introduction to basic python programming. Python is a general purpose, very flexible and useful programming language. It is used pretty extensively in scientific computing.

dan wu: wu12345@gmail.com Let me know when we're meeting

- Benji: bzusman@gmail.com 

-Keegan

-Christa (maybe- I'm competent at the very basics, but could still use some help)

-Riccardo

- Oleksandr: krystoferivanov@gmail.com

- Nona: nona.karalashvili@gmail.com

- Xiaoli: xiaolidong2008@gmail.com

- Abby: Abbyhorn@Mit.edu

- Marco: maduenase@gmail.com

===Information Theory===
Interested in turning your data into bits, or seeing how the bits over there are related to the bits over here? If so, sign up below. 
- Matteo

- Benji: bzusman@gmail.com

-Keegan

-Riccardo

-Christa

- Katrien

- Xiaoli

- Abby

- Jasmeen

===Computational Mechanics===
If you'd like to know more about epsilon machines, measures of complexity, how to go from a map to a machine, i'm happy to discuss it all. 
- Matteo

Yes please! --Chloe

-Keegan

-Christa

-Xiaoli

-Jasmeen

==Order Book Dynamics: Learn how to trade in 15min==

--I'm happy to repeat this -just get in touch with me.--

If you are curious about how stocks trade and want to try your luck, I'll
be going over some of the basics with a hands-on example.

Meet at 7.30pm in main lecture hall Thursday June 7th. Please make sure
to bring your laptop.

Sanith

==An easier way to get a bifurcation plot==

Hey guys
I have been working in the past in obtaining bifurcation plots for different physical systems. There's a better way to get these pictures instead of getting the evolution at every parameter value of interest. This is called ''numerical continuation'' and basically involves tracking a curve. I plan to give a informal talk on how to do this and maybe even a demo on applying this technique on 14th June at 6.30 pm. Do mail me if you are interested at '''iitm.priya@gmail.com''' or sign up below.
[[User:Priya|Priya]]

- [[Ryan James|Ryan]] is interested in this. 
- Riccardo is interested in this. 
- Vikram is interested in this. 
- Matteo is interested in this. 
- Hide is interested in this. 
- Katrien wants to hear more about this. 
- Cameron is interested in this and would like to see [http://itunes.apple.com/us/app/xpp/id433859546?mt=8 this] in action if anyone has an iPad. 
- Oscar is interested in this. 
- Charlie is interested in this. (I've done this once for a paper.) 

==Using Tisean on R on OS X==
first install TISEAN, like you've done already. Make sure R is up to date (v 2.15).
you can try to install RTisean from CRAN
install.packages("RTisean"); library(RTisean); henon()
But me and Dave both got an error about some bad file name, something about con and something about a long path involving -Tmp-
Solution:
remove.packages("RTisean")
restart R
download this: http://cl.ly/0I0b2P2L311y1q0q0y0n
install it, it changes line 74 of nativeTISEAN.R which has some problems with file handling
If you are golden, then:
> henon()
V1 V2
[1,] -0.1232481 -1.030383

Complex Systems Summer School 2012-Tutorials

2012-06-13T23:24:36Z

Duenas: /* Python */

{{Complex Systems Summer School 2012}}

CSSS participants come from a wide range of disciplines. Participants are encouraged to share their knowledge by organizing their own tutorials.

Also, please post requests for tutorials here.

==Python, Computational Mechanics, and Information Theory==

There has been interest in more discussion on a number of topics, and so i'm offering to have evening discussions on them. please sign up below so that i can get a feel for the number of people who would be attending. also, please put a preference for what day it should be.

===Python===
Sign up below if you'd like an introduction to basic python programming. Python is a general purpose, very flexible and useful programming language. It is used pretty extensively in scientific computing.

dan wu: wu12345@gmail.com Let me know when we're meeting

- Benji: bzusman@gmail.com 

-Keegan

-Christa (maybe- I'm competent at the very basics, but could still use some help)

-Riccardo

- Oleksandr: krystoferivanov@gmail.com

- Nona: nona.karalashvili@gmail.com

- Xiaoli: xiaolidong2008@gmail.com

- Abby: Abbyhorn@Mit.edu

- Marco

===Information Theory===
Interested in turning your data into bits, or seeing how the bits over there are related to the bits over here? If so, sign up below. 
- Matteo

- Benji: bzusman@gmail.com

-Keegan

-Riccardo

-Christa

- Katrien

- Xiaoli

- Abby

- Jasmeen

===Computational Mechanics===
If you'd like to know more about epsilon machines, measures of complexity, how to go from a map to a machine, i'm happy to discuss it all. 
- Matteo

Yes please! --Chloe

-Keegan

-Christa

-Xiaoli

-Jasmeen

==Order Book Dynamics: Learn how to trade in 15min==

--I'm happy to repeat this -just get in touch with me.--

If you are curious about how stocks trade and want to try your luck, I'll
be going over some of the basics with a hands-on example.

Meet at 7.30pm in main lecture hall Thursday June 7th. Please make sure
to bring your laptop.

Sanith

==An easier way to get a bifurcation plot==

Hey guys
I have been working in the past in obtaining bifurcation plots for different physical systems. There's a better way to get these pictures instead of getting the evolution at every parameter value of interest. This is called ''numerical continuation'' and basically involves tracking a curve. I plan to give a informal talk on how to do this and maybe even a demo on applying this technique on 14th June at 6.30 pm. Do mail me if you are interested at '''iitm.priya@gmail.com''' or sign up below.
[[User:Priya|Priya]]

- [[Ryan James|Ryan]] is interested in this. 
- Riccardo is interested in this. 
- Vikram is interested in this. 
- Matteo is interested in this. 
- Hide is interested in this. 
- Katrien wants to hear more about this. 
- Cameron is interested in this and would like to see [http://itunes.apple.com/us/app/xpp/id433859546?mt=8 this] in action if anyone has an iPad. 
- Oscar is interested in this. 
- Charlie is interested in this. (I've done this once for a paper.) 

==Using Tisean on R on OS X==
first install TISEAN, like you've done already. Make sure R is up to date (v 2.15).
you can try to install RTisean from CRAN
install.packages("RTisean"); library(RTisean); henon()
But me and Dave both got an error about some bad file name, something about con and something about a long path involving -Tmp-
Solution:
remove.packages("RTisean")
restart R
download this: http://cl.ly/0I0b2P2L311y1q0q0y0n
install it, it changes line 74 of nativeTISEAN.R which has some problems with file handling
If you are golden, then:
> henon()
V1 V2
[1,] -0.1232481 -1.030383

Robustness of complex networks (project)

2012-06-11T04:16:10Z

Duenas: /* Participants */

[[File:Zoo.png|thumb|300px|Fig. 1. Zoo of complex networks (an example). Taken from Sol´e and Valverde, 2001.]]
== Problem statement ==
Complex networks have various properties which can be measured in real networks (WWW, social networks, biological networks), e.g. degree distribution, modularity, hierarchy, assortativity etc. Robustness of complex networks is a big question, however only some progress have been done in this direction. For example, it was shown that the scale-free networks are much more topologically robust to random attacks than random networks. Many people claim that various characteristics of complex networks will influence the robustness interdependently. The question I am interested in is how?

== Approach ==
The idea is to generate continuous topology space of various complex networks (networks with different modularity, degree distribution, hierarchy etc) and use it to measure their robustness (see Fig. 1). There are many approaches to measure the robustness of complex networks. For example we can remove edges of vertices of a complex network graph and look at the size of a giant cluster. We can discuss other possibilities.

If you are interested you can contact me directly or via my E-mail: krystoferivanov@gmail.com or via my [[Oleksandr Ivanov|discussion page in CSSS 2012 wiki]].

== Relevant literature ==
* ''Important papers about network generation are highlighted in bold''
* '''[http://www.barabasilab.com/pubs/CCNR-ALB_Publications/199910-15_Science-Emergence/199910-15_Science-Emergence.pdf BA Scale-free network]'''
* '''[http://people.maths.ox.ac.uk/maini/PKM%20publications/195.pdf How to generate Scale-free modular network using preferential attachment]'''
* '''[http://arxiv.org/pdf/cond-mat/0402009v1.pdf Scale-free networks with tunable degree distribution exponents]'''
* '''[http://arxiv.org/pdf/cond-mat/0110452v1.pdf Scale free networks with tunable clustering]'''
* [http://www.barabasilab.com/pubs/CCNR-ALB_Publications/200007-27_Nature-ErrorAttack/200007-27_Nature-ErrorAttack.pdf Error and attack tollerance of complex networks]
* [http://vw.indiana.edu/netsci06/conference/Ng_Structural.pdf Structural Robustness of Complex networks]
* [http://arxiv.org/pdf/cond-mat/0205405.pdf Assortative mixing in networks]
* [http://www.cis.upenn.edu/~mkearns/teaching/NetworkedLife/prefatt.pdf Mean field theory to study scale-free networks]
* [http://www.graphanalysis.org/SIAM-PP08/Leskovic.pdf Kroneker Graphs]
* [http://www.lem.sssup.it/WPLem/files/2011-07.pdf Exact maximum-likelihood method to detect patterns in real networks]
* [http://www-users.york.ac.uk/~lsdc1/SysBiol/kitano.robustness.naturegenetics.2004.pdf Biological robustness]
* [http://arxiv.org/ftp/cond-mat/papers/0202/0202410.pdf Attack vulnerability of complex networks]
* [http://jmvidal.cse.sc.edu/papers/nair11a.pdf Supply Network Topology and Robustness against Disruptions – an investigation using multi agent model]

* [http://arxiv.org/abs/cond-mat/0007235 Random graphs with arbitrary degree distributions and their applications]
* [http://www.pnas.org/content/104/1/36 Resolution limit in community detection] - about a typical modularity measure and its limitations

* Add a relevant paper...

== Learning Python ==
* [http://code.google.com/edu/languages/google-python-class/ Google's Python Class]

== Participants ==
# [[Oleksandr Ivanov]] - krystoferivanov@gmail.com
# [[Ian Wood]] - ibwood@indiana.edu
# [[Xin Lu]] - xin.lu@ki.se
# [[Duenas-Esterling Marco-Antonio]] - maduenase@gmail.com

== BA algorithm in Python ==
''Caution! when you copy this to the Python delete one space from the first line, i.e., before def''
def barabasi_albert_graph(n, m, seed=None):
"""Return random graph using Barabási-Albert preferential attachment model.
A graph of n nodes is grown by attaching new nodes each with m
edges that are preferentially attached to existing nodes with high
degree.

Parameters
----------
n : int
Number of nodes
m : int
Number of edges to attach from a new node to existing nodes
seed : int, optional
Seed for random number generator (default=None). 
Returns
-------
G : Graph

Notes
-----
The initialization is a graph with with m nodes and no edges.
References
----------
.. [1] A. L. Barabási and R. Albert "Emergence of scaling in
random networks", Science 286, pp 509-512, 1999.
"""
if m < 1 or m >=n:
raise nx.NetworkXError(\
"Barabási-Albert network must have m>=1 and m<n, m=%d,n=%d"%(m,n))
if seed is not None:
random.seed(seed) 
# Add m initial nodes (m0 in barabasi-speak)
G=empty_graph(m)
G.name="barabasi_albert_graph(%s,%s)"%(n,m)
# Target nodes for new edges
targets=list(range(m))
# List of existing nodes, with nodes repeated once for each adjacent edge
repeated_nodes=[]
# Start adding the other n-m nodes. The first node is m.
source=m
while source<n:
# Add edges to m nodes from the source.
G.add_edges_from(zip([source]*m,targets))
# Add one node to the list for each new edge just created.
repeated_nodes.extend(targets)
# And the new node "source" has m edges to add to the list.
repeated_nodes.extend([source]*m)
# Now choose m unique nodes from the existing nodes
# Pick uniformly from repeated_nodes (preferential attachement)
targets = _random_subset(repeated_nodes,m)
source += 1
return G

Bandelier Trip 2012

2012-06-06T23:38:17Z

Duenas: /* Christa's Car: 4 (maybe 5) seats */

{{Complex Systems Summer School 2012}}

Please sign up here so we know who's going. 
Also: If you have a car, please let us know. The more cars, the more people. 

We'll meet Saturday at 10:00am in the parking circle.

Please remember to bring a hat, sunscreen, water, hiking shoes, and anything else you'll need for a day out in the field.

==Cars:==

===Tom's Sedan: 4 seats===
1. [[Nicholas Allgaier]] 

2. Vikram Vijayaraghavan 

3. Katrien Beuls 

4. Riccardo Fusaroli 

===John Paul's Camry: 4 (maybe 5) seats===

1. [[John Paul]] 

2. [[Matteo Chinazzi]] 

3. [[Chloe Lewis]] 

4. [[Xue Feng]] 

5. [[Joanne Rodrigues]] 

===Juniper's Car: 4 (maybe 5) seats===

1. Jasmeen Kanwal

2. Sarah Tweedt

3. Mark Longo

4.

5.

===[http://tuvalu.santafe.edu/events/workshops/index.php/Christa_Brelsford Christa]'s Car: 4 (maybe 5) seats===

1. Christa

2. Nicolas Goudemand

3. Marco

4.

5(middle seat in a 2 door civic).

===STILL NEEDS A SEAT!===
1.

2.

3.

Duenas-Esterling Marco-Antonio

2012-06-06T06:46:10Z

Duenas: Created page with 'I'm a 4th year PhD student in Economics at Sant'Anna School of Advanced Studies in Pisa-Italy. My research is related to Trade Networks and Economic Growth. I have a degree in ph…'

I'm a 4th year PhD student in Economics at Sant'Anna School of Advanced Studies in Pisa-Italy. My research is related to Trade Networks and Economic Growth. I have a degree in physics, I worked on quantum gates using cold atoms, that was a fantastic theoretical work. Then something happened and I decided to do a MA in Economics, the thesis was related to spatial prisoners dilemma.

To give you an idea about my PhD thesis I investigate whether the gravity model employed in international trade theory can explain the statistical properties of the International Trade Network. The idea is to estimate with econometrics methods the trade flows among countries, or the weights of the links, and then see if these estimations are equivalent to what it is observed in the real network. It can sound strange a "gravity model in economics", but the idea actually works quite nice, the term "gravity" comes about because the predicted relation between trade flows and explanatory variables is similar to Newton's formula: the magnitude of aggregated trade flows between a pair of countries is proportional to the product of country sizes (e.g. the masses, as proxied by country GDPs) and inversely proportional to their geographic distance (interpreted as proxies of trade-resistance factors, e.g. tariffs).

Look that this notion of gravity in social sciences can be adapted to many systems, e.g. migrations, describe how consumers flow between different shopping malls, patients between hospitals... I would be very happy to help interested people in econometric techniques related with the gravity like model, it is connected to Poisson models in count data analysis and Logistic regressions... So if you have the data we could start now to think a project.

One of the conclusions of my research is that the gravity model in trade successfully replicates some weighted-network structure of the trade network, but only if one fixes its binary architecture equal to the observed one. Conversely, the gravity approach performs very badly when asked to predict the presence of a link, or the level of the trade flow it carries, whenever the binary structure must be simultaneously estimated. Hence, one topic I'm very interested is in network formation.

On the side of economic growth I did an empirical analysis of cross sectional GDP business cycles. Business cycles are obtained after applying filtering techniques to country time series, and the cycle is sometimes used in economic literature as white noise that characterize economic fluctuations and volatility. The probability density functions of those cycles show fat-tails, and the volatilities are characterized by an inverse power law relation with the country size. The conclusion is that heterogeneity in economic systems survives to many frequency levels, in other words independently of the filter you can apply there is something that remains, so is the cycle white noise?

Complex Systems Summer School 2012-After Hours

2012-06-06T04:28:32Z

Duenas: /* FOOTBALL! */

{{Complex Systems Summer School 2012}}

Use this space to organize your own after hours activities.

==Mafia==

[[JP]] is a huge fan of Mafia/Werewolf. Let's play a game sometime in the lower commons.

- [[Ryan_James|Ryan]] is down for this.

==FOOTBALL!==

Anyone up for a friendly game of soccer? We can check out equipment from the gym.

[Team: Continuous] 
1. [[Piotr Milanowski|Piotr]] 
2. [[Marco Duenas|Marco]] 
3. 
4. 
5. 
[Team: Discrete] 
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Alfred Hubler's Nonlinear Dynamics Lab 2012

2012-06-03T20:52:19Z

Duenas: /* Tuesday, June 12, 6:00pm */

{{Complex Systems Summer School 2012}}

==Thursday, June 7, 6:00pm==

1. Sarah Tweedt 
2. Georg F. Weber 
3. Georg M. Goerg 
4. Cameron Smith 
5. Mikkel Vestergaard 
6. Friederike Greb 
7. Fabio Cresto Aleina 
8. 
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15. 

==Friday, June 8 7:00am==
PLEASE NOTE THAT THIS IS AN EARLY MORNING CLASS! 
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==Monday, June 11, 6:00pm==
1. Hidetoshi Inamine 
2. Dan Wu 
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==Tuesday, June 12, 6:00pm==
1. Marco Duenas

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