Computer simulations, mathematics and economics

Economists lise different kinds of computer simulation. However, there is little attention on the theory of simulation, which is considered either a technology or an extension of mathematical theory or, else, a way of modelling that is alternative to verbal description and mathematical models. The paper suggests a systematisation of the relationship between simulations, mathematics and economics. In particular, it traces the evolution of simulation techniques, comments some of the contributions that deal with their nature, and, finally, illustrates with some examples their influence on economie theory. Keywords: Computer simulation, economie methodology, multi-agent programming techniques.

Socionic Multi-Agent Systems Based on Reflexive Petri Nets and Theories of Social Self-Organisation

This contribution summarises the core results of the transdisciplinary ASKO project, part of the German DFG's programme Sozionik, which combines sociologists' and computer scientists' skills in order to create improved theories and models of artificial societies. Our research group has (a) formulated a social theory, which is able to explain fundamental mechanisms of self-organisation in both natural and artificial societies, (b) modelled this in a mathematical way using a visual formalism, and (c) developed a novel multi-agent system architecture which is conceptually coherent, recursively structured (hence non-eclectic) and based on our social theory. The article presents an outline of both a sociological middle-range theory of social self-organisation in educational institutions, its formal, Petri net based model, including a simulation of one of its main mechanisms, and the multi-agent system architecture SONAR. It describes how the theory was created by a re-analysis of some grand social theories, by grounding it empirically, and finally how the theory was evaluated by modelling its concepts and statements.Multi-Agents Systems, Petri Nets, Self-Organisation, Social Theories

On the "principle of the quantumness", the quantumness of Relativity, and the computational grand-unification

After reviewing recently suggested operational "principles of the quantumness", I address the problem on whether Quantum Theory (QT) and Special Relativity (SR) are unrelated theories, or instead, if the one implies the other. I show how SR can be indeed derived from causality of QT, within the computational paradigm "the universe is a huge quantum computer", reformulating QFT as a Quantum-Computational Field Theory (QCFT). In QCFT SR emerges from the fabric of the computational network, which also naturally embeds gauge invariance. In this scheme even the quantization rule and the Planck constant can in principle be derived as emergent from the underlying causal tapestry of space-time. In this way QT remains the only theory operating the huge computer of the universe. Is QCFT only a speculative tautology (theory as simulation of reality), or does it have a scientific value? The answer will come from Occam's razor, depending on the mathematical simplicity of QCFT. Here I will just start scratching the surface of QCFT, analyzing simple field theories, including Dirac's. The number of problems and unmotivated recipes that plague QFT strongly motivates us to undertake the QCFT project, since QCFT makes all such problems manifest, and forces a re-foundation of QFT.Comment: To be published on AIP Proceedings of Vaxjo conference. The ideas on Quantum-Circuit Field Theory are more recent. V4 Largely improved, with new interesting results and concepts. Dirac equation solve

Mathematical aspects of mean field spin glass theory

A comprehensive review will be given about the rich mathematical structure of mean field spin glass theory, mostly developed, until now, in the frame of the methods of theoretical physics, based on deep physical intuition and hints coming from numerical simulation. Central to our treatment is a very simple and yet powerful interpolation method, allowing to compare different probabilistic schemes, by using convexity and positivity arguments. In this way we can prove the existence of the thermodynamic limit for the free energy density of the system, a long standing open problem. Moreover, in the frame of a generalized variational principle, we can show the emergency of the Derrida-Ruelle random probability cascades, leading to the form of free energy given by the celebrated Parisi \textit {Ansatz}. All these results seem to be in full agreement with the mechanism of spontaneous replica symmetry breaking as developed by Giorgio Parisi.Comment: proceedings of the "4th European Congress of Mathematics", Stockholm, 2004. 17 page

The impact of nonlinear dynamics on the resilience of a grocery supply chain

Purpose of this paper: In an effort to improve operational and logistical efficiencies, UK grocery retailers combined primary and secondary distribution increasing the importance of designing resilient replenishment systems in the distribution centre. This paper has the purpose to analyse the resilience performance of the distribution centre stock ordering system within a grocery retailer. Design/methodology/approach: A system dynamics approach is used for framing and building a credible representation of the real system. Mathematical analysis of the nonlinear model based on nonlinear control engineering techniques in combination with system dynamics simulation have been used to understand the behaviour of stock and shipment output responses in the distribution centre given step and periodic demand signals. Findings: Preliminary mathematical analysis through nonlinear control theory techniques has been undertaken in order to gain initial insights in the understanding of the replenishment control model. This practice allowed the researcher to identify specific behaviour change in the DC stock and shipment responses, which are key indicators for assessing supply chain resilience, without going through a time-consuming simulation process. Transfer function analysis and describing function serve as a guideline for undertaking system dynamics simulation. Value: This paper aims to fill the gap in the literature of supply chain resilience by using quantitative system dynamics methods to assess the resilience performance of a grocery retailer. In this way, we also supplement the literature with empirical data. Moreover, we explore different analytical methods since simulation is the predominant method for quantitative analysis of system dynamics. Research limitations/implications (if applicable): This research is limited to the dynamics of single-echelon supply chain systems. Although the EPOS sales data and the store replenishment system have been considered in the validation process, this study has focused on analysing the resilience performance of the DC replenishment system only. Considering the multi-echelon supply chain is intended for further research activities. Practical implications (if applicable): The findings suggest that the distribution centre replenishment system can be re-designed in order to improve the supply chain resilience performance. The ‘As Is’ scenario produces slow response of stock levels and inventory targets are never recovered due to a permanent offset

Random State Technology

We review and extend, in a self-contained way, the mathematical foundations of numerical simulation methods that are based on the use of random states. The power and versatility of this simulation technology is illustrated by calculations of physically relevant properties such as the density of states of large single particle systems, the specific heat, current-current correlations, density-density correlations, and electron spin resonance spectra of many-body systems. We explore a new field of applications of the random state technology by showing that it can be used to analyze numerical simulations and experiments that aim to realize quantum supremacy on a noisy intermediate-scale quantum processor. Additionally, we show that concepts of the random state technology prove useful in quantum information theory

Improved kernel estimation of copulas: Weak convergence and goodness-of-fit testing

We reconsider the existing kernel estimators for a copula function, as proposed in Gijbels and Mielniczuk [Comm. Statist. Theory Methods 19 (1990) 445--464], Fermanian, Radulovi\v{c} and Wegkamp [Bernoulli 10 (2004) 847--860] and Chen and Huang [Canad. J. Statist. 35 (2007) 265--282]. All of these estimators have as a drawback that they can suffer from a corner bias problem. A way to deal with this is to impose rather stringent conditions on the copula, outruling as such many classical families of copulas. In this paper, we propose improved estimators that take care of the typical corner bias problem. For Gijbels and Mielniczuk [Comm. Statist. Theory Methods 19 (1990) 445--464] and Chen and Huang [Canad. J. Statist. 35 (2007) 265--282], the improvement involves shrinking the bandwidth with an appropriate functional factor; for Fermanian, Radulovi\v{c} and Wegkamp [Bernoulli 10 (2004) 847--860], this is done by using a transformation. The theoretical contribution of the paper is a weak convergence result for the three improved estimators under conditions that are met for most copula families. We also discuss the choice of bandwidth parameters, theoretically and practically, and illustrate the finite-sample behaviour of the estimators in a simulation study. The improved estimators are applied to goodness-of-fit testing for copulas.Comment: Published in at http://dx.doi.org/10.1214/08-AOS666 the Annals of Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical Statistics (http://www.imstat.org