MIMIC

Last updated

MIMIC, known in capitalized form only, is a former simulation computer language developed 1964 by H. E. Petersen, F. J. Sansom and L. M. Warshawsky of Systems Engineering Group within the Air Force Materiel Command at the Wright-Patterson AFB in Dayton, Ohio, United States. [1] It is an expression-oriented continuous block simulation language, but capable of incorporating blocks of FORTRAN-like algebra.

MIMIC is a further development from MIDAS (Modified Integration Digital Analog Simulator), which represented analog computer design. Written completely in FORTRAN but one routine in COMPASS, and ran on Control Data supercomputers, MIMIC is capable of solving much larger simulation models.

With MIMIC, ordinary differential equations describing mathematical models in several scientific disciplines as in engineering, physics, chemistry, biology, economics and as well as in social sciences can easily be solved by numerical integration and the results of the analysis are listed or drawn in diagrams. It also enables the analysis of nonlinear dynamic conditions.

The MIMIC software package, written as FORTRAN overlay programs, executes input statements of the mathematical model in six consecutive passes. Simulation programs written in MIMIC are compiled rather than interpreted. The core of the simulation package is a variable step numerical integrator of fourth-order Runge-Kutta method. Many useful functions related to electrical circuit elements exist besides some mathematical functions found in most scientific programming languages. There is no need to sort the statements in order of dependencies of the variables, since MIMIC does it internally.

Parts of the software organized in overlays are:

Example

Problem

Consider a predator-prey model from the field of marine biology to determine the dynamics of fish and shark populations. As a simple model, we choose the Lotka–Volterra equation and the constants given in a tutorial. [2]

If

f(t): Fish population over time (fish)
s(t): Shark population over time (sharks)
df / dt or : growth rate of fish population (fish/year)
ds / dt or : growth rate of shark population (sharks/year)
: growth rate of fish in the absence of sharks (1/year)
: death rate per encounter of fish with sharks (1/sharks and year).
: death rate of sharks in the absence of their prey, fish (1/year)
: efficiency of turning predated fish into sharks (sharks/fish)

then

with initial conditions

The problem's constants are given as:

Code sample
Card columns 0        1         2         3         4         5         6         7 12345678901234567890123456789012345678901234567890123456789012345678901 ----------------------------------------------------------------------- * A SIMPLE PREDATOR-PREY MODEL FROM MARINE BIOLOGY / (TUTORIAL 2: NUMERICAL SOLUTION OF ODE'S - 19/08/02) / ENVIRONMENTAL FLUID MECHANICS LAB / DEPT OF CIVIL AND ENVIRONMENTAL ENGINEERİNG / STANFORD UNIVERSITY * * LOTKA–VOLTERRA EQUATION                   CON(F0,S0,TMAX)                   CON(ALPHA,BETA,GAMMA,EPS)           1DF   = ALPHA*F-BETA*F*S           F     = INT(1DF,F0)           1DS   = EPS*BETA*F*S-GAMMA*S           S     = INT(1DS,S0)                   HDR(TIME,FISH,SHARK)                   OUT(T,F,S)                   PLO(F,S)                   FIN(T,TMAX)                   END <EOR> 600.       50.          50. 0.7        0.007        0.5         0.1 <EOF>

Related Research Articles

In tensor analysis, a mixed tensor is a tensor which is neither strictly covariant nor strictly contravariant; at least one of the indices of a mixed tensor will be a subscript (covariant) and at least one of the indices will be a superscript (contravariant).

The Flipped SU(5) model is a grand unified theory (GUT) first contemplated by Stephen Barr in 1982, and by Dimitri Nanopoulos and others in 1984. Ignatios Antoniadis, John Ellis, John Hagelin, and Dimitri Nanopoulos developed the supersymmetric flipped SU(5), derived from the deeper-level superstring.

The Lotka–Volterra equations, also known as the Lotka–Volterra predator–prey model, are a pair of first-order nonlinear differential equations, frequently used to describe the dynamics of biological systems in which two species interact, one as a predator and the other as prey. The populations change through time according to the pair of equations:

An infinitary logic is a logic that allows infinitely long statements and/or infinitely long proofs. The concept was introduced by Zermelo in the 1930s.

In differential geometry, the Einstein tensor is used to express the curvature of a pseudo-Riemannian manifold. In general relativity, it occurs in the Einstein field equations for gravitation that describe spacetime curvature in a manner that is consistent with conservation of energy and momentum.

In differential geometry, a tensor density or relative tensor is a generalization of the tensor field concept. A tensor density transforms as a tensor field when passing from one coordinate system to another, except that it is additionally multiplied or weighted by a power W of the Jacobian determinant of the coordinate transition function or its absolute value. A tensor density with a single index is called a vector density. A distinction is made among (authentic) tensor densities, pseudotensor densities, even tensor densities and odd tensor densities. Sometimes tensor densities with a negative weight W are called tensor capacity. A tensor density can also be regarded as a section of the tensor product of a tensor bundle with a density bundle.

<span class="mw-page-title-main">Electromagnetic tensor</span> Mathematical object that describes the electromagnetic field in spacetime

In electromagnetism, the electromagnetic tensor or electromagnetic field tensor is a mathematical object that describes the electromagnetic field in spacetime. The field tensor was first used after the four-dimensional tensor formulation of special relativity was introduced by Hermann Minkowski. The tensor allows related physical laws to be written very concisely, and allows for the quantization of the electromagnetic field by Lagrangian formulation described below.

The Havriliak–Negami relaxation is an empirical modification of the Debye relaxation model in electromagnetism. Unlike the Debye model, the Havriliak–Negami relaxation accounts for the asymmetry and broadness of the dielectric dispersion curve. The model was first used to describe the dielectric relaxation of some polymers, by adding two exponential parameters to the Debye equation:

In general relativity, the Gibbons–Hawking–York boundary term is a term that needs to be added to the Einstein–Hilbert action when the underlying spacetime manifold has a boundary.

The time-evolving block decimation (TEBD) algorithm is a numerical scheme used to simulate one-dimensional quantum many-body systems, characterized by at most nearest-neighbour interactions. It is dubbed Time-evolving Block Decimation because it dynamically identifies the relevant low-dimensional Hilbert subspaces of an exponentially larger original Hilbert space. The algorithm, based on the Matrix Product States formalism, is highly efficient when the amount of entanglement in the system is limited, a requirement fulfilled by a large class of quantum many-body systems in one dimension.

In mathematical finance, the SABR model is a stochastic volatility model, which attempts to capture the volatility smile in derivatives markets. The name stands for "stochastic alpha, beta, rho", referring to the parameters of the model. The SABR model is widely used by practitioners in the financial industry, especially in the interest rate derivative markets. It was developed by Patrick S. Hagan, Deep Kumar, Andrew Lesniewski, and Diana Woodward.

The Fama–MacBeth regression is a method used to estimate parameters for asset pricing models such as the capital asset pricing model (CAPM). The method estimates the betas and risk premia for any risk factors that are expected to determine asset prices. The method works with multiple assets across time. The parameters are estimated in two steps:

  1. First regress each of n asset returns against m proposed risk factors to determine each asset's beta exposures.
  2. Then regress all asset returns for each of T time periods against the previously estimated betas to determine the risk premium for each factor.

Interaction nets are a graphical model of computation devised by Yves Lafont in 1990 as a generalisation of the proof structures of linear logic. An interaction net system is specified by a set of agent types and a set of interaction rules. Interaction nets are an inherently distributed model of computation in the sense that computations can take place simultaneously in many parts of an interaction net, and no synchronisation is needed. The latter is guaranteed by the strong confluence property of reduction in this model of computation. Thus interaction nets provide a natural language for massive parallelism. Interaction nets are at the heart of many implementations of the lambda calculus, such as efficient closed reduction and optimal, in Lévy's sense, Lambdascope.

In continuum mechanics, a compatible deformation tensor field in a body is that unique tensor field that is obtained when the body is subjected to a continuous, single-valued, displacement field. Compatibility is the study of the conditions under which such a displacement field can be guaranteed. Compatibility conditions are particular cases of integrability conditions and were first derived for linear elasticity by Barré de Saint-Venant in 1864 and proved rigorously by Beltrami in 1886.

The narrow escape problem is a ubiquitous problem in biology, biophysics and cellular biology.

<span class="mw-page-title-main">Calculus of moving surfaces</span> Extension of the classical tensor calculus

The calculus of moving surfaces (CMS) is an extension of the classical tensor calculus to deforming manifolds. Central to the CMS is the Tensorial Time Derivative whose original definition was put forth by Jacques Hadamard. It plays the role analogous to that of the covariant derivative on differential manifolds in that it produces a tensor when applied to a tensor.

In mathematics, Ricci calculus constitutes the rules of index notation and manipulation for tensors and tensor fields on a differentiable manifold, with or without a metric tensor or connection. It is also the modern name for what used to be called the absolute differential calculus, developed by Gregorio Ricci-Curbastro in 1887–1896, and subsequently popularized in a paper written with his pupil Tullio Levi-Civita in 1900. Jan Arnoldus Schouten developed the modern notation and formalism for this mathematical framework, and made contributions to the theory, during its applications to general relativity and differential geometry in the early twentieth century.

Vasiliev equations are formally consistent gauge invariant nonlinear equations whose linearization over a specific vacuum solution describes free massless higher-spin fields on anti-de Sitter space. The Vasiliev equations are classical equations and no Lagrangian is known that starts from canonical two-derivative Frønsdal Lagrangian and is completed by interactions terms. There is a number of variations of Vasiliev equations that work in three, four and arbitrary number of space-time dimensions. Vasiliev's equations admit supersymmetric extensions with any number of super-symmetries and allow for Yang–Mills gaugings. Vasiliev's equations are background independent, the simplest exact solution being anti-de Sitter space. It is important to note that locality is not properly implemented and the equations give a solution of certain formal deformation procedure, which is difficult to map to field theory language. The higher-spin AdS/CFT correspondence is reviewed in Higher-spin theory article.

<span class="mw-page-title-main">Dual graviton</span> Hypothetical particle found in supergravity

In theoretical physics, the dual graviton is a hypothetical elementary particle that is a dual of the graviton under electric-magnetic duality, as an S-duality, predicted by some formulations of supergravity in eleven dimensions.

<span class="mw-page-title-main">Courant–Snyder parameters</span> Set of quantities in accelerator physics

In accelerator physics, the Courant–Snyder parameters are a set of quantities used to describe the distribution of positions and velocities of the particles in a beam. When the positions along a single dimension and velocities along that dimension of every particle in a beam are plotted on a phase space diagram, an ellipse enclosing the particles can be given by the equation:

References

  1. Defense Technical Information Center [ dead link ]
  2. "Tutorial 2: Numerical Solutions of ODE's" (PDF). Stanford University-Dept of Civil and Environmental Engineering, Environmental Fluid Mechanics Lab. 2002-08-19. Archived from the original (PDF) on 2010-07-20. Retrieved 2012-02-26.
Notes