Education

Teaching and learning about math, Maple and MapleSim

I'm back from presenting work in the "23rd Conference on Applications of Computer Algebra - 2017" . It was a very interesting event. This second presentation, about "Differential algebra with mathematical functions, symbolic powers and anticommutative variables", describes a project I started working in 1997 and that is at the root of Maple's dsolve and pdsolve performance with systems of equations. It is a unique approach. Not yet emulated in any other computer algebra system.

At the end, there is a link to the presentation worksheet, with which one could open the sections and reproduce the presentation examples.
 

Differential algebra with mathematical functions,

symbolic powers and anticommutative variables

 

Edgardo S. Cheb-Terrab

Physics, Differential Equations and Mathematical Functions, Maplesoft

 

Abstract:
Computer algebra implementations of Differential Algebra typically require that the systems of equations to be tackled be rational in the independent and dependent variables and their partial derivatives, and of course that A*B = A*B, everything is commutative.

 

It is possible, however, to extend this computational domain and apply Differential Algebra techniques to systems of equations that involve arbitrary compositions of mathematical functions (elementary or special), fractional and symbolic powers, as well as anticommutative variables and functions. This is the subject of this presentation, with examples of the implementation of these ideas in the Maple computer algebra system and its ODE and PDE solvers.

 

 

restartwith(PDEtools); interface(imaginaryunit = i)

sys := [diff(xi(x, y), y, y) = 0, -6*(diff(xi(x, y), y))*y+diff(eta(x, y), y, y)-2*(diff(xi(x, y), x, y)) = 0, -12*(diff(xi(x, y), y))*a^2*y-9*(diff(xi(x, y), y))*a*y^2-3*(diff(xi(x, y), y))*b-3*(diff(xi(x, y), x))*y-3*eta(x, y)+2*(diff(eta(x, y), x, y))-(diff(xi(x, y), x, x)) = 0, -8*(diff(xi(x, y), x))*a^2*y-6*(diff(xi(x, y), x))*a*y^2+4*(diff(eta(x, y), y))*a^2*y+3*(diff(eta(x, y), y))*a*y^2-4*eta(x, y)*a^2-6*eta(x, y)*a*y-2*(diff(xi(x, y), x))*b+(diff(eta(x, y), y))*b-3*(diff(eta(x, y), x))*y+diff(eta(x, y), x, x) = 0]

 

declare((xi, eta)(x, y))

xi(x, y)*`will now be displayed as`*xi

 

eta(x, y)*`will now be displayed as`*eta

(1)

for eq in sys do eq end do

diff(diff(xi(x, y), y), y) = 0

 

-6*(diff(xi(x, y), y))*y+diff(diff(eta(x, y), y), y)-2*(diff(diff(xi(x, y), x), y)) = 0

 

-12*(diff(xi(x, y), y))*a^2*y-9*(diff(xi(x, y), y))*a*y^2-3*(diff(xi(x, y), y))*b-3*(diff(xi(x, y), x))*y-3*eta(x, y)+2*(diff(diff(eta(x, y), x), y))-(diff(diff(xi(x, y), x), x)) = 0

 

-8*(diff(xi(x, y), x))*a^2*y-6*(diff(xi(x, y), x))*a*y^2+4*(diff(eta(x, y), y))*a^2*y+3*(diff(eta(x, y), y))*a*y^2-4*eta(x, y)*a^2-6*eta(x, y)*a*y-2*(diff(xi(x, y), x))*b+(diff(eta(x, y), y))*b-3*(diff(eta(x, y), x))*y+diff(diff(eta(x, y), x), x) = 0

(2)

casesplit(sys)

`casesplit/ans`([eta(x, y) = 0, diff(xi(x, y), x) = 0, diff(xi(x, y), y) = 0], [])

(3)

NULL

Differential polynomial forms for mathematical functions (basic)

   

Differential polynomial forms for compositions of mathematical functions

   

Generalization to many variables

   

Arbitrary functions of algebraic expressions

   

Examples of the use of this extension to include mathematical functions

   

Differential Algebra with anticommutative variables

   


 

Download DifferentialAlgebra.mw

Download DifferentialAlgebra.pdf

Edgardo S. Cheb-Terrab
Physics, Differential Equations and Mathematical Functions, Maplesoft

 

I'm back from presenting work in the "23rd Conference on Applications of Computer Algebra - 2017" . It was a very interesting event. This first presentation, about "Active Learning in High-School Mathematics using Interactive Interfaces", describes a project I started working 23 years ago, which I believe will be part of the future in one or another form. This is work actually not related to my work at Maplesoft.

At the end, there is a link to the presentation worksheet, with which one could open the sections and reproduce the presentation examples.
 

 

Active learning in High-School mathematics using Interactive Interfaces

 

Edgardo S. Cheb-Terrab

Physics, Differential Equations and Mathematical Functions, Maplesoft

 

Abstract:


The key idea in this project is to learn through exploration using a web of user-friendly Highly Interactive Graphical Interfaces (HIGI). The HIGIs, structured as trees of interlinked windows, present concepts using a minimal amount of text while maximizing the possibility of visual and analytic exploration. These interfaces run computer algebra software in the background. Assessment tools are integrated into the learning experience within the general conceptual map, the Navigator. This Navigator offers students self-assessment tools and full access to the logical sequencing of course concepts, helping them to identify any gaps in their knowledge and to launch the corresponding learning interfaces. An interactive online set of HIGIS of this kind can be used at school, at home, in distance education, and both individually and in a group.

 

 

Computer algebra interfaces for High-School students of "Colegio de Aplicação"  (UERJ/1994)

   

Motivation

 

 

When we are the average high-school student facing mathematics, we tend to feel

 

• 

Bored, fragmentarily taking notes, listening to a teacher for 50 or more minutes

• 

Anguished because we do not understand some math topics (too many gaps accumulated)

• 

Powerless because we don't know what to do to understand (don't have any instant-tutor to ask questions and without being judged for having accumulated gaps)

• 

Stressed by the upcoming exams where the lack of understanding may become evident

 

Computer algebra environments can help in addressing these issues.

 

 

• 

Be as active as it can get while learning at our own pace.

• 

Explore at high speed and without feeling judged. There is space for curiosity with no computational cost.

• 

Feel empowered by success. That leads to understanding.

• 

Possibility for making of learning a social experience.

 

Interactive interfaces

 

 

 

Interactive interfaces do not replace the teacher - human learning is an emotional process. A good teacher leading good active learning is a positive experience a student will never forget

 

 

Not every computer interface is a valuable resource, at all. It is the set of pedagogical ideas implemented that makes an interface valuable (the same happens with textbooks)

 

 

A course on high school mathematics using interactive interfaces - the Edukanet project

 

 

– 

Brazilian and Canadian students/programmers were invited to participate - 7 people worked in the project.

 

– 

Some funding provided by the Brazilian Research agency CNPq.

Tasks:

-Develop a framework to develop the interfaces covering the last 3 years of high school mathematics (following the main math textbook used in public schools in Brazil)

- Design documents for the interfaces according to given pedagogical guidelines.

- Create prototypes of Interactive interfaces, running Maple on background, according to design document and specified layout (allow for everybody's input/changes).

 

The pedagogical guidelines for interactive interfaces

   

The Math-contents design documents for each chapter

 

Example: complex numbers

   

Each math topic:  a interactive interrelated interfaces (windows)

 

 

For each topic of high-school mathematics (chapter of a textbook), develop a tree of interactive interfaces (applets) related to the topic (main) and subtopics

 

Example: Functions

 

• 

Main window

 

• 

Analysis window

• 

 

• 

Parity window

• 

Visualization of function's parity

• 

Step-by-Step solution window

The Navigator: a window with a tile per math topic

 

 

 

• 

Click the topic-tile to launch a smaller window, topic-specific, map of interrelated sub-topic tiles, that indicates the logical sequence for the sub-topics, and from where one could launch the corresponding sub-topic interactive interface.

• 

This topic-specific smaller window allows for identifying the pre-requisites and gaps in understanding, launching the corresponding interfaces to fill the gaps, and tracking the level of familiarity with a topic.

 

 

 

 

 

The framework to create the interfaces: a version of NetBeans on steroids ...

   

Complementary classroom activity on a computer algebra worksheet

 

 

This course is organized as a guided experience, 2 hours per day during five days, on learning the basics of the Maple language, and on using it to formulate algebraic computations we do with paper and pencil in high school and 1st year of undergraduate science courses.

 

Explore. Having success doesn't matter, using your curiosity as a compass does - things can be done in so many different ways. Have full permission to fail. Share your insights. All questions are valid even if to the side. Computer algebra can transform the learning of mathematics into interesting understanding, success and fun.

1. Arithmetic operations and elementary functions

   

2. Algebraic Expressions, Equations and Functions

   

3. Limits, Derivatives, Sums, Products, Integrals, Differential Equations

   

4. Algebraic manipulation: simplify, factorize, expand

   

5. Matrices (Linear Algebra)

   

 

Advanced students: guiding them to program mathematical concepts on a computer algebra worksheet

   

Status of the project

 

 

Prototypes of interfaces built cover:

 

• 

Natural numbers

• 

Functions

• 

Integer numbers

• 

Rational numbers

• 

Absolute value

• 

Logarithms

• 

Numerical sequences

• 

Trigonometry

• 

Matrices

• 

Determinants

• 

Linear systems

• 

Limits

• 

Derivatives

• 

Derivative of the inverse function

• 

The point in Cartesian coordinates

• 

The line

• 

The circle

• 

The ellipse

• 

The parabole

• 

The hyperbole

• 

The conics

More recent computer algebra frameworks: Maple Mobius for online courses and automated evaluation

   

 


 

Download Computer_Algebra_in_Education.mw

Download Computer_Algebra_in_Education.pdf

Edgardo S. Cheb-Terrab
Physics, Differential Equations and Mathematical Functions, Maplesoft

The representation of the tangent plane in the form of a square with a given length of the side at any point on the surface.

The equation of the tangent plane to the surface at a given point is obtained from the condition that the tangent plane is perpendicular to the normal vector. With the aid of any auxiliary point not lying on this normal to the surface, we define the direction on the tangent plane. From the given point in this direction, we lay off segments equal to half the length of the side of our square and with the help of these segments we construct the square itself, lying on the tangent plane with the center at a given point.

An examples of constructing tangent planes at points of the same intersection line for two surfaces.
Tangent_plane.mw

This app is used to study the behavior of water in its different properties besides air. Also included is the study of the fluids in the state of rest ie the pressure generated on a flat surface. Integral developed in Maple for the community of users in space to the civil engineers.

App_for_fluids_in_flat_state_of_rest.mw

Lenin Araujo Castillo

Ambassador of Maple

 

We have just released the 3rd edition of the Mathematics Survival Kit – Maple Edition.

The Math Survival Kit helps students get unstuck when they are stuck. Sometimes students are prevented from solving a problem, not because they haven’t understood the new concept, but because they forget how to do one of the steps, like completely the square, or dealing with log properties.  That’s where this interactive e- book comes in. It gives students the opportunity to review exactly the concept or technique they are stuck on, work through an example, practice as much (or as little) as they want using randomly generated, automatically graded questions on that exact topic, and then continue with their homework.

This book covers over 150 topics known to cause students grief, from dividing fractions to integration by parts. This 3rd edition contains 31 additional topics, deepening the coverage of mathematical topics at every level, from pre-high school to university.

See the Mathematics Survival Kit for more information about this updated e-book, including the complete list of topics.

eithne

This post is the answer to this question.

The procedure named  IntOverDomain  finds a double integral over an arbitrary domain bounded by a non-selfintersecting piecewise smooth curve. The code of the procedure uses the well-known Green's theorem.

Each section in the border should be specified by a list in the following formats :    
1. If a section is given parametrically, then  [[f(t), g(t)], t=t1..t2]    
2. If several consecutive sections of the border or the entire border is a broken line, then it is sufficient to set vertices of this broken line  [ [x1,y1], [x2,y2], .., [xn,yn] ] (for the entire border should be  [xn,yn]=[x1,y1] ).

Required parameters of the procedure:  f  is an expression in variables  x  and  y , L  is the list of all the sections. The sublists of the list  L  must follow in the positive direction (counterclockwise).

The code of the procedure:

restart;
IntOverDomain := proc(f, L) 
local n, i, j, m, yk, yb, xk, xb, Q, p, P, var;
n:=nops(L);
Q:=int(f,x);  
for i from 1 to n do 
if type(L[i], listlist(algebraic)) then
m:=nops(L[i]);
for j from 1 to m-1 do
yk:=L[i,j+1,2]-L[i,j,2]; yb:=L[i,j,2];
xk:=L[i,j+1,1]-L[i,j,1]; xb:=L[i,j,1];
p[j]:=int(eval(Q*yk,[y=yk*t+yb,x=xk*t+xb]),t=0..1);
od;
P[i]:=add(p[j],j=1..m-1) else
var := lhs(L[i, 2]);
P[i]:=int(eval(Q*diff(L[i,1,2],var),[x=L[i,1,1],y=L[i,1,2]]),L[i,2]) fi;
od; 
add(P[i], i = 1 .. n); 
end proc:

 

Examples of use.

1. In the first example, we integrate over a quadrilateral:

with(plottools): with(plots):
f:=x^2+y^2:
display(polygon([[0,0],[3,0],[0,3],[1,1]], color="LightBlue"));  
# Visualization of the domain of integration
IntOverDomain(x^2+y^2, [[[0,0],[3,0],[0,3],[1,1],[0,0]]]);  # The value of integral

 

2. In the second example, some sections of the boundary of the domain are curved lines:

display(inequal({{y<=sqrt(x),y>=sin(Pi*x/3)/2,y<=3-x}, {y>=-2*x+3,y>=sqrt(x),y<=3-x}}, x=0..3,y=0..3, color="LightGreen", nolines), plot([[t,sqrt(t),t=0..1],[t,-2*t+3,t=0..1],[t,3-t,t=0..3],[t,sin(Pi*t/3)/2,t=0..3]], color=black, thickness=2));
f:=x^2+y^2: L:=[[[t,sin(Pi*t/3)/2],t=0..3],[[3,0],[0,3],[1,1]], [[t,sqrt(t)],t=1..0]]:
IntOverDomain(f, L);

 

3. If  f=1  then the procedure returns the area of the domain:

IntOverDomain(1, L);  # The area of the above domain
evalf(%);

 

IntOverDomain.mw

Edit.

This app shows the calculation of the final speed of a body after it made contact with a variable force; Taking as reference the initial velocity, mass and graph of the variation of F as a function of time. That is, given the variable forces represented by the lines in the time intervals, we will show the equation of momentum and momentum; With their respective values, followed by their response.

Momentum_with_two_variable_force.mw

https://www.youtube.com/watch?v=2xWkF7JhkpI

Lenin Araujo C.

Ambassador of Maple

 

 

 

 

 

 

 

Physics

 

 

Maple provides a state-of-the-art environment for algebraic and tensorial computations in Physics, with emphasis on ensuring that the computational experience is as natural as possible.

 

The theme of the Physics project for Maple 2017 has been the consolidation of the functionality introduced in previous releases, together with significant enhancements and new functionality in General Relativity, in connection with classification of solutions to Einstein's equations and tensor representations to work in an embedded 3D curved space - a new ThreePlusOne  package. This package is relevant in numerical relativity and a Hamiltonian formulation of gravity. The developments also include first steps in connection with computational representations for all the objects entering the Standard Model in particle physics.

Classification of solutions to Einstein's equations and the Tetrads package

 

In Maple 2016, the digitizing of the database of solutions to Einstein's equations  was finished, added to the standard Maple library, with all the metrics from "Stephani, H.; Kramer, D.; MacCallum, M.; Hoenselaers, C.; and Herlt, E., Exact Solutions to Einstein's Field Equations". These metrics can be loaded to work with them, or change them, or searched using g_  (the Physics command representing the spacetime metric that also sets the metric to your choice in one go) or using the command DifferentialGeometry:-Library:-MetricSearch .


In Maple 2017, the Physics:-Tetrads  package has been vastly improved and extended, now including new commands like PetrovType  and SegreType  to classify these metrics, and the TransformTetrad  now has an option canonicalform to automatically derive a transformation and put the tetrad in canonical form (reorientation of the axis of the local system of references), a relevant step in resolving the equivalence between two metrics.

Examples

 

Petrov and Segre types, tetrads in canonical form

   

Equivalence for Schwarzschild metric (spherical and Kruskal coordinates)

 

Formulation of the problem (remove mixed coordinates)

   

Solving the Equivalence

   

The ThreePlusOne (3 + 1) new Maple 2017 Physics package

 

ThreePlusOne , is a package to cast Einstein's equations in a 3+1 form, that is, representing spacetime as a stack of nonintersecting 3-hypersurfaces Σ. This 3+1 description is key in the Hamiltonian formulation of gravity as well as in the study of gravitational waves, black holes, neutron stars, and in general to study the evolution of physical system in general relativity by running numerical simulations as traditional initial value (Cauchy) problems. ThreePlusOne includes computational representations for the spatial metric gamma[i, j] that is induced by g[mu, nu] on the 3-dimensional hypersurfaces, and the related covariant derivative, Christoffel symbols and Ricci and Riemann tensors, the Lapse, Shift, Unit normal and Time vectors and Extrinsic curvature related to the ADM equations.

 

The following is a list of the available commands:

 

ADMEquations

Christoffel3

D3_

ExtrinsicCurvature

gamma3_

Lapse

Ricci3

Riemann3

Shift

TimeVector

UnitNormalVector

 

 

The other four related new Physics  commands:

 

• 

Decompose , to decompose 4D tensorial expressions (free and/or contracted indices) into the space and time parts.

• 

gamma_ , representing the three-dimensional metric tensor, with which the element of spatial distance is defined as  `#mrow(msup(mi("dl"),mrow(mo("&InvisibleTimes;"),mn("2"))),mo("&equals;"),msub(mi("&gamma;",fontstyle = "normal"),mrow(mi("i"),mo("&comma;"),mi("j"))),mo("&InvisibleTimes;"),msup(mi("dx"),mi("i")),mo("&InvisibleTimes;"),msup(mi("dx"),mi("j")))`.

• 

Redefine , to redefine the coordinates and the spacetime metric according to changes in the signature from any of the four possible signatures(− + + +), (+ − − −), (+ + + −) and ((− + + +) to any of the other ones.

• 

EnergyMomentum , is a computational representation for the energy-momentum tensor entering Einstein's equations as well as their 3+1 form, the ADMEquations .

 

Examples

 

restart; with(Physics); Setup(coordinatesystems = cartesian)

`Default differentiation variables for d_, D_ and dAlembertian are: `*{X = (x, y, z, t)}

 

`Systems of spacetime Coordinates are: `*{X = (x, y, z, t)}

 

[coordinatesystems = {X}]

(2.1.1)

with(ThreePlusOne)

`Setting lowercaselatin_is letters to represent space indices `

 

0, "%1 is not a command in the %2 package", ThreePlusOne, Physics

 

`Changing the signature of spacetime from `(`- - - +`)*` to `(`+ + + -`)*` in order to match the signature customarily used in the ADM formalism`

 

[ADMEquations, Christoffel3, D3_, ExtrinsicCurvature, Lapse, Ricci3, Riemann3, Shift, TimeVector, UnitNormalVector, gamma3_]

(2.1.2)

Note the different color for gamma[mu, nu], now a 4D tensor representing the metric of a generic 3-dimensional hypersurface induced by the 4D spacetime metric g[mu, nu]. All the ThreePlusOne tensors are displayed in black to distinguish them of the corresponding 4D or 3D tensors. The particular hypersurface gamma[mu, nu] operates is parameterized by the Lapse  alpha and the Shift  beta[mu].

The induced metric gamma[mu, nu]is defined in terms of the UnitNormalVector  n[mu] and the 4D metric g[mu, nu] as

gamma3_[definition]

Physics:-ThreePlusOne:-gamma3_[mu, nu] = Physics:-ThreePlusOne:-UnitNormalVector[mu]*Physics:-ThreePlusOne:-UnitNormalVector[nu]+Physics:-g_[mu, nu]

(2.1.3)

where n[mu] is defined in terms of the Lapse  alpha and the derivative of a scalar function t that can be interpreted as a global time function

UnitNormalVector[definition]

Physics:-ThreePlusOne:-UnitNormalVector[mu] = -Physics:-ThreePlusOne:-Lapse*Physics:-D_[mu](t)

(2.1.4)

The TimeVector  is defined in terms of the Lapse  alpha and the Shift  beta[mu] and this vector  n[mu] as

TimeVector[definition]

Physics:-ThreePlusOne:-TimeVector[mu] = Physics:-ThreePlusOne:-Lapse*Physics:-ThreePlusOne:-UnitNormalVector[mu]+Physics:-ThreePlusOne:-Shift[mu]

(2.1.5)

The ExtrinsicCurvature  is defined in terms of the LieDerivative  of  gamma[mu, nu]

ExtrinsicCurvature[definition]

Physics:-ThreePlusOne:-ExtrinsicCurvature[mu, nu] = -(1/2)*Physics:-LieDerivative[Physics:-ThreePlusOne:-UnitNormalVector](Physics:-ThreePlusOne:-gamma3_[mu, nu])

(2.1.6)

The metric gamma[mu, nu]is also a projection tensor in that it projects 4D tensors into the 3D hypersurface Σ. The definition for any 4D tensor that is also a 3D tensor in Σ, can thus be written directly by contracting their indices with gamma[mu, nu]. In the case of Christoffel3 , Ricci3  and Riemann3,  these tensors can be defined by replacing the 4D metric g[mu, nu] by gamma[mu, nu] and the 4D Christoffel symbols GAMMA[mu, nu, alpha] by the ThreePlusOne GAMMA[mu, nu, alpha] in the definitions of the corresponding 4D tensors. So, for instance

Christoffel3[definition]

Physics:-ThreePlusOne:-Christoffel3[mu, nu, alpha] = (1/2)*Physics:-ThreePlusOne:-gamma3_[mu, `~beta`]*(Physics:-d_[alpha](Physics:-ThreePlusOne:-gamma3_[beta, nu], [X])+Physics:-d_[nu](Physics:-ThreePlusOne:-gamma3_[beta, alpha], [X])-Physics:-d_[beta](Physics:-ThreePlusOne:-gamma3_[nu, alpha], [X]))

(2.1.7)

Ricci3[definition]

Physics:-ThreePlusOne:-Ricci3[mu, nu] = Physics:-d_[alpha](Physics:-ThreePlusOne:-Christoffel3[`~alpha`, mu, nu], [X])-Physics:-d_[nu](Physics:-ThreePlusOne:-Christoffel3[`~alpha`, mu, alpha], [X])+Physics:-ThreePlusOne:-Christoffel3[`~beta`, mu, nu]*Physics:-ThreePlusOne:-Christoffel3[`~alpha`, beta, alpha]-Physics:-ThreePlusOne:-Christoffel3[`~beta`, mu, alpha]*Physics:-ThreePlusOne:-Christoffel3[`~alpha`, nu, beta]

(2.1.8)

Riemann3[definition]

Physics:-ThreePlusOne:-Riemann3[mu, nu, alpha, beta] = Physics:-g_[mu, lambda]*(Physics:-d_[alpha](Physics:-ThreePlusOne:-Christoffel3[`~lambda`, nu, beta], [X])-Physics:-d_[beta](Physics:-ThreePlusOne:-Christoffel3[`~lambda`, nu, alpha], [X])+Physics:-ThreePlusOne:-Christoffel3[`~lambda`, upsilon, alpha]*Physics:-ThreePlusOne:-Christoffel3[`~upsilon`, nu, beta]-Physics:-ThreePlusOne:-Christoffel3[`~lambda`, upsilon, beta]*Physics:-ThreePlusOne:-Christoffel3[`~upsilon`, nu, alpha])

(2.1.9)

When working with the ADM formalism, the line element of an arbitrary spacetime metric can be expressed in terms of the differentials of the coordinates dx^mu, the Lapse , the Shift  and the spatial components of the 3D metric gamma3_ . From this line element one can derive the relation between the Lapse , the spatial part of the Shift , the spatial part of the gamma3_  metric and the g[0, j] components of the 4D spacetime metric.

For this purpose, define a tensor representing the differentials of the coordinates and an alias  dt = `#msup(mi("dx"),mn("0"))`

Define(dx[mu])

`Defined objects with tensor properties`

 

{Physics:-ThreePlusOne:-D3_[mu], Physics:-Dgamma[mu], Physics:-Psigma[mu], Physics:-ThreePlusOne:-Ricci3[mu, nu], Physics:-ThreePlusOne:-Shift[mu], Physics:-d_[mu], dx[mu], Physics:-g_[mu, nu], Physics:-ThreePlusOne:-gamma3_[mu, nu], Physics:-gamma_[i, j], Physics:-ThreePlusOne:-Christoffel3[mu, nu, alpha], Physics:-KroneckerDelta[mu, nu], Physics:-LeviCivita[alpha, beta, mu, nu], Physics:-ThreePlusOne:-Riemann3[mu, nu, alpha, beta], Physics:-ThreePlusOne:-TimeVector[mu], Physics:-ThreePlusOne:-ExtrinsicCurvature[mu, nu], Physics:-ThreePlusOne:-UnitNormalVector[mu], Physics:-SpaceTimeVector[mu](X)}

(2.1.10)

"alias(dt = dx[~0]):"

The expression for the line element in terms of the Lapse  and Shift   is (see [2], eq.(2.123))

ds^2 = (-Lapse^2+Shift[i]^2)*dt^2+2*Shift[i]*dt*dx[`~i`]+gamma_[i, j]*dx[`~i`]*dx[`~j`]

ds^2 = (-Physics:-ThreePlusOne:-Lapse^2+Physics:-ThreePlusOne:-Shift[i]*Physics:-ThreePlusOne:-Shift[`~i`])*dt^2+2*Physics:-ThreePlusOne:-Shift[i]*dt*dx[`~i`]+Physics:-gamma_[i, j]*dx[`~i`]*dx[`~j`]

(2.1.11)

Compare this expression with the 3+1 decomposition of the line element in an arbitrary system. To avoid the automatic evaluation of the metric components, work with the inert form of the metric %g_

ds^2 = %g_[mu, nu]*dx[`~mu`]*dx[`~nu`]

ds^2 = %g_[mu, nu]*dx[`~mu`]*dx[`~nu`]

(2.1.12)

Decompose(ds^2 = %g_[mu, nu]*dx[`~mu`]*dx[`~nu`])

ds^2 = %g_[0, 0]*dt^2+%g_[0, j]*dt*dx[`~j`]+%g_[i, 0]*dt*dx[`~i`]+%g_[i, j]*dx[`~i`]*dx[`~j`]

(2.1.13)

The second and third terms on the right-hand side are equal

op(2, rhs(ds^2 = dt^2*%g_[0, 0]+dt*%g_[0, j]*dx[`~j`]+dt*%g_[i, 0]*dx[`~i`]+%g_[i, j]*dx[`~i`]*dx[`~j`])) = op(3, rhs(ds^2 = dt^2*%g_[0, 0]+dt*%g_[0, j]*dx[`~j`]+dt*%g_[i, 0]*dx[`~i`]+%g_[i, j]*dx[`~i`]*dx[`~j`]))

%g_[0, j]*dt*dx[`~j`] = %g_[i, 0]*dt*dx[`~i`]

(2.1.14)

subs(%g_[0, j]*dt*dx[`~j`] = %g_[i, 0]*dt*dx[`~i`], ds^2 = dt^2*%g_[0, 0]+dt*%g_[0, j]*dx[`~j`]+dt*%g_[i, 0]*dx[`~i`]+%g_[i, j]*dx[`~i`]*dx[`~j`])

ds^2 = %g_[0, 0]*dt^2+2*%g_[i, 0]*dt*dx[`~i`]+%g_[i, j]*dx[`~i`]*dx[`~j`]

(2.1.15)

Taking the difference between this expression and the one in terms of the Lapse  and Shift  we get

simplify((ds^2 = dt^2*%g_[0, 0]+2*dt*%g_[i, 0]*dx[`~i`]+%g_[i, j]*dx[`~i`]*dx[`~j`])-(ds^2 = (-Physics:-ThreePlusOne:-Lapse^2+Physics:-ThreePlusOne:-Shift[i]*Physics:-ThreePlusOne:-Shift[`~i`])*dt^2+2*Physics:-ThreePlusOne:-Shift[i]*dt*dx[`~i`]+Physics:-gamma_[i, j]*dx[`~i`]*dx[`~j`]))

0 = (Physics:-ThreePlusOne:-Lapse^2-Physics:-ThreePlusOne:-Shift[i]*Physics:-ThreePlusOne:-Shift[`~i`]+%g_[0, 0])*dt^2+2*dx[`~i`]*(%g_[i, 0]-Physics:-ThreePlusOne:-Shift[i])*dt-dx[`~i`]*dx[`~j`]*(Physics:-gamma_[i, j]-%g_[i, j])

(2.1.16)

Taking coefficients, we get equations for the Shift , the Lapse  and the spatial components of the metric gamma3_

eq[1] := coeff(coeff(rhs(0 = (Physics:-ThreePlusOne:-Lapse^2-Physics:-ThreePlusOne:-Shift[i]*Physics:-ThreePlusOne:-Shift[`~i`]+%g_[0, 0])*dt^2+2*dx[`~i`]*(%g_[i, 0]-Physics:-ThreePlusOne:-Shift[i])*dt-dx[`~i`]*dx[`~j`]*(Physics:-gamma_[i, j]-%g_[i, j])), dt), dx[`~i`]) = 0

2*%g_[i, 0]-2*Physics:-ThreePlusOne:-Shift[i] = 0

(2.1.17)

eq[2] := coeff(rhs(0 = (Physics:-ThreePlusOne:-Lapse^2-Physics:-ThreePlusOne:-Shift[i]*Physics:-ThreePlusOne:-Shift[`~i`]+%g_[0, 0])*dt^2+2*dx[`~i`]*(%g_[i, 0]-Physics:-ThreePlusOne:-Shift[i])*dt-dx[`~i`]*dx[`~j`]*(Physics:-gamma_[i, j]-%g_[i, j])), dt^2)

Physics:-ThreePlusOne:-Lapse^2-Physics:-ThreePlusOne:-Shift[i]*Physics:-ThreePlusOne:-Shift[`~i`]+%g_[0, 0]

(2.1.18)

eq[3] := coeff(coeff(rhs(0 = (Physics:-ThreePlusOne:-Lapse^2-Physics:-ThreePlusOne:-Shift[i]*Physics:-ThreePlusOne:-Shift[`~i`]+%g_[0, 0])*dt^2+2*dx[`~i`]*(%g_[i, 0]-Physics:-ThreePlusOne:-Shift[i])*dt-dx[`~i`]*dx[`~j`]*(Physics:-gamma_[i, j]-%g_[i, j])), dx[`~i`]), dx[`~j`]) = 0

-Physics:-gamma_[i, j]+%g_[i, j] = 0

(2.1.19)

Using these equations, these quantities can all be expressed in terms of the time and space components of the 4D metric g[0, 0] and g[i, j]

isolate(eq[1], Shift[i])

Physics:-ThreePlusOne:-Shift[i] = %g_[i, 0]

(2.1.20)

isolate(eq[2], Lapse^2)

Physics:-ThreePlusOne:-Lapse^2 = Physics:-ThreePlusOne:-Shift[i]*Physics:-ThreePlusOne:-Shift[`~i`]-%g_[0, 0]

(2.1.21)

isolate(eq[3], gamma_[i, j])

Physics:-gamma_[i, j] = %g_[i, j]

(2.1.22)

References

 
  

[1] Landau, L.D., and Lifshitz, E.M. The Classical Theory of Fields, Course of Theoretical Physics Volume 2, fourth revised English edition. Elsevier, 1975.

  

[2] Alcubierre, M., Introduction to 3+1 Numerical Relativity, International Series of Monographs on Physics 140, Oxford University Press, 2008.

  

[3] Baumgarte, T.W., Shapiro, S.L., Numerical Relativity, Solving Einstein's Equations on a Computer, Cambridge University Press, 2010.

  

[4] Gourgoulhon, E., 3+1 Formalism and Bases of Numerical Relativity, Lecture notes, 2007, https://arxiv.org/pdf/gr-qc/0703035v1.pdf.

  

[5] Arnowitt, R., Dese, S., Misner, C.W., The Dynamics of General Relativity, Chapter 7 in Gravitation: an introduction to current research (Wiley, 1962), https://arxiv.org/pdf/gr-qc/0405109v1.pdf

  

 

Examples: Decompose, gamma_

 

restartwith(Physics)NULL

Setup(mathematicalnotation = true)

[mathematicalnotation = true]

(2.2.1)

Define  now an arbitrary tensor A

Define(A)

`Defined objects with tensor properties`

 

{A, Physics:-Dgamma[mu], Physics:-Psigma[mu], Physics:-d_[mu], Physics:-g_[mu, nu], Physics:-KroneckerDelta[mu, nu], Physics:-LeviCivita[alpha, beta, mu, nu]}

(2.2.2)

So A^mu is a 4D tensor with only one free index, where the position of the time-like component is the position of the different sign in the signature, that you can query about via

Setup(signature)

[signature = `- - - +`]

(2.2.3)

To perform a decomposition into space and time, set - for instance - the lowercase latin letters from i to s to represent spaceindices and

Setup(spaceindices = lowercase_is)

[spaceindices = lowercaselatin_is]

(2.2.4)

Accordingly, the 3+1 decomposition of A^mu is

Decompose(A[`~mu`])

Array(%id = 18446744078724512334)

(2.2.5)

The 3+1 decomposition of the inert representation %g_[mu,nu] of the 4D spacetime metric; use the inert representation when you do not want the actual components of the metric appearing in the output

Decompose(%g_[mu, nu])

Matrix(%id = 18446744078724507998)

(2.2.6)

Note the position of the component %g_[0, 0], related to the trailing position of the time-like component in the signature "(- - - +)".

Compare the decomposition of the 4D inert with the decomposition of the 4D active spacetime metric

g[]

g[mu, nu] = (Matrix(4, 4, {(1, 1) = -1, (1, 2) = 0, (1, 3) = 0, (1, 4) = 0, (2, 1) = 0, (2, 2) = -1, (2, 3) = 0, (2, 4) = 0, (3, 1) = 0, (3, 2) = 0, (3, 3) = -1, (3, 4) = 0, (4, 1) = 0, (4, 2) = 0, (4, 3) = 0, (4, 4) = 1}))

(2.2.7)

Decompose(g_[mu, nu])

Matrix(%id = 18446744078724494270)

(2.2.8)

Note that in general the 3D space part of g[mu, nu] is not equal to the 3D metric gamma[i, j] whose definition includes another term (see [1] Landau & Lifshitz, eq.(84.7)).

gamma_[definition]

Physics:-gamma_[i, j] = -Physics:-g_[i, j]+Physics:-g_[0, i]*Physics:-g_[0, j]/Physics:-g_[0, 0]

(2.2.9)

The 3D space part of -g[`~mu`, `~nu`] is actually equal to the 3D metric "gamma[]^(i,j)"

"gamma_[~,definition];"

Physics:-gamma_[`~i`, `~j`] = -Physics:-g_[`~i`, `~j`]

(2.2.10)

To derive the formula  for the covariant components of the 3D metric, Decompose into 3+1 the identity

%g_[`~alpha`, `~mu`]*%g_[mu, beta] = KroneckerDelta[`~alpha`, beta]

%g_[`~alpha`, `~mu`]*%g_[mu, beta] = Physics:-KroneckerDelta[beta, `~alpha`]

(2.2.11)

To the side, for illustration purposes, these are the 3 + 1 decompositions, first excluding the repeated indices, then excluding the free indices

Eq := Decompose(%g_[`~alpha`, `~mu`]*%g_[mu, beta] = Physics[KroneckerDelta][beta, `~alpha`], repeatedindices = false)

Matrix(%id = 18446744078132963318)

(2.2.12)

Eq := Decompose(%g_[`~alpha`, `~mu`]*%g_[mu, beta] = Physics[KroneckerDelta][beta, `~alpha`], freeindices = false)

%g_[0, beta]*%g_[`~alpha`, `~0`]+%g_[i, beta]*%g_[`~alpha`, `~i`] = Physics:-KroneckerDelta[beta, `~alpha`]

(2.2.13)

Compare with a full decomposition

Eq := Decompose(%g_[`~alpha`, `~mu`]*%g_[mu, beta] = Physics[KroneckerDelta][beta, `~alpha`])

Matrix(%id = 18446744078724489454)

(2.2.14)

Eq is a symmetric matrix of equations involving non-contracted occurrences of `#msup(mi("g"),mrow(mn("0"),mo("&comma;"),mn("0")))`, `#msup(mi("g"),mrow(mi("j"),mo("&comma;"),mo("0")))` and `#msup(mi("g"),mrow(mi("j"),mo("&comma;"),mi("i")))`. Isolate, in Eq[1, 2], `#msup(mi("g"),mrow(mi("j"),mo("&comma;"),mo("0")))`, that you input as %g_[~j, ~0], and substitute into Eq[1, 1]

"isolate(Eq[1, 2], `%g_`[~j, ~0]);"

%g_[`~j`, `~0`] = -%g_[i, 0]*%g_[`~j`, `~i`]/%g_[0, 0]

(2.2.15)

subs(%g_[`~j`, `~0`] = -%g_[i, 0]*%g_[`~j`, `~i`]/%g_[0, 0], Eq[1, 1])

-%g_[0, k]*%g_[i, 0]*%g_[`~j`, `~i`]/%g_[0, 0]+%g_[i, k]*%g_[`~j`, `~i`] = Physics:-KroneckerDelta[k, `~j`]

(2.2.16)

Collect `#msup(mi("g"),mrow(mi("j"),mo("&comma;"),mi("i")))`, that you input as %g_[~j, ~i]

collect(-%g_[0, k]*%g_[i, 0]*%g_[`~j`, `~i`]/%g_[0, 0]+%g_[i, k]*%g_[`~j`, `~i`] = Physics[KroneckerDelta][k, `~j`], %g_[`~j`, `~i`])

(-%g_[0, k]*%g_[i, 0]/%g_[0, 0]+%g_[i, k])*%g_[`~j`, `~i`] = Physics:-KroneckerDelta[k, `~j`]

(2.2.17)

Since the right-hand side is the identity matrix and, from , `#msup(mi("g"),mrow(mi("i"),mo("&comma;"),mi("j")))` = -`#msup(mi("&gamma;",fontstyle = "normal"),mrow(mi("i"),mo("&comma;"),mi("j")))`, the expression between parenthesis, multiplied by -1, is the reciprocal of the contravariant 3D metric `#msup(mi("&gamma;",fontstyle = "normal"),mrow(mi("i"),mo("&comma;"),mi("j")))`, that is the covariant 3D metric gamma[i, j], in accordance to its definition for the signature `- - - +`

gamma_[definition]

Physics:-gamma_[i, j] = -Physics:-g_[i, j]+Physics:-g_[0, i]*Physics:-g_[0, j]/Physics:-g_[0, 0]

(2.2.18)

NULL

References

 
  

[1] Landau, L.D., and Lifshitz, E.M. The Classical Theory of Fields, Course of Theoretical Physics Volume 2, fourth revised English edition. Elsevier, 1975.

Example: Redefine

   

Tensors in Special and General Relativity

 

A number of relevant changes happened in the tensor routines of the Physics package, towards making the routines pack more functionality both for special and general relativity, as well as working more efficiently and naturally, based on Maple's Physics users' feedback collected during 2016.

New functionality

 
• 

Implement conversions to most of the tensors of general relativity (relevant in connection with functional differentiation)

• 

New setting in the Physics Setup  allows for specifying the cosmologicalconstant and a default tensorsimplifier


 

Download PhysicsMaple2017.mw

Edgardo S. Cheb-Terrab
Physics, Differential Equations and Mathematical Functions, Maplesoft

In this file you will be able to observe and analyze how the exercises and problems of Kinematics and Dynamics are solved using the commands and operators through a very well-structured syntax; Allowing me to save time and use it in interpretation. I hope you can share and spread to break the traditional and unnecessary myths. Only for Engineering and Science. Share if you like.

In Spanish.

Kinematics_using_syntax_in_Maple.mw

Lenin Araujo Castillo

Ambassador of Maple

   It’s that time of year again for the University of Waterloo’s Submarine Racing Team – international competitions for their WatSub are set to soon begin. With a new submarine design in place, they’re getting ready to suit up, dive in, and race against university teams from around the world.

 

   The WatSub team has come a long way from its roots in a 2014 engineering project. Growing to over 100 members, students have designed and redesigned their submarine in efforts to shave time off their race numbers while maintaining the required safety and performance standards. Their submarine – “Bolt,” as it’s named – was officially unveiled for the 2017 season on Thursday, June 1st.

 

 

   As the WatSub team says, "Everything is simple, until you go underwater."

 

 

    Designing a working submarine is no easy task, and that’s before you even think about all the details involved. Bolt needs to accommodate a pilot, be transported around the world, and cut through the water with speed, to name a few of the requirements if the WatSub team is to be a serious competitor.

 

    To help squeeze even more performance out of their design, the team has been using Maple to fine tune and optimize some of their most important structural components. At Maplesoft, we’ve been excited to maintain our sponsorship of the WatSub team as they continue to find new ways to push Bolt’s performance even further.

 

 

   The 2017 design unveiling on June 1st. After adding decals and final touches, Bolt will soon be ready to race.

 

   This year, the WatSub team has given their sub a whole new design, machining new body parts, optimizing the weight distribution of their gearbox, and installing a redesigned propeller system. Using Maple, they could go deep into design trade-offs early, and come away knowing the optimal gearbox design for their submarine.

 

   In just over a month, the WatSub team will take Bolt across the pond and compete in the European International Submarine Races (eISR). Many teams competing have been in existence for well over a decade, but the leaps and strides taken by the WatSub team have made them a serious competitor for this year.

  Best of luck to the WatSub team and their submarine, Bolt – we’re all rooting for you!

With this application the components of the acceleration can be calculated. The components of the acceleration in scalar and vector of the tangent and the normal. In addition to the curvilinear kinetics in polar coordinates. It can be used in different engineers, especially mechanics, civilians and more.

In Spanish.

Kinematics_Curvilinear v18.mw

Kinematics_Curvilinear_updated_v2017.mw

Cinemática_en_Coordenadas_Polares_Cilindricas.mw

Kinematics_Curvilinear_updated_v2018.mw

Cinemática_de_una_partícula_nueva_sintaxis.mw

Lenin Araujo Castillo

Ambassador of Maple

 

 

Meta Keijzer-de Ruijter is a Project Manager for Digital Testing at TU Delft, an institution that is at the forefront of the digital revolution in academic institutions. Meta has been using Maple T.A. for years, and offered to provide her insight on the role that automated testing & assessment played in improving student pass rates at TU Delft.

 

Modern technology is transforming many aspects of the world we live in, including education. At TU Delft in the Netherlands, we have taken a leadership role in transforming learning through the use of technology. Our ambition is to get to a point where we are offering fully digitalized degree programs and we believe digital testing and assessment can play an important role in this process.

 

A few years ago we launched a project with the goal of using digital testing to drastically improve the pass rates in our programs. Digital testing helps organize testing more efficiently for a larger number of students, addressing issues of overcrowded classrooms, and high teaching workloads. To better facilitate this transformation, we decided to adopt Maple T.A., the online testing and assessment suite from Maplesoft. Maple T.A. also provides anytime/anywhere testing, allowing students to take tests digitally, even from remote locations.

 

Regular and repeated testing produces the best learning results because progressive monitoring offers instructors the possibility of making adjustments throughout the course. The randomization feature in Maple T.A. provides each student with an individual set of problems, reducing the likelihood that answers will be copied. Though Maple T.A. is specialized in mathematics, it also supports more common question types like multiple choice, multiple selection, fill-in-the-blanks and hot spot. Maple T.A.’s question randomization, possibilities for multiple response fields per question and question workflow (adaptive questions) are superior to other options. By offering regular homework assignments and analyzing the results, we gain better insight into the progress of students and the topics that students perceive as difficult. Our lecturers can use this insight to decide whether to repeat particular material or to offer it in another manner. In many courses, preparing and reviewing practice tests comprise an important, yet time-consuming task for lecturers, and Maple T.A. alleviates that burden.

 

At TU Delft, we require all first-year students to take a math entry test using Maple T.A in order to assess the required level of math. Since the assessment of the student’s ability is so heavily dependent upon qualifying tests, it is extremely important for the test to be completed under controlled conditions. In Maple T.A., it is easy to generate multiple versions of the test questions without increasing the burden of review, as the tests are graded immediately. Students that fail the entry test are offered a remedial course in which they receive explanations and complete exercises, under the supervision of student assistants. The use of Maple T.A. facilitates this process without placing additional burden on the teacher. When the practice tests and the associated feedback are placed in a shared item bank in Maple T.A., teachers are able to offer additional practice materials to students with little effort. It makes it considerably easier on us as teachers to be able to use a variety of question types, thus creating a varied test.

 

Each semester, TU Delft offers an English placement test that is taken by approximately 200 students and 50 PhD candidates, in which students are required to formulate their reasons for their program choices or research topics. It used to take four lecturers working full-time for two days to mark the tests and report the results to participants in a timely manner. The digitization of this test has saved us considerable time. The hundred fill-in-the-blank questions are now marked automatically, and we no longer have to decipher handwriting for the open questions!

 

TU Delft is not alone in its emphasis on digital testing; it has a prominent position on the agendas of many institutions in Europe and elsewhere. These institutions are intensively involved in improving, expanding and advocating the positive results from digital testing and digital learning experiences. Online education solutions like Maple T.A. are playing a key role in improving the quality of digital offerings at institutions.

In the recent years much software has undergone a change towards allowing for better sharing of documents. As is the case with other software as well, the users are no longer mainly single persons sitting in a dark corner doing their own stuff. Luckily Maplesoft has taken an important step in that direction too by introducing MapleCloud some years ago. This means that it is now possible quite easily to discuss calculations done in Maple in the classroom. One student uploads and the Teacher can find the document seconds later on his own computer connected to a Projector and show the student's solutions for the other  students in the classroom. That's indeed great! Maple is however lacking in one important aspect: It's Graphics User Interface (GUI) is not completely ready to for that challenge! I noticed that quite recently when the entire teaching staff received new netbooks: 14 inch Lenovo Yoga X1 with a resolution of 2560 x 1440 pixels. From factory defaults text zoom was set to 200%. Without it, text would be too small in all applications used on the computer. The Microsoft Office package and most other software has adapted to this new situation dealing with high variation in the users screen resolutions, but not Maplesoft:

  1. Plots and Images inserted become very small
  2. Open File dialogs and the like contain shortened text for folder names ... (you actually have to guess what the folders are)
  3. Help menus are cluttered up and difficult to read.

I show screen images of all three types below.

I know it is possible to make plots larger by using the option size, but since it relies on pixels it doesn't work when documents are shared between students and teachers. You cannot expect the receiving student/teacher to make a lot of changes in the document just to be able to read it. It will completely destroy the workflow!

Why doesn't Maplesoft allow for letting documents display proportionally on the users computer like so many other programs do? Why do it need to be in pixels? If it is possible to make it proportional, it would also solve another issue: Making prints (to a printer or to pdf) look more like they do on the screen than is the case at present.

I really hope Maplesoft will address this GUI challenge, because I am sure the issue will pile up quite rapidly. Due to higher costs, most laptops/netbooks among students don't have that high resolution compared to computer dimensions at the moment, but we already have received a few remarks from students owning such computers. Very soon those highend solution computers will dive into the consumer market and become very common.

I have mentioned this important GUI issue in the beta-testing group, but I don't think those groups really are adapted to discussions, more bug fixes. Therefore I have made this Post in the hope that some Maple users and some chief developers will comment on it!
     

Now I have criticized the Maple GUI, I also feel urged to tell in what departments I think Maple really excels:

  1. The Document-structure is great. One can produce good looking documents containing 'written math' (inactive math) and/or 'calculated math'. All-in-one! Other competting software does need one to handle things separatly.
  2. Sections and subsections. We have actually started using Maple to create documents containing entire chapters or surveys of mathematics or physics subjects, helping students to get a better overview. I am pretty sure the Workbook tool also will help here.
  3. Calculations are all connected. One can recalculate the document or parts of it, eventually using new parameters. Using Maple for performing matematical experiments. Mathematical experiments is a method entering more into the different mathematics curriculums.
  4. MapleCloud. Easy sharing of documents among students and teachers.
  5. Interactive possibilities through the Explore command and other commands. Math Apps as well.
  6. Besides that mathematical symbols can be accessed from the keyboard, they can also be accessed from palettes by less experinced users.  
  7. Good choice by Maple to let the user globally decide the size text and math is displayed in Maple - set globally in the menu Tools < Options.
  8. Maple can handle units in Physics
  9. Maple has World-Class capabilities. If you have a mathematical problem, Maple can probably handle it. You just need to figure out how.
  10. etc.

 

Small plots:

 

Shortened dialog text:

 

Cluttered help menus:

 

Regards,

Erik

 

This worksheet is designed to develop engineering exercises with Maple applications. You should know the theory before using these applications. It is designed to solve problems faster. I hope you use something that is fully developed with embedded components.

In Spanish

Vector_Force.mw

Vector_Force_updated.mw

Lenin Araujo Castillo

Ambassador Of Maple

 

 

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