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Matrix Multiplication in C HINDI
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C++ Tutorial in Hindi – Arrays: Matrices operation – Addition, Subtraction and Product of Two Matrices with C++ Coding Example
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Write a computer program which declares a one dimensional integer array of 10 elements and initialize that array with 0. After initialization it inputs the value in each element of an array from user calculate product of all elements of an array and then displays all the elements of array and their product.
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Green Star Pixels

Showing that matrix products are associative
Watch the next lesson: https://www.khanacademy.org/math/linear-algebra/matrix_transformations/composition_of_transformations/v/distributive-property-of-matrix-products?utm_source=YT&utm_medium=Desc&utm_campaign=LinearAlgebra
Missed the previous lesson?
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Linear Algebra on Khan Academy: Have you ever wondered what the difference is between speed and velocity? Ever try to visualize in four dimensions or six or seven? Linear algebra describes things in two dimensions, but many of the concepts can be extended into three, four or more. Linear algebra implies two dimensional reasoning, however, the concepts covered in linear algebra provide the basis for multi-dimensional representations of mathematical reasoning. Matrices, vectors, vector spaces, transformations, eigenvectors/values all help us to visualize and understand multi dimensional concepts. This is an advanced course normally taken by science or engineering majors after taking at least two semesters of calculus (although calculus really isn't a prereq) so don't confuse this with regular high school algebra.
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Khan Academy

Operations Management Lecture Series, by Dr. Narendar Sumukadas
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Narendar Sumukadas

Kronecker Product of two matrices in image processing.
AXB is not equal to BXA.
.........................................................
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Shrenik Jain

Vector Cross Products are a big thing in Calculus 3, but they can be tedious to calculate due to all the repetitive arithmetic. So I’ve made a program to calculate a cross product for you or use to check an answer. You can easily expand it to use for the Triple Scalar Product of 3 vectors.
Download the program http://www.mediafire.com/download/vrj42rkepyqb61c/A2CROSS.8xp
➤Dot products are simple:
-2nd STAT
-Left arrow to "MATH"
-option 5 is sum(
-type your 2 vectors in curly braces separated by commas
-sum( {1,2,3}{3,4,5}
-Press Enter & you’ve got the answer
➤Cross Products program:
Input "{A,B,C}=",L3
Input "{D,E,F}=",L4
Disp "AXB=",{L3(2)L4(3)-L3(3)L4(2),L3(3)L4(1)-L3(1)L4(3),L3(1)L4(2)-L3(2)L4(1)}
You could paste these 3 lines into the cemetech editor and create your own program https://www.cemetech.net/sc/
➤When running the program you must enter the vectors in curly braces (the last one is optional)
-So when it prompts "{A,B,C}=" you enter "{1,2,3"
The program’s answer is a list NOT an actual vector (e.g. {2 4 5}
(Notice no commas)
If you need to use it as a vector, copy it manually
➤Scalar Triple Product:
-is defined by a•(bXc) or b•(aXc)
-so do a cross product first
-then dot product that answer with the third vector
Cross Product Definition http://www.mathportal.org/linear-algebra/vectors/cross-product.php
Slightly Modified source https://answers.yahoo.com/question/index?qid=20110207191241AAOr0XA

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TanUv90

This video explains how to write a matrix as a product of elementary matrices.
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Mathispower4u

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alpinehomeair

Taking the transpose of the product of two matrices
Watch the next lesson: https://www.khanacademy.org/math/linear-algebra/matrix_transformations/matrix_transpose/v/linear-algebra-transposes-of-sums-and-inverses?utm_source=YT&utm_medium=Desc&utm_campaign=LinearAlgebra
Missed the previous lesson?
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Linear Algebra on Khan Academy: Have you ever wondered what the difference is between speed and velocity? Ever try to visualize in four dimensions or six or seven? Linear algebra describes things in two dimensions, but many of the concepts can be extended into three, four or more. Linear algebra implies two dimensional reasoning, however, the concepts covered in linear algebra provide the basis for multi-dimensional representations of mathematical reasoning. Matrices, vectors, vector spaces, transformations, eigenvectors/values all help us to visualize and understand multi dimensional concepts. This is an advanced course normally taken by science or engineering majors after taking at least two semesters of calculus (although calculus really isn't a prereq) so don't confuse this with regular high school algebra.
About Khan Academy: Khan Academy offers practice exercises, instructional videos, and a personalized learning dashboard that empower learners to study at their own pace in and outside of the classroom. We tackle math, science, computer programming, history, art history, economics, and more. Our math missions guide learners from kindergarten to calculus using state-of-the-art, adaptive technology that identifies strengths and learning gaps. We've also partnered with institutions like NASA, The Museum of Modern Art, The California Academy of Sciences, and MIT to offer specialized content.
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Khan Academy

Discrete structureshttps://www.youtube.com/playlist?list=PLJo7y1Pu7hNgAX52SDIYrVprQxfXRAacs

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Random Tutorial

In this video, we explore the associative property for matrix multiplication. We continue with our Fruit Store example. This time, we find the total wholesale cost of selling all of the fruit packages for the months of July, August and September.
We start with a table of the wholesale cost of each fruit item, which we write as a column matrix.
We find that the cost matrix C, which describes the wholesale cost for each month is the product of:
C = M x P x W
But for associativity, we discover that it doesn't matter how we group this operation, as long as we keep the order of the matrices in the same. So:
C = (M x P) x W
Or
C = M x (P x W)
Thanks for watching. Please give me a "thumbs up" if you have found this video helpful.
Please ask me a maths question by commenting below and I will try to help you in future videos.
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MasterWuMathematics

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Patrick Hood-Daniel

Today;s Topic is :- Product of Matrix class -7 | Business Mathematics | Excercise solved | By free ki pathshala
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Matrices and determinant :- https://www.youtube.com/watch?v=WNH9XsVMGrI&list=PLGeio_2Vs0yg3kpGzkCsqaBASuNBa477b
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INTRODUCTION OF GST :-
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Matrices shortcuts and tricks
Multiplication of matrices
tricks to multiply matrices
matrix multiplication
Class 11 matrices
class 12 matrices
Matrices multiplication inverse 3x3 2x2 3x2
Unit II: Algebra
1. Matrices
Concept, notation, order, equality, types of matrices, zero and identity matrix, transpose of a matrix, symmetric and skew symmetric matrices. Operation on matrices: Addition and multiplication and multiplication with a scalar. Simple properties of addition, multiplication and scalar multiplication. Noncommutativity of multiplication of matrices and existence of non-zero matrices whose product is the zero matrix (restrict to square matrices of order 2).Concept of elementary row and column operations. Invertible matrices and proof of the uniqueness of inverse, if it exists;
2. Determinants
Determinant of a square matrix (up to 3 x 3 matrices), properties of determinants, minors, co-factors and applications of determinants in finding the area of a triangle. Adjoint and inverse of a square matrix. Consistency, inconsistency and number of solutions of system of linear equations by examples, solving system of linear equations in two or three variables (having unique solution) using inverse of a matrix.
Introduction and Examples
DEFINITION: A matrix is defined as an ordered rectangular array of numbers. They can be used to represent systems of linear equations, as will be explained below.
Here are a couple of examples of different types of matrices:
Symmetric Diagonal Upper Triangular Lower Triangular Zero Identity
Symmetric Matix Diagonal Matrix Upper Triangular Matix Lower Triangular Matix Zero Matix Identity Matix
And a fully expanded m×n matrix A, would look like this:
n×n matrix
... or in a more compact form: m×n simplified
Top
Matrix Addition and Subtraction
DEFINITION: Two matrices A and B can be added or subtracted if and only if their dimensions are the same (i.e. both matrices have the same number of rows and columns. Take:
matrices A&B
Addition
If A and B above are matrices of the same type then the sum is found by adding the corresponding elements aij + bij .
Here is an example of adding A and B together.
Sum of matrices A&B
Subtraction
If A and B are matrices of the same type then the subtraction is found by subtracting the corresponding elements aij − bij.
Here is an example of subtracting matrices.
Subtraction of A&B
Now, try adding and subtracting your own matrices.
Addition/subtraction Top
Matrix Multiplication
DEFINITION: When the number of columns of the first matrix is the same as the number of rows in the second matrix then matrix multiplication can be performed.
Here is an example of matrix multiplication for two 2×2 matrices.
Matrix multiplication 2×2
Here is an example of matrix multiplication for two 3×3 matrices.
Matrix multiplication 3×3
Now lets look at the n×n matrix case, Where A has dimensions m×n, B has dimensions n×p. Then the product of A and B is the matrix C, which has dimensions m×p. The ijth element of matrix C is found by multiplying the entries of the ith row of A with the corresponding entries in the jth column of B and summing the n terms. The elements of C are:
Matrix multiplication for n×n
Note: That A×B is not the same as B×A
Now, try multiplying your own matrices.
Matrix multiplication Top
Transpose of Matrices
DEFINITION: The transpose of a matrix is found by exchanging rows for columns i.e. Matrix A = (aij) and the transpose of A is:
AT = (aji) where j is the column number and i is the row number of matrix A.
For example, the transpose of a matrix would be:
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Free Ki Pathshala

Multiplying two 2x2 matrices.
Practice this yourself on Khan Academy right now: https://www.khanacademy.org/e/multiplying_a_matrix_by_a_matrix?utm_source=YTdescription&utm_medium=YTdescription&utm_campaign=YTdescription

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Khan Academy

This course is on Lemma: http://lem.ma Lemma looking for developers: http://lem.ma/jobs
Other than http://lem.ma, I recommend Strang http://bit.ly/StrangYT, Gelfand http://bit.ly/GelfandYT, and my short book of essays http://bit.ly/HALAYT
Questions and comments below will be promptly addressed.
Linear Algebra is one of the most important subjects in mathematics. It is a subject with boundless practical and conceptual applications.
Linear Algebra is the fabric by which the worlds of geometry and algebra are united at the most profound level and through which these two mathematical worlds make each other far more powerful than they ever were individually.
Virtually all subsequent subjects, including applied mathematics, physics, and all forms of engineering, are deeply rooted in Linear Algebra and cannot be understood without a thorough understanding of Linear Algebra. Linear Algebra provides the framework and the language for expressing the most fundamental relationships in virtually all subjects.
This collection of videos is meant as a stand along self-contained course. There are no prerequisites. Our focus is on depth, understanding and applications. Our innovative approach emphasizes the geometric and algorithmic perspective and was designed to be fun and accessible for learners of all levels.
Numerous exercises will be provided via the Lemma system (under development)
We will cover the following topics:
Vectors
Linear combinations
Decomposition
Linear independence
Null space
Span
Linear systems
Gaussian elimination
Matrix multiplication and matrix algebra
The inverse of a matrix
Elementary matrices
LU decomposition
LDU decomposition
Linear transformations
Determinants
Cofactors
Eigenvalues
Eigenvectors
Eigenvalue decomposition (also known as the spectral decomposition)
Inner product (also known as the scalar product and dot product)
Self-adjoint matrices
Symmetric matrices
Positive definite matrices
Cholesky decomposition
Gram-Schmidt orthogonalization
QR decomposition
Elements of numerical linear algebra
I’m Pavel Grinfeld. I’m an applied mathematician. I study problems in differential geometry, particularly with moving surfaces.

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MathTheBeautiful

Thanks to all of you who support me on Patreon. You da real mvps! $1 per month helps!! :) https://www.patreon.com/patrickjmt !! In this video, I give the formula for the cross product of two vectors, discuss geometrically what the cross product is, and do an example of finding the cross product.
For more free math videos, visit http://PatrickJMT.com

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patrickJMT

C++ Program to calculate Product of two Matrices
Hello! I am vaibhav sharma.
Plz subscibe to my Channel
Write down in the comment section that which type of question you want me to code.

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PROG TECH IS A CHANNEL ALL ABOUT
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Prog Tech

Motivation for the definition of matrix multiplication. Alternative ways of thinking about matrix multiplication.

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Sheldon Axler

Coding interview question from http://www.byte-by-byte.com/matrixproduct
In this video, I show how to find the path through a matrix with the greatest product.
Do you have a big interview coming up with Google or Facebook? Do you want to ace your coding interviews once and for all? If so, Byte by Byte has everything that you need to go to get your dream job. We've helped thousands of students improve their interviewing and we can help you too.
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Byte By Byte

Inverse of 3x3 matrix example. Visit http://Mathmeeting.com to see all all video tutorials covering the inverse of a 3x3 matrix.

Views: 1570604
Math Meeting

Let's consider a three-dimensional square matrices and apply exactly the same logic as in a 2-dimensional case of the previous lecture.
If
matrix A=[aij], i,j ∈ [1,2,3]
matrix B=[bij], i,j ∈ [1,2,3]
matrix C=A·B=[cij],
i,j ∈ [1,2,3]
vector u=(u1,u2,u3)
vector v=B·u=(v1,v2,v3)
vector w=A·v=A·(B·u)=(w1,w2,w3)
then:
(1) the transformation v=B·u looks like
v1 = b11·u1+b12·u2+b13·u3
v2 = b21·u1+b22·u2+b23·u3
v3 = b31·u1+b32·u2+b33·u3
(2) the transformation w=A·v looks like
w1 = a11·v1+a12·v2+a13·v3 =
= a11·(b11·u1+b12·u2+b13·u3) +
+ a12·(b21·u1+b22·u2+b23·u3) +
+ a13·(b31·u1+b32·u2+b33·u3) =
= (a11·b11+a12·b21+a13·b31)·u1 +
+ (a11·b12+a12·b22+a13·b32)·u2 +
+ (a11·b13+a12·b23+a13·b33)·u3
w2 = a21·v1+a22·v2+a23·v3 =
= a21·(b11·u1+b12·u2+b13·u3) +
+ a22·(b21·u1+b22·u2+b23·u3) +
+ a23·(b31·u1+b32·u2+b33·u3) =
= (a21·b11+a22·b21+a23·b31)·u1 +
+ (a21·b12+a22·b22+a23·b32)·u2 +
+ (a21·b13+a22·b23+a23·b33)·u3
w3 = a31·v1+a32·v2+a33·v3 =
= a31·(b11·u1+b12·u2+b13·u3) +
+ a32·(b21·u1+b22·u2+b23·u3) +
+ a33·(b31·u1+b32·u2+b33·u3) =
= (a31·b11+a32·b21+a33·b31)·u1 +
+ (a31·b12+a32·b22+a33·b32)·u2 +
+ (a31·b13+a32·b23+a33·b33)·u3
Since we want to define a matrix product C=A·B=[cij] to perform the same transformation as a composition of, first, B and then A, as derived above, the same vector w should result from a multiplication of matrix C by vector u, that is
w1 = c11·u1+c12·u2+c13·u3
w2 = c21·u1+c22·u2+c23·u3
w3 = c31·u1+c32·u2+c33·u3
Comparing this with the derivation above, we conclude:
c11 = a11·b11+a12·b21+a13·b31
c12 = a11·b12+a12·b22+a13·b32
c13 = a11·b13+a12·b23+a13·b33
c21 = a21·b11+a22·b21+a23·b31
c22 = a21·b12+a22·b22+a23·b32
c23 = a21·b13+a22·b23+a23·b33
c31 = a31·b11+a32·b21+a33·b31
c32 = a31·b12+a32·b22+a33·b32
c33 = a31·b13+a32·b23+a33·b33
The above is a definition of a product of two 3x3 matrices C=A·B that satisfies our requirement of representing a transformation C equivalent to a composition of transformations of these two matrices, first, B and then A.
As you see, we have derived this definition based on a reasonable assumption about its properties.
Exactly as in a case of two 2x2 matrices, looking at these expressions above, we can notice that the ij-th element of matrix C is a scalar product of two vectors: i-th row-vector of matrix A, denoted as Ai or ai*=(ai1,ai2,ai3), and j-th column-vector of matrix B, denoted as B j or b*j=(b1j,b2j,b3j).

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VID.education

Find Complete Code at GeeksforGeeks Article: https://www.geeksforgeeks.org/closest-product-pair-array/
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Views: 3622
Prasad Senesi

To ask Unlimited Maths doubts download Doubtnut from - https://goo.gl/9WZjCW If the product of the matrix `B=[(2,6,4),(1,0,1),(-1,1,-1)]` with a matrix A has inverse `C=[(-1,0,1),(1,1,3),(2,0,2)]` then `A^-1=`

Views: 0
Doubtnut

Product(multiplication) of digits of any given number by user based on C language.
please like and subscribe our channel. for free pdf books please visit on my site
http://www.books4learn.yolasite.com

Views: 51
source zone

A shortcut for having to evaluate the cross product of three vectors
Watch the next lesson: https://www.khanacademy.org/math/linear-algebra/vectors_and_spaces/dot_cross_products/v/normal-vector-from-plane-equation?utm_source=YT&utm_medium=Desc&utm_campaign=LinearAlgebra
Missed the previous lesson?
https://www.khanacademy.org/math/linear-algebra/vectors_and_spaces/dot_cross_products/v/dot-and-cross-product-comparison-intuition?utm_source=YT&utm_medium=Desc&utm_campaign=LinearAlgebra
Linear Algebra on Khan Academy: Have you ever wondered what the difference is between speed and velocity? Ever try to visualize in four dimensions or six or seven? Linear algebra describes things in two dimensions, but many of the concepts can be extended into three, four or more. Linear algebra implies two dimensional reasoning, however, the concepts covered in linear algebra provide the basis for multi-dimensional representations of mathematical reasoning. Matrices, vectors, vector spaces, transformations, eigenvectors/values all help us to visualize and understand multi dimensional concepts. This is an advanced course normally taken by science or engineering majors after taking at least two semesters of calculus (although calculus really isn't a prereq) so don't confuse this with regular high school algebra.
About Khan Academy: Khan Academy offers practice exercises, instructional videos, and a personalized learning dashboard that empower learners to study at their own pace in and outside of the classroom. We tackle math, science, computer programming, history, art history, economics, and more. Our math missions guide learners from kindergarten to calculus using state-of-the-art, adaptive technology that identifies strengths and learning gaps. We've also partnered with institutions like NASA, The Museum of Modern Art, The California Academy of Sciences, and MIT to offer specialized content.
For free. For everyone. Forever. #YouCanLearnAnything
Subscribe to KhanAcademy’s Linear Algebra channel:: https://www.youtube.com/channel/UCGYSKl6e3HM0PP7QR35Crug?sub_confirmation=1
Subscribe to KhanAcademy: https://www.youtube.com/subscription_center?add_user=khanacademy

Views: 167312
Khan Academy

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About : Intellectual Indies is a YouTube Channel, Intellectual Indies is all about improving Mentally, Emotionally, Psychologically, Spiritually & Physically. #Marketing #Marketing101 #GrowBusiness

Views: 15188
Intellectual Indies

This video explains what is meant by the covariance and correlation between two random variables, providing some intuition for their respective mathematical formulations. Check out https://ben-lambert.com/econometrics-course-problem-sets-and-data/ for course materials, and information regarding updates on each of the courses. Quite excitingly (for me at least), I am about to publish a whole series of new videos on Bayesian statistics on youtube. See here for information: https://ben-lambert.com/bayesian/ Accompanying this series, there will be a book: https://www.amazon.co.uk/gp/product/1473916364/ref=pe_3140701_247401851_em_1p_0_ti

Views: 235482
Ben Lambert

Based on pages 7 to 9 of my notes. Inner product for n-tuples over K=R,C, H are described using appropriate conjugations. Also, the isometries of these standard inner products naturally give rise to On(K) which produces at once the seemingly distinct matrix groups O(n) over R, U(n) over C and Sp(n) over H; that is orthogonal, unitary and symplectic matrices

Views: 253
James Cook

Definitions of the vector dot product and vector length
Watch the next lesson: https://www.khanacademy.org/math/linear-algebra/vectors_and_spaces/dot_cross_products/v/proving-vector-dot-product-properties?utm_source=YT&utm_medium=Desc&utm_campaign=LinearAlgebra
Missed the previous lesson?
https://www.khanacademy.org/math/linear-algebra/vectors_and_spaces/subspace_basis/v/linear-algebra-basis-of-a-subspace?utm_source=YT&utm_medium=Desc&utm_campaign=LinearAlgebra
Linear Algebra on Khan Academy: Have you ever wondered what the difference is between speed and velocity? Ever try to visualize in four dimensions or six or seven? Linear algebra describes things in two dimensions, but many of the concepts can be extended into three, four or more. Linear algebra implies two dimensional reasoning, however, the concepts covered in linear algebra provide the basis for multi-dimensional representations of mathematical reasoning. Matrices, vectors, vector spaces, transformations, eigenvectors/values all help us to visualize and understand multi dimensional concepts. This is an advanced course normally taken by science or engineering majors after taking at least two semesters of calculus (although calculus really isn't a prereq) so don't confuse this with regular high school algebra.
About Khan Academy: Khan Academy offers practice exercises, instructional videos, and a personalized learning dashboard that empower learners to study at their own pace in and outside of the classroom. We tackle math, science, computer programming, history, art history, economics, and more. Our math missions guide learners from kindergarten to calculus using state-of-the-art, adaptive technology that identifies strengths and learning gaps. We've also partnered with institutions like NASA, The Museum of Modern Art, The California Academy of Sciences, and MIT to offer specialized content.
For free. For everyone. Forever. #YouCanLearnAnything
Subscribe to KhanAcademy’s Linear Algebra channel:: https://www.youtube.com/channel/UCGYSKl6e3HM0PP7QR35Crug?sub_confirmation=1
Subscribe to KhanAcademy: https://www.youtube.com/subscription_center?add_user=khanacademy

Views: 640312
Khan Academy

Quantum tensor network states provide a natural framework for the representation of ground states of gapped, topologically ordered systems. From the technological point of view, such systems could be instrumental in creating fault tolerant architectures for quantum computation. From the theoretical point of view, such systems are fascinating due to the fact that all the relevant physics is encoded in the entanglement structure of the corresponding many body wavefunction. This is captured in the tensor network framework by a matrix product operator symmetry of the underlying tensors. In our work we present a systematic study of those matrix product operators, and show how this relates entanglement properties of projected entangled-pair states to the formalism of fusion tensor categories. From the matrix product operators we construct a C*-algebra and find that emergent topological superselection sectors can be identified with the central idempotents of this algebra. This allows us to construct projected entangled-pair states containing an arbitrary number of anyons. Physical properties such as topological spin, the S matrix, fusion and braiding relations are readily extracted from the idempotents. As the matrix product operator symmetries are acting purely on the virtual level of the tensor network, the ensuing Wilson loops are not fattened when perturbing the system. This opens up the possibility of simulating topological theories away from commuting projector fixed point Hamiltonians and studying topological phase transitions due to anyon condensation. We explicitly describe how discrete gauge theories and string-net models fit into the general formalism. Our approach leads to a new description of topological quantum computation where the relevant information is carried by virtual degrees of freedom in a tensor network, reminiscent of the PEPS description of measurement-based quantum computation.

Views: 340
Microsoft Research

Introduction to Linear Algebra
Strang 4th edition
2-5-12
If the product C = A B is invertible (A and B are square), then A itself is invertible. Find a formula for A-I that involves C-1 and B

Views: 335
Marx Academy

Continuing our series of videos on the ISMM Diploma in Sales and Marketing, this webcast looks at Unit U502, in particular at the Boston Consulting Group Matrix and the Product Life Cycle.
Both of these models are useful when analysing marketing communications and product portfolios.

Views: 3740
LAMMORE

Watch the latest from New Venture Mentor: "How to Beat Your Bigger Competitors in Attracting and Retaining Top Talent"
https://www.youtube.com/watch?v=b4OD44N7a6k --~--
This video gives a brief description of the Boston Consulting Group (BCG) Matrix method of analyzing various product lines within a business.

Views: 61631
Cate Costa

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Views: 4741
Suzanne Beauty Shaman

eigenvalues of a product of matrices, characteristics polynomial of A.B and B.A,

Views: 7185
Gurukul Institute of Mathematics

Writing the Euclidean inner product in the form of matrix multiplication.

Views: 1499
Juan Klopper

© 2018 Victoria secret paris shop

For towns, each building is described, along with what and who can you can talk to, who to buy skills from, and what quests are available. For the outlying areas, the dungeons are listed. Dungeon maps are not given -- they would be too extensive to fit easily into a web page and the automapping in the game is excellent. Also, every dungeon should be explored completely to get all of the loot, but only puzzles and hidden locations are described. I also skip most of the fighting because it isnt something that you can easily describe, nor does it matter in most places, except that you have to survive it. I do list the creatures that you will encounter in a dungeon or grid location to give you an idea of how difficult the location is. Stores are listed with a "buy" and "sell". The "buy" value is multiplied by the items value to determine the price you have to pay for it. The "sell" value is divided by the items value to determine the price you can sell it to the store for. Higher is always worse, and a "buy" or "sell" of 1 means that you are buying/selling an item at cost. Every location has a "reset" timer. This starts when you first enter the area, and after it "goes off", the entire grid square resets: monsters reappear and random treasure is replaced. Nonrandom treasure (including most stat-gaining liquids) is not replaced. All dungeons have a reset of 2 years (24 months), unless otherwise noted. Overland areas have reset times listed with their descriptions. Artifacts are unique items that can be found. They come in two flavors: Minor artifacts are always benificial and have a value of 20000gp. Major artifacts always have a drawback, but their benificial powers are much stronger. They have a value of 30000gp. There are 15 minor and 15 major artifacts -- some of these artifacts are placed at specific locations; others are randomly generated. Table of Contents.