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Summary
- Row-echelon form A matrix is in row-echelon form if
- all zero rows (if any) are at the bottom of the matrix and
- if two successive rows are non-zero, the second row starts with more zeros than the first (moving from left to right).
- Example 1 (row-echelon form)
\begin{bmatrix}0 & 1 & 0 & 0 \\ 0 & 0 & 1 & 0 \\ 0 & 0 & 0 & 0 \\ 0 & 0 & 0 & 0 \end{bmatrix} - Example 2 (not row-echelon form)
\begin{bmatrix}0 & 1 & 0 & 0\\ 0 & 1 & 0 & 0\\ 0 & 0 & 0 & 0 \\ 0 & 0 & 0 & 0 \end{bmatrix}
A matrix is in reduced row-echelon form if
- it is in row-echelon form,
- the leading (leftmost non-zero) entry in each non-zero row is 1,
- all other elements of the column in which the leading entry 1 occurs are zeros.
- Example 1 (reduced row-echelon form)
\begin{bmatrix}1 & 0\\ 0 & 1 \end{bmatrix} - Example 2 (reduced row-echelon form)
\begin{bmatrix}0 & 1 & 2 & 0 & 0 & 2\\ 0 & 0 & 0 & 1 & 0 & 3\\ 0 & 0 & 0 & 0 & 1 & 4\\ 0 & 0 & 0 & 0 & 0 & 0 \end{bmatrix} - Example 3 (not reduced row-echelon form)
\begin{bmatrix}1 & 0 & 0\\ 0 & 1 & 0\\ 0 & 0 & 2 \end{bmatrix} - Example 4 (not reduced row-echelon form)
\begin{bmatrix}1 & 2 & 0\\ 0 & 1 & 0\\ 0 & 0 & 0 \end{bmatrix}
These types of elementary row operations can be performed on matrices:
- Interchanging two rows: R_i\leftrightarrow R_j interchanges rows i and j.
- Multiplying a row by a non-zero scalar: R_i\rightarrow tR_j multiplies row i by the non-zero scalar t.
- Adding a multiple of one row to another row: R_j\rightarrow R_j+tR_i adds t times row i to row j.
Matrix A is row-equivalence to matrix B if B is obtained from A by a sequence of elementary row operations.
The Gauss-Jordan algorithm is a process which starts with a given matrix A and produces a matrix B in reduced row-echelon form, which is row-equivalent to A.
If A is the augmented matrix of a system of linear equations, then B will be a much simpler matrix than A from which the consistency or inconsistency of the corresponding system is immediately apparent and in fact the complete solution of the system can be read off.
A field F is a set F which possesses operations of addition and multiplication which satisfy the familiar rules of rational arithmetic.\\ There are ten basic properties that a field must have:
- (a+b)+c=a+(b+c) for all a, b, c in F;
- (ab)c=a(bc) for all a, b, c in F;
- a+b=b+a for all a, b in F;
- ab=ba for all a, b in F;
- there exists an element 0 in F such that 0+a=a for all a in F;
- there exists an element 1 in F such that 1a=a for all a in F;
- to every a in F, there corresponds an additive inverse -a in F, satisfying a+(-a)=0;
- to every non-zero a in F, there corresponds a multiplication inverse a^{-1} in F, satisfying aa^{-1}=1;
- a(b+c)=ab+ac for all a, b, c in F;
- 0\neq1
- \mathbb{Z}_p field contains exactly p elements, where p is a prime number. That is, \mathbb{Z}_p=\left\{0, 1, \cdots, p-1\right\}.
- Note that \mathbb{Z}_p forms a field under the operations of modular addition and multiplication mod p.
- For instance, the simplest \mathbb{Z}_2 field consists of two elements 0 and 1, and we have 1+1=0\Rightarrow 1=-1.
Problems 1.6 1. Which of the following matrices of rationals is in reduced row-echelon form? (a) \begin{bmatrix}1 & 0 & 0 & 0 & -3\\ 0 & 0 & 1 & 0 & 4\\ 0 & 0 & 0 & 1 & 2 \end{bmatrix} (b) \begin{bmatrix}0& 1& 0& 0& 5\\ 0& 0& 1& 0& -4\\ 0& 0& 0& -1& 3 \end{bmatrix} (c) \begin{bmatrix}0& 1& 0& 0\\ 0& 0& 1& 0\\ 0& 1& 0& -2 \end{bmatrix} (d) \begin{bmatrix}0& 1& 0& 0& 2\\ 0& 0& 0& 0& -1\\ 0& 0& 0& 1& 4\\ 0& 0& 0& 0& 0 \end{bmatrix} (e) \begin{bmatrix}1& 2& 0& 0& 0\\ 0& 0& 1& 0& 0\\ 0& 0& 0& 0& 1\\ 0& 0& 0& 0& 0 \end{bmatrix} (f) \begin{bmatrix}0& 0& 0& 0\\ 0& 0& 1& 2\\ 0& 0& 0& 1\\ 0& 0& 0& 0 \end{bmatrix} (g) \begin{bmatrix}1& 0& 0& 0& 1\\ 0& 1& 0& 0& 2\\ 0& 0& 0& 1& -1\\ 0& 0& 0& 0& 0 \end{bmatrix} Solution: (a), (e), (g) are correct. For (b), a_{34}=-1 is wrong; for (c), a_{32}=1 is wrong; for (d), a_{25}=-1 is wrong; for (f), a_{24}=2 is wrong. 2. Find reduced row-echelon forms which are row-equivalent to the following matrices: (a) \begin{bmatrix}0& 0& 0 \\ 2& 4& 0 \end{bmatrix} (b) \begin{bmatrix}0& 1& 3\\ 1& 2& 4 \end{bmatrix} (c) \begin{bmatrix}1& 1& 1\\ 1& 1& 0\\ 1& 0& 0 \end{bmatrix} (d) \begin{bmatrix}2& 0& 0\\ 0& 0& 0\\ -4& 0& 0 \end{bmatrix} Solution: (a) \begin{bmatrix}0& 0& 0 \\ 2& 4& 0 \end{bmatrix}\Leftrightarrow R_1\leftrightarrow R_2 \begin{bmatrix}2& 4& 0\\ 0& 0& 0 \end{bmatrix}\Leftrightarrow R_1\rightarrow{1\over2}R_1 \begin{bmatrix}1& 2& 0\\ 0& 0& 0 \end{bmatrix} (b) \begin{bmatrix}0& 1& 3\\ 1& 2& 4 \end{bmatrix}\Leftrightarrow R_1\leftrightarrow R_2 \begin{bmatrix}1& 2& 4\\ 0& 1& 3 \end{bmatrix}\Leftrightarrow R_1\rightarrow R_1-2R_2 \begin{bmatrix}1& 0& -2\\ 0& 1& 3 \end{bmatrix} (c) \begin{bmatrix}1& 1& 1\\ 1& 1& 0\\ 1& 0& 0 \end{bmatrix} \Leftrightarrow\begin{cases}R_2\rightarrow R_2-R_1\\ R_3\rightarrow R_3-R_1\end{cases}\begin{bmatrix}1& 1& 1\\ 0& 0& -1\\ 0& -1& -1 \end{bmatrix} \Leftrightarrow\begin{cases}R_1\rightarrow R_1+R_3\\ R_3\rightarrow R_3-R_2 \end{cases}\begin{bmatrix}1& 0& 0\\ 0& 0& -1\\ 0& -1& 0 \end{bmatrix} \Leftrightarrow\begin{cases}R_2\leftrightarrow R_3\\ R_2\rightarrow -R_2\\ R_3\rightarrow-R_3\end{cases}\begin{bmatrix}1& 0& 0\\ 0& 1& 0\\ 0& 0& 1 \end{bmatrix} (d) \begin{bmatrix}2& 0& 0\\ 0& 0& 0\\ -4& 0& 0 \end{bmatrix}\Leftrightarrow\begin{cases}R_3\rightarrow R_3+R_1\\ R_1\rightarrow{1\over2}R_1\end{cases}\begin{bmatrix}1& 0& 0\\ 0& 0& 0\\ 0& 0& 0 \end{bmatrix} 3. Solve the following systems of linear equations by reducing the augmented matrix to reduced row-echelon form: (a) \begin{cases} x+y+z=2\\ 2x+3y-z=8\\x-y-z=-8\end{cases} (b) \begin{cases}x_1+x_2-x_3+2x_4=10\\ 3x_1-x_2+7x_3+4x_4=1\\-5x_1+3x_2-15x_3-6x_4=9\end{cases} (c) \begin{cases}3x-y+7z=0\\ 2x-y+4z={1\over2}\\ x-y+z=1\\ 6x-4y+10z=3 \end{cases} (d) \begin{cases}2x_2+3x_3-4x_4=1\\ 2x_3+3x_4=4\\ 2x_1+2x_2-5x_3+2x_4=4\\2x_1-6x_3+9x_4=7 \end{cases} Solution: (a) The augmented matrix is A=\begin{bmatrix}1& 1& 1& 2\\ 2& 3& -1& 8\\ 1& -1& -1& -8\end{bmatrix} \Leftrightarrow\begin{cases}R_2\rightarrow R_2-2R_1\\ R_3\rightarrow R_3-R_1\end{cases} \begin{bmatrix}1& 1& 1& 2\\ 0& 1& -3& 4\\ 0& -2& -2& -10\end{bmatrix} \Leftrightarrow\begin{cases}R_1\rightarrow R_1-R_2\\ R_3\rightarrow R_3+2R_2\end{cases} \begin{bmatrix}1& 0& 4& -2\\ 0& 1& -3& 4\\ 0& 0& -8& -2\end{bmatrix} \Leftrightarrow\begin{cases}R_1\rightarrow R_1+{1\over2}R_3\\ R_2\rightarrow R_2-{3\over8}R_3\\ R_3\rightarrow-{1\over8}R_3\end{cases}\begin{bmatrix}1& 0& 0& -3\\ 0& 1& 0& {19\over4}\\ 0& 0& 1& {1\over4}\end{bmatrix}=B Matrix B is an equivalent reduced row-echelon form of A. We can read off the solution: \begin{cases}x=-3\\ y={19\over4}\\ z={1\over4}\end{cases} (b) The augmented matrix is A=\begin{bmatrix}1& 1& -1& 2& 10\\ 3& -1& 7& 4& 1\\ -5& 3& -15& -6& 9 \end{bmatrix} \Leftrightarrow\begin{cases}R_2\rightarrow R_2-3R_1\\ R_3\rightarrow R_3+5R_1\end{cases} \begin{bmatrix}1& 1& -1& 2& 10\\ 0& -4& 10& -2& -29\\ 0& 8& -20& 4& 59 \end{bmatrix} \Leftrightarrow\begin{cases}R_1\rightarrow R_1+{1\over4}R_2\\ R_3\rightarrow R_3+2R_2\end{cases} \begin{bmatrix}1& 0& {3\over2}& {3\over2}& {11\over4}\\ 0& -4& 10& -2& -29\\ 0& 0& 0& 0& 1 \end{bmatrix} From the last matrix we see that the original system is inconsistent. (c) The augmented matrix is A=\begin{bmatrix}3& -1& 7& 0\\ 2& -1& 4& {1\over2}\\ 1& -1& 1& 1\\ 6& -4& 10& 3\end{bmatrix} \Leftrightarrow\begin{cases}R_1\rightarrow R_1-3R_3\\ R_2\rightarrow R_2-2R_3\\ R_4\rightarrow R_4-6R_3\end{cases} \begin{bmatrix}0& 2& 4& -3\\ 0& 1& 2& -{3\over2}\\ 1& -1& 1& 1\\ 0& 2& 4& -3\end{bmatrix} \Leftrightarrow\begin{cases}R_1\rightarrow R_1-2R_2\\ R_3\rightarrow R_3+R_2\\ R_4\rightarrow R_4-2R_2\end{cases} \begin{bmatrix}0& 0& 0& 0\\ 0& 1& 2& -{3\over2}\\ 1& 0& 3& -{1\over2}\\ 0& 0& 0& 0\end{bmatrix} \Leftrightarrow R_1\leftrightarrow R_3\, \begin{bmatrix}1& 0& 3& -{1\over2}\\0& 1& 2& -{3\over2}\\ 0& 0& 0& 0\\ 0& 0& 0& 0\end{bmatrix}=B Matrix B is an equivalent reduced row-echelon form of A. We can read off the solution: \begin{cases}x=-{1\over2}-3z\\ y=-{3\over2}-2z\end{cases} \mbox{with arbitrary}\, z. (d) The augmented matrix is A=\begin{bmatrix}0& 2& 3& -4& 1\\ 0& 0& 2& 3& 4\\ 2& 2& -5& 2& 4\\ 2& 0& -6& 9& 7\end{bmatrix} \Leftrightarrow\begin{cases}R_4\rightarrow R_4-R_3\\ R_1\leftrightarrow R_3\end{cases} \begin{bmatrix}2& 2& -5& 2& 4\\ 0& 0& 2& 3& 4\\ 0& 2& 3& -4& 1\\ 0& -2& -1& 7& 3\end{bmatrix} \Leftrightarrow\begin{cases}R_1\rightarrow R_1-R_3\\ R_4\rightarrow R_4+R_3\end{cases} \begin{bmatrix}2& 0& -8& 6& 3\\ 0& 0& 2& 3& 4\\ 0& 2& 3& -4& 1\\ 0& 0& 2& 3& 4\end{bmatrix} \Leftrightarrow\begin{cases}R_1\rightarrow R_1+4R_2\\ R_3\rightarrow R_3-{3\over2}R_2\\ R_4\rightarrow R_4-R_2\end{cases} \begin{bmatrix}2& 0& 0& 18& 19\\ 0& 0& 2& 3& 4\\ 0& 2& 0& -{17\over2}& -5\\ 0& 0& 0& 0& 0\end{bmatrix} \Leftrightarrow\begin{cases}R_1\rightarrow{1\over2}R_1\\ R_2\rightarrow{1\over2}R_2\\ R_3\rightarrow{1\over2}R_3\\ R_2\leftrightarrow R_3\end{cases} \begin{bmatrix}1& 0& 0& 9& {19\over2}\\ 0& 1& 0& -{17\over4}& -{5\over2}\\0& 0& 1& {3\over2}& 2\\ 0& 0& 0& 0& 0\end{bmatrix}=B Matrix B is an equivalent reduced row-echelon form of A. We can read off the solution: \begin{cases}x_1={19\over2}-9x_4\\ x_2=-{5\over2}+{17\over4}x_4\\ x_3=2-{3\over2}x_4\end{cases} \mbox{with arbitrary}\, x_4. 4. Show that the following system is consistent if and only if c=2a-3b and solve the system in this case. \begin{cases}2x-y+3z=a\\ 3x+y-5z=b\\ -5x-5y+21z=c \end{cases} Solution: The augmented matrix is A=\begin{bmatrix}2& -1& 3& a\\ 3& 1& -5& b\\ -5& -5& 21& c\end{bmatrix} \Leftrightarrow\begin{cases}R_2\rightarrow R_2-{3\over2}R_1\\ R_3\rightarrow R_3+{5\over2}R_1 \end{cases} \begin{bmatrix}2& -1& 3& a\\ 0& {5\over2}& -{19\over2}& b-{3\over2}a\\ 0& -{15\over2}& {57\over2}& c+{5\over2}a\end{bmatrix} \Leftrightarrow\begin{cases}R_1\rightarrow R_1+{2\over5}R_2\\ R_3\rightarrow R_3+3R_2\end{cases}\begin{bmatrix}2& 0& -{4\over5}& {2\over5}(a+b)\\ 0& {5\over2}& -{19\over2}& b-{3\over2}a\\ 0& 0& 0 & -2a+3b+c\end{bmatrix} \Leftrightarrow\begin{cases}R_1\rightarrow{1\over2}R_1\\ R_2\rightarrow{2\over5}R_2\end{cases}\begin{bmatrix}1& 0& -{2\over5}& {1\over5}(a+b)\\ 0& 1 & -{19\over5}& {2\over5}b-{3\over5}a\\ 0& 0& 0 & -2a+3b+c\end{bmatrix} From the last matrix we see that the original system is consistent if and only if -2a+3b+c=0\Rightarrow c=2a-3b. And the solution is \begin{cases}x={a+b\over5}+{2\over5}z\\ y={-3a+2b\over5}+{19\over5}z \end{cases}\mbox{with arbitrary}\, z. 5. Find the value of t for which the following system is consistent and solve the system for this value of t. \begin{cases}x+y=1\\ tx+y=t\\ (1+t)x+2y=3 \end{cases} Solution: The augmented matrix is A=\begin{bmatrix}1& 1& 1\\ t& 1& t\\ 1+t& 2& 3\end{bmatrix} \Leftrightarrow\begin{cases}R_2\rightarrow R_2-tR_1\\ R_3\rightarrow R_3-(1+t)R_1 \end{cases}\begin{bmatrix}1& 1& 1\\ 0& 1-t& 0\\ 0& 1-t& 2-t\end{bmatrix} \Leftrightarrow R_2\rightarrow{1\over1-t}R_2(t\neq1)\,\begin{bmatrix}1& 1& 1\\ 0& 1& 0\\ 0& 1-t& 2-t\end{bmatrix} \Leftrightarrow\begin{cases}R_1\rightarrow R_1-R_2\\ R_3\rightarrow R_3-(1-t)R_2\end{cases}\begin{bmatrix}1& 0& 1\\ 0& 1& 0\\ 0& 0& 2-t\end{bmatrix} From the last matrix we see that the original system is consistent if and only if 2-t=0\Rightarrow t=2 and the solution is \begin{cases}x=1\\ y=0 \end{cases} 6. Solve the homogeneous system \begin{cases}-3x_1+x_2+x_3+x_4=0\\ x_1-3x_2+x_3+x_4=0\\x_1+x_2-3x_3+x_4=0\\x_1+x_2+x_3-3x_4=0 \end{cases} Solution: The coefficient matrix is A=\begin{bmatrix}-3& 1& 1& 1\\ 1& -3& 1& 1\\ 1& 1& -3& 1\\ 1& 1& 1& -3 \end{bmatrix} \Leftrightarrow \begin{cases}R_1\rightarrow R_1-R_4\\ R_2\rightarrow R_2-R_4\\ R_3\rightarrow R_3-R_4\end{cases}\begin{bmatrix}-4& 0& 0& 4\\ 0& -4& 0& 4\\ 0& 0& -4& 4\\ 1& 1& 1& -3 \end{bmatrix} \Leftrightarrow \begin{cases}R_1\rightarrow-{1\over4}R_1\\ R_2\rightarrow-{1\over4}R_2\\ R_3\rightarrow-{1\over4}R_3 \end{cases}\begin{bmatrix}1& 0& 0& -1\\ 0& 1& 0& -1\\ 0& 0& 1& -1\\ 1& 1& 1& -3 \end{bmatrix} \Leftrightarrow R_4\rightarrow R_4-R_1-R_2-R_3\, \begin{bmatrix}1& 0& 0& -1\\ 0& 1& 0& -1\\ 0& 0& 1& -1\\ 0& 0& 0& 0 \end{bmatrix} The solution is \begin{cases}x_1=x_4\\x_2=x_4\\x_3=x_4\end{cases}\Rightarrow x_1=x_2=x_3=x_4,\, \mbox{with arbitrary}\, x_4. 7. For which rational numbers \lambda does the homogeneous system \begin{cases}x+(\lambda-3)y=0\\ (\lambda-3)x+y=0 \end{cases} have a non-trivial solution? Solution: The coefficient matrix is A=\begin{bmatrix}1& \lambda-3\\ \lambda-3& 1\end{bmatrix} \Leftrightarrow R_2\rightarrow R_2-(\lambda-3)R_1\, \begin{bmatrix}1& \lambda-3\\ 0& -{\lambda}^2+6\lambda-8\end{bmatrix}=\begin{bmatrix}1& \lambda-3\\ 0& -(\lambda-2)(\lambda-4)\end{bmatrix}
- \lambda=2\Rightarrow\begin{bmatrix}1& -1\\ 0& 0\end{bmatrix}\Rightarrow x=y, with arbitrary y.
- \lambda=4\Rightarrow\begin{bmatrix}1& 1\\ 0& 0\end{bmatrix}\Rightarrow x=-y, with arbitrary y.
- \lambda\neq2,\, 4\Rightarrow x=y=0 which is the trial solution.
- a\neq0 A=\begin{bmatrix}a& b\\ c& d\end{bmatrix}\Leftrightarrow R_2\rightarrow R_2-{c\over a}R_1\, \begin{bmatrix}a& b\\ 0& {ad-bc\over a}\end{bmatrix}(\ast) \Leftrightarrow R_1\rightarrow R_1-{ab\over ad-bc}R_2\, \begin{bmatrix}a& 0\\ 0& {ad-bc\over a}\end{bmatrix}\Leftrightarrow\begin{cases}R_1\rightarrow{1\over a}R_1\\ R_2\rightarrow{a\over ad-bc}R_2\end{cases}\begin{bmatrix}1& 0\\ 0& 1\end{bmatrix}
- a=0\Rightarrow c\neq0, otherwise ad-bc=0. Similar to the above case, we can obtain the same row-equivalent matrix \begin{bmatrix}1& 0\\ 0& 1\end{bmatrix}.
- a^2-16\neq0\Rightarrow a\neq\pm4 B=\begin{bmatrix}1& 0& 1& {8\over7}\\0& 1& -2& {10\over7}\\0& 0& a^2-16& a-4 \end{bmatrix} \Leftrightarrow\begin{cases}R_1\rightarrow R_1-{1\over a^2-16}R_3\\ R_2\rightarrow R_2+{2\over a^2-16}R_3\\R_3\rightarrow {1\over a^2-16}R_3\end{cases}\begin{bmatrix}1& 0& 0& {8a+25\over 7(a+4)}\\0& 1&0 & {10a+54\over 7(a+4)}\\0& 0& 1& {1\over a+4} \end{bmatrix} \Rightarrow\begin{cases}x={8a+25\over 7(a+4)}\\ y={10a+54\over 7(a+4)}\\ z={1\over a+4}\end{cases} which has exactly one solution.
- a=4 B=\begin{bmatrix}1& 0& 1& {8\over7}\\0& 1& -2& {10\over7}\\0& 0& a^2-16& a-4 \end{bmatrix}=\begin{bmatrix}1& 0& 1& {8\over7}\\0& 1& -2& {10\over7}\\0& 0& 0& 0 \end{bmatrix} \Rightarrow \begin{cases}x={8\over7}-z\\ y={10\over7}+2z \end{cases}\, \mbox{with arbitrary}\, z. which has infinitely many solutions.
- a=-4 B=\begin{bmatrix}1& 0& 1& {8\over7}\\0& 1& -2& {10\over7}\\0& 0& a^2-16& a-4 \end{bmatrix}=\begin{bmatrix}1& 0& 1& {8\over7}\\0& 1& -2& {10\over7}\\0& 0& 0& -8 \end{bmatrix} The last matrix shows that the system is inconsistent, which means no solution.
- If a=2 B=\begin{bmatrix}1& 0& 2& 0& 1\\ 0& 0& 0&0&b-2\\ 0& -1&3&-1& 0 \end{bmatrix}
- If b\neq0, it is inconsistent.
- If b=2 B=\begin{bmatrix}1& 0& 2& 0& 1\\ 0& 0& 0&0&0\\ 0& -1&3&-1& 0 \end{bmatrix} \Leftrightarrow\begin{cases} R_2\rightarrow -R_2\\ R_2\leftrightarrow R_3\end{cases}\begin{bmatrix}1& 0& 2& 0& 1\\0& 1&-3&1& 0 \\ 0& 0& 0&0&0\end{bmatrix}\Rightarrow \begin{cases}x=1-2z\\ y=3z-w \end{cases} with z,\, w arbitrary.
- If a\neq2 B=\begin{bmatrix}1& 0& 2& a-2& a-1\\ 0& 0& 4-2a& -a^2+3a-2& -a^2+2a+b-2\\ 0& -1&3& a-3& a-2 \end{bmatrix} \Leftrightarrow\begin{cases}R_2\leftrightarrow R_3\\ R_2\rightarrow -R_2\\ R_3\rightarrow -R_3 \end{cases}\begin{bmatrix}1& 0& 2& a-2& a-1\\0& 1&-3& 3-a& 2-a \\ 0& 0& 2(a-2)& (a-1)(a-2)& a^2-2a-b+2 \end{bmatrix} \Leftrightarrow R_3\rightarrow{1\over2(a-2)}R_3\begin{bmatrix}1& 0& 2& a-2& a-1\\0& 1&-3& 3-a& 2-a \\ 0& 0& 1& {a-1\over2}& {a^2-2a-b+2\over2(a-2)} \end{bmatrix} Thus we can solve for x,\, y,\, z with arbitrary w.
Now we will make the multiplication table for F. First, a\cdot0=0,\, a\cdot1=a, \, If a\cdot b =b then a=1 which is inconsistent. So a\cdot b=1. Similarly, b\cdot0=0,\, b\cdot1=b,\, b\cdot a=1. Next, a\cdot a=1 or a or b (if a\cdot a=0 then a=0). If a^2=1\Rightarrow (a+1)\cdot(a-1)= b\cdot(a-1)=(a-1)\cdot(a-1)=0\Rightarrow a=1, which is inconsistent. If a^2=a\Rightarrow a\cdot(a-1)=0\Rightarrow a=0 or a=1, which are both inconsistent. Thus a\cdot a=b Similarly, b\cdot b=a. The multiplication table for F is:
(b) According to Table 1 and Table 2, we have A=\begin{bmatrix}1& a& b& a\\ a& b& b& 1\\ 1& 1& 1& a \end{bmatrix} \Leftrightarrow\begin{cases}R_2\rightarrow R_2+aR_1\\ R_3\rightarrow R_3+R_1 \end{cases}\begin{bmatrix}1& a& b& a\\ 0& 0& a& a\\ 0& b& a& 0 \end{bmatrix} \Leftrightarrow R_2\leftrightarrow R_3 \begin{bmatrix}1& a& b& a\\0& b& a& 0\\ 0& 0& a& a \end{bmatrix} \Leftrightarrow\begin{cases}R_2\rightarrow aR_2\\ R_3\rightarrow bR_3\end{cases}\begin{bmatrix}1& a& b& a\\0& 1& b& 0\\ 0& 0& 1& 1 \end{bmatrix} \Leftrightarrow\begin{cases}R_1\rightarrow R_1+aR_2\\ R_2\rightarrow R_2+bR_3\end{cases}\begin{bmatrix}1& 0& a& a\\0& 1& 0& b\\ 0& 0& 1& 1 \end{bmatrix} \Leftrightarrow R_1\rightarrow R_1+aR_3 \begin{bmatrix}1& 0& 0& 0\\0& 1& 0& b\\ 0& 0& 1& 1 \end{bmatrix}=B Matrix B is the reduced row-echelon form of matrix A.
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