Concept understanding — Adjoint and Inverse of a Matrix
For a square matrix A=[aij] of order n, the cofactor of aij is the signed minor Aij=(−1)i+jMij (the minor Mij is the determinant left after deleting row i and column j). Replace every entry of A by its cofactor to get the cofactor matrix; its transpose is the adjoint, adjA.
Theorem (the central identity). For every square matrix A of order n,
A(adjA)=(adjA)A=∣A∣In.
This follows from Laplace expansion: a row's entries dotted with their own cofactors reproduce ∣A∣, while a row's entries dotted with a different row's cofactors always give 0 -- so the product matrix is ∣A∣ on the diagonal and 0 off it.
Definition of the inverse. A square matrix B with AB=BA=In is called the inverse of A, written A−1. The inverse, when it exists, is unique. A−1 exists if and only if A is non-singular (∣A∣=0): dividing the central identity by ∣A∣ (possible exactly when ∣A∣=0) gives the working formula
A−1=∣A∣1adjA.
A singular matrix (∣A∣=0) has no inverse.
Worked illustration (order 2). For A=(acbd), the cofactors are A11=d,A12=−c,A21=−b,A22=a, so adjA=(d−c−ba) (swap the diagonal entries, negate the off-diagonal ones) and A−1=ad−bc1(d−c−ba) whenever ad−bc=0.
Standing laws of inverses (for non-singular A,B of the same order, λ=0 a scalar):
∣A−1∣=∣A∣1.
(AT)−1=(A−1)T.
(λA)−1=λ1A−1.
Left/right cancellation:AB=AC⇒B=C; BA=CA⇒B=C (pre/post-multiply by A−1) -- this fails when A is singular.
Reversal law:(AB)−1=B−1A−1 (note the order flips, exactly as for transposes).
Double inverse:(A−1)−1=A.
Six adjoint identities (non-singular A, order n): (i) adj(A−1)=(adjA)−1=∣A∣A; (ii) ∣adjA∣=∣A∣n−1; (iii) adj(adjA)=∣A∣n−2A; (iv) adj(λA)=λn−1adjA; (v) ∣adj(adjA)∣=∣A∣(n−1)2; (vi) (adjA)T=adj(AT); and for two non-singular matrices of the same order, adj(AB)=(adjB)(adjA) (order reverses, exactly like the inverse and the transpose).
Note
For a non-singular matrix of order 3, since ∣adjA∣=∣A∣2>0, one can also write A=±adjA1adj(adjA) -- useful when only adjA is given and A itself must be recovered.
Orthogonal matrices. A square matrix A is orthogonal if AAT=ATA=I, equivalently A is non-singular and A−1=AT. The standard rotation matrix W=(cosθsinθ−sinθcosθ) that converts one 2-D coordinate system into another (rotated by θ) is orthogonal, since W−1=WT is exactly the inverse rotation by −θ.
Cryptography via a non-singular matrix. Assign each letter A--Z a number 1--26 and a blank space 0. Group the plaintext numbers into row vectors of length n (padding with 0s if needed) and multiply each by a chosen non-singular encoding matrixE of order n (post-multiplication: (row)×E) to get the coded row. The receiver recovers the plaintext by post-multiplying each coded row by the decoding matrixE−1, since (row)E⋅E−1=row. The security of the scheme rests entirely on E being invertible and known only to sender and receiver.
Multiply F(α) by F(−α), using cos(−α)=cosα and sin(−α)=−sinα, and show the product is I3; that identity is exactly the definition of the inverse.
F(α)F(−α)=I3, and by the same computation with the roles swapped, F(−α)F(α)=I3 too.
✓Final answer
F(α)F(−α)=F(−α)F(α)=I3⇒[F(α)]−1=F(−α).
Rather than computing [F(α)]−1 from scratch via the adjoint, we multiply F(α) directly by F(−α) and show the product is I3 — which, for square matrices, is exactly the definition of a two-sided inverse.
Step 1. Write F(−α) using even/odd symmetry. Since cos(−α)=cosα and sin(−α)=−sinα: F(−α)=cosα0sinα010−sinα0cosα.
Step 2. Confirm F(α) is invertible. Expanding ∣F(α)∣ along row 2 (which has two zeros): ∣F(α)∣=1⋅cosα−sinαsinαcosα=cos2α+sin2α=1=0 for every α, so an inverse exists.
Step 3. Multiply F(α)F(−α) entry by entry.
(1,1):cosαcosα+0+sinαsinα=cos2α+sin2α=1
(1,2):0+0+0=0,(1,3):cosα(−sinα)+0+sinαcosα=0
(2,1)=0,(2,2)=1,(2,3)=0 (row 2 of F(α) is (0,1,0), so it just selects the middle entry of each column)
(3,1):−sinαcosα+0+cosαsinα=0,(3,2):0
(3,3):−sinα(−sinα)+0+cosαcosα=sin2α+cos2α=1
So F(α)F(−α)=100010001=I3.
Step 4. Multiply the other way, F(−α)F(α). This is the identical computation with α and −α exchanged; every cos,sin product above is symmetric under that exchange, so F(−α)F(α)=I3 as well.
Step 5. Conclude. For square matrices, F(α)F(−α)=F(−α)F(α)=I3 is precisely the defining property of a two-sided inverse, so [F(α)]−1=F(−α).
✓Final answer
F(α)F(−α)=F(−α)F(α)=I3⇒[F(α)]−1=F(−α).
Direct matrix multiplication using cos(−α)=cosα,sin(−α)=−sinα, matched to the definition of inverse
Forgetting the sign flip sin(−α)=−sinα when writing out F(−α)
Checking only F(α)F(−α) and skipping the reverse product F(−α)F(α)
Detouring through the full adjoint/determinant inverse formula instead of the direct-multiplication argument the question is steering towards