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Esercizi sul prodotto scalare
Teoria del Prodotto Scalare
Il prodotto scalare (o prodotto interno) è un’operazione algebrica che prende due vettori e restituisce un numero reale. È uno strumento fondamentale in geometria e fisica, utilizzato per calcolare angoli, proiezioni e lavori.
Definizione
Se abbiamo due vettori a e b in uno spazio euclideo, il prodotto scalare è definito come:
\mathbf{a} \cdot \mathbf{b} = |\mathbf{a}| |\mathbf{b}| \cos(\theta) a ⋅ b = ∣ a ∣ ∣ b ∣ cos ⁡ ( θ ) \mathbf{a} \cdot \mathbf{b} = |\mathbf{a}| |\mathbf{b}| \cos(\theta) a ⋅ b = ∣ a ∣∣ b ∣ cos ( θ )
dove:
|\mathbf{a}| ∣ a ∣ |\mathbf{a}| ∣ a ∣ e |\mathbf{b}| ∣ b ∣ |\mathbf{b}| ∣ b ∣ sono le lunghezze (norme) dei vettori,
\theta θ \theta θ è l’angolo tra i due vettori.
In forma componente, se:
\mathbf{a} = (a_1, a_2, a_3) \quad \text{e} \quad \mathbf{b} = (b_1, b_2, b_3) a = ( a 1 , a 2 , a 3 ) e b = ( b 1 , b 2 , b 3 ) \mathbf{a} = (a_1, a_2, a_3) \quad \text{e} \quad \mathbf{b} = (b_1, b_2, b_3) a = ( a 1 ​ , a 2 ​ , a 3 ​ ) e b = ( b 1 ​ , b 2 ​ , b 3 ​ )
allora il prodotto scalare si calcola come:
\mathbf{a} \cdot \mathbf{b} = a_1 b_1 + a_2 b_2 + a_3 b_3 a ⋅ b = a 1 b 1 + a 2 b 2 + a 3 b 3 \mathbf{a} \cdot \mathbf{b} = a_1 b_1 + a_2 b_2 + a_3 b_3 a ⋅ b = a 1 ​ b 1 ​ + a 2 ​ b 2 ​ + a 3 ​ b 3 ​
Proprietà del Prodotto Scalare
Commutatività : \mathbf{a} \cdot \mathbf{b} = \mathbf{b} \cdot \mathbf{a} a ⋅ b = b ⋅ a \mathbf{a} \cdot \mathbf{b} = \mathbf{b} \cdot \mathbf{a} a ⋅ b = b ⋅ a
Distributività : \mathbf{a} \cdot (\mathbf{b} + \mathbf{c}) = \mathbf{a} \cdot \mathbf{b} + \mathbf{a} \cdot \mathbf{c} a ⋅ ( b + c ) = a ⋅ b + a ⋅ c \mathbf{a} \cdot (\mathbf{b} + \mathbf{c}) = \mathbf{a} \cdot \mathbf{b} + \mathbf{a} \cdot \mathbf{c} a ⋅ ( b + c ) = a ⋅ b + a ⋅ c
Associatività rispetto alla moltiplicazione per uno scalare : k(\mathbf{a} \cdot \mathbf{b}) = (k\mathbf{a}) \cdot \mathbf{b} = \mathbf{a} \cdot (k\mathbf{b}) k ( a ⋅ b ) = ( k a ) ⋅ b = a ⋅ ( k b ) k(\mathbf{a} \cdot \mathbf{b}) = (k\mathbf{a}) \cdot \mathbf{b} = \mathbf{a} \cdot (k\mathbf{b}) k ( a ⋅ b ) = ( k a ) ⋅ b = a ⋅ ( k b )
Esercizi sul Prodotto Scalare
Esercizio 1: Calcolo del Prodotto Scalare
Calcola il prodotto scalare dei vettori:
\mathbf{a} = (2, 3, 4) \quad e \quad \mathbf{b} = (1, 0, -1) a = ( 2 , 3 , 4 ) e b = ( 1 , 0 , − 1 ) \mathbf{a} = (2, 3, 4) \quad e \quad \mathbf{b} = (1, 0, -1) a = ( 2 , 3 , 4 ) e b = ( 1 , 0 , − 1 )
Svolgimento:
Utilizziamo la formula del prodotto scalare in forma componente:
\mathbf{a} \cdot \mathbf{b} = a_1 b_1 + a_2 b_2 + a_3 b_3 a ⋅ b = a 1 b 1 + a 2 b 2 + a 3 b 3 \mathbf{a} \cdot \mathbf{b} = a_1 b_1 + a_2 b_2 + a_3 b_3 a ⋅ b = a 1 ​ b 1 ​ + a 2 ​ b 2 ​ + a 3 ​ b 3 ​
Sostituendo i valori:
\begin{align*}
\mathbf{a} \cdot \mathbf{b} & = 2(1) + 3(0) + 4(-1)\\
& = 2 + 0 - 4\\
& = -2
\end{align*} a ⋅ b = 2 ( 1 ) + 3 ( 0 ) + 4 ( − 1 ) = 2 + 0 − 4 = − 2 \begin{align*}
\mathbf{a} \cdot \mathbf{b} & = 2(1) + 3(0) + 4(-1)\\
& = 2 + 0 - 4\\
& = -2
\end{align*} a ⋅ b ​ = 2 ( 1 ) + 3 ( 0 ) + 4 ( − 1 ) = 2 + 0 − 4 = − 2 ​
Risultato:
Il prodotto scalare \mathbf{a} \cdot \mathbf{b} = -2 a ⋅ b = − 2 \mathbf{a} \cdot \mathbf{b} = -2 a ⋅ b = − 2 .
Esercizio 2: Calcolo dell’Angolo tra Due Vettori
Calcola l’angolo θ θ θ θ tra i vettori:
\mathbf{u} = (3, 4) \quad e \quad \mathbf{v} = (5, 0) u = ( 3 , 4 ) e v = ( 5 , 0 ) \mathbf{u} = (3, 4) \quad e \quad \mathbf{v} = (5, 0) u = ( 3 , 4 ) e v = ( 5 , 0 )
Svolgimento:
Calcoliamo il prodotto scalare \mathbf{u} \cdot \mathbf{v} u ⋅ v \mathbf{u} \cdot \mathbf{v} u ⋅ v :
u_v = 3(5) + 4(0) = 15 u v = 3 ( 5 ) + 4 ( 0 ) = 15 u_v = 3(5) + 4(0) = 15 u v ​ = 3 ( 5 ) + 4 ( 0 ) = 15
Calcoliamo le norme dei vettori:
|\mathbf{u}| = \sqrt{3^2 + 4^2} = \sqrt{9 + 16} = 5 ∣ u ∣ = 3 2 + 4 2 = 9 + 16 = 5 |\mathbf{u}| = \sqrt{3^2 + 4^2} = \sqrt{9 + 16} = 5 ∣ u ∣ = 3 2 + 4 2 ​ = 9 + 16 ​ = 5
|\mathbf{v}| = |5| = 5 ∣ v ∣ = ∣ 5 ∣ = 5 |\mathbf{v}| = |5| = 5 ∣ v ∣ = ∣5∣ = 5
Utilizziamo la formula del prodotto scalare per trovare l’angolo:
u_v = |\mathbf{u}| |\mathbf{v}| cos(θ) u v = ∣ u ∣ ∣ v ∣ c o s ( θ ) u_v = |\mathbf{u}| |\mathbf{v}| cos(θ) u v ​ = ∣ u ∣∣ v ∣ cos ( θ )
Sostituendo i valori:
15 = 5(5) cos(θ) 15 = 5 ( 5 ) c o s ( θ ) 15 = 5(5) cos(θ) 15 = 5 ( 5 ) cos ( θ )
cos(θ) = \frac{15}{25} = 0.6 c o s ( θ ) = 15 25 = 0.6 cos(θ) = \frac{15}{25} = 0.6 cos ( θ ) = 25 15 ​ = 0.6
Ora calcoliamo l’angolo:
θ = cos^{-1}(0.6) ≈ 53.13° θ = c o s − 1 ( 0.6 ) ≈ 53.13 ° θ = cos^{-1}(0.6) ≈ 53.13° θ = co s − 1 ( 0.6 ) ≈ 53.13°
Risultato:
L’angolo tra i vettori θ ≈ 53.13° θ ≈ 53.13 ° θ ≈ 53.13° θ ≈ 53.13° .
Esercizio 3: Proiezione di un Vettore su un Altro Vettore
Calcola la proiezione del vettore:
\mathbf{x} = (4, -2, 6) x = ( 4 , − 2 , 6 ) \mathbf{x} = (4, -2, 6) x = ( 4 , − 2 , 6 )
sul vettore:
\mathbf{y} = (1, 1, 1). y = ( 1 , 1 , 1 ) . \mathbf{y} = (1, 1, 1). y = ( 1 , 1 , 1 ) .
Svolgimento:
La proiezione di \mathbf{x} x \mathbf{x} x su \mathbf{y} y \mathbf{y} y è data dalla formula:
\text{proj}_{\mathbf{y}}(\mathbf{x}) = \frac{\mathbf{x} \cdot \mathbf{y}}{\|\mathbf{y}\|^2}\,\mathbf{y} proj y ( x ) = x ⋅ y ∥ y ∥ 2   y \text{proj}_{\mathbf{y}}(\mathbf{x}) = \frac{\mathbf{x} \cdot \mathbf{y}}{\|\mathbf{y}\|^2}\,\mathbf{y} proj y ​ ( x ) = ∥ y ∥ 2 x ⋅ y ​ y
Calcoliamo il prodotto scalare x_y = (4)(1) + (-2)(1) + (6)(1) = 4 - 2 + 6 = 8 x y = ( 4 ) ( 1 ) + ( − 2 ) ( 1 ) + ( 6 ) ( 1 ) = 4 − 2 + 6 = 8 x_y = (4)(1) + (-2)(1) + (6)(1) = 4 - 2 + 6 = 8 x y ​ = ( 4 ) ( 1 ) + ( − 2 ) ( 1 ) + ( 6 ) ( 1 ) = 4 − 2 + 6 = 8 .
Calcoliamo la norma al quadrato di y y y y :
|\mathbf{y}|^2 = (1^2 + 1^2 + 1^2) = 3. ∣ y ∣ 2 = ( 1 2 + 1 2 + 1 2 ) = 3. |\mathbf{y}|^2 = (1^2 + 1^2 + 1^2) = 3. ∣ y ∣ 2 = ( 1 2 + 1 2 + 1 2 ) = 3.
Ora calcoliamo la proiezione:proj_{\mathbf{y}}(\mathbf{x}) = \frac{x_y}{|\mathbf{y}|^2}\,\mathbf{y} p r o j y ( x ) = x y ∣ y ∣ 2   y proj_{\mathbf{y}}(\mathbf{x}) = \frac{x_y}{|\mathbf{y}|^2}\,\mathbf{y} p ro j y ​ ( x ) = ∣ y ∣ 2 x y ​ ​ y
Sostituendo i valori:proj_{\mathbf{y}}(\mathbf{x}) = \frac{8}{3}(1, 1, 1) = (\frac{8}{3},\,\frac{8}{3},\,\frac{8}{3}) p r o j y ( x ) = 8 3 ( 1 , 1 , 1 ) = ( 8 3 ,   8 3 ,   8 3 ) proj_{\mathbf{y}}(\mathbf{x}) = \frac{8}{3}(1, 1, 1) = (\frac{8}{3},\,\frac{8}{3},\,\frac{8}{3}) p ro j y ​ ( x ) = 3 8 ​ ( 1 , 1 , 1 ) = ( 3 8 ​ , 3 8 ​ , 3 8 ​ )
Risultato:
La proiezione di x x x x su y y y y è (\frac{8}{3},\,\frac{8}{3},\,\frac{8}{3}) ( 8 3 ,   8 3 ,   8 3 ) (\frac{8}{3},\,\frac{8}{3},\,\frac{8}{3}) ( 3 8 ​ , 3 8 ​ , 3 8 ​ ) .
English version
Scalar Product Exercises
Scalar Product Theory
The scalar product (or inner product) is an algebraic operation that takes two vectors and returns a real number. It is a fundamental tool in geometry and physics, used to calculate angles, projections and work.
Definition
If we have two vectors a and b in a Euclidean space, the scalar product is defined as:
\mathbf{a} \cdot \mathbf{b} = |\mathbf{a}| |\mathbf{b}| \cos(\theta) a ⋅ b = ∣ a ∣ ∣ b ∣ cos ⁡ ( θ ) \mathbf{a} \cdot \mathbf{b} = |\mathbf{a}| |\mathbf{b}| \cos(\theta) a ⋅ b = ∣ a ∣∣ b ∣ cos ( θ )
where:
|\mathbf{a}| ∣ a ∣ |\mathbf{a}| ∣ a ∣ and |\mathbf{b}| ∣ b ∣ |\mathbf{b}| ∣ b ∣ are the lengths (norms) of the vectors,
\theta θ \theta θ is the angle between the two vectors.
In component form, if:
\mathbf{a} = (a_1, a_2, a_3) \quad \text{e} \quad \mathbf{b} = (b_1, b_2, b_3) a = ( a 1 , a 2 , a 3 ) e b = ( b 1 , b 2 , b 3 ) \mathbf{a} = (a_1, a_2, a_3) \quad \text{e} \quad \mathbf{b} = (b_1, b_2, b_3) a = ( a 1 ​ , a 2 ​ , a 3 ​ ) e b = ( b 1 ​ , b 2 ​ , b 3 ​ )
then the scalar product is calculated as:
\mathbf{a} \cdot \mathbf{b} = a_1 b_1 + a_2 b_2 + a_3 b_3 a ⋅ b = a 1 b 1 + a 2 b 2 + a 3 b 3 \mathbf{a} \cdot \mathbf{b} = a_1 b_1 + a_2 b_2 + a_3 b_3 a ⋅ b = a 1 ​ b 1 ​ + a 2 ​ b 2 ​ + a 3 ​ b 3 ​
Properties of the Scalar Product
Commutativity : \mathbf{a} \cdot \mathbf{b} = \mathbf{b} \cdot \mathbf{a} a ⋅ b = b ⋅ a \mathbf{a} \cdot \mathbf{b} = \mathbf{b} \cdot \mathbf{a} a ⋅ b = b ⋅ a
Distributivity : \mathbf{a} \cdot (\mathbf{b} + \mathbf{c}) = \mathbf{a} \cdot \mathbf{b} + \mathbf{a} \cdot \mathbf{c} a ⋅ ( b + c ) = a ⋅ b + a ⋅ c \mathbf{a} \cdot (\mathbf{b} + \mathbf{c}) = \mathbf{a} \cdot \mathbf{b} + \mathbf{a} \cdot \mathbf{c} a ⋅ ( b + c ) = a ⋅ b + a ⋅ c
Associativity with respect to scalar multiplication : k(\mathbf{a} \cdot \mathbf{b}) = (k\mathbf{a}) \cdot \mathbf{b} = \mathbf{a} \cdot (k\mathbf{b}) k ( a ⋅ b ) = ( k a ) ⋅ b = a ⋅ ( k b ) k(\mathbf{a} \cdot \mathbf{b}) = (k\mathbf{a}) \cdot \mathbf{b} = \mathbf{a} \cdot (k\mathbf{b}) k ( a ⋅ b ) = ( k a ) ⋅ b = a ⋅ ( k b )
Exercises on the Scalar Product
Exercise 1: Calculating the Scalar Product
Calculate the scalar product of the vectors:
\mathbf{a} = (2, 3, 4) \quad and \quad \mathbf{b} = (1, 0, -1) a = ( 2 , 3 , 4 ) a n d b = ( 1 , 0 , − 1 ) \mathbf{a} = (2, 3, 4) \quad and \quad \mathbf{b} = (1, 0, -1) a = ( 2 , 3 , 4 ) an d b = ( 1 , 0 , − 1 )
Solution:
We use the scalar product formula in the form component:
\mathbf{a} \cdot \mathbf{b} = a_1 b_1 + a_2 b_2 + a_3 b_3 a ⋅ b = a 1 b 1 + a 2 b 2 + a 3 b 3 \mathbf{a} \cdot \mathbf{b} = a_1 b_1 + a_2 b_2 + a_3 b_3 a ⋅ b = a 1 ​ b 1 ​ + a 2 ​ b 2 ​ + a 3 ​ b 3 ​
Substituting the values:
\begin{align*}
\mathbf{a} \cdot \mathbf{b} & = 2(1) + 3(0) + 4(-1)\\
& = 2 + 0 - 4\\
& = -2
\end{align*} a ⋅ b = 2 ( 1 ) + 3 ( 0 ) + 4 ( − 1 ) = 2 + 0 − 4 = − 2 \begin{align*}
\mathbf{a} \cdot \mathbf{b} & = 2(1) + 3(0) + 4(-1)\\
& = 2 + 0 - 4\\
& = -2
\end{align*} a ⋅ b ​ = 2 ( 1 ) + 3 ( 0 ) + 4 ( − 1 ) = 2 + 0 − 4 = − 2 ​
Result:
The dot product \mathbf{a} \cdot \mathbf{b} = -2 a ⋅ b = − 2 \mathbf{a} \cdot \mathbf{b} = -2 a ⋅ b = − 2 .
Exercise 2: Calculating the Angle Between Two Vectors
Calculate the angle θ θ θ θ between the vectors:
\mathbf{u} = (3, 4) \quad and \quad \mathbf{v} = (5, 0) u = ( 3 , 4 ) a n d v = ( 5 , 0 ) \mathbf{u} = (3, 4) \quad and \quad \mathbf{v} = (5, 0) u = ( 3 , 4 ) an d v = ( 5 , 0 )
Solution:
Let’s calculate the scalar product \mathbf{u} \cdot \mathbf{v} u ⋅ v \mathbf{u} \cdot \mathbf{v} u ⋅ v :
u_v = 3(5) + 4(0) = 15 u v = 3 ( 5 ) + 4 ( 0 ) = 15 u_v = 3(5) + 4(0) = 15 u v ​ = 3 ( 5 ) + 4 ( 0 ) = 15
Let’s calculate the norms of the vectors:
|\mathbf{u}| = \sqrt{3^2 + 4^2} = \sqrt{9 + 16} = 5 ∣ u ∣ = 3 2 + 4 2 = 9 + 16 = 5 |\mathbf{u}| = \sqrt{3^2 + 4^2} = \sqrt{9 + 16} = 5 ∣ u ∣ = 3 2 + 4 2 ​ = 9 + 16 ​ = 5
|\mathbf{v}| = |5| = 5 ∣ v ∣ = ∣ 5 ∣ = 5 |\mathbf{v}| = |5| = 5 ∣ v ∣ = ∣5∣ = 5
We use the scalar product formula to find the angle:
u_v = |\mathbf{u}| |\mathbf{v}| cos(θ) u v = ∣ u ∣ ∣ v ∣ c o s ( θ ) u_v = |\mathbf{u}| |\mathbf{v}| cos(θ) u v ​ = ∣ u ∣∣ v ∣ cos ( θ )
Substituting the values:
15 = 5(5) cos(θ) 15 = 5 ( 5 ) c o s ( θ ) 15 = 5(5) cos(θ) 15 = 5 ( 5 ) cos ( θ )
cos(θ) = \frac{15}{25} = 0.6 c o s ( θ ) = 15 25 = 0.6 cos(θ) = \frac{15}{25} = 0.6 cos ( θ ) = 25 15 ​ = 0.6
Now we calculate the angle:
θ = cos^{-1}(0.6) ≈ 53.13° θ = c o s − 1 ( 0.6 ) ≈ 53.13 ° θ = cos^{-1}(0.6) ≈ 53.13° θ = co s − 1 ( 0.6 ) ≈ 53.13°
Result:
The angle between the vectors θ ≈ 53.13° θ ≈ 53.13 ° θ ≈ 53.13° θ ≈ 53.13° .
Exercise 3: Projection of a Vector onto Another Vector
Calculate the projection of the vector:
\mathbf{x} = (4, -2, 6) x = ( 4 , − 2 , 6 ) \mathbf{x} = (4, -2, 6) x = ( 4 , − 2 , 6 )
on the vector:
\mathbf{y} = (1, 1, 1). y = ( 1 , 1 , 1 ) . \mathbf{y} = (1, 1, 1). y = ( 1 , 1 , 1 ) .
Process:
The projection of \mathbf{x} x \mathbf{x} x onto \mathbf{y} y \mathbf{y} y is given by the formula:
\text{proj}_{\mathbf{y}}(\mathbf{x}) = \frac{\mathbf{x} \cdot \mathbf{y}}{\|\mathbf{y}\|^2}\,\mathbf{y} proj y ( x ) = x ⋅ y ∥ y ∥ 2   y \text{proj}_{\mathbf{y}}(\mathbf{x}) = \frac{\mathbf{x} \cdot \mathbf{y}}{\|\mathbf{y}\|^2}\,\mathbf{y} proj y ​ ( x ) = ∥ y ∥ 2 x ⋅ y ​ y
Let’s calculate the scalar product x_y = (4)(1) + (-2)(1) + (6)(1) = 4 - 2 + 6 = 8 x y = ( 4 ) ( 1 ) + ( − 2 ) ( 1 ) + ( 6 ) ( 1 ) = 4 − 2 + 6 = 8 x_y = (4)(1) + (-2)(1) + (6)(1) = 4 - 2 + 6 = 8 x y ​ = ( 4 ) ( 1 ) + ( − 2 ) ( 1 ) + ( 6 ) ( 1 ) = 4 − 2 + 6 = 8 .
Let’s calculate the squared norm of y y y y :
|\mathbf{y}|^2 = (1^2 + 1^2 + 1^2) = 3. ∣ y ∣ 2 = ( 1 2 + 1 2 + 1 2 ) = 3. |\mathbf{y}|^2 = (1^2 + 1^2 + 1^2) = 3. ∣ y ∣ 2 = ( 1 2 + 1 2 + 1 2 ) = 3.
Now let’s calculate the projection:
proj_{\mathbf{y}}(\mathbf{x}) = \frac{x_y}{|\mathbf{y}|^2}\,\mathbf{y} p r o j y ( x ) = x y ∣ y ∣ 2   y proj_{\mathbf{y}}(\mathbf{x}) = \frac{x_y}{|\mathbf{y}|^2}\,\mathbf{y} p ro j y ​ ( x ) = ∣ y ∣ 2 x y ​ ​ y
Substituting the values:
proj_{\mathbf{y}}(\mathbf{x}) = \frac{8}{3}(1, 1, 1) = (\frac{8}{3},\,\frac{8}{3},\,\frac{8}{3}) p r o j y ( x ) = 8 3 ( 1 , 1 , 1 ) = ( 8 3 ,   8 3 ,   8 3 ) proj_{\mathbf{y}}(\mathbf{x}) = \frac{8}{3}(1, 1, 1) = (\frac{8}{3},\,\frac{8}{3},\,\frac{8}{3}) p ro j y ​ ( x ) = 3 8 ​ ( 1 , 1 , 1 ) = ( 3 8 ​ , 3 8 ​ , 3 8 ​ )
Result:
The projection of x x x x onto y y y y is (\frac{8}{3},\,\frac{8}{3},\,\frac{8}{3}) ( 8 3 ,   8 3 ,   8 3 ) (\frac{8}{3},\,\frac{8}{3},\,\frac{8}{3}) ( 3 8 ​ , 3 8 ​ , 3 8 ​ ) .
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