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  • Abstract vector spaces

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  • Linear combinations
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  • The 0 vector is unique.
  • The additive inverse of a vector is unique.
  • The 0 scalar multiplied by any vector equals the 0 vector.
  • The 0 vector multiplied by any scalar equals the 0 vector.
  • If the product of a vector and a scalar is 0
  • The additive inverse of a vector equals the vector multiplied by -1.
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Description:Added basic properties with proofs
# Basic properties

Put content here**Theorem (Basic Properties of Vector Spaces):** Let $V$ be a vector space over $F$. Then:
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1. **$0v = 0$** — The scalar zero times any vector equals the zero vector.
2. **$a0 = 0$** — Any scalar times the zero vector equals the zero vector.
3. **$(-1)v = -v$** — Multiplying by $-1$ gives the additive inverse.
4. **If $av = 0$, then $a = 0$ or $v = 0$** — No zero divisors.
5. **The zero vector is unique.**
6. **Additive inverses are unique.**
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**Proof sketch for (1):** $0v = (0+0)v = 0v + 0v$ by D2. Adding $-(0v)$ to both sides gives $0 = 0v$. $\blacksquare$
⏎
**Proof sketch for (4):** If $a \neq 0$, multiply both sides of $av = 0$ by $a^{-1}$: $a^{-1}(av) = a^{-1} \cdot 0$, so $(a^{-1}a)v = 0$, hence $1 \cdot v = 0$, so $v = 0$. $\blacksquare$
⏎
**Application:** These properties are used constantly in proofs. For instance, property (4) is key in proving that eigenvectors corresponding to distinct eigenvalues are linearly independent.

# Parents

* Abstract vector spaces
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