MATRICES AND VECTOR SPACES
a discussion of how to use these properties to solve systems of linear equations.
The application of matrices to the study of oscillations in physical systems is
takenupinchapter9.
8.1 Vector spacesA set of objects (vectors)a,b,c,...is said to form alinear vector spaceVif:
(i) the set is closed under commutative and associative addition, so thata+b=b+a, (8.2)(a+b)+c=a+(b+c); (8.3)(ii) the set is closed under multiplication by a scalar (any complex number) to
form a new vectorλa, the operation being both distributive and associative
so thatλ(a+b)=λa+λb, (8.4)(λ+μ)a=λa+μa, (8.5)λ(μa)=(λμ)a, (8.6)whereλandμare arbitrary scalars;
(iii) there exists anull vector 0 such thata+ 0 =afor alla;
(iv) multiplication by unity leaves any vector unchanged, i.e. 1×a=a;
(v) all vectors have a correspondingnegative vector−asuch thata+(−a)= 0.
It follows from (8.5) withλ= 1 andμ=−1that−ais the same vector as
(−1)×a.We note that if we restrict all scalars to be real then we obtain areal vector
space(an example of which is our familiar three-dimensional space); otherwise,
in general, we obtain acomplex vector space. We note that it is common to use the
terms ‘vector space’ and ‘space’, instead of the more formal ‘linear vector space’.
Thespanof a set of vectorsa,b,...,sis defined as the set of all vectors thatmay be written as a linear sum of the original set, i.e. all vectors
x=αa+βb+···+σs (8.7)that result from the infinite number of possible values of the (in general complex)
scalarsα,β,...,σ.Ifxin (8.7) is equal to 0 for some choice ofα,β,...,σ(notall
zero), i.e. if
αa+βb+···+σs= 0 , (8.8)then the set of vectorsa,b,...,s,issaidtobelinearly dependent.Insuchaset
at least one vector is redundant, since it can be expressed as a linear sum of
the others. If, however, (8.8) is not satisfied byanyset of coefficients (other than