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Summary Complex Vector Space

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brief summarizing notes for Complex vector space for quantum computing.

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  • February 28, 2023
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Complex Vector State


Set of Vectors



Example: set of vectors of length 4.



a typical element of it will look like:




To simply put C means a matrix of n
in it.



Operations




That is V + W ∈ C
4
n






7 + 3i

4.2 − 8.1i

−3i




Properties followed by addition operator:

commutative V
Associative (V
+ W = W + V
C










4




+




+ W ) + X = V + (W + X)


Additive Inverse, ie. V + Z = 0
⎢⎥
Notes from Quantum Computing for Computer Scientists book by Noson S. Yanofsky
and Micro A. Mannucci




Primary example of a complex vector space is set of vectors of a fixed length with
complex enteries.
These vectors describe the states of a quantum systems and quantum computers.


= C × C × C × C
























here Z
6 − 4i

7 + 3i

4.2 − 8.1i

−3i



× 1




−7i

6

−4i




= −V










( 1D array )having complex numbers as




All operations that we can perform on Real vector space can be performed on
complex vector space. taking example of

Addition
Consider:

6 − 4i 16 + 2.3i






=






22 − 1.7i

7 − 4i

10.2 − 8.1i

−7i







,
as
Scalar multplication




some other Scaler multplication properties:

1.V = V


c 1 . (c 2 . V ) = (c 1


c. (V + W ) = c. V + c. W




C
m × n
× c 2 ). V




(c 1 + c 2 ). V = c 1 . V + c 2 . V




3

−2


5




3




(3 + 2i).




+ 5
3








⎦ ⎣




0

1

4




⎢⎥










4




− 4
6 + 3i




⎦ ⎣








0

5 + 1i

4




, the set of all m-by-n matrices, with complex enteries in it.




Basis and Dimension




−6

1

0

0
















=




A set B = {V 0, V 1, . . . , V n − 1} ⊆ V of vectors is called a basis of a (complex) vector
space V if both

every, V
B
∈ V can be written as a liner combination of vectors from B and
is linearly independent,each of the vectors in the set {V
written as a combination of the others in the set.

Example:
we can say [45.3, −2.9, 31.1] is a liner combination of
T









−2
5
⎤ ⎡

,
0

1
⎤ ⎡

,
−6


1




+ 2.1




The dimension of a (complex) vector space is the number of elements in a basis of
the vector space.
For example, if V is a complex vector space with a basis B = {v , v , … , v }, then
the dimension of V is n.

R


C
n



n
has dimension n as a real vector space.
has dimension n as a complex vector space










, and
12 + 12i




3
⎡ ⎤



⎣ ⎦




3

1
1




⎡ ⎤


⎣ ⎦
1
0

13 + 13i

12 + 8i




1




=














0,




45.3

−2.9

31.1
V 1 , … , V n−1 }












1 2
cannot be




n

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