Basics Of Functional Analysis: With Bicomplex Sc...

Basics Of Functional Analysis: With Bicomplex Sc...

This decomposition is the key to bicomplex analysis: it reduces bicomplex problems to two independent complex problems . In classical functional analysis, we work with vector spaces over ( \mathbbR ) or ( \mathbbC ). Over ( \mathbbBC ), a bicomplex module replaces the vector space, but caution: ( \mathbbBC ) is not a division algebra (it has zero divisors, e.g., ( \mathbfe_1 \cdot \mathbfe_2 = 0 ) but neither factor is zero). Hence, we cannot define a bicomplex-valued norm in the usual sense—the triangle inequality fails due to zero divisors.

Any bicomplex Banach space ( X ) is isomorphic (as a real Banach space) to ( X_1 \oplus X_2 ), where ( X_1, X_2 ) are complex Banach spaces, and bicomplex scalars act by: [ (z_1 + z_2 \mathbfj) (x_1 \mathbfe_1 + x_2 \mathbfe_2) = (z_1 - i z_2) x_1 \mathbfe_1 + (z_1 + i z_2) x_2 \mathbfe_2. ] Basics of Functional Analysis with Bicomplex Sc...

The bicomplex spectrum of ( T ) is: [ \sigma_\mathbbBC(T) = \lambda \in \mathbbBC : \lambda I - T \text is not invertible . ] In idempotent form: [ \sigma_\mathbbBC(T) = \sigma_\mathbbC(T_1) \mathbfe 1 + \sigma \mathbbC(T_2) \mathbfe_2 ] where the sum is in the sense of idempotent decomposition: ( \alpha \mathbfe_1 + \beta \mathbfe_2 : \alpha \in \sigma(T_1), \beta \in \sigma(T_2) ). This decomposition is the key to bicomplex analysis:

Every bicomplex number has a unique :