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jk22
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Just a question : do we have in Dirac notation $$\langle u|A|u\rangle\langle u|B|u\rangle=\langle u|\langle u|A\otimes B|u\rangle |u\rangle$$ ?
So ##A## and ##B## act on the same space? Without context, the right-hand side looks like an unnecessary inflation of the state space but technically correct to me.jk22 said:Just a question : do we have in Dirac notation $$\langle u|A|u\rangle\langle u|B|u\rangle=\langle u|\langle u|A\otimes B|u\rangle |u\rangle$$ ?
Your use of Dirac notation seems quite non-standard to me. I haven't seen it in QM texts. Instead of your ##(\langle a| \otimes \langle b|) (|c\rangle, |d\rangle)## I would write ##(\langle a| \otimes \langle b|) (|c\rangle \otimes |d\rangle)## which has the usual symmetry between bra and ket vectors.Geofleur said:Then I guess we would write ## u^1(A\textbf{u})u^1(B\textbf{u}) ## in Dirac notation as ## \langle u | \otimes \langle u | (A| u \rangle, B| u \rangle)##. The first ## \langle u | ## would act on the ## A | u \rangle ## and the second ## \langle u | ## would act on the ## B | u \rangle ##.
The main difference between scalar and tensor products is that scalar products result in a single scalar value while tensor products result in a tensor, which is a multidimensional array. Another difference is that scalar products are commutative, meaning the order of the operands does not matter, while tensor products are not necessarily commutative.
The scalar product, also known as the dot product, is calculated by taking the sum of the products of the corresponding components of two vectors. In other words, it is the magnitude of one vector multiplied by the magnitude of the other vector and the cosine of the angle between them.
The scalar product has several important applications in physics, including calculating work, power, and projections. It is also used in equations for momentum, force, and torque. Additionally, the scalar product can be used to determine whether two vectors are perpendicular or parallel to each other.
The tensor product is different from matrix multiplication in several ways. First, the tensor product allows for the combination of vectors and matrices of different dimensions, while matrix multiplication requires the matrices to have the same number of rows and columns. Additionally, the tensor product is not associative, meaning that the order of multiplication matters, while matrix multiplication is associative.
The concept of scalar and tensor products has applications in many fields of science, including physics, engineering, and mathematics. In physics, they are used in mechanics, electromagnetism, and quantum mechanics. In engineering, they are used in areas such as structural analysis and fluid mechanics. In mathematics, they are used in linear algebra, differential geometry, and tensor calculus.