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---
title: "Gram-Schmidt method"
sort_title: "Gram-Schmidt method"
date: 2021-02-22
categories:
- Mathematics
- Algorithms
layout: "concept"
---
Given a set of linearly independent non-orthonormal vectors
$$\ket{V_1}, \ket{V_2}, ...$$ from a [Hilbert space](/know/concept/hilbert-space/),
the **Gram-Schmidt method**
turns them into an orthonormal set $$\ket{n_1}, \ket{n_2}, ...$$ as follows:
1. Take the first vector $$\ket{V_1}$$ and normalize it to get $$\ket{n_1}$$:
$$\begin{aligned}
\ket{n_1} = \frac{\ket{V_1}}{\sqrt{\inprod{V_1}{V_1}}}
\end{aligned}$$
2. Begin loop. Take the next non-orthonormal vector $$\ket{V_j}$$, and
subtract from it its projection onto every already-processed vector:
$$\begin{aligned}
\ket{n_j'} = \ket{V_j} - \ket{n_1} \inprod{n_1}{V_j} - \ket{n_2} \inprod{n_2}{V_j} - ... - \ket{n_{j-1}} \inprod{n_{j-1}}{V_{j-1}}
\end{aligned}$$
This leaves only the part of $$\ket{V_j}$$ which is orthogonal to
$$\ket{n_1}$$, $$\ket{n_2}$$, etc. This why the input vectors must be
linearly independent; otherwise $$\Ket{n_j'}$$ may become zero at some
point.
3. Normalize the resulting ortho*gonal* vector $$\ket{n_j'}$$ to make it
ortho*normal*:
$$\begin{aligned}
\ket{n_j} = \frac{\ket{n_j'}}{\sqrt{\inprod{n_j'}{n_j'}}}
\end{aligned}$$
4. Loop back to step 2, taking the next vector $$\ket{V_{j+1}}$$.
If you are unfamiliar with this notation, take a look at [Dirac notation](/know/concept/dirac-notation/).
## References
1. R. Shankar,
*Principles of quantum mechanics*, 2nd edition,
Springer.
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