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Documentation for Generalized Stabilizer Representation
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3 changes: 3 additions & 0 deletions docs/make.jl
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Expand Up @@ -41,6 +41,9 @@ pages = [
"Circuit Operations" => "noisycircuits_ops.md",
"API" => "noisycircuits_API.md"
],
"Generalized Stabilizer" => [
"Overview" => "genstab.md",
],
"ECC compendium" => [
"Evaluating codes and decoders" => "ECC_evaluating.md"
"API" => "ECC_API.md"
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81 changes: 81 additions & 0 deletions docs/src/genstab.md
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# [Generalized Stabilizer Representation](@id Generalized-Stabilizer-Overview)

Gottesman's introduction of stabilizer formalism in 1997 greatly impacted quantum complexity and coding
theory.The Heisenberg representation[^1], vital to the Gottesman-Knill theorem, enables classical simulations
to use fewer Pauli operators, easing computational demands. However, this approach is limited to stabilizer
circuits with Clifford gates and measurements. While effective, the theorem has a narrow scope, making it
essential to generalize it for broader quantum circuit simulations. Theodore Yoder[^2] introduces a generalized
stabilizer representation to address this challenge.

## Advances in Stabilizer Formalism

Since its inception, the stabilizer formalism has undergone several improvements. Notable enhancements include:

```@raw html
<div class="mermaid">
timeline
title Related Work in Generalization of the Gottesman-Knill Theorem
1997 : Gottesman [3] introduces stabilizer formalism and the Gottesman-Knill theorem.
2002 : Bartlett et al. [4] expand to continuous variable quantum computation.
2004 : Aaronson and Gottesman [5] improve measurement time complexity to 𝒪(n²).
2006 : Anders and Briegel [6] achieve 𝒪(n log n) speedup in time complexity with graph states.
2012 : Bermejo-Vega and Van den Nest [7] generalize to any finite Abelian group from n-qubits ℤ₂ⁿ.
2012 : Yoder [2] presents the Generalized Stabilizer with a novel state representation.
</div>
```

## Generalized Stabilizer Representation

The generalized stabilizer representation provides a flexible framework for simulating quantum circuits by:

- Enabling the representation of any quantum state, pure or mixed.
- Allowing simulations of arbitrary quantum circuits, including unitary operations, measurements, and
quantum channels.

This representation expands on the stabilizer formalism by incorporating non-stabilizer states and circuits,
enabling the simulation of non-Clifford gates and broader quantum channels for diverse quantum computations.

Unlike previous methods that may use a superposition of stabilizer states to represent arbitrary states,
this approach employs the tableau construction developed by Aaronson and Gottesman[^3]. This method implicitly
represents a set of orthogonal stabilizer states, forming a stabilizer basis capable of representing arbitrary
quantum states.Updating the tableau takes only twice as long as updating a single stabilizer, enabling efficient
updates of the entire stabilizer basis with minimal computational overhead.

## Simulation of Quantum Channels

The generalized stabilizer representation enables the simulation of arbitrary quantum channels, beyond just
unitary gates and measurements. It does this by decomposing the Kraus operators of a channel into Pauli operators
from the state’s tableau, allowing for a broader range of quantum operations.

## Advantages of the Generalized Stabilizer

The proposed representation combines the rapid update capabilities of stabilizer states with the generality of
density matrices. Key features include:

- High update efficiency for unitary gates, measurements, and quantum channels, influenced by the sparsity of
the density matrix, `Λ(χ)`, which indicates the count of non-zero elements in `χ`.

- Simulations maintain linear complexity with respect to the number of measurements, and the representation
remains straightforward, reflecting the principle that measurements simplify quantum states through collapse.

## Implications for Classical and Quantum Computation

Investigating stabilizer circuits enhances our understanding of classical and quantum computation. Simulating these
circuits is a complete problem in the classical complexity class `⊕L`, a subset of `P`, indicating that stabilizer
circuits may not be universal in classical computation contexts. Surprisingly, adding just one non-Clifford gate to
circuits with Clifford gates and measurements generally enables universal quantum computation—a contrast that highlights
intriguing questions about the computational boundaries between classical and quantum systems.

[^1]: [gottesman1998heisenberg](@cite)

[^2]: [yoder2012generalization](@cite)

[^3]: [gottesman1997stabilizer](@cite)

[^4]: [bartlett2002efficient](@cite)

[^5]: [aaronson2004improved](@cite)

[^6]: [anders2006fast](@cite)

[^7]: [bermejo2012classical](@cite)
39 changes: 39 additions & 0 deletions docs/src/references.bib
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Expand Up @@ -191,6 +191,45 @@ @article{nahum2017quantum
year = {2017}
}

% Generalized Stabilizer
@article{yoder2012generalization,
title={A generalization of the stabilizer formalism for simulating arbitrary quantum circuits},
author={Yoder, Theodore J},
journal={See http://www. scottaaronson. com/showcase2/report/ted-yoder. pdf},
year={2012},
publisher={Citeseer}
}

@article{bartlett2002efficient,
title={Efficient classical simulation of continuous variable quantum information processes},
author={Bartlett, Stephen D and Sanders, Barry C and Braunstein, Samuel L and Nemoto, Kae},
journal={Physical Review Letters},
volume={88},
number={9},
pages={097904},
year={2002},
publisher={APS}
}

@article{anders2006fast,
title={Fast simulation of stabilizer circuits using a graph-state representation},
author={Anders, Simon and Briegel, Hans J},
journal={Physical Review A?Atomic, Molecular, and Optical Physics},
volume={73},
number={2},
pages={022334},
year={2006},
publisher={APS}
}

@article{bermejo2012classical,
title={Classical simulations of Abelian-group normalizer circuits with intermediate measurements},
author={Bermejo-Vega, Juan and Nest, Maarten Van den},
journal={arXiv preprint arXiv:1210.3637},
year={2012}
}

% codes
@article{mackay2004sparse,
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