rehap

\[ I = \begin{pmatrix} 1 & 0\\ 0 & 1 \end{pmatrix} X = \begin{pmatrix} 0 & 1\\ 1 & 0 \end{pmatrix} H = \frac{1}{\sqrt{2}} \begin{pmatrix} 1 & 1\\ 1 & -1 \end{pmatrix} \] \[ Y = \begin{pmatrix} 0 & -i\\ i & 0 \end{pmatrix} Z = \begin{pmatrix} 1 & 0\\ 0 & -1 \end{pmatrix} S = \begin{pmatrix} 1 & 0\\ 0 & i \end{pmatrix} \] \[ CNOT = \begin{pmatrix} 1 & 0 & 0 & 0 \\ 0 & 1 & 0 & 0 \\ 0 & 0 & 0 & 1 \\ 0 & 0 & 1 & 0 \end{pmatrix} \] \[ \begin{aligned} & XY = iZ \\ & YZ = iX \\ & ZX = iY \\ & YX = -iZ \\ & ZY = -iX \\ & XZ = -iY \\ & X^2 = Y^2 = Z^2 = I \end{aligned} \]

Gottesman-Knill Theorem:

Quantum circuit consisting only of CNOT, H, S, measurement on computational basis can be simulated efficiently on a classical computer

Pauli Group

\[ \{ \pm 1, \pm i \} \{ I, X, Y, Z \} \]

Pauli Group on \(n\) qubits:

\[ P_n = \{ \pm 1, \pm i \} \{ X^{a_1} Z^{b_1} \otimes X^{a_2} Z^{b_2} \otimes \cdots \otimes X^{a_n} Z^{b_n} \} \]

Clifford Group on \(n\) qubits:

\[ C_n : C_n P_n C_n^{\dagger} = P_n \]

up to complex phases.

more specifically

\[ \forall p \in P_n, \forall c \in C_n, cpc^{\dagger} \in P_n \]

up to complex phases.

\(C_n\) is generated by H, S and CNOT

Intuitive example:

\[ HXH^{\dagger} = Z \] \[ CNOT(X \otimes I) CNOT^{\dagger} = X \otimes X \]

Stabilizer Group of quantum state \(\ket{\psi}\)

\[ \text{Stab}(\ket{\psi}) : \forall U \in \text{Stab}(\ket{\psi}), U\ket{\psi} = \ket{\psi} \]

Theorem 1 in the paper[1].

Given an n-qubits state \(\ket{\psi}\), the following are equivalent:

conclusion from group theory

Any finite group \(G\) has a generating set of size at most \(log_2|G|\)

if \(\ket{\psi}\) is a stabilizer states on n qubits, then the group \(\mathcal{S}_{P_n} := \text{Stab}(\ket{\psi}) \cap P_n\) of Pauli operators that stabilize \(\ket{\psi}\) has a generating set of size \(log_2 2^n = n\)

\(\text{Stab}(\ket{\psi})\) is a group

if \(U\ket{\psi} = \ket{\psi}\), \(V\ket{\psi} = \ket{\psi}\) then \(U^{\dagger}\ket{\psi} = \ket{\psi}\), \(UV\ket{\psi} = \ket{\psi}\)

\(\mathcal{S}_{P_n} := \text{Stab}(\ket{\psi}) \cap P_n\) is a group

indeed:

\[ \text{Stab}(\ket{\psi}) \subset P_n \]

so

\[ \text{Stab}(\ket{\psi}) \cap P_n = \text{Stab}(\ket{\psi}) \]

which is a group

recall

\[ C_n : C_n P_n C_n^{\dagger} = P_n \]

up to complex phases.

So \(\mathcal{S}_{P_n}\) is our stabilizer groups (which is a subgroup of Pauli group), \(C_n\) is the set of circuits that builds up clifford group (i.e. clifford circuits)

this tells us that clifford circuits transform a state stabilized by \(\mathcal{S}_{P_n}^{(i)} \sub P_n\) into another state stabilized by \(\mathcal{S}_{P_n}^{(j)} \sub P_n\), such states form a closed algebra structure.

It can be easily shown that there is one-one corespondence between \(C_n\) and the states.

Example:

| \(\ket{\psi}\) | \(P_n\) | | – | – | | \(\ket{0}^{\otimes n}\) | \(Z^{\otimes n}\) | | \(C_n \ket{0}^{\otimes n}\) | \(C_n Z^{\otimes n} C_n^{\dagger}\) |

To show why:

\[ \begin{aligned} S\ket{\psi} &= \ket{\psi} \\ C_n S C_n^{\dagger} C_n \ket{\psi} &= C_n \ket{\psi} \end{aligned} \]

i.e.

\[ \frac {\vdash S \in \mathcal{S}_{P_n}(\ket{\psi})} {\vdash C_n S C_n^{\dagger} \in \mathcal{S}_{P_n}(C_n\ket{\psi})} \]

revisiting \(\mathcal{S}_{P_n} := \text{Stab}(\ket{\psi}) \cap P_n\)

\[ P_n = \{ \pm 1, \pm i \} \{ X^{a_1} Z^{b_1} \otimes X^{a_2} Z^{b_2} \otimes \cdots \otimes X^{a_n} Z^{b_n} \} \] \[ \mathcal{S}_{P_n} = \{ \pm 1\} \{ X^{a_1} Z^{b_1} \otimes X^{a_2} Z^{b_2} \otimes \cdots \otimes X^{a_n} Z^{b_n} \} \]

To show Why:

if we do not add the restriction, then:

\[ \mathcal{S}_{P_n} \mathcal{S}_{P_n}^{\dagger} := (\pm i)^2 \{\}\{\}^{\dagger} = -I^{\otimes n} \]

is not unitary, which is forbidden.

Example:

\[ \begin{aligned} Y &= i X Z \\ SYS^{\dagger} &= iYZ = -X \end{aligned} \]

Tablue Algorithm:

Representing state generated by clifford circuits using its set of stabilizer generators: \(\mathcal{S}_{P_n}\)

Example:

\[ \begin{aligned} S :& X \to Y & Z \to Z \\ H : & X \to Z & Z \to X \\ CNOT : & X_1 \to X_1 X_2 & X_2 \to X_2 \\ & Z_1 \to Z_1 & Z_2 \to Z_1 Z_2 \\ X : & X \to X & Z \to -Z \\ Y : & X \to -X & Z \to -Z \end{aligned} \]

For \(n\) qubits states, \(\mathcal{S}_{P_n}\) contains \(n\) Pauli strings, each Pauli string can be represented using \(2n\) bits.

\[ \begin{pmatrix} X_{11} & \cdots & X_{1n} & | & Z_{11} & \cdots & Z_{1n} & | & r_1 \\ \vdots & & \vdots & | & \vdots & & \vdots & | & \vdots \\ X_{n1} & \cdots & X_{nn} & | & Z_{n1} & \cdots & Z_{nn} & | & r_n \\ \end{pmatrix} \begin{matrix} R_1 \\ \vdots \\ R_n \end{matrix} \]

each row represents a stabilizer.

Example:

2-qubit \(\ket{00}\):

\[ \begin{pmatrix} 0 & 0 & | & 1 & 0 & | & 0 \\ 0 & 0 & | & 0 & 1 & | & 0 \\ \end{pmatrix} \begin{matrix} R_1 \\ R_2 \end{matrix} \]

the group multiply operation can be done with XOR:

\[ [g_{R_1} * g_{R_2}]_{rep} := R_1 \oplus R_2 \] \[\begin{aligned} \oplus: & 0 \oplus 0 = 0 & & I I = I \\ & 0 \oplus 1 = 1 & & I P = P \\ & 1 \oplus 0 = 1 & & P I = P\\ & 1 \oplus 1 = 0 & & P P = I \end{aligned} \]

two row operation can be safely applied without disturbing the state(i.e. the symmetry introduced with this algebra structure)

update rule for CNOT, H, S

to be continue

update rule for measurement:

suppose we have a single measurement on computational basis onto qubit \(a\): \(Z_a\)

check if \(\exist k, X_{ka}=1\) in the tablue:

if yes:

the measurement is random.

we can reduce the number of such \(k\) to be exactly one:

if there is another \(p\) s.t. \(X_{pa}=1\), we can:

do \(R_p = R_k \oplus R_p\) so that \(X_{pa}\) is canceled out.

then we know

if no:

the measurement is determinant.

\[ \forall k, R_k Z_a = Z_a R_k \]

\(\pm Z_a\) is also a stabilizer of \(\ket{\psi}\)

but \(+1\) or \(-1\)?

\[ \exist \{i, j, k .. l\} s.t. \prod_{p \in \{i, j, k .. l\}} R_p = Z_a \text{or} -Z_a \]

how to get this?

\[ R'_i = (X_{i1} \cdots X_{in} | Z_{i1} \cdots Z_{in}) \]

we need to solve:

\[ R' B = Z_a \]

solving this equation using Gaussian elimination requires \(\mathcal{O}(n^3)\)

CHP improvement

destabilizer

the update rule for stabilizers also works for destabilizers

using destabilizer to help keeping track of phases

recall

\[ \exist \{i, j, k .. l\} s.t. \prod_{p \in \{i, j, k .. l\}} R_p = Z_a \text{or} -Z_a \]

\(Z_a\) will anticommute with \(R_i, i \in \{1 .. n\}\) iff \({i+n}\) is in the generator list of \(\{i, j, k .. l\}\) to produce \(\pm Z_a\)

Demo:

\[ \begin{aligned} & R_i R_{i+n} = (-1) R_{i+n} R_{i} \\ & \text{suppose:} Z_a = R_i R_j R_k ... R_l \\ \end{aligned} \] \[ \begin{aligned} Z_a R_{i+n} & = R_i R_j R_k ... R_l R_{i+n} \\ &= R_i R_{i+n} R_j R_k ... R_l \\ &= (-1) R_{i+n} R_i R_j R_k ... R_l \end{aligned} \]

the procedure is simple

This algorithm is of order \(\mathcal{O}(n^2)\)

reference

[1] S. Aaronson and D. Gottesman, “Improved Simulation of Stabilizer Circuits”.

[2] "An Introduction to Stabilizer Circuit Simulation"

[3] V. Gheorghiu, “Efficient simulation of quantum computers: the Gottesman-Knill theorem or an application of group theory to quantum information (part 2),” . . ..

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