Simulation ยท Analysis
qDRIFT averaged-channel induced trace-norm error
Theorem statement
Let $d,m,N$ be positive integers, $B,t\geq0$,
$H_1,\ldots,H_m\in\mathbb{C}^{d\times d}$ be Hermitian
matrices with $\|H_j\|\leq B$, and $h_1,\ldots,h_m\geq0$
satisfy $\lambda=\sum_{j=1}^{m}h_j>0$.
Set $p_j=h_j/\lambda$ and $T=t\lambda$, and define
$E(X)=\sum_{j=1}^{m}p_j e^{-i(T/N)H_j}X e^{i(T/N)H_j}$
and
$U(X)=e^{-i(T/N)\sum_{j=1}^{m}p_jH_j}
X e^{i(T/N)\sum_{j=1}^{m}p_jH_j}$
for $X\in\mathbb{C}^{d\times d}$.
Then
$$
\|U^N-E^N\|_{1\to1}
\leq
B^2\left(e^{TB}(2+TB)+2\right)\frac{T^2}{N},
$$
where powers denote repeated composition,
$\|M\|=\sup\{\|Mv\|_2:v\in\mathbb{C}^d,\ \|v\|_2\leq1\}$,
$\|X\|_1=\operatorname{Tr}\sqrt{X^\dagger X}$,
and
$\|\Phi\|_{1\to1}=\sup_{\|X\|_1\leq1}\|\Phi(X)\|_1$.
Sources
- A random compiler for fast Hamiltonian simulation
Earl Campbell, 2019
Lean context
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QuantumAlg.Analysis.QDrift
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