From d77b6b03256f8b254b4550e5374a6b8228c97c0a Mon Sep 17 00:00:00 2001 From: "Kevin J. Sung" Date: Thu, 23 Jan 2025 08:07:30 -0500 Subject: [PATCH] fix doc link (#53) --- docs/tutorials/01_getting_started.ipynb | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/docs/tutorials/01_getting_started.ipynb b/docs/tutorials/01_getting_started.ipynb index cb42503..3137882 100644 --- a/docs/tutorials/01_getting_started.ipynb +++ b/docs/tutorials/01_getting_started.ipynb @@ -269,7 +269,7 @@ "\n", "Determining the static MPF coefficients for a given set of $k_j$ values amounts to solving a linear system of equations:\n", "$Ax=b$, where $x$ are our coefficients of interest, $A$ is a matrix depending on $k_j$ and the type of PF we use ($S$), and $b$ is a vector of constraints.\n", - "For brevity, we are not going to go into more detail here and instead refer you to the documentation of [LSE](https://qiskit.github.io/qiskit-addon-mpf/stubs/qiskit_addon_mpf.costs.LSE.html).\n", + "For brevity, we are not going to go into more detail here and instead refer you to the documentation of [LSE](https://qiskit.github.io/qiskit-addon-mpf/apidocs/qiskit_addon_mpf.costs.html#qiskit_addon_mpf.costs.LSE).\n", "\n", "We can find a solution for $x$ analytically as $x = A^{-1}b$, see e.g. [Carrera Vazquez et al., 2023] or [Zhuk et al., 2023].\n", "However, this exact solution can be _\"ill-conditioned\"_ resulting in very large L1-norms of our coefficients, $x$, which can lead to bad performance of the MPF.\n",