We consider a class of sparse random matrices which includes the adjacency matrix of the Erdős-Rényi graph
. We show that if
N^{\varepsilon} \leq Np \leq N^{1/3-\varepsilon}
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then all nontrivial eigenvalues away from 0 have asymptotically Gaussian fluctuations. These fluctuations are governed by a single random variable, which has the interpretation of the total degree of the graph. This extends the result [19] on the fluctuations of the extreme eigenvalues from
Np \geq N^{2/9 + \varepsilon}
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down to the optimal scale
. The main technical achievement of our proof is a rigidity bound of accuracy
N^{-1/2-\varepsilon} \, (Np)^{-1/2}
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for the extreme eigenvalues, which avoids the
-expansions from [9,19,24]. Our result is the last missing piece, added to [8, 12, 19, 24], of a complete description of the eigenvalue fluctuations of sparse random matrices for
.