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	<meta name="DC.Creator.PersonalName" content="Aline Duarte Bessa"/>
	<meta name="DC.Creator.PersonalName" content="Ivan Carmo Rocha-Neto"/>
	<meta name="DC.Creator.PersonalName" content="Suani Tavares Rubim de Pinho"/>
	<meta name="DC.Creator.PersonalName" content="Roberto Fernandes Silva Andrade"/>
	<meta name="DC.Creator.PersonalName" content="Thierry Correa Petit Lobao"/>
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	<meta name="DC.Description" xml:lang="en" content="In this note we address the problem of graph isomorphism by means of eigenvalue spectra of different matrix representations:  the neighborhood matrix $\hat{M}$, its corresponding signless Laplacian $Q_{\hat{M}}$, and the set of higher order adjacency matrices $M_{\ell}$s. We find that, in relation to graphs with at most 10 vertices, $Q_{\hat{M}}$ leads to better results than the signless Laplacian $Q$; besides, when combined with $\hat{M}$, it even surpasses the Godsil and McKay switching method."/>
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	<div id="articleTitle"><h3>Graph Cospectrality using Neighborhood Matrices</h3></div>
	<div id="authorString"><em>Aline Duarte Bessa, Ivan Carmo Rocha-Neto, Suani Tavares Rubim de Pinho, Roberto Fernandes Silva Andrade, Thierry Correa Petit Lobao</em></div>
	<br />
			<div id="articleAbstract">
		<h4>Abstract</h4>
		<br />
		<div>In this note we address the problem of graph isomorphism by means of eigenvalue spectra of different matrix representations:  the neighborhood matrix $\hat{M}$, its corresponding signless Laplacian $Q_{\hat{M}}$, and the set of higher order adjacency matrices $M_{\ell}$s. We find that, in relation to graphs with at most 10 vertices, $Q_{\hat{M}}$ leads to better results than the signless Laplacian $Q$; besides, when combined with $\hat{M}$, it even surpasses the Godsil and McKay switching method.</div>
		<br />
		</div>
	
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		<h4>Keywords</h4>
		<br />
		<div>graph theory; cospectrality; neighborhood</div>
		<br />
		</div>
	
	
				
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