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For a graph $G$, let its Laplacian be $\Delta = I - D^{-1/2}AD^{-1/2}$, where $A$ is the adjacency matrix, $I$ is the identity matrix and $D$ is the diagonal matrix with vertex degrees. I'm interested in the spectral gap of $G$, i.e. the first nonzero eigenvalue of $\Delta$, denoted by $\lambda_{1}(G)$.

Is it true that a randomly chosen (with uniform distribution) $d$-regular bipartite graph on $(n, n)$ vertices (with multiple edges allowed) has, with probability approaching $1$ as $n \to \infty$, $\lambda_1$ arbitrarily close to $1$ (i.e. we can make arbitrarily close by taking $d$ large enough)?

If yes, is there a reference for this fact?

Proofs of expanding properties for random regular graphs which I have found in the literature usually give the probability only bounded from below by a constant, i. e. $1/2$, although I imagine that actually almost all random graphs have good spectral gap.

Note: by $d$-regular bipartite graph I mean a graph in which each vertex (on the left and on the right) has degree $d$.

For a graph $G$, let its Laplacian be $\Delta = I - D^{-1/2}AD^{-1/2}$, where $A$ is the adjacency matrix, $I$ is the identity matrix and $D$ is the diagonal matrix with vertex degrees. I'm interested in the spectral gap of $G$, i.e. the first nonzero eigenvalue of $\Delta$, denoted by $\lambda_{1}(G)$.

Is it true that a randomly chosen (with uniform distribution) $d$-regular bipartite graph on $(n, n)$ vertices has, with probability approaching $1$ as $n \to \infty$, $\lambda_1$ arbitrarily close to $1$ (i.e. we can make arbitrarily close by taking $d$ large enough)?

If yes, is there a reference for this fact?

Proofs of expanding properties for random regular graphs which I have found in the literature usually give the probability only bounded from below by a constant, i. e. $1/2$, although I imagine that actually almost all random graphs have good spectral gap.

Note: by $d$-regular bipartite graph I mean a graph in which each vertex (on the left and on the right) has degree $d$.

For a graph $G$, let its Laplacian be $\Delta = I - D^{-1/2}AD^{-1/2}$, where $A$ is the adjacency matrix, $I$ is the identity matrix and $D$ is the diagonal matrix with vertex degrees. I'm interested in the spectral gap of $G$, i.e. the first nonzero eigenvalue of $\Delta$, denoted by $\lambda_{1}(G)$.

Is it true that a randomly chosen (with uniform distribution) $d$-regular bipartite graph on $(n, n)$ vertices (with multiple edges allowed) has, with probability approaching $1$ as $n \to \infty$, $\lambda_1$ arbitrarily close to $1$ (i.e. we can make arbitrarily close by taking $d$ large enough)?

If yes, is there a reference for this fact?

Proofs of expanding properties for random regular graphs which I have found in the literature usually give the probability only bounded from below by a constant, i. e. $1/2$, although I imagine that actually almost all random graphs have good spectral gap.

Note: by $d$-regular bipartite graph I mean a graph in which each vertex (on the left and on the right) has degree $d$.

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For a graph $G$, let its Laplacian be $\Delta = I - D^{-1/2}AD^{-1/2}$, where $A$ is the adjacency matrix, $I$ is the identity matrix and $D$ is the diagonal matrix with vertex degrees. I'm interested in the spectral gap of $G$, i.e. the first nonzero eigenvalue of $\Delta$, denoted by $\lambda_{1}(G)$.

Is it true that a randomly chosen (with uniform distribution) $d$-regular bipartite graph on $(n, n)$ vertices has, with probability approaching $1$ as $n \to \infty$, $\lambda_1$ arbitrarily close to $1$ (i.e. we can make arbitrarily close by taking $d$ large enough)?

If yes, is there a reference for this fact?

Proofs of expanding properties for random regular graphs which I have found in the literature usually give the probability only bounded from below by a constant, i. e. $1/2$, although I imagine that actually almost all random graphs have good spectral gap.

Note: by $d$-regular bipartite graph I mean a graph in which each vertex on one side has degree $d$ (and there are no restrictions onon the verticesleft and on the other sideright), although the standard notion of regularity (all vertices have has degree $d$) is also OK.

For a graph $G$, let its Laplacian be $\Delta = I - D^{-1/2}AD^{-1/2}$, where $A$ is the adjacency matrix, $I$ is the identity matrix and $D$ is the diagonal matrix with vertex degrees. I'm interested in the spectral gap of $G$, i.e. the first nonzero eigenvalue of $\Delta$, denoted by $\lambda_{1}(G)$.

Is it true that a randomly chosen (with uniform distribution) $d$-regular bipartite graph on $(n, n)$ vertices has, with probability approaching $1$ as $n \to \infty$, $\lambda_1$ arbitrarily close to $1$ (i.e. we can make arbitrarily close by taking $d$ large enough)?

If yes, is there a reference for this fact?

Proofs of expanding properties for random regular graphs which I have found in the literature usually give the probability only bounded from below by a constant, i. e. $1/2$, although I imagine that actually almost all random graphs have good spectral gap.

Note: by $d$-regular bipartite graph I mean a graph in which each vertex on one side has degree $d$ (and there are no restrictions on the vertices on the other side), although the standard notion of regularity (all vertices have degree $d$) is also OK.

For a graph $G$, let its Laplacian be $\Delta = I - D^{-1/2}AD^{-1/2}$, where $A$ is the adjacency matrix, $I$ is the identity matrix and $D$ is the diagonal matrix with vertex degrees. I'm interested in the spectral gap of $G$, i.e. the first nonzero eigenvalue of $\Delta$, denoted by $\lambda_{1}(G)$.

Is it true that a randomly chosen (with uniform distribution) $d$-regular bipartite graph on $(n, n)$ vertices has, with probability approaching $1$ as $n \to \infty$, $\lambda_1$ arbitrarily close to $1$ (i.e. we can make arbitrarily close by taking $d$ large enough)?

If yes, is there a reference for this fact?

Proofs of expanding properties for random regular graphs which I have found in the literature usually give the probability only bounded from below by a constant, i. e. $1/2$, although I imagine that actually almost all random graphs have good spectral gap.

Note: by $d$-regular bipartite graph I mean a graph in which each vertex (on the left and on the right) has degree $d$.

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For a graph $G$, let its Laplacian be $\Delta = I - D^{-1/2}AD^{-1/2}$, where $A$ is the adjacency matrix, $I$ is the identity matrix and $D$ is the diagonal matrix with vertex degrees. I'm interested in the spectral gap of $G$, i.e. the first nonzero eigenvalue of $\Delta$, denoted by $\lambda_{1}(G)$.

Is it true that a randomly chosen (with uniform distribution) $d$-regular bipartite graph on $(n, n)$ vertices has, with probability approaching $1$ as $n \to \infty$, $\lambda_1$ arbitrarily close to $1$ (i.e. we can make arbitrarily close by taking $d$ large enough)?

If yes, is there a reference for this fact?

Proofs of expanding properties for random regular graphs which I have found in the literature usually give the probability only bounded from below by a constant, i. e. $1/2$, although I imagine that actually almost all random graphs have good spectral gap.

Note: by $d$-regular bipartite graph I mean a graph in which each vertex on one side has degree $d$ (and there are no restrictions on the vertices on the other side), although the standard notion of regularity (all vertices have degree $d$) is also OK.

For a graph $G$, let its Laplacian be $\Delta = I - D^{-1/2}AD^{-1/2}$, where $A$ is the adjacency matrix, $I$ is the identity matrix and $D$ is the diagonal matrix with vertex degrees. I'm interested in the spectral gap of $G$, i.e. the first nonzero eigenvalue of $\Delta$, denoted by $\lambda_{1}(G)$.

Is it true that a randomly chosen (with uniform distribution) $d$-regular bipartite graph on $(n, n)$ vertices has, with probability approaching $1$ as $n \to \infty$, $\lambda_1$ arbitrarily close to $1$ (i.e. we can make arbitrarily close by taking $d$ large enough)?

If yes, is there a reference for this fact?

Proofs of expanding properties for random regular graphs which I have found in the literature usually give the probability only bounded from below by a constant, i. e. $1/2$, although I imagine that actually almost all random graphs have good spectral gap.

Note: by $d$-regular bipartite graph I mean a graph in which each vertex on one side has degree $d$ (and there are no restrictions on the vertices on the other side).

For a graph $G$, let its Laplacian be $\Delta = I - D^{-1/2}AD^{-1/2}$, where $A$ is the adjacency matrix, $I$ is the identity matrix and $D$ is the diagonal matrix with vertex degrees. I'm interested in the spectral gap of $G$, i.e. the first nonzero eigenvalue of $\Delta$, denoted by $\lambda_{1}(G)$.

Is it true that a randomly chosen (with uniform distribution) $d$-regular bipartite graph on $(n, n)$ vertices has, with probability approaching $1$ as $n \to \infty$, $\lambda_1$ arbitrarily close to $1$ (i.e. we can make arbitrarily close by taking $d$ large enough)?

If yes, is there a reference for this fact?

Proofs of expanding properties for random regular graphs which I have found in the literature usually give the probability only bounded from below by a constant, i. e. $1/2$, although I imagine that actually almost all random graphs have good spectral gap.

Note: by $d$-regular bipartite graph I mean a graph in which each vertex on one side has degree $d$ (and there are no restrictions on the vertices on the other side), although the standard notion of regularity (all vertices have degree $d$) is also OK.

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