Table 1 \(\left\{ {A_{{\mathrm{nt}}},\alpha _{{\mathrm{nt}}}} \right\}\) values for networks obtained by fitting the power law \({\it \Gamma} _{{\mathrm{nt}}} = A_{{\mathrm{nt}}}I^{\alpha _{{\mathrm{nt}}}}\) onto the curves of Fig. 2

From: Emergence of winner-takes-all connectivity paths in random nanowire networks

\({\boldsymbol{A}}_{\mathbf{j}}\)

0.01

0.05

0.1

0.5

\({\boldsymbol{\alpha }}_{\mathbf{j}} = 0.9\)

{0.0027,0.892}

{0.0133,0.896}

{0.0266,0.9}

{0.1407,0.925}

\({\boldsymbol{\alpha }}_{\mathbf{j}} = 1.0\)

{0.0025,1.0}

{0.0125,1.0}

{0.0251,1.0}

{0.13071,1.024}

\({\boldsymbol{\alpha }}_{\mathbf{j}} = 1.1\)

{0.0024,1.115}

{0.0125,1.115}

{0.0251,1.113}

{0.13941,1.159}

\(\langle{\boldsymbol{\alpha }}_{\mathbf{j}}\rangle = 1.05\)

{0.0025,1.054}

{0.0125,1.049}

{0.0251,1.051}

{0.1323,1.071}

  1. All junctions in a given network are set to have the same prefactor and exponent except for the heterogeneous case in which a narrow dispersion was induced in the exponents using a truncated normal distribution with mean value of αj. Note the strong correlation between αnt and αj.