Fit of elastic ($m_Y=m_p$) and proton-dissociative ($1<m_Y<10$ GeV) $\pi^{+}\pi^{-}$ photoproduction off protons with a Soeding-inspired analytic function --- statistical correlations only. Only one half of the (symmetric) matrix is stored.

Elastic ($m_Y=m_p$) and proton-dissociative ($1<m_Y<10$ GeV) $\pi^{+}\pi^{-}$ photoproduction off protons, differential in the dipion mass and in bins of $W$. The tabulated cross sections are $\gamma p$ cross sections but can be converted to $ep$ cross sections using the effective photon flux $\Phi_{\gamma/e}$.

Elastic ($m_Y=m_p$) and proton-dissociative ($1<m_Y<10$ GeV) $\pi^{+}\pi^{-}$ photoproduction off protons, differential in the dipion mass and in bins of $W$ --- statistical correlations coefficients $\rho_{ij}$ only. Only one half of the (symmetric) matrix is stored. Bins are identified by their global bin number.

Elastic ($m_Y=m_p$) and proton-dissociative ($1<m_Y<10$ GeV) $\rho^0(770)$ photoproduction off protons, in bins of the photon-proton energy $W$. The cross section is defined as the integral of the relativistic Breit Wigner resonance in the dipion mass over the range $2m_\pi<m_{\pi\pi}<1.53$ GeV. The tabulated cross sections are $\gamma p$ cross sections but can be converted to $ep$ cross sections using the effective photon flux $\Phi_{\gamma/e}$.

Elastic ($m_Y=m_p$) and proton-dissociative ($1<m_Y<10$ GeV) $\rho^0(770)$ photoproduction off protons in bins of the photon-proton energy $W$ --- statistical correlations coefficients $\rho_{ij}$ only. Only one half of the (symmetric) matrix is stored. Bins are identified by their global bin number.

Fit of elastic ($m_Y=m_p$) and proton-dissociative ($1<m_Y<10$ GeV) $\rho^0(770)$ photoproduction cross sections off protons as a function of energy. Parameters with subscript "el" and "pd" correspond to elastic and proton-dissociative cross sections, respectively.

Fit of elastic ($m_Y=m_p$) and proton-dissociative ($1<m_Y<10$ GeV) $\rho^0(770)$ photoproduction cross sections off protons as a function of energy --- statistical correlations coefficients $\rho_{ij}$ only. Only one half of the (symmetric) matrix is stored. Bins are identified by their global bin number.

Fit of elastic $\rho^0(770)$ photoproduction cross section off protons as a function of energy (various experiments)

Fit of elastic $\rho^0(770)$ photoproduction cross sections off protons as a function of energy (various experiments) --- statistical correlations coefficients $\rho_{ij}$ only. Only one half of the (symmetric) matrix is stored. Bins are identified by their global bin number.

Elastic ($m_Y=m_p$) and proton-dissociative ($1<m_Y<10$ GeV) $\pi^{+}\pi^{-}$ photoproduction cross section off protons, double-differential in the dipion mass and the momentum transfer $\vert t\vert$. The tabulated cross sections are $\gamma p$ cross sections but can be converted to $ep$ cross sections using the effective photon flux $\Phi_{\gamma/e}$.

Elastic ($m_Y=m_p$) and proton-dissociative ($1<m_Y<10$ GeV) $\pi^{+}\pi^{-}$ photoproduction cross section off protons, double-differential in the dipion mass and the momentum transfer $\vert t\vert$ --- statistical correlations coefficients $\rho_{ij}$ only. Only one half of the (symmetric) matrix is stored. Bins are identified by their global bin number.

Elastic ($m_Y=m_p$) and proton-dissociative ($1<m_Y<10$ GeV) $\rho^0(770)$ photoproduction off protons, single-differential in the momentum transfer $\vert t\vert$. The cross section is defined as the integral of the relativistic Breit Wigner resonance in the dipion mass over the range $2m_\pi<m_{\pi\pi}<1.53$ GeV. The tabulated cross sections are $\gamma p$ cross sections but can be converted to $ep$ cross sections using the effective photon flux $\Phi_{\gamma/e}$.

Elastic ($m_Y=m_p$) and proton-dissociative ($1<m_Y<10$ GeV) $\rho^0(770)$ photoproduction off protons, single differential in the momentum transfer $\vert t\vert$ --- statistical correlations coefficients $\rho_{ij}$ only. Only one half of the (symmetric) matrix is stored. Bins are identified by their global bin number.

Fit of elastic ($m_Y=m_p$) and proton-dissociative ($1<m_Y<10$ GeV) $\rho^0(770)$ photoproduction single-differential cross sections off protons as a function of momentum transfer $t$. Parameters with subscript "el" and "pd" correspond to elastic and proton-dissociative cross sections, respectively.

Fit of elastic ($m_Y=m_p$) and proton-dissociative ($1<m_Y<10$ GeV) $\rho^0(770)$ photoproduction single-differential cross sections off protons as a function of momentum transfer $t$ --- statistical correlations coefficients $\rho_{ij}$ only. Only one half of the (symmetric) matrix is stored. Bins are identified by their global bin number.

Elastic ($m_Y=m_p$) and proton-dissociative ($1<m_Y<10$ GeV) $\pi^{+}\pi^{-}$ photoproduction double-differenial cross section off protons, as a function of the dipion mass and the momentum transfer $\vert t\vert$, in bins of the photon-proton energy $W$ The tabulated cross sections are $\gamma p$ cross sections but can be converted to $ep$ cross sections using the effective photon flux $\Phi_{\gamma/e}$.

Elastic ($m_Y=m_p$) and proton-dissociative ($1<m_Y<10$ GeV) $\pi^{+}\pi^{-}$ photoproduction double-differenial cross section off protons, as a function of the dipion mass and the momentum transfer $\vert t\vert$, in bins of the photon-proton energy $W$ --- statistical correlations coefficients $\rho_{ij}$ only. Only one half of the (symmetric) matrix is stored. Bins are identified by their global bin number.

Elastic ($m_Y=m_p$) and proton-dissociative ($1<m_Y<10$ GeV) $\rho^0(770)$ photoproduction off protons, single-differential in the momentum transfer $\vert t\vert$, in bins of the photon-proton energy $W$. The cross section is defined as the integral of the relativistic Breit Wigner resonance in the dipion mass over the range $2m_\pi<m_{\pi\pi}<1.53$ GeV. The tabulated cross sections are $\gamma p$ cross sections but can be converted to $ep$ cross sections using the effective photon flux $\Phi_{\gamma/e}$.

Elastic ($m_Y=m_p$) and proton-dissociative ($1<m_Y<10$ GeV) $\rho^0(770)$ photoproduction cross section off protons, single differential in the momentum transfer $\vert t\vert$ and in bins of the photon-proton energy $W$ --- statistical correlations coefficients $\rho_{ij}$ only. Only one half of the (symmetric) matrix is stored. Bins are identified by their global bin number.

Regge fit of elastic ($m_Y=m_p$) and proton-dissociative ($1<m_Y<10$ GeV) $\rho^0(770)$ photoproduction single-differential cross sections off protons as a function of momentum transfer $t$ and photon-proton energy $W$. Parameters with subscript "el" and "pd" correspond to elastic and proton-dissociative cross sections, respectively.

Regge fit of elastic ($m_Y=m_p$) and proton-dissociative ($1<m_Y<10$ GeV) $\rho^0(770)$ photoproduction single-differential cross sections off protons as a function of momentum transfer $t$ and photon-proton energy $W$ --- statistical correlations coefficients $\rho_{ij}$ only. Only one half of the (symmetric) matrix is stored. Bins are identified by their global bin number.

Fit of $b$-slopes in elastic ($m_Y=m_p$) $\rho^0(770)$ photoproduction single-differential cross sections off protons as a function of momentum transfer $t$ in bins of photon-proton energy $W$.

Fit of $b$-slopes in elastic ($m_Y=m_p$) $\rho^0(770)$ photoproduction single-differential cross sections off protons as a function of momentum transfer $t$ in bins of photon-proton energy $W$ --- statistical correlations coefficients $\rho_{ij}$ only. Only one half of the (symmetric) matrix is stored. Bins are identified by their global bin number.

Fit of Pomeron trajectories in elastic ($m_Y=m_p$) $\rho^0(770)$ photoproduction single-differential cross sections off protons as a function of momentum transfer $t$ in bins of photon-proton energy $W$.

Fit of Pomeron trajectories in elastic ($m_Y=m_p$) $\rho^0(770)$ photoproduction single-differential cross sections off protons as a function of momentum transfer $t$ in bins of photon-proton energy $W$ --- statistical correlations coefficients $\rho_{ij}$ only. Only one half of the (symmetric) matrix is stored. Bins are identified by their global bin number.

This table contains thinned out samples of the Markov chains used in the parameter estimation of the SDME measurements for $-(t-t_\text{0}) = 0.400\pm0.056~\text{GeV}^2/c^2$, reported in the main article. One in about 250 steps in the chain, which results in 200 different sets of SDMEs, is provided. These values should be used instead of bootstrapping of the results, in order to estimate uncertainties of physics models fitted to this data. To assess how the uncertainties propagate to the model uncertainties, one should evaluate the model under scrutiny for each of the 200 different sets of SDMEs. Plotting all resulting lines in a single plot will create bands which reflect the influence of the uncertainties in the data on the model. This method has the great advantage that all correlations are accurately taken into account.

This table contains thinned out samples of the Markov chains used in the parameter estimation of the SDME measurements for $-(t-t_\text{0}) = 0.597\pm0.057~\text{GeV}^2/c^2$, reported in the main article. One in about 250 steps in the chain, which results in 200 different sets of SDMEs, is provided. These values should be used instead of bootstrapping of the results, in order to estimate uncertainties of physics models fitted to this data. To assess how the uncertainties propagate to the model uncertainties, one should evaluate the model under scrutiny for each of the 200 different sets of SDMEs. Plotting all resulting lines in a single plot will create bands which reflect the influence of the uncertainties in the data on the model. This method has the great advantage that all correlations are accurately taken into account.

This table contains thinned out samples of the Markov chains used in the parameter estimation of the SDME measurements for $-(t-t_\text{0}) = 0.793\pm0.057~\text{GeV}^2/c^2$, reported in the main article. One in about 250 steps in the chain, which results in 200 different sets of SDMEs, is provided. These values should be used instead of bootstrapping of the results, in order to estimate uncertainties of physics models fitted to this data. To assess how the uncertainties propagate to the model uncertainties, one should evaluate the model under scrutiny for each of the 200 different sets of SDMEs. Plotting all resulting lines in a single plot will create bands which reflect the influence of the uncertainties in the data on the model. This method has the great advantage that all correlations are accurately taken into account.

This table contains thinned out samples of the Markov chains used in the parameter estimation of the SDME measurements for $-(t-t_\text{0}) = 0.992\pm0.058~\text{GeV}^2/c^2$, reported in the main article. One in about 250 steps in the chain, which results in 200 different sets of SDMEs, is provided. These values should be used instead of bootstrapping of the results, in order to estimate uncertainties of physics models fitted to this data. To assess how the uncertainties propagate to the model uncertainties, one should evaluate the model under scrutiny for each of the 200 different sets of SDMEs. Plotting all resulting lines in a single plot will create bands which reflect the influence of the uncertainties in the data on the model. This method has the great advantage that all correlations are accurately taken into account.

This table contains thinned out samples of the Markov chains used in the parameter estimation of the SDME measurements for $-(t-t_\text{0}) = 1.189\pm0.058~\text{GeV}^2/c^2$, reported in the main article. One in about 250 steps in the chain, which results in 200 different sets of SDMEs, is provided. These values should be used instead of bootstrapping of the results, in order to estimate uncertainties of physics models fitted to this data. To assess how the uncertainties propagate to the model uncertainties, one should evaluate the model under scrutiny for each of the 200 different sets of SDMEs. Plotting all resulting lines in a single plot will create bands which reflect the influence of the uncertainties in the data on the model. This method has the great advantage that all correlations are accurately taken into account.

This table contains thinned out samples of the Markov chains used in the parameter estimation of the SDME measurements for $-(t-t_\text{0}) = 1.435\pm0.086~\text{GeV}^2/c^2$, reported in the main article. One in about 250 steps in the chain, which results in 200 different sets of SDMEs, is provided. These values should be used instead of bootstrapping of the results, in order to estimate uncertainties of physics models fitted to this data. To assess how the uncertainties propagate to the model uncertainties, one should evaluate the model under scrutiny for each of the 200 different sets of SDMEs. Plotting all resulting lines in a single plot will create bands which reflect the influence of the uncertainties in the data on the model. This method has the great advantage that all correlations are accurately taken into account.

This table contains thinned out samples of the Markov chains used in the parameter estimation of the SDME measurements for $-(t-t_\text{0}) = 1.761\pm0.111~\text{GeV}^2/c^2$, reported in the main article. One in about 250 steps in the chain, which results in 200 different sets of SDMEs, is provided. These values should be used instead of bootstrapping of the results, in order to estimate uncertainties of physics models fitted to this data. To assess how the uncertainties propagate to the model uncertainties, one should evaluate the model under scrutiny for each of the 200 different sets of SDMEs. Plotting all resulting lines in a single plot will create bands which reflect the influence of the uncertainties in the data on the model. This method has the great advantage that all correlations are accurately taken into account.