could resolve individual photons. A Poisson noise model was therefore used in *Dragonfly*. Both the orientation as well as a relative scale factor was estimated for each pattern to account for incident fluence fluctuations and variations in impact parameter of the virus relative to the beam. The predicted intensities on the detector for a given orientation were multiplied by this scale factor before calculating the probability distribution over orientations (PDOs). These scale factors were updated every iteration using the current estimate for the PDO for each pattern. In order to avoid convergence issues due to the high signal per pattern, the PDO was raised to the power of the deterministic annealing parameter, $\beta$. This parameter was increased from 0.001 by a factor of $\sqrt{2}$ every 10 iterations. The detailed procedure used for this reconstruction is described in Appendix A.

\[sec:phasing\_steps\]Phasing: Iterative phase retrieval with background estimation
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The three dimensional diffraction volume from *Dragonfly* was phased to arrive at the real space electron density using a background-aware iterative projection phase retrieval algorithm as described in Algorithm \[alg:phase\]. The update rule for this algorithm consists of a modulus projection defined to incorporate a spherically symmetric background intensity which is incoherently added 