deletions | additions       diff --git a/section_Experimental_results_We_configure__.tex b/section_Experimental_results_We_configure__.tex  index f96e96a..0a35205 100644  --- a/section_Experimental_results_We_configure__.tex  +++ b/section_Experimental_results_We_configure__.tex 
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We tune our CW source at $λ_s$, attenuated to a count rate of about $50000$ events/s during the duration of the gate ($\vert\alpha\vert \simeq 1$ in the nonlinear fiber), and by recording, separately, the depletion of the signal and the gain of the idler, we measure the conversion efficiency $\eta$ as the total pump power varies, while keeping the two pumps balanced and the polarization aligned, as shown in figure \ref{fig:vs_power}.  Our setup reaches conversion efficiency of .., for peak power of ?. For $r > 1.5$, conversion deviates from the expected sinusoidal model because higher order frequency conversion start taking place. In figure \ref{fig:vs_power}b) we show the measurement taken using the DCM to spectrally separate the fields, showing the evolution of the second order signal $\omega_{sII} = \omega_s - \Delta\omega$ and idler $\omega_{iII} = \omega_i + \Delta\omega$.  We tune the single photon source and filtering filters  toemit an  heralded photon the presence of photons  at $λ_s$ into the BS setup: we choose an setup. The  heralding rate of is  about 200 KHz for a detected pair rate of ~6000 #/s. Pumps can indeed be triggered to be generated on the event of a heralded photons, but the conversion efficiency is technically limited by the amplitude fluctuations introduced by the EDFA due to the random time between pulse generation. In this condition, the best conversion obtained is ??. To overcome this limitation, we let the system run independently in condition similar to the classical measurement, and we record the three-fold coincidences between signal, herald and pump: in this condition the detected pair rate is ~20 pairs/s in a 0.8-nanosecond window. We show the results figure ?, where we observe a conversion efficiency of ?.  Unitary conversion efficiency is limited by the fact that single photon bandwidth ( δλ =0.57 nm FWHM) and the acceptance ( δλBS = 1.17(2) nm FWHM) are comparable: theoretical calculation show a maximum efficiency $\eta$ of about $89%$.  We measure the second order correlation of the output state to verify the preservation of the quantum statistic on the translated output.  Fig. 7. \label{fig:vs_power} Conversion efficiency  Without filtering the conversion efficiency is limited by the fact that single photon bandwidth ( δλ =0.57 nm FWHM) and the acceptance ( δλBS = 1.17(2) nm FWHM) are comparable: theoretical calculation of translation efficiency, show a maximum efficiency η of about 89 We measure the second order correlation of the output state to verify the preservation of the quantum statistic on the translated output.  We inject the output field into a 50/50 fiber beamsplitter, and record detection rates A(t) and B(t) , and coincidence rate C(τ) from the two coupler outputs. Normalization of the g(2)(τ)=C(τ)/N(τ) is obtained from the discrete cross-correlation of the singles N(τ)=A(t) ∗ B(t) . Error bars are extracted from statistical error on the count events. To remove the dark counts contribution to the measurement, we observe that the contribution of the dark counts to the coincidence count is (with the assumption of uncorrelated noise where and We compare the g(2) (τ) measurements of the single photon traversing the setup, with pump either off or on. Even if the fields are not selected, because of the large conversion efficiency, we are measuring respectively at λs and λi : we observe an input (i.e. converted) g(2)(0)= 0.19. Though this value is below 0.5, the non classical boundary for single photons, it is limited by the presence of generated photons at that, unheralded, create a background noise. Upon frequency translation, the correlation takes the value of g(2)(0)= 0.23, showing a slight increase but still well within the quantum regime. Next, we select the idler field with the free space filter and repeat the measurement, shown in figure 8: fitting the raw data with a Gaussian factor, we measure g(2)(0)= 0.2(1) (the losses introduced by the filtering reduced the SNR). When we correct for dark counts, we obtain g(2)(0)= 0.02(2). Because g(2)(0) has a bounded value, we utilize Bayes statistics to estimate the uncertainty.