Dataset Open Access

Source data for "Synthetic gauge fields for phonon transport in a nano-optomechanical system"

Javier del Pino

Researcher(s)
Javier del Pino; John P. Mathew; Ewold Verhagen

  • Experimental raw data for density plots in Fig 2. Each .csv contains an array, where 1st row corresponds to x_axis (mechanical frequency in MHz for panels 1,2,3,4) and first column the y_axis (optical frequency in THz for panel 1, modulation frequency in MHz for panels 2,3,4). First nonzero component is the 2nd for each array. Remaining array elements contain the z values (Thermomechanical noise spectral for panel 1, Amplitude of driven responses for panels 2,3,4). An illustrative example of plotting in an ipython notebook follows:

         %pylab inline

            A= genfromtxt('Fig2_data_modVolt=0mV_experiment.csv', delimiter=',')   

            x = A[0,1:]
            y = A[1:,0]
            z = A[1:,1:]
            imshow(z,aspect='auto',vmin=z.min(),vmax=z.max(),extent=[x.min(),x.max(),y.min(),y.max()],cmap='magma') 

  •    Theoretical data for panel 4 in Fig 2, stored in a .csv with the same structure as previous.
  •    Raw experimental data for upper panels in Fig 3. Each .csv contains an array where 1st row corresponds to x_axis (modulation phase) and first column the y_axis (optical frequency in THz). Z values contain the experimental signal proportional to the Y optical quadrature of the transferred mode.
  • Theoretical data for lower panels in Fig 3, stored in a .csv with the same structure as previous.
  • Jupyter notebook to produce and plot typical data for Fig 4: phononic amplitude averaged over 100 disorder realizations, normalized to the maximum value (*extra_dependencies: Kwant Python library: https://kwant-project.org/).
Files (78.1 MB)
Name Size
Fig2_data_modVolt=0mV_experiment.csv
md5:70a7a8a6a331c8cd1389475010a6a581
587.9 kB Download
Fig2_data_modVolt=100mV_experiment.csv
md5:877c1bf6abcd7e88a74742a932627617
587.9 kB Download
Fig2_data_modVolt=300mV_experiment.csv
md5:b36f8441a4a127a4993f60b488e40e0d
587.9 kB Download
Fig2_data_theory_lower_panel.csv
md5:15bf9fd6516d9c2000f1aaaeca8b47e6
6.3 MB Download
Fig2_data_theory_upper_panel.csv
md5:641f5c7227d4941df276a800cc805491
6.3 MB Download
Fig2_spring_shift_experimental.csv
md5:94c21b4f923687fd36712d212a0b3cc4
43.0 MB Download
Fig3_data_down_transfer_experiment.csv
md5:b9a6ec80fe8398a0119c3a4e5f437ddd
121.9 kB Download
Fig3_data_theory_down_transfer.csv
md5:dbaf46291ae9a73f524948292e268306
10.2 MB Download
Fig3_data_theory_up_transfer.csv
md5:796d86c21fa9d89f9e5f9b5fd713ef01
10.2 MB Download
Fig3_data_up_transfer_experiment.csv
md5:9a5ddfec8a346600965c9e095e7ba1be
121.9 kB Download
Fig4_minimal_example.ipynb
md5:68b1a8e6483f2085ef0123609e95fc2d
90.5 kB Download
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