Published March 10, 2026 | Version 1.0

Data repository for the paper: "Solving the inverse parametric problem"

  • 1. KTH - Royal Institute of Technology
  • 2. ROR icon Dartmouth College

Description

Abstract: 

We present a method to calculate the frequency components of a pump waveform driving a parametric oscillator, which realizes a desired frequency mixing or scattering between frequency modes.  The method is validated by numerical analysis and we study its sensitivity to added Gaussian noise. A series of experiments apply the method and demonstrate its ability to realize complex scattering processes involving many modes at microwave frequencies, including non-reciprocal mode circulation.  We also present an approximate method to dynamically control mode scattering, capable of rapidly routing signals between modes in a prescribed manner.  These methods are useful tools for encoding and manipulating continuous variable quantum information with multi-modal Gaussian states.

Article DOI:

ArXiV: arXiv:2512.15453

Notes

Description:

Data Files:

  • Error_vs_N_2025-10-01_22_56.npz               -- Numerical data analysis used to generate Fig.2 (generated by Inverse_Pump_Problem_Analysis.ipynb))
  • Error_vs_N_stat2025-10-07_06_08.npz         -- Numerical data analysis used to generate Fig.2 (generated by Inverse_Pump_Problem_Analysis.ipynb)
  • Error_vs_N_2025-10-01_22_56.npz               -- Numerical data analysis used to generate Fig.2
  • Error_vs_N_stat2025-10-07_06_08.npz         -- Numerical data analysis used to generate Fig.2
  • Data_Img.hdf5                                              -- JPA Experimental Data for Image of Fig. 5
  • PeaceFilmx2_BW_96x151.png                      -- Original image used for the experiment of Fig. 5
  • Stargets_Image_PeaceFilmx2_BW_96x151.npz     -- Numerical data, and Numerical scattering matrix corresponding to experiment of Fig. 5
  • 2025-11.hdf5                                               -- Dataset used for Fig. 3 and Fig. 4

                   Contains:

                            1.  '2025-11-14_10_23_31'        -- Dataset to create Fig.3

                            2.  '2025-11-21_16_40_49'        -- Dataset to create Fig.4

  • Sexp_abs_dB_3.npz                            -- Extracted data from 2025-11.hdf5 for Figure 3
  • S_tar_dB_13_best.npz                         -- Extracted data from 2025-11.hdf5 for Figure 4
  • Sexp_abs_dB_13_best.npz                  -- Extracted data from 2025-11.hdf5 for Figure 4
 

Data Folders:

  • Folders.zip
                 Contains:

                            1.  Scattering                                 -- Contains the pumping scheme used for the experiment of Fig. 3

                            2.  Pumping Scheme NonRec       -- Contains the pumping scheme used for the experiment of Fig. 4

Figure Scripts:

  • Figures_InversePumpProblem_Fig2.ipynb        -- Jupiter notebook script to generate Fig.2
  • Figures_InversePumpProblem_Fig3.ipynb        -- Jupiter notebook script to generate Fig.3
  • Figures_InversePumpProblem_Fig4.ipynb        -- Jupiter notebook script to generate Fig.4
  • Figures_InversePumpProblem_Fig5.ipynb        -- Jupiter notebook script to generate Fig.5
 

Data Analysis Scripts:

  • Inverse_Pump_Problem_Analysis.ipynb           -- Script that perform the numerical study of validation of the PPM behind Fig.2    
  • Img2Scattering.ipynb                                       -- Script to generate pumping scheme to recreate an image (used to generate the pumping scheme that generates Fig. 5 )
  • inverse_problem_visualize_&_savedata.ipynb  -- Script to Visualize and save npz files to generate Fig. 3 and Fig. 4
 

Libraries:

  • myPy_functions.py                        -- Library of functions with inverse (PPM) and direct scattering problems solver and other functions used to analyzed data
  • PyPump.py                                    -- Library with functions of the PPM problem only

 

Files

Figures_InversePumpProblem_Fig2.ipynb

Files (65.2 MB)

Name Size
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9.5 kB Download
md5:8928c529ede22e900b47ee023dcb4869
22.5 MB Download

Additional details

Dates

Available
2026-03-11

Software

Programming language
Python