Kerr nonlinearity and parametric amplification with an Al-InAs superconductor-semiconductor Josephson junction
<h1>Brief description</h1> <p><br>This repository contains data, code, and other materials for "Kerr nonlinearity and parametric amplification with an Al-InAs superconductor-semiconductor Josephson junction". Files are zipped by types (data, fabrication, measurement code and results) and experiments (Kerr nonlinearity measurements and parametric amplifier experiment).</p> <h1><br>Data formats:</h1> <p>.db: database file storing all measured data. QCoDeS version 0.39.1, QCoDeS github repo: https://github.com/microsoft/Qcodes. Please refer to 'plottr' tool to view the database files: https://github.com/toolsforexperiments/plottr . Plottr version: 0.0<br>.gds: GDSII pattern files for Litography<br>.ipynb: ipython notebooks that run measurements<br>.py: python scripts for generating the GDSII patterns or conducting measurements<br>.emz: AWR projects (model and data), AWR design environment version is 22.1<br>others: figures, etc..</p> <h1><br>File structure and instruction:</h1> <p>GDS patterns << GDS files for simulations and device fabrication<br> 4cavtunable_nocost_Q150-300_top-GND_bot-OP.gds << the GDS for device B, used in AWR simulation for BBQ model.<br> Distributed_JJFET_sim_v12.gds << the GDS for device A, used in AWR simulation for BBQ model.<br> Distributed_JJFET_sim_v12.py << the python script to generate the 'sim' GDS<br> Distributed_JJFET_v12.gds << the GDS pattern for fabrication (e-beam lithography)<br> Distributed_JJFET_v12.py << the python script to generate the 'fab' GDS<br>AWR_simulation << files of microwave simulations<br> Compare_P1db.ipynb << simulate P1dB of AlOx based JPA and Al-InAs based JPA<br> plots << Raw plots from Compare_P1db.ipynb<br> 202312 single JJ compression power.emz << AWR project for simulating P1dB of AlOx based JPA and Al-InAs based JPA<br> extra data << extra AWR data (user-defined format) to plot the gain versus pump frequency and power for Al-InAs based JPA - AWR tends to run out of system memory, therefore I manually divided the simulation task into small segements, and save data after each small tasks.<br> Series BBQ - device B.emz << AWR project to derive the BBQ model for device B<br> Series BBQ - device A.emz << AWR project to derive the BBQ model for device A<br>Code-Kerr-measurement<br> Compute and compare c4c2 << code that takes the measured Kerr into the c4/c2 ratio <br> Kerr fit device A.ipynb << code to analyze Kerr of device A, database file needed is jjfeta0425.db<br> Kerr fit device B.ipynb << code to analyze Kerr of device B, database file needed is 0722.db<br> Data_analysis_IMD.ipynb << code to analyze Kerr of device B using intermodulation spectroscopy, data needed is Data_IMD<br> Data_analysis_plots << Raw plots from data analysis codes<br>Code-Parametric_amp<br> Data_acquisition.ipynb << code to take measurements<br> Data_analysis_parametric_noise_ratio_plot.ipynb << code for analyzing the noise visibility ratio of the 4WM amp, database files needed are jjfeta0226.db <br> Data_analysis_parametric_amp.ipynb << code for analyzing the parametric amplification, including gain, bandwidth etc., database files needed are jjfeta0226.db, jjfeta0225.db, jjfeta0223.db, jjfetamp0113-3.db<br> Data_analysis_plots << Raw plots from data analysis codes<br>Data << raw data for analysis<br> Data-4WM_parametric_amplifier << data for the parametric amplifier<br> jjfeta0226.db <br> jjfeta0225.db<br> jjfeta0223.db<br> jjfetamp0113-3.db<br> Data-Kerr_measurement << data for the Kerr measurement (Stark shift)<br> jjfeta0425.db<br> 0722.db<br> Data_IMD << data for the Kerr measurement on device B (IMD)</p>
ShareScore
32/100
Overall dataset sharing score
Score breakdown
These five areas show where the dataset supports — or may limit — practical reuse.
- Stewardship
- 4
- Harmonization
- 4
- Access
- 16
- Reuse readiness
- 8
- Engagement
- 0