Solar Orbiter Data Tutorial¶

RPW BIAS - Thermal Noise Receiver (TNR)¶

author: Louis Richard, IRFU¶

louisr@irfu.se

Outline¶

  1. Setup
  2. TNR data analysis
  3. Plasma line
  4. Radio Burst
  5. Some waves
  6. Earth's Flyby

Import SolO submodule from the pyrfu package and setup path to SolO data¶

In [13]:
%matplotlib inline

import os 

import os
import numpy as np

from scipy import constants

# import SolO subpackage from the pyrfu package
from pyrfu import solo

# import ploting packages and setup plot style
import matplotlib.pyplot as plt
import matplotlib.ticker as ticker

from pyrfu.plot import plot_spectr, plot_line

# Setup path to SolO data
solo.db_init("./data")

TNR data analysis¶

Load TNR data¶

In [14]:
tint = ["2020-11-13T00:00:00", "2020-11-13T23:59:59"]
sensor = 4
tnr_spec = solo.read_tnr(tint)

15-Sep-22 16:57:12: Loading solo_L2_rpw-tnr-surv_20201113_V02.cdf...

Plot TNR spectrum¶

In [15]:
f, ax = plt.subplots(1, figsize=(10, 7))
f.subplots_adjust(left=.1, right=.9, bottom=.08, top=.95)
ax, cax = plot_spectr(ax, tnr_spec, yscale="log", cscale="log")
ax.tick_params("y", which="both", direction="out")
ax.yaxis.set_major_locator(ticker.LogLocator(base=10, numticks=15))
ax.set_ylabel("$f$ [kHz]")
cax.set_ylabel("V1 - V2")
Out[15]:
Text(0, 0.5, 'V1 - V2')

Plasma Line¶

Load LFR density¶

In [16]:
help(solo.read_lfr_density)

Help on function read_lfr_density in module pyrfu.solo.read_lfr_density:

read_lfr_density(tint, data_path: str = '', tree: bool = False)
    Read L3 density data from LFR
    
    Parameters
    ----------
    tint : list
        Time interval
    data_path : str, Optional
        Path of MMS data. Default uses `pyrfu.solo.config.json`
    tree : bool, Optional
        Flag for tree structured data repos. Default is False.
    
    Returns
    -------
    out : xarray.DataArray
        Time series of the density.
In [17]:
dens = solo.read_lfr_density(tint)

15-Sep-22 16:57:14: Loading solo_L3_rpw-bia-density_20201113_V01.cdf...

Compute plasma frequency from density¶

In [18]:
w_pe = np.sqrt(dens * constants.elementary_charge ** 2 / (constants.electron_mass * constants.epsilon_0))
f_pe = w_pe / (2 * np.pi)
In [19]:
f, ax = plt.subplots(1, figsize=(10, 7))
f.subplots_adjust(left=.1, right=.9, bottom=.08, top=.95)
ax, cax = plot_spectr(ax, tnr_spec, yscale="log", cscale="log")
plot_line(ax, f_pe, color="k", label="$f_{pe}$")
ax.legend()
ax.tick_params("y", which="both", direction="out")
ax.yaxis.set_major_locator(ticker.LogLocator(base=10, numticks=15))
ax.set_ylabel("$f$ [kHz]")
cax.set_ylabel("V1 - V2")
Out[19]:
Text(0, 0.5, 'V1 - V2')

Radio Burst and Langmuir Waves¶

In [20]:
tint = ["2020-11-18T00:00:00", "2020-11-18T23:59:59"]

# TNR spectrum
sensor = 4
tnr_spec = solo.read_tnr(tint)

# LFR density
dens = solo.read_lfr_density(tint)

# Compute plasma line
w_pe = np.sqrt(dens * constants.elementary_charge ** 2 / (constants.electron_mass * constants.epsilon_0))
f_pe = w_pe / (2 * np.pi)

15-Sep-22 16:57:18: Loading solo_L2_rpw-tnr-surv_20201118_V01.cdf...
15-Sep-22 16:57:18: Loading solo_L3_rpw-bia-density_20201118_V01.cdf...

Plot TNR spectrum¶

In [21]:
f, ax = plt.subplots(1, figsize=(10, 7))
f.subplots_adjust(left=.1, right=.9, bottom=.08, top=.95)
ax, cax = plot_spectr(ax, tnr_spec, yscale="log", cscale="log")
plot_line(ax, f_pe, color="k", label="$f_{pe}$")
ax.legend()
ax.tick_params("y", which="both", direction="out")
ax.yaxis.set_major_locator(ticker.LogLocator(base=10, numticks=15))
ax.set_ylabel("$f$ [kHz]")
cax.set_ylabel("V1 - V2")
Out[21]:
Text(0, 0.5, 'V1 - V2')

Langmuir Waves¶

In [22]:
tint = ["2021-05-12T00:00:00", "2021-05-12T23:59:59"]

# TNR spectrum
sensor = 4
tnr_spec = solo.read_tnr(tint)

# LFR density
dens = solo.read_lfr_density(tint)

# Compute plasma line
w_pe = np.sqrt(dens * constants.elementary_charge ** 2 / (constants.electron_mass * constants.epsilon_0))
f_pe = w_pe / (2 * np.pi)

15-Sep-22 16:57:20: Loading solo_L2_rpw-tnr-surv_20210512_V02.cdf...
15-Sep-22 16:57:20: Loading solo_L3_rpw-bia-density_20210512_V01.cdf...

Plot TNR spectrum¶

In [23]:
f, ax = plt.subplots(1, figsize=(10, 7))
f.subplots_adjust(left=.1, right=.9, bottom=.08, top=.95)
ax, cax = plot_spectr(ax, tnr_spec, yscale="log", cscale="log", clim=[1e-15, 1e-10])
plot_line(ax, f_pe, color="w", label="$f_{pe}$")
ax.legend()
ax.tick_params("y", which="both", direction="out")
ax.yaxis.set_major_locator(ticker.LogLocator(base=10, numticks=15))
ax.set_ylabel("$f$ [kHz]")
cax.set_ylabel("V1 - V2")
Out[23]:
Text(0, 0.5, 'V1 - V2')