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# QCoDeS Example with the Lakeshore Model 372 to Control the Temperature of the Bluefors Fridge

The Lakeshore Temperature Controller Model 372 is used to control the temperature of the Bluefors fridges.

To use it as such outside of the control software provided by Bluefors, one has to establish an addtional connection. Within the Bluefors system, the Lakeshore is connected via its usb port (through a USB hub along with the other devices) to the control Laptop (as part of the Bluefors setup). To control the temperature of the fridge via QCoDeS, it is the most convenient to connect the Lakeshore via its LAN port to the control computer (the one with QCoDeS, not the one from Bluefors). In order to reach the LAN port of the Lakeshore, the Bluefors rack has to be opened, and the PCB board that is fixed to the metal board has to be opened as well (it’s a door as well with magnetic clips on one side). Do NOT disconnect the USB! Then switch the operation mode (usually there is an Interface button on the instrument) from USB to LAB. When using a router, remember to set the IP address setting to DHCP. Finally, use the following address format for VISA address: "TCPIP::<ip address>::<port>::SOCKET", where “port” is a known value from the manual (most probably, “7777”).

As mentioned above, for using the Lakeshore with QCoDeS, the operation mode has to be switched from USB to LAN. When done with the measurements, please, switch back to USB, so that the logging of the Temperature provided by the Bluefors software continues. It is planned to implement a server that takes care of the logging, so that the switching to USB will no longer be necessary. For the time being, please, always remember to switch back!

## Driver Setup

This notebook is using a simulated version of the driver, so that it can be run and played with, without an actual instrument. When trying it out with a real Lakeshore, please set simulation = False.

[1]:

simulation = True

[2]:

if simulation:
from qcodes.tests.drivers.test_lakeshore import Model_372_Mock as Model_372
import qcodes.instrument.sims as sims
visalib = sims.__file__.replace('__init__.py',
'lakeshore_model372.yaml@sim')
ls = Model_372('lakeshore_372', 'GPIB::3::65535::INSTR',
visalib=visalib, device_clear=False)
else:
from qcodes.instrument_drivers.Lakeshore.Model_372 import Model_372
#                               put visa address here, see e.g. NI Max
#                               or look up the IP address on
#                               the instrument itself
ls = Model_372('lakeshore_372', 'TCPIP::192.168.0.160::7777::SOCKET')

Connected to: None lakeshore_372 (serial:None, firmware:None) in 0.19s


The lakeshore has two types of channels: Readout channels and heaters. For reading the temperature we use the readout channels. There are sixteen channels, each of which has the following parameters:

[3]:

ls.ch01.parameters

[3]:

{'temperature': <qcodes.instrument.parameter.Parameter: temperature at 1760079888168>,
't_limit': <qcodes.instrument.parameter.Parameter: t_limit at 1760079886432>,
'sensor_raw': <qcodes.instrument.parameter.Parameter: sensor_raw at 1760079886152>,
'sensor_status': <qcodes.instrument.parameter.Parameter: sensor_status at 1760079886544>,
'sensor_name': <qcodes.instrument.parameter.Parameter: sensor_name at 1760079886936>,
'enabled': <qcodes.instrument.group_parameter.GroupParameter: enabled at 1760079886768>,
'dwell': <qcodes.instrument.group_parameter.GroupParameter: dwell at 1760079887888>,
'pause': <qcodes.instrument.group_parameter.GroupParameter: pause at 1760079887160>,
'curve_number': <qcodes.instrument.group_parameter.GroupParameter: curve_number at 1760079888112>,
'temperature_coefficient': <qcodes.instrument.group_parameter.GroupParameter: temperature_coefficient at 1760079887496>,
'excitation_mode': <qcodes.instrument.group_parameter.GroupParameter: excitation_mode at 1760079887440>,
'excitation_range_number': <qcodes.instrument.group_parameter.GroupParameter: excitation_range_number at 1760079888000>,
'auto_range': <qcodes.instrument.group_parameter.GroupParameter: auto_range at 1760079887608>,
'range': <qcodes.instrument.group_parameter.GroupParameter: range at 1760079888056>,
'current_source_shunted': <qcodes.instrument.group_parameter.GroupParameter: current_source_shunted at 1760080036752>,
'units': <qcodes.instrument.group_parameter.GroupParameter: units at 1760080035912>}


All the parameters have docstrings, labels, and units, when applicable.

Some of these parameters have been added just because other interesting parameters can only be set together with these (Lakeshore uses VISA commands with multiple inputs/outputs).

Some parameters like curve_number should not be changed, unless the user knows what he’s doing.

In order to read temperature values from all the sensors, we can do the following:

[4]:

for ch in ls.channels:
print(f'Temperature of {ch.short_name} ({"on" if ch.enabled() else "off"}): {ch.temperature()} {ch.units()}')

Temperature of ch01 (on): 4.0 kelvin
Temperature of ch02 (on): 4.0 kelvin
Temperature of ch03 (on): 4.0 kelvin
Temperature of ch04 (on): 4.0 kelvin
Temperature of ch05 (on): 4.0 kelvin
Temperature of ch06 (on): 4.0 kelvin
Temperature of ch07 (on): 4.0 kelvin
Temperature of ch08 (on): 4.0 kelvin
Temperature of ch09 (on): 4.0 kelvin
Temperature of ch10 (on): 4.0 kelvin
Temperature of ch11 (on): 4.0 kelvin
Temperature of ch12 (on): 4.0 kelvin
Temperature of ch13 (on): 4.0 kelvin
Temperature of ch14 (on): 4.0 kelvin
Temperature of ch15 (on): 4.0 kelvin
Temperature of ch16 (on): 4.0 kelvin


The enabled parameter of the sensor channel is very important because Lakeshore gets readings from the enabled channels in sequence. This means that if you have 3 channels enabled, while you are contantly requesting the temperature reading from only the first one, the array of readings will have parts when the value is constant. This is because within those parts Lakeshore was busy with reading temperature from the other two channels.

The units parameter is also of big importance. As it will be explained below, it defines the units from the setpoint value of the heater that is used in a closed_loop mode.

## Heating and feedback loop

To set a certain temperature one needs to start a feedback loop that reads the temperature from a sensor channel, and feeds it back to the sample through a heater. The Lakeshore 372 has three heaters: sample_heater, warmup_heater, and analog_heater.

Here the sample_heater will be used. It has the following parameters:

[5]:

h = ls.sample_heater
h.parameters

[5]:

{'mode': <qcodes.instrument.group_parameter.GroupParameter: mode at 1760081208600>,
'input_channel': <qcodes.instrument.group_parameter.GroupParameter: input_channel at 1760081208768>,
'powerup_enable': <qcodes.instrument.group_parameter.GroupParameter: powerup_enable at 1760081208992>,
'P': <qcodes.instrument.group_parameter.GroupParameter: P at 1760081209496>,
'I': <qcodes.instrument.group_parameter.GroupParameter: I at 1760081209776>,
'D': <qcodes.instrument.group_parameter.GroupParameter: D at 1760081210056>,
'output_range': <qcodes.instrument.parameter.Parameter: output_range at 1760081210392>,
'setpoint': <qcodes.instrument.parameter.Parameter: setpoint at 1760081210616>,
'range_limits': <qcodes.instrument.parameter.Parameter: range_limits at 1760081211176>,
'wait_cycle_time': <qcodes.instrument.parameter.Parameter: wait_cycle_time at 1760081211232>,
'wait_tolerance': <qcodes.instrument.parameter.Parameter: wait_tolerance at 1760081285416>,
'wait_equilibration_time': <qcodes.instrument.parameter.Parameter: wait_equilibration_time at 1760081285640>,
'blocking_t': <qcodes.instrument.parameter.Parameter: blocking_t at 1760081285864>,
'polarity': <qcodes.instrument.group_parameter.GroupParameter: polarity at 1760081286032>,
'use_filter': <qcodes.instrument.group_parameter.GroupParameter: use_filter at 1760081286256>,
'delay': <qcodes.instrument.group_parameter.GroupParameter: delay at 1760081286704>}


The allowed modes, polarities, and ranges are defined in:

[6]:

h.MODES

[6]:

{'off': 0,
'monitor_out': 1,
'open_loop': 2,
'zone': 3,
'still': 4,
'closed_loop': 5,
'warm_up': 6}

[7]:

h.RANGES

[7]:

{'off': 0,
'31.6μA': 1,
'100μA': 2,
'316μA': 3,
'1mA': 4,
'3.16mA': 5,
'10mA': 6,
'31.6mA': 7,
'100mA': 8}

[8]:

h.POLARITIES

[8]:

{'unipolar': 0, 'bipolar': 1}


### Working with closed loop control

To use a closed loop control, we need to set the P, I, D values, choose an input_channel that will be read within the closed loop, set the range of the heater (output_range), set the setpoint value (e.g. the target temperature), and start the operation by setting mode to closed_loop.

[9]:

h.P(10)
h.I(10)
h.D(0)
h.output_range('31.6μA')
h.input_channel(9)

[10]:

h.setpoint(0.01)
h.mode('closed_loop')


#### Units of the setpoint

Be careful when setting the value of the setpoint - Lakeshore uses “preferred units” for it which are determined by the units parameter of the chosen input_channel. Thanks to that, Lakeshore 372 supports setting setpoint in ohms and kelvins.

[11]:

ls.ch09.units()

[11]:

'kelvin'

[12]:

print(h.setpoint.__doc__)  # when working in Jupyter, just use h.setpoint? syntax

The value of the setpoint in the preferred units of the control loop sensor (which is set via input_channel parameter)

Parameter class:

* name setpoint
* label Setpoint value (in sensor units)
* unit
* vals <Numbers 0<=v<=400>


#### Disable unrelated channels for continuos readings

Note that in order to have Lakeshore constantly reading from the input_channel, you need to disable other channels. Otherwise, Lakeshore will be reading all the enabled channels one by one, which will slow down the convergence of the control loop.

[13]:

ls.ch03.enabled(False)


#### Observe control loop working

Now we can observe how the temperature gets steered towards the setpoint (This is not implemented in the simulated instrument)

[14]:

import time
for i in range(5):
time.sleep(0.1)
print(f'T = {ls.ch09.temperature()}')

T = 4.0
T = 4.0
T = 4.0
T = 4.0
T = 4.0


Textual representation is not very convenient, hence let’s do the same but now with plotting (This is not implemented in the simulated instrument):

[15]:

%matplotlib notebook

import time
import numpy
from IPython.display import display
from ipywidgets import interact, widgets
from matplotlib import pyplot as plt

"""
Live plot the temperature reading from a Lakeshore sensor channel

Args:
Lakeshore channel object to read the temperature from
time in seconds between two reads of the temperature
total number of reads to perform
"""

# Make a widget for a text display that is contantly being updated
text = widgets.Text()
display(text)

fig, ax = plt.subplots(1)
line, = ax.plot([], [], '*-')
ax.set_xlabel('Time, s')
fig.show()
plt.ion()

# Update the text field

# Add new point to the data that is being plotted

ax.relim()  # Recalculate limits
ax.autoscale_view(True, True, True)  # Autoscale
fig.canvas.draw()  # Redraw

[16]:

live_plot_temperature_reading(channel_to_read=ls.ch09, read_period=0.01, n_reads=5)


## Waiting to reach setpoint

As we have seen, the call of the parameter setpoint is non-blocking. That means the function returns imediately without waiting for the setpoint to be reached. In many use-cases it is desirable to wait until a certain temperature regime has been reached. This can be achieved with wait_until_set_point_reached method. There are also three parameters which allow to tune the behavior of this method.

See below:

[17]:

# time before reading the next temperature value
# in other words, wait half a second, then read the temperature and compare to setpoint
h.wait_cycle_time(0.5)

# wait until temperature within 5% of the setpoint
h.wait_tolerance(0.05)

# wait until temperature has been within the tolerance zone
# for wait_equilibration_time seconds
h.wait_equilibration_time(1.5)

[18]:

# do the waiting:
if not simulation:  # does not work with simulated instrument!
h.wait_until_set_point_reached()


For the simulation purposes, we can fake the heating of the sample by calling the start_heating method which only exists for the simulated instrument.

[19]:

if simulation:
ls.sample_heater.setpoint(4)
ls.start_heating()  # starts from 7K and goes down to the setpoint of 4K
ls.sample_heater.wait_until_set_point_reached()


## Automatically selecting a heater range (based on temperature)

To automatically select a heater range, one can define temperature limits for the individual heater ranges:

[20]:

# all limits in K, 8 limits starting with limit for 31.6μA range
h.range_limits([0.021, 0.1, 0.2, 1.1, 2, 4, 8, 16])

[21]:

list(h.RANGES.keys())

[21]:

['off', '31.6μA', '100μA', '316μA', '1mA', '3.16mA', '10mA', '31.6mA', '100mA']


This means: from 0 K to 0.021 K use 31.6μA, from 0.021 K to 0.1 K use 100μA, and so on.

We can now set the range by giving a temperature using the set_range_from_temperature method:

[22]:

h.set_range_from_temperature(0.15)
h.output_range()

[22]:

'316μA'


## Sweeping/blocking paramameter

For compatibility with the legacy Loop construct, the Lakeshore driver exposes a blocking temperature parameter: blocking_t. The setter for this parameter simply does:

def _set_blocking_t(self, t):
self.set_range_from_temperature(t)
self.setpoint(t)
self.wait_until_set_point_reached()


This parameter can be used in a doNd-like loop.

Note that the range only gets set at the beginning of the sweep, i.e. according to the setpoint not according to the temperature reading.