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The aim of this laboratory course is to understand how spectrometric chain works. You will look at behavior of components like preamplier or shaper. Next step will be to measure basic parameters of such a chain like gain or noise performence.
The most often used front-end electronics configuration consists of the charge
sensitive preamplifier and the filter known as pseudo-gaussian shaper.
The
filter is called pseudo-gaussian because the response of such
filter to step function becomes exactly gaussian when its order n approches infinity.
The pseudo-gaussian shaper is frequently used because of its simplicity and because
it allows to obtain close to optimum S/N ratio [ref-gatti,radeka].
Neglecting initially the preamplifier output voltage can be written as:
where is a Laplace transform of a sensor pulse and assuming
that
is high enough (reasonable assumption since the gain of
operational amplifiers is of the order
).
The shaper output signal can be then writrten as:
where is the shaper transfer function and again
assuming high enough gain of the operational amplifiers
.
Writing equations for the first shaper stage:
and for the following shaper stages:
and setting equal the differentiating and the integrating time constant
one obtains the shaper transfer function:
The transfer function of the whole circuit may be written as:
Usually, a very good assumption for sensor pulse shape is a dirac delta i.e. with its integral equal to a total charge
deposited in the sensor. This assumption reflects the fact that the charge collection time in the sensor is much shorter than the front-end electronics shaping time.
Under this assumption the front-end response in time domain equals:
which has the maximum amplitude at time which is equal to:
To pass from the theoretical considerations to a practical circuit the only
thing needed is to add a resistance in parallel to
. It is needed
for two purposes: first to set the DC level of the preamplifier input and
second, to assure that the feedback capacitance
gets discharged
and so it will not saturate the preamplifier output after a number of
subsequent pulses from the sensor. The derived above transfer function becomes
practically unaffected if the
value is sufficiently large (
in this work).
There are two main sources of noise which deteriorate signal to noise ratio
in the proposed spectrometric system: the sensor noise and the front-end electronics
noise. The sensor noise comes mainly from a shot noise caused by the sensor
leakage current and its spectral power density is equal to:
The front-end electronics noise is mainly due to the preamplifier and the feedback
resistance . In properly designed system the following shaper stages
give small contribution to the total noise (since the signal is already amplified).
The overall effect of preamplifier noise is described in terms of an equivalent
input noise expressed by series (voltage) and parallel (current) noise sources
with spectral densities respectively and
.
The feedback resistance is characterized by its thermal noise with
spectral density:
The noise diagram of the front-end electronics with the equivalent input noise sources
is shown in fig.
Knowing that for the circuit with transfer function the input noise
spectral power density
is transformed to the output as:
where ,
one can derive the preamplifier output spectral power density.
This is easily done using the superposition principle.
Since in practical systems
is large and the
time constant is much larger than the signal duration the contribution from
may be calculated neglecting
the
. To calculate the contribution from
one assumes that
in the signal bandwith.
With such approximations the preamplifier output noise density equals:
and subsequently the shaper() output noise density equals:
In order to obtain the voltage noise at the output the spectral noise density needs to be integrated in the frequecny domain:
For this integration the explicite dependence of
on frequency is needed. The main contribution are white (constant) voltage and current noise sources
. In JFET or CMOS technology also the flicker noise voltage component should be taken into account so one can assume the equivalent spectral noise densities as:
and
.
For the proposed pseudo-gaussian shaping (fig.~\ref{fig:sch_front})
the above integral can be calculated analytically as:
where is the Gamma function.
Knowing the signal amplitude (eq.
) and the noise
value (eq.
) the
ratio may be easily obtained. This is rarely done. Instead the noise performance is usually expressed in a slightly different way i.e. by means of an equivalent input noise charge (ENC), in the number of electrons. The ENC is calculated dividing
by the amplitude
obtained for single electron input charge
and gives in result:
It is seen that in order to minimize the noise one should minimize the sensor leakage curent and use the highest possible value. It is also seen that the voltage white noise decreases with shaping time on the contrary to the current white noise which increases with
. For a given filter order one can minimize the ENC finding an optimum
shaping time:
In such case the minimum ENC equals:
For practical applications it is often more convinient to study the noise performance
as the function of instead of
. In this case the formula
will be espressed as:
Now, instead of optimizing the shaping time the optimization
of the peaking time
can be done in order to equalize the
contribution of voltage and current noise. As before the voltage component decreases
with the increase of
while the current component increases
with increasing
.
The noise dependence on the shaping order is more complicated and in general it is
better seen with numerical simulations. Qualitatively one can only say that the ratio
of voltage to current noise contribution increases with increasing shaping order.
To get feeling about the real noise performance it is instructive to plot the ENC as the function of peaking time, for different shaping orders. This is done below setting all required parameters to the reasonable values corresponding to this work.
As expected the optimum peaking time exists. Reagarding the shaping order it is seen that in general the higher order the better noise performance.
Assuming that the further signal processing stages add negligible contribution
to the overall system noise one can estimate the expected resolution of the spectrometric system in terms of the number of electrones, on the basis of eq. .
For example one can assume second order shaping,
,
,
,
and spectral noise densities of Texas Instruments OPA657 operational amplifier
,
.
In such case the total system noise with ENC below 200 electrons may be expected.
Requesting the S/N of 10 for good separation between the signal and noise one can expect
that the signals corresponding to 2000 or more electrons realased in the sensor should be well seen by such system.
As a practical example a copper(
) Xray fluorescence
line may be considered. Each Xray photon should release in silicon sensor about (8050 eV)/(3.7 eV)=2175 electron-hole pairs which is above the requested minimum
for the given readout electronics specifications. It means that the specified readout
system should be able to detect the
line
and higher energy photons.
Schematic diagram of the implemented spectrometric chain is shown below on figure## .
One can see a few differenses betwen figures XX and ZZ.
At the input of the preamplifier charge adapter was added. Such a circuit allows injecting quasi dirac current pulses. Amount of charge is given by amplitude of rectangular pulses. Rt resistor is added for line termination. Looking at resistors R1 and R2 as at voltage divider one can write value of injected charge as
.
All capasistances in shaper are changeable in a wide range. Such a construction will allow to study shaping time impact on singal shape and noise performence of whole chain. Such a changeble capasistance is realized from tens of binary weight capasistances cross connected by switches. All switches is controled by microcontroler. On front panel You may observe shaping time () given in microseconds. To change this time You should use rotary switch (selector).
Outputs of subsequent stages are routed via switches to one output connector. Those swichces are controled by same digital circuite. Active output is displayed in box OUTPUT. By clicking rotary knob one can select active variable: shaping time or output.
Laboratory module contains also build in integrated voltage regulator to generate all needed voltages both for analog and digital components.
During this laboratory we use following equipment:
The connection of the setup is shown in the figure X.
Ask leading person to check all connections and do following steps:
Select 0 as an active output. Try to find output pulse on osciloscope. Set time base of osciloscope to 400ns. Does signal look like voltage step? Try to estimete charge gain (having in mind formula “charge adapter”) and compare it with formula “x”.
Try to look mode deeply on pulse head (change time base to 40ns). How would You explain non zero rising time? Then look at pulse tail. Try to estimate time constant of this pulse and compare to “y”.
Perform measurement of output pulse amplitude at preamplifier output for set of input test pulse amplitudes. Obtained results write to file preamp.dat
in following format:
#vin[mv] vout[v] 500 XXX.Y 1000 XXX.Y 1500 XXX.Y 2000 XXX.Y ...
Then run script linearity.gnu
and see results at file linearity.png
.
Look at output of first stage of shaper. Check if displayed time constant corresponds to peaking time (time after pulse has its maximum). Look at pulses at the output of subsequent stages. Find pulses peaking time and compare it with shaping time constant. Try to compare pulse shapes witch same peaking time for different orders.
E. Gatti i P.F. Manfredi, Processing the Signals from Solid-State Detectors in Elementary-Particle Physics, Revista Del Nuovo Cimento (1986).