Doctoral Lectures on HEP ELECTRONICS

Doctoral Lectures on

HEP ELECTRONICS

Dr. Luigi Cimmino - University of Naples «Federico II» (IT)

@UCLouvain (BE), 30Aug-3Spt, 2021

TABLE OF Contents

PART 1

• A little bit of Physics

• Basics• Transistor• OP AMP

• Noise

• Signal Formation in a Detector

• Analog Chain Blocks• Pre-amplification• Shaper• Sample and Hold (Track and Hold)• Analog Pipeline

• Digital Blocks and Digital conversion• MUX (Universal gate)• DAC• ADC

• Measure of the Time-Of-Flight • General• Time Expansion TDC

PART 2

• Detectors

• Silicon Photomultipliers• General• Dark Noise• Cooling

• Autonomous Control System• RISC Architecture (Short)• Realtime vs Multitasking• Clocking with a RISC System• Syncronous and Asyncronous tasks

• Do we really need AI? (Debate)

Dr. L. Cimmino@UCLouvain, 30Aug-3Spt, 2021

DEtectorsDr. L. Cimmino@UCLouvain, 30Aug-3Spt, 2021

The detectors used in HEP are fantastic machines, whose main parameters are:

• speed

• efficiency

• resolution

• granularity

Designing a detector is not trivial! Knowing the physics of the detector and the one you want to measure does not guarantee success. That’s why, the improvement of the abilities of computers to carry out complex simulations in a short time, has contributed to the creation of more and more performing detectors.

The use of electronics allows to manage a huge number of channels with exceptional speed and throughput capacity. In other words, we have observed and determined, directly or indirectly, the physics of events that occur in the time of 10-25 s with detectors of 107 electronic channels.


Most of HEP detectors are calorimeters, used to measure the energy of the particles, or trackers, used to measure the trajectory of particles. Some detector is made of alternated layers of the two types (e.g. CMS and ATLAS) and other integrate both.

How a tracker works, it is quite intuitive. A particle passes through a series of detection layers and its trajectory is reconstructed.

On the other hand, calorimeters are based on destructive processes that take place within them. We have to make a distinction between electromagnetic calorimeters and hadronic calorimeters, which differ from each other for the physics and for the intrinsic relative resolution in energy.

In general, the detector and the particle experience an interaction that results in a change in the physical characteristics of both. Through the changes that occur in the detector we measure the physics of the interaction. The processes to which the particle is subjected determine its loss of energy and momentum changes.

Let’s focus on processes involving charged particles like electrons/positrons and muons. These are :

• Bremsstrahlung

• Ionization

• Cherenkov radiation emission


The Bremsstrahlung is a radiative process due to the braking of a charged particle moving in a coulomb field.

Electrons with energy less than the critical energy loose energy mostly by ionization and proportionally to ln(𝐸𝐸). The critical energy is the energy at which the value of the stopping power due to the two processes is the same.

Heavy particles don’t undergo bremsstrahlung because of their mass and the different interactions. In particular, muons experience Bremsstrahlung at energies above 1 TeV.

−d𝐸𝐸d𝑥𝑥 =

𝐸𝐸𝑋𝑋0

with 𝑋𝑋0 𝑔𝑔 𝑐𝑐𝑚𝑚−2 ∝ 𝐴𝐴𝑍𝑍2

−d𝐸𝐸d𝑥𝑥 ∝

𝑍𝑍2𝐸𝐸𝑚𝑚𝑒𝑒2

CRITICAL ENERGY

The loss of kinetic energy due to the momentum change, involves the emission of photons of energy 𝐸𝐸 = ℎ𝜈𝜈, which can be seen with a photon detector.

The stopping power experienced by the charge particle depends on the mass of the particle, the atomic number 𝑍𝑍 and the mass number 𝐴𝐴 of the atom. If 𝑋𝑋0 is the radiation lenght, we have

𝑍𝑍 > 4


On the other hand, the ionization is an inelastic process which produces a loss of energy in the incident particle due to collisions with the electrons of the atoms of the medium it passes through. The target atom can be ionized (RPC) or excited (scintillator). The stopping power of heavy charged particles is given by the Bethe-Bloch formula

−d𝐸𝐸d𝑥𝑥

∝𝑍𝑍2

𝛽𝛽2 ln(𝑎𝑎𝛽𝛽2γ2)

where 𝑎𝑎 is a costant term that depends on the material traversed and on the charged particle.

Charge particles with 𝛽𝛽γ in the range 3-5 experience the minimum energy loss rate. In the practice, relativistic charged particles are minimum ioniziong particles.

−2 𝑀𝑀e𝑉𝑉 𝑐𝑐𝑚𝑚2𝑔𝑔−1

CRITICAL ENERGY


We discussed the main processes that are exploited, respectively, to make an electromagnetic calorimeter or a tracker. They have in common the production of light. Another process that produces light by the interaction of a charged particle with the medium passing through, is due to the Cherenkov effect. This occurs when a charged particle passes through a medium at a faster speed than light has moving through the same medium and this phenomenon causes the production of light by the medium.

The production of Cherenkov light normally happens inside some nuclear reactor. A detector that take advantage of this phenomenon, can be operated as a calorimeter or as a counter/tracker.

As an exercise, design a threshold Cherenkov detector, using gas and an optical coupling with really low efficiency trapping efficiency (4%). We want to maximize the number of photons detectable when charged particles, muons, cross a length of 1 m.

How could we use this detector? With what kind of light detector could we make the readout?

v

θ

Silicon PhotomultipliersDr. L. Cimmino@UCLouvain, 30Aug-3Spt, 2021

Silicon Photomultipliers are photosensors capable to reveal the single photon. The main characteristics are:

• Ruggedness

• Durability

• Low power consumption

SiPMs are constituted by a parallel matrix of avalanche photodiodes working in Geiger-mode (G-APD). When a photon triggers an avalanche, this grows exponentially until it reaches its maximum, depending on how many cells have been activated at the same time. The SiPM is restored by meaning of the quenching resistor in series with the APD.

Incoming photon closes the switch

QUENCHING RESISTOR

microcell output amplitude ∶ 𝑨𝑨𝒊𝒊 ∝ 𝑪𝑪 𝑽𝑽𝒃𝒃𝒊𝒊𝒊𝒊𝒊𝒊 − 𝑽𝑽𝒃𝒃𝒅𝒅


ZENER BREAKDOWN(not linear)

LINEAR AVALANCHE

GEIGER AVALANCHE

The Zener breakdown is the effect of the conduction, due to the thinning of the depletion region, of the electrons under a high reverse biased field. The avalanche breakdown happens linearly, unlike the ZB, but also involves holes in the mechanics of multiplication. In Gieger mode the grow rate of the avalanche is exponential.


The typical response of these devices is hundreds of ps. The recovery time is of order 100 ns and the amplitude of the signal depends on how many microcells have been activated at the same time.

A single microcell can be fired both by a photon or by a free carrier inside the APD. The distance between peaks is called Single PhotoElectron Response. The output signal 𝐴𝐴 is proportional to the number of fired cells 𝑁𝑁𝐹𝐹 and the gain is usually in the range 105-109.

ELECTRONIC PEDESTALPEDESTAL1 PHOTOELECTRONS

2 PHOTOELECTRONS3 PHOTOELECTRONS

A.U.

AB

UN

DA

NC

E

RISE TIME

A.U.

AB

UN

DA

NC

E

Light ON

Light OFF

SPER

SPER


The typical response of these devices is hundreds of ps. The recovery time is of order 100 ns and the amplitude of the signal depends on how many microcells have been activated at the same time.

A single microcell can be fired both by a photon or by a free carrier inside the APD. The distance between peaks is called Single Photoelectron Response. The output signal 𝑨𝑨 is proportional to the number of fired cells 𝑵𝑵𝑭𝑭 and the gain is usually in the range 105-109.

A.U.

AB

UN

DA

NC

E

∝ 𝑁𝑁𝐹𝐹 = 𝑁𝑁𝑇𝑇 1 − e−𝑁𝑁𝑃𝑃ℎPDE

𝑁𝑁𝑇𝑇

∝

Quantum efficiency

Fill factor

Avalanche probability

ELECTRONIC PEDESTALPEDESTAL1 PHOTOELECTRONS

2 PHOTOELECTRONS3 PHOTOELECTRONS

Silicon PhotomultipliersFree carriers not generated by incoming photons, can trigger avalanches. Minor generation effects occur for afterpulsing or for the optical crosstalk.

SiPM are mainly affected by the Dark Noise that is generated because of thermally or field-assisted generation of free carriers. The effect of the dark noise is deleterious for the photon detection and cannot be eliminated. It is usually limited by adjusting both on the temperature, to reduce the thermally generated events, and on the over voltage, to limit those produced by tunneling.

In general, the performance of the SiPM are changed, sometimes dramatically, because of the change in avalanche production dynamics.

Small variations concern the SPER shift, which lead to a deterioration in resolution. Great variations can determine the the total disappearance of the signal and the flattening of its spectrum.

∆T = 15°

∆T = 0°


Silicon PhotomultipliersThe effect of dark counts, when the rate is controllable, can be attenuated by setting an ad hoc threshold depending on the temperature. Overvoltage also has a tuning effect on dynamics and dark counts rate control.

The best choice is to set intermediate threshold, with a cut around 5 photoelectrons, with the SiPM at controlled temperature, by setting an appropriate overvoltage. Because, keeping the SiPM at a lower temperature decreases the dark counts by limiting the thermal agitation, but also decreases the breakdown voltage.


Autonomous Control SystemsAdvanced RISC Machines are one of the latest standard in RISC architecture microprocessors. The Reduced Instruction Set Computing architecture was developed and evolved almost in parallel with CISC (Complex) architectures.

The pipeline is the core concept of the RISC architecture and it consists in the parallelization of the instruction at the processor level. Instructions have fixed width, and all the operations are fetched, loaded and executed, together with their operands, in the registers of the CPU. This involves a great saving in resource occupancy and throughput because of sequential execution of the code, a minimal decoding of the instructions and the load-store memory access. x

The problems related to this architecture concern the possibility of deadlocks during the execution of the instructions and the need to use a scheduling mechanism in the execution of the code. In fact, if the CPU processes a jump, the contents of each register must be stored in memory in order to allow the new code to have access to the CPU.

In a pipeline this means to flush away the instruction already in it. Moreover, if an instruction is closely related to previous one, it must wait the end of execution before it can be executed, clogging the pipeline.

To get around these problems, ARM architecture have high specialized and optimized microcode, 5 bit for the register addressing and advanced non-preemptive scheduling.


Autonomous Control SystemsDr. L. Cimmino@UCLouvain, 30Aug-3Spt, 2021

In a RISC machine, the management of the program execution flow is totally handed over to the program being executed. The operating system and other programs, waiting to be executed, can not interrupt the process to claim the CPU control. This is in contrast with the preemptive scheduling of the CISC architectures, which allows for native multitasking. In a multitasking system, processes can be interrupted at any time to temporarily relinquish the control of the CPU.

Although the performance of a multitasking system is better, computers dedicated to the control of instrumentation, in particular for detectors that require remote control, work in real-time. Multitasking can generate delay effects in the production and reading of signals, when the system is connected at low level with the instrumentation.

DATA TRANSFER WITH REAL-TIME CLOCK

On the other hand, real-time system can not handle interrupts. This makes it impossible to trigger a change in processes execution based on external events at the same time they are generated. instead of the interrupt, polling is used. Polling is a time-consuming task that loops, introducing jumps in the code, until an event is recognized.

Autonomous Control SystemsA RISC based computer embedded in the detector electronics, allows to operate at high level to:

• apply settings dynamically

• program routines and schedule tasks

• check working conditions

• check data quality

• force detector’s operating mode

• prevent instrumentation damage

• self-adjust working point

• set alarms

• furnish advanced diagnostic and self-repairing capacity

Autonomous control systems are not based on process automation. They are real self-pilots who in the absence of the operator can intervene on the system to avoid critical situations. Their implementation must therefore be carried out in such a way that interfacing occurs at the lowest possible level.

An ACS reads sensors and status flags to apply changes in real time, as soon as a change in operating conditions occurs. Its programming is mainly conditional-sequential, although implementations for parallel processes are possible.


Autonomous Control SystemsThe greatest advantage that one can have from the implementation of an ACS in a particle detector, is related to the mode of operation of the detector itself.

When a detector is in acquisition, it switches from RUN mode to DIAG mode. During the first phase it acquires events locally through the front-end electronics; during the second it transfers the digitized form of the detected signals and arranges them in groups of data to be processed.

An ACS, not only can govern the alternation of the two modes based on the detector’s trigger system, it can intervene in the two phases by carrying out checks on the data during the DIAG phase and behaving like a real observer during the RUN phase.

This is particularly true for asynchronous trigger systems, which operate on the basis of detected events rather than on the basis of a fixed timing of the acquisition system, as for synchronous trigger systems.

In the case of a synchronous system, a snapshot of the status of the acquisition registers is taken at a certain rate. All the events that occur in a given time interval are recorded and then processed offline. This results in an excellent time saving, especially for what concerns fake events, but involves a greater data processing time, especially for what concerns the selection of the tracks.

On the contrary, an asynchronous system is triggered by the event itself, which will be recorded or not depending on the satisfaction of the trigger logic. Although the presence of deadtime due to events that did not produce a track is not negligible, the savings in terms of time spent in offline analysis is considerable.

Ultimately, it's just a choice between real-time or offline track selection.


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Doctoral Lectures on HEP ELECTRONICS