Lecture

From signal to observables

Graph Chat

Chat with Graph Search

Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.

DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.

In course

PHYS-452: Radiation detection

The course presents the detection of ionizing radiation in the keV and MeV energy ranges. Physical processes of radiation/matter interaction are introduced. All steps of detection are covered, as well as detectors, instrumentations and measurements methods ...

Description

This lecture covers the comparison of detectors' types, counting statistics, error prediction, and making sense of data. It delves into gaseous detector types, scintillator types, and semiconductor detectors, emphasizing their characteristics, typical radiation detected, and applications. The lecture also explores the importance of uncertainty estimation in measurements, glossary of terms related to counting statistics, and statistical tests for counting. It discusses critical limits, detection limits, confidence intervals, and the significance of different statistical interpretations. The optimization of experiments, statistical tests for counting, and the difference between detection and critical limits are also addressed.

Instructor

Vincent Pierre Lamirand

After a PhD on the measurement of (p,n) reactions cross sections on small accelerators (IRSN, France), I have worked on the development of neutron detectors and measurement methods for reactor physics (CEA, France). I am part of the LRS staff since October 2014.

Official source

Ontological neighbourhood

Statistics

Statistical inference: Statistical hypothesis testing

Related concepts (32)

Semiconductor detector

A semiconductor detector in ionizing radiation detection physics is a device that uses a semiconductor (usually silicon or germanium) to measure the effect of incident charged particles or photons. Semiconductor detectors find broad application for radiation protection, gamma and X-ray spectrometry, and as particle detectors. In semiconductor detectors, ionizing radiation is measured by the number of charge carriers set free in the detector material which is arranged between two electrodes, by the radiation.

Particle detector

In experimental and applied particle physics, nuclear physics, and nuclear engineering, a particle detector, also known as a radiation detector, is a device used to detect, track, and/or identify ionizing particles, such as those produced by nuclear decay, cosmic radiation, or reactions in a particle accelerator. Detectors can measure the particle energy and other attributes such as momentum, spin, charge, particle type, in addition to merely registering the presence of the particle.

Gaseous ionization detector

Gaseous ionization detectors are radiation detection instruments used in particle physics to detect the presence of ionizing particles, and in radiation protection applications to measure ionizing radiation. They use the ionising effect of radiation upon a gas-filled sensor. If a particle has enough energy to ionize a gas atom or molecule, the resulting electrons and ions cause a current flow which can be measured. Gaseous ionisation detectors form an important group of instruments used for radiation detection and measurement.

Interval estimation

In statistics, interval estimation is the use of sample data to estimate an interval of possible values of a parameter of interest. This is in contrast to point estimation, which gives a single value. The most prevalent forms of interval estimation are confidence intervals (a frequentist method) and credible intervals (a Bayesian method); less common forms include likelihood intervals and fiducial intervals.

Statistical hypothesis testing

A statistical hypothesis test is a method of statistical inference used to decide whether the data at hand sufficiently support a particular hypothesis. Hypothesis testing allows us to make probabilistic statements about population parameters. While hypothesis testing was popularized early in the 20th century, early forms were used in the 1700s. The first use is credited to John Arbuthnot (1710), followed by Pierre-Simon Laplace (1770s), in analyzing the human sex ratio at birth; see .

Related lectures (64)

Describing Data: Statistics & Uncertainty

Introduces descriptive statistics, uncertainty quantification, and variable relationships, emphasizing the importance of statistical interpretation and critical analysis.

Hypothesis Testing and Confidence Intervals: An Overview

Covers hypothesis testing, confidence intervals, and their applications in statistics.

Hypothesis Testing and Confidence Intervals: Key Concepts

Provides an overview of hypothesis testing and confidence intervals in statistics, including practical examples and key concepts.

Confidence Intervals and Hypothesis Testing

Explores confidence intervals, hypothesis testing, and ROC curves in statistical analysis.

Radiation Detection: From Signal to Observables