Unpredictable? Randomness, Chance and Free Will

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Coursera
Free Online Course (Audit)
English
Certificate Available
2-3 hours a week
selfpaced

Overview

This cross-disciplinary course deals with the undetermined, the unpredictable -- or what appears to be such. Among the questions that will be addressed are:
  • How is randomness defined?
  • How has randomness, often seen as a nuisance, become a useful resource for communication and computing? How is it generated?
  • How can physicists make the astounding claim that there is real randomness in nature?
  • Can our apparently free acts be predicted by monitoring the activity of the brain?

Lecture 1: Basic of randomness
  • History of randomness
  • The fair coin as ideal case
  • Definitions of randomness
Lecture 2: Randomness as a resource
  • Review of various tasks in which randomness is used
  • Randomized algorithms and de-randomization
  • Cryptography: randomness for secrecy
  • Zero-knowledge proofs
Lecture 3: Characterizing a source of randomness
  • The biased coin and other weaker sources of randomness
  • Amount of randomness: min-entropy
  • Extraction of randomness
Lecture 4: Noise as a random number generator
  • Definition of "noise"
  • Thermal noise: example of a resistor
  • How to extract random numbers from thermal fluctuations
Lecture 5: Deterministic chaos
  • Physical (in)determinism
  • Definition and examples of chaos
Lecture 6: Quantum physics, a first encounter
  • Overview of quantum physics
  • Single-particle interferences (Mach-Zehnder, double slit)
  • Uncertainty
Lecture 7: Intrinsic randomness and its practical uses
  • Bell's theorem and its implication
  • Elements of quantum information science
Lecture 8: Introduction to free will in science
  • Measurement independence
  • Quanta in the brain?
  • Libet's experiments

Syllabus

Lecture 1: Basic of randomness
  • History of randomness
  • The fair coin as ideal case
  • Definitions of randomness
Lecture 2: Randomness as a resource
  • Review of various tasks in which randomness is used
  • Randomized algorithms and de-randomization
  • Cryptography: randomness for secrecy
  • Zero-knowledge proofs
Lecture 3: Characterizing a source of randomness
  • The biased coin and other weaker sources of randomness
  • Amount of randomness: min-entropy
  • Extraction of randomness
Lecture 4: Noise as a random number generator
  • Definition of "noise"
  • Thermal noise: example of a resistor
  • How to extract random numbers from thermal fluctuations
Lecture 5: Deterministic chaos
  • Physical (in)determinism
  • Definition and examples of chaos
Lecture 6: Quantum physics, a first encounter
  • Overview of quantum physics
  • Single-particle interferences (Mach-Zehnder, double slit)
  • Uncertainty
Lecture 7: Intrinsic randomness and its practical uses
  • Bell's theorem and its implication
  • Elements of quantum information science
Lecture 8: Introduction to free will in science
  • Measurement independence
  • Quanta in the brain?
  • Libet's experiments

Taught by

Valerio Scarani