Quantum Random Number Generator

A device that produces true randomness from quantum measurements, not pseudo-randomness from algorithms.


A Quantum Random Number Generator (QRNG) exploits the fundamental randomness of quantum mechanics to generate provably random numbers. Unlike classical pseudo-random number generators (PRNGs), QRNGs produce true randomness.

Why Quantum?

Classical “Random” Numbers

  • PRNGs are deterministic algorithms
  • Given the seed, output is predictable
  • Technically pseudo-random, not truly random

Quantum Randomness

  • Measurement outcomes are fundamentally unpredictable
  • Not due to ignorance: nature itself is random
  • No hidden variables determine outcomes (Bell’s theorem)

Basic Principle

Simplest QRNG:

  1. Prepare qubit in
  2. Measure in computational basis
  3. Result (0 or 1) is truly random with 50/50 probability

Implementation Methods

Photon-Based

MethodPrinciple
Beam splitterPhoton randomly reflects or transmits
Vacuum fluctuationsQuantum noise in light field
Photon arrival timeRandom detection timing
PolarizationRandom polarization measurement

Other Platforms

  • Superconducting qubits
  • Atomic systems
  • Quantum dots

Rates and Devices

Device TypeTypical Rate
Commercial QRNG100 Mbps - 1 Gbps
Lab systemsUp to 100 Gbps
Integrated chips10-100 Mbps

Commercial QRNGs are available from companies like ID Quantique, Quantis, and others.

Applications

Cryptography

  • Key generation for encryption
  • Nonces and initialization vectors
  • QKD bit choices

Scientific

  • Monte Carlo simulations
  • Statistical sampling
  • Randomized algorithms

Gaming and Lotteries

  • Provably fair random selection
  • Online gambling
  • Government lotteries

Certifying Randomness

How do you know the QRNG is working properly?

Device-Dependent

Trust that the device implements quantum measurement correctly.

Device-Independent

Use Bell inequality violations to certify randomness without trusting devices:

  • CHSH violation proves quantum process
  • Randomness certified by physics, not device specifications

Self-Testing

Intermediate approaches that verify some properties.

Challenges

ChallengeIssue
BiasImperfect devices may favor 0 or 1
CorrelationsAdjacent bits might be correlated
Classical noiseMix of quantum and classical randomness
VerificationProving the source is truly quantum

Solutions

  • Randomness extraction (post-processing to remove bias)
  • Statistical testing (NIST tests, Diehard tests)
  • Device certification

See also: Quantum Key Distribution, Measurement, Bell Inequality