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:
- Prepare qubit in
- Measure in computational basis
- Result (0 or 1) is truly random with 50/50 probability
Implementation Methods
Photon-Based
| Method | Principle |
|---|---|
| Beam splitter | Photon randomly reflects or transmits |
| Vacuum fluctuations | Quantum noise in light field |
| Photon arrival time | Random detection timing |
| Polarization | Random polarization measurement |
Other Platforms
- Superconducting qubits
- Atomic systems
- Quantum dots
Rates and Devices
| Device Type | Typical Rate |
|---|---|
| Commercial QRNG | 100 Mbps - 1 Gbps |
| Lab systems | Up to 100 Gbps |
| Integrated chips | 10-100 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
| Challenge | Issue |
|---|---|
| Bias | Imperfect devices may favor 0 or 1 |
| Correlations | Adjacent bits might be correlated |
| Classical noise | Mix of quantum and classical randomness |
| Verification | Proving 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