True vs Pseudo‑Randomness: When to Use Each and Why It Matters

Not all “random” is the same. Some randomness comes from unpredictable physical processes (true RNGs), while other randomness is generated algorithmically from a seed (PRNGs). Choosing the right one depends on your task.

True Random Number Generators (TRNGs)

• Source: Physical phenomena (thermal noise, radioactive decay, quantum effects).
• Properties: Non‑deterministic, slower, hardware or external service required.
• Strengths: Unpredictability suitable for key generation, lotteries.

Pseudo‑Random Number Generators (PRNGs)

• Source: Deterministic algorithms initialized with a seed.
• Properties: Fast, reproducible, statistically random‑looking sequences.
• Strengths: Ideal for simulations, games, procedural generation, and statistics.

Choosing the Right Tool

• Security/cryptography: Use CSPRNGs (cryptographically secure RNGs) or TRNG‑fed CSPRNGs.
• Science/simulation: High‑quality PRNGs (e.g., PCG, xoshiro) with documented seeds for reproducibility.
• Education/games: PRNGs are plenty and far easier to manage.

Practical Considerations

• Speed: PRNGs are typically orders of magnitude faster.
• Repeatability: PRNGs can reproduce results; TRNGs cannot without recorded streams.
• Access: TRNGs require hardware or trusted services; PRNGs are built into most languages/libraries.

FAQs

Which is faster? PRNGs. They’re optimized in software and can generate huge streams quickly.

Can I mix TRNG and PRNG? Yes—use TRNG output to seed a CSPRNG for strong unpredictability with speed.