Quantum Expectations: What can today's quantum computers actually do?

Base Error Rate: The probability of an error occurring during a single quantum operation (typically 10⁻³ to 10⁻² for current hardware).
Effective Error Rate: The cumulative probability that your quantum computation produces an incorrect result.
Quantum Error Correction: Techniques using multiple physical qubits to create more reliable logical qubits. The surface code threshold is approximately 1.4%.

# Quantum Computing Expectations - Agent Brief

## What this website is
- An educational, interactive tool for estimating whether a quantum computation is feasible under noise.
- Core idea: error accumulation grows with both qubit count and circuit depth. Quantum error correction can help reduce the error rate, but at the cost of more qubits and more operations.
- Main UI is a heatmap that marks feasible vs infeasible regions.

## Main model used
- Simplified noise model approximation (depolarizing-noise).
- Effective error rate is computed from base error rate, depth.
- Key variables are:
- p: base error rate (typically treated as 2-qubit gate error rate)
- d: circuit/computation depth
- n: number of qubits

## How to read outputs
- Green regions: below chosen effective error threshold (more likely acceptable).
- Red regions: above threshold (likely unreliable).
- Moving toward larger n and d generally worsens effective error rate.

## Error correction context
- Optional surface-code style error-correction context is included.
- Trade-off: large physical-qubit overhead per logical qubit.

## Scope and caveats
- This is an intuition and planning aid, not a full hardware-validated simulator.
- Assumptions are intentionally simplified.
- Historical hardware trends and examples are not guarantees.

## Content focus areas on the site
- Why errors matter in quantum computing.
- Parameter intuition (p, n, d, acceptable effective error).
- QEC and surface-code overhead intuition.
- Current hardware examples and benchmark problem scale comparisons.