gaussian-mean-width-identification-capacity

# Gaussian Mean Width Identification Capacity Bound ## Methodology Single-letter strong converse bound on classical identification capacity of quantum channels using geometric analysis of output space. ## Key Techniques 1. **σ-Euclidean geometry**: Product state-weighted geometry for channel output space 2. **Sudakov's inequality**: Bounds covering numbers via Gaussian mean widths 3. **Semidefinite representation**: Bound admits efficient SDP computation 4. **Channel improvements**: Improves bounds for depolarizing, Pauli, erasure, and amplitude damping channels ## Mathematical Framework - Trace-distance separation controlled by Euclidean covering estimates - Exponential growth governed by operator norm of single-letter positive operator - Optimization over weighting states yields tight bounds ## Activation identification capacity, Gaussian mean width, strong converse, quantum channels, semidefinite programming