EX#7 Hypersurface and Optimization

in gmail, grade in depth EX#7. positive tone, bilingual, english first, mark graded by Claude Assistant, compose reply in the same thread rather than an independent mail, do not send, save in the draft box, wait for my confirmation 

general guidelines for grading

 check physical accuracy and correctness.

EX#8 LNA

 read assignment EX#8 at https://minstral.blogspot.com/2026/04/ex8-lna-low-noise-amplifier.html

grade in depth EX#8 submitted to gmail sat. Do not include scores/marks.
Mark you are Claude TA. positive tone, bilingual, english first. Compose reply. batch of five. Output grading in plain tex. do not send it out. keep in the draft box. 

Grade HW# 8 Benchmark with Claude Cowork

 read assignment HW#8 at https://nptechsl.blogspot.com/2026/04/hw8-claude-cowork.html

grade in depth HW#8 submitted to gmail within one week. Do not include scores/marks.
Mark you are Claude TA. positive tone, bilingual, english first. Compose reply. batch of five. Output grading in plain tex. do not send it out. keep in the draft box. 

HW#9

  課堂練習 

Deadline: This Saturday at 23:59

Send all the share links to  me chang212@gmail.com by email with subject HW#9 [your id, your name]

1. Benchmark the three algorithms (GD, NM, A*) and their cascades (one designed by you and the other design by AI )

• For the five methods, each runs with 10 seeds
• Tabulate Gain, Pout, PAE, OP1dB, S₁₁ (5 methods = 5 tables, each table with 5 metrics × 10 seeds = 40 cells).
• Visualize all of your data

Two-stage Cascode Class-AB RF PA Driver targeting 5G n78 (3.5 GHz) in TSMC 28nm RF

Build Sub 6 GHz Power Amplifier Optimizer with Die Synced

share, artifact (Closed-Form)

2. Benchmark the three designs of RF PA Drivers

2-stage RF PA driver 

Closed-form Optimizer with Load-Pull Contours 

Performance-first Thermal build  ∠Γ_3f₀ phase (deg) · open=0, -170 deg

Margin-first Thermal build ∠Γ_3f₀ phase (deg) · open=0, -170 deg

Using Cowork or Claude.ai, benchmark the three models. Experiment with 5 seeds. For each seed, optimize the circuit design using built-in A* and then NM. 

• For each seed, record metrics from the cascaded optimizers: 
• Compare Closed-Form vs. margin-first build vs. comprehensive model. 
• -Tabulate Gain, Pout, PAE, OP1dB, S₁₁ (5 metrics × 10 seeds = 40 cells).
• -Identify which metric the closed-form most over- or under-estimates.
• Cross-check both thermal designs: compute junction temperature rise ΔT_j at peak Pout. Which design runs cooler? By how many °C?
• -Build a 2×2 comparison table: rows = {Performance-first, Margin-first}, columns = {Fitness, min-spec-margin (dB), ΔT_j (°C), PAE @ 6dB back-off}.
• Visualize all of your data

Supplemental

Margin vs. Performance builds

design choices