Share 看不到畫面
正確可靠的輸出畫面方式 How to publish a Claude artifact
聊天中的內嵌視覺內容（SVG 圖表、HTML 小工具、直接渲染在對話中的圖表）預設是暫時性的——它們作為 Claude 回應的一部分以內嵌方式存在，
Artifacts（製品）就不一樣了——
- 存成 Artifact — 把內嵌視覺轉成可分享、可繼續迭代的持久化 artifact
- 下載 — 存成本地的
.svg或.html檔案 - 複製為圖片 — 截一張靜態快照
至於上傳的檔案（您附加的 PNG），原因不太一樣：如果分享的聊天裡有附加檔案，
簡單來說：
- 內嵌的自製視覺 = 暫時性的（不在快照裡）
- 上傳的檔案 = 為了隱私刻意被剝除
- Artifacts = 本來就是設計用來分享的
如果有特定的圖想保留下來分享，可以叫 Claude「把這個存成 artifact」，這樣下次分享時對方就看得到了。
To speed up the process, you may want to use Claude cowork to run the batch using Python which Claude will make one for you automatically.
Interesting result — the MNA contradicts the React optimizer. Let me sweep mirror mismatch to show what's going on:The MNA disagrees with the optimizer by oo dB. Here's why:
analytic (React) MNA (full nodal solve)
|Ad| 1286.7 1293.4
|Acm| 3.50×10⁻⁵ 1.70×10⁻³
CMRR (dB) 151.30 117.65
← 34 dB lower
Root cause: PNP mirror β-error, which the React formula completely omits.
The textbook expression Acm = 1/(2·gm·R_tail) assumes a perfect mirror — gain exactly 1. Real PNP mirrors lose 2/(β+2) of the reference current to base currents. With β_p ≈ 106:
δ_β = 2/(β+2) = 1.84%
Predicted Acm from β-loss: δ·Rout/(2·R_tail) = 1.66×10⁻³
Observed Acm (MNA): 1.70×10⁻³
→ β-error explains 98.1% of the actual CM gain
The tail-impedance term (3.5×10⁻⁵) is real but it's the floor, not the dominant contributor. The mirror β-error is 48× larger and sets the actual CMRR.
Mirror Is-mismatch sweep confirms the mechanism — there's an asymmetric peak where Is mismatch cancels β-loss:
ΔIs/Is CMRR
−5% 106.5
−2% 111.5
0% 117.7 ← matched (β-loss alone)
+1% 123.8
+2% 155.7 ← cancellation peak (Δ_Is exactly = δ_β)
+3% 123.5
+5% 114.2
That sharp 156 dB peak at +1.84% is real but useless — it's a single bias-trim point. Process variation puts every die somewhere else on the curve.
Monte Carlo with realistic process σ (0.5% Is, 1% β):
CMRR mean = 119.4 dB
CMRR median = 117.5 dB
CMRR p10 = 112.8 dB
CMRR p90 = 127.4 dB
CMRR std = 7.3 dB
Verdict on the optimizer's CMRR numbers: systematically optimistic by ~33 dB. The 117–120 dB result is in line with what real BJT diff pairs with active loads achieve (LM394: 120 dB typ; MAT02: 124 dB typ — both trimmed). The optimizer's 151 dB was the textbook ceiling for an idealized topology, not what the topology actually delivers.
Two-line fix for the React calcPerf:
const deltaBeta = 2 / (bp + 2); // mirror β-loss
const Acm_beta = deltaBeta * Rout / (2 * RoTail);
const AcmTotal = Math.hypot(AcmLin, Acm_beta); // RMS combine
const CMRR = 20 * Math.log10(AdLin / AcmTotal);
That alone pulls the reported CMRR from 151 to ~118 dB and aligns it with what an MNA — or a real chip — would show.
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