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 title: "FINAL-Bench Quantum: An Open, Neutral Benchmark for Quantum-Computing Methods"
-thumbnail: 
+thumbnail:
 authors:
 - user: SeaWolf-AI
-tags: [quantum, quantum-error-correction, benchmark, qec, decoders, vqe, qram]
+tags: [quantum, quantum-error-correction, benchmark, qec, vqe, qram]
 ---
 
 # FINAL-Bench Quantum: An Open, Neutral Benchmark for Quantum-Computing Methods
 
-Quantum-computing results are notoriously hard to compare. A "logical error rate," a
-"query fidelity," or an "approximation ratio" only mean something next to a clearly stated
-protocol — yet papers use different codes, noise models, hardware, and shot counts. **FINAL-Bench
-Quantum** is our attempt at a single, fair yardstick: an open, neutral benchmark suite where
-methods compete in five events under identical, published protocols, and where every number is
-labeled as either *measured here* or *quoted from a source*.
+Quantum-computing results are remarkably hard to compare. The same "logical error rate (LER)" or
+"query fidelity" can mean entirely different things depending on the code, the noise model, the
+hardware, and how many shots were taken. **FINAL-Bench Quantum** is our attempt to bring *one fair
+yardstick* to that confusion: a suite where methods compete in five events under **identical,
+published protocols**, and where every number is clearly labeled as either *measured here* or
+*quoted from a source*.
 
 🔗 **Leaderboard:** `huggingface.co/spaces/FINAL-Bench/quantum-bench-leaderboard`
 
-## Two tracks, one rule: say exactly what you measured
+## The core rule — two tracks
 
-- **Track A — Verified.** Methods run here on one frozen, public test set, reported with 95%
-  confidence intervals. These are directly comparable.
-- **Track B — Reported.** Numbers quoted from their papers/sources. Codes, noise models, and
-  hardware differ, so they are **not** directly comparable — and we say so.
+- **Track A (Verified).** Methods are *measured here* on one frozen, public test set and reported
+  with 95% confidence intervals. These numbers **are** directly comparable.
+- **Track B (Reported).** Numbers *quoted* from each paper or announcement. Codes, noise models,
+  and hardware differ, so they are **not** directly comparable — and we say so plainly.
 
-We make **no quantum-advantage claims**. Where a result is a simulation, we call it a simulation;
-where it is real hardware, we name the chip and job ID. Where two results are within their
-confidence intervals, we call it a statistical tie rather than crowning a winner.
+Two principles hold throughout:
+
+1. **No quantum-advantage claims.**
+2. **A simulation is labeled a simulation; real hardware is named with its chip.** When two results
+   fall within each other's confidence intervals, we call it a **statistical tie** rather than
+   crowning a winner.
 
 ## The five events
 
-| Event | What it measures | Verified highlight |
+| Event | What it measures | One-line analogy |
 |---|---|---|
-| ① QEC Decoder | logical error rate on a rotated surface code (Stim, circuit noise) | a maximum-likelihood decoder (Tesseract) leads; the BP-class decoders (BeliefMatching, BP+OSD) and a neural ensemble are a statistical tie just behind |
-| ② Optimization | Max-Cut quality (cut / optimum) | QAOA reaches ~0.88 approximation ratio at depth p=3 on a 14-node instance |
-| ③ VQE | molecular ground-state energy vs FCI | H₂ to **chemical accuracy** (0.22 mHa); a real-hardware 4-qubit run on IBM Heron r2 |
-| ④ QRAM | quantum-memory query fidelity | a 4-cell select-QRAM on **IBM Heron r2 at 0.92 mean query fidelity**; a QEC-protected variant reaches 99.6% in simulation |
-| ⑤ Simulation | how large a circuit a classical method handles | **100,000-qubit** Clifford (stabilizer) sampling; 30-qubit exact statevector on a GPU |
-
-## A few results we found interesting
-
-**Decoders are near a floor on idealized syndromes.** On a distance-5 rotated surface code, the
-strong classical decoders (BP+OSD ≈ 0.0095, BeliefMatching ≈ 0.010) and a regularized neural
-ensemble (≈ 0.0098) all sit within each other's 95% CIs — only the brute-force maximum-likelihood
-decoder (Tesseract, ≈ 0.0092) is lower, and it runs at ~79 ms/shot, far too slow for real-time use.
-The practical lesson: on *binary* syndromes there is little headroom; a fancier architecture does
-not beat the floor.
-
-**…but soft information changes the game.** When the decoder is given *analog* (soft) readout
-values instead of thresholded bits, a small neural decoder cuts logical error by **40–46%** versus
-hard-decision decoding on a repetition memory — matching the soft-optimal decoder. This is the same
-mechanism behind Google's AlphaQubit gains: the advantage is in the *information*, not the network.
-
-**Real hardware, honestly bounded.** On IBM Heron r2 processors, a repetition-code memory shows the
-error-correcting distance boundary directly — distance-3 fails to correct two injected errors
-(~97% logical error) while distance-5 corrects them (0.5–3%), a 29–175× reduction across three
-backends (z = 7–552σ). This is a *repetition code* with offline majority-vote decoding — **not**
-surface-code below-threshold, not fault-tolerant QEC, and not a quantum-advantage claim.
-
-## Submit your method
-
-The **Submit** tab takes a method name, links (GitHub / Hugging Face), an email, and an optional
-file. Submissions are stored privately, reproduced under the event's fixed protocol, and the
-submitter is emailed about inclusion. Entries are labeled by origin (country flag + author/group),
-exactly like every other entry.
-
-## Why neutrality is the point
-
-A leaderboard is only useful if you trust it. That means including strong competitors even when
-they beat the host's own entries, quoting sources faithfully, and refusing to round a simulation up
-into a hardware claim. FINAL-Bench Quantum is built around that discipline. Several entries come
-from our own group (VIDRAFT, 🇰🇷); they are shown under the same protocol, confidence intervals, and
-honesty boundaries as Google, IBM, NVIDIA, USTC, Riverlane, and the rest.
+| ① **QEC Decoder** | logical error rate on a rotated surface code (Stim, circuit noise) | accuracy of a quantum "spell-checker" |
+| ② **Optimization** | Max-Cut quality (cut found / optimum) | finding the best answer among astronomically many |
+| ③ **VQE** | molecular ground-state energy vs the exact solution | quantum energy calculation for chemistry/drugs |
+| ④ **QRAM** | quantum-memory query fidelity | accuracy of a quantum "memory chip" |
+| ⑤ **Simulation** | how large a circuit a classical method can handle | faking a quantum computer on a classical one |
+
+Each event tab is organized as **A. verified measurements / B. real hardware (where available) /
+C. published references**, alongside dedicated **📈 Charts** (threshold, distance-scaling, and
+latency-vs-accuracy plots), **🏅 Medals** (participation by country), and **ℹ️ About**
+(methodology and citation).
+
+## How to read the tables
+
+- **Flag** = a method's / team's origin; **By** = its authors (e.g., Tesseract = Google Quantum AI,
+  PyMatching = O. Higgott).
+- **✓ VERIFIED** = measured on this benchmark. **REPORTED** = quoted from a source.
+- The **±value** next to a number is its 95% confidence interval. Overlapping intervals mean a tie.
+- The **latency** column matters as much as accuracy — a decoder that is "accurate but slow" can be
+  useless for real-time error correction, where decoding must keep pace with the QPU cycle.
+
+## How to submit
+
+The **📤 Submit** tab takes a method name, links (GitHub / Hugging Face), an email, and an optional
+results file. Submissions are **stored privately**, reproduced under the event's fixed protocol, and
+the submitter is emailed about inclusion. Listed entries appear with the same origin and author
+labels as everyone else.
+
+## Why neutrality is the whole point
+
+A leaderboard is only useful if you can trust it. So FINAL-Bench Quantum is built on a discipline:
+**include strong competitors even when they beat the host's own entries, quote sources faithfully,
+and never round a simulation up into a hardware claim.** Methods from Google, IBM, NVIDIA, USTC,
+Riverlane and others sit next to a Korean entry (VIDRAFT 🇰🇷) under the *same* protocol, confidence
+intervals, and honesty boundaries.
+
+Quantum computing has not yet reached the fault-tolerant era — which is exactly why a shared,
+hype-free yardstick that honestly records *what has actually been measured today* is worth building.
+Come and compete with your own method.
 
 *A methods paper is in preparation. Feedback and submissions are welcome.*