QTQB | Quantum Technology · Quantitative BusinessQTQB | 量子科技 · 量化商業
Q-Augmented Intelligence 量子增強型智能生態
QTQB unifies hybrid quantum-classical machine learning, quantum optimization, and NIST-aligned post-quantum cryptography so funds and fintech teams can improve decision systems today while hardening long-lived digital assets against Q-Day risk.
QTQB 整合混合量子–古典機器學習、量子優化與 NIST 後量子密碼學，協助基金與 fintech 團隊在今日提升決策系統， 並為長期數位資產建立對抗 Q-Day 的防禦能力。
Vision願景
Build Asia's leading Q-Augmented Intelligence ecosystem—moving quantum technology from theory into daily finance, AI decision systems, and secure digital-asset operations.
建立亞洲領先的量子增強型智能生態，讓量子技術從理論走向金融、AI 決策系統與安全數位資產營運的日常應用。
Quantum phenomena量子特性
Steer a Bloch sphere, collapse a Bell pair, and pinch a wave packet against ħ/2. These are the primitives behind QT-Flow encodings and QB-Shield threat models. 轉動 Bloch 球、坍縮 Bell 對、把波包壓向 ħ/2。這些就是 QT-Flow 編碼與 QB-Shield 威脅模型背後的原語。
A quick field guide for decision makers: what quantum really changes, where hybrid AI helps, and why post-quantum security starts now.給決策者的速覽：量子真正改變什麼、混合 AI 何處有用，以及為何後量子安全現在就要開始。
A register of n qubits can hold a superposition over 2ⁿ basis states at once. That exponential state space is the raw material for quantum algorithms—and also why simulation cost explodes classically.n 個 qubit 的暫存器可同時疊加 2ⁿ 個基底態。這個指數級狀態空間是量子演算法的原料，也是經典模擬成本暴增的原因。
A sufficiently large fault-tolerant quantum computer can factor integers and solve discrete logs efficiently—threatening today’s public-key crypto. That is the core driver for NIST post-quantum standards (ML-KEM, ML-DSA).足夠大規模、容錯的量子電腦可有效分解整數與求解離散對數，威脅今日公鑰密碼。這正是 NIST 後量子標準（ML-KEM、ML-DSA）的核心動機。
Today’s devices are Noisy Intermediate-Scale Quantum machines: tens to hundreds of qubits with limited coherence. Useful work often means hybrid loops—classical optimizers driving short quantum circuits—not full fault tolerance yet.今日裝置屬 Noisy Intermediate-Scale Quantum：數十到數百 qubit，相干時間有限。實用路線多為混合迴路——古典優化器驅動短量子線路——尚未全面容錯。
Most production-minded quantum ML stacks train classical neural nets on GPUs while embedding variational quantum circuits or quantum kernels as specialized layers—not replacing PyTorch, but augmenting it where the feature map may help.多數面向生產的量子 ML 棧仍在 GPU 上訓練古典網路，並將變分量子線路或量子核嵌入為特殊層——不是取代 PyTorch，而是在特徵映射可能有優勢處增強它。
Unstructured search drops from O(N) to roughly O(√N) queries. That is powerful for some crypto and combinatorial settings, but it is not exponential—and noise, oracle design, and data loading still dominate real deployments.無結構搜尋可從 O(N) 降到約 O(√N) 次查詢。對部分密碼與組合問題有用，但並非指數加速；雜訊、oracle 設計與資料載入仍主導實際部署。
Adversaries can record encrypted traffic and wallets today, then decrypt when quantum cryptanalysis matures. Long-lived keys and reused addresses make finance and crypto especially exposed—migration planning cannot wait for Q-Day headlines.攻擊者可今日錄下加密流量與錢包資料，待量子破密成熟後再解密。長生命週期金鑰與重用地址使金融與加密特別暴露——遷移規劃不能等 Q-Day 上新聞。
Variational circuits, quantum annealing-style formulations, and hybrid optimizers for combinatorial and continuous allocation problems that stress classical solvers.以變分線路、類退火配方與混合優化器，處理經典求解器難以有效探索的組合與連續配置問題。
Quantum neural networks, VQCs, and quantum-inspired feature maps integrated with GPU training pipelines for risk signals, regime detection, and strategy research.將量子神經網絡、VQC 與量子啟發特徵映射接入 GPU 訓練管線，支援風險訊號、市場狀態偵測與策略研究。
Lattice-based PQC (ML-KEM / ML-DSA), hybrid classical+PQC handshakes, wallet exposure analysis, and institutional migration roadmaps before large-scale cryptanalysis becomes practical.涵蓋格基 PQC（ML-KEM / ML-DSA）、混合古典+PQC 握手、錢包曝險分析，以及大規模量子破密成為可行前的機構遷移路線。
Hybrid quantum-classical models for equities and digital-asset allocation, risk budgeting, and scenario stress testing.股票與數位資產的混合量子–古典配置、風險預算與情境壓力測試。
QML · Optimization · RiskQML · 優化 · 風險
Audit signature schemes, custody paths, and protocol exposure; design PQC-ready migration architectures.盤點簽章方案、託管路徑與協議曝險，設計 PQC 就緒遷移架構。
PQC · Custody · Q-DayPQC · 託管 · Q-Day
Map high-ROI quantum opportunities against cryptographic and operational risk, with a prioritized roadmap.對照加密與營運風險，定位高價值量子機會並輸出優先路線圖。
Strategy · Gap Analysis策略 · 缺口分析
Hands-on enablement for executives, quants, and engineering leads on quantum advantage boundaries and secure migration.面向管理層、量化與工程主管的實作賦能，釐清量子優勢邊界與安全遷移。
Training · Enablement培訓 · 賦能
QTQB architecture couples QT-Flow (quantum machine learning & optimization) with QB-Shield (quantum-safe cryptography) so research, production APIs, and security controls evolve on one roadmap.QTQB 架構將 QT-Flow（量子機器學習與優化）與 QB-Shield（量子安全密碼）耦合，使研究、生產 API 與安全控制沿同一路線演進。
Use superposition and entanglement-inspired encodings to process high-dimensional market features for portfolio optimization, anomaly detection, and strategy backtesting.利用疊加與糾纏啟發的編碼處理高維市場特徵，支援投組優化、異常檢測與策略回測。
Defend harvest-now-decrypt-later risk and long-lived signatures with crypto-agile designs aligned to NIST PQC standards.以符合 NIST PQC 的加密敏捷設計，防禦「先收集後解密」風險與長生命週期簽章威脅。
| Phase階段 | Stage Name階段名稱 | Technical Goal技術目標 | Primary Use Cases主要應用場景 |
|---|---|---|---|
| Phase 1 | Q-Simulation | Efficient circuit simulation and hybrid QML prototypes on classical hardware.在經典硬體上高效模擬量子線路與混合 QML 原型。 | Strategy backtesting, feature research, portfolio optimization pilots.策略回測、特徵研究、投組優化試點。 |
| Phase 2 | Hybrid AI | Enterprise APIs that combine GPU models with quantum kernels and optimizers.結合 GPU 模型與量子核 / 優化器的企業級 API。 | Anomaly detection, risk signals, crypto asset allocation workflows.異常檢測、風險訊號、加密資產配置流程。 |
| Phase 3 | Quantum Core | Direct access to quantum hardware backends (IBM, IonQ, Rigetti, Braket).直連量子硬體後端（IBM、IonQ、Rigetti、Braket）。 | Hardware-validated advantage experiments and production-grade QPU jobs.硬體驗證的優勢實驗與生產級 QPU 任務。 |
Interactive environment for portfolio optimization experiments, post-quantum signature demos, and wallet quantum-threat scanning—designed for research and technical evaluation. 互動環境，用於投組優化實驗、後量子簽章示範與錢包量子威脅掃描，服務研究與技術評估。
Open Quantum Lab開啟實驗室A field guide to how quantum computers are built — architectures, hardware families, and manufacturing maps. 量子電腦如何被製造的圖鑑：架構、硬體路線與製程地圖。
Open the Atlas開啟圖鑑We turn theoretical quantum advances into measurable business outcomes with transparent, explainable, and pilot-driven delivery. 我們將理論量子能力轉化為可衡量商業成果，並以可解釋、可試點的方式交付。
Read Founder Story閱讀品牌故事Hybrid optimizer comparison against mean-variance baselines under multi-asset constraints and regime shifts.在多資產約束與市場狀態切換下，混合優化器與均值–方差基準的對比評估。
Signature exposure inventory and staged PQC / hybrid migration for institutional custody workflows.簽章曝險盤點，以及機構託管流程的分階段 PQC / 混合遷移。
