Financial risk and asset allocation
Quantum application entry & quantum world model
INDUSTRY EVOLVESQUANTUM SOLVES
EvolveQ's quantum world model understands industry objectives and constraints, learns hardware capabilities, noise and cost, and predicts outcomes before execution. Feedback improves its choice of algorithms, hardware and control strategies.
INDUSTRY EVOLVES QUANTUM SOLVES
About Us
The application entry and quantum world model for industrial quantum computing
EvolveQ｜弈赋量子 is building the application entry and quantum world model for industrial quantum computing.
Enterprises submit problems, define objectives and connect data through one entry point. AI task agents extract constraints and generate classical baselines and executable tasks. FinQ, OptQ and BioQ Skill components connect to quantum, HPC and AI/GPU resources. The quantum world model learns hardware states, predicts outcomes and improves action strategies through execution feedback.
Six capabilities from industry entry to autonomous execution01—06
- 01Unified industry application entry
- 02AI task agents and problem compilation
- 03Reusable quantum Skill components
- 04Heterogeneous compute orchestration
- 05Quantum-system representation and outcome prediction
- 06Execution planning and feedback optimization
Initial industry Skill componentsFinQ · OptQ · BioQ
Supply chains, logistics, scheduling, and energy networks
Molecular simulation, candidate screening, and experimental-resource optimisation
Our mission
Start with the first partner projects and train a quantum world model across industries, compute types and hardware platforms—so quantum computing can deliver practical industry value.
Industry Evolves. Quantum Solves.Access Gap
Enterprises need quantum computing, but lack a clear, usable and verifiable way in
Four barriers keep industry problems outside a continuous compute-and-validation loop: machine understanding, changing hardware capabilities, uncertain outcomes and manually configured execution paths.
Machines struggle to understand industry problems
Business objectives, constraints and data lack a unified representation, preventing systems from forming executable compute tasks.
Hardware capabilities are hard to assess
Quantum hardware capabilities, noise and costs keep changing, making it difficult to match tasks to suitable resources.
Outcomes cannot be predicted in advance
Without predictions of result quality and resource consumption before a run, pilots remain costly.
Execution paths depend on manual planning
Algorithms, hardware and control strategies require manual configuration, limiting continuous improvement and reuse at scale.
Quantum World Model Stack
A quantum world model that predicts outcomes and plans the best action
The industry entry connects AI task agents and standard Skill components. Unified hardware representations, process prediction, noise learning and outcome prediction support autonomous execution and control. Feedback continuously updates the quantum world model.
Industry demand
Real problems and enterprise data
FinanceSupply ChainEnergyLife Sciences
02 · ENTRYApplication entry
01Submit problems
02Define objectives
03Connect data
04Review results
FinQREADY
OptQREADY
BioQREADY
Quantum World Model
- Unified hardware representation
- Process prediction & noise learning
- Compute outcome prediction
EXECUTION & CONTROLAutonomous execution & control
Hardware selection · Compilation optimization · Measurement strategy · Feedback updates
01Quantum hardware02HPC & AI03Enterprise data & systems
First Skill Portfolio
Building quantum computing Skill components for industry with our partners
FinQ, OptQ and BioQ begin with real problems in finance, complex optimization and biological R&D. They package established methods into verifiable, reusable Skill components for faster deployment across similar enterprises.
01FinQ Skill
Financial risk & asset allocation
Turn risk constraints, portfolios, hedging decisions and scenarios into auditable computation.
- Portfolio optimization
- Risk budgeting
- Hedging
- Stress testing
02OptQ Skill
Supply chain, logistics, scheduling & energy networks
Translate orders, fleets, warehouses, capacity and network constraints into executable optimization.
- Vehicle routing
- Scheduling
- Inventory allocation
- Energy dispatch
03BioQ Skill
Molecular simulation, screening & experiment allocation
Connect quantum simulation, R&D search and experiment workflows across molecular and candidate spaces.
- Molecular simulation
- Candidate screening
- Experiment design
- Resource allocation
↳
Real industry problem → Verifiable Skill component → Faster deployment across similar enterprises
AI Task Agent
The world model connects an industry problem to a verifiable decision
Describe the objective, constraints and data boundaries. An AI agent generates a classical baseline and a compute task. The quantum world model predicts result quality and resource use, plans algorithms, hardware and control strategies, then validates outcomes and learns from the run.
OPTIONS HEDGE ANALYSISOptions Book A
NEW ANALYSIS
DRAFTDescribe the objective in business language
Ask FinQ
A broker holds Options Book A. Keep portfolio risk below $12.0M while minimizing the total hedging cost.
Options Book A · CSV⌘ ↵
Risk limit$12.00MExpected Shortfall · 99%
Compute budget18,000 QUEst. 2–4 minutes
Structure & run→
01 / 03
Compile → predict → execute → verify, with feedback returning to the world model
Four Quantum World Model Pillars
Understand, represent, predict and execute industry tasks
Industry problem understanding, quantum system representation, compute outcome prediction and execution strategy planning turn business objectives into executable, verifiable tasks that improve through feedback.
Industry Problem Understanding
Identify business objectives, constraints and data, then generate executable compute tasks.
Quantum System Representation
Learn hardware capability, noise and cost to match the best-fit quantum device.
Compute Outcome Prediction
Predict result quality and success probability while assessing resource use and application value.
Execution Strategy Planning
Select algorithms, hardware and control strategies, then improve them with execution feedback.
Business Model
Facility Access establishes the revenue base; Quantum Units drive usage growth
Facility Access covers continuous access and enterprise governance, while the primary revenue stream scales with Quantum Unit consumption.
Quantum Units
Measure problem size, Skill calls and the use of classical, cloud and quantum resources.
Facility Access
A fixed subscription for continuous access, run records and enterprise governance.
Private Deployment
Private deployment, access control and usage monitoring for enterprise data requirements.
Leadership & Expertise
Key Persons
EvolveQ's key persons bring together quantum and biotechnology research, product engineering, commercial execution and strategic experience in one closely connected leadership group.
Dr. Yan ZHU
Chief Executive Officer- Research Assistant Professor, School of Computing and Data Science, The University of Hong Kong
- PhD in Computer Science, The University of Hong Kong | BSc in Computer Science, Zhejiang University
- Research published in leading international journals including Nature Reviews Physics, Nature Communications, Physical Review Letters and npj Quantum Information
- Specialization in interdisciplinary innovation at the intersection of artificial intelligence and quantum technologies
- Leadership role in development of AI-powered characterization techniques transferable across multiple quantum systems, with applications in quantum benchmarking, complex property prediction and quantum system control
Dr. Xingyu YUE
Chief Technology Officer- PhD in Physics, The University of Hong Kong | BSc in Physics, Nankai University
- Expertise in quantum materials, quantum transport and chip design
- Specialized in cryogenic and ultrahigh-vacuum quantum laboratory development
- Focus on quantum technology, AI, and scalable engineering systems
Dr. Min-Quan HE
Chief Operating Officer- PhD in Quantum Computation, The University of Hong Kong | BBA in Finance and BSc in Physics, Fu Jen Catholic University
- Published Research in Quantum Algorithms and Quantum Simulation
- Extensive entrepreneurial experience in technology startups
- Various executive roles across AI, FinTech and Quantum education
Mr. Isaac CHEUK
Chief Commercial Officer- Founding Partner & CMO, Qebula Mind
- Founder of Trillion Bonus Investment
- 5 years of experience in investing in digital assets, consumer marketing, commercialization, clientele management across Hong Kong & Mainland China
- BBA in Marketing, The Hong Kong University of Science and Technology
Mr. Maverick HUI
Chairman- Founder & Chairman, Mile Green and Mass Gravity Group｜Founding Partner, CMAG Funds | General Partner & Industry Advisor, Wonder Capital
- Former Non-Executive Director, Pangaea Connectivity Technology Limited (1473.HK)
- 25+ years of experience in global corporate strategy, investment, business development and operations across Asia, Europe and the US
- President, International Finance & Economic Association
- BSc in Physics, The Hong Kong University of Science and Technology
Ms. Gigi CHAN
Non-Executive Director- Founder & CEO, Wonder Capital｜Founding Partner, CMAG Funds｜Co-Founder, Mile Green
- Independent Non-Executive Director, ZhongAn Online P&C Insurance (6060.HK)
- Former COO & Head of Asia Pacific, Janus Capital Group｜Former CFO, Asia ex-Japan, AllianceBernstein | Former Executive Member, Hong Kong Investment Fund Association
- 25+ years of experience in financial services, investment management, corporate finance, governance and risk management across Asia Pacific
- HKSFC Type 1, 4 & 9 Responsible Officer | HKICPA
- EMBA, The University of Oxford | MEcon, The University of Hong Kong | BBA in Accounting, The Hong Kong University of Science and Technology
Advisory Board
Scientific insight for technology and industry innovation
Deep research experience and cross-disciplinary perspectives guide EvolveQ's research direction, technical validation and long-term development.
Prof. Giulio CHIRIBELLA
Chief Scientist- Professor & Associate Dean, School of Computing and Data Science, The University of Hong Kong｜Director, QICI
- Former Associate Professor, Institute for Interdisciplinary Information Sciences (IIIS), Tsinghua University (2012–2015)｜Selected for China’s Young 1000 Talents Program
- Internationally recognized quantum information scientist and consistently ranked among the world’s top 2% scientists
- Visiting Professor, The University of Oxford｜Special Supernumerary Fellow, St Hilda’s College, The University of Oxford｜Visiting Fellow, Perimeter Institute for Theoretical Physics
- Elected Member, Hong Kong Young Academy of Sciences｜Young Member, Hong Kong Academy of Engineering Sciences｜Member, Accademia Nazionale Virgiliana
- Recipient of the Hermann Weyl Prize and CIFAR-Azrieli Global Scholar Award
- Croucher Senior Research Fellowship and RGC Senior Research Fellowship
- Extensive experience in international research collaboration, talent development and frontier technology ecosystem building
Prof. Yuk Lam LO, BBS
Chief Biotech Advisor- Strategic Advisor to the President, Adjunct Professor & Honorary Fellow, The Hong Kong University of Science and Technology
- Chairman, HK Bio-Med Innotech Association | President, Hong Kong Biotechnology Organization
- Chairman, GT Healthcare Capital Partners｜Partner, Hongsen Investment Management
- Independent Director, Sinovac Biotech (SVA)｜Independent Non-executive Director, Luye Pharma Group (2186.HK), Zhaoke Ophthalmology (6622.HK)
- Former Chairman, Advisory Council for Food Safety, Food and Health Bureau, HKSAR | Former Consultant, Chinese Center for Disease Control and Prevention
- Former President, Asia Pacific, Bio-Rad Laboratories｜Former Chairman, Asia Pacific, PerkinElmer
- Recipient of the 2020 Bronze Bauhinia Star
- Awardee of the 2019 Pericles International Prize (the first Hong Kong and the second Asian honoree)
Prof. Yuxiang YANG
Advisor (Quantum Sensing)- Assistant Professor, School of Computing and Data Science, The University of Hong Kong
- Research in quantum sensing and quantum metrology, with publications in Physical Review Letters and IEEE Transactions on Information Theory
- Bachelor’s degree in Physics, Tsinghua University｜PhD in Computer Science, The University of Hong Kong
- Postdoctoral research, ETH Zurich
- Selected for the NSFC Excellent Young Scientists Fund (Hong Kong and Macao)｜Recipient of the Microsoft Research Asia Fellowship
Prof. Yadong WU
Advisor (Quantum AI)- Associate Professor, John Hopcroft Center, Shanghai Jiao Tong University
- Research at the intersection of AI and quantum technologies, with publications in Nature portfolio journals and Physical Review Letters
- Bachelor’s and master’s degrees in Electronic Engineering, Shanghai Jiao Tong University｜PhD in Physics, University of Calgary, Canada
- Postdoctoral research, The University of Hong Kong
- Selected for China’s Overseas Excellent Young Scientists program
Research Foundations
Research Papers
Research in quantum machine learning, system representation, control, error mitigation and cross-hardware validation underpins the world model's ability to sense, predict and execute.
Sorted by latest publication2026 → 2022
202601 PAPER
Quantum AI Representation
Combines AI with quantum-system representations for identification, characterization and high-level technical modeling.
202601 PAPER
Data-Driven Quantum Control
Data-driven state representations control unknown quantum states and support AI agents that operate hardware and design experiments.
202501 PAPER
Hardware-Aware Error Mitigation
Data-augmented neural models enable noise-agnostic quantum error mitigation for more stable hardware results.
202402 PAPERS
Generative Quantum Learning
Learns quantum properties from short-range correlations and generative query networks for compression, modeling and simulation.
202301 PAPER
Cross-Hardware Validation
Quantum similarity testing compares quantum states and computational results across different hardware platforms.
How research enters the quantum world modelFrom papers to verifiable system capability
- 01Problem Understanding & Compilation
- 02Quantum System Representation
- 03Prediction, Control & Validation
Start with a real industry problem
Train the quantum world model through the first partner projects
Define business objectives, establish classical baselines and validate Skill components. Use computation results and hardware feedback to train the quantum world model across industries, compute types and hardware platforms.