PUBLISHER: Future Markets, Inc. | PRODUCT CODE: 1930298
PUBLISHER: Future Markets, Inc. | PRODUCT CODE: 1930298
The Global Quantum 2.0 Market 2026-2036
The term "Quantum 2.0" denotes the second quantum revolution - a transformation from passively exploiting quantum effects (as in lasers and semiconductors) to actively engineering, controlling, and measuring individual quantum systems. Where the first quantum revolution gave the world transistors and MRI machines, the second harnesses phenomena such as superposition, entanglement, quantum coherence, and quantum tunnelling as deliberate engineering tools, enabling a new generation of technologies with capabilities that are fundamentally unreachable by any classical means.
The Quantum 2.0 market encompasses five primary technology pillars. Quantum computing encodes information in qubits that can exist in superpositions of 0 and 1 simultaneously, enabling exponential parallelism for optimisation, simulation, and machine learning problems intractable to the fastest classical supercomputers. Hardware platforms currently in commercial development include superconducting, trapped ion, silicon spin, photonic, neutral atom, and topological qubit architectures, each with distinct fidelity, coherence, and scalability trade-offs. Quantum communications - spanning quantum key distribution, quantum random number generation, and post-quantum cryptography - exploits entanglement and the no-cloning theorem to deliver provably secure cryptographic protocols. Quantum sensing produces precision instruments - atomic clocks, gravimeters, magnetometers, gyroscopes, and RF field sensors - whose sensitivity surpasses classical limits by harnessing squeezed states and quantum interference. Quantum simulation uses controllable quantum systems to model molecular and materials dynamics that overwhelm classical computers, with high-value applications in pharmaceutical drug discovery, materials science, and catalyst design. Quantum machine learning combines quantum algorithms with classical neural networks to identify quantum advantages in optimisation and pattern recognition.
Commercially, 2025 proved the decisive inflection point. Full-year quantum financings approached $10 billion globally - more than five times the 2023 trough - with fifteen companies each raising over $100 million. Cumulative global investment from 2012 through early 2026 exceeded $60 billion, with government commitments representing roughly half. North America holds approximately 47% of global investment share, followed by Asia-Pacific at 29% and Europe at 15-16%. National quantum strategies - from the US National Quantum Initiative and the EU Quantum Flagship to programmes in China, the UK, Germany, France, Australia, and India - reflect a strategic global race that spans both civilian commerce and national security.
The Global Quantum 2.0 Market 2026-2036, published by Future Markets, Inc. is the most comprehensive commercial intelligence report available on the second quantum revolution. At 608 pages and spanning 17 chapters, 185 data tables, and company profiles of more than 320 organisations, it constitutes an authoritative reference for investors, technology developers, corporate strategists, and government policymakers navigating the rapidly expanding quantum technology landscape.
The report opens with an exceptionally detailed Executive Summary that documents the historic investment surge of 2025 - a year in which total global quantum financings approached $10 billion, more than double any prior year. It traces cumulative investment trajectories from 2012 through early 2026 (exceeding $60 billion globally), maps the investment landscape by technology segment, company, application, and region, and provides a granular account of the most significant deals, acquisitions, and government commitments of the 2024-2025 period. Key milestones documented include IonQ's $1.075 billion acquisition of Oxford Ionics, PsiQuantum's $1 billion Series E led by BlackRock and Temasek, Quantinuum's $600 million raise at a $10 billion valuation, and Microsoft's unveiling of its Majorana 1 topological qubit chip. The Executive Summary also presents a high-level Quantum 2.0 Market Map, SWOT analysis, value chain overview, and consolidated market forecasts to 2036.
The main body of the report provides deep technical and commercial analysis across all six Quantum 2.0 technology domains. The quantum computing chapter covers all major qubit hardware architectures - superconducting, trapped ion, silicon spin, topological, photonic, neutral atom, and diamond-defect qubits - with technology descriptions, materials analysis, hardware roadmaps, SWOT analyses, market player profiles, and competitive benchmarking against classical, quantum-inspired, and neuromorphic computing approaches. It also addresses quantum software, cloud-based quantum computing as a service (QCaaS), error correction and fault tolerance, quantum data centres, and end-use applications across pharmaceuticals, chemicals, transportation, and financial services. A dedicated chapter on Quantum Chemistry and Artificial Intelligence examines the convergence of quantum simulation with AI-driven materials discovery and drug design.
Quantum machine learning and quantum simulation each receive standalone chapters covering their technical foundations, algorithmic approaches, phase evolution, application landscapes, and market forecasts to 2036. The quantum communications chapter is particularly extensive, addressing quantum random number generation (QRNG), quantum key distribution (QKD) across fibre, free-space, and satellite modalities, post-quantum cryptography following the NIST 2024 standardisation outcomes, quantum networks and the quantum internet, quantum teleportation, and quantum memory. Quantum sensing covers the full spectrum of sensor types including atomic clocks, magnetometers, gravimeters, gyroscopes, image sensors, quantum radar, quantum RF sensors, and quantum NEMS/MEMS, with per-sensor forecasts by volume, price band, and end-use industry. Quantum batteries - an emerging segment covering quantum-coherence-enhanced energy storage - are also comprehensively examined.
The materials chapter addresses superconductors, silicon photonics, photonic integrated circuits, nanomaterials, and artificial diamond as enabling material platforms, with supply chain analysis and materials market forecasts. A regional analysis chapter covers North America, Europe (including the EU, UK, Germany, France, and Netherlands individually), Asia-Pacific (China, Japan, South Korea, Australia, Singapore), and the rest of the world. The global market analysis chapter consolidates revenue forecasts across all segments from 2018 to 2046. The report concludes with an extensive company profiles chapter and a comprehensive references section.
Throughout, the report maintains strict methodological rigour, drawing on primary interviews with manufacturers and end users, supplemented by secondary research. Its market forecasts are independently derived and segmented by technology type, end-use industry, and geography, providing a multi-dimensional view of commercial opportunity across the entire Quantum 2.0 value chain.
Report Contents include:
- Executive Summary - 2025 investment surge analysis; $10 billion in quantum financings; Technology Readiness Level (TRL) assessment; market map, SWOT, value chain, and consolidated 2026-2036 forecast
- Introduction to Quantum 2.0 Technologies - First and second quantum revolutions; quantum mechanics principles (superposition, entanglement, coherence, tunnelling); enabling technologies and standards development
- Quantum Computing - All qubit hardware platforms (superconducting, trapped ion, silicon spin, topological, photonic, neutral atom, diamond-defect, quantum annealers); benchmarking metrics; quantum volume; algorithms; software stack; QCaaS; error correction; fault tolerance; data centres; end-use applications in pharma, chemicals, transportation, and financial services; market forecasts
- Quantum Chemistry & Artificial Intelligence - Technology description; applications; SWOT; market challenges; market players; opportunity analysis; technology roadmap
- Quantum Machine Learning - Classical vs quantum ML paradigms; QML phases (NISQ-era and fault-tolerant); quantum neural networks; variational quantum classifiers; quantum kernel methods; advantages; challenges; applications; market forecasts 2026-2036
- Quantum Simulation - Analog vs digital simulation; platforms (neutral atom, trapped ion, superconducting, photonic); applications (molecular simulation, materials discovery, high-energy physics, condensed matter, drug discovery); market forecasts 2026-2036
- Quantum Communications - QRNG (technology, entropy sources, standards, applications); QKD (fibre, free-space, satellite, MDI-QKD, DV/CV protocols); post-quantum cryptography (NIST standards, migration implications); quantum networks; quantum teleportation; quantum memory; quantum internet; global deployments by region; market forecasts
- Quantum Sensors - Atomic clocks; quantum magnetometers (SQUIDs, OPMs, TMR sensors, NV centres); quantum gravimeters; quantum gyroscopes; quantum image sensors; quantum radar; quantum chemical sensors; quantum RF sensors (Rydberg-atom and NV-centre); quantum NEMS/MEMS; market forecasts by sensor type, volume, price band, and end-use industry; technology roadmap
- Quantum Batteries - Technology description; types; applications; SWOT; market challenges; market players; opportunity analysis; technology roadmap
- End-Use Markets & Applications - Pharmaceuticals & drug discovery; financial services (portfolio optimisation, risk assessment, algorithmic trading, fraud detection); aerospace & defence; energy & utilities; healthcare & medical; telecommunications; government & public sector
- Materials for Quantum Technologies - Superconductors (types, properties, critical temperatures, supply chain, SQUIDs, SNSPDs); photonics, silicon photonics, and PICs; nanomaterials; artificial diamond; materials market forecasts
- Regional Market Analysis - North America (US, Canada); Europe (EU, UK, Germany, France, Netherlands); Asia-Pacific (China, Japan, South Korea, Australia, Singapore); Rest of World; government initiatives comparison
- Global Market Analysis - Market map; key industry players (start-ups, tech giants, national initiatives); global market revenues 2018-2046 across all segments; consolidated Quantum 2.0 total forecast
- Company Profiles - 320+ companies across all Quantum 2.0 domains
- Research Methodology, Terms & Definitions, References
The report profiles more than 320 companies spanning all Quantum 2.0 technology segments, including hardware manufacturers, software developers, communications specialists, sensing companies, materials suppliers, and quantum-enabled application providers. Companies profiled include 1QBit, A* Quantum, AbaQus, Absolut System, Adaptive Finance Technologies, Aegiq, Agnostiq GmbH, Airbus, Alea Quantum, Alice & Bob, Aliro Quantum, Algorithmiq Oy, Alpine Quantum Technologies GmbH (AQT), Anametric Inc., Anyon Systems Inc., Aqarios GmbH, Aquark Technologies, Archer Materials, Arclight Quantum, Arctic Instruments, Arqit Quantum Inc., ARQUE Systems GmbH, Artificial Brain, Artilux, Atlantic Quantum, Atom Computing, Atom Quantum Labs, Atomionics, Atos Quantum, Baidu Inc., BEIT, Beyond Blood Diagnostics, Bifrost Electronics, Bleximo, BlueFors, BlueQubit, Bohr Quantum Technology, Bosch Quantum Sensing, BosonQ Ps, C12 Quantum Electronics, Cambridge Quantum Computing (CQC), CAS Cold Atom, CEW Systems Canada Inc., Cerca Magnetics, Chipiron, Chiral Nano AG, Classiq Technologies, ColibriTD, Commutator Studios GmbH, Covesion, Crypta Labs Ltd., CryptoNext Security, Crystal Quantum Computing, D-Wave Systems, Delft Circuits, Delta g, DeteQt, Diatope GmbH, Dirac, Diraq, Duality Quantum Photonics, EeroQ, eleQtron, Element Six, Elyah, Entropica Labs, Ephos, Equal1.labs, EuQlid, EvolutionQ, Exail Quantum Sensors, EYL, First Quantum Inc., Fujitsu, Genesis Quantum Technology, GenMat, Good Chemistry, Google Quantum AI, Groove Quantum, g2-Zero, Haiqu, Hefei Wanzheng Quantum Technology Co. Ltd., High Q Technologies Inc., Horizon Quantum Computing, HQS Quantum Simulations, HRL, Huayi Quantum, IBM, Icarus Quantum, Iceberg Quantum, Icosa Computing, ID Quantique and more....
TABLE OF CONTENTS
1 EXECUTIVE SUMMARY
- 1.1 Quantum Technologies Market in 2026
- 1.1.1 Q1 2025: The Surge That Set the Tone
- 1.1.2 Q2 2025: Momentum Builds Across the Stack
- 1.1.3 Q3 2025: Mega-Rounds and a New Valuation Era
- 1.1.4 Q4 2025: Going Public and Consolidation Accelerates
- 1.1.5 Into 2026: The Public Market Era Begins
- 1.1.6 The Strategic Picture: What $10 Billion Means
- 1.1.7 2025 as Quantum Technology's Commercial Watershed
- 1.2 First and second quantum revolutions
- 1.3 Current quantum technology market landscape
- 1.3.1 Key developments
- 1.4 Technology Readiness Assessment
- 1.5 Quantum Technologies Investment Landscape
- 1.5.1 Total market investments 2012-2025
- 1.5.2 By Technology
- 1.5.3 By Company
- 1.5.4 By Application
- 1.5.5 By Region
- 1.5.5.1 The Quantum Market in North America
- 1.5.5.2 The Quantum Market in Asia
- 1.5.5.3 The Quantum Market in Europe
- 1.5.6 Key Investment Trends 2025-2026
- 1.6 Global government initiatives and funding
- 1.6.1 United States
- 1.6.2 China
- 1.6.3 European Union
- 1.6.4 Germany
- 1.6.5 United Kingdom
- 1.6.6 France
- 1.6.7 Canada
- 1.6.8 Australia
- 1.6.9 Japan
- 1.6.10 India
- 1.6.11 Cross-Cutting Themes in Government Quantum Investment
- 1.7 Challenges for quantum technologies adoption
- 1.8 Quantum 2.0 Market Map
- 1.9 SWOT Analysis
- 1.10 Quantum 2.0 Value Chain
- 1.11 Global Market Forecast 2026-2036
- 1.11.1 Total Market Revenues
- 1.11.2 By Technology Segment
- 1.11.3 By End-Use Industry
2 INTRODUCTION TO QUANTUM 2.0 TECHNOLOGIES
- 2.1 First and Second Quantum Revolutions
- 2.2 Quantum Mechanics Principles
- 2.2.1 Superposition
- 2.2.2 Entanglement
- 2.2.3 Quantum Coherence
- 2.2.4 Quantum Tunnelling
- 2.3 The Quantum 2.0 Technology Ecosystem
- 2.4 Enabling Technologies and Infrastructure
- 2.5 Standards Development
3 QUANTUM COMPUTING
- 3.1 What is quantum computing?
- 3.1.1 Operating principle
- 3.1.2 Classical vs quantum computing
- 3.1.3 Quantum computing technology
- 3.1.3.1 Quantum emulators
- 3.1.3.2 Quantum inspired computing
- 3.1.3.3 Quantum annealing computers
- 3.1.3.4 Quantum simulators
- 3.1.3.5 Digital quantum computers
- 3.1.3.6 Continuous variables quantum computers
- 3.1.3.7 Measurement Based Quantum Computing (MBQC)
- 3.1.3.8 Topological quantum computing
- 3.1.3.9 Quantum Accelerator
- 3.2 Benchmarking and Performance Metrics
- 3.2.1 Qubit Count
- 3.2.2 Gate Fidelity
- 3.2.3 Coherence Times
- 3.2.4 Quantum Volume
- 3.2.5 Competition from other technologies
- 3.2.6 Quantum algorithms
- 3.2.6.1 Quantum Software Stack
- 3.2.6.2 Quantum Machine Learning
- 3.2.6.3 Quantum Simulation
- 3.2.6.4 Quantum Optimization
- 3.2.6.5 Quantum Cryptography
- 3.2.6.5.1 Quantum Key Distribution (QKD)
- 3.2.6.5.2 Post-Quantum Cryptography
- 3.2.7 Architectural Approaches
- 3.2.7.1 Modular vs. Single Core
- 3.2.7.2 Heterogeneous Multi-Qubit Architectures
- 3.2.8 Hardware
- 3.2.8.1 Qubit Technologies
- 3.2.8.1.1 Superconducting Qubits
- 3.2.8.1.1.1 Technology description
- 3.2.8.1.1.2 Materials
- 3.2.8.1.1 Superconducting Qubits
- 3.2.8.2 Hardware Architecture
- 3.2.8.2.1.1 Market players
- 3.2.8.2.1.2 Swot analysis
- 3.2.8.2.1.3 Superconducting Hardware Roadmap
- 3.2.8.2.2 Trapped Ion Qubits
- 3.2.8.2.2.1 Technology description
- 3.2.8.2.2.2 Materials
- 3.2.8.2.2.2.1 Integrating optical components
- 3.2.8.2.2.2.2 Incorporating high-quality mirrors and optical cavities
- 3.2.8.2.2.2.3 Engineering the vacuum packaging and encapsulation
- 3.2.8.2.2.2.4 Removal of waste heat
- 3.2.8.2.2.3 Market players
- 3.2.8.2.2.4 Swot analysis
- 3.2.8.2.2.5 Trapped Ion Hardware Roadmap
- 3.2.8.2.3 Silicon Spin Qubits
- 3.2.8.2.3.1 Technology description
- 3.2.8.2.3.2 Quantum dots
- 3.2.8.2.3.3 Market players
- 3.2.8.2.3.4 SWOT analysis
- 3.2.8.2.3.5 Silicon Spin Hardware Roadmap
- 3.2.8.2.4 Topological Qubits
- 3.2.8.2.4.1 Technology description
- 3.2.8.2.4.1.1 Cryogenic cooling
- 3.2.8.2.4.2 Market players
- 3.2.8.2.4.3 SWOT analysis
- 3.2.8.2.4.1 Technology description
- 3.2.8.2.5 Photonic Qubits
- 3.2.8.2.5.1 Technology description
- 3.2.8.2.5.2 Market players
- 3.2.8.2.5.3 Swot analysis
- 3.2.8.2.5.4 Photonic Hardware Roadmap
- 3.2.8.2.6 Neutral atom (cold atom) qubits
- 3.2.8.2.6.1 Technology description
- 3.2.8.2.6.2 Market players
- 3.2.8.2.6.3 Swot analysis
- 3.2.8.2.6.4 Neutral Atom Hardware Roadmap
- 3.2.8.2.7 Diamond-defect qubits
- 3.2.8.2.7.1 Technology description
- 3.2.8.2.7.2 SWOT analysis
- 3.2.8.2.7.3 Market players
- 3.2.8.2.7.4 Diamond-Defect Hardware Roadmap
- 3.2.8.2.8 Quantum annealers
- 3.2.8.2.8.1 Technology description
- 3.2.8.2.8.2 SWOT analysis
- 3.2.8.2.8.3 Market players
- 3.2.8.2.8.4 Quantum Annealing Hardware Roadmap
- 3.2.8.3 Architectural Approaches
- 3.2.8.4 Quantum Computing Infrastructure Requirements
- 3.2.8.1 Qubit Technologies
- 3.2.9 Software
- 3.2.9.1 Technology description
- 3.2.9.2 Cloud-based services- QCaaS (Quantum Computing as a Service).
- 3.2.9.3 Market players
- 3.3 Market challenges
- 3.4 SWOT analysis
- 3.5 Business Models
- 3.6 Error Correction and Fault Tolerance
- 3.7 Quantum Computing in Data Centres
- 3.8 Quantum computing value chain
- 3.9 Markets and applications for quantum computing
- 3.9.1 Pharmaceuticals
- 3.9.1.1 Market overview
- 3.9.1.1.1 Drug discovery
- 3.9.1.1.2 Diagnostics
- 3.9.1.1.3 Molecular simulations
- 3.9.1.1.4 Genomics
- 3.9.1.1.5 Proteins and RNA folding
- 3.9.1.2 Market players
- 3.9.1.1 Market overview
- 3.9.2 Chemicals
- 3.9.2.1 Market overview
- 3.9.2.2 Market players
- 3.9.3 Transportation
- 3.9.3.1 Market overview
- 3.9.3.2 Market players
- 3.9.4 Financial services
- 3.9.4.1 Market overview
- 3.9.4.2 Market players
- 3.9.1 Pharmaceuticals
- 3.10 Opportunity analysis
- 3.11 Technology roadmap
4 QUANTUM CHEMISTRY AND ARTIFICIAL INTELLIGENCE (AI)
- 4.1 Technology description
- 4.2 Applications
- 4.3 SWOT analysis
- 4.4 Market challenges
- 4.5 Market players
- 4.6 Opportunity analysis
- 4.7 Technology roadmap
5 QUANTUM MACHINE LEARNING
- 5.1 What is Quantum Machine Learning?
- 5.2 Classical vs. Quantum Computing Paradigms for ML
- 5.3 Quantum Mechanical Principles for ML
- 5.4 Machine Learning Fundamentals
- 5.5 The Intersection - Why Combine Quantum and ML?
- 5.6 QML Phases and Evolution
- 5.6.1 The First Phase of QML
- 5.6.2 The Second Phase of QML
- 5.7 Algorithms and Software for QML
- 5.8 Quantum Neural Networks
- 5.9 Variational Quantum Classifiers
- 5.10 Quantum Kernel Methods
- 5.11 Advantages of QML
- 5.11.1 Improved Optimisation and Generalisation
- 5.11.2 Quantum Advantage in ML
- 5.11.3 Training Advantages and Opportunities
- 5.11.4 Improved Accuracy
- 5.12 Challenges and Limitations
- 5.12.1 Hardware Constraints
- 5.12.2 Costs
- 5.12.3 Nascent Technology
- 5.13 QML Applications
- 5.14 QML Roadmap
- 5.15 Market Players
- 5.16 Market Forecasts 2026-2036
6 QUANTUM SIMULATION
- 6.1 What is Quantum Simulation?
- 6.2 Analog vs. Digital Quantum Simulation
- 6.3 Quantum Simulation Platforms
- 6.3.1 Neutral Atom Simulators
- 6.3.2 Trapped Ion Simulators
- 6.3.3 Superconducting Circuit Simulators
- 6.3.4 Photonic Simulators
- 6.4 Applications of Quantum Simulation
- 6.4.1 Molecular and Chemical Simulation
- 6.4.2 Materials Discovery
- 6.4.3 High-Energy Physics
- 6.4.4 Condensed Matter Physics
- 6.4.5 Drug Discovery and Protein Folding
- 6.5 Quantum Chemistry Simulation
- 6.6 Market Players
- 6.7 SWOT Analysis
- 6.8 Market Forecasts 2026-2036
7 QUANTUM COMMUNICATIONS
- 7.1 Technology description
- 7.2 Types
- 7.3 Applications
- 7.4 Quantum Random Numbers Generators (QRNG)
- 7.4.1 Overview
- 7.4.2 QRNG Product Design and Technology Evolution
- 7.4.3 Entropy Sources
- 7.4.4 High Throughput as Key Differentiator
- 7.4.5 Standards Development
- 7.4.6 Applications
- 7.4.6.1 Encryption for Data Centers
- 7.4.6.2 Consumer Electronics
- 7.4.6.3 Automotive/Connected Vehicle
- 7.4.6.4 Gambling and Gaming
- 7.4.6.5 Monte Carlo Simulations
- 7.4.6.6 Government and Defense Applications
- 7.4.6.7 Enterprise Networks and Data Centers
- 7.4.6.8 Automotive Applications
- 7.4.6.9 Online Gaming
- 7.4.7 Advantages
- 7.4.8 Principle of Operation of Optical QRNG Technology
- 7.4.9 Non-optical approaches to QRNG technology
- 7.4.10 SWOT Analysis
- 7.4.11 Market Forecasts
- 7.5 Quantum Key Distribution (QKD)
- 7.5.1 Overview
- 7.5.2 Asymmetric and Symmetric Keys
- 7.5.3 Principle behind QKD
- 7.5.4 Why is QKD More Secure Than Other Key Exchange Mechanisms?
- 7.5.5 Discrete Variable vs. Continuous Variable QKD Protocols
- 7.5.6 MDI-QKD (Measurement Device Independent QKD)
- 7.5.7 Fiber-Based QKD
- 7.5.8 Free-Space and Satellite QKD
- 7.5.9 Key Players
- 7.5.10 Challenges
- 7.5.11 SWOT Analysis
- 7.5.12 Market Forecasts
- 7.6 Post-quantum cryptography (PQC)
- 7.6.1 Overview
- 7.6.2 Security systems integration
- 7.6.3 PQC standardization
- 7.6.3.1 NIST Standardisation Process and Outcomes
- 7.6.3.2 Migration Implications
- 7.6.4 Transitioning cryptographic systems to PQC
- 7.6.5 Market players
- 7.6.6 SWOT Analysis
- 7.6.7 Market Forecasts
- 7.7 Quantum homomorphic cryptography
- 7.8 Quantum Teleportation
- 7.9 Quantum Networks
- 7.9.1 Overview
- 7.9.2 Advantages
- 7.9.3 Role of Trusted Nodes and Trusted Relays
- 7.9.4 Entanglement Swapping and Optical Switches
- 7.9.5 Multiplexing quantum signals with classical channels in the O-band
- 7.9.5.1 Wavelength-division multiplexing (WDM) and time-division multiplexing (TDM)
- 7.9.6 Twin-Field Quantum Key Distribution (TF-QKD)
- 7.9.7 Enabling global-scale quantum communication
- 7.9.8 Advanced optical fibers and interconnects
- 7.9.9 Photodetectors in quantum networks
- 7.9.9.1 Avalanche photodetectors (APDs)
- 7.9.9.2 Single-photon avalanche diodes (SPADs)
- 7.9.9.3 Silicon Photomultipliers (SiPMs)
- 7.9.10 Cryostats
- 7.9.10.1 Cryostat architectures
- 7.9.11 Infrastructure requirements
- 7.9.12 Global activity
- 7.9.12.1 China
- 7.9.12.2 Europe
- 7.9.12.3 The Netherlands
- 7.9.12.4 The United Kingdom
- 7.9.12.5 US
- 7.9.12.6 Japan
- 7.9.13 SWOT analysis
- 7.10 Quantum Memory
- 7.11 Quantum Internet
- 7.12 Global Market for Quantum Communications by Technology Type 2026-2036
- 7.13 Market challenges
- 7.14 Market players
- 7.15 Opportunity analysis
- 7.16 Technology roadmap
8 QUANTUM SENSORS
- 8.1 Technology description
- 8.1.1 Quantum Sensing Principles
- 8.1.2 SWOT analysis
- 8.1.3 Atomic Clocks
- 8.1.3.1 High frequency oscillators
- 8.1.3.1.1 Emerging oscillators
- 8.1.3.2 Caesium atoms
- 8.1.3.3 Self-calibration
- 8.1.3.4 Optical atomic clocks
- 8.1.3.4.1 Chip-scale optical clocks
- 8.1.3.5 Bench/Rack-Scale Atomic Clocks
- 8.1.3.6 Chip-Scale Atomic Clocks (CSAC)
- 8.1.3.7 Atomic Clocks Market Forecasts - Total
- 8.1.3.8 Companies
- 8.1.3.9 SWOT analysis
- 8.1.3.1 High frequency oscillators
- 8.1.4 Quantum Magnetic Field Sensors
- 8.1.4.1 Introduction
- 8.1.4.2 Motivation for use
- 8.1.4.3 Market opportunity
- 8.1.4.4 Superconducting Quantum Interference Devices (Squids)
- 8.1.4.4.1 Applications
- 8.1.4.4.2 Key players
- 8.1.4.4.3 SWOT analysis
- 8.1.4.5 Optically Pumped Magnetometers (OPMs)
- 8.1.4.5.1 Applications
- 8.1.4.5.2 Key players
- 8.1.4.5.3 SWOT analysis
- 8.1.4.6 Tunneling Magneto Resistance Sensors (TMRs)
- 8.1.4.6.1 Applications
- 8.1.4.6.2 Key players
- 8.1.4.6.3 SWOT analysis
- 8.1.4.7 Nitrogen Vacancy Centers (N-V Centers)
- 8.1.4.7.1 Applications
- 8.1.4.7.2 Key players
- 8.1.4.7.3 SWOT analysis
- 8.1.5 Quantum Gravimeters
- 8.1.5.1 Technology description
- 8.1.5.2 Applications
- 8.1.5.3 Key players
- 8.1.5.4 SWOT analysis
- 8.1.6 Quantum Gyroscopes
- 8.1.6.1 Technology description
- 8.1.6.1.1 Inertial Measurement Units (IMUs)
- 8.1.6.1.2 Atomic quantum gyroscopes
- 8.1.6.2 Applications
- 8.1.6.3 Key players
- 8.1.6.4 SWOT analysis
- 8.1.6.1 Technology description
- 8.1.7 Quantum Image Sensors
- 8.1.7.1 Technology description
- 8.1.7.2 Applications
- 8.1.7.3 SWOT analysis
- 8.1.7.4 Key players
- 8.1.8 Quantum Radar
- 8.1.8.1 Technology description
- 8.1.8.2 Applications
- 8.1.9 Quantum Navigation
- 8.1.10 Quantum Sensor Components
- 8.1.11 Quantum Chemical Sensors
- 8.1.11.1 Technology overview
- 8.1.11.2 Commercial activities
- 8.1.12 Quantum Radio Frequency Field Sensors
- 8.1.12.1 Overview
- 8.1.12.2 Rydberg Atom Based Electric Field Sensors and Radio Receivers
- 8.1.12.2.1 Principles
- 8.1.12.2.2 Commercialization
- 8.1.12.3 Nitrogen-Vacancy Centre Diamond Electric Field Sensors and Radio Receivers
- 8.1.12.3.1 Principles
- 8.1.12.3.2 Applications
- 8.1.12.4 Market
- 8.1.13 Quantum NEM and MEMs
- 8.1.13.1 Technology description
- 8.2 Market and technology challenges
- 8.3 Market forecasts
- 8.3.1 By Sensor Type
- 8.3.2 By Volume
- 8.3.3 By Sensor Price
- 8.3.4 By End-Use Industry
- 8.4 Technology roadmap
9 QUANTUM BATTERIES
- 9.1 Technology description
- 9.2 Types
- 9.3 Applications
- 9.4 SWOT analysis
- 9.5 Market challenges
- 9.6 Market players
- 9.7 Opportunity analysis
- 9.8 Technology roadmap
10 END-USE MARKETS AND APPLICATIONS
- 10.1 Overview
- 10.2 Pharmaceuticals and Drug Discovery
- 10.2.1 Market Overview
- 10.2.2 Drug Discovery Applications
- 10.3 Financial Services
- 10.3.1 Market Overview
- 10.3.2 Portfolio Optimisation
- 10.3.3 Risk Assessment
- 10.3.4 Algorithmic Trading
- 10.3.5 Fraud Detection
- 10.4 Aerospace and Defence
- 10.4.1 Market Overview
- 10.4.2 Navigation and Positioning
- 10.4.3 Secure Communications
- 10.4.4 Simulation and Optimisation
- 10.5 Energy and Utilities
- 10.5.1 Market Overview
- 10.5.2 Grid Optimisation
- 10.5.3 Renewable Energy Integration
- 10.5.4 Carbon Capture Optimisation
- 10.6 Healthcare and Medical
- 10.6.1 Market Overview
- 10.6.2 Medical Imaging
- 10.6.3 Diagnostics
- 10.6.4 Personalized Medicine
- 10.7 Telecommunications
- 10.7.1 Market Overview
- 10.7.2 Network Optimisation
- 10.7.3 Quantum-Secure Networks
- 10.8 Government and Public Sector
- 10.8.1 Market Overview
11 MATERIALS FOR QUANTUM TECHNOLOGIES
- 11.1 Superconductors
- 11.1.1 Overview
- 11.1.2 Types and Properties
- 11.1.3 Critical Temperature and Material Selection
- 11.1.3.1 Critical Material Supply Chain Considerations
- 11.1.4 Superconducting Quantum Circuits
- 11.1.4.1 Introduction
- 11.1.4.2 Fabricating Superconducting Qubits
- 11.1.5 Defects and Sources of Noise
- 11.1.6 Superconducting Nanowire Single-Photon Detectors (SNSPDs) - Materials and Fabrication
- 11.1.7 Opportunities
- 11.2 Photonics, Silicon Photonics and Optical Components
- 11.2.1 Overview
- 11.2.2 Types and Properties
- 11.2.3 Photonic Integrated Circuits for Quantum Technology
- 11.2.3.1 Overview
- 11.2.4 PICs for Quantum Sensing
- 11.2.5 Opportunities
- 11.3 Nanomaterials
- 11.3.1 Overview
- 11.3.2 Types and Properties
- 11.3.3 Opportunities
- 11.4 Artificial Diamond for Quantum Technology
- 11.4.1 Overview
- 11.4.2 Supply Chain and Materials for Diamond-Based Quantum Computers
- 11.4.3 Quantum Grade Diamond
- 11.4.4 Silicon-Vacancy in Diamond Quantum Memory
- 11.5 Materials Market Forecasts
12 REGIONAL MARKET ANALYSIS
- 12.1 North America
- 12.1.1 United States
- 12.1.2 Canada
- 12.2 Europe
- 12.2.1 European Union Initiatives
- 12.2.2 United Kingdom
- 12.2.3 Germany
- 12.2.4 France
- 12.2.5 Netherlands
- 12.3 Asia-Pacific
- 12.3.1 China
- 12.3.2 Japan
- 12.3.3 South Korea
- 12.3.4 Australia
- 12.3.5 Singapore
- 12.4 Rest of World
- 12.5 Government Initiatives Comparison
13 GLOBAL MARKET ANALYSIS
- 13.1 Market map
- 13.2 Key industry players
- 13.2.1 Start-ups
- 13.2.2 Tech Giants
- 13.2.3 National Initiatives
- 13.3 Global market revenues 2018-2046
- 13.3.1 Quantum Computing
- 13.3.2 Quantum Sensors
- 13.3.3 QKD Systems
- 13.3.4 Quantum Random Number Generators (QRNG)
- 13.3.5 Post-Quantum Cryptography (PQC)
- 13.3.6 Quantum Machine Learning
- 13.3.7 Quantum Simulation
- 13.3.8 Quantum Batteries
- 13.3.9 Total Quantum 2.0 Market - Consolidated Forecast
14 COMPANY PROFILES (331 company profiles)
15 RESEARCH METHODOLOGY
16 TERMS AND DEFINITIONS
17 REFERENCES
List of Tables
- Table 1. 2025-2026 Quantum Technology Investment
- Table 2. First and second quantum revolutions.
- Table 3. Technology Readiness Level (TRL) assessment by quantum platform
- Table 4. Quantum Technology Total Investments 2012-2026 (millions USD)
- Table 5. Major Quantum Technologies Investments 2024-2026
- Table 6. Quantum Technology Investments 2012-2026 by Technology Subsector (millions USD)
- Table 7. Quantum Technology Funding 2022-2026 by Company (USD)
- Table 8. Quantum Technology Investment by Application 2012-2026 (millions USD)
- Table 9. Quantum Technology Investments 2012-2026 by Region (millions USD)
- Table 10. Key Quantum Investment Trends 2025-2026
- Table 11.Global Government Quantum Commitments (2022-2026)
- Table 12. Challenges for quantum technologies adoption.
- Table 13. Quantum 2.0 value chain
- Table 14. Total Quantum 2.0 market forecast 2026-2036 (billions USD)
- Table 15. Quantum 2.0 market by end-use industry 2026-2036 (billions USD)
- Table 16. Quantum 2.0 market by region 2026-2036 (billions USD)
- Table 17. First and second quantum revolutions
- Table 18. Comparison - Classical vs. Quantum Technologies
- Table 19. Applications for quantum computing
- Table 20. Comparison of classical versus quantum computing.
- Table 21. Key quantum mechanical phenomena utilized in quantum computing.
- Table 22. Types of quantum computers.
- Table 23. Qubit performance benchmarking by platform
- Table 24. Coherence times for different qubit implementations
- Table 25. Quantum computer benchmarking metrics
- Table 26. Logical qubit progress
- Table 27. Comparative analysis of quantum computing with classical computing, quantum-inspired computing, and neuromorphic computing.
- Table 28. Different computing paradigms beyond conventional CMOS.
- Table 29. Applications of quantum algorithms.
- Table 30. QML approaches.
- Table 31. Modular vs. single core architectures
- Table 32. Heterogeneous architectural approaches by provider
- Table 33. Coherence times for different qubit implementations.
- Table 34. Superconducting qubit market players.
- Table 35. Initialization, manipulation and readout for trapped ion quantum computers.
- Table 36. Ion trap market players.
- Table 37. Initialization, manipulation, and readout methods for silicon-spin qubits.
- Table 38. Silicon spin qubits market players.
- Table 39. Initialization, manipulation and readout of topological qubits.
- Table 40. Topological qubits market players.
- Table 41. Pros and cons of photon qubits.
- Table 42. Comparison of photon polarization and squeezed states.
- Table 43. Initialization, manipulation and readout of photonic platform quantum computers.
- Table 44. Photonic qubit market players.
- Table 45. Initialization, manipulation and readout for neutral-atom quantum computers.
- Table 46. Pros and cons of cold atoms quantum computers and simulators
- Table 47. Neural atom qubit market players.
- Table 48. Initialization, manipulation and readout of Diamond-Defect Spin-Based Computing.
- Table 49. Key materials for developing diamond-defect spin-based quantum computers.
- Table 50. Diamond-defect qubits market players.
- Table 51. Pros and cons of quantum annealers.
- Table 52. Quantum annealers market players.
- Table 53. Quantum computing infrastructure requirements
- Table 54. Quantum computing software market players.
- Table 55. Market challenges in quantum computing.
- Table 56. Business models in quantum computing
- Table 57. Quantum computing value chain.
- Table 58. Markets and applications for quantum computing.
- Table 59. Market players in quantum technologies for pharmaceuticals.
- Table 60. Market players in quantum computing for chemicals.
- Table 61. Automotive applications of quantum computing,
- Table 62. Market players in quantum computing for transportation.
- Table 63. Market players in quantum computing for financial services
- Table 64. Market opportunities in quantum computing.
- Table 65. Applications in quantum chemistry and artificial intelligence (AI).
- Table 66. Market challenges in quantum chemistry and Artificial Intelligence (AI).
- Table 67. Market players in quantum chemistry and AI.
- Table 68. Market opportunities in quantum chemistry and AI.
- Table 69. Classical vs. quantum computing paradigms for machine learning
- Table 70. QML phases and evolution
- Table 71. QML approaches
- Table 72. Advantages of quantum machine learning
- Table 73. Challenges and limitations of QML
- Table 74. QML applications by industry
- Table 75. QML market players
- Table 76. QML market forecasts 2026-2036 (millions USD)
- Table 77. Comparison of analog and digital quantum simulation approaches
- Table 78. Quantum simulation platforms comparison
- Table 79. Applications of quantum simulation by industry
- Table 80. Applications in quantum chemistry and artificial intelligence
- Table 81. Market challenges in quantum chemistry simulation
- Table 82. Quantum simulation market players
- Table 83. Quantum simulation market forecasts 2026-2036 (millions USD)
- Table 84. Main types of quantum communications.
- Table 85. Applications in quantum communications.
- Table 86. QRNG entropy sources comparison
- Table 87. QRNG standards development
- Table 88. QRNG applications.
- Table 89. Key Players Developing QRNG Products.
- Table 90. Optical QRNG by company.
- Table 91. QRNG market forecasts 2026-2036 by application segment (millions USD)
- Table 92. QKD protocols comparison
- Table 93. Markets for QKD systems by end-use industry and delivery method 2026-2036 (millions USD)
- Table 94. Market players in post-quantum cryptography.
- Table 95. PQC market forecasts by cryptographic approach 2026-2036 (millions USD)
- Table 96. Global market for quantum communications by technology type 2026-2036 (millions USD)
- Table 97. Market challenges in quantum communications.
- Table 98. Market players in quantum communications.
- Table 99. Market opportunities in quantum communications.
- Table 100. Comparison between classical and quantum sensors.
- Table 101. Applications in quantum sensors.
- Table 102. Technology approaches for enabling quantum sensing
- Table 103. Value proposition for quantum sensors.
- Table 104. Key challenges and limitations of quartz crystal clocks vs. atomic clocks.
- Table 105. New modalities being researched to improve the fractional uncertainty of atomic clocks.
- Table 106. Global market for bench/rack-scale atomic clocks 2026-2036 (millions USD)
- Table 107. Global market for chip-scale atomic clocks 2026-2036 (millions USD)
- Table 108. Global market for atomic clocks 2026-2036 (billions USD)
- Table 109. Companies developing high-precision quantum time measurement
- Table 110. Key players in atomic clocks.
- Table 111. Comparative analysis of key performance parameters and metrics of magnetic field sensors.
- Table 112. Types of magnetic field sensors.
- Table 113. Market opportunity for different types of quantum magnetic field sensors.
- Table 114. Applications of SQUIDs.
- Table 115. Market opportunities for SQUIDs (Superconducting Quantum Interference Devices).
- Table 116. Key players in SQUIDs.
- Table 117. Applications of optically pumped magnetometers (OPMs).
- Table 118. Key players in Optically Pumped Magnetometers (OPMs).
- Table 119. Applications for TMR (Tunneling Magnetoresistance) sensors.
- Table 120. Market players in TMR (Tunneling Magnetoresistance) sensors.
- Table 121. Applications of N-V center magnetic field centers
- Table 122. Key players in N-V center magnetic field sensors.
- Table 123. Applications of quantum gravimeters
- Table 124. Comparative table between quantum gravity sensing and some other technologies commonly used for underground mapping.
- Table 125. Key players in quantum gravimeters.
- Table 126. Comparison of quantum gyroscopes with MEMs gyroscopes and optical gyroscopes.
- Table 127. Markets and applications for quantum gyroscopes.
- Table 128. Key players in quantum gyroscopes.
- Table 129. Types of quantum image sensors and their key features/.
- Table 130. Applications of quantum image sensors.
- Table 131. Key players in quantum image sensors.
- Table 132. Comparison of quantum radar versus conventional radar and lidar technologies.
- Table 133. Applications of quantum radar.
- Table 134. Single-photon detector technology comparison
- Table 135. SNSPD market players
- Table 136. Quantum sensor component categories and functions
- Table 137. Challenges for quantum sensor components
- Table 138. Value Proposition of Quantum RF Sensors
- Table 139. Types of Quantum RF Sensors
- Table 140. Markets for Quantum RF Sensors
- Table 141. Technology Transition Milestones.
- Table 142. Market and technology challenges in quantum sensing.
- Table 143. Global market for quantum sensors by sensor type 2018-2036 (Millions USD)
- Table 144. Extended forecast to 2046 (Millions USD)
- Table 145. Global market for quantum sensors by volume 2018-2046 (Units)
- Table 146. Global market for quantum sensors by sensor price 2025-2046 (Units)
- Table 147. Extended price segmentation to 2046 (Units - selected years)
- Table 148. Global market for quantum sensors by end-use industry 2018-2036 (Millions USD)
- Table 149. Extended forecast to 2046 (Millions USD)
- Table 150. Comparison between quantum batteries and other conventional battery types.
- Table 151. Types of quantum batteries.
- Table 152. Applications of quantum batteries.
- Table 153. Market challenges in quantum batteries.
- Table 154. Market players in quantum batteries.
- Table 155. Market opportunities in quantum batteries.
- Table 156. Total addressable market (TAM) for quantum technologies by sector
- Table 157. End-user industry investment in quantum readiness
- Table 158. Market players in quantum technologies for pharmaceuticals
- Table 159. Market players in quantum computing for financial services
- Table 160. Materials in Quantum Technology.
- Table 161. Superconductors in quantum technology.
- Table 162. Critical temperature of superconducting materials for quantum technology
- Table 163. Transmon superconducting qubit structure and materials
- Table 164. Summary of manufacturing processes for superconducting quantum chips
- Table 165. Defects and sources of noise for superconducting quantum circuits
- Table 166. Fabrication methods for SNSPDs
- Table 167. Photonics, silicon photonics and optics in quantum technology.
- Table 168. Quantum PIC material platforms benchmarked
- Table 169. PIC materials used by quantum technology companies
- Table 170. Nanomaterials in quantum technology.
- Table 171. Material advantages and disadvantages of diamond for quantum applications
- Table 172. Synthetic diamond value chain for quantum technology
- Table 173. Market forecast for superconducting chips for quantum technologies 2026-2036 (millions USD)
- Table 174. Market forecast for PICs for quantum technologies 2026-2036 (millions USD)
- Table 175. Market forecast for diamond for quantum technologies 2026-2036 (millions USD)
- Table 176. Global government quantum initiatives comparison
- Table 177. Global Market for Quantum Computing - Hardware, Software & Services 2025-2046 (billions USD)
- Table 178. Markets for Quantum Sensors by Type 2025-2046 (millions USD)
- Table 179. Markets for QKD Systems 2025-2046 (millions USD)
- Table 180. Global Market for Quantum Random Number Generators by Application 2025-2046 (millions USD)
- Table 181. Global Market for Post-Quantum Cryptography by Approach 2025-2046 (millions USD)
- Table 182. Global Market for Quantum Machine Learning by Segment 2025-2046 (millions USD)
- Table 183. Global Market for Quantum Simulation by Application 2025-2046 (millions USD)
- Table 184. Global Market for Quantum Batteries by Application 2025-2046 (millions USD)
- Table 185. Total Quantum 2.0 Market by Segment 2026-2036 (billions USD)
- Table 186. Quantum 2.0 Market by End-Use Industry 2026-2036 (billions USD)
- Table 187. Quantum 2.0 Market by Region 2026-2036 (billions USD)
List of Figures
- Figure 1. Quantum computing development timeline.
- Figure 2. Quantum computing architectures.
- Figure 3. An early design of an IBM 7-qubit chip based on superconducting technology.
- Figure 4. Various 2D to 3D chips integration techniques into chiplets.
- Figure 5. IBM Q System One quantum computer.
- Figure 6. Unconventional computing approaches.
- Figure 7. 53-qubit Sycamore processor.
- Figure 8. Interior of IBM quantum computing system. The quantum chip is located in the small dark square at center bottom.
- Figure 9. Superconducting quantum computer.
- Figure 10. Superconducting quantum computer schematic.
- Figure 11. Components and materials used in a superconducting qubit.
- Figure 12. SWOT analysis for superconducting quantum computers:.
- Figure 13. Ion-trap quantum computer.
- Figure 14. Various ways to trap ions.
- Figure 15. Universal Quantum's shuttling ion architecture in their Penning traps.
- Figure 16. SWOT analysis for trapped-ion quantum computing.
- Figure 17. CMOS silicon spin qubit.
- Figure 18. Silicon quantum dot qubits.
- Figure 19. SWOT analysis for silicon spin quantum computers.
- Figure 20. SWOT analysis for topological qubits
- Figure 21 . SWOT analysis for photonic quantum computers.
- Figure 22. Neutral atoms (green dots) arranged in various configurations
- Figure 23. SWOT analysis for neutral-atom quantum computers.
- Figure 24. NV center components.
- Figure 25. SWOT analysis for diamond-defect quantum computers.
- Figure 26. D-Wave quantum annealer.
- Figure 27. SWOT analysis for quantum annealers.
- Figure 28. Quantum software development platforms.
- Figure 29. SWOT analysis for quantum computing.
- Figure 30. Technology roadmap for quantum computing 2025-2046.
- Figure 31. SWOT analysis for quantum chemistry and AI.
- Figure 32. Technology roadmap for quantum chemistry and AI 2025-2046.
- Figure 33. IDQ quantum number generators.
- Figure 34. SWOT Analysis of Quantum Random Number Generator Technology.
- Figure 35. SWOT Analysis of Quantum Key Distribution Technology.
- Figure 36. SWOT Analysis: Post Quantum Cryptography (PQC).
- Figure 37. SWOT analysis for networks.
- Figure 38. Technology roadmap for quantum communications 2025-2046.
- Figure 39. Q.ANT quantum particle sensor.
- Figure 40. SWOT analysis for quantum sensors market.
- Figure 41. NIST's compact optical clock.
- Figure 42. SWOT analysis for atomic clocks.
- Figure 43.Principle of SQUID magnetometer.
- Figure 44. SWOT analysis for SQUIDS.
- Figure 45. SWOT analysis for OPMs
- Figure 46. Tunneling magnetoresistance mechanism and TMR ratio formats.
- Figure 47. SWOT analysis for TMR (Tunneling Magnetoresistance) sensors.
- Figure 48. SWOT analysis for N-V Center Magnetic Field Sensors.
- Figure 49. Quantum Gravimeter.
- Figure 50. SWOT analysis for Quantum Gravimeters.
- Figure 51. SWOT analysis for Quantum Gyroscopes.
- Figure 52. SWOT analysis for Quantum image sensing.
- Figure 53. Principle of quantum radar.
- Figure 54. Illustration of a quantum radar prototype.
- Figure 55. Quantum RF Sensors Market Roadmap (2023-2046).
- Figure 56. Technology roadmap for quantum sensors 2025-2046.
- Figure 57. Schematic of the flow of energy (blue) from a source to a battery made up of multiple cells. (left)
- Figure 58. SWOT analysis for quantum batteries.
- Figure 59. Technology roadmap for quantum batteries 2025-2046.
- Figure 60. Market map for quantum technologies industry.
- Figure 61. Tech Giants quantum technologies activities.
- Figure 62. Archer-EPFL spin-resonance circuit.
- Figure 63. IBM Q System One quantum computer.
- Figure 64. ColdQuanta Quantum Core (left), Physics Station (middle) and the atoms control chip (right).
- Figure 65. Intel Tunnel Falls 12-qubit chip.
- Figure 66. IonQ's ion trap
- Figure 67. 20-qubit quantum computer.
- Figure 68. Maybell Big Fridge.
- Figure 69. PsiQuantum's modularized quantum computing system networks.
- Figure 70. Quantum Brilliance device
- Figure 71. The Ez-Q Engine 2.0 superconducting quantum measurement and control system.
- Figure 72. Conceptual illustration (left) and physical mockup (right, at OIST) of Qubitcore's distributed ion-trap quantum computer, visualizing quantum entanglement via optical fiber links between traps.
- Figure 73. Quobly's processor.
- Figure 74. SemiQ first chip prototype.
- Figure 75. SpinMagIC quantum sensor.
- Figure 76. Toshiba QKD Development Timeline.
- Figure 77. Toshiba Quantum Key Distribution technology.
