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Copyright © 2025 IonQ, Inc. All Rights Reserved. 1 IonQ’s Path to Large-Scale, Fault-Tolerant Quantum Computing Technology Roadmap Webinar
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This presentation contains statements that constitute forward-looking statements within the meaning of the Private Securities Litigation Reform Act of 1995 and other securities laws. Whenever we use words such as "believe," "expect," “enable,” “accelerate,” "anticipate," "intend," "plan," “evolve,” "estimate," “can,” "will," "may," “has the potential to” and negatives and derivatives of these or similar expressions, we are making forward-looking statements. Forward-looking statements in this presentation relate to various aspects of our business, including statements about lonQ, Inc. ("IonQ," "our" or "we") and our technology roadmap; our anticipated timing and ability to achieve higher algorithmic qubits, faster gates speed, higher fidelity, better error correction and sustained growth in system usage; the potential benefits of our partnership with Quantum Basel, DESY, NRL, and other partners and customers; the sufficiency of our cash reserves; the growth, retention and capabilities of our team; the scale and projected growth of quantum computing’s total addressable market; the possible applications of quantum computing; the commercial value for our system and for potential applications; the advantages of IonQ's architecture in higher performance, scalability and attainment of commercial value; IonQ's ability to achieve higher performance and scalability; the advantages of IonQ's approach to manufacturing and deployment of our systems; and the timing and value impact of maturity growth in quantum computing. These forward-looking statements are based upon our present intent, beliefs or expectations, but forward-looking statements are not guaranteed or may not occur. The achievement of any or all of these forward-looking statements is subject to various and myriad risks and uncertainties, which you can learn more about in IonQ’s Annual Report on 10-K and its Quarterly Reports on 10-Q filed with the Securities and Exchange Commission, at www.sec.gov. Forward Looking Statements Copyright © 2024 IonQ, Inc. All Rights Reserved.
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Copyright © 2025 IonQ, Inc. All Rights Reserved. 3 IonQ’s Path to Large-Scale, Fault-Tolerant Quantum Computing Technology Roadmap Webinar Niccolo de Masi CEO
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Copyright © 2025 IonQ, Inc. All Rights Reserved. 4 Copyright © 2025 IonQ, Inc. All Rights Reserved. Leadership From Near Term to Fault Tolerance Accelerating Value: Expanding the Quantum Application Opportunity Commercial Value
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Copyright © 2025 IonQ, Inc. All Rights Reserved. Copyright © 2025 IonQ, Inc. All Rights Reserved. Positioned to Succeed In the Quantum Computing Race 5 Leadership Across Multiple Fronts Financials First pure-play quantum company to go public $96M in bookings in 2024 2 year CAGR of ~100% $1B in funding since inception ~$700M in cash Technology 30+ years of groundbreaking trapped ion research The only modular, scalable, high performance trapped ion platform ~1,000 owned and controlled quantum patents and applications Commercialization 4th generation commercial quantum computers Only QPUs on all 3 major public clouds First dedicated quantum computing factory in US Expanding global presence
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Copyright © 2025 IonQ, Inc. All Rights Reserved. 6 Leveraging Strong Position to Accelerate Technology Roadmap Positioned to Succeed In the Quantum Computing Race Networking Acquisitions Computing Acquisitions Entangled Networks *Planned
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Copyright © 2025 IonQ, Inc. All Rights Reserved. Technology Strategy and Roadmap 7 01 Dr. Dean Kassmann SVP , Engineering & Technology
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Copyright © 2025 IonQ, Inc. All Rights Reserved. Copyright © 2025 IonQ, Inc. All Rights Reserved. Ion Qubits Naturally Identical High Performance Long Coherence Universal Gates Highly Scalable 8 Photonically Interconnected Qubit Parcels Photon-Ion Entanglement Well Demonstrated Distributed Computing Scale High Connectivity + Parallelization Efficient Time-to-solution Algorithmic Flexibility Fault Tolerance Low Overhead QEC Flexibility to Implement Various Codes Efficient Logical Qubit Scaling Technology Strategy IonQ’s Winning Architecture Full Stack Product Development HW/SW Co-development Customer application- focused
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Copyright © 2025 IonQ, Inc. All Rights Reserved. 9 Deepening IonQ’s Scientific Bench Positioned to Succeed in the Quantum Computing Race Dr. Chris Ballance Dr. Mihir Bhaskar CEO, Lightsynq Technologies Acquired by IonQ (2024 - 2025) Research Lead, AWS Center for Quantum Networking (2021 - 2024) PhD, Harvard University (2015 - 2021) Citations: 5085 h-index: 21 CEO, Oxford Ionics Intention to be acquired by IonQ June 2025 (2019 - 2025) Fellow, University of Oxford (2019 - 2025) PhD, University of Oxford (2010 - 2014) Citations: 4475 h-index: 25
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Copyright © 2025 IonQ, Inc. All Rights Reserved. Accelerating Development Areas 10 Unlocking Scale Through Larger Parcel Size The integration of Oxford Ionics’ trap-on- a-chip into IonQ’s architecture will enable the qubit count within a single trap to increase thanks to a significantly more dense qubit placement. 10 up to 50X 50X more qubits in a single trap compared to 1D linear approach up to From 1D Linear Trap To Dense 2D Qubit Fabric
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Copyright © 2025 IonQ, Inc. All Rights Reserved. Accelerating Development Areas 11 Unlocking Scale by Improving Remote Entanglement The integration of Lightsynq quantum memory technology into existing photonic interconnect systems will improve entanglement rates by removing existing bottlenecks that limit the speed at which remote traps can be connected 11 up to 50X 50X remote entanglement efficacy compared to non-memory approach up to From No Memory Solution To Memory Enabled
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Copyright © 2025 IonQ, Inc. All Rights Reserved. 12 Current Technology Roadmap 12 2025 2026 2027 2028 #AQ 64 256 384 1,024
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Copyright © 2025 IonQ, Inc. All Rights Reserved. 13 Updated Technology Roadmap 13 2025 2026 2027 2028 #AQ 64 256 384 1,024 Qubits 64 256 10,000 20,000 +20X +19.5X
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Copyright © 2025 IonQ, Inc. All Rights Reserved. 14 Updated Technology Roadmap 14 2025 2026 2027 2028 2029 2030 #AQ 64 256 384 1,024 Qubits 64 256 10,000 20,000 200,000 2,000,000
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Copyright © 2025 IonQ, Inc. All Rights Reserved. 15 Updated Technology Roadmap 15 2025 2026 2027 2028 2029 2030 #AQ 64 256 384 1,024 Qubits 64 256 10,000 20,000 200,000 2,000,000 Logical Qubits 12 800 1,600 8,000 80,000 Logical Error Rate <1.00E-7 <1.00E-12
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Copyright © 2025 IonQ, Inc. All Rights Reserved. 16
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Copyright © 2025 IonQ, Inc. All Rights Reserved. Accelerating ScaleOxford Ionics Technology 17 02 Dr. Chris Ballance CEO, Oxford Ionics
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Copyright © 2025 IonQ, Inc. All Rights Reserved. 18 Architecture based on building larger quantum computers by replicating discrete unit cells, without reengineering the fundamentals or compromising world-record qubit performance. Utilize unique Electronic Qubit Control The only technology that can trap and control qubits on the chip Use unique WISE architecture They can be connected without an explosion of wiring or complexity Use only well-established technologies High yield Low variability Quick turnaround times A Repeatable Cell Unit Oxford Ionics Technology
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Copyright © 2025 IonQ, Inc. All Rights Reserved. Performance without limits EQC does not have intrinsic performance limitations that lasers can cause with photon scattering Electronics works! EQC takes advantage of the mature electronics industry and the naturally low noise of electronics compared to lasers Performance at scale EQC is scale-invariant, enabling parallel operation of multiple ions without cross-talk 1. Magnetic field 2. Trapped ion qubits 3. Integrated antenna 1 3 19 Oxford Ionics Technology Electronic Qubit Control (EQC) 2 3 3
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Copyright © 2025 IonQ, Inc. All Rights Reserved. 10,000-qubit quantum computer 8-qubit unit cell 256-qubit quantum computer A quantum computer is highly scalable when larger devices can be built by copy-pasting existing unit cells, without compromising performance Higher Qubit Counts by Replicating, not Reinventing 20 Oxford Ionics Technology 20
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Copyright © 2025 IonQ, Inc. All Rights Reserved. Accelerating ScaleLightsynq Technology 21 03 Dr. Mihir Bhaskar Sr. Director, Quantum Interconnects
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Copyright © 2025 IonQ, Inc. All Rights Reserved. 22 Lightsynq Technology Quantum Memory Enhanced Photonic Interconnects 1 2 Leading quantum memory Proven to enhance networking rates over quantum channels Integrated photonics approach Foundry-compatible nanofabrication for performance at scale Proprietary fiber-to-chip coupling Insertion loss 10x+ better than industry standard techniques 3
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Copyright © 2025 IonQ, Inc. All Rights Reserved. Improving Remote Entanglement Rates Lightsynq Technology 23 Previous best-in-class: No quantum memory QPU A QPU B Detection Hub✔ Successful connection requires simultaneous photon arrival at detector If photon is lost, connection fails and network must re-attempt link, decreasing rates
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Copyright © 2025 IonQ, Inc. All Rights Reserved. Improving Remote Entanglement Rates Lightsynq Technology 24 Previous best-in-class: No quantum memory QPU A QPU B Detection Hub✔ Successful connection requires simultaneous photon arrival at detector If photon is lost, connection fails and network must re-attempt link, decreasing rates Lightsynq’s approach: Memory-enhanced interconnects QPU A QPU B ✔ No requirement for simultaneous arrival Quantum memory mitigates loss, increasing network speed by up to 50x ✔ Buffer Combine with buffer
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Copyright © 2025 IonQ, Inc. All Rights Reserved. Demonstrated Performance in Real-World Conditions 25 Lightsynq Technology Showed >50x speedup in a quantum network using Lightsynq’s technology Proven performance using real-world telecommunications fiber outside the lab Force-multiplier for connecting high-performance ion trap compute nodes 25
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Copyright © 2025 IonQ, Inc. All Rights Reserved. Applying ScaleCommercial Applications 26 04 Ariel Braunstein SVP , Product and Quantum Applications
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Copyright © 2025 IonQ, Inc. All Rights Reserved. 27 Quantum Optimization Case Study (NISQ) Accelerating Finite Element Simulation with Quantum-Enhanced Graph Partitioning Business and Technical Challenges: LS-DYNA crash simulations are slowed by costly graph partitioning on massive FEM meshes IonQ’s Quantum Solution: QITE approach breaks down large meshes into smaller subgraphs for quantum processing Business Impact: Up to 12% faster simulation times, with strong potential for continued quantum-driven acceleration arXiv:2503.13128 Up to 12% Improvement over classical heuristics | 2.6M vertices & 40M edges
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Copyright © 2025 IonQ, Inc. All Rights Reserved. 28 Quantum Simulation Case Study (NISQ) Accelerating Drug Development and Synthesis with Enhanced Simulations Business and Technical Challenges: Traditional computational methods struggle to efficiently and accurately simulate complex transition metal catalysis IonQ’s Quantum Solution: QC-AFQMC approach can efficiently model reaction energetics at scale with high accuracy Business Impact: Enables faster, more cost-effective drug development and material design by reducing compute time and resources 20X Faster time-to-solution than best previously published implementation by AWS Read the Blog Post CPU QPU GPU <1 hr Laptop 32 hrs Forte 45 hrs 320x H200
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Copyright © 2025 IonQ, Inc. All Rights Reserved. 29 Quantum AI Case Study (NISQ) Quantum Hybrid LLM Fine-Tuning Boosts Accuracy and Efficiency Business and Technical Challenges: Classical Large Language Models (LLMs) struggle with sparse, complex, or proprietary data IonQ’s Quantum Solution: Hybrid fine-tuning adds quantum layers to pre-trained LLMs, improving small dataset learning and outperforming classical Machine Learning models Business Impact: Improves accuracy by 3.14% and reduces energy use at scale, delivering practical quantum benefits from 46 qubits arXiv:2504.08732 Scaling Efficiently Beyond Classical Energy (kJ) Number of qubits
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Copyright © 2025 IonQ, Inc. All Rights Reserved. Higher Accuracy More Variables Larger Peptides Higher Accuracy More Variables More Complex Models More Agents More Dimensions Modeled Larger Molecules Higher Resolution More Complex Models More Orbitals More Assets AI/ML LLM Fine-Tuning Optimization Unit Commitment in Electric Grids Simulation Protein Folding for Drug Discovery Copyright© 2025 IonQ, Inc. All Rights Reserved. AI/ML Image Change Detection Optimization Vehicle Routing Simulation Laminar Fluid Dynamics AI/ML AI Agent Assignment Optimization Fantasy Sports Team Picking Simulation Drug-target Affinity Prediction With Solvent Model AI/ML Medical Imaging Analysis Optimization Battery Materials Discovery Optimization Pharma Catalysts Redesign Simulation Institutional Portfolio Rebalancing Updated Technology Roadmap 2025 Quantum Computing Hardware 64 Physical Qubits 1 Select Commercial Applications 2026 Quantum Computing Hardware 256 Physical Qubits 12 Logical Qubits <1.00E-7 Logical Error Rate 2027 Quantum Computing Hardware 10,000 Physical Qubits 800 Logical Qubits <1.00E-7 Logical Error Rate 2028 Quantum Computing Hardware 20,000 Physical Qubits 1600 Logical Qubits <1.00E-7 Logical Error Rate Enabling New Classes of Applications
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Copyright © 2025 IonQ, Inc. All Rights Reserved. Higher Resolution More Complex Models More Orbitals More Assets More Parameters More Parameters More Actions More Complex Models Larger Molecules Larger Molecules Broad Quantum Advantage applications from previous years are still applicable Copyright© 2025 IonQ, Inc. All Rights Reserved. Updated Technology Roadmap 2028 Quantum Computing Hardware 20,000 Physical Qubits 1600 Logical Qubits <1.00E-7 Logical Error Rate Select Commercial Applications 2029 Quantum Computing Hardware 200,000 Physical Qubits 8000 Logical Qubits <1.00E-12 Logical Error Rate 2030 Quantum Computing Hardware 2,000,000 Physical Qubits 80,000 Logical Qubits <1.00E-12 Logical Error Rate AI/ML Medical Imaging Analysis Optimization Battery Materials Discovery Optimization Pharma Catalysts Redesign Simulation Institutional Portfolio Rebalancing AI/ML Training Robotic AI Models AI/ML Quantum Federated Learning Optimization Optimization of Ai Agent Action Planning Simulation Materials Discovery for Advanced Medical equipment Simulation Carbon Capture Catalyst Design Simulation Polymorph Screening for Drug Discovery Enabling New Classes of Applications
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Copyright © 2025 IonQ, Inc. All Rights Reserved. 32 Fault-tolerant App Deep Dive Catalyst Redesign at Scale: Faster, Cheaper, Greener Algorithms Used: Spectral amplification, Quantum phase estimation, Qubitization Industries/Customers: Chemicals, Specialty Chemicals, Materials Science, Industrial Solutions, Sustainable Technologies Time-to-Solution (TTS): Reduced from weeks/months to days or hours by ~2030 SAM: ~$100M in early-stage addressable market Level 1 2028-2029 Develop Mo-based catalysts for more efficient fertilizer production ~2,000 Logical Qubits Level 2 2028-2029 Redesign catalysts using cheaper alternatives to precious metals ~3,000 Logical Qubits Level 3 2029 Optimize catalytic cycles for carbon capture and utilization ~4,000 Logical Qubits
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Copyright © 2025 IonQ, Inc. All Rights Reserved. 33 IonQ’s Path to Large-Scale, Fault-Tolerant Quantum Computing Technology Roadmap Webinar Niccolo de Masi CEO
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Copyright © 2025 IonQ, Inc. All Rights Reserved. 34 Copyright © 2025 IonQ, Inc. All Rights Reserved. Accelerating Value: Expanding the Quantum Application Opportunity Leadership From Near Term to Fault Tolerance