What if a blockchain network could run on quantum computers—and use a fraction of the energy?

On this episode of Quantum Matters, Postquant Labs co-founders Colton Dillion and Rick Karbach share how D-Wave's annealing quantum technology is integrated into the Quip Network, a quantum-classical blockchain network. They explain their “proof of useful work” model, where quantum and classical computers compete side by side to solve optimization problems as a way to validate transactions more efficiently. Early testing with D-Wave’s quantum processing unit suggests it can produce higher-quality solutions faster and with significantly lower energy use than comparable GPU-based approaches, while the classical compute decentralizes the network until quantum computers become more numerous.

Listen in to hear how this hybrid approach works in practice and why energy efficiency is quickly becoming one of the most important challenges in the future of blockchain systems.

Learn More about D-Wave: https://www.dwavequantum.com/

D-Wave blockchain paper: https://www.dwavequantum.com/blockchain/

Quip Network: https://quip.network/

Postquant Labs: https://postquant.xyz/

Highlights:

09:32 – Building a Hybrid System Between Classical and Quantum

15:43 – Real-World Energy and Speed Tradeoffs

25:47 – The Vision: A Worldwide Quantum-Classical Computer

What does quantum advantage actually mean? How do you prove a quantum computer can outperform the world’s most powerful supercomputers? And why is its energy efficiency arriving at such an important time for the world?

In this episode of Quantum Matters, host Murray Thom sits down with Dr. Andrew King, Senior Distinguished Scientist at D-Wave, to discuss the company’s landmark peer-reviewed research demonstrating quantum computational advantage on a

problem relevant to materials discovery.

Together, they unpack the result behind the headlines, including a calculation completed in minutes on a quantum processor that could take classical supercomputers nearly a million years. They explore what it took to validate that claim, why energy efficiency is becoming a critical part of the quantum computing story, and how these advances could impact materials science, blockchain, and AI.

Join us for an inside look at one of the most significant milestones in quantum computing and what it could mean for the future of computation.

Learn more about the Beyond Classical research:

https://www.dwavequantum.com/beyond-classical/

Explore the Blockchain research: https://www.dwavequantum.com/blockchain/

Highlights:

03:41 — The Most Exciting Quantum Breakthrough in Years

11:49 — Why Quantum Computing Could Revolutionize Energy Efficiency

29:12 — What’s Next for Quantum Computing: New Controls and Capabilities

Show Glossary

• Quantum Phase Transition: A change in the state of a quantum system driven by quantum effects rather than changes in temperature.
• Programmable Quantum Magnet: A controllable quantum system designed to mimic the behavior of magnetic materials for experiments and simulations.
• Constraint Satisfaction Problem (CSP): A problem where a solution must satisfy a specified set of constraints or rules.
• Spin Glass: A disordered magnetic system with competing interactions that make finding its lowest-energy state difficult.
• Polynomial Speedup: An improvement where a quantum algorithm scales more favorably than a classical algorithm as problem size increases.
• Matrix Product State (MPS): A mathematical representation used to efficiently simulate certain quantum systems on classical computers.
• Projected Entangled Pair States (PEPS): An advanced tensor-network method used to model higher-dimensional quantum systems.
• Thermal Bath: The surrounding environment that exchanges heat with a physical system and can influence its behavior.
• Topological Phase Transition: A phase transition characterized by changes in a system’s global structure rather than conventional ordering.
• Order by Disorder: A phenomenon where fluctuations create an ordered state from a set of equally possible disordered configurations.
• Degenerate Ground States: Multiple lowest-energy states of a system that all have exactly the same energy.
• Hamiltonian: The mathematical description of the total energy and evolution of a physical system.
• Non-Ising Hamiltonian: A Hamiltonian that includes interactions beyond those found in the standard Ising model of magnetism.
• Multicolor Annealing: A quantum annealing technique that applies different control schedules to different groups of qubits.
• State Preparation: The process of initializing a quantum system into a desired starting state before computation or simulation.
• Doping Parameter: A variable describing how impurities are intentionally added to a material to alter its properties.
• Hopfield Network: A type of recurrent neural network that stores and retrieves patterns using an energy-based framework.
• Tensor Network: A mathematical framework used to represent and compute properties of complex quantum systems.

What role can quantum computing play in national defense? In this episode of Quantum Matters, host Murray Thom speaks with Dale Moore, president and CEO of Davidson

Technologies, about the effort to bring quantum computing into practical defense applications.

Dale details his team’s collaboration with D-Wave and Anduril applying quantum computing to

air and missile defense planning, and discusses the importance of housing a D-Wave

Advantage2 system at Davidson’s facilities in Huntsville, Alabama.

From advanced simulations to mission-critical decision-making, discover what quantum

computing can do when national security is on the line.

Learn More: https://www.dwavequantum.com/solutions-and-products/public-sector/

Highlights include:

08:24 - Quantum Breakthrough in Missile Defense (Anduril × D-Wave × Davidson)

12:25 - Why Missile Defense Is a Perfect Quantum Use Case

22:59 - Making Quantum Real in Defense (Huntsville Deployment & Access)