Quantum computing · AI · Finance · Cybersecurity
Quantum computing and AI harnessing the synergy in finance and cybersecurity.
QuantMagic assists financial institutions and cybersecurity teams to realize real advantage and mitigate operational risks.
01 Why magic
Magic is what makes a quantum computer quantum
Our name isn’t a metaphor. In quantum computing, magic is a measurable property. It marks the line between what a quantum computer can do and what a classical one can copy.
Without magic, it’s classical
A large family of quantum circuits, the ones built only from Clifford gates, can be simulated efficiently on an ordinary computer. That holds no matter how much superposition or entanglement they contain. This is the Gottesman–Knill theorem.
Clifford only → a laptop can do it
Magic is the missing ingredient
Add one more kind of operation, the T gate, or a supply of special “magic states,” and the same circuits can compute anything a quantum computer can. Physicists call this property non-stabilizerness. It is the resource a quantum computer needs to get beyond classical reach.
Clifford + T = universal
Magic is also the bottleneck
On error-corrected machines, magic states are the expensive part. They are prepared and purified (“distilled”) in dedicated areas of the chip. How much magic an algorithm needs is a major driver of how big, slow and costly it is to run.
T-count drives much of the cost
Why it matters to you
Magic is a useful first test for any quantum claim. If a proposed use needs little of it, a classical computer can probably match it. Needing a lot is necessary for an advantage, but not enough on its own. We use that lens to separate what is real from what is hype.
where the advantage actually lives
02 Quantum and AI
Each makes the other stronger
Quantum computing and AI are converging in both directions. The near-term wins run from AI to quantum. The bigger, longer-term prize runs the other way.
Now
AI for quantum
Google DeepMind’s AlphaQubit, a neural-network decoder, beat leading conventional decoders on error data from Google’s Sycamore processor (Nature, 2024), though it is not yet fast enough for real-time use. Machine learning also helps find better circuits, calibrations and gate sequences.
Next
Quantum for AI
Quantum algorithms for sampling, optimization and linear algebra could speed up parts of machine learning. The strongest proposals need error-corrected machines, and many early claims were later matched by better classical methods. We track which results hold up.
In practice
Hybrid systems
Real workflows pair GPUs and classical supercomputers with quantum processors, each doing the part it does best. That is where finance and security teams will meet quantum computing first.
03 Focus
Where we focus
Two industries where quantum computing and AI matter soonest, one for the opportunity and one for the threat.
Finance
Quantum computing in financial markets
Pricing, risk, portfolio optimization and fraud: what quantum and AI could change, on what timeline, and how to prepare without over-investing.
Read more →Cybersecurity
Quantum-safe security
A large enough quantum computer would break the public-key cryptography that protects payments, identities and data today. Migrating takes years, and data stolen now can be decrypted later.
Read more →04 How we help
From briefing to roadmap
We shape strategy, so you can act on quantum computing and AI with confidence and stay ahead of both the opportunity and the risk.
Briefings
For leaders and boards
A plain-language picture of quantum computing and AI for your sector: what is real, what is hype, and what your peers are doing.
Assessments
Quantum readiness
Where you are exposed to quantum risk and where you could gain, starting with an inventory of the cryptography your business depends on.
Roadmaps
Strategy you can execute
A staged plan covering quantum-safe migration, pilots worth running, partners worth talking to, and the skills to build in-house.
Contact
Start with a conversation
Tell us what you are working on, or ask to join our briefings and events.