Chemistry, materials, large-scale optimization, cryptography: the hardest computational problems are running into the limits of classical hardware. Quantum computers can attack a growing class of them, once their errors are low enough for useful algorithms to run.
Why Quantum, Why Now
Across finance, logistics, energy, and the life sciences, the same pattern repeats: optimization and simulation problems whose classical cost grows faster than any reasonable budget. Cryptography sits on a different axis: today’s public-key systems will not survive a useful quantum computer, and the migration is already underway.
Portfolio construction, risk aggregation across correlated assets, and Monte Carlo pricing of derivatives scale poorly classically. Quantum methods offer quadratic to polynomial speed-ups for the underlying sampling and optimization.
Multi-depot vehicle routing, grid load balancing, and energy forecasting are large combinatorial optimization problems where classical solvers strain on real-world data. Quantum heuristics offer plausible routes to better solutions, faster.
Designing better catalysts, batteries, and pharmaceuticals depends on simulating quantum mechanics directly. For strongly correlated systems, classical methods scale exponentially; quantum computers are the natural tool.
Public-key cryptography (RSA, ECC) rests on problems quantum computers can break. NIST has already finalized post-quantum standards, and “harvest now, decrypt later” attacks make the migration urgent today.
The Engineering Challenge
A classical bit is a switch. A quantum bit is a single atom. A stray photon, a faint vibration, a breath of stray heat, and the information is gone.
A gap of six orders of magnitude. There are only two ways to close it.
Path 1 · Hardware
Better atoms, quieter lasers, smarter pulse shapes. Hardware vendors push to squeeze every last source of noise out of each physical qubit. A real and necessary effort, but physics imposes a hard ceiling on how clean any single qubit can ever be.
Path 2 · QPerfect
Spread one piece of quantum information across many noisy qubits. Detect and correct errors continuously, as they happen. The same trick classical engineers used to build reliable machines from unreliable parts, only much harder. This is where we focus.
Our Stack
A coherent vertical: a fast, hardware-agnostic emulator at the bottom; a hardware-faithful digital twin in the middle; a fault-tolerant execution layer on top. Each tier builds on the one below.
Tier 1 · In production
Quantum Circuit Emulator
Universal emulator. Statevector and MPS engines, up to thousands of qubits, hardware-accurate noise, mid-circuit measurement. Vendor-agnostic at the digital level. Cloud and on-prem.
Tier 2 · In deployment
Hardware-Aware Emulator & Compiler
Physics-informed model of one specific machine: native ISA, operational constraints (atom transport), live calibration. Acts as a virtual backend behind the same API as the QPU. First instance: aQCess. Architecture extendable to other neutral-atom platforms.
Tier 3 · In development
Quantum Logic Unit · FT execution
Fault-tolerant compiler, hardware-specific QEC, real-time syndrome decoder. Bridges quantum-advantage applications to early fault-tolerant neutral-atom QPUs.
MIMIQ™ powers the Digital Twin and the QLU™ compilation stack. One codebase, three products.
What You Get Today
A production-grade emulator your engineers can connect to today, in Python or Julia, running quantum algorithms with thousands of qubits and millions of gates.
Who MIMIQ™ Serves
Every organization trying to make quantum computing real faces the same problem: bridging algorithm and hardware.
Layer 1
Hardware builders need to benchmark their hardware, develop more efficient error correction codes, and give developers a way to write and test circuits before physical access is available.
Layer 2
Application builders need to develop and stress-test quantum algorithms at scale without depending on scarce, expensive, noisy physical hardware.
Layer 3
Cloud providers need a strong quantum simulation engine to power their QaaS offerings, giving enterprise clients quantum capabilities without owning hardware.
In Production
Real workloads in active use, not pilot projects.
BTQ Technologies (the company set to become QPerfect’s parent) develops quantum algorithms for digital signatures and secure communications. MIMIQ™ simulates complex circuits to verify their security guarantees ahead of physical deployment.
CRS4 uses MIMIQ to run hybrid quantum algorithms on Multi-Depot Vehicle Routing Problems with real traffic data, feeding results directly into a smart-city operational control platform.
Quobly’s QLEO emulator, powered by MIMIQ engines and integrated with NVIDIA CUDA-Q, is available on OVHcloud for debugging and optimizing complex logical circuits.
Collaboration with QuEra to simulate large-scale logical quantum algorithms such as magic state distillation, one of the building blocks of fault-tolerant operations.
Roadmap
A staged plan from validation to scaled fault tolerance, backed by European institutional grants and strategic investment.
Phase 1 · Now
End-to-end fault-tolerant compilation of cryptographically relevant applications.
Phase 2 · Near term
Deployment of QLU™ on neutral-atom quantum computers as hardware comes online.
Phase 3 · Horizon
Live cryptographic applications running in production at quantum-advantage scale.
Where to Start
A structured engagement spanning our full stack: MIMIQ™ for design, Digital Twin for hardware-aware validation, QLU™ for fault-tolerant compilation.
Step 01
Pick a real-world workload where classical compute is the binding constraint: routing, risk modeling, molecular simulation, cryptographic verification.
Step 02
Establish a classical baseline. Survey candidate quantum algorithms. Decide whether quantum is the right tool and which method fits.
Step 03
Design, simulate, and optimize the quantum algorithm on MIMIQ. Iterate against hardware-accurate noise. Reach the fidelity, runtime, and resource budgets your application needs.
Step 04
Run the algorithm on a hardware-faithful model of a specific neutral-atom processor. Confirm ISA compatibility, atom-transport feasibility, and noise resilience.
Step 05
Compile to fault-tolerant operations and estimate hardware resources. As neutral-atom quantum computers come online, QLU executes the workload directly.
MIMIQ™ lets you develop, test, and validate quantum algorithms today, at scale.