Company
Qubitor
QUBITOR is developing the technological infrastructure required to connect quantum computation and classical computational intelligence for solving hard or intractable problems.
One mathematical structure recurs across an enormous number of apparently unrelated problems. QUBITOR does not build a product for any single industry — it builds an engine for the structure underneath all of them.
QUBO and Ising-mapped problems are, in general, classically NP-hard combinatorial optimisation problems — a different classification from BQP, which describes decision problems efficiently solvable by a gate-model quantum computer. QUBITOR's annealing approach targets the former directly: finding low-energy ground states of a physical system, rather than executing a quantum circuit.
That single capability is then embedded into every domain below
QUBITOR is not building another generic optimisation library. The mandate is a mathematical niche where the algorithm-hardware pairing produces an order-of-magnitude advantage — not a broader one, a sharper one.
Digital/analog CMOS circuits emulating Ising dynamics — today's deployable substrate.
Optical parametric oscillator networks exploiting phase coherence to search the energy landscape.
Alternative physical substrates — memristive, spintronic, and analog systems — mapped onto the same Hamiltonian.
Genuine quantum tunnelling through the energy landscape, on integrated photonic hardware.
Classical computers collapse under exponential complexity. AI/ML struggles with NP-hard optimisation, quantum simulation, and chaotic systems. QUBITOR applies annealing architectures precisely where conventional approaches face increasing complexity.
Problems such as SAT, TSP, or protein folding scale exponentially with system size.
Classical digital logic explores solution spaces sequentially, making global search intractable.
AI models excel at pattern recognition but fail on combinatorial optimisation without huge compute budgets.
Simulating even modest quantum systems classically requires memory and operations that grow exponentially.
A factory floor, a satellite constellation, a semiconductor chip, a financial portfolio, a cancer drug candidate, and a telecommunications network can look like they have nothing to do with one another. Computationally, they often share the same underlying structure: a large number of discrete decisions whose interactions must be optimised simultaneously.
QUBITOR converts these problems into mathematical optimisation models — principally QUBO and Ising formulations — and develops specialised hardware and algorithms to solve them. Mathematics → Optimisation → Hardware → Applications. Quantum is the future computational layer beneath that stack, not the company's only identity.
We're looking to collaborate with domain experts in each of these fields to build out every vertical properly — the mathematics generalises, but the modelling detail in any one domain benefits from people who live in it.
| Real-World Application | Problem | What the Annealer Optimises |
|---|
We don't replace existing classical solvers. Rather, we add a layer on top of them — or step in when classical solvers can't keep up.
Classical methods to benchmark against, and QUBITOR's expected performance.
| Problem Family | Classical Methods to Benchmark Against | QUBITOR |
|---|---|---|
| Max-Cut | MILP, branch-and-bound, local search, simulated annealing | High |
| TSP / routing | Branch-and-cut, LKH, MILP, local search | Medium–High |
| Job scheduling | CP-SAT, MILP, constraint programming | High |
| Graph coloring | CP-SAT, MILP, branch-and-bound | High |
| Satellite task assignment | MILP, CP-SAT, metaheuristics | Very High |
| Constellation optimisation | MILP, metaheuristics, custom heuristics | Very High |
| Drone routing / fleet optimisation | MILP, CP-SAT, metaheuristics | Very High |
| Robot task allocation | MILP, CP-SAT, local search | Very High |
| Robot configuration | Nonlinear optimisation, numerical methods | Selective |
Classical exact/heuristic methods can't meet the application's time or energy budget, while the annealer still produces a sufficiently good solution.
| Problem Size / Variables | Classical Solvers | Qubitor |
|---|---|---|
| 50 | 1 ms | 2ms |
| 100 | 5 ms | 2 ms |
| 200 | 100 ms | 3 ms |
| 500 | 30 s | 5 ms |
| 1,000 | 20 min | 10 ms |
| 2,000 | >1 hr | 20 ms |
In above example, the interesting point isn't simply "2,000 variables". It's the crossover region where N ≈ 500–1000, for that particular problem family and hardware. That's where Qubitor starts becoming compelling.
We work with you to validate, deploy, and scale QUBITOR's optimisation engine for your most complex challenges. The project duration is just an indicative ones and might vary depending on the nature/complexity of the project.
A no-commitment session to understand your challenges. We present QUBITOR's technologies, showcase relevant use cases, and discuss potential applicability. It is Free of charge.
A focused engagement to model your problem and run it through our optimisation engines. We benchmark against your current workflows to demonstrate tangible performance improvements. This is a project-based engagement.
We build a production-ready, containerised optimisation pipeline for your specific problem, integrating it with your existing infrastructure and scaling it for real-world data volumes.
A comprehensive program for complex, enterprise-wide challenges. This involves deep integration, hybrid quantum-classical workflow orchestration, and long-term support for your existing computational infrastructure.
QUBITOR develops technologies at the intersection of electronics and photonics — validating each independently before advancing them, together, toward quantum computing systems.
From CMOS annealers toward quantum annealers, QUBITOR builds computational hardware for solving the most complex discrete optimisation problems.
Photons transfer information across distance with minimal loss. QUBITOR develops photonic technologies for high-speed interconnection between computational resources, on the path to scalable quantum networks.
QUBITOR is developing IP portfolios covering technologies at the intersection of quantum computing, photonics, and computational hardware.
Filed internationally in 2006. Part of the engineering foundation — precision positioning and micro/nanotechnology — from which QUBITOR's current technology development has evolved.