Workloads
In progress
Running Quantum Workloads from Kubernetes
What changes when quantum execution becomes part of a cloud-native workload — without making Kubernetes Mathnetica's identity.
Read moreAmsterdam · Netherlands
QuantumInfrastructureEngineering
Build and operate hybrid quantum-classical systems.
Mathnetica explores the infrastructure layer connecting classical compute, GPU and HPC systems, quantum simulators and QPUs.
The thesis
Quantum doesn't run alone.
Quantum workloads are inherently hybrid. Data preparation, simulation, optimization and post-processing happen on classical infrastructure, while selected parts of a workload may execute on quantum processors.
Mathnetica focuses on the infrastructure layer connecting these worlds — not quantum algorithms, and not quantum hardware.
CPU · GPU · HPC
↓
Hybrid workload
↓
Simulator · QPUWhat we are building
Infrastructure for hybrid quantum-classical systems.
Quantum remains central. Useful quantum workloads still require classical compute, GPUs, HPC and simulators. Mathnetica researches and builds the control layer connecting them.
01
Hybrid workflows
We are exploring controlled infrastructure workflows that span CPU, GPU, HPC, simulators and QPUs — including policy checks and human approval for high-risk steps — without treating quantum execution as an isolated experiment.
02
Workload placement
We are investigating how infrastructure can reason about where each stage should run — based on performance, availability, cost, hardware requirements and policy — including when a simulator is the better target than a QPU.
03
Operations & constraints
We are researching observability, cost awareness, infrastructure lifecycle and sovereignty constraints across the quantum–classical boundary — including European data residency and trusted-provider requirements where organizations need them. Platform capabilities, not a separate product.
The platform
A control layer above existing infrastructure.
Mathnetica is building a quantum-aware control layer for modern computing infrastructure. We are exploring hybrid workflow orchestration, workload placement, infrastructure automation, policy and sovereignty, observability and cost awareness — extending proven cloud-native and HPC technologies where they already exist. Status: Experimental.
MATHNETICA
Quantum Control Plane
│
┌─────────────┼─────────────┐
│ │ │
QPU Resources Workloads Operations
│ │ │
Discovery Routing Telemetry
Allocation Lifecycle Provenance
│ │ │
└─────────────┼─────────────┘
│
───── Existing Infrastructure ─────
Kubernetes / Argo / Kueue / HPC
│
CPU / GPU / HPC / Simulator / QPUResearch directions
Hybrid workflow orchestration
Controlled workflows across classical and quantum stages — with policy and approval where required.
Workload placement
Choosing CPU, GPU, HPC, simulator or QPU for each stage.
Infrastructure automation
Provisioning and releasing resources as part of the workload lifecycle — when needed.
Policy and sovereignty
Respecting region, data location, approved providers, budget and organizational policy — including European data residency and cloud sovereignty constraints where they apply.
Observability
Workflow-first visibility, cost signals and execution provenance across classical and quantum stages.
Cost awareness
Estimating and comparing cost and turnaround as part of placement — not a separate FinOps product.
Existing stack is the foundation. Our code is the layer that makes infrastructure understand hybrid quantum-classical workloads.
Who it's for
Teams that need quantum compute inside real infrastructure.
Quantum computing providers
Integrate QPUs with modern cloud and HPC infrastructure.
HPC & supercomputing centres
Operate CPU, GPU and QPU resources as part of hybrid workloads.
Research institutions
Run reproducible hybrid quantum–classical experiments.
Platform engineering teams
Integrate quantum resources without creating a separate infrastructure stack.
Open source
Mathnetica Platform
Infrastructure and control software for hybrid quantum-classical computing. Status: Experimental.
Capabilities described on this site are research and early engineering directions. Do not assume providers, schedulers or automation are production-ready unless listed as implemented.
QBridge — QBridge explores a portable infrastructure layer for connecting classical workloads with quantum simulators and QPU backends. It is an open-source adapter direction within the Mathnetica Platform — not a finished enterprise product.
Research → open source → real-world engineering → reusable technology → Mathnetica Platform.
Research
Engineering the missing pieces.
Mathnetica Research documents the engineering problems we encounter while building infrastructure for hybrid quantum-classical computing — including placement, automation, sovereignty and observability. Research feeds directly into the platform.
Resources
Planned
Designing a QPU Resource Model
CPU and GPU abstractions do not map directly to quantum processors. What information should infrastructure understand about a QPU?
Research topicScheduling
Planned
Scheduling Across Heterogeneous QPUs
How should infrastructure place and schedule stages when backends differ in availability, topology, queue time, fidelity, cost and policy?
Research topicWork with us
Architecture Review today. Infrastructure workflows next.
Mathnetica is a commercial engineering company under Quantum Infrastructure Engineering. We design controlled infrastructure workflows — policy, approval, placement, provisioning, execution and audit — across CPU, GPU, HPC, simulators and QPUs. Specialized engagements fund and inform the Mathnetica Platform.
Mathnetica builds controlled infrastructure workflows for hybrid quantum-classical computing — connecting policy, human approval, provisioning and execution across CPU, GPU, HPC and QPU environments.
Architecture Review
Entry point
The easiest starting point — a focused senior review of your quantum, hybrid or classical infrastructure plans and constraints.
Controlled infrastructure workflows for hybrid quantum-classical computing — connecting policy, human approval, provisioning and execution across CPU, GPU, HPC, simulators and QPUs.
Target architecture for operating quantum workloads alongside classical systems — control plane, providers, operations.
Engineering work to connect quantum backends with existing HPC, cloud or Kubernetes environments.
Assess readiness of workloads and infrastructure for hybrid quantum-classical experimentation.
Work with Mathnetica.
Start with an Architecture Review, or engage us to design controlled hybrid quantum infrastructure workflows. Open-source and research feed the Mathnetica Platform — they are not the whole company.