Enterprises

Develop the capability
to evaluate quantum computing

Build technical understanding before choosing a quantum project. QuantumClass supports learning and problem formulation, while Spinorio Lab provides a workspace for practical investigation and comparison.

The challenge

Turn interest into a well-defined evaluation

A useful quantum initiative starts with a specific computational problem. Teams need to understand how it can be represented, what classical methods already achieve and which hardware and resource constraints matter. A demonstration becomes informative when its evaluation criteria are explicit.

Training and experimentation need to connect. Shared mathematical foundations help a team examine technical claims, while a common development environment supports the practical work of implementing a candidate method and reviewing its evidence.

Learning and experimentation

Develop a sound understanding of quantum computation, then put it to work in a practical research environment.

QuantumClass

Build technical understanding with QuantumClass

Structured courses and research preparation help practitioners connect quantum concepts with implementation. Assignments and instructor feedback support careful reasoning about what a method can demonstrate.

  • Develop foundations in quantum mathematics, circuits and algorithms.
  • Practice implementation through Python and Qiskit coding assignments.
  • Use the research programme to examine quantum fit, formulate a problem and design an evaluation.
Explore QuantumClass

Spinorio Lab

Investigate the workload in Spinorio Lab

Use a prepared JupyterLab environment to develop a proof of concept, begin with local simulation and inspect the resulting circuits and records.

  • Work with pre-installed quantum SDKs and scientific Python tools.
  • Prepare circuits for a selected target and compare compilation outputs with a standard baseline.
  • Inspect captured circuit states, processing runs and available execution evidence.
  • Organise selected records and source snapshots in projects with controlled access.

Automatic capture covers supported Qiskit-family activity. Hardware execution depends on provider access and notebook authentication; compilation metrics alone do not establish execution performance.

Explore Spinorio Lab

In practice

A practical route to an informed decision

Combine learning with a bounded technical investigation, using criteria that make the findings useful to the team.

  1. Build shared foundations

    Develop the knowledge needed to discuss states, circuits, measurement and algorithmic assumptions. Connect the training to a problem your team understands.

  2. Evaluate a specific workload

    Define inputs, a baseline and an objective. Implement a candidate workflow, inspect its resource requirements and choose appropriate simulation or hardware experiments.

  3. Review the evidence

    Compare results under stated conditions and record the limits of the study. Use the findings to decide what further investigation would be justified.

A participant perspective

“In general, it’s not just about understanding quantum computing but, more importantly, understanding the fundamentals so I can then apply them to my role and think about how products and services might be developed in the future.”

Anthony Macey

Director at Barclays Ventures

QuantGates workshop at Barbican, London

Our learning community

Our industry community

Users and participants from these organisations are part of the QuantGates learning and research community.