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@QMeshPy

QMeshPy

QMeshPy

QMeshPy

Building a distributed internet for quantum computation.

We are exploring how quantum operations can become discoverable peer-to-peer services—routed across a global compute mesh, executed by specialized nodes, and assembled into complete scientific results.

PythonQiskitlibp2p

The distributed quantum internet

Quantum program
↓
Split into executable circuit fragments
↓
Discover compatible peers through libp2p
↓
Route fragments to distributed quantum services
↓
Execute on simulators today—and quantum processors tomorrow
↓
Reassemble, verify, analyze, and share results through IPFS

Nodes advertise capabilities through GossipSub, receive circuit fragments over libp2p streams, and return partial quantum states to a coordinator. Qiskit currently provides execution and analysis while IPFS enables content-addressed sharing of circuits and research artifacts.

What we are working on

  • Financial modelling — QAOA portfolio optimization, option pricing, risk analysis, and quantum-versus-classical comparisons.
  • Drug discovery — molecular simulation, quantum chemistry workflows, candidate scoring, and distributed scientific search.
  • Scientific computing — reusable quantum operations exposed as network services for researchers and autonomous agents.
  • Open quantum infrastructure — peer discovery, execution planning, fault-aware routing, provenance, and independently operated compute nodes.

Benchmark snapshot

Current Qiskit statevector experiments compare QAOA portfolio optimization with Simulated Annealing:

Portfolio sizeClassical (SA)Quantum (QAOA)Result
10 assets20 ms1,500 msClassical 75× faster
20 assets600 ms1,700 msClassical 2.8× faster
40 assets6,000 ms1,900 msQuantum 3.2× faster
60 assets20,000 ms2,100 msQuantum 9.5× faster

One important finding: roughly 97% of current QAOA runtime is classical parameter search, not circuit execution. That means distributed nodes alone do not create quantum advantage—the opportunity comes from better optimization methods and more favorable scaling as problems grow.

These are simulator-based research benchmarks, not claims of production quantum-hardware advantage. Results depend on the workload, solver, configuration, and machine.

Build the mesh. Route the circuit. Discover what scales.

Explore our research · View the organization

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