AtomGPT.org Quantum Computation Explorer¶
A hosted, interactive version of these workflows runs at atomgpt.org/quantum. It lets you pick a material, choose a back end, and run VQE / ADAPT-VQE at a single \(k\)-point or compute a full VQD bandstructure — all from the browser, with live circuit diagrams, statevector / Bloch-sphere visualizations, and the Hamiltonian matrix shown alongside the results.
The web app is implemented in the AtomGPT / Open WebUI backend:
- Routes:
my-open-webui/backend/open_webui/custom_routes/quantum.py - UI:
my-open-webui/backend/open_webui/custom_templates/quantum.html
Endpoints exposed by the app:
| Method & path | Purpose |
|---|---|
GET /quantum |
Serves the interactive HTML page. |
POST /quantum/vqe |
Run Qiskit VQE at a single \(k\)-point. |
POST /quantum/adaptvqe |
Run Qiskit ADAPT-VQE at a single \(k\)-point. |
POST /quantum/bandstructure |
Full VQD bandstructure via get_bandstruct. |
GET /quantum/materials |
List the available demo WTBHs. |
GET /quantum/backends |
List available simulator/hardware back ends. |
Demo materials include FCC Al, diamond Si, hexagonal PbS, and FCC Cu (electron
Hamiltonians) plus Al and Si phonon Hamiltonians. The same JARVIS-DFT + HermitianSolver
machinery used in the package powers the app; it adds modern qiskit>=2.0 primitives,
optional IBM Quantum hardware execution, and per-qubit Bloch-vector / statevector
extraction for visualization.
Related ecosystem¶
- AtomGPT.org (atomgpt.org) — foundation models + 50+ domain apps (atomgpt.org/apps).
- SlaKoNet (atomgpt.org/slakonet) — a learned tight-binding \(H(k)\) that can feed the same VQE / VQD pipeline for materials with no pre-computed Wannier data.
- ALIGNN / ALIGNN-FF — graph-network property prediction & force fields.