🚀 Skip the local bottleneck. Qoro is giving away $100 in free cloud compute credits. Get your API key at dash.qoroquantum.net to run these tutorials at scale.
Example programs demonstrating quantum algorithms with the Divi quantum programming framework — each structured as a two-phase tutorial showing the jump from local toy problems to cloud-scale execution on QoroService.
Running quantum simulations locally hits a wall fast. A 50-qubit statevector needs 8 PB of RAM. Even clever MPS simulators grind to a halt on high-entanglement circuits. Qoro's Divi + Maestro stack solves this with:
- ⚡ Parallelized circuit execution — Divi automatically partitions large problems and dispatches sub-circuits in parallel
- 🧠 Maestro MPS simulator — GPU-accelerated simulation for deep circuits
- ☁️ QoroService cloud backend — swap one line of code (
backend=QoroService(...)) and run at scale
Every example below follows the same pattern: Phase 1 runs locally on a toy problem to prove the algorithm works. Phase 2 scales up and offloads to QoroService — because your laptop shouldn't be the bottleneck.
pip install qoro-diviCreate a .env file in the repo root:
QORO_API_KEY="your_api_key_here"
from divi.backends import QoroService, JobConfig
backend = QoroService(job_config=JobConfig(shots=10_000))1. Cluster MaxCut ☁️
Partitioned QAOA for MaxCut on large, community-structured graphs. Splits large graphs (e.g., 50 qubits) into smaller sub-graphs via spectral clustering for parallel QAOA execution.
The bottleneck: A 50-node MaxCut graph has a 2⁵⁰ statevector. Your laptop can't touch it. The fix: Divi partitions the graph and QoroService runs every partition in parallel.
📓 Interactive notebook — step-by-step tutorial
VQE-based approach to find the Birkhoff decomposition of doubly stochastic matrices. Showcases the modular design of Divi — a sophisticated application built by inheriting from the VQE class with minimal code.
The bottleneck: VQE optimizer iterations × multi-threaded classical post-processing compound quickly. The fix: QoroService offloads the VQE circuit evaluations so the classical optimizer isn't starved.
📓 Interactive notebook — step-by-step tutorial
3. Portfolio Optimization ☁️
Quantum portfolio optimization using QAOA and PCE combined with spectral partitioning for large-scale financial problems. Partitions the asset correlation graph into smaller sub-problems.
The bottleneck: 480 assets → dozens of QAOA partitions. Running them sequentially on a local simulator takes hours. The fix: QoroService runs every partition in parallel — all portfolios optimized simultaneously.
📓 QAOA notebook — full QAOA workflow
📓 PCE notebook — same problem with logarithmic qubit compression
Implementation of the Quantum-Guided Cluster Algorithm from arXiv:2508.10656. QAOA extracts two-point correlations ⟨Z_i Z_j⟩ to guide a classical cluster Monte Carlo for Max-Cut.
The bottleneck: The paper's key result uses 28-node, 10-regular graphs at QAOA depth p=5 — 28 qubits with deep circuits. Infeasible locally. The fix: QoroService handles 28+ qubit QAOA with Maestro's GPU-accelerated MPS simulation.
📓 Interactive notebook — step-by-step tutorial
5. Economic Load Dispatch ☁️
Quantum-classical solution for the Economic Load Dispatch (ELD) problem using PCE-VQE with polynomial encoding to compress 12 binary variables into just 5 qubits.
The bottleneck: The PCE optimizer needs hundreds of circuit evaluations per iteration. Locally, each evaluation blocks the next. The fix: QoroService evaluates circuits in parallel, collapsing wall-clock time.
📓 Interactive notebook — step-by-step tutorial
6. Molecular Ground State ☁️
Potential energy surface of H₂ computed with VQE. Divi's VQEHyperparameterSweep grid-searches over ansätze × geometries in parallel.
The bottleneck: 2 ansätze × 12 bond lengths = 24 independent VQE runs. Sequentially, that's 24× the wait. The fix: QoroService dispatches all 24 VQE instances in parallel — same result, fraction of the time.
📓 Interactive notebook — step-by-step tutorial
Quantum solution for the TSP using QUBO + QAOA. Demonstrates Direct QAOA, Partitioned QAOA, and PCE encoding.
The bottleneck: 8 cities = 64-qubit QUBO. Even partitioned, each sub-problem is a full QAOA run. The fix: QoroService parallelizes the partitioned sub-problems and handles deeper circuits with Maestro.
📓 Interactive notebook — step-by-step tutorial
8. Spin Dynamics (TFIM) ☁️
Quantum simulation of spin dynamics using Divi's TimeEvolution module. Simulates a 1D spin chain under the Transverse-Field Ising Model Hamiltonian.
The bottleneck: Each time step generates a full Trotter circuit. 15-qubit chains with 15 time points = massive circuit volume. The fix: QoroService runs every time-step circuit on Maestro's GPU-accelerated simulator.
📓 Interactive notebook — step-by-step tutorial
Every example in this repo works locally on small problems. But when you're ready to go beyond toy instances:
- Get your free API key — $100 in credits, no credit card required
pip install qoro-divi- Set
QORO_API_KEYin your environment - Change one line:
backend = QoroService()
That's it. Same code, cloud scale.
See LICENSE for details.