Developers
Sample Notebooks
Ready-to-run Jupyter notebooks for the Quantum Rings SDK. Run them right in your browser, open them in Google Colab, or grab the source from our public GitHub repository.
Start here
New to the Quantum Rings SDK? This one walks you through your first simulation.
Getting started with the Quantum Rings SDK
Install the SDK, build your first circuit, and simulate systems with hundreds of qubits right on your laptop.
Quantum algorithms
The classic quantum algorithms, implemented directly on the Quantum Rings SDK and matched to the documentation examples.
GHZ state
Entangle 50 qubits into a GHZ state, a scale far beyond statevector simulators.
Bernstein-Vazirani algorithm
Recover a hidden bit string in a single query instead of one per bit.
Simon's algorithm
The first exponential quantum speedup: find the hidden period of an oracle function.
Grover's search
Search an unstructured space with quadratic speedup via amplitude amplification.
Quantum Fourier Transform
The QFT and its inverse, with quantum adders and multipliers built on top.
Shor's algorithm
Factor integers with the period-finding algorithm that started it all.
Optimization with QAOA
Solve Max-Cut with the Quantum Approximate Optimization Algorithm and a classical optimizer loop.
Variational Quantum Eigensolver
Find ground-state energies with a hybrid variational loop and Pauli expectation values.
Quantum Rings for Qiskit
Keep your Qiskit code and swap in the Quantum Rings provider: basic usage and every primitive.
Basic usage with Qiskit
Point Qiskit at the Quantum Rings provider and run your first circuit on the simulator.
Sampler usage
Use the Qiskit Sampler primitive backed by the Quantum Rings simulator.
Estimator usage
Estimate observable expectation values with the Estimator primitive.
Statevector estimator example
Exact expectation values from the statevector-based Estimator.
Statevector sampler example
Exact sampling from the statevector-based Sampler.
Qiskit tutorials on Quantum Rings
Classic Qiskit tutorials, adapted to run at scale on the Quantum Rings simulator.
CHSH inequality
Violate the CHSH inequality and see quantum entanglement beat any classical strategy.
Grover's search
Find a marked item quadratically faster with Grover's algorithm.
QAOA
Solve a combinatorial problem with the Quantum Approximate Optimization Algorithm.
Heisenberg chain ground state with VQE
Estimate the ground-state energy of a Heisenberg spin chain with the Variational Quantum Eigensolver.
Hadron dynamics
Simulate hadron dynamics on a lattice, a physics workload that leans on large qubit counts.
Finance
Qiskit Finance applications running on the Quantum Rings simulator.
Quantum amplitude estimation
The estimation primitive behind quantum risk analysis and option pricing.
Portfolio optimization
Pick an optimal asset portfolio by mapping mean-variance optimization to a quantum problem.
Pricing European call options
Price a European call option with quantum amplitude estimation.
Pricing European put options
Price a European put option with quantum amplitude estimation.
Pricing bull spreads
Price a bull spread, a two-option strategy, on the simulator.
Pricing basket options
Price an option written on a basket of underlying assets.
Asian barrier spreads
Price a path-dependent Asian barrier spread, a harder derivative.
Pricing fixed-income assets
Value a fixed-income asset with uncertain interest rates.
Credit risk analysis
Estimate value at risk for a loan portfolio with quantum amplitude estimation.
Option pricing with qGANs
Learn the underlying asset distribution with a quantum GAN, then price the option.
Optimization
Qiskit Optimization applications running on the Quantum Rings simulator.
Quadratic programs
Build the quadratic programs that quantum optimizers consume.
Converters for quadratic programs
Transform constrained problems into forms a quantum optimizer can solve.
Minimum eigen optimizer
Solve optimization problems by finding minimum eigenvalues with QAOA or VQE.
Grover optimizer
Use Grover adaptive search to minimize a quadratic program.
ADMM optimizer
Split mixed-binary problems between quantum and classical solvers with ADMM.
Max-cut and TSP
Two classic graph problems, max-cut and the traveling salesman, solved quantum-style.
Vehicle routing
Route a fleet of vehicles with a quantum optimizer.
CVaR optimization
Improve variational optimization by minimizing conditional value at risk.
Application classes
The ready-made application classes for common optimization problems.
Warm-start QAOA
Seed QAOA with a classical solution for better convergence.
Quantum random access optimizer
Encode more than one variable per qubit with quantum random access codes.
Nature
Qiskit Nature workloads running on the Quantum Rings simulator.
Deuteron binding energy
Compute the binding energy of the deuteron, a small nuclear-physics VQE problem.
Performance and accuracy
Advanced: measure how far the simulator can go on your problem and how accurate it stays.
Finding the simulation size
Discover how large a circuit your machine can handle: sweep qubit counts and watch where the simulator tops out.
Mirror fidelity calculation
Quantify simulation accuracy by running mirror circuits and computing their fidelity.
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