Start Learning Quantum,
Learn For Free
Are you interested in learning about quantum computing? Find out how to access quantum simulators / real QPU hardware and start your journey for free.
Everything You Need to Start
From local simulators to free cloud QPUs — all the resources you need.
Free Simulators
Run quantum circuits locally or in the cloud on powerful simulators — supported on traditional hardware with no costs, no limits
Real Quantum Hardware
Access actual quantum processing units (QPUs) from IBM, IonQ, Quantinuum and others through free cloud programs.
Guides for SDKs & Platforms
Detailed setup guides for major quantum SDKs, including free-tier configuration.
IBM Qiskit
The most widely-used quantum SDK. Free access to IBM Quantum simulators and real QPUs via IBM Quantum Platform.
Google Cirq
Google's open-source framework for NISQ devices. Includes powerful local simulators with optional cloud backend.
Xanadu PennyLane
Quantum ML focused framework with many free backends. Perfect for variational algorithms and quantum-classical hybrid models.
Amazon Braket
AWS managed quantum service. Free simulators (SV1, DM1, TN1) with optional real hardware on pay-per-shot pricing.
NVIDIA CUDA-Q
GPU-accelerated quantum simulation. Run massive circuits orders of magnitude faster using NVIDIA GPUs — completely free locally.
Start in Minutes with HLQuantum
Run a real quantum algorithm in minutes — no circuit assembly, no boilerplate, just results.
Install HLQuantum with your preferred backend
HLQuantum ships with built-in implementations of QFT, Grover's search, VQE, QAOA, and more. Install once with whichever SDK you want to target underneath.
pip install hlquantum[qiskit] # or [cirq], [pennylane], [cudaq]…Define your search problem
Grover's algorithm finds a marked item in an unsorted list quadratically faster than any classical approach. Describe the target with a phase oracle — HLQuantum handles the full circuit construction.
import hlquantum as hlq
# Mark the target state in a 3-qubit (8-item) search space
oracle = hlq.oracles.phase_oracle(target="101")Run the algorithm — one function call
No circuit assembly, no ancilla qubit management, no manual diffuser. HLQuantum compiles and runs the optimal number of Grover iterations automatically.
result = hlq.algorithms.grover(oracle, qubits=3, shots=1024)
print(result.top_state()) # '101' found with ~97% probabilitySwap backends or scale to real hardware
The same call runs on any backend — swap to GPU-accelerated simulation for larger search spaces, or point at a real QPU with one extra flag.
# GPU simulation
result = hlq.algorithms.grover(oracle, qubits=3, backend="cudaq")
# Real IBM quantum hardware
result = hlq.algorithms.grover(oracle, qubits=3, backend="qiskit", device="ibm_sherbrooke")