BlueQubit | Quantum Tutorials

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Explore Quantum Computing Tutorials

Learn quantum computing by building real circuits instead of just reading theory. From quantum computing for beginners (like our BQ 101 guide) to advanced VQE and QAOA algorithms, every quantum computing tutorial here makes it easy to see exactly how do you program a quantum computer. Stop wondering how to start quantum computing—grab your API token and begin building, optimizing, and simulating complex circuits using Qiskit and PennyLane on high-performance infrastructure

BQ 201: Choosing a Quantum Circuit Simulator

Learn how to choose a quantum circuit simulator for your workload. Compare statevector, MPS, and Pauli-path simulation by qubit count, entanglement, bond dimension, and CPU/GPU performance.

Accelerated Quantum Research with AI Agents and Compute

See how combining AI agents with compute and a dedicated quantum environment such as BlueQubit's platform can let anyone accelerate their computationally heavy experiments and R&D in general.

Certifying T-Count Lower Bounds with MITM

Learn how T-gate quantum computing relies on certifying magic-state T-count lower bounds in the measurement-assisted model: stabilizer nullity, meet-in-the-middle (MITM) search, and exhaustive rule-out in the all-measurements-at-end family. Walk through a controlled-S witness as a Clifford+T circuit, then push a laptop-scale CCZ bound past nullity.

Writing Quantum Code with BlueQubit AI

Learn quantum portfolio optimization with BlueQubit AI: QAOA, QUBO, and Ising encoding for a 10-asset portfolio, then run and verify in-notebook.

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Quantum Image Classification with Pauli-Path Simulation

This quantum image classification tutorial demonstrates how to train a utility-scale quantum image classifier with the BlueQubit SDK using the Pauli-Path Simulation (PPS) pipeline and Simultaneous Perturbation Stochastic Approximation (SPSA). Each image is split into blocks and encoded as state-preparation circuits with BlockImageLoader, a parameterized trainer ansatz with single-qubit Pauli-Z observables acts as the feature extractor, and a linear classification head is trained end-to-end with SPSA. A small two-class real-data subset of the Honda Scenes Dataset (clear-day vs snow-day driving scenes) keeps the run to a few minutes while showing how the same method scales to 60+ qubit circuits, where forward state-vector simulation is intractable.

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Hierarchical Block-Based Image Loading with BlockImageLoader

Learn how to load images into quantum circuits using BlueQubit's BlockImageLoader pipeline, which uses hierarchical training and block-based encoding for accurate amplitude representations.

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Finding Hamiltonian Ground State Energy

Learn how to find molecular ground-state energies on BlueQubit using hamiltonian_gs() function, which uses variational quantum methods. In this hands-on Variational Quantum Eigensolver tutorial, you'll build the hydrogen Hamiltonian, run a VQE workflow with the BlueQubit Estimator, optimize circuit parameters, and compare sampled results against classical baselines.

QAOA for Low Autocorrelation Binary Sequences (LABS) problem

Learn how to solve combinatorial optimization problems on the BlueQubit platform using the Quantum Approximate Optimization Algorithm (QAOA). This hands-on QAOA tutorial tackles the Low Autocorrelation Binary Sequences (LABS) problem - a challenging benchmark from signal processing - and walks you through building the cost Hamiltonian, optimizing QAOA circuit parameters with the BlueQubit Estimator, and sampling results to beat classical random search.

Breaking Peaked Quantum Circuits Classically

This tutorial explores several classical strategies for attacking ("breaking") peaked quantum circuits, including sampling-based methods and the marginal attack. Using Statevector, MPS, and Pauli-Path simulators, we show how these techniques can recover the hidden peak bitstring for peaked circuits of moderate size, even when the circuits are designed to look random and hard to analyze. Along the way, we outline an elementary construction of peaked circuits and examine their robustness and the extent to which they are vulnerable to circuit "compression" attacks.

QAOA with BlueQubit

This tutorial demonstrates how to solve the Maximal Independent Set (MIS) problem using the Quantum Approximate Optimization Algorithm (QAOA). It shows how to construct the QAOA ansatz by alternating cost and mixer unitaries and then optimize its energy using BlueQubit's Pauli-path simulator (PPS), which is significantly faster than statevector simulators for this problem at 25 or more qubits.

BQ 101: An Introduction to the BlueQubit Platform

This quantum computing basics tutorial introduces the BlueQubit platform by first reviewing fundamental quantum computing concepts such as qubits, superposition, entanglement, and controlled quantum gates. Through this quantum computing introduction, readers will then learn how to build, simulate, and analyze canonical circuits like the Bell state and GHZ-state circuit using different backends, including the StateVector and Matrix Product State (MPS) simulators.

Pauli-Path Simulation of Quantum Circuits

Learn how to simulate large-scale quantum circuits on the BQ platform using Pauli-Path Simulation, a powerful classical method that evolves observables instead of states. This hands-on tutorial explains the essential technique of coefficient truncation and walks you through recreating the results of IBM's landmark 127-qubit utility experiment.