Basic Tutorials
- Quantum Entanglement with Classiq
- Exponentiation and Hamiltonian Simulation
- Grover Algorithm for Graph Coloring Problem
- Optimizing MCX Gates, Preparing for Future Hardware Today
- Learning Optimization
- Walk-through:
prepare_state - Quantum Machine Learning with Classiq
- Linear Combination of Unitaries (LCU)
- Quantum walk on complex network
- Quantum Monte Carlo Integration to Estimate Pi Using Quantum Amplitude Estimation
- Classiq Overview Tutorial
- Qmod Tutorial - Part 1
- Qmod Tutorial - Part 2
- Synthesis Tutorial
- Execution Tutorial - Part 1
- Execution Tutorial - Part 2
Advanced Tutorials
- Discrete Quantum Walks
- Quantum walks on one and two dimentional lattice
- Designing Quantum Algorithms with Second Order Functions: A Flexible QPE
Workshops
- High-level Algorithm Design with Qmod Part I
- High-level Algorithm Design with Qmod Part II
- Combinatorial Optimization Workshop using the Qmod quantum types - part 1
- Estimating European Option Price Using Amplitude Estimation - Workshop
- Quantum Optimization Training - part 3
- Quantum Optimization Training - part 2
- Rainbow options workshop with the bruteforce methodology
- Grover from functional building blocks
- Modeling an HHL Algorithm to Solve a Set of Linear Equations
- Quantum Oracles Workshop
Technology Demonstrations
- Approximated State Preparation
- Arithmetic Expressions
- Auxiliary Reuse and Management
- Discrete Quantum Walk on a Circle
- Hamiltonian Evolution for a Water Molecule
- HW-aware Synthesis of MCX
- HHL for Solving
- Oracle generation for 3-SAT problems
- QAOA
- Quantum Phase Estimation on a Grover Operator
- Quantum Phase Estimation for a Matrix
- Classiq code for QSVT example
- PennyLane code for QSVT example
- Qiskit code for QSVT example
- PyTket code for QSVT example
- Classiq code for discrete quantum walk
- PennyLane code for discrete quantum walk
- Qiskit code for discrete quantum walk
- PyTket code for discrete quantum walk