Quantum Quest
Discover quantum computing through our interactive learning platform. We’ve built Quantum Quest to suit your needs, fitting for beginners and experts alike.
Learn quantum computing, with us
Embark on your journey in quantum! Discover our approach to quantum computing through our interactive learning platform. We've built Quantum Quest to suit your needs, fitting for beginners and experts alike.
Discover Quantum Quest's five learning modules
Introduction
Learn about the fundamentals of quantum computing: qubits and quantum algorithms and what makes quantum processors different from classical ones, and how they enable us to solve complex problems.
What you will learn
- Fundamental principles
- Quantum speed-up
- Hardware platforms
- Development roadmap
- Quantum computing as a service
- Business use cases
Mathematics
Delve into Dirac notation, bra and ket vectors through engaging activities. Learn about the foundational postulates of quantum mechanics, qubits and superposition, as well as more advanced topics such as unitary transformations and Hamiltonian evolution.
What you will learn
- Dirac Notation
- Qubits & Superposition
- Unitary evolution
- Projective Measurements
Physics
Dive deeper into neutral atom quantum processors. Learn about Pulser, Pasqal&pos;s open-source package for designing pulse sequences in programmable neutral-atom arrays.
What you will learn
- Neutral atom arrays
- Two-level transitions
- Interacting atoms
- Analog quantum computing with neutral atoms
Quantum optimization
Learn about Linear Optimization and QUBO problems, and how to solve them using hybrid quantum-classical methods.
What you will learn
- Quantum and hybrid quantum-classical solvers for linear optimization problems
- QAOA and QAA to solve a QUBO problem
- A hybrid quantum-classical column-generation algorithm to solve a graph optimization problem
- A MILP solver using Benders decomposition assisted by neutral atom quantum processor
Machine Learning
Learn about Machine Learning, from basics to Quantum Machine Learning, Transformer models and how neutral atom quantum computers can enhance their performance.
What you will learn
- Machine Learning in a nutshell
- Quantum classical models and quantum feature maps
- A quantum evolution kernel to solve a graph classification problem
- Quantum positional encoding for graph neural networks
