QDaria Quantum Book#
A comprehensive educational resource covering quantum mechanics, quantum computing, quantum machine learning, post-quantum cryptography, and their real-world applications across the QDaria product ecosystem.
What You’ll Learn#
From wave-particle duality to density matrices. Build physical intuition for quantum phenomena.
Gate model, algorithms (Shor, Grover, VQE), error correction, and multi-framework programming.
Superconducting qubits, trapped ions, photonics, topological approaches, and the DiVincenzo criteria.
Variational circuits, quantum kernels, hybrid algorithms, and quantum-enhanced optimization.
NIST FIPS 203/204/205, lattice cryptography, QRNG, and the quantum threat timeline.
15 hands-on Jupyter notebooks with Colab launch buttons. Learn by doing.
QDaria Products#
PQC encryption infrastructure
Quantum finance & HFT
Education & ESG certification
Quantum HPC/CFD research
Quantum LLM & artifacts
Framework Coverage#
All code examples are provided in four quantum computing frameworks:
Framework |
Provider |
Strengths |
|---|---|---|
Qiskit |
IBM |
Largest ecosystem, real hardware access |
Cirq |
Low-level control, Sycamore access |
|
PennyLane |
Xanadu |
ML integration, autodiff |
PyQuil |
Rigetti |
Quilc compiler, forest SDK |
Q# (Microsoft) is included where topological quantum computing is discussed.
How to Use This Book#
Foundations first: Parts I-V build conceptual understanding
Products: Parts VI-X show real-world applications
Notebooks: Part XI provides hands-on practice with Colab buttons
Appendix: Reference material, glossary, and curated resources
Prerequisites
Basic linear algebra (vectors, matrices, eigenvalues) and Python programming. No prior quantum knowledge required.