Welcome to the repository for CNYT (Ciencias Naturales y Tecnología - Natural Sciences and Technology) at the Escuela Colombiana de Ingeniería Julio Garavito. This comprehensive collection showcases the fascinating journey through quantum computing fundamentals, from complex number operations to advanced quantum algorithms — exploring the intersection of mathematics, physics, and computer science 🌌.
- Complex number operations, vector spaces, and matrix algebra
- Inner products, eigenvectors, and eigenvalues
- Hermitian and Unitary matrices, tensor products
- Quantum states, superposition, and measurement theory
- Quantum observables and probability amplitudes
- Classic to quantum system transitions
- Double-slit experiment simulations
- Deutsch and Deutsch-Jozsa algorithms
- Grover's search algorithm
- Shor's factorization algorithm
- Quantum circuit design and IBM Quantum Composer
- Quantum computing architecture and hardware principles
Throughout this course, several specialized repositories were developed to implement quantum computing concepts:
A Python library implementing complex number operations from scratch, including arithmetic operations, polar/cartesian conversions, and complex conjugates. 🔗 View Repository
Advanced complex number and matrix operations using NumPy, including vector spaces, inner products, and quantum state representations. 🔗 View Repository
A comprehensive quantum system simulator implementing state evolution, measurement operations, and basic quantum gates. 🔗 View Repository
Implementation of quantum observable measurements, Hermitian operators, and probability calculations for quantum states. 🔗 View Repository
Interactive simulation of the famous double-slit experiment demonstrating wave-particle duality and quantum interference patterns. 🔗 View Repository
Python implementation of Shor's quantum factorization algorithm, one of the most significant quantum algorithms for cryptography. 🔗 View Repository
Focus: Complex numbers, vector spaces, and quantum mathematical structures
- Complex Number Operations – Introduction to complex arithmetic and representations
- Vector & Matrix Operations with NumPy – Advanced linear algebra for quantum computing
- Inner Products & Eigenvectors – Essential mathematical tools for quantum mechanics
- Hermitian, Unitary & Tensor Operations – Quantum operators and multi-qubit systems
Key Notebooks:
- ComplexIntro.ipynb – Complex numbers fundamentals
- Complex_Vector_Matrix_Operations_with_NumPy.ipynb
- TallerEsp.Vect-ProdInterno-VectoPropios.ipynb
Focus: Transition from classical to quantum systems, measurement theory, and quantum experiments
- Classic to Quantum Transitions – Understanding the quantum leap from classical physics
- Quantum Observable Measurements – Implementing measurement operations and collapse
- Double-Slit Competition – Simulating wave-particle duality and interference
Key Notebooks:
Related Repositories:
- Quantum Systems Simulator – Classic to quantum transitions
- Quantum Observables – Measurement theory
- Double-Slit Experiment – Wave-particle duality
Focus: Advanced quantum algorithms and real quantum hardware implementation
- Deutsch Algorithm – First quantum algorithm demonstrating quantum advantage
- Deutsch-Jozsa Algorithm – Extended version for function analysis
- Grover's Algorithm – Quantum search with quadratic speedup
- Shor's Algorithm – Integer factorization for cryptography
Algorithm Directories:
Related Repository:
- Quantum hardware principles and error correction
- Quantum circuit optimization
- IBM Quantum hardware specifications
Architecture Materials:
- Hands-on quantum circuit design using IBM's cloud platform
- Real quantum hardware execution and simulation
- Quantum gate implementation and testing
IBM Composer Work:
Interactive Python notebooks implementing quantum computing concepts with step-by-step explanations and visualizations.
Practical implementations of quantum algorithms and mathematical operations using Python, NumPy, and quantum computing libraries.
Visual representations of quantum phenomena including state evolution, interference patterns, and algorithm performance.
Comprehensive slides covering quantum mechanics, complex analysis, linear algebra, and computational theory.
Python 🐍– Primary programming languageNumPy 🔢– Numerical computing and linear algebraJupyter Notebooks 📓– Interactive development environmentIBM Quantum Composer ⚛️– Real quantum hardware accessQiskit 🌀– Quantum computing frameworkMatplotlib & Visualization Tools 📊– Data visualization
FIRST TERM: Mathematical Foundations
↓
Complex Numbers → Vector Spaces → Quantum Operators
↓
SECOND TERM: Quantum Systems
↓
Classical to Quantum → Measurements → Experiments
↓
THIRD TERM: Advanced Applications
↓
Quantum Algorithms → Architecture → Real Hardware
- LS_Notes/ – Learning support materials and additional notebooks
- Slides/ – Complete theoretical presentations organized by term
- Exams/ – Practice problems and assessment materials
- Libreria computación cuántica/ – Custom quantum computing library
Explore the quantum realm, experiment with superposition, and unlock the power of quantum computing. 💌 andersson.sanchez-m@mail.escuelaing.edu.co — Let's explore quantum possibilities together!
"If you think you understand quantum mechanics, you don't understand quantum mechanics." – Richard Feynman
Embrace the uncertainty. Measure the impossible. Compute the future. ⚛️🌌