Description
Mathematics for Quantum Technology
Foundation Course for Quantum Computing & Quantum Algorithms
Quantum technologies such as Quantum Computing, Quantum Machine Learning, Quantum Simulation, and Quantum Optimization rely heavily on mathematical concepts. This course is designed to help students, researchers, and professionals build the mathematical intuition required to understand quantum algorithms and quantum systems.
The Mathematics for Quantum Technology program focuses on the essential mathematical tools used in quantum mechanics and quantum computing, including linear algebra, probability theory, complex numbers, vector spaces, and matrix operations.
Through guided explanations and practical examples, participants will learn how these mathematical concepts are applied in quantum states, quantum gates, quantum circuits, and quantum algorithms.
This course is ideal for learners who want to strengthen their mathematical foundation before moving into advanced quantum computing courses such as QML, QIO, or QTP programs at KwantumG.
Course Details
Course Name: Mathematics for Quantum Technology
Total Sessions: 10 Sessions
Batch Type: Weekend Batch
Schedule: Every Saturday & Sunday
Time: 6:00 PM – 7:00 PM
Mode: Online Live Sessions
What You Will Learn
Participants will build a strong understanding of the mathematical concepts used in quantum technologies:
1. Mathematical Foundations
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Complex numbers and Euler representation
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Vectors and vector spaces
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Dirac notation (Bra-Ket notation)
2. Linear Algebra for Quantum Systems
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Matrices and matrix operations
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Eigenvalues and eigenvectors
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Unitary and Hermitian matrices
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Tensor products
3. Probability & Quantum Measurement
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Classical probability vs quantum probability
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Measurement operators
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Quantum state collapse
4. Quantum States Representation
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Qubits and state vectors
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Bloch sphere representation
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Superposition and entanglement (mathematical view)
5. Mathematical Representation of Quantum Gates
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Pauli matrices
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Hadamard gate
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Rotation gates
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Multi-qubit operators






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