Course Details

Exam Registration2302
Course StatusOngoing
Course TypeElective
LanguageEnglish
Duration12 weeks
CategoriesComputer Science and Engineering
Credit Points3
LevelPostgraduate
Start Date19 Jan 2026
End Date10 Apr 2026
Enrollment Ends02 Feb 2026
Exam Registration Ends20 Feb 2026
Exam Date24 Apr 2026 IST
NCrF Level4.5 — 8.0

Quantum Computing: Algorithms and Limitations Through the Query Model

Quantum computing has transitioned from a theoretical curiosity to a tangible frontier in computer science and engineering. With the promise of solving problems intractable for classical computers, it has captured the imagination of researchers and industry alike. This detailed exploration is based on a comprehensive 12-week postgraduate course designed and taught by Prof. Rajat Mittal at IIT Kanpur, which delves deep into the algorithms that define quantum advantage and the fundamental limitations that bound it, primarily through the powerful lens of the query model.

Course Overview and Instructor Profile

This advanced course is structured to provide a rigorous, computer science-focused perspective on quantum computation. It is led by Prof. Rajat Mittal, an associate professor at IIT Kanpur with a distinguished background. After completing his PhD from Rutgers University, Prof. Mittal spent three years as a postdoctoral fellow at the prestigious Institute for Quantum Computing in Waterloo, Canada. His research interests lie at the intersection of quantum and classical computing, where he employs tools like linear/semidefinite programming and Fourier analysis to explore the advantages and inherent limits of quantum machines. His dedication to pedagogy is evidenced by awards like the “1989 Batch faculty teaching award for innovation in teaching 2021” and the “Excellence in teaching award 2019, IIT Kanpur”.

Who Should Take This Course?

The course is meticulously designed for postgraduate students and professionals aiming to build a strong theoretical foundation in quantum algorithms.

  • Intended Audience: Computer scientists and mathematicians seeking to understand the fundamentals and advanced concepts of quantum algorithms.
  • Prerequisites: A solid grasp of Linear Algebra and Probability is essential to follow the mathematical formalism.
  • Industry Support: The curriculum is highly relevant for:
    • Quantum Technology Companies & Startups
    • Government & Research Labs (e.g., DRDO, ISRO)
    • Advanced Software Consulting Firms

Detailed 12-Week Course Layout

The course progresses from foundational concepts to advanced topics in quantum complexity theory.

WeekTopics Covered
Week 1What is quantum computing? Quantum weirdness: Mach-Zehnder interferometer.
Week 2Linear algebraic formulation of states: deterministic, randomized and quantum, qubits, composite systems.
Week 3Operations in quantum computing, basic gates and circuits, Mach-Zehnder in terms of quantum operations.
Week 4Semidefinite matrices, projectors, measurements, principle of deferred measurement.
Week 5Classical vs. quantum circuits, Deutsch (from Mach-Zehnder) and Deutsch-Jozsa algorithms, swap circuit.
Week 6Randomized computation with examples, setting the stage for quantum speedups.
Week 7Simon’s algorithm, Quantum Fourier transform, and its groundbreaking applications: phase estimation and Shor’s factoring algorithm.
Week 8Grover’s search algorithm, amplitude amplification and its variants.
Week 9Random walks and discrete-time quantum walks.
Week 10Query Model: Classical and quantum, approximate degree, optimality of Grover search.
Week 11Total functions: Understanding why there is at most a polynomial separation between deterministic and quantum query complexity.
Week 12Super-quadratic separation: Cheatsheet model, partial functions, Aaronson-Ambainis conjecture, and the Forrelation problem.

Core Focus: Algorithms and the Query Model

The heart of the course lies in its dual focus: understanding the revolutionary algorithms that promise quantum advantage and the theoretical models that define its limits.

Key Quantum Algorithms Covered

  • Shor’s Algorithm: The algorithm that sparked widespread interest in quantum computing by showing an efficient method for integer factorization, threatening classical cryptographic systems like RSA.
  • Grover’s Algorithm: Provides a quadratic speedup for unstructured search problems, a fundamental primitive with broad applications.
  • Quantum Fourier Transform (QFT): The quantum analogue of the discrete Fourier transform, serving as the crucial subroutine in Shor’s algorithm and many others.
  • Amplitude Amplification: A generalization of Grover's search that boosts the probability of a desired outcome.

Understanding Limits: The Power of the Query Model

A significant portion of the course is dedicated to the query model (or black-box model), a powerful abstraction in computational complexity. This model allows computer scientists to:

  • Prove lower bounds on the number of queries (or calls to an oracle) a quantum algorithm must make to solve a problem.
  • Formally establish the optimality of algorithms like Grover’s search.
  • Explore the maximum possible separation between quantum and classical computing power for different problem types (e.g., total vs. partial functions).
  • Investigate modern conjectures and results, such as the Aaronson-Ambainis conjecture and the Forrelation problem, which demonstrate super-quadratic quantum advantages in specific, structured settings.

Recommended Textbooks

To supplement the lectures, the course draws from two seminal texts in the field:

  • Nielsen & Chuang: Quantum Computation and Quantum Information (often called the "bible" of quantum computing).
  • Kaye, Laflamme & Mosca: An Introduction to Quantum Computing.

This course, through its structured journey from quantum weirdness to the cutting-edge query complexity of partial functions, offers a unparalleled deep dive into why quantum computing is powerful, where that power comes from, and what its ultimate theoretical limitations might be. It is an essential intellectual journey for anyone serious about the future of computation.

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