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    +91 88943 57155
    Pune, Maharashtra, India

    Duration

    4 Years

    Physics

    Plaksha University, Mohali
    Duration
    4 Years
    Physics UG OFFLINE

    Duration

    4 Years

    Physics

    Plaksha University, Mohali
    Duration
    Apply

    Fees

    ₹2,50,000

    Placement

    92.0%

    Avg Package

    ₹6,50,000

    Highest Package

    ₹12,00,000

    OverviewAdmissionsCurriculumFeesPlacements
    4 Years
    Physics
    UG
    OFFLINE

    Fees

    ₹2,50,000

    Placement

    92.0%

    Avg Package

    ₹6,50,000

    Highest Package

    ₹12,00,000

    Seats

    120

    Students

    120

    ApplyCollege

    Seats

    120

    Students

    120

    Curriculum

    Curriculum Overview

    The Physics program at Plaksha University Mohali is structured to provide a comprehensive education that balances fundamental theory with contemporary applications. The curriculum spans eight semesters and includes core courses, departmental electives, science electives, and laboratory sessions designed to foster critical thinking and practical problem-solving skills.

    Course Structure Table

    SemesterCourse CodeFull Course TitleCredit (L-T-P-C)Prerequisites
    IPYS101Introduction to Physics3-0-2-4-
    IMAT101Calculus I4-0-0-4-
    IMAT102Linear Algebra and Differential Equations3-0-0-3-
    ICHM101Chemistry for Physics Students3-0-2-4-
    IBIO101Biology for Scientists3-0-2-4-
    IPHY101Basic Mechanics3-0-0-3-
    IIMAT201Calculus II4-0-0-4MAT101
    IIMAT202Probability and Statistics3-0-0-3MAT101
    IIPHY102Thermodynamics and Statistical Mechanics3-0-0-3PHY101
    IIPHY103Electromagnetic Theory I3-0-0-3PHY101
    IIPHY104Quantum Mechanics I3-0-0-3PHY101
    IIIMAT301Advanced Calculus4-0-0-4MAT201
    IIIPHY201Electromagnetic Theory II3-0-0-3PHY103
    IIIPHY202Quantum Mechanics II3-0-0-3PHY104
    IIIPHY203Solid State Physics3-0-0-3PHY101
    IIIPHY204Optics and Waves3-0-0-3PHY101
    IVPHY301Atomic Physics3-0-0-3PHY202
    IVPHY302Nuclear and Particle Physics3-0-0-3PHY202
    IVPHY303Computational Physics3-0-2-4MAT201, MAT202
    IVPHY304Biophysics3-0-0-3PHY201
    VPHY401Advanced Electromagnetic Theory3-0-0-3PHY201
    VPHY402Quantum Field Theory3-0-0-3PHY202
    VPHY403Nanotechnology3-0-2-4PHY203
    VPHY404Plasma Physics3-0-0-3PHY201
    VIPHY501Research Methodology2-0-2-3-
    VIPHY502Mini Project I2-0-4-4-
    VIPHY503Mini Project II2-0-4-4-
    VIPHY504Physics Lab I2-0-4-4-
    VIIPHY601Final Year Thesis/Capstone Project4-0-8-8PHY501
    VIIPHY602Special Topics in Physics3-0-0-3-
    VIIPHY603Physics of Emerging Technologies3-0-0-3-
    VIIPHY604Internship in Physics2-0-0-2-
    VIIIPHY701Advanced Research Project4-0-8-8PHY601
    VIIIPHY702Capstone Presentation2-0-0-2-
    VIIIPHY703Professional Ethics and Communication2-0-0-2-
    VIIIPHY704Internship Report Writing2-0-0-2-

    Advanced Departmental Elective Courses

    Departmental electives are designed to deepen students' understanding of specialized areas within physics and encourage interdisciplinary exploration. These courses are taught by faculty members who are actively involved in cutting-edge research.

    • Quantum Algorithms: This course explores the design and implementation of quantum algorithms, focusing on their applications in cryptography, optimization, and machine learning. Students will gain hands-on experience with quantum programming languages like Qiskit and Cirq.
    • Advanced Nanofabrication Techniques: This course covers the principles and techniques used in creating nanostructures for electronic, optical, and biological devices. Topics include electron beam lithography, atomic layer deposition, and molecular self-assembly.
    • Computational Modeling of Biological Systems: Using computational methods to model complex biological processes such as protein folding, gene expression, and neural networks. Students will learn simulation techniques using tools like MATLAB and Python.
    • Energy Storage Technologies: This course examines the physics behind modern energy storage systems, including batteries, supercapacitors, and fuel cells. Students will explore materials science aspects and efficiency improvements.
    • Optical Fiber Communications: An in-depth look at how light is transmitted through optical fibers and how this technology underpins modern telecommunications networks. Includes practical lab sessions on fiber optic equipment.
    • Medical Imaging Physics: Focuses on the physical principles underlying medical imaging modalities such as MRI, CT scans, X-rays, and ultrasound. Students will study image reconstruction algorithms and radiation safety.
    • Nonlinear Dynamics and Chaos Theory: Explores chaotic behavior in dynamical systems and its relevance to physics, engineering, and biology. Covers phase space analysis, bifurcation diagrams, and computer simulations.
    • Relativistic Quantum Mechanics: Extends quantum mechanics to include relativistic effects, covering topics such as the Klein-Gordon equation, Dirac equation, and spinor fields. Applications in particle physics are emphasized.
    • Plasma Diagnostics and Instrumentation: Introduces diagnostic techniques used to study plasmas in laboratory settings and astrophysical environments. Includes Langmuir probe measurements, spectroscopy, and interferometry.
    • Quantum Optics and Quantum Information: Examines the interaction between light and matter at the quantum level, focusing on applications in quantum communication and computing. Covers entanglement, quantum teleportation, and quantum cryptography.

    Project-Based Learning Philosophy

    The department emphasizes project-based learning as a cornerstone of its educational approach. Mini-projects are introduced in the second year, allowing students to apply theoretical knowledge in practical settings. These projects typically span 2-3 months and involve small teams working under faculty supervision.

    Mini-projects are assigned based on student interests and available research topics. For example, a recent project involved designing a low-cost spectrometer for environmental monitoring, while another explored the use of machine learning algorithms in predicting material properties.

    The final-year capstone project is a significant undertaking that requires students to conduct original research or develop an innovative solution to a real-world problem. The project is guided by a faculty mentor and must culminate in a comprehensive report and presentation.

    Students are encouraged to collaborate with industry partners, government agencies, or other academic institutions during their projects. This exposure helps them understand the practical implications of their work and prepares them for future careers in research or development.