RITHIK RAI
Research Profile Statement

Physics graduate with research experience in quantum combinatorial optimisation, including QUBO formulations for vehicle routing and graph-theoretic approaches to quantum annealer scalability. Core interest in digital quantum simulation — using established physical theory to design quantum algorithms that model complex phenomena inaccessible to classical computation. Background in general relativistic perturbation theory and linearised GR. Seeking to contribute to computational quantum algorithms research with applications in optimisation and simulation.

Education

Master of Science in Physics

Jul 2022 – Aug 2024 | Kochi, India

CGPA: 8.19 / 10

  • •Relevant coursework: Quantum Mechanics I & II, Quantum Computation & Information, Statistical Mechanics, Mathematical Physics, Deep Learning.

    • Thesis supervised by Dr. Sayan Chakrabarti, Associate Professor, IIT Guwahati (Remote).

    Reproduced foundational derivations in linearised GR: gravitational wave propagation in flat spacetime (TT gauge, quadrupole formula, binary inspiral); linearisation of Einstein's equations on Schwarzschild background; derivation of the Regge-Wheeler equation via spherical harmonic decomposition; quasinormal mode boundary conditions and WKB frequency computation.

    Bachelor of Science in Physics

    Jun 2018 – Apr 2021 | Mumbai, India

    CGPA: 9.43 / 10

    Research Experience

    Quantum Computing Researcher (International Open-source Research Collaboration)

    Jul 2025 – Present | Remote

    Supervisor: Dr. Paweł Gora (Fundacja Quantum AI)

  • •Formulated QUBO models and implemented Full QUBO Solver (FQS) and Average Partitioning Solver (APS) based on (Borowski et al., 2020⁠); validated solutions using classical simulated annealing and quantum simulated annealing.
  • •Built a graph-coarsening pipeline to scale VRP instances (supernode creation → solve → uncoarsen) based on (Nałęcz-Charkiewicz et al., 2025⁠), improving solver runtime on large instances.
  • •Investigating spectral graph coarsening via Laplacian eigendecomposition to improve QUBO scalability for large VRP instances.

    • Master's Thesis Fellow

    Jan 2024 – May 2024 | Remote

    Supervisor: Dr. Sayan Chakrabarti, Associate Professor, IIT Guwahati

  • •Reviewed and reproduced mathematical foundations of gravitational wave theory under IIT Guwahati supervision; see Thesis above.
    • Projects

    Team project of 3 members

  • •Implementation: Translated a theoretical quantum algorithm (Xin et al., 2020⁠) into a working Classiq SDK model to solve the 2nd-order LDE of a Quantum Harmonic Oscillator using the Truncated Taylor Series (LCU) method.
  • •Energy Computation: Mapped the time evolution of the system to a quantum circuit, successfully extracting the physical Kinetic and Potential Energies directly from the work qubit's measurement probabilities.
  • •Circuit Optimisation: Mathematically proved the redundancy of the routing ancilla qubit (a_1) for closed systems (b=0). By stripping this out of the synthesis model, reduced the circuit width by 25% and depth by ~50% compared to the original compiler.

    • Team project of 3 members⁠⁠

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  • •Implemented the Galton Board using quantum circuits based on (Carney & Varcoe, 2022⁠): demonstrated how quantum interference produces a qualitatively different probability distribution from the classical case, with destructive interference creating a valley at the centre rather than the Gaussian peak.
  • •Identified and documented multiple discrepancies between the reference paper's stated derivations and the correct theoretical predictions for specific interference configurations; recorded corrections in a dedicated GitHub repository. See: github.com/iarithik/Corrections-to-Universal-Statistical-Simulator-arXiv-2202.01735⁠

    • Team project of 4 members

  • •Optimised battery temperature in lithium-ion EV batteries using quantum annealing to maintain State of Charge (SoC) and improve State of Health (SoH); processed NASA battery datasets, formulated the optimisation as a QUBO model, and implemented solutions on D-Wave's quantum annealer to minimise temperature.
    • Skills

    Programming Languages: Python

    Mathematical: QUBO formulation, perturbation theory (linearised GR), quantum circuit optimisation

    Libraries & Frameworks: Qiskit, PennyLane, Classiq, D-Wave Ocean SDK

    Research Methods: quantum annealing, simulated annealing, graph coarsening, quantum circuit synthesis and optimisation

    Achievements

    C-DAC India - Qniverse Developer Certification Exam 2025 (Top 5 performer)

    Nov 2025 | India
  • •Scored 92/​100 in the C‑DAC Qniverse Developer Certification Exam, which assesses practical quantum circuit and algorithm skills similar to those tested in the IBM Qiskit Developer Certification.

    • Joint Admission Test for Masters (JAM) 2022 - Rank 1091 (top 9% of ~12,000 candidates)

    Feb 2022 | India
  • •Qualifying exam for MSc admission at IITs and central universities.

    • Teaching & Outreach

    Quantum Computing Instructor

    Dec 2025 – Present | Online
  • •Certified QBronze instructor; completed a three-stage evaluation process including remote presentation interviews assessed by a QWorld mentor. Delivered a session on quantum entanglement and superdense coding to ~40 engineering students participating in the Africa Quantum Hackathon 2025 (QBronze180, Dec 2025).

    • Quantum Computing Assistant

    Jun 2025 – Aug 2025 | Online
  • •Recognised as one of the best assistants of the program. Supported students with Qiskit installation, algorithm execution, code troubleshooting, assignment hints, and project-related queries. Also served as an assistant in the same program from July to August 2024.

    • Academic Outreach Volunteer

    Feb 2023 | Kochi, India
  • •Delivered career guidance on postgraduate admissions and university entrance examinations to undergraduate and pre-university students at CUSAT, organised by Dr. Anoop K.K. (CUSAT).
    • Training Programs

    IBM Qiskit Global Summer School 2025

    Jul 2025 | Online

    Completed IBM Qiskit Global Summer School 2025 (Advanced): hands-on training in Qiskit: circuit design, Aer simulation, IBM backend execution, noise modelling, and error mitigation.

    Womanium & WISER Quantum Program 2024 & 2025

    Jun 2025 – Aug 2025 | Online

    Completed Womanium & WISER Quantum Program (2024 & 2025): training across quantum computing, quantum machine learning, and quantum hardware tracks.

    Referees

    Position: Founder & CEO, Fundacja Quantum AI (Poland); Chairperson of the Board, QWorld

    Relationship: Research Supervisor

    Position: Assistant Professor at CUSAT (India)

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    Relationship: Course Instructor (Quantum Computation & Information)

    Position: Assistant Professor at CUSAT (India)

    Relationship: Course Instructor (Atomic and Molecular Spectroscopy)

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