Srinivasan Arunachalam

my picture

I am a a Postdoctoral Researcher at the Center for Theoretical Physics at MIT.

I received my PhD from Centrum Wiskunde & Informatica and QuSoft, Amsterdam, Netherlands, supervised by Ronald de Wolf.
Before that I finished my M.Math in Mathematics from University of Waterloo and Institute of Quantum computing, Canada in 2014, supervised by Michele Mosca.

Research interests

Quantum algorithms, Quantum learning theory, Quantum complexity theory, Quantum optimization, Analysis of Boolean functions.

Contact information

Email: arunacha (at) mit (dot) edu.

Address: 6-307, Center of Theoretical Physics, MIT.


Papers

  1. Quantum hardness of learning shallow classical circuits
    Srinivasan Arunachalam, Alex B. Grilo, Aarthi Sundaram
    [arXiv] [ECCC TR19-041]

  2. Two new results about quantum exact learning
    Srinivasan Arunachalam, Sourav Chakraborty, Troy Lee, Ronald de Wolf
    [arXiv]

  3. Improved bounds on Fourier entropy and Min-entropy
    Srinivasan Arunachalam, Sourav Chakraborty, Michal Koucký , Nitin Saurabh , Ronald de Wolf
    [arXiv] [ECCC TR18-167]

  4. Optimizing quantum optimization algorithms via faster quantum gradient computation
    András Gilyén, Srinivasan Arunachalam, Nathan Wiebe
    Proceedings of ACM-SIAM Symposium on Discrete Algorithms (SODA), 2019
    [arXiv] [SODA 2019]

  5. Quantum query algorithms are completely bounded forms
    Srinivasan Arunachalam, Jop Briët, Carlos Palazuelos
    Presented at Innovations in Theoretical Computer Science Conference (ITCS), 2018
    Presented at the 22nd Annual Conference on Quantum Information Processing (QIP 2019)
    To appear in SIAM Journal on Computing
    [arXiv] [ITCS 2018] [SICOMP] [QIP 2019: Video]

  6. A survey of quantum learning theory
    Srinivasan Arunachalam, Ronald de Wolf
    Computational Complexity Column, ACM SIGACT News, Vol. 48, June 2017.
    [arXiv] [SIGACT Column]

  7. Optimal quantum sample complexity of learning algorithms
    Srinivasan Arunachalam, Ronald de Wolf
    Presented at the 20th Annual Conference on Quantum Information Processing (QIP 2017)
    32nd Conference on Computational Complexity (CCC), Vol. 79, 2017
    Journal of Machine Learning Research (JMLR), Vol. 19, 2018
    [arXiv] [CCC 2017] [JMLR] [QIP 2017: Video|Slides]

  8. Optimizing the Number of Gates in Quantum Search
    Srinivasan Arunachalam, Ronald de Wolf
    Quantum Information & Computation, Vol. 17, 2017
    [arXiv] [Quantum Information & Computation]
  9. Quantum hedging in two-round prover-verifier interactions
    Srinivasan Arunachalam, Abel Molina, Vincent Russo
    Proceedings of Theory of Quantum computation, Communication and Cryptography (TQC), 2017
    [arXiv] [TQC 2017]

  10. On the robustness of bucket brigade quantum RAM
    Srinivasan Arunachalam,Vlad Gheorghiu, Tomas Jochym-O’Connor, Michele Mosca, Priyaa Varshini Srinivasan
    Presented at Asian Quantum information science (AQIS), 2015
    Proceedings of Theory of Quantum computation, Communication and Cryptography (TQC), 2015
    New Journal of Physics, Vol. 17, 2015
    [arXiv] [TQC 2015] [New Journal of Physics: Article|Video abstract]
  11. Is absolute separability determined by the partial transpose?
    Srinivasan Arunachalam, Nathaniel Johnston, Vincent Russo
    Quantum Information & Computation, Vol. 15, 2015
    [arXiv] [Quantum Information & Computation]
  12. Some older projects

    Hard satisfiable 3-SAT instances via auto-correlation
    Srinivasan Arunachalam, Ilias Kotsireas
    Journal on Satisfiability, Boolean Modeling & Computation, Vol. 10, 2016
    Proceedings of SAT Competition 2014
    [SAT competition] [Journal version]

    Evaluation of Riemann Zeta function on the Line Re(s) = 1 and Odd Arguments
    Srinivasan Arunachalam
    [arXiv]

    A Substitution to Bernoulli Numbers in easier computation of ζ(2k)
    Srinivasan Arunachalam
    [arXiv]

    Thesis

    Quantum Speed-ups for Boolean Satisfiability and Derivative-Free Optimization.
    Srinivasan Arunachalam
    Master's thesis (2014)
    University of Waterloo. [PDF]

    Quantum algorithms and learning theory.
    Srinivasan Arunachalam
    PhD thesis (2014)
    University of Amsterdam. [PDF]

    External links: Google Scholar, ArXiv