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Department of Computer Science and Technology

  • Research Fellow

I am a Postdoctoral Research Fellow in the Department of Computer Science and Technology at the University of Cambridge. I work closely with Prof. Tom Gur and Dr. Sergii Strelchuk in the Algorithms and Complexity theme.

I recently obtained my PhD in Applied Mathematics (Quantum Information) from the University of Waterloo, Canada. I was supervised by Prof. Joseph Emerson and was a part of the Institute for Quantum Computing. My thesis can be found here.

Research

  • Quantum computing
  • Classical and quantum error correction
  • Quantum error characterization

In particular, my research focuses on assessing and reducing the resource requirements for quantum fault-tolerance schemes.

Teaching

I supervised Computer Science Part II Quantum Computing course in Lent 2024.

I lectured the Applied Linear Algebra I course at the University of Waterloo during Spring 2022. The course had over a hundred undergraduate students and was taught completely online.
Topics : Systems of linear equations, Matrix algebra, Determinants, Introduction to vector spaces, Applications.

I am fortunate to co-supervise Debankan Sannamoth, who is a Master's student at the University of Waterloo working with Prof. Joseph Emerson.

Professional Activities

Publications

Enhancing Quantum Error Correction with Partial Noise Characterization
Pavithran Iyer, Aditya Jain, Stephen D. Bartlett, and Joseph Emerson
Accepted for a talk at QCMC 2024 - July 2024

Improved quantum error correction with randomized compiling
Aditya Jain, Pavithran Iyer, Stephen D. Bartlett, and Joseph Emerson
Phys. Rev. Research 5, 033049 – Published 25 July 2023

Efficient diagnostics for quantum error correction
Pavithran Iyer*, Aditya Jain*, Stephen D Bartlett, and Joseph Emerson
Phys. Rev. Research 4, 043218 – Published 27 December 2022

Asymmetric broadcasting of quantum correlations
Aditya Jain, Indranil Chakrabarty, and Sourav Chatterjee
Phys. Rev. A 99, 022315 – Published 13 February 2019

How local is the information in tensor networks of matrix product states or projected entangled pairs states
Anurag Anshu, Itai Arad, and Aditya Jain
Phys. Rev. B 94, 195143 – Published 28 November 2016

Contact Details

Room: 
FC15
Email: 

aj722@cam.ac.uk