Rupak Chatterjee

  • Industry Assistant Professor

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Research Interests
Quantum Information and Computation: Quantum systems for Machine Learning algorithms; Quantum optimization.

Mathematical Physics: C∗ and von Neumann Algebras; Supersymmetric and Conformal Quantum Mechanics; Quantum Gravity.

University of Chicago, Chicago, IL

Postdoctoral Scholar,

Department of Physics, James Franck Institute

Stony Brook University, Stony Brook, NY

Ph.D., Physics

M.S., Physics

University of Waterloo, Waterloo, Canada

M.Math., Mathematics

University of Calgary, Calgary, Canada

B.Sc., Physics


[1] V. Padmasola and R. Chatterjee, Optimization on Large Interconnected Graphs and Networks Using Adiabatic Quantum Computation, International Journal of Quantum Information 21 (06), (2023).

[2] A. Das and R. Chatterjee, Discrete phase space and continuous time relativistic Klein- Gordon and Dirac equations, and a new non-singular Yukawa potential, Sci Rep 13, 20356 (2023).

[3] C.Gallaro and R. Chatterjee, A Modular Operator Approach to Entanglement of Causally Closed Regions, International Journal of Theoretical Physics, 61 (8), (2022).

[4] A. Das and R. Chatterjee, Discrete phase space and continuous time relativistic quantum mechanics II: Peano circles, hyper-tori phase cells, and fibre bundles, Modern Physics Letters, A 36 (35), (2021).

[5] R. Chatterjee and T.Yu, Modular Operators and Entanglement in Supersymmetric Quantum Mechanics, Journal of Physics A: Mathematical and Theoretical 54 (20), (2021).

[6] Q. Ding, R. Chatterjee, Y. Huang, and T. Yu, High-Dimensional Temporal Mode Propagation in a Turbulent Environment, Quantum Information and Computation, 21 (3&4), 233-254 (2021).

[7] S. Tudor, R. Chatterjee, and I. Tydniouk, On a New Parametrization Class of Solvable Diffusion Models and Transition Probability Kernels, Quantitative Finance, 21 (10), 1773-1790 (2021).

[8] A.Das and R. Chatterjee, Discrete phase space and continuous time relativistic quantum mechanics I: Planck oscillators and closed string-like circular orbits, Modern Physics Letters, A 36 (20), (2021).

[9] P. Golbayani, I. Florescu, and R. Chatterjee, A comparative study of forecasting Corporate Credit Ratings using Neural Networks, Support Vector Machines, and Decision Trees, The North American Journal of Economics and Finance 54, 101251, (2020).

[10] A. Das, R. Chatterjee, and T. Yu, Discrete Phase Space, Relativistic Quantum Electrodynamics, and a Non-Singular Coulomb Potential, Modern Physics Letters A 35 (24), (2020).

[11] A. Sarma, R. Chatterjee, K. Gili, and T Yu, Quantum Unsupervised and Supervised Learning on Superconducting Processors, Quantum Information and Computation 20 (7&8), 541-552 (2020).

[12] D.W. Luo, H.Q. Lin, J.Q. You, L.A. Wu, R. Chatterjee, T. Yu, Geometric Decoherence in Diffusive Open Quantum Systems, Phys. Rev. A 100 (6), 062112, (2019).

[13] S. Tudor, R. Chatterjee, L. Nguyen, Y. Huang, Quantum Systems for Monte Carlo Methods and Applications to Fractional Stochastic Processes, Physica A: Statistical Mechanics and its Applications 534, 121901, (2019).

[14] H. Cao, R. Chatterjee, Z. Cui, Options Valuation and Calibration for Leveraged Exchange-Traded Funds with Heston-Nandi and Inverse Gaussian GARCH Models, International Journal of Financial Engineering 6 (03), 1950027, (2019).

[15] E. Alos, R. Chatterjee, S. Tudor, and TH. Wang, Target Volatility Option Pricing in Lognormal Fractional SABR Model, Quantitative Finance, 19 (8), 1339-1356, (2019).

[16] H. Zhao, R. Chatterjee, T. Lonon, I. Florescu, Pricing Bermudan Variance Swaptions Using Multinomial Trees, The Journal of Derivatives, Spring, 26 (3), 22-34 (2019).

[17] R. Chatterjee, Z. Cui, J. Fan, M. Liu, An Efficient and Stable Method for Short Maturity Asian Options, Journal of Futures Markets 38 (12), 1470-1486, (2018).

[18] R. Chatterjee and T. Yu, Generalized Coherent States, Reproducing Kernels, and Quantum Support Vector Machines, Quantum Information and Computation, 17 (15&16), 1292 (2017).

[19] H. Zhao, Z. Zhao, R. Chatterjee, T. Lonon, and I. Florescu, Pricing Variance, Gamma and Corridor Swaps Using Multinomial Trees, Journal of Derivatives, Winter, 25 (2), 7-21 (2017).

[20] A. Petrelli, R. Balachandran, O. Siu, R. Chatterjee, Z. Jun, V. Kapoor, Optimal Dynamic Hedging of Equity Options: Residual-Risks, Transaction-Costs, and Condition- ing, SSRN 1530046 (2010).

[21] J Wang, A Petrelli, R Balachandran, O Siu, J Zhang, R. Chatterjee, V Kapoor, General Auto-Regressive Asset Model, SSRN 1428555 (2009).

[22] A. Petrelli, R. Balachandran, J. Zhang, O. Siu, R. Chatterjee, V Kapoor, Optimal Dynamic Hedging of Multi-Asset Options, SSRN 1358667 (2009).

[23] A. Petrelli, J. Zhang, O. Siu, R. Chatterjee, V Kapoor, Optimal Dynamic Hedging of Cliquets, DefaultRisk.com, May (2008).

[24] R. Chatterjee and L. Takhtajan, Aspects of Classical and Quantum Nambu Mechanics, Letters in Mathematical Physics, 37(4), 475-482 (1996).

[25] R. Chatterjee, Dynamical Symmetries and Nambu Mechanics, Letters in Mathematical Physics, 36(2), 117-126 (1996).

[26] R. Chatterjee and A.D. Jackson, "Surfing Arnold’s Web", Nuclear Physics A 606, 1-2, 27-40 (1996).

[27] R. Chatterjee, A.D. Jackson, and N.L. Balazs, Rigid Body Motion, Interacting Billiards, and Billiards on Curved Manifolds, Phys. Rev. E53, 5670-5679 (1996).

[28] N.L. Balazs, R. Chatterjee, and A.D. Jackson, Coin Tossing as a Billiard Problem, Phys. Rev. E52, 3608-3613 (1995).