Renaud Raquépas, Phillip Griffiths Assistant Research Professor

More information on renaudraquepas.github.io.

Contact Info:

Office Location:
Office Phone:	(919) 660-2800
Email Address:
Web Page:	https://renaudraquepas.github.io/

Teaching (Spring 2026):

• MATH 230.01, PROBABILITY Synopsis

  Physics 154, TuTh 08:30 AM-09:45 AM

  (also cross-listed as STA 230.01)

• MATH 451S.01, NONLINEAR DYNAMICS AND CHAOS Synopsis

  Physics 047, TuTh 10:05 AM-11:20 AM

• MATH 730.01, PROBABILITY Synopsis

  Physics 154, TuTh 08:30 AM-09:45 AM

• MATH 751S.01, NONLIN ORD DIFF EQUA Synopsis

  Physics 047, TuTh 10:05 AM-11:20 AM

Education:

Ph.D.

McGill University (Canada)

2021

Keywords:

Classical equilibrium statistical mechanics (general) • Dynamical systems in statistical mechanics • Equilibrium statistical mechanics • General mathematical topics and methods in quantum theory • Large deviations • One-parameter semigroups and linear evolution equations • Probability theory and stochastic processes • Quantum dynamics and nonequilibrium statistical mechanics (general) • Time-dependent statistical mechanics (dynamic and nonequilibrium)

Recent Publications   (More Publications)

1. Barnfield, N; Grondin, R; Pozzoli, G; Raquépas, R, On the Ziv–Merhav theorem beyond Markovianity I, Canadian Journal of Mathematics, vol. 77 no. 3 (June, 2025), pp. 891-915 [doi]  [abs]
2. Raquépas, R; Schenker, J, Quenched Large Deviations of Birkhoff Sums Along Random Quantum Measurements, Annales Henri Poincare (January, 2025) [doi]  [abs]
3. Cuneo, N; Raquépas, R, Large Deviations of Return Times and Related Entropy Estimators on Shift Spaces, Communications in Mathematical Physics, vol. 405 no. 6 (June, 2024) [doi]  [abs]
4. Raquépas, R, The large-time and vanishing-noise limits for entropy production in nondegenerate diffusions, Annales De L Institut Henri Poincare B Probability and Statistics, vol. 60 no. 1 (February, 2024), pp. 431-462 [doi]  [abs]
5. Barnfield, N; Grondin, R; Pozzoli, G; Raquepas, R, Ziv-Merhav Estimation for Hidden-Markov Processes, IEEE International Symposium on Information Theory Proceedings (January, 2024), pp. 3606-3611 [doi]  [abs]