Dear Colleagues, We are pleased to invite you to the following SPASS seminar <https://sites.google.com/unipi.it/spass/seminars?authuser=0> (jointly organised by UniPi, SNS, UniFi and UniSi): _Speaker_: *Francesco Russo* (ENSTA Paris, Institut Polytechnique de Paris) _Title_: *Exponential twist of probability measures: drift correction in term of a generalized gradient* _Date and time_: *Tue, September 15th* at *14:00 CET* _Place_: Aula Mancini, Palazzo della Carovana, Scuola Normale Superiore, Pisa On behalf of the organisers, Lorenzo Marino ********************* _Abstract_: \This talk will concern the exponential twist, i.e. a path-integral exponential change of measure, of a Markovian reference probability measure P. This type of transformation naturally appears in variational representation formulae originating from the theory of large deviations and can be interpreted in some cases, as the solution of a specific stochastic control problem. Under a very general Markovian assumption on P, we fully characterize the exponential twist probability measure as the solution of a martingale problem and prove that it inherits the Markov property of the reference measure. The ”generator” of the martingale problem shows a drift depending on a generalized gradient of some suitable value function v. Applications of this work refer to an entropy minimization algorithm, see e.g. [1] and [2].\ \This work is based on a collaboration with Th. Bourdais (ENSTA and Mazars), and N. Oudjane (EDF). It is the object of [3].\ *References* [1] T. Bourdais, N. Oudjane, and F. Russo. An entropy penalized approach for stochastic control problem. Complete Version. Preprint HAL-04193113 v3, 2025. [2] T. Bourdais, N. Oudjane, and F. Russo. An entropy penalized approach for stochastic control problem. SIAM Journal on Control and Optimization (SICON), 64 (1):363–386, 2026. [3] T. Bourdais, N. Oudjane, and F. Russo. Exponential twist of probability measures: drift correction in term of a generalized gradient. Stochastic Processes Appl., 201:28, 2026. Id/No 105064.