UMR 5672

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Condensed matter
D. Carpentier, P. Degiovanni, P. Delplace, A. Fedorenko, P. Holdsworth, F. Mezzacapo, E. Orignac, T. Roscilde, L. Savary, E. Brillaux (PhD student), C. Cabart (PhD student), R. Menu (PhD student), J. Thibaut(PhD student), L.K. Upreti (PhD student),F. Zouari Ahmed (PhD student)
Located in Teams / Theoretical Physics / Research Topics
Mathematical physics
A. Alastuey, J. Bouttier, F. Delduc, K. Gawedzki, M. Geiller, K. K. Kozlowski, G. Niccoli, E. Livine, M. Magro, J. M. Maillet, H. Samtleben, K. Takashi (Postdoc), A. Baguet (PhD student), C. Goeller (PhD student), S. Lacroix (PhD student), B. Pezelier (PhD student)
Located in Teams / Theoretical Physics / Research Topics
Statistical physics
A. Alastuey, A.A. Fedorenko, P. Holdsworth, R. Raban (PhD student)
Located in Teams / Theoretical Physics / Research Topics
Optimization and inverse problems
The group has recently developed an activity focused on the resolution of inverse problems and optimisation. The inverse problems we consider can be split in three topics : - Image restoration - Non-stationarity and optimisation - Change-point detection and segmentation for regularity estimation
Located in Teams / SIgnals, SYstems & PHysics / Research Topics
Biomedical image and signal processing
SiSyPh research team is putting significant efforts into developing signal/image processing tools for biomedical applications. On the image processing side, an efficient reconstruction procedure mixing on non-smooth convex optimization to balance data fidelity and regularization provides an efficient reconstruction procedure for high resolution image from low resolution records. On the signal processing side, statistical tools are customized to analyze scale invariance in heart rate variability (notably in the context of intrapartum fetal heart beat analysis) as well as in infraslow brain activity. It notably permits to relate scale invariance in background brain activity to functional connectivity and to quantify task-rest modulation of brain scaling.
Located in Teams / SIgnals, SYstems & PHysics / Research Topics
Fluctuation theorems and thermal noise
In out of equilibrium or mesoscopic systems, fluctuations play an important role and provide a unique tool to probe the underlying physics. Our team develops various experiments to measure directly this noise and test statistical physics approaches : fluctuations theorems, nano-mechanics, confined phase transitions…
Located in Teams / Non Linear Physics & Hydrodynamics / Research Topics
Nonstationary signal processing
The group has a strong history of studying nonstationary signal processing, ranging from theoretical analalysis or development of approaches such as time-frequency methods, data-driven decompositions (e.g., Empirical Mode Decomposition), practical characterization of stationarity and non-stationarity. Many applications of these methods have been put forward as well by the group.
Located in Teams / SIgnals, SYstems & PHysics / Research Topics
Scale invariance, multifractals and wavelets
Scale invariance analysis and modeling has been a long standing research topic within SiSyPh team. Significant efforts have been and still are devoted to the definition, design and practical synthesis of stochastic processes with prescribed scaling properties, combined either to other statistic properties (distributions, dependencies) or to geometrical properties (free divergence, prescribed curl,...) to match a given application field (mainly hydrodynamic turbulence). Statistical signal processing tools are also designed and studied theoretically and practically, aiming to test the existence of scale invariance, to estimate scaling parameters or the scaling range bounds. The recent focus is on multivariate signals, and multidimensional fields with possible anisotropy.
Located in Teams / SIgnals, SYstems & PHysics / Research Topics
Graph signals and complex networks
Data appear often with a mixture or relational properties –coded by graphs or networks–, and attributes —naturally dealt as signals (possibly multivariate signals). An activity of the group is to study signal an ddata processing for these types of data, both for graph signals (when a signal is indexed by a graph) and for complex networks where the signal of interest is the network itself. In both cases, the group has a specific interest in networks which are dynamic, or for which a multiscale approach is fruitful.
Located in Teams / SIgnals, SYstems & PHysics / Research Topics
Biological and genomic signals and images
Located in Teams / SIgnals, SYstems & PHysics / Research Topics