A gas of Brownian particles whose collective reset is triggered by a first-passage event — the first one to reach a threshold drags the others back. Correlations, stationary density, and extreme-value statistics in this first-passage-coupled setting.
Dynamically emergent correlations in Brownian particles subject to simultaneous non-Poissonian resetting protocols
Gabriele de Mauro, Marco Biroli, Satya N. Majumdar, Grégory Schehr
Physical Review E 113, 014120
Generalizes the correlated Brownian gas to non-Poissonian resetting protocols — deterministic, power-law, heavy-tailed. The shape of the inter-reset distribution reshapes the correlation structure.
Discovering and decoding latent mean-field structure with variational autoencoders
Marco Biroli, Max Welling, Vincenzo Vitelli
arXiv preprint
A capacity bound — latent channel rate against the data's bipartite mutual information — shows that any successful VAE decoder is structurally a finite-size mean-field factorization, so its microscopic parameters can be read off the trained network. Validated on Curie–Weiss, Hopfield and Maier–Saupe models, and on salamander retinal recordings, where two latents suffice to recover the stored patterns of the neural population.
Experimental evidence for strong emergent correlations between particles in a switching trap
Marco Biroli, Sergio Ciliberto, Manas Kulkarni, Satya N. Majumdar, Artyom Petrosyan, Grégory Schehr
arXiv preprint
An optical-tweezers experiment that directly measures the emergent correlations predicted for particles in a stochastically switching trap — the first experimental realization of the mechanism.
Dyson Brownian motion of N eigenvalues, reset simultaneously. Stationary density, extreme-eigenvalue statistics, and the crossover between resetting-dominated and repulsion-dominated regimes.
A unified review of the strongly-correlated stochastic systems that motivated the papers above: resetting as a correlation-generating mechanism, exactly solvable gas models, extreme and order statistics in the correlated regime.
Exact extreme, order, and sum statistics in a class of strongly correlated systems
Marco Biroli, Hernán Larralde, Satya N. Majumdar, Grégory Schehr
Physical Review E 109, 014101
A class of strongly correlated systems where the joint distribution factorizes after conditioning on a single random variable — enabling closed-form extreme, order, and sum statistics.
Resetting by rescaling: exact results for a diffusing particle in one dimension
Marco Biroli, Yannick Feld, Alexander K. Hartmann, Satya N. Majumdar, Grégory Schehr
Physical Review E 110, 044142
A diffusing particle whose position is rescaled (rather than reset to the origin) at Poisson events. Exact stationary distribution and large-deviation tails, with numerical checks.
Dynamically emergent correlations between particles in a switching harmonic trap
Marco Biroli, Manas Kulkarni, Satya N. Majumdar, Grégory Schehr
Physical Review E 109, L032106
Non-interacting particles in a harmonic trap whose stiffness switches stochastically develop non-trivial correlations purely from the shared environmental noise.
Critical number of walkers for diffusive search processes with resetting
Marco Biroli, Satya N. Majumdar, Grégory Schehr
Physical Review E 107, 064141
For N searchers independently diffusing with resetting, the mean first-passage time to a target has a non-monotonic dependence on N — we characterize the critical number of walkers below which a single fast walker beats the crowd.
Extreme statistics and spacing distribution in a Brownian gas correlated by resetting
Marco Biroli, Hernán Larralde, Satya N. Majumdar, Grégory Schehr
Physical Review Letters 130, 207101
N Brownian particles on a line, each simultaneously reset to the origin at rate r. The shared resetting event alone correlates otherwise-independent particles; we derive the resulting order-statistics and spacing distributions in closed form.
Time, privacy, robustness, accuracy: trade-offs for the open vote network protocol
Fatima-Ezzahra El Orche, Rémi Géraud-Stewart, Peter B. Rønne, Gergei Bana, David Naccache, Peter YA Ryan, Marco Biroli, Megi Dervishi, Hugo Waltsburger
E-Vote-ID 2022 (LNCS 13553)
A cryptography / e-voting paper from an earlier collaboration: analysis of the open vote network protocol along the axes of time, privacy, robustness, and accuracy.