activity
20082026
most citedNonperturbative renormalization-group approach to strongly-correlated lattice bosons

62 citations · 672 across the 47 of their papers we have counts for

collaborators

47 papers

cond-mat.quant-gas2026

Universal scaling of fluctuations and correlations across the superfluid transition

Paul Paquiez, Géraud Dupuy, Maxime Allemand +6

The critical behavior of a system near a continuous phase transition is commonly characterized by power laws and a set of universal critical exponents. Yet universality at phase tr…

quant-ph2025

Bidimensional measurements of photon statistics within a multimodal temporal framework

C. Hainaut, K. Ouahrouche, A. Rancon +5

Ultrafast imaging of photon statistics in two dimensions is a powerful tool for probing non-equilibrium and transient optical phenomena, yet it remains experimentally challenging d…

cond-mat.stat-mech2025★ 1 cited

Constraint correlation functions of the one-dimensional Ising model in the scaling limit

Ivan Balog, Adam Rançon

We study the correlation function of the one-dimensional Ising model at fixed magnetization. Focusing on the scaling limit close to the zero-temperature fixed point, we show that t…

cond-mat.stat-mech2025★ 1 cited

Constraint effective action and critical correlation functions at fixed magnetization

Félix Rose, Adam Rançon, Ivan Balog

We present an extension of the functional renormalization group (FRG) framework developed to compute critical probability distributions of the order parameter to momentum-dependent…

cond-mat.quant-gas2025

Observation of universal non-Gaussian statistics of the order parameter across a continuous phase transition

Maxime Allemand, Géraud Dupuy, Paul Paquiez +5

Second-order phase transitions are characterised by critical scaling and universality. The singular behaviour of thermodynamic quantities at the transition, in particular, is deter…

cond-mat.stat-mech2025★ 1 cited

Dreaming up scale invariance via inverse renormalization group

Adam Rançon, Ulysse Rançon, Tomislav Ivek +1

We explore how minimal neural networks can invert the renormalization group (RG) coarse-graining procedure in the two-dimensional Ising model, effectively ``dreaming up'' microscop…