A new variance transfer principle proves 2D Coulomb gases are 2-hyperuniform and 3D ones are 1-hyperuniform while giving optimal perimeter-like number variance for Girko matrix eigenvalues on microscopic and some mesoscopic scales.
[Ser23] S
8 Pith papers cite this work. Polarity classification is still indexing.
8
Pith papers citing it
citation-role summary
background 1
citation-polarity summary
verdicts
UNVERDICTED 8roles
background 1polarities
background 1representative citing papers
Establishes large deviation principle with speed n² for the normalized count of points in bounded set U for finite β-ensembles on R and C under suitable boundary conditions on U.
Derives explicit formulas for mixed spectral moments of complex and symplectic non-Hermitian random matrices in terms of orthogonal polynomial norms, with large-N asymptotics matching elliptic and non-Hermitian Marchenko-Pastur laws.
Develops an RDT-based LDP framework for spectral edges of Wishart and Wigner matrices matching prior Coulomb gas results.
Derives explicit free energy expansion including constant term for determinantal Coulomb gases in quadratic fields with point charge, equating the constant to the Liouville action associated with the droplet.
Establishes entropy-cost inequalities for McKean-Vlasov SDEs with singular interactions to prove well-posedness and regularity estimates via a new probability distance induced by local integrable functions.
Under relative scalings lim ε log(1/δ)=0 and stricter variants, the authors establish LLN, LDP, and CLT for an additive-noise model approximating fluctuating chemotactic particle hydrodynamics in distribution and function spaces via singular SPDE techniques.
Turbulent dissipation is represented as a Gaussian Multiplicative Chaos and extended to a spatio-temporal model, with properties checked against public DNS of Navier–Stokes.
citing papers explorer
-
From smooth to discontinuous kernels: a variance transfer principle for hyperuniform processes
A new variance transfer principle proves 2D Coulomb gases are 2-hyperuniform and 3D ones are 1-hyperuniform while giving optimal perimeter-like number variance for Girko matrix eigenvalues on microscopic and some mesoscopic scales.
-
Large deviations of crowding in finite $\beta$-ensembles
Establishes large deviation principle with speed n² for the normalized count of points in bounded set U for finite β-ensembles on R and C under suitable boundary conditions on U.
-
Spectral moments of complex and symplectic non-Hermitian random matrices
Derives explicit formulas for mixed spectral moments of complex and symplectic non-Hermitian random matrices in terms of orthogonal polynomial norms, with large-N asymptotics matching elliptic and non-Hermitian Marchenko-Pastur laws.
-
An RDT based approach to large deviations of Wishart and Wigner matrices spectral edges
Develops an RDT-based LDP framework for spectral edges of Wishart and Wigner matrices matching prior Coulomb gas results.
-
Free energy expansion of determinantal Coulomb gases in the quadratic fields with a point charge
Derives explicit free energy expansion including constant term for determinantal Coulomb gases in quadratic fields with point charge, equating the constant to the Liouville action associated with the droplet.
-
Entropy-Cost Inequalities for McKean-Vlasov SDEs with Singular Interactions
Establishes entropy-cost inequalities for McKean-Vlasov SDEs with singular interactions to prove well-posedness and regularity estimates via a new probability distance induced by local integrable functions.
-
An Additive-Noise Approximation to Keller-Segel-Dean-Kawasaki Dynamics: Small-Noise Results
Under relative scalings lim ε log(1/δ)=0 and stricter variants, the authors establish LLN, LDP, and CLT for an additive-noise model approximating fluctuating chemotactic particle hydrodynamics in distribution and function spaces via singular SPDE techniques.
-
The spatio-temporal statistical structure of the turbulent dissipation field and its stochastic representation as a Gaussian Multiplicative Chaos
Turbulent dissipation is represented as a Gaussian Multiplicative Chaos and extended to a spatio-temporal model, with properties checked against public DNS of Navier–Stokes.