bio  website  math.kth.se/~ahardy 

location  Sweden  
age  30  
visits  member for  3 years, 11 months 
seen  18 hours ago  
stats  profile views  997 
Since September 2013, I am a postdoctoral researcher at the Royal Institute of Technology (KTH), mainly working in random matrix theory.
I obtained my PhD degree from KU Leuven (Belgium, with Arno Kuijlaars) jointly with the University of Toulouse (France, with Michel Ledoux).
2d

revised 
Positivity of the Coulomb energy in two dimensions
"potentialtheory" tags is added 
2d

suggested  approved edit on Positivity of the Coulomb energy in two dimensions 
Apr 9 
awarded  Yearling 
Feb 23 
awarded  Revival 
Feb 15 
comment 
Most harmful heuristic?
Yes, and certainly because of that I remember to be shocked when I realized that a map like $x^2 \boldsymbol{1}_{\mathbb Q}(x)$ is continuous (with all derivatives continuous!) at zero. 
Jan 12 
comment 
Simple Spectrum of Jacobi matrices
Because the spectrum of an nxn truncation of a Jacobi matrix has for eigenvalues the zeroes of a degree n orthogonal polynomial, read the literature on OPs. 
Dec 3 
comment 
Geometric interpretation of the average of two independent Cauchy distributions
Can you precise what you mean by "average" ? 
Dec 2 
comment 
rigidity of eigenvalues of circular ensemble
@JohnJiang You're the welcome. I don't know what you have in mind, but I think this type of questions is interesting and I'd be glad to discuss more about it; please write to me at ahardy(you know what)kth.se 
Nov 29 
answered  rigidity of eigenvalues of circular ensemble 
Nov 22 
answered  Positivity of the Coulomb energy in two dimensions 
Jul 2 
awarded  Curious 
May 8 
answered  Characteristic polynomials of certain random symmetric matrices and the complexity of random Morse functions 
May 1 
awarded  Popular Question 
Apr 29 
awarded  Popular Question 
Apr 1 
answered  When should we expect TracyWidom ? 
Feb 12 
answered  Markovtype functions 
Dec 21 
answered  Usage of complex moments in complex plane 
Nov 20 
awarded  Autobiographer 
Nov 16 
comment 
Statistical models in terms of families of random variables
I'm kind of lost: as Michael Greinecker recalled, you can always build a huge probability space in which all your variables live, whatever $\Theta$ is, thanks to the tensor product construction. Then, maybe the "natural" topology you look for just the convergence in distribution of random variables ? In this case, that $x:\Theta\rightarrow L$ is continuous is by definition equivalent to $P:\Theta\rightarrow \Delta(X)$ continuous. But maybe I misunderstood the question. 
Jun 25 
awarded  Promoter 