885 citations · 3.5k across the 45 of their papers we have counts for
7 papers · 1 filter
A Note on Convex Relaxations for the Inverse Eigenvalue Problem
Utkan Candogan, Yong Sheng Soh, Venkat Chandrasekaran
The affine inverse eigenvalue problem consists of identifying a real symmetric matrix with a prescribed set of eigenvalues in an affine space. Due to its ubiquity in applications,…
Symmetries, charges and conservation laws at causal diamonds in general relativity
Venkatesa Chandrasekaran, Kartik Prabhu
We study the covariant phase space of vacuum general relativity at the null boundary of causal diamonds. The past and future components of such a null boundary each have an infinit…
Signomial and Polynomial Optimization via Relative Entropy and Partial Dualization
Riley Murray, Venkat Chandrasekaran, Adam Wierman
We describe a generalization of the Sums-of-AM/GM Exponential (SAGE) relaxation methodology for obtaining bounds on constrained signomial and polynomial optimization problems. Our…
Entropy Variations and Light Ray Operators from Replica Defects
Srivatsan Balakrishnan, Venkatesa Chandrasekaran, Thomas Faulkner +2
We study the defect operator product expansion (OPE) of displacement operators in free and interacting conformal field theories using replica methods. We show that as approache…
Ignorance is Cheap: From Black Hole Entropy To Energy-Minimizing States In QFT
Raphael Bousso, Venkatesa Chandrasekaran, Arvin Shahbazi-Moghaddam
Behind certain marginally trapped surfaces one can construct a geometry containing an extremal surface of equal, but not larger area. This construction underlies the Engelhardt-Wal…
Convex Graph Invariant Relaxations For Graph Edit Distance
Utkan Onur Candogan, Venkat Chandrasekaran
The edit distance between two graphs is a widely used measure of similarity that evaluates the smallest number of vertex and edge deletions/insertions required to transform one gra…
Fitting Tractable Convex Sets to Support Function Evaluations
Yong Sheng Soh, Venkat Chandrasekaran
The geometric problem of estimating an unknown compact convex set from evaluations of its support function arises in a range of scientific and engineering applications. Traditional…