collaborators

5 papers

quant-ph2026

Trading Imaginary Time for Randomness in Ground State Preparation

Alvan Arulandu, John M. Martyn, Isaac L. Chuang

Imaginary-time evolution (ITE) is a foundational method for ground state preparation on quantum computers. However, because ITE is non-unitary, existing implementations incur a sam…

quant-ph2026

Resolving the Edge of a Quantum Pyramid

Alvan Arulandu

Standing on the shoulders of giants, we resolve the quantum pyramids conjecture, confirming the globally information-optimal measurement for an ensemble of equiangular equiprobable…

quant-ph2026

Agnostic Product Mixed State Tomography via Robust Statistics

Alvan Arulandu, Ilias Diakonikolas, Daniel Kane +1

We study the complexity of two closely related learning problems, one quantum and one classical. In the quantum setting, we consider agnostic tomography for the natural class of pr…

math.AT2026

Through the Grapevine: Vineyard Distance as a Measure of Topological Dissimilarity

Alvan Arulandu, Daniel Gottschalk, Thomas Payne +2

We introduce a new measure of distance between datasets, based on vineyards from topological data analysis, which we call the vineyard distance. Vineyard distance measures the exte…

cs.LG2025

Position: Model Collapse Does Not Mean What You Think

Rylan Schaeffer, Joshua Kazdan, Alvan Caleb Arulandu +1

The proliferation of AI-generated content online has fueled concerns over \emph{model collapse}, a degradation in future generative models' performance when trained on synthetic da…