activity
20232026
most citedDiagonalization of large many-body Hamiltonians on a quantum processor

23 citations · 27 across the 12 of their papers we have counts for

collaborators

17 papers

quant-ph2026

A note on tomography of states with low stabilizer rank

Arkopal Dutt

In this note, we consider tomography of -qubit quantum states that are promised to have stabilizer rank i.e., admit a stabilizer decomposition of $|ψ\rangle = \s…

cs.CC2026

Marton's conjecture in polynomial time

Srinivasan Arunachalam, Arkopal Dutt, Sabee Grewal +1

Gowers, Green, Manners, and Tao (Annals '25) recently resolved Marton's polynomial Freiman-Ruzsa conjecture. We give an algorithmic counterpart to their result: given uniform sampl…

quant-ph2026

Quantum simulation of non-Markovian dynamical systems

Abtin Ameri, Arkopal Dutt, Hari Krovi

Existing quantum algorithms for simulating dynamical systems -- from Hamiltonian simulation to linear and nonlinear differential equations solvers -- simulate Markovian dynamics, i…

quant-ph2026

Learning Clifford-structured quantum unitaries and Hamiltonians

Arkopal Dutt, Dale Jacobs, John Jeang +2

Learning algorithms for structured quantum unitaries and Hamiltonians have primarily considered classes of processes that are local or sparse in the Pauli basis. We turn our attent…

quant-ph2026

Separating quantum circuits from classical LLMs

Srinivasan Arunachalam, Arkopal Dutt, Hari Krovi +1

Modern large language models - transformers and diffusion language models - are built around two canonical algorithmic tasks: prediction and generation. We prove unconditional sepa…

quant-ph2026

Tomography of quantum states with bounded extent

Srinivasan Arunachalam, Arkopal Dutt

We give a general framework for tomography of states that have bounded-extent with respect to a structured class of states. Let be a family of -qubit states such th…

quant-ph2026

Simulating dynamics of RLC circuits with a quantum differential-algebraic equations solver

Arkopal Dutt, Anirban Chowdhury, Kristan Temme +1

We introduce a quantum algorithm for simulating the dynamics of electrical circuits consisting of resistors, inductors and capacitors (aka RLC circuits) along with power sources. G…

math.CO2026

An algorithmic Polynomial Freiman-Ruzsa theorem

Davi Castro-Silva, Jop Briët, Srinivasan Arunachalam +2

We provide algorithmic versions of the Polynomial Freiman-Ruzsa theorem of Gowers, Green, Manners, and Tao (Ann. of Math., 2025). In particular, we give a polynomial-time algorithm…

quant-ph2025

Learning stabilizer structure of quantum states

Srinivasan Arunachalam, Arkopal Dutt

We consider the task of learning a structured stabilizer decomposition of an arbitrary -qubit quantum state : for , output a state with stabilizer-r…

math.CO2025

Algorithmic Polynomial Freiman-Ruzsa Theorems

Srinivasan Arunachalam, Davi Castro-Silva, Arkopal Dutt +1

We prove algorithmic versions of the polynomial Freiman-Ruzsa theorem of Gowers, Green, Manners, and Tao (Annals of Mathematics, 2025) in additive combinatorics. In particular, we…

quant-ph2025

Learning depth-3 circuits via quantum agnostic boosting

Srinivasan Arunachalam, Arkopal Dutt, Alexandru Gheorghiu +1

We initiate the study of quantum agnostic learning of phase states with respect to a function class : given copies of an unk…

quant-ph2024

Testing and learning structured quantum Hamiltonians

Srinivasan Arunachalam, Arkopal Dutt, Francisco Escudero Gutiérrez

We consider the problems of testing and learning an unknown -qubit Hamiltonian from queries to its evolution operator under the normalized Frobenius norm. We prov…

quant-ph2024

A note on polynomial-time tolerant testing stabilizer states

Srinivasan Arunachalam, Sergey Bravyi, Arkopal Dutt

We show an improved inverse theorem for the Gowers- norm of -qubit quantum states which states that: for every , if the $\textsf{Gowers}(|ψ\rangle,3)^8 \…

quant-ph2024

Polynomial-time tolerant testing stabilizer states

Srinivasan Arunachalam, Arkopal Dutt

We consider the following task: suppose an algorithm is given copies of an unknown -qubit quantum state promised is -close to a stab…

quant-ph2024★ 23 cited

Diagonalization of large many-body Hamiltonians on a quantum processor

Nobuyuki Yoshioka, Mirko Amico, William Kirby +16

The estimation of low energies of many-body systems is a cornerstone of computational quantum sciences. Variational quantum algorithms can be used to prepare ground states on pre-f…

quant-ph2024

Learning low-degree quantum objects

Srinivasan Arunachalam, Arkopal Dutt, Francisco Escudero Gutiérrez +1

We consider the problem of learning low-degree quantum objects up to -error in -distance. We show the following results: unknown -qubit degree- (in…

quant-ph2023★ 4 cited

Practical Benchmarking of Randomized Measurement Methods for Quantum Chemistry Hamiltonians

Arkopal Dutt, William Kirby, Rudy Raymond +4

Many hybrid quantum-classical algorithms for the application of ground state energy estimation in quantum chemistry involve estimating the expectation value of a molecular Hamilton…