23 citations · 27 across the 12 of their papers we have counts for
14 papers · 1 filter
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…
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…
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…
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…
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…
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…
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…
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…
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…
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 \…
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…
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…
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…
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…