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Related papers: Simple algorithms to test and learn local Hamilton…

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We consider the problems of testing and learning an unknown $n$-qubit Hamiltonian $H$ from queries to its evolution operator $e^{-iHt}$ under the normalized Frobenius norm. We prove: 1. Local Hamiltonians: We give a tolerant testing…

Quantum Physics · Physics 2025-06-09 Srinivasan Arunachalam , Arkopal Dutt , Francisco Escudero Gutiérrez

In this work, we study the problems of certifying and learning quantum $k$-local Hamiltonians, for a constant $k$. Our main contributions are as follows: - Certification of Hamiltonians. We show that certifying a local Hamiltonian in…

The (tolerant) Hamiltonian locality testing problem, introduced in [Bluhm, Caro,Oufkir `24], is to determine whether a Hamiltonian $H$ is $\varepsilon_1$-close to being $k$-local (i.e. can be written as the sum of weight-$k$ Pauli…

Quantum Physics · Physics 2025-05-13 John Kallaugher , Daniel Liang

We formalize and study the Hamiltonian certification problem. Given access to $e^{-\mathrm{i} Ht}$ for an unknown Hamiltonian $H$, the goal of the problem is to determine whether $H$ is $\varepsilon_1$-close to or $\varepsilon_2$-far from a…

Quantum Physics · Physics 2026-05-07 Minbo Gao , Zhengfeng Ji , Qisheng Wang , Wenjun Yu , Qi Zhao

We study the problem of learning a $k$-body Hamiltonian with $M$ unknown Pauli terms that are not necessarily geometrically local. We propose a protocol that learns the Hamiltonian to precision $\epsilon$ with total evolution time…

Quantum Physics · Physics 2024-12-13 Muzhou Ma , Steven T. Flammia , John Preskill , Yu Tong

In this work, we study the problems of certifying and learning quantum Ising Hamiltonians. Our main contributions are as follows: Certification of Ising Hamiltonians. We show that certifying an Ising Hamiltonian in normalized Frobenius norm…

Locality is a fundamental feature of many physical time evolutions. Assumptions on locality and related structural properties also underlie recently proposed procedures for learning an unknown Hamiltonian from access to the induced time…

Quantum Physics · Physics 2026-01-21 Andreas Bluhm , Matthias C. Caro , Aadil Oufkir

Learning about a Hamiltonian $H$ from its time evolution $e^{-iHt}$ is a fundamental task in quantum science. A flurry of recent work has developed powerful new algorithms with provable guarantees for this task, for a variety of natural…

Quantum Physics · Physics 2026-04-20 Ziyun Chen , Jerry Li , Joseph Slote

Learning the Hamiltonian underlying a quantum many-body system in thermal equilibrium is a fundamental task in quantum learning theory and experimental sciences. To learn the Gibbs state of local Hamiltonians at any inverse temperature…

Quantum Physics · Physics 2025-04-04 Chi-Fang Chen , Anurag Anshu , Quynh T. Nguyen

We study the problem of learning Hamiltonians $H$ that are $s$-sparse in the Pauli basis, given access to their time evolution. Although Hamiltonian learning has been extensively investigated, two issues recur in much of the existing…

We consider the problem of learning local quantum Hamiltonians given copies of their Gibbs state at a known inverse temperature, following Haah et al. [2108.04842] and Bakshi et al. [arXiv:2310.02243]. Our main technical contribution is a…

Quantum Physics · Physics 2024-02-09 Ales Wodecki , Jakub Marecek

The k-local Hamiltonian problem is a natural complete problem for the complexity class QMA, the quantum analog of NP. It is similar in spirit to MAX-k-SAT, which is NP-complete for k<=2. It was known that the problem is QMA-complete for any…

Quantum Physics · Physics 2007-05-23 Julia Kempe , Alexei Kitaev , Oded Regev

We study the problem of learning a Hamiltonian $H$ to precision $\varepsilon$, supposing we are given copies of its Gibbs state $\rho=\exp(-\beta H)/\operatorname{Tr}(\exp(-\beta H))$ at a known inverse temperature $\beta$. Anshu,…

Quantum Physics · Physics 2025-10-14 Jeongwan Haah , Robin Kothari , Ewin Tang

This work proposes a protocol for Fermionic Hamiltonian learning. For the Hubbard model defined on a bounded-degree graph, the Heisenberg-limited scaling is achieved while allowing for state preparation and measurement errors. To achieve…

Quantum Physics · Physics 2024-05-03 Hongkang Ni , Haoya Li , Lexing Ying

Hamiltonian learning protocols are essential tools to benchmark quantum computers and simulators. Yet rigorous methods for time-dependent Hamiltonians and Lindbladians remain scarce despite their wide use. We close this gap by learning the…

Quantum Physics · Physics 2025-10-10 Daniel Stilck França , Tim Möbus , Cambyse Rouzé , Albert H. Werner

Hamiltonian learning is an important procedure in quantum system identification, calibration, and successful operation of quantum computers. Through queries to the quantum system, this procedure seeks to obtain the parameters of a given…

Quantum Physics · Physics 2023-08-25 Arkopal Dutt , Edwin Pednault , Chai Wah Wu , Sarah Sheldon , John Smolin , Lev Bishop , Isaac L. Chuang

With the fast development of quantum technology, the sizes of both digital and analog quantum systems increase drastically. In order to have better control and understanding of the quantum hardware, an important task is to characterize the…

Quantum Physics · Physics 2023-07-05 Wenjun Yu , Jinzhao Sun , Zeyao Han , Xiao Yuan

We study the problem of learning a local quantum Hamiltonian $H$ given copies of its Gibbs state $\rho = e^{-\beta H}/\textrm{tr}(e^{-\beta H})$ at a known inverse temperature $\beta>0$. Anshu, Arunachalam, Kuwahara, and Soleimanifar…

Quantum Physics · Physics 2026-05-11 Ainesh Bakshi , Allen Liu , Ankur Moitra , Ewin Tang

We consider the problem of learning the Hamiltonian of a quantum system from estimates of Gibbs-state expectation values. Various methods for achieving this task were proposed recently, both from a practical and theoretical point of view.…

Quantum Physics · Physics 2024-10-31 Adam Artymowicz , Hamza Fawzi , Omar Fawzi , Samuel O. Scalet

Efficiently learning an unknown Hamiltonian given access to its dynamics is a problem of interest for quantum metrology, many-body physics and machine learning. A fundamental question is whether learning can be performed at the Heisenberg…

Quantum Physics · Physics 2025-01-03 Arjun Mirani , Patrick Hayden
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