Cover Image

Structure learning of Hamiltonians from real-time evolution

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Bakshi, Ainesh, Liu, Allen, Moitra, Ankur, Tang, Ewin
Format:	Preprint
Published:	2024
Subjects:	Quantum Physics Data Structures and Algorithms Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Learning quantum Hamiltonians at any temperature in polynomial time
by: Bakshi, Ainesh, et al.
Published: (2023)

A Dobrushin condition for quantum Markov chains: Rapid mixing and conditional mutual information at high temperature
by: Bakshi, Ainesh, et al.
Published: (2025)

High-Temperature Gibbs States are Unentangled and Efficiently Preparable
by: Bakshi, Ainesh, et al.
Published: (2024)

An Improved Classical Singular Value Transformation for Quantum Machine Learning
by: Bakshi, Ainesh, et al.
Published: (2023)

Optimal learning of quantum Hamiltonians from high-temperature Gibbs states
by: Haah, Jeongwan, et al.
Published: (2021)

Rapid mixing for high-temperature Gibbs states with arbitrary external fields
by: Bakshi, Ainesh, et al.
Published: (2026)

Do you know what q-means?
by: Cornelissen, Arjan, et al.
Published: (2023)

Model Stealing for Any Low-Rank Language Model
by: Liu, Allen, et al.
Published: (2024)

Sharp Bounds on the Eigenvalues of Kikuchi Graphs and Applications to Quantum Max Cut
by: Bakshi, Ainesh, et al.
Published: (2026)

Better Models and Algorithms for Learning Ising Models from Dynamics
by: Gaitonde, Jason, et al.
Published: (2025)

Bypassing the Noisy Parity Barrier: Learning Higher-Order Markov Random Fields from Dynamics
by: Gaitonde, Jason, et al.
Published: (2024)

Efficient Certificates of Anti-Concentration Beyond Gaussians
by: Bakshi, Ainesh, et al.
Published: (2024)

Improved algorithms for learning quantum Hamiltonians, via flat polynomials
by: Narayanan, Shyam
Published: (2024)

The tractability landscape of diffusion alignment: regularization, rewards, and computational primitives
by: Moitra, Ankur, et al.
Published: (2026)

Steering diffusion models with quadratic rewards: a fine-grained analysis
by: Moitra, Ankur, et al.
Published: (2026)

Overcomplete Tensor Decomposition via Koszul-Young Flattenings
by: Kothari, Pravesh K., et al.
Published: (2024)

Sample-Optimal Private Regression in Polynomial Time
by: Anderson, Prashanti, et al.
Published: (2025)

Metric Embeddings Beyond Bi-Lipschitz Distortion via Sherali-Adams
by: Bakshi, Ainesh, et al.
Published: (2023)

Amplitude amplification and estimation require inverses
by: Tang, Ewin, et al.
Published: (2025)

Are controlled unitaries helpful?
by: Tang, Ewin, et al.
Published: (2025)

Learning $\mathsf{AC}^0$ Under Graphical Models
by: Chandrasekaran, Gautam, et al.
Published: (2026)

Learning the structure of any Hamiltonian from minimal assumptions
by: Zhao, Andrew
Published: (2024)

Query-optimal estimation of unitary channels in diamond distance
by: Haah, Jeongwan, et al.
Published: (2023)

Learning $k$-body Hamiltonians via compressed sensing
by: Ma, Muzhou, et al.
Published: (2024)

Conjugate queries can help
by: Tang, Ewin, et al.
Published: (2025)

Efficient learning of bosonic Gaussian unitaries
by: Fanizza, Marco, et al.
Published: (2025)

Heisenberg-limited Hamiltonian learning without short-time control
by: Shin, Myeongjin, et al.
Published: (2026)

Beating full state tomography for unentangled spectrum estimation
by: Pelecanos, Angelos, et al.
Published: (2025)

Additive Approximation Schemes for Low-Dimensional Embeddings
by: Anderson, Prashanti, et al.
Published: (2025)

Entrywise Low-Rank Approximation and Matrix $p \rightarrow q$ Norms via Global Correlation Rounding
by: Anderson, Prashanti, et al.
Published: (2026)

Exploration is Harder than Prediction: Cryptographically Separating Reinforcement Learning from Supervised Learning
by: Golowich, Noah, et al.
Published: (2024)

Taming Imperfect Process Verifiers: A Sampling Perspective on Backtracking
by: Rohatgi, Dhruv, et al.
Published: (2025)

Simple algorithms to test and learn local Hamiltonians
by: Gutiérrez, Francisco Escudero
Published: (2024)

An optimal tradeoff between entanglement and copy complexity for state tomography
by: Chen, Sitan, et al.
Published: (2024)

Optimal high-precision shadow estimation
by: Chen, Sitan, et al.
Published: (2024)

Quantum principal component analysis without eigenvector recovery
by: Yuan, Yewei, et al.
Published: (2026)

Non-iid hypothesis testing: from classical to quantum
by: De Palma, Giacomo, et al.
Published: (2025)

Predicting quantum channels over general product distributions
by: Chen, Sitan, et al.
Published: (2024)

QCircuitBench: A Large-Scale Dataset for Benchmarking Quantum Algorithm Design
by: Yang, Rui, et al.
Published: (2024)

Sublinear Time Quantum Algorithm for Attention Approximation
by: Song, Zhao, et al.
Published: (2026)