Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Optimal short-time measurements for Hamiltonian learning   Characterizing noisy quantum devices requires methods for learning the
underlying quantum Hamiltonian which governs their dynamics. Often, such
methods compare measurements to simulations of candidate Hamiltonians, a task
which requires exponential computational complexity. Here, we propose efficient
measurement schemes based on short-time dynamics which circumvent this
exponential difficulty. We provide estimates for the optimal measurement
schedule and reconstruction error, and verify these estimates numerically. We
demonstrate that the reconstruction requires a system-size independent number
of experimental shots, and identify a minimal set of state preparations and
measurements which yields optimal accuracy for learning short-ranged
Hamiltonians. Finally, we show how grouping of commuting observables and use of
Hamiltonian symmetries improve the accuracy of the Hamiltonian reconstruction.

17
The categories of this paper are: q-fin
11
The categories of this paper are: hep-lat
30
The categories of this paper are: q-alg
15
The categories of this paper are: nucl-ex
18
The categories of this paper are: econ
22
The categories of this paper are: chao-dyn
34
The categories of this paper are: chem-ph
19
The categories of this paper are: eess
27
The categories of this paper are: comp-gas
3
The categories of this paper are: physics
32
The categories of this paper are: atom-ph
25
The categories of this paper are: patt-sol
10
The categories of this paper are: q-bio
7
The categories of this paper are: hep-th
14
The categories of this paper are: math-ph
24
The categories of this paper are: dg-ga