Data for: A linear response framework for simulating bosonic and fermionic correlation functions on quantum computers
Data files
Apr 30, 2024 version files 2.37 MB
Abstract
Response functions are a fundamental aspect of physics; they represent the link between experimental observations and the underlying quantum many-body state. However, this link is often under-appreciated, as the Lehmann formalism for obtaining response functions in linear response has no direct link to experiments. Within the context of quantum computing, and by using a linear response framework, we restore this link by making the experiment an inextricable part of the quantum simulation. This method can be frequency- and momentum-selective, avoids limitations on operators that can be directly measured, and is ancilla-free. As prototypical examples of response functions, we demonstrate that both bosonic and fermionic Green's functions can be obtained, and apply these ideas to the study of a charge-density-wave material on {\emph{ibm\_auckland}}. The linear response method provides a robust framework for using quantum computers to study systems in physics and chemistry.
README: Title of Dataset: Data for: A linear response framework for simulating bosonic and fermionic correlation functions on quantum computers
This is the raw data for the manuscript: A linear response framework for simulating bosonic and fermionic correlation functions on quantum computers.
Description of the Data and file structure
1st data set (ibm_auckland.zip)
Raw quantum computer counts and calibration information for the calculations from ibm_auckland shown in Fig. 2 of the manuscript. It contains subdirectories:
.
gap_0.0
q0
172adb72-388a-11ed-bb02-acde48001122
4d9d8768-388a-11ed-bb02-acde48001122
87c11a18-388a-11ed-bb02-acde48001122
q1
5c80e050-3889-11ed-bb02-acde48001122
92b2ef9c-3889-11ed-bb02-acde48001122
c9c905de-3889-11ed-bb02-acde48001122
q2
0f764534-3889-11ed-bb02-acde48001122
.
.
.
The top level indicates the gap value, the second level the momentum (q) point, the the 3rd level the quantum computer job ID. Within each job directory are
backend_data.txt --- backend error information
backend_data_dict.txt --- full backend information as a python dict()
counts.json --- json file containing the bit string counts
info --- metadata
tlist.dat --- time axis values
Note that the gap_0.8 data has the full bit strings for the post-selection, whereas the other two have just the measured qubit.
2nd data set (polarizability.zip)
Data for the calculations leading to Fig 4.
Two numpy zip files (see https://numpy.org/doc/stable/reference/generated/numpy.savez.html) containing the arrays
dn -- change in on-site densities. This is a 24xNt array.
hoft -- driving field array. This is length Nt.
tax -- time axis values. This is length Nt.
3rd data set (noisy_sim.zip)
Noisy simulator data shown in Fig 3. The zip file contains the data for the 3 methods, which are numpy zip files with the following arrays:
For the position type files counts_pos_ancilla.npz and counts_position.npz, the arrays are arr0, arr1, arr2, arr3, arr4, arr5, arr6, arr7, tlist, N, nshots. The arr arrays contain the position basis A(r,t), tlist the time axis values. N is the number of sites, and shots the number of shots used in the simulator.
For the momentum type files counts_momentum.npz, the arrays are q0, q1, q2, q3, q4, q5, q6, q7, tlist, N, nshots. The q arrays contain the momentum basis A(q,t), tlist the time axis values. N is the number of sites, and shots the number of shots used in the simulator.
Sharing/access Information
Links to other publicly accessible locations of the data:
None
Was data derived from another source?
No
Methods
The experimental raw-data is obtained from superconducting ion quantum computer. Other data is from computer simulations.
Usage notes
The data is a mix of raw text and numpy zip files (which can be opened with numpy).