add neutron scattering tutorial#5274
Conversation
Co-authored-by: nathanearnestnoble <51792809+nathanearnestnoble@users.noreply.github.com>
|
Check out this pull request on See visual diffs & provide feedback on Jupyter Notebooks. Powered by ReviewNB |
|
One or more of the following people are relevant to this code:
|
|
May want to remove "While that paper ran a 50-qubit experiment, here we run a 20-qubit experiment to keep the cost of performing approximate quantum compilation (AQC) more manageable." sentence at the start, now that you have been able to scale it up |
done |
- make Next steps links root-relative and match actual page titles - remove unneeded cspell ignore words (eigsh, Aer's, XLA) - add TUT_SNS job tag to the hardware estimator - copyedits: spell out DMRG, DD, and TREX on first use, lowercase "approximate quantum compiling", reword a few em dashes and "via", fix a double space and an en dash
henryzou50
left a comment
There was a problem hiding this comment.
Thanks for the changes, this tutorial looks great!
I pushed a commit with some small copyedits (root-relative Next steps links, trimming unused words from the cspell ignore list, a TUT_SNS job tag, and a few wording fixes in line with earlier review comments), so the checks should pass now. None of it touches code that affects results.
Beyond that, here are a few things I noted that could be changed or adjusted, let me know what you think.
Commentary/results
- The intro's caveat only covers the AQC fidelity, but the printed ground-state ansatz fidelity also drops sharply (0.984 at 10 qubits → 0.646 at 50) with no explanation, so readers might think their ground-state prep failed. Suggest adding a sentence to the large-scale intro noting the ~0.65 fidelity is expected, and that increasing
gs_n_layersormaxiterimproves it at additional classical cost. - The text says the two-layer ansatz is used "where higher fidelity is needed," yet its printed fidelities (k=7–10: 0.67–0.77) are lower than the one-layer ones (k=1–6: 0.81–1.0). That's expected, as later time steps are just harder to compress, but a short sentence saying so would keep it from reading as a regression.
- The large-scale section ends at the plots with no discussion. One or two closing sentences pointing out the continuum boundaries and the intensity at q = π would be nice here
Step 2c runtime for k > 6
When I ran the notebook, Step 2c only completed overnight, which matches the committed outputs: the one-layer stage (k=1–6) takes ~28 minutes, but the two-layer stage (k=7–10) takes ~5.3 hours (k=7 alone is ~3 hours, maybe because the stage boundary resets to fresh initial parameters and it runs all ~100 L-BFGS-B iterations on the 3412-parameter ansatz). That puts Step 2c at ~6 hours end to end.
Is there a way to shorten this, or should we expect it to always take this long to get good results?
Index placement (question for @abbycross)
The new entry is inserted at the top of the Observable estimation section in both _toc.json and index.mdx, whereas #5280 appended its tutorial at the end of the section. Which placement do we want?
- Explained in the large-scale intro that the lower fidelities at 50 qubits (~0.65 ground state, ~0.7 AQC) are expected, and which knobs improve them. - Clarified that the two-layer AQC fidelities being lower than the one-layer ones is not a regression (later steps are harder to compress). - Added a short closing discussion after the hardware plots tying the measured DSF back to the two-spinon continuum.
henryzou50
left a comment
There was a problem hiding this comment.
Since Kevin is away, I applied the following commentary revisions as I mentioned before:
- Explained in the large-scale intro that the lower fidelities at 50 qubits (~0.65 ground state, ~0.7 AQC) are expected, and which knobs improve them.
- Clarified that the two-layer AQC fidelities being lower than the one-layer ones is not a regression (later steps are harder to compress).
- Added a short closing discussion after the hardware plots tying the measured DSF back to the two-spinon continuum.
This tutorial LGTM! Let me know if you want to do a quick pass on this @nathanearnestnoble
corresponding paper: https://arxiv.org/abs/2603.15608
produced with assistance from Claude