Final QA of documentation before 0.3.0 release (#2)

* Update tutorial and docs Action. Add mergify.

* Clean up

* Minor updates

* Add qiskit logos

* Move logo files

* Fix two workflows

* Use 3.11 for min version tests

* Bump down to 3.10

* Bumpy scipy to support py312

* Remove basetest env

* typo

* Remove tests that require scraping project deps

* Final QA

* Add fermion changes

* style

* Add dice-solver how-to

* style

.github/workflows/docs.yml

@@ -12,9 +12,9 @@ on:
     branches:
       - main
       - 'stable/**'
-
 jobs:
-  build_and_deploy_docs:
+  build:
+    name: Build docs
     runs-on: ubuntu-latest
     timeout-minutes: 20
     steps:
@@ -34,21 +34,24 @@ jobs:
         shell: bash
         run: |
           tox -edocs
-      - name: Prepare docs artifact
-        if: always()
-        shell: bash
-        run: |
-          mkdir artifact
-          cp -a docs/_build/html artifact/addon_sqd_html_docs
       - name: Upload docs artifact
         if: always()
-        uses: actions/upload-artifact@v4
+        uses: actions/upload-pages-artifact@v3
         with:
-          name: addon_sqd_html_docs
-          path: ./artifact
-      - name: Deploy docs
-        if: ${{ github.ref == 'refs/heads/stable/0.3' }}
-        uses: peaceiris/actions-gh-pages@v4
-        with:
-          github_token: ${{ secrets.GITHUB_TOKEN }}
-          publish_dir: ./docs/_build/html/
+          path: docs/_build/html
+
+  deploy:
+    name: Deploy docs
+    if: ${{ github.ref == 'refs/heads/stable/0.3' }}
+    needs: build
+    permissions:
+      pages: write
+      id-token: write
+    environment:
+      name: github-pages
+      url: ${{ steps.deployment.outputs.page_url }}
+    runs-on: ubuntu-latest
+    steps:
+      - name: Deploy to GitHub Pages
+        id: deployment
+        uses: actions/deploy-pages@v4

.mergify.yml

@@ -0,0 +1,8 @@
+pull_request_rules:
+  - name: backport
+    conditions:
+      - label=stable backport potential
+    actions:
+      backport:
+        branches:
+          - stable/0.3

README.md

@@ -19,7 +19,7 @@ Qiskit addons are a collection of modular tools for building utility-scale workl
 
 This package contains the Qiskit addon for sample-based quantum diagonalization (SQD) -- a technique for finding eigenvalues and eigenvectors of quantum operators, such as a quantum system Hamiltonian, using quantum and distributed classical computing together.
 
-Classical distributed computing is used to process samples obtained from a quantum processor, and to project and diagonalize a target Hamiltonian in a subspace spanned by them. This allows SQD to be robust to samples corrupted by quantum noise and deal with large Hamiltonians, such as chemistry Hamiltonians with millions of interaction terms, beyond the reach of any exact diagonalization methods.  
+Classical distributed computing is used to process samples obtained from a quantum processor and to project and diagonalize a target Hamiltonian in a subspace spanned by them. This allows SQD to be robust to samples corrupted by quantum noise and deal with large Hamiltonians, such as chemistry Hamiltonians with millions of interaction terms, beyond the reach of any exact diagonalization methods. 
 
 The SQD tool can target Hamiltonians expressed as linear combination of Pauli operators, or second-quantized fermionic operators. The input samples are obtained by quantum circuits defined by the user, which are believed to be good representations of eigenstates (e.g. the ground state) of a target operator. The convergence rate of SQD as a function of the number of samples improves with the sparseness of the target eigenstate. 
 
@@ -53,11 +53,11 @@ The [`qiskit_addon_sqd.fermion.solve_fermion()`](qiskit_addon_sqd/fermion.py) fu
 
 ##### Choosing subspace dimensions
 
-The choice of the subspace dimension affects the accuracy and runtime of the eigenstate solver. The larger the subspace the more accurate the calculation, at the cost of increasing the runtime and memory requirements. It is not known *a priori* the optimal subspace size, thus a convergence study with the subspace dimension may be performed, as described in this [example](docs/how_tos/choose_subspace_dimension.ipynb).
+The choice of the subspace dimension affects the accuracy and runtime of the eigenstate solver. The larger the subspace the more accurate the calculation, at the cost of increasing the runtime and memory requirements. The optimal subspace size for a given system is not known, thus a convergence study with the subspace dimension may be performed as described in this [example](docs/how_tos/choose_subspace_dimension.ipynb).
 
 ##### The subspace dimension is set indirectly
 
-In this package, the user controls the number of bitstrings (see the `samples_per_batch` argument in [`qiskit_addon_sqd.subsampling.postselect_and_subsample()`](qiskit_addon_sqd/subsampling.py)) contained in each subspace. The value of this argument determines an upper bound to the subspace dimension in the case of quantum chemistry applications. See this [example](docs/how_tos/select_open_closed_shell.ipynb) for more details.
+In this package, the user controls the number of bitstrings (see the `samples_per_batch` argument in [`qiskit_addon_sqd.subsampling.postselect_and_subsample()`](qiskit_addon_sqd/subsampling.py)) contained in each subspace. The value of this argument sets an upper bound to the subspace dimension in the case of quantum chemistry applications. See this [example](docs/how_tos/select_open_closed_shell.ipynb) for more details.
 
 ----------------------------------------------------------------------------------------------------