Consolidate changelog into the 0.1.0 release

CHANGELOG.md

@@ -4,20 +4,6 @@ All notable changes to this project are documented here. The format follows
 [Keep a Changelog](https://keepachangelog.com/en/1.1.0/), and the project uses
 [Semantic Versioning](https://semver.org/spec/v2.0.0.html).
 
-## [Unreleased]
-
-### Added
-- Stacked layers: `num_layers` on `QLSTM`/`LQLSTM` stacks recurrent layers, with
-  `h_n`/`c_n` shaped `(num_layers, batch, hidden_size)`, matching
-  `torch.nn.LSTM`.
-- Inter-layer `dropout` on `QLSTM`/`LQLSTM`, applied to the output of every layer
-  except the last.
-- `examples/benchmark_vs_classical.py`: a fair side-by-side against
-  `torch.nn.LSTM` on the same task.
-- Community health files: `CONTRIBUTING.md`, issue templates, and a pull-request
-  template.
-- Python 3.13 added to the packaging classifiers (already covered by CI).
-
 ## [0.1.0] - 2026-08-13
 
 First packaged release. The quantum LSTM from the paper is now an installable,
@@ -26,11 +12,18 @@ paper-reproduction code under `src/`.
 
 ### Added
 - `QLSTM` and `LQLSTM` layers with a `torch.nn.LSTM`-compatible call signature
-  (`(seq, batch, feature)` or `batch_first`, returning `output, (h_n, c_n)`).
+  (`(seq, batch, feature)` or `batch_first`, returning `output, (h_n, c_n)`),
+  including stacked layers via `num_layers` (with `h_n`/`c_n` shaped
+  `(num_layers, batch, hidden_size)`) and inter-layer `dropout`.
 - `QLSTMCell` for single-step use, with a `linear_enhanced` flag selecting the
   linear-enhanced L-QLSTM (default) or the classic QLSTM.
 - `make_vqc`, a variational-circuit factory built from PennyLane templates
   (`basic` and `strong` ansätze; `X`/`Y`/`Z` angle embedding).
-- Test suite covering output shapes, gradient flow to every parameter and to the
-  inputs, a learning check, and the API surface.
-- MIT license, packaging metadata, `CITATION.cff`, and CI on Python 3.10-3.12.
+- Examples: a `quickstart.py` training loop and `benchmark_vs_classical.py`, a
+  fair side-by-side against `torch.nn.LSTM` on the same task.
+- Test suite (18 tests) covering output shapes, gradient flow to every parameter
+  and to the inputs, a learning check, stacked-layer behaviour, and the API
+  surface.
+- Community health files: `CONTRIBUTING.md`, issue templates, and a pull-request
+  template.
+- MIT license, packaging metadata, `CITATION.cff`, and CI on Python 3.10-3.13.