From 88b3d640f5464f4f5ff96244b1a6157f1493fc4f Mon Sep 17 00:00:00 2001
From: nicomeyer96 <161021867+nicomeyer96@users.noreply.github.com>
Date: Wed, 3 Jun 2026 13:25:40 +0000
Subject: [PATCH 1/2] feat: :card_file_box: add component "Qiskit-Torch-Module"
 from Issue #133

---
 _components/qiskit-torch-module.md | 15 +++++++++++++++
 1 file changed, 15 insertions(+)
 create mode 100644 _components/qiskit-torch-module.md

diff --git a/_components/qiskit-torch-module.md b/_components/qiskit-torch-module.md
new file mode 100644
index 0000000..8541f0f
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+++ b/_components/qiskit-torch-module.md
@@ -0,0 +1,15 @@
+---
+title: Qiskit-Torch-Module
+languages:
+  - Python
+frameworks:
+  - Qiskit
+links:
+  docs: https://github.com/nicomeyer96/qiskit-torch-module/blob/main/README.md
+  github: https://github.com/nicomeyer96/qiskit-torch-module
+  releases: https://pypi.org/project/qiskit-torch-module/
+maintainers:
+  - Fraunhofer IIS (Quantum Compilation Group)
+---
+
+The qiskit-torch-module is a Qiskit-based simulation and training framework for variational quantum circuits with a native PyTorch interface, designed for fast prototyping of quantum neural networks on single-CPU machines. It provides efficient multi‑observable evaluation, batch‑parallelized expectation and gradient computation, and flexible automatic differentiation for hybrid classical–quantum models. Compared to qiskit‑machine‑learning, it achieves up to two orders of magnitude lower runtimes with minimal code changes to existing Qiskit workflows.

From 9ef3457cbede866280f85df0942e1be6cf8edcf1 Mon Sep 17 00:00:00 2001
From: "pre-commit-ci[bot]"
 <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Date: Wed, 3 Jun 2026 13:25:54 +0000
Subject: [PATCH 2/2] =?UTF-8?q?=F0=9F=8E=A8=20pre-commit=20fixes?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
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 _components/qiskit-torch-module.md | 7 ++++++-
 1 file changed, 6 insertions(+), 1 deletion(-)

diff --git a/_components/qiskit-torch-module.md b/_components/qiskit-torch-module.md
index 8541f0f..5b5b9ac 100644
--- a/_components/qiskit-torch-module.md
+++ b/_components/qiskit-torch-module.md
@@ -12,4 +12,9 @@ maintainers:
   - Fraunhofer IIS (Quantum Compilation Group)
 ---
 
-The qiskit-torch-module is a Qiskit-based simulation and training framework for variational quantum circuits with a native PyTorch interface, designed for fast prototyping of quantum neural networks on single-CPU machines. It provides efficient multi‑observable evaluation, batch‑parallelized expectation and gradient computation, and flexible automatic differentiation for hybrid classical–quantum models. Compared to qiskit‑machine‑learning, it achieves up to two orders of magnitude lower runtimes with minimal code changes to existing Qiskit workflows.
+The qiskit-torch-module is a Qiskit-based simulation and training framework for variational quantum
+circuits with a native PyTorch interface, designed for fast prototyping of quantum neural networks
+on single-CPU machines. It provides efficient multi‑observable evaluation, batch‑parallelized
+expectation and gradient computation, and flexible automatic differentiation for hybrid
+classical–quantum models. Compared to qiskit‑machine‑learning, it achieves up to two orders of
+magnitude lower runtimes with minimal code changes to existing Qiskit workflows.