fix(qaas): some minor fixes (#5961)

* fix(qaas): minor changes

* fix(qaas): minor changes

* fix(aer): config link

* fix(pennylane): revoke soon iqm

* Update pages/quantum-computing/additional-content/iqm-qpus.mdx

Co-authored-by: Rowena Jones <[email protected]>

---------

Co-authored-by: Rowena Jones <[email protected]>

Author: vmscw

pages/quantum-computing/additional-content/iqm-qpus.mdx

@@ -30,8 +30,8 @@ The table below summarizes the key technical specifications and pricing models f
 
 | Platform name | QPU Model | Qubits & Topology | Fidelity Metrics (Avg)* | Speed Metrics | Benchmarks | Pricing Model |
 | :--- | :--- | :--- | :--- | :--- | :--- | :--- |
+| **QPU-SIRIUS-24PQ** | Star-24 | 16 Active (of 24) [Star topology](https://www.iqmacademy.com/qpu/sirius/) | 1-gate: 99.89%, 2-gates:9 8.27%, readout: 98.05% | 2550 CLOPS | Q-score: 10 | 0.2€/circuit + 0.00075€/shot or 1200€/hour |
 | **QPU-GARNET-20PQ** | Crystal-20 | 20 Qubits [Square grid](https://www.iqmacademy.com/qpu/garnet/) | 1-gate: 99.88%, 2-gates: 99.4%, readout: 96.80% | 2600 CLOPS | Qv: 32 Q-score: 15 | 0.22€/circuit + 0.0012€/shot or 2000€/hour |
-| **QPU-SIRIUS-24PQ** | Star-24 | 16 Active (of 24) [Star tpology](https://www.iqmacademy.com/qpu/sirius/) | 1-gate: 99.89%, 2-gates:9 8.27%, readout: 98.05% | 2550 CLOPS | X | 0.2€/circuit + 0.00075€/shot or 1200€/hour |
 | **QPU-EMERALD-54PQ**|  Crystal-54 | 54 Qubits [Square grid](https://www.iqmacademy.com/qpu/emerald/) | 1-gate: 99.8%, 2-gates: 98.86%, readout: 96.53%  | 2550 CLOPS | Qv: 64  Q-score: 24 | 0.25€/circuit +0.0014€/shot or 3000€/hour |
 
 <Message type="note">

pages/quantum-computing/additional-content/quandela-qpus.mdx

@@ -20,8 +20,8 @@ Developed by **Quandela**, a French quantum computing leader founded in 2017. Th
 ## Use cases
 
 * **Quantum Machine Learning (QML):** Ideal for generative modeling, classification, and training quantum neural networks (QNNs).
-* **Linear algebra:** Efficiently solves differential equations and complex linear algebra problems used in engineering and physics.
 * **Certified randomness:** Generation of high-quality entropy for cryptography and stochastic simulations.
+* **Sampling tasks:** Efficiently performs sampling from complex probability distributions, useful in various scientific applications.
 
 ## Quandela QPUs available at Scaleway
 
@@ -30,8 +30,8 @@ Scaleway provides access to Quandela's "Mosaiq" generation devices and their dig
 | Platform name | QPU Model | Qubits & Topology | Fidelity Metrics (Avg)* | Speed Metrics | Pricing Model |
 | :--- | :--- | :--- | :--- | :--- | :--- |
 | **QPU-ASCELLA-6PQ** | Mosaiq-6 | 6 photons, 12 modes, All-to-All | 1-gate: 99.6%, 2-gates: 99%, readout: 99% | 4Mhz 144 op/s | 0.3€/circuit + 0.000001€/shot or 750€/hour |
-| **QPU-ALTAIR-10PQ** | Mosaiq-10 | 10 photons, 20 modes,  All-to-All | 1-gate: 99.94%, 2-gates: 98.2%, readout: 99% | 3Mhz 400 op/s | X | 0.3€/circuit + 0.000001€/shot |
-| **QPU-BELENOS-12PQ** | Mosaiq-12 | 12 photons, 24 modes, Dual-Rail-Encoding,  All-to-All | 1-gate: 99.6%, 2-gates: 99%, readout: 99% | 3Mhz 576 op/s | X | 0.3€/circuit + 0.000001€/shot or 1000€/hour |
+| **QPU-ALTAIR-10PQ** | Mosaiq-10 | 10 photons, 20 modes,  All-to-All | 1-gate: 99.94%, 2-gates: 98.2%, readout: 99% | 3Mhz 400 op/s | 0.3€/circuit + 0.000001€/shot |
+| **QPU-BELENOS-12PQ** | Mosaiq-12 | 12 photons, 24 modes, Dual-Rail-Encoding,  All-to-All | 1-gate: 99.6%, 2-gates: 99%, readout: 99% | 3Mhz 576 op/s | 0.3€/circuit + 0.000001€/shot or 1000€/hour |
 
 Developed by Quandela, exQalibur is a cutting-edge photonic quantum emulator accelerated by Scaleway's most powerful GPUs. This synergy enables large-scale simulations, allowing users to explore complex parameter spaces across 31 photonic qubits at kilohertz rates, accelerating prototyping and optimization of advanced quantum algorithms.
 

pages/quantum-computing/how-to/use-pennylane.mdx

@@ -26,7 +26,7 @@ Scaleway offers access to the `pennylane-scaleway` plugin, which enables you to
 
     - `scaleway.aer`
     - `scaleway.aqt`
-    - `scaleway.iqm` (Available soon)
+    - `scaleway.iqm`
 
 2. Select which backend to use within the chose device. This will determine the performance of your device. Refer to the detailed list of [Scaleweay Quantum Computing offers](https://www.scaleway.com/en/quantum-as-a-service/) on the Scaleway Website to find a complete list of the available backend platforms.
 

pages/quantum-computing/menu.ts

@@ -40,7 +40,7 @@ export const quantumComputingMenu = {
         },
         {
           label: 'Run Quantum Machine Learning with Pennylane',
-          slug: 'use-qsim-emulators',
+          slug: 'use-pennylane',
         },
       ],
       label: 'How to',

pages/quantum-computing/quickstart.mdx

@@ -58,7 +58,7 @@ This guide shows you how to execute your first "Hello World" circuit (a Bell Sta
   backend_name = "QPU-GARNET-20PQ"  # IQM (Transmons qubits)
 
   # 3. Retrieve the platform
-  # Example platform ID: 'EMU-AER-2L40S' (Aer emulator using an Nvidia H100 GPU)
+  # Example platform: 'EMU-AER-2L40S' (Aer emulator using a managed cluster of 2 Nvidia L40S GPU)
   backend = provider.get_backend(backend_name)
 
   # 3. Create a Quantum Circuit