Merge pull request #48859 from SoniaLopezBravo/SoniaLopezBravo/quantum-modules-freshness

Freshness pass of Azure Quantum modules

Author: JamesJBarnett

learn-pr/quantum/choose-the-best-azure-quantum/includes/6-knowledge-check.md

@@ -1 +1 @@
-Choose the right response for each question. 
+Test your knowledge of the concepts covered in this module. Choose the right response for each question.

learn-pr/quantum/estimate-resources-quantum-algorithms/1-introduction.yml

@@ -1,12 +1,12 @@
 ### YamlMime:ModuleUnit
 uid: learn.quantum.estimate-resources-quantum-algorithms.introduction
 title: Introduction
-metadata:
-  adobe-target: true
+metadata:
+  adobe-target: true
   prefetch-feature-rollout: true
   title: Introduction
   description: Introduction.
-  ms.date: 06/05/2024
+  ms.date: 01/22/2025
   author: SoniaLopezBravo
   ms.author: sonialopez
   manager: tedhudek

learn-pr/quantum/estimate-resources-quantum-algorithms/2-resource-estimation-in-quantum-computing.yml

@@ -1,12 +1,12 @@
 ### YamlMime:ModuleUnit
 uid: learn.quantum.estimate-resources-quantum-algorithms.resource-estimation-in-quantum-computing
-title: Resource estimation in quantum computing
-metadata:
-  adobe-target: true
+title: Why is resource estimation important?
+metadata:
+  adobe-target: true
   prefetch-feature-rollout: true
-  title: Resource Estimation in Quantum Computing
+  title: Why is resource estimation important in quantum computing?
   description: Learn what resource estimation is and why it is important in quantum computing.
-  ms.date: 06/05/2024
+  ms.date: 01/22/2025
   author: SoniaLopezBravo
   ms.author: sonialopez
   manager: tedhudek

learn-pr/quantum/estimate-resources-quantum-algorithms/3-azure-quantum-resource-estimator.yml

@@ -1,12 +1,12 @@
 ### YamlMime:ModuleUnit
 uid: learn.quantum.estimate-resources-quantum-algorithms.azure-quantum-resource-estimator
 title: The Azure Quantum Resource Estimator
-metadata:
-  adobe-target: true
+metadata:
+  adobe-target: true
   prefetch-feature-rollout: true
   title: The Azure Quantum Resource Estimator
   description: Learn how to use the Azure Quantum Resource Estimator.
-  ms.date: 06/05/2024
+  ms.date: 01/22/2025
   author: SoniaLopezBravo
   ms.author: sonialopez
   manager: tedhudek

learn-pr/quantum/estimate-resources-quantum-algorithms/4-get-started-with-azure-quantum-resource-estimator.yml

@@ -1,12 +1,12 @@
 ### YamlMime:ModuleUnit
 uid: learn.quantum.estimate-resources-quantum-algorithms.get-started-with-azure-quantum-resource-estimator
 title: Exercise - Get started with the Azure Quantum Resource Estimator
-metadata:
-  adobe-target: true
+metadata:
+  adobe-target: true
   prefetch-feature-rollout: true
   title: Exercise - Get started with the Azure Quantum Resource Estimator
   description: Learn to enable the Azure Quantum Resource Estimator and how to submit a job.
-  ms.date: 06/05/2024
+  ms.date: 01/22/2025
   author: SoniaLopezBravo
   ms.author: sonialopez
   manager: tedhudek

learn-pr/quantum/estimate-resources-quantum-algorithms/5-estimate-resources-with-azure-quantum.yml

@@ -1,12 +1,12 @@
 ### YamlMime:ModuleUnit
 uid: learn.quantum.estimate-resources-quantum-algorithms.estimate-resources-of-a-real-world-problem
 title: Exercise - Estimate resources for a real-world problem
-metadata:
-  adobe-target: true
+metadata:
+  adobe-target: true
   prefetch-feature-rollout: true
   title: Exercise - Estimate resources for a real-world problem
   description: Learn how to run a QIR quantum algorithm on the Azure Quantum Resource Estimator. 
-  ms.date: 06/05/2024
+  ms.date: 01/22/2025
   author: SoniaLopezBravo
   ms.author: sonialopez
   manager: tedhudek

learn-pr/quantum/estimate-resources-quantum-algorithms/includes/1-introduction.md

@@ -1,8 +1,8 @@
-The potential of quantum computers to solve important scientific problems extends to commercial problems, as well. To achieve commercial viability in using quantum computers, you must have  large-scale, fault-tolerant computers that have both a large number of qubits (or *quantum bits*, the basic unit of measurement in quantum computing) in superposition and physical error rates below a certain threshold. You also need quantum error correction (QEC) schemes to achieve fault tolerance. QEC is both time intensive and space intensive, so the execution time for algorithm-level or logical-level operations increases. Then, you need more physical qubits to store and compute more information.
+Quantum computers have the potential to tackle significant scientific and commercial problems. To make them commercially viable, quantum computers need to be large-scale, fault-tolerant machines with many qubits in superposition and low physical error rates. Achieving fault tolerance also requires quantum error correction (QEC), which is both time and space intensive, leading to increased execution time for operations and the need for more physical qubits.
 
-Given these requirements, resource estimation becomes crucial as you develop quantum computers and quantum solutions for commercial uses. It's important to understand the impact of architectural design choices and QEC schemes as you plan your quantum computing solution.
+Given these requirements, estimating resources is crucial in developing quantum computers and solutions for commercial use. It's essential to understand how architectural design choices and QEC schemes impact your quantum computing plans.
 
-You can use the Azure Quantum Resource Estimator to analyze the impact of various choices for architectural parameters like physical qubit and QEC models on overall physical-resource estimates. In this module, you'll learn some basic concepts about resource estimation in fault-tolerant quantum computing, and you'll explore the Azure Quantum Resource Estimator.
+The Azure Quantum Resource Estimator helps you analyze how different architectural parameters, like physical qubit and QEC models, affect overall physical-resource estimates. In this module, you'll learn how to use the Azure Quantum Resource Estimator to estimate the resources needed to run a real quantum algorithm.
 
 ## Learning objectives
 

learn-pr/quantum/estimate-resources-quantum-algorithms/includes/2-resource-estimation-in-quantum-computing.md

@@ -1,13 +1,32 @@
-In quantum computing, resource estimation is the ability to understand the resources that are required for a given algorithm. The resources will be the number of qubits, the number of quantum gates, or processing time. Required resources vary for different computational scenarios based on the type of error correction scheme and other parameters. 
+In quantum computing, resource estimation is the ability to understand the resources that are required to run a given algorithm. The resources are, for example, the number of qubits, the number of quantum gates, and processing time. 
 
-## Why is resource estimation important?
+In this unit, you'll learn why the estimation of these resources is important in quantum computing.
 
-Quantum computers have the potential of *quantum advantage* to solve some scientifically and commercially valuable problems. They can outperform any classical computer. To achieve quantum advantage, you must have a large-scale, fault-tolerant quantum compute; that is, a quantum computer that's capable of allowing a large number of qubits in superposition, and with a physical error rate below a certain threshold. Through the application of QEC schemes, quantum information is protected from errors caused by decoherence and quantum noise.
+## How long does it take to run a quantum algorithm? 
 
-Quantum operations at the physical level are noisy. The long computations required for practical quantum advantage require error correction to achieve fault tolerance. QEC is both time intensive and space intensive. It requires increased execution time for an algorithm-level or logical-level operation, and an extra number of physical qubits to store and compute information at the logical level.
+Quantum computers have the potential of *quantum advantage* to solve some scientifically and commercially valuable problems. For example, one of the top applications for quantum computing is to break encryption. The RSA encryption algorithm is based on the difficulty of factoring large numbers. A quantum computer can factor large numbers exponentially faster than a classical computer. So, the question is, how long does it take to run a quantum algorithm that breaks encryption on a real quantum computer? Or in other words, how long are my passwords secure?
 
-Understanding the impact of architecture design choices and QEC schemes for specific applications is an important challenge. You have to answer several questions; for example, how large does a quantum computer need to be to achieve practical quantum advantage? How long does the computation take? Are some qubit technologies better suited than others to solve the problem you want to solve? What are the best architecture choices in the hardware and software stacks to support scaled quantum computation?
+The truth is the required resources needed to run a quantum algorithm on a future scaled quantum computer vary for different computational scenarios based on the type of qubits, the error correction scheme, and other architecture design choices. The Azure Quantum Resource Estimator is a tool that helps you estimate the resources needed to run a quantum algorithm for a future scaled quantum computer. For example, the Azure Quantum Resource Estimator can estimate the resources needed to break a particular encryption algorithm. 
 
-Estimating the running time, the number of qubits, and other resources to be used in realistic models of quantum computers is the first step to reducing these resource requirements. Resource estimation allows you to understand the differences between qubit technologies so you can prepare and refine your quantum solutions to run on scaled quantum machines in the future.
+The diagram shows the estimated runtime and number of qubits needed to break different encryption algorithms for different qubit types. The diagram shows the following:
+
+- Classical encryption algorithms, which are RSA (blue), Elliptic Curve (green), and Advanced Encryption Standard (red).
+- Key strength, which is set to highest.
+- Qubit types, which are topological (circle) and superconducting (triangle).
+- Qubit error rate, which is set to reasonable.
+
+
+:::image type="content" source="../media/resource-estimation-crypto.png" alt-text="Diagram showing the number of qubits and runtime required to break different encryption algorithms for different qubit types.":::
+
+The diagram shows that the number of qubits and runtime needed to break the Advanced Encryption Standard (AES) encryption algorithm is significantly higher than the number of qubits and runtime needed to break the Elliptic Curve and RSA algorithms. The diagram also shows that the number of qubits and runtime needed to break any encryption algorithm is higher for  superconducting qubits than for topological qubits. If you want to know more about the diagram, see [Analyze cryptographic protocols with the Resource Estimator](/azure/quantum/resource-estimator-quantum-safe-planning).
+
+With this in mind, the Azure Quantum Resource Estimator helps you to analyze the impact of quantum computing on the security of some classical encryption methods, and prepare for a quantum-safe future. 
+
+## Why is resource estimation important in quantum computing?
+
+Understanding the impact of architecture design choices and quantum error correction schemes for specific applications is an important challenge. You have to answer several questions; for example, how large does a quantum computer need to be to achieve practical quantum advantage? How long does the computation take? Are some qubit technologies better suited than others to solve the problem you want to solve? What are the best architecture choices in the hardware and software stacks to support scaled quantum computation?
+
+The Resource Estimator helps you understand how many qubits are needed to run an application, how long it will take to run, and which qubit technologies are better suited to solving a specific problem. Understanding these requirements will allow you to prepare and refine quantum solutions to run on future, scaled quantum machines.
+
+Next, let's learn about the Azure Quantum Resource Estimator and how to customize it to estimate the resources needed to run a quantum algorithm. 
 
-Next, let's learn about the Azure Quantum tool you can use to estimate a quantum algorithm's resources.