Hello everyone. This is Na Krishna. I'm a technical architect with 11 years of experience in AWS Cloud DevOps, and automations. Today I'm gonna discuss about quantum computing and its implementation on AWS Cloud Quantum computing promises. To revolutionize how we solve complex problems from cryptography to drug discovery. By harnessing the strange behavior of quantum particles, quantum computers can perform certain calculations exponentially faster than classical computers. This presentation explores how a WCS democratizing access to quantum technology and empowering mores to explore the next computing frontier. Deep. The topics covered in this presentation are classical versus quantum computing. Quantum computing applications, hybrid quantum classical computing, quantum programming languages, AWS quantum computing portfolio, quantum hardware, and A-W-S-A-W. Bracket architecture design getting started with AWS Quantum Computing access models. And the final topic is future of quantum computing, classical versus quantum computing. The current classical computers use bits for calculations and computations. The bits can maintain the state of zero or one, whereas quantum computing uses qubits where each qubit can maintain state of zero, one or both. To double the computation power of a classical computer, we need to double the beats, whereas to double the power of a quantum computer, we just need to add one more qubit. That's the best thing about quantum computing. Quantum compute applications. Where do we need quantum computing in discovery, supply chain and traffic flow improvements. Especially in financial modeling for portfolio optimization and disc analysis. This picture explains about hybrid classical quantum algorithms where you can see both classical computer and a quantum hardware or simulator work together making it as a hybrid computing. In hybrid computing, a classical computer handles the most of the work by doing the initial setup, pre-pro and final analysis. And it controls a quantum computer, like a co-pro. And when it comes to quantum computer, it tackles hard part it. Quantum routines where the quantum effects will help, like position and untanglement. And then these results would be sent back to the classical computer for interpretation. This explains a hybrid model of classical and quantum computing together. And let's discuss about quantum programming languages. So we have mainly four quantum programming languages. The first one is Python with Kiki from IBM. Currently this is the most used quantum SDK and Q Sharp from Microsoft and circ from Google's Python framework. And the final one would be Amazon's bracket sdk. This is the native to AWS bracket. Let's discuss AWS Quantum Computing portfolio. AWS Quantum Portfolio comes with main three aspects. Amazon sub bracket, a WS Center for Quantum Computing, Amazon Quantum Solutions Lab. Let's talk about AWS bracket. It's a fully managed quantum computing survey. That lets design, test, and run quantum algorithms on different types of quantum hardwares and simulators. AWS Center for Quantum Computing. It is a research partnership with Caltech to advance quantum hardwares and algorithms under a w. Quantum solutions and they help various orations to solve the quantum computing challenges. Let's talk about various quantum hardwares available on a WS for quantum computing. The first one would be superconducting qubits. These are among the most mature quantum technologies, and these are provided by IQM and rete. The second type of hardware is ion trap quantum computers, and these have been offered by Ion Q, and the third one is neutral atom processors. These use areas of neutral atoms that are mandated by lasers, and this hardware is provided by two ERA computing and AWS also provides quantum simulators where alterations can test their algorithms. The simulators before actually actually getting started on the real quantum hardware so that they can do a pre-analysis and analyze the results. AWS Oxford Innovation, this is the latest innovation being announced by AWS in February, 2025, where this chip uses cat. Where the qubit stays on superposition of two states, like zero and one at the same time, while being more resistant to errors than the regular qubits, so it reduces the error corrections by 90%. This innovation helps the development of smaller and more reliable quantum computers like our regular personal computers. The Amazon user was launched in December 19. Now it's generally available and it is a unified platform for multiple quantum hardware types where our missions can explore various quantum hardware types as per the requirement. And it is a pay as you go service model where we, where our nations need not to invest upfront, but they can get started with the service and they pay as they use it. It democratized access. It enables innovation for researchers and businesses by simply using a Ws in a simple and fast way. How Amazon bracket works. First, we create algorithms with Python, SDK, and then we submit quantum tasks to devices or simulators, then run the hardware and classical computers like we run hybrid quantum jobs on quantum hardware and classical computers. And then we compare the results, and then we switch between hardware with minor code changes based upon how our results came up. And this is the Amazon bracket architecture diagram here. On the side there are three ways we can interact with manage notebooks. D, Amazon Bracket Console. These are the three ways where we can interact with Amazon's bracket. In this picture, in the middle, you can see Amazon bracket, so it has managed simulators that have been provided by a s and in the backend you'll see different types of hardwares, as we discussed in the previous slides. Hardware's approved by various vendors. So based upon our requirement, we can choose which hardware is suitable for us, and AWS bracket can seamlessly interact with other AWS services like Amazon CloudWatch for notifications, Amazon S3 for storage of objects or data, and a s management for permissions for management. AWS key management for data production. In this slide, it explains about how the quantum computers will process the operations, okay. On a quantum computer. So the smallest execution is called a shop. A single execution of quantum operation on a device is called shot. This one the first one explains how a shot works. So basically we call it as a circuit. Okay. If we have more than 10 shots, okay. So we can combine it as a task and submit it to. Quantum computer. So a series, it's, it executes a series of shorts in a single task. And the third option would be like hybrid job, what we saw in the previous slides. So basically a classical computer and quantum computer work together to make it as a hybrid job. This hardware can be used on cloud on AWS as a pay as you go model, or the hardware can be set up on premises, which would be incurring a cost. We can use combination of both cloud and local resources. And this is how we can get started with Amazon bracket. In database console, we can search with Amazon bracket or simply type bracket. It brings us to a bracket console where on the left side we can see devices, notebooks, jobs, tasks. On the part we can see different hardware that. So based upon the requirement, so we can choose our specific hardware, what we wanna use for our operations and the notebooks, we can rate our algorithm here and submit it to the quantum computer and. Final slide of the presentation. So as we have seen that quantum computing can help us to resolve more complex problems, the current research is going on so that in the future we can have fault tolerance systems where we'll have less errors in the quantum computing analysis, and they can be used for the regular commercial applications. And then we can use it for cryptography. And also we should be seeing more quantum education coming up, like workforce development for quantum economy. At the end, we want to see a quantum computer as small as like our personal computer with economically affordable and less and feasible for all computing applications. Very much.