quantum programming tutorial
November 13th, 2020

Currently, the Agave 8-qubit chip (8Q-Agave) is live and available for you connect to using the Forest API. Here we are using the the H gate, or Hadamard gate, which we imported previously. Well, a computer, in its most basic form, is simply a machine that performs calculations. So when we call the measure.all() method, each of our qubits are collapsed into a random state of either 0 or 1. (Disclosure: I’m a product manager at Rigetti Quantum Computing. We put that ball inside a closed box, and while inside the box, the ball uses some quantum properties to change its color to purple—an in-between combination of both red and blue (i.e. You can learn more about the design and architecture of Quil here, and check out the docs for how you can customize it using the API here. Now we have three qubits—each in superposition, and each with a random probability to return either 0 or 1 when they are measured. You can request access to the QPU here. With quantum computing, everything changes. In the early days of computers, we actually had mechanical computers — Charles Babbage designed such a machineto perform general … our laptops, phones, etc), all of the interactions and information that we generate eventually gets compiled down into a series of binary bits: 0's or 1’s. In a quantum environment, taking a measurement causes a qubit to collapse out of superposition. Welcome to a series on programming quantum computers. There’s many different types of computers. This not only helps to generate true randomness but also protects the randomization operation from any attempts to observe or intercept it, as this would disturb and collapse the quantum environment. To illustrate how this works, let’s go back to our quantum dice program. With quantum computing, this randomization is performed and hidden by nature in the quantum world. These are quantum operations that are analogous to the classical boolean logic gates (e.g. In quantum computing, we have quantum bits, or qubits. Now, let’s see how we can do this on the actual quantum computer itself. In this tutorial, I want to talk a bit more about qubits, and subsequently their gates. To see what’s happening under the hood, you can print the roll_dice function. For example, the quantumX gate changes a qubit’s state from 0 to 1. Quantum computing is radically different from the conventional approach of transforming bits strings from one set of 0's and 1's to another. Run your quantum_dice.py file to test it out. The purpose of this tutorial is to introduce you to the basic concepts of quantum programming using examples that you can try out on the online jsqubits runner. The Hadamard gate, H gate, places a qubit in superposition and generates a 50/50 random chance of measuring either a 0 or 1. The way in which we build such devices is different, requiring new materials, new design rules and new processor architectures. ), but that have extra features because they are quantum. We repeat this for two more qubits: H(1), H(2). Like conventional computers, quantum … Today, anyone with an internet connection can access and program quantum computers via the cloud. Thanks to Will Zeng, Lauren Rugani, and Nima Alidoust for your feedback and edits. At the top of the file, we’ll import the following: Before moving on, let’s quickly introduce some quantum computing concepts. First, we pass in a single qubit : H(0). Specifically, we’ll build an 8-sided quantum dice that generates a random result. Consider this analogy: a ball starts off as either red or blue (its initial state). Here’s our program: Some context: I’m a product manager at Rigetti, and we’re building quantum computers that anyone can access over the cloud. Now that we have 8 equally random outcomes, we need to generate a single result, i.e. When we measure the qubit, it collapses out of its quantum state and returns either a 0 or 1. Tutorial on Quantum Programming: An Introduction. Now that you’ve installed pyQuil, open up your code editor, or spin up a Jupyter notebook, and create a new file named quantum_dice.py. Quantum computers shine when solving involves number or data crunching with huge amounts of inputs. The physics that we use to understand bits of information and the devices that manipulate them are totally different. You’ll see an assemby-like set of instructions is being generated: These instructions are written in a language called Quil (Quantum Instruction Language), a compilation layer that connects pyQuil programs to the quantum computing backend. First, you’ll need to sign up for a free API key for Forest here. NOT, AND, XOR, etc. When I was first introduced to quantum computing, the thought of quantum computers alone was mindblowing; it seemed more science fiction than reality. If you can believe it, I only told you part of … What makes qubits unique is that they are non-binary, meaning they can be in a state of 0, 1, or a special in-between state known as superposition. Finally, here’s some recommended resources I’ve found helpful to getting started in quantum computing: Note: Another important benefit of quantum computing we demonstrated in this example is using quantum computers for random number generation. We also demonstrated the exponential scaling power of quantum computers (N qubits = 2^N bits). Today, there’s already thousands of developers, researchers, and organizations using the Forest SDK, with over 60M+ jobs run to date. They are designed to tackle complex problems that would take supercomputers from days to being unable to solve. We’re at the beginning of the quantum … The inner list represents the final state of our three qubits—one of the 8 possibilities listed above (i.e. In order to uncover the full potential of quantum computers, there is a need to engage people from various backgrounds in a … We only needed three qubits to generate 8 potential outcomes. N qubits = 2^N bits). Using pyQuil, we can simply import these gates into our program. To summarize, we’ve successfully simulated an 8-sided dice on a quantum computer using Rigetti’s quantum virtual machine. While in superposition, a qubit is simultaneously both 0 and 1. I try to assume as little knowledge of quantum physics as possible and minimize the amount mathematics required. Qubits. While this is a simple operation we already do today, the threat of being able to reverse engineer or manipulate these techniques makes many of today’s cryptographic systems vulnerable. This gives us 8 total possible outcomes (2 * 2 * 2 = 2³), which will represent each side for our quantum dice: You may have noticed that each additional qubit we add to our program will double the number of sides on our dice. Hello and welcome to part 2 of the Quantum computer programming tutorials. Quantum computers can simulate the universe’s subatomic particles by speaking the same language as an electron or proton. Once you have the right version of Python, you’ll need to install pyQuil: Alternatively, you can also pip install pyquil, although some users have experienced issues with this method, so we recommend using conda. Two tutorials that cover the math necessary for working with quantum computing – complex arithmetic and linear algebra – are written in Python, and the four that introduce the quantum … # Measure the qubits to get a result, i.e. superposition). Quantum computing takes a radically different approach to programming. In classical computers (e.g. So, a fourth qubit would create a 16-sided dice; five qubits would generate a 32-sided dice; and so on. Let’s start off by understanding what quantum computers really are and how they are different from other computers. We’d love for you to try out the challenge and publish a post on how you did it. In this post, I’ll introduce you to the basics of quantum computing, demonstrate why they’re useful, and show you how easy it is to start building quantum programs. We use quantum gates to help change the state of our qubits, and control them while in superposition. Your access will then be scheduled for a dedicated window of time. That’s it! Bits are the fundamental building blocks of computers. Near-term applications are being developed to solve some of the world’s most complex problems—such as simulating molecules that lead to the discovery of new materials and pharmaceuticals, designing catalysts to help build next generation battery technologies, and solving complex optimization problems for achieving new advancements in machine learning and artificial intelligence. the result of our dice roll). Finally, let’s format the result into a nice readable dice value between 1 and 8. Using Rigetti’s software development kit, Forest, and its Python-based pyQuil library, I’ll walk you through an example of how to do it in just 10 lines of code. When we open this box to observe the purple ball, suddenly it changes its color again and we only see either a red or blue ball. roll the dice. Rigetti’s quantum processing units (QPUs), or quantum chips, are fabricated at our lab in Fremont, CA, and then wired and integrated into a dilution refrigerator in Berkeley, CA, where it’s made available over the cloud. Once you’ve received access, you can simply replace your connection to the QVM with a connection to the QPU in a few lines of code: We introduced how qubits, superposition, and quantum gates work in quantum programming, and built a quantum program in just 10 lines of code.

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