QRISE 2024 Challenges and Selected Projects
Selected Projects
Atom Shuttling Compilation Visualizer
Neutral atoms have recently set themselves apart from other quantum computing technologies by demonstrating the capacity to operate protocols on up to 48 logical qubits. The features that allow this advance include the high capacity for parallelization of operations, large scale registers of qubits, and high-performing 2-qubit gates. All of this is catalyzed by the capacity to shuttle qubits through the quantum devices, actually enabling these machines to have specialized zones for memory, processing, and measurement, with a quantum information bus that allows almost any-to-any connectivity.
Your task is to create a compilation visualizer for neutral-atom gate-based quantum computers that incorporates the capacity to shuttle atoms between different regions of the processor during the course of a computation.
GitHub Link: https://github.com/QuEraComputing/QRISE_2024
Selected Projects
Team name: Atomique
Contributors: Quinn Manning, Kevin Li, Dmitrii Khitrin, Daniil Shatokhin, David Nizovsky
Project link: https://github.com/Dalbick/DPQA-Compilation-Visualizer
Team name: Rydberg Rangers
Contributors: Rasmit Devkota, Sameer Arora, Alexandre Boutot, Srijan Deoraj
Project link: https://github.com/RasmitDevkota/QRISE_2024
Stacking Error Mitigation Techniques
Quantum computers hold immense potential for solving complex problems, but their practical utility is hindered by their susceptibility to errors. Mitigating these errors is crucial for realizing the full capabilities of quantum computers. This challenge aims to find effective methods of reducing noise by means of combining multiple quantum error mitigation (QEM) techniques. QEM is a field of research that aims to find ways to increase the accuracy of quantum computers without the full machinery needed to implement quantum error correction. A plethora of QEM techniques have been proposed and studied over the past ~7 years, yet the capabilities of these techniques have not been thoroughly tested and explored in conjunction.
In this research challenge, you will explore the efficacy of stacking multiple quantum error mitigation techniques leveraging the Mitiq Python toolkit. The goal is to compare different combinations of error mitigation strategies in simulation to achieve the lowest possible error rate.
GitHub Link: https://github.com/quantumcoalition/qrise2024-unitaryfund-challenge
Team name: DNA Game
Contributors: Skylar Chan, Jeffrey Kwan, Wilson Smith, Marco Qin
Project link: http://github.com/schance995/qrise-2024/
Team name: MACS
Contributors: Matthew Chang, Eric Yarnot
Project link: https://github.com/MChang360686/QRISE2024
Selected Projects
Implementing an Exponential Quantum Advantage Algorithm
The progress of quantum computers in the last few years has been immense, with better and better quantum computers being developed each year. Nowadays there are quantum computers with hundreds of qubits that can compute quantum algorithms with circuit depth of up to a few thousand and still receive a significant signal. One of the key challenges is the development of efficient and novel quantum algorithms that are useful and offer exponential advantage over classical methods. One of the very few we know of is an algorithm to simulate systems of classical coupled harmonic oscillators introduced in 2023 by Babbush et al.
Your challenge is to implement the above paper using the Classiq platform. Classiq is an end-to-end quantum software platform that enables you to design, optimize, analyze and execute quantum algorithms.
GitHub Link: https://github.com/quantumcoalition/qrise2024-classiq-challenge
Team name: Classiq Entanglers
Contributors: Ramachandran Sekanipuram Srikanthan, Hirmay Sandesara, Aman Gupta
Project link: https://github.com/Hirmay/QRise
Team name: Schrodinger’s Coders
Contributors: Marcel Augusto Pinto, Mohammed Shoaib Ahmed
Project link: https://github.com/marcel-pinto/qrise2024-classiq-challenge
Team name: The Entangled Pair
Contributors: Adam Godel, Katie Emerson
Project link: https://github.com/adam-godel/qrise2024-classiq-challenge
Resource estimation of quantum algorithms
Quantum resource estimation is the area of quantum information science that aims to answer the question “How many physical qubits and how much time is necessary to execute a quantum algorithm under specific assumptions about the hardware platform used?” The estimates of the answers are done under realistic assumptions about architecture of fault tolerant quantum computers, such as physical qubit parameters and error correction schemes used. Getting these kinds of resource estimates serves at least three purposes. First, we can use it to deduce the conditions that quantum hardware needs to meet to offer practical quantum advantage. Second, resource estimation clarifies which algorithms truly give quantum advantage over their classical counterparts, and which ones do not. Third, it allows us to compare the efficiency of different algorithms that solve the same problem long before they become viable to run on quantum machines. Being able to answer such questions gives us essential information for defining our vision for the future of quantum computing.
In this research challenge you will implement one or several quantum algorithms and obtain and analyze the estimates of resources required for running them on fault tolerant quantum computers using the Microsoft Azure Quantum Resource Estimator.
GitHub Link: https://github.com/quantumcoalition/qrise2024-microsoft-challenge
Selected Projects
Team name: Qu-Cats
Contributors: Katie Harrison, Muhammad Waqar Amin, Nikhil Londhe, Sarah Dweik
Project link: https://github.com/nikhil-co/QU_Cats_QRISE2024
Team name: Exponential
Contributors: Niraj Venkat
Project link: https://github.com/nirajvenkat/regev-factor
Selected Projects
Quantum computer-aided design (QCAD) of atomic clocks
Atomic clocks are an extremely useful quantum technology. The usage of atomic clocks in GPS satellites has enormous real-world impact. This makes the improvement of atomic clocks an important application of quantum computers. Recent work has used a quantum computer to design a precise clock.
In this research challenge you will discover ways to use quantum computers to improve the design of atomic clocks.
GitHub link: https://github.com/quantumcoalition/qrise2024-infleqtion-challenge
Team name: MaybeACat
Contributors: Ankon Dey Animesh, Tulsi Chaudhari, Shivani Mayekar, Ganisetti Gunadham, Prince Odoi Asare
Project link: https://github.com/ShivaniDM/qrise2024-infleqtion-challenge/
Dynamic Circuit Challenge: Maximizing Performance and Tayloring Noise
Dynamic circuits are an exciting feature of IBM Quantum hardware that incorporates quantum circuits with real-time classical communication. Different from the static counterpart, dynamic circuits can not only implement a set of basic quantum operations like the Hardmard gate, CNOT gate, or qubit reset but also can implement measurement in the middle of a circuit, store the measurement results to classical bits, evaluate classical expressions on the fly, and determine what quantum operation to do next. This capability has a variety of applications, for example, quantum error correction, quantum simulation, and so on.
In this challenge, you will explore can do with dynamic circuits. Bonus point if you show improvement of your dynamic circuit implementation over its static counterpart - for example, use dynamic circuit feature to shorten the circuit depth, suppress error rate, and so on.
GitHub Link: https://github.com/quantumcoalition/qrise2024-ibm-challenge
Selected Projects
Team name: Dynamic Quantumvengers
Contributors: Hubert Kolcz, Ayeman Fatima, Umi Yamaguchi
Project link: https://github.com/hubertkolcz/dynamic-quantumvengers/
Team name: Feynman Prodigies
Contributors: Abdullah Kazi, Jacob Park, Owais Siddiqui
Project link: https://github.com/owaisishtiaqsiddiqui/QRISE