About the QAGC 2024
Timeline
February 1, 2024, 0:00 (JST) - Start Date
June 30, 2024, 23:59 (JST) - Final Submission Deadline
Awards
- 1st Place - $5,000
- 2nd Place - $2,500
- 3rd Place - $1,500
Currently, QunaSys is planning to apply to hold a workshop to be hosted by QunaSys at IEEE Quantum Week 2024. IEEE Quantum Week 2024 will be held as an in-person event with virtual participation on Sep 15–20 at Palais des Congrès Montréal, Québec, Canada. As in previous years, if applications are approved, the top three teams will be invited to present their algorithms at this workshop. We plan to share the details with participants as soon as they are finalized.
For more information on IEEE Quantum Week 2024, please visit the website https://qce.quantum.ieee.org/2024/.
Problem
Quantum chemistry is considered one of the most promising fields for considering practical applications of Noisy Intermediate-Scale Quantum (NISQ) devices and algorithms. The ground state energy of a molecule is an important quantity for understanding its properties and behavior, and many quantum chemistry studies focus on the ground state energy of individual atoms or molecules.
In QAGC, the task of participants is to calculate the ground state energy of a model (Hamiltonian) which we have prepared. Since the focuses of QAGC are on the industrial application and defining evaluation criteria for appropriate performance comparison of NISQ algorithms, the hamiltonian should have some properties as follows:
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Has similar properties as the molecular Hamiltonian used in quantum chemistry.
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In order to evaluate algorithms in large qubit systems that cannot be simulated in classical computers, the exact value of ground state energy of this hamiltonian can be calculated classically for the arbitrary size of the system.
We have prepared an orbital-rotated one-dimensional Fermi-Hubbard model. The hamiltonian of this model satisfies all of these properties.
For further details, please refer to the following paper.
Evaluation
All the proposed algorithms are evaluated by the accuracy which is the absolute difference of proposed results and the exact solution.
Rules
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The size of the system in evaluation will be 28 qubits.
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The algorithm is evaluated by using the sampling simulator that reflects the properties of the NISQ device.
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The number of shots that participants can use during sampling will be limited.
Score
The score S is calculated as the average accuracy computed from each absolute error over 10 runs of the algorithm. The smaller the score, the higher the ranking you can achieve.
Sampling simulation
In order to explore the practical application of NISQ devices and to visualize the bottlenecks in their use, it is necessary to perform simulations that reflect the features of NISQ devices in systems with enough qubits to address practical problems.
In QAGC, the participants need to use a sampling simulator we have provided. In this sampling simulator, quantum circuits are internally converted to Matrix Product State (MPS) and sampled using the MPS simulator, which is faster than ordinary simulators. This enables sampling simulation at 28 qubits, which is difficult to achieve with ordinary simulators.
In addition to this, noise is an important feature of NISQ devices, and it is necessary to consider how to deal with noise when considering the practical use of NISQ devices. Therefore, in this simulator, the approximation error in converting the quantum circuit to MPS is regarded as noise, and a simulation with noise at 28 qubits is performed. Note that the noise in this simulator comes from a different source than the noise in the NISQ device.
Available Packages
The following Python software library can be used in QAGC.
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QURI Parts (https://quri-parts.qunasys.com/)
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Qiskit (https://qiskit.org/)
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Amazon Braket Python SDK (https://amazon-braket-sdk-python.readthedocs.io/en/latest/#)
QURI Parts is an open-source quantum computing library that is modular, efficient, and platform-independent, developed by QunaSys.
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Platform-independent: Run one algorithm code on various simulators and platforms.
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Modularity and Scalability: Combine parts to create your own algorithm, and easily create and use your own parts.
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High-speed: Classical processing and simulator calls associated with quantum computing are efficient. It is the fastest platform-independent library using Qulacs.
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Open source: Released under Apache License 2.0.
All codes we have prepared are written by using QURI Parts.
In QURI Parts, there are codes to convert circuits of Braket and circuits and operators of Qiskit and Cirq to QURI Parts circuits and operators. Therefore, when implementing with Braket, Qiskit, and Cirq, these conversion codes can be used to take advantage of the sampling features provided. We ahave provided some example codes of these conversion codes in the tutorials folder.
Version
The version of the main package used in the challenge for participants will be fixed as follows:
python >= 3.9.8, <=3.11
quri-parts == 0.16.1
quri-parts-braket==0.16.1
quri-parts-cirq==0.16.1
quri-parts-itensor==0.16.1
quri-parts-openfermion==0.16.1
quri-parts-qiskit==0.16.1
qiskit == 0.41.1
cirq == 1.1.0
amazon-braket-sdk == 1.66.0
openfermion == 1.5.1
numpy == 1.23.5
juliacall >= 0.9.12
# following package is used in example codes
# scipy >= 1.9.1
Please refer to the requirements.txt in the repository.
If you use a version other than the specified one, or use other packages, please specify the name of that package and its version in the issue to be registered when submitting.
How to submit
First, please apply from here.
The participants' code will be submitted as an issue using this template summarizing your project.
The GitHub repository of QAGC :
https://github.com/QunaSys/quantum-algorithm-grand-challenge-2024
Specifically, this issue should contain:
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Team name: Your team's name
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Team members: Listup all members name
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Project Description: A brief description of your project (1-2 paragraphs).
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Presentation: A link of presentation with slides of your team’s hackathon project.
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Source code: A link to the final source code for your team's hackathon project (e.g., a GitHub repo).
The score will be calculated by the management side, and the rankings will be determined and published on the score page.
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Participants can submit their work as many times as they want during the period of QAGC.
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Participants can form teams with members.
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Submitted code is evaluated once a week and rankings are presented along with scores.
Notes on submission
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The participants's code can be viewed by other participants.
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If for some reason you do not wish to make the code public, please send the reason and the code directly to the management (qagc@qunasys.com). If this reason is accepted, your score will be calculated and your ranking determined without publishing your code.