174 Registered
Allowed team size:
**
3 - 7
**

Winners are announced.

Signup and Team Formation

Online

starts on:

Feb 15, 2021, 06:00 AM UTC (UTC)

ends on:

Feb 18, 2021, 09:00 AM UTC (UTC)

Building and Presenting

Online

starts on:

Feb 18, 2021, 10:00 AM UTC (UTC)

ends on:

Feb 19, 2021, 06:00 AM UTC (UTC)

Winning Team

Second Prize

by
mutQoin

Theme:

Quantum (Qiskit)

Third Prize

by
Solvers

Theme:

Quantum (Qiskit)

Community Choice Award

by
Quanputing

Theme:

Quantum (Qiskit)

Figuring out where to start is hard sometimes. We would love for you and your team to come up with your own project! However, if you need some help, here’s a list of projects that our event coaches have suggested.

Feel free to use, remix, or pick apart these ideas. All are encouraged! Most include the name of the coach who pitched it as well, so you know who to reach out to over Slack for help.

**Compute qubit permutations in the StochasticSwap mapper**- (Paul Nation)**Create a tutorial for Iterative Phase Estimation (IPE) algorithm**- (Hwajung Kang)**Solving classical puzzles by a quantum computer**- (Atsushi Matsuo)**QBlockChain with Quantum Random Number Generator**- (Soyoung Shin)**Create a Quantum Volume circuit generator for reproducible results**- (Paul Nation)**Implement a special converter of Quadratic Program of Qiskit Optimization**- (Takashi Imamichi)**Design your optimization problem and solve it with Qiskit Optimization**- (Takashi Imamichi)**(let beginners teach beginners) Let's make Quantum Computing Wiki by interactive Jupyter Notebook**- (Soyoung Shin)**Write a set of quantum computing command-line utilities following the UNIX Philosophy**- (Samuel Choi)**Exploring Hybrid quantum-classical Neural Networks with PyTorch and Qiskit**- (Kifumi Numata)- Classify the numbers you wrote.
- Classify the numbers other than 0 and 1.
- Add more quantum layers to improve the algorithm.
**Metal Project 1A: Designing a simple two-qubit chip**- (Yuri Kobayashi)**Metal Project 1B: Designing a simple three-qubit chip**- (Yuri Kobayashi)**Metal Project 1C: Designing a four-qubit chip**- (Yuri Kobayashi)**Metal Project 2: Comsol Renderer**- (Yuri Kobayashi)**Compute if two circuits are equivilent to each other**- (Paul Nation)**Create your design of PQC and analyze its Expressibility and Entanglement Capacity**- (Siheon Park)**QPong 1.0**- (Junye Huang)**EntangledMeasurementGrouper**- (Ikko Hamamura)**Demonstration of quantum violation of realism**- (Ikko Hamamura)

Compute the permutation of qubits from their initial placements, e.g. [0,1,2,3,4], to their permuted positions, e.g. [1,2,0,4,3] after being passed through the StochasticSwap mapper.

See: https://github.com/qiskit-community/qiskit-hackathon-korea-21/issues/2 for more details.

The "length" of a quantum circuit is the primary factor when determining the magnitude of the errors in the resulting output distribution; quantum circuits with greater depth have decreased fidelity. Therefore, implementing algorithms based on shallow depth circuits is of the great importance in near-term quantum computing. Iterative Phase Estimation (IPE) algorithm is one algorithm for estimating quantum phase called the Iterative Phase Estimation (IPE) algorithm which requires a system comprised of only a single ancillary qubit and evaluate the phase through a repeatative process.

See: https://github.com/qiskit-community/qiskit-hackathon-korea-21/issues/3 for more details.

We can solve classical puzzles by a quantum computer. Examples of classical puzzles are "8 queens" or "Sudoku". We can decide what puzzle we want to solve. We can choose a solving method from Grover's algorithm, VQE or QAOA (For VQE and QAOA, first, we need to formulate a puzzle).

See: https://github.com/qiskit-community/qiskit-hackathon-korea-21/issues/4 for more details.

Let's build a simple blockchain application with a powerful quantum computer and Cloud technology!

See: https://github.com/qiskit-community/qiskit-hackathon-korea-21/issues/5 for more details.

Quantum Volume (QV) is a holistic benchmark invented at for gate-based quantum computing platforms. This metric has gained traction amongst hardware makers as one of the key performance metrics for near-term quantum computers. However, it is impossible to reproduce benchmark results from literature because there is no unique way to identify which QV circuits were executed.

This project aims to build a QV program that deterministically generates one or more QV circuits in a platform independent manner. The QV circuits are generated using random numbers, so this would involve a generator that takes a seed value and offset (number of times the random generator has been called since seeding) and returns a circuit that is identical across all computing platforms. Multiple circuits would be generated in sequence starting at a given seed and offset starting point.

See: https://github.com/qiskit-community/qiskit-hackathon-korea-21/issues/6 for more details.

Implement a new converters of QuadraticProgram of Qiskit Optimization to translate some special types of constraints into penalties of the objective function of QUBO more efficiently than generic converters of Qiskit Optimization.

See: https://github.com/qiskit-community/qiskit-hackathon-korea-21/issues/7 for more details.

Qiskit optimization automatically generates an Ising Hamiltonian for an optimization problem and you can solve it with quantum computers by applying VQE or QAOA. Let's come up with a unique optimization problem and solve it with quantum computers.

See: https://github.com/qiskit-community/qiskit-hackathon-korea-21/issues/8 for more details.

Teaching is one of the best ways to learn something. We have a lot of materials to learn quantum computing, already, but let's build an easy Quantum Computing wiki by Jupyter notebook which everybody can easily access without any account.

See: https://github.com/qiskit-community/qiskit-hackathon-korea-21/issues/9 for more details.

Large toolboxes are useful. It helps beginners to learn, and experts to respond in many situations. However, sometimes our toolkit just requires some minimalism. If the program is small and it works well with other programs, it can be a building block of many other brilliant programs. My thoughts about minimal and modular quantum software

See: https://github.com/qiskit-community/qiskit-hackathon-korea-21/issues/11 for more details.

Let's try and explore Hybrid quantum-classical Neural Networks with PyTorch and Qiskit:
https://qiskit.org/textbook/ch-machine-learning/machine-learning-qiskit-pytorch.html

Examples:

See: https://github.com/qiskit-community/qiskit-hackathon-korea-21/issues/12 for more details.

The designing of a simple two qubit chip using Qiskit Metal.

See: https://github.com/qiskit-community/qiskit-hackathon-korea-21/issues/13 for more details.

The designing of a simple three qubit system using Qiskit Metal.

See: https://github.com/qiskit-community/qiskit-hackathon-korea-21/issues/14 for more details.

The designing of a four qubit system using Qiskit Metal.

See: https://github.com/qiskit-community/qiskit-hackathon-korea-21/issues/15 for more details.

One key aspect of Qiskit Metal is that it allows for easy translation of a design into external software in an optimal and native manner. This is accomplished via Renderers. Currently, Metal has renderers for Ansys Electronic Desktop, and for GDS file creation, but this project is focused on creating one for Comsol.

See: https://github.com/qiskit-community/qiskit-hackathon-korea-21/issues/16 for more details.

It is often of interest to determine if circuits are equivalent to each other, for example when looking at the output from circuit compilation or when comparing different implementations of the same algorithm. This requires determining if the circuits are unitarily equivalent, possibly up to a collection of different transformations. This project will create a basic checker for this.

There is a PR in Qiskit for this (Qiskit/qiskit-terra#5700) but I think it is beneficial to consider a different implementation route [while also learning some about operators and Qiskit :) ]

See: https://github.com/qiskit-community/qiskit-hackathon-korea-21/issues/17 for more details.

The good ansatz generation is crucial for any quantum variational algorithm like QAOA and VQE in the NISQ era. Sim at el analyzed various forms of Parameterized Quantum Circuits(PQC) from past studies by introducing the concept of Expressibility and entangling capacity. Create your unique PQC and compare it with benchmark circuits in the paper.

See: https://github.com/qiskit-community/qiskit-hackathon-korea-21/issues/18 for more details.

Feb 28 this year is the 2nd anniversary of QPong. Let's make QPong even more awesome (& to reach 1.0 finally!)!

See: https://github.com/qiskit-community/qiskit-hackathon-korea-21/issues/19 for more details.

Reduction of the number of measurements is one of the most important topic for variational quantum algorithms. In Qiskit, Abelian grouper was implemented for the evaluations of expectation values by joint measurement of tensor product basis (TPB). This project enhances the grouper by using entangled measurements.

See: https://github.com/qiskit-community/qiskit-hackathon-korea-21/issues/20 for more details.

Einstein, Podolsky, and Rosen (EPR) pointed out that quantum theory (QT) is not a "complete" theory[1]. Well-known Bell[2] and Clauser-Horne-Shimony-Holt[3] inequalities showed inconsistency between the local realism and QT, and Bell[4] and Kochen-Specker[5] discussed the inconsistency between noncontextual realism and QT. In this project, our goal is a demonstration of such a violation on a quantum computer.

See: https://github.com/qiskit-community/qiskit-hackathon-korea-21/issues/21 for more details.

If you want to pitch your own project idea but are still looking for some inspiration, here's a very helpful video from Anastasia Marchenkova, one of our Qiskit Community members that guides you through choosing projects with quantum computing even if you're a total beginner.

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