Building a Quantum Ecosystem Through Education and SDK Challenges

Anne Matsuura is the director of Quantum Applications and Architecture at Intel Labs.

Highlights:

• Intel continues its efforts to make quantum computing more accessible to the developer community through educational programs and Intel® Quantum SDK challenges.
• Five universities that received grants from Intel in 2022 have now established quantum curricula based on the Intel Quantum SDK.
• The work of three teams has been recognized as winners of the 2024 Intel Quantum SDK Challenge.
  
  

Intel is continuing efforts to make quantum computing more intuitive and accessible to the developer community through support of educational programs and a series of Intel Quantum SDK challenges. In 2022, Intel provided grants to five universities to develop quantum course curricula to share with additional universities and proliferate its use across academia. Deggendorf Institute of Technology in Germany, The Ohio State University, University of Pennsylvania, and Keio University in Japan have established quantum centers to encourage students to explore programming applications for quantum computing, while Pennsylvania State University has developed coursework using the Intel Quantum SDK.

Not only is Intel collaborating with universities to develop quantum courses, the company also is supporting coding competitions to build a quantum ecosystem. Hosted by the Deggendorf Institute of Technology, the Intel Quantum SDK Challenge is open to scientists, researchers, and professionals of all backgrounds. Participants in the second annual challenge were tasked with identifying and solving a real-world problem using the Intel Quantum SDK 1.0 as the central tool.

The winners of the 2024 Intel Quantum SDK Challenge are:

• First place: Shraddha Mahesh Thanki (India) and Tejas Shinde (Finland) received top honors for their work on Preliminary Lattice Boltzmann Method Simulation Using Intel Quantum SDK. The quantum lattice Boltzmann method (LBM) is applied to examine the novel intersection of quantum computing and computational fluid dynamics (CFD). The team used the SDK to tackle tricky transport phenomena such as heat and mass transfer in computational physics. They focused on a simple one-dimensional advection-diffusion equation to demonstrate the efficacy and potential of the quantum LBM algorithm, as derived by Ljubomir Budinski, in a quantum computing environment.
  
  
• Second place: Digvijaysinh Ajarekar (India) and Suhaib Al-Rousan (Jordan) were recognized for their work on Advancing Image Classification: Integrating NAQSS Encoding with Hybrid Quantum-Classical PQC Models via Intel Quantum SDK. The team introduced the use of normal arbitrary quantum superposition state (NAQSS) for encoding images into a quantum circuit. Learning of trainable parameters for image classification is achieved by using layers of post-quantum cryptography (PQC) with a hybrid optimizer.
  
  
• Third place: Shraddha Thanki (India) and Harish Rajendran (India) were recognized for their work on Implementation of Hybrid Quantum Classical Library for Molecular Energy Simulation in Intel Quantum SDK. The team explored the implementation of a Hybrid Quantum Classical Library (HQCL) developed by Intel Labs to enhance the productivity of variational quantum algorithms (VQA) in quantum chemistry. In conjunction with simulated annealing, the team applied the variational quantum eigensolver (VQE) algorithm using HQCL to determine the minimum energy eigenvalue of a hydrogen molecule.

After the Intel Quantum SDK Challenge, the work of first place participants Thanki and Shinde has been accepted for publication at ISC High Performance 2024 and the paper by second place participants Ajarekar and Al-Rousan has been accepted at the International Workshop on Advanced Computing and Analysis Techniques in Physics Research (ACAT 2024).