Explore Quantum Computing (QC) by modeling and simulating quantum bits with Hamiltonian energy operator on various HPC platforms. Study permutation problems and their computation complexity. Formulate and compare performance on permutation problem solving among Quantum-Simulation on HPC, Graphical Modeling, Cloud-based Quantum Annealing and parallel programming on various GPU/FPGA-accelerated HPC platforms.
Job Description
1. Learn and program Hamiltonian quantum operator for quantum bit simulation. 2. Learn to program and compare performance on various GPU/FPGA-accelerated HPC platforms. 3. Explore cloud-based Quantum Annealer/Computers. 4. Complexity analysis and efficient algorithm design for Sudoku/TSP permutation problem. 5. Work as XSEDE student campus champions and teaching/equipment assistants for monthly XSEDE training.
Computational Resources
1. XSEDE supercomputing Clusters with GPU/FPGA accelerators. 2. Additional FPGA-accelerated HPC clusters at TACC. 3. Graphical modeling based simulation software. 4. Cloud-based Quantum Computing of D-Wave and IBM.
Contribution to Community
Position Type
Apprentice
Training Plan
Training Approach – Building Quantum Constraint Thinker/Solver based on student's strength and interest within QC project scope
Training Format - weekly meetings + self-guided tutorials/papers/websites + classes + hands-on programming
4/2-3/2019 XSEDE Big Data & ML Workshop 12 hrs Outcome: TSP/Sudoku on ML
4/10/2019 Compare QC HPC Performance 6 hrs Outcome: Performance stat
4/17/2019 Final poster/PPT/report 6 hrs Outcome: Documentation
Student Prerequisites/Conditions/Qualifications
1. Interest and background in quantum mechanics and quantum computing.
2. Thrive on challenge in complex problem solving.
3. Multidisciplinary team synergy - Math/Physics/Mechanics/Computer...
4. Effective communication.