| Classical computers use individual bits which store information as binary 0 or 1 states. However, the power of classical computers is becoming saturated which prevents the most complex problems from being solved. Quantum computing offers an exciting solution as quantum bits (called qubits) can exist as a superposition of both 0 or 1. This greatly increases the potential performance of quantum computers as the computing power increases exponentially with the number of qubits. Because of the difficulty in building quantum computers, they are not readily available to the general public. However, IBM scientists have built the IBM Q experience, a first-of-a-kind quantum computing platform delivered via the IBM Cloud and accessible by desktop or mobile devices. It enables users to run experiments on IBM’s quantum processor, work with individual qubits, and explore tutorials and simulations of the wondrous possibilities of quantum computing. This project offers undergraduate students first-hand experience in developing algorithms that can be executed on a IBM-Q to solve real world problems at the intersection of physics and economics. Ultimate goal of the project is the implementation of an algorithm able to solve a real world problem with potential applications towards weather prediction, network security, drug discovery, and materials design, just to name a few. First hand experience is provided by already existing research experience with IBM-Q in the group of Prof Jung and others. Successful candidates will learn to use the simulation environment of the IBM-Q, which allows to study the performance and application of quantum algorithms. Potential first algorithm to implement and study is the Grover search algorithm. Expected Student Contributions: 1. Benefit from existing experience in the research groups and quickly become prolific in using the simulation framework “IBM Qiskit Aer”. 2. Apply this knowledge to develop algorithms to solve real world problems, e.g. starting with the Grover algorithm. Most optimal progress is made with candidates who already have participated in the previous DURI project, but new student are equally welcome and encouraged to apply. Quick progress is possible due to existing experience and the significant time commitment during summer. Students are expected to work closely with the Quantum. Weekly meetings prepare/teach participants in the relevant background information on IBM-Q and potential algorithms. Simulation via IBM-Q Qiskit are to be carried out first, followed by application on a real IBM-Q. Intern will implement algorithms at the intersection of physics and economics applications. The intern will be embedded in the usual weekly meetings and reporting. |
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