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Center for Science of Information (CSoI): Quantum Algorithms, Information, and Learning Workshop

May 24, 2022
9:30 AM - 4:00 PM


May 24, 2022
9:30am - 4pm (Eastern Time Zone, U.S.A.)

Zoom Link:

The past few decades have witnessed significant advances in quantum technologies with a few hundred qubit capacities. Quantum computers are at the cusp of surpassing contemporary and even future supercomputers in achieving scientific breakthroughs. In addition, recent achievements in quantum algorithms and information processing to collect, store, and process qubits endow us with a more powerful ability, learning from quantum information. The leading applications of the so-called "Noisy Intermediate Scale Quantum" (NISQ) computers are expected to be the simulation of physical systems, quantum machine learning, and, more generally, optimization. However, employing noisy quantum computers for such applications raises major challenges at experimental and theoretical fronts. Algorithms realizable on near-term quantum computers need to comply with quantum mechanical postulates, address the device imperfections (e.g., gate infidelity and qubit decoherence), and be scalable in terms of circuit utilization.

This workshop aims to present the current solutions and key questions in quantum information and computation. The workshop touches on both computer science and quantum physics foundations to formalize a common framework for the challenges and solutions in quantum computing. Moreover, it discusses relevant ideas from learning theory, quantum mechanics, and information theory and covers recent progress on quantum algorithms, information, and machine learning. The workshop's critical questions regarding the potentials of quantum computers are about (i) models for quantum machine learning, (ii) approaches for quantum algorithms on noisy devices, and (iii) frameworks for leveraging quantum information and learning from quantum data.

Workshop Organizers: 

  • Mohsen Heidari, Center for Science of Information, Purdue University, and Indiana University
  • Wojciech Szpankowski, Center for Science of Information, Purdue University

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