Quantum Algorithms, Information, and Learning Workshop
May 24, 2022
9:30am - 4pm (Eastern Time Zone, U.S.A.)
Recorded talks are available as a Center for Science of Information YouTube playlist or individually by presentation title (see below).
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
Useful Links:
Center for Science of Information, NSF Science & Technology Center
Book Series: World Scientific Series on Quantum Algorithms, Information, and Learning
Conference at UIUC: 17th Annual Theory of Quantum Computation, Communication and Cryptography (TQC)
Schedule at a Glance (Eastern time zone, USA): Presentation recordings available for viewing at each link.
Wojciech Szpankowski (CSoI and Purdue)
Opening remarks
Sandeep Pradhan (U of MI)
"Computation using structured measurements in Quantum Systems"
"Improved Approximation Algorithms for Bounded-degree Local Hamiltonians"
Workshop Speakers (listed in presentation order for the workshop):
Sandeep Pradhan
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Mohsen Heidari
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Eric Chitambar
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Anurag Anshu
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Graeme Smith |
3d quantum image Credit: © Jackie Niam – stock.adob.com |