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Scalable approaches for ion trap quantum computing

Summary
Jonathan Home (ETH Zürich)
Spilker 232
May
19
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Content

Abstract: Quantum computing requires implementation of high fidelity control operations across an interconnected array of qubit systems. The requirements of quantum error correction put stringent limits on tolerable errors as well as introducing a larger overhead in the number of qubits. In this talk I will describe two approaches to the challenges of scaling trapped-ion quantum computers. The first is in the optical delivery, where we have recently demonstrated the first multi-qubit gates between ions using light delivered from trap-integrated waveguides. In further work, we have been investigating further possibilities arising from this technology, including the use of optical standing waves generated on-chip and protocols for entanglement generation. A second generation of photonic chips recently ordered from the foundry features modifications for blue light, tightly focused laser beams and better ion performance. I will then outline a new approach to implementing large scale quantum computing with trapped-ions based on micro fabricated Penning traps, also giving an insight into the physics of these systems and their advantages for scaling up. 

Bio: Jonathan Home is Professor for Experimental Quantum Information at the ETH Zürich. He performed his PhD in Oxford with Andrew Steane before working as a post-doc with David Wineland at NIST.  He currently leads the Trapped-Ion group at ETH Zürich, which has produced pioneering demonstrations of quantum error correction, squeezed state generation and oscillator, as well as exploring new directions for scaling up trapped-ion quantum computers. His group is active in outreach, recently enabling the public to view atoms with the naked eye at the Swiss Science Museum. Jonathan’s work has been recognised with multiple awards, including the APS Landauer-Bennett Award, an ERC Consolidator Grant, and a TED Fellowship. 

Zoom Meeting ID: 914 8268 2357; Password: 999112.