Top Tweets for #QSS22
Science and technology has enabled us to study our universe more deeply.
@JarrodMcclean presents recent results showing how quantum computers could enable us to reveal aspects of our universe that would be invisible without this technology. → https://t.co/9VeCtv2xJJ #QSS22
In this #QSS22 video, our Research Scientist, Nicholas Rubin, presents numerical simulation evidence of a quantum advantage boundary for a chemical simulation challenge to show how quantum algorithms can be used in various industries.
Watch here → https://t.co/U3sE8NMruK
Maria Spiropulu, Professor of Physics at Caltech , presented a deep dive at #QSS22 on how we use quantum computing for fundamental physics.
Watch Maria's talk here → https://t.co/zmEiq7wes7
Learn about the work done by our Chip Architecture and Fabrication team to enable a distance-5 surface code experiment on a 72 qubit processor, specifically in managing yield, performance, and parameter spreads.
Hear from @ofer_naaman at #QSS22 → https://t.co/dqGMijkoD5
Learn how the correlation matrix tool can be used to determine the weights of error edges (including hyper-edges) that are input parameters to decoders.
Juan Atalaya, a Senior Research Scientist breaks this down in his #QSS22 talk here. → https://t.co/uwRpFi5T5R
Here's a look at the high level concepts behind initial device calibration and maintenance. → https://t.co/tCvtXgL107
Sabrina shows how we applied our calibration infrastructure to provide a high performing and stable platform for our recent surface code demonstrations.
#QSS22
See the power of using a cryptographic leash as a classical verifier to level the playing field in Umesh Vazirani's talk. → https://t.co/NPtUxYU4hA
Umesh does a deep dive into quantum supremacy, quitbit certification protocol, and more.
#QSS22
To accurately predict the performance of a fault-tolerant quantum memory, comprehensive numerical models are needed.
Dvir Kafri, our Senior Research Scientist discusses the challenges in developing these models for error correction experiments. → https://t.co/52lb9MSHHO
#QSS22
Google Quantum AI Research Scientist, Alexis Morvan,
talks about our work where we show experimental evidence for bound states of interacting photons and discovers their stability beyond the integrability limit.
Watch #QSS22 here → https://t.co/dyOoLlca6Q
We performed an experiment recently where we studied majorana edge modes on quantum processors.
Google Research Scientist, Xiao Mi shares our findings at #QSS22.
Watch 'Noise-resilient Majorana edge modes on a chain of superconducting qubits' → https://t.co/gZBxKUmC3E
Get an introduction to surface codes. ↓
In Alexei Kitaev's #QSS22 talk, you'll learn about the toric code and surface codes, hear their physical interpretation, and get a better understanding of logical error scaling.
Learn more. → https://t.co/pEIdqSfBUA
Hear about Australia's #QuantumComputing community and future opportunities for global action in this #QSS22 keynote session with Australia's Chief Scientist, Dr. Cathy Foley.
Tune in ↓ https://t.co/prGuPEXAX9
Ready to explore how to use quantum learning algorithms to quantify and understand aspects of quantum chaos and more?
Watch Jordan Cotler's #QSS22 talk here. → https://t.co/infpaV7bE4
Learn about the latest research and results in #QuantumComputing at this year's #QSS22.
Amira Abbas, a Google PhD Fellow and PhD candidate at the University of KwaZulu-Natal, joined us to speak about quantum machine learning research.
Tune in → https://t.co/kXqoPLctHe
Hear from @quantum_aram, Professor of Physics, MIT, as he explains quantum walks on hierarchical graphs, and their associated speedups. Watch Aram's #QSS22 talk → https://t.co/5dZpqxwChP
Learn how we go about building our models and use the data to help us project future performance in this #QSS22 talk by our Research Scientist, @DriptoDebroy. → https://t.co/HfaPLSEzUv
One of our goals is to achieve better error suppression as we increase the system size on our chips.
Google Quantum AI Hardware Engineer, Kenneth Lee discusses the system performance improvements we've made in our recent work.
Watch #QSS22 → https://t.co/A2dI4ttBkq
Check out the work that went into decoding experimental surface code data in @MikeNewmQuantum's #QSS22 talk. → https://t.co/a5qcnSCnEg
Mike analyzes the behavior and performance of different decoders on a real surface code data obtained from a Sycamore quantum processor.
Transmon vs. Fluxonium ↓
Hear about Superconducting qubits for quantum computation in this #QSS22 talk by Michel Devoret, F. W. Beinecke Professor of Applied Physics at Yale University. → https://t.co/eyByzYiB3Z
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