Narendra Hegade retweetledi
Bias-field digitized counterdiabatic quantum optimization, Alejandro Gomez Cadavid et al #Quantum #QuantumInformation go.aps.org/42DXYft
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Narendra Hegade
396 posts
Narendra Hegade
@NarendraHegade
Physicist | Quantum Computation and Simulation. Head of Innovation @KipuQuantum
Berlin, Germany Katılım Ekim 2012
421 Takip Edilen707 Takipçiler
@DulwichQuantum linkedin.com/posts/trevor-l…
Here's D-Wave's reply!
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Summary of the situation so far:
* arxiv.org/abs/2403.00910
* arxiv.org/abs/2503.05693
* arxiv.org/abs/2503.08247
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Waiting for the DWave reply
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Miles Stoudenmire@MStoudenmire
In a new preprint arxiv.org/abs/2503.05693, led by Joseph Tindall & Antonio Mello at CCQ, we simulate annealing of disordered quantum magnets 🧲and in many cases find better accuracy than recent results from D-Wave devices and leading classical methods (arxiv.org/abs/2403.00910).
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Kudos to the entire @KipuQuantum team and our amazing collaborators—stay tuned for more exciting results! @agm668 @pranav_xd @KikeSolanoPhys @AdolfodelCampo7 and all the co-authors.
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Even with today’s noisy quantum computers, our results show we’re inching closer to solving problems that classical computers simply can’t handle.
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Simulating quantum critical dynamics isn’t just an exciting research problem—it has huge industrial implications for material design. I’m excited to share our latest work on arXiv: "Digitized counterdiabatic quantum critical dynamics" arxiv.org/abs/2502.15100
GIF
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@MvsCerezo Interesting! I heard a similar debate between Scott and Lukin. Is this recorded and available online?
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The panel is getting wild:
Jens Eisert@jenseisert
The panel discussion on the “future of quantum computing” at #qtml2024 features @quantum_aram, @andrewmchilds, Scott Aaronson, and Ed Farhi delivers a number of highly insightful points. To date, it is not so clear what #quantumcomputing can deliver for the the unstructured problems in common in #machinelearning.
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I am deeply grateful for having been awarded the Hans G. A. Hellmann by @AGTheoChem at the #STC24
@MCQST_cluster @MunichQuantum @LMU_Muenchen @researchbavaria
That’s a great opportunity for me to thank all my collaborators, team members and:
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Pedram Roushan@PedramRoushan
New hope for quantum optimization? Optimization, as one of the primary applications of quantum computers has a third (or fourth?) life. My colleagues developed an approach that provides an exponential speedup over known classical methods for some problems arxiv.org/abs/2408.08292
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What you can actually expect from quantum algorithms when it comes to optimization.
arxiv.org/abs/2408.07086
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@MJBiercuk @dallairedemers Yes, it would be great to combine some of these techniques with better optimization algorithm like digitized counterdiabatic quantum optimization (DCQO), which already shows superior performance than QAOA.
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@NarendraHegade @dallairedemers We definitely leave open the possibility to use much better algorithms. We don't make algos so just use what exists and focus on HW execution.
But with the combo of error suppression and new variational update strategies the important thing is we get the right answer.
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While I'm usually skeptical of QAOA, those results look very good.
We are way past the stage where the number of samples is comparable to the number of configurations, yet the convergence is excellent.
Michael J. Biercuk@MJBiercuk
It's finally here! New result that show for the first time that @IBM #quantumcomputers enabled with @qctrlHQ performance management software can outperform previous results from trapped ions AND quantum annealers for quantum optimization! arxiv.org/abs/2406.01743
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Error suppression techniques are definitely needed. Most importantly, better algorithms are also required. The CD protocol surely performs better here (as mentioned in the discussion section of the paper). In addition, we have tested it experimentally for even more complex problems at this scale (soon in arXiv).
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@NarendraHegade NISQ without quantum control feels like tying shoelaces with boxing gloves.
Do you think the distributions get even narrower with counter-adiabaticity?
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@PedramRoushan @KikeSolanoPhys @qmisanz @LucasLamata @Google Thanks for your reply 🙏. We will DM you.
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@NarendraHegade @KikeSolanoPhys @qmisanz @LucasLamata @Google My apologies. Please tell us which works needs to be added to our citations and we will take a look.
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Amazing work by Google and others on digital-analog quantum simulation! The authors surely know Kike @KikeSolanoPhys and his group's @qmisanz @LucasLamata work on DAQS and DAQC, but unfortunately, there's not a single citation/credit
@Google @PedramRoushan
arxiv.org/abs/2405.17385
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5/5 Thanks to all the co-authors for the great collaboration!
@agm668 @ArchismitaD Anton Simen @KikeSolanoPhys @KipuQuantum
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🧵 4/5 BF-DCQO also achieves two orders of magnitude improvement in ground-state success probability and a 1.3x better approximation ratio than QAOA for the problem sizes studied, showcasing its potential in outperforming standard variational quantum optimization algorithms.
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🧵 1/5 Tired of variational quantum algorithms like QAOA due to trainability issues on noisy quantum computers? Check out our new work—a purely quantum approach to tackle combinatorial optimization problems! Featuring experimental results with 100 qubits! arxiv.org/abs/2405.13898
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