Narendra Hegade

Physicist | Quantum Computation and Simulation. Head of Innovation @KipuQuantum

[Physical Review Research @PhysRevResearch]

Bias-field digitized counterdiabatic quantum optimization, Alejandro Gomez Cadavid et al #Quantum #QuantumInformation https://t.co/hLisg4hzVW

[Narendra Hegade @NarendraHegade]

@DulwichQuantum https://t.co/6YtqbXX2e6

Here's D-Wave's reply!

[Narendra Hegade @NarendraHegade]

@MvsCerezo https://t.co/d55z07SOgp
Here it is!

[Narendra Hegade @NarendraHegade]

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.

[Narendra Hegade @NarendraHegade]

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" https://t.co/PUl4p2y3Id

[Narendra Hegade @NarendraHegade]

Even with today’s noisy quantum computers, our results show we’re inching closer to solving problems that classical computers simply can’t handle.

[Narendra Hegade @NarendraHegade]

@MvsCerezo Interesting! I heard a similar debate between Scott and Lukin. Is this recorded and available online?

[Narendra Hegade @NarendraHegade]

@TQPSchilling @AGTheoChem @MCQST_cluster @MunichQuantum @LMU_Muenchen @researchbavaria Congrats! 🎉

[Narendra Hegade @NarendraHegade]

@DulwichQuantum https://t.co/qPtbtv8yso

[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
https://t.co/DsonrFrEsO

[Narendra Hegade @NarendraHegade]

@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.

[Narendra Hegade @NarendraHegade]

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).

[Narendra Hegade @NarendraHegade]

@PedramRoushan @KikeSolanoPhys @qmisanz @LucasLamata @Google Thanks for your reply 🙏. We will DM you.

[Narendra Hegade @NarendraHegade]

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
https://t.co/58sC7l84kJ

[Narendra Hegade @NarendraHegade]

5/5 Thanks to all the co-authors for the great collaboration!
@agm668 @ArchismitaD Anton Simen @KikeSolanoPhys @KipuQuantum

[Narendra Hegade @NarendraHegade]

🧵 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! https://t.co/kSptUytNbI

[Narendra Hegade @NarendraHegade]

🧵 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.