Kunal Sharma
@kunalq.bsky.social
Senior Research Scientist @IBM Research | Editor @Quantum Journal
Reposted by Kunal Sharma
Reposted by Kunal Sharma
Thrilled to share that our paper on preparing matrix product states with adaptive circuits was selected for inclusion in the International Year of Quantum Collection in PRX Quantum. Quite humbling to see it listed among so many amazing papers from this year!
IYQ Collection – Impacting the Next DecadeIYQ Collection – Impacting the Next Decade
prxquantumcollection.org
March 14, 2025 at 1:42 PM
Thrilled to share that our paper on preparing matrix product states with adaptive circuits was selected for inclusion in the International Year of Quantum Collection in PRX Quantum. Quite humbling to see it listed among so many amazing papers from this year!
March 7, 2025 at 1:51 PM
I'm the worst host in NYC, according to @qzoeholmes.bsky.social but the Thai food/cocktails aren't bad!
February 12, 2025 at 1:58 AM
I'm the worst host in NYC, according to @qzoeholmes.bsky.social but the Thai food/cocktails aren't bad!
Reposted by Kunal Sharma
I am very excited that this work is out today on the arXiv: arxiv.org/pdf/2501.09702
We wondered for quite some time if a sample-based quantum diagonalization method could have convergence guarantees similar to phase estimation, while retaining the noise robustness of a sample-based method.
We wondered for quite some time if a sample-based quantum diagonalization method could have convergence guarantees similar to phase estimation, while retaining the noise robustness of a sample-based method.
January 17, 2025 at 9:37 PM
I am very excited that this work is out today on the arXiv: arxiv.org/pdf/2501.09702
We wondered for quite some time if a sample-based quantum diagonalization method could have convergence guarantees similar to phase estimation, while retaining the noise robustness of a sample-based method.
We wondered for quite some time if a sample-based quantum diagonalization method could have convergence guarantees similar to phase estimation, while retaining the noise robustness of a sample-based method.
Excited to share our latest results:
Sample-based Krylov Quantum Diagonalization arxiv.org/abs/2501.09702
This work was a collaboration between colleagues at IBM Research and Oak Ridge National Laboratory. Check it out!
Sample-based Krylov Quantum Diagonalization arxiv.org/abs/2501.09702
This work was a collaboration between colleagues at IBM Research and Oak Ridge National Laboratory. Check it out!
Sample-based Krylov Quantum Diagonalization
Approximating the ground state of many-body systems is a key computational bottleneck underlying important applications in physics and chemistry. It has long been viewed as a promising application for...
arxiv.org
January 17, 2025 at 6:03 PM
Excited to share our latest results:
Sample-based Krylov Quantum Diagonalization arxiv.org/abs/2501.09702
This work was a collaboration between colleagues at IBM Research and Oak Ridge National Laboratory. Check it out!
Sample-based Krylov Quantum Diagonalization arxiv.org/abs/2501.09702
This work was a collaboration between colleagues at IBM Research and Oak Ridge National Laboratory. Check it out!