Search SciRate

3 results for au:Colina_J in:quant-ph

Show all abstracts

Potential Applications of Quantum Computing at Los Alamos National Laboratory
Andreas Bärtschi, Francesco Caravelli, Carleton Coffrin, Jonhas Colina, Stephan Eidenbenz, Abhijith Jayakumar, Scott Lawrence, Minseong Lee, Andrey Y. Lokhov, Avanish Mishra, Sidhant Misra, Zachary Morrell, Zain Mughal, Duff Neill, Andrei Piryatinski, Allen Scheie, Marc Vuffray, Yu Zhang
Jun 12 2024 quant-ph arXiv:2406.06625v1

@misc{2406.06625, author = {Andreas Bärtschi and Francesco Caravelli and Carleton Coffrin and Jonhas Colina and Stephan Eidenbenz and Abhijith Jayakumar and Scott Lawrence and Minseong Lee and Andrey Y.~Lokhov and Avanish Mishra and Sidhant Misra and Zachary Morrell and Zain Mughal and Duff Neill and Andrei Piryatinski and Allen Scheie and Marc Vuffray and Yu Zhang}, title = {{P}otential {A}pplications of {Q}uantum {C}omputing at {L}os {A}lamos {N}ational {L}aboratory}, year = {2024}, eprint = {2406.06625}, note = {arXiv:2406.06625v1} }
PDF
The emergence of quantum computing technology over the last decade indicates the potential for a transformational impact in the study of quantum mechanical systems. It is natural to presume that such computing technologies would be valuable to large scientific institutions, such as United States national laboratories. However, detailed descriptions of what these institutions would like to use these computers for are limited. To help provide some initial insights into this topic, this report develops detailed use cases of how quantum computing technology could be utilized to enhance a variety of quantum physics research activities at Los Alamos National Laboratory, including quantum magnetic materials, high-temperature superconductivity and nuclear astrophysics simulations. The report discusses how current high-performance computers are used for scientific discovery today and develops detailed descriptions of the types of quantum physics simulations that Los Alamos National Laboratory scientists would like to conduct, if a sufficient computing technology became available. While the report strives to highlight the breadth of potential application areas for quantum computation, this investigation has also indicated that many more use cases exist at Los Alamos National Laboratory, which could be documented in similar detail with sufficient time and effort.
The computational power of random quantum circuits in arbitrary geometries
Matthew DeCross, Reza Haghshenas, Minzhao Liu, Enrico Rinaldi, Johnnie Gray, Yuri Alexeev, Charles H. Baldwin, John P. Bartolotta, Matthew Bohn, Eli Chertkov, Julia Cline, Jonhas Colina, Davide DelVento, Joan M. Dreiling, Cameron Foltz, John P. Gaebler, Thomas M. Gatterman, Christopher N. Gilbreth, Joshua Giles, Dan Gresh, et al (32)
Jun 05 2024 quant-ph arXiv:2406.02501v3

@misc{2406.02501, author = {Matthew DeCross and Reza Haghshenas and Minzhao Liu and Enrico Rinaldi and Johnnie Gray and Yuri Alexeev and Charles H.~Baldwin and John P.~Bartolotta and Matthew Bohn and Eli Chertkov and Julia Cline and Jonhas Colina and Davide DelVento and Joan M.~Dreiling and Cameron Foltz and John P.~Gaebler and Thomas M.~Gatterman and Christopher N.~Gilbreth and Joshua Giles and Dan Gresh and Alex Hall and Aaron Hankin and Azure Hansen and Nathan Hewitt and Ian Hoffman and Craig Holliman and Ross B.~Hutson and Trent Jacobs and Jacob Johansen and Patricia J.~Lee and Elliot Lehman and Dominic Lucchetti and Danylo Lykov and Ivaylo S.~Madjarov and Brian Mathewson and Karl Mayer and Michael Mills and Pradeep Niroula and Juan M.~Pino and Conrad Roman and Michael Schecter and Peter E.~Siegfried and Bruce G.~Tiemann and Curtis Volin and James Walker and Ruslan Shaydulin and Marco Pistoia and Steven.~A.~Moses and David Hayes and Brian Neyenhuis and Russell P.~Stutz and Michael Foss-Feig}, title = {{T}he computational power of random quantum circuits in arbitrary geometries}, year = {2024}, eprint = {2406.02501}, note = {arXiv:2406.02501v3} }
PDF
Empirical evidence for a gap between the computational powers of classical and quantum computers has been provided by experiments that sample the output distributions of two-dimensional quantum circuits. Many attempts to close this gap have utilized classical simulations based on tensor network techniques, and their limitations shed light on the improvements to quantum hardware required to frustrate classical simulability. In particular, quantum computers having in excess of $\sim 50$ qubits are primarily vulnerable to classical simulation due to restrictions on their gate fidelity and their connectivity, the latter determining how many gates are required (and therefore how much infidelity is suffered) in generating highly-entangled states. Here, we describe recent hardware upgrades to Quantinuum's H2 quantum computer enabling it to operate on up to $56$ qubits with arbitrary connectivity and $99.843(5)\%$ two-qubit gate fidelity. Utilizing the flexible connectivity of H2, we present data from random circuit sampling in highly connected geometries, doing so at unprecedented fidelities and a scale that appears to be beyond the capabilities of state-of-the-art classical algorithms. The considerable difficulty of classically simulating H2 is likely limited only by qubit number, demonstrating the promise and scalability of the QCCD architecture as continued progress is made towards building larger machines.
A Race Track Trapped-Ion Quantum Processor
S. A. Moses, C. H. Baldwin, M. S. Allman, R. Ancona, L. Ascarrunz, C. Barnes, J. Bartolotta, B. Bjork, P. Blanchard, M. Bohn, J. G. Bohnet, N. C. Brown, N. Q. Burdick, W. C. Burton, S. L. Campbell, J. P. Campora III, C. Carron, J. Chambers, J. W. Chan, Y. H. Chen, et al (76)
May 09 2023 quant-ph arXiv:2305.03828v2

@misc{2305.03828, author = {S.~A.~Moses and C.~H.~Baldwin and M.~S.~Allman and R.~Ancona and L.~Ascarrunz and C.~Barnes and J.~Bartolotta and B.~Bjork and P.~Blanchard and M.~Bohn and J.~G.~Bohnet and N.~C.~Brown and N.~Q.~Burdick and W.~C.~Burton and S.~L.~Campbell and J.~P.~Campora III and C.~Carron and J.~Chambers and J.~W.~Chan and Y.~H.~Chen and A.~Chernoguzov and E.~Chertkov and J.~Colina and J.~P.~Curtis and R.~Daniel and M.~DeCross and D.~Deen and C.~Delaney and J.~M.~Dreiling and C.~T.~Ertsgaard and J.~Esposito and B.~Estey and M.~Fabrikant and C.~Figgatt and C.~Foltz and M.~Foss-Feig and D.~Francois and J.~P.~Gaebler and T.~M.~Gatterman and C.~N.~Gilbreth and J.~Giles and E.~Glynn and A.~Hall and A.~M.~Hankin and A.~Hansen and D.~Hayes and B.~Higashi and I.~M.~Hoffman and B.~Horning and J.~J.~Hout and R.~Jacobs and J.~Johansen and L.~Jones and J.~Karcz and T.~Klein and P.~Lauria and P.~Lee and D.~Liefer and C.~Lytle and S.~T.~Lu and D.~Lucchetti and A.~Malm and M.~Matheny and B.~Mathewson and K.~Mayer and D.~B.~Miller and M.~Mills and B.~Neyenhuis and L.~Nugent and S.~Olson and J.~Parks and G.~N.~Price and Z.~Price and M.~Pugh and A.~Ransford and A.~P.~Reed and C.~Roman and M.~Rowe and C.~Ryan-Anderson and S.~Sanders and J.~Sedlacek and P.~Shevchuk and P.~Siegfried and T.~Skripka and B.~Spaun and R.~T.~Sprenkle and R.~P.~Stutz and M.~Swallows and R.~I.~Tobey and A.~Tran and T.~Tran and E.~Vogt and C.~Volin and J.~Walker and A.~M.~Zolot and J.~M.~Pino}, title = {{A} {R}ace {T}rack {T}rapped-{I}on {Q}uantum {P}rocessor}, year = {2023}, eprint = {2305.03828}, note = {arXiv:2305.03828v2} }
PDF
1 comment
We describe and benchmark a new quantum charge-coupled device (QCCD) trapped-ion quantum computer based on a linear trap with periodic boundary conditions, which resembles a race track. The new system successfully incorporates several technologies crucial to future scalability, including electrode broadcasting, multi-layer RF routing, and magneto-optical trap (MOT) loading, while maintaining, and in some cases exceeding, the gate fidelities of previous QCCD systems. The system is initially operated with 32 qubits, but future upgrades will allow for more. We benchmark the performance of primitive operations, including an average state preparation and measurement error of 1.6(1)$\times 10^{-3}$, an average single-qubit gate infidelity of $2.5(3)\times 10^{-5}$, and an average two-qubit gate infidelity of $1.84(5)\times 10^{-3}$. The system-level performance of the quantum processor is assessed with mirror benchmarking, linear cross-entropy benchmarking, a quantum volume measurement of $\mathrm{QV}=2^{16}$, and the creation of 32-qubit entanglement in a GHZ state. We also tested application benchmarks including Hamiltonian simulation, QAOA, error correction on a repetition code, and dynamics simulations using qubit reuse. We also discuss future upgrades to the new system aimed at adding more qubits and capabilities.