%0 Journal Article %D 2023 %T Ever more optimized simulations of fermionic systems on a quantum computer %A Qingfeng Wang %A Ze-Pei Cian %A Ming Li %A Igor L. Markov %A Yunseong Nam %X

Despite using a novel model of computation, quantum computers break down programs into elementary gates. Among such gates, entangling gates are the most expensive. In the context of fermionic simulations, we develop a suite of compilation and optimization techniques that massively reduce the entangling-gate counts. We exploit the well-studied non-quantum optimization algorithms to achieve up to 24\% savings over the state of the art for several small-molecule simulations, with no loss of accuracy or hidden costs. Our methodologies straightforwardly generalize to wider classes of near-term simulations of the ground state of a fermionic system or real-time simulations probing dynamical properties of a fermionic system. 

%8 3/6/2023 %G eng %U https://arxiv.org/abs/2303.03460 %0 Journal Article %D 2023 %T Quantum-centric Supercomputing for Materials Science: A Perspective on Challenges and Future Directions %A Yuri Alexeev %A Maximilian Amsler %A Paul Baity %A Marco Antonio Barroca %A Sanzio Bassini %A Torey Battelle %A Daan Camps %A David Casanova %A Young jai Choi %A Frederic T. Chong %A Charles Chung %A Chris Codella %A Antonio D. Corcoles %A James Cruise %A Alberto Di Meglio %A Jonathan Dubois %A Ivan Duran %A Thomas Eckl %A Sophia Economou %A Stephan Eidenbenz %A Bruce Elmegreen %A Clyde Fare %A Ismael Faro %A Cristina Sanz Fernández %A Rodrigo Neumann Barros Ferreira %A Keisuke Fuji %A Bryce Fuller %A Laura Gagliardi %A Giulia Galli %A Jennifer R. Glick %A Isacco Gobbi %A Pranav Gokhale %A Salvador de la Puente Gonzalez %A Johannes Greiner %A Bill Gropp %A Michele Grossi %A Emmanuel Gull %A Burns Healy %A Benchen Huang %A Travis S. Humble %A Nobuyasu Ito %A Artur F. Izmaylov %A Ali Javadi-Abhari %A Douglas Jennewein %A Shantenu Jha %A Liang Jiang %A Barbara Jones %A Wibe Albert de Jong %A Petar Jurcevic %A William Kirby %A Stefan Kister %A Masahiro Kitagawa %A Joel Klassen %A Katherine Klymko %A Kwangwon Koh %A Masaaki Kondo %A Doga Murat Kurkcuoglu %A Krzysztof Kurowski %A Teodoro Laino %A Ryan Landfield %A Matt Leininger %A Vicente Leyton-Ortega %A Ang Li %A Meifeng Lin %A Junyu Liu %A Nicolas Lorente %A Andre Luckow %A Simon Martiel %A Francisco Martin-Fernandez %A Margaret Martonosi %A Claire Marvinney %A Arcesio Castaneda Medina %A Dirk Merten %A Antonio Mezzacapo %A Kristel Michielsen %A Abhishek Mitra %A Tushar Mittal %A Kyungsun Moon %A Joel Moore %A Mario Motta %A Young-Hye Na %A Yunseong Nam %A Prineha Narang %A Yu-ya Ohnishi %A Daniele Ottaviani %A Matthew Otten %A Scott Pakin %A Vincent R. Pascuzzi %A Ed Penault %A Tomasz Piontek %A Jed Pitera %A Patrick Rall %A Gokul Subramanian Ravi %A Niall Robertson %A Matteo Rossi %A Piotr Rydlichowski %A Hoon Ryu %A Georgy Samsonidze %A Mitsuhisa Sato %A Nishant Saurabh %A Vidushi Sharma %A Kunal Sharma %A Soyoung Shin %A George Slessman %A Mathias Steiner %A Iskandar Sitdikov %A In-Saeng Suh %A Eric Switzer %A Wei Tang %A Joel Thompson %A Synge Todo %A Minh Tran %A Dimitar Trenev %A Christian Trott %A Huan-Hsin Tseng %A Esin Tureci %A David García Valinas %A Sofia Vallecorsa %A Christopher Wever %A Konrad Wojciechowski %A Xiaodi Wu %A Shinjae Yoo %A Nobuyuki Yoshioka %A Victor Wen-zhe Yu %A Seiji Yunoki %A Sergiy Zhuk %A Dmitry Zubarev %X

Computational models are an essential tool for the design, characterization, and discovery of novel materials. Hard computational tasks in materials science stretch the limits of existing high-performance supercomputing centers, consuming much of their simulation, analysis, and data resources. Quantum computing, on the other hand, is an emerging technology with the potential to accelerate many of the computational tasks needed for materials science. In order to do that, the quantum technology must interact with conventional high-performance computing in several ways: approximate results validation, identification of hard problems, and synergies in quantum-centric supercomputing. In this paper, we provide a perspective on how quantum-centric supercomputing can help address critical computational problems in materials science, the challenges to face in order to solve representative use cases, and new suggested directions.

%8 12/14/2023 %G eng %U https://arxiv.org/abs/2312.09733 %0 Journal Article %D 2021 %T Cross-Platform Comparison of Arbitrary Quantum Computations %A Daiwei Zhu %A Ze-Pei Cian %A Crystal Noel %A Andrew Risinger %A Debopriyo Biswas %A Laird Egan %A Yingyue Zhu %A Alaina M. Green %A Cinthia Huerta Alderete %A Nhung H. Nguyen %A Qingfeng Wang %A Andrii Maksymov %A Yunseong Nam %A Marko Cetina %A Norbert M. Linke %A Mohammad Hafezi %A Christopher Monroe %X

As we approach the era of quantum advantage, when quantum computers (QCs) can outperform any classical computer on particular tasks, there remains the difficult challenge of how to validate their performance. While algorithmic success can be easily verified in some instances such as number factoring or oracular algorithms, these approaches only provide pass/fail information for a single QC. On the other hand, a comparison between different QCs on the same arbitrary circuit provides a lower-bound for generic validation: a quantum computation is only as valid as the agreement between the results produced on different QCs. Such an approach is also at the heart of evaluating metrological standards such as disparate atomic clocks. In this paper, we report a cross-platform QC comparison using randomized and correlated measurements that results in a wealth of information on the QC systems. We execute several quantum circuits on widely different physical QC platforms and analyze the cross-platform fidelities.

%8 7/27/2021 %G eng %U https://arxiv.org/abs/2107.11387 %0 Journal Article %D 2021 %T Efficient quantum programming using EASE gates on a trapped-ion quantum computer %A Nikodem Grzesiak %A Andrii Maksymov %A Pradeep Niroula %A Yunseong Nam %X

Parallel operations in conventional computing have proven to be an essential tool for efficient and practical computation, and the story is not different for quantum computing. Indeed, there exists a large body of works that study advantages of parallel implementations of quantum gates for efficient quantum circuit implementations. Here, we focus on the recently invented efficient, arbitrary, simultaneously entangling (EASE) gates, available on a trapped-ion quantum computer. Leveraging its flexibility in selecting arbitrary pairs of qubits to be coupled with any degrees of entanglement, all in parallel, we show a n-qubit Clifford circuit can be implemented using 6log(n) EASE gates, a n-qubit multiply-controlled NOT gate can be implemented using 3n/2 EASE gates, and a n-qubit permutation can be implemented using six EASE gates. We discuss their implications to near-term quantum chemistry simulations and the state of the art pattern matching algorithm. Given Clifford + multiply-controlled NOT gates form a universal gate set for quantum computing, our results imply efficient quantum computation by EASE gates, in general.

%8 7/15/2021 %G eng %U https://arxiv.org/abs/2107.07591 %0 Journal Article %D 2021 %T Interactive Protocols for Classically-Verifiable Quantum Advantage %A Daiwei Zhu %A Gregory D. Kahanamoku-Meyer %A Laura Lewis %A Crystal Noel %A Or Katz %A Bahaa Harraz %A Qingfeng Wang %A Andrew Risinger %A Lei Feng %A Debopriyo Biswas %A Laird Egan %A Alexandru Gheorghiu %A Yunseong Nam %A Thomas Vidick %A Umesh Vazirani %A Norman Y. Yao %A Marko Cetina %A Christopher Monroe %X

Achieving quantum computational advantage requires solving a classically intractable problem on a quantum device. Natural proposals rely upon the intrinsic hardness of classically simulating quantum mechanics; however, verifying the output is itself classically intractable. On the other hand, certain quantum algorithms (e.g. prime factorization via Shor's algorithm) are efficiently verifiable, but require more resources than what is available on near-term devices. One way to bridge the gap between verifiability and implementation is to use "interactions" between a prover and a verifier. By leveraging cryptographic functions, such protocols enable the classical verifier to enforce consistency in a quantum prover's responses across multiple rounds of interaction. In this work, we demonstrate the first implementation of an interactive quantum advantage protocol, using an ion trap quantum computer. We execute two complementary protocols -- one based upon the learning with errors problem and another where the cryptographic construction implements a computational Bell test. To perform multiple rounds of interaction, we implement mid-circuit measurements on a subset of trapped ion qubits, with subsequent coherent evolution. For both protocols, the performance exceeds the asymptotic bound for classical behavior; maintaining this fidelity at scale would conclusively demonstrate verifiable quantum advantage.

%8 12/9/2021 %G eng %U https://arxiv.org/abs/2112.05156 %0 Journal Article %J Quantum %D 2021 %T Resource-Optimized Fermionic Local-Hamiltonian Simulation on Quantum Computer for Quantum Chemistry %A Qingfeng Wang %A Ming Li %A Christopher Monroe %A Yunseong Nam %X

The ability to simulate a fermionic system on a quantum computer is expected to revolutionize chemical engineering, materials design, nuclear physics, to name a few. Thus, optimizing the simulation circuits is of significance in harnessing the power of quantum computers. Here, we address this problem in two aspects. In the fault-tolerant regime, we optimize the $\rzgate$ and $\tgate$ gate counts along with the ancilla qubit counts required, assuming the use of a product-formula algorithm for implementation. We obtain a savings ratio of two in the gate counts and a savings ratio of eleven in the number of ancilla qubits required over the state of the art. In the pre-fault tolerant regime, we optimize the two-qubit gate counts, assuming the use of the variational quantum eigensolver (VQE) approach. Specific to the latter, we present a framework that enables bootstrapping the VQE progression towards the convergence of the ground-state energy of the fermionic system. This framework, based on perturbation theory, is capable of improving the energy estimate at each cycle of the VQE progression, by about a factor of three closer to the known ground-state energy compared to the standard VQE approach in the test-bed, classically-accessible system of the water molecule. The improved energy estimate in turn results in a commensurate level of savings of quantum resources, such as the number of qubits and quantum gates, required to be within a pre-specified tolerance from the known ground-state energy. We also explore a suite of generalized transformations of fermion to qubit operators and show that resource-requirement savings of up to more than 20% is possible.

%B Quantum %V 5 %8 7/21/2021 %G eng %U https://arxiv.org/abs/2004.04151 %N 509 %R https://doi.org/10.22331/q-2021-07-26-509 %0 Journal Article %J npj Quantum Information %D 2020 %T Approximate Quantum Fourier Transform with O(nlog(n)) T gates %A Yunseong Nam %A Yuan Su %A Dmitri Maslov %X

The ability to implement the Quantum Fourier Transform (QFT) efficiently on a quantum computer enables the advantages offered by a variety of fundamental quantum algorithms, such as those for integer factoring, computing discrete logarithm over Abelian groups, and phase estimation. The standard fault-tolerant implementation of an n-qubit QFT approximates the desired transformation by removing small-angle controlled rotations and synthesizing the remaining ones into Clifford+t gates, incurring the t-count complexity of O(n log2 (n)). In this paper we show how to obtain approximate QFT with the t-count of O(n log(n)). Our approach relies on quantum circuits with measurements and feedforward, and on reusing a special quantum state that induces the phase gradient transformation. We report asymptotic analysis as well as concrete circuits, demonstrating significant advantages in both theory and practice.

%B npj Quantum Information %V 6 %8 3/13/2020 %G eng %U https://arxiv.org/abs/1803.04933 %N 26 %R https://doi.org/10.1038/s41534-020-0257-5 %0 Journal Article %D 2019 %T Ground-state energy estimation of the water molecule on a trapped ion quantum computer %A Yunseong Nam %A Jwo-Sy Chen %A Neal C. Pisenti %A Kenneth Wright %A Conor Delaney %A Dmitri Maslov %A Kenneth R. Brown %A Stewart Allen %A Jason M. Amini %A Joel Apisdorf %A Kristin M. Beck %A Aleksey Blinov %A Vandiver Chaplin %A Mika Chmielewski %A Coleman Collins %A Shantanu Debnath %A Andrew M. Ducore %A Kai M. Hudek %A Matthew Keesan %A Sarah M. Kreikemeier %A Jonathan Mizrahi %A Phil Solomon %A Mike Williams %A Jaime David Wong-Campos %A Christopher Monroe %A Jungsang Kim %X

Quantum computing leverages the quantum resources of superposition and entanglement to efficiently solve computational problems considered intractable for classical computers. Examples include calculating molecular and nuclear structure, simulating strongly-interacting electron systems, and modeling aspects of material function. While substantial theoretical advances have been made in mapping these problems to quantum algorithms, there remains a large gap between the resource requirements for solving such problems and the capabilities of currently available quantum hardware. Bridging this gap will require a co-design approach, where the expression of algorithms is developed in conjunction with the hardware itself to optimize execution. Here, we describe a scalable co-design framework for solving chemistry problems on a trapped ion quantum computer, and apply it to compute the ground-state energy of the water molecule. The robust operation of the trapped ion quantum computer yields energy estimates with errors approaching the chemical accuracy, which is the target threshold necessary for predicting the rates of chemical reaction dynamics.

%8 03/07/2019 %G eng %U https://arxiv.org/abs/1902.10171 %0 Journal Article %D 2019 %T Toward convergence of effective field theory simulations on digital quantum computers %A Omar Shehab %A Kevin A. Landsman %A Yunseong Nam %A Daiwei Zhu %A Norbert M. Linke %A Matthew J. Keesan %A Raphael C. Pooser %A Christopher R. Monroe %X

We report results for simulating an effective field theory to compute the binding energy of the deuteron nucleus using a hybrid algorithm on a trapped-ion quantum computer. Two increasingly complex unitary coupled-cluster ansaetze have been used to compute the binding energy to within a few percent for successively more complex Hamiltonians. By increasing the complexity of the Hamiltonian, allowing more terms in the effective field theory expansion and calculating their expectation values, we present a benchmark for quantum computers based on their ability to scalably calculate the effective field theory with increasing accuracy. Our result of E4=−2.220±0.179MeV may be compared with the exact Deuteron ground-state energy −2.224MeV. We also demonstrate an error mitigation technique using Richardson extrapolation on ion traps for the first time. The error mitigation circuit represents a record for deepest quantum circuit on a trapped-ion quantum computer. 

%8 04/18/2019 %G eng %U https://arxiv.org/abs/1904.04338 %0 Journal Article %J npj:Quantum Information %D 2018 %T Automated optimization of large quantum circuits with continuous parameters %A Yunseong Nam %A Neil J. Ross %A Yuan Su %A Andrew M. Childs %A Dmitri Maslov %X

We develop and implement automated methods for optimizing quantum circuits of the size and type expected in quantum computations that outperform classical computers. We show how to handle continuous gate parameters and report a collection of fast algorithms capable of optimizing large-scale quantum circuits. For the suite of benchmarks considered, we obtain substantial reductions in gate counts. In particular, we provide better optimization in significantly less time than previous approaches, while making minimal structural changes so as to preserve the basic layout of the underlying quantum algorithms. Our results help bridge the gap between the computations that can be run on existing hardware and those that are expected to outperform classical computers. 

%B npj:Quantum Information %V 4 %8 2017/10/19 %G eng %U https://arxiv.org/abs/1710.07345 %N 23 %R https://doi.org/10.1038/s41534-018-0072-4 %0 Journal Article %J Proceedings of the National Academy of Sciences %D 2018 %T Toward the first quantum simulation with quantum speedup %A Andrew M. Childs %A Dmitri Maslov %A Yunseong Nam %A Neil J. Ross %A Yuan Su %X

With quantum computers of significant size now on the horizon, we should understand how to best exploit their initially limited abilities. To this end, we aim to identify a practical problem that is beyond the reach of current classical computers, but that requires the fewest resources for a quantum computer. We consider quantum simulation of spin systems, which could be applied to understand condensed matter phenomena. We synthesize explicit circuits for three leading quantum simulation algorithms, using diverse techniques to tighten error bounds and optimize circuit implementations. Quantum signal processing appears to be preferred among algorithms with rigorous performance guarantees, whereas higher-order product formulas prevail if empirical error estimates suffice. Our circuits are orders of magnitude smaller than those for the simplest classically infeasible instances of factoring and quantum chemistry, bringing practical quantum computation closer to reality.

%B Proceedings of the National Academy of Sciences %V 115 %P 9456-9461 %G eng %U https://arxiv.org/abs/1711.10980 %R https://doi.org/10.1073/pnas.1801723115 %0 Journal Article %J Quantum Information Processing %D 2017 %T Optimal length of decomposition sequences composed of imperfect gates %A Yunseong Nam %A R. Blümel %X

Quantum error correcting circuitry is both a resource for correcting errors and a source for generating errors. A balance has to be struck between these two aspects. Perfect quantum gates do not exist in nature. Therefore, it is important to investigate how flaws in the quantum hardware affect quantum computing performance. We do this in two steps. First, in the presence of realistic, faulty quantum hardware, we establish how quantum error correction circuitry achieves reduction in the extent of quantum information corruption. Then, we investigate fault-tolerant gate sequence techniques that result in an approximate phase rotation gate, and establish the existence of an optimal length Lopt of the length L of the decomposition sequence. The existence of Lopt is due to the competition between the increase in gate accuracy with increasing L, but the decrease in gate performance due to the diffusive proliferation of gate errors due to faulty basis gates. We present an analytical formula for the gate fidelity as a function of L that is in satisfactory agreement with the results of our simulations and allows the determination of Lopt via the solution of a transcendental equation. Our result is universally applicable since gate sequence approximations also play an important role, e.g., in atomic and molecular physics and in nuclear magnetic resonance.

%B Quantum Information Processing %V 16 %P 123 %8 2017/03/24 %G eng %U https://link.springer.com/article/10.1007/s11128-017-1571-5 %R 10.1007/s11128-017-1571-5 %0 Journal Article %J New Journal of Physics %D 2017 %T Use of global interactions in efficient quantum circuit constructions %A Dmitri Maslov %A Yunseong Nam %X

In this paper we study the ways to use a global entangling operator to efficiently implement circuitry common to a selection of important quantum algorithms. In particular, we focus on the circuits composed with global Ising entangling gates and arbitrary addressable single-qubit gates. We show that under certain circumstances the use of global operations can substantially improve the entangling gate count.

%B New Journal of Physics %8 2017/12/21 %G eng %U http://iopscience.iop.org/article/10.1088/1367-2630/aaa398 %R 10.1088/1367-2630/aaa398