@article {3261, title = {Ever more optimized simulations of fermionic systems on a quantum computer}, year = {2023}, month = {3/6/2023}, abstract = {

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.\ 

}, url = {https://arxiv.org/abs/2303.03460}, author = {Qingfeng Wang and Ze-Pei Cian and Ming Li and Igor L. Markov and Yunseong Nam} } @article {3397, title = {Quantum-centric Supercomputing for Materials Science: A Perspective on Challenges and Future Directions}, year = {2023}, month = {12/14/2023}, abstract = {

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.

}, url = {https://arxiv.org/abs/2312.09733}, author = {Yuri Alexeev and Maximilian Amsler and Paul Baity and Marco Antonio Barroca and Sanzio Bassini and Torey Battelle and Daan Camps and David Casanova and Young jai Choi and Frederic T. Chong and Charles Chung and Chris Codella and Antonio D. Corcoles and James Cruise and Alberto Di Meglio and Jonathan Dubois and Ivan Duran and Thomas Eckl and Sophia Economou and Stephan Eidenbenz and Bruce Elmegreen and Clyde Fare and Ismael Faro and Cristina Sanz Fern{\'a}ndez and Rodrigo Neumann Barros Ferreira and Keisuke Fuji and Bryce Fuller and Laura Gagliardi and Giulia Galli and Jennifer R. Glick and Isacco Gobbi and Pranav Gokhale and Salvador de la Puente Gonzalez and Johannes Greiner and Bill Gropp and Michele Grossi and Emmanuel Gull and Burns Healy and Benchen Huang and Travis S. Humble and Nobuyasu Ito and Artur F. Izmaylov and Ali Javadi-Abhari and Douglas Jennewein and Shantenu Jha and Liang Jiang and Barbara Jones and Wibe Albert de Jong and Petar Jurcevic and William Kirby and Stefan Kister and Masahiro Kitagawa and Joel Klassen and Katherine Klymko and Kwangwon Koh and Masaaki Kondo and Doga Murat Kurkcuoglu and Krzysztof Kurowski and Teodoro Laino and Ryan Landfield and Matt Leininger and Vicente Leyton-Ortega and Ang Li and Meifeng Lin and Junyu Liu and Nicolas Lorente and Andre Luckow and Simon Martiel and Francisco Martin-Fernandez and Margaret Martonosi and Claire Marvinney and Arcesio Castaneda Medina and Dirk Merten and Antonio Mezzacapo and Kristel Michielsen and Abhishek Mitra and Tushar Mittal and Kyungsun Moon and Joel Moore and Mario Motta and Young-Hye Na and Yunseong Nam and Prineha Narang and Yu-ya Ohnishi and Daniele Ottaviani and Matthew Otten and Scott Pakin and Vincent R. Pascuzzi and Ed Penault and Tomasz Piontek and Jed Pitera and Patrick Rall and Gokul Subramanian Ravi and Niall Robertson and Matteo Rossi and Piotr Rydlichowski and Hoon Ryu and Georgy Samsonidze and Mitsuhisa Sato and Nishant Saurabh and Vidushi Sharma and Kunal Sharma and Soyoung Shin and George Slessman and Mathias Steiner and Iskandar Sitdikov and In-Saeng Suh and Eric Switzer and Wei Tang and Joel Thompson and Synge Todo and Minh Tran and Dimitar Trenev and Christian Trott and Huan-Hsin Tseng and Esin Tureci and David Garc{\'\i}a Valinas and Sofia Vallecorsa and Christopher Wever and Konrad Wojciechowski and Xiaodi Wu and Shinjae Yoo and Nobuyuki Yoshioka and Victor Wen-zhe Yu and Seiji Yunoki and Sergiy Zhuk and Dmitry Zubarev} } @article {2919, title = {Cross-Platform Comparison of Arbitrary Quantum Computations}, year = {2021}, month = {7/27/2021}, abstract = {

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.

}, url = {https://arxiv.org/abs/2107.11387}, author = {Daiwei Zhu and Ze-Pei Cian and Crystal Noel and Andrew Risinger and Debopriyo Biswas and Laird Egan and Yingyue Zhu and Alaina M. Green and Cinthia Huerta Alderete and Nhung H. Nguyen and Qingfeng Wang and Andrii Maksymov and Yunseong Nam and Marko Cetina and Norbert M. Linke and Mohammad Hafezi and Christopher Monroe} } @article {2821, title = {Efficient quantum programming using EASE gates on a trapped-ion quantum computer}, year = {2021}, month = {7/15/2021}, abstract = {

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.

}, url = {https://arxiv.org/abs/2107.07591}, author = {Nikodem Grzesiak and Andrii Maksymov and Pradeep Niroula and Yunseong Nam} } @article {2908, title = {Interactive Protocols for Classically-Verifiable Quantum Advantage}, year = {2021}, month = {12/9/2021}, abstract = {

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\&$\#$39;s algorithm) are efficiently verifiable, but require more resources than what is available on near-term devices. One way to bridge the gap between verifiability and implementation is to use \"interactions\" between a prover and a verifier. By leveraging cryptographic functions, such protocols enable the classical verifier to enforce consistency in a quantum prover\&$\#$39;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.

}, url = {https://arxiv.org/abs/2112.05156}, author = {Daiwei Zhu and Gregory D. Kahanamoku-Meyer and Laura Lewis and Crystal Noel and Or Katz and Bahaa Harraz and Qingfeng Wang and Andrew Risinger and Lei Feng and Debopriyo Biswas and Laird Egan and Alexandru Gheorghiu and Yunseong Nam and Thomas Vidick and Umesh Vazirani and Norman Y. Yao and Marko Cetina and Christopher Monroe} } @article {2569, title = {Resource-Optimized Fermionic Local-Hamiltonian Simulation on Quantum Computer for Quantum Chemistry}, journal = {Quantum}, volume = {5}, year = {2021}, month = {7/21/2021}, abstract = {

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.

}, doi = {https://doi.org/10.22331/q-2021-07-26-509}, url = {https://arxiv.org/abs/2004.04151}, author = {Qingfeng Wang and Ming Li and Christopher Monroe and Yunseong Nam} } @article {2154, title = {Approximate Quantum Fourier Transform with O(nlog(n)) T gates}, journal = {npj Quantum Information }, volume = {6}, year = {2020}, month = {3/13/2020}, abstract = {

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.

}, doi = {https://doi.org/10.1038/s41534-020-0257-5}, url = {https://arxiv.org/abs/1803.04933}, author = {Yunseong Nam and Yuan Su and Dmitri Maslov} } @article {2369, title = {Ground-state energy estimation of the water molecule on a trapped ion quantum computer}, year = {2019}, month = {03/07/2019}, abstract = {

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.

}, url = {https://arxiv.org/abs/1902.10171}, author = {Yunseong Nam and Jwo-Sy Chen and Neal C. Pisenti and Kenneth Wright and Conor Delaney and Dmitri Maslov and Kenneth R. Brown and Stewart Allen and Jason M. Amini and Joel Apisdorf and Kristin M. Beck and Aleksey Blinov and Vandiver Chaplin and Mika Chmielewski and Coleman Collins and Shantanu Debnath and Andrew M. Ducore and Kai M. Hudek and Matthew Keesan and Sarah M. Kreikemeier and Jonathan Mizrahi and Phil Solomon and Mike Williams and Jaime David Wong-Campos and Christopher Monroe and Jungsang Kim} } @article {2392, title = {Toward convergence of effective field theory simulations on digital quantum computers}, year = {2019}, month = {04/18/2019}, abstract = {

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.\ 

}, url = {https://arxiv.org/abs/1904.04338}, author = {Omar Shehab and Kevin A. Landsman and Yunseong Nam and Daiwei Zhu and Norbert M. Linke and Matthew J. Keesan and Raphael C. Pooser and Christopher R. Monroe} } @article {2067, title = {Automated optimization of large quantum circuits with continuous parameters}, journal = {npj:Quantum Information}, volume = {4}, year = {2018}, month = {2017/10/19}, abstract = {

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.\ 

}, doi = {https://doi.org/10.1038/s41534-018-0072-4}, url = {https://arxiv.org/abs/1710.07345}, author = {Yunseong Nam and Neil J. Ross and Yuan Su and Andrew M. Childs and Dmitri Maslov} } @article {2220, title = {Toward the first quantum simulation with quantum speedup}, journal = {Proceedings of the National Academy of Sciences}, volume = {115 }, year = {2018}, pages = {9456-9461}, abstract = {

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.

}, doi = {https://doi.org/10.1073/pnas.1801723115}, url = {https://arxiv.org/abs/1711.10980}, author = {Andrew M. Childs and Dmitri Maslov and Yunseong Nam and Neil J. Ross and Yuan Su} } @article {1965, title = {Optimal length of decomposition sequences composed of imperfect gates}, journal = {Quantum Information Processing}, volume = {16}, year = {2017}, month = {2017/03/24}, pages = {123}, abstract = {

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.

}, issn = {1573-1332}, doi = {10.1007/s11128-017-1571-5}, url = {https://link.springer.com/article/10.1007/s11128-017-1571-5}, author = {Yunseong Nam and R. Bl{\"u}mel} } @article {2069, title = {Use of global interactions in efficient quantum circuit constructions}, journal = {New Journal of Physics}, year = {2017}, month = {2017/12/21}, abstract = {

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.

}, doi = {10.1088/1367-2630/aaa398}, url = {http://iopscience.iop.org/article/10.1088/1367-2630/aaa398}, author = {Dmitri Maslov and Yunseong Nam} }