TY - JOUR T1 - Ever more optimized simulations of fermionic systems on a quantum computer Y1 - 2023 A1 - Qingfeng Wang A1 - Ze-Pei Cian A1 - Ming Li A1 - Igor L. Markov A1 - Yunseong Nam AB -

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. 

UR - https://arxiv.org/abs/2303.03460 ER - TY - JOUR T1 - Quantum-centric Supercomputing for Materials Science: A Perspective on Challenges and Future Directions Y1 - 2023 A1 - Yuri Alexeev A1 - Maximilian Amsler A1 - Paul Baity A1 - Marco Antonio Barroca A1 - Sanzio Bassini A1 - Torey Battelle A1 - Daan Camps A1 - David Casanova A1 - Young jai Choi A1 - Frederic T. Chong A1 - Charles Chung A1 - Chris Codella A1 - Antonio D. Corcoles A1 - James Cruise A1 - Alberto Di Meglio A1 - Jonathan Dubois A1 - Ivan Duran A1 - Thomas Eckl A1 - Sophia Economou A1 - Stephan Eidenbenz A1 - Bruce Elmegreen A1 - Clyde Fare A1 - Ismael Faro A1 - Cristina Sanz Fernández A1 - Rodrigo Neumann Barros Ferreira A1 - Keisuke Fuji A1 - Bryce Fuller A1 - Laura Gagliardi A1 - Giulia Galli A1 - Jennifer R. Glick A1 - Isacco Gobbi A1 - Pranav Gokhale A1 - Salvador de la Puente Gonzalez A1 - Johannes Greiner A1 - Bill Gropp A1 - Michele Grossi A1 - Emmanuel Gull A1 - Burns Healy A1 - Benchen Huang A1 - Travis S. Humble A1 - Nobuyasu Ito A1 - Artur F. Izmaylov A1 - Ali Javadi-Abhari A1 - Douglas Jennewein A1 - Shantenu Jha A1 - Liang Jiang A1 - Barbara Jones A1 - Wibe Albert de Jong A1 - Petar Jurcevic A1 - William Kirby A1 - Stefan Kister A1 - Masahiro Kitagawa A1 - Joel Klassen A1 - Katherine Klymko A1 - Kwangwon Koh A1 - Masaaki Kondo A1 - Doga Murat Kurkcuoglu A1 - Krzysztof Kurowski A1 - Teodoro Laino A1 - Ryan Landfield A1 - Matt Leininger A1 - Vicente Leyton-Ortega A1 - Ang Li A1 - Meifeng Lin A1 - Junyu Liu A1 - Nicolas Lorente A1 - Andre Luckow A1 - Simon Martiel A1 - Francisco Martin-Fernandez A1 - Margaret Martonosi A1 - Claire Marvinney A1 - Arcesio Castaneda Medina A1 - Dirk Merten A1 - Antonio Mezzacapo A1 - Kristel Michielsen A1 - Abhishek Mitra A1 - Tushar Mittal A1 - Kyungsun Moon A1 - Joel Moore A1 - Mario Motta A1 - Young-Hye Na A1 - Yunseong Nam A1 - Prineha Narang A1 - Yu-ya Ohnishi A1 - Daniele Ottaviani A1 - Matthew Otten A1 - Scott Pakin A1 - Vincent R. Pascuzzi A1 - Ed Penault A1 - Tomasz Piontek A1 - Jed Pitera A1 - Patrick Rall A1 - Gokul Subramanian Ravi A1 - Niall Robertson A1 - Matteo Rossi A1 - Piotr Rydlichowski A1 - Hoon Ryu A1 - Georgy Samsonidze A1 - Mitsuhisa Sato A1 - Nishant Saurabh A1 - Vidushi Sharma A1 - Kunal Sharma A1 - Soyoung Shin A1 - George Slessman A1 - Mathias Steiner A1 - Iskandar Sitdikov A1 - In-Saeng Suh A1 - Eric Switzer A1 - Wei Tang A1 - Joel Thompson A1 - Synge Todo A1 - Minh Tran A1 - Dimitar Trenev A1 - Christian Trott A1 - Huan-Hsin Tseng A1 - Esin Tureci A1 - David García Valinas A1 - Sofia Vallecorsa A1 - Christopher Wever A1 - Konrad Wojciechowski A1 - Xiaodi Wu A1 - Shinjae Yoo A1 - Nobuyuki Yoshioka A1 - Victor Wen-zhe Yu A1 - Seiji Yunoki A1 - Sergiy Zhuk A1 - Dmitry Zubarev AB -

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.

UR - https://arxiv.org/abs/2312.09733 ER - TY - JOUR T1 - Cross-Platform Comparison of Arbitrary Quantum Computations Y1 - 2021 A1 - Daiwei Zhu A1 - Ze-Pei Cian A1 - Crystal Noel A1 - Andrew Risinger A1 - Debopriyo Biswas A1 - Laird Egan A1 - Yingyue Zhu A1 - Alaina M. Green A1 - Cinthia Huerta Alderete A1 - Nhung H. Nguyen A1 - Qingfeng Wang A1 - Andrii Maksymov A1 - Yunseong Nam A1 - Marko Cetina A1 - Norbert M. Linke A1 - Mohammad Hafezi A1 - Christopher Monroe AB -

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.

UR - https://arxiv.org/abs/2107.11387 ER - TY - JOUR T1 - Efficient quantum programming using EASE gates on a trapped-ion quantum computer Y1 - 2021 A1 - Nikodem Grzesiak A1 - Andrii Maksymov A1 - Pradeep Niroula A1 - Yunseong Nam AB -

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.

UR - https://arxiv.org/abs/2107.07591 ER - TY - JOUR T1 - Interactive Protocols for Classically-Verifiable Quantum Advantage Y1 - 2021 A1 - Daiwei Zhu A1 - Gregory D. Kahanamoku-Meyer A1 - Laura Lewis A1 - Crystal Noel A1 - Or Katz A1 - Bahaa Harraz A1 - Qingfeng Wang A1 - Andrew Risinger A1 - Lei Feng A1 - Debopriyo Biswas A1 - Laird Egan A1 - Alexandru Gheorghiu A1 - Yunseong Nam A1 - Thomas Vidick A1 - Umesh Vazirani A1 - Norman Y. Yao A1 - Marko Cetina A1 - Christopher Monroe AB -

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.

UR - https://arxiv.org/abs/2112.05156 ER - TY - JOUR T1 - Resource-Optimized Fermionic Local-Hamiltonian Simulation on Quantum Computer for Quantum Chemistry JF - Quantum Y1 - 2021 A1 - Qingfeng Wang A1 - Ming Li A1 - Christopher Monroe A1 - Yunseong Nam AB -

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.

VL - 5 UR - https://arxiv.org/abs/2004.04151 CP - 509 U5 - https://doi.org/10.22331/q-2021-07-26-509 ER - TY - JOUR T1 - Approximate Quantum Fourier Transform with O(nlog(n)) T gates JF - npj Quantum Information Y1 - 2020 A1 - Yunseong Nam A1 - Yuan Su A1 - Dmitri Maslov AB -

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.

VL - 6 UR - https://arxiv.org/abs/1803.04933 CP - 26 U5 - https://doi.org/10.1038/s41534-020-0257-5 ER - TY - JOUR T1 - Ground-state energy estimation of the water molecule on a trapped ion quantum computer Y1 - 2019 A1 - Yunseong Nam A1 - Jwo-Sy Chen A1 - Neal C. Pisenti A1 - Kenneth Wright A1 - Conor Delaney A1 - Dmitri Maslov A1 - Kenneth R. Brown A1 - Stewart Allen A1 - Jason M. Amini A1 - Joel Apisdorf A1 - Kristin M. Beck A1 - Aleksey Blinov A1 - Vandiver Chaplin A1 - Mika Chmielewski A1 - Coleman Collins A1 - Shantanu Debnath A1 - Andrew M. Ducore A1 - Kai M. Hudek A1 - Matthew Keesan A1 - Sarah M. Kreikemeier A1 - Jonathan Mizrahi A1 - Phil Solomon A1 - Mike Williams A1 - Jaime David Wong-Campos A1 - Christopher Monroe A1 - Jungsang Kim AB -

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.

UR - https://arxiv.org/abs/1902.10171 ER - TY - JOUR T1 - Toward convergence of effective field theory simulations on digital quantum computers Y1 - 2019 A1 - Omar Shehab A1 - Kevin A. Landsman A1 - Yunseong Nam A1 - Daiwei Zhu A1 - Norbert M. Linke A1 - Matthew J. Keesan A1 - Raphael C. Pooser A1 - Christopher R. Monroe AB -

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. 

UR - https://arxiv.org/abs/1904.04338 ER - TY - JOUR T1 - Automated optimization of large quantum circuits with continuous parameters JF - npj:Quantum Information Y1 - 2018 A1 - Yunseong Nam A1 - Neil J. Ross A1 - Yuan Su A1 - Andrew M. Childs A1 - Dmitri Maslov AB -

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. 

VL - 4 UR - https://arxiv.org/abs/1710.07345 CP - 23 U5 - https://doi.org/10.1038/s41534-018-0072-4 ER - TY - JOUR T1 - Toward the first quantum simulation with quantum speedup JF - Proceedings of the National Academy of Sciences Y1 - 2018 A1 - Andrew M. Childs A1 - Dmitri Maslov A1 - Yunseong Nam A1 - Neil J. Ross A1 - Yuan Su AB -

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.

VL - 115 U4 - 9456-9461 UR - https://arxiv.org/abs/1711.10980 U5 - https://doi.org/10.1073/pnas.1801723115 ER - TY - JOUR T1 - Optimal length of decomposition sequences composed of imperfect gates JF - Quantum Information Processing Y1 - 2017 A1 - Yunseong Nam A1 - R. Blümel AB -

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.

VL - 16 U4 - 123 UR - https://link.springer.com/article/10.1007/s11128-017-1571-5 U5 - 10.1007/s11128-017-1571-5 ER - TY - JOUR T1 - Use of global interactions in efficient quantum circuit constructions JF - New Journal of Physics Y1 - 2017 A1 - Dmitri Maslov A1 - Yunseong Nam AB -

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.

UR - http://iopscience.iop.org/article/10.1088/1367-2630/aaa398 U5 - 10.1088/1367-2630/aaa398 ER -