output
20172025
most citedQuantum Chemistry in the Age of Quantum Computing

1.5k citations

46 papers

quant-ph2025

Variational decision diagrams for quantum-inspired machine learning applications

Vladimir Vargas-Calderón, Santiago Acevedo-Mancera, Herbert Vinck-Posada

Decision diagrams (DDs) have emerged as an efficient tool for simulating quantum circuits due to their capacity to exploit data redundancies in quantum states and quantum operation…

quant-ph2024★ 3 cited

Feasibility of accelerating homogeneous catalyst discovery with fault-tolerant quantum computers

Nicole Bellonzi, Alexander Kunitsa, Joshua T. Cantin +16

The industrial manufacturing of chemicals consumes a significant amount of energy and raw materials. In principle, the development of new catalysts could greatly improve the effici…

quant-ph2024★ 2 cited

Superconducting qubits in the millions: the potential and limitations of modularity

S. N. Saadatmand, Tyler L. Wilson, Mark J. Hodson +11

The development of fault-tolerant quantum computers (FTQCs) is receiving increasing attention within the quantum computing community. Like conventional digital computers, FTQCs, wh…

math.NA2024★ 4 cited

Cons-training Tensor Networks: Embedding and Optimization Over Discrete Linear Constraints

Javier Lopez-Piqueres, Jing Chen

In this study, we introduce a novel family of tensor networks, termed constrained matrix product states (MPS), designed to incorporate exactly arbitrary discrete linear constraints…

quant-ph2023★ 99 cited

Early Fault-Tolerant Quantum Computing

Amara Katabarwa, Katerina Gratsea, Athena Caesura +1

Over the past decade, research in quantum computing has tended to fall into one of two camps: near-term intermediate scale quantum (NISQ) and fault-tolerant quantum computing (FTQC…

quant-ph2023★ 13 cited

Modeling the Performance of Early Fault-Tolerant Quantum Algorithms

Qiyao Liang, Yiqing Zhou, Archismita Dalal +1

Progress in fault-tolerant quantum computation (FTQC) has driven the pursuit of practical applications with early fault-tolerant quantum computers (EFTQC). These devices, limited i…

quant-ph2023★ 6 cited

Efficient ground-state energy estimation and certification on early fault-tolerant quantum computers

Guoming Wang, Daniel Stilck França, Gumaro Rendon +1

A major thrust in quantum algorithm development over the past decade has been the search for the quantum algorithms that will deliver practical quantum advantage first. Today's qua…

physics.chem-ph2023★ 6 cited

Ionization Potentials of First-Row Transition Metal Aqua Ions

Daniel Mejia-Rodriguez, Alexander A. Kunitsa, Edoardo Aprà +1

We report computations of the vertical ionization potentials within the approximation of the near-complete series of first-row transition metal (V-Cu) aqua ions in their most…

cond-mat.str-el2023★ 9 cited

Matrix Product Study of Spin Fractionalization in the 1D Kondo Insulator

Jing Chen, E. Miles Stoudenmire, Yashar Komijani +1

The Kondo lattice is one of the classic examples of strongly correlated electronic systems. We conduct a controlled study of the Kondo lattice in one dimension, highlighting the ro…

quant-ph2022★ 20 cited

Improved Accuracy for Trotter Simulations Using Chebyshev Interpolation

Gumaro Rendon, Jacob Watkins, Nathan Wiebe

Quantum metrology allows for measuring properties of a quantum system at the optimal Heisenberg limit. However, when the relevant quantum states are prepared using digital Hamilton…

quant-ph2022★ 15 cited

Symmetric Tensor Networks for Generative Modeling and Constrained Combinatorial Optimization

Javier Lopez-Piqueres, Jing Chen, Alejandro Perdomo-Ortiz

Constrained combinatorial optimization problems abound in industry, from portfolio optimization to logistics. One of the major roadblocks in solving these problems is the presence…

quant-ph2022★ 88 cited

Exploring the Advantages of Quantum Generative Adversarial Networks in Generative Chemistry

Po-Yu Kao, Ya-Chu Yang, Wei-Yin Chiang +8

De novo drug design with desired biological activities is crucial for developing novel therapeutics for patients. The drug development process is time and resource-consuming, and i…

quant-ph2022★ 10 cited

On proving the robustness of algorithms for early fault-tolerant quantum computers

Rutuja Kshirsagar, Amara Katabarwa, Peter D. Johnson

The hope of the quantum computing field is that quantum architectures are able to scale up and realize fault-tolerant quantum computing. Due to engineering challenges, such ''cheap…

quant-ph2022★ 62 cited

Quantum algorithm for ground state energy estimation using circuit depth with exponentially improved dependence on precision

Guoming Wang, Daniel Stilck França, Ruizhe Zhang +2

A milestone in the field of quantum computing will be solving problems in quantum chemistry and materials faster than state-of-the-art classical methods. The current understanding…

quant-ph2022★ 3 cited

Noise tailoring for Robust Amplitude Estimation

Archismita Dalal, Amara Katabarwa

A universal fault-tolerant quantum computer holds the promise to speed up computational problems that are otherwise intractable on classical computers; however, for the next decade…

quant-ph2022★ 65 cited

Synergy Between Quantum Circuits and Tensor Networks: Short-cutting the Race to Practical Quantum Advantage

Manuel S. Rudolph, Jacob Miller, Danial Motlagh +3

While recent breakthroughs have proven the ability of noisy intermediate-scale quantum (NISQ) devices to achieve quantum advantage in classically-intractable sampling tasks, the us…

quant-ph2022★ 15 cited

Neural network enhanced measurement efficiency for molecular groundstates

Dmitri Iouchtchenko, Jérôme F. Gonthier, Alejandro Perdomo-Ortiz +1

It is believed that one of the first useful applications for a quantum computer will be the preparation of groundstates of molecular Hamiltonians. A crucial task involving state pr…

quant-ph2022★ 5 cited

Near-term quantum algorithm for computing molecular and materials properties based on recursive variational series methods

Phillip W. K. Jensen, Peter D. Johnson, Alexander A. Kunitsa

Determining the properties of molecules and materials is one of the premier applications of quantum computing. A major question in the field is: how might we use imperfect near-ter…

physics.chem-ph2022★ 32 cited

On the basis set selection for molecular core-level calculations

Daniel Mejia-Rodriguez, Alexander Kunitsa, Edoardo Aprà +1

The approximation has been recently gaining popularity among the method for simulating molecular core-level X-ray photoemission spectra. Traditionally, core-level binding…

quant-ph2022★ 19 cited

State Preparation Boosters for Early Fault-Tolerant Quantum Computation

Guoming Wang, Sukin Sim, Peter D. Johnson

Quantum computing is believed to be particularly useful for the simulation of chemistry and materials, among the various applications. In recent years, there have been significant…

quant-ph2021★ 50 cited

Computing Ground State Properties with Early Fault-Tolerant Quantum Computers

Ruizhe Zhang, Guoming Wang, Peter Johnson

Significant effort in applied quantum computing has been devoted to the problem of ground state energy estimation for molecules and materials. Yet, for many applications of practic…

quant-ph2021★ 17 cited

Connecting geometry and performance of two-qubit parameterized quantum circuits

Amara Katabarwa, Sukin Sim, Dax Enshan Koh +1

Parameterized quantum circuits (PQCs) are a central component of many variational quantum algorithms, yet there is a lack of understanding of how their parameterization impacts alg…

quant-ph2021★ 19 cited

Quantum algorithm for credit valuation adjustments

Javier Alcazar, Andrea Cadarso, Amara Katabarwa +4

Quantum mechanics is well known to accelerate statistical sampling processes over classical techniques. In quantitative finance, statistical samplings arise broadly in many use cas…

quant-ph2020★ 55 cited

Analyzing the Performance of Variational Quantum Factoring on a Superconducting Quantum Processor

Amir H. Karamlou, William A. Simon, Amara Katabarwa +3

In the near-term, hybrid quantum-classical algorithms hold great potential for outperforming classical approaches. Understanding how these two computing paradigms work in tandem is…