506 citations · 2.6k across the 68 of their papers we have counts for
70 papers
Decoder Model Compatibility Provides Information beyond the Logical Gap under Drifting and Correlated Quantum Noise
Aaron C. Hoyt, Chunshu Wu, Shuwen Kan +8
Quantum error-correcting decoders provide both corrections and confidence estimates for the logical-error risk of individual measurement records. Such confidence can guide postsele…
Performance Model for Hybrid Quantum-Classical Workflows
Pooja Rao, Dimitar Trenev, Jerome Gonthier +13
Hybrid quantum-classical workflows are expected to underpin practical quantum computing applications, yet the quantum and HPC communities lack a shared framework for reasoning abou…
Overlapped groupings for quantum energy estimation: Maximal variance reduction and deterministic algorithms for reducing variance
Jeremiah Rowland, Rahul Sarkar, Nicolas PD Sawaya +2
Grouping-based measurement strategies are widely used to reduce measurement complexity in near-term quantum algorithms. While these schemes have typically produced disjoint groups,…
The cost of quantum algorithms for biochemistry: A case study in metaphosphate hydrolysis
Ryan LaRose, Antonios M. Alvertis, Alan Bidart +10
We evaluate the quantum resource requirements for ATP/metaphosphate hydrolysis, one of the most important reactions in all of biology with implications for metabolism, cellular sig…
Hybrid continuous-discrete-variable quantum computing: a guide to utility
A. F. Kemper, Antonios Alvertis, Muhammad Asaduzzaman +24
Quantum computing has traditionally centered around the discrete variable paradigm. A new direction is the inclusion of continuous variable modes and the consideration of a hybrid…
Efficient Floating-Point Arithmetic on Fault-Tolerant Quantum Computers
José E. Cruz Serrallés, Oluwadara Ogunkoya, Do{g}a Murat Kürkçüo{g}lu +5
We propose a novel floating-point encoding scheme that builds on prior work involving fixed-point encodings. We encode floating-point numbers using Two's Complement fixed-point man…
Efficient Classical Processing of Constant-Depth Time Evolution Circuits in Control Hardware
Akhil Francis, Abhi D. Rajagopala, Norm M. Tubman +2
Improving quantum algorithms run-time performance involves several strategies such as reducing the quantum gate counts, decreasing the number of measurements, advancement in QPU te…
Theory of ab initio downfolding with arbitrary range electron-phonon coupling
Norm M. Tubman, Christopher J. N. Coveney, Chih-En Hsu +6
Ab initio downfolding describes the electronic structure of materials within a low-energy subspace, often around the Fermi level. Typically starting from mean-field calculations, t…
Phonon-mediated electron attraction in SrTiO via the generalized Fröhlich and deformation potential mechanisms
Christopher J. N. Coveney, Norm M. Tubman, Chih-En Hsu +6
Superconductivity in doped SrTiO was discovered in 1964, the first superconducting transition observed in a doped semiconductor. However, the mechanism of electron pairing in S…
Classical Pre-optimization Approach for ADAPT-VQE: Maximizing the Potential of High-Performance Computing Resources to Improve Quantum Simulation of Chemical Applications
J. Wayne Mullinax, Panagiotis G. Anastasiou, Jeffrey Larson +2
The ADAPT-VQE algorithm is a promising method for generating a compact ansatz based on derivatives of the underlying cost function, and it yields accurate predictions of electronic…
Artificial Intelligence for Quantum Computing
Yuri Alexeev, Marwa H. Farag, Taylor L. Patti +25
Artificial intelligence (AI) advancements over the past few years have had an unprecedented and revolutionary impact across everyday application areas. Its significance also extend…
Compressing Hamiltonians with ab initio downfolding for simulating strongly-correlated materials on quantum computers
Antonios M. Alvertis, Abid Khan, Norm M. Tubman
The accurate first-principles description of strongly-correlated materials is an important and challenging problem in condensed matter physics. Ab initio downfolding has emerged as…
Surrogate Constructed Scalable Circuits ADAPT-VQE in the Schwinger model
Erik Gustafson, Kyle Sherbert, Adrien Florio +8
Inspired by recent advancements of simulating periodic systems on quantum computers, we develop a new approach, (SC)-ADAPT-VQE, to further advance the simulation of these syste…
Non-Clifford diagonalization for measurement shot reduction in quantum expectation value estimation
Nicolas P. D. Sawaya, Daan Camps, Ben DalFavero +3
Estimating expectation values on near-term quantum computers often requires a prohibitively large number of measurements. One widely-used strategy to mitigate this problem has been…
Classical Benchmarks for Variational Quantum Eigensolver Simulations of the Hubbard Model
Antonios M. Alvertis, Abid Khan, Thomas Iadecola +2
Simulating the Hubbard model is of great interest to a wide range of applications within condensed matter physics, however its solution on classical computers remains challenging i…
Towards Efficient Quantum Computation of Molecular Ground State Energies using Bayesian Optimization with Priors over Surface Topology
Farshud Sorourifar, Mohamed Taha Rouabah, Nacer Eddine Belaloui +6
Variational Quantum Eigensolvers (VQEs) represent a promising approach to computing molecular ground states and energies on modern quantum computers. These approaches use a classic…
Bayesian Optimization Priors for Efficient Variational Quantum Algorithms
Farshud Sorourifar, Diana Chamaki, Norm M. Tubman +2
Quantum computers currently rely on a hybrid quantum-classical approach known as Variational Quantum Algorithms (VQAs) to solve problems. Still, there are several challenges with V…
Quantum Hardware-Enabled Molecular Dynamics via Transfer Learning
Abid Khan, Prateek Vaish, Yaoqi Pang +8
The ability to perform ab initio molecular dynamics simulations using potential energies calculated on quantum computers would allow virtually exact dynamics for chemical and bioch…
Surrogate optimization of variational quantum circuits
Erik J. Gustafson, Juha Tiihonen, Diana Chamaki +8
Variational quantum eigensolvers are touted as a near-term algorithm capable of impacting many applications. However, the potential has not yet been realized, with few claims of qu…
A circuit-generated quantum subspace algorithm for the variational quantum eigensolver
Mark R. Hirsbrunner, J. Wayne Mullinax, Yizhi Shen +4
Recent research has shown that wavefunction evolution in real- and imaginary-time can generate quantum subspaces with significant utility for obtaining accurate ground state energi…
Simple Diagonal State Designs with Reconfigurable Real-Time Circuits
Yizhi Shen, Katherine Klymko, Eran Rabani +4
Unitary designs are widely used in quantum computation, but in many practical settings it suffices to construct a diagonal state design generated with unitary gates diagonal in the…
Pre-optimizing variational quantum eigensolvers with tensor networks
Abid Khan, Bryan K. Clark, Norm M. Tubman
The variational quantum eigensolver (VQE) is a promising algorithm for demonstrating quantum advantage in the noisy intermediate-scale quantum (NISQ) era. However, optimizing VQE f…
HamLib: A library of Hamiltonians for benchmarking quantum algorithms and hardware
Nicolas PD Sawaya, Daniel Marti-Dafcik, Yang Ho +13
In order to characterize and benchmark computational hardware, software, and algorithms, it is essential to have many problem instances on-hand. This is no less true for quantum co…
Estimating Eigenenergies from Quantum Dynamics: A Unified Noise-Resilient Measurement-Driven Approach
Yizhi Shen, Daan Camps, Aaron Szasz +5
Ground state energy estimation in physical, chemical, and materials sciences is one of the most promising applications of quantum computing. In this work, we introduce a new hybrid…