Publications (44)
Measuring the Capabilities of Quantum Computers
Timothy Proctor, Kenneth Rudinger, Kevin Young +2
A quantum computer has now solved a specialized problem believed to be intractable for supercomputers, suggesting that quantum processors may soon outperform supercomputers on scie…
Platform-Agnostic Modular Architecture for Quantum Benchmarking
Neer Patel, Anish Giri, Hrushikesh Pramod Patil +6
We present a platform-agnostic modular architecture that addresses the increasingly fragmented landscape of quantum computing benchmarking by decoupling problem generation, circuit…
Simulating Quantum Error Correction beyond Pauli Stochastic Errors
Jordan Hines, Corey Ostrove, Kenneth Rudinger +4
Quantum error correction (QEC), the lynchpin of fault-tolerant quantum computing (FTQC), is designed and validated against well-behaved Pauli stochastic error models. But in real-w…
Benchmarking quantum computers
Timothy Proctor, Kevin Young, Andrew D. Baczewski +1
The rapid pace of development in quantum computing technology has sparked a proliferation of benchmarks for assessing the performance of quantum computing hardware and software. Go…
Quantum Circuit Transformations with a Multi-Level Intermediate Representation Compiler
Thien Nguyen, Dmitry Lyakh, Raphael C. Pooser +3
Quantum computing promises remarkable approaches for processing information, but new tools are needed to compile program representations into the physical instructions required by…
Probing context-dependent errors in quantum processors
Kenneth Rudinger, Timothy Proctor, Dylan Langharst +3
Gates in error-prone quantum information processors are often modeled using sets of one- and two-qubit process matrices, the standard model of quantum errors. However, the results…
Scalable linearized gate set tomography
Ashe Miller, Corey Ostrove, Jordan Hines +4
Characterizing errors on many-qubit quantum computers remains a key challenge to understanding and improving the performance of these devices. Current characterization methods eith…
Wildcard error: Quantifying unmodeled errors in quantum processors
Robin Blume-Kohout, Kenneth Rudinger, Erik Nielsen +2
Error models for quantum computing processors describe their deviation from ideal behavior and predict the consequences in applications. But those processors' experimental behavior…
Quantum circuit debugging and sensitivity analysis via local inversions
Fernando A. Calderon-Vargas, Timothy Proctor, Kenneth Rudinger +1
As the width and depth of quantum circuits implemented by state-of-the-art quantum processors rapidly increase, circuit analysis and assessment via classical simulation are becomin…
Generating non-classical states from spin coherent states via interaction with ancillary spins
Shane Dooley, Jaewoo Joo, Timothy Proctor +1
The generation of non-classical states of large quantum systems has attracted much interest from a foundational perspective, but also because of the significant potential of such s…
Application-Oriented Performance Benchmarks for Quantum Computing
Thomas Lubinski, Sonika Johri, Paul Varosy +6
In this work we introduce an open source suite of quantum application-oriented performance benchmarks that is designed to measure the effectiveness of quantum computing hardware at…
Efficient flexible characterization of quantum processors with nested error models
Erik Nielsen, Kenneth Rudinger, Timothy Proctor +2
We present a simple and powerful technique for finding a good error model for a quantum processor. The technique iteratively tests a nested sequence of models against data obtained…
Benchmarking quantum logic operations relative to thresholds for fault tolerance
Akel Hashim, Stefan Seritan, Timothy Proctor +6
Contemporary methods for benchmarking noisy quantum processors typically measure average error rates or process infidelities. However, thresholds for fault-tolerant quantum error c…
Software for Creating Scalable Benchmarks from Quantum Algorithms
Noah Siekierski, Stefan Seritan, Neer Patel +3
Creating scalable, reliable, and well-motivated benchmarks for quantum computers is challenging: straightforward approaches to benchmarking suffer from exponential scaling, are ins…
Quantum Characterization, Verification, and Validation
Robin Blume-Kohout, Timothy Proctor, Kevin Young
Quantum characterization, verification, and validation (QCVV) is a set of techniques to probe, describe, and assess the behavior of quantum bits (qubits), quantum information-proce…
Easy better quantum process tomography
Robin Blume-Kohout, Kenneth Rudinger, Timothy Proctor
Quantum process tomography (QPT), used to estimate the linear map that best describes a quantum operation, is usually performed using a priori assumptions about state preparation a…
Scalable Full-Stack Benchmarks for Quantum Computers
Jordan Hines, Timothy Proctor
Quantum processors are now able to run quantum circuits that are infeasible to simulate classically, creating a need for benchmarks that assess a quantum processor's rate of errors…
Benchmarking quantum computers with any quantum algorithm
Stefan K. Seritan, Aditya Dhumuntarao, Aidan Q. Wilber-Gauthier +5
Application-based benchmarks are increasingly used to quantify and compare quantum computers' performance. However, because contemporary quantum computers cannot run utility-scale…
Predictive Models from Quantum Computer Benchmarks
Daniel Hothem, Jordan Hines, Karthik Nataraj +2
Holistic benchmarks for quantum computers are essential for testing and summarizing the performance of quantum hardware. However, holistic benchmarks -- such as algorithmic or rand…
A Theory of Direct Randomized Benchmarking
Anthony M. Polloreno, Arnaud Carignan-Dugas, Jordan Hines +3
Randomized benchmarking (RB) protocols are widely used to measure an average error rate for a set of quantum logic gates. However, the standard version of RB is limited because it…
Pauli Noise Learning for Mid-Circuit Measurements
Jordan Hines, Timothy Proctor
Current benchmarks for mid-circuit measurements (MCMs) are limited in scalability or the types of error they can quantify, necessitating new techniques for quantifying their perfor…
A simple asymptotically optimal Clifford circuit compilation algorithm
Timothy Proctor, Kevin Young
We present an algorithm that decomposes any -qubit Clifford operator into a circuit consisting of three subcircuits containing only CNOT or CPHASE gates with layers of one-qubit…
Characterizing mid-circuit measurements on a superconducting qubit using gate set tomography
Kenneth Rudinger, Guilhem J. Ribeill, Luke C. G. Govia +6
Measurements that occur within the internal layers of a quantum circuit -- mid-circuit measurements -- are an important quantum computing primitive, most notably for quantum error…
Detecting crosstalk errors in quantum information processors
Mohan Sarovar, Timothy Proctor, Kenneth Rudinger +3
Crosstalk occurs in most quantum computing systems with more than one qubit. It can cause a variety of correlated and nonlocal crosstalk errors that can be especially harmful to fa…
A Practical Introduction to Benchmarking and Characterization of Quantum Computers
Akel Hashim, Long B. Nguyen, Noah Goss +16
Rapid progress in quantum technology has transformed quantum computing and quantum information science from theoretical possibilities into tangible engineering challenges. Breakthr…
Efficient simulation of Clifford circuits with small Markovian errors
Ashe Miller, Corey Ostrove, Jordan Hines +3
Classical simulation of noisy quantum circuits is essential for understanding quantum computing experiments. It enables scalable error characterization, analysis of how noise impac…
Helios: A 98-qubit trapped-ion quantum computer
Anthony Ransford, M. S. Allman, Jake Arkinstall +183
We report on Quantinuum Helios, a 98-qubit trapped-ion quantum processor based on the quantum charge-coupled device (QCCD) architecture. Helios features Ba hyperfine…
Learning a quantum computer's capability
Daniel Hothem, Kevin Young, Tommie Catanach +1
Accurately predicting a quantum computer's capability -- which circuits it can run and how well it can run them -- is a foundational goal of quantum characterization and benchmarki…
When Clifford benchmarks are sufficient; estimating application performance with scalable proxy circuits
Seth Merkel, Timothy Proctor, Samuele Ferracin +4
The goal of benchmarking is to determine how far the output of a noisy system is from its ideal behavior; this becomes exceedingly difficult for large quantum systems where classic…
Featuremetric benchmarking: Quantum computer benchmarks based on circuit features
Timothy Proctor, Anh Tran, Xingxin Liu +4
Benchmarks that concisely summarize the performance of many-qubit quantum computers are essential for measuring progress towards the goal of useful quantum computation. In this wor…
Detecting and tracking drift in quantum information processors
Timothy Proctor, Melissa Revelle, Erik Nielsen +5
If quantum information processors are to fulfill their potential, the diverse errors that affect them must be understood and suppressed. But errors typically fluctuate over time, a…
Measuring error rates of mid-circuit measurements
Daniel Hothem, Jordan Hines, Charles Baldwin +3
High-fidelity mid-circuit measurements, which read out the state of specific qubits in a multiqubit processor without destroying them or disrupting their neighbors, are a critical…
What randomized benchmarking actually measures
Timothy Proctor, Kenneth Rudinger, Kevin Young +2
Randomized benchmarking (RB) is widely used to measure an error rate of a set of quantum gates, by performing random circuits that would do nothing if the gates were perfect. In th…
Establishing trust in quantum computations
Timothy Proctor, Stefan Seritan, Erik Nielsen +4
Quantum computing hardware has grown sufficiently complex that it often can no longer be simulated by classical computers, but its computational power remains limited by errors. Th…
Scalable randomized benchmarking of quantum computers using mirror circuits
Timothy Proctor, Stefan Seritan, Kenneth Rudinger +3
The performance of quantum gates is often assessed using some form of randomized benchmarking. However, the existing methods become infeasible for more than approximately five qubi…
Experimental Characterization of Crosstalk Errors with Simultaneous Gate Set Tomography
Kenneth Rudinger, Craig W. Hogle, Ravi K. Naik +11
Crosstalk is a leading source of failure in multiqubit quantum information processors. It can arise from a wide range of disparate physical phenomena, and can introduce subtle corr…
Ancilla-driven quantum computation for qudits and continuous variables
Timothy Proctor, Melissa Giulian, Natalia Korolkova +2
Although qubits are the leading candidate for the basic elements in a quantum computer, there are also a range of reasons to consider using higher dimensional qudits or quantum con…
A Comprehensive Cross-Model Framework for Benchmarking the Performance of Quantum Hamiltonian Simulations
Avimita Chatterjee, Sonny Rappaport, Anish Giri +5
Quantum Hamiltonian simulation is one of the most promising applications of quantum computing and forms the basis for many quantum algorithms. Benchmarking them is an important gau…
The Road to Useful Quantum Computers
Timothy Proctor, Robin Blume-Kohout, Andrew Baczewski
Building a useful quantum computer is a grand science and engineering challenge, currently pursued intensely by teams around the world. In the 1980s, Richard Feynman and Yuri Manin…
Demonstrating scalable randomized benchmarking of universal gate sets
Jordan Hines, Marie Lu, Ravi K. Naik +12
Randomized benchmarking (RB) protocols are the most widely used methods for assessing the performance of quantum gates. However, the existing RB methods either do not scale to many…
Fully scalable randomized benchmarking without motion reversal
Jordan Hines, Daniel Hothem, Robin Blume-Kohout +2
We introduce binary randomized benchmarking (BiRB), a protocol that streamlines traditional RB by using circuits consisting almost entirely of i.i.d. layers of gates. BiRB reliably…
Probing quantum processor performance with pyGSTi
Erik Nielsen, Kenneth Rudinger, Timothy Proctor +3
PyGSTi is a Python software package for assessing and characterizing the performance of quantum computing processors. It can be used as a standalone application, or as a library, t…
A taxonomy of small Markovian errors
Robin Blume-Kohout, Marcus P. da Silva, Erik Nielsen +4
Errors in quantum logic gates are usually modeled by quantum process matrices (CPTP maps). But process matrices can be opaque, and unwieldy. We show how to transform a gate's proce…
What is my quantum computer good for? Quantum capability learning with physics-aware neural networks
Daniel Hothem, Ashe Miller, Timothy Proctor
Quantum computers have the potential to revolutionize diverse fields, including quantum chemistry, materials science, and machine learning. However, contemporary quantum computers…