Current Projects
Research Collaborations
Research projects are intended to advance the state-of-the-art in using quantum and classical computers for interesting applications. These projects feature close collaboration between UChicago and IBM researchers.
Verifying Error-Correcting Codes for Broad Deployment
This collaboration intends to produce a Coq library with implementations of a variety of error correcting codes. This library will be extensible, allowing users to add new variants of existing codes and novel codes that use familiar mathematical formalizers (for instance, stabilizers). Rand intends for this library to reflect error-correction as implemented on both the classical and quantum computer.
Robert Rand, Assistant Professor of Computer Science, University of Chicago
Next-Generation Quantum Algorithms & Software for Constrained Tomography in Scalable Quantum Molecular Computations
Quantum chemistry is one of the expected early transformative applications for quantum computing. However, most existing algorithms are severely limited by significant costs related to the scalable tomography of the two-electron reduced density matrix (2-RDM) on quantum devices. This collaboration proposes a novel Quantum-HPC algorithm for quantum tomography—combining classical shadow tomography, semidefinite programming (SDP), and a hierarchy of semidefinite constraints on the 2-RDM known as N-representability conditions—to transform quantum chemistry.
David Mazziotti, Professor of Chemistry, UChicago
Jeanette Garcia, Senior Research Manager for the Quantum Applications and Software, IBM Quantum
Kevin Sung, Software Engineer, IBM Quantum
Efficient Quantum System Calibration and Co-Designed Quantum Error Suppression
Efficiently calibrating quantum systems is crucial for large-scale quantum information processing. For example, efficient calibration of Pauli channels to mitigate errors from quantum gates is a pressing issue. This collaboration intends to develop sample-efficient protocols for calibrating Pauli channels, do efficient benchmarking of mid-circut measurment, and develop novel noise-resilient protocols and error suppression schemes for modular systems.
Liang Jiang, Professor of Molecular Engineering
Alireza Seif, Research Staff, IBM
Abhinav Kandala, Research Staff, IBM
Localized Quantum Chemistry Algorithms for Quantum Computers
This joint collaboration aims to create a hybrid quantum-classical methodology to study properties of strongly correlated systems with implementation on quantum computers. They plan to integrate their approach with neutral-atom quantum computer architectures to enhance stability and performance of hardware.
Laura Gagliardi, Richard & Kathy Leventhal Professor of Chemistry, Molecular Engineering, and James Franck Institute
Dr. Gavin Jones, Manager and Senior Research Scientist, Quantum Applications, IBM Quantum
Dr. Mario Motta, Senior Research Staff Member, IBM Quantum
Javier Robledo Moreno, Research Scientist, IBM Quantum
Kevin J. Sung, Software Engineer, IBM Quantum
Co-designing Quantum Machine Learning Algorithms for ‘Omics-based Oncology Applications
In tandem with QML design and model fitting, this collaboration will leverage and innovate on quantum error mitigation techniques. They will employ techniques, such as zero-noise extrapolation, pulse-level optimization techniques, measurements error mitigation, Clifford-guided optimizations, and noise-aware circuit synthesis. They will incorporate these techniques – as well as novel techniques that we will develop to exploit both application specific knowledge and hardware platform-specific information – within our designed algorithms to maximize their performance on quantum devices with hardware constraints (e.g., qubit connectivity, coherence time, and error rate).
Samantha Riesenfeld, Assistant Professor of Molecular Engineering
Fred Chong, Seymour Goodman Professor of Computer Science
Alexander Pearson, Associate Professor of Medicine
Ali Javadi-Abhari, IBM Quantum Compiler Manager and Research Staff Member
Nathan Earnest-Noble, IBM Quantum Algorith Engineering Global Lead and Technical Manager
Daniel Puzzuoli, IBM Software Engineer
Compute Projects
Compute projects are intended to provide UChicago researchers with access to state-of-the-art quantum computing hardware for the purposes of advancing scientific research and knowledge creation.
Exploring crosstalk and multiqubit operations on tunable-coupler hardware
This project aims to develop and use architectural analysis of superconducting systems to guide the co-design of hardware and quantum error correcting codes.
Exploring hardware implementations of VQE in the NISQ and near-term fault tolerant regime
This project aims to conduct explorations for the Variational Quantum Eigensolver (VQE) to design efficient software components that maximize the fidelity of execution of the VQE on NISQ and near fault-tolerant hardware.
Fred Chong, Seymour Goodman Professor of Computer Science