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Advancing Science with Quantum

Our researchers are exploring the application of quantum computing for discoveries in physics, chemistry, biology, and more.


Advancing Integrated Development Environments for Quantum Computing through Fundamental Research (AIDE-QC)

Scientists are developing and delivering open-source computing, programming, and simulation environment that supports the diversity of quantum computing research at the Department of Energy. AIDE-QC efforts focus on programming languages, compilers and verification, and debugging of quantum simulations. All of this will be packaged in an integrated software development environment. Contact: Bert de Jong (de Jong on the Web)

HEP Quantum Pattern Recognition (HEP.QPR)

As ever more powerful accelerators flood detectors with billions of charged particle tracks per second, classical iterative pattern recognition algorithms are becoming the limiting factor in the discovery potential of many HEP experiments. Quantum Pattern Recognition (QPR) algorithms have the potential to provide orders of magnitude speed improvements and increased precision. The HEP.QPR pilot project aims to create a community of computer scientists and physicists dedicated to addressing the challenges of HEP pattern recognition and to start building a suite of promising QPR algorithms and tools. Contact: Heather Gray(Gray on the Web)

Quantum Information Science (QIS) at NERSC

[email protected] program awarded more than 250,000 Perlmutter GPU node hours to pioneering research efforts, including simulating defects in materials for QIS, applying quantum deep learning algorithms to high energy physics data analysis, and developing surrogate models for variational quantum algorithms, to name just a few. Contacts: Katie Klymko, Nick Wright

Quantum Computing for High Energy Physics

Our quantum computing activities span HEP phenomenology, formal theory, and experiment. In phenomenology, we aim to develop quantum algorithms to enable calculations and simulations that are intractable using classical computers. In formal theory, we will develop a new quantum circuit on near-term devices that can teleport multiple qubits using fast-scrambling dynamics of black holes, and study of the ground state. We will study how quantum algorithms can improve particle tracking algorithms in HEP experiments. Contact: Maurice Garcia-Sciveres

Quantum Algorithms Team

This integrated team of scientists develops quantum algorithms for chemical sciences working closely working together with computer scientists, applied mathematicians, and quantum hardware developers. Bert de Jong (de Jong on the Web)

Architecture for Quantum Time-dependent Circuits (ArQTiC)

ArQTiC is a domain-specific full-stack software package built for the dynamic simulations of materials on quantum computers. Its main contributions include providing a software library for high-level programming of such simulations on quantum computers and providing post-processing capabilities that allow users to analyze results from the quantum computer more efficiently. Paired with the power to optimize and execute quantum circuits, ArQTiC opens the field of dynamic materials simulations on quantum computers to a broader community of scientists from a wider range of domain sciences, paving the way for accelerated progress towards physical quantum supremacy. Contacts: Lindsay Bassman, Katie Klymko

Fundamental Algorithmic Research for Quantum Computing (FAR-QC)

The FAR-QC team is exploring and identifying scientific domains and problems for which quantum resources may offer significant advantages over classical counterparts, which is vital in realizing the potential of quantum computing. FAR-QC seeks to deliver quantum algorithms that offer provable asymptotic advantages over the best-known or best-possible classical counterparts. Contact: Bert de Jong (Berkeley Lab Lead)

Quantum Numerical Linear Algebra

We are developing efficient algorithms for solving eigenvalue problems, linear systems of equations, and block encodings of sparse matrices. Contacts: Lin Lin, Chao Yang

Quantum Signal Processing

We are developing an optimization-based algorithm for a robust solution of phase factors in quantum signal processing, which can be used in a variety of scientific computing applications. Contact: Lin Lin


QCLAB is an object-oriented software library for creating and representing quantum circuits. QCLAB can be used for rapid prototyping and testing of quantum algorithms and allows for fast algorithm development and discovery. QCLAB provides I/O through openQASM making it compatible with quantum hardware. Contact: Roel Van Beeumen (Van Beeumen on the Web)


Fast Free Fermion Compiler (F3C) is a software library for compiling time-evolution quantum circuits of spin Hamiltonians that can be mapped to free fermions. Contact: Roel Van Beeumen (Van Beeumen on the Web)


Fast Approximate BLock Encodings (FABLE) is a software library for synthesizing quantum circuits of approximate block-encodings of matrices. A block-encoding is the embedding of a matrix in the leading block of a larger unitary matrix. Contact: Roel Van Beeumen (Van Beeumen on the Web)