Quantum technologies, especially quantum computers, show great promise for revolutionizing highperformance computing and simulation. As prototype quantum computers come online, it is becoming clear that obtaining useful output from such devices will require layers of sophisticated classical software that provide interpretation and analysis of the quantum computer's state and output. OVERQC will develop critical components in this software stack with a particular focus on enabling nearterm Noisy IntermediateScale Quantum (NISQ) technologies. We have identified three critical needs for nearterm quantum computing platforms, and the project is structured around three thrusts that address these needs:
Thrust 1: develop capabilities to verify and certify translations of abstract quantum algorithms to quantum circuit programs;
Thrust 2: develop tools to identify the reliable information that can extracted from nearterm devices in the absence of faulttolerant operation;
Thrust 3: develop interfaces for variational hybrid quantumclassical processors (VHPs) that enable applications by connecting classical algorithms to quantum coprocessors.
The following figure illustrates how these thrusts fit into the conventional picture of a quantum computing software stack, and how the outcomes of each thrust inform the other ones.
A key aspect of OVERQC is that we will not only develop software tools targeted for use with nearterm quantum computers, but we will also invest significant effort into understanding the reliability and computational power of nearterm devices. In particular, we will address two key questions:
 Is it possible to engineer the dynamics of NISQ devices so that they have robust algorithmic properties in the presence relevant error models.
 What is the real computational advantage posed by algorithms running on NISQ devices, and specifically, what level/type of noise permits some computational advantage over classical algorithms and heuristics for the same tasks.
Answering these questions will not only guide the development of quantum algorithms tailored to nearterm quantum devices, but it will also reveal the fundamental computational potential of nonfaulttolerant quantum devices.
The fouryear project started in October 2018. The project's members are from Sandia National Laboratories, Los Alamos National Laboratory, Dartmouth College and University of New Mexico. OVERQC is closely linked to its sister project QOALAS, funded under the Quantum Algorithm Teams program of DOE/ASCR. Other DOE/ASCR projects the OVERQC team members collaborate with are:
 The Quantum Performance project led by the Quantum Performance Laboratory at Sandia.
 QAT4Chem led by Lawrence Berkeley National Lab.
 Heterogeneous DigitalAnalog Quantum Dynamics Simulations (HDAQDS) led by Oak Ridge National Lab.
 STAQC led by Oak Ridge National Lab.
Members of the OVERQC Project
View the OVERQC Publications
Mohan Sarovar, Lead PI, Thrust 2 Lead, Sandia National Laboratories. Expertise: Quantum computing, quantum control, open quantum systems. 

Andrew Baczewski, Thrust 3 Lead, Sandia National Laboratories. Expertise: Quantum simulation, qubit modeling, numerical analysis, and materials science.


Wayne Witzel, Thrust 1 Lead, Sandia National Laboratories. Expertise: Quantum computing, qubit modeling, software for theorem proving. 

Patrick Coles, PI, Los Alamos National Laboratory. Expertise: Quantum computing, quantum algorithms. 

James Whitfield, PI, Dartmouth College. Expertise: Quantum computing, electronic structure, molecular physics. 

Ojas Parekh, Sandia National Laboratories. Expertise: Quantum optimization, discrete optimization, algorithm design and analysis. 

Matthew Grace, Sandia National Laboratories. Expertise: Control, analysis, and simulation of quantum dynamical systems, especially in the context of quantum information and devices 

Denis Ridzal, Sandia National Laboratories. Expertise: Applied mathematics, numerical analysis, numerical optimization 

Greg von Winckel, Sandia National Laboratories. Expertise: Applied mathematics, numerical analysis, numerical optimization 

Kenneth Rudinger, Sandia National Laboratories. Expertise: Quantum computing, quantum algorithms, quantum characterization, verification and validation 

Antonio Russo, Sandia National Laboratories. Expertise: Quantum computing, condensed matter theory, topological order 

Lucas Kocia, Sandia National Laboratories. Expertise: Semiclassical theory, quantum computing 

Geoffrey Hulette, Sandia National Laboratories. Expertise: Formal methods, logic, trusted digital systems 

Lukasz Cincio, Los Alamos National Laboratory. Expertise: Quantum computing, computational quantum manybody physics, machinelearning


Yigit Subasi, Los Alamos National Laboratory. Expertise: Quantum computing, quantum thermodynamics, nonequilibrium statistical mechanics


Jon Aytac, Sandia National Laboratories. Expertise: Formal methods, quantum computing 

Alicia Magann, Sandia National Laboratories and Princeton University. Expertise: Quantum control, quantum computing, molecular systems 