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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Quantum tensor network algorithms for evaluation of spectral functions on quantum computers

We investigate quantum algorithms derived from tensor networks to simulate the static and dynamic properties of quantum many-body systems. Using a sequentially prepared quantum circuit representation of a matrix product state (MPS) that we call a quantum tensor network (QTN), we demonstrate algorithms to prepare ground and excited states on a quantum computer and apply them to molecular nanomagnets (MNMs) as a paradigmatic example. In this setting, we develop two approaches for extracting the spectral correlation functions measured in neutron-scattering experiments: (a) a generalization of the SWAP test for computing wave function overlaps and, (b) a generalization of the notion of matrix product operators to the QTN setting which generates a linear combination of unitaries. The latter method is discussed in detail for translationally invariant spin-half systems, where it is shown to reduce the qubit resource requirements compared with the SWAP method and may be generalized to other systems. We demonstrate the versatility of our approaches by simulating spin-1/2 and spin-3/2 MNMs, with the latter being an experimentally relevant model of a Cr$^{3+}_{8}$ ring. Here, our approach has qubit requirements that are independent of the number of constituents of the many-body system and scale only logarithmically with the bond dimension of the MPS representation, making them appealing for implementation on near-term quantum hardware with mid-circuit measurement and reset.

Neutron scattering↗
DOE OSTI2025

Radiative processes on a quantum computer

Radiative processes, where a photon/neutrino is emitted as a result of a collision or decay of a particle, play a central role in atomic, nuclear, and particle physics. Their rate is determined by certain off-diagonal matrix elements between different initial and final states. We propose a method to compute them using quantum computers. It relies on a single extra qubit that, in a certain sense, represents the photon/neutrino. The generic formula relating this matrix element to the amplitude and frequency of oscillations of the extra qubit is derived for the near-resonance case. Furthermore, we demonstrate the feasibility of the method by using it in actual quantum computations and simulations of simple systems.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Lie-algebraic classical simulations for quantum computing

The classical simulation of quantum dynamics plays an important role in our understanding of quantum complexity and in the development of quantum technologies. Efficient techniques such as those based on the Gottesman-Knill theorem for Clifford circuits, tensor networks for low entanglement-generating circuits, or Wick's theorem for fermionic Gaussian states have become central tools in quantum computing. In this work, we contribute to this body of knowledge by presenting a framework for classical simulations, dubbed “𝔤-sim”, which is based on the underlying Lie algebraic structure of the dynamical process. When the dimension of the algebra grows at most polynomially in the system size, there exist observables for which the simulation is efficient. Indeed, we show that 𝔤-sim enables new regimes for classical simulations, is able to deal with certain forms of noise in the evolution, as well as can be used to tackle several paradigmatic variational and nonvariational quantum computing tasks. For the former, we perform Lie-algebraic simulations to train and optimize parametrized quantum circuits (thus effectively showing that some variational models can be dequantized), design enhanced parameter initialization strategies, solve tasks of quantum circuit synthesis, and train a quantum-phase classifier. For the latter, we report large-scale noiseless and noisy simulations on benchmark problems. By comparing the limitations of 𝔤-sim and certain Wick's theorem-based simulations, we find that the two methods become inefficient for different types of states or observables, hinting at the existence of distinct, nonequivalent resources for classical simulation.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2009

Non-unitary probabilistic quantum computing circuit and method

A quantum circuit performing quantum computation in a quantum computer. A chosen transformation of an initial n-qubit state is probabilistically obtained. The circuit comprises a unitary quantum operator obtained from a non-unitary quantum operator, operating on an n-qubit state and an ancilla state. When operation on the ancilla state provides a success condition, computation is stopped. When operation on the ancilla state provides a failure condition, computation is performed again on the ancilla state and the n-qubit state obtained in the previous computation, until a success condition is obtained.

Williams, Colin P.↗
DOE OSTI2025

Benchmarking quantum computers

The rapid pace of development in quantum computing technology has sparked a proliferation of benchmarks to assess the performance of quantum computing hardware and software. However, not all benchmarks are of equal merit. Good ones empower scientists, engineers, programmers and users to understand the power of a computing system, whereas bad ones can misdirect research and inhibit progress. In this Perspective, we survey the science of quantum computer benchmarking. Here, we discuss the role of benchmarks and benchmarking and how good benchmarks can drive and measure progress towards the long-term goal of useful quantum computations, known as quantum utility. We explain how different kinds of benchmark quantify the performance of different parts of a quantum computer, discuss existing benchmarks, examine recent trends in benchmarking, and highlight important open research questions in this field.

Proctor, Timothy James [Sandia National Laboratori↗
DOE OSTI2026

Energy and physical resource impacts of quantum computing merit greater attention

Quantum computing research and development is growing worldwide; yet the energy and physical resource demands of future quantum-accelerated data centres are unknown. Planning for quantum computing requires strong collaboration between research communities across engineering, physics, environmental sciences, economics, policy, and energy systems and scenario modelling.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Quantum Computing Market Report

The quantum computing market is entering a rapid growth phase. Growth was originally driven by private investment interest in high value applications such as drug discovery, materials science, and finance. Currently the main market drivers include technical advances, continued private investment, and rising public funding. The quantum computing market is poised for explosive growth — with its market size estimated at $1.42 billion USD in 2024, and an expected compound annual growth rate of 20.5% from 2025 to 2030 [4]. Superconducting qubits are the largest qubit type by revenue. However, alternative approaches such as trapped ion, neutral atom, spin based, and photonic qubits are also attracting investment.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

How Do You Hear a Quantum Computer Whisper?

Quantum transduction is the process of upconverting microwave quantum signals into optical signals to develop quantum networks through optical fibers outside the dilution refrigerator, enabling connections between quantum technologies on the quantum internet. In this project, upconversion is achieved by directing an optical laser and the microwave quantum signal into an electro-optic bulk crystal. The crystal is housed within a Superconducting Radio Frequency (SRF) cavity designed to maximize the overlap between the microwave field and the crystal volume. In the presence of microwaves, the refractive index of the crystal changes through the Pockels effect. This change in refractive index modifies the propagation of the optical field within the crystal, allowing the quantum information carried by the microwave field to be transferred to the optical field. This study focuses on coupling laser light from suspended waveguide chips into the whispering-gallery modes (WGMs) of the crystal to enable transduction. The coupling efficiency between the optical field in the suspended waveguide and the WGM depends on the position of the laser spot on the crystal. To address this challenge, a feedback-based algorithm is being developed to fine-tune the waveguide position so that the optical signal is coupled efficiently into the crystal. After passing through the crystal, the optical signal is detected by a photodiode connected to an oscilloscope. The algorithm evaluates the coupling quality and iteratively adjusts the waveguide position to maximize coupling efficiency. The expected outcome is an automated waveguide alignment method that improves optical coupling and enables more efficient microwave-to-optical quantum transduction.

Karanastasis, Mihael [Fermilab]↗
DOE OSTI2024

ARQUIN: Architectures for Multinode Superconducting Quantum Computers

Many proposals to scale quantum technology rely on modular or distributed designs wherein individual quantum processors, called nodes, are linked together to form one large multinode quantum computer (MNQC). One scalable method to construct an MNQC is using superconducting quantum systems with optical interconnects. However, internode gates in these systems may be two to three orders of magnitude noisier and slower than local operations. Surmounting the limitations of internode gates will require improvements in entanglement generation, use of entanglement distillation, and optimized software and compilers. Still, it remains unclear what performance is possible with current hardware and what performance algorithms require. In this article, we employ a systems analysis approach to quantify overall MNQC performance in terms of hardware models of internode links, entanglement distillation, and local architecture. We show how to navigate tradeoffs in entanglement generation and distillation in the context of algorithm performance, lay out how compilers and software should balance between local and internode gates, and discuss when noisy quantum internode links have an advantage over purely classical links. Here, we find that a factor of 10–100× better link performance is required and introduce a research roadmap for the co-design of hardware and software towards the realization of early MNQCs. While we focus on superconducting devices with optical interconnects, our approach is general across MNQC implementations.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Quantum Circuits for the Preparation of Spin Eigenfunctions on Quantum Computers

The application of quantum algorithms to the study of many-particle quantum systems requires the ability to prepare wave functions that are relevant in the behavior of the system under study. Hamiltonian symmetries are important instruments used to classify relevant many-particle wave functions and to improve the efficiency of numerical simulations. In this work, quantum circuits for the exact and approximate preparation of total spin eigenfunctions on quantum computers are presented. Two different strategies are discussed and compared: exact recursive construction of total spin eigenfunctions based on the addition theorem of angular momentum, and heuristic approximation of total spin eigenfunctions based on the variational optimization of a suitable cost function. The construction of these quantum circuits is illustrated in detail, and the preparation of total spin eigenfunctions is demonstrated on IBM quantum devices, focusing on three- and five-spin systems on graphs with triangle connectivity.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2022

Control Implemented on Quantum Computers: Effects of Noise, Non-Determinism, and Entanglement

Quantum computing has advanced in recent years to the point that there are now some quantum computers and quantum simulators available to the public for use. In addition, quantum computing is beginning to receive attention within the process systems engineering community for directions such as machine learning and optimization. A logical next step for its evaluation within process systems engineering is for control, specifically, for computing control actions to be applied to process systems. In this work, we provide some initial studies regarding the implementation of control on quantum computers, including the implementation of a single-input/single-output proportional control law on a quantum simulator with noise, evaluation of potential impacts of non-determinism on theory for advanced control laws, and discussion of consequences of the way that entanglement works for next-generation manufacturing communication objectives.

Kip Nieman↗
DOE OSTI2025

Mathematical Foundation for Quantum Computing of Electromagnetic Wave Propagation in Dielectric Media

Can quantum computers effectively simulate the propagation and scattering of electromagnetic waves in a classical plasma? This chapter introduces some of the basic concepts in mathematics and physics essential to answering that question. The numerical simulations of Maxwell equations for wave propagation in dielectrics are constrained by technological limitations of the present-day computers. In contrast, there has been ample fanfare around quantum computers and their potential to far exceed the performance of traditional computers. Whether the enhanced capabilities of a quantum computer can be put to use for simulating topics in classical physics is a source of intrigue and curiosity.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRSDate not supplied

A Quantum Volume Metric for Qudit Quantum Computers

Qudit-based quantum computers, such as the high-Q superconducting radio frequency resonator cavities being pursued by the SQMS Center hosted at Fermilab, may provide computational advantages relative to qubit-based machines for some problems. However, the novel system’s hardware and software will present different errors that must be understood and mitigated, along with other unforeseen inefficiencies across the entire stack. It is essential to benchmark these qudit platforms against existing systems. We propose such a benchmark by generalizing the qubit-based quantum volume metric to qudit devices. In particular, we show that the performance depends on the available gateset used to compile unitary operations, as well as realistic noise sources.

Quantum Computing↗
DOE OSTI2025

Learning quantum computers' errors using interpretable neural networks

Learning and reducing the errors and noise in quantum computing systems is necessary for achieving quantum computation’s promise. However, rapid advances in experimental quantum computing are making this task increasingly difficult, because state-of-the-art systems now contain hundreds of qubits and many characterization techniques are hard to apply at this scale. Furthermore, complex kinds of errors in these systems, such as crosstalk and non-Markovian effects, must be understood and decreased, but these errors are challenging to study with most existing methods. In this project, we explored using neural networks for scalable characterization of complex errors in quantum computers. We proposed and demonstrated characterizing a quantum computer’s errors with neural networks that have interpretable parameters corresponding to the rates of different kinds of errors, within a sparse Lindbladian parameterization for errors. To enable scaling to many qubit systems, these networks then predict how these errors combine within quantum circuits and impact their outcomes using an efficient approximations. We demonstrated these networks ability to learn coherent crosstalk errors and context-dependent errors in a simulated 4-qubit system.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2017

Quantum Computation: Entangling with the Future

Commercial applications of quantum computation have become viable due to the rapid progress of the field in the recent years. Efficient quantum algorithms are discovered to cope with the most challenging real-world problems that are too hard for classical computers. Manufactured quantum hardware has reached unprecedented precision and controllability, enabling fault-tolerant quantum computation. Here, I give a brief introduction on what principles in quantum mechanics promise its unparalleled computational power. I will discuss several important quantum algorithms that achieve exponential or polynomial speedup over any classical algorithm. Building a quantum computer is a daunting task, and I will talk about the criteria and various implementations of quantum computers. I conclude the talk with near-future commercial applications of a quantum computer.

Jiang, Zhang↗
DOE OSTI2025

Playing Nonlocal Games across a Topological Phase Transition on a Quantum Computer

Many-body quantum games provide a natural perspective on phases of matter in quantum hardware, crisply relating the quantum correlations inherent in phases of matter to the securing of quantum advantage at a device-oriented task. In this Letter, we introduce a family of multiplayer quantum games for which topologically ordered phases of matter are a resource yielding quantum advantage. Unlike previous examples, quantum advantage persists away from the exactly solvable point and is robust to arbitrary local perturbations, irrespective of system size. We demonstrate this robustness experimentally on Quantinuum’s H1-1 quantum computer by playing the game with a continuous family of randomly deformed toric code states that can be created with constant-depth circuits leveraging midcircuit measurements and unitary feedback. We are thus able to tune through a topological phase transition—witnessed by the loss of robust quantum advantage—on currently available quantum hardware. This behavior is contrasted with an analogous family of deformed Greenberger-Horne-Zeilinger states, for which arbitrarily weak local perturbations destroy quantum advantage in the thermodynamic limit. Lastly, we discuss a topological interpretation of the game, which leads to a natural generalization involving an arbitrary number of players.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Unification of finite symmetries in the simulation of many-body systems on quantum computers

Symmetry is fundamental in the description and simulation of quantum systems. Leveraging symmetries in classical simulations of many-body quantum systems can result in significant overhead due to the exponentially growing size of some symmetry groups as the number of particles increases. Quantum computers hold the promise of achieving exponential speedup in simulating quantum many-body systems; however, a general method for utilizing symmetries in quantum simulations has not yet been established. In this work, we present a unified framework for incorporating symmetry group transforms on quantum computers to simulate many-body systems. The core of our approach lies in the development of efficient quantum circuits for symmetry-adapted projection onto irreducible representations of a group or pairs of commuting groups. We provide resource estimations for common groups, including the cyclic and permutation groups. Our algorithms demonstrate the capability to prepare coherent superpositions of symmetry-adapted states and to perform quantum evolution across a wide range of models in condensed-matter physics and ab initio electronic structure in quantum chemistry. Specifically, we execute a symmetry-adapted quantum subroutine for small molecules in first-quantization on noisy hardware and demonstrate the emulation of symmetry-adapted quantum phase estimation for preparing coherent superpositions of quantum states in various irreducible representations of a symmetry group. In addition, we present a discussion of open problems regarding treating symmetries in digital quantum simulations of many-body systems, paving the way for future systematic investigations into leveraging symmetries quantumly for practical quantum advantage. The broad applicability and rigorous resource estimation for symmetry transformations make our framework appealing for achieving provable quantum advantage on fault-tolerant quantum computers, especially for symmetry-related properties.

quantum algorithms↗
DOE OSTI2025

Quantum graph learning and algorithms applied in quantum computer sciences and image classification

Graph and network theory play a fundamental role in quantum computer sciences, including quantum information and computation. Random graphs and complex network theory are pivotal in predicting novel quantum phenomena, where entangled links are represented by edges. Quantum algorithms have been developed to enhance solutions for various network problems, giving rise to quantum graph computing and quantum graph learning (QGL). Here, in this review, we explore graph theory and graph learning methods as powerful tools for quantum computers to generate efficient solutions to problems beyond the reach of classical systems. We delve into the development of quantum complex network theory and its applications in quantum computation, materials discovery, and research. We also discuss quantum machine learning (QML) methodologies for effective image classification using qubits, quantum gates, and quantum circuits. Additionally, the paper addresses the challenges of QGL and algorithms, emphasizing the steps needed to develop flexible QGL solvers. This review presents a comprehensive overview of the fields of QGL and QML, highlights recent advancements, and identifies opportunities for future research.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗