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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

High-fidelity dimer excitations using quantum hardware

The quantum simulation of entangled spin systems can play a central role in quantum magnetic materials discovery. Additionally, the simulation of spectroscopic signatures, such as the dynamical structure factor accessed in inelastic neutron scattering (INS), necessitates a long timescale for circuit evolution. This is because the energy resolution is directly related to the time over which the circuit could be meaningfully evolved. However, canonical Trotterization requires deep circuits precluding such long-time evolution—even for a small number of qubits. Here, in this study, we demonstrate “direct” resource efficient fast-forwarding (REFF) measurements with short-depth circuits that can be used to capture longer time dynamics of spin Hamiltonians. We showcase the results of the dynamics of a quantum spin dimer, the basic quantum unit of emergent many-body spin systems, whose density of states we simulate accurately. The long temporal evolution and measurement of the two-spin correlation functions enable the calculation of the dynamical structure factor S⁡(Q = 0, ω) measured in the neutron scattering cross-section. We exhibit the clarity of the triplet gap and the triplet splitting of the quantum dimer with class-leading fidelity that enables comparison to experimental neutron data. Our results on current circuit hardware outline an important workflow to predict and benchmark against the outputs of INS experiments of quantum magnets.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Experimental advances with the QICK (Quantum Instrumentation Control Kit) for superconducting quantum hardware

The Quantum Instrumentation Control Kit (QICK) is a standalone open-source qubit controller that was first introduced in 2022. In this follow-up work, we present recent upgrades to the QICK and the experimental use cases they uniquely enabled for superconducting qubit systems. These include multiplexed signal generation and readout, mixer-free readout, predistorted fast flux pulses, and phase-coherent pulses for parametric operations, including high-fidelity parametric entangling gates. We explain in detail how the QICK was used to enable these experiments.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Quantum Simulation of Molecular Dynamics Processes─A Benchmark Study Using a Classical Simulator and Present-Day Quantum Hardware

Here, we explore how the fundamental problems in quantum molecular dynamics can be modeled using classical simulators (emulators) of quantum computers and the actual quantum hardware available to us today. The list of problems we tackle includes propagation of a free wave packet, vibration of a harmonic oscillator, and tunneling through a barrier. Each of these problems starts with the initial wave packet setup. Although Qiskit provides a general method for initializing wave functions, in most cases it generates deep quantum circuits. While these circuits perform well on noiseless simulators, they suffer from excessive noise on quantum hardware. To overcome this issue, we designed a shallower quantum circuit for preparing a Gaussian-like initial wave packet, which improves the performance of real hardware. Next, quantum circuits are implemented to apply the kinetic and potential energy operators for the evolution of a wave function over time. The results of our modeling on classical emulators of quantum hardware agree perfectly with the results obtained using the traditional (classical) methods. This serves as a benchmark and demonstrates that the quantum algorithms and Qiskit codes we developed are accurate. However, the results obtained on the actual quantum hardware available today, such as IBM’s superconducting qubits and IonQ’s trapped ions, indicate large discrepancies due to hardware limitations. This work highlights both the potential and challenges of using quantum computers to solve fundamental quantum molecular dynamics problems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Long-time simulations for fixed input states on quantum hardware

Publicly accessible quantum computers open the exciting possibility of experimental dynamical quantum simulations. While rapidly improving, current devices have short coherence times, restricting the viable circuit depth. Despite these limitations, we demonstrate long-time, high fidelity simulations on current hardware. Specifically, we simulate an XY-model spin chain on Rigetti and IBM quantum computers, maintaining a fidelity over 0.9 for 150 times longer than is possible using the iterated Trotter method. Our simulations use an algorithm we call fixed state Variational Fast Forwarding (fsVFF). Recent work has shown an approximate diagonalization of a short time evolution unitary allows a fixed-depth simulation. fsVFF substantially reduces the required resources by only diagonalizing the energy subspace spanned by the initial state, rather than over the total Hilbert space. We further demonstrate the viability of fsVFF through large numerical simulations, and provide an analysis of the noise resilience and scaling of simulation errors.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Demonstration of Quantum Energy Teleportation on Superconducting Quantum Hardware

Teleporting physical quantities to remote locations remains a key challenge for quantum information science and technology. Quantum teleportation has enabled the transfer of quantum information, but teleportation of quantum physical quantities has not yet been realized. Here we report the realization and observation of quantum energy teleportation on real superconducting quantum hardware. We achieve this by using several IBM superconducting quantum computers. The results are consistent with the exact solution of the theory and are improved by the mitigation of measurement error. Quantum energy teleportation requires only local operations and classical communication. Furthermore, our results provide a realistic benchmark that is fully achievable with current quantum computing and communication technologies.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Determining quantum phase diagrams of topological Kitaev-inspired models on NISQ quantum hardware

Topological protection is employed in fault-tolerant error correction and in developing quantum algorithms with topological qubits. But, topological protection intrinsic to models being simulated , also robustly protects calculations, even on NISQ hardware. We leverage it by simulating Kitaev-inspired models on IBM quantum computers and accurately determining their phase diagrams. This requires constructing conventional quantum circuits for Majorana braiding to prepare the ground states of Kitaev-inspired models. The entanglement entropy is then measured to calculate the quantum phase boundaries. We show how maintaining particle-hole symmetry when sampling through the Brillouin zone is critical to obtaining high accuracy. This work illustrates how topological protection intrinsic to a quantum model can be employed to perform robust calculations on NISQ hardware, when one measures the appropriate protected quantum properties. It opens the door for further simulation of topological quantum models on quantum hardware available today.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Simulations for HEP with SQMS Quantum Hardware (Snowmass2021 - Letter of Interest)

The Superconducting Quantum Materials and Systems (SQMS) Center, a Fermilab lead NQI center, will develop and deploy a beyond state of the art quantum computers. These systems will exhibit long coherent times, and a high degree of connectivity. We are interested in exploring the utility of these devices to address computational challenges in HEP, such as the simulation of strongly coupled quantum field theories. A progression of toy models and simulations can begin to chart a course towards simulating QCD-like systems.

42 ENGINEERING↗
DOE OSTI2020

Error-mitigated data-driven circuit learning on noisy quantum hardware

Application-level benchmarks measure how well a quantum device performs meaningful calculations. In the case of parameterized circuit training, the computational task is the preparation of a target quantum state via optimization over a loss landscape. This is complicated by various sources of noise, fixed hardware connectivity, and generative modeling, the choice of target distribution. Gradient-based training has become a useful benchmarking task for noisy intermediate-scale quantum computers because of the additional requirement that the optimization step uses the quantum device to estimate the loss function gradient. In this work, we use gradient-based data-driven circuit learning to qualitatively evaluate the performance of several superconducting platform devices and present results that show how error mitigation can improve the training of quantum circuit Born machines with 28 tunable parameters.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Quantum-Hardware Focused Application Performance Benchmarks (Final Technical Report)

Quantum computers promise to transform how we do scientific calculations. In this project, we benchmark different current quantum computers for solving chemistry problems and find ways to build noise-resilient implementations. We also use the characterization techniques developed to test ion trap quantum computers.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2021

Real time evolution for ultracompact Hamiltonian eigenstates on quantum hardware

In this work we present a detailed analysis of variational quantum phase estimation (VQPE), a method based on real-time evolution for ground and excited state estimation on near-term hardware. We derive the theoretical ground on which the approach stands, and demonstrate that it provides one of the most compact variational expansions to date for solving strongly correlated Hamiltonians. At the center of VQPE lies a set of equations, with a simple geometrical interpretation, which provides conditions for the time evolution grid in order to decouple eigenstates out of the set of time evolved expansion states, and connects the method to the classical filter diagonalization algorithm. Further, we introduce what we call the unitary formulation of VQPE, in which the number of matrix elements that need to be measured scales linearly with the number of expansion states, and we provide an analysis of the effects of noise which substantially improves previous considerations. The unitary formulation allows for a direct comparison to iterative phase estimation. Our results mark VQPE as both a natural and highly efficient quantum algorithm for ground and excited state calculations of general many-body systems. We demonstrate a hardware implementation of VQPE for the transverse field Ising model. Further, we illustrate its power on a paradigmatic example of strong correlation (Cr2 in the SVP basis set), and show that it is possible to reach chemical accuracy with as few as ~50 timesteps.

Klymko, Katherine↗
DOE OSTI2025

Visual Analytics of Crosstalk in Quantum Hardware

Crosstalk remains a major obstacle to building scalable and fault-tolerant quantum computers. Conventional diagnostic techniques-often based on numerical simulation or statistical modeling-struggle to scale with hardware complexity and offer limited interpretability. In this work, we present a visual analytics framework for diagnosing qubit crosstalk using lightweight, circuit-based models integrated with an interactive user interface. Our approach quantifies correlations between active and idle qubits under parameterized single- and twoqubit operations, enabling detection of both spatial and gateinduced crosstalk. The system incorporates qubit topology and gate performance data to support sector-based exploration and correlation mapping. This tool assists users in identifying correlated error sources, informing qubit placement strategies, and guiding noise-aware circuit design.

Chae, Junghoon [ORNL] (ORCID:0000000206016746)↗
DOE OSTI2022

Variational Adiabatic Gauge Transformation on Real Quantum Hardware for Effective Low-Energy Hamiltonians and Accurate Diagonalization

Effective low-energy theories represent powerful theoretical tools to reduce the complexity in modeling interacting quantum many-particle systems. However, common theoretical methods rely on perturbation theory, which limits their applicability to weak interactions. Here we introduce the Variational Adiabatic Gauge Transformation (VAGT), a nonperturbative hybrid quantum algorithm that can use nowadays quantum computers to learn the variational parameters of the unitary circuit that brings the Hamiltonian to either its block-diagonal or full-diagonal form. If a Hamiltonian can be diagonalized via a shallow quantum circuit, then VAGT can learn the optimal parameters using a polynomial number of runs. The accuracy of VAGT is tested through numerical simulations, as well as simulations on Rigetti and IonQ quantum computers.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Quantum hardware accelerators for real-world applications (CRADA FP00007654 Final Report)

The research Bleximo Corp. conducted at Cyclotron Road was focused on developing application-specific superconducting quantum processors for high-value problems in quantum chemistry, in particular, calculating chemical binding energy in biomolecular systems, such as protein-ligand complexes, with chemical precision. Several candidate architectures were identified through simulations, which included experimentally-proven quantum bit architectures and realistic noise and cross-talk models in multi-qubit superconducting quantum processors.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2026

Machine Learning on Heterogeneous, Edge, and Quantum Hardware for Particle Physics (ML-HEQUPP)

The next generation of particle physics experiments will face a new era of challenges in data acquisition, due to unprecedented data rates and volumes along with extreme environments and operational constraints. Harnessing this data for scientific discovery demands real-time inference and decision-making, intelligent data reduction, and efficient processing architectures beyond current capabilities. Crucial to the success of this experimental paradigm are several emerging technologies, such as artificial intelligence and machine learning (AI/ML) and silicon microelectronics, and the advent of quantum algorithms and processing. Their intersection includes areas of research such as low-power and low-latency devices for edge computing, heterogeneous accelerator systems, reconfigurable hardware, novel codesign and synthesis strategies, readout for cryogenic or high-radiation environments, and analog computing. This white paper presents a community-driven vision to identify and prioritize research and development opportunities in hardware-based ML systems and corresponding physics applications, contributing towards a successful transition to the new data frontier of fundamental science.

Gonski, Julia [SLAC]↗