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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Microscopic Derivation of Transition-state Theory for Complex Quantum Systems

The decay of quantum complex systems through a potential barrier is often described with transition-state theory, also known as RRKM theory in chemistry. Here we derive the basic formula for transition-state theory based on a generic Hamiltonian as might be constructed in a configuration-interaction basis. Two reservoirs of random Hamiltonians from Gaussian orthogonal ensembles are coupled to intermediate states representing the transition states at a barrier. Under the condition that the decay of the reservoirs to open channels is large, an analytic formula for reaction rates is derived. Here, the transition states act as independent Breit–Wigner resonances which contribute additively to the total transition probability, as is well known for electronic conductance through resonant tunneling states. It is also found that the transition probability is independent of the decay properties of the states in the second reservoir over a wide range of decay widths.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Dynamics of magnetization at infinite temperature in a Heisenberg spin chain

Understanding universal aspects of quantum dynamics is an unresolved problem in statistical mechanics. In particular, the spin dynamics of the one-dimensional Heisenberg model were conjectured as to belong to the Kardar-Parisi-Zhang (KPZ) universality class based on the scaling of the infinite-temperature spin-spin correlation function. In a chain of 46 superconducting qubits, we studied the probability distribution of the magnetization transferred across the chain’s center, P M . The first two moments of P M show superdiffusive behavior, a hallmark of KPZ universality. However, the third and fourth moments ruled out the KPZ conjecture and allow for evaluating other theories. Our results highlight the importance of studying higher moments in determining dynamic universality classes and provide insights into universal behavior in quantum systems.

Science & Technology - Other Topics↗
DOE OSTI2021

Orbits and Masses of Binaries from Speckle Interferometry at SOAR

We present results from Speckle inteferometric observations of 15 visual binaries and one double-line spectroscopic binary, carried out with the HRCam Speckle camera of the SOAR 4.1 m telescope. These systems were observed as a part of an on-going survey to characterize the binary population in the solar vicinity, out to a distance of 250 pc. We obtained orbital elements and mass sums for our sample of visual binaries. The orbits were computed using a Markov Chain Monte Carlo algorithm that delivers maximum likelihood estimates of the parameters, as well as posterior probability density functions that allow us to evaluate their uncertainty. Their periods cover a range from 5 yr to more than 500 yr; and their spectral types go from early A to mid M, implying total system masses from slightly more than 4M{sub ⊙} down to 0.2M {sub ⊙}. They are located at distances between approximately 12 and 200 pc, mostly at low Galactic latitude. For the double-line spectroscopic binary YSC8, we present the first combined astrometric/radial-velocity orbit resulting from a self-consistent fit, leading to individual component masses of 0.897 ± 0.027 M {sub ⊙} and 0.857 ± 0.026 M {sub ⊙}; and an orbital parallax of 26.61 ± 0.29 mas, which compares very well with the Gaia DR2 trigonometric parallax (26.55 ± 0.27 mas). In combination with published photometry and trigonometric parallaxes, we place our objects on an H-R diagram and discuss their evolutionary status. We also present a thorough analysis of the precision and consistency of the photometry available for them.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Nonadiabatic transitions during a passage near a critical point

The passage through a critical point of a many-body quantum system leads to abundant nonadiabatic excitations. Here, we explore a regime, in which the critical point is not crossed although the system is passing slowly very close to it. Here, we show that the leading exponent for the excitation probability can then be obtained by standard arguments of the Dykhne formula, but the exponential prefactor is no longer simple and behaves as a power law on the characteristic transition rate. We derive this prefactor for the nonlinear Landau–Zener model by adjusting Dykhne’s approach. Then, we introduce an exactly solvable model of the transition near a critical point in the Stark ladder. We derive the number of excitations for it without approximations and find qualitatively similar results for the excitation scaling.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Maximally entangled gluons for any x

Individual quarks and gluons at small x inside an unpolarized hadron can be regarded as Bell states in which qubits in the spin and orbital angular momentum spaces are maximally entangled. Using the machinery of quantum information science, we generalize this observation to all values 0 < x <1 and describe gluons (but not quarks) as maximally entangled states between a qubit and a qudit. We introduce the conditional probability distribution P⁡(l z |s z ) of a gluon’s orbital angular momentum l z given its helicity s z . Restricting to the three states l z =0,±1, which constitute a qutrit, we explicitly compute P as a function of x.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Observation and differential cross section measurement of neutral current DIS events with an empty hemisphere in the Breit frame

The Breit frame provides a natural frame to analyze lepton–proton scattering events. In this reference frame, the parton model hard interactions between a quark and an exchanged boson defines the coordinate system such that the struck quark is back-scattered along the virtual photon momentum direction. In Quantum Chromodynamics (QCD), higher order perturbative or non-perturbative effects can change this picture drastically. As Bjorken-x decreases below one half, a rather peculiar event signature is predicted with increasing probability, where no radiation is present in one of the two Breit-frame hemispheres and all emissions are to be found in the other hemisphere. At higher orders in $\alpha$ s or in the presence of soft QCD effects, predictions of the rate of these events are far from trivial, and that motivates measurements with real data. We report on the first observation of the empty current hemisphere events in electron–proton collisions at the HERA collider using data recorded with the H1 detector at a center-of-mass energy of 319 GeV. The fraction of inclusive neutral-current DIS events with an empty hemisphere is found to be 0.0112 ± 3.9% stat ± 4.5% syst ± 1.6% mod in the selected kinematic region of 150 < Q 2 < 1500 GeV 2 and inelasticity 0.14 < y < 0.7. The data sample corresponds to an integrated luminosity of 351.1 pb -1 , sufficient to enable differential cross section measurements of these events. The results show an enhanced discriminating power at lower Bjorken-x among different Monte Carlo event generator predictions.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

Efficient, Predictive Tomography of Multi-Qubit Quantum Processors

After decades of R&D, quantum computers comprising more than 2 qubits are appearing. If this progress is to continue, the research community requires a capability for precise characterization (“tomography”) of these enlarged devices, which will enable benchmarking, improvement, and finally certification as mission-ready. As world leaders in characterization -- our gate set tomography (GST) method is the current state of the art – the project team is keenly aware that every existing protocol is either (1) catastrophically inefficient for more than 2 qubits, or (2) not rich enough to predict device behavior. GST scales poorly, while the popular randomized benchmarking technique only measures a single aggregated error probability. This project explored a new insight: that the combinatorial explosion plaguing standard GST could be avoided by using an ansatz of few-qubit interactions to build a complete, efficient model for multi-qubit errors. We developed this approach, prototyped it, and tested it on a cutting-edge quantum processor developed by Rigetti Quantum Computing (RQC), a US-based startup. We implemented our new models within Sandia’s PyGSTi open-source code, and tested them experimentally on the RQC device by probing crosstalk. We found two major results: first, our schema worked and is viable for further development; second, while the Rigetti device is indeed a “real” 8-qubit quantum processor, its behavior fluctuated significantly over time while we were experimenting with it and this drift made it difficult to fit our models of crosstalk to the data.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Nonlocal subpicosecond delay metrology using spectral quantum interference

Precise knowledge of position and timing information is critical to support elementary protocols such as entanglement swapping on quantum networks. While approaches have been devised to use quantum light for such metrology, they largely rely on time-of-flight (ToF) measurements with single-photon detectors and, therefore, are limited to picosecond-scale resolution owing to detector jitter. In this work, we demonstrate an approach to distributed sensing that leverages phase modulation to map changes in the spectral phase to coincidence probability, thereby overcoming the limits imposed by single-photon detection. By extracting information about the joint biphoton phase, we measure a generalized delay—the difference in signal–idler arrival, relative to local radio frequency (RF) phase modulation. For nonlocal ranging measurements, we achieve (2$σ$) precision of ±0.04 ps and for measurements of the relative RF phase, (2$σ$) precision of ±0.7°. We complement this fine timing information with ToF data from single-photon time-tagging to demonstrate absolute measurement of time delay. By relying on off-the-shelf telecommunications equipment and standard quantum resources, this approach has the potential to reduce overhead in practical quantum networks.

42 ENGINEERING↗
DOE OSTI2025

Exact block encoding of imaginary time evolution with universal quantum neural networks

We develop a constructive approach to generate quantum neural networks capable of representing the exact thermal states of all many-body qubit Hamiltonians. The Trotter expansion of the imaginary time propagator is implemented through an exact block encoding by means of a unitary, restricted Boltzmann machine architecture. Marginalization over the hidden-layer neurons (auxiliary qubits) creates the nonunitary action on the visible layer. Then, we introduce a unitary deep Boltzmann machine architecture in which the hidden-layer qubits are allowed to couple laterally to other hidden qubits. We prove that this wave-function is closed under the action of the imaginary time propagator and, more generally, can represent the action of a universal set of quantum gate operations. We provide analytic expressions for the coefficients for both architectures, thus enabling exact network representations of thermal states without stochastic optimization of the network parameters. In the limit of large imaginary time, the yields the ground state of the system. The number of qubits grows linearly with the number of interactions and total imaginary time for a fixed interaction order. Both networks can be readily implemented on quantum hardware via midcircuit measurements of auxiliary qubits. If only one auxiliary qubit is measured and reset, the circuit depth scales linearly with imaginary time and number of interactions, while the width is constant. Alternatively, one can employ a number of auxiliary qubits linearly proportional to the number of interactions, and circuit depth grows linearly with imaginary time only. Every midcircuit measurement has a postselection success probability, and the overall success probability is equal to the product of the probabilities of the midcircuit measurements.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

QuGrav: Bringing gravitational waves to light with qumodes

We propose using qumodes, quantum bosonic modes, for detecting high-frequency gravitational waves via the inverse Gertsenshtein effect, where a gravitational wave resonantly converts into a single photon in a magnetized cavity. For an occupation number n of the photon field in a qumode, the conversion probability is enhanced by a factor of n + 1 due to Bose-Einstein statistics. Unlocking this increased sensitivity entails the ability to continuously prepare the qumode and perform nondemolition measurement on the qumode-qubit system within the qumode coherence time. Our results indicate that, at microwave frequencies and with existing technology, the proposed setup can attain sensitivities within 1.7 orders of magnitude of the cosmological bound. With anticipated near-future improvements, it has the potential to surpass this limit and pave the way for the first exploration of high-frequency cosmological gravitational wave backgrounds. At optical frequencies, it can enhance the sensitivity of current detectors by one order of magnitude. That further enhances their potential in reaching the single-graviton level.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

A study of events with photoelectric emission in the DarkSide-50 liquid argon Time Projection Chamber

Finding unequivocal evidence of dark matter interactions in a particle detector is a major goal of research in physics. Liquid argon time projection chambers offer a path to probe Weakly Interacting Massive Particles scattering cross sections on nuclei down to the so-called neutrino floor, in a mass range from a few GeV to hundreds of TeV. Based on the successful operation of the DarkSide-50 detector at LNGS, a new and more sensitive experiment, DarkSide-20k, has been designed and is now under construction. A thorough understanding of the DarkSide-50 detector response and, therefore, of all types of events observed in the detector, is essential for the optimal design of the new experiment. In this article, we report on a specific set of events, namely, standard two-pulse scintillation–ionization signals with a third small amplitude pulse, occurring within the 440 μ s data acquisition window of standard events. Some of these events are due to the photoionization of the TPC cathode. We compare our results with those published by collaborations using liquid xenon time projection chambers, which observed a similar phenomenon, and, in particular, with a recent paper by the LUX Collaboration (D.S. Akerib et al. Phys.Rev.D 102, 092004 (2020)) From the measured rate of these events, we estimate for the first time the quantum efficiency of the tetraphenyl butadiene deposited on the DarkSide-50 cathode at wavelengths of around 128 nm, in liquid argon. Also, both experiments observe events likely related to the photoionization of impurities in the liquid. The probability of photoelectron emission per unit length turns out to be an order of magnitude lower in DarkSide-50 than in LUX.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Extraction of the higher-twist parton distribution $e(x)$ from CLAS data

We present the first point-by-point extraction of a twist-3 PDF. The scalar PDF, e(x), is accessed through the analysis of the data for the sin φR-moment of the beam-spin asymmetry for dihadron production in semi-inclusive DIS off proton target at CLAS and CLAS12. The dihadron formalism allows for use of collinear framework, hence calling for a minimal set of approximations and hypotheses. The extracted PDF e(x) carries insights into the physics of the largely-unexplored quark-gluon correlations, and its first Mellin moment is related to the marginally known scalar charge of the nucleon. We show that the proton flavor combination of the scalar PDF is nonzero at more than 74% probability.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Evaluating Space Object Conjunction Probabilities Using Characteristic Function Inversion

This report discusses an approach to computing the probability of a conjunction between two space objects in the short-term encounter scenario. A conjunction is defined here as an event where the miss distance between the objects is less than some specified value. The scenario assumptions are that the motion of the objects is linear, their positions are Gaussian distributed, and their velocities are known and constant. Under these assumptions, the squared-miss distance is shown to have the generalized chi-square distribution. An established statistical technique called characteristic function inversion is employed to evaluate the distribution and obtain conjunction probabilities. The method is closely related to a recent approach based on moment generating function inversion, and a qualitative comparison of the approaches is provided. Last, the method is tested on several benchmark test cases where it agrees with numerical integration on the cases with conjunction probabilities above 10 –12 . However, the exact probability in these cases is usually not needed and this probability can be bounded above using an independent Gaussian approximation. Overall, the report shows how to compute conjunction probabilities using a standard statistical method, though numerical integration seems to perform equally well.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Machine Learning Predictions of Transition Probabilities in Atomic Spectra

Forward modeling of optical spectra with absolute radiometric intensities requires knowledge of the individual transition probabilities for every transition in the spectrum. In many cases, these transition probabilities, or Einstein A-coefficients, quickly become practically impossible to obtain through either theoretical or experimental methods. Complicated electronic orbitals with higher order effects will reduce the accuracy of theoretical models. Experimental measurements can be prohibitively expensive and are rarely comprehensive due to physical constraints and sheer volume of required measurements. Due to these limitations, spectral predictions for many element transitions are not attainable. In this work, we investigate the efficacy of using machine learning models, specifically fully connected neural networks (FCNN), to predict Einstein A-coefficients using data from the NIST Atomic Spectra Database. For simple elements where closed form quantum calculations are possible, the data-driven modeling workflow performs well but can still have lower precision than theoretical calculations. For more complicated nuclei, deep learning emerged more comparable to theoretical predictions, such as Hartree–Fock. Unlike experiment or theory, the deep learning approach scales favorably with the number of transitions in a spectrum, especially if the transition probabilities are distributed across a wide range of values. It is also capable of being trained on both theoretical and experimental values simultaneously. In addition, the model performance improves when training on multiple elements prior to testing. The scalability of the machine learning approach makes it a potentially promising technique for estimating transition probabilities in previously inaccessible regions of the spectral and thermal domains on a significantly reduced timeline.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2023

Ablation loading of barium ions into a surface-electrode trap

Trapped-ion quantum information processing may benefit from qubits encoded in isotopes that are practically available in only small quantities, e.g., due to low natural abundance or radioactivity. Laser ablation provides a method of controllably liberating neutral atoms or ions from low-volume targets, but energetic ablation products can be difficult to confine in the small ion-electrode distance, micron-scale microfabricated traps amenable to high-speed, high-fidelity manipulation of ion arrays. Here, we investigate ablation-based ion loading into surface-electrode traps of different sizes to test a model describing ion loading probability as a function of effective trap volume and other trap parameters. We characterize loading of ablated barium from a metallic source in two cryogenic surface-electrode traps with 730 and 50 μm ion-electrode distances. Furthermore, our loading rate agrees with a predictive analytical model, providing insight for the confinement of limited-quantity species of interest for quantum computing, simulation, and sensing.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2022

Discovering causal structure with reproducing-kernel Hilbert space ε -machines

We merge computational mechanics’ definition of causal states (predictively equivalent histories) with reproducing-kernel Hilbert space (RKHS) representation inference. The result is a widely applicable method that infers causal structure directly from observations of a system’s behaviors whether they are over discrete or continuous events or time. A structural representation—a finite- or infinite-state kernel ϵ-machine—is extracted by a reduced-dimension transform that gives an efficient representation of causal states and their topology. In this way, the system dynamics are represented by a stochastic (ordinary or partial) differential equation that acts on causal states. We introduce an algorithm to estimate the associated evolution operator. Paralleling the Fokker–Planck equation, it efficiently evolves causal-state distributions and makes predictions in the original data space via an RKHS functional mapping. We demonstrate these techniques, together with their predictive abilities, on discrete-time, discrete-value infinite Markov-order processes generated by finite-state hidden Markov models with (i) finite or (ii) uncountably infinite causal states and (iii) continuous-time, continuous-value processes generated by thermally driven chaotic flows. The method robustly estimates causal structure in the presence of varying external and measurement noise levels and for very high-dimensional data.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Optimal Zeno Dragging for Quantum Control: A Shortcut to Zeno with Action-Based Scheduling Optimization

The quantum Zeno effect asserts that quantum measurements inhibit simultaneous unitary dynamics when the “collapse” events are sufficiently strong and frequent. This applies in the limit of strong continuous measurement or dissipation. It is possible to implement a dissipative control that is known as “Zeno dragging” by dynamically varying the monitored observable, and hence also the eigenstates, which are attractors under Zeno dynamics. This is similar to adiabatic processes, in that the Zeno-dragging fidelity is highest when the rate of eigenstate change is slow compared to the measurement rate. We demonstrate here two theoretical methods for using such dynamics to achieve control of quantum systems. The first, which we shall refer to as “shortcut to Zeno,” is analogous to the shortcuts to adiabaticity (counterdiabatic driving) that are frequently used to accelerate unitary adiabatic evolution. In the second approach, we apply the Chantasri-Dressel-Jordan stochastic action [PRA 88, 042110 (2013)], and demonstrate that the extremal-probability readout paths derived from this are well suited to setting up a Pontryagin-style optimization of the Zeno-dragging schedule. A fundamental contribution of the latter approach is to show that an action suitable for measurement-driven control optimization can be derived quite generally from statistical arguments. Implementing these methods on the Zeno dragging of a qubit, we find that both approaches yield the same solution, namely, that the optimal control is a unitary that matches the motion of the Zeno-monitored eigenstate. We then show that such a solution can be more robust than a unitary-only operation and we comment on solvable generalizations of our qubit example embedded in larger systems. These methods open up new pathways toward systematically developing dynamic control of Zeno subspaces to realize dissipatively stabilized quantum operations. Published by the American Physical Society 2024

Physics↗
DOE OSTI2021

Impact of graph structures for QAOA on MaxCut

The quantum approximate optimization algorithm (QAOA) is a promising method of solving combinatorial optimization problems using quantum computing. QAOA on the MaxCut problem has been studied extensively on graphs with specific structure; however, little is known about the general performance of the algorithm on arbitrary graphs. Here, we investigate how different graph characteristics correlate with QAOA performance at depths at most three on the MaxCut problem for all connected non-isomorphic graphs with at most eight vertices. Some good predictors of QAOA success relate to graph symmetries, odd cycles, and density. For example, on eight vertex graphs, the average probability for selecting an optimal solution for graphs that contain no odd cycles after three iterations of QAOA is 60.6% compared to 48.2% for those that do. The data generated from these studies are shared in a publicly accessible database to serve as a benchmark for QAOA calculations and experiments. Knowing the relationship between structure and performance can be used to identify classes of combinatorial problems that are likely to exhibit a quantum advantage.

97 MATHEMATICS AND COMPUTING↗