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At least 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Inference-Based Quantum Sensing

In a standard quantum sensing (QS) task one aims at estimating an unknown parameter θ, encoded into an n-qubit probe state, via measurements of the system. The success of this task hinges on the ability to correlate changes in the parameter to changes in the system response $\mathscr{R}$⁡(θ) (i.e., changes in the measurement outcomes). For simple cases the form of $\mathscr{R}$⁡(θ) is known, but the same cannot be said for realistic scenarios, as no general closed-form expression exists. Here, in this Letter, we present an inference-based scheme for QS. We show that, for a general class of unitary families of encoding, $\mathscr{R}$⁡(θ) can be fully characterized by only measuring the system response at 2⁢n+1 parameters. This allows us to infer the value of an unknown parameter given the measured response, as well as to determine the sensitivity of the scheme, which characterizes its overall performance. We show that inference error is, with high probability, smaller than δ, if one measures the system response with a number of shots that scales only as Ω⁢(log 3 ⁡(n)/δ 2 ). Furthermore, the framework presented can be broadly applied as it remains valid for arbitrary probe states and measurement schemes, and, even holds in the presence of quantum noise. We also discuss how to extend our results beyond unitary families. Finally, to showcase our method we implement it for a QS task on real quantum hardware, and in numerical simulations.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRS2003

Laboratory Characterization and Modeling of a Near-Infrared Enhanced Photomultiplier Tube

The photon-starved channel for optical communications from deep space requires the development of detector technology that can achieve photon-counting sensitivities with high bandwidth. In this article, a near-infrared enhanced photomultiplier tube (PMT) with a quantum e.ciency of 0.08 at a 1.06- m wavelength is characterized in the laboratory. A Polya distribution model is used to compute the probability distribution function of the emitted secondary photoelectrons from the PMT. The model is compared with measured pulse-height distributions with reasonable agreement. The model accounts for realistic device parameters, such as the individual dynode stage gains and a shape parameter that is representative of the spatial uniformity of response across the photocathode and dynodes. Bit-error rate (BER) measurements also are presented for 4- and 8-pulse-position modulation (PPM) modulation schemes with data rates of 20 to 30 Mb/s. A BER of 10-2 is obtained for a mean of 8 detected photons.

Biswas, A.↗
DOE OSTI2022

Hot and dense matter equation of state probability distributions for astrophysical simulations

We add an ensemble of nuclei to the equation of state for homogeneous nucleonic matter to generate a new set of models suitable for astrophysical simulations of core-collapse supernovae and neutron star mergers. We implement empirical constraints from (i) nuclear mass measurements, (ii) proton-proton scattering phase shifts, and (iii) neutron star observations. Our model is also guided by microscopic many-body theory calculations based on realistic nuclear forces, including the zero-temperature neutron matter equation of state from quantum Monte Carlo simulations and thermal contributions to the free energy from finite-temperature many-body perturbation theory. We ensure that the parameters of our model can be varied while preserving thermodynamic consistency and the connection to experimental or observational data, thus providing a probability distribution of the astrophysical hot and dense matter equation of state. Furthermore, we compare our results with those obtained from other available equations of state. While our probability distributions indeed represent a large number of possible equations of state, we cannot yet claim to have fully explored all of the uncertainties, especially with regard to the structure of nuclei in the hot and dense medium.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Learning Many-Body Hamiltonians with Heisenberg-Limited Scaling

Learning a many-body Hamiltonian from its dynamics is a fundamental problem in physics. Here, in this Letter, we propose the first algorithm to achieve the Heisenberg limit for learning an interacting N-qubit local Hamiltonian. After a total evolution time of $\mathscr{O}$⁡(ε –1 ), the proposed algorithm can efficiently estimate any parameter in the N-qubit Hamiltonian to ε error with high probability. Our algorithm uses ideas from quantum simulation to decouple the unknown N-qubit Hamiltonian H into noninteracting patches and learns H using a quantum-enhanced divide-and-conquer approach. The proposed algorithm is robust against state preparation and measurement error, does not require eigenstates or thermal states, and only uses polylog⁡(ε –1 ) experiments. In contrast, the best existing algorithms require $\mathscr{O}$⁡⁡(ε –2 ) experiments and total evolution time. We prove a matching lower bound to establish the asymptotic optimality of our algorithm.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Modeling phonon-mediated quasiparticle poisoning in superconducting qubit arrays

Correlated errors caused by ionizing radiation impacting superconducting qubit chips are problematic for quantum error correction. Such impacts generate quasiparticle (QP) excitations in the qubit electrodes, which temporarily reduce qubit coherence significantly. The many energetic phonons produced by a particle impact travel efficiently throughout the device substrate and generate quasiparticles with high probability, thus causing errors on a large fraction of the qubits in an array simultaneously. Here, we describe a comprehensive strategy for the numerical simulation of the phonon and quasiparticle dynamics in the aftermath of an impact. We compare the simulations with experimental measurements of phonon-mediated QP poisoning and demonstrate that our modeling captures the spatial and temporal footprint of the QP poisoning for various configurations of phonon downconversion structures. We thus present a path forward for the operation of superconducting quantum processors in the presence of ionizing radiation.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
NASA NTRS1979

Transition probabilities and Stark-broadening parameters of neutral and singly ionized lead

Strengths and Stark widths of the prominent visible PbI and PbII lines are measured in emission by means of a gas-driven shock tube. Absolute ionic line strengths for 7s-7p and 7p-7d arrays conform well to quantum-mechanical sum rules and agree with theoretical predictions, but 6d-5f results differ markedly from central-field approximations. Neutral-line strengths agree satisfactorily with available comparison data. Semiempirical theory predicts the widths of PbII lines with characteristic reliability of better than 25%.

Miller, M. H.↗
NASA NTRS1996

Quantum Probability Cancellation Due to a Single-Photon State

When an N-photon state enters a lossless symmetric beamsplitter from one input port, the photon distribution for the two output ports has the form of Bernouli Binormial, with highest probability at equal partition (N/2 at one outport and N/2 at the other). However, injection of a single photon state at the other input port can dramatically change the photon distribution at the outputs, resulting in zero probability at equal partition. Such a strong deviation from classical particle theory stems from quantum probability amplitude cancellation. The effect persists even if the N-photon state is replaced by an arbitrary state of light. A special case is the coherent state which corresponds to homodyne detection of a single photon state and can lead to the measurement of the wave function of a single photon state.

Ou, Z. Y.↗
DOE OSTI2021

Classical symmetries and the Quantum Approximate Optimization Algorithm

Here, we study the relationship between the Quantum Approximate Optimization Algorithm (QAOA) and the underlying symmetries of the objective function to be optimized. Our approach formalizes the connection between quantum symmetry properties of the QAOA dynamics and the group of classical symmetries of the objective function. The connection is general and includes but is not limited to problems defined on graphs. We show a series of results exploring the connection and highlight examples of hard problem classes where a nontrivial symmetry subgroup can be obtained efficiently. In particular, we show how classical objective function symmetries lead to invariant measurement outcome probabilities across states connected by such symmetries, independent of the choice of algorithm parameters or number of layers. To illustrate the power of the developed connection, we apply machine learning techniques toward predicting QAOA performance based on symmetry considerations. We provide numerical evidence that a small set of graph symmetry properties suffices to predict the minimum QAOA depth required to achieve a target approximation ratio on the MaxCut problem, in a practically important setting where QAOA parameter schedules are constrained to be linear and hence easier to optimize.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Scaling quantum approximate optimization on near-term hardware

The quantum approximate optimization algorithm (QAOA) is an approach for near-term quantum computers to potentially demonstrate computational advantage in solving combinatorial optimization problems. However, the viability of the QAOA depends on how its performance and resource requirements scale with problem size and complexity for realistic hardware implementations. Here, we quantify scaling of the expected resource requirements by synthesizing optimized circuits for hardware architectures with varying levels of connectivity. Assuming noisy gate operations, we estimate the number of measurements needed to sample the output of the idealized QAOA circuit with high probability. We show the number of measurements, and hence total time to solution, grows exponentially in problem size and problem graph degree as well as depth of the QAOA ansatz, gate infidelities, and inverse hardware graph degree. These problems may be alleviated by increasing hardware connectivity or by recently proposed modifications to the QAOA that achieve higher performance with fewer circuit layers.

97 MATHEMATICS AND COMPUTING↗
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 OSTI2024

Förster Resonance Energy Transfer and Enhanced Emission in Cs 4 PbBr 6 Nanocrystals Encapsulated in Silicon Nano-Sheets for Perovskite Light Emitting Diode Applications

Encapsulating Cs 4 PbBr 6 quantum dots in silicon nano-sheets not only stabilizes the halide perovskite, but also takes advantage of the nano-sheet for a compatible integration with the traditional silicon semiconductor. Here, we report the preparation of un-passivated Cs 4 PbBr 6 ellipsoidal nanocrystals and pseudo-spherical quantum dots in silicon nano-sheets and their enhanced photoluminescence (PL). For a sample with low concentrations of quantum dots in silicon nano-sheets, the emission from Cs 4 PbBr 6 pseudo-spherical quantum dots is quenched and is dominated with Pb 2+ ion/silicene emission, which is very stable during the whole measurement period. For a high concentration of Cs 4 PbBr 6 ellipsoidal nanocrystals in silicon nano-sheets, we have observed Förster resonance energy transfer with up to 87% efficiency through the oscillation of two PL peaks when UV excitation switches between on and off, using recorded video and PL lifetime measurements. In an area of a non-uniform sample containing both ellipsoidal nanocrystals and pseudo-spherical quantum dots, where Pb 2+ ion/silicene emissions, broadband emissions from quantum dots, and bandgap edge emissions (515 nm) appear, the 515 nm peak intensity increases five times over 30 min of UV excitation, probably due to a photon recycling effect. This irradiated sample has been stable for one year of ambient storage. Cs 4 PbBr 6 quantum dots encapsulated in silicon nano-sheets can lead to applications of halide perovskite light emitting diodes (PeLEDs) and integration with traditional semiconductor materials.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Lower bounds on entanglement entropy without twin copy

We discuss the possibility of estimating experimentally the von Neumann entanglement entropy S A v N of a symmetric bipartite quantum system A B by using the basic measurement counts (bitstrings) for a single copy of a prepared state. Using exact diagonalization and analog simulations performed with the publicly available QuEra facilities for chains and ladders of Rydberg atoms, we calculate the Shannon entropy S A B X associated with the bitstrings of adiabatically prepared ground states and the reduced entropies S A X and S B X obtained from the marginal probabilities in A and B . We then calculate the classical mutual information I A B X = S A X + S B X − S A B X , which is a lower bound on S A v N . We show that for a broad range of lattice spacing and detuning, I A B X is typically 20% below S A v N in regions where S A v N is large and a less close bound in regions where S A v N is low. We argue that this use of the easily available bitstrings provides a robust and efficient way to explore empirically the phase diagram of qubit-based quantum simulators and identify critical regions. Published by the American Physical Society 2025

Meurice, Yannick (ORCID:0000000209959694)↗
NASA NTRS1980

Tables of stark level transition probabilities and branching ratios in hydrogen-like atoms

The transition probabilities which are given in terms of n prime k prime and n k are tabulated. No additional summing or averaging is necessary. The electric quantum number k plays the role of the angular momentum quantum number l in the presence of an electric field. The branching ratios between stark levels are also tabulated. Necessary formulas for the transition probabilities and branching ratios are given. Symmetries are discussed and selection rules are given. Some disagreements for some branching ratios are found between the present calculation and the measurement of Mark and Wierl. The transition probability multiplied by the statistical weight of the initial state is called the static intensity J sub S, while the branching ratios are called the dynamic intensity J sub D.

Omidvar, K.↗
NASA NTRS2011

The Dolinar Receiver in an Information Theoretic Framework

Optical communication at the quantum limit requires that measurements on the optical field be maximally informative, but devising physical measurements that accomplish this objective has proven challenging. The Dolinar receiver exemplifies a rare instance of success in distinguishing between two coherent states: an adaptive local oscillator is mixed with the signal prior to photodetection, which yields an error probability that meets the Helstrom lower bound with equality. Here we apply the same local-oscillator-based architecture with aninformation-theoretic optimization criterion. We begin with analysis of this receiver in a general framework for an arbitrary coherent-state modulation alphabet, and then we concentrate on two relevant examples. First, we study a binary antipodal alphabet and show that the Dolinar receiver's feedback function not only minimizes the probability of error, but also maximizes the mutual information. Next, we study ternary modulation consistingof antipodal coherent states and the vacuum state. We derive an analytic expression for a near-optimal local oscillator feedback function, and, via simulation, we determine its photon information efficiency (PIE). We provide the PIE versus dimensional information efficiency (DIE) trade-off curve and show that this modulation and the our receiver combination performs universally better than (generalized) on-off keying plus photoncounting, although, the advantage asymptotically vanishes as the bits-per-photon diverges towards infinity.

optical communications↗
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 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 OSTI2021

Empirical performance bounds for quantum approximate optimization

The quantum approximate optimization algorithm (QAOA) has been put forth as a method for near-term quantum computers to solve optimization problems. However, assessments of QAOA performance have mostly focused on small structured problem instances while performance on more general instances is less clear. Here, we numerically simulate QAOA pure state dynamics for every instance of MaxCut on non-isomorphic unweighted graphs with nine or fewer vertices with depth parameters p ≤ 3. We find the approximation ratios and optimized circuit parameters concentrate across graphs of a given size and empirically show increases in concentration as graph size increases. The parameter concentration leads to two median-angle heuristics that overcome difficulties in QAOA parameter optimization and obtain mean approximation ratios within 3% and 0.2% of the optimal. We also analyze the probability to measure an optimal solution and find increasing variations between graphs as depth increases, in stark contrast to the approximation ratios which concentrate as depth increases. Furthermore, the resulting benchmark data set gives empirical bounds for on-going experimental realizations and lays groundwork for theoretical extensions to greater problem sizes and depths where QAOA may prove important for practically relevant problems.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Low-dose high-resolution $\mathrm{TOF}$-$\mathrm{PET}$ using ionization-activated multi-state low-$\mathrm{Z}$ detector media

We propose PET scanners using low atomic number media that undergo a persistent local change of state along the paths of the Compton recoil electrons. Measurement of the individual scattering locations and angles, deposited energies, and recoil electron directions allows using the kinematical constraints of the 2-body Compton scattering process to perform a statistical time-ordering of the scatterings, with a high probability of precisely identifying where the gamma first interacted in the detector. In these cases the Line-of-Response is measured with high resolution, determined by the underlying physics processes and not the detector segmentation. There are multiple such media that act through different mechanisms. As an example in which the change of state is quantum-mechanical through a change in molecular configuration, rather than thermodynamic, as in a bubble chamber, we present simulations of a two-state photoswitchable organic dye, a ‘Switchillator’, that is activated to a fluorescent-capable state by the ionization of the recoil electrons. The activated state is persistent, and can be optically excited multiple times to image individual activated molecules. Energy resolution is provided by counting the activated molecules. Location along the LOR is implemented by large-area time-of-flight MCP-PMT photodetectors with single photon time resolution in the tens of ps and sub-mm spatial resolution. Simulations indicate a large reduction of dose.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗