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At least 109 records · Page 6

In situ compression artifact removal in scientific data using deep transfer learning and experience replay

The massive amount of data produced during simulation on high-performance computers has grown exponentially over the past decade, exacerbating the need for streaming compression and decompression methods for efficient storage and transfer of this data---key to realizing the full potential of large-scale computational science. Lossy compression approaches such as JPEG when applied to scientific simulation data realized as a stream of images can achieve good compression rates but at the cost of introducing compression artifacts and loss of information. This paper develops a unified framework for in situ compression artifact removal in which the fully convolutional neural network architectures are combined with scalable training, transfer learning, and experience replay to achieve superior accuracy and efficiency while significantly decreasing the storage footprint as compared with the traditional optimization-based approaches. We demonstrate the proposed approach and compare it with compressed sensing postprocessing and other baseline deep learning models using climate simulations and nuclear reactor simulations, both of which are driven by hyperbolic partial differential equations. Our approach when applied to remove the compression artifacts on the JPEG-compressed nuclear reactor simulation data (using a transfer-trained model that was pretrained on the climate simulation data and updated incrementally as the nuclear reactor simulation progressed), achieved a significant improvement---mean peak signal-to-noise ratio of 42.438 as compared with 27.725 obtained with the compressed sensing approach.

97 MATHEMATICS AND COMPUTING↗

Importance of finite-size corrections for accurate ab initio modeling of carrier capture at semiconductor defects: A case study of substitutional C N in GaN

In ab initio studies of carrier-capture processes in defective semiconductor materials, the single-effective-mode formalism and the static-coupling approximation have become the predominant theoretical approaches for determining carrier-capture coefficients. The single-mode formalism relies on accurate nonequilibrium defect energies obtained from density-functional theory (DFT), where required inputs are a series of configurationally displaced, defect-containing supercells obtained using an interpolative ansatz, and where the DFT outputs are corresponding total energies that have traditionally been postprocessed using a long-established ground-state formulation of finite-size corrections and defect-formation energies. This formulation remains commonly used even though the defects that form a configuration-coordinate (CC) diagram typically exist as structures that are displaced from the ground state. To remedy this inconsistency, Kumagai has recently proposed novel methods for implementing finite-size corrections specifically intended for DFT calculations of the defect energies used to construct CC diagrams and implement the single-mode formalism [Y. Kumagai, Phys. Rev. B 107, L220101 (2023)]. Kumagai's approach builds on the latest finite-size-correction methods introduced to describe vertical charge-state transitions for charge-localizing point defects in semiconductors and insulators [T. Gake et al., Phys. Rev. B 101, 020102 (2020); S. Falletta et al., Phys. Rev. B 102, 041115 (2020)]. The newly identified finite-size artifact treated in these studies is the polarization charge induced on a configurationally frozen defect and its subsequent interaction with a vertical transition in charge state. In this work, we evaluate Kumagai's proposed methodology by applying it in a high-precision DFT study of carrier capture by substitutional C N in GaN, a well-characterized and technologically relevant defect and material. We have rigorously calculated C N defect energies across various supercell sizes for each defect configuration and charge state on the hole-capture CC diagram of C N (𝑞=−1), enabling a direct comparison of the slopes of the defect energies versus inverse cell size with those predicted by Kumagai. The most consequential prediction of Kumagai's method is that these slopes distinctly vary as the square of the linear-interpolation parameter used to construct the nonequilibrium defect configurations. Our results quantitatively support this prediction. Moreover, with these new finite-size corrections and multiple-cell-size DFT calculations in place, we find that the classical energy barrier for hole capture by C N (𝑞=−1) in GaN decreases to 0.092–0.127 eV. This finding confirms the recent ≈ 0.1 eV prediction of Reshchikov based on the weak temperature dependence for hole capture observed in photoluminescence experiments [M. A. Reshchikov, J. Appl. Phys. 129, 121101 (2021)]. These results stand in stark contrast to previously calculated barriers of 0.486 and 0.73 eV, which also used the single-mode formalism but were obtained by instead using ground-state-based finite-size corrections. Our reduced classical barrier for capture increases the temperature-dependent hole-capture coefficient of a C N (𝑞=−1) defect by more than two to four orders of magnitude for temperatures of 100–600 K, compared to the previous 0.486 eV results. While other defects may not be as dramatically affected as here, we suggest that incorporating proper finite-size corrections for the vertical-transition-like states embedded within CC diagrams is an essential, yet previously unrecognized, component of accurate modeling of carrier-capture when using the single-effective-mode formalism.

dielectric properties↗

Error-mitigated nonorthogonal quantum eigensolver via shadow tomography

We present a shadow-tomography-enhanced nonorthogonal quantum eigensolver (NOQE) for more efficient and accurate electronic structure calculations on near-term quantum devices. By integrating shadow tomography into the NOQE, the measurement cost scales linearly rather than quadratically with the number of reference states, while also reducing the required qubits and circuit depth by half. This approach enables extraction of all matrix elements via randomized measurements and classical postprocessing. We analyze its sample complexity and show that, for small systems, it remains constant in the high-precision regime, while for larger systems, it scales linearly with the system size. We further apply shadow-based error mitigation to suppress noise-induced bias without increasing quantum resources. Demonstrations on the hydrogen molecule in the strongly correlated regime achieve chemical accuracy under realistic noise, showing that our method is both resource-efficient and noise-resilient for practical quantum chemistry simulations in the near term.

quantum algorithms & computation↗

Revealing the Structure and Dynamics of Self-Generated Electric and Magnetic Fields Near Plasma Stagnation in Laser-Driven Hohlraums

By coupling newly developed triparticle charged particle radiography with radiography reconstruction algorithms and novel reconstruction postprocessing techniques, the spatial structure and time evolution of self-generated electric and magnetic fields in laser-driven vacuum hohlraums have been quantitatively revealed. Through high-fidelity data from a series of experiments, it is shown that late in the hohlraum evolution (after the end of laser drive) these fields are strongly correlated in both space and time, providing evidence that their evolution is primarily dominated by advection with the plasma flow. At these late times, plasma flow velocities inferred from both gross radiography analysis and field reconstructions (and corroborated with Thomson scattering measurements) indicate that the plasma is approaching stagnation near the hohlraum axis. Finally, these experiments provide not only new physical insight into spontaneously generated hohlraum fields, but also provide important spatially and temporally resolved information for future benchmarking of numerical codes.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Neutrino flavor instabilities in neutron star mergers with moment transport: Slow, fast, and collisional modes

Determining where, when, and how neutrino flavor oscillations must be included in large-scale simulations of hot and dense astrophysical environments is an enduring challenge that must be tackled to obtain accurate predictions. Here, using an angular moment-based linear stability analysis framework, we examine the different kinds of flavor instabilities that can take place in the context of the postprocessing of a neutron star merger simulation, with a particular focus on the collisional flavor instability and a careful assessment of several commonly used approximations. First, neglecting anisotropies of the neutrino field, we investigate the extent to which commonly used monoenergetic growth rates reproduce the results obtained from a full multienergy treatment. Contrary to the large discrepancies found in core-collapse supernova environments, we propose a simple combination of energy-averaged estimates that reproduces the multienergy growth rates in our representative simulation snapshot. We then quantify the impact of additional physical effects, including nuclear many-body corrections, scattering opacities, and the inclusion of the vacuum term in the neutrino Hamiltonian. Finally, we include the neutrino distribution anisotropies, which allows us to explore, for the first time in a multienergy setting, the interplay between collisional, fast, and slow modes in a moment-based neutron star merger simulation. We find that, despite a dominance of the fast instability in most of the simulation volume, certain regions exhibit only a collisional instability, while others, especially at large distances, exhibit a slow instability that is largely underestimated if anisotropic effects are neglected.

neutrino oscillations↗

Short-depth circuits for efficient expectation-value estimation

The evaluation of expectation values Tr[$\rho \mathcal{O}$] for some pure state $\rho$ and Hermitian operator $\mathcal{O}$ is of central importance in a variety of quantum algorithms. Near-optimal techniques have been developed in the past and require a number of measurements N approaching the Heisenberg limit N = O(1/ ε) as a function of target accuracy ε. The use of quantum phase estimation (QPE) requires, however, long circuit depths C = O(1/ ε) making its implementation difficult on near-term noisy devices. The more direct strategy of operator averaging is usually preferred as it can be performed using N = O(1/ε 2 ) measurements and no additional gates aside from those needed for the state preparation. In this work we use a simple but realistic model to describe the bound state of a neutron and a proton (the deuteron) to show that the latter strategy can require an overly large number of measurements in order to achieve a prefixed relative target accuracy ε r . Further, we propose to overcome this problem using a single step of QPE and classical postprocessing. This approach leads to a circuit depth C = O (ε μ ) (with μ ≥ 0) and to a number of measurements N = O (1/ε 2 + ν ) for 0 < ν ≤ 1 and a much smaller prefactor. We provide detailed descriptions of two implementations of our strategy for ν = 1 and ν ≈ 0.5 and derive appropriate conditions that a particular problem instance has to satisfy in order for our method to provide an advantage.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Readout rebalancing for near-term quantum computers

Readout errors are a significant source of noise for near-term intermediate-scale quantum computers. Mismeasuring a qubit as |1) when it should be |0) occurs much less often than mismeasuring a qubit as |0) when it should have been |1). We make the simple observation that one can improve the readout fidelity of quantum computers by applying targeted X gates prior to performing a measurement. These X gates are placed so that the expected number of qubits in the |1) state is minimized. Classical postprocessing can undo the effect of the X gates so that the expectation value of any observable is unchanged. This protocol is designed to have no effect when readout errors are symmetric. We show that the statistical uncertainty following readout error corrections is smaller when using readout rebalancing. The statistical advantage is circuit and computer dependent and is demonstrated for the W state, a Grover search, and for a Gaussian state. The benefit in statistical precision is most pronounced (and nearly a factor of 2 in some cases) when states with many qubits in the excited state have high probability.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Extending quantum probabilistic error cancellation by noise scaling

Here, we propose a general framework for quantum error mitigation that combines and generalizes two techniques: probabilistic error cancellation (PEC) and zero-noise extrapolation (ZNE). Similar to PEC, the proposed method represents ideal operations as linear combinations of noisy operations that are implementable on hardware. However, instead of assuming a fixed level of hardware noise, we extend the set of implementable operations by noise scaling. By construction, this method encompasses both PEC and ZNE as particular cases and allows us to investigate a larger set of hybrid techniques. For example, gate extrapolation can be used to implement PEC without requiring knowledge of the device’s noise model, e.g., avoiding gate-set tomography. Alternatively, probabilistic error reduction can be used to estimate expectation values at intermediate virtual noise strengths (below the hardware level), leading to partially mitigated results at a lower sampling cost. Moreover, multiple results obtained with different noise-reduction factors can be further postprocessed with ZNE to better approximate the zero-noise limit.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Filtering states with total spin on a quantum computer

Starting from a general wave-function described on a set of spins or qubits, we propose several quantum algorithms to extract the components of this state on eigenstates of total spin S 2 and its z component S z . The method plays the role of total spin projection and gives access to the amplitudes of the initial state on a total spin basis. Here, the different algorithms have various degrees of sophistication depending on the requested tasks. They can either solely project onto the subspace with good total spin or completely uplift the degeneracy in this subspace. In the former case, when the projection on the total spin j is made, we show that the number of operations for the projection can be reduced from a quadratic to a linear dependence in j. After each measurement, the state collapses to one of the spin eigenstates that could be used for postprocessing. For this reason, we call the method total quantum spin filtering.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Quantum advantage for differential equation analysis

Quantum algorithms for differential equation solving, data processing, and machine learning potentially offer an exponential speedup over all known classical algorithms. However, there also exist obstacles to obtaining this potential speedup in useful problem instances. The essential obstacle for quantum differential equation solving is that outputting useful information may require difficult postprocessing, and the essential obstacle for quantum data processing and machine learning is that inputting the data is a difficult task just by itself. In this study, we demonstrate that, when combined, these difficulties solve one another. We show how the output of quantum differential equation solving can serve as the input for quantum data processing and machine learning, allowing dynamical analysis in terms of principal components, power spectra, and wavelet decompositions. To illustrate this, we consider continuous-time Markov processes on epidemiological and social networks. These quantum algorithms provide an exponential advantage over existing classical Monte Carlo methods.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Alternative approach to quantum imaginary time evolution

There is increasing interest in quantum algorithms (QAs) that are based on the imaginary time evolution (ITE), a successful classical numerical approach to obtain ground states. However, most of the proposals so far require heavy postprocessing computational steps on a classical computer, such as solving linear equations. Here we provide an alternative approach to implement ITE. A key feature in our approach is the use of an orthogonal basis set: the propagated state is efficiently expressed in terms of orthogonal basis states at every step of the evolution. We argue that the number of basis states needed at those steps to achieve an accurate solution can be kept on the order of n , the number of qubits, by controlling the precision (number of significant digits) and the imaginary time increment. The number of quantum gates per imaginary time step is estimated to be polynomial in n . Additionally, while in many QAs the locality of the Hamiltonian is a key assumption, in our algorithm this restriction is not required. This characteristic of our algorithm renders it useful for studying highly nonlocal systems, such as the occupation-representation nuclear shell model. Here, we illustrate our algorithm through numerical implementation on an IBM quantum simulator.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Perturbative readout-error mitigation for near-term quantum computers

Readout errors on near-term quantum computers can introduce significant error to the empirical probability distribution sampled from the output of a quantum circuit. These errors can be mitigated by classical postprocessing given the access of an experimental response matrix that describes the error associated with the measurement of each computational basis state. However, the resources required to characterize a complete response matrix and to compute the corrected probability distribution scale exponentially with the number of qubits, n . In this work, we modify standard matrix inversion techniques using perturbative approximations with significantly reduced complexity and bounded error when the likelihood of high-order bit-flip events is strongly suppressed. Given a characteristic error rate q , we discuss a method to recover the probability of the all-zeros bit string p 0 by sampling only a small subspace of the response matrix before inverting readout error, resulting in a relative speedup of poly [ 2 n / ( n w ) ] , which we motivate using a simplified error model for which the approximation incurs only O ( q w ) error for some integer w . We then provide a generalized technique to efficiently recover full output distributions with O ( q w ) error in the perturbative limit. These approximate techniques for readout-error correction may greatly accelerate near-term quantum computing applications.

97 MATHEMATICS AND COMPUTING↗

Strongly Coupled Plasmon and Phonon Polaritons as Seen by Photon and Electron Probes

The ability to control and modify infrared excitations in condensed matter is of both fundamental and applied interest. Here we explore a system supporting low-energy excitations, in particular, mid-infrared localized plasmon modes and phonon polaritons that are tuned to be strongly coupled. We study the coupled modes by using far-field infrared spectroscopy, state-of-the-art monochromated electron energy-loss spectroscopy, numerical simulations, and analytical modeling. Here we demonstrate that the electron probe facilitates a precise characterization of polaritons constituting the coupled system, and enables an active control over the coupling and the resulting sample response both in frequency and space. Although far-field optical spectra can be substantially different from near-field electron energy-loss spectra, we show that a direct comparison is possible via postprocessing and right positioning of the electron beam. The resulting spectra allow us to evaluate the key parameters of the coupled system, such as the coupling strength, which we demonstrate to be probe independent. Our work establishes a rigorous description of the spectral features observed in light- and localized electron-based spectroscopies, which can be extended to the analysis of analogous optical systems with applications in heat management and electromagnetic field concentration or nanofocusing.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Shell-model studies of the astrophysical r p -process reactions S 34 ( p , γ ) Cl 35 and Cl 34 g , m ( p , γ ) Ar 35

Background: Dust grains condensed in the outflows of presolar classical novae should have been present in the protosolar nebula. Candidates for such presolar nova grains have been found in primitive meteorites and can in principle be identified by their isotopic ratios, but the ratios predicted by state-of-the-art one-dimensional hydrodynamic models are uncertain due to nuclear-physics uncertainties. Purpose: To theoretically calculate the thermonuclear rates and uncertainties of the S 34 ( p , γ ) Cl 35 and Cl 34 g , m ( p , γ ) Ar 35 reactions and investigate their impacts on the predicted 34 S/ 32 S isotopic ratio for presolar nova grains. Method: A shell-model approach in a (0 +1 ) ℏ ω model space was used to calculate the properties of resonances in the 34 S(p ,γ ) 35 Cl and 34 g,m Cl (p ,γ ) 35 Ar reactions and their thermonuclear rates. Uncertainties were estimated using a Monte Carlo method. The implications of these rates and their uncertainties on sulfur isotopic nova yields were investigated using a postprocessing nucleosynthesis code. The rates for transitions from the ground state of 34 Cl as well as from the isomeric first excited state of 34 Cl were explicitly calculated. Results: At energies in the resonance region near the proton-emission threshold, many negative-parity states appear. Energies, spectroscopic factors, and proton-decay widths are reported. The resulting thermonuclear rates are compared with previous determinations. Conclusions: The shell-model calculations alone are sufficient to constrain the variation of the 34 S/ 32 S ratios to within about 30%. Uncertainties associated with other reactions must also be considered, but in general we find that the 34 S/ 32 S ratios are not a robust diagnostic to clearly identify presolar grains made from nova ejecta.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Constraints on key O 17 ( α , γ ) Ne 21 resonances and impact on the weak s process

The efficiency of the slow neutron-capture process in massive stars is strongly influenced by neutron-capture reactions on light elements. At low metallicity, 16 O is an important neutron absorber, but the effectiveness of 16 O as a light-element neutron poison is modified by competition between subsequent 17 O(α,n) 20 Ne and 17 O(α,γ) 21 Ne reactions. The strengths of key 17 O(α,γ) 21 Ne resonances within the Gamow window for core helium burning in massive stars are not well constrained by experiment. This work presents more precise measurements of resonances in the energy range E c.m. = 612–1319 keV. We extract resonance strengths of ωγ 638 = 4.85 ± 0.79 μeV, ωγ 721 =13.1$^{+3.2}_{-2.4}$ μeV, ωγ 814 = 7.72 ± 0.55 meV, and ωγ 1318 = 136 ±13 meV, for resonances at E c.m. = 638, 721, 814, and 1318 keV, respectively. We also report an upper limit for the 612 keV resonance of ωγ < 140 neV (95% c.l.), which effectively rules out any significant contribution from this resonance to the reaction rate. From this work, a new 17 O(α,γ) 21 Ne thermonuclear reaction rate is calculated and compared to the literature. The effect of present uncertainties in the 17 O(α,γ) 21 Ne reaction rate on weak s-process yields are then explored using postprocessing calculations based on a rotating 20M ⊙ low-metallicity massive star. The resulting 17 O(α,γ) 21 Ne reaction rate is lower with respect to the preexisting literature and found to enhance weak s-process yields in rotating massive star models.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Transport of an intense proton beam from a cone-structured target through plastic foam with unique proton source modeling

Laser-accelerated proton beams are applicable to several research areas within high-energy density science, including warm dense matter generation, proton radiography, and inertial confinement fusion, which all involve transport of the beam through matter. Here, we report on experimental measurements of intense proton beam transport through plastic foam blocks. The intense proton beam was accelerated by the 10 ps, 700 $\textit{J}$ OMEGA EP laser irradiating a curved foil target, and focused by an attached hollow cone. The protons then entered the foam block of density 0.38 g/cm 3 and thickness 0.55 or 1.00 mm. At the rear of the foam block, a Cu layer revealed the cross section of the intense beam via proton- and hot electron-induced Cu-K α emission. Images of x-ray emission show a bright spot on the rear Cu film indicative of a forward-directed beam without major breakup. 2D fluid-PIC simulations of the transport were conducted using a unique multi-injection source model incorporating energy-dependent beam divergence. Along with postprocessed calculations of the Cu – $K_α$ emission profile, simulations showed that protons retain their ballistic transport through the foam and are able to heat the foam up to several keV in temperature. The total experimental emission profile for the 1.0 mm foam agrees qualitatively with the simulated profile, suggesting that the protons indeed retain their beamlike qualities.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Mixed-State Entanglement from Local Randomized Measurements

In this work, we propose a method for detecting bipartite entanglement in a many-body mixed state based on estimating moments of the partially transposed density matrix. The estimates are obtained by performing local random measurements on the state, followed by postprocessing using the classical shadows framework. Our method can be applied to any quantum system with single-qubit control. We provide a detailed analysis of the required number of experimental runs, and demonstrate the protocol using existing experimental data [Brydges et al., Science 364, 260 (2019)].

1-dimensional spin chains↗

Correlating dynamic microstructure to observed color in electrophoretic displays via in situ small-angle x-ray scattering

Electrophoretic deposition (EPD) is an industrially relevant and scalable technique used to form particle deposits from colloidal suspensions. Highly concentrated particle suspensions generally prevent real-time in situ microscopy observations which limit the characterization of EPD films to ex situ, or postprocessed, laboratory techniques. For dynamic systems, such as tunable amorphous photonic crystals (APCs), only reversible deposits are formed during the EPD process. Since reversible deposits cannot be characterized with standard ex situ methods, the particle-particle and particle-field interactions that govern the displayed color and crystallinity of these systems are not well understood. In this paper, we present in situ small-angle x-ray scattering and UV-Vis techniques for measuring both the structural and optical response of an APC under applied electric fields. Furthermore, we also develop a computational model based on colloidal interactions to explain the observed change in the interparticle spacing of APCs due to the applied electric field which correlates to displayed color. Ultimately, this work provides a new in situ characterization method that could be expanded for other dynamic, tunable colloidal systems.

36 MATERIALS SCIENCE↗