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At least 1,207 records · Page 67

Energy Shifts and Broadening of Excitonic Resonances in Electrostatically Doped Semiconductors

Tuning the density of resident electrons or holes in semiconductors through electrostatic doping provides crucial insight into the composition of the many excitonic complexes that are routinely observed as absorption or photoluminescence resonances in optical studies. Moreover, we can change the way these resonances shift and broaden in energy by controlling the quantum numbers (e.g., spin and valley) of the resident carriers with applied magnetic fields and doping levels, as well as by selecting the quantum numbers of the photoexcited or recombining electron-hole (𝑒−ℎ) pair through optical polarization. Here, we discuss the roles of distinguishability and optimality of excitonic complexes, showing them to be key ingredients that determine the energy shifts and broadening of optical resonances in charge-tunable semiconductors. A distinguishable 𝑒−ℎ pair means that the electron and hole undergoing photoexcitation or recombination have quantum numbers that are not shared by any of the resident carriers. An optimal excitonic complex refers to a complex whose particles come with all available quantum numbers of the resident carriers. Based on the carrier density, magnetic field, and light polarization, all optical resonances may be classified as either distinct or indistinct depending on the distinguishability of the 𝑒−ℎ pair, and the underlying excitonic complex can be classified as either optimal or suboptimal. The universality of these classifications, inherited from the fundamental Pauli exclusion principle, allows us to understand how optical resonances shift in energy and whether they should broaden as doping is increased. This understanding is supported by conclusive evidence that the broadening and decay of optical resonances cannot be simply attributed to enhanced screening when resident carriers are added to a semiconductor. Finally, applying the classification scheme in either monolayer or moiré heterobilayer semiconductor systems, we relate the energy shift and amplitude of the neutral-exciton resonance to the compressibility of the resident carrier gas.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Utilizing multiple state variables to improve the dynamic range of analog switching in a memristor

Memristors and memristive systems have been extensively studied for data storage and computing applications such as neuromorphic systems. To act as synapses in neuromorphic systems, the memristor needs to exhibit analog resistive switching (RS) behavior with incremental conductance change. In this study, we show that the dynamic range of the analog RS behavior can be significantly enhanced in a tantalum-oxide-based memristor. By controlling different state variables enabled by different physical effects during the RS process, the gradual filament expansion stage can be selectively enhanced without strongly affecting the abrupt filament length growth stage. Detailed physics-based modeling further verified the observed experimental effects and revealed the roles of oxygen vacancy drift and diffusion processes, and how the diffusion process can be selectively enhanced during the filament expansion stage. These findings lead to more desirable and reliable memristor behaviors for analog computing applications. Additionally, the ability to selectively control different internal physical processes demonstrated in the current study provides guidance for continued device optimization of memristor devices in general.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Asymptotic optimality of twist-untwist protocols for Heisenberg scaling in atom-based sensing

Twist-untwist protocols for quantum metrology consist of a serial application of (1) unitary nonlinear dynamics (e.g., spin squeezing or Kerr nonlinearity), (2) parameterized dynamics U ( φ ) (e.g., a collective rotation or phase space displacement), and (3) time reversed application of step 1. Such protocols are known to produce states that allow Heisenberg scaling for experimentally accessible estimators of φ even when the nonlinearities are applied for times much shorter than required to produce Schrödinger cat states. In this work, we prove that, asymptotically in the number of particles, twist-untwist protocols provide the lowest estimation error among quantum metrology protocols that utilize two calls to a weakly nonlinear evolution and a readout involving only first and second moments of a total spin operator n → · J → . We consider the following physical settings: all-to-all interactions generated by one-axis twisting J z 2 (e.g., interacting Bose gases), constant finite range spin-spin interactions of distinguishable or bosonic atoms (e.g., trapped ions or Rydberg atoms, or lattice bosons). In these settings, we further show that the optimal twist-untwist protocols asymptotically achieve 85% and 92% of the respective quantum Cramér-Rao bounds. We show that the error of a twist-untwist protocol can be decreased by a factor of L without an increase in the noise of the spin measurement if the twist-untwist protocol can be noiselessly iterated as an L layer quantum alternating operator ansatz.

74 ATOMIC AND MOLECULAR PHYSICS↗

A room-temperature polarization-sensitive CMOS terahertz camera based on quantum-dot-enhanced terahertz-to-visible photon upconversion

Detection of terahertz (THz) radiation has many potential applications, but presently available detectors are limited in many aspects of their performance, including sensitivity, speed, bandwidth and operating temperature. Most do not allow the characterization of THz polarization states. Recent observation of THz-driven luminescence in quantum dots offers a possible detection mechanism via field-driven interdot charge transfer. Here, we demonstrate a room-temperature complementary metal–oxide–semiconductor THz camera and polarimeter based on quantum-dot-enhanced THz-to-visible upconversion mechanism with optimized luminophore geometries and fabrication designs. Besides broadband and fast responses, the nanoslit-based sensor can detect THz pulses with peak fields as low as 10 kV cm–1. A related coaxial nanoaperture-type device shows a to-date-unexplored capability to simultaneously record the THz polarization state and field strength with similar sensitivity.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Lieb-Mattis States for Robust Entangled Differential Phase Sensing

We explore a two-node, entanglement-enhanced sensor network for differential phase sensing that exploits decoherence-free subspaces to suppress common-mode noise, a primary limitation of many state-of-the-art quantum sensors. We identify a class of entangled states that, while not strictly optimal, achieve the same asymptotic sensitivity scaling as optimal states and can be prepared efficiently from initially unentangled atomic ensembles. Importantly, the preparation time decreases with increasing system size, which makes the states compatible with realistic noise processes in present-day quantum sensors that operate with large particle numbers but lack full error correction. We illustrate these ideas using two cavity-mediated preparation protocols: (i) coherent, unitary entanglement generation analogous to bosonic two-mode squeezing, yielding Heisenberg scaling, and (ii) dissipative preparation through collective emission into a shared cavity mode, providing a square-root improvement beyond the standard quantum limit. Numerical simulations show that both approaches remain effective at experimentally realistic cavity cooperativities, establishing a practical path toward scalable, quantum-enhanced differential phase sensing.

Kaubruegger, Raphael [National Institute of Standa↗

Diffusive and ballistic transport in thin InSb nanowire devices using a few-layer-graphene-AlO x gate

Abstract Quantum devices based on InSb nanowires (NWs) are a prime candidate system for realizing and exploring topologically-protected quantum states and for electrically-controlled spin-based qubits. The influence of disorder on achieving reliable quantum transport regimes has been studied theoretically, highlighting the importance of optimizing both growth and nanofabrication. In this work, we consider both aspects. We developed InSb NW with thin diameters, as well as a novel gating approach, involving few-layer graphene and atomic layer deposition-grown AlO x . Low-temperature electronic transport measurements of these devices reveal conductance plateaus and Fabry–Pérot interference, evidencing phase-coherent transport in the regime of few quantum modes. The approaches developed in this work could help mitigate the role of material and fabrication-induced disorder in semiconductor-based quantum devices.

36 MATERIALS SCIENCE↗

Degeneracy engineering for classical and quantum annealing: A case study of sparse linear regression in collider physics

Classical and quantum annealing are computing paradigms that have been proposed to solve a wide range of optimization problems. In this paper, we aim to enhance the performance of annealing algorithms by introducing the technique of degeneracy engineering, through which the relative degeneracy of the ground state is increased by modifying a subset of terms in the objective Hamiltonian. We illustrate this novel approach by applying it to the example of ℓ 0 -norm regularization for sparse linear regression, which is, in general, an NP-hard optimization problem. Specifically, we show how to cast ℓ 0 -norm regularization as a quadratic unconstrained binary optimization (QUBO) problem, suitable for implementation on annealing platforms. As a case study, we apply this QUBO formulation to energy flow polynomials in high-energy collider physics, finding that degeneracy engineering substantially improves the annealing performance. Furthermore, our results motivate the application of degeneracy engineering to a variety of regularized optimization problems.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

An approach to improving transporting velocity in the long-range ultrasonic transportation of micro-particles

In existing ultrasonic transportation methods, the long-range transportation of micro-particles is always realized in step-by-step way. Due to the substantial decrease of the driving force in each step, the transportation is lower-speed and stair-stepping. To improve the transporting velocity, a non-stepping ultrasonic transportation approach is proposed. By quantitatively analyzing the acoustic potential well, an optimal region is defined as the position, where the largest driving force is provided under the condition that the driving force is simultaneously the major component of an acoustic radiation force. To keep the micro-particle trapped in the optimal region during the whole transportation process, an approach of optimizing the phase-shifting velocity and phase-shifting step is adopted. Due to the stable and large driving force, the displacement of the micro-particle is an approximately linear function of time, instead of a stair-stepping function of time as in the existing step-by-step methods. An experimental setup is also developed to validate this approach. Long-range ultrasonic transportations of zirconium beads with high transporting velocity were realized. The experimental results demonstrated that this approach is an effective way to improve transporting velocity in the long-range ultrasonic transportation of micro-particles.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Quantum Noise Spectroscopy of Dynamical Critical Phenomena

The transition between distinct phases of matter is characterized by the nature of fluctuations near the critical point. We demonstrate that noise spectroscopy can not only diagnose the presence of a phase transition, but can also determine fundamental properties of its criticality. In particular, by analyzing a scaling collapse of the decoherence profile, one can directly extract the critical exponents of the transition and identify its universality class. Our approach naturally captures the presence of conservation laws and distinguishes between classical and quantum phase transitions. In the context of quantum magnetism, our proposal complements existing techniques and provides a novel toolset optimized for interrogating two-dimensional magnetic materials.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Multireference Electron Correlation Methods: Journeys along Potential Energy Surfaces

Multireference electron correlation methods describe static and dynamical electron correlation in a balanced way and, therefore, can yield accurate and predictive results even when single-reference methods or multiconfigurational self-consistent field theory fails. One of their most prominent applications in quantum chemistry is the exploration of potential energy surfaces. This includes the optimization of molecular geometries, such as equilibrium geometries and conical intersections and on-the-fly photodynamics simulations, both of which depend heavily on the ability of the method to properly explore the potential energy surface. Because such applications require nuclear gradients and derivative couplings, the availability of analytical nuclear gradients greatly enhances the scope of quantum chemical methods. This review focuses on the developments and advances made in the past two decades. A detailed account of the analytical nuclear gradient and derivative coupling theories is presented. Emphasis is given to the software infrastructure that allows one to make use of these methods. Notable applications of multireference electron correlation methods to chemistry, including geometry optimizations and on-the-fly dynamics, are summarized at the end followed by a discussion of future prospects.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Atomically Precise Manufacturing for 2D-Designed Materials

The primary purpose of this program was to develop atomically precise fabrication techniques for semiconductor systems that places dopant atoms in a single buried (100) atomic plane in silicon with near atomic precision to create unprecedented structures that can be used for a wide variety of quantum experiments, devices, and potentially designer quantum materials. The potential impacts on reducing industrial energy use are many: 1) optimized and more energy efficient industrial processes via more efficient computational approaches, 2) dramatically improved materials for industrial use including higher critical-temperature superconductors eliminating losses in electrical transmission, 3) the better understanding of quantum chemistry via Analog Quantum Simulation(AQS) in the near term and universal quantum computing in the longer term that will lead to new industrial processes with smaller or zero production of greenhouse gases.

36 MATERIALS SCIENCE↗

Enhanced current collection in 1.7 eV GaInAsP solar cells grown on GaAs by metalorganic vapor phase epitaxy

Quaternary GaInAsP solar cells with a bandgap of ~1.7 eV offer an attractive Al-free alternative to AlGaAs solar cells for integration in next generation of III-V multijunction solar cells with five or more junctions. Development of a high quality 1.7 eV solar cell is also highly sought for III-V/Si tandem solar cells. In this work, we systematically investigate the impact of varying base thicknesses and doping concentrations on the carrier collection and performance of 1.7 eV GaInAsP solar cells. The photoresponse of these cells is found to be very sensitive to p-type zinc doping concentration in the base layer. Prototype 1.7 eV GaInAsP n-i-p solar cell designs are demonstrated that leverage enhanced depletion width as an effective method to achieve peak quantum efficiency exceeding 90%. We also show the importance of optimal i-layer thickness as a critical parameter to reduce the drop in fill-factor (FF) due to field-aided collection. Furthermore, we demonstrate substantial improvement in the cell performance when the GaInAsP base layer is grown at 650 degrees C instead of 600 degrees C. The best GaInAsP solar cell (Eg ~ 1.65 eV) in this study achieved JSC of 21.1 mA/cm 2 , VOC of 1.18 V, FF of 83.8%, and an efficiency of 20.8 +/- 1% under AM1.5D spectrum (21.5 +/- 1% under AM1.5G spectrum). Finally, these results highlight the potential of Al-free GaInAsP solar cells for integration in the next generation of III-V multijunction solar cells.

14 SOLAR ENERGY↗

Computing an Optimal Entanglement Path with Throughput and Fidelity Considerations

Entanglement distribution is a core function of quantum networks essential for operations including teleportation, distributed quantum sensing, and multisite computation. Entanglement throughput and fidelity are two critical performance measures that depend on the quantum transmission along the links and swapping operations at the repeaters along the path. We study the problem of computing a end-to-end entanglement path that satisfies both fidelity and throughput requirements, leveraging qubit buffers at the nodes and considering the sequential swapping order. We show that the general problem of simultaneously satisfying both metrics to be NP-hard, and develop an algorithm to maximize throughput subject to a given fidelity threshold. We introduce the concepts of entanglement probability distribution and path domination and exploit them in the design of our algorithm. Extensive numerical results show that our algorithm can find optimal solutions in networks with thousands of nodes in less than a second. We also describe practical and possible implementation aspects of this algorithm in terms of devices and architecture support.

Xue, Guoliang [Arizona State University]↗

Efficient Mixed-Precision Matrix Factorization of the Inverse Overlap Matrix in Electronic Structure Calculations with AI-Hardware and GPUs

In recent years, a new kind of accelerated hardware has gained popularity in the artificial intelligence (AI) community which enables extremely high-performance tensor contractions in reduced precision for deep neural network calculations. In this article, we exploit Nvidia Tensor cores, a prototypical example of such AI-hardware, to develop a mixed precision approach for computing a dense matrix factorization of the inverse overlap matrix in electronic structure theory, S –1 . This factorization of S –1 , written as ZZT = S –1 , is used to transform the general matrix eigenvalue problem into a standard matrix eigenvalue problem. Here we present a mixed precision iterative refinement algorithm where Z is given recursively using matrix–matrix multiplications and can be computed with high performance on Tensor cores. To understand the performance and accuracy of Tensor cores, comparisons are made to GPU-only implementations in single and double precision. Additionally, we propose a nonparametric stopping criteria which is robust in the face of lower precision floating point operations. The algorithm is particularly useful when we have a good initial guess to Z, for example, from previous time steps in quantum-mechanical molecular dynamics simulations or from a previous iteration in a geometry optimization.

36 MATERIALS SCIENCE↗

Bayesian optimization of PYTHIA 8 tunes

A new tune (set of model parameters) is found for the six most important parameters of the PYTHIA 8 final state parton shower and hadronization model using Bayesian optimization. The tune fits the Large Electron-Positron collider (LEPI) data from ALEPH better than the default tune in PYTHIA 8. To the best of our knowledge, we present the most comprehensive application of Bayesian optimization to the tuning of a parton shower and hadronization model using the LEPI data.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

TU-F-18A-08: Effect of Quantum Detection Efficiency and Energy Bin Selection On Contrast-To-Noise-Ratio for Energy-Resolved Photon-Counting Detectors

Purpose: Energy-resolved photon-counting detectors have the capability to discriminate photons according to their energies. By using optimal energy weighting factors, the contrast-to-noise-ratio (CNR) of the reconstructed image can be improved. In this work, we investigate how quantum detection efficiency (QDE) affects the determination of the optimal energy threshold bins, and therefore the CNR improvement of photon-counting detectors. Methods: In this simulation study a photon-counting detector, based on Silicon (Si), was investigated. A task-oriented algorithm was used to determine the optimal energy bin setting in order to maximize CNR. Projection-based and Image-based energy weighting techniques were implemented. A 13 mm PMMA phantom with two contrast materials, hydroxyapatite (HA) and iodine (I), at different concentrations (100, 200, and 300 mg/mL for HA and 2, 4, and 8 mg/mL for I) was used. TASMIP algorithm was used to generate the spectrum with 2.7 mm Al filter. Different tube voltages, number of energy bins, and bin widths were investigated. Different thicknesses of Si were also investigated to determine the QDE effect on CNR. Results: CNR increased as the detector material thickness increased until it reached 30 mm for Si thickness such that the CNR value was near to the value predicted by an ideal detector. Also, the results indicated that the improvement of CNR due to the QDE is task-dependent when comparing weighted images to photon-counting images. For hydroxyapatite the improvement is approximately 20%, whereas for iodine it is less than 10%. Conclusion: The results showed that the improvement of CNR for an energy-resolved photon-counting detector is highly task-dependent when QDE is taken into account.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Iterative subspace algorithms for finite-temperature solution of Dyson equation

One-particle Green’s functions obtained from the self-consistent solution of the Dyson equation can be employed in the evaluation of spectroscopic and thermodynamic properties for both molecules and solids. However, typical acceleration techniques used in the traditional quantum chemistry self-consistent algorithms cannot be easily deployed for the Green’s function methods because of a non-convex grand potential functional and a non-idempotent density matrix. Moreover, the optimization problem can become more challenging due to the inclusion of correlation effects, changing chemical potential, and fluctuations of the number of particles. In this paper, we study acceleration techniques to target the self-consistent solution of the Dyson equation directly. We use the direct inversion in the iterative subspace (DIIS), the least-squared commutator in the iterative subspace (LCIIS), and the Krylov space accelerated inexact Newton method (KAIN). We observe that the definition of the residual has a significant impact on the convergence of the iterative procedure. Based on the Dyson equation, we generalize the concept of the commutator residual used in DIIS and LCIIS and compare it with the difference residual used in DIIS and KAIN. The commutator residuals outperform the difference residuals for all considered molecular and solid systems within both GW and GF2. For a number of bond-breaking problems, we found that an easily obtained high-temperature solution with effectively suppressed correlations is a very effective starting point for reaching convergence of the problematic low-temperature solutions through a sequential reduction of temperature during calculations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Quantum Tunneling Enabled Self-Assembly of Hydrogen Atoms on Cu(111)

Atomic and molecular self-assembly are key phenomena that underpin many important technologies. Typically, thermally enabled diffusion allows a system to sample many areas of configurational space, and ordered assemblies evolve that optimize interactions between species. Herein we describe a system in which the diffusion is quantum tunneling in nature and report the self-assembly of H atoms on a Cu(111) surface into complex arrays based on local clustering followed by larger scale islanding of these clusters. By scanning tunneling microscope tip-induced scrambling of H atom assemblies, we are able to watch the atomic scale details of H atom self-assembly in real time. The ordered arrangements we observe are complex and very different from those formed by H on other metals that occur in much simpler geometries. We contrast the diffusion and assembly of H with D, which has a much slower tunneling rate and is not able to form the large islands observed with H over equivalent time scales. Using density functional theory, we examine the interaction of H atoms on Cu(111) by calculating the differential binding energy as a function of H coverage. At the temperature of the experiments (5 K), H(D) diffusion by quantum tunneling dominates. The quantum-tunneling-enabled H and D diffusion is studied using a semiclassically corrected transition state theory coupled with density functional theory. This system constitutes the first example of quantum-tunneling-enabled self-assembly, while simultaneously demonstrating the complex ordering of H on Cu(111), a catalytically relevant surface.

Environmental Molecular Sciences Laboratory↗