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At least 55 records · Page 3

Absolutely Localized Projection-Based Embedding for Excited States

We present a quantum embedding method that allows for calculation of local excited states embedded in a Kohn–Sham density functional theory (DFT) environment. Projection-based quantum embedding methodologies provide a rigorous framework for performing DFT-in-DFT and wave function in DFT (WF-in-DFT) calculations. The use of absolute localization, where the density of each subsystem is expanded in only the basis functions associated with the atoms of that subsystem, provide improved computationally efficiency for WF-in-DFT calculations by reducing the number of orbitals in the WF calculation. In this work, we extend absolutely localized projection-based quantum embedding to study localized excited states using EOM-CCSD-in-DFT and TDDFT-in-DFT. The embedding results are highly accurate compared to the corresponding canonical EOM-CCSD and TDDFT results on the full system, with TDDFT-in-DFT frequently more accurate than canonical TDDFT. The absolute localization method is shown to eliminate the spurious low-lying excitation energies for charge-transfer states and prevent overdelocalization of excited states. Additionally, we attempt to recover the environment response caused by the electronic excitations in the high-level subsystem using different schemes and compare their accuracy. Finally, we apply this method to the calculation of the excited-state energy of green fluorescent protein and show that we systematically converge to the full system results. Here we demonstrate how this method can be useful in understanding excited states, specifically which chemical moieties polarize to the excitation. Furthermore, this work shows absolutely localized projection-based quantum embedding can treat local electronic excitations accurately and make computationally expensive WF methods applicable to systems beyond current computational limits.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Towards utility-scale electronic structure with sample-based quantum bootstrap embedding

One of the main applications for which quantum computers are hoped to find utility is in simulating ground state energies and other observables of molecular chemical systems. The recently proposed sample-based diagonalization method is a readily implementable method for this task on current-day hardware using short circuit depths and has been demonstrated on as many as 85 qubits in recent studies. In this work, we combine the recently proposed quantum bootstrap embedding (QBE) method with sampled-based diagonalization (QBE-SQD) and present the first benchmarking study of the QBE method on real quantum hardware, ibm_pittsburgh, a Heron r3 processor with 156 qubits. Our test system is a hydrogen ring with 8 hydrogen atoms in the cc-pVDZ basis. We show that for this system, QBE-SQD using an active space of (8e, 19o) per fragment with a 43 qubit footprint produces a ground state energy accuracy which exceeds that of an SQD calculation with an (8e, 30o) active space with a 67 qubit footprint when using a comparable number of Slater determinants. This demonstrates that the use of quantum bootstrap embedding techniques is a promising path towards extending the capabilities of state-of-the-art quantum eigensolvers on near-term devices.

Bierman, Joel [North Carolina State University, Ra↗

Embedding Learning in Hybrid Quantum-Classical Neural Networks

Quantum embedding learning is an important step in the application of quantum machine learning to classical data. In this paper we propose a quantum few-shot embedding learning paradigm, which learns embeddings useful for training downstream quantum machine learning tasks. Crucially, we identify the circuit bypass problem in hybrid neural networks, where learned classical parameters are optimized to represent the dataset without the quantum kernel. We observe that the few-shot learning embeddings generalize to unseen classes, and suffer less from the circuit bypass problem in terms of better occupation of the parameter space compared with embeddings learned from regression and classification.

Liu, Minzhao↗

Embedding PbS Quantum Dots (QDs) in Pb-Halide Perovskite Matrices: QD Surface Chemistry and Antisolvent Effects on QD Dispersion and Confinement Properties

Hybrid materials of metal chalcogenide colloidal quantum dots (QDs) embedded in metal halide perovskites (MHPs) have led to composites with synergistic properties. Here, we investigate how QD size, surface chemistry, and MHP film formation methods affect the resulting optoelectronic properties of QD/MHP “dot-in-matrix” systems. We monitor the QD absorption and photoluminescence throughout synthesis, ligand exchange, and transfer into the MHP ink, and we characterize the final QD/MHP films via electron microscopy and transient absorption. In addition, we are the first to globally map how PbS QDs are distributed on the micrometer scale within these dot-in-matrix systems, using three-dimensional (3D) tomography time-of-flight secondary ion mass spectrometry. The surface chemistry imparted during synthesis directly affects the optical properties of the dot-in-matrix composites. Pb-halide passivation leads to QD/MHP dot-in-matrix samples with optical properties that are well-described by a theoretical model, based on a Type I finite-barrier heterostructure between the PbS QD and the MHP matrix. Samples without Pb-halide passivation show complicated size-dependent behavior, indicating a transition from a Type I heterostructure between the PbS QD wells and MHP barriers for small-sized QDs to PbS QDs that are electronically decoupled from the MHP matrix for larger QDs. Furthermore, the choice in perovskite antisolvent crystallization method leads to a difference in the spatial QD distribution within the perovskite matrix, differences in carrier lifetime, and photoluminescence shifts of up to 180 meV for PbS in methylammonium lead iodide. This work establishes an understanding of such emerging synergistic systems relevant for technologies such as photovoltaics, infrared emitters and detectors, and other unexplored technological applications.

92 SC - Basic Energy Sciences (BES) (SC-22)↗

Liquid-phase plasma synthesis of silicon quantum dots embedded in carbon matrix for lithium battery anodes

Graphical abstract: - Highlights: • Silicon quantum dots embedded in carbon matrix (SiQDs/C) were fabricated. • SiQDs/C exhibits excellent battery performance as anode materials with high specific capacity. • The good performance was attributed to the marriage of small sized SiQDs and carbon. - Abstract: Silicon quantum dots embedded in carbon matrix (SiQDs/C) nanocomposites were prepared by a novel liquid-phase plasma assisted synthetic process. The SiQDs/C nanocomposites were demonstrated to show high specific capacity, good cycling life and high coulmbic efficiency as anode materials for lithium-ion battery.

36 MATERIALS SCIENCE↗

On-chip beamsplitter operation on single photons from quasi-resonantly excited quantum dots embedded in GaAs rib waveguides

We present an on-chip beamsplitter operating on a single-photon level by means of a quasi-resonantly driven InGaAs/GaAs quantum dot. The single photons are guided by rib waveguides and split into two arms by an evanescent field coupler. Although the waveguides themselves support the fundamental TE and TM modes, the measured degree of polarization (∼90%) reveals the main excitation and propagation of the TE mode. We observe the preserved single-photon nature of a quasi-resonantly excited quantum dot by performing a cross-correlation measurement on the two output arms of the beamsplitter. Additionally, the same quantum dot is investigated under resonant excitation, where the same splitting ratio is observed. An autocorrelation measurement with an off-chip beamsplitter on a single output arm reveal the single-photon nature after evanescent coupling inside the on-chip splitter. Due to their robustness, adjustable splitting ratio, and their easy implementation, rib waveguide beamsplitters with embedded quantum dots provide a promising step towards fully integrated quantum circuits.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Individual electron and hole localization in submonolayer InN quantum sheets embedded in GaN

We investigate sub-monolayer InN quantum sheets embedded in GaN(0001) by temperature-dependent photoluminescence spectroscopy under both continuous-wave and pulsed excitation. Both the peak energy and the linewidth of the emission band associated with the quantum sheets exhibit an anomalous dependence on temperature indicative of carrier localization. Photoluminescence transients reveal a power law decay at low temperatures reflecting that the recombining electrons and holes occupy spatially separate, individual potential minima reminiscent of conventional (In,Ga)N(0001) quantum wells exhibiting the characteristic disorder of a random alloy. At elevated temperatures, carrier delocalization sets in and is accompanied by a thermally activated quenching of the emission. We ascribe the strong nonradiative recombination to extended states in the GaN barriers and confirm our assumption by a simple rate-equation model.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Characterizing Quantum Classifier Utility in Natural Language Processing Workflows

Quantum Natural Language Processing (QNLP) develops natural language processing (NLP) models for deployment on quantum computers. We explore feature and data prototype selection techniques to address challenges posed by encoding high dimensional features. Our study builds quantum circuit classifiers that includes classical feature pre-processing, quantum embedding and quantum model training. The quantum models are built on 4 or 6 qubits and the quantum neural network (QNN) uses the established bricklayer design. We compare the dependence of model performance (in terms of accuracy and F1 scores) on feature length, embedding gates and parameterized unitary design. We compare the performance of quantum machine learning models to classical convolution neural network model (CNN) on binary and multi-class classification tasks using two datasets of synthetic features and labels. The first is the ECP-CANDLE P3B3 dataset a corpus of synthetically generated cancer pathology reports. The second dataset is extracted from well-known benchmark dataset (MADELON) - features are generated with a combination of informative, repeated and uninformative features. Both datasets are used for binary classification and multi-class classification with 3 classes. We observe robust, accurate performance from all models on the binary classification tasks, but multiclass classification is a challenge for the quantum models-there is a notable decrease in accuracy when using 3 classes. Overall the performance is comparable in terms of recall and accuracy between QNNs and CNNs, even with large datasets. These results provide a point of comparison between quantum and classical models on real-world datasets.

Hamilton, Kathleen↗

Green’s Function Formulation of Quantum Defect Embedding Theory

Here, we present a Green’s function formulation of the quantum defect embedding theory (QDET) where a double counting scheme is rigorously derived within the $G_0W_0$ approximation. We then show the robustness of our methodology by applying the theory with the newly derived scheme to several defects in diamond. Additionally, we discuss a strategy to obtain converged results as a function of the size and composition of the active space. Our results show that QDET is a promising approach to investigate strongly correlated states of defects in solids.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Charging/discharging behavior and mechanism of silicon quantum dots embedded in amorphous silicon carbide films

The charging/discharging behavior of Si quantum dots (QDs) embedded in amorphous silicon carbide (a-SiC{sub x}) was investigated based on the Al/insulating layer/Si QDs embedded in a-SiC{sub x}/SiO{sub 2}/p-Si (metal-insulator-quantum dots-oxide-silicon) multilayer structure by capacitance-voltage (C-V) and conductance-voltage (G-V) measurements. Transmission electron microscopy and Raman scattering spectroscopy measurements reveal the microstructure and distribution of Si QDs. The occurrence and shift of conductance peaks indicate the carrier transfer and the charging/discharging behavior of Si QDs. The multilayer structure shows a large memory window of 5.2 eV at ±8 V sweeping voltage. Analysis of the C-V and G-V results allows a quantification of the Coulomb charging energy and the trapped charge density associated with the charging/discharging behavior. It is found that the memory window is related to the size effect, and Si QDs with large size or low Coulomb charging energy can trap two or more electrons by changing the charging voltage. Meanwhile, the estimated lower potential barrier height between Si QD and a-SiC{sub x}, and the lower Coulomb charging energy of Si QDs could enhance the charging and discharging effect of Si QDs and lead to an enlarged memory window. Further studies of the charging/discharging mechanism of Si QDs embedded in a-SiC{sub x} can promote the application of Si QDs in low-power consumption semiconductor memory devices.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Charge transport and memristive properties of graphene quantum dots embedded in poly(3-hexylthiophene) matrix

We show that graphene quantum dots (GQD) embedded in a semiconducting poly(3-hexylthiophene) polymeric matrix act as charge trapping nanomaterials. In plane current-voltage (I-V) measurements of thin films realized from this nanocomposite deposited on gold interdigitated electrodes revealed that the GQD enhanced dramatically the hole transport. I-V characteristics exhibited a strong nonlinear behavior and a pinched hysteresis loop, a signature of a memristive response. The transport properties of this nanocomposite were explained in terms of a trap controlled space charge limited current mechanism.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Multireference Embedding and Fragmentation Methods for Classical and Quantum Computers: From Model Systems to Realistic Applications

One of the primary challenges in quantum chemistry is the accurate modeling of strong electron correlation. While multireference methods effectively capture such correlation, their steep scaling with system size prohibits their application to large molecules and extended materials. Quantum embedding offers a promising solution by partitioning complex systems into manageable subsystems. In this Review, we highlight recent advances in multireference density matrix embedding and localized active space self-consistent field approaches for complex molecules and extended materials. We discuss both classical implementations and the emerging potential of these methods on quantum computers. Here, by extending classical embedding concepts to the quantum landscape, these algorithms have the potential to expand the reach of multireference methods in quantum chemistry and materials.

Algorithms↗

Embedding Methods for Quantum Chemistry: Applications from Materials to Life Sciences

Quantum mechanical embedding methods hold the promise to transform not just the way calculations are performed, but to significantly reduce computational costs and improve scaling for macro molecular systems containing hundreds if not thousands of atoms. The field of embedding has grown increasingly broad with many approaches of different intersecting flavors. Here, we lay out the methods into two streams: QM:MM and QM:QM, showcasing the advantages and disadvantages of both. We provide a review of the literature, the underpinning theories including our contributions, and we highlight current applications with select examples spanning both materials and life sciences. Lastly, we conclude with prospects and future outlook on embedding, and our view on the use of universal test case scenarios for cross comparisons of the many available (and future) embedding theories.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Control of Quantized Spontaneous Emission from Single GaAs Quantum Dots Embedded in Huygens’ Metasurfaces

Advancements in photonic quantum information systems (QIS) have driven the development of high-brightness, on-demand, and indistinguishable semiconductor epitaxial quantum dots (QDs) as single photon sources. Strain-free, monodisperse, and spatially sparse local-droplet-etched (LDE) QDs have recently been demonstrated as a superior alternative to traditional Stranski–Krastanov QDs. However, integration of LDE QDs into nanophotonic architectures with the ability to scale to many interacting QDs is yet to be demonstrated. Here, we present a potential solution by embedding isolated LDE GaAs QDs within an Al 0.4 Ga 0.6 As Huygens’ metasurface with spectrally overlapping fundamental electric and magnetic dipolar resonances. We demonstrate for the first time a position- and size-independent, 1 order of magnitude increase in the collection efficiency and emission lifetime control for single-photon emission from LDE QDs embedded within the Huygens’ metasurfaces. Our results represent a significant step toward leveraging the advantages of LDE QDs within nanophotonic architectures to meet the scalability demands of photonic QIS.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Extending density functional embedding theory for covalently bonded systems

Significance Quantum mechanics (QM) simulations increasingly help researchers understand phenomena in chemistry, geoscience, material science, and biology. Unfortunately, the exact solution of the relevant QM equations is not available; consequently approximate yet accurate QM methods must be developed. In many situations, e.g., heterogeneous catalysis and enzymatic reactions, although the entire system is too large to treat with high-level QM, the relevant phenomena happen in a confined space. Quantum embedding theories can study exactly such cases by using highly accurate but expensive QM methods to simulate only the region of interest, while using fast but less accurate approximations to treat the surroundings. In this article, we present a unique, accurate quantum embedding theory applicable to covalently bonded systems.

42 ENGINEERING↗

Anomalous X-ray scattering study of quantum dots embedded in MBE grown silicon/germanium multilayers

Anomalous X-ray scattering is a unique technique to determine the composition profile of quantum dots embedded in buried interfaces of multilayer-structures. Here we present the results of MBE grown Si/Ge multilayer structures on Si(001) substrates having self-assembled Ge quantum dots in its buried interfaces. We performed grazing incidence diffraction measurements of (400) reflections along with (004) diffraction profiles exhibiting super-lattice reflections at and away from the germanium K-edge. Systematic analysis of the acquired data enabled us to extract average composition and strain profiles of the quantum dots.

36 MATERIALS SCIENCE↗

Light harvesting with Ge quantum dots embedded in SiO{sub 2} or Si{sub 3}N{sub 4}

Germanium quantum dots (QDs) embedded in SiO{sub 2} or in Si{sub 3}N{sub 4} have been studied for light harvesting purposes. SiGeO or SiGeN thin films, produced by plasma enhanced chemical vapor deposition, have been annealed up to 850 °C to induce Ge QD precipitation in Si based matrices. By varying the Ge content, the QD diameter can be tuned in the 3–9 nm range in the SiO{sub 2} matrix, or in the 1–2 nm range in the Si{sub 3}N{sub 4} matrix, as measured by transmission electron microscopy. Thus, Si{sub 3}N{sub 4} matrix hosts Ge QDs at higher density and more closely spaced than SiO{sub 2} matrix. Raman spectroscopy revealed a higher threshold for amorphous-to-crystalline transition for Ge QDs embedded in Si{sub 3}N{sub 4} matrix in comparison with those in the SiO{sub 2} host. Light absorption by Ge QDs is shown to be more effective in Si{sub 3}N{sub 4} matrix, due to the optical bandgap (0.9–1.6 eV) being lower than in SiO{sub 2} matrix (1.2–2.2 eV). Significant photoresponse with a large measured internal quantum efficiency has been observed for Ge QDs in Si{sub 3}N{sub 4} matrix when they are used as a sensitive layer in a photodetector device. These data will be presented and discussed, opening new routes for application of Ge QDs in light harvesting devices.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Stark spectroscopy of CdTe and CdMnTe quantum dots embedded in n-i-p diodes

We investigate charging effects in CdTe and Cd{sub 1−x}Mn{sub x}Te quantum dots embedded in n-i-p diodes. The tunneling of holes out of the dots at reverse bias and hole injection at forward bias control the dot charge state and allow for its electric field tuning. Furthermore, we analyze the Stark shifts of the photoluminescence transitions and evaluate the effect of the electric field on the binding of the observed excitonic complexes. We find that the binding can be strengthened or weakened depending on the zero-field alignment of the electron and hole wavefunctions.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗