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At least 37 records · Page 2

Study of the Scintillating Properties of Materials Based on Self- Assembling Quantum Dots Embedded into a Semiconductor Bulk

The goal of the project is to investigate scintillating properties of materials based on self-assembled InAs QDs embedded into GaAs bulk. According to theoretical predictions, such materials can have scintillating properties and low self-absorption. Compared to scintillators based on inorganic scintillating crystals, QD-based scintillators could have significantly higher light yield and shorter emission times. We intend to check the theoretical predictions experimentally, measure scintillation parameters and their dependence on the QD-based materials and learn how the properties could be optimized for practical applications.

36 MATERIALS SCIENCE↗

Quantum solver for single-impurity Anderson models with particle-hole symmetry

Quantum embedding methods, such as dynamical mean-field theory (DMFT), provide a powerful framework for investigating strongly correlated materials. A central computational bottleneck in DMFT is in solving the Anderson impurity model (AIM), whose exact solution is classically intractable for large bath sizes. In this work, we benchmark a quantum-classical hybrid solver tailored for particle-hole symmetric AIMs, using the variational quantum eigensolver to prepare the ground state of the model with shallow quantum circuits. The solver uses shallow quantum ansätze and one set of variational parameters to prepare the ground state and its particle and hole excitations, enabling the construction of the impurity Green’s function through a continued-fraction expansion. We evaluate the performance of this approach across a few bath sizes and interaction strengths under noisy, shot-limited conditions. We compare three optimization routines (COBYLA, Adam, and L-BFGS-B) in terms of convergence and fidelity, assess the benefits of estimating a quantum-computed moment correction to the variational energies, and benchmark the approach by comparing the density of states computed from the impurity Green’s function against that obtained using a classical pipeline. Our results demonstrate the feasibility of Green’s function construction on near-term devices and establish practical benchmarks for quantum impurity solvers embedded within self-consistent DMFT loops.

Karabin, Mariia [ORNL]↗

Cooperative effects in thin dielectric layers: Long-range Dicke superradiance

The realization and control of collective quantum effects so far have predominantly focused on cold atomic ensembles. Quantum photonic platforms, with their engineered Green's functions and integration capability of advanced solid-state quantum emitters, provide opportunities to explore regimes of light-matter interaction beyond the scope of atomic systems. In this work, we demonstrate that embedding quantum emitters within a thin dielectric layer fundamentally alters their collective radiative behavior. The optical modes in the dielectric layer mediate long-range dipole-dipole interactions between emitters, enabling both total and directional superradiance between emitters separated by several wavelengths. Crucially, this mechanism supports Dicke superradiance even in parameter regimes where standard settings fail to support an interaction, unveiling a dimensionality-driven enhancement of cooperative effects. By bridging many-body quantum optics and photonic engineering, our work reveals a distinct interplay between surrounding dimensionality and collective quantum dynamics. Experimental realization of these predictions, readily achievable in solid-state quantum optics platforms, paves the way for scalable, directional quantum light sources and frontiers in many-body quantum optics.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Comparing three generations of D-Wave quantum annealers for minor embedded combinatorial optimization problems

Abstract Quantum annealing (QA) is a novel type of analog computation that aims to use quantum mechanical fluctuations to search for optimal solutions of Ising problems. QA in the transverse Ising model, implemented on D-Wave quantum processing units, are available as cloud computing resources. In this study we report concise benchmarks across three generations of D-Wave quantum annealers, consisting of four different devices, for the NP-hard discrete combinatorial optimization problems unweighted maximum clique and unweighted maximum cut on random graphs. The Ising, or equivalently quadratic unconstrained binary optimization, formulation of these problems do not require auxiliary variables for order reduction, and their overall structure and weights are not highly variable, which makes these problems simple test cases to understand the sampling capability of current D-Wave quantum annealers. All-to-all minor embeddings of size 52, with relatively uniform chain lengths, are used for a direct comparison across the Chimera, Pegasus, and Zephyr device topologies. A grid-search over annealing times and the minor embedding chain strengths is performed in order to determine the level of reasonable performance for each device and problem type. Experiment metrics that are reported are approximation ratios for non-broken chain samples, chain break proportions, and time-to-solution for the maximum clique problem instances. How fairly the quantum annealers sample optimal maximum cliques, for instances which contain multiple maximum cliques, is quantified using entropy of the measured ground state distributions. The newest generation of quantum annealing hardware, which has a Zephyr hardware connectivity, performed the best overall with respect to approximation ratios and chain break frequencies.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Graphene Quantum Dot Composites Embedded with CoZn Alloy Nanoparticles for Enhanced Oxygen Reduction and Evolution Reactions

Developing efficient and durable electrocatalysts for oxygen reduction (ORR) and oxygen evolution reactions (OER) is crucial for energy conversion technologies. In this study, core–shell graphene quantum dot (GQD) composites embedded with Co, Zn, and CoZn alloy nanoparticles were synthesized using a solid-state microwave synthesis method and systematically investigated for their electrochemical performance. The structural and compositional analyses confirm that the integration of transition metal nanoparticles enhances the electronic properties of GQDs, providing abundant active sites and facilitating charge transfer. Electrochemical characterization reveals that GQD-CoZn-3 (GQD:Co:Zn = 10.5:0.5:0.5) exhibits superior ORR and OER catalytic activities, achieving the highest current densities of 205 A g–1 and 102 A g–1 at 100 mV s–1, respectively. These performance values surpass those of pristine GQDs and single-metal (Co or Zn) embedded counterparts, emphasizing the strong synergistic effect between the CoZn alloy and the functionalized carbon framework. Impedance measurements further reveal a substantial reduction in charge-transfer resistance, while chronoamperometry tests demonstrate excellent catalytic stability and CO tolerance, highlighting the robustness of the core–shell GQD structure. These findings provide valuable insights into the design of advanced carbon-based electrocatalysts for energy applications.

Panda, Pradeep Kumar↗

Thermal Stability of the Dot-in-Well Gain Medium for Photonic Crystal Surface Emitting Lasers

Self-assembled quantum dots (QDs) embedded in InGaAs quantum wells (QWs) are used as active regions for photonic-crystal surface-emitting lasers (PCSELs). An epitaxial regrowth method is developed to fabricate the dot-in-well (DWELL) PCSELs. Here, the epitaxial regrowth starts with the growth of a partial laser structure containing bottom cladding, waveguide, active region, and the photonic crystal (PC) layer. The PC layer is patterned to realize the cavity. Subsequently a top cladding layer is regrown to complete the laser structure. During the regrowth of the top cladding layer, the partial laser structure is subjected to high growth temperatures in excess of 600 °C resulting in an unintentional annealing of the active region. This annealing of the active region can alter the QDs by changing their size resulting in a blue shift in photoluminescence (PL) and narrowing PL emission. This effect results in the misaligning of the gain peak and the cavity resonance, resulting in sub-optimal lasing performance. DWELL active regions are known to have better thermal stability compared to both QDs and QWs and could be an ideal candidate for regrown PCSELs. We successfully demonstrate an optically-pumped epitaxially-regrown DWELL PCSEL with an emission wavelength of 1230 nm operating at room temperature. Furthermore, the DWELL active region shows excellent emission wavelength stability and intensity despite the high temperature regrowth process.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

High conductivity coherently strained quantum well XHEMT heterostructures on AlN substrates with delta doping

Polarization-induced two-dimensional electron gases (2DEGs) in AlN/GaN/AlN quantum well high-electron-mobility transistors on ultrawide bandgap AlN substrates offer a promising route to advance microwave and power electronics with nitride semiconductors. The electron mobility in thin GaN quantum wells embedded in AlN is limited by high internal electric field and the presence of undesired polarization-induced two-dimensional hole gases (2DHGs). To enhance the electron mobility in such heterostructures on AlN, previous efforts have resorted to thick, relaxed GaN channels with dislocations. In this work, we introduce n-type compensation δ-doping in a coherently strained single-crystal (Xtal) AlN/GaN/AlN heterostructure to counter the 2DHG formation at the GaN/AlN interface, and simultaneously lower the internal electric field in the well. This approach yields a δ-doped XHEMT structure with a high 2DEG density of ∼3.2×1013 cm−2 and a room temperature (RT) mobility of ∼855 cm2/Vs, resulting in the lowest RT sheet resistance 226.7 Ω/□ reported to date in coherently strained AlN/GaN/AlN HEMT heterostructures on the AlN platform.

Physics↗

Phonon Screening of Excitons in Atomically Thin Semiconductors

Atomically thin semiconductors, encompassing both 2D materials and quantum wells, exhibit a pronounced enhancement of excitonic effects due to geometric confinement. Consequently, these materials have become foundational platforms for the exploration and utilization of excitons. Recent ab initio studies have demonstrated that phonons can substantially screen electron-hole interactions in bulk semiconductors and strongly modify the properties of excitons. While excitonic properties of atomically thin semiconductors have been the subject of extensive theoretical investigations, the role of phonon screening on excitons in atomically thin structures remains unexplored. In this Letter, we demonstrate via ab initio GW-Bethe-Salpeter equation calculations that phonon screening can have a significant impact on optical excitations in atomically thin semiconductors. We further show that the degree of phonon screening can be tuned by structural engineering. We focus on atomically thin GaN quantum wells embedded in AlN and identify specific phonons in the surrounding material, AlN, that dramatically alter the lowest-lying exciton in monolayer GaN via screening. Our studies provide new intuition beyond standard models into the interplay among structural properties, phonon characteristics, and exciton properties in atomically thin semiconductors, and have implications for future experiments.

2-dimensional systems↗

Quantum computing approach for building surface sunlit in urban-scale energy modeling

Solar shadow calculations are needed in building energy modeling and performance simulation of PV systems installed on roofs or facades of buildings. We present a quantum computing approach for calculation of building surface sunlit fractions by recasting solar visibility as a binary optimization problem solved by quantum annealing. Each triangulated surface centroid is encoded as a binary qubit indicating sunlit or shaded status. Geometric visibility constraints are derived from the Möller-Trumbore intersection algorithm and converted into a constrained quadratic binary model compatible with contemporary quantum annealers. The coefficients were embedded to D-Wave quantum computer. To demonstrate feasibility, we conducted a case study in San Francisco for a target building with 52 triangles and roughly 2700 nearby triangles within 50 m evaluated at representative winter and summer solar positions. The results demonstrated that quantum annealing can reliably calculate and distinguish sunlit from shaded surfaces. Quantum samples achieved average accuracy exceeding 92.4 %, with the aggregate surface-level agreement approaching 99.9 %. The outputs of quantum computers agreed closely with classical algorithms, indicating practical feasibility and promising scalability. Finally, the hourly sunlit fractions of building surfaces can be obtained for urban energy modelling. This is the first study to apply quantum computing to the solar shadow and building surface sunlit calculation. It introduces a new paradigm that differs fundamentally from traditional approaches.

Deng, Zhipeng↗

Nonmagnetic fractional conductance in high mobility InAs quantum point contacts

In this paper, we report the magnetoelectronic properties of high mobility InAs quantum point contacts grown on InP substrates. The InAs quantum well is embedded between In 0.72 ⁢Ga 0.28 ⁢As cladding layers and In 0.81 ⁢Al 0.19 ⁢As barrier layers, and is populated via self-accumulation. The one-dimensional (1D) conductance reaches a maximum value of 17 plateaus, quantized in units of 2⁢𝑒 2 /ℎ, where 𝑒 is the fundamental unit of charge and ℎ is Planck's constant. The in-plane effective 𝑔 factor was estimated to be −10.9 ± 1.5 for subband 𝑁 = 1 and −10.8 ± 1.6 for subband 𝑁 = 2. Furthermore, a study of the nonmagnetic fractional conductance states at 0.2 (𝑒 2 /ℎ) and 0.1 (𝑒 2 /ℎ) is provided. While their origin remains under discussion, evidence suggests that they arise from strong electron-electron interactions and momentum-conserving backscattering between electrons in two distinct channels within the 1D region. This phenomenon may also be interpreted as an entanglement between the two channel directions facilitated by momentum-conserving backscattering.

Ballistic transport↗

A Perspective on Quantum Computing Applications in Quantum Chemistry Using 25-100 Logical Qubits

The intersection of quantum computing and quantum chemistry represents a promising frontier for achieving quantum utility in domains of both scientific and societal relevance. Owing to the exponential growth of classical resource requirements for simulating quantum systems, quantum chemistry has long been recognized as a natural candidate for quantum computation. This perspective focuses on identifying scientifically meaningful use cases where early fault-tolerant quantum computers, which are considered to be equipped with approximately 25-100 logical qubits, could deliver tangible impact. While recent advances in classical computing have pushed the boundaries of tractable simulations to unprecedented scales, this logical-qubit regime represents the first window where quantum devices can pursue qualitatively distinct strategies, such as polynomial-scaling phase estimation, direct simulation of quantum dynamics, and active-space embedding, that remain challenging for classical solvers, such as multireference charge-transfer and conical-intersection states central to photochemistry and materials design. We highlight near-term opportunities in algorithm and software design, discuss representative chemical problems suited for quantum acceleration, and propose strategic roadmaps and collaborative pathways for advancing practical quantum utility in quantum chemistry.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Quantum mechanical closure of partial differential equations with symmetries

We develop a statistical framework for the dynamical closure of spatiotemporal dynamics governed by partial differential equations. Employing the mathematical framework of quantum mechanics to embed the original classical dynamics into a quantum mechanical representation, we use the space of quantum density operators to model the unresolved degrees of freedom of the original dynamics in a statistical sense, and the framework of quantum measurement to predict their contributions to the resolved dynamics. The embedded dynamics is discretized by a positivity preserving process, leading to a compressed representation that is invariant under the dynamical symmetries of the resolved dynamics. We present a data based formulation of the closure scheme and apply it to a closure problem for the shallow water equations. The numerical results demonstrate that our closure model can accurately predict the main features of the true dynamics, including for out of sample initial conditions.

Delay embedding↗

Quantum block encoding for one-pair semiseparable matrices

Quantum block encoding (QBE) is a crucial step in the development of most quantum algorithms, as it provides an embedding of a given matrix into a suitable larger unitary matrix. Historically, the development of efficient techniques for QBE has mostly focused on sparse matrices; less effort has been devoted to data-sparse (e.g., rank-structured) matrices. In this work we examine a particular case of rank structure, namely, one-pair semiseparable matrices. We present a new block encoding approach that relies on a suitable factorization of the given matrix as the product of triangular and diagonal factors. To encode the matrix, the algorithm needs $2\log(N)+7$ ancillary qubits. Assuming that the data input oracles can be implemented with polylogarithmic depth, or that a QRAM input model is available, our proposed method requires $\mathcal{O}({\rm polylog} (N))$ time and has an error of $\mathcal{O}(N^2)$, where $N$ is the matrix size.

Antonioli, Giacomo [Pisa U.; CERN] (ORCID:00090000↗

Dual atom catalysts for rapid electrochemical reduction of CO to ethylene

Strong CO adsorption and facile CO dimerization are the key challenges in electrochemical CO2 reduction towards multi-carbon (C2+) products. We recently showed that CoPc immobilized on a single-walled carbon nanotube can selectively reduce CO2 to methanol. This is enabled through molecular strain, which dramatically improves the CO adsorption energy to CoPc, which in turn facilitates methanol formation. We now examine the extended Phthalocyanine (PcEx) dual atom catalyst (DAC), which is intrinsically strained and contains two catalyst centers, making it a candidate for reducing CO to C2+ products. Using Quantum Mechanics (QM), we screened 20 elements embedded in the PcEx, seeking catalysts with weak hydrogen binding, strong CO binding, and facile CO dimerization. We identi>ied Fe, Ru, Co, and Ir as the best performers and subsequently evaluated the entire CO to C2H4 mechanism (9 steps) using each of these elements as catalysts. In terms of limiting potential and overall exergonicity, we identi>ied CoPcEx as the best catalyst, followed by IrPcEx. We then examined the full CO to C2H4 mechanism on the bimetallic IrCoPcEx catalyst using grand canonical QM to obtain the reaction energetics as a function of applied potential. We conclude that the bimetallic IrCoPcEx is most promising for ef>iciently converting CO to ethylene.

Musgrave, Charles B.↗

Coherent Erbium Spin Defects in Colloidal Nanocrystal Hosts

We demonstrate nearly a microsecond of spin coherence in Er 3+ ions doped in cerium dioxide nanocrystal hosts, despite a large gyromagnetic ratio and nanometric proximity of the spin defect to the nanocrystal surface. The long spin coherence is enabled by reducing the dopant density below the instantaneous diffusion limit in a nuclear spin-free host material, reaching the limit of a single erbium spin defect per nanocrystal. We observe a large Orbach energy in a highly symmetric cubic site, further protecting the coherence in a qubit that would otherwise rapidly decohere. Spatially correlated electron spectroscopy measurements reveal the presence of Ce 3+ at the nanocrystal surface, which likely acts as extraneous paramagnetic spin noise. Even with these factors, defect-embedded nanocrystal hosts show tremendous promise for quantum sensing and quantum communication applications, with multiple avenues, including core-shell fabrication, redox tuning of oxygen vacancies, and organic surfactant modification, available to further enhance their spin coherence and functionality in the future.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Enhanced spectral purity of WSe 2 quantum emitters via conformal organic adlayers

Quantum emitters in solid-state materials are typically embedded in the bulk of their hosts, making their electronic transitions inaccessible to surface modification. In contrast, two-dimensional materials, with their all-surface nature, offer a platform for tuning quantum emitters via chemical functionalization. Because of its semiconducting properties that enable electrical addressability, monolayer WSe 2 is a promising candidate for quantum emission, although the complex interplay between point defects and the localized strain needed to activate quantum emission leads to poor spectral purity. Here, we demonstrate that functionalizing monolayer WSe 2 with conformal adlayers of 3,4,9,10-perylenetetracarboxylic dianhydride (PTCDA) improves quantum emission spectral purity. Optical spectroscopy reveals that PTCDA functionalization lowers defect activation energies by 10 meV and induces a 30 nm redshift in quantum emission wavelength, while preserving the bright and dark exciton energies of monolayer WSe 2 . First-principles calculations corroborate these findings, thus providing molecular-level insight into the underlying mechanism of enhanced spectral purity.

Ananth, Riddhi [Northwestern Univ., Evanston, IL (↗

Hybrid Quantum–Classical Graph Transformers for Efficient Sentiment Analysis

Quantum Machine Learning (QML) offers a promising paradigm that leverages quantum computing principles to develop efficient and expressive models for learning from complex and structured data. Recent advances in natural language processing (NLP) and artificial intelligence (AI) have demonstrated capabilities in understanding, generating, and reasoning over linguistic and multimodal information. In this work, we present the Quantum Graph Transformer (QGT), a hybrid quantum–classical architecture that extends graph transformer capabilities through quantum self-attention. The QGT models variable-length sentences as token graphs, where both the embedding encoding and the self-attention mechanisms are implemented using parameterized quantum circuits (PQCs), enabling efficient contextual learning with significantly fewer trainable parameters. We train QGT using both fully connected and 𝑘 -nearest-neighbor graph structures and evaluate it on five benchmark sentiment-classification datasets. Experimental results show that QGT consistently achieves higher or comparable accuracy to existing quantum NLP models and outperforms a Classical Graph Transformer (CGT) baseline with identical architecture, achieving 29.4 × fewer parameters while requiring 3–5 × fewer samples to reach comparable performance. These findings highlight the potential of graph-based quantum models as scalable and data-efficient architectures for natural language understanding.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Optical properties of a diamond NV color center from capped embedded multiconfigurational correlated wavefunction theory

Diamond defects are among the most promising qubits. Modeling their properties through accurate quantum mechanical simulations can further their development into robust units of information. We use the recently developed capped density functional embedding theory (capped-DFET) with the multiconfigurational n-electron valence second-order perturbation theory to characterize the electronic excitation energies for different spin manifolds of the well-characterized negatively charged substitutional N defect adjacent to a vacancy (V C ) in diamond (N C V C − ). We successfully reproduce vertical excitation energies for both triplet and singlet states of N C V C − with errors < 0.1 eV. Unlike other embedding methods, capped-DFET exhibits robust predictions that are approximately independent of the embedded cluster size: it only requires a cluster to contain the defect atoms and their nearest neighbors (as small as a 40-atom capped cluster). Furthermore, our method is free from slowly converging Coulomb interactions between charged defects, and thus also only weakly dependent on supercell size.

Chemistry↗