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At least 721 records · Page 40

Phase space localization for anti-de Sitter quantum mechanics and its zero curvature limit

Using techniques of geometric quantization and SO(sub 0)(3,2)-coherent states, a notion of optimal localization on phase space is defined for the quantum theory of a massive and spinning particle in anti-de Sitter space time. It is shown that this notion disappears in the zero curvature limit, providing one with a concrete example of the regularizing character of the constant (nonzero) curvature of the anti-de Sitter space time. As a byproduct a geometric characterization of masslessness is obtained.

Elgradechi, Amine M.↗

Triple-junction solar cells with 39.5% terrestrial and 34.2% space efficiency enabled by thick quantum well superlattices

Multijunction solar cell design is guided by both the theoretical optimal bandgap combination as well as the realistic limitations to materials with these bandgaps. For instance, triple-junction III-V multijunction solar cells commonly use GaAs as a middle cell because of its near-perfect material quality, despite its bandgap being higher than optimal for the global spectrum. Here, we modify the middle cell bandgap using thick GaInAs/GaAsP strain-balanced quantum well (QW) solar cells with excellent voltage and absorption. Additionally, these high-performance QWs are incorporated into a triple-junction inverted metamorphic multijunction device consisting of a GaInP top cell, GaInAs/GaAsP QW middle cell, and lattice-mismatched GaInAs bottom cell, each of which has been highly optimized. We demonstrate triple-junction efficiencies of 39.5% and 34.2% under the AM1.5 global and AM0 space spectra, respectively, and the global efficiency is higher than previous record six-junction devices.

14 SOLAR ENERGY↗

Characterization of Tunnel Oxides in TOPCon Solar Cells

The 1.12 nm thickness for the tunnel oxide layer is near the optimal range described by Choi et al. This thickness should be effective at enabling quantum tunneling; however, it is slightly lower than the reported optimal range which could negatively impact the passivation of the poly-Si interface. An appropriate balance between the two functions must be met to optimize efficiency. Follow up work could focus on testing the optimal range for tunnel oxide thickness in TOPCon solar cells, as well as improving the manufacturing process to produce better control of film thickness. This work could be extended into more advanced TOPCon solar cells including double or triple stack structures, as well as experimental pinhole designs.

SOLAR ENERGY↗

MEMS terahertz-to-infrared band converter using frequency selective planar metamaterial

A MEMS terahertz-to-infrared converter has been developed based on the unique properties of metamaterials that allow for selective control of the absorptivity and emissivity of the sensors. The converter consists of a sensing element structurally made of planar metamaterial membranes, connected to a substrate frame by four symmetrically-located thermal insulators. Upon THz absorption, the temperature of the sensing element increases and the outward infrared flux from the backside of the element is read by a commercial long-wave infrared camera. Two configurations were designed and fabricated with metamaterial absorptivity optimized for 3.8THz and 4.75THz quantum cascade lasers. The first sensor, fabricated with an oxidized aluminum backside, exhibits higher responsivity, but lower conversion efficiency than the second sensor, fabricated with a metamaterial backside. The spectral characteristics of the metamaterial on the two sides can be optimized to improve both responsivity and sensitivity, while keeping the sensors’ thermal time constant sufficiently small for real time imaging. No dedicated electronics or optics are required for readout making metamaterial-based MEMS THz-to-IR converters very attractive for THz imaging as means of a simple attachment to commercial IR cameras.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Absence of Barren Plateaus and Scaling of Gradients in the Energy Optimization of Isometric Tensor Network States

Abstract Vanishing gradients can pose substantial obstacles for high-dimensional optimization problems. Here we consider energy minimization problems for quantum many-body systems with extensive Hamiltonians and finite-range interactions, which can be studied on classical computers or in the form of variational quantum eigensolvers on quantum computers. Barren plateaus correspond to scenarios where the average amplitude of the energy gradient decreases exponentially with increasing system size. This occurs, for example, for quantum neural networks and for brickwall quantum circuits when the depth increases polynomially in the system size. Here we prove that the variational optimization problems for matrix product states, tree tensor networks, and the multiscale entanglement renormalization ansatz are free of barren plateaus. The derived scaling properties for the gradient variance provide an analytical guarantee for the trainability of randomly initialized tensor network states (TNS) and motivate certain initialization schemes. In a suitable representation, unitary tensors that parametrize the TNS are sampled according to the uniform Haar measure. We employ a Riemannian formulation of the gradient based optimizations which simplifies the analytical evaluation.

Barthel, Thomas↗

Dynamics of reverse annealing for the fully connected p -spin model

Reverse annealing is a relatively new variant of quantum annealing in which one starts from a classical state and increases and then decreases the amplitude of the transverse field, in the hope of finding a better classical state than the initial state for a given optimization problem. We numerically study the unitary quantum dynamics of reverse annealing for the mean-field-type p -spin model and show that the results are consistent with the predictions of equilibrium statistical mechanics. In particular, we corroborate the equilibrium analysis prediction that reverse annealing provides an exponential speedup over conventional quantum annealing in terms of solving the p -spin model. This lends support to the expectation that equilibrium analyses are effective at revealing essential aspects of the dynamics of quantum annealing. We also compare the results of quantum dynamics with the corresponding classical dynamics to reveal their similarities and differences. We distinguish between two reverse annealing protocols we call adiabatic and iterated reverse annealing. We further show that iterated reverse annealing, as has been realized in the D-Wave device, is ineffective in the case of the p-spin model but note that a recently introduced protocol (“ h -gain”), which implements adiabatic reverse annealing, may lead to improved performance.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Balanced k -means clustering on an adiabatic quantum computer

Adiabatic quantum computers are a promising platform for efficiently solving challenging optimization problems. Therefore, many are interested in using these computers to train computationally expensive machine learning models. We present a quantum approach to solving the balanced k-means clustering training problem on the D-Wave 2000Q adiabatic quantum computer. In order to do this, we formulate the training problem as a quadratic unconstrained binary optimization (QUBO) problem. Unlike existing classical algorithms, our QUBO formulation targets the global solution to the balanced k-means model. We test our approach on a number of small problems and observe that despite the theoretical benefits of the QUBO formulation, the clustering solution obtained by a modern quantum computer is usually inferior to the solution obtained by the best classical clustering algorithms. Nevertheless, the solutions provided by the quantum computer do exhibit some promising characteristics. We also perform a scalability study to estimate the run time of our approach on large problems using future quantum hardware. Finally, as a final proof of concept, we used the quantum approach to cluster random subsets of the Iris benchmark data set.

97 MATHEMATICS AND COMPUTING↗

KinBot: Automated stationary point search on potential energy surfaces

KinBot is a Python code that automatically characterizes kinetically important stationary points on reactive potential energy surfaces and arranges the results into a form that lends itself easily to master equation calculations. This version of KinBot tackles C, H, O and S atom containing species and unimolecular (isomerization or dissociation) reactions. KinBot iteratively changes the geometry of the reactant to obtain initial guesses for reactive saddle points defined by KinBot’s reaction types, which are then optimized by a third-party quantum chemistry package. KinBot verifies the connectivity of the saddle points with the reactant and identifies the products through intrinsic reaction coordinate calculations. Here, new calculations can be automatically spawned from the products to obtain complete potential energy surfaces. The utilities of KinBot include conformer searches, projected frequency and hindered rotor calculations, and the automatic determination of the rotational symmetry numbers. Input files for popular RRKM master equation codes are automatically built, enabling an automated workflow all the way to the calculation of pressure and temperature dependent rate coefficients. Four examples are as follows: (i) [1,3]-sigmatropic H-migration reactions of unsaturated hydrocarbons and oxygenates are calculated to assess the relative importance of suprafacial and antrafacial reactions. (ii) Saddle points on three products of gamma-valerolactone thermal decomposition are studied and compared to literature potential energy surfaces. (iii) The previously published propene+OH reaction is reproduced to show the capability of building an entire potential energy surface. (iv) All species up to C4 in the Aramco Mech 2.0 are subjected to a KinBot search.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Optimal Orbital Selection for Full Configuration Interaction (OptOrbFCI): Pursuing the Basis Set Limit under a Budget

Full configuration interaction (FCI) solvers are limited to small basis sets due to their expensive computational costs. An optimal orbital selection for FCI (OptOrbFCI) is proposed to boost the power of existing FCI solvers to pursue the basis set limit under a computational budget. The optimization problem coincides with that of the complete active space SCF method (CASSCF), while OptOrbFCI is algorithmically quite different. OptOrbFCI effectively finds an optimal rotation matrix via solving a constrained optimization problem directly to compress the orbitals of large basis sets to one with a manageable size, conducts FCI calculations only on rotated orbital sets, and produces a variational ground-state energy and its wave function. Coupled with coordinate descent full configuration interaction (CDFCI), we demonstrate the efficiency and accuracy of the method on the carbon dimer and nitrogen dimer under basis sets up to cc-pV5Z. We also benchmark the binding curve of the nitrogen dimer under the cc-pVQZ basis set with 28 selected orbitals, which provide consistently lower ground-state energies than the FCI results under the cc-pVDZ basis set. Furthermore, the dissociation energy in this case is found to be of higher accuracy.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Axial H-Bonding Solvent Controls Inhomogeneous Spectral Broadening, While Peripheral H-Bonding Solvent Controls Vibronic Broadening: Cresyl Violet in Methanol

The dynamics of the nuclei of both a chromophore and its condensed-phase environment control many spectral features, including the vibronic and inhomogeneous broadening present in spectral line shapes. For the cresyl violet chromophore in methanol, we here analyze and isolate the effect of specific chromophore–solvent interactions on simulated spectral densities, reorganization energies, and linear absorption spectra. Employing both chromophore and its condensed-phase environment control many spectral features, including the vibronic and inhomogeneous broadening present in spectral line shapes. For the cresyl violet chromophore in methanol, we here analyze and isolate the effect of specific chromophore–solvent interactions on simulated spectral densities, reorganization energies, and linear absorption spectra. Employing both force field and ab initio molecular dynamics trajectories along with the inclusion of only certain solvent molecules in the excited-state calculations, we determine that the methanol molecules axial to the chromophore are responsible for the majority of inhomogeneous broadening, with a single methanol molecule that forms an axial hydrogen bond dominating the response. Furthermore, the strong peripheral hydrogen bonds do not contribute to spectral broadening, as they are very stable throughout the dynamics and do not lead to increased energy-gap fluctuations. We also find that treating the strong peripheral hydrogen bonds as molecular mechanical point charges during the molecular dynamics simulation underestimates the vibronic coupling. Including these peripheral hydrogen bonding methanol molecules in the quantum-mechanical region in a geometry optimization increases the vibronic coupling, suggesting that a more advanced treatment of these strongly interacting solvent molecules during the molecular dynamics trajectory may be necessary to capture the full vibronic spectral broadening.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Identification of Active Sites of Pure and Nitrogen-Doped Carbon Materials for Oxygen Reduction Reaction Using Constant-Potential Calculations

Nitrogen-doped carbon materials are promising metal-free catalysts for the electrochemical oxygen reduction reaction (ORR). A better theoretical understanding on the nature of the active site(s) would help further optimization of their ORR activity. Although quantum mechanical calculations have been widely employed to elucidate the active sites over various catalysts, these calculations are typically done assuming constantcharge conditions rather than the experimentally relevant constant-potential conditions. In this study, we employ the double-reference method to simulate the energetics of the ORR over pure and N-doped carbon materials under constant-potential conditions. We demonstrate that constant-potential calculations enable more accurate theoretical predictions, comparing well with existing experiments. Our key findings are (1) the zigzag edge of pure graphite is highly active for ORR, (2) the pyridinic N-doped armchair edge is highly active for ORR in alkaline media but not in acid, and (3) graphitic N can donate electrons to pyridinic N to enhance the ORR activity. Furthermore, these fundamental insights provide guidelines for the design of better carbonbased ORR catalysts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Improving Strain-localized GaSe Single Photon Emitters with Electrical Doping

Exciton localization through nanoscale strain has been used to create highly efficient single-photon emitters (SPEs) in 2D materials. However, the strong Coulomb interactions between excitons can lead to nonradiative recombination through exciton–exciton annihilation, negatively impacting SPE performance. Here, we investigate the effect of Coulomb interactions on the brightness, single photon purity, and operating temperatures of strain-localized GaSe SPEs by using electrostatic doping. By gating GaSe to the charge neutrality point, the exciton–exciton annihilation nonradiative pathway is suppressed, leading to ∼60% improvement of emission intensity and an enhancement of the single photon purity g (2) (0) from 0.55 to 0.28. The operating temperature also increased from 4.5 K to 85 K consequently. In conclusion, this research provides insight into many-body interactions in excitons confined by nanoscale strain and lays the groundwork for the optimization of SPEs for optoelectronics and quantum photonics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Comparison of temperature and doping dependence of elastoresistivity near a putative nematic quantum critical point

Abstract Strong electronic nematic fluctuations have been discovered near optimal doping for several families of Fe-based superconductors, motivating the search for a possible link between these fluctuations, nematic quantum criticality, and high temperature superconductivity. Here we probe a key prediction of quantum criticality, namely power-law dependence of the associated nematic susceptibility as a function of composition and temperature approaching the compositionally tuned putative quantum critical point. To probe the ‘bare’ quantum critical point requires suppression of the superconducting state, which we achieve by using large magnetic fields, up to 45 T, while performing elastoresistivity measurements to follow the nematic susceptibility. We performed these measurements for the prototypical electron-doped pnictide, Ba(Fe 1− x Co x ) 2 As 2 , over a dense comb of dopings. We find that close to the putative quantum critical point, the elastoresistivity appears to obey power-law behavior as a function of composition over almost a decade of variation in composition. Paradoxically, however, we also find that the temperature dependence for compositions close to the critical value cannot be described by a single power law.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Design of AlGaN-Zn(Si,Ge)N2 quantum wells for high-efficiency ultraviolet light emitters

The effect of inserting a nm-scale layer of Zn(Si,Ge)N2 into an AlGaN quantum well structure designed for light emission in the wavelength range from 255 to 305 nm is investigated here. The enhanced confinement of the hole within the quantum well results in an enhancement of the overlap of the hole and electron wave functions, resulting in an enhancement of the radiative recombination rate. In this theoretical calculation, for emission at a 270 nm wavelength, the enhancement in the wavefunction overlap can reach a factor of 7 when compared to an AlGaN quantum well device specifically engineered for optimal emission at the identical wavelength. Increases of almost an order of magnitude in both the peak spontaneous emission intensity and the radiative recombination rate are predicted. The peak emission wavelength can be tuned from 255 to 305 nm by adjusting the width and/or the composition of the inserted layer. The proposed structures provide a route to higher efficiency ultraviolet practical light emitting diodes and lasers.

Physics↗

High-throughput spin-bath characterization of spin defects in semiconductors

Detailed knowledge of the local environments of spin defects in semiconductors, such as nitrogenvacancy (NV) centers in diamond or divacancies in silicon carbide, is crucial for optimizing control and entanglement protocols in quantum sensing and information applications. However, at present a direct experimental characterization of individual defect environments is not scalable, as conventional spin-bath measurements are time consuming and difficult to automate. Achieving high-throughput characterization requires short experiments to probe the spin bath. However, with fewer and noisier measurements, the inverse problem of recovering spin-bath properties from measured data becomes ill posed, with multiple spin baths having a high likelihood of yielding the same data. In this work, we present a set of computational tools to resolve the ill-posed inverse problem of recovering the atomic positions and hyperfine couplings of random nuclei surrounding spin defects from sparse, noisy experimental coherence data, which can be obtained in hours. Here, we use a trans-dimensional Bayesian approach that incorporates ab initio data to yield full posterior distributions over nuclear spin environments, enabling robust recovery from limited data. We also provide practical tools and guidelines to determine the limits of detectability for hyperfine couplings under specific dynamical decoupling sequences and sampling conditions. In addition, we demonstrate how the tools developed here, in combination with ab initio simulations of spin baths, can guide the design of efficient experimental protocols for application-specific high-throughput screening. To showcase the utility of our approach, we apply it to design fast dynamical decoupling experiments to characterize the spin baths often individual NV centers in diamond. While the primary focus is on accelerating spin-bath characterization of spin defects, this Bayesian approach also lays the foundation for digital-twin studies of spin defects, where a virtual model of the spin-defect system evolves in real time with ongoing experimental measurements. Together, the set of tools we designed and applied paves the way for scalable deployment of spin defects in semiconductors for quantum sensing and information applications.

Bayesian methods↗

Spin squeezing of macroscopic nuclear spin ensembles

Spin squeezing has been explored in atomic systems as a tool for quantum sensing, improving experimental sensitivity beyond the spin standard quantum limit for certain measurements. To optimize absolute metrological sensitivity, it is beneficial to consider macroscopic spin ensembles, such as nuclear spins in solids and liquids. Coupling a macroscopic spin ensemble to a parametrically-modulated resonant circuit can create collective spin squeezing by generating spin correlations mediated by the circuit. We analyze the squeezing dynamics in the presence of decoherence and finite spin polarization, showing that achieving 7 dB spin squeezing is feasible in several nuclear spin systems. The metrological benefit of squeezing a macroscopic spin ensemble lies in the suppression of technical noise sources in the spin detection system relative to the spin projection noise. This expands the experimental sensitivity bandwidth when searching for signals of unknown frequency and can improve the resonant signal-to-noise ratio. Squeezing macroscopic spin ensembles may prove to be a useful technique for fundamental physics experiments aimed at detecting spin interactions with oscillating background fields, such as ultralight dark matter. Published by the American Physical Society 2025

Boyers, Eric↗

Optimizing the formation of depth-confined nitrogen vacancy center spin ensembles in diamond for quantum sensing

Spin ensembles of nitrogen vacancy (NV) centers in diamond are emerging as powerful spin-based sensors for magnetic, electric and thermal field imaging with high spatial and temporal resolution. In this work, we characterize the formation of depth-confined NV center ensembles, activated by electron irradiation in diamond layers grown by plasma enhanced chemical vapor deposition with nitrogen co-doping. To do so, we exploit the high magnetic sensitivity of ensembles of NV centers to probe their spin environment as a function of growth and irradiation parameters. We engineer an NV ensemble whose magnetic sensitivity is within a factor of two of the static NV-NV dipolar interaction limit, thus demonstrating a powerful platform for quantum sensing.

36 MATERIALS SCIENCE↗