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At least 1,333 records · Page 74

Bilayer Crystals of Trapped Ions for Quantum Information Processing

Trapped-ion systems are a leading platform for quantum information processing, but they are currently limited to 1D and 2D arrays, which imposes restrictions on both their scalability and their range of applications. Here, we propose a path to overcome this limitation by demonstrating that Penning traps can be used to realize remarkably clean bilayer crystals, wherein hundreds of ions self-organize into two well-defined layers. These bilayer crystals are made possible by the inclusion of an anharmonic trapping potential, which is readily implementable with current technology. We study the normal modes of this system and discover salient differences compared to the modes of single-plane crystals. The bilayer geometry and the unique properties of the normal modes open new opportunities—in particular, in quantum sensing and quantum simulation—that are not straightforward in single-plane crystals. Furthermore, we illustrate that it may be possible to extend the ideas presented here to realize multilayer crystals with more than two layers. Our work increases the dimensionality of trapped-ion systems by efficiently utilizing all three spatial dimensions, and it lays the foundation for a new generation of quantum information processing experiments with multilayer 3D crystals of trapped ions. Published by the American Physical Society 2024

Physics↗

On-demand indistinguishable single photons from an efficient and pure source based on a Rydberg ensemble

Single photons coupled to atomic systems have shown to be a promising platform for developing quantum technologies. Yet a bright on-demand, highly pure, and highly indistinguishable single-photon source compatible with atomic platforms is lacking. In this work, we demonstrate such a source based on a strongly interacting Rydberg system. The large optical nonlinearities in a blockaded Rydberg ensemble convert coherent light into a single collective excitation that can be coherently retrieved as a quantum field. We simultaneously observe a fully single-mode (spectral, temporal, spatial, and polarization) efficiency up to 0.098(2), a detector-background-subtracted g ( 2 ) = 5.0 ( 1.6 ) × <#comment/> 10 − <#comment/> 4 , and indistinguishability of 0.980(7), at an average photon production rate of 1.18 ( 2 ) × <#comment/> 10 4 s − <#comment/> 1 . All of these make this system promising for scalable quantum information applications. Furthermore, we investigate the effects of contaminant Rydberg excitations on the source efficiency and observed single-mode efficiencies up to 0.18(2) for lower photon rates. Finally, recognizing that many quantum information protocols require a single photon in a fully single mode, we introduce metrics that take into account all degrees of freedom to benchmark the performance of on-demand sources.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Estimating the randomness of quantum circuit ensembles up to 50 qubits

Random quantum circuits have been utilized in the contexts of quantum supremacy demonstrations, variational quantum algorithms for chemistry and machine learning, and blackhole information. The ability of random circuits to approximate any random unitaries has consequences on their complexity, expressibility, and trainability. To study this property of random circuits, we develop numerical protocols for estimating the frame potential, the distance between a given ensemble and the exact randomness. Our tensor-network-based algorithm has polynomial complexity for shallow circuits and is high-performing using CPU and GPU parallelism. We study 1. local and parallel random circuits to verify the linear growth in complexity as stated by the Brown–Susskind conjecture, and; 2. hardware-efficient ansätze to shed light on its expressibility and the barren plateau problem in the context of variational algorithms. Our work shows that large-scale tensor network simulations could provide important hints toward open problems in quantum information science.

97 MATHEMATICS AND COMPUTING↗

Observable measurement-induced transitions

One of the main postulates of quantum mechanics is that measurements destroy quantum coherence (wave function collapse). Recently it was discovered that in a many-body system dilute local measurements still preserve some coherence across the entire system. As the measurement density is increased, a phase transition occurs that is characterized by the disentanglement of different parts of the system. Unfortunately, this transition is impossible to observe experimentally for macroscopic systems because it requires an exponentially costly full tomography of the many-body wave function or a comparison with the simulation on an oracle classical computer. In this work we report the discovery of another measurement-induced phase transition that can be observed experimentally if quantum dynamics can be reversed. On one side of this phase transition the quantum information encoded in some part of the Hilbert space is fully recovered after the time inversion. On the other side, all quantum information is corrupted. This transition also manifests itself as the change in the behavior of the probability to observe the same measurement outcome in the process that consists of identical blocks repeated many times. In each block the unitary evolution is followed by the measurement. On one side of the transition the probability decreases exponentially with the number of repetitions, on the other it tends to a constant as the number of repetitions is increased. We confirm the existence of the proposed phase transition through numerical simulations of realistic quantum circuits and analytical calculations using an effective random-matrix theory model.

Measurement-induced phase transitions↗

Activating dislocation mediated plasticity in boron carbide through Al-doping

Dislocation slip, deformation twinning, phase transformations, and fast fracture are energy dissipation mechanisms that accommodate mechanical loading in materials. The energetically unfavorable formation of dislocation attributes to the ease of cracking and the low damage tolerance observed in superhard ceramics, notably boron carbide. Here, this work demonstrates that room temperature dislocation slip can be enabled in boron carbide by altering its chemistry through Al doping. The activation of dislocation slip is mechanistically explained by quantum mechanics simulations and electron microscopy, which indicate that strain energy is released through basal icosahedral slip facilitated by icosahedral rotation and chain bond breaking and reconfiguring. The new insight gained through this work suggests that atomic doping could be an effective strategy to tune deformation mechanisms in boron carbide, which provides a significant potential for limiting amorphization and catastrophic failure, and opens a new strategy to enhance damage tolerance in brittle ceramics.

36 MATERIALS SCIENCE↗

Improved Kelbg Potentials for Z > 1 and Application to Carbon Plasmas

In this work, we present a general form for the electron‐ion diffractive potential derived from the quantum pair density matrix and fit to the improved Kelbg potential for atomic numbers up to $Z = 54$. We apply classical molecular dynamics using the improved Kelbg potential for carbon with various forms of the Pauli potential to compute internal energies and pressures for hot, dense plasma conditions. Our results are compared to an equation of state model based on path integral Monte Carlo and density functional theory simulations to examine the extent to which the improved Kelbg potential reproduces the internal energy and pressure of carbon plasmas. The regions of validity for carbon agree generally with those derived previously for hydrogen once pressure ionization effects are incorporated. Based on our carbon results and previously published hydrogen studies, we discuss the general applicability and limitations of these potentials for equation of state studies in warm dense matter and high energy density plasmas.

general physics↗

Physics of the Inverted Harmonic Oscillator: From the lowest Landau level to event horizons

In this work, we present the inverted harmonic oscillator (IHO) Hamiltonian as a paradigm to understand the quantum mechanics of scattering and time-decay in a diverse set of physical systems. As one of the generators of area preserving transformations, the IHO Hamiltonian can be studied as a dilatation generator, squeeze generator, a Lorentz boost generator, or a scattering potential. In establishing these different forms, we demonstrate the physics of the IHO that underlies phenomena as disparate as the Hawking–Unruh effect and scattering in the lowest Landau level (LLL) in quantum Hall systems. We derive the emergence of the IHO Hamiltonian in the LLL in a gauge invariant way and show its exact parallels with the Rindler Hamiltonian that describes quantum mechanics near event horizons. This approach of studying distinct physical systems with symmetries described by isomorphic Lie algebras through the emergent IHO Hamiltonian enables us to reinterpret geometric response in the lowest Landau level in terms of relativistic effects such as Wigner rotation. Further, the analytic scattering matrix of the IHO points to the existence of quasinormal modes (QNMs) in the spectrum, which have quantized time-decay rates. We present a way to access these QNMs through wave packet scattering, thus proposing a novel effect in quantum Hall point contact geometries that parallels those found in black holes.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Bayesian sparse learning with preconditioned stochastic gradient MCMC and its applications

Deep neural networks have been successfully employed in an extensive variety of research areas, including solving partial differential equations. Despite its significant success, there are some challenges in effectively training DNN, such as avoiding overfitting in over-parameterized DNNs and accelerating the optimization in DNNs with pathological curvature. Here, we propose a Bayesian type sparse deep learning algorithm. The algorithm utilizes a set of spike-and-slab priors for the parameters in the deep neural network. The hierarchical Bayesian mixture will be trained using an adaptive empirical method. That is, one will alternatively sample from the posterior using preconditioned stochastic gradient Langevin Dynamics (PSGLD), and optimize the latent variables via stochastic approximation. The sparsity of the network is achieved while optimizing the hyperparameters with adaptive searching and penalizing. A popular SG-MCMC approach is Stochastic gradient Langevin dynamics (SGLD). However, considering the complex geometry in the model parameter space in nonconvex learning, updating parameters using a universal step size in each component as in SGLD may cause slow mixing. To address this issue, we apply a computationally manageable preconditioner in the updating rule, which provides a step-size parameter to adapt to local geometric properties. Moreover, by smoothly optimizing the hyperparameter in the preconditioning matrix, our proposed algorithm ensures a decreasing bias, which is introduced by ignoring the correction term in the preconditioned SGLD. According to the existing theoretical framework, we show that the proposed algorithm can asymptotically converge to the correct distribution with a controllable bias under mild conditions. Numerical tests are performed on both synthetic regression problems and learning solutions of elliptic PDE, which demonstrate the accuracy and efficiency of the present work.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Enhancement of van der Waals Interlayer Coupling through Polar Janus MoSSe

Interlayer coupling plays essential roles in the quantum transport, polaritonic, and electrochemical properties of stacked van der Waals (vdW) materials. In this work, we report the unconventional interlayer coupling in vdW heterostructures (HSs) by utilizing an emerging 2D material, Janus transition metal dichalcogenides (TMDs). In contrast to conventional TMDs, monolayer Janus TMDs have two different chalcogen layers sandwiching the transition metal and thus exhibit broken mirror symmetry and an intrinsic vertical dipole moment. Such a broken symmetry is found to strongly enhance the vdW interlayer coupling by as much as 13.2% when forming MoSSe/MoS 2 HS as compared to the pristine MoS 2 counterparts. Our noncontact ultralow-frequency Raman probe, linear chain model, and density functional theory calculations confirm the enhancement and reveal the origins as charge redistribution in Janus MoSSe and reduced interlayer distance. Furthermore, our results uncover the potential of tuning interlayer coupling strength through Janus heterostacking.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Tunable electron–flexural phonon interaction in graphene heterostructures

Peculiar electron-phonon interaction characteristics underpin the ultrahigh mobility, electron hydrodynamics, superconductivity, and superfluidity observed in graphene heterostructures. Here, the Lorenz ratio (L) between the electronic thermal conductivity and the product of the electrical conductivity and temperature provides unique insight into electron-phonon interactions that is inaccessible to past graphene measurements. Here we show an unusual L peak in degenerate graphene near 60 Kelvin and decreased peak magnitude with increased mobility. When combined with ab initio calculations of the many-body electron-phonon self-energy and analytical models, this experimental observation reveals that broken reflection symmetry in graphene heterostructures can relax a restrictive selection rule to allow quasielastic electron coupling with an odd number of flexural phonons, contributing to the increase of L toward the Sommerfeld limit at an intermediate temperature sandwiched between the low-temperature hydrodynamic regime and the inelastic electron-phonon scattering regime above 120 Kelvin. In contrast to past practices of neglecting flexural phonon contributions to transport in two-dimensional materials, this work suggests that tunable electron-flexural phonon coupling can provide a handle to control quantum matter at the atomic scale, such as magic angle twisted bilayer graphene where low-energy excitations may mediate Cooper pairing of flat-band electrons.

36 MATERIALS SCIENCE↗

Charge density wave and superconductivity in the disordered Holstein model

The interplay between electron-electron correlations and disorder has been a central theme of condensed matter physics over the past several decades, with particular interest in the possibility that interactions might cause delocalization of an Anderson insulator into a metallic state, and the disrupting effects of randomness on magnetic order and the Mott phase. In this work, we extend this physics to explore electron-phonon interactions and show, via exact quantum Monte Carlo simulations, that the suppression of the charge density wave correlations in the half-filled Holstein model by disorder can stabilize a superconducting phase. Our simulations thus capture qualitatively the suppression of charge ordered phases and emergent superconductivity recently seen experimentally.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Temperature Dependence of Charge Distributions and Carrier Mobility in an Undoped Si/SiGe Heterostructure

Capacitance–voltage (C–V ) characteristics and carrier transport properties of 2-D electron gases (2DEGs) in an undoped Si/SiGe heterostructure at T = 4 – 35 K are presented here. In this work, two capacitance plateaus due to density saturation of the 2DEG in the buried Si quantum well (QW) are observed and explained by a model of surface tunneling. The peak mobility at 4 K is 4.1 × 10 5 cm 2 /V·s and enhanced by a factor of 1.97 at an even lower carrier density compared to the saturated carrier density, which is attributed to the effect of remote carrier screening. At T = 35 K, the mobility enhancement with a factor of 1.35 is still observed, which suggests the surface tunneling is still dominant.

42 ENGINEERING↗

Quantum materials for nanosensing and fault-tolerant quantum computing

New concepts of symmetry related to topological order emerged from the discovery of the fractional quantum Hall effect and high-temperature superconductivity in strongly correlated electron systems. This led to the study of quantum materials-- materials exhibiting emergent quantum phenomena with no classical analogues. While these materials have engendered exciting basic materials science and physics, realizing novel devices is a key challenge in the field. The goal of this proposal is to harness the unique properties of topological materials for quantum computing and quantum sensing applications. In this project, we investigated a variety of topological superconducting platforms and identified three technologies that can benefit from their quantum properties: quantum memory, single-photon detection, and non reciprocal electronics. The platforms developed in this work will be broadly useful to National Security and Basic Science.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Background-field Method and QCD Factorization

One method for deriving a factorization for QCD processes is to use successive integration over fields in the functional integral. In this approach, we separate the fields into two categories: dynamical fields with momenta above a relevant cutoff, and background fields with momenta below the cutoff. The dynamical fields are then integrated out in the background of the low-momentum background fields. This strategy works well at tree level, allowing us to quickly derive QCD factorization formulas at leading order. However, to extend the approach to higher loops, it is necessary to rigorously define the functional integral over dynamical fields in an arbitrary background field. This framework was carefully developed for the calculation of the effective action in a background field at the two-loop level in the classic paper by Abbott «The Background Field Method Beyond One Loop», Nucl. Phys. B 185 , 189 (1981). Building on this work, I specify the renormalized background-field Lagrangian and define the notion of the quantum average of an operator in a background field, consistent with the “separation of scales” scheme mentioned earlier. As examples, I discuss the evolution of the twist-2 gluon light-ray operator and the one-loop gluon propagator in a background field near the light cone.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Theoretical and experimental considerations for high silicon solar cell performance

This paper reviews ongoing research aimed at the attainment of highly efficient silicon solar cells. The importance of low-recombination highly-doped n(+) and p(+) regions and the manner in which such regions are fabricated are discussed. Theoretical light-trapping considerations are combined with experimental reflectance data to show that high quantum efficiency may be obtained from thin (100-micron) cells. The principal finding of this work is that thin solar cells with conversion efficiencies of over 20 percent may be fabricated if recombination at the front and back metal/silicon interfaces is reduced. Large-area cells (53 sq cm) with an efficiency of 18 percent are reported.

Spitzer, M. B.↗

Delocalized Excitation Transfer in Open Quantum Systems with Long-Range Interactions

The interplay between coherence and system-environment interactions is at the basis of a wide range of phenomena, from quantum information processing to charge and energy transfer in molecular systems, biomolecules, and photochemical materials. In this work, we use a Frenkel exciton model with long-range interacting qubits coupled to a damped collective bosonic mode to investigate vibrationally assisted transfer processes in donor-acceptor systems featuring internal substructures analogous to light-harvesting complexes. We find that certain delocalized excitonic states maximize the transfer rate and that the entanglement is preserved during the dissipative transfer over a wide range of parameters. We investigate the reduction in transfer caused by static disorder, white noise, and finite temperature and study how transfer efficiency scales as a function of the number of dimerized monomers and the component number of each monomer, finding which excitonic states lead to optimal transfer. Finally, we provide a realistic experimental setting to realize this model in analog trapped-ion quantum simulators. Analog quantum simulation of systems comprising many and increasingly complex monomers could offer valuable insights into the design of light-harvesting materials, particularly in the nonperturbative intermediate parameter regime examined in this study, where classical simulation methods are resource intensive.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Near-field probing of strong light-matter coupling in single IR antennae

Quantum well intersubband polaritons are traditionally studied in large scale ensembles, over many wavelengths in size.In this presentation, we demonstrate that it is possible to detect and investigate intersubband polaritons in a single sub-wavelength nanoantenna in the IR frequency range. We observe polariton formation using a scattering-type near-fieldmicroscope and nano-FTIR spectroscopy. In this work, we will discuss near-field spectroscopic signatures of plasmonic antennae withand without coupling to the intersubband transition in quantum wells located underneath the antenna. Evanescent fieldamplitude spectra recorded on the antenna surface show a mode anti-crossing behavior in the strong coupling case. Wealso observe a corresponding strong-coupling signature in the phase of the detected field. We anticipate that this near-fieldapproach will enable explorations of strong and ultrastrong light-matter coupling in the single nanoantenna regime,including investigations of the elusive effect of ISB polariton condensation.

36 MATERIALS SCIENCE↗

Adiabatic quantum linear regression

Abstract A major challenge in machine learning is the computational expense of training these models. Model training can be viewed as a form of optimization used to fit a machine learning model to a set of data, which can take up significant amount of time on classical computers. Adiabatic quantum computers have been shown to excel at solving optimization problems, and therefore, we believe, present a promising alternative to improve machine learning training times. In this paper, we present an adiabatic quantum computing approach for training a linear regression model. In order to do this, we formulate the regression problem as a quadratic unconstrained binary optimization (QUBO) problem. We analyze our quantum approach theoretically, test it on the D-Wave adiabatic quantum computer and compare its performance to a classical approach that uses the Scikit-learn library in Python. Our analysis shows that the quantum approach attains up to $${2.8 \times }$$ 2.8 × speedup over the classical approach on larger datasets, and performs at par with the classical approach on the regression error metric. The quantum approach used the D-Wave 2000Q adiabatic quantum computer, whereas the classical approach used a desktop workstation with an 8-core Intel i9 processor. As such, the results obtained in this work must be interpreted within the context of the specific hardware and software implementations of these machines.

97 MATHEMATICS AND COMPUTING↗