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At least 469 records · Page 26

Testbed and Experiments for Quantum-Conventional Networking

The realization of quantum networks requires the development of devices and methods unprecedented in conventional networks, and yet they critically depend on the latter for implementing foundational blocks and essential operations. We describe a testbed to support the development and testing of their functionality and performance by providing quantum and conventional data planes and devices, together with a secure conventional control plane. It incorporates a variety of entangled photon sources, qubit technologies, detector technologies, photonic components, and supporting conventional switches and workstations. It implements a novel fiber telescoping scheme that provides suites of connections using fiber spools and inground-aerial fiber loops. We briefly summarize a variety of experiments conducted over this testbed including: (i) flex-grid quantum connection experiments, (ii) quantum state and channel tomography, (iii) utilization of quantum key distribution keys to secure conventional encryption and firewall devices, (iv) comparative study of analytical capacity estimates and entanglement throughput, (v) deployed squeezing coexisting with conventional communications, and (iv) measurement of polarization time variation.

Rao, Nageswara [ORNL] (ORCID:0000000234085941)↗

Additively Manufactured Compliant Hybrid Gas Thrust Bearing for Supercritical Carbon Dioxide Turbomachinery: Experimental Evaluation and Fluid–Structure Model Predictions

This paper presents rotating test results and advances an analytical predictive fluid–structure model for a new type of gas-lubricated thrust bearing fabricated using direct metal laser melting. The bearing concept in this study is a compliant hybrid gas thrust bearing that uses external pressurization to increase load carrying capacity, where the testing campaign in this study was only focused on steady-state static performance. The need for the bearing concept comes from enabling highly efficient supercritical carbon dioxide (sCO2) turbomachinery by replacing oil-lubricated bearings with process gas lubrication. Leveraging the process gas of the turbomachine for bearing lubrication results in lowered bearing power loss, simplified mechanical design, and allows for novel oil-free hermetic drivetrains resulting in an efficient emission-free system. The new concept utilizes hydrostatic pressurization on individual tilting pads flexibly mounted with hermetic squeeze film dampers (HSFDs). This paper focuses on rotating tests of a 173 mm outer diameter gas thrust bearing in air up to 10 krpm and hydrostatic inlet pressures to 365 psi (2.52 MPa). The influence of thrust runner speed and bearing inlet pressure on force deflection characteristics and load carrying capability of the gas film were experimentally evaluated. This work also advances a predictive fluid–structure thrust bearing model using an isothermal ideal-gas-based compressible Reynolds flow equation directly coupled to a lumped stiffness element possessing axial and rotational degrees-of-freedom. The rotating testing demonstrated load capability of 1816 lbs (8.1 kN), which equates to a thrust bearing unit load of 67 psi (0.46 MPa). Gas film force–deflection curves reveal a nonlinear relationship between thrust load and film clearance. Comparison of film thickness values with the predictive model show good agreement under high load and inlet pressure, however deviate as load and pressure decrease. Load capability was shown to increase with increasing hydrostatic inlet pressure, while the increase in thrust runner speed revealed a small decrease in load capacity.

Engineering↗

Additively Manufactured Compliant Hybrid Gas Thrust Bearing for Supercritical Carbon Dioxide Turbomachinery: Design and Proof of Concept Testing

The following paper presents a new type of gas lubricated thrust bearing that utilizes additive manufacturing or also known as direct metal laser melting (DMLM) to fabricate the bearing. The motivation for the new bearing concept is derived from the need for highly efficient supercritical carbon dioxide (sCO2) turbomachinery in the mega-watt power range. The paper provides a review of existing gas thrust-bearing technology, outlines the need for the new DMLM concept, and discusses proof-of-concept testing results. The new concept combines hydrostatic pressurization with individual tilting pads that are flexibly mounted using hermetic squeeze film dampers (HSFD) in the bearing-pad support. This paper describes the thrust-bearing concept and discusses the final design approach. Proof-of-concept testing in air for a 6.8 in. (173 mm) outer diameter thrust gas bearing was performed; with thrust loading, up to 1500 lbs (6.67 kN) and a thrust runner speed of 10krpm (91 m/s tip speed). The experiments were performed with a bent shaft resulting in thrust runner axial vibration magnitudes of 2.9 mils (74 μm) p-p and dynamic thrust loads of 270 lbs (1.2 kN) p-p. In addition, force deflection characteristics and stiffness coefficients of the bearing system are presented for an inlet hydrostatic pressure of 380 psi (2.62 MPa). Results at 10 krpm show that the pad support architecture was able to sustain high levels of dynamic misalignment equaling 6 times the nominal film clearance while demonstrating a unit load-carrying capacity of 55 psi (0.34 Mpa). Gas-film force deflection tests portrayed nonlinear behavior like a hardening spring, while the bearing pad support stiffness was measured to be linear and independent of gas film thickness.

Engineering↗

Observation of the magnonic Dicke superradiant phase transition

Two-level atoms ultrastrongly coupled with single-mode cavity photons are predicted to exhibit a quantum phase transition, entering a phase in which both the atomic polarization and the photonic field are finite even without external driving. However, this phenomenon, the superradiant phase transition (SRPT), is forbidden by a no-go theorem due to the existence of the diamagnetic term. Here, we present spectroscopic evidence for a magnonic SRPT in ErFeO 3 , where the role of the photonic mode (two-level atoms) in the photonic SRPT is played by an Fe 3+ magnon mode (Er 3+ spins). The absence of the diamagnetic term in the Fe 3+ -Er 3+ exchange coupling ensures that the no-go theorem does not apply. Ultrabroadband terahertz and gigahertz magnetospectroscopy experiments revealed the signatures of the SRPT in thermal equilibrium, a kink and a softening, respectively, of two spin-magnon hybridized modes at the critical point. Systems near this phase are expected to harbor large-scale squeezing, which will potentially provide a route to next-generation quantum technologies.

74 ATOMIC AND MOLECULAR PHYSICS↗

The noise of gravitons

We show that when the gravitational field is treated quantum-mechanically, it induces fluctuations — noise — in the lengths of the arms of gravitational wave detectors. Here, the characteristics of the noise depend on the quantum state of the gravitational field and can be calculated exactly in several interesting cases. For coherent states, the noise is very small, but it can be greatly enhanced in thermal and (especially) squeezed states. Detection of this fundamental noise would constitute direct evidence for the quantization of gravity and the existence of gravitons.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Chiral catalysis of nuclear fusion in molecules

At low energies, nuclear fusion is strongly affected by electron screening of the Coulomb repulsion among the fusing nuclei. It may thus be possible to catalyze nuclear fusion in molecules (i.e., to fuse specific nuclei in situ) through quantum control of electron wave functions in intense laser fields. The circularly polarized (chiral) laser field can effectively squeeze the electron wave functions, greatly enhancing the screening in the spatial region relevant for the fusion process. Here, we estimate the corresponding fusion probabilities, and find that the proposed chiral catalysis of nuclear fusion in molecules may be observable, potentially with important practical applications.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

A Power-Law Decrease in Interfacial Resistance Between Li 7 La 3 Zr 2 O 12 and Lithium Metal After Removing Stack Pressure

The high interfacial resistance between solid electrolytes and lithium metal is a hurdle to developing all solid-state batteries. External pressure applied on the lithium and solid electrolyte interface prior to electrochemical cycling is known to effectively lower the interfacial resistance. Here we report that the interfacial resistance between Li 6.4 La 3 Zr 1.4 Ta 0.6 O 12 (LLZTO) and lithium metal decreases over time even after removing the external pressure. The irreversible decrease of interfacial resistance can be understood by a gradual reduction of the total energy of the system, including strain energy and interfacial energy. Under external pressure exceeding ~25 MPa, however, lithium can be squeezed into LLZTO, fracturing the ceramic solid electrolyte. As a result, these observations can help improve the understanding of lithium metal creep and the interactions between garnet-type solid electrolytes and lithium metal.

25 ENERGY STORAGE↗

risingMicrobubbleLattice

This code is a simulation case to be run with OpenFOAM, an open-source computational fluid dynamics software. A gmsh mesh file is also included. Specifically, this simulation demonstrates the transport of a single microbubble rising through an ordered lattice due to an applied flow. The bubble deforms as it squeezes through the pores of the lattice. Is

Guo, Jack [Lawrence Livermore National Laboratory ↗

DISTEMA: distance map-based estimation of single protein model accuracy with attentive 2D convolutional neural network

Abstract Background Estimation of the accuracy (quality) of protein structural models is important for both prediction and use of protein structural models. Deep learning methods have been used to integrate protein structure features to predict the quality of protein models. Inter-residue distances are key information for predicting protein’s tertiary structures and therefore have good potentials to predict the quality of protein structural models. However, few methods have been developed to fully take advantage of predicted inter-residue distance maps to estimate the accuracy of a single protein structural model. Result We developed an attentive 2D convolutional neural network (CNN) with channel-wise attention to take only a raw difference map between the inter-residue distance map calculated from a single protein model and the distance map predicted from the protein sequence as input to predict the quality of the model. The network comprises multiple convolutional layers, batch normalization layers, dense layers, and Squeeze-and-Excitation blocks with attention to automatically extract features relevant to protein model quality from the raw input without using any expert-curated features. We evaluated DISTEMA’s capability of selecting the best models for CASP13 targets in terms of ranking loss of GDT-TS score. The ranking loss of DISTEMA is 0.079, lower than several state-of-the-art single-model quality assessment methods. Conclusion This work demonstrates that using raw inter-residue distance information with deep learning can predict the quality of protein structural models reasonably well. DISTEMA is freely at https://github.com/jianlin-cheng/DISTEMA

59 BASIC BIOLOGICAL SCIENCES↗

Spatially Multiplexed Cluster State Generation

We demonstrate the use of spatially multimode two-mode squeezed states (TMSSs) interfered at beamsplitters to generate an arbitrarily large cluster state. A four-mode state is generated using two TMSSs, leveraging spatial modes of four-wave mixing.

Leger, Zacharie [ORNL] (ORCID:0000000179044775)↗

Realistic model of entanglement-enhanced sensing in optical fibers

Experimental limitations such as optical loss and noise have prevented entanglement-enhanced measurements from demonstrating a significant quantum advantage in sensitivity. Holland-Burnett entangled states can mitigate these limitations and still present a quantum advantage in sensitivity. Here we model a fiber-based Mach-Zehnder interferometer with internal loss, detector efficiency, and external phase noise and without pure entanglement. This model features a practical fiber source that transforms the two-mode squeezed vacuum (TMSV) into Holland-Burnett entangled states. We predict that a phase sensitivity 28% beyond the shot noise limit is feasible with current technology. Simultaneously, a TMSV source can provide about 25 times more photon flux than other entangled sources. This system will make fiber-based quantum-enhanced sensing accessible and practical for remote sensing and probing photosensitive materials.

Krueper, Gregory↗

Overcoming the fundamental limit of quantum transduction via intraband entanglement

A quantum transducer converts an input signal to an output probe at a distant frequency band while maintaining the quantum information with high fidelity, which is crucial for quantum networking and distributed quantum sensing and computing. In terms of microwave–optical quantum transduction, the state-of-the-art quantum transducers suffer low transduction efficiency from weak nonlinear coupling, wherein increasing pump power to enhance efficiency inevitably leads to thermal noise from heating. Moreover, we reveal that the efficiency-bandwidth product of a cavity electro-optical or electro-optomechanical transducer is fundamentally limited by pump power and nonlinear coupling coefficient, irrespective of cavity engineering efforts. To overcome this fundamental limit, we propose to noiselessly boost the transduction efficiency by consuming intraband entanglement (e.g., microwave–microwave or optical–optical entanglement in the case of microwave–optical transduction). Via a squeezer–coupler–antisqueezer sandwich structure, the protocol enhances the transduction efficiency to unity in the ideal lossless case, given an arbitrarily weak pump and nonlinear coupling. In practical cavity systems, our entanglement-assisted protocol surpasses the non-assisted fundamental limit of the efficiency-bandwidth product and reduces the threshold cooperativity for positive quantum capacity by a factor proportional to two-mode squeezing gain. Given a fixed cooperativity, our approach increases the broadband quantum capacity by orders of magnitude. The entanglement-assisted advantage is robust to ancilla loss and cavity detuning.

Shi, Haowei [Southern California U.] (ORCID:000000↗

Towards Cluster State Generation with Spatial Modes

We leverage spatial modes to generate multipartite entangled states in a cross-coupled SU(1,1) interferometer with intensity-difference squeezing of 4.2 dB. Theoretical analysis shows that the generated state can be converted to a cluster state.

Leger, Zacharie [ORNL] (ORCID:0000000179044775)↗

Bayesian optimization of Fisher Information in nonlinear multiresonant quantum photonics gyroscopes

Abstract We propose an on-chip gyroscope based on nonlinear multiresonant optics in a thin film χ (2) resonator that combines high sensitivity, compact form factor, and low power consumption simultaneously. We theoretically analyze a novel holistic metric – Fisher Information capacity of a multiresonant nonlinear photonic cavity – to fully characterize the sensitivity of our gyroscope under fundamental quantum noise conditions. Leveraging Bayesian optimization techniques, we directly maximize the nonlinear multiresonant Fisher Information. Our holistic optimization approach orchestrates a harmonious convergence of multiple physical phenomena – including noise squeezing, nonlinear wave mixing, nonlinear critical coupling, and noninertial signals – all encapsulated within a single sensor-resonator, thereby significantly augmenting sensitivity. We show that ∼ 470 × $\sim 470{\times}$ improvement is possible over the shot-noise limited linear gyroscope with the same footprint, intrinsic quality factors, and power budget.

42 ENGINEERING↗

Optimization of Water-Alternating-CO2 Injection Field Operations Using a Machine-Learning-Assisted Workflow

Summary This paper will present a robust workflow to address multiobjective optimization (MOO) of carbon dioxide (CO2)-enhanced oil recovery (EOR)-sequestration projects with a large number of operational control parameters. Farnsworth unit (FWU) field, a mature oil reservoir undergoing CO2 alternating water injection (CO2-WAG) EOR, will be used as a field case to validate the proposed optimization protocol. The expected outcome of this work would be a repository of Pareto-optimal solutions of multiple objective functions, including oil recovery, carbon storage volume, and project economics. FWU’s numerical model is used to demonstrate the proposed optimization workflow. Because using MOO requires computationally intensive procedures, machine-learning-based proxies are introduced to substitute for the high-fidelity model, thus reducing the total computation overhead. The vector machine regression combined with the Gaussian kernel (Gaussian-SVR) is used to construct proxies. An iterative self-adjusting process prepares the training knowledge base to develop robust proxies and minimizes computational time. The proxies’ hyperparameters will be optimally designed using Bayesian optimization to achieve better generalization performance. Trained proxies will be coupled with multiobjective particle swarm Optimization (MOPSO) protocol to construct the Pareto-front solution repository. The outcomes of this workflow will be a repository containing Pareto-optimal solutions of multiple objectives considered in the CO2-WAG project. The proposed optimization workflow will be compared with another established methodology using a multilayer neural network (MLNN) to validate its feasibility in handling MOO with a large number of parameters to control. Optimization parameters used include operational variables that might be used to control the CO2-WAG process, such as the duration of the water/gas injection period, producer bottomhole pressure (BHP) control, and water injection rate of each well included in the numerical model. It is proved that the workflow coupling Gaussian-SVR proxies and the iterative self-adjusting protocol is more computationally efficient. The MOO process is made more rapid by squeezing the size of the required training knowledge base while maintaining the high accuracy of the optimized results. The outcomes of the optimization study show promising results in successfully establishing the solution repository considering multiple objective functions. Results are also verified by validating the Pareto fronts with simulation results using obtained optimized control parameters. The outcome from this work could provide field operators an opportunity to design a CO2-WAG project using as many inputs as possible from the reservoir models. The proposed work introduces a novel concept that couples Gaussian-SVR proxies with a self-adjusting protocol to increase the computational efficiency of the proposed workflow and to guarantee the high accuracy of the obtained optimized results. More importantly, the workflow can optimize a large number of control parameters used in a complex CO2-WAG process, which greatly extends its utility in solving large-scale MOO problems in various projects with similar desired outcomes.

Energy & Fuels↗

Stroboscopic aliasing in long-range interacting quantum systems

We unveil a mechanism for generating oscillations with arbitrary multiplets of the period of a given external drive, in long-range interacting quantum many-particle spin systems. These oscillations break discrete time translation symmetry as in time crystals, but they are understood via two intertwined stroboscopic effects similar to the aliasing resulting from video taping a single fast rotating helicopter blade. The first effect is similar to a single blade appearing as multiple blades due to a frame rate that is in resonance with the frequency of the helicopter blades' rotation; the second is akin to the optical appearance of the helicopter blades moving in reverse direction. Analogously to other dynamically stabilized states in interacting quantum many-body systems, this stroboscopic aliasing is robust to detuning and excursions from a chosen set of driving parameters, and it offers a novel route for engineering dynamical n-tuplets in long-range quantum simulators, with potential applications to spin squeezing generation and entangled state preparation.

Kelly, Shane↗

Quantum enhanced metrology in the search for fundamental physical phenomena

These notes summarize lectures given at the 2019 Les Houches summer school on Quantum Information Machines. They describe and review an application of quantum metrology concepts to searches for ultralight dark matter. In particular, for ultralight dark matter that couples as a weak classical force to a laboratory harmonic oscillator, quantum squeezing benefits experiments in which the mass of the dark matter particle is unknown. This benefit is present even if the oscillatory dark matter signal is much more coherent than the harmonic oscillator that it couples to, as is the case for microwave frequency searches for dark matter axion particles.

Lehnert, Konrad↗