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At least 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

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↗
DOE OSTI2024

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↗
DOE OSTI2025

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)↗
DOE OSTI2024

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↗
DOE OSTI2022

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↗
DOE OSTI2021

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↗
DOE OSTI2022

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↗
DOE OSTI2023

Quantum-enhanced Imaging and Spectroscopy and their Relevance to International Safeguards

As a follow-up to our previous report on quantum sensing for safeguards, here we delve deeper into quantum-enhanced imaging & spectroscopy and address their relevance to international safeguards. Much of the approaches rely on entangled photons, a quantum phenomenon not possible with classical physics, although just correlated photons will work for some applications, such as ghost imaging. We provide a comprehensive survey of quantum approaches, including multiple entangled photon ghost imaging and spectroscopy techniques. Entangled photons for noise reduction are also described, as well as Non-Line-Of-Sight imaging, compressive techniques, and squeezed light. Of particular interest is the generation of entangled photons with large wavelength separation, such as infrared/visible entangled photon pairs. Such entangled pairs would allow interaction with objects in the IR, such as in the molecular “fingerprint” wavelength region, while the recording device captures the visible photons, thus leveraging the high efficiency and lower cost of visible detectors. Unfortunately, entangled x-ray photons are not practical, which would have been useful for safeguards to interrogate shielded materials. Entangled gamma rays are even further beyond reason. We provide our assessment for application of quantum-enhanced imaging & spectroscopy for international safeguards, including suggested improvements to existing IAEA instruments and destructive assay measurements that are done at IAEA lab facilities.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Space Charge Simulations of High Intensity Proton Beams in the AGS Booster

Computer simulation studies have been performed to understand the beam behavior and to explore intensity limitations of proton beams in the AGS Booster at higher beam intensities. During the 100 GeV polarized proton operations of RHIC Run 2024, sPHENIX operated in modes with a crossing angle at collisions in order to mitigate beam-beam effects. Three different running modes were employed: (a) sPHENIX operated with a negative (-2 mrad) crossing angle, and STAR operated with 0 mrad. Both experiments were brought into collisions at the start of the store. (b) sPHENIX was brought into collisions with 0 mrad first. Then STAR was brought into collisions after the beam-beam parameter from sPHENIX reduced to below $10 \times 10^{-3}$. (c) sPHENIX operated with a positive (+1.5 mrad) crossing angle, and STAR operated with 0 mrad. Both experiments were brought into collisions at the start of the store. The collisions with a crossing angle of up to $\pm 2$ mrad, as in running modes (a) and (c), lead to large Piwinski angle in the new sPHENIX detector, which reduces luminosity if other parameters are unchanged. There are two ways to compensate the reduction in luminosity: squeeze $\beta^{*}$ if there is sufficient dynamic aperture, or increase the injected beam intensity. The first part of polarized proton operation during RHIC Run 2024 was dedicated to increasing the intensity. Different configurations were tested with crossing angle and lattice adjustments on RHIC. At the same time, new injector configurations were developed and tested in an effort to push for both higher intensity and better quality of the beam injected into RHIC. When the beam intensity is increased, space charge is a concern particularly in the lower energy stages of acceleration, such as during the injection and the early part of the Booster cycle, which could become a dominant effect in limiting the intensity of the beam that can be delivered to RHIC.

43 PARTICLE ACCELERATORS↗
DOE OSTI2026

Precision spectroscopy of nuclear decays using quantum optomechanical sensors

This project developed and demonstrated a fundamentally new way to detect individual nuclear decays: rather than capturing the energy that decay products deposit in a detector, we measure the tiny mechanical recoil of the entire micron- or nanometer-sized particle in which the decaying nucleus is embedded. Because momentum is conserved, this approach is sensitive even to neutral, weakly interacting particles, including neutrinos, that escape conventional detectors. During the award, the Yale group reported the first-ever mechanical detection of single nuclear decays, a result featured widely in the scientific press, and pushed the sensitivity of smaller levitated nanoparticles into the quantum measurement regime, reaching an impulse resolution within a factor of five of the fundamental Standard Quantum Limit (SQL), good enough in principle to detect the momentum kicked to the particle by a single emitted neutrino. In parallel, the LBNL group developed the theory of quantum-enhanced (sub-SQL) readout tailored to this experiment, showing how squeezed light can push the sensitivity below the SQL. Together these results establish levitated optomechanical sensors as a new tool for precision nuclear decay spectroscopy, with further applications in neutrino physics, quantum metrology, and nuclear forensics and safeguards.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

Nonadiabatic Energy Fluctuations of Scale-Invariant Quantum Systems in a Time-Dependent Trap

We consider the nonadiabatic energy fluctuations of a many-body system in a time-dependent harmonic trap. In the presence of scale-invariance, the dynamics becomes self-similar and the nondiabatic energy fluctuations can be found in terms of the initial expectation values of the second moments of the Hamiltonian, square position, and squeezing operators. Nonadiabatic features are expressed in terms of the scaling factor governing the size of the atomic cloud, which can be extracted from time-of-flight images. We apply this exact relation to a number of examples: the single-particle harmonic oscillator, the one-dimensional Calogero-Sutherland model, describing bosons with inverse-square interactions that includes the non-interacting Bose gas and the Tonks-Girdardeau gas as limiting cases, and the unitary Fermi gas. We illustrate these results for various expansion protocols involving sudden quenches of the trap frequency, linear ramps and shortcuts to adiabaticity. Our results pave the way to the experimental study of nonadiabatic energy fluctuations in driven quantum fluids.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Real Space and Time Imaging of Collective Headgroup Dipole Motions in Zwitterionic Lipid Bilayers

Lipid bilayers are supramolecular structures responsible for a range of processes, such as transmembrane transport of ions and solutes, and sorting and replication of genetic materials, to name just a few. Some of these processes are transient and currently, cannot be visualized in real space and time. Here, we developed an approach using 1D, 2D, and 3D Van Hove correlation functions to image collective headgroup dipole motions in zwitterionic phospholipid bilayers. We show that both 2D and 3D spatiotemporal images of headgroup dipoles are consistent with commonly understood dynamic features of fluids. However, analysis of the 1D Van Hove function reveals lateral transient and re-emergent collective dynamics of the headgroup dipoles—occurring at picosecond time scales—that transmit and dissipate heat at longer times, due to relaxation processes. At the same time, the headgroup dipoles also generate membrane surface undulations due a collective tilting of the headgroup dipoles. A continuous intensity band of headgroup dipole spatiotemporal correlations—at nanometer length and nanosecond time scales—indicates that dipoles undergo stretching and squeezing elastic deformations. Importantly, the above mentioned intrinsic headgroup dipole motions can be externally stimulated at GHz-frequency scale, enhancing their flexoelectric and piezoelectric capabilities (i.e., increased conversion efficiency of mechanical energy into electric energy). In conclusion, we discuss how lipid membranes can provide molecular-level insights about biological learning and memory, and as platforms for the development of the next generation of neuromorphic computers.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Searching for Interstellar Quantum Communications

The modern search for extraterrestrial intelligence began with the seminal publications of Cocconi & Morrison and Schwartz & Townes, who proposed searching for narrowband signals in the radio spectrum and optical laser pulses. Over the last six decades, more than 100 dedicated search programs have targeted these wavelengths, all with null results. All of these campaigns searched for classical communications, that is, for a significant number of photons above a noise threshold, with the assumption of a pattern encoded in time and/or frequency space. I argue that future searches should also target quantum communications. They are preferred over classical communications with regard to security and information efficiency, and they would have escaped detection in all previous searches. The measurement of Fock state photons or squeezed light would indicate the artificiality of a signal. I show that quantum coherence is feasible over interstellar distances and explain for the first time how astronomers can search for quantum transmissions sent by ETI to Earth using commercially available telescopes and receiver equipment.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Ab-initio General-relativistic Neutrino-radiation Hydrodynamics Simulations of Long-lived Neutron Star Merger Remnants to Neutrino Cooling Timescales

Abstract We perform the first 3D ab-initio general-relativistic neutrino-radiation hydrodynamics of a long-lived neutron star merger remnant spanning a fraction of its cooling timescale. We find that neutrino cooling becomes the dominant energy loss mechanism after the gravitational-wave dominated phase (∼20 ms postmerger). Electron flavor antineutrino luminosity dominates over electron flavor neutrino luminosity at early times, resulting in a secular increase of the electron fraction in the outer layers of the remnant. However, the two luminosities become comparable ∼20–40 ms postmerger. A dense gas of electron antineutrinos is formed in the outer core of the remnant at densities ∼10 14.5 g cm −3 , corresponding to temperature hot spots. The neutrinos account for ∼10% of the lepton number in this region. Despite the negative radial temperature gradient, the radial entropy gradient remains positive, and the remnant is stably stratified according to the Ledoux criterion for convection. A massive accretion disk is formed from the material squeezed out of the collisional interface between the stars. The disk carries a large fraction of the angular momentum of the system, allowing the remnant massive neutron star to settle to a quasi-steady equilibrium within the region of possible, stable, rigidly rotating configurations. The remnant is differentially rotating, but it is stable against the magnetorotational instability. Other MHD mechanisms operating on longer timescales are likely responsible for the removal of the differential rotation. Our results indicate the remnant massive neutron star is thus qualitatively different from a protoneutron stars formed in core-collapse supernovae.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Probing for Artifacts: Detecting Imagenet Model Evasions

While deep learning models have made incredible progress across a variety of machine learning tasks, they remain vulnerable to adversarial examples crafted to fool otherwise trustworthy models. In this work we approach this problem through the lens of a detection framework. We propose a classification network that uses the hidden layer activations of a trained model as inputs to detect adversarial artifacts in an input. We train this classification network simultaneously against multiple adversarial algorithms to create a more robust detector and show higher detection rates than several alternatives. The novelty of our approach is in the scale and scope of probing Imagenet models for adversarial artifacts. In addition, we propose an improvement to feature squeezing, another common adversarial example detection method.

Rounds, Jeremiah↗
DOE OSTI2020

Systematic Evaluation of Backdoor Data Poisoning Attacks on Image Classifiers

Backdoor data poisoning attacks have recently been demonstrated in computer vision research as a potential safety risk for machine learning (ML) systems. Traditional data poisoning attacks manipulate training data to induce unreliability of an ML model, whereas backdoor data poisoning attacks maintain system performance unless the MLmodel is presented with an input containing an embedded“trigger” that provides a predetermined response advantageous to the adversary. Our work builds upon prior back-door data-poisoning research for ML image classifiers and systematically assesses different experimental conditions including types of trigger patterns, persistence of trigger patterns during retraining, poisoning strategies, architectures (ResNet-50, NasNet, NasNet-Mobile), datasets (Flowers, CIFAR-10), and potential defensive regularization techniques (Contrastive Loss, Logit Squeezing, Manifold Mixup,Soft-Nearest-Neighbors Loss). Experiments yield four key findings. First, the success rate of backdoor poisoning at-tacks varies widely, depending on several factors, including model architecture, trigger pattern and regularization technique. Second, we find that poisoned models are hard to detect through performance inspection alone. Third, regularization typically reduces backdoor success rate, although it can have no effect or even slightly increase it, depending on the form of regularization. Finally, backdoors inserted through data poisoning can be rendered ineffective after just a few epochs of additional training on a small set of clean data without affecting the model’s performance.

Truong, Loc T.↗