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At least 1,639 records · Page 91

Data transmission by quantum matter wave modulation

Abstract Classical communication schemes exploiting wave modulation are the basis of our information era. Quantum information techniques with photons enable future secure data transfer in the dawn of decoding quantum computers. Here we demonstrate that also matter waves can be applied for secure data transfer. Our technique allows the transmission of a message by a quantum modulation of coherent electrons in a biprism interferometer. The data is encoded in the superposition state by a Wien filter introducing a longitudinal shift between separated matter wave packets. The transmission receiver is a delay line detector performing a dynamic contrast analysis of the fringe pattern. Our method relies on the Aharonov–Bohm effect but does not shift the phase. It is demonstrated that an eavesdropping attack will terminate the data transfer by disturbing the quantum state and introducing decoherence. Furthermore, we discuss the security limitations of the scheme due to the multi-particle aspect and propose the implementation of a key distribution protocol that can prevent active eavesdropping.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Robust and ultrafast state preparation by ramping artificial gauge potentials

Abstract The implementation of static artificial magnetic fields in ultracold atomic systems has become a powerful tool, e.g. for simulating quantum-Hall physics with charge-neutral atoms. Taking an interacting bosonic flux ladder as a minimal model, we investigate protocols for adiabatic state preparation via magnetic flux ramps. Considering the fact that it is actually the artificial vector potential (in the form of Peierls phases) that can be experimentally engineered in optical lattices, rather than the magnetic field, we find that the time required for adiabatic state preparation dramatically depends on which pattern of Peierls phases is used. This can be understood intuitively by noting that different patterns of time-dependent Peierls phases that all give rise to the same magnetic field ramp, generally lead to different artificial electric fields during the ramp. As an intriguing result, we find that an optimal choice allows for preparing the ground state almost instantaneously in the non-interacting system, which can be related to the concept of counterdiabatic driving. Remarkably, we find extremely short preparation times also in the strongly-interacting regime. Our findings open new possibilities for robust state preparation in atomic quantum simulators.

Wang, Botao (ORCID:0000000282202452)↗

Engineering long-lived entanglement through dissipation in quantum hybrid solid-state platforms

Spin squeezing, a form of many-body entanglement, is a crucial resource in quantum metrology and information processing. While experimentally viable protocols for generating stable spin squeezing have been proposed in quantum optics setups, there is growing interest in quantum hybrid solid-state systems as alternative platforms for both engineering and exploring many-body quantum phenomena. In this work, we propose a scheme to generate long-lived spin squeezing in an ensemble of solid-state qubits interacting with electromagnetic noise emitted by a squeezed solid-state bath. We identify the conditions under which quantum correlations within the bath can be transferred to the qubit array, driving it into an entangled state independently of its initial configuration. To assess the experimental feasibility of our approach, we analyze the dynamics of an array of solid-state spin defects coupled to a common ferromagnetic bath, which is driven into a non-equilibrium squeezed state through its interaction with a surface acoustic wave mode. Our results demonstrate that the ensemble can exhibit steady-state spin squeezing under suitable conditions, opening new pathways for the generation of robust many-body entanglement in solid-state spin ensembles.

NV centers↗

Development and experimental qualification of novel disruption prevention techniques on DIII-D

Novel disruption prevention solutions spanning a range of control regimes are being developed and tested on DIII-D to enable ITER success. First, a new real-time control algorithm has been developed and tested for regulating nearness to stability limits and maintaining safety-margins. Its first application has been for reliable prevention of vertical displacement events (VDEs) by adjusting plasma elongation (κ) and the inner-gap between the plasma and inner-wall in response to real- time open-loop VDE growth rate (γ) estimators. VDEs were robustly prevented up to average open-loop growth rates of 800 rad/s with initial tunings, with only applying shape modification when near safety limits. Second, the disruption risk during fast, emergency shutdown after large tearing and locked modes can be significantly improved by transitioning to a limited topology during shutdown. More than 50% of emergency limited shutdowns after locked modes reach a final normalized current I_N < 0.3 before terminating, scaling to the 3 MA ITER requirement. Furthermore, this is in contrast to diverted shutdowns, the majority of which disrupt at I_N > 0.8. Despite improvements, these results highlight the critical importance of early prevention. Third, a novel emergency shut down method has been developed which excites instabilities to form a warm, helical core post-thermal quench. The current quench extends to ~100ms and avoids VDEs and runaway electron generation. Novel real-time machine learning disruption prediction has been integrated with the DIII-D proximity controller, and a real- time compatible multi-mode MHD spectroscopy technique has been developed. Results presented here were enabled by a focused effort, the Disruption Free Protocol, in DIII-D’s 2019-20 campaign to complement disruption prevention experiments with a large piggy-back program. In addition to testing novel techniques, it is estimated to have helped avoid 32 potential disruptions in piggyback operations with rapid, early shutdowns after large rotating n=1 or locked modes.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Flexible visualization of a 3rd party Intrusion Prevention (Security) tool: A use case with the ELK stack

A difficult aspect of cyber security is the ability to achieve automated real time intrusion prevention across various sets of systems. To this extent, several companies are offering comprehensive solutions that leverage an "accuracy of scale" and moving much of the intelligence and detection on the Cloud, relying on an ever-growing set of data and analytics to increase decision accuracy. Often, they provide tools to visualize the decision workflows in attack prevention (as well as tune the algorithm) but those solutions are not always practical as companies see the problem as "global" that is, from a unified Cyber-security standpoint. However, a key to a successful Cyber-security program is transparency and trust: from an experimental team viewpoint, this specifically means having the ability to immediately see what and from where, who has been blocked and being able to inform the community in case of a revoked access without the need for filing a "ticket" (that may eventually be answered) – in other words, rapid response to their user-base is essential but solutions targeting "sub-groups" in an organization are not often available. We have come up with a versatile solution leveraging the ELK stack (Elasticsearch, Logstash, & Kibana) and an IPS (Intrusion Prevention System) based WAF (Web Application Firewall) from Signal Sciences. Signal Science allows the streaming of detailed logs in a Logstash format suitable for custom solutions for visualization. By combining these two tools, we have strengthened our security posture and enabled individual experiments to monitor their own traffic. Specifically, the IPS WAF provides unique data such as country of origin, protocol, response code, source IP, and paths accessed. In this contribution, we will show how we engineered a visualization solution so experiment groups could access a dashboard with predefined graphs but also, where they can create individual customizable dashboards used to display blocked traffic and troubleshoot latency issues. We will discuss the details and procedures for developing and configuring these tools and how it benefits cyber security postures across our scientific based environment.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DCTRGAN: improving the precision of generative models with reweighting

Significant advances in deep learning have led to more widely used and precise neural network-based generative models such as Generative Adversarial Networks (Gans). We introduce a post-hoc correction to deep generative models to further improve their fidelity, based on the Deep neural networks using the Classification for Tuning and Reweighting (Dctr) protocol. The correction takes the form of a reweighting function that can be applied to generated examples when making predictions from the simulation. We illustrate this approach using Gans trained on standard multimodal probability densities as well as calorimeter simulations from high energy physics. We show that the weighted Gan examples significantly improve the accuracy of the generated samples without a large loss in statistical power. This approach could be applied to any generative model and is a promising refinement method for high energy physics applications and beyond.

47 OTHER INSTRUMENTATION↗

Multi-channel front-end ASIC for a 3D position-sensitive detector

Arrays of 3D position-sensitive detectors (3DPSD), operating at room temperature and using cadmium zinc telluride (CZT) and thallium bromide (TIBr) sensors, are suitable for gamma-ray spectrometry in many applications. One detector configuration, the 3D position-sensitive Virtual Frisch-Grid detector (VFG), is particularly advantageous for integrating into large area arrays. The signals generated inside each detector of the array are captured with the anode, cathode and four pads that enable the reconstruction of the position and energy of the ionizing interaction by measurements of amplitude and timing of the signals. For these applications, a low-noise front-end ASIC has been developed, capable of processing bipolar signals (needed because of AC-coupling of certain electrodes). The ASIC can be coupled to an ADC in order to form a compound “waveform digitizer” capable of post-processing the analog signals and determining amplitude and timing information. This paper describes a 32-channel front-end ASIC that is suitable for reading out a 3 × 3 or 4 × 4 element matrix in the VFG configuration. Each channel is composed of a low-noise charge amplifier with an adaptive continuous reset feedback circuit suitable for both positive and negative charge, a first order shaper and a single-to-differential converter output stage. Voltage and current references are all internally generated by 10-bit DACs and the chip is fully controllable with the I 2 C communication protocol. The readout channel response has been verified using the implemented injection circuit. Linear behavior up to ~75 ke ± with the gain of ~80 mV/fC, and up to ~200 ke ± with the gain of ~30 mV/fC was demonstrated. In conclusion, the first test result waveforms using a 137 Cs radioactive source on a 5 × 5 × 12 mm 3 TIBr crystal are reported.

47 OTHER INSTRUMENTATION↗

Analysis of humidity sensitivity of silicon strip sensors for ATLAS upgrade tracker, pre- and post-irradiation

During the prototyping phase of the new ATLAS Inner-Tracker (ITk) strip sensors, a degradation of the device breakdown voltage at high humidity was observed. Although the degradation was temporary, showing a fast recovery in dry conditions, the study of the influence of humidity on the sensor performance was critical to establish counter-measures and handling protocols during production testing in order to ensure the proper performance of the upgraded detector. The work presented here has the objective to study for the first time the breakdown voltage deterioration in presence of ambient humidity of ATLAS ITk production-layout strip sensors with different surface properties, before and after proton, neutron and gamma irradiations. A study of the humidity sensitivity of miniature ATLAS ITk strip sensors, before and after proton irradiations, is also presented to compare the sensitivity of devices with different sizes. The sensors were also exposed for several days to high humidity with the aim to recreate and evaluate the influence of the detector integration environment expected during the Large Hadron Collider (LHC) Long Shutdown 3 (LS3) in 2026, where the sensors will be exposed to ambient humidity for prolonged times.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Pronounced and unavoidable impacts of low-end global warming on northern high-latitude land ecosystems

Arctic ecosystems are particularly vulnerable to climate change because of Arctic amplification. Here, we assessed the climatic impacts of low-end, 1.5 °C, and 2.0 °C global temperature increases above pre-industrial levels, on the warming of terrestrial ecosystems in northern high latitudes (NHL, above 60 °N including pan-Arctic tundra and boreal forests) under the framework of the Inter-Sectoral Impact Model Intercomparison Project phase 2b protocol. We analyzed the simulated changes of net primary productivity, vegetation biomass, and soil carbon stocks of eight ecosystem models that were forced by the projections of four global climate models and two atmospheric greenhouse gas pathways (RCP2.6 and RCP6.0). Our results showed that considerable impacts on ecosystem carbon budgets, particularly primary productivity and vegetation biomass, are very likely to occur in the NHL areas. The models agreed on increases in primary productivity and biomass accumulation, despite considerable inter-model and inter-scenario differences in the magnitudes of the responses. The inter-model variability highlighted the inadequacies of the present models, which fail to consider important components such as permafrost and wildfire. The simulated impacts were attributable primarily to the rapid temperature increases in the NHL and the greater sensitivity of northern vegetation to warming, which contrasted with the less pronounced responses of soil carbon stocks. The simulated increases of vegetation biomass by 30–60 Pg C in this century have implications for climate policy such as the Paris Agreement. Comparison between the results at two warming levels showed the effectiveness of emission reductions in ameliorating the impacts and revealed unavoidable impacts for which adaptation options are urgently needed in the NHL ecosystems.

54 ENVIRONMENTAL SCIENCES↗

Spectra of perfect state transfer Hamiltonians on fractal-like graphs

Abstract In this paper we study the spectral features, on fractal-like graphs, of Hamiltonians which exhibit the special property of perfect quantum state transfer (PQST): the transmission of quantum states without dissipation. The essential goal is to develop the theoretical framework for understanding the interplay between PQST, spectral properties, and the geometry of the underlying graph, in order to design novel protocols for applications in quantum information science. We present a new lifting and gluing construction, and use this to prove results concerning an inductive spectral structure, applicable to a wide variety of fractal-like graphs. We illustrate this construction with explicit examples for several classes of diamond graphs.

Physics↗

Epitaxial growth of monolayer PdTe 2 and patterned PtTe 2 by direct tellurization of Pd and Pt surfaces

Two-dimensional (2D) palladium ditelluride (PdTe 2 ) and platinum ditelluride (PtTe 2 ) are two Dirac semimetals, which have fascinating quantum properties such as superconductivity, magnetism and topological order and show the promising applications in future nanoelectronics and optoelectronics. However, the synthesis of PdTe 2 and PtTe 2 monolayers (MLs) is hindered by a strong interlayer coupling and orbital hybridization. Here, in this study, we demonstrate an efficient synthesis of PdTe 2 and PtTe 2 MLs Large-area and high quality MLs of PdTe 2 and patterned PtTe 2 were epitaxially grown on the Pd(111) and Pt(111) surfaces by direct telurization in ultra-high vacuum. This was confirmed by x-ray photoelectron spectroscopy, low energy electron diffraction and scanning tunnelling microscopy. PdTe 2 ML demonstrated high thermal stability showing no decomposition sign after annealing at 470 °C. A well-ordered (2 × 2) PtTe 2 structure with Kagome lattice was observed on Te/Pt(111) surface following annealing at 200 °C in UHV, where the (2 × 2) pattern was formed by Te atom vacancies. PtTe 2 multilayer film was prepared as well, and it demonstrated the excitation of the Dirac plasmons as measured by high-resolution electron energy loss spectroscopy. The direct tellurization offers the simple and reliable protocol for the preparation of the ML of PdTe 2 and patterned PtTe 2 , and this opens new opportunities for quantum phenomena research and for practical optoelectronics applications.

2D materials↗

Engineering an effective three-spin Hamiltonian in trapped-ion systems for applications in quantum simulation

Trapped-ion quantum simulators, in analog and digital modes, are considered a primary candidate to achieve quantum advantage in quantum simulation and quantum computation. The underlying controlled ion–laser interactions induce all-to-all two-spin interactions via the collective modes of motion through Cirac–Zoller or Mølmer–Sørensen schemes, leading to effective two-spin Hamiltonians, as well as two-qubit entangling gates. In this work, the Mølmer–Sørensen scheme is extended to induce three-spin interactions via tailored first- and second-order spin–motion couplings. The scheme enables engineering single-, two-, and three-spin interactions, and can be tuned via an enhanced protocol to simulate purely three-spin dynamics. Analytical results for the effective evolution are presented, along with detailed numerical simulations of the full dynamics to support the accuracy and feasibility of the proposed scheme for near-term applications. With a focus on quantum simulation, the advantage of a direct analog implementation of three-spin dynamics is demonstrated via the example of matter-gauge interactions in the U(1) lattice gauge theory within the quantum link model. The mapping of degrees of freedom and strategies for scaling the three-spin scheme to larger systems, are detailed, along with a discussion of the expected outcome of the simulation of the quantum link model given realistic fidelities in the upcoming experiments. The applications of the three-spin scheme go beyond the lattice gauge theory example studied here and include studies of static and dynamical phase diagrams of strongly interacting condensed-matter systems modeled by two- and three-spin Hamiltonians.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Ion trap long-range XY model for quantum state transfer and optimal spatial search

Abstract Linear ion trap chains are a promising platform for quantum computation and simulation. The XY model with long-range interactions can be implemented with a single side-band Mølmer–Sørensen scheme, giving interactions that decay as 1 / r α , where α parameterises the interaction range. Lower α leads to longer range interactions, allowing faster long-range gate operations for quantum computing. However, decreasing α causes an increased generation of coherent phonons and appears to dephase the effective XY interaction model. We characterise and show how to correct for this effect completely, allowing lower α interactions to be coherently implemented. Ion trap chains are thus shown to be a viable platform for spatial quantum search in optimal O ( N ) time, for N ions. Finally, we introduce a O ( N ) quantum state transfer protocol, with a qubit encoding that maintains a high fidelity.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Pauli transfer matrix direct reconstruction: channel characterization without full process tomography

Abstract We present a tomographic protocol for the characterization of multiqubit quantum channels. We discuss a specific class of input states, for which the set of Pauli measurements at the output of the channel directly relates to its Pauli transfer matrix components. We compare our results to those of standard quantum process tomography, showing an exponential reduction in the number of different experimental configurations required by a single matrix element extraction, while keeping the same number of shots. This paves the way for more efficient experimental implementations, whenever a selective knowledge of the Pauli transfer matrix is needed. We provide several examples and simulations.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Grover-QAOA for 3-SAT: quadratic speedup, fair-sampling, and parameter clustering

Abstract The SAT problem is a prototypical NP-complete problem of fundamental importance in computational complexity theory with many applications in science and engineering; as such, it has long served as an essential benchmark for classical and quantum algorithms. This study shows numerical evidence for a quadratic speedup of the Grover Quantum Approximate Optimization Algorithm (G-QAOA) over random sampling for finding all solutions to 3-SAT (All-SAT) and Max-SAT problems. G-QAOA is less resource-intensive and more adaptable for these problems than Grover’s algorithm, and it surpasses conventional QAOA in its ability to sample all solutions. We show these benefits by classical simulations of many-round G-QAOA on thousands of random 3-SAT instances. We also observe G-QAOA advantages on the IonQ Aria quantum computer for small instances, finding that current hardware suffices to determine and sample all solutions. Interestingly, a single-angle-pair constraint that uses the same pair of angles at each G-QAOA round greatly reduces the classical computational overhead of optimizing the G-QAOA angles while preserving its quadratic speedup. We also find parameter clustering of the angles. The single-angle-pair protocol and parameter clustering significantly reduce obstacles to classical optimization of the G-QAOA angles.

Zhang, Zewen (ORCID:000000032258613X)↗

Hierarchical and scalable integration of nanostructures for energy and environmental applications: a review of processing, devices, and economic analyses

Hierarchical nanostructure, an engineered nanostructure with a higher assembly-level of constituents by low dimensional nano-building blocks, has received extensive attentions in the latest advancements in nanomaterial science and nanotechnology development. The ordered hierarchical nanostructures could offer merits such as more active sites, synergistic properties owing to their geometric complexity and building blocks variation, as well as the resultant multi-functional capabilities. In this review, we specifically focus on the integration approaches that may be feasible for large-scale production and manufacturing of engineered nanomaterials for various industrial applications, and the design criteria of hierarchical nanostructures targeted at various sustainable energy and environmental applications. In addition to chemical synthesis and integration methods, the development and application of hierarchical nanostructures are surveyed in energy conversion, generation, storage, utilization, and sensing devices. Meanwhile, a much-needed survey is also touched upon the techno-economic analyses of engineered nanomaterials, proposing the need of establishing various standard protocols on various factors and parameters that could be envisaged as a guide toward the viable transition to the practices in the future nano-industries.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Reflections on one million compounds in the open quantum materials database (OQMD)

Abstract Density functional theory (DFT) has been widely applied in modern materials discovery and many materials databases, including the open quantum materials database (OQMD), contain large collections of calculated DFT properties of experimentally known crystal structures and hypothetical predicted compounds. Since the beginning of the OQMD in late 2010, over one million compounds have now been calculated and stored in the database, which is constantly used by worldwide researchers in advancing materials studies. The growth of the OQMD depends on project-based high-throughput DFT calculations, including structure-based projects, property-based projects, and most recently, machine-learning-based projects. Another major goal of the OQMD is to ensure the openness of its materials data to the public and the OQMD developers are constantly working with other materials databases to reach a universal querying protocol in support of the FAIR data principles.

08 HYDROGEN↗

Quantum Kerr learning

Quantum machine learning is a rapidly evolving field of research that could facilitate important applications for quantum computing and also significantly impact data-driven sciences. In our work, based on various arguments from complexity theory and physics, we demonstrate that a single Kerr mode can provide some 'quantum enhancements' when dealing with kernel-based methods. Using kernel properties, neural tangent kernel theory, first-order perturbation theory of the Kerr non-linearity, and non-perturbative numerical simulations, we show that quantum enhancements could happen in terms of convergence time and generalization error. Furthermore, we make explicit indications on how higher-dimensional input data could be considered. Finally, we propose an experimental protocol, that we call quantum Kerr learning, based on circuit QED.

97 MATHEMATICS AND COMPUTING↗