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The microscopic description of 1/f magnetic flux noise in superconducting circuits has remained an open question for several decades despite extensive experimental and theoretical investigation. Recent progress in superconducting devices for quantum information has highlighted the need to mitigate sources of qubit decoherence, driving a renewed interest in understanding the underlying noise mechanism(s). Though a consensus has emerged attributing flux noise to surface spins, their identity and interaction mechanisms remain unclear, prompting further study. Here, we apply weak in-plane magnetic fields to a capacitively shunted flux qubit (where the Zeeman splitting of surface spins lies below the device temperature) and study the flux-noise-limited qubit dephasing, revealing previously unexplored trends that may shed light on the dynamics behind the emergent 1/f noise. Notably, we observe an enhancement (suppression) of the spin-echo (Ramsey) pure-dephasing time in fields up to B=100 G. With direct noise spectroscopy, we further observe a transition from a 1/f to approximately Lorentzian frequency dependence below 10 Hz and a reduction of the noise above 1 MHz with increasing magnetic field. We suggest that these trends are qualitatively consistent with an increase of spin cluster sizes with magnetic field. These results should help to inform a complete microscopic theory of 1/f flux noise in superconducting circuits.

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Dielectrics with low loss at microwave frequencies are imperative for high-coherence solid-state quantum computing platforms. Here we study the dielectric loss of hexagonal boron nitride (hBN) thin films in the microwave regime by measuring the quality factor of parallel-plate capacitors (PPCs) made of NbSe2-hBN-NbSe2 heterostructures integrated into superconducting circuits. The extracted microwave loss tangent of hBN is bounded to be at most in the mid-10-6 range in the low-temperature, single-photon regime. We integrate hBN PPCs with aluminium Josephson junctions to realize transmon qubits with coherence times reaching 25 µs, consistent with the hBN loss tangent inferred from resonator measurements. The hBN PPC reduces the qubit feature size by approximately two orders of magnitude compared with conventional all-aluminium coplanar transmons. Our results establish hBN as a promising dielectric for building high-coherence quantum circuits with substantially reduced footprint and with a high energy participation that helps to reduce unwanted qubit cross-talk.

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System noise identification is crucial to the engineering of robust quantum systems. Although existing quantum noise spectroscopy (QNS) protocols measure an aggregate amount of noise affecting a quantum system, they generally cannot distinguish between the underlying processes that contribute to it. Here, we propose and experimentally validate a spin-locking-based QNS protocol that exploits the multi-level energy structure of a superconducting qubit to achieve two notable advances. First, our protocol extends the spectral range of weakly anharmonic qubit spectrometers beyond the present limitations set by their lack of strong anharmonicity. Second, the additional information gained from probing the higher-excited levels enables us to identify and distinguish contributions from different underlying noise mechanisms.

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Advanced microscopy and/or spectroscopy tools play indispensable roles in nanoscience and nanotechnology research, as they provide rich information about material processes and properties. However, the interpretation of imaging data heavily relies on the "intuition" of experienced researchers. As a result, many of the deep graphical features obtained through these tools are often unused because of difficulties in processing the data and finding the correlations. Such challenges can be well addressed by deep learning. In this work, the optical characterization of 2D materials is used as a case study, and a neural-network-based algorithm is demonstrated for the material and thickness identification of 2D materials with high prediction accuracy and real-time processing capability. Further analysis shows that the trained network can extract deep graphical features such as contrast, color, edges, shapes, flake sizes, and their distributions, based on which an ensemble approach is developed to predict the most relevant physical properties of 2D materials. Finally, a transfer learning technique is applied to adapt the pretrained network to other optical identification applications. This artificial-intelligence-based material characterization approach is a powerful tool that would speed up the preparation, initial characterization of 2D materials and other nanomaterials, and potentially accelerate new material discoveries.

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Quantum coherence and control is foundational to the science and engineering of quantum systems1,2. In van der Waals materials, the collective coherent behaviour of carriers has been probed successfully by transport measurements3-6. However, temporal coherence and control, as exemplified by manipulating a single quantum degree of freedom, remains to be verified. Here we demonstrate such coherence and control of a superconducting circuit incorporating graphene-based Josephson junctions. Furthermore, we show that this device can be operated as a voltage-tunable transmon qubit7-9, whose spectrum reflects the electronic properties of massless Dirac fermions travelling ballistically4,5. In addition to the potential for advancing extensible quantum computing technology, our results represent a new approach to studying van der Waals materials using microwave photons in coherent quantum circuits.

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Electron surface states in solids are typically confined to the outermost atomic layers and, due to surface disorder, have negligible impact on electronic transport. Here, we demonstrate a very different behavior for surface states in graphene. We probe the wavelike character of these states by Fabry-Perot (FP) interferometry and find that, in contrast to theoretical predictions, these states can propagate ballistically over micron-scale distances. This is achieved by embedding a graphene resonator formed by gate-defined p-n junctions within a graphene superconductor-normal-superconductor structure. By combining superconducting Aharanov-Bohm interferometry with Fourier methods, we visualize spatially resolved current flow and image FP resonances due to p-n-p cavity modes. The coherence of the standing-wave edge states is revealed by observing a new family of FP resonances, which coexist with the bulk resonances. The edge resonances have periodicity distinct from that of the bulk states manifest in a repeated spatial redistribution of current on and off the FP resonances. This behavior is accompanied by a modulation of the multiple Andreev reflection amplitude on-and-off resonance, indicating that electrons propagate ballistically in a fully coherent fashion. These results, which were not anticipated by theory, provide a practical route to developing electron analog of optical FP resonators at the graphene edge.

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PURPOSE: The authors discuss measurement methods and instrumentation useful for the characterization of the gray tracking performance of medical color monitors for diagnostic applications. The authors define gray tracking as the variability in the chromaticity of the gray levels in a color monitor. METHODS: The authors present data regarding the capability of color measurement instruments with respect to their abilities to measure a target white point corresponding to the CIE Standard Illuminant D65 at different luminance values within the grayscale palette of a medical display. The authors then discuss evidence of significant differences in performance among color measurement instruments currently available for medical physicists to perform calibrations and image quality checks for the consistent representation of color in medical displays. In addition, the authors introduce two metrics for quantifying grayscale chromaticity consistency of gray tracking. RESULTS: The authors' findings show that there is an order of magnitude difference in the accuracy of field and reference instruments. The gray tracking metrics quantify how close the grayscale chromaticity is to the chromaticity of the full white point (equal amounts of red, green, and blue at maximum level) or to consecutive levels (equal values for red, green, and blue), with a lower value representing an improved grayscale tracking performance. An illustrative example of how to calculate and report the gray tracking performance according to the Task Group definitions is provided. CONCLUSIONS: The authors' proposed methodology for characterizing the grayscale degradation in chromaticity for color monitors that can be used to establish standards and procedures aiding in the quality control testing of color displays and color measurement instrumentation.

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We report high quality graphene and WSe2 devices encapsulated between two hexagonal boron nitride (hBN) flakes using a pick-up method with etched hBN flakes. Picking up prepatterned hBN flakes to be used as a gate dielectric or mask for other 2D materials opens new possibilities for the design and fabrication of 2D heterostructures. In this Letter, we demonstrate this technique in two ways: first, a dual-gated graphene device that is encapsulated between an hBN substrate and prepatterned hBN strips. The conductance of the graphene device shows pronounced Fabry-Pérot oscillations as a function of carrier density, which implies strong quantum confinement and ballistic transport in the locally gated region. Second, we describe a WSe2 device encapsulated in hBN with the top hBN patterned as a mask for the channel of a Hall bar. Ionic liquid selectively tunes the carrier density of the contact region of the device, while the hBN mask allows independent tunability of the contact region for low contact resistance. Hall mobility larger than 600 cm(2)/(V·s) for few-layer p-type WSe2 at 220 K is measured, the highest mobility of a thin WSe2 device reported to date. The observations of ballistic transport in graphene and high mobility in WSe2 confirm pick-up of prepatterned hBN as a versatile technique to fabricate ultraclean devices with high quality contact.

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The crystal structure of a material plays an important role in determining its electronic properties. Changing from one crystal structure to another involves a phase transition that is usually controlled by a state variable such as temperature or pressure. In the case of trilayer graphene, there are two common stacking configurations (Bernal and rhombohedral) that exhibit very different electronic properties. In graphene flakes with both stacking configurations, the region between them consists of a localized strain soliton where the carbon atoms of one graphene layer shift by the carbon-carbon bond distance. Here we show the ability to move this strain soliton with a perpendicular electric field and hence control the stacking configuration of trilayer graphene with only an external voltage. Moreover, we find that the free-energy difference between the two stacking configurations scales quadratically with electric field, and thus rhombohedral stacking is favoured as the electric field increases. This ability to control the stacking order in graphene opens the way to new devices that combine structural and electrical properties.