A5012021687- Quantum Information and Cryptography
- Machine Learning in Materials Science
- Quantum and electron transport phenomena
- Quantum Computing Algorithms and Architecture
- Computational Drug Discovery Methods
- X-ray Diffraction in Crystallography
- Physics of Superconductivity and Magnetism
- Quantum-Dot Cellular Automata
- Molecular Junctions and Nanostructures
- Acoustic Wave Resonator Technologies
- Long-Term Effects of COVID-19
- Intensive Care Unit Cognitive Disorders
- Particle accelerators and beam dynamics
- Photonic and Optical Devices
- Superconductivity in MgB2 and Alloys
- Surface and Thin Film Phenomena
- Advanced Antenna and Metasurface Technologies
- Superconducting and THz Device Technology
- Rough Sets and Fuzzy Logic
- Complex Network Analysis Techniques
- Advanced Materials Characterization Techniques
- Advancements in Semiconductor Devices and Circuit Design
- COVID-19 Clinical Research Studies
- Quantum Mechanics and Applications
- Microwave Engineering and Waveguides
Lawrence Berkeley National Laboratory
2022-2024
University of Oxford
2023-2024
University of California, Berkeley
2022-2024
King Fahd University of Petroleum and Minerals
2021-2022
King Abdullah University of Science and Technology
2022
Using selective post-fabrication etching, different ratios of TLS and other resonator losses are associated with the silicon niobium surface oxides, while coherent lifetime is increased by a factor five.
Predicting crystal structure from the chemical composition is one of most challenging and long-standing problems in condensed matter physics. This problem resides at interface between materials sciences With reliable data proper physics-guided modeling, machine learning (ML) can provide an alternative venue to undertake reduce problem's complexity. In this work, very robust ML classifiers for crystallographic symmetry groups were developed applied ternary (AlBmCn) binary (AlBm) starting only...
One of the most challenging problems in condensed matter physics is to predict crystal structure just from chemical formula material. In this work, we present a robust machine learning (ML) predictor for point group ternary materials (A[Formula: see text]B[Formula: text]C[Formula: text]) - as first step with very small set ionic and positional fundamental features. From ML perspective, problem strenuous due multi-labelity, multi-class, data imbalance. The resulted prediction reliable high...
Decoherence in superconducting quantum circuits, caused by loss mechanisms like material imperfections and two-level system (TLS) defects, remains a major obstacle to improving the performance of devices. In this work, we present atomic-level characterization cross-sections Josephson junction spiral resonator assess quality critical interfaces. Employing scanning transmission electron microscopy (STEM) combined with energy-dispersive X-ray spectroscopy (EDS) electron-energy (EELS), identify...
Hardware-efficient methods for high-fidelity quantum state measurements are crucial superconducting qubit experiments, as numbers grow and feedback reset begin to be employed error correction. We present a three-dimensional reentrant-cavity filter designed frequency-multiplexed readout of qubits. The cavity is situated out the plane circuit capacitively couples an array on-chip resonators in manner that can scale large arrays. reentrant functions large-linewidth bandpass with intrinsic...
Backgroundand Objectives: COVID-19 is a novel infectious disease caused by single-stranded RNA coronavirus called severe acute respiratory syndrome 2 (SARS-CoV-2). We aimed to conduct nationwide multicenter study determine the characteristics and clinical prognostic outcome of critically ill patients admitted intensive care units (ICUs). Materials Methods: This cohort retrospective conducted in twenty Saudi hospitals. Results: An analysis 1470 demonstrated that majority were male with mean...
Abstract In planar superconducting circuits, decoherence due to materials imperfections, especially two-level-system (TLS) defects at different interfaces, is a primary hurdle for advancing quantum computing and sensing applications. Traditional methods mitigating TLS loss, such as etching oxide layers metal substrate have proven be inadequate the persistent challenge of regrowth. this work, we introduce novel approach that employs molecular self-assembled monolayers (SAMs) chemically bind...
Suspending devices on thin SiN membranes can limit their interaction with the bulk substrate and reduce parasitic capacitance to ground. While suspending are used in many fields including radiation detection using superconducting circuits, there has been less investigation into maximum membrane aspect ratios achievable suspended device quality, metrics important establish applicable scope of technique. Here, we investigate these by fabricating coplanar waveguide resonators entirely atop...
In materials science, machine learning (ML) has become an essential and indispensable tool. ML emerged as a powerful tool in particularly for predicting material properties based on chemical composition. This review provides comprehensive overview of the current status future prospects using this domain, with special focus physics-guided (PGML). By integrating physical principles into models, PGML ensures that predictions are not only accurate but also interpretable, addressing critical need...
Superconducting coplanar waveguide (CPW) microwave resonators in quantum circuits are the best components for reading and changing state of artificial atoms because their excellent coupling to systems. This forms basis developing circuit electrodynamic architecture. In processors, oscillators used store transmit information using microwave-frequency wave packets. However, presence amorphous thin-film defects is deleterious can result an irrevocable loss coherent with uncontrolled degrees...
Background: Acute Respiratory Distress Syndrome (ARDS) is caused by non-cardiogenic pulmonary edema and occurs in critically ill patients. It one of the fatal complications observed among severe COVID-19 cases managed intensive care units (ICU). Supportive lung-protective ventilation prone positioning remain mainstay interventions. Purpose: We describe severity ARDS, clinical outcomes, management ICU patients with laboratory-confirmed infection multiple Saudi hospitals. Methods: A...
Correlated errors in superconducting circuits due to nonequilibrium quasiparticles are a notable concern efforts achieve fault tolerant quantum computing. The propagation of causing these correlated can potentially be mediated by phonons the substrate. Therefore, methods that decouple devices from substrate possible solutions, such as isolating atop SiN membranes. In this work, we validate compatibility membrane technology with high quality circuits, adding technique community's fabrication...
Quantum state discrimination plays an essential role in quantum technology, crucial for error correction, metrology, and sensing. While conventional methods rely on integrating readout signals or classifying raw signals, we developed a method to extract information about transitions during readout, based the path signature method, tool analyzing stochastic time series. The hardware experiments demonstrate improvement transmon qutrit fidelity from 85.9 $\pm$ 1.0% 91.0 0.5%, without need...
Abstract Quantum computing is a radical new paradigm for technology that capable to revolutionise information processing. Simulators of universal quantum computer are important understanding the basic principles and operations current noisy intermediate‐scale processors, building in future fault‐tolerant computers. As next‐generation technologies continue advance, it crucial address impact on education training physics. The emergence industries driven by progress simulation will create...
Fully automated self-driving laboratories are promising to enable high-throughput and large-scale scientific discovery by reducing repetitive labour. However, effective automation requires deep integration of laboratory knowledge, which is often unstructured, multimodal, difficult incorporate into current AI systems. This paper introduces the k-agents framework, designed support experimentalists in organizing knowledge automating experiments with agents. Our framework employs large language...
Hardware efficient methods for high fidelity quantum state measurements are crucial superconducting qubit experiments, as numbers grow and feedback reset begin to be employed error correction. We present a 3D re-entrant cavity filter designed frequency-multiplexed readout of qubits. The is situated out the plane circuit capacitively couples an array on-chip resonators in manner that can scale large arrays. functions large-linewidth bandpass with intrinsic Purcell filtering. demonstrate...
Quantum computation is a radical new candidate for technology that capable to make paradigm shift in information processing. However, current promising devices are limited performance due many decoherence mechanisms. computer simulators thus important understanding and solving existing problems of the noisy intermediate-scale quantum (NISQ) processors. In this work, we present Psitrum – universal gate-model based simulator implemented on classical hardware. The allows emulate debug...
Abstract Quantum computing is a radical new paradigm for technology that capable to revolutionize information processing. Simulators of universal quantum computer are important understanding the basic principles and operations current noisy intermediate-scale (NISQ) processors, building in future fault-tolerant computers. In this work, we present simulation computers by introducing Psitrum – gate-model simulator implemented on classical hardware. The allows emulate debug algorithms form...
Quantum computing is a radical new paradigm for technology that capable to revolutionize information processing. Simulators of universal quantum computer are important understanding the basic principles and operations current noisy intermediate-scale (NISQ) processors, building in future fault-tolerant computers. In this work, we present simulation computers by introducing Psitrum -- gate-model simulator implemented on classical hardware. The allows emulate debug algorithms form circuits...