A5040172106- Quantum Computing Algorithms and Architecture
- Quantum Information and Cryptography
- Quantum and electron transport phenomena
- Advancements in Semiconductor Devices and Circuit Design
- Quantum Mechanics and Applications
- Physics of Superconductivity and Magnetism
- Parallel Computing and Optimization Techniques
- Neural Networks and Reservoir Computing
- Cloud Computing and Resource Management
- Quantum-Dot Cellular Automata
- Smart Agriculture and AI
- Sensor Technology and Measurement Systems
- Quantum Dots Synthesis And Properties
- Photonic and Optical Devices
- Cold Atom Physics and Bose-Einstein Condensates
- Stochastic Gradient Optimization Techniques
- Molecular Junctions and Nanostructures
- Semiconductor Quantum Structures and Devices
- Neural Networks and Applications
- Water Quality Monitoring Technologies
- Advanced MEMS and NEMS Technologies
- Surface and Thin Film Phenomena
- Water-Energy-Food Nexus Studies
- Advanced Memory and Neural Computing
- Cellular Automata and Applications
Princeton University
2019-2023
Queensland Rail
2021-2023
Sinhgad Dental College and Hospital
2021
Indian Institute of Science Bangalore
2020
Parasitic crosstalk in superconducting quantum devices is a leading limitation for gates. We demonstrate the suppression of static ZZ two-qubit, two-coupler circuit, where frequency tunable coupler can be adjusted such that interaction from each destructively interfere. verify elimination with simultaneous randomized benchmarking, and use parametrically activated iSWAP to achieve Bell state preparation fidelity 98.5% $\sqrt{\textrm{iSWAP}}$ gate 94.8% obtained via process tomography.
The superconducting transmon qubit is a leading platform for quantum computing and science. Building large, useful systems based on qubits will require significant improvements in relaxation coherence times, which are orders of magnitude shorter than limits imposed by bulk properties the constituent materials. This indicates that likely originates from uncontrolled surfaces, interfaces, contaminants. Previous efforts to improve lifetimes have focused primarily designs minimize contributions...
A bottleneck for scaling quantum hardware is solved: An AI-based technique to design gates without knowledge of the physical model or noise processes demonstrated experimentally, outperforming best human-designed gates.
Excitement about the promise of quantum computers is tempered by reality that hardware remains exceptionally fragile and error prone, forming a bottleneck in development alternative applications. In this paper, we describe experimentally test fully autonomous workflow designed to deterministically suppress errors algorithms from gate level through circuit execution measurement. We introduce key elements workflow, delivered as software package called Fire Opal, survey underlying physical...
Protecting superconducting qubits from low-frequency noise is essential for advancing quantum computation. Based on the application of a periodic drive field, we develop protocol engineering dynamical sweet spots which reduce susceptibility qubit to noise. Using framework Floquet theory, prove rigorously that there are manifolds marked by extrema in quasi-energy differences driven qubit. In particular, example fluxonium biased slightly away half flux quantum, predict an enhancement...
We employ quantum optimal control theory to realize gates for two protected superconducting circuits: the heavy-fluxonium qubit and 0-$\ensuremath{\pi}$ qubit. Utilizing automatic differentiation facilitates simultaneous inclusion of multiple optimization targets, allowing one obtain high-fidelity with realistic pulse shapes. For both qubits, disjoint support low-lying wave functions prevents direct population transfer between computational-basis states. Instead, favors dynamics involving...
Encoding a qubit in logical quantum states with wavefunctions characterized by disjoint support and robust energies can offer simultaneous protection against relaxation pure dephasing. Using circuit-quantum-electrodynamics architecture, we experimentally realize superconducting $0-\pi$ qubit, which hosts protected suitable for quantum-information processing. Multi-tone spectroscopy measurements reveal the energy level structure of system, be precisely described simple two-mode Hamiltonian....
The ability to perform fast, high-fidelity entangling gates is a requirement for viable quantum processor. In practice, achieving fast often comes with the penalty of strong-drive effects that are not captured by rotating-wave approximation. These can be analyzed in simulations gate protocol, but those computationally costly and hide physics at play. Here, we show how efficiently extract parameters directly solving Floquet eigenproblem using exact numerics perturbative analytical approach....
We introduce a comprehensive quantum solver for binary combinatorial optimization problems on gate-model computers that outperforms any published alternative and consistently delivers correct solutions with up to 127 qubits. provide an overview of the internal workflow, describing integration customized ansatz variational parameter update strategy, efficient error suppression in hardware execution, overhead-free post-processing bit-flip errors. benchmark this IBM several classically...
In the last two decades development of superconducting qubits has yielded tremendous improvement, with coherence times increasing over five orders magnitude. Theory and experiment have shown that $1/f$ noise is currently limiting factor for qubit in state-of-the-art devices. Here authors use a qubit's Floquet states to store quantum information, mitigating flux achieving 40-fold improvement time. This experimental demonstration solves longstanding, critical problem field, as it provides...
The QED-C suite of Application-Oriented Benchmarks provides the ability to gauge performance characteristics quantum computers as applied real-world applications. Its benchmark programs sweep over a range problem sizes and inputs, capturing key metrics related quality results, total time execution, gate resources consumed. In this manuscript, we investigate challenges in broadening relevance benchmarking methodology applications greater complexity. First, introduce method for improving...
Hybrid quantum-classical optimization using near-term quantum technology is an emerging direction for exploring advantage in high-dimensional systems. However, precise characterization of all experimental parameters often impractical and challenging. A viable approach to use algorithms that rely only on black-box inference rather than analytical gradients. Here, we combine randomized perturbation gradient estimation with adaptive momentum updates create the AdamSPSA AdamRSGF algorithms. We...
The transfer of charge carriers across the optically excited hetero-interface graphene and semiconducting transition metal dichalcogenides (TMDCs) is key to convert light electricity, although intermediate steps from creation excitons in TMDC collection free layer are not fully understood. Here, we investigate photo-induced transport graphene–MoS2 graphene–WSe2 hetero-interfaces using time-dependent photoresistance relaxation with varying temperature, wavelength, gate voltage. In both types...
Near-term quantum computers are primarily limited by errors in operations (or gates) between two bits qubits). A physical machine typically provides a set of basis gates that include primitive 2-qubit (2Q) and 1-qubit (1Q) can be implemented given technology. 2Q entangling gates, coupled with some 1Q allow for universal computation. In superconducting technologies, the current state art is to implement same gate every pair qubits (typically an XX-or XY-type gate). This strict hardware...
The ability to perform fast, high-fidelity entangling gates is an important requirement for a viable quantum processor. In practice, achieving fast often comes with the penalty of strong-drive effects that are not captured by rotating-wave approximation. These can be analyzed in simulations gate protocol, but those computationally costly and hide physics at play. Here, we show how efficiently extract parameters directly solving Floquet eigenproblem using exact numerics perturbative...
We introduce and experimentally test a machine-learning-based method for ranking logically equivalent quantum circuits based on expected performance estimates derived from training procedure conducted real hardware. apply our to the problem of layout selection, in which abstracted qubits are assigned physical given device. Circuit measurements performed IBM hardware indicate that maximum median fidelities layouts can differ by an order magnitude. circuit score used is parameterized terms...
We introduce and experimentally test a machine-learning-based method for ranking logically equivalent quantum circuits based on expected performance estimates derived from training procedure conducted real hardware. apply our to the problem of layout selection, in which abstracted qubits are assigned physical given device. Circuit measurements performed IBM hardware indicate that maximum median fidelities layouts can differ by an order magnitude. circuit score used is parameterized terms...
The resource overhead required to achieve net computational benefits from quantum error correction (QEC) limits its utility while current systems remain constrained in size, despite exceptional progress experimental demonstrations. In this paper, we demonstrate that the strategic application of QEC primitives without logical encoding can yield significant advantages on superconducting processors--relative any alternative error-reduction strategy--while only requiring modest overhead. We...
The ability to perform fast, high-fidelity entangling gates is an important requirement for a viable quantum processor. In practice, achieving fast often comes with the penalty of strong-drive effects that are not captured by rotating-wave approximation. These can be analyzed in simulations gate protocol, but those computationally costly and hide physics at play. Here, we show how efficiently extract parameters directly solving Floquet eigenproblem using exact numerics perturbative...
Hybrid quantum classical optimization using near-term technology is an emerging direction for exploring advantage in high-dimensional systems. However, precise characterization of all experimental parameters often impractical and challenging. A viable approach to use algorithms that rely entirely on black-box inference rather than analytical gradients. Here, we combine randomized perturbation gradient estimation with adaptive momentum updates propose AdamSPSA AdamRSGF algorithms. We prove...
Excitement about the promise of quantum computers is tempered by reality that hardware remains exceptionally fragile and error-prone, forming a bottleneck in development novel applications. In this manuscript, we describe experimentally test fully autonomous workflow designed to deterministically suppress errors algorithms from gate level through circuit execution measurement. We introduce key elements workflow, delivered as software package called Fire Opal, survey underlying physical...
Gate-defined quantum dots are a promising candidate system for realizing scalable, coupled qubit systems and serving as fundamental building block computers. However, present-day dot devices suffer from imperfections that must be accounted for, which hinders the characterization, tuning, operation process. Moreover, with an increasing number of qubits, relevant parameter space grows sufficiently to make heuristic control infeasible. Thus, it is imperative reliable scalable autonomous tuning...