activity
20142026
most citedTowards Quantum Machine Learning with Tensor Networks

314 citations · 1k across the 12 of their papers we have counts for

collaborators

12 papers

quant-ph2026

Observable Estimation in the Absence of Classical Verification

Samantha V. Barron, Bradley Mitchell, Vinay Tripathi +45

The predictive success of quantum mechanics underpins many areas of modern science, even as the exact simulation of large, interacting quantum systems remains beyond the reach of c…

quant-ph2022★ 21 cited

Demonstrating scalable randomized benchmarking of universal gate sets

Jordan Hines, Marie Lu, Ravi K. Naik +12

Randomized benchmarking (RB) protocols are the most widely used methods for assessing the performance of quantum gates. However, the existing RB methods either do not scale to many…

quant-ph2022★ 141 cited

High-Fidelity Qutrit Entangling Gates for Superconducting Circuits

Noah Goss, Alexis Morvan, Brian Marinelli +9

Ternary quantum information processing in superconducting devices poses a promising alternative to its more popular binary counterpart through larger, more connected computational…

quant-ph2022★ 91 cited

Scalable High-Performance Fluxonium Quantum Processor

Long B. Nguyen, Gerwin Koolstra, Yosep Kim +12

The technological development of hardware heading toward universal fault-tolerant quantum computation requires a large-scale processing unit with high performance. While fluxonium…

quant-ph2021★ 82 cited

Hardware-Efficient Microwave-Activated Tunable Coupling Between Superconducting Qubits

Bradley K. Mitchell, Ravi K. Naik, Alexis Morvan +7

Generating high-fidelity, tunable entanglement between qubits is crucial for realizing gate-based quantum computation. In superconducting circuits, tunable interactions are often i…

quant-ph2021★ 5 cited

Automatic Qubit Characterization and Gate Optimization with QubiC

Yilun Xu, Gang Huang, Jan Balewski +6

As the size and complexity of a quantum computer increases, quantum bit (qubit) characterization and gate optimization become complex and time-consuming tasks. Current calibration…

quant-ph2021★ 15 cited

Leveraging Randomized Compiling for the QITE Algorithm

Jean-Loup Ville, Alexis Morvan, Akel Hashim +13

The success of the current generation of Noisy Intermediate-Scale Quantum (NISQ) hardware shows that quantum hardware may be able to tackle complex problems even without error corr…

quant-ph2021★ 72 cited

QubiC: An open source FPGA-based control and measurement system for superconducting quantum information processors

Yilun Xu, Gang Huang, Jan Balewski +6

As quantum information processors grow in quantum bit (qubit) count and functionality, the control and measurement system becomes a limiting factor to large scale extensibility. To…

quant-ph2020★ 35 cited

Randomized compiling for scalable quantum computing on a noisy superconducting quantum processor

Akel Hashim, Ravi K. Naik, Alexis Morvan +11

The successful implementation of algorithms on quantum processors relies on the accurate control of quantum bits (qubits) to perform logic gate operations. In this era of noisy int…

quant-ph2020★ 145 cited

Qutrit randomized benchmarking

A. Morvan, V. V. Ramasesh, M. S. Blok +7

Ternary quantum processors offer significant computational advantages over conventional qubit technologies, leveraging the encoding and processing of quantum information in qutrits…

quant-ph2018★ 314 cited

Towards Quantum Machine Learning with Tensor Networks

William Huggins, Piyush Patel, K. Birgitta Whaley +1

Machine learning is a promising application of quantum computing, but challenges remain as near-term devices will have a limited number of physical qubits and high error rates. Mot…

physics.ins-det2014★ 91 cited

Future Directions in the Microwave Cavity Search for Dark Matter Axions

T. M. Shokair, J. Root, K. A. Van Bibber +9

The axion is a light pseudoscalar particle which suppresses CP-violating effects in strong interactions and also happens to be an excellent dark matter candidate. Axions constituti…