activity
20192026
most citedSuperadiabatic population transfer in a three-level superconducting circuit

164 citations · 183 across the 5 of their papers we have counts for

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9 papers · 1 filter

quant-ph20261 cited

Numerical simulation methods for quantum sensing at parametric criticality

Kirill Petrovnin, Jiaming Wang, Gheorghe Sorin Paraoanu

Microwave photon detection is a key technology for low-temperature superconducting electronics and quantum information processing. A promising possibility is to use switching proce…

quant-ph2025

Neural-network-based design and implementation of fast and robust quantum gates

Marko Kuzmanović, Ilya Moskalenko, Yu-Han Chang +11

We present a continuous-time, neural-network-based approach to optimal control in quantum systems, with a focus on pulse engineering for quantum gates. Leveraging the framework of…

quant-ph2025

Quantum Process Tomography with Digital Twins of Error Matrices

Tangyou Huang, Akshay Gaikwad, Ilya Moskalenko +19

Accurate and robust quantum process tomography (QPT) is crucial for verifying quantum gates and diagnosing implementation faults in experiments aimed at building universal quantum…

quant-ph2025

Pareto-optimality of pulses for robust population transfer in a ladder-type qutrit

John J. McCord, Marko Kuzmanović, Gheorghe Sorin Paraoanu

Frequency-modulation schemes offer an alternative to standard Rabi pulses for realizing robust quantum operations. In this work, we investigate short-duration population transfer b…

quant-ph2021

Protocol for temperature sensing using a three-level transmon circuit

Aidar Sultanov, Marko Kuzmanović, Andrey V. Lebedev +1

We present a method for in situ temperature measurement of superconducting quantum circuits, by using the first three levels of a transmon device to which we apply a sequence of $π…

quant-ph202118 cited

Benchmarking Machine Learning Algorithms for Adaptive Quantum Phase Estimation with Noisy Intermediate-Scale Quantum Sensors

Nelson Filipe Costa, Yasser Omar, Aidar Sultanov +1

Quantum phase estimation is a paradigmatic problem in quantum sensing andmetrology. Here we show that adaptive methods based on classical machinelearning algorithms can be used to…