35 citations · 87 across the 6 of their papers we have counts for
7 papers
Unexpected Benefits of Self-Modeling in Neural Systems
Vickram N. Premakumar, Michael Vaiana, Florin Pop +4
Self-models have been a topic of great interest for decades in studies of human cognition and more recently in machine learning. Yet what benefits do self-models confer? Here we sh…
Fault-tolerant measurement-free quantum error correction with multi-qubit gates
Michael A. Perlin, Vickram N. Premakumar, Jiakai Wang +2
Measurement-free quantum error correction (MFQEC) offers an alternative to standard measurement-based QEC in platforms with an unconditional qubit reset gate. We revisit the questi…
2-Designs and Redundant Syndrome Extraction for Quantum Error Correction
Vickram N. Premakumar, Hele Sha, Daniel Crow +2
Imperfect measurement can degrade a quantum error correction scheme. A solution that restores fault tolerance is to add redundancy to the process of syndrome extraction. In this wo…
Spatial Noise Correlations in a Si/SiGe Two-Qubit Device from Bell State Coherences
Jelmer M. Boter, Xiao Xue, Tobias S. Krähenmann +10
We study spatial noise correlations in a Si/SiGe two-qubit device with integrated micromagnets. Our method relies on the concept of decoherence-free subspaces, whereby we measure t…
Error Mitigation in Quantum Computers subject to Spatially Correlated Noise
Vickram N. Premakumar, Robert Joynt
The most common error models for quantum computers assume the independence of errors on different qubits. However, most noise mechanisms have some correlations in space. We show ho…
Measurement-free implementations of small-scale surface codes for quantum dot qubits
H. Ekmel Ercan, Joydip Ghosh, Daniel Crow +4
The performance of quantum error correction schemes depends sensitively on the physical realizations of the qubits and the implementations of various operations. For example, in qu…