activity
20202023
most citedTransmon qubit readout fidelity at the threshold for quantum error correction without a quantum-limited amplifier

87 citations · 172 across the 6 of their papers we have counts for

collaborators

6 papers

cs.CV2023

Contrastive Attention Networks for Attribution of Early Modern Print

Nikolai Vogler, Kartik Goyal, Kishore PV Reddy +5

In this paper, we develop machine learning techniques to identify unknown printers in early modern (c.~1500--1800) English printed books. Specifically, we focus on matching uniquel…

quant-ph2023★ 40 cited

Mitigation of frequency collisions in superconducting quantum processors

Amr Osman, Jorge Fernàndez-Pendàs, Christopher Warren +6

The reproducibility of qubit parameters is a challenge for scaling up superconducting quantum processors. Signal crosstalk imposes constraints on the frequency separation between n…

quant-ph2022★ 87 cited

Transmon qubit readout fidelity at the threshold for quantum error correction without a quantum-limited amplifier

Liangyu Chen, Hang-Xi Li, Yong Lu +17

High-fidelity and rapid readout of a qubit state is key to quantum computing and communication, and it is a prerequisite for quantum error correction. We present a readout scheme f…

quant-ph2022★ 43 cited

Extensive characterization of a family of efficient three-qubit gates at the coherence limit

Christopher W. Warren, Jorge Fernández-Pendás, Shahnawaz Ahmed +13

While all quantum algorithms can be expressed in terms of single-qubit and two-qubit gates, more expressive gate sets can help reduce the algorithmic depth. This is important in th…

quant-ph2022★ 1 cited

Reference-State Error Mitigation: A Strategy for High Accuracy Quantum Computation of Chemistry

Phalgun Lolur, Mårten Skogh, Christopher Warren +6

Decoherence and gate errors severely limit the capabilities of state-of-the-art quantum computers. This work introduces a strategy for reference-state error mitigation (REM) of qua…

cs.LG2020★ 1 cited

A Probabilistic Generative Model for Typographical Analysis of Early Modern Printing

Kartik Goyal, Chris Dyer, Christopher Warren +2

We propose a deep and interpretable probabilistic generative model to analyze glyph shapes in printed Early Modern documents. We focus on clustering extracted glyph images into und…