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Previous Quantum School Highlights

Information about previous Quantum Computing Summer School Fellowships

Highlights from 2023 School

Invited speakers:

Giacomo Nannicini (University of Southern California), Vincent Elfving (Pasqal), Brajesh Gupt (Amazon), Kristan Temme (IBM), Zoe Holmes (EPFL), Lex Kemper (North Carolina State University), Mikhail Lukin (Harvard), Kunal Sharma (IBM)

Completed Projects

  • open_in_newClassical surrogate simulation of quantum systems with LOWESA
  • open_in_newLie-algebraic classical simulations for variational quantum computing
  • open_in_newA framework of partial error correction for intermediate-scale quantum computers
  • open_in_newLimitations for Quantum Algorithms to Solve Turbulent and Chaotic Systems

Highlights from 2022 School

Invited speakers:

Tameem Albash (University of New Mexico), Piotr Czarnik (Jagiellonian University), David Gosset (University of Waterloo), Aram Harrow (MIT), Robert Huang (Caltech), Nathan Killoran (Xanadu), Jarrod McClean (Google), Peter Shor (MIT), Guillaume Verdon, Stephan Woerner (IBM Research)

Completed Projects

  • open_in_newResource frugal optimizer for quantum machine learning
  • open_in_newOn the practical usefulness of the Hardware Efficient Ansatz
  • open_in_newTheoretical Guarantees for Permutation-Equivariant Quantum Neural Networks
  • open_in_newTheory for Equivariant Quantum Neural Networks
  • open_in_newRepresentation Theory for Geometric Quantum Machine Learning

Highlights from 2021 School

Invited speakers: 

Tameem Albash (University of New Mexico), Andrew Childs (University of Maryland), Elizabeth Crosson (University of New Mexico), Jens Eisert (Free University of Berlin), David Gosset (University of Waterloo), Shelby Kimmel (Middlebury College), Raymond Laflamme (Institute for Quantum Computing), Pavel Lougovski (Amazon Web Services), Mohan Sarovar (Sandia), Kristan Temme (IBM)

Completed Projects

  • open_in_newSubtleties in the trainability of quantum machine learning models
  • open_in_newTheory of overparametrization in quantum neural networks
  • open_in_newEntangled Datasets for Quantum Machine Learning
  • open_in_newCan Error Mitigation Improve Trainability of Noisy Variational Quantum Algorithms?
  • open_in_newAdaptive shot allocation for fast convergence in variational quantum algorithms
  • open_in_newUnifying and benchmarking state-of-the-art quantum error mitigation techniques
  • open_in_newSingle-Qubit Cross Platform Comparison of Quantum Computing Hardware

Highlights from 2020 School

Invited speakers:

Tameem Albash (U New Mexico), Juan Miguel Arrazola (Xanadu), Robin Blume-Kohout (Sandia), Thomas Bromley (Xanadu), Elizabeth Crosson (U New Mexico), Bill Fefferman (U Chicago), Jay Gambetta (IBM), Sonika Johri (IonQ), Mikhail Lukin (Harvard), Eleanor Rieffel (NASA), Maria Schuld (Xanadu), Graeme Smith (U Colorado), Wim van Dam (UCSB / QCWare), Nathan Wiebe (U Toronto)

Completed Projects

  • open_in_newUnified Approach to Data-driven Quantum Error Mitigation
  • open_in_newVariational Quantum Algorithm for Estimating the Quantum Fisher Information
  • open_in_newA Generalized Measure of Quantum Fisher Information
  • open_in_newCorrelation-Informed Permutation of Qubits for Reducing Ansatz Depth in VQE
  • open_in_newNoise- Induced Barren Plateaus in Variational Quantum Algorithms
  • open_in_newAbsence of Barren Plateaus in Quantum Convolutional Neural Networks

Highlights from 2019 School

Invited Speakers:

Scott Aaronson (UT Austin), Fernando Brandao (CalTech), Elizabeth Crosson (U New Mexico), Christopher Granade (Microsoft Research), Travis Humble (ORNL), John Martinis (Google), Margaret Martonosi (Princeton U), Jarrod McClean (Google), Seth Merkel (IBM), Chris Monroe (U Maryland), Alejandro Perdomo-Ortiz (Zapata Computing), Mauricio Reis (D-Wave), Will Zeng (Stanford U)

Completed Projects

  • open_in_newAn Adaptive Optimizer for Measurement-Frugal Variational Algorithms
  • open_in_newVariational Quantum Linear Solver: A Hybrid Algorithm for Linear Systems
  • open_in_newNoise Resilience of Variational Quantum Compiling
  • open_in_newThe Quantum Alternating Operator Ansatz on Max-k Vertex Cover
  • open_in_newQuantum Isomer Search
  • open_in_newThe Potential of Quantum Annealing for Rapid Solution Structure Identification

Highlights from 2018 School

Invited Speakers:

Sergio Boixo (Google), Alex Condello (D-Wave), Susan Coppersmith (Wisconsin), Ivan Deutsch (UNM), Jungsang Kim (IonQ / Duke), Daniel Lidar (USC), Doug McClure (IBM), Peter Shor (MIT), Matthias Troyer (Microsoft), Eleanor Rieffel (NASA), Will Zeng (Rigetti)

Completed Projects

  • open_in_newVariational Quantum State Diagonalization
  • open_in_newQuantum-Assisted Quantum Compiling
  • open_in_newVariational Fast Forwarding for Quantum Simulation Beyond the Coherence Time

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