Format results
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Interpretable Quantum Advantage in Neural Sequence Learning
Eric Anschuetz - Massachusetts Institute of Technology (MIT)
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Quantum Constraint Problems can be complete for BQP, QCMA, and BPP
Alexander Meiburg - University of California System
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Quantum-enhanced telescopy
Yunkai Wang - Perimeter Institute for Theoretical Physics
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An operator-algebraic formulation of self-testing
Connor Paul-Paddock - University of Waterloo
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Newton’s Cradle Spectra
Barbara Soda - Perimeter Institute for Theoretical Physics
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Entanglement distillation in tensor networks
Takato Mori - Rikkyo University
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On nonlinear transformations in quantum computation
Zoe Holmes - Los Alamos National Laboratory
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Resource theory of quantum complexity
Anthony Munson - University of Maryland, College Park
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Causal aspects of quantum information in quantum gravity
Alex May - Perimeter Institute for Theoretical Physics
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Neural Network Decoders for Measurement-Induced Phase Transitions
Michael Gullans - University of Maryland, College Park
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Fault tolerance as topology, a duet for chalk and violin
Daniel Gottesman - University of Maryland, College Park , Lucy Liuxuan Zhang - University of Maryland, College Park
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Interpretable Quantum Advantage in Neural Sequence Learning
Eric Anschuetz - Massachusetts Institute of Technology (MIT)
Quantum neural networks have been widely studied in recent years, given their potential practical utility and recent results regarding their ability to efficiently express certain classical data. However, analytic results to date rely on assumptions and arguments from complexity theory. Due to this… -
Quantum Constraint Problems can be complete for BQP, QCMA, and BPP
Alexander Meiburg - University of California System
Constraint satisfaction problems are known to always be "easy" or "hard", in the sense of being either solvable in P or being NP-complete, with no intermediate difficulty levels. The quantum analog of constraint problems, frustration-free Hamiltonians, are known to exhibit at least two more levels… -
Quantum-enhanced telescopy
Yunkai Wang - Perimeter Institute for Theoretical Physics
Optical astronomical imaging looks for better imaging quality in extreme cases of weak and subdiffraction limits. I focus on the quantum enhancement of astronomical interferometric imaging, including its fundamental limit and practical issues. For the fundamental aspects, I ignore any resource limit… -
Learning efficient decoders for quasi-chaotic quantum scramblers
Scrambling of quantum information is an important feature at the root of randomization and benchmarking protocols, the onset of quantum chaos, and black-hole physics. Unscrambling this information is possible given perfect knowledge of the scrambler [ArXiv: 1710.03363]. We show that one can retrieve… -
An operator-algebraic formulation of self-testing
Connor Paul-Paddock - University of Waterloo
We give a new definition of self-testing for correlations in terms of states on C*-algebras. We show that this definition is equivalent to the standard definition for any class of finite-dimensional quantum models which is closed under submodels and direct sums, provided that the correlation is… -
Newton’s Cradle Spectra
Barbara Soda - Perimeter Institute for Theoretical Physics
We present broadly applicable nonperturbative results on the behavior of eigenvalues and eigenvectors under the addition of self-adjoint operators and under the multiplication of unitary operators, in finite-dimensional Hilbert spaces. To this end, we decompose these operations into elementary 1… -
Entanglement distillation in tensor networks
Takato Mori - Rikkyo University
Tensor network provides a geometric representation of quantum many-body wave functions. Inspired by holography, we discuss a geometric realization of (one-shot) entanglement distillation for tensor networks including the multi-scale entanglement renormalization ansatz and matrix product states. We… -
On nonlinear transformations in quantum computation
Zoe Holmes - Los Alamos National Laboratory
While quantum computers are naturally well-suited to implementing linear operations, it is less clear how to implement nonlinear operations on quantum computers. However, nonlinear subroutines may prove key to a range of applications of quantum computing from solving nonlinear equations to data… -
Resource theory of quantum complexity
Anthony Munson - University of Maryland, College Park
Quantum complexity is emerging as a key property of many-body systems, including black holes, topological materials, and early quantum computers. A state's complexity quantifies the number of computational gates required to prepare the state from a simple tensor product. The greater a state's… -
Causal aspects of quantum information in quantum gravity
Alex May - Perimeter Institute for Theoretical Physics
Quantum information science was initially motivated by questions about information processing. For example, what are the consequences of quantum mechanics for computation? Or for cryptography? More recently, quantum information has also become a perspective through which we can study questions in… -
Neural Network Decoders for Measurement-Induced Phase Transitions
Michael Gullans - University of Maryland, College Park
The sustained storage, transmission, or processing of quantum information will likely be a non-equilibrium process that requires monitoring the system and applying some form of feedback to produce fault-tolerance. In this talk, I will discuss a class of models based on random quantum circuits with… -
Fault tolerance as topology, a duet for chalk and violin
Daniel Gottesman - University of Maryland, College Park , Lucy Liuxuan Zhang - University of Maryland, College Park
We are used to thinking of there being different types of fault-tolerant gates allowing reliable computation on states in a noisy quantum computer: Some are transversal, some involve measurement and magic states, some involve topological manipulations, etc. In this talk, we will demonstrate that…