
Scalable Benchmarks for GateBased Quantum Computers
In the nearterm "NISQ"era of noisy, intermediatescale, quantum hardwa...
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(Sub)Exponential advantage of adiabatic quantum computation with no sign problem
We demonstrate the possibility of (sub)exponential quantum speedup via a...
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An improved quantuminspired algorithm for linear regression
We give a classical algorithm for linear regression analogous to the qua...
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Quantum algorithm for Petz recovery channels and pretty good measurements
The Petz recovery channel plays an important role in quantum information...
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Symmetries, graph properties, and quantum speedups
Aaronson and Ambainis (2009) and Chailloux (2018) showed that fully symm...
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A Unified Framework of Quantum Walk Search
The main results on quantum walk search are scattered over different, in...
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Samplingbased sublinear lowrank matrix arithmetic framework for dequantizing quantum machine learning
We present an algorithmic framework generalizing quantuminspired polylo...
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Quadratic speedup for finding marked vertices by quantum walks
A quantum walk algorithm can detect the presence of a marked vertex on a...
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Distributional property testing in a quantum world
A fundamental problem in statistics and learning theory is to test prope...
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Quantuminspired lowrank stochastic regression with logarithmic dependence on the dimension
We construct an efficient classical analogue of the quantum matrix inver...
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Convex optimization using quantum oracles
We study to what extent quantum algorithms can speed up solving convex o...
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The power of blockencoded matrix powers: improved regression techniques via faster Hamiltonian simulation
We apply the framework of blockencodings, introduced by Low and Chuang ...
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Optimizing quantum optimization algorithms via faster quantum gradient computation
We consider a generic framework of optimization algorithms based on grad...
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András Gilyén
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