Seth Lloyd

Quantum Hopfield neural network

2018 · Physical Review A

Neural networks, ubiquitous in machine learning, are generalized to the quantum realm. The method results in a network that can be exploited to offer exponential speedup on many applications, such as image processing and optimization, …

Dense coding capacity of a quantum channel

2020 · Physical Review Research

The authors consider a realistic dense coding scenario where noise is affecting both the transmission of quantum systems from the sender (Bob) to the receiver (Alice), and the distribution of the resource state from Alice …

Convex optimization of programmable quantum computers

2020 · npj Quantum Information

Abstract A fundamental model of quantum computation is the programmable quantum gate array. This is a quantum processor that is fed by a program state that induces a corresponding quantum operation on input states. While …

Passive states as optimal inputs for single-jump lossy quantum channels

2016 · DSpace@MIT (Massachusetts Institute of Technology)

The passive states of a quantum system minimize the average energy among all the states with a given spectrum. We prove that passive states are the optimal inputs of single-jump lossy quantum channels. These channels …

Learning Unitaries by Gradient Descent

2020 · arXiv (Cornell University)

We study the hardness of learning unitary transformations in $U(d)$ via gradient descent on time parameters of alternating operator sequences. We provide numerical evidence that, despite the non-convex nature of the loss landscape, gradient descent …

An efficient quantum algorithm for spectral estimation

2017 · DSpace@MIT (Massachusetts Institute of Technology)

We develop an efficient quantum implementation of an important signal processing algorithm for line spectral estimation: the matrix pencil method, which determines the frequencies and damping factors of signals consisting of finite sums of exponentially …

Hamiltonian singular value transformation and inverse block encoding

2021 · arXiv (Cornell University)

The quantum singular value transformation is a powerful quantum algorithm that allows one to apply a polynomial transformation to the singular values of a matrix that is embedded as a block of a unitary transformation. …

Comment on “Saturating quantum advantages in postselected metrology with the positive Kirkwood-Dirac distribution”

2024 · Physical Review A

In a recent paper [Das, Modak, and Bera, Phys. Rev. A 107, 042413 (2023)], Das et al. claim that Kirkwood-Dirac negativity is not required to achieve anomalous values of the quantum Fisher information encoded in …