Papers

Galit Anikeeva, Isaac H. Kim, P. Hayden·Dec 3, 2020

Quantum computers are capable of efficiently contracting unitary tensor networks, a task that is likely to remain difficult for classical computers. For instance, networks based on matrix product states or the multi-scale entanglement renormalization...

Srinivasan Arunachalam, A. Grilo, Tom Gur +2 more·Dec 3, 2020

We establish the first general connection between the design of quantum algorithms and circuit lower bounds. Specifically, let $\mathfrak{C}$ be a class of polynomial-size concepts, and suppose that $\mathfrak{C}$ can be PAC-learned with membership q...

C. Neill, T. McCourt, X. Mi +89 more·Dec 2, 2020

A promising approach to study condensed-matter systems is to simulate them on an engineered quantum platform1–4. However, the accuracy needed to outperform classical methods has not been achieved so far. Here, using 18 superconducting qubits, we prov...

Lucas Kohn, G. Santoro·Dec 2, 2020

We propose an efficient algorithm to numerically solve Anderson impurity problems using matrix product states. By introducing a modified chain mapping we obtain significantly lower entanglement, as compared to all previous attempts, while keeping the...

Bowen Liu, Kaizhi Wang, Dongmei Xiao +1 more·Dec 2, 2020

Various combinatorial optimization NP-hard problems can be reduced to finding the minimizer of an Ising model, which is a discrete mathematical model. It is an intellectual challenge to develop some mathematical tools or algorithms for solving the Is...

R. East, J. J. Van De Wetering, N. Chancellor +1 more·Dec 2, 2020

From Feynman diagrams to tensor networks, diagrammatic representations of computations in quantum mechanics have catalysed progress in physics. These diagrams represent the underlying mathematical operations and aid physical interpretation, but canno...

Cenk Tuysuz, Kristiane Novotny, C. Rieger +7 more·Dec 2, 2020

The Large Hadron Collider (LHC) at the European Organisation for Nuclear Research (CERN) will be upgraded to further increase the instantaneous rate of particle collisions (luminosity) and become the High Luminosity LHC. This increase in luminosity, ...

Samuel Mugel, Mario Abad, M. Bermejo +3 more·Dec 2, 2020

In this paper we propose a hybrid quantum-classical algorithm for dynamic portfolio optimization with minimal holding period. Our algorithm is based on sampling the near-optimal portfolios at each trading step using a quantum processor, and efficient...

R. Movassagh, Yingkai Ouyang·Dec 2, 2020

Implementing robust quantum error correction (QEC) is imperative for harnessing the promise of quantum technologies. We introduce a framework that takes any classical code and explicitly constructs the corresponding QEC code. Our framework can be see...

S. Stein, Ryan L'Abbate, W. Mu +6 more·Dec 1, 2020

Deep neural network powered artificial intelligence has rapidly changed our daily life with various applications. However, as one of the essential steps of deep neural networks, training a heavily-weighted network requires a tremendous amount of comp...

Leonardo Novo, S. Ribeiro·Dec 1, 2020

The formalism of continuous-time quantum walks on graphs has been widely used in the study of quantum transport of energy and information, as well as in the development of quantum algorithms. In experimental settings, however, there is limited contro...

Daniel T. Chen, Yekun Xu, Betis Baheri +5 more·Dec 1, 2020

Recently, there has been a surge of interest for quantum computation for its ability to exponentially speed up algorithms, including machine learning algorithms. However, Tang suggested that the exponential speed up can also be done on a classical co...

L. Buffoni, F. Caruso·Dec 1, 2020

Here we will give a perspective on new possible interplays between machine learning and quantum physics, including also practical cases and applications. We will explore the ways in which machine learning could benefit from new quantum technologies a...

A. Anand, M. Degroote, Alán Aspuru-Guzik·Nov 30, 2020

Natural evolutionary strategies (NES) are a family of gradient-free black-box optimization algorithms. This study illustrates their use for the optimization of randomly-initialized parametrized quantum circuits (PQCs) in the region of vanishing gradi...

Kosuke Fukui, R. N. Alexander, P. van Loock·Nov 30, 2020

Quantum repeaters are a promising platform for realizing long-distance quantum communication and thus could form the backbone of a secure quantum internet, a scalable quantum network, or a distributed quantum computer. Repeater protocols that encode ...

J. Barata, N. Mueller, A. Tarasov +1 more·Nov 30, 2020

Motivated by the parton picture of high energy quantum chromodynamics, we develop a single-particle digitization strategy for the efficient quantum simulation of relativistic scattering processes in a $d+1$ dimensional scalar $\phi^4$ field theory. W...

T. G. Wong·Nov 30, 2020

The task of finding an entry in an unsorted list of $N$ elements famously takes $O(N)$ queries to an oracle for a classical computer and $O(\sqrt{N})$ queries for a quantum computer using Grover's algorithm. Reformulated as a spatial search problem, ...

T. Haug, Kishor Bharti·Nov 30, 2020

We provide a noisy intermediate-scale quantum framework for simulating the dynamics of open quantum systems, generalized time evolution, non-linear differential equations and Gibbs state preparation. Our algorithm does not require any classical–quant...

F. Rozpędek, Kyungjoo Noh, Qiang-Da Xu +2 more·Nov 30, 2020

We propose an architecture of quantum-error-correction-based quantum repeaters that combines techniques used in discrete- and continuous-variable quantum information. Specifically, we propose to encode the transmitted qubits in a concatenated code co...

Siddharth Dangwal, Ritvik Sharma, D. Bhowmik·Nov 29, 2020

We propose a novel algorithm for fast training of variational classifiers by processing multiple samples parallelly. The algorithm can be adapted for any ansatz used in the variational circuit. The presented algorithm utilizes qRAM and other quantum ...