Papers

Thomas Wagner, H. Kampermann, D. Bruß +1 more·Oct 5, 2020

Quantum error correction allows to actively correct errors occurring in a quantum computation when the noise is weak enough. To make this error correction competitive information about the specific noise is required. Traditionally, this information i...

S. Kimmel, R. Witter·Oct 5, 2020

We design quantum algorithms for maximum matching. Working in the query model, in both adjacency matrix and adjacency list settings, we improve on the best known algorithms for general graphs, matching previously obtained results for bipartite graphs...

Jonathan Gorard, Manojna Namuduri, X. Arsiwalla·Oct 5, 2020

Categorical quantum mechanics and the Wolfram model offer distinct but complementary approaches to studying the relationship between diagrammatic rewriting systems over combinatorial structures and the foundations of physics; the objective of the pre...

Yunchao Liu, Srinivasan Arunachalam, K. Temme·Oct 5, 2020

Recently, several quantum machine learning algorithms have been proposed that may offer quantum speed-ups over their classical counterparts. Most of these algorithms are either heuristic or assume that data can be accessed quantum-mechanically, makin...

Rafael I. Nepomechie·Oct 4, 2020

We consider the feasibility of studying the anisotropic Heisenberg quantum spin chain with the Variational Quantum Eigensolver (VQE) algorithm, by treating Bethe states as variational states, and Bethe roots as variational parameters. For short chain...

O. M. Shir, Xi Xing, H. Rabitz·Oct 4, 2020

This paper introduces a multi-level (m-lev) mechanism into Evolution Strategies (ESs) in order to address a class of global optimization problems that could benefit from fine discretization of their decision variables. Such problems arise in engineer...

Samuel Mugel, Enrique Lizaso, R. Orús·Oct 3, 2020

In this paper we briefly review two recent use-cases of quantum optimization algorithms applied to hard problems in finance and economy. Specifically, we discuss the prediction of financial crashes as well as dynamic portfolio optimization. We commen...

Kesha Hietala, Robert Rand, S. Hung +2 more·Oct 3, 2020

As quantum computing progresses steadily from theory into practice, programmers will face a common problem: How can they be sure that their code does what they intend it to do? This paper presents encouraging results in the application of mechanized ...

R. Ruskov, C. Tahan·Oct 3, 2020

We propose entangling operations based on the energy curvature couplings of encoded spin qubits to a superconducting cavity, exploring the nonlinear qubit response to a gate voltage variation. For a two-qubit ($n$-qubit) entangling gate we explore ac...

D. Suess, N. Maraviglia, R. Kueng +6 more·Oct 1, 2020

Linear-optical circuits are elementary building blocks for classical and quantum information processing with light. In particular, due to its monolithic structure, integrated photonics offers great phase-stability and can rely on the large scale manu...

R. Severino, Michele Spasaro, D. Zito·Oct 1, 2020

This paper investigates the implementation of microwave and mm-wave integrated circuits for control and readout of electron/hole spin qubits, as elementary building blocks for future emerging quantum computing technologies. In particular, it summariz...

Sukin Sim, J. Romero, J. Gonthier +1 more·Oct 1, 2020

Variational hybrid quantum–classical algorithms are powerful tools to maximize the use of noisy intermediate-scale quantum devices. While past studies have developed powerful and expressive ansatze, their near-term applications have been limited by t...

·Oct 1, 2020

We explore the effectiveness of high-depth, noiseless, parameteric quantum circuits by challenging their capability to simulate the ground states of quantum many-body Hamiltonians. Even a generic layered circuit Ansatz can approximate the ground stat...

Pramod Padmanabhan, Fumihiko Sugino, Diego Trancanelli·Oct 1, 2020

For a generic n-qubit system, local invariants under the action of SL(2,C)⊗n characterize non-local properties of entanglement. In general, such properties are not immediately apparent and hard to construct. Here we consider two-qubit Yang–Baxter ope...

Kento Oonishi, Tomoki Tanaka, Shumpei Uno +3 more·Oct 1, 2020

Control modular addition is a core arithmetic function, and we must consider the computational cost for actual quantum computers to realize efficient implementation. To achieve a low computational cost in a control modular adder, we focus on minimizi...

A. Hashim, R. Naik, A. Morvan +11 more·Oct 1, 2020

The successful implementation of algorithms on quantum processors relies on the accurate control of quantum bits (qubits) to perform logic gate operations. In this era of noisy intermediate-scale quantum (NISQ) computing, systematic miscalibrations, ...

A. Armenàkas, O. Baker·Oct 1, 2020

We demonstrate a novel method for applying a scientific quantum algorithm - the Grover Algorithm (GA) - to search for rare events in proton-proton collisions at 13 TeV collision energy using CERN's Large Hadron Collider. The search is of an unsorted ...

J. Doi, H. Horii·Oct 1, 2020

Classical computers require large memory resources and computational power to simulate quantum circuits with a large number of qubits. Even supercomputers that can store huge amounts of data face a scalability issue in regard to parallel quantum comp...

Khadeejah Bepari, S. Malik, M. Spannowsky +1 more·Sep 30, 2020

The interpretation of measurements of high-energy particle collisions relies heavily on the performance of full event generators. By far the largest amount of time to predict the kinematics of multi-particle final states is dedicated to the calculati...

V. Nguyen, S. Orbell, D. Lennon +9 more·Sep 30, 2020

Deep reinforcement learning is an emerging machine-learning approach that can teach a computer to learn from their actions and rewards similar to the way humans learn from experience. It offers many advantages in automating decision processes to navi...