Quantum Brain

Papers

Live trends in quantum computing research, updated daily from arXiv.

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13,354 papers in 12 months (+7% vs prior quarter)

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Qubit Platforms

Hardware platform mentions in abstractsPhotonic leads

2,507 papers found

Direct estimation of minimum gate fidelity

Yiping Lu, J. Sim, J. Suzuki +2 more·Apr 6, 2020

With the current interest in building quantum computers, there is a strong need for accurate and efficient characterization of the noise in quantum gate implementations. A key measure of the performance of a quantum gate is the minimum gate fidelity,...

Physics

Classical Optimizers for Noisy Intermediate-Scale Quantum Devices

W. Lavrijsen, Ana Tudor, Juliane Müller +2 more·Apr 6, 2020

We present a collection of optimizers tuned for usage on Noisy Intermediate-Scale Quantum (NISQ) devices. Optimizers have a range of applications in quantum computing, including the Variational Quantum Eigensolver (VQE) and Quantum Approximate Optimi...

Computer SciencePhysics

Implementation of Geometric Quantum Gates on Microwave‐Driven Semiconductor Charge Qubits

Chengxian Zhang, Tao Chen, Xin Wang +1 more·Apr 1, 2020

A semiconductor‐based charge qubit, confined in double quantum dots, can be a platform to implement quantum computing. However, it suffers severely from charge noises. Here, a theoretical framework to implement universal geometric quantum gates in th...

Physics

Small quantum computers and large classical data sets

A. Harrow·Mar 31, 2020

We introduce hybrid classical-quantum algorithms for problems involving a large classical data set X and a space of models Y such that a quantum computer has superposition access to Y but not X. These algorithms use data reduction techniques to const...

Computer SciencePhysics

Solving Large‐Scale Linear Systems of Equations by a Quantum Hybrid Algorithm

M. Perelshtein, A. Pakhomchik, A. Melnikov +5 more·Mar 28, 2020

Today's intermediate‐scale quantum computers, although imperfect, already perform computational tasks that are manifestly beyond the capabilities of modern classical supercomputers. However, so far, quantum‐enabled large‐scale solutions have been rea...

Physics

A Hybrid Quantum-Classical Approach to Mitigating Measurement Errors in Quantum Algorithms

Hyeokjea Kwon, J. Bae·Mar 27, 2020

When noisy intermediate scalable quantum (NISQ) devices are applied in information processing, all of the stages through preparation, manipulation, and measurement of multipartite qubit states contain various types of noise that are generally hard to...

Computer SciencePhysics

A Phononic Bus for Coherent Interfaces Between a Superconducting Quantum Processor, Spin Memory, and Photonic Quantum Networks

T. Neuman, M. Eichenfield, Matthew E. Trusheim +3 more·Mar 18, 2020

We introduce a method for high-fidelity quantum state transduction between a superconducting microwave qubit and the ground state spin system of a solid-state artificial atom, mediated via an acoustic bus connected by piezoelectric transducers. Appli...

Physics

Cross Entropy Hyperparameter Optimization for Constrained Problem Hamiltonians Applied to QAOA

Christoph Roch, Alexander Impertro, Thomy Phan +3 more·Mar 11, 2020

Hybrid quantum-classical algorithms such as the Quantum Approximate Optimization Algorithm (QAOA) are considered as one of the most encouraging approaches for taking advantage of near-term quantum computers in practical applications. Such algorithms ...

Computer SciencePhysics

Circuit design for clique problem and its implementation on quantum computer

Arpita Sanyal, A. Saha, Banani Saha +1 more·Mar 10, 2020

Finding cliques in a graph has several applications for its pattern matching ability. $k$-clique problem, a special case of clique problem, determines whether an arbitrary graph contains a clique of size $k$, has already been addressed in quantum dom...

Computer Science

Gutzwiller hybrid quantum-classical computing approach for correlated materials

Yongxin Yao, Feng Zhang, Caizhuang Wang +2 more·Mar 9, 2020

Rapid progress in noisy intermediate-scale quantum (NISQ) computing technology has led to the development of novel resource-efficient hybrid quantum-classical algorithms, such as the variational quantum eigensolver (VQE), that can address open challe...

Physics

TensorFlow Quantum: A Software Framework for Quantum Machine Learning

·Mar 6, 2020

We introduce TensorFlow Quantum (TFQ), an open source library for the rapid prototyping of hybrid quantum-classical models for classical or quantum data. This framework offers high-level abstractions for the design and training of both discriminative...

PhysicsComputer Science

Considerations for evaluating thermodynamic properties with hybrid quantum-classical computing work flows

Spencer T. Stober, Stuart M. Harwood, Dimitar Trenev +3 more·Mar 4, 2020

Quantum chemistry applications on quantum computers currently rely heavily on the variational quantum eigensolver (VQE) algorithm. This hybrid quantum-classical algorithm aims at finding ground state solutions of molecular systems based on the variat...

Physics

AccQOC: Accelerating Quantum Optimal Control Based Pulse Generation

Jinglei Cheng, Haoqing Deng, Xuehai Qian·Mar 1, 2020

In the last decades, we have witnessed the rapid growth of Quantum Computing. In the current Noisy Intermediate-Scale Quantum (NISQ) era, the capability of a quantum machine is limited by the decoherence time, gate fidelity and the number of Qubits. ...

PhysicsComputer Science

Near-optimal ground state preparation

Lin Lin, Yu Tong·Feb 28, 2020

Preparing the ground state of a given Hamiltonian and estimating its ground energy are important but computationally hard tasks. However, given some additional information, these problems can be solved efficiently on a quantum computer. We assume tha...

Computer SciencePhysicsMathematics

Digital quantum simulation of molecular dynamics and control

Alicia B. Magann, Matthew D. Grace, H. Rabitz +1 more·Feb 28, 2020

Optimally-shaped electromagnetic fields have the capacity to coherently control the dynamics of quantum systems, and thus offer a promising means for controlling molecular transformations relevant to chemical, biological, and materials applications. ...

Computer SciencePhysics

A Quantum Money Solution to the Blockchain Scalability Problem

Andrea Coladangelo, Or Sattath·Feb 27, 2020

We put forward the idea that classical blockchains and smart contracts are potentially useful primitives not only for classical cryptography, but for quantum cryptography as well. Abstractly, a smart contract is a functionality that allows parties to...

PhysicsComputer Science

Is all-electrical silicon quantum computing feasible in the long term?

E. Ferraro, E. Prati·Feb 25, 2020

Abstract The development of the first generation of commercial quantum computers is based on superconductive qubits and trapped ions respectively. Other technologies such as semiconductor quantum dots, neutral ions and photons could in principle prov...

Physics

Policy Gradient based Quantum Approximate Optimization Algorithm

Jiahao Yao, Marin Bukov, Lin Lin·Feb 4, 2020

The quantum approximate optimization algorithm (QAOA), as a hybrid quantum/classical algorithm, has received much interest recently. QAOA can also be viewed as a variational ansatz for quantum control. However, its direct application to emergent quan...

Computer SciencePhysics

Solving Vehicle Routing Problem Using Quantum Approximate Optimization Algorithm

Utkarsh Azad, B. K. Behera, Emad A. Ahmed +2 more·Feb 2, 2020

Intelligent transportation systems (ITS) are a critical component of Industry 4.0 and 5.0, particularly having applications in logistic management. One of their crucial utilization is in supply-chain management and scheduling for optimally routing tr...

Computer SciencePhysics

A hybrid quantum enabled RBM advantage: convolutional autoencoders for quantum image compression and generative learning

Jennifer Sleeman, J. Dorband, M. Halem·Jan 31, 2020

Understanding how the D-Wave quantum computer could be used for machine learning problems is of growing interest. Our work explores the feasibility of using the D-Wave as a sampler for a machine learning task. We describe a hybrid method that combine...

EngineeringComputer SciencePhysics
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