Quantum Brain

Papers

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

Total Papers

30,856

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902

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0

Research Volume

15,145 papers in 12 months (-14% vs prior quarter)

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Papers by research theme (12 months). Hover for details.

Qubit Platforms

Hardware platform mentions in abstractsPhotonic leads

30,856 papers found

Stabilizing Remote Entanglement via Waveguide Dissipation

Parth S. Shah, Frank Yang, Chaitali Joshi +1 more·Feb 24, 2024

Distributing entanglement between remote sites is integral to quantum networks. Here, we demonstrate the autonomous stabilization of remote entanglement between a pair of noninteracting superconducting qubits connected by an open waveguide on a chip....

Physics

Lower bounds for quantum-inspired classical algorithms via communication complexity

Nikhil S. Mande, Changpeng Shao·Feb 24, 2024

Quantum-inspired classical algorithms provide us with a new way to understand the computational power of quantum computers for practically-relevant problems, especially in machine learning. In the past several years, numerous efficient algorithms for...

PhysicsComputer Science

Progressive-Proximity Bit-Flipping for Decoding Surface Codes

Michele Pacenti, Mark F. Flanagan, Dimitris Chytas +1 more·Feb 24, 2024

Topological quantum codes, such as toric and surface codes, are excellent candidates for hardware implementation due to their robustness against errors and their local interactions between qubits. However, decoding these codes efficiently remains a c...

PhysicsComputer ScienceMathematics

Ultrafast superconducting qubit readout with the quarton coupler

Yufeng Ye, Jeremy B Kline, Sean Chen +2 more·Feb 24, 2024

Fast, high-fidelity, and quantum nondemolition (QND) qubit readout is an essential element of quantum information processing. For superconducting qubits, state-of-the-art readout is based on a dispersive cross-Kerr coupling between a qubit and its re...

PhysicsMedicine

Curve fitting on a quantum annealer for an advanced navigation method

Philipp Isserstedt, Daniel Jaroszewski, Wolfgang Mergenthaler +2 more·Feb 23, 2024

We explore the applicability of quantum annealing to the approximation task of curve fitting. To this end, we consider a function that shall approximate a given set of data points and is written as a finite linear combination of standardized function...

math.OCQuantum Physics

Shell-model study of 58Ni using quantum computing algorithm

Bharti Bhoy, P. Stevenson·Feb 23, 2024

This study presents a simulated quantum computing approach for the investigation into the shell-model energy levels of 58Ni through the application of the variational quantum eigensolver (VQE) method in combination with a problem-specific ansatz. The...

Physics

Resisting High-Energy Impact Events through Gap Engineering in Superconducting Qubit Arrays.

M. McEwen, K. Miao, J. Atalaya +24 more·Feb 23, 2024

Quantum error correction (QEC) provides a practical path to fault-tolerant quantum computing through scaling to large qubit numbers, assuming that physical errors are sufficiently uncorrelated in time and space. In superconducting qubit arrays, high-...

MedicinePhysics

Modeling phonon-mediated quasiparticle poisoning in superconducting qubit arrays

E. Yelton, C. P. Larson, V. Iaia +8 more·Feb 23, 2024

Correlated errors caused by ionizing radiation impacting superconducting qubit chips are problematic for quantum error correction. Such impacts generate quasiparticle (QP) excitations in the qubit electrodes, which temporarily reduce qubit coherence ...

Physics

Simulation of dissipative dynamics without interferometers

Fabr'icio Lustosa, R. Serra, Luciano S. Cruz +1 more·Feb 23, 2024

Developing techniques that reduce experimental complexity and minimize errors is of utmost importance for modeling quantum channels. In general, quantum simulators are focused on universal algorithms, whose practical implementation requires extra qub...

Physics

Calculating the expected value function of a two-stage stochastic optimization program with a quantum algorithm

Caleb Rotello, Peter Graf, Matthew Reynolds +3 more·Feb 23, 2024

Two-stage stochastic programming is a problem formulation for decision-making under uncertainty. In the first stage, the actor makes a best"here and now"decision in the presence of uncertain quantities that will be resolved in the future, represented...

Physics

Sparse Probabilistic Synthesis of Quantum Operations

Bálint Koczor·Feb 23, 2024

Successful implementations of quantum technologies require protocols and algorithms that use as few quantum resources as possible. However, many important quantum operations, such as continuous rotation gates in quantum computing or broadband pulses ...

Physics

Entanglement Detection by Approximate Entanglement Witnesses

Samuel Dai, Ning Bao·Feb 22, 2024

The problem of determining whether a given quantum state is separable is known to be computationally difficult. We develop an approach to this problem based on approximations of convex polytopes in high dimensions. By showing that a convex polytope c...

Quantum Physics

Neutron-nucleus dynamics simulations for quantum computers

Soorya Rethinasamy, Ethan Guo, Alexander Wei +2 more·Feb 22, 2024

With a view toward addressing the explosive growth in the computational demands of nuclear structure and reactions modeling, we develop a novel quantum algorithm for neutron-nucleus simulations with general potentials, which provides acceptable bound...

Quantum Physicsnucl-th

Spectral invariance and maximality properties of the frequency spectrum of quantum neural networks

Patrick Holzer, Ivica Turkalj·Feb 22, 2024

We analyze the frequency spectrum of Quantum Neural Networks (QNNs) using Minkowski sums, which yields a compact algebraic description and permits explicit computation. Using this description, we prove several maximality results for broad classes of ...

Quantum Physicscs.LGstat.ML

Quantum-Annealing-Inspired Algorithms for Track Reconstruction at High-Energy Colliders

Hideki Okawa, Qingguo Zeng, Xian-Zhe Tao +1 more·Feb 22, 2024

Charged particle reconstruction or track reconstruction is one of the most crucial components of pattern recognition in high-energy collider physics. It is known to entail enormous consumption of computing resources, especially when the particle mult...

PhysicsComputer Science

Quantum Theory and Application of Contextual Optimal Transport

Nicola Mariella, A. Akhriev, F. Tacchino +9 more·Feb 22, 2024

Optimal Transport (OT) has fueled machine learning (ML) across many domains. When paired data measurements $(\boldsymbol{\mu}, \boldsymbol{\nu})$ are coupled to covariates, a challenging conditional distribution learning setting arises. Existing appr...

Computer ScienceMathematicsBiologyPhysics

The Stability of Gapped Quantum Matter and Error-Correction with Adiabatic Noise

A. Lavasani, Sagar Vijay·Feb 22, 2024

The codespace of a quantum error-correcting code can often be identified with the degenerate ground-space within a gapped phase of quantum matter. We argue that the stability of such a phase is directly related to a set of coherent error processes ag...

Physics

Dynamical quantum maps for single-qubit gates under universal non-Markovian noise

J. M. Sánchez Velázquez, A. Steiner, R. Freund +4 more·Feb 22, 2024

Noise is both ubiquitous and generally deleterious in settings where precision is required. This is especially true in the quantum technology sector where system utility typically decays rapidly under its influence. Understanding the noise in quantum...

Physics

On Schrödingerization based quantum algorithms for linear dynamical systems with inhomogeneous terms

Shi Jin, Nana Liu, Chuwen Ma·Feb 22, 2024

We analyze the Schr\"odingerization method for quantum simulation of a general class of non-unitary dynamics with inhomogeneous source terms. The Schr\"odingerization technique, introduced in [31], transforms any linear ordinary and partial different...

Computer ScienceMathematics

A Quick Introduction to Quantum Machine Learning for Non-Practitioners

Ethan N. Evans, Dominic M. Byrne, Matthew Cook·Feb 22, 2024

This paper provides an introduction to quantum machine learning, exploring the potential benefits of using quantum computing principles and algorithms that may improve upon classical machine learning approaches. Quantum computing utilizes particles g...

Computer SciencePhysics
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