Quantum Brain

Papers

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

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13,147 papers in 12 months (+1% vs prior quarter)

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

Qubit Platforms

Hardware platform mentions in abstractsPhotonic leads

6,169 papers found

Solving Linear Systems of Equations with the Quantum HHL Algorithm: A Tutorial on the Physical and Mathematical Foundations for Undergraduate Students

Lucas Q. Galvão, Anna Beatriz M. de Souza, Alexandre Oliveira S. Santos +2 more·Sep 20, 2025

Quantum computing enables the efficient resolution of complex problems, often outperforming classical methods across various applications. In 2009, Harrow, Hassidim and Lloyd proposed an algorithm for solving linear systems of equations, demonstratin...

Quantum Physicsphysics.ed-ph

Quantum Generative Adversarial Autoencoders: Learning latent representations for quantum data generation

Naipunnya Raj, Rajiv Sangle, Avinash Singh +1 more·Sep 19, 2025

In this work, we introduce the Quantum Generative Adversarial Autoencoder (QGAA), a quantum model for generation of quantum data. The QGAA consists of two components: (a) Quantum Autoencoder (QAE) to compress quantum states, and (b) Quantum Generativ...

Quantum Physicscs.LGstat.ML

Theory of Multi-photon Processes for Applications in Quantum Control

Longxiang Huang, Jacquelin Luneau, Johannes Schirk +5 more·Sep 19, 2025

We present a general theoretical framework for evaluating multi-photon processes in periodically driven quantum systems, which have been identified as a versatile tool for engineering and controlling nontrivial interactions in various quantum technol...

Quantum Physics

Scalable Quantum Reinforcement Learning on NISQ Devices with Dynamic-Circuit Qubit Reuse and Grover Optimization

Thet Htar Su, Shaswot Shresthamali, Masaaki Kondo·Sep 19, 2025

A scalable and resource-efficient quantum reinforcement learning framework is presented that eliminates the linear qubit-scaling barrier in multi-step quantum Markov decision processes (QMDPs). The proposed framework integrates a QMDP formulation, dy...

Quantum Physicscs.LG

Products between block-encodings

Dekuan Dong, Yingzhou Li, Jungong Xue·Sep 19, 2025

Block-encoding is a standard framework for embedding matrices into unitary operators in quantum algorithms. Efficient implementation of products between block-encoded matrices is crucial for applications such as Hamiltonian simulation and quantum lin...

Quantum Physics

Task-Oriented Gaussian Optimization for Non-Gaussian Resources in Continuous-Variable Quantum Computation

Boxuan Jing, Feng-Xiao Sun, Qiongyi He·Sep 19, 2025

In continuous-variable systems, non-Gaussian resources are essential for achieving universal quantum computation that lies beyond classical simulation. Among the candidate states, the cubic phase state stands out as the simplest form of single-mode n...

Quantum Physics

Hamiltonian learning via quantum Zeno effect

Giacomo Franceschetto, Egle Pagliaro, Luciano Pereira +2 more·Sep 19, 2025

Determining the Hamiltonian of a quantum system is essential for understanding its dynamics and validating its behavior. Hamiltonian learning provides a data-driven approach to reconstruct the generator of the dynamics from measurements on the evolve...

Quantum Physics

Hamiltonian truncation and quantum simulation of strong-field QED beyond tree level

Patrick Draper, Luis Hidalgo, Anton Ilderton·Sep 19, 2025

Quantum electrodynamics in strong background fields provides an interesting class of problems for classical and quantum simulation. In this paper we formulate simulations of polarization (helicity) flip for a photon colliding with a high-intensity pl...

hep-phhep-latQuantum Physics

Discrete Flow-Based Generative Models for Measurement Optimization in Quantum Computing

Isaac L. Huidobro-Meezs, Jun Dai, Rodrigo A. Vargas-Hernández·Sep 18, 2025

Achieving chemical accuracy in quantum simulations is often constrained by the measurement bottleneck: estimating operators requires a large number of shots, which remains costly even on fault-tolerant devices and is further exacerbated on today's no...

Quantum Physics

Dispersion Relations in Two- and Three-Dimensional Quantum Systems

Valeriia Bilokon, Elvira Bilokon, Illya Lukin +2 more·Sep 18, 2025

Extracting momentum-resolved excitation spectra in strongly correlated quantum systems remains a major challenge, especially beyond one spatial dimension. We present an efficient tensor-network approach to compute dispersion relations via imaginary-t...

Quantum Physicscond-mat.str-el

Fault-tolerant quantum computing with a high-rate symplectic double code

Naoyuki Kanomata, Hayato Goto·Sep 18, 2025

High-rate and large-distance quantum codes are expected to make fault-tolerant quantum computing more efficient, but most of them lack efficient fault-tolerant encoded-state preparation methods. We propose such a fault-tolerant encoder for a [[30, 6,...

Quantum Physics

Strong converse exponent of channel interconversion

Aadil Oufkir, Yongsheng Yao, Mario Berta·Sep 18, 2025

In their seminal work, Bennett et al. [IEEE Trans. Inf. Theory (2002)] showed that, with sufficient shared randomness, one noisy channel can simulate another at a rate equal to the ratio of their capacities. We establish that when coding above this c...

Quantum Physicscs.IT

TITAN: A Trajectory-Informed Technique for Adaptive Parameter Freezing in Large-Scale VQE

Yifeng Peng, Xinyi Li, Samuel Yen-Chi Chen +4 more·Sep 18, 2025

Variational quantum Eigensolver (VQE) is a leading candidate for harnessing quantum computers to advance quantum chemistry and materials simulations, yet its training efficiency deteriorates rapidly for large Hamiltonians. Two issues underlie this bo...

Quantum PhysicsAI

Quantum Gambling: Best-Arm Strategies for Generator Selection in Adaptive Variational Algorithms

Rick Huang, Artur F. Izmaylov·Sep 18, 2025

Adaptive variational algorithms suffer from prohibitively high measurement costs during the generator selection step, since energy gradients must be estimated for a large operator pool. This scaling bottleneck limits their applicability to larger mol...

Quantum Physicsphysics.chem-ph

Red Teaming Quantum-Resistant Cryptographic Standards: A Penetration Testing Framework Integrating AI and Quantum Security

P. Radanliev·Sep 18, 2025

Quantum computing and artificial intelligence (AI) are transforming the cybersecurity landscape, dictating a reassessment of cryptographic resilience in the face of emerging threats. This study presents a structured approach to evaluating vulnerabili...

Computer ScienceEngineering

Scaling Hybrid Quantum-HPC Applications with the Quantum Framework

Srikar Chundury, Amir Shehata, Seongmin Kim +6 more·Sep 17, 2025

Hybrid quantum-high performance computing (Q-HPC) workflows are emerging as a key strategy for running quantum applications at scale in current noisy intermediate-scale quantum (NISQ) devices. These workflows must operate seamlessly across diverse si...

Quantum Physicscs.DC

Quantum advantage without exponential concentration: Trainable kernels for symmetry-structured data

Laura J. Henderson, Kerstin Beer, Salini Karuvade +3 more·Sep 17, 2025

Quantum kernel methods promise enhanced expressivity for learning structured data, but their usefulness has been limited by kernel concentration and barren plateaus. Both effects are mathematically equivalent and suppress trainability. We analyticall...

Quantum Physicsphysics.data-an

Probing the meV QCD Axion with the $\texttt{SQWARE}$ Quantum Semiconductor Haloscope

Jaanita Mehrani, Tao Xu, Andrey Baydin +6 more·Sep 17, 2025

We propose the Semiconductor-Quantum-Well Axion Radiometer Experiment ($\texttt{SQWARE}$) -- a new experimental platform for direct detection of axion dark matter in the meV mass range -- based on resonantly enhanced axion-photon conversion through t...

hep-phastro-ph.COMesoscale Physicsphysics.ins-det

Quantum Utility in Simulating the Real-time Dynamics of the Fermi-Hubbard Model using Superconducting Quantum Computers

Talal Ahmed Chowdhury, Vladimir Korepin, Vincent R. Pascuzzi +1 more·Sep 17, 2025

The Fermi-Hubbard model is a fundamental model in condensed matter physics that describes strongly correlated electrons. On the other hand, quantum computers are emerging as powerful tools for exploring the complex dynamics of these quantum many-body...

Quantum Physicscond-mat.str-el

A Closeness Centrality-based Circuit Partitioner for Quantum Simulations

Doru Thom Popovici, Harlin Lee, Mauro Del Ben +5 more·Sep 17, 2025

Simulating quantum circuits (QC) on high-performance computing (HPC) systems has become an essential method to benchmark algorithms and probe the potential of large-scale quantum computation despite the limitations of current quantum hardware. Howeve...

Quantum Physicscs.DC
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