Quantum Brain

Papers

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

Total Papers

27,548

This Month

1,041

Today

0

Research Volume

12,909 papers in 12 months (-5% vs prior quarter)

Research Focus Areas

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

Qubit Platforms

Hardware platform mentions in abstractsPhotonic leads

2,459 papers found

Density of States (Gate) - Controlled Andreev Molecule and Sensor

Xiaofan Shi, Z. Dou, Guoan Li +19 more·Aug 6, 2025

Topological quantum computing typically relies on topological Andreev bound states (ABSs) engineered in hybrid superconductor-semiconductor devices, where gate control offers key advantages. While strong Zeeman fields can induce such states, an alter...

Physics

Advantages of Co-locating Quantum-HPC Platforms: A Survey for Near-Future Industrial Applications

D. Honda, Yuta Nishiyama, Junya Ishikawa +10 more·Aug 6, 2025

We conducted a systematic survey of emerging quantum-HPC platforms, which integrate quantum computers and High-Performance Computing (HPC) systems through co-location. Currently, it remains unclear whether such platforms provide tangible benefits for...

PhysicsComputer Science

Hybrid Quantum-Classical Machine Learning Potential with Variational Quantum Circuits

S. Y. Willow, David ChangMo Yang, Chang Woo·Aug 6, 2025

Quantum algorithms for simulating large and complex molecular systems are still in their infancy, and surpassing state-of-the-art classical techniques remains an ever-receding goal post. A promising avenue of inquiry in the meanwhile is to seek pract...

PhysicsComputer Science

Quantum Temporal Fusion Transformer

Krishnakanta Barik, Goutam Paul·Aug 6, 2025

The \textit{Temporal Fusion Transformer} (TFT), proposed by Lim \textit{et al.}, published in \textit{International Journal of Forecasting} (2021), is a state-of-the-art attention-based deep neural network architecture specifically designed for multi...

Computer SciencePhysics

Path-Integral Formulation of Bosonic Markovian Open Quantum Dynamics with Monte Carlo stochastic trajectories using the Glauber-Sudarshan P, Wigner, and Husimi Q Functions and Hybrids

Toma Yoneya, Kazuya Fujimoto, Yuki Kawaguchi·Aug 4, 2025

The Monte Carlo (MC) trajectory sampling of stochastic differential equations (SDEs) based on the quasiprobabilities, such as the Glauber-Sudarshan P, Wigner, and Husimi Q functions, enables us to investigate bosonic open quantum many-body dynamics d...

cond-mat.quant-gascond-mat.stat-mechQuantum Physics

Evaluating Angle and Amplitude Encoding Strategies for Variational Quantum Machine Learning: their impact on model's accuracy

A. Tudisco, Andrea Marchesin, Maurizio Zamboni +2 more·Aug 1, 2025

Recent advancements in Quantum Computing and Machine Learning have increased attention to Quantum Machine Learning (QML), which aims to develop machine learning models by exploiting the quantum computing paradigm. One of the widely used models in thi...

Computer Science

Swap Network Augmented Ansätze on Arbitrary Connectivity

Teodor Parella-Dilmé, Jakob S. Kottmann, Antonio Acín·Jul 31, 2025

Efficient parametrizations of quantum states are essential for trainable hybrid classical-quantum algorithms. A key challenge in their design consists in adapting to the available qubit connectivity of the quantum processor, which limits the capacity...

Quantum Physics

Search for $t\bar tt\bar tW$ Production at $\sqrt{s} = 13$ TeV Using a Modified Graph Neural Network at the LHC

Syed Haider Ali, A. Ahmad, Muhammad Saiel +1 more·Jul 31, 2025

The simultaneous production of four top quarks in association with a ($W$) boson at $(\sqrt{s} = 13)$ TeV is an rare SM process with a next-to-leading-order (NLO) cross-section of $(6.6^{+2.4}_{-2.6} {ab})$\cite{saiel}. Identifying this process in th...

Physics

Dynamical mean field theory with quantum computing

Thomas Ayral·Jul 31, 2025

Near-term quantum processors are limited in terms of the number of qubits and gates they can afford. They nevertheless give unprecedented access to programmable quantum systems that can efficiently, although imperfectly, simulate quantum time evoluti...

Physics

Dimension reduction with structure-aware quantum circuits for hybrid machine learning

A. Daskin·Jul 31, 2025

Schmidt decomposition of a vector can be understood as writing the singular value decomposition (SVD) in vector form. A vector can be written as a linear combination of tensor product of two dimensional vectors by recursively applying Schmidt decompo...

PhysicsComputer Science

On the Simulation of Conical Intersections in Water and Methanimine Molecules Via Variational Quantum Algorithms

Samir Belaloui, N. Belaloui, Achour Benslama·Jul 30, 2025

We investigate the electronic structure of methanimine (CH2NH) and water (H2O) molecules in an effort to locate conical intersections (CIs) using variational quantum algorithms. Our approach implements and compares a range of hybrid quantum-classical...

Physics

A Bit of Freedom Goes a Long Way: Classical and Quantum Algorithms for Reinforcement Learning under a Generative Model

A. Ambainis, J. F. Doriguello, Debbie Lim·Jul 30, 2025

We propose novel classical and quantum online algorithms for learning finite-horizon and infinite-horizon average-reward Markov Decision Processes (MDPs). Our algorithms are based on a hybrid exploration-generative reinforcement learning (RL) model w...

Computer ScienceMathematicsPhysics

Hybrid Quantum Classical Surrogate for Real Time Inverse Finite Element Modeling in Digital Twins

A. Alavi, Sanduni Jayasinghe, M. Mahmoodian +3 more·Jul 30, 2025

Large-scale civil structures, such as bridges, pipelines, and offshore platforms, are vital to modern infrastructure, where unexpected failures can cause significant economic and safety repercussions. Although finite element (FE) modeling is widely u...

PhysicsComputer Science

Structured quantum learning via em algorithm for Boltzmann machines

Takeshi Kimura, Kohtaro Kato, Masahito Hayashi·Jul 29, 2025

Quantum Boltzmann machines (QBMs) are generative models with potential advantages in quantum machine learning, yet their training is fundamentally limited by the barren plateau problem, where gradients vanish exponentially with system size. We introd...

Quantum Physicscs.LG

Quantum Solvers: Predictive Aeroacoustic&Aerodynamic modeling

Nis-Luca van Hulst, Theofanis Panagos, Greta Sophie Reese +2 more·Jul 29, 2025

This technical report presents our winning contribution to the 2024 Airbus and BMW Group Quantum Computing Challenge under the category'Quantum Solvers'. This submission addresses efficient simulation in industrial CFD using (i) quantum-inspired algo...

Physics

Robust qubit interactions mediated by photonic topological edge states

Boris Gurevich, Weihua Xie, Mohsen Yarmohammadi +1 more·Jul 28, 2025

We investigate the coupling of two spatially separated qubits via topologically protected edge states in a two-dimensional Hofstadter lattice. In this hybrid platform, the qubits are coupled to distinct edge sites of the lattice, enabling long-range ...

Quantum Physicscond-mat.str-el

Quantum Reinforcement Learning by Adaptive Non-Local Observables

Hsin-Yi Lin, Samuel Yen-Chi Chen, H. Tseng +1 more·Jul 25, 2025

Hybrid quantum-classical frameworks leverage quantum computing for machine learning; however, variational quantum circuits (VQCs) are limited by local measurements. We introduce an adaptive non-local observable (ANO) paradigm within VQCs for quantum ...

Computer SciencePhysics

Towards System-Level Quantum-Accelerator Integration

Ralf Ramsauer, Wolfgang Mauerer·Jul 25, 2025

Quantum computers are often treated as experimental add-ons that are loosely coupled to classical infrastructure through high-level interpreted languages and cloud-like orchestration. However, future deployments in both, high-performance computing (H...

PhysicsComputer Science

Quantum-Efficient Convolution through Sparse Matrix Encoding and Low-Depth Inner Product Circuits

Mohammad Rasoul Roshanshah, Payman Kazemikhah, Hossein Aghababa·Jul 25, 2025

Convolution operations are foundational to classical image processing and modern deep learning architectures, yet their extension into the quantum domain has remained algorithmically and physically costly due to inefficient data encoding and prohibit...

Physics

FD4QC: Application of Classical and Quantum-Hybrid Machine Learning for Financial Fraud Detection A Technical Report

Matteo Cardaioli, Luca Marangoni, Giada Martini +5 more·Jul 25, 2025

The increasing complexity and volume of financial transactions pose significant challenges to traditional fraud detection systems. This technical report investigates and compares the efficacy of classical, quantum, and quantum-hybrid machine learning...

Computer Science
Quantum Intelligence

Ask about quantum research, companies, or market developments.