Variational Quantum Algorithms

Abstract

Applications such as simulating complicated quantum systems or solving large-scale linear algebra problems are very challenging for classical computers due to the extremely high computational cost. Quantum computers promise a solution, although fault-tolerant quantum computers will likely not be available in the near future. Current quantum devices have serious constraints, including limited numbers of qubits and noise processes that limit circuit depth. Variational Quantum Algorithms (VQAs), which use a classical optimizer to train a parametrized quantum circuit, have emerged as a leading strategy to address these constraints. VQAs have now been proposed for essentially all applications that researchers have envisioned for quantum computers, and they appear to the best hope for obtaining quantum advantage. Nevertheless, challenges remain including the trainability, accuracy, and efficiency of VQAs. Here we overview the field of VQAs, discuss strategies to overcome their challenges, and highlight the exciting prospects for using them to obtain quantum advantage.

arXiv commentReview Article. 33 pages, 7 figures. Updated to published version

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• A super-polynomial quantum-classical separation for density modelling
• Enhanced estimation of quantum properties with common randomized measurements
• Robustness of quantum algorithms against coherent control errors
• Simulating fluid flows with quantum computing
• Neural Quantum Embedding: Pushing the Limits of Quantum Supervised Learning
• Networked Quantum Services
• Extending the Variational Quantum Eigensolver to Finite Temperatures
• Recommending Solution Paths for Solving Optimization Problems with Quantum Computing
• Local minima in quantum systems
• Block-encoding dense and full-rank kernels using hierarchical matrices: applications in quantum numerical linear algebra
• The Unified Effect of Data Encoding, Ansatz Expressibility and Entanglement on the Trainability of HQNNs
• An open-source modular framework for quantum computing
• Scalable Quantum Simulations of Scattering in Scalar Field Theory on 120 Qubits
• Quantum Circuit AutoEncoder
• Quantum Neural Estimation of Entropies
• The quantum cost function concentration dependency on the parametrization expressivity
• Connecting geometry and performance of two-qubit parameterized quantum circuits
• Activation of metrologically useful genuine multipartite entanglement
• Effects of quantum resources on the statistical complexity of quantum circuits
• Variational dynamics as a ground-state problem on a quantum computer
• Quantum version of the k-NN classifier based on a quantum sorting algorithm
• Assessing and Advancing the Potential of Quantum Computing: A NASA Case Study
• Quantum-assisted Monte Carlo algorithms for fermions
• Quantum circuits for the preparation of spin eigenfunctions on quantum computers
• Atomic Quantum Technologies for Quantum Matter and Fundamental Physics Applications
• Compact quantum algorithms for time-dependent differential equations
• Classification of Hybrid Quantum-Classical Computing
• Variational quantum algorithms for Poisson equations based on the decomposition of sparse Hamiltonians
• Quantum algorithms for scientific computing
• Symmetry breaking in geometric quantum machine learning in the presence of noise
• Solution of SAT Problems with the Adaptive-Bias Quantum Approximate Optimization Algorithm
• Problem specific classical optimization of Hamiltonian simulation
• Transfer learning of optimal QAOA parameters in combinatorial optimization
• Quantum Annealing for Neural Network optimization problems: a new approach via Tensor Network simulations
• High-Round QAOA for MAX $k$-SAT on Trapped Ion NISQ Devices
• Ensemble-learning error mitigation for variational quantum shallow-circuit classifiers
• Simulating gauge theories with variational quantum eigensolvers in superconducting microwave cavities
• Quantum Energy Landscape and VQA Optimization
• Variational Quantum-Neural Hybrid Error Mitigation
• Qibolab: an open-source hybrid quantum operating system
• Approximately Equivariant Quantum Neural Network for $p4m$ Group Symmetries in Images
• Hybrid Quantum-Classical Heuristic for the Bin Packing Problem
• Seven Useful Questions in Density Functional Theory
• Virtual quantum resource distillation: General framework and applications
• Testing symmetry on quantum computers
• Q${}^2$Chemistry: A quantum computation platform for quantum chemistry
• Extension of the Trotterized Unitary Coupled Cluster to Triple Excitations
• Quantum Latent Diffusion Models
• Multiobjective variational quantum optimization for constrained problems: an application to Cash Management
• Variational determination of multi-qubit geometrical entanglement in NISQ computers
• On-Premises Superconducting Quantum Computer for Education and Research
• Gutzwiller wave function on a quantum computer using a discrete Hubbard-Stratonovich transformation
• Ability of error correlations to improve the performance of variational quantum algorithms
• Dynamical mean-field theory for the Hubbard-Holstein model on a quantum device
• Towards Finding an Optimal Flight Gate Assignment on a Digital Quantum Computer
• Trainability and Expressivity of Hamming-Weight Preserving Quantum Circuits for Machine Learning
• Calibrating the Classical Hardness of the Quantum Approximate Optimization Algorithm
• Variational Quantum Cloning: Improving Practicality for Quantum Cryptanalysis
• Guaranteed efficient energy estimation of quantum many-body Hamiltonians using ShadowGrouping
• Leveraging Randomized Compiling for the QITE Algorithm
• Learning How to Dynamically Decouple
• What can we learn from quantum convolutional neural networks?
• Encoding trade-offs and design toolkits in quantum algorithms for discrete optimization: coloring, routing, scheduling, and other problems
• Natural parameterized quantum circuit
• Mixer-Phaser Ansätze for Quantum Optimization with Hard Constraints
• Measurement optimization of variational quantum simulation by classical shadow and derandomization
• On the universality of $S_n$-equivariant $k$-body gates
• Variational quantum solutions to the Shortest Vector Problem
• A Perspective on Quantum Computing Applications in Quantum Chemistry using 25--100 Logical Qubits
• Taming quantum systems: A tutorial for using shortcuts-to-adiabaticity, quantum optimal control, and reinforcement learning
• Mitigating errors by quantum verification and post-selection
• Correlations enable lossless ergotropy transport
• Impact of decoherence on the fidelity of quantum gates leaving the computational subspace
• Optimizing edge state transfer in a Su-Schrieffer-Heeger chain via hybrid analog-digital strategies
• Pauli path simulations of noisy quantum circuits beyond average case
• Parallel tomography of quantum non-demolition measurements in multi-qubit devices
• Jarzynski-like Equality of Nonequilibrium Information Production Based on Quantum Cross Entropy
• EHA: Entanglement-variational Hardware-efficient Ansatz for Eigensolvers
• Continuous-variable quantum approximate optimization on a programmable photonic quantum processor
• Quantum Computing and Tensor Networks for Laminate Design: A Novel Approach to Stacking Sequence Retrieval
• Computationally Efficient Quantum Expectation with Extended Bell Measurements
• Simulation of a Variational Quantum Perceptron using Grover's Algorithm
• Improving the speed of variational quantum algorithms for quantum error correction
• AI and Quantum Computing in Binary Photocatalytic Hydrogen Production
• Variational quantum state discriminator for supervised machine learning
• Tensor-network-assisted variational quantum algorithm
• Towards Efficient Quantum Hybrid Diffusion Models
• Variational Quantum Algorithms for Semidefinite Programming
• Non-Markovian feedback for optimized quantum error correction
• Realization of a quantum neural network using repeat-until-success circuits in a superconducting quantum processor
• Introducing Non-Linear Activations into Quantum Generative Models
• Semisupervised Anomaly Detection using Support Vector Regression with Quantum Kernel
• Automatic Generation of an Efficient Less-Than Oracle for Quantum Amplitude Amplification
• Retrieving past quantum features with deep hybrid classical-quantum reservoir computing
• Variational quantum algorithms for scanning the complex spectrum of non-Hermitian systems
• Beyond unital noise in variational quantum algorithms: noise-induced barren plateaus and limit sets
• Thermal variational quantum simulation on a superconducting quantum processor
• Fermionic approach to variational quantum simulation of Kitaev spin models
• A blueprint for a Digital-Analog Variational Quantum Eigensolver using Rydberg atom arrays
• Long-lived Particles Anomaly Detection with Parametrized Quantum Circuits
• Randomized adaptive quantum state preparation
• Algorithmic Shadow Spectroscopy
• A Parameter Setting Heuristic for the Quantum Alternating Operator Ansatz
• A Benchmarking Study of Quantum Algorithms for Combinatorial Optimization
• Quantum Chemistry Calculations using Energy Derivatives on Quantum Computers
• A Privacy-Preserving Federated Framework with Hybrid Quantum-Enhanced Learning for Financial Fraud Detection
• Mitigated barren plateaus in the time-nonlocal optimization of analog quantum-algorithm protocols
• Quantum computing Floquet energy spectra
• Automatic quantum circuit encoding of a given arbitrary quantum state
• Combinatorial Optimization with Quantum Computers
• Binary Control Pulse Optimization for Quantum Systems
• Observation of a non-Hermitian supersonic mode on a trapped-ion quantum computer
• Quantum-machine-learning channel discrimination
• Quantum Algorithms for Inverse Participation Ratio Estimation in multi-qubit and multi-qudit systems
• Spin coupling is all you need: Encoding strong electron correlation in molecules on quantum computers
• Boundary Treatment for Variational Quantum Simulations of Partial Differential Equations on Quantum Computers
• General quantum correlation from nonreal values of Kirkwood-Dirac quasiprobability over orthonormal product bases
• Variational quantum iterative power algorithms for global optimization
• Quantum computing through the lens of control: A tutorial introduction
• A quantum annealing-sequential quadratic programming assisted finite element simulation for non-linear and history-dependent mechanical problems
• Learning fermionic correlations by evolving with random translationally invariant Hamiltonians
• Solving The Vehicle Routing Problem via Quantum Support Vector Machines
• Towards a Quantum Simulation of Nonlinear Sigma Models with a Topological Term
• Optimizing Variational Quantum Algorithms with qBang: Efficiently Interweaving Metric and Momentum to Navigate Flat Energy Landscapes
• Analyzing variational quantum landscapes with information content
• Optimizing Quantum Algorithms on Bipotent Architectures
• Inferring physical properties of symmetric states from the fewest copies
• A compiler for universal photonic quantum computers
• The battle of clean and dirty qubits in the era of partial error correction
• Resource analysis of quantum algorithms for coarse-grained protein folding models
• Constrained and Vanishing Expressivity of Quantum Fourier Models
• Exploiting In-Constraint Energy in Constrained Variational Quantum Optimization
• Partitioning Quantum Chemistry Simulations with Clifford Circuits
• Demonstration of a bosonic quantum classifier with data re-uploading
• When Federated Learning Meets Quantum Computing: Survey and Research Opportunities
• Nonstabilizerness dynamics in many-body localized systems
• Variational quantum eigensolver with linear depth problem-inspired ansatz for solving portfolio optimization in finance
• Beyond MP2 initialization for unitary coupled cluster quantum circuits
• Opportunities and challenges of quantum computing for climate modelling
• Hybrid quantum learning with data re-uploading on a small-scale superconducting quantum simulator
• Convergence of Digitized-Counterdiabatic QAOA: circuit depth versus free parameters
• Sampling Error Analysis in Quantum Krylov Subspace Diagonalization
• Optimizing Quantum Convolutional Neural Network Architectures for Arbitrary Data Dimension
• Hybrid discrete-continuous compilation of trapped-ion quantum circuits with deep reinforcement learning
• Expressivity of Variational Quantum Machine Learning on the Boolean Cube
• Symmetry-informed transferability of optimal parameters in the Quantum Approximate Optimization Algorithm
• Dissipative variational quantum algorithms for Gibbs state preparation
• Estimating the randomness of quantum circuit ensembles up to 50 qubits
• Measurement-induced entanglement phase transitions in variational quantum circuits
• Noise-induced shallow circuits and absence of barren plateaus
• Quantum Goemans-Williamson Algorithm with the Hadamard Test and Approximate Amplitude Constraints
• Quantum variational learning for entanglement witnessing
• Quantum support vector data description for anomaly detection
• Algorithm-Oriented Qubit Mapping for Variational Quantum Algorithms
• Avoiding Barren Plateaus with Entanglement
• Low-depth Clifford circuits approximately solve MaxCut
• Quantum Information Driven Ansatz (QIDA): shallow-depth empirical quantum circuits from Quantum Chemistry
• Leveraging Analog Quantum Computing with Neutral Atoms for Solvent Configuration Prediction in Drug Discovery
• A Quantum Leaky Integrate-and-Fire Spiking Neuron and Network
• Quantum Algorithms for Testing Hamiltonian Symmetry
• Entanglement-induced provable and robust quantum learning advantages
• Adaptive projected variational quantum dynamics
• Distributed Quantum Computing: Applications and Challenges
• Experimental demonstration of a high-fidelity virtual two-qubit gate
• Resource estimations for the Hamiltonian simulation in correlated electron materials
• Kernel-based quantum regressor models learn non-Markovianity
• Explainable Representation Learning of Small Quantum States
• Towards chemical accuracy with shallow quantum circuits: A Clifford-based Hamiltonian engineering approach
• Fermionic Simulators for Enhanced Scalability of Variational Quantum Simulation
• Quantum Lazy Training
• Accumulative reservoir construction: Bridging continuously relaxed and periodically refreshed extended reservoirs
• QAOA-MC: Markov chain Monte Carlo enhanced by Quantum Alternating Operator Ansatz
• Unitary Coupled Cluster: Seizing the Quantum Moment
• Measurement-based infused circuits for variational quantum eigensolvers
• Quantum Fourier Iterative Amplitude Estimation
• Coarse grained intermolecular interactions on quantum processors
• A Quantum Hopfield Associative Memory Implemented on an Actual Quantum Processor
• Robustness of Variational Quantum Algorithms against stochastic parameter perturbation
• Variational Quantum Algorithms for Trace Distance and Fidelity Estimation
• Can shallow quantum circuits scramble local noise into global white noise?
• Jet Discrimination with Quantum Complete Graph Neural Network
• Parameterized quantum circuits as universal generative models for continuous multivariate distributions
• Extending the reach of quantum computing for materials science with machine learning potentials
• Emergence of noise-induced barren plateaus in arbitrary layered noise models
• Investigating the Effect of Noise on the Training Performance of Hybrid Quantum Neural Networks
• Splitting and Parallelizing of Quantum Convolutional Neural Networks for Learning Translationally Symmetric Data
• Hückel Molecular Orbital Theory on a Quantum Computer: A Scalable System-Agnostic Variational Implementation with Compact Encoding
• Programmable adiabatic demagnetization for systems with trivial and topological excitations
• Faster variational quantum algorithms with quantum kernel-based surrogate models
• Guided-SPSA: Simultaneous Perturbation Stochastic Approximation assisted by the Parameter Shift Rule
• Variational approach to photonic quantum circuits via the parameter shift rule
• Sequential optimal selection of a single-qubit gate and its relation to barren plateau in parameterized quantum circuits
• Information recoverability of noisy quantum states
• Laziness, Barren Plateau, and Noise in Machine Learning
• A Photonic Parameter-shift Rule: Enabling Gradient Computation for Photonic Quantum Computers
• Unified multivariate trace estimation and quantum error mitigation
• Identification of topological phases using classically-optimized variational quantum eigensolver
• Analog quantum variational embedding classifier
• Near-term Efficient Quantum Algorithms for Entanglement Analysis
• NISQ-compatible approximate quantum algorithm for unconstrained and constrained discrete optimization
• Quantum Federated Learning for Multimodal Data: A Modality-Agnostic Approach
• F-Divergences and Cost Function Locality in Generative Modelling with Quantum Circuits
• Inferring Quantum Network Topology using Local Measurements
• Symmetry-invariant quantum machine learning force fields
• Numerical solution of nonlinear Schrödinger equation by a hybrid pseudospectral-variational quantum algorithm
• Assessing the Impact of Noise on Quantum Neural Networks: An Experimental Analysis
• Bayesian Learning of Parameterised Quantum Circuits
• Characterization of variational quantum algorithms using free fermions
• Stochastic approach for quantum metrology with generic Hamiltonians
• Variational quantum algorithm for generalized eigenvalue problems and its application to the finite element method
• Efficient and Robust Parameter Optimization of the Unitary Coupled-Cluster Ansatz
• Photonic quantum metrology with variational quantum optical non-linearities
• Simulating Majorana zero modes on a noisy quantum processor
• Quantum algorithms for generator coordinate methods
• Energy-dependent barren plateau in bosonic variational quantum circuits
• Calculating the many-body density of states on a digital quantum computer
• Quantum subspace expansion in the presence of hardware noise
• Generalization Error Bound for Quantum Machine Learning in NISQ Era -- A Survey
• Markovian Noise Modelling and Parameter Extraction Framework for Quantum Devices
• Fast-forwarding quantum simulation with real-time quantum Krylov subspace algorithms
• Convex Optimization for Nonequilibrium Steady States on a Hybrid Quantum Processor
• Quantum DeepONet: Neural operators accelerated by quantum computing
• Qudit Machine Learning
• Simulation of Quantum Computers: Review and Acceleration Opportunities
• Image Classification with Rotation-Invariant Variational Quantum Circuits
• Variational Quantum Eigensolver Ansatz for the $J_1$-$J_2$-model
• Efficient Quantum Circuit Compilation for Near-Term Quantum Advantage
• Random coordinate descent: a simple alternative for optimizing parameterized quantum circuits
• Towards Efficient Quantum Computing for Quantum Chemistry: Reducing Circuit Complexity with Transcorrelated and Adaptive Ansatz Techniques
• Improved iterative quantum algorithm for ground-state preparation
• Quantum-walk search in motion
• Protocols for Trainable and Differentiable Quantum Generative Modelling
• Dequantizing the Quantum Singular Value Transformation: Hardness and Applications to Quantum Chemistry and the Quantum PCP Conjecture
• Synergistic Dynamical Decoupling and Circuit Design for Enhanced Algorithm Performance on Near-Term Quantum Devices
• Barren plateaus are swamped with traps
• Improving the performance of quantum approximate optimization for preparing non-trivial quantum states without translational symmetry
• Variational-quantum-eigensolver-inspired optimization for spin-chain work extraction
• Using a Feedback-Based Quantum Algorithm to Analyze the Critical Properties of the ANNNI Model Without Classical Optimization
• Density Matrix Emulation of Quantum Recurrent Neural Networks for Multivariate Time Series Prediction
• A Hybrid Quantum-Classical Method for Electron-Phonon Systems
• Variational Quantum Support Vector Machine based on $\Gamma$ matrix expansion and Variational Universal-Quantum-State Generator
• Qsun: an open-source platform towards practical quantum machine learning applications
• Equivalence of cost concentration and gradient vanishing for quantum circuits: An elementary proof in the Riemannian formulation
• Exploring Quantum Average-Case Distances: proofs, properties, and examples
• Virtual distillation with noise dilution
• Training Quantum Boltzmann Machines with the $\beta$-Variational Quantum Eigensolver
• Subsystem Information Capacity in Random Circuits and Hamiltonian Dynamics
• Evaluating the Resilience of Variational Quantum Algorithms to Leakage Noise
• A Holistic Approach to Quantum Ethics Education
• Solving Fractional Differential Equations on a Quantum Computer: A Variational Approach
• Hybrid quantum-classical unsupervised data clustering based on the self-organizing feature map
• A full circuit-based quantum algorithm for excited-states in quantum chemistry
• Efficient variational quantum circuit structure for correlated topological phases
• A quantum computing concept for 1-D elastic wave simulation with exponential speedup
• The cross-sectional stock return predictions via quantum neural network and tensor network
• Experimental quantum natural gradient optimization in photonics
• Optimal Parameter Configurations for Sequential Optimization of Variational Quantum Eigensolver
• Ansatz-Independent Variational Quantum Classifier
• Partially Unitary Learning
• Quantum algorithms for group convolution, cross-correlation, and equivariant transformations
• Asymmetric quantum multicast network coding: asymmetric optimal cloning over quantum networks
• Variational quantum computing for quantum simulation: principles, implementations, and challenges
• Quantum Volume for Photonic Quantum Processors
• Quantum Channel Learning
• Optimizing one-axis twists for variational Bayesian quantum metrology
• Accelerating quantum imaginary-time evolution with random measurements
• Quantum Algorithms for Geologic Fracture Networks
• Error estimation in current noisy quantum computers
• Unveiling quantum phase transitions from traps in variational quantum algorithms
• Digital-analog quantum learning on Rydberg atom arrays
• Hype or Heuristic? Quantum Reinforcement Learning for Join Order Optimisation
• Universal imaginary-time critical dynamics on a quantum computer
• Deep Quantum Circuit Simulations of Low-Energy Nuclear States
• Simulating photonic devices with noisy optical elements
• Efficient Strategies for Reducing Sampling Error in Quantum Krylov Subspace Diagonalization
• Photonic quantum generative adversarial networks for classical data
• Quantum reservoir computing on random regular graphs
• Quantum Computing for Discrete Optimization: A Highlight of Three Technologies
• Subspace Preserving Quantum Convolutional Neural Network Architectures
• Beyond Quantum Annealing: Optimal control solutions to MaxCut problems
• A quantum information theoretic analysis of reinforcement learning-assisted quantum architecture search
• SnCQA: A hardware-efficient equivariant quantum convolutional circuit architecture
• Applicability of Measurement-based Quantum Computation towards Physically-driven Variational Quantum Eigensolver
• Parameterized Two-Qubit Gates for Enhanced Variational Quantum Eigensolver
• Hybrid Quantum Machine Learning Assisted Classification of COVID-19 from Computed Tomography Scans
• Fast quantum state preparation and bath dynamics using non-Gaussian variational ansatz and quantum optimal control
• Qubit-efficient Variational Quantum Algorithms for Image Segmentation
• Characterization of a Transmon Qubit in a 3D Cavity for Quantum Machine Learning and Photon Counting
• Virtual quantum error detection
• Classical Pre-optimization Approach for ADAPT-VQE: Maximizing the Potential of High-Performance Computing Resources to Improve Quantum Simulation of Chemical Applications
• Noise-Robust Detection of Quantum Phase Transitions
• Variational generation of spin squeezing on one-dimensional quantum devices with nearest-neighbor interactions
• Parametrized constant-depth quantum neuron
• Implementing Jastrow--Gutzwiller operators on a quantum computer using the cascaded variational quantum eigensolver algorithm
• Faster Born probability estimation via gate merging and frame optimisation
• Recursive Quantum Relaxation for Combinatorial Optimization Problems
• Information flow in parameterized quantum circuits
• Analytical results for the Quantum Alternating Operator Ansatz with Grover Mixer
• Equivariant Variational Quantum Eigensolver to detect Phase Transitions through Energy Level Crossings
• Error-Mitigated Quantum Simulation of Interacting Fermions with Trapped Ions
• State preparation of lattice field theories using quantum optimal control
• Double-bracket quantum algorithms for quantum imaginary-time evolution
• Calculating the Green's function of two-site Fermionic Hubbard model in a photonic system
• Efficient simulation of parametrized quantum circuits under non-unital noise through Pauli backpropagation
• Towards Variational Quantum Algorithms for generalized linear and nonlinear transport phenomena
• Practical quantum simulation of small-scale non-Hermitian dynamics
• Designing fast quantum gates using optimal control with a reinforcement-learning ansatz
• Gradient-descent methods for fast quantum state tomography
• Simulation of a feedback-based algorithm for quantum optimization for a realistic neutral atom system with an optimized small-angle controlled-phase gate
• Quantum algorithms for cooling: a simple case study
• Quantum Architecture Search for Quantum Monte Carlo Integration via Conditional Parameterized Circuits with Application to Finance
• Quantum error cancellation in photonic systems -- undoing photon losses
• Approaching Collateral Optimization for NISQ and Quantum-Inspired Computing
• A generalization of Bernstein-Vazirani algorithm with multiple secret keys and a probabilistic oracle
• Quantum Power Flows: From Theory to Practice
• A Quantum Algorithmic Approach to Multiconfigurational Valence Bond Theory: Insights from Interpretable Circuit Design
• Reduce&chop: Shallow circuits for deeper problems
• Swap Test with Quantum-Dot Charge Qubits
• Parametrized quantum circuit for weight-adjustable quantum loop gas
• Measuring Trotter error and its application to precision-guaranteed Hamiltonian simulations
• On Optimizing Hyperparameters for Quantum Neural Networks
• Photonic counterdiabatic quantum optimization algorithm
• Genuine Multipartite Entanglement in Quantum Optimization
• Amplitude Amplification for Optimization via Subdivided Phase Oracle
• QuanTest: Entanglement-Guided Testing of Quantum Neural Network Systems
• Efficient Encodings of the Travelling Salesperson Problem for Variational Quantum Algorithms
• Analyzing the quantum approximate optimization algorithm: ansätze, symmetries, and Lie algebras
• Efficient Learning for Linear Properties of Bounded-Gate Quantum Circuits
• Precision ground-state energy calculation for the water molecule on a superconducting quantum processor
• Gradients and frequency profiles of quantum re-uploading models
• Improving the Performance of Digitized Counterdiabatic Quantum Optimization via Algorithm-Oriented Qubit Mapping
• Parameter-Parallel Distributed Variational Quantum Algorithm
• Characterizing randomness in parameterized quantum circuits through expressibility and average entanglement
• Random Natural Gradient
• Learning the expressibility of quantum circuit ansatz using transformer
• Running the Dual-PQC GAN on noisy simulators and real quantum hardware
• Quantum optimal control in quantum technologies. Strategic report on current status, visions and goals for research in Europe
• Quantum Algorithm for Smoothed Particle Hydrodynamics
• Quantum Mini-Apps: A Framework for Developing and Benchmarking Quantum-HPC Applications
• Fast elementary gates for universal quantum computation with Kerr parametric oscillator qubits
• Reconstructing Thermal Quantum Quench Dynamics from Pure States
• Adaptive variational ground state preparation for spin-1 models on qubit-based architectures
• Variational measurement-based quantum computation for generative modeling
• Navigating the noise-depth tradeoff in adiabatic quantum circuits
• Simulating thermodynamic properties of dinuclear metal complexes using Variational Quantum Algorithms
• Quantum algorithm for the Vlasov simulation of the large-scale structure formation with massive neutrinos
• Time-Optimal Quantum Driving by Variational Circuit Learning
• Diagrammatic Analysis for Parameterized Quantum Circuits
• SHARC-VQE: Simplified Hamiltonian Approach with Refinement and Correction enabled Variational Quantum Eigensolver for Molecular Simulation
• Scalable circuit depth reduction in feedback-based quantum optimization with a quadratic approximation
• FragPT2: Multi-Fragment Wavefunction Embedding with Perturbative Interactions
• Adaptive variational quantum dynamics simulations with compressed circuits and fewer measurements
• Quantum Gate Sets for Lattice QCD in the strong coupling limit: $N_f=1$
• A Study on Quantum Graph Neural Networks Applied to Molecular Physics
• Bang-bang algorithms for quantum many-body ground states: a tensor network exploration
• Efficient and quantum-adaptive machine learning with fermion neural networks
• Variational quantum simulation of long-range interacting systems
• QUBO.jl: A Julia Ecosystem for Quadratic Unconstrained Binary Optimization
• Framework for Learning and Control in the Classical and Quantum Domains
• A variational quantum algorithm for tackling multi-dimensional Poisson equations with inhomogeneous boundary conditions
• Systematic study on the dependence of the warm-start quantum approximate optimization algorithm on approximate solutions
• A Quantum Annealing Protocol to Solve the Nuclear Shell Model
• Quantum algorithms for Schrieffer-Wolff transformation
• Assisted quantum simulation of open quantum systems
• Simulating quantum circuits with arbitrary local noise using Pauli Propagation
• Mixed-Integer Programming Using a Bosonic Quantum Computer
• Quantum Simulation of non-Abelian Lattice Gauge Theories: a variational approach to ${\mathbb{D}}_8$
• Benchmarking hybrid digitized-counterdiabatic quantum optimization
• A model of interacting quantum neurons with a dynamic synapse
• Quantum gradient evaluation through quantum non-demolition measurements
• Quantum topology optimization of ground structures using noisy intermediate-scale quantum devices
• Energy Landscape Structure of Small Graph Isomorphism Under Variational Optimization
• Quantum Dynamics Simulation of the Advection-Diffusion Equation
• Compilation of Entangling Gates for High-Dimensional Quantum Systems
• Probing the limits of variational quantum algorithms for nonlinear ground states on real quantum hardware: The effects of noise
• Quantum computing for genomics: conceptual challenges and practical perspectives
• Segmented Composite Design of Robust Single-Qubit Quantum Gates
• Red-QAOA: Efficient Variational Optimization through Circuit Reduction
• Sparse Probabilistic Synthesis of Quantum Operations
• Quantum Kernel Evaluation via Hong-Ou-Mandel Interference
• Mimicking quantum correlation of a long-range Hamiltonian by finite-range interactions
• Maximising Quantum-Computing Expressive Power through Randomised Circuits
• Bounds on the ground state energy of quantum $p$-spin Hamiltonians
• MLQAOA: Graph Learning Accelerated Hybrid Quantum-Classical Multilevel QAOA
• Parameterization and optimizability of pulse-level VQEs
• Quantum Circuit Design using a Progressive Widening Enhanced Monte Carlo Tree Search
• Quantum computing for data science
• Generation of Pseudo-Random Quantum States on Actual Quantum Processors
• Exploring the topological sector optimization on quantum computers
• Machine-Learning Insights into the Entanglement-trainability Correlation of Parameterized Quantum Circuits
• Variational quantum eigensolver with embedded entanglement using a tensor-network ansatz
• Reusability Report: Comparing gradient descent and monte carlo tree search optimization of quantum annealing schedules
• Resource-efficient utilization of quantum computers
• Kernel-Function Based Quantum Algorithms for Finite Temperature Quantum Simulation
• Efficient quantum-enhanced classical simulation for patches of quantum landscapes
• Iteration Complexity of Variational Quantum Algorithms
• Differentiable matrix product states for simulating variational quantum computational chemistry
• Classically Replaceable Operations
• Characterization of overparametrization in the simulation of realistic quantum systems
• Quantum computing quantum Monte Carlo algorithm
• Exploring Ground States of Fermi-Hubbard Model on Honeycomb Lattices with Counterdiabaticity
• Quantum techniques for eigenvalue problems
• Improved resource-tunable near-term quantum algorithms for transition probabilities, with applications in physics and variational quantum linear algebra
• Accurate harmonic vibrational frequencies for diatomic molecules via quantum computing
• Virtual mitigation of coherent non-adiabatic transitions by echo verification
• Quantum delegated and federated learning via quantum homomorphic encryption
• QSlack: A slack-variable approach for variational quantum semi-definite programming
• An example of use of Variational Methods in Quantum Machine Learning
• Connection between single-layer Quantum Approximate Optimization Algorithm interferometry and thermal distributions sampling
• Quantum-classical tradeoffs and multi-controlled quantum gate decompositions in variational algorithms
• Correlated states in super-moiré materials with a kernel polynomial quantics tensor cross interpolation algorithm
• Error-mitigated photonic quantum circuit Born machine
• Limitations of variational quantum algorithms: a quantum optimal transport approach
• All you need is spin: SU(2) equivariant variational quantum circuits based on spin networks
• Training iterated protocols for distillation of GHZ states with variational quantum algorithms
• Classification and reconstruction for single-pixel imaging with classical and quantum neural networks
• On the Baltimore Light RailLink into the quantum future
• Trade-off between Gradient Measurement Efficiency and Expressivity in Deep Quantum Neural Networks
• Digital Quantum Simulation and Circuit Learning for the Generation of Coherent States
• Learning quantum phases via single-qubit disentanglement
• Machine learning of quantum channels on NISQ devices
• Schrödinger as a Quantum Programmer: Estimating Entanglement via Steering
• Hermitian-preserving ansatz and variational open quantum eigensolver
• Optimal-order Trotter-Suzuki decomposition for quantum simulation on noisy quantum computers
• Quantum algorithm for calculation of transition amplitudes in hybrid tensor networks
• Energy Landscape Plummeting in Variational Quantum Eigensolver: Subspace Optimization, Non-iterative Corrections and Generator-informed Initialization for Improved Quantum Efficiency
• Scalability Challenges in Variational Quantum Optimization under Stochastic Noise
• Variational Quantum Crank-Nicolson and Method of Lines for the Solution of Initial Value Problems
• Sequence of penalties method to study excited states using VQE
• Efficient quantum algorithms for testing symmetries of open quantum systems
• Streaming IoT Data and the Quantum Edge: A Classic/Quantum Machine Learning Use Case
• Quantum annealer accelerates the variational quantum eigensolver in a triple-hybrid algorithm
• Calibrating quantum gates up to 52 qubits in a superconducting processor
• Volcano Architecture for Scalable Quantum Processor Units
• Large-scale Efficient Molecule Geometry Optimization with Hybrid Quantum-Classical Computing
• Entanglement Detection with Quantum-inspired Kernels and SVMs
• Warm Start Adaptive-Bias Quantum Approximate Optimization Algorithm
• Quantum machine learning for multiclass classification beyond kernel methods
• Bringing Quantum Systems under Control: A Tutorial Invitation to Quantum Computing and Its Relation to Bilinear Control Systems
• Enhancing Variational Quantum Circuit Training: An Improved Neural Network Approach for Barren Plateau Mitigation
• Deep Circuit Compression for Quantum Dynamics via Tensor Networks
• QuForge: A Library for Qudits Simulation
• Quantum Natural Gradient with Geodesic Corrections for Small Shallow Quantum Circuits
• Demonstration of Hardware Efficient Photonic Variational Quantum Algorithm
• Non-Iterative Disentangled Unitary Coupled-Cluster based on Lie-algebraic structure
• Quantum Annealing based Power Grid Partitioning for Parallel Simulation
• Pulse family optimization for parametrized quantum gates using spectral clustering
• Experimental benchmarking of quantum state overlap estimation strategies with photonic systems
• Photonic variational quantum eigensolver using entanglement measurements
• Quantum optical classifier with superexponential speedup
• Using quantum computers in control: interval matrix properties
• Partitioned Quantum Subspace Expansion
• Efficient Quantum Cooling Algorithm for Fermionic Systems
• Low-Rank Variational Quantum Algorithm for the Dynamics of Open Quantum Systems
• Neutron-nucleus dynamics simulations for quantum computers
• Supervised Learning Guarantee for Quantum AdaBoost
• Geodesic Algorithm for Unitary Gate Design with Time-Independent Hamiltonians
• Hamiltonian-based graph-state ansatz for variational quantum algorithms
• Hierarchical Multigrid Ansatz for Variational Quantum Algorithms
• Exploring thermal equilibria of the Fermi-Hubbard model with variational quantum algorithms
• Channel Attention for Quantum Convolutional Neural Networks
• Refining resource estimation for the quantum computation of vibrational molecular spectra through Trotter error analysis
• The 7 faces of quantum NP
• From Heisenberg to Hubbard: An initial state for the shallow quantum simulation of correlated electrons
• Tridiagonal matrix decomposition for Hamiltonian simulation on a quantum computer
• Classical shadows meet quantum optimal mass transport
• Quantum Circuit Distillation and Compression
• Parallel-in-time quantum simulation via Page and Wootters quantum time
• Single entanglement connection architecture between multi-layer bipartite Hardware Efficient Ansatz
• Backpropagation scaling in parameterised quantum circuits
• Going Beyond Gadgets: The Importance of Scalability for Analogue Quantum Simulators
• Measurement-Based Control for Minimizing Energy Functions in Quantum Systems
• Cascaded variational quantum eigensolver algorithm
• Pitfalls of the sublinear QAOA-based factorization algorithm
• Restricting to the chip architecture maintains the quantum neural network accuracy
• Quantum error mitigation for rotation symmetric bosonic codes with symmetry expansion
• Computing Electronic Correlation Energies using Linear Depth Quantum Circuits
• Calculation of the moscovium ground-state energy by quantum algorithms
• Exploiting subspace constraints and ab initio variational methods for quantum chemistry
• Computational Characteristics of Random Field Ising Model with Long-Range Interaction
• Improving the efficiency of learning-based error mitigation
• Variational Quantum Simulation of Valence-Bond Solids
• Metropolis-style random sampling of quantum gates for the estimation of low-energy observables
• Encoding-dependent generalization bounds for parametrized quantum circuits
• Quantum mean value approximator for hard integer value problems
• More buck-per-shot: Why learning trumps mitigation in noisy quantum sensing
• Optimized numerical gradient and Hessian estimation for variational quantum algorithms
• Variational LOCC-assisted quantum circuits for long-range entangled states
• Automated Discovery of Coupled Mode Setups
• Quantum Iterative Methods for Solving Differential Equations with Application to Computational Fluid Dynamics
• Boson sampling enhanced quantum chemistry
• Quantum eigenstate broadcasting assisted by a coherent link
• Non-linear classification capability of quantum neural networks due to emergent quantum metastability
• Compact Multi-Threshold Quantum Information Driven Ansatz For Strongly Interactive Lattice Spin Models
• Utility of NISQ devices: optimizing experimental parameters for the fabrication of Au atomic junction using gate-based quantum computers
• Universal compiling and (No-)Free-Lunch theorems for continuous variable quantum learning
• Quantum noise modeling through Reinforcement Learning
• Out of the Loop: Structural Approximation of Optimisation Landscapes and non-Iterative Quantum Optimisation
• Cross-platform hardware benchmark of style-based quantum GANs for data augmentation on superconducting and trapped-ion processors
• Classical Benchmarks for Variational Quantum Eigensolver Simulations of the Hubbard Model
• A Monte Carlo Tree Search approach to QAOA: finding a needle in the haystack
• Quantum-inspired clustering with light
• Automatic Structural Search of Tensor Network States including Entanglement Renormalization
• Variational Microcanonical Estimator
• Switching Time Optimization for Binary Quantum Optimal Control
• Quantum Feasibility Labeling for NP-complete Vertex Coloring Problem
• Simulation of a Three-Nucleons System Transition on Quantum Circuits
• Resource-efficient Generalized Quantum Subspace Expansion
• Virtual Z gates and symmetric gate compilation
• Continuous monitoring for noisy intermediate-scale quantum processors
• Probing many-body Bell correlation depth with superconducting qubits
• Minimal evolution times for fast, pulse-based state preparation in silicon spin qubits
• Multidimensional Quantum Generative Modeling by Quantum Hartley Transform
• Quantum-enhanced mean value estimation via adaptive measurement
• Quantum state tomography with disentanglement algorithm
• Efficient preparation of the AKLT State with Measurement-based Imaginary Time Evolution
• Noise tailoring for Robust Amplitude Estimation
• Evaluating Variational Quantum Circuit Architectures for Distributed Quantum Computing
• Ising Hamiltonians for Constrained Combinatorial Optimization Problems and the Metropolis-Hastings Warm-Starting Algorithm
• Introduction to Quantum Error Correction with Stabilizer Codes
• Minimizing the negativity of quantum circuits in overcomplete quasiprobability representations
• Pitfalls when tackling the exponential concentration of parameterized quantum models
• Optimal compression of constrained quantum time evolution
• Parent Hamiltonian as a benchmark problem for variational quantum eigensolvers
• Hardware-efficient quantum phase estimation via local control
• Quantum Reservoir Computing for Realized Volatility Forecasting
• Evaluating the Practicality of Quantum Optimization Algorithms for Prototypical Industrial Applications
• Leveraging commuting groups for an efficient variational Hamiltonian ansatz
• Dual-VQE: A quantum algorithm to lower bound the ground-state energy
• QuOp_MPI: a framework for parallel simulation of quantum variational algorithms
• Bang-bang preparation of quantum many-body ground states in two dimensions: optimization of the algorithm with a two-dimensional tensor network
• Accelerating Feedback-Based Quantum Algorithms through Time Rescaling
• Perturbative gadgets for gate-based quantum computing: Non-recursive constructions without subspace restrictions
• A Novel Noise-Aware Classical Optimizer for Variational Quantum Algorithms
• Variational quantum algorithm for Gaussian discrete solitons and their boson sampling
• Double-bracket algorithm for quantum signal processing without post-selection
• Full Characterization of the Depth Overhead for Quantum Circuit Compilation with Arbitrary Qubit Connectivity Constraint
• Trained quantum neural networks are Gaussian processes
• Exponentiation of Parametric Hamiltonians via Unitary interpolation
• Clifford circuit based heuristic optimization of fermion-to-qubit mappings
• Variational post-selection for ground states and thermal states simulation
• Optimization via Quantum Preconditioning
• Data-Dependent Generalization Bounds for Parameterized Quantum Models Under Noise
• Estimating Eigenenergies from Quantum Dynamics: A Unified Noise-Resilient Measurement-Driven Approach
• Estimation of Quantum Fisher Information via Stein's Identity in Variational Quantum Algorithms
• Distance-four quantum codes with combined postselection and error correction
• Basis set generation and optimization in the NISQ era with Quiqbox.jl
• An Amplitude-Based Implementation of the Unit Step Function on a Quantum Computer
• Limitations of Noisy Quantum Devices in Computational and Entangling Power
• Quantum Machine Learning of Molecular Energies with Hybrid Quantum-Neural Wavefunction
• Learning Fourier series with parametrized quantum circuits
• Variational Quantum Imaginary Time Evolution for Matrix Product State Ansatz with Tests on Transcorrelated Hamiltonians
• Generic eigenstate preparation via measurement-based purification
• Entangled states from sparsely coupled spins for metrology with neutral atoms
• Deep-Circuit QAOA
• Addition and Differentiation of ZX-diagrams
• Quantum Neural Networks in Practice: A Comparative Study with Classical Models from Standard Data Sets to Industrial Images
• Inequality constraints in variational quantum circuits with qudits
• Separation of measurement uncertainty into quantum and classical parts based on Kirkwood-Dirac quasiprobability and generalized entropy
• QKAN: quantum Kolmogorov-Arnold networks with applications in machine learning and multivariate state preparation
• On the Effects of Small Graph Perturbations in the MaxCut Problem by QAOA
• An Energy Estimation Benchmark for Quantum Computers
• Adaptively partitioned analog quantum simulation on near-term quantum computers: The nonclassical free-induction decay of NV centers in diamond
• Determining probability density functions with adiabatic quantum computing
• Q-Profile: Profiling Tool for Quantum Control Stacks applied to the Quantum Approximate Optimization Algorithm
• Comparing Quantum Service Offerings
• Quantum Approximation Optimization Algorithm for the Trellis based Viterbi Decoding of Classical Error Correcting Codes
• Crosstalk-Based Parameterized Quantum Circuit Approximation
• QHDL: a Low-Level Circuit Description Language for Quantum Computing
• Practical limitations of quantum data propagation on noisy quantum processors
• Determining the ability for universal quantum computing: Testing controllability via dimensional expressivity
• Full-counting statistics of particle distribution on a digital quantum computer
• Quantum tensor network algorithms for evaluation of spectral functions on quantum computers
• Density matrix representation of hybrid tensor networks for noisy quantum devices
• Adaptive measurement strategy for quantum subspace methods
• Ground state energy and magnetization curve of a frustrated magnetic system from real-time evolution on a digital quantum processor
• Parameterized quantum comb and simpler circuits for reversing unknown qubit-unitary operations
• Quadratic speed-ups in quantum kernelized binary classification
• Quantum Approximation of Normalized Schatten Norms and Applications to Learning
• Demonstration of quantum projective simulation on a single-photon-based quantum computer
• Comprehensive Library of Variational LSE Solvers
• Adiabatic quantum computing with parameterized quantum circuits
• Barren plateaus are amplified by the dimension of qudits
• Cost of Locally Approximating High-Dimensional Ground States of Contextual Quantum Models
• Graph Neural Networks for Parameterized Quantum Circuits Expressibility Estimation
• Quantum Software Ecosystem Design
• Model-Driven Engineering for Quantum Programming: A Case Study on Ground State Energy Calculation
• Quantum Active Learning
• Performance and scaling analysis of variational quantum simulation
• Multi-target quantum compilation algorithm
• Atom Cavity Encoding for NP-Complete Problems
• Variational quantum algorithm based on Lagrange polynomial encoding to solve differential equations
• Variational quantum cloning machine on an integrated photonic interferometer
• Quantum Curriculum Learning
• Tomography of parametrized quantum states
• A recipe for local simulation of strongly-correlated fermionic matter on quantum computers: the 2D Fermi-Hubbard model
• Quantum many-body simulation of finite-temperature systems with sampling a series expansion of a quantum imaginary-time evolution
• Learning Density Functionals from Noisy Quantum Data
• Hardness-dependent quantum adiabatic schedules for the maximum-independent-set problem
• Quantum Computational Insurance and Actuarial Science
• Stabilizer configuration interaction: Finding molecular subspaces with error detection properties
• Agnostic Process Tomography
• Nearly query-optimal classical shadow estimation of unitary channels
• Policy Gradients using Variational Quantum Circuits
• Expressibility, entangling power and quantum average causal effect for causally indefinite circuits
• A Universal Quantum Computer From Relativistic Motion
• Expressivity of deterministic quantum computation with one qubit
• Exact Quantum Algorithm for Unit Commitment Optimization based on Partially Connected Quantum Neural Networks
• Effective temperature in approximate quantum many-body states
• Grover's search meets Ising models: a quantum algorithm for finding low-energy states
• Variational quantum compiling for three-qubit gates design in quantum dots
• Simulating methylamine using symmetry adapted qubit-excitation-based variational quantum eigensolver
• Modified Conjugate Quantum Natural Gradient
• Evolved Quantum Boltzmann Machines
• Experimentally validated quantum-secure federated learning over a multi-user quantum network
• Benchmarking Quantum Convolutional Neural Networks for Signal Classification in Simulated Gamma-Ray Burst Detection
• Entanglement-informed Construction of Variational Quantum Circuits
• Quantum implicit representation of vortex filaments in turbulence
• Quantum multiphase estimation
• Exploring new variational quantum circuit ansatzes for solving $SU(2)$ matrix models
• Space-time tradeoff in networked virtual distillation
• Coupled-cluster pairing models for radicals with strong correlations
• Demonstration of a variational quantum eigensolver with a solid-state spin system under ambient conditions
• Multi-set variational quantum dynamics algorithm for simulating nonadiabatic dynamics on quantum computers
• Optimal solutions to quantum annealing using two independent control functions
• State Specific Measurement Protocols for the Variational Quantum Eigensolver
• Hybrid Quantum Classical Graph Neural Networks for Particle Track Reconstruction
• The Lie Algebra of XY-mixer Topologies and Warm Starting QAOA for Constrained Optimization
• Regularizing quantum loss landscapes by noise injection
• Exponential distillation of dominant eigenproperties
• Variational Inference for Quantum HyperNetworks
• Solving the Hubbard model using density matrix embedding theory and the variational quantum eigensolver
• Resource-Efficient Hadamard Test Tailored Variational Framework for Nonlinear Dynamics on Quantum Computers
• Tangent Space Excitation Ansatz for Quantum Circuits
• Perspectives on Utilization of Measurements in Quantum Algorithms
• Toolchain for Faster Iterations in Quantum Software Development
• Stochastic Entanglement Configuration for Constructive Entanglement Topologies in Quantum Machine Learning with Application to Cardiac MRI
• On the Differential Topology of Expressivity of Parameterized Quantum Circuits
• Quantum generative modeling for financial time series with temporal correlations
• Simulating Quantum Turbulence with Matrix Product States
• Scalable Quantum Computational Science: A Perspective from Block-Encodings and Polynomial Transformations
• Universal Quantum Computer Simulation of 50 Qubits on Europe`s First Exascale Supercomputer Harnessing Its Heterogeneous CPU-GPU Architecture
• Constraint-Aware Quantum Optimization via Hamming Weight Operators
• Photonic variational quantum eigensolver for NISQ-compatible quantum technology
• Freedom of mixer rotation-axis improves performance in the quantum approximate optimization algorithm
• Generative flow-based warm start of the variational quantum eigensolver
• Sparse Non-Markovian Noise Modeling of Transmon-Based Multi-Qubit Operations
• Robustness of optimized numerical estimation schemes for noisy variational quantum algorithms
• Symmetry-based quantum algorithms for open-shop scheduling with hard constraints
• Shot-based quantum encoding: a data-loading paradigm for quantum neural networks
• Feasibility of performing quantum chemistry calculations on quantum computers
• A Noise-Aware Scalable Subspace Classical Optimizer for the Quantum Approximate Optimization Algorithm
• Notes on Quantum Computing for Thermal Science
• Active Learning for Quantum Mechanical Measurements
• Estimating the degree of non-Markovianity using variational quantum circuits
• Efficient Estimation and Sequential Optimization of Cost Functions in Variational Quantum Algorithms
• Towards Symmetry-Aware Efficient Simulation of Quantum Systems and Beyond
• Lie groups for quantum complexity and barren plateau theory
• Unsupervised detection of decoupled subspaces: many-body scars and beyond
• The Dual Role of Low-Weight Pauli Propagation: A Flawed Simulator but a Powerful Initializer for Variational Quantum Algorithms
• Efficient Fermi-Hubbard model ground-state preparation by coupling to a classical reservoir in the instantaneous-response limit
• Expressiveness of Commutative Quantum Circuits: A Probabilistic Approach
• Quantum Circuit Pruning: Improving Fidelity via Compilation-Aware Circuit Approximation
• Experimental factoring integers using fixed-point-QAOA with a trapped-ion quantum processor
• Double descent in quantum kernel methods
• Blockwise Optimization for Projective Variational Quantum Dynamics (BLOP-VQD): Algorithm and Implementation for Lattice Systems
• Compressed sensing enhanced by quantum approximate optimization algorithm
• Hardware-efficient quantum annealing with error mitigation via classical shadow
• Binary Quantum Control Optimization with Uncertain Hamiltonians
• Parallelized Givens Ansatz for Molecular ground-states: Bridging Accuracy and Efficiency on NISQ Platforms
• Encoding strongly-correlated many-boson wavefunctions on a photonic quantum computer: application to the attractive Bose-Hubbard model
• Distributing Quantum Computations, Shot-wise
• Evaluating the Limits of QAOA Parameter Transfer at High-Rounds on Sparse Ising Models With Geometrically Local Cubic Terms
• Investigation of tantalum films growth for coplanar resonators with internal quality factors above ten million
• Artificial intelligence for representing and characterizing quantum systems
• Suppressing decoherence in quantum state transfer with unitary operations
• Bounding Entanglement Entropy with Clifford Double Cosets
• Symmetry-enhanced Counterdiabatic Quantum Algorithm for Qudits
• Multi-channel convolutional neural quantum embedding
• Disentangling quantum neural networks for unified estimation of quantum entropies and distance measures
• Scaling of symmetry-restricted quantum circuits
• High-Entanglement Capabilities for Variational Quantum Algorithms: The Poisson Equation Case
• Arbitrary Ground State Observables from Quantum Computed Moments
• Efficient Online Quantum Circuit Learning with No Upfront Training
• Consensus-based qubit configuration optimization for variational algorithms on neutral atom quantum systems
• Cheaper and more noise-resilient quantum state preparation using eigenvector continuation
• An Error Mitigated Non-Orthogonal Quantum Eigensolver via Shadow Tomography
• Performance analysis of a filtering variational quantum algorithm
• A quantum approach for optimal control
• Rovibrational energy levels of H${}_2$O by quantum computing
• Qiskit-Torch-Module: Fast Prototyping of Quantum Neural Networks
• Sub-universal variational circuits for combinatorial optimization problems
• Warm Start of Variational Quantum Algorithms for Quadratic Unconstrained Binary Optimization Problems
• Finding eigenvectors with a quantum variational algorithm
• Short-time simulation of quantum dynamics by Pauli measurements
• Quantum natural gradient with thermal-state initialization
• Feedback-Based Quantum Strategies for Constrained Combinatorial Optimization Problems
• Chasing shadows with Gottesman-Kitaev-Preskill codes
• HQNET: Harnessing Quantum Noise for Effective Training of Quantum Neural Networks in NISQ Era
• Variational-toolbox-based separability detection of multiqubit states
• Vanishing performance of the parity-encoded quantum approximate optimization algorithm applied to spin-glass models
• ReCon: Reconfiguring Analog Rydberg Atom Quantum Computers for Quantum Generative Adversarial Networks
• Quantum neural network autoencoder and classifier applied to an industrial case study
• Adaptive Quantum Generative Training using an Unbounded Loss Function
• Variational simulation of higher-spin systems on qubit-based quantum simulators
• Edge of Many-Body Quantum Chaos in Quantum Reservoir Computing
• Lower bounds on the number of rounds of the quantum approximate optimization algorithm required for guaranteed approximation ratios
• A Novel Single-Layer Quantum Neural Network for Approximate SRBB-Based Unitary Synthesis
• Neural-network-assisted Monte Carlo sampling trained by Quantum Approximate Optimization Algorithm
• Dynamical transition in controllable quantum neural networks with large depth
• Self-attention U-Net decoder for toric codes
• Post-Quantum Security: Origin, Fundamentals, and Adoption
• A Practical Quantum Hoare Logic with Classical Variables, I
• Global optimization in variational quantum algorithms via dynamic tunneling method
• When Quantum and Classical Models Disagree: Learning Beyond Minimum Norm Least Square
• Quantum-enhanced learning with a controllable bosonic variational sensor network
• Variational quantum algorithms with invariant probabilistic error cancellation on noisy quantum processors
• Stability of emergent time periodicity in a few-body interacting system
• High-fidelity initialization a logical qubit with multiple injections
• Efficient Large-Scale Quantum Optimization via Counterdiabatic Ansatz
• Guided Graph Compression for Quantum Graph Neural Networks
• Quick design of feasible tensor networks for constrained combinatorial optimization
• A variational quantum algorithm for entanglement quantification
• Resource-efficient quantum algorithm for linear systems of equations
• Hamiltonian formulations of centroid-based clustering
• Learning quantum symmetries with interactive quantum-classical variational algorithms
• A coherent approach to quantum-classical optimization
• Dissipative ground state preparation in ab initio electronic structure theory
• Digitized Counter-Diabatic Quantum Optimization for Bin Packing Problem
• Quantum-data-driven dynamical transition in quantum learning
• Exploring the application of quantum technologies to industrial and real-world use cases
• Adiabatic state preparation from general initial states
• Efficient quantum algorithm for weighted partial sums and numerical integration
• QTIS: A QAOA-Based Quantum Time Interval Scheduler
• On Reducing the Execution Latency of Superconducting Quantum Processors via Quantum Job Scheduling
• Warm-Start Variational Quantum Policy Iteration
• Qubit-efficient quantum combinatorial optimization solver
• Quantum speed limit for observables from quantum asymmetry
• Trainability issues in quantum policy gradients
• Improving the trainability of VQE on NISQ computers for solving portfolio optimization using convex interpolation
• Unraveling Rodeo Algorithm Through the Zeeman Model
• Quantum Computing Solution of the Bethe-Salpeter Equation for Relativistic Scalar Bound States via Tensor-Network VQE
• Feedback-Based Quantum Algorithm for Constrained Optimization Problems
• Many-body thermal states on a quantum computer: a variational approach
• Toward Density Functional Theory on Quantum Computers?
• Performance Guarantees for Quantum Neural Estimation of Entropies
• Distributed Exact Generalized Grover's Algorithm
• Variational Quantum Algorithm Landscape Reconstruction by Low-Rank Tensor Completion
• Double-bracket quantum algorithms for high-fidelity ground state preparation
• Resilience-Runtime Tradeoff Relations for Quantum Algorithms
• Ancillary entangling Floquet kicks for accelerating quantum algorithms
• Optical resonators constitute a universal spin simulator
• Exploring fixed points and eigenstates of quantum systems with reinforcement learning
• Light Cone Cancellation for Variational Quantum Eigensolver in Solving Noisy Max-Cut
• Circuit connectivity boosts by quantum-classical-quantum interfaces
• Verifiable cloud-based variational quantum algorithms
• Zero-Noise Extrapolation via Cyclic Permutations of Quantum Circuit Layouts
• Quantum-Enhanced Neural Exchange-Correlation Functionals
• Information Processing in Quantum Thermodynamic Systems: an Autonomous Hamiltonian Approach
• Moments of Quantum Channel Ensembles
• Exploring the performance of superposition of product states: from 1D to 3D quantum spin systems
• Noisy Monitored Quantum Circuits
• Quantum imaginary time evolution and UD-MIS problem
• Applying Grover-mixer quantum alternating operator ansatz algorithm to higher-order unconstrained binary optimization problems
• Variational matrix product states for combinatorial optimization
• Learning Feedback Mechanisms for Measurement-Based Variational Quantum State Preparation
• Quantum tree generator improves QAOA state-of-the-art for the knapsack problem
• Unitary-transformed projective squeezing: applications for circuit-knitting and state-preparation of non-Gaussian states
• Pulse engineering via projection of response functions
• Nonadiabatic Self-Healing of Trotter Errors in Digitized Counterdiabatic Dynamics
• Efficient implementation of single particle Hamiltonians in exponentially reduced qubit space
• Topology-Aware Block Coordinate Descent for Qubit Frequency Allocation of Superconducting Quantum Processors
• Variational Quantum Generative Modeling by Sampling Expectation Values of Tunable Observables
• Entropy density benchmarking of near-term quantum circuits
• Quantum Computing Demonstration of the Polaron-Molecule Transition on a NISQ Device
• Using optimal control to guide neural-network interpolation of continuously-parameterized gates
• Quantum community detection via deterministic elimination
• Schmidt quantum compressor
• Practical Quantum Reservoir Computing in Rydberg Atom Arrays
• A Quantum Genetic Algorithm with application to Cosmological Parameters Estimation
• Equivalence between exponential concentration in quantum machine learning kernels and barren plateaus in variational algorithms
• Limits of Clifford Disentangling in Tensor Network States
• Hamiltonian-reconstruction distance as a success metric for the Variational Quantum Eigensolver
• Optical Quantum Computing
• Resource-efficient Quantum Algorithms for Selected Hamiltonian Subspace Diagonalization
• Designing a Machine Learning-Driven, Cross-Hardware Emulator for Noisy Quantum Computers with Gate-Based Protocols
• Variational decision diagrams for quantum-inspired machine learning applications
• Quantum Encoding of Structured Data with Matrix Product States
• Identification of quantum generative circuits with parallel quantum neural network
• Challenges and opportunities in the supervised learning of quantum circuit outputs
• Active Sampling Sample-based Quantum Diagonalization from Finite-Shot Measurements
• Quantum Chebyshev Probabilistic Models for Fragmentation Functions
• A Useful Metric for the NISQ Era: Qubit Error Probability and Its Role in Zero Noise Extrapolation
• Counting with the quantum alternating operator ansatz
• New perspectives on quantum kernels through the lens of entangled tensor kernels
• A quantum wire approach to weighted combinatorial graph optimisation problems
• Performance evaluation of variational quantum eigensolver and quantum dynamics algorithms on the advection-diffusion equation
• Error Mitigation in Dynamic Circuits for Hamiltonian Simulation
• How Many Shots Are Enough for a Quantum Circuit?
• A Quantum Variational Approach to Prototypical Recurrent Unit
• Distributed variational quantum computing with deterministic entanglement tuning
• Measuring Incompatible Observables with Quantum Neural Networks
• PHOENIX: Pauli-Based High-Level Optimization Engine for Instruction Execution on NISQ Devices
• Direct entanglement ansatz learning (DEAL) with ZNE on error-prone superconducting qubits
• iSwitch: QEC on Demand via In-Situ Encoding of Bare Qubits for Ion Trap Architectures
• Towards quantum machine learning for assessing the resilience of post-quantum cryptography
• Variational Quantum Algorithm for Constrained Combinatorial Optimization Problems
• Unbiased observable estimation with approximate channels in fault-tolerant quantum computation
• Quantum Algorithms for Causal Estimands
• QSSA: An SSA-based IR for Quantum Computing
• Velocity Verlet-based optimization for variational quantum eigensolvers
• TabularQGAN: A quantum generative model for tabular data synthesis
• Accelerating Quantum State Encoding with SIMD: Design, Implementation, and Benchmarking
• A variational quantum eigensolver tailored to multi-band tight-binding simulations of electronic structures
• Learning Variational Quantum Circuit Parameters with Classical Artificial Intelligence for Quantum Phase Transition Detection
• Accelerated spin-adapted ground state preparation with non-variational quantum algorithms
• The Rise of Quantum Computing -- Take a BITE for Built Environment and Urban Microclimate Research
• Quantum-Inspired Multi Agent Reinforcement Learning for Exploration Exploitation Optimization in UAV-Assisted 6G Network Deployment
• Matrix-product entanglement characterizing the optimality of state-preparation quantum circuits
• QAISim: A Toolkit for Modeling and Simulation of AI in Quantum Cloud Computing Environments
• Quantum Machine Learning for State Tomography Using Classical Data
• Quantum Machine Learning for Climate Modelling
• Gradient Scalability and Taylor Surrogation of Quantum Cost Landscapes
• Hamiltonian Expressibility for Ansatz Selection in Variational Quantum Algorithms
• Variational quantum simulation of the quantum critical regime
• Error-mitigated inference of quantum network topology
• Towards a pulse-level intermediate representation for diverse quantum control systems
• Shot-Efficient ADAPT-VQE via Reused Pauli Measurements and Variance-Based Shot Allocation
• Quantum circuit evolutionary framework applied on set partitioning problem
• Data-driven Quantum Dynamical Embedding Method for Long-term Prediction on Near-term Quantum Computers
• Extended parameter shift rules with minimal derivative variance for parameterized quantum circuits
• Constrained free energy minimization for the design of thermal states and stabilizer thermodynamic systems
• From barren plateaus through fertile valleys: Conic extensions of parameterised quantum circuits
• Multiclass Portfolio Optimization via Variational Quantum Eigensolver with Dicke State Ansatz
• Imaginary Time Spectral Transforms for Excited State Preparation
• Role of overparametrization in quantum approximate optimization
• Superior resilience to poisoning and amenability to unlearning in quantum machine learning
• Decoded Quantum Interferometry Under Noise
• The Quantum Ensemble Variational Optimization Algorithm: Applications to Molecular Inverse Design
• Power and limitations of distributed quantum state purification
• Quantum reservoir computing for predicting and characterizing chaotic maps
• Training Hybrid Classical-Quantum Classifiers via Stochastic Variational Optimization
• Classical Neural Networks on Quantum Devices via Tensor Network Disentanglers: A Case Study in Image Classification
• Real-time hybrid quantum-classical computations for trapped-ions with Python control-flow
• Digital controllability of transverse field Ising chains
• Quantum approximate optimization of finite-state bosonic systems
• Quantum Machine Learning with SQUID
• Quantum Alternating Operator Ansatz for the Preparation and Detection of Long-Lived Singlet States in NMR
• Exploiting biased noise in variational quantum models
• Quantifying the Expressive Capacity of Quantum Systems: Fundamental Limits and Eigentasks
• Qudit-native measurement protocol for dynamical correlations using Hadamard tests
• Molecular resonance identification in complex absorbing potentials via integrated quantum computing and high-throughput computing
• Resource-Optimized Grouping Shadow for Efficient Energy Estimation
• Hybrid Quantum-Classical Clustering for Preparing a Prior Distribution of Eigenspectrum