Cover Image

Designing lattice proteins with variational quantum algorithms

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Linn, Hanna, Knuthson, Lucas, Irbäck, Anders, Mohanty, Sandipan, García-Álvarez, Laura, Johansson, Göran
Format:	Preprint
Published:	2025
Subjects:	Quantum Physics
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Folding lattice proteins confined on minimal grids using a quantum-inspired encoding
by: Irbäck, Anders, et al.
Published: (2025)

Using quantum annealing to design lattice proteins
by: Irbäck, Anders, et al.
Published: (2024)

Penalty-free quantum optimization applied to lattice protein folding
by: Gellsersen, Leif, et al.
Published: (2026)

Resource analysis of quantum algorithms for coarse-grained protein folding models
by: Linn, Hanna, et al.
Published: (2023)

Efficient Quantum Protein Structure Prediction with Problem-Agnostic Ansatzes
by: Linn, Hanna, et al.
Published: (2025)

Lecture notes on quantum computing
by: Kockum, Anton Frisk, et al.
Published: (2023)

Learning to learn with an evolutionary strategy applied to variational quantum algorithms
by: Friedrich, Lucas, et al.
Published: (2023)

Finding eigenvectors with a quantum variational algorithm
by: Garcia-Escartin, Juan Carlos
Published: (2023)

A variational quantum algorithm for entanglement quantification
by: Friedrich, Lucas, et al.
Published: (2025)

Impact of decoherence on the fidelity of quantum gates leaving the computational subspace
by: Abad, Tahereh, et al.
Published: (2023)

Cascaded variational quantum eigensolver algorithm
by: Gunlycke, Daniel, et al.
Published: (2023)

Undecidable problems associated with variational quantum algorithms
by: Korpas, Georgios, et al.
Published: (2025)

Perturbative variational quantum algorithms for material simulations
by: Liu, Jie, et al.
Published: (2024)

Neural network encoded variational quantum algorithms
by: Miao, Jiaqi, et al.
Published: (2023)

Statistical analysis of barren plateaus in variational quantum algorithms
by: Ho, Le Bin, et al.
Published: (2025)

Performance analysis of a filtering variational quantum algorithm
by: Marin-Sanchez, Gabriel, et al.
Published: (2024)

Dissipative variational quantum algorithms for Gibbs state preparation
by: Ilin, Yigal, et al.
Published: (2024)

Hardware-efficient variational quantum algorithm in trapped-ion quantum computer
by: Zhuang, J. -Z., et al.
Published: (2024)

Unveiling quantum phase transitions from traps in variational quantum algorithms
by: Cao, Chenfeng, et al.
Published: (2024)

A circuit-generated quantum subspace algorithm for the variational quantum eigensolver
by: Hirsbrunner, Mark R., et al.
Published: (2024)

Exploring lattice supersymmetry with variational quantum deflation
by: Schaich, David, et al.
Published: (2024)

Gravitational-wave matched filtering with variational quantum algorithms
by: Pye, Jason, et al.
Published: (2024)

Hamiltonian-based graph-state ansatz for variational quantum algorithms
by: Anand, Abhinav, et al.
Published: (2023)

Resource reduction for variational quantum algorithms by non-demolition measurements
by: Melegari, Dario, et al.
Published: (2025)

Exact gradient for general cost functions in variational quantum algorithms
by: Urbaneja, Jesus, et al.
Published: (2025)

Loss-aware state space geometry for quantum variational algorithms
by: Gill, Ankit, et al.
Published: (2026)

Noise-induced transition in optimal solutions of variational quantum algorithms
by: Li, Andy C. Y., et al.
Published: (2024)

Verifiable cloud-based variational quantum algorithms
by: Yang, Junhong, et al.
Published: (2024)

Learning quantum symmetries with interactive quantum-classical variational algorithms
by: Lu, Jonathan Z., et al.
Published: (2022)

Multi-set variational quantum dynamics algorithm for simulating nonadiabatic dynamics on quantum computers
by: Li, Jingjing, et al.
Published: (2025)

Quantum algorithm for the lattice Boltzmann method with applications on real quantum devices
by: Bastida-Zamora, Antonio, et al.
Published: (2026)

Signatures of quantum chaos and complexity in the Ising model on random graphs
by: Sreejith, GJ, et al.
Published: (2025)

Efficient hybrid variational quantum algorithm for solving graph coloring problem
by: Liu, Dongmei, et al.
Published: (2025)

Genetic optimization of ansatz expressibility for enhanced variational quantum algorithm performance
by: Mallapur, Manish, et al.
Published: (2025)

Enhancing the reachability of variational quantum algorithms via input-state design
by: Wu, Shaojun, et al.
Published: (2025)

Reducing measurement costs by recycling the Hessian in adaptive variational quantum algorithms
by: Ramôa, Mafalda, et al.
Published: (2024)

Robustness of optimized numerical estimation schemes for noisy variational quantum algorithms
by: Teo, Yong Siah
Published: (2023)

Gaussian process model kernels for noisy optimization in variational quantum algorithms
by: Arceci, Luca, et al.
Published: (2024)

Global optimization in variational quantum algorithms via dynamic tunneling method
by: Park, Seung, et al.
Published: (2024)

Training iterated protocols for distillation of GHZ states with variational quantum algorithms
by: Rozgonyi, Áron, et al.
Published: (2023)