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Variational quantum eigensolvers (VQEs) combine classical optimization with efficient cost function evaluations on quantum computers. We propose a new approach to VQEs using the principles of measurement-based quantum computation. This…

The Variational Quantum Eigensolver (VQE) is a promising algorithm for Noisy Intermediate Scale Quantum (NISQ) computation. Verification and validation of NISQ algorithms' performance on NISQ devices is an important task. We consider the…

Quantum Physics · Physics 2021-09-14 Kenneth Robbins , Peter J. Love

Variational quantum eigensolver (VQE), which combines quantum systems with classical computational power, has been arisen as a promising candidate for near-term quantum computing applications. However, the experimental resources such as the…

We investigated quantum thermal machines powered by sequential nonselective generalized measurements, taking a double quantum dot with coherent interdot tunneling as a working substance. In this platform, the competition between detuning…

Quantum Physics · Physics 2026-05-11 Bruno Carvalho , Jonas F. G. Santos , Moises Rojas

While numerical simulations are presented in most papers introducing new methods to enhance the VQE performance, comprehensive, comparative, and applied studies remain relatively rare. We present a comprehensive, yet concise guide for the…

Single-qubit thermometry presents the simplest tool to measure the temperature of thermal baths with reduced invasivity. At thermal equilibrium, the temperature uncertainty is linked to the heat capacity of the qubit, however the best…

Quantum Chemistry (QC) is one of the most promising applications of Quantum Computing. However, present quantum processing units (QPUs) are still subject to large errors. Therefore, noisy intermediate-scale quantum (NISQ) hardware is…

Quantum Physics · Physics 2025-10-21 Mohammad Haidar , Marko J. Rančić , Thomas Ayral , Yvon Maday , Jean-Philip Piquemal

We present a model for an autonomous quantum thermal machine comprised of two qubits capable of manipulating and even amplifying the local coherence in a non-degenerate external system. The machine uses only thermal resources, namely,…

Quantum Physics · Physics 2019-05-01 Gonzalo Manzano , Ralph Silva , Juan M. R. Parrondo

The variational quantum eigensolver (VQE) is a hybrid quantum-classical algorithm for finding the minimum eigenvalue of a Hamiltonian that involves the optimization of a parameterized quantum circuit. Since the resulting optimization…

We extend the program initiated in [T. Werlang et al., Phys. Rev. Lett. 105, 095702 (2010)] in several directions. Firstly, we investigate how useful quantum correlations, such as entanglement and quantum discord, are in the detection of…

Quantum Physics · Physics 2015-05-27 T. Werlang , G. A. P. Ribeiro , Gustavo Rigolin

We present a quantum thermometric protocol for the estimation of multiple temperatures within the collisional model framework. Employing the formalism of multiparameter quantum metrology, we develop a systematic strategy to estimate the…

Quantum Physics · Physics 2025-11-26 Srijon Ghosh , Sagnik Chakraborty , Rosario Lo Franco

Variational Quantum Eigensolver (VQE) is widely used in near-term hardware. However, their performances remain limited by the poor trainability and are dependent on random parameter initialization. In this work, we propose a warm start…

Quantum Physics · Physics 2025-12-19 Yahui Chai , Karl Jansen , Stefan Kühn , Tim Schwägerl , Tobias Stollenwerk

This study introduces a novel minimalistic variational quantum ansatz inspired by algorithmic cooling principles. The proposed Heat Exchange algorithmic cooling ansatz (HE ansatz) facilitates efficient population redistribution without…

Quantum Physics · Physics 2025-01-29 Soyoung Shin , Ha Eum Kim , Hyeonjun Yeo , Kabgyun Jeong , Wonho Jhe , Jaewan Kim

Under the Eigenstate Thermalization Hypothesis (ETH), quantum-quenched systems equilibrate towards canonical, thermal ensembles. While at first glance the ETH might seem a very strong hypothesis, we show that it is indeed not only…

Quantum Physics · Physics 2016-02-03 Giacomo De Palma , Alessio Serafini , Vittorio Giovannetti , Marcus Cramer

Variational quantum algorithms are among the most promising approaches for simulating interacting quantum many-body systems on noisy intermediate-scale quantum (NISQ) devices. However, the practical success of variational quantum…

Quantum Physics · Physics 2026-01-01 Rudraksh Sharma

The wave function Ansatze are crucial in the context of the Variational Quantum Eigensolver (VQE). In the Noisy Intermediate-Scale Quantum era, the design of low-depth wave function Ansatze is of great importance for executing quantum…

Quantum Physics · Physics 2024-06-18 Zhijie Sun , Jie Liu , Zhenyu Li , Jinlong Yang

The variational approach is a cornerstone of computational physics, considering both conventional and quantum computing computational platforms. The variational quantum eigensolver (VQE) algorithm aims to prepare the ground state of a…

Quantum Physics · Physics 2022-12-16 Nikita Astrakhantsev , Guglielmo Mazzola , Ivano Tavernelli , Giuseppe Carleo

Computing finite temperature properties of a quantum many-body system is key to describing a broad range of correlated quantum many-body physics from quantum chemistry and condensed matter to thermal quantum field theories. Quantum…

Quantum Physics · Physics 2023-08-16 Hai Wang , Jue Nan , Tao Zhang , Xingze Qiu , Wenlan Chen , Xiaopeng Li

In the pursuit of numerically identifying the ground state of quantum many-body systems, approximate quantum wavefunction ansatzes are commonly employed. This study focuses on the spectral decomposition of these approximate quantum…

Quantum Physics · Physics 2025-08-29 Yu-Qin Chen , Shi-Xin Zhang

The variational quantum eigensolver (VQE) is one of the most representative quantum algorithms in the noisy intermediate-size quantum (NISQ) era, and is generally speculated to deliver one of the first quantum advantages for the…

Quantum Physics · Physics 2022-04-13 Shi-Xin Zhang , Zhou-Quan Wan , Chee-Kong Lee , Chang-Yu Hsieh , Shengyu Zhang , Hong Yao