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We introduce the Hamiltonian Monte Carlo Particle Swarm Optimizer (HMC-PSO), an optimization algorithm that reaps the benefits of both Exponentially Averaged Momentum PSO and HMC sampling. The coupling of the position and velocity of each…

Machine Learning · Computer Science 2022-06-29 Omatharv Bharat Vaidya , Rithvik Terence DSouza , Snehanshu Saha , Soma Dhavala , Swagatam Das

We consider bipartite entangled states that cannot outperform separable states in any linear interferometer. Then, we show that these states can still be more useful metrologically than separable states if several copies of the state are…

Quantum Physics · Physics 2021-04-21 Géza Tóth , Tamás Vértesi , Paweł Horodecki , Ryszard Horodecki

Realizing nonabelian topological orders and their anyon excitations is an esteemed objective. In this work, we propose a novel approach towards this goal: quantum simulating topological orders in the doubled Hilbert space - the space of…

Quantum Physics · Physics 2024-06-24 Shang Liu

We present differentially private (DP) algorithms for bilevel optimization, a problem class that received significant attention lately in various machine learning applications. These are the first algorithms for such problems under standard…

Machine Learning · Computer Science 2026-01-15 Guy Kornowski

The goal of this paper is to review several qualitative properties of well-known eigenvalue problems using a different perspective based on the theory of effective Hamiltonians, working exclusively on the Hopf-Cole transform of the…

Analysis of PDEs · Mathematics 2025-06-06 Idriss Mazari-Fouquer

A generic procedure is proposed to construct many-body quantum Hamiltonians with partial dynamical symmetry. It is based on a tensor decomposition of the Hamiltonian and allows the construction of a hierarchy of interactions that have…

Nuclear Theory · Physics 2009-04-09 J. E. Garcia-Ramos , A. Leviatan , P. Van Isacker

Quantum simulators with hundreds of qubits and engineerable Hamiltonians have the potential to explore quantum many-body models that are intractable for classical computers. However, learning the simulated Hamiltonian, a prerequisite for…

The local Hamiltonian problem consists of estimating the ground-state energy (given by the minimum eigenvalue) of a local quantum Hamiltonian. First, we show the existence of a good product-state approximation for the ground-state energy of…

Quantum Physics · Physics 2016-02-04 Fernando G. S. L. Brandão , Aram W. Harrow

Here we consider using quantum annealing to solve Set Cover with Pairs (SCP), an NP-hard combinatorial optimization problem that play an important role in networking, computational biology, and biochemistry. We show an explicit construction…

Quantum Physics · Physics 2016-08-31 Yudong Cao , Shuxian Jiang , Debbie Perouli , Sabre Kais

The entanglement entropy probing novel phases and phase transitions numerically via quantum Monte Carlo has made great achievements in large-scale interacting spin/boson systems. In contrast, the numerical exploration in interacting fermion…

Statistical Mechanics · Physics 2025-05-15 Weilun Jiang , Gaopei Pan , Zhe Wang , Bin-Bin Mao , Heng Shen , Zheng Yan

The variational quantum-classical algorithms are the most promising approach for achieving quantum advantage on near-term quantum simulators. Among these methods, the variational quantum eigensolver has attracted a lot of attention in…

Quantum Physics · Physics 2023-01-24 Chufan Lyu , Xusheng Xu , Man-Hong Yung , Abolfazl Bayat

The paper proposes a new Monte-Carlo simulator combining the advantages of Sequential Monte Carlo simulators and Hamiltonian Monte Carlo simulators. The result is a method that is robust to multimodality and complex shapes to use for…

Computation · Statistics 2018-12-20 Remi Daviet

Quantum algorithms for probing ground-state properties of quantum systems require good initial states. Projection-based methods such as eigenvalue filtering rely on inputs that have a significant overlap with the low-energy subspace, which…

Quantum Physics · Physics 2024-04-10 Danial Motlagh , Modjtaba Shokrian Zini , Juan Miguel Arrazola , Nathan Wiebe

To analyze quantum many-body Hamiltonians, recently, machine learning techniques have been shown to be quite useful and powerful. However, the applicability of such machine learning solvers is still limited. Here, we propose schemes that…

Strongly Correlated Electrons · Physics 2020-04-17 Yusuke Nomura

We study numerically a disordered transverse-field Ising Hamiltonian with long-range couplings. This model was recently investigated experimentally in a trapped-ion quantum simulator and was found to exhibit features of many-body…

Disordered Systems and Neural Networks · Physics 2016-03-01 Yang-Le Wu , S. Das Sarma

Hamiltonian learning is crucial to the certification of quantum devices and quantum simulators. In this paper, we propose a hybrid quantum-classical Hamiltonian learning algorithm to find the coefficients of the Pauli operator components of…

Quantum Physics · Physics 2023-10-16 Youle Wang , Guangxi Li , Xin Wang

A high-order accurate adjoint-based optimization framework is presented for unsteady multiphysics problems. The fully discrete adjoint solver relies on the high-order, linearly stable, partitioned solver introduced in [1], where different…

Numerical Analysis · Mathematics 2019-01-01 Daniel Z. Huang , Per-Olof Persson , Matthew J. Zahr

The tunneling decay event of a metastable state in a fully connected quantum spin model can be simulated efficiently by path integral quantum Monte Carlo (QMC) [Isakov $et~al.$, Phys. Rev. Lett. ${\bf 117}$, 180402 (2016).]. This is because…

Quantum Physics · Physics 2017-11-01 Zhang Jiang , Vadim N. Smelyanskiy , Sergio Boixo , Hartmut Neven

Interference and diffraction of two-identical-particles are considered in the context of open quantum systems. This theoretical study is carried out within two approaches, the effective time-dependent Hamiltonian due to Caldirola-Kanai (CK)…

Quantum Physics · Physics 2020-01-22 S. V. Mousavi , S. Miret-Artés

Quantum annealing promises to be an effective heuristic for complex NP-hard problems. However, clear demonstrations of quantum advantage are wanting, primarily constrained by the difficulty of embedding the problem into the quantum…

Quantum Physics · Physics 2022-11-15 Minjae Jo , Michael Hanks , M. S. Kim