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We report on an analog computing system with coupled non-linear oscillators which is capable of solving complex combinatorial optimization problems using the weighted Ising model. The circuit is composed of a fully-connected 4-node LC…

Computational Physics · Physics 2019-08-28 Jeffrey Chou , Suraj Bramhavar , Siddhartha Ghosh , William Herzog

The 1+1D Ising model is an ideal benchmark for quantum algorithms, as it is very well understood theoretically. This is true even when expanding the model to include complex coupling constants. In this work, we implement quantum algorithms…

Quantum Physics · Physics 2023-12-01 Erik Gustafson , Michael Hite , Jay Hubisz , Bharath Sambasivam , Judah Unmuth-Yockey

Determining properties of ground states of spin Hamiltonians remains a topic of central relevance connecting disciplines of mathematical, theoretical and applied physics. In the last few decades, ground state properties of physical systems…

Quantum Physics · Physics 2021-12-28 Jacob Biamonte

A non-equilibrium open-dissipative neural network, such as a coherent Ising machine based on mutually coupled optical parametric oscillators, has been proposed and demonstrated as a novel computing machine for hard combinatorial…

Quantum ground-state problems are computationally hard problems; for general many-body Hamiltonians, there is no classical or quantum algorithm known to be able to solve them efficiently. Nevertheless, if a trial wavefunction approximating…

Neural network quantum states provide a novel representation of the many-body states of interacting quantum systems and open up a promising route to solve frustrated quantum spin models that evade other numerical approaches. Yet its…

Strongly Correlated Electrons · Physics 2022-01-19 Eric Zou , Erik Long , Erhai Zhao

Two-photon coherent states are one of the main building pillars of non-linear and quantum optics. It is the basis for the generation of minimum-uncertainty quantum states and entangled photon pairs, applications not obtainable from standard…

Mesoscale and Nanoscale Physics · Physics 2022-05-30 A. A. Reynoso , G. Usaj , D. L. Chafatinos , F. Mangussi , A. E. Bruchhausen , A. S. Kuznetsov , K. Biermann , P. V. Santos , A. Fainstein

Quantum state tomography (QST) is essential for validating quantum devices but suffers from exponential scaling in system size. Neural-network quantum states, such as Restricted Boltzmann Machines (RBMs), can efficiently parameterize…

Quantum Physics · Physics 2026-01-30 Simon Tonner , Viet T. Tran , Richard Kueng

Topological symmetries, invertible and otherwise, play a fundamental role in the investigation of quantum field theories. Despite their ubiquitous importance across a multitude of disciplines ranging from string theory to condensed matter…

Quantum Physics · Physics 2025-10-17 Christopher Lamb , Robert M. Konik , Hubert Saleur , Ananda Roy

A new simulation technique to obtain the synchronized steady-state solutions existing in coupled oscillator systems is presented. The technique departs from a semi-analytical formulation presented in previous works. It extends the model of…

Systems and Control · Electrical Eng. & Systems 2024-04-22 Pedro Umpierrez , Victor Arana , Sergio Sancho

The possibility of using strongly and continuously interacting spins for quantum computation has recently been discussed. Here we present a simple optical scheme that achieves this goal while avoiding the drawbacks of earlier proposals. We…

Quantum Physics · Physics 2009-11-10 Simon C. Benjamin , Brendon W. Lovett , John H. Reina

We show how quantum metrology protocols that seek to estimate the parameters of a Hamiltonian that exhibits a quantum phase transition can be efficiently simulated on an exponentially smaller quantum computer. Specifically, by exploiting…

Quantum Physics · Physics 2016-12-28 W. L. Boyajian , M. Skotiniotis , W. Dür , B. Kraus

Networks of optical oscillators simulating coupled Ising spins have been recently proposed as a heuristic platform to solve hard optimization problems. These networks, called coherent Ising machines (CIMs), exploit the fact that the…

Emerging Technologies · Computer Science 2021-11-15 Marcello Calvanese Strinati , Davide Pierangeli , Claudio Conti

Stabilizer states, which are also known as the Clifford states, have been commonly utilized in quantum information, quantum error correction, and quantum circuit simulation due to their simple mathematical structure. In this work, we apply…

Quantum Physics · Physics 2025-06-26 Jiace Sun , Lixue Cheng , Shi-Xin Zhang

By analytically continuing the eigenvalue problem of a system of two coupled harmonic oscillators in the complex coupling constant $g$, we have found a continuation structure through which the conventional ground state of the decoupled…

Mathematical Physics · Physics 2018-08-16 Alexander Felski , S. P. Klevansky

We propose a polynomial-time algorithm for simulation of the class of pairing Hamiltonians, e.g., the BCS Hamiltonian, on an NMR quantum computer. The algorithm adiabatically finds the low-lying spectrum in the vicinity of the gap between…

Quantum Physics · Physics 2009-11-07 L. -A. Wu , M. S. Byrd , D. A. Lidar

The Kennedy and O'Hagan (KOH) calibration framework uses coupled Gaussian processes (GPs) to meta-model an expensive simulator (first GP), tune its ``knobs" (calibration inputs) to best match observations from a real physical/field…

Methodology · Statistics 2024-10-01 Scott Koermer , Justin Loda , Aaron Noble , Robert B. Gramacy

State measurement of a quantum harmonic oscillator is essential in quantum optics and quantum information processing. In a system of trapped ions, we experimentally demonstrate the projective measurement of the state of the ions' motional…

Quantum Physics · Physics 2017-11-15 Shiqian Ding , Gleb Maslennikov , Roland Hablutzel , Dzmitry Matsukevich

Solving combinatorial optimization problems efficiently through emerging hardware by converting the problem to its equivalent Ising model and obtaining its ground state is known as Ising computing. Phase-binarized oscillators (PBO), modeled…

The growing challenges of scaling digital computing motivate new approaches, especially through the dynamical evolution of physical systems that mimic neural networks and combinatorial optimization problems. While light is a hyper efficient…

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