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Most experimental and theoretical studies of adiabatic optimization use stoquastic Hamiltonians, whose ground states are expressible using only real nonnegative amplitudes. This raises a question as to whether classical Monte Carlo methods…

Quantum Physics · Physics 2016-11-01 Michael Jarret , Stephen P. Jordan , Brad Lackey

Digital-analog is a universal quantum computing paradigm which employs the natural entangling Hamiltonian of the system and single-qubit gates as resources. Here, we study the stability of these protocols against Hamiltonian…

Quantum Physics · Physics 2026-03-10 Mikel Garcia-de-Andoin , Alatz Álvarez-Ahedo , Adrián Franco-Rubio , Mikel Sanz

Fast nonadiabatic control protocols known as shortcuts to adiabaticity have found a plethora of applications, but their use has been severely limited to speeding up the dynamics of isolated quantum systems. We introduce shortcuts for open…

Quantum Physics · Physics 2020-08-06 L. Dupays , I. L. Egusquiza , A. del Campo , A. Chenu

Online and stochastic learning has emerged as powerful tool in large scale optimization. In this work, we generalize the Douglas-Rachford splitting (DRs) method for minimizing composite functions to online and stochastic settings (to our…

Numerical Analysis · Computer Science 2016-12-22 Ziqiang Shi , Rujie Liu

The ability to execute a large number of quantum gates in parallel is a fundamental requirement for quantum error correction, allowing an error threshold to exist under the finite coherence time of physical qubits. Recently, two-dimensional…

Quantum Physics · Physics 2025-01-20 Fangxuan Liu , Gaoxiang Tang , Luming Duan , Yukai Wu

Real-time simulations of laser-driven electron dynamics contain information about molecular optical properties through all orders in response theory. These properties can be extracted by assuming convergence of the power series expansion of…

Stochastic optimization in learning and inference often relies on Markov chain Monte Carlo (MCMC) to approximate gradients when exact computation is intractable. However, finite-time MCMC estimators are biased, and reducing this bias…

Statistics Theory · Mathematics 2026-02-02 Antoine Godichon-Baggioni , Gabriel Lang , Sylvain Le Corff , Julien Stoehr , Sobihan Surendran

The finite time operation of a quantum Otto heat engine leads to a trade-off between efficiency and output power, which is due to the deviation of the system from the adiabatic path. This trade-off caveat can be bypassed by using the…

Quantum Physics · Physics 2024-12-31 Krishna Shende , Matreyee Kandpal , Arvind , Kavita Dorai

Codesign, an integral part of computer architecture referring to the information interaction in hardware-software stack, is able to boost the algorithm mapping and execution in the computer hardware. This well applies to the noisy…

Adiabatic protocols are often employed in state preparation schemes but require the system to be driven by a slowly varying Hamiltonian so that transitions between instantaneous eigenstates are exponentially suppressed. Counterdiabatic…

Quantum Physics · Physics 2024-03-20 Callum W. Duncan

Shortcut to adiabaticity in various quantum systems has attracted much attention with the wide applications in quantum information processing and quantum control. In this paper, we concentrate on stimulated Raman shortcut-to-adiabatic…

Quantum Physics · Physics 2016-12-21 Yi-Chao Li , Xi Chen

We study a deformation of the counterdiabatic-driving Hamiltonian as a systematic strategy for an adiabatic control of quantum states. Using a unitary transformation, we design a convenient form of the driver Hamiltonian. We apply the…

Quantum Physics · Physics 2015-04-16 Kazutaka Takahashi

Past research has indicated that the covariance of the Stochastic Gradient Descent (SGD) error done via minibatching plays a critical role in determining its regularization and escape from low potential points. Motivated by some new…

Machine Learning · Statistics 2023-03-02 Riddhiman Bhattacharya , Tiefeng Jiang

Topological quantum information processing relies on adiabatic braiding of nonabelian quasiparticles. Performing the braiding operations in finite time introduces transitions out of the ground-state manifold and deviations from the…

Mesoscale and Nanoscale Physics · Physics 2015-05-29 Torsten Karzig , Falko Pientka , Gil Refael , Felix von Oppen

An important class of physical systems that are of interest in practice are input-output open quantum systems that can be described by quantum stochastic differential equations and defined on an infinite-dimensional underlying Hilbert…

Quantum Physics · Physics 2016-09-26 O. Techakesari , H. I. Nurdin

We consider Monte-Carlo discretizations of partial differential equations based on a combination of semi-lagrangian schemes and probabilistic representations of the solutions. We study the Monte-Carlo error in a simple case, and show that…

Numerical Analysis · Mathematics 2013-03-18 Charles-Edouard Bréhier , Erwan Faou

An extension is given for the standard two component model of adiabatic, Born-Oppenheimer (BO) electronic states in a polyatonic molecule, by use of Mathieu functions of arbitrary order. The curl or compatibility conditions for the…

Chemical Physics · Physics 2016-09-08 R. Englman , A. Yahalom , M. Baer

In the circuit model of quantum computing, amplitude amplification techniques can be used to find solutions to NP-hard problems defined on $n$-bits in time $\text{poly}(n) 2^{n/2}$. In this work, we investigate whether such general…

Consider the multiple linear regression model $y_{i} = \boldsymbol{x}'_{i} \boldsymbol{\beta} + \epsilon_{i}$, where $\epsilon_i$'s are independent and identically distributed random variables, $\mathbf{x}_i$'s are known design vectors and…

Statistics Theory · Mathematics 2017-12-19 Debraj Das , Soumendra Nath Lahiri

In noisy quantum systems, achieving high-fidelity state preparation using the adiabatic approach faces a dilemma: either extending the evolution time to reduce diabatic transitions or shortening it to mitigate decoherence effects. Here, we…

Quantum Physics · Physics 2024-08-28 Kang Cai , Prabin Parajuli , Anuvetha Govindarajan , Lin Tian