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Adaptive data collection and analysis, where data are being fed back to update the measurement settings, can greatly increase speed, precision, and reliability of the characterization of quantum systems. However, decoherence tends to make…

Quantum Physics · Physics 2016-02-03 Markku P. V. Stenberg , Oliver Köhn , Frank K. Wilhelm

Integrability is a cornerstone of classical mechanics, where it has a precise meaning. Extending this notion to quantum systems, however, remains subtle and unresolved. In particular, deciding whether a quantum Hamiltonian - viewed simply…

Statistical Mechanics · Physics 2026-02-10 Feng He , Arthur Hutsalyuk , Giuseppe Mussardo , Andrea Stampiggi

Obtaining accurate estimates of machine learning model uncertainties on newly predicted data is essential for understanding the accuracy of the model and whether its predictions can be trusted. A common approach to such uncertainty…

In the supersymmetric quantum mechanics formalism, the shape invariance condition provides a sufficient constraint to make a quantum mechanical problem solvable; i.e., we can determine its eigenvalues and eigenfunctions algebraically. Since…

High Energy Physics - Theory · Physics 2011-11-10 Jonathan Bougie , Asim Gangopadhyaya , Jeffry V. Mallow

The dynamics induced while controlling quantum systems by optimally shaped laser pulses have often been difficult to understand in detail. A method is presented for quantifying the importance of specific sequences of quantum transitions…

Quantum Physics · Physics 2009-11-07 Eric Dennis , Herschel Rabitz

A set of exactly solvable one-dimensional quantum mechanical potentials is described. It is defined by a finite-difference-differential equation generating in the limiting cases the Rosen-Morse, harmonic, and P\"oschl-Teller potentials.…

High Energy Physics - Theory · Physics 2009-01-23 V. Spiridonov

Quantum metrology is a promising practical use case for quantum technologies, where physical quantities can be measured with unprecedented precision. In lieu of quantum error correction procedures, near term quantum devices are expected to…

Quantum Physics · Physics 2021-12-03 Yingkai Ouyang , Nathan Shettell , Damian Markham

Solutions to many-body problem instances often involve an intractable number of degrees of freedom and admit no known approximations in general form. In practice, representing quantum-mechanical states of a given Hamiltonian using available…

Quantum Physics · Physics 2020-11-10 Andrey Kardashin , Alexey Uvarov , Dmitry Yudin , Jacob Biamonte

We present a variational algorithm for fault tolerant quantum computing to solve a system of linear equations which directly maximises the parameters of the target fidelity. This so-called measurement test algorithm can be applied to any…

Quantum Physics · Physics 2026-04-30 Alain Giresse Tene , Thomas Konrad

We address quantum invisibility in the context of electronics in nanoscale quantum structures. We make use of the freedom of design that quantum corrals provide and show that quantum mechanical objects can be hidden inside the corral, with…

Mesoscale and Nanoscale Physics · Physics 2010-05-18 J. Fransson , H. C. Manoharan , A. V. Balatsky

Resampling methods such as the bootstrap have proven invaluable in the field of machine learning. However, the applicability of traditional bootstrap methods is limited when dealing with large streams of dependent data, such as time series…

Machine Learning · Statistics 2024-02-28 Nicolai Palm , Thomas Nagler

This paper proposes parametric and non-parametric hypothesis testing algorithms for detecting anisotropy -- rotational variance of the covariance function in random fields. Both algorithms are based on resampling mechanisms, which enable…

Methodology · Statistics 2021-06-08 Assaf Rabinowicz , Saharon Rosset

We test the bootstrap approach for determining the spectrum of one dimensional Hamiltonians. In this paper we focus on problems that have a two parameter search space in the bootstrap approach: the double well and a periodic potential…

High Energy Physics - Theory · Physics 2022-06-29 David Berenstein , George Hulsey

We present two results which combined enable one to reliably detect multimode, multipartite entanglement in the presence of measurement errors. The first result leads to a method to compute the best (approximated) physical covariance matrix…

Quantum Physics · Physics 2016-10-05 E. Shchukin , P. van Loock

Classical shadows are an efficient method for constructing an approximate classical description of a quantum state using very few measurements. In the paper we propose to enhance classical shadow methods using bootstrap resampling methods.…

Quantum Physics · Physics 2025-11-18 Eric Ghysels , Jack Morgan

We address parameter estimation for complex/structured systems and suggest an effective estimation scheme based on continuous-variables quantum probes. In particular, we investigate the use of a single bosonic mode as a probe for Ohmic…

Quantum Physics · Physics 2018-01-31 Matteo Bina , Federico Grasselli , Matteo G. A. Paris

The partially linear binary choice model can be used for estimating structural equations where nonlinearity may appear due to diminishing marginal returns, different life cycle regimes, or hectic physical phenomena. The inference procedure…

Econometrics · Economics 2023-12-01 Wenzheng Gao , Zhenting Sun

This thesis seeks to develop a general method for solving so-called quantum realizability problems, which are questions of the following form: under which conditions does there exist a quantum state exhibiting a given collection of…

Quantum Physics · Physics 2024-02-20 Thomas C. Fraser

Second order integrals of motion for 3d quantum mechanical systems with position dependent masses (PDM) are classified. Namely, all PDM systems are specified which, in addition to their rotation invariance, admit at least one second order…

Mathematical Physics · Physics 2016-03-04 A. G. Nikitin

Recovering dynamical equations from observed noisy data is the central challenge of system identification. We develop a statistical mechanics approach to analyze sparse equation discovery algorithms, which typically balance data fit and…

Statistical Mechanics · Physics 2025-09-16 Andrei A. Klishin , Joseph Bakarji , J. Nathan Kutz , Krithika Manohar