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Many remarkable properties of quantum materials emerge from states with intricate coupling between the charge, spin and orbital degrees of freedom. Ultrafast photo-excitations of these materials hold great promise for understanding and…

Strongly Correlated Electrons · Physics 2019-04-02 Y. Cao , D. G. Mazzone , D. Meyers , J. P. Hill , X. Liu , S. Wall , M. P. M. Dean

We provide a protocol to measure out-of-time-order correlation functions. These correlation functions are of theoretical interest for diagnosing the scrambling of quantum information in black holes and strongly interacting quantum systems…

Quantum Physics · Physics 2016-11-02 Brian Swingle , Gregory Bentsen , Monika Schleier-Smith , Patrick Hayden

We address the challenge of estimation in the context of constant linear effect models with dense functional responses. In this framework, the conditional expectation of the response curve is represented by a linear combination of…

Methodology · Statistics 2024-10-07 Pratim Guha Niyogi , Ping-Shou Zhong

In many unconventional superconductors, nematic quantum fluctuations are strongest where the critical temperature is highest, inviting the conjecture that nematicity plays an important role in the pairing mechanism. Recently,…

Strongly Correlated Electrons · Physics 2020-05-13 Samuel Lederer , Erez Berg , Eun-Ah Kim

Sequential measurements on a single particle play an important role in fundamental tests of quantum mechanics. We provide a general method to analyze temporal quantum correlations, which allows us to compute the maximal correlations for…

Quantum Physics · Physics 2013-07-17 Costantino Budroni , Tobias Moroder , Matthias Kleinmann , Otfried Gühne

Analyzing time series in the frequency domain enables the development of powerful tools for investigating the second-order characteristics of multivariate processes. Parameters like the spectral density matrix and its inverse, the coherence…

Methodology · Statistics 2024-01-19 Jonas Krampe , Efstathios Paparoditis

A precise time-dependent control of a quantum system relies on an accurate account of the quantum interference among the system, the control and the environment. A diagrammatic technique has been recently developed to precisely calculate…

Mesoscale and Nanoscale Physics · Physics 2015-05-30 Ching-Kit Chan , L. J. Sham

Machine learning models are a powerful theoretical tool for analyzing data from quantum simulators, in which results of experiments are sets of snapshots of many-body states. Recently, they have been successfully applied to distinguish…

We measure the intensity correlation function of two interfering spatially displaced copies of a phase fluctuating Bose-Einstein Condensate (BEC). It is shown that this corresponds to a measurement of the phase correlation properties of the…

Soft Condensed Matter · Physics 2009-11-10 D. Hellweg , L. Cacciapuoti , M. Kottke , T. Schulte , K. Sengstock , W. Ertmer , J. J. Arlt

We put forward a functional renormalisation group approach for the direct computation of real time correlation functions, also applicable at finite temperature and density. We construct a general class of regulators that preserve the…

High Energy Physics - Phenomenology · Physics 2017-07-07 Jan M. Pawlowski , Nils Strodthoff

We measure the temporal pair correlation function $g^{(2)}(\tau)$ of a trapped gas of bosons above and below the critical temperature for Bose-Einstein condensation. The measurement is performed {\it in situ} using a local, time-resolved…

We will examine the possible link between spin fluctuations and the superconducting mechanism in the iron-based high temperature superconductor Ba(Fe,Co)2As2 based on NMR and high pressure transport measurements.

Superconductivity · Physics 2015-05-14 K. Ahilan , F. L. Ning , T. Imai , A. S. Sefat , M. A. McGuire , B. C. Sales , D. Mandrus , P. Cheng , B. Shen , H. H. Wen

We consider a quantum mechanical system represented in phase space (referred to hereafter as "Wigner space"), coupled to a harmonic oscillator bath. We derive quantum hierarchal Fokker-Planck (QHFP) equations not only in real time, but also…

Statistical Mechanics · Physics 2015-04-16 Yoshitaka Tanimura

Spatial correlation functions provide a glimpse into the quantum correlations within a quantum system. Ions in a linear trap collectively form a nonuniform, discretized background on which a scalar field of phonons propagates. Trapped ions…

Quantum Physics · Physics 2009-09-29 Nicolas C. Menicucci , G. J. Milburn

Time-resolved studies of quantum systems are the key to understand quantum dynamics at its core. The real-time measurement of individual quantum numbers as they switch between certain discrete values, well known as random telegraph signal,…

Mesoscale and Nanoscale Physics · Physics 2022-03-02 Eric Kleinherbers , Philipp Stegmann , Annika Kurzmann , Martin Geller , Axel Lorke , Jürgen König

We present an elementary and self-contained account of the analogies existing between classical diffusion and the imaginary-time evolution of quantum systems. These analogies are used to develop a new quantum simulation method which allows…

Condensed Matter · Physics 2007-05-23 S. Baroni , S. Moroni

We present a real-space method for computing the random phase approximation (RPA) correlation energy within Kohn-Sham density functional theory, leveraging the low-rank nature of the frequency-dependent density response operator. In…

Computational Physics · Physics 2025-04-03 Boqin Zhang , Shikhar Shah , John E. Pask , Edmond Chow , Phanish Suryanarayana

Feynman path integrals (PIs) have found many uses in approximate quantum dynamics methods that are able to efficiently calculate real-time quantum correlation functions. The PIs typically take the form of discrete imaginary time slices over…

Chemical Physics · Physics 2025-10-14 Nathan London , Mohammad R. Momeni

Time-varying volatility is an inherent feature of most economic time-series, which causes standard correlation estimators to be inconsistent. The quadrant correlation estimator is consistent but very inefficient. We propose a novel…

Econometrics · Economics 2023-11-01 Peter Reinhard Hansen , Yiyao Luo

Canonical correlation analysis (CCA) is a technique to find statistical dependencies between a pair of multivariate data. However, its application to high dimensional data is limited due to the resulting time complexity. While the…

Machine Learning · Computer Science 2020-12-29 Naoko Koide-Majima , Kei Majima