Efficient pseudomode representation and complexity of quantum impurity models

In many important applications a signal consists of a sum of exponential terms. The signal is measured at a discrete set of points in time, with possible errors in the measurements. The Signal Identification (SI) problem is to recover the correct exponents and amplitudes from the noisy data. An algorithm (SNTLN) has been developed which can be used to solve the SI problem by minimizing the residual error in the L1 norm. In this paper the convergence of the SNTLN algorithm is shown, and computational results for two different types of signal are presented, one of which is the sum of complex exponentials with complex amplitudes. For comparison, the test problems were also solved by VarPro, which is based on minimizing the L2 norm of the residual error. It is shown that the SNTLN algorithm is very robust in recovering correct values, in spite of some large errors in the measured data and the initial estimates of the exponents. For the test problems solved, the errors in the exponents and amplitudes obtained by SNTLN1 were essentially independent of the largest errors in the measured data, while the corresponding errors in the VarPro solutions were proportional to these largest data errors.

Electronic-vibrational dynamics in molecular systems that interact with an environment involve a large number of degrees of freedom and are therefore often described by means of open quantum system approaches. A popular approach is to include only the electronic degrees of freedom into the system part and to couple these to a non-Markovian bath of harmonic vibrational modes that is characterized by a spectral density. Since this bath represents both intra-molecular and external vibrations, it is important to understand how to construct a spectral density that accounts for intra-molecular vibrational modes that couple further to other modes. Here, we address this problem by explicitly incorporating an intra-molecular vibrational mode together with the electronic degrees of freedom into the system part and using the Fano theory for a resonance coupled to a continuum to derive an "effective" bath spectral density, which describes the contribution of intra-molecular modes. We compare this effective model for the intra-molecular mode with the method of pseudomodes, a widely used approach in simulation of non-Markovian dynamics. We clarify the difference between these two approaches and demonstrate that the respective resulting dynamics and optical spectra can be very different.

The GPOF (generalized pencil-of-function) method was used to extrapolate the time response from FDTD simulations of EMI problems by approximating the time history as a sum of complex exponentials. This method can significantly shorten the FDTD program execution time. However, various difficulties can arise from parameterization during data-processing. The GPOF is applied to, and studied for, two relevant EMI problems, enclosure design and EMI antenna modeling. The merits of GPOF in modeling shielding enclosures and EMI antennas is evaluated through several examples.

In this paper, the interference mitigation for Frequency Modulated Continuous Wave (FMCW) radar system with a dechirping receiver is investigated. After dechirping operation, the scattered signals from targets result in beat signals, i.e., the sum of complex exponentials while the interferences lead to chirp-like short pulses. Taking advantage of these different time and frequency features between the useful signals and the interferences, the interference mitigation is formulated as an optimization problem: a sparse and low-rank decomposition of a Hankel matrix constructed by lifting the measurements. Then, an iterative optimization algorithm is proposed to tackle it by exploiting the Alternating Direction of Multipliers (ADMM) scheme. Compared to the existing methods, the proposed approach does not need to detect the interference and also improves the estimation accuracy of the separated useful signals. Both numerical simulations with point-like targets and experiment results with distributed targets (i.e., raindrops) are presented to demonstrate and verify its performance. The results show that the proposed approach is generally applicable for interference mitigation in both stationary and moving target scenarios.

This paper develops fast algorithms for the construction of a circulant modulated rate process to match with the two primary traffic statistical functions: rate distribution f(x) and autocorrelation R(/spl tau/). Using existing modeling techniques, f(x) has to be limited to certain forms such as Gaussian or binomial; R(/spl tau/) can only consist of one or two exponential terms which are often real exponentials rather than complex. In reality, these two functions are collected from real traffic traces and generally expressed in a very complicated form. We only consider the traffic whose correlation function can be approximated by the sum of complex exponentials. Our emphasis is placed on the algorithm design for matching complicated R(/spl tau/) in traffic modeling. The typical CPU time for traffic modeling with R(/spl tau/) consisting of five or six complex exponential terms is found to be in the range of a few minutes by the proposed algorithms. Our study further shows an excellent agreement between the original traffic traces and the sequences generated by the matched analytical model. The selection of the measurement-window in traffic statistics collection for queueing performance analysis is also discussed.

Representing real-time data as a sum of complex exponentials provides a compact form that enables both denoising and extrapolation. As a fully data-driven method, the Estimation of Signal Parameters via Rotational Invariance Techniques (ESPRIT) algorithm is agnostic to the underlying physical equations, making it broadly applicable to various observables and experimental or numerical setups. In this work, we consider applications of the ESPRIT algorithm primarily to extend real-time dynamical data from simulations of quantum systems. We evaluate ESPRIT's performance in the presence of noise and compare it to other extrapolation methods. We demonstrate its ability to extract information from short-time dynamics to reliably predict long-time behavior and determine the minimum time interval required for accurate results. We discuss how this insight can be leveraged in numerical methods that propagate quantum systems in time, and show how ESPRIT can predict infinite-time values of dynamical observables, offering a purely data-driven approach to characterizing quantum phases.

We develop a method to study quantum impurity models, small interacting quantum systems bilinearly coupled to an environment, in the presence of an additional Markovian quantum bath, with a generic nonlinear coupling to the impurity. We aim at computing the evolution operator of the reduced density matrix of the impurity, obtained after tracing out all the environmental degrees of freedom. First, we derive an exact real-time hybridization expansion for this quantity, which generalizes the result obtained in the absence of the additional Markovian dissipation and which could be amenable to stochastic sampling through diagrammatic Monte Carlo. Then, we obtain a Dyson equation for this quantity and we evaluate its self-energy with a resummation technique known as the noncrossing approximation. We apply this novel approach to a simple fermionic impurity coupled to a zero temperature fermionic bath and in the presence of Markovian pump, losses, and dephasing.

Central to condensed matter physics are quantum impurity models, which describe how a local degree of freedom interacts with a continuum. Surprisingly, these models are often universal in that they can quantitatively describe many outwardly unrelated physical systems. Here we develop a double quantum dot-based experimental realization of the SU(4) Kondo model, which describes the maximally symmetric screening of a local four-fold degeneracy. As demonstrated through transport measurements and detailed numerical renormalization group calculations, our device affords exquisite control over orbital and spin physics. Because the two quantum dots are coupled only capacitively, we can achieve orbital state- or "pseudospin"-resolved bias spectroscopy, providing intimate access to the interplay of spin and orbital Kondo effects. This cannot be achieved in the few other systems realizing the SU(4) Kondo state.

Quantum dissipative effect on the thermodynamics of an electron in the combined presence of a parabolic potential and a uniform (and homogeneous) magnetic field, is investigated here. Starting from the microscopic system plus bath model, we explicitly derive the thermodynamic properties using the reduced partition function of the system which is calculated using the imaginary time path integral method. The quantum heat bath we consider here is a structured heat bath whose spectral density corresponds to a structured thermal harmonic noise. All the statistical thermodynamic functions calculated do reconcile with the requirements of the fundamental axioms of physics. In particular, the specific heat and the entropy vanishes as the temperature approaches its absolute zero value, a necessity of the third law of thermodynamics. Moreover the specific heat satisfies classical equipartition theorem at high temperatures. The coefficients of the leading temperature dependent terms of the thermodynamic quantities depend only on the damping constant but not on other parameters of the bath spectral density, which is similar to the analysis based on the Drude bath spectral density. Our study facilitates the physics of small quantum systems, which are always in contact with some environments, at very low temperatures. image

Spectral analysis connects graph structure to the eigenvalues and eigenvectors of associated matrices. Much of spectral graph theory descends directly from spectral geometry, the study of differentiable manifolds through the spectra of associated differential operators. But the translation from spectral geometry to spectral graph theory has largely focused on results involving only a few extreme eigenvalues and their associated eigenvalues. Unlike in geometry, the study of graphs through the overall distribution of eigenvalues - the spectral density - is largely limited to simple random graph models. The interior of the spectrum of real-world graphs remains largely unexplored, difficult to compute and to interpret. In this paper, we delve into the heart of spectral densities of real-world graphs. We borrow tools developed in condensed matter physics, and add novel adaptations to handle the spectral signatures of common graph motifs. The resulting methods are highly efficient, as we illustrate by computing spectral densities for graphs with over a billion edges on a single compute node. Beyond providing visually compelling fingerprints of graphs, we show how the estimation of spectral densities facilitates the computation of many common centrality measures, and use spectral densities to estimate meaningful information about graph structure that cannot be inferred from the extremal eigenpairs alone.

Rapid, far-from-equilibrium processes involving excitation of electronic, vibrational, spin, photon, topological, and other degrees of freedom form the basis of modern technologies, including electronics and optoelectronics, solar energy harvesting and conversion to electrical and chemical energy, quantum information processing, spin- and valleytronics, chemical detection, and medical therapies. Such processes are studied experimentally with various time-resolved spectroscopies that allow scientists to track system's evolution on ultrafast time scales and at close to atomistic level of detail. The availability of various forms of lasing has made such measurements easily accessible to many experimental groups worldwide, to study atoms and small molecules, nanoscale and condensed matter systems, proteins, cells, and mesoscopic materials. The experimental work necessitates parallel theoretical efforts needed to interpret the experiments and to provide insights that cannot be gained through measurements due to experimental limitations.Non-adiabatic (NA) molecular dynamics (MD) allows one to study processes at the atomistic level and in the time domain most directly mimicking the time-resolved experiments. Atomistic modeling takes full advantage of chemical intuition and principles that guide design and fabrication of molecules and materials. It provides atomistic origins of quasi-particles, such as holes, excitons, trions, plasmons, phonons, polarons, polaritons, spin-waves, momentum-resolved and topological states, electrically and magnetically polarized structures, and other abstract concepts. An atomistic description enables one to study realistic aspects of materials, which necessarily contain defects, dopants, surfaces, interfaces, passivating ligands, and solvent layers. Often, such realistic features govern material properties and are hard to account for phenomenologically. NA-MD requires few approximations and assumptions. It does not need to assume that atomic motions are harmonic, that electrons are Drude oscillators, that coupling between different degrees of freedom is weak, that dynamics is Markovian or has short memory, or that evolution occurs by exponential kinetics of transitions between few states. The classical or semiclassical treatment of atomic motions constitutes the main approximation of NA-MD and is used because atoms are 3-5 orders of magnitude heavier than electrons. NA-MD is limited by system size, typically hundreds or thousands of atoms, and time scale, picoseconds to nanoseconds. The quality of NA-MD simulations depends on the electronic structure method used to obtain excited state energies and NA couplings.NA-MD has been largely popularized and advanced in the chemistry community that focuses on molecules. Modeling far-from-equilibrium dynamics in nanoscale and condensed matter systems often has to account for other types of physics. At the same time, condensed phase NA-MD allows for approximations that may not work in molecules. Focusing on the recent NA-MD developments aimed at studying excited state processes in nanoscale and condensed phases, this Account considers how the phenomena important on the nanoscale can be incorporated into NA-MD and what approximations can be made to increase its efficiency with complex systems and processes.

Gauge and matter condensates in realistic string models

Matrix product state applications for the ALPS project

The non-Markovian approach developed in the companion paper [Hughes et al., J. Chem. Phys. 131, 024109 (2009)], which employs a hierarchical series of approximate spectral densities, is extended to the treatment of nonadiabatic dynamics of coupled electronic states. We focus on a spin-boson-type Hamiltonian including a subset of system vibrational modes which are treated without any approximation, while a set of bath modes is transformed to a chain of effective modes and treated in a reduced-dimensional space. Only the first member of the chain is coupled to the electronic subsystem. The chain construction can be truncated at successive orders and is terminated by a Markovian closure acting on the end of the chain. From this Mori-type construction, a hierarchy of approximate spectral densities is obtained which approach the true bath spectral density with increasing accuracy. Applications are presented for the dynamics of a vibronic subsystem comprising a high-frequency mode and interacting with a low-frequency bath. The bath is shown to have a striking effect on the nonadiabatic dynamics, which can be rationalized in the effective-mode picture. A reduced two-dimensional subspace is constructed which accounts for the essential features of the nonadiabatic process induced by the effective environmental mode. Electronic coherence is found to be preserved on the shortest time scale determined by the effective mode, while decoherence sets in on a longer time scale. Numerical simulations are carried out using either an explicit wave function representation of the system and overall bath or else an explicit representation of the system and effective-mode part in conjunction with a Caldeira-Leggett master equation.

We analyze the efficiency of quantum simulations of fermionic and bosonic models in trapped ions. In particular, we study the optimal time of entangling gates and the required number of total elementary gates. Furthermore, we exemplify these estimations in the light of quantum simulations of quantum field theories, condensed-matter physics, and quantum chemistry. Finally, we show that trapped-ion technologies are a suitable platform for implementing quantum simulations involving interacting fermionic and bosonic modes, paving the way for overcoming classical computers in the near future.