Challenges
Datasets
Workspaces
Papers
Discussions
Leaderboard
Log inSign up
Challenges
Datasets
Workspaces
Papers
Discussions
Leaderboard
Blog
Job Board
Q3AS

© 2026 Aqora Quantum S.A.S.

TermsPrivacyLegal Notice

arXiv:2406.01978 · The Journal of Chemical Physics

Improved memory truncation scheme for quasi-adiabatic propagator path integral via influence functional renormalization

Limin Liu, Jiajun Ren, Wei‐Hai Fang

Published Aug 22, 2024• 1 citation
arXivHTMLPDF

Abstract

Accurately simulating non-Markovian quantum dynamics in system-bath coupled problems remains challenging. In this work, we present a novel memory truncation scheme for the iterative quasi-adiabatic propagator path integral (iQuAPI) method to improve accuracy. Conventional memory truncation in iQuAPI discards all influence functional beyond a certain time interval, which is not effective for problems with a long memory time. Our proposed scheme selectively retains the most significant parts of the influence functional using the density matrix renormalization group algorithm. We validate the effectiveness of our scheme through simulations of the spin-boson model across various parameter sets, demonstrating faster convergence and improved accuracy compared to the conventional scheme. Our findings suggest that the new memory truncation scheme significantly advances the capabilities of iQuAPI for problems with a long memory time.

DOI
10.1063/5.0221916

Related papers

Small Matrix Path Integral for Driven Dissipative Dynamics

Nancy Makri

The small matrix decomposition of the quasi-adiabatic propagator path integral (SMatPI) for a system coupled to a harmonic bath, which accounts for multitime memory correlations in the influence functional without the use of tensors, is extended to include a time-dependent term that drives the system. In the case of a periodic field, the algorithm requires the construction of SMatPI matrices initialized over a short time interval. The SMatPI algorithm circumvents the large array storage of tensor-based iterative path integral decompositions and, in the case of a periodic field, also eliminates the demanding tensor multiplication at each time step, leading to dramatic savings which allow the fully quantum mechanical treatment of multistate systems and long-memory environments.

The Journal of Physical Chemistry A•Nov 23, 2021•29 citations

Numerically efficient quasi-adiabatic propagator path integral approach with two independent non-commuting baths

Roman Ovcharenko, Benjamin Philipp Fingerhut

Path integral methods, such as the quasi-adiabatic propagator path integral (QUAPI), are widely used in general-purpose and highly accurate numerical benchmark simulations of open quantum systems, particularly in regimes inaccessible to perturbative methods. Nevertheless, the applicability of the QUAPI method to realistic systems of interest is restricted by the exponentially growing computer memory requirements with respect to the size of the quantum system and the time range of non-Markovian correlation effects. This exponential "wall" becomes even more severe for multiple non-commuting fluctuating environments. In the present work, we address the numerical efficiency and accuracy of approximations that have been introduced for the QUAPI method with a single general environment, for the case of two independent non-commuting environments where one of them is considered as a pure dephasing environment. In particular, we consider a sharply defined cutoff of the memory time, path filtering, and mask assisted coarse graining of influence functional coefficients as approximations. We demonstrate that commonly applied numerical techniques, such as path filtering, cannot be straightforwardly transferred to the two-bath case even in the weak-coupling and quasi-Markovian limits. On the other hand, the sharply defined memory cutoff can be accurately handled with the mask assisted coarse graining approach. Our findings demonstrate that if system coupling operators to different baths do not commute, the additive nature of the statistically independent environments may be misleading. In particular, the quasi-Markovian nature of a pure dephasing bath is lost once there simultaneously exists another non-commuting source of fluctuations.

arXiv:2503.21693•The Journal of Chemical Physics•Jul 7, 2025•3 citations

Path integral renormalization for quantum dissipative dynamics with multiple timescales

Nancy Makri

The reduced density matrix of a system coupled to a harmonic dissipative bath can be obtained accurately using an iterative path integral methodology that involves a propagator tensor, whose rank is roughly equal to the number of time steps that span the bath-induced memory. The present work shows that even in situations where the bath is characterized by high-frequency modes (which necessitate a small time step) and slow oscillators (which give rise to very long memory), efficient propagation that takes into account the memory on all time scales is feasible by renormalizing the propagator matrix to include successively larger-length influence functional correlations. At its crudest level, the renormalized propagator is an ordinary matrix, thus the computational demands of the method are very modest, similar to those for propagating the bare system. Yet, test applications on dissipative two-level systems show that the method produces accurate results in demanding situations. By including memory on successively increasing time scales, the method is capable of capturing nonexponential kinetics induced by sluggish solvents.

Molecular Physics•May 10, 2012•30 citations

Numerical path integral techniques for long time dynamics of quantum dissipative systems

Nancy Makri

Recent progress in numerical methods for evaluating the real-time path integral in dissipative harmonic environments is reviewed. Quasi-adiabatic propagators constructed numerically allow convergence of the path integral with large time increments. Integration of the harmonic bath leads to path integral expressions that incorporate the exact dynamics of the quantum particle along the adiabatic path, with an influence functional that describes nonadiabatic corrections. The resulting quasi-adiabatic propagator path integral is evaluated by efficient system-specific quadratures in most regimes of parameter space, although some cases are handled by grid Monte Carlo sampling. Exploiting the finite span of nonlocal influence functional interactions characteristic of broad condensed phase spectra leads to an iterative scheme for calculating the path integral over arbitrary time lengths. No uncontrolled approximations are introduced, and the resulting methodology converges to the exact quantum result with modest amounts of computational power. Applications to tunneling dynamics in the condensed phase are described.

Journal of Mathematical Physics•May 1, 1995•377 citations

Scalable Distributed Memory Implementation of the Quasi-Adiabatic Propagator Path Integral

Roman Ovcharenko, Xiangyu Xu, Benjamin Philipp Fingerhut

The accurate simulation of dissipative quantum dynamics subject to a non-Markovian environment poses persistent numerical challenges, in particular, for structured environments, where sharp mode resonances induce long-time system bath correlations. We present a scalable distributed memory implementation of the mask-assisted coarse graining of influence coefficients (MACGIC)-quasi-adiabatic propagator path integral (-QUAPI) method that exploits the memory resources of multiple compute nodes and mitigates the memory bottleneck of the method via a new premerging algorithm and a hash-based look-up (hMACGIC-QUAPI) while preserving numerical accuracy. The source code of the hMACGIC-QUAPI implementation is available in a publicly accessible Git repository under GPL license. The developed distributed memory implementation spreads the paths over the computing nodes by means of the MPI protocol, and efficient high level path management is achieved via the hash map-based implementation with constant access time. The efficiency of the implementation is demonstrated in large-scale dissipative quantum dynamics simulations that account for the coupling to a structured non-Markovian environment containing a sharp resonance, a setup for which convergence properties are investigated in depth. Broad applicability and the nonperturbative nature of the simulation method is illustrated via the tuning of the mode resonance frequency of the structured environment with respect to the characteristic system frequency. The simulations reveal a splitting of resonances due to a strong system–environment interaction and the emergence of sidebands due to multiexcitations of the bosonic mode that are not accounted for in perturbative approaches. The simulations demonstrate the versatility of the new hMACGIC-QUAPI method in the presence of strong non-Markovian system bath correlations.

arXiv:2506.03127•Journal of Chemical Theory and Computation•Apr 8, 2026•2 citations

Efficient memory equation algorithm for reduced dynamics in spin-boson models

Andrei A. Golosov, Richard A. Friesner, Philip Pechukas

The dynamics of a one-dimensional quantum system coupled to a harmonic bath can be expressed through Feynman’s path integral expression for the reduced density matrix. In this expression the influence of the environment is seen in correlations between positions of the system that are nonlocal in time. Makri and Makarov [J. Chem. Phys. 102, 4600 (1995)] showed that for many practical problems correlations over only a few time steps, Δkmax, need to be taken into account, which led to an efficient iterative scheme. However, this algorithm scales as the size of the system to the power of 2(Δkmax+1), which restricts the size of the system that can be studied with this method. In this work we present an efficient algorithm which scales linearly with Δkmax. In our method the reduced density matrix is written as a convolution of its past values with an integral equation kernel. The calculation of that kernel is based on a perturbative expansion of the discretized quasiadiabatic path integral expression for the reduced density matrix. The expansion ignores certain types of correlations.

The Journal of Chemical Physics•Jan 1, 1999•60 citations
Accurately simulating non-Markovian quantum dynamics in system-bath coupled problems remains challenging. In this work, we present a novel memory truncation scheme for the iterative quasi-adiabatic propagator path integral (iQuAPI) method to improve accuracy. Conventional memory truncation in iQuAPI discards all influence functional beyond a certain time interval, which is not effective for problems with a long memory time. Our proposed scheme selectively retains the most significant parts of the influence functional using the density matrix renormalization group algorithm. We validate the effectiveness of our scheme through simulations of the spin-boson model across various parameter sets, demonstrating faster convergence and improved accuracy compared to the conventional scheme. Our findings suggest that the new memory truncation scheme significantly advances the capabilities of iQuAPI for problems with a long memory time.
The small matrix decomposition of the quasi-adiabatic propagator path integral (SMatPI) for a system coupled to a harmonic bath, which accounts for multitime memory correlations in the influence functional without the use of tensors, is extended to include a time-dependent term that drives the system. In the case of a periodic field, the algorithm requires the construction of SMatPI matrices initialized over a short time interval. The SMatPI algorithm circumvents the large array storage of tensor-based iterative path integral decompositions and, in the case of a periodic field, also eliminates the demanding tensor multiplication at each time step, leading to dramatic savings which allow the fully quantum mechanical treatment of multistate systems and long-memory environments.
Path integral methods, such as the quasi-adiabatic propagator path integral (QUAPI), are widely used in general-purpose and highly accurate numerical benchmark simulations of open quantum systems, particularly in regimes inaccessible to perturbative methods. Nevertheless, the applicability of the QUAPI method to realistic systems of interest is restricted by the exponentially growing computer memory requirements with respect to the size of the quantum system and the time range of non-Markovian correlation effects. This exponential "wall" becomes even more severe for multiple non-commuting fluctuating environments. In the present work, we address the numerical efficiency and accuracy of approximations that have been introduced for the QUAPI method with a single general environment, for the case of two independent non-commuting environments where one of them is considered as a pure dephasing environment. In particular, we consider a sharply defined cutoff of the memory time, path filtering, and mask assisted coarse graining of influence functional coefficients as approximations. We demonstrate that commonly applied numerical techniques, such as path filtering, cannot be straightforwardly transferred to the two-bath case even in the weak-coupling and quasi-Markovian limits. On the other hand, the sharply defined memory cutoff can be accurately handled with the mask assisted coarse graining approach. Our findings demonstrate that if system coupling operators to different baths do not commute, the additive nature of the statistically independent environments may be misleading. In particular, the quasi-Markovian nature of a pure dephasing bath is lost once there simultaneously exists another non-commuting source of fluctuations.
The reduced density matrix of a system coupled to a harmonic dissipative bath can be obtained accurately using an iterative path integral methodology that involves a propagator tensor, whose rank is roughly equal to the number of time steps that span the bath-induced memory. The present work shows that even in situations where the bath is characterized by high-frequency modes (which necessitate a small time step) and slow oscillators (which give rise to very long memory), efficient propagation that takes into account the memory on all time scales is feasible by renormalizing the propagator matrix to include successively larger-length influence functional correlations. At its crudest level, the renormalized propagator is an ordinary matrix, thus the computational demands of the method are very modest, similar to those for propagating the bare system. Yet, test applications on dissipative two-level systems show that the method produces accurate results in demanding situations. By including memory on successively increasing time scales, the method is capable of capturing nonexponential kinetics induced by sluggish solvents.
Recent progress in numerical methods for evaluating the real-time path integral in dissipative harmonic environments is reviewed. Quasi-adiabatic propagators constructed numerically allow convergence of the path integral with large time increments. Integration of the harmonic bath leads to path integral expressions that incorporate the exact dynamics of the quantum particle along the adiabatic path, with an influence functional that describes nonadiabatic corrections. The resulting quasi-adiabatic propagator path integral is evaluated by efficient system-specific quadratures in most regimes of parameter space, although some cases are handled by grid Monte Carlo sampling. Exploiting the finite span of nonlocal influence functional interactions characteristic of broad condensed phase spectra leads to an iterative scheme for calculating the path integral over arbitrary time lengths. No uncontrolled approximations are introduced, and the resulting methodology converges to the exact quantum result with modest amounts of computational power. Applications to tunneling dynamics in the condensed phase are described.
The accurate simulation of dissipative quantum dynamics subject to a non-Markovian environment poses persistent numerical challenges, in particular, for structured environments, where sharp mode resonances induce long-time system bath correlations. We present a scalable distributed memory implementation of the mask-assisted coarse graining of influence coefficients (MACGIC)-quasi-adiabatic propagator path integral (-QUAPI) method that exploits the memory resources of multiple compute nodes and mitigates the memory bottleneck of the method via a new premerging algorithm and a hash-based look-up (hMACGIC-QUAPI) while preserving numerical accuracy. The source code of the hMACGIC-QUAPI implementation is available in a publicly accessible Git repository under GPL license. The developed distributed memory implementation spreads the paths over the computing nodes by means of the MPI protocol, and efficient high level path management is achieved via the hash map-based implementation with constant access time. The efficiency of the implementation is demonstrated in large-scale dissipative quantum dynamics simulations that account for the coupling to a structured non-Markovian environment containing a sharp resonance, a setup for which convergence properties are investigated in depth. Broad applicability and the nonperturbative nature of the simulation method is illustrated via the tuning of the mode resonance frequency of the structured environment with respect to the characteristic system frequency. The simulations reveal a splitting of resonances due to a strong system–environment interaction and the emergence of sidebands due to multiexcitations of the bosonic mode that are not accounted for in perturbative approaches. The simulations demonstrate the versatility of the new hMACGIC-QUAPI method in the presence of strong non-Markovian system bath correlations.
The dynamics of a one-dimensional quantum system coupled to a harmonic bath can be expressed through Feynman’s path integral expression for the reduced density matrix. In this expression the influence of the environment is seen in correlations between positions of the system that are nonlocal in time. Makri and Makarov [J. Chem. Phys. 102, 4600 (1995)] showed that for many practical problems correlations over only a few time steps, Δkmax, need to be taken into account, which led to an efficient iterative scheme. However, this algorithm scales as the size of the system to the power of 2(Δkmax+1), which restricts the size of the system that can be studied with this method. In this work we present an efficient algorithm which scales linearly with Δkmax. In our method the reduced density matrix is written as a convolution of its past values with an integral equation kernel. The calculation of that kernel is based on a perturbative expansion of the discretized quasiadiabatic path integral expression for the reduced density matrix. The expansion ignores certain types of correlations.