Heating Rates in Periodically Driven Strongly Interacting Quantum Many-Body Systems
Krishnanand Mallayya, Marcos Rigol

TL;DR
This paper investigates heating rates in strongly interacting quantum lattice systems under periodic driving, revealing exponential regimes and connections to eigenstate thermalization, with implications for experimental probing.
Contribution
It introduces a numerical linked cluster expansion approach to calculate heating rates and links these rates to the eigenstate thermalization hypothesis in both integrable and nonintegrable systems.
Findings
Heating rates follow an exponential regime.
Heating rates agree with Fermi's golden rule.
Heating rates can be experimentally probed via drive frequency.
Abstract
We study heating rates in strongly interacting quantum lattice systems in the thermodynamic limit. Using a numerical linked cluster expansion, we calculate the energy as a function of the driving time and find a robust exponential regime. The heating rates are shown to be in excellent agreement with Fermi's golden rule. We discuss the relationship between heating rates and, within the eigenstate thermalization hypothesis, the smooth function that characterizes the off-diagonal matrix elements of the drive operator in the eigenbasis of the static Hamiltonian. We show that such a function, in nonintegrable and (remarkably) integrable Hamiltonians, can be probed experimentally by studying heating rates as functions of the drive frequency.
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Taxonomy
TopicsAdvanced Thermodynamics and Statistical Mechanics · Quantum many-body systems · Cold Atom Physics and Bose-Einstein Condensates
Heating Rates in Periodically Driven Strongly Interacting
Quantum Many-Body Systems
Krishnanand Mallayya
Department of Physics, The Pennsylvania State University, University Park, Pennsylvania 16802, USA
Marcos Rigol
Department of Physics, The Pennsylvania State University, University Park, Pennsylvania 16802, USA
Abstract
We study heating rates in strongly interacting quantum lattice systems in the thermodynamic limit. Using a numerical linked cluster expansion, we calculate the energy as a function of the driving time and find a robust exponential regime. The heating rates are shown to be in excellent agreement with Fermi’s golden rule. We discuss the relationship between heating rates and, within the eigenstate thermalization hypothesis, the smooth function that characterizes the off-diagonal matrix elements of the drive operator in the eigenbasis of the static Hamiltonian. We show that such a function, in nonintegrable and (remarkably) integrable Hamiltonians, can be probed experimentally by studying heating rates as functions of the drive frequency.
pacs:
02.30.Lt, 02.60.-x, 05.30.Jp, 05.70.Ln, 75.10.Jm
Periodic perturbations are a ubiquitous tool to excite and probe quantum systems and study their response functions. Recent developments in theory and experiments have expanded the scope of periodic driving to generate effective magnetic fields Dalibard et al. (2011); Kitagawa et al. (2011); Aidelsburger et al. (2013); Goldman et al. (2014), as well as to engineer topologically nontrivial band structures Oka and Aoki (2009); Lindner et al. (2011); Rechtsman et al. (2013); Cooper et al. (2019) and novel time-crystalline phases Else et al. (2016, 2017); Khemani et al. (2016); Yao et al. (2017a); *Yao_2017_Erratum; Zhang et al. (2017); Choi et al. (2017). However, under periodic driving, generic many-body interacting systems are expected to heat up and (for a bounded spectrum, typical of lattice fermions and spins) equilibrate at long times to states that are effectively at infinite temperature D’Alessio and Rigol (2014); Lazarides et al. (2014).
Driving at high frequencies, because of prethermalization Moeckel and Kehrein (2008); *moeckel_kehrein_2009; Eckstein et al. (2009); Kollar et al. (2011); Tavora and Mitra (2013); Tavora et al. (2014); Nessi et al. (2014); Essler et al. (2014); Bertini et al. (2015); *bertini2016prethermalization; Canovi et al. (2016); Fagotti and Collura ; Lange et al. (2018); Lenarčič et al. (2018); Reimann and Dabelow (2019); Mallayya et al. (2019), has been proposed to slow down heating Abanin et al. (2015); Else et al. (2017); Machado et al. ; Weidinger and Knap (2017); Kuhlenkamp and Knap . It results in initial fast prethermal dynamics towards time-periodic steady states (prethermal states) of effective local Hamiltonians Abanin et al. (2017a, b); Mori et al. (2016); Kuwahara et al. (2016), before thermalization dynamics eventually results in featureless “infinite-temperature” states D’Alessio and Rigol (2014); Lazarides et al. (2014); Prosen (1998); D’Alessio and Polkovnikov (2013). Prethermalization is a universal phenomenon that occurs during dynamics in isolated Mallayya et al. (2019) and open Lange et al. (2018); Lenarčič et al. (2018) systems whenever conservation laws are weakly broken. Numerical studies of prethermalization and thermalization, or, in general, of energy absorption in driven strongly interacting systems with many particles (or spins) are challenging. Progress has been achieved using massively parallel Krylov subspace methods Machado et al. , density matrix truncation Ye et al. , and t-DMRG Kollath et al. (2006), but there is a dearth of computational techniques to study generic models in arbitrary dimensions.
Here, we report on the implementation of a numerical linked cluster expansion (NLCE) for driven systems. NLCEs can be used to study arbitrary interaction strengths in arbitrary dimensions. They were originally introduced to study thermal equilibrium ensembles Rigol et al. (2006); *rigol2007numerical; *rigol2007numerical2, where they outperform full exact diagonalization calculations Iyer et al. (2015). NLCEs were recently implemented to study thermalization Rigol (2014); *rigol_16 and quantum dynamics under time-independent Hamiltonians in one Mallayya and Rigol (2018); Mallayya et al. (2019) and two White et al. ; Guardado-Sanchez et al. (2018) dimensions, and combined with dynamical quantum typicality Richter and Steinigeweg (2019). We use them to determine heating rates in strongly interacting one-dimensional (1D) lattices in the thermodynamic limit. The numerically obtained rates are shown to agree with Fermi’s golden rule predictions. We argue that, in addition to helping quantify the stability of prethermal states, heating rates can be used to probe the structure of the off-diagonal matrix elements of the drive operator in the eigenstates of the static Hamiltonian.
We consider a time-periodic Hamiltonian of the form , where is the static Hamiltonian and is a weak time-periodic perturbation of strength , period , and zero time average. The system is initialized (at ) in a state that is a thermal equilibrium state of an initial static Hamiltonian at an inverse temperature . At stroboscopic times , the density matrix can be written as , where is the (time ordered ) Floquet evolution operator (we set ). We assume that , , and are translationally invariant sums of local operators, and that they are mutually noncommuting (nontrivial dynamics occurs even if ).
The obvious conservation law broken by is energy conservation. For sufficiently small in the thermodynamic limit, we expect prethermalization to occur (independently of the value of ), wherein the system quickly relaxes to the equilibrium state of described by a (generalized) Gibbs ensemble [up to corrections]. The relaxation towards infinite temperature can be described by a slowly evolving (generalized) Gibbs ensemble of , characterized by the instantaneous expectation values of the conserved quantities of Mallayya et al. (2019). The dynamics of those quantities is described by autonomous equations, with drifts given by Fermi’s golden rule Mallayya et al. (2019).
We study the evolution of the energy defined by the static Hamiltonian, which is also the time-averaged Hamiltonian , . We consider general time-periodic perturbations, which can be Fourier decomposed as . After a short initial transient dynamics, in the linear response regime, the system absorbs energy independently from each Fourier mode . The average rate of energy absorption over a cycle is with, as expected from Fermi’s golden rule,
[TABLE]
where () are the eigenkets of with eigenenergies (), and is the projection of into the basis of . The latter defines the so-called diagonal ensemble (DE) at time Rigol et al. (2008), . is expected to characterize the equilibrated state under at time D’Alessio et al. (2016). We define the rate , where is the rate for Fourier mode , and is the energy at infinite temperature. Only when it is sufficiently small does one expect to be an exponential function, and to be meaningful.
We focus on 1D lattice system of hard-core bosons, with and given by
[TABLE]
where standard notation was used Cazalilla et al. (2011). We drive the system with a square wave , and set (our unit of energy and frequency). is integrable for (and mappable to the spin-1/2 Hamiltonian Cazalilla et al. (2011)), and nonintegrable for nonvanishing , , and . We study integrable and nonintegrable (with and ) cases, and select to have the same terms as [Eq. (2)] but with different nearest neighbor coupling parameters ( and ).
We implement a NLCE to calculate the energy per site at stroboscopic times in the thermodynamic limit . Within NLCEs, is expressed as a sum over the contributions of all connected clusters () that can be embedded on the lattice, , where is the number of “embeddings” (per site) of cluster , and is the weight of in cluster . is obtained recursively using the inclusion-exclusion principle: , where denotes the connected subclusters of and is the energy in cluster [ is the static Hamiltonian, and is the density matrix at time , both in cluster ]. The series starts with the smallest cluster (a site) for which . For each cluster, is calculated numerically using full exact diagonalization. We use maximally connected clusters (clusters with contiguous sites and all possible bonds) as they are optimal to study dynamics in chains in the presence of nearest and next-nearest neighbor interactions Rigol (2014); *rigol_16; Mallayya and Rigol (2018, 2017). The order of the NLCE is set by the number of sites of the largest cluster considered. For nonintegrable , we compute 17 orders of the NLCE (after exploiting all symmetries, the dimension of largest sector of the Hamiltonian is 32 896). When is integrable, due to particle number conservation, we are able to compute 18 orders of the NLCE (the dimension of the largest sector in this case is 21 942).
In the main panels of Fig. 1, we show NLCE results for vs for (a) the nonintegrable and (b) the integrable static Hamiltonians, for three strengths , 0.2, and 0.8 of the drive, for an initial thermal equilibrium state of at an inverse temperature . The exponential fits, which exclude the short-time transient dynamics and long times at which the NLCE does not converge, make apparent that the approach of to the infinite-temperature energy () is exponential. The rates obtained from such fits are plotted in the insets of Fig. 1 vs , for the two highest orders of the NLCE. They agree with each other, indicating that the fits are robust. The rates are and are in excellent agreement with Fermi’s golden rule [Eq. (1)], evaluated numerically using full exact diagonalization in chains with periodic boundary conditions sup .
It follows from eigenstate thermalization for nonintegrable Hamiltonians Deutsch (1991); Srednicki (1994); Rigol et al. (2008); D’Alessio et al. (2016) (generalized eigenstate thermalization for integrable Hamiltonians Cassidy et al. (2011); Vidmar and Rigol (2016)) that the predictions of for few-body operators agree with those of the thermal (generalized Gibbs) ensemble D’Alessio et al. (2016); Vidmar and Rigol (2016); Essler and Fagotti (2016); Caux (2016). We first focus on the case in which is nonintegrable with no local conservation law. In this case, the inverse temperature alone characterizes the thermal (grand canonical) ensemble at , , where is determined by the condition . Only when is that one expects to become independent of , and to approach as a single exponential.
To illustrate this, in the main panel of Fig. 2 we plot (normalized by its initial value ) for various initial inverse temperatures . The normalized energies for and exhibit a nearly identical exponential decay (within the times at which the NLCE has converged) implying that is independent of [hence, of ] when . For , one can still use exponentials to fit , but the rates obtained depend on . In the inset in Fig. 2, we report the rates obtained from such fits vs using two orders of the NLCE and for two values of . The rates from the two orders of the NLCE agree with each other and agree well with Fermi’s golden rule predictions. (A worse agreement is seen for than for due to the effect of higher order corrections.) The increase in the rate seen in the inset in Fig. 2 with decreasing is the one expected to occur as a function of driving time for initial states that are not in the regime .
Next, we focus on the dependence of the heating rates on . In nonintegrable systems, the eigenstate thermalization hypothesis Deutsch (1991); Srednicki (1994); Rigol et al. (2008); D’Alessio et al. (2016) allows one to compute . After resolving all symmetries of the static Hamiltonian, the eigenstate thermalization hypothesis ansatz for the matrix elements of the operator (used as drive) in each block diagonal sector of has the form D’Alessio et al. (2016); Srednicki (1999)
[TABLE]
where , , is the density of states of in sector at energy , and is a random variable with zero mean and unit variance. and are smooth functions of their arguments.
Using Eqs. (1) and (4), changing sums over eigenstates by integrals over energy, replacing by and assuming high temperature [], one obtains the following expression for the heating rate sup
[TABLE]
where () is the minimum (maximum) energy in sector , and is smaller than (otherwise there is no linear response heating for that mode).
In Fig. 3(a), we compare heating rates (for the nonintegrable case and normalized by ) obtained from dynamics evaluated with NLCE (see inset) and the ones predicted by Eq. (5) sup . NLCE results are not reported for small and large values of because the time interval in which the NLCE converges is not sufficiently long to produce robust exponential fits. The normalized rates for and are nearly identical to one another, and are well described by Eq. (5). For high , we find that the evaluation of Eq. (5) results in heating rates that can be well described by an exponential in . This is consistent with rigorous bounds Abanin et al. (2015, 2017b); Else et al. (2017).
When is integrable (the spin-1/2 limit), the prethermal states are described by a generalized Gibbs ensemble (GGE) Wouters et al. (2014); Pozsgay et al. (2014); Ilievski et al. (2015). When is a thermal state with (or in general after long driving times), with He and Rigol (2012). In this regime, Eq. (5) gives the heating rates for the integrable static Hamiltonian provided that there is a well defined . In Fig. 3(b), we show the equivalent of Fig. 3(a) but for the integrable case. Despite the differences between the dependence of the heating rates on in the nonintegrable and integrable cases, the heating rates in the latter are described by Eq. (5) and, for high , they are well described by an exponential in .
The previous results show that heating rates can be used to probe the function in nonintegrable and integrable systems. Still, Eq. (4) involves the density of states. For large system sizes, since is extensive but is not, and . Using the saddle point approximation to compute the integral in Eq. (5), and using that is maximal, the heating rate for Fourier mode in the thermodynamic limit can be written as
[TABLE]
where is the Hilbert space dimension of sector . Thus, the rate for Fourier mode , which Fig. 4 shows to be in excellent agreement with the heating rates obtained from the NLCE dynamics for a wide range of values of , gives the average over all sectors of the Hamiltonian in the thermodynamic limit sup .
In summary, we studied heating in strongly interacting driven lattice systems and showed that, at sufficiently high effective temperatures (), it can be well characterized by rates no matter whether the system is nonintegrable or integrable. We also showed that the rates agree with Fermi’s golden rule predictions for both nonintegrable or integrable cases. We then argued that heating rates can be used to probe the structure of off-diagonal matrix elements of the operator used to drive the system, in the eigenstates of the static Hamiltonian. Our results suggest that there is a well defined in integrable interacting systems. This has been confirmed in a recent full exact diagonalization study of the spin-1/2 chain LeBlond et al. , and needs to be further explored to place it on equal footing with what is known for quantum chaotic systems Khatami et al. (2013); Steinigeweg et al. (2013); Beugeling et al. (2015); D’Alessio et al. (2016); Luitz and Bar Lev (2016); Mondaini and Rigol (2017); Jansen et al. (2019).
Acknowledgements.
This work was supported by the National Science Foundation under Grant No. PHY-1707482. We are grateful to W. De Roeck and S. Gopalakrishnan for motivating discussions. The computations were carried out at the Institute for CyberScience at Penn State.
S1 S1. Numerical evaluation of Eq. (1) in the main text
Equation (1) in the main text is evaluated using full exact diagonalization of chains with sites and periodic boundary conditions. Defining a small energy window , Eq. (1) is modified to the following expression (which is amenable to numerical evaluation)
[TABLE]
where are eigenkets of with eigenenergies (), and . With this coarse graining procedure, for Fourier mode is calculated as
[TABLE]
where is also evaluated using full exact diagonalization, and for our model. is the relaxation rate of .
In Fig. S1, we show vs for three values of when , , and , for the nonintegrable [, Fig. S1(a)] and the integrable [, Fig. S1(b)] static Hamiltonians (the period of the drive is ). The initial thermal state has . It is apparent in Fig. S1 that is nearly constant, with a slight drift at long times (apparent for ), and that it is independent of the value of . We identify a range of and where is (nearly) constant [and where the dynamics of is exponential and robust against finite-size effects, see Sec. S3] and compute the average of in this range.
In the main text, all the rates reported in Figs. 1 and 2 for which Eq. (1) was used were obtained averaging over and (a total of 160 values) for the nonintegrable , and and (a total of 50 values) for the integrable . The standard deviation of the averages were reported as error bars.
S2 S2. Derivation of Eq. (5) in the main text
Equation (1), accounting for the block diagonalization of in symmetry sectors , has the form
[TABLE]
where , for , and . From the eigenstate thermalization hypothesis (ETH) it follows that the results from the diagonal ensemble and the Gibbs ensemble agree Deutsch (1991); Srednicki (1994); Rigol et al. (2008); D’Alessio et al. (2016), so one can replace by , where is the partition function, and the inverse temperature is set by the energy .
Using the Gibbs ensemble, the ETH ansatz for (see main text), and replacing sums by integrals, Eq. (S3) can be written as
[TABLE]
where () is the minimum (maximum) energy in sector , and we used that . A change of variable in the first integral, and in the second integral, allows one to rewrite the expression above as
[TABLE]
At high temperatures, when , one has to lowest order in
[TABLE]
Using Eqs. (S5) and (S6), the heating rate reduces to Eq. (5) in the main text.
S2.1 Numerical evaluation of Eq. (5) in the main text
Like Eq. (1), Eq. (5) in the main text is evaluated using full exact diagonalization of chains with sites and periodic boundary conditions. We define a small energy window , which we use to bin the spectrum of in each symmetry sector . Each bin , with energy , includes all eigenstates with eigenenergies . The density of states at energy is then , where is the number of energy eigenstates in bin . The function , with , after coarse graining is given by
[TABLE]
where and are such that bin containing and containing satisfy and . This coarse graining procedure modifies Eq. (5) in the main text to
[TABLE]
where the inner sum is over all the bins whose energy .
In contrast to Eq. (S1), Eq. (S8) does not involve calculating the time evolution of the system. As a result, we are able to evaluate Eq. (S8) in chains with () for the nonintegrable (integrable) static Hamiltonian. The dimension of the largest symmetry resolved sector is 13,797 (16,796) for the nonintegrable (integrable) .
In Fig. S2, we show heating rates for the mode, , evaluated at for two values of for the nonintegrable and the integrable static Hamiltonians. Our values of are such that the spectrum of is divided into bins [(a) and (b) ] and bins [(a) and (b) ]. The results obtained can be seen to be robust against the choice of . For the results reported in Fig. 3 of the main text, we use ( bins) to evaluate , , and in Fig. 3(a) for the nonintegrable static Hamiltonian, and ( bins) to evaluate , , and in Fig. 3(b) for the integrable static Hamiltonian.
In Fig. S2, we also show results of the numerical evaluation of Eq. (6) in the main text using full exact diagonalization of chains with periodic boundary conditions and sites. The coarse grained Eq. (6), using Eq. (S7), has the form
[TABLE]
It is apparent in Fig. S2, both for the nonintegrable and the integrable static Hamiltonians, that the results for calculated using Eq. (S9) do not agree with the ones for using Eq. (S8). This is because of strong finite-size effects in . We note that the disagreement increases as increases. The fact that finite-size effects in increase with increasing is also apparent in the increasing discrepancy with increasing between the results for the two chain sizes shown in Fig. S2. This is in contrast to the results for (similar to at large ) evaluated from Eq. (S8) and reported in Fig. 3 in the main text for two systems sizes. The strong finite-size effects in are not surprising as the assumptions made to derive Eq. (6) are not valid for the small system sizes studied in this work.
S3 S3. Convergence of NLCE and exact diagonalization
In Fig. S3(a), we plot the absolute value of the energy per site of the nonintegrable Hamiltonian for , period , and . The results shown for were obtained within the last four orders of the numerical linked cluster expansion (NLCE), and for the four largest chain sizes (with periodic boundary conditions) studied using exact diagonalization (ED). At short times (), both NLCE and ED give nearly identical results (all lines are indistinguishable in the scale of the figure). The small finite-size effects of the ED calculations for are the reason we evaluate Eq. (1) of the main text with ED in the range (see Fig. S1). All the curves in this range are well described by an exponential, so we fit an exponential to the results from the largest chain calculated with ED () in this range of [shown in Fig. S3(a) as a black line]. For , ED calculations deviate from the exponential, and with increasing the curves monotonically approach the exponential fit. On the other hand, NLCE results ( and ) remain exponential up to [apparent in the inset in Fig. S3(a)]. Increasing the order of the NLCE significantly improves the convergence towards the exponential at longer times. We remark here that, purely from the ED calculations, it is difficult to identify the exponential regime (in order to accurately predict the rates) as the results from ED smoothly drift away from an exponential and the discrepancies between and are small at most times. We use the NLCE results as reference in order to identify the time interval in which the ED results exhibit the “correct exponential”. That time interval is then used to compute robust Fermi’s golden rule predictions.
Next, we quantify the convergence errors of NLCE and the finite-size errors of ED calculations. At the times at which the highest order () NLCE results are very close to the exponential fits to the ED (and NLCE) data, the NLCE results serve best as reference to quantify the errors at lower orders of the NLCE and finite-size errors of ED. For evaluated with the NLCE order [] and with the -site periodic chain ED [], we define the convergence errors for and , respectively, as the relative differences from given by
[TABLE]
Fig. S3(b) reports and vs and , respectively, at and , for the same as in Fig. S3(a). The plots make apparent that the errors decrease with increasing and , that the errors at are greater than the corresponding ones at , and suggest that the NLCE convergence errors decrease faster with increasing than the ED finite-size errors with increasing , a known fact in equilibrium calculations Iyer et al. (2015).
At , the estimated of error for the ED calculation [] for in Fig. S3(b) is less than 0.2%. For all calculations with ED in this paper, is the largest time considered for the nonintegrable .
As argued in the main text, in the thermodynamic limit is essentially a single exponential in for . Hence, for , we can estimate errors via the deviation of the NLCE and ED results from an exponential fit to the shorter-time results. To avoid any bias towards the NLCE results, here we compute the exponential fit from the ED results of for . The normalized deviation from the exponential fit for the NLCE order [] and the -site periodic chain solved with ED [], are given by
[TABLE]
where fit() is the value of the exponential fit at . In Fig. S3(c), and are plotted vs and , respectively, for and . It is apparent that the NLCE results converge faster towards the exponential [at , is less than 0.5%]. The errors in the ED calculations are an order of magnitude higher, and vanish more slowly with increasing [as in Fig. S3(b)]. The excellent convergence of the NLCE results (for the nonintegrable ) was essential for the accuracy of the relaxation rates computed via fits to the NLCE data that were reported in the main text.
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