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Energy transfer properties and absorption spectra of the FMO complex: from exact PIMC calculations to TCL master equations PDF

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Preview Energy transfer properties and absorption spectra of the FMO complex: from exact PIMC calculations to TCL master equations

Energy transfer properties and absorption spectra of the FMO complex: from exact PIMC calculations to 3 1 0 2 TCL master equations n a J 9 Piet Schijven,∗ Lothar Mühlbacher,∗ and Oliver Mülken∗ ] h p - PhysikalischesInstitut,UniversitätFreiburg,Hermann-Herder-Strasse3,79104Freiburg, m e Germany h c . s c E-mail: [email protected]; [email protected]; i s y [email protected] h p [ 2 v 9 3 8 0 . 1 0 3 1 : v i X r a ∗Towhomcorrespondenceshouldbeaddressed 1 Abstract Weinvestigate theexcitonic energy transfer(EET)intheFenna-Matthews-Olsen complex andobtainthelinearabsorptionspectrum(at300K)byaphenomenologicaltime-convolutionless (TCL)masterequation whichisvalidated byutilizing PathIntegralMonteCarlo(PIMC)sim- ulations. ByapplyingMarcus’theoryforchoosingtheproperLindbladoperatorsforthelong- time incoherent hopping process and using local non-Markovian dephasing rates, our model shows very good agreement with the PIMC results for EET. It also correctly reproduces the linearabsorption spectrum thatisfoundinexperiment, withoutusinganyfittingparameters. Introduction Since the seminal experiments on the Fenna-Matthews-Olsen (FMO) complex performed by the Fleminggroupin20071 andsubsequentlyconfirmed bytheEngelgroupin2010,2 manytheoreti- calmodelshavebeenproposedinordertoproperlydescribetheobservedlong-lastingoscillations in the 2D spectroscopic data. While many methods are based on quantum master equations of some sort or the other, like Lindblad or Redfield equations,3–8 only recently a more detailed de- scriptionofdissipativeeffectshasbeenattemptedintheformofPathIntegralMonteCarlo(PIMC) calculations based on results from atomisticmodelingcombiningmolecular-dynamics (MD) sim- ulationswithelectronicstructurecalculations.9 Incontrasttoaphenomenologicalmodelingofthe “environment”(proteinscaffold,watermolecules,etc.), thelatterapproach utilizesBChl-resolved spectral densities which can be directly incorporated in the PIMC calculations to obtain an exact account ofthefull excitondynamics. Most quantum master equation approaches use special analytical forms of spectral densities, such as Ohmic or Lorentzian forms. Although this allows to obtain solutions for the equations, it remainstobeaphenomenologicalansatz. Sofartheresultsthathavebeenobtainedbyhierarchical time-nonlocalmasterequationswithaLorentzianspectraldensityshowreasonableagreementwith theexperimentalresultsofboththeabsorptionand 2D spectraat 77K.10,11 In contrast, numerically exact methods like PIMC simulations12 or the QUAPI method13–15 2 have proven to be capable to produce the exact quantum dynamics of excitonic energy transfer overtheexperimentallyrelevant timescales. However,this comes at the priceof ratherlarge com- putational costs. Here, we combine the respective strengths of numerically exact and approxima- tive methods while overcoming their respective weaknesses: we use PIMC results for the exact quantum dynamics of the excitonic population dynamics over intermediate timescales (i.e. 600fs) whichstillallowforafastproductionoftherespectiveresults,yetaresufficienttoallowforacom- parisontoatime-convolutionless(TCL)masterequationbasedonaLindbladapproach;wefurther corroborateourresultsbycomparisonwithPIMCdataforupto1.5ps. Foramodeldimersystems theauthorshavealreadysuccessfullydemonstratedsuchaconcept.16 Here,ouransatzcapturesthe long-timebehaviorbyrelatingtoMarcus’theoryofelectrontransport17,18 becauseweassumethat thelong-timebehaviorisgovernedbyaclassicalhoppingprocessbetweentheindividualsites,18,19 seebelow. Fortheshort-timedephasingbehaviorweintroducenon-Markoviandephasingrates.20 Since, in principle, we then obtain results for arbitrarily long times, we have an efficient yet very accurate way to calculate arbitrary transfer properties. Furthermore, we use the master equation to calculate the absorption spectrum of the FMO complex (at 300 K), an observable which can straightforwardly be obtained experimentally.21 This opens the possibility to estimate the valid- ity of the underlying microscopic Hamiltonian as well as its respective parametrization based on recent results from mixed quantum-classical simulations22 by getting into direct contact with ex- perimentaldata. Energy transfer on the FMO complex Microscopic description The dynamics of single excitations on the FMO complex is often de- scribed by a tight-binding Hamiltonian with 7 localized sites, corresponding to the 7 bacteri- ochlorophylls(BChls)oftheFMOmonomer.23,24Theinfluenceoftheproteinscaffoldandsolvent on the excitonicdynamics is treated, in the spirit of the Caldeira-Leggett model,25 as a collection ofharmonicmodesthatare linearlycoupled toeach BChl. Previousstudiesshowedno significant 3 correlationsbetweenthebathinducedenergyfluctuationsatdifferentsites,26,27 soweassumethat each BChl is coupled to its own individual environment. The full Hamiltonian of the system can nowbewrittenas: H =H +H +H , (1) S B SB with H = (cid:229) e |nihn|+ (cid:229) J |mihn|, (2) S n mn n m6=n HB = n(cid:229) ,k (cid:18)2Pmn2nkk +21mnk w n2k Xn2k (cid:19), (3) HSB = (cid:229) |nihn| cnk Xnk +L (ncl) . (4) n (cid:16) (cid:17) Thestate|nicorrespondstothesingle-excitationstateofsiten,theparametere denotestheenergy n gap between ground and excited state of site n, and J describes the excitonic coupling between mn sites m and n. Furthermore, Xnk , Pnk , mnk and w nk denote the position, momentum, mass and frequency of the bath oscillators, respectively. In the interaction Hamiltonian H , the constants SB cnk (in units of eV/m) denote the coupling strength between site n and the bath modes. We have included the classical reorganization energies L (cl) as a counter-term in H to prevent further n SB renormalizationofthesiteenergies bytheenvironment.20,25,28 Thisquantityisdefined as: h¯ ¥ J (w ) L (cl) = dw n , (5) n p w 0 Z whereJ (w )(inunitsof1/s)isthespectraldensityofthebaththatiscoupledtositen. Intermsof n thesystemparameters, itis givenby: Jn(w )= ph¯ (cid:229) k 2mcnk2nkw nk d (w −w nk ). (6) The precise numerical values of the different parameters entering in the expressions above were obtained from combined quantum-classical simulations for the full FMO complex including the 4 solvent.22,29 Effective master equation approach We use now use the microscopic description of the FMO complex to set up a phenomenological second order time-local quantum master equation. In doing so, we are able to reproduce the dy- namics obtained from the PIMC simulationsas well as extendingit to, in principle, arbitrary long times. Additionally, our approach also allows to obtain results for the linear absorption spectrum whichare incloseaccordance toexperimentalfindings. The spectral density of the FMO complex22 leads to reorganization energies L (cl) of the order n of 0.02−0.09 eV, which is comparable to the differences in the site energies e , while the exci- n tonic couplings J are of the order of 1 meV. This implies that we can expect that the protein mn environment is relatively strongly coupled to the FMO complex and that it therefore leads to a strong damping for the population dynamics. This is also reflected by the results of the PIMC simulations.9 We now assume that in the long-time limit, after most of the coherences (i.e. off-diagonal el- ements of the reduced density matrix in the site-basis representation) in the system have decayed, EET can be described by a classical hopping process between the different sites (BChl’s), that is inducedby theproteinenvironment. Thetransfer rates k havetosatisfydetailed balance, ensur- mn ing acorrect equilibriumstate, and are assumed to followfrom Fermi’s golden rule. Furthermore, the rates should also depend on the reorganization energies L (cl) and L (cl) of the baths that are n m coupled to the sites n and m, reflecting the differences in the coupling strengths of the protein en- vironment to each BChl. Unlike Förster theory, which assumes incoherent hopping between the energy eigenstatesofH ,30 Marcus’stheoryofelectrontransportsatisfiesalltheseproperties,17,18 s leadingto transferrates k oftheform: mn pb b (e −e +L (cl))2 k = |J |2exp − n m mn , (7) mn mn sh¯2L (cl) " 4L (cl) # mn mn 5 withb =1/k T and L (cl) =L (cl)+L (cl). B mn m n Asidefromincoherenttransferbetweenthesites,theenvironmentalsoinducesastrongdephas- ing on each site. In the framework of the second order TCL master equation,20 these dephasing rates (in unitsof1/fs)aregivenby: t ¥ l (t)=2Re ds dw J (w )[coth(b h¯w /2)cos(w s)−isin(w s)]. (8) n n 0 0 Z Z Here, we use the spectral densities J (w ) which have been obtained by MD simulations in Ref.22 n and numericallycalculatethecorrelation function. TheTCL masterequationthatdescribes theexcitationdynamicscan nowbewrittenas:20 dr (t) i ≡L(t)r (t)=− [H ,r (t)]+D(t)r (t). (9) s dt h¯ Our numerical results (not displayed) show that the Lamb shift term that usually appears in this equation, only leads to a negligible difference in both the population dynamics and the linear absorptionspectrum (thepositionof thepeak is shifted by approximately-1 meV). The dissipator D(t)isassumedtotakethefollowingLindbladform, according totheconsiderationsabove:20 D(t)r (t)=(cid:229) g (t) L r L† −1 L† L ,r . (10) mn mn mn 2 mn mn mn (cid:18) (cid:19) n o TheLindbladoperatorsare defined by L =|mihn|andtherates by g (t)=l (t)and g (t)= mn mm m mn k for m 6= n. The operators L model the dephasing process, while the operators L model mn mm mn the incoherent transfer between sites m and n. This choice of Lindblad operators will lead - in the long-time limit - to incoherent hopping transfer between the sites, which is different from, e.g., Redfield theory, which requires incoherent transfer between the eigenstates |y i of H , leading to S LindbladoperatorsoftheformL∼|y ihy |.18,20 n m However, we note that the equilibrium state of our master equation (r ) is slightly differ- eq ent from the one that follows from Marcus theory r , which is given by detailed balance, eq,db 6 limt→¥ r nn(t)=(1/Z)exp(−be n) and limt→¥ r mn(t)=0 for m 6=n, where r mn(t)= hm|r (t)|ni. This can be shown by noting that D(t)r = 0 but [H ,r ] 6= 0. This implies that r is eq,db S eq,db eq,db not astationary stateofour masterequation. For thepresent calculation, thedevationsare only of theorderof1%,so westillexpect ourapproach to givegoodresults. Path Integral Monte Carlo simulations PIMCsimulationsallowtoextracttheexactquantumdynamicsinthepresenceofadissipativeen- vironment,bothforchargetransport12,31,32 aswellasenergytransfer.9 Inshort,thetimeevolution of the reduced density operator of a dissipative quantum systems is calculated by employing the pathintegralrepresentationforthepropagatoraccording totheFeynman-Vernontheory33 forfac- torizingoritsextensiontocorrelatedinitialpreparations.34 Thesepathintegralsarethenevaluated by a stochastic sampling process based on Markov walks through the configuration space of all conceivable quantum paths which self-consistently emphasize the physically most relevant ones. WhilethereisnolimitationwithrespecttothechoiceofsystemparametersforwhichPIMCsimu- lationare capableof producingnumerically exact results, thisapproach is subjectto the notorious ‘dynamical sign problem’,35 which reflects quantum-mechanical interferences between different systempathsand resultsinan increase ofthecomputationaleffortnecessary toobtainstatistically converged results which scales exponentially with the timescale over which the dynamics of the system is investigated. However, the presence of a dissipativeenvironment substantially weakens these interference effects and therefore the sign problem. Furthermore, it allows for various effi- cientoptimizationschemeswhichleadtoafurthersoothingofthiscomputationalbottleneck,thus significantlyenlargingtheaccessibletimescales.12,36,37 Forthepresentcase, weutilizethePIMCdatapresentedinRef.9 todemonstratethereliability ofthemasterequationresultsandextendsomeoftheformertolongertimescales. Tothatextend,a factorizinginitialpreparationhas beenemployed,where, resemblingthesituationpriorto thecre- ationofan exciton,thebathmodesinitiallyarein thermalequilibriumwithrespect tothemselves, while the exciton has been modeled to be either initially localized on one of the seven BChl sites 7 orinoneofthesevenexcitoniceigenstates. Populationdynamics In Fig. 1 we show the population dynamics that is obtained by solving the TCL master equation, Eq. (9), forinitialconditionscorrespondingtoalocalizationonthesites|ni,e.g. r (0)=|nihn|,in comparisontothecorrespondingnumericallyexactPIMCresults. Thedottedcurvesrepresentsthe latterand the solidlines represent theresults from ourmaster equationapproach. Fig. 2 showsan extensionoftheresultsupto1200and1500fsforinitialpreparationsinsites1and6,respectively. In general we observe good quantitative agreement of our approach with the PIMC results for all localized initial preparations and over all observed timescales. The largest deviations are observedforaninitialconditionlocalizedonsite4forwhichthebathhasthelowestreorganization energy (0.025 eV). Since our assumption of a classical hopping process at long-times is based on having a strong coupling to the environment, we would expect that our approach becomes worse with decreasing reorganization energy. Also, from Fig. 2 one observes a good agreement in the approach toequilibrium,althoughthedecay isslightlyslowerthanpredictedby thePIMCresults. Figure 3 corroborates our results. Here, the excitonic excitation is initially in one of the seven eigenstates |y i of H . Again we find very good agreement with the PIMC results, where once n S more the strongest deviations occur for the initial preparation exhibiting the largest population on site 4. We note that there is no fitting parameter involved. Introducing a parameter which interpolates between purely coherent and purely incoherent transfer, as in,38–40 could lead to a furtherimprovementoftheagreement. Nevertheless,alreadythisrathersimplephenomenological model captures most of the details which are present in the PIMC calculations. Additionally, it allowsforacomputationallycheap calculation ofthelinearabsorptionspectrum. 8 1 1 r (0)=|1æÆ 1| r (0)=|2æÆ 2| 0.8 0.8 0.6 0.6 0.4 0.4 0.2 0.2 0 0 r (0)=|3æÆ 3| r (0)=|4æÆ 4| 0.8 0.8 0.6 0.6 0.4 0.4 0.2 0.2 0 0 r (0)=|5æÆ 5| r (0)=|6æÆ 6| 0.8 0.8 0.6 0.6 0.4 0.4 0.2 0.2 0 0 r (0)=|7æÆ 7|0 100 200 300 400 500 600 0.8 t (fs) 0.6 Site 1 0.4 Site 2 Site 3 Site 4 0.2 Site 5 Site 6 Site 7 0 0 100 200 300 400 500 600 t (fs) Figure1: Comparisonofpopulationdynamicsofthe7differentsitesoftheFMOcomplexobtained from the numerically exact PIMC results (circles) with the results from the TCL master equation approach (solid lines) for different localized initial conditions on the sites |ni, n =1,...,7. Note that the statisticalerror of thePIMC calculationsis typicallysmallerthan thesymbolsize. There- forewedo notshowtheerrorbars. 9 1 1 Site 1 r (0)=|1æÆ 1| r (0)=|6æÆ 6| Site 2 0.8 0.8 Site 3 Site 4 Site 5 0.6 0.6 Site 6 Site 7 0.4 0.4 0.2 0.2 0 0 0 200 400 600 800 1000 0 200 400 600 800 1000 1200 Figure2: SameasFig.1forlocalizedinitialpreparationsinsites1and6,butnowextendedbeyond 1ps . Table 1: The numerical values for the x-, y-, and z- component as well as the absolute value squared of the transition dipole moments~m =(m ,m ,m ) in units of Debye [D]. The z m m,x m,y m,z axisischosenalongtheC -symmetryaxisoftheFMOcomplex,andtheyaxisischosentobe 3 parallelto the N −N axisofBChl 1. B D m 1 2 3 4 5 6 7 m 0.0 -6.10 -5.27 0.0 -6.39 5.16 0.0 m,x m 1.86 1.08 -3.04 2.49 0.0 2.98 -1.14 m,y m 6.07 1.66 -2.10 5.85 -0.45 2.29 5.85 m,z |~m |2 40.32 41.09 41.47 40.45 41.09 40.70 35.52 m 10

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