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. 2021 Apr 13;183(1):17. doi: 10.1007/s10955-021-02752-y

Perturbation Analysis of Quantum Reset Models

Géraldine Haack 1,, Alain Joye 2
PMCID: PMC8550307  PMID: 34720182

Abstract

This paper is devoted to the analysis of Lindblad operators of Quantum Reset Models, describing the effective dynamics of tri-partite quantum systems subject to stochastic resets. We consider a chain of three independent subsystems, coupled by a Hamiltonian term. The two subsystems at each end of the chain are driven, independently from each other, by a reset Lindbladian, while the center system is driven by a Hamiltonian. Under generic assumptions on the coupling term, we prove the existence of a unique steady state for the perturbed reset Lindbladian, analytic in the coupling constant. We further analyze the large times dynamics of the corresponding CPTP Markov semigroup that describes the approach to the steady state. We illustrate these results with concrete examples corresponding to realistic open quantum systems.

Keyword: Spectral analysis of Lindbladians; Markovian quantum dynamics; Quantum reset models

Introduction

A major challenge when investigating small quantum systems is to assess their dynamics when coupled to several environments that put the system in an out-of-equilibrium situation. To do so, one often resorts to effective master equations governing the reduced density operator for the small system. Under the Born-Markov approximation (that involves weak system-bath coupling and short bath time-correlations), the evolution equation for the reduced density operator becomes linear, and is cast into the form of a Lindblad-type master equation [12, 13] for the corresponding map to be CPTP (Completely Positive and Trace Preserving). A Hamiltonian approach using perturbation theory is probably the most standard way to derive such a (continuous in time) effective evolution equation for the reduced quantum system [5, 28]. For an account of mathematical results, we refer the reader to the review [10] and to the recent paper [22] which implements this procedure rigorously for a general class of systems. Alternatively, repeated-interaction schemes (discrete in time) have attracted lots of attention among both mathematicians [1, 79, 14, 18] and physicists [2, 3, 20, 25, 26, 29, 31], especially in the context of quantum thermodynamics. Exact solutions for the asymptotic steady states generated by both types of dynamics can in general be derived for quantum systems with low dimensional Hilbert space only.

Appealing master equations to investigate the dynamics of higher dimensional quantum systems are provided by a specific class of models, known as Quantum Reset Models (QRM hereafter). These models can be viewed as a natural extension of classical stochastic models, see [16] for a review and [11] for an example treating diffusion processes. Remarkably, QRM can be formulated in terms of Lindblad master equations so that they generate CPTP maps. This is achieved by making specific choices of dissipation channels (corresponding to a fully depolarized quantum channel), see [15, 23, 33] for examples in specific physical setups. These QRM, thanks to their structural simplicity, present the strong advantage to allow for analytical solutions for the reduced density operator of multipartite quantum systems and have been successfully exploited to assess the dynamics of specific quantum systems, namely small quantum thermal machines made of a few qubits, qutrits or higher-dimensional quantum systems [4, 6, 19, 30, 32, 33].

In this work, we raise the question to which extent general properties of the dynamics generated by QRM can be analyzed mathematically. Our aim is to go beyond specific models to determine generic properties of the dynamics of QRM, i.e. induced by the mathematical structure itself of the QRM. A first step in that direction is performed in the recent work [27] where a single system driven by a Lindbladian subject to a reset process is considered. The spectral properties of the total Lindbladian perturbed by the reset processes are established, under the assumption that the unperturbed Lindbladian possesses a unique stationary state. Extensions to certain degenerate unperturbed Lindbladians are also discussed and examplified. In the present paper, we consider QRM describing the dynamics of more complex structures that are therefore intrinsically degenerate and not amenable to the cases dealt with above. We reach a two-fold objective. On the one hand, we show that those degenerate QRM nevertheless allow for a complete mathematical treatment revealing a rich structure. On the other hand, we demonstrate the relevance of our perturbative analysis to assess the dynamics of realistic multipartite quantum systems characterized by Hilbert spaces of dimension as high as 8.

More precisely, our generic model is made of a tripartite structure, A-C-B, where A and B are the two quantum systems subject to reset processes, and C is a central system with its own free evolution. The three subsystems are weakly interacting through a Hamiltonian. We first recall that QRM are always characterised by Lindblad generators, with explicit dissipators. Then we analyse the spectral properties of the resulting Lindbladians and the dynamics of the tri-partite system they generate, under generic hypotheses on the coupling term. We conduct this analysis first in absence of interaction between the A-C-B parts of the Hilbert space they are defined on, which gives rise to an uncoupled Lindbladian displaying large degeneracies, i.e. a large subspace of invariant states. Then, we introduce a generic interaction between these different parts and perform a perturbative analysis in the coupling constant. We prove uniqueness of an invariant steady state under the coupled dynamics, analytic in the coupling constant, and provide a description of the converging power series of this non-equilibrium steady state that develops in the small system. Building up on our spectral analysis, we elucidate the long time properties of the dynamics of the tri-partite system and its approach to the steady state. Finally, we focus on the case where the uncoupled system has no Hamiltonian drive and we describe in particular the emergence of a natural classical Markov process in the description of the large time behaviour of the coupled system. The paper closes with the study of two examples illustrating the key features of this analysis: the systems A and B are two qubits while the central system C is of arbitrary dimension N and the uncoupled dynamics has no Hamiltonian drive. For a rather general choice of QRM coupled dynamics, we compute the leading order of the steady state for N arbitrary and, for N=2—when C is another qubit—we determine the steady state up to order three in the coupling constant as well as the associated classical Markov process.

Mathematical Framework

Simple Hilbert Space Setup

As a warmup, we consider a single quantum system of finite dimension characterized by its Hamiltonian H defined on its Hilbert space H which is coupled to M reservoirs. QRMs assume the state of the quantum system to be reset to a given state τl with probability γldt within each time interval dt. The QRM-type evolution equation is given by [4, 15, 19]:

ρ˙(t)=-i[H,ρ]+l=1Mγl(τltr(ρ)-ρ). 2.1

The operator ρ is the reduced density operator of the system defined on H, and γl characterizes the coupling rate to the reservoir l, l=1,,M.

For the sake of comparison with our main concern—tri-partite systems—and to set the notation, we discuss the dynamics of QRM defined in this simple setup, essentially along the lines of [27]. We provide a full description of its generic features, under the following assumptions.

Gen:

Let H be a Hilbert space, with dimH=N<. The dissipative part of the generator is characterised by

  • {τl}1lM a collection of density matrices on H, i.e. τlB(H), with τl0 and tr(τl)=1, for all l1,,M,

  • γl>0, l1,,M, the collection of associated non-zero rates for the coupling to the M baths.

The Hamiltonian part of the generator, H=HB(H), is generic in the spectral sense

  • σ(H)={e1,e2,,eN}, consists of simple eigenvalues with associated normalised eigenvectors denoted by {φj}1jN, i.e. Hφj=ejφj, j{1,,N},

  • The differences (Bohr frequencies) {ej-ek}jk are all distinct.

The generator of QRM is thus the (super-)operator LB(B(H)) defined by

L(ρ)=-i[H,ρ]+l=1Mγl(τltr(ρ)-ρ), 2.2

where ρ here is arbitrary in B(H), such that the dynamics of the QRM reads

ρ˙(t)=L(ρ(t)),t(0,),ρ(0)=ρ0B(H). 2.3

In case ρDM(H), the set of density matrices DM(H)={ρB(H)|ρ0,tr(ρ)=1}, the trace factor in (2.2) disappears. Indeed, we will see below in a more general framework that the operator L enjoys further symmetries, being a Lindblad operator, see Proposition 3.2; in particular if ρ0DM(H), ρ(t)DM(H), for all t[0,).

However, we perform the full spectral analysis of L as an operator on B(H) and, accordingly, solve the equation (2.3) without resorting to these symmetries.

We first combine the density matrices τl with corresponding rates γl into a single density matrix T with corresponding rate Γ. Setting

Γ=l=1Mγl>0,T=1Γl=1MγlτlDM(H), 2.4

we get that (2.2) writes

L(ρ)=-i[H,ρ]+Γ(Ttr(ρ)-ρ). 2.5

In the sequel, we denote the matrix elements of any AB(H) in the basis {φj}1jN by Ajk=φj|Aφk, and the operator |φψ|B(H), for φ,ψH, is defined by |φψ|:ηφψ|η.

Lemma 2.1

Under our assumptions Gen, the operator L:B(H)B(H) defined by (2.5) is diagonalisable with spectrum given by

σ(L)={0,-Γ}{-i(ej-ek)-Γ}jk}. 2.6

All eigenvalues are simple, except -Γ which has multiplicity N-1.

Moreover, the solution to (2.3) reads

ρ(t)=e-t(i[H,·]+Γ)(ρ0-tr(ρ0)Γ(i[H,·]+Γ)-1(T))+tr(ρ0)Γ(i[H,·]+Γ)-1(T). 2.7

Expressed in the eigenbasis of H, this means that, with λjk=i(ej-ek)+Γ,

ρjk(t)=e-tλjkρ0jk+tr(ρ0)ΓTjkλjk(1-e-tλjk),forall1j,kN. 2.8

Remark 2.2

  • i)
    In the limit t the steady state is independent of the initial condition and reads
    ρSSlimtρ(t)=Γ(i[H,·]+Γ)-1(T) 2.9
  • ii)

    In particular, for ρ0DM(H), all populations decay to Tjj at the same exponential rate without oscillations ρjj(t)=e-tΓρ0jj+Tjj(1-e-tΓ).

  • iii)

    The result is known, see e.g. [27]; we provide a proof for the sake of comparison with those of the sections to come.

Proof

We first deal with the dynamical aspects and note that L(·)=-(i[H,·]+Γ·)+ΓTtr(·), with trT=1 implies trL(ρ)=0 for any ρB(H), so that the trace is conserved by (2.3). Hence, considering the jk matrix element of the differential equation (2.3) we get

ρ˙jk=-λjkρjk+ΓTjktr(ρ0)whereλjk0, 2.10

which yields (2.8). The basis independent formulation (2.7) follows by the decomposition ρ=1j,kNρjk|φjφk| and the observation

i[H,|φjφk|]+Γ|φjφk|=λjk|φjφk|, 2.11

which yields (i[H,·]+Γ)-1(T)jk=Tjk/λjk.

On the spectral side, the observation above immediately yields L(|φjφk|)=-λjk|φjφk| for jk, showing {-λjk}jk are simple eigenvalues by our genericity assumption. To compute the other nonzero eigenvalues of L, we note that if ρ is an eigenvector of L associated with an eigenvalue λ, then λtrρ=0. Hence λ0 implies trρ=0. Thus, considering the N-1 dimensional subspace of diagonal traceless matrices in the eigenbasis of H, {ρ=1jNrj|φjφj||1jNrj=0}, and making use of the identity L(|φjφj|)=Γ(T-|φjφj|), for any j, we see that it coincides with Ker(L+ΓI). Finally, the one-dimensional kernel of L is spanned by Γ(i[H,·]+Γ)-1(T): the inverse is well defined thanks to (2.11), it has matrix elements ΓTjk/λjk, and trace one. Thus

L(Γ(i[H,·]+Γ)-1(T))=-Γ(i[H,·]+Γ·)((i[H,·]+Γ)-1(T))+ΓT=0. 2.12

Tri-partite Hilbert Spaces

We define here the tri-partite systems whose dynamical properties are studied in this paper.

Consider H=HAHCHB, where H# are Hilbert spaces, with dimensions noted n#<, where #{A,B,C}. Let τADM(HA), τBDM(HB) be two density matrices on their respective Hilbert space and γA,γB>0 two positive rates. Consider three Hamiltonians HA,HB,HC on their respective Hilbert space that further satisfy

[HA,τA]=0,and[HB,τB]=0, 2.13

while HC is arbitrary at this point. In applications, the reset state τ# will typically be defined as a Gibbs state at some inverse temperature β# associated to H#; i.e. τ#=e-β#H#/Z# which satisfies (2.13), where Z# is the corresponding partition function. In Sect.3, we perform the analysis of the uncoupled case (system A-C-B is non-interacting), and in Sect.4, we make use of analytic perturbation theory to treat the case where a weak interaction is added to the system A-C-B.

The Non-interacting Tripartite QRM

We define the uncoupled QRM by the generator

L(ρ)=-i[HAICIB+IAHCIB+IAICHB,ρ]+γA(τAtrA(ρ)-ρ)+γB(trB(ρ)τB-ρ), 3.1

where I# denotes the identity operator on H# and tr# denotes the operator on the tensor product of Hilbert spaces with indices different from #, obtained by taking the partial trace over H#. For later purposes, tr## denotes the operator on the Hilbert space with index different from # and # obtained by taking the partial trace over H#H#. For example,

trA:B(HAHCHB)B(HCHB),trAB:B(HAHCHB)B(HC) 3.2

will be viewed as linear maps. We shall abuse notations and write H# for the Hamiltonian both on H# and H, the context making it clear what we mean. Also, we shall denote the non-Hamiltonian part of the generator by

D(ρ)=γA(τAtrA(ρ)-ρ)+γB(trB(ρ)τB-ρ), 3.3

so that L(ρ)=-i[HA+HC+HB,ρ]+D(ρ).

Remark 3.1

If nB=1, HBC and the last tensor product is trivial. Hence the QRM reduces to L(ρ)=-i[HA+HC,ρ]+γA(τAtrA(ρ)-ρ) on HAHC, while keeping γB>0.

Let us start by a structural result saying that the QRM at time t, etL(ρ0), with ρ0 a state, is a CPTP map, by recalling that its generator can be cast under the form of a Lindblad operator, see e.g. [4, 15, 19]. More precisely, the non-Hamiltonian part of their generator (3.1) takes the form of a dissipator, i.e.

jAjρAj-12{AjAj,ρ}=j12{[Ajρ,Aj]+[Aj,ρAj]},forAjB(H). 3.4

Given (3.1), it is enough to consider τAtrA(ρ)-ρ defined on H=HAHC.

Proposition 3.2

Let τA=ktk|φkφk| be the spectral decomposition of τA, where {φk}k is a complete orthonormal basis of HA. Then

τAtrA(ρ)-ρ=j,k(AjkρAjk-12{AjkAjk,ρ}),whereAjk=tj|φjφk|IC. 3.5

Remark 3.3

  • i)

    This result applies to the non-Hamiltonian part of the generator of QRM defined on a simple Hilbert space as well, by considering HC=C, in which case trA reduces to the scalar valued trace.

  • ii)

    The operators Ajk can be replaced by tj|φjψk|IC, where {ψk}k is any orthonormal basis of HA without altering the result.

Spectrum of the Uncoupled QRM

We proceed by analysing the spectrum of the uncoupled QRM L (3.1) in the tri-partite case, making use of the fact that, by construction, the Hamiltonian part of the decoupled QRM commutes with the dissipator as we quickly check:

[HA,·](τAtrA(·))(ρ)=[HA,τAtrA(ρ)]=[HA,τA]trA(ρ)=0, 3.6

since τA and HA commute, while

(τAtrA(·))[HA,·](ρ)=τA(trA(HAρ)-trA(ρHA))=0, 3.7

using trA(·)=jφjA|I·|φjAI with {φjA}1jnA an orthonormal basis of eigenvectors of HA. Now, replacing HA by HB (or HC for that matter) yields

[HB,·](τAtrA(·))(ρ)=τA[HB,trA(ρ)],and(τAtrA(·))[HB,·](ρ)=τA(trA(HBρ)-trA(ρHB))=τA[HB,trA(ρ)], 3.8

since HB commutes with φjA|I and |φjAI. Altogether, the dissipator and the Hamiltonian parts of L admit a basis of common eigenvectors that we now determine.

Let us start with the dissipator and its spectral properties.

Proposition 3.4

The dissipator, as an operator on B(H), admits the following spectral decomposition

σ(γA(τAtrA(·)-I)+γB(trB(·)τB-I))={0,-γA,-γB,-(γA+γB)}γA(τAtrA(·)-I)+γB(trB(·)τB-I)=0Q0-γAQA-γBQB-(γA+γB)QAB,

where the spectral projectors Q#, #{0,A,B,AB} are given by

Q0(ρ)=τAtrAB(ρ)τB,QAB(ρ)=ρ-trB(ρ)τB-τAtrA(ρ)+τAtrAB(ρ)τB,QA(ρ)=(trB(ρ)-τAtrAB(ρ))τB,QB(ρ)=τA(trA(ρ)-trAB(ρ)τB).

Moreover, the different spectral subspaces in B(H) are

graphic file with name 10955_2021_2752_Equ233_HTML.gif

Remark 3.5

  • i)

    In case γA=γB, there are only three distinct eigenvalues and the corresponding spectral projector is QA+QB.

  • ii)

    Being spectral projectors, the Q#’s, #{0,A,B,AB} satisfy Q0+QA+QB+QAB=I and Q#Q#=δ#,#Q#

  • iii)

    The dimensions referred to correspond to complex dimensions for B(H).

  • iv)

    The result essentially follows from the observation that τAtrA(·) and trB(·)τB are commuting projectors.

Proof

We start with point iv) of Remark 3.5. For any ρ in B(H),

(τAtrA(·)trB(·)τB)(ρ)=τAtrAB(ρ)τB=(trB(·)τBτAtrA(·))(ρ) 3.9

while τAtrA(·)τAtrA(·)=τAtrA(·), and similarly for trB(·)τB. Hence the dissipator is a linear combination of two commuting projectors to which we can apply the next Lemma.

Lemma 3.6

Let P,QB(H) such that P2=P,Q2=Q, and [P,Q]=0. Then, for any α,βC, the identity

αP+βQ=0(I-P)(I-Q)+αP(I-Q)+βQ(I-P)+(α+β)PQ, 3.10

provides the spectral decomposition of αP+βQ, so that σ(αP+βQ)={0,α,β,α+β}, with respective spectral projectors (I-P)(I-Q),P(I-Q),Q(I-P),PQ, and no eigennilpotent.

The proof of the Lemma is immediate, and in case some eigenvalues coincide, the corresponding spectral projector is simply the sum of the individual projectors.

The identifications P=I-τAtrA(·), Q=I-trB(·)τB, α=-γA, β=-γB yield the announced spectral decomposition of the dissipator, together with the explicit spectral projectors. A direct verification then gives the corresponding spectral subspaces.

The eigenvectors of the Hamiltonian part of L are readily computed. For #{A,B,C}, let {φj#}1jn# be an orthonormal basis of H# of eigenvectors of H#, with associated eigenvalues ej#, 1jn#. The eigenvalues need not to be distinct at that point. We denote by Pj,k#B(H#), j,k{1,,n#}, the operators Pj,k#=|φj#φk#| that yield a basis of eigenvectors of the Hamiltonian part of (3.1) of B(H)):

-i[HA+HC+HB,Pj,kAPj,kCPj,kB]=-i(ejA-ekA+ejC-ekC+ejB-ekB)Pj,kAPj,kCPj,kB. 3.11

It remains to take into account the role of the trace in the spectral subspaces of the dissipator to get the sought for common basis of eigenvectors of (3.3). To do so, we introduce the n#-1 dimensional basis of diagonal (w.r.t. to the eigenbasis of H#) traceless matrices

Δj#=|φj#φj#|-|φj+1#φj+1#|,j=1,2,,n#-1, 3.12

such that [H#,Δj#]=0. Together with τ#, the Δj#’s form a basis of diagonal matrices. Proposition 3.4 then provides the full spectral analysis of the uncoupled QRM .

Proposition 3.7

The vectors listed below form a basis of B(H) consisting in eigenvectors associated with the mentioned eigenvalue of the uncoupled QRM

L(·)=-i[HA+HC+HB,·]+D(·) defined on H=HAHCHB by (3.1):

τAPj,kCτB-i(ejC-ekC),1j,knCΔjAPj,kCτB-γA-i(ejC-ekC),1jnA-1,1j,knCPj,kAPj,kCτB-γA-i(ejA-ekA+ejC-ekC),1jknA,1j,knCτAPj,kCΔjB-γB-i(ejC-ekC),1jnB-1,1j,knCτAPj,kCPj,kB-γB-i(ejC-ekC+ejB-ekB),1jknB,1j,knCΔjAPj,kCΔjB-(γA+γB)-i(ejC-ekC),1jnA-1,1jnB-1,1j,knCΔjAPj,kCPj,kB-(γA+γB)-i(ejC-ekC+ejB-ekB),1jnA-1,1jknB,1j,knCPj,kAPj,kCΔjB-(γA+γB)-i(ejA-ekA+ejC-ekC),1jknA,1jnB-1,1j,knCPj,kAPj,kCPj,kB-(γA+γB)-i(ejA-ekA+ejC-ekC+ejB-ekB),1jknA,1jknB,1j,knC

Remark 3.8

  • 0)

    The Hamiltonians H#B(H#) are arbitrary at that point.

  • i)

    The uncoupled reset model Lindbladian L is thus diagonalisable, with eigenvalues located on the (generically) four vertical lines Rz=0, Rz=-γA, Rz=-γB, Rz=-(γA+γB) in the complex plane, symmetrically with respect to the real axis.

  • ii)

    In particular, the kernel of L is degenerate, since dimKerL(·)nC.

  • iii)

    It is straightforward to generalise this result to the case where the dissipator admits a reset part acting on HC as well, and to the case of a p-partite non interacting system, with pN arbitrary.

The spectral projectors of L can be constructed explicitly, making use of the next Lemma:

Lemma 3.9

Consider a Hilbert space H and τB(H) a density matrix. Let {φj}1jn be an orthonormal basis of eigenvectors of τ for H. Consider the basis of B(H) given by

Pjk=|φjφk|,1jkn,Δj=|φjφj|-|φj+1φj+1|,1jn-1,andτ. 3.13

Set σj=k=1j|φkφk|, 1jn. Then the operators on B(H) defined by

Qjk(·)=Pjktr(Pjk·),1jkn,Qj(·)=Δjtr(σj(·-τtr(·))),1jn-1,andQ0(·)=τtr(I·) 3.14

yield a complete set of rank one projectors onto the span of the corresponding basis vectors of (3.13) so that the composition of any two of them equals zero.

Remark 3.10

The spectral projectors of L corresponding to Proposition 3.7 are then given by the appropriate tensor products of projectors (3.14).

The solution to ρ˙=L(ρ), ρ(0)=ρ0 follows immediately by expanding ρ0 along those eigenvectors. In particular, one gets for this uncoupled QRM model

ρ(t)=τA(e-i[HC,·]ttrAB(ρ0))τB+O(e-tmin{γA,γB}),t0, 3.15

where e-i[HC,·]ttrAB(ρ0) satisfies the Hamiltonian evolution equation ρ˙C=-i[HC,ρC], ρC(0)=trAB(ρ0) on HC, as expected in this uncoupled context.

The Weakly-Interacting Tripartite QRM

We consider now the coupled QRM defined by the Lindblad generator on B(H), with H=HAHCHB,

Lg(ρ)=L(ρ)-ig[H,ρ]L0(ρ)+gL1(ρ) 4.1

where H=HB(H) is a Hamiltonian that effectively couples the different Hilbert spaces H#, while gR is a coupling constant. We focus on the determination of the kernel of Lg, as g0, which describes the asymptotic state of the system driven by Lg, under generic hypotheses. Then we turn to the consequences for the dynamics generated by Lg. By generic hypotheses, we mean that all assumptions we make along the way ensure the coupling is effective enough to lift all degeneracies, so that all accidental degeneracies are eliminated order by order in g.

Leading Order Analytic Perturbation Theory

When g=0, Proposition 3.7 shows that

KerL0span{τA|φjCφjC|τB}1jnC, 4.2

whatever the properties of the Hamiltonian HC. We shall consider below both cases HC=0 and HC0, which give rise to different results. In case the Hamiltonian HC is trivial,

HC=0KerL0=span{τAρCτB}ρCB(HC) 4.3

has dimension nC2, and the corresponding spectral projector coincides with Q0, the spectral projector on KerD, see Proposition 3.4. In order to avoid accidental degeneracies when HC0, we will assume HC satisfies the spectral hypothesis

Spec(HC):

The spectrum of HCB(HC) is simple and the Bohr frequencies {ejC-ekC}jk are distinct.

Under this assumption, we have

KerL0=span{τAρCτB,s.t.[ρC,HC]=0}, 4.4

which is of dimension nC. The corresponding spectral projector acts as follows

Q0(ρ)=τADiagC(trAB(ρ))τB, 4.5

where the projector DiagC:B(HC)B(HC) defined by

DiagC(·)=j=1nC|φjCφjC|·|φjCφjC| 4.6

extracts the diagonal part of ρC within the normalised eigenbasis of HC. Observe that OffdiagC:B(HC)B(HC), extracting the offdiagonal part of ρC within the same basis, yields the complementary projector

OffdiagC=I-DiagC. 4.7

We also note, for later reference, that Q0 on B(H) is trace preserving, so that Ran(I-Q0){ρ|trρ=0}.

Analytic perturbation theory, see e.g. Chapter II §2 [17], allows us to compute the splitting of the degenerate eigenvalue zero of L0 by the perturbation gL1. Recall here that Lg being a Lindblad operator (Proposition 3.2), the following structural constraints hold:

0σ(Lg)=σ(Lg)¯{zC|Rz0},gR. 4.8

Moreover, the eigenvalue 0 is semisimple, that is there is no eigennilpotent (Jordan block) corresponding to that eigenvalue in the spectral decomposition of Lg. The same is actually true for all eigenvalues sitting on the imaginary axis.

Let {λj(g)}1jm be the set of eigenvalues of Lg that stem from the eigenvalue 0 of L0, with m=nC2 if HC=0 or m=nC if HC0. They form the so-called λ-group for λ=0, and for gC\{0} with |g| small enough, {λj(g)}1jm are analytic functions of a (fractional) power of g that tend to zero as g0. These eigenvalues may be permanently degenerate. For the structural reasons recalled above, one of these eigenvalues, denoted by λ0(g), is identically equal to zero, λ0(g)0, gC\0, and in case λ0(g) is degenerate, it is semisimple.

We show that under generic hypotheses, λ0(g)0 is a simple eigenvalue, see Theorem 4.3, and we determine the corresponding eigenvector ρ0(g), normalized to be a state, i.e. ρ0(g)0 and trρ0(g)=1.

Let us denote by Q0(g) the analytic spectral projector of Lg corresponding to the set of eigenvalues in the 0-group . It writes

Q0(g)=-12iπΓ0(Lg-z)-1dz=Q0+gQ1+g2Q2+O(g3), 4.9

for |g| small where Γ0 is a circle of small radius centered at the origin. Also, since 0 is a semisimple eigenvalue of L0,

Q1=-Q0L1S0-S0L1Q0=Q0Q1(I-Q0)+(I-Q0)Q1Q0, 4.10

where S0 is the reduced resolvent of L0 at 0, satisfying S0Q0=Q0S0=0 and S0L0=L0S0=I-Q0. In other words, S0=L0-1(I-Q0), that we shall sometimes abusively write S0=L0-1, with the understanding that it acts on (I-Q0)B(H). The analytic reduced operator in the corresponding subspace which describes the splitting reads

Q0(g)LgQ0(g)=(Q0+gQ1+g2Q2+O(g3))×(L0+gL1)(Q0+gQ1+g2Q2+O(g3))=gQ0L1Q0+g2(Q1L0Q1+Q1L1Q0+Q0L1Q1)+O(g3), 4.11

where we used L0Q0=Q0L0=0.

Lemma 4.1

Under assumption Spec(HC) when HC0, we have

Q0L1Q0(ρ)=0ifHC0-iτA[H¯τ,trAB(ρ)]τBifHC=0 4.12

where

H¯τ:=trAB(τA1/2ICτB1/2HτA1/2ICτB1/2)=trAB(HτAICτB)=trAB(τAICτBH)B(HC). 4.13

Explicitly, with τ#=1jn#tj#|φj#φj#|,

H¯τ=1jnA1knBtjAtkB(φjA|ICφkB|)H(|φjAIC|φkB). 4.14

As a consequence, when HC0 the splitting is generically described by the order g2 correction, while in case HC=0, the non-zero first order correction imposes that the elements of the kernel of Q0(g) commute with H¯τ which, generically, decreases the degeneracy from nC2 to nC. In both cases, the eigenvalue zero of Q0L1Q0 is semisimple.

Proof

We first compute for any ρCB(HC), using (4.13),

trAB([H,τAρCτB])=[H¯τ,ρC]. 4.15

One gets the explicit expression for H¯τ by expressing the partial trace within the eigenbases of τ#. Therefore

Q0L1Q0(ρ)=-iτA(trAB([H,τAtrAB(ρ)τB]))τB=-iτA[H¯τ,trAB(ρ)]τB. 4.16

The fact that HC0 implies Q0L1Q0=0 then follows from

Q0L1Q0(ρ)=-iτADiagC(trAB([H,τADiagC(trAB(ρ))τB]))τB, 4.17

and the identity

DiagC(trAB([H,τADiagC(ρC)τB]))=DiagC[H¯τ,DiagC(ρC)]=0. 4.18

Let us investigate the next order correction in order to analyse the splitting from the eigenvalue zero. Following [17] we consider the analytic matrix

L~g=1gQ0(g)LgQ0(g)=Q0L1Q0+g(Q1L0Q1+Q1L1Q0+Q0L1Q1)+O(g2)L~0+gL~1+O(g2), 4.19

where we observe with (4.10) that

L~1=-Q0L1S0L1Q0-S0L1Q0L1Q0-Q0L1Q0L1S0. 4.20

Let Q~0 be the eigenprojector onto KerL~0. Then the spectrum of Q~0L~1Q~0 describes the splitting to order g2, see [17], Thm 5.11: for λ~j(1)σ(Q~0L~1Q~0) of multiplicity mj(1), there exist exactly mj(1) eigenvalue of Lg of the form

λj(g)=g2λ~j(1)+O(g3). 4.21

Notice that Q~0L~1Q~0 is viewed as an operator on Q0B(H) here.

We observe that Q~0=Q~0Q0=Q0Q~0, hence

Q~0L~1Q~0=-Q~0(Q0L1S0L1Q0)Q~0=-Q~0L1L0-1L1Q~0, 4.22

since L1Q~0=(I-Q0)L1Q~0.

In order to proceed, we shall also assume in the sequel that the operator H¯τ appearing in Lemma 4.1 has generic spectral properties.

Spec(H¯τ):

The spectrum of H¯τB(HC) is simple and the corresponding Bohr frequencies are distinct. We denote the normalised eigenvectors and eigenvalues of H¯τ by φjτ and ejτ, 1jnC.

Under Spec(H¯τ), we get from (4.5) and Lemma 4.1

Q~0(ρ)=τADiagCtrAB(ρ)τBifHC0τADiagτtrAB(ρ)τBifHC=0, 4.23

where Diagτ is the projector that extracts the diagonal part of the matrices expressed in the orthonormal eigenbasis {φjτ}. Therefore

Q~0L~1Q~0=τADiagtrAB([H,L0-1([H,τADiagtrAB(·)τB])])τB, 4.24

where Diag stands here for DiagC (resp. Diagτ) if HC0 (resp. HC=0). Equivalently, Q~0L~1Q~0 is fully characterised by the following linear map. Set

Φ(·):=trAB([H,L0-1([H,τADiag(·)τB])]):B(HC)B(HC){ρC|trρC=0}. 4.25

Note that Φ is well defined and takes the form Φ(ρ)=trAB([H,M(ρ)]), for M(ρ)B(H), hence trΦ(ρ)=tr([H,M(ρ)])=0, for any ρ. Then, the restriction of Φ to DiagB(HC), which has dimension nC, satisfies

ΦD:=DiagΦ|DiagB(HC)andQ~0L~1Q~0(·)=τAΦD(·)τBtrAB(·). 4.26

We shall abuse notations in the sequel and simply write

Q~0L~1Q~0(·)=τAΦD(·)τB, 4.27

identifying operators defined on Q~0B(H) and DiagB(HC). Hence

σ(Q~0L~1Q~0)=σ(ΦD). 4.28

Note that dimKerΦD1, since RanΦDDiagB(HC){ρC|trρC=0}, a subspace of dimension nC-1, in keeping with the fact that KerLg is never trivial. Hence, for the zero eigenvalue of Lg to be non-degenerate at second order perturbation in g, we assume the coupling satisfies the assumption.

Coup:

The linear map

ΦD(·)=DiagtrAB([H,L0-1([H,τADiag(·)τB])])definedonDiagB(HC), 4.29

where Diag stands here DiagC (resp. Diagτ) if HC0 (resp. HC=0), is such that dimKerΦD=1.

Remark 4.2

Assumption Coup is equivalent to the statement

ΦD-1 exists on the nc-1 dimension subspace DiagB(HC){ρC|trρC=0}=RanΦD.

Indeed, both statements entail dimKerΦD=1, and the corresponding spectral projector onto KerΦD, say Π0, is such that RanΦD=(I-Π0)RanΦD, and KerΦDRanΦD={0}.

As a consequence,

Theorem 4.3

Consider the coupled QRM Lg(ρ) defined on B(HAHCHB) by

Lg(ρ)=-i[HA+HC+HB+gH,ρ]+γA(τAtrA(ρ)-ρ)+γB(trB(ρ)τB-ρ) 4.30

and assume Spec(HC) if HC0 or Spec(H¯τ) if HC=0. Then for gC\{0}, |g| small enough, dimKerLg=1 if Coup holds.

Remark 4.4

Under assumption Spec(H¯τ), the non-zero eigenvalues of L~0 are all simple, of the form λjk=-i(ejτ-ekτ) with associated eigenvector τA|φjτφkτ|τB, jk, and corresponding eigenprojector

Q~λjk(ρ)=τA|φjτφkτ|τBtr(τA|φkτφjτ|τBρ). 4.31

The next order correction, given by the eigenvalue of the operator -Q~λjkL1L0-1L1Q~λjk, reads

λ~jk(1)=tr{(IA|φkτφjτ|IB)[H,L0-1([H,τA|φjτφkτ|τB])]}. 4.32

Dynamics

We push here the spectral analysis a bit further in order to get sufficient information to analyse the behaviour of the dynamics of the coupled QRM Lg(·), as g0. We first discuss the richer case HC=0 and then describe the modifications required for the case HC0.

Let Q0(g) be the spectral projector of Lg given by (4.9), and Q0(g)=I-Q0(g). We have accordingly

etLg=etLg0Q0(g)+etLgQ0(g), 4.33

where Lg0=Lg|RanQ0(g), and Lg=Lg|RanQ0(g). Since the spectrum of Lg is a positive distance away from the imaginary axis, uniformly in g small enough, functional calculus yields the existence of Γ>0, independent of g, such that

etLg=etLg0Q0(g)+O(e-tΓ), 4.34

where O is uniform in g, since Q0(g) is analytic in g. Now, by (4.19)

Lg0=gL~g=g(L~0+gL~1+O(g2)), 4.35

where, for HC=0 under assumption Spec(H¯τ),

L~0=0Q~0+jkλjkQ~λjk,whereλjk=-i(ejτ-ekτ), 4.36

with simple non zero eigenvalues, see Remark 4.4. In case HC0 under hypothesis Spec(HC), L~0=0 by Lemma 4.1, so that (4.36) holds with Q~0=Q0 and Q~λjk=0.

Since Lg0=O(g) (and even Lg0=O(g2) in case HC0), the long time behaviour of etLg is controlled by the first term in (4.34) when g is small. This requires addressing the behaviour of the non self-adjoint spectral projectors associated to eigenvalues of Lg that vanish as g goes to zero.

Proposition 4.5

Assuming HC=0, Spec(H¯τ) and Coup, there exists g0>0 such that for all |g|<g0, Lg admits analytic spectral projector Q~0(g) and Q~λjk(g) and analytic simple eigenvalues λjk(g) such that

Lg0=gQ~0(g)L~gQ~0(g)+jkλjk(g)Q~λjk(g). 4.37

Here Q~0(g)=Q~0+O(g), Q~λjk(g)=Q~λjk+O(g) and λjk(g)=-ig(ejτ-ekτ)+g2λ~jk(1)+O(g3), see (4.32).

Assuming HC0, Spec(HC) and Coup, the same statement holds with Q~0(g)=Q0+O(g) and Q~λjk(g)0, λjk(g)0 in (4.37).

Moreover, assuming Coup and Spec(H¯τ), (respectively Spec(HC)), if HC=0, (respectively HC0), we have dimKerQ~0(g)L~gQ~0(g)1 and the corresponding spectral projector Q~0S(g) is analytic for |g|<g0, and satisfies

Q~0S(g)Lg=LgQ~0S(g)=0. 4.38

Here

Q~0(g)L~gQ~0(g)=gQ~0L~1Q~0+O(g2)=gτAΦDτB+O(g2) 4.39

and Q~0S(g)=Q~0S+O(g) where Q~0S is the projector on KerQ~0L~1Q~0.

Remark 4.6

The spectral constraints on Lindblad operators imply,

Rσ(Q~0L~1Q~0)\{0}0,andRλ~jk(1)0. 4.40

We give conditions ensuring Rλ~jk(1)<0 in case the model has no leading order Hamiltonian drive, L0=D, that we analyse in more details in Sect. 6.

Proof

We consider HC=0 only, the other case being similar. Thanks to (4.35) and (4.36), perturbation theory applies to L~g and yields the analytic projectors Q~0(g) and Q~λjk(g) converging to Q~0 and Q~λjk respectively, and the analytic simple eigenvalues λjk(g), such that (4.37) holds. Expanding the first term using Q~0L~0=L~0Q~0=0, one gets thanks to (4.26)

Q~0(g)L~gQ~0(g)=gQ~0L~1Q~0+O(g2)=gτAΦDτB+O(g2). 4.41

Assumption Coup implies that Q~0L~1Q~0 has one dimensional kernel, with associated spectral projector we write Q~0S. Hence, perturbation theory again ensures the existence of an analytic one dimensional spectral projector Q~0S(g) of Q~0(g)L~gQ~0(g) corresponding to the simple zero eigenvalue of Q~0L~1Q~0 at g=0. Necessarily, Q~0S(g) coincides with the spectral projector onto the nontrivial kernel of Lg for all g small enough, which proves (4.38).

Let us turn to the dynamical implications.

Corollary 4.7

Under the hypotheses for HC=0 above, the following holds for all t0 and g real small enough:

etLg=etg2(Q~0L~1Q~0+O(g))Q~0(g)+jketλjk(g)Q~λjk(g)+O(e-tΓ). 4.42

Further assuming maxjk{Rλ~jk(1)}<0, there exists δ>0 such that for all t0,

etLg=Q~0S(g)+O(e-δg2t), 4.43

where the constant in the O is uniform in t0 and g small.

Setting η=minjk{|Rλ~jk(1)|}>0, we have

etLg=etg2Q~0L~1Q~0Q~0+O(e-tg2η)+O(g)+O(g3t)=τAetg2ΦDDiagτtrABτB+O(e-tg2η)+O(g)+O(g3t) 4.44

where the constants in all O are uniform in t0, g small.

Under the hypotheses for HC0 above, for all t0 and g real small enough,

etLg=etg2(Q0L~1Q0+O(g))Q~0(g)+O(e-tΓ), 4.45

and there exists δ>0 such that for all t0,

etLg=Q~0S(g)+O(e-δg2t), 4.46

where the constant in the O is uniform in t0 and g small. Moreover,

etLg=etg2Q0L~1Q0Q0+O(e-tΓ)+O(g)+O(g3t)=τAetg2ΦDDiagCtrABτB+O(e-tΓ)+O(g)+O(g3t) 4.47

where the constants in all O are uniform in t0, g small.

Remark 4.8

  • 0)

    The identical statements (4.43) and (4.46) show that 1/g2 is the time scale of the approach to the asymptotic state, as expected.

  • i)

    The full evolution can be approximated by the restriction of etg2τAΦDτB to RanQ~0, (provided η is larger than the absolute value of the real part of the eigenvalues of τAΦDτB in case HC=0).

  • ii)

    In case L0=D, we provide in Sect. 6 an interpretation of the approximate evolution etg2τAΦDτB as a classical continuous time Markov process.

  • iii)

    Set F=max{|Rλ|λσ(ΦD)}. When HC=0, the explicit term in (4.44) is the leading term if F<η, and for times which satisfy 0t<1ϵ+F|ln(g)|/g2, as g0, for any ϵ>0. When HC0, the same is true for the explicit term in (4.47), without constraint on F.

  • iv)

    This corollary is relevant for an analysis along the lines of [21].

Proof

Again we prove the statements for HC=0 only, the other case being similar. The first two statements follow from functional calcul, and Proposition 4.5, taking into account the analyticity of the spectral data involved. To get the last statement, we observe that since the CPTP map etLg has a norm which is uniformly bounded in t0 and g small enough, the norm of

etg2(Q~0L~1Q~0+O(g))Q~0(g)=etLg-jketλjk(g)Q~λjk(g)+O(e-tΓ) 4.48

is bounded above by a constant C>0 which uniform in t0 and g small enough. Thus, by Duhamel formula

eτ(A+B)=eτA+0τeτ(A+B)Be(τ-τ)Adτ 4.49

applied to A=Q~0L~1Q~0 subject to (4.40), B=O(g), τ=g2t we get

etg2(Q~0L~1Q~0+O(g))Q~0(g)=etg2Q~0L~1Q~0Q~0(g)+O(g3t). 4.50

Moreover, η=minjk{|Rλ~jk(1)|}>0 immediately implies upon expanding Q~0(g),

etLg=etg2Q~0L~1Q~0Q~0+O(e-tg2η)+O(g)+O(g3t), 4.51

where the constants in all O are uniform in t0 and g small. Finally,

Q~0L~1Q~0=τAΦDτB allows us to express the exponential in terms of that of ΦD.

Construction of the Asymptotic State

We now turn to the determination of the state ρ0(g)KerLg where Lg=L0+gL1B(B(H)) given by a power series in g

ρ0(g)=ρ0+gρ1+g2ρ2+, 5.1

where tr(ρ0)=1 and tr(ρj)=0, j>0. Expanding L0(ρ0(g))+gL1(ρ0(g))0, and equating like powers of g we get

L0(ρ0)=0L0(ρ1)+L1(ρ0)=0L0(ρ2)+L1(ρ1)=0L0(ρj)+L1(ρj-1)=0j1. 5.2

The way to solve this set of equations, in principle, is as follows. Note that the spectral decomposition of L0 yields

KerL0=RanQ0andRanL0=KerQ0. 5.3

The first equation is solved by picking a trace one element R0 in KerL0=Q0(B(H)), described in Proposition 3.7. The addition of any traceless vector r0KerL0 yields an equally good solution for ρ0:=R0+r0 at that order. The next equation amounts to solve L0(R1)=-L1(R0+r0) for R1, a traceless matrix. This requires L1(R0+r0)RanL0. Since RanL0=KerQ0, this is equivalent to Q0L1Q0r0=-Q0L1R0, which determines r0=Q0r0 up to the addition of an element of KerQ0L1Q0 (Q0L1Q0 viewed as an operator on Q0(B(H))). Let us assume for the discussion here that Q0L1Q00, i.e. HC=0. This yields R1=-L0-1(L1(R0+r0)). Again, the addition of any traceless vector r1=Q0r1KerL0 to that R1 yields an equally good solution ρ1:=R1+r1 to that equation. The next order requires L1(r1-L0-1(L1(R0+r0)))RanL0, which is equivalent to Q0L1Q0r1=Q0L1L0-1L1(R0+r0). This equation will then determine r0 completely, under generic hypotheses, as we shall see. Then we proceed by induction.

The case HC0 is slightly different, see Lemma 4.1, but is approached in the same spirit. We start by working out the first few steps and then give the general statements about this construction in Theorem 5.2 for HC=0 and Theorem 5.4 for HC0.

Again, the inverse of L0 on its range is the reduced resolvent S0=L0-1(I-Q0)=L0-1|(I-Q0)B(H). To express S0, it is enough to consider the spectral decomposition L0=k>0λkQk, where λk0 and Qk are the spectral projectors corresponding to Proposition 3.7, while λ0=0 corresponds to the projector Q0.

HC=0

We consider here that HC=0 and work under the spectral assumption Spec(H¯τ) on the self-adjoint operator defined by (4.13). We first work out the orders g0 and g1 terms, i.e. ρ0 and ρ1, and then state an abstract result on the full perturbation series in Theorem 5.2.

The first equation yields R0=τAρCτB where ρC is a state. We choose ρC=1nCIC, and r0=τArC(0)τB with any traceless rC(0) can be added to that choice so that

ρ0=τAρC(0)τB,withρC(0)=1nCIC+rC(0). 5.4

Then we compute Q0L1(R0+r0):

Q0(-i[H,R0+r0])=-iτA[H¯τ,ρC(0)]τB=-iτA[H¯τ,rC(0)]τB. 5.5

The condition to solve the equation for R1 requires rC(0)=Diagτ(rC(0)), where Diagτ(·) extracts the diagonal part of rC(0) in the normalised eigenbasis of H¯τ. Thanks to our assumption, we set

R1:=iL0-1([H,R0+r0])=ik>0λk-1Qk([H,R0+r0]), 5.6

which is traceless, since R1=(I-Q0)R1, and self-adjoint if rC(0) is. Next we look for R2, which requires Q0(L1(R1+r1))=0, where r1=Q0(r1)=τArC(1)τB:

Q0([H,{L0-1(i[H,τADiagτ(ρC(0))τB])+τArC(1)τB}])=0. 5.7

This is equivalent to the equation on B(HC)

itrAB([H,L0-1([H,τADiagτ(ρC(0))τB])])+[H¯τ,rC(1)]=0, 5.8

where we note that Diagτ(rC(1)) is arbitrary. Our hypotheses on H¯τ imply that

Ker[H¯τ,·]={ρC|ρC=DiagτρC}, 5.9
Ran[H¯τ,·]={ρC|ρC=OffdiagτρC}. 5.10

Now, assumption Coup on H ensures (5.8) determines DiagτrC(0) and OffdiagτrC(1): Separating the diagonal from the offdiagonal parts, we have for the former

ΦD(ρC(0))=0, 5.11

which determines ρC(0)=IC/nC+DiagτrC(0)=Diagτ(ρC(0)) fully since dimKerΦD=1, and thus R1 as well. The offdiagonal part yields

OffdiagτrC(1)=-i[H¯τ,·]-1(OffdiagτtrAB([H,L0-1([H,τAρC(0)τB])]))=-i[H¯τ,·]-1(OffdiagτΦ(ρC(0)))) 5.12

which fixes OffdiagτrC(1) and leaves DiagτrC(1) open for now.

At this point, the formula which defines R2 makes sense,

R2=iL0-1([H,R1+r1])=ik>0λk-1Qk([H,R1+r1]), 5.13

where R2 depends parametrically on DiagτrC(1). At order two, the contribution is R2+r2, where r2=Q0(r2)=τArC(2)τB is arbitrary. The term DiagτrC(1) is determined by the requirement that Q0(L1(R2+r2))=0 necessary to solve for R3, i.e.

trAB([H,{L0-1(i[H,R1+τArC(1)τB])+τArC(2)τB}])=trAB([H,L0-1(i[H,R1+τArC(1)τB])+[H¯τ,rC(2)]=0. 5.14

Splitting this equation into its diagonal and offdiagonal parts, we get, making use of (4.29),

DiagτtrAB([H,L0-1(i[H,R1+τAOffdiagτrC(1)τB])]+ΦD(DiagτrC(1))=0, 5.15
OffdiagτtrAB([H,L0-1(i[H,R1+τArC(1)τB])]+[H¯τ,rC(2)]=0. 5.16

Using assumption Coup under the form: ΦD is invertible on the subspace RanΦD=DiagτB(HC){ρC|trρC=0}, the first equation determines

DiagτrC(1)=-ΦD-1(DiagτtrAB([H,L0-1(i[H,R1+τAOffdiagτrC(1)τB])]), 5.17

so that rC(1) is determined and therefore the second equation yields

OffdiagτrC(2)=-i[H¯τ,·]-1(OffdiagτtrAB([H,L0-1([H,R1+τArC(1)τB])])). 5.18

Consequently, we can set

R3=iL0-1([H,R2+r2])=(I-Q0)R3. 5.19

At this point, ρ0=R0+r0, ρ1=R1+r1 are known, as well as R2, OffdiagτrC(2) and R3.

Remark 5.1

The fact that ρC(0)KerΦD implies trρC(0)0, so the assumption that ρC is a state in the initial step amounts to set a normalisation.

Let us formulate a general result that summarises the foregoing and guarantees the process can be pursued:

Theorem 5.2

Consider the QRM Lindbladian Lg (4.30) with HC=0 under the assumptions Spec(H¯τ) and Coup. Then there exists g0>0 such that ρ0(g), the unique invariant state of Lg, admits a convergent expansion

ρ0(g)=ρ0+gρ1+g2ρ2+, 5.20

for all gC with |g|<g0. We have,

ρ0=τAρC(0)τB,whereρC(0)KerΦD 5.21

see (4.29) and (5.4), and

ρj=Rj+τArC(j)τB 5.22

for all j1. Moreover, there exists a linear map R:B(H)B(H){ρC|trρC=0} such that ρj=R(ρj-1), where

Rj=iL0-1([H,ρj-1]), 5.23
OffdiagτrC(j)=-i[H¯τ,·]-1(OffdiagτtrAB([H,L0-1([H,ρj-1])])), 5.24
DiagτrC(j)=-ΦD-1(DiagτtrAB([H,L0-1(i[H,Rj+τAOffdiagτrC(j)τB])])). 5.25

Consequently, for |g|<g0,

ρ0(g)=(I-gR)-1(ρ0). 5.26

Remark 5.3

  • 0)

    Replacing Rj and OffdiagτrC(j) by their expression into (5.25) shows DiagτrC(j) is linear in ρj-1 as well an yields the map R.

  • i)
    Eq. (5.26) is equivalent to
    ρ0(g)=k=1NMk1-gμk+l=1mk-1glNkl(1-gμk)l+1(ρ0), 5.27
    where μk,Mk,Nk and mk are the eigenvalues, eigenprojectors, eigennilpotents and algebraic multiplicities appearing in the spectral decomposition of R=k=1NμkMk+Nk. Hence the radius of convergence is g0=1/max1kN(|μk|).
  • ii)

    In case σ(R)R±=, the steady state ρ0(g) is well defined for all gR±.

  • iii)

    The iteration terminates if and only if R has a zero eigenvalue and ρ0 belongs to the corresponding eigenspace; see Sect. 8 for examples.

  • iv)

    The restriction of the invariant state to HC is given by trAB(ρ0(g))=ρC(0)+j1gjrC(j).

  • v)

    We provide necessary and sufficient conditions in Proposition 6.1 for Coup to be satisfied in case L0=D and HC=0.

Proof

Recall that dimKerLg=1 is proven in Theorem 4.3.

We solve the higher orders equations for ρj=Rj+rj of (5.2) with

Rj=(I-Q0)Rj,rj=Q0rj=τArC(j)τB, 5.28

for all j by induction. Let j2 and assume Rk, rk are given traceless matrices satisfying (5.28) for 1kj-1 as well as

Rj=iL0-1([H,Rj-1+rj-1]),τAOffdiagτrC(j)τBandRj+1=iL0-1([H,Rj+rj]). 5.29

This is the situation we arrived at for j=2. Consider Q0(L1(Rj+1+rj+1))=0, a necessary condition to compute Rj+2, which yields

trAB([H,L0-1(i[H,Rj+τArC(j)τB]))+[H¯τ,rC(j)]=0. 5.30

Splitting the equation into its diagonal and offdiagonal parts gives

DiagτtrAB([H,L0-1(i[H,Rj+τAOffdiagτrC(j)τB])+ΦD(DiagτrC(j))=0, 5.31
OffdiagτtrAB([H,L0-1(i[H,Rj+τArC(j)τB])+[H¯τ,rC(j+1)]=0. 5.32

The first equation determines

DiagτrC(j)=-ΦD-1(DiagτtrAB([H,L0-1(i[H,Rj+τAOffdiagτrC(j)τB])])), 5.33

so that rC(j) is fully determined and therefore the second equation yields

OffdiagτrC(j+1)=-i[H¯τ,·]-1(OffdiagτtrAB([H,L0-1([H,Rj+τArC(j)τB])])). 5.34

Consequently we can define

Rj+2=iL0-1([H,Rj+1+rj+1]), 5.35

where DiagτrC(j+1) remains free, while rj is determined. This finishes the proof of the induction.

HC 0

We consider here HC0 and the necessary modifications to compute the series (5.1) due to the identities

Q0(·)=τADiagC(trAB(·))τBandQ0L1Q00. 5.36

The first equation in (5.2) yields ρ0=Q0ρ0=τAρC(0)τB, where ρC(0)DiagCB(HC) is free. The condition to solve the second equation is Q0L1(ρ0)=Q0L1Q0(ρ0)=0 which is trivially satisfied. Thus, writing ρ1=R1+r1 with R1=(I-Q0)ρ1 and r1=Q0ρ1, we can solve partially the equation setting

R1=-L0-1L1(ρ0). 5.37

The next equation L0(ρ2)=-L1(ρ1) requires Q0L1(R1)+Q0L1(r1)=0. Thanks to r1=Q0r1 and the identity (5.36), this equation reduces to

Q0L1L0-1L1Q0(ρ0)=0, 5.38

where we used the expression for R1 and ρ0=Q0ρ0. Thanks to assumption Coup for HC0, this determines ρ0=τADiagCρC(0)τB since (5.38) is equivalent to

ρC(0)KerΦD,wheredimKerΦD=1. 5.39

Thus R1 is now determined, while the traceless part r1=τADiagCrC(1)τB is not. With the familiar decomposition ρ2=R2+r2 with respect to the projector Q0, we set

R2=-L0-1L1(R1+r1) 5.40

and turn to the equation for ρ3=R3+r3: L0(ρ3)=L0(R3)=-L1(ρ2). It requires Q0L1(R2+r2)=Q0L1(R2)=0, where we used (5.36) and r2=Q0r2. With (5.40), this is equivalent to

Q0L1L0-1L1Q0(r1)=-Q0L1L0-1L1(R1)=-τADiagCtrAB(L1L0-1L1(R1))τB, 5.41

where trL1L0-1L1(R1)=0, since L1(·)=-i[H,·]. Thanks to Coup, we can thus determine r1=τADiagCrC(1)τB uniquely in terms of ΦD

rC(1)=ΦD-1(DiagCtrAB{[H,L0-1([H,R1]]}). 5.42

In turn R2 is fully determined while r2=τADiagCrC(2)τB remains to be computed, and

R3=-L0-1L1(R2+r2). 5.43

From there on we can iterate the process to get the equivalent of Theorem 5.2 in the case HC0. The proof being similar and simpler, we omit it.

Theorem 5.4

Consider the QRM Lindbladian Lg (4.30) with HC0 under the assumptions Spec(H¯τ) and Coup. Then there exists g0>0 such that ρ0(g), the unique invariant state of Lg, admits a convergent expansion

ρ0(g)=ρ0+gρ1+g2ρ2+, 5.44

for all gC with |g|<g0. We have,

ρ0=τAρC(0)τB,whereρC(0)KerΦD 5.45

see (4.29) and (5.39), and ρj=Rj+τArC(j)τB for all j1, with rC(j)=DiagC(rC(j)). Moreover, there exists a linear map R:B(H)B(H){ρC|trρC=0} such that ρj=R(ρj-1), where

Rj=iL0-1([H,ρj-1]), 5.46
rC(j)=ΦD-1(DiagCtrAB([H,L0-1([H,Rj])]))=iΦD-1(DiagCtrAB([H,L0-1([H,L0-1([H,ρj-1])])])). 5.47

Consequently, for |g|<g0,

ρ0(g)=(I-gR)-1(ρ0). 5.48

Remark 5.5

  • 0)

    Remarks (i), (ii), (iii) below Theorem 5.2 remain in force here.

  • i)
    The map R can be expressed as
    Rj=-L0-1L1(ρj-1),rC(j)=-ΦD-1(trAB{Q0L1L0-1L1(Rj)})=ΦD-1(trAB{Q0L1L0-1L1L0-1L1(ρj-1)}) 5.49
    so that
    ρj=(-L0-1L1(·)+τAΦD-1(trAB{Q0L1L0-1L1L0-1L1(·)})τB)(ρj-1). 5.50

No Leading order Hamiltonian Drive

We consider here the case where HA=HB=HC=0 on their respective spaces, so that L0=D with τA and τB arbitrary, while L1=-i[H,·] with H arbitrary as well. This allows us to keep things relatively simple, while retaining a certain level of generality, since the dimensions of the different Hilbert spaces are arbitrary as well.

Let us consider the hypothesis Coup in this simplified setup, assuming Spec(H¯τ) holds. Recall that {φjτ}1jnC denotes the normalized eigenbasis of H¯τ with respect to which the projectors Diagτ and Offdiagτ are defined, and set Pjτ=|φjτφjτ|. Given the definition (4.29) of ΦD, we need to compute for all j,k{1,,nC}

(ΦD)jk:=tr{(IAPjτIB)([H,L0-1([H,τAPkττB])}. 6.1

Thanks to Proposition 3.4, we can express L0-1=D-1 in a compact way. Let ρ~0B(H) such that trAB(ρ~0)=0, so that Q0(ρ~0)=0. Thus

D-1(ρ~0)=-1γA+γBρ~0+γAγBτAtrA(ρ~0)+γBγAtrB(ρ~0)τB 6.2

Therefore, introducing

H¯τA=trA(H(τAICIB))=trA((τAICIB)H)B(HCHB), 6.3
H¯τB=trB(H(IAICτB))=trB((IAICτB)H)B(HAHC) 6.4

and making use of trAB[H,τAPkττB]=0, a straightforward computation yields

[H,L0-1([H,τAPkττB])]=-1γA+γB[H,[H,τAPkττB]]-γA/γBγA+γB[H,τA[H¯τA,PkττB]]-γB/γAγA+γB[H,[H¯τB,τAPkτ]τB]. 6.5

Then we note using the cyclicity of the trace that

tr{(IAPjτIB)([H,[H,τAPkττB]])}=2(δjktr(H(τAPkττB)H)-tr((IAPjτIB)H(τAPkττB)H)) 6.6

where the operator in the first trace reads

((τA1/2PkττB1/2)H)(τA1/2PkττB1/2)H0, 6.7

while the second trace yields the jj element of its partial trAB. Hence,

tr{(IAPjτIB)([H,[H,τAPkττB]])}=2-trAB(H(τAPkττB)H)jj0ifjklktrAB(H(τAPkττB)H)ll0ifj=k. 6.8

Similar considerations can be made for the traces of the other two operators in (6.5):

tr{(IAPjτIB)([H,[H¯τB,τAPkτ]τB])}=tr{(IAPjτ)([H¯τB,[H¯τB,τAPkτ]])}=2(δjktr(H¯τB(τAPkτ)H¯τB)-tr((IAPjτ)H¯τB(τAPkτ)H¯τB))=2-trA(H¯τB(τAPkτ)H¯τB)jj0ifjklktrA(H¯τB(τAPkτ)H¯τB)ll0ifj=k, 6.9

and

tr{(IAPjτIB)([H,τA[H¯τA,PkττB]])}=tr{(PjτIB)([H¯τA,[H¯τA,PkττB]])}=2(δjktr(H¯τA(PkττB)H¯τA)-tr((PjτIA)H¯τA(PkττB)H¯τA))=2-trB(H¯τA(PkττB)H¯τA)jj0ifjklktrB(H¯τB(PkττB)H¯τB)ll0ifj=k. 6.10

Defining for 1knC the non negative operator h(k)B(HC) by

h(k)=2γA+γBtrAB(H(τAPkττB)H)+2γA/γBγA+γBtrB(H¯τA(PkττB)H¯τA)+2γB/γAγA+γBtrA(H¯τB(τAPkτ)H¯τB), 6.11

we eventually obtain

(ΦD)jk=-h(k)jj0ifjk+lkh(k)ll0ifj=k, 6.12

where ΦD is viewed as a matrix on CnC, and any diagonal matrix r=k=1nCrkPkτDiagτB(HC) is viewed as a vector r1r2rnCt of CnC.

We provide a necessary and sufficient condition on the coupling Hamiltonian H in terms of the diagonal matrix elements of h(k), 1knC for assumption Coup to hold, i.e. that ΦD restricted to diagonal traceless matrices is invertible.

Proposition 6.1

Assume L0=D, L1=-i[H,·] and consider the non negative operators {h(k)}1knC defined by (6.11). Assumption Coup holds if and only if there exists j{1,,nC} such that hjj(k)>0 for all 1kjnC.

Remark 6.2

  • i)

    Since h(k) is a sum of non negative operators, it is sufficient to check the condition on any of its constituants.

  • ii)

    Explicit computations show that for dimHC=2, assumption Coup holds as soon as ΦD0, while for dimHC=3 it is true if hr(j)hs(k)>0 for some 1jk3, rj, sk and (r,s)(k,j).

Proof

Within the framework introduced above we identify ΦD with its matrix (ΦD)jk. We need to show it admits zero as a simple eigenvalue, which amounts to showing that RankΦD=nC-1.

We use the short hand notations hj(k)=h(k)jj0 for jk and hj(j)=kjhk(j)0 to express the matrix elements of -ΦD. The proof follows once we establish the following Lemma

Lemma 6.3

Consider hMn(R) given by

h=h1(1)-h1(2)-h1(n)-h2(1)h2(2)-h2(n)-hn(1)-hn(2)hn(n),wherehj(k)0forjkhj(j)=kjhk(j)0. 6.13

Then, Rankh=n-1 if and only if 1jn such that hj(k)>0, 1kjn.

Remark 6.4

It is possible that Rankh=n-1 and one diagonal element hj(j)=0, in which case hej=0, where ej is the jth canonical basis vector of Cn.

We can associate to h a stochastic matrix p the elements of which are

graphic file with name 10955_2021_2752_Equ143_HTML.gif 6.14

such that xCn satisfies hx=0 iff pty=y, where y=Diag(h)xCn, if hk(k)>0 for all k. Hence, if Rankh=n-1, the components of x can all be chosen to be non negative, by Perron Frobenius theorem.

However p is not necessarily irreducible as one sees from the example h=100-11-10-11 with σ(h)={0,1,2} that admits the non strictly positive eigenvector 011T in its kernel

Proof

We know 0σ(h) and by Jacobi’s formula,

ddzdet(h-z)|z=0=trcomt(h)=j=1ndeth^jj, 6.15

where com(A) is the comatrix of A and A^jk is obtained by deleting the jth row and kth column of A. In our case

h^jj=h1(1)-h1(j-1)-h1(j+1)-h1(n)-hj-1(1)hj-1(j-1)-hj-1(j+1)-hj-1(n)-hj+1(1)-hj+1(j-1)hj+1(j+1)-hj+1(n)-hn(1)-hn(j-1)-hn(j+1)hn(n) 6.16

is real valued so that σ(h^jj)=σ(h^jj)¯. Moreover, by definition, for all kj

hk(k)=lkhl(k)lkljhl(k), 6.17

so that by Gershgorin Theorem

σ(h^jj)kj{zC||z-hk(k)|lkljhl(k)}kjGk 6.18

where the circle Gk centered at hk(k) of radius lkljhl(k) intersects the imaginary axis if and only if hj(k)=0, in which case the intersection reduces to the origin. Since the determinant of h^jj is the product of its complex conjugate eigenvalues, (6.18) yields

deth^jj0,withequalityiffkjs.t.hj(k)=0. 6.19

Therefore

j=1ndeth^jj0,withequalityiff1jn,kjs.t.hj(k)=0. 6.20

This ends the proof of the Proposition.

Emergence of a Classical Markov Process

Coming back to Corollary 4.7, we know that for times s.t. 0t1F+ϵ|ln(g)|/g2, the evolution semigroup et(D(·)-ig[H,·]) can be approximated by

etg2ΦD:DiagτB(HC)DiagτB(HC). 6.21

In the case at hand, ΦD is expressed in the orthonormal basis {|φjτφjτ|}1jnC as the matrix (6.12) denoted by h in Lemma 6.3. The negative of the transpose hT of h is thus a transition rate matrix or Q-matrix, associated to a classical continuous time Markov chain with finitely many states, see [24]. Therefore we can associate to our quantum problem ρ˙=D(ρ)-ig[H,ρ] a classical continuous time Markov chain (Xt)t0 on the state space {|φjτφjτ|}1jnC identified with {1,2,,n} with n=nC, as follows.

Let us recall the general framework. The Markov process (Xt)t0 is characterised by the probability to find the process in state j at time t0, given the process at time 0 is in state i, is denoted by

pij(t)=P(Xt=j|X0=i),i,j{1,2,,n}. 6.22

These transition probabilities P(t)=(pij(t))1i,jn are solutions to the matrix form forward and backward equations

P(t)=P(t)Q,P(0)=IP(t)T=QTPT(t),P(0)=I, 6.23

where Q=(qij)1i,jn is a transition rate matrix such that qii0, qij0 and j=1nqij=0. Hence, with the identification Q=-hT we get the following interpretation

Theorem 6.5

Consider Lg(·)=D(·)-ig[H,·] under assumptions Spec(H¯τ) and Coup. Then, the operator etg2ΦD arising in the approximation of etLg provided in (4.44), describes a (rescaled) continuous time Markov process (Xt)t0 on the state space {|φjτφjτ|}1jnC{1,,n} such that for all S0,

P(Xs=j|X0=i)=trC{|φiτφiτ|esΦD(|φjτφjτ|)}. 6.24

Remark 6.6

Therefore, for any S0, the transpose of esΦD is a stochastic matrix.

Let us note that appearance of a classical Markov process on the eigenstates of the leading order driving Hamiltonian within the derivation of Lindblad generators for open quantum systems is well known. By contrast, in absence of leading order driving Hamiltonian, the state space of the Markov process into play is determined by the eigenstates of the averaged first order Hamiltonian H¯τ, which takes into account the effects of the reset matrices.

Finally, let us address the computation of the order g2 corrections (4.32) of the simple eigenvalues λjk(g) of Lg(·)=D(·)-ig[H,·] given by

λ~jk(1)=tr{(IA|φkτφjτ|IB)[H,L0-1([H,τA|φjτφkτ|τB])]}. 6.25

We prove in Appendix that

Proposition 6.7

Consider Lg(·)=D(·)-ig[H,·] under assumptions Spec(H¯τ) and Coup. Then, the eigenvalues λjk(g) of Lg, see Proposition 4.5, satisfy

Rλjk(g)-g2γA2+γAγB+γB2γAγB(γA+γB)(ejτ-ekτ)2+O(g3) 6.26

Remark 6.8

Actually, we show that Rλ~jk(1) is upper bounded by a sum of non positive explicit contributions. Hence one can decrease the contributions stemming from these eigenvalues in the approximations of the dynamics shown in Corollary 4.7 by assuming the coupling Hamiltonian H makes the lower bounds of Lemma 9.1 below large enough.

Example on C2CNC2

We present here an example where the two parts of the Hilbert space on which the dissipator acts non trivially are both C2=HA=HB, while the central part HC=CN, with N arbitrary. The orthonormal bases of HA, HB and HC are denoted respectively by {|g,|e}, {|,|} and {φj}j=1N. The reset states associated with rates γA,γB>0 are

τA=tA|gg|+(1-tA)|ee|,τB=tB||+(1-tB)||, 7.1

where 0<tA,tB<1. We consider again a case without leading order Hamiltonian drive, that is HA=HB=HC=0, while the order g Hamiltonian reads

H=HαIB+IAHβ,whereHα=j=1Naj(g)|gφjgφj|+aj(e)|eφjeφj|+k=1Nαk|gφ1eφk|+h.c.Hβ=j=1Nbj()|φjφj|+bj()|φjφj|+k=1Nβk|φNφk|+h.c. 7.2

In other words,

Hα=|gg|Ha(g)+|ee|Ha(e)+|ge||φ1Φα|+|eg||Φαφ1| 7.3
Hβ=||Hb()+||Hb()+|||φNΦβ|+|||ΦβφN| 7.4

with Ha(#)=j=1Naj(#)|φjφj|, #{g,e}, Φα=k=1Nαkφk, and similarly for Hβ, introducing Hb(#)=j=1Nbj(#)|φjφj|, #{,}, and Φβ=k=1Nβkφk.

On the one hand, this example shows our hypotheses can be checked for arbitrary N and, on the other hand, it can lead to physically relevant models under additional assumptions, see for instance Sect. 8 where we deal with qubits (N=2) subject to inter-qubit Coulomb interaction and flip-flop type interaction Hamiltonian.

With these definitions we compute

H¯τ=tAHa(g)+(1-tA)Ha(e)+tBHb()+(1-tB)Hb()=j=1N(tAaj(g)+(1-tA)aj(e)+tBbj()+(1-tB)bj())|φjφj|, 7.5

which yields

φjτ=φjandejτ=(tAaj(g)+(1-tA)aj(e)+tBbj()+(1-tB)bj()). 7.6

We can choose the real parameters aj(g),aj(e),bj(),bj() so that the generic assumption Spec H¯τ holds for any choice of 0<tA,tB<1.

Leading Order Term

The next step consists in determining the diagonal elements of the nonnegative operators h(k) defined in (6.11), 1kN; more precisely hj(k):=φj|h(k)φj, for jk. We first compute

H¯τA=Hβ+(tAHa(g)+(1-tA)Ha(e))IB 7.7
H¯τB=Hα+IA(tBHb()+(1-tB)Hb()). 7.8

Since we do not need the elements φk|h(k)φk, we do not make explicit their contribution, that we generically denote below by ci(k)Pk, where ci(k)0, i=1,2,3,4. With this convention, we get for the different elements h(k) is made of

trAB(H(τAPkττB)H)=c1(k)Pk+(1-tA)|αk|2|φ1φ1|+δk,1tA|ΦαΦα|+(1-tB)|βk|2|φNφN|+δk,NtB|ΦβΦβ|trA(H¯τB(τAPkτ)H¯τB))=c2(k)Pk+(1-tA)|αk|2|φ1φ1|+δk,1tA|ΦαΦα|trB(H¯τA(PkττB)H¯τA))=c3(k)Pk+(1-tB)|βk|2|φNφN|+δk,NtB|ΦβΦβ|. 7.9

Eventually,

h(k)=2γAγB{(1-tA)|αk|2γB|φ1φ1|+δk,1tAγB|ΦαΦα|+δk,NtBγA|ΦβΦβ|+(1-tB)|βk|2γA|φNφN|}+c4(k)Pk, 7.10

The offdiagonal elements hj(k), jk, of the matrix -ΦD immediately follow: let

graphic file with name 10955_2021_2752_Equ166_HTML.gif 7.11

Therefore the matrix form (8.17) of the operator ΦD reads

graphic file with name 10955_2021_2752_Equ167_HTML.gif 7.12

where the diagonal elements h~j(j)=Tj+Sj, 0<j<N, h~1(1)=j=2NUj+TN and h~N(N)=j=2NVj+SN.

Note that αj0 Sj0 and Uj0 , while βj0 Tj0 and Vj0. Hence, looking at the first row of (7.12), one sees that Coup holds for this model when

α2α3αN-10and|β1|2+|αN|20, 7.13

or, looking at the last row, when

β2β3βN-10and|β1|2+|αN|20. 7.14

In either cases, this validates the conclusions of Theorem 5.2 on the invariant state and the way to compute it. From now on, we assume that either (7.13) or (7.14) holds.

The leading term of the invariant state is determined by the one dimensional kernel of ΦD which turns out to be computable explicitly. We have, noting that Sj+Tj>0 for 2jN-1,

KerΦD=Cx1x2xN,wherex1=SN+j=2N-1VjSjSj+Tj+V1xN=UN+j=2N-1UjTjSj+Tj+T1xj=Ujx1+VjxNSj+Tj,2jN-1. 7.15

The corresponding faithful leading order ρ0, i.e. ρ0>0, of the invariant state of the QRM thus reads

ρ0=1ZτAj=1Nxj|φjφj|τB,whereZ=k=1Nxk. 7.16

Actually, the following more explicit expressions are true. With

y(N)=j=2N-1γAγB|αjβj|2(1-tA)γB|αj|2+(1-tB)γA|βj|2, 7.17

we can write

x1=(1-tA)|αN|2γB+y(N)tB(1-tA)+tB|β1|2γA 7.18
xN=tA|αN|2γB+y(N)tA(1-tB)+(1-tB)|β1|2γA 7.19
xj=tA|αN|2γB+tB|β1|2γA+y(N)tAtB+γAγB(|αN|2tA(2tB-1)|βj|2+|β1|2tB(2tA-1)|αj|2)(1-tA)γB|αj|2+(1-tB)γA|βj|2, 7.20

for 2jN.

Note in particular the generic nontrivial dependence on j of the populations of (the reduced) leading order ρ0 of the invariant state. Further remarks are in order:

  • For non zero coefficients αj and βj, xj is independent of 2jN-1 if
    (2tA-1)tB(1-tA)γA|β1|2=(2tB-1)tA(1-tB)γB|αN|2. 7.21
  • In case we consider thermal states for τ# on C2, #{A,B}, such that t#=11+e-β#E#, with excitation energy E#>0. We get that t#1 when β#, while t#1/2 when β#0, which shows that at high temperature, the populations tend to be constant.

Example on C2C2C2

With the previous example considering HCCN, we could derive the exact expressions of the map ΦD and of the leading order solution. However, going to first order correction and beyond requires considerable effort and would not be enlightening for the reader. This motivates this second example, where we restrict HC to be in C2 and consider an interaction Hamiltonian H that is appropriate to describe effective physical systems. The goal of this section is twofold. First, we derive explicitly higher order corrections illustrating the theorems of Sect. 5, showing that we can capture the main features of the dynamics with relatively little effort as compared to the complexity of the system. Second, we make a clear connection between a tri-partite quantum reset model and models suitable to describe realistic physical systems.

Model

Explicitly, we consider here a chain of three qubits characterized by their bare energies eA,eB,eC entering H0. They are interacting through H. The two Hamiltonians are given by

H0=eA|11|ICIB+IAeC|11|IB+IAICeB|11|, 8.1
H=U(|11AC11|IB+IA(|11CB11|)+(Jα|01AC10|IB+IAJβ|01CB10|+h.c). 8.2

Without loss of generality, we assume the interaction strengths U,Jα,Jβ to be real. This model could be effective for instance for three qubits subject to nearest-neighbour interactions: a Coulomb interaction (set by U) whenever two adjacent qubits are occupied and to a flip-flop interaction term of the form |0110|+h.c. that conserves the number of excitations (set by Jα,Jβ with JαJβ). In the ordered computational basis of the three qubits

{|000,|001,|010,|011,|100,|101,|110,|111}, 8.3

the total Hamiltonian Htot=H0+gH reads

Htot=000000000eBgJβ000000gJβeC0gJα000000eB+eC+gU0gJα0000gJα0eA000000gJα0eA+eBgJβ000000gJβeA+eC+gU00000000eA+eB+eC+2gU. 8.4

This model corresponds exactly to the previous example with N=2 and setting:

α1=β2=a2(e)=a1(g)=a2(g)=b2()=b2()=b1()=0 8.5
a1(e)=b1()=U,α2=Jα,β1=Jβ, 8.6

The ground state for the three qubits is now simply given by |000 and corresponds to |gφ2 in the previous example with N=2. For clarity, we provide the expression of Htot in the form introduced in (7.2)

Hα=U|eφ1eφ1|+Jα|gφ1eφ2|+h.c.Hβ=U|φ1φ1|+Jβ|φ2φ1|+h.c. 8.7

The two ends (A and B) of the 3-qubit chain are weakly coupled to their own thermal baths at inverse temperatures βA and βB with coupling strengths γA and γB respectively. Dissipation takes place following QRM . The reset states are assumed to be thermal states defined by the Maxwell-Boltzmann distribution with their respective inverse temperature β#=1/T# (kB=1 in the following) in the basis {|0,|1}:

τ#=1Z#100e-β#e#=t#001-t#,#{A,B}. 8.8

Note that since the ground state |0 in the C part of the Hilbert space corresponds to |, the substitution tB(1-tB) is in order to use the results of Sect. 7.

Let us remark that this model for a tri-partite open quantum system differs from previous works on reset models in the context of quantum thermodynamics, studying in particular quantum absorption refrigerators and entanglement engines, Refs. [4, 30, 32]. These models consist of a chain of 2, 3 or N qubits, each of them being coupled to its own thermal bath. Dissipation due to the presence of environments is captured through QRM . In Ref. [30], the steady-state solution for 3 qubits with three different environments is derived analytically, whereas the case of two qubits is fully solved in Ref. [4]. In contrast, in this work, we derive the steady-state solution considering an arbitrary system C only coupled to the two ends A and B of the chain, as long as HC satisfies generic assumptions.

Generic Assumptions

We first check the assumptions for HC and H. The condition Spec(HC), is trivially satisfied in this case as the spectrum σ(HC)={0,eC} is simple with eC0. We can then verify Spec(H¯τ) with

H¯τ=trAB(HτAICτB)=U(2-tA-tB)|11|, 8.9

as defined by Eq. (4.13) . The spectrum σ(H¯τ)={0,U(2-tA-tB)} with associated eigenvectors {|0,|1} is simple whenever U0 and tA+tB2 where tA,tB stand for the ground state populations of the reset states τA,τB. The identity tA+tB=2 is only satisfied for zero temperature reservoirs, tA=tB=1. Hence we stay in the generic case, tA,tB<1. The condition U0 also tells us that a flip-flop interaction Hamiltonian of the form (|0110|+h.c.) is not sufficient to ensure the required non-degeneracy conditions in the 0-subspace of L0. We easily verify that the kernel of L0 has dimension nC2=4 if HC=0 and nC=2 if HC0.

In the following, we will restrict the derivation of the steady-state solution up to the second order correction assuming no drive, i.e. HA=HB=HC=0. Let us note that in two dimensions, there is no loss of generality to consider the reset states τA and τB defined as thermal states with respect to HA and HB.

Leading Order Solution, No Drive

Under Spec(H¯τ) and Lemma 4.1, the first-order-correction projector Q~0L~1Q~0 in the 0-eigenvalue subspace is fully characterized by the map Φ acting onto HC, see Eq. (4.25) and Theorem 4.3

Φ(·):=trAB([H,L0-1([H,τADiag(·)τB])]):B(HC)B(HC){ρC|trρC=0}. 8.10

In contrast to the previous example, we can compute explicitly here the map Φ and not only ΦD. To this end, we consider ρC to be initially in an arbitrary diagonal state (with respect to the eigenbasis of H¯τ)

ρC=rC000rC1. 8.11

Defining the linear form on C2

X(rC0,rC1)=-rC0(Jβ2(1-tB)γA+Jα2(1-tA)γB)+rC1(Jβ2tBγA+Jα2tAγB), 8.12

we find the matrix Φ(ρC)B(HC) to be given by (with respect to the eigenbasis of H¯τ)

Φ(ρC)=2γAγBX(rC0,rC1)00-X(rC0,rC1). 8.13

Note that Φ(ρC) is diagonal, so that for this example we have Φ(·)=ΦD(·). In particular

KerΦD(·)=CγAtBJβ2+γBtAJα200γA(1-tB)Jβ2+γB(1-tA)Jα2 8.14

is one dimensional, so that Assumption Coup is satisfied. Then KerΦD provides the leading order steady-state solution ρ0=τAρC(0)τB with

ρC(0)=γAtBJβ2+γBtAJα2γAJβ2+γBJα200γA(1-tB)Jβ2+γB(1-tA)Jα2γAJβ2+γBJα2. 8.15

Interestingly, the zeroth order solution is the exact solution in the equilibrium situation, i.e. when τA=τB=τ, the state ρ0=τττ satisfies for any gR (or C) Lg(ρ0)=0, an instance of Remark ii) 5.3.

Remark 8.1

In this example, the matrix ΦD can also be derived directly from the previous example with N=2, starting from the positive operator h(k):

h(k)=2γAγB(|αk|2(1-tA)γB|11|+|βk|2tBγA|00|+tAγB|00|+(1-tB)γA|11|)+c4(k)P(k). 8.16

In the basis {|00|,|11|}, given (8.5), the substitution tB1-tB, and according to (7.12), the matrix ΦD reads

ΦD=-2γAγBγAJβ2(1-tB)+γBJα2(1-tA)-γAJβ2tB-γBJα2tA-γAJβ2(1-tB)-γBJα2(1-tA)γAJβ2tB+γBJα2tA, 8.17

whose kernel in this same basis is generated by the two-dimensional vector

KerΦD=C(γAJβ2tB+γBJα2tA,γAJβ2(1-tB)+γBJα2(1-tA))T. 8.18

Let us note that ΦD, when written as a superoperator acting onto diagonal matrices, takes a diagonal form, see Eq. (8.13).

Underlying Markov Process

We have enough information here to determine the natural two-state classical continuous Markov process associated to the model, according to Theorem 6.5. The state space is denoted by {0,1}{|00|,|11|}, and by (6.24) we need to compute esΦD to determine the transition probabilities of the process

P(Xs=j|X0=k)=tr{|kk|esΦD(|jj|)}(esΦD)k,j,0j,k1 8.19

The spectral decomposition of ΦD in the matrix form (8.17) is easily obtained. Introducing

φ+=γAJβ2tB+γBJα2tA,φ-=γAJβ2(1-tB)+γBJα2(1-tA), 8.20

we have

σ(ΦD)={0,-2(φ++φ-)/(γAγB)}={0,-2(γAJβ2+γBJα2)/(γAγB)}, 8.21

with eigenvector associated to the non zero eigenvalue proportional to 1-1T. Hence,

ΦD=-2(φ++φ-)γAγBQ++0Q0, 8.22

with spectral projectors

Q0=|φ+φ-11|φ-+φ+,Q+=|1-1φ--φ+|φ-+φ+. 8.23

Therefore, with s~=2s(φ++φ-)γAγB,

esΦD=e-s~Q++Q0=1φ-+φ+φ++e-s~φ-φ+-e-s~φ+φ--e-s~φ-φ-+e-s~φ+. 8.24

In turn this eventually yields the sought for transition probabilities

P(Xs=0|X0=0)=φ++e-s~φ-φ-+φ+,P(Xs=1|X0=1)=φ-+e-s~φ+φ-+φ+,P(Xs=1|X0=0)=φ-(1-e-s~)φ-+φ+,P(Xs=0|X0=1)=φ+(1-e-s~)φ-+φ+. 8.25

We stress that in absence of leading order driving Hamiltonian, the state space of the Markov process into play is determined by the eigenstates of H¯τ, that takes into account the effects of the reset matrices.

Higer-Order Corrections, No Drive

We now illustrate Theorem 5.2 by deriving the converging expansion of the unique invariant state of Lg

ρ0(g)=ρ0+gρ1+g2ρ2+with,ρ0=τAρC(0)τB, 8.26

and

ρj=Rj+τArC(j)τBj1. 8.27

We recall the definitions for convenience

Rj=iL0-1([H,ρj-1]),OffdiagτrC(j)=-i[H¯τ,·]-1(OffdiagτtrAB([H,L0-1([H,ρj-1])])),DiagτrC(j)=-ΦD-1(DiagτtrAB([H,L0-1(i[H,Rj+τAOffdiagτrC(j)τB])])).

For the first-order correction, we start computing R1=iL0-1([H,τAρC(0)τB]) which can be expressed with F=i(|0110|-|1001|) (acting on HAHC or HCHB depending on the context) as

R1=(tA-tB)JαJβγAJβ2+γBJα2(JβFτB+JατAF)=(tA-tB)JαJβγAJβ2+γBJα2(Jβi(|0110|-|1001|)τB+JατAi(|0110|-|1001|)). 8.28

We first note that since Φ=ΦD, the expression for OffdiagτrC(1) reduces to zero:

OffdiagτrC(1)=-i[H¯τ,·]-1(OffdiagτΦ(ρC(0)))0. 8.29

Then, it remains to determine DiagτrC(1) to get the first order correction in g. Thanks to (8.29) and using (8.28) for R1, we compute

DiagτrC(1)=-ΦD-1(DiagτtrAB([H,L0-1(i[H,R1])]))=0. 8.30

Hence, the first order correction is simply given by R1, ρ1=R1 and we obtain

ρ0(g)=τAρC(0)τB+gR1+O(g2). 8.31

We proceed with the second-order correction and compute R2=iL0-1([H,R1]). The matrix R2 is rather complex and we provide the expressions for its diagonal and off-diagonal elements separately. Its 8 diagonal elements in the ordered basis (8.3) are proportional to by

Diag(R2)=JαJβγAγB(tAtB(γA-γB),-tA(tBγA+γB(1-tB)),tAγA(1-tB)-tBγB(1-tA),(1-tB)(tAγA-γB(1-tA)),tB(γBtA+γA(1-tA)),γAtA(1-tB)-γAtB(1-tA),(1-tA)(γBtB+γA(1-tB)),(1-tA)(1-tB)(γB-γA)). 8.32

For its off-diagonal elements, we introduce F2=|0110|+|1001| and the coefficient matrices

ΓA=γA00γA+γB/(1-tA);ΓB=γB00γB+γA/(1-tB). 8.33

The matrix R2 can then be written in a compact form

R2=2JαJβ(tA-tB)Jβ2γA+Jα2γB{Diag(R2)+1γA+γB×(-JαU(1-tA)2γBτAΓAF2+JβU(1-tB)2γAF2τBΓB-12(Jα2tA-Jβ2tB)|001100|+12(Jα2(1-tA)-Jβ2(1-tB))|110011|)}. 8.34

For OffdiagrC(2), we find that it is equal to 0. This leads us to:

DiagrC(2)=X(2)00-X(2) 8.35

with

X(2)=2iJα2Jβ2(tA-tB)γA2γB2(γA+γB)(Jβ2γA+Jα2γB)×{(γA+γB)(Jβ2γA(2γA-γB)-Jα2γB(2γB-γA))+U2((1-tA)γA2(γB+(1-tA)γA)-(1-tB)γB2(γA-(1-tB)γB))}. 8.36

The solution up to the second-order correction is then given by

ρ0(g)=τA(ρC(0)+g2rC(2))τB+gR1+g2R2+O(g3). 8.37

We note that coulomb-interaction term like in U starts playing a role when considering the second-order correction.

Acknowledgements

GH acknowledges support from the Swiss National Science Foundation through the starting grant PRIMA PR00P2_179748 and the National Center of Competence in Research SwissMap for a stimulating research environment. AJ is partially supported by the Agence Nationale de la Recherche through the grant NONSTOPS (ANR-17-CE40-0006-01), and he wishes to thank the Université de Genève for hospitality during the first stages of this work. Both authors acknowledge support from the Banff International Research Station which hosted the 2019 meeting ”Charge and Energy Transfer Processes: Open Problems in Open Quantum Systems” where this project started.

Appendix

We provide here the proof of Proposition 6.7.

Proof

By computations similar to those performed in the determination of ΦD, we have with Pjkτ=|φjτφkτ|,

[H,L0-1([H,τAPjkττB])]=-1γA+γB[H,[H,τAPjkττB]]-γB/γAγA+γB[H,[H¯τB,τAPjkτ]τB]-γA/γBγA+γB[H,τA[H¯τA,PjkττB]]-γA2+γAγB+γB2γAγB(γA+γB)(ejτ-ekτ)[H,τAPjkττB]. 9.1

The last term in (9.1) yields the following contribution to λ~jk(1), using cyclicity of the trace and H¯τφjτ=ejτφjτ,

-γA2+γAγB+γB2γAγB(γA+γB)(ejτ-ekτ)2<0. 9.2

Then, using cyclicity of the trace and PkjτPjkτ=Pkkτ, we have

tr(IAPkjτIB[H,[H,τAPjkττB]])=-2tr(IAPkjτIBHτAPjkττBH)+tr(H(τAPjjττB)H)+tr(H(τAPkkττB)H)=tr(H(τAPjjττB)H)+tr(H(τAPkkττB)H)-2(trAB(H(τAPjkττB)H))jk. 9.3

Here Ajk denotes the jk of the matrix AB(HC) with respect to the basis {φjτ}. Note that the operators in the full traces are non negative, whereas the last term is a priori complex valued.

Similarly,

tr(IAPkjτIB[H,τA[H¯τA,PjkττB]])=trAC(H¯τA(PjjττB)H¯τA)+trAC(H¯τA(PkkττB)H¯τA)-2(trB(H¯τAPjkττBH¯τA))jk, 9.4

and the analogous formula holds for the term involving H¯τB. These expressions allow us to bound below their real part by a non negative quantity, as the next lemma shows.

Lemma 9.1

Under the hypotheses above, we compute

Rtr{(IAPkjτIB)[H,[H,τAPjkττB]]}tr{(IA(IC-Pjjτ)IB)H(τAPjjττB)H(IA(IC-Pjjτ)IB)}+samewithkj. 9.5
Rtr{IAPkjτIB[H,τA[H¯τA,PjkττB]]}tr{((IC-Pjjτ)IB)H¯τA(PjjττB)H¯τA((IC-Pjjτ)IB)}+samewithkj. 9.6
Rtr{IAPkjτIB)[H,[H¯τB,τAPjkτ]τB]}tr{(IA(IC-Pjjτ))H¯τB(τAPjjτ)H¯τB(IA(IC-Pjjτ))}+samewithkj. 9.7

Remark 9.2

Since

(IA(IC-Pjjτ)IB)H(τAPjjττB)H(IA(IC-Pjjτ)IB)=((τA1/2PjjττB1/2)H(IA(IC-Pjjτ)IB))×((τA1/2PjjττB1/2)H(IA(IC-Pjjτ)IB)) 9.8

is a non negative operator, we get from (9.1), (9.2) and the Lemma that

Rλ~jk(1)-γA2+γAγB+γB2γAγB(γA+γB)(ejτ-ekτ)2<0, 9.9

which proves Proposition 6.7.

Proof

We prove the first inequality, the others are similar. Let G=H(τA1/2ICτB1/2), so that the real part we need to consider reads, see (9.3),

tr(G(IAPjjτIB)G)+tr(G(IAPkkτIB)G)-2tr((IAPjkτIB)G(IAPkjτIB)G). 9.10

Spelling out the traces we get

tr(G(IAPjjτIB)G)=n,m,r,sl|φrAφlτφsB|GφnAφjτφmB|2 9.11
tr((IAPjkτIB)G(IAPkjτIB)G)=n,m,r,sφrAφkτφsB|GφnAφkτφmBφnAφjτφmB|GφrAφjτφsB, 9.12

and we observe that the complex conjugate of (9.12) is obtained by exchanging j and k. Hence we can express the real part of (9.10) as

n,m,r,s|φrAφjτφsB|GφnAφjτφmB|2+|φrAφkτφsB|GφnAφkτφmB|2-φrAφkτφsB|GφnAφkτφmBφnAφjτφmB|GφrAφjτφsB-φrAφjτφsB|GφnAφjτφmBφnAφkτφmB|GφrAφkτφsB+|φrAφkτφsB|GφnAφjτφmB|2+|φrAφjτφsB|GφnAφkτφmB|2+n,m,r,sl{j,k}|φrAφlτφsB|GφnAφjτφmB|2+|φrAφlτφsB|GφnAφkτφmB|2. 9.13

With a=φrAφjτφsB|GφnAφjτφmB and b=φrAφkτφsB|GφnAφkτφmB, we rewrite the first four terms of the summand as

|a|2+|b|2-ba¯-ab¯=ab|1-1-11ab0, 9.14

since 1-1-110. The remaining terms can reorganised as follows,

n,m,r,s|φrAφjτφsB|GφnAφkτφmB|2+l{j,k}|φrAφlτφsB|GφnAφjτφmB|2=n,m,r,slj|φrAφlτφsB|GφnAφjτφmB|2=tr{(I-IAPjjτIB)G(IAPjjτIB)G(I-IAPjjτIB)}, 9.15

and similarly for the terms with second index equal to k, which yields the result.

And the proof of Proposition 6.7 is finished.

Funding

Open Access funding provided by University of Geneva.

Footnotes

Publisher's Note

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