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, 7–9, 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, , 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 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 —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 which is coupled to M reservoirs. QRMs assume the state of the quantum system to be reset to a given state with probability within each time interval dt. The QRM-type evolution equation is given by [4, 15, 19]:
2.1 |
The operator is the reduced density operator of the system defined on , and characterizes the coupling rate to the reservoir l, .
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 be a Hilbert space, with . The dissipative part of the generator is characterised by
a collection of density matrices on , i.e. , with and , for all ,
, , the collection of associated non-zero rates for the coupling to the M baths.
The Hamiltonian part of the generator, , is generic in the spectral sense
, consists of simple eigenvalues with associated normalised eigenvectors denoted by , i.e. , ,
The differences (Bohr frequencies) are all distinct.
The generator of QRM is thus the (super-)operator defined by
2.2 |
where here is arbitrary in , such that the dynamics of the QRM reads
2.3 |
In case , the set of density matrices , the trace factor in (2.2) disappears. Indeed, we will see below in a more general framework that the operator enjoys further symmetries, being a Lindblad operator, see Proposition 3.2; in particular if , , for all .
However, we perform the full spectral analysis of as an operator on and, accordingly, solve the equation (2.3) without resorting to these symmetries.
We first combine the density matrices with corresponding rates into a single density matrix T with corresponding rate . Setting
2.4 |
we get that (2.2) writes
2.5 |
In the sequel, we denote the matrix elements of any in the basis by , and the operator , for , is defined by .
Lemma 2.1
Under our assumptions Gen, the operator defined by (2.5) is diagonalisable with spectrum given by
2.6 |
All eigenvalues are simple, except which has multiplicity .
Moreover, the solution to (2.3) reads
2.7 |
Expressed in the eigenbasis of H, this means that, with ,
2.8 |
Remark 2.2
-
i)In the limit the steady state is independent of the initial condition and reads
2.9 -
ii)
In particular, for , all populations decay to at the same exponential rate without oscillations .
-
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 , with implies for any , so that the trace is conserved by (2.3). Hence, considering the jk matrix element of the differential equation (2.3) we get
2.10 |
which yields (2.8). The basis independent formulation (2.7) follows by the decomposition and the observation
2.11 |
which yields .
On the spectral side, the observation above immediately yields for , showing are simple eigenvalues by our genericity assumption. To compute the other nonzero eigenvalues of , we note that if is an eigenvector of associated with an eigenvalue , then . Hence implies . Thus, considering the dimensional subspace of diagonal traceless matrices in the eigenbasis of H, , and making use of the identity , for any j, we see that it coincides with . Finally, the one-dimensional kernel of is spanned by : the inverse is well defined thanks to (2.11), it has matrix elements , and trace one. Thus
2.12 |
Tri-partite Hilbert Spaces
We define here the tri-partite systems whose dynamical properties are studied in this paper.
Consider , where are Hilbert spaces, with dimensions noted , where . Let , be two density matrices on their respective Hilbert space and two positive rates. Consider three Hamiltonians on their respective Hilbert space that further satisfy
2.13 |
while is arbitrary at this point. In applications, the reset state will typically be defined as a Gibbs state at some inverse temperature associated to ; i.e. which satisfies (2.13), where is the corresponding partition function. In Sect.3, we perform the analysis of the uncoupled case (system 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 .
The Non-interacting Tripartite QRM
We define the uncoupled QRM by the generator
3.1 |
where denotes the identity operator on and denotes the operator on the tensor product of Hilbert spaces with indices different from , obtained by taking the partial trace over . For later purposes, denotes the operator on the Hilbert space with index different from and obtained by taking the partial trace over . For example,
3.2 |
will be viewed as linear maps. We shall abuse notations and write for the Hamiltonian both on and , the context making it clear what we mean. Also, we shall denote the non-Hamiltonian part of the generator by
3.3 |
so that
Remark 3.1
If , and the last tensor product is trivial. Hence the QRM reduces to on , while keeping .
Let us start by a structural result saying that the QRM at time t, , with 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.
3.4 |
Given (3.1), it is enough to consider defined on .
Proposition 3.2
Let be the spectral decomposition of , where is a complete orthonormal basis of . Then
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 , in which case reduces to the scalar valued trace.
-
ii)
The operators can be replaced by , where is any orthonormal basis of without altering the result.
Spectrum of the Uncoupled QRM
We proceed by analysing the spectrum of the uncoupled QRM (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:
3.6 |
since and commute, while
3.7 |
using with an orthonormal basis of eigenvectors of . Now, replacing by (or for that matter) yields
3.8 |
since commutes with and . Altogether, the dissipator and the Hamiltonian parts of 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 , admits the following spectral decomposition
where the spectral projectors , are given by
Moreover, the different spectral subspaces in are
Remark 3.5
-
i)
In case , there are only three distinct eigenvalues and the corresponding spectral projector is .
-
ii)
Being spectral projectors, the ’s, satisfy and
-
iii)
The dimensions referred to correspond to complex dimensions for .
-
iv)
The result essentially follows from the observation that and are commuting projectors.
Proof
We start with point iv) of Remark 3.5. For any in ,
3.9 |
while , and similarly for . Hence the dissipator is a linear combination of two commuting projectors to which we can apply the next Lemma.
Lemma 3.6
Let such that and . Then, for any , the identity
3.10 |
provides the spectral decomposition of , so that , with respective spectral projectors , 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 , , , 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 are readily computed. For , let be an orthonormal basis of of eigenvectors of , with associated eigenvalues , . The eigenvalues need not to be distinct at that point. We denote by , , the operators that yield a basis of eigenvectors of the Hamiltonian part of (3.1) of :
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 dimensional basis of diagonal (w.r.t. to the eigenbasis of ) traceless matrices
3.12 |
such that . Together with , the ’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 consisting in eigenvectors associated with the mentioned eigenvalue of the uncoupled QRM
defined on by (3.1):
Remark 3.8
-
0)
The Hamiltonians are arbitrary at that point.
-
i)
The uncoupled reset model Lindbladian is thus diagonalisable, with eigenvalues located on the (generically) four vertical lines , , , in the complex plane, symmetrically with respect to the real axis.
-
ii)
In particular, the kernel of is degenerate, since .
-
iii)
It is straightforward to generalise this result to the case where the dissipator admits a reset part acting on as well, and to the case of a p-partite non interacting system, with arbitrary.
The spectral projectors of can be constructed explicitly, making use of the next Lemma:
Lemma 3.9
Consider a Hilbert space and a density matrix. Let be an orthonormal basis of eigenvectors of for . Consider the basis of given by
3.13 |
Set , . Then the operators on defined by
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 corresponding to Proposition 3.7 are then given by the appropriate tensor products of projectors (3.14).
The solution to , follows immediately by expanding along those eigenvectors. In particular, one gets for this uncoupled QRM model
3.15 |
where satisfies the Hamiltonian evolution equation , on , as expected in this uncoupled context.
The Weakly-Interacting Tripartite QRM
We consider now the coupled QRM defined by the Lindblad generator on , with ,
4.1 |
where is a Hamiltonian that effectively couples the different Hilbert spaces , while is a coupling constant. We focus on the determination of the kernel of , as , which describes the asymptotic state of the system driven by , under generic hypotheses. Then we turn to the consequences for the dynamics generated by . 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 , Proposition 3.7 shows that
4.2 |
whatever the properties of the Hamiltonian . We shall consider below both cases and , which give rise to different results. In case the Hamiltonian is trivial,
4.3 |
has dimension , and the corresponding spectral projector coincides with , the spectral projector on , see Proposition 3.4. In order to avoid accidental degeneracies when , we will assume satisfies the spectral hypothesis
Spec():
The spectrum of is simple and the Bohr frequencies are distinct.
Under this assumption, we have
4.4 |
which is of dimension . The corresponding spectral projector acts as follows
4.5 |
where the projector defined by
4.6 |
extracts the diagonal part of within the normalised eigenbasis of . Observe that , extracting the offdiagonal part of within the same basis, yields the complementary projector
4.7 |
We also note, for later reference, that on is trace preserving, so that .
Analytic perturbation theory, see e.g. Chapter II §2 [17], allows us to compute the splitting of the degenerate eigenvalue zero of by the perturbation . Recall here that being a Lindblad operator (Proposition 3.2), the following structural constraints hold:
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 . The same is actually true for all eigenvalues sitting on the imaginary axis.
Let be the set of eigenvalues of that stem from the eigenvalue 0 of , with if or if . They form the so-called group for , and for with |g| small enough, are analytic functions of a (fractional) power of g that tend to zero as . These eigenvalues may be permanently degenerate. For the structural reasons recalled above, one of these eigenvalues, denoted by , is identically equal to zero, , , and in case is degenerate, it is semisimple.
We show that under generic hypotheses, is a simple eigenvalue, see Theorem 4.3, and we determine the corresponding eigenvector , normalized to be a state, i.e. and .
Let us denote by the analytic spectral projector of corresponding to the set of eigenvalues in the 0-group . It writes
4.9 |
for |g| small where is a circle of small radius centered at the origin. Also, since 0 is a semisimple eigenvalue of ,
4.10 |
where is the reduced resolvent of at 0, satisfying and . In other words, , that we shall sometimes abusively write , with the understanding that it acts on . The analytic reduced operator in the corresponding subspace which describes the splitting reads
4.11 |
where we used .
Lemma 4.1
Under assumption Spec() when , we have
4.12 |
where
4.13 |
Explicitly, with ,
4.14 |
As a consequence, when the splitting is generically described by the order correction, while in case , the non-zero first order correction imposes that the elements of the kernel of commute with which, generically, decreases the degeneracy from to . In both cases, the eigenvalue zero of is semisimple.
Proof
We first compute for any , using (4.13),
4.15 |
One gets the explicit expression for by expressing the partial trace within the eigenbases of . Therefore
4.16 |
The fact that implies then follows from
4.17 |
and the identity
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
4.19 |
where we observe with (4.10) that
4.20 |
Let be the eigenprojector onto . Then the spectrum of describes the splitting to order , see [17], Thm 5.11: for of multiplicity , there exist exactly eigenvalue of of the form
4.21 |
Notice that is viewed as an operator on here.
We observe that , hence
4.22 |
since .
In order to proceed, we shall also assume in the sequel that the operator appearing in Lemma 4.1 has generic spectral properties.
Spec():
The spectrum of is simple and the corresponding Bohr frequencies are distinct. We denote the normalised eigenvectors and eigenvalues of by and , .
Under Spec(), we get from (4.5) and Lemma 4.1
4.23 |
where is the projector that extracts the diagonal part of the matrices expressed in the orthonormal eigenbasis . Therefore
4.24 |
where stands here for (resp. ) if (resp. ). Equivalently, is fully characterised by the following linear map. Set
4.25 |
Note that is well defined and takes the form , for , hence , for any . Then, the restriction of to , which has dimension , satisfies
4.26 |
We shall abuse notations in the sequel and simply write
4.27 |
identifying operators defined on and . Hence
4.28 |
Note that , since , a subspace of dimension , in keeping with the fact that is never trivial. Hence, for the zero eigenvalue of to be non-degenerate at second order perturbation in g, we assume the coupling satisfies the assumption.
Coup:
The linear map
4.29 |
where stands here (resp. ) if (resp. ), is such that .
Remark 4.2
Assumption Coup is equivalent to the statement
exists on the dimension subspace .
Indeed, both statements entail , and the corresponding spectral projector onto , say , is such that , and .
As a consequence,
Theorem 4.3
Consider the coupled QRM defined on by
4.30 |
and assume Spec() if or Spec() if . Then for , |g| small enough, if Coup holds.
Remark 4.4
Under assumption Spec(), the non-zero eigenvalues of are all simple, of the form with associated eigenvector , , and corresponding eigenprojector
4.31 |
The next order correction, given by the eigenvalue of the operator , reads
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 , as . We first discuss the richer case and then describe the modifications required for the case .
Let be the spectral projector of given by (4.9), and . We have accordingly
4.33 |
where , and . Since the spectrum of is a positive distance away from the imaginary axis, uniformly in g small enough, functional calculus yields the existence of , independent of g, such that
4.34 |
where is uniform in g, since is analytic in g. Now, by (4.19)
4.35 |
where, for under assumption Spec(),
4.36 |
with simple non zero eigenvalues, see Remark 4.4. In case under hypothesis Spec(), by Lemma 4.1, so that (4.36) holds with and .
Since (and even in case ), the long time behaviour of 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 that vanish as g goes to zero.
Proposition 4.5
Assuming , Spec() and Coup, there exists such that for all , admits analytic spectral projector and and analytic simple eigenvalues such that
4.37 |
Here , and , see (4.32).
Assuming , Spec() and Coup, the same statement holds with and , in (4.37).
Moreover, assuming Coup and Spec(), (respectively Spec()), if , (respectively ), we have and the corresponding spectral projector is analytic for , and satisfies
4.38 |
Here
4.39 |
and where is the projector on .
Remark 4.6
The spectral constraints on Lindblad operators imply,
4.40 |
We give conditions ensuring in case the model has no leading order Hamiltonian drive, , that we analyse in more details in Sect. 6.
Proof
We consider only, the other case being similar. Thanks to (4.35) and (4.36), perturbation theory applies to and yields the analytic projectors and converging to and respectively, and the analytic simple eigenvalues , such that (4.37) holds. Expanding the first term using , one gets thanks to (4.26)
4.41 |
Assumption Coup implies that has one dimensional kernel, with associated spectral projector we write . Hence, perturbation theory again ensures the existence of an analytic one dimensional spectral projector of corresponding to the simple zero eigenvalue of at . Necessarily, coincides with the spectral projector onto the nontrivial kernel of for all g small enough, which proves (4.38).
Let us turn to the dynamical implications.
Corollary 4.7
Under the hypotheses for above, the following holds for all and g real small enough:
4.42 |
Further assuming , there exists such that for all ,
4.43 |
where the constant in the is uniform in and g small.
Setting , we have
4.44 |
where the constants in all are uniform in , g small.
Under the hypotheses for above, for all and g real small enough,
4.45 |
and there exists such that for all ,
4.46 |
where the constant in the is uniform in and g small. Moreover,
4.47 |
where the constants in all are uniform in , g small.
Remark 4.8
-
0)
The identical statements (4.43) and (4.46) show that is the time scale of the approach to the asymptotic state, as expected.
-
i)
The full evolution can be approximated by the restriction of to , (provided is larger than the absolute value of the real part of the eigenvalues of in case ).
-
ii)
In case , we provide in Sect. 6 an interpretation of the approximate evolution as a classical continuous time Markov process.
-
iii)
Set . When , the explicit term in (4.44) is the leading term if , and for times which satisfy , as , for any . When , 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 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 has a norm which is uniformly bounded in and g small enough, the norm of
4.48 |
is bounded above by a constant which uniform in and g small enough. Thus, by Duhamel formula
4.49 |
applied to subject to (4.40), , we get
4.50 |
Moreover, immediately implies upon expanding ,
4.51 |
where the constants in all are uniform in and g small. Finally,
allows us to express the exponential in terms of that of .
Construction of the Asymptotic State
We now turn to the determination of the state where given by a power series in g
5.1 |
where and , . Expanding , and equating like powers of g we get
5.2 |
The way to solve this set of equations, in principle, is as follows. Note that the spectral decomposition of yields
5.3 |
The first equation is solved by picking a trace one element in , described in Proposition 3.7. The addition of any traceless vector yields an equally good solution for at that order. The next equation amounts to solve for , a traceless matrix. This requires . Since , this is equivalent to , which determines up to the addition of an element of ( viewed as an operator on ). Let us assume for the discussion here that , i.e. . This yields . Again, the addition of any traceless vector to that yields an equally good solution to that equation. The next order requires , which is equivalent to . This equation will then determine completely, under generic hypotheses, as we shall see. Then we proceed by induction.
The case 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 and Theorem 5.4 for .
Again, the inverse of on its range is the reduced resolvent . To express , it is enough to consider the spectral decomposition , where and are the spectral projectors corresponding to Proposition 3.7, while corresponds to the projector .
We consider here that and work under the spectral assumption Spec() on the self-adjoint operator defined by (4.13). We first work out the orders and terms, i.e. and , and then state an abstract result on the full perturbation series in Theorem 5.2.
The first equation yields where is a state. We choose , and with any traceless can be added to that choice so that
5.4 |
Then we compute :
5.5 |
The condition to solve the equation for requires , where extracts the diagonal part of in the normalised eigenbasis of . Thanks to our assumption, we set
5.6 |
which is traceless, since , and self-adjoint if is. Next we look for , which requires , where :
5.7 |
This is equivalent to the equation on
5.8 |
where we note that is arbitrary. Our hypotheses on imply that
5.9 |
5.10 |
Now, assumption Coup on H ensures (5.8) determines and : Separating the diagonal from the offdiagonal parts, we have for the former
5.11 |
which determines fully since , and thus as well. The offdiagonal part yields
5.12 |
which fixes and leaves open for now.
At this point, the formula which defines makes sense,
5.13 |
where depends parametrically on . At order two, the contribution is , where is arbitrary. The term is determined by the requirement that necessary to solve for , i.e.
5.14 |
Splitting this equation into its diagonal and offdiagonal parts, we get, making use of (4.29),
5.15 |
5.16 |
Using assumption Coup under the form: is invertible on the subspace , the first equation determines
5.17 |
so that is determined and therefore the second equation yields
5.18 |
Consequently, we can set
5.19 |
At this point, , are known, as well as , and .
Remark 5.1
The fact that implies , so the assumption that 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 (4.30) with under the assumptions Spec() and Coup. Then there exists such that , the unique invariant state of , admits a convergent expansion
5.20 |
for all with . We have,
5.21 |
5.22 |
for all . Moreover, there exists a linear map such that where
5.23 |
5.24 |
5.25 |
Consequently, for ,
5.26 |
Remark 5.3
-
0)
Replacing and by their expression into (5.25) shows is linear in as well an yields the map .
-
i)Eq. (5.26) is equivalent to
where and are the eigenvalues, eigenprojectors, eigennilpotents and algebraic multiplicities appearing in the spectral decomposition of . Hence the radius of convergence is .5.27 -
ii)
In case , the steady state is well defined for all .
-
iii)
The iteration terminates if and only if has a zero eigenvalue and belongs to the corresponding eigenspace; see Sect. 8 for examples.
-
iv)
The restriction of the invariant state to is given by .
-
v)
We provide necessary and sufficient conditions in Proposition 6.1 for Coup to be satisfied in case and .
Proof
Recall that is proven in Theorem 4.3.
We solve the higher orders equations for of (5.2) with
5.28 |
for all j by induction. Let and assume , are given traceless matrices satisfying (5.28) for as well as
5.29 |
This is the situation we arrived at for . Consider , a necessary condition to compute , which yields
5.30 |
Splitting the equation into its diagonal and offdiagonal parts gives
5.31 |
5.32 |
The first equation determines
5.33 |
so that is fully determined and therefore the second equation yields
5.34 |
Consequently we can define
5.35 |
where remains free, while is determined. This finishes the proof of the induction.
0
We consider here and the necessary modifications to compute the series (5.1) due to the identities
5.36 |
The first equation in (5.2) yields , where is free. The condition to solve the second equation is which is trivially satisfied. Thus, writing with and , we can solve partially the equation setting
5.37 |
The next equation requires . Thanks to and the identity (5.36), this equation reduces to
5.38 |
where we used the expression for and . Thanks to assumption Coup for , this determines since (5.38) is equivalent to
5.39 |
Thus is now determined, while the traceless part is not. With the familiar decomposition with respect to the projector , we set
5.40 |
and turn to the equation for : . It requires , where we used (5.36) and . With (5.40), this is equivalent to
5.41 |
where , since . Thanks to Coup, we can thus determine uniquely in terms of
5.42 |
In turn is fully determined while remains to be computed, and
5.43 |
From there on we can iterate the process to get the equivalent of Theorem 5.2 in the case . The proof being similar and simpler, we omit it.
Theorem 5.4
Consider the QRM Lindbladian (4.30) with under the assumptions Spec() and Coup. Then there exists such that , the unique invariant state of , admits a convergent expansion
5.44 |
for all with . We have,
5.45 |
see (4.29) and (5.39), and for all , with . Moreover, there exists a linear map such that where
5.46 |
5.47 |
Consequently, for ,
5.48 |
Remark 5.5
-
0)
Remarks (i), (ii), (iii) below Theorem 5.2 remain in force here.
-
i)The map can be expressed as
so that5.49 5.50
No Leading order Hamiltonian Drive
We consider here the case where on their respective spaces, so that with and arbitrary, while 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() holds. Recall that denotes the normalized eigenbasis of with respect to which the projectors and are defined, and set . Given the definition (4.29) of , we need to compute for all
6.1 |
Thanks to Proposition 3.4, we can express in a compact way. Let such that , so that . Thus
6.2 |
Therefore, introducing
6.3 |
6.4 |
and making use of , a straightforward computation yields
6.5 |
Then we note using the cyclicity of the trace that
6.6 |
where the operator in the first trace reads
6.7 |
while the second trace yields the jj element of its partial . Hence,
6.8 |
Similar considerations can be made for the traces of the other two operators in (6.5):
6.9 |
and
6.10 |
Defining for the non negative operator by
6.11 |
we eventually obtain
6.12 |
where is viewed as a matrix on , and any diagonal matrix is viewed as a vector of .
We provide a necessary and sufficient condition on the coupling Hamiltonian H in terms of the diagonal matrix elements of h(k), for assumption Coup to hold, i.e. that restricted to diagonal traceless matrices is invertible.
Proposition 6.1
Assume , and consider the non negative operators defined by (6.11). Assumption Coup holds if and only if there exists such that for all .
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 , assumption Coup holds as soon as , while for it is true if for some , , and .
Proof
Within the framework introduced above we identify with its matrix . We need to show it admits zero as a simple eigenvalue, which amounts to showing that .
We use the short hand notations for and to express the matrix elements of . The proof follows once we establish the following Lemma
Lemma 6.3
Consider given by
6.13 |
Then, if and only if such that , .
Remark 6.4
It is possible that and one diagonal element , in which case , where is the canonical basis vector of .
We can associate to a stochastic matrix the elements of which are
6.14 |
such that satisfies iff , where , if for all k. Hence, if , the components of x can all be chosen to be non negative, by Perron Frobenius theorem.
However is not necessarily irreducible as one sees from the example with that admits the non strictly positive eigenvector in its kernel
Proof
We know and by Jacobi’s formula,
6.15 |
where is the comatrix of A and is obtained by deleting the row and column of A. In our case
6.16 |
is real valued so that . Moreover, by definition, for all
6.17 |
so that by Gershgorin Theorem
6.18 |
where the circle centered at of radius intersects the imaginary axis if and only if , in which case the intersection reduces to the origin. Since the determinant of is the product of its complex conjugate eigenvalues, (6.18) yields
6.19 |
Therefore
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. , the evolution semigroup can be approximated by
6.21 |
In the case at hand, is expressed in the orthonormal basis as the matrix (6.12) denoted by in Lemma 6.3. The negative of the transpose of 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 a classical continuous time Markov chain on the state space identified with with , as follows.
Let us recall the general framework. The Markov process is characterised by the probability to find the process in state j at time , given the process at time 0 is in state i, is denoted by
6.22 |
These transition probabilities are solutions to the matrix form forward and backward equations
6.23 |
where is a transition rate matrix such that , and . Hence, with the identification we get the following interpretation
Theorem 6.5
Consider under assumptions Spec() and Coup. Then, the operator arising in the approximation of provided in (4.44), describes a (rescaled) continuous time Markov process on the state space such that for all ,
6.24 |
Remark 6.6
Therefore, for any , the transpose of 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 , which takes into account the effects of the reset matrices.
Finally, let us address the computation of the order corrections (4.32) of the simple eigenvalues of given by
6.25 |
We prove in Appendix that
Proposition 6.7
Consider under assumptions Spec() and Coup. Then, the eigenvalues of , see Proposition 4.5, satisfy
6.26 |
Remark 6.8
Actually, we show that 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
We present here an example where the two parts of the Hilbert space on which the dissipator acts non trivially are both , while the central part , with N arbitrary. The orthonormal bases of , and are denoted respectively by , and . The reset states associated with rates are
7.1 |
where . We consider again a case without leading order Hamiltonian drive, that is , while the order g Hamiltonian reads
7.2 |
In other words,
7.3 |
7.4 |
with , , , and similarly for , introducing , , and .
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 () subject to inter-qubit Coulomb interaction and flip-flop type interaction Hamiltonian.
With these definitions we compute
7.5 |
which yields
7.6 |
We can choose the real parameters so that the generic assumption Spec holds for any choice of .
Leading Order Term
The next step consists in determining the diagonal elements of the nonnegative operators h(k) defined in (6.11), ; more precisely , for . We first compute
7.7 |
7.8 |
Since we do not need the elements , we do not make explicit their contribution, that we generically denote below by , where , . With this convention, we get for the different elements h(k) is made of
7.9 |
Eventually,
7.10 |
The offdiagonal elements , , of the matrix immediately follow: let
7.11 |
Therefore the matrix form (8.17) of the operator reads
7.12 |
where the diagonal elements , , and .
Note that and , while and . Hence, looking at the first row of (7.12), one sees that Coup holds for this model when
7.13 |
or, looking at the last row, when
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 which turns out to be computable explicitly. We have, noting that for ,
7.15 |
The corresponding faithful leading order , i.e. , of the invariant state of the QRM thus reads
7.16 |
Actually, the following more explicit expressions are true. With
7.17 |
we can write
7.18 |
7.19 |
7.20 |
for .
Note in particular the generic nontrivial dependence on j of the populations of (the reduced) leading order of the invariant state. Further remarks are in order:
- For non zero coefficients and , is independent of if
7.21 In case we consider thermal states for on , , such that , with excitation energy . We get that when , while when , which shows that at high temperature, the populations tend to be constant.
Example on
With the previous example considering , we could derive the exact expressions of the map 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 to be in 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 entering . They are interacting through H. The two Hamiltonians are given by
8.1 |
8.2 |
Without loss of generality, we assume the interaction strengths 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 that conserves the number of excitations (set by with ). In the ordered computational basis of the three qubits
8.3 |
the total Hamiltonian reads
8.4 |
This model corresponds exactly to the previous example with and setting:
8.5 |
8.6 |
The ground state for the three qubits is now simply given by and corresponds to in the previous example with . For clarity, we provide the expression of in the form introduced in (7.2)
8.7 |
The two ends (A and B) of the 3-qubit chain are weakly coupled to their own thermal baths at inverse temperatures and with coupling strengths and 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 ( in the following) in the basis :
8.8 |
Note that since the ground state in the C part of the Hilbert space corresponds to , the substitution 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 satisfies generic assumptions.
Generic Assumptions
We first check the assumptions for and H. The condition , is trivially satisfied in this case as the spectrum is simple with . We can then verify with
8.9 |
as defined by Eq. (4.13) . The spectrum with associated eigenvectors is simple whenever and where stand for the ground state populations of the reset states . The identity is only satisfied for zero temperature reservoirs, . Hence we stay in the generic case, . The condition also tells us that a flip-flop interaction Hamiltonian of the form is not sufficient to ensure the required non-degeneracy conditions in the 0-subspace of . We easily verify that the kernel of has dimension if and if .
In the following, we will restrict the derivation of the steady-state solution up to the second order correction assuming no drive, i.e. . Let us note that in two dimensions, there is no loss of generality to consider the reset states and defined as thermal states with respect to and .
Leading Order Solution, No Drive
Under Spec() and Lemma 4.1, the first-order-correction projector in the 0-eigenvalue subspace is fully characterized by the map acting onto , see Eq. (4.25) and Theorem 4.3
8.10 |
In contrast to the previous example, we can compute explicitly here the map and not only . To this end, we consider to be initially in an arbitrary diagonal state (with respect to the eigenbasis of )
8.11 |
Defining the linear form on
8.12 |
we find the matrix to be given by (with respect to the eigenbasis of )
8.13 |
Note that is diagonal, so that for this example we have . In particular
8.14 |
is one dimensional, so that Assumption Coup is satisfied. Then provides the leading order steady-state solution with
8.15 |
Interestingly, the zeroth order solution is the exact solution in the equilibrium situation, i.e. when , the state satisfies for any (or ) an instance of Remark ii) 5.3.
Remark 8.1
In this example, the matrix can also be derived directly from the previous example with , starting from the positive operator h(k):
8.16 |
In the basis , given (8.5), the substitution , and according to (7.12), the matrix reads
8.17 |
whose kernel in this same basis is generated by the two-dimensional vector
8.18 |
Let us note that , 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 , and by (6.24) we need to compute to determine the transition probabilities of the process
8.19 |
The spectral decomposition of in the matrix form (8.17) is easily obtained. Introducing
8.20 |
we have
8.21 |
with eigenvector associated to the non zero eigenvalue proportional to . Hence,
8.22 |
with spectral projectors
8.23 |
Therefore, with ,
8.24 |
In turn this eventually yields the sought for transition probabilities
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 , 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
8.26 |
and
8.27 |
We recall the definitions for convenience
For the first-order correction, we start computing which can be expressed with (acting on or depending on the context) as
8.28 |
We first note that since , the expression for reduces to zero:
8.29 |
Then, it remains to determine to get the first order correction in g. Thanks to (8.29) and using (8.28) for , we compute
8.30 |
Hence, the first order correction is simply given by , and we obtain
8.31 |
We proceed with the second-order correction and compute . The matrix 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
8.32 |
For its off-diagonal elements, we introduce and the coefficient matrices
8.33 |
The matrix can then be written in a compact form
8.34 |
For , we find that it is equal to 0. This leads us to:
8.35 |
with
8.36 |
The solution up to the second-order correction is then given by
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 PR00P2179748 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 , we have with ,
9.1 |
The last term in (9.1) yields the following contribution to , using cyclicity of the trace and ,
9.2 |
Then, using cyclicity of the trace and , we have
9.3 |
Here denotes the jk of the matrix with respect to the basis . Note that the operators in the full traces are non negative, whereas the last term is a priori complex valued.
Similarly,
9.4 |
and the analogous formula holds for the term involving . 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
9.5 |
9.6 |
9.7 |
Remark 9.2
Since
9.8 |
is a non negative operator, we get from (9.1), (9.2) and the Lemma that
9.9 |
which proves Proposition 6.7.
Proof
We prove the first inequality, the others are similar. Let , so that the real part we need to consider reads, see (9.3),
9.10 |
Spelling out the traces we get
9.11 |
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
9.13 |
With and , we rewrite the first four terms of the summand as
9.14 |
since . The remaining terms can reorganised as follows,
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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