
3
that λ2(t|t1)tends to follow Θ(t−t1)λc(t)in the high temper-
ature limit. This can be better seen from Fig. 1(k), where λc(t)
is plotted by the black dotted curve for comparison. These be-
haviors show that, as the electrode temperature increases, the
electron emission approaches a time-dependent Poisson pro-
cess at long times, but the correlations between the emission
events are always preserved at short times. By using a simi-
lar procedure, we find that similar behaviors can also be seen
when the emission is driven by a Lorentzian pulse carrying
two electron charge.
This paper is organized as follows. In Sec. II, we introduce
a procedure to calculate the time-resolved statistics and emis-
sion rates for the electron emission in quantum conductors. In
Sec. III, we demonstrate the procedure by studying the sin-
gle and two electron emissions at zero temperature. The finite
temperature effect is discussed in Sec. IV. We summarize our
results in Sec. V.
II. TIME-RESOLVED STATISTICS OF A QUANTUM
EMITTER
The statistics of the electron emission process can be de-
scribed by two equivalently ways. On one hand, it can be
characterized by n-fold delayed coincidences, which gives the
joint probability that one electron is emitted in each infinites-
imal time interval [ti, ti+dt](with i= 1,2, . . . , n). It can be
expressed as
gn(t1, . . . , tn) = ha†(t1). . . a†(tn)a(tn). . . a(t1)i
− ha†(t1). . . a†(tn)a(tn). . . a(t1)i0,(3)
where a†(t)and a(t)represent the creation and annihilation
operations of electrons, respectively. Here the two angular
brackets h. . . iand h. . . i0denote the quantum-statistical aver-
age over the many-body electron states with and without the
emitted electrons, respectively. In doing so, one excludes the
contribution from the undisturbed Fermi sea [4, 21]. The coin-
cidences functions are just the diagonal part of the Glauber’s
correlation functions [22–27], which can be extracted from
the current correlation measurements [3, 4, 28].
In contrast, the emission process can also be investigated by
real-time electron counting techniques [29–33]. This can be
used to extract the information of electron process in single-
shot experiments. In this case, the emission process can be de-
scribed by recording each individual emission event in a time
trace [See Fig.1(a) for illustration]. This allows us to repre-
sent emission events by random points in a line. One usually
further assumes that two emission events cannot occur exactly
at the same time, i.e., there can only exist at most one emis-
sion event in an arbitrary infinitesimal time interval [t, t +dt].
This assumption has been proved to be valid for typical emis-
sion processes, such as photon emission in quantum optics
and neuronal spike emission in neuroscience [24, 34–36].
The emission process can be characterized by the time-
resolved statistics of these events. For example, it can be char-
acterized by the time-dependent counting statistics Pn(ts, te),
which gives the probability to emit nelectrons in a given
time interval [ts, te]. It can also be described by statistics of
times, such as idle time distribution Π0(ts, te), which gives
the probability that no electron is emitted in the time inter-
val [ts, te]. The WTD can be obtained from Π0(ts, te)by its
second derivative [16]. Note that all these quantities usually
depend on two times tsand te, which can be treated as the
starting and ending times of the electron counting measure-
ments.
It is inconvenient to describe the time-resolved statis-
tics directly in terms of the n-fold delayed coincidences
gn(t1, . . . , tn). In contrast, the exclusive joint probability
density fn(t1, . . . , tn;ts, te)(with n≥1) has been intro-
duced [24, 38]. It gives the joint probability that one electron
is emitted in each infinitesimal time interval [ti, ti+dt](with
i= 1,2, . . . , n and all ti∈[ts, te]), while no other electron
is emitted in the time interval [ts, te]. It has been shown that
fn(t1, . . . , tk;ts, te)can be related to gn(t1, . . . , tn)as
fn(t1, . . . , tn;ts, te) =
+∞
X
k=n
(−1)k−n
(k−n)! Zte
ts
dtn+1... Zte
ts
dtkgk(t1, . . . , tn, tn+1, . . . , tk).(4)
This relation is derived from the definition of
fn(t1, . . . , tn;ts, te)and gn(t1, . . . , tn), which is inde-
pendent on the nature of the emitted particles [24]. So it can
be applied to both Bosons and Fermions.
All the time-resolved statistics can be obtained from
fn(t1, . . . , tn;ts, te)in a direct way. In particular, the FCS
Pn(ts, te)for n≥1can be given as
Pn(ts, te) = 1
n!Zte
ts
dt1· · · Zte
ts
dtnfn(t1, t2, . . . , tn;ts, te).
(5)
For n= 0, the corresponding FCS P0(ts, te), or equivalently
the idle time distribution Π0(ts, te), can be obtained via the
normalization relation
Π0(ts, te) = P0(ts, te)=1−
+∞
X
n=1
Pn(ts, te).(6)
Comparing to the FCS, the exclusive joint probability den-
sities fn(t1, . . . , tn;ts, te)contain much detailed informa-
tion on the emission process. In particular, one can ex-
tract the emission rate of each individual electron from them
[36, 38, 39]. This can be better understood by starting from
a stationary Poisson process with emission rate λ0. In this