In this paper, we investigate the limits of communication over optical on-off-keying channels with 1-D or 2-D crosstalk, where photons are transferable between adjacent time slots or spatial pixels, and the receiver is equipped with single-photon detectors.We observe that high transmission power (measured by the expected number of photons emitted in each signal slot or pixel) may not lead to high information rate; the maximum capacity is typically achieved in a low-photon regime - with about expected 3 to 8 photons received in each signal slot or pixel. Furthermore, we study the selection of slot length for maximizing the channel bandwidth, as the slot length affects the crosstalk probability and hence the channel capacity. It reveals that optimum optical-communication systems do not minimize the level of crosstalk between slots or pixels.
Recently, considerable interest has emerged in quantum states of light fields other than a classical coherent state. One example of such nonclassical quantum states is the number state which features zero uncertainty for the photon number. Because of this unique property, the number states are promising as information bearing lights in direct-detection optical communications. However, if a channel is lossy, the benefit of using the number state is lessened because random photon deletions due to dissipative effect of the channel introduce inherent uncertainty to the photon number measurement at a receiver. Therefore, even in noiseless optical channels, the lossy effect must be taken into account as an important degradation factor which limits the channel performance. In this paper we compute the capacity of lossy photon channels which utilize the number state light under a certain input constraint. For binary and ternary PAM schemes, we obtain the capacity C (Γ) which is subject to the input constraint that the average number of photons per transmitted symbol can not exceed the fixed number Γ.
An expression is derived for the capacity of a noiseless photon channel as a function of bandwidth, carrier frequency, and average signal power. This expression is an extension of a formula derived by Gordon which is applicable in the limit of narrow bandwidth. By comparison of the two results, it is shown that Gordon's formula is highly accurate over a large range of bandwidth, and that significant deviations occur only when the average signal power is extremely small. The derivation is based on a model of transmitting photons at different frequencies, distinguishable to the limit of the Heisenberg principle, which allows distinguishable states to have the same energy. This degeneracy, which in the narrow-band limit is simply related to the time-bandwidth product, plays a role in the (maximum entropy) energy distributions. These distributions are shown to vary from noise-like (where the rms fluctuations exceed the mean value) to Poisson as the time-bandwidth product varies from unity (or nondegenerate) to infinity. For any degeneracy, the distribution is the discrete analog of its continuous (classical) counterpart. For infinite degeneracy, when photon frequencies may take a continuum of values, the channel capacity is achieved for a signal power spectral density which has the same form as the average energy of a quantized oscillator in thermal equilibrium. As a concluding result, it is shown that for a noiseless channel with fixed average power but without any frequency restrictions, there exists an upper bound to channel capacity which is proportional to the square root of the average signal power.
How much classical information can a noisy optical channel carry when both signal energy and preshared entanglement are limited? This work gives an exact capacity frontier for this joint resource problem. It allows one to determine the best asymptotic communication rate, price the benefit of additional entanglement, and distinguish the effect of tolerating errors from that of changing how entanglement is supplied. Exact capacity under two resource constraints The setting is any fixed bosonic Gaussian channel
Φ with finitely many input and output modes. Signal energy is measured by a positive quadratic Hamiltonian
HG=21RTGR, with
G>0 and ground energy
E0;
R collects the canonical quadratures. The budgets satisfy
E≥E0 and
P≥0. For an
n-use code, the mean total signal energy is at most
nE, while the same initially shared maximally entangled state has Schmidt rank
Kn satisfying
logKn≤nP. Thus
P is a strictly supplied entanglement rate. Encoders may be arbitrary joint quantum operations, and decoding may be collective. The classical capacity is
C(E,P)=maxU≥Vphysical21Tr(GU)≤E,SG(V)≤P[SG(ΦU)+SG(V)−SG(ΦcV)]. Here
V is a Gaussian seed covariance,
U is the average-input covariance, and
U−V is the displacement-modulation covariance. A covariance is physical when
V+iΩ/2≥0, where
Ω is the canonical commutation matrix and the vacuum covariance is
I/2. The notation
SG denotes Gaussian von Neumann entropy, and
Φc is the full complementary channel, including any environment purification. All logarithms are natural, so rates are in nats per channel use. This formula replaces optimization over arbitrary quantum block codes by a finite-dimensional covariance optimization. It supplies both an achievable rate and a converse against non-Gaussian, correlated encodings. At
P=0, it also determines the unassisted capacity of general fixed finite-mode Gaussian channels, including channels without a passive decomposition into independent modes. The reduction specifies the exact capacity value; it does not require a closed-form optimizer for every device. Energy and strict entanglement supply respond differently to errors For a fixed allowed average error
0≤ε<1, the exact capacity under the mean-energy constraint is
Cε(E,P)=C(E0+1−εE−E0,P). Allowing failure rescales the mean energy above the ground state, but leaves the strict initial entanglement budget unchanged. The proof uses an exponential strong converse for codes whose inputs obey a hard total-energy cutoff. In a different model, where a readable flag permits random entanglement supply constrained only on average, the work establishes an achievable bound and a strict small-supply advantage for thermal attenuation at positive energy and fixed nonzero error. That comparison identifies the operational importance of the supply rule; it is not a complete capacity characterization of the flagged model. The communication value of entanglement For a thermal attenuator, let
0<η<1 be the transmissivity,
b>0 the output mean photon number for vacuum input, and
N the input mean photon number. Write its capacity as
CN(P), and define
g(N)=(N+1)log(N+1)−NlogN. The gain from entanglement obeys the sharp bound
0≤CN(P)−CN(0)≤1+bηP. For every fixed
N>0, the coefficient
η/(1+b) is attained as the initial right derivative at
P=0. In the low-photon limit, the stronger resource law is
CN(P)−CN(0)=1+bηmin{P,g(N)}+O(N),N↓0. The remainder is uniform over
P≥0 at fixed
η and positive
b. Noise therefore determines the conversion efficiency, while
g(N)∼Nlog(1/N) sets the entanglement scale sufficient for saturation. This uniform limit concerns the entanglement budget, not a simultaneous limit of vanishing thermal noise. Multimode resource allocation and scope A coupled two-mode example demonstrates how the frontier can guide resource allocation. A global resource-price certificate proves that a legal covariance pair exceeds the entire common-passive-frame Gaussian profile hull by at least
10−5 nat per two-mode use at specified budgets. The comparison includes all common passive frames, local squeezing and average-resource mixtures. The mechanism is the freedom to choose different mode allocations for the seed and average input; the benchmark is this precisely defined Gaussian class, rather than all unentangled encodings. The universal scope is the stated family of fixed finite-mode Gaussian channels, positive quadratic signal costs and strict initial maximally entangled Schmidt-rank supply, with unrestricted joint encoding and collective decoding. The model has no feedback or credit for returned entanglement. The capacity frontier and its resource consequences provide a common way to assess optical communication designs under these operational constraints.
The applications of the general formulae of channel capacity developed in the quantum information theory to evaluation of information transmission capacity of optical channel are interesting subjects. In this review paper, we will point out that the formulation based on only classical-quantum channel mapping model may be inadequate when one takes into account a power constraint for noisy channel. To define the power constraint well, we should explicitly consider how quantum states are conveyed through a transmission channel. Basing on such consideration, we calculate a capacity formula for an attenuated noisy optical channel with genreral Gaussian state input; this gives certain progress beyond the example in our former paper.
Free-space optical communication systems potentially gain many dBs over RF systems. There is no upper limit on the theoretically achievable photon efficiency when the system is quantum-noise-limited: a) Intensity modulations plus photon counting can achieve arbitrarily high photon efficiency, but with sub-optimal spectral efficiency. b) Quantum-ideal number states can achieve the ultimate capacity in the limit of perfect transmissivity. Appropriate error correction codes are needed to communicate reliably near the capacity limits. Poisson-modeled noises, detector losses, and atmospheric effects must all be accounted for: a) Theoretical models are used to analyze performance degradations. b) Mitigation strategies derived from this analysis are applied to minimize these degradations.