Source: https://www.groundai.com/project/quantum-memristors-in-quantum-photonics/
Timestamp: 2019-04-18 20:24:43+00:00

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We propose a method to build quantum memristors in quantum photonic platforms. We firstly design an effective beam splitter, which is tunable in real-time, by means of a Mach-Zehnder-type array with two equal 50:50 beam splitters and a tunable retarder, which allows us to control its reflectivity. Then, we show that this tunable beam splitter, when equipped with weak measurements and classical feedback, behaves as a quantum memristor. Indeed, in order to prove its quantumness, we show how to codify quantum information in the coherent beams. Moreover, we estimate the memory capability of the quantum memristor. Finally, we show the feasibility of the proposed setup in integrated quantum photonics.
where the state-variable dynamics, encoded in the real-valued function G(μ(t),V(t)), and the state-variable-dependent conductance function F(μ(t))>0, lead to a characteristic pinched hysteresis loop of a memristor when a periodic driving is applied (8) . Memristor technology is currently a promising paradigm to replace in the medium term computing architectures based on transistors for certain specific tasks, because of the low energy consumption (9) . Indeed, they are energetically more efficient (10) , and the presence of memory seems to make them more powerful for key machine learning tasks, such as image recognition (9); (11); (12); (13); (14) .
The quantization of these devices with memory, especially the memristor, is a complicated challenge which has only recently been achieved (15); (16); (17) . The difficulty lies on the fact that it is necessary to engineer an open quantum system whose classical limit corresponds to the general dynamics given by Eqs. (1). This question was addressed in Ref. (15) by replacing the memristor by a tunable resistor, a weak-measurement protocol and classical feedback acting on the system-resistor coupling. It was proven that this system behaves in the classical limit as the dynamics given by Eqs. (1). Additionally, it was proven that the dynamics of this composed system is genuinely quantum and, therefore, might be used for quantum information tasks. Afterwards, an implementation of quantum memristors in superconducting circuits was proposed (16) , making use of the fact that a memristive behavior emerges naturally in the presence of Josephson junctions (18) .
Figure 1: Scheme for a quantum memristor in an optical setup by means of a tunable beam splitter, weak measurements and classical feedback.
However, a memristive behavior can be extended to a more general framework beyond charges and fluxes. Indeed, a memristive behavior is characterized by non-Markovian history-dependent dynamics, which produces the characteristic pinched hysteresis loops when observables of the input and output states are depicted (19); (20) . Additionally, we call these devices quantum memristors when the dynamics cannot be described for all states by means of a classical process. They can be used as building blocks for the simulation of complex non-Markovian quantum dynamics or for an efficient (in terms of resources) codification of quantum machine leaning protocols, mimicking the classical case (9); (11); (12); (13); (14) .
In this Article, we construct the first quantum memristor in quantum photonics, codifying the quantum information into different quantum states of the photons as depicted in Fig. 1. By showing that the fundamental elements which constitute a quantum memristor, namely a tunable dissipative element, weak measurements and classical feedback (15) , can be straightforwardly constructed in quantum photonics, we study the dynamics of different initial quantum states and demonstrate the presence of prototypical hysteresis loops. We also compute the persistence of the memory of these devices.
where the parameters are Θ=π+θ−2ϕT, ΦT=ϕT+π2, and ΦR=ϕR, which is an invertible system. The phase difference between the transmitted and reflected phases is Φ=ΦT−ΦR=ϕT−ϕR+π2=ϕ+π2, which proves Eq. (2). Now that we can construct an in-time tunable beam splitter, let us study the effect on different initial states, analyzing the hysteretical response and the quantum dynamics of such systems.
Figure 2: Two 50:50 beam splitters together with three retarders in a Mach-Zehnder-type array play a role of a beam splitter with arbitrary reflectivity. As the retarder can be straightforwardly in-time controlled, this is suitable for constructing a quantum memristor in quantum photonics.
In our case, we pumped the system with a periodic coherent state fulfilling ⟨xin⟩a1=⟨xmaxin⟩a1cos(ωt). As ⟨xmaxin⟩a1=α∈\mathbbmR, we have that f(θ,⟨xin⟩a1)=⟨xin⟩a1cos2θ2, which may be interpreted as the transmitted intensity per unit of initial displacement. The function g(θ,⟨xin⟩a1), which updates the reflectivity of the beam splitter, can be chosen freely. In our case, for illustrative proposes, we will select a linear behavior of ˙θ=ω0x0⟨xin⟩a1. In Fig. 3, we have depicted the resulting hysteresis loop when plotting ⟨^nout⟩b1 vs ⟨xin⟩a1. As expected, this is a pinched hysteresis loop with an enclosed area decreasing with the frequency of the driving, which shows that this system behaves as a memristor in these variables. As discussed below in detail, this dynamics is deeply related with refractive optical bistability, which makes use of an optical mechanism to change the refractive index inversely to the intensity of the light source (22) , but the classical feedback in our proposal is flexible and we can change the refractive index arbitrarily.
Figure 3: Pinched hysteresis loop in the variables ⟨xin⟩a1 vs ⟨^nout⟩b1 under a periodic driving. The plot corresponds to three different frequencies of the driving, showing that the enclosed area decreases when the frequency increases. This proves that this system behaves as a memristor.
where J2(x) is the Bessel function of second order. This formula is valid for ω≥⟨xmaxin⟩a1ω0x0π, since the curve suffers additional crosses for smaller frequencies and it must be computed more carefully (in fact, if ω<⟨xmaxin⟩a1ω0nx0π, 0<n∈\mathbbmN, each bubble suffers n crossings, generating n+1 sub-loops). For large frequencies, this area decreases polynomially as A∼π⟨xmaxin⟩4a1ω0x0ω+O(ω−3), so the area decays slowly and memristive behavior is resilient for a large window of frequencies, as expected.
The problem with coherent states is that a beam splitter cannot change the entanglement degree of any state codified in them (21) , so the dynamics is essentially classical (23); (24); (25); (26); (27); (28) .
with φ=0, squeezing in the x quadrature. We choose g(θ,⟨x2in⟩b1)=±ω0x0√⟨x20⟩−⟨x2in⟩b1, where the sign is chosen depending on the angle, and drive the squeezing below the vacuum variance, so ⟨x2in⟩b1=12(1−αcos2ωt), with 0<α<1. Hence, θ(t)=θ0+√αω202x20ω2sinωt. The pinched hysteresis loop is depicted in Fig. 4.
Figure 4: Pinched hysteresis loop in the variables ⟨x2vac⟩a1−⟨x2in⟩a1 vs ⟨^nout⟩b1 under a periodic driving. The plot corresponds to three different frequencies of the driving, showing that the enclosed area decreases when the frequency increases. For frequencies ω<√α2ω0nπx0 additional crosses appear generating n+1 sub-loops.
The area can be computed again by using Eq. (4), but in this case, there is no analytical expression. However, the asymptotic expression of the area for large frequencies ω≫1 and strong squeezing α≃1 can be computed as A∼π16√2ω√1−α. Therefore, A vanishes in the high-frequency regime as O(ω−1), which agrees with Fig. 4 and also shows resilience of te memory with the frequency.
The dynamics of the beam splitter is quantum when working with squeezed states, and it cannot be simulated by an equivalent classical dynamics. The final state without updating the reflectivity of the beam splitter is given by ρf=tr2[B(θ,ϕ)S1(ζ)|00⟩⟨00|S†1(ζ)B(θ,ϕ)†] and the quantum information may be codified in continuous variables (30) .
Let us now prove the memristive behavior of this construction. In order to get it, we have that the mean value of x in the initial state |Ψ⟩ is given by ⟨xin⟩a1=1√2sin(2ϕ), while the intensity of light coming out through channel 1 is given by ⟨nout⟩b1=sin2ϕsin2θ2. Straightforwardly, one obtains that ⟨nout⟩b2=sin2ϕcos2θ2. Let us consider the same dynamical equation for the internal variable as in the previous cases ˙θ=g(θ,⟨xin⟩a1)=√2ω0⟨xin⟩a1=ω0sin2ωt. Then, the hysteresis loops generated, which are valid for frequencies ω>ω0(4n−1)π, 0≤n∈N, are depicted in Fig. 5. For lower frequencies n crosses appear, which generates n+1 sub-loops. Differently to the previous cases, the hysteresis loops are not pinched, which means that the memristor is not passive and the energy introduced only vanishes when the initial state is |0⟩. Additionally, this fact also reflects in the fact that the area asymptotically approaches to a constant for high frequencies A∼π4√2+πω08√2ω. This robustness could be a useful resource for quantum information processing.
Figure 5: Non-pinched hysteresis loop in the variables ⟨^nout⟩b1 vs ⟨xin⟩a1 under a periodic driving. The plot corresponds to three different frequencies of the driving, showing that the enclosed area approaches to a constant value A∼π4√2 for high frequencies. For frequencies ω<ω0(4n−1)π, 0<n∈\mathbbmN, n additional crosses of the loop appear.
Let us study the final state in channel 1 when we measure projectively the number of photons in channel 2 given by Eq. (6). If we measure Fock state |1⟩, then the final state in channel 1 is simply |0⟩. Otherwise, if we measure Fock state |0⟩ in channel 2, the final state in channel 1 is eiαcosϕ√1−sin2ϕsin2θ2|0⟩+isinϕeiθ2sinθ2√1−sin2ϕsin2θ2|1⟩, which means that the amplitudes of the initial qubit may be modified by means of the reflectivity of the beam splitter.
Therefore, this is a natural candidate to be considered for (digital qubit-based) quantum information processing, by creating multiple copies of the same initial state. A possible relevant application could be the simulation of non-Markovian quantum dynamics by considering quantum feedback and n Fock states in input channel 1 (32) . The reflectivity of the beam splitter should be updated depending on the environment that we want to simulate.
Optical bistability.— Optical bistability is a property of optical devices to show two resonant states, both stable and dependent on the input state. In other words, two different output intensities are possible for a given input intensity, and we need to know the previous states in order to determine which is the right one (non-Markovianity) (22) . This property is characterized by the presence of a hysteresis loop when the output intensity is plotted versus a periodic input intensity. Particularly, refractive bistability makes use of changes in the refractive index of the optical device depending inversely on the intensity of the source light to produce such hysteresis loops with coherent states. This is exactly what we are producing here with different quantum input states, in such a way that the dynamics shows optical bistability / memristive behavior, but must be described quantum mechanically due to the presence of entanglement. Consequently, quantum information and processing may be encoded in this process, combined with the intrinsic memory (non-Markovianity) of the quantum memristor. Indeed, our system shows all the main elements required for the quantum memristor described in Ref. (15) .
Implementation in quantum photonics.— The technology for the implementation of our proposal in photonic quantum technology, as for example integrated quantum photonics, is currently available. Indeed, fully reconfigurable two-qubit gates based on integrated photonic chips have been developed (33) and their basic principles, as dynamically-tunable directional couplers, can be directly applied to produce our basic unit of quantum memristor. Moreover, the ease of fabrication of a wide variety of chip designs will allow for establishing a network of quantum memristors based on photonic-chip technology, which could give rise to scalable neuromorphic quantum computing.
Conclusions.— By using the fundamental elements for the quantization of a memristor, namely a tunable dissipative environment, weak measurements and classical feedback, we have extended the concept of quantum memristor from superconducting circuits to quantum photonics, showing that all these elements are present in current technology. We have studied the dynamics of this photonics quantum memristor with respect to different paradigmatic initial quantum states, showing the prototypical hysteresis loops, computing the corresponding area, and proving that these dynamics are quantum for squeezed states and Fock states. Finally, we have briefly discussed the implementation in integrated quantum photonics. In a long term vision, we expect that these quantum devices can be use as building blocks for quantum machine learning and neural networks (34); (35); (36); (37) and in the simulation of quantum artificial life (38); (39) .
We thank G. Gatti, R. Sweke and F. Flamini for fruitful discussions. This work was supported by Spanish MINECO/FEDER FIS2015-69983-P, Ramón y Cajal Grant RYC-2012-11391, and Basque Government IT986-16.
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