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Register a new userEnergetic Considerations in Quantum Target Ranging
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While quantum illumination (QI) can offer a quantum-enhancement in target detection, its potential for performing target ranging remains unclear. With its capabilities hinging on a joint-measurement between a returning signal and its retained idler, an unknown return time makes a QI-based protocol difficult to realise. This paper outlines a potential QI-based approach to quantum target ranging based on recent developments in multiple quantum hypothesis testing and quantum-enhanced channel position finding (CPF). Applying CPF to time bins, one finds an upper-bound on the error probability for quantum target ranging. However, using energetic considerations, we show that for such a scheme a quantum advantage may not physically be realised.
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Single-photon light detection and ranging (LiDAR) is a key technology for depth imaging through complex environments. Despite recent advances, an open challenge is the ability to isolate the LiDAR signal from other spurious sources including background light and jamming signals. Here we show that a time-resolved coincidence scheme can address these challenges by exploiting spatiotemporal correlations between entangled photon pairs. We demonstrate that a photon-pair-based LiDAR can distill desired depth information in the presence of both synchronous and asynchronous spurious signals without prior knowledge of the scene and the target object. This result enables the development of robust and secure quantum LiDAR systems and paves the way to time-resolved quantum imaging applications.
The validity of the work by Lamata et al [Phys. Rev. Lett. 98, 253005 (2007)] can be further shown by quantum field theory considerations.
We describe a simple multivariate technique of likelihood ratios for improved discrimination of signal and background in multi-dimensional quantum target detection. The technique combines two independent variables, time difference and summed energy, of a photon pair from the spontaneous parametric down-conversion source into an optimal discriminant. The discriminant performance was studied in experimental data and in Monte-Carlo modelling with clear improvement shown compared to previous techniques. As novel detectors become available, we expect this type of multivariate analysis to become increasingly important in multi-dimensional quantum optics.
We quantitatively assess the energetic cost of several well-known control protocols that achieve a finite time adiabatic dynamics, namely counterdiabatic and local counterdiabatic driving, optimal control, and inverse engineering. By employing a cost measure based on the norm of the total driving Hamiltonian, we show that a hierarchy of costs emerges that is dependent on the protocol duration. As case studies we explore the Landau-Zener model, the quantum harmonic oscillator, and the Jaynes-Cummings model and establish that qualitatively similar results hold in all cases. For the analytically tractable Landau-Zener case, we further relate the effectiveness of a control protocol with the spectral features of the new driving Hamiltonians and show that in the case of counterdiabatic driving, it is possible to further minimize the cost by optimizing the ramp.
We have developed a quantum annealing processor, based on an array of tunably coupled rf-SQUID flux qubits, fabricated in a superconducting integrated circuit process [1]. Implementing this type of processor at a scale of 512 qubits and 1472 programmable inter-qubit couplers and operating at ~ 20 mK has required attention to a number of considerations that one may ignore at the smaller scale of a few dozen or so devices. Here we discuss some of these considerations, and the delicate balance necessary for the construction of a practical processor that respects the demanding physical requirements imposed by a quantum algorithm. In particular we will review some of the design trade-offs at play in the floor-planning of the physical layout, driven by the desire to have an algorithmically useful set of inter-qubit couplers, and the simultaneous need to embed programmable control circuitry into the processor fabric. In this context we have developed a new ultra-low power embedded superconducting digital-to-analog flux converters (DACs) used to program the processor with zero static power dissipation, optimized to achieve maximum flux storage density per unit area. The 512 single-stage, 3520 two-stage, and 512 three-stage flux-DACs are controlled with an XYZ addressing scheme requiring 56 wires. Our estimate of on-chip dissipated energy for worst-case reprogramming of the whole processor is ~ 65 fJ. Several chips based on this architecture have been fabricated and operated successfully at our facility, as well as two outside facilities (see for example [2]).
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