Equilibration of quantum chaotic systems

Quantum ergordic theorem for a large class of quantum systems was proved by von Neumann [Z. Phys. {\bf 57}, 30 (1929)] and again by Reimann [Phys. Rev. Lett. {\bf 101}, 190403 (2008)] in a more practical and well-defined form. However, it is not clear whether the theorem applies to quantum chaotic systems. With the rigorous proof still elusive, we illustrate and verify this theorem for quantum chaotic systems with examples. Our numerical results show that a quantum chaotic system with an initial low-entropy state will dynamically relax to a high-entropy state and reach equilibrium. The quantum equilibrium state reached after dynamical relaxation bears a remarkable resemblance to the classical micro-canonical ensemble. However, the fluctuations around equilibrium are distinct: the quantum fluctuations are exponential while the classical fluctuations are Gaussian.Comment: 11 pages, 8 figure

Increase of degeneracy improves the performance of the quantum adiabatic algorithm

We propose a strategy to improve the performance of the quantum adiabatic algorithm (QAA) on an NP-hard (nondeterministic-polynomial-time-hard) problem exact cover, by increasing the ground-state degeneracy of the problem Hamiltonian. Our strategy is based on the empirical finding that for the QAA the difficulty of random instances decreases with the degeneracy of the ground state. We increase the degeneracy by adding extra qubits to form additional clauses. Our numerical results show that on average our strategy can provide an increase in the minimum gap size along the linear interpolation path of Hamiltonian for both easy and difficult instances. The success probability at fixed total evolution time is thus increased.Massachusetts Institute of Technology. Department of Physic

Distributed Quantum Sensing Using Continuous-Variable Multipartite Entanglement

Distributed quantum sensing uses quantum correlations between multiple sensors to enhance the measurement of unknown parameters beyond the limits of unentangled systems. We describe a sensing scheme that uses continuous-variable multipartite entanglement to enhance distributed sensing of field-quadrature displacement. By dividing a squeezed-vacuum state between multiple homodyne-sensor nodes using a lossless beam-splitter array, we obtain a root-mean-square (rms) estimation error that scales inversely with the number of nodes (Heisenberg scaling), whereas the rms error of a distributed sensor that does not exploit entanglement is inversely proportional to the square root of number of nodes (standard quantum limit scaling). Our sensor's scaling advantage is destroyed by loss, but it nevertheless retains an rms-error advantage in settings in which there is moderate loss. Our distributed sensing scheme can be used to calibrate continuous-variable quantum key distribution networks, to perform multiple-sensor cold-atom temperature measurements, and to do distributed interferometric phase sensing.Comment: 7 pages, 3 figure

Quantifying precision loss in local quantum thermometry via diagonal discord

When quantum information is spread over a system through nonclassical correlation, it makes retrieving information by local measurements difficult---making global measurement necessary for optimal parameter estimation. In this paper, we consider temperature estimation of a system in a Gibbs state and quantify the separation between the estimation performance of the global optimal measurement scheme and a greedy local measurement scheme by diagonal quantum discord. In a greedy local scheme, instead of global measurements, one performs sequential local measurement on subsystems, which is potentially enhanced by feed-forward communication. We show that, for finite-dimensional systems, diagonal discord quantifies the difference in the quantum Fisher information quantifying the precision limits for temperature estimation of these two schemes, and we analytically obtain the relation in the high-temperature limit. We further verify this result by employing the examples of spins with Heisenberg's interaction.Comment: 5+4 pages, 4 figures, We thank the referees and editors for helpful opinions. Accepted by Phys. Rev. A (accepted version

Quantum ranging with Gaussian entanglement

It is well known that entanglement can benefit quantum information processing tasks. Quantum illumination, when first proposed, is surprising as entanglement's benefit survives entanglement-breaking noise. Since then, many efforts have been devoted to study quantum sensing in noisy scenarios. The applicability of such schemes, however, is limited to a binary quantum hypothesis testing scenario. In terms of target detection, such schemes interrogate a single polarization-azimuth-elevation-range-Doppler resolution bin at a time, limiting the impact to radar detection. We resolve this binary-hypothesis limitation by proposing a quantum ranging protocol enhanced by entanglement. By formulating a ranging task as a multiary hypothesis testing problem, we show that entanglement enables a 6-dB advantage in the error exponent against the optimal classical scheme. Moreover, the proposed ranging protocol can also be utilized to implement a pulse-position modulated entanglement-assisted communication protocol. Our ranging protocol reveals entanglement's potential in general quantum hypothesis testing tasks and paves the way towards a quantum-ranging radar with a provable quantum advantage.Comment: 5+5 pages, 4 figures, comments are welcomed, typos correcte

Distributed quantum sensing enhanced by continuous-variable error correction

A distributed sensing protocol uses a network of local sensing nodes to estimate a global feature of the network, such as a weighted average of locally detectable parameters. In the noiseless case, continuous-variable (CV) multipartite entanglement shared by the nodes can improve the precision of parameter estimation relative to the precision attainable by a network without shared entanglement; for an entangled protocol, the root mean square estimation error scales like 1/M with the number M of sensing nodes, the so-called Heisenberg scaling, while for protocols without entanglement, the error scales like 1√M. However, in the presence of loss and other noise sources, although multipartite entanglement still has some advantages for sensing displacements and phases, the scaling of the precision with M is less favorable. In this paper, we show that using CV error correction codes can enhance the robustness of sensing protocols against imperfections and reinstate Heisenberg scaling up to moderate values of M. Furthermore, while previous distributed sensing protocols could measure only a single quadrature, we construct a protocol in which both quadratures can be sensed simultaneously. Our work demonstrates the value of CV error correction codes in realistic sensing scenarios

Large-Alphabet Encoding Schemes for Floodlight Quantum Key Distribution

Floodlight quantum key distribution (FL-QKD) uses binary phase-shift keying (BPSK) of multiple optical modes to achieve Gbps secret-key rates (SKRs) at metropolitan-area distances. We show that FL-QKD's SKR can be doubled by using 32-ary PSK.Comment: 2 pages, 2 figure

Entanglement-Enhanced Lidars for Simultaneous Range and Velocity Measurements

Lidar is a well known optical technology for measuring a target's range and radial velocity. We describe two lidar systems that use entanglement between transmitted signals and retained idlers to obtain significant quantum enhancements in simultaneous measurement of these parameters. The first entanglement-enhanced lidar circumvents the Arthurs-Kelly uncertainty relation for simultaneous measurement of range and radial velocity from detection of a single photon returned from the target. This performance presumes there is no extraneous (background) light, but is robust to the roundtrip loss incurred by the signal photons. The second entanglement-enhanced lidar---which requires a lossless, noiseless environment---realizes Heisenberg-limited accuracies for both its range and radial-velocity measurements, i.e., their root-mean-square estimation errors are both proportional to $1/M$ when $M$ signal photons are transmitted. These two lidars derive their entanglement-based enhancements from use of a unitary transformation that takes a signal-idler photon pair with frequencies $\omega_S$ and $\omega_I$ and converts it to a signal-idler photon pair whose frequencies are $(\omega_S + \omega_I)/2$ and $\omega_S-\omega_I$. Insight into how this transformation provides its benefits is provided through an analogy to superdense coding.Comment: 7 pages, 3 figure