IA Scholar Query: Minimum Relative Entropy for Quantum Estimation: Feasibility and General Solution.
https://scholar.archive.org/
Internet Archive Scholar query results feedeninfo@archive.orgWed, 28 Sep 2022 00:00:00 GMTfatcat-scholarhttps://scholar.archive.org/help1440Techniques for combining fast local decoders with global decoders under circuit-level noise
https://scholar.archive.org/work/h7z4krmvibe6pkf4bjmndwpvfu
Implementing algorithms on a fault-tolerant quantum computer will require fast decoding throughput and latency times to prevent an exponential increase in buffer times between the applications of gates. In this work we begin by quantifying these requirements. We then introduce the construction of local neural network (NN) decoders using three-dimensional convolutions. These local decoders are adapted to circuit-level noise and can be applied to surface code volumes of arbitrary size. Their application removes errors arising from a certain number of faults, which serves to substantially reduce the syndrome density. Remaining errors can then be corrected by a global decoder, such as Blossom or Union Find, with their implementation significantly accelerated due to the reduced syndrome density. However, in the circuit-level setting, the corrections applied by the local decoder introduce many vertical pairs of highlighted vertices. To obtain a low syndrome density in the presence of vertical pairs, we consider a strategy of performing a syndrome collapse which removes many vertical pairs and reduces the size of the decoding graph used by the global decoder. We also consider a strategy of performing a vertical cleanup, which consists of removing all local vertical pairs prior to implementing the global decoder. Lastly, we estimate the cost of implementing our local decoders on Field Programmable Gate Arrays (FPGAs).Christopher Chamberland and Luis Goncalves and Prasahnt Sivarajah and Eric Peterson and Sebastian Grimbergwork_h7z4krmvibe6pkf4bjmndwpvfuWed, 28 Sep 2022 00:00:00 GMTThermal Transport Properties of Diamond Phonons by Electric Field
https://scholar.archive.org/work/eayhmpyscbgstfxjgx6mgyvf4a
For the preparation of diamond heat sinks with ultra-high thermal conductivity by Chemical Vapor Deposition (CVD) technology, the influence of diamond growth direction and electric field on thermal conductivity is worth exploring. In this work, the phonon and thermal transport properties of diamond in three crystal orientation groups (<100>, <110>, and <111>) were investigated using first-principles calculations by electric field. The results show that the response of the diamond in the three-crystal orientation groups presented an obvious anisotropy under positive and negative electric fields. The electric field can break the symmetry of the diamond lattice, causing the electron density around the C atoms to be segregated with the direction of the electric field. Then the phonon spectrum and the thermodynamic properties of diamond were changed. At the same time, due to the coupling relationship between electrons and phonons, the electric field can affect the phonon group velocity, phonon mean free path, phonon–phonon interaction strength and phonon lifetime of the diamond. In the crystal orientation [111], when the electric field strength is ±0.004 a.u., the thermal conductivity is 2654 and 1283 , respectively. The main reason for the change in the thermal conductivity of the diamond lattice caused by the electric field is that the electric field has an acceleration effect on the extranuclear electrons of the C atoms in the diamond. Due to the coupling relationship between the electrons and the phonons, the thermodynamic and phonon properties of the diamond change.Yongsheng Zhao, Fengyun Yan, Xue Liu, Hongfeng Ma, Zhenyu Zhang, Aisheng Jiaowork_eayhmpyscbgstfxjgx6mgyvf4aWed, 28 Sep 2022 00:00:00 GMTArtificial Intelligence and Advanced Materials
https://scholar.archive.org/work/tkf566mg6zf77a7xan6anloxvu
Artificial intelligence is gaining strength and materials science can both contribute to and profit from it. In a simultaneous progress race, new materials, systems and processes can be devised and optimized thanks to machine learning techniques and such progress can be turned into in-novative computing platforms. Future materials scientists will profit from understanding how machine learning can boost the conception of advanced materials. This review covers aspects of computation from the fundamentals to directions taken and repercussions produced by compu-tation to account for the origins, procedures and applications of artificial intelligence. Machine learning and its methods are reviewed to provide basic knowledge on its implementation and its potential. The materials and systems used to implement artificial intelligence with electric charges are finding serious competition from other information carrying and processing agents. The impact these techniques are having on the inception of new advanced materials is so deep that a new paradigm is developing where implicit knowledge is being mined to conceive materi-als and systems for functions instead of finding applications to found materials. How far this trend can be carried is hard to fathom as exemplified by the power to discover unheard of mate-rials or physical laws buried in data.Cefe Lópezwork_tkf566mg6zf77a7xan6anloxvuWed, 28 Sep 2022 00:00:00 GMTQuantum and classical correlations in open quantum-spin lattices via truncated-cumulant trajectories
https://scholar.archive.org/work/zi3cn3r3avbhrif4is4djnyonm
The study of quantum many-body physics in Liouvillian open quantum systems becomes increasingly important with the recent progress in experimental control on dissipative systems and their technological exploitation . A central question in open quantum systems concerns the fate of quantum correlations, and the possibility of controlling them by engineering the competition between the Hamiltonian dynamics and the coupling to a bath. Such a question is challenging from a theoretical point of view, as numerical methods faithfully accounting for quantum correlations are either relying on exact diagonalization, limiting drastically the sizes that can be treated; or on approximations on the range or strength of quantum correlations, associated to the choice of a specific Ansatz for the density matrix. In this work we propose a new method to treat open quantum-spin lattices, based on stochastic quantum trajectories for the solution of the open-system dynamics. Along each trajectory, the hierarchy of equations of motion for many-point spin-spin correlators is truncated to a given finite order, assuming that multivariate k-th order cumulants vanish for k exceeding a cutoff k_c. This allows tracking the evolution of quantum spin-spin correlations up to order k_c for all length scales. We validate this approach in the paradigmatic case of the phase transitions of the dissipative 2D XYZ lattice, subject to spontaneous decay. We convincingly assess the existence of steady-state phase transitions from paramagnetic to ferromagnetic, and back to paramagnetic, upon increasing one of the Hamiltonian couplings; as well as their classical Ising nature. Moreover, the approach allows us to show the presence of significant quantum correlations in the vicinity of the dissipative critical point, and to unveil the presence of spin squeezing, a tight lower bound to the quantum Fisher information.Wouter Verstraelen and Dolf Huybrechts and Tommaso Roscilde and Michiel Wouterswork_zi3cn3r3avbhrif4is4djnyonmTue, 27 Sep 2022 00:00:00 GMTInflationary phenomenology of quadratic gravity in the Palatini formulation
https://scholar.archive.org/work/quaon6ge45evvaaglpa5fvs3zm
Angelos Lykkas, University Of Ioanninawork_quaon6ge45evvaaglpa5fvs3zmMon, 26 Sep 2022 00:00:00 GMTSearches for Baryon Number Violation in Neutrino Experiments: A White Paper
https://scholar.archive.org/work/bhmjnik2q5bf5efqlfbzqxmtda
Baryon number conservation is not guaranteed by any fundamental symmetry within the Standard Model, and therefore has been a subject of experimental and theoretical scrutiny for decades. So far, no evidence for baryon number violation has been observed. Large underground detectors have long been used for both neutrino detection and searches for baryon number violating processes. The next generation of large neutrino detectors will seek to improve upon the limits set by past and current experiments and will cover a range of lifetimes predicted by several Grand Unified Theories. In this White Paper, we summarize theoretical motivations and experimental aspects of searches for baryon number violation in neutrino experiments.P. S. B. Dev, L. W. Koerner, S. Saad, S. Antusch, M. Askins, K. S. Babu, J. L. Barrow, J. Chakrabortty, A. de Gouvêa, Z. Djurcic, S. Girmohanta, I. Gogoladze, M. C. Goodman, A. Higuera, D. Kalra, G. Karagiorgi, E. Kearns, V. A. Kudryavtsev, T. Kutter, J. P. Ochoa-Ricoux, M. Malinský, D. A. Martinez Caicedo, R. N. Mohapatra, P. Nath, S. Nussinov, V. Pec, A. Rafique, J. Rodriguez Rondon, R. Shrock, H. W. Sobel, T. Stokes, M. Strait, R. Svoboda, S. Syritsyn, V. Takhistov, Y.-T. Tsai, R. A. Wendell, Y.-L. Zhouwork_bhmjnik2q5bf5efqlfbzqxmtdaMon, 26 Sep 2022 00:00:00 GMTEnhanced Gravitational Entanglement in Modulated Optomechanics
https://scholar.archive.org/work/i5u77sscfzdvnkb55w3c77pfta
The role of entanglement in determining the non-classicality of a given interaction has gained significant traction over the last few years. In particular, as the basis for new experimental proposals to test the quantum nature of the gravitational field. Here we show that the rate of gravity mediated entanglement between two otherwise isolated optomechanical systems can be significantly increased by modulating the optomechanical coupling. This is most pronounced for low mass, high frequency systems - convenient for reaching the quantum regime - and can lead to improvements of several orders of magnitude, as well as a broadening of the measurement window. Nevertheless, significant obstacles still remain. In particular, we find that modulations increase decoherence effects at the same rate as the entanglement improvements. This adds to the growing evidence that the constraint on noise (acting on the position d.o.f) depends only on the particle mass, separation, and temperature of the environment and cannot be improved by novel quantum control. Finally, we highlight the close connection between the observation of quantum correlations and the limits of measurement precision derived via the Cram\'er-Rao Bound. An immediate consequence is that probing superpositions of the gravitational field places similar demands on detector sensitivity as entanglement verification.A. Douglas K. Plato, Dennis Rätzel, Chuanqi Wanwork_i5u77sscfzdvnkb55w3c77pftaMon, 26 Sep 2022 00:00:00 GMTQuantum capacity and codes for the bosonic loss-dephasing channel
https://scholar.archive.org/work/pxr54n2hmffolk7edrueudrn54
Bosonic qubits encoded in continuous-variable systems provide a promising alternative to two-level qubits for quantum computation and communication. So far, photon loss has been the dominant source of errors in bosonic qubits, but the significant reduction of photon loss in recent bosonic qubit experiments suggests that dephasing errors should also be considered. However, a detailed understanding of the combined photon loss and dephasing channel is lacking. Here, we show that, unlike its constituent parts, the combined loss-dephasing channel is non-degradable, pointing towards a richer structure of this channel. We provide bounds for the capacity of the loss-dephasing channel and use numerical optimization to find optimal single-mode codes for a wide range of error rates.Peter Leviant, Qian Xu, Liang Jiang, Serge Rosenblumwork_pxr54n2hmffolk7edrueudrn54Sat, 24 Sep 2022 00:00:00 GMTAdvances in Chip-Based Quantum Key Distribution
https://scholar.archive.org/work/lok2tk7r2fcz3msemezmyu6r4i
Quantum key distribution (QKD), guaranteed by the principles of quantum mechanics, is one of the most promising solutions for the future of secure communication. Integrated quantum photonics provides a stable, compact, and robust platform for the implementation of complex photonic circuits amenable to mass manufacture, and also allows for the generation, detection, and processing of quantum states of light at a growing system's scale, functionality, and complexity. Integrated quantum photonics provides a compelling technology for the integration of QKD systems. In this review, we summarize the advances in integrated QKD systems, including integrated photon sources, detectors, and encoding and decoding components for QKD implements. Complete demonstrations of various QKD schemes based on integrated photonic chips are also discussed.Qiang Liu, Yinming Huang, Yongqiang Du, Zhengeng Zhao, Minming Geng, Zhenrong Zhang, Kejin Weiwork_lok2tk7r2fcz3msemezmyu6r4iThu, 22 Sep 2022 00:00:00 GMTGeneration of gravitational waves in dynamical Chern-Simons gravity
https://scholar.archive.org/work/lpnn4d6cpngbrfqarn4fxnxunq
We investigate gravitational waves (GWs) generated in a two-field inflationary model with a non-canonical kinetic term, in which the gravitational Chern-Simons term is coupled to a heavy dynamical field. In such a model, primordial GWs experience a period of resonant amplification for some modes. In addition, isocurvature perturbations suffer from a temporary tachyonic instability due to an effective negative mass, which source curvature perturbations, resulting in large induced GWs. These two stochastic gravitational wave backgrounds correspond to different frequency bands, which are expected to be detected by future GW detectors such as SKA, LISA and Taiji.Zhi-Zhang Peng, Zhen-Min Zeng, Chengjie Fu, Zong-Kuan Guowork_lpnn4d6cpngbrfqarn4fxnxunqWed, 21 Sep 2022 00:00:00 GMTIteration Complexity of Variational Quantum Algorithms
https://scholar.archive.org/work/vahtqlq57vdslgk77vokbxhile
There has been much recent interest in near-term applications of quantum computers. Variational quantum algorithms (VQA), wherein an optimization algorithm implemented on a classical computer evaluates a parametrized quantum circuit as an objective function, are a leading framework in this space. In this paper, we analyze the iteration complexity of VQA, that is, the number of steps VQA required until the iterates satisfy a surrogate measure of optimality. We argue that although VQA procedures incorporate algorithms that can, in the idealized case, be modeled as classic procedures in the optimization literature, the particular nature of noise in near-term devices invalidates the claim of applicability of off-the-shelf analyses of these algorithms. Specifically, the form of the noise makes the evaluations of the objective function via circuits biased, necessitating the perspective of convergence analysis of variants of these classical optimization procedures, wherein the evaluations exhibit systematic bias. We apply our reasoning to the most often used procedures, including SPSA the parameter shift rule, which can be seen as zeroth-order, or derivative-free, optimization algorithms with biased function evaluations. We show that the asymptotic rate of convergence is unaffected by the bias, but the level of bias contributes unfavorably to both the constant therein, and the asymptotic distance to stationarity.Vyacheslav Kungurtsev and Georgios Korpas and Jakub Marecek and Elton Yechao Zhuwork_vahtqlq57vdslgk77vokbxhileWed, 21 Sep 2022 00:00:00 GMTCocrystals and Drug–Drug Cocrystals of Anticancer Drugs: A Perception towards Screening Techniques, Preparation, and Enhancement of Drug Properties
https://scholar.archive.org/work/ffxqug3kpre57ce3nh42n2zt3i
The most favored approach for drug administration is the oral route. Several anticancer drugs come under this category and mostly lack solubility and oral bioavailability, which are the most common causes of inadequate clinical efficiency. Enhancing oral absorption of anticancer drugs with low aqueous solubility and drug impermeability is currently an effective area of research. Many scientists have looked into pharmaceutical cocrystals as a way to improve the physicochemical properties of several anticancer drugs. Benefits of pharmaceutical cocrystals over other solid forms may include improved solubility, bioavailability, and a reduced susceptibility for phase transition. Cocrystal strategy also stands as a green synthesis tool by using very limited organic solvents during its formulation. Having so many advantages, to date, the reported cocrystals and drug–drug cocrystals of anticancer drugs are limited. Here we review the pharmaceutical cocrystals and drug–drug cocrystals of the anticancer drugs reported in the last decade and their future in imaging, and also shed light on the opportunities and challenges for the development of anticancer drug cocrystals.Divya Dhatri Kara, Mahalaxmi Rathnanandwork_ffxqug3kpre57ce3nh42n2zt3iWed, 21 Sep 2022 00:00:00 GMTGeometric Brownian Information Engine: Essentials for the best performance
https://scholar.archive.org/work/ykyugnt7qvfifnxn2ts7uk2gqy
We investigate a Geometric Brownian Information Engine (GBIE) in the presence of an error-free feedback controller that transforms the information gathered on the state of Brownian particles entrapped in monolobal geometric confinement into extractable work. Outcomes of the information engine depend on the reference measurement distance x_m, feedback site x_f and the transverse force G. We determine the benchmarks for utilizing the available information in an output work and the optimum operating requisites for best work extraction. Transverse bias force (G) tunes the entropic contribution in the effective potential and hence the standard deviation (σ) of the equilibrium marginal probability distribution. We recognize that the amount of extracted work reaches a global maximum when x_f = 2x_m with x_m ∼ 0.6σ, irrespective of the extent of the entropic limitation. Because of the higher loss of information during the relaxation process, the best achievable work of a GBIE is lower in an entropic system. The feedback regulation also bears the unidirectional passage of particles. The average displacement increases with growing entropic control and is maximum when x_m ∼ 0.81σ. Finally, we explore the efficacy of the information engine, a quantity that regulates the efficiency in utilizing the information acquired. With x_f=2x_m, the maximum efficacy reduces with increasing entropic control and shows a cross over from 2 to 11/9. We discover that the condition for the best efficacy depends only on the confinement length scale along the feedback direction. The broader marginal probability distribution accredits the increased average displacement in a cycle and the lower efficacy in an entropy-dominated system.Rafna Rafeek, Syed Yunus Ali, Debasish Mondalwork_ykyugnt7qvfifnxn2ts7uk2gqyMon, 19 Sep 2022 00:00:00 GMTProgress on stochastic analytic continuation of quantum Monte Carlo data
https://scholar.archive.org/work/eahyejzztbcajetpcbh2qid6c4
We report multipronged progress on the stochastic averaging approach to numerical analytic continuation of quantum Monte Carlo data. With the sampled spectrum parametrized with delta-functions in continuous frequency space, a calculation of the configurational entropy lends support to a simple goodness-of-fit criterion for the optimal sampling temperature. To further investigate entropic effects, we compare spectra sampled in continuous frequency with results of amplitudes sampled on a fixed frequency grid. We demonstrate equivalences between sampling and optimizing spectral functions with the maximum-entropy approach with different forms of the entropy. These insights revise prevailing notions of the maximum-entropy method and its relationship to stochastic analytic continuation. We further explore various adjustable (optimized) constraints that allow sharp spectral features to be resolved, in particular at the lower frequency edge. The constraints, e.g., the location of the edge or the spectral weight of a quasi-particle peak, are optimized using a statistical criterion. We show that this method can correctly reproduce both narrow and broad quasi-particle peaks. We next introduce a parametrization for more intricate spectral functions with sharp edges, e.g., power-law singularities. Tests with synthetic data as well as with real simulation data for the spin-1/2 Heisenberg chain demonstrate that constrained sampling methods can reproduce spectral functions with sharp edge features at unprecedented fidelity. We present new results for S=1/2 Heisenberg 2-leg and 3-leg ladders to illustrate the ability of the methods to resolve spectral features arising from both elementary and composite excitations. Finally, we also propose how the methods developed here could be used as "pre processors" for analytic continuation by machine learning.Hui Shao, Anders W. Sandvikwork_eahyejzztbcajetpcbh2qid6c4Mon, 19 Sep 2022 00:00:00 GMTQuantum Annealing for Neural Network optimization problems: a new approach via Tensor Network simulations
https://scholar.archive.org/work/n3ijfwdr4vgmzfc3n2miwabvcy
Quantum Annealing (QA) is one of the most promising frameworks for quantum optimization. Here, we focus on the problem of minimizing complex classical cost functions associated with prototypical discrete neural networks, specifically the paradigmatic Hopfield model and binary perceptron. We show that the adiabatic time evolution of QA can be efficiently represented as a suitable Tensor Network. This representation allows for simple classical simulations, well-beyond small sizes amenable to exact diagonalization techniques. We show that the optimized state, expressed as a Matrix Product State (MPS), can be recast into a Quantum Circuit, whose depth scales only linearly with the system size and quadratically with the MPS bond dimension. This may represent a valuable starting point allowing for further circuit optimization on near-term quantum devices.Guglielmo Lami, Pietro Torta, Giuseppe E. Santoro, Mario Collurawork_n3ijfwdr4vgmzfc3n2miwabvcySat, 17 Sep 2022 00:00:00 GMTDeep learning of quantum entanglement from incomplete measurements
https://scholar.archive.org/work/lzswcbslw5aufjxqqumiextid4
The quantification of the entanglement present in a physical system is of paramount importance for fundamental research and many cutting-edge applications. Currently, achieving this goal requires either a priori knowledge on the system or very demanding experimental procedures such as full state tomography or collective measurements. Here, we demonstrate that by employing neural networks we can quantify the degree of entanglement without needing to know the full description of the quantum state. Our method allows for direct quantification of the quantum correlations using an incomplete set of local measurements. Despite using undersampled measurements, we achieve an estimation error of up to an order of magnitude lower than the state-of-the-art quantum tomography. Furthermore, we achieve this result employing networks trained using exclusively simulated data. Finally, we derive a method based on a convolutional network input that can accept data from various measurement scenarios and perform, to some extent, independently of the measurement device.Dominik Koutný, Laia Ginés, Magdalena Moczała-Dusanowska, Sven Höfling, Christian Schneider, Ana Predojević, Miroslav Ježekwork_lzswcbslw5aufjxqqumiextid4Fri, 16 Sep 2022 00:00:00 GMTImpact of large-mass constraints on the properties of neutron stars
https://scholar.archive.org/work/hcnzqxckgbe7xkvn5smuwl42c4
The maximum mass of a nonrotating neutron star, M_ TOV, plays a very important role in deciphering the structure and composition of neutron stars and in revealing the equation of state (EOS) of nuclear matter. Although with a large-error bar, the recent mass estimate for the black-widow binary pulsar PSR J0952-0607, i.e. M=2.35±0.17 M_⊙, provides the strongest lower bound on M_ TOV and suggests that neutron stars with very large masses can in principle be observed. Adopting an agnostic modelling of the EOS, we study the impact that large masses have on the neutron-star properties. In particular, we show that assuming M_ TOV≳ 2.35 M_⊙ constrains tightly the behaviour of the pressure as a function of the energy density and moves the lower bounds for the stellar radii to values that are significantly larger than those constrained by the NICER measurements, rendering the latter ineffective in constraining the EOS. We also provide updated analytic expressions for the lower bound on the binary tidal deformability in terms of the chirp mass and show how larger bounds on M_ TOV lead to tighter constraints for this quantity. In addition, we point out a novel quasi-universal relation for the pressure profile inside neutron stars that is only weakly dependent from the EOS and the maximum-mass constraint. Finally, we study how the sound speed and the conformal anomaly are distributed inside neutron stars and show how these quantities depend on the imposed maximum-mass constraints.Christian Ecker, Luciano Rezzollawork_hcnzqxckgbe7xkvn5smuwl42c4Fri, 16 Sep 2022 00:00:00 GMTMajorana Zero Modes in Fermionic Wires coupled by Aharonov-Bohm Cages
https://scholar.archive.org/work/4sg3ssuvzzfg7hzljbtcpkwvz4
We devise a number-conserving scheme for the realization of Majorana Zero Modes in an interacting fermionic ladder coupled by Aharonov-Bohm cages. The latter provide an efficient mechanism to cancel single-particle hopping by destructive interference. The crucial parity symmetry in each wire is thus encoded in the geometry of the setup, in particular, its translation invariance. A generic nearest-neighbor interaction generates the desired correlated hopping of pairs. We exhibit the presence of an extended topological region in parameter space, first in a simplified effective model via bosonization techniques, and subsequently in a larger parameter regime with matrix-product-states numerical simulations. We demonstrate the adiabatic connection to previous models, including exactly-solvable ones, and we briefly comment on possible experimental realizations in synthetic quantum platforms, like cold atomic samples.Niklas Tausendpfund, Sebastian Diehl, Matteo Rizziwork_4sg3ssuvzzfg7hzljbtcpkwvz4Fri, 16 Sep 2022 00:00:00 GMTAdvances in honeycomb layered oxides: Part II – Theoretical advances in the characterisation of honeycomb layered oxides with optimised lattices of cations
https://scholar.archive.org/work/dknl5fqwxzcv3l3n4f5xuk2roa
The quest for a successful condensed matter theory that incorporates diffusion of cations, whose trajectories are restricted to a honeycomb/hexagonal pattern prevalent in honeycomb layered materials is ongoing, with the recent progress discussed herein focusing on symmetries, topological aspects and phase transition descriptions of the theory. Such a theory is expected to differ both qualitatively and quantitatively from 2D electron theory on static carbon lattices, by virtue of the dynamical nature of diffusing cations within lattices in honeycomb layered materials. Herein, we have focused on recent theoretical progress in the characterisation of pnictogen- and chalcogen-based honeycomb layered oxides with emphasis on hexagonal/honeycomb lattices of cations. Particularly, we discuss the link between Liouville conformal field theory to expected experimental results characterising the optimal nature of the honeycomb/hexagonal lattices in congruent sphere packing problems. The diffusion and topological aspects are captured by an idealised model, which successfully incorporates the duality between the theory of cations and their vacancies. Moreover, the rather intriguing experimental result that a wide class of silver-based layered materials form stable Ag bilayers, each comprising a pair of triangular sub-lattices, suggests a bifurcation mechanism for the Ag triangular sub-lattices, which ultimately requires conformal symmetry breaking within the context of the idealised model, resulting in a cation monolayer-bilayer phase transition. Other relevant experimental, theoretical and computational techniques applicable to the characterisation of honeycomb layered materials have been availed for completeness.Godwill Mbiti Kanyolo, Titus Masesework_dknl5fqwxzcv3l3n4f5xuk2roaThu, 15 Sep 2022 00:00:00 GMTAutomated design of quantum optical experiments for device-independent quantum key distribution
https://scholar.archive.org/work/cn55cmudonhsrgktjukb4sq6va
Device-independent quantum key distribution (DIQKD) reduces the vulnerability to side-channel attacks of standard QKD protocols by removing the need for characterized quantum devices. The higher security guarantees come however, at the price of a challenging implementation. Here, we tackle the question of the conception of an experiment for implementing DIQKD with photonic devices. We introduce a technique combining reinforcement learning, optimisation algorithm and a custom efficient simulation of quantum optics experiments to automate the design of photonic setups maximizing a given function of the measurement statistics. Applying the algorithm to DIQKD, we get unexpected experimental configurations leading to high key rates and to a high resistance to loss and noise. These configurations might be helpful to facilitate a first implementation of DIQKD with photonic devices and for future developments targeting improved performances.Xavier Valcarce, Pavel Sekatski, Elie Gouzien, Alexey Melnikov, Nicolas Sangouardwork_cn55cmudonhsrgktjukb4sq6vaThu, 15 Sep 2022 00:00:00 GMT