Abstract: Presents a listing of the editorial board, board of governors, current staff, committee members, and/or society editors for this issue of the publication. PubDate:
2022
Issue No:Vol. 3 (2022)

Authors:
Leonardo Bacciottini;Luciano Lenzini;Enzo Mingozzi;Giuseppe Anastasi;
Pages: 1 - 15 Abstract: In an article published in 2009, Brun et al. proved that in the presence of a “Deutschian” closed timelike curve, one can map $K$ distinct nonorthogonal states (hereafter, input set) to the standard orthonormal basis of a $K$-dimensional state space. To implement this result, the authors proposed a quantum circuit that includes, among SWAP gates, a fixed set of controlled operators (boxes) and an algorithm for determining the unitary transformations carried out by such boxes. To our knowledge, what is still missing to complete the picture is an analysis evaluating the performance of the aforementioned circuit from an engineering perspective. The objective of this article is, therefore, to address this gap through an in-depth simulation analysis, which exploits the approach proposed by Brun et al. in 2017. This approach relies on multiple copies of an input state, multiple iterations of the circuit until a fixed point is (almost) reached. The performance analysis led us to a number of findings. First, the number of iterations is significantly high even if the number of states to be discriminated against is small, such as 2 or 3. Second, we envision that such a number may be shortened as there is plenty of room to improve the unitary transformation acting in the aforementioned controlled boxes. Third, we also revealed a relationship between the number of iterations required to get close to the fixed point and the Chernoff limit of the input set used: the higher the Chernoff bound, the smaller the number of iterations. A comparison, although partial, with another quantum circuit discriminating the nonorthogonal states, proposed by Nareddula et al. in 2018, is carried out and differences are highlighted. PubDate:
2022
Issue No:Vol. 3 (2022)

Authors:
Run-Hua Shi;Yi-Fei Li;
Pages: 1 - 12 Abstract: In this article, we first define a primitive problem of secure multiparty computations, i.e., secure multiparty disjunction (SMD), and present a novel quantum protocol for SMD that can ensure information-theoretical security, i.e., unconditional security. Furthermore, based on the quantum SMD protocol, we design a quantum sealed-bid auction (QSA) scheme without an auctioneer. In the proposed QSA scheme, all bidders can jointly find the winning bidder without the help of an auctioneer while it can perfectly protect the privacy of nonwinning bidders. The proposed quantum SMD protocol and quantum QSA scheme take Bell states as quantum resources and only perform single-particle Pauli operators and two-particle Bell measurements. Finally, we simulate the related quantum protocols in Qiskit and verify the correctness and the feasibility of the proposed protocols. PubDate:
2022
Issue No:Vol. 3 (2022)

Authors:
Vedika Saravanan;Samah M. Saeed;
Pages: 1 - 11 Abstract: Noisy intermediate-scale quantum algorithms, which run on noisy quantum computers, should be carefully designed to boost the output state fidelity. While several compilation approaches have been proposed to minimize circuit errors, they often omit the detailed circuit structure information that does not affect the circuit depth or the gate count. In the presence of spatial variation in the error rate of the quantum gates, adjusting the circuit structure can play a major role in mitigating errors. In this article, we exploit the freedom of gate reordering based on the commutation rules to show the impact of gate error propagation paths on the output state fidelity of the quantum circuit, propose advanced predictive techniques to project the success rate of the circuit, and develop a new compilation phase postquantum circuit mapping to improve its reliability. Our proposed approaches have been validated using a variety of quantum circuits with different success metrics, which are executed on IBM quantum computers. Our results show that rescheduling quantum gates based on their error propagation paths can significantly improve the fidelity of the quantum circuit in the presence of variable gate error rates. PubDate:
2022
Issue No:Vol. 3 (2022)

Authors:
Prashanti Priya Angara;Ulrike Stege;Andrew MacLean;Hausi A. Müller;Tom Markham;
Pages: 1 - 15 Abstract: Quantum computing is aninterdisciplinary field that lies at the intersection of mathematics, quantum physics, and computer science, and finds applications in areas including optimization, machine learning, and simulation of chemical, physical, and biological systems. It has the potential to help solve problems that so far have no satisfying method solving them, and to provide significant speedup to solutions when compared with their best classical approaches. In turn, quantum computing may allow us to solve problems for inputs that so far are deemed practically intractable. With the computational power of quantum computers and the proliferation of quantum development kits, quantum computing is anticipated to become mainstream, and the demand for a skilled workforce in quantum computing is expected to increase significantly. Therefore, quantum computing education is ramping up. This article describes our experiences in designing and delivering quantum computing workshops for youth (Grades 9–12). We introduce students to the world of quantum computing in innovative ways, such as newly designed unplugged activities for teaching basic quantum computing concepts. We also take a programmatic approach and introduce students to the IBM Quantum Experience using Qiskit and Jupyter notebooks. Our contributions are as follows. First, we present creative ways to teach quantum computing to youth with little or no experience in science, technology, engineering, and mathematics areas; second, we discuss diversity and highlight various pathways into quantum computing from quantum software to quantum hardware; and third, we discuss the design and delivery of online and in-person motivational, introductory, and advanced workshops for youth. PubDate:
2022
Issue No:Vol. 3 (2022)

Authors:
Koichi Miyamoto;Kenji Kubo;
Pages: 1 - 25 Abstract: Following the recent great advance of quantum computing technology, there are growing interests in its applications to industries, including finance. In this article, we focus on derivative pricing based on solving the Black–Scholes partial differential equation by the finite-difference method (FDM), which is a suitable approach for some types of derivatives but suffers from the curse of dimensionality, that is, exponential growth of complexity in the case of multiple underlying assets. We propose a quantum algorithm for FDM-based pricing of multi-asset derivative with exponential speedup with respect to dimensionality compared with classical algorithms. The proposed algorithm utilizes the quantum algorithm for solving differential equations, which is based on quantum linear system algorithms. Addressing the specific issue in derivative pricing, that is, extracting the derivative price for the present underlying asset prices from the output state of the quantum algorithm, we present the whole of the calculation process and estimate its complexity. We believe that the proposed method opens the new possibility of accurate and high-speed derivative pricing by quantum computers. PubDate:
2022
Issue No:Vol. 3 (2022)

Authors:
Qing Zhou;Songfeng Lu;
Pages: 1 - 10 Abstract: We propose a Quantum inspired Hash Function using controlled alternate quantum walks with Memory on cycles (QHFM), where the $j$th message bit decides whether to run quantum walk with one-step memory or to run quantum walk with two-step memory at the $j$th time step, and the hash value is calculated from the resulting probability distribution of the walker. Numerical simulation shows that the proposed hash function has near-ideal statistical performance and is at least on a par with the state-of-the-art hash functions based on quantum walks in terms of sensitivity of hash value to message, diffusion and confusion properties, uniform distribution property, and collision resistance property; and theoretical analysis indicates that the time and space complexity of the new scheme are not greater than those of its peers. The good performance of QHFM suggests that quantum walks that differ not only in coin operators but also in memory lengths can be combined to build good hash functions, which, in turn, enriches the construction of controlled alternate quantum walks. PubDate:
2022
Issue No:Vol. 3 (2022)

Authors:
Guangsheng Ma;Hongbo Li;Jiman Zhao;
Pages: 1 - 16 Abstract: This article extends the Radon transform, a classical image-processing tool for fast tomography and denoising, to the quantum computing platform. A new kind of periodic discrete Radon transform (PDRT), called the quantum periodic discrete Radon transform (QPRT), is proposed. The quantum implementation of QPRT based on the amplitude encoding method is exponentially faster than the classical PDRT. We design an efficient quantum image denoising algorithm using QPRT. The simulation results show that QPRT preserves good denoising capability as in the classical PDRT. Also, a quantum algorithm for IDRT is proposed, which can be used for fast line detection. Both the quantum extension of IDRT and the line detection algorithm can provide polynomial speedups over the classical counterparts in certain cases. PubDate:
2022
Issue No:Vol. 3 (2022)

Authors:
Kento Oonishi;Tomoki Tanaka;Shumpei Uno;Takahiko Satoh;Rodney Van Meter;Noboru Kunihiro;
Pages: 1 - 18 Abstract: Control modular addition is a core arithmetic function, and we must consider the computational cost for actual quantum computers to realize efficient implementation. To achieve a low computational cost in a control modular adder, we focus on minimizingKQ (where K is the number of logical qubits required by the algorithm, and Q is the elementary gate step), defined by the product of the number of qubits and the depth of the circuit. In this article, we construct an efficient control modular adder with small KQ by using relative-phase Toffoli gates in two major types of quantum computers: fault-tolerant quantum computers (FTQ) on the logical layer and noisy intermediate-scale quantum computers (NISQ). We give a more efficient construction compared with Van Meter and Itoh’s, based on a carry-lookahead adder. In FTQ, $T$ gates incur heavy cost due to distillation, which fabricates ancilla for running $T$ gates with high accuracy but consumes a lot of especially prepared ancilla qubits and a lot of time. Thus, we must reduce the number of $T$ gates. We propose a new control modular adder that uses only 20% of the number of $T$ gates of the original. Moreover, when we take distillation into consideration, we find that we minimize $text{KQ}_{T}$ (the product of the number of qubits and $T$-depth) by running $Theta (n / sqrt{log n})$ $T$ gates simultaneously. In NISQ, cn-t gates are the major error source. We propose a new control modular adder that uses only 35% of the number of cnot gates of the original. Moreover, we show that the $text{KQ}_{text{CX}}$ (the product of the number of qubits and cnot-depth) of our circuit is 38% of the original. Thus, we realize an efficient control modular adder, improving prospects for the efficient execution of arithmetic in quantum computers. PubDate:
2022
Issue No:Vol. 3 (2022)

Authors:
Ethan T. Wang;
Pages: 1 - 9 Abstract: The benefits of the quantum Monte Carlo algorithm heavily rely on the efficiency of the superposition state preparation. So far, most reported Monte Carlo algorithms use the Grover–Rudolph state preparation method, which is suitable for efficiently integrable distribution functions. Consequently, most reported works are based on log-concave distributions, such as normal distributions. However, non-log-concave distributions still have many uses, such as in financial modeling. Recently, a new method was proposed that does not need integration to calculate the rotation angle for state preparation. However, performing efficient state preparation is still difficult due to the high cost associated with high precision and low error in the calculation for the rotation angle. Many methods of quantum state preparation use polynomial Taylor approximations to reduce the computation cost. However, Taylor approximations do not work well with heavy-tailed distribution functions that are not bounded exponentially. In this article, we present a method of efficient state preparation for heavy-tailed distribution functions. Specifically, we present a quantum gate-level algorithm to prepare quantum superposition states based on the Cauchy distribution, which is a non-log-concave heavy-tailed distribution. Our procedure relies on a piecewise polynomial function instead of a single Taylor approximation to reduce computational cost and increase accuracy. The Cauchy distribution is an even function, so the proposed piecewise polynomial contains only a quadratic term and a constant term to maintain the simplest approximation of an even function. Numerical analysis shows that the required number of subdomains increases linearly as the approximation error decreases exponentially. Furthermore, the computation complexity of the proposed algorithm is independent of the number of subdomains in the quantum implementation of the piecewise function due to quantum parallelism. An -xample of the proposed algorithm based on a simulation conducted in Qiskit is presented to demonstrate its capability to perform state preparation based on the Cauchy distribution. PubDate:
2022
Issue No:Vol. 3 (2022)

Authors:
Chen He;Jiazhen Li;Weiqi Liu;Jinye Peng;Z. Jane Wang;
Pages: 1 - 13 Abstract: In this article, we propose a low-complexity quantum principal component analysis (qPCA) algorithm. Similar to the state-of-the-art qPCA, it achieves dimension reduction by extracting principal components of the data matrix, rather than all components of the data matrix, to quantum registers, so that the samples of measurement required can be reduced considerably. Both our qPCA and Lin’s qPCA are based on quantum singular-value thresholding (QSVT). The key of Lin’s qPCA is to combine QSVT, and modified QSVT is to obtain the superposition of the principal components. The key of our algorithm, however, is to modify QSVT by replacing the rotation-controlled operation of QSVT with the controlled-not operation to obtain the superposition of the principal components. As a result, this small trick makes the circuit much simpler. Particularly, the proposed qPCA requires three phase estimations, while the state-of-the-art qPCA requires five phase estimations. Since the runtime of qPCA mainly comes from phase estimations, the proposed qPCA achieves a runtime of roughly 3/5 of that of the state of the art. We simulate the proposed qPCA on the IBM quantum computing platform, and the simulation result verifies that the proposed qPCA yields the expected quantum state. PubDate:
2022
Issue No:Vol. 3 (2022)

Authors:
Mostafizar Rahman;Goutam Paul;
Pages: 1 - 9 Abstract: This article presents the cost analysis of mounting Grover’s key search attack on the family of KATAN block cipher. Several designs of the reversible quantum circuit of KATAN are proposed. Owing to the National Insitute of Standards and Technology’s (NIST) proposal for postquantum cryptography standardization, the circuits are designed focusing on minimizing the overall depth. We observe that the reversible quantum circuits designed using and gates and $T$-depth one Toffoli gate give more shallow circuits. Grover oracle for KATAN is designed based on the reversible circuits, which are used further to mount Grover’s key search attack on KATAN. The designs are implemented using the software framework ProjectQ, which provides a resource estimation tool to perform an appropriate cost analysis in an automated way. While estimating the resources, NIST’s depth restrictions are also respected. PubDate:
2022
Issue No:Vol. 3 (2022)

Authors:
Xiaoyuan Liu;Anthony Angone;Ruslan Shaydulin;Ilya Safro;Yuri Alexeev;Lukasz Cincio;
Pages: 1 - 20 Abstract: Combinatorial optimization on near-term quantum devices is a promising path to demonstrating quantum advantage. However, the capabilities of these devices are constrained by high noise or error rates. In this article, inspired by the variational quantum eigensolver (VQE), we propose an iterative layer VQE (L-VQE) approach. We present a large-scale numerical study, simulating circuits with up to 40 qubits and 352 parameters, that demonstrates the potential of the proposed approach. We evaluate quantum optimization heuristics on the problem of detecting multiple communities in networks, for which we introduce a novel qubit-frugal formulation. We numerically compare L-VQE with the quantum approximate optimization algorithm (QAOA) and demonstrate that QAOA achieves lower approximation ratios while requiring significantly deeper circuits. We show that L-VQE is more robust to finite sampling errors and has a higher chance of finding the solution as compared with standard VQE approaches. Our simulation results show that L-VQE performs well under realistic hardware noise. PubDate:
2022
Issue No:Vol. 3 (2022)

Authors:
Sayan Mukherjee;
Pages: 1 - 8 Abstract: Graph coloring is a computationally difficult problem, and currently the best known classical algorithm for $k$-coloring of graphs on $n$ vertices has runtimes $Omega (2^n)$ for $kgeq 5$. The list coloring problem asks the following more general question: given a list of available colors for each vertex in a graph, does it admit a proper coloring' We propose a hybrid classical-quantum algorithm based on Grover search 12 to quadratically speed up exhaustive search. Our algorithm loses in complexity to classical ones in specific restricted cases, but improves exhaustive search for cases, where the lists and graphs considered are arbitrary in nature. PubDate:
2022
Issue No:Vol. 3 (2022)

Authors:
Matthew A. Steinberg;Sebastian Feld;Carmen G. Almudever;Michael Marthaler;Jan-Michael Reiner;
Pages: 1 - 14 Abstract: The qubit-mapping problem aims to assign and route qubits of a quantum circuit onto an noisy intermediate-scale quantum (NISQ) device in an optimized fashion, with respect to some cost function. Finding an optimal solution to this problem is known to scale exponentially in computational complexity; as such, it is imperative to investigate scalable qubit-mapping solutions for NISQ computation. In this work, a noise-aware heuristic qubit-assignment algorithm (which assigns initial placements for qubits in a quantum algorithm to qubits on an NISQ device, but does not route qubits during the quantum algorithm’s execution) is presented and compared against the optimal brute-force solution, as well as a trivial qubit assignment, with the aim to quantify the performance of our heuristic qubit-assignment algorithm. We find that for small, connected-graph algorithms, our heuristic-assignment algorithm faithfully lies in between the effective upper and lower bounds given by the brute-force and trivial qubit-assignment algorithms. Additionally, we find that the topological-graph properties of quantum algorithms with over six qubits play an important role in our heuristic qubit-assignment algorithm’s performance on NISQ devices. Finally, we investigate the scaling properties of our heuristic algorithm for quantum processors with up to 100 qubits; here, the algorithm was found to be scalable for quantum-algorithms that admit path-like graphs. Our findings show that as the size of the quantum processor in our simulation grows, so do the benefits from utilizing the heuristic qubit-assignment algorithm, under particular constraints for our heuristic algorithm. This work, thus, characterizes the performance of a heuristic qubit-assignment algorithm with respect to the topological-graph and scaling properties of a quantum algorithm that one may wish to run on a given NISQ device. PubDate:
2022
Issue No:Vol. 3 (2022)

Authors:
Adriana Meijer - van de Griend;Jukka K. Nurminen;
Pages: 1 - 6 Abstract: Thanks to the rise of quantum computers, many variations of the variational quantum eigensolver (VQE) have been proposed in recent times. This is a promising development for real quantum algorithms, as the VQE is a promising algorithm that runs on current quantum hardware. However, the popular method of comparing your algorithm versus a classical baseline in a small basis set is not meaningful in the big picture. Moreover, many papers use a different molecular representation or a different quantum computer to test their algorithms such that the used baselines are different between different papers. Thus, it is almost impossible to compare the different algorithms to each other. As a solution, we have built a benchmarking framework to standardize the VQE performance metrics, such that they can be analyzed more easily. Using our framework, any researcher working on the VQE can easily test their own algorithms against previous ones on the leaderboard without the need to reproduce previous work themselves. PubDate:
2022
Issue No:Vol. 3 (2022)

Authors:
Alexandru Paler;Oumarou Oumarou;Robert Basmadjian;
Pages: 1 - 11 Abstract: We provide evidence that commonly held intuitions when designing quantum circuits can be misleading. In particular, we show that 1) reducing the T-count can increase the total depth; 2) it may be beneficial to trade controlled NOTs for measurements in noisy intermediate-scale quantum (NISQ) circuits; 2) measurement-based uncomputation of relative phase Toffoli ancillae can make up to 30% of a circuit’s depth; and 4) area and volume cost metrics can misreport the resource analysis. Our findings assume that qubits are and will remain a very scarce resource. The results are applicable for both NISQ and quantum error-corrected protected circuits. Our method uses multiple ways of decomposing Toffoli gates into Clifford+T gates. We illustrate our method on addition and multiplication circuits using ripple-carry. As a byproduct result, we show systematically that for a practically significant range of circuit widths, ripple-carry addition circuits are more resource-efficient than the carry-lookahead addition ones. The methods and circuits were implemented in the open-source QUANTIFY software. PubDate:
2022
Issue No:Vol. 3 (2022)

Authors:
Khaled A. Helal Kelany;Nikitas Dimopoulos;Clemens P. J. Adolphs;Amirali Baniasadi;
Pages: 1 - 20 Abstract: The focus of this work is to explore the use of quantum annealing solvers for the problem of phase unwrapping of synthetic aperture radar (SAR) images. Although solutions to this problem exist based on network programming, these techniques do not scale well to larger sized images. Our approach involves formulating the problem as a quadratic unconstrained binary optimization (QUBO) problem, which can be solved on a quantum annealer. Given that present embodiments of quantum annealers remain limited in the number of qubits they possess, we decompose the problem into a set of subproblems that can be solved individually. These individual solutions are close to optimal up to an integer constant, with one constant per subimage. In a second phase, these integer constants are determined as a solution to yet another QUBO problem. This basic idea is extended to several passes, where each pass results in an image which is subsequently decomposed to yet another set of subproblems until the resulting image can be accommodated by the annealer at hand. Additionally, we explore improvements to the method by decomposing the original image into overlapping subimages and ignoring the results on the overlapped (marginal) pixels. We test our approach with a variety of software-based QUBO solvers and on a variety of images, both synthetic and real. Additionally, we experiment using D-wave systems’ quantum annealer, the D-wave 2000Q_6 and developed an embedding method which, for our problem, yielded improved results. Our method resulted in high quality solutions, comparable to state-of-the-art phase-unwrapping solvers. PubDate:
2022
Issue No:Vol. 3 (2022)

Authors:
Neel Kanth Kundu;Matthew R. McKay;Ranjan K. Mallik;
Pages: 1 - 13 Abstract: In this article, we propose a machine-learning framework for parameter estimation of single-mode Gaussian quantum states. Under a Bayesian framework, our approach estimates parameters of suitable prior distributions from measured data. For phase-space displacement and squeezing parameter estimation, this is achieved by introducing expectation–maximization (EM)-based algorithms, while for phase parameter estimation, an empirical Bayes method is applied. The estimated prior distribution parameters along with the observed data are used for finding the optimal Bayesian estimate of the unknown displacement, squeezing, and phase parameters. Our simulation results show that the proposed algorithms have estimation performance that is very close to that of “Genie Aided” Bayesian estimators, which assume perfect knowledge of the prior parameters. In practical scenarios, when numerical values of the prior distribution parameters are not known beforehand, our proposed methods can be used to find optimal Bayesian estimates from the observed measurement data. PubDate:
2022
Issue No:Vol. 3 (2022)

Authors:
Mikio Fujiwara;Ryo Nojima;Toyohiro Tsurumaru;Shiho Moriai;Masahiro Takeoka;Masahide Sasaki;
Pages: 1 - 11 Abstract: The quantum key distribution (QKD) network with Vernam's one-time pad encryption and secret sharing are powerful security tools to realize an information theoretically secure (ITS) distributed storage system. In the work of Fujiwara et al., a single-password-authenticated secret sharing (SPSS) scheme based on the QKD network and Shamirs secret sharing was experimentally demonstrated; it confirmed ITS data transmission, storage, authentication, and integrity. To achieve data integrity, an ITS message authentication code (MAC) tag is employed, and a data owner of the secret sharing performs both the MAC tag generation and verification. However, for a scenario in which the data owner and end users are different entities, the above approach may not work, since the data owner can cheat the end users. In this article, we resolve this problem by proposing an ITS integrity protection scheme employing a third-party verification with time-stamp. The ITS integrity protection is realized by two steps: integrity check by the data owner at data reconstruction and data integrity certification by the data owner, the end user, and the third-party verifier using a MAC based on universal2 hash function and random number provided from the QKD network. In addition to introducing the third-party verifier, we institute “a trusted calculator,” which computes shares of the data and MAC tags and sends MAC tags to the third-party verifier. The random number used in calculation is stored in the trusted calculator. We implement this scheme on the SPSS system installed in the Tokyo QKD Network. PubDate:
2022
Issue No:Vol. 3 (2022)

Authors:
Linh Le;Tu N. Nguyen;
Pages: 1 - 12 Abstract: Quantum routing plays a key role in the development of the next-generation network system. In particular, an entangled routing path can be constructed with the help of quantum entanglement and swapping among particles (e.g., photons) associated with nodes in the network. From another side of computing, machine learning has achieved numerous breakthrough successes in various application domains, including networking. Despite its advantages and capabilities, machine learning is not as much utilized in quantum networking as in other areas. To bridge this gap, in this article, we propose a novel quantum routing model for quantum networks that employs machine learning architectures to construct the routing path for the maximum number of demands (source–destination pairs) within a time window. Specifically, we present a deep reinforcement routing scheme that is called Deep Quantum Routing Agent (DQRA). In short, DQRA utilizes an empirically designed deep neural network that observes the current network states to accommodate the network’s demands, which are then connected by a qubit-preserved shortest path algorithm. The training process of DQRA is guided by a reward function that aims toward maximizing the number of accommodated requests in each routing window. Our experiment study shows that, on average, DQRA is able to maintain a rate of successfully routed requests at above 80% in a qubit-limited grid network and approximately 60% in extreme conditions, i.e., each node can be repeater exactly once in a window. Furthermore, we show that the model complexity and the computational time of DQRA are polynomial in terms of the sizes of the quantum networks. PubDate:
2022
Issue No:Vol. 3 (2022)

Authors:
Richard A. Brewster;Julius Goldhar;Mark Morris;Gerald Baumgartner;Yanne K. Chembo;
Pages: 1 - 10 Abstract: The Clauser–Horne–Shimony–Holt (CHSH) experiment is an essential test of nonlocality in quantum mechanics and can be used to validate the principle of entanglement. In addition to verifying entanglement, the measurable CHSH parameter can also be used to gauge the quality of the entanglement present in a system. The measurement of Hong–Ou–Mandel (HOM) interference is another important fundamental experiment in quantum optics that measures the indistinguishability of a pair of photons. In this article, we demonstrate how the results of a HOM interference experiment, a relatively simple experiment, can be used to obtain an estimate for the value of the CHSH $S$ parameter, which is a more complicated measurement. We experimentally demonstrate that the HOM interference technique is capable of providing an estimate of the value of the CHSH parameter that is within one standard deviation of measurement error when spectral impairments are present. We expect that this technique will aid in the calibration of quantum optical systems. PubDate:
2022
Issue No:Vol. 3 (2022)

Authors:
Mohammad Ghaderibaneh;Caitao Zhan;Himanshu Gupta;C. R. Ramakrishnan;
Pages: 1 - 20 Abstract: Quantum network communication is challenging, as the no-cloning theorem in the quantum regime makes many classical techniques inapplicable; in particular, the direct transmission of qubit states over long distances is infeasible due to unrecoverable errors. For the long-distance communication of unknown quantum states, the only viable communication approach (assuming local operations and classical communications) is the teleportation of quantum states, which requires a prior distribution of the entangled pairs (EPs) of qubits. The establishment of EPs across remote nodes can incur significant latency due to the low probability of success of the underlying physical processes. The focus of our work is to develop efficient techniques that minimize EP generation latency. Prior works have focused on selecting entanglement paths; in contrast, we select entanglement swapping trees—a more accurate representation of the entanglement generation structure. We develop a dynamic programming algorithm to select an optimal swapping tree for a single pair of nodes, under the given capacity and fidelity constraints. For the general setting, we develop an efficient iterative algorithm to compute a set of swapping trees. We present simulation results, which show that our solutions outperform the prior approaches by an order of magnitude and are viable for long-distance entanglement generation. PubDate:
2022
Issue No:Vol. 3 (2022)

Authors:
Robert Fulton Spivey;Ismail Volkan Inlek;Zhubing Jia;Stephen Crain;Ke Sun;Junki Kim;Geert Vrijsen;Chao Fang;Colin Fitzgerald;Steffen Kross;Tom Noel;Jungsang Kim;
Pages: 1 - 11 Abstract: Cryogenic environments benefit ion trapping experiments by offering lower motional heating rates, collision energies, and an ultrahigh vacuum (UHV) environment for maintaining long ion chains for extended periods of time. Mechanical vibrations caused by compressors in closed-cycle cryostats can introduce relative motion between the ion and the wavefronts of lasers used to manipulate the ions. Here, we present a novel ion trapping system where a commercial low-vibration closed-cycle cryostat is used in a custom monolithic enclosure. We measure mechanical vibrations of the sample stage using an optical interferometer, and observe a root-mean-square relative displacement of 2.4 nm and a peak-to-peak displacement of 17 nm between free-space beams and the trapping location. We packaged a surface ion trap in a cryopackage assembly that enables easy handling while creating a UHV environment for the ions. The trap cryopackage contains activated carbon getter material for enhanced sorption pumping near the trapping location, and source material for ablation loading. Using $^{171}$Yb$^{+}$ as our ion, we estimate the operating pressure of the trap as a function of package temperature using phase transitions of zig-zag ion chains as a probe. We measured the radial mode heating rate of a single ion to be 13 quanta/s on average. The Ramsey coherence measurements yield 330-ms coherence time for counter-propagating Raman carrier transitions using a 355-nm mode-locked pulse laser, demonstrating the high optical stability. PubDate:
2022
Issue No:Vol. 3 (2022)

Authors:
Andrea Stanco;Francesco B. L. Santagiustina;Luca Calderaro;Marco Avesani;Tommaso Bertapelle;Daniele Dequal;Giuseppe Vallone;Paolo Villoresi;
Pages: 1 - 8 Abstract: This article presents a hardware and software architecture, which can be used in those systems that implement practical quantum key distribution (QKD) and quantum random-number generation (QRNG) schemes. This architecture fully exploits the capability of a System on a Chip (SoC), which comprehends both a field-programmable gate array (FPGA) and a dual-core CPU unit. By assigning the time-related tasks to the FPGA and the management to the CPU, we built a flexible system with optimized resource sharing on a commercial off-the-shelf (COTS) evaluation board, which includes an SoC. Furthermore, by changing the dataflow direction, the versatile system architecture can be exploited as a QKD transmitter, QKD receiver, and QRNG control-acquiring unit. Finally, we exploited the dual-core functionality and realized a concurrent stream device to implement a practical QKD transmitter, where one core continuously receives fresh data at a sustained rate from an external QRNG source, while the other operates with the FPGA to drive the qubit transmission to the QKD receiver. The system was successfully tested on a long-term run proving its stability and security. This demonstration paves the way toward a more secure QKD implementation, with fully unconditional security as the QKD states are entirely generated by a true random process and not by deterministic expansion algorithms. Eventually, this enables the realization of a standalone quantum transmitter, including both the random numbers and the qubit generation. PubDate:
2022
Issue No:Vol. 3 (2022)

Authors:
Andrew S. Dzurak;Julien Epps;Arne Laucht;Robert Malaney;Andrea Morello;Hendra I. Nurdin;Jarryd J. Pla;Andre Saraiva;Chih Hwan Yang;
Pages: 1 - 10 Abstract: Quantum computing, communications, sensing, and simulations are radically transformative technologies, with great potential to impact industries and economies. Worldwide, national governments, industries, and universities are moving to create a new class of workforce—the Quantum Engineers. Demand for such engineers is predicted to be in the tens of thousands within a five-year timescale, far exceeding the rate at which the world’s universities can produce Ph.D. graduates in the discipline. How best to train this next generation of engineers is currently a matter of debate. Quantum mechanics—long a pillar of traditional physics undergraduate degrees—must now be merged with traditional engineering offerings. This article discusses the history, development, and the first year of operation of the world’s first undergraduate degree in quantum engineering to be grown out of an engineering curriculum. The main purpose of this article is to inform the wider discussion, now being held by many institutions worldwide, on how best to formally educate the Quantum Engineer. PubDate:
2022
Issue No:Vol. 3 (2022)