The Buffered \pi-Calculus: A Model for Concurrent Languages

Message-passing based concurrent languages are widely used in developing large distributed and coordination systems. This paper presents the buffered $\pi$-calculus --- a variant of the $\pi$-calculus where channel names are classified into buffered and unbuffered: communication along buffered channels is asynchronous, and remains synchronous along unbuffered channels. We show that the buffered $\pi$-calculus can be fully simulated in the polyadic $\pi$-calculus with respect to strong bisimulation. In contrast to the $\pi$-calculus which is hard to use in practice, the new language enables easy and clear modeling of practical concurrent languages. We encode two real-world concurrent languages in the buffered $\pi$-calculus: the (core) Go language and the (Core) Erlang. Both encodings are fully abstract with respect to weak bisimulations

A Novel Deep Learning Framework for Internal Gross Target Volume Definition from 4D Computed Tomography of Lung Cancer Patients

In this paper, we study the reliability of a novel deep learning framework for internal gross target volume (IGTV) delineation from four-dimensional computed tomography (4DCT), which is applied to patients with lung cancer treated by Stereotactic Body Radiation Therapy (SBRT). 77 patients who underwent SBRT followed by 4DCT scans were incorporated in a retrospective study. The IGTV_DL was delineated using a novel deep machine learning algorithm with a linear exhaustive optimal combination framework, for the purpose of comparison, three other IGTVs base on common methods was also delineated, we compared the relative volume difference (RVI), matching index (MI) and encompassment index (EI) for the above IGTVs. Then, multiple parameter regression analysis assesses the tumor volume and motion range as clinical influencing factors in the MI variation. Experimental results demonstrated that the deep learning algorithm with linear exhaustive optimal combination framework has a higher probability of achieving optimal MI compared with other currently widely used methods. For patients after simple breathing training by keeping the respiratory frequency in 10 BMP, the four phase combinations of 0%, 30%, 50% and 90% can be considered as a potential candidate for an optimal combination to synthesis IGTV in all respiration amplitudes

The Crystal Structure of Monovalent Streptavidin.

The strong interaction between streptavidin (SA) and biotin is widely utilized in biotechnological applications. A SA variant, monovalent SA, was developed with a single and high affinity biotin-binding site within the intact tetramer. However, its structural characterization remains undetermined. Here, we seek to determine the crystal structure of monovalent SA at 1.7-Å resolution. We show that, in contrast to its 'close-state' in the only wild-type subunit, the L3,4 loops of three Dead SA subunits are free from crystal packing and remain in an 'open state', stabilized by a consistent H-bonding network involving S52. This H-bonding network also applies to the previously reported open state of the wild-type apo-SA. These results suggest that specific substitutions (N23A/S27D/S45A) at biotin-binding sites stabilize the open state of SA L3,4 loop, thereby further reducing biotin-binding affinity. The general features of the 'open state' SA among different SA variants may facilitate its rational design. The structural information of monovalent SA will be valuable for its applications across a wide range of biotechnological areas

Effect of weak measurement on entanglement distribution over noisy channels

Being able to implement effective entanglement distribution in noisy environments is a key step towards practical quantum communication, and long-term efforts have been made on the development of it. Recently, it has been found that the null-result weak measurement (NRWM) can be used to enhance probabilistically the entanglement of a single copy of amplitude-damped entangled state. This paper investigates remote distributions of bipartite and multipartite entangled states in the amplitudedamping environment by combining NRWMs and entanglement distillation protocols (EDPs). We show that the NRWM has no positive effect on the distribution of bipartite maximally entangled states and multipartite Greenberger-Horne-Zeilinger states, although it is able to increase the amount of entanglement of each source state (noisy entangled state) of EDPs with a certain probability. However, we find that the NRWM would contribute to remote distributions of multipartite W states. We demonstrate that the NRWM can not only reduce the fidelity thresholds for distillability of decohered W states, but also raise the distillation efficiencies of W states. Our results suggest a new idea for quantifying the ability of a local filtering operation in protecting entanglement from decoherence.Comment: 15 pages, 9 figures. Minor revision has been mad

Multiparty quantum secret sharing with pure entangled states and decoy photons

We present a scheme for multiparty quantum secret sharing of a private key with pure entangled states and decoy photons. The boss, say Alice uses the decoy photons, which are randomly in one of the four nonorthogonal single-photon states, to prevent a potentially dishonest agent from eavesdropping freely. This scheme requires the parties of communication to have neither an ideal single-photon quantum source nor a maximally entangled one, which makes this scheme more convenient than others in a practical application. Moreover, it has the advantage of having high intrinsic efficiency for qubits and exchanging less classical information in principle.Comment: 5 pages, no figure

Optimizing Quantum Programs against Decoherence: Delaying Qubits into Quantum Superposition

Quantum computing technology has reached a second renaissance in the last decade. However, in the NISQ era pointed out by John Preskill in 2018, quantum noise and decoherence, which affect the accuracy and execution effect of quantum programs, cannot be ignored and corrected by the near future NISQ computers. In order to let users more easily write quantum programs, the compiler and runtime system should consider underlying quantum hardware features such as decoherence. To address the challenges posed by decoherence, in this paper, we propose and prototype QLifeReducer to minimize the qubit lifetime in the input OpenQASM program by delaying qubits into quantum superposition. QLifeReducer includes three core modules, i.e.,the parser, parallelism analyzer and transformer. It introduces the layered bundle format to express the quantum program, where a set of parallelizable quantum operations is packaged into a bundle. We evaluate quantum programs before and after transformed by QLifeReducer on both real IBM Q 5 Tenerife and the self-developed simulator. The experimental results show that QLifeReducer reduces the error rate of a quantum program when executed on IBMQ 5 Tenerife by 11%; and can reduce the longest qubit lifetime as well as average qubit lifetime by more than 20% on most quantum workloads.Comment: To appear in TASE2019 - the 13th International Symposium on Theoretical Aspects of Software Engineering (submitted on Jan 25, 2019, and this is camera-ready version