723 research outputs found
Stream VByte: Faster Byte-Oriented Integer Compression
Arrays of integers are often compressed in search engines. Though there are
many ways to compress integers, we are interested in the popular byte-oriented
integer compression techniques (e.g., VByte or Google's Varint-GB). They are
appealing due to their simplicity and engineering convenience. Amazon's
varint-G8IU is one of the fastest byte-oriented compression technique published
so far. It makes judicious use of the powerful single-instruction-multiple-data
(SIMD) instructions available in commodity processors. To surpass varint-G8IU,
we present Stream VByte, a novel byte-oriented compression technique that
separates the control stream from the encoded data. Like varint-G8IU, Stream
VByte is well suited for SIMD instructions. We show that Stream VByte decoding
can be up to twice as fast as varint-G8IU decoding over real data sets. In this
sense, Stream VByte establishes new speed records for byte-oriented integer
compression, at times exceeding the speed of the memcpy function. On a 3.4GHz
Haswell processor, it decodes more than 4 billion differentially-coded integers
per second from RAM to L1 cache
Heralded photonic interaction between distant single ions
We establish heralded interaction between two remotely trapped single 40Ca+
ions through the exchange of single photons. In the sender ion, we release
single photons with controlled temporal shape on the P_3/2 to D_5/2 transition
and transmit them to the distant receiver ion. Individual absorption events in
the receiver ion are detected by quantum jumps. For continuously generated
photons, the absorption reduces significantly the lifetime of the long-lived
D_5/2 state. For triggered single-photon transmission, we observe coincidence
between the emission at the sender and quantum jump events at the receiver.Comment: 5 pages, 4 figures. v2: number on p. 3, bottom, correcte
Optimal Opinion Control: The Campaign Problem
Opinion dynamics is nowadays a very common field of research. In this article
we formulate and then study a novel, namely strategic perspective on such
dynamics: There are the usual normal agents that update their opinions, for
instance according the well-known bounded confidence mechanism. But,
additionally, there is at least one strategic agent. That agent uses opinions
as freely selectable strategies to get control on the dynamics: The strategic
agent of our benchmark problem tries, during a campaign of a certain length, to
influence the ongoing dynamics among normal agents with strategically placed
opinions (one per period) in such a way, that, by the end of the campaign, as
much as possible normals end up with opinions in a certain interval of the
opinion space. Structurally, such a problem is an optimal control problem. That
type of problem is ubiquitous. Resorting to advanced and partly non-standard
methods for computing optimal controls, we solve some instances of the campaign
problem. But even for a very small number of normal agents, just one strategic
agent, and a ten-period campaign length, the problem turns out to be extremely
difficult. Explicitly we discuss moral and political concerns that immediately
arise, if someone starts to analyze the possibilities of an optimal opinion
control.Comment: 47 pages, 12 figures, and 11 table
Demand for Medical Care by the Elderly: A Nonparametric Variational Bayesian Mixture Approach
Outpatient care is a large share of total health care spending, making analysis of data on outpatient utilization an important part of understanding patterns and drivers of health care spending growth. Common features of outpatient utilization measures include zero-inflation, over-dispersion, and skewness, all of which complicate statistical modeling. Mixture modeling is a popular approach because it can accommodate these features of health care utilization data. In this work, we add a nonparametric clustering component to such models. Our fully Bayesian model framework allows for an unknown number of mixing components, so that the data, rather than the researcher, determine the number of mixture components. We apply the modeling framework to data on visits to physicians by elderly individuals and show that each subgroup has different characteristics that allow easy interpretation and new insights
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