79,139 research outputs found
Stokes Parameters as a Minkowskian Four-vector
It is noted that the Jones-matrix formalism for polarization optics is a
six-parameter two-by-two representation of the Lorentz group. It is shown that
the four independent Stokes parameters form a Minkowskian four-vector, just
like the energy-momentum four-vector in special relativity. The optical filters
are represented by four-by-four Lorentz-transformation matrices. This
four-by-four formalism can deal with partial coherence described by the Stokes
parameters. A four-by-four matrix formulation is given for decoherence effects
on the Stokes parameters, and a possible experiment is proposed. It is shown
also that this Lorentz-group formalism leads to optical filters with a symmetry
property corresponding to that of two-dimensional Euclidean transformations.Comment: RevTeX, 22 pages, no figures, submitted to Phys. Rev.
Scalable Compression of Deep Neural Networks
Deep neural networks generally involve some layers with mil- lions of
parameters, making them difficult to be deployed and updated on devices with
limited resources such as mobile phones and other smart embedded systems. In
this paper, we propose a scalable representation of the network parameters, so
that different applications can select the most suitable bit rate of the
network based on their own storage constraints. Moreover, when a device needs
to upgrade to a high-rate network, the existing low-rate network can be reused,
and only some incremental data are needed to be downloaded. We first
hierarchically quantize the weights of a pre-trained deep neural network to
enforce weight sharing. Next, we adaptively select the bits assigned to each
layer given the total bit budget. After that, we retrain the network to
fine-tune the quantized centroids. Experimental results show that our method
can achieve scalable compression with graceful degradation in the performance.Comment: 5 pages, 4 figures, ACM Multimedia 201
Generation of GHZ entangled states of photons in multiple cavities via a superconducting qutrit or an atom through resonant interaction
We propose an efficient method to generate a GHZ entangled state of n photons
in n microwave cavities (or resonators) via resonant interaction to a single
superconducting qutrit. The deployment of a qutrit, instead of a qubit, as the
coupler enables us to use resonant interactions exclusively for all
qutrit-cavity and qutrit-pulse operations. This unique approach significantly
shortens the time of operation which is advantageous to reducing the adverse
effects of qutrit decoherence and cavity decay on fidelity of the protocol.
Furthermore, the protocol involves no measurement on either the state of qutrit
or cavity photons. We also show that the protocol can be generalized to other
systems by replacing the superconducting qutrit coupler with different types of
physical qutrit, such as an atom in the case of cavity QED, to accomplish the
same task.Comment: 11 pages, 5 figures, accepted by Phys. Rev.
Symmetries of coupled harmonic oscillators
It is shown that the system of two coupled harmonic oscillators possesses many interesting symmetries. It is noted that the symmetry of a single oscillator is that of the three-parameter group Sp(2). Thus two uncoupled oscillator exhibits a direct product of two Sp(2) groups, with six parameters. The coupling can be achieved through a rotation in the two-dimensional space of two oscillator coordinates. The closure of the commutation relations for the generators leads to the ten-parameter group Sp(4) which is locally isomorphic to the deSitter group O(3,2)
Coauthor prediction for junior researchers
Research collaboration can bring in different perspectives and generate more productive results. However, finding an appropriate collaborator can be difficult due to the lacking of sufficient information. Link prediction is a related technique for collaborator discovery; but its focus has been mostly on the core authors who have relatively more publications. We argue that junior researchers actually need more help in finding collaborators. Thus, in this paper, we focus on coauthor prediction for junior researchers. Most of the previous works on coauthor prediction considered global network feature and local network feature separately, or tried to combine local network feature and content feature. But we found a significant improvement by simply combing local network feature and global network feature. We further developed a regularization based approach to incorporate multiple features simultaneously. Experimental results demonstrated that this approach outperformed the simple linear combination of multiple features. We further showed that content features, which were proved to be useful in link prediction, can be easily integrated into our regularization approach. © 2013 Springer-Verlag
- …