10 research outputs found
Towards a Nonviolent Alternative for the Black Hole Information Paradox
In the semiclassical approximation, quantum field theory suggests that blackholes eventually evaporate in a manner largely independent of their internal structure. Doing so, however, leads to a violation of unitarity of quantum mechanics, rendering the system inconsistent. One possible resolution is soft violations of locality in the near horizon region. The first consistency check is whether such a proposal can actually get the information out. Using quantum information techniques, a large class of evolutions into paired states is ruled out. More generally, information transfer can be characterized by the mutual information of a specially prepared state. Minimizing this quantity saturates a subadditivity inequality, leading to "subspace transfer"; maximizing it generically leads to an enhanced particle flux. Using the tools of effective field theory, one can then try to model the nonlocality as arising from an effective source localized near the horizon. To get information out at the right rate, this source must have a characteristic size. The horizon is altered, but nonviolent. This model also naturally accommodates black hole mining, avoiding a potential flaw. Having passed important consistency checks, nonviolent nonlocality is a viable solution to the information paradox
Quantum information transfer and models for black hole mechanics
General features of information transfer between quantum subsystems, via
unitary evolution, are investigated, with applications to the problem of
information transfer from a black hole to its surroundings. A particularly
direct form of quantum information transfer is "subspace transfer," which can
be characterized by saturation of a subadditivity inequality. We also describe
more general unitary quantum information transfer, and categorize different
models for black hole evolution. Evolution that only creates paired excitations
inside/outside the black hole is shown not to extract information, but
information-transferring models exist both in the "saturating" and
"non-saturating" category. The former more closely capture thermodynamic
behavior; the latter generically have enhanced energy flux, beyond that of
Hawking.Comment: 31 pages, harvmac. v2: nomenclature change, minor added explanation.
v3: small corrections/rewordings; improved figure; version to match
publication in PR
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Towards a Nonviolent Alternative for the Black Hole Information Paradox
In the semiclassical approximation, quantum field theory suggests that blackholes eventually evaporate in a manner largely independent of their internal structure. Doing so, however, leads to a violation of unitarity of quantum mechanics, rendering the system inconsistent. One possible resolution is soft violations of locality in the near horizon region. The first consistency check is whether such a proposal can actually get the information out. Using quantum information techniques, a large class of evolutions into paired states is ruled out. More generally, information transfer can be characterized by the mutual information of a specially prepared state. Minimizing this quantity saturates a subadditivity inequality, leading to "subspace transfer"; maximizing it generically leads to an enhanced particle flux. Using the tools of effective field theory, one can then try to model the nonlocality as arising from an effective source localized near the horizon. To get information out at the right rate, this source must have a characteristic size. The horizon is altered, but nonviolent. This model also naturally accommodates black hole mining, avoiding a potential flaw. Having passed important consistency checks, nonviolent nonlocality is a viable solution to the information paradox
VideoINR: Learning Video Implicit Neural Representation for Continuous Space-Time Super-Resolution
Videos typically record the streaming and continuous visual data as discrete
consecutive frames. Since the storage cost is expensive for videos of high
fidelity, most of them are stored in a relatively low resolution and frame
rate. Recent works of Space-Time Video Super-Resolution (STVSR) are developed
to incorporate temporal interpolation and spatial super-resolution in a unified
framework. However, most of them only support a fixed up-sampling scale, which
limits their flexibility and applications. In this work, instead of following
the discrete representations, we propose Video Implicit Neural Representation
(VideoINR), and we show its applications for STVSR. The learned implicit neural
representation can be decoded to videos of arbitrary spatial resolution and
frame rate. We show that VideoINR achieves competitive performances with
state-of-the-art STVSR methods on common up-sampling scales and significantly
outperforms prior works on continuous and out-of-training-distribution scales.
Our project page is at http://zeyuan-chen.com/VideoINR/ .Comment: Accepted to CVPR 2022. Project page: http://zeyuan-chen.com/VideoINR