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Category Archives: Physics
Islands behind the horizon
If you’ve been following the arXiv, or keeping abreast of developments in highenergy theory more broadly, you may have noticed that the longstanding black hole information paradox seems to have entered a new phase, instigated by a pair of papers … Continue reading
Posted in Physics
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QFT in curved space, part 2: Bogolyubov transformations & the Unruh effect
One of the most important lessons of QFT in curved space is that the notion of a particle is an observerdependent concept. That’s not to say it isn’t locally useful, but without specifying the details of the mode decomposition and … Continue reading
Posted in Physics
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QFT in curved space, part 1: Green functions
I was recently** asked to give a lecture on black hole thermodynamics and the associated quantum puzzles, which provided a perfect excuse to spend some time reviewing one of my favourite subjects: quantum field theory (QFT) in curved spacetime. I’ll … Continue reading
Posted in Physics
2 Comments
Mean field theory: from physics to deep neural nets
In a previous post, I alluded to the question of whether criticality played any role in deep neural networks. The question I originally had in mind was whether the fact that the correlation length diverges at a critical point implies … Continue reading
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Black hole thermodynamics, quantum puzzles, and the holographic principle
I was asked to give a lecture on “quantum puzzles and black holes” at the 20th Jürgen Ehlers Spring School, which was to be hosted at AEI this week. Unfortunately the school was cancelled due to the SARSCoV2 pandemic, but … Continue reading
Interior operators in AdS/CFT
In a previous post, I mentioned that the firewall paradox could be phrased as a question about the existence of interior operators that satisfy the correct thermal correlation functions, namely where and operators inside and outside the black hole, respectively; cf. … Continue reading
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Deep learning and the renormalization group
In recent years, a number of works have pointed to similarities between deep learning (DL) and the renormalization group (RG) [17]. This connection was originally made in the context of certain lattice models, where decimation RG bears a superficial resemblance … Continue reading
Posted in Minds & Machines, Physics
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Cumulants, correlators, and connectivity
Lately, I’ve been spending a lot of time exploring the surprisingly rich mathematics at the intersection of physics, information theory, and machine learning. Among other things, this has led me to a new appreciation of cumulants. At face value, these … Continue reading
Posted in Physics
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Black hole interiors, state dependence, and all that
In the context of firewalls, the crux of the paradox boils down to whether black holes have smooth horizons (as required by the equivalence principle). It turns out that this is intimately related to the question of how the interior … Continue reading
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Black hole entropy: the heat kernel method
As part of my ongoing love affair with black holes, I’ve been digging more deeply into what it means for them to have entropy, which of course necessitates investigating how this is assigned in the first place. This is a … Continue reading
Posted in Physics
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