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7.1 Earthquake in Japan

https://www.data.jma.go.jp/multi/quake/quake_detail.html?eventID=20260728163528&lang=en
352•krembo•4h ago•70 comments

About the security content of macOS Tahoe 26.6

https://support.apple.com/en-us/128067
85•andor•2h ago•38 comments

Google's Beyond Zero: Enterprise Security for the AI Era

https://spawn-queue.acm.org/doi/10.1145/3819083
32•jordigg•2h ago•20 comments

Our position on open-weights models

https://www.anthropic.com/news/position-open-weights-models
986•surprisetalk•14h ago•1431 comments

How to Survive Boiling Water

https://taxa.substack.com/p/how-to-survive-boiling-water
97•cainxinth•3d ago•16 comments

A $500 RL fine-tune of a 9B open model beat frontier models on catalog review

https://fermisense.com/when-machines-take-the-wheel/
231•ilreb•10h ago•70 comments

Golang Maps: how Swiss Tables replaced the old bucket design

https://blog.gaborkoos.com/posts/2026-07-24-Golang-Maps-How-Swiss-Tables-Replaced-the-Old-Bucket-...
23•Terretta•3d ago•5 comments

Ars Astronomica – English translations of rare Hebrew and Latin astronomy texts

https://arsastronomica.com/
78•sweisman•7h ago•22 comments

Benchmarking Opus 5 on SlopCodeBench

https://github.com/humanlayer/advanced-context-engineering-for-coding-agents/blob/main/benchmarki...
323•dhorthy•13h ago•78 comments

Vehicle Motion Cues

https://support.apple.com/guide/iphone/iphone-comfortably-riding-a-vehicle-iph55564cb22/ios
144•Austin_Conlon•11h ago•68 comments

TWC Classics

https://twcclassics.com/
21•stefanpie•5d ago•1 comments

Watching Go's new garbage collector move through the heap

https://theconsensus.dev/p/2026/07/19/observing-gos-garbage-collector-old-and-new.html
240•matheusmoreira•3d ago•31 comments

PyTorch: A Reference Language

https://docs.pytorch.org/devlogs/compiler/2026-07-25-pytorch-a-reference-language/
45•matt_d•7h ago•4 comments

Neutrino-1 8B

https://www.fermionresearch.com/models/neutrino-8b/
103•handfuloflight•7h ago•36 comments

Kimi K3 Now Available via Telnyx Inference API

https://telnyx.com/release-notes/kimi-k3-telnyx-inference
105•fionaattelnyx•13h ago•54 comments

Which Odyssey translation wins a blind reading test?

https://homer.scrivium.com/report/
12•curo•4d ago•13 comments

Programming Languages Are Authoring Tools for Platforms

https://www.makonea.com/en-US/blog/programming-languages-are-authoring-tools-for-platforms
27•jdw64•4d ago•6 comments

DConf 2026 in London

https://dconf.org/2026/index.html
108•teleforce•13h ago•47 comments

RTX 2080 Ti Memory Upgrade to 22 GB

https://gpusolutions.net/rbservices/graphics-card-upgrade/
131•wslh•3d ago•95 comments

Show HN: Yap – OSS on-device voice dictation for macOS with no model to download

https://github.com/FrigadeHQ/yap
80•pancomplex•17h ago•28 comments

Launch HN: Rise Reforming (YC S26) – Turning Waste Gases into Valuable Chemicals

https://www.rise-reforming.com
78•george_rose25•16h ago•31 comments

Ray tracing massive amounts of animated geometry using tetrahedral cages

https://gpuopen.com/learn/ray-tracing-massive-amounts-animated-geometry/
114•LorenDB•4d ago•15 comments

Paged Out #9 [pdf]

https://pagedout.institute/download/PagedOut_009.pdf
260•laurensr•22h ago•30 comments

Self-contained highly-portable Python distributions

https://gregoryszorc.com/docs/python-build-standalone/main/
153•jcbhmr•17h ago•33 comments

Some combinatorial applications of spacefilling curves

https://www2.isye.gatech.edu/~jjb/research/mow/mow.html
60•shraiwi•2d ago•11 comments

Don't ask an LLM for a confidence score

https://justinflick.com/2026/07/27/llm-confidence-scores.html
52•pamplemeese•12h ago•12 comments

Securing Services with Rootless Containers

https://blog.coderspirit.xyz/blog/2026/07/06/securing-services-with-rootless-containers/
106•speckx•4d ago•32 comments

C/C++ projects packaged for Zig

https://github.com/allyourcodebase
68•jcbhmr•13h ago•39 comments

A Dying Art: The last of the morticians

https://harpers.org/archive/2026/08/a-dying-art-john-semley-mortuary-sciences-competition/
41•Petiver•4d ago•8 comments

How real are real numbers? (2004)

https://arxiv.org/abs/math/0411418
86•surprisetalk•20h ago•64 comments
Open in hackernews

The Fastest Way yet to Color Graphs

https://www.quantamagazine.org/the-fastest-way-yet-to-color-graphs-20250512/
62•GavCo•1y ago

Comments

tonyarkles•1y ago
In case you haven't looked at the article, this is looking specifically at the Edge Coloring problem and not the more commonly known Vertex Coloring problem. Vertex Coloring is NP-complete unfortunately.
erikvanoosten•1y ago
You can convert edge coloring problems into vertex coloring problems and vice versa through a simple O(n) procedure.
meindnoch•1y ago
Wrong. You can convert edge-coloring problems into vertex-coloring problems of the so-called line graph: https://en.m.wikipedia.org/wiki/Line_graph

But the opposite is not true, because not every graph is a line graph of some other graph.

erikvanoosten•1y ago
Indeed. Thanks, I stand corrected.
tonyarkles•1y ago
Hrm... right. It's been a while. And it looks like both Vertex Coloring and Edge Coloring are both NP-complete (because of the O(n) procedure you're talking about and the ability to reduce both problems down to 3-SAT). I've started looking closer at the actual paper to try to figure out what's going on here. Thanks for the reminder, I miss getting to regularly work on this stuff.

Edit: thanks sibling reply for pointing out that it's not a bidirectional transform.

mauricioc•1y ago
For the edge-coloring problem, the optimal number of colors needed to properly color the edges of G is always either Delta(G) (the maximum degree of G) or Delta(G) + 1, but deciding which one is the true optimum is an NP-complete problem.

Nevertheless, you can always properly edge-color a graph with Delta(G) + 1 colors. Finding such a coloring could in principle be slow, though: the original proof that Delta(G) + 1 colors is always doable amounted to a O(e(G) * v(G)) algorithm, where e(G) and v(G) denote the number of edges and vertices of G, respectively. This is polynomial, but nowhere near linear. What the paper in question shows is how, given any graph G, to find an edge coloring using Delta(G) + 1 colors in O(e(G) * log(Delta(G))) time, which is linear time if the maximum degree is a constant.

Syzygies•1y ago
Yes. The article ran through this point as follows:

"In 1964, a mathematician named Vadim Vizing proved a shocking result: No matter how large a graph is, it’s easy to figure out how many colors you’ll need to color it. Simply look for the maximum number of lines (or edges) connected to a single point (or vertex), and add 1."

I keep wondering why I ever read Quanta Magazine. It takes a pretty generous reading of "need" to make this a correct statement.

JohnKemeny•1y ago
phkahler•1y ago
Is this going to lead to faster compile times? Faster register allocation...
john-h-k•1y ago
Very few compilers actually use vertex coloring for register allocation
isaacimagine•1y ago
Totally. The hard part isn't coloring (you can use simple heuristics to get a decent register assignment), rather, it's figuring out which registers to spill (don't spill registers in hot loops! and a million other things!).
NooneAtAll3•1y ago
and this post isn't even about vertex coloring
DannyBee•1y ago
No.

In SSA, the graphs are chordal, so were already easily colorable (relatively).

Outside of SSA, this is not true, but the coloring is still not the hard part, it's the easy part.

Not really. Coloring a graph is almost always talking about proper coloring, meaning that things that objects that are related receive different colors.

If you read the introduction, you'll also read that the goal is to "color each of your lines and require that for every point, no two lines connected to it have the same color."

Ps. "How many colors a graph needs" is a very well established term in computer science and graph theory.

mockerell•1y ago
I think the comment referred to the phrase „a graph needs X (colors or whatever)“. For me, this can be read two ways: 1. „a graph always needs at least X colors“ or 2. „a graph always needs at most X colors“.

Personally, I would interpret this as option 1 (and so did the comment above I assume). In that case, the statement is wrong. But I’d prefer to specify „at most/ at least“ anyways.

Or even better, use actual vocabulary. „For every graph there exists a coloring with X colors.“ or „any graph can be coloured using X colors“.

PS: I also agree with the sentiment about quanta magazine. It’s hard to get some actual information from their articles if you know the topic.

JohnKemeny•1y ago
What about this statement:

No matter how large a car is, it is easy to figure out how much money you'll need to buy it. Simply look at the price tag.

(From: No matter how large a graph is, it’s easy to figure out how many colors you’ll need to color it. Simply look for the maximum ...)

mauricioc•1y ago
Parent's point is that sometimes (but not always) the store is perfectly fine selling you a car for $1 less than what the "price tag" of Delta(G)+1 dollars asks for, so "need" is a bit inaccurate.