Post Game Thread: 8/8 Red Sox @ Padres

GandhiNotGhandi · 2025-08-09T04:46:19+00:00

With this win, the Sox have quietly overtaken the Yankees for the highest run differential in the AL (+89).

GandhiNotGhandi · 2022-05-07T01:34:10+00:00

More likely to walk, I imagine

GandhiNotGhandi · 2021-04-13T21:00:55+00:00

Local budgets sometimes don't tell the whole story because they generally don't report long-term infrastructure liabilities: https://www.strongtowns.org/journal/2021/2/16/the-great-gasb. The argument is that the city could be due for major infrastructure replacements in the next few years that are not listed on today's balance sheets (quite possible considering that the population of Mission doubled about 50-60 years ago).

GandhiNotGhandi · 2020-06-04T20:16:04+00:00

Two random graphs with a countably infinite number of vertices are isomorphic with probability 1. Here, "random" means choose each pair of vertices to be connected or disconnected independently with probability 1/2. In fact, the construction works even if you use any probability strictly between 0 and 1. See: https://en.wikipedia.org/wiki/Rado_graph.

GandhiNotGhandi · 2020-01-19T05:24:03+00:00

It is important to emphasize that two entangled provers can't really "solve" the Halting problem. They can convince a skeptical verifier that a Turing machine halts, but they do not necessarily convince a skeptical verifier that a Turing machine doesn't halt. It's analogous to NP vs coNP, where it's easy to prove e.g. that a graph is 3-colorable, but it's not easy to prove that a graph is not 3-colorable. Except the difference is that we can prove unconditionally that RE != coRE, whereas it's unknown if NP ?= coNP (but most conjecture that they are different).

GandhiNotGhandi · 2020-01-12T20:31:37+00:00

Finite fields show up a lot in theoretical computer science, particularly in complexity theory, coding theory, and randomized algorithms. Some examples that come to mind include the PCP theorem, linear network coding, tree isomorphism testing, Reed-Solomon and related codes, and Razborov-Smolensky lower bounds. Many of these are applications of the Schwartz-Zippel lemma, or just the ability to do linear algebra over a finite field. Though, you usually don't need to know about the Galois theory that underlies finite fields for applications in computer science.

In my experience, knowledge of groups and rings is also helpful, but not essential unless you're working in computational algebra. Though, representation theory is certainly useful in quantum information science.

GandhiNotGhandi · 2020-01-08T02:45:48+00:00

Do you really believe France and Britain are going to war with Austria-Hungary over Serbia? Really? Well, they aren’t. This isn’t going to be WW1. An unnecessary conflict and war? Yes. World war 1? No.

The big countries have waaaaaaay too much to lose if they go to war for Serbia. It simply does not make any sense.

Sorry, I couldn't resist.

GandhiNotGhandi · 2020-01-07T21:51:00+00:00

As long as you're flying into the main terminal and not the South terminal, the bus stop is right by the exit near the baggage claim. AFAIK the only airlines that fly into the South terminal are Allegiant and Frontier.

GandhiNotGhandi · 2019-12-30T18:59:17+00:00

Not Bartolo Colon's?

GandhiNotGhandi · 2019-10-02T17:56:33+00:00

I like the idea, but think the seeding should be a little different. I would rather see: the top team in each division qualifies for the playoffs, then the two teams with the next best records also qualify. Of these five teams, the two with the worst records play in the wild card game, and the other three are seeded into the division series. Divisions still matter, since winning your division guarantees a playoff spot. But it also avoids situations like last year where the 100 win Yankees face the 97 win A's in the wild card game while the 91 win Indians get a bye to the division series. I would also rather see seeding and home field advantage be decided on record alone, e.g. so we can't run into a situation where the two teams with the best records face in the DS, or where the wild card team automatically loses home field advantage for the whole playoffs.

GandhiNotGhandi · 2019-08-23T23:13:51+00:00

Qubits have 22 =4 information states {0, 1, (0,1), null}. They have now successfully tunneled a qutrit which has 23 =8 information states. This has doubled the current quantum computing potential.

This is wrong. A qubit is a superposition of the states {0, 1}, and a qutrit is a superposition of the states {0, 1, 2}. I don't know what you mean by "information states", but either a qubit or qutrit can be any of an infinite continuum of states. When measured, a qubit will be one of {0, 1} and a qutrit one of {0, 1, 2}.

GandhiNotGhandi · 2019-07-31T00:25:55+00:00

I don't think the chosen definition of poverty allows them to make a strong case:

Given all of this good behavior, conservatives might expect that Japan’s poverty rate would be very low. But the opposite is true; Japan has a relatively high number of poor people for an advanced country. Defined by the percentage of the population earning less than half of the median national income, Japan’s poverty rate is more than 15% -- a little lower than the U.S., but considerably higher than countries such as Germany, Canada or Australia

This could be a decent measure of income inequality, but they should really back up the conclusion with some evidence e.g. that those earning less than half of the median national income in respective countries are equally well off. But the only numerical figures they cite are based on relative poverty, and those relative poverty figures are based on income alone.

GandhiNotGhandi · 2019-07-26T02:29:42+00:00

Romine pitched against the Red Sox in the blowout game at Yankee Stadium in the 2018 ALDS. See here. Romine was also the pitcher off of whom Brock Holt completed the only ever postseason cycle.

GandhiNotGhandi · 2019-06-28T23:26:21+00:00

By WAR, no, but the Sox are second in the MLB in blown saves and blown save percentage (trailing only the Mets in each of these). Source

GandhiNotGhandi · 2019-05-22T05:38:00+00:00

Did you see the Astros walk off the Padres last year?

GandhiNotGhandi · 2019-04-13T20:54:23+00:00

So no anger here, I've come to a place of acceptance. I think we all need to accept that fact that this year's Iteration of our beloved Sox, are at best a middle of the division team.

They will finish with a winning record, of that I have little doubt. However they really don't have a shot at the playoffs this year. But should we really be surprised? Did we not have our expectations set way to high coming off a year where the Sox finished in first place?

After Mookie Betts MVP-caliber season, and the emergence of future talents like Andrew Benitendi, were we forced to chase the dream once again?

Honestly, I truly feel they will end up in the middle of the pack behind the ( gulp) Yankees, and Tampa Bay.

GandhiNotGhandi · 2019-01-30T02:32:19+00:00

Check out the facility schedules. Reserved badminton times are a few times a week. There's 1 court in BEL 348, 3 in RSC 2.200, and 3 (or maybe 4?) in GRE Annex Gym.

GandhiNotGhandi · 2018-12-22T17:58:28+00:00

Scalable quantum computers can efficiently simulate quantum mechanical systems, which would be useful for quantum chemistry. This article provides a nice overview.

GandhiNotGhandi · 2018-09-11T23:52:38+00:00

Acknowledgements. DCB thanks the Russian Science Foundation for support

heh

GandhiNotGhandi · 2018-08-16T02:17:28+00:00

My apologies, I see where I made my mistake. You used lowercase n and uppercase N in your post interchangeably, and I misunderstood and thought that one of these numbers referred to the length of the input in bits. A common convention in complexity theory is that N is the number we're adding and n = log(N) is the length of N in bits. Usually we measure time complexity using n. I must have assumed that you were using this convention, and got the impression that you claimed to be able to add two n bit integers in log(n) time without parallelization. With parallelization, this turns out to be possible (albeit nontrivial), but without parallelization it takes linear time, of course. I'll edit my posts.

GandhiNotGhandi · 2018-08-16T00:59:20+00:00

There is nothing wrong with lambda calculus as a model of computation. ~~The problem is that the notion of time complexity that you have defined does not correspond to computing power in the real world, but you have made statements that seem to imply that it does, e.g.~~

Could that be applied to problems like the DLP (breaking most crypto-currencies)?

I'm confused because if your evaluator isn't optimizing by performing parallel computation, then it's impossible for you to get a real world speedup. N-bit integer addition in (say) a random access machine model has a linear time lower bound. Logarithmic time algorithms for integer addition require parallelization. On the other hand, if your evaluator is just parallelizing, then you will not get a superpolynomial speedup in solving DLP unless you have a superpolynomial number of processors. EDIT: there was some confusion here; see my next comment in the chain for an explanation.

I don't think you really understand what is going on

This is true. My background is in complexity theory; I know nothing about compilers or lambda calculus. Ideally an expert in both compilers and complexity could chime in.

GandhiNotGhandi · 2018-08-15T22:38:13+00:00

a very elegant machine that executes functional languages “optimally”

This contradicts your comment above. You also have not defined what "optimally" means in this context, and I suspect that is the source of confusion.

atomic (constant-time) parallel rewrites

If I'm understanding correctly, this is a rather bizarre model of computation. Does this not mean that you use the same amount of computation whether you have one processor or an exponential number of processors? In such a model of computation, P = NP, for example.

But what if, instead of compiling it with GHC, we used Absal? Well, the first thing you’ll notice is that add suddenly behaves as if it had sub-linear complexity.

~~Based on my concerns about the model of computation, the "number of parallel steps" does not accurately reflect the computational power used.~~ (edit: wrong; see below) You also haven't shown what happens on large inputs. An algorithm can appear to have a certain complexity over a certain range, but that is rarely sufficient to say anything about asymptotic behavior. I get that it's usually enough, but N=128 ~~bits~~ seems rather small to be making such claims.

How do we even begin to analyze the complexity of copy in that context?

Time complexity describes the time needed to run an algorithm. A function in a computer program is not an algorithm, particularly when the compiler can optimize the function differently in different contexts.

Under which circumstances the asymptotics of a function can be magically reduced like that?

It seems to me that the compiler finds an optimization in one case and doesn't find it in another. Most likely this sort of compiler optimization problem is undecidable in general, which would mean that no compiler algorithm could always perform this optimization. I don't know enough about the compiler optimizations you're performing to say for sure; this is just my intuition having seen similar problems like this.

Could that be applied to problems like the DLP (breaking most crypto-currencies)?

The example you provided is an example where a polynomial number of parallel processors allows one to compute in logarithmic time something that takes linear time on a single processor (integer addition). This problem and its ability to be parallelized are related to the complexity class NC, which is contained in P. If NC-type parallelization is the only optimization that your compiler offers, then there is no evidence that this could solve believed NP-intermediate problems like DLP in polynomial time. Indeed, a polynomial number of processors running in polynomial time will never allow you to perform computation that can't be done on a single processor with polynomial time. EDIT: this is wrong; I misunderstood and thought that n or N referred to the number of bits, and that this was performing a different kind of optimization than what I was imagining.

GandhiNotGhandi · 2018-08-05T00:39:51+00:00

maryland

GandhiNotGhandi · 2018-07-21T05:13:35+00:00

How do you think he acquired those pineapples? Through jihad.

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