Another Round of Fillers Begin!

Unlike last year, we have a lot of posts to publish this year to reach the magic number.

But we hope it is possible and the quest to do that has already started with the previous post. It may not have felt like a filler so this post will take care of that feeling.

A lot of things have happened this year, mostly unpleasant (both academic and social/personal), which deserve their own posts, but my Superpartner convinced me to postpone making those “public” right after they’d happened so for now I’ll leave those events be.

A few pleasant things did manage to happen this year:

1. Getting a paper published with half a dozen authors whose initials form AB²J²M (the second J being me).

2. Making a barebones AcBook app for Android (+Win10 UWP) which only my Superpartner and my nephew use. More on this in a later filler.

3. Visiting IMSc, Chennai (twice) including Sujay’s treat at the “Little Italy”; HRI, Allahabad (once); IISER TVM (once).

4. Putting up a paper on arXiv “rubbishing” another paper, whose authors did not bother to correct their misleading claims about our earlier papers (including other related papers). More on this in a later filler.

5. Giving half a dozen lectures on “Supersymmetry” at S.N. Bose Centre, the new institute I joined as a postdoc after SINP.

So that’s it for now and look forward (or don’t) to other fillers appearing almost daily till the end of this year.😀

A Tale by Bob Mortimer

The Seasons

I recently finished watching the 3^rd season of Marvelous Mrs. Maisel & The Crown. The season 3 of Mrs. Maisel was much more musical this time. I totally liked it, not sure about my Superpartner though and on beautiful days like today, I listen to all the songs from all the episodes in a loop. It is these rare occasions when I understand the lyrics without having to listen to the songs over and over again. Most of the songs chosen in the Series have simple lyrics and are slow in the rhythm, sort of my taste. I have many personal favorites but here is one for you to listen and sing along.

Maybe I'm right, and maybe I'm wrong
And maybe I'm weak, and maybe I'm strong
But nevertheless, I'm in love, with you

Maybe I'll win, and maybe I'll lose
And maybe I'm in for crying the blues
But nevertheless, I'm in love, with you

Somehow, I know at a glance
The terrible chances I'm taking
Fine at the start, then left with a heart that is breaking

Maybe I'll live a life of regret,
And maybe I'll give much more than I'll get
But nevertheless, I'm in love with you

Somehow, I know at a glance
The terrible chances I'm taking
Fine at the start, then left with a heart that is breaking

Maybe I'll live a life of regret,
And maybe I'll give much more than I'll get
But nevertheless, I'm in love with you
But nevertheless, I'm in love with you

– The Mills Brothers
[Song featured in the MGM movie – Three Little Words]

Great Shayari Once More

Not sure if we will reach the magic number of posts this year but let me publish one to start, anyway.

This year has been an interesting point in my life, both personally and professionally. I have been recently diagnosed with middle-age, less-than-average-functioning body organs and couldn’t-care-less-attitude. In short, haven’t got many years left to live, which is a good thing given the state of this world.

With that internal note out of the way, let me translate a couple of ghazals by the great poet Shakeel Azmi. Giving credit where credit is due, read the tab above marked “Shayari” first and then let’s crack on with the first Ghazal.

कहानी जिसकी थी उसके ही जैसा हो गया था मैं
तमाशा करते करते खुद तमाशा हो गया था मैं

Kahaani jiski thi uske hi jaisa ho gaya tha main
Tamaasha karte karte khud tamaasha ho gaya tha main

I became just like them, whom-so-ever's story it was
Playing so many dramas, a drama was what I'd become

न मेरा नाम था न दाम बाजार-ए-मोहब्बत में
बस उसने भाव पूछा और महंगा हो गया था मैं

Na mera naam tha na daam bazaar-e-mohabbat mein
Bas usne bhaav puchha aur mahanga ho gaya tha main

Neither had I fame nor wealth in the market-of-love
She just asked price, and valuable was what I'd become

बितादी उम्र मैंने उसकी एक आवाज सुनने में
उसे जब बोलना आया तो बहरा हो गया था मैं

Bitaadi umra maine uski ek awaaz sunne mein
Use jab bolna aaya to bahra ho gaya tha main

Spent my whole life expecting to hear her speak once
When she was able to speak, deaf was what I'd become

बुझा तो खुद में एक चिंगारी भी बाकी नहीं रखी
उसे तारा बनाने में अंधेरा हो गया था मैं

Bujha to khud mein ek chingaari bhi baaki nahin rakhi
Use taara banaane mein andhera ho gaya tha main

No sparks were left in me when I got extinguished
To make her a star, darkness was what I'd become

खुद को ढूंढ कर एक रोज गोली मार दी मैंने
जिसे चाहा उसी की जान का खतरा हो गया था मैं

Khud ko dhoondh kar ek roz goli maar di maine
Jise chaaha usi ki jaan ka khatra ho gaya tha main

Having searched, I found and shot myself one day
For my loved one's life, danger was what I'd become

That went in quite a different direction by the end so let us start a second Ghazal:

शाम होने को है घर जाते हैं
अब बुलंदी से उतर जाते हैं

Shaam hone ko hai ghar jaate hain
Ab bulandi se utar jaate hain

It's about dusk, let's go home
Now, let us get off the summit

ज़िंदगी सामने मत आया कर
हम तुझे देख कर डर जाते हैं

Zindagi saamne mat aaya kar
Ham tujhe dekh kar dar jaate hain

Life, do not confront me
I get scared at your sight

ख़ाब क्या देखें थके हारे लोग
ऐसे सोते हैं की मर जाते हैं

Khaab kya dekhen thake haare log
Aise sote hain ki mar jaate hain

How can the tired dream?
They sleep and they die

Well, not quite a full-fledged Ghazal, but here is a bonus Sher and a great one at that:

उसे भूला भी दिया याद भी रखा उसको
नशा उतार दिया ख़ुमार रहने दिया

Use bhula bhi diya yaad bhi rakha usko
Nasha utaar diya khumaar rahne diya

I forgot her and kept her in memories too
Hangover cured but intoxication retained

– शकील आज़मी (Shakeel Azmi)

That’s all for this post. Till the next one,

Discover more of Azmi’s Shayari

Sketchbook 208

This is the last chapter of Sketchbook. It was released on 25th June and the great saga of Art Club has ended with that. This chapter is special as it does not follow the usual 4-panel style. Most probably, it tells the story of the last day of the students at the school, their graduation, their future, and so on. They also seem to be preparing a feast in the club room. The last page has Sora sitting beside a sketch of all her friends, colleagues and teachers.

An era has ended with the end of Sketchbook. My life won’t be the same anymore. No more looking forward to 25th of each month to ‘read’ less than a dozen pages of supposed hilarity, trivialities and enlightenment about bugs, insects, plants and life in general. This was a true slice of life manga. The manga which I could relate to because of my life experiences whether in school or otherwise. All characters felt like they were part of me and in turn, it felt like I was a part of the manga.

I could have been Sora trying to find some courage to speak to a stranger. I could have been Natsumi trying to be carefree. I could have been Hazuki trying to save some money. I could have been Kokage trying to be dark and witty. I could have been Nagisa trying to be knowledgeable about everything and Juju trying to remain calm in the presence of caterpillars. I could never be the SuzuKaze combo but could have been Fuu and Ryou trying to be resourceful just for the hell of it. I could have been Asaka trying to never fail in my endeavours and Daichi trying to convince others that I AM NOT ANGRY! I could have been Kate trying to see the funny or dumb side of things. I could have been Asakura-Sensei trying to be an adult among kids, Kasugano-Sensei trying to be a child among adults and the President (Ujou) trying to be just the right person among all. I could have been Takane and Kei trying to avoid extra-curricular activities. I could have been Minamo trying to learn photography. I could have been Ao trying to help my sister in the kitchen. I could have been Tsukiyo trying to vanish in the background of this world.

The last volume 14 of Sketchbook should be released in a few months. Will share it as and when I get my hands on it. For now, I leave you with the

Official Website

Bibliography Style

This is a self-promotion, very much like this post about AcBook was. I have ‘created’ a new bibliography style for papers typeset in $\LaTeX$ called “hephys”, which can be used by theoretical High Energy Physicists who use BibTeX (data mostly obtained from inSpireHEP) to include the references in their papers. For more details, head over to my ‘Physics Blog’. For less details, check the tab above titled ‘LaTeX’. For those who just want to get hold of the style file, here’s ‘hephys’.

As a side note, if you want to input Greek characters and other mathematical symbols (like →⊕⊗∈∑∏←) in the $\LaTeX$ files directly, you can download the Unicode Keyboard Layout I created for Windows. [For macOS, head over to Warren Siegel’s ‘Unicode’ webpage.] This .zip folder also includes a .pdf ‘manual’ that you should go through at least once. As a disclaimer, this is still $\LaTeX$ code. If you want cutting / bleeding edge code, get hold of Lua$\LaTeX$ code available from Warren Siegel’s ‘TeX’ webpage.

That’s it for this year from us, till next year

Keep Storytelling!

It’s Greek to Me!

Recently I looked at the Greek alphabets more keenly. I need to know them myself clearly before teaching them to Sakura.😉 I was reminded that there exists such a keyboard prepared by Him. It works with Shift & Ctrl+Alt combinations to get the small & capital letters in Greek. The mapping is below:

a	α
b	β
c	χ
d	δ
e	ε
f	φ
g	γ
h	η
i	ι
j	ψ
k	κ
l	λ
m	μ
n
o	o
p	π
q	θ
r	ρ
s	σ
t	τ
u
v	ν
w	ω
x	ξ
y	υ
z	ζ

The keyboard layout of the same is:

Now that I was looking at things keenly, I realized the Greek alphabets could be made to match the English ones more closely and I made one on my own which looks like:

a	α
b	β
c	χ
d	δ
e	ε,η
f	φ
g	γ
h
i	ι
j
k	κ
l	λ
m	μ
n	ν
o	o,ω
p	π
q
r	ρ
s	σ,ψ
t	θ,τ
u	υ
v
w
x	ξ
y
z	ζ

I know the above is not a one-to-one mapping but it ‘sounds’ all right to me.😊

See you tomorrow!

Let the Fillers Begin!

That’s how it’s going to be again this year.

Three posts during the last three days of the year.

And, as is usual, the content of the filler posts is not much to write about.

We will just agree that something important was said and something important was understood.

There is a lot of backlog in my life right now: Writing emails, Watching Christmas/New Year TV show specials, Doing research, Enjoying life with family, Writing paper(s), Teaching my daughter group theory, etc.

Obviously, some are easier than others but I have yet to optimize their order of execution. In the mean time, writing 3 blog posts is another backlog that we have to deal with urgently. So here we have accomplished 1/3 of that job. As we wait for the remaining 2/3,

Wonder Why?

Sketchbook Slices…

Keeping my stream of consciousness flowing, here are some snapshots of Sketchbook Vol 13:

Ooba senpai interacting with Kuga-senpai and Ryou-senpai.

The interaction continues but we also see that Kuma struggles to ‘fit’ in the Kamiya household!

Hazuki cooking and Asaka timing…

Takane & Kei parodying(?)…

Sketchbook Art Club’s Night Out.

Hazuki overthinking and Asaka being her usual self.

Sora figuring out stuff!

And here we stop.

Looking forward to year end.

Confusion Matrix…

I completed a Machine Learning course by Andrew NG on Coursera nearly 2 months ago, a course with an enrollment of 1.7mn people apparently. Not sure what the ‘course completion %’ is, though. Thanks to the course, I was able to revise some basics, primarily the math and intuition behind Machine Learning models. After you build a model, one of the important metrics by which people judge your model is the model accuracy. The problem is that there are so many of these evaluation metrics that quite often someone asks me to give a feedback on my model using a different accuracy metric.

In a typical classification problem solved using Machine learning techniques, the outputs can be represented in a 2x2 matrix form which is called the ‘Confusion matrix’, shown below:-

1) Sensitivity = TP/(TP+FN) = TP/P
A useful metric when you are interested in predicting the positives right. Tests in Medical diagnosis are a good example. We wish to have as less false negatives as possible, i.e., no room for non-identification of a disease when the test is conducted.

2) Specificity = TN/(TN+FP) = TN/N
A useful metric when you wish to have the negatives right. Follow-up tests in Medical diagnosis are the best example. We don’t want to start treatment on people who don’t have the disease in the first place.

3) Precision = TP/(TP+FP)
A metric that tells you how precise is your prediction on the positives.

4) Recall = Sensitivity
Another fancy name for Sensitivity.

5) True Negative% = Specificity*100
Just a different name for Specificity.

6) True Positive% = Recall*100
Again, just a different name for sensitivity but more intuitive.

7) Accuracy = (TP+TN)/(TP+FN+FP+TN)
Helps to know what percentage of the predictions are correct. The limitation of this metric is in the cases of rare events. Say for example, 1% of the population has heart related diseases and the model predicts that none of them have heart diseases, the accuracy of the model will still be 99%.

8) F1-score = (2*Precision*Sensitivity)/(Precision+Sensitivity)
A good metric because it penalizes if you have got either high False positives or False Negatives.

Of course, we would like to have all these metrics as high as possible (close to 1 / near 100%) and that simply means our model is very good. The thing to wonder about is that if this 2x2 matrix can create so many evaluation metrics (many not shared above), how sophisticated/complicated is this evaluation business!