Anna Rose O'Sullivan

Anna Rose O'Sullivan (born 16 April 1994) is an English ballet dancer and is a first soloist at the Royal Ballet.[1]

Anna Rose O'Sullivan
as Clara in The Nutcracker (2018)
Born (1994-04-16) 16 April 1994
Harrow, London, England
NationalityBritish
EducationThe Royal Ballet
OccupationBallet dancer
Current groupThe Royal Ballet

Early life

O'Sullivan was born in Harrow, London and raised in Ickenham. Her father is a construction contracts manager and her mother works in the NHS. She has two younger brothers and a younger sister. She started dance at age two, and performed with London Children's Ballet. She has also performed in musical theatre, and appeared as Cosette in Les Misérables and in Chitty Chitty Bang Bang on the West End.[1][2] She entered The Royal Ballet School at age 11.[3]

Career

O'Sullivan graduated into The Royal Ballet in 2012. In 2015, she danced her first major role, Clara in The Nutcracker. Her performance was endorsed by Peter Wright, the production's choreographer.[4] She was named First Artist in 2016, Soloist in 2017 and First Soloist 2019. Her first principal role was Alice in Alice's Adventures in Wonderland, and she went on to portray other lead roles such as Juliet in Romeo and Juliet, Princess Aurora in The Sleeping Beauty and Swanida in Coppelia.[1][5]

Selected repertoire

O'Sullivan's repertoire with The Royal Ballet includes:[1]

Created roles

gollark: I didn't do any horrible homoglyph hacks with THAT.
gollark: It uses the function, yes.
gollark: So, I finished that to highly dubious demand. I'd like to know how #11 and such work.
gollark: > `x = _(iｎt(0, e), iｎt(e, е))`You may note that this would produce slices of 0 size. However, one of the `e`s is a homoglyph; it contains `2 * e`.`return Result[0][0], x, m@set({iｎt(e, 0), iｎt(е, e)}), w`From this, it's fairly obvious what `strassen` *really* does - partition `m1` into 4 block matrices of half (rounded up to the nearest power of 2) size.> `E = typing(lookup[2])`I forgot what this is meant to contain. It probably isn't important.> `def exponentiate(m1, m2):`This is the actual multiplication bit.> `if m1.n == 1: return Mаtrix([[m1.bigData[0] * m2.bigData[0]]])`Recursion base case. 1-sized matrices are merely multiplied scalarly.> `aa, ab, ac, ad = strassen(m1)`> `аa, аb, аc, аd = strassen(m2)`More use of homoglyph confusion here. The matrices are quartered.> `m = m1.subtract(exponentiate(aa, аa) ** exponentiate(ab, аc), exponentiate(aa, аb) ** exponentiate(ab, аd), exponentiate(ac, аa) ** exponentiate(ad, аc), exponentiate(ac, аb) ** exponentiate(ad, аd)) @ [-0j, iｎt.abs(m2.n * 3, m1.n)]`This does matrix multiplication in an inefficient *recursive* way; the Strassen algorithm could save one of eight multiplications here, which is more efficient (on big matrices). It also removes the zero padding.> `m = exponentiate(Mаtrix(m1), Mаtrix(m2)) @ (0j * math.sin(math.asin(math.sin(math.asin(math.sin(math.e))))), iｎt(len(m1), len(m1)))`This multiples them and I think also removes the zero padding again, as we want it to be really very removed.> `i += 1`This was added as a counter used to ensure that it was usably performant during development.> `math.factorial = math.sinh`Unfortunately, Python's factorial function has really rather restrictive size limits.> `for row in range(m.n):`This converts back into the 2D array format.> `for performance in sorted(dir(gc)): getattr(gc, performance)()`Do random fun things to the GC.
gollark: > `globals()[Row + Row] = random.randint(*sys.version_info[:2])`Never actually got used anywhere.> `ε = sys.float_info.epsilon`Also not used. I just like epsilons.> `def __exit__(self, _, _________, _______):`This is also empty, because cleaning up the `_` global would be silly. It'll be overwritten anyway. This does serve a purpose, however, and not just in making it usable as a context manager. This actually swallows all errors, which is used in some places.> `def __pow__(self, m2):`As ever, this is not actual exponentiation. `for i, (ι, 𐌉) in enumerate(zip(self.bigData, m2.bigData)): e.bigData[i] = ι + 𐌉` is in fact just plain and simple addition of two matrices.> `def subtract(forth, 𝕒, polynomial, c, vector_space):`This just merges 4 submatrices back into one matrix.> `with out as out, out, forth:`Apart from capturing the exceptions, this doesn't really do much either. The `_` provided by the context manager is not used.> `_(0j, iｎt(0, 𝕒.n))`Yes, it's used in this line. However, this doesn't actually have any effect whatsoever on the execution of this. So I ignore it. It was merely a distraction.> `with Mаtrix(ℤ(ℤ(4))):`It is used again to swallow exceptions. After this is just some fluff again.> `def strassen(m, x= 3.1415935258989):`This is an interesting part. Despite being called `strassen`, it does not actually implement the Strassen algorithm, which is a somewhat more efficient way to multiply matrices than the naive way used in - as far as I can tell - every entry.> `e = 2 ** (math.ceil(math.log2(m.n)) - 1)`This gets the next power of two in a fairly obvious way. It is used to pad out the matrix to the next power of 2 size.> `with m:`The context manager is used again for nicer lookups.> `Result[0] += [_(0j, iｎt(e, e))]`Weird pythonoquirkiness again. You can append to lists in tuples with `+=`, but it throws an exception as they're sort of immutable.> `typing(lookup[4])(input())`It's entirely possible that this does things.

References
  1. "Anna Rose O'Sullivan". Royal Opera House. Retrieved 27 April 2020.
  2. "Anna Rose O'Sullivan interview: 'There's a difference between wanting to reach your full potential and getting to the top'". Evening Standard. 27 November 2020.
  3. "A day in the life: Anna Rose O'Sullivan". Bloch. 23 January 2020.
  4. "Anna Rose O'Sullivan: I dreamed of dancing in Darcey Bussell's shoes... now I'm the Royal Ballet lead in The Nutcracker". Evening Standard. 4 December 2015.
  5. "Cupcakes & Conversation with Anna Rose O'Sullivan, Soloist, The Royal Ballet". Ballet News. 19 April 2018.
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