# Exp(x) is CKKS without ChebyshevFunction

**URL:** <https://openfhe.discourse.group/t/exp-x-is-ckks-without-chebyshevfunction/1437>\
**Category:** FHE Questions\
**Created:** [July 22, 2024, 2:50am UTC](https://openfhe.discourse.group/t/exp-x-is-ckks-without-chebyshevfunction/1437 "2024-07-22T02:50:42Z")\
**Posts on this page:** 3\
**Page:** 1

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**Author:** ![sumw](https://avatars.discourse-cdn.com/v4/letter/s/e480ec/32.png) [@sumw](https://openfhe.discourse.group/u/sumw)\
**Post date:** [July 22, 2024, 2:50am UTC](https://openfhe.discourse.group/t/exp-x-is-ckks-without-chebyshevfunction/1437/1 "2024-07-22T02:50:42Z")

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Since ChebyshevFunction requires relatively large parameters, is there a way in CKKS to evaluate exp(x) without using ChebyshevFunction?

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**Author:** ![lujoho](https://avatars.discourse-cdn.com/v4/letter/l/a587f6/32.png) [@lujoho](https://openfhe.discourse.group/u/lujoho)\
**Post date:** [July 22, 2024, 11:42am UTC](https://openfhe.discourse.group/t/exp-x-is-ckks-without-chebyshevfunction/1437/2 "2024-07-22T11:42:07Z")

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Hi,  
I suggest reading [this](https://doi.org/10.1007/s10207-023-00781-0) paper.  
You can approximate the exponential function with a truncated Taylor series. Depending on the application, you can use a reduction that allows you to achieve faster convergence at the expense of slightly greater depth. This is explained in more detail in the paper.

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**Author:** ![sumw](https://avatars.discourse-cdn.com/v4/letter/s/e480ec/32.png) [@sumw](https://openfhe.discourse.group/u/sumw)\
**Post date:** [July 22, 2024, 2:39pm UTC](https://openfhe.discourse.group/t/exp-x-is-ckks-without-chebyshevfunction/1437/3 "2024-07-22T14:39:53Z")

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Thanks for your reply! This is very helpful.