{"id":169,"date":"2006-09-28T11:07:03","date_gmt":"2006-09-28T11:07:03","guid":{"rendered":"http:\/\/scientopia.org\/blogs\/goodmath\/2006\/09\/28\/computing-square-roots-on-paper\/"},"modified":"2006-09-28T11:07:03","modified_gmt":"2006-09-28T11:07:03","slug":"computing-square-roots-on-paper","status":"publish","type":"post","link":"http:\/\/www.goodmath.org\/blog\/2006\/09\/28\/computing-square-roots-on-paper\/","title":{"rendered":"Computing Square Roots on Paper"},"content":{"rendered":"<p>To do a square root on an abacus, you use partitions to do a paper algorithm for square root using the abacus. The catch is that most people don&#8217;t even *remember* how to do square roots on paper, if they ever learned it at all. (In fact, in school, *I* didn&#8217;t learn the classical paper algorithm; we never really did roots on paper; the closest we did was using square root as an example of Newton&#8217;s method. Like so much of  my basic math, I learned this from my father.)<br \/>\nSo, for your entertainment and edification, today, I&#8217;ll describe the classical algorithm for computing square roots on paper. I&#8217;ll also show you just why it works.<\/p>\n<p><!--more--><br \/>\nSuppose you want to take the square root of *n*. Start by writing down *n*. The algorithm is going to work using *pairs* of digits, so you need to divide the number into *pairs* of digits. A pair *can&#8217;t* cross the decimal point, so start at the decimal, and break into pairs going both right and left. If you don&#8217;t have enough digits, you pad out the ends with zeros.<br \/>\nSo let&#8217;s do that much with an example, Let&#8217;s say we wanted to take the square root of 513.5. The pairing would look like:<\/p>\n<pre>\n05 13. 20\n<\/pre>\n<p>Now, start with the first pair, and approximate: what&#8217;s the single digit that is *closest* to being the square root of that pair? Write that down *above* the first pair. Then take the square of that digit, and write it *beneath* the pair, and subtract.<br \/>\nSo with our example, the first pair is &#8220;05&#8221;. The closest single digit approximation of the square root is &#8220;2&#8221;. So we&#8217;d write &#8220;2&#8221; above the &#8220;05&#8221;; and &#8220;4&#8221; beneath it, and subtract. The number on *top* of the radical is the current root estimate, which we&#8217;ll call *est*; the result of the subtraction is the current remainder.<\/p>\n<pre>\n2\n\/--------\n\/ 05 13. 20\n4\n----\n1\n<\/pre>\n<p>That&#8217;s the setup. Now we get to the part where we iterate. We&#8217;ll take the next pair from the number we&#8217;re taking the square root of, pull it down, and write it next to the current remainder. The current remainder concatenated with those two digits is the *target number* for this iteration, which we&#8217;ll call *t*. What we want to do in the iteration is find a number *x* for which (20&times;*est*+n)&times;n &le; t. That number *x* will be the next digit of the square root. So we&#8217;ll write *x* on top of the radical as the next digit; and subtract (20&times;*est*+x)&times;x from the target.<br \/>\nSo we take the *est*, multiply it by 20; and write it down next to the current target:<\/p>\n<pre>\n2\n\/--------\n\/ 05 13. 20\n4\n----\n(40)  1 13\n<\/pre>\n<p>Now, we need to approximate again. What&#8217;s the largest *x* for which (40+x)&times;x &le; 113? 3&times;43=123, so 3 is too large. 2&times;42=84. So the next digit is two. So we write 2 on top of the radical, and subtract 84 from the target. Then we pull down the next two digits, and repeat.<\/p>\n<pre>\n2 2<br \/>\n\/--------------<br \/>\n\/ 05 13. 20<br \/>\n4<br \/>\n----<br \/>\n(40)  113<br \/>\n84<\/p>\n","protected":false},"excerpt":{"rendered":"<p>To do a square root on an abacus, you use partitions to do a paper algorithm for square root using the abacus. The catch is that most people don&#8217;t even *remember* how to do square roots on paper, if they ever learned it at all. (In fact, in school, *I* didn&#8217;t learn the classical paper [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"jetpack_post_was_ever_published":false,"_jetpack_newsletter_access":"","_jetpack_dont_email_post_to_subs":false,"_jetpack_newsletter_tier_id":0,"_jetpack_memberships_contains_paywalled_content":false,"_jetpack_memberships_contains_paid_content":false,"footnotes":"","jetpack_publicize_message":"","jetpack_publicize_feature_enabled":true,"jetpack_social_post_already_shared":false,"jetpack_social_options":{"image_generator_settings":{"template":"highway","default_image_id":0,"font":"","enabled":false},"version":2}},"categories":[34],"tags":[],"class_list":["post-169","post","type-post","status-publish","format-standard","hentry","category-manual-computing-devices"],"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_shortlink":"https:\/\/wp.me\/p4lzZS-2J","jetpack_sharing_enabled":true,"jetpack_likes_enabled":true,"_links":{"self":[{"href":"http:\/\/www.goodmath.org\/blog\/wp-json\/wp\/v2\/posts\/169","targetHints":{"allow":["GET"]}}],"collection":[{"href":"http:\/\/www.goodmath.org\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"http:\/\/www.goodmath.org\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"http:\/\/www.goodmath.org\/blog\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"http:\/\/www.goodmath.org\/blog\/wp-json\/wp\/v2\/comments?post=169"}],"version-history":[{"count":0,"href":"http:\/\/www.goodmath.org\/blog\/wp-json\/wp\/v2\/posts\/169\/revisions"}],"wp:attachment":[{"href":"http:\/\/www.goodmath.org\/blog\/wp-json\/wp\/v2\/media?parent=169"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"http:\/\/www.goodmath.org\/blog\/wp-json\/wp\/v2\/categories?post=169"},{"taxonomy":"post_tag","embeddable":true,"href":"http:\/\/www.goodmath.org\/blog\/wp-json\/wp\/v2\/tags?post=169"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}