LEADER 02586nam0 22005293i 450 001 VAN00234374 005 20240806101335.261 017 70$2N$a9783030775629 100 $a20211112d2021 |0itac50 ba 101 $aeng 102 $aCH 105 $a|||| ||||| 200 1 $aˆThe ‰Calabi?Yau Landscape$efrom Geometry, to Physics, to Machine Learning$fYang-Hui He 210 $aCham$cSpringer$d2021 215 $axvii, 206 p.$cill.$d24 cm 461 1$1001VAN00102250$12001 $aLecture notes in mathematics$1210 $aBerlin [etc.]$cSpringer$v2293 500 1$3VAN00234375$aˆThe ‰Calabi?Yau Landscape : from Geometry, to Physics, to Machine Learning$91907598 606 $a14-XX$xAlgebraic geometry [MSC 2020]$3VANC019702$2MF 606 $a14Qxx$xComputational aspects in algebraic geometry [MSC 2020]$3VANC020815$2MF 606 $a81T30$xString and superstring theories; other extended objects (e.g., branes) in quantum field theory [MSC 2020]$3VANC021514$2MF 606 $a81T33$xDimensional compactification in quantum field theory [MSC 2020]$3VANC036537$2MF 606 $a81T35$xCorrespondence, duality, holography (AdS/CFT, gauge/gravity, etc.) [MSC 2020]$3VANC036538$2MF 610 $aAlgebraic geometry in physics$9KW:K 610 $aCalabi-Yau Compactifications$9KW:K 610 $aComplex geometry in physics$9KW:K 610 $aComputational algebraic geometry$9KW:K 610 $aGap$9KW:K 610 $aMacaulay2$9KW:K 610 $aMachine learning in algebraic geometry$9KW:K 610 $aPython Tensorflow$9KW:K 610 $aQuiver representation$9KW:K 610 $aSageMath$9KW:K 610 $aSingular$9KW:K 610 $aString Theory$9KW:K 610 $aSupersymmetry$9KW:K 610 $aWolfram Mathematica$9KW:K 620 $aCH$dCham$3VANL001889 700 1$aHe$bYang-Hui$3VANV194088$0846256 712 $aSpringer $3VANV108073$4650 801 $aIT$bSOL$c20240906$gRICA 856 4 $uhttp://doi.org/10.1007/978-3-030-77562-9$zE-book ? Accesso al full-text attraverso riconoscimento IP di Ateneo, proxy e/o Shibboleth 912 $fN 912 $aVAN00234374 950 $aBIBLIOTECA DEL DIPARTIMENTO DI MATEMATICA E FISICA$d08CONS e-book 2293 $e08LNM2293 20211112 950 $aBIBLIOTECA DEL DIPARTIMENTO DI MATEMATICA E FISICA$d08CONS e-book 8438 $e08eMF8438 20240503 996 $aCalabi?Yau Landscape : from Geometry, to Physics, to Machine Learning$91907598 997 $aUNICAMPANIA