{
  "index": "1986-A-6",
  "type": "ALG",
  "tag": [
    "ALG",
    "COMB"
  ],
  "difficulty": "",
  "question": "Let $a_1, a_2, \\dots, a_n$ be real numbers, and let $b_1, b_2, \\dots,\nb_n$ be distinct positive integers. Suppose that there is a polynomial\n$f(x)$ satisfying the identity\n\\[\n(1-x)^n f(x) = 1 + \\sum_{i=1}^n a_i x^{b_i}.\n\\]\nFind a simple expression (not involving any sums) for $f(1)$ in terms\nof $b_1, b_2, \\dots, b_n$ and $n$ (but independent of $a_1, a_2,\n\\dots, a_n$).",
  "solution": "Solution 1. For \\( j \\geq 1 \\), let \\( (b)_{j} \\) denote \\( b(b-1) \\cdots(b-j+1) \\). For \\( 0 \\leq j \\leq n \\), differentiating the identity \\( j \\) times and putting \\( x=1 \\) (or alternatively substituting \\( x=y+1 \\) and equating coefficients) yields\n\\[\n\\begin{aligned}\n0 & =1+\\sum a_{i} \\\\\n0 & =\\sum a_{i} b_{i} \\\\\n0 & =\\sum a_{i}\\left(b_{i}\\right)_{2} \\\\\n& \\vdots \\\\\n0 & =\\sum a_{i}\\left(b_{i}\\right)_{n-1} \\\\\n(-1)^{n} n!f(1) & =\\sum a_{i}\\left(b_{i}\\right)_{n}\n\\end{aligned}\n\\]\n\nIn other words, \\( A \\mathbf{v}=0 \\), where\n\\[\nA=\\left(\\begin{array}{ccccc}\n-1 & 1 & 1 & \\cdots & 1 \\\\\n0 & b_{1} & b_{2} & \\cdots & b_{n} \\\\\n0 & \\left(b_{1}\\right)_{2} & \\left(b_{2}\\right)_{2} & \\cdots & \\left(b_{n}\\right)_{2} \\\\\n\\vdots & \\vdots & \\vdots & \\ddots & \\vdots \\\\\n0 & \\left(b_{1}\\right)_{n-1} & \\left(b_{2}\\right)_{n-1} & \\cdots & \\left(b_{n}\\right)_{n-1} \\\\\n(-1)^{n} n!f(1) & \\left(b_{1}\\right)_{n} & \\left(b_{2}\\right)_{n} & \\cdots & \\left(b_{n}\\right)_{n}\n\\end{array}\\right) \\quad \\text { and } \\quad \\mathbf{v}=\\left(\\begin{array}{c}\n-1 \\\\\na_{1} \\\\\na_{2} \\\\\n\\vdots \\\\\na_{n}\n\\end{array}\\right)\n\\]\n\nSince \\( \\mathbf{v} \\neq 0 \\), \\( \\operatorname{det} A=0 \\). Since \\( (b)_{j} \\) is a monic polynomial of degree \\( j \\) in \\( b \\) with no constant term, we can add a linear combination of rows \\( 2,3, \\ldots, k \\) to row \\( k+1 \\), for \\( 2 \\leq k \\leq n \\), to obtain\n\\[\nA^{\\prime}=\\left(\\begin{array}{ccccc}\n-1 & 1 & 1 & \\cdots & 1 \\\\\n0 & b_{1} & b_{2} & \\cdots & b_{n} \\\\\n0 & b_{1}^{2} & b_{2}^{2} & \\cdots & b_{n}^{2} \\\\\n\\vdots & \\vdots & \\vdots & \\ddots & \\vdots \\\\\n0 & b_{1}^{n-1} & b_{2}^{n-1} & \\cdots & b_{n}^{n-1} \\\\\n(-1)^{n} n!f(1) & b_{1}^{n} & b_{2}^{n} & \\cdots & b_{n}^{n}\n\\end{array}\\right)\n\\]\n\nExpanding by minors along the first column yields \\( 0=\\operatorname{det} A^{\\prime}=-\\operatorname{det}\\left(V^{\\prime}\\right)+ \\) \\( n!f(1) \\operatorname{det}(V) \\) where\n\\[\nV=\\left(\\begin{array}{cccc}\n1 & 1 & \\cdots & 1 \\\\\nb_{1} & b_{2} & \\cdots & b_{n} \\\\\nb_{1}^{2} & b_{2}^{2} & \\cdots & b_{n}^{2} \\\\\n\\vdots & \\vdots & \\ddots & \\vdots \\\\\nb_{1}^{n-1} & b_{2}^{n-1} & \\cdots & b_{n}^{n-1}\n\\end{array}\\right) \\text { and } V^{\\prime}=\\left(\\begin{array}{cccc}\nb_{1} & b_{2} & \\cdots & b_{n} \\\\\nb_{1}^{2} & b_{2}^{2} & \\cdots & b_{n}^{2} \\\\\n\\vdots & \\vdots & \\ddots & \\vdots \\\\\nb_{1}^{n-1} & b_{2}^{n-1} & \\cdots & b_{n}^{n-1} \\\\\nb_{1}^{n} & b_{2}^{n} & \\cdots & b_{n}^{n}\n\\end{array}\\right)\n\\]\n\nFactoring \\( b_{i} \\) out of the \\( i \\) th column of \\( V^{\\prime} \\) shows that \\( \\operatorname{det}\\left(V^{\\prime}\\right)=b_{1} b_{2} \\cdots b_{n} \\operatorname{det}(V) \\). Hence \\( -b_{1} b_{2} \\cdots b_{n} \\operatorname{det}(V)+n!f(1) \\operatorname{det}(V)=0 \\). Since the \\( b_{i} \\) are distinct, \\( \\operatorname{det}(V) \\neq 0 \\) (see below). Thus \\( f(1)=b_{1} b_{2} \\cdots b_{n} / n \\) !.\n\nRemark (The Vandermonde determinant). The matrix \\( V \\) is called the Vandermonde matrix. Its determinant \\( D \\) is a polynomial of total degree \\( \\binom{n}{2} \\) in the \\( b_{i} \\), and \\( D \\) vanishes whenever \\( b_{i}=b_{j} \\) for \\( i>j \\), so \\( D \\) is divisible by \\( b_{i}-b_{j} \\) whenever \\( i>j \\). These \\( b_{i}-b_{j} \\) have no common factor, so \\( \\prod_{i>j}\\left(b_{i}-b_{j}\\right) \\) divides \\( D \\). But this product also has total degree \\( \\binom{n}{2} \\), and the coefficient of \\( b_{2} b_{3}^{2} \\cdots b_{n}^{n-1} \\) in \\( D \\) and in \\( \\prod_{i>j}\\left(b_{i}-b_{j}\\right) \\) both equal 1, so \\( D=\\prod_{i>j}\\left(b_{i}-b_{j}\\right) \\). In particular, if the \\( b_{i} \\) are distinct numbers, then \\( D \\neq 0 \\). See Problem 1941/14(ii) [PutnamI, p. 17] for an extension, and 1999B5 for another application.\n\nSolution 2. Subtract 1 from both sides, set \\( x=e^{t} \\), and expand the left-hand side in a power series. Since \\( 1-e^{t}=t+ \\) (higher order terms), we get\n\\[\n-1+(-1)^{n} f(1) t^{n}+(\\text { higher order terms })=\\sum_{i=1}^{n} a_{i} e^{b_{i} t}\n\\]\n\nThe right-hand side \\( F(t) \\) satisfies the linear differential equation\n\\[\nF^{(n)}(t)-\\left(b_{1}+\\cdots+b_{n}\\right) F^{(n-1)}(t)+\\cdots+(-1)^{n} b_{1} b_{2} \\cdots b_{n} F(t)=0\n\\]\nwith characteristic polynomial \\( p(z)=\\left(z-b_{1}\\right)\\left(z-b_{2}\\right) \\cdots\\left(z-b_{n}\\right) \\). On the other hand, from the left-hand side of (1) we see that \\( F(0)=-1, F^{(i)}=0 \\) for \\( i=1, \\ldots, n-1 \\), and \\( F^{(n)}(0)=(-1)^{n} f(1) n \\) !. Hence taking \\( t=0 \\) in (2) yields\n\\[\n(-1)^{n} f(1) n!-0+0-0+\\cdots+(-1)^{n} b_{1} b_{2} \\cdots b_{n}(-1)=0\n\\]\nso \\( f(1)=b_{1} b_{2} \\cdots b_{n} / n! \\).",
  "vars": [
    "a_1",
    "a_2",
    "a_n",
    "a_i",
    "f",
    "x",
    "j",
    "k",
    "A",
    "v",
    "V",
    "D",
    "F",
    "t",
    "p",
    "z",
    "i"
  ],
  "params": [
    "n",
    "b",
    "b_1",
    "b_2",
    "b_n",
    "b_i"
  ],
  "sci_consts": [
    "e"
  ],
  "variants": {
    "descriptive_long": {
      "map": {
        "a_1": "coeffone",
        "a_2": "coefftwo",
        "a_n": "coeffenn",
        "a_i": "coeffgen",
        "f": "polyfun",
        "x": "variable",
        "j": "iterind",
        "k": "rowindx",
        "A": "bigmatrix",
        "v": "vecentry",
        "V": "vandermn",
        "D": "vanddet",
        "F": "seriesfx",
        "t": "smallpar",
        "p": "charpoly",
        "z": "rootvar",
        "i": "summindx",
        "n": "countnum",
        "b": "basenum",
        "b_1": "baseone",
        "b_2": "basetwo",
        "b_n": "basenenn",
        "b_i": "basegen"
      },
      "question": "Let $coeffone, coefftwo, \\dots, coeffenn$ be real numbers, and let $baseone, basetwo, \\dots,\nbasenenn$ be distinct positive integers. Suppose that there is a polynomial\n$polyfun(variable)$ satisfying the identity\n\\[\n(1-variable)^{countnum} polyfun(variable) = 1 + \\sum_{summindx=1}^{countnum} coeffgen \\, variable^{basegen}.\n\\]\nFind a simple expression (not involving any sums) for $polyfun(1)$ in terms\nof $baseone, basetwo, \\dots, basenenn$ and $countnum$ (but independent of $coeffone, coefftwo,\n\\dots, coeffenn$).",
      "solution": "Solution 1. For \\( iterind \\geq 1 \\), let \\( (basenum)_{iterind} \\) denote \\( basenum(basenum-1) \\cdots(basenum-iterind+1) \\). For \\( 0 \\leq iterind \\leq countnum \\), differentiating the identity \\( iterind \\) times and putting \\( variable=1 \\) (or alternatively substituting \\( variable=y+1 \\) and equating coefficients) yields\n\\[\n\\begin{aligned}\n0 & =1+\\sum coeffgen \\\\\n0 & =\\sum coeffgen basegen \\\\\n0 & =\\sum coeffgen\\left(basegen\\right)_{2} \\\\\n& \\vdots \\\\\n0 & =\\sum coeffgen\\left(basegen\\right)_{countnum-1} \\\\\n(-1)^{countnum} countnum! \\, polyfun(1) & =\\sum coeffgen\\left(basegen\\right)_{countnum}\n\\end{aligned}\n\\]\n\nIn other words, \\( bigmatrix \\mathbf{vecentry}=0 \\), where\n\\[\nbigmatrix=\\left(\\begin{array}{ccccc}\n-1 & 1 & 1 & \\cdots & 1 \\\\\n0 & baseone & basetwo & \\cdots & basenenn \\\\\n0 & \\left(baseone\\right)_{2} & \\left(basetwo\\right)_{2} & \\cdots & \\left(basenenn\\right)_{2} \\\\\n\\vdots & \\vdots & \\vdots & \\ddots & \\vdots \\\\\n0 & \\left(baseone\\right)_{countnum-1} & \\left(basetwo\\right)_{countnum-1} & \\cdots & \\left(basenenn\\right)_{countnum-1} \\\\\n(-1)^{countnum} countnum! \\, polyfun(1) & \\left(baseone\\right)_{countnum} & \\left(basetwo\\right)_{countnum} & \\cdots & \\left(basenenn\\right)_{countnum}\n\\end{array}\\right) \\quad \\text { and } \\quad \\mathbf{vecentry}=\\left(\\begin{array}{c}\n-1 \\\\\ncoeffone \\\\\ncoefftwo \\\\\n\\vdots \\\\\ncoeffenn\n\\end{array}\\right)\n\\]\n\nSince \\( \\mathbf{vecentry} \\neq 0 \\), \\( \\operatorname{det} bigmatrix=0 \\). Since \\( (basenum)_{iterind} \\) is a monic polynomial of degree \\( iterind \\) in \\( basenum \\) with no constant term, we can add a linear combination of rows \\( 2,3, \\ldots, rowindx \\) to row \\( rowindx+1 \\), for \\( 2 \\leq rowindx \\leq countnum \\), to obtain\n\\[\nbigmatrix^{\\prime}=\\left(\\begin{array}{ccccc}\n-1 & 1 & 1 & \\cdots & 1 \\\\\n0 & baseone & basetwo & \\cdots & basenenn \\\\\n0 & baseone^{2} & basetwo^{2} & \\cdots & basenenn^{2} \\\\\n\\vdots & \\vdots & \\vdots & \\ddots & \\vdots \\\\\n0 & baseone^{countnum-1} & basetwo^{countnum-1} & \\cdots & basenenn^{countnum-1} \\\\\n(-1)^{countnum} countnum! \\, polyfun(1) & baseone^{countnum} & basetwo^{countnum} & \\cdots & basenenn^{countnum}\n\\end{array}\\right)\n\\]\n\nExpanding by minors along the first column yields \\( 0=\\operatorname{det} bigmatrix^{\\prime}=-\\operatorname{det}\\left(vandermn^{\\prime}\\right)+ \\)\n\\( countnum! \\, polyfun(1) \\operatorname{det}(vandermn) \\) where\n\\[\nvandermn=\\left(\\begin{array}{cccc}\n1 & 1 & \\cdots & 1 \\\\\nbaseone & basetwo & \\cdots & basenenn \\\\\nbaseone^{2} & basetwo^{2} & \\cdots & basenenn^{2} \\\\\n\\vdots & \\vdots & \\ddots & \\vdots \\\\\nbaseone^{countnum-1} & basetwo^{countnum-1} & \\cdots & basenenn^{countnum-1}\n\\end{array}\\right) \\text { and } vandermn^{\\prime}=\\left(\\begin{array}{cccc}\nbaseone & basetwo & \\cdots & basenenn \\\\\nbaseone^{2} & basetwo^{2} & \\cdots & basenenn^{2} \\\\\n\\vdots & \\vdots & \\ddots & \\vdots \\\\\nbaseone^{countnum-1} & basetwo^{countnum-1} & \\cdots & basenenn^{countnum-1} \\\\\nbaseone^{countnum} & basetwo^{countnum} & \\cdots & basenenn^{countnum}\n\\end{array}\\right)\n\\]\n\nFactoring \\( basegen \\) out of the \\( \\text{column} \\) corresponding to it in \\( vandermn^{\\prime} \\) shows that \\( \\operatorname{det}(vandermn^{\\prime})=baseone basetwo \\cdots basenenn \\operatorname{det}(vandermn) \\). Hence \\( -baseone basetwo \\cdots basenenn \\operatorname{det}(vandermn)+countnum! \\, polyfun(1) \\operatorname{det}(vandermn)=0 \\). Since the \\( basegen \\) are distinct, \\( \\operatorname{det}(vandermn) \\neq 0 \\) (see below). Thus \\( polyfun(1)=baseone basetwo \\cdots basenenn / countnum! \\).\n\nRemark (The Vandermonde determinant). The matrix \\( vandermn \\) is called the Vandermonde matrix. Its determinant \\( vanddet \\) is a polynomial of total degree \\( \\binom{countnum}{2} \\) in the \\( basegen \\), and \\( vanddet \\) vanishes whenever two of the \\( basegen \\) coincide, so \\( vanddet \\) is divisible by the differences of any two of them. These differences have no common factor, so their product divides \\( vanddet \\). But this product also has total degree \\( \\binom{countnum}{2} \\), and the leading coefficients agree, so \\( vanddet \\) equals that product. In particular, if the \\( basegen \\) are distinct numbers, then \\( vanddet \\neq 0 \\).\n\nSolution 2. Subtract 1 from both sides, set \\( variable=e^{smallpar} \\), and expand the left-hand side in a power series. Since \\( 1-e^{smallpar}=smallpar+ \\) (higher order terms), we get\n\\[\n-1+(-1)^{countnum} polyfun(1) smallpar^{countnum}+(\\text { higher order terms })=\\sum_{summindx=1}^{countnum} coeffgen e^{basegen smallpar}\n\\]\n\nThe right-hand side \\( seriesfx(smallpar) \\) satisfies the linear differential equation\n\\[\nseriesfx^{(countnum)}(smallpar)-\\left(baseone+\\cdots+basenenn\\right) seriesfx^{(countnum-1)}(smallpar)+\\cdots+(-1)^{countnum} baseone basetwo \\cdots basenenn \\, seriesfx(smallpar)=0\n\\]\nwith characteristic polynomial \\( charpoly(rootvar)=\\left(rootvar-baseone\\right)\\left(rootvar-basetwo\\right) \\cdots\\left(rootvar-basenenn\\right) \\). On the other hand, from the left-hand side of (1) we see that \\( seriesfx(0)=-1, seriesfx^{(summindx)}(0)=0 \\) for \\( summindx=1, \\ldots, countnum-1 \\), and \\( seriesfx^{(countnum)}(0)=(-1)^{countnum} polyfun(1) countnum! \\). Hence taking \\( smallpar=0 \\) in (2) yields\n\\[\n(-1)^{countnum} polyfun(1) countnum!-0+0-0+\\cdots+(-1)^{countnum} baseone basetwo \\cdots basenenn(-1)=0\n\\]\nso \\( polyfun(1)=baseone basetwo \\cdots basenenn / countnum! \\)."
    },
    "descriptive_long_confusing": {
      "map": {
        "a_1": "pineapple",
        "a_2": "watermelon",
        "a_n": "raspberry",
        "a_i": "strawberry",
        "f": "harvests",
        "x": "longitude",
        "j": "coastline",
        "k": "sandstorm",
        "A": "raincloud",
        "v": "arrowhead",
        "V": "foxgloves",
        "D": "snowflake",
        "F": "starlight",
        "t": "silvermaple",
        "p": "lighthouse",
        "z": "windspeed",
        "i": "shoreline",
        "n": "aftershock",
        "b": "parchment",
        "b_1": "bluegrass",
        "b_2": "elderberry",
        "b_n": "snowberry",
        "b_i": "corncakes"
      },
      "question": "Let $pineapple, watermelon, \\dots, raspberry$ be real numbers, and let $bluegrass, elderberry, \\dots,\nsnowberry$ be distinct positive integers. Suppose that there is a polynomial\n$harvests(longitude)$ satisfying the identity\n\\[\n(1-longitude)^{aftershock} harvests(longitude) = 1 + \\sum_{shoreline=1}^{aftershock} strawberry longitude^{corncakes}.\n\\]\nFind a simple expression (not involving any sums) for $harvests(1)$ in terms\nof $bluegrass, elderberry, \\dots, snowberry$ and $aftershock$ (but independent of $pineapple, watermelon,\n\\dots, raspberry$).",
      "solution": "Solution 1. For \\( coastline \\geq 1 \\), let \\( (parchment)_{coastline} \\) denote \\( parchment(parchment-1) \\cdots(parchment-coastline+1) \\). For \\( 0 \\leq coastline \\leq aftershock \\), differentiating the identity \\( coastline \\) times and putting \\( longitude=1 \\) (or alternatively substituting \\( longitude=y+1 \\) and equating coefficients) yields\n\\[\n\\begin{aligned}\n0 & =1+\\sum_{shoreline} strawberry \\\\\n0 & =\\sum_{shoreline} strawberry corncakes \\\\\n0 & =\\sum_{shoreline} strawberry\\left(corncakes\\right)_{2} \\\\\n& \\vdots \\\\\n0 & =\\sum_{shoreline} strawberry\\left(corncakes\\right)_{aftershock-1} \\\\\n(-1)^{aftershock} aftershock! harvests(1) & =\\sum_{shoreline} strawberry\\left(corncakes\\right)_{aftershock}\n\\end{aligned}\n\\]\n\nIn other words, \\( raincloud \\mathbf{arrowhead}=0 \\), where\n\\[\nraincloud=\\left(\\begin{array}{ccccc}\n-1 & 1 & 1 & \\cdots & 1 \\\\\n0 & bluegrass & elderberry & \\cdots & snowberry \\\\\n0 & \\left(bluegrass\\right)_{2} & \\left(elderberry\\right)_{2} & \\cdots & \\left(snowberry\\right)_{2} \\\\\n\\vdots & \\vdots & \\vdots & \\ddots & \\vdots \\\\\n0 & \\left(bluegrass\\right)_{aftershock-1} & \\left(elderberry\\right)_{aftershock-1} & \\cdots & \\left(snowberry\\right)_{aftershock-1} \\\\\n(-1)^{aftershock} aftershock! harvests(1) & \\left(bluegrass\\right)_{aftershock} & \\left(elderberry\\right)_{aftershock} & \\cdots & \\left(snowberry\\right)_{aftershock}\n\\end{array}\\right) \\quad \\text { and } \\quad \\mathbf{arrowhead}=\\left(\\begin{array}{c}\n-1 \\\\\npineapple \\\\\nwatermelon \\\\\n\\vdots \\\\\nraspberry\n\\end{array}\\right)\n\\]\n\nSince \\( \\mathbf{arrowhead} \\neq 0 \\), \\( \\operatorname{det} raincloud=0 \\). Since \\( (parchment)_{coastline} \\) is a monic polynomial of degree \\( coastline \\) in \\( parchment \\) with no constant term, we can add a linear combination of rows \\( 2,3, \\ldots, sandstorm \\) to row \\( sandstorm+1 \\), for \\( 2 \\leq sandstorm \\leq aftershock \\), to obtain\n\\[\nraincloud^{\\prime}=\\left(\\begin{array}{ccccc}\n-1 & 1 & 1 & \\cdots & 1 \\\\\n0 & bluegrass & elderberry & \\cdots & snowberry \\\\\n0 & bluegrass^{2} & elderberry^{2} & \\cdots & snowberry^{2} \\\\\n\\vdots & \\vdots & \\vdots & \\ddots & \\vdots \\\\\n0 & bluegrass^{aftershock-1} & elderberry^{aftershock-1} & \\cdots & snowberry^{aftershock-1} \\\\\n(-1)^{aftershock} aftershock! harvests(1) & bluegrass^{aftershock} & elderberry^{aftershock} & \\cdots & snowberry^{aftershock}\n\\end{array}\\right)\n\\]\n\nExpanding by minors along the first column yields \\( 0=\\operatorname{det} raincloud^{\\prime}=-\\operatorname{det}\\left(foxgloves^{\\prime}\\right)+ aftershock! harvests(1) \\operatorname{det}(foxgloves) \\) where\n\\[\nfoxgloves=\\left(\\begin{array}{cccc}\n1 & 1 & \\cdots & 1 \\\\\nbluegrass & elderberry & \\cdots & snowberry \\\\\nbluegrass^{2} & elderberry^{2} & \\cdots & snowberry^{2} \\\\\n\\vdots & \\vdots & \\ddots & \\vdots \\\\\nbluegrass^{aftershock-1} & elderberry^{aftershock-1} & \\cdots & snowberry^{aftershock-1}\n\\end{array}\\right) \\text { and } foxgloves^{\\prime}=\\left(\\begin{array}{cccc}\nbluegrass & elderberry & \\cdots & snowberry \\\\\nbluegrass^{2} & elderberry^{2} & \\cdots & snowberry^{2} \\\\\n\\vdots & \\vdots & \\ddots & \\vdots \\\\\nbluegrass^{aftershock-1} & elderberry^{aftershock-1} & \\cdots & snowberry^{aftershock-1} \\\\\nbluegrass^{aftershock} & elderberry^{aftershock} & \\cdots & snowberry^{aftershock}\n\\end{array}\\right)\n\\]\n\nFactoring \\( corncakes \\) out of the \\( shoreline \\) th column of \\( foxgloves^{\\prime} \\) shows that \\( \\operatorname{det}\\left(foxgloves^{\\prime}\\right)=bluegrass\\, elderberry \\cdots snowberry \\operatorname{det}(foxgloves) \\). Hence \\( -bluegrass\\, elderberry \\cdots snowberry \\operatorname{det}(foxgloves)+aftershock! harvests(1) \\operatorname{det}(foxgloves)=0 \\). Since the \\( corncakes \\) are distinct, \\( \\operatorname{det}(foxgloves) \\neq 0 \\) (see below). Thus \\( harvests(1)=bluegrass\\, elderberry \\cdots snowberry / aftershock! \\).\n\nRemark (The Vandermonde determinant). The matrix \\( foxgloves \\) is called the Vandermonde matrix. Its determinant \\( snowflake \\) is a polynomial of total degree \\( \\binom{aftershock}{2} \\) in the \\( corncakes \\), and \\( snowflake \\) vanishes whenever \\( corncakes=corncakes \\) for \\( shoreline>coastline \\), so \\( snowflake \\) is divisible by \\( corncakes-corncakes \\) whenever \\( shoreline>coastline \\). These \\( corncakes-corncakes \\) have no common factor, so \\( \\prod_{shoreline>coastline}\\left(corncakes-corncakes\\right) \\) divides \\( snowflake \\). But this product also has total degree \\( \\binom{aftershock}{2} \\), and the coefficient of \\( elderberry\\, elderberry^{2} \\cdots snowberry^{aftershock-1} \\) in \\( snowflake \\) and in \\( \\prod_{shoreline>coastline}\\left(corncakes-corncakes\\right) \\) both equal 1, so \\( snowflake=\\prod_{shoreline>coastline}\\left(corncakes-corncakes\\right) \\). In particular, if the \\( corncakes \\) are distinct numbers, then \\( snowflake \\neq 0 \\). See Problem 1941/14(ii) [PutnamI, p. 17] for an extension, and 1999B5 for another application.\n\nSolution 2. Subtract 1 from both sides, set \\( longitude=e^{silvermaple} \\), and expand the left-hand side in a power series. Since \\( 1-e^{silvermaple}=silvermaple+ \\) (higher order terms), we get\n\\[\n-1+(-1)^{aftershock} harvests(1) silvermaple^{aftershock}+(\\text { higher order terms })=\\sum_{shoreline=1}^{aftershock} strawberry e^{corncakes silvermaple}\n\\]\n\nThe right-hand side \\( starlight(silvermaple) \\) satisfies the linear differential equation\n\\[\nstarlight^{(aftershock)}(silvermaple)-\\left(bluegrass+\\cdots+snowberry\\right) starlight^{(aftershock-1)}(silvermaple)+\\cdots+(-1)^{aftershock} bluegrass\\, elderberry \\cdots snowberry\\, starlight(silvermaple)=0\n\\]\nwith characteristic polynomial \\( lighthouse(windspeed)=\\left(windspeed-bluegrass\\right)\\left(windspeed-elderberry\\right) \\cdots\\left(windspeed-snowberry\\right) \\). On the other hand, from the left-hand side of (1) we see that \\( starlight(0)=-1, starlight^{(shoreline)}=0 \\) for \\( shoreline=1, \\ldots, aftershock-1 \\), and \\( starlight^{(aftershock)}(0)=(-1)^{aftershock} harvests(1) aftershock! \\). Hence taking \\( silvermaple=0 \\) in (2) yields\n\\[\n(-1)^{aftershock} harvests(1) aftershock!-0+0-0+\\cdots+(-1)^{aftershock} bluegrass\\, elderberry \\cdots snowberry(-1)=0\n\\]\nso \\( harvests(1)=bluegrass\\, elderberry \\cdots snowberry / aftershock! \\)."
    },
    "descriptive_long_misleading": {
      "map": {
        "a_1": "firstconstant",
        "a_2": "secondconstant",
        "a_n": "lastconstant",
        "a_i": "genericconstant",
        "f": "nonpolyfunc",
        "x": "constantval",
        "j": "maximus",
        "k": "minimizer",
        "A": "scalarset",
        "v": "scalarval",
        "V": "nonvanderm",
        "D": "nondetermin",
        "F": "staticvalue",
        "t": "spacedim",
        "p": "nonpolyexp",
        "z": "vertexval",
        "i": "fixposval",
        "n": "infinitecount",
        "b": "staticvar",
        "b_1": "firststatic",
        "b_2": "secondstatic",
        "b_n": "laststatic",
        "b_i": "genericstatic"
      },
      "question": "Let $firstconstant, secondconstant, \\dots, lastconstant$ be real numbers, and let $firststatic, secondstatic, \\dots, laststatic$ be distinct positive integers. Suppose that there is a polynomial $nonpolyfunc(constantval)$ satisfying the identity\n\\[\n(1-constantval)^{infinitecount} nonpolyfunc(constantval) = 1 + \\sum_{fixposval=1}^{infinitecount} genericconstant\\, constantval^{genericstatic}.\n\\]\nFind a simple expression (not involving any sums) for $nonpolyfunc(1)$ in terms of $firststatic, secondstatic, \\dots, laststatic$ and $infinitecount$ (but independent of $firstconstant, secondconstant, \\dots, lastconstant$).",
      "solution": "Solution 1. For \\( maximus \\ge 1 \\), let \\( (staticvar)_{maximus} \\) denote \\( staticvar(staticvar-1)\\cdots(staticvar-maximus+1) \\). For \\( 0 \\le maximus \\le infinitecount \\), differentiating the identity \\( maximus \\) times and putting \\( constantval=1 \\) (or alternatively substituting \\( constantval=y+1 \\) and equating coefficients) yields\n\\[\n\\begin{aligned}\n0 & =1+\\sum genericconstant \\\\\n0 & =\\sum genericconstant genericstatic \\\\\n0 & =\\sum genericconstant\\left(genericstatic\\right)_{2} \\\\\n& \\vdots \\\\\n0 & =\\sum genericconstant\\left(genericstatic\\right)_{infinitecount-1} \\\\\n(-1)^{infinitecount} infinitecount! nonpolyfunc(1) & =\\sum genericconstant\\left(genericstatic\\right)_{infinitecount}\n\\end{aligned}\n\\]\n\nIn other words, \\( scalarset \\mathbf{scalarval}=0 \\), where\n\\[\nscalarset=\\left(\\begin{array}{ccccc}\n-1 & 1 & 1 & \\cdots & 1 \\\\\n0 & firststatic & secondstatic & \\cdots & laststatic \\\\\n0 & \\left(firststatic\\right)_{2} & \\left(secondstatic\\right)_{2} & \\cdots & \\left(laststatic\\right)_{2} \\\\\n\\vdots & \\vdots & \\vdots & \\ddots & \\vdots \\\\\n0 & \\left(firststatic\\right)_{infinitecount-1} & \\left(secondstatic\\right)_{infinitecount-1} & \\cdots & \\left(laststatic\\right)_{infinitecount-1} \\\\\n(-1)^{infinitecount} infinitecount! nonpolyfunc(1) & \\left(firststatic\\right)_{infinitecount} & \\left(secondstatic\\right)_{infinitecount} & \\cdots & \\left(laststatic\\right)_{infinitecount}\n\\end{array}\\right) \\quad \\text { and } \\quad \\mathbf{scalarval}=\\left(\\begin{array}{c}\n-1 \\\\\nfirstconstant \\\\\nsecondconstant \\\\\n\\vdots \\\\\nlastconstant\n\\end{array}\\right)\n\\]\n\nSince \\( \\mathbf{scalarval} \\neq 0 \\), \\( \\operatorname{det} scalarset=0 \\). Since \\( (staticvar)_{maximus} \\) is a monic polynomial of degree \\( maximus \\) in \\( staticvar \\) with no constant term, we can add a linear combination of rows \\( 2,3, \\ldots, minimizer \\) to row \\( minimizer+1 \\), for \\( 2 \\le minimizer \\le infinitecount \\), to obtain\n\\[\nscalarset^{\\prime}=\\left(\\begin{array}{ccccc}\n-1 & 1 & 1 & \\cdots & 1 \\\\\n0 & firststatic & secondstatic & \\cdots & laststatic \\\\\n0 & firststatic^{2} & secondstatic^{2} & \\cdots & laststatic^{2} \\\\\n\\vdots & \\vdots & \\vdots & \\ddots & \\vdots \\\\\n0 & firststatic^{infinitecount-1} & secondstatic^{infinitecount-1} & \\cdots & laststatic^{infinitecount-1} \\\\\n(-1)^{infinitecount} infinitecount! nonpolyfunc(1) & firststatic^{infinitecount} & secondstatic^{infinitecount} & \\cdots & laststatic^{infinitecount}\n\\end{array}\\right)\n\\]\n\nExpanding by minors along the first column yields \\( 0=\\operatorname{det} scalarset^{\\prime}=-\\operatorname{det}\\left(nonvanderm^{\\prime}\\right)+ infinitecount! nonpolyfunc(1) \\operatorname{det}(nonvanderm) \\) where\n\\[\nnonvanderm=\\left(\\begin{array}{cccc}\n1 & 1 & \\cdots & 1 \\\\\nfirststatic & secondstatic & \\cdots & laststatic \\\\\nfirststatic^{2} & secondstatic^{2} & \\cdots & laststatic^{2} \\\\\n\\vdots & \\vdots & \\ddots & \\vdots \\\\\nfirststatic^{infinitecount-1} & secondstatic^{infinitecount-1} & \\cdots & laststatic^{infinitecount-1}\n\\end{array}\\right) \\text { and } nonvanderm^{\\prime}=\\left(\\begin{array}{cccc}\nfirststatic & secondstatic & \\cdots & laststatic \\\\\nfirststatic^{2} & secondstatic^{2} & \\cdots & laststatic^{2} \\\\\n\\vdots & \\vdots & \\ddots & \\vdots \\\\\nfirststatic^{infinitecount-1} & secondstatic^{infinitecount-1} & \\cdots & laststatic^{infinitecount-1} \\\\\nfirststatic^{infinitecount} & secondstatic^{infinitecount} & \\cdots & laststatic^{infinitecount}\n\\end{array}\\right)\n\\]\n\nFactoring \\( firststatic, secondstatic, \\ldots , laststatic \\) out of the respective columns of \\( nonvanderm^{\\prime} \\) shows that \\( \\operatorname{det}\\left(nonvanderm^{\\prime}\\right)=firststatic secondstatic \\cdots laststatic \\operatorname{det}(nonvanderm) \\). Hence \\( -firststatic secondstatic \\cdots laststatic \\operatorname{det}(nonvanderm)+infinitecount! nonpolyfunc(1) \\operatorname{det}(nonvanderm)=0 \\). Since the \\( firststatic, secondstatic, \\ldots , laststatic \\) are distinct, \\( \\operatorname{det}(nonvanderm) \\neq 0 \\) (see below). Thus \\( nonpolyfunc(1)=firststatic secondstatic \\cdots laststatic / infinitecount! \\).\n\nRemark (The Vandermonde determinant). The matrix \\( nonvanderm \\) is called the Vandermonde matrix. Its determinant \\( nondetermin \\) is a polynomial of total degree \\( \\binom{infinitecount}{2} \\) in the \\( firststatic, secondstatic, \\ldots , laststatic \\), and \\( nondetermin \\) vanishes whenever \\( firststatic=secondstatic \\) for \\( fixposval>maximus \\), so \\( nondetermin \\) is divisible by \\( firststatic-secondstatic \\) whenever \\( fixposval>maximus \\). These \\( firststatic-secondstatic \\) have no common factor, so \\( \\prod_{fixposval>maximus}\\left(firststatic-secondstatic\\right) \\) divides \\( nondetermin \\). But this product also has total degree \\( \\binom{infinitecount}{2} \\), and the coefficient of \\( secondstatic firststatic^{2} \\cdots laststatic^{infinitecount-1} \\) in \\( nondetermin \\) and in \\( \\prod_{fixposval>maximus}\\left(firststatic-secondstatic\\right) \\) both equal 1, so \\( nondetermin=\\prod_{fixposval>maximus}\\left(firststatic-secondstatic\\right) \\). In particular, if the \\( firststatic, secondstatic, \\ldots , laststatic \\) are distinct numbers, then \\( nondetermin \\neq 0 \\). See Problem 1941/14(ii) [PutnamI, p. 17] for an extension, and 1999B5 for another application.\n\nSolution 2. Subtract 1 from both sides, set \\( constantval=e^{spacedim} \\), and expand the left-hand side in a power series. Since \\( 1-e^{spacedim}=spacedim+ \\) (higher order terms), we get\n\\[\n-1+(-1)^{infinitecount} nonpolyfunc(1) spacedim^{infinitecount}+(\\text { higher order terms })=\\sum_{fixposval=1}^{infinitecount} genericconstant e^{genericstatic spacedim}\n\\]\n\nThe right-hand side \\( staticvalue(spacedim) \\) satisfies the linear differential equation\n\\[\nstaticvalue^{(infinitecount)}(spacedim)-\\left(firststatic+\\cdots+laststatic\\right) staticvalue^{(infinitecount-1)}(spacedim)+\\cdots+(-1)^{infinitecount} firststatic secondstatic \\cdots laststatic\\, staticvalue(spacedim)=0\n\\]\nwith characteristic polynomial \\( nonpolyexp(vertexval)=\\left(vertexval-firststatic\\right)\\left(vertexval-secondstatic\\right) \\cdots\\left(vertexval-laststatic\\right) \\). On the other hand, from the left-hand side of (1) we see that \\( staticvalue(0)=-1, staticvalue^{(maximus)}=0 \\) for \\( maximus=1, \\ldots, infinitecount-1 \\), and \\( staticvalue^{(infinitecount)}(0)=(-1)^{infinitecount} nonpolyfunc(1) infinitecount! \\). Hence taking \\( spacedim=0 \\) in (2) yields\n\\[\n(-1)^{infinitecount} nonpolyfunc(1) infinitecount!-0+0-0+\\cdots+(-1)^{infinitecount} firststatic secondstatic \\cdots laststatic(-1)=0\n\\]\nso \\( nonpolyfunc(1)=firststatic secondstatic \\cdots laststatic / infinitecount! \\)."
    },
    "garbled_string": {
      "map": {
        "a_1": "qzxwvtnp",
        "a_2": "hjgrksla",
        "a_n": "mflqpsow",
        "a_i": "rnbdakue",
        "f": "vgczyplk",
        "x": "sbnifero",
        "j": "uvlaznqo",
        "k": "dpseirgw",
        "A": "soactrmv",
        "v": "ylwpxdqe",
        "V": "zmhuqtga",
        "D": "ecrvjoxb",
        "F": "xludsepq",
        "t": "nkivchya",
        "p": "wdrtqmlu",
        "z": "bksyejph",
        "i": "glsafezn",
        "n": "kodyunwe",
        "b": "vifranco",
        "b_1": "zictemah",
        "b_2": "rvoupnla",
        "b_n": "sweldeax",
        "b_i": "ljotgcra"
      },
      "question": "Let $qzxwvtnp, hjgrksla, \\dots, mflqpsow$ be real numbers, and let $zictemah, rvoupnla, \\dots,\nsweldeax$ be distinct positive integers. Suppose that there is a polynomial\n$vgczyplk(sbnifero)$ satisfying the identity\n\\[\n(1-sbnifero)^{kodyunwe} vgczyplk(sbnifero) = 1 + \\sum_{glsafezn=1}^{kodyunwe} rnbdakue \\, sbnifero^{ljotgcra}.\n\\]\nFind a simple expression (not involving any sums) for $vgczyplk(1)$ in terms\nof $zictemah, rvoupnla, \\dots, sweldeax$ and $kodyunwe$ (but independent of $qzxwvtnp, hjgrksla,\n\\dots, mflqpsow$).",
      "solution": "Solution 1. For \\( uvlaznqo \\geq 1 \\), let \\( (vifranco)_{uvlaznqo} \\) denote \\( vifranco(vifranco-1) \\cdots(vifranco-uvlaznqo+1) \\). For \\( 0 \\leq uvlaznqo \\leq kodyunwe \\), differentiating the identity \\( uvlaznqo \\) times and putting \\( sbnifero=1 \\) (or alternatively substituting \\( sbnifero=y+1 \\) and equating coefficients) yields\n\\[\n\\begin{aligned}\n0 & =1+\\sum rnbdakue \\\\\n0 & =\\sum rnbdakue \\, ljotgcra \\\\\n0 & =\\sum rnbdakue\\left(ljotgcra\\right)_{2} \\\\\n& \\vdots \\\\\n0 & =\\sum rnbdakue\\left(ljotgcra\\right)_{kodyunwe-1} \\\\\n(-1)^{kodyunwe} kodyunwe! \\, vgczyplk(1) & =\\sum rnbdakue\\left(ljotgcra\\right)_{kodyunwe}\n\\end{aligned}\n\\]\n\nIn other words, \\( soactrmv \\mathbf{ylwpxdqe}=0 \\), where\n\\[\nsoactrmv=\\left(\\begin{array}{ccccc}\n-1 & 1 & 1 & \\cdots & 1 \\\\\n0 & zictemah & rvoupnla & \\cdots & sweldeax \\\\\n0 & \\left(zictemah\\right)_{2} & \\left(rvoupnla\\right)_{2} & \\cdots & \\left(sweldeax\\right)_{2} \\\\\n\\vdots & \\vdots & \\vdots & \\ddots & \\vdots \\\\\n0 & \\left(zictemah\\right)_{kodyunwe-1} & \\left(rvoupnla\\right)_{kodyunwe-1} & \\cdots & \\left(sweldeax\\right)_{kodyunwe-1} \\\\\n(-1)^{kodyunwe} kodyunwe! \\, vgczyplk(1) & \\left(zictemah\\right)_{kodyunwe} & \\left(rvoupnla\\right)_{kodyunwe} & \\cdots & \\left(sweldeax\\right)_{kodyunwe}\n\\end{array}\\right) \\quad \\text { and } \\quad \\mathbf{ylwpxdqe}=\\left(\\begin{array}{c}\n-1 \\\\\nqzxwvtnp \\\\\nhjgrksla \\\\\n\\vdots \\\\\nmflqpsow\n\\end{array}\\right)\n\\]\n\nSince \\( \\mathbf{ylwpxdqe} \\neq 0 \\), \\( \\operatorname{det} soactrmv=0 \\). Since \\( (vifranco)_{uvlaznqo} \\) is a monic polynomial of degree \\( uvlaznqo \\) in \\( vifranco \\) with no constant term, we can add a linear combination of rows \\( 2,3, \\ldots, dpseirgw \\) to row \\( dpseirgw+1 \\), for \\( 2 \\leq dpseirgw \\leq kodyunwe \\), to obtain\n\\[\nsoactrmv^{\\prime}=\\left(\\begin{array}{ccccc}\n-1 & 1 & 1 & \\cdots & 1 \\\\\n0 & zictemah & rvoupnla & \\cdots & sweldeax \\\\\n0 & zictemah^{2} & rvoupnla^{2} & \\cdots & sweldeax^{2} \\\\\n\\vdots & \\vdots & \\vdots & \\ddots & \\vdots \\\\\n0 & zictemah^{kodyunwe-1} & rvoupnla^{kodyunwe-1} & \\cdots & sweldeax^{kodyunwe-1} \\\\\n(-1)^{kodyunwe} kodyunwe! \\, vgczyplk(1) & zictemah^{kodyunwe} & rvoupnla^{kodyunwe} & \\cdots & sweldeax^{kodyunwe}\n\\end{array}\\right)\n\\]\n\nExpanding by minors along the first column yields\n\\( 0=\\operatorname{det} soactrmv^{\\prime}=-\\operatorname{det}\\left(zmhuqtga^{\\prime}\\right)+kodyunwe! \\, vgczyplk(1)\\operatorname{det}(zmhuqtga) \\)\nwhere\n\\[\nzmhuqtga=\\left(\\begin{array}{cccc}\n1 & 1 & \\cdots & 1 \\\\\nzictemah & rvoupnla & \\cdots & sweldeax \\\\\nzictemah^{2} & rvoupnla^{2} & \\cdots & sweldeax^{2} \\\\\n\\vdots & \\vdots & \\ddots & \\vdots \\\\\nzictemah^{kodyunwe-1} & rvoupnla^{kodyunwe-1} & \\cdots & sweldeax^{kodyunwe-1}\n\\end{array}\\right) \\quad \\text { and } \\quad\nzmhuqtga^{\\prime}=\\left(\\begin{array}{cccc}\nzictemah & rvoupnla & \\cdots & sweldeax \\\\\nzictemah^{2} & rvoupnla^{2} & \\cdots & sweldeax^{2} \\\\\n\\vdots & \\vdots & \\ddots & \\vdots \\\\\nzictemah^{kodyunwe-1} & rvoupnla^{kodyunwe-1} & \\cdots & sweldeax^{kodyunwe-1} \\\\\nzictemah^{kodyunwe} & rvoupnla^{kodyunwe} & \\cdots & sweldeax^{kodyunwe}\n\\end{array}\\right)\n\\]\n\nFactoring \\( ljotgcra \\) out of the \\( glsafezn \\)th column of \\( zmhuqtga^{\\prime} \\) shows that \\( \\operatorname{det}\\left(zmhuqtga^{\\prime}\\right)=zictemah \\, rvoupnla \\cdots sweldeax \\, \\operatorname{det}(zmhuqtga) \\). Hence\n\\( -zictemah \\, rvoupnla \\cdots sweldeax \\, \\operatorname{det}(zmhuqtga)+kodyunwe! \\, vgczyplk(1)\\operatorname{det}(zmhuqtga)=0 \\).\nSince the \\( ljotgcra \\) are distinct, \\( \\operatorname{det}(zmhuqtga) \\neq 0 \\) (see below). Thus\n\\( vgczyplk(1)=\\dfrac{zictemah \\, rvoupnla \\cdots sweldeax}{kodyunwe!}. \\)\n\nRemark (The Vandermonde determinant). The matrix \\( zmhuqtga \\) is called the Vandermonde matrix. Its determinant \\( ecrvjoxb \\) is a polynomial of total degree \\( \\binom{kodyunwe}{2} \\) in the \\( ljotgcra \\), and \\( ecrvjoxb \\) vanishes whenever \\( ljotgcra=ljotgcra^{\\prime} \\) for \\( glsafezn>uvlaznqo \\), so \\( ecrvjoxb \\) is divisible by \\( ljotgcra-ljotgcra^{\\prime} \\) whenever \\( glsafezn>uvlaznqo \\). These \\( ljotgcra-ljotgcra^{\\prime} \\) have no common factor, so \\( \\prod_{glsafezn>uvlaznqo}\\left(ljotgcra-ljotgcra^{\\prime}\\right) \\) divides \\( ecrvjoxb \\). But this product also has total degree \\( \\binom{kodyunwe}{2} \\), and the coefficient of \\( rvoupnla \\, sweldeax^{kodyunwe-1} \\) in \\( ecrvjoxb \\) and in \\( \\prod_{glsafezn>uvlaznqo}\\left(ljotgcra-ljotgcra^{\\prime}\\right) \\) both equal 1, so \\( ecrvjoxb=\\prod_{glsafezn>uvlaznqo}\\left(ljotgcra-ljotgcra^{\\prime}\\right) \\). In particular, if the \\( ljotgcra \\) are distinct numbers, then \\( ecrvjoxb \\neq 0 \\). See Problem 1941/14(ii) [PutnamI, p. 17] for an extension, and 1999B5 for another application.\n\nSolution 2. Subtract 1 from both sides, set \\( sbnifero=e^{nkivchya} \\), and expand the left-hand side in a power series. Since \\( 1-e^{nkivchya}=nkivchya+ \\) (higher order terms), we get\n\\[\n-1+(-1)^{kodyunwe} vgczyplk(1) \\, nkivchya^{kodyunwe}+(\\text { higher order terms })=\\sum_{glsafezn=1}^{kodyunwe} rnbdakue \\, e^{ljotgcra \\, nkivchya}\n\\]\n\nThe right-hand side \\( xludsepq(nkivchya) \\) satisfies the linear differential equation\n\\[\nxludsepq^{(kodyunwe)}(nkivchya)-\\left(zictemah+rvoupnla+\\cdots+sweldeax\\right) xludsepq^{(kodyunwe-1)}(nkivchya)+\\cdots+(-1)^{kodyunwe} zictemah \\, rvoupnla \\cdots sweldeax \\, xludsepq(nkivchya)=0\n\\]\nwith characteristic polynomial \\( wdrtqmlu(bksyejph)=\\left(bksyejph-zictemah\\right)\\left(bksyejph-rvoupnla\\right) \\cdots\\left(bksyejph-sweldeax\\right) \\). On the other hand, from the left-hand side of (1) we see that \\( xludsepq(0)=-1, xludsepq^{(glsafezn)}=0 \\) for \\( glsafezn=1, \\ldots, kodyunwe-1 \\), and \\( xludsepq^{(kodyunwe)}(0)=(-1)^{kodyunwe} vgczyplk(1) kodyunwe! \\). Hence taking \\( nkivchya=0 \\) in (2) yields\n\\[\n(-1)^{kodyunwe} vgczyplk(1) kodyunwe!-0+0-0+\\cdots+(-1)^{kodyunwe} zictemah \\, rvoupnla \\cdots sweldeax(-1)=0,\n\\]\nso \\( vgczyplk(1)=\\dfrac{zictemah \\, rvoupnla \\cdots sweldeax}{kodyunwe!}. \\)"
    },
    "kernel_variant": {
      "question": "Let $r,n$ be positive integers with $n\\ge 2$.  \nFor each $k\\in\\{1,2,\\dots ,r\\}$ choose  \n\\[\nb_{k,1},\\,b_{k,2},\\dots ,b_{k,n}\\qquad(\\text{pairwise distinct positive integers}).\n\\]\n\nAssume that there exists a real polynomial in $r$ variables  \n\\[\nf(x_{1},x_{2},\\dots ,x_{r})\\in\\mathbb{R}[x_{1},x_{2},\\dots ,x_{r}]\n\\]\nsatisfying the identity  \n\\[\n\\Bigl(\\,\\prod_{k=1}^{r}(1-x_{k})^{\\,n}\\Bigr)\\,f(x_{1},\\dots ,x_{r})\n\\;=\\;\n1+\\sum_{i_{1}=1}^{n}\\cdots\\sum_{i_{r}=1}^{n}\na_{i_{1},\\dots ,i_{r}}\\;\nx_{1}^{\\,b_{1,i_{1}}}\\,x_{2}^{\\,b_{2,i_{2}}}\\,\\cdots\\,x_{r}^{\\,b_{r,i_{r}}}.\n\\tag{$\\star$}\n\\]\n\n(The real numbers $a_{i_{1},\\dots ,i_{r}}$ are arbitrary; the hypothesis\nmerely guarantees that some polynomial $f$ exists for the given data.)\n\nFind a closed-form expression, containing \\emph{no} summations and independent\nof the $a$’s, for  \n\\[\nf(1,1,\\dots ,1)\n\\]\nin terms of $n$ and the numbers $b_{k,j}$.\n\n\n\n────────────────────────────────────────────",
      "solution": "Boldface letters denote multi-indices;  \n$\\mathbf{0}=(0,\\dots ,0)$ and $\\mathbf{1}=(1,\\dots ,1)$ are the constant\n$r$–tuples.\n\n\n\n1.  Factorial–Vandermonde matrices.  \nFor $m\\ge 0$ and $t\\in\\mathbb{R}$ put\n\\[\n(t)_{m}=t(t-1)\\cdots(t-m+1)\\qquad\\bigl((t)_{0}=1\\bigr).\n\\]\nFor every $k$ define the $n\\times n$ matrix\n\\[\nB^{(k)}\n=\\bigl[(b_{k,j})_{s}\\bigr]_{0\\le s\\le n-1,\\;1\\le j\\le n},\n\\]\na factorial Vandermonde; hence $\\det B^{(k)}\\neq 0$.\n\nSet  \n\\[\nu^{(k)}=\\begin{pmatrix}-1\\\\0\\\\\\vdots\\\\0\\end{pmatrix},\n\\qquad\nw^{(k)}=\\begin{pmatrix}(b_{k,1})_{n}\\\\ \\vdots\\\\ (b_{k,n})_{n}\\end{pmatrix},\n\\]\nand form the Kronecker products  \n\\[\nB:=B^{(r)}\\otimes\\cdots\\otimes B^{(1)},\\qquad\nu:=u^{(r)}\\otimes\\cdots\\otimes u^{(1)}.\n\\]\nAll three objects have length $n^{\\,r}$; $B$ is invertible.\n\n\n\n2.  A linear system for the coefficients $a_{\\,\\dots}$.  \nApply $\\partial^{\\boldsymbol{\\alpha}}$ to $(\\star)$ and set\n$x=\\mathbf{1}$.\n\n•  If $0\\le\\alpha_{k}\\le n-1$ for every $k$ and\n$\\boldsymbol{\\alpha}\\neq\\mathbf{0}$, the factor\n$(1-x_{j})$ survives for some $j$, so the left-hand side vanishes at\n$x=\\mathbf{1}$.  Thus\n\\[\n\\sum_{i_{1},\\dots ,i_{r}}\na_{i_{1},\\dots ,i_{r}}\n\\prod_{k=1}^{r}(b_{k,i_{k}})_{\\alpha_{k}}\n=0.\n\\tag{1}\n\\]\n\n•  For $\\boldsymbol{\\alpha}=\\mathbf{0}$ we obtain\n\\[\n1+\\sum_{i_{1},\\dots ,i_{r}}a_{i_{1},\\dots ,i_{r}}=0,\n\\qquad\\Longrightarrow\\qquad\n\\sum_{i_{1},\\dots ,i_{r}}a_{i_{1},\\dots ,i_{r}}=-1.\n\\tag{2}\n\\]\n\nArrange the $n^{\\,r}$ unknowns\n$A=\\operatorname{vec}[a_{i_{1},\\dots ,i_{r}}]$.  \nConditions (1)–(2) are equivalent to the linear system\n\\[\nB\\,A = e,\n\\tag{3}\n\\]\nwhere the right-hand side vector $e\\in\\mathbb{R}^{n^{\\,r}}$ is defined by  \n\n– \\emph{Row-wise description}: $e$ has entry $-1$ in the row indexed by\n$\\boldsymbol{\\alpha}=\\mathbf{0}$ and $0$ in every other row.  \n\n– \\emph{Kronecker description}:  \n\\[\ne=(-1)^{\\,1-r}\\,u,\n\\]\nso that the very first component of $e$ equals $-1$ (not $(-1)^{\\,r}$).\n\nBecause $B$ is nonsingular, (3) has the unique solution\n\\[\nA=B^{-1}e.\n\\tag{4}\n\\]\n\n\n\n3.  A high derivative links $f(\\mathbf{1})$ to the $a$’s.  \nLet $\\boldsymbol{\\beta}=(n,n,\\dots ,n)$.  Differentiating $(\\star)$ by\n$\\partial^{\\boldsymbol{\\beta}}$ and then putting $x=\\mathbf{1}$ gives\n\\[\n(-1)^{\\,nr}\\,(n!)^{\\,r}\\,f(\\mathbf{1})\n=\\sum_{i_{1},\\dots ,i_{r}}\na_{i_{1},\\dots ,i_{r}}\n\\prod_{k=1}^{r}(b_{k,i_{k}})_{n}\n=w^{\\mathsf T}B^{-1}e,\n\\tag{5}\n\\]\nwhere $w:=w^{(r)}\\otimes\\cdots\\otimes w^{(1)}$.\n\n\n\n4.  Kronecker factorisation.  \nThe scalar $w^{\\mathsf T}B^{-1}e$ separates:\n\\[\nw^{\\mathsf T}B^{-1}e\n=(-1)^{\\,1-r}\\,\n\\prod_{k=1}^{r}\\bigl[(w^{(k)})^{\\mathsf T}(B^{(k)})^{-1}u^{(k)}\\bigr].\n\\tag{6}\n\\]\nThus we need the one-variable constant\n\\[\nS_{k}:=(w^{(k)})^{\\mathsf T}(B^{(k)})^{-1}u^{(k)}.\n\\]\n\n\n\n5.  Evaluation of $S_{k}$.  \nFix $k$ and abbreviate $B=B^{(k)},\\,w=w^{(k)},\\,u=u^{(k)}$.\nCramer’s rule gives\n\\[\nB^{-1}u\n=-\\,\\frac{\\operatorname{adj}B_{\\,\\cdot ,1}}{\\det B},\n\\qquad\\Longrightarrow\\qquad\nS_{k}\n=-\\,\\frac{w^{\\mathsf T}\\!\\operatorname{adj}B_{\\,\\cdot ,1}}{\\det B}.\n\\]\nThe numerator is\n$\\det B[1\\leftarrow w]$, the determinant of the matrix obtained by\nreplacing the first \\emph{row} of $B$ by $w^{\\mathsf T}$.  A standard\nfactorial-Vandermonde computation yields\n\\[\n\\det B[1\\leftarrow w]\n=(-1)^{\\,n+1}\\Bigl(\\prod_{j=1}^{n}b_{k,j}\\Bigr)\\det B,\n\\]\nhence\n\\[\nS_{k}=(-1)^{\\,n}\\prod_{j=1}^{n}b_{k,j}.\n\\tag{7}\n\\]\n\n\n\n6.  Completion.  \nInsert (7) into (6):\n\\[\nw^{\\mathsf T}B^{-1}e\n=(-1)^{\\,1-r}\\,\n\\prod_{k=1}^{r}(-1)^{\\,n}\\prod_{j=1}^{n}b_{k,j}\n=(-1)^{\\,nr+1-r}\\,\n\\prod_{k=1}^{r}\\prod_{j=1}^{n}b_{k,j}.\n\\tag{8}\n\\]\n\nCombine (5) with (8).  The factor $(-1)^{\\,nr}$ cancels, leaving\n\\[\nf(1,1,\\dots ,1)\n\\;=\\;\n(-1)^{\\,r-1}\\;\n\\frac{\\displaystyle\\prod_{k=1}^{r}\\prod_{j=1}^{n}b_{k,j}}\n      {(n!)^{\\,r}}.\n\\qquad\\qquad\\blacksquare\n\\]\n\n\n\n────────────────────────────────────────────",
      "metadata": {
        "replaced_from": "harder_variant",
        "replacement_date": "2025-07-14T19:09:31.692525",
        "was_fixed": false,
        "difficulty_analysis": "1. Higher dimensionality.  \n   • The problem moves from one variable to r variables (r≥2), so the\n     unknown polynomial lives in a space of significantly higher\n     dimension.  \n   • The number of unknown coefficients rises from n to n^{r}.  \n   • Mixed partial derivatives and Kronecker-product linear algebra are\n     required.\n\n2. Additional constraints.  \n   • All mixed derivatives of order < n in every direction must vanish at\n     (1,…,1), producing a system of n^{r} simultaneous equations rather\n     than n.\n\n3. More sophisticated structure.  \n   • The solution uses factorial Vandermonde matrices in each variable\n     and their Kronecker product; this demands familiarity with tensor\n     products, multi-index calculus, and properties of block determinants.\n\n4. Deeper theory and multiple interacting concepts.  \n   • One must combine multivariate calculus, combinatorial identities for\n     falling factorials, determinant factorisation, and Kronecker\n     geometry to isolate the single surviving mixed derivative and relate\n     it to det M.  \n   • The determinant evaluation generalises the classical Vandermonde\n     argument to multi-linear algebra, a non-trivial extension.\n\nHence the enhanced variant is substantially more intricate than the\noriginal (one variable, n equations, ordinary Vandermonde) and the\nprevious kernel variant (constant term 2, primes only).  Solving it\ndemands advanced multivariate techniques beyond routine pattern\nmatching."
      }
    },
    "original_kernel_variant": {
      "question": "Let $r,n$ be positive integers with $n\\ge 2$.  \nFor each $k\\in\\{1,2,\\dots ,r\\}$ choose  \n\\[\nb_{k,1},\\,b_{k,2},\\dots ,b_{k,n}\\qquad(\\text{pairwise distinct positive integers}).\n\\]\n\nAssume that there exists a real polynomial in $r$ variables  \n\\[\nf(x_{1},x_{2},\\dots ,x_{r})\\in\\mathbb{R}[x_{1},x_{2},\\dots ,x_{r}]\n\\]\nsatisfying the identity  \n\\[\n\\Bigl(\\,\\prod_{k=1}^{r}(1-x_{k})^{\\,n}\\Bigr)\\,f(x_{1},\\dots ,x_{r})\n\\;=\\;\n1+\\sum_{i_{1}=1}^{n}\\cdots\\sum_{i_{r}=1}^{n}\na_{i_{1},\\dots ,i_{r}}\\;\nx_{1}^{\\,b_{1,i_{1}}}\\,x_{2}^{\\,b_{2,i_{2}}}\\,\\cdots\\,x_{r}^{\\,b_{r,i_{r}}}.\n\\tag{$\\star$}\n\\]\n\n(The real numbers $a_{i_{1},\\dots ,i_{r}}$ are arbitrary; the hypothesis\nmerely guarantees that some polynomial $f$ exists for the given data.)\n\nFind a closed-form expression, containing \\emph{no} summations and independent\nof the $a$’s, for  \n\\[\nf(1,1,\\dots ,1)\n\\]\nin terms of $n$ and the numbers $b_{k,j}$.\n\n\n\n────────────────────────────────────────────",
      "solution": "Boldface letters denote multi-indices;  \n$\\mathbf{0}=(0,\\dots ,0)$ and $\\mathbf{1}=(1,\\dots ,1)$ are the constant\n$r$–tuples.\n\n\n\n1.  Factorial–Vandermonde matrices.  \nFor $m\\ge 0$ and $t\\in\\mathbb{R}$ put\n\\[\n(t)_{m}=t(t-1)\\cdots(t-m+1)\\qquad\\bigl((t)_{0}=1\\bigr).\n\\]\nFor every $k$ define the $n\\times n$ matrix\n\\[\nB^{(k)}\n=\\bigl[(b_{k,j})_{s}\\bigr]_{0\\le s\\le n-1,\\;1\\le j\\le n},\n\\]\na factorial Vandermonde; hence $\\det B^{(k)}\\neq 0$.\n\nSet  \n\\[\nu^{(k)}=\\begin{pmatrix}-1\\\\0\\\\\\vdots\\\\0\\end{pmatrix},\n\\qquad\nw^{(k)}=\\begin{pmatrix}(b_{k,1})_{n}\\\\ \\vdots\\\\ (b_{k,n})_{n}\\end{pmatrix},\n\\]\nand form the Kronecker products  \n\\[\nB:=B^{(r)}\\otimes\\cdots\\otimes B^{(1)},\\qquad\nu:=u^{(r)}\\otimes\\cdots\\otimes u^{(1)}.\n\\]\nAll three objects have length $n^{\\,r}$; $B$ is invertible.\n\n\n\n2.  A linear system for the coefficients $a_{\\,\\dots}$.  \nApply $\\partial^{\\boldsymbol{\\alpha}}$ to $(\\star)$ and set\n$x=\\mathbf{1}$.\n\n•  If $0\\le\\alpha_{k}\\le n-1$ for every $k$ and\n$\\boldsymbol{\\alpha}\\neq\\mathbf{0}$, the factor\n$(1-x_{j})$ survives for some $j$, so the left-hand side vanishes at\n$x=\\mathbf{1}$.  Thus\n\\[\n\\sum_{i_{1},\\dots ,i_{r}}\na_{i_{1},\\dots ,i_{r}}\n\\prod_{k=1}^{r}(b_{k,i_{k}})_{\\alpha_{k}}\n=0.\n\\tag{1}\n\\]\n\n•  For $\\boldsymbol{\\alpha}=\\mathbf{0}$ we obtain\n\\[\n1+\\sum_{i_{1},\\dots ,i_{r}}a_{i_{1},\\dots ,i_{r}}=0,\n\\qquad\\Longrightarrow\\qquad\n\\sum_{i_{1},\\dots ,i_{r}}a_{i_{1},\\dots ,i_{r}}=-1.\n\\tag{2}\n\\]\n\nArrange the $n^{\\,r}$ unknowns\n$A=\\operatorname{vec}[a_{i_{1},\\dots ,i_{r}}]$.  \nConditions (1)–(2) are equivalent to the linear system\n\\[\nB\\,A = e,\n\\tag{3}\n\\]\nwhere the right-hand side vector $e\\in\\mathbb{R}^{n^{\\,r}}$ is defined by  \n\n– \\emph{Row-wise description}: $e$ has entry $-1$ in the row indexed by\n$\\boldsymbol{\\alpha}=\\mathbf{0}$ and $0$ in every other row.  \n\n– \\emph{Kronecker description}:  \n\\[\ne=(-1)^{\\,1-r}\\,u,\n\\]\nso that the very first component of $e$ equals $-1$ (not $(-1)^{\\,r}$).\n\nBecause $B$ is nonsingular, (3) has the unique solution\n\\[\nA=B^{-1}e.\n\\tag{4}\n\\]\n\n\n\n3.  A high derivative links $f(\\mathbf{1})$ to the $a$’s.  \nLet $\\boldsymbol{\\beta}=(n,n,\\dots ,n)$.  Differentiating $(\\star)$ by\n$\\partial^{\\boldsymbol{\\beta}}$ and then putting $x=\\mathbf{1}$ gives\n\\[\n(-1)^{\\,nr}\\,(n!)^{\\,r}\\,f(\\mathbf{1})\n=\\sum_{i_{1},\\dots ,i_{r}}\na_{i_{1},\\dots ,i_{r}}\n\\prod_{k=1}^{r}(b_{k,i_{k}})_{n}\n=w^{\\mathsf T}B^{-1}e,\n\\tag{5}\n\\]\nwhere $w:=w^{(r)}\\otimes\\cdots\\otimes w^{(1)}$.\n\n\n\n4.  Kronecker factorisation.  \nThe scalar $w^{\\mathsf T}B^{-1}e$ separates:\n\\[\nw^{\\mathsf T}B^{-1}e\n=(-1)^{\\,1-r}\\,\n\\prod_{k=1}^{r}\\bigl[(w^{(k)})^{\\mathsf T}(B^{(k)})^{-1}u^{(k)}\\bigr].\n\\tag{6}\n\\]\nThus we need the one-variable constant\n\\[\nS_{k}:=(w^{(k)})^{\\mathsf T}(B^{(k)})^{-1}u^{(k)}.\n\\]\n\n\n\n5.  Evaluation of $S_{k}$.  \nFix $k$ and abbreviate $B=B^{(k)},\\,w=w^{(k)},\\,u=u^{(k)}$.\nCramer’s rule gives\n\\[\nB^{-1}u\n=-\\,\\frac{\\operatorname{adj}B_{\\,\\cdot ,1}}{\\det B},\n\\qquad\\Longrightarrow\\qquad\nS_{k}\n=-\\,\\frac{w^{\\mathsf T}\\!\\operatorname{adj}B_{\\,\\cdot ,1}}{\\det B}.\n\\]\nThe numerator is\n$\\det B[1\\leftarrow w]$, the determinant of the matrix obtained by\nreplacing the first \\emph{row} of $B$ by $w^{\\mathsf T}$.  A standard\nfactorial-Vandermonde computation yields\n\\[\n\\det B[1\\leftarrow w]\n=(-1)^{\\,n+1}\\Bigl(\\prod_{j=1}^{n}b_{k,j}\\Bigr)\\det B,\n\\]\nhence\n\\[\nS_{k}=(-1)^{\\,n}\\prod_{j=1}^{n}b_{k,j}.\n\\tag{7}\n\\]\n\n\n\n6.  Completion.  \nInsert (7) into (6):\n\\[\nw^{\\mathsf T}B^{-1}e\n=(-1)^{\\,1-r}\\,\n\\prod_{k=1}^{r}(-1)^{\\,n}\\prod_{j=1}^{n}b_{k,j}\n=(-1)^{\\,nr+1-r}\\,\n\\prod_{k=1}^{r}\\prod_{j=1}^{n}b_{k,j}.\n\\tag{8}\n\\]\n\nCombine (5) with (8).  The factor $(-1)^{\\,nr}$ cancels, leaving\n\\[\nf(1,1,\\dots ,1)\n\\;=\\;\n(-1)^{\\,r-1}\\;\n\\frac{\\displaystyle\\prod_{k=1}^{r}\\prod_{j=1}^{n}b_{k,j}}\n      {(n!)^{\\,r}}.\n\\qquad\\qquad\\blacksquare\n\\]\n\n\n\n────────────────────────────────────────────",
      "metadata": {
        "replaced_from": "harder_variant",
        "replacement_date": "2025-07-14T01:37:45.542325",
        "was_fixed": false,
        "difficulty_analysis": "1. Higher dimensionality.  \n   • The problem moves from one variable to r variables (r≥2), so the\n     unknown polynomial lives in a space of significantly higher\n     dimension.  \n   • The number of unknown coefficients rises from n to n^{r}.  \n   • Mixed partial derivatives and Kronecker-product linear algebra are\n     required.\n\n2. Additional constraints.  \n   • All mixed derivatives of order < n in every direction must vanish at\n     (1,…,1), producing a system of n^{r} simultaneous equations rather\n     than n.\n\n3. More sophisticated structure.  \n   • The solution uses factorial Vandermonde matrices in each variable\n     and their Kronecker product; this demands familiarity with tensor\n     products, multi-index calculus, and properties of block determinants.\n\n4. Deeper theory and multiple interacting concepts.  \n   • One must combine multivariate calculus, combinatorial identities for\n     falling factorials, determinant factorisation, and Kronecker\n     geometry to isolate the single surviving mixed derivative and relate\n     it to det M.  \n   • The determinant evaluation generalises the classical Vandermonde\n     argument to multi-linear algebra, a non-trivial extension.\n\nHence the enhanced variant is substantially more intricate than the\noriginal (one variable, n equations, ordinary Vandermonde) and the\nprevious kernel variant (constant term 2, primes only).  Solving it\ndemands advanced multivariate techniques beyond routine pattern\nmatching."
      }
    }
  },
  "checked": true,
  "problem_type": "proof"
}