Package cc.redberry.core.tensor

Examples of cc.redberry.core.tensor.Expression.transform()

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                + "+d_d^l*R_c^m"
                + "+d_d^m*R_c^l)"
                + "-g^lm*R_cd"
                + "-R^lm*g_cd"
                + "+(-d_c^l*d_d^m-d_c^m*d_d^l+g^lm*g_cd)*R/2");
        W = (Expression) P.transform(W);
        Expression F = Tensors.parseExpression("F_lm^kd_pr = "
                + "R^k_plm*d^d_r+R^d_rlm*d^k_p");

        OneLoopInput input = new OneLoopInput(2, iK, K, S, W, null, null, F);

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                        + "(1/4)*(d^{m}_{c}*g^{a l}*d^{b}_{d} + d^{m}_{d}*g^{a l}*d^{b}_{c}+d^{m}_{c}*g^{b l}*d^{a}_{d}+ d^{m}_{d}*g^{b l}*d^{a}_{c}) -"
                        + "(1/4)*(g_{cd}*g^{l a}*g^{m b}+g_{cd}*g^{l b}*g^{m a})-"
                        + "(1/4)*(g^{ab}*d^{l}_{c}*d^{m}_{d}+g^{ab}*d^{l}_{d}*d^{m}_{c})+(1/8)*g^{lm}*g_{cd}*g^{ab})");
        Expression P = Tensors.parseExpression(
                "P^{ab}_{lm} = (1/2)*(d^{a}_{l}*d^{b}_{m}+d^{a}_{m}*d^{b}_{l})-(1/4)*g_{lm}*g^{ab}");
        iK = (Expression) P.transform(iK);
        K = (Expression) P.transform(K);

        Expression consts[] = {
                Tensors.parseExpression("c=(1+2*beta)/(5+6*beta)"),
                Tensors.parseExpression("b=-(1+2*beta)/(1+beta)")
 
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                        + "(1/4)*(g_{cd}*g^{l a}*g^{m b}+g_{cd}*g^{l b}*g^{m a})-"
                        + "(1/4)*(g^{ab}*d^{l}_{c}*d^{m}_{d}+g^{ab}*d^{l}_{d}*d^{m}_{c})+(1/8)*g^{lm}*g_{cd}*g^{ab})");
        Expression P = Tensors.parseExpression(
                "P^{ab}_{lm} = (1/2)*(d^{a}_{l}*d^{b}_{m}+d^{a}_{m}*d^{b}_{l})-(1/4)*g_{lm}*g^{ab}");
        iK = (Expression) P.transform(iK);
        K = (Expression) P.transform(K);

        Expression consts[] = {
                Tensors.parseExpression("c=(1+2*beta)/(5+6*beta)"),
                Tensors.parseExpression("b=-(1+2*beta)/(1+beta)")
        };
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        P = (Expression) ExpandTransformation.expand(P,
                EliminateMetricsTransformation.ELIMINATE_METRICS,
                Tensors.parseExpression("R_{l m}^{l}_{a} = R_{ma}"),
                Tensors.parseExpression("R_{lm}^{a}_{a}=0"),
                Tensors.parseExpression("R_{l}^{l}= R"));
        W = (Expression) P.transform(W);
        Expression F = Tensors.parseExpression("F_lm^kd_pr = "
                + "R^k_plm*d^d_r+R^d_rlm*d^k_p");

        OneLoopInput input = new OneLoopInput(2, iK, K, S, W, null, null, F);

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                + "(1/4)*(d^{\\nu}_{\\gamma}*g^{\\alpha \\mu}*d^{\\beta}_{\\delta} + d^{\\nu}_{\\delta}*g^{\\alpha \\mu}*d^{\\beta}_{\\gamma}+d^{\\nu}_{\\gamma}*g^{\\beta \\mu}*d^{\\alpha}_{\\delta}+ d^{\\nu}_{\\delta}*g^{\\beta \\mu}*d^{\\alpha}_{\\gamma}) -"
                + "(1/4)*(g_{\\gamma\\delta}*g^{\\mu \\alpha}*g^{\\nu \\beta}+g_{\\gamma\\delta}*g^{\\mu \\beta}*g^{\\nu \\alpha})-"
                + "(1/4)*(g^{\\alpha\\beta}*d^{\\mu}_{\\gamma}*d^{\\nu}_{\\delta}+g^{\\alpha\\beta}*d^{\\mu}_{\\delta}*d^{\\nu}_{\\gamma})+(1/8)*g^{\\mu\\nu}*g_{\\gamma\\delta}*g^{\\alpha\\beta})");
        Expression P = Tensors.parseExpression(
                "P^{\\alpha\\beta}_{\\mu\\nu} = (1/2)*(d^{\\alpha}_{\\mu}*d^{\\beta}_{\\nu}+d^{\\alpha}_{\\nu}*d^{\\beta}_{\\mu})-(1/4)*g_{\\mu\\nu}*g^{\\alpha\\beta}");
        KINV = (Expression) P.transform(KINV);
        K = (Expression) P.transform(K);

//        Expression consts[] = {Tensors.parseExpression("a=1"),
//                               Tensors.parseExpression("b=0"),
//                               Tensors.parseExpression("d=1"),
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                + "(1/4)*(g_{\\gamma\\delta}*g^{\\mu \\alpha}*g^{\\nu \\beta}+g_{\\gamma\\delta}*g^{\\mu \\beta}*g^{\\nu \\alpha})-"
                + "(1/4)*(g^{\\alpha\\beta}*d^{\\mu}_{\\gamma}*d^{\\nu}_{\\delta}+g^{\\alpha\\beta}*d^{\\mu}_{\\delta}*d^{\\nu}_{\\gamma})+(1/8)*g^{\\mu\\nu}*g_{\\gamma\\delta}*g^{\\alpha\\beta})");
        Expression P = Tensors.parseExpression(
                "P^{\\alpha\\beta}_{\\mu\\nu} = (1/2)*(d^{\\alpha}_{\\mu}*d^{\\beta}_{\\nu}+d^{\\alpha}_{\\nu}*d^{\\beta}_{\\mu})-(1/4)*g_{\\mu\\nu}*g^{\\alpha\\beta}");
        KINV = (Expression) P.transform(KINV);
        K = (Expression) P.transform(K);

//        Expression consts[] = {Tensors.parseExpression("a=1"),
//                               Tensors.parseExpression("b=0"),
//                               Tensors.parseExpression("d=1"),
//                               Tensors.parseExpression("beta=1"),
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        Expression F = Tensors.parseExpression("F_\\mu\\nu\\alpha\\beta=R_\\mu\\nu\\alpha\\beta");


        Expression lambda = Tensors.parseExpression("\\lambda=gamma/(1+gamma)");
        Expression gamma = Tensors.parseExpression("\\gamma=gamma");
        KINV = (Expression) gamma.transform(lambda.transform(KINV));
        K = (Expression) gamma.transform(lambda.transform(K));
        S = (Expression) gamma.transform(lambda.transform(S));
        W = (Expression) gamma.transform(lambda.transform(W));

        OneLoopInput input = new OneLoopInput(2, KINV, K, S, W, null, null, F);
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        Expression lambda = Tensors.parseExpression("\\lambda=gamma/(1+gamma)");
        Expression gamma = Tensors.parseExpression("\\gamma=gamma");
        KINV = (Expression) gamma.transform(lambda.transform(KINV));
        K = (Expression) gamma.transform(lambda.transform(K));
        S = (Expression) gamma.transform(lambda.transform(S));
        W = (Expression) gamma.transform(lambda.transform(W));

        OneLoopInput input = new OneLoopInput(2, KINV, K, S, W, null, null, F);
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        Expression lambda = Tensors.parseExpression("\\lambda=gamma/(1+gamma)");
        Expression gamma = Tensors.parseExpression("\\gamma=gamma");
        KINV = (Expression) gamma.transform(lambda.transform(KINV));
        K = (Expression) gamma.transform(lambda.transform(K));
        S = (Expression) gamma.transform(lambda.transform(S));
        W = (Expression) gamma.transform(lambda.transform(W));

        OneLoopInput input = new OneLoopInput(2, KINV, K, S, W, null, null, F);

        OneLoopCounterterms action = OneLoopCounterterms.calculateOneLoopCounterterms(input);
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        Expression lambda = Tensors.parseExpression("\\lambda=gamma/(1+gamma)");
        Expression gamma = Tensors.parseExpression("\\gamma=gamma");
        KINV = (Expression) gamma.transform(lambda.transform(KINV));
        K = (Expression) gamma.transform(lambda.transform(K));
        S = (Expression) gamma.transform(lambda.transform(S));
        W = (Expression) gamma.transform(lambda.transform(W));

        OneLoopInput input = new OneLoopInput(2, KINV, K, S, W, null, null, F);

        OneLoopCounterterms action = OneLoopCounterterms.calculateOneLoopCounterterms(input);
    }
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