Package cc.redberry.core.tensor

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


        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));
        M = (Expression) gamma.transform(lambda.transform(M));

        OneLoopInput input = new OneLoopInput(4, KINV, K, S, W, N, M, F);
        OneLoopCounterterms action = OneLoopCounterterms.calculateOneLoopCounterterms(input);
    }
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        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));
        M = (Expression) gamma.transform(lambda.transform(M));

        OneLoopInput input = new OneLoopInput(4, KINV, K, S, W, N, M, F);
        OneLoopCounterterms action = OneLoopCounterterms.calculateOneLoopCounterterms(input);
    }
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        Expression W = Tensors.parseExpression("W^{\\alpha}_{\\beta}=(1+beta/2)*R^\\alpha_\\beta");
        Expression F = Tensors.parseExpression("F_\\mu\\nu\\alpha\\beta=R_\\mu\\nu\\alpha\\beta");


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

        OneLoopInput input = new OneLoopInput(2, KINV, K, S, W, null, null, F);
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        Expression F = Tensors.parseExpression("F_\\mu\\nu\\alpha\\beta=R_\\mu\\nu\\alpha\\beta");


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

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

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

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

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

        OneLoopCounterterms action = OneLoopCounterterms.calculateOneLoopCounterterms(input);
    }
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                + "+d_\\delta^\\mu*R_\\gamma^\\nu"
                + "+d_\\delta^\\nu*R_\\gamma^\\mu)"
                + "-g^\\mu\\nu*R_\\gamma\\delta"
                + "-R^\\mu\\nu*g_\\gamma\\delta"
                + "+(-d_\\gamma^\\mu*d_\\delta^\\nu-d_\\gamma^\\nu*d_\\delta^\\mu+g^\\mu\\nu*g_\\gamma\\delta)*R/2");
        W = (Expression) P.transform(W);
        Expression F = Tensors.parseExpression("F_\\mu\\nu^\\lambda\\delta_\\rho\\tau = "
                + "R^\\lambda_\\rho\\mu\\nu*d^\\delta_\\tau+R^\\delta_\\tau\\mu\\nu*d^\\lambda_\\rho");

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

View Full Code Here

                        + "(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("c=(1+2*beta)/(5+6*beta)"),
                Tensors.parseExpression("b=-(1+2*beta)/(1+beta)")
 
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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("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_{\\mu \\nu}^{\\mu}_{\\alpha} = R_{\\nu\\alpha}"),
                Tensors.parseExpression("R_{\\mu\\nu}^{\\alpha}_{\\alpha}=0"),
                Tensors.parseExpression("R_{\\mu}^{\\mu}= R"));
        W = (Expression) P.transform(W);
        Expression F = Tensors.parseExpression("F_\\mu\\nu^\\lambda\\delta_\\rho\\tau = "
                + "R^\\lambda_\\rho\\mu\\nu*d^\\delta_\\tau+R^\\delta_\\tau\\mu\\nu*d^\\lambda_\\rho");

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

View Full Code Here

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