Package cc.redberry.core.tensor

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

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

        OneLoopInput input = new OneLoopInput(4, KINV, K, S, W, N, M, 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));
        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 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);

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