0.000 046 473 597 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 0.000 046 473 597(10) to 64 bit double precision IEEE 754 binary floating point representation standard (1 bit for sign, 11 bits for exponent, 52 bits for mantissa)

What are the steps to convert decimal number
0.000 046 473 597(10) to 64 bit double precision IEEE 754 binary floating point representation (1 bit for sign, 11 bits for exponent, 52 bits for mantissa)

1. First, convert to binary (in base 2) the integer part: 0.
Divide the number repeatedly by 2.

Keep track of each remainder.

We stop when we get a quotient that is equal to zero.


  • division = quotient + remainder;
  • 0 ÷ 2 = 0 + 0;

2. Construct the base 2 representation of the integer part of the number.

Take all the remainders starting from the bottom of the list constructed above.

0(10) =


0(2)


3. Convert to binary (base 2) the fractional part: 0.000 046 473 597.

Multiply it repeatedly by 2.


Keep track of each integer part of the results.


Stop when we get a fractional part that is equal to zero.


  • #) multiplying = integer + fractional part;
  • 1) 0.000 046 473 597 × 2 = 0 + 0.000 092 947 194;
  • 2) 0.000 092 947 194 × 2 = 0 + 0.000 185 894 388;
  • 3) 0.000 185 894 388 × 2 = 0 + 0.000 371 788 776;
  • 4) 0.000 371 788 776 × 2 = 0 + 0.000 743 577 552;
  • 5) 0.000 743 577 552 × 2 = 0 + 0.001 487 155 104;
  • 6) 0.001 487 155 104 × 2 = 0 + 0.002 974 310 208;
  • 7) 0.002 974 310 208 × 2 = 0 + 0.005 948 620 416;
  • 8) 0.005 948 620 416 × 2 = 0 + 0.011 897 240 832;
  • 9) 0.011 897 240 832 × 2 = 0 + 0.023 794 481 664;
  • 10) 0.023 794 481 664 × 2 = 0 + 0.047 588 963 328;
  • 11) 0.047 588 963 328 × 2 = 0 + 0.095 177 926 656;
  • 12) 0.095 177 926 656 × 2 = 0 + 0.190 355 853 312;
  • 13) 0.190 355 853 312 × 2 = 0 + 0.380 711 706 624;
  • 14) 0.380 711 706 624 × 2 = 0 + 0.761 423 413 248;
  • 15) 0.761 423 413 248 × 2 = 1 + 0.522 846 826 496;
  • 16) 0.522 846 826 496 × 2 = 1 + 0.045 693 652 992;
  • 17) 0.045 693 652 992 × 2 = 0 + 0.091 387 305 984;
  • 18) 0.091 387 305 984 × 2 = 0 + 0.182 774 611 968;
  • 19) 0.182 774 611 968 × 2 = 0 + 0.365 549 223 936;
  • 20) 0.365 549 223 936 × 2 = 0 + 0.731 098 447 872;
  • 21) 0.731 098 447 872 × 2 = 1 + 0.462 196 895 744;
  • 22) 0.462 196 895 744 × 2 = 0 + 0.924 393 791 488;
  • 23) 0.924 393 791 488 × 2 = 1 + 0.848 787 582 976;
  • 24) 0.848 787 582 976 × 2 = 1 + 0.697 575 165 952;
  • 25) 0.697 575 165 952 × 2 = 1 + 0.395 150 331 904;
  • 26) 0.395 150 331 904 × 2 = 0 + 0.790 300 663 808;
  • 27) 0.790 300 663 808 × 2 = 1 + 0.580 601 327 616;
  • 28) 0.580 601 327 616 × 2 = 1 + 0.161 202 655 232;
  • 29) 0.161 202 655 232 × 2 = 0 + 0.322 405 310 464;
  • 30) 0.322 405 310 464 × 2 = 0 + 0.644 810 620 928;
  • 31) 0.644 810 620 928 × 2 = 1 + 0.289 621 241 856;
  • 32) 0.289 621 241 856 × 2 = 0 + 0.579 242 483 712;
  • 33) 0.579 242 483 712 × 2 = 1 + 0.158 484 967 424;
  • 34) 0.158 484 967 424 × 2 = 0 + 0.316 969 934 848;
  • 35) 0.316 969 934 848 × 2 = 0 + 0.633 939 869 696;
  • 36) 0.633 939 869 696 × 2 = 1 + 0.267 879 739 392;
  • 37) 0.267 879 739 392 × 2 = 0 + 0.535 759 478 784;
  • 38) 0.535 759 478 784 × 2 = 1 + 0.071 518 957 568;
  • 39) 0.071 518 957 568 × 2 = 0 + 0.143 037 915 136;
  • 40) 0.143 037 915 136 × 2 = 0 + 0.286 075 830 272;
  • 41) 0.286 075 830 272 × 2 = 0 + 0.572 151 660 544;
  • 42) 0.572 151 660 544 × 2 = 1 + 0.144 303 321 088;
  • 43) 0.144 303 321 088 × 2 = 0 + 0.288 606 642 176;
  • 44) 0.288 606 642 176 × 2 = 0 + 0.577 213 284 352;
  • 45) 0.577 213 284 352 × 2 = 1 + 0.154 426 568 704;
  • 46) 0.154 426 568 704 × 2 = 0 + 0.308 853 137 408;
  • 47) 0.308 853 137 408 × 2 = 0 + 0.617 706 274 816;
  • 48) 0.617 706 274 816 × 2 = 1 + 0.235 412 549 632;
  • 49) 0.235 412 549 632 × 2 = 0 + 0.470 825 099 264;
  • 50) 0.470 825 099 264 × 2 = 0 + 0.941 650 198 528;
  • 51) 0.941 650 198 528 × 2 = 1 + 0.883 300 397 056;
  • 52) 0.883 300 397 056 × 2 = 1 + 0.766 600 794 112;
  • 53) 0.766 600 794 112 × 2 = 1 + 0.533 201 588 224;
  • 54) 0.533 201 588 224 × 2 = 1 + 0.066 403 176 448;
  • 55) 0.066 403 176 448 × 2 = 0 + 0.132 806 352 896;
  • 56) 0.132 806 352 896 × 2 = 0 + 0.265 612 705 792;
  • 57) 0.265 612 705 792 × 2 = 0 + 0.531 225 411 584;
  • 58) 0.531 225 411 584 × 2 = 1 + 0.062 450 823 168;
  • 59) 0.062 450 823 168 × 2 = 0 + 0.124 901 646 336;
  • 60) 0.124 901 646 336 × 2 = 0 + 0.249 803 292 672;
  • 61) 0.249 803 292 672 × 2 = 0 + 0.499 606 585 344;
  • 62) 0.499 606 585 344 × 2 = 0 + 0.999 213 170 688;
  • 63) 0.999 213 170 688 × 2 = 1 + 0.998 426 341 376;
  • 64) 0.998 426 341 376 × 2 = 1 + 0.996 852 682 752;
  • 65) 0.996 852 682 752 × 2 = 1 + 0.993 705 365 504;
  • 66) 0.993 705 365 504 × 2 = 1 + 0.987 410 731 008;
  • 67) 0.987 410 731 008 × 2 = 1 + 0.974 821 462 016;

We didn't get any fractional part that was equal to zero. But we had enough iterations (over Mantissa limit) and at least one integer that was different from zero => FULL STOP (Losing precision - the converted number we get in the end will be just a very good approximation of the initial one).


4. Construct the base 2 representation of the fractional part of the number.

Take all the integer parts of the multiplying operations, starting from the top of the constructed list above:


0.000 046 473 597(10) =


0.0000 0000 0000 0011 0000 1011 1011 0010 1001 0100 0100 1001 0011 1100 0100 0011 111(2)

5. Positive number before normalization:

0.000 046 473 597(10) =


0.0000 0000 0000 0011 0000 1011 1011 0010 1001 0100 0100 1001 0011 1100 0100 0011 111(2)

6. Normalize the binary representation of the number.

Shift the decimal mark 15 positions to the right, so that only one non zero digit remains to the left of it:


0.000 046 473 597(10) =


0.0000 0000 0000 0011 0000 1011 1011 0010 1001 0100 0100 1001 0011 1100 0100 0011 111(2) =


0.0000 0000 0000 0011 0000 1011 1011 0010 1001 0100 0100 1001 0011 1100 0100 0011 111(2) × 20 =


1.1000 0101 1101 1001 0100 1010 0010 0100 1001 1110 0010 0001 1111(2) × 2-15


7. Up to this moment, there are the following elements that would feed into the 64 bit double precision IEEE 754 binary floating point representation:

Sign 0 (a positive number)


Exponent (unadjusted): -15


Mantissa (not normalized):
1.1000 0101 1101 1001 0100 1010 0010 0100 1001 1110 0010 0001 1111


8. Adjust the exponent.

Use the 11 bit excess/bias notation:


Exponent (adjusted) =


Exponent (unadjusted) + 2(11-1) - 1 =


-15 + 2(11-1) - 1 =


(-15 + 1 023)(10) =


1 008(10)


9. Convert the adjusted exponent from the decimal (base 10) to 11 bit binary.

Use the same technique of repeatedly dividing by 2:


  • division = quotient + remainder;
  • 1 008 ÷ 2 = 504 + 0;
  • 504 ÷ 2 = 252 + 0;
  • 252 ÷ 2 = 126 + 0;
  • 126 ÷ 2 = 63 + 0;
  • 63 ÷ 2 = 31 + 1;
  • 31 ÷ 2 = 15 + 1;
  • 15 ÷ 2 = 7 + 1;
  • 7 ÷ 2 = 3 + 1;
  • 3 ÷ 2 = 1 + 1;
  • 1 ÷ 2 = 0 + 1;

10. Construct the base 2 representation of the adjusted exponent.

Take all the remainders starting from the bottom of the list constructed above.


Exponent (adjusted) =


1008(10) =


011 1111 0000(2)


11. Normalize the mantissa.

a) Remove the leading (the leftmost) bit, since it's allways 1, and the decimal point, if the case.


b) Adjust its length to 52 bits, only if necessary (not the case here).


Mantissa (normalized) =


1. 1000 0101 1101 1001 0100 1010 0010 0100 1001 1110 0010 0001 1111 =


1000 0101 1101 1001 0100 1010 0010 0100 1001 1110 0010 0001 1111


12. The three elements that make up the number's 64 bit double precision IEEE 754 binary floating point representation:

Sign (1 bit) =
0 (a positive number)


Exponent (11 bits) =
011 1111 0000


Mantissa (52 bits) =
1000 0101 1101 1001 0100 1010 0010 0100 1001 1110 0010 0001 1111


Decimal number 0.000 046 473 597 converted to 64 bit double precision IEEE 754 binary floating point representation:

0 - 011 1111 0000 - 1000 0101 1101 1001 0100 1010 0010 0100 1001 1110 0010 0001 1111


How to convert numbers from the decimal system (base ten) to 64 bit double precision IEEE 754 binary floating point standard

Follow the steps below to convert a base 10 decimal number to 64 bit double precision IEEE 754 binary floating point:

  • 1. If the number to be converted is negative, start with its the positive version.
  • 2. First convert the integer part. Divide repeatedly by 2 the positive representation of the integer number that is to be converted to binary, until we get a quotient that is equal to zero, keeping track of each remainder.
  • 3. Construct the base 2 representation of the positive integer part of the number, by taking all the remainders from the previous operations, starting from the bottom of the list constructed above. Thus, the last remainder of the divisions becomes the first symbol (the leftmost) of the base two number, while the first remainder becomes the last symbol (the rightmost).
  • 4. Then convert the fractional part. Multiply the number repeatedly by 2, until we get a fractional part that is equal to zero, keeping track of each integer part of the results.
  • 5. Construct the base 2 representation of the fractional part of the number, by taking all the integer parts of the multiplying operations, starting from the top of the list constructed above (they should appear in the binary representation, from left to right, in the order they have been calculated).
  • 6. Normalize the binary representation of the number, shifting the decimal mark (the decimal point) "n" positions either to the left, or to the right, so that only one non zero digit remains to the left of the decimal mark.
  • 7. Adjust the exponent in 11 bit excess/bias notation and then convert it from decimal (base 10) to 11 bit binary, by using the same technique of repeatedly dividing by 2, as shown above:
    Exponent (adjusted) = Exponent (unadjusted) + 2(11-1) - 1
  • 8. Normalize mantissa, remove the leading (leftmost) bit, since it's allways '1' (and the decimal mark, if the case) and adjust its length to 52 bits, either by removing the excess bits from the right (losing precision...) or by adding extra bits set on '0' to the right.
  • 9. Sign (it takes 1 bit) is either 1 for a negative or 0 for a positive number.

Example: convert the negative number -31.640 215 from the decimal system (base ten) to 64 bit double precision IEEE 754 binary floating point:

  • 1. Start with the positive version of the number:

    |-31.640 215| = 31.640 215

  • 2. First convert the integer part, 31. Divide it repeatedly by 2, keeping track of each remainder, until we get a quotient that is equal to zero:
    • division = quotient + remainder;
    • 31 ÷ 2 = 15 + 1;
    • 15 ÷ 2 = 7 + 1;
    • 7 ÷ 2 = 3 + 1;
    • 3 ÷ 2 = 1 + 1;
    • 1 ÷ 2 = 0 + 1;
    • We have encountered a quotient that is ZERO => FULL STOP
  • 3. Construct the base 2 representation of the integer part of the number by taking all the remainders of the previous dividing operations, starting from the bottom of the list constructed above:

    31(10) = 1 1111(2)

  • 4. Then, convert the fractional part, 0.640 215. Multiply repeatedly by 2, keeping track of each integer part of the results, until we get a fractional part that is equal to zero:
    • #) multiplying = integer + fractional part;
    • 1) 0.640 215 × 2 = 1 + 0.280 43;
    • 2) 0.280 43 × 2 = 0 + 0.560 86;
    • 3) 0.560 86 × 2 = 1 + 0.121 72;
    • 4) 0.121 72 × 2 = 0 + 0.243 44;
    • 5) 0.243 44 × 2 = 0 + 0.486 88;
    • 6) 0.486 88 × 2 = 0 + 0.973 76;
    • 7) 0.973 76 × 2 = 1 + 0.947 52;
    • 8) 0.947 52 × 2 = 1 + 0.895 04;
    • 9) 0.895 04 × 2 = 1 + 0.790 08;
    • 10) 0.790 08 × 2 = 1 + 0.580 16;
    • 11) 0.580 16 × 2 = 1 + 0.160 32;
    • 12) 0.160 32 × 2 = 0 + 0.320 64;
    • 13) 0.320 64 × 2 = 0 + 0.641 28;
    • 14) 0.641 28 × 2 = 1 + 0.282 56;
    • 15) 0.282 56 × 2 = 0 + 0.565 12;
    • 16) 0.565 12 × 2 = 1 + 0.130 24;
    • 17) 0.130 24 × 2 = 0 + 0.260 48;
    • 18) 0.260 48 × 2 = 0 + 0.520 96;
    • 19) 0.520 96 × 2 = 1 + 0.041 92;
    • 20) 0.041 92 × 2 = 0 + 0.083 84;
    • 21) 0.083 84 × 2 = 0 + 0.167 68;
    • 22) 0.167 68 × 2 = 0 + 0.335 36;
    • 23) 0.335 36 × 2 = 0 + 0.670 72;
    • 24) 0.670 72 × 2 = 1 + 0.341 44;
    • 25) 0.341 44 × 2 = 0 + 0.682 88;
    • 26) 0.682 88 × 2 = 1 + 0.365 76;
    • 27) 0.365 76 × 2 = 0 + 0.731 52;
    • 28) 0.731 52 × 2 = 1 + 0.463 04;
    • 29) 0.463 04 × 2 = 0 + 0.926 08;
    • 30) 0.926 08 × 2 = 1 + 0.852 16;
    • 31) 0.852 16 × 2 = 1 + 0.704 32;
    • 32) 0.704 32 × 2 = 1 + 0.408 64;
    • 33) 0.408 64 × 2 = 0 + 0.817 28;
    • 34) 0.817 28 × 2 = 1 + 0.634 56;
    • 35) 0.634 56 × 2 = 1 + 0.269 12;
    • 36) 0.269 12 × 2 = 0 + 0.538 24;
    • 37) 0.538 24 × 2 = 1 + 0.076 48;
    • 38) 0.076 48 × 2 = 0 + 0.152 96;
    • 39) 0.152 96 × 2 = 0 + 0.305 92;
    • 40) 0.305 92 × 2 = 0 + 0.611 84;
    • 41) 0.611 84 × 2 = 1 + 0.223 68;
    • 42) 0.223 68 × 2 = 0 + 0.447 36;
    • 43) 0.447 36 × 2 = 0 + 0.894 72;
    • 44) 0.894 72 × 2 = 1 + 0.789 44;
    • 45) 0.789 44 × 2 = 1 + 0.578 88;
    • 46) 0.578 88 × 2 = 1 + 0.157 76;
    • 47) 0.157 76 × 2 = 0 + 0.315 52;
    • 48) 0.315 52 × 2 = 0 + 0.631 04;
    • 49) 0.631 04 × 2 = 1 + 0.262 08;
    • 50) 0.262 08 × 2 = 0 + 0.524 16;
    • 51) 0.524 16 × 2 = 1 + 0.048 32;
    • 52) 0.048 32 × 2 = 0 + 0.096 64;
    • 53) 0.096 64 × 2 = 0 + 0.193 28;
    • We didn't get any fractional part that was equal to zero. But we had enough iterations (over Mantissa limit = 52) and at least one integer part that was different from zero => FULL STOP (losing precision...).
  • 5. Construct the base 2 representation of the fractional part of the number, by taking all the integer parts of the previous multiplying operations, starting from the top of the constructed list above:

    0.640 215(10) = 0.1010 0011 1110 0101 0010 0001 0101 0111 0110 1000 1001 1100 1010 0(2)

  • 6. Summarizing - the positive number before normalization:

    31.640 215(10) = 1 1111.1010 0011 1110 0101 0010 0001 0101 0111 0110 1000 1001 1100 1010 0(2)

  • 7. Normalize the binary representation of the number, shifting the decimal mark 4 positions to the left so that only one non-zero digit stays to the left of the decimal mark:

    31.640 215(10) =
    1 1111.1010 0011 1110 0101 0010 0001 0101 0111 0110 1000 1001 1100 1010 0(2) =
    1 1111.1010 0011 1110 0101 0010 0001 0101 0111 0110 1000 1001 1100 1010 0(2) × 20 =
    1.1111 1010 0011 1110 0101 0010 0001 0101 0111 0110 1000 1001 1100 1010 0(2) × 24

  • 8. Up to this moment, there are the following elements that would feed into the 64 bit double precision IEEE 754 binary floating point representation:

    Sign: 1 (a negative number)

    Exponent (unadjusted): 4

    Mantissa (not-normalized): 1.1111 1010 0011 1110 0101 0010 0001 0101 0111 0110 1000 1001 1100 1010 0

  • 9. Adjust the exponent in 11 bit excess/bias notation and then convert it from decimal (base 10) to 11 bit binary (base 2), by using the same technique of repeatedly dividing it by 2, as shown above:

    Exponent (adjusted) = Exponent (unadjusted) + 2(11-1) - 1 = (4 + 1023)(10) = 1027(10) =
    100 0000 0011(2)

  • 10. Normalize mantissa, remove the leading (leftmost) bit, since it's allways '1' (and the decimal sign) and adjust its length to 52 bits, by removing the excess bits, from the right (losing precision...):

    Mantissa (not-normalized): 1.1111 1010 0011 1110 0101 0010 0001 0101 0111 0110 1000 1001 1100 1010 0

    Mantissa (normalized): 1111 1010 0011 1110 0101 0010 0001 0101 0111 0110 1000 1001 1100

  • Conclusion:

    Sign (1 bit) = 1 (a negative number)

    Exponent (8 bits) = 100 0000 0011

    Mantissa (52 bits) = 1111 1010 0011 1110 0101 0010 0001 0101 0111 0110 1000 1001 1100

  • Number -31.640 215, converted from decimal system (base 10) to 64 bit double precision IEEE 754 binary floating point =
    1 - 100 0000 0011 - 1111 1010 0011 1110 0101 0010 0001 0101 0111 0110 1000 1001 1100