Absolute zero is the theoretical temperature at which entropy reaches its minimum value. The laws of thermodynamics state that absolute zero cannot be reached using only thermodynamic means. A system at absolute zero still possesses quantum mechanical zero-point energy, the energy of its ground state. The kinetic energy of the ground state cannot be removed. However, in the classical interpretation it is zero and the thermal energy of matter vanishes.

The zero point of any thermodynamic temperature scale, such as Kelvin or Rankine, is set at absolute zero. By international agreement, absolute zero is defined as 0K on the Kelvin scale and as −273.15 °C on the Celsius scale.[1][2] This equates to −459.67 °F on the Fahrenheit scale and 0 °R on the Rankine scale.[2] Scientists have achieved temperatures very close to absolute zero, where matter exhibits quantum effects such as superconductivity and superfluidity.

The great white shark, scientific name Carcharodon carcharias, also known as the great white, white pointer, white shark, or white death, is a large lamniform shark found in coastal surface waters in all major oceans. It is known for its size, with the largest individuals known to have approached or exceeded 6 metres (20 ft) in length,[3] and 2,268 kilograms (5,000 lb) in weight.[4] This shark reaches maturity at around 15 years of age and can have a life span of over 30 years.

A pseudorandom number generator (PRNG), also known as a deterministic random bit generator (DRBG),[1] is an algorithm for generating a sequence of numbers that approximates the properties of random numbers. The sequence is not truly random in that it is completely determined by a relatively small set of initial values, called the PRNG's state, which includes a truly random seed. Although sequences that are closer to truly random can be generated using hardware random number generators, pseudorandom numbers are important in practice for their speed in number generation and their reproducibility, and they are thus central in applications such as simulations (e.g., of physical systems with the Monte Carlo method), in cryptography, and in procedural generation. Good statistical properties are a central requirement for the output of a PRNG, and common classes of suitable algorithms include linear congruential generators, lagged Fibonacci generators, and linear feedback shift registers.

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