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20201115 ASERT
layout: specification
title: ASERT Difficulty Adjustment Algorithm (aserti32d)
date: 20200817
category: spec
activation: 1605441600
version: 0.6.3
author: freetrader, Jonathan Toomim, Calin Culianu, Mark Lundeberg, Tobias Ruck
Summary
Activation of a new new difficulty adjustment algorithm ‘aserti32d’ (or ‘ASERT’ for short) for the November 2020 Bitcoin Cash upgrade. Activation will be based on MTP, with the last prefork block used as the anchor block.
Motivation
 To eliminate periodic oscillations in difficulty and hashrate
 To reduce the difference in profitability between steady miners and those who switch to mining other blockchains.
 To maintain average block intervals close to the 10 minute target.
 To bring the average transaction confirmation time close to target time.
Technical background
The November 2017 Bitcoin Cash upgrade introduced a simple moving average as difficulty adjustment algorithm. This change unfortunately introduced daily periodic difficulty oscillations, which resulted in long confirmation times followed by a burst of rapid blocks. This harms the user experience of Bitcoin Cash, and punishes steady hashrate miners.
Research into the family of difficulty algorithms based on an exponential moving average (EMA) resulted in ASERT (Absolutely Scheduled Exponentially Rising Targets) [1], which has been developed by Mark Lundeberg in 2019 and fully described by him in 2020. An equivalent formula was independently discovered in 2018 by Jacob Eliosoff and in 2020 by Werner et. al [6].
ASERT does not have the same oscillations as the DAA introduced in the November 2017 upgrade and has a range of other attractive qualities such as robustness against singularities [15] without a need for additional rules, and absence of accumulation of rounding/approximation errors.
In extensive simulation against a range of other stable algorithms [2], an ASERT algorithm performed best across criteria that included:
 Average block times closest to an ideal target time of 600 seconds.
 Average transaction confirmation times closest to the target time.
 Reducing the advantage of nonsteady mining strategies, thereby maximizing the relative profitability of steady mining.
Specification
Terms and conventions
 Fork block: The first block mined according to the new consensus rules.
 Anchor block: The parent of the fork block.
Requirements
Target computation
The current block’s target bits are calculated by the following algorithm.
The aserti32d algorithm can be described by the following formula:
next_target = anchor_target * 2**((time_delta  ideal_block_time * (height_delta + 1)) / halflife)
where:
anchor_target
is the unsigned 256 bit integer equivalent of thenBits
value in the header of the anchor block.time_delta
is the difference, in signed integer seconds, between the timestamp in the header of the current block and the timestamp in the parent of the anchor block.ideal_block_time
is a constant: 600 seconds, the targeted average time between blocks.height_delta
is the difference in block height between the current block and the anchor block.halflife
is a constant parameter sometimes referred to as ’tau’, with a value of 172800 (seconds) on mainnet.next_target
is the integer value of the target computed for the block after the current block.
The algorithm below implements the above formula using fixedpoint integer arithmetic and a cubic polynomial approximation to the 2^x term.
The ’target’ values used as input and output are the compact representations of actual 256bit integer targets as specified for the ’nBits’ field in the block header.
Pythoncode, uses Python 3 syntax:
def next_target_aserti3_2d(
anchor_height: int, # height of the anchor block.
anchor_parent_time: int, # timestamp (nTime) of the parent of the anchor block.
anchor_bits: int, # 'nBits' value of the anchor block.
current_height: int, # height of the current block.
current_time: int, # timestamp of the current block.
) > int: # 'target' nBits of the current block.
ideal_block_time = 600 # in seconds
halflife = 172_800 # 2 days (in seconds)
radix = 2**16 # 16 bits for decimal part of fixedpoint integer arithmetic
max_bits = 0x1d00_ffff # maximum target in nBits representation
max_target = bits_to_target(max_bits) # maximum target as integer
anchor_target = bits_to_target(anchor_bits)
time_delta = current_time  anchor_parent_time
height_delta = current_height  anchor_height # can be negative
# `//` is truncating division (int.__floordiv__)  see note 3 below
exponent = time_delta  ideal_block_time * (height_delta + 1) // halflife
# Compute equivalent of `num_shifts = math.floor(exponent / 2**16)`
num_shifts = exponent >> 16
exponent = exponent  num_shifts * radix
factor = ((195_766_423_245_049 * exponent +
971_821_376 * exponent**2 +
5_127 * exponent**3 +
2**47) >> 48) + radix
next_target = anchor_target * factor
# Calculate `next_target = math.floor(next_target * 2**factor)`
if num_shifts < 0:
next_target >>= num_shifts
else:
# Implementations should be careful of overflow here (see note 6 below).
next_target <<= num_shifts
next_target >>= 16
if next_target == 0:
return target_to_bits(1) # hardest valid target
if next_target > max_target:
return max_bits # limit on easiest target
return target_to_bits(next_target)
Note 1: The reference implementations make use of signed integer arithmetic. Alternative implementations may use strictly unsigned integer arithmetic.
Note 2: All implementations should strictly avoid use of floating point arithmetic in the computation of the exponent.
Note 3: In the calculation of the exponent, truncating integer division [7, 10]
must be used, as indicated by the //
division operator (int.__floordiv__
).
Note 5: The convenience functions bits_to_target()
and target_to_bits()
are assumed to be available for conversion between compact ’nBits’
and unsigned 256bit integer representations of targets.
Examples of such functions are available in the C++ and Python3
reference implementations.
Note 6: If a limitedwidth integer type is used for current_target
, then the <<
operator may cause an overflow exception or silent discarding of
mostsignificant bits.
Implementations must detect and handle such cases to correctly emulate
the behaviour of an unlimitedwidth calculation. Note that if the result
at this point would exceed radix * max_target
then max_bits
may be returned
immediately.
Note 7: The polynomial approximation that computes factor
must be performed
with 64 bit unsigned integer arithmetic or better. It will
overflow a signed 64 bit integer. Since exponent is signed, it may be
necessary to cast it to unsigned 64 bit integer. In languages like
Java where long is always signed, an unsigned shift >>> 48
must be
used to divide by 2^48.
Activation
The ASERT algorithm will be activated according to the toplevel upgrade spec [3].
Anchor block
ASERT requires the choice of an anchor block to schedule future target computations.
The first block with an MTP that is greater/equal to the upgrade activation time will be used as the anchor block for subsequent ASERT calculations.
This corresponds to the last block mined under the preASERT DAA rules.
Note 1: The anchor block is the block whose height and target (nBits) are used as the ‘absolute’ basis for ASERT’s scheduled target. The timestamp (nTime) of the anchor block’s parent is used.
Note 2: The height, timestamp, and nBits of this block are not known ahead of the upgrade. Implementations MUST dynamically determine it across the upgrade. Once the network upgrade has been consolidated by sufficient chain work or a checkpoint, implementations can simply hardcode the known height, nBits and associated (parent) timestamp this anchor block. Implementations MAY also hardcode other equivalent representations, such as an nBits value and a time offset from the genesis block.
REQASERTTESTNETDIFFRESET (testnet difficulty reset)
On testnet, an additional rule will be included: Any block with a timestamp
that is more than 1200 seconds after its parent’s timestamp must use an
nBits value of max_bits
(0x1d00ffff
).
Rationale and commentary on requirements / design decisions

Choice of anchor block determination
Choosing an anchor block that is far enough in the past would result in slightly simpler coding requirements but would create the possibility of a significant difficulty adjustment at the upgrade.
The last block mined according to the old DAA was chosen since this block is the most proximal anchor and allows for the smoothest transition to the new algorithm.

Avoidance of floating point calculations
Compliance with IEEE754 floating point arithmetic is not generally guaranteed by programming languages on which a new DAA needs to be implemented. This could result in floating point calculations yielding different results depending on compilers, interpreters or hardware.
It is therefore highly advised to perform all calculations purely using integers and highly specific operators to ensure identical difficulty targets are enforced across all implementations.

Choice of halflife
A halflife of 2 days (
halflife = 2 * 24 * 3600
), equivalent to an e^xbased time constant of2 * 144 * ln(2)
or aserti3415.5, was chosen because it reaches nearoptimal performance in simulations by balancing the need to buffer against statistical noise and the need to respond rapidly to swings in price or hashrate, while also being easy for humans to understand: For every 2 days ahead of schedule a block’s timestamp becomes, the difficulty doubles. 
Choice of approximation polynomial
The DAA is part of a control system feedback loop that regulates hashrate, and the exponential function and its integer approximation comprise its transfer function. As such, standard guidelines for ensuring control system stability apply. Control systems tend to be far more sensitive to differential nonlinearity (DNL) than integral nonlinearity (INL) in their transfer functions. Our requirements were to have a transfer function that was (a) monotonic, (b) contained no abrupt changes, (c) had precision and differential nonlinearity that was better than our multiblock statistical noise floor, (d) was simple to implement, and (e) had integral nonlinearity that was no worse than our singleblock statistical noise floor.
A simple, fast to compute cubic approximation of 2^x for 0 <= x < 1 was found to satisfy all of these requirements. It maintains an absolute error margin below 0.013% over this range [8]. In order to address the full (infinity, +infinity) domain of the exponential function, we found the
2**(x + n) = 2**n * 2**x
identity to be of use. Our cubic approximation gives the exactly correct valuesf(0) == 1
andf(1) == 2
, which allows us to use this identity without concern for discontinuities at the edges of the approximation’s domain.First, there is the issue of DNL. Our goal was to ensure that our algorithm added no more than 25% as much noise as is inherent in our dataset. Our algorithm is effectively trying to estimate the characteristic hashrate over the recent past, using a 2day (~288block) halflife. Our expected exponential distribution of block intervals has a standard deviation (stddev) of 600 seconds. Over a 2day halflife, our noise floor in our estimated hashrate should be about
sqrt(1 / 288) * 600
seconds, or 35.3 seconds. Our chosen approximation method is able to achieve precision of 3 seconds in most circumstances, limited in two places by 16bit operations:172800 sec / 65536 = 2.6367 sec
Our worstcase precision is 8 seconds, and is limited by the worstcase 15bit precision of the nBits value. This 8 second worstcase is not within the scope of this work to address, as it would require a change to the block header. Our worstcase step size is 0.00305%,[11] due to the worstcase 15bit nBits mantissa issue. Outside the 15bit nBits mantissa range, our approximation has a worstcase precision of 0.0021%. Overall, we considered this to be satisfactory DNL performance.Second, there is the issue of INL. Simulation testing showed that difficulty and hashrate regulation performance was remarkably insensitive to integral nonlinearity. We found that even the use of
f(x) = 1 + x
as an approximation of2**x
in theaserti1
algorithm was satisfactory when coupled with the2**(x + n) = 2^n * 2^x
identity, despite having 6% worstcase INL.[12, 13] An approximation with poor INL will still show good hashrate regulation ability, but will have a different amount of drift for a given change in hashrate depending on where in the [0, 1) domain our exponent (modulo 1) lies. With INL of +/ 1%, for any given difficulty (or target), a block’s timestamp might end up being 1% of 172800 seconds ahead of or behind schedule. However, out of an abundance of caution, and because achieving higher precision was easy, we chose to aim for INL that would be comparable to or less than the typical drift that can be caused by one block. Out of a 2day halflife window, one block’s variance comprises:600 / 172800 = 0.347%
Our cubic approximation’s INL performance is better than 0.013%,[14] which exceeds that requirement by a comfortable margin. 
Conversion of difficulty bits (nBits) to 256bit target representations
As there are few calculations in ASERT which involve 256bit integers and the algorithm is executed infrequently, it was considered unnecessary to require more complex operations such as doing arithmetic directly on the compact target representations (nBits) that are the inputs/output of the difficulty algorithm.
Furthermore, 256bit (or even bignum) arithmetic is available in existing implementation and used within the previous DAA. Performance impacts are negligible.

Choice of 16bits of precision for fixedpoint math
The nBits format is comprised of 8 bits of base_256 exponent, followed by a 24bit mantissa. The mantissa must have a value of at least 0x008000, which means that the worstcase scenario gives the mantissa only 15 bits of precision. The choice of 16bit precision in our fixed point math ensures that overall precision is limited by this 15bit nBits limit.

Choice of name
The specific algorithm name ‘aserti32d’ was chosen based on:
 the ‘i’ refers to the integeronly arithmetic
 the ‘3’ refers to the cubic approximation of the exponential
 the ‘2d’ refers to the 2day (172800 second) halflife
Implementation advice
Implementations must not make any rounding errors during their calculations. Rounding must be done exactly as specified in the algorithm. In practice, to guarantee that, you likely need to use integer arithmetic exclusively.
Implementations which use signed integers and use bitshifting must ensure that the bitshifting is arithmetic.
Note 1: In C++ compilers, right shifting negative signed integers is formally unspecified behavior until C++20 when it will become standard [5]. In practice, C/C++ compilers commonly implement arithmetic bit shifting for signed numbers. Implementers are advised to verify good behavior through compiletime assertions or unit tests.
Reference implementations
 C++ code for aserti32d (see pow.cpp): https://reviews.bitcoinabc.org/D7174
 Python3 code (see contrib/testgen/validate_nbits_aserti3_2d.py): https://gitlab.com/bitcoincashnode/bitcoincashnode//merge_requests/692
 Java code: https://github.com/pokkst/asertjava
Test vectors
Test vectors suitable for validating further implementations of the aserti32d algorithm are available at:
alternatively at:
https://gitlab.com/bitcoincashnode/bchnsw/qaassets//tree/master/test_vectors/aserti32d
and alternatively at:
https://download.bitcoincashnode.org/misc/data/asert/test_vectors
Acknowledgements
Thanks to Mark Lundeberg for granting permission to publish the ASERT paper [1], Jonathan Toomim for developing the initial Python and C++ implementations, upgrading the simulation framework [9] and evaluating the various difficulty algorithms.
Thanks to Jacob Eliosoff, Tom Harding and Scott Roberts for evaluation work on the families of EMA and other algorithms considered as replacements for the Bitcoin Cash DAA, and thanks to the following for review and their valuable suggestions for improvement:
 Andrea Suisani (sickpig)
 BigBlockIfTrue
 Fernando Pellicioni
 imaginary_username
 mtrycz
 Jochen Hoenicke
 John Nieri (emergent_reasons)
 Tom Zander
References
[1] “Static difficulty adjustments, with absolutely scheduled exponentially rising targets (DAASERT) – v2”, Mark B. Lundeberg, July 31, 2020
[2] “BCH upgrade proposal: Use ASERT as the new DAA”, Jonathan Toomim, 8 July 2020
[3] Bitcoin Cash November 15, 2020 Upgrade Specification.
[4] https://en.wikipedia.org/wiki/Arithmetic_shift
[5] https://en.cppreference.com/w/cpp/language/operator_arithmetic
[6] “Unstable Throughput: When the Difficulty Algorithm Breaks”, Sam M. Werner, Dragos I. Ilie, Iain Stewart, William J. Knottenbelt, June 2020
[7] “Different kinds of integer division”, Harry Garrood, blog, 2018
[8] Error in a cubic approximation of 2^x for 0 <= x < 1
[9] Jonathan Toomim adaptation of kyuupichan’s difficulty algorithm simulator: https://github.com/jtoomim/difficulty/tree/comparator
[10] “The Euclidean definition of the functions div and mod”, Raymond T. Boute, 1992, ACM Transactions on Programming Languages and Systems (TOPLAS). 14. 127144. 10.1145/128861.128862
[11] http://toom.im/bch/aserti3_step_size.html
[12] f(x) = (1 + x)/2^x for 0<x<1, WolframAlpha.
[13] https://github.com/zawy12/difficultyalgorithms/issues/62#issuecomment647060200
[14] http://toom.im/bch/aserti3_approx_error.html
[15] https://github.com/zawy12/difficultyalgorithms/issues/62#issuecomment646187957
License
This specification is duallicensed under the Creative Commons CC0 1.0 Universal and GNU AllPermissive licenses.