← Back to article

Equation 73 · The Bit Comes Back Before the Bearing

What does this equation mean?

⟨Sm,n⟩=∑k=n+1mn1k  −  m−12n\langle S_{m,n}\rangle = \sum_{k=n+1}^{mn}\frac1k \;-\; \frac{m-1}{2n}

Read the formula alongside the article passage below. Each part has a deeper page with its role in the equation, the supporting passage and nearby citations.

Start withm-1
Divide by2n
This relates tolangle S_m,nrangle
How to read the two sides of this formula. Follow the article passage for the meaning of each quantity.

This equation states an equality: the expressions on both sides have the same value under the article’s assumptions. Read the equation part by part below; each part has a contextual explanation and a link to its mathematical background.

Read it piece by piece

Sm,nS_{m,n}

Symbol S_m,n

SmS_m,n is part of the quantity the equation computes from the expression on the right.

Understand this part →

kk

Symbol k

k appears in the bound of this sum. The bound states where the repeated operation starts, ends, or which values it includes.

Understand this part →

nn

Symbol n

n occurs below the fraction bar. The quantity above the bar is divided by this expression; zero is excluded as a denominator.

Understand this part →

mm

Symbol m

m occurs above the fraction bar. The numerator is divided by the entire denominator below it.

Understand this part →

=

=

The expressions on both sides represent the same quantity under the stated assumptions.

Understand this part →

See an illustrated explanation →
fraction

fraction

Divide the expression above the line by the one below it.

Understand this part →

See an illustrated explanation →
addition

addition

Add the term after the plus sign to the term or group before it.

Understand this part →

subtraction

subtraction

Subtract the following term or group from the preceding one. A leading minus marks a negative quantity.

Understand this part →

subscript

subscript

The lower label selects a particular version, component, or indexed member of the quantity. For example, x₀ and xₜ can be values at different positions.

Understand this part →

superscript

superscript

A raised number can be a power. When it is a label or bound, it selects a case or the upper limit of a sum; the formula’s structure distinguishes these uses.

Understand this part →

See an illustrated explanation →
k=n+1k=n+1

Starting index or lower bound: k=n+1

This label says where the repeated addition, multiplication, or accumulation starts. Read its value or condition together with the article’s description of the index.

Understand this part →

mnmn

Ending index or upper bound: mn

This label says where the repeated addition, multiplication, or accumulation stops. It sets the last term or end of the range.

Understand this part →

m−1m-1

Numerator: m-1

The complete quantity above the fraction bar.

Understand this part →

2n2n

Denominator: 2n

The complete quantity below the fraction bar; it must be nonzero for this division.

Understand this part →

How to interpret it

With a fixed numerator, increasing a nonzero denominator reduces the fraction. Read it with the definitions, units, and assumptions supplied by the article.

What the article says around this equation

Hayden and Preskill’s own result, sharpened into an explicit, efficient decoding circuit by Yoshida and Kitaev, is that once scrambling of this kind has run for about t∗t_* , collecting only a handful more qubits of radiation than were thrown in — not a number that grows with the hole’s size — suppresses ϵL\epsilon_L exponentially in that small handful [ 15 ] . The mechanism behind that exponential suppression is worth seeing exactly rather than taking on faith, and Page’s own formula for the average entanglement entropy of a subsystem of a random pure state supplies it. For an m -dimensional subsystem embedded in an mn -dimensional Haar-random pure state, ⟨Sm,n⟩=∑k=n+1mn1k  −  m−12n\langle S_{m,n}\rangle = \sum_{k=n+1}^{mn}\frac1k \;-\; \frac{m-1}{2n}. is exact [ 4 ] .…
Read the full surrounding passage
Hayden and Preskill’s own result, sharpened into an explicit, efficient decoding circuit by Yoshida and Kitaev, is that once scrambling of this kind has run for about t∗t_* , collecting only a handful more qubits of radiation than were thrown in — not a number that grows with the hole’s size — suppresses ϵL\epsilon_L exponentially in that small handful [ 15 ] . The mechanism behind that exponential suppression is worth seeing exactly rather than taking on faith, and Page’s own formula for the average entanglement entropy of a subsystem of a random pure state supplies it. For an m -dimensional subsystem embedded in an mn -dimensional Haar-random pure state, ⟨Sm,n⟩=∑k=n+1mn1k  −  m−12n\langle S_{m,n}\rangle = \sum_{k=n+1}^{mn}\frac1k \;-\; \frac{m-1}{2n}. is exact [ 4 ] . Fixing m=2 (a single qubit) and letting n — the effective size of everything else the qubit could be entangled with — grow gives ⟨\langle S2,4S_{2,4}⟩\rangle = 0.5095 nats, ⟨\langle S2,16S_{2,16}⟩\rangle = 0.6465 nats, and ⟨\langle S2,64S_{2,64}⟩\rangle = 0.6814 nats, closing in on the ceiling ln⁡\ln 2 = 0.6931 nats. The residual gap to that ceiling shrinks by a factor of 3.94 when n quadruples from 4 to 16 , and by 3.98 when it quadruples again from 16 to 64 — converging, as more radiation-sized dimension is added two qubits at a time, on a clean factor of four per doubling of collected qubits, or two per single qubit. This is an exact, hand-computable corroboration of the folklore “each extra collected qubit roughly halves what is left to recover,” not a re-derivation of Hayden and Preskill’s original bound, and it is why tL(ϵ)t_L(\epsilon) depends on ϵ\epsilon only logarithmically: driving ϵ\epsilon from 10^{-1} to 10^{-9} costs on the order of thirty extra qubits of radiation, a negligible addition to t∗t_* for any astrophysically sized hole. None of this requires the hole’s dynamics to be literally Haar-random for an unbounded time; Harrow and Low showed that circuits of only polynomial depth already approximate the Haar distribution’s first two moments closely enough for arguments like this one to apply [ 14 ] .

Read the equation in its article →

Sources cited in the surrounding passage

These citations give research context. Read each source to check which claims it supports.

Return to The Bit Comes Back Before the Bearing

See this formula across 1 published context →

Browse the mathematical compendium →