Non-Markovian jumping process conjecture for the birth Mallows process

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Let n≥4n\geq 4, and let (Mt)t∈[0,∞)({\mathcal{M}}_t)_{t\in[0,\infty)} be the birth Mallows process. If TkT_k are its jump times, its jumping process is (MTk)0≤k≤(n2)({\mathcal{M}}_{T_k})_{0\leq k\leq\binom{n}{2}}. Non-Markovian jumping-process conjecture. For every n≥4n\geq 4, the jumping process of the birth Mallows process is not a Markov chain. The source says that computations for small nn support this claim, but that no formal proof is available.

References

Primary source

Benoît Corsini, “Continuous-time Mallows processes”, arXiv:2205.04967 (2022).

Progress summary

Refreshed
Claimed solved

The original paper had only small-computation evidence, while a reader-written argument claims a complete proof for all cases, but it has not been independently checked.

The conjecture asserts that, for every n≥4n\geq 4, the jump sequence of the birth Mallows process is not a Markov chain. Benoît Corsini recorded it as Conjecture 3 in 2022 and stated that no formal proof was available.

Known results

  • Corsini (2022): computations for small nn support non-Markovianity but do not prove the conjecture.
  • Corsini (2022): the birth Mallows process is the unique regular Mallows process that is Markov; this does not settle its jumping process.

Posted attempt

A reader-written argument claims a complete proof for every n≥4n\geq 4, by comparing two histories reaching the same state and showing that their future-event probabilities differ. The argument has not been independently verified.

Current status (as of August 2026): The conjecture has a complete but unverified proof claim; no independently corroborated proof or counterexample is recorded, so the mathematical problem remains open.

Sources

Solutions 1

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Proof for every n≥4n\ge4. Write

[j]t=1+t+⋯+tj−1,Zn(t)=∏j=2n[j]t,N=(n2).[j]_t=1+t+\cdots+t^{j-1}, \qquad Z_n(t)=\prod_{j=2}^n[j]_t, \qquad N=\binom n2.

By the source's independent inversion-coordinate construction, the birth Mallows process corresponds bijectively to independent unit-birth processes Bj(t)B_j(t) with

Pr⁡(Bj(t)=r)=tr[j]t,0≤r<j.\Pr(B_j(t)=r)=\frac{t^r}{[j]_t}, \qquad 0\le r<j.

Let H23H_{23} be the history in which the first two global jumps occur in coordinates 2,32,3, and H32H_{32} the reverse history. Both have positive probability and end at the identical state

(B2,B3,B4,…,Bn)=(1,1,0,…,0).(B_2,B_3,B_4,\ldots,B_n)=(1,1,0,\ldots,0).

If TT denotes the second jump time, independence gives the unnormalized history-time densities

f23(t)=t[2]t[3]t′[3]t2∏j=4n1[j]t,f_{23}(t) = \frac{t}{[2]_t} \frac{[3]'_t}{[3]_t^2} \prod_{j=4}^n\frac1{[j]_t}, f32(t)=t[3]t1[2]t2∏j=4n1[j]t=t(1+t)Zn(t)=:w(t).f_{32}(t) = \frac{t}{[3]_t} \frac1{[2]_t^2} \prod_{j=4}^n\frac1{[j]_t} = \frac{t}{(1+t)Z_n(t)} =:w(t).

Their ratio is

R(t)=f23(t)f32(t)=(1+t)(1+2t)1+t+t2=2+ϕ(t),ϕ(t)=t−11+t+t2.R(t) = \frac{f_{23}(t)}{f_{32}(t)} = \frac{(1+t)(1+2t)}{1+t+t^2} = 2+\phi(t), \qquad \phi(t)=\frac{t-1}{1+t+t^2}.

Palindromicity of ZnZ_n gives

w(1/t)t2=tN−3w(t),ϕ(1/t)=−tϕ(t).\frac{w(1/t)}{t^2}=t^{N-3}w(t), \qquad \phi(1/t)=-t\phi(t).

Therefore

∫0∞w(t)(R(t)−2) dt=∫01w(t)ϕ(t)(1−tN−2) dt<0.\int_0^\infty w(t)(R(t)-2)\,dt = \int_0^1 w(t)\phi(t)(1-t^{N-2})\,dt <0.

Consequently the normalization ratio

cn=∫f23∫f32c_n=\frac{\int f_{23}}{\int f_{32}}

satisfies 1<cn<21<c_n<2. Moreover RR is strictly increasing on (0,1)(0,1), and R(t)≥2R(t)\ge2 for t≥1t\ge1. Hence R(t)−cnR(t)-c_n changes sign exactly once, from negative to positive. The two conditional time distributions therefore satisfy strict stochastic ordering:

T∣H23>stT∣H32.(1)T\mid H_{23}>_{\mathrm{st}}T\mid H_{32}. \tag{1}

Now consider the future embedded-chain event

E={the second jump in coordinate 3 precedes the first jump in coordinate 4}.E= \{ \text{the second jump in coordinate }3 \text{ precedes the first jump in coordinate }4 \}.

Jumps in all other coordinates can be ignored. The two competing birth rates are

a(t)=q3,1(t)=t+21+t+t2,b(t)=q4,0(t)=3t2+2t+1(1+t)(1+t2).a(t)=q_{3,1}(t)=\frac{t+2}{1+t+t^2}, \qquad b(t)=q_{4,0}(t) =\frac{3t^2+2t+1}{(1+t)(1+t^2)}.

A direct calculation yields

(a(t)b(t))′=−4t6+6t5+15t4+32t3+30t2+18t+3(t2+t+1)2(3t2+2t+1)2<0.\left(\frac{a(t)}{b(t)}\right)' = -\frac{ 4t^6+6t^5+15t^4+32t^3+30t^2+18t+3 }{ (t^2+t+1)^2(3t^2+2t+1)^2 } <0.

Thus h(t)=a(t)/(a(t)+b(t))h(t)=a(t)/(a(t)+b(t)) is strictly decreasing. If τt\tau_t is the first ring of these two clocks after time tt, then

Q(t):=Pr⁡(E∣T=t,B(T)=(1,1,0,…,0))=E[h(τt)].Q(t):=\Pr(E\mid T=t,B(T)=(1,1,0,\ldots,0)) =\mathbb E[h(\tau_t)].

For t<st<s, splitting at ss gives

Q(t)=∫tsh(u)(a(u)+b(u))e−∫tu(a+b) du+e−∫ts(a+b)Q(s).Q(t) = \int_t^s h(u)(a(u)+b(u)) e^{-\int_t^u(a+b)} \,du + e^{-\int_t^s(a+b)}Q(s).

Since h(u)>h(s)>Q(s)h(u)>h(s)>Q(s) for t<u<st<u<s, this identity implies Q(t)>Q(s)Q(t)>Q(s). Thus QQ is strictly decreasing.

Applying this to the strict stochastic ordering (1),

Pr⁡(E∣H23)<Pr⁡(E∣H32).\boxed{\displaystyle \Pr(E\mid H_{23}) < \Pr(E\mid H_{32}). }

The two histories reach the same state at the same jump index, yet yield different conditional probabilities for a future event determined entirely by the jumping chain. This contradicts the Markov property. Therefore the jumping process is not a Markov chain for every n≥4n\ge4.

Source: Benoît Corsini, Continuous-time Mallows processes, Conjecture 3, §4.2, https://arxiv.org/abs/2205.04967.